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from app import db
from app.Collections.Courses import Courses
from app.Collections.Users import Users
from app.Collections.Departments import Departments
from pymongo.errors import WriteError
from flask import jsonify, Response
import datetime
import jwt
class departmentServices():
@staticmethod
def add_department(departmentName):
departments = db['departments']
print({"name":departmentName})
try:
departments.insert_one({"name":departmentName})
return jsonify({
"status": 200,
"result": {
"status": 201,
"message": "department created"
}
})
except WriteError as werror:
return jsonify({
"status": 200,
"result": {
"status": 400,
"message": werror._message
}
})
@staticmethod
def get_all_departments():
departments = db['departments']
return departments.find({})
|
"""
simple_calendar.py
This is an utterly hopeless calendar system, that in no way should be let near real-world pricing
applications.
Although we could later define a date object, dates for internal calculations are real numbers, with 1.0
equalling one year. This is good enough for really simple yield and price calculations.
We fall flat on our faces once we start to interact with index-linked bonds. So I am creating a simple
calendar to simulate the principles of index-linked calculations -- without doing them correctly (oops).
Copyright 2018 Brian Romanchuk
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.
"""
class SimpleCalendar360(object):
"""
This class holds the functions for a calendar that consists of:
(1) 12 months
(2) 30 days per month.
The day/month determines the fractional offset from the year.
Day/month are "1-based," like the real world.
"January 1" is associated with an offset of zero. So the date 1976.0 is "January 1, 1976."
"""
def __init__(self):
self.NumMonths = 12.
self.NumDaysPerMonth = 30.
self.NumDaysPerYear = self.NumMonths * self.NumDaysPerMonth
def GetDate(self, year, month=1, day=1):
"""
Returns the
:param year: int
:param month: int
:param day: int
:return: float
"""
return float(year) + (float(month-1)/self.NumMonths) + (float(day-1) / self.NumDaysPerYear)
def AddMonths(self, date, num_months):
"""
Shift a date by a number of months
:param date: float
:param num_months: int
:return: float
"""
# NOTE: If we get rounding issues, could do modulo-12.
return date + (float(num_months)/self.NumMonths)
class Indexation(object):
"""
Class that manages simple indexation calculations.
Probably should be done with numeric array objects, but stick with lists for now.
I want this code to be very easy to understand, with no worries about performance.
"""
def __init__(self):
self.Calendar = SimpleCalendar360()
self.IndexDateValues = []
self.ExtrapolationRate = None
def SetIndexValues(self, dates, values):
"""
Add two lists of dates/values to the
:param dates: list
:param values: list
:return:
"""
if not len(dates) == len(values):
raise ValueError('dates and values vectors not the same size')
# Not sure how to do this efficiently, do it brute force style
self.IndexDateValues = []
# Save the data as tuples
for d,v in zip(dates, values):
self.IndexDateValues.append((d, v))
self.IndexDateValues.sort()
def GetValue(self, date):
"""
Return the index value for a date
:param date: float
:return: float
"""
if len(self.IndexDateValues) == 0:
raise ValueError('No index data in object')
if date < self.IndexDateValues[0][0]:
raise ValueError('Date before start of index data')
prev_d, prev_v = self.IndexDateValues[0]
# Go through the index points, which we assume are ordered.
for d,v in self.IndexDateValues:
# Special case, we hit the new point exactly.
# This also covers the special case where the date matches the first index date exactly
if d == date:
return v
# Is date in the interval [prev_d, d]?
if date < d:
# Interpolate
fac = (date - prev_d)/(d - prev_d)
return prev_v + fac*(v - prev_v)
# Otherwise, keep going
prev_d = d
prev_v = v
# If we get here, we are outside the interval
# TODO: Add an extrapolation feature.
if self.ExtrapolationRate is None:
raise ValueError('Date greater than index data')
return prev_v*pow(1+self.ExtrapolationRate,date-prev_d)
|
# VRC Peripheral Python Library
# Written by Casey Hanner
import time
from struct import pack
from typing import Any, List, Literal, Union
from loguru import logger
import serial
class VRC_Peripheral(object):
def __init__(self, port: int, use_serial: bool = True) -> None:
self.port = port
self.PREAMBLE = (0x24, 0x50)
self.HEADER_OUTGOING = (*self.PREAMBLE, 0x3C)
self.HEADER_INCOMING = (*self.PREAMBLE, 0x3E)
self.commands = {
"SET_SERVO_OPEN_CLOSE": 0,
"SET_SERVO_MIN": 1,
"SET_SERVO_MAX": 2,
"SET_SERVO_PCT": 3,
"SET_BASE_COLOR": 4,
"SET_TEMP_COLOR": 5,
"RESET_VRC_PERIPH": 6,
"CHECK_SERVO_CONTROLLER": 7,
}
self.use_serial = use_serial
if self.use_serial:
logger.debug("Opening serial port")
self.ser = serial.Serial()
self.ser.baudrate = 115200
self.ser.port = self.port
self.ser.open()
else:
logger.debug("VRC_Peripheral: Serial Transmission is OFF")
self.shutdown: bool = False
def run(self) -> None:
while not self.shutdown:
if self.use_serial:
while self.ser.in_waiting > 0:
print(self.ser.read(1), end="")
time.sleep(0.01)
def set_base_color(self, wrgb: List[int]) -> None:
# wrgb + code = 5
if len(wrgb) != 4:
wrgb = [0, 0, 0, 0]
for i, color in enumerate(wrgb):
if not isinstance(color, int) or color > 255 or color < 0:
wrgb[i] = 0
command = self.commands["SET_BASE_COLOR"]
data = self._construct_payload(command, 1 + len(wrgb), wrgb)
if self.use_serial is True:
self.ser.write(data)
else:
logger.debug("VRC_Peripheral serial data: ")
logger.debug(data)
def set_temp_color(self, wrgb: List[int], time: float = 0.5) -> None:
# wrgb + code = 5
if len(wrgb) != 4:
wrgb = [0, 0, 0, 0]
for i, color in enumerate(wrgb):
if not isinstance(color, int) or color > 255 or color < 0:
wrgb[i] = 0
command = self.commands["SET_TEMP_COLOR"]
time_bytes = self.list_pack("<f", time)
data = self._construct_payload(
command, 1 + len(wrgb) + len(time_bytes), wrgb + time_bytes
)
if self.use_serial is True:
self.ser.write(data)
else:
logger.debug("VRC_Peripheral serial data: ")
logger.debug(data)
def set_servo_open_close(self, servo: int, action: Literal["open", "close"]) -> None:
valid_command = False
command = self.commands["SET_SERVO_OPEN_CLOSE"]
length = 3 # command + servo + action
data = []
# 128 is inflection point, over 128 == open; under 128 == close
if action == "open":
data = [servo, 150]
valid_command = True
elif action == "close":
data = [servo, 100]
valid_command = True
if valid_command:
if self.use_serial is True:
self.ser.write(self._construct_payload(command, length, data))
else:
logger.debug("VRC_Peripheral serial data: ")
logger.debug(data)
def set_servo_min(self, servo: int, minimum: float) -> None:
valid_command = False
command = self.commands["SET_SERVO_MIN"]
length = 3 # command + servo + min pwm
data = []
if isinstance(minimum, (float, int)) and minimum < 1000 and minimum > 0:
valid_command = True
data = [servo, minimum]
if valid_command:
if self.use_serial is True:
self.ser.write(self._construct_payload(command, length, data))
else:
logger.debug("VRC_Peripheral serial data: ")
logger.debug(data)
def set_servo_max(self, servo: int, maximum: float) -> None:
valid_command = False
command = self.commands["SET_SERVO_MAX"]
length = 3 # command + servo + min pwm
data = []
if isinstance(maximum, (float, int)) and maximum < 1000 and maximum > 0:
valid_command = True
data = [servo, maximum]
if valid_command:
if self.use_serial is True:
self.ser.write(self._construct_payload(command, length, data))
else:
logger.debug("VRC_Peripheral serial data: ")
logger.debug(data)
def set_servo_pct(self, servo: int, pct: float) -> None:
valid_command = False
command = self.commands["SET_SERVO_PCT"]
length = 3 # command + servo + percent
data = []
if isinstance(pct, (float, int)) and pct < 100 and pct > 0:
valid_command = True
data = [servo, int(pct)]
if valid_command:
if self.use_serial is True:
self.ser.write(self._construct_payload(command, length, data))
else:
logger.debug("VRC_Peripheral serial data: ")
logger.debug(data)
def reset_vrc_peripheral(self) -> None:
command = self.commands["RESET_VRC_PERIPH"]
length = 1 # just the reset command
if self.use_serial:
self.ser.write(self._construct_payload(command, length))
self.ser.close()
# wait for the VRC_Periph to reboot
time.sleep(5)
# try to reconnect
self.ser.open()
else:
logger.debug("VRC_Peripheral reset triggered (NO SERIAL)")
def check_servo_controller(self) -> None:
if self.use_serial:
command = self.commands["CHECK_SERVO_CONTROLLER"]
length = 1
self.ser.write(self._construct_payload(command, length))
def _construct_payload(self, code: int, size: int = 0, data: list = []):
# [$][P][>][LENGTH-HI][LENGTH-LOW][DATA][CRC]
payload = bytes()
new_data = (
("<3b", self.HEADER_OUTGOING),
(">H", [size]),
("<B", [code]),
("<%dB" % len(data), data),
)
for section in new_data:
payload += pack(section[0], *section[1])
crc = self.calc_crc(payload, len(payload))
payload += pack("<B", crc)
return payload
def list_pack(self, bit_format: Union[str, bytes], value: Any) -> List[int]:
bytez = pack(bit_format, value)
return [byte for byte in bytez]
def crc8_dvb_s2(self, crc, a):
# https://stackoverflow.com/a/52997726
crc ^= a
for _ in range(8):
if crc & 0x80:
crc = ((crc << 1) ^ 0xD5) % 256
else:
crc = (crc << 1) % 256
return crc
def calc_crc(self, string: Union[str, bytes], length: int):
crc = 0
for i in range(length):
crc = self.crc8_dvb_s2(crc, string[i])
return crc
|
from autodp.mechanism_zoo import GaussianMechanism
from autodp.fdp_bank import fDP_gaussian
import numpy as np
from absl.testing import absltest
from absl.testing import parameterized
params = [0.05, 0.1, 0.2, 0.5,1.0, 2.0,5.0, 10.0]
def _fdp_conversion(sigma):
# Using the log(1-f(fpr)) and log(- \partial f(fpr)) that are implemented dedicatedly
fpr_list = np.linspace(0, 1, 21)
# analytical gaussian implementation (privacy profile)
gm2 = GaussianMechanism(sigma, name='GM2', RDP_off=True)
# direct f-DP implementation
fdp = lambda x: fDP_gaussian({'sigma': sigma},x)
fdp_direct = fdp(fpr_list)
# the fdp is converted by numerical methods from privacy profile.
fdp_converted = np.array([gm2.get_fDP(fpr) for fpr in fpr_list])
return fdp_direct - fdp_converted
class Test_approxDP2fDP_Conversion(parameterized.TestCase):
@parameterized.parameters(p for p in params)
def test_fdp_conversion(self, sigma):
max_diff = _fdp_conversion(sigma)
self.assertSequenceAlmostEqual(max_diff, np.zeros_like(max_diff), places=4)
if __name__ == '__main__':
absltest.main()
|
from estudent import data_generator
from estudent.school import School
def run_example():
students = data_generator.generate_students()
students.sort(key=lambda student: student.grades_avg(), reverse=True)
school = School(name="Hogwart", students=students)
best_student = school.students[0]
# print(f"Oceny najlepszego ucznia: {best_student.get_final_grades()}")
print(f"Oceny najlepszego ucznia: {best_student.final_grades}")
if __name__ == '__main__':
run_example()
|
import os
import pandas as pd
from sklearn.metrics.pairwise import cosine_similarity
from sklearn.feature_extraction.text import CountVectorizer
# code to read the xlsx File
filepath = os.path.abspath(os.path.dirname(__name__))
sheet_name = 'commonwordswithIPA'
filename = filepath + '/application/resources/recommender/files/AccentGURU.xlsx'
df = pd.read_excel(filename, sheet_name=sheet_name)
df = df[['word', 'category', 'word_s1', 'word_s2', 'word_s3', 'word_s4', 'phase', 'primary_syllable_stress']]
df.set_index('word', inplace=True)
df['bag_of_words'] = ''
columns = df.columns
for index, row in df.iterrows():
data = ''
for col in columns:
df[col] = df[col].astype(str)
df[col] = df[col].map(lambda x: x.lower())
data = data + row[col] + ' '
row['bag_of_words'] = data
df.drop(columns=[col for col in df.columns if col != 'bag_of_words'], inplace=True)
count = CountVectorizer()
count_matrix = count.fit_transform(df['bag_of_words'])
indices = pd.Series(df.index)
def recommendations(words):
recommended_words = []
cosine_sim = cosine_similarity(count_matrix, count_matrix)
# getting the index of the words that matches the word
idx = indices[indices == words].index[0]
# creating a Series with the similarity scores in descending order
score_series = pd.Series(cosine_sim[idx]).sort_values(ascending=False)
# getting the indexes of the 10 most similar words
top_10_indexes = list(score_series.iloc[1:6].index)
# populating the list with the words of the best matching words
for i in top_10_indexes:
recommended_words.append(list(df.index)[i])
return recommended_words
|
from coreapi import codecs, exceptions, transports
from coreapi.compat import string_types
from coreapi.document import Document, Link
from coreapi.utils import determine_transport, get_installed_codecs
import collections
import itypes
LinkAncestor = collections.namedtuple('LinkAncestor', ['document', 'keys'])
def _lookup_link(document, keys):
"""
Validates that keys looking up a link are correct.
Returns a two-tuple of (link, link_ancestors).
"""
if not isinstance(keys, (list, tuple)):
msg = "'keys' must be a list of strings or ints."
raise TypeError(msg)
if any([
not isinstance(key, string_types) and not isinstance(key, int)
for key in keys
]):
raise TypeError("'keys' must be a list of strings or ints.")
# Determine the link node being acted on, and its parent document.
# 'node' is the link we're calling the action for.
# 'document_keys' is the list of keys to the link's parent document.
node = document
link_ancestors = [LinkAncestor(document=document, keys=[])]
for idx, key in enumerate(keys):
try:
node = node[key]
except (KeyError, IndexError, TypeError):
index_string = ''.join('[%s]' % repr(key).strip('u') for key in keys)
msg = 'Index %s did not reference a link. Key %s was not found.'
raise exceptions.LinkLookupError(msg % (index_string, repr(key).strip('u')))
if isinstance(node, Document):
ancestor = LinkAncestor(document=node, keys=keys[:idx + 1])
link_ancestors.append(ancestor)
# Ensure that we've correctly indexed into a link.
if not isinstance(node, Link):
index_string = ''.join('[%s]' % repr(key).strip('u') for key in keys)
msg = "Can only call 'action' on a Link. Index %s returned type '%s'."
raise exceptions.LinkLookupError(
msg % (index_string, type(node).__name__)
)
return (node, link_ancestors)
def _validate_parameters(link, parameters):
"""
Ensure that parameters passed to the link are correct.
Raises a `ParameterError` if any parameters do not validate.
"""
provided = set(parameters.keys())
required = set([
field.name for field in link.fields if field.required
])
optional = set([
field.name for field in link.fields if not field.required
])
errors = {}
# Determine if any required field names not supplied.
missing = required - provided
for item in missing:
errors[item] = 'This parameter is required.'
# Determine any parameter names supplied that are not valid.
unexpected = provided - (optional | required)
for item in unexpected:
errors[item] = 'Unknown parameter.'
if errors:
raise exceptions.ParameterError(errors)
def get_default_decoders():
return [
codecs.CoreJSONCodec(),
codecs.JSONCodec(),
codecs.TextCodec(),
codecs.DownloadCodec()
]
def get_default_transports(auth=None, session=None):
return [
transports.HTTPTransport(auth=auth, session=session)
]
class Client(itypes.Object):
def __init__(self, decoders=None, transports=None, auth=None, session=None):
assert transports is None or auth is None, (
"Cannot specify both 'auth' and 'transports'. "
"When specifying transport instances explicitly you should set "
"the authentication directly on the transport."
)
if decoders is None:
decoders = get_default_decoders()
if transports is None:
transports = get_default_transports(auth=auth, session=session)
self._decoders = itypes.List(decoders)
self._transports = itypes.List(transports)
@property
def decoders(self):
return self._decoders
@property
def transports(self):
return self._transports
def get(self, url, format=None, force_codec=False):
link = Link(url, action='get')
decoders = self.decoders
if format:
force_codec = True
decoders = [decoder for decoder in self.decoders if decoder.format == format]
if not decoders:
installed_codecs = get_installed_codecs()
if format in installed_codecs:
decoders = [installed_codecs[format]]
else:
raise ValueError("No decoder available with format='%s'" % format)
# Perform the action, and return a new document.
transport = determine_transport(self.transports, link.url)
return transport.transition(link, decoders, force_codec=force_codec)
def reload(self, document, format=None, force_codec=False):
# Fallback for v1.x. To be removed in favour of explict `get` style.
return self.get(document.url, format=format, force_codec=force_codec)
def action(self, document, keys, params=None, validate=True, overrides=None,
action=None, encoding=None, transform=None):
if (action is not None) or (encoding is not None) or (transform is not None):
# Fallback for v1.x overrides.
# Will be removed at some point, most likely in a 2.1 release.
if overrides is None:
overrides = {}
if action is not None:
overrides['action'] = action
if encoding is not None:
overrides['encoding'] = encoding
if transform is not None:
overrides['transform'] = transform
if isinstance(keys, string_types):
keys = [keys]
if params is None:
params = {}
# Validate the keys and link parameters.
link, link_ancestors = _lookup_link(document, keys)
if validate:
_validate_parameters(link, params)
if overrides:
# Handle any explicit overrides.
url = overrides.get('url', link.url)
action = overrides.get('action', link.action)
encoding = overrides.get('encoding', link.encoding)
transform = overrides.get('transform', link.transform)
fields = overrides.get('fields', link.fields)
link = Link(url, action=action, encoding=encoding, transform=transform, fields=fields)
# Perform the action, and return a new document.
transport = determine_transport(self.transports, link.url)
return transport.transition(link, self.decoders, params=params, link_ancestors=link_ancestors)
|
import abc
from munch import Munch
from .path import Path
from .serialization import YAMLMixin
from .storage import Storage
from .utils import import_class as _import_class
class Persistent(Storage, YAMLMixin, abc.ABC):
"""Base class for persistent storages.
A persistent storage must expose two *gateways*, one for reading from it, and one for writing to it. These will be
defined in the form of two abstract property methods which must be overridden.
Attributes
----------
path: Path
Contains details about the provided path.
Parameters
----------
plainStorage: Munch
Description for the persistent storage.
