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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
c7cabf046a3443a84dda5d9798b1d9e671eb1936 | 879 | py | Python | pyEX/tests/test_account.py | briangu/pyEX | 2eacc322932f4b686817b3d162cb1e4f399fd696 | [
"Apache-2.0"
] | null | null | null | pyEX/tests/test_account.py | briangu/pyEX | 2eacc322932f4b686817b3d162cb1e4f399fd696 | [
"Apache-2.0"
] | null | null | null | pyEX/tests/test_account.py | briangu/pyEX | 2eacc322932f4b686817b3d162cb1e4f399fd696 | [
"Apache-2.0"
] | null | null | null | # *****************************************************************************
#
# Copyright (c) 2020, the pyEX authors.
#
# This file is part of the jupyterlab_templates library, distributed under the terms of
# the Apache License 2.0. The full license can be found in the LICENSE file.
#
# for Coverage
from mock import MagicMock, patch
| 25.852941 | 87 | 0.527873 | # *****************************************************************************
#
# Copyright (c) 2020, the pyEX authors.
#
# This file is part of the jupyterlab_templates library, distributed under the terms of
# the Apache License 2.0. The full license can be found in the LICENSE file.
#
# for Coverage
from mock import MagicMock, patch
class TestAccount:
def test_account(self):
from pyEX import Client
c = Client("sktest")
with patch("pyEX.account._getJson"):
c.account()
c.metadata()
def test_usage(self):
from pyEX import Client, PyEXception
c = Client("sktest")
with patch("pyEX.account._getJson"):
c.usage()
c.usage("messages")
try:
c.usage("test")
assert False
except PyEXception:
pass
| 463 | -3 | 76 |
7508b094c2efcaeaa3e918083c65f2196933bea6 | 865 | py | Python | grouper/fe/handlers/user_view.py | lfaraone/grouper | 7df5eda8003a0b4a9ba7f0dcb044ae1e4710b171 | [
"Apache-2.0"
] | null | null | null | grouper/fe/handlers/user_view.py | lfaraone/grouper | 7df5eda8003a0b4a9ba7f0dcb044ae1e4710b171 | [
"Apache-2.0"
] | 1 | 2016-02-18T18:55:29.000Z | 2016-02-18T18:55:29.000Z | grouper/fe/handlers/user_view.py | lfaraone/grouper | 7df5eda8003a0b4a9ba7f0dcb044ae1e4710b171 | [
"Apache-2.0"
] | null | null | null | from grouper.fe.handlers.template_variables import get_user_view_template_vars
from grouper.fe.util import GrouperHandler
from grouper.models.user import User
| 33.269231 | 100 | 0.63237 | from grouper.fe.handlers.template_variables import get_user_view_template_vars
from grouper.fe.util import GrouperHandler
from grouper.models.user import User
class UserView(GrouperHandler):
def get(self, user_id=None, name=None):
self.handle_refresh()
user = User.get(self.session, user_id, name)
if user_id is not None:
user = self.session.query(User).filter_by(id=user_id).scalar()
else:
user = self.session.query(User).filter_by(username=name).scalar()
if not user:
return self.notfound()
if user.role_user:
return self.redirect("/service/{}".format(user_id or name))
self.render("user.html",
user=user,
**get_user_view_template_vars(self.session, self.current_user, user, self.graph)
)
| 645 | 10 | 50 |
2d4248111d00e78de73707c1325a267a4ed83524 | 362 | py | Python | Lecture I/feynman.py | bmtgoncalves/TorinoCourse | 7c365dcd1211817a8b4d85e178dcb20a84d142d9 | [
"MIT"
] | 5 | 2017-05-03T14:33:27.000Z | 2020-05-26T20:43:26.000Z | Lecture I/feynman.py | bmtgoncalves/TorinoCourse | 7c365dcd1211817a8b4d85e178dcb20a84d142d9 | [
"MIT"
] | null | null | null | Lecture I/feynman.py | bmtgoncalves/TorinoCourse | 7c365dcd1211817a8b4d85e178dcb20a84d142d9 | [
"MIT"
] | 2 | 2019-03-21T03:41:20.000Z | 2019-11-17T07:58:51.000Z | import requests
from bs4 import BeautifulSoup
url = "http://scholar.google.com/citations?hl=en&user=B7vSqZsAAAAJ&view_op=list_works&pagesize=100"
request = requests.get(url)
soup = BeautifulSoup(request.text, 'lxml')
table = soup.find("table", attrs={"id" : "gsc_a_t"})
for paper in table.findAll("td", attrs={"class": "gsc_a_t"}):
print(paper.a.string)
| 27.846154 | 99 | 0.726519 | import requests
from bs4 import BeautifulSoup
url = "http://scholar.google.com/citations?hl=en&user=B7vSqZsAAAAJ&view_op=list_works&pagesize=100"
request = requests.get(url)
soup = BeautifulSoup(request.text, 'lxml')
table = soup.find("table", attrs={"id" : "gsc_a_t"})
for paper in table.findAll("td", attrs={"class": "gsc_a_t"}):
print(paper.a.string)
| 0 | 0 | 0 |
ba06f8cd508c1ded56a9c512cc12ae50881eb1a3 | 1,548 | py | Python | robot-server/robot_server/service/notifications/handle_subscriber.py | mrakitin/opentrons | d9c7ed23d13cdb62bd1bc397dc2871d4bd5b77e9 | [
"Apache-2.0"
] | null | null | null | robot-server/robot_server/service/notifications/handle_subscriber.py | mrakitin/opentrons | d9c7ed23d13cdb62bd1bc397dc2871d4bd5b77e9 | [
"Apache-2.0"
] | null | null | null | robot-server/robot_server/service/notifications/handle_subscriber.py | mrakitin/opentrons | d9c7ed23d13cdb62bd1bc397dc2871d4bd5b77e9 | [
"Apache-2.0"
] | null | null | null | """Websocket subscriber handler functions."""
import asyncio
import logging
from asyncio import CancelledError
from typing import List
from starlette.websockets import WebSocket, WebSocketDisconnect
from notify_server.clients.serdes import TopicEvent
from notify_server.clients.subscriber import Subscriber, create
from robot_server.settings import get_settings
log = logging.getLogger(__name__)
async def handle_socket(
websocket: WebSocket,
topics: List[str]) -> None:
"""Handle a websocket connection."""
subscriber = create(
get_settings().notification_server_subscriber_address,
topics
)
await asyncio.gather(
receive(websocket, subscriber),
route_events(websocket, subscriber)
)
async def receive(websocket: WebSocket, subscriber: Subscriber) -> None:
"""Read data from websocket. Will exit on websocket disconnect."""
try:
while True:
await websocket.receive_json()
except WebSocketDisconnect:
log.info("Websocket subscriber disconnected.")
subscriber.close()
async def send(websocket: WebSocket, entry: TopicEvent) -> None:
"""Send entry to web socket."""
await websocket.send_text(entry.json())
async def route_events(websocket: WebSocket, subscriber: Subscriber) -> None:
"""Route events from subscriber to websocket."""
try:
async for entry in subscriber:
await send(websocket, entry)
except CancelledError:
log.exception("Connection to notify-server closed.")
| 29.207547 | 77 | 0.713178 | """Websocket subscriber handler functions."""
import asyncio
import logging
from asyncio import CancelledError
from typing import List
from starlette.websockets import WebSocket, WebSocketDisconnect
from notify_server.clients.serdes import TopicEvent
from notify_server.clients.subscriber import Subscriber, create
from robot_server.settings import get_settings
log = logging.getLogger(__name__)
async def handle_socket(
websocket: WebSocket,
topics: List[str]) -> None:
"""Handle a websocket connection."""
subscriber = create(
get_settings().notification_server_subscriber_address,
topics
)
await asyncio.gather(
receive(websocket, subscriber),
route_events(websocket, subscriber)
)
async def receive(websocket: WebSocket, subscriber: Subscriber) -> None:
"""Read data from websocket. Will exit on websocket disconnect."""
try:
while True:
await websocket.receive_json()
except WebSocketDisconnect:
log.info("Websocket subscriber disconnected.")
subscriber.close()
async def send(websocket: WebSocket, entry: TopicEvent) -> None:
"""Send entry to web socket."""
await websocket.send_text(entry.json())
async def route_events(websocket: WebSocket, subscriber: Subscriber) -> None:
"""Route events from subscriber to websocket."""
try:
async for entry in subscriber:
await send(websocket, entry)
except CancelledError:
log.exception("Connection to notify-server closed.")
| 0 | 0 | 0 |
c21c7d29e3bcee06fbecc490ee797021609d0b25 | 897 | py | Python | naslib/defaults/additional_primitives.py | NUDTNASLab/NASLib | 451cdb4738a7c1501ac62f78727c6244039dc657 | [
"Apache-2.0"
] | 1 | 2022-03-28T09:35:33.000Z | 2022-03-28T09:35:33.000Z | naslib/defaults/additional_primitives.py | NUDTNASLab/NASLib | 451cdb4738a7c1501ac62f78727c6244039dc657 | [
"Apache-2.0"
] | null | null | null | naslib/defaults/additional_primitives.py | NUDTNASLab/NASLib | 451cdb4738a7c1501ac62f78727c6244039dc657 | [
"Apache-2.0"
] | null | null | null | import torch
from naslib.search_spaces.core.primitives import AbstractPrimitive, Identity
class DropPathWrapper(AbstractPrimitive):
"""
A wrapper for the drop path training regularization.
"""
| 28.03125 | 82 | 0.600892 | import torch
from naslib.search_spaces.core.primitives import AbstractPrimitive, Identity
class DropPathWrapper(AbstractPrimitive):
"""
A wrapper for the drop path training regularization.
"""
def __init__(self, op):
super().__init__(locals())
self.op = op
self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
def forward(self, x, edge_data):
x = self.op(x, edge_data)
if (
edge_data.drop_path_prob > 0.0
and not isinstance(self.op, Identity)
and self.training
):
keep_prob = 1.0 - edge_data.drop_path_prob
mask = torch.FloatTensor(x.size(0), 1, 1, 1).bernoulli_(keep_prob)
mask = mask.to(self.device)
x.div_(keep_prob)
x.mul_(mask)
return x
def get_embedded_ops(self):
return self.op
| 608 | 0 | 81 |
d7dfdd8f08a81fb05baa04d55f7322c18e491c5e | 76 | py | Python | testpkg/__init__.py | HurricanKai/PythonTest | d46c9367279c5e94d7d40e96db87d4016c5d4549 | [
"MIT"
] | null | null | null | testpkg/__init__.py | HurricanKai/PythonTest | d46c9367279c5e94d7d40e96db87d4016c5d4549 | [
"MIT"
] | null | null | null | testpkg/__init__.py | HurricanKai/PythonTest | d46c9367279c5e94d7d40e96db87d4016c5d4549 | [
"MIT"
] | null | null | null | from version import get_version
__version__ = get_version(pep440=False)
| 19 | 40 | 0.802632 | from version import get_version
__version__ = get_version(pep440=False)
| 0 | 0 | 0 |
6af5d94646c777d26329c38ee32a5379d1bf8b19 | 4,346 | py | Python | kubeluigi/__init__.py | optimizely/kubeluigi | a9a84bd8bb4531cb4ea138da28ce0be6bdceb324 | [
"Apache-2.0"
] | 3 | 2022-02-24T05:36:35.000Z | 2022-03-15T21:05:55.000Z | kubeluigi/__init__.py | optimizely/kubeluigi | a9a84bd8bb4531cb4ea138da28ce0be6bdceb324 | [
"Apache-2.0"
] | 3 | 2021-11-04T05:08:40.000Z | 2022-03-22T06:26:57.000Z | kubeluigi/__init__.py | optimizely/kubeluigi | a9a84bd8bb4531cb4ea138da28ce0be6bdceb324 | [
"Apache-2.0"
] | 1 | 2021-11-02T06:40:01.000Z | 2021-11-02T06:40:01.000Z | import logging
from typing import List
import yaml
from kubeluigi.k8s import (
clean_job_resources,
job_definition,
pod_spec_from_dict,
run_and_track_job,
kubernetes_client,
attach_volume_to_spec,
FailedJob,
)
from kubeluigi.volumes import AttachableVolume
from kubernetes.client import ApiClient
from kubernetes.client.models.v1_job import V1Job
from kubernetes.client.models.v1_pod_spec import V1PodSpec
logger = logging.getLogger(__name__)
| 29.972414 | 121 | 0.613438 | import logging
from typing import List
import yaml
from kubeluigi.k8s import (
clean_job_resources,
job_definition,
pod_spec_from_dict,
run_and_track_job,
kubernetes_client,
attach_volume_to_spec,
FailedJob,
)
from kubeluigi.volumes import AttachableVolume
from kubernetes.client import ApiClient
from kubernetes.client.models.v1_job import V1Job
from kubernetes.client.models.v1_pod_spec import V1PodSpec
logger = logging.getLogger(__name__)
class KubernetesJobTask:
volumes: List[AttachableVolume] = []
def _init_task_metadata(self):
self.uu_name = self.name
def _init_kubernetes(self):
self.kubernetes_client = kubernetes_client()
@property
def restart_policy(self):
return "Never"
@property
def backoff_limit(self):
"""
Maximum number of retries before considering the job as failed.
See: https://kubernetes.io/docs/concepts/workloads/controllers/jobs-run-to-completion/#pod-backoff-failure-policy
"""
return 6
@property
def name(self):
"""
A name for this job. This needs to be unique otherwise it will fail if another job
with the same name is running.
"""
raise NotImplementedError("subclass must define name")
@property
def labels(self):
"""
Return custom labels for kubernetes job.
example::
``{"run_dt": datetime.date.today().strftime('%F')}``
"""
return {}
def spec_schema(self):
"""
Kubernetes Job spec schema in JSON format, an example follows.
.. code-block:: javascript
{
"containers": [{
"name": "pi",
"image": "perl",
"command": ["perl", "-Mbignum=bpi", "-wle", "print bpi(2000)"]
}]
}
"""
raise NotImplementedError("subclass must define spec_schema")
def build_job_definition(self) -> V1Job:
self._init_task_metadata()
schema = self.spec_schema()
schema_with_volumes = self._attach_volumes_to_spec(schema)
pod_template_spec = pod_spec_from_dict(
self.uu_name, schema_with_volumes, self.labels, self.restart_policy
)
job = job_definition(
job_name=self.uu_name,
backoff_limit=self.backoff_limit,
pod_template_spec=pod_template_spec,
labels=self.labels,
namespace=self.namespace,
)
return job
def onpodstarted(self, pod):
logger.info(
f"Tail the Pod logs using: kubectl logs -f -n {pod.namespace} {pod.name}"
)
def as_yaml(self):
job = self.build_job_definition()
job_dict = ApiClient().sanitize_for_serialization(job)
str_yaml = yaml.safe_dump(job_dict, default_flow_style=False, sort_keys=False)
return str_yaml
def run(self):
self._init_kubernetes()
job = self.build_job_definition()
logger.debug("Submitting Kubernetes Job: " + self.uu_name)
try:
run_and_track_job(self.kubernetes_client, job, self.onpodstarted)
except FailedJob as e:
logger.exception(
f"Luigi's job has failed running: {e.job.metadata.name}, {e.pod.status.message}"
)
raise
except Exception:
logger.exception(f"Luigi has failed to run: {job}, starting cleaning")
raise
finally:
clean_job_resources(self.kubernetes_client, job)
def output(self):
"""
An output target is necessary for checking job completion unless
an alternative complete method is defined.
Example::
return luigi.LocalTarget(os.path.join('/tmp', 'example'))
"""
pass
def _attach_volumes_to_spec(self, spec_schema):
"""
overrides the spec_schema of a task to attach a volume
"""
if "volumes" not in spec_schema and hasattr(self, "volumes"):
for volume in self.volumes:
spec_schema = attach_volume_to_spec(spec_schema, volume)
return spec_schema
def add_volume(self, volume):
"""
adds a volume to the task
"""
return self.volumes.append(volume)
| 1,640 | 2,207 | 23 |
7f001c619b2baa82a9faffcc2a4a2132735d5cae | 2,900 | py | Python | raiden/tests/unit/test_cli.py | anmolshl/raiden | f1cecb68cb43a2c00b2f719eadbe83137611a92a | [
"MIT"
] | null | null | null | raiden/tests/unit/test_cli.py | anmolshl/raiden | f1cecb68cb43a2c00b2f719eadbe83137611a92a | [
"MIT"
] | null | null | null | raiden/tests/unit/test_cli.py | anmolshl/raiden | f1cecb68cb43a2c00b2f719eadbe83137611a92a | [
"MIT"
] | null | null | null | from raiden.utils import (
is_minified_address,
is_supported_client,
)
| 36.25 | 89 | 0.713448 | from raiden.utils import (
is_minified_address,
is_supported_client,
)
class MockVersion:
def __init__(self, node):
self.node = node
class MockWeb3:
def __init__(self, version):
self.version = version
class MockClient:
def __init__(self, version):
version = MockVersion(version)
self.web3 = MockWeb3(version)
def test_check_json_rpc_geth():
assert is_supported_client('Geth/v1.7.3-unstable-e9295163/linux-amd64/go1.9.1')
assert is_supported_client('Geth/v1.7.2-unstable-e9295163/linux-amd64/go1.9.1')
assert is_supported_client('Geth/v1.8.2-unstable-e9295163/linux-amd64/go1.9.1')
assert is_supported_client('Geth/v2.0.3-unstable-e9295163/linux-amd64/go1.9.1')
assert is_supported_client('Geth/v11.55.86-unstable-e9295163/linux-amd64/go1.9.1')
assert is_supported_client('Geth/v999.999.999-unstable-e9295163/linux-amd64/go1.9.1')
assert not is_supported_client('Geth/v1.7.1-unstable-e9295163/linux-amd64/go1.9.1')
assert not is_supported_client('Geth/v0.7.1-unstable-e9295163/linux-amd64/go1.9.1')
assert not is_supported_client('Geth/v0.0.0-unstable-e9295163/linux-amd64/go1.9.1')
assert not is_supported_client('Geth/v0.0.0-unstable-e9295163/linux-amd64/go1.9.1')
def test_check_json_rpc_parity():
assert is_supported_client(
'Parity//v1.7.6-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert is_supported_client(
'Parity//v1.7.7-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert is_supported_client(
'Parity//v1.8.7-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert is_supported_client(
'Parity//v2.9.7-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert is_supported_client(
'Parity//v23.94.75-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert is_supported_client(
'Parity//v99.994.975-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert not is_supported_client(
'Parity//v1.7.5-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert not is_supported_client(
'Parity//v1.5.1-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert not is_supported_client(
'Parity//v0.7.1-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert not is_supported_client(
'Parity//v0.8.7-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
assert not is_supported_client(
'Parity//v0.0.0-stable-19535333c-20171013/x86_64-linux-gnu/rustc1.20.0',
)
def test_minified_address_checker():
assert is_minified_address('9bed7fd1')
assert is_minified_address('8c1d1f23')
assert not is_minified_address('xxxxxx')
assert not is_minified_address('123zzz')
assert not is_minified_address('$@$^$')
| 2,612 | -13 | 216 |
5b6af1964b0e257850fda734c7fce277fcb3017a | 459 | py | Python | sess_3.py | sarb9/maktabkhooneh | 6fcc63eb84899439de4dbaebd8d380d1570542c9 | [
"MIT"
] | 2 | 2021-03-08T14:12:04.000Z | 2021-05-16T07:17:46.000Z | sess_3.py | sarb9/maktabkhooneh | 6fcc63eb84899439de4dbaebd8d380d1570542c9 | [
"MIT"
] | null | null | null | sess_3.py | sarb9/maktabkhooneh | 6fcc63eb84899439de4dbaebd8d380d1570542c9 | [
"MIT"
] | null | null | null | from numpy import number
from settings import NORMALIZATION_NUMBER_OF_BUCKETS
from dataset.raw_dataset import RawDataset
from normalization.price_normalizer import PriceNormalizer
if __name__ == "__main__":
raw_dataset = RawDataset()
size = raw_dataset.load()
number_of_buckets = NORMALIZATION_NUMBER_OF_BUCKETS
normalizer = PriceNormalizer(raw_dataset.books, number_of_buckets)
normalizer.plot_buckets()
normalizer.sample_plot()
| 27 | 70 | 0.803922 | from numpy import number
from settings import NORMALIZATION_NUMBER_OF_BUCKETS
from dataset.raw_dataset import RawDataset
from normalization.price_normalizer import PriceNormalizer
if __name__ == "__main__":
raw_dataset = RawDataset()
size = raw_dataset.load()
number_of_buckets = NORMALIZATION_NUMBER_OF_BUCKETS
normalizer = PriceNormalizer(raw_dataset.books, number_of_buckets)
normalizer.plot_buckets()
normalizer.sample_plot()
| 0 | 0 | 0 |
a5a508f70828eb8773f459320e0ef7d830e95709 | 2,114 | py | Python | user.py | LucaPetrucci/test_image | bb21d4714ee6c2a7e866ae2baf6e041e8a0d761c | [
"BSD-4-Clause"
] | null | null | null | user.py | LucaPetrucci/test_image | bb21d4714ee6c2a7e866ae2baf6e041e8a0d761c | [
"BSD-4-Clause"
] | 1 | 2021-06-02T01:28:41.000Z | 2021-06-02T01:28:41.000Z | user.py | LucaPetrucci/test_image | bb21d4714ee6c2a7e866ae2baf6e041e8a0d761c | [
"BSD-4-Clause"
] | null | null | null | import datetime
from bson.json_util import dumps
| 44.041667 | 120 | 0.634816 | import datetime
from bson.json_util import dumps
class User:
def __init__(self, username, password=None, role="user"):
self.username = username
self.password = password
self.role = role
def save_to_db(self, mongo_connection, user_collection):
return mongo_connection[user_collection].insert_one({"userID": self.username, "password": self.password,
"role": self.role, "last_login": "never",
"creationTime": datetime.datetime.now().isoformat()})
def remove_from_db(self, mongo_connection, user_collection):
token_to_remove = dict(mongo_connection[user_collection].find_one({"userID": self.username})).get('token', None)
mongo_connection[user_collection].delete_one({"userID": self.username})
return token_to_remove
def get_role(self, mongo_connection, user_collection):
user = mongo_connection[user_collection].find_one({"userID": self.username}, {'id': 0})
return user['role']
# thi function checks if the current user are allowed to perform the requested operation.
# return true if the user has sufficient permission
def check_user_permission(self, mongo_connection, user_collection, user_id):
user = mongo_connection[user_collection].find_one({"userID": self.username}, {'id': 0})
if user['role'] != 'admin':
if user['userID'] != user_id:
return False
else:
return True
else:
return True
def check_admin_permission(self, mongo_connection, user_collection):
user = mongo_connection[user_collection].find_one({"userID": self.username}, {'id': 0})
return user['role'] == 'admin'
@classmethod
def find_by_username(cls, mongo_connection, user_collection, tenant_id):
user = mongo_connection[user_collection].find_one({"userID": tenant_id}, {'id': 0})
if user is not None:
return user['userID'], user['password']
return None, None
| 1,695 | 346 | 23 |
02bbe0af3ace93bd713baa73aa346200670cf9ff | 476 | py | Python | oct/cli/tests/test_version.py | staebler/origin-ci-tool | 2cb86c3cad7a37450e711571ac75997118c899e5 | [
"Apache-2.0"
] | 23 | 2017-01-06T21:32:09.000Z | 2022-03-14T17:14:49.000Z | oct/cli/tests/test_version.py | staebler/origin-ci-tool | 2cb86c3cad7a37450e711571ac75997118c899e5 | [
"Apache-2.0"
] | 129 | 2017-01-06T18:29:51.000Z | 2022-01-27T17:37:21.000Z | oct/cli/tests/test_version.py | staebler/origin-ci-tool | 2cb86c3cad7a37450e711571ac75997118c899e5 | [
"Apache-2.0"
] | 52 | 2017-01-06T16:03:49.000Z | 2022-01-24T18:58:58.000Z | # coding=utf-8
from __future__ import absolute_import, division, print_function
from oct.cli.version import VERSION
from oct.tests.unit.playbook_runner_test_case import PlaybookRunnerTestCase, TestCaseParameters, show_stack_trace
if not show_stack_trace:
__unittest = True
| 28 | 113 | 0.754202 | # coding=utf-8
from __future__ import absolute_import, division, print_function
from oct.cli.version import VERSION
from oct.tests.unit.playbook_runner_test_case import PlaybookRunnerTestCase, TestCaseParameters, show_stack_trace
if not show_stack_trace:
__unittest = True
class VersionTestCase(PlaybookRunnerTestCase):
def test_version(self):
self.run_test(TestCaseParameters(
args=['version'],
expected_output=VERSION,
))
| 122 | 25 | 49 |
fa07c813d7442bdd20056463ab719e52d2c3fcfb | 6,872 | py | Python | tttchess.py | kq18G8/mcmk | 07a263298f14798cd4410dcb273448fefaa93d6f | [
"MIT"
] | null | null | null | tttchess.py | kq18G8/mcmk | 07a263298f14798cd4410dcb273448fefaa93d6f | [
"MIT"
] | null | null | null | tttchess.py | kq18G8/mcmk | 07a263298f14798cd4410dcb273448fefaa93d6f | [
"MIT"
] | 2 | 2018-06-14T11:36:13.000Z | 2019-09-09T02:16:04.000Z | import numpy as np
import cv2
import random
face_cascade = cv2.CascadeClassifier('D:\python36\Lib\site-packages\cv2\data\haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('D:\python36\Lib\site-packages\cv2\data\haarcascade_eye.xml')
#先检测人脸，存到face.jpg中
cap=cv2.VideoCapture(0)
while(True):
ret,frame = cap.read()
img = frame
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
cv2.imshow('roi_color',roi_color)
cv2.imwrite('face.jpg',roi_color)
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('img',img)
# 按s键保存退出
if cv2.waitKey(1000)&0xFF==ord('s'):
break
cv2.destroyAllWindows()
#下棋程序开始
ret,frame = cap.read()
L=len(frame)
W=len(frame[0])
print(L,W)
SIZE=100
X0=int(W/2-1.5*SIZE)
Y0=int(L/2-1.5*SIZE)
R=int(SIZE/2)
chessboard=[[0,0,0],[0,0,0],[0,0,0]]
print(chessboard)
playsteps=0
#顺序查找空格版本
#随机数AI版本
#j堵活二版
# 创建图像与窗口并将窗口与回调函数绑定
cv2.namedWindow('frame')
cv2.setMouseCallback('frame',mouse_dclick)
while(True):
ret,frame = cap.read()
#画棋盘和棋子
for i in range(3):
for j in range(3):
cv2.rectangle(frame,(i*SIZE+X0,j*SIZE+Y0),(i*SIZE+SIZE+X0,j*SIZE+SIZE+Y0),(255,128,255),2)
if chessboard[i][j]==1:
cv2.circle(frame,(i*SIZE+X0+R,j*SIZE+Y0+R),R,(255,0,0),-1)
mychess1(frame,(i*SIZE+X0+R,j*SIZE+Y0+R),R)
elif chessboard[i][j]==2:
cv2.circle(frame,(i*SIZE+X0+R,j*SIZE+Y0+R),R,(255,0,0),3)
mychess2(frame,(i*SIZE+X0+R,j*SIZE+Y0+R),R)
cv2.imshow('frame',frame)
#判断输赢，检查每行
winner=0
for i in range(3):
counter1=0
counter2=0
for j in range(3):
if chessboard[i][j]==1:
counter1+=1
elif chessboard[i][j]==2:
counter2+=1
if counter1==3:
winner=1
break
elif counter2==3:
winner=2
break
if winner !=0:
print("winner=",winner)
break
# 判断输赢，坚持每列
for j in range(3):
counter1=0
counter2=0
for i in range(3):
if chessboard[i][j]==1:
counter1+=1
elif chessboard[i][j]==2:
counter2+=1
if counter1==3:
winner=1
break
elif counter2==3:
winner=2
break
if winner !=0:
print("winner=",winner)
break
# 判断输赢，检查对角线。
counter1=0
counter2=0
for j in range(3):
if chessboard[j][j]==1:
counter1+=1
elif chessboard[j][j]==2:
counter2+=1
if counter1==3:
winner=1
elif counter2==3:
winner=2
if winner !=0:
print("winner=",winner)
break
# 判断输赢，检查对角线。
counter1=0
counter2=0
for j in range(3):
if chessboard[j][2-j]==1:
counter1+=1
elif chessboard[j][2-j]==2:
counter2+=1
if counter1==3:
winner=1
elif counter2==3:
winner=2
if winner !=0:
print("winner=",winner)
break
if cv2.waitKey(1000)&0xFF==ord('q'):
break
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame,'Winnner '+str(winner),(160,70), font, 2,(255,255,255),4)
cv2.imshow("frame",frame)
cv2.waitKey(5000)
cap.release()
cv2.destroyAllWindows()
| 26.430769 | 115 | 0.493161 | import numpy as np
import cv2
import random
face_cascade = cv2.CascadeClassifier('D:\python36\Lib\site-packages\cv2\data\haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('D:\python36\Lib\site-packages\cv2\data\haarcascade_eye.xml')
#先检测人脸，存到face.jpg中
cap=cv2.VideoCapture(0)
while(True):
ret,frame = cap.read()
img = frame
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
for (x,y,w,h) in faces:
img = cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
roi_gray = gray[y:y+h, x:x+w]
roi_color = img[y:y+h, x:x+w]
cv2.imshow('roi_color',roi_color)
cv2.imwrite('face.jpg',roi_color)
eyes = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('img',img)
# 按s键保存退出
if cv2.waitKey(1000)&0xFF==ord('s'):
break
cv2.destroyAllWindows()
#下棋程序开始
ret,frame = cap.read()
L=len(frame)
W=len(frame[0])
print(L,W)
SIZE=100
X0=int(W/2-1.5*SIZE)
Y0=int(L/2-1.5*SIZE)
R=int(SIZE/2)
chessboard=[[0,0,0],[0,0,0],[0,0,0]]
print(chessboard)
playsteps=0
#顺序查找空格版本
def AIplayer2():
for i in range(3):
for j in range(3):
if chessboard[i][j]==0:
chessboard[i][j]=2
return
#随机数AI版本
def AIplayerR2():
i=0
j=0
trycounter=0
while(chessboard[i][j]!=0):
i=int(random.uniform(0,3))
j=int(random.uniform(0,3))
trycounter+=1
if(trycounter>=20):
break
print("AIR2 play",i,j)
if chessboard[i][j]==0:
chessboard[i][j]=2
return
#随机试20次没有碰到空的，则启用顺序
AIplayer2()
#j堵活二版
def AIplayerA2():
#找竖的2，堵之
for i in range(3):
counter1=0
for j in range(3):
if chessboard[i][j]==1:
counter1+=1
if counter1==2:
for j in range(3):
if chessboard[i][j]==0:
chessboard[i][j]=2
return
#找横的2，堵之
for j in range(3):
counter1=0
for i in range(3):
if chessboard[i][j]==1:
counter1+=1
if counter1==2:
for j in range(3):
if chessboard[i][j]==0:
chessboard[i][j]=2
return
#找主对角线的2，堵之
counter1=0
for i in range(3):
if chessboard[i][i]==1:
counter1+=1
if counter1==2:
for i in range(3):
if chessboard[i][i]==0:
chessboard[i][i]=2
return
#找副主对角线的2，堵之
counter1=0
for i in range(3):
if chessboard[i][2-i]==1:
counter1+=1
if counter1==2:
for i in range(3):
if chessboard[i][2-i]==0:
chessboard[i][2-i]=2
return
#纵横及对角线均没有成2的，则随机下
AIplayerR2()
def mouse_dclick(event,x,y,flags,param):
global playsteps
if event == cv2.EVENT_LBUTTONDBLCLK:
if x>X0 and y>Y0 and x<(X0+SIZE*3) and y<(Y0+SIZE*3):
i=int((x-X0)/SIZE)
j=int((y-Y0)/SIZE)
if chessboard[i][j]==0:
player=playsteps%2+1
print("mc",player)
chessboard[i][j]=player
playsteps+=1
if player==1:
player=playsteps%2+1
print("mc",player)
AIplayerA2()
playsteps+=1
# 创建图像与窗口并将窗口与回调函数绑定
cv2.namedWindow('frame')
cv2.setMouseCallback('frame',mouse_dclick)
def mychess1(frame,xy,R):
# cv2.circle(frame,xy,R,(255,0,0),-1)
img=cv2.imread("face.jpg")
x0=xy[1]-R
y0=xy[0]-R
frame[x0:x0+SIZE,y0:y0+SIZE]= cv2.resize(img[0:200,0:200],(SIZE,SIZE),interpolation=cv2.INTER_CUBIC)
def mychess2(frame,xy,R):
img=cv2.imread("123.jpg")
x0=xy[1]-R
y0=xy[0]-R
frame[x0:x0+SIZE,y0:y0+SIZE]= cv2.resize(img[0:400,0:600],(SIZE,SIZE),interpolation=cv2.INTER_CUBIC)
while(True):
ret,frame = cap.read()
#画棋盘和棋子
for i in range(3):
for j in range(3):
cv2.rectangle(frame,(i*SIZE+X0,j*SIZE+Y0),(i*SIZE+SIZE+X0,j*SIZE+SIZE+Y0),(255,128,255),2)
if chessboard[i][j]==1:
cv2.circle(frame,(i*SIZE+X0+R,j*SIZE+Y0+R),R,(255,0,0),-1)
mychess1(frame,(i*SIZE+X0+R,j*SIZE+Y0+R),R)
elif chessboard[i][j]==2:
cv2.circle(frame,(i*SIZE+X0+R,j*SIZE+Y0+R),R,(255,0,0),3)
mychess2(frame,(i*SIZE+X0+R,j*SIZE+Y0+R),R)
cv2.imshow('frame',frame)
#判断输赢，检查每行
winner=0
for i in range(3):
counter1=0
counter2=0
for j in range(3):
if chessboard[i][j]==1:
counter1+=1
elif chessboard[i][j]==2:
counter2+=1
if counter1==3:
winner=1
break
elif counter2==3:
winner=2
break
if winner !=0:
print("winner=",winner)
break
# 判断输赢，坚持每列
for j in range(3):
counter1=0
counter2=0
for i in range(3):
if chessboard[i][j]==1:
counter1+=1
elif chessboard[i][j]==2:
counter2+=1
if counter1==3:
winner=1
break
elif counter2==3:
winner=2
break
if winner !=0:
print("winner=",winner)
break
# 判断输赢，检查对角线。
counter1=0
counter2=0
for j in range(3):
if chessboard[j][j]==1:
counter1+=1
elif chessboard[j][j]==2:
counter2+=1
if counter1==3:
winner=1
elif counter2==3:
winner=2
if winner !=0:
print("winner=",winner)
break
# 判断输赢，检查对角线。
counter1=0
counter2=0
for j in range(3):
if chessboard[j][2-j]==1:
counter1+=1
elif chessboard[j][2-j]==2:
counter2+=1
if counter1==3:
winner=1
elif counter2==3:
winner=2
if winner !=0:
print("winner=",winner)
break
if cv2.waitKey(1000)&0xFF==ord('q'):
break
font=cv2.FONT_HERSHEY_SIMPLEX
cv2.putText(frame,'Winnner '+str(winner),(160,70), font, 2,(255,255,255),4)
cv2.imshow("frame",frame)
cv2.waitKey(5000)
cap.release()
cv2.destroyAllWindows()
| 2,831 | 0 | 164 |
e01efa9954f87b0a8fa55e637e946548460fe4f2 | 48,285 | py | Python | bddtests/steps/bootstrap_util.py | liuhuanyuxfq/fabric | 21ce6b23cf9129b98a1c22a3128d30b762f96c81 | [
"Apache-2.0"
] | 2 | 2017-07-11T15:42:03.000Z | 2020-02-27T12:37:48.000Z | bddtests/steps/bootstrap_util.py | liuhuanyuxfq/fabric | 21ce6b23cf9129b98a1c22a3128d30b762f96c81 | [
"Apache-2.0"
] | null | null | null | bddtests/steps/bootstrap_util.py | liuhuanyuxfq/fabric | 21ce6b23cf9129b98a1c22a3128d30b762f96c81 | [
"Apache-2.0"
] | null | null | null | # Copyright IBM Corp. 2016 All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import time
import sys
import hashlib
if sys.version_info < (3, 6):
import sha3
from OpenSSL import crypto
from OpenSSL import rand
import ecdsa
from collections import namedtuple
from itertools import groupby
from enum import Enum
from google.protobuf import timestamp_pb2
from common import common_pb2 as common_dot_common_pb2
from common import configtx_pb2 as common_dot_configtx_pb2
from common import configuration_pb2 as common_dot_configuration_pb2
from common import policies_pb2 as common_dot_policies_pb2
from common import msp_principal_pb2
from msp import mspconfig_pb2
from peer import configuration_pb2 as peer_dot_configuration_pb2
from orderer import configuration_pb2 as orderer_dot_configuration_pb2
import orderer_util
from contexthelper import ContextHelper
import os
import re
import shutil
import compose
# Type to represent tuple of user, nodeName, ogranization
NodeAdminTuple = namedtuple("NodeAdminTuple", ['user', 'nodeName', 'organization'])
ApplicationGroup = "Application"
OrdererGroup = "Orderer"
MSPKey = "MSP"
toValue = lambda message: message.SerializeToString()
def computeCryptoHash(data):
' This will currently return 128 hex characters'
# s = hashlib.sha3_256()
s = hashlib.sha256()
# s = hashlib.shake_256()
#return s.digest(64)
s.update(data)
return s.digest()
def createCertRequest(pkey, digest="sha256", **name):
"""
Create a certificate request.
Arguments: pkey - The key to associate with the request
digest - Digestion method to use for signing, default is sha256
**name - The name of the subject of the request, possible
arguments are:
C - Country name
ST - State or province name
L - Locality name
O - Organization name
OU - Organizational unit name
CN - Common name
emailAddress - E-mail address
Returns: The certificate request in an X509Req object
"""
req = crypto.X509Req()
subj = req.get_subject()
for key, value in name.items():
setattr(subj, key, value)
req.set_pubkey(pkey)
req.sign(pkey, digest)
return req
def createCertificate(req, issuerCertKey, serial, validityPeriod, digest="sha256", isCA=False):
"""
Generate a certificate given a certificate request.
Arguments: req - Certificate request to use
issuerCert - The certificate of the issuer
issuerKey - The private key of the issuer
serial - Serial number for the certificate
notBefore - Timestamp (relative to now) when the certificate
starts being valid
notAfter - Timestamp (relative to now) when the certificate
stops being valid
digest - Digest method to use for signing, default is sha256
Returns: The signed certificate in an X509 object
"""
issuerCert, issuerKey = issuerCertKey
notBefore, notAfter = validityPeriod
cert = crypto.X509()
cert.set_version(3)
cert.set_serial_number(serial)
cert.gmtime_adj_notBefore(notBefore)
cert.gmtime_adj_notAfter(notAfter)
cert.set_issuer(issuerCert.get_subject())
cert.set_subject(req.get_subject())
cert.set_pubkey(req.get_pubkey())
if isCA:
cert.add_extensions([crypto.X509Extension("basicConstraints", True,
"CA:TRUE, pathlen:0"),
crypto.X509Extension("subjectKeyIdentifier", False, "hash",
subject=cert)])
#TODO: This only is appropriate for root self signed!!!!
cert.add_extensions([crypto.X509Extension("authorityKeyIdentifier", False, "keyid:always", issuer=cert)])
else:
cert.add_extensions([crypto.X509Extension("basicConstraints", True,
"CA:FALSE"),
crypto.X509Extension("subjectKeyIdentifier", False, "hash",
subject=cert)])
cert.add_extensions([crypto.X509Extension("authorityKeyIdentifier", False, "keyid:always", issuer=issuerCert)])
cert.sign(issuerKey, digest)
return cert
# SUBJECT_DEFAULT = {countryName : "US", stateOrProvinceName : "NC", localityName : "RTP", organizationName : "IBM", organizationalUnitName : "Blockchain"}
def addOrdererBootstrapAdminOrgReferences(context, policyName, orgNames):
'Adds a key/value pair of policyName/[orgName,...]'
directory = getDirectory(context)
ordererBootstrapAdmin = directory.getUser(userName="ordererBootstrapAdmin", shouldCreate=False)
if not 'OrgReferences' in ordererBootstrapAdmin.tags:
ordererBootstrapAdmin.tags['OrgReferences'] = {}
policyNameToOrgNamesDict = ordererBootstrapAdmin.tags['OrgReferences']
assert not policyName in policyNameToOrgNamesDict, "PolicyName '{0}' already registered with ordererBootstrapAdmin".format(
policyName)
policyNameToOrgNamesDict[policyName] = orgNames
return policyNameToOrgNamesDict
def createConfigUpdateTxEnvelope(chainId, configUpdateEnvelope):
'The Join channel flow'
bootstrapHelper = BootstrapHelper(chainId=chainId)
payloadChainHeader = bootstrapHelper.makeChainHeader(
type=common_dot_common_pb2.HeaderType.Value("CONFIG_UPDATE"))
# Now the SignatureHeader
serializedCreatorCertChain = None
nonce = None
payloadSignatureHeader = common_dot_common_pb2.SignatureHeader(
creator=serializedCreatorCertChain,
nonce=bootstrapHelper.getNonce(),
)
payloadHeader = common_dot_common_pb2.Header(
channel_header=payloadChainHeader,
signature_header=payloadSignatureHeader,
)
payload = common_dot_common_pb2.Payload(header=payloadHeader, data=configUpdateEnvelope.SerializeToString())
envelope = common_dot_common_pb2.Envelope(payload=payload.SerializeToString(), signature=None)
return envelope
def createGenesisBlock(context, chainId, consensusType, signedConfigItems=[]):
'Generates the genesis block for starting the oderers and for use in the chain config transaction by peers'
# assert not "bootstrapGenesisBlock" in context,"Genesis block already created:\n{0}".format(context.bootstrapGenesisBlock)
directory = getDirectory(context)
assert len(directory.ordererAdminTuples) > 0, "No orderer admin tuples defined!!!"
channelConfig = createChannelConfigGroup()
for configGroup in signedConfigItems:
mergeConfigGroups(channelConfig, configGroup)
# (fileName, fileExist) = ContextHelper.GetHelper(context=context).getTmpPathForName(name="t",extension="protobuf")
# with open(fileName, 'w') as f:
# f.write(channelConfig.SerializeToString())
config = common_dot_configtx_pb2.Config(
header=common_dot_common_pb2.ChannelHeader(channel_id=chainId,
type=common_dot_common_pb2.HeaderType.Value("CONFIG")),
channel=channelConfig)
configEnvelope = common_dot_configtx_pb2.ConfigEnvelope(config=config)
envelope = createConfigTxEnvelope(chainId=chainId, config_envelope=configEnvelope)
blockData = common_dot_common_pb2.BlockData(data=[envelope.SerializeToString()])
# Spoke with kostas, for orderer in general
signaturesMetadata = ""
lastConfigurationBlockMetadata = common_dot_common_pb2.Metadata(
value=common_dot_common_pb2.LastConfig(index=0).SerializeToString()).SerializeToString()
ordererConfigMetadata = ""
transactionFilterMetadata = ""
bootstrapHelper = BootstrapHelper(chainId="NOT_USED")
block = common_dot_common_pb2.Block(
header=common_dot_common_pb2.BlockHeader(
number=0,
previous_hash=None,
data_hash=bootstrapHelper.computeBlockDataHash(blockData),
),
data=blockData,
metadata=common_dot_common_pb2.BlockMetadata(
metadata=[signaturesMetadata, lastConfigurationBlockMetadata, transactionFilterMetadata,
ordererConfigMetadata]),
)
# Add this back once crypto certs are required
for nodeAdminTuple in directory.ordererAdminTuples:
userCert = directory.ordererAdminTuples[nodeAdminTuple]
certAsPEM = crypto.dump_certificate(crypto.FILETYPE_PEM, userCert)
# print("UserCert for orderer genesis:\n{0}\n".format(certAsPEM))
# print("")
return (block, envelope)
class PathType(Enum):
'Denotes whether Path relative to Local filesystem or Containers volume reference.'
Local = 1
Container = 2
class OrdererGensisBlockCompositionCallback(compose.CompositionCallback, CallbackHelper):
'Responsible for setting the GensisBlock for the Orderer nodes upon composition'
def decomposing(self, composition, context):
'Will remove the orderer volume path folder for the context'
shutil.rmtree(self.getVolumePath(composition))
class PeerCompositionCallback(compose.CompositionCallback):
'Responsible for setting up Peer nodes upon composition'
def composing(self, composition, context):
'Will copy local MSP info over at this point for each peer node'
directory = getDirectory(context)
for peerService in self.getPeerList(composition):
localMspConfigPath = self.getLocalMspConfigPath(composition, peerService)
self._createLocalMspConfigDirs(localMspConfigPath)
# Loop through directory and place Peer Organization Certs into cacerts folder
for peerOrg in [org for orgName, org in directory.organizations.items() if Network.Peer in org.networks]:
with open("{0}/cacerts/{1}.pem".format(localMspConfigPath, peerOrg.name), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, peerOrg.getSelfSignedCert()))
# Loop through directory and place Peer Organization Certs into admincerts folder
# TODO: revisit this, ASO recommended for now
for peerOrg in [org for orgName, org in directory.organizations.items() if Network.Peer in org.networks]:
with open("{0}/admincerts/{1}.pem".format(localMspConfigPath, peerOrg.name), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, peerOrg.getSelfSignedCert()))
# Find the peer signer Tuple for this peer and add to signcerts folder
for pnt, cert in [(peerNodeTuple, cert) for peerNodeTuple, cert in directory.ordererAdminTuples.items() if
peerService in peerNodeTuple.user and "signer" in peerNodeTuple.user.lower()]:
# Put the PEM file in the signcerts folder
with open("{0}/signcerts/{1}.pem".format(localMspConfigPath, pnt.user), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, cert))
# Put the associated private key into the keystore folder
user = directory.getUser(pnt.user, shouldCreate=False)
with open("{0}/keystore/{1}.pem".format(localMspConfigPath, pnt.user), "w") as f:
f.write(user.ecdsaSigningKey.to_pem())
# f.write(crypto.dump_privatekey(crypto.FILETYPE_PEM, user.pKey))
def decomposing(self, composition, context):
'Will remove the orderer volume path folder for the context'
shutil.rmtree(self.getVolumePath(composition))
def createChainCreatorsPolicy(context, chainCreatePolicyName, chaindId, orgNames):
'Creates the chain Creator Policy with name'
directory = getDirectory(context)
bootstrapHelper = BootstrapHelper(chainId=chaindId)
# This represents the domain of organization which can create channels for the orderer
# First create org MSPPrincicpal
# Collect the orgs from the table
mspPrincipalList = []
for org in [directory.getOrganization(orgName) for orgName in orgNames]:
mspPrincipalList.append(msp_principal_pb2.MSPPrincipal(
PrincipalClassification=msp_principal_pb2.MSPPrincipal.Classification.Value("ByIdentity"),
Principal=crypto.dump_certificate(crypto.FILETYPE_ASN1, org.getSelfSignedCert())))
policy = common_dot_policies_pb2.Policy(
type=common_dot_policies_pb2.Policy.PolicyType.Value("SIGNATURE"),
policy=AuthDSLHelper.Envelope(
signaturePolicy=AuthDSLHelper.NOutOf(
0, []),
identities=mspPrincipalList).SerializeToString())
channel = common_dot_configtx_pb2.ConfigGroup()
channel.policies[chainCreatePolicyName].policy.CopyFrom(policy)
# print("signed Config Item:\n{0}\n".format(chainCreationPolicyNamesSignedConfigItem))
# print("chain Creation orgs signed Config Item:\n{0}\n".format(chainCreatorsOrgsPolicySignedConfigItem))
return channel
def setOrdererBootstrapGenesisBlock(genesisBlock):
'Responsible for setting the GensisBlock for the Orderer nodes upon composition'
| 47.759644 | 258 | 0.70001 | # Copyright IBM Corp. 2016 All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import time
import sys
import hashlib
if sys.version_info < (3, 6):
import sha3
from OpenSSL import crypto
from OpenSSL import rand
import ecdsa
from collections import namedtuple
from itertools import groupby
from enum import Enum
from google.protobuf import timestamp_pb2
from common import common_pb2 as common_dot_common_pb2
from common import configtx_pb2 as common_dot_configtx_pb2
from common import configuration_pb2 as common_dot_configuration_pb2
from common import policies_pb2 as common_dot_policies_pb2
from common import msp_principal_pb2
from msp import mspconfig_pb2
from peer import configuration_pb2 as peer_dot_configuration_pb2
from orderer import configuration_pb2 as orderer_dot_configuration_pb2
import orderer_util
from contexthelper import ContextHelper
import os
import re
import shutil
import compose
# Type to represent tuple of user, nodeName, ogranization
NodeAdminTuple = namedtuple("NodeAdminTuple", ['user', 'nodeName', 'organization'])
ApplicationGroup = "Application"
OrdererGroup = "Orderer"
MSPKey = "MSP"
toValue = lambda message: message.SerializeToString()
class Network(Enum):
Orderer = 1
Peer = 2
def GetUUID():
return compose.Composition.GetUUID()
def createRSAKey():
# Create RSA key, 2048 bit
pk = crypto.PKey()
pk.generate_key(crypto.TYPE_RSA, 2048)
assert pk.check() == True
return pk
def createECDSAKey(curve=ecdsa.NIST256p):
# Create ECDSA key
sk = ecdsa.SigningKey.generate(curve=curve)
return sk
def computeCryptoHash(data):
' This will currently return 128 hex characters'
# s = hashlib.sha3_256()
s = hashlib.sha256()
# s = hashlib.shake_256()
#return s.digest(64)
s.update(data)
return s.digest()
def createCertRequest(pkey, digest="sha256", **name):
"""
Create a certificate request.
Arguments: pkey - The key to associate with the request
digest - Digestion method to use for signing, default is sha256
**name - The name of the subject of the request, possible
arguments are:
C - Country name
ST - State or province name
L - Locality name
O - Organization name
OU - Organizational unit name
CN - Common name
emailAddress - E-mail address
Returns: The certificate request in an X509Req object
"""
req = crypto.X509Req()
subj = req.get_subject()
for key, value in name.items():
setattr(subj, key, value)
req.set_pubkey(pkey)
req.sign(pkey, digest)
return req
def createCertificate(req, issuerCertKey, serial, validityPeriod, digest="sha256", isCA=False):
"""
Generate a certificate given a certificate request.
Arguments: req - Certificate request to use
issuerCert - The certificate of the issuer
issuerKey - The private key of the issuer
serial - Serial number for the certificate
notBefore - Timestamp (relative to now) when the certificate
starts being valid
notAfter - Timestamp (relative to now) when the certificate
stops being valid
digest - Digest method to use for signing, default is sha256
Returns: The signed certificate in an X509 object
"""
issuerCert, issuerKey = issuerCertKey
notBefore, notAfter = validityPeriod
cert = crypto.X509()
cert.set_version(3)
cert.set_serial_number(serial)
cert.gmtime_adj_notBefore(notBefore)
cert.gmtime_adj_notAfter(notAfter)
cert.set_issuer(issuerCert.get_subject())
cert.set_subject(req.get_subject())
cert.set_pubkey(req.get_pubkey())
if isCA:
cert.add_extensions([crypto.X509Extension("basicConstraints", True,
"CA:TRUE, pathlen:0"),
crypto.X509Extension("subjectKeyIdentifier", False, "hash",
subject=cert)])
#TODO: This only is appropriate for root self signed!!!!
cert.add_extensions([crypto.X509Extension("authorityKeyIdentifier", False, "keyid:always", issuer=cert)])
else:
cert.add_extensions([crypto.X509Extension("basicConstraints", True,
"CA:FALSE"),
crypto.X509Extension("subjectKeyIdentifier", False, "hash",
subject=cert)])
cert.add_extensions([crypto.X509Extension("authorityKeyIdentifier", False, "keyid:always", issuer=issuerCert)])
cert.sign(issuerKey, digest)
return cert
# SUBJECT_DEFAULT = {countryName : "US", stateOrProvinceName : "NC", localityName : "RTP", organizationName : "IBM", organizationalUnitName : "Blockchain"}
class Entity:
def __init__(self, name):
self.name = name
# Create a ECDSA key, then a crypto pKey from the DER for usage with cert requests, etc.
self.ecdsaSigningKey = createECDSAKey()
self.pKey = crypto.load_privatekey(crypto.FILETYPE_ASN1, self.ecdsaSigningKey.to_der())
# Signing related ecdsa config
self.hashfunc = hashlib.sha256
self.sigencode = ecdsa.util.sigencode_der_canonize
self.sigdecode = ecdsa.util.sigdecode_der
def createCertRequest(self, nodeName):
req = createCertRequest(self.pKey, CN=nodeName)
# print("request => {0}".format(crypto.dump_certificate_request(crypto.FILETYPE_PEM, req)))
return req
def computeHash(self, data):
s = self.hashfunc()
s.update(data)
return s.digest()
def sign(self, dataAsBytearray):
return self.ecdsaSigningKey.sign(dataAsBytearray, hashfunc=self.hashfunc, sigencode=self.sigencode)
def verifySignature(self, signature, signersCert, data):
'Will verify the signature of an entity based upon public cert'
vk = ecdsa.VerifyingKey.from_der(crypto.dump_publickey(crypto.FILETYPE_ASN1, signersCert.get_pubkey()))
assert vk.verify(signature, data, hashfunc=self.hashfunc, sigdecode=self.sigdecode), "Invalid signature!!"
def getPrivateKeyAsPEM(self):
return self.ecdsaSigningKey.to_pem()
class User(Entity, orderer_util.UserRegistration):
def __init__(self, name):
Entity.__init__(self, name)
orderer_util.UserRegistration.__init__(self, name)
self.tags = {}
def setTagValue(self, tagKey, tagValue, overwrite=False):
if tagKey in self.tags:
assert not overwrite,"TagKey '{0}' already exists for user {1}, and did not provide overwrite=True".format(tagKey, self.getUserName())
self.tags[tagKey] = tagValue
return tagValue
class Organization(Entity):
def __init__(self, name):
Entity.__init__(self, name)
req = createCertRequest(self.pKey, CN=name)
numYrs = 1
self.signedCert = createCertificate(req, (req, self.pKey), 1000, (0, 60 * 60 * 24 * 365 * numYrs), isCA=True)
# Which networks this organization belongs to
self.networks = []
def getSelfSignedCert(self):
return self.signedCert
def getCertAsPEM(self):
return crypto.dump_certificate(crypto.FILETYPE_PEM, self.getSelfSignedCert())
def getMSPConfig(self):
certPemsList = [crypto.dump_certificate(crypto.FILETYPE_PEM, self.getSelfSignedCert())]
# For now, admin certs and CA certs are the same per @ASO
adminCerts = certPemsList
cacerts = adminCerts
# Currently only 1 component, CN=<orgName>
# name = self.getSelfSignedCert().get_subject().getComponents()[0][1]
name = self.name
fabricMSPConfig = mspconfig_pb2.FabricMSPConfig(admins=adminCerts, root_certs=cacerts, name=name)
mspConfig = mspconfig_pb2.MSPConfig(config=fabricMSPConfig.SerializeToString(), type=0)
return mspConfig
def createCertificate(self, certReq):
numYrs = 1
return createCertificate(certReq, (self.signedCert, self.pKey), 1000, (0, 60 * 60 * 24 * 365 * numYrs))
def addToNetwork(self, network):
'Used to track which network this organization is defined in.'
# assert network in Network, 'Network not recognized ({0}), expected to be one of ({1})'.format(network, list(Network))
if not network in self.networks:
self.networks.append(network)
class Directory:
def __init__(self):
self.organizations = {}
self.users = {}
self.ordererAdminTuples = {}
def getNamedCtxTuples(self):
return self.ordererAdminTuples
def _registerOrg(self, orgName):
assert orgName not in self.organizations, "Organization already registered {0}".format(orgName)
self.organizations[orgName] = Organization(orgName)
return self.organizations[orgName]
def _registerUser(self, userName):
assert userName not in self.users, "User already registered {0}".format(userName)
self.users[userName] = User(userName)
return self.users[userName]
def getUser(self, userName, shouldCreate=False):
if not userName in self.users and shouldCreate:
# self.users[userName] = User(userName)
self._registerUser(userName)
return self.users[userName]
def getUsers(self):
return self.users
def getOrganization(self, orgName, shouldCreate=False):
if not orgName in self.organizations and shouldCreate:
# self.organizations[orgName] = Organization(orgName)
self._registerOrg(orgName)
return self.organizations[orgName]
def getOrganizations(self):
return self.organizations
def findCertByTuple(self, userName, contextName, orgName):
ordererAdminTuple = NodeAdminTuple(user=userName, nodeName=contextName, organization=orgName)
return self.ordererAdminTuples[ordererAdminTuple]
def findCertForNodeAdminTuple(self, nodeAdminTuple):
assert nodeAdminTuple in self.ordererAdminTuples, "Node admin tuple not found for: {0}".format(nodeAdminTuple)
return self.ordererAdminTuples[nodeAdminTuple]
def getCertAsPEM(self, nodeAdminTuple):
assert nodeAdminTuple in self.ordererAdminTuples, "Node admin tuple not found for: {0}".format(nodeAdminTuple)
return crypto.dump_certificate(crypto.FILETYPE_PEM, self.ordererAdminTuples[nodeAdminTuple])
def findNodeAdminTuple(self, userName, contextName, orgName):
nodeAdminTuple = NodeAdminTuple(user=userName, nodeName=contextName, organization=orgName)
assert nodeAdminTuple in self.ordererAdminTuples, "Node admin tuple not found for: {0}".format(nodeAdminTuple)
return nodeAdminTuple
def registerOrdererAdminTuple(self, userName, ordererName, organizationName):
' Assign the user as orderer admin'
ordererAdminTuple = NodeAdminTuple(user=userName, nodeName=ordererName, organization=organizationName)
assert ordererAdminTuple not in self.ordererAdminTuples, "Orderer admin tuple already registered {0}".format(
ordererAdminTuple)
assert organizationName in self.organizations, "Orderer Organization not defined {0}".format(organizationName)
user = self.getUser(userName, shouldCreate=True)
certReq = user.createCertRequest(ordererAdminTuple.nodeName)
userCert = self.getOrganization(organizationName).createCertificate(certReq)
# Verify the newly created certificate
store = crypto.X509Store()
# Assuming a list of trusted certs
for trustedCert in [self.getOrganization(organizationName).signedCert]:
store.add_cert(trustedCert)
# Create a certificate context using the store and the certificate to verify
store_ctx = crypto.X509StoreContext(store, userCert)
# Verify the certificate, returns None if it can validate the certificate
store_ctx.verify_certificate()
self.ordererAdminTuples[ordererAdminTuple] = userCert
return ordererAdminTuple
class AuthDSLHelper:
@classmethod
def Envelope(cls, signaturePolicy, identities):
'Envelope builds an envelope message embedding a SignaturePolicy'
return common_dot_policies_pb2.SignaturePolicyEnvelope(
version=0,
policy=signaturePolicy,
identities=identities)
@classmethod
def NOutOf(cls, n, policies):
'NOutOf creates a policy which requires N out of the slice of policies to evaluate to true'
return common_dot_policies_pb2.SignaturePolicy(
n_out_of=common_dot_policies_pb2.SignaturePolicy.NOutOf(
N=n,
policies=policies,
),
)
class BootstrapHelper:
KEY_CONSENSUS_TYPE = "ConsensusType"
KEY_CHAIN_CREATION_POLICY_NAMES = "ChainCreationPolicyNames"
KEY_ACCEPT_ALL_POLICY = "AcceptAllPolicy"
KEY_INGRESS_POLICY = "IngressPolicyNames"
KEY_EGRESS_POLICY = "EgressPolicyNames"
KEY_HASHING_ALGORITHM = "HashingAlgorithm"
KEY_BATCH_SIZE = "BatchSize"
KEY_BATCH_TIMEOUT = "BatchTimeout"
KEY_CREATIONPOLICY = "CreationPolicy"
KEY_MSP_INFO = "MSP"
KEY_ANCHOR_PEERS = "AnchorPeers"
KEY_NEW_CONFIGURATION_ITEM_POLICY = "NewConfigurationItemPolicy"
DEFAULT_CHAIN_CREATORS = [KEY_ACCEPT_ALL_POLICY]
DEFAULT_NONCE_SIZE = 24
@classmethod
def getNonce(cls):
return rand.bytes(BootstrapHelper.DEFAULT_NONCE_SIZE)
@classmethod
def addSignatureToSignedConfigItem(cls, configUpdateEnvelope, (entity, cert)):
sigHeader = common_dot_common_pb2.SignatureHeader(creator=crypto.dump_certificate(crypto.FILETYPE_ASN1, cert),
nonce=BootstrapHelper.getNonce())
sigHeaderBytes = sigHeader.SerializeToString()
# Signature over the concatenation of configurationItem bytes and signatureHeader bytes
signature = entity.sign(sigHeaderBytes + configUpdateEnvelope.config_update)
# Now add new signature to Signatures repeated field
newConfigSig = configUpdateEnvelope.signatures.add()
newConfigSig.signature_header = sigHeaderBytes
newConfigSig.signature = signature
def __init__(self, chainId, lastModified=0, msgVersion=1, epoch=0, consensusType="solo", batchSize=10,
batchTimeout="10s", absoluteMaxBytes=100000000, preferredMaxBytes=512 * 1024, signers=[]):
self.chainId = str(chainId)
self.lastModified = lastModified
self.msgVersion = msgVersion
self.epoch = epoch
self.consensusType = consensusType
self.batchSize = batchSize
self.batchTimeout = batchTimeout
self.absoluteMaxBytes = absoluteMaxBytes
self.preferredMaxBytes = preferredMaxBytes
self.signers = signers
def makeChainHeader(self, type, txID="", extension='',
version=1,
timestamp=timestamp_pb2.Timestamp(seconds=int(time.time()), nanos=0)):
return common_dot_common_pb2.ChannelHeader(type=type,
version=version,
timestamp=timestamp,
channel_id=self.chainId,
epoch=self.epoch,
tx_id=txID,
extension=extension)
def makeSignatureHeader(self, serializeCertChain, nonce):
return common_dot_common_pb2.SignatureHeader(creator=serializeCertChain,
nonce=nonce)
def signConfigItem(self, configItem):
# signedConfigItem = common_dot_configuration_pb2.SignedConfigurationItem(
# ConfigurationItem=configItem.SerializeToString(), Signatures=None)
# return signedConfigItem
return configItem
def getConfigItem(self, commonConfigType, key, value):
configItem = common_dot_configtx_pb2.ConfigItem(
version=self.lastModified,
configPath=commonConfigType,
key=key,
mod_policy=BootstrapHelper.KEY_NEW_CONFIGURATION_ITEM_POLICY,
value=value)
return configItem
def encodeAnchorInfo(self, ciValue):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("PEER"),
key=BootstrapHelper.KEY_ANCHOR_PEERS,
value=ciValue.SerializeToString())
return self.signConfigItem(configItem)
def encodeMspInfo(self, mspUniqueId, ciValue):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("MSP"),
key=mspUniqueId,
value=ciValue.SerializeToString())
return self.signConfigItem(configItem)
def encodeHashingAlgorithm(self, hashingAlgorithm="SHAKE256"):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("CHAIN"),
key=BootstrapHelper.KEY_HASHING_ALGORITHM,
value=common_dot_configuration_pb2.HashingAlgorithm(name=hashingAlgorithm).SerializeToString())
return self.signConfigItem(configItem)
def encodeBatchSize(self):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("ORDERER"),
key=BootstrapHelper.KEY_BATCH_SIZE,
value=orderer_dot_configuration_pb2.BatchSize(maxMessageCount=self.batchSize,
absoluteMaxBytes=self.absoluteMaxBytes,
preferredMaxBytes=self.preferredMaxBytes).SerializeToString())
return self.signConfigItem(configItem)
def encodeBatchTimeout(self):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("ORDERER"),
key=BootstrapHelper.KEY_BATCH_TIMEOUT,
value=orderer_dot_configuration_pb2.BatchTimeout(timeout=self.batchTimeout).SerializeToString())
return self.signConfigItem(configItem)
def encodeConsensusType(self):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("ORDERER"),
key=BootstrapHelper.KEY_CONSENSUS_TYPE,
value=orderer_dot_configuration_pb2.ConsensusType(type=self.consensusType).SerializeToString())
return self.signConfigItem(configItem)
def encodeChainCreators(self, ciValue=orderer_dot_configuration_pb2.ChainCreationPolicyNames(
names=DEFAULT_CHAIN_CREATORS).SerializeToString()):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("ORDERER"),
key=BootstrapHelper.KEY_CHAIN_CREATION_POLICY_NAMES,
value=ciValue)
return self.signConfigItem(configItem)
def encodePolicy(self, key, policy=common_dot_policies_pb2.Policy(
type=common_dot_policies_pb2.Policy.PolicyType.Value("SIGNATURE"),
policy=AuthDSLHelper.Envelope(signaturePolicy=AuthDSLHelper.NOutOf(0, []), identities=[]).SerializeToString())):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("POLICY"),
key=key,
value=policy.SerializeToString())
return self.signConfigItem(configItem)
def encodeEgressPolicy(self):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("ORDERER"),
key=BootstrapHelper.KEY_EGRESS_POLICY,
value=orderer_dot_configuration_pb2.EgressPolicyNames(
names=[BootstrapHelper.KEY_ACCEPT_ALL_POLICY]).SerializeToString())
return self.signConfigItem(configItem)
def encodeIngressPolicy(self):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("ORDERER"),
key=BootstrapHelper.KEY_INGRESS_POLICY,
value=orderer_dot_configuration_pb2.IngressPolicyNames(
names=[BootstrapHelper.KEY_ACCEPT_ALL_POLICY]).SerializeToString())
return self.signConfigItem(configItem)
def encodeAcceptAllPolicy(self):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("POLICY"),
key=BootstrapHelper.KEY_ACCEPT_ALL_POLICY,
value=common_dot_policies_pb2.Policy(type=1, policy=AuthDSLHelper.Envelope(
signaturePolicy=AuthDSLHelper.NOutOf(0, []), identities=[]).SerializeToString()).SerializeToString())
return self.signConfigItem(configItem)
def lockDefaultModificationPolicy(self):
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("POLICY"),
key=BootstrapHelper.KEY_NEW_CONFIGURATION_ITEM_POLICY,
value=common_dot_policies_pb2.Policy(type=1, policy=AuthDSLHelper.Envelope(
signaturePolicy=AuthDSLHelper.NOutOf(1, []), identities=[]).SerializeToString()).SerializeToString())
return self.signConfigItem(configItem)
def computeBlockDataHash(self, blockData):
return computeCryptoHash(blockData.SerializeToString())
def signInitialChainConfig(self, signedConfigItems, chainCreationPolicyName):
'Create a signedConfigItem using previous config items'
# Create byte array to store concatenated bytes
# concatenatedConfigItemsBytes = bytearray()
# for sci in signedConfigItems:
# concatenatedConfigItemsBytes = concatenatedConfigItemsBytes + bytearray(sci.ConfigurationItem)
# hash = computeCryptoHash(concatenatedConfigItemsBytes)
# data = ''
# for sci in signedConfigItems:
# data = data + sci.ConfigurationItem
# # Compute hash over concatenated bytes
# hash = computeCryptoHash(data)
configItem = self.getConfigItem(
commonConfigType=common_dot_configtx_pb2.ConfigItem.ConfigType.Value("ORDERER"),
key=BootstrapHelper.KEY_CREATIONPOLICY,
value=orderer_dot_configuration_pb2.CreationPolicy(policy=chainCreationPolicyName).SerializeToString())
return [self.signConfigItem(configItem)] + signedConfigItems
def createConfigUpdateEnvelope(channelConfigGroup, chainId, chainCreationPolicyName):
# Returns a list prepended with a signedConfiguration
channelConfigGroup.groups[OrdererGroup].values[BootstrapHelper.KEY_CREATIONPOLICY].value = toValue(
orderer_dot_configuration_pb2.CreationPolicy(policy=chainCreationPolicyName))
config_update_envelope = createNewConfigUpdateEnvelope(channelConfig=channelConfigGroup, chainId=chainId)
return config_update_envelope
def getDirectory(context):
if 'bootstrapDirectory' not in context:
context.bootstrapDirectory = Directory()
return context.bootstrapDirectory
def getOrdererBootstrapAdmin(context, shouldCreate=False):
directory = getDirectory(context)
ordererBootstrapAdmin = directory.getUser(userName="ordererBootstrapAdmin", shouldCreate=shouldCreate)
return ordererBootstrapAdmin
def addOrdererBootstrapAdminOrgReferences(context, policyName, orgNames):
'Adds a key/value pair of policyName/[orgName,...]'
directory = getDirectory(context)
ordererBootstrapAdmin = directory.getUser(userName="ordererBootstrapAdmin", shouldCreate=False)
if not 'OrgReferences' in ordererBootstrapAdmin.tags:
ordererBootstrapAdmin.tags['OrgReferences'] = {}
policyNameToOrgNamesDict = ordererBootstrapAdmin.tags['OrgReferences']
assert not policyName in policyNameToOrgNamesDict, "PolicyName '{0}' already registered with ordererBootstrapAdmin".format(
policyName)
policyNameToOrgNamesDict[policyName] = orgNames
return policyNameToOrgNamesDict
def getOrdererBootstrapAdminOrgReferences(context):
directory = getDirectory(context)
ordererBootstrapAdmin = directory.getUser(userName="ordererBootstrapAdmin", shouldCreate=False)
if not 'OrgReferences' in ordererBootstrapAdmin.tags:
ordererBootstrapAdmin.tags['OrgReferences'] = {}
return ordererBootstrapAdmin.tags['OrgReferences']
def getSignedMSPConfigItems(context, orgNames):
directory = getDirectory(context)
orgs = [directory.getOrganization(orgName) for orgName in orgNames]
channel = common_dot_configtx_pb2.ConfigGroup()
for org in orgs:
channel.groups[ApplicationGroup].groups[org.name].values[BootstrapHelper.KEY_MSP_INFO].value = toValue(
org.getMSPConfig())
return [channel]
def getAnchorPeersConfigGroup(context, nodeAdminTuples):
directory = getDirectory(context)
config_group = common_dot_configtx_pb2.ConfigGroup()
for orgName, group in groupby([(nat.organization, nat) for nat in nodeAdminTuples], lambda x: x[0]):
anchorPeers = peer_dot_configuration_pb2.AnchorPeers()
for (k,nodeAdminTuple) in group:
anchorPeer = anchorPeers.anchor_peers.add()
anchorPeer.host = nodeAdminTuple.nodeName
anchorPeer.port = 5611
anchorPeer.cert = crypto.dump_certificate(crypto.FILETYPE_PEM,
directory.findCertForNodeAdminTuple(nodeAdminTuple))
config_group.groups[ApplicationGroup].groups[orgName].values[BootstrapHelper.KEY_ANCHOR_PEERS].value=toValue(anchorPeers)
return [config_group]
def getMspConfigItemsForPolicyNames(context, policyNames):
policyNameToOrgNamesDict = getOrdererBootstrapAdminOrgReferences(context)
# Get unique set of org names and return set of signed MSP ConfigItems
orgNamesReferenced = list(
set([orgName for policyName in policyNames for orgName in policyNameToOrgNamesDict[policyName]]))
orgNamesReferenced.sort()
return getSignedMSPConfigItems(context=context, orgNames=orgNamesReferenced)
def createSignedConfigItems(configGroups=[]):
channelConfig = createChannelConfigGroup()
for configGroup in configGroups:
mergeConfigGroups(channelConfig, configGroup)
return channelConfig
def createChannelConfigGroup(hashingAlgoName="SHA256", consensusType="solo", batchTimeout="10s", batchSizeMaxMessageCount=10, batchSizeAbsoluteMaxBytes=100000000, batchSizePreferredMaxBytes=512 * 1024):
channel = common_dot_configtx_pb2.ConfigGroup()
# channel.groups[ApplicationGroup] = common_dot_configtx_pb2.ConfigGroup()
# channel.groups[OrdererGroup] = common_dot_configtx_pb2.ConfigGroup()
channel.groups[ApplicationGroup]
channel.groups[OrdererGroup]
# v = common_dot_configtx_pb2.ConfigItem.ConfigType.Value
# configItems.append(bootstrapHelper.encodeHashingAlgorithm())
channel.values[BootstrapHelper.KEY_HASHING_ALGORITHM].value = toValue(
common_dot_configuration_pb2.HashingAlgorithm(name=hashingAlgoName))
channel.groups[OrdererGroup].values[BootstrapHelper.KEY_BATCH_SIZE].value = toValue(orderer_dot_configuration_pb2.BatchSize(maxMessageCount=batchSizeMaxMessageCount,absoluteMaxBytes=batchSizeAbsoluteMaxBytes,preferredMaxBytes=batchSizePreferredMaxBytes))
channel.groups[OrdererGroup].values[BootstrapHelper.KEY_BATCH_TIMEOUT].value = toValue(orderer_dot_configuration_pb2.BatchTimeout(timeout=batchTimeout))
channel.groups[OrdererGroup].values[BootstrapHelper.KEY_CONSENSUS_TYPE].value = toValue(orderer_dot_configuration_pb2.ConsensusType(type=consensusType))
acceptAllPolicy = common_dot_policies_pb2.Policy(type=1, policy=AuthDSLHelper.Envelope(
signaturePolicy=AuthDSLHelper.NOutOf(0, []), identities=[]).SerializeToString())
channel.policies[BootstrapHelper.KEY_ACCEPT_ALL_POLICY].policy.CopyFrom(acceptAllPolicy)
channel.groups[OrdererGroup].values[
BootstrapHelper.KEY_INGRESS_POLICY].value = toValue(
orderer_dot_configuration_pb2.IngressPolicyNames(
names=[BootstrapHelper.KEY_ACCEPT_ALL_POLICY]))
channel.groups[OrdererGroup].values[
BootstrapHelper.KEY_EGRESS_POLICY].value = toValue(
orderer_dot_configuration_pb2.EgressPolicyNames(
names=[BootstrapHelper.KEY_ACCEPT_ALL_POLICY]))
return channel
def createConfigUpdateTxEnvelope(chainId, configUpdateEnvelope):
'The Join channel flow'
bootstrapHelper = BootstrapHelper(chainId=chainId)
payloadChainHeader = bootstrapHelper.makeChainHeader(
type=common_dot_common_pb2.HeaderType.Value("CONFIG_UPDATE"))
# Now the SignatureHeader
serializedCreatorCertChain = None
nonce = None
payloadSignatureHeader = common_dot_common_pb2.SignatureHeader(
creator=serializedCreatorCertChain,
nonce=bootstrapHelper.getNonce(),
)
payloadHeader = common_dot_common_pb2.Header(
channel_header=payloadChainHeader,
signature_header=payloadSignatureHeader,
)
payload = common_dot_common_pb2.Payload(header=payloadHeader, data=configUpdateEnvelope.SerializeToString())
envelope = common_dot_common_pb2.Envelope(payload=payload.SerializeToString(), signature=None)
return envelope
def createConfigTxEnvelope(chainId, config_envelope):
# configEnvelope = common_dot_configtx_pb2.ConfigEnvelope(last_update=envelope.SerializeToString())
bootstrapHelper = BootstrapHelper(chainId=chainId)
payloadChainHeader = bootstrapHelper.makeChainHeader(
type=common_dot_common_pb2.HeaderType.Value("CONFIG"))
# Now the SignatureHeader
serializedCreatorCertChain = None
nonce = None
payloadSignatureHeader = common_dot_common_pb2.SignatureHeader(
creator=serializedCreatorCertChain,
nonce=bootstrapHelper.getNonce(),
)
payloadHeader = common_dot_common_pb2.Header(
channel_header=payloadChainHeader,
signature_header=payloadSignatureHeader,
)
payload = common_dot_common_pb2.Payload(header=payloadHeader, data=config_envelope.SerializeToString())
envelope = common_dot_common_pb2.Envelope(payload=payload.SerializeToString(), signature=None)
return envelope
return configEnvelope
def createNewConfigUpdateEnvelope(channelConfig, chainId):
configUpdate = common_dot_configtx_pb2.ConfigUpdate(header=common_dot_common_pb2.ChannelHeader(channel_id=chainId,
type=common_dot_common_pb2.HeaderType.Value(
"CONFIG_UPDATE")),
write_set=channelConfig)
configUpdateEnvelope = common_dot_configtx_pb2.ConfigUpdateEnvelope(config_update=configUpdate.SerializeToString(), signatures =[])
return configUpdateEnvelope
def mergeConfigGroups(configGroupTarget, configGroupSource):
for k, v in configGroupSource.groups.iteritems():
if k in configGroupTarget.groups.keys():
mergeConfigGroups(configGroupTarget.groups[k], configGroupSource.groups[k])
else:
configGroupTarget.groups[k].MergeFrom(v)
for k, v in configGroupSource.policies.iteritems():
if k in configGroupTarget.policies.keys():
mergeConfigGroups(configGroupTarget.policies[k], configGroupSource.policies[k])
else:
configGroupTarget.policies[k].MergeFrom(v)
for k, v in configGroupSource.values.iteritems():
assert not k in configGroupTarget.values.keys(), "Value already exists in target config group: {0}".format(k)
configGroupTarget.values[k].CopyFrom(v)
def createGenesisBlock(context, chainId, consensusType, signedConfigItems=[]):
'Generates the genesis block for starting the oderers and for use in the chain config transaction by peers'
# assert not "bootstrapGenesisBlock" in context,"Genesis block already created:\n{0}".format(context.bootstrapGenesisBlock)
directory = getDirectory(context)
assert len(directory.ordererAdminTuples) > 0, "No orderer admin tuples defined!!!"
channelConfig = createChannelConfigGroup()
for configGroup in signedConfigItems:
mergeConfigGroups(channelConfig, configGroup)
# (fileName, fileExist) = ContextHelper.GetHelper(context=context).getTmpPathForName(name="t",extension="protobuf")
# with open(fileName, 'w') as f:
# f.write(channelConfig.SerializeToString())
config = common_dot_configtx_pb2.Config(
header=common_dot_common_pb2.ChannelHeader(channel_id=chainId,
type=common_dot_common_pb2.HeaderType.Value("CONFIG")),
channel=channelConfig)
configEnvelope = common_dot_configtx_pb2.ConfigEnvelope(config=config)
envelope = createConfigTxEnvelope(chainId=chainId, config_envelope=configEnvelope)
blockData = common_dot_common_pb2.BlockData(data=[envelope.SerializeToString()])
# Spoke with kostas, for orderer in general
signaturesMetadata = ""
lastConfigurationBlockMetadata = common_dot_common_pb2.Metadata(
value=common_dot_common_pb2.LastConfig(index=0).SerializeToString()).SerializeToString()
ordererConfigMetadata = ""
transactionFilterMetadata = ""
bootstrapHelper = BootstrapHelper(chainId="NOT_USED")
block = common_dot_common_pb2.Block(
header=common_dot_common_pb2.BlockHeader(
number=0,
previous_hash=None,
data_hash=bootstrapHelper.computeBlockDataHash(blockData),
),
data=blockData,
metadata=common_dot_common_pb2.BlockMetadata(
metadata=[signaturesMetadata, lastConfigurationBlockMetadata, transactionFilterMetadata,
ordererConfigMetadata]),
)
# Add this back once crypto certs are required
for nodeAdminTuple in directory.ordererAdminTuples:
userCert = directory.ordererAdminTuples[nodeAdminTuple]
certAsPEM = crypto.dump_certificate(crypto.FILETYPE_PEM, userCert)
# print("UserCert for orderer genesis:\n{0}\n".format(certAsPEM))
# print("")
return (block, envelope)
class PathType(Enum):
'Denotes whether Path relative to Local filesystem or Containers volume reference.'
Local = 1
Container = 2
class CallbackHelper:
def __init__(self, discriminator, volumeRootPathInContainer = "/var/hyperledger/bddtests"):
self.volumeRootPathInContainer = volumeRootPathInContainer
self.discriminator = discriminator
def getVolumePath(self, composition, pathType=PathType.Local):
assert pathType in PathType, "Expected pathType of {0}".format(PathType)
basePath = "."
if pathType == PathType.Container:
basePath = self.volumeRootPathInContainer
return "{0}/volumes/{1}/{2}".format(basePath, self.discriminator, composition.projectName)
def getLocalMspConfigPath(self, composition, compose_service, pathType=PathType.Local):
return "{0}/{1}/localMspConfig".format(self.getVolumePath(composition, pathType), compose_service)
def _writeMspFiles(self, directory , composition, compose_service, network):
localMspConfigPath = self.getLocalMspConfigPath(composition, compose_service=compose_service)
os.makedirs("{0}/{1}".format(localMspConfigPath, "signcerts"))
os.makedirs("{0}/{1}".format(localMspConfigPath, "admincerts"))
os.makedirs("{0}/{1}".format(localMspConfigPath, "cacerts"))
os.makedirs("{0}/{1}".format(localMspConfigPath, "keystore"))
# Loop through directory and place Organization Certs into cacerts folder
for targetOrg in [org for orgName, org in directory.organizations.items() if network in org.networks]:
with open("{0}/cacerts/{1}.pem".format(localMspConfigPath, targetOrg.name), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, targetOrg.getSelfSignedCert()))
# Loop through directory and place Organization Certs into admincerts folder
# TODO: revisit this, ASO recommended for now
for targetOrg in [org for orgName, org in directory.organizations.items() if network in org.networks]:
with open("{0}/admincerts/{1}.pem".format(localMspConfigPath, targetOrg.name), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, targetOrg.getSelfSignedCert()))
# Find the peer signer Tuple for this peer and add to signcerts folder
for pnt, cert in [(peerNodeTuple, cert) for peerNodeTuple, cert in directory.ordererAdminTuples.items() if
compose_service in peerNodeTuple.user and "signer" in peerNodeTuple.user.lower()]:
# Put the PEM file in the signcerts folder
with open("{0}/signcerts/{1}.pem".format(localMspConfigPath, pnt.user), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, cert))
# Put the associated private key into the keystore folder
user = directory.getUser(pnt.user, shouldCreate=False)
with open("{0}/keystore/{1}.pem".format(localMspConfigPath, pnt.user), "w") as f:
f.write(user.ecdsaSigningKey.to_pem())
# f.write(crypto.dump_privatekey(crypto.FILETYPE_PEM, user.pKey))
class OrdererGensisBlockCompositionCallback(compose.CompositionCallback, CallbackHelper):
'Responsible for setting the GensisBlock for the Orderer nodes upon composition'
def __init__(self, context, genesisBlock, genesisFileName="genesis_file"):
CallbackHelper.__init__(self, discriminator="orderer")
self.context = context
self.genesisFileName = genesisFileName
self.genesisBlock = genesisBlock
self.volumeRootPathInContainer = "/var/hyperledger/bddtests"
compose.Composition.RegisterCallbackInContext(context, self)
def getVolumePath(self, composition, pathType=PathType.Local):
assert pathType in PathType, "Expected pathType of {0}".format(PathType)
basePath = "."
if pathType == PathType.Container:
basePath = self.volumeRootPathInContainer
return "{0}/volumes/orderer/{1}".format(basePath, composition.projectName)
def getGenesisFilePath(self, composition, pathType=PathType.Local):
return "{0}/{1}".format(self.getVolumePath(composition, pathType), self.genesisFileName)
def getOrdererList(self, composition):
return [serviceName for serviceName in composition.getServiceNames() if "orderer" in serviceName]
def composing(self, composition, context):
print("Will copy gensisiBlock over at this point ")
os.makedirs(self.getVolumePath(composition))
with open(self.getGenesisFilePath(composition), "wb") as f:
f.write(self.genesisBlock.SerializeToString())
directory = getDirectory(context)
for ordererService in self.getOrdererList(composition):
self._writeMspFiles(directory=directory,
compose_service=ordererService,
composition=composition,
network=Network.Orderer)
def decomposing(self, composition, context):
'Will remove the orderer volume path folder for the context'
shutil.rmtree(self.getVolumePath(composition))
def getEnv(self, composition, context, env):
env["ORDERER_GENERAL_GENESISMETHOD"] = "file"
env["ORDERER_GENERAL_GENESISFILE"] = self.getGenesisFilePath(composition, pathType=PathType.Container)
for ordererService in self.getOrdererList(composition):
localMspConfigPath = self.getLocalMspConfigPath(composition, ordererService, pathType=PathType.Container)
env["{0}_ORDERER_GENERAL_LOCALMSPDIR".format(ordererService.upper())] = localMspConfigPath
class PeerCompositionCallback(compose.CompositionCallback):
'Responsible for setting up Peer nodes upon composition'
def __init__(self, context):
self.context = context
self.volumeRootPathInContainer = "/var/hyperledger/bddtests"
compose.Composition.RegisterCallbackInContext(context, self)
def getVolumePath(self, composition, pathType=PathType.Local):
assert pathType in PathType, "Expected pathType of {0}".format(PathType)
basePath = "."
if pathType == PathType.Container:
basePath = self.volumeRootPathInContainer
return "{0}/volumes/peer/{1}".format(basePath, composition.projectName)
def getPeerList(self, composition):
return [serviceName for serviceName in composition.getServiceNames() if "peer" in serviceName]
def getLocalMspConfigPath(self, composition, peerService, pathType=PathType.Local):
return "{0}/{1}/localMspConfig".format(self.getVolumePath(composition, pathType), peerService)
def _createLocalMspConfigDirs(self, mspConfigPath):
os.makedirs("{0}/{1}".format(mspConfigPath, "signcerts"))
os.makedirs("{0}/{1}".format(mspConfigPath, "admincerts"))
os.makedirs("{0}/{1}".format(mspConfigPath, "cacerts"))
os.makedirs("{0}/{1}".format(mspConfigPath, "keystore"))
def composing(self, composition, context):
'Will copy local MSP info over at this point for each peer node'
directory = getDirectory(context)
for peerService in self.getPeerList(composition):
localMspConfigPath = self.getLocalMspConfigPath(composition, peerService)
self._createLocalMspConfigDirs(localMspConfigPath)
# Loop through directory and place Peer Organization Certs into cacerts folder
for peerOrg in [org for orgName, org in directory.organizations.items() if Network.Peer in org.networks]:
with open("{0}/cacerts/{1}.pem".format(localMspConfigPath, peerOrg.name), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, peerOrg.getSelfSignedCert()))
# Loop through directory and place Peer Organization Certs into admincerts folder
# TODO: revisit this, ASO recommended for now
for peerOrg in [org for orgName, org in directory.organizations.items() if Network.Peer in org.networks]:
with open("{0}/admincerts/{1}.pem".format(localMspConfigPath, peerOrg.name), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, peerOrg.getSelfSignedCert()))
# Find the peer signer Tuple for this peer and add to signcerts folder
for pnt, cert in [(peerNodeTuple, cert) for peerNodeTuple, cert in directory.ordererAdminTuples.items() if
peerService in peerNodeTuple.user and "signer" in peerNodeTuple.user.lower()]:
# Put the PEM file in the signcerts folder
with open("{0}/signcerts/{1}.pem".format(localMspConfigPath, pnt.user), "w") as f:
f.write(crypto.dump_certificate(crypto.FILETYPE_PEM, cert))
# Put the associated private key into the keystore folder
user = directory.getUser(pnt.user, shouldCreate=False)
with open("{0}/keystore/{1}.pem".format(localMspConfigPath, pnt.user), "w") as f:
f.write(user.ecdsaSigningKey.to_pem())
# f.write(crypto.dump_privatekey(crypto.FILETYPE_PEM, user.pKey))
def decomposing(self, composition, context):
'Will remove the orderer volume path folder for the context'
shutil.rmtree(self.getVolumePath(composition))
def getEnv(self, composition, context, env):
for peerService in self.getPeerList(composition):
localMspConfigPath = self.getLocalMspConfigPath(composition, peerService, pathType=PathType.Container)
env["{0}_CORE_PEER_MSPCFGPATH".format(peerService.upper())] = localMspConfigPath
def createChainCreationPolicyNames(context, chainCreationPolicyNames, chaindId):
channel = common_dot_configtx_pb2.ConfigGroup()
channel.groups[OrdererGroup].values[BootstrapHelper.KEY_CHAIN_CREATION_POLICY_NAMES].value = toValue(
orderer_dot_configuration_pb2.ChainCreationPolicyNames(
names=chainCreationPolicyNames))
return channel
def createChainCreatorsPolicy(context, chainCreatePolicyName, chaindId, orgNames):
'Creates the chain Creator Policy with name'
directory = getDirectory(context)
bootstrapHelper = BootstrapHelper(chainId=chaindId)
# This represents the domain of organization which can create channels for the orderer
# First create org MSPPrincicpal
# Collect the orgs from the table
mspPrincipalList = []
for org in [directory.getOrganization(orgName) for orgName in orgNames]:
mspPrincipalList.append(msp_principal_pb2.MSPPrincipal(
PrincipalClassification=msp_principal_pb2.MSPPrincipal.Classification.Value("ByIdentity"),
Principal=crypto.dump_certificate(crypto.FILETYPE_ASN1, org.getSelfSignedCert())))
policy = common_dot_policies_pb2.Policy(
type=common_dot_policies_pb2.Policy.PolicyType.Value("SIGNATURE"),
policy=AuthDSLHelper.Envelope(
signaturePolicy=AuthDSLHelper.NOutOf(
0, []),
identities=mspPrincipalList).SerializeToString())
channel = common_dot_configtx_pb2.ConfigGroup()
channel.policies[chainCreatePolicyName].policy.CopyFrom(policy)
# print("signed Config Item:\n{0}\n".format(chainCreationPolicyNamesSignedConfigItem))
# print("chain Creation orgs signed Config Item:\n{0}\n".format(chainCreatorsOrgsPolicySignedConfigItem))
return channel
def setOrdererBootstrapGenesisBlock(genesisBlock):
'Responsible for setting the GensisBlock for the Orderer nodes upon composition'
def broadcastCreateChannelConfigTx(context, composeService, chainId, configTxEnvelope, user):
dataFunc = lambda x: configTxEnvelope
user.broadcastMessages(context=context, numMsgsToBroadcast=1, composeService=composeService, chainID=chainId,
dataFunc=dataFunc)
def getArgsFromContextForUser(context, userName):
directory = getDirectory(context)
# Update the chaincodeSpec ctorMsg for invoke
args = []
if 'table' in context:
if context.table:
# There are function arguments
user = directory.getUser(userName)
# Allow the user to specify expressions referencing tags in the args list
pattern = re.compile('\{(.*)\}$')
for arg in context.table[0].cells:
m = pattern.match(arg)
if m:
# tagName reference found in args list
tagName = m.groups()[0]
# make sure the tagName is found in the users tags
assert tagName in user.tags, "TagName '{0}' not found for user '{1}'".format(tagName,
user.getUserName())
args.append(user.tags[tagName])
else:
# No tag referenced, pass the arg
args.append(arg)
return args
| 27,791 | 5,540 | 1,082 |
58df7f16e56e87e15dfa9041e31ca6ce6ba9565a | 3,657 | py | Python | examples/single_whistler/deck.py | tien-vo/tpsim | 8ea7153ff252774533a9567b5eb8f4c11edd5dde | [
"MIT"
] | 1 | 2021-12-30T05:49:09.000Z | 2021-12-30T05:49:09.000Z | examples/single_whistler/deck.py | tien-vo/tpsim | 8ea7153ff252774533a9567b5eb8f4c11edd5dde | [
"MIT"
] | null | null | null | examples/single_whistler/deck.py | tien-vo/tpsim | 8ea7153ff252774533a9567b5eb8f4c11edd5dde | [
"MIT"
] | null | null | null | from itertools import product
import matplotlib.pyplot as plt
import tpsim as tp
import numpy as np
# --------------------------------------------------------------------------- #
# Simulation parameters
# --------------------------------------------------------------------------- #
## ---------- Simulation time
# Start time [1/wce]
t_start = 0
# Stop time [1/wce]
t_stop = 70 * 2 * np.pi
# Time step [1/wce]
dt = np.pi * 1e-3
# Number of time steps
Nt = int(t_stop / dt)
# Interval to save data
save_interval = Nt // 1000
## ---------- Background parameters
# Background magnetic field [nT]
B0 = 60
# Number density [1/cc]
n = 350
# Electron cyclotron frequency
wce = tp.wcs(B0, "e-")
# Electron plasma frequency
wpe = tp.wps(n, "e-")
## ---------- Wave parameters
# w/wce
w_wce = 0.15
# Obliquity [rad]
theta = np.radians(65)
# Amplitude [mV/m]
E0 = 20.0
# Normalized amplitude
E0n = tp.normalize_E(E0, B0)
# Calculate polarizations
Nx, Nz, pex, pey, pez, pbx, pby, pbz = tp.whistler_polarization(
theta, B0, n, w_wce * wce
)
"""NOTE:
In this coordinate system, the electric field is determined analytically as
Ew = E0 ( pex cos(psi), -ey sin(psi), ez cos(psi) ). So the original electric
field magnitude is Ew0 = E0n sqrt(pex^2 + pez^2) if psi0 = 0. Since we wish the
wave amplitude to be E0n, we have to rescale it such that Ew0 = E0n.
"""
E0n /= np.sqrt(pex ** 2 + pez ** 2)
# Recalculate original amplitude in physical units (just to make sure)
Ew0_recal = E0n * np.sqrt(pex ** 2 + pez ** 2) * tp.c * B0 * 1e-3
Bw0_recal = E0n * pby * B0
## ---------- Particle parameters
# Speed
S_range = np.linspace(0, tp.KE2S(3000), 30) / tp.c
# Gyrophase
G_range = np.radians(np.arange(0, 1, 20))
# Pitch angle
P_range = np.radians(np.arange(0, 181, 5))
S, G, P = np.array(list(product(S_range, G_range, P_range))).T
# Number of particles
Np = len(S)
# Normalized position
xn, yn, zn = np.zeros((3, Np))
# Normalized velocity
uxn, uyn, uzn = S * np.array([
np.sin(P) * np.cos(G),
np.sin(P) * np.sin(G),
np.cos(P),
])
## ---------- Electromagnetic field model
## Define the electromagnetic field here (background + perturbations)
def EM_model(t, x, y, z, ux, uy, uz):
"""Returns `Np`-dimensional arrays `Ex`, `Ey`, `Ez`, `Bx`, `By`, `Bz` in
normalized units.
"""
psi = w_wce * (Nx * x + Nz * z - t)
Ex = E0n * pex * np.cos(psi)
Ey =-E0n * pey * np.sin(psi)
Ez = E0n * pez * np.cos(psi)
Bx = E0n * pbx * np.sin(psi)
By = E0n * pby * np.cos(psi)
Bz = E0n * pbz * np.sin(psi) + 1
return Ex, Ey, Ez, Bx, By, Bz
# Simulation information
sim_info = f"""
------------------------------------------------------------------
Simulation of particle dynamics in a single uniform whistler.