"""
def __init__(self, plainStorage, settings):
self.path = Path(plainStorage.path, settings)
self.format = plainStorage.get('format')
def extension(self):
if self.format is not None:
extension, *compression = self.format.split('.')
return f'.{extension}', (f'.{compression[0]}' if compression else None)
return self.path.extension()
@abc.abstractmethod
def read(self):
"""
A context manager for reading data from the file.
"""
pass
@abc.abstractmethod
def write(self):
"""
A context manager for writing data to the file.
"""
pass
def toDict(self):
return {'path': self.path.raw}
def import_class(identifier):
return _import_class('persistents', identifier)
|
import torch
import numpy as np
import math
from . import common_functions as c_f
# input must be 2D
def logsumexp(x, keep_mask=None, add_one=True, dim=1):
if keep_mask is not None:
x = x.masked_fill(~keep_mask, c_f.neg_inf(x.dtype))
if add_one:
zeros = torch.zeros(x.size(dim-1), dtype=x.dtype, device=x.device).unsqueeze(dim)
x = torch.cat([x,zeros], dim=dim)
output = torch.logsumexp(x, dim=dim, keepdim=True)
if keep_mask is not None:
output = output.masked_fill(~torch.any(keep_mask, dim=dim, keepdim=True), 0)
return output
def meshgrid_from_sizes(x, y, dim=0):
a = torch.arange(x.size(dim)).to(x.device)
b = torch.arange(y.size(dim)).to(y.device)
return torch.meshgrid(a,b)
def get_all_pairs_indices(labels, ref_labels=None):
"""
Given a tensor of labels, this will return 4 tensors.
The first 2 tensors are the indices which form all positive pairs
The second 2 tensors are the indices which form all negative pairs
"""
if ref_labels is None:
ref_labels = labels
labels1 = labels.unsqueeze(1)
labels2 = ref_labels.unsqueeze(0)
matches = (labels1 == labels2).byte()
diffs = matches ^ 1
if ref_labels is labels:
matches.fill_diagonal_(0)
a1_idx, p_idx = torch.where(matches)
a2_idx, n_idx = torch.where(diffs)
return a1_idx, p_idx, a2_idx, n_idx
def convert_to_pairs(indices_tuple, labels):
"""
This returns anchor-positive and anchor-negative indices,
regardless of what the input indices_tuple is
Args:
indices_tuple: tuple of tensors. Each tensor is 1d and specifies indices
within a batch
labels: a tensor which has the label for each element in a batch
"""
if indices_tuple is None:
return get_all_pairs_indices(labels)
elif len(indices_tuple) == 4:
return indices_tuple
else:
a, p, n = indices_tuple
return a, p, a, n
def convert_to_pos_pairs_with_unique_labels(indices_tuple, labels):
a, p, _, _ = convert_to_pairs(indices_tuple, labels)
_, unique_idx = np.unique(labels[a].cpu().numpy(), return_index=True)
return a[unique_idx], p[unique_idx]
def pos_pairs_from_tuple(indices_tuple):
return indices_tuple[:2]
def neg_pairs_from_tuple(indices_tuple):
return indices_tuple[2:]
def get_all_triplets_indices(labels, ref_labels=None):
if ref_labels is None:
ref_labels = labels
labels1 = labels.unsqueeze(1)
labels2 = ref_labels.unsqueeze(0)
matches = (labels1 == labels2).byte()
diffs = matches ^ 1
if ref_labels is labels:
matches.fill_diagonal_(0)
triplets = matches.unsqueeze(2)*diffs.unsqueeze(1)
return torch.where(triplets)
# sample triplets, with a weighted distribution if weights is specified.
def get_random_triplet_indices(labels, ref_labels=None, t_per_anchor=None, weights=None):
a_idx, p_idx, n_idx = [], [], []
labels_device = labels.device
ref_labels = labels if ref_labels is None else ref_labels
ref_labels_is_labels = ref_labels is labels
labels = labels.cpu().numpy()
ref_labels = ref_labels.cpu().numpy()
batch_size = ref_labels.shape[0]
indices = np.arange(batch_size)
for i, label in enumerate(labels):
all_pos_pair_mask = ref_labels == label
if ref_labels_is_labels:
all_pos_pair_mask &= indices != i
all_pos_pair_idx = np.where(all_pos_pair_mask)[0]
curr_label_count = len(all_pos_pair_idx)
if curr_label_count == 0:
continue
k = curr_label_count if t_per_anchor is None else t_per_anchor
if weights is not None and not np.any(np.isnan(weights[i])):
n_idx += c_f.NUMPY_RANDOM.choice(batch_size, k, p=weights[i]).tolist()
else:
possible_n_idx = list(np.where(ref_labels != label)[0])
n_idx += c_f.NUMPY_RANDOM.choice(possible_n_idx, k).tolist()
a_idx.extend([i] * k)
curr_p_idx = c_f.safe_random_choice(all_pos_pair_idx, k)
p_idx.extend(curr_p_idx.tolist())
a_idx = torch.LongTensor(a_idx).to(labels_device)
p_idx = torch.LongTensor(p_idx).to(labels_device)
n_idx = torch.LongTensor(n_idx).to(labels_device)
return a_idx, p_idx, n_idx
def repeat_to_match_size(smaller_set, larger_size, smaller_size):
num_repeat = math.ceil(float(larger_size) / float(smaller_size))
return smaller_set.repeat(num_repeat)[:larger_size]
def matched_size_indices(curr_p_idx, curr_n_idx):
num_pos_pairs = len(curr_p_idx)
num_neg_pairs = len(curr_n_idx)
if num_pos_pairs > num_neg_pairs:
n_idx = repeat_to_match_size(curr_n_idx, num_pos_pairs, num_neg_pairs)
p_idx = curr_p_idx
else:
p_idx = repeat_to_match_size(curr_p_idx, num_neg_pairs, num_pos_pairs)
n_idx = curr_n_idx
return p_idx, n_idx
def convert_to_triplets(indices_tuple, labels, t_per_anchor=100):
"""
This returns anchor-positive-negative triplets
regardless of what the input indices_tuple is
"""
if indices_tuple is None:
if t_per_anchor == "all":
return get_all_triplets_indices(labels)
else:
return get_random_triplet_indices(labels, t_per_anchor=t_per_anchor)
elif len(indices_tuple) == 3:
return indices_tuple
else:
a_out, p_out, n_out = [], [], []
a1, p, a2, n = indices_tuple
empty_output = [torch.tensor([]).to(labels.device)] * 3
if len(a1) == 0 or len(a2) == 0:
return empty_output
for i in range(len(labels)):
pos_idx = torch.where(a1 == i)[0]
neg_idx = torch.where(a2 == i)[0]
if len(pos_idx) > 0 and len(neg_idx) > 0:
p_idx = p[pos_idx]
n_idx = n[neg_idx]
p_idx, n_idx = matched_size_indices(p_idx, n_idx)
a_idx = torch.ones_like(c_f.longest_list([p_idx, n_idx])) * i
a_out.append(a_idx)
p_out.append(p_idx)
n_out.append(n_idx)
try:
return [torch.cat(x, dim=0) for x in [a_out, p_out, n_out]]
except RuntimeError:
# assert that the exception was caused by disjoint a1 and a2
# otherwise something has gone wrong
assert len(np.intersect1d(a1, a2)) == 0
return empty_output
def convert_to_weights(indices_tuple, labels, dtype):
"""
Returns a weight for each batch element, based on
how many times they appear in indices_tuple.
"""
weights = torch.zeros_like(labels).type(dtype)
if indices_tuple is None:
return weights + 1
if all(len(x) == 0 for x in indices_tuple):
return weights + 1
indices, counts = torch.unique(torch.cat(indices_tuple, dim=0), return_counts=True)
counts = (counts.type(dtype) / torch.sum(counts))
weights[indices] = counts / torch.max(counts)
return weights
|
from invoke import task
import requests
from os.path import join
from subprocess import run
from tasks.util.env import WASM_BUILD_DIR, WASM_INSTALL_DIR, clean_dir
from tasks.util.faasm import get_faasm_upload_host_port
from tasks.lammps.env import (
LAMMPS_DIR,
LAMMPS_FAASM_USER,
LAMMPS_FAASM_FUNC,
)
CMAKE_TOOLCHAIN_FILE = "/usr/local/faasm/toolchain/tools/WasiToolchain.cmake"
@task(default=True)
def build(ctx, clean=False, verbose=False):
"""
Build LAMMPS to wasm
"""
cmake_dir = join(LAMMPS_DIR, "cmake")
clean_dir(WASM_BUILD_DIR, clean)
clean_dir(WASM_INSTALL_DIR, clean)
cmake_cmd = [
"cmake",
"-GNinja",
"-DLAMMPS_FAASM=ON",
"-DCMAKE_TOOLCHAIN_FILE={}".format(CMAKE_TOOLCHAIN_FILE),
"-DCMAKE_BUILD_TYPE=Release",
"-DCMAKE_INSTALL_PREFIX={}".format(WASM_INSTALL_DIR),
cmake_dir,
]
cmake_str = " ".join(cmake_cmd)
print(cmake_str)
res = run(cmake_str, shell=True, cwd=WASM_BUILD_DIR)
if res.returncode != 0:
raise RuntimeError("LAMMPS CMake config failed")
res = run("ninja", shell=True, cwd=WASM_BUILD_DIR)
if res.returncode != 0:
raise RuntimeError("LAMMPS build failed")
res = run("ninja install", shell=True, cwd=WASM_BUILD_DIR)
if res.returncode != 0:
raise RuntimeError("LAMMPS install failed")
@task
def upload(ctx):
"""
Upload the LAMMPS function to Faasm
"""
wasm_file = join(WASM_INSTALL_DIR, "bin", "lmp")
host, port = get_faasm_upload_host_port()
url = "http://{}:{}/f/{}/{}".format(
host, port, LAMMPS_FAASM_USER, LAMMPS_FAASM_FUNC
)
print("Putting function to {}".format(url))
response = requests.put(url, data=open(wasm_file, "rb"))
print("Response {}: {}".format(response.status_code, response.text))
|
import logging
import pathlib
import torch.utils.data as data
import torchvision.transforms as T
from torchvision.datasets import ImageFolder
from codebase.torchutils.distributed import world_size
from ..utils import get_samplers
_logger = logging.getLogger(__name__)
def get_train_transforms(crop_size, mean, std, is_training):
pipelines = []
if is_training:
pipelines.append(T.RandomResizedCrop(crop_size))
pipelines.append(T.RandomHorizontalFlip())
else:
pipelines.append(T.Resize(int(crop_size/7*8)))
pipelines.append(T.CenterCrop(crop_size))
pipelines.append(T.ToTensor())
pipelines.append(T.Normalize(mean=mean, std=std))
return T.Compose(pipelines)
def _build_imagenet_loader(root, is_training, image_size, mean, std, batch_size, num_workers):
transforms = get_train_transforms(image_size, mean, std, is_training)
dataset = ImageFolder(pathlib.Path(root)/("train" if is_training else "val"), transform=transforms)
sampler = get_samplers(dataset, is_training)
loader = data.DataLoader(dataset, batch_size=batch_size,
shuffle=(sampler is None),
sampler=sampler,
num_workers=num_workers,
persistent_workers=True,
drop_last=is_training)
_logger.info(f"Loading ImageNet dataset using torchvision from folder"
f" with {'trainset' if is_training else 'valset'} (len={len(dataset)})")
_logger.info(f"Total batch_size={batch_size*world_size()} with world_size={world_size()}, run with {len(loader)} iters per epoch")
return loader
def build_imagenet_loader(root, image_size, mean, std, batch_size, num_workers):
return _build_imagenet_loader(root, True, image_size, mean, std, batch_size, num_workers),\
_build_imagenet_loader(root, False, image_size, mean, std, batch_size, num_workers)
|
import psycopg2
from faker import Faker
import os
import traceback
import psycopg2.extras
import random
import string
def connect_db():
db_name = os.getenv('COMPANY_NAME', 'apporbit')
user = os.getenv('POSTGRES_USER', 'odoo')
passwd = os.getenv('POSTGRES_PASSWORD', 'odoo')
host = os.getenv('DB_TIER', 'ds2db')
conn = psycopg2.connect("dbname='{0}' user='{1}' host='{2}' password='{3}'".format(db_name,
user,
host,
passwd))
return conn
def get_records(query):
conn = connect_db()
cur = conn.cursor(cursor_factory=psycopg2.extras.DictCursor)
cur.execute(query)
rows = cur.fetchall()
return rows
def update_passports(rows):
conn = connect_db()
cur = conn.cursor()
for row in rows:
if row[1]:
cur.execute("UPDATE hr_employee SET passport_id='{0}' WHERE id={1}".format(row[1], row[0]))
conn.commit()
cur.close()
def update_work_phone(rows):
conn = connect_db()
cur = conn.cursor()
for row in rows:
if row[1]:
cur.execute("UPDATE hr_employee SET work_phone='{0}' WHERE id={1}".format(row[1], row[0]))
conn.commit()
cur.close()
def update_bank_accounts(rows):
conn = connect_db()
cur = conn.cursor()
for row in rows:
if row[1]:
cur.execute("UPDATE res_partner_bank SET acc_number='{0}' WHERE id={1}".format(row[1], row[0]))
conn.commit()
cur.close()
def mask_passports():
rows = get_records("SELECT id, passport_id FROM hr_employee")
print "Rows for passport are " + str(rows)
for row in rows:
row[1] = ''.join(random.choice(string.digits) for _ in range(8))
print "Passports rows after masking " + str(rows)
update_passports(rows)
def mask_work_phone():
rows = get_records("SELECT id, work_phone FROM hr_employee")
print "Rows for workphone are " + str(rows)
for row in rows:
row[1] = '+' + ''.join(random.choice(string.digits) for _ in range(8))
print "work_phone rows after masking " + str(rows)
update_work_phone(rows)
def mask_bank_account():
rows = get_records("SELECT id, acc_number FROM res_partner_bank ")
print "Rows for bank accounts are " + str(rows)
for row in rows:
if row[1]:
row[1] = ''.join(random.choice(string.digits) for _ in range(10))
print "Bank account rows after masking " + str(rows)
update_bank_accounts(rows)
def mask_data():
try:
mask_passports()
mask_work_phone()
mask_bank_account()
with open("/tmp/result", 'w') as outf:
outf.write("success")
except:
print "Failed to mask data"
traceback.print_exc()
with open("result", 'w') as outf:
outf.write("failure")
if __name__ == '__main__':
mask_data()
|
import argparse
from dataclasses import (
dataclass,
)
import logging
from pathlib import (
Path,
)
from typing import (
Any,
FrozenSet,
IO,
Iterable,
NamedTuple,
Optional,
Union,
)
import docker
from more_itertools import (
one,
)
import requirements
from requirements.requirement import (
Requirement,
)
from azul import (
RequirementError,
cached_property,
config,
reject,
require,
)
from azul.logging import (
configure_script_logging,
)
log = logging.getLogger(__name__)
Version = str
class Versions(FrozenSet[Version]):
def __new__(cls, *versions: Version) -> Any:
return super().__new__(cls, versions)
def __str__(self) -> str:
return ','.join('==' + v for v in self)
def __or__(self, other: 'Versions') -> 'Versions':
# We need to hand-implement this because the overridden base class
# method returns a base class instance, unfortunately.
return type(self)(*self, *other)
@dataclass(frozen=True)
class PinnedRequirement:
name: str
versions: Versions = Versions()
@classmethod
def create(cls, req: Requirement) -> Optional['PinnedRequirement']:
if req.specifier:
op, version = one(req.specs)
assert op == '=='
return cls(name=req.name.lower(), versions=Versions(version))
elif req.vcs:
reject(req.revision is None, 'VCS requirements must carry a specific revision', req)
return cls(name=req.name.lower())
elif req.recursive:
return None
else:
raise RequirementError('Unable to handle requirement', req)
def __or__(self, other: Optional['PinnedRequirement']) -> 'PinnedRequirement':
assert self.name == other.name
if self.versions == other.versions:
return self
else:
return PinnedRequirement(name=other.name,
versions=self.versions | other.versions)
def __str__(self) -> str:
assert self.versions
return self.name + str(self.versions)
class PinnedRequirements:
def __init__(self, reqs: Iterable[Optional[PinnedRequirement]]) -> None:
reqs = list(filter(None, reqs))
self._reqs = {req.name: req for req in reqs}
assert len(reqs) == len(self._reqs)
def __and__(self, other: 'PinnedRequirements') -> 'PinnedRequirements':
def lookup(req: PinnedRequirement) -> Optional[PinnedRequirement]:
try:
other_req = other[req]
except KeyError:
return None
else:
return req | other_req
return PinnedRequirements(lookup(req) for req in self)
def __sub__(self, other: 'PinnedRequirements') -> 'PinnedRequirements':
return PinnedRequirements(req for req in self if req not in other)
def __le__(self, other: 'PinnedRequirements') -> bool:
return self._reqs.keys() <= other._reqs.keys()
def __iter__(self):
return iter(self._reqs.values())
def __contains__(self, item: Union[str, PinnedRequirement]):
return self._name(item) in self._reqs
def _name(self, item: Union[str, PinnedRequirement]) -> str:
return item.name if isinstance(item, PinnedRequirement) else item
def __getitem__(self, item: Union[str, PinnedRequirement]) -> PinnedRequirement:
return self._reqs[self._name(item)]
def __setitem__(self, item: Union[str, PinnedRequirement], req: PinnedRequirement) -> None:
self._reqs[self._name(item)] = req
def __repr__(self) -> str:
return f'Requirements({repr(list(self._reqs.values()))})'
def __str__(self) -> str:
return '\n'.join(map(str, self._reqs.values()))
def __bool__(self):
return bool(self._reqs)
class Qualifier(NamedTuple):
name: str
extension: str
image: Optional[str]
@dataclass
class Main:
build_image: str
runtime_image: str
@cached_property
def pip(self): return Qualifier(name='pip',
extension='.pip',
image=None)
@cached_property
def runtime(self): return Qualifier(name='runtime',
extension='',
image=self.runtime_image)
@cached_property
def build(self): return Qualifier(name='build',
extension='.dev',
image=self.build_image)
@cached_property
def project_root(self):
return Path(config.project_root)
@cached_property
def docker(self):
return docker.from_env()
def run(self):
pip_deps = self.get_direct_reqs(self.pip)
direct_runtime_reqs = self.get_direct_reqs(self.runtime)
direct_build_reqs = self.get_direct_reqs(self.build)
dupes = direct_build_reqs & direct_runtime_reqs
require(not dupes, 'Some requirements are declared as both run and build time', dupes)
build_reqs = self.get_reqs(self.build) - pip_deps
runtime_reqs = self.get_reqs(self.runtime) - pip_deps
require(runtime_reqs <= build_reqs,
'Runtime requirements are not a subset of build requirements',
runtime_reqs - build_reqs)
overlap = build_reqs & runtime_reqs
ambiguities = PinnedRequirements(req for req in overlap if len(req.versions) > 1)
for req in ambiguities:
build_req = build_reqs[req]
# We can't resolve these ambiguities automatically because different
# versions of a package may have different dependencies in and of
# themselves, so pinning just the dependency in question might omit
# some of its dependencies. By pinning it explicitly the normal
# dependency resolution kicks in, including all transitive
# dependencies of the pinned version.
log.error('Ambiguous version of transitive runtime requirement %s. '
'Consider pinning it to the version used at build time (%s).',
req, build_req.versions)
require(not ambiguities,
'Ambiguous transitive runtime requirement versions',
ambiguities)
build_only_reqs = build_reqs - runtime_reqs
transitive_build_reqs = build_only_reqs - direct_build_reqs
transitive_runtime_reqs = runtime_reqs - direct_runtime_reqs
assert not transitive_build_reqs & transitive_runtime_reqs
self.write_transitive_reqs(transitive_build_reqs, self.build)
self.write_transitive_reqs(transitive_runtime_reqs, self.runtime)
def parse_reqs(self, file_or_str: Union[IO, str]) -> PinnedRequirements:
parsed_reqs = requirements.parse(file_or_str, recurse=False)
parsed_reqs = set(map(PinnedRequirement.create, parsed_reqs))
return PinnedRequirements(parsed_reqs - {None})
def get_reqs(self, qualfier: Qualifier) -> PinnedRequirements:
command = '.venv/bin/pip freeze --all'
log.info('Getting direct and transitive %s requirements by running %s on image %s',
qualfier.name, command, qualfier.image)
stdout = self.docker.containers.run(image=qualfier.image,
command=command,
detach=False,
stdout=True,
auto_remove=True)
return self.parse_reqs(stdout.decode())
def get_direct_reqs(self, qualifier: Qualifier) -> PinnedRequirements:
file_name = f'requirements{qualifier.extension}.txt'
path = self.project_root / file_name
log.info('Reading direct %s requirements from %s', qualifier.name, path)
with open(path) as f:
return self.parse_reqs(f)
def write_transitive_reqs(self, reqs: PinnedRequirements, qualifier: Qualifier) -> None:
file_name = f'requirements{qualifier.extension}.trans.txt'
path = self.project_root / file_name
log.info('Writing transitive requirements to %s', path)
with open(path, 'w') as f:
f.writelines(sorted(f'{req}\n' for req in reqs))
if __name__ == '__main__':
configure_script_logging(log)
parser = argparse.ArgumentParser()
parser.add_argument('--image', required=True)
parser.add_argument('--build-image', required=True)
options = parser.parse_args()
main = Main(build_image=options.build_image,
runtime_image=options.image)
main.run()
|
#!/usr/bin/python
##############################
#### Modules Import Start ####
##############################
from flask import Flask, render_template, request, redirect, send_file
from werkzeug import secure_filename
from app import app
import global_variables
from sys import argv
#script, filename = argv
import os.path
#if os.path.isfile("%s" % (filename)) == False: # If file doesn't exist, exit the script
# print 'File "%s" doesn\'t exist.' % (filename)
# file_note = raw_input('Press <Enter> to exit the script.\n')
# quit()
import time
import zipfile
import tarfile
import re
import operator
import ipaddress
from datetime import datetime
import math
import readline
readline.set_completer_delims("$")
############################
#### Modules Import End ####
############################
######################################
#### Script Beginning Notes Start ####
######################################
#@app.route('/')
#@app.route('/index')
@app.route('/lp_6_12_index', methods=['GET', 'POST'])
def index():
reload(global_variables)
global_variables.counter += 1
user_ip = request.remote_addr
users_ips_log = open("app/users_ips_logs", "a") # This is the access logs file
current_time = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')
print >>users_ips_log, '\033[1m%s\033[0m #User_Logged_In: User with IP %s logged in.' % (current_time, user_ip)
users_ips_log.close()
#if global_variables.counter > 1:
#return "Too many users connected, try again later."
#else:
return render_template('index.html')
@app.route('/validate_file', methods=['POST'])
@app.route('/validate_file.js')
def validate_js():
if request.method == 'GET':
return send_file('validate_file.js')
elif request.method == 'POST':
check_user_file = str(request.form['user_output_file'])
if not check_user_file:
return render_template('file_status.html', file_status="empty")
elif os.path.isfile("app/%s_config" % (check_user_file)) == True:
return render_template('file_status.html', file_status="error")
else:
return render_template('file_status.html', file_status="ok")
@app.route('/jquery-1.11.2.min.js')
def jquery():
return send_file('jquery-1.11.2.min.js')
@app.route('/getfile', methods=['GET','POST'])
def getfile():
if request.method == 'POST':
# for secure filenames. Read the documentation.
lp_config_file = request.files['myfile']
lp_config_filename = secure_filename(lp_config_file.filename)
# os.path.join is used so that paths work in every operating system
lp_config_file.save(os.path.join(lp_config_filename))
# You should use os.path.join here too.
with open(lp_config_filename) as lp_to_lpng:
lp_to_lpng = lp_to_lpng.read()
lp_to_lpng = lp_to_lpng.replace(' \\\r\n', " ") # In case there's a white space before the "\"
lp_to_lpng = lp_to_lpng.replace('\\\r\n ', " ") # In case there's a white space after the "\"
lp_to_lpng = lp_to_lpng.replace('\\\r\n', " ") # In case there's no white space between the "\" and the next line
lp_to_lpng = lp_to_lpng.split('\r\n')
lp_to_lpng = [var + " " for var in lp_to_lpng] # Adds a white space in the end of each list object
global lp_to_lpng
######################################
#### Script Beginning Notes Start ####
######################################
for line in lp_to_lpng: # Loops over the LP configuration
if "Software Version" in line: # LP software version check
def find_sw_version( line, first, last):
try:
start = line.index( first ) + len( first )
end = line.index( last, start )
return line[start:end]
except ValueError:
return "error"
sw_version = find_sw_version( line, "!Software Version: ", ")" )
#if "6.12" not in sw_version or "6.13" not in sw_version: # If the LP software version is 6.20 or 6.21, the script exists
if not sw_version.startswith("6.12") and not sw_version.startswith("6.13"):
return render_template('sw_version_error.html', sw_version=sw_version)
return render_template('startnotes.html')
#return redirect('/startnotes')
#@app.route('/startnotes')
#def startnotes():
#return render_template('startnotes.html')
@app.route('/page1', methods=['GET','POST'])
def page1():
global user_output_file
global output_file
global migration_errors
global ingress_vlan
global ingress_ports
global hc_note
global hc_fqdn1
global hc_fqdn2
global hc_dns1
global hc_dns2
user_output_file = str(request.form['user_output_file'])
#if os.path.isfile("app/%s_config" % (user_output_file)) == True:
# error = 'File %s already exists.' % (user_output_file)
# return render_template('startnotes.html', error=error)
#else:
output_file = open("app/%s_config" % (user_output_file), "abc") # This is the target Alteon configuration file
migration_errors = open("app/%s_logs" % (user_output_file), "w") # This is the logs file
ingress_vlan = str(request.form['vlan_id'])
if ingress_vlan == "0":
ingress_vlan = "any"
ingress_ports = request.form['ingress_ports']
ingress_ports = str(ingress_ports).split(',') # Creates list of ingress ports
ingress_ports = [p.replace(' ', '') for p in ingress_ports] # Removes white spaces
egress_ports = request.form['egress_ports']
egress_ports = str(egress_ports).split(',') # Creates list of egress ports
egress_ports = [p.replace(' ', '') for p in egress_ports] # Removes white spaces
hc_note = str(request.form['hc_types'])
hc_fqdn1 = str(request.form['fqdn1'])
hc_fqdn2 = str(request.form['fqdn2'])
hc_dns1 = str(request.form['dns1'])
hc_dns2 = str(request.form['dns2'])
global allports
allports = ingress_ports + egress_ports # Creates a list of all ports, ingress and egress
allports = list(set(allports)) # This list will be used later on when configuring filters
allports = sorted(allports)
####################################
#### Script Beginning Notes End ####
####################################
#########################
#### Main Code Start ####
#########################
##################################
#### Interfaces Section Start ####
##################################
### ###
# L2 Interface Section #
### ###
for line in lp_to_lpng:
if "net l2-interface" in line:
l2_if_id = global_variables.find_fnc( line, "set ", " " ) # Find interface ID
l2_if_admin_status = global_variables.find_fnc( line, "-ad ", " " ) # Find interface admin status
if l2_if_admin_status == "down": # If admin status is down, populates a dictionary with the following values: # ---->
# L2 interface ID as a key # ---->
# The admin status (always "down") as a value # ---->
# This is used later on to create another dictionary that maps the L3 interface ID and the admin status
l2_if_admin_status_dcn_key = "%s" % (l2_if_id)
global_variables.l2_if_admin_status_dcn.setdefault(l2_if_admin_status_dcn_key, [])
global_variables.l2_if_admin_status_dcn[l2_if_admin_status_dcn_key].append('%s' % (l2_if_admin_status))
### ###
# L3 Interface Section #
### ###
if "ip-interface" in line and "MNG" not in line:
if_ip = global_variables.find_fnc( line, "create ", " " ) # Finds L3 interface IP
global_variables.own_addresses_lst.append(if_ip) # Populates a list with the interface IPs as objects # ---->
# This is used later on when creating Smart NAT objects, to check for unsupported addresses
if_mask = global_variables.find_fnc( line, "%s " % (if_ip), " " ) # Finds L3 interface mask
l3_if_id = global_variables.find_fnc( line, "%s " % (if_mask), " " ) # Finds L3 interface ID
if_vlan = global_variables.find_fnc( line, "-v ", " " ) # Finds L3 interface VLAN
if_pa = global_variables.find_fnc( line, "-pac ", " " ) # Finds L3 interface peer IP
if_ip_to_peer_key = "%s" % (if_ip) # This dictionary is not in use
global_variables.if_ip_to_peer_dcn.setdefault(if_ip_to_peer_key, [])
global_variables.if_ip_to_peer_dcn[if_ip_to_peer_key].append('%s' % (if_pa))
if if_pa != 'error': # If interface peer IP exists, populates a dictionary with the following values: # ---->
# Interface IP as a key # ---->
# Interface peer IP as a value # ---->
# This is used later on to create SLB sync and HA configuration
if_ip_to_peer_no_error_key = "%s" % (if_ip)
global_variables.if_ip_to_peer_no_error_dcn.setdefault(if_ip_to_peer_no_error_key, [])
global_variables.if_ip_to_peer_no_error_dcn[if_ip_to_peer_no_error_key].append('%s' % (if_pa))
global_variables.own_addresses_lst.append(if_pa) # Populates a list with the interface peer IPs as objects # ---->
# This is used later on when creating Smart NAT objects, to check for unsupported addresses
global_variables.if_number += 1 # Used for Alteon L3 interface ID
global_variables.if_numbers_lst.append("%s" % (global_variables.if_number))
if l3_if_id in global_variables.l2_if_admin_status_dcn.keys(): # If admin status is down, populates a dictionary with the following values: # ---->
# L3 interface ID as a key # ---->
# The admin status (always "down") as a value # ---->
# This is used later on to configure the admin status of the L3 interface
l3_if_admin_status_dcn_key = "%s" % (global_variables.if_number)
global_variables.l3_if_admin_status_dcn.setdefault(l3_if_admin_status_dcn_key, [])
global_variables.l3_if_admin_status_dcn[l3_if_admin_status_dcn_key].append('%s' % (global_variables.l2_if_admin_status_dcn[l3_if_id][0]))
print >>output_file, "/c/l3/if %s" % (global_variables.if_number) # Starts printing the L3 interface commands
if str(global_variables.if_number) in global_variables.l3_if_admin_status_dcn.keys():
print >>output_file, " dis"
else:
print >>output_file, " ena"
print >>output_file, " addr %s" % (if_ip)
print >>output_file, " mask %s" % (if_mask)
if if_vlan != "error":
print >>output_file, " vlan %s" % (if_vlan)
if if_pa != "error":
print >>output_file, " peer %s" % (if_pa)
ipnet = ipaddress.ip_network('%s/%s' % (if_ip, if_mask), strict=False)
only_ipnet = str(ipnet).split('/')[0] # Finds the network address
last_host = [int(s) for s in str(list(ipaddress.ip_network('%s' % (ipnet)).hosts())[-1]).split('.')] # Finds the last host
ipbroad = '.'.join([str(s) for s in last_host[:-1] + [last_host[-1] + 1]]) # Finds the broadcast address
global_variables.own_addresses_lst.append(only_ipnet) # Populates a list with the network addresses as objects # ---->
# This is used later on when creating Smart NAT objects, to check for unsupported addresses
global_variables.own_addresses_lst.append(ipbroad) # Same as above, with broadcast addresses
subnet_to_new_ifs_key = "%s" % (ipnet) # Populates a dictionary with the following values: # ---->
# The network address as a key # ---->
# The L3 interface ID as a value # ---->
# This is used later on to map the static routes to the correct L3 interface IDs
global_variables.subnet_to_new_ifs_dcn.setdefault(subnet_to_new_ifs_key, [])
global_variables.subnet_to_new_ifs_dcn[subnet_to_new_ifs_key].append('%s' % (global_variables.if_number))
int_subnet_to_new_ifs_dcn = {k:int(v[0]) for k, v in global_variables.subnet_to_new_ifs_dcn.iteritems()} # Maps the dictionary values to integers
sorted_int_subnet_to_new_ifs_dcn = sorted(int_subnet_to_new_ifs_dcn.items(), key=operator.itemgetter(1)) # Converts the dictionary to a list of tuples and sorts it
subnet_to_mask_dcn_key = "%s" % (only_ipnet) # Populates a dictionary with the following values: # ---->
# The network address as a key # ---->
# The network mask as a value # ---->
# This is used later on to create a network class to allow traffic to local networks
global_variables.subnet_to_mask_dcn.setdefault(subnet_to_mask_dcn_key, [])
global_variables.subnet_to_mask_dcn[subnet_to_mask_dcn_key].append('%s' % (if_mask))
################################
#### Interfaces Section End ####
################################
###############################
#### Routing Section Start ####
###############################
for line in lp_to_lpng: # Loops over the LP configuration again for the routing table command
if "net route table create" in line and "0.0.0.0" not in line and "MNG" not in line:
print >>output_file, "/c/l3/route/ip4/"
break # Breaks the loop in order to print the routing table commmand only once
for line in lp_to_lpng: # Loops over the LP configuration again to continue with the code
if "net route table create" in line and "0.0.0.0" not in line and "MNG" not in line:
find_route_ips = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the route destination network, mask and next hop
for subnet, if_var in sorted_int_subnet_to_new_ifs_dcn:
if ipaddress.ip_address('%s' % (find_route_ips[2])) in ipaddress.ip_network('%s' % (subnet)): # Checks if the next hop belongs to one of the subnets in the dictionary
print >>output_file, " add %s %s %s %s" % (find_route_ips[0], find_route_ips[1], find_route_ips[2], if_var) # If it belongs, prints the static route with the correct L3 interface ID
for line in lp_to_lpng:
if "net route table create" in line and "0.0.0.0" in line and "MNG" not in line:
find_route_ips2 = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the default route next hop
print >>output_file, "/c/l3/gw 1" # Starts printing the GW
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " addr %s" % (find_route_ips2[2])
break # Breaks the loop in order to print the gateway only once
#############################
#### Routing Section End ####
#############################
##########################
#### HA Section Start ####
##########################
global alt_ha_mode
for line in lp_to_lpng:
if "redundancy mode set" in line:
ha_mode = global_variables.find_fnc( line, "set ", " " )
if ha_mode == "VRRP": # If LP redundancy mode is "VRRP", Alteon HA flag is on with 1
alt_ha_mode = 1
break
elif ha_mode == "Proprietary": # If LP redundancy mode is "Proprietary", Alteon HA flag is on with 2
alt_ha_mode = 2
break
else: # If HA mode is set to disable, Alteon HA flag is off
alt_ha_mode = 0
else: # If the redundancy mode command is not in the configuration, Alteon HA flag is off
alt_ha_mode = 0
for line in lp_to_lpng:
### ###
# Create Shared IPs List #
### ###
## ##
# This is used to check if there are VRRP associated IP addresses that are not present in NAT/DNS VIP/Remote VIP #
# Addresses that are not present will be used as HA floating IP if HA is used #
## ##
if alt_ha_mode == 1:
if "smartnat dynamic-nat" in line:
find_snd_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the SND addresses
if find_snd_ip[3] not in global_variables.lp_shared_ips_lst: # Populates a list with the SND addresses as objects
global_variables.lp_shared_ips_lst.append("%s" % (find_snd_ip[3]))
if "smartnat static-nat" in line:
find_sns_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the SNS addresses
if find_sns_ip[3] == find_sns_ip[4]: # If both from and to SNS addresses are the same
if find_sns_ip[3] not in global_variables.lp_shared_ips_lst: # Populates a list with the SNS addresses as objects
global_variables.lp_shared_ips_lst.append("%s" % (find_sns_ip[3]))
else: # If from and to SNS addresses are different
sns_natip_range = global_variables.ipRange_fnc(find_sns_ip[3], find_sns_ip[4]) # Executes the "ipRange" function to find all IPs
for sns in sns_natip_range: # Populates a list with the SNS addresses as objects
if sns not in global_variables.lp_shared_ips_lst:
global_variables.lp_shared_ips_lst.append("%s" % (sns))
if "smartnat static-pat" in line:
find_snp_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the SNP addresses
if find_snp_ip[0] not in global_variables.lp_shared_ips_lst: # Populates a list with the SNP addresses as objects
global_variables.lp_shared_ips_lst.append("%s" % (find_snp_ip[0]))
if "lp dns virtual-ip create" in line:
dns_vip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the DNS VIPs
if dns_vip[0] not in global_variables.lp_shared_ips_lst: # Populates a list with the DNS VIPs as objects
global_variables.lp_shared_ips_lst.append("%s" % (dns_vip[0]))
if "lp remote-vip create" in line:
find_float_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the remote VIPs
if find_float_ip[0] not in global_variables.lp_shared_ips_lst: # Populates a list with the remove VIPs as objects
global_variables.lp_shared_ips_lst.append("%s" % (find_float_ip[0]))
### ###
# Global HA Section #
### ###
for line in lp_to_lpng:
if "redundancy mode set" in line:
ha_mode = global_variables.find_fnc( line, "set ", " " )
if ha_mode == "VRRP" or ha_mode == "Proprietary": # If LP redundancy mode is VRRP or Proprietary
print >>output_file, "/c/l3/hamode switch" # Starts printing the global HA configuration
print >>output_file, "/c/l3/ha/switch"
print >>output_file, " srvpbkp dis"
print >>output_file, " filtpbkp dis"