------------------------------------------------------------------
* dtwce : {dt:.4f}
* Number of time steps : {Nt}
----------
* Number of particles : {Np}
----------
* Background magnetic field : {B0} nT
* Background electron density : {n} cm-3
* Electron plasma frequency : {wpe:.4f} rad/s
* Electron cyclotron frequency : {wce:.4f} rad/s
* wpe / wce : {wpe / wce:.4f}
----------
* Original wave electric field amplitude : {Ew0_recal:.4f} mV/m
* Original wave magnetic field amplitude : {Bw0_recal:.4f} nT
* Wave frequency : {w_wce} wce
* Wave obliquity : {np.degrees(theta)} deg
------------------------------------------------------------------
"""
| 32.362832 | 79 | 0.527208 | from itertools import product
import matplotlib.pyplot as plt
import tpsim as tp
import numpy as np
# --------------------------------------------------------------------------- #
# Simulation parameters
# --------------------------------------------------------------------------- #
## ---------- Simulation time
# Start time [1/wce]
t_start = 0
# Stop time [1/wce]
t_stop = 70 * 2 * np.pi
# Time step [1/wce]
dt = np.pi * 1e-3
# Number of time steps
Nt = int(t_stop / dt)
# Interval to save data
save_interval = Nt // 1000
## ---------- Background parameters
# Background magnetic field [nT]
B0 = 60
# Number density [1/cc]
n = 350
# Electron cyclotron frequency
wce = tp.wcs(B0, "e-")
# Electron plasma frequency
wpe = tp.wps(n, "e-")
## ---------- Wave parameters
# w/wce
w_wce = 0.15
# Obliquity [rad]
theta = np.radians(65)
# Amplitude [mV/m]
E0 = 20.0
# Normalized amplitude
E0n = tp.normalize_E(E0, B0)
# Calculate polarizations
Nx, Nz, pex, pey, pez, pbx, pby, pbz = tp.whistler_polarization(
theta, B0, n, w_wce * wce
)
"""NOTE:
In this coordinate system, the electric field is determined analytically as
Ew = E0 ( pex cos(psi), -ey sin(psi), ez cos(psi) ). So the original electric
field magnitude is Ew0 = E0n sqrt(pex^2 + pez^2) if psi0 = 0. Since we wish the
wave amplitude to be E0n, we have to rescale it such that Ew0 = E0n.
"""
E0n /= np.sqrt(pex ** 2 + pez ** 2)
# Recalculate original amplitude in physical units (just to make sure)
Ew0_recal = E0n * np.sqrt(pex ** 2 + pez ** 2) * tp.c * B0 * 1e-3
Bw0_recal = E0n * pby * B0
## ---------- Particle parameters
# Speed
S_range = np.linspace(0, tp.KE2S(3000), 30) / tp.c
# Gyrophase
G_range = np.radians(np.arange(0, 1, 20))
# Pitch angle
P_range = np.radians(np.arange(0, 181, 5))
S, G, P = np.array(list(product(S_range, G_range, P_range))).T
# Number of particles
Np = len(S)
# Normalized position
xn, yn, zn = np.zeros((3, Np))
# Normalized velocity
uxn, uyn, uzn = S * np.array([
np.sin(P) * np.cos(G),
np.sin(P) * np.sin(G),
np.cos(P),
])
## ---------- Electromagnetic field model
## Define the electromagnetic field here (background + perturbations)
def EM_model(t, x, y, z, ux, uy, uz):
"""Returns `Np`-dimensional arrays `Ex`, `Ey`, `Ez`, `Bx`, `By`, `Bz` in
normalized units.
"""
psi = w_wce * (Nx * x + Nz * z - t)
Ex = E0n * pex * np.cos(psi)
Ey =-E0n * pey * np.sin(psi)
Ez = E0n * pez * np.cos(psi)
Bx = E0n * pbx * np.sin(psi)
By = E0n * pby * np.cos(psi)
Bz = E0n * pbz * np.sin(psi) + 1
return Ex, Ey, Ez, Bx, By, Bz
# Simulation information
sim_info = f"""
------------------------------------------------------------------
Simulation of particle dynamics in a single uniform whistler.
------------------------------------------------------------------
* dtwce : {dt:.4f}
* Number of time steps : {Nt}
----------
* Number of particles : {Np}
----------
* Background magnetic field : {B0} nT
* Background electron density : {n} cm-3
* Electron plasma frequency : {wpe:.4f} rad/s
* Electron cyclotron frequency : {wce:.4f} rad/s
* wpe / wce : {wpe / wce:.4f}
----------
* Original wave electric field amplitude : {Ew0_recal:.4f} mV/m
* Original wave magnetic field amplitude : {Bw0_recal:.4f} nT
* Wave frequency : {w_wce} wce
* Wave obliquity : {np.degrees(theta)} deg
------------------------------------------------------------------
"""
| 0 | 0 | 0 |
a86d3520a0bb4718e9f10358c3dffc208a816a15 | 6,196 | py | Python | tinyapi/session.py | jsvine/tinyapi | ac2cf0400b2a9b22bd0b1f43b36be99f5d1a787c | [
"MIT"
] | 12 | 2015-12-14T16:53:35.000Z | 2022-01-18T03:31:19.000Z | tinyapi/session.py | jsvine/tinyapi | ac2cf0400b2a9b22bd0b1f43b36be99f5d1a787c | [
"MIT"
] | 2 | 2017-03-17T04:04:03.000Z | 2022-01-18T03:32:40.000Z | tinyapi/session.py | jsvine/tinyapi | ac2cf0400b2a9b22bd0b1f43b36be99f5d1a787c | [
"MIT"
] | 4 | 2017-11-22T08:10:28.000Z | 2019-02-28T06:25:31.000Z | """
The :class:`.Session` class provides TinyAPI's core functionality. It manages the authentication cookies and token for all requests to TinyLetter's undocumented API.
"""
import requests
import re
import json
from .draft import Draft
URL = "https://app.tinyletter.com/__svcbus__/"
DEFAULT_MESSAGE_STATUSES = [
"sent",
"sending",
]
token_pat = re.compile(r'csrf_token="([^"]+)"')
class Session(object):
"""An authenticated tinyletter.com session."""
def __init__(self, username, password=False):
"""Returns a logged-in session."""
self.username = username
self.cookies, self.token = get_cookies_and_token()
self._login(password)
def request(self, service, data):
"""
Makes a call to TinyLetter's __svcbus__ endpoint.
"""
_res = self._request(service, data)
res = _res.json()[0][0]
if res["success"] == True:
return res["result"]
else:
err_msg = res["errmsg"]
raise Exception("Request not successful: '{0}'".format(err_msg))
def count_messages(self, statuses=DEFAULT_MESSAGE_STATUSES):
"""Returns the number of messages your account has sent.
``DEFAULT_MESSAGE_STATUSES`` is set to ``[ "sent", "sending" ]``.
Other possible statuses include "draft", "failed_review", "failed_disabled", and "failed_schedule".
"""
return self.request("count:Message", [{"status": statuses}])
def get_messages(self,
statuses=DEFAULT_MESSAGE_STATUSES,
order="sent_at desc",
offset=None,
count=None,
content=False):
"""Returns a list of messages your account sent.
Messages are sorted by ``order``, starting at an optional integer ``offset``, and optionally limited to the first ``count`` items (in sorted order).
Returned data includes various statistics about each message, e.g., ``total_opens``, ``open_rate``, ``total_clicks``, ``unsubs``, ``soft_bounces``. If ``content=True``, the returned data will also include HTML content of each message.
"""
req_data = [ { "status": statuses }, order, fmt_paging(offset, count) ]
service = "query:Message.stats"
if content: service += ", Message.content"
return self.request(service, req_data)
def get_drafts(self, **kwargs):
"""Same as Session.get_messages, but where ``statuses=["draft"]``."""
default_kwargs = { "order": "updated_at desc" }
default_kwargs.update(kwargs)
return self.get_messages(statuses=["draft"], **default_kwargs)
def get_message(self, message_id):
"""Return stats *and* message content for a given message."""
req_data = [ str(message_id) ]
return self.request("find:Message.stats, Message.content", req_data)
def count_urls(self):
"""Returns the total number of URLs included in your messages"""
return self.request("count:Message_Url", [ None ])
def get_urls(self, order="total_clicks desc", offset=None, count=None):
"""Returns a list of URLs you've included in messages.
List is sorted by ``total_clicks``, starting at an optional integer ``offset``, and optionally limited to the first ``count`` items.
"""
req_data = [ None, order, fmt_paging(offset, count) ]
return self.request("query:Message_Url", req_data)
def get_message_urls(self, message_id, order="total_clicks desc"):
"""Returns a list of URLs you've included in a specific message.
List is sorted by ``total_clicks``, starting at an optional integer ``offset``, and optionally limited to the first ``count`` items.
"""
req_data = [ { "message_id": str(message_id) }, order, None ]
return self.request("query:Message_Url", req_data)
def count_subscribers(self):
"""Returns your newsletter's number of subscribers."""
return self.request("count:Contact", [ None ])
def get_subscribers(self,
order="created_at desc",
offset=None,
count=None):
"""Returns a list of subscribers.
List is sorted by most-recent-to-subsribe, starting at an optional integer ``offset``, and optionally limited to the first ``count`` items (in sorted order).
Returned data includes various statistics about each subscriber, e.g., ``total_sent``, ``total_opens``, ``total_clicks``.
"""
req_data = [ None, order, fmt_paging(offset, count)]
return self.request("query:Contact.stats", req_data)
def get_subscriber(self, subscriber_id):
"""Returns data corresponding to a specific subcriber."""
req_data = [ str(subscriber_id) ]
return self.request("find:Contact.stats", req_data)
def create_draft(self):
"""Create a new draft message."""
return Draft(self)
def edit_draft(self, message_id):
"""Fetch a specific draft to be edited."""
return Draft(self, message_id).fetch()
| 38.725 | 242 | 0.630245 | """
The :class:`.Session` class provides TinyAPI's core functionality. It manages the authentication cookies and token for all requests to TinyLetter's undocumented API.
"""
import requests
import re
import json
from .draft import Draft
URL = "https://app.tinyletter.com/__svcbus__/"
DEFAULT_MESSAGE_STATUSES = [
"sent",
"sending",
]
token_pat = re.compile(r'csrf_token="([^"]+)"')
def get_cookies_and_token():
res = requests.get("https://app.tinyletter.com/")
token = re.search(token_pat, res.content.decode("utf-8")).group(1)
return (res.cookies, token)
def create_payload(service, data, token):
return json.dumps([[[service, data]], [], token])
def fmt_paging(offset, count):
if offset == None and count == None:
return None
return "{0}, {1}".format(offset or 0, count)
class Session(object):
"""An authenticated tinyletter.com session."""
def __init__(self, username, password=False):
"""Returns a logged-in session."""
self.username = username
self.cookies, self.token = get_cookies_and_token()
self._login(password)
def _request(self, service, data):
payload = create_payload(service, data, self.token)
res = requests.post(URL,
cookies=self.cookies,
data=payload,
headers={'Content-Type': 'application/octet-stream'})
self.cookies = res.cookies
return res
def request(self, service, data):
"""
Makes a call to TinyLetter's __svcbus__ endpoint.
"""
_res = self._request(service, data)
res = _res.json()[0][0]
if res["success"] == True:
return res["result"]
else:
err_msg = res["errmsg"]
raise Exception("Request not successful: '{0}'".format(err_msg))
def _login(self, password):
req_data = [self.username, password, None, None, None, None ]
try:
self.request("service:User.loginService", req_data)
except:
raise Exception("Login not successful.")
def get_profile(self):
return self.request("service:User.currentUser", [])
def count_messages(self, statuses=DEFAULT_MESSAGE_STATUSES):
"""Returns the number of messages your account has sent.
``DEFAULT_MESSAGE_STATUSES`` is set to ``[ "sent", "sending" ]``.
Other possible statuses include "draft", "failed_review", "failed_disabled", and "failed_schedule".
"""
return self.request("count:Message", [{"status": statuses}])
def get_messages(self,
statuses=DEFAULT_MESSAGE_STATUSES,
order="sent_at desc",
offset=None,
count=None,
content=False):
"""Returns a list of messages your account sent.
Messages are sorted by ``order``, starting at an optional integer ``offset``, and optionally limited to the first ``count`` items (in sorted order).
Returned data includes various statistics about each message, e.g., ``total_opens``, ``open_rate``, ``total_clicks``, ``unsubs``, ``soft_bounces``. If ``content=True``, the returned data will also include HTML content of each message.
"""
req_data = [ { "status": statuses }, order, fmt_paging(offset, count) ]
service = "query:Message.stats"
if content: service += ", Message.content"
return self.request(service, req_data)
def get_drafts(self, **kwargs):
"""Same as Session.get_messages, but where ``statuses=["draft"]``."""
default_kwargs = { "order": "updated_at desc" }
default_kwargs.update(kwargs)
return self.get_messages(statuses=["draft"], **default_kwargs)
def get_message(self, message_id):
"""Return stats *and* message content for a given message."""
req_data = [ str(message_id) ]
return self.request("find:Message.stats, Message.content", req_data)
def count_urls(self):
"""Returns the total number of URLs included in your messages"""
return self.request("count:Message_Url", [ None ])
def get_urls(self, order="total_clicks desc", offset=None, count=None):
"""Returns a list of URLs you've included in messages.
List is sorted by ``total_clicks``, starting at an optional integer ``offset``, and optionally limited to the first ``count`` items.
"""
req_data = [ None, order, fmt_paging(offset, count) ]
return self.request("query:Message_Url", req_data)
def get_message_urls(self, message_id, order="total_clicks desc"):
"""Returns a list of URLs you've included in a specific message.
List is sorted by ``total_clicks``, starting at an optional integer ``offset``, and optionally limited to the first ``count`` items.
"""
req_data = [ { "message_id": str(message_id) }, order, None ]
return self.request("query:Message_Url", req_data)
def count_subscribers(self):
"""Returns your newsletter's number of subscribers."""
return self.request("count:Contact", [ None ])
def get_subscribers(self,
order="created_at desc",
offset=None,
count=None):
"""Returns a list of subscribers.
List is sorted by most-recent-to-subsribe, starting at an optional integer ``offset``, and optionally limited to the first ``count`` items (in sorted order).
Returned data includes various statistics about each subscriber, e.g., ``total_sent``, ``total_opens``, ``total_clicks``.
"""
req_data = [ None, order, fmt_paging(offset, count)]
return self.request("query:Contact.stats", req_data)
def get_subscriber(self, subscriber_id):
"""Returns data corresponding to a specific subcriber."""
req_data = [ str(subscriber_id) ]
return self.request("find:Contact.stats", req_data)
def create_draft(self):
"""Create a new draft message."""
return Draft(self)
def edit_draft(self, message_id):
"""Fetch a specific draft to be edited."""
return Draft(self, message_id).fetch()
| 926 | 0 | 158 |
f409cb051e59b19461bb161deaf05f5327ab5ada | 4,030 | py | Python | src/tddw.py | AshirwadPradhan/tpsql | e240a273acfe8ec06502910b52a795cfb51aaf65 | [
"MIT"
] | 2 | 2020-06-07T06:21:31.000Z | 2021-01-21T05:02:04.000Z | src/tddw.py | AshirwadPradhan/tpsql | e240a273acfe8ec06502910b52a795cfb51aaf65 | [
"MIT"
] | null | null | null | src/tddw.py | AshirwadPradhan/tpsql | e240a273acfe8ec06502910b52a795cfb51aaf65 | [
"MIT"
] | null | null | null | from flask import Flask, request, abort, jsonify
from pyspark import SparkContext
from pyspark.sql import SQLContext
from pyspark.sql.types import *
import os
from itertools import combinations
from pyspark.sql.functions import monotonically_increasing_id
app = Flask(__name__)
sc = SparkContext()
sqlContext = SQLContext(sc)
@app.route('/')
@app.route('/runq', methods=['POST'])
if __name__ == '__main__':
import argparse
ap = argparse.ArgumentParser()
ap.add_argument('-p', '--port', required=False, help='port number')
args = vars(ap.parse_args())
try:
port = args['port']
app.run(port=int(port), debug=True)
except ValueError:
app.run(port=5000, debug=True) | 36.972477 | 109 | 0.545906 | from flask import Flask, request, abort, jsonify
from pyspark import SparkContext
from pyspark.sql import SQLContext
from pyspark.sql.types import *
import os
from itertools import combinations
from pyspark.sql.functions import monotonically_increasing_id
app = Flask(__name__)
sc = SparkContext()
sqlContext = SQLContext(sc)
@app.route('/')
def index():
return "Hello, World!"
@app.route('/runq', methods=['POST'])
def run_query():
# print('this')
if request.method == 'POST':
# print(request.method)
p_path = os.path.join('src','')
if not request.json or not 'query' in request.json or not 'table' in request.json:
abort(400)
query = request.json['query']
dbname = request.json['dbname']
table = request.json['table']
# print(query)
# print(table)
#load the table in the db
tpath = os.path.join(p_path+'db', dbname, table[0])
df = sqlContext.read.load(tpath+'.csv', format='csv', inferSchema='true', header='true')
print('Table 1 loaded....')
df.registerTempTable(table[0])
left_len = len(df.columns)
right_len = 0
if len(table) == 4:
print('Join Condition Identified')
df.registerTempTable(table[1])
#load the table in the db
tpath = os.path.join(p_path+'db', dbname, table[2])
df_j = sqlContext.read.load(tpath+'.csv', format='csv', inferSchema='true', header='true')
print('Table 2 loaded...')
df_j.registerTempTable(table[2])
df_j.registerTempTable(table[3])
#run SQL query here
df = sqlContext.sql(query)
print('Query Execution Completed')
# df.show(10)
#save in the partial output path
# toutpath = os.path.join('tmp','f.csv')
print('Removing duplicates from the query output')
try:
# df.printSchema()
df_n = None
#remove duplicate columns
u_col = list(dict.fromkeys(df.columns))
for col in u_col:
print('Selecting...'+col)
try:
if df_n == None:
df_n = df.select(col)
else:
t_m = df_n
t_m = t_m.withColumn('__id__', monotonically_increasing_id())
s_m = df.select(col).withColumn('__id__', monotonically_increasing_id())
df_n = t_m.join(s_m,'__id__','inner').drop('__id__')
except:
if df_n == None:
df_n = df.select(table[1]+'.'+col)
else:
t_m = df_n
t_m = t_m.withColumn('__id__', monotonically_increasing_id())
s_m = df.select(table[1]+'.'+col).withColumn('__id__', monotonically_increasing_id())
df_n = t_m.join(s_m,'__id__','inner').drop('__id__')
print('Removing Duplicates Done')
# df_n = df_n.coalesce(1)
# df_n.show(10)
# df_n.printSchema()
df_n.toPandas().to_csv(p_path+'tmp\db'+dbname+'.csv', index=False)
print('Task Query Output Saved')
# df.coalesce(1).write.csv(p_path+'tmp\db'+dbname+'.csv', mode='overwrite', header=True)
except ValueError:
print('Task Manager Interrupted')
raise ValueError
except Exception as e:
print('Task Manager Interrupted')
raise e
data = {'lt': left_len}
print(data)
return jsonify(data), 202
if __name__ == '__main__':
import argparse
ap = argparse.ArgumentParser()
ap.add_argument('-p', '--port', required=False, help='port number')
args = vars(ap.parse_args())
try:
port = args['port']
app.run(port=int(port), debug=True)
except ValueError:
app.run(port=5000, debug=True) | 3,272 | 0 | 44 |
c0264f9b7ae20616b41a392c80f4c21e7ecc3fe7 | 7,014 | py | Python | grao_table_processing/grao.py | INDEAVRDataStrategyServices/GRAO-Tables-Processing | 42722d1efe8db9749bad6cc7ed3e31a90b0ab1ea | [
"MIT"
] | null | null | null | grao_table_processing/grao.py | INDEAVRDataStrategyServices/GRAO-Tables-Processing | 42722d1efe8db9749bad6cc7ed3e31a90b0ab1ea | [
"MIT"
] | null | null | null | grao_table_processing/grao.py | INDEAVRDataStrategyServices/GRAO-Tables-Processing | 42722d1efe8db9749bad6cc7ed3e31a90b0ab1ea | [
"MIT"
] | null | null | null | """
This is the project's main file, it has a function for each of the main classes, as well
as the wikidata uploader file. The imports are above, as well as split into each file.
There is a simple logger to track any critical errors.
"""
import logging
import pandas as pd
import datetime
from grao_table_processing.markdown_to_df import ReadMarkdownTable
from grao_table_processing.acquire_url import DataURL
from grao_table_processing.ekatte_dataframe import EkatteDataframe
from grao_table_processing.wikidata_codes import WikidataCodes
from grao_table_processing.wikidata_uploader import upload_to_wikidata, set_old_ranks_to_normal
logging.basicConfig(filename='logs/ekatte.log', filemode='a+', level=logging.CRITICAL,
format='%(asctime)s %(levelname)s %(name)s %(message)s')
def generate_url(url_object: DataURL()) -> str:
"""
Calls the DataURL class and provides a URL to extract data from
Args:
url_object: DataURL() class object
Return:
DataURL.generate_data_url(url_object): string
"""
return DataURL.generate_data_url(url_object)
def extract_date(url: str) -> datetime.date:
"""
By using the result of the generate URL function, extracts the date to be used
in the data loading.
Args:
url: a string URL that leads to a markdown table for date extraction
Return:
date_object: datetime.date object
"""
markdown_object = ReadMarkdownTable(url, '|')
date_object = markdown_object.extract_date()
return date_object
def transformations(url: str) -> pd.DataFrame:
"""
This function invokes the ReadMarkdownTable class, and does all necessary
transformations so that it is ready to be merged forward.
Args:
url: a string URL that leads to a markdown table for data extraction
Return:
markdown_object.markdown_df: pd.DataFrame
"""
markdown_object = ReadMarkdownTable(url, '|')
# ''''''''''''''' Drop unused columns '''''''''''''''''
column_list = [0, 5, 6, 7, 9, 10, 11, 12]
markdown_object.drop_attributes(column_list)
# ''''''''''''''' Use meaningful labels '''''''''''''''''
markdown_object.markdown_df.columns = ['region', 'municipality', 'settlement',
'permanent_population', 'current_population']
# '''''''''''Cleaning initial data'''''''''''''''''
atts_clean = ['region', 'municipality', 'settlement']
markdown_object.strip_columns(atts_clean)
markdown_object.lower_columns(atts_clean)
markdown_object.replace_letters(atts_clean, 'ь,ъ')
markdown_object.replace_letters(atts_clean, 'ъо,ьо')
markdown_object.change_labels('settlement', 'с.елин пелин (гара елин п', 'с.елин пелин')
markdown_object.change_labels('municipality', 'добричка', 'добрич-селска')
markdown_object.change_labels('municipality', 'добрич-град', 'добрич')
markdown_object.change_labels('municipality', 'добрич-селска', 'добрич')
markdown_object.change_labels('region', 'добрич-град', 'добрич')
markdown_object.change_labels('region', 'добрич-селска', 'добрич')
markdown_object.change_labels('region', "софийска", 'софия')
markdown_object.change_labels('region', "столична", 'софия')
markdown_object.change_labels('municipality', "софийска", 'софия')
markdown_object.change_labels('municipality', "столична", 'софия')
markdown_object.change_labels('municipality', "софия (столица)", 'софия')
markdown_object.change_labels('region', "софия (столица)", 'софия')
# ''''''''''''''' Remove neighborhoods, vacation areas, Vulchovci '''''''''''''''''
clear_settlements = [
"кв.",
"ж.к.",
"к.к.",
"с.вълчовци"
]
markdown_object.clear_kv_zk('settlement', clear_settlements)
# ''''''''''''''' Clean Markdown DataFrame '''''''''''''''''
return markdown_object.markdown_df
def merge_with_ekatte(dataframe: pd.DataFrame) -> pd.DataFrame:
"""
The function invokes the EkatteDataframe class, produces the ekatte_dataframe
and merges it with the GRAO markdown table.
Args:
dataframe: pd.DataFrame
Return:
EkatteDataframe.merge_with_main(ekatte_frame): a pd.DataFrame
"""
ekatte_frame = EkatteDataframe(dataframe)
return EkatteDataframe.remove_ambigious_names(ekatte_frame)
def merge_with_q_codes(dataframe: pd.DataFrame) -> pd.DataFrame:
"""
The function invokes the WikidataCodes class, produces the Q code dataframe
and merges it with the GRAO Dataframe with Ekatte codes.
Args:
dataframe: pd.DataFrame
Return:
matched_data: pd.DataFrame, ready to have its values uploaded to WikiData
"""
wikidata_codes = WikidataCodes(dataframe)
matched_data = WikidataCodes.merge_with_ekatte(wikidata_codes)
return matched_data
def reset_ranks_to_normal(dataframe: pd.DataFrame) -> None:
"""
This function calls the Set old ranks to normal function from wikidata uploader,
it goes through each settlement resetting its historic values to "Normal Rank"
subsequently, the upload sets the most recent population values to "Preferred Rank"
and they appear on Wikipedia. This repeats each subsequent time data is uploaded.
Args:
dataframe: pandas DataFrame
Return:
None
"""
set_old_ranks_to_normal(dataframe)
def upload_data(matched_data: pd.DataFrame, url: str, date: datetime.date) -> None:
"""
This function invokes the Upload_to_wikidata function from the wikidata_uploader module.
it carries out the functions by clearing out the ranks, uploading the data quarter by quarter
for all settlements.
Args:
matched_data: pd.DataFrame
url: string
date: datetime.date
Return:
None
"""
upload_to_wikidata(matched_data, url, date)
def update_date_file(url_object: DataURL()) -> None:
"""
If the upload concludes successfully, this function is invoked. It finally updates
the date helper file with the most recent date, so that the future uploads happen on schedule.
The URL is added to the processed reports log for archiving.
Args:
url_object: DataURL() class object
Return:
None
"""
DataURL.update_date_file(url_object)
def main():
"""
The main function sets the parameters for every function in the grao.py module.
It carries out the entire logic of the project from data extraction to loading.
Return:
None
"""
url_object = DataURL()
url = generate_url(url_object)
print(url)
date = extract_date(url)
print(date)
dataframe = transformations(url)
print(dataframe.shape)
ekatte_frame = merge_with_ekatte(dataframe)
print(ekatte_frame.shape)
matched_data = merge_with_q_codes(ekatte_frame)
print(matched_data.shape)
reset_ranks_to_normal(matched_data)
upload_data(matched_data, url, date)
update_date_file(url_object)
if __name__ == "__main__":
main()
| 34.895522 | 98 | 0.699458 | """
This is the project's main file, it has a function for each of the main classes, as well
as the wikidata uploader file. The imports are above, as well as split into each file.
There is a simple logger to track any critical errors.
"""
import logging
import pandas as pd
import datetime
from grao_table_processing.markdown_to_df import ReadMarkdownTable
from grao_table_processing.acquire_url import DataURL
from grao_table_processing.ekatte_dataframe import EkatteDataframe
from grao_table_processing.wikidata_codes import WikidataCodes
from grao_table_processing.wikidata_uploader import upload_to_wikidata, set_old_ranks_to_normal
logging.basicConfig(filename='logs/ekatte.log', filemode='a+', level=logging.CRITICAL,
format='%(asctime)s %(levelname)s %(name)s %(message)s')
def generate_url(url_object: DataURL()) -> str:
"""
Calls the DataURL class and provides a URL to extract data from
Args:
url_object: DataURL() class object
Return:
DataURL.generate_data_url(url_object): string
"""
return DataURL.generate_data_url(url_object)
def extract_date(url: str) -> datetime.date:
"""
By using the result of the generate URL function, extracts the date to be used
in the data loading.
Args:
url: a string URL that leads to a markdown table for date extraction
Return:
date_object: datetime.date object
"""
markdown_object = ReadMarkdownTable(url, '|')
date_object = markdown_object.extract_date()
return date_object
def transformations(url: str) -> pd.DataFrame:
"""
This function invokes the ReadMarkdownTable class, and does all necessary
transformations so that it is ready to be merged forward.
Args:
url: a string URL that leads to a markdown table for data extraction
Return:
markdown_object.markdown_df: pd.DataFrame
"""
markdown_object = ReadMarkdownTable(url, '|')
# ''''''''''''''' Drop unused columns '''''''''''''''''
column_list = [0, 5, 6, 7, 9, 10, 11, 12]
markdown_object.drop_attributes(column_list)
# ''''''''''''''' Use meaningful labels '''''''''''''''''
markdown_object.markdown_df.columns = ['region', 'municipality', 'settlement',
'permanent_population', 'current_population']
# '''''''''''Cleaning initial data'''''''''''''''''
atts_clean = ['region', 'municipality', 'settlement']
markdown_object.strip_columns(atts_clean)
markdown_object.lower_columns(atts_clean)
markdown_object.replace_letters(atts_clean, 'ь,ъ')
markdown_object.replace_letters(atts_clean, 'ъо,ьо')
markdown_object.change_labels('settlement', 'с.елин пелин (гара елин п', 'с.елин пелин')
markdown_object.change_labels('municipality', 'добричка', 'добрич-селска')
markdown_object.change_labels('municipality', 'добрич-град', 'добрич')
markdown_object.change_labels('municipality', 'добрич-селска', 'добрич')
markdown_object.change_labels('region', 'добрич-град', 'добрич')
markdown_object.change_labels('region', 'добрич-селска', 'добрич')
markdown_object.change_labels('region', "софийска", 'софия')
markdown_object.change_labels('region', "столична", 'софия')
markdown_object.change_labels('municipality', "софийска", 'софия')
markdown_object.change_labels('municipality', "столична", 'софия')
markdown_object.change_labels('municipality', "софия (столица)", 'софия')
markdown_object.change_labels('region', "софия (столица)", 'софия')
# ''''''''''''''' Remove neighborhoods, vacation areas, Vulchovci '''''''''''''''''
clear_settlements = [
"кв.",
"ж.к.",
"к.к.",
"с.вълчовци"
]
markdown_object.clear_kv_zk('settlement', clear_settlements)
# ''''''''''''''' Clean Markdown DataFrame '''''''''''''''''
return markdown_object.markdown_df
def merge_with_ekatte(dataframe: pd.DataFrame) -> pd.DataFrame:
"""
The function invokes the EkatteDataframe class, produces the ekatte_dataframe
and merges it with the GRAO markdown table.
Args:
dataframe: pd.DataFrame
Return:
EkatteDataframe.merge_with_main(ekatte_frame): a pd.DataFrame
"""
ekatte_frame = EkatteDataframe(dataframe)
return EkatteDataframe.remove_ambigious_names(ekatte_frame)
def merge_with_q_codes(dataframe: pd.DataFrame) -> pd.DataFrame:
"""
The function invokes the WikidataCodes class, produces the Q code dataframe
and merges it with the GRAO Dataframe with Ekatte codes.
Args:
dataframe: pd.DataFrame
Return:
matched_data: pd.DataFrame, ready to have its values uploaded to WikiData
"""
wikidata_codes = WikidataCodes(dataframe)
matched_data = WikidataCodes.merge_with_ekatte(wikidata_codes)
return matched_data
def reset_ranks_to_normal(dataframe: pd.DataFrame) -> None:
"""
This function calls the Set old ranks to normal function from wikidata uploader,
it goes through each settlement resetting its historic values to "Normal Rank"
subsequently, the upload sets the most recent population values to "Preferred Rank"
and they appear on Wikipedia. This repeats each subsequent time data is uploaded.
Args:
dataframe: pandas DataFrame
Return:
None
"""
set_old_ranks_to_normal(dataframe)
def upload_data(matched_data: pd.DataFrame, url: str, date: datetime.date) -> None:
"""
This function invokes the Upload_to_wikidata function from the wikidata_uploader module.
it carries out the functions by clearing out the ranks, uploading the data quarter by quarter
for all settlements.
Args:
matched_data: pd.DataFrame
url: string
date: datetime.date
Return:
None
"""
upload_to_wikidata(matched_data, url, date)
def update_date_file(url_object: DataURL()) -> None:
"""
If the upload concludes successfully, this function is invoked. It finally updates
the date helper file with the most recent date, so that the future uploads happen on schedule.
The URL is added to the processed reports log for archiving.
Args:
url_object: DataURL() class object
Return:
None
"""
DataURL.update_date_file(url_object)
def main():
"""
The main function sets the parameters for every function in the grao.py module.
It carries out the entire logic of the project from data extraction to loading.
Return:
None
"""
url_object = DataURL()
url = generate_url(url_object)
print(url)
date = extract_date(url)
print(date)
dataframe = transformations(url)
print(dataframe.shape)
ekatte_frame = merge_with_ekatte(dataframe)
print(ekatte_frame.shape)
matched_data = merge_with_q_codes(ekatte_frame)
print(matched_data.shape)
reset_ranks_to_normal(matched_data)
upload_data(matched_data, url, date)
update_date_file(url_object)
if __name__ == "__main__":
main()
| 0 | 0 | 0 |
8baf0f58c798d89822847950ad3c8d73b55bbcc0 | 479 | py | Python | Lesson 6/HW_6.py | ProfessorAtomicManiac/Webscraping-Projects | 595d74a106c523e10ef93958af93a3355721d1ca | [
"MIT"
] | null | null | null | Lesson 6/HW_6.py | ProfessorAtomicManiac/Webscraping-Projects | 595d74a106c523e10ef93958af93a3355721d1ca | [
"MIT"
] | null | null | null | Lesson 6/HW_6.py | ProfessorAtomicManiac/Webscraping-Projects | 595d74a106c523e10ef93958af93a3355721d1ca | [
"MIT"
] | null | null | null | import requests
from bs4 import BeautifulSoup
import requests
url = 'https://www.imdb.com/search/title/?series=tt0285335&view=simple&sort=release_date,asc&start=1'
bru = 'https://www.imdb.com/search/title/?series=tt0285335&view=simple&sort=release_date,asc&start=51'
for pg in range(1, 362, 50):
page = requests.get(url, params={})
soup = BeautifulSoup(page.content, 'html.parser')
table = soup.find('table', {"class": "wikitable sortable plainrowheaders"})
| 34.214286 | 103 | 0.726514 | import requests
from bs4 import BeautifulSoup
import requests
url = 'https://www.imdb.com/search/title/?series=tt0285335&view=simple&sort=release_date,asc&start=1'
bru = 'https://www.imdb.com/search/title/?series=tt0285335&view=simple&sort=release_date,asc&start=51'
for pg in range(1, 362, 50):
page = requests.get(url, params={})
soup = BeautifulSoup(page.content, 'html.parser')
table = soup.find('table', {"class": "wikitable sortable plainrowheaders"})
| 0 | 0 | 0 |
8631dbe3953f2f98e70d7805b3d51c0383bce0f2 | 12,609 | py | Python | scipy/integrate/tests/test_quadpack.py | rostyboost/scipy | 2f5aa264724099c03772ed784e7a947d2bea8398 | [
"BSD-3-Clause"
] | null | null | null | scipy/integrate/tests/test_quadpack.py | rostyboost/scipy | 2f5aa264724099c03772ed784e7a947d2bea8398 | [
"BSD-3-Clause"
] | null | null | null | scipy/integrate/tests/test_quadpack.py | rostyboost/scipy | 2f5aa264724099c03772ed784e7a947d2bea8398 | [
"BSD-3-Clause"
] | 1 | 2021-09-17T03:51:02.000Z | 2021-09-17T03:51:02.000Z | from __future__ import division, print_function, absolute_import
import sys
import math
import numpy as np
from numpy import sqrt, cos, sin, arctan, exp, log, pi, Inf
from numpy.testing import (assert_,
assert_allclose, assert_array_less, assert_almost_equal, assert_raises)
import pytest
from scipy.integrate import quad, dblquad, tplquad, nquad
from scipy._lib.six import xrange
from scipy._lib._ccallback import LowLevelCallable
import ctypes
import ctypes.util
from scipy._lib._ccallback_c import sine_ctypes
import scipy.integrate._test_multivariate as clib_test
| 32.921671 | 89 | 0.529067 | from __future__ import division, print_function, absolute_import
import sys
import math
import numpy as np
from numpy import sqrt, cos, sin, arctan, exp, log, pi, Inf
from numpy.testing import (assert_,
assert_allclose, assert_array_less, assert_almost_equal, assert_raises)
import pytest
from scipy.integrate import quad, dblquad, tplquad, nquad
from scipy._lib.six import xrange
from scipy._lib._ccallback import LowLevelCallable
import ctypes
import ctypes.util
from scipy._lib._ccallback_c import sine_ctypes
import scipy.integrate._test_multivariate as clib_test
def assert_quad(value_and_err, tabled_value, errTol=1.5e-8):
value, err = value_and_err
assert_allclose(value, tabled_value, atol=err, rtol=0)
if errTol is not None:
assert_array_less(err, errTol)
class TestCtypesQuad(object):
def setup_method(self):
if sys.platform == 'win32':
if sys.version_info < (3, 5):
files = [ctypes.util.find_msvcrt()]
else:
files = ['api-ms-win-crt-math-l1-1-0.dll']
elif sys.platform == 'darwin':
files = ['libm.dylib']
else:
files = ['libm.so', 'libm.so.6']
for file in files:
try:
self.lib = ctypes.CDLL(file)
break
except OSError:
pass
else:
# This test doesn't work on some Linux platforms (Fedora for
# example) that put an ld script in libm.so - see gh-5370
self.skipTest("Ctypes can't import libm.so")
restype = ctypes.c_double
argtypes = (ctypes.c_double,)
for name in ['sin', 'cos', 'tan']:
func = getattr(self.lib, name)
func.restype = restype
func.argtypes = argtypes
def test_typical(self):
assert_quad(quad(self.lib.sin, 0, 5), quad(math.sin, 0, 5)[0])
assert_quad(quad(self.lib.cos, 0, 5), quad(math.cos, 0, 5)[0])
assert_quad(quad(self.lib.tan, 0, 1), quad(math.tan, 0, 1)[0])
def test_ctypes_sine(self):
quad(LowLevelCallable(sine_ctypes), 0, 1)
def test_ctypes_variants(self):
lib = ctypes.CDLL(clib_test.__file__)
sin_0 = lib._sin_0
sin_0.restype = ctypes.c_double
sin_0.argtypes = [ctypes.c_double, ctypes.c_void_p]
sin_1 = lib._sin_1
sin_1.restype = ctypes.c_double
sin_1.argtypes = [ctypes.c_int, ctypes.POINTER(ctypes.c_double), ctypes.c_void_p]
sin_2 = lib._sin_2
sin_2.restype = ctypes.c_double
sin_2.argtypes = [ctypes.c_double]
sin_3 = lib._sin_3
sin_3.restype = ctypes.c_double
sin_3.argtypes = [ctypes.c_int, ctypes.POINTER(ctypes.c_double)]
sin_4 = lib._sin_3
sin_4.restype = ctypes.c_double
sin_4.argtypes = [ctypes.c_int, ctypes.c_double]
all_sigs = [sin_0, sin_1, sin_2, sin_3, sin_4]
legacy_sigs = [sin_2, sin_4]
legacy_only_sigs = [sin_4]
# LowLevelCallables work for new signatures
for j, func in enumerate(all_sigs):
callback = LowLevelCallable(func)
if func in legacy_only_sigs:
assert_raises(ValueError, quad, callback, 0, pi)
else:
assert_allclose(quad(callback, 0, pi)[0], 2.0)
# Plain ctypes items work only for legacy signatures
for j, func in enumerate(legacy_sigs):
if func in legacy_sigs:
assert_allclose(quad(func, 0, pi)[0], 2.0)
else:
assert_raises(ValueError, quad, func, 0, pi)
class TestMultivariateCtypesQuad(object):
def setup_method(self):
self.lib = ctypes.CDLL(clib_test.__file__)
restype = ctypes.c_double
argtypes = (ctypes.c_int, ctypes.c_double)
for name in ['_multivariate_typical', '_multivariate_indefinite',
'_multivariate_sin']:
func = getattr(self.lib, name)
func.restype = restype
func.argtypes = argtypes
def test_typical(self):
# 1) Typical function with two extra arguments:
assert_quad(quad(self.lib._multivariate_typical, 0, pi, (2, 1.8)),
0.30614353532540296487)
def test_indefinite(self):
# 2) Infinite integration limits --- Euler's constant
assert_quad(quad(self.lib._multivariate_indefinite, 0, Inf),
0.577215664901532860606512)
def test_threadsafety(self):
# Ensure multivariate ctypes are threadsafe
def threadsafety(y):
return y + quad(self.lib._multivariate_sin, 0, 1)[0]
assert_quad(quad(threadsafety, 0, 1), 0.9596976941318602)
class TestQuad(object):
def test_typical(self):
# 1) Typical function with two extra arguments:
def myfunc(x, n, z): # Bessel function integrand
return cos(n*x-z*sin(x))/pi
assert_quad(quad(myfunc, 0, pi, (2, 1.8)), 0.30614353532540296487)
def test_indefinite(self):
# 2) Infinite integration limits --- Euler's constant
def myfunc(x): # Euler's constant integrand
return -exp(-x)*log(x)
assert_quad(quad(myfunc, 0, Inf), 0.577215664901532860606512)
def test_singular(self):
# 3) Singular points in region of integration.
def myfunc(x):
if 0 < x < 2.5:
return sin(x)
elif 2.5 <= x <= 5.0:
return exp(-x)
else:
return 0.0
assert_quad(quad(myfunc, 0, 10, points=[2.5, 5.0]),
1 - cos(2.5) + exp(-2.5) - exp(-5.0))
def test_sine_weighted_finite(self):
# 4) Sine weighted integral (finite limits)
def myfunc(x, a):
return exp(a*(x-1))
ome = 2.0**3.4
assert_quad(quad(myfunc, 0, 1, args=20, weight='sin', wvar=ome),
(20*sin(ome)-ome*cos(ome)+ome*exp(-20))/(20**2 + ome**2))
def test_sine_weighted_infinite(self):
# 5) Sine weighted integral (infinite limits)
def myfunc(x, a):
return exp(-x*a)
a = 4.0
ome = 3.0
assert_quad(quad(myfunc, 0, Inf, args=a, weight='sin', wvar=ome),
ome/(a**2 + ome**2))
def test_cosine_weighted_infinite(self):
# 6) Cosine weighted integral (negative infinite limits)
def myfunc(x, a):
return exp(x*a)
a = 2.5
ome = 2.3
assert_quad(quad(myfunc, -Inf, 0, args=a, weight='cos', wvar=ome),
a/(a**2 + ome**2))
def test_algebraic_log_weight(self):
# 6) Algebraic-logarithmic weight.
def myfunc(x, a):
return 1/(1+x+2**(-a))
a = 1.5
assert_quad(quad(myfunc, -1, 1, args=a, weight='alg',
wvar=(-0.5, -0.5)),
pi/sqrt((1+2**(-a))**2 - 1))
def test_cauchypv_weight(self):
# 7) Cauchy prinicpal value weighting w(x) = 1/(x-c)
def myfunc(x, a):
return 2.0**(-a)/((x-1)**2+4.0**(-a))
a = 0.4
tabledValue = ((2.0**(-0.4)*log(1.5) -
2.0**(-1.4)*log((4.0**(-a)+16) / (4.0**(-a)+1)) -
arctan(2.0**(a+2)) -
arctan(2.0**a)) /
(4.0**(-a) + 1))
assert_quad(quad(myfunc, 0, 5, args=0.4, weight='cauchy', wvar=2.0),
tabledValue, errTol=1.9e-8)
def test_double_integral(self):
# 8) Double Integral test
def simpfunc(y, x): # Note order of arguments.
return x+y
a, b = 1.0, 2.0
assert_quad(dblquad(simpfunc, a, b, lambda x: x, lambda x: 2*x),
5/6.0 * (b**3.0-a**3.0))
def test_double_integral2(self):
def func(x0, x1, t0, t1):
return x0 + x1 + t0 + t1
g = lambda x: x
h = lambda x: 2 * x
args = 1, 2
assert_quad(dblquad(func, 1, 2, g, h, args=args),35./6 + 9*.5)
def test_triple_integral(self):
# 9) Triple Integral test
def simpfunc(z, y, x, t): # Note order of arguments.
return (x+y+z)*t
a, b = 1.0, 2.0
assert_quad(tplquad(simpfunc, a, b,
lambda x: x, lambda x: 2*x,
lambda x, y: x - y, lambda x, y: x + y,
(2.,)),
2*8/3.0 * (b**4.0 - a**4.0))
class TestNQuad(object):
def test_fixed_limits(self):
def func1(x0, x1, x2, x3):
val = (x0**2 + x1*x2 - x3**3 + np.sin(x0) +
(1 if (x0 - 0.2*x3 - 0.5 - 0.25*x1 > 0) else 0))
return val
def opts_basic(*args):
return {'points': [0.2*args[2] + 0.5 + 0.25*args[0]]}
res = nquad(func1, [[0, 1], [-1, 1], [.13, .8], [-.15, 1]],
opts=[opts_basic, {}, {}, {}], full_output=True)
assert_quad(res[:-1], 1.5267454070738635)
assert_(res[-1]['neval'] > 0 and res[-1]['neval'] < 4e5)
def test_variable_limits(self):
scale = .1
def func2(x0, x1, x2, x3, t0, t1):
val = (x0*x1*x3**2 + np.sin(x2) + 1 +
(1 if x0 + t1*x1 - t0 > 0 else 0))
return val
def lim0(x1, x2, x3, t0, t1):
return [scale * (x1**2 + x2 + np.cos(x3)*t0*t1 + 1) - 1,
scale * (x1**2 + x2 + np.cos(x3)*t0*t1 + 1) + 1]
def lim1(x2, x3, t0, t1):
return [scale * (t0*x2 + t1*x3) - 1,
scale * (t0*x2 + t1*x3) + 1]
def lim2(x3, t0, t1):
return [scale * (x3 + t0**2*t1**3) - 1,
scale * (x3 + t0**2*t1**3) + 1]
def lim3(t0, t1):
return [scale * (t0 + t1) - 1, scale * (t0 + t1) + 1]
def opts0(x1, x2, x3, t0, t1):
return {'points': [t0 - t1*x1]}
def opts1(x2, x3, t0, t1):
return {}
def opts2(x3, t0, t1):
return {}
def opts3(t0, t1):
return {}
res = nquad(func2, [lim0, lim1, lim2, lim3], args=(0, 0),
opts=[opts0, opts1, opts2, opts3])
assert_quad(res, 25.066666666666663)
def test_square_separate_ranges_and_opts(self):
def f(y, x):
return 1.0
assert_quad(nquad(f, [[-1, 1], [-1, 1]], opts=[{}, {}]), 4.0)
def test_square_aliased_ranges_and_opts(self):
def f(y, x):
return 1.0
r = [-1, 1]
opt = {}
assert_quad(nquad(f, [r, r], opts=[opt, opt]), 4.0)
def test_square_separate_fn_ranges_and_opts(self):
def f(y, x):
return 1.0
def fn_range0(*args):
return (-1, 1)
def fn_range1(*args):
return (-1, 1)
def fn_opt0(*args):
return {}
def fn_opt1(*args):
return {}
ranges = [fn_range0, fn_range1]
opts = [fn_opt0, fn_opt1]
assert_quad(nquad(f, ranges, opts=opts), 4.0)
def test_square_aliased_fn_ranges_and_opts(self):
def f(y, x):
return 1.0
def fn_range(*args):
return (-1, 1)
def fn_opt(*args):
return {}
ranges = [fn_range, fn_range]
opts = [fn_opt, fn_opt]
assert_quad(nquad(f, ranges, opts=opts), 4.0)
def test_matching_quad(self):
def func(x):
return x**2 + 1
res, reserr = quad(func, 0, 4)
res2, reserr2 = nquad(func, ranges=[[0, 4]])
assert_almost_equal(res, res2)
assert_almost_equal(reserr, reserr2)
def test_matching_dblquad(self):
def func2d(x0, x1):
return x0**2 + x1**3 - x0 * x1 + 1
res, reserr = dblquad(func2d, -2, 2, lambda x: -3, lambda x: 3)
res2, reserr2 = nquad(func2d, [[-3, 3], (-2, 2)])
assert_almost_equal(res, res2)
assert_almost_equal(reserr, reserr2)
def test_matching_tplquad(self):
def func3d(x0, x1, x2, c0, c1):
return x0**2 + c0 * x1**3 - x0 * x1 + 1 + c1 * np.sin(x2)
res = tplquad(func3d, -1, 2, lambda x: -2, lambda x: 2,
lambda x, y: -np.pi, lambda x, y: np.pi,
args=(2, 3))
res2 = nquad(func3d, [[-np.pi, np.pi], [-2, 2], (-1, 2)], args=(2, 3))
assert_almost_equal(res, res2)
def test_dict_as_opts(self):
try:
out = nquad(lambda x, y: x * y, [[0, 1], [0, 1]], opts={'epsrel': 0.0001})
except(TypeError):
assert False
| 11,087 | 33 | 903 |
77de29881c13ccbc8ecdf489f8227ca452346bf3 | 267 | py | Python | Algorithms/DynamicProgramming/count-number-of-ways-to-cover-a-distance.py | Sangeerththan/pythonDSA | d126b3a7a8acc1e202107e20a21ed96fb4ab144e | [
"MIT"
] | 1 | 2021-09-12T20:40:37.000Z | 2021-09-12T20:40:37.000Z | Algorithms/DynamicProgramming/count-number-of-ways-to-cover-a-distance.py | Sangeerththan/pythonDataStructure | d126b3a7a8acc1e202107e20a21ed96fb4ab144e | [
"MIT"
] | null | null | null | Algorithms/DynamicProgramming/count-number-of-ways-to-cover-a-distance.py | Sangeerththan/pythonDataStructure | d126b3a7a8acc1e202107e20a21ed96fb4ab144e | [
"MIT"
] | null | null | null | dist = 4
print(prCountDP(dist))
| 20.538462 | 79 | 0.453184 | def prCountDP(dist):
ways = [0] * 3
n = dist
ways[0] = 1
ways[1] = 1
ways[2] = 2
for i in range(3, n + 1):
ways[i % 3] = ways[(i - 1) % 3] + ways[(i - 2) % 3] + ways[(i - 3) % 3]
return ways[n % 3]
dist = 4
print(prCountDP(dist))
| 213 | 0 | 22 |
06250141bfa3dc205ab66849d321ace72101a1e6 | 2,339 | py | Python | avionics/firmware/monitors/loadcell_analog.py | leozz37/makani | c94d5c2b600b98002f932e80a313a06b9285cc1b | [
"Apache-2.0"
] | 1,178 | 2020-09-10T17:15:42.000Z | 2022-03-31T14:59:35.000Z | avionics/firmware/monitors/loadcell_analog.py | leozz37/makani | c94d5c2b600b98002f932e80a313a06b9285cc1b | [
"Apache-2.0"
] | 1 | 2020-05-22T05:22:35.000Z | 2020-05-22T05:22:35.000Z | avionics/firmware/monitors/loadcell_analog.py | leozz37/makani | c94d5c2b600b98002f932e80a313a06b9285cc1b | [
"Apache-2.0"
] | 107 | 2020-09-10T17:29:30.000Z | 2022-03-18T09:00:14.000Z | # Copyright 2020 Makani Technologies LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Loadcell analog hardware monitor configuration."""
from makani.avionics.firmware.monitors import analog_types
from makani.avionics.firmware.serial import loadcell_serial_params as rev
# Output value = (input - input_offset) / input_divider.
analog_default = {
'name': '',
'channel': -1,
'type': analog_types.kAnalogTypeVoltage,
'input_divider': 1.0,
'input_offset': 0.0,
'nominal': 0.0,
'min': 0.0,
'max': 0.0,
}
voltage = dict(analog_default, type=analog_types.kAnalogTypeVoltage)
logic_high = dict(analog_default, type=analog_types.kAnalogTypeLogicHigh)
v_5v = dict(voltage, nominal=5.0, min=5.0 * 0.95, max=5.0 * 1.05) # [V]
# Allowable current range based on the allowable zero error range over temp of
# +/- 60 mV on the current sensor.
i_batt = dict(voltage, nominal=0.0, min=-0.5, max=0.5) # [A]
v_aoa = dict(voltage, nominal=1.5, min=0.0, max=3.0) # [V]
v_release = dict(voltage, nominal=0.0, min=0.0, max=30.0) # [V]
rev_ab = [
dict(i_batt, name='i_batt', channel=14, input_divider=0.095,
input_offset=0.357),
dict(v_release, name='v_release', channel=15, input_divider=9.31 / 109.31),
dict(v_aoa, name='v_aoa_1', channel=16),
dict(v_aoa, name='v_aoa_2', channel=17),
dict(v_5v, name='5v', channel=19, input_divider=14.3 / 43.0),
dict(v_release, name='v_arm', channel=20, input_divider=9.31 / 109.31),
dict(voltage, name='v_batt_test', channel=21, input_divider=9.31 / 109.31),
dict(logic_high, name='eeprom_wp', channel=23),
]
rev_aa = rev_ab + [
dict(v_5v, name='v_loadcell_bias', channel=18, input_divider=14.3 / 43.0),
]
analog_config = (rev.LoadcellHardware, {
rev.LoadcellHardware.REV_AA: rev_aa,
rev.LoadcellHardware.REV_AB: rev_ab
})
| 37.725806 | 79 | 0.705857 | # Copyright 2020 Makani Technologies LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Loadcell analog hardware monitor configuration."""
from makani.avionics.firmware.monitors import analog_types
from makani.avionics.firmware.serial import loadcell_serial_params as rev
# Output value = (input - input_offset) / input_divider.
analog_default = {
'name': '',
'channel': -1,
'type': analog_types.kAnalogTypeVoltage,
'input_divider': 1.0,
'input_offset': 0.0,
'nominal': 0.0,
'min': 0.0,
'max': 0.0,
}
voltage = dict(analog_default, type=analog_types.kAnalogTypeVoltage)
logic_high = dict(analog_default, type=analog_types.kAnalogTypeLogicHigh)
v_5v = dict(voltage, nominal=5.0, min=5.0 * 0.95, max=5.0 * 1.05) # [V]
# Allowable current range based on the allowable zero error range over temp of
# +/- 60 mV on the current sensor.
i_batt = dict(voltage, nominal=0.0, min=-0.5, max=0.5) # [A]
v_aoa = dict(voltage, nominal=1.5, min=0.0, max=3.0) # [V]
v_release = dict(voltage, nominal=0.0, min=0.0, max=30.0) # [V]
rev_ab = [
dict(i_batt, name='i_batt', channel=14, input_divider=0.095,
input_offset=0.357),
dict(v_release, name='v_release', channel=15, input_divider=9.31 / 109.31),
dict(v_aoa, name='v_aoa_1', channel=16),
dict(v_aoa, name='v_aoa_2', channel=17),
dict(v_5v, name='5v', channel=19, input_divider=14.3 / 43.0),
dict(v_release, name='v_arm', channel=20, input_divider=9.31 / 109.31),
dict(voltage, name='v_batt_test', channel=21, input_divider=9.31 / 109.31),
dict(logic_high, name='eeprom_wp', channel=23),
]
rev_aa = rev_ab + [
dict(v_5v, name='v_loadcell_bias', channel=18, input_divider=14.3 / 43.0),
]
analog_config = (rev.LoadcellHardware, {
rev.LoadcellHardware.REV_AA: rev_aa,
rev.LoadcellHardware.REV_AB: rev_ab
})
| 0 | 0 | 0 |
e71a84183d587e3eb7b1475c43b27c9f9c581b82 | 13,174 | py | Python | pull.py | mlinksva/fsf-api | 4962e961e9ffa63bdd1963ab9ee9ce59194c8c39 | [
"MIT"
] | 5 | 2017-12-29T22:38:33.000Z | 2021-03-10T12:16:38.000Z | pull.py | goneall/fsf-api | 4962e961e9ffa63bdd1963ab9ee9ce59194c8c39 | [
"MIT"
] | 19 | 2017-10-20T20:19:26.000Z | 2021-09-09T07:04:31.000Z | pull.py | goneall/fsf-api | 4962e961e9ffa63bdd1963ab9ee9ce59194c8c39 | [
"MIT"
] | 6 | 2017-10-21T20:49:43.000Z | 2021-09-05T17:52:08.000Z | #!/usr/bin/env python3
#
# SPDX-License-Identifier: MIT
import glob
import itertools
import json
import os
import sys
import urllib.parse
import urllib.request
try:
from lxml import etree
except ImportError:
import xml.etree.ElementTree as etree
URI = 'https://www.gnu.org/licenses/license-list.html'
TAGS = {
'blue': {'viewpoint'},
'green': {'gpl-2-compatible', 'gpl-3-compatible', 'libre'},
'orange': {'libre'},
'purple': {'fdl-compatible', 'libre'},
'red': {'non-free'},
}
SPLITS = {
'AcademicFreeLicense': [ # all versions through 3.0
'AcademicFreeLicense1.1',
'AcademicFreeLicense1.2',
'AcademicFreeLicense2.0',
'AcademicFreeLicense2.1',
'AcademicFreeLicense3.0',
],
'CC-BY-NC': [ # any version (!)
'CC-BY-NC-1.0',
'CC-BY-NC-2.0',
'CC-BY-NC-2.5',
'CC-BY-NC-3.0',
'CC-BY-NC-4.0',
],
'CC-BY-ND': [ # any version
'CC-BY-ND-1.0',
'CC-BY-ND-2.0',
'CC-BY-ND-2.5',
'CC-BY-ND-3.0',
'CC-BY-ND-4.0',
],
'ccbynd': ['CC-BY-ND-4.0'], # unify (multi-tag)
'FDL': [
'FDLv1.1',
'FDLv1.2',
'FDLv1.3',
],
'FDLOther': [ # unify with FDL (multi-tag)
'FDLv1.1',
'FDLv1.2',
'FDLv1.3',
],
'FreeBSDDL': ['FreeBSD'], # unify (multi-tag)
'NPL': [ # versions 1.0 and 1.1
'NPL-1.0',
'NPL-1.1',
],
'OSL': [ # any version through 3.0
'OSL-1.0',
'OSL-1.1',
'OSL-2.0',
'OSL-2.1',
'OSL-3.0',
],
'PythonOld': [ # 1.6b1 through 2.0 and 2.1
'Python1.6b1',
'Python2.0',
'Python2.1',
],
'SILOFL': [ # title has 1.1 but text says the same metadata applies to 1.0
'SILOFL-1.0',
'SILOFL-1.1',
],
'Zope2.0': [ # versions 2.0 and 2.1
'Zope2.0',
'Zope2.1',
],
}
TAG_OVERRIDES = {
'AGPLv3.0': {'libre', 'gpl-3-compatible'},
'ECL2.0': {'libre', 'gpl-3-compatible'},
'freetype': {'libre', 'gpl-3-compatible'},
'GNUGPLv3': {'libre', 'gpl-3-compatible'},
'GPLv2': {'libre', 'gpl-2-compatible'},
'LGPLv3': {'libre', 'gpl-3-compatible'},
}
IDENTIFIERS = {
'AGPLv1.0': {'spdx': ['AGPL-1.0']},
'AGPLv3.0': {'spdx': ['AGPL-3.0-or-later', 'AGPL-3.0-only', 'AGPL-3.0']},
'AcademicFreeLicense1.1': {'spdx': ['AFL-1.1']},
'AcademicFreeLicense1.2': {'spdx': ['AFL-1.2']},
'AcademicFreeLicense2.0': {'spdx': ['AFL-2.0']},
'AcademicFreeLicense2.1': {'spdx': ['AFL-2.1']},
'AcademicFreeLicense3.0': {'spdx': ['AFL-3.0']},
'Aladdin': {'spdx': ['Aladdin']},
'apache1.1': {'spdx': ['Apache-1.1']},
'apache1': {'spdx': ['Apache-1.0']},
'apache2': {'spdx': ['Apache-2.0']},
'apsl1': {'spdx': ['APSL-1.0']},
'apsl2': {'spdx': ['APSL-2.0']},
'ArtisticLicense': {'spdx': ['Artistic-1.0']},
'ArtisticLicense2': {'spdx': ['Artistic-2.0']},
'BerkeleyDB': {'spdx': ['Sleepycat']},
'bittorrent': {'spdx': ['BitTorrent-1.1']},
'boost': {'spdx': ['BSL-1.0']},
'ccby': {'spdx': ['CC-BY-4.0']},
'CC-BY-NC-1.0': {'spdx': ['CC-BY-NC-1.0']},
'CC-BY-NC-2.0': {'spdx': ['CC-BY-NC-2.0']},
'CC-BY-NC-2.5': {'spdx': ['CC-BY-NC-2.5']},
'CC-BY-NC-3.0': {'spdx': ['CC-BY-NC-3.0']},
'CC-BY-NC-4.0': {'spdx': ['CC-BY-NC-4.0']},
'CC-BY-ND-1.0': {'spdx': ['CC-BY-ND-1.0']},
'CC-BY-ND-2.0': {'spdx': ['CC-BY-ND-2.0']},
'CC-BY-ND-2.5': {'spdx': ['CC-BY-ND-2.5']},
'CC-BY-ND-3.0': {'spdx': ['CC-BY-ND-3.0']},
'CC-BY-ND-4.0': {'spdx': ['CC-BY-ND-4.0']},
'ccbysa': {'spdx': ['CC-BY-SA-4.0']},
'CC0': {'spdx': ['CC0-1.0']},
'CDDL': {'spdx': ['CDDL-1.0']},
'CPAL': {'spdx': ['CPAL-1.0']},
'CeCILL': {'spdx': ['CECILL-2.0']},
'CeCILL-B': {'spdx': ['CECILL-B']},
'CeCILL-C': {'spdx': ['CECILL-C']},
'ClarifiedArtistic': {'spdx': ['ClArtistic']},
'clearbsd': {'spdx': ['BSD-3-Clause-Clear']},
'CommonPublicLicense10': {'spdx': ['CPL-1.0']},
'cpol': {'spdx': ['CPOL-1.02']},
'Condor': {'spdx': ['Condor-1.1']},
'ECL2.0': {'spdx': ['ECL-2.0']},
'eCos11': {'spdx': ['RHeCos-1.1']},
'eCos2.0': {'spdx': ['GPL-2.0+ WITH eCos-exception-2.0', 'eCos-2.0']},
'EPL': {'spdx': ['EPL-1.0']},
'EPL2': {'spdx': ['EPL-2.0']},
'EUDataGrid': {'spdx': ['EUDatagrid']},
'EUPL-1.1': {'spdx': ['EUPL-1.1']},
'EUPL-1.2': {'spdx': ['EUPL-1.2']},
'Eiffel': {'spdx': ['EFL-2.0']},
'Expat': {'spdx': ['MIT']},
'FDLv1.1': {'spdx': ['GFDL-1.1-or-later', 'GFDL-1.1-only', 'GFDL-1.1']},
'FDLv1.2': {'spdx': ['GFDL-1.2-or-later', 'GFDL-1.2-only', 'GFDL-1.2']},
'FDLv1.3': {'spdx': ['GFDL-1.3-or-later', 'GFDL-1.3-only', 'GFDL-1.3']},
'FreeBSD': {'spdx': ['BSD-2-Clause-FreeBSD']},
'freetype': {'spdx': ['FTL']},
'GNUAllPermissive': {'spdx': ['FSFAP']},
'GNUGPLv3': {'spdx': ['GPL-3.0-or-later', 'GPL-3.0-only', 'GPL-3.0', 'GPL-3.0+']},
'gnuplot': {'spdx': ['gnuplot']},
'GPLv2': {'spdx': ['GPL-2.0-or-later', 'GPL-2.0-only', 'GPL-2.0', 'GPL-2.0+']},
'HPND': {'spdx': ['HPND']},
'IBMPL': {'spdx': ['IPL-1.0']},
'iMatix': {'spdx': ['iMatix']},
'imlib': {'spdx': ['Imlib2']},
'ijg': {'spdx': ['IJG']},
'intel': {'spdx': ['Intel']},
'IPAFONT': {'spdx': ['IPA']},
'ISC': {'spdx': ['ISC']},
'JSON': {'spdx': ['JSON']},
'LGPLv3': {'spdx': ['LGPL-3.0-or-later', 'LGPL-3.0-only', 'LGPL-3.0', 'LGPL-3.0+']},
'LGPLv2.1': {'spdx': ['LGPL-2.1-or-later', 'LGPL-2.1-only', 'LGPL-2.1', 'LGPL-2.1+']},
'LPPL-1.2': {'spdx': ['LPPL-1.2']},
'LPPL-1.3a': {'spdx': ['LPPL-1.3a']},
'lucent102': {'spdx': ['LPL-1.02']},
'ModifiedBSD': {'spdx': ['BSD-3-Clause']},
'MPL': {'spdx': ['MPL-1.1']},
'MPL-2.0': {'spdx': ['MPL-2.0']},
'ms-pl': {'spdx': ['MS-PL']},
'ms-rl': {'spdx': ['MS-RL']},
'NASA': {'spdx': ['NASA-1.3']},
'NCSA': {'spdx': ['NCSA']},
'newOpenLDAP': {'spdx': ['OLDAP-2.7']},
'Nokia': {'spdx': ['Nokia']},
'NoLicense': {'spdx': ['NONE']},
'NOSL': {'spdx': ['NOSL']},
'NPL-1.0': {'spdx': ['NPL-1.0']},
'NPL-1.1': {'spdx': ['NPL-1.1']},
'ODbl': {'spdx': ['ODbL-1.0']},
'oldOpenLDAP': {'spdx': ['OLDAP-2.3']},
'OpenPublicL': {'spdx': ['OPL-1.0']},
'OpenSSL': {'spdx': ['OpenSSL']},
'OriginalBSD': {'spdx': ['BSD-4-Clause']},
'OSL-1.0': {'spdx': ['OSL-1.0']},
'OSL-1.1': {'spdx': ['OSL-1.1']},
'OSL-2.0': {'spdx': ['OSL-2.0']},
'OSL-2.1': {'spdx': ['OSL-2.1']},
'OSL-3.0': {'spdx': ['OSL-3.0']},
'PHP-3.01': {'spdx': ['PHP-3.01']},
'Python2.0': {'spdx': ['Python-2.0']},
'QPL': {'spdx': ['QPL-1.0']},
'RPSL': {'spdx': ['RPSL-1.0']},
'Ruby': {'spdx': ['Ruby']},
'SGIFreeB': {'spdx': ['SGI-B-2.0']},
'SILOFL-1.0': {'spdx': ['OFL-1.0']},
'SILOFL-1.1': {'spdx': ['OFL-1.1']},
'SPL': {'spdx': ['SPL-1.0']},
'StandardMLofNJ': {'spdx': ['SMLNJ', 'StandardML-NJ']},
'Unlicense': {'spdx': ['Unlicense']},
'UPL': {'spdx': ['UPL-1.0']},
'Vim': {'spdx': ['Vim']},
'W3C': {'spdx': ['W3C']},
'Watcom': {'spdx': ['Watcom-1.0']},
'WTFPL': {'spdx': ['WTFPL']},
'X11License': {'spdx': ['X11']},
'XFree861.1License': {'spdx': ['XFree86-1.1']},
'xinetd': {'spdx': ['xinetd']},
'Yahoo': {'spdx': ['YPL-1.1']},
'Zend': {'spdx': ['Zend-2.0']},
'Zimbra': {'spdx': ['Zimbra-1.3']},
'ZLib': {'spdx': ['Zlib', 'Nunit']},
'Zope2.0': {'spdx': ['ZPL-2.0']},
'Zope2.1': {'spdx': ['ZPL-2.1']},
}
if __name__ == '__main__':
dir = os.curdir
if len(sys.argv) > 1:
dir = sys.argv[1]
tree = get(uri=URI)
root = tree.getroot()
licenses = extract(root=root, base_uri=URI)
unused_identifiers = {
key for key in IDENTIFIERS.keys() if key not in licenses}
if unused_identifiers:
raise ValueError('unused IDENTIFIERS keys: {}'.format(
', '.join(sorted(unused_identifiers))))
save(licenses=licenses, base_uri='https://wking.github.io/fsf-api/', dir=dir)
| 35.509434 | 90 | 0.493092 | #!/usr/bin/env python3
#
# SPDX-License-Identifier: MIT
import glob
import itertools
import json
import os
import sys
import urllib.parse
import urllib.request
try:
from lxml import etree
except ImportError:
import xml.etree.ElementTree as etree
URI = 'https://www.gnu.org/licenses/license-list.html'
TAGS = {
'blue': {'viewpoint'},
'green': {'gpl-2-compatible', 'gpl-3-compatible', 'libre'},
'orange': {'libre'},
'purple': {'fdl-compatible', 'libre'},
'red': {'non-free'},
}
SPLITS = {
'AcademicFreeLicense': [ # all versions through 3.0
'AcademicFreeLicense1.1',
'AcademicFreeLicense1.2',
'AcademicFreeLicense2.0',
'AcademicFreeLicense2.1',
'AcademicFreeLicense3.0',
],
'CC-BY-NC': [ # any version (!)
'CC-BY-NC-1.0',
'CC-BY-NC-2.0',
'CC-BY-NC-2.5',
'CC-BY-NC-3.0',
'CC-BY-NC-4.0',
],
'CC-BY-ND': [ # any version
'CC-BY-ND-1.0',
'CC-BY-ND-2.0',
'CC-BY-ND-2.5',
'CC-BY-ND-3.0',
'CC-BY-ND-4.0',
],
'ccbynd': ['CC-BY-ND-4.0'], # unify (multi-tag)
'FDL': [
'FDLv1.1',
'FDLv1.2',
'FDLv1.3',
],
'FDLOther': [ # unify with FDL (multi-tag)
'FDLv1.1',
'FDLv1.2',
'FDLv1.3',
],
'FreeBSDDL': ['FreeBSD'], # unify (multi-tag)
'NPL': [ # versions 1.0 and 1.1
'NPL-1.0',
'NPL-1.1',
],
'OSL': [ # any version through 3.0
'OSL-1.0',
'OSL-1.1',
'OSL-2.0',
'OSL-2.1',
'OSL-3.0',
],
'PythonOld': [ # 1.6b1 through 2.0 and 2.1
'Python1.6b1',
'Python2.0',
'Python2.1',
],
'SILOFL': [ # title has 1.1 but text says the same metadata applies to 1.0
'SILOFL-1.0',
'SILOFL-1.1',
],
'Zope2.0': [ # versions 2.0 and 2.1
'Zope2.0',
'Zope2.1',
],
}
TAG_OVERRIDES = {
'AGPLv3.0': {'libre', 'gpl-3-compatible'},
'ECL2.0': {'libre', 'gpl-3-compatible'},
'freetype': {'libre', 'gpl-3-compatible'},
'GNUGPLv3': {'libre', 'gpl-3-compatible'},
'GPLv2': {'libre', 'gpl-2-compatible'},
'LGPLv3': {'libre', 'gpl-3-compatible'},
}
IDENTIFIERS = {
'AGPLv1.0': {'spdx': ['AGPL-1.0']},
'AGPLv3.0': {'spdx': ['AGPL-3.0-or-later', 'AGPL-3.0-only', 'AGPL-3.0']},
'AcademicFreeLicense1.1': {'spdx': ['AFL-1.1']},
'AcademicFreeLicense1.2': {'spdx': ['AFL-1.2']},
'AcademicFreeLicense2.0': {'spdx': ['AFL-2.0']},
'AcademicFreeLicense2.1': {'spdx': ['AFL-2.1']},
'AcademicFreeLicense3.0': {'spdx': ['AFL-3.0']},
'Aladdin': {'spdx': ['Aladdin']},
'apache1.1': {'spdx': ['Apache-1.1']},
'apache1': {'spdx': ['Apache-1.0']},
'apache2': {'spdx': ['Apache-2.0']},
'apsl1': {'spdx': ['APSL-1.0']},
'apsl2': {'spdx': ['APSL-2.0']},
'ArtisticLicense': {'spdx': ['Artistic-1.0']},
'ArtisticLicense2': {'spdx': ['Artistic-2.0']},
'BerkeleyDB': {'spdx': ['Sleepycat']},
'bittorrent': {'spdx': ['BitTorrent-1.1']},
'boost': {'spdx': ['BSL-1.0']},
'ccby': {'spdx': ['CC-BY-4.0']},
'CC-BY-NC-1.0': {'spdx': ['CC-BY-NC-1.0']},
'CC-BY-NC-2.0': {'spdx': ['CC-BY-NC-2.0']},
'CC-BY-NC-2.5': {'spdx': ['CC-BY-NC-2.5']},
'CC-BY-NC-3.0': {'spdx': ['CC-BY-NC-3.0']},
'CC-BY-NC-4.0': {'spdx': ['CC-BY-NC-4.0']},
'CC-BY-ND-1.0': {'spdx': ['CC-BY-ND-1.0']},
'CC-BY-ND-2.0': {'spdx': ['CC-BY-ND-2.0']},
'CC-BY-ND-2.5': {'spdx': ['CC-BY-ND-2.5']},
'CC-BY-ND-3.0': {'spdx': ['CC-BY-ND-3.0']},
'CC-BY-ND-4.0': {'spdx': ['CC-BY-ND-4.0']},
'ccbysa': {'spdx': ['CC-BY-SA-4.0']},
'CC0': {'spdx': ['CC0-1.0']},
'CDDL': {'spdx': ['CDDL-1.0']},
'CPAL': {'spdx': ['CPAL-1.0']},
'CeCILL': {'spdx': ['CECILL-2.0']},
'CeCILL-B': {'spdx': ['CECILL-B']},
'CeCILL-C': {'spdx': ['CECILL-C']},
'ClarifiedArtistic': {'spdx': ['ClArtistic']},
'clearbsd': {'spdx': ['BSD-3-Clause-Clear']},
'CommonPublicLicense10': {'spdx': ['CPL-1.0']},
'cpol': {'spdx': ['CPOL-1.02']},
'Condor': {'spdx': ['Condor-1.1']},
'ECL2.0': {'spdx': ['ECL-2.0']},
'eCos11': {'spdx': ['RHeCos-1.1']},
'eCos2.0': {'spdx': ['GPL-2.0+ WITH eCos-exception-2.0', 'eCos-2.0']},
'EPL': {'spdx': ['EPL-1.0']},
'EPL2': {'spdx': ['EPL-2.0']},
'EUDataGrid': {'spdx': ['EUDatagrid']},
'EUPL-1.1': {'spdx': ['EUPL-1.1']},
'EUPL-1.2': {'spdx': ['EUPL-1.2']},
'Eiffel': {'spdx': ['EFL-2.0']},
'Expat': {'spdx': ['MIT']},
'FDLv1.1': {'spdx': ['GFDL-1.1-or-later', 'GFDL-1.1-only', 'GFDL-1.1']},
'FDLv1.2': {'spdx': ['GFDL-1.2-or-later', 'GFDL-1.2-only', 'GFDL-1.2']},
'FDLv1.3': {'spdx': ['GFDL-1.3-or-later', 'GFDL-1.3-only', 'GFDL-1.3']},
'FreeBSD': {'spdx': ['BSD-2-Clause-FreeBSD']},
'freetype': {'spdx': ['FTL']},
'GNUAllPermissive': {'spdx': ['FSFAP']},
'GNUGPLv3': {'spdx': ['GPL-3.0-or-later', 'GPL-3.0-only', 'GPL-3.0', 'GPL-3.0+']},
'gnuplot': {'spdx': ['gnuplot']},
'GPLv2': {'spdx': ['GPL-2.0-or-later', 'GPL-2.0-only', 'GPL-2.0', 'GPL-2.0+']},
'HPND': {'spdx': ['HPND']},
'IBMPL': {'spdx': ['IPL-1.0']},
'iMatix': {'spdx': ['iMatix']},
'imlib': {'spdx': ['Imlib2']},
'ijg': {'spdx': ['IJG']},
'intel': {'spdx': ['Intel']},
'IPAFONT': {'spdx': ['IPA']},
'ISC': {'spdx': ['ISC']},
'JSON': {'spdx': ['JSON']},
'LGPLv3': {'spdx': ['LGPL-3.0-or-later', 'LGPL-3.0-only', 'LGPL-3.0', 'LGPL-3.0+']},
'LGPLv2.1': {'spdx': ['LGPL-2.1-or-later', 'LGPL-2.1-only', 'LGPL-2.1', 'LGPL-2.1+']},
'LPPL-1.2': {'spdx': ['LPPL-1.2']},
'LPPL-1.3a': {'spdx': ['LPPL-1.3a']},
'lucent102': {'spdx': ['LPL-1.02']},
'ModifiedBSD': {'spdx': ['BSD-3-Clause']},
'MPL': {'spdx': ['MPL-1.1']},
'MPL-2.0': {'spdx': ['MPL-2.0']},
'ms-pl': {'spdx': ['MS-PL']},
'ms-rl': {'spdx': ['MS-RL']},
'NASA': {'spdx': ['NASA-1.3']},
'NCSA': {'spdx': ['NCSA']},
'newOpenLDAP': {'spdx': ['OLDAP-2.7']},
'Nokia': {'spdx': ['Nokia']},
'NoLicense': {'spdx': ['NONE']},
'NOSL': {'spdx': ['NOSL']},
'NPL-1.0': {'spdx': ['NPL-1.0']},
'NPL-1.1': {'spdx': ['NPL-1.1']},
'ODbl': {'spdx': ['ODbL-1.0']},
'oldOpenLDAP': {'spdx': ['OLDAP-2.3']},
'OpenPublicL': {'spdx': ['OPL-1.0']},
'OpenSSL': {'spdx': ['OpenSSL']},
'OriginalBSD': {'spdx': ['BSD-4-Clause']},
'OSL-1.0': {'spdx': ['OSL-1.0']},
'OSL-1.1': {'spdx': ['OSL-1.1']},
'OSL-2.0': {'spdx': ['OSL-2.0']},
'OSL-2.1': {'spdx': ['OSL-2.1']},
'OSL-3.0': {'spdx': ['OSL-3.0']},
'PHP-3.01': {'spdx': ['PHP-3.01']},
'Python2.0': {'spdx': ['Python-2.0']},
'QPL': {'spdx': ['QPL-1.0']},
'RPSL': {'spdx': ['RPSL-1.0']},
'Ruby': {'spdx': ['Ruby']},
'SGIFreeB': {'spdx': ['SGI-B-2.0']},
'SILOFL-1.0': {'spdx': ['OFL-1.0']},
'SILOFL-1.1': {'spdx': ['OFL-1.1']},
'SPL': {'spdx': ['SPL-1.0']},
'StandardMLofNJ': {'spdx': ['SMLNJ', 'StandardML-NJ']},
'Unlicense': {'spdx': ['Unlicense']},
'UPL': {'spdx': ['UPL-1.0']},
'Vim': {'spdx': ['Vim']},
'W3C': {'spdx': ['W3C']},
'Watcom': {'spdx': ['Watcom-1.0']},
'WTFPL': {'spdx': ['WTFPL']},
'X11License': {'spdx': ['X11']},
'XFree861.1License': {'spdx': ['XFree86-1.1']},
'xinetd': {'spdx': ['xinetd']},
'Yahoo': {'spdx': ['YPL-1.1']},
'Zend': {'spdx': ['Zend-2.0']},
'Zimbra': {'spdx': ['Zimbra-1.3']},
'ZLib': {'spdx': ['Zlib', 'Nunit']},
'Zope2.0': {'spdx': ['ZPL-2.0']},
'Zope2.1': {'spdx': ['ZPL-2.1']},
}
def get(uri):
parser = etree.XMLParser(ns_clean=True, resolve_entities=False)
with urllib.request.urlopen(uri) as response:
return etree.parse(response, base_url=uri, parser=parser)
def extract(root, base_uri=None):
oids = set()
licenses = {}
for dl in root.iter(tag='{http://www.w3.org/1999/xhtml}dl'):
try:
tags = TAGS[dl.attrib.get('class')]
except KeyError:
raise ValueError(
'unrecognized class {!r}'.format(dl.attrib.get('class')))
for a in dl.iter(tag='{http://www.w3.org/1999/xhtml}a'):
if 'id' not in a.attrib:
continue
oid = a.attrib['id']
oids.add(oid)
for id in SPLITS.get(oid, [oid]):
license = {
'tags': TAG_OVERRIDES.get(id, tags).copy(),
}
if a.text and a.text.strip():
license['name'] = a.text.strip()
else:
continue
uris = ['{}#{}'.format(base_uri, oid)]
uri = a.attrib.get('href')
if uri:
if base_uri:
uris.append(urllib.parse.urljoin(base=base_uri, url=uri))
license['uris'] = uris
identifiers = IDENTIFIERS.get(id)
if identifiers:
license['identifiers'] = identifiers
if id not in licenses:
licenses[id] = license
else:
licenses[id]['tags'].update(tags)
for uri in uris:
if uri not in licenses[id]['uris']:
licenses[id]['uris'].append(uri)
unused_splits = set(SPLITS.keys()).difference(oids)
if unused_splits:
raise ValueError('unused SPLITS keys: {}'.format(
', '.join(sorted(unused_splits))))
return licenses
def save(licenses, base_uri, dir=os.curdir):
schema_dir = os.path.join(dir, 'schema')
os.makedirs(schema_dir, exist_ok=True)
if sys.version_info >= (3, 5):
paths = glob.glob(os.path.join(dir, '**', '*.json'), recursive=True)
else:
paths = itertools.chain(
glob.glob(os.path.join(dir, '*.json')),
glob.glob(os.path.join(dir, '*', '*.json')),
)
for path in paths:
os.remove(path)
license_schema = {
'@context': {
'schema': 'https://schema.org/',
'id': {
'@id': 'schema:identifier'
},
'name': {
'@id': 'schema:name',
},
'uris': {
'@container': '@list',
'@id': 'schema:url',
},
'tags': {
'@id': 'schema:keywords',
},
'identifiers': {
'@container': '@index',
'@id': 'schema:identifier',
},
},
}
with open(os.path.join(schema_dir, 'license.jsonld'), 'w') as f:
json.dump(obj=license_schema, fp=f, indent=2, sort_keys=True)
f.write('\n')
license_schema_uri = urllib.parse.urljoin(
base=base_uri, url='schema/license.jsonld')
licenses_schema = license_schema.copy()
licenses_schema['@context']['licenses'] = {
'@container': '@index',
'@id': license_schema_uri,
}
licenses_schema.update(license_schema)
with open(os.path.join(schema_dir, 'licenses.jsonld'), 'w') as f:
json.dump(obj=licenses_schema, fp=f, indent=2, sort_keys=True)
f.write('\n')
licenses_schema_uri = urllib.parse.urljoin(
base=base_uri, url='schema/licenses.jsonld')
index = sorted(licenses.keys())
with open(os.path.join(dir, 'licenses.json'), 'w') as f:
json.dump(obj=index, fp=f, indent=2, sort_keys=True)
f.write('\n')
full_index = {
'@context': licenses_schema_uri,
'licenses': {},
}
for id, license in licenses.items():
license = license.copy()
if 'tags' in license:
license['tags'] = sorted(license['tags'])
license['id'] = id
full_index['licenses'][id] = license.copy()
license['@context'] = urllib.parse.urljoin(
base=base_uri, url='schema/license.jsonld')
license_path = os.path.join(dir, '{}.json'.format(id))
with open(license_path, 'w') as f:
json.dump(obj=license, fp=f, indent=2, sort_keys=True)
f.write('\n')
for scheme, identifiers in license.get('identifiers', {}).items():
scheme_dir = os.path.join(dir, scheme)
os.makedirs(scheme_dir, exist_ok=True)
if isinstance(identifiers, str):
identifiers = [identifiers]
for identifier in identifiers:
id_path = os.path.join(scheme_dir, '{}.json'.format(identifier))
os.link(license_path, id_path)
with open(os.path.join(dir, 'licenses-full.json'), 'w') as f:
json.dump(obj=full_index, fp=f, indent=2, sort_keys=True)
f.write('\n')
if __name__ == '__main__':
dir = os.curdir
if len(sys.argv) > 1:
dir = sys.argv[1]
tree = get(uri=URI)
root = tree.getroot()
licenses = extract(root=root, base_uri=URI)
unused_identifiers = {
key for key in IDENTIFIERS.keys() if key not in licenses}
if unused_identifiers:
raise ValueError('unused IDENTIFIERS keys: {}'.format(
', '.join(sorted(unused_identifiers))))
save(licenses=licenses, base_uri='https://wking.github.io/fsf-api/', dir=dir)
| 5,053 | 0 | 69 |
5a0ebe855d94d3df5fe0a486265b362c329095a7 | 5,935 | py | Python | tests/api/common/experimental/test_delete_dag.py | rfrenoy/incubator-airflow | 33d604b9f3a006f27579a233563280a0893fefbd | [
"Apache-2.0"
] | null | null | null | tests/api/common/experimental/test_delete_dag.py | rfrenoy/incubator-airflow | 33d604b9f3a006f27579a233563280a0893fefbd | [
"Apache-2.0"
] | null | null | null | tests/api/common/experimental/test_delete_dag.py | rfrenoy/incubator-airflow | 33d604b9f3a006f27579a233563280a0893fefbd | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import unittest
from airflow.orm import DagBag
from airflow import models
from airflow import settings
from airflow.api.common.experimental.delete_dag import delete_dag
from airflow.exceptions import DagNotFound, DagFileExists
from airflow.operators.dummy_operator import DummyOperator
from airflow.utils.dates import days_ago
from airflow.utils.state import State
DM = models.DagModel
DS = models.DagStat
DR = models.DagRun
TI = models.TaskInstance
LOG = models.Log
if __name__ == '__main__':
unittest.main()
| 41.503497 | 101 | 0.663858 | # -*- coding: utf-8 -*-
#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
import unittest
from airflow.orm import DagBag
from airflow import models
from airflow import settings
from airflow.api.common.experimental.delete_dag import delete_dag
from airflow.exceptions import DagNotFound, DagFileExists
from airflow.operators.dummy_operator import DummyOperator
from airflow.utils.dates import days_ago
from airflow.utils.state import State
DM = models.DagModel
DS = models.DagStat
DR = models.DagRun
TI = models.TaskInstance
LOG = models.Log
class TestDeleteDAGCatchError(unittest.TestCase):
def setUp(self):
self.session = settings.Session()
self.dagbag = DagBag(include_examples=True)
self.dag_id = 'example_bash_operator'
self.dag = self.dagbag.dags[self.dag_id]
def tearDown(self):
self.dag.clear()
self.session.close()
def test_delete_dag_non_existent_dag(self):
with self.assertRaises(DagNotFound):
delete_dag("non-existent DAG")
def test_delete_dag_dag_still_in_dagbag(self):
models_to_check = ['DagModel', 'DagStat', 'DagRun', 'TaskInstance']
record_counts = {}
for model_name in models_to_check:
m = getattr(models, model_name)
record_counts[model_name] = self.session.query(m).filter(m.dag_id == self.dag_id).count()
with self.assertRaises(DagFileExists):
delete_dag(self.dag_id)
# No change should happen in DB
for model_name in models_to_check:
m = getattr(models, model_name)
self.assertEqual(
self.session.query(m).filter(
m.dag_id == self.dag_id
).count(),
record_counts[model_name]
)
class TestDeleteDAGSuccessfulDelete(unittest.TestCase):
def setUp(self):
self.session = settings.Session()
self.key = "test_dag_id"
task = DummyOperator(task_id='dummy',
dag=models.DAG(dag_id=self.key,
default_args={'start_date': days_ago(2)}),
owner='airflow')
self.session.add(DM(dag_id=self.key))
self.session.add(DS(dag_id=self.key, state=State.SUCCESS))
self.session.add(DR(dag_id=self.key))
self.session.add(TI(task=task,
execution_date=days_ago(1),
state=State.SUCCESS))
self.session.add(LOG(dag_id=self.key, task_id=None, task_instance=None,
execution_date=days_ago(1), event="varimport"))
self.session.commit()
def tearDown(self):
self.session.query(DM).filter(DM.dag_id == self.key).delete()
self.session.query(DS).filter(DS.dag_id == self.key).delete()
self.session.query(DR).filter(DR.dag_id == self.key).delete()
self.session.query(TI).filter(TI.dag_id == self.key).delete()
self.session.query(LOG).filter(LOG.dag_id == self.key).delete()
self.session.commit()
self.session.close()
def test_delete_dag_successful_delete(self):
self.assertEqual(self.session.query(DM).filter(DM.dag_id == self.key).count(), 1)
self.assertEqual(self.session.query(DS).filter(DS.dag_id == self.key).count(), 1)
self.assertEqual(self.session.query(DR).filter(DR.dag_id == self.key).count(), 1)
self.assertEqual(self.session.query(TI).filter(TI.dag_id == self.key).count(), 1)
self.assertEqual(self.session.query(LOG).filter(LOG.dag_id == self.key).count(), 1)
delete_dag(dag_id=self.key)
self.assertEqual(self.session.query(DM).filter(DM.dag_id == self.key).count(), 0)
self.assertEqual(self.session.query(DS).filter(DS.dag_id == self.key).count(), 0)
self.assertEqual(self.session.query(DR).filter(DR.dag_id == self.key).count(), 0)
self.assertEqual(self.session.query(TI).filter(TI.dag_id == self.key).count(), 0)
self.assertEqual(self.session.query(LOG).filter(LOG.dag_id == self.key).count(), 1)
def test_delete_dag_successful_delete_not_keeping_records_in_log(self):
self.assertEqual(self.session.query(DM).filter(DM.dag_id == self.key).count(), 1)
self.assertEqual(self.session.query(DS).filter(DS.dag_id == self.key).count(), 1)
self.assertEqual(self.session.query(DR).filter(DR.dag_id == self.key).count(), 1)
self.assertEqual(self.session.query(TI).filter(TI.dag_id == self.key).count(), 1)
self.assertEqual(self.session.query(LOG).filter(LOG.dag_id == self.key).count(), 1)
delete_dag(dag_id=self.key, keep_records_in_log=False)
self.assertEqual(self.session.query(DM).filter(DM.dag_id == self.key).count(), 0)
self.assertEqual(self.session.query(DS).filter(DS.dag_id == self.key).count(), 0)
self.assertEqual(self.session.query(DR).filter(DR.dag_id == self.key).count(), 0)
self.assertEqual(self.session.query(TI).filter(TI.dag_id == self.key).count(), 0)
self.assertEqual(self.session.query(LOG).filter(LOG.dag_id == self.key).count(), 0)
if __name__ == '__main__':
unittest.main()
| 4,279 | 62 | 262 |
bf7207da2c2ecc135b865d2cf21bf5b324883b0d | 16,409 | py | Python | static2/ida/remoteobj.py | pAplakidis/qira | 9d0aa4f887e9dce8c0307a54c7051755ede26810 | [
"MIT"
] | null | null | null | static2/ida/remoteobj.py | pAplakidis/qira | 9d0aa4f887e9dce8c0307a54c7051755ede26810 | [
"MIT"
] | null | null | null | static2/ida/remoteobj.py | pAplakidis/qira | 9d0aa4f887e9dce8c0307a54c7051755ede26810 | [
"MIT"
] | 1 | 2020-12-02T16:32:17.000Z | 2020-12-02T16:32:17.000Z | #!/usr/bin/env python
# remoteobj v0.4, best yet!
# TODO: This will get wrecked by recursive sets/lists/dicts; need a more picklish method.
# TODO: Dict/sets/lists should get unpacked to wrappers that are local for read-only access,
# but update the remote for write access. Note that __eq__ will be an interesting override.
import marshal
import struct
import socket
import sys, exceptions, errno, traceback
from types import CodeType, FunctionType
from os import urandom
from hashlib import sha1
DEBUG = False
class Proxy(object):
# GC isn't useful anyway...
"""
def __del__(self):
if object.__getattribute__(self, '_proxyparent') is not None: return
if not marshal or not struct or not socket: return # Reduce spurious messages when quitting python
object.__getattribute__(self, '_proxyconn').delete(self)
"""
# hash and repr need to be handled specially, due to hash(type) != type.__hash__()
# (and the same for repr). Incidentally, we'll cache the hash.
# Special methods don't always go through __getattribute__, so redirect them all there.
for special in ('__str__', '__lt__', '__le__', '__eq__', '__ne__', '__gt__', '__ge__', '__cmp__', '__rcmp__', '__nonzero__', '__unicode__', '__len__', '__getitem__', '__setitem__', '__delitem__', '__iter__', '__reversed__', '__contains__', '__getslice__', '__setslice__', '__delslice__', '__add__', '__sub__', '__mul__', '__floordiv__', '__mod__', '__divmod__', '__pow__', '__lshift__', '__rshift__', '__and__', '__xor__', '__or__', '__div__', '__truediv__', '__radd__', '__rsub__', '__rmul__', '__rdiv__', '__rtruediv__', '__rfloordiv__', '__rmod__', '__rdivmod__', '__rpow__', '__rlshift__', '__rrshift__', '__rand__', '__rxor__', '__ror__', '__iadd__', '__isub__', '__imul__', '__idiv__', '__itruediv__', '__ifloordiv__', '__imod__', '__ipow__', '__ilshift__', '__irshift__', '__iand__', '__ixor__', '__ior__', '__neg__', '__pos__', '__abs__', '__invert__', '__complex__', '__int__', '__long__', '__float__', '__oct__', '__hex__', '__index__', '__coerce__', '__enter__', '__exit__'):
exec "def {special}(self, *args, **kwargs):\n\treturn object.__getattribute__(self, '_proxyconn').callattr(self, '{special}', args, kwargs)".format(special=special) in None, None
# Note: must send after non-info_only packing, or objects will be left with +1 retain count in self.vended
# Define a function on the remote side. Its __globals__ will be
# the local client-side func.__globals__ filtered to the keys in
# func_globals, underlaid with the remote server-side globals()
# filtered to the keys in remote_globals. None is a special value
# for the filters, and disables any filtering.
__all__ = [Connection,]
# For demo purposes.
if __name__ == "__main__":
from sys import argv
if len(argv) <= 3:
print >> sys.stderr, "Usage:", argv[0], "server <address> <port> [<password>]"
print >> sys.stderr, " python -i", argv[0], "client <address> <port> [<password>]"
print >> sys.stderr, "In the client python shell, the server's module is available as 'proxy'"
print >> sys.stderr, "A good demo is `proxy.__builtins__.__import__('ctypes').memset(0,0,1)`"
exit(64)
hostport = (argv[2], int(argv[3]))
password = argv[4] if len(argv) > 4 else 'lol, python'
if argv[1] == 'server':
import SocketServer
SocketServer.TCPServer.allow_reuse_address = True
SocketServer.TCPServer(hostport, Server).serve_forever()
exit(1)
elif argv[1] == 'client':
connection = Connection(socket.create_connection(hostport), password)
proxy = connection.connectProxy()
print >> sys.stderr, "`proxy` and `connection` are available for you to play with at the interactive prompt."
else:
exit(64)
| 42.510363 | 988 | 0.65781 | #!/usr/bin/env python
# remoteobj v0.4, best yet!
# TODO: This will get wrecked by recursive sets/lists/dicts; need a more picklish method.
# TODO: Dict/sets/lists should get unpacked to wrappers that are local for read-only access,
# but update the remote for write access. Note that __eq__ will be an interesting override.
import marshal
import struct
import socket
import sys, exceptions, errno, traceback
from types import CodeType, FunctionType
from os import urandom
from hashlib import sha1
DEBUG = False
class Proxy(object):
def __init__(self, conn, info, _hash=None, parent=None):
object.__setattr__(self, '_proxyconn', conn)
object.__setattr__(self, '_proxyinfo', info)
object.__setattr__(self, '_proxyparent', parent)
def __getattribute__(self, attr):
t = object.__getattribute__(self, '_proxyinfo').getattr(attr)
if t:
# We need to retain parent for garbage collection purposes.
return Proxy(object.__getattribute__(self, '_proxyconn'), t, parent=self)
else:
return object.__getattribute__(self, '_proxyconn').get(self, attr)
def __getattr__(self, attr):
return object.__getattribute__(self, '__getattribute__')(attr)
def __setattr__(self, attr, val):
object.__getattribute__(self, '_proxyconn').set(self, attr, val)
def __delattr__(self, attr):
object.__getattribute__(self, '_proxyconn').callattr(self, '__delattr__', (attr,), {})
def __call__(self, *args, **kwargs):
return object.__getattribute__(self, '_proxyconn').call(self, args, kwargs)
# GC isn't useful anyway...
"""
def __del__(self):
if object.__getattribute__(self, '_proxyparent') is not None: return
if not marshal or not struct or not socket: return # Reduce spurious messages when quitting python
object.__getattribute__(self, '_proxyconn').delete(self)
"""
# hash and repr need to be handled specially, due to hash(type) != type.__hash__()
# (and the same for repr). Incidentally, we'll cache the hash.
def __hash__(self):
info = object.__getattribute__(self, '_proxyinfo')
if info.proxyhash is None:
info.proxyhash = object.__getattribute__(self, '_proxyconn').hash(self)
return info.proxyhash
def __repr__(self):
return object.__getattribute__(self, '_proxyconn').repr(self)
# Special methods don't always go through __getattribute__, so redirect them all there.
for special in ('__str__', '__lt__', '__le__', '__eq__', '__ne__', '__gt__', '__ge__', '__cmp__', '__rcmp__', '__nonzero__', '__unicode__', '__len__', '__getitem__', '__setitem__', '__delitem__', '__iter__', '__reversed__', '__contains__', '__getslice__', '__setslice__', '__delslice__', '__add__', '__sub__', '__mul__', '__floordiv__', '__mod__', '__divmod__', '__pow__', '__lshift__', '__rshift__', '__and__', '__xor__', '__or__', '__div__', '__truediv__', '__radd__', '__rsub__', '__rmul__', '__rdiv__', '__rtruediv__', '__rfloordiv__', '__rmod__', '__rdivmod__', '__rpow__', '__rlshift__', '__rrshift__', '__rand__', '__rxor__', '__ror__', '__iadd__', '__isub__', '__imul__', '__idiv__', '__itruediv__', '__ifloordiv__', '__imod__', '__ipow__', '__ilshift__', '__irshift__', '__iand__', '__ixor__', '__ior__', '__neg__', '__pos__', '__abs__', '__invert__', '__complex__', '__int__', '__long__', '__float__', '__oct__', '__hex__', '__index__', '__coerce__', '__enter__', '__exit__'):
exec "def {special}(self, *args, **kwargs):\n\treturn object.__getattribute__(self, '_proxyconn').callattr(self, '{special}', args, kwargs)".format(special=special) in None, None
class ProxyInfo(object):
@classmethod
def isPacked(self, obj):
return type(obj) == tuple and len(obj) == 7 and obj[:2] == (StopIteration, Ellipsis)
@classmethod
def fromPacked(self, obj):
return self(obj[2], obj[3], obj[4] or '', obj[5], obj[6] or ())
def __init__(self, endpoint, remoteid, attrpath = '', proxyhash = None, lazyattrs = (), dbgnote = ''):
self.endpoint = endpoint
self.remoteid = remoteid
self.attrpath = attrpath
self.proxyhash = proxyhash
self.lazyattrs = set(lazyattrs)
self.dbgnote = dbgnote
def __repr__(self):
return 'ProxyInfo'+repr((self.endpoint, hex(self.remoteid))) + ('' if not self.dbgnote else ' <'+self.dbgnote+'>')
def packed(self):
return (StopIteration, Ellipsis, self.endpoint, self.remoteid, self.attrpath or None, self.proxyhash, None) # Don't pack lazyattrs
def getattr(self, attr):
if attr not in self.lazyattrs: return None
path = self.attrpath+'.'+attr if self.attrpath else attr
return type(self)(self.endpoint, self.remoteid, attrpath = path, lazyattrs = self.lazyattrs)
class Connection(object):
def __init__(self, sock, secret, endpoint = urandom(8).encode('hex')):
self.sock = sock
self.secret = secret
self.endpoint = endpoint
self.garbage = []
def __del__(self):
try: self.sock.close()
except: pass
def sendmsg(self, msg):
x = marshal.dumps(msg)
self.sock.sendall(struct.pack('<I', len(x)))
self.sock.sendall(x)
def recvmsg(self):
x = self.sock.recv(4)
if len(x) == 4:
y = struct.unpack('<I', x)[0]
z = self.sock.recv(y)
if len(z) == y:
return marshal.loads(z)
raise socket.error(errno.ECONNRESET, 'The socket was closed while receiving a message.')