print >>output_file, " def 1"
print >>output_file, "/c/l3/ha/switch/trigger/ifs"
for subnet, if_var in sorted_int_subnet_to_new_ifs_dcn: # Prints all L3 interfaces as HA triggers
print >>output_file, " add %s" % (if_var)
### ###
# HA Floating IPs Section #
### ###
if alt_ha_mode == 1 or alt_ha_mode == 2:
if "lp remote-vip create" in line: # Configures LP remote-vips as Alteon HA floating IPs
find_float_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the remove VIP
global_variables.float_id += 1
print >>output_file, "/c/l3/ha/floatip %s" % (global_variables.float_id) # Starts printing the HA floating IP
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " addr %s" % (find_float_ip[0])
for subnet, if_var in sorted_int_subnet_to_new_ifs_dcn:
if ipaddress.ip_address('%s' % (find_float_ip[0])) in ipaddress.ip_network('%s' % (subnet)): # Checks if the floating IP belongs to one of the subnets in the dictionary
print >>output_file, " if %s" % (if_var) # If it belongs, prints the correct L3 interface ID
if "redundancy vrrp associated-ip" in line and alt_ha_mode == 1: # Configures standalone LP assoicated IPs as floating IPs
find_associated_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the associated IP
if find_associated_ip[0] not in global_variables.lp_shared_ips_lst: # If the associated IP is not in the shared IPs list
for subnet, if_var in sorted_int_subnet_to_new_ifs_dcn:
if ipaddress.ip_address('%s' % (find_associated_ip[0])) in ipaddress.ip_network('%s' % (subnet)): # Checks if the associated IP belongs to one of the subnets in the dictionary and if it is, prints the correct L3 interface ID
global_variables.float_id += 1
print >>output_file, "/c/l3/ha/floatip %s" % (global_variables.float_id) # Starts printing the floating IP
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " addr %s" % (find_associated_ip[0])
print >>output_file, " if %s" % (if_var)
### ###
# SLB Sync Section #
### ###
for line in lp_to_lpng:
if (alt_ha_mode == 1 or alt_ha_mode == 2) and len(global_variables.if_ip_to_peer_no_error_dcn) > 0: # If peer IP addresses are present in the LP configuration
print >>output_file, "/c/slb/sync" # Starts printing the SLB sync configuration
print >>output_file, " prios d"
print >>output_file, " pips e"
print >>output_file, " certs e"
print >>output_file, " state e"
print >>output_file, " if e"
print >>output_file, " gw e"
print >>output_file, " ddstore ena"
print >>output_file, "/c/slb/sync/peer 1"
print >>output_file, " ena"
for pac in global_variables.if_ip_to_peer_no_error_dcn.values():
print >>output_file, " addr %s" % (pac[0])
break
print >>output_file, "/c/slb/sync/ucast"
print >>output_file, " ena"
print >>output_file, " primif %s" % (global_variables.if_numbers_lst[0])
if len(global_variables.if_numbers_lst) > 1:
print >>output_file, " secif %s" % (global_variables.if_numbers_lst[1])
break
########################
#### HA Section End ####
########################
#########################################
#### Preliminary Farms Section Start ####
#########################################
### ###
# Finds "NAT Mode Disabled" Farms #
### ###
## ##
# This is used to find the farms that are "NAT Mode Disabled" #
# Later on, the objects created here will be used to configure the real servers with "PIP Mode NoNAT" #
## ##
for line in lp_to_lpng:
if "farms table setCreate" in line:
farm_name_nonat = global_variables.find_fnc( line, ' setCreate "', '"' ) # Finds the farm name
if farm_name_nonat == 'error': # If there are no double quotes in the farm name
farm_name_nonat = global_variables.find_fnc( line, ' setCreate ', ' ' ) # Finds the farm name again
nat_mode = global_variables.find_fnc( line, " -nm ", " " ) # Finds the NAT mode
if nat_mode == 'error': # If NAT mode is set to "Disable", adds the farm name to a list
global_variables.farms_nonat_lst.append("%s" % (farm_name_nonat))
### ###
# Finds DNS Rules with "NAT Mode Disabled" Farms #
### ###
## ##
# This is used to create specific regular groups for DNS resolution #
# This is in case that the real servers are part of NAT and NoNAT groups #
## ##
global dns_ttl
for line in lp_to_lpng:
if "name-to-ip" in line:
dns_farm_name_nonat = global_variables.find_fnc( line, ' -fn "', '"' ) # Finds the farm name associated with the DNS rule
if dns_farm_name_nonat == 'error': # If there are no double quotes in the farm name
dns_farm_name_nonat = global_variables.find_fnc( line, ' -fn ', ' ' ) # Finds the farm name associated with the DNS rule again
if dns_farm_name_nonat != 'error' and dns_farm_name_nonat in global_variables.farms_nonat_lst and dns_farm_name_nonat not in global_variables.dns_farms_nonat_lst: # If the farm is a No NAT farm and it's not already in the DNS No NAT list, adds it to the list
global_variables.dns_farms_nonat_lst.append("%s" % (dns_farm_name_nonat))
### ###
# Finds Farms - Farm Flow Section #
### ###
## ##
# This is the section used to find the farm flows and farms associations #
## ##
if "farms-flow-table" in line:
farm_flow = global_variables.find_fnc( line, 'setCreate "', '"' ) # Finds the farm flow
if farm_flow == 'error': # If there are no double quotes in the farm flow name
farm_flow = global_variables.find_fnc( line, "setCreate ", " " ) # Finds the farm flow again
farm_in_fc = global_variables.find_fnc( line, '%s" "' % (farm_flow), '" -id' ) # Finds the farm associated with the farm flow
if farm_in_fc == 'error': # if there are no double quotes in the farm flow name and in the farm name
farm_in_fc = global_variables.find_fnc( line, '%s "' % (farm_flow), '" -id' ) # Finds the farm associated with the farm flow again
if farm_in_fc == 'error': # If there are no double quotes in the farm name
farm_in_fc = global_variables.find_fnc( line, '%s" ' % (farm_flow), " -id" ) # Finds the farm associated with the farm flow again
if farm_in_fc == 'error': # If there are no double quotes in the farm flow name
farm_in_fc = global_variables.find_fnc( line, ' %s ' % (farm_flow), " -id" ) # Finds the farm associated with the farm flow again
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
farm_in_fc = farm_in_fc.replace ('%s' % (unsupported_char), "%s" % (supported_char))
if farm_in_fc != 'error':
farm_flow_to_farm_dcn_key = "%s" % (farm_flow)
global_variables.farm_flow_to_farm_dcn.setdefault(farm_flow_to_farm_dcn_key, [])
global_variables.farm_flow_to_farm_dcn[farm_flow_to_farm_dcn_key].append('%s' % (farm_in_fc))
#######################################
#### Preliminary Farms Section End ####
#######################################
###########################################
#### DNS Global Settings Section Start ####
###########################################
### ###
# Finds DNS TTL and RR #
### ###
## ##
# This section is used to find the DNS TTL and RR #
# These parameters will later on be used on the GSLB rules #
## ##
if "dns response-ttl" in line: # Finds the global DNS TTL
dns_ttl = global_variables.find_fnc( line, "set ", " " )
break
elif "dns response-ttl" not in line: # If no DNS TTL command, default TTL (0)
dns_ttl = '0'
global dns_rr
for line in lp_to_lpng:
if "dns two-records" in line: # Finds the global DNS RR
dns_rr = global_variables.find_fnc( line, "set ", " " )
if dns_rr == 'disable': # If disable, RR = 1
dns_rr = '1'
else: # If enabled, RR = 2
dns_rr = '2'
break
elif "dns two-records" not in line: # If no DNS RR command, default RR (1)
dns_rr = '1'
#########################################
#### DNS Global Settings Section End ####
#########################################
#################################################
#### Proximity Global Settings Section Start ####
#################################################
### ###
# Finds proximity settings #
### ###
## ##
# This section is used to find the proximity settings #
# These parameters will later on be used on GSLB rules and filters #
## ##
global proximity_mode
for line in lp_to_lpng:
if "lp proximity mode" in line: # Finds the proximity mode
proximity_mode = global_variables.find_fnc( line, 'set "', '"' )
if proximity_mode == 'Full Proximity Inbound' or proximity_mode == 'Full Proximity Both':
current_time = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')
print >>migration_errors, '%s #Unsupported_feature: the following command is partly supported by LP NG:' % (current_time)
print >>migration_errors, " Command: %s" % (line)
print >>migration_errors, " Details: LP NG only supports outbound proximity with Smart NAT, inbound is not supported."
print >>migration_errors, ' Therefore, on the GSLB rules, "gmetric proximity" has not been configured.'
break
elif "lp proximity mode" not in line: # If no proximity mode command, use default (no proximity)
proximity_mode = "No Proximity"
if proximity_mode != "No Proximity": # If proximity not disabled, find other proximity settings
global proximity_mask
for line in lp_to_lpng:
if "lp proximity subnet-mask" in line: # Finds the proximity mask
proximity_mask = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line )
proximity_mask = proximity_mask[0]
break
else:
proximity_mask = "255.255.255.0"
global proximity_main_dns
for line in lp_to_lpng:
if "lp proximity main-dns-address" in line: # Dinds the proximity main DNS server
proximity_main_dns = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line )
proximity_main_dns = proximity_main_dns[0]
break
else:
proximity_main_dns = "0.0.0.0"
global proximity_backup_dns
for line in lp_to_lpng:
if "lp proximity backup-dns-address" in line: # Finds the proximity backup DNS server
proximity_backup_dns = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line )
proximity_backup_dns = proximity_backup_dns[0]
break
else:
proximity_backup_dns = "0.0.0.0"
global proximity_aging
for line in lp_to_lpng:
if "lp proximity aging-period" in line: # Finds the proximity aging
proximity_aging = [int(s) for s in line.split() if s.isdigit()]
proximity_aging = proximity_aging[0]
break
else:
proximity_aging = 2800
global proximity_retries
for line in lp_to_lpng:
if "lp proximity check-retries" in line: # Finds the proximity checks retries
proximity_retries = [int(s) for s in line.split() if s.isdigit()]
proximity_retries = proximity_retries[0]
break
else:
proximity_retries = 2
global proximity_interval
for line in lp_to_lpng:
if "lp proximity check-interval" in line: # Finds the proximity checks interval
proximity_interval = [int(s) for s in line.split() if s.isdigit()]
proximity_interval = proximity_interval[0]
break
else:
proximity_interval = 5
###############################################
#### Proximity Global Settings Section End ####
###############################################
######################################
#### Router Servers Section Start ####
######################################
### ###
# Finds Router Servers - Main Section #
### ###
## ##
# This is the main section used to find the router servers configuration #
# In this section, we only find the router servers, we don't print them #
## ##
for line in lp_to_lpng:
if "router-servers" in line:
wl_farm_name = global_variables.find_fnc( line, 'setCreate "', '"' ) # Finds the router server's associated farm
if wl_farm_name == 'error': # If no double quotes in the farm name
wl_farm_name = global_variables.find_fnc( line, "setCreate ", " " ) # Finds the router server's associated farm again
new_wl_farm_name = wl_farm_name
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
new_wl_farm_name = new_wl_farm_name.replace ('%s' % (unsupported_char), "%s" % (supported_char))
wl_name = global_variables.find_fnc( line, '%s" "' % (wl_farm_name), '"' ) # Finds the router server name
if wl_name == 'error': # If there are no double quotes in the farm name and router server name
wl_name = global_variables.find_fnc( line, '%s "' % (wl_farm_name), '"') # Finds the router server name again
if wl_name == 'error': # If there are no double quotes in the router server name
wl_name = global_variables.find_fnc( line, '%s" ' % (wl_farm_name), ' ') # Finds the router server name again
if wl_name == 'error': # If there are no double quotes in the farm name
wl_name = global_variables.find_fnc( line, '%s ' % (wl_farm_name), ' ') # Finds the router server name again
new_wl_name = wl_name
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
new_wl_name = new_wl_name.replace ('%s' % (unsupported_char), "%s" % (supported_char))
find_wl_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the router server IP
wl_ip = find_wl_ip[0]
if wl_ip != 'error': # Populates a dictionary with the following values: # ---->
# Router server IP as a key # ---->
# Router server name as a value # ---->
# This is used later on to check if a router server IP has different names
duplicate_wls_dcn_key = "%s" % (wl_ip)
global_variables.duplicate_wls_dcn.setdefault(duplicate_wls_dcn_key, [])
global_variables.duplicate_wls_dcn[duplicate_wls_dcn_key].append('%s' % (new_wl_name))
if wl_ip not in global_variables.own_addresses_lst:
global_variables.own_addresses_lst.append(wl_ip)
if wl_ip != 'error' and wl_farm_name not in global_variables.farms_nonat_lst: # If the farm has NAT mode enabled, populates a dictionary with the following: # ---->
# Farm name with NAT mode enable as a key # ---->
# A list of its associated router servers as values # ---->
# This is used later on to create the groups
group_to_routers_dcn_key = "%s" % (new_wl_farm_name)
global_variables.group_to_routers_dcn.setdefault(group_to_routers_dcn_key, [])
global_variables.group_to_routers_dcn[group_to_routers_dcn_key].append('%s' % (wl_ip))
elif wl_ip != 'error' and wl_farm_name in global_variables.farms_nonat_lst: # If the farm has NAT mode disabled, populates a dictionary with the following: # ---->
# Farm name with NAT mode disable as a key # ---->
# A list of its associated router servers as values # ---->
# This is used later on to create the No NAT groups
group_to_routers_nonat_dcn_key = "%s" % (new_wl_farm_name)
global_variables.group_to_routers_nonat_dcn.setdefault(group_to_routers_nonat_dcn_key, [])
global_variables.group_to_routers_nonat_dcn[group_to_routers_nonat_dcn_key].append('%s' % (wl_ip))
if wl_ip != 'error': # Populates a dictionary of all group to routers for all types of farms
group_to_routers_all_dcn_key = "%s" % (new_wl_farm_name)
global_variables.group_to_routers_all_dcn.setdefault(group_to_routers_all_dcn_key, [])
global_variables.group_to_routers_all_dcn[group_to_routers_all_dcn_key].append('%s' % (wl_ip))
operation_mode = global_variables.find_fnc( line, ' -om ' , ' ' ) # Finds the router server operation mode (regular or backup)
if operation_mode != 'error': # Populates a dictionary with the following values: # ---->
# Farm name as a key # ---->
# A list with the operation mode and router server IP as a value # ---->
# This is used later on to map IP to name and configure the real server in mode backup
om_key = "%s" % (new_wl_farm_name)
global_variables.operation_mode_dcn.setdefault(om_key, [])
global_variables.operation_mode_dcn[om_key].append('%s' % (operation_mode))
global_variables.operation_mode_dcn[om_key].append('%s' % (wl_ip))
bck_dcn_key = "%s" % (new_wl_farm_name) # Populates a dictionary with the following values: # ---->
# Farm name as a key # ---->
# The router server IP as a value # ---->
# This is used later on when creating the backup groups
global_variables.bck_dcn.setdefault(bck_dcn_key, [])
global_variables.bck_dcn[bck_dcn_key].append('%s' % (wl_ip))
admin_status = global_variables.find_fnc( line, ' -as ' , ' ' ) # Finds the rotuer server admin status
if admin_status != 'error': # Populates a dictionary with the following values: # ---->
# Farm name as a key # ---->
# A list with the admin status and router server IP as a value # ---->
# This is used later on to map IP to name and disable the real server in the relevant group
as_key = "%s" % (new_wl_farm_name)
global_variables.admin_status_dcn.setdefault(as_key, [])
global_variables.admin_status_dcn[as_key].append('%s' % (admin_status))
global_variables.admin_status_dcn[as_key].append('%s' % (wl_ip))
####################################
#### Router Servers Section End ####
####################################
########################################
#### Main Finds Farms Section Start ####
########################################
### ###
# Finds Farms - Main Section #
### ###
## ##
# This is the main section used to find the farms and their configuration #
# In this section, we only find the farms, we don't print them #
## ##
if "farms table setCreate" in line:
# print(line)
farm_name = global_variables.find_fnc( line, 'setCreate "', '"' ) # Finds the farm name
if farm_name == 'error': # If no double quotes in farm name
farm_name = global_variables.find_fnc( line, "setCreate ", " " ) # Finds the farm name again
new_farm_name = farm_name
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
new_farm_name = new_farm_name.replace ('%s' % (unsupported_char), "%s" % (supported_char))
if new_farm_name not in global_variables.default_group_lst:
global_variables.default_group_lst.append(new_farm_name)
if new_farm_name not in global_variables.all_farms_lst: # Populates a list of all farms
global_variables.all_farms_lst.append(new_farm_name)
dispatch_method = global_variables.find_fnc( line, '-dm "', '"' ) # Finds the farm's dispatch method
if dispatch_method == "Least Amount of Traffic": # Each statement below maps the dispatch method to Alteon metric
metric = "bandwidth"
elif dispatch_method in ["Least Amount of Local Traffic", "Least Amount of Bytes", "Least Number of Bytes", "Least Amount of Local Bytes"]:
metric = "bandwidth"
elif dispatch_method == "Fewest Number of Users":
metric = "leastconns"
elif dispatch_method == "Fewest Number of Local Users":
metric = "svcleast"
elif dispatch_method in ["Source IP Hashing", "Destination IP Hashing", "Layer-3 Hashing"]:
metric = "phash 255.255.255.255"
elif dispatch_method == "Response Time":
metric = "response"
elif dispatch_method == "error": # If no double quotes in the dispatch method
dispatch_method = global_variables.find_fnc( line, '-dm ', ' ' ) # Finds the dispatch method again (can be only "Hashing")
if dispatch_method == "Hashing":
metric = "phash 255.255.255.255"
else: # If no dispatch method found, use the LP default ("Cyclic", in Alteon, "roundrobin")
metric = "roundrobin"
aging_time = global_variables.find_fnc( line, '-cl ', ' ' ) # Finds the farm's client aging time
if aging_time == 'error': # If nothing found, use the LP default (60 seconds) # ---->
# Converting to minutes, this is 1 minute. # ---->
# We add 1 since Alteon doesn't support odd minutes # ----->
# We add 2 for the Alteon's slowstart algorithm, we end up with 4 minutes
new_aging_time = 4
else: # if client aging time is found - non default
new_aging_time = int(math.ceil(float(aging_time)/60)) # We convert to minutes, then float and round the number
if (new_aging_time % 2 == 0):
new_aging_time = new_aging_time
if new_aging_time == 0: # If we end up with 0, we use 4
new_aging_time = 4
else: # Else, we add 2 minutes for the Alteon's slowstart algorithm
new_aging_time += 2
else: # If number is odd, we add 1 to use even number, then add 2 for the Alteon's slowstart algorithm
new_aging_time = int(new_aging_time)+1
new_aging_time += 2
farm_parameters_dcn_key = "%s" % (new_farm_name) # Populates a dictionary with the following values: # ---->
# The new farm name as a key # ---->
# The farm's metric as a value # ---->
# This is used later on to configure the metric when creating the group # ---->
# This is also used later on to configure the gmetric when creating the GSLB rule
global_variables.farm_parameters_dcn.setdefault(farm_parameters_dcn_key, [])
global_variables.farm_parameters_dcn[farm_parameters_dcn_key].append('%s' % (metric))
#global_variables.farm_parameters_dcn[farm_parameters_dcn_key].append('%s' % (aging_time))
orig_farm_parameters_dcn_key = "%s" % (farm_name) # Populates a dictionary with the following values: # ---->
# The original farm name as a key # ---->
# The farm's original dispatch method as a value # ---->
# This is used later on to generate a log when the dispatch method can't be used as gmetric
global_variables.orig_farm_parameters_dcn.setdefault(orig_farm_parameters_dcn_key, [])
global_variables.orig_farm_parameters_dcn[orig_farm_parameters_dcn_key].append('%s' % (dispatch_method))
orig_dm_dcn_key = "%s" % (new_farm_name) # Populates a dictionary with the following values: # ---->
# The farm name as a key # ---->
# The original dispatch method as a value # ---->
# This is used later on to configure the pbind/thash on filters if needed
global_variables.orig_dm_dcn.setdefault(orig_dm_dcn_key, [])
global_variables.orig_dm_dcn[orig_dm_dcn_key].append('%s' % (dispatch_method))
global_variables.farms_aging_times_lst.append("%s" % (new_aging_time)) # Populates a list with the new client aging times as objects # ---->
# This is used later on to compare with application aging times
if "client-table application-aging-time" in line:
app_aging_time = global_variables.find_fnc( line, ' -at ', ' ' ) # Finds the application aging time
# We use the same calculation as with the farm client aging time
if app_aging_time == 'error':
new_app_aging_time = 4
else:
new_app_aging_time = int(math.ceil(float(app_aging_time)/60))
if (new_app_aging_time % 2 == 0):
new_app_aging_time = new_app_aging_time
if new_app_aging_time == 0:
new_app_aging_time = 4
else:
new_app_aging_time += 2
else:
new_app_aging_time = int(new_app_aging_time)+1
new_app_aging_time += 2
global_variables.app_aging_times_lst.append("%s" % (new_app_aging_time)) # Populates a list with the new app aging times as objects # ---->
# This is used later on to compare with farm client aging times
farms_aging_times_lst = map(int, global_variables.farms_aging_times_lst)
app_aging_times_lst = map(int, global_variables.app_aging_times_lst)
for line in lp_to_lpng:
farms_max_aging_time = max(farms_aging_times_lst)
if len(app_aging_times_lst) > 0:
app_max_aging_time = max(app_aging_times_lst)
break
else:
app_max_aging_time = 0
global max_aging_time
max_aging_time = max(farms_max_aging_time, app_max_aging_time) # Finds the maximum aging time among the client and app aging times
# This is done since Alteon doesn't support tmout on LLB filter
# and doesn't support app aging time
# Therefore, we use the highest aging time on all real servers
#####################################
#### Main Find Farms Section End ####
#####################################
#############################################
#### Real Servers Creation Section Start ####
#############################################
### ###
# Real Servers Creation - Main Section #
### ###
## ##
# This is the main section used to create the real servers configuraiton #
# In this section, we use the dictionaries populated in the find section #
# #
# Rules: #
# #
# 1.) We check if the router server IP has multiple names #
# If it has, we ask the user to choose one of the names or a new name #
# If it has a single name, we use it and we don't ask the user #
# 2.) We always disable real servers in the group level #
# 3.) When creating "No NAT" groups, we check the following: #
# a. If the real server belongs to another regular group: #
# We create it again with the same name with "_NAT" appended #
# PIP mode will be "nonat" #
# b. If the real server only belongs to a "No NAT group": #
# We create it with the chosen name, we do not append "_NAT" #
# PIP mode will be "nonat" #
# c. If a DNS rule uses a "No NAT" farm, and: #
# Its real servers belong also to a regular farm #
# This means that the real servers have "_NAT" appended, therefore: #
# In this case, we create a special group for GSLB #
# The group will have the regular real server names #
# It'll only be used in GSLB rules #
# This behavior will be changed soon as it doesn't conform with LP #
## ##
### ###
# WAN Link Name Selection Section #
### ###
## ##
# This is a section used to prompt the user to select names for the WAN links #
# This section will be shown to the user only if there is at least one router server with multiuple names #
## ##
#for orig_wl_ip, orig_wl_name in global_variables.duplicate_wls_dcn.iteritems(): # Loops over the dictionary that contains the IP to real names mapping
#wl_names_equal_status = global_variables.all_same(orig_wl_name) # For each real server IP, we check if all of its values are the same
#if wl_names_equal_status == False: # If they're not the same, we prompt the user with the WAN link selection screen
equal_status = 0
for orig_wl_ip, orig_wl_name in global_variables.duplicate_wls_dcn.iteritems(): # Loops over the dictionary that contains the IP to real names mapping
wl_names_equal_status = global_variables.all_same(orig_wl_name) # For each real server IP, we check if all of its values are the same
if wl_names_equal_status == False: # If they're not the same, we prompt the user with the WAN link selection screen
equal_status = 1
uniq_unequal_wl_names = list(set(orig_wl_name)) # Remove duplicate unequal names
unequal_wl_names = ', '.join(uniq_unequal_wl_names) # Creates a visible list of unequal names, comma separated
global_variables.isp_id += 1 # ISP ID for showing the user ISPs with multiple names
unequal_wl_names_to_html_dcn = {}
unequal_wl_names_to_html_dcn['id'] = '%s' % (global_variables.isp_id)
unequal_wl_names_to_html_dcn['ip'] = '%s' % (orig_wl_ip)
#unequal_wl_names_to_html_dcn['wl_names'] = '%s' % (uniq_unequal_wl_names)
for a in uniq_unequal_wl_names:
unequal_wl_names_to_html_dcn.setdefault("wl_names", []).append(a)
global_variables.unequal_wls_lst.append(unequal_wl_names_to_html_dcn)
if equal_status == 1:
return render_template('isps.html', title='ISPs', unequal_wls_lst=global_variables.unequal_wls_lst)
else:
return redirect('/page3')
@app.route('/page2', methods=['GET','POST'])
@app.route('/page3', methods=['GET','POST'])
def page2():
def print_adv_hc_fnc(hc_name, hc_destIP, hc_dname):
'''Prints the script's predefined advanced HCs for WLs.
Takes the HC name, HC destination IP and HC domain name as arguments.
'''
print >>output_file, "/c/slb/advhc/health %s DNS" % (hc_name)
print >>output_file, " dport 53"
print >>output_file, " dest 4 %s" % (hc_destIP)
print >>output_file, " transp enabled"
print >>output_file, " retry 2"
print >>output_file, " timeout 4"
print >>output_file, " downtime 5"
print >>output_file, "/c/slb/advhc/health %s DNS/dns" % (hc_name)
print >>output_file, ' domain "%s"' % (hc_dname)
def print_real_hc_fnc(hc_type, hc_real_name, hc_rip):
'''Prints the WL direct HC and the LOGEXP that binds it with the advanced HCs.
Takes the HC type (predefined or user-defined), WL name and WL IP as arguments.
'''
if hc_type == "Y" or hc_type == "y" or hc_type == "Setup":
print >>output_file, "/c/slb/advhc/health %s_ICMP ICMP" % (hc_real_name) # Prints the direct HC
print >>output_file, " dest 4 %s" % (hc_rip)
print >>output_file, " retry 2"
print >>output_file, " timeout 4"
print >>output_file, " downtime 5"
print >>output_file, "/c/slb/advhc/health %s_HCs LOGEXP" % (hc_real_name) # Prints the LOGEXP that binds the predefined HCs and the direct
if hc_type == "Y" or hc_type == "y":
print >>output_file, ' logexp "(%s_ICMP)&(Yahoo_DNS1|CNN_DNS1|Yahoo_DNS2|CNN_DNS2)"' % (hc_real_name)
elif hc_type == "Setup":
print >>output_file, ' logexp "(%s_ICMP)&(%s_DNS1|%s_DNS1|%s_DNS2|%s_DNS2)"' % (hc_real_name, hc_fqdn1, hc_fqdn2, hc_fqdn1, hc_fqdn2)
def print_real_fnc(real_type, real_name, rip, max_aging_time):
'''Prints the WL real server.
Takes the real type, WL name, WL IP and max aging time as arguments.
Real server types defined in this script are:
1.) Regular.
2.) nonat_not_in_regular (No NAT that doesn't belong also to a regular farm).
3.) nonat_no_regular (No NAT while there are no regular farms in the configuration).
4.) nonat_in_regular (NO NAT that also belongs to a regular farm).
'''
if real_type == "nonat_in_regular": # If the real server is no NAT but there also a regular server in another farm
print >>output_file, "/c/slb/real %s_NoNAT" % (real_name) # We print the name and append "_NoNAT"
else: # If it's a regular server, or "no NAT" that is not also regular, or "no NAT" while there are no regular servers
print >>output_file, "/c/slb/real %s" % (real_name) # We print the regular name
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " rip %s" % (rip)
print >>output_file, " type wanlink"
print >>output_file, " maxcon 0 logical"
print >>output_file, " tmout %s" % (max_aging_time)
if hc_note == "Y" or hc_note == "y" or hc_note == "Setup": # Binds the LOGEXP HC if the user chose the predefined HC or the HC setup
print >>output_file, " health WLs_HCs"
else: # Uses "health icmp" if the user chose to not configure HCs
print >>output_file, " health icmp"
if real_type == "nonat_in_regular": # Mode "nonat" configuration for "no NAT" real servers
print >>output_file, "/c/slb/real %s_NoNAT/adv/pip" % (real_name)
print >>output_file, " mode nonat"
elif real_type == "nonat_not_in_regular" or real_type == "nonat_no_regular":
print >>output_file, "/c/slb/real %s/adv/pip" % (real_name)
print >>output_file, " mode nonat"
def add_servers_to_regular_group_fnc(wl_ip, wl_name):
'''Adds regular WL servers to a WL group.
Takes WL IP and WL name as arguments.
'''
if server == wl_ip: # We validate that the IP in the regular farm is the same as the IP in the user chosen WL names dict
if farm in global_variables.gbck_dcn.keys(): # If the farm has a backup group
if farm not in global_variables.back_added_lst: # Checking if we didn't yet add the backup group, then add it
print >>output_file, " backup g%s" % (global_variables.gbck_dcn[farm][0])
global_variables.back_added_lst.append(farm) # Add the farm to the list so we know a backup group was already added to it
if server not in global_variables.operation_mode_dcn[farm]: # Adding other servers if they're not backup
print >>output_file, " add %s" % (wl_name)
if farm in global_variables.admin_status_dcn.keys(): # Disables the real server if needed
if server in global_variables.admin_status_dcn[farm]:
print >>output_file, " dis %s" % (wl_name)
elif farm in global_variables.operation_mode_dcn.keys() and len(global_variables.operation_mode_dcn[farm]) == 2: # If the farm has one backup server
if server in global_variables.operation_mode_dcn[farm]: # We check if the server is a backup server and if so, add it as backup
print >>output_file, " backup r%s" % (wl_name)
if farm in global_variables.admin_status_dcn.keys(): # Disables the real server if needed
if server in global_variables.admin_status_dcn[farm]:
print >>output_file, " dis %s" % (wl_name)
else: # If this server is not a backup server, we add it regularly
print >>output_file, " add %s" % (wl_name)
if farm in global_variables.admin_status_dcn.keys(): # Disables the real server if needed
if server in global_variables.admin_status_dcn[farm]:
print >>output_file, " dis %s" % (wl_name)
elif farm not in global_variables.operation_mode_dcn.keys() and farm not in global_variables.gbck_dcn.keys(): # If the farm has no backup server, we add the real server regularly
print >>output_file, " add %s" % (wl_name)
if farm in global_variables.admin_status_dcn.keys(): # Disables the real server if needed
if server in global_variables.admin_status_dcn[farm]:
print >>output_file, " dis %s" % (wl_name)
def add_servers_to_nonat_group_fnc(nonat_wl_ip, nonat_wl_name):
'''Adds No NAT WL servers to a WL group.
Takes WL IP and WL name as arguments.
'''
if server == nonat_wl_ip: # We validate that the IP in the No NAT farm is the same as the IP in the user chosen WL names dict
if farm in global_variables.gbck_dcn.keys(): # If the farm has a backup group
if farm not in global_variables.back_added_lst: # Checking if we didn't yet add the backup group, then add it
print >>output_file, " backup g%s" % (global_variables.gbck_dcn[farm][0])
global_variables.back_added_lst.append(farm) # Add the farm to the list so we know a backup group was already added to it
if server not in global_variables.operation_mode_dcn[farm]: # Adding other servers if they're not backup
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if server in group_to_routers_values: # if the server is also in a regular farm
print >>output_file, " add %s_NoNAT" % (nonat_wl_name[0]) # Adds the server and appends "_NoNAT"
else: # if the server is not in a regular farm
print >>output_file, " add %s" % (nonat_wl_name[0]) # Adds the server with the user chosen name
else: # If there are no regular farms
print >>output_file, " add %s" % (nonat_wl_name[0]) # Adds the server with the user chosen name
if farm in global_variables.admin_status_dcn.keys(): # If the farm is in the admin state dictionary keys
if server in global_variables.admin_status_dcn[farm]: # Validates if the current real server is disabled
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if server in group_to_routers_values: # If the server is also in a regular farm
print >>output_file, " dis %s_NoNAT" % (nonat_wl_name[0]) # Disables the server and appends "_NoNAT"
else: # If the server is not in a regular farm
print >>output_file, " dis %s" % (nonat_wl_name[0]) # Disables the server with the user chosen name
else: # If there are no regular farms
print >>output_file, " dis %s" % (nonat_wl_name[0]) # Disables the server with the user chosen name
elif farm in global_variables.operation_mode_dcn.keys() and len(global_variables.operation_mode_dcn[farm]) == 2: # If the farm has one backup server
if server in global_variables.operation_mode_dcn[farm]: # We check if the server is a backup server
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if server in group_to_routers_values: # If the server is also in a regular farm
print >>output_file, " backup r%s_NoNAT" % (nonat_wl_name[0]) # Adds the server as a backup and appends "_NoNAT"
else: # If the server is not in a regular farm
print >>output_file, " backup r%s" % (nonat_wl_name[0]) # Adds the server as a backup with the user chosen name
else: # If there are no regular farms
print >>output_file, " backup r%s" % (nonat_wl_name[0]) # Adds the server as a backup with the user chosen name
if farm in global_variables.admin_status_dcn.keys(): # If the farm is in the admin state dictionary keys
if server in global_variables.admin_status_dcn[farm]: # Validates if the current real server is disabled
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if server in group_to_routers_values: # If the server is also in a regular farm
print >>output_file, " dis %s_NoNAT" % (nonat_wl_name[0]) # Disables the server and appends "_NoNAT"
else: # If the server is not in a regular farm
print >>output_file, " dis %s" % (nonat_wl_name[0]) # Disables the server with the user chosen name
else: # If there are no regular farms
print >>output_file, " dis %s" % (nonat_wl_name[0]) # Disables the server with the user chosen name
else: # If farm has backup at least one backup server, but this specific server is not a backup server
if len(global_variables.group_to_routers_dcn) > 0: # if there are regular farms
if server in group_to_routers_values: # If the server is also in a regular farm
print >>output_file, " add %s_NoNAT" % (nonat_wl_name[0]) # Adds the server and appends "_NoNAT"
else: # If the server is not in a regular farm
print >>output_file, " add %s" % (nonat_wl_name[0]) # Adds the server with the user chosen name
else: # If there are not regular farms
print >>output_file, " add %s" % (nonat_wl_name[0]) # Adds the server with the user chosen name
if farm in global_variables.admin_status_dcn.keys(): # If the farm is in the admin state dictionary keys
if server in global_variables.admin_status_dcn[farm]: # Validates if the current real server is disabled
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if server in group_to_routers_values: # If the server is also in a regular farm
print >>output_file, " dis %s_NoNAT" % (nonat_wl_name[0]) # Disables the server and appends "_NoNAT"
else: # If the server is not ina regular farm
print >>output_file, " dis %s" % (nonat_wl_name[0]) # Disables the server with the user chosen name
else: # If there are no regular farms
print >>output_file, " dis %s" % (nonat_wl_name[0]) # Disables the server with the user chosen name
elif farm not in global_variables.operation_mode_dcn.keys() and farm not in global_variables.gbck_dcn.keys(): # If the farm has no backup servers
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if server in group_to_routers_values: # If the server is also in a regular farm
print >>output_file, " add %s_NoNAT" % (nonat_wl_name[0]) # Adds the server and appends "_NoNAT"
else: # If the server is not in a regular farm
print >>output_file, " add %s" % (nonat_wl_name[0]) # Adds the server with the user chosen name
else: # If there are no regular farms
print >>output_file, " add %s" % (nonat_wl_name[0]) # Adds the server with the user chosen name
if farm in global_variables.admin_status_dcn.keys(): # If the farm is in the admin state dictionary keys
if server in global_variables.admin_status_dcn[farm]: # Validates if the current real server is disabled
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if server in group_to_routers_values: # If the server is also in a regular farm
print >>output_file, " dis %s_NoNAT" % (nonat_wl_name[0]) # Disables the server and appends "_NoNAT"
else: # if the server is not in a regular farm
print >>output_file, " dis %s" % (nonat_wl_name[0]) # Disables the server with the user chosen name
else: # If there are no regular farms
print >>output_file, " dis %s" % (nonat_wl_name[0]) # Disables the server with the user chosen name
def add_servers_to_bck_group_fnc(bck_wl_ip, bck_wl_name):
'''Adds WL servers to a WL backup group.i
Takes WL IP and WL name as arguments.