# Note: must send after non-info_only packing, or objects will be left with +1 retain count in self.vended
def pack(self, val, info_only = False, isDictKey = False):
if type(val) in (bool, int, long, float, complex, str, unicode) or val is None or val is StopIteration or val is Ellipsis:
return val
elif type(val) == tuple:
return tuple(self.pack(i, info_only) for i in val)
elif type(val) == list:
return [self.pack(i, info_only) for i in val]
elif type(val) == set:
return {self.pack(i, info_only) for i in val}
elif type(val) == frozenset:
return frozenset(self.pack(i, info_only) for i in val)
elif type(val) == dict:
return {self.pack(k, info_only, isDictKey = True):self.pack(v, info_only) for k,v in val.iteritems()}
elif type(val) == Proxy:
return object.__getattribute__(val, '_proxyinfo').packed()
elif type(val) == CodeType:
return val
else:
if not info_only:
self.vended.setdefault(id(val), [val, 0])[1] += 1
t = hash(val) if isDictKey else None
return ProxyInfo(self.endpoint, id(val), proxyhash=t).packed()
def unpack(self, val, info_only = False):
if ProxyInfo.isPacked(val):
info = ProxyInfo.fromPacked(val)
try:
if self.endpoint == info.endpoint:
try:
obj = self.vended[info.remoteid][0]
except KeyError:
if not info_only:
raise Exception("Whoops, "+self.endpoint+" can't find reference to object "+repr(info.remoteid))
else:
info.dbgnote = 'missing local reference'
return info
if info.attrpath:
for i in info.attrpath.split('.'):
obj = getattr(obj, i)
return obj
else:
return Proxy(self, info) if not info_only else info
except:
if not info_only: raise
info.dbgnote = 'While unpacking, ' + ''.join(traceback.format_exc())
return info
elif type(val) == tuple:
return tuple(self.unpack(i, info_only) for i in val)
elif type(val) == list:
return [self.unpack(i, info_only) for i in val]
elif type(val) == set:
return {self.unpack(i, info_only) for i in val}
elif type(val) == frozenset:
return frozenset(self.unpack(i, info_only) for i in val)
elif type(val) == dict:
return {self.unpack(k, info_only):self.unpack(v, info_only) for k,v in val.iteritems()}
elif type(val) == CodeType:
return val
else:
return val
def connectProxy(self):
self.vended = {}
self.sock.sendall('yo')
chal = urandom(20)
self.sock.sendall(chal)
if self.sock.recv(20) != sha1(self.secret+chal).digest():
print >> sys.stderr, "Server failed challenge!"
return None
self.sock.sendall(sha1(self.secret+self.sock.recv(20)).digest())
return self.unpack(self.recvmsg())
def runServer(self, obj):
if self.sock.recv(2) != 'yo':
print >> sys.stderr, "Spurious connection!"
return
self.sock.sendall(sha1(self.secret+self.sock.recv(20)).digest())
chal = urandom(20)
self.sock.sendall(chal)
if self.sock.recv(20) != sha1(self.secret+chal).digest():
print >> sys.stderr, "Client failed challenge!"
return None
try:
self.vended = {}
self.sendmsg(self.pack(obj))
while self.vended:
self.handle(self.recvmsg())
except socket.error as e:
if e.errno in (errno.EPIPE, errno.ECONNRESET): pass # Client disconnect is a non-error.
else: raise
finally:
del self.vended
def request(self, msg):
self.sendmsg(msg)
while True:
x = self.recvmsg()
if DEBUG: print >> sys.stderr, self.endpoint, self.unpack(x, True)
if x[0] == 'ok':
return self.unpack(x[1])
elif x[0] == 'exn':
exntyp = exceptions.__dict__.get(x[1])
args = self.unpack(x[2])
trace = x[3]
if exntyp and issubclass(exntyp, BaseException):
if DEBUG: print >> sys.stderr, 'Remote '+''.join(trace)
raise exntyp(*args)
else:
raise Exception(str(x[1])+repr(args)+'\nRemote '+''.join(trace))
else:
self.handle(x)
def handle(self, msg):
if DEBUG: print >> sys.stderr, self.endpoint, self.unpack(msg, True)
try:
ret = {
'get' : self.handle_get,
'set' : self.handle_set,
'call' : self.handle_call,
'callattr' : self.handle_callattr,
'hash' : self.handle_hash,
'repr' : self.handle_repr,
'gc' : self.handle_gc,
'eval' : self.handle_eval,
'exec' : self.handle_exec,
'deffun' : self.handle_deffun,
}[msg[0]](*msg[1:])
self.sendmsg(('ok', ret))
except:
typ, val, tb = sys.exc_info()
self.sendmsg(('exn', typ.__name__, self.pack(val.args), traceback.format_exception(typ, val, tb)))
def get(self, proxy, attr):
info = object.__getattribute__(proxy, '_proxyinfo')
x, addlazy = self.request(('get', info.packed(), attr))
if addlazy:
info.lazyattrs.add(attr)
return x
def handle_get(self, obj, attr):
obj1 = self.unpack(obj)
attr1 = getattr(obj1, attr)
# Start of the "addlazy" perf hack, which may lead to incorrect behavior in some cases.
addlazy = True
addlazy = addlazy and type(attr1) not in (bool, int, long, float, complex, str, unicode, tuple, list, set, frozenset, dict)
addlazy = addlazy and attr1 is not None
try: addlazy = addlazy and not isinstance(getattr(obj1.__class__, attr), property)
except: pass
return self.pack(attr1), addlazy
def set(self, proxy, attr, val):
self.request(('set', object.__getattribute__(proxy, '_proxyinfo').packed(), attr, self.pack(val)))
def handle_set(self, obj, attr, val):
setattr(self.unpack(obj), attr, self.unpack(val))
def call(self, proxy, args, kwargs):
return self.request(('call', object.__getattribute__(proxy, '_proxyinfo').packed(), self.pack(args or None), self.pack(kwargs or None)))
def handle_call(self, obj, args, kwargs):
return self.pack(self.unpack(obj)(*(self.unpack(args) or ()), **(self.unpack(kwargs) or {})))
def callattr(self, proxy, attr, args, kwargs):
return self.request(('callattr', object.__getattribute__(proxy, '_proxyinfo').packed(), attr, self.pack(args or None), self.pack(kwargs or None)))
def handle_callattr(self, obj, attr, args, kwargs):
return self.pack(getattr(self.unpack(obj), attr)(*(self.unpack(args) or ()), **(self.unpack(kwargs) or {})))
def hash(self, proxy):
return self.request(('hash', object.__getattribute__(proxy, '_proxyinfo').packed()))
def handle_hash(self, obj):
return self.pack(hash(self.unpack(obj)))
def repr(self, proxy):
return self.request(('repr', object.__getattribute__(proxy, '_proxyinfo').packed()))
def handle_repr(self, obj):
return self.pack(repr(self.unpack(obj)))
def delete(self, proxy):
info = object.__getattribute__(proxy, '_proxyinfo')
if info.attrpath != '': return
self.garbage.append(info.packed())
if len(self.garbage) > 50:
try: self.request(('gc', tuple(self.garbage)))
except socket.error: pass # No need for complaints about a dead connection
self.garbage[:] = []
def handle_gc(self, objs):
for obj in objs:
try:
info = ProxyInfo.fromPacked(obj)
if info.endpoint != self.endpoint: continue
assert info.attrpath == ''
self.vended[info.remoteid][1] -= 1
if self.vended[info.remoteid][1] == 0:
del self.vended[info.remoteid]
elif self.vended[info.remoteid][1] < 0:
print >> sys.stderr, "Too many releases on", self.unpack(obj, True), self.vended[info.remoteid][1]
except:
print >> sys.stderr, "Exception while releasing", self.unpack(obj, True)
traceback.print_exc(sys.stderr)
def disconnect(self):
self.garbage = []
self.sock.close()
def _eval(self, expr, local = None):
ret, d = self.request(('eval', self.pack(expr), self.pack(local)))
if local is not None:
local.clear()
local.update(d)
return ret
def handle_eval(self, expr, local):
d = self.unpack(local)
ret = eval(self.unpack(expr), globals(), d)
return self.pack(ret), (self.pack(d) if d is not None else None)
def _exec(self, stmt, local = None):
d = self.request(('exec', self.pack(stmt), self.pack(local)))
if local is not None:
local.clear()
local.update(d)
def handle_exec(self, stmt, local):
d = self.unpack(local)
exec(self.unpack(stmt), globals(), d)
return self.pack(d) if d is not None else None
# Define a function on the remote side. Its __globals__ will be
# the local client-side func.__globals__ filtered to the keys in
# func_globals, underlaid with the remote server-side globals()
# filtered to the keys in remote_globals. None is a special value
# for the filters, and disables any filtering.
def deffun(self, func, func_globals = (), remote_globals = None):
glbls = {k:v for k,v in func.__globals__.iteritems() if k in func_globals} if func_globals is not None else func.__globals__
return self.request(('deffun', self.pack((func.__code__, glbls, func.__name__, func.__defaults__, func.__closure__)), self.pack(func.__dict__), self.pack(func.__doc__), remote_globals))
def handle_deffun(self, func, fdict, fdoc, remote_globals):
func = self.unpack(func)
g = globals()
glbls = {k:g[k] for k in remote_globals if k in g} if remote_globals is not None else g.copy()
glbls.update(func[1])
func[1].update(glbls)
f = FunctionType(*func)
f.__dict__ = self.unpack(fdict)
f.__doc__ = self.unpack(fdoc)
return self.pack(f)
__all__ = [Connection,]
# For demo purposes.
if __name__ == "__main__":
from sys import argv
if len(argv) <= 3:
print >> sys.stderr, "Usage:", argv[0], "server <address> <port> [<password>]"
print >> sys.stderr, " python -i", argv[0], "client <address> <port> [<password>]"
print >> sys.stderr, "In the client python shell, the server's module is available as 'proxy'"
print >> sys.stderr, "A good demo is `proxy.__builtins__.__import__('ctypes').memset(0,0,1)`"
exit(64)
hostport = (argv[2], int(argv[3]))
password = argv[4] if len(argv) > 4 else 'lol, python'
if argv[1] == 'server':
import SocketServer
class Server(SocketServer.BaseRequestHandler):
def handle(self):
print >> sys.stderr, 'Accepting client', self.client_address
Connection(self.request, password).runServer(sys.modules[__name__])
print >> sys.stderr, 'Finished with client', self.client_address
SocketServer.TCPServer.allow_reuse_address = True
SocketServer.TCPServer(hostport, Server).serve_forever()
exit(1)
elif argv[1] == 'client':
connection = Connection(socket.create_connection(hostport), password)
proxy = connection.connectProxy()
print >> sys.stderr, "`proxy` and `connection` are available for you to play with at the interactive prompt."
else:
exit(64)
| 11,408 | 210 | 1,054 |
92fb4a723733c81f832a4920208362fbc999a86f | 21 | py | Python | datasets/voc/__init__.py | gjy3035/WSAL_released | fad6490d032eb37dfb62bc0a1eb30fc062dc27a4 | [
"MIT"
] | 22 | 2019-08-19T09:58:29.000Z | 2021-11-15T09:35:17.000Z | datasets/voc/__init__.py | gjy3035/WSAL_released | fad6490d032eb37dfb62bc0a1eb30fc062dc27a4 | [
"MIT"
] | null | null | null | datasets/voc/__init__.py | gjy3035/WSAL_released | fad6490d032eb37dfb62bc0a1eb30fc062dc27a4 | [
"MIT"
] | 4 | 2020-07-03T01:08:09.000Z | 2021-12-02T16:02:54.000Z | from .voc import VOC
| 10.5 | 20 | 0.761905 | from .voc import VOC
| 0 | 0 | 0 |
b7956ce6f249b6a6cc12973448b0d470c760bbe1 | 6,666 | py | Python | test/unit/transform/test_dataframe.py | arkhn/fhir-pipe | fd54e1910f6f037b12e60cd8d29c033971fe1de0 | [
"Apache-2.0"
] | 27 | 2018-10-16T13:03:17.000Z | 2022-01-05T01:21:37.000Z | test/unit/transform/test_dataframe.py | arkhn/fhir-pipe | fd54e1910f6f037b12e60cd8d29c033971fe1de0 | [
"Apache-2.0"
] | 45 | 2018-10-21T14:14:11.000Z | 2020-06-25T14:32:28.000Z | test/unit/transform/test_dataframe.py | arkhn/fhir-pipe | fd54e1910f6f037b12e60cd8d29c033971fe1de0 | [
"Apache-2.0"
] | 2 | 2019-03-27T12:39:54.000Z | 2019-04-06T22:33:20.000Z | import pandas as pd
from unittest import mock
import fhirpipe.transform.dataframe as transform
from fhirpipe.analyze.attribute import Attribute
from fhirpipe.analyze.sql_column import SqlColumn
from fhirpipe.analyze.concept_map import ConceptMap
from fhirpipe.analyze.cleaning_script import CleaningScript
from fhirpipe.analyze.merging_script import MergingScript
from test.unit.conftest import mock_config, mock_api_get_maps
@mock.patch("fhirpipe.analyze.cleaning_script.scripts.get_script", return_value=mock_get_script)
@mock.patch("fhirpipe.analyze.concept_map.fhirpipe.global_config", mock_config)
@mock.patch("fhirpipe.analyze.concept_map.requests.get", mock_api_get_maps)
@mock.patch("fhirpipe.analyze.merging_script.scripts.get_script", return_value=mock_get_script)
| 36.828729 | 98 | 0.583108 | import pandas as pd
from unittest import mock
import fhirpipe.transform.dataframe as transform
from fhirpipe.analyze.attribute import Attribute
from fhirpipe.analyze.sql_column import SqlColumn
from fhirpipe.analyze.concept_map import ConceptMap
from fhirpipe.analyze.cleaning_script import CleaningScript
from fhirpipe.analyze.merging_script import MergingScript
from test.unit.conftest import mock_config, mock_api_get_maps
def mock_get_script(*args):
if len(args) == 1:
return args[0] + "cleaned"
elif len(args) == 2:
return args[0]
else:
return args[0] + args[1] + "merge"
@mock.patch("fhirpipe.analyze.cleaning_script.scripts.get_script", return_value=mock_get_script)
@mock.patch("fhirpipe.analyze.concept_map.fhirpipe.global_config", mock_config)
@mock.patch("fhirpipe.analyze.concept_map.requests.get", mock_api_get_maps)
def test_clean_data(_, fhir_concept_map_code, fhir_concept_map_gender):
df = pd.DataFrame(
{
"PATIENTS_NAME": ["alice", "bob", "charlie"],
"PATIENTS_ID": ["id1", "id2", "id3"],
"PATIENTS_ID2": ["id21", "id22", "id23"],
"ADMISSIONS_LANGUAGE": ["M", "F", "F"],
"ADMISSIONS_ID": ["ABC", "DEF", "GHI"],
},
)
attr_name = Attribute(
"name", columns=[SqlColumn("PATIENTS", "NAME", cleaning_script=CleaningScript("clean1"),)]
)
attr_id = Attribute(
"id",
columns=[SqlColumn("PATIENTS", "ID"), SqlColumn("PATIENTS", "ID2")],
static_inputs=["null"],
)
attr_language = Attribute(
"language",
columns=[SqlColumn("ADMISSIONS", "LANGUAGE", concept_map=ConceptMap("id_cm_gender"))],
static_inputs=["val"],
)
attr_admid = Attribute(
"code",
columns=[
SqlColumn(
"ADMISSIONS",
"ID",
cleaning_script=CleaningScript("clean2"),
concept_map=ConceptMap("id_cm_code"),
)
],
)
attributes = [attr_name, attr_id, attr_language, attr_admid]
primary_key_column = SqlColumn("PATIENTS", "ID")
cleaned_df = transform.clean_dataframe(df, attributes, primary_key_column)
df_columns = pd.MultiIndex.from_tuples(
[
(attr_name, ("PATIENTS_NAME", "PATIENTS")),
(attr_id, ("PATIENTS_ID", "PATIENTS")),
(attr_id, ("PATIENTS_ID2", "PATIENTS")),
(attr_language, ("ADMISSIONS_LANGUAGE", "ADMISSIONS")),
(attr_admid, ("ADMISSIONS_ID", "ADMISSIONS")),
("pk", ("PATIENTS_ID", "PATIENTS")),
]
)
expected = pd.DataFrame(
{
df_columns[0]: ["alicecleaned", "bobcleaned", "charliecleaned"],
df_columns[1]: ["id1", "id2", "id3"],
df_columns[2]: ["id21", "id22", "id23"],
df_columns[3]: ["male", "female", "female"],
df_columns[4]: ["abc", "def", "ghi"],
df_columns[5]: ["id1", "id2", "id3"],
},
)
assert cleaned_df.equals(expected)
def test_squash_rows():
attr_name = Attribute("name", columns=[SqlColumn("PATIENTS", "NAME")])
attr_id = Attribute("id", columns=[SqlColumn("PATIENTS", "ID")])
attr_language = Attribute("language", columns=[SqlColumn("ADMISSIONS", "LANGUAGE")])
attr_admid = Attribute("admid", columns=[SqlColumn("ADMISSIONS", "ID")])
df_columns = pd.MultiIndex.from_tuples(
[
(attr_name, ("PATIENTS_NAME", "PATIENTS")),
(attr_id, ("PATIENTS_ID", "PATIENTS")),
(attr_language, ("ADMISSIONS_LANGUAGE", "ADMISSIONS")),
(attr_admid, ("ADMISSIONS_ID", "ADMISSIONS")),
]
)
df = pd.DataFrame(
{
df_columns[0]: ["bob", "bob", "alice", "bob"],
df_columns[1]: ["id1", "id1", "id2", "id3"],
df_columns[2]: ["lang1", "lang2", "lang3", "lang4"],
df_columns[3]: ["id1", "id2", "id3", "id4"],
},
)
squash_rules = ["PATIENTS", [["ADMISSIONS", []]]]
actual = transform.squash_rows(df, squash_rules)
# Sort to be sure actual and expected are in the same order
actual = actual.sort_values(by=df_columns[1]).reset_index(drop=True)
expected = pd.DataFrame(
{
df_columns[0]: ["bob", "alice", "bob"],
df_columns[1]: ["id1", "id2", "id3"],
df_columns[2]: [("lang1", "lang2"), ("lang3",), ("lang4",)],
df_columns[3]: [("id1", "id2"), ("id3",), ("id4",)],
},
)
# Sort to be sure actual and expected are in the same order
expected = expected.sort_values(by=df_columns[1]).reset_index(drop=True)
assert actual.equals(expected)
@mock.patch("fhirpipe.analyze.merging_script.scripts.get_script", return_value=mock_get_script)
def test_merge_dataframe(_):
attr_name = Attribute("name", columns=[SqlColumn("PATIENTS", "NAME")])
attr_id = Attribute(
"id",
columns=[SqlColumn("PATIENTS", "ID"), SqlColumn("PATIENTS", "ID2")],
static_inputs=["unknown"],
merging_script=MergingScript("merge"),
)
attr_language = Attribute("language", columns=[SqlColumn("ADMISSIONS", "LANGUAGE")])
attr_admid = Attribute("admid", columns=[SqlColumn("ADMISSIONS", "ID")])
df_columns = pd.MultiIndex.from_tuples(
[
(attr_name, ("PATIENTS_NAME", "PATIENTS")),
(attr_id, ("PATIENTS_ID", "PATIENTS")),
(attr_id, ("PATIENTS_ID2", "PATIENTS")),
(attr_language, ("ADMISSIONS_LANGUAGE", "ADMISSIONS")),
(attr_admid, ("ADMISSIONS_ID", "ADMISSIONS")),
("pk", ("PATIENTS_ID", "PATIENTS")),
]
)
df = pd.DataFrame(
{
df_columns[0]: ["bob", "bob", "alice", "bob"],
df_columns[1]: ["id1", "id1", "id2", "id3"],
df_columns[2]: ["id21", "id21", "id22", "id23"],
df_columns[3]: ["lang1", "lang2", "lang3", "lang4"],
df_columns[4]: ["hadmid1", "hadmid2", "hadmid3", "hadmid4"],
df_columns[5]: ["id1", "id2", "id3", "id4"],
},
)
attributes = [attr_name, attr_id, attr_language, attr_admid]
primary_key_column = SqlColumn("PATIENTS", "ID")
actual = transform.merge_dataframe(df, attributes, primary_key_column)
expected = pd.DataFrame(
{
attr_name: ["bob", "bob", "alice", "bob"],
attr_id: ["id1id21merge", "id1id21merge", "id2id22merge", "id3id23merge"],
attr_language: ["lang1", "lang2", "lang3", "lang4"],
attr_admid: ["hadmid1", "hadmid2", "hadmid3", "hadmid4"],
},
)
assert actual.equals(expected)
| 5,793 | 0 | 90 |
575e1b2b5d0fa016430c298fbdb1587d14bbcc10 | 7,198 | py | Python | solution/operators/sdi_pandas_0.0.37/sdi_pandas_0.0.36/content/files/vflow/subengines/com/sap/python36/operators/sdi_pandas/linRegressionPredict/linRegressionPredict.py | thhapke/DI_Pandas | 7a9108007459260a30ea7ee404a76b42861c81c5 | [
"MIT"
] | 2 | 2020-01-02T19:54:46.000Z | 2020-03-09T08:49:33.000Z | solution/operators/sdi_pandas_0.0.37/sdi_pandas_0.0.36/content/files/vflow/subengines/com/sap/python36/operators/sdi_pandas/linRegressionPredict/linRegressionPredict.py | thhapke/DI_Pandas | 7a9108007459260a30ea7ee404a76b42861c81c5 | [
"MIT"
] | null | null | null | solution/operators/sdi_pandas_0.0.37/sdi_pandas_0.0.36/content/files/vflow/subengines/com/sap/python36/operators/sdi_pandas/linRegressionPredict/linRegressionPredict.py | thhapke/DI_Pandas | 7a9108007459260a30ea7ee404a76b42861c81c5 | [
"MIT"
] | 1 | 2020-03-28T22:53:16.000Z | 2020-03-28T22:53:16.000Z | import sdi_utils.gensolution as gs
import sdi_utils.set_logging as slog
import sdi_utils.textfield_parser as tfp
import pandas as pd
import numpy as np
try:
api
except NameError:
inports = [{'name': 'inData', 'type': 'message.DataFrame'}, {'name': 'inCoef', 'type': 'message.DataFrame'}]
outports = [{'name': 'log', 'type': 'string'}, {'name': 'output', 'type': 'message.DataFrame'}]
api.set_port_callback([inports[0]['name'], inports[1]['name']], call_on_input)
| 40.438202 | 266 | 0.601834 | import sdi_utils.gensolution as gs
import sdi_utils.set_logging as slog
import sdi_utils.textfield_parser as tfp
import pandas as pd
import numpy as np
try:
api
except NameError:
class api:
class Message:
def __init__(self,body = None,attributes = ""):
self.body = body
self.attributes = attributes
def send(port,msg) :
if isinstance(msg,api.Message) :
print('Port: ', port)
print('Attributes: ', msg.attributes)
print('Body: ', str(msg.body))
else :
print(str(msg))
return msg
def call(config,msg_coef,msg_data):
api.config = config
return process(msg_coef,msg_data)
def set_port_callback(port, callback) :
data_df = pd.DataFrame(
{'icol': [1, 1, 3, 3, 3], 'col2': [1, 2, 3, 4, 5], 'col3': [2, 3, 4, 5, 6], 'col4': [5, 6.5, 7.5, 8, 9], \
'col5': [6, 6.7, 8.2, 9, 10.1]})
msg_data = api.Message(attributes= {'format': 'panda', 'name': 'DF_name'},body = data_df)
# without segmentation
coef_df = pd.Series({'coef': [0.57, 0.57, -0.09], 'intercept': 4.67})
att_coef = {'format': 'panda', 'name': 'Coeff', 'regression_columns': ['col2', 'col3', 'col4'], \
'prediction_column': 'col5'}
msg_coef = api.Message(attributes=att_coef,body=coef_df)
# with segmentation
coef_df = pd.DataFrame(
{'icol': [1, 3], 'coef': [[0.165, 0.165, 0.25], [0.25, 0.25, 0.6]], 'intercept': [4.27, 1.95]})
att_coef = {'format': 'panda', 'name': 'Coeff', 'regression_columns': ['col2', 'col3', 'col4'], \
'prediction_column': 'col5', 'segmentation_columns': ['icol']}
msg_coef = api.Message(attributes=att_coef, body=coef_df)
callback(msg_coef,msg_data)
class config:
## Meta data
config_params = dict()
version = '0.0.17'
tags = {'pandas': '', 'sklearn': ''}
operator_description = "Linear Regression Predict"
operator_description_long = "Using the model calculated with the Scikit Learn module to predict values."
add_readme = dict()
add_readme["References"] = '[ScitLearn Linear Regression](https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html)'
prediction_col_only = False
config_params['prediction_col_only'] = {'title': 'Prediction Columns only', 'description': 'The output only contains the prediction columns', 'type': 'boolean'}
regresssion_cols_value = 'None'
config_params['regresssion_cols_value'] = {'title': 'Set value for some regression columns', 'type': 'string'}
config_params['regresssion_cols_value']['description'] = "list of comma-separated maps with columns and values that overrides the prediction data of the *inData* message. Only applicable for fixe values. Otherwise the *inData* message needs to be used. "
prediction_prefix = 'p_'
config_params['prediction_prefix'] = {'title': 'Prefix for prediction columns', 'description': 'Prefix for prediction columns', 'type': 'string'}
def process(msg_coef, msg_data) :
logger, log_stream = slog.set_logging('DEBUG')
# start custom process definition
prev_att = msg_data.attributes
df = msg_data.body
coef_df = msg_coef.body
if not isinstance(df, pd.DataFrame):
logger.error('Message body does not contain a pandas DataFrame')
raise TypeError('Message body does not contain a pandas DataFrame')
att_dict = dict()
att_dict['config'] = dict()
###### start of doing calculation
# segment columns
segment_cols = None
if 'segmentation_columns' in msg_coef.attributes:
segment_cols = msg_coef.attributes['segmentation_columns']
# regression columns
regression_cols = msg_coef.attributes['regression_columns']
# prediction column
prediction_col = msg_coef.attributes['prediction_column']
# setting values of regression column values (if not in the dataMsg already done
att_dict['config']['regresssion_cols_value'] = api.config.regresssion_cols_value
valmap = tfp.read_dict(api.config.regresssion_cols_value)
if valmap:
for col, val in valmap.items():
if np.issubdtype(df[col].dtype, np.integer):
val = int(val)
elif np.issubdtype(df[col].dtype, np.float):
val = float(val)
else:
raise ValueError('Regression value needs to be numeric')
df[col] = val
# merge data and coef df
if segment_cols:
df = pd.merge(df, coef_df, how='inner', left_on=segment_cols, right_on=segment_cols)
prefix = tfp.read_value(api.config.prediction_prefix)
if prefix == None:
prefix = ''
pcol = prefix + prediction_col
if segment_cols:
def predict(x):
x[pcol] = np.dot(x['coef'], x[regression_cols].values) + x['intercept']
return x
df = df.apply(predict, axis=1, result_type=None)
df.drop(columns=['coef', 'intercept'], inplace=True)
else:
def predict(x):
x[pcol] = np.dot(coef_df['coef'], x[regression_cols].values) + coef_df['intercept']
return x
df = df.apply(predict, axis=1, result_type=None)
# cast type of prediction col from prediction variable
if df[prediction_col].dtype == np.integer:
logger.debug('Cast prediction column to <int>')
df[pcol] = df[pcol].round().astype(df[prediction_col].dtype)
if api.config.prediction_col_only:
logger.debug('Output only prediction columns')
if segment_cols:
df[prediction_col] = df[pcol]
df = df[segment_cols + [prediction_col]]
else:
df = df[prediction_col]
att_dict['config']['prediction_col_only'] = api.config.prediction_col_only
###### end of doing calculation
##############################################
# final infos to attributes and info message
##############################################
if df.empty:
raise ValueError('DataFrame is empty')
att_dict['operator'] = 'regressionTrainingDataFrame'
att_dict['name'] = prev_att['name']
# end custom process definition
log = log_stream.getvalue()
msg = api.Message(attributes=att_dict,body=df)
return log, msg
inports = [{'name': 'inData', 'type': 'message.DataFrame'}, {'name': 'inCoef', 'type': 'message.DataFrame'}]
outports = [{'name': 'log', 'type': 'string'}, {'name': 'output', 'type': 'message.DataFrame'}]
def call_on_input(msg, msg1) :
log, msg = process(msg, msg1)
api.send(outports[0]['name'], log)
api.send(outports[1]['name'], msg)
api.set_port_callback([inports[0]['name'], inports[1]['name']], call_on_input)
def main() :
print('Test: Default')
api.set_port_callback([inports[0]['name'], inports[1]['name']], call_on_input)
| 5,070 | 1,557 | 95 |
46693bdfb16cac38db1a0703abb922a44a3dbf9d | 47 | py | Python | python_01_simple/simple_message.py | lexiaoyuan/PythonCrashCourse | 9d1c59012d3ae9fdbfc468bbf401f567ce88681b | [
"MIT"
] | null | null | null | python_01_simple/simple_message.py | lexiaoyuan/PythonCrashCourse | 9d1c59012d3ae9fdbfc468bbf401f567ce88681b | [
"MIT"
] | null | null | null | python_01_simple/simple_message.py | lexiaoyuan/PythonCrashCourse | 9d1c59012d3ae9fdbfc468bbf401f567ce88681b | [
"MIT"
] | null | null | null | message = "Hello Python World！"
print(message)
| 15.666667 | 31 | 0.744681 | message = "Hello Python World！"
print(message)
| 0 | 0 | 0 |
9388ebfede0310c6b34b3d18a015f71a449ec16b | 16,912 | py | Python | diagnostic_order/order/views.py | ideaworld/DiagnosticORwithHAPI | f9554678c9d04d97a957e596a3fd891650bb1d2e | [
"MIT"
] | null | null | null | diagnostic_order/order/views.py | ideaworld/DiagnosticORwithHAPI | f9554678c9d04d97a957e596a3fd891650bb1d2e | [
"MIT"
] | null | null | null | diagnostic_order/order/views.py | ideaworld/DiagnosticORwithHAPI | f9554678c9d04d97a957e596a3fd891650bb1d2e | [
"MIT"
] | null | null | null | from django.shortcuts import render
from django.http import HttpResponse
from django.http import HttpResponseRedirect
import json
from django.http import JsonResponse
from urllib import urlencode
from urllib import quote
import requests
from django.template import RequestContext, loader
import re
from django.shortcuts import redirect
from django.views.decorators.csrf import csrf_exempt
from config import GENOMICSCOPE, GENOMIC_ID, testJ, INDENTIFIER,REPORT,testJson, ID_SRCRET_BASE64, redirect_uri, API_BASE, AUTH_BASE, CLIENT_ID, REDIRECT_URI, SCOPES
from whoosh.index import create_in, open_dir
from whoosh.fields import *
from whoosh.qparser import QueryParser
from whoosh.query import *
import os.path
import string
@csrf_exempt
@csrf_exempt
@csrf_exempt
@csrf_exempt
@csrf_exempt
| 30.749091 | 165 | 0.647351 | from django.shortcuts import render
from django.http import HttpResponse
from django.http import HttpResponseRedirect
import json
from django.http import JsonResponse
from urllib import urlencode
from urllib import quote
import requests
from django.template import RequestContext, loader
import re
from django.shortcuts import redirect
from django.views.decorators.csrf import csrf_exempt
from config import GENOMICSCOPE, GENOMIC_ID, testJ, INDENTIFIER,REPORT,testJson, ID_SRCRET_BASE64, redirect_uri, API_BASE, AUTH_BASE, CLIENT_ID, REDIRECT_URI, SCOPES
from whoosh.index import create_in, open_dir
from whoosh.fields import *
from whoosh.qparser import QueryParser
from whoosh.query import *
import os.path
import string
def get_ref(key, data):
if (key in data):
order = data[key]['reference']
#order = ''.join(map(lambda x: "%c" % ord(x), list(order)))
return order
order = ''
return order
def check_order(request):
data = search(request, 'orderforgenetics')
return HttpResponse(json.dumps(data), content_type="application/json")
def new_order(request):
return render(request, 'new_order.html')
def get_key_value(key, data):
if (key in data.keys()):
return data[key]
return ''
def get_name(str):
return str[:str.index('/')]
def get_ID(str):
return str[str.index('/')+1:]
def order_detail(request, id):
order = read_api(request, id, 'orderforgenetics')
print order
subject = read_api(request, get_ID(order['subject']['reference']), get_name(order['subject']['reference']))
subject = subject['name'][0]['text']
specimen = get_key_value('specimen', order)
priority = get_key_value('priority', order)
reason = ''
if (('reason' in order.keys()) and ('text' in order['reason'][0].keys())):
reason = order['reason'][0]['text']
sptinfo = ''
if ('supportingInformation' in order.keys()):
sptinfo = order['supportingInformation'][0]['reference']
note = ''
if ('note' in order.keys()):
note = order['note'][0]['text']
for item in order['extension']:
for s in item['extension']:
if s['url'] == 'obsForSequence' and s['valueReference']['reference'] != '':
name = get_name(s['valueReference']['reference'])
id = get_ID(s['valueReference']['reference'])
data = read_api(request, id, 'observationforgenetics')
for e in data['extension']:
if e['url'] == r'http://hl7.org/fhir/StructureDefinition/observation-geneticsSequence':
url = e['valueReference']['reference']
access_token = request.COOKIES['genomic_access_token']
resp = requests.get('%s/%s?_format=json'%(API_BASE, url),
headers={'Accept': 'application/json','Authorization': 'Bearer %s'% access_token})
data = resp.json()
obs = data['text']['div'][5:-6]
var_id = obs[obs.index(" of ")+4: obs.index("is ")]
obs = obs[obs.index("is ")+3:]
obs = "Variation ID: "+ var_id + "(Genotype:" + obs + ")"
s['valueReference']['reference'] = obs
args = {
'id':id,
'status':order['status'],
'subject':subject,
'orderer':order['orderer']['reference'],
'encounter':get_ref('encounter',order),
'reason':reason,
'sptinfo':sptinfo,
'specimen': specimen,
'priority': priority,
'event_list':order['event'],
'item_list': order['extension'],
'note':note,
}
return render(request, 'order_detail.html', args)
def home(request):
template = loader.get_template('home/index.html')
context = RequestContext(request, {
})
return HttpResponse(template.render(context))
def launch(request):
iss = request.GET.get('iss', '')
launch = request.GET.get('launch', '')
request.session['iss'] = iss
request.session['launch'] = launch
scope = ' '.join(GENOMICSCOPE)
print 'Genomic authorization'
args = {
'scope':scope,
'client_id':GENOMIC_ID,
'response_type':'code',
'redirect_uri':REDIRECT_URI
}
re = 'http://genomics-advisor.smartplatforms.org:2048/auth/authorize?'+ urlencode(args)
resp = HttpResponseRedirect(re)
return resp
class OAuthError(Exception):
pass
def get_access_token(auth_code):
exchange_data = {
'code':auth_code,
'redirect_uri': 'http://localhost:8000/index.html',
'grant_type': 'authorization_code'
}
headers = {
"Content-Type": 'application/x-www-form-urlencoded',
"Content-Length" : len(exchange_data),
}
resp = requests.post(AUTH_BASE+'/token', data=exchange_data, headers=headers)
if resp.status_code != 200:
raise OAuthError
else:
return resp.json()['access_token']
def recv_code(request):
code = request.GET.get('code', '')
access_token = get_access_token(code)
#redirect to home page
resp = HttpResponseRedirect('fhir-app/')
resp.set_cookie('access_token', access_token)
resp.set_cookie('genomic_access_token', request.session.get('genomic_access_token'))
return resp
def recv_redirect(request):
print "recv_redirect"
code = request.GET.get('code', '')
datas = {
'code':code,
'client_id': GENOMIC_ID,
'redirect_uri': REDIRECT_URI,
'grant_type': 'authorization_code'
}
headers = {
"Content-Type": 'application/x-www-form-urlencoded',
"Content-Length" : len(datas)
}
print 'begin'
resp = requests.post('http://genomics-advisor.smartplatforms.org:2048/auth/token', data=datas,headers=headers)
print resp
print 'end'
if resp.status_code != 200:
raise OAuthError
else:
genomic_access_token = resp.json()['access_token']
#resp.set_cookie('genomic_access_token', genomic_access_token)
request.session['genomic_access_token'] = genomic_access_token
re = 'http://localhost:8000/fhir-app/'
resp = HttpResponseRedirect(re)
resp.set_cookie('genomic_access_token', request.session.get('genomic_access_token'))
return resp
def get_id(_id, res):
start, end = re.search(res, _id).span()
return _id[start:]
def search(request, url, args={}):
print 'def search'
url = '/'+ url
args['session'] = request.COOKIES['genomic_access_token']
order_search = call_api(url, args);
return order_search
def noIssue(data):
if 'issue' not in data:
return True
else:
return False
def get_datas_list(request, subject):
order_search = search(request, subject);
datas=[]
entry={}
if order_search['total'] != 0:
for e in order_search['entry']:
div = e['resource']['name'][0]['text']
id = e['resource']['id']
entry={
'div': div,
'id': subject + '/' +id
}
datas.append(entry)
datas={
'total': order_search['total'],
'entry': datas
}
return datas
def search_subject(request):
subject = request.GET.get('subject')
print subject
datas = get_datas_list(request, subject)
return JsonResponse(datas, safe=False)
def search_type(request):
subject = request.GET.get('subject')
datas = get_datas_list(subject)
order_search = search(request, subject)
if noIssue(order_search):
datas=[]
entry={}
if order_search['total'] != 0:
for e in order_search['entry']:
div = e['resource']['text']['div']
id = e['resource']['id']
entry={
'div': div,
'id': subject + '/' +id
}
datas.append(entry)
datas={
'total': order_search['total'],
'entry': datas
}
return JsonResponse(datas, safe=False)
else:
datas={
'issue':order_search['issue']['details']
}
return JsonResponse(datas, safe=False)
def search_sptInfo(request):
subject = request.GET.get('subject')
order_search = search(request, subject)
return JsonResponse(order_search, safe=False)
def search_Observation(request):
subject = request.GET.get('subject')
subject = 'observationforgenetics'
order_search = search(request, subject)
datas = []
for entry in order_search['entry']:
for extension in entry['resource']['extension']:
if extension['url'] == r'http://hl7.org/fhir/StructureDefinition/observation-geneticsSequence':
url = extension['valueReference']['reference']
access_token = request.COOKIES['genomic_access_token']
resp = requests.get('%s/%s?_format=json'%(API_BASE, url),
headers={'Accept': 'application/json','Authorization': 'Bearer %s'% access_token})
data = resp.json()
div = data['text']['div']
_id = entry['resource']['id']
entry = {
'div': div,
'id': subject + '/' +_id
}
datas.append(entry);
le = len(datas);
datas = {
'total' : le,
'entry' : datas,
}
return JsonResponse(datas, safe=False)
def search_specimen(request):
subject = request.GET.get('subject')
order_search = search(request, subject)
return JsonResponse(order_search, safe=False)
def search_actor(request):
subject = request.GET.get('subject')
order_search = search(request, subject)
return JsonResponse(order_search['entry'], safe=False)
def search_target(request):
subject = request.GET.get('subject')
if subject == 'Organization':
datas={
'total': 1,
'entry':[
{
'div':'<div>Myriad Lab</div>',
'id':'123456'
}
]
}
return JsonResponse(datas, safe=False)
order_search = search(request, subject)
datas=[]
entry={}
if order_search['total'] != 0:
for e in order_search['entry']:
div = e['resource']['text']['div']
_id = e['resource']['id']
entry={
'div': div,
'id': subject + '/' +_id
}
datas.append(entry)
datas={
'total': order_search['total'],
'entry': datas
}
return JsonResponse(datas, safe=False)
def oldsubmit(request):
args={}
#args['session'] = request.session.get('genomic_access_token')
args['session'] = request.COOKIES['genomic_access_token']
upload_seq(request, testJson)
resp = HttpResponseRedirect('new_order/')
return resp
def submit(request):
req = json.loads(request.body)
order = req["order"]
resp = requests.post('%s/orderforgenetics?_format=json'% API_BASE,
data=json.dumps(dorder),
headers={'Authorization': 'Bearer %s'% access_token})
print resp.json()
return HttpResponse(content=resp.json(), content_type="application/json")
def edit(request, id):
order_search = search(request, 'orderforgenetics', {'id':id})
entry = order_search['entry']
order = None
for e in entry:
if e['resource']['id'] == id :
order = e['resource']
break
specimen = ''
if ('specimen' in order.keys()):
specimen = order['specimen']
priority = ''
if ('priority' in order.keys()):
priority = order['priority']
reason = ''
if (('reason' in order.keys()) and ('text' in order['reason'][0].keys())):
reason = order['reason'][0]['text']
sptinfo = ''
if ('supportingInformation' in order.keys()):
sptinfo = order['supportingInformation'][0]['reference']
args = {
'id':id,
'order_id':order['identifier'][0]['value'],
'status':order['status'],
'subject':order['subject']['reference'],
'orderer':order['orderer']['reference'],
'encounter':get_ref('encounter',order),
'reason':reason,
'sptinfo':sptinfo,
'specimen': specimen,
'priority': priority,
'event_list':order['event'],
'event_status':order['event'][0]['status'],
'event_actor':order['event'][0]['actor']['reference'],
'event_datetime':order['event'][0]['dateTime'],
'item_list': order['item'][0],
}
return render(request, 'edit.html', args)
@csrf_exempt
def update_order(request):
req = json.loads(request.body)
order = req['order']
oid = req['id']
access_token = request.COOKIES['genomic_access_token']
print '%s/orderforgenetics/%s' %(API_BASE,oid)
resp = requests.put('%s/orderforgenetics/%s?_format=json' %(API_BASE,oid),
data=order,
headers={'Content-Type':'application/json','Authorization':'Bearer %s'% access_token})
print resp.text
return HttpResponse(json.dumps(resp.json()), content_type="application/json")
@csrf_exempt
def updata(request):
req = json.loads(request.body)
dorder = req["diagnostic_order"]
order = req["order"]
#access_token = request.session.get('genomic_access_token')
access_token = request.COOKIES['genomic_access_token']
#resp = requests.post('%s/Order?_format=json'% API_BASE,
# data=json.dumps(order),
# headers={'Authorization': 'Bearer %s'% access_token})
#print 'Order is OK'
#print resp.json()
#order_id = resp.json()
#dorder['identifier'][0]['value'] = order_id["id"]
print '-'*20
print dorder
resp = requests.post('%s/orderforgenetics?_format=json'% API_BASE,
data=json.dumps(dorder),
headers={'Authorization': 'Bearer %s'% access_token})
print 'Diagnostic Order is ok'
print resp.json()
print resp
#f = open('log.txt', 'w')
#f.write(resp.content)
#f.close()
#print resp.content
print '-'*20
#print resp.json()
#print '-'*20
return HttpResponse(json.dumps(resp.json()), content_type='application/json')
@csrf_exempt
def updataOrder(request):
req = json.loads(request.body)
order = req["order"]
#access_token = request.session.get('genomic_access_token')
access_token = request.COOKIES['genomic_access_token']
print order
#resp = requests.put('%s/Order/%s' %(API_BASE, order_id),
# data = json.dumps(order),
# headers={'Authorization': 'Bearer %s'% access_token})
#print resp.json()
dorder_id = req["id"]
resp = requests.post('%s/orderforgenetics?_format=json' %(API_BASE),
data=json.dumps(order),
headers={'Content-Type':'application/json','Authorization':'Bearer %s'% access_token})
print resp.text
print resp.status_code
return HttpResponse(json.dumps(resp.json()), content_type='application/json')
def test(request):
args={}
args['session'] = request.COOKIES['genomic_access_token']
#order_search = upload_seq(request, testJson)
#order_search = delete(request, 'orderforgenetics', '35948c17-3c0d-4d05-a3b5-e34bae4b71d7')
order_search = call_api('/orderforgenetics', args)
return render(request, 'test.html', {'data':order_search})
#upload_seq(request, testJson)
#return render(request, 'test.html', {'data':'order_search'})
@csrf_exempt
def all_typedata(request):
print 'started'
data_type = request.GET.get('type', '')
print data_type
args = {
'session':request.COOKIES['genomic_access_token']
}
res_data = []
if len(data_type) > 0:
res_data = call_api('/%s'%data_type, args)
return HttpResponse(json.dumps(res_data), content_type="application/json")
def read_api(request, id, url='orderforgenetics'):
access_token = request.COOKIES['genomic_access_token']
resp = requests.get('%s/%s/%s?_format=json'%(API_BASE, url, id),
headers={'Accept': 'application/json',
'Authorization': 'Bearer %s'% access_token})
return resp.json()
def upload_seq(request, seq, url='orderforgenetics'):
access_token = request.COOKIES['genomic_access_token']
resp = requests.post('%s/orderforgenetics?_format=json'% API_BASE,
data=json.dumps(seq),
headers={'Authorization': 'Bearer %s'% access_token})
return resp.json()
def call_api(url, args={}):
access_token = args['session']
del args['session']
args['_format'] = 'json'
resp = requests.get('%s%s?%s'% (API_BASE, url, urlencode(args)),
headers={'Accept': 'application/json',
'Authorization': 'Bearer %s'% access_token})
print resp
return resp.json()
def delete(request, type, id):
access_token = request.COOKIES['genomic_access_token']
resp = requests.delete('%s/%s/%s?_format=json'%(API_BASE,type, id),
headers={'Accept': 'application/json',
'Authorization': 'Bearer %s'% access_token})
return resp.json()
@csrf_exempt
def search_code(request):
code_type = request.GET.get('type', '')
search_text = request.GET.get('text', '')
if len(search_text) == 0:
return HttpResponse(json.dumps([]), content_type="application/json")
#fuzzy search with whoosh
ix = open_dir(code_type)
# fuzzy search in Display
parser = QueryParser("Display", schema=ix.schema, termclass=FuzzyTerm)
#parser.add_plugin(FuzzyTermPlugin())
results = [] # final result list
with ix.searcher() as searcher:
# c = searcher.collector(limit=None)
# tlc = TimeLimitCollector(c, timelimit=10)
res = searcher.search(FuzzyTerm("Display", search_text))
for item in list(res):
results.append([item['code'], item['Display']])
return HttpResponse(json.dumps(results), content_type="application/json")
| 15,254 | 16 | 845 |
3ab88bee4c61ac767b22d56198ab86940d4cf51c | 6,305 | py | Python | sindy_bvp/sindy_bvp.py | sheadan/SINDy-BVP | ac5b2bb4854bb311e4f6f26b180dde87cc10c13d | [
"MIT"
] | 8 | 2020-05-19T23:56:39.000Z | 2022-03-04T19:22:56.000Z | sindy_bvp/sindy_bvp.py | sheadan/SINDy-BVP | ac5b2bb4854bb311e4f6f26b180dde87cc10c13d | [
"MIT"
] | null | null | null | sindy_bvp/sindy_bvp.py | sheadan/SINDy-BVP | ac5b2bb4854bb311e4f6f26b180dde87cc10c13d | [
"MIT"
] | 3 | 2020-08-07T17:57:02.000Z | 2021-03-19T23:44:44.000Z | """SINDy-BVP Logic collection."""
# Import Python packages
import pickle
import warnings
# Third-Party Imports
from sklearn.model_selection import train_test_split
# Package Imports
from sindy_bvp.variables import DependentVariable, IndependentVariable
from sindy_bvp.library_builders import TermBuilder, NoiseMaker
from sindy_bvp.differentiators import BaseDifferentiator
from sindy_bvp.optimizers import GroupRegressor, SGTR
from sindy_bvp.analysis.plotter import Plotter
from sindy_bvp.groupers import PointwiseGrouper
class SINDyBVP:
"""Collection of all logic associated with SINDy-BVP."""
def __init__(self, file_stem: str, num_trials: int,
differentiator: BaseDifferentiator,
outcome_var: str,
noisemaker: NoiseMaker = None,
known_vars: list = None,
dep_var_name: str = 'u',
ind_var_name: str = 'x'):
"""Initialize the attributes from parameters.
Keyword arguments:
file_stem --
num_trials --
differentiator --
outcome_var --
noisemaker --
known_vars --
dep_var_name --
ind_var_name --
"""
self.file_stem = file_stem
self.num_trials = num_trials
self.differentiator = differentiator
self.outcome_var = outcome_var
self.noisemaker = noisemaker
self.known_vars = known_vars
self.dv_name = dep_var_name
self.iv_name = ind_var_name
def sindy_bvp(self, report_results: bool = False):
"""Execute the core logic of SINDy-BVP.
Keyword argument:
report_results -- boolean if results should be printed.
Returns:
coeffs -- a dictionary containing key-np.ndarray pairs of
the terms with nonzero coefficients
pltr - a Plotter instance for generating analysis plots.
"""
# Step 1. Load in the data
x_vector, ode_sols, forcings, sl_coeffs = self.load_data()
# Step 2. Split data into testing and training
# I've put a warning catch here because train_test_split will give
# a future warning about test size being complement of train size
# which is desired in our case and not worth warning the user about
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
data_split = train_test_split(ode_sols, forcings,
train_size=self.num_trials,
random_state=0)
# Random state is set to 0 for consistency
sol_train, sol_test, f_train, f_test = data_split
# Step 3. Build DataFrames containing data from each trial
dfs = self.build_dataframes(sol_train, f_train)
# Step 4. Prepare regression
# Create the group regressor (Uses SGTR regression function above)
aggregator = PointwiseGrouper(lhs_term=self.outcome_var)
self.groupreg = GroupRegressor(aggregator, dfs, self.iv_name,
sgtr=SGTR())
# Step 5. Execute group regression
self.groupreg.group_regression(known_vars=self.known_vars)
if report_results:
self.groupreg.report_learning_results()
# Step 6. Return learned coefficients and Plotter instance
# which can generate analysis plots.
coeffs = self.groupreg.return_coefficients()
# Construct a plotter object with groupreg (which stores results)
pltr = Plotter(groupreg=self.groupreg,
x_vector=x_vector,
true_coeffs=sl_coeffs,
dependent_variable=self.dv_name,
ode_sols=sol_train,
is_sturm_liouville=True,
show_legends=False)
return coeffs, pltr
def load_data(self):
"""Load in the saved data based on the provided file stem.
Returns:
x_vector -- the vector of x values used ([0,0.01,...,10])
ode_sols -- the solutions to BVP given different forcings
forcings -- the forcings used for the ode solutions
sl_coeffs -- the true coefficients used for the BVP model
"""
x_vector = pickle.load(open(self.file_stem + "x.pickle", "rb"))
ode_sols = pickle.load(open(self.file_stem + "sols.pickle", "rb"))
forcings = pickle.load(open(self.file_stem + "fs.pickle", "rb"))
sl_coeffs = pickle.load(open(self.file_stem + "coeffs.pickle", "rb"))
return x_vector, ode_sols, forcings, sl_coeffs
def build_dataframes(self, ode_sols: list, used_fs: list):
"""Build dataframes containing evaluated symbolic functions.
Keyword arguments:
ode_sols -- the differential equation solutions to use
used_fs -- the corresponding forcing functions for the solutions
Returns:
dataframes -- a list of dataframes containing the evaluated
symbolic functions generated from each trial.
"""
# Create empty lists to house the stacked theta's and u's
dataframes = []
# Create the dataframes
for sol, f in zip(ode_sols, used_fs):
# Prepare independent variable
x_data = sol.t
x = IndependentVariable(self.iv_name, x_data, poly_deg=0)
# And prepare the dependent variable
signal = sol.y[0]
if self.noisemaker is not None:
signal = self.noisemaker.apply_noise(signal)
u = DependentVariable(self.dv_name, signal, nonlinear_deg=5)
# TermBuilder instance builds dataframe from the trial data
tb = TermBuilder([x], [u], self.differentiator)
# Inject the forcing function into the dataframe
tb.register_custom_term("f", f)
# build_library_terms method computes symbolic functions for all
# functions in the library and the outcome variable matrices at
# all spatial coordinates in the system
dataframe = tb.build_library_terms(lhs_term=self.outcome_var)
# Add the dataframe to dataframes list
dataframes.append(dataframe)
# Return the dataframes
return dataframes
| 38.212121 | 77 | 0.633941 | """SINDy-BVP Logic collection."""
# Import Python packages
import pickle
import warnings
# Third-Party Imports
from sklearn.model_selection import train_test_split
# Package Imports
from sindy_bvp.variables import DependentVariable, IndependentVariable
from sindy_bvp.library_builders import TermBuilder, NoiseMaker
from sindy_bvp.differentiators import BaseDifferentiator
from sindy_bvp.optimizers import GroupRegressor, SGTR
from sindy_bvp.analysis.plotter import Plotter
from sindy_bvp.groupers import PointwiseGrouper
class SINDyBVP:
"""Collection of all logic associated with SINDy-BVP."""
def __init__(self, file_stem: str, num_trials: int,
differentiator: BaseDifferentiator,
outcome_var: str,
noisemaker: NoiseMaker = None,
known_vars: list = None,
dep_var_name: str = 'u',
ind_var_name: str = 'x'):
"""Initialize the attributes from parameters.
Keyword arguments:
file_stem --
num_trials --
differentiator --
outcome_var --
noisemaker --
known_vars --
dep_var_name --
ind_var_name --
"""
self.file_stem = file_stem
self.num_trials = num_trials
self.differentiator = differentiator
self.outcome_var = outcome_var
self.noisemaker = noisemaker
self.known_vars = known_vars
self.dv_name = dep_var_name
self.iv_name = ind_var_name
def sindy_bvp(self, report_results: bool = False):
"""Execute the core logic of SINDy-BVP.
Keyword argument:
report_results -- boolean if results should be printed.
Returns:
coeffs -- a dictionary containing key-np.ndarray pairs of
the terms with nonzero coefficients
pltr - a Plotter instance for generating analysis plots.
"""
# Step 1. Load in the data
x_vector, ode_sols, forcings, sl_coeffs = self.load_data()
# Step 2. Split data into testing and training
# I've put a warning catch here because train_test_split will give
# a future warning about test size being complement of train size
# which is desired in our case and not worth warning the user about
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
data_split = train_test_split(ode_sols, forcings,
train_size=self.num_trials,
random_state=0)
# Random state is set to 0 for consistency
sol_train, sol_test, f_train, f_test = data_split
# Step 3. Build DataFrames containing data from each trial
dfs = self.build_dataframes(sol_train, f_train)
# Step 4. Prepare regression
# Create the group regressor (Uses SGTR regression function above)
aggregator = PointwiseGrouper(lhs_term=self.outcome_var)
self.groupreg = GroupRegressor(aggregator, dfs, self.iv_name,
sgtr=SGTR())
# Step 5. Execute group regression
self.groupreg.group_regression(known_vars=self.known_vars)
if report_results:
self.groupreg.report_learning_results()
# Step 6. Return learned coefficients and Plotter instance
# which can generate analysis plots.
coeffs = self.groupreg.return_coefficients()
# Construct a plotter object with groupreg (which stores results)
pltr = Plotter(groupreg=self.groupreg,
x_vector=x_vector,
true_coeffs=sl_coeffs,
dependent_variable=self.dv_name,
ode_sols=sol_train,
is_sturm_liouville=True,
show_legends=False)
return coeffs, pltr
def load_data(self):
"""Load in the saved data based on the provided file stem.
Returns:
x_vector -- the vector of x values used ([0,0.01,...,10])
ode_sols -- the solutions to BVP given different forcings
forcings -- the forcings used for the ode solutions
sl_coeffs -- the true coefficients used for the BVP model
"""
x_vector = pickle.load(open(self.file_stem + "x.pickle", "rb"))
ode_sols = pickle.load(open(self.file_stem + "sols.pickle", "rb"))
forcings = pickle.load(open(self.file_stem + "fs.pickle", "rb"))
sl_coeffs = pickle.load(open(self.file_stem + "coeffs.pickle", "rb"))
return x_vector, ode_sols, forcings, sl_coeffs
def build_dataframes(self, ode_sols: list, used_fs: list):
"""Build dataframes containing evaluated symbolic functions.
Keyword arguments:
ode_sols -- the differential equation solutions to use
used_fs -- the corresponding forcing functions for the solutions
Returns:
dataframes -- a list of dataframes containing the evaluated
symbolic functions generated from each trial.
"""
# Create empty lists to house the stacked theta's and u's
dataframes = []
# Create the dataframes
for sol, f in zip(ode_sols, used_fs):
# Prepare independent variable
x_data = sol.t
x = IndependentVariable(self.iv_name, x_data, poly_deg=0)
# And prepare the dependent variable
signal = sol.y[0]
if self.noisemaker is not None:
signal = self.noisemaker.apply_noise(signal)
u = DependentVariable(self.dv_name, signal, nonlinear_deg=5)
# TermBuilder instance builds dataframe from the trial data
tb = TermBuilder([x], [u], self.differentiator)
# Inject the forcing function into the dataframe
tb.register_custom_term("f", f)
# build_library_terms method computes symbolic functions for all
# functions in the library and the outcome variable matrices at
# all spatial coordinates in the system
dataframe = tb.build_library_terms(lhs_term=self.outcome_var)
# Add the dataframe to dataframes list
dataframes.append(dataframe)
# Return the dataframes
return dataframes
| 0 | 0 | 0 |
e06d168497a958893a06d13b3a0656f98d2f9b51 | 30,764 | py | Python | scripts.py | Laura-00/ADMHOMEWORKS | 6dc48a7a98e02005a61a2489e4b7534e60b6a563 | [
"MIT"
] | null | null | null | scripts.py | Laura-00/ADMHOMEWORKS | 6dc48a7a98e02005a61a2489e4b7534e60b6a563 | [
"MIT"
] | null | null | null | scripts.py | Laura-00/ADMHOMEWORKS | 6dc48a7a98e02005a61a2489e4b7534e60b6a563 | [
"MIT"
] | null | null | null | #INSERTION SORT - PART 2
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the insertionSort2 function below.
if __name__ == '__main__':
n = int(input())
arr = list(map(int, input().rstrip().split()))
insertionSort2(n, arr)
#INSERTION SORT - PART 2
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the insertionSort1 function below.
if __name__ == '__main__':
n = int(input())
arr = list(map(int, input().rstrip().split()))
insertionSort1(n, arr)
#RECURSIVE DIGIT SUM
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the superDigit function below.
if __name__ == '__main__':
fptr = open(os.environ['OUTPUT_PATH'], 'w')
nk = input().split()
n = nk[0]
k = int(nk[1])
result = superDigit(n, k)
fptr.write(str(result) + '\n')
fptr.close()
#VIRAL ADVERTISING
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the viralAdvertising function below.
if __name__ == '__main__':
fptr = open(os.environ['OUTPUT_PATH'], 'w')
n = int(input())
result = viralAdvertising(n)
fptr.write(str(result) + '\n')
fptr.close()
#NUMBER LINE JUMPS
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the kangaroo function below.
if __name__ == '__main__':
fptr = open(os.environ['OUTPUT_PATH'], 'w')
x1V1X2V2 = input().split()
x1 = int(x1V1X2V2[0])
v1 = int(x1V1X2V2[1])
x2 = int(x1V1X2V2[2])
v2 = int(x1V1X2V2[3])
result = kangaroo(x1, v1, x2, v2)
fptr.write(result + '\n')
fptr.close()
#BIRTHDAY CAKE CANDLES
#!/bin/python3
import math
import os
import random
import re
import sys
#
# Complete the 'birthdayCakeCandles' function below.
#
# The function is expected to return an INTEGER.
# The function accepts INTEGER_ARRAY candles as parameter.
#
if __name__ == '__main__':
fptr = open(os.environ['OUTPUT_PATH'], 'w')
candles_count = int(input().strip())
candles = list(map(int, input().rstrip().split()))
result = birthdayCakeCandles(candles)
fptr.write(str(result) + '\n')
fptr.close()
#POLYNOMIALS
import numpy
print(numpy.polyval(numpy.array(input().split(),float),int(input())))
#INNER AND OUTER
import numpy
a=numpy.array([input().split()], int)
b=numpy.array([input().split()], int)
print (int(numpy.inner(a,b)))
print (numpy.outer(a,b))
#DOT AND CROSS
import numpy
n=int(input())
a=numpy.array([input().split() for _ in range (n)],int)
b=numpy.array([input().split() for _ in range (n)], int)
print(numpy.dot(a,b))
#MEAN, VAR AND STD
import numpy
n,m=map(int,input().split())
arr=numpy.array([input().split() for _ in range (n)], int)
numpy.set_printoptions(sign=' ')
numpy.set_printoptions(legacy='1.13')
print (numpy.mean(arr, axis=1))
print (numpy.var(arr, axis=0))
print (numpy.std(arr, axis= None))
#MIN AND MAX
import numpy
n,m=map(int,input().split())
arr=numpy.array([input().split() for _ in range (n)], int)
minimum=numpy.min(arr, axis=1)
print(numpy.max(minimum))
#SUM AND PROD
import numpy
n,m=map(int,input().split())
arr=numpy.array([input().split() for _ in range (n)], int)
somma=numpy.sum(arr, axis=0)
print (numpy.prod(somma))
#FLOOR, CEIL AND RINT
import numpy
a=numpy.array(input().split(), float)
numpy.set_printoptions(sign=' ')
print(numpy.floor(a))
print(numpy.ceil(a))
print(numpy.rint(a))
#ARRAY MATHEMATICS
import numpy
n,m=map(int,input().split())
a=numpy.array([input().split() for i in range(n)],dtype=int)
b=numpy.array([input().split() for i in range(n)],dtype=int)
print (a+b)
print (a-b)
print (a*b)
print (a//b)
print (a%b)
print (a**b)
#EYE AND IDENTITY
import numpy
n,m=map(int,input().split())
print (str(numpy.eye(n,m,k=0)).replace('1',' 1').replace('0',' 0'))
#ZEROS AND ONES
import numpy
num = tuple(map(int, input().split()))
print (numpy.zeros(num, dtype = numpy.int))
print (numpy.ones(num, dtype = numpy.int))
#CONCATENATE
import numpy
n,m,p=map(int,input().split())
arr1 = numpy.array([input().split() for _ in range(n)],int)
arr2 = numpy.array([input().split() for _ in range(m)],int)
print(numpy.concatenate((arr1, arr2), axis = 0))
#TRANSPOSE AND FLATTEN
import numpy
n, m = map(int, input().split())
mat = numpy.array([input().strip().split() for _ in range(n)], int)
trans=numpy.transpose(mat)
print (trans)
print (mat.flatten())
#SHAPE AND RESHAPE
import numpy
print (numpy.reshape(numpy.array(input().split(),int),(3,3)))
#ARRAYS
#DECORATORS 2 - NAME DIRECTORY
#STANDARDIZE MOBILE NUMBER USING DECORATORS
#XML2 - FIND THE MAXIMUM DEPTH
maxdepth = 0
#XML1 - FIND THE SCORE
k=[]
#MATRIX SCRIPT
#!/bin/python3
import math
import os
import random
import re
import sys
x,y = list(map(int,input().split()))
rows =[input() for i in range(x)]
text = "".join([row[i] for i in range(y) for row in rows])
text = re.sub('([A-Za-z1-9])[^A-Za-z1-9]+([A-Za-z1-9])', r'\1 \2', text)
text = re.sub(' ', ' ', text)
print(text)
first_multiple_input = input().rstrip().split()
n = int(first_multiple_input[0])
m = int(first_multiple_input[1])
matrix = []
for _ in range(n):
matrix_item = input()
matrix.append(matrix_item)
#VALIDATING POSTAL CODES
regex_integer_in_range = r"^[1-9][\d]{5}$" # Do not delete 'r'.
regex_alternating_repetitive_digit_pair = r"(\d)(?=\d\1)" # Do not delete 'r'.
#VALIDATING UID
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
for _ in range(int(input())):
u = ''.join(sorted(input()))
try:
assert re.search(r'[A-Z]{2}', u)
assert re.search(r'\d\d\d', u)
assert not re.search(r'[^a-zA-Z0-9]', u)
assert not re.search(r'(.)\1', u)
assert len(u) == 10
except:
print('Invalid')
else:
print('Valid')
#DETECT HTML TAGS, ATTRIBUTES AND ATTRIBUTE VALUES
# Enter your code here. Read input from STDIN. Print output to STDOUT
from html.parser import HTMLParser
html = '\n'.join([input() for _ in range(int(input()))])
parser = MyHTMLParser()
parser.feed(html)
parser.close()
#HTML PARSER - PART 2
from html.parser import HTMLParser
import re
html = ""
for i in range(int(input())):
html += input().rstrip()
html += '\n'
parser = MyHTMLParser()
parser.feed(html)
parser.close()
#HTML PARSER - PART 1
# Enter your code here. Read input from STDIN. Print output to STDOUT
from html.parser import HTMLParser
html = ""
for i in range(int(input())):
html += input()
parser = MyHTMLParser()
parser.feed(html)
parser.close()
#HEX COLOR CODE
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
reg = re.compile(r"(:|,| +)(#[abcdefABCDEF1234567890]{3}|#[abcdefABCDEF1234567890]{6})\b")
n = int(input())
for i in range(n):
line = input()
items = reg.findall(line)
if items:
for item in items:
print( item[1] )
#VALIDATING AND PARSING EMAIL ADDRESSES
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
import email.utils
pattern = re.compile(r"^[a-zA-Z][\w\-.]*@[a-zA-Z]+\.[a-zA-Z]{1,3}$")
for _ in range(int(input())):
u_name, u_email = email.utils.parseaddr(input())
if pattern.match(u_email):
print(email.utils.formataddr((u_name, u_email)))
#VALIDATING PHONE NUMBERS
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
n= int(input())
for i in range(n):
if (re.search(r"^[789]\d{9}$",input())):
print ('YES')
else:
print ('NO')
#VALIDATING ROMAN NUMERALS
regex_pattern = r"^(?=[MDCLXVI])M{0,3}(CM|CD|D?C{0,3})(XC|XL|L?X{0,3})(IX|IV|V?I{0,3})$" # Do not delete 'r'.
#REGEX SUBSTITUTION
## Enter your code here. Read input from STDIN. Print output to STDOUT
import re
N = int(input())
for i in range(N):
print (re.sub(r'(?<= )(&&|\|\|)(?= )', lambda x: 'and' if x.group() == '&&' else 'or', input()))
#RE.START() & RE.END()
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
S = input()
k = input()
pattern = re.compile(k)
r = pattern.search(S)
if not r: print ("(-1, -1)")
while r:
print ("({0}, {1})".format(r.start(), r.end() - 1))
r = pattern.search(S,r.start() + 1)
#RE.FINDALL() & RE.FINDITER()
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
consonanti = 'qwrtypsdfghjklzxcvbnm'
vocali = 'aeiou'
match = re.findall(r'(?<=['+consonanti+'])(['+vocali+']{2,})(?=['+consonanti+'])',input(),flags = re.I)
if match:
for i in match:
print (i)
else:
print (-1)
#GROUP(), GROUPS() & GROUPDICT()
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
m = re.search(r'([A-Za-z0-9])\1+',input())
if m:
print (m.group(1))
else:
print (-1)
#RE.SPLIT()
regex_pattern = r"[,.]" # Do not delete 'r'.
#DETECT FLOATING POINT NUMBER
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
for i in range(int(input())):
k = input()
print (bool(re.match(r'^[+-]?\d*?\.{1}\d+$',k)))
#GINORTS
# Enter your code here. Read input from STDIN. Print output to STDOUT
low=[]
upper=[]
odd=[]
even=[]
for i in sorted(input()):
if i.isalpha():
x = upper if i.isupper() else low
else:
x = odd if int(i)%2 else even
x.append(i)
print("".join(low+upper+odd+even))
#ATHLETE SORT
#!/bin/python3
import math
import os
import random
import re
import sys
if __name__ == '__main__':
nm = input().split()
n = int(nm[0])
m = int(nm[1])
arr = []
for _ in range(n):
arr.append(list(map(int, input().rstrip().split())))
k = int(input())
s = sorted(arr, key = lambda x: x[k])
for i in range(n):
print (str.join(' ', map(str, s[i])))
#ZIPPED!
# Enter your code here. Read input from STDIN. Print output to STDOUT
n,x= list(map(int,input().split()))
C=[]
for i in range (x):
C.append(list(map(float, input().split())))
for j in list(zip(*C)):
print (sum(j)/len(j))
#PILING UP!
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import defaultdict,deque
T = int(input())
D = defaultdict(list)
for i in range(T):
k = input()
D[i].append(list(map(int,input().split())))
for y in D:
l = D[y][0].index(min(D[y][0]))
if ordAsc(D[y][0][l:]):
print ('Yes')
else:
print ('No')
#COLLECTIONS.DEQUE()
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import deque
d = deque()
for i in range(int(input())):
com = input().split()
if com[0]=='append':
d.append(int(com[1]))
elif com[0]=='appendleft':
d.appendleft(int(com[1]))
elif com[0]=='pop':
d.pop()
else:
d.popleft()
for i in (d):
print (i,end=' ')
#WORD ORDER
# Enter your code here. Read input from STDIN. Print output to STDOUT
import collections;
N = int(input())
d = collections.OrderedDict()
for i in range(N):
word = input()
if word in d:
d[word] +=1
else:
d[word] = 1
print(len(d))
for k,v in d.items():
print(v,end = " ")
#COLLECTIONS.ORDEREDDICT()
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import OrderedDict
N = int(input());
d = OrderedDict();
for i in range(N):
item = input().split()
itemPrice = int(item[-1])
itemName = " ".join(item[:-1])
if(d.get(itemName)):
d[itemName] += itemPrice
else:
d[itemName] = itemPrice
for i in d.keys():
print(i, d[i])
#COLLECTIONS.NAMEDTUPLE()
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import namedtuple
n = int(input())
col = input()
a = 0
student = namedtuple("student", col)
for i in range (n):
stud = student._make(input().split())
a += int(stud.MARKS)
print ("{:.2f}".format(a/n))
#DEFAULTDICT TUTORIAL
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import defaultdict
n, m = map(int, input().split())
d = defaultdict(lambda: -1)
for i in range(1, n+1):
word = input()
d[word] = d[word] + ' ' + str(i) if word in d else str(i)
for _ in range(m):
print(d[input()])
#EXCEPTIONS
for test in range(int(input())):
try:
a,b = map(int,input().split())
division_result = a // b
print(division_result)
except ZeroDivisionError as e:
print("Error Code:", e)
except ValueError as e:
print("Error Code:", e)
#COLLECTIONS.COUNTER()
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import Counter
X = int(input())
shoes = [int(val) for val in input().split()]
N = int(input())
shoe_collection = Counter(shoes)
total_money = 0
for i in range(N):
size, money = [int(val) for val in input().split()]
if shoe_collection.get(size):
total_money += money
shoe_collection[size] -= 1
print(total_money)
#CHECK STRICT SUPERSET
# Enter your code here. Read input from STDIN. Print output to STDOUT
set_A = set(input().split())
n= int(input())
cnt = 0
check = True
for _ in range(n):
if not set_A.issuperset(set(input().split())):
check = False
break
print(check)
#CHECK SUBSET
# Enter your code here. Read input from STDIN. Print output to STDOUT
test_case=int(input())
for _ in range(test_case):
line_1, line_2 = int(input()), set(input().split())
line_3, line_4 = int(input()), set(input().split())
print(line_2.issubset(line_4))
#THE CAPTAIN'S ROOM
# Enter your code here. Read input from STDIN. Print output to STDOUT
k = input()
set_a= set()
set_b= set()
for room in (input().split()):
if room not in set_a:
set_a.add(room)
else:
set_b.add(room)
set_a.difference_update(set_b)
print(set_a.pop())
#SET MUTATIONS
# Enter your code here. Read input from STDIN. Print output to STDOUT
n=int(input())
a=set(map(int,input().split()))
m=int(input())
for _ in range (m):
com=(input().split())
s=set(map(int,input().split()))
if com[0]=='intersection_update':
a.intersection_update(s)
elif com[0]=='update':
a.update(s)
elif com[0]=='symmetric_difference_update':
a.symmetric_difference_update(s)
elif com[0]=='difference_update':
a.difference_update(s)
print (sum(map(int,a)))
#SET .SYMMETRIC_DIFFERENCE() OPERATION
# Enter your code here. Read input from STDIN. Print output to STDOUT
n =int(input())
e=set(input().split())
m=int(input())
f=set(input().split())
tot=len(e.symmetric_difference(f))
print (tot)
#SET .DIFFERENCE() OPERATION
# Enter your code here. Read input from STDIN. Print output to STDOUT
n =int(input())
e=set(input().split())
m=int(input())
f=set(input().split())
tot=len(e.difference(f))
print (tot)
#SET .INTERSECTION() OPERATION
# Enter your code here. Read input from STDIN. Print output to STDOUT
n =int(input())
e=set(input().split())
m=int(input())
f=set(input().split())
tot=len(e.intersection(f))
print (tot)
#SET .UNION() OPERATION
# Enter your code here. Read input from STDIN. Print output to STDOUT
n =int(input())
e=set(input().split())
m=int(input())
f=set(input().split())
tot=len(e.union(f))
print (tot)
#SET .DISCARD(), .REMOVE() & .POP()
n = int(input())
s = set(map(int, input().split()))
N = int(input())
for _ in range(N):
x = input().split()
if len(x) == 1:
s.pop()
elif x[0] == 'remove':
try:
s.remove(int(x[1]))
except:
next
elif x[0] == 'discard':
s.discard(int(x[1]))
print(sum(s))
#MAP AND LAMBDA FUNCTION
cube = lambda x: x*x*x# complete the lambda function
#SET .ADD()
# Enter your code here. Read input from STDIN. Print output to STDOUT
n=int(raw_input())
stamps=set(raw_input() for i in range (n))
tot=len(stamps)
print tot
#NO IDEA!
# Enter your code here. Read input from STDIN. Print output to STDOUT
n_m = map(int,raw_input().split())
n = map(int, raw_input().split())
A = set(map(int, raw_input().split()))
B = set(map(int, raw_input().split()))
happiness = 0
for i in n:
if i in A:
happiness += 1
elif i in B:
happiness -= 1
print happiness
#SYMMETRIC DIFFERENCE
# Enter your code here. Read input from STDIN. Print output to STDOUT
M = int(raw_input())
set_M = set(map(int,raw_input().split()))
N = int(raw_input())
set_N = set(map(int,raw_input().split()))
diff = (set_M.difference(set_N)).union(set_N.difference(set_M))
for i in sorted(list(diff)):
print i
#INTRODUCTION TO SETS
#CALENDAR MODULE
# Enter your code here. Read input from STDIN. Print output to STDOUT
import calendar
import calendar
k = map(int,raw_input().split())
m = calendar.weekday(k[2],k[0],k[1])
w = ['MONDAY','TUESDAY','WEDNESDAY','THURSDAY','FRIDAY','SATURDAY','SUNDAY']
print w[m]
#MERGE THE TOOLS!
#THE MINION GAME
#CAPITALIZE!
# Complete the solve function below.
#ALPHABET RANGOLI
#STRING FORMATTING
#DESIGNER DOOR MAT
# Enter your code here. Read input from STDIN. Print output to STDOUT
N, M = map(int,raw_input().split())
for i in xrange(0,N/2):
print ('.|.'*i).rjust((M-2)/2,'-')+'.|.'+('.|.'*i).ljust((M-2)/2,'-')
print 'WELCOME'.center(M,'-')
for i in reversed(xrange(0,N/2)):
print ('.|.'*i).rjust((M-2)/2,'-')+'.|.'+('.|.'*i).ljust((M-2)/2,'-')
#TEXT WRAP
#TEXT ALIGNMENT
# Enter your code here. Read input from STDIN. Print output to STDOUT
thickness = int(input()) # This must be an odd number
c = 'H'
# Top Cone
for i in range(thickness):
print((c * i).rjust(thickness - 1) + c + (c * i).ljust(thickness - 1))
# Top Pillars
for i in range(thickness + 1):
print((c * thickness).center(thickness * 2) + (c * thickness).center(thickness * 6))
# Middle Belt
for i in range((thickness + 1) // 2):
print((c * thickness * 5).center(thickness * 6))
# Bottom Pillars
for i in range(thickness + 1):
print((c * thickness).center(thickness * 2) + (c * thickness).center(thickness * 6))
# Bottom Cone
for i in range(thickness):
print(((c * (thickness - i - 1)).rjust(thickness) + c + (c * (thickness - i - 1)).ljust(thickness)).rjust(thickness * 6))
#STRING VALIDATORS
if __name__ == '__main__':
s = raw_input()
print (any(c.isalnum() for c in s))
print (any(c.isalpha() for c in s))
print (any(c.isdigit() for c in s))
print (any(c.islower() for c in s))
print (any(c.isupper() for c in s))
#FIND A STRING
#MUTATIONS
#WHAT'S YOUR NAME?
#STRING SPLIT AND JOIN
#SWAP CASE
#TUPLES
if __name__ == '__main__':
n = int(raw_input())
integer_list = map(int, raw_input().split())
t = tuple(integer_list)
print(hash(t))
#LISTS
if __name__ == '__main__':
N = int(raw_input())
lista = []
for i in range(N):
option = raw_input().split()
if option[0] == 'print':
print(lista)
elif option[0] == 'sort':
lista.sort()
elif option[0] == 'remove':
lista.remove(int(option[1]))
elif option[0] == 'append':
lista.append(int(option[1]))
elif option[0] == 'insert':
lista.insert(int(option[1]),int(option[2]))
elif option[0] == 'reverse':
lista.reverse()
elif option[0] == 'pop':
lista.pop()
#VALIDATING CREDIT CARD NUMBERS
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
for i in range(int(raw_input())):
S = raw_input().strip()
pre_match = re.search(r'^[456]\d{3}(-?)\d{4}\1\d{4}\1\d{4}$',S)
if pre_match:
processed_string = "".join(pre_match.group(0).split('-'))
final_match = re.search(r'(\d)\1{3,}',processed_string)
print 'Invalid' if final_match else 'Valid'
else:
print 'Invalid'
#LINEAR ALGEBRA
# Enter your code here. Read input from STDIN. Print output to STDOUT
import numpy
n=int(raw_input())
m=[]
for i in range(n):
m.append(map(float,raw_input().split()))
print round(numpy.linalg.det(numpy.array(m)),2)
#FINDING THE PERCENTAGE
if __name__ == '__main__':
n = int(raw_input())
student_marks = {}
for _ in range(n):
line = raw_input().split()
name, scores = line[0], line[1:]
scores = map(float, scores)
student_marks[name] = scores
query_name = raw_input()
l=list(student_marks[query_name])
length=len(l)
s=sum(l)
average=s/length
print('%.2f'%average)
#LIST COMPREHENSIONS
if __name__ == '__main__':
x = int(raw_input())
y = int(raw_input())
z = int(raw_input())
n = int(raw_input())
result=[[i,j,k] for i in range (x+1) for j in range (y+1) for k in range (z+1) if (i+j+k!=n)]
print (result)
#NESTED LISTS
from __future__ import print_function
score_list = {}
for _ in range(input()):
name = raw_input()
score = float(raw_input())
if score in score_list:
score_list[score].append(name)
else:
score_list[score] = [name]
new_list = []
for i in score_list:
new_list.append([i, score_list[i]])
new_list.sort()
result = new_list[1][1]
result.sort()
print (*result, sep = "\n")
#FIND THE RUNNER-UP SCORE!
if __name__ == '__main__':
n = int(raw_input())
arr = map(int, raw_input().split())
s1 = max(arr)
s2 = -9999999999
for i in range(n):
if arr[i] != s1 and arr[i] > s2:
s2 = arr[i]
print s2
#COMPRESS THE STRING!
# Enter your code here. Read input from STDIN. Print output to STDOUT
from __future__ import print_function
from itertools import *
for i,j in groupby(map(int,list(raw_input()))):
print(tuple([len(list(j)), i]) ,end = " ")
#COMPANY LOGO
# Enter your code here. Read input from STDIN. Print output to STDOUT
S = raw_input()
letters = [0]*26
for letter in S:
letters[ord(letter)-ord('a')] += 1
for _ in range(3):
max_letter = max(letters)
for index in range(26):
if max_letter == letters[index]:
print chr(ord('a')+index), max_letter
letters[index] = -1
break
#PRINT FUNCTION
from __future__ import print_function
if __name__ == '__main__':
n = int(input())
for i in range (n):
print (i+1,end="")
#WRITE A FUNCTION
#LOOPS
if __name__ == '__main__':
n = int(raw_input())
for i in range (n) :
if i<n:
print (i*i)
#PYTHON: DIVISION
from __future__ import division
if __name__ == '__main__':
a = int(raw_input())
b = int(raw_input())
print (a//b)
print (a/b)
#ARITHMETIC OPERATORS
if __name__ == '__main__':
a = int(raw_input())
b = int(raw_input())
print (a+b)
print (a-b)
print (a*b)
#PYTHON IF-ELSE
#!/bin/python
import math
import os
import random
import re
import sys
if __name__ == '__main__':
n = int(raw_input().strip())
if n in range (2,5):
if n%2==0:
print ("Not Weird")
else: print ("Weird")
elif n in range (6,20):
#if n%2==0:
#print ("Not Weird")
#else: print ("Weird")
print ("Weird")
elif n > 20:
if n%2==0:
print ("Not Weird")
else: print ("Weird")
else : print ("Weird")
#SAY "HELLO, WORLD!" WITH PYTHON
if __name__ == '__main__':
print "Hello, World!"
#SOLVE ME FIRST
num1 = int(input())
num2 = int(input())
res = solveMeFirst(num1,num2)
print(res)
| 22.941089 | 148 | 0.577298 | #INSERTION SORT - PART 2
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the insertionSort2 function below.
def insertionSort2(n, arr):
temp=[]
for q in range(1,n):
for i in range(q):
if(arr[q] < arr[i]):
temp=arr[q]
arr[q]=arr[i]
arr[i]=temp
print(' '.join(str(x) for x in arr))
if __name__ == '__main__':
n = int(input())
arr = list(map(int, input().rstrip().split()))
insertionSort2(n, arr)
#INSERTION SORT - PART 2
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the insertionSort1 function below.
def insertionSort1(n, arr):
probe = arr[-1]
for ind in range(len(arr)-2, -1, -1):
if arr[ind] > probe:
arr[ind+1] = arr[ind]
print(" ".join(map(str, arr)))
else:
arr[ind+1] = probe
print(" ".join(map(str, arr)))
break
if arr[0] > probe:
arr[0] = probe
print(" ".join(map(str, arr)))
if __name__ == '__main__':
n = int(input())
arr = list(map(int, input().rstrip().split()))
insertionSort1(n, arr)
#RECURSIVE DIGIT SUM
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the superDigit function below.
def superDigit(n, k):
n=int (n)
k=int (k)
p = (n * k) % 9
if p:
return p
else:
return 9
if __name__ == '__main__':
fptr = open(os.environ['OUTPUT_PATH'], 'w')
nk = input().split()
n = nk[0]
k = int(nk[1])
result = superDigit(n, k)
fptr.write(str(result) + '\n')
fptr.close()
#VIRAL ADVERTISING
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the viralAdvertising function below.
def viralAdvertising(n):
people = [2]
for i in range(n-1):
people.append(people[-1]*3//2)
tot=sum(people)
return tot
if __name__ == '__main__':
fptr = open(os.environ['OUTPUT_PATH'], 'w')
n = int(input())
result = viralAdvertising(n)
fptr.write(str(result) + '\n')
fptr.close()
#NUMBER LINE JUMPS
#!/bin/python3
import math
import os
import random
import re
import sys
# Complete the kangaroo function below.
def kangaroo(x1, v1, x2, v2):
if (v1 > v2) and not (x2 - x1) % (v2 - v1):
return ('YES')
else:
return ('NO')
if __name__ == '__main__':
fptr = open(os.environ['OUTPUT_PATH'], 'w')
x1V1X2V2 = input().split()
x1 = int(x1V1X2V2[0])
v1 = int(x1V1X2V2[1])
x2 = int(x1V1X2V2[2])
v2 = int(x1V1X2V2[3])
result = kangaroo(x1, v1, x2, v2)
fptr.write(result + '\n')
fptr.close()
#BIRTHDAY CAKE CANDLES
#!/bin/python3
import math
import os
import random
import re
import sys
#
# Complete the 'birthdayCakeCandles' function below.
#
# The function is expected to return an INTEGER.
# The function accepts INTEGER_ARRAY candles as parameter.
#
def birthdayCakeCandles(candles):
count=0
maxx=max(candles)
for i in (candles):
if i == maxx:
count= count +1
return count
if __name__ == '__main__':
fptr = open(os.environ['OUTPUT_PATH'], 'w')
candles_count = int(input().strip())
candles = list(map(int, input().rstrip().split()))
result = birthdayCakeCandles(candles)
fptr.write(str(result) + '\n')
fptr.close()
#POLYNOMIALS
import numpy
print(numpy.polyval(numpy.array(input().split(),float),int(input())))
#INNER AND OUTER
import numpy
a=numpy.array([input().split()], int)
b=numpy.array([input().split()], int)
print (int(numpy.inner(a,b)))
print (numpy.outer(a,b))
#DOT AND CROSS
import numpy
n=int(input())
a=numpy.array([input().split() for _ in range (n)],int)
b=numpy.array([input().split() for _ in range (n)], int)
print(numpy.dot(a,b))
#MEAN, VAR AND STD
import numpy
n,m=map(int,input().split())
arr=numpy.array([input().split() for _ in range (n)], int)
numpy.set_printoptions(sign=' ')
numpy.set_printoptions(legacy='1.13')
print (numpy.mean(arr, axis=1))
print (numpy.var(arr, axis=0))
print (numpy.std(arr, axis= None))
#MIN AND MAX
import numpy
n,m=map(int,input().split())
arr=numpy.array([input().split() for _ in range (n)], int)
minimum=numpy.min(arr, axis=1)
print(numpy.max(minimum))
#SUM AND PROD
import numpy
n,m=map(int,input().split())
arr=numpy.array([input().split() for _ in range (n)], int)
somma=numpy.sum(arr, axis=0)
print (numpy.prod(somma))
#FLOOR, CEIL AND RINT
import numpy
a=numpy.array(input().split(), float)
numpy.set_printoptions(sign=' ')
print(numpy.floor(a))
print(numpy.ceil(a))
print(numpy.rint(a))
#ARRAY MATHEMATICS
import numpy
n,m=map(int,input().split())
a=numpy.array([input().split() for i in range(n)],dtype=int)
b=numpy.array([input().split() for i in range(n)],dtype=int)
print (a+b)
print (a-b)
print (a*b)
print (a//b)
print (a%b)
print (a**b)
#EYE AND IDENTITY
import numpy
n,m=map(int,input().split())
print (str(numpy.eye(n,m,k=0)).replace('1',' 1').replace('0',' 0'))
#ZEROS AND ONES
import numpy
num = tuple(map(int, input().split()))
print (numpy.zeros(num, dtype = numpy.int))
print (numpy.ones(num, dtype = numpy.int))
#CONCATENATE
import numpy
n,m,p=map(int,input().split())
arr1 = numpy.array([input().split() for _ in range(n)],int)
arr2 = numpy.array([input().split() for _ in range(m)],int)
print(numpy.concatenate((arr1, arr2), axis = 0))
#TRANSPOSE AND FLATTEN
import numpy
n, m = map(int, input().split())
mat = numpy.array([input().strip().split() for _ in range(n)], int)
trans=numpy.transpose(mat)
print (trans)
print (mat.flatten())
#SHAPE AND RESHAPE
import numpy
print (numpy.reshape(numpy.array(input().split(),int),(3,3)))
#ARRAYS
def arrays(arr):
return numpy.array(arr[::-1], float)
#DECORATORS 2 - NAME DIRECTORY
def person_lister(f):
def inner(people):
return map(f, sorted(people, key=lambda x: int(x[2])))
return inner
#STANDARDIZE MOBILE NUMBER USING DECORATORS
def wrapper(f):
def fun(l):
f(["+91 "+c[-10:-5]+" "+c[-5:] for c in l])
return fun
#XML2 - FIND THE MAXIMUM DEPTH
maxdepth = 0
def depth(elem, level):
global maxdepth
level += 1
if (maxdepth < level):
maxdepth = level
for i in elem:
depth(i, level)
#XML1 - FIND THE SCORE
k=[]
def get_attr_number(node):
for elem in node.iter():
k.append(len(elem.attrib))
return sum(k)
#MATRIX SCRIPT
#!/bin/python3
import math
import os
import random
import re
import sys
x,y = list(map(int,input().split()))
rows =[input() for i in range(x)]
text = "".join([row[i] for i in range(y) for row in rows])
text = re.sub('([A-Za-z1-9])[^A-Za-z1-9]+([A-Za-z1-9])', r'\1 \2', text)
text = re.sub(' ', ' ', text)
print(text)
first_multiple_input = input().rstrip().split()
n = int(first_multiple_input[0])
m = int(first_multiple_input[1])
matrix = []
for _ in range(n):
matrix_item = input()
matrix.append(matrix_item)
#VALIDATING POSTAL CODES
regex_integer_in_range = r"^[1-9][\d]{5}$" # Do not delete 'r'.
regex_alternating_repetitive_digit_pair = r"(\d)(?=\d\1)" # Do not delete 'r'.
#VALIDATING UID
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
for _ in range(int(input())):
u = ''.join(sorted(input()))
try:
assert re.search(r'[A-Z]{2}', u)
assert re.search(r'\d\d\d', u)
assert not re.search(r'[^a-zA-Z0-9]', u)
assert not re.search(r'(.)\1', u)
assert len(u) == 10
except:
print('Invalid')
else:
print('Valid')
#DETECT HTML TAGS, ATTRIBUTES AND ATTRIBUTE VALUES
# Enter your code here. Read input from STDIN. Print output to STDOUT
from html.parser import HTMLParser
class MyHTMLParser(HTMLParser):
def handle_starttag(self, tag, attrs):
print(tag)
for attr in attrs:
print('-> {} > {}'.format(*attr))
html = '\n'.join([input() for _ in range(int(input()))])
parser = MyHTMLParser()
parser.feed(html)
parser.close()
#HTML PARSER - PART 2
from html.parser import HTMLParser
import re
class MyHTMLParser(HTMLParser):
def handle_comment(self, comment):
if '\n' in comment:
print('>>> Multi-line Comment')
else:
print('>>> Single-line Comment')
print(comment)
def handle_data(self, data):
if data == '\n': return
print('>>> Data')
print(data)
html = ""
for i in range(int(input())):
html += input().rstrip()
html += '\n'
parser = MyHTMLParser()
parser.feed(html)
parser.close()
#HTML PARSER - PART 1
# Enter your code here. Read input from STDIN. Print output to STDOUT
from html.parser import HTMLParser
class MyHTMLParser(HTMLParser):
def handle_starttag(self, tag, attrs):
print ('Start :',tag)
for attr in attrs:
print ('->',' > '.join(map(str,attr)))
def handle_endtag(self, tag):
print ('End :',tag)
def handle_startendtag(self, tag, attrs):
print ('Empty :',tag)
for attr in attrs:
print ('->',' > '.join(map(str,attr)))
html = ""
for i in range(int(input())):
html += input()
parser = MyHTMLParser()
parser.feed(html)
parser.close()
#HEX COLOR CODE
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
reg = re.compile(r"(:|,| +)(#[abcdefABCDEF1234567890]{3}|#[abcdefABCDEF1234567890]{6})\b")
n = int(input())
for i in range(n):
line = input()
items = reg.findall(line)
if items:
for item in items:
print( item[1] )
#VALIDATING AND PARSING EMAIL ADDRESSES
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
import email.utils
pattern = re.compile(r"^[a-zA-Z][\w\-.]*@[a-zA-Z]+\.[a-zA-Z]{1,3}$")
for _ in range(int(input())):
u_name, u_email = email.utils.parseaddr(input())
if pattern.match(u_email):
print(email.utils.formataddr((u_name, u_email)))
#VALIDATING PHONE NUMBERS
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
n= int(input())
for i in range(n):
if (re.search(r"^[789]\d{9}$",input())):
print ('YES')
else:
print ('NO')
#VALIDATING ROMAN NUMERALS
regex_pattern = r"^(?=[MDCLXVI])M{0,3}(CM|CD|D?C{0,3})(XC|XL|L?X{0,3})(IX|IV|V?I{0,3})$" # Do not delete 'r'.