'''
if bserver == bck_wl_ip: # We validate that the IP in the backup farm is the same as the IP in the user chosen WL names dict
if len(global_variables.group_to_routers_nonat_dcn) > 0: # If there are "No NAT" farms
if bfarm in global_variables.group_to_routers_nonat_dcn.keys(): # If the current backup farm name is a No NAT farm
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if bserver in group_to_routers_values: # If the current WAN link IP is in a regular farm
print >>output_file, " add %s_NoNAT" % (bck_wl_name[0]) # We add the WAN link and append "_NoNAT"
else: # If the current WAN link IP is not in a regular farm
print >>output_file, " add %s" % (bck_wl_name[0]) # We add the WAN link with its user chosen name
else: # If there are no regular farms
print >>output_file, " add %s" % (bck_wl_name[0]) # We add the WAN link with its user chosen name
else: # If the current backup farm name is a regular farm
print >>output_file, " add %s" % (bck_wl_name[0]) # We add the WAN link with its user chosen name
else: # If there are no "No NAT" farms
print >>output_file, " add %s" % (bck_wl_name[0]) # We add the WAN link with its user chosen name
if bfarm in global_variables.admin_status_dcn.keys(): # Loops over the admin status dictionary keys
if bserver in global_variables.admin_status_dcn[bfarm]: # Validates if the current real server is disabled
if len(global_variables.group_to_routers_nonat_dcn) > 0: # If there are "No NAT" farms
if bfarm in global_variables.group_to_routers_nonat_dcn.keys(): # If the current backup farm name is a No NAT farm
if len(global_variables.group_to_routers_dcn) > 0: # If there are regular farms
if bserver in group_to_routers_values: # If the current WAN link IP is in a regular farm
print >>output_file, " dis %s_NoNAT" % (bck_wl_name[0]) # We disable the WAN link and append "_NoNAT"
else: # If the current WAN link IP is not in a regular farm
print >>output_file, " dis %s" % (bck_wl_name[0]) # We disable the WAN link with its user chosen name
else: # If there are no regular farms
print >>output_file, " dis %s" % (bck_wl_name[0]) # We disable the WAN link with its user chosen name
else: # If the current backup farm name is a regular farm
print >>output_file, " dis %s" % (bck_wl_name[0]) # We disable the WAN link with its user chosen name
else: # If there are no "No NAT" farms
print >>output_file, " dis %s" % (bck_wl_name[0]) # We add the WAN link with its user chosen name
if request.path == '/page2':
chosen_wl_names = str(request.form['new_isps'])
chosen_wl_names = chosen_wl_names.split(",")
for isp in chosen_wl_names:
user_new_wl_names_dcn_key = "%s" % (isp.split("&")[0])
global_variables.user_new_wl_names_dcn.setdefault(user_new_wl_names_dcn_key, [])
global_variables.user_new_wl_names_dcn[user_new_wl_names_dcn_key].append('%s' % (isp.split("&")[1]))
### ###
# Health Checks Section #
### ###
## ##
# This is a section used to prompt the user that health checks will not be migrated #
# The user will have the following choices: #
# #
# 1.) Use a predefined advanced HC configuration #
# 2.) Go to a setup screen to create his own advanced HC configration (DNS based health checks) #
# 3.) Not create any advanced HC configuration #
# In this case, the script will create "health icmp" on each real server #
# It'll also prompt the user to migrate the LP HC configuration manually #
## ##
if hc_note == "Y" or hc_note == "y": # If the user chose "Y/y", we'll use the predefined HC configuration
print_adv_hc_fnc("CNN_DNS1", "8.8.8.8", "www.cnn.com")
print_adv_hc_fnc("CNN_DNS2", "209.244.0.3", "www.cnn.com")
print_adv_hc_fnc("Yahoo_DNS1", "8.8.8.8", "www.yahoo.com")
print_adv_hc_fnc("Yahoo_DNS2", "209.244.0.3", "www.yahoo.com")
print >>output_file, "/c/slb/advhc/health WLs_HCs LOGEXP"
print >>output_file, ' logexp "(icmp)&(Yahoo_DNS1|CNN_DNS1|Yahoo_DNS2|CNN_DNS2)"'
elif hc_note == "Setup": # If the user chose "Setup", we'll present the HC setup menu
# Starts printing the HCs that the user created
print_adv_hc_fnc("%s_DNS1" % (hc_fqdn1), hc_dns1, hc_fqdn1)
print_adv_hc_fnc("%s_DNS2" % (hc_fqdn1), hc_dns2, hc_fqdn1)
print_adv_hc_fnc("%s_DNS1" % (hc_fqdn2), hc_dns1, hc_fqdn2)
print_adv_hc_fnc("%s_DNS2" % (hc_fqdn2), hc_dns2, hc_fqdn2)
print >>output_file, "/c/slb/advhc/health WLs_HCs LOGEXP"
print >>output_file, ' logexp "(icmp)&(%s_DNS1|%s_DNS1|%s_DNS2|%s_DNS2)"' % (hc_fqdn1, hc_fqdn2, hc_fqdn1, hc_fqdn2)
### ###
# WAN Link Real Server Creation Section #
### ###
## ##
# This is a section used to create the WAN link real servers and their direct HCs #
# In this section we perform the following: #
# #
# 1.) Check if there are WAN links with different names and use the user chosen name #
# 2.) Check if there are WAN links with a single name and use it #
# 3.) If the WAN link is No NAT, we check the following: #
# a. If it's also part of a NAT farm, we print it with "NoNAT" appended #
# b. If it's not part of a NAT farm, we print the regular name #
## ##
group_to_routers_values = ','.join(str(v) for v in global_variables.group_to_routers_dcn.values()) # Creates a large string that contains all of the real servers IP addresses that belong to farms that have NAT mode enabled # ---->
# It'll be used later on to check if a No NAT router server also belongs to a NAT mode enabled farm
group_to_routers_nonat_values = ','.join(str(v) for v in global_variables.group_to_routers_nonat_dcn.values())
## ##
# This section creates the WAN links that have different names, using the user chosen name #
## ##
if global_variables.user_new_wl_names_dcn != '': # If the user chosen WL names dictionary is not empty
for user_wl_ip, user_wl_name in global_variables.user_new_wl_names_dcn.iteritems(): # Loops over the dictionary to create direct HCs and real servers
#print_real_hc_fnc(hc_note, user_wl_name[0], user_wl_ip) # Executes the function that prints the direct HC
if user_wl_ip in group_to_routers_values: # If the router server IP is in the regular WAN links list, we print the real server with the user chosen name
print_real_fnc("regular", user_wl_name[0], user_wl_ip, max_aging_time)
if user_wl_ip in group_to_routers_nonat_values: # If the router server IP in in the no NAT WAN links
if len(global_variables.group_to_routers_dcn) > 0: # If the dictionary of the regular WAN links to groups is not empty
if user_wl_ip in group_to_routers_values: # If the router server IP is in the regular WAN links list too, we append "_NoNAT" to the real server name
print_real_fnc("nonat_in_regular", user_wl_name[0], user_wl_ip, max_aging_time)
else: # If the router server IP is not in the regular WAN links list, we use the regular name
print_real_fnc("nonat_not_in_regular", user_wl_name[0], user_wl_ip, max_aging_time)
else: # If the dictionary of the regular WAN links to group is empty (meaning there's only No NAT farms), we use the regular real server name
print_real_fnc("nonat_no_regular", user_wl_name[0], user_wl_ip, max_aging_time)
## ##
# This section creates the WAN links that have a single name, using their regular name #
## ##
for orig_wl_ip, orig_wl_name in global_variables.duplicate_wls_dcn.iteritems(): # Loops over the dictionary to create direct HCs and real servers
wl_names_equal_status = global_variables.all_same(orig_wl_name)
if wl_names_equal_status == True: # If the router names are the same
#print_real_hc_fnc(hc_note, orig_wl_name[0], orig_wl_ip)
if orig_wl_ip in group_to_routers_values: # If the router server IP is in the WAN links list, we print the regular real server name
print_real_fnc("regular", orig_wl_name[0], orig_wl_ip, max_aging_time)
user_equal_wl_names_dcn_key = "%s" % (orig_wl_ip) # Populates a dictionary with the following values: # ---->
# The real server IP as a key # ---->
# The real server name as a value # ---->
# This is used later on to add the real servers to the group
global_variables.user_equal_wl_names_dcn.setdefault(user_equal_wl_names_dcn_key, [])
global_variables.user_equal_wl_names_dcn[user_equal_wl_names_dcn_key].append('%s' % (orig_wl_name[0]))
if orig_wl_ip in group_to_routers_nonat_values: # If the router server IP is in the no NAT WAN links
if len(global_variables.group_to_routers_dcn) > 0: # If the dictionary of the regular WAN links to groups is not empty
if orig_wl_ip in group_to_routers_values: # If the router server IP is in the regular WAN links list too, we append "_NoNAT" to the real server name
print_real_fnc("nonat_in_regular", orig_wl_name[0], orig_wl_ip, max_aging_time)
user_equal_wl_names_dcn_key = "%s" % (orig_wl_ip)
global_variables.user_equal_wl_names_dcn.setdefault(user_equal_wl_names_dcn_key, [])
global_variables.user_equal_wl_names_dcn[user_equal_wl_names_dcn_key].append('%s' % (orig_wl_name[0]))
else: # If the router server IP is not in the regular WAN links list, we use the regular name
print_real_fnc("nonat_not_in_regular", orig_wl_name[0], orig_wl_ip, max_aging_time)
user_equal_wl_names_dcn_key = "%s" % (orig_wl_ip)
global_variables.user_equal_wl_names_dcn.setdefault(user_equal_wl_names_dcn_key, [])
global_variables.user_equal_wl_names_dcn[user_equal_wl_names_dcn_key].append('%s' % (orig_wl_name[0]))
else: # If the dictionary of the regular WAN links to group is empty (meaning there's only No NAT farms), we use the regular real server name
print_real_fnc("nonat_no_regular", orig_wl_name[0], orig_wl_ip, max_aging_time)
user_equal_wl_names_dcn_key = "%s" % (orig_wl_ip)
global_variables.user_equal_wl_names_dcn.setdefault(user_equal_wl_names_dcn_key, [])
global_variables.user_equal_wl_names_dcn[user_equal_wl_names_dcn_key].append('%s' % (orig_wl_name[0]))
###########################################
#### Real Servers Creation Section End ####
###########################################
#######################################
#### Groups Creation Section Start ####
#######################################
### ###
# Groups Creation - Main Section #
### ###
## ##
# This is the main section used to create the groups configuraiton #
# In this section, we use the following dictionaries: #
# #
# 1.) Dictionaries populated in the real servers find section #
# 2.) Dictionaries populated in the real servers creation section #
# #
# Rules: #
# #
# 1.) We create the following: #
# a. Regular groups #
# b. A "backup r" if we find only one backup real server in the farm #
# c. A backup group if we find more than one backup real server in the farm #
# d. No NAT groups #
# 2.) We always disable real servers in the group level #
# 3.) When creating "No NAT" groups, we check the following: #
# a. A backup group is created with the following name convention: #
# The regular group name and "_BCK" appended #
# b. If a DNS rule uses a "No NAT" farm, and: #
# Its real servers also belong to a regular farm #
# This means that the real servers have "_NAT" appended, therefore: #
# In this case, we create a special group for GSLB #
# The group will have the regular real server names #
# It'll only be used in GSLB rules #
# This behavior will be changed soon as it doesn't conform with LP #
## ##
### ###
# Groups Creation - Backup Groups Section #
### ###
group_to_routers_values = ','.join(str(v) for v in global_variables.group_to_routers_dcn.values())
for bfarm, bservers in global_variables.bck_dcn.iteritems(): # Looping over the backup group to routers dictionary
if len(bservers) > 1: # If the amount of real servers is more than 1, we know we need a backup group
gbck = "%s_BCK" % (bfarm) # Creates the backup group ID
print >>output_file, "/c/slb/group %s_BCK" % (bfarm) # Prints the general backup group general configuration
print >>output_file, " ipver v4"
print >>output_file, " type wanlink"
print >>output_file, " metric %s" % (global_variables.farm_parameters_dcn[bfarm][0]) # We use the metric of the regular group
gbck_dcn_key = "%s" % (bfarm) # Populates a dictionary with the following values: # ---->
# The regular group ID as a key # ---->
# The backup group ID as a value # ---->
# This is used later on to associate the backup group to the regular group
global_variables.gbck_dcn.setdefault(gbck_dcn_key, [])
global_variables.gbck_dcn[gbck_dcn_key].append('%s' % (gbck))
for bserver in bservers: # Loop over the real servers in the backup farm
for bck_user_wl_ip, bck_user_wl_name in global_variables.user_new_wl_names_dcn.iteritems(): # Loop over the user chosen WL IPs and names
add_servers_to_bck_group_fnc(bck_user_wl_ip, bck_user_wl_name) # Executes the function that adds the reals to the group
for bck_orig_wl_ip, bck_orig_wl_name in global_variables.user_equal_wl_names_dcn.iteritems(): # Loops over the equal WL IPs and names
add_servers_to_bck_group_fnc(bck_orig_wl_ip, bck_orig_wl_name) # Executes the function that adds the reals to the group
### ###
# Groups Creation - Regular Groups Section #
### ###
group_to_routers_nonat_values = ','.join(str(v) for v in global_variables.group_to_routers_nonat_dcn.values())
if len(global_variables.group_to_routers_dcn) > 0:
for farm, servers in global_variables.group_to_routers_dcn.iteritems(): # Loops over the regular group to routers dictionary
print >>output_file, "/c/slb/group %s" % (farm) # Prints the general group configuration
print >>output_file, " ipver v4"
print >>output_file, " type wanlink"
if farm in global_variables.farm_parameters_dcn.keys():
print >>output_file, " metric %s" % (global_variables.farm_parameters_dcn[farm][0])
for server in servers: # Loops over the real servers in the regular farm
for user_wl_ip, user_wl_name in global_variables.user_new_wl_names_dcn.iteritems(): # Loop over the user chosen WL IPs and names
add_servers_to_regular_group_fnc(user_wl_ip, user_wl_name[0]) # Executes the function that adds the reals to the group
for orig_wl_ip, orig_wl_name in global_variables.user_equal_wl_names_dcn.iteritems(): # Loops over the equal WL IPs and names
add_servers_to_regular_group_fnc(orig_wl_ip, orig_wl_name[0]) # Executes the function that adds the reals to the group
### ###
# Groups Creation - No NAT Groups Section #
### ###
for farm, servers in global_variables.group_to_routers_nonat_dcn.iteritems(): # Loops over the No NAT group to routers dictionary
print >>output_file, "/c/slb/group %s" % (farm) # Prints the general group configuration
print >>output_file, " ipver v4"
print >>output_file, " type wanlink"
if farm in global_variables.farm_parameters_dcn.keys():
print >>output_file, " metric %s" % (global_variables.farm_parameters_dcn[farm][0])
for server in servers: # Loops over the real servers in the No NAT farm
for nonat_user_wl_ip, nonat_user_wl_name in global_variables.user_new_wl_names_dcn.iteritems(): # Loop over the user chosen WL IPs and names
add_servers_to_nonat_group_fnc(nonat_user_wl_ip, nonat_user_wl_name) # Executes the function that adds the reals to the group
for nonat_orig_wl_ip, nonat_orig_wl_name in global_variables.user_equal_wl_names_dcn.iteritems():
add_servers_to_nonat_group_fnc(nonat_orig_wl_ip, nonat_orig_wl_name) # Executes the function that adds the reals to the group
for farm in global_variables.all_farms_lst: # Loops over the list of farms
if farm not in global_variables.group_to_routers_all_dcn.keys(): # If the farm has no servers, prints the group with no servers
print >>output_file, "/c/slb/group %s" % (farm)
print >>output_file, " ipver v4"
print >>output_file, " type wanlink"
#####################################
#### Groups Creation Section End ####
#####################################
############################################################
#### Default Farm, SLB Ports and DNS VIPs Section Start ####
############################################################
for line in lp_to_lpng: # Loops over the LP configuration
if "farms default-farm set" in line:
default_farm = global_variables.find_fnc( line, '-fn "', '"' ) # Finds the default farm
if default_farm == 'error': # If no double quotes in the default farm
default_farm = global_variables.find_fnc( line, '-fn ', ' ' ) # Finds the default farm again
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
default_farm = default_farm.replace ('%s' % (unsupported_char), "%s" % (supported_char))
if default_farm not in global_variables.default_farm_lst:
global_variables.default_farm_lst.append(default_farm)
### ###
# Default Farm Selection Section #
### ###
## ##
# This is a section used to prompt the user to select the default farm for the default filter #
# This section will be shown to the user only if the LP's default farms are different #
## ##
default_farm_equal_status = global_variables.all_same(global_variables.default_farm_lst) # Checks is all default farms are the same
if default_farm_equal_status == False: # If all default farms are not the same
return render_template('default_filter.html', title='Default Filter', default_group_lst=global_variables.default_group_lst)
else:
return redirect('/page5')
@app.route('/page4', methods=['GET','POST'])
@app.route('/page5', methods=['GET','POST'])
def page4():
def print_dummy_slb_fnc(dns_local_ip, dns_dummy_vip, gslb_network_id):
'''Prints dummy real server, group and virt.
Takes the DNS rule local IP, DNS dummy VIP and GSLB network ID as arguments.
This fucntion is used for cases where Alteon needs to respond to DNS queries with the local IP.
IP range 169.254.0.1 to 169.254.7.254 is used for the dummy VIP.
IP 169.254.254.253 is used for the dummy local real server and IP 169.254.254.254 is used for the dummy WL real server.
'''
if global_variables.dummy_status == 0:
print >>output_file, "/c/slb/real Dummy_Local_Srv"
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " rip 169.254.254.253"
print >>output_file, " health NoCheck"
print >>output_file, ' name "Dummy Real for DNS Resolution"'
print >>output_file, "/c/slb/real Dummy_WL"
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " rip 169.254.254.254"
print >>output_file, " type wanlink"
print >>output_file, " health NoCheck"
print >>output_file, ' name "Dummy WL for DNS Resolution"'
print >>output_file, "/c/slb/group Dummy_Local_GRP"
print >>output_file, " ipver v4"
print >>output_file, " add Dummy_Local_Srv"
print >>output_file, ' name "Dummy Group for DNS Resolution"'
print >>output_file, "/c/slb/virt Local_%s" % (dns_local_ip)
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " vip %s" % (dns_dummy_vip)
print >>output_file, " nat %s" % (dns_local_ip)
print >>output_file, " rtsrcmac ena"
print >>output_file, ' vname "Dummy VIP for IP %s"' % (dns_local_ip)
print >>output_file, ' dname "inherit"'
print >>output_file, ' wanlink "Dummy_WL"'
print >>output_file, "/c/slb/virt Local_%s/service 1234 basic-slb" % (dns_local_ip)
print >>output_file, ' name "Dummy Service for DNS Resolution"'
print >>output_file, " group Dummy_Local_GRP"
print >>output_file, " rport 1234"
print >>output_file, "/c/slb/gslb/network %s" % (gslb_network_id)
print >>output_file, " ena"
print >>output_file, " addvirt Local_%s 65535" % (dns_local_ip)
global_variables.nonat_gslb_nets_lst.append(gslb_network_id)
def create_smartat_local_range(nat_type):
'''This function is used to check if the No NAT local IP range includes unusable addresses.
We loop over all local IPs, then we check against the dictionary that includes all unusable IPs.
If we find that an unusable IP is in the local IP range, we remove it.
We then create the repsective local IP network class.
The function takes the NAT type as an argument.
'''
smartnat_local_range_new_lst1 = [] # Creates No NAT local IPs lists # ---->
# These lists are then used to hold to usable local IPs for Smart NAT entry
# Usable local IPs include any IP which is not network, broadcast, interface IP or peer interface IP
smartnat_local_range_new_lst2 = []
smartnat_local_range_new_lst3 = []
smartnat_local_range_new_lst4 = []
smartnat_local_range_new_lst5 = []
smartnat_local_range_new_lst6 = []
smartnat_local_range_new_lst7 = []
smartnat_local_range_lst_idx = 0
smartnat_local_nwclss_net_id = 0
smartnat_local_loop_status = ""
for x, smartnat_local_addr in enumerate(smartnat_localip_range): # Loop over the local IPs list
if smartnat_local_addr not in global_variables.own_addresses_lst: # If the local IP is not in the unsupported IPs list
smartnat_local_range_new_lst1.append(smartnat_local_addr) # We add it to the range of supported addresses
if x == len(smartnat_localip_range) - 1: # If we're in the end of the local IPs list, we mark it as last
smartnat_local_loop_status = "last"
else: # If the local IP is in the unsupported IPs list
smartnat_local_range_lst_idx = x + 1 # We increment the last list index by 1 and break the loop
break
if smartnat_local_loop_status != "last": # We check if we're in the end of the local IPs list and if not, continue
for x, smartnat_local_addr in enumerate(smartnat_localip_range[smartnat_local_range_lst_idx:]): # Loop again over the local IPs list, strating from the last non looped index
if smartnat_local_addr not in global_variables.own_addresses_lst: # If the local IP is not in the unsupported IPs list
smartnat_local_range_new_lst2.append(smartnat_local_addr) # We add it to the range of supported addresses
if smartnat_local_range_lst_idx + x == len(smartnat_localip_range) - 1: # If we're in the end of the local IPs list, we mark it as last
smartnat_local_loop_status = "last"
else: # If the local IP is in the unsupported IPs list
smartnat_local_range_lst_idx = x + smartnat_local_range_lst_idx + 1 # We increment the last list index by 1 and break the loop
break
if smartnat_local_loop_status != "last": # Repeat the same logic again as per the amount of unsupported IPs + 1
for x, smartnat_local_addr in enumerate(smartnat_localip_range[smartnat_local_range_lst_idx:]):
if smartnat_local_addr not in global_variables.own_addresses_lst:
smartnat_local_range_new_lst3.append(smartnat_local_addr)
if smartnat_local_range_lst_idx + x == len(smartnat_localip_range) - 1:
smartnat_local_loop_status = "last"
else:
smartnat_local_range_lst_idx = x + smartnat_local_range_lst_idx + 1
break
if smartnat_local_loop_status != "last":
for x, smartnat_local_addr in enumerate(smartnat_localip_range[smartnat_local_range_lst_idx:]):
if smartnat_local_addr not in global_variables.own_addresses_lst:
smartnat_local_range_new_lst4.append(smartnat_local_addr)
if smartnat_local_range_lst_idx + x == len(smartnat_localip_range) - 1:
smartnat_local_loop_status = "last"
else:
smartnat_local_range_lst_idx = x + smartnat_local_range_lst_idx + 1
break
if smartnat_local_loop_status != "last":
for x, smartnat_local_addr in enumerate(smartnat_localip_range[smartnat_local_range_lst_idx:]):
if smartnat_local_addr not in global_variables.own_addresses_lst:
smartnat_local_range_new_lst5.append(smartnat_local_addr)
if smartnat_local_range_lst_idx + x == len(smartnat_localip_range) - 1:
smartnat_local_loop_status = "last"
else:
smartnat_local_range_lst_idx = x + smartnat_local_range_lst_idx + 1
break
if smartnat_local_loop_status != "last":
for x, smartnat_local_addr in enumerate(smartnat_localip_range[smartnat_local_range_lst_idx:]):
if smartnat_local_addr not in global_variables.own_addresses_lst:
smartnat_local_range_new_lst6.append(smartnat_local_addr)
if smartnat_local_range_lst_idx + x == len(smartnat_localip_range) - 1:
smartnat_local_loop_status = "last"
else:
smartnat_local_range_lst_idx = x + smartnat_local_range_lst_idx + 1
break
if smartnat_local_loop_status != "last":
for x, smartnat_local_addr in enumerate(smartnat_localip_range[smartnat_local_range_lst_idx:]):
if smartnat_local_addr not in global_variables.own_addresses_lst:
smartnat_local_range_new_lst7.append(smartnat_local_addr)
if nat_type == "SNN":
smartnat_local_nwclss_id = global_variables.locl_snn_nwclss_id
else:
smartnat_local_nwclss_id = global_variables.locl_snd_nwclss_id
if smartnat_local_range_new_lst1: # If the first supported local IP list is not empty
if smartnat_local_nwclss_net_id == 0: # We check if the net ID is 0, this way we know that we didn't yet create the network class
print >>output_file, "/c/slb/nwclss %s_Local_%s" % (nat_type, smartnat_local_nwclss_id) # We then create the general network class configuration
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss %s_Local_%s/network %s" % (nat_type, smartnat_local_nwclss_id, smartnat_local_nwclss_net_id) # We create the first net
print >>output_file, " net range %s %s include" % (smartnat_local_range_new_lst1[0], smartnat_local_range_new_lst1[-1])
smartnat_local_nwclss_net_id += 1 # We increment the net ID
if smartnat_local_range_new_lst2: # If the 2nd supported local IP list is not empty
if smartnat_local_nwclss_net_id == 0: # We repeat the same logic for all local IPs lists
print >>output_file, "/c/slb/nwclss %s_Local_%s" % (nat_type, smartnat_local_nwclss_id)
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss %s_Local_%s/network %s" % (nat_type, smartnat_local_nwclss_id, smartnat_local_nwclss_net_id)
print >>output_file, " net range %s %s include" % (smartnat_local_range_new_lst2[0], smartnat_local_range_new_lst2[-1])
smartnat_local_nwclss_net_id += 1
if smartnat_local_range_new_lst3:
if smartnat_local_nwclss_net_id == 0:
print >>output_file, "/c/slb/nwclss %s_Local_%s" % (nat_type, smartnat_local_nwclss_id)
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss %s_Local_%s/network %s" % (nat_type, smartnat_local_nwclss_id, smartnat_local_nwclss_net_id)
print >>output_file, " net range %s %s include" % (smartnat_local_range_new_lst3[0], smartnat_local_range_new_lst3[-1])
smartnat_local_nwclss_net_id += 1
if smartnat_local_range_new_lst4:
if smartnat_local_nwclss_net_id == 0:
print >>output_file, "/c/slb/nwclss %s_Local_%s" % (nat_type, smartnat_local_nwclss_id)
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss %s_Local_%s/network %s" % (nat_type, smartnat_local_nwclss_id, smartnat_local_nwclss_net_id)
print >>output_file, " net range %s %s include" % (smartnat_local_range_new_lst4[0], smartnat_local_range_new_lst4[-1])
smartnat_local_nwclss_net_id += 1
if smartnat_local_range_new_lst5:
if smartnat_local_nwclss_net_id == 0:
print >>output_file, "/c/slb/nwclss %s_Local_%s" % (nat_type, smartnat_local_nwclss_id)
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss %s_Local_%s/network %s" % (nat_type, smartnat_local_nwclss_id, smartnat_local_nwclss_net_id)
print >>output_file, " net range %s %s include" % (smartnat_local_range_new_lst5[0], smartnat_local_range_new_lst5[-1])
smartnat_local_nwclss_net_id += 1
if smartnat_local_range_new_lst6:
if smartnat_local_nwclss_net_id == 0:
print >>output_file, "/c/slb/nwclss %s_Local_%s" % (nat_type, smartnat_local_nwclss_id)
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss %s_Local_%s/network %s" % (nat_type, smartnat_local_nwclss_id, smartnat_local_nwclss_net_id)
print >>output_file, " net range %s %s include" % (smartnat_local_range_new_lst6[0], smartnat_local_range_new_lst6[-1])
smartnat_local_nwclss_net_id += 1
if smartnat_local_range_new_lst7:
if smartnat_local_nwclss_net_id == 0:
print >>output_file, "/c/slb/nwclss %s_Local_%s" % (nat_type, smartnat_local_nwclss_id)
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss %s_Local_%s/network %s" % (nat_type, smartnat_local_nwclss_id, smartnat_local_nwclss_net_id)
print >>output_file, " net range %s %s include" % (smartnat_local_range_new_lst7[0], smartnat_local_range_new_lst7[-1])
if request.path == '/page4':
default_group = str(request.form['default_group'])
else: # If all default farms are the same, we will use the default farm for the default filter and only present the below note for the user
default_group = global_variables.default_farm_lst[0] # Creates a variable which is the default farm bame, will be used later on the default filter
### ###
# SLB Ports Section #
### ###
## ##
# This is a section used to create the SLB ports configuration and enable filter processing #
# In this section we loop over all of the ports that was chosen by the user in the beginning of the script #
# We then use these ports when creating the SLB ports configuration #
## ##
for port in allports: # Loops over the list of all user chosen ports
print >>output_file, '/c/slb/port "%s"' % (port) # Prints the SLB ports configuration
print >>output_file, " filt ena"
for line in lp_to_lpng: # Loops over the LP configuration
### ###
# DNS VIPs Section #
### ###
## ##
# This is a section used to create the DNS VIPs configuration #
# In this section we look for the DNS VIPs in the LP configuration and print the corresponding Alteon configuration #
## ##
if "lp dns virtual-ip create" in line:
dns_vip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the DNS VIP
print >>output_file, "/c/slb/gslb/dnsresvip DnsResp%s,DnsResp%s" % (global_variables.dns_vip_id1, global_variables.dns_vip_id2) # Prints the DNS VIP configuration
print >>output_file, " ipver v4"
print >>output_file, " vip %s" % (dns_vip[0])
print >>output_file, " ena"
print >>output_file, " rtsrcmac ena"
if dns_vip[0] not in global_variables.own_addresses_lst:
global_variables.own_addresses_lst.append(dns_vip[0])
global_variables.dns_vip_id1 += 2 # used to increment the first DNS VIP ID
global_variables.dns_vip_id2 += 2 # Used to increment the second DNS VIP ID
##########################################################
#### Default Farm, SLB Ports and DNS VIPs Section End ####
##########################################################
#################################
#### Smart NAT Section Start ####
#################################
for line in lp_to_lpng: # Loops over the LP configuration
### ###
# Smart NAT Configuration - Main Section #
### ###
## ##
# This is the main section used to configure all of the Smart NAT configuration #
# In this section, we fine the Smart NAT configuration and print the Alteon equivalent #
# #
# Rules: #
# #
# 1.) We configure the following Smart NAT types: #
# a. Dynamic NAT #
# b. Static NAT #
# c. No NAT #
# d. Static PAT (using virts) #
# 2.) On dynamic NAT, we treat the following loca IPs as "any" in Alteon: #
# a. 0.0.0.0 #
# b. 0.0.0.1 #
# c. 1.0.0.0 #
# d. 1.0.0.1 #
# 3.) On No NAT, we check the if the local IP range has the following IP addresses: #
# a. Network address of any network on the LP #
# b. Broadcast address of any network on the LP #
# c. Any interface IP on the LP #
# d. Any peer interface IP on the LP #
# The above IP addresses are not supported as local IPs in Smart NAT entry #
# If we find them, we remove them and create the network class without them #
## ##
### ###
# Smart NAT Dynamic NAT Section #
### ###
## ##
# This section is used to find and configure the Smart NAT dynamic NAT #
## ##
if "smartnat dynamic-nat" in line:
find_snd_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds all relevant IP addresses (local from, local to, WAN link, NAT)
if find_snd_ip[0] == find_snd_ip[1]: # If the "Local IP From" is the same as the "Local IP To", uses mode address
snd_local_ip = "%s 255.255.255.255" % (find_snd_ip[0]) # The local IP
elif find_snd_ip[0] == '0.0.0.0': # If the "Local IP From" is one of the below options, we use "any" in Alteon
snd_local_ip = 'any'
elif find_snd_ip[0] == '0.0.0.1':
snd_local_ip = 'any'
elif find_snd_ip[0] == '1.0.0.0':
snd_local_ip = 'any'
elif find_snd_ip[0] == '1.0.0.1':
snd_local_ip = 'any'
elif find_snd_ip[0] == find_snd_ip[1]:
snd_local_ip = "%s 255.255.255.255" % (find_snd_ip[0])
else: # If the "Local IP From" is not one of the above, we define a network class for the local IP range
smartnat_localip_range = global_variables.ipRange_fnc(find_snd_ip[0], find_snd_ip[1]) # Finds all IP addresses in the local IP range
global_variables.locl_snd_nwclss_id += 1
global_variables.smartnat_local_nwclss_id += 1
create_smartat_local_range("SND") # Executes the function that creates the network classes
snd_local_ip = "SND_Local_%s" % (global_variables.locl_snd_nwclss_id) # This is the local IP network class name
wan_ip_nat = find_snd_ip[2] # Defines the WAN link IP
if wan_ip_nat in global_variables.user_new_wl_names_dcn: # Loops for the WAN link IP in the user chosen WL names dictionary in order to map it to the WAN link name
if len(global_variables.user_new_wl_names_dcn[wan_ip_nat]) > 0:
wanlink = global_variables.user_new_wl_names_dcn[wan_ip_nat][0] # We then define the WAN link name to be associated with the Smart NAT entry
elif wan_ip_nat in global_variables.duplicate_wls_dcn: # If the WAN link IP is not in the user chosen WL names, we loop in the single WL names dictionary to find it
if len(global_variables.duplicate_wls_dcn[wan_ip_nat]) > 0:
wanlink = global_variables.duplicate_wls_dcn[wan_ip_nat][0] # We then define the WAN link name to be associated with the Smart NAT entry
global_variables.smartnat_id += 1 # Smart NAT ID will be incremented by 1 for each entry
print >>output_file, "/c/slb/lp/nat %s" % (global_variables.smartnat_id) # Prints the Smart NAT dynamic NAT configuration
print >>output_file, " type dynamic"
print >>output_file, " wanlink %s" % (wanlink)
print >>output_file, " locladd %s" % (snd_local_ip)
print >>output_file, " natadd %s 255.255.255.255" % (find_snd_ip[3])
### ###
# Smart NAT Static NAT Section #
### ###
## ##
# This section is used to find and configure the Smart NAT static NAT #
## ##
if "smartnat static-nat" in line:
find_sns_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds all relevant IP addresses (local from, local to, WAN link, NAT IP from, NAT IP to)
if find_sns_ip[0] == find_sns_ip[1]: # If the "Local IP From" is the same as the "Local IP To" and if it is, uses mode address
sns_local_ip = "%s 255.255.255.255" % (find_sns_ip[0]) # The local IP
sns_nat_ip = "%s 255.255.255.255" % (find_sns_ip[3]) # The NAT IP
if find_sns_ip[0] not in global_variables.smart_nat_local_ips_lst: # Appends the local IP to a list with all Smart NAT local IPs # ---->
# This is later on used to check if a DNS rule local IP is not in this list and in this case, the DNS rule won't be configured
global_variables.smart_nat_local_ips_lst.append("%s" % (find_sns_ip[0]))
else: # If the "Local IP From" is not the same as the "Local IP To", users mode nwclss
sns_localip_range = global_variables.ipRange_fnc(find_sns_ip[0], find_sns_ip[1]) # Finds all IP addresses in the local IP range
for localip in sns_localip_range: # Appends each local IP to a list with all Smart NAT local IPs # ---->
# This is later on used to check if a DNS rule local IP is not in this list and in this case, the DNS rule won't be configured
if localip not in global_variables.smart_nat_local_ips_lst:
global_variables.smart_nat_local_ips_lst.append("%s" % (localip))
current_sns_local_range = "%s_%s" % (find_sns_ip[0], find_sns_ip[1])
for sns_local_range_key, sns_nwclss_id_value in global_variables.sns_local_range_to_nwclss_dcn.iteritems():
if sns_local_range_key == current_sns_local_range:
sns_local_ip = sns_nwclss_id_value[0]
break
else:
global_variables.locl_sns_nwclss_id += 1 # Increments the local IP network class ID
sns_local_ip = "SNS_Local_%s" % (global_variables.locl_sns_nwclss_id) # This is the local IP netowrk class name
print >>output_file, "/c/slb/nwclss SNS_Local_%s" % (global_variables.locl_sns_nwclss_id) # Prints the local IP network class
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss SNS_Local_%s/network 0" % (global_variables.locl_sns_nwclss_id)
print >>output_file, " net range %s %s include" % (find_sns_ip[0], find_sns_ip[1])
sns_local_range_to_nwclss_dcn_key = "%s" % (current_sns_local_range)
global_variables.sns_local_range_to_nwclss_dcn.setdefault(sns_local_range_to_nwclss_dcn_key, [])
global_variables.sns_local_range_to_nwclss_dcn[sns_local_range_to_nwclss_dcn_key].append('%s' % (sns_local_ip))
global_variables.nat_sns_nwclss_id += 1 # Increments the NAT IP network class ID
sns_nat_ip = "SNS_NAT_%s" % (global_variables.nat_sns_nwclss_id) # This is the NAT IP network class
print >>output_file, "/c/slb/nwclss SNS_NAT_%s" % (global_variables.nat_sns_nwclss_id) # Prints the NAT IP network class
print >>output_file, ' type "address"'
print >>output_file, "/c/slb/nwclss SNS_NAT_%s/network 0" % (global_variables.nat_sns_nwclss_id)
print >>output_file, " net range %s %s include" % (find_sns_ip[3], find_sns_ip[4])
wan_ip_nat = find_sns_ip[2] # Defines the WAN link IP, then extracts the WAN link name from the dictionaries
if wan_ip_nat in global_variables.user_new_wl_names_dcn:
if len(global_variables.user_new_wl_names_dcn[wan_ip_nat]) > 0:
wanlink = global_variables.user_new_wl_names_dcn[wan_ip_nat][0]
elif wan_ip_nat in global_variables.duplicate_wls_dcn:
if len(global_variables.duplicate_wls_dcn[wan_ip_nat]) > 0:
wanlink = global_variables.duplicate_wls_dcn[wan_ip_nat][0]
global_variables.smartnat_id += 1 # Increments the Smart NAT ID
print >>output_file, "/c/slb/lp/nat %s" % (global_variables.smartnat_id) # Prints the Smart NAT static NAT configuration
print >>output_file, " type static"
print >>output_file, " wanlink %s" % (wanlink)
print >>output_file, " locladd %s" % (sns_local_ip)
print >>output_file, " natadd %s" % (sns_nat_ip)
### ###
# Smart NAT No NAT Section #
### ###
## ##
# This section is used to find and configure the Smart NAT No NAT #
## ##
if "smartnat no-nat" in line:
find_snn_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds all relevant IP addresses (local from, local to and WAN link)
if find_snn_ip[0] == find_snn_ip[1]: # If the "Local IP From" is the same as the "Local IP To" and if it is, uses mode address
snn_local_ip = "%s 255.255.255.255" % (find_snn_ip[0]) # The local IP
if find_snn_ip[0] not in global_variables.smart_nat_local_ips_lst:
global_variables.smart_nat_local_ips_lst.append("%s" % (find_snn_ip[0]))
else: # If the "Local IP From" is not the same as the "Local IP To", users mode nwclss
smartnat_localip_range = global_variables.ipRange_fnc(find_snn_ip[0], find_snn_ip[1]) # Finds all IP addresses in the local IP range # ---->
# Specifically for No NAT, this is later on used to find if any of these IPs is network, broadcast, interface or peer interface
for localip in smartnat_localip_range:
if localip not in global_variables.smart_nat_local_ips_lst:
global_variables.smart_nat_local_ips_lst.append("%s" % (localip))
global_variables.locl_snn_nwclss_id += 1
global_variables.smartnat_local_nwclss_id += 1
create_smartat_local_range("SNN") # Executes the function that creates the network class
snn_local_ip = "SNN_Local_%s" % (global_variables.locl_snn_nwclss_id) # This is the local IP network class name
wan_ip_nat = find_snn_ip[2] # Defines the WAN link IP, then extracts the WAN link name from the dictionaries
if wan_ip_nat in global_variables.user_new_wl_names_dcn:
if len(global_variables.user_new_wl_names_dcn[wan_ip_nat]) > 0:
wanlink = global_variables.user_new_wl_names_dcn[wan_ip_nat][0]
elif wan_ip_nat in global_variables.duplicate_wls_dcn:
if len(global_variables.duplicate_wls_dcn[wan_ip_nat]) > 0:
wanlink = global_variables.duplicate_wls_dcn[wan_ip_nat][0]
global_variables.smartnat_id += 1 # Increments the Smart NAT ID
print >>output_file, "/c/slb/lp/nat %s" % (global_variables.smartnat_id) # Prints the Smart NAT No NAT configuration
print >>output_file, " wanlink %s" % (wanlink)
print >>output_file, " locladd %s" % (snn_local_ip)
nonat_port = [int(s) for s in line.split() if s.isdigit()]
if nonat_port[0] != 0:
current_time = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')
print >>migration_errors, '\033[1m%s\033[0m #Unsupported_flag_option: the following command contains a flag with an unsupported option:' % (current_time)
print >>migration_errors, ' Command: %s' % (line)
print >>migration_errors, ' Unsupported flag option: No NAT Destination Port which is not 0.'
print >>migration_errors, ' Alteon will treat it as 0 (any).'