#REGEX SUBSTITUTION
## Enter your code here. Read input from STDIN. Print output to STDOUT
import re
N = int(input())
for i in range(N):
print (re.sub(r'(?<= )(&&|\|\|)(?= )', lambda x: 'and' if x.group() == '&&' else 'or', input()))
#RE.START() & RE.END()
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
S = input()
k = input()
pattern = re.compile(k)
r = pattern.search(S)
if not r: print ("(-1, -1)")
while r:
print ("({0}, {1})".format(r.start(), r.end() - 1))
r = pattern.search(S,r.start() + 1)
#RE.FINDALL() & RE.FINDITER()
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
consonanti = 'qwrtypsdfghjklzxcvbnm'
vocali = 'aeiou'
match = re.findall(r'(?<=['+consonanti+'])(['+vocali+']{2,})(?=['+consonanti+'])',input(),flags = re.I)
if match:
for i in match:
print (i)
else:
print (-1)
#GROUP(), GROUPS() & GROUPDICT()
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
m = re.search(r'([A-Za-z0-9])\1+',input())
if m:
print (m.group(1))
else:
print (-1)
#RE.SPLIT()
regex_pattern = r"[,.]" # Do not delete 'r'.
#DETECT FLOATING POINT NUMBER
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
for i in range(int(input())):
k = input()
print (bool(re.match(r'^[+-]?\d*?\.{1}\d+$',k)))
#GINORTS
# Enter your code here. Read input from STDIN. Print output to STDOUT
low=[]
upper=[]
odd=[]
even=[]
for i in sorted(input()):
if i.isalpha():
x = upper if i.isupper() else low
else:
x = odd if int(i)%2 else even
x.append(i)
print("".join(low+upper+odd+even))
#ATHLETE SORT
#!/bin/python3
import math
import os
import random
import re
import sys
if __name__ == '__main__':
nm = input().split()
n = int(nm[0])
m = int(nm[1])
arr = []
for _ in range(n):
arr.append(list(map(int, input().rstrip().split())))
k = int(input())
s = sorted(arr, key = lambda x: x[k])
for i in range(n):
print (str.join(' ', map(str, s[i])))
#ZIPPED!
# Enter your code here. Read input from STDIN. Print output to STDOUT
n,x= list(map(int,input().split()))
C=[]
for i in range (x):
C.append(list(map(float, input().split())))
for j in list(zip(*C)):
print (sum(j)/len(j))
#PILING UP!
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import defaultdict,deque
T = int(input())
D = defaultdict(list)
def ordAsc(A):
return all(A[i] <= A[i+1] for i in range(len(A)-1))
for i in range(T):
k = input()
D[i].append(list(map(int,input().split())))
for y in D:
l = D[y][0].index(min(D[y][0]))
if ordAsc(D[y][0][l:]):
print ('Yes')
else:
print ('No')
#COLLECTIONS.DEQUE()
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import deque
d = deque()
for i in range(int(input())):
com = input().split()
if com[0]=='append':
d.append(int(com[1]))
elif com[0]=='appendleft':
d.appendleft(int(com[1]))
elif com[0]=='pop':
d.pop()
else:
d.popleft()
for i in (d):
print (i,end=' ')
#WORD ORDER
# Enter your code here. Read input from STDIN. Print output to STDOUT
import collections;
N = int(input())
d = collections.OrderedDict()
for i in range(N):
word = input()
if word in d:
d[word] +=1
else:
d[word] = 1
print(len(d))
for k,v in d.items():
print(v,end = " ")
#COLLECTIONS.ORDEREDDICT()
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import OrderedDict
N = int(input());
d = OrderedDict();
for i in range(N):
item = input().split()
itemPrice = int(item[-1])
itemName = " ".join(item[:-1])
if(d.get(itemName)):
d[itemName] += itemPrice
else:
d[itemName] = itemPrice
for i in d.keys():
print(i, d[i])
#COLLECTIONS.NAMEDTUPLE()
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import namedtuple
n = int(input())
col = input()
a = 0
student = namedtuple("student", col)
for i in range (n):
stud = student._make(input().split())
a += int(stud.MARKS)
print ("{:.2f}".format(a/n))
#DEFAULTDICT TUTORIAL
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import defaultdict
n, m = map(int, input().split())
d = defaultdict(lambda: -1)
for i in range(1, n+1):
word = input()
d[word] = d[word] + ' ' + str(i) if word in d else str(i)
for _ in range(m):
print(d[input()])
#EXCEPTIONS
for test in range(int(input())):
try:
a,b = map(int,input().split())
division_result = a // b
print(division_result)
except ZeroDivisionError as e:
print("Error Code:", e)
except ValueError as e:
print("Error Code:", e)
#COLLECTIONS.COUNTER()
# Enter your code here. Read input from STDIN. Print output to STDOUT
from collections import Counter
X = int(input())
shoes = [int(val) for val in input().split()]
N = int(input())
shoe_collection = Counter(shoes)
total_money = 0
for i in range(N):
size, money = [int(val) for val in input().split()]
if shoe_collection.get(size):
total_money += money
shoe_collection[size] -= 1
print(total_money)
#CHECK STRICT SUPERSET
# Enter your code here. Read input from STDIN. Print output to STDOUT
set_A = set(input().split())
n= int(input())
cnt = 0
check = True
for _ in range(n):
if not set_A.issuperset(set(input().split())):
check = False
break
print(check)
#CHECK SUBSET
# Enter your code here. Read input from STDIN. Print output to STDOUT
test_case=int(input())
for _ in range(test_case):
line_1, line_2 = int(input()), set(input().split())
line_3, line_4 = int(input()), set(input().split())
print(line_2.issubset(line_4))
#THE CAPTAIN'S ROOM
# Enter your code here. Read input from STDIN. Print output to STDOUT
k = input()
set_a= set()
set_b= set()
for room in (input().split()):
if room not in set_a:
set_a.add(room)
else:
set_b.add(room)
set_a.difference_update(set_b)
print(set_a.pop())
#SET MUTATIONS
# Enter your code here. Read input from STDIN. Print output to STDOUT
n=int(input())
a=set(map(int,input().split()))
m=int(input())
for _ in range (m):
com=(input().split())
s=set(map(int,input().split()))
if com[0]=='intersection_update':
a.intersection_update(s)
elif com[0]=='update':
a.update(s)
elif com[0]=='symmetric_difference_update':
a.symmetric_difference_update(s)
elif com[0]=='difference_update':
a.difference_update(s)
print (sum(map(int,a)))
#SET .SYMMETRIC_DIFFERENCE() OPERATION
# Enter your code here. Read input from STDIN. Print output to STDOUT
n =int(input())
e=set(input().split())
m=int(input())
f=set(input().split())
tot=len(e.symmetric_difference(f))
print (tot)
#SET .DIFFERENCE() OPERATION
# Enter your code here. Read input from STDIN. Print output to STDOUT
n =int(input())
e=set(input().split())
m=int(input())
f=set(input().split())
tot=len(e.difference(f))
print (tot)
#SET .INTERSECTION() OPERATION
# Enter your code here. Read input from STDIN. Print output to STDOUT
n =int(input())
e=set(input().split())
m=int(input())
f=set(input().split())
tot=len(e.intersection(f))
print (tot)
#SET .UNION() OPERATION
# Enter your code here. Read input from STDIN. Print output to STDOUT
n =int(input())
e=set(input().split())
m=int(input())
f=set(input().split())
tot=len(e.union(f))
print (tot)
#SET .DISCARD(), .REMOVE() & .POP()
n = int(input())
s = set(map(int, input().split()))
N = int(input())
for _ in range(N):
x = input().split()
if len(x) == 1:
s.pop()
elif x[0] == 'remove':
try:
s.remove(int(x[1]))
except:
next
elif x[0] == 'discard':
s.discard(int(x[1]))
print(sum(s))
#MAP AND LAMBDA FUNCTION
cube = lambda x: x*x*x# complete the lambda function
def fibonacci(n):
a = []
for i in range(n):
if i < 2:
a += [i]
else:
a += [a[-1] + a[-2]]
return a
#SET .ADD()
# Enter your code here. Read input from STDIN. Print output to STDOUT
n=int(raw_input())
stamps=set(raw_input() for i in range (n))
tot=len(stamps)
print tot
#NO IDEA!
# Enter your code here. Read input from STDIN. Print output to STDOUT
n_m = map(int,raw_input().split())
n = map(int, raw_input().split())
A = set(map(int, raw_input().split()))
B = set(map(int, raw_input().split()))
happiness = 0
for i in n:
if i in A:
happiness += 1
elif i in B:
happiness -= 1
print happiness
#SYMMETRIC DIFFERENCE
# Enter your code here. Read input from STDIN. Print output to STDOUT
M = int(raw_input())
set_M = set(map(int,raw_input().split()))
N = int(raw_input())
set_N = set(map(int,raw_input().split()))
diff = (set_M.difference(set_N)).union(set_N.difference(set_M))
for i in sorted(list(diff)):
print i
#INTRODUCTION TO SETS
def average(array):
# your code goes here
heights_dist = set(array)
sum_heights_dist = sum(heights_dist)
len_heights_dist = len(heights_dist)
avg = sum_heights_dist/len_heights_dist
return avg
#CALENDAR MODULE
# Enter your code here. Read input from STDIN. Print output to STDOUT
import calendar
import calendar
k = map(int,raw_input().split())
m = calendar.weekday(k[2],k[0],k[1])
w = ['MONDAY','TUESDAY','WEDNESDAY','THURSDAY','FRIDAY','SATURDAY','SUNDAY']
print w[m]
#MERGE THE TOOLS!
def merge_the_tools(string, k):
# your code goes here
for i in range(0,len(string), k):
line = string[i:i+k]
new = ""
for i in line:
if i not in new:
new+=i
print(new)
#THE MINION GAME
def minion_game(string):
# your code goes here
vowels_list = set(['a','e','i','o','u','A','E','I','O','U'])
consonants = 0
vowels = 0
n = len(string)
for i, l in enumerate(string):
if l in vowels_list:
vowels += n-i
else:
consonants += n-i
if vowels == consonants:
print "Draw"
elif vowels > consonants:
print "Kevin {}".format(vowels)
else:
print "Stuart {}".format(consonants)
#CAPITALIZE!
# Complete the solve function below.
def solve(s):
for i in s.split():
s = s.replace(i,i.capitalize())
return s
#ALPHABET RANGOLI
def print_rangoli(size):
# your code goes here
width = size*4-3
string = ''
for i in range(1,size+1):
for j in range(0,i):
string += chr(96+size-j)
if len(string) < width :
string += '-'
for k in range(i-1,0,-1):
string += chr(97+size-k)
if len(string) < width :
string += '-'
print(string.center(width,'-'))
string = ''
for i in range(size-1,0,-1):
string = ''
for j in range(0,i):
string += chr(96+size-j)
if len(string) < width :
string += '-'
for k in range(i-1,0,-1):
string += chr(97+size-k)
if len(string) < width :
string += '-'
print(string.center(width,'-'))
#STRING FORMATTING
def print_formatted(number):
# your code goes here
width = len("{0:b}".format(number)) + 1
for i in xrange(1, number + 1):
print "{0:d}".format(i).rjust(width - 1) + "{0:o}".format(i).rjust(width) + "{0:X}".format(i).rjust(width) + "{0:b}".format(i).rjust(width)
#DESIGNER DOOR MAT
# Enter your code here. Read input from STDIN. Print output to STDOUT
N, M = map(int,raw_input().split())
for i in xrange(0,N/2):
print ('.|.'*i).rjust((M-2)/2,'-')+'.|.'+('.|.'*i).ljust((M-2)/2,'-')
print 'WELCOME'.center(M,'-')
for i in reversed(xrange(0,N/2)):
print ('.|.'*i).rjust((M-2)/2,'-')+'.|.'+('.|.'*i).ljust((M-2)/2,'-')
#TEXT WRAP
def wrap(string, max_width):
return textwrap.fill(string, max_width)
#TEXT ALIGNMENT
# Enter your code here. Read input from STDIN. Print output to STDOUT
thickness = int(input()) # This must be an odd number
c = 'H'
# Top Cone
for i in range(thickness):
print((c * i).rjust(thickness - 1) + c + (c * i).ljust(thickness - 1))
# Top Pillars
for i in range(thickness + 1):
print((c * thickness).center(thickness * 2) + (c * thickness).center(thickness * 6))
# Middle Belt
for i in range((thickness + 1) // 2):
print((c * thickness * 5).center(thickness * 6))
# Bottom Pillars
for i in range(thickness + 1):
print((c * thickness).center(thickness * 2) + (c * thickness).center(thickness * 6))
# Bottom Cone
for i in range(thickness):
print(((c * (thickness - i - 1)).rjust(thickness) + c + (c * (thickness - i - 1)).ljust(thickness)).rjust(thickness * 6))
#STRING VALIDATORS
if __name__ == '__main__':
s = raw_input()
print (any(c.isalnum() for c in s))
print (any(c.isalpha() for c in s))
print (any(c.isdigit() for c in s))
print (any(c.islower() for c in s))
print (any(c.isupper() for c in s))
#FIND A STRING
def count_substring(string, sub_string):
count = 0
for i in range(len(string) - len(sub_string) + 1):
if string[i:i+len(sub_string)] == sub_string:
count += 1
return count
#MUTATIONS
def mutate_string(string, position, character):
l=list(string)
l[position]=character
string="".join(l)
return string
#WHAT'S YOUR NAME?
def print_full_name(a, b):
print ('Hello '+a+' '+b+'! You just delved into python.')
#STRING SPLIT AND JOIN
def split_and_join(line):
line=line.split(" ")
line="-".join(line)
return line
#SWAP CASE
def swap_case(s):
return s.swapcase()
#TUPLES
if __name__ == '__main__':
n = int(raw_input())
integer_list = map(int, raw_input().split())
t = tuple(integer_list)
print(hash(t))
#LISTS
if __name__ == '__main__':
N = int(raw_input())
lista = []
for i in range(N):
option = raw_input().split()
if option[0] == 'print':
print(lista)
elif option[0] == 'sort':
lista.sort()
elif option[0] == 'remove':
lista.remove(int(option[1]))
elif option[0] == 'append':
lista.append(int(option[1]))
elif option[0] == 'insert':
lista.insert(int(option[1]),int(option[2]))
elif option[0] == 'reverse':
lista.reverse()
elif option[0] == 'pop':
lista.pop()
#VALIDATING CREDIT CARD NUMBERS
# Enter your code here. Read input from STDIN. Print output to STDOUT
import re
for i in range(int(raw_input())):
S = raw_input().strip()
pre_match = re.search(r'^[456]\d{3}(-?)\d{4}\1\d{4}\1\d{4}$',S)
if pre_match:
processed_string = "".join(pre_match.group(0).split('-'))
final_match = re.search(r'(\d)\1{3,}',processed_string)
print 'Invalid' if final_match else 'Valid'
else:
print 'Invalid'
#LINEAR ALGEBRA
# Enter your code here. Read input from STDIN. Print output to STDOUT
import numpy
n=int(raw_input())
m=[]
for i in range(n):
m.append(map(float,raw_input().split()))
print round(numpy.linalg.det(numpy.array(m)),2)
#FINDING THE PERCENTAGE
if __name__ == '__main__':
n = int(raw_input())
student_marks = {}
for _ in range(n):
line = raw_input().split()
name, scores = line[0], line[1:]
scores = map(float, scores)
student_marks[name] = scores
query_name = raw_input()
l=list(student_marks[query_name])
length=len(l)
s=sum(l)
average=s/length
print('%.2f'%average)
#LIST COMPREHENSIONS
if __name__ == '__main__':
x = int(raw_input())
y = int(raw_input())
z = int(raw_input())
n = int(raw_input())
result=[[i,j,k] for i in range (x+1) for j in range (y+1) for k in range (z+1) if (i+j+k!=n)]
print (result)
#NESTED LISTS
from __future__ import print_function
score_list = {}
for _ in range(input()):
name = raw_input()
score = float(raw_input())
if score in score_list:
score_list[score].append(name)
else:
score_list[score] = [name]
new_list = []
for i in score_list:
new_list.append([i, score_list[i]])
new_list.sort()
result = new_list[1][1]
result.sort()
print (*result, sep = "\n")
#FIND THE RUNNER-UP SCORE!
if __name__ == '__main__':
n = int(raw_input())
arr = map(int, raw_input().split())
s1 = max(arr)
s2 = -9999999999
for i in range(n):
if arr[i] != s1 and arr[i] > s2:
s2 = arr[i]
print s2
#COMPRESS THE STRING!
# Enter your code here. Read input from STDIN. Print output to STDOUT
from __future__ import print_function
from itertools import *
for i,j in groupby(map(int,list(raw_input()))):
print(tuple([len(list(j)), i]) ,end = " ")
#COMPANY LOGO
# Enter your code here. Read input from STDIN. Print output to STDOUT
S = raw_input()
letters = [0]*26
for letter in S:
letters[ord(letter)-ord('a')] += 1
for _ in range(3):
max_letter = max(letters)
for index in range(26):
if max_letter == letters[index]:
print chr(ord('a')+index), max_letter
letters[index] = -1
break
#PRINT FUNCTION
from __future__ import print_function
if __name__ == '__main__':
n = int(input())
for i in range (n):
print (i+1,end="")
#WRITE A FUNCTION
def is_leap(year):
leap = False
# Write your logic here
if (year%4==0):
leap= True
if (year%100==0):
leap = False
if (year%400==0):
leap = True
return leap
#LOOPS
if __name__ == '__main__':
n = int(raw_input())
for i in range (n) :
if i<n:
print (i*i)
#PYTHON: DIVISION
from __future__ import division
if __name__ == '__main__':
a = int(raw_input())
b = int(raw_input())
print (a//b)
print (a/b)
#ARITHMETIC OPERATORS
if __name__ == '__main__':
a = int(raw_input())
b = int(raw_input())
print (a+b)
print (a-b)
print (a*b)
#PYTHON IF-ELSE
#!/bin/python
import math
import os
import random
import re
import sys
if __name__ == '__main__':
n = int(raw_input().strip())
if n in range (2,5):
if n%2==0:
print ("Not Weird")
else: print ("Weird")
elif n in range (6,20):
#if n%2==0:
#print ("Not Weird")
#else: print ("Weird")
print ("Weird")
elif n > 20:
if n%2==0:
print ("Not Weird")
else: print ("Weird")
else : print ("Weird")
#SAY "HELLO, WORLD!" WITH PYTHON
if __name__ == '__main__':
print "Hello, World!"
#SOLVE ME FIRST
def solveMeFirst(a,b):
# Hint: Type return a+b below
return a+b
num1 = int(input())
num2 = int(input())
res = solveMeFirst(num1,num2)
print(res)
| 5,305 | 30 | 869 |
10a3d9ad28e3984e397907e2c074ff656531eda3 | 11,551 | py | Python | dcplib/component_entities/ingest_entities.py | HumanCellAtlas/dcplib | 5d1bd939393640b9623b040f13db1c97d83bcabd | [
"MIT"
] | 3 | 2019-02-28T06:03:05.000Z | 2019-07-01T18:29:11.000Z | dcplib/component_entities/ingest_entities.py | HumanCellAtlas/dcplib | 5d1bd939393640b9623b040f13db1c97d83bcabd | [
"MIT"
] | 64 | 2018-07-27T05:43:46.000Z | 2020-01-04T14:17:59.000Z | dcplib/component_entities/ingest_entities.py | HumanCellAtlas/dcplib | 5d1bd939393640b9623b040f13db1c97d83bcabd | [
"MIT"
] | 3 | 2019-11-01T14:24:25.000Z | 2020-09-07T18:42:17.000Z | import json
from termcolor import colored
from dcplib.component_entities import EntityBase
class Project(EntityBase):
"""
Model an Ingest Project entity
"""
@classmethod
@classmethod
@property
@property
@property
@property
@property
@property
"""
Yields [name, role]
for contributors that have a role
"""
class SubmissionEnvelope(EntityBase):
"""
Model an Ingest Submission Envelope entity
"""
UNPROCESSED_STATUSES = ['Invalid', 'Draft', 'Valid', 'Pending', 'Validating']
@classmethod
@classmethod
@property
@property
@property
@property
@property
@property
def project(self):
""" Assumes only one project """
projects = self.projects()
if len(projects) != 1:
raise RuntimeError(f"Expect 1 project got {len(projects)}")
return projects[0]
def upload_credentials(self):
""" Return upload area credentials or None if this envelope doesn't have an upload area yet """
staging_details = self.data.get('stagingDetails', None)
if staging_details and 'stagingAreaLocation' in staging_details:
return staging_details.get('stagingAreaLocation', {}).get('value', None)
return None
def bundle_count(self):
"""An optimized version of bundle counting, using the fact that the HAL API returns
'totalElements' in the first response.
"""
bundle_manifest_url = self.data['_links']['bundleManifests']['href']
data = self.api.get(bundle_manifest_url)
return data['page']['totalElements']
class File:
"""
Model an Ingest File entity
"""
@property
@property
| 35.984424 | 119 | 0.630508 | import json
from termcolor import colored
from dcplib.component_entities import EntityBase
class Project(EntityBase):
"""
Model an Ingest Project entity
"""
@classmethod
def load_by_id(cls, project_id, ingest_api_agent):
data = ingest_api_agent.get(f"/projects/{project_id}")
return Project(project_data=data, ingest_api_agent=ingest_api_agent)
@classmethod
def load_by_uuid(cls, project_uuid, ingest_api_agent):
data = ingest_api_agent.get(f"/projects/search/findByUuid?uuid={project_uuid}")
return Project(project_data=data, ingest_api_agent=ingest_api_agent)
def __init__(self, project_data=None, ingest_api_agent=None):
self.api = ingest_api_agent
self.data = project_data
def __str__(self, prefix="", verbose=False):
return colored(f"{prefix}Project {self.id}\n", 'green') + \
f"{prefix} uuid={self.uuid}\n" \
f"{prefix} short_name={self.short_name}\n"
@property
def id(self):
return self.data['_links']['self']['href'].split('/')[-1]
@property
def uuid(self):
return self.data['uuid']['uuid']
@property
def short_name(self):
project_core = self.data['content']['project_core']
return project_core.get('project_short_name') or project_core.get('project_shortname')
@property
def title(self):
return self.data['content']['project_core']['project_title']
@property
def primary_investigator(self):
primary_investigator = ''
for name, role in self._iter_contributors():
if role == "principal investigator":
primary_investigator += f"{name}; "
return 'N/A' if primary_investigator == '' else primary_investigator
@property
def data_curator(self):
data_curator = ''
for name, role in self._iter_contributors():
if role == "data curator" or role == "Human Cell Atlas wrangler":
data_curator += f"{name}; "
return 'N/A' if data_curator == '' else data_curator
"""
Yields [name, role]
for contributors that have a role
"""
def _iter_contributors(self):
for contributor in self.data['content']['contributors']:
project_role = contributor.get('project_role')
if project_role:
if contributor.get('contact_name'):
name = contributor['contact_name']
else:
name = contributor['name']
if type(project_role) == str:
role_ontology_label = project_role
else:
role_ontology_label = project_role.get('ontology_label')
yield name, role_ontology_label
def print(self, prefix="", verbose=False, associated_entities_to_show=None):
print(self.__str__(prefix=prefix, verbose=verbose))
if associated_entities_to_show:
prefix = f"{prefix}\t"
if 'submissions' in associated_entities_to_show or 'all' in associated_entities_to_show:
for subm in self.submission_envelopes():
subm.print(prefix=prefix, verbose=verbose, associated_entities_to_show=associated_entities_to_show)
def submission_envelopes(self):
data = self.api.get(self.data['_links']['submissionEnvelopes']['href'])
return [
SubmissionEnvelope(submission_data=subm_data, ingest_api_agent=self.api)
for subm_data in data['_embedded']['submissionEnvelopes']
]
class Biomaterials(EntityBase):
def __init__(self, biomaterial_data=None, ingest_api_agent=None):
self.api = ingest_api_agent
self.data = biomaterial_data
@property
def species(self):
"""
:returns: an array of species
:rtype: list
"""
all_species = []
if self.data['content'].get('genus_species'):
genus_species = self.data['content']['genus_species']
for species in genus_species:
if species.get('ontology_label'):
all_species.append(species['ontology_label'])
elif species.get('text'):
all_species.append(species['text'])
return all_species
class Protocol(EntityBase):
def __init__(self, protocol_data=None, ingest_api_agent=None):
self.api = ingest_api_agent
self.data = protocol_data
@property
def library_construction_method(self):
"""
:return: library construction method or None
:rtype: str or None
"""
content = self.data['content']
method = content.get('library_construction_method') or content.get('library_construction_approach')
if method:
return method.get('ontology_label') or method.get('text')
else:
return None
class Process(EntityBase):
def __init__(self, process_data=None, ingest_api_agent=None):
self.api = ingest_api_agent
self.data = process_data
@property
def input_bundles(self):
"""
:return: input_bundles
:rtype: list
"""
content = self.data['content']
input_bundles = content.get('input_bundles', [])
return input_bundles
class SubmissionError(EntityBase):
def __init__(self, submission_error_data=None, ingest_api_agent=None):
self.api = ingest_api_agent
self.data = submission_error_data
class SubmissionEnvelope(EntityBase):
"""
Model an Ingest Submission Envelope entity
"""
UNPROCESSED_STATUSES = ['Invalid', 'Draft', 'Valid', 'Pending', 'Validating']
@classmethod
def load_by_id(cls, submission_id, ingest_api_agent):
data = ingest_api_agent.get(f"/submissionEnvelopes/{submission_id}")
return SubmissionEnvelope(submission_data=data, ingest_api_agent=ingest_api_agent)
@classmethod
def iter_submissions(cls, ingest_api_agent, page_size=500, sort_by='submissionDate,desc'):
for page in ingest_api_agent.iter_pages('/submissionEnvelopes', page_size=page_size, sort=sort_by):
for submission_data in page['submissionEnvelopes']:
yield SubmissionEnvelope(submission_data=submission_data, ingest_api_agent=ingest_api_agent)
def __init__(self, submission_data, ingest_api_agent):
self.data = submission_data
self.api = ingest_api_agent
self.envelope_id = self.data['_links']['self']['href'].split('/')[-1]
def __str__(self, prefix="", verbose=False):
return colored(f"{prefix}SubmissionEnvelope {self.envelope_id}\n", 'green') + \
f"{prefix} uuid={self.uuid}\n" \
f"{prefix} status={self.status}"
def print(self, prefix="", verbose=False, associated_entities_to_show=None):
print(self.__str__(prefix=prefix, verbose=verbose))
if associated_entities_to_show:
prefix = f"{prefix} "
if 'bundles' in associated_entities_to_show or 'all' in associated_entities_to_show:
if self.status == 'Complete':
print(colored(f"{prefix}Bundles:", 'cyan'))
for bundle in self.bundles():
print(prefix + " " + bundle)
if 'files' in associated_entities_to_show or 'all' in associated_entities_to_show:
print(colored(f"{prefix}Files:", 'cyan'))
for file in self.files():
file.print(prefix=prefix, verbose=verbose,
associated_entities_to_show=associated_entities_to_show)
@property
def submission_id(self):
return self.data['_links']['self']['href'].split('/')[-1]
@property
def status(self):
return self.data['submissionState']
@property
def submission_date(self):
return self.data['submissionDate']
@property
def update_date(self):
return self.data['updateDate']
@property
def uuid(self):
return self.data['uuid']['uuid']
@property
def is_unprocessed(self):
return self.status in self.UNPROCESSED_STATUSES
def files(self):
return [File(file_data) for file_data in
self.api.get_all(self.data['_links']['files']['href'], 'files')]
def iter_files(self):
url = self.data['_links']['files']['href']
for page in self.api.iter_pages(url):
for file in page['files']:
yield file
def projects(self):
return [Project(project_data=proj_data, ingest_api_agent=self.api) for proj_data in
self.api.get_all(self.data['_links']['projects']['href'], 'projects')]
def biomaterials(self):
return [Biomaterials(biomaterial_data, ingest_api_agent=self.api) for biomaterial_data in
self.api.get_all(self.data['_links']['biomaterials']['href'], 'biomaterials', page_size=20)]
def protocols(self):
return [Protocol(protocol_data, ingest_api_agent=self.api) for protocol_data in
self.api.get_all(self.data['_links']['protocols']['href'], 'protocols', page_size=1000)]
def processes(self):
return [Process(process_data, ingest_api_agent=self.api) for process_data in
self.api.get_all(self.data['_links']['processes']['href'], 'processes', page_size=20)]
def submission_errors(self):
return [SubmissionError(error_data, ingest_api_agent=self.api) for error_data in
self.api.get_all(self.data['_links']['submissionEnvelopeErrors']['href'],
'submissionErrors',
page_size=20)]
def project(self):
""" Assumes only one project """
projects = self.projects()
if len(projects) != 1:
raise RuntimeError(f"Expect 1 project got {len(projects)}")
return projects[0]
def upload_credentials(self):
""" Return upload area credentials or None if this envelope doesn't have an upload area yet """
staging_details = self.data.get('stagingDetails', None)
if staging_details and 'stagingAreaLocation' in staging_details:
return staging_details.get('stagingAreaLocation', {}).get('value', None)
return None
def bundle_count(self):
"""An optimized version of bundle counting, using the fact that the HAL API returns
'totalElements' in the first response.
"""
bundle_manifest_url = self.data['_links']['bundleManifests']['href']
data = self.api.get(bundle_manifest_url)
return data['page']['totalElements']
def bundles(self):
url = self.data['_links']['bundleManifests']['href']
manifests = self.api.get_all(url, 'bundleManifests')
return [manifest['bundleUuid'] for manifest in manifests]
class File:
"""
Model an Ingest File entity
"""
def __init__(self, file_data):
self._data = file_data
def __str__(self, prefix="", verbose=False):
return (f"{prefix} fileName {self.name}\n"
f"{prefix} cloudUrl {self.cloud_url}\n")
def __repr__(self):
return json.dumps(self._data, indent=2)
@property
def name(self):
return self._data['fileName']
@property
def cloud_url(self):
return self._data['cloudUrl']
def print(self, prefix="", verbose=False, associated_entities_to_show=None):
print(self.__str__(prefix=prefix, verbose=verbose))
| 7,331 | 1,346 | 1,126 |
759c72415bfc39b20572f269f71e73621613fbd8 | 2,264 | py | Python | AdamK2Ddyfuzja.py | AdamK1993r/Fizyka2DDyfuzjaCiep-a | b8796ebcad262b0a3376f07a92cd32d4e6f24022 | [
"MIT"
] | null | null | null | AdamK2Ddyfuzja.py | AdamK1993r/Fizyka2DDyfuzjaCiep-a | b8796ebcad262b0a3376f07a92cd32d4e6f24022 | [
"MIT"
] | null | null | null | AdamK2Ddyfuzja.py | AdamK1993r/Fizyka2DDyfuzjaCiep-a | b8796ebcad262b0a3376f07a92cd32d4e6f24022 | [
"MIT"
] | null | null | null | #!/usr/bin/python
import numpy as np
import time
import matplotlib.pyplot as plt
import random
NUM = 30
if __name__ == '__main__':
XX,YY,dx,dy = gen_lattice(1.0,1.0,NUM)
vmin = 0.0
vmax = 2.0
#start = 2.0*np.exp(-10.0*(np.power(XX-0.5,2)+np.power(YY-0.5,2)))
start = np.zeros((NUM,NUM))
for j in range(2000):
start[random.randrange(0,NUM-1,1)][random.randrange(0,NUM-1,1)] = random.random()+1
fig, ax = plt.subplots()
im = ax.imshow(start,origin='lower',vmin=vmin,vmax=vmax)
step = start
for i in range(600):
step = update(step,0.0004,dx,dy)
ax.cla()
im = ax.imshow(step,origin='lower',vmin=vmin,vmax=vmax)
ax.set_title("frame {}".format(i))
plt.pause(0.0001) | 30.186667 | 205 | 0.555212 | #!/usr/bin/python
import numpy as np
import time
import matplotlib.pyplot as plt
import random
NUM = 30
def gen_lattice(Lx,Ly,N=1024):
X = np.linspace(0.0,Lx,N)
Y = np.linspace(0.0,Ly,N)
XX, YY = np.meshgrid(X, Y)
dx = Lx/float(N-1)
dy = Ly/float(N-1)
return (XX,YY,dx,dy)
def update(arr,dt,dx,dy):
arrRegular = calculateDeltaRegular(arr, dt, dx, dy)
arrEdgeC = calculateDeltaEdge(arr,dt,dx,dy)
return arr + arrRegular + arrEdgeC
def calculateDeltaEdge(arr, dt, dx, dy):
tempArr = np.zeros((NUM,NUM))
for i in range (NUM-1):
tempArr[i][0] = (-0.5 * arr[i][1] + 0.5 * arr[i][2]) / dy
tempArr[i][NUM-1] = (-0.5 * arr[i][NUM-2] + 0.5 * arr[i][NUM-3]) / dy
for j in range (NUM-1):
tempArr[0][j] = (-0.5 * arr[1][j] + 0.5 * arr[2][j]) / dx
tempArr[NUM-1][j] = (-0.5 * arr[NUM-2][j] + 0.5 * arr[NUM-3][j]) / dx
tempArr[0][0] = (-0.5 * arr[1][1] + 0.5 * arr[2][2]) / dx*1.4
tempArr[NUM-1][0] = (-0.5 * arr[NUM-2][1] + 0.5 * arr[NUM-3][2]) / dx*1.4
tempArr[0][NUM-1] = (-0.5 * arr[1][NUM-2] + 0.5 * arr[2][NUM-3]) / dx*1.4
tempArr[NUM-1][NUM-1] = (-0.5 * arr[NUM-2][NUM-2] + 0.5 * arr[NUM-3][NUM-3]) / dx*1.4
tempArr *= dt
return tempArr
def calculateDeltaRegular(arr, dt, dx, dy):
tempArr = np.zeros((NUM,NUM))
for i in range (NUM):
for j in range(NUM):
if i > 0 and i < NUM - 1 and j > 0 and j < NUM - 1:
tempArr[i][j] = (0.67 * (arr[i+1][j] + arr[i-1][j] + arr[i][j+1] + arr[i][j-1] - (4 * arr[i][j])) + 0.33 * (arr[i+1][j+1] + arr[i-1][j+1] + arr[i+1][j-1] + arr[i-1][j-1] - (4 * arr[i][j]))) / (dx * dy)
tempArr *= dt
return tempArr
if __name__ == '__main__':
XX,YY,dx,dy = gen_lattice(1.0,1.0,NUM)
vmin = 0.0
vmax = 2.0
#start = 2.0*np.exp(-10.0*(np.power(XX-0.5,2)+np.power(YY-0.5,2)))
start = np.zeros((NUM,NUM))
for j in range(2000):
start[random.randrange(0,NUM-1,1)][random.randrange(0,NUM-1,1)] = random.random()+1
fig, ax = plt.subplots()
im = ax.imshow(start,origin='lower',vmin=vmin,vmax=vmax)
step = start
for i in range(600):
step = update(step,0.0004,dx,dy)
ax.cla()
im = ax.imshow(step,origin='lower',vmin=vmin,vmax=vmax)
ax.set_title("frame {}".format(i))
plt.pause(0.0001) | 1,405 | 0 | 92 |
cada438b053befc03d5921f042af35702d71b090 | 8,237 | py | Python | MachineLearning/checkNerualNetworkResults.py | ChanaRoss/Thesis | 39ab83d52055d401a3bb71da25b3458ad9196ecd | [
"Apache-2.0"
] | null | null | null | MachineLearning/checkNerualNetworkResults.py | ChanaRoss/Thesis | 39ab83d52055d401a3bb71da25b3458ad9196ecd | [
"Apache-2.0"
] | 9 | 2020-03-24T17:19:30.000Z | 2022-03-11T23:55:15.000Z | MachineLearning/checkNerualNetworkResults.py | ChanaRoss/Thesis | 39ab83d52055d401a3bb71da25b3458ad9196ecd | [
"Apache-2.0"
] | null | null | null | # mathematical imports -
import numpy as np
from matplotlib import pyplot as plt
from sklearn import metrics
from math import sqrt
import seaborn as sns
sns.set()
import torch
# load network imports -
import os
import sys
sys.path.insert(0, '/Users/chanaross/dev/Thesis/MachineLearning/forGPU/')
from CNN_LSTM_NeuralNet_LimitZerosV2 import Model
def createEventDistributionUber(previousEventMatrix, my_net, eventTimeWindow, startTime, endTime):
"""
this function calculates future events based on cnn lstm network
:param previousEventMatrix: event matrix of previous events
:param my_net: learned network
:param eventTimeWindow: time each event is opened (for output)
:param startTime: start time from which events are created
:param endTime: end time to create events (start and end time define the output sequence length)
:return: eventPos, eventTimeWindow, outputEventMat
"""
# previousEventMatrix is of size: [seq_len, x_size, y_size]
if endTime - startTime == 0: # should output one prediction
out_seq = 1
else:
out_seq = endTime - startTime
x_size = previousEventMatrix.shape[1]
y_size = previousEventMatrix.shape[2]
netEventOut = torch.zeros([out_seq, x_size, y_size])
for seq in range(out_seq):
tempEventMat = previousEventMatrix
input = getInputMatrixToNetwork(previousEventMatrix, my_net.cnn_input_dimension)
k = 0
for x in range(x_size):
for y in range(y_size): # calculate output for each grid_id
testOut = my_net.forward(input[:, :, :, :, k])
_, netEventOut[seq, x, y] = torch.max(torch.exp(testOut.data), 1)
k += 1
previousEventMatrix[0:-1, :, :] = tempEventMat[1:, :, :]
previousEventMatrix[-1, :, :] = netEventOut[seq, :, :]
# in the end netEventOut is a matrix of size [out_seq_len, size_x, size_y]
eventPos = []
eventTimes = []
for t in range(out_seq):
for x in range(x_size):
for y in range(y_size):
numEvents = netEventOut[t, x, y]
# print('at loc:' + str(x) + ',' + str(y) + ' num events:' + str(numEvents))
#for n in range(numEvents):
if numEvents > 0:
eventPos.append(np.array([x, y]))
eventTimes.append(t+startTime)
eventsPos = np.array(eventPos)
eventTimes = np.array(eventTimes)
eventsTimeWindow = np.column_stack([eventTimes, eventTimes + eventTimeWindow])
return eventsPos, eventsTimeWindow, netEventOut.detach().numpy()
if __name__ == '__main__':
main()
print('Done.') | 41.812183 | 135 | 0.673061 | # mathematical imports -
import numpy as np
from matplotlib import pyplot as plt
from sklearn import metrics
from math import sqrt
import seaborn as sns
sns.set()
import torch
# load network imports -
import os
import sys
sys.path.insert(0, '/Users/chanaross/dev/Thesis/MachineLearning/forGPU/')
from CNN_LSTM_NeuralNet_LimitZerosV2 import Model
def createRealEventsUberML_network(eventMatrix, startTime, endTime):
firstTime = startTime
if (endTime - startTime==0):
numTimeSteps = 1
else:
numTimeSteps = endTime - startTime
realMatOut = eventMatrix[ firstTime: firstTime + numTimeSteps, :, :]
return realMatOut
def getInputMatrixToNetwork(previousMat, sizeCnn):
# previousMat is of shape : [seq_len , size_x, size_y]
lenSeqIn = previousMat.shape[0]
lengthX = previousMat.shape[1]
lengthY = previousMat.shape[2]
temp2 = np.zeros(shape=(1, lenSeqIn, sizeCnn, sizeCnn, lengthX * lengthY))
tempPadded = np.zeros(shape=(lenSeqIn, lengthX + sizeCnn, lengthY + sizeCnn))
padding_size = np.floor_divide(sizeCnn, 2)
tempPadded[:, padding_size: padding_size + lengthX, padding_size: padding_size + lengthY] = previousMat
k = 0
for i in range(lengthX):
for j in range(lengthY):
try:
temp2[0, :, :, :, k] = tempPadded[:, i:i + sizeCnn, j: j + sizeCnn]
except:
print("couldnt create input for cnn ")
k += 1
xArr = temp2
if torch.cuda.is_available():
xTensor = torch.Tensor(xArr).cuda()
else:
xTensor = torch.Tensor(xArr)
# xTensor is of shape: [grid id, seq, x_cnn, y_cnn]
return xTensor
def createEventDistributionUber(previousEventMatrix, my_net, eventTimeWindow, startTime, endTime):
"""
this function calculates future events based on cnn lstm network
:param previousEventMatrix: event matrix of previous events
:param my_net: learned network
:param eventTimeWindow: time each event is opened (for output)
:param startTime: start time from which events are created
:param endTime: end time to create events (start and end time define the output sequence length)
:return: eventPos, eventTimeWindow, outputEventMat
"""
# previousEventMatrix is of size: [seq_len, x_size, y_size]
if endTime - startTime == 0: # should output one prediction
out_seq = 1
else:
out_seq = endTime - startTime
x_size = previousEventMatrix.shape[1]
y_size = previousEventMatrix.shape[2]
netEventOut = torch.zeros([out_seq, x_size, y_size])
for seq in range(out_seq):
tempEventMat = previousEventMatrix
input = getInputMatrixToNetwork(previousEventMatrix, my_net.cnn_input_dimension)
k = 0
for x in range(x_size):
for y in range(y_size): # calculate output for each grid_id
testOut = my_net.forward(input[:, :, :, :, k])
_, netEventOut[seq, x, y] = torch.max(torch.exp(testOut.data), 1)
k += 1
previousEventMatrix[0:-1, :, :] = tempEventMat[1:, :, :]
previousEventMatrix[-1, :, :] = netEventOut[seq, :, :]
# in the end netEventOut is a matrix of size [out_seq_len, size_x, size_y]
eventPos = []
eventTimes = []
for t in range(out_seq):
for x in range(x_size):
for y in range(y_size):
numEvents = netEventOut[t, x, y]
# print('at loc:' + str(x) + ',' + str(y) + ' num events:' + str(numEvents))
#for n in range(numEvents):
if numEvents > 0:
eventPos.append(np.array([x, y]))
eventTimes.append(t+startTime)
eventsPos = np.array(eventPos)
eventTimes = np.array(eventTimes)
eventsTimeWindow = np.column_stack([eventTimes, eventTimes + eventTimeWindow])
return eventsPos, eventsTimeWindow, netEventOut.detach().numpy()
def getPreviousEventMat(dataInputReal, start_time, in_seq_len = 5):
lastPreviousTime = start_time
previousEventMatrix = np.zeros(shape=(in_seq_len, dataInputReal.shape[1], dataInputReal.shape[2]))
if lastPreviousTime - in_seq_len >= 0: # there are enough previous events known to system
previousEventMatrix = dataInputReal[lastPreviousTime-in_seq_len:lastPreviousTime, :, :]
else: # need to pad results
previousEventMatrix[in_seq_len-lastPreviousTime:, :, :] = dataInputReal
return previousEventMatrix
def main():
# has results different from 0 but was trained on wrong input -
# network_path = '/Users/chanaross/dev/Thesis/MachineLearning/forGPU/GPU_results/limitedZero_500grid/'
# network_name = 'gridSize11_epoch4_batch5_torch.pkl'
network_path = '/Users/chanaross/dev/Thesis/MachineLearning/forGPU/GPU_results/limitedZero_updatedCode/'
network_name = 'gridSize11_epoch1_batch25_torch.pkl'
data_path = '/Users/chanaross/dev/Thesis/UberData/'
data_name = '3D_allDataLatLonCorrected_500gridpickle_30min.p'
# network_name = 'gridSize20_epoch608_batch9_torch.pkl'
# data_path = '/Users/chanaross/dev/Thesis/UberData/'
# data_name = '3D_allDataLatLonCorrected_500gridpickle_30min.p'
dataInputReal = np.load(data_path + data_name)
my_net = torch.load(network_path + network_name, map_location=lambda storage, loc: storage)
my_net.eval()
xmin = 0
xmax = dataInputReal.shape[0]
ymin = 0
ymax = dataInputReal.shape[1]
zmin = 48
dataInputReal = dataInputReal[xmin:xmax, ymin:ymax, zmin:] #shrink matrix size for fast training in order to test model
dataInputReal[dataInputReal > 1] = 1
# reshape input data for network format -
lengthT = dataInputReal.shape[2]
lengthX = dataInputReal.shape[0]
lengthY = dataInputReal.shape[1]
dataInputReal = dataInputReal.reshape(lengthT, lengthX, lengthY)
accuracy = []
accuracy1 = []
rmse = []
numEventsCreated = []
numEventsPredicted = []
for i in range(10):
print("run num:"+str(i))
# start_time = i+200
start_time = np.random.randint(10, dataInputReal.shape[0] - 10)
end_time = start_time + 0
realMatOut = createRealEventsUberML_network(dataInputReal, start_time, end_time)
previousEventMatrix = getPreviousEventMat(dataInputReal, start_time, my_net.sequence_size)
eventsPos, eventsTimeWindow, netEventOut = createEventDistributionUber(previousEventMatrix, my_net, 3, start_time, end_time)
rmse.append(sqrt(metrics.mean_squared_error(realMatOut.reshape(-1), netEventOut.reshape(-1))))
accuracy.append(np.sum(realMatOut == netEventOut) / (realMatOut.shape[0] * realMatOut.shape[1] * realMatOut.shape[2]))
realMatOut[realMatOut > 1] = 1
netEventOut[netEventOut > 1] = 1
accuracy1.append(np.sum(np.sum(realMatOut == netEventOut) / (realMatOut.shape[0] * realMatOut.shape[1] * realMatOut.shape[2])))
numEventsCreated.append(np.sum(realMatOut))
print("number of real events is:"+str(np.sum(realMatOut)))
numEventsPredicted.append(np.sum(netEventOut))
print("number of predicted events is:"+str(np.sum(netEventOut)))
print("run num:" + str(i) +", finished")
plt.scatter(range(len(accuracy)), 100 * np.array(accuracy))
plt.xlabel('run number [#]')
plt.ylabel('accuracy [%]')
plt.figure()
plt.scatter(range(len(rmse)), np.array(rmse))
plt.xlabel('run number [#]')
plt.ylabel('RMSE')
plt.figure()
plt.scatter(range(len(numEventsCreated)), np.array(numEventsCreated), label = "num real events")
plt.scatter(range(len(numEventsPredicted)), np.array(numEventsPredicted), label = "num predicted")
plt.xlabel('run number [#]')
plt.ylabel('num events created')
plt.legend()
plt.figure()
plt.scatter(range(len(accuracy1)), 100 * np.array(accuracy1))
print("average RMSE for 300 runs is:" + str(np.mean(np.array(rmse))))
print("average accuracy for 300 runs is:" + str(np.mean(np.array(accuracy))))
print("average corrected accuracy for 300 runs is:" + str(100*np.mean(np.array(accuracy1))))
plt.show()
return
if __name__ == '__main__':
main()
print('Done.') | 5,464 | 0 | 92 |
fdd9077d05d2b146e1dbcb3e01166e1802a1c7c5 | 2,230 | py | Python | examples/coco/check_dataset.py | knorth55/chainer-fcis | a3dcebf5c31395dbd4b596509707bc9fe91a06e0 | [
"MIT"
] | 45 | 2017-10-06T12:24:17.000Z | 2021-11-10T05:28:31.000Z | examples/coco/check_dataset.py | knorth55/chainer-fcis | a3dcebf5c31395dbd4b596509707bc9fe91a06e0 | [
"MIT"
] | 14 | 2017-10-13T11:03:54.000Z | 2018-12-12T04:48:35.000Z | examples/coco/check_dataset.py | knorth55/chainer-fcis | a3dcebf5c31395dbd4b596509707bc9fe91a06e0 | [
"MIT"
] | 10 | 2017-10-13T09:24:15.000Z | 2020-07-12T09:05:47.000Z | #!/usr/bin/env python
import chainercv
# import cv2
import fcis
from fcis.datasets.coco import COCOInstanceSegmentationDataset
import numpy as np
from train import get_keep_indices
from train import remove_zero_bbox
if __name__ == '__main__':
main()
| 28.961039 | 77 | 0.64574 | #!/usr/bin/env python
import chainercv
# import cv2
import fcis
from fcis.datasets.coco import COCOInstanceSegmentationDataset
import numpy as np
from train import get_keep_indices
from train import remove_zero_bbox
def check(dataset, model, i, target_height, max_width):
img_id = dataset.ids[i]
bboxes, masks, labels, _, _ = dataset._get_annotations(i)
orig_H = dataset.img_props[img_id]['height']
orig_W = dataset.img_props[img_id]['width']
resize_scale = fcis.utils.get_resize_scale(
(orig_H, orig_W), target_height, max_width)
resize_scale = fcis.utils.get_resize_scale(
(orig_H, orig_W), target_height, max_width)
H = int(round(resize_scale * orig_H))
W = int(round(resize_scale * orig_W))
scale = H / orig_H
bboxes = chainercv.transforms.resize_bbox(
bboxes, (orig_H, orig_W), (H, W))
indices = get_keep_indices(bboxes)
bboxes = bboxes[indices, :]
labels = labels[indices]
assert len(bboxes) == len(labels)
assert len(bboxes) > 0
for bbox in bboxes:
bbox = np.round(bbox).astype(np.int32)
mask_height = bbox[2] - bbox[0]
mask_width = bbox[3] - bbox[1]
if mask_height == 0 or mask_width == 0:
print('Detect zero size bbox')
print('i: {}'.format(i))
print('labels: {}'.format(labels))
print('scale: {}'.format(scale))
print('bboxes')
print(bboxes)
print('bbox')
print(bbox)
def main():
target_height = 600
max_width = 1000
print('preparing')
print('train_dataset load')
train_dataset = COCOInstanceSegmentationDataset(split='train2014')
print('train_dataset remove zero bbox')
train_dataset = remove_zero_bbox(train_dataset, target_height, max_width)
print('model load')
model = fcis.models.FCISResNet101()
print('finish preparing')
print('check running')
print('checking train dataset')
for i in range(0, len(train_dataset)):
check(train_dataset, model, i, target_height, max_width)
if i % 5000 == 0:
print('checking {}'.format(i))
print('finish checking train dataset')
if __name__ == '__main__':
main()
| 1,925 | 0 | 46 |
6011bffcbdfecc6022bb50c01e9cec768bbe0025 | 21,682 | py | Python | til/tilfile.py | aerosoul94/tilutil | 4851267baf1aca73c0fd27854d841ef768c2aff8 | [
"MIT"
] | 14 | 2019-02-15T15:14:57.000Z | 2022-01-24T18:06:36.000Z | til/tilfile.py | aerosoul94/tilutil | 4851267baf1aca73c0fd27854d841ef768c2aff8 | [
"MIT"
] | null | null | null | til/tilfile.py | aerosoul94/tilutil | 4851267baf1aca73c0fd27854d841ef768c2aff8 | [
"MIT"
] | 2 | 2020-11-06T10:21:14.000Z | 2022-01-24T07:30:13.000Z | import zlib
import io
from .datatypes import *
from .utils import *
class TypeString:
"""Representation of `qtype`."""
def __getitem__(self, x):
"""Index/slice typestring"""
if isinstance(x, slice):
if x.step is not None:
raise NotImplementedError(
"Type string slice does not handle stepping")
if x.stop is None:
return self._typestring[self._pos + x.start:]
else:
return self._typestring[self._pos + x.start:self._pos + x.stop]
return self._typestring[self._pos + x]
def __len__(self):
"""Get the length of the typestring"""
return len(self._typestring) - self._offset
def __iadd__(self, n):
"""Increment stream position"""
self._pos += n
return self
def seek(self, n):
""" ptr+=n """
self._pos += n
def get(self):
""" ptr_copy = ptr """
return TypeString(self._typestring, self._pos)
def peek_db(self, pos=0):
""" u8 val = *(u8*)ptr """
return self[pos]
def read_db(self, pos=0):
""" u8 val = *(u8*)ptr++"""
data = self[pos]
self.seek(1)
return data
def read_dt(self):
""" Reads 1 to 2 bytes.
Value Range: 0-0xFFFE
Usage: 16bit numbers
Returns:
int: Arbitrary value.
"""
val = self.read_db()
if val & 0x80:
val = ((val & 0x7f) | (self.read_db() << 7))
return val - 1
def read_de(self):
""" Reads 1 to 5 bytes
Value Range: 0-0xFFFFFFFF
Usage: Enum Deltas
Returns:
int: Delta value
"""
val = 0
while True:
b = self.read_db()
hi = val << 6
sign = (b & 0x80)
if not sign:
lo = b & 0x3f
else:
lo = 2 * hi
hi = b & 0x7f
val = lo | hi
if not sign:
break
return val
def read_da(self):
""" Reads 1 to 9 bytes.
ValueRange: 0x-0x7FFFFFFF, 0-0xFFFFFFFF
Usage: Arrays
Returns:
(bool, int, int): Status, number of elements, and base.
"""
a = 0
b = 0
da = 0
base = 0
nelem = 0
while True:
c = self.peek_db()
if c & 0x80 == 0:
break
self.seek(1)
da = (da << 7) | c & 0x7f
b += 1
if b >= 4:
z = self.peek_db()
if z != 0:
base = 0x10 * da | z & 0xf
nelem = (self.read_db() >> 4) & 7
while True:
c = self.peek_db()
if (c & 0x80) == 0:
break
self.seek(1)
nelem = (nelem << 7) | c & 0x7f
a += 1
if a >= 4:
return True, nelem, base
return False, nelem, base
@staticmethod
class TypeInfo:
"""Representation of tinfo_t."""
@staticmethod
class TypeData:
"""Represents the serialized type data."""
def get_name(self):
""" Get the name for this type.
Returns:
str: Type name.
"""
return self._name.decode("ascii")
def get_ordinal(self):
""" Get the type's ordinal/value.
Returns:
int: Ordinal or value for symbols.
"""
return self._ordinal
def get_type_string(self):
""" Get the serialized type info string.
Returns:
TypeString: Serialized type info string.
"""
return self._typestr
def get_fields(self):
""" Get the serialized field name p-list.
Returns:
TypeString: Serialized field names.
"""
return self._fields
def get_field_comments(self):
""" Get the serialized field comments p-list.
Returns:
TypeString: Serialized field comments.
"""
return self._fieldcmts
def get_comment(self):
""" Get the serialized comment p-list.
Returns:
TypeString: Serialized comments.
"""
return self._cmt
def set_type_info(self, tinfo):
""" Set TypeInfo object.
Args:
tinfo (TypeInfo): Input type info object.
"""
self._tinfo = tinfo
def get_type_info(self):
""" Get TypeInfo object.
Returns:
TypeInfo: Type info object.
"""
return self._tinfo
class Macro:
"""Represents a macro loaded from a bucket.
TODO: Should probably be merged with TypeData.
"""
# TIL values for `flags`
TIL_ZIP = 0x0001
TIL_MAC = 0x0002
TIL_ESI = 0x0004
TIL_UNI = 0x0008
TIL_ORD = 0x0010
TIL_ALI = 0x0020
TIL_MOD = 0x0040
TIL_STM = 0x0080
TIL_SLD = 0x0100
class TILBucket:
"""Handle's unpacking a single TIL bucket."""
def __iter__(self):
"""Yields a type from the type list.
Returns:
Union[TypeData,Macro]: Serialized type data.
"""
for typ in self._types:
yield typ
class TILHeader:
"""Parses the TIL header."""
class TIL:
"""Represents a single TIL file."""
def _read_header(self):
"""Read the TIL header."""
self._stream.seek(0)
self._header = TILHeader(self._stream)
def _read_buckets(self):
"""Read each bucket."""
self._syms = TILBucket(self._header.flag & 0xCF, self._stream)
self._types = TILBucket(self._header.flag, self._stream)
self._macros = TILBucket(self._header.flag & 0xCF, self._stream)
self._load_bucket(self._syms)
self._load_bucket(self._types)
self._load_macros(self._macros)
self._process_bucket(self._syms)
self._process_bucket(self._types)
def deserialize(self, typestr, fields, fieldcmts):
""" Deserialize a TypeString into a TypeInfo object.
Args:
typestr (TypeString): Input serialized type string.
fields (TypeString): Input serialized fields p-list.
fieldcmts (TypeString): Input serialized field comments p-list.
Returns:
TypeInfo: Output TypeInfo object.
"""
typ = typestr.peek_db()
base = typ & TYPE_BASE_MASK
flags = typ & TYPE_FLAGS_MASK
if base <= BT_LAST_BASIC:
typestr += 1
return TypeInfo(typ)
if base > BT_LAST_BASIC:
typedata = None
if base == BT_COMPLEX and flags != BTMT_TYPEDEF:
t = typestr.get()
t += 1
N = t.read_complex_n()
if N == 0:
typedata = TypedefTypeData()
typedata.name = t.read_pstring().decode("ascii")
# I don't like this, we're going to need to come up with a
# way to do this automatically
typestr += t.pos()
return TypeInfo.create_type_info(typ, typedata)
if base == BT_PTR:
typedata = PointerTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif base == BT_ARRAY:
typedata = ArrayTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif base == BT_FUNC:
typedata = FuncTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif base == BT_COMPLEX:
if flags == BTMT_STRUCT or flags == BTMT_UNION:
typedata = UdtTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif flags == BTMT_ENUM:
typedata = EnumTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif flags == BTMT_TYPEDEF:
typedata = TypedefTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif base == BT_BITFIELD:
typedata = BitfieldTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
return TypeInfo.create_type_info(typ, typedata)
def serialize(self, tinfo, typestr):
""" Serialize a TypeInfo object into a TypeString.
Args:
tinfo (TypeInfo): Input TypeInfo object.
typestr (TypeString): Output TypeString.
"""
typ = tinfo.get_decl_type()
base = typ & TYPE_BASE_MASK
if base <= BT_LAST_BASIC:
typestr.append_db(typ)
return
if base > BT_LAST_BASIC:
details = tinfo.get_type_details()
if details is not None:
details.serialize(self, tinfo, typestr)
def get_header(self):
""" Get header information.
Returns:
TILHeader: The header information.
"""
return self._header
def get_syms(self):
""" Get the symbol bucket.
Returns:
TILBucket: The symbol bucket.
"""
return self._syms
def get_types(self):
""" Get the type bucket.
Returns:
TILBucket: The type bucket.
"""
return self._types
def get_macros(self):
""" Get the macro bucket.
Returns:
TILBucket: The macro bucket.
"""
return self._macros
def get_named_type(self, name, is_type):
""" Get named typeinfo.
Args:
name (str): The name of the type.
is_type (bool): True if this is a type and otherwise for symbols.
Returns:
TypeData: The serialized type data.
"""
bucket = self._types if is_type else self._syms
for type_data in bucket.get_types():
if name == type_data.get_name():
return type_data
return None
| 29.660739 | 94 | 0.52961 | import zlib
import io
from .datatypes import *
from .utils import *
class TypeString:
"""Representation of `qtype`."""
def __init__(self, data=None, pos=0):
if data is None:
data = bytearray()
self._offset = pos
self._pos = pos
self._typestring = bytearray(data)
def __getitem__(self, x):
"""Index/slice typestring"""
if isinstance(x, slice):
if x.step is not None:
raise NotImplementedError(
"Type string slice does not handle stepping")
if x.stop is None:
return self._typestring[self._pos + x.start:]
else:
return self._typestring[self._pos + x.start:self._pos + x.stop]
return self._typestring[self._pos + x]
def __len__(self):
"""Get the length of the typestring"""
return len(self._typestring) - self._offset
def __iadd__(self, n):
"""Increment stream position"""
self._pos += n
return self
def __eq__(self, other):
return self.data() == other.data()
def data(self):
return self._typestring
def pos(self):
return self._pos - self._offset
def peek(self, n, pos=0):
return self[pos:pos+n]
def read(self, n, pos=0):
data = self[pos:pos+n]
self.seek(n)
return data
def append(self, data):
self._typestring += data
def seek(self, n):
""" ptr+=n """
self._pos += n
def get(self):
""" ptr_copy = ptr """
return TypeString(self._typestring, self._pos)
def peek_db(self, pos=0):
""" u8 val = *(u8*)ptr """
return self[pos]
def read_db(self, pos=0):
""" u8 val = *(u8*)ptr++"""
data = self[pos]
self.seek(1)
return data
def read_dt(self):
""" Reads 1 to 2 bytes.
Value Range: 0-0xFFFE
Usage: 16bit numbers
Returns:
int: Arbitrary value.
"""
val = self.read_db()
if val & 0x80:
val = ((val & 0x7f) | (self.read_db() << 7))
return val - 1
def read_de(self):
""" Reads 1 to 5 bytes
Value Range: 0-0xFFFFFFFF
Usage: Enum Deltas
Returns:
int: Delta value
"""
val = 0
while True:
b = self.read_db()
hi = val << 6
sign = (b & 0x80)
if not sign:
lo = b & 0x3f
else:
lo = 2 * hi
hi = b & 0x7f
val = lo | hi
if not sign:
break
return val
def read_da(self):
""" Reads 1 to 9 bytes.
ValueRange: 0x-0x7FFFFFFF, 0-0xFFFFFFFF
Usage: Arrays
Returns:
(bool, int, int): Status, number of elements, and base.
"""
a = 0
b = 0
da = 0
base = 0
nelem = 0
while True:
c = self.peek_db()
if c & 0x80 == 0:
break
self.seek(1)
da = (da << 7) | c & 0x7f
b += 1
if b >= 4:
z = self.peek_db()
if z != 0:
base = 0x10 * da | z & 0xf
nelem = (self.read_db() >> 4) & 7
while True:
c = self.peek_db()
if (c & 0x80) == 0:
break
self.seek(1)
nelem = (nelem << 7) | c & 0x7f
a += 1
if a >= 4:
return True, nelem, base
return False, nelem, base
def read_complex_n(self):
n = self.read_dt()
if n == 0x7FFE:
n = self.read_de()
return n
def read_pstring(self):
length = self.read_dt()
return self.read(length)
def append_db(self, n):
self._typestring.append(n)
def append_dt(self, n):
if n > 0x7ffe:
raise ValueError("Value too high for append_dt")
lo = n + 1
hi = n + 1
if lo > 127:
self.append_db(lo & 0x7f | 0x80)
hi = (lo >> 7) & 0xff
self.append_db(hi)
def append_de(self, n):
buf = bytearray()
if n & 0xf8000000:
buf.append(((n >> 0x1b) & 0x7f) | 0x80)
buf.append(((n >> 0x14) & 0x7f) | 0x80)
buf.append(((n >> 0xd) & 0x7f) | 0x80)
buf.append(((n >> 0x6) & 0x7f) | 0x80)
elif n & 0x7f00000:
buf.append(((n >> 0x14) & 0x7f) | 0x80)
buf.append(((n >> 0xd) & 0x7f) | 0x80)
buf.append(((n >> 0x6) & 0x7f) | 0x80)
elif n & 0xfe000:
buf.append(((n >> 0xd) & 0x7f) | 0x80)
buf.append(((n >> 0x6) & 0x7f) | 0x80)
elif n & 0x1fc0:
buf.append(((n >> 6) & 0x7f) | 0x80)
buf.append((n & 0x3f) | 0x40)
self.append(buf)
def append_da(self, n1, n2):
buf = bytearray()
# Stores 32 bits for n2 and 31 bits for n1
buf.append(((n2 >> 0x19) & 0x7f) | 0x80)
buf.append(((n2 >> 0x12) & 0x7f) | 0x80)
buf.append(((n2 >> 0xb) & 0x7f) | 0x80)
buf.append(((n2 >> 0x4) & 0x7f) | 0x80)
buf.append(((n1 >> 0x18) & 0x70) | ((n2 >> 0) & 0x0f) | 0x80)
buf.append(((n1 >> 0x15) & 0x7f) | 0x80)
buf.append(((n1 >> 0xe) & 0x7f) | 0x80)
buf.append(((n1 >> 0x7) & 0x7f) | 0x80)
buf.append((n1 & 0x7f) | 0x80)
self._typestring += buf
def append_complex_n(self, n, is_empty):
if n < 0x7ffe and is_empty is False:
self.append_dt(n)
else:
self.append_db(0xff)
self.append_db(0xff)
self.append_de(n)
def append_pstring(self, string):
self.append_dt(len(string))
self.append(string.encode("ascii"))
def is_tah_byte(self):
return self.peek_db() == TAH_BYTE
def is_sdacl_byte(self):
return ((self.peek_db() & ~TYPE_FLAGS_MASK)
^ TYPE_MODIF_MASK) <= BT_VOID
def parse_type_attr(self):
tah = self.read_db()
tmp = ((tah & 1) | ((tah >> 3) & 6)) + 1
res = 0
if tah == TAH_BYTE or tmp == 8:
if tmp == 8:
res = tmp
next_byte = self.read_db()
shift = 0
while True:
res |= (next_byte & 0x7f) << shift
if next_byte & 0x80 == 0:
break
shift += 7
next_byte = self.read_db()
if next_byte == 0:
raise ValueError("parse_type_attr(): failed to parse")
if res & TAH_HASATTRS:
# deserialize type_attrs_t
val = self.read_dt()
for _ in range(val):
key = self.read_pstring()
val = self.read_pstring()
return res
def read_type_attr(self):
if self.is_tah_byte():
return self.parse_type_attr()
def read_sdacl_attr(self):
if self.is_sdacl_byte():
return self.parse_type_attr()
@staticmethod
def read_typestring(stream):
typestring = bytearray()
while True:
b = stream.read(1)
typestring += b
if b == b'\0':
break
return TypeString(typestring)
class TypeInfo:
"""Representation of tinfo_t."""
def __init__(self, base_type=BT_UNK):
self._type = base_type
self._flags = 0
# TODO: Should create a new class TypeDetails to store missing info
self._typedetails = None
def get_decl_type(self):
return self._type
def get_base_type(self):
return self._type & TYPE_BASE_MASK
def get_type_flags(self):
return self._type & TYPE_FLAGS_MASK
def get_full_type(self):
return self._type & TYPE_FULL_MASK
def get_type_details(self):
return self._typedetails
def is_ptr(self):
return self.get_base_type() == BT_PTR
def is_array(self):
return self.get_base_type() == BT_ARRAY
def is_func(self):
return self.get_base_type() == BT_FUNC
def is_bitfield(self):
return self.get_base_type() == BT_BITFIELD
def print_type(self, name):
if self._typedetails:
datatype = self._typedetails.print_type(name)
if datatype is None:
print("{} is None".format(name))
return "{};\n".format(datatype)
#
# datatype = print_type(self, name)
# return f"{datatype} {name};\n"
@staticmethod
def create_type_info(base, details=None):
tinfo = TypeInfo(base)
tinfo._typedetails = details
return tinfo
class TypeData:
"""Represents the serialized type data."""
def __init__(self, stream, format):
self._stream = stream
self._type = 0 # BT_UNK
self._tinfo = None # Should be filled in by deserialize
self._read(format)
def _read(self, format):
self._flags = u32(self._stream)
self._name = cstring(self._stream)
if self._flags not in (0x7fffffff, 0xffffffff):
raise ValueError("Invalid flags")
# Format below 0x12 does not have 64 bit ordinal's
if format < 0x12:
self._flags &= 0x7fffffff
# For symbols, this is the value
self._ordinal = u64(self._stream) if bool(self._flags >> 31) \
else u32(self._stream)
self._typestr = TypeString.read_typestring(self._stream)
self._cmt = cstring(self._stream)
self._fields = TypeString.read_typestring(self._stream)
self._fieldcmts = TypeString.read_typestring(self._stream)
self._sclass = u8(self._stream)
def __repr__(self):
return self.get_name()
def get_name(self):
""" Get the name for this type.
Returns:
str: Type name.
"""
return self._name.decode("ascii")
def get_ordinal(self):
""" Get the type's ordinal/value.
Returns:
int: Ordinal or value for symbols.
"""
return self._ordinal
def get_type_string(self):
""" Get the serialized type info string.
Returns:
TypeString: Serialized type info string.
"""
return self._typestr
def get_fields(self):
""" Get the serialized field name p-list.
Returns:
TypeString: Serialized field names.
"""
return self._fields
def get_field_comments(self):
""" Get the serialized field comments p-list.
Returns:
TypeString: Serialized field comments.
"""
return self._fieldcmts
def get_comment(self):
""" Get the serialized comment p-list.
Returns:
TypeString: Serialized comments.
"""
return self._cmt
def set_type_info(self, tinfo):
""" Set TypeInfo object.
Args:
tinfo (TypeInfo): Input type info object.
"""
self._tinfo = tinfo
def get_type_info(self):
""" Get TypeInfo object.
Returns:
TypeInfo: Type info object.
"""
return self._tinfo
class Macro:
"""Represents a macro loaded from a bucket.
TODO: Should probably be merged with TypeData.
"""
def __init__(self, stream):
self._name = cstring(stream)
self._nparams = u8(stream)
self._isfunc = bool(u8(stream))
self._value = cstring(stream)
def get_name(self):
name = self._name.decode("ascii")
if self._isfunc:
name += "("
for n in range(self._nparams):
name += 'a' + str(n)
if n != self._nparams - 1:
name += ","
name += ")"
return name
def get_value(self):
# TODO: I don't expect this to be reliable.
# This may break when a macro contains a token named 'a' + some number (example: a0)
# It may also break if nparams > 0x7f
value = self._value
if self._isfunc:
# Each argument is encoded as 0x80 | (n) where n is the param index.
# Decode arguments to strings in the format 'a' + str(param index).
value = b""
start = 0
for i, b in enumerate(self._value):
if b & 0x80:
# Copy the text in between this encoded argument and the last one.
value += self._value[start:i]
value += b'a' + bytearray(str(b & 0x7f), encoding='ascii')
start = i+1
value += self._value[start:]
return value.decode("ascii")
def print_type(self):
return "#define {} {}\n".format(self.get_name(), self.get_value())
# TIL values for `flags`
TIL_ZIP = 0x0001
TIL_MAC = 0x0002
TIL_ESI = 0x0004
TIL_UNI = 0x0008
TIL_ORD = 0x0010
TIL_ALI = 0x0020
TIL_MOD = 0x0040
TIL_STM = 0x0080
TIL_SLD = 0x0100
class TILBucket:
"""Handle's unpacking a single TIL bucket."""
def __init__(self, flags, stream):
self._types = []
if flags & TIL_ORD:
self.nords = u32(stream) # Number of ordinals
self.ndefs = u32(stream) # Number of definitions
self.size = u32(stream) # Size of uncompressed buffer
self.buffer = None # Buffer
if flags & TIL_ZIP:
csize = u32(stream)
self.buffer = zlib.decompress(stream.read(csize))
else:
self.buffer = stream.read(self.size)
def add_type(self, t):
self._types.append(t)
def get_types(self):
return self._types
def __iter__(self):
"""Yields a type from the type list.
Returns:
Union[TypeData,Macro]: Serialized type data.
"""
for typ in self._types:
yield typ
class TILHeader:
"""Parses the TIL header."""
def __init__(self, stream):
self._stream = stream
self._read()
def _read(self):
self.sig = self._stream.read(6)
if self.sig != b'IDATIL':
raise ValueError("Unexpected TIL signature")
self.form = u32(self._stream)
if self.form > 0x12:
raise ValueError("Unexpected TIL format")
self.flag = u32(self._stream)
self.titlelen = u8(self._stream)
self.title = self._stream.read(self.titlelen)
self.baselen = u8(self._stream)
self.base = self._stream.read(self.baselen)
self.id = u8(self._stream)
self.cm = u8(self._stream)
self.size_i = u8(self._stream)
self.size_b = u8(self._stream)
self.size_e = u8(self._stream)
self.defalign = u8(self._stream)
if self.flag & 0x4:
self.size_s = u8(self._stream)
self.size_l = u8(self._stream)
self.size_ll = u8(self._stream)
if self.flag & 0x100:
self.size_ldbl = u8(self._stream)
class TIL:
"""Represents a single TIL file."""
def __init__(self, stream):
self._stream = stream
self._header = None
self._typeinfos = []
self._read_header()
self._read_buckets()
def _read_header(self):
"""Read the TIL header."""
self._stream.seek(0)
self._header = TILHeader(self._stream)
def _read_buckets(self):
"""Read each bucket."""
self._syms = TILBucket(self._header.flag & 0xCF, self._stream)
self._types = TILBucket(self._header.flag, self._stream)
self._macros = TILBucket(self._header.flag & 0xCF, self._stream)
self._load_bucket(self._syms)
self._load_bucket(self._types)
self._load_macros(self._macros)
self._process_bucket(self._syms)
self._process_bucket(self._types)
def _load_bucket(self, bucket):
buffer = io.BytesIO(bucket.buffer)
for _ in range(bucket.ndefs):
bucket.add_type(TypeData(buffer, self._header.form))
def _load_macros(self, bucket):
buffer = io.BytesIO(bucket.buffer)
for _ in range(bucket.ndefs):
bucket.add_type(Macro(buffer))
def _process_bucket(self, bucket):
self._deserialize_bucket(bucket)
def _deserialize_bucket(self, bucket):
for tdata in bucket.get_types():
tinfo = self.deserialize(tdata.get_type_string(),
tdata.get_fields(),
tdata.get_field_comments())
if tinfo is not None:
self._typeinfos.append(tinfo)
tdata.set_type_info(tinfo)
def deserialize(self, typestr, fields, fieldcmts):
""" Deserialize a TypeString into a TypeInfo object.
Args:
typestr (TypeString): Input serialized type string.
fields (TypeString): Input serialized fields p-list.
fieldcmts (TypeString): Input serialized field comments p-list.
Returns:
TypeInfo: Output TypeInfo object.
"""
typ = typestr.peek_db()
base = typ & TYPE_BASE_MASK
flags = typ & TYPE_FLAGS_MASK
if base <= BT_LAST_BASIC:
typestr += 1
return TypeInfo(typ)
if base > BT_LAST_BASIC:
typedata = None
if base == BT_COMPLEX and flags != BTMT_TYPEDEF:
t = typestr.get()
t += 1
N = t.read_complex_n()
if N == 0:
typedata = TypedefTypeData()
typedata.name = t.read_pstring().decode("ascii")
# I don't like this, we're going to need to come up with a
# way to do this automatically
typestr += t.pos()
return TypeInfo.create_type_info(typ, typedata)
if base == BT_PTR:
typedata = PointerTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif base == BT_ARRAY:
typedata = ArrayTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif base == BT_FUNC:
typedata = FuncTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif base == BT_COMPLEX:
if flags == BTMT_STRUCT or flags == BTMT_UNION:
typedata = UdtTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif flags == BTMT_ENUM:
typedata = EnumTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif flags == BTMT_TYPEDEF:
typedata = TypedefTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
elif base == BT_BITFIELD:
typedata = BitfieldTypeData() \
.deserialize(self, typestr, fields, fieldcmts)
return TypeInfo.create_type_info(typ, typedata)
def serialize(self, tinfo, typestr):
""" Serialize a TypeInfo object into a TypeString.
Args:
tinfo (TypeInfo): Input TypeInfo object.
typestr (TypeString): Output TypeString.
"""
typ = tinfo.get_decl_type()
base = typ & TYPE_BASE_MASK
if base <= BT_LAST_BASIC:
typestr.append_db(typ)
return
if base > BT_LAST_BASIC:
details = tinfo.get_type_details()
if details is not None:
details.serialize(self, tinfo, typestr)
def get_header(self):
""" Get header information.
Returns:
TILHeader: The header information.
"""
return self._header
def get_syms(self):
""" Get the symbol bucket.
Returns:
TILBucket: The symbol bucket.
"""
return self._syms
def get_types(self):
""" Get the type bucket.
Returns:
TILBucket: The type bucket.
"""
return self._types
def get_macros(self):
""" Get the macro bucket.
Returns:
TILBucket: The macro bucket.
"""
return self._macros
def get_named_type(self, name, is_type):
""" Get named typeinfo.
Args:
name (str): The name of the type.
is_type (bool): True if this is a type and otherwise for symbols.
Returns:
TypeData: The serialized type data.
"""
bucket = self._types if is_type else self._syms
for type_data in bucket.get_types():
if name == type_data.get_name():
return type_data
return None
def get_enums(self):
enums = []
for tdata in self._types.get_types():
tinfo = tdata.get_type_info()
typ = tinfo.get_decl_type()
base = typ & TYPE_BASE_MASK
flags = typ & TYPE_FLAGS_MASK
if base == BT_COMPLEX and flags == BTMT_ENUM:
enums.append(tdata)
return enums
def get_structs(self):
structs = []
for tdata in self._types.get_types():
tinfo = tdata.get_type_info()
typ = tinfo.get_decl_type()
base = typ & TYPE_BASE_MASK
flags = typ & TYPE_FLAGS_MASK
if base == BT_COMPLEX and flags == BTMT_STRUCT:
structs.append(tdata)
return structs
| 10,178 | 0 | 1,395 |
e00e8fd1a6ca7ced7e31454775076b1f6cec2802 | 9,465 | py | Python | src/changeset/utils.py | fekblom/critic | a6b60c9053e13d4c878d50531860d7389568626d | [
"Apache-2.0"
] | null | null | null | src/changeset/utils.py | fekblom/critic | a6b60c9053e13d4c878d50531860d7389568626d | [
"Apache-2.0"
] | null | null | null | src/changeset/utils.py | fekblom/critic | a6b60c9053e13d4c878d50531860d7389568626d | [
"Apache-2.0"
] | null | null | null | # -*- mode: python; encoding: utf-8 -*-
#
# Copyright 2012 Jens Lindström, Opera Software ASA
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not
# use this file except in compliance with the License. You may obtain a copy of
# the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations under
# the License.
from subprocess import Popen as process, PIPE
from sys import argv, stderr, exit
import re
from dbutils import find_file, describe_file
import gitutils
import syntaxhighlight
import syntaxhighlight.request
from diffutils import expandWithContext
from htmlutils import htmlify, jsify
from time import strftime
import diff
import diff.analyze
import diff.parse
import diff.merge
import load
import dbutils
import client
| 39.11157 | 211 | 0.599366 | # -*- mode: python; encoding: utf-8 -*-
#
# Copyright 2012 Jens Lindström, Opera Software ASA
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may not
# use this file except in compliance with the License. You may obtain a copy of
# the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
# License for the specific language governing permissions and limitations under
# the License.
from subprocess import Popen as process, PIPE
from sys import argv, stderr, exit
import re
from dbutils import find_file, describe_file
import gitutils
import syntaxhighlight
import syntaxhighlight.request
from diffutils import expandWithContext
from htmlutils import htmlify, jsify
from time import strftime
import diff
import diff.analyze
import diff.parse
import diff.merge
import load
import dbutils
import client
def createFullMergeChangeset(db, user, repository, commit, **kwargs):
assert len(commit.parents) > 1
changesets = createChangeset(db, user, repository, commit, **kwargs)
assert len(changesets) == len(commit.parents)
replayed = createChangeset(db, user, repository, commit, conflicts=True, **kwargs)
assert len(replayed) == 1
changesets.append(replayed[0])
return changesets
def createChangesets(db, repository, commits):
cursor = db.cursor()
requests = []
for commit in commits:
if len(commit.parents) > 1: changeset_type = 'merge'
else: changeset_type = 'direct'
cursor.execute("SELECT 1 FROM changesets WHERE child=%s AND type=%s", (commit.getId(db), changeset_type))
if not cursor.fetchone():
requests.append({ "repository_name": repository.name,
"changeset_type": changeset_type,
"child_sha1": commit.sha1 })
if requests:
client.requestChangesets(requests)
def createChangeset(db, user, repository, commit=None, from_commit=None, to_commit=None, rescan=False, reanalyze=False, conflicts=False, filtered_file_ids=None, review=None, do_highlight=True, load_chunks=True):
cursor = db.cursor()
if conflicts:
if commit:
assert len(commit.parents) > 1
cursor.execute("SELECT replay FROM mergereplays WHERE original=%s", (commit.getId(db),))
row = cursor.fetchone()
if row:
replay = gitutils.Commit.fromId(db, repository, row[0])
else:
replay = repository.replaymerge(db, user, commit)
if not replay: return None
cursor.execute("INSERT INTO mergereplays (original, replay) VALUES (%s, %s)", (commit.getId(db), replay.getId(db)))
from_commit = replay
to_commit = commit
parents = [replay]
else:
parents = [from_commit]
commit = to_commit
changeset_type = 'conflicts'
elif commit:
parents = [gitutils.Commit.fromSHA1(db, repository, sha1) for sha1 in commit.parents] or [None]
changeset_type = 'merge' if len(parents) > 1 else 'direct'
else:
parents = [from_commit]
commit = to_commit
changeset_type = 'direct' if len(to_commit.parents) == 1 and from_commit == to_commit.parents[0] else 'custom'
changesets = []
thin_diff = False
changeset_ids = []
for parent in parents:
if parent:
cursor.execute("SELECT id FROM changesets WHERE parent=%s AND child=%s AND type=%s",
(parent.getId(db), commit.getId(db), changeset_type))
else:
cursor.execute("SELECT id FROM changesets WHERE parent IS NULL AND child=%s AND type=%s",
(commit.getId(db), changeset_type))
row = cursor.fetchone()
if row: changeset_ids.append(row[0])
else: break
assert len(changeset_ids) in (0, len(parents))
if changeset_ids:
if rescan and user.hasRole(db, "developer"):
cursor.executemany("DELETE FROM changesets WHERE id=%s", [(changeset_id,) for changeset_id in changeset_ids])
db.commit()
changeset_ids = []
else:
for changeset_id in changeset_ids:
if changeset_type == 'custom':
cursor.execute("UPDATE customchangesets SET time=NOW() WHERE changeset=%s", (changeset_id,))
changeset = load.loadChangeset(db, repository, changeset_id, filtered_file_ids=filtered_file_ids, load_chunks=load_chunks)
changeset.conflicts = conflicts
if reanalyze and user.hasRole(db, "developer"):
analysis_values = []
for file in changeset.files:
if not filtered_file_ids or file.id in filtered_file_ids:
for index, chunk in enumerate(file.chunks):
old_analysis = chunk.analysis
chunk.analyze(file, index == len(file.chunks) - 1, True)
if old_analysis != chunk.analysis:
analysis_values.append((chunk.analysis, chunk.id))
if reanalyze == "commit" and analysis_values:
cursor.executemany("UPDATE chunks SET analysis=%s WHERE id=%s", analysis_values)
changesets.append(changeset)
if not changesets:
if len(parents) == 1 and from_commit and to_commit and filtered_file_ids:
if from_commit.isAncestorOf(to_commit):
iter_commit = to_commit
while iter_commit != from_commit:
if len(iter_commit.parents) > 1:
thin_diff = True
break
iter_commit = gitutils.Commit.fromSHA1(db, repository, iter_commit.parents[0])
else:
thin_diff = True
if not thin_diff:
if changeset_type == "direct":
request = { "changeset_type": "direct",
"child_sha1": commit.sha1 }
elif changeset_type == "custom":
request = { "changeset_type": "custom",
"parent_sha1": from_commit.sha1 if from_commit else "0" * 40,
"child_sha1": to_commit.sha1 }
elif changeset_type == "merge":
request = { "changeset_type": "merge",
"child_sha1": commit.sha1 }
else:
request = { "changeset_type": "conflicts",
"parent_sha1": from_commit.sha1,
"child_sha1": to_commit.sha1 }
request["repository_name"] = repository.name
db.commit()
client.requestChangesets([request])
db.commit()
for parent in parents:
if parent:
cursor.execute("SELECT id FROM changesets WHERE parent=%s AND child=%s AND type=%s",
(parent.getId(db), commit.getId(db), changeset_type))
else:
cursor.execute("SELECT id FROM changesets WHERE parent IS NULL AND child=%s AND type=%s",
(commit.getId(db), changeset_type))
changeset_id = cursor.fetchone()[0]
changeset = load.loadChangeset(db, repository, changeset_id, filtered_file_ids=filtered_file_ids, load_chunks=load_chunks)
changeset.conflicts = conflicts
changesets.append(changeset)
else:
changes = diff.parse.parseDifferences(repository, from_commit=from_commit, to_commit=to_commit, filter_paths=[describe_file(db, file_id) for file_id in filtered_file_ids])[from_commit.sha1]
dbutils.find_files(db, changes)
for file in changes:
for index, chunk in enumerate(file.chunks):
chunk.analyze(file, index == len(file.chunks) - 1)
changeset = diff.Changeset(None, from_commit, to_commit, changeset_type)
changeset.conflicts = conflicts
changeset.files = diff.File.sorted(changes)
changesets.append(changeset)
if do_highlight:
highlights = {}
for changeset in changesets:
for file in changeset.files:
if file.canHighlight():
if file.old_sha1 and file.old_sha1 != '0' * 40:
highlights[file.old_sha1] = (file.path, file.getLanguage())
if file.new_sha1 and file.new_sha1 != '0' * 40:
highlights[file.new_sha1] = (file.path, file.getLanguage())
syntaxhighlight.request.requestHighlights(repository, highlights)
return changesets
def getCodeContext(db, sha1, line, minimized=False):
cursor = db.cursor()
cursor.execute("SELECT context FROM codecontexts WHERE sha1=%s AND first_line<=%s AND last_line>=%s ORDER BY first_line DESC LIMIT 1", [sha1, line, line])
row = cursor.fetchone()
if row:
context = row[0]
if minimized: context = re.sub("\\(.*(?:\\)|...$)", "(...)", context)
return context
else: return None
| 8,312 | 0 | 92 |
9f82ddb39616da1e6715e95dd97c71c16ea3c2b9 | 1,023 | py | Python | log.py | KongHag/emotion_project | c3b4899a87dfda1e39bba9ef04fea818af8e7bd4 | [
"MIT"
] | 1 | 2020-03-27T19:28:17.000Z | 2020-03-27T19:28:17.000Z | log.py | KongHag/emotion_project | c3b4899a87dfda1e39bba9ef04fea818af8e7bd4 | [
"MIT"
] | 1 | 2020-02-21T16:21:58.000Z | 2020-02-21T18:34:49.000Z | log.py | KongHag/emotion_project | c3b4899a87dfda1e39bba9ef04fea818af8e7bd4 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Defines the the logger object to track execution
Logs are stored into logs/emotion_YYYY-mm-dd.log files
Default logger level is set to INFO, use --logger-level DEBUG tag
to get more information about execution trace.
To setup logger :
>>> from log import stetup_custom_logger
>>> logger = setup_custom_logger()
To log log into file :
>>> logger.info("my first log message")
Content of logs/emotion_YYYY-mm-dd.log
> YYYY-mm-dd HH:MM:SS,sss - INFO - <module> - my first message
"""
import logging
import time
import os
| 24.357143 | 72 | 0.688172 | # -*- coding: utf-8 -*-
"""
Defines the the logger object to track execution
Logs are stored into logs/emotion_YYYY-mm-dd.log files
Default logger level is set to INFO, use --logger-level DEBUG tag
to get more information about execution trace.
To setup logger :
>>> from log import stetup_custom_logger
>>> logger = setup_custom_logger()
To log log into file :
>>> logger.info("my first log message")
Content of logs/emotion_YYYY-mm-dd.log
> YYYY-mm-dd HH:MM:SS,sss - INFO - <module> - my first message
"""
import logging
import time
import os
def setup_custom_logger(name):
formatter = logging.Formatter(
fmt='%(asctime)s - %(levelname)s - %(module)s - %(message)s')
if not os.path.exists('logs'):
os.makedirs('logs')
log_file_name = "logs/emotion_" + time.strftime("%Y-%m-%d") + ".log"
fh = logging.FileHandler(log_file_name, mode="w")
fh.setLevel(logging.DEBUG)
fh.setFormatter(formatter)
logger = logging.getLogger()
logger.addHandler(fh)
return logger
| 448 | 0 | 23 |
cdcb86bc96774326c3b1a347d1b4db3b173d9955 | 2,594 | py | Python | src/CreateMappingSequencesFromVariantTable.py | broadinstitute/CRISPRiTilingDesign | cc07d2e5636cc91588b9d91e074a95e1514ceb93 | [
"MIT"
] | 1 | 2021-09-13T03:10:39.000Z | 2021-09-13T03:10:39.000Z | src/CreateMappingSequencesFromVariantTable.py | broadinstitute/CRISPRiTilingDesign | cc07d2e5636cc91588b9d91e074a95e1514ceb93 | [
"MIT"
] | null | null | null | src/CreateMappingSequencesFromVariantTable.py | broadinstitute/CRISPRiTilingDesign | cc07d2e5636cc91588b9d91e074a95e1514ceb93 | [
"MIT"
] | null | null | null | ###############################################################################
## Jesse Engreitz
## September 29, 2021
import pybedtools
from pybedtools import BedTool
import pandas as pd
import numpy as np
import argparse
from pandas.io.parsers import read_table
from Bio.SeqFeature import FeatureLocation
from collections import OrderedDict
from Bio import SeqUtils
from itertools import product
from random import sample
###############################################
##############################################
##############################################
if __name__ == '__main__':
args = parseargs()
main(args)
| 36.027778 | 154 | 0.638782 | ###############################################################################
## Jesse Engreitz
## September 29, 2021
import pybedtools
from pybedtools import BedTool
import pandas as pd
import numpy as np
import argparse
from pandas.io.parsers import read_table
from Bio.SeqFeature import FeatureLocation
from collections import OrderedDict
from Bio import SeqUtils
from itertools import product
from random import sample
def parseargs():
class formatter(argparse.ArgumentDefaultsHelpFormatter, argparse.RawTextHelpFormatter):
pass
epilog = ("")
parser = argparse.ArgumentParser(description='Input: Variant table from CreateVariantTable.py. Output: same table with MappingSequence column added.',
epilog=epilog,
formatter_class=formatter)
readable = argparse.FileType('r')
parser.add_argument('--input', required=True, help="Input variant table")
parser.add_argument('--genomeFasta', required=False, help="Genome FASTA file, if using a BED file")
parser.add_argument('--output', required=True, help="Output variant table with MappingSequence column added")
parser.add_argument('--bufferLength', type=int, default=5, help="Specify number of nucleotides on each side to output for mapping sequence.")
args = parser.parse_args()
return(args)
###############################################
def addMappingSequences(variantTable, bufferLength, fasta):
## For each row of the variant table, add a column corresponding to a 'mapping sequence' for downstream VFF analysis,
## which contains the edited sequence plus some number of additional nucleotides on each side
variantTable['MappingSequence'] = ""
for index, row in variantTable.iterrows():
editedSeq = BedTool.seq((row['chr'], row['start']-bufferLength, row['start']), fasta) + \
row['alt'] + \
BedTool.seq((row['chr'], row['end'], row['end']+bufferLength), fasta)
variantTable.loc[index,'MappingSequence'] = editedSeq
return(variantTable)
##############################################
def main(args):
## Read input BED4 file
variants = read_table(args.input)
## Get FASTA file to get sequences
fasta = pybedtools.example_filename(args.genomeFasta)
results = addMappingSequences(variants, args.bufferLength, fasta)
results.to_csv(args.output, sep='\t', header=True, index=False)
##############################################
if __name__ == '__main__':
args = parseargs()
main(args)
| 1,884 | 0 | 68 |
4e80aaf4de81bb10067bf0ce50c5406a527f1332 | 5,097 | py | Python | tests.py | bendmorris/beaver | 4db3e1690145dee89d30144f3632396313218214 | [
"MIT"
] | 2 | 2018-10-06T08:35:41.000Z | 2019-04-03T21:15:02.000Z | tests.py | bendmorris/beaver | 4db3e1690145dee89d30144f3632396313218214 | [
"MIT"
] | null | null | null | tests.py | bendmorris/beaver | 4db3e1690145dee89d30144f3632396313218214 | [
"MIT"
] | null | null | null | from lib.types import *
from lib.graph import *
from lib.command import *
from lib.parser import *
import inspect
import os
import doctest
import sys
def parser_tests():
'''
>>> variable.parseString('?a', parseAll=True)[0]
?a
>>> literal.parseString('1.0', parseAll=True)[0]
1.0
>>> literal.parseString('1', parseAll=True)[0]
1
>>> print literal.parseString('"abc"', parseAll=True)[0]
"abc"
>>> expression.parseString(':a :b 3 .', parseAll=True)[0]
:a :b 3 .
>>> expression.parseString('?a <http://www.example.com> abc:def .', parseAll=True)[0]
?a ( <http://www.example.com> abc:def )
>>> [s for s in expression.parseString('<a> a <b> ; <c> <d>, <e> .', parseAll=True)]
[<a> rdf:type <b> ; <c> <d>, <e> .]
>>> expression.parseString('@reinit', parseAll=True)[0]
@reinit
>>> expression.parseString('@draw <test.png>', parseAll=True)[0]
@draw <test.png>
>>> expression.parseString('@import <test.ttl>', parseAll=True)[0]
@import <test.ttl>
>>> expression.parseString('@load <test.xml>', parseAll=True)[0]
@load <test.xml>
>>> expression.parseString('?a = :a :b 3 .', parseAll=True)[0]
?a = :a :b 3 .
>>> expression.parseString('@prefix ex: <http://www.example.com/example#> .', parseAll=True)[0]
@prefix ex: <http://www.example.com/example#>
>>> expression.parseString('@for ?obj in (1 <a> ?x b:c "five") { <a> <b> ?obj . }', parseAll=True)[0]
@for ?obj in ( 1 <a> ?x b:c "five" ) <a> <b> ?obj .
>>> expression.parseString('@out', parseAll=True)[0]
@out
>>> expression.parseString('@out <test.ttl>', parseAll=True)[0]
@out <test.ttl>
>>> expression.parseString('@reinit', parseAll=True)[0]
@reinit
>>> expression.parseString('@base <abc.org>', parseAll=True)[0]
@base <abc.org>
>>> expression.parseString('<a> <b> true .', parseAll=True)[0]
<a> <b> true .
>>> expression.parseString('<a> <b> false .', parseAll=True)[0]
<a> <b> false .
>>> expression.parseString('?a :b :c ; :d :e .', parseAll=True)[0]
?a :b :c ; :d :e .
'''
def w3_tests():
'''
>>> g = Graph()
>>> g.parse(text='@import <test.nt>')
1
>>> g.reinit()
>>> for i in range(14):
... uri = 'http://www.w3.org/2001/sw/DataAccess/df1/tests/test-%s.ttl' % str(i).zfill(2)
... p = g.parse(text='@import <%s> .' % uri)
... assert(p == 1)
>>> g.parse(text='@import <http://www.w3.org/2001/sw/DataAccess/df1/tests/rdfs-namespace.ttl>')
1
>>> g.parse(text='@import <http://www.w3.org/2001/sw/DataAccess/df1/tests/manifest.ttl>')
1
'''
def graph_tests():
'''
>>> g = Graph()
>>> g.execute(Statement(Uri('node1'), [(QUri('p:node2'), [Uri('node3'), Uri('node4')])]))
>>> g.statements
{<node1>: {p:node2: set([<node3>, <node4>])}}
>>> prefix = PrefixCommand(prefix='ex', uri=Uri('http://www.example.com/example#'))
>>> g.execute(prefix)
>>> g.prefixes
{'rdf': <http://www.w3.org/1999/02/22-rdf-syntax-ns#>, 'ex': <http://www.example.com/example#>}
>>> str(Uri('http://www.example.com/example#sample').apply_prefix(g))
'ex:sample'
>>> try: os.remove('test.png')
... except OSError: pass
>>> os.path.exists('test.png')
False
>>> g.draw('test.png')
>>> os.path.exists('test.png')
True
>>> g.parse(text='@load <test.xml>')
1
>>> g.parse(text='@import <test.bvr>')
1
>>> g.parse(text='<a> a <b>, <c> .')
1
>>> g.reinit()
>>> g.parse(text='@load <http://www.nexml.org/nexml/examples/trees.rdf>')
1
>>> sorted([str(s) for s in g.statements.keys()])[:5]
['<http://example.org/e1>', '<http://example.org/e2>', '<http://example.org/e3>', '<http://example.org/e4>', '<http://example.org/e5>']
>>> g.reinit()
>>> g.parse(text='@for ?x in (1 2 3 4 5) { <a> <b> ?x . }')
1
>>> g.statements[Uri('a')][Uri('b')]
set([1, 2, 3, 4, 5])
>>> g.parse(text="?cat ?name = { ?name a example:cat . <ben> <has_cat> ?name . }")
1
>>> g.parse(text="@for ?name in (<whiskers> <socks> <oreo>) ?cat ?name .")
1
>>> g.statements[Uri('ben')][Uri('has_cat')]
set([<socks>, <whiskers>, <oreo>])
>>> g.reinit()
>>> g.parse(text='?a ?b = { <things> <not_a_one> ?b } . ?a 1 = { <things> <is_a_one> 1 } .')
2
>>> g.parse(text='@for ?x in (1 2 <bob> "1") ?a ?x .')
1
>>> g.statements[Uri('things')][Uri('is_a_one')]
set([1])
>>> g.statements[Uri('things')][Uri('not_a_one')]
set(["1", 2, <bob>])
>>> g.parse(text='@for ?x in (2 <bob> "1") @del <things> <not_a_one> ?x . @del <things> <is_a_one> 1 .')
2
>>> g.statements
{}
>>> g.base_uri is None
True
>>> g.parse(text='@base <http://www.example.org> .')
1
>>> g.base_uri
<http://www.example.org>
'''
if __name__ == '__main__':
if len(sys.argv) > 1:
verbose = eval(sys.argv[1])
else: verbose=False
run_tests(verbose=verbose)
| 33.98 | 139 | 0.54895 | from lib.types import *
from lib.graph import *
from lib.command import *
from lib.parser import *
import inspect
import os
import doctest
import sys
def parser_tests():
'''
>>> variable.parseString('?a', parseAll=True)[0]
?a
>>> literal.parseString('1.0', parseAll=True)[0]
1.0
>>> literal.parseString('1', parseAll=True)[0]
1
>>> print literal.parseString('"abc"', parseAll=True)[0]
"abc"
>>> expression.parseString(':a :b 3 .', parseAll=True)[0]
:a :b 3 .
>>> expression.parseString('?a <http://www.example.com> abc:def .', parseAll=True)[0]
?a ( <http://www.example.com> abc:def )
>>> [s for s in expression.parseString('<a> a <b> ; <c> <d>, <e> .', parseAll=True)]
[<a> rdf:type <b> ; <c> <d>, <e> .]
>>> expression.parseString('@reinit', parseAll=True)[0]
@reinit
>>> expression.parseString('@draw <test.png>', parseAll=True)[0]
@draw <test.png>
>>> expression.parseString('@import <test.ttl>', parseAll=True)[0]
@import <test.ttl>
>>> expression.parseString('@load <test.xml>', parseAll=True)[0]
@load <test.xml>
>>> expression.parseString('?a = :a :b 3 .', parseAll=True)[0]
?a = :a :b 3 .
>>> expression.parseString('@prefix ex: <http://www.example.com/example#> .', parseAll=True)[0]
@prefix ex: <http://www.example.com/example#>
>>> expression.parseString('@for ?obj in (1 <a> ?x b:c "five") { <a> <b> ?obj . }', parseAll=True)[0]
@for ?obj in ( 1 <a> ?x b:c "five" ) <a> <b> ?obj .
>>> expression.parseString('@out', parseAll=True)[0]
@out
>>> expression.parseString('@out <test.ttl>', parseAll=True)[0]
@out <test.ttl>
>>> expression.parseString('@reinit', parseAll=True)[0]
@reinit
>>> expression.parseString('@base <abc.org>', parseAll=True)[0]
@base <abc.org>
>>> expression.parseString('<a> <b> true .', parseAll=True)[0]
<a> <b> true .
>>> expression.parseString('<a> <b> false .', parseAll=True)[0]
<a> <b> false .
>>> expression.parseString('?a :b :c ; :d :e .', parseAll=True)[0]
?a :b :c ; :d :e .
'''
def w3_tests():
'''
>>> g = Graph()
>>> g.parse(text='@import <test.nt>')
1
>>> g.reinit()
>>> for i in range(14):
... uri = 'http://www.w3.org/2001/sw/DataAccess/df1/tests/test-%s.ttl' % str(i).zfill(2)
... p = g.parse(text='@import <%s> .' % uri)
... assert(p == 1)
>>> g.parse(text='@import <http://www.w3.org/2001/sw/DataAccess/df1/tests/rdfs-namespace.ttl>')
1
>>> g.parse(text='@import <http://www.w3.org/2001/sw/DataAccess/df1/tests/manifest.ttl>')
1
'''
def graph_tests():
'''
>>> g = Graph()
>>> g.execute(Statement(Uri('node1'), [(QUri('p:node2'), [Uri('node3'), Uri('node4')])]))
>>> g.statements
{<node1>: {p:node2: set([<node3>, <node4>])}}
>>> prefix = PrefixCommand(prefix='ex', uri=Uri('http://www.example.com/example#'))
>>> g.execute(prefix)
>>> g.prefixes
{'rdf': <http://www.w3.org/1999/02/22-rdf-syntax-ns#>, 'ex': <http://www.example.com/example#>}
>>> str(Uri('http://www.example.com/example#sample').apply_prefix(g))
'ex:sample'
>>> try: os.remove('test.png')
... except OSError: pass
>>> os.path.exists('test.png')
False
>>> g.draw('test.png')
>>> os.path.exists('test.png')
True
>>> g.parse(text='@load <test.xml>')
1
>>> g.parse(text='@import <test.bvr>')
1
>>> g.parse(text='<a> a <b>, <c> .')
1
>>> g.reinit()
>>> g.parse(text='@load <http://www.nexml.org/nexml/examples/trees.rdf>')
1
>>> sorted([str(s) for s in g.statements.keys()])[:5]
['<http://example.org/e1>', '<http://example.org/e2>', '<http://example.org/e3>', '<http://example.org/e4>', '<http://example.org/e5>']
>>> g.reinit()
>>> g.parse(text='@for ?x in (1 2 3 4 5) { <a> <b> ?x . }')
1
>>> g.statements[Uri('a')][Uri('b')]
set([1, 2, 3, 4, 5])
>>> g.parse(text="?cat ?name = { ?name a example:cat . <ben> <has_cat> ?name . }")
1
>>> g.parse(text="@for ?name in (<whiskers> <socks> <oreo>) ?cat ?name .")
1
>>> g.statements[Uri('ben')][Uri('has_cat')]
set([<socks>, <whiskers>, <oreo>])
>>> g.reinit()
>>> g.parse(text='?a ?b = { <things> <not_a_one> ?b } . ?a 1 = { <things> <is_a_one> 1 } .')
2
>>> g.parse(text='@for ?x in (1 2 <bob> "1") ?a ?x .')
1
>>> g.statements[Uri('things')][Uri('is_a_one')]
set([1])
>>> g.statements[Uri('things')][Uri('not_a_one')]
set(["1", 2, <bob>])
>>> g.parse(text='@for ?x in (2 <bob> "1") @del <things> <not_a_one> ?x . @del <things> <is_a_one> 1 .')
2
>>> g.statements
{}
>>> g.base_uri is None
True
>>> g.parse(text='@base <http://www.example.org> .')
1
>>> g.base_uri
<http://www.example.org>
'''
def run_tests(verbose=False):
doctest.testmod(inspect.getmodule(parser_tests), verbose=verbose)
if __name__ == '__main__':
if len(sys.argv) > 1:
verbose = eval(sys.argv[1])
else: verbose=False
run_tests(verbose=verbose)
| 78 | 0 | 23 |
ca42f5a69b548d40902183930d2869603e6adced | 145 | py | Python | tests/dat/actions/unicode3.py | gnodet/incubator-openwhisk | 8da57de213a61200305d093bf84e5c0825a9402e | [
"Apache-2.0"
] | 11 | 2018-04-20T14:55:41.000Z | 2021-10-02T03:20:08.000Z | tests/dat/actions/unicode3.py | gnodet/incubator-openwhisk | 8da57de213a61200305d093bf84e5c0825a9402e | [
"Apache-2.0"
] | 2 | 2018-09-29T17:47:28.000Z | 2020-09-29T14:02:38.000Z | tests/dat/actions/unicode3.py | gnodet/incubator-openwhisk | 8da57de213a61200305d093bf84e5c0825a9402e | [
"Apache-2.0"
] | 5 | 2018-05-13T13:48:07.000Z | 2019-10-24T15:34:13.000Z | """Python 3 Unicode test."""
| 16.111111 | 28 | 0.531034 | """Python 3 Unicode test."""
def main(args):
sep = args['delimiter']
str = sep + " ☃ " + sep
print(str)
return {"winter": str}
| 94 | 0 | 23 |
af9c353c471bc8b285b2ddee1a58d16bc873224f | 3,365 | py | Python | custom_components/ipx800v5/tools_ipx_entity.py | Aohzan/ipx800v5 | 2aeaa6e7f5f9cb19469d334fc13ce6aab19441b6 | [
"Apache-2.0"
] | 2 | 2021-12-03T23:53:22.000Z | 2022-01-20T10:53:05.000Z | custom_components/ipx800v5/tools_ipx_entity.py | Aohzan/ipx800v5 | 2aeaa6e7f5f9cb19469d334fc13ce6aab19441b6 | [
"Apache-2.0"
] | 3 | 2021-12-06T21:28:54.000Z | 2022-01-20T10:16:30.000Z | custom_components/ipx800v5/tools_ipx_entity.py | Aohzan/ipx800v5 | 2aeaa6e7f5f9cb19469d334fc13ce6aab19441b6 | [
"Apache-2.0"
] | null | null | null | """Represent the IPX800V5 base entity."""
from pypx800v5 import IPX800
from pypx800v5.const import EXTENSIONS, IPX
from voluptuous.util import Upper
from homeassistant.const import (
CONF_DEVICE_CLASS,
CONF_ENTITY_CATEGORY,
CONF_ICON,
CONF_ID,
CONF_NAME,
CONF_UNIT_OF_MEASUREMENT,
)
from homeassistant.helpers.device_registry import CONNECTION_NETWORK_MAC
from homeassistant.helpers.update_coordinator import (
CoordinatorEntity,
DataUpdateCoordinator,
)
from homeassistant.util import slugify
from .const import (
CONF_COMPONENT,
CONF_EXT_NAME,
CONF_EXT_NUMBER,
CONF_EXT_TYPE,
CONF_IO_NUMBER,
CONF_IO_NUMBERS,
CONF_TRANSITION,
DEFAULT_TRANSITION,
DOMAIN,
)
class IpxEntity(CoordinatorEntity):
"""Representation of a IPX800 generic device entity."""
def __init__(
self,
device_config: dict,
ipx: IPX800,
coordinator: DataUpdateCoordinator,
suffix_name: str = None,
device_name: str = None,
) -> None:
"""Initialize the device."""
super().__init__(coordinator)
self.ipx = ipx
self._transition = int(
device_config.get(CONF_TRANSITION, DEFAULT_TRANSITION) * 1000
)
self._component = device_config[CONF_COMPONENT]
self._ext_type = device_config[CONF_EXT_TYPE]
self._ext_number = device_config.get(CONF_EXT_NUMBER)
self._io_number = device_config.get(CONF_IO_NUMBER)
self._io_numbers = device_config.get(CONF_IO_NUMBERS, [])
self._io_id = device_config.get(CONF_ID)
self._attr_name: str = device_config[CONF_NAME]
if suffix_name:
self._attr_name = f"{self._attr_name} {suffix_name}"
self._attr_device_class = device_config.get(CONF_DEVICE_CLASS)
self._attr_native_unit_of_measurement = device_config.get(
CONF_UNIT_OF_MEASUREMENT
)
self._attr_icon = device_config.get(CONF_ICON)
self._attr_entity_category = device_config.get(CONF_ENTITY_CATEGORY)
self._attr_unique_id = "_".join(
[DOMAIN, self.ipx.host, self._component, slugify(self._attr_name)]
)
if device_name:
self._device_name = device_name
elif self._ext_type == IPX:
self._device_name = coordinator.name
else:
self._device_name = device_config.get(
CONF_EXT_NAME, f"{Upper(self._ext_type)} N°{self._ext_number}"
)
configuration_url = f"http://{self.ipx.host}:{self.ipx.port}/"
self._attr_device_info = {
"identifiers": {(DOMAIN, slugify(self._device_name))},
"default_name": self._device_name,
"manufacturer": "GCE Electronics",
"via_device": (DOMAIN, slugify(coordinator.name)),
"configuration_url": configuration_url,
}
if self._ext_type in EXTENSIONS:
self._attr_device_info.update({"model": Upper(self._ext_type)})
else:
self._attr_device_info.update({"model": "IPX800 V5"})
if self._ext_type == IPX:
self._attr_device_info.update(
{
"sw_version": self.ipx.firmware_version,
"connections": {(CONNECTION_NETWORK_MAC, self.ipx.mac_address)},
}
)
| 33.316832 | 84 | 0.646062 | """Represent the IPX800V5 base entity."""
from pypx800v5 import IPX800
from pypx800v5.const import EXTENSIONS, IPX
from voluptuous.util import Upper
from homeassistant.const import (
CONF_DEVICE_CLASS,
CONF_ENTITY_CATEGORY,
CONF_ICON,
CONF_ID,
CONF_NAME,
CONF_UNIT_OF_MEASUREMENT,
)
from homeassistant.helpers.device_registry import CONNECTION_NETWORK_MAC
from homeassistant.helpers.update_coordinator import (
CoordinatorEntity,
DataUpdateCoordinator,
)
from homeassistant.util import slugify
from .const import (
CONF_COMPONENT,
CONF_EXT_NAME,
CONF_EXT_NUMBER,
CONF_EXT_TYPE,
CONF_IO_NUMBER,
CONF_IO_NUMBERS,
CONF_TRANSITION,
DEFAULT_TRANSITION,
DOMAIN,
)
class IpxEntity(CoordinatorEntity):
"""Representation of a IPX800 generic device entity."""
def __init__(
self,
device_config: dict,
ipx: IPX800,
coordinator: DataUpdateCoordinator,
suffix_name: str = None,
device_name: str = None,
) -> None:
"""Initialize the device."""
super().__init__(coordinator)
self.ipx = ipx
self._transition = int(
device_config.get(CONF_TRANSITION, DEFAULT_TRANSITION) * 1000
)
self._component = device_config[CONF_COMPONENT]
self._ext_type = device_config[CONF_EXT_TYPE]
self._ext_number = device_config.get(CONF_EXT_NUMBER)
self._io_number = device_config.get(CONF_IO_NUMBER)
self._io_numbers = device_config.get(CONF_IO_NUMBERS, [])
self._io_id = device_config.get(CONF_ID)
self._attr_name: str = device_config[CONF_NAME]
if suffix_name:
self._attr_name = f"{self._attr_name} {suffix_name}"
self._attr_device_class = device_config.get(CONF_DEVICE_CLASS)
self._attr_native_unit_of_measurement = device_config.get(
CONF_UNIT_OF_MEASUREMENT
)
self._attr_icon = device_config.get(CONF_ICON)
self._attr_entity_category = device_config.get(CONF_ENTITY_CATEGORY)
self._attr_unique_id = "_".join(
[DOMAIN, self.ipx.host, self._component, slugify(self._attr_name)]
)
if device_name:
self._device_name = device_name
elif self._ext_type == IPX:
self._device_name = coordinator.name
else:
self._device_name = device_config.get(
CONF_EXT_NAME, f"{Upper(self._ext_type)} N°{self._ext_number}"
)
configuration_url = f"http://{self.ipx.host}:{self.ipx.port}/"
self._attr_device_info = {
"identifiers": {(DOMAIN, slugify(self._device_name))},
"default_name": self._device_name,
"manufacturer": "GCE Electronics",
"via_device": (DOMAIN, slugify(coordinator.name)),
"configuration_url": configuration_url,
}
if self._ext_type in EXTENSIONS:
self._attr_device_info.update({"model": Upper(self._ext_type)})
else:
self._attr_device_info.update({"model": "IPX800 V5"})
if self._ext_type == IPX:
self._attr_device_info.update(
{
"sw_version": self.ipx.firmware_version,
"connections": {(CONNECTION_NETWORK_MAC, self.ipx.mac_address)},
}
)
| 0 | 0 | 0 |
90e6d15deacbcd7b93e6e6337ed56a5c3b7747ab | 14,108 | py | Python | src/blogpost.py | cdeck3r/instablog | 7c621d2b0454672474eb667f39ff1861beaaee73 | [
"MIT"
] | null | null | null | src/blogpost.py | cdeck3r/instablog | 7c621d2b0454672474eb667f39ff1861beaaee73 | [
"MIT"
] | 1 | 2019-09-11T16:27:34.000Z | 2019-09-11T16:27:34.000Z | src/blogpost.py | cdeck3r/instablog | 7c621d2b0454672474eb667f39ff1861beaaee73 | [
"MIT"
] | null | null | null | # generic, util
import click
import logging
from pathlib import Path
import random
# website download and parsing
import json
import requests
from bs4 import BeautifulSoup
from lxml.html.soupparser import fromstring
# reading and writing files
import sys
import csv
import os
import pandas as pd
#
# Classify posts
#
# presentation: pres_type
# * fullscreen
# * regular
# * leftright
# * album
#
# description type: desc_type
# * caption
# * paragraph
#
# simple and pragmatic approach
# enumerate blog posts by the day in relation to a reference date
# default: the tour start
#
# A rather generic function
# to encapsulate the concrete one
#############################################
# Main
#############################################
@click.command()
@click.argument('post_file',
type=click.Path(exists=True, dir_okay=False) )
@click.argument('blog_file',
type=click.Path(exists=False, dir_okay=False, writable=True) )
@click.argument('blog_date',
type=click.DateTime(formats=['%Y-%m-%d']) )
@click.option('--no-filter', '-f', required=False, is_flag=True,
help='Do not filter <post_file> entries by <blog_date>.')
def blogpost(post_file, blog_file, blog_date, no_filter):
"""Creates a blog post file
\b
<post_file> Filepath containing all relevant information for each Instagram post.
<blog_file> Filepath containing the blog post, usually a .md markdown file.
<blog_date> Blog entry date [YYYY-MM-DD]; only <post_file> entries matching the date will be included.
You may disable the date filtering using -f switch.
The blog post file will then contain all <post_file> entries.
"""
logger = logging.getLogger(__file__)
logger.info('Start creating blog post')
blog_date = pd.to_datetime(blog_date).date().strftime('%Y-%m-%d')
post_info_df = load_post_info(post_file, blog_date, no_filter)
post_entry_df = create_post_entries(post_info_df)
post_frontmatter = create_post_frontmatter(post_info_df, blog_date)
store_blog(blog_file, post_frontmatter, post_entry_df)
if len(post_frontmatter) < 1:
logger.info('No blog post created.')
else:
logger.info('Blog post created.')
pass
#############################################
# Entry
#############################################
if __name__ == '__main__':
log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
logging.basicConfig(level=logging.INFO, format=log_fmt)
# not used in this stub but often useful for finding various files
project_dir = Path(__file__).resolve().parents[2]
# start the crawler
blogpost()
| 32.962617 | 110 | 0.617876 | # generic, util
import click
import logging
from pathlib import Path
import random
# website download and parsing
import json
import requests
from bs4 import BeautifulSoup
from lxml.html.soupparser import fromstring
# reading and writing files
import sys
import csv
import os
import pandas as pd
def load_post_info(post_file, blog_date, no_filter):
logger = logging.getLogger(__file__)
logger.info('Load post info from file: %s', post_file)
post_info_df = pd.DataFrame()
blog_date = pd.to_datetime(blog_date).date()
try:
post_info_df = pd.read_csv(post_file, sep=';', encoding='utf-8')
except:
# log error handling
logger.error('Error reading file : %s', post_file)
sys.exit(1)
# convert to datetime
post_info_df['uploadDate'] = pd.to_datetime(post_info_df['uploadDate'])
post_info_df['post_date'] = [d.date() for d in post_info_df['uploadDate']]
# filter for image content
logger.info('Filter for image content')
post_info_df_filtered = post_info_df[ (post_info_df['post_content_type'] == 'image') ]
# now filter for blog_date
if no_filter:
# do nothing
post_info_df_filtered = post_info_df_filtered
else:
logger.info('Filter for post date: %s', blog_date)
post_info_df_filtered = post_info_df_filtered[ (post_info_df_filtered['post_date'] == blog_date) ]
if len(post_info_df_filtered) < 1:
logger.warning('No post info found. Maybe filtered out?')
else:
logger.info('Number of post info loaded: %d', len(post_info_df_filtered))
return post_info_df_filtered
#
# Classify posts
#
# presentation: pres_type
# * fullscreen
# * regular
# * leftright
# * album
#
# description type: desc_type
# * caption
# * paragraph
#
def classify_posts(post_info_df,
post_count_threshold = 2,
caption_len_threshold = 25,
caption_huge_threshold = 200,
album_threshold = 8,
album_img_count = 4):
logger = logging.getLogger(__file__)
post_info_df['pres_type'] =''
post_info_df['desc_type'] =''
# few images --> regular
if len(post_info_df) <= post_count_threshold:
post_info_df['pres_type'] = 'regular'
# single image --> fullscreen
if len(post_info_df) <= 1: # single post
post_info_df['pres_type'] = 'fullscreen'
for index, post in post_info_df.iterrows():
if len(str(post['caption'])) <= caption_len_threshold:
post_info_df.loc[index, 'desc_type'] = 'caption'
else:
post_info_df.loc[index, 'desc_type'] = 'paragraph'
if len(post_info_df) <= post_count_threshold:
return post_info_df
#
# post counts > post_count_threshold
#
for index, post in post_info_df.iterrows():
if len(str(post['caption'])) <= caption_huge_threshold:
post_info_df.loc[index, 'pres_type'] = 'regular'
post_info_df.loc[index, 'desc_type'] = 'caption'
logger.debug('Classify [regular / caption] for post: %s', post['shortcode'])
else:
post_info_df.loc[index, 'pres_type'] = 'leftright'
post_info_df.loc[index, 'desc_type'] = 'paragraph'
logger.debug('Classify [leftright / paragraph] for post: %s', post['shortcode'])
# many short captions: album with caption
numOfRows = len(post_info_df[
(post_info_df['pres_type'] == 'regular') &
(post_info_df['desc_type'] == 'caption')
])
# decide on albums
if numOfRows > album_threshold:
# we define albums
img_idx = 0
pres_type_rollover = album_img_count + 1
for index, post in post_info_df.iterrows():
if (post['pres_type'] == 'regular') and (img_idx % pres_type_rollover == 0):
# we leave it as it is
img_idx = img_idx + 1
logger.debug('Remain classification [regular] for post: %s', post['shortcode'])
continue
if (post['pres_type'] == 'regular') and (img_idx % pres_type_rollover > 0):
post_info_df.loc[index, 'pres_type'] = 'album'
img_idx = img_idx + 1
logger.debug('Classify [album / caption] for post: %s', post['shortcode'])
return post_info_df
def pres_fullscreen(post):
entry = '<figure class="large" markdown="1">'
entry = entry + '<p><img src="'
entry = entry + post['post_image_url']
entry = entry + '" alt=""/></p> '
if post['desc_type'] == 'caption':
entry = entry + '<figcaption>'
entry = entry + str(post['caption'])
entry = entry + '</figcaption>'
entry = entry + '</figure>'
if post['desc_type'] == 'paragraph':
entry = entry + '<p>' + str(post['caption']) + '</p>'
return entry
def pres_regular(post):
entry = '<figure>'
entry = entry + '<img src="'
entry = entry + post['post_image_url']
entry = entry + '"/> '
if post['desc_type'] == 'caption':
entry = entry + '<figcaption>'
entry = entry + str(post['caption'])
entry = entry + '</figcaption>'
entry = entry + '</figure>'
if post['desc_type'] == 'paragraph':
entry = entry + '<p>' + str(post['caption']) + '</p>'
return entry
def pres_leftright(post, lr_idx):
entry = '<p><img src="'
entry = entry + post['post_image_url']
if lr_idx % 2:
entry = entry + '#right" alt=""/>'
else:
entry = entry + '#left" alt=""/>'
pass
entry = entry + '</p>'
if post['desc_type'] == 'paragraph':
entry = entry + '<p>' + str(post['caption']) + '</p>'
return entry
def pres_album(post_info_df, post_album_idx):
# album start
entry = '<div class="album">'
for index in post_album_idx:
# figure start
entry += '<figure>'
# first the image reference
entry += '<img src="'
entry += post_info_df.loc[index, 'post_image_url']
entry += '" />'
# second, the caption
entry += '<figcaption>'
entry += post_info_df.loc[index, 'caption']
entry += '</figcaption>'
# figure end
entry += '</figure>'
# album end
entry += '</div>'
return entry
def create_post_entries(post_info_df, album_img_count=4):
logger = logging.getLogger(__file__)
if len(post_info_df) < 1:
logger.warning('No posts found for creating blog post entries.')
return post_info_df
# first: sort uploadDate asc
post_info_df = post_info_df.sort_values(by=['uploadDate'])
# apply heuristics to indicate for each entry
# the type of presentation
post_info_df = classify_posts(post_info_df, album_img_count=album_img_count)
post_info_df['post_entry'] = ''
# posts are classified
# let's render the presentation
lr_idx = 0
# album image accumulator
post_album_idx = []
for index, post in post_info_df.iterrows():
if post['pres_type'] == 'fullscreen':
logger.debug('Render [fullscreen] for post: %s', post['shortcode'])
post_info_df.loc[index, 'post_entry'] = pres_fullscreen(post)
if post['pres_type'] == 'regular':
logger.debug('Render [regular] for post: %s', post['shortcode'])
post_info_df.loc[index, 'post_entry'] = pres_regular(post)
if post['pres_type'] == 'album':
logger.debug('Render [album] for post: %s', post['shortcode'])
if len(post_album_idx) < (album_img_count-1):
# accumulate image for album
post_album_idx.append(index)
# last known album index
# we will not fill post_entry at this index
# post_entry will stay empty
last_empty_album_index = index
else:
#add this last image to album
post_album_idx.append(index)
logger.debug('Album images to render: %d', len(post_album_idx))
# render album
post_info_df.loc[index, 'post_entry'] = pres_album(post_info_df, post_album_idx)
# reset album image accumulator
post_album_idx = []
if post['pres_type'] == 'leftright':
logger.debug('Render [leftright] for post: %s', post['shortcode'])
post_info_df.loc[index, 'post_entry'] = pres_leftright(post, lr_idx)
lr_idx = lr_idx + 1
# special case, leftover album image
if len(post_album_idx) > 0:
# album images left, but not rendered
logger.debug('Leftover album images to render: %d', len(post_album_idx))
# render album
# last_album_index is the last known album index
# we know that at last_empty_album_index the post_entry is empty
post_info_df.loc[last_empty_album_index, 'post_entry'] = pres_album(post_info_df, post_album_idx)
# reset album image accumulator
post_album_idx = []
return post_info_df
# simple and pragmatic approach
# enumerate blog posts by the day in relation to a reference date
# default: the tour start
def create_title_refdate(post_info_df, blog_date, ref_date = '2019-08-22'):
ref_date = pd.to_datetime(ref_date).date()
blog_date = pd.to_datetime(blog_date).date()
tourday = (blog_date - ref_date).days
if tourday < 0:
title = 'Noch ' + str(abs(tourday)) + ' Tage bis zum Tourstart'
elif tourday == 0:
title = 'Heute ist Tourstart'
else:
# because tourday 0 (== tourstart) is the 1st tourday
# So, if tourday == 1, then we are actually at day 2 of tour.
tourday += 1
title = 'Tourtag: ' + str(tourday)
return title
#
# A rather generic function
# to encapsulate the concrete one
def create_title(post_info_df, blog_date):
return create_title_refdate(post_info_df, blog_date)
def create_post_frontmatter(post_info_df, blog_date):
logger = logging.getLogger(__file__)
if len(post_info_df) < 1:
logger.warning('No posts found for frontmatter.')
return ''
post_info_df = post_info_df.reset_index(drop=True)
# randomly select an image as cover image
cover_idx = random.randint(0,len(post_info_df)-1)
# determine title
title = create_title(post_info_df, blog_date)
# linebreak char
lb = '\n'
post_frontmatter = '---'
post_frontmatter += lb
post_frontmatter += 'layout: post'
post_frontmatter += lb
post_frontmatter += 'title: "' + title + '"'
post_frontmatter += lb
post_frontmatter += 'menutitle: "' + title + '"'
post_frontmatter += lb
post_frontmatter += 'cover: ' + post_info_df.loc[cover_idx, 'post_image_url']
post_frontmatter += lb
post_frontmatter += 'category: Tourblog'
post_frontmatter += lb
post_frontmatter += 'date: ' + blog_date
post_frontmatter += lb
post_frontmatter += 'author: instablog'
post_frontmatter += lb
post_frontmatter += 'tags: Tour'
post_frontmatter += lb
post_frontmatter += 'published: true'
post_frontmatter += lb
post_frontmatter += 'comments: false'
post_frontmatter += lb
post_frontmatter += 'math: false'
post_frontmatter += lb
post_frontmatter += '---'
post_frontmatter += lb
post_frontmatter += lb
return post_frontmatter
def store_blog(blog_file, post_frontmatter, post_entry_df):
logger = logging.getLogger(__file__)
if len(post_frontmatter) < 1:
logger.warning('No posts found. Will not create blog post.')
return
logger.info('Write data in file: %s', blog_file)
lb = '\n'
try:
with open(blog_file, 'w') as f:
# frontmatter
f.write(post_frontmatter)
# content
for index, post in post_entry_df.iterrows():
f.write(post['post_entry'])
f.write(lb)
f.closed
except:
# log error handling
logger.error('Error writing file : %s', pos_file)
sys.exit(1)
#############################################
# Main
#############################################
@click.command()
@click.argument('post_file',
type=click.Path(exists=True, dir_okay=False) )
@click.argument('blog_file',
type=click.Path(exists=False, dir_okay=False, writable=True) )
@click.argument('blog_date',
type=click.DateTime(formats=['%Y-%m-%d']) )
@click.option('--no-filter', '-f', required=False, is_flag=True,
help='Do not filter <post_file> entries by <blog_date>.')
def blogpost(post_file, blog_file, blog_date, no_filter):
"""Creates a blog post file
\b
<post_file> Filepath containing all relevant information for each Instagram post.
<blog_file> Filepath containing the blog post, usually a .md markdown file.
<blog_date> Blog entry date [YYYY-MM-DD]; only <post_file> entries matching the date will be included.
You may disable the date filtering using -f switch.
The blog post file will then contain all <post_file> entries.
"""
logger = logging.getLogger(__file__)
logger.info('Start creating blog post')
blog_date = pd.to_datetime(blog_date).date().strftime('%Y-%m-%d')
post_info_df = load_post_info(post_file, blog_date, no_filter)
post_entry_df = create_post_entries(post_info_df)
post_frontmatter = create_post_frontmatter(post_info_df, blog_date)
store_blog(blog_file, post_frontmatter, post_entry_df)
if len(post_frontmatter) < 1:
logger.info('No blog post created.')
else:
logger.info('Blog post created.')
pass
#############################################
# Entry
#############################################
if __name__ == '__main__':
log_fmt = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
logging.basicConfig(level=logging.INFO, format=log_fmt)
# not used in this stub but often useful for finding various files
project_dir = Path(__file__).resolve().parents[2]
# start the crawler
blogpost()
| 11,159 | 0 | 250 |
25566b056d5c52b0e4af37f19c8c581d8d0cc565 | 3,962 | py | Python | ref/MTPythonSampleCode.py | rgtjf/translator-repo | 574c588f39c6be37e8489a56a0355b4bf7cdc37a | [
"MIT"
] | 1 | 2016-10-26T03:03:09.000Z | 2016-10-26T03:03:09.000Z | ref/MTPythonSampleCode.py | rgtjf/translator-repo | 574c588f39c6be37e8489a56a0355b4bf7cdc37a | [
"MIT"
] | null | null | null | ref/MTPythonSampleCode.py | rgtjf/translator-repo | 574c588f39c6be37e8489a56a0355b4bf7cdc37a | [
"MIT"
] | null | null | null | import websocket
import thread
import json
import requests
import urllib
import wave
import audioop
from time import sleep
import StringIO
import struct
import sys
import codecs
from xml.etree import ElementTree
doItAgain = "yes" #Control While loop
#End GetToken
#End GetTextAndTranslate()
if __name__ == "__main__":
finalToken = GetToken()
while (doItAgain == 'yes') or (doItAgain == 'Yes'):
GetTextAndTranslate(finalToken)
print ' '
doItAgain = raw_input('Type yes to translate more, any other key to end: ')
#end while
goodBye = raw_input('Thank you for using Microsoft Translator, we appreciate it. Good Bye')
#end main | 29.789474 | 141 | 0.619132 | import websocket
import thread
import json
import requests
import urllib
import wave
import audioop
from time import sleep
import StringIO
import struct
import sys
import codecs
from xml.etree import ElementTree
doItAgain = "yes" #Control While loop
def GetToken(): #Get the access token from ADM, token is good for 10 minutes
urlArgs = {
'client_id': 'ecnu_translator',
'client_secret': 'sc6x4pJQDBtyqmGhhRmOknjeeXcL1YGBUTkvZLtn62k=',
'scope': 'http://api.microsofttranslator.com',
'grant_type': 'client_credentials'
}
oauthUrl = 'https://datamarket.accesscontrol.windows.net/v2/OAuth2-13'
try:
oauthToken = json.loads(requests.post(oauthUrl, data = urllib.urlencode(urlArgs)).content) #make call to get ADM token and parse json
finalToken = "Bearer " + oauthToken['access_token'] #prepare the token
except OSError:
pass
return finalToken
#End GetToken
def GetTextAndTranslate(finalToken):
fromLangCode = " "
toLangCode = " "
textToTranslate = " "
print " "
print " Language List"
print " English"
print " German"
print " Italian"
print " Spanish"
print " French"
#Get the source Language
while (fromLangCode == " "):
sourceLang = raw_input("Type the name of a language from the list that you want to translate from: ")
if (sourceLang == "english") or (sourceLang == "English"):
fromLangCode = "en"
elif (sourceLang == "German") or (sourceLang == "german"):
fromLangCode = "de"
elif (sourceLang == "Italian") or (sourceLang == "italian"):
fromLangCode = "it"
elif (sourceLang == "Spanish") or (sourceLang == "spanish"):
fromLangCode = "es"
elif (sourceLang == "French") or (sourceLang == "french"):
fromLangCode = "fr"
else:
print " "
print "You need to pick a language from the List"
error = raw_input("Press any key to continue")
#End while
print " "
#Get the desitination Language
while (toLangCode == " "):
destLang = raw_input("Type the name of a language from the list that you want to translate to: ")
if (destLang == "english") or (destLang == "English"):
toLangCode = "en"
elif (destLang == "German") or (destLang == "german"):
toLangCode = "de"
elif (destLang == "Italian") or (destLang == "italian"):
toLangCode = "it"
elif (destLang == "Spanish") or (destLang == "spanish"):
toLangCode = "es"
elif (destLang == "French") or (destLang == "french"):
toLangCode = "fr"
else:
print " "
print "You need to pick a language from the List"
error = raw_input("Press any key to continue")
#End while
print " "
textToTranslate = raw_input("Type the text that you want to translate: ")
print " "
#Call to Microsoft Translator Service
headers = {"Authorization ": finalToken}
translateUrl = "http://api.microsofttranslator.com/v2/Http.svc/Translate?text={}&to={}".format(textToTranslate, toLangCode)
try:
translationData = requests.get(translateUrl, headers = headers) #make request
translation = ElementTree.fromstring(translationData.text.encode('utf-8')) # parse xml return values
print "The translation is---> ", translation.text #display translation
except OSError:
pass
print " "
#End GetTextAndTranslate()
if __name__ == "__main__":
finalToken = GetToken()
while (doItAgain == 'yes') or (doItAgain == 'Yes'):
GetTextAndTranslate(finalToken)
print ' '
doItAgain = raw_input('Type yes to translate more, any other key to end: ')
#end while
goodBye = raw_input('Thank you for using Microsoft Translator, we appreciate it. Good Bye')
#end main | 3,242 | 0 | 46 |
1c2a02f1b3096641c5efcafcd493401dbe62ecf8 | 21 | py | Python | aliyun-python-sdk-push/aliyunsdkpush/__init__.py | xiaozhao1/aliyun-openapi-python-sdk | 7297b69619fbe18a053ce552df9ab378b7c5719f | [
"Apache-2.0"
] | null | null | null | aliyun-python-sdk-push/aliyunsdkpush/__init__.py | xiaozhao1/aliyun-openapi-python-sdk | 7297b69619fbe18a053ce552df9ab378b7c5719f | [
"Apache-2.0"
] | null | null | null | aliyun-python-sdk-push/aliyunsdkpush/__init__.py | xiaozhao1/aliyun-openapi-python-sdk | 7297b69619fbe18a053ce552df9ab378b7c5719f | [
"Apache-2.0"
] | 1 | 2021-01-26T05:01:42.000Z | 2021-01-26T05:01:42.000Z | __version__ = "3.9.0" | 21 | 21 | 0.666667 | __version__ = "3.9.0" | 0 | 0 | 0 |
5031fd0853d0c74e88cffb6e61dfa6bc09087921 | 4,753 | py | Python | NNFS/Numpy_functions.py | AloBer03/MA_Alo-sBerger | 93e72f7940a3ea8bab3c72e00c92091c01dc5324 | [
"Unlicense"
] | null | null | null | NNFS/Numpy_functions.py | AloBer03/MA_Alo-sBerger | 93e72f7940a3ea8bab3c72e00c92091c01dc5324 | [
"Unlicense"
] | null | null | null | NNFS/Numpy_functions.py | AloBer03/MA_Alo-sBerger | 93e72f7940a3ea8bab3c72e00c92091c01dc5324 | [
"Unlicense"
] | null | null | null | # Numpy_functions
# (Own code)
# Why use Numpy?
# Because it's quicker (python libraries can be writen in C which can be much faster)
# It also makes the code much cleaner
# I still tried to recreate some Numpy function
# Dotproduct vector
# Transposition
# Dotproduct with matrices
# Adding vector
# Random (np.random.randn())
# Normal (gaussian) distribution with mean 0 and variance (1)
# and * 0.01 small enough to not affect training???
# Parameters are the dimension of the output matrix
# np.zeros() creates a matrix with the dimension being the parameters
# and all values being zero
# Numpy maximum (ReLU avtivation function)
# Sum function (axis=1)
# Highest value in a matrix (list wise)
# Average (mean)
# Clipping on both side
# Creating a list/array with steps
# Creating a array filled with zeros and the same shape
# Eye function: turning a list in one-hot vector
# Eye function but a vector as a diagonal
import random
print(random_binomial(1,0.2,10))
# Gives the absolute value back
# Gives the sign in return
# Calculates the standard deviation to the mean
| 26.259669 | 96 | 0.670734 | # Numpy_functions
# (Own code)
# Why use Numpy?
# Because it's quicker (python libraries can be writen in C which can be much faster)
# It also makes the code much cleaner
# I still tried to recreate some Numpy function
def randn(x, y):
ret = []
for i in range(x):
ret.append([np.random.randn() for y in range(y)])
return ret
# Dotproduct vector
def dotproduct(input_value, weights):
#only vectors
output = 0
for a, b in zip(input_value, weights):
output += a*b
return output
# Transposition
def transposition(matrix):
transposed_matrix = [[] for x in range(len(matrix[0]))]
for j in range(len(matrix)):
for i in range(len(matrix[j])):
transposed_matrix[i].append(matrix[j][i])
return transposed_matrix
# Dotproduct with matrices
def dotmatrix(matrix1, matrix2):
output_matrix = [[] for x in range(len(matrix1))]
for i in range(len(matrix1)):
additionar = 0
for j in range(len(matrix1[0])):
additionar += matrix1[i][j] * matrix2[j][i]
output_matrix[i].append(additionar)
return output_matrix
# Adding vector
def addition(vec1, vec2):
output = []
for a, b in zip(vec1, vec2):
output.append(a+b)
return(output)
# Random (np.random.randn())
# Normal (gaussian) distribution with mean 0 and variance (1)
# and * 0.01 small enough to not affect training???
# Parameters are the dimension of the output matrix
# np.zeros() creates a matrix with the dimension being the parameters
# and all values being zero
# Numpy maximum (ReLU avtivation function)
def activeate_ReLU(bias, inputs):
output = []
for i in inputs:
if i > -bias:
output.append(i+bias)
else:
output.append(0.0)
# Sum function (axis=1)
def sums(inputs,axis=1,keepdims=True):
output = []
for i in inputs:
output.append([sum(i)])
return output
# Highest value in a matrix (list wise)
def argmax(inputs):
output = []
for batch_set in inputs:
previous_value = batch_set[0]
for value in batch_set:
if value > previous_value:
previous_value = value
else:
pass
output.append([previous_value])
return output
# Average (mean)
def mean(inputs):
output = sum(inputs) / len(inputs)
return output
# Clipping on both side
def clipped(inputs, lower_boundery, upper_boundery):
while inputs[0] < lower_boundery:
del inputs[0]
while inputs[-1] > upper_boundery:
del inputs[-1]
return inputs
# Creating a list/array with steps
def arrange(start, end, step):
length = (end - start) /step
output = [start + x*step for x in range(int(length))]
return output
# Creating a array filled with zeros and the same shape
def zeros_like(inputs):
for i in range(len(inputs)):
for j in range(len(inputs[i])):
inputs[i][j] = 0
return inputs
# Eye function: turning a list in one-hot vector
def eye(length, true_values):
example = []
output = []
for i in range(length):
example.append([1 if x==i else 0 for x in range(length)])
for i in range(len(true_values)):
output.append(example[true_values[i]])
return output
# Eye function but a vector as a diagonal
def diagflat(inputs):
output = []
for i in range(len(inputs)):
output.append([inputs[i] if x==i else 0 for x in range(len(inputs))])
return output
import random
def random_binomial(n, p, size):
example_output = [1 for x in range(size)] ## Have the same dimension than output of neuron
while True: # repeat as long as necessary
index = random.randint(0, len(example_output) - 1) # Randomly choose index and set value to 0
example_output[index] = 0 # We might set an index that already is zeroed
dropped_out = 0 # There are different ways of overcoming this problem,
for value in example_output: # for simplicity we count values taht are exactly 0
if value == 0: # while it's extremely rare in real model,
dropped_out += 1 # that weights are exactly 0, this is not the best method for sure
if dropped_out / len(example_output) >= 1-p: # If required number of outputs is zeroed
break # - leave the loop
return example_output
print(random_binomial(1,0.2,10))
# Gives the absolute value back
def abs(value):
if value < 0:
return value * -1
else:
return value
# Gives the sign in return
def sign(value):
if value < 0:
return -1
elif value == 0:
return 0
else:
return 1
# Calculates the standard deviation to the mean
def std(values):
length = len(values)
adder = 0
for e in values:
adder += e
mean = adder / length # Calculate mean
adder = 0 # Reset adder
for e in values:
adder += (e-mean)**2
std = (adder / (length - 1))**0.5
return std
def reshape(y, axis1, axis2):
pass
| 3,151 | 0 | 444 |
a86c1bd2066142cee43c8949562ce9da445773be | 18,452 | py | Python | empress/core.py | 1Harshini/empress | 8ccd57b70207d2877cde11755d7e789c61313d0c | [
"Apache-2.0",
"CC0-1.0",
"BSD-3-Clause"
] | 34 | 2018-10-18T21:39:13.000Z | 2022-03-15T21:52:59.000Z | empress/core.py | 1Harshini/empress | 8ccd57b70207d2877cde11755d7e789c61313d0c | [
"Apache-2.0",
"CC0-1.0",
"BSD-3-Clause"
] | 486 | 2018-04-26T18:11:34.000Z | 2022-02-09T21:12:11.000Z | empress/core.py | 1Harshini/empress | 8ccd57b70207d2877cde11755d7e789c61313d0c | [
"Apache-2.0",
"CC0-1.0",
"BSD-3-Clause"
] | 28 | 2018-10-14T03:59:40.000Z | 2022-01-25T20:36:40.000Z | # ----------------------------------------------------------------------------
# Copyright (c) 2016-2020, empress development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from empress.tree import validate_tree, bp_tree_tips
from empress.tools import (
match_inputs, match_tree_and_feature_metadata,
shifting, filter_feature_metadata_to_tree
)
from empress.compression_utils import (
remove_empty_samples_and_features, compress_table,
compress_sample_metadata, compress_feature_metadata
)
import pkg_resources
import os
import pandas as pd
from shutil import copytree
from emperor import Emperor
from jinja2 import Environment, FileSystemLoader
SUPPORT_FILES = pkg_resources.resource_filename('empress', 'support_files')
TEMPLATES = os.path.join(SUPPORT_FILES, 'templates')
EMPEROR_CALLBACK_PATH = os.path.join(SUPPORT_FILES, 'js',
'emperor-callbacks.js')
| 41.1875 | 79 | 0.604758 | # ----------------------------------------------------------------------------
# Copyright (c) 2016-2020, empress development team.
#
# Distributed under the terms of the Modified BSD License.
#
# The full license is in the file LICENSE, distributed with this software.
# ----------------------------------------------------------------------------
from empress.tree import validate_tree, bp_tree_tips
from empress.tools import (
match_inputs, match_tree_and_feature_metadata,
shifting, filter_feature_metadata_to_tree
)
from empress.compression_utils import (
remove_empty_samples_and_features, compress_table,
compress_sample_metadata, compress_feature_metadata
)
import pkg_resources
import os
import pandas as pd
from shutil import copytree
from emperor import Emperor
from jinja2 import Environment, FileSystemLoader
SUPPORT_FILES = pkg_resources.resource_filename('empress', 'support_files')
TEMPLATES = os.path.join(SUPPORT_FILES, 'templates')
EMPEROR_CALLBACK_PATH = os.path.join(SUPPORT_FILES, 'js',
'emperor-callbacks.js')
class Empress():
def __init__(self, tree, table=None, sample_metadata=None,
feature_metadata=None, ordination=None,
ignore_missing_samples=False, filter_extra_samples=False,
filter_missing_features=False, resource_path=None,
shear_to_table=True, shear_to_feature_metadata=False):
"""Visualize a phylogenetic tree
Use this object to interactively display a phylogenetic tree using the
Empress GUI.
Note that the table and sample metadata must either both be specified
or both be None. If only one of them is None, this will raise a
ValueError. If both are None, then the values of the ordination,
ignore_missing_samples, filter_extra_samples, filter_missing_features,
and shear_to_table arguments will be ignored since no sample
information is available.
Parameters
----------
tree: bp.BP
The phylogenetic tree to visualize.
table: biom.Table, optional
The matrix to visualize paired with the phylogenetic tree.
sample_metadata: pd.DataFrame, optional
DataFrame object with the metadata associated to the samples in the
``ordination`` object, should have an index set and it should match
the identifiers in the ``ordination`` object.
feature_metadata: pd.DataFrame, optional
DataFrame object with the metadata associated to the names of
tips and/or internal nodes in the ``tree`` object, should have an
index set and it should match at least one of these nodes' names.
ordination: skbio.OrdinationResults, optional
Object containing the computed values for an ordination method in
scikit-bio. Currently supports skbio.stats.ordination.PCoA and
skbio.stats.ordination.RDA results.
ignore_missing_samples: bool, optional (default False)
If True, pads missing samples (i.e. samples in the table but not
the metadata) with placeholder metadata. If False, raises a
DataMatchingError if any such samples exist. (Note that in either
case, samples in the metadata but not in the table are filtered
out; and if no samples are shared between the table and metadata, a
DataMatchingError is raised regardless.) This is analogous to the
ignore_missing_samples flag in Emperor.
filter_extra_samples: bool, optional (default False)
If True, ignores samples in the feature table that are not present
in the ordination. If False, raises a DataMatchingError if such
samples exist.
filter_missing_features: bool, optional (default False)
If True, filters features from the table that aren't present as
tips in the tree. If False, raises a DataMatchingError if any such
features exist. (Note that in either case, features in the tree but
not in the table are preserved.)
resource_path: str, optional
Load the resources from a user-specified remote location. If set to
None resources are loaded from the current directory.
shear_to_table: bool, optional
If True, shears the tree to just the tips that are present as
features in the feature table. Otherwise, the tree is not shorn.
Attributes
----------
tree:
Phylogenetic tree.
table:
Contingency matrix for the phylogeny.
samples:
Sample metadata.
features:
Feature metadata.
ordination:
Ordination matrix to visualize simultaneously with the tree.
base_url:
Base path to the remote resources.
"""
self.tree = tree
# Use XOR to verify that either both or neither of the table and
# sample metadata are None. Parens needed for precedence stuff.
if (table is None) ^ (sample_metadata is None):
# The caller messed something up, so raise an error.
# It should not be possible for the user to pass *just* one of
# these things (qiime empress community-plot requires both, and
# qiime empress tree-plot accepts neither).
raise ValueError(
"Both the table and sample metadata should be specified or "
"None. However, only one of them is None."
)
elif table is not None and sample_metadata is not None:
self.is_community_plot = True
else:
self.is_community_plot = False
self.table = table
if sample_metadata is not None:
self.samples = sample_metadata.copy()
else:
self.samples = None
if feature_metadata is not None:
# this will be transformed into self.tip_md and self.int_md in
# self._validate_and_match_data()
self.features = feature_metadata.copy()
else:
if shear_to_feature_metadata:
raise ValueError(
"Feature metadata must be provided in order to shear "
"to feature metadata."
)
self.features = None
self.ordination = ordination
self.is_empire_plot = (self.ordination is not None)
self.base_url = resource_path
if self.base_url is None:
self.base_url = 'support_files'
self._validate_and_match_data(
ignore_missing_samples,
filter_extra_samples,
filter_missing_features,
shear_to_table,
shear_to_feature_metadata,
)
if self.is_empire_plot:
# biplot arrows can optionally have metadata, think for example
# a study where the arrows represent pH, Alkalinity, etc.
# Therefore, check if there are matches in the metadata, if
# there aren't additional errors can be overriden with the
# ignore_missing_samples flag
feature_metadata = None
if self.ordination.features is not None:
# if there are no matches set to None so Emperor can ignore
# the feature metadata
if self.tip_md is None and self.int_md is None:
feature_metadata = pd.DataFrame()
else:
feature_metadata = pd.concat([self.tip_md, self.int_md])
arrows = self.ordination.features.index
if (feature_metadata.index.intersection(arrows).empty or
feature_metadata.empty):
feature_metadata = None
self._emperor = Emperor(
self.ordination, mapping_file=self.samples,
feature_mapping_file=feature_metadata,
ignore_missing_samples=ignore_missing_samples,
remote='./emperor-resources')
else:
self._emperor = None
def _validate_and_match_data(self, ignore_missing_samples,
filter_extra_samples,
filter_missing_features,
shear_to_table,
shear_to_feature_metadata):
if self.is_community_plot:
# Hack to unpack long tuples: https://stackoverflow.com/q/26036143
(
self.table, self.samples, self.tip_md, self.int_md,
self.tax_cols
) = match_inputs(
self.tree, self.table, self.samples, self.features,
self.ordination, ignore_missing_samples, filter_extra_samples,
filter_missing_features
)
# Remove empty samples and features from the table (and remove the
# removed samples from the sample metadata). We also pass in the
# ordination, if present, to this function -- so we can throw an
# error if the ordination actually contains these empty
# samples/features.
#
# We purposefully do this removal *after* matching (so we know the
# data inputs match up) and *before* shearing (so empty features
# in the table are no longer included as tips in the tree).
self.table, self.samples = remove_empty_samples_and_features(
self.table, self.samples, self.ordination
)
# remove unobserved features from the phylogeny (shear the tree)
if shear_to_table:
features = set(self.table.ids(axis='observation'))
self.tree = self.tree.shear(features)
# Remove features in the feature metadata that are no longer
# present in the tree, due to being shorn off
if self.tip_md is not None or self.int_md is not None:
# (Technically they should always both be None or both be
# DataFrames -- there's no in-between)
self.tip_md, self.int_md = filter_feature_metadata_to_tree(
self.tip_md, self.int_md, self.tree
)
else:
if shear_to_feature_metadata:
features = set(self.features.index)
all_tips = set(bp_tree_tips(self.tree))
# check that feature metadata contains at least 1 tip
if not features.intersection(all_tips):
raise ValueError(
"Cannot shear tree to feature metadata: no tips in "
"the tree are present in the feature metadata."
)
self.tree = self.tree.shear(features)
(
self.tip_md, self.int_md, self.tax_cols
) = match_tree_and_feature_metadata(self.tree, self.features)
validate_tree(self.tree)
def copy_support_files(self, target=None):
"""Copies the support files to a target directory
If an ordination is included Emperor's support files will also be
copied over (in a directory named emperor-resources).
Parameters
----------
target : str
The path where resources should be copied to. By default it copies
the files to ``self.base_url``.
"""
if target is None:
target = self.base_url
# copy the required resources
copytree(SUPPORT_FILES, os.path.join(target, 'support_files'))
if self._emperor is not None:
self._emperor.copy_support_files(os.path.join(target,
'emperor-resources'))
def __str__(self):
return self.make_empress()
def make_empress(self):
"""Build an empress plot
Returns
-------
str
Formatted empress plot.
Notes
-----
Once you generate the plot (and write it to a HTML file in a given
directory) you will need to copy the support files (the JS/CSS/etc.
code needed to view the visualization) to the same directory by calling
the ``copy_support_files`` method.
See Also
--------
empress.core.Empress.copy_support_files
"""
main_template = self._get_template()
# _process_data does a lot of munging to the coordinates data and
# to_dict puts the data into a dictionary-like object for consumption
data = self.to_dict()
plot = main_template.render(data)
return plot
def to_dict(self):
"""Convert processed data into a dictionary
Warning: the object returned by to_dict will contain references to
internal variables. Exercise caution if modifying the value of objects
returned by to_dict.
Returns
-------
dict
A dictionary describing the plots contained in the ordination
object and the sample + feature metadata.
"""
s_ids = f_ids = cmp_table = sm_cols = compressed_sm = None
sid2idxs = fid2idxs = {}
if self.is_community_plot:
# The fid2idxs dict we get from compress_table() is temporary --
# later, we'll restructure it so that the keys (feature IDs) are
# nodes' postorder positions in the tree rather than arbitrary
# unique integers. (TODO: it should be possible to speed this up by
# passing the tree to compress_table() so postorder positions can
# immediately be used as keys / feature IDs without an intermediate
# step.)
s_ids, f_ids, sid2idxs, fid2idxs_t, cmp_table = compress_table(
self.table
)
sm_cols, compressed_sm = compress_sample_metadata(
sid2idxs, self.samples
)
fm_cols, compressed_tm_tmp, compressed_im_tmp = \
compress_feature_metadata(self.tip_md, self.int_md)
# Use nodes' postorder positions as their "IDs" for the BIOM table and
# feature metadata
compressed_tm = {}
compressed_im = {}
# bptree indices start at one, hence we pad the arrays
names = [-1]
lengths = [-1]
for i in range(1, len(self.tree) + 1):
node = self.tree.postorderselect(i)
name = self.tree.name(node)
names.append(name)
lengths.append(self.tree.length(node))
if self.is_community_plot and name in fid2idxs_t:
fid2idxs[i] = fid2idxs_t[name]
f_ids[fid2idxs[i]] = i
if name in compressed_tm_tmp:
compressed_tm[i] = compressed_tm_tmp[name]
# Note: for internal metadata, node names may not be unique. Thus,
# we duplicate the internal node metadata for each node in the
# metadata with the same name.
if name in compressed_im_tmp:
compressed_im[i] = compressed_im_tmp[name]
data_to_render = {
'base_url': self.base_url,
# tree info
'tree': shifting(self.tree.B),
'lengths': lengths,
'names': names,
# Should we show sample metadata coloring / animation panels?
'is_community_plot': self.is_community_plot,
# Are we working with an EMPire plot?
'is_empire_plot': self.is_empire_plot,
# feature table
's_ids': s_ids,
'f_ids': f_ids,
's_ids_to_indices': sid2idxs,
'f_ids_to_indices': fid2idxs,
'compressed_table': cmp_table,
# sample metadata
'sample_metadata_columns': sm_cols,
'compressed_sample_metadata': compressed_sm,
# feature metadata
'feature_metadata_columns': fm_cols,
'split_taxonomy_columns': self.tax_cols,
'compressed_tip_metadata': compressed_tm,
'compressed_int_metadata': compressed_im,
# Emperor integration
'emperor_div': '',
'emperor_require_logic': '',
'emperor_style': '',
'emperor_base_dependencies': '',
'emperor_classes': ''
}
if self._emperor is not None:
data_to_render.update(self._scavenge_emperor())
return data_to_render
def _get_template(self, standalone=False):
"""Get the jinja template object
Parameters
----------
standalone: bool, optional
Whether or not the generated plot will load resources locally
(``True``), or from a specified URL (``False``).
Returns
-------
jinja2.Template
Template where the plot is created.
"""
# based on: http://stackoverflow.com/a/6196098
env = Environment(loader=FileSystemLoader(TEMPLATES))
return env.get_template('empress-template.html')
def _scavenge_emperor(self):
self._emperor.width = '50vw'
self._emperor.height = '100vh; float: right'
# make the background white so it matches Empress
self._emperor.set_background_color('white')
self._emperor.set_axes(color='black')
# The following line references will be replace with API calls to the
# Emperor object, however those are not implemented yet
emperor_base_dependencies = self._emperor.render_base_dependencies()
style = self._emperor.render_style()
# main divs for emperor
emperor_div = self._emperor.render_html('emperor-in-empire')
# main js script for emperor, including additional callbacks
with open(EMPEROR_CALLBACK_PATH) as f:
self._emperor.js_on_ready = f.read()
emperor_require_logic = self._emperor.render_js('emperor-in-empire')
emperor_data = {
'emperor_div': emperor_div,
'emperor_require_logic': emperor_require_logic,
'emperor_style': style,
'emperor_base_dependencies': emperor_base_dependencies,
'emperor_classes': 'combined-plot-container'
}
return emperor_data
| 4,131 | 13,207 | 23 |
05ce99a0b2198dd5a20f43623646c98a8d4cb464 | 513 | py | Python | chapter9/task2.py | nvnovitskiy/python_sstu_course | 5de1830eb4430349df8ab1c65a9f16f82a9b91a6 | [
"MIT"
] | null | null | null | chapter9/task2.py | nvnovitskiy/python_sstu_course | 5de1830eb4430349df8ab1c65a9f16f82a9b91a6 | [
"MIT"
] | null | null | null | chapter9/task2.py | nvnovitskiy/python_sstu_course | 5de1830eb4430349df8ab1c65a9f16f82a9b91a6 | [
"MIT"
] | null | null | null | """
Используя цифры 1, 2, 3, 4, 5, 6, 7, 8, 9 по одному разу, составить два натуральных числа А и В,
таких, что A корень из B. Найти все решения.
"""
second_exercise()
| 28.5 | 98 | 0.538012 | """
Используя цифры 1, 2, 3, 4, 5, 6, 7, 8, 9 по одному разу, составить два натуральных числа А и В,
таких, что A корень из B. Найти все решения.
"""
def second_exercise():
for y in range(1, 32000):
x = y ** 2
str_a, str_b = str(x), str(y),
set_a, set_b = set(str_a), set(str_b)
if '0' not in set_a and '0' not in set_b:
if len(set_a) == len(str_a) and len(set_b) == len(str_b):
print(f"Корень из {x} = {y}")
second_exercise()
| 316 | 0 | 25 |
ee5a8800786aad67b3d5ec815bd0ac4b0a437a35 | 2,087 | py | Python | tests/cells_test.py | martinxyz/pixeldrift | 205a17473d7dfb1abf8cf357d045cff12d0c615e | [
"MIT"
] | null | null | null | tests/cells_test.py | martinxyz/pixeldrift | 205a17473d7dfb1abf8cf357d045cff12d0c615e | [
"MIT"
] | null | null | null | tests/cells_test.py | martinxyz/pixeldrift | 205a17473d7dfb1abf8cf357d045cff12d0c615e | [
"MIT"
] | null | null | null | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from pixeldrift import Cells, tile_size
if __name__ == '__main__':
unittest.main()
| 43.479167 | 94 | 0.620987 | import unittest
import numpy as np
from numpy.testing import assert_array_equal
from pixeldrift import Cells, tile_size
class CellTest(unittest.TestCase):
def test_initialization(self):
cells = Cells()
self.assertTrue(np.all(cells.get_data() == 0))
def test_mask(self):
cells = Cells()
self.assertTrue(np.all(cells.get_mask()))
self.assertEqual(np.sum(cells.get_mask(-1000, 0, w=1000)), 0)
self.assertEqual(np.sum(cells.get_mask(0, -1000, h=1000)), 0)
self.assertEqual(np.sum(cells.get_mask(-999, 0, w=1000, h=1)), 1)
self.assertEqual(np.sum(cells.get_mask(0, -999, w=1, h=1000)), 1)
self.assertEqual(np.sum(cells.get_mask(tile_size-1, 0, w=1000, h=7)), 7)
self.assertEqual(np.sum(cells.get_mask(0, tile_size-1, w=7, h=1000)), 7)
def test_data_tiling(self):
cells = Cells()
data = np.random.randint(0, 2, size=(tile_size, tile_size))
for dx, dy in [(0, 0), (-tile_size, 0), (0, tile_size), (-7*tile_size, -9*tile_size)]:
msg = f'dx,dy: {dx, dy}'
cells.set_data(data, x=dx, y=dy)
assert_array_equal(cells.get_data(), data, msg)
assert_array_equal(cells.get_data(x=tile_size), data, msg)
assert_array_equal(cells.get_data(x=-tile_size, y=-30*tile_size), data, msg)
cells.set_data(np.zeros((tile_size, tile_size)), -33, -11)
self.assertTrue(np.all(cells.get_data() == 0))
self.assertTrue(np.all(cells.get_data(-88, -88, tile_size+2*88, tile_size+2*88) == 0))
def test_data_offset_coordinates(self):
cells = Cells()
data = np.ones((2, 7), dtype='uint8')
cells.set_data(data, -1, -1)
self.assertEqual(np.sum(cells.get_data()), 2*7)
self.assertEqual(np.sum(cells.get_data(-1, -1, 7, 2)), 2*7)
self.assertEqual(np.sum(cells.get_data(0, 0, 20, 20)), 6)
self.assertEqual(np.sum(cells.get_data(-1, 0, 20, 20)), 7)
self.assertEqual(np.sum(cells.get_data(0, -1, 20, 20)), 2*6)
if __name__ == '__main__':
unittest.main()
| 1,775 | 13 | 130 |
2cac0291ce4b11387a4c6fbc008dd43bd9ad7e0e | 2,394 | py | Python | garden_scorer/src/garden_scorer.py | emilybache/BeeFriendly | 7582d8f7140f2d0088404d9cb1d47b6231606c49 | [
"MIT"
] | 4 | 2020-06-14T13:42:39.000Z | 2022-01-29T14:36:53.000Z | garden_scorer/src/garden_scorer.py | emilybache/BeeFriendly | 7582d8f7140f2d0088404d9cb1d47b6231606c49 | [
"MIT"
] | 2 | 2022-02-13T15:19:44.000Z | 2022-02-25T12:32:16.000Z | garden_scorer/src/garden_scorer.py | emilybache/BeeFriendly | 7582d8f7140f2d0088404d9cb1d47b6231606c49 | [
"MIT"
] | 4 | 2020-06-11T09:31:45.000Z | 2021-08-17T14:00:41.000Z | import sys
import json
import requests
from flask import Flask, jsonify
from flask import request
from tracing import init_tracer, flask_to_scope, parse_baggage
import opentracing
from opentracing_instrumentation.client_hooks import install_all_patches
from flask_opentracing import FlaskTracer
from flask_cors import CORS, cross_origin
app = Flask('garden-scorer')
init_tracer('garden-scorer')
CORS(app)
install_all_patches()
flask_tracer = FlaskTracer(opentracing.tracer, True, app)
@app.route("/flower_scorer", methods=['GET', 'POST'])
@cross_origin()
if __name__ == "__main__":
app.run(port=3004)
| 34.2 | 150 | 0.700919 | import sys
import json
import requests
from flask import Flask, jsonify
from flask import request
from tracing import init_tracer, flask_to_scope, parse_baggage
import opentracing
from opentracing_instrumentation.client_hooks import install_all_patches
from flask_opentracing import FlaskTracer
from flask_cors import CORS, cross_origin
app = Flask('garden-scorer')
init_tracer('garden-scorer')
CORS(app)
install_all_patches()
flask_tracer = FlaskTracer(opentracing.tracer, True, app)
@app.route("/flower_scorer", methods=['GET', 'POST'])
@cross_origin()
def flower_scorer():
with flask_to_scope(flask_tracer, request) as scope:
#parse_baggage(request.headers, scope)
if request.method == 'POST':
params = json.loads(request.data)
print(f"got form data {params.keys()}")
garden_size = params['selected_garden_size']
flowers = params['selected_flowers']
score = calculate_score(garden_size, flowers)
opentracing.tracer.active_span.set_tag('response', score)
return jsonify({"score": score})
def fetch_flowering_months(flowers):
flowering_months = set()
for flower in flowers:
json_object = _get("http://localhost:3005/getFlower/" + flower).json()
flowering_months = flowering_months.union(json_object["flowering_months"])
return flowering_months
def _get(url, params=None):
r = requests.get(url, params=params)
assert r.status_code == 200
return r
def calculate_score(garden_size, flowers):
with opentracing.tracer.start_active_span('calculate-score'):
if len(flowers) == 0:
return f"Our furry flying friends will be disappointed! You should plant some more flowers in your {garden_size} garden."
if garden_size == "windowbox":
return f"Top marks! Bees love your windowbox."
else:
flowering_months = fetch_flowering_months(flowers)
if "july" not in flowering_months and "august" not in flowering_months:
return f"Good work! Your garden would be even more friendly if you planted some flowers that bloom in " + get_months(flowering_months)
else:
return f"Top marks! Bees love your {garden_size} garden."
def get_months(flowering_months):
return "July and August"
if __name__ == "__main__":
app.run(port=3004)
| 1,666 | 0 | 114 |
6dc0b87b22762e447f85f1aba8796f02985cbf0e | 2,251 | py | Python | restiro/tests/test_middlewares.py | Ati-ns/restiro | d18be226d162ee81f6af7bdf83ca9e0747eb8837 | [
"MIT"
] | null | null | null | restiro/tests/test_middlewares.py | Ati-ns/restiro | d18be226d162ee81f6af7bdf83ca9e0747eb8837 | [
"MIT"
] | null | null | null | restiro/tests/test_middlewares.py | Ati-ns/restiro | d18be226d162ee81f6af7bdf83ca9e0747eb8837 | [
"MIT"
] | null | null | null | import pytest
from os.path import join
from webtest.debugapp import debug_app
from restiro import DocumentationRoot, clean_examples_dir
from restiro.tests.helpers import package_dir, mockup_resources
examples_dir = join(package_dir, 'examples')
@pytest.fixture('session', autouse=True)
| 28.493671 | 77 | 0.689916 | import pytest
from os.path import join
from webtest.debugapp import debug_app
from restiro import DocumentationRoot, clean_examples_dir
from restiro.tests.helpers import package_dir, mockup_resources
examples_dir = join(package_dir, 'examples')
@pytest.fixture('session', autouse=True)
def wrap_directories():
clean_examples_dir()
yield
def test_webtest_middleware():
from restiro.middlewares.webtest import TestApp
# Initiate test app (middleware)
test_app = TestApp(
app=debug_app
)
# Default request with no documentation
test_app.get('/too/far/away')
# Simple request
test_app.doc = True
test_app.get('/far/away')
test_app.doc = True
test_app.get('/user', 'a=b').mustcontain('a=b')
# Fill examples by request
test_app.doc = True
test_app.get('/user')
# JSON request
test_app.doc = True
test_app.post_json('/user', {
'full_name': 'Meyti'
})
test_app.doc = True
test_app.post_json('/user?status=400+Bad+name', {
'full_name': 'Meyti2'
}, status=400)
# Initiate documentation root
docs_root = DocumentationRoot(
title='Hello World'
)
docs_root.set_resources(*mockup_resources())
docs_root.load_resource_examples()
resource = docs_root.resources.find(path='/user', method='get')
assert len(resource.examples) == 2
assert resource.examples[0].response.status == 200
assert resource.examples[0].response.body_format is None
# JSON Request
resource = docs_root.resources.find(path='/user', method='post')
assert 'Meyti' in resource.examples[0].request.__repr__()
assert 'Meyti' in resource.examples[0].response.__repr__()
assert 'content-type' in resource.examples[0].request.headers
assert resource.examples[1].response.reason == 'Bad name'
resource = docs_root.resources.find(path='/user/1/image/1', method='get')
assert resource.__str__() == 'GET /user/:user_id/image/:image_id'
resource = docs_root.resources.find(path='/user/1/image', method='get')
assert resource.__str__() == 'GET /user/:user_id/image'
resource = docs_root.resources.find(path='/user/1', method='get')
assert resource.__str__() == 'GET /user/:user_id'
| 1,913 | 0 | 45 |
c968cd59f2cf518a3622db559012541072f7024b | 6,562 | py | Python | code/proto/run_params_pb2.py | ndjaitly/multi-frame | a403de34a5d196d1843e483f35b9573f5dbb2548 | [
"Apache-2.0"
] | 7 | 2015-02-10T05:58:03.000Z | 2018-03-06T21:55:19.000Z | code/proto/run_params_pb2.py | ndjaitly/multi-frame | a403de34a5d196d1843e483f35b9573f5dbb2548 | [
"Apache-2.0"
] | null | null | null | code/proto/run_params_pb2.py | ndjaitly/multi-frame | a403de34a5d196d1843e483f35b9573f5dbb2548 | [
"Apache-2.0"
] | null | null | null | # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: run_params.proto
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
DESCRIPTOR = _descriptor.FileDescriptor(
name='run_params.proto',
package='run_params',
serialized_pb='\n\x10run_params.proto\x12\nrun_params\"\xa1\x02\n\nDataParams\x12\x17\n\tuse_delta\x18\x01 \x02(\x08:\x04true\x12\x45\n\rnormalization\x18\x02 \x02(\x0e\x32(.run_params.DataParams.NormalizationType:\x04\x43MVN\x12\x1d\n\x11num_frames_per_pt\x18\x03 \x02(\x05:\x02\x31\x35\x12$\n\x18num_output_frames_per_pt\x18\x04 \x01(\x05:\x02\x31\x35\x12 \n\x11smooth_alignments\x18\x05 \x01(\x08:\x05\x66\x61lse\"L\n\x11NormalizationType\x12\x07\n\x03\x43MN\x10\x00\x12\x08\n\x04\x43MVN\x10\x01\x12\x12\n\x0eGLOB_NORMALIZE\x10\x02\x12\x10\n\x0cNO_NORMALIZE\x10\x03\"\x82\x01\n\x06params\x12+\n\x0b\x64\x61ta_params\x18\x01 \x02(\x0b\x32\x16.run_params.DataParams\x12\x17\n\nbatch_size\x18\x02 \x02(\x05:\x03\x31\x32\x38\x12\x1a\n\x0emax_bad_epochs\x18\x03 \x02(\x05:\x02\x31\x30\x12\x16\n\nmax_epochs\x18\x04 \x02(\x05:\x02\x34\x30')
_DATAPARAMS_NORMALIZATIONTYPE = _descriptor.EnumDescriptor(
name='NormalizationType',
full_name='run_params.DataParams.NormalizationType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='CMN', index=0, number=0,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='CMVN', index=1, number=1,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='GLOB_NORMALIZE', index=2, number=2,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='NO_NORMALIZE', index=3, number=3,
options=None,
type=None),
],
containing_type=None,
options=None,
serialized_start=246,
serialized_end=322,
)
_DATAPARAMS = _descriptor.Descriptor(
name='DataParams',
full_name='run_params.DataParams',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='use_delta', full_name='run_params.DataParams.use_delta', index=0,
number=1, type=8, cpp_type=7, label=2,
has_default_value=True, default_value=True,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='normalization', full_name='run_params.DataParams.normalization', index=1,
number=2, type=14, cpp_type=8, label=2,
has_default_value=True, default_value=1,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='num_frames_per_pt', full_name='run_params.DataParams.num_frames_per_pt', index=2,
number=3, type=5, cpp_type=1, label=2,
has_default_value=True, default_value=15,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='num_output_frames_per_pt', full_name='run_params.DataParams.num_output_frames_per_pt', index=3,
number=4, type=5, cpp_type=1, label=1,
has_default_value=True, default_value=15,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='smooth_alignments', full_name='run_params.DataParams.smooth_alignments', index=4,
number=5, type=8, cpp_type=7, label=1,
has_default_value=True, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
_DATAPARAMS_NORMALIZATIONTYPE,
],
options=None,
is_extendable=False,
extension_ranges=[],
serialized_start=33,
serialized_end=322,
)
_PARAMS = _descriptor.Descriptor(
name='params',
full_name='run_params.params',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='data_params', full_name='run_params.params.data_params', index=0,
number=1, type=11, cpp_type=10, label=2,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='batch_size', full_name='run_params.params.batch_size', index=1,
number=2, type=5, cpp_type=1, label=2,
has_default_value=True, default_value=128,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='max_bad_epochs', full_name='run_params.params.max_bad_epochs', index=2,
number=3, type=5, cpp_type=1, label=2,
has_default_value=True, default_value=10,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='max_epochs', full_name='run_params.params.max_epochs', index=3,
number=4, type=5, cpp_type=1, label=2,
has_default_value=True, default_value=40,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
extension_ranges=[],
serialized_start=325,
serialized_end=455,
)
_DATAPARAMS.fields_by_name['normalization'].enum_type = _DATAPARAMS_NORMALIZATIONTYPE
_DATAPARAMS_NORMALIZATIONTYPE.containing_type = _DATAPARAMS;
_PARAMS.fields_by_name['data_params'].message_type = _DATAPARAMS
DESCRIPTOR.message_types_by_name['DataParams'] = _DATAPARAMS
DESCRIPTOR.message_types_by_name['params'] = _PARAMS
# @@protoc_insertion_point(module_scope)
| 37.497143 | 839 | 0.742457 | # Generated by the protocol buffer compiler. DO NOT EDIT!
# source: run_params.proto
from google.protobuf import descriptor as _descriptor
from google.protobuf import message as _message
from google.protobuf import reflection as _reflection
from google.protobuf import descriptor_pb2
# @@protoc_insertion_point(imports)
DESCRIPTOR = _descriptor.FileDescriptor(
name='run_params.proto',
package='run_params',
serialized_pb='\n\x10run_params.proto\x12\nrun_params\"\xa1\x02\n\nDataParams\x12\x17\n\tuse_delta\x18\x01 \x02(\x08:\x04true\x12\x45\n\rnormalization\x18\x02 \x02(\x0e\x32(.run_params.DataParams.NormalizationType:\x04\x43MVN\x12\x1d\n\x11num_frames_per_pt\x18\x03 \x02(\x05:\x02\x31\x35\x12$\n\x18num_output_frames_per_pt\x18\x04 \x01(\x05:\x02\x31\x35\x12 \n\x11smooth_alignments\x18\x05 \x01(\x08:\x05\x66\x61lse\"L\n\x11NormalizationType\x12\x07\n\x03\x43MN\x10\x00\x12\x08\n\x04\x43MVN\x10\x01\x12\x12\n\x0eGLOB_NORMALIZE\x10\x02\x12\x10\n\x0cNO_NORMALIZE\x10\x03\"\x82\x01\n\x06params\x12+\n\x0b\x64\x61ta_params\x18\x01 \x02(\x0b\x32\x16.run_params.DataParams\x12\x17\n\nbatch_size\x18\x02 \x02(\x05:\x03\x31\x32\x38\x12\x1a\n\x0emax_bad_epochs\x18\x03 \x02(\x05:\x02\x31\x30\x12\x16\n\nmax_epochs\x18\x04 \x02(\x05:\x02\x34\x30')
_DATAPARAMS_NORMALIZATIONTYPE = _descriptor.EnumDescriptor(
name='NormalizationType',
full_name='run_params.DataParams.NormalizationType',
filename=None,
file=DESCRIPTOR,
values=[
_descriptor.EnumValueDescriptor(
name='CMN', index=0, number=0,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='CMVN', index=1, number=1,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='GLOB_NORMALIZE', index=2, number=2,
options=None,
type=None),
_descriptor.EnumValueDescriptor(
name='NO_NORMALIZE', index=3, number=3,
options=None,
type=None),
],
containing_type=None,
options=None,
serialized_start=246,
serialized_end=322,
)
_DATAPARAMS = _descriptor.Descriptor(
name='DataParams',
full_name='run_params.DataParams',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='use_delta', full_name='run_params.DataParams.use_delta', index=0,
number=1, type=8, cpp_type=7, label=2,
has_default_value=True, default_value=True,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='normalization', full_name='run_params.DataParams.normalization', index=1,
number=2, type=14, cpp_type=8, label=2,
has_default_value=True, default_value=1,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='num_frames_per_pt', full_name='run_params.DataParams.num_frames_per_pt', index=2,
number=3, type=5, cpp_type=1, label=2,
has_default_value=True, default_value=15,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='num_output_frames_per_pt', full_name='run_params.DataParams.num_output_frames_per_pt', index=3,
number=4, type=5, cpp_type=1, label=1,
has_default_value=True, default_value=15,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='smooth_alignments', full_name='run_params.DataParams.smooth_alignments', index=4,
number=5, type=8, cpp_type=7, label=1,
has_default_value=True, default_value=False,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
_DATAPARAMS_NORMALIZATIONTYPE,
],
options=None,
is_extendable=False,
extension_ranges=[],
serialized_start=33,
serialized_end=322,
)
_PARAMS = _descriptor.Descriptor(
name='params',
full_name='run_params.params',
filename=None,
file=DESCRIPTOR,
containing_type=None,
fields=[
_descriptor.FieldDescriptor(
name='data_params', full_name='run_params.params.data_params', index=0,
number=1, type=11, cpp_type=10, label=2,
has_default_value=False, default_value=None,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='batch_size', full_name='run_params.params.batch_size', index=1,
number=2, type=5, cpp_type=1, label=2,
has_default_value=True, default_value=128,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='max_bad_epochs', full_name='run_params.params.max_bad_epochs', index=2,
number=3, type=5, cpp_type=1, label=2,
has_default_value=True, default_value=10,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
_descriptor.FieldDescriptor(
name='max_epochs', full_name='run_params.params.max_epochs', index=3,
number=4, type=5, cpp_type=1, label=2,
has_default_value=True, default_value=40,
message_type=None, enum_type=None, containing_type=None,
is_extension=False, extension_scope=None,
options=None),
],
extensions=[
],
nested_types=[],
enum_types=[
],
options=None,
is_extendable=False,
extension_ranges=[],
serialized_start=325,
serialized_end=455,
)
_DATAPARAMS.fields_by_name['normalization'].enum_type = _DATAPARAMS_NORMALIZATIONTYPE
_DATAPARAMS_NORMALIZATIONTYPE.containing_type = _DATAPARAMS;
_PARAMS.fields_by_name['data_params'].message_type = _DATAPARAMS
DESCRIPTOR.message_types_by_name['DataParams'] = _DATAPARAMS
DESCRIPTOR.message_types_by_name['params'] = _PARAMS
class DataParams(_message.Message):
__metaclass__ = _reflection.GeneratedProtocolMessageType
DESCRIPTOR = _DATAPARAMS
# @@protoc_insertion_point(class_scope:run_params.DataParams)
class params(_message.Message):
__metaclass__ = _reflection.GeneratedProtocolMessageType
DESCRIPTOR = _PARAMS
# @@protoc_insertion_point(class_scope:run_params.params)
# @@protoc_insertion_point(module_scope)
| 0 | 318 | 46 |
7d06bd46893cd5ea180e1a8a50ef425bd315ff52 | 628 | py | Python | setup.py | cjsoft/feitify | 02b1e48e9943ec05fa6d573d71a4dab9462e0a9e | [
"MIT"
] | 2 | 2020-11-25T10:07:31.000Z | 2021-04-04T09:28:58.000Z | setup.py | cjsoft/feitify | 02b1e48e9943ec05fa6d573d71a4dab9462e0a9e | [
"MIT"
] | null | null | null | setup.py | cjsoft/feitify | 02b1e48e9943ec05fa6d573d71a4dab9462e0a9e | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
from setuptools import setup
import setuptools
setup_dict = dict(
name="feititfy",
version="0.0.2a0",
author="cjsoft",
author_email="egwcyh@gmail.com",
description="Notify you using feishu custom bot by webhook",
long_description="""Notify you using feishu custom bot by webhook
Plese refer to project homepage to get usage introduction.""",
url="https://github.com/cjsoft/feitify",
python_requires=">=3.5",
packages=setuptools.find_packages(where=".", include=("feitify.*")),
scripts=["bin/feitify"],
install_requires=["requests"],
)
setup(**setup_dict)
| 29.904762 | 72 | 0.697452 | #!/usr/bin/env python3
from setuptools import setup
import setuptools
setup_dict = dict(
name="feititfy",
version="0.0.2a0",
author="cjsoft",
author_email="egwcyh@gmail.com",
description="Notify you using feishu custom bot by webhook",
long_description="""Notify you using feishu custom bot by webhook
Plese refer to project homepage to get usage introduction.""",
url="https://github.com/cjsoft/feitify",
python_requires=">=3.5",
packages=setuptools.find_packages(where=".", include=("feitify.*")),
scripts=["bin/feitify"],
install_requires=["requests"],
)
setup(**setup_dict)
| 0 | 0 | 0 |
70fb63dac3f7267c5cf03188da2aae729875bf8f | 2,354 | py | Python | netbox_rbac/auth/ldap.py | shakefu/netbox-rbac | ed7acbf00ae0a289d417465addfb723f8dca8cec | [
"MIT"
] | null | null | null | netbox_rbac/auth/ldap.py | shakefu/netbox-rbac | ed7acbf00ae0a289d417465addfb723f8dca8cec | [
"MIT"
] | null | null | null | netbox_rbac/auth/ldap.py | shakefu/netbox-rbac | ed7acbf00ae0a289d417465addfb723f8dca8cec | [
"MIT"
] | null | null | null | import ldap
from .. import auth
# Required when using self-signed certificates.
ldap.set_option(ldap.OPT_X_TLS_REQUIRE_CERT, ldap.OPT_X_TLS_NEVER)
| 26.75 | 74 | 0.584112 | import ldap
from .. import auth
# Required when using self-signed certificates.
ldap.set_option(ldap.OPT_X_TLS_REQUIRE_CERT, ldap.OPT_X_TLS_NEVER)
class Driver:
def __init__(self, config):
self.config = config
def session(self):
return Session(**self.config)
class Session:
def __init__(self, domain, search, server):
self.domain = domain
self.search = search
# Cache group membership to avoid repeated lookups.
self.groups = {}
# Connect, and ensure the connection is encrypted.
self.client = ldap.initialize(server)
self.client.start_tls_s()
def authenticate(self, username, password):
# Authenticate as the user.
self.client.simple_bind_s(self.domain + "\\" + username, password)
# Retrieve user attributes.
result = self.lookup("user", username)
if not result:
raise Exception("search: no results")
# Each result is a tuple: (distinguishedName, attributes)
attrs = result[1]
props = {
"email": "mail",
"first_name": "givenName",
"last_name": "sn",
}
# Map from LDAP attributes to account properties.
for prop, attr in props.items():
props[prop] = ""
if attr in attrs and attrs[attr]:
props[prop] = attrs[attr][0].decode("utf8")
return auth.Account(**props)
def close(self):
self.client.unbind_ext_s()
def lookup(self, kind, *args):
results = self.client.search_s(
self.search[kind]["base"],
ldap.SCOPE_SUBTREE,
self.search[kind]["filter"] % tuple(args),
)
return next(iter(results), None)
def member(self, username, groups):
for group in groups:
# Populate the cache for this group, if necessary.
if group not in self.groups:
self.groups[group] = self.member_query(username, group)
if self.groups[group]:
return True
return False
def member_query(self, username, group):
# Get the DN of the group.
group = self.lookup("group", group)
# Get membership.
if group and self.lookup("member", username, group[0]):
return True
return False
| 1,958 | -15 | 260 |
c617ecaf2c39088de692453e76ce99620c5cebb1 | 1,328 | py | Python | Aula 15 - Interrompendo repetições while/desafio070.py | josue-rosa/Python---Curso-em-Video | 2d74c7421a49952b7c3eadb1010533525f2de338 | [
"MIT"
] | 3 | 2020-10-07T03:21:07.000Z | 2020-10-13T14:18:49.000Z | Aula 15 - Interrompendo repetições while/desafio070.py | josue-rosa/Python---Curso-em-Video | 2d74c7421a49952b7c3eadb1010533525f2de338 | [
"MIT"
] | null | null | null | Aula 15 - Interrompendo repetições while/desafio070.py | josue-rosa/Python---Curso-em-Video | 2d74c7421a49952b7c3eadb1010533525f2de338 | [
"MIT"
] | null | null | null | total = totmil = cont = menor = 0
barato = ''
while True:
produto = str(input('Nome do produto: '))
preco = float(input('Preço: R$ '))
cont += 1
total += preco
if preco > 1000:
totmil += 1
if cont == 1 or preco < menor:
barato = produto
menor = preco
resp = ' '
while resp not in 'SN':
resp = str(input('Quer continuar: [S/N] ')).upper().strip()[0]
if resp == 'N':
break
print('{:-^40}'.format(" Fim do programa "))
print(f'O total da compra foi R$ {total:.2f}')
print(f'Temos {totmil} produtos custando mais de R$1.000 ')
print(f'O produto mais barato foi {barato} que custa R${menor:.2f}')
# Meu código
# Faltou fazer o nome do produto mais barato
"""
nome_produto = str(input('Nome do produto: ')).strip()
preco_produto = float(input('Preço: '))
resp = 'S'
valor_total_produtos = 0
cont_preco = 0
while True:
if preco_produto > 1000.0:
cont_preco += 1
valor_total_produtos += preco_produto
resp = str(input('Quer continuar [S/N]: '))
if resp in 'Ss':
nome_produto = str(input('Nome do produto: ')).strip()
preco_produto = float(input('Preço: R$ '))
else:
break
print(f'Gasto total em compras: R${valor_total_produtos:.2f}')
print(f'{cont_preco} produtos custam acima de MIL Reais')
"""
| 24.592593 | 70 | 0.606928 | total = totmil = cont = menor = 0
barato = ''
while True:
produto = str(input('Nome do produto: '))
preco = float(input('Preço: R$ '))
cont += 1
total += preco
if preco > 1000:
totmil += 1
if cont == 1 or preco < menor:
barato = produto
menor = preco
resp = ' '
while resp not in 'SN':
resp = str(input('Quer continuar: [S/N] ')).upper().strip()[0]
if resp == 'N':
break
print('{:-^40}'.format(" Fim do programa "))
print(f'O total da compra foi R$ {total:.2f}')
print(f'Temos {totmil} produtos custando mais de R$1.000 ')
print(f'O produto mais barato foi {barato} que custa R${menor:.2f}')
# Meu código
# Faltou fazer o nome do produto mais barato
"""
nome_produto = str(input('Nome do produto: ')).strip()
preco_produto = float(input('Preço: '))
resp = 'S'
valor_total_produtos = 0
cont_preco = 0
while True:
if preco_produto > 1000.0:
cont_preco += 1
valor_total_produtos += preco_produto
resp = str(input('Quer continuar [S/N]: '))
if resp in 'Ss':
nome_produto = str(input('Nome do produto: ')).strip()
preco_produto = float(input('Preço: R$ '))
else:
break
print(f'Gasto total em compras: R${valor_total_produtos:.2f}')
print(f'{cont_preco} produtos custam acima de MIL Reais')
"""
| 0 | 0 | 0 |
33f9633f4f7425ffb32048befcc6ce4717dfaa04 | 7,154 | py | Python | bot/main/errors.py | AkshuAgarwal/Aperture-1.7 | c55ffa68d3a4de0daaaad2c918173e5ebca9f006 | [
"MIT"
] | 2 | 2021-09-05T16:42:13.000Z | 2021-09-09T18:41:14.000Z | bot/main/errors.py | AkshuAgarwal/Aperture-1.7 | c55ffa68d3a4de0daaaad2c918173e5ebca9f006 | [
"MIT"
] | null | null | null | bot/main/errors.py | AkshuAgarwal/Aperture-1.7 | c55ffa68d3a4de0daaaad2c918173e5ebca9f006 | [
"MIT"
] | null | null | null | import sys
import traceback
from contextlib import suppress
from discord.ext.commands import * | 76.106383 | 294 | 0.712329 | import sys
import traceback
from contextlib import suppress
from discord.ext.commands import *
async def error_handler(ctx, error):
ignored = (CommandNotFound, )
error = getattr(error, 'original', error)
if ctx.command.has_error_handler():
return
if isinstance(error, ignored):
return
elif isinstance(error, MissingRequiredArgument):
await ctx.reply(f'Missing Required Argument!\n> Missing Arguments: `{error.param}`\n> Usage: `{ctx.prefix}{ctx.invoked_with} {ctx.command.usage}`\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error, TooManyArguments):
await ctx.reply(f'Too Many Arguments!\n> Usage: `{ctx.prefix}{ctx.invoked_with} {ctx.command.usage}`\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error, MessageNotFound):
await ctx.reply(f'Unable to find Message!\n> Argument passed: `{error.argument}`')
elif isinstance(error, MemberNotFound):
await ctx.reply(f'Unable to find Member!\n> Argument passed: `{error.argument}`')
elif isinstance(error, UserNotFound):
await ctx.reply(f'Unable to find User!\n> Argument passed: `{error.argument}`')
elif isinstance(error, ChannelNotFound):
await ctx.reply(f'Unable to find Channel!\n> Argument passed: `{error.argument}`')
elif isinstance(error, ChannelNotReadable):
await ctx.reply(f'I am missing Permissions to read a Required Channel!\n> Channel: `{error.argument.mention}`')
elif isinstance(error, BadColourArgument):
await ctx.reply(f'The Color argument is not Valid.\n> Color: `{error.argument}`')
elif isinstance(error, RoleNotFound):
await ctx.reply(f'Unable to find Role!\n> Argument passed: `{error.argument}`')
elif isinstance(error, BadInviteArgument):
await ctx.reply(f'The Invite is either Invalid or Expired!')
elif isinstance(error, EmojiNotFound):
await ctx.reply(f'Unable to find Emoji!\n> Argument passed: `{error.argument}`')
elif isinstance(error, PartialEmojiConversionFailure):
await ctx.reply(f'Emoji does not match the correct format!\n> Arguments passed: `{error.argument}`')
elif isinstance(error, BadBoolArgument):
await ctx.reply(f'Boolean Argument does not match the valid format!\n> Arguments passed: `{error.argument}`')
elif isinstance(error, BadUnionArgument):
await ctx.reply(f'Invaild Inupt type passed in Arguments!\n> Parameter failed: {error.param}\n> Valid Input Types: {", ".join(i for i in error.converters)}\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error, UnexpectedQuoteError):
await ctx.reply(f'Found Unexpected Quote mark inside non-quoted string!\n Quote: `{error.quote}`')
elif isinstance(error, InvalidEndOfQuotedStringError):
await ctx.reply(f'Expected space after closing quote but `{error.char}` found!')
elif isinstance(error, ExpectedClosingQuoteError):
await ctx.reply(f'Expected `{error.close_quote}` Closing quote but not Found!')
elif isinstance(error, CheckAnyFailure):
pass
elif isinstance(error, PrivateMessageOnly):
await ctx.reply('This command or an Operation in this command works in Private Messages (DMs) only!')
elif isinstance(error, NoPrivateMessage):
with suppress(Exception):
await ctx.author.send('This command or an Operation in this command do not work in Private Messages (DMs)!')
elif isinstance(error, NotOwner):
await ctx.reply('This is a **Developer Only** Command!')
elif isinstance(error, MissingPermissions):
await ctx.reply(f'You are Missing Permissions to use this Command!\n> Missing Permissions: `{", ".join(str(i).replace("_", " ").capitalize() for i in error.missing_perms)}`\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error, BotMissingPermissions):
await ctx.reply(f'I am Missing Permissions to execute this Command!\n> Missing Permissions: `{", ".join(str(i).replace("_", " ").capitalize() for i in error.missing_perms)}`\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error, MissingRole):
await ctx.reply(f'You are Missing required Role to use this Command!\n> Missing Role Parameter: `{error.missing_role}`\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error, BotMissingRole):
await ctx.reply(f'I am Missing required Role to execute this Command!\n> Missing Role Parameter: `{error.missing_role}`\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error, MissingAnyRole):
await ctx.reply(f'You are Missing required Role to use this Command! You need to have atleast one role out of the Missing Roles to run this Command.\n> Missing Roles Parameters: `{", ".join(i for i in error.missing_roles)}`\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error,BotMissingAnyRole):
await ctx.reply(f'I am Missing required Role to use this Command! I need to have atleast one role out of the Missing Roles to execute this Command.\n> Missing Roles Parameters: `{", ".join(i for i in error.missing_roles)}`\n\nNeed more info? Use `{ctx.prefix}help {ctx.invoked_with}`')
elif isinstance(error, NSFWChannelRequired):
await ctx.reply('This command can only be used in NSFW channels!')
elif isinstance(error, DisabledCommand):
await ctx.reply('This command is Disabled!')
elif isinstance(error, CommandInvokeError):
await ctx.reply(f'Oops! Some error occured while invoking the command!\n> Error: `{error.__cause__}`')
elif isinstance(error, CommandOnCooldown):
await ctx.reply(f'Woah! Looks like you\'re in hurry! This command is on `{(str(error.cooldown.type)[11:]).capitalize()}` type Cooldown! Try again in `{error.retry_after:,.0f}` seconds.')
elif isinstance(error, MaxConcurrencyReached):
await ctx.reply(f'Woah! Looks like this command is being used a lot...\nThe command reached it\'s Max Concurrency of `{error.number}` invokers per `{error.per}`. Try again in a few seconds...')
elif isinstance(error, ExtensionAlreadyLoaded):
await ctx.reply('Extension is Already Loaded!')
elif isinstance(error, ExtensionNotLoaded):
await ctx.reply('Extension is not Loaded!')
elif isinstance(error, NoEntryPointError):
await ctx.reply('The Extension do not have a `setup` entry point function.')
elif isinstance(error, ExtensionNotFound):
await ctx.reply('Unable to find the Extension!')
elif isinstance(error, CommandRegistrationError):
await ctx.reply(f'Command with name `{error.name}` cannot be addded because it\'s name is already taken by a different Command.\n> Alias Conflict: `{error.alias_conflict}`')
else:
await ctx.reply(f'Oops! Some error Occured...\n> Error: `{error}`')
print('Ignoring exception in command {}:'.format(ctx.command), file=sys.stderr)
traceback.print_exception(type(error), error, error.__traceback__, file=sys.stderr) | 7,036 | 0 | 23 |
435508f823dce78a1ff7d21864bf7adf9b2c3100 | 3,474 | py | Python | homeassistant/components/juicenet/sensor.py | bogdal/core | ed0fd0074670ed56d056f139a9f934b3f89d9487 | [
"Apache-2.0"
] | null | null | null | homeassistant/components/juicenet/sensor.py | bogdal/core | ed0fd0074670ed56d056f139a9f934b3f89d9487 | [
"Apache-2.0"
] | 23 | 2021-09-14T06:14:33.000Z | 2022-03-31T06:17:42.000Z | homeassistant/components/juicenet/sensor.py | bogdal/core | ed0fd0074670ed56d056f139a9f934b3f89d9487 | [
"Apache-2.0"
] | null | null | null | """Support for monitoring juicenet/juicepoint/juicebox based EVSE sensors."""
from __future__ import annotations
from homeassistant.components.sensor import (
STATE_CLASS_MEASUREMENT,
SensorEntity,
SensorEntityDescription,
)
from homeassistant.const import (
DEVICE_CLASS_CURRENT,
DEVICE_CLASS_ENERGY,
DEVICE_CLASS_POWER,
DEVICE_CLASS_TEMPERATURE,
DEVICE_CLASS_VOLTAGE,
ELECTRIC_CURRENT_AMPERE,
ELECTRIC_POTENTIAL_VOLT,
ENERGY_WATT_HOUR,
POWER_WATT,
TEMP_CELSIUS,
TIME_SECONDS,
)
from .const import DOMAIN, JUICENET_API, JUICENET_COORDINATOR
from .entity import JuiceNetDevice
SENSOR_TYPES: tuple[SensorEntityDescription, ...] = (
SensorEntityDescription(
key="status",
name="Charging Status",
),
SensorEntityDescription(
key="temperature",
name="Temperature",
unit_of_measurement=TEMP_CELSIUS,
device_class=DEVICE_CLASS_TEMPERATURE,
state_class=STATE_CLASS_MEASUREMENT,
),
SensorEntityDescription(
key="voltage",
name="Voltage",
unit_of_measurement=ELECTRIC_POTENTIAL_VOLT,
device_class=DEVICE_CLASS_VOLTAGE,
),
SensorEntityDescription(
key="amps",
name="Amps",
unit_of_measurement=ELECTRIC_CURRENT_AMPERE,
device_class=DEVICE_CLASS_CURRENT,
state_class=STATE_CLASS_MEASUREMENT,
),
SensorEntityDescription(
key="watts",
name="Watts",
unit_of_measurement=POWER_WATT,
device_class=DEVICE_CLASS_POWER,
state_class=STATE_CLASS_MEASUREMENT,
),
SensorEntityDescription(
key="charge_time",
name="Charge time",
unit_of_measurement=TIME_SECONDS,
icon="mdi:timer-outline",
),
SensorEntityDescription(
key="energy_added",
name="Energy added",
unit_of_measurement=ENERGY_WATT_HOUR,
device_class=DEVICE_CLASS_ENERGY,
),
)
async def async_setup_entry(hass, config_entry, async_add_entities):
"""Set up the JuiceNet Sensors."""
juicenet_data = hass.data[DOMAIN][config_entry.entry_id]
api = juicenet_data[JUICENET_API]
coordinator = juicenet_data[JUICENET_COORDINATOR]
entities = [
JuiceNetSensorDevice(device, coordinator, description)
for device in api.devices
for description in SENSOR_TYPES
]
async_add_entities(entities)
class JuiceNetSensorDevice(JuiceNetDevice, SensorEntity):
"""Implementation of a JuiceNet sensor."""
def __init__(self, device, coordinator, description: SensorEntityDescription):
"""Initialise the sensor."""
super().__init__(device, description.key, coordinator)
self.entity_description = description
self._attr_name = f"{self.device.name} {description.name}"
@property
def icon(self):
"""Return the icon of the sensor."""
icon = None
if self.entity_description.key == "status":
status = self.device.status
if status == "standby":
icon = "mdi:power-plug-off"
elif status == "plugged":
icon = "mdi:power-plug"
elif status == "charging":
icon = "mdi:battery-positive"
else:
icon = self.entity_description.icon
return icon
@property
def state(self):
"""Return the state."""
return getattr(self.device, self.entity_description.key, None)
| 29.948276 | 82 | 0.668106 | """Support for monitoring juicenet/juicepoint/juicebox based EVSE sensors."""
from __future__ import annotations
from homeassistant.components.sensor import (
STATE_CLASS_MEASUREMENT,
SensorEntity,
SensorEntityDescription,
)
from homeassistant.const import (
DEVICE_CLASS_CURRENT,
DEVICE_CLASS_ENERGY,
DEVICE_CLASS_POWER,
DEVICE_CLASS_TEMPERATURE,
DEVICE_CLASS_VOLTAGE,
ELECTRIC_CURRENT_AMPERE,
ELECTRIC_POTENTIAL_VOLT,
ENERGY_WATT_HOUR,
POWER_WATT,
TEMP_CELSIUS,
TIME_SECONDS,
)
from .const import DOMAIN, JUICENET_API, JUICENET_COORDINATOR
from .entity import JuiceNetDevice
SENSOR_TYPES: tuple[SensorEntityDescription, ...] = (
SensorEntityDescription(
key="status",
name="Charging Status",
),
SensorEntityDescription(
key="temperature",
name="Temperature",
unit_of_measurement=TEMP_CELSIUS,
device_class=DEVICE_CLASS_TEMPERATURE,
state_class=STATE_CLASS_MEASUREMENT,
),
SensorEntityDescription(
key="voltage",
name="Voltage",
unit_of_measurement=ELECTRIC_POTENTIAL_VOLT,
device_class=DEVICE_CLASS_VOLTAGE,
),
SensorEntityDescription(
key="amps",
name="Amps",
unit_of_measurement=ELECTRIC_CURRENT_AMPERE,
device_class=DEVICE_CLASS_CURRENT,
state_class=STATE_CLASS_MEASUREMENT,
),
SensorEntityDescription(
key="watts",
name="Watts",
unit_of_measurement=POWER_WATT,
device_class=DEVICE_CLASS_POWER,
state_class=STATE_CLASS_MEASUREMENT,
),
SensorEntityDescription(
key="charge_time",
name="Charge time",
unit_of_measurement=TIME_SECONDS,
icon="mdi:timer-outline",
),
SensorEntityDescription(
key="energy_added",
name="Energy added",
unit_of_measurement=ENERGY_WATT_HOUR,
device_class=DEVICE_CLASS_ENERGY,
),
)
async def async_setup_entry(hass, config_entry, async_add_entities):
"""Set up the JuiceNet Sensors."""
juicenet_data = hass.data[DOMAIN][config_entry.entry_id]
api = juicenet_data[JUICENET_API]
coordinator = juicenet_data[JUICENET_COORDINATOR]
entities = [
JuiceNetSensorDevice(device, coordinator, description)
for device in api.devices
for description in SENSOR_TYPES
]
async_add_entities(entities)
class JuiceNetSensorDevice(JuiceNetDevice, SensorEntity):
"""Implementation of a JuiceNet sensor."""
def __init__(self, device, coordinator, description: SensorEntityDescription):
"""Initialise the sensor."""
super().__init__(device, description.key, coordinator)
self.entity_description = description
self._attr_name = f"{self.device.name} {description.name}"
@property
def icon(self):
"""Return the icon of the sensor."""
icon = None
if self.entity_description.key == "status":
status = self.device.status
if status == "standby":
icon = "mdi:power-plug-off"
elif status == "plugged":
icon = "mdi:power-plug"
elif status == "charging":
icon = "mdi:battery-positive"
else:
icon = self.entity_description.icon
return icon
@property
def state(self):
"""Return the state."""
return getattr(self.device, self.entity_description.key, None)
| 0 | 0 | 0 |
56fc7a06ad0c0dccbb59323dceea01c1d082f24c | 929 | py | Python | examples/multiple_gaussian_2d.py | medvidov/PyNomaly | 0862bc0504b7cc0b77fe6123fbac85c50f50bf73 | [
"Apache-2.0"
] | 284 | 2017-06-14T02:20:54.000Z | 2022-03-06T08:55:18.000Z | examples/multiple_gaussian_2d.py | medvidov/PyNomaly | 0862bc0504b7cc0b77fe6123fbac85c50f50bf73 | [
"Apache-2.0"
] | 39 | 2017-06-12T15:04:19.000Z | 2021-11-18T10:54:25.000Z | examples/multiple_gaussian_2d.py | medvidov/PyNomaly | 0862bc0504b7cc0b77fe6123fbac85c50f50bf73 | [
"Apache-2.0"
] | 41 | 2017-08-20T15:38:21.000Z | 2021-09-16T11:38:42.000Z | import numpy as np
import matplotlib.pyplot as plt
from PyNomaly import loop
import pandas as pd
# import the multiple gaussian data #
df = pd.read_csv('../data/multiple-gaussian-2d-data-only.csv')
print(df)
# fit LoOP according to the original settings outlined in the paper #
m = loop.LocalOutlierProbability(df[['x', 'y']], n_neighbors=20, extent=3).fit()
scores = m.local_outlier_probabilities
print(scores)
# plot the results #
# base 3 width, then set as multiple
threshold = 0.1
color = np.where(scores > threshold, "white", "black")
label_mask = np.where(scores > threshold)
area = (20 * scores) ** 2
plt.scatter(df['x'], df['y'], c=color, s=area.astype(float), edgecolor='red', linewidth=1)
plt.scatter(df['x'], df['y'], c='black', s=3)
for i in range(len(scores)):
if scores[i] > threshold:
plt.text(df['x'].loc[i] * (1 + 0.01), df['y'].loc[i] * (1 + 0.01), round(scores[i], 2), fontsize=8)
plt.show()
| 32.034483 | 107 | 0.678149 | import numpy as np
import matplotlib.pyplot as plt
from PyNomaly import loop
import pandas as pd
# import the multiple gaussian data #
df = pd.read_csv('../data/multiple-gaussian-2d-data-only.csv')
print(df)
# fit LoOP according to the original settings outlined in the paper #
m = loop.LocalOutlierProbability(df[['x', 'y']], n_neighbors=20, extent=3).fit()
scores = m.local_outlier_probabilities
print(scores)
# plot the results #
# base 3 width, then set as multiple
threshold = 0.1
color = np.where(scores > threshold, "white", "black")
label_mask = np.where(scores > threshold)
area = (20 * scores) ** 2
plt.scatter(df['x'], df['y'], c=color, s=area.astype(float), edgecolor='red', linewidth=1)
plt.scatter(df['x'], df['y'], c='black', s=3)
for i in range(len(scores)):
if scores[i] > threshold:
plt.text(df['x'].loc[i] * (1 + 0.01), df['y'].loc[i] * (1 + 0.01), round(scores[i], 2), fontsize=8)
plt.show()
| 0 | 0 | 0 |
e99e076028831f633a976bfada333cc75d379bc8 | 25,752 | py | Python | Cable_car/main.py | ChairOfStructuralMechanicsTUM/Mechanics_Apps | b064a42d4df3fa9bde62a5cff9cb27ca61b0127c | [
"MIT"
] | 11 | 2017-05-06T17:05:29.000Z | 2020-11-12T09:26:47.000Z | Cable_car/main.py | ChairOfStructuralMechanicsTUM/Mechanics_Apps | b064a42d4df3fa9bde62a5cff9cb27ca61b0127c | [
"MIT"
] | 49 | 2017-04-20T11:26:11.000Z | 2020-05-29T13:18:06.000Z | Cable_car/main.py | ChairOfStructuralMechanicsTUM/Mechanics_Apps | b064a42d4df3fa9bde62a5cff9cb27ca61b0127c | [
"MIT"
] | 4 | 2017-02-14T12:55:34.000Z | 2022-01-12T15:07:07.000Z | """
TENSIONS ON THE CABLE CAR TRANSPORTATION SYSTEM - This interactive web app
computes the cable tensions of the cable car system for a user defined axial
location of the carriage car
Created on Tue Jun 1 22:53:14 2021
@author: Ramsubramanian Pazhanisamy
"""
#################################
## IMPORTS ##
#################################
# general imports
import numpy as np
import sympy as sp
# bokeh imports
from bokeh.io import curdoc
from bokeh.plotting import figure
from bokeh.models import ColumnDataSource, Arrow, OpenHead, Range1d, TeeHead
from bokeh.models.glyphs import ImageURL
from bokeh.models.widgets import Button
from bokeh.layouts import column, row
# latex integration
import os
from os.path import dirname, join, split, abspath
import sys, inspect
currentdir = dirname(abspath(inspect.getfile(inspect.currentframe())))
parentdir = join(dirname(currentdir), "shared/")
sys.path.insert(0,parentdir)
from latex_support import LatexDiv, LatexLabelSet, LatexSlider
# ----------------------------------------------------------------- #
###################################################
## APP THEORETICAL DESCRIPTION ##
###################################################
#Theoretical description of the app in Latex
description_filename1 = join(dirname(__file__), "description1.html") #Part I of the description
description1 = LatexDiv(text=open(description_filename1).read(), render_as_text=False, width=1000)
description_filename2 = join(dirname(__file__), "description2.html") #Part II of the description
description2 = LatexDiv(text=open(description_filename2).read(), render_as_text=False, width=1000)
description_filename3 = join(dirname(__file__), "description3.html") #Part III of the description
description3 = LatexDiv(text=open(description_filename3).read(), render_as_text=False, width=1000)
#Figures_static
# Plot
#Kinematics of the cable car
kinematics_img=os.path.join(os.path.basename(os.path.dirname(__file__)), "static", "Kinematics.svg")
figure_kin = figure(height=235, width=298)
figure_kin.toolbar.logo = None # do not display the bokeh logo
figure_kin.toolbar_location = None # do not display the tools
figure_kin.x_range=Range1d(start=0, end=1)
figure_kin.y_range=Range1d(start=0, end=1)
figure_kin.xaxis.visible = None
figure_kin.yaxis.visible = None
figure_kin.xgrid.grid_line_color = None
figure_kin.ygrid.grid_line_color = None
figure_kin.toolbar.active_drag = None
figure_kin.toolbar.active_scroll = None
figure_kin.toolbar.active_tap = None
kinematics_src = ColumnDataSource(dict(url = [kinematics_img]))
figure_kin.image_url(url='url', x=0, y = 1, h=1, w=1, source=kinematics_src)
figure_kin.outline_line_alpha = 0
# Free boy diagram of the cable car
fbd_img=os.path.join(os.path.basename(os.path.dirname(__file__)), "static", "Free_Body_Diagram.svg")
figure_fbd = figure(height=385, width=450)
figure_fbd.toolbar.logo = None # do not display the bokeh logo
figure_fbd.toolbar_location = None # do not display the tools
figure_fbd.x_range=Range1d(start=0, end=1)
figure_fbd.y_range=Range1d(start=0, end=1)
figure_fbd.xaxis.visible = None
figure_fbd.yaxis.visible = None
figure_fbd.xgrid.grid_line_color = None
figure_fbd.ygrid.grid_line_color = None
figure_fbd.toolbar.active_drag = None
figure_fbd.toolbar.active_scroll = None
figure_fbd.toolbar.active_tap = None
fbd_src = ColumnDataSource(dict(url = [fbd_img]))
figure_fbd.image_url(url='url', x=0, y = 1, h=1, w=1, source=fbd_src)
figure_fbd.outline_line_alpha = 0
#################################
## INITIALIZATION ##
#################################
# Initial parameters & its limits
# Cable car dimensions & user inputs
H_max =525.0 #Verical distance between the supports (m) -H
H_min= 475.0
H=500.0
B_max=525.0 #Horizontal distance between the supports (m) -B
B_min=475.0
B=500.0
c_max=1.9 #Cable length stretch factor -c
c_min=1.00001
c=(c_min+c_max)/2
M_max=300.0 #Mass of the cable car - M (Kg)
M_min=200.0
M=250.0
x=0.55*B #Axial location of the cable car
D=np.sqrt(H*H+B*B) #Diagonal distance between the supports (m)
L=c*D #Length of the cable (m) - cable length should be always higher than the distance between the supports
W=M*9.81 #Weight of the car (N)
#Symbolic constants
theta1=sp.Symbol('theta1',real=True)
theta2=sp.Symbol('theta2',real=True)
#Kinematic equations
eq1= sp.Eq(((L-x/sp.cos(theta1))*sp.cos(theta2))+x-B,0)
eq2= sp.Eq(((x/sp.cos(theta1))*sp.sin(theta1))+((L-x/sp.cos(theta1))*sp.sin(theta2))-H,0)
#Solving the system of equations numerically
[t1,t2]=sp.nsolve((eq1,eq2),(theta1,theta2),(0.25,0.75))
#Effective angles on the Cable
theta_total1=float(t1) #Actual angle at S1 for a specific car position on the rope
theta_total2=float(t2) #Actual angle at S2 for a specific car position on the rope
Lx=x/np.cos(theta_total1) #Length of the bottom cable segement
#Tensions on the Cable
T1= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1)))*(np.cos(theta_total2)/np.cos(theta_total1)) # Cable tension in the bottom
T2= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1))) # Cable tension in the top
# ----------------------------------------------------------------- #
#################################
## CALLBACK FUNCTIONS ##
#################################
# Div to show tension and distance values
value_plot_distance_cable_length= LatexDiv(text="", render_as_text=False, width=400)
value_plot_angles = LatexDiv(text="", render_as_text=False, width=400)
value_plot_tensions = LatexDiv(text="", render_as_text=False, width=400)
#Display the results
#Slider change call back function for H, c, M, X
#Slider change call back function for B
#Call back function for reset button
# ----------------------------------------------------------------- #
####################################
## SLIDERS & BUTTONS ##
####################################
#Sliders
#Vertical Distance between the supports
H_slider = LatexSlider(title="\\text{Vertical distance between supports (H)}=", value_unit="\\text{m}", value=H, start=H_min, end=H_max, step=1.0, width=400, css_classes=["slider"])
H_slider.on_change('value',slider_cb_fun) # callback function is called when value changes
#Horizontal Distance between the supports
B_slider = LatexSlider(title="\\text{Horizontal distance between supports (B)}=", value_unit="\\text{m}", value=B, start=B_min, end=B_max, step=1.0, width=400, css_classes=["slider"])
B_slider.on_change('value',slider_cb_fun_b) # callback function is called when value changes
#Cable length stretch factor to compute the length of the cable from the distance between the supports
c_slider=LatexSlider(title="\\text{Cable length stretch factor (c = L/D)=}", value=float("{:.5f}".format((c))), start=c_min, end=c_max, step=0.005, width=400, css_classes=["slider"])
c_slider.on_change('value',slider_cb_fun) # callback function is called when value changes
#Mass carried by the cable car container
M_slider = LatexSlider(title="\\text{Mass carried by the system (M)}=", value_unit="\\text{Kg}", value=M, start=M_min, end=M_max, step=1.0, width=400, css_classes=["slider"])
M_slider.on_change('value',slider_cb_fun) # callback function is called when value changes
#Axial location of the carriage
X_slider = LatexSlider(title="\\text{Horizontal location of the carriage (X)}=", value_unit="\\text{m}", value=int(0.55*B_slider.value), start=int(0.2*B_slider.value), end=int(0.9*B_slider.value), step=1.0, width=400, css_classes=["slider"])
X_slider.on_change('value',slider_cb_fun) # callback function is called when value changes
#Reset Button
button_width = 400
Reset_button=Button(label='Reset', button_type='success', width=button_width)
Reset_button.on_click(callback_reset)
# ----------------------------------------------------------------- #
####################################
## ANIMATED PLOT ##
####################################
# Plot
plot = figure(title="", tools="", x_range=(-150,B+200), y_range=(min(-200,Lx * np.sin(theta_total1)-320),H+150),aspect_scale=2.0)
plot.plot_height=700
plot.plot_width=850
plot.toolbar.logo = None
plot.axis.axis_label_text_font_style="normal"
plot.axis.axis_label_text_font_size="14pt"
plot.axis.major_label_text_font_size="14pt"
plot.xaxis.axis_label='x (m)'
plot.yaxis.axis_label='y (m)'
plot.outline_line_width=1.5
plot.outline_line_color="#333333"
plot.outline_line_alpha=0.9
#Column Data Sources definition
# Support source
support_source_bottom = ColumnDataSource(dict(x = [0], y = [0+10.0] , src = [os.path.join(os.path.basename(os.path.dirname(__file__)), "static", "fixed_support.svg")]))
support_source_top = ColumnDataSource(dict(x = [B], y = [H+5.0] , src = [os.path.join(os.path.basename(os.path.dirname(__file__)), "static", "fixed_support.svg")]))
#Line source for the cable
line_source_bottom = ColumnDataSource(dict(xs = [0, Lx * np.cos(theta_total1)], ys =[0, Lx * np.sin(theta_total1)] ))
line_source_top = ColumnDataSource(dict(xs = [Lx * np.cos(theta_total1), B], ys =[Lx * np.sin(theta_total1), H] ))
# Carriage
line_source_carriage = ColumnDataSource(dict(xs = [Lx * np.cos(theta_total1),Lx * np.cos(theta_total1)], ys= [Lx * np.sin(theta_total1)-120,Lx * np.sin(theta_total1)] ))
mass_source_carriage=ColumnDataSource(dict(x = [Lx * np.cos(theta_total1)], y = [Lx * np.sin(theta_total1)-120], size=[int(M/M_max*80)] ))
connecting_pt_circle=ColumnDataSource(dict(x = [Lx * np.cos(theta_total1)], y = [ Lx * np.sin(theta_total1)] ))
#Annotations
B_dist_source = ColumnDataSource(dict(xS=[0], xE=[B], yS=[min(-200+50,Lx * np.sin(theta_total1)-320+50)], yE=[min(-200+50,Lx * np.sin(theta_total1)-320+50)], xL=[B*0.5], yL=[min(-200+60,Lx * np.sin(theta_total1)-320+60)], text=["B"]))
H_dist_source = ColumnDataSource(dict(xS=[B+100], xE=[B+100], yS=[0], yE=[H], xL=[B+70], yL=[0.5*H], text=["H"]))
D_dist_source = ColumnDataSource(dict(xS=[+0], xE=[B-20], yS=[0+30], yE=[H+10], xL=[B*0.5-30], yL=[H*0.5+30], text=["D"]))
x_pt_circle=ColumnDataSource(dict(x = [Lx * np.cos(theta_total1)], y = [min(-200+25,Lx * np.sin(theta_total1)-320+25)] ))
y_pt_circle=ColumnDataSource(dict(x = [-150+15], y = [ Lx * np.sin(theta_total1)] ))
#Cable Tensions & Load
T1_source = ColumnDataSource(dict(xS=[0], xE=[-(np.cos(theta_total1)*150*T1/(T1+T2))], yS=[0], yE=[-(np.sin(theta_total1)*150*T1/(T1+T2))], xL=[-50-0.5*(np.cos(theta_total1)*150*T1/(T1+T2))], yL=[-50-0.5*(np.sin(theta_total1)*150*T1/(T1+T2))], name=["T_1"]))
T2_source =ColumnDataSource(dict(xS=[B], xE=[B+(np.cos(theta_total2)*150*T2/(T1+T2))], yS=[H], yE=[H+(np.sin(theta_total2)*150*T2/(T1+T2))], xL=[+25+B+0.5*(np.cos(theta_total2)*150*T2/(T1+T2))], yL=[-25+H+0.5*(np.sin(theta_total2)*150*T2/(T1+T2))], name=["T_2"]))
#Labels and arrows for annotations & cable tensions
B_dist = Arrow(end=TeeHead(line_color="#808080", line_width=1, size=10),
start=TeeHead(line_color="#808080",line_width=1, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=1, line_color="#808080", source=B_dist_source)
B_dist_label = LatexLabelSet(x='xL', y='yL', text='text', source=B_dist_source)
H_dist = Arrow(end=TeeHead(line_color="#808080", line_width=1, size=10),
start=TeeHead(line_color="#808080",line_width=1, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=1, line_color="#808080", source=H_dist_source)
H_dist_label = LatexLabelSet(x='xL', y='yL', text='text', source=H_dist_source)
D_dist = Arrow(end=TeeHead(line_color="#808080", line_width=1, size=10),
start=TeeHead(line_color="#808080",line_width=1, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=1, line_color="#808080", source=D_dist_source)
D_dist_label = LatexLabelSet(x='xL', y='yL', text='text', source=D_dist_source)
T1_arrow_glyph = Arrow(end=OpenHead(line_color="#333333", line_width=4, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=4, source=T1_source,line_color="#333333")
T2_arrow_glyph = Arrow(end=OpenHead(line_color="#333333", line_width=4, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=4, source=T2_source,line_color="#333333")
T1_label_glyph=LatexLabelSet(x='xL', y='yL', text='name', text_font_size="15pt", level='glyph', source=T1_source)
T2_label_glyph=LatexLabelSet(x='xL', y='yL', text='name', text_font_size="15pt", level='glyph', source=T2_source)
#Adding all glyps into the plot - lines, carriage, supports, tensions & annotations
plot.line(x='xs', y='ys', source=line_source_bottom , line_width=10, color='#3070B3')
plot.line(x='xs', y='ys', source=line_source_top , line_width=10, color='#3070B3')
plot.circle(x='x', y='y', source=connecting_pt_circle, size=20, color="#e37222")
plot.line(x='xs', y='ys', source=line_source_carriage, line_width=10, color="#e37222")
plot.square(x='x', y='y', size='size', source=mass_source_carriage, color="#e37222")
plot.circle(x='x', y='y', source=x_pt_circle, size=20, color="#a2ad00")
plot.circle(x='x', y='y', source=y_pt_circle, size=20, color="#a2ad00")
plot.add_glyph(support_source_top,ImageURL(url="src", x='x', y='y', w=60, h=60, anchor="top_center"))
plot.add_glyph(support_source_bottom,ImageURL(url="src", x='x', y='y', w=60, h=60, anchor="top_center"))
plot.add_layout(T1_arrow_glyph)
plot.add_layout(T2_arrow_glyph)
plot.add_layout(T1_label_glyph)
plot.add_layout(T2_label_glyph)
plot.add_layout(B_dist)
plot.add_layout(B_dist_label)
plot.add_layout(H_dist)
plot.add_layout(H_dist_label)
plot.add_layout(D_dist)
plot.add_layout(D_dist_label)
# ----------------------------------------------------------------- #
####################################
## LAYOUT ##
####################################
curdoc().add_root(column(
description1,
figure_kin,
description2,
figure_fbd,
description3,
column(column(
row(H_slider,B_slider,c_slider),
row(M_slider,X_slider,Reset_button),
row(plot),
row(value_plot_distance_cable_length,value_plot_angles, value_plot_tensions)
))))
curdoc().title = split(dirname(__file__))[-1].replace('_',' ').replace('-',' ') # get path of parent directory and only use the name of the Parent Directory for the tab name. Replace underscores '_' and minuses '-' with blanks ' '
# ----------------------------------------------------------------- #
| 55.143469 | 272 | 0.653464 | """
TENSIONS ON THE CABLE CAR TRANSPORTATION SYSTEM - This interactive web app
computes the cable tensions of the cable car system for a user defined axial
location of the carriage car
Created on Tue Jun 1 22:53:14 2021
@author: Ramsubramanian Pazhanisamy
"""
#################################
## IMPORTS ##
#################################
# general imports
import numpy as np
import sympy as sp
# bokeh imports
from bokeh.io import curdoc
from bokeh.plotting import figure
from bokeh.models import ColumnDataSource, Arrow, OpenHead, Range1d, TeeHead
from bokeh.models.glyphs import ImageURL
from bokeh.models.widgets import Button
from bokeh.layouts import column, row
# latex integration
import os
from os.path import dirname, join, split, abspath
import sys, inspect
currentdir = dirname(abspath(inspect.getfile(inspect.currentframe())))
parentdir = join(dirname(currentdir), "shared/")
sys.path.insert(0,parentdir)
from latex_support import LatexDiv, LatexLabelSet, LatexSlider
# ----------------------------------------------------------------- #
###################################################
## APP THEORETICAL DESCRIPTION ##
###################################################
#Theoretical description of the app in Latex
description_filename1 = join(dirname(__file__), "description1.html") #Part I of the description
description1 = LatexDiv(text=open(description_filename1).read(), render_as_text=False, width=1000)
description_filename2 = join(dirname(__file__), "description2.html") #Part II of the description
description2 = LatexDiv(text=open(description_filename2).read(), render_as_text=False, width=1000)
description_filename3 = join(dirname(__file__), "description3.html") #Part III of the description
description3 = LatexDiv(text=open(description_filename3).read(), render_as_text=False, width=1000)
#Figures_static
# Plot
#Kinematics of the cable car
kinematics_img=os.path.join(os.path.basename(os.path.dirname(__file__)), "static", "Kinematics.svg")
figure_kin = figure(height=235, width=298)
figure_kin.toolbar.logo = None # do not display the bokeh logo
figure_kin.toolbar_location = None # do not display the tools
figure_kin.x_range=Range1d(start=0, end=1)
figure_kin.y_range=Range1d(start=0, end=1)
figure_kin.xaxis.visible = None
figure_kin.yaxis.visible = None
figure_kin.xgrid.grid_line_color = None
figure_kin.ygrid.grid_line_color = None
figure_kin.toolbar.active_drag = None
figure_kin.toolbar.active_scroll = None
figure_kin.toolbar.active_tap = None
kinematics_src = ColumnDataSource(dict(url = [kinematics_img]))
figure_kin.image_url(url='url', x=0, y = 1, h=1, w=1, source=kinematics_src)
figure_kin.outline_line_alpha = 0
# Free boy diagram of the cable car
fbd_img=os.path.join(os.path.basename(os.path.dirname(__file__)), "static", "Free_Body_Diagram.svg")
figure_fbd = figure(height=385, width=450)
figure_fbd.toolbar.logo = None # do not display the bokeh logo
figure_fbd.toolbar_location = None # do not display the tools
figure_fbd.x_range=Range1d(start=0, end=1)
figure_fbd.y_range=Range1d(start=0, end=1)
figure_fbd.xaxis.visible = None
figure_fbd.yaxis.visible = None
figure_fbd.xgrid.grid_line_color = None
figure_fbd.ygrid.grid_line_color = None
figure_fbd.toolbar.active_drag = None
figure_fbd.toolbar.active_scroll = None
figure_fbd.toolbar.active_tap = None
fbd_src = ColumnDataSource(dict(url = [fbd_img]))
figure_fbd.image_url(url='url', x=0, y = 1, h=1, w=1, source=fbd_src)
figure_fbd.outline_line_alpha = 0
#################################
## INITIALIZATION ##
#################################
# Initial parameters & its limits
# Cable car dimensions & user inputs
H_max =525.0 #Verical distance between the supports (m) -H
H_min= 475.0
H=500.0
B_max=525.0 #Horizontal distance between the supports (m) -B
B_min=475.0
B=500.0
c_max=1.9 #Cable length stretch factor -c
c_min=1.00001
c=(c_min+c_max)/2
M_max=300.0 #Mass of the cable car - M (Kg)
M_min=200.0
M=250.0
x=0.55*B #Axial location of the cable car
D=np.sqrt(H*H+B*B) #Diagonal distance between the supports (m)
L=c*D #Length of the cable (m) - cable length should be always higher than the distance between the supports
W=M*9.81 #Weight of the car (N)
#Symbolic constants
theta1=sp.Symbol('theta1',real=True)
theta2=sp.Symbol('theta2',real=True)
#Kinematic equations
eq1= sp.Eq(((L-x/sp.cos(theta1))*sp.cos(theta2))+x-B,0)
eq2= sp.Eq(((x/sp.cos(theta1))*sp.sin(theta1))+((L-x/sp.cos(theta1))*sp.sin(theta2))-H,0)
#Solving the system of equations numerically
[t1,t2]=sp.nsolve((eq1,eq2),(theta1,theta2),(0.25,0.75))
#Effective angles on the Cable
theta_total1=float(t1) #Actual angle at S1 for a specific car position on the rope
theta_total2=float(t2) #Actual angle at S2 for a specific car position on the rope
Lx=x/np.cos(theta_total1) #Length of the bottom cable segement
#Tensions on the Cable
T1= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1)))*(np.cos(theta_total2)/np.cos(theta_total1)) # Cable tension in the bottom
T2= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1))) # Cable tension in the top
# ----------------------------------------------------------------- #
#################################
## CALLBACK FUNCTIONS ##
#################################
# Div to show tension and distance values
value_plot_distance_cable_length= LatexDiv(text="", render_as_text=False, width=400)
value_plot_angles = LatexDiv(text="", render_as_text=False, width=400)
value_plot_tensions = LatexDiv(text="", render_as_text=False, width=400)
#Display the results
def setValueText(D,L,t1,t2,T1,T2):
value_plot_distance_cable_length.text = "$$\\begin{aligned} D&=" + "{:4.1f}".format(D) + "\\,\\mathrm{m}\\\\ L&=" + "{:4.1f}".format(L) + "\\,\\mathrm{m} \\end{aligned}$$" #Display the D & L
value_plot_angles.text = "$$\\begin{aligned} \\theta_1&=" + "{:4.1f}".format((t1)) + "\\,\\mathrm{°}\\\\ \\theta_2&=" + "{:4.1f}".format(t2) + "\\,\\mathrm{°} \\end{aligned}$$" #Display Theta1 & Theta2
value_plot_tensions.text = "$$\\begin{aligned} T_1&=" + "{:4.1f}".format(T1) + "\\,\\mathrm{N}\\\\ T_2&=" + "{:4.1f}".format(T2) + "\\,\\mathrm{N} \\end{aligned}$$" #Display T1 & T2
#Slider change call back function for H, c, M, X
def slider_cb_fun(attr,old,new):
H=H_slider.value
B=B_slider.value
c=c_slider.value
M=M_slider.value
x=X_slider.value
D=np.sqrt(H*H+B*B) #Height of the support (m)
L=c*D #Length of the rope (m)
W=M*9.81 #Weight of the car (N)
#Symbolic constants
theta1=sp.Symbol('theta1',real=True)
theta2=sp.Symbol('theta2',real=True)
#Kinematic equations
eq1= sp.Eq(((L-x/sp.cos(theta1))*sp.cos(theta2))+x-B,0)
eq2= sp.Eq(((x/sp.cos(theta1))*sp.sin(theta1))+((L-x/sp.cos(theta1))*sp.sin(theta2))-H,0)
#Solving the system of equations numerically
[t1,t2]=sp.nsolve((eq1,eq2),(theta1,theta2),(0.25,0.75))
#Effective angles on the Cable
theta_total1=float(t1) #Actual angle at S1 for a specific car position on the rope
theta_total2=float(t2) #Actual angle at S2 for a specific car position on the rope
Lx=x/np.cos(theta_total1) #Length of the bottom cable segement
#Tensions on the Cable
T1= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1)))*(np.cos(theta_total2)/np.cos(theta_total1)) # Rope tension in the bottom
T2= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1))) # Rope tension in the top
#Update the result display
setValueText(D, L,theta_total1*180/np.pi, theta_total2*180/np.pi, T1, T2)
#Update the animated plot
plot.x_range.end=B+200.0
plot.y_range.start=min (-200,Lx * np.sin(theta_total1)-320)
plot.y_range.end=H+150.0
support_source_top.patch( {'x':[(0,B)]} )
support_source_top.patch( {'y':[(0,H+5.0)]} )
line_source_bottom.data=dict(xs = [0, Lx * np.cos(theta_total1)], ys =[0, Lx * np.sin(theta_total1)] )
line_source_top.data=dict(xs = [Lx * np.cos(theta_total1), B], ys =[Lx * np.sin(theta_total1), H] )
line_source_carriage.data=dict(xs = [Lx * np.cos(theta_total1),Lx * np.cos(theta_total1)], ys= [Lx * np.sin(theta_total1)-120,Lx * np.sin(theta_total1)] )
mass_source_carriage.data=dict(x = [Lx * np.cos(theta_total1)], y = [Lx * np.sin(theta_total1)-120], size=[int(M/M_max*80)] )
connecting_pt_circle.data=dict(x = [Lx * np.cos(theta_total1)], y = [ Lx * np.sin(theta_total1)] )
x_pt_circle.data=dict(x = [Lx * np.cos(theta_total1)], y = [min(-200+25,Lx * np.sin(theta_total1)-320+25)] )
y_pt_circle.data=dict(x = [-150+15], y = [ Lx * np.sin(theta_total1)] )
B_dist_source.patch( {'xE':[(0,B)], 'yS':[(0,min(-150,Lx * np.sin(theta_total1)-270))], 'yE':[(0,min(-150,Lx * np.sin(theta_total1)-270))], 'xL':[(0,0.5*B)],'yL':[(0,min(-140,Lx * np.sin(theta_total1)-260))]} )
H_dist_source.patch( {'xS':[(0,B+100)],'xE':[(0,B+100)],'yE':[(0,H)], 'xL':[(0,B+70)], 'yL':[(0,0.5*H)]} )
D_dist_source.patch( {'xE':[(0,B-20)], 'xL':[(0,0.5*B-30)], 'yE':[(0,H+10)], 'yL':[(0,0.5*H+30)]} )
T1_source.patch( {'xE':[(0,-(np.cos(theta_total1)*150*(T1/(T1+T2))))],'yE':[(0,-(np.sin(theta_total1)*150*(T1/(T1+T2))))], 'xL':[(0,-50-0.5*(np.cos(theta_total1)*150*(T1/(T1+T2))))], 'yL':[(0,-50-0.5*(np.sin(theta_total1)*150*(T1/(T1+T2))))]} )
T2_source.patch( {'xS':[(0,B)],'xE':[(0,B+(np.cos(theta_total2)*150*T2/(T1+T2)))],'yS':[(0,H)],'yE':[(0,H+(np.sin(theta_total2)*150*T2/(T1+T2)))], 'xL':[(0,+25+B+0.5*(np.cos(theta_total2)*150*T2/(T1+T2)))], 'yL':[(0,-25+H+0.5*(np.sin(theta_total2)*150*T2/(T1+T2)))]} )
#Slider change call back function for B
def slider_cb_fun_b(attr,old,new):
H=H_slider.value
B=B_slider.value
M=M_slider.value
x_old_fraction = (X_slider.value - X_slider.start) / (X_slider.end - X_slider.start)
X_slider.start=int(0.2*B)
X_slider.end=int(0.9*B)
X_slider.value=int(x_old_fraction * (X_slider.end - X_slider.start) + X_slider.start)
x=int(x_old_fraction * (X_slider.end - X_slider.start) + X_slider.start)
D=np.sqrt(H*H + B*B) #Height of the support (m)
c=c_slider.value
L=c*D #Length of the rope (m)
W=M*9.81 #Weight of the car (N)
#Symbolic constants
theta1=sp.Symbol('theta1',real=True)
theta2=sp.Symbol('theta2',real=True)
#Kinematic equations
eq1= sp.Eq(((L-x/sp.cos(theta1))*sp.cos(theta2))+x-B,0)
eq2= sp.Eq(((x/sp.cos(theta1))*sp.sin(theta1))+((L-x/sp.cos(theta1))*sp.sin(theta2))-H,0)
#Solving the system of equations numerically
[t1,t2]=sp.nsolve((eq1,eq2),(theta1,theta2),(0.25,0.75))
#Effective angles on the Cable
theta_total1=float(t1) #Actual angle at S1 for a specific car position on the rope
theta_total2=float(t2) #Actual angle at S2 for a specific car position on the rope
Lx=x/np.cos(theta_total1) #Length of the bottom cable segement
#Tensions on the Cable
T1= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1)))*(np.cos(theta_total2)/np.cos(theta_total1)) # Rope tension in the bottom
T2= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1))) # Rope tension in the top
#Update the result display
setValueText(D, L,theta_total1*180/np.pi, theta_total2*180/np.pi, T1, T2)
#Update the animated plot
plot.x_range.end=B+200.0
plot.y_range.start=min (-200,Lx * np.sin(theta_total1)-320)
plot.y_range.end=H+150.0
support_source_top.patch( {'x':[(0,B)]} )
support_source_top.patch( {'y':[(0,H+5.0)]} )
line_source_bottom.data=dict(xs = [0, Lx * np.cos(theta_total1)], ys =[0, Lx * np.sin(theta_total1)] )
line_source_top.data=dict(xs = [Lx * np.cos(theta_total1), B], ys =[Lx * np.sin(theta_total1), H] )
line_source_carriage.data=dict(xs = [Lx * np.cos(theta_total1),Lx * np.cos(theta_total1)], ys= [Lx * np.sin(theta_total1)-120,Lx * np.sin(theta_total1)] )
mass_source_carriage.data=dict(x = [Lx * np.cos(theta_total1)], y = [Lx * np.sin(theta_total1)-120], size=[int(M/M_max*80)] )
connecting_pt_circle.data=dict(x = [Lx * np.cos(theta_total1)], y = [ Lx * np.sin(theta_total1)] )
x_pt_circle.data=dict(x = [Lx * np.cos(theta_total1)], y = [min(-200+25,Lx * np.sin(theta_total1)-320+25)] )
y_pt_circle.data=dict(x = [-150+15], y = [ Lx * np.sin(theta_total1)] )
B_dist_source.patch( {'xE':[(0,B)], 'yS':[(0,min(-150,Lx * np.sin(theta_total1)-270))], 'yE':[(0,min(-150,Lx * np.sin(theta_total1)-270))], 'xL':[(0,0.5*B)],'yL':[(0,min(-140,Lx * np.sin(theta_total1)-260))]} )
H_dist_source.patch( {'xS':[(0,B+100)],'xE':[(0,B+100)],'yE':[(0,H)], 'xL':[(0,B+70)], 'yL':[(0,0.5*H)]} )
D_dist_source.patch( {'xE':[(0,B-20)], 'xL':[(0,0.5*B-30)], 'yE':[(0,H+10)], 'yL':[(0,0.5*H+30)]} )
T1_source.patch( {'xE':[(0,-(np.cos(theta_total1)*150*(T1/(T1+T2))))],'yE':[(0,-(np.sin(theta_total1)*150*(T1/(T1+T2))))], 'xL':[(0,-50-0.5*(np.cos(theta_total1)*150*(T1/(T1+T2))))], 'yL':[(0,-50-0.5*(np.sin(theta_total1)*150*(T1/(T1+T2))))]} )
T2_source.patch( {'xS':[(0,B)],'xE':[(0,B+(np.cos(theta_total2)*150*T2/(T1+T2)))],'yS':[(0,H)],'yE':[(0,H+(np.sin(theta_total2)*150*T2/(T1+T2)))], 'xL':[(0,+25+B+0.5*(np.cos(theta_total2)*150*T2/(T1+T2)))], 'yL':[(0,-25+H+0.5*(np.sin(theta_total2)*150*T2/(T1+T2)))]} )
#Call back function for reset button
def callback_reset(event):
H_slider.value=H
c_slider.value=c
B_slider.value=B
M_slider.value=M
X_slider.start=0.2*B
X_slider.end=0.9*B
X_slider.value=0.55*B
x=X_slider.value
D=np.sqrt(H*H+B*B) #Height of the support (m)
L=c*D #Length of the rope (m)
W=M*9.81 #Weight of the car (N)
#Symbolic constants
theta1=sp.Symbol('theta1',real=True)
theta2=sp.Symbol('theta2',real=True)
#Kinematic equations
eq1= sp.Eq(((L-x/sp.cos(theta1))*sp.cos(theta2))+x-B,0)
eq2= sp.Eq(((x/sp.cos(theta1))*sp.sin(theta1))+((L-x/sp.cos(theta1))*sp.sin(theta2))-H,0)
#Solving the system of equations numerically
[t1,t2]=sp.nsolve((eq1,eq2),(theta1,theta2),(0.25,0.75))
#Effective angles on the Cable
theta_total1=float(t1) #Actual angle at S1 for a specific car position on the rope
theta_total2=float(t2) #Actual angle at S2 for a specific car position on the rope
Lx=x/np.cos(theta_total1) #Length of the bottom cable segement
#Tensions on the Cable
T1= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1)))*(np.cos(theta_total2)/np.cos(theta_total1)) # Rope tension in the bottom
T2= W/(np.sin(theta_total2)-(np.cos(theta_total2)*np.sin(theta_total1)/np.cos(theta_total1))) # Rope tension in the top
#Update the result display
setValueText(D, L,theta_total1*180/np.pi, theta_total2*180/np.pi, T1, T2)
#Update the animated plot
plot.x_range.end=B+200.0
plot.y_range.start=min (-200,Lx * np.sin(theta_total1)-320)
plot.y_range.end=H+150.0
support_source_top.patch( {'x':[(0,B)]} )
support_source_top.patch( {'y':[(0,H+5.0)]} )
line_source_bottom.data=dict(xs = [0, Lx * np.cos(theta_total1)], ys =[0, Lx * np.sin(theta_total1)] )
line_source_top.data=dict(xs = [Lx * np.cos(theta_total1), B], ys =[Lx * np.sin(theta_total1), H] )
line_source_carriage.data=dict(xs = [Lx * np.cos(theta_total1),Lx * np.cos(theta_total1)], ys= [Lx * np.sin(theta_total1)-120,Lx * np.sin(theta_total1)] )
mass_source_carriage.data=dict(x = [Lx * np.cos(theta_total1)], y = [Lx * np.sin(theta_total1)-120], size=[int(M/M_max*80)] )
connecting_pt_circle.data=dict(x = [Lx * np.cos(theta_total1)], y = [ Lx * np.sin(theta_total1)] )
x_pt_circle.data=dict(x = [Lx * np.cos(theta_total1)], y = [min(-200+25,Lx * np.sin(theta_total1)-320+25)] )
y_pt_circle.data=dict(x = [-150+15], y = [ Lx * np.sin(theta_total1)] )
B_dist_source.patch( {'xE':[(0,B)], 'yS':[(0,min(-150,Lx * np.sin(theta_total1)-270))], 'yE':[(0,min(-150,Lx * np.sin(theta_total1)-270))], 'xL':[(0,0.5*B)],'yL':[(0,min(-140,Lx * np.sin(theta_total1)-260))]} )
H_dist_source.patch( {'xS':[(0,B+100)],'xE':[(0,B+100)],'yE':[(0,H)], 'xL':[(0,B+70)], 'yL':[(0,0.5*H)]} )
D_dist_source.patch( {'xE':[(0,B-20)], 'xL':[(0,0.5*B-30)], 'yE':[(0,H+10)], 'yL':[(0,0.5*H+30)]} )
T1_source.patch( {'xE':[(0,-(np.cos(theta_total1)*150*(T1/(T1+T2))))],'yE':[(0,-(np.sin(theta_total1)*150*(T1/(T1+T2))))], 'xL':[(0,-50-0.5*(np.cos(theta_total1)*150*(T1/(T1+T2))))], 'yL':[(0,-50-0.5*(np.sin(theta_total1)*150*(T1/(T1+T2))))]} )
T2_source.patch( {'xS':[(0,B)],'xE':[(0,B+(np.cos(theta_total2)*150*T2/(T1+T2)))],'yS':[(0,H)],'yE':[(0,H+(np.sin(theta_total2)*150*T2/(T1+T2)))], 'xL':[(0,+25+B+0.5*(np.cos(theta_total2)*150*T2/(T1+T2)))], 'yL':[(0,-25+H+0.5*(np.sin(theta_total2)*150*T2/(T1+T2)))]} )
# ----------------------------------------------------------------- #
####################################
## SLIDERS & BUTTONS ##
####################################
#Sliders
#Vertical Distance between the supports
H_slider = LatexSlider(title="\\text{Vertical distance between supports (H)}=", value_unit="\\text{m}", value=H, start=H_min, end=H_max, step=1.0, width=400, css_classes=["slider"])
H_slider.on_change('value',slider_cb_fun) # callback function is called when value changes
#Horizontal Distance between the supports
B_slider = LatexSlider(title="\\text{Horizontal distance between supports (B)}=", value_unit="\\text{m}", value=B, start=B_min, end=B_max, step=1.0, width=400, css_classes=["slider"])
B_slider.on_change('value',slider_cb_fun_b) # callback function is called when value changes
#Cable length stretch factor to compute the length of the cable from the distance between the supports
c_slider=LatexSlider(title="\\text{Cable length stretch factor (c = L/D)=}", value=float("{:.5f}".format((c))), start=c_min, end=c_max, step=0.005, width=400, css_classes=["slider"])
c_slider.on_change('value',slider_cb_fun) # callback function is called when value changes
#Mass carried by the cable car container
M_slider = LatexSlider(title="\\text{Mass carried by the system (M)}=", value_unit="\\text{Kg}", value=M, start=M_min, end=M_max, step=1.0, width=400, css_classes=["slider"])
M_slider.on_change('value',slider_cb_fun) # callback function is called when value changes
#Axial location of the carriage
X_slider = LatexSlider(title="\\text{Horizontal location of the carriage (X)}=", value_unit="\\text{m}", value=int(0.55*B_slider.value), start=int(0.2*B_slider.value), end=int(0.9*B_slider.value), step=1.0, width=400, css_classes=["slider"])
X_slider.on_change('value',slider_cb_fun) # callback function is called when value changes
#Reset Button
button_width = 400
Reset_button=Button(label='Reset', button_type='success', width=button_width)
Reset_button.on_click(callback_reset)
# ----------------------------------------------------------------- #
####################################
## ANIMATED PLOT ##
####################################
# Plot
plot = figure(title="", tools="", x_range=(-150,B+200), y_range=(min(-200,Lx * np.sin(theta_total1)-320),H+150),aspect_scale=2.0)
plot.plot_height=700
plot.plot_width=850
plot.toolbar.logo = None
plot.axis.axis_label_text_font_style="normal"
plot.axis.axis_label_text_font_size="14pt"
plot.axis.major_label_text_font_size="14pt"
plot.xaxis.axis_label='x (m)'
plot.yaxis.axis_label='y (m)'
plot.outline_line_width=1.5
plot.outline_line_color="#333333"
plot.outline_line_alpha=0.9
#Column Data Sources definition
# Support source
support_source_bottom = ColumnDataSource(dict(x = [0], y = [0+10.0] , src = [os.path.join(os.path.basename(os.path.dirname(__file__)), "static", "fixed_support.svg")]))
support_source_top = ColumnDataSource(dict(x = [B], y = [H+5.0] , src = [os.path.join(os.path.basename(os.path.dirname(__file__)), "static", "fixed_support.svg")]))
#Line source for the cable
line_source_bottom = ColumnDataSource(dict(xs = [0, Lx * np.cos(theta_total1)], ys =[0, Lx * np.sin(theta_total1)] ))
line_source_top = ColumnDataSource(dict(xs = [Lx * np.cos(theta_total1), B], ys =[Lx * np.sin(theta_total1), H] ))
# Carriage
line_source_carriage = ColumnDataSource(dict(xs = [Lx * np.cos(theta_total1),Lx * np.cos(theta_total1)], ys= [Lx * np.sin(theta_total1)-120,Lx * np.sin(theta_total1)] ))
mass_source_carriage=ColumnDataSource(dict(x = [Lx * np.cos(theta_total1)], y = [Lx * np.sin(theta_total1)-120], size=[int(M/M_max*80)] ))
connecting_pt_circle=ColumnDataSource(dict(x = [Lx * np.cos(theta_total1)], y = [ Lx * np.sin(theta_total1)] ))
#Annotations
B_dist_source = ColumnDataSource(dict(xS=[0], xE=[B], yS=[min(-200+50,Lx * np.sin(theta_total1)-320+50)], yE=[min(-200+50,Lx * np.sin(theta_total1)-320+50)], xL=[B*0.5], yL=[min(-200+60,Lx * np.sin(theta_total1)-320+60)], text=["B"]))
H_dist_source = ColumnDataSource(dict(xS=[B+100], xE=[B+100], yS=[0], yE=[H], xL=[B+70], yL=[0.5*H], text=["H"]))
D_dist_source = ColumnDataSource(dict(xS=[+0], xE=[B-20], yS=[0+30], yE=[H+10], xL=[B*0.5-30], yL=[H*0.5+30], text=["D"]))
x_pt_circle=ColumnDataSource(dict(x = [Lx * np.cos(theta_total1)], y = [min(-200+25,Lx * np.sin(theta_total1)-320+25)] ))
y_pt_circle=ColumnDataSource(dict(x = [-150+15], y = [ Lx * np.sin(theta_total1)] ))
#Cable Tensions & Load
T1_source = ColumnDataSource(dict(xS=[0], xE=[-(np.cos(theta_total1)*150*T1/(T1+T2))], yS=[0], yE=[-(np.sin(theta_total1)*150*T1/(T1+T2))], xL=[-50-0.5*(np.cos(theta_total1)*150*T1/(T1+T2))], yL=[-50-0.5*(np.sin(theta_total1)*150*T1/(T1+T2))], name=["T_1"]))
T2_source =ColumnDataSource(dict(xS=[B], xE=[B+(np.cos(theta_total2)*150*T2/(T1+T2))], yS=[H], yE=[H+(np.sin(theta_total2)*150*T2/(T1+T2))], xL=[+25+B+0.5*(np.cos(theta_total2)*150*T2/(T1+T2))], yL=[-25+H+0.5*(np.sin(theta_total2)*150*T2/(T1+T2))], name=["T_2"]))
#Labels and arrows for annotations & cable tensions
B_dist = Arrow(end=TeeHead(line_color="#808080", line_width=1, size=10),
start=TeeHead(line_color="#808080",line_width=1, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=1, line_color="#808080", source=B_dist_source)
B_dist_label = LatexLabelSet(x='xL', y='yL', text='text', source=B_dist_source)
H_dist = Arrow(end=TeeHead(line_color="#808080", line_width=1, size=10),
start=TeeHead(line_color="#808080",line_width=1, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=1, line_color="#808080", source=H_dist_source)
H_dist_label = LatexLabelSet(x='xL', y='yL', text='text', source=H_dist_source)
D_dist = Arrow(end=TeeHead(line_color="#808080", line_width=1, size=10),
start=TeeHead(line_color="#808080",line_width=1, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=1, line_color="#808080", source=D_dist_source)
D_dist_label = LatexLabelSet(x='xL', y='yL', text='text', source=D_dist_source)
T1_arrow_glyph = Arrow(end=OpenHead(line_color="#333333", line_width=4, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=4, source=T1_source,line_color="#333333")
T2_arrow_glyph = Arrow(end=OpenHead(line_color="#333333", line_width=4, size=10),
x_start='xS', y_start='yS', x_end='xE', y_end='yE', line_width=4, source=T2_source,line_color="#333333")
T1_label_glyph=LatexLabelSet(x='xL', y='yL', text='name', text_font_size="15pt", level='glyph', source=T1_source)
T2_label_glyph=LatexLabelSet(x='xL', y='yL', text='name', text_font_size="15pt", level='glyph', source=T2_source)
#Adding all glyps into the plot - lines, carriage, supports, tensions & annotations
plot.line(x='xs', y='ys', source=line_source_bottom , line_width=10, color='#3070B3')
plot.line(x='xs', y='ys', source=line_source_top , line_width=10, color='#3070B3')
plot.circle(x='x', y='y', source=connecting_pt_circle, size=20, color="#e37222")
plot.line(x='xs', y='ys', source=line_source_carriage, line_width=10, color="#e37222")
plot.square(x='x', y='y', size='size', source=mass_source_carriage, color="#e37222")
plot.circle(x='x', y='y', source=x_pt_circle, size=20, color="#a2ad00")
plot.circle(x='x', y='y', source=y_pt_circle, size=20, color="#a2ad00")
plot.add_glyph(support_source_top,ImageURL(url="src", x='x', y='y', w=60, h=60, anchor="top_center"))
plot.add_glyph(support_source_bottom,ImageURL(url="src", x='x', y='y', w=60, h=60, anchor="top_center"))
plot.add_layout(T1_arrow_glyph)
plot.add_layout(T2_arrow_glyph)
plot.add_layout(T1_label_glyph)
plot.add_layout(T2_label_glyph)
plot.add_layout(B_dist)
plot.add_layout(B_dist_label)
plot.add_layout(H_dist)
plot.add_layout(H_dist_label)
plot.add_layout(D_dist)
plot.add_layout(D_dist_label)
# ----------------------------------------------------------------- #
####################################
## LAYOUT ##
####################################
curdoc().add_root(column(
description1,
figure_kin,
description2,
figure_fbd,
description3,
column(column(
row(H_slider,B_slider,c_slider),
row(M_slider,X_slider,Reset_button),
row(plot),
row(value_plot_distance_cable_length,value_plot_angles, value_plot_tensions)
))))
curdoc().title = split(dirname(__file__))[-1].replace('_',' ').replace('-',' ') # get path of parent directory and only use the name of the Parent Directory for the tab name. Replace underscores '_' and minuses '-' with blanks ' '
# ----------------------------------------------------------------- #
| 11,116 | 0 | 88 |
ace151f9d07e22911ec8de4866e79b4177de2d14 | 3,155 | py | Python | PBP.py | j-friedrich/neuronalGPR | 0a05f0b0a30ac6ecbd5b3ff175d3cbfeb723479b | [
"Apache-2.0"
] | 2 | 2020-11-26T04:23:04.000Z | 2021-06-10T11:32:40.000Z | PBP.py | j-friedrich/neuronalGPR | 0a05f0b0a30ac6ecbd5b3ff175d3cbfeb723479b | [
"Apache-2.0"
] | null | null | null | PBP.py | j-friedrich/neuronalGPR | 0a05f0b0a30ac6ecbd5b3ff175d3cbfeb723479b | [
"Apache-2.0"
] | null | null | null | from GPnet import logpdf
import math
import numpy as np
import os
import sys
from time import time
sys.path.append('Probabilistic-Backpropagation-master/c/PBP_net')
import PBP_net
# pass the name of the UCI Dataset directory as argument
try:
data_directory = sys.argv[1]
except:
data_directory = 'bostonHousing'
_UCI_DIRECTORY_PATH = "DropoutUncertaintyExps-master/UCI_Datasets/"
subfolders = [f.name for f in os.scandir(_UCI_DIRECTORY_PATH) if f.is_dir()]
subfolders.sort()
if data_directory not in subfolders:
raise ValueError("data directory must be one of the following " +
repr(subfolders) + " but was " + data_directory)
_DATA_DIRECTORY_PATH = _UCI_DIRECTORY_PATH + data_directory + "/data/"
data = np.loadtxt(_DATA_DIRECTORY_PATH + "data.txt")
index_features = np.loadtxt(_DATA_DIRECTORY_PATH + "index_features.txt")
index_target = np.loadtxt(_DATA_DIRECTORY_PATH + "index_target.txt")
X = data[:, [int(i) for i in index_features.tolist()]]
y = data[:, int(index_target.tolist())]
n_splits = int(np.loadtxt(_DATA_DIRECTORY_PATH + 'n_splits.txt'))
n_hidden = int(np.loadtxt(_DATA_DIRECTORY_PATH + "n_hidden.txt"))
n_epochs = int(np.loadtxt(_DATA_DIRECTORY_PATH + 'n_epochs.txt'))
def _get_index_train_test_path(split_num, train=True):
"""
Method to generate the path containing the training/test split for the given
split number (generally from 1 to 20).
@param split_num Split number for which the data has to be generated
@param train Is true if the data is training data. Else false.
@return path Path of the file containing the requried data
"""
if train:
return _DATA_DIRECTORY_PATH + "index_train_" + str(split_num) + ".txt"
else:
return _DATA_DIRECTORY_PATH + "index_test_" + str(split_num) + ".txt"
perf = np.nan * np.zeros((n_splits, 2, 3))
for n_layers in (1, 2):
np.random.seed(1)
for split in range(n_splits):
# We load the indexes of the training and test sets
print('Loading file: ' + _get_index_train_test_path(split, train=True))
print('Loading file: ' + _get_index_train_test_path(split, train=False))
index_train = np.loadtxt(_get_index_train_test_path(split, train=True))
index_test = np.loadtxt(_get_index_train_test_path(split, train=False))
X_train = X[[int(i) for i in index_train.tolist()]]
y_train = y[[int(i) for i in index_train.tolist()]]
X_test = X[[int(i) for i in index_test.tolist()]]
y_test = y[[int(i) for i in index_test.tolist()]]
net = PBP_net.PBP_net(X_train, y_train, [n_hidden] * n_layers,
normalize=True, n_epochs=n_epochs)
# We make predictions for the test set
t = -time()
m, v, v_noise = net.predict(X_test)
t += time()
# We compute the test RMSE and ll
perf[split, n_layers - 1, :2] = (np.sqrt(np.mean((y_test - m)**2)),
logpdf(y_test - m, v + v_noise).mean())
perf[split, n_layers - 1, 2] = t
np.save('results/PBP/' + data_directory, perf)
| 39.4375 | 85 | 0.666878 | from GPnet import logpdf
import math
import numpy as np
import os
import sys
from time import time
sys.path.append('Probabilistic-Backpropagation-master/c/PBP_net')
import PBP_net
# pass the name of the UCI Dataset directory as argument
try:
data_directory = sys.argv[1]
except:
data_directory = 'bostonHousing'
_UCI_DIRECTORY_PATH = "DropoutUncertaintyExps-master/UCI_Datasets/"
subfolders = [f.name for f in os.scandir(_UCI_DIRECTORY_PATH) if f.is_dir()]
subfolders.sort()
if data_directory not in subfolders:
raise ValueError("data directory must be one of the following " +
repr(subfolders) + " but was " + data_directory)
_DATA_DIRECTORY_PATH = _UCI_DIRECTORY_PATH + data_directory + "/data/"
data = np.loadtxt(_DATA_DIRECTORY_PATH + "data.txt")
index_features = np.loadtxt(_DATA_DIRECTORY_PATH + "index_features.txt")
index_target = np.loadtxt(_DATA_DIRECTORY_PATH + "index_target.txt")
X = data[:, [int(i) for i in index_features.tolist()]]
y = data[:, int(index_target.tolist())]
n_splits = int(np.loadtxt(_DATA_DIRECTORY_PATH + 'n_splits.txt'))
n_hidden = int(np.loadtxt(_DATA_DIRECTORY_PATH + "n_hidden.txt"))
n_epochs = int(np.loadtxt(_DATA_DIRECTORY_PATH + 'n_epochs.txt'))
def _get_index_train_test_path(split_num, train=True):
"""
Method to generate the path containing the training/test split for the given
split number (generally from 1 to 20).
@param split_num Split number for which the data has to be generated
@param train Is true if the data is training data. Else false.
@return path Path of the file containing the requried data
"""
if train:
return _DATA_DIRECTORY_PATH + "index_train_" + str(split_num) + ".txt"
else:
return _DATA_DIRECTORY_PATH + "index_test_" + str(split_num) + ".txt"
perf = np.nan * np.zeros((n_splits, 2, 3))
for n_layers in (1, 2):
np.random.seed(1)
for split in range(n_splits):
# We load the indexes of the training and test sets
print('Loading file: ' + _get_index_train_test_path(split, train=True))
print('Loading file: ' + _get_index_train_test_path(split, train=False))
index_train = np.loadtxt(_get_index_train_test_path(split, train=True))
index_test = np.loadtxt(_get_index_train_test_path(split, train=False))
X_train = X[[int(i) for i in index_train.tolist()]]
y_train = y[[int(i) for i in index_train.tolist()]]
X_test = X[[int(i) for i in index_test.tolist()]]
y_test = y[[int(i) for i in index_test.tolist()]]
net = PBP_net.PBP_net(X_train, y_train, [n_hidden] * n_layers,
normalize=True, n_epochs=n_epochs)
# We make predictions for the test set
t = -time()
m, v, v_noise = net.predict(X_test)
t += time()
# We compute the test RMSE and ll
perf[split, n_layers - 1, :2] = (np.sqrt(np.mean((y_test - m)**2)),
logpdf(y_test - m, v + v_noise).mean())
perf[split, n_layers - 1, 2] = t
np.save('results/PBP/' + data_directory, perf)
| 0 | 0 | 0 |
5599830627e1810ca48894b577fe421208753155 | 1,134 | py | Python | game_snake.py | Index-Eletronic/python2 | 92b6e844171976c782bd827ebb8c05364c34d6ad | [
"MIT"
] | null | null | null | game_snake.py | Index-Eletronic/python2 | 92b6e844171976c782bd827ebb8c05364c34d6ad | [
"MIT"
] | null | null | null | game_snake.py | Index-Eletronic/python2 | 92b6e844171976c782bd827ebb8c05364c34d6ad | [
"MIT"
] | null | null | null | import pygame, random
from random import randint
from pygame.locals import *
UP = 0
RIGHT = 1
DOWN = 2
LEFT = 3
pygame.init()
screen = pygame.display.set_mode((600, 600))
pygame.display.set_caption('Snake')
snake = [(200, 200, (210, 210), (200, 200))]
snake_skin = pygame.Surface((10, 10))
snake_skin.fill((255, 255, 255))
apple_pos = (random, randint(0, 590), random.randint(0, 590))
apple = pygame.Surface((10, 10))
apple.fill((255, 0, 0))
my_direction = LEFT
while True:
for event in pygame.event.get():
if event.type == QUIT:
pygame.quit()
if my_direction == UP:
snake[0] = (snake[0][0], snake[0][1] - 10)
if my_direction == DOWN:
snake[0] = (snake[0][0], snake[0][1] + 10)
if my_direction == RIGHT:
snake[0] = (snake[0][0] + 10, snake[0][1])
if my_direction == LEFT:
snake[0] = (snake[0][0] - 10, snake[0][1])
for i in range(len(snake) - 1, 0, -1):
snake[i] = (snake[i][0], snake[i][1])
screen.fill((0, 0, 0))
screen.blit(apple, apple_pos)
for pos in snake:
screen.blit(snake_skin, pos)
pygame.display.update()
| 24.12766 | 61 | 0.593474 | import pygame, random
from random import randint
from pygame.locals import *
UP = 0
RIGHT = 1
DOWN = 2
LEFT = 3
pygame.init()
screen = pygame.display.set_mode((600, 600))
pygame.display.set_caption('Snake')
snake = [(200, 200, (210, 210), (200, 200))]
snake_skin = pygame.Surface((10, 10))
snake_skin.fill((255, 255, 255))
apple_pos = (random, randint(0, 590), random.randint(0, 590))
apple = pygame.Surface((10, 10))
apple.fill((255, 0, 0))
my_direction = LEFT
while True:
for event in pygame.event.get():
if event.type == QUIT:
pygame.quit()
if my_direction == UP:
snake[0] = (snake[0][0], snake[0][1] - 10)
if my_direction == DOWN:
snake[0] = (snake[0][0], snake[0][1] + 10)
if my_direction == RIGHT:
snake[0] = (snake[0][0] + 10, snake[0][1])
if my_direction == LEFT:
snake[0] = (snake[0][0] - 10, snake[0][1])
for i in range(len(snake) - 1, 0, -1):
snake[i] = (snake[i][0], snake[i][1])
screen.fill((0, 0, 0))
screen.blit(apple, apple_pos)
for pos in snake:
screen.blit(snake_skin, pos)
pygame.display.update()
| 0 | 0 | 0 |
c391af00e60bd4865d7153fb1a73ff817c1cd33b | 4,317 | py | Python | imaginglss/utils/fits.py | desihub/imaginglss | 09258d20015869fead9bad6020da2bc0d161f670 | [
"MIT"
] | 6 | 2015-04-30T18:58:28.000Z | 2020-11-23T16:52:02.000Z | imaginglss/utils/fits.py | desihub/imaginglss | 09258d20015869fead9bad6020da2bc0d161f670 | [
"MIT"
] | 15 | 2015-07-21T18:44:30.000Z | 2018-09-07T22:40:31.000Z | imaginglss/utils/fits.py | desihub/imaginglss | 09258d20015869fead9bad6020da2bc0d161f670 | [
"MIT"
] | 2 | 2017-11-29T16:58:34.000Z | 2018-07-23T15:52:59.000Z | from __future__ import print_function
"""
Simple routines that provide a uniform interface for reading
fits hdus via either astropy.io.fits or fitsio.
Three functions are provided:
read_image, read_table, read_metadata
Warning: A copy of data is returned to detach any backreference to
the original fits library. Use with caution with extremely
large files. (> half of avail memory on machine)
"""
__author__ = "Yu Feng and Martin White"
__version__ = "0.9"
__email__ = "yfeng1@berkeley.edu or mjwhite@lbl.gov"
__all__ = ['read_image', 'read_table', 'read_metadata', 'size_table']
import numpy
def use_astropy():
""" select the astropy backend """
global read_image
global read_table
global size_table
global read_metadata
global backend
backend = "astropy"
from astropy.io import fits
def read_image(filename, hdu=0):
"""
Read the zeroth image HDU from a fits file
"""
file = fits.open(filename)
# A copy of data is made before the file object
# is dereferenced. This is to ensure no back references
# to the fits object and file gets closed in a timely
# fashion.
return numpy.array(file[hdu].data, copy=True)
def read_table(filename, hdu=1, subset=None):
"""
Read the first HDU table from a fits file
"""
file = fits.open(filename)
if subset is not None:
column, start, end = subset
return numpy.array(file[hdu][column][start:end], copy=True)
return numpy.array(file[hdu].data, copy=True)
def size_table(filename, hdu=1):
"""
Read the first HDU table from a fits file
"""
file = fits.open(filename)
return file[hdu].shape[0]
def read_metadata(filename, hdu=0):
"""
Read the metadata of a HDU table
"""
file = fits.open(filename)
return dict(file[hdu].header)
def use_fitsio():
""" select the fitsio backend """
global read_image
global read_table
global size_table
global read_metadata
global backend
backend = "fitsio"
from fitsio import FITS
def read_image(filename, hdu=0):
"""
Read the zeroth image HDU from a fits file
"""
file = FITS(filename, upper=True)
# A copy of data is made before the file object
# is dereferenced. This is to ensure no back references
# to the fits object and file gets closed in a timely
# fashion.
return numpy.array(file[hdu].read(), copy=True)
def read_table(filename, hdu=1, subset=None):
"""
Read the first HDU table from a fits file
"""
file = FITS(filename, upper=True)
if subset is not None:
column, start, end = subset
return numpy.array(file[hdu][column][start:end], copy=True)
else:
return numpy.array(file[hdu].read(), copy=True)
def size_table(filename, hdu=1):
"""
Read the first HDU table from a fits file
"""
file = FITS(filename, upper=True)
return file[hdu].get_nrows()
def read_metadata(filename, hdu=0):
"""
Read the metadata of a HDU table
"""
file = FITS(filename, upper=True)
return dict(file[hdu].read_header())
_priorities = [use_fitsio, use_astropy]
for backend in _priorities:
try:
backend()
break
except ImportError:
continue
if __name__ == '__main__':
use_fitsio()
im0 = read_image('depth-370143-g.fits.gz')
meta0 = read_metadata('depth-370143-g.fits.gz')
tbl0 = read_table('tractor-370143.fits')
assert backend == 'fitsio'
use_astropy()
im1 = read_image('depth-370143-g.fits.gz')
meta1 = read_metadata('depth-370143-g.fits.gz')
tbl1 = read_table('tractor-370143.fits')
assert backend == 'astropy'
assert (im0[...] == im1[...]).all()
assert set(tbl0.dtype.names) == set(tbl1.dtype.names)
assert set(meta0.keys()) == set(meta1.keys())
for k in meta0.keys():
if k == "COMMENT": continue
print (k, '::::', meta0[k], '::::', meta1[k])
assert meta0[k] == meta1[k]
| 28.973154 | 71 | 0.603428 | from __future__ import print_function
"""
Simple routines that provide a uniform interface for reading
fits hdus via either astropy.io.fits or fitsio.
Three functions are provided:
read_image, read_table, read_metadata
Warning: A copy of data is returned to detach any backreference to
the original fits library. Use with caution with extremely
large files. (> half of avail memory on machine)
"""
__author__ = "Yu Feng and Martin White"
__version__ = "0.9"
__email__ = "yfeng1@berkeley.edu or mjwhite@lbl.gov"
__all__ = ['read_image', 'read_table', 'read_metadata', 'size_table']
import numpy
def use_astropy():
""" select the astropy backend """
global read_image
global read_table
global size_table
global read_metadata
global backend
backend = "astropy"
from astropy.io import fits
def read_image(filename, hdu=0):
"""
Read the zeroth image HDU from a fits file
"""
file = fits.open(filename)
# A copy of data is made before the file object
# is dereferenced. This is to ensure no back references
# to the fits object and file gets closed in a timely
# fashion.
return numpy.array(file[hdu].data, copy=True)
def read_table(filename, hdu=1, subset=None):
"""
Read the first HDU table from a fits file
"""
file = fits.open(filename)
if subset is not None:
column, start, end = subset
return numpy.array(file[hdu][column][start:end], copy=True)
return numpy.array(file[hdu].data, copy=True)
def size_table(filename, hdu=1):
"""
Read the first HDU table from a fits file
"""
file = fits.open(filename)
return file[hdu].shape[0]
def read_metadata(filename, hdu=0):
"""
Read the metadata of a HDU table
"""
file = fits.open(filename)
return dict(file[hdu].header)
def use_fitsio():
""" select the fitsio backend """
global read_image
global read_table
global size_table
global read_metadata
global backend
backend = "fitsio"
from fitsio import FITS
def read_image(filename, hdu=0):
"""
Read the zeroth image HDU from a fits file
"""
file = FITS(filename, upper=True)
# A copy of data is made before the file object
# is dereferenced. This is to ensure no back references
# to the fits object and file gets closed in a timely
# fashion.
return numpy.array(file[hdu].read(), copy=True)
def read_table(filename, hdu=1, subset=None):
"""
Read the first HDU table from a fits file
"""
file = FITS(filename, upper=True)
if subset is not None:
column, start, end = subset
return numpy.array(file[hdu][column][start:end], copy=True)
else:
return numpy.array(file[hdu].read(), copy=True)
def size_table(filename, hdu=1):
"""
Read the first HDU table from a fits file
"""
file = FITS(filename, upper=True)
return file[hdu].get_nrows()
def read_metadata(filename, hdu=0):
"""
Read the metadata of a HDU table
"""
file = FITS(filename, upper=True)
return dict(file[hdu].read_header())
_priorities = [use_fitsio, use_astropy]
for backend in _priorities:
try:
backend()
break
except ImportError:
continue
if __name__ == '__main__':
use_fitsio()
im0 = read_image('depth-370143-g.fits.gz')
meta0 = read_metadata('depth-370143-g.fits.gz')
tbl0 = read_table('tractor-370143.fits')
assert backend == 'fitsio'
use_astropy()
im1 = read_image('depth-370143-g.fits.gz')
meta1 = read_metadata('depth-370143-g.fits.gz')
tbl1 = read_table('tractor-370143.fits')
assert backend == 'astropy'
assert (im0[...] == im1[...]).all()
assert set(tbl0.dtype.names) == set(tbl1.dtype.names)
assert set(meta0.keys()) == set(meta1.keys())
for k in meta0.keys():
if k == "COMMENT": continue
print (k, '::::', meta0[k], '::::', meta1[k])
assert meta0[k] == meta1[k]
| 0 | 0 | 0 |
9ccb8b74b69c210584f743a4cebd0476dc64ae0e | 4,171 | py | Python | test/core/039-black-metadata/blackdiamond.py | ahnitz/pegasus | e269b460f4d87eb3f3a7e91cd82e2c28fdb55573 | [
"Apache-2.0"
] | 127 | 2015-01-28T19:19:13.000Z | 2022-03-31T05:57:40.000Z | test/core/039-black-metadata/blackdiamond.py | ahnitz/pegasus | e269b460f4d87eb3f3a7e91cd82e2c28fdb55573 | [
"Apache-2.0"
] | 14 | 2015-04-15T17:44:20.000Z | 2022-02-22T22:48:49.000Z | test/core/039-black-metadata/blackdiamond.py | ahnitz/pegasus | e269b460f4d87eb3f3a7e91cd82e2c28fdb55573 | [
"Apache-2.0"
] | 70 | 2015-01-22T15:20:32.000Z | 2022-02-21T22:50:23.000Z | #!/usr/bin/env python3
import logging
from pathlib import Path
from datetime import datetime
from Pegasus.api import *
logging.basicConfig(level=logging.DEBUG)
PEGASUS_LOCATION = "/usr/bin/pegasus-keg"
# --- Work Dir Setup -----------------------------------------------------------
RUN_ID = "black-diamond-metadata-" + datetime.now().strftime("%s")
TOP_DIR = Path.cwd()
WORK_DIR = TOP_DIR / "work"
try:
Path.mkdir(WORK_DIR)
except FileExistsError:
pass
# --- Configuration ------------------------------------------------------------
print("Generating pegasus.conf at: {}".format(TOP_DIR / "pegasus.properties"))
conf = Properties()
conf["pegasus.catalog.site.file"] = "./conf/sites.yml"
conf["pegasus.catalog.site"] = "YAML"
conf.write()
# --- Replicas -----------------------------------------------------------------
print("Generating replica catalog at: {}".format(TOP_DIR / "replicas.yml"))
# create initial input file
with open("f.a", "w") as f:
f.write("This is sample input to KEG\n")
fa = File("f.a", size=1024).add_metadata({"raw_input": "true"})
ReplicaCatalog().add_replica("local", fa, TOP_DIR / fa.lfn).write()
# --- Transformations ----------------------------------------------------------
print(
"Generating transformation catalog at: {}".format(TOP_DIR / "transformations.yml")
)
preprocess = Transformation(
"preprocess",
namespace="pegasus",
version="4.0",
site="condorpool",
pfn=PEGASUS_LOCATION,
is_stageable=False,
arch=Arch.X86_64,
os_type=OS.LINUX
).add_metadata(size=2048, transformation="preprocess")
findrange = Transformation(
"findrange",
namespace="pegasus",
version="4.0",
site="condorpool",
pfn=PEGASUS_LOCATION,
is_stageable=False,
arch=Arch.X86_64,
os_type=OS.LINUX
).add_metadata(size=2048, transformation="findrange")
analyze = Transformation(
"analyze",
namespace="pegasus",
version="4.0",
site="condorpool",
pfn=PEGASUS_LOCATION,
is_stageable=False,
arch=Arch.X86_64,
os_type=OS.LINUX
).add_metadata(size=2048, transformation="analyze")
TransformationCatalog().add_transformations(preprocess, findrange, analyze).write()
# --- Workflow -----------------------------------------------------------------
print("Generating workflow")
wf = Workflow("diamond")
wf.add_metadata(label="keg-diamond", group="test")
fb1 = File("f.ƀ1")
fb2 = File("f.β2")
fc1 = File("f.Ҫ1")
fc2 = File("f.Ͻ2")
fd = File("f.Ɗ").add_metadata(final_output=True)
preprocess_job = Job(preprocess)\
.add_args("-a", "preprocess", "-T", "60", "-i", fa, "-o", fb1, fb2)\
.add_inputs(fa)\
.add_outputs(fb1, fb2, register_replica=True)\
.add_metadata(time=60)
findrange_1_job = Job(findrange)\
.add_args("-a", "findrange", "-T", "60", "-i", fb1, "-o", fc1)\
.add_inputs(fb1)\
.add_outputs(fc1, register_replica=True)\
.add_metadata(time=60)
findrange_2_job = Job(findrange)\
.add_args("-a", "findrange", "-T", "60", "-i", fb2, "-o", fc2)\
.add_inputs(fb2)\
.add_outputs(fc2, register_replica=True)\
.add_metadata(time=60)
analyze_job = Job(analyze)\
.add_args("-a", "analyze", "-T", "60", "-i", fc1, fc2, "-o", fd)\
.add_inputs(fc1, fc2)\
.add_outputs(fd, register_replica=True)\
.add_metadata(time=60)
wf.add_jobs(preprocess_job, findrange_1_job, findrange_2_job, analyze_job)
try:
wf.plan(
dir=WORK_DIR,
verbose=3,
relative_dir=RUN_ID,
sites=["condorpool"],
force=True,
submit=True,
)
except PegasusClientError as e:
print(e.output)
| 31.360902 | 88 | 0.525533 | #!/usr/bin/env python3
import logging
from pathlib import Path
from datetime import datetime
from Pegasus.api import *
logging.basicConfig(level=logging.DEBUG)
PEGASUS_LOCATION = "/usr/bin/pegasus-keg"
# --- Work Dir Setup -----------------------------------------------------------
RUN_ID = "black-diamond-metadata-" + datetime.now().strftime("%s")
TOP_DIR = Path.cwd()
WORK_DIR = TOP_DIR / "work"
try:
Path.mkdir(WORK_DIR)
except FileExistsError:
pass
# --- Configuration ------------------------------------------------------------
print("Generating pegasus.conf at: {}".format(TOP_DIR / "pegasus.properties"))
conf = Properties()
conf["pegasus.catalog.site.file"] = "./conf/sites.yml"
conf["pegasus.catalog.site"] = "YAML"
conf.write()
# --- Replicas -----------------------------------------------------------------
print("Generating replica catalog at: {}".format(TOP_DIR / "replicas.yml"))
# create initial input file
with open("f.a", "w") as f:
f.write("This is sample input to KEG\n")
fa = File("f.a", size=1024).add_metadata({"raw_input": "true"})
ReplicaCatalog().add_replica("local", fa, TOP_DIR / fa.lfn).write()
# --- Transformations ----------------------------------------------------------
print(
"Generating transformation catalog at: {}".format(TOP_DIR / "transformations.yml")
)
preprocess = Transformation(
"preprocess",
namespace="pegasus",
version="4.0",
site="condorpool",
pfn=PEGASUS_LOCATION,
is_stageable=False,
arch=Arch.X86_64,
os_type=OS.LINUX
).add_metadata(size=2048, transformation="preprocess")
findrange = Transformation(
"findrange",
namespace="pegasus",
version="4.0",
site="condorpool",
pfn=PEGASUS_LOCATION,
is_stageable=False,
arch=Arch.X86_64,
os_type=OS.LINUX
).add_metadata(size=2048, transformation="findrange")
analyze = Transformation(
"analyze",
namespace="pegasus",
version="4.0",
site="condorpool",
pfn=PEGASUS_LOCATION,
is_stageable=False,
arch=Arch.X86_64,
os_type=OS.LINUX
).add_metadata(size=2048, transformation="analyze")
TransformationCatalog().add_transformations(preprocess, findrange, analyze).write()
# --- Workflow -----------------------------------------------------------------
print("Generating workflow")
wf = Workflow("diamond")
wf.add_metadata(label="keg-diamond", group="test")
fb1 = File("f.ƀ1")
fb2 = File("f.β2")
fc1 = File("f.Ҫ1")
fc2 = File("f.Ͻ2")
fd = File("f.Ɗ").add_metadata(final_output=True)
preprocess_job = Job(preprocess)\
.add_args("-a", "preprocess", "-T", "60", "-i", fa, "-o", fb1, fb2)\
.add_inputs(fa)\
.add_outputs(fb1, fb2, register_replica=True)\
.add_metadata(time=60)
findrange_1_job = Job(findrange)\
.add_args("-a", "findrange", "-T", "60", "-i", fb1, "-o", fc1)\
.add_inputs(fb1)\
.add_outputs(fc1, register_replica=True)\
.add_metadata(time=60)
findrange_2_job = Job(findrange)\
.add_args("-a", "findrange", "-T", "60", "-i", fb2, "-o", fc2)\
.add_inputs(fb2)\
.add_outputs(fc2, register_replica=True)\
.add_metadata(time=60)
analyze_job = Job(analyze)\
.add_args("-a", "analyze", "-T", "60", "-i", fc1, fc2, "-o", fd)\
.add_inputs(fc1, fc2)\
.add_outputs(fd, register_replica=True)\
.add_metadata(time=60)
wf.add_jobs(preprocess_job, findrange_1_job, findrange_2_job, analyze_job)
try:
wf.plan(
dir=WORK_DIR,
verbose=3,
relative_dir=RUN_ID,
sites=["condorpool"],
force=True,
submit=True,
)
except PegasusClientError as e:
print(e.output)
| 0 | 0 | 0 |
4136de2a6c45e4353c6f0e7ae6ce04c83b0bae79 | 781 | py | Python | traindataset.py | RetrainIt/Perfect-Half-Million-Beauty-Product-Image-Recognition-Challenge | 080aa5ae2f2755c6dc10b7cdc910ec0f76bc82c3 | [
"Apache-2.0"
] | 15 | 2018-07-06T09:29:20.000Z | 2021-05-15T05:22:36.000Z | traindataset.py | X-Lambert/Perfect-Half-Million-Beauty-Product-Image-Recognition-Challenge | 55b1be6fdb80e403efb495000e85157bbc626dbf | [
"Apache-2.0"
] | 1 | 2019-03-17T12:11:30.000Z | 2019-03-27T02:47:51.000Z | traindataset.py | X-Lambert/Perfect-Half-Million-Beauty-Product-Image-Recognition-Challenge | 55b1be6fdb80e403efb495000e85157bbc626dbf | [
"Apache-2.0"
] | 3 | 2018-07-06T09:29:22.000Z | 2021-05-15T05:22:37.000Z | import os
import pickle
from PIL import Image
import torch
import torch.utils.data as data
| 24.40625 | 64 | 0.604353 | import os
import pickle
from PIL import Image
import torch
import torch.utils.data as data
def imresize(img,imsize):
img.thumbnail((imsize,imsize),Image.ANTIALIAS)
return img
class myImageFloder(data.Dataset):
def __init__(self, img_list, transform = None,imsize = 480):
im = []
self.img_list = img_list
self.transform = transform
self.imsize = imsize
def __getitem__(self,index):
img = self.img_list[index]
im = Image.open(img).convert('RGB')
im = imresize(im,self.imsize)
if self.transform is not None:
im = self.transform(im)
im_name = img.split('/')[-1]
return im, im_name
def __len__(self):
return len(self.img_list)
| 543 | 13 | 134 |
3b1524375d427e160ae74fcd3b7a16474be0dda4 | 7,587 | py | Python | AuxeBot/cogs/ReactionRoles.py | pintermor9/AuxeBot | 5646a400fcf301fb736066d26158b6d76f6fbe3a | [
"MIT"
] | null | null | null | AuxeBot/cogs/ReactionRoles.py | pintermor9/AuxeBot | 5646a400fcf301fb736066d26158b6d76f6fbe3a | [
"MIT"
] | 2 | 2022-03-27T07:29:26.000Z | 2022-03-27T14:38:48.000Z | AuxeBot/cogs/ReactionRoles.py | pintermor9/AuxeBot | 5646a400fcf301fb736066d26158b6d76f6fbe3a | [
"MIT"
] | null | null | null | import uuid
import discord
import logging
from discord.ext import commands
from asyncio import TimeoutError
logger = logging.getLogger(__name__)
| 42.385475 | 155 | 0.58218 | import uuid
import discord
import logging
from discord.ext import commands
from asyncio import TimeoutError
logger = logging.getLogger(__name__)
class ReactionRoles(commands.Cog):
def __init__(self, bot):
self.bot = bot
logger.info("Loaded " + __name__)
def parse_reaction_payload(self, payload: discord.RawReactionActionEvent):
guild_id = payload.guild_id
data = self.bot.data["reaction_roles"].get(str(guild_id), None)
if data is not None:
for rr in data:
emote = rr.get("emote")
if int(payload.message_id) == int(rr.get("messageID")):
if int(payload.channel_id) == int(rr.get("channelID")):
if str(payload.emoji) == str(emote):
guild = self.bot.get_guild(guild_id)
role = guild.get_role(int(rr.get("roleID")))
user = guild.get_member(int(payload.user_id))
if user != self.bot.user:
return role, user
return None, None
@commands.Cog.listener()
async def on_raw_reaction_add(self, payload: discord.RawReactionActionEvent):
role, user = self.parse_reaction_payload(payload)
if role is not None and user is not None and user is not self.bot.user:
await user.add_roles(role, reason="ReactionRole")
@commands.Cog.listener()
async def on_raw_reaction_remove(self, payload: discord.RawReactionActionEvent):
role, user = self.parse_reaction_payload(payload)
if role is not None and user is not None and user is not self.bot.user:
await user.remove_roles(role, reason="ReactionRole")
@commands.has_permissions(manage_channels=True, manage_roles=True)
@commands.command(description="Creates a new reaction role.")
async def reaction(
self,
ctx,
emote,
role: discord.Role,
channel: discord.TextChannel,
title,
message,
):
"""Creates a new reaction role. The bot will send an embed message, wich will be the base of the reaction role.
**Parameters:**
`emote`: The emoji that users need to react in order to get the role.
`role`: A role that users get.
`channel`: The channel that the embed gets sent in. This can be the channels mention, name or id.
`title`: Title of the embed.
`message`: Description of the embed.
"""
embed = discord.Embed(title=title, description=message)
msg = await channel.send(embed=embed)
await msg.add_reaction(emote)
self.add_reaction(ctx.guild.id, emote, role.id, channel.id, msg.id)
@commands.has_permissions(manage_channels=True, manage_roles=True)
@commands.group(
invoke_without_command=True,
description="Lists the reaction roles in the current guild.",
)
async def reactions(self, ctx):
guild_id = ctx.guild.id
data = self.bot.data["reaction_roles"].get(str(guild_id), None)
embed = discord.Embed(title="Reaction Roles")
if data == None or data == []:
embed.description = "There are no reaction roles set up right now."
else:
for index, rr in enumerate(data):
emote = rr.get("emote")
role_id = rr.get("roleID")
role = ctx.guild.get_role(role_id)
channel_id = rr.get("channelID")
message_id = rr.get("messageID")
embed.add_field(
name=index,
value=f"{emote} - @{role} - [message](https://www.discord.com/channels/{guild_id}/{channel_id}/{message_id})",
inline=False,
)
await ctx.send(embed=embed)
@commands.has_permissions(manage_channels=True, manage_roles=True)
@reactions.command(description="Creates a new reaction role.")
async def add(
self, ctx, emote, role: discord.Role, channel: discord.TextChannel, message_id
):
"""Creates a new reaction role for an existing message.
**Parameters:**
`emote`: The emoji that users need to react in order to get the role.
`role`: A role that users get.
`channel`: The channel that the embed gets sent in. This can be the channels mention, name or id.
`message_id`: This is the id of the message that will be the base of the reaction role.
"""
msg = await channel.fetch_message(int(message_id))
await msg.add_reaction(emote)
self.add_reaction(ctx.guild.id, emote, role.id, channel.id, message_id)
@commands.has_permissions(manage_channels=True)
@reactions.command(description="Removes an existing reaction role.")
async def remove(self, ctx, index: int):
"""Removes an existing reaction role in the current guild. It takes the `index` of the reaction role, which you can see by invoking `reactions`."""
guild_id = ctx.guild.id
data = self.bot.data["reaction_roles"].get(str(guild_id), None)
embed = discord.Embed(title=f"Remove Reaction Role {index}")
rr = None
if data is None:
embed.description = "Given Reaction Role was not found."
else:
embed.description = (
"Do you wish to remove the reaction role below? Please react with 🗑️."
)
rr = data[index]
emote = rr.get("emote")
role_id = rr.get("roleID")
role = ctx.guild.get_role(role_id)
channel_id = rr.get("channelID")
message_id = rr.get("messageID")
_id = rr.get("id")
embed.set_footer(text=_id)
embed.add_field(
name=index,
value=f"{emote} - @{role} - [message](https://www.discord.com/channels/{guild_id}/{channel_id}/{message_id})",
inline=False,
)
msg = await ctx.send(embed=embed)
if rr is not None:
await msg.add_reaction("🗑️")
def check(reaction, user):
return (
reaction.message.id == msg.id
and user == ctx.message.author
and str(reaction.emoji) == "🗑️"
)
try:
reaction, user = await self.bot.wait_for(
"reaction_add", check=check, timeout=15
)
data.remove(rr)
embed = discord.Embed(title="Ok. Deleted.🗑️")
except TimeoutError:
embed = discord.Embed(title="Timed out...")
finally:
await msg.clear_reactions()
await msg.edit(embed=embed)
self.bot.data["reaction_roles"][str(guild_id)] = data
if self.bot.data["reaction_roles"][str(guild_id)] == []:
del self.bot.data["reaction_roles"][str(guild_id)]
def add_reaction(
self, guild_id, emote: discord.Emoji, role_id, channel_id, message_id
):
if not str(guild_id) in self.bot.data["reaction_roles"]:
self.bot.data["reaction_roles"][str(guild_id)] = []
self.bot.data["reaction_roles"][str(guild_id)].append(
{
"id": str(uuid.uuid4()),
"emote": emote,
"roleID": int(role_id),
"channelID": int(channel_id),
"messageID": int(message_id),
}
)
async def setup(bot):
await bot.add_cog(ReactionRoles(bot))
| 3,022 | 4,391 | 46 |
b9b0d2d749d7f06828ccc393051a07753c0cb316 | 873 | py | Python | resolwe/storage/migrations/0003_add_hash_fields_to_referenced_path.py | plojyon/resolwe | 1bee6f0860fdd087534adf1680e9350d79ab97cf | [
"Apache-2.0"
] | 27 | 2015-12-07T18:29:12.000Z | 2022-03-16T08:01:47.000Z | resolwe/storage/migrations/0003_add_hash_fields_to_referenced_path.py | plojyon/resolwe | 1bee6f0860fdd087534adf1680e9350d79ab97cf | [
"Apache-2.0"
] | 681 | 2015-12-01T11:52:24.000Z | 2022-03-21T07:43:37.000Z | resolwe/storage/migrations/0003_add_hash_fields_to_referenced_path.py | plojyon/resolwe | 1bee6f0860fdd087534adf1680e9350d79ab97cf | [
"Apache-2.0"
] | 28 | 2015-12-01T08:32:57.000Z | 2021-12-14T00:04:16.000Z | # Generated by Django 2.2.10 on 2020-05-12 08:44
from django.db import migrations, models
| 29.1 | 67 | 0.584192 | # Generated by Django 2.2.10 on 2020-05-12 08:44
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
("storage", "0002_create_filestorage_objects"),
]
operations = [
migrations.AddField(
model_name="referencedpath",
name="awss3etag",
field=models.CharField(default="etag", max_length=50),
preserve_default=False,
),
migrations.AddField(
model_name="referencedpath",
name="crc32c",
field=models.CharField(default="crc32c", max_length=8),
preserve_default=False,
),
migrations.AddField(
model_name="referencedpath",
name="md5",
field=models.CharField(default="md5", max_length=32),
preserve_default=False,
),
]
| 0 | 759 | 23 |
cdf13f358d62a975add6fa1a1a8f513e3bc9a083 | 721 | py | Python | python/obra_hacks/api/notifications.py | brandond/obra-hacks | df451c6c6cd78b48f6e32bbd102a8e8a6bd77cb3 | [
"Apache-2.0"
] | null | null | null | python/obra_hacks/api/notifications.py | brandond/obra-hacks | df451c6c6cd78b48f6e32bbd102a8e8a6bd77cb3 | [
"Apache-2.0"
] | null | null | null | python/obra_hacks/api/notifications.py | brandond/obra-hacks | df451c6c6cd78b48f6e32bbd102a8e8a6bd77cb3 | [
"Apache-2.0"
] | null | null | null | import logging
from flask_restx import Resource, fields, marshal
logger = logging.getLogger(__name__)
| 31.347826 | 94 | 0.676838 | import logging
from flask_restx import Resource, fields, marshal
logger = logging.getLogger(__name__)
def register(api, cache):
# TODO - how am I going to store PushSubscription data now that there's no subscriptionId?
# Now need some way to store it as part of session data or something, but I don't want
# to require registration...
ns = api.namespace('notifications', 'Push Notifications')
response = fields.Integer
@ns.route('/')
@ns.response(200, 'Success', response)
@ns.response(400, 'Bad Request')
@ns.response(500, 'Server Error')
class People(Resource):
def get(self):
return (marshal(1, response), 200, {'Cache-Control': 'no-cache, no-store'})
| 593 | 0 | 23 |
b3513cea9894cb7e4c95248d55641576df739084 | 248 | py | Python | Algorithms/Maximum subarray sum/kadane_algorithm.py | NixonZ/Code_Chef | 5bffb7c1f88e2754b31d724158f684dc2c91089b | [
"Apache-2.0"
] | null | null | null | Algorithms/Maximum subarray sum/kadane_algorithm.py | NixonZ/Code_Chef | 5bffb7c1f88e2754b31d724158f684dc2c91089b | [
"Apache-2.0"
] | null | null | null | Algorithms/Maximum subarray sum/kadane_algorithm.py | NixonZ/Code_Chef | 5bffb7c1f88e2754b31d724158f684dc2c91089b | [
"Apache-2.0"
] | null | null | null | A=[]
print("Enter array(exit to end)")
while 1:
x=input()
if x=='exit':
break
A.append(int(x))
best=0
tempsum=0
for x in A:
tempsum=max(tempsum+x,x)
best=max(best,tempsum)
print("Max sum="+str(best))
#complexity is O(n)
| 16.533333 | 33 | 0.600806 | A=[]
print("Enter array(exit to end)")
while 1:
x=input()
if x=='exit':
break
A.append(int(x))
best=0
tempsum=0
for x in A:
tempsum=max(tempsum+x,x)
best=max(best,tempsum)
print("Max sum="+str(best))
#complexity is O(n)
| 0 | 0 | 0 |
5e5e6c82330a2dbaa87e433940128835c33604c1 | 42,593 | py | Python | sdk/python/pulumi_google_native/deploymentmanager/v2/outputs.py | AaronFriel/pulumi-google-native | 75d1cda425e33d4610348972cd70bddf35f1770d | [
"Apache-2.0"
] | 44 | 2021-04-18T23:00:48.000Z | 2022-02-14T17:43:15.000Z | sdk/python/pulumi_google_native/deploymentmanager/v2/outputs.py | AaronFriel/pulumi-google-native | 75d1cda425e33d4610348972cd70bddf35f1770d | [
"Apache-2.0"
] | 354 | 2021-04-16T16:48:39.000Z | 2022-03-31T17:16:39.000Z | sdk/python/pulumi_google_native/deploymentmanager/v2/outputs.py | AaronFriel/pulumi-google-native | 75d1cda425e33d4610348972cd70bddf35f1770d | [
"Apache-2.0"
] | 8 | 2021-04-24T17:46:51.000Z | 2022-01-05T10:40:21.000Z | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
from . import outputs
from ._enums import *
__all__ = [
'AuditConfigResponse',
'AuditLogConfigResponse',
'BindingResponse',
'ConfigFileResponse',
'DeploymentLabelEntryResponse',
'DeploymentUpdateLabelEntryResponse',
'DeploymentUpdateResponse',
'ExprResponse',
'ImportFileResponse',
'OperationErrorErrorsItemResponse',
'OperationErrorResponse',
'OperationResponse',
'OperationWarningsItemDataItemResponse',
'OperationWarningsItemResponse',
'TargetConfigurationResponse',
]
@pulumi.output_type
class AuditConfigResponse(dict):
"""
Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.
"""
@staticmethod
def __init__(__self__, *,
audit_log_configs: Sequence['outputs.AuditLogConfigResponse'],
service: str):
"""
Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.
:param Sequence['AuditLogConfigResponse'] audit_log_configs: The configuration for logging of each type of permission.
:param str service: Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.
"""
pulumi.set(__self__, "audit_log_configs", audit_log_configs)
pulumi.set(__self__, "service", service)
@property
@pulumi.getter(name="auditLogConfigs")
def audit_log_configs(self) -> Sequence['outputs.AuditLogConfigResponse']:
"""
The configuration for logging of each type of permission.
"""
return pulumi.get(self, "audit_log_configs")
@property
@pulumi.getter
def service(self) -> str:
"""
Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.
"""
return pulumi.get(self, "service")
@pulumi.output_type
class AuditLogConfigResponse(dict):
"""
Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.
"""
@staticmethod
def __init__(__self__, *,
exempted_members: Sequence[str],
log_type: str):
"""
Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.
:param Sequence[str] exempted_members: Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.
:param str log_type: The log type that this config enables.
"""
pulumi.set(__self__, "exempted_members", exempted_members)
pulumi.set(__self__, "log_type", log_type)
@property
@pulumi.getter(name="exemptedMembers")
def exempted_members(self) -> Sequence[str]:
"""
Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.
"""
return pulumi.get(self, "exempted_members")
@property
@pulumi.getter(name="logType")
def log_type(self) -> str:
"""
The log type that this config enables.
"""
return pulumi.get(self, "log_type")
@pulumi.output_type
class BindingResponse(dict):
"""
Associates `members`, or principals, with a `role`.
"""
def __init__(__self__, *,
condition: 'outputs.ExprResponse',
members: Sequence[str],
role: str):
"""
Associates `members`, or principals, with a `role`.
:param 'ExprResponse' condition: The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
:param Sequence[str] members: Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.
:param str role: Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
"""
pulumi.set(__self__, "condition", condition)
pulumi.set(__self__, "members", members)
pulumi.set(__self__, "role", role)
@property
@pulumi.getter
def condition(self) -> 'outputs.ExprResponse':
"""
The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
"""
return pulumi.get(self, "condition")
@property
@pulumi.getter
def members(self) -> Sequence[str]:
"""
Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.
"""
return pulumi.get(self, "members")
@property
@pulumi.getter
def role(self) -> str:
"""
Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
"""
return pulumi.get(self, "role")
@pulumi.output_type
@pulumi.output_type
class DeploymentLabelEntryResponse(dict):
"""
Label object for Deployments
"""
def __init__(__self__, *,
key: str,
value: str):
"""
Label object for Deployments
:param str key: Key of the label
:param str value: Value of the label
"""
pulumi.set(__self__, "key", key)
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def key(self) -> str:
"""
Key of the label
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> str:
"""
Value of the label
"""
return pulumi.get(self, "value")
@pulumi.output_type
class DeploymentUpdateLabelEntryResponse(dict):
"""
Label object for DeploymentUpdate
"""
def __init__(__self__, *,
key: str,
value: str):
"""
Label object for DeploymentUpdate
:param str key: Key of the label
:param str value: Value of the label
"""
pulumi.set(__self__, "key", key)
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def key(self) -> str:
"""
Key of the label
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> str:
"""
Value of the label
"""
return pulumi.get(self, "value")
@pulumi.output_type
@pulumi.output_type
class ExprResponse(dict):
"""
Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.
"""
def __init__(__self__, *,
description: str,
expression: str,
location: str,
title: str):
"""
Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.
:param str description: Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
:param str expression: Textual representation of an expression in Common Expression Language syntax.
:param str location: Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
:param str title: Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
"""
pulumi.set(__self__, "description", description)
pulumi.set(__self__, "expression", expression)
pulumi.set(__self__, "location", location)
pulumi.set(__self__, "title", title)
@property
@pulumi.getter
def description(self) -> str:
"""
Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
"""
return pulumi.get(self, "description")
@property
@pulumi.getter
def expression(self) -> str:
"""
Textual representation of an expression in Common Expression Language syntax.
"""
return pulumi.get(self, "expression")
@property
@pulumi.getter
def location(self) -> str:
"""
Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
"""
return pulumi.get(self, "location")
@property
@pulumi.getter
def title(self) -> str:
"""
Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
"""
return pulumi.get(self, "title")
@pulumi.output_type
@pulumi.output_type
@pulumi.output_type
class OperationErrorResponse(dict):
"""
[Output Only] If errors are generated during processing of the operation, this field will be populated.
"""
def __init__(__self__, *,
errors: Sequence['outputs.OperationErrorErrorsItemResponse']):
"""
[Output Only] If errors are generated during processing of the operation, this field will be populated.
:param Sequence['OperationErrorErrorsItemResponse'] errors: The array of errors encountered while processing this operation.
"""
pulumi.set(__self__, "errors", errors)
@property
@pulumi.getter
def errors(self) -> Sequence['outputs.OperationErrorErrorsItemResponse']:
"""
The array of errors encountered while processing this operation.
"""
return pulumi.get(self, "errors")
@pulumi.output_type
class OperationResponse(dict):
"""
Represents an Operation resource. Google Compute Engine has three Operation resources: * [Global](/compute/docs/reference/rest/{$api_version}/globalOperations) * [Regional](/compute/docs/reference/rest/{$api_version}/regionOperations) * [Zonal](/compute/docs/reference/rest/{$api_version}/zoneOperations) You can use an operation resource to manage asynchronous API requests. For more information, read Handling API responses. Operations can be global, regional or zonal. - For global operations, use the `globalOperations` resource. - For regional operations, use the `regionOperations` resource. - For zonal operations, use the `zonalOperations` resource. For more information, read Global, Regional, and Zonal Resources.
"""
@staticmethod
def __init__(__self__, *,
client_operation_id: str,
description: str,
end_time: str,
error: 'outputs.OperationErrorResponse',
http_error_message: str,
http_error_status_code: int,
insert_time: str,
kind: str,
name: str,
operation_group_id: str,
operation_type: str,
progress: int,
region: str,
self_link: str,
start_time: str,
status: str,
status_message: str,
target_id: str,
target_link: str,
user: str,
warnings: Sequence['outputs.OperationWarningsItemResponse'],
zone: str):
"""
Represents an Operation resource. Google Compute Engine has three Operation resources: * [Global](/compute/docs/reference/rest/{$api_version}/globalOperations) * [Regional](/compute/docs/reference/rest/{$api_version}/regionOperations) * [Zonal](/compute/docs/reference/rest/{$api_version}/zoneOperations) You can use an operation resource to manage asynchronous API requests. For more information, read Handling API responses. Operations can be global, regional or zonal. - For global operations, use the `globalOperations` resource. - For regional operations, use the `regionOperations` resource. - For zonal operations, use the `zonalOperations` resource. For more information, read Global, Regional, and Zonal Resources.
:param str client_operation_id: The value of `requestId` if you provided it in the request. Not present otherwise.
:param str description: A textual description of the operation, which is set when the operation is created.
:param str end_time: The time that this operation was completed. This value is in RFC3339 text format.
:param 'OperationErrorResponse' error: If errors are generated during processing of the operation, this field will be populated.
:param str http_error_message: If the operation fails, this field contains the HTTP error message that was returned, such as `NOT FOUND`.
:param int http_error_status_code: If the operation fails, this field contains the HTTP error status code that was returned. For example, a `404` means the resource was not found.
:param str insert_time: The time that this operation was requested. This value is in RFC3339 text format.
:param str kind: Type of the resource. Always `compute#operation` for Operation resources.
:param str name: Name of the operation.
:param str operation_group_id: An ID that represents a group of operations, such as when a group of operations results from a `bulkInsert` API request.
:param str operation_type: The type of operation, such as `insert`, `update`, or `delete`, and so on.
:param int progress: An optional progress indicator that ranges from 0 to 100. There is no requirement that this be linear or support any granularity of operations. This should not be used to guess when the operation will be complete. This number should monotonically increase as the operation progresses.
:param str region: The URL of the region where the operation resides. Only applicable when performing regional operations.
:param str self_link: Server-defined URL for the resource.
:param str start_time: The time that this operation was started by the server. This value is in RFC3339 text format.
:param str status: The status of the operation, which can be one of the following: `PENDING`, `RUNNING`, or `DONE`.
:param str status_message: An optional textual description of the current status of the operation.
:param str target_id: The unique target ID, which identifies a specific incarnation of the target resource.
:param str target_link: The URL of the resource that the operation modifies. For operations related to creating a snapshot, this points to the persistent disk that the snapshot was created from.
:param str user: User who requested the operation, for example: `user@example.com`.
:param Sequence['OperationWarningsItemResponse'] warnings: If warning messages are generated during processing of the operation, this field will be populated.
:param str zone: The URL of the zone where the operation resides. Only applicable when performing per-zone operations.
"""
pulumi.set(__self__, "client_operation_id", client_operation_id)
pulumi.set(__self__, "description", description)
pulumi.set(__self__, "end_time", end_time)
pulumi.set(__self__, "error", error)
pulumi.set(__self__, "http_error_message", http_error_message)
pulumi.set(__self__, "http_error_status_code", http_error_status_code)
pulumi.set(__self__, "insert_time", insert_time)
pulumi.set(__self__, "kind", kind)
pulumi.set(__self__, "name", name)
pulumi.set(__self__, "operation_group_id", operation_group_id)
pulumi.set(__self__, "operation_type", operation_type)
pulumi.set(__self__, "progress", progress)
pulumi.set(__self__, "region", region)
pulumi.set(__self__, "self_link", self_link)
pulumi.set(__self__, "start_time", start_time)
pulumi.set(__self__, "status", status)
pulumi.set(__self__, "status_message", status_message)
pulumi.set(__self__, "target_id", target_id)
pulumi.set(__self__, "target_link", target_link)
pulumi.set(__self__, "user", user)
pulumi.set(__self__, "warnings", warnings)
pulumi.set(__self__, "zone", zone)
@property
@pulumi.getter(name="clientOperationId")
def client_operation_id(self) -> str:
"""
The value of `requestId` if you provided it in the request. Not present otherwise.
"""
return pulumi.get(self, "client_operation_id")
@property
@pulumi.getter
def description(self) -> str:
"""
A textual description of the operation, which is set when the operation is created.
"""
return pulumi.get(self, "description")
@property
@pulumi.getter(name="endTime")
def end_time(self) -> str:
"""
The time that this operation was completed. This value is in RFC3339 text format.
"""
return pulumi.get(self, "end_time")
@property
@pulumi.getter
def error(self) -> 'outputs.OperationErrorResponse':
"""
If errors are generated during processing of the operation, this field will be populated.
"""
return pulumi.get(self, "error")
@property
@pulumi.getter(name="httpErrorMessage")
def http_error_message(self) -> str:
"""
If the operation fails, this field contains the HTTP error message that was returned, such as `NOT FOUND`.
"""
return pulumi.get(self, "http_error_message")
@property
@pulumi.getter(name="httpErrorStatusCode")
def http_error_status_code(self) -> int:
"""
If the operation fails, this field contains the HTTP error status code that was returned. For example, a `404` means the resource was not found.
"""
return pulumi.get(self, "http_error_status_code")
@property
@pulumi.getter(name="insertTime")
def insert_time(self) -> str:
"""
The time that this operation was requested. This value is in RFC3339 text format.
"""
return pulumi.get(self, "insert_time")
@property
@pulumi.getter
def kind(self) -> str:
"""
Type of the resource. Always `compute#operation` for Operation resources.
"""
return pulumi.get(self, "kind")
@property
@pulumi.getter
def name(self) -> str:
"""
Name of the operation.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="operationGroupId")
def operation_group_id(self) -> str:
"""
An ID that represents a group of operations, such as when a group of operations results from a `bulkInsert` API request.
"""
return pulumi.get(self, "operation_group_id")
@property
@pulumi.getter(name="operationType")
def operation_type(self) -> str:
"""
The type of operation, such as `insert`, `update`, or `delete`, and so on.
"""
return pulumi.get(self, "operation_type")
@property
@pulumi.getter
def progress(self) -> int:
"""
An optional progress indicator that ranges from 0 to 100. There is no requirement that this be linear or support any granularity of operations. This should not be used to guess when the operation will be complete. This number should monotonically increase as the operation progresses.
"""
return pulumi.get(self, "progress")
@property
@pulumi.getter
def region(self) -> str:
"""
The URL of the region where the operation resides. Only applicable when performing regional operations.
"""
return pulumi.get(self, "region")
@property
@pulumi.getter(name="selfLink")
def self_link(self) -> str:
"""
Server-defined URL for the resource.
"""
return pulumi.get(self, "self_link")
@property
@pulumi.getter(name="startTime")
def start_time(self) -> str:
"""
The time that this operation was started by the server. This value is in RFC3339 text format.
"""
return pulumi.get(self, "start_time")
@property
@pulumi.getter
def status(self) -> str:
"""
The status of the operation, which can be one of the following: `PENDING`, `RUNNING`, or `DONE`.
"""
return pulumi.get(self, "status")
@property
@pulumi.getter(name="statusMessage")
def status_message(self) -> str:
"""
An optional textual description of the current status of the operation.
"""
return pulumi.get(self, "status_message")
@property
@pulumi.getter(name="targetId")
def target_id(self) -> str:
"""
The unique target ID, which identifies a specific incarnation of the target resource.
"""
return pulumi.get(self, "target_id")
@property
@pulumi.getter(name="targetLink")
def target_link(self) -> str:
"""
The URL of the resource that the operation modifies. For operations related to creating a snapshot, this points to the persistent disk that the snapshot was created from.
"""
return pulumi.get(self, "target_link")
@property
@pulumi.getter
def user(self) -> str:
"""
User who requested the operation, for example: `user@example.com`.
"""
return pulumi.get(self, "user")
@property
@pulumi.getter
def warnings(self) -> Sequence['outputs.OperationWarningsItemResponse']:
"""
If warning messages are generated during processing of the operation, this field will be populated.
"""
return pulumi.get(self, "warnings")
@property
@pulumi.getter
def zone(self) -> str:
"""
The URL of the zone where the operation resides. Only applicable when performing per-zone operations.
"""
return pulumi.get(self, "zone")
@pulumi.output_type
@pulumi.output_type
@pulumi.output_type
| 50.887694 | 1,947 | 0.672012 | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
from . import outputs
from ._enums import *
__all__ = [
'AuditConfigResponse',
'AuditLogConfigResponse',
'BindingResponse',
'ConfigFileResponse',
'DeploymentLabelEntryResponse',
'DeploymentUpdateLabelEntryResponse',
'DeploymentUpdateResponse',
'ExprResponse',
'ImportFileResponse',
'OperationErrorErrorsItemResponse',
'OperationErrorResponse',
'OperationResponse',
'OperationWarningsItemDataItemResponse',
'OperationWarningsItemResponse',
'TargetConfigurationResponse',
]
@pulumi.output_type
class AuditConfigResponse(dict):
"""
Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.
"""
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "auditLogConfigs":
suggest = "audit_log_configs"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in AuditConfigResponse. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
AuditConfigResponse.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
AuditConfigResponse.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
audit_log_configs: Sequence['outputs.AuditLogConfigResponse'],
service: str):
"""
Specifies the audit configuration for a service. The configuration determines which permission types are logged, and what identities, if any, are exempted from logging. An AuditConfig must have one or more AuditLogConfigs. If there are AuditConfigs for both `allServices` and a specific service, the union of the two AuditConfigs is used for that service: the log_types specified in each AuditConfig are enabled, and the exempted_members in each AuditLogConfig are exempted. Example Policy with multiple AuditConfigs: { "audit_configs": [ { "service": "allServices", "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" }, { "log_type": "ADMIN_READ" } ] }, { "service": "sampleservice.googleapis.com", "audit_log_configs": [ { "log_type": "DATA_READ" }, { "log_type": "DATA_WRITE", "exempted_members": [ "user:aliya@example.com" ] } ] } ] } For sampleservice, this policy enables DATA_READ, DATA_WRITE and ADMIN_READ logging. It also exempts jose@example.com from DATA_READ logging, and aliya@example.com from DATA_WRITE logging.
:param Sequence['AuditLogConfigResponse'] audit_log_configs: The configuration for logging of each type of permission.
:param str service: Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.
"""
pulumi.set(__self__, "audit_log_configs", audit_log_configs)
pulumi.set(__self__, "service", service)
@property
@pulumi.getter(name="auditLogConfigs")
def audit_log_configs(self) -> Sequence['outputs.AuditLogConfigResponse']:
"""
The configuration for logging of each type of permission.
"""
return pulumi.get(self, "audit_log_configs")
@property
@pulumi.getter
def service(self) -> str:
"""
Specifies a service that will be enabled for audit logging. For example, `storage.googleapis.com`, `cloudsql.googleapis.com`. `allServices` is a special value that covers all services.
"""
return pulumi.get(self, "service")
@pulumi.output_type
class AuditLogConfigResponse(dict):
"""
Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.
"""
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "exemptedMembers":
suggest = "exempted_members"
elif key == "logType":
suggest = "log_type"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in AuditLogConfigResponse. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
AuditLogConfigResponse.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
AuditLogConfigResponse.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
exempted_members: Sequence[str],
log_type: str):
"""
Provides the configuration for logging a type of permissions. Example: { "audit_log_configs": [ { "log_type": "DATA_READ", "exempted_members": [ "user:jose@example.com" ] }, { "log_type": "DATA_WRITE" } ] } This enables 'DATA_READ' and 'DATA_WRITE' logging, while exempting jose@example.com from DATA_READ logging.
:param Sequence[str] exempted_members: Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.
:param str log_type: The log type that this config enables.
"""
pulumi.set(__self__, "exempted_members", exempted_members)
pulumi.set(__self__, "log_type", log_type)
@property
@pulumi.getter(name="exemptedMembers")
def exempted_members(self) -> Sequence[str]:
"""
Specifies the identities that do not cause logging for this type of permission. Follows the same format of Binding.members.
"""
return pulumi.get(self, "exempted_members")
@property
@pulumi.getter(name="logType")
def log_type(self) -> str:
"""
The log type that this config enables.
"""
return pulumi.get(self, "log_type")
@pulumi.output_type
class BindingResponse(dict):
"""
Associates `members`, or principals, with a `role`.
"""
def __init__(__self__, *,
condition: 'outputs.ExprResponse',
members: Sequence[str],
role: str):
"""
Associates `members`, or principals, with a `role`.
:param 'ExprResponse' condition: The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
:param Sequence[str] members: Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.
:param str role: Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
"""
pulumi.set(__self__, "condition", condition)
pulumi.set(__self__, "members", members)
pulumi.set(__self__, "role", role)
@property
@pulumi.getter
def condition(self) -> 'outputs.ExprResponse':
"""
The condition that is associated with this binding. If the condition evaluates to `true`, then this binding applies to the current request. If the condition evaluates to `false`, then this binding does not apply to the current request. However, a different role binding might grant the same role to one or more of the principals in this binding. To learn which resources support conditions in their IAM policies, see the [IAM documentation](https://cloud.google.com/iam/help/conditions/resource-policies).
"""
return pulumi.get(self, "condition")
@property
@pulumi.getter
def members(self) -> Sequence[str]:
"""
Specifies the principals requesting access for a Cloud Platform resource. `members` can have the following values: * `allUsers`: A special identifier that represents anyone who is on the internet; with or without a Google account. * `allAuthenticatedUsers`: A special identifier that represents anyone who is authenticated with a Google account or a service account. * `user:{emailid}`: An email address that represents a specific Google account. For example, `alice@example.com` . * `serviceAccount:{emailid}`: An email address that represents a service account. For example, `my-other-app@appspot.gserviceaccount.com`. * `group:{emailid}`: An email address that represents a Google group. For example, `admins@example.com`. * `deleted:user:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a user that has been recently deleted. For example, `alice@example.com?uid=123456789012345678901`. If the user is recovered, this value reverts to `user:{emailid}` and the recovered user retains the role in the binding. * `deleted:serviceAccount:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a service account that has been recently deleted. For example, `my-other-app@appspot.gserviceaccount.com?uid=123456789012345678901`. If the service account is undeleted, this value reverts to `serviceAccount:{emailid}` and the undeleted service account retains the role in the binding. * `deleted:group:{emailid}?uid={uniqueid}`: An email address (plus unique identifier) representing a Google group that has been recently deleted. For example, `admins@example.com?uid=123456789012345678901`. If the group is recovered, this value reverts to `group:{emailid}` and the recovered group retains the role in the binding. * `domain:{domain}`: The G Suite domain (primary) that represents all the users of that domain. For example, `google.com` or `example.com`.
"""
return pulumi.get(self, "members")
@property
@pulumi.getter
def role(self) -> str:
"""
Role that is assigned to the list of `members`, or principals. For example, `roles/viewer`, `roles/editor`, or `roles/owner`.
"""
return pulumi.get(self, "role")
@pulumi.output_type
class ConfigFileResponse(dict):
def __init__(__self__, *,
content: str):
"""
:param str content: The contents of the file.
"""
pulumi.set(__self__, "content", content)
@property
@pulumi.getter
def content(self) -> str:
"""
The contents of the file.
"""
return pulumi.get(self, "content")
@pulumi.output_type
class DeploymentLabelEntryResponse(dict):
"""
Label object for Deployments
"""
def __init__(__self__, *,
key: str,
value: str):
"""
Label object for Deployments
:param str key: Key of the label
:param str value: Value of the label
"""
pulumi.set(__self__, "key", key)
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def key(self) -> str:
"""
Key of the label
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> str:
"""
Value of the label
"""
return pulumi.get(self, "value")
@pulumi.output_type
class DeploymentUpdateLabelEntryResponse(dict):
"""
Label object for DeploymentUpdate
"""
def __init__(__self__, *,
key: str,
value: str):
"""
Label object for DeploymentUpdate
:param str key: Key of the label
:param str value: Value of the label
"""
pulumi.set(__self__, "key", key)
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def key(self) -> str:
"""
Key of the label
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> str:
"""
Value of the label
"""
return pulumi.get(self, "value")
@pulumi.output_type
class DeploymentUpdateResponse(dict):
def __init__(__self__, *,
description: str,
labels: Sequence['outputs.DeploymentUpdateLabelEntryResponse'],
manifest: str):
"""
:param str description: An optional user-provided description of the deployment after the current update has been applied.
:param Sequence['DeploymentUpdateLabelEntryResponse'] labels: Map of One Platform labels; provided by the client when the resource is created or updated. Specifically: Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?` Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`.
:param str manifest: URL of the manifest representing the update configuration of this deployment.
"""
pulumi.set(__self__, "description", description)
pulumi.set(__self__, "labels", labels)
pulumi.set(__self__, "manifest", manifest)
@property
@pulumi.getter
def description(self) -> str:
"""
An optional user-provided description of the deployment after the current update has been applied.
"""
return pulumi.get(self, "description")
@property
@pulumi.getter
def labels(self) -> Sequence['outputs.DeploymentUpdateLabelEntryResponse']:
"""
Map of One Platform labels; provided by the client when the resource is created or updated. Specifically: Label keys must be between 1 and 63 characters long and must conform to the following regular expression: `[a-z]([-a-z0-9]*[a-z0-9])?` Label values must be between 0 and 63 characters long and must conform to the regular expression `([a-z]([-a-z0-9]*[a-z0-9])?)?`.
"""
return pulumi.get(self, "labels")
@property
@pulumi.getter
def manifest(self) -> str:
"""
URL of the manifest representing the update configuration of this deployment.
"""
return pulumi.get(self, "manifest")
@pulumi.output_type
class ExprResponse(dict):
"""
Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.
"""
def __init__(__self__, *,
description: str,
expression: str,
location: str,
title: str):
"""
Represents a textual expression in the Common Expression Language (CEL) syntax. CEL is a C-like expression language. The syntax and semantics of CEL are documented at https://github.com/google/cel-spec. Example (Comparison): title: "Summary size limit" description: "Determines if a summary is less than 100 chars" expression: "document.summary.size() < 100" Example (Equality): title: "Requestor is owner" description: "Determines if requestor is the document owner" expression: "document.owner == request.auth.claims.email" Example (Logic): title: "Public documents" description: "Determine whether the document should be publicly visible" expression: "document.type != 'private' && document.type != 'internal'" Example (Data Manipulation): title: "Notification string" description: "Create a notification string with a timestamp." expression: "'New message received at ' + string(document.create_time)" The exact variables and functions that may be referenced within an expression are determined by the service that evaluates it. See the service documentation for additional information.
:param str description: Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
:param str expression: Textual representation of an expression in Common Expression Language syntax.
:param str location: Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
:param str title: Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
"""
pulumi.set(__self__, "description", description)
pulumi.set(__self__, "expression", expression)
pulumi.set(__self__, "location", location)
pulumi.set(__self__, "title", title)
@property
@pulumi.getter
def description(self) -> str:
"""
Optional. Description of the expression. This is a longer text which describes the expression, e.g. when hovered over it in a UI.
"""
return pulumi.get(self, "description")
@property
@pulumi.getter
def expression(self) -> str:
"""
Textual representation of an expression in Common Expression Language syntax.
"""
return pulumi.get(self, "expression")
@property
@pulumi.getter
def location(self) -> str:
"""
Optional. String indicating the location of the expression for error reporting, e.g. a file name and a position in the file.
"""
return pulumi.get(self, "location")
@property
@pulumi.getter
def title(self) -> str:
"""
Optional. Title for the expression, i.e. a short string describing its purpose. This can be used e.g. in UIs which allow to enter the expression.
"""
return pulumi.get(self, "title")
@pulumi.output_type
class ImportFileResponse(dict):
def __init__(__self__, *,
content: str,
name: str):
"""
:param str content: The contents of the file.
:param str name: The name of the file.
"""
pulumi.set(__self__, "content", content)
pulumi.set(__self__, "name", name)
@property
@pulumi.getter
def content(self) -> str:
"""
The contents of the file.
"""
return pulumi.get(self, "content")
@property
@pulumi.getter
def name(self) -> str:
"""
The name of the file.
"""
return pulumi.get(self, "name")
@pulumi.output_type
class OperationErrorErrorsItemResponse(dict):
def __init__(__self__, *,
code: str,
location: str,
message: str):
"""
:param str code: The error type identifier for this error.
:param str location: Indicates the field in the request that caused the error. This property is optional.
:param str message: An optional, human-readable error message.
"""
pulumi.set(__self__, "code", code)
pulumi.set(__self__, "location", location)
pulumi.set(__self__, "message", message)
@property
@pulumi.getter
def code(self) -> str:
"""
The error type identifier for this error.
"""
return pulumi.get(self, "code")
@property
@pulumi.getter
def location(self) -> str:
"""
Indicates the field in the request that caused the error. This property is optional.
"""
return pulumi.get(self, "location")
@property
@pulumi.getter
def message(self) -> str:
"""
An optional, human-readable error message.
"""
return pulumi.get(self, "message")
@pulumi.output_type
class OperationErrorResponse(dict):
"""
[Output Only] If errors are generated during processing of the operation, this field will be populated.
"""
def __init__(__self__, *,
errors: Sequence['outputs.OperationErrorErrorsItemResponse']):
"""
[Output Only] If errors are generated during processing of the operation, this field will be populated.
:param Sequence['OperationErrorErrorsItemResponse'] errors: The array of errors encountered while processing this operation.
"""
pulumi.set(__self__, "errors", errors)
@property
@pulumi.getter
def errors(self) -> Sequence['outputs.OperationErrorErrorsItemResponse']:
"""
The array of errors encountered while processing this operation.
"""
return pulumi.get(self, "errors")
@pulumi.output_type
class OperationResponse(dict):
"""
Represents an Operation resource. Google Compute Engine has three Operation resources: * [Global](/compute/docs/reference/rest/{$api_version}/globalOperations) * [Regional](/compute/docs/reference/rest/{$api_version}/regionOperations) * [Zonal](/compute/docs/reference/rest/{$api_version}/zoneOperations) You can use an operation resource to manage asynchronous API requests. For more information, read Handling API responses. Operations can be global, regional or zonal. - For global operations, use the `globalOperations` resource. - For regional operations, use the `regionOperations` resource. - For zonal operations, use the `zonalOperations` resource. For more information, read Global, Regional, and Zonal Resources.
"""
@staticmethod
def __key_warning(key: str):
suggest = None
if key == "clientOperationId":
suggest = "client_operation_id"
elif key == "endTime":
suggest = "end_time"
elif key == "httpErrorMessage":
suggest = "http_error_message"
elif key == "httpErrorStatusCode":
suggest = "http_error_status_code"
elif key == "insertTime":
suggest = "insert_time"
elif key == "operationGroupId":
suggest = "operation_group_id"
elif key == "operationType":
suggest = "operation_type"
elif key == "selfLink":
suggest = "self_link"
elif key == "startTime":
suggest = "start_time"
elif key == "statusMessage":
suggest = "status_message"
elif key == "targetId":
suggest = "target_id"
elif key == "targetLink":
suggest = "target_link"
if suggest:
pulumi.log.warn(f"Key '{key}' not found in OperationResponse. Access the value via the '{suggest}' property getter instead.")
def __getitem__(self, key: str) -> Any:
OperationResponse.__key_warning(key)
return super().__getitem__(key)
def get(self, key: str, default = None) -> Any:
OperationResponse.__key_warning(key)
return super().get(key, default)
def __init__(__self__, *,
client_operation_id: str,
description: str,
end_time: str,
error: 'outputs.OperationErrorResponse',
http_error_message: str,
http_error_status_code: int,
insert_time: str,
kind: str,
name: str,
operation_group_id: str,
operation_type: str,
progress: int,
region: str,
self_link: str,
start_time: str,
status: str,
status_message: str,
target_id: str,
target_link: str,
user: str,
warnings: Sequence['outputs.OperationWarningsItemResponse'],
zone: str):
"""
Represents an Operation resource. Google Compute Engine has three Operation resources: * [Global](/compute/docs/reference/rest/{$api_version}/globalOperations) * [Regional](/compute/docs/reference/rest/{$api_version}/regionOperations) * [Zonal](/compute/docs/reference/rest/{$api_version}/zoneOperations) You can use an operation resource to manage asynchronous API requests. For more information, read Handling API responses. Operations can be global, regional or zonal. - For global operations, use the `globalOperations` resource. - For regional operations, use the `regionOperations` resource. - For zonal operations, use the `zonalOperations` resource. For more information, read Global, Regional, and Zonal Resources.
:param str client_operation_id: The value of `requestId` if you provided it in the request. Not present otherwise.
:param str description: A textual description of the operation, which is set when the operation is created.
:param str end_time: The time that this operation was completed. This value is in RFC3339 text format.
:param 'OperationErrorResponse' error: If errors are generated during processing of the operation, this field will be populated.
:param str http_error_message: If the operation fails, this field contains the HTTP error message that was returned, such as `NOT FOUND`.
:param int http_error_status_code: If the operation fails, this field contains the HTTP error status code that was returned. For example, a `404` means the resource was not found.
:param str insert_time: The time that this operation was requested. This value is in RFC3339 text format.
:param str kind: Type of the resource. Always `compute#operation` for Operation resources.
:param str name: Name of the operation.
:param str operation_group_id: An ID that represents a group of operations, such as when a group of operations results from a `bulkInsert` API request.
:param str operation_type: The type of operation, such as `insert`, `update`, or `delete`, and so on.
:param int progress: An optional progress indicator that ranges from 0 to 100. There is no requirement that this be linear or support any granularity of operations. This should not be used to guess when the operation will be complete. This number should monotonically increase as the operation progresses.
:param str region: The URL of the region where the operation resides. Only applicable when performing regional operations.
:param str self_link: Server-defined URL for the resource.
:param str start_time: The time that this operation was started by the server. This value is in RFC3339 text format.
:param str status: The status of the operation, which can be one of the following: `PENDING`, `RUNNING`, or `DONE`.
:param str status_message: An optional textual description of the current status of the operation.
:param str target_id: The unique target ID, which identifies a specific incarnation of the target resource.
:param str target_link: The URL of the resource that the operation modifies. For operations related to creating a snapshot, this points to the persistent disk that the snapshot was created from.
:param str user: User who requested the operation, for example: `user@example.com`.
:param Sequence['OperationWarningsItemResponse'] warnings: If warning messages are generated during processing of the operation, this field will be populated.
:param str zone: The URL of the zone where the operation resides. Only applicable when performing per-zone operations.
"""
pulumi.set(__self__, "client_operation_id", client_operation_id)
pulumi.set(__self__, "description", description)
pulumi.set(__self__, "end_time", end_time)
pulumi.set(__self__, "error", error)
pulumi.set(__self__, "http_error_message", http_error_message)
pulumi.set(__self__, "http_error_status_code", http_error_status_code)
pulumi.set(__self__, "insert_time", insert_time)
pulumi.set(__self__, "kind", kind)
pulumi.set(__self__, "name", name)
pulumi.set(__self__, "operation_group_id", operation_group_id)
pulumi.set(__self__, "operation_type", operation_type)
pulumi.set(__self__, "progress", progress)
pulumi.set(__self__, "region", region)
pulumi.set(__self__, "self_link", self_link)
pulumi.set(__self__, "start_time", start_time)
pulumi.set(__self__, "status", status)
pulumi.set(__self__, "status_message", status_message)
pulumi.set(__self__, "target_id", target_id)
pulumi.set(__self__, "target_link", target_link)
pulumi.set(__self__, "user", user)
pulumi.set(__self__, "warnings", warnings)
pulumi.set(__self__, "zone", zone)
@property
@pulumi.getter(name="clientOperationId")
def client_operation_id(self) -> str:
"""
The value of `requestId` if you provided it in the request. Not present otherwise.
"""
return pulumi.get(self, "client_operation_id")
@property
@pulumi.getter
def description(self) -> str:
"""
A textual description of the operation, which is set when the operation is created.
"""
return pulumi.get(self, "description")
@property
@pulumi.getter(name="endTime")
def end_time(self) -> str:
"""
The time that this operation was completed. This value is in RFC3339 text format.
"""
return pulumi.get(self, "end_time")
@property
@pulumi.getter
def error(self) -> 'outputs.OperationErrorResponse':
"""
If errors are generated during processing of the operation, this field will be populated.
"""
return pulumi.get(self, "error")
@property
@pulumi.getter(name="httpErrorMessage")
def http_error_message(self) -> str:
"""
If the operation fails, this field contains the HTTP error message that was returned, such as `NOT FOUND`.
"""
return pulumi.get(self, "http_error_message")
@property
@pulumi.getter(name="httpErrorStatusCode")
def http_error_status_code(self) -> int:
"""
If the operation fails, this field contains the HTTP error status code that was returned. For example, a `404` means the resource was not found.
"""
return pulumi.get(self, "http_error_status_code")
@property
@pulumi.getter(name="insertTime")
def insert_time(self) -> str:
"""
The time that this operation was requested. This value is in RFC3339 text format.
"""
return pulumi.get(self, "insert_time")
@property
@pulumi.getter
def kind(self) -> str:
"""
Type of the resource. Always `compute#operation` for Operation resources.
"""
return pulumi.get(self, "kind")
@property
@pulumi.getter
def name(self) -> str:
"""
Name of the operation.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="operationGroupId")
def operation_group_id(self) -> str:
"""
An ID that represents a group of operations, such as when a group of operations results from a `bulkInsert` API request.
"""
return pulumi.get(self, "operation_group_id")
@property
@pulumi.getter(name="operationType")
def operation_type(self) -> str:
"""
The type of operation, such as `insert`, `update`, or `delete`, and so on.
"""
return pulumi.get(self, "operation_type")
@property
@pulumi.getter
def progress(self) -> int:
"""
An optional progress indicator that ranges from 0 to 100. There is no requirement that this be linear or support any granularity of operations. This should not be used to guess when the operation will be complete. This number should monotonically increase as the operation progresses.
"""
return pulumi.get(self, "progress")
@property
@pulumi.getter
def region(self) -> str:
"""
The URL of the region where the operation resides. Only applicable when performing regional operations.
"""
return pulumi.get(self, "region")
@property
@pulumi.getter(name="selfLink")
def self_link(self) -> str:
"""
Server-defined URL for the resource.
"""
return pulumi.get(self, "self_link")
@property
@pulumi.getter(name="startTime")
def start_time(self) -> str:
"""
The time that this operation was started by the server. This value is in RFC3339 text format.
"""
return pulumi.get(self, "start_time")
@property
@pulumi.getter
def status(self) -> str:
"""
The status of the operation, which can be one of the following: `PENDING`, `RUNNING`, or `DONE`.
"""
return pulumi.get(self, "status")
@property
@pulumi.getter(name="statusMessage")
def status_message(self) -> str:
"""
An optional textual description of the current status of the operation.
"""
return pulumi.get(self, "status_message")
@property
@pulumi.getter(name="targetId")
def target_id(self) -> str:
"""
The unique target ID, which identifies a specific incarnation of the target resource.
"""
return pulumi.get(self, "target_id")
@property
@pulumi.getter(name="targetLink")
def target_link(self) -> str:
"""
The URL of the resource that the operation modifies. For operations related to creating a snapshot, this points to the persistent disk that the snapshot was created from.
"""
return pulumi.get(self, "target_link")
@property
@pulumi.getter
def user(self) -> str:
"""
User who requested the operation, for example: `user@example.com`.
"""
return pulumi.get(self, "user")
@property
@pulumi.getter
def warnings(self) -> Sequence['outputs.OperationWarningsItemResponse']:
"""
If warning messages are generated during processing of the operation, this field will be populated.
"""
return pulumi.get(self, "warnings")
@property
@pulumi.getter
def zone(self) -> str:
"""
The URL of the zone where the operation resides. Only applicable when performing per-zone operations.
"""
return pulumi.get(self, "zone")
@pulumi.output_type
class OperationWarningsItemDataItemResponse(dict):
def __init__(__self__, *,
key: str,
value: str):
"""
:param str key: A key that provides more detail on the warning being returned. For example, for warnings where there are no results in a list request for a particular zone, this key might be scope and the key value might be the zone name. Other examples might be a key indicating a deprecated resource and a suggested replacement, or a warning about invalid network settings (for example, if an instance attempts to perform IP forwarding but is not enabled for IP forwarding).
:param str value: A warning data value corresponding to the key.
"""
pulumi.set(__self__, "key", key)
pulumi.set(__self__, "value", value)
@property
@pulumi.getter
def key(self) -> str:
"""
A key that provides more detail on the warning being returned. For example, for warnings where there are no results in a list request for a particular zone, this key might be scope and the key value might be the zone name. Other examples might be a key indicating a deprecated resource and a suggested replacement, or a warning about invalid network settings (for example, if an instance attempts to perform IP forwarding but is not enabled for IP forwarding).
"""
return pulumi.get(self, "key")
@property
@pulumi.getter
def value(self) -> str:
"""
A warning data value corresponding to the key.
"""
return pulumi.get(self, "value")
@pulumi.output_type
class OperationWarningsItemResponse(dict):
def __init__(__self__, *,
code: str,
data: Sequence['outputs.OperationWarningsItemDataItemResponse'],
message: str):
"""
:param str code: A warning code, if applicable. For example, Compute Engine returns NO_RESULTS_ON_PAGE if there are no results in the response.
:param Sequence['OperationWarningsItemDataItemResponse'] data: Metadata about this warning in key: value format. For example: "data": [ { "key": "scope", "value": "zones/us-east1-d" }
:param str message: A human-readable description of the warning code.
"""
pulumi.set(__self__, "code", code)
pulumi.set(__self__, "data", data)
pulumi.set(__self__, "message", message)
@property
@pulumi.getter
def code(self) -> str:
"""
A warning code, if applicable. For example, Compute Engine returns NO_RESULTS_ON_PAGE if there are no results in the response.
"""
return pulumi.get(self, "code")
@property
@pulumi.getter
def data(self) -> Sequence['outputs.OperationWarningsItemDataItemResponse']:
"""
Metadata about this warning in key: value format. For example: "data": [ { "key": "scope", "value": "zones/us-east1-d" }
"""
return pulumi.get(self, "data")
@property
@pulumi.getter
def message(self) -> str:
"""
A human-readable description of the warning code.
"""
return pulumi.get(self, "message")
@pulumi.output_type
class TargetConfigurationResponse(dict):
def __init__(__self__, *,
config: 'outputs.ConfigFileResponse',
imports: Sequence['outputs.ImportFileResponse']):
"""
:param 'ConfigFileResponse' config: The configuration to use for this deployment.
:param Sequence['ImportFileResponse'] imports: Specifies any files to import for this configuration. This can be used to import templates or other files. For example, you might import a text file in order to use the file in a template.
"""
pulumi.set(__self__, "config", config)
pulumi.set(__self__, "imports", imports)
@property
@pulumi.getter
def config(self) -> 'outputs.ConfigFileResponse':
"""
The configuration to use for this deployment.
"""
return pulumi.get(self, "config")
@property
@pulumi.getter
def imports(self) -> Sequence['outputs.ImportFileResponse']:
"""
Specifies any files to import for this configuration. This can be used to import templates or other files. For example, you might import a text file in order to use the file in a template.
"""
return pulumi.get(self, "imports")
| 2,349 | 8,513 | 394 |
d881f975cf2d832d6bc86d988457a89edf496ff7 | 703 | py | Python | face_mask_detector/file_helper.py | kareemsasa3/face-mask-detector | cae54a3c7b9d8d16e42e3850a138ddcbb335c82b | [
"MIT"
] | 3 | 2020-07-21T02:22:12.000Z | 2021-06-28T04:10:32.000Z | face_mask_detector/file_helper.py | kareemsasa3/face-mask-detector | cae54a3c7b9d8d16e42e3850a138ddcbb335c82b | [
"MIT"
] | 22 | 2020-07-16T23:36:48.000Z | 2022-02-10T02:09:46.000Z | face_mask_detector/file_helper.py | kareemsasa3/face-mask-detector | cae54a3c7b9d8d16e42e3850a138ddcbb335c82b | [
"MIT"
] | 5 | 2020-07-21T02:22:14.000Z | 2022-02-16T12:24:01.000Z | """Provides convenience functions for interacting with files and directories
"""
import os
def file_is_not_readable(file_path: str) -> bool:
"""Returns True if the given file is not readable
"""
if os.access(file_path, os.R_OK):
return False
return True
def directory_is_not_readable(directory_path: str) -> bool:
"""Returns True if the given directory is not readable
"""
if os.access(directory_path, os.R_OK):
return False
return True
def directory_is_not_writeable(directory_path: str) -> bool:
"""Returns True if the given directory is not writeable
"""
if os.access(directory_path, os.W_OK):
return False
return True
| 22.677419 | 76 | 0.688478 | """Provides convenience functions for interacting with files and directories
"""
import os
def file_is_not_readable(file_path: str) -> bool:
"""Returns True if the given file is not readable
"""
if os.access(file_path, os.R_OK):
return False
return True
def directory_is_not_readable(directory_path: str) -> bool:
"""Returns True if the given directory is not readable
"""
if os.access(directory_path, os.R_OK):
return False
return True
def directory_is_not_writeable(directory_path: str) -> bool:
"""Returns True if the given directory is not writeable
"""
if os.access(directory_path, os.W_OK):
return False
return True
| 0 | 0 | 0 |
525f2debbe8b534d23dc2ac5eea30d7572c6ba88 | 4,964 | py | Python | src/manager/om/script/gspylib/inspection/items/database/CheckTableSpace.py | wotchin/openGauss-server | ebd92e92b0cfd76b121d98e4c57a22d334573159 | [
"MulanPSL-1.0"
] | 1 | 2020-06-30T15:00:50.000Z | 2020-06-30T15:00:50.000Z | src/manager/om/script/gspylib/inspection/items/database/CheckTableSpace.py | wotchin/openGauss-server | ebd92e92b0cfd76b121d98e4c57a22d334573159 | [
"MulanPSL-1.0"
] | null | null | null | src/manager/om/script/gspylib/inspection/items/database/CheckTableSpace.py | wotchin/openGauss-server | ebd92e92b0cfd76b121d98e4c57a22d334573159 | [
"MulanPSL-1.0"
] | null | null | null | # -*- coding:utf-8 -*-
# Copyright (c) 2020 Huawei Technologies Co.,Ltd.
#
# openGauss is licensed under Mulan PSL v2.
# You can use this software according to the terms
# and conditions of the Mulan PSL v2.
# You may obtain a copy of Mulan PSL v2 at:
#
# http://license.coscl.org.cn/MulanPSL2
#
# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS,
# WITHOUT WARRANTIES OF ANY KIND,
# EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT,
# MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE.
# See the Mulan PSL v2 for more details.
# ----------------------------------------------------------------------------
import os
from gspylib.common.Common import DefaultValue
from gspylib.inspection.common.CheckItem import BaseItem
from gspylib.inspection.common.CheckResult import ResultStatus
| 43.54386 | 79 | 0.547542 | # -*- coding:utf-8 -*-
# Copyright (c) 2020 Huawei Technologies Co.,Ltd.
#
# openGauss is licensed under Mulan PSL v2.
# You can use this software according to the terms
# and conditions of the Mulan PSL v2.
# You may obtain a copy of Mulan PSL v2 at:
#
# http://license.coscl.org.cn/MulanPSL2
#
# THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS,
# WITHOUT WARRANTIES OF ANY KIND,
# EITHER EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO NON-INFRINGEMENT,
# MERCHANTABILITY OR FIT FOR A PARTICULAR PURPOSE.
# See the Mulan PSL v2 for more details.
# ----------------------------------------------------------------------------
import os
from gspylib.common.Common import DefaultValue
from gspylib.inspection.common.CheckItem import BaseItem
from gspylib.inspection.common.CheckResult import ResultStatus
class CheckTableSpace(BaseItem):
def __init__(self):
super(CheckTableSpace, self).__init__(self.__class__.__name__)
def getClusterDirectorys(self, dbNode):
"""
function : Get cluster all directorys
input : NA
output : List
"""
nodeDirs = []
# including cm_server, cm_agent, cn, dn, gtm, etcd, ssd
for dbInst in dbNode.datanodes:
nodeDirs.append(dbInst.datadir)
if (hasattr(dbInst, 'ssdDir') and len(dbInst.ssdDir) != 0):
nodeDirs.append(dbInst.ssdDir)
return nodeDirs
def doCheck(self):
self.result.val = ""
nodeInfo = self.cluster.getDbNodeByName(self.host)
clusterPathList = self.getClusterDirectorys(nodeInfo)
clusterPathList.append(self.cluster.appPath)
clusterPathList.append(self.cluster.logPath)
clusterPathList.append(DefaultValue.getEnv('GPHOME'))
clusterPathList.append(DefaultValue.getEnv('PGHOST'))
nodeInfo = self.cluster.getDbNodeByName(self.host)
if self.cluster.isSingleInstCluster():
dirPath = nodeInfo.datanodes[0].datadir
else:
dirPath = nodeInfo.coordinators[0].datadir
tableSpaceDir = os.path.join(dirPath, "pg_tblspc")
tableSpaceList = os.listdir(tableSpaceDir)
tablespacePaths = []
if (len(tableSpaceList)):
for filename in tableSpaceList:
if (os.path.islink(os.path.join(tableSpaceDir, filename))):
linkDir = os.readlink(
os.path.join(tableSpaceDir, filename))
if (os.path.isdir(linkDir)):
tablespacePaths.append(linkDir)
flag = "Normal"
for tableSpace in tablespacePaths:
if (tableSpace.find(' ') >= 0):
flag = "Error"
self.result.val += "Table space path[%s] contains spaces.\n" \
% tableSpace
# Support create tablespace in pg_location dir for V1R7
if (tableSpace.find(os.path.join(dirPath, "pg_location")) == 0):
continue
tableSpaces = tableSpace.split('/')
for clusterPath in clusterPathList:
clusterPaths = clusterPath.split('/')
if (tableSpace.find(clusterPath) == 0 and
tableSpaces[:len(clusterPaths)] == clusterPaths):
if (flag == "Normal"):
flag = "Warning"
self.result.val += "Table space path[%s] and cluster " \
"path[%s] are nested.\n" % (
tableSpace, clusterPath)
elif (clusterPath.find(tableSpace) == 0 and
clusterPaths[:len(tableSpaces)] == tableSpaces):
flag = "Error"
self.result.val += "Table space path[%s] and cluster " \
"path[%s] are nested.\n" % (tableSpace,
clusterPath)
else:
continue
for tableSpace1 in tablespacePaths:
tableSpaces1 = tableSpace1.split('/')
for tableSpace2 in tablespacePaths:
if (tableSpace1 == tableSpace2):
continue
tableSpaces2 = tableSpace2.split('/')
if (tableSpace1.find(tableSpace2) == 0 and
tableSpaces1[:len(tableSpaces2)] == tableSpaces2):
flag = "Error"
self.result.val += "Table space path[%s] and table space" \
" path[%s] are nested.\n" \
% (tableSpace1, tableSpace2)
if (flag == "Error"):
self.result.rst = ResultStatus.NG
elif (flag == "Warning"):
self.result.rst = ResultStatus.WARNING
else:
self.result.rst = ResultStatus.OK
self.result.val = "All table space path is normal."
| 3,595 | 533 | 23 |
5facad7c98a0d4cd69fab150b8c01cdacd6abcf8 | 9,058 | py | Python | Brautec starten.py | Mahagon/Brautec-Python-Launcher | d8f4b823ab82b5dcfcc6afc2682624c48ee4defa | [
"Apache-2.0"
] | 1 | 2016-01-23T10:45:52.000Z | 2016-01-23T10:45:52.000Z | Brautec starten.py | Mahagon/Brautec-Python-Launcher | d8f4b823ab82b5dcfcc6afc2682624c48ee4defa | [
"Apache-2.0"
] | null | null | null | Brautec starten.py | Mahagon/Brautec-Python-Launcher | d8f4b823ab82b5dcfcc6afc2682624c48ee4defa | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/python3
#imports
import os,json,urllib.request,urllib.parse,glob,zipfile,sys,shutil
from os.path import expanduser
#functions
#Variablen
brautecversion='3'
mcversion='1.6.4'
forgeversion='9.11.1.953'
modpackdownload='http://users.minecraft.name/maha'
modpackversiondownload=modpackdownload+'/Brautec'+brautecversion+'.json'
modpackmodsdownload=modpackdownload+'/mods'
modpackconfigdownload=modpackdownload+'/config'
if os.name=='nt':
minecraftlauncherdownload='https://s3.amazonaws.com/Minecraft.Download/launcher/Minecraft.exe'
minecraftclient=os.path.abspath(module_path()+'/minecraft_launcher.exe')
mcpath=os.path.abspath(os.getenv('APPDATA')+'/.minecraft')
elif os.name=='mac':
minecraftlauncherdownload='https://s3.amazonaws.com/Minecraft.Download/launcher/Minecraft.jar'
minecraftclient=os.path.abspath(module_path()+'/minecraft_launcher.jar')
mcpath=os.path.abspath(expanduser('~')+'/Library/Application Support/minecraft')
else:
minecraftlauncherdownload='https://s3.amazonaws.com/Minecraft.Download/launcher/Minecraft.jar'
minecraftclient=os.path.abspath(module_path()+'/minecraft_launcher.jar')
mcpath=os.path.abspath(expanduser('~')+'/.minecraft')
mcprofiles=os.path.abspath(mcpath+'/launcher_profiles.json')
modpackpath=os.path.abspath(mcpath+'/modpacks/brautec3')
modspath=os.path.abspath(modpackpath+'/mods')
configpath=os.path.abspath(modpackpath+'/config')
versionspath=os.path.abspath(mcpath+'/versions')
modpackversionfile=os.path.abspath(modpackpath+'/Brautec'+brautecversion)
print('Lade aktuelle Versionsinformationen herunter...')
getmodpackjson=urllib.request.urlopen(modpackversiondownload)
modpackjson=getmodpackjson.read().decode()
if modpackjson:
j_modpackjson=json.loads(modpackjson)
mcversion=j_modpackjson['MinecraftVersion']
forgeversion=j_modpackjson['ForgeVersion']
else:
print('Updateserver nicht erreichbar')
if os.path.exists(modpackpath):
print('Installation nicht moeglich: Abbruch!')
exit(1)
forgedownload='http://files.minecraftforge.net/maven/net/minecraftforge/forge/'+mcversion+'-'+forgeversion+'/forge-'+mcversion+'-'+forgeversion+'-installer.jar'
minecraftjardownload='https://s3.amazonaws.com/Minecraft.Download/versions/'+mcversion+'/'+mcversion+'.jar'
minecraftjsondownload='https://s3.amazonaws.com/Minecraft.Download/versions/'+mcversion+'/'+mcversion+'.json'
forgeversionspath=os.path.abspath(versionspath+'/'+mcversion+'-Forge'+forgeversion)
mcversionspath=os.path.abspath(versionspath+'/'+mcversion)
#Code
print('Suche Minecraft Ordner')
print(mcpath)
if os.path.isfile(mcprofiles):
fo = open(mcprofiles, 'r')
j_mcprofiles = json.loads(fo.read())
fo.close()
auth = list(j_mcprofiles['authenticationDatabase'])
if not auth:
print("Kein Minecraft Profil gefunden. Bitte den Minecraft Launcher starten und einloggen!")
exit(1)
if os.name != 'nt' or os.path.exists(os.getenv('programfiles(x86)','C:\\this dir does not exist')):
j_mcprofiles['profiles']['Brautec'+brautecversion]={'name':'Brautec'+brautecversion, 'gameDir':modpackpath, 'javaArgs':'-XX:InitialHeapSize=512M -XX:MaxHeapSize=2G -XX:MaxPermSize=256M -XX:+AggressiveOpts -XX:+UseFastAccessorMethods','lastVersionId':mcversion+'-Forge'+forgeversion,'playerUUID':auth[0]}
else:
j_mcprofiles['profiles']['Brautec'+brautecversion]={'name':'Brautec'+brautecversion, 'gameDir':modpackpath, 'javaArgs':'-XX:InitialHeapSize=512M -XX:MaxHeapSize=1024M -XX:MaxPermSize=256M','lastVersionId':mcversion+'-Forge'+forgeversion,'playerUUID':auth[0]}
j_mcprofiles['selectedProfile'] = 'Brautec3'
fo = open(mcprofiles, 'w+')
fo.write(json.dumps(j_mcprofiles))
fo.close()
else:
print('Du musst Minecraft wenigstens einmal mit dem aktuellen Minecraft Client starten und dich einloggen.')
print('Diesen bekommst du auf der Seite https://minecraft.net/download')
exit(1)
#Hier wird die Minecraft Version heruntergeladen
if not os.path.exists(mcversionspath):
print('Erstelle Versionsordner')
os.makedirs(mcversionspath)
print('Lade Minecraft Version '+mcversion+' herunter...')
mcjarfile=os.path.abspath(mcversionspath+'/'+mcversion+'.jar')
urllib.request.urlretrieve(minecraftjardownload,mcjarfile )
print(mcjarfile+' herunter geladen')
print('Lade Minecraft Profil '+mcversion+' herunter...')
mcjsonfile=os.path.abspath(mcversionspath+'/'+mcversion+'.json')
urllib.request.urlretrieve(minecraftjsondownload,mcjsonfile )
print(mcjsonfile+' herunter geladen')
#Hier wird die Forge Version heruntergeladen
if not os.path.exists(forgeversionspath):
print('Lade Forge Installationsassistent herunter...')
print('Der Assistent wird im Anschluss gestartet.')
print('Bitte fuehre anschliessend eine Clientinstallation durch')
forgeinstallerfile=os.path.abspath(module_path()+'/minecraftforge-installer-'+mcversion+'-'+forgeversion+'.jar')
urllib.request.urlretrieve(forgedownload,forgeinstallerfile )
print(forgeinstallerfile+' herunter geladen')
print('Forge Installationsassistent wird nun ausgefuehrt')
if os.name == 'nt':
os.system('"'+forgeinstallerfile+'"')
else:
os.system('chmod -x "'+forgeinstallerfile+'"')
os.system('java -jar "'+forgeinstallerfile+'"')
os.remove(forgeinstallerfile)
if not os.path.exists(forgeversionspath):
print('Forgesetup wurde scheinbar abgebrochen oder es trat ein Fehler auf.')
print('Brautec'+brautecversion+' Installation wird abgebrochen')
exit(1)
else:
print('Benoetigte Forge Version ist bereits installiert: '+mcversion+'-Forge'+forgeversion)
#Versionscheck
if os.path.isfile(modpackversionfile):
fo = open(modpackversionfile, 'r')
localmodpackversion=fo.readline()
fo.close()
else:
localmodpackversion='0'
print('Aktuell installierte Version: '+localmodpackversion)
if modpackjson:
if (int(j_modpackjson['version']) > int(localmodpackversion)):
if os.path.exists(modspath):
installedmods=glob.glob(modspath+'/*')
for installedmod in installedmods:
if (installedmod.lower().find('jar') != -1) or (installedmod.lower().find('zip') != -1):
if not any(os.path.basename(installedmod).lower() == mod['file'].lower() for mod in j_modpackjson['mods']):
print(os.path.basename(installedmod).lower()+' wird geloescht')
os.remove(installedmod)
if os.path.exists(modspath+'/'+mcversion):
if os.name == 'nt':
os.system('CMD /C RMDIR /S /Q "'+modspath+'/'+mcversion+'"')
else:
shutil.rmtree(modspath+'/'+mcversion)
else:
os.makedirs(modspath)
for mod in j_modpackjson['mods']:
if os.path.isfile(os.path.abspath(modspath+'/'+mod['file'])):
print(mod['name']+' ist aktuell')
else:
print(mod['name']+' wird heruntergeladen')
urllib.request.urlretrieve(urllib.parse.quote(modpackmodsdownload+'/'+mod['file'],safe="%/:=&?~#+!$,;'@()*[]"),os.path.abspath(modspath+'/'+mod['file']))
print('Einstellungen werden heruntergeladen')
for config in j_modpackjson['config']:
configdownloadpath=os.path.abspath(module_path()+'/'+config['file'])
print('Downloade '+config['name'])
print(urllib.parse.quote(modpackconfigdownload+'/'+config['file'],safe="%/:=&?~#+!$,;'@()*[]"))
urllib.request.urlretrieve(urllib.parse.quote(modpackconfigdownload+'/'+config['file'],safe="%/:=&?~#+!$,;'@()*[]"),configdownloadpath)
print('Entpacke '+config['name'])
if config['overwrite']==0:
overwrite=0
zippedfiles=zipfile.ZipFile(configdownloadpath,'r').namelist()
for zippedfile in zippedfiles:
if not os.path.isfile(os.path.abspath(modpackpath+'/'+zippedfile)):
overwrite=1
else:
overwrite=1
if overwrite==1:
zipfile.ZipFile(configdownloadpath,'r').extractall(modpackpath)
else:
print(config['name']+' existiert bereits und wird nicht ueberschrieben')
os.remove(configdownloadpath)
fo = open(modpackversionfile, 'w+')
fo.write(str(j_modpackjson['version']))
fo.close()
else:
print('Version ist aktuell')
else:
print('Modpackinformationen konnten nicht geladen werden.')
print('Brautec wird trotzdem gestartet.')
if not os.path.isfile(minecraftclient):
urllib.request.urlretrieve(minecraftlauncherdownload,minecraftclient)
if os.name == 'nt':
os.system('"'+minecraftclient+'"')
else:
os.system('chmod -x "'+minecraftclient+'"')
os.system('java -jar "'+minecraftclient+'"')
| 50.88764 | 311 | 0.694524 | #!/usr/bin/python3
#imports
import os,json,urllib.request,urllib.parse,glob,zipfile,sys,shutil
from os.path import expanduser
#functions
def we_are_frozen():
return hasattr(sys, "frozen")
def module_path():
if we_are_frozen():
return os.path.dirname(sys.executable)
return os.path.dirname(__file__)
#Variablen
brautecversion='3'
mcversion='1.6.4'
forgeversion='9.11.1.953'
modpackdownload='http://users.minecraft.name/maha'
modpackversiondownload=modpackdownload+'/Brautec'+brautecversion+'.json'
modpackmodsdownload=modpackdownload+'/mods'
modpackconfigdownload=modpackdownload+'/config'
if os.name=='nt':
minecraftlauncherdownload='https://s3.amazonaws.com/Minecraft.Download/launcher/Minecraft.exe'
minecraftclient=os.path.abspath(module_path()+'/minecraft_launcher.exe')
mcpath=os.path.abspath(os.getenv('APPDATA')+'/.minecraft')
elif os.name=='mac':
minecraftlauncherdownload='https://s3.amazonaws.com/Minecraft.Download/launcher/Minecraft.jar'
minecraftclient=os.path.abspath(module_path()+'/minecraft_launcher.jar')
mcpath=os.path.abspath(expanduser('~')+'/Library/Application Support/minecraft')
else:
minecraftlauncherdownload='https://s3.amazonaws.com/Minecraft.Download/launcher/Minecraft.jar'
minecraftclient=os.path.abspath(module_path()+'/minecraft_launcher.jar')
mcpath=os.path.abspath(expanduser('~')+'/.minecraft')
mcprofiles=os.path.abspath(mcpath+'/launcher_profiles.json')
modpackpath=os.path.abspath(mcpath+'/modpacks/brautec3')
modspath=os.path.abspath(modpackpath+'/mods')
configpath=os.path.abspath(modpackpath+'/config')
versionspath=os.path.abspath(mcpath+'/versions')
modpackversionfile=os.path.abspath(modpackpath+'/Brautec'+brautecversion)
print('Lade aktuelle Versionsinformationen herunter...')
getmodpackjson=urllib.request.urlopen(modpackversiondownload)
modpackjson=getmodpackjson.read().decode()
if modpackjson:
j_modpackjson=json.loads(modpackjson)
mcversion=j_modpackjson['MinecraftVersion']
forgeversion=j_modpackjson['ForgeVersion']
else:
print('Updateserver nicht erreichbar')
if os.path.exists(modpackpath):
print('Installation nicht moeglich: Abbruch!')
exit(1)
forgedownload='http://files.minecraftforge.net/maven/net/minecraftforge/forge/'+mcversion+'-'+forgeversion+'/forge-'+mcversion+'-'+forgeversion+'-installer.jar'
minecraftjardownload='https://s3.amazonaws.com/Minecraft.Download/versions/'+mcversion+'/'+mcversion+'.jar'
minecraftjsondownload='https://s3.amazonaws.com/Minecraft.Download/versions/'+mcversion+'/'+mcversion+'.json'
forgeversionspath=os.path.abspath(versionspath+'/'+mcversion+'-Forge'+forgeversion)
mcversionspath=os.path.abspath(versionspath+'/'+mcversion)
#Code
print('Suche Minecraft Ordner')
print(mcpath)
if os.path.isfile(mcprofiles):
fo = open(mcprofiles, 'r')
j_mcprofiles = json.loads(fo.read())
fo.close()
auth = list(j_mcprofiles['authenticationDatabase'])
if not auth:
print("Kein Minecraft Profil gefunden. Bitte den Minecraft Launcher starten und einloggen!")
exit(1)
if os.name != 'nt' or os.path.exists(os.getenv('programfiles(x86)','C:\\this dir does not exist')):
j_mcprofiles['profiles']['Brautec'+brautecversion]={'name':'Brautec'+brautecversion, 'gameDir':modpackpath, 'javaArgs':'-XX:InitialHeapSize=512M -XX:MaxHeapSize=2G -XX:MaxPermSize=256M -XX:+AggressiveOpts -XX:+UseFastAccessorMethods','lastVersionId':mcversion+'-Forge'+forgeversion,'playerUUID':auth[0]}
else:
j_mcprofiles['profiles']['Brautec'+brautecversion]={'name':'Brautec'+brautecversion, 'gameDir':modpackpath, 'javaArgs':'-XX:InitialHeapSize=512M -XX:MaxHeapSize=1024M -XX:MaxPermSize=256M','lastVersionId':mcversion+'-Forge'+forgeversion,'playerUUID':auth[0]}
j_mcprofiles['selectedProfile'] = 'Brautec3'
fo = open(mcprofiles, 'w+')
fo.write(json.dumps(j_mcprofiles))
fo.close()
else:
print('Du musst Minecraft wenigstens einmal mit dem aktuellen Minecraft Client starten und dich einloggen.')
print('Diesen bekommst du auf der Seite https://minecraft.net/download')
exit(1)
#Hier wird die Minecraft Version heruntergeladen
if not os.path.exists(mcversionspath):
print('Erstelle Versionsordner')
os.makedirs(mcversionspath)
print('Lade Minecraft Version '+mcversion+' herunter...')
mcjarfile=os.path.abspath(mcversionspath+'/'+mcversion+'.jar')
urllib.request.urlretrieve(minecraftjardownload,mcjarfile )
print(mcjarfile+' herunter geladen')
print('Lade Minecraft Profil '+mcversion+' herunter...')
mcjsonfile=os.path.abspath(mcversionspath+'/'+mcversion+'.json')
urllib.request.urlretrieve(minecraftjsondownload,mcjsonfile )
print(mcjsonfile+' herunter geladen')
#Hier wird die Forge Version heruntergeladen
if not os.path.exists(forgeversionspath):
print('Lade Forge Installationsassistent herunter...')
print('Der Assistent wird im Anschluss gestartet.')
print('Bitte fuehre anschliessend eine Clientinstallation durch')
forgeinstallerfile=os.path.abspath(module_path()+'/minecraftforge-installer-'+mcversion+'-'+forgeversion+'.jar')
urllib.request.urlretrieve(forgedownload,forgeinstallerfile )
print(forgeinstallerfile+' herunter geladen')
print('Forge Installationsassistent wird nun ausgefuehrt')
if os.name == 'nt':
os.system('"'+forgeinstallerfile+'"')
else:
os.system('chmod -x "'+forgeinstallerfile+'"')
os.system('java -jar "'+forgeinstallerfile+'"')
os.remove(forgeinstallerfile)
if not os.path.exists(forgeversionspath):
print('Forgesetup wurde scheinbar abgebrochen oder es trat ein Fehler auf.')
print('Brautec'+brautecversion+' Installation wird abgebrochen')
exit(1)
else:
print('Benoetigte Forge Version ist bereits installiert: '+mcversion+'-Forge'+forgeversion)
#Versionscheck
if os.path.isfile(modpackversionfile):
fo = open(modpackversionfile, 'r')
localmodpackversion=fo.readline()
fo.close()
else:
localmodpackversion='0'
print('Aktuell installierte Version: '+localmodpackversion)
if modpackjson:
if (int(j_modpackjson['version']) > int(localmodpackversion)):
if os.path.exists(modspath):
installedmods=glob.glob(modspath+'/*')
for installedmod in installedmods:
if (installedmod.lower().find('jar') != -1) or (installedmod.lower().find('zip') != -1):
if not any(os.path.basename(installedmod).lower() == mod['file'].lower() for mod in j_modpackjson['mods']):
print(os.path.basename(installedmod).lower()+' wird geloescht')
os.remove(installedmod)
if os.path.exists(modspath+'/'+mcversion):
if os.name == 'nt':
os.system('CMD /C RMDIR /S /Q "'+modspath+'/'+mcversion+'"')
else:
shutil.rmtree(modspath+'/'+mcversion)
else:
os.makedirs(modspath)
for mod in j_modpackjson['mods']:
if os.path.isfile(os.path.abspath(modspath+'/'+mod['file'])):
print(mod['name']+' ist aktuell')
else:
print(mod['name']+' wird heruntergeladen')
urllib.request.urlretrieve(urllib.parse.quote(modpackmodsdownload+'/'+mod['file'],safe="%/:=&?~#+!$,;'@()*[]"),os.path.abspath(modspath+'/'+mod['file']))
print('Einstellungen werden heruntergeladen')
for config in j_modpackjson['config']:
configdownloadpath=os.path.abspath(module_path()+'/'+config['file'])
print('Downloade '+config['name'])
print(urllib.parse.quote(modpackconfigdownload+'/'+config['file'],safe="%/:=&?~#+!$,;'@()*[]"))
urllib.request.urlretrieve(urllib.parse.quote(modpackconfigdownload+'/'+config['file'],safe="%/:=&?~#+!$,;'@()*[]"),configdownloadpath)
print('Entpacke '+config['name'])
if config['overwrite']==0:
overwrite=0
zippedfiles=zipfile.ZipFile(configdownloadpath,'r').namelist()
for zippedfile in zippedfiles:
if not os.path.isfile(os.path.abspath(modpackpath+'/'+zippedfile)):
overwrite=1
else:
overwrite=1
if overwrite==1:
zipfile.ZipFile(configdownloadpath,'r').extractall(modpackpath)
else:
print(config['name']+' existiert bereits und wird nicht ueberschrieben')
os.remove(configdownloadpath)
fo = open(modpackversionfile, 'w+')
fo.write(str(j_modpackjson['version']))
fo.close()
else:
print('Version ist aktuell')
else:
print('Modpackinformationen konnten nicht geladen werden.')
print('Brautec wird trotzdem gestartet.')
if not os.path.isfile(minecraftclient):
urllib.request.urlretrieve(minecraftlauncherdownload,minecraftclient)
if os.name == 'nt':
os.system('"'+minecraftclient+'"')
else:
os.system('chmod -x "'+minecraftclient+'"')
os.system('java -jar "'+minecraftclient+'"')
| 138 | 0 | 45 |
8a056550603d907e05490e5508ae969bc10f0de8 | 232,121 | py | Python | Integration/main_rc.py | WikiGaze/Wikipedia-readers-gaze | b723fcad149662a9af981c4e507678d9c7f106d2 | [
"BSD-3-Clause"
] | null | null | null | Integration/main_rc.py | WikiGaze/Wikipedia-readers-gaze | b723fcad149662a9af981c4e507678d9c7f106d2 | [
"BSD-3-Clause"
] | null | null | null | Integration/main_rc.py | WikiGaze/Wikipedia-readers-gaze | b723fcad149662a9af981c4e507678d9c7f106d2 | [
"BSD-3-Clause"
] | null | null | null | # -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.11.2)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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qt_resource_name = b"\
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qt_resource_struct_v1 = b"\
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\x00\x00\x00\x00\x00\x02\x00\x00\x00\x04\x00\x00\x00\x02\
\x00\x00\x00\x2c\x00\x00\x00\x00\x00\x01\x00\x00\x12\x65\
\x00\x00\x00\x12\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\
\x00\x00\x00\x76\x00\x00\x00\x00\x00\x01\x00\x00\xad\x54\
\x00\x00\x00\x9c\x00\x00\x00\x00\x00\x01\x00\x00\xb8\x34\
"
qt_resource_struct_v2 = b"\
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x01\
\x00\x00\x00\x00\x00\x00\x00\x00\
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x04\x00\x00\x00\x02\
\x00\x00\x00\x00\x00\x00\x00\x00\
\x00\x00\x00\x2c\x00\x00\x00\x00\x00\x01\x00\x00\x12\x65\
\x00\x00\x01\x6c\x2d\xf9\x44\x26\
\x00\x00\x00\x12\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\
\x00\x00\x01\x6c\x39\x98\x92\xec\
\x00\x00\x00\x76\x00\x00\x00\x00\x00\x01\x00\x00\xad\x54\
\x00\x00\x01\x6c\x2d\xf9\x44\x16\
\x00\x00\x00\x9c\x00\x00\x00\x00\x00\x01\x00\x00\xb8\x34\
\x00\x00\x01\x6c\x2d\xf9\x44\x28\
"
qt_version = [int(v) for v in QtCore.qVersion().split('.')]
if qt_version < [5, 8, 0]:
rcc_version = 1
qt_resource_struct = qt_resource_struct_v1
else:
rcc_version = 2
qt_resource_struct = qt_resource_struct_v2
qInitResources()
| 65.147628 | 129 | 0.727198 | # -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.11.2)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
\x00\x00\x12\x61\
\x89\
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\x00\x00\x00\xf3\x50\x4c\x54\x45\x2e\xa9\xd3\xff\xff\xff\x25\x87\
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qt_resource_name = b"\
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qt_resource_struct_v1 = b"\
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qt_resource_struct_v2 = b"\
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qt_version = [int(v) for v in QtCore.qVersion().split('.')]
if qt_version < [5, 8, 0]:
rcc_version = 1
qt_resource_struct = qt_resource_struct_v1
else:
rcc_version = 2
qt_resource_struct = qt_resource_struct_v2
def qInitResources():
QtCore.qRegisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| 209 | 0 | 46 |
09455b4e8b5022aaae84d6d0e510d32e052e7b5a | 204 | py | Python | config/custom_components/logbook_cache/const.py | allanpersson/home-assistant-conf | 0545dd3e1904ac9e49c6d52129ad99a4a1255c57 | [
"Apache-2.0"
] | 94 | 2019-10-13T06:54:00.000Z | 2022-02-01T22:30:01.000Z | config/custom_components/logbook_cache/const.py | allanpersson/home-assistant-conf | 0545dd3e1904ac9e49c6d52129ad99a4a1255c57 | [
"Apache-2.0"
] | 10 | 2019-10-25T14:54:06.000Z | 2019-12-12T11:05:23.000Z | config/custom_components/logbook_cache/const.py | allanpersson/home-assistant-conf | 0545dd3e1904ac9e49c6d52129ad99a4a1255c57 | [
"Apache-2.0"
] | 17 | 2019-10-14T12:00:10.000Z | 2021-07-01T17:57:42.000Z | """Constants for the Logbook Cache integration."""
DOMAIN = "logbook_cache"
NAME = "Logbook Cache"
CACHE_DAYS = "cache_days"
ONLY_CACHE = "only_cache"
DEFAULT_CACHE_DAYS = 2
DEFAULT_ONLY_CACHE = False
| 18.545455 | 50 | 0.759804 | """Constants for the Logbook Cache integration."""
DOMAIN = "logbook_cache"
NAME = "Logbook Cache"
CACHE_DAYS = "cache_days"
ONLY_CACHE = "only_cache"
DEFAULT_CACHE_DAYS = 2
DEFAULT_ONLY_CACHE = False
| 0 | 0 | 0 |
7928c5c04fb72d08fb684604cffaa731cc92dd66 | 11,963 | py | Python | freesas/app/extract_ascii.py | maaeli/freesas | 418cdd1b72ab650198453a06defa3a57e5c4daea | [
"MIT"
] | null | null | null | freesas/app/extract_ascii.py | maaeli/freesas | 418cdd1b72ab650198453a06defa3a57e5c4daea | [
"MIT"
] | 5 | 2020-07-04T15:58:16.000Z | 2021-06-17T18:47:10.000Z | freesas/app/extract_ascii.py | maaeli/freesas | 418cdd1b72ab650198453a06defa3a57e5c4daea | [
"MIT"
] | null | null | null | #!/usr/bin/python3
# coding: utf-8
#
# Project: freesas
# https://github.com/kif/freesas
#
# Copyright (C) 2020 European Synchrotron Radiation Facility, Grenoble, France
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
__author__ = "Jérôme Kieffer"
__license__ = "MIT"
__copyright__ = "2020, ESRF"
__date__ = "15/01/2021"
import io
import os
import sys
import logging
import glob
import platform
import posixpath
from collections import namedtuple, OrderedDict
import json
import copy
import pyFAI
from pyFAI.io import Nexus
from .sas_argparser import SASParser
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("extract_ascii")
if sys.version_info[0] < 3:
logger.error("This code requires Python 3.4+")
NexusJuice = namedtuple("NexusJuice", "filename h5path npt unit q I poni mask energy polarization signal2d error2d buffer concentration")
def parse():
""" Parse input and return list of files.
:return: list of input files
"""
description = "Extract the SAXS data from a Nexus files as a 3 column ascii (q, I, err). Metadata are exported in the headers as needed."
epilog = """extract_ascii.py allows you to export the data in inverse nm or inverse A with possible intensity scaling.
"""
parser = SASParser(prog="extract-ascii.py", description=description, epilog=epilog)
# Commented option need to be implemented
# parser.add_argument("-o", "--output", action='store', help="Output filename, by default the same with .dat extension", default=None, type=str)
# parser.add_argument("-u", "--unit", action='store', help="Unit for q: inverse nm or Angstrom?", default="nm", type=str)
# parser.add_argument("-n", "--normalize", action='store', help="Re-normalize all intensities with this factor ", default=1.0, type=float)
parser.add_file_argument("HDF5 input data")
parser.add_argument("-a", "--all", action='store_true', help="extract every individual frame", default=False)
return parser.parse_args()
def extract_averaged(filename):
"return some infomations extracted from a HDF5 file "
results = OrderedDict()
results["filename"] = filename
# Missing: comment normalization
with Nexus(filename, "r") as nxsr:
entry_grp = nxsr.get_entries()[0]
results["h5path"] = entry_grp.name
nxdata_grp = nxsr.h5[entry_grp.attrs["default"]]
signal = nxdata_grp.attrs["signal"]
axis = nxdata_grp.attrs["axes"]
results["I"] = nxdata_grp[signal][()]
results["q"] = nxdata_grp[axis][()]
results["std"] = nxdata_grp["errors"][()]
results["unit"] = pyFAI.units.to_unit(axis + "_" + nxdata_grp[axis].attrs["units"])
integration_grp = nxdata_grp.parent
results["geometry"] = json.loads(integration_grp["configuration/data"][()])
results["polarization"] = integration_grp["configuration/polarization_factor"][()]
instrument_grps = nxsr.get_class(entry_grp, class_type="NXinstrument")
if instrument_grps:
detector_grp = nxsr.get_class(instrument_grps[0], class_type="NXdetector")[0]
results["mask"] = detector_grp["pixel_mask"].attrs["filename"]
sample_grp = nxsr.get_class(entry_grp, class_type="NXsample")[0]
results["sample"] = posixpath.split(sample_grp.name)[-1]
results["buffer"] = sample_grp["buffer"][()]
results["storage temperature"] = sample_grp["temperature_env"][()]
results["exposure temperature"] = sample_grp["temperature"][()]
results["concentration"] = sample_grp["concentration"][()]
if "2_correlation_mapping" in entry_grp:
results["to_merge"] = entry_grp["2_correlation_mapping/results/to_merge"][()]
return results
def extract_all(filename):
"return some infomations extracted from a HDF5 file for all individual frames"
res = []
results = OrderedDict()
results["filename"] = filename
with Nexus(filename, "r") as nxsr:
entry_grp = nxsr.get_entries()[0]
results["h5path"] = entry_grp.name
nxdata_grp = nxsr.h5[entry_grp.name + "/1_integration/results"]
signal = nxdata_grp.attrs["signal"]
axis = nxdata_grp.attrs["axes"][1]
I = nxdata_grp[signal][()]
results["q"] = nxdata_grp[axis][()]
std = nxdata_grp["errors"][()]
results["unit"] = pyFAI.units.to_unit(axis + "_" + nxdata_grp[axis].attrs["units"])
integration_grp = nxdata_grp.parent
results["geometry"] = json.loads(integration_grp["configuration/data"][()])
results["polarization"] = integration_grp["configuration/polarization_factor"][()]
instrument_grp = nxsr.get_class(entry_grp, class_type="NXinstrument")[0]
detector_grp = nxsr.get_class(instrument_grp, class_type="NXdetector")[0]
results["mask"] = detector_grp["pixel_mask"].attrs["filename"]
sample_grp = nxsr.get_class(entry_grp, class_type="NXsample")[0]
results["sample"] = posixpath.split(sample_grp.name)[-1]
results["buffer"] = sample_grp["buffer"][()]
if "temperature_env" in sample_grp:
results["storage temperature"] = sample_grp["temperature_env"][()]
if "temperature" in sample_grp:
results["exposure temperature"] = sample_grp["temperature"][()]
if "concentration" in sample_grp:
results["concentration"] = sample_grp["concentration"][()]
# if "2_correlation_mapping" in entry_grp:
# results["to_merge"] = entry_grp["2_correlation_mapping/results/to_merge"][()]
for i, s in zip(I, std):
r = copy.copy(results)
r["I"] = i
r["std"] = s
res.append(r)
return res
def write_ascii(results, output=None, hdr="#", linesep=os.linesep):
"""
:param resusts: dict containing some NexusJuice
:param output: name of the 3-column ascii file to be written
:param hdr: header mark, usually '#'
:param linesep: to be able to addapt the end of lines
Adam Round explicitelly asked for (email from Date: Tue, 04 Oct 2011 15:22:29 +0200) :
Modification from:
# BSA buffer
# Sample c= 0.0 mg/ml (these two lines are required for current DOS pipeline and can be cleaned up once we use EDNA to get to ab-initio models)
#
# Sample environment:
# Detector = Pilatus 1M
# PixelSize_1 = 0.000172
# PixelSize_2 = 6.283185 (I think it could avoid confusion if we give teh actual pixel size as 0.000172 for X and Y and not to give the integrated sizes. Also could there also be a modification for PixelSize_1 as on the diagonal wont it be the hypotenuse (0.000243)? and thus will be on average a bit bigger than 0.000172)
#
# title = BSA buffer
# Frame 7 of 10
# Time per frame (s) = 10
# SampleDistance = 2.43
# WaveLength = 9.31e-11
# Normalization = 0.0004885
# History-1 = saxs_angle +pass -omod n -rsys normal -da 360_deg -odim = 1 /data/id14eh3/inhouse/saxs_pilatus/Adam/EDNAtests/2d/dumdum_008_07.edf/data/id14eh3/inhouse/saxs_pilatus/Adam/EDNAtests/misc/dumdum_008_07.ang
# DiodeCurr = 0.0001592934
# MachCurr = 163.3938
# Mask = /data/id14eh3/archive/CALIBRATION/MASK/Pcon_01Jun_msk.edf
# SaxsDataVersion = 2.40
#
# N 3
# L q*nm I_BSA buffer stddev
#
# Sample Information:
# Storage Temperature (degrees C): 4
# Measurement Temperature (degrees C): 10
# Concentration: 0.0
# Code: BSA
s-vector Intensity Error
s-vector Intensity Error
s-vector Intensity Error
s-vector Intensity Error
"""
hdr = str(hdr)
headers = []
if "comments" in results:
headers.append(hdr + " " + results["comments"])
else:
headers.append(hdr)
headers.append(hdr + " Sample c= %s mg/ml" % results.get("concentration", -1))
headers += [hdr, hdr + " Sample environment:"]
if "geometry" in results:
headers.append(hdr + " Detector = %s" % results["geometry"]["detector"])
headers.append(hdr + " SampleDistance = %s" % results["geometry"]["dist"])
headers.append(hdr + " WaveLength = %s" % results["geometry"]["wavelength"])
headers.append(hdr)
if "comments" in results:
headers.append(hdr + " title = %s" % results["comment"])
if "to_merge" in results:
headers.append(hdr + " Frames merged: " + " ".join([str(i) for i in results["to_merge"]]))
if 'normalization' in results:
headers.append(hdr + " Normalization = %s" % results["normalization"])
if "mask" in results:
headers.append(hdr + " Mask = %s" % results["mask"])
headers.append(hdr)
headers.append(hdr + (" N 3" if "std" in results else " N 2"))
line = hdr + " L "
if "unit" in results:
a, b = str(results["unit"]).split("_")
line += a + "*" + b.strip("^-1") + " I_"
else:
line += "q I_"
if "comment" in results:
line += results["comments"]
if "std" in results:
line += " stddev"
headers.append(line)
headers.append(hdr)
headers.append(hdr + " Sample Information:")
if "storage temperature" in results:
headers.append(hdr + " Storage Temperature (degrees C): %s" % results["storage temperature"])
if "exposure temperature" in results:
headers.append(hdr + " Measurement Temperature (degrees C): %s" % results["exposure temperature"])
headers.append(hdr + " Concentration: %s" % results.get("concentration", -1))
if "buffer" in results:
headers.append(hdr + " Buffer: %s" % results["buffer"])
headers.append(hdr + " Code: %s" % results.get("sample", ""))
if output:
with open(output, "w") as f:
write(headers, f)
else:
f = io.StringIO()
write(headers, f)
f.seek(0)
return f.read()
if __name__ == "__main__":
main()
| 42.272085 | 322 | 0.655438 | #!/usr/bin/python3
# coding: utf-8
#
# Project: freesas
# https://github.com/kif/freesas
#
# Copyright (C) 2020 European Synchrotron Radiation Facility, Grenoble, France
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
# THE SOFTWARE.
__author__ = "Jérôme Kieffer"
__license__ = "MIT"
__copyright__ = "2020, ESRF"
__date__ = "15/01/2021"
import io
import os
import sys
import logging
import glob
import platform
import posixpath
from collections import namedtuple, OrderedDict
import json
import copy
import pyFAI
from pyFAI.io import Nexus
from .sas_argparser import SASParser
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("extract_ascii")
if sys.version_info[0] < 3:
logger.error("This code requires Python 3.4+")
NexusJuice = namedtuple("NexusJuice", "filename h5path npt unit q I poni mask energy polarization signal2d error2d buffer concentration")
def parse():
""" Parse input and return list of files.
:return: list of input files
"""
description = "Extract the SAXS data from a Nexus files as a 3 column ascii (q, I, err). Metadata are exported in the headers as needed."
epilog = """extract_ascii.py allows you to export the data in inverse nm or inverse A with possible intensity scaling.
"""
parser = SASParser(prog="extract-ascii.py", description=description, epilog=epilog)
# Commented option need to be implemented
# parser.add_argument("-o", "--output", action='store', help="Output filename, by default the same with .dat extension", default=None, type=str)
# parser.add_argument("-u", "--unit", action='store', help="Unit for q: inverse nm or Angstrom?", default="nm", type=str)
# parser.add_argument("-n", "--normalize", action='store', help="Re-normalize all intensities with this factor ", default=1.0, type=float)
parser.add_file_argument("HDF5 input data")
parser.add_argument("-a", "--all", action='store_true', help="extract every individual frame", default=False)
return parser.parse_args()
def extract_averaged(filename):
"return some infomations extracted from a HDF5 file "
results = OrderedDict()
results["filename"] = filename
# Missing: comment normalization
with Nexus(filename, "r") as nxsr:
entry_grp = nxsr.get_entries()[0]
results["h5path"] = entry_grp.name
nxdata_grp = nxsr.h5[entry_grp.attrs["default"]]
signal = nxdata_grp.attrs["signal"]
axis = nxdata_grp.attrs["axes"]
results["I"] = nxdata_grp[signal][()]
results["q"] = nxdata_grp[axis][()]
results["std"] = nxdata_grp["errors"][()]
results["unit"] = pyFAI.units.to_unit(axis + "_" + nxdata_grp[axis].attrs["units"])
integration_grp = nxdata_grp.parent
results["geometry"] = json.loads(integration_grp["configuration/data"][()])
results["polarization"] = integration_grp["configuration/polarization_factor"][()]
instrument_grps = nxsr.get_class(entry_grp, class_type="NXinstrument")
if instrument_grps:
detector_grp = nxsr.get_class(instrument_grps[0], class_type="NXdetector")[0]
results["mask"] = detector_grp["pixel_mask"].attrs["filename"]
sample_grp = nxsr.get_class(entry_grp, class_type="NXsample")[0]
results["sample"] = posixpath.split(sample_grp.name)[-1]
results["buffer"] = sample_grp["buffer"][()]
results["storage temperature"] = sample_grp["temperature_env"][()]
results["exposure temperature"] = sample_grp["temperature"][()]
results["concentration"] = sample_grp["concentration"][()]
if "2_correlation_mapping" in entry_grp:
results["to_merge"] = entry_grp["2_correlation_mapping/results/to_merge"][()]
return results
def extract_all(filename):
"return some infomations extracted from a HDF5 file for all individual frames"
res = []
results = OrderedDict()
results["filename"] = filename
with Nexus(filename, "r") as nxsr:
entry_grp = nxsr.get_entries()[0]
results["h5path"] = entry_grp.name
nxdata_grp = nxsr.h5[entry_grp.name + "/1_integration/results"]
signal = nxdata_grp.attrs["signal"]
axis = nxdata_grp.attrs["axes"][1]
I = nxdata_grp[signal][()]
results["q"] = nxdata_grp[axis][()]
std = nxdata_grp["errors"][()]
results["unit"] = pyFAI.units.to_unit(axis + "_" + nxdata_grp[axis].attrs["units"])
integration_grp = nxdata_grp.parent
results["geometry"] = json.loads(integration_grp["configuration/data"][()])
results["polarization"] = integration_grp["configuration/polarization_factor"][()]
instrument_grp = nxsr.get_class(entry_grp, class_type="NXinstrument")[0]
detector_grp = nxsr.get_class(instrument_grp, class_type="NXdetector")[0]
results["mask"] = detector_grp["pixel_mask"].attrs["filename"]
sample_grp = nxsr.get_class(entry_grp, class_type="NXsample")[0]
results["sample"] = posixpath.split(sample_grp.name)[-1]
results["buffer"] = sample_grp["buffer"][()]
if "temperature_env" in sample_grp:
results["storage temperature"] = sample_grp["temperature_env"][()]
if "temperature" in sample_grp:
results["exposure temperature"] = sample_grp["temperature"][()]
if "concentration" in sample_grp:
results["concentration"] = sample_grp["concentration"][()]
# if "2_correlation_mapping" in entry_grp:
# results["to_merge"] = entry_grp["2_correlation_mapping/results/to_merge"][()]
for i, s in zip(I, std):
r = copy.copy(results)
r["I"] = i
r["std"] = s
res.append(r)
return res
def write_ascii(results, output=None, hdr="#", linesep=os.linesep):
"""
:param resusts: dict containing some NexusJuice
:param output: name of the 3-column ascii file to be written
:param hdr: header mark, usually '#'
:param linesep: to be able to addapt the end of lines
Adam Round explicitelly asked for (email from Date: Tue, 04 Oct 2011 15:22:29 +0200) :
Modification from:
# BSA buffer
# Sample c= 0.0 mg/ml (these two lines are required for current DOS pipeline and can be cleaned up once we use EDNA to get to ab-initio models)
#
# Sample environment:
# Detector = Pilatus 1M
# PixelSize_1 = 0.000172
# PixelSize_2 = 6.283185 (I think it could avoid confusion if we give teh actual pixel size as 0.000172 for X and Y and not to give the integrated sizes. Also could there also be a modification for PixelSize_1 as on the diagonal wont it be the hypotenuse (0.000243)? and thus will be on average a bit bigger than 0.000172)
#
# title = BSA buffer
# Frame 7 of 10
# Time per frame (s) = 10
# SampleDistance = 2.43
# WaveLength = 9.31e-11
# Normalization = 0.0004885
# History-1 = saxs_angle +pass -omod n -rsys normal -da 360_deg -odim = 1 /data/id14eh3/inhouse/saxs_pilatus/Adam/EDNAtests/2d/dumdum_008_07.edf/data/id14eh3/inhouse/saxs_pilatus/Adam/EDNAtests/misc/dumdum_008_07.ang
# DiodeCurr = 0.0001592934
# MachCurr = 163.3938
# Mask = /data/id14eh3/archive/CALIBRATION/MASK/Pcon_01Jun_msk.edf
# SaxsDataVersion = 2.40
#
# N 3
# L q*nm I_BSA buffer stddev
#
# Sample Information:
# Storage Temperature (degrees C): 4
# Measurement Temperature (degrees C): 10
# Concentration: 0.0
# Code: BSA
s-vector Intensity Error
s-vector Intensity Error
s-vector Intensity Error
s-vector Intensity Error
"""
hdr = str(hdr)
headers = []
if "comments" in results:
headers.append(hdr + " " + results["comments"])
else:
headers.append(hdr)
headers.append(hdr + " Sample c= %s mg/ml" % results.get("concentration", -1))
headers += [hdr, hdr + " Sample environment:"]
if "geometry" in results:
headers.append(hdr + " Detector = %s" % results["geometry"]["detector"])
headers.append(hdr + " SampleDistance = %s" % results["geometry"]["dist"])
headers.append(hdr + " WaveLength = %s" % results["geometry"]["wavelength"])
headers.append(hdr)
if "comments" in results:
headers.append(hdr + " title = %s" % results["comment"])
if "to_merge" in results:
headers.append(hdr + " Frames merged: " + " ".join([str(i) for i in results["to_merge"]]))
if 'normalization' in results:
headers.append(hdr + " Normalization = %s" % results["normalization"])
if "mask" in results:
headers.append(hdr + " Mask = %s" % results["mask"])
headers.append(hdr)
headers.append(hdr + (" N 3" if "std" in results else " N 2"))
line = hdr + " L "
if "unit" in results:
a, b = str(results["unit"]).split("_")
line += a + "*" + b.strip("^-1") + " I_"
else:
line += "q I_"
if "comment" in results:
line += results["comments"]
if "std" in results:
line += " stddev"
headers.append(line)
headers.append(hdr)
headers.append(hdr + " Sample Information:")
if "storage temperature" in results:
headers.append(hdr + " Storage Temperature (degrees C): %s" % results["storage temperature"])
if "exposure temperature" in results:
headers.append(hdr + " Measurement Temperature (degrees C): %s" % results["exposure temperature"])
headers.append(hdr + " Concentration: %s" % results.get("concentration", -1))
if "buffer" in results:
headers.append(hdr + " Buffer: %s" % results["buffer"])
headers.append(hdr + " Code: %s" % results.get("sample", ""))
def write(headers, file_):
file_.writelines(linesep.join(headers))
file_.write(linesep)
if "std" in results:
data = ["%14.6e\t%14.6e\t%14.6e" % (q, I, std)
for q, I, std in zip(results["q"], results["I"], results["std"])]
else:
data = ["%14.6e\t%14.6e\t" % (q, I)
for q, I in zip(results["q"], results["I"])]
data.append("")
file_.writelines(linesep.join(data))
if output:
with open(output, "w") as f:
write(headers, f)
else:
f = io.StringIO()
write(headers, f)
f.seek(0)
return f.read()
def main():
args = parse()
if args.verbose:
logging.root.setLevel(logging.DEBUG)
files = [i for i in args.file if os.path.exists(i)]
if platform.system() == "Windows" and files == []:
files = glob.glob(args.file[0])
files.sort()
input_len = len(files)
logger.debug("%s input files", input_len)
for src in files:
if args.all:
dest = os.path.splitext(src)[0] + "%04i.dat"
for idx, frame in enumerate(extract_all(src)):
print(src, " --> ", dest % idx)
write_ascii(frame, dest % idx)
else:
dest = os.path.splitext(src)[0] + ".dat"
write_ascii(extract_averaged(src), dest)
print(src, " --> ", dest)
if __name__ == "__main__":
main()
| 1,186 | 0 | 50 |
0ced0aee508911498c274d9bdeedb39bd6618ca1 | 2,259 | py | Python | public_21CMvFAST_MC/Programs/CosmoHammer_21CMMC/likelihood/ChainContext.py | NNSSA/21cmvFAST | 8f015427f3609a3051b4fa185bdbe55b379c930f | [
"MIT"
] | 5 | 2019-04-18T11:31:34.000Z | 2020-11-15T03:29:14.000Z | public_21CMvFAST_MC/Programs/CosmoHammer_21CMMC/likelihood/ChainContext.py | NNSSA/21cmvFAST | 8f015427f3609a3051b4fa185bdbe55b379c930f | [
"MIT"
] | 1 | 2019-12-17T05:27:25.000Z | 2019-12-18T19:59:55.000Z | public_21CMvFAST_MC/Programs/CosmoHammer_21CMMC/likelihood/ChainContext.py | NNSSA/21cmvFAST | 8f015427f3609a3051b4fa185bdbe55b379c930f | [
"MIT"
] | 2 | 2019-11-14T13:54:46.000Z | 2019-12-08T17:16:53.000Z | from CosmoHammer_21CMMC.likelihood.ChainConstants import *
class ChainContext(object):
"""
Context holding a dict to store data and information durring the computation of the likelihood
"""
def __init__(self, parent, params):
"""
Constructor of the context
"""
self._data = dict()
self.add(PARENT_KEY, parent)
self.add(PARAMS_KEY, params)
self.add(DATA_KEY, dict())
def add(self, key, value):
"""
Adds the value to the context using the key
:param key: string
key to use
:param value: object
the value to store
"""
self._data[key] = value
def remove(self, key):
"""
Removes the value from the context
:param key: string
key to remove from the context
"""
assert key != None ("The key must not be empty!")
del(self._data[key])
def contains(self, key):
"""
Checks if the key is in the context
:param key: string
key to check
:return: True if the key is in the context
"""
return key in self._data
def get(self, key, default=None):
"""
Returns the value stored in the context at the key or the default value in the
context doesn't contain the key
:param key: string
key to use
:param default: string
the default value to use if the key is not available
"""
if(self.contains(key)):
return self._data[key]
return default
def getParams(self):
"""
Returns the currently processed parameters
:return: The param of this context
"""
return self.get(PARAMS_KEY)
def getParent(self):
"""
Returns the parent
:return: The parent chain of this context
"""
return self.get(PARENT_KEY)
def getData(self):
"""
Returns the data
:return: The data of this context
"""
return self.get(DATA_KEY)
| 25.1 | 98 | 0.517928 | from CosmoHammer_21CMMC.likelihood.ChainConstants import *
class ChainContext(object):
"""
Context holding a dict to store data and information durring the computation of the likelihood
"""
def __init__(self, parent, params):
"""
Constructor of the context
"""
self._data = dict()
self.add(PARENT_KEY, parent)
self.add(PARAMS_KEY, params)
self.add(DATA_KEY, dict())
def add(self, key, value):
"""
Adds the value to the context using the key
:param key: string
key to use
:param value: object
the value to store
"""
self._data[key] = value
def remove(self, key):
"""
Removes the value from the context
:param key: string
key to remove from the context
"""
assert key != None ("The key must not be empty!")
del(self._data[key])
def contains(self, key):
"""
Checks if the key is in the context
:param key: string
key to check
:return: True if the key is in the context
"""
return key in self._data
def get(self, key, default=None):
"""
Returns the value stored in the context at the key or the default value in the
context doesn't contain the key
:param key: string
key to use
:param default: string
the default value to use if the key is not available
"""
if(self.contains(key)):
return self._data[key]
return default
def getParams(self):
"""
Returns the currently processed parameters
:return: The param of this context
"""
return self.get(PARAMS_KEY)
def getParent(self):
"""
Returns the parent
:return: The parent chain of this context
"""
return self.get(PARENT_KEY)
def getData(self):
"""
Returns the data
:return: The data of this context
"""
return self.get(DATA_KEY)
| 0 | 0 | 0 |
ac84974f2ca52ac2301d8a81d59e2c86d4cf9645 | 966 | py | Python | config/urls.py | copydataai/clon-trello | f088a6da770d9cc32decad6ae45637207d91a80b | [
"MIT"
] | null | null | null | config/urls.py | copydataai/clon-trello | f088a6da770d9cc32decad6ae45637207d91a80b | [
"MIT"
] | null | null | null | config/urls.py | copydataai/clon-trello | f088a6da770d9cc32decad6ae45637207d91a80b | [
"MIT"
] | null | null | null | from django.conf import settings
from django.conf.urls.static import static
from django.contrib import admin
from django.urls import include, path
from drf_spectacular.views import SpectacularAPIView, SpectacularSwaggerView
# API URLS
urlpatterns = [
# API base url
path(settings.ADMIN_URL, admin.site.urls),
path("api/", include("config.api_router")),
path("api/schema/", SpectacularAPIView.as_view(), name="api-schema"),
path(
"api/docs/",
SpectacularSwaggerView.as_view(url_name="api-schema"),
name="api-docs",
),
] + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
if settings.DEBUG:
# This allows the error pages to be debugged during development, just visit
# these url in browser to see how these error pages look like.
if "debug_toolbar" in settings.INSTALLED_APPS:
import debug_toolbar
urlpatterns = [path("__debug__/", include(debug_toolbar.urls))] + urlpatterns
| 35.777778 | 85 | 0.723602 | from django.conf import settings
from django.conf.urls.static import static
from django.contrib import admin
from django.urls import include, path
from drf_spectacular.views import SpectacularAPIView, SpectacularSwaggerView
# API URLS
urlpatterns = [
# API base url
path(settings.ADMIN_URL, admin.site.urls),
path("api/", include("config.api_router")),
path("api/schema/", SpectacularAPIView.as_view(), name="api-schema"),
path(
"api/docs/",
SpectacularSwaggerView.as_view(url_name="api-schema"),
name="api-docs",
),
] + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
if settings.DEBUG:
# This allows the error pages to be debugged during development, just visit
# these url in browser to see how these error pages look like.
if "debug_toolbar" in settings.INSTALLED_APPS:
import debug_toolbar
urlpatterns = [path("__debug__/", include(debug_toolbar.urls))] + urlpatterns
| 0 | 0 | 0 |
2a926b3a01ca9f414016203d9b6e5ec81586ac48 | 1,789 | py | Python | lda_classification/model/tomotopy_lda_vectorizer.py | FeryET/lda_classification | 530f972b8955c9f51668475ef640cb644f9b3ab7 | [
"MIT"
] | 8 | 2020-10-12T07:35:13.000Z | 2022-02-24T21:30:31.000Z | lda_classification/model/tomotopy_lda_vectorizer.py | FeryET/LDAThis | 530f972b8955c9f51668475ef640cb644f9b3ab7 | [
"MIT"
] | null | null | null | lda_classification/model/tomotopy_lda_vectorizer.py | FeryET/LDAThis | 530f972b8955c9f51668475ef640cb644f9b3ab7 | [
"MIT"
] | 3 | 2021-01-12T22:45:15.000Z | 2022-01-15T02:25:04.000Z | from sklearn.base import BaseEstimator, TransformerMixin
from tomotopy import LDAModel
import numpy as np
from scipy.sparse import csr_matrix, csc_matrix
"""
tw=TermWeight.ONE, min_cf=0, min_df=0, rm_top=0, k=1, alpha=0.1, eta=0.01,
seed=None, corpus=None, transform=None
"""
| 37.270833 | 79 | 0.642817 | from sklearn.base import BaseEstimator, TransformerMixin
from tomotopy import LDAModel
import numpy as np
from scipy.sparse import csr_matrix, csc_matrix
"""
tw=TermWeight.ONE, min_cf=0, min_df=0, rm_top=0, k=1, alpha=0.1, eta=0.01,
seed=None, corpus=None, transform=None
"""
class TomotopyLDAVectorizer(BaseEstimator, TransformerMixin):
def __init__(self, num_of_topics, workers=2, train_iter=10, infer_iter=100,
train_steps=100, return_dense=True, sparse_threshold=0.01,
min_df=5, rm_top=10):
self.num_of_topics = num_of_topics
self.min_df = min_df
self.rm_top = rm_top
self.workers = workers
self.train_steps = train_steps
self.train_iter = train_iter
self.infer_iter = infer_iter
self.return_dense = return_dense
self.sparse_threshold = sparse_threshold
def fit(self, docs):
self.lda = LDAModel(k=self.num_of_topics, min_df=self.min_df,
rm_top=self.rm_top)
for d in docs:
self.lda.add_doc(d)
for _ in range(0, self.train_steps * self.train_iter, self.train_iter):
self.lda.train(iter=self.train_iter, workers=self.workers)
return self
def transform(self, docs):
trans_docs = [self.lda.make_doc(d) for d in docs]
inferred = self.lda.infer(trans_docs, iter=self.infer_iter,
workers=self.workers)[0]
if self.return_dense:
inferred = np.array(inferred)
else:
inferred = [i[i > self.sparse_threshold] for i in inferred]
inferred = csr_matrix(inferred)
return inferred
def fit_transform(self, docs, y=None, **fit_params):
return self.fit(docs).transform(docs)
| 1,340 | 40 | 130 |
583a19b653c9fec90b8b140b1bbb0807eb12ad60 | 36 | py | Python | lists.py | tacowerkz/tutor.py | 90862013f3e4eed5648ced228e674c35217699c1 | [
"MIT"
] | null | null | null | lists.py | tacowerkz/tutor.py | 90862013f3e4eed5648ced228e674c35217699c1 | [
"MIT"
] | null | null | null | lists.py | tacowerkz/tutor.py | 90862013f3e4eed5648ced228e674c35217699c1 | [
"MIT"
] | null | null | null |
content = "my pride was beatufil"
| 9 | 33 | 0.694444 |
content = "my pride was beatufil"
| 0 | 0 | 0 |
62a3fa406c46839b1feec67c53ef310f2a088f02 | 110 | py | Python | rllib/agents/__init__.py | carlos-aguayo/ray | fedbdd5dc6a47aa9cba170816f8c0950193b4fd6 | [
"Apache-2.0"
] | null | null | null | rllib/agents/__init__.py | carlos-aguayo/ray | fedbdd5dc6a47aa9cba170816f8c0950193b4fd6 | [
"Apache-2.0"
] | null | null | null | rllib/agents/__init__.py | carlos-aguayo/ray | fedbdd5dc6a47aa9cba170816f8c0950193b4fd6 | [
"Apache-2.0"
] | null | null | null | from ray.rllib.agents.trainer import Trainer, with_common_config
__all__ = ["Trainer", "with_common_config"]
| 27.5 | 64 | 0.8 | from ray.rllib.agents.trainer import Trainer, with_common_config
__all__ = ["Trainer", "with_common_config"]
| 0 | 0 | 0 |
5195691dea0aea3be0af683764406f56bcd8e61c | 2,430 | py | Python | tests/unit/test_utils.py | dataiku-research/mealy | 039978fbb4bbda4e89e55ae05a75bdb3560191e2 | [
"Apache-2.0"
] | 12 | 2021-09-17T19:58:09.000Z | 2022-03-22T16:04:05.000Z | tests/unit/test_utils.py | dataiku-research/mealy | 039978fbb4bbda4e89e55ae05a75bdb3560191e2 | [
"Apache-2.0"
] | 16 | 2021-02-03T16:29:54.000Z | 2021-05-27T14:15:52.000Z | tests/unit/test_utils.py | dataiku/mealy | 52fa90aa2e8dc16cf846d0590fcd7ee710dcd862 | [
"Apache-2.0"
] | null | null | null | from unittest import TestCase
from unittest.mock import patch, Mock
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import OneHotEncoder
from .. import generate_preprocessing_steps
| 39.836066 | 89 | 0.669136 | from unittest import TestCase
from unittest.mock import patch, Mock
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import OneHotEncoder
from .. import generate_preprocessing_steps
class TestFeatureTransformer(TestCase):
def test_generate_preprocessing_steps_pipeline(self):
ohe = Mock(spec=OneHotEncoder)
pipe = Mock(spec=Pipeline, steps=[
("d", "drop"),
("p", "passthrough"),
("o", ohe)
])
generator = generate_preprocessing_steps(pipe)
self.assertEqual(next(generator), "passthrough")
self.assertEqual(next(generator), ohe)
with self.assertRaises(StopIteration):
next(generator)
def test_generate_preprocessing_steps_pipeline_inverted(self):
ohe = Mock(spec=OneHotEncoder)
pipe = Mock(spec=Pipeline, steps=[
("d", "drop"),
("p", "passthrough"),
("o", ohe)
])
generator = generate_preprocessing_steps(pipe, True)
self.assertEqual(next(generator), ohe)
self.assertEqual(next(generator), "passthrough")
with self.assertRaises(StopIteration):
next(generator)
def test_generate_preprocessing_steps_only_drop(self):
generator = generate_preprocessing_steps("drop")
with self.assertRaises(StopIteration):
next(generator)
def test_generate_preprocessing_steps_only_supported(self):
ohe = Mock(spec=OneHotEncoder)
generator = generate_preprocessing_steps(ohe)
self.assertEqual(next(generator), ohe)
with self.assertRaises(StopIteration):
next(generator)
def test_generate_preprocessing_steps_only_passthrough(self):
generator = generate_preprocessing_steps("passthrough")
self.assertEqual(next(generator), "passthrough")
with self.assertRaises(StopIteration):
next(generator)
def test_generate_preprocessing_steps_only_unsupported(self):
msg = 'Mealy package does not support {}. '.format(Mock) + \
'It might be because it changes output dimension without ' +\
'providing a get_feature_names function to keep track of the ' + \
'generated features, or that it does not provide an inverse_tranform method.'
g = generate_preprocessing_steps(Mock())
with self.assertRaisesRegex(TypeError, msg):
next(g)
| 2,029 | 18 | 184 |
aeacda2fef2a86bb7a7109c214fc2efd28560e30 | 826 | py | Python | tests/unit/test_base.py | Paperspace/paperspace-python | 93bdacab520ffc538ecf4d142c5f84c40446d619 | [
"0BSD"
] | 47 | 2017-07-07T11:29:13.000Z | 2021-03-15T21:49:56.000Z | tests/unit/test_base.py | Paperspace/paperspace-python | 93bdacab520ffc538ecf4d142c5f84c40446d619 | [
"0BSD"
] | 14 | 2018-04-11T10:12:54.000Z | 2019-05-31T16:17:28.000Z | tests/unit/test_base.py | Paperspace/paperspace-python | 93bdacab520ffc538ecf4d142c5f84c40446d619 | [
"0BSD"
] | 7 | 2017-08-27T11:21:35.000Z | 2019-06-03T23:52:47.000Z | from collections import OrderedDict
import mock
from paperspace.commands.common import CommandBase
output_response = ""
| 21.179487 | 71 | 0.575061 | from collections import OrderedDict
import mock
from paperspace.commands.common import CommandBase
output_response = ""
class TestBaseClass(object):
def test_json_print(self):
global output_response
output_response = ""
def log_to_var(message):
global output_response
output_response = "{}{}\n".format(output_response, message)
logger_ = mock.MagicMock()
logger_.log = log_to_var
input_dict = {
"foo": {
'bar': {
"baz": "faz"
}
}
}
expected_string = """foo:
bar:
baz:
faz
"""
command = CommandBase(logger_=logger_)
command._print_dict_recursive(OrderedDict(input_dict))
assert output_response == expected_string
| 646 | 7 | 49 |
fb366580413c75d908917d8f1e7f980034266206 | 2,389 | py | Python | wencai/core/event.py | bruce2792/wencai | 1b4e8bdcb02e594e575601c0893c1b356cc2256b | [
"MIT"
] | null | null | null | wencai/core/event.py | bruce2792/wencai | 1b4e8bdcb02e594e575601c0893c1b356cc2256b | [
"MIT"
] | null | null | null | wencai/core/event.py | bruce2792/wencai | 1b4e8bdcb02e594e575601c0893c1b356cc2256b | [
"MIT"
] | null | null | null | # -*- coding:utf-8 -*-
from wencai.core.crawler import Wencai
global_cn_col = False
global_proxies = None
verify = False
| 47.78 | 139 | 0.566764 | # -*- coding:utf-8 -*-
from wencai.core.crawler import Wencai
global_cn_col = False
global_proxies = None
verify = False
def set_variable(cn_col=False, proxies=None, is_verify=False):
global global_cn_col, global_proxies, verify
global_cn_col = cn_col
global_proxies = proxies
verify = is_verify
def get_scrape_report(query, start_date, end_date, period, benchmark):
return Wencai(cn_col=globals()['global_cn_col'], proxies=globals()['global_proxies'],
verify=globals()['verify']).backtest(
query=query, start_date=start_date, end_date=end_date, period=period, benchmark=benchmark
)
def get_strategy(query, start_date, end_date, stock_hold, upper_income, lower_income, period, fall_income,
day_buy_stock_num):
return Wencai(cn_col=globals()['global_cn_col'], proxies=globals()['global_proxies'],
verify=globals()['verify']).yieldbacktest(query=query,
start_date=start_date,
end_date=end_date,
period=period,
fall_income=fall_income,
day_buy_stock_num=day_buy_stock_num,
upper_income=upper_income,
lower_income=lower_income,
stock_hold=stock_hold)
def get_event_evaluate(query, start_date, end_date, period, index_code):
return Wencai(cn_col=globals()['global_cn_col'], proxies=globals()['global_proxies'],
verify=globals()['verify']).eventbacktest(query=query, start_date=start_date, end_date=end_date,
period=period, index_code=index_code)
def get_lastjs(code):
return Wencai(cn_col=globals()['global_cn_col'],
proxies=globals()['global_proxies'], verify=globals()['verify']).lastjs(code)
def search(query, page, pageSize):
print(globals()['global_proxies'])
return Wencai(proxies=globals()['global_proxies'], verify=globals()['verify']).search(query_string=query,page=page , pageSize=pageSize)
| 2,124 | 0 | 138 |
5f753cee051e2714203f37002751b3e9d750c1f6 | 1,946 | py | Python | sustancia quimica.py | CodeHuntersLab/SustanciaQuimica | 533955438a54fc1a70792ba32399d0c40d356b99 | [
"Apache-2.0"
] | null | null | null | sustancia quimica.py | CodeHuntersLab/SustanciaQuimica | 533955438a54fc1a70792ba32399d0c40d356b99 | [
"Apache-2.0"
] | null | null | null | sustancia quimica.py | CodeHuntersLab/SustanciaQuimica | 533955438a54fc1a70792ba32399d0c40d356b99 | [
"Apache-2.0"
] | null | null | null | from turtle import*
import turtle
setup(600,490)
bgcolor("white")
title("Curie")
estructuraquimica(5)
hideturtle()
turtle.exitonclick() | 16.921739 | 47 | 0.644399 | from turtle import*
import turtle
setup(600,490)
bgcolor("white")
title("Curie")
def estructuraquimica(velocidad):
cpq = turtle.Turtle()
cpq.speed(velocidad)
cpq.pencolor("black")
cpq.pensize(3)
cpq.begin_fill()
cpq.penup()
cpq.left(30)
cpq.forward(280)
cpq.pendown()
cpq.right(175)
cpq.forward(70)
cpq.left(55)
cpq.forward(70)
cpq.right(180)
cpq.forward(70)
cpq.left(55)
cpq.forward(60)
cpq.left(70)
cpq.forward(60)
cpq.left(55)
cpq.forward(70)
cpq.right(60)
cpq.forward(60)
cpq.penup()
cpq.right(148)
cpq.forward(114)
cpq.pendown()
cpq.left(90)
cpq.forward(70)
cpq.right(62)
cpq.forward(60)
cpq.left(180)
cpq.forward(60)
cpq.right(65)
cpq.forward(70)
cpq.left(65)
cpq.forward(70)
cpq.right(60)
cpq.forward(60)
cpq.right(60)
cpq.forward(60)
cpq.left(65)
cpq.forward(60)
cpq.left(180)
cpq.forward(60)
cpq.left(55)
cpq.forward(70)
cpq.right(65)
cpq.forward(60)
cpq.right(50)
cpq.forward(55)
cpq.right(180)
cpq.forward(55)
cpq.right(65)
cpq.forward(70)
cpq.left(65)
cpq.forward(60)
cpq.left(50)
cpq.forward(60)
cpq.right(65)
cpq.forward(60)
cpq.left(180)
cpq.forward(60)
cpq.right(50)
cpq.forward(70)
cpq.left(65)
cpq.forward(60)
cpq.penup()
cpq.left(150)
cpq.forward(98)
cpq.pendown()
cpq.left(15)
cpq.forward(70)
cpq.penup()
cpq.left(180)
cpq.forward(100)
cpq.left(90)
cpq.forward(60)
cpq.pendown()
cpq.right(75)
cpq.forward(45)
cpq.penup()
cpq.right(85)
cpq.forward(105)
cpq.pendown()
cpq.left(20)
cpq.forward(55)
cpq.penup()
cpq.left(65)
cpq.forward(50)
cpq.pendown()
cpq.left(55)
cpq.forward(45)
cpq.penup()
cpq.left(60)
cpq.forward(60)
cpq.pendown()
cpq.left(65)
cpq.forward(45)
cpq.penup()
cpq.left(120)
cpq.forward(200)
cpq.write(" ¿ Que elemento es ? ")
estructuraquimica(5)
hideturtle()
turtle.exitonclick() | 1,776 | 0 | 25 |
5db2263ca53d29361f1661366eb57fa44663825d | 2,043 | py | Python | application.py | phoughton/ensign | 946b513c0df7ae82da73e9cd3b5fe04471e641de | [
"MIT"
] | null | null | null | application.py | phoughton/ensign | 946b513c0df7ae82da73e9cd3b5fe04471e641de | [
"MIT"
] | null | null | null | application.py | phoughton/ensign | 946b513c0df7ae82da73e9cd3b5fe04471e641de | [
"MIT"
] | null | null | null | from flask import Flask
from flask import request, redirect, render_template
from fastai.learner import load_learner
import pathlib
from fastai.vision.core import PILImage
import platform
application = Flask(__name__)
application.config['MAX_CONTENT_LENGTH'] = 12 * 1024 * 1024
MIN_STANDARD = 0.9
# Workaround pytorch issue with models developed on linux being used on Windows
if platform.system() == 'Windows':
pathlib.PosixPath = pathlib.WindowsPath
ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', 'gif'}
learn_inf = load_learner('flag_export.pkl', cpu=True)
@application.route("/upload-image/", methods=["GET", "POST"])
@application.route('/')
if __name__ == '__main__':
application.run()
| 37.145455 | 138 | 0.610866 | from flask import Flask
from flask import request, redirect, render_template
from fastai.learner import load_learner
import pathlib
from fastai.vision.core import PILImage
import platform
application = Flask(__name__)
application.config['MAX_CONTENT_LENGTH'] = 12 * 1024 * 1024
MIN_STANDARD = 0.9
# Workaround pytorch issue with models developed on linux being used on Windows
if platform.system() == 'Windows':
pathlib.PosixPath = pathlib.WindowsPath
ALLOWED_EXTENSIONS = {'png', 'jpg', 'jpeg', 'gif'}
learn_inf = load_learner('flag_export.pkl', cpu=True)
def allowed_file(filename):
return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
@application.route("/upload-image/", methods=["GET", "POST"])
def upload_image():
if request.method == "POST":
if request.files:
image = request.files["image"]
if allowed_file(image.filename):
pred, pred_idx, probs = learn_inf.predict(PILImage.create(image))
pred = pred.replace('_', ' ').title()
if probs[pred_idx] > MIN_STANDARD:
return render_template("public/upload_image.html",
messages=f"I think it is a {pred} flag; Probability: {probs[pred_idx]:.04f}")
else:
return render_template("public/upload_image.html",
messages=f"I can't recognise this one." +
f" But if had to guess, " +
f"I would say it was the flag of {pred}; Probability: {probs[pred_idx]:.04f}")
else:
return render_template("public/upload_image.html", messages=f"Sorry, invalid image type: Must be a: {ALLOWED_EXTENSIONS}")
return render_template("public/upload_image.html", messages="")
@application.route('/')
def go_to_upload():
return redirect("upload-image/")
if __name__ == '__main__':
application.run()
| 1,268 | 0 | 67 |
b9df7b6e2812f63f6fbc00dc9ee6b84c136862bd | 5,655 | py | Python | tcrdist/automate.py | agartland/tcrdist3 | 34f8d50e7448b2bf7cf7cd9ab9a2d80759f47240 | [
"MIT"
] | 26 | 2020-12-28T17:37:01.000Z | 2022-01-29T01:31:13.000Z | tcrdist/automate.py | agartland/tcrdist3 | 34f8d50e7448b2bf7cf7cd9ab9a2d80759f47240 | [
"MIT"
] | 31 | 2020-08-17T22:17:57.000Z | 2022-03-18T23:47:34.000Z | tcrdist/automate.py | agartland/tcrdist3 | 34f8d50e7448b2bf7cf7cd9ab9a2d80759f47240 | [
"MIT"
] | 7 | 2020-08-18T23:55:40.000Z | 2021-09-22T18:15:54.000Z | """
Functions that automate expressive functions of tcrdist3.
These use sensible defaults but users should consider
flexibile elements of these functions that might better
suit their specific data or research questions.
"""
import os
import pandas as pd
import numpy as np
import warnings
from progress.bar import IncrementalBar
"""
Test Automatic Pgen Esimator Functions
"""
def auto_pgen(tcrrep):
"""
Automate a pgen estimation of cdr3s alpha/beta given a tcrrep with a clones_df attribute
Parameters
----------
tcrrep : tcrdist.repertoire.TCRrep
TCRrep instance with a clone_df
Returns
-------
tcrrep : tcrdist.repertoire.TCRrep
tcrrep : tcrdist.repertoire.TCRrep
TCRrep instance with a clone_df
"""
if tcrrep.organism == "mouse" and 'alpha' in tcrrep.chains:
raise ValueError("UNFORTUNATELY OLGA DOES NOT YET SUPPORT MOUSE ALPHA PGEN ESTIMATES")
for chain in tcrrep.chains:
tcrrep = _auto_pgen(tcrrep=tcrrep, organism = tcrrep.organism, chain = chain, ncpus = tcrrep.cpus)
return tcrrep
def _auto_pgen(tcrrep = None, organism = 'human', chain = 'beta', ncpus = 2):
"""
Automate a pgen estimation of cdr3s alpha/beta given a tcrrep with a clones_df attribute
Parameters
----------
tcrrep : tcrdist.repertoire.TCRrep
TCRrep instance with a clone_df
organism : str
'human' or 'mouse'
chain : str
'beta' or 'alpha'
Returns
-------
tcrrep : tcrdist.repertoire.TCRrep
"""
import tcrdist
import parmap
import pandas as pd
from tcrdist.pgen import OlgaModel
assert organism in ['human', 'mouse']
assert chain in ['beta', 'alpha']
assert isinstance(tcrrep, tcrdist.repertoire.TCRrep)
assert isinstance(tcrrep.clone_df, pd.DataFrame)
cdr3_col = {'alpha': 'cdr3_a_aa', 'beta': 'cdr3_b_aa'}[chain]
cdr3s = tcrrep.clone_df[cdr3_col]
olga_models = {
('human', 'beta') :
OlgaModel(chain_folder = "human_T_beta", recomb_type="VDJ"),
('human', 'alpha') :
OlgaModel(chain_folder = "human_T_alpha", recomb_type="VJ"),
('mouse', 'beta') :
OlgaModel(chain_folder = "mouse_T_beta", recomb_type="VDJ")}
olga_model = olga_models[(organism, chain)]
pgens = parmap.map(olga_model.compute_aa_cdr3_pgen, cdr3s, pm_pbar = True, pm_processes = ncpus)
tcrrep.clone_df[f"pgen_{cdr3_col}"] = pgens
return tcrrep
def _default_tcrsampler_human_beta(default_background = None, default_background_if_missing=None):
"""
Responsible for providing the default human beta sampler 'britanova_human_beta_t_cb.tsv.sampler.tsv'
Returns
-------
t : tcrsampler.sampler.TCRsampler
"""
from tcrsampler.sampler import TCRsampler
if default_background is None:
default_background = 'britanova_human_beta_t_cb.tsv.sampler.tsv'
if default_background_if_missing is None:
default_background_if_missing ='britanova_human_beta_t_cb.tsv.sampler.tsv.zip'
print(default_background)
try:
t = TCRsampler(default_background=default_background)
except OSError:
t = TCRsampler()
t.download_background_file(default_background_if_missing)
t = TCRsampler(default_background=default_background)
return t
def _default_tcrsampler_human_alpha(default_background = None, default_background_if_missing=None ):
"""
Responsible for providing the default human alpha sampler 'ruggiero_human_alpha_t.tsv.sampler.tsv'
"""
from tcrsampler.sampler import TCRsampler
if default_background is None:
default_background = 'ruggiero_human_alpha_t.tsv.sampler.tsv'
if default_background_if_missing is None:
default_background_if_missing = 'ruggiero_human_alpha_t.tsv.sampler.tsv.zip'
print(default_background)
try:
t = TCRsampler(default_background=default_background)
except OSError:
t = TCRsampler()
t.download_background_file(default_background_if_missing)
t = TCRsampler(default_background=default_background)
return t
def _default_tcrsampler_mouse_beta(default_background = None, default_background_if_missing=None):
"""
Responsible for providing the default mouse beta sampler
Returns
-------
t : tcrsampler.sampler.TCRsampler
"""
from tcrsampler.sampler import TCRsampler
if default_background is None:
default_background = 'ruggiero_mouse_beta_t.tsv.sampler.tsv'
if default_background_if_missing is None:
default_background_if_missing = 'ruggiero_mouse_sampler.zip'
print(default_background)
try:
t = TCRsampler(default_background=default_background)
except OSError:
t = TCRsampler()
t.download_background_file(default_background_if_missing)
t = TCRsampler(default_background=default_background)
return t
def _default_tcrsampler_mouse_alpha(default_background = None, default_background_if_missing=None):
"""
Responsible for providing the default mouse alpha sampler
"""
from tcrsampler.sampler import TCRsampler
if default_background is None:
default_background = 'ruggiero_mouse_alpha_t.tsv.sampler.tsv'
if default_background_if_missing is None:
default_background_if_missing = 'ruggiero_mouse_sampler.zip'
print(default_background)
try:
t = TCRsampler(default_background=default_background)
except OSError:
t = TCRsampler()
t.download_background_file(default_background_if_missing)
t = TCRsampler(default_background=default_background)
return t
| 28.705584 | 101 | 0.770115 | """
Functions that automate expressive functions of tcrdist3.
These use sensible defaults but users should consider
flexibile elements of these functions that might better
suit their specific data or research questions.
"""
import os
import pandas as pd
import numpy as np
import warnings
from progress.bar import IncrementalBar
"""
Test Automatic Pgen Esimator Functions
"""
def auto_pgen(tcrrep):
"""
Automate a pgen estimation of cdr3s alpha/beta given a tcrrep with a clones_df attribute
Parameters
----------
tcrrep : tcrdist.repertoire.TCRrep
TCRrep instance with a clone_df
Returns
-------
tcrrep : tcrdist.repertoire.TCRrep
tcrrep : tcrdist.repertoire.TCRrep
TCRrep instance with a clone_df
"""
if tcrrep.organism == "mouse" and 'alpha' in tcrrep.chains:
raise ValueError("UNFORTUNATELY OLGA DOES NOT YET SUPPORT MOUSE ALPHA PGEN ESTIMATES")
for chain in tcrrep.chains:
tcrrep = _auto_pgen(tcrrep=tcrrep, organism = tcrrep.organism, chain = chain, ncpus = tcrrep.cpus)
return tcrrep
def _auto_pgen(tcrrep = None, organism = 'human', chain = 'beta', ncpus = 2):
"""
Automate a pgen estimation of cdr3s alpha/beta given a tcrrep with a clones_df attribute
Parameters
----------
tcrrep : tcrdist.repertoire.TCRrep
TCRrep instance with a clone_df
organism : str
'human' or 'mouse'
chain : str
'beta' or 'alpha'
Returns
-------
tcrrep : tcrdist.repertoire.TCRrep
"""
import tcrdist
import parmap
import pandas as pd
from tcrdist.pgen import OlgaModel
assert organism in ['human', 'mouse']
assert chain in ['beta', 'alpha']
assert isinstance(tcrrep, tcrdist.repertoire.TCRrep)
assert isinstance(tcrrep.clone_df, pd.DataFrame)
cdr3_col = {'alpha': 'cdr3_a_aa', 'beta': 'cdr3_b_aa'}[chain]
cdr3s = tcrrep.clone_df[cdr3_col]
olga_models = {
('human', 'beta') :
OlgaModel(chain_folder = "human_T_beta", recomb_type="VDJ"),
('human', 'alpha') :
OlgaModel(chain_folder = "human_T_alpha", recomb_type="VJ"),
('mouse', 'beta') :
OlgaModel(chain_folder = "mouse_T_beta", recomb_type="VDJ")}
olga_model = olga_models[(organism, chain)]
pgens = parmap.map(olga_model.compute_aa_cdr3_pgen, cdr3s, pm_pbar = True, pm_processes = ncpus)
tcrrep.clone_df[f"pgen_{cdr3_col}"] = pgens
return tcrrep
def _default_sampler(organism = 'human', chain = 'beta'):
assert organism in ['human', 'mouse']
assert chain in ['beta','alpha']
default_tcrsampler_generator = {
('human','beta'):
_default_tcrsampler_human_beta,
('human','alpha'):
_default_tcrsampler_human_alpha,
('mouse','beta'):
_default_tcrsampler_mouse_beta,
('mouse','alpha'):
_default_tcrsampler_mouse_alpha,
}[(organism, chain)]
return default_tcrsampler_generator
def _default_tcrsampler_human_beta(default_background = None, default_background_if_missing=None):
"""
Responsible for providing the default human beta sampler 'britanova_human_beta_t_cb.tsv.sampler.tsv'
Returns
-------
t : tcrsampler.sampler.TCRsampler
"""
from tcrsampler.sampler import TCRsampler
if default_background is None:
default_background = 'britanova_human_beta_t_cb.tsv.sampler.tsv'
if default_background_if_missing is None:
default_background_if_missing ='britanova_human_beta_t_cb.tsv.sampler.tsv.zip'
print(default_background)
try:
t = TCRsampler(default_background=default_background)
except OSError:
t = TCRsampler()
t.download_background_file(default_background_if_missing)
t = TCRsampler(default_background=default_background)
return t
def _default_tcrsampler_human_alpha(default_background = None, default_background_if_missing=None ):
"""
Responsible for providing the default human alpha sampler 'ruggiero_human_alpha_t.tsv.sampler.tsv'
"""
from tcrsampler.sampler import TCRsampler
if default_background is None:
default_background = 'ruggiero_human_alpha_t.tsv.sampler.tsv'
if default_background_if_missing is None:
default_background_if_missing = 'ruggiero_human_alpha_t.tsv.sampler.tsv.zip'
print(default_background)
try:
t = TCRsampler(default_background=default_background)
except OSError:
t = TCRsampler()
t.download_background_file(default_background_if_missing)
t = TCRsampler(default_background=default_background)
return t
def _default_tcrsampler_mouse_beta(default_background = None, default_background_if_missing=None):
"""
Responsible for providing the default mouse beta sampler
Returns
-------
t : tcrsampler.sampler.TCRsampler
"""
from tcrsampler.sampler import TCRsampler
if default_background is None:
default_background = 'ruggiero_mouse_beta_t.tsv.sampler.tsv'
if default_background_if_missing is None:
default_background_if_missing = 'ruggiero_mouse_sampler.zip'
print(default_background)
try:
t = TCRsampler(default_background=default_background)
except OSError:
t = TCRsampler()
t.download_background_file(default_background_if_missing)
t = TCRsampler(default_background=default_background)
return t
def _default_tcrsampler_mouse_alpha(default_background = None, default_background_if_missing=None):
"""
Responsible for providing the default mouse alpha sampler
"""
from tcrsampler.sampler import TCRsampler
if default_background is None:
default_background = 'ruggiero_mouse_alpha_t.tsv.sampler.tsv'
if default_background_if_missing is None:
default_background_if_missing = 'ruggiero_mouse_sampler.zip'
print(default_background)
try:
t = TCRsampler(default_background=default_background)
except OSError:
t = TCRsampler()
t.download_background_file(default_background_if_missing)
t = TCRsampler(default_background=default_background)
return t
| 435 | 0 | 23 |
bb6ce8d8ae5249c0e965543d1a33120cbc40acd2 | 213 | py | Python | core/models.py | AlexBoliachiy/SegmentationError | f741b61c797c5d64f1277ef3fcc681aca1951440 | [
"MIT"
] | null | null | null | core/models.py | AlexBoliachiy/SegmentationError | f741b61c797c5d64f1277ef3fcc681aca1951440 | [
"MIT"
] | null | null | null | core/models.py | AlexBoliachiy/SegmentationError | f741b61c797c5d64f1277ef3fcc681aca1951440 | [
"MIT"
] | null | null | null | from django.db import models
from django.contrib.auth.models import User
| 19.363636 | 43 | 0.741784 | from django.db import models
from django.contrib.auth.models import User
class Account(models.Model):
about_me = models.TextField()
love_lang = models.TextField()
user = models.OneToOneField(User)
| 0 | 114 | 23 |
5052b9e7d291434daf0bf2dd403df7740ad1ec46 | 3,465 | py | Python | install/app_store/tk-multi-publish/v0.10.7/python/tk_multi_publish/ui/item_list.py | JoanAzpeitia/lp_sg | e0ee79555e419dd2ae3a5f31e5515b3f40b22a62 | [
"MIT"
] | null | null | null | install/app_store/tk-multi-publish/v0.10.7/python/tk_multi_publish/ui/item_list.py | JoanAzpeitia/lp_sg | e0ee79555e419dd2ae3a5f31e5515b3f40b22a62 | [
"MIT"
] | null | null | null | install/app_store/tk-multi-publish/v0.10.7/python/tk_multi_publish/ui/item_list.py | JoanAzpeitia/lp_sg | e0ee79555e419dd2ae3a5f31e5515b3f40b22a62 | [
"MIT"
] | 1 | 2020-02-15T10:42:56.000Z | 2020-02-15T10:42:56.000Z | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'item_list.ui'
#
# by: pyside-uic 0.2.15 running on PySide 1.2.2
#
# WARNING! All changes made in this file will be lost!
from tank.platform.qt import QtCore, QtGui
from . import resources_rc
| 45.592105 | 193 | 0.715152 | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'item_list.ui'
#
# by: pyside-uic 0.2.15 running on PySide 1.2.2
#
# WARNING! All changes made in this file will be lost!
from tank.platform.qt import QtCore, QtGui
class Ui_ItemList(object):
def setupUi(self, ItemList):
ItemList.setObjectName("ItemList")
ItemList.resize(397, 265)
self.horizontalLayout_2 = QtGui.QHBoxLayout(ItemList)
self.horizontalLayout_2.setContentsMargins(12, 2, 2, 2)
self.horizontalLayout_2.setObjectName("horizontalLayout_2")
self.main_frame = QtGui.QFrame(ItemList)
self.main_frame.setStyleSheet("#main_frame {\n"
"border-style: solid;\n"
"border-width: 1;\n"
"border-radius: 2px;\n"
"}")
self.main_frame.setFrameShape(QtGui.QFrame.StyledPanel)
self.main_frame.setFrameShadow(QtGui.QFrame.Raised)
self.main_frame.setObjectName("main_frame")
self.verticalLayout = QtGui.QVBoxLayout(self.main_frame)
self.verticalLayout.setSpacing(2)
self.verticalLayout.setContentsMargins(2, 2, 2, 2)
self.verticalLayout.setObjectName("verticalLayout")
self.horizontalLayout = QtGui.QHBoxLayout()
self.horizontalLayout.setObjectName("horizontalLayout")
self.section_label = QtGui.QLabel(self.main_frame)
self.section_label.setStyleSheet("#section_label {\n"
"font-size: 10pt\n"
"}")
self.section_label.setIndent(4)
self.section_label.setObjectName("section_label")
self.horizontalLayout.addWidget(self.section_label)
self.expand_label = QtGui.QLabel(self.main_frame)
self.expand_label.setMinimumSize(QtCore.QSize(20, 20))
self.expand_label.setBaseSize(QtCore.QSize(20, 20))
self.expand_label.setText("")
self.expand_label.setPixmap(QtGui.QPixmap(":/res/group_expand.png"))
self.expand_label.setScaledContents(False)
self.expand_label.setAlignment(QtCore.Qt.AlignCenter)
self.expand_label.setObjectName("expand_label")
self.horizontalLayout.addWidget(self.expand_label)
self.horizontalLayout.setStretch(0, 1)
self.verticalLayout.addLayout(self.horizontalLayout)
self.line = QtGui.QFrame(self.main_frame)
self.line.setFrameShadow(QtGui.QFrame.Plain)
self.line.setFrameShape(QtGui.QFrame.HLine)
self.line.setFrameShadow(QtGui.QFrame.Sunken)
self.line.setObjectName("line")
self.verticalLayout.addWidget(self.line)
self.item_frame = QtGui.QFrame(self.main_frame)
self.item_frame.setStyleSheet("#item_frame {\n"
"border-style: none;\n"
"}")
self.item_frame.setFrameShape(QtGui.QFrame.StyledPanel)
self.item_frame.setFrameShadow(QtGui.QFrame.Raised)
self.item_frame.setObjectName("item_frame")
self.verticalLayout.addWidget(self.item_frame)
self.verticalLayout.setStretch(2, 1)
self.horizontalLayout_2.addWidget(self.main_frame)
self.retranslateUi(ItemList)
QtCore.QMetaObject.connectSlotsByName(ItemList)
def retranslateUi(self, ItemList):
ItemList.setWindowTitle(QtGui.QApplication.translate("ItemList", "Form", None, QtGui.QApplication.UnicodeUTF8))
self.section_label.setText(QtGui.QApplication.translate("ItemList", "<b>n items available</b>, <i>expand to turn individual items on and off</i>", None, QtGui.QApplication.UnicodeUTF8))
from . import resources_rc
| 3,107 | 5 | 76 |
836ce298a3d47bd247735f251ea9f154e23cbf09 | 1,093 | py | Python | src/fractal/demon/basic/laws.py | jedhsu/fractal | 97833ddc5063fae72352cf590738fef508c02f0c | [
"MIT"
] | null | null | null | src/fractal/demon/basic/laws.py | jedhsu/fractal | 97833ddc5063fae72352cf590738fef508c02f0c | [
"MIT"
] | null | null | null | src/fractal/demon/basic/laws.py | jedhsu/fractal | 97833ddc5063fae72352cf590738fef508c02f0c | [
"MIT"
] | null | null | null | """
*War*
Parameters that govern the evaluation process that compares
the current neural network with the best one seen so far
(which is used to generate data).
"""
from dataclasses import dataclass
"""
# Explanation (two-player games)
* The two competing networks are instantiated into two MCTS players
of parameter `mcts` and then play `sim.num_games` games.
* The evaluated network replaces the current best one if its
average collected reward is greater or equal than `update_threshold`.
# Explanation (single-player games)
* The two competing networks play `sim.num_games` games each.
* The evaluated network replaces the current best one if its average collected rewards
exceeds the average collected reward of the old one by `update_threshold` at least.
"""
"""
# Remarks
+ See [`necessary_samples`](@ref) to make an informed choice for `sim.num_games`.
# AlphaGo Zero Parameters
In the original AlphaGo Zero paper, 400 games are played to evaluate a network
and the `update_threshold` parameter is set to a value that corresponds to a
55% win rate.
"""
| 26.02381 | 86 | 0.755718 | """
*War*
Parameters that govern the evaluation process that compares
the current neural network with the best one seen so far
(which is used to generate data).
"""
from dataclasses import dataclass
"""
# Explanation (two-player games)
* The two competing networks are instantiated into two MCTS players
of parameter `mcts` and then play `sim.num_games` games.
* The evaluated network replaces the current best one if its
average collected reward is greater or equal than `update_threshold`.
# Explanation (single-player games)
* The two competing networks play `sim.num_games` games each.
* The evaluated network replaces the current best one if its average collected rewards
exceeds the average collected reward of the old one by `update_threshold` at least.
"""
"""
# Remarks
+ See [`necessary_samples`](@ref) to make an informed choice for `sim.num_games`.
# AlphaGo Zero Parameters
In the original AlphaGo Zero paper, 400 games are played to evaluate a network
and the `update_threshold` parameter is set to a value that corresponds to a
55% win rate.
"""
| 0 | 0 | 0 |
e232881fe48e1a81885e2540f860a3181646607e | 1,385 | py | Python | tests/test_types.py | daitakahashi/tinydb-query | 2090bc57eb368bce435a737979c6bb35476807bf | [
"MIT"
] | null | null | null | tests/test_types.py | daitakahashi/tinydb-query | 2090bc57eb368bce435a737979c6bb35476807bf | [
"MIT"
] | null | null | null | tests/test_types.py | daitakahashi/tinydb-query | 2090bc57eb368bce435a737979c6bb35476807bf | [
"MIT"
] | null | null | null | import numbers
import pytest
TESTSET = [
(
{'blob': {'$types': ['string']}},
lambda x: isinstance(x['blob'], str)
), (
{'blob': {'$types': ['number']}},
lambda x: isinstance(x['blob'], numbers.Number)
), (
{'blob': {'$types': ['boolean']}},
lambda x: isinstance(x['blob'], bool)
), (
{'blob': {'$types': ['array']}},
lambda x: isinstance(x['blob'], list)
), (
{'blob': {'$types': ['object']}},
lambda x: isinstance(x['blob'], dict)
), (
{'blob': {'$types': ['object', 'array']}},
lambda x: isinstance(x['blob'], (dict, list))
), (
{'status': {'$types': ['string']}},
lambda x: False
), (
{'status': {'$types': ['boolean']}},
lambda x: False
), (
{'name': {'$types': ['number']}},
lambda x: False
), (
{'name': {'$types': ['array']}},
lambda x: False
), (
{'name': {'$types': ['object']}},
lambda x: False
), (
{'name': {'$types': []}},
lambda x: False
)
]
@pytest.mark.parametrize('spec', TESTSET)
ERRORSET = [
{'name': {'$types': ['asdfw']}}
]
@pytest.mark.parametrize('spec', ERRORSET)
| 24.732143 | 55 | 0.47509 | import numbers
import pytest
TESTSET = [
(
{'blob': {'$types': ['string']}},
lambda x: isinstance(x['blob'], str)
), (
{'blob': {'$types': ['number']}},
lambda x: isinstance(x['blob'], numbers.Number)
), (
{'blob': {'$types': ['boolean']}},
lambda x: isinstance(x['blob'], bool)
), (
{'blob': {'$types': ['array']}},
lambda x: isinstance(x['blob'], list)
), (
{'blob': {'$types': ['object']}},
lambda x: isinstance(x['blob'], dict)
), (
{'blob': {'$types': ['object', 'array']}},
lambda x: isinstance(x['blob'], (dict, list))
), (
{'status': {'$types': ['string']}},
lambda x: False
), (
{'status': {'$types': ['boolean']}},
lambda x: False
), (
{'name': {'$types': ['number']}},
lambda x: False
), (
{'name': {'$types': ['array']}},
lambda x: False
), (
{'name': {'$types': ['object']}},
lambda x: False
), (
{'name': {'$types': []}},
lambda x: False
)
]
@pytest.mark.parametrize('spec', TESTSET)
def test_by_selector(run_test_by_selector, spec):
run_test_by_selector(spec)
ERRORSET = [
{'name': {'$types': ['asdfw']}}
]
@pytest.mark.parametrize('spec', ERRORSET)
def test_error(run_test_error, spec):
run_test_error(spec)
| 100 | 0 | 44 |
63b3d331ef144c7ad74d79b4c3d07d950d9c17c3 | 358 | py | Python | esque/cli/commands/create/__init__.py | real-digital/esque | 0b779fc308ce8bce45c1903f36c33664b2e832e7 | [
"MIT"
] | 29 | 2019-05-10T21:12:38.000Z | 2021-08-24T08:09:49.000Z | esque/cli/commands/create/__init__.py | real-digital/esque | 0b779fc308ce8bce45c1903f36c33664b2e832e7 | [
"MIT"
] | 103 | 2019-05-17T07:21:41.000Z | 2021-12-02T08:29:00.000Z | esque/cli/commands/create/__init__.py | real-digital/esque | 0b779fc308ce8bce45c1903f36c33664b2e832e7 | [
"MIT"
] | 2 | 2019-05-28T06:45:14.000Z | 2019-11-21T00:33:15.000Z | import click
from esque.cli.options import State, default_options
from .consumergroup import create_consumergroup
from .topic import create_topic
@click.group(help="Create a new instance of a resource.", no_args_is_help=True)
@default_options
create.add_command(create_consumergroup)
create.add_command(create_topic)
| 21.058824 | 79 | 0.815642 | import click
from esque.cli.options import State, default_options
from .consumergroup import create_consumergroup
from .topic import create_topic
@click.group(help="Create a new instance of a resource.", no_args_is_help=True)
@default_options
def create(state: State):
pass
create.add_command(create_consumergroup)
create.add_command(create_topic)
| 13 | 0 | 22 |
143ebc229df4891cea29b076302b9427e714e0b2 | 263 | py | Python | pyvisdk/enums/net_bios_config_info_mode.py | Infinidat/pyvisdk | f2f4e5f50da16f659ccc1d84b6a00f397fa997f8 | [
"MIT"
] | null | null | null | pyvisdk/enums/net_bios_config_info_mode.py | Infinidat/pyvisdk | f2f4e5f50da16f659ccc1d84b6a00f397fa997f8 | [
"MIT"
] | null | null | null | pyvisdk/enums/net_bios_config_info_mode.py | Infinidat/pyvisdk | f2f4e5f50da16f659ccc1d84b6a00f397fa997f8 | [
"MIT"
] | null | null | null |
########################################
# Automatically generated, do not edit.
########################################
from pyvisdk.thirdparty import Enum
NetBIOSConfigInfoMode = Enum(
'disabled',
'enabled',
'enabledViaDHCP',
'unknown',
)
| 16.4375 | 40 | 0.467681 |
########################################
# Automatically generated, do not edit.
########################################
from pyvisdk.thirdparty import Enum
NetBIOSConfigInfoMode = Enum(
'disabled',
'enabled',
'enabledViaDHCP',
'unknown',
)
| 0 | 0 | 0 |
0d30b15b243554dab45f11e6eedf8d4242270c45 | 2,949 | py | Python | memobuilder/mtrainer/trainer.py | stbalduin/memobuilder | c99eb8e711d5109c1322f443441b5a07c079e2f0 | [
"MIT"
] | null | null | null | memobuilder/mtrainer/trainer.py | stbalduin/memobuilder | c99eb8e711d5109c1322f443441b5a07c079e2f0 | [
"MIT"
] | null | null | null | memobuilder/mtrainer/trainer.py | stbalduin/memobuilder | c99eb8e711d5109c1322f443441b5a07c079e2f0 | [
"MIT"
] | null | null | null | """ """
from sklearn.model_selection import train_test_split
from memobuilder import mtrainer as memotrainer
from memobuilder.mdb import memomodel
| 35.963415 | 79 | 0.672092 | """ """
from sklearn.model_selection import train_test_split
from memobuilder import mtrainer as memotrainer
from memobuilder.mdb import memomodel
class SurrogateModelTrainer(object):
def __init__(self, test_split_ratio=0.2, num_cv_folds=5):
self.name = None
self.metamodel_trainer = Trainer(test_split_ratio, num_cv_folds)
self.metamodels = []
def fit(self, input_response_dataset):
training_results = []
for metamodel in self.metamodels:
training_results.append(
self.metamodel_trainer.fit(metamodel, input_response_dataset))
result = memomodel.SurrogateModelTrainingResult()
result.training_results = training_results
result.surrogate_model_name = self.name
return result
def __repr__(self):
return str(self.__dict__)
class Trainer(object):
def __init__(self, test_split_ratio=0.2, num_cv_folds=5):
self.test_split_ratio = test_split_ratio
self.num_cross_val_folds = num_cv_folds
def fit(self, metamodel, input_response_data):
# select input dataset for this metamodel
selected_data = input_response_data.select(
selected_inputs=metamodel.input_names,
selected_responses=metamodel.response_names)
# split train and test data
train_data, test_data = self.train_test_split(selected_data)
# fit the metamodel to the training data
metamodel.fit(train_data.inputs, train_data.responses)
# compute different scores of the metamodel on the test data
score_r2 = memotrainer.scores.r2_score(metamodel, test_data)
score_mae = memotrainer.scores.mae_score(metamodel, test_data)
score_hae = memotrainer.scores.hae_score(metamodel, test_data)
score_mse = memotrainer.scores.mse_score(metamodel, test_data)
# compose a result object and return it
result = memomodel.TrainingResult()
result.train_data = train_data
result.test_data = test_data
result.metamodel = metamodel
result.score_r2 = score_r2
result.score_mae = score_mae
result.score_hae = score_hae
result.score_mse = score_mse
return result
def train_test_split(self, input_response_data):
split = train_test_split(
input_response_data.inputs,
input_response_data.responses,
test_size=self.test_split_ratio, random_state=0)
train_data = memomodel.InputResponseDataset()
train_data.inputs = split[0]
train_data.responses = split[2]
test_data = memomodel.InputResponseDataset()
test_data.inputs = split[1]
test_data.responses = split[3]
return train_data, test_data
def __repr__(self):
return '%s [%s]' % (self.__class__.__name__, str(self.__dict__))
| 2,525 | 16 | 251 |
93fdcad87fe85750724c2d69dc3e999a1759702d | 2,208 | py | Python | examples/hello_procedural.py | isabella232/wamr-python | 44a296304c6649f03a22ff275a812db43efd068b | [
"Apache-2.0"
] | 2 | 2022-03-07T05:04:39.000Z | 2022-03-12T08:07:36.000Z | examples/hello_procedural.py | bytecodealliance/wamr-python | 82e6a5678fb9e838f67ef6ed49a92f69eb85ff2c | [
"Apache-2.0"
] | 2 | 2022-02-28T22:46:50.000Z | 2022-03-04T03:22:39.000Z | examples/hello_procedural.py | isabella232/wamr-python | 44a296304c6649f03a22ff275a812db43efd068b | [
"Apache-2.0"
] | 4 | 2022-01-24T09:09:53.000Z | 2022-03-20T19:06:27.000Z | # -*- coding: utf-8 -*-
#!/usr/bin/env python3
#
# Copyright (C) 2019 Intel Corporation. All rights reserved.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
#
import ctypes
from wamr.ffi import *
if __name__ == "__main__":
main()
| 25.976471 | 87 | 0.699728 | # -*- coding: utf-8 -*-
#!/usr/bin/env python3
#
# Copyright (C) 2019 Intel Corporation. All rights reserved.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
#
import ctypes
from wamr.ffi import *
def hello_callback(args, results):
print("Calling back...")
print("> Hello World!")
return 0
def wasm_functype_new_0_0():
params = wasm_valtype_vec_t()
results = wasm_valtype_vec_t()
wasm_valtype_vec_new_empty(byref(params))
wasm_valtype_vec_new_empty(byref(results))
return wasm_functype_new(byref(params), byref(results))
def main():
print("Initializing...")
engine = wasm_engine_new()
store = wasm_store_new(engine)
print("Loading binary...")
with open("hello.wasm", "rb") as f:
wasm = f.read()
binary = wasm_byte_vec_t()
wasm_byte_vec_new_uninitialized(byref(binary), len(wasm))
# underlying buffer is not writable
binary.data = (ctypes.c_ubyte * len(wasm)).from_buffer_copy(wasm)
print("Compiling module...")
module = wasm_module_new(store, byref(binary))
binary.data = None
wasm_byte_vec_delete(byref(binary))
print("Creating callback...")
hello_type = wasm_functype_new_0_0()
hello_func = wasm_func_new(store, hello_type, wasm_func_callback_t(hello_callback))
wasm_functype_delete(hello_type)
print("Instantiating module...")
imports = wasm_extern_vec_t()
wasm_extern_vec_new(byref(imports), 1, wasm_func_as_extern(hello_func))
instance = wasm_instance_new(store, module, imports, None)
wasm_func_delete(hello_func)
print("Extracting export...")
exports = wasm_extern_vec_t()
wasm_instance_exports(instance, exports)
run_func = wasm_extern_as_func(exports.data[0])
wasm_instance_delete(instance)
wasm_module_delete(module)
print("Calling export...")
args = wasm_val_vec_t()
results = wasm_val_vec_t()
wasm_val_vec_new_empty(byref(args))
wasm_val_vec_new_empty(byref(results))
wasm_func_call(run_func, byref(args), byref(results))
print("Shutting down...")
wasm_store_delete(store)
wasm_engine_delete(engine)
print("Done.")
if __name__ == "__main__":
main()
| 1,888 | 0 | 69 |
86403c36150e08b964402a883cb2a095cb0c3f46 | 7,001 | py | Python | calm/dsl/cli/app_commands.py | nutanixdev/calm-dsl | 90e1c583d7b9ac905cdfb3e2ad27f9f930e69831 | [
"Apache-2.0"
] | null | null | null | calm/dsl/cli/app_commands.py | nutanixdev/calm-dsl | 90e1c583d7b9ac905cdfb3e2ad27f9f930e69831 | [
"Apache-2.0"
] | null | null | null | calm/dsl/cli/app_commands.py | nutanixdev/calm-dsl | 90e1c583d7b9ac905cdfb3e2ad27f9f930e69831 | [
"Apache-2.0"
] | null | null | null | import click
from calm.dsl.api import get_api_client
from .main import main, get, describe, delete, run, watch, download, create
from .utils import Display, FeatureFlagGroup
from .apps import (
get_apps,
describe_app,
run_actions,
watch_action,
watch_app,
delete_app,
download_runlog,
create_app,
)
from calm.dsl.log import get_logging_handle
LOG = get_logging_handle(__name__)
@create.command("app")
@click.option(
"--file",
"-f",
"bp_file",
type=click.Path(exists=True, file_okay=True, dir_okay=False, readable=True),
required=True,
help="Path of Blueprint file to upload",
)
@click.option(
"--brownfield_deployments",
"-b",
"brownfield_deployment_file",
type=click.Path(exists=True, file_okay=True, dir_okay=False, readable=True),
help="Path of Brownfield Deployment file",
)
@click.option(
"--name", "-n", "app_name", default=None, help="Application name (Optional)"
)
@click.option(
"--ignore_runtime_variables",
"-i",
is_flag=True,
default=False,
help="Ignore runtime variables and use defaults while launching blueprint",
)
@click.option(
"--launch_params",
"-l",
type=click.Path(exists=True, file_okay=True, dir_okay=False, readable=True),
help="Path to python file for runtime editables",
)
def _create_app(
app_name,
bp_file,
brownfield_deployment_file,
ignore_runtime_variables,
launch_params,
):
"""Creates an application.
\b
Command consumes a dsl blueprint file and creates a blueprint from it.
If created blueprint is in ACTIVE state, then it got launched to create an application.
"""
create_app(
app_name=app_name,
bp_file=bp_file,
patch_editables=not ignore_runtime_variables,
launch_params=launch_params,
brownfield_deployment_file=brownfield_deployment_file,
)
@get.command("apps")
@click.option("--name", "-n", default=None, help="Search for apps by name")
@click.option(
"--filter", "filter_by", "-f", default=None, help="Filter apps by this string"
)
@click.option("--limit", "-l", default=20, help="Number of results to return")
@click.option(
"--offset", "-s", default=0, help="Offset results by the specified amount"
)
@click.option(
"--quiet", "-q", is_flag=True, default=False, help="Show only application names"
)
@click.option(
"--all-items", "-a", is_flag=True, help="Get all items, including deleted ones"
)
@click.option(
"--out",
"-o",
"out",
type=click.Choice(["text", "json"]),
default="text",
help="output format",
)
def _get_apps(name, filter_by, limit, offset, quiet, all_items, out):
"""Get Apps, optionally filtered by a string"""
get_apps(name, filter_by, limit, offset, quiet, all_items, out)
@describe.command("app")
@click.argument("app_name")
@click.option(
"--out",
"-o",
"out",
type=click.Choice(["text", "json"]),
default="text",
help="output format",
)
def _describe_app(app_name, out):
"""Describe an app"""
describe_app(app_name, out)
@run.command("action")
@click.argument("action_name")
@click.option(
"--app",
"app_name",
"-a",
default=None,
required=True,
help="Watch action run in an app",
)
@click.option("--watch/--no-watch", "-w", default=False, help="Watch scrolling output")
def _run_actions(app_name, action_name, watch):
"""App lcm actions"""
render_actions = display_with_screen(app_name, action_name, watch)
Display.wrapper(render_actions, watch)
@watch.command("action_runlog")
@click.argument("runlog_uuid")
@click.option(
"--app",
"app_name",
"-a",
default=None,
required=True,
help="Watch action run in an app",
)
@click.option(
"--poll-interval",
"poll_interval",
"-p",
type=int,
default=10,
show_default=True,
help="Give polling interval",
)
def _watch_action_runlog(runlog_uuid, app_name, poll_interval):
"""Watch an app"""
Display.wrapper(display_action, watch=True)
LOG.info("Action run {} completed for app {}".format(runlog_uuid, app_name))
@watch.command("app")
@click.argument("app_name")
@click.option(
"--poll-interval",
"poll_interval",
"-p",
type=int,
default=10,
show_default=True,
help="Give polling interval",
)
def _watch_app(app_name, poll_interval):
"""Watch an app"""
Display.wrapper(display_action, watch=True)
LOG.info("Action runs completed for app {}".format(app_name))
@download.command("action_runlog")
@click.argument("runlog_uuid")
@click.option(
"--app", "app_name", "-a", required=True, help="App the action belongs to"
)
@click.option("--file", "file_name", "-f", help="How to name the downloaded file")
def _download_runlog(runlog_uuid, app_name, file_name):
"""Download runlogs, given runlog uuid and app name"""
download_runlog(runlog_uuid, app_name, file_name)
@delete.command("app")
@click.argument("app_names", nargs=-1)
@click.option("--soft", "-s", is_flag=True, default=False, help="Soft delete app")
def _delete_app(app_names, soft):
"""Deletes an application"""
delete_app(app_names, soft)
@main.group(cls=FeatureFlagGroup)
def start():
"""Start entities"""
pass
@main.group(cls=FeatureFlagGroup)
def stop():
"""Stop entities"""
pass
@main.group(cls=FeatureFlagGroup)
def restart():
"""Restart entities"""
pass
@start.command("app")
@click.argument("app_name")
@click.option("--watch/--no-watch", "-w", default=False, help="Watch scrolling output")
def start_app(app_name, watch):
"""Starts an application"""
render_actions = display_with_screen(app_name, "start", watch)
Display.wrapper(render_actions, watch)
@stop.command("app")
@click.argument("app_name")
@click.option("--watch/--no-watch", "-w", default=False, help="Watch scrolling output")
def stop_app(app_name, watch):
"""Stops an application"""
render_actions = display_with_screen(app_name, "stop", watch)
Display.wrapper(render_actions, watch)
@restart.command("app")
@click.argument("app_name")
@click.option("--watch/--no-watch", "-w", default=False, help="Watch scrolling output")
def restart_app(app_name, watch):
"""Restarts an application"""
render_actions = display_with_screen(app_name, "restart", watch)
Display.wrapper(render_actions, watch)
| 26.123134 | 91 | 0.675189 | import click
from calm.dsl.api import get_api_client
from .main import main, get, describe, delete, run, watch, download, create
from .utils import Display, FeatureFlagGroup
from .apps import (
get_apps,
describe_app,
run_actions,
watch_action,
watch_app,
delete_app,
download_runlog,
create_app,
)
from calm.dsl.log import get_logging_handle
LOG = get_logging_handle(__name__)
@create.command("app")
@click.option(
"--file",
"-f",
"bp_file",
type=click.Path(exists=True, file_okay=True, dir_okay=False, readable=True),
required=True,
help="Path of Blueprint file to upload",
)
@click.option(
"--brownfield_deployments",
"-b",
"brownfield_deployment_file",
type=click.Path(exists=True, file_okay=True, dir_okay=False, readable=True),
help="Path of Brownfield Deployment file",
)
@click.option(
"--name", "-n", "app_name", default=None, help="Application name (Optional)"
)
@click.option(
"--ignore_runtime_variables",
"-i",
is_flag=True,
default=False,
help="Ignore runtime variables and use defaults while launching blueprint",
)
@click.option(
"--launch_params",
"-l",
type=click.Path(exists=True, file_okay=True, dir_okay=False, readable=True),
help="Path to python file for runtime editables",
)
def _create_app(
app_name,
bp_file,
brownfield_deployment_file,
ignore_runtime_variables,
launch_params,
):
"""Creates an application.
\b
Command consumes a dsl blueprint file and creates a blueprint from it.
If created blueprint is in ACTIVE state, then it got launched to create an application.
"""
create_app(
app_name=app_name,
bp_file=bp_file,
patch_editables=not ignore_runtime_variables,
launch_params=launch_params,
brownfield_deployment_file=brownfield_deployment_file,
)
@get.command("apps")
@click.option("--name", "-n", default=None, help="Search for apps by name")
@click.option(
"--filter", "filter_by", "-f", default=None, help="Filter apps by this string"
)
@click.option("--limit", "-l", default=20, help="Number of results to return")
@click.option(
"--offset", "-s", default=0, help="Offset results by the specified amount"
)
@click.option(
"--quiet", "-q", is_flag=True, default=False, help="Show only application names"
)
@click.option(
"--all-items", "-a", is_flag=True, help="Get all items, including deleted ones"
)
@click.option(
"--out",
"-o",
"out",
type=click.Choice(["text", "json"]),
default="text",
help="output format",
)
def _get_apps(name, filter_by, limit, offset, quiet, all_items, out):
"""Get Apps, optionally filtered by a string"""
get_apps(name, filter_by, limit, offset, quiet, all_items, out)
@describe.command("app")
@click.argument("app_name")
@click.option(
"--out",
"-o",
"out",
type=click.Choice(["text", "json"]),
default="text",
help="output format",
)
def _describe_app(app_name, out):
"""Describe an app"""
describe_app(app_name, out)
@run.command("action")
@click.argument("action_name")
@click.option(
"--app",
"app_name",
"-a",
default=None,
required=True,
help="Watch action run in an app",
)
@click.option("--watch/--no-watch", "-w", default=False, help="Watch scrolling output")
def _run_actions(app_name, action_name, watch):
"""App lcm actions"""
render_actions = display_with_screen(app_name, action_name, watch)
Display.wrapper(render_actions, watch)
def display_with_screen(app_name, action_name, watch):
def render_actions(screen):
screen.clear()
screen.print_at(
"Running action {} for app {}".format(action_name, app_name), 0, 0
)
screen.refresh()
run_actions(screen, app_name, action_name, watch)
screen.wait_for_input(10.0)
return render_actions
@watch.command("action_runlog")
@click.argument("runlog_uuid")
@click.option(
"--app",
"app_name",
"-a",
default=None,
required=True,
help="Watch action run in an app",
)
@click.option(
"--poll-interval",
"poll_interval",
"-p",
type=int,
default=10,
show_default=True,
help="Give polling interval",
)
def _watch_action_runlog(runlog_uuid, app_name, poll_interval):
"""Watch an app"""
def display_action(screen):
watch_action(runlog_uuid, app_name, get_api_client(), screen, poll_interval)
screen.wait_for_input(10.0)
Display.wrapper(display_action, watch=True)
LOG.info("Action run {} completed for app {}".format(runlog_uuid, app_name))
@watch.command("app")
@click.argument("app_name")
@click.option(
"--poll-interval",
"poll_interval",
"-p",
type=int,
default=10,
show_default=True,
help="Give polling interval",
)
def _watch_app(app_name, poll_interval):
"""Watch an app"""
def display_action(screen):
watch_app(app_name, screen)
screen.wait_for_input(10.0)
Display.wrapper(display_action, watch=True)
LOG.info("Action runs completed for app {}".format(app_name))
@download.command("action_runlog")
@click.argument("runlog_uuid")
@click.option(
"--app", "app_name", "-a", required=True, help="App the action belongs to"
)
@click.option("--file", "file_name", "-f", help="How to name the downloaded file")
def _download_runlog(runlog_uuid, app_name, file_name):
"""Download runlogs, given runlog uuid and app name"""
download_runlog(runlog_uuid, app_name, file_name)
@delete.command("app")
@click.argument("app_names", nargs=-1)
@click.option("--soft", "-s", is_flag=True, default=False, help="Soft delete app")
def _delete_app(app_names, soft):
"""Deletes an application"""
delete_app(app_names, soft)
@main.group(cls=FeatureFlagGroup)
def start():
"""Start entities"""
pass
@main.group(cls=FeatureFlagGroup)
def stop():
"""Stop entities"""
pass
@main.group(cls=FeatureFlagGroup)
def restart():
"""Restart entities"""
pass
@start.command("app")
@click.argument("app_name")
@click.option("--watch/--no-watch", "-w", default=False, help="Watch scrolling output")
def start_app(app_name, watch):
"""Starts an application"""
render_actions = display_with_screen(app_name, "start", watch)
Display.wrapper(render_actions, watch)
@stop.command("app")
@click.argument("app_name")
@click.option("--watch/--no-watch", "-w", default=False, help="Watch scrolling output")
def stop_app(app_name, watch):
"""Stops an application"""
render_actions = display_with_screen(app_name, "stop", watch)
Display.wrapper(render_actions, watch)
@restart.command("app")
@click.argument("app_name")
@click.option("--watch/--no-watch", "-w", default=False, help="Watch scrolling output")
def restart_app(app_name, watch):
"""Restarts an application"""
render_actions = display_with_screen(app_name, "restart", watch)
Display.wrapper(render_actions, watch)
| 553 | 0 | 77 |
700f20a297d0d397646316e3744a3a7b64c0f8dd | 503 | py | Python | teachers/models.py | Rakib1508/django-school | b76fa8442878944fe73ed4a49503d442a3093acb | [
"MIT"
] | 1 | 2021-07-31T09:29:36.000Z | 2021-07-31T09:29:36.000Z | teachers/models.py | Rakib1508/django-school | b76fa8442878944fe73ed4a49503d442a3093acb | [
"MIT"
] | null | null | null | teachers/models.py | Rakib1508/django-school | b76fa8442878944fe73ed4a49503d442a3093acb | [
"MIT"
] | null | null | null | from django.db import models
from users.models import CustomUser
| 22.863636 | 63 | 0.705765 | from django.db import models
from users.models import CustomUser
class Teacher(models.Model):
teacher = models.OneToOneField(
CustomUser, on_delete=models.CASCADE, primary_key=True)
started_on = models.DateTimeField(auto_now_add=True)
def __str__(self):
return self.teacher.__str__()
def username(self):
return self.teacher.username
def gender(self):
return self.teacher.sex
def phone_number(self):
return self.teacher.phone_number
| 141 | 272 | 23 |
e64b049eeb4f79a38078cf1765056519e11a4996 | 9,116 | py | Python | soundground/winman.py | bspst/soundground | 28259ed1067e0b038a2bdf4a1902ac825fbaf762 | [
"MIT"
] | 6 | 2017-12-18T10:30:15.000Z | 2021-08-05T14:09:38.000Z | soundground/winman.py | bspst/soundground | 28259ed1067e0b038a2bdf4a1902ac825fbaf762 | [
"MIT"
] | 4 | 2017-12-21T14:19:17.000Z | 2019-05-27T06:58:32.000Z | soundground/winman.py | bspst/soundground | 28259ed1067e0b038a2bdf4a1902ac825fbaf762 | [
"MIT"
] | 4 | 2017-12-18T10:29:59.000Z | 2018-06-03T09:02:04.000Z | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Window manager
Coordinates in (y, x) to be consistent with curses
"""
from soundground import metadata, utils
import curses
import time
class Value(object):
"""
Defines a number used for relative calculations
"""
def apply(self, target):
"""
Applies the percentage value to a target
"""
if type(self) is Value:
return int(round((self.value / 100) * target) + self.bias)
else:
return int(round(self))
class WindowGroup(object):
"""
A group of windows
"""
def __init__(self, stdscr):
"""
Initialization
"""
self.windows = {}
self.stdscr = stdscr
self.extra_draws = []
def __getitem__(self, name):
"""
Returns a window by its name
"""
return self.windows[name].window
def draw(self):
"""
Refresh all windows
"""
self.stdscr.clear()
for name in self.windows:
window = self.windows[name].window
window.overwrite(self.stdscr)
window.noutrefresh()
# Also refresh extra stuff (e.g. SelectableList)
for instance in self.extra_draws:
instance.draw()
curses.doupdate()
def resize(self):
"""
Resizes windows based on their percent values
"""
curses.endwin()
height, width = self.stdscr.getmaxyx()
self.stdscr.move(height - 1, 0)
for name in self.windows:
window = self.windows[name]
window.resize(height, width)
self.draw()
def create_window(self, name, y, x, h, w):
"""
Creates a new window, accepting either integer or Value
"""
if name in self.windows:
raise Exception("Window exists!")
ymax, xmax = (curses.LINES, curses.COLS)
self.windows[name] = RelativeWindow(y, x, h, w, self.stdscr)
class RelativeWindow(object):
"""
Windows with relative sizes
"""
def __init__(self, y, x, h, w, stdscr):
"""
Initialize sizes
"""
self.y = y
self.x = x
self.h = h
self.w = w
self.window = curses.newwin(1, 1, 0, 0)
ymax, xmax = stdscr.getmaxyx()
self.resize(ymax, xmax)
pass
def resize(self, height, width):
"""
Resize window based on actual size
"""
new_y = Value.apply(self.y, height)
new_x = Value.apply(self.x, width)
new_height = Value.apply(self.h, height)
new_width = Value.apply(self.w, width)
self.window.resize(new_height, new_width)
self.window.mvwin(new_y, new_x)
class SelectableList(object):
"""
Implements a scrollable list with selectable items
"""
def draw(self):
"""
Redraw list
"""
self.window.clear()
height, width = self.window.getmaxyx()
for offset in range(height):
index = self.scrollpos + offset
if index >= len(self.items):
# No more items to draw
break
item = self.items[index]
# Highlight selected item
attr = curses.A_NORMAL
if self.active and index == self.selected:
attr = curses.A_REVERSE
padded = item['caption'].ljust(width)
try:
self.window.addstr(offset, 0, padded, attr)
except:
pass
self.window.refresh()
def add(self, caption, selectable=True, value=None):
"""
Add an item to the list and draws it
An item is a map with the following keys:
- caption: the text displayed on the list
- selectable: if False, the item will skip selection
- value: a custom value, could be used to specify a command to be
executed when selected
- info: some additional info
"""
if value == None:
value = caption
self.items.append({
'caption': caption,
'selectable': selectable,
'value': value,
'info': {}
})
self.draw()
def remove(self, index):
"""
Remove an item by its index
"""
self.items.pop(index)
self.draw()
def select(self, index, relative=True):
"""
Highlight an item by its index. If relative, the current selection index
will be incremented by the index parameter instead of being set.
"""
if len(self.items) < 1:
return False
if relative:
self.selected += index
else:
self.selected = index
# Make sure selection doesn't go out of bounds
if self.selected < 0:
self.selected = 0
elif self.selected >= len(self.items):
self.selected = len(self.items) - 1
# Skip unselectable items
while not self.items[self.selected]['selectable']:
if not relative:
return False
self.selected += index
# Prevent overflow
if self.selected < 0 or self.selected >= len(self.items):
self.selected -= 2 * index
# Update scroll position
height, width = self.window.getmaxyx()
if self.selected + 1 >= self.scrollpos + height:
self.scrollpos = self.selected - height + 1
elif self.selected < self.scrollpos:
self.scrollpos = self.selected
self.draw()
class StatusLine(object):
"""
Manages the bottom status bar text
"""
SYM_PLAY = u"\u25B6"
SYM_PAUSE = u"\u23F8"
def draw(self):
"""
Redraw status bar
"""
self.window.erase()
# Fetch some parameters
playing = self.SYM_PLAY if self.player.is_playing() else self.SYM_PAUSE
title = self.player.get_title()
t_total = utils.format_millis(self.player.get_length())
t_now = utils.format_millis(self.player.get_position() * self.player.get_length())
vol = self.player.audio_get_volume()
# Format params
text = "[ {} ] {} [{}/{}] | Vol: {}"
formatted = text.format(playing, title, t_now, t_total, vol)
# Override status text if present
if self.override_text != None and self.override_cycles > 0:
formatted = self.override_text
self.override_cycles -= 1
# Draw to screen
try:
self.window.addstr(0, 0, formatted)
self.window.refresh()
except:
pass
def notify(self, text):
"""
Shows text in the status bar until next refresh or manually dismissed
"""
self.override_text = text
self.override_cycles = 30
self.draw()
def dismiss(self):
"""
Dismiss notification text
"""
self.override_cycles = 0
self.draw()
def prompt(self, text, hidden=False):
"""
Prompts the user for input
Keystrokes will be hidden if hidden is True
"""
import curses.textpad
self.prompting = True
self.prompt_hidden = hidden
self.window.clear()
try:
self.window.addstr(0, 0, text)
self.window.refresh()
except:
pass
box = curses.textpad.Textbox(self.window)
box.edit(self._prompt_validator)
while self.prompting:
# Block until user finishes input
time.sleep(0.1)
if hidden:
return self.prompt_value
else:
return box.gather()[len(text):].strip()
def _prompt_validator(self, char):
"""
Listens for keystrokes on prompt
"""
if char == 10:
# Line feed (Enter/Return)
self.prompting = False
return char
# If hidden (password mode)
if self.prompt_hidden:
if char == curses.KEY_BACKSPACE:
# Backspace
self.prompt_value = self.prompt_value[:-1]
return char
if char < 32 or char > 126:
# Only allow printable characters
return 0
self.prompt_value += chr(char)
# Replace printable characters with asterisks
return ord('*')
self.prompt_value = ''
return char
| 26.270893 | 90 | 0.541904 | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
Window manager
Coordinates in (y, x) to be consistent with curses
"""
from soundground import metadata, utils
import curses
import time
class Value(object):
"""
Defines a number used for relative calculations
"""
def __init__(self, percent_value, absolute_bias=0):
self.value = percent_value
self.bias = absolute_bias
def apply(self, target):
"""
Applies the percentage value to a target
"""
if type(self) is Value:
return int(round((self.value / 100) * target) + self.bias)
else:
return int(round(self))
class WindowGroup(object):
"""
A group of windows
"""
def __init__(self, stdscr):
"""
Initialization
"""
self.windows = {}
self.stdscr = stdscr
self.extra_draws = []
def __getitem__(self, name):
"""
Returns a window by its name
"""
return self.windows[name].window
def draw(self):
"""
Refresh all windows
"""
self.stdscr.clear()
for name in self.windows:
window = self.windows[name].window
window.overwrite(self.stdscr)
window.noutrefresh()
# Also refresh extra stuff (e.g. SelectableList)
for instance in self.extra_draws:
instance.draw()
curses.doupdate()
def resize(self):
"""
Resizes windows based on their percent values
"""
curses.endwin()
height, width = self.stdscr.getmaxyx()
self.stdscr.move(height - 1, 0)
for name in self.windows:
window = self.windows[name]
window.resize(height, width)
self.draw()
def create_window(self, name, y, x, h, w):
"""
Creates a new window, accepting either integer or Value
"""
if name in self.windows:
raise Exception("Window exists!")
ymax, xmax = (curses.LINES, curses.COLS)
self.windows[name] = RelativeWindow(y, x, h, w, self.stdscr)
class RelativeWindow(object):
"""
Windows with relative sizes
"""
def __init__(self, y, x, h, w, stdscr):
"""
Initialize sizes
"""
self.y = y
self.x = x
self.h = h
self.w = w
self.window = curses.newwin(1, 1, 0, 0)
ymax, xmax = stdscr.getmaxyx()
self.resize(ymax, xmax)
pass
def resize(self, height, width):
"""
Resize window based on actual size
"""
new_y = Value.apply(self.y, height)
new_x = Value.apply(self.x, width)
new_height = Value.apply(self.h, height)
new_width = Value.apply(self.w, width)
self.window.resize(new_height, new_width)
self.window.mvwin(new_y, new_x)
class SelectableList(object):
"""
Implements a scrollable list with selectable items
"""
def __init__(self, window):
self.window = window
self.items = []
self.selected = 0
self.scrollpos = 0
self.active = False
def draw(self):
"""
Redraw list
"""
self.window.clear()
height, width = self.window.getmaxyx()
for offset in range(height):
index = self.scrollpos + offset
if index >= len(self.items):
# No more items to draw
break
item = self.items[index]
# Highlight selected item
attr = curses.A_NORMAL
if self.active and index == self.selected:
attr = curses.A_REVERSE
padded = item['caption'].ljust(width)
try:
self.window.addstr(offset, 0, padded, attr)
except:
pass
self.window.refresh()
def add(self, caption, selectable=True, value=None):
"""
Add an item to the list and draws it
An item is a map with the following keys:
- caption: the text displayed on the list
- selectable: if False, the item will skip selection
- value: a custom value, could be used to specify a command to be
executed when selected
- info: some additional info
"""
if value == None:
value = caption
self.items.append({
'caption': caption,
'selectable': selectable,
'value': value,
'info': {}
})
self.draw()
def remove(self, index):
"""
Remove an item by its index
"""
self.items.pop(index)
self.draw()
def select(self, index, relative=True):
"""
Highlight an item by its index. If relative, the current selection index
will be incremented by the index parameter instead of being set.
"""
if len(self.items) < 1:
return False
if relative:
self.selected += index
else:
self.selected = index
# Make sure selection doesn't go out of bounds
if self.selected < 0:
self.selected = 0
elif self.selected >= len(self.items):
self.selected = len(self.items) - 1
# Skip unselectable items
while not self.items[self.selected]['selectable']:
if not relative:
return False
self.selected += index
# Prevent overflow
if self.selected < 0 or self.selected >= len(self.items):
self.selected -= 2 * index
# Update scroll position
height, width = self.window.getmaxyx()
if self.selected + 1 >= self.scrollpos + height:
self.scrollpos = self.selected - height + 1
elif self.selected < self.scrollpos:
self.scrollpos = self.selected
self.draw()
class StatusLine(object):
"""
Manages the bottom status bar text
"""
SYM_PLAY = u"\u25B6"
SYM_PAUSE = u"\u23F8"
def __init__(self, window, player):
self.window = window
self.player = player
self.override_text = None
self.override_cycles = 0
self.prompting = False
self.prompt_hidden = False
self.prompt_value = ''
def draw(self):
"""
Redraw status bar
"""
self.window.erase()
# Fetch some parameters
playing = self.SYM_PLAY if self.player.is_playing() else self.SYM_PAUSE
title = self.player.get_title()
t_total = utils.format_millis(self.player.get_length())
t_now = utils.format_millis(self.player.get_position() * self.player.get_length())
vol = self.player.audio_get_volume()
# Format params
text = "[ {} ] {} [{}/{}] | Vol: {}"
formatted = text.format(playing, title, t_now, t_total, vol)
# Override status text if present
if self.override_text != None and self.override_cycles > 0:
formatted = self.override_text
self.override_cycles -= 1
# Draw to screen
try:
self.window.addstr(0, 0, formatted)
self.window.refresh()
except:
pass
def notify(self, text):
"""
Shows text in the status bar until next refresh or manually dismissed
"""
self.override_text = text
self.override_cycles = 30
self.draw()
def dismiss(self):
"""
Dismiss notification text
"""
self.override_cycles = 0
self.draw()
def prompt(self, text, hidden=False):
"""
Prompts the user for input
Keystrokes will be hidden if hidden is True
"""
import curses.textpad
self.prompting = True
self.prompt_hidden = hidden
self.window.clear()
try:
self.window.addstr(0, 0, text)
self.window.refresh()
except:
pass
box = curses.textpad.Textbox(self.window)
box.edit(self._prompt_validator)
while self.prompting:
# Block until user finishes input
time.sleep(0.1)
if hidden:
return self.prompt_value
else:
return box.gather()[len(text):].strip()
def _prompt_validator(self, char):
"""
Listens for keystrokes on prompt
"""
if char == 10:
# Line feed (Enter/Return)
self.prompting = False
return char
# If hidden (password mode)
if self.prompt_hidden:
if char == curses.KEY_BACKSPACE:
# Backspace
self.prompt_value = self.prompt_value[:-1]
return char
if char < 32 or char > 126:
# Only allow printable characters
return 0
self.prompt_value += chr(char)
# Replace printable characters with asterisks
return ord('*')
self.prompt_value = ''
return char
| 476 | 0 | 79 |
2bab3a69f2b36620531849cf6227007d9d7f6a7a | 147 | py | Python | python/cuxfilter/charts/datashader/custom_extensions/__init__.py | bryevdv/cuxfilter | 7d26792cc97dbf1caae77e6e3c7429777846b5cf | [
"Apache-2.0"
] | 201 | 2018-12-21T18:32:40.000Z | 2022-03-22T11:50:29.000Z | python/cuxfilter/charts/datashader/custom_extensions/__init__.py | bryevdv/cuxfilter | 7d26792cc97dbf1caae77e6e3c7429777846b5cf | [
"Apache-2.0"
] | 258 | 2018-12-27T07:37:50.000Z | 2022-03-31T20:01:32.000Z | python/cuxfilter/charts/datashader/custom_extensions/__init__.py | bryevdv/cuxfilter | 7d26792cc97dbf1caae77e6e3c7429777846b5cf | [
"Apache-2.0"
] | 51 | 2019-01-10T19:03:09.000Z | 2022-03-08T01:37:11.000Z | from .interactive_image import InteractiveImage
from .graph_inspect_widget import CustomInspectTool
from .graph_assets import calc_connected_edges
| 36.75 | 51 | 0.897959 | from .interactive_image import InteractiveImage
from .graph_inspect_widget import CustomInspectTool
from .graph_assets import calc_connected_edges
| 0 | 0 | 0 |
49dad87a72c5c246404626aca65756c9887f9335 | 2,292 | py | Python | setup.py | KuangDD/phkit | de6d12e6718b238714d233607cecd8e7df8436ce | [
"MIT"
] | 113 | 2020-02-17T14:02:26.000Z | 2021-08-06T07:43:10.000Z | setup.py | kuangdd/phkit | b4247416b5f0aa1f1522c6b1cd0e613c476491b2 | [
"MIT"
] | 2 | 2020-04-15T02:00:00.000Z | 2020-06-09T09:14:16.000Z | setup.py | KuangDD/phkit | de6d12e6718b238714d233607cecd8e7df8436ce | [
"MIT"
] | 26 | 2020-04-24T03:34:37.000Z | 2021-08-05T04:47:08.000Z | #!usr/bin/env python
# -*- coding: utf-8 -*-
# author: kuangdd
# date: 2019/12/15
"""
语音处理工具箱。
生成whl格式安装包：python setup.py bdist_wheel
直接上传pypi：python setup.py sdist upload
用twine上传pypi：
生成安装包：python setup.py bdist_wheel
上传安装包：twine upload dist/phkit-0.3.0-py3-none-any.whl
注意：需要在home目录下建立.pypirc配置文件，文件内容格式：
[distutils]
index-servers=pypi
[pypi]
repository = https://upload.pypi.org/legacy/
username: admin
password: admin
"""
from setuptools import setup, find_packages
import os
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(os.path.splitext(os.path.basename(__file__))[0])
install_requires = ['pypinyin>=0.41.0', 'hanziconv', 'jieba>=0.42.1', 'tqdm', 'inflect', 'unidecode']
requires = install_requires
pip_install()
phkit_doc = create_readme()
from phkit import __version__ as phkit_version
setup(
name="phkit",
version=phkit_version,
author="kuangdd",
author_email="kuangdd@foxmail.com",
description="phoneme toolkit",
long_description=phkit_doc,
long_description_content_type="text/markdown",
url="https://github.com/KuangDD/phkit",
packages=find_packages(exclude=['contrib', 'docs', 'tests*']),
install_requires=install_requires, # 指定项目最低限度需要运行的依赖项
python_requires='>=3.5', # python的依赖关系
package_data={
'txt': ['requirements.txt'],
'md': ['**/*.md', '*.md'],
}, # 包数据，通常是与软件包实现密切相关的数据
classifiers=[
'Intended Audience :: Developers',
'Topic :: Software Development :: Build Tools',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
"Operating System :: OS Independent",
],
)
if __name__ == "__main__":
print(__file__)
| 26.344828 | 101 | 0.66274 | #!usr/bin/env python
# -*- coding: utf-8 -*-
# author: kuangdd
# date: 2019/12/15
"""
语音处理工具箱。
生成whl格式安装包：python setup.py bdist_wheel
直接上传pypi：python setup.py sdist upload
用twine上传pypi：
生成安装包：python setup.py bdist_wheel
上传安装包：twine upload dist/phkit-0.3.0-py3-none-any.whl
注意：需要在home目录下建立.pypirc配置文件，文件内容格式：
[distutils]
index-servers=pypi
[pypi]
repository = https://upload.pypi.org/legacy/
username: admin
password: admin
"""
from setuptools import setup, find_packages
import os
import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(os.path.splitext(os.path.basename(__file__))[0])
install_requires = ['pypinyin>=0.41.0', 'hanziconv', 'jieba>=0.42.1', 'tqdm', 'inflect', 'unidecode']
requires = install_requires
def create_readme():
from phkit import readme_docs
docs = []
with open("README.md", "wt", encoding="utf8") as fout:
for doc in readme_docs:
fout.write(doc)
docs.append(doc)
return "".join(docs)
def pip_install():
for pkg in install_requires + requires:
try:
os.system("pip install {}".format(pkg))
except Exception as e:
logger.info("pip install {} failed".format(pkg))
pip_install()
phkit_doc = create_readme()
from phkit import __version__ as phkit_version
setup(
name="phkit",
version=phkit_version,
author="kuangdd",
author_email="kuangdd@foxmail.com",
description="phoneme toolkit",
long_description=phkit_doc,
long_description_content_type="text/markdown",
url="https://github.com/KuangDD/phkit",
packages=find_packages(exclude=['contrib', 'docs', 'tests*']),
install_requires=install_requires, # 指定项目最低限度需要运行的依赖项
python_requires='>=3.5', # python的依赖关系
package_data={
'txt': ['requirements.txt'],
'md': ['**/*.md', '*.md'],
}, # 包数据，通常是与软件包实现密切相关的数据
classifiers=[
'Intended Audience :: Developers',
'Topic :: Software Development :: Build Tools',
'License :: OSI Approved :: MIT License',
'Programming Language :: Python :: 3.5',
'Programming Language :: Python :: 3.6',
'Programming Language :: Python :: 3.7',
"Operating System :: OS Independent",
],
)
if __name__ == "__main__":
print(__file__)
| 418 | 0 | 46 |
b15a7575c351597937eb5f79e67946659d2392f1 | 3,229 | py | Python | examples/attacks.py | dli7319/cmsc498v_convex | 5578b8f07575860a93eb4894ce9f7b224c90cba9 | [
"MIT"
] | 349 | 2017-11-03T11:55:27.000Z | 2022-03-24T10:45:21.000Z | examples/attacks.py | dli7319/cmsc498v_convex | 5578b8f07575860a93eb4894ce9f7b224c90cba9 | [
"MIT"
] | 35 | 2018-02-27T21:57:52.000Z | 2022-03-11T14:58:28.000Z | examples/attacks.py | dli7319/cmsc498v_convex | 5578b8f07575860a93eb4894ce9f7b224c90cba9 | [
"MIT"
] | 84 | 2017-12-11T04:52:08.000Z | 2021-11-03T06:27:56.000Z | import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.optim as optim
import torchvision.transforms as transforms
import torchvision.datasets as datasets
from convex_adversarial import robust_loss
| 33.28866 | 119 | 0.593373 | import torch
from torch.autograd import Variable
import torch.nn as nn
import torch.optim as optim
import torchvision.transforms as transforms
import torchvision.datasets as datasets
from convex_adversarial import robust_loss
class Flatten(nn.Module):
def forward(self, x):
return x.view(x.size(0), -1)
def mean(l):
return sum(l)/len(l)
def _fgs(model, X, y, epsilon):
opt = optim.Adam([X], lr=1e-3)
out = model(X)
ce = nn.CrossEntropyLoss()(out, y)
err = (out.data.max(1)[1] != y.data).float().sum() / X.size(0)
opt.zero_grad()
ce.backward()
eta = X.grad.data.sign()*epsilon
X_fgs = Variable(X.data + eta)
err_fgs = (model(X_fgs).data.max(1)[1] != y.data).float().sum() / X.size(0)
return err, err_fgs
def fgs(loader, model, epsilon, verbose=False, robust=False):
return attack(loader, model, epsilon, verbose=verbose, atk=_fgs,
robust=robust)
def _pgd(model, X, y, epsilon, niters=100, alpha=0.01):
out = model(X)
ce = nn.CrossEntropyLoss()(out, y)
err = (out.data.max(1)[1] != y.data).float().sum() / X.size(0)
X_pgd = Variable(X.data, requires_grad=True)
for i in range(niters):
opt = optim.Adam([X_pgd], lr=1e-3)
opt.zero_grad()
loss = nn.CrossEntropyLoss()(model(X_pgd), y)
loss.backward()
eta = alpha*X_pgd.grad.data.sign()
X_pgd = Variable(X_pgd.data + eta, requires_grad=True)
# adjust to be within [-epsilon, epsilon]
eta = torch.clamp(X_pgd.data - X.data, -epsilon, epsilon)
X_pgd = Variable(X.data + eta, requires_grad=True)
err_pgd = (model(X_pgd).data.max(1)[1] != y.data).float().sum() / X.size(0)
return err, err_pgd
def pgd(loader, model, epsilon, niters=100, alpha=0.01, verbose=False,
robust=False):
return attack(loader, model, epsilon, verbose=verbose, atk=_pgd,
robust=robust)
def attack(loader, model, epsilon, verbose=False, atk=None,
robust=False):
total_err, total_fgs, total_robust = [],[],[]
if verbose:
print("Requiring no gradients for parameters.")
for p in model.parameters():
p.requires_grad = False
for i, (X,y) in enumerate(loader):
X,y = Variable(X.cuda(), requires_grad=True), Variable(y.cuda().long())
if y.dim() == 2:
y = y.squeeze(1)
if robust:
robust_ce, robust_err = robust_loss_batch(model, epsilon, X, y, False, False)
err, err_fgs = atk(model, X, y, epsilon)
total_err.append(err)
total_fgs.append(err_fgs)
if robust:
total_robust.append(robust_err)
if verbose:
if robust:
print('err: {} | attack: {} | robust: {}'.format(err, err_fgs, robust_err))
else:
print('err: {} | attack: {}'.format(err, err_fgs))
if robust:
print('[TOTAL] err: {} | attack: {} | robust: {}'.format(mean(total_err), mean(total_fgs), mean(total_robust)))
else:
print('[TOTAL] err: {} | attack: {}'.format(mean(total_err), mean(total_fgs)))
return total_err, total_fgs, total_robust
| 2,810 | 4 | 187 |