### ###
# Smart NAT Static PAT Section #
### ###
## ##
# This section is used to find and configure the Smart NAT Static PAT #
## ##
if "smartnat static-pat" in line:
find_snp_ip = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds all relevant IP addresses (internal, external, WAN link)
global_variables.type_group_local_lst.append("%s" % (find_snp_ip[0])) # Populates a list with the internal IPs as objects # ---->
# This is later on used to identify that it's a PAT, to create GSLB network of type "group"
if find_snp_ip[0] not in global_variables.smart_nat_local_ips_lst: # Appends the local IP to a list with all Smart NAT local IPs # ---->
# This is later on used to check if a DNS rule local IP is not in this list and in this case, the DNS rule won't be configured
global_variables.smart_nat_local_ips_lst.append("%s" % (find_snp_ip[0]))
find_snp_ports = [int(s) for s in line.split() if s.isdigit()] # Finds the internal and external ports
wan_ip_nat = find_snp_ip[1] # Defines the WAN link IP, then extracts the WAN link name from the dictionaries
if wan_ip_nat in global_variables.user_new_wl_names_dcn:
if len(global_variables.user_new_wl_names_dcn[wan_ip_nat]) > 0:
wanlink = global_variables.user_new_wl_names_dcn[wan_ip_nat][0]
elif wan_ip_nat in global_variables.duplicate_wls_dcn:
if len(global_variables.duplicate_wls_dcn[wan_ip_nat]) > 0:
wanlink = global_variables.duplicate_wls_dcn[wan_ip_nat][0]
snp_protocol = global_variables.find_fnc( line, "%s " % (find_snp_ports[0]), " " ) # Finds the PAT protocol
snp_name = global_variables.find_fnc( line, ' -pn "', '"' ) # Finds the PAT name
if snp_name == 'error': # If no double quotes, finds it again
snp_name = global_variables.find_fnc( line, " -pn ", " " )
snp_real_to_virt_dcn_key = "%s" % (find_snp_ip[0]) # Populates a dictionary with the following values: # ---->
# The internal IP as a key # ---->
# The external IP as a value # ---->
# This is later on used to add the correct virt to the GSLB network
global_variables.snp_real_to_virt_dcn.setdefault(snp_real_to_virt_dcn_key, [])
global_variables.snp_real_to_virt_dcn[snp_real_to_virt_dcn_key].append('%s' % (find_snp_ip[2]))
snp_virt_to_service_dcn_key = "%s" % (find_snp_ip[2]) # Populates a dictionary with the following values: # ---->
# The external IP as a key
# The external port as a value
# This is used later on to print the correct service on the GSLB rule
global_variables.snp_virt_to_service_dcn.setdefault(snp_virt_to_service_dcn_key, [])
global_variables.snp_virt_to_service_dcn[snp_virt_to_service_dcn_key].append('%s' % (find_snp_ports[1]))
print >>output_file, "/c/slb/real Srv_%s" % (find_snp_ip[0]) # Starts printing the real server (the internal IP)
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " rip %s" % (find_snp_ip[0])
print >>output_file, " health NoCheck"
print >>output_file, ' name "PAT Srv %s"' % (find_snp_ip[0])
print >>output_file, "/c/slb/group Srv_%s" % (find_snp_ip[0]) # Starts printing the group (for the internal IP)
print >>output_file, " ipver v4"
print >>output_file, " add Srv_%s" % (find_snp_ip[0])
print >>output_file, ' name "Group 4 PAT Srv %s"' % (find_snp_ip[0])
print >>output_file, "/c/slb/virt PAT_%s" % (find_snp_ip[2]) # Starts printing the virt (the external IP)
print >>output_file, " ena"
print >>output_file, " ipver v4"
print >>output_file, " vip %s" % (find_snp_ip[2])
print >>output_file, " rtsrcmac ena"
print >>output_file, ' vname "PAT %s"' % (find_snp_ip[2])
print >>output_file, ' dname "inherit"'
print >>output_file, ' wanlink "%s"' % (wanlink) # Associates the WAN link
if str(find_snp_ports[1]) in global_variables.port_to_service_dcn.keys(): # If the external port is a well-known port, we print the known service
print >>output_file, "/c/slb/virt PAT_%s/service %s %s" % (find_snp_ip[2], find_snp_ports[1], global_variables.port_to_service_dcn[str(find_snp_ports[1])])
else: # If it's not a well-known port, we print >>output_file, "basic-slb"
print >>output_file, "/c/slb/virt PAT_%s/service %s basic-slb" % (find_snp_ip[2], find_snp_ports[1])
if snp_name == 'error':
print >>output_file, ' name "PAT %s, %s"' % (find_snp_ip[2], find_snp_ports[1])
else:
print >>output_file, ' name "PAT %s"' % (snp_name)
print >>output_file, " group Srv_%s" % (find_snp_ip[0]) # Assicates the group (the internal IP)
print >>output_file, " rport %s" % (find_snp_ports[0]) # Configures the rport (the internal port)
print >>output_file, " protocol %s" % (snp_protocol) # Configuration the protocol
print >>output_file, " tmout %s" % (max_aging_time)
if alt_ha_mode == 1 or alt_ha_mode == 2:
print >>output_file, " mirror ena"
###############################
#### Smart NAT Section End ####
###############################
#######################################
#### Network Classes Section Start ####
#######################################
for line in lp_to_lpng: # Loops over the LP configuration
### ###
# Network Classes Configuration - Main Section #
### ###
## ##
# This is the main section used to find and configure all the network classes #
## ##
if "classes modify network" in line:
class_name = global_variables.find_fnc( line, 'setCreate "', '"' ) # Finds the network class name
if class_name == 'error': # If no double qoutes, finds again
class_name = global_variables.find_fnc( line, 'setCreate ', ' ' )
new_class_name = class_name
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
new_class_name = new_class_name.replace ('%s' % (unsupported_char), "%s" % (supported_char))
class_id = global_variables.find_fnc( line, '%s" ' % (class_name), " " ) # Finds the network class ID
if class_id == 'error': # If not double quotes in the network class name, finds again
class_id = global_variables.find_fnc( line, '%s ' % (class_name), " " )
print >>output_file, "/c/slb/nwclss %s" % (new_class_name) # Starts printing the network class general configuration
print >>output_file, ' type "address"'
class_mode = global_variables.find_fnc( line, ' -m "', '"' ) # Finds the network class mode
if class_mode == 'IP Mask': # If the network class mode is "IP Mask"
class_addr = global_variables.find_fnc( line, " -a ", " " ) # Finds the network class address
class_mask = global_variables.find_fnc( line, " -s ", " " ) # Finds the network class mask
print >>output_file, "/c/slb/nwclss %s/network %s" % (new_class_name, class_id) # Starts printing the net, in mode subnet
print >>output_file, " net subnet %s %s include" % (class_addr, class_mask)
elif class_mode == 'IP Range': # If the network class mode is "IP Range"
class_from = global_variables.find_fnc( line, " -f ", " " ) # Finds the network class range start
class_to = global_variables.find_fnc( line, " -t ", " " ) # Finds the network class range end
print >>output_file, "/c/slb/nwclss %s/network %s" % (new_class_name, class_id) # Starts printing the net, in mode range
print >>output_file, " net range %s %s include" % (class_from, class_to)
#####################################
#### Network Classes Section End ####
#####################################
#####################################################
#### Outbound Policies and Filters Section Start ####
#####################################################
### ###
# Outbound Policies and filters - Filters 1-3 #
### ###
## ##
# This is the section used to configure filters 1-3 #
# These filters are used to catch important traffic, so it won't mistakenly match other filters: #
# #
# 1.) Filter 1 - Catch broadcasts and allow #
# 2.) Filter 2 - Catch multicasts and allow #
# 3.) Filter 3 - Catch traffic to local networks and allow #
## ##
print >>output_file, "/c/slb/filt 1" # Starts printing filter 1
print >>output_file, ' name "Broadcasts"'
print >>output_file, " ena"
print >>output_file, " action allow"
print >>output_file, " ipver v4"
print >>output_file, " sip any"
print >>output_file, " smask 0.0.0.0"
print >>output_file, " dmac ff:ff:ff:ff:ff:ff"
print >>output_file, " group 1"
print >>output_file, " rport 0"
print >>output_file, " vlan any"
for port in allports: # Loops over all ports list to add all ports
print >>output_file, " add %s" % (port)
print >>output_file, "/c/slb/filt 1/adv"
print >>output_file, " cache dis"
print >>output_file, " reverse ena"
print >>output_file, "/c/slb/nwclss Multicast" # Starts printing the multicast network class
print >>output_file, ' type "address"'
print >>output_file, " ipver v4"
print >>output_file, "/c/slb/nwclss Multicast/network 0"
print >>output_file, " net subnet 224.0.0.0 240.0.0.0 include"
print >>output_file, "/c/slb/filt 2" # Starts printing filter 2
print >>output_file, ' name "Multicast"'
print >>output_file, " ena"
print >>output_file, " action allow"
print >>output_file, " ipver v4"
print >>output_file, " sip any"
print >>output_file, " smask 0.0.0.0"
print >>output_file, " dip Multicast"
print >>output_file, " group 1"
print >>output_file, " rport 0"
print >>output_file, " vlan any"
for port in allports: # Loops over all ports list to add all ports
print >>output_file, " add %s" % (port)
print >>output_file, "/c/slb/filt 2/adv"
print >>output_file, " cache dis"
print >>output_file, " reverse ena"
print >>output_file, "/c/slb/nwclss Local_Networks" # Starts printing the local networks network class general configuration
print >>output_file, ' type "address"'
for subnet, mask in global_variables.subnet_to_mask_dcn.iteritems(): # Loops over the local subnets to mask dictionary
print >>output_file, "/c/slb/nwclss Local_Networks/net %s" % (global_variables.local_nets_nwclss_net_id) # For each local subnet, prints net
print >>output_file, " net subnet %s %s include" % (subnet, mask[0])
global_variables.local_nets_nwclss_net_id += 1
print >>output_file, "/c/slb/filt 3" # Starts printing filter 3
print >>output_file, ' name "Allow Local Networks"'
print >>output_file, " ena"
print >>output_file, " action allow"
print >>output_file, " ipver v4"
print >>output_file, " sip any"
print >>output_file, " smask 0.0.0.0"
print >>output_file, " dip Local_Networks"
print >>output_file, " group 1"
print >>output_file, " rport 0"
print >>output_file, " vlan any"
for port in allports: # Loops over all ports list to add all ports
print >>output_file, " add %s" % (port)
print >>output_file, "/c/slb/filt 3/adv"
print >>output_file, " cache dis"
print >>output_file, " reverse ena"
for line in lp_to_lpng: # Loops over the LP configuration
### ###
# Outbound Policies and filters - Finding the services classes #
### ###
## ##
# This is the section used to find the services classes #
# In this section, we find only the basic services and or-groups #
# They're later on used on the filters #
## ##
if "classes modify service basic" in line:
basic_service_name = global_variables.find_fnc( line, ' setCreate "', '"' ) # Finds the basic service name
if basic_service_name == 'error': # If no double quotes, find again
basic_service_name = global_variables.find_fnc( line, " setCreate ", " " )
basic_service_protocol = global_variables.find_fnc( line, " -pr ", " " ) # Finds the basic service protocol
basic_service_dport = global_variables.find_fnc( line, " -dp ", " " ) # Finds the basic service destination port
user_defined_basic_services_key = "%s" % (basic_service_name) # Populates a dictionary with the following values: # ---->
# Basic services name as a key # ---->
# A list containing the protocol and dport as values # ---->
# This is later on used to configure the dport on the filters
global_variables.user_defined_basic_services_dcn.setdefault(user_defined_basic_services_key, [])
global_variables.user_defined_basic_services_dcn[user_defined_basic_services_key].append('%s' % (basic_service_protocol))
global_variables.user_defined_basic_services_dcn[user_defined_basic_services_key].append('%s' % (basic_service_dport))
### ###
# Outbound Policies and filters - Main Section #
### ###
## ##
# This is the main section used to find the outbound policies and print the filters #
# In this section, we find the outbound policies configuraiton and we print the filters accordingly #
# #
# Rules: #
# #
# 1.) Even if the policies we not ordered in the LP configuration, we print them in the correct order #
# 2.) We always start with filter index 101 #
# This means that the original policy ID will have its index incremented by 100 on the Alteon #
# This is because the first filters (1-3) are for the broadcasts, multicasts and local networks #
# 3.) We convert only policies with basic services, or-groups or no service #
# We will convert the following services: #
# a. User defined basic services #
# b. Default system basic services #
# c. Default system or-groups #
# #
# We will not convert user defined or-groups and any and-groups #
# 4.) For policies with services that have more than one service port which is not continuous: #
# a. We duplicate the filter per the amount of services #
# b. We append the following to the end of the original policy name #
# i. An underscore ("_") #
# ii. An incermenting number (starting from 1) to the end of the original policy name #
# c. We retain the original gap between the policies #
## ##
if "modify-policy-table" in line:
policy_id = global_variables.find_fnc( line, " -i ", " " ) # Finds the policy ID
key_outbound_pols_dcn = "%s" % (line) # Populates a dictionary with the following values: # ---->
# The complete policy configuration line as a key # ---->
# The policy ID as a value # ---->
# This is used later on to sort the policies based on their IDs
global_variables.outbound_pols_dcn.setdefault(key_outbound_pols_dcn, [])
global_variables.outbound_pols_dcn[key_outbound_pols_dcn].append('%s' % (policy_id))
int_outbound_pols_dcn = {k:int(v[0]) for k, v in global_variables.outbound_pols_dcn.iteritems()} # Converts the values to integers
sorted_int_outbound_pols_dcn = sorted(int_outbound_pols_dcn.items(), key=operator.itemgetter(1)) # Converts the dictionary to a list of tuples and sorts it
for cmd, pol_id in sorted_int_outbound_pols_dcn: # Loops over the sorted policy configuration
### ###
# Find Policy Configuration Section #
### ###
policy_id = global_variables.find_fnc( cmd, " -i ", " " ) # Finds the policy ID
policy_id = int(policy_id) # Converts the policy ID to an integer
new_policy_id = policy_id - global_variables.static_pol_id # Not in use anymore
policy_name = global_variables.find_fnc( cmd, "setCreate ", " -i" ) # Finds the policy name
policy_name = policy_name.replace ('"', "")
policy_dst = global_variables.find_fnc( cmd, ' -dst "', '" ' ) # Finds policy destination port
if policy_dst == 'error': # If no double quotes, finds again
policy_dst = global_variables.find_fnc( cmd, ' -dst ', ' ' )
if policy_dst == 'error': # If no destination port, it's "any"
policy_dst = 'any'
if policy_dst != 'error':
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
policy_dst = policy_dst.replace ('%s' % (unsupported_char), "%s" % (supported_char))
policy_src = global_variables.find_fnc( cmd, ' -src "', '" ' ) # Finds the policy source port
if policy_src == 'error': # If no double quotes, find again
policy_src = global_variables.find_fnc( cmd, ' -src ', ' ' )
if policy_src == 'error': # If not source port, it's "any"
policy_src = 'any'
if policy_src != 'error':
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
policy_src = policy_src.replace ('%s' % (unsupported_char), "%s" % (supported_char))
policy_fc = global_variables.find_fnc( cmd, ' -fc "', '"' ) # Finds the policy farm flow
if policy_fc == 'error': # If no double quotes, find again
policy_fc = global_variables.find_fnc( cmd, " -fc ", " " )
if policy_fc != 'error': # If the farm flow exists
policy_farm = global_variables.farm_flow_to_farm_dcn[policy_fc][0] # Extracts the associated farm, will be used as the group in the filter
else: # If no farm flow is associated to the policy
policy_farm = default_group # Uses the deafult group and will associate it to the filter
policy_service_type = global_variables.find_fnc( cmd, ' -pt "', '"' ) # Finds the policy services type
if policy_service_type == "Basic Filter" or policy_service_type == "OR Group": # If it's "Basic Filter" or "OR Group"
policy_service = global_variables.find_fnc( cmd, ' -p "', '"' ) # Finds the policy service
if policy_service == 'error': # If no double quotes, find again
policy_service = global_variables.find_fnc( cmd, ' -p ', ' ' )
policy_operational_status = global_variables.find_fnc( cmd, ' -os ', ' ' ) # Finds the policy operational status
### ###
# Print Filters Section #
### ###
def print_filt_fnc(proto):
'''Prints the filter configuration.
Takes the service protocol as an argument.
'''
print >>output_file, "/c/slb/filt %s" % (new_policy_id2) # Starts printing the filter
if ((' -pt "Basic Filter"' in cmd or ' -pt "OR Group"' in cmd) and proto == "single") or (proto == "noService"):
print >>output_file, ' name "%s"' % (policy_name)
elif (' -pt "Basic Filter"' in cmd or ' -pt "OR Group"' in cmd):
print >>output_file, ' name "%s_%s"' % (policy_name, filt_name_index)
if policy_operational_status == 'error':
print >>output_file, " ena"
else:
print >>output_file, " dis"
print >>output_file, " action outbound-llb"
print >>output_file, " ipver v4"
find_policy_src_ip = re.findall( r"^\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$",policy_src)
if len(find_policy_src_ip) == 1: # If policy source is an IP address, use "sip" and "smask"
print >>output_file, " sip %s" % (find_policy_src_ip[0])
print >>output_file, " smask 255.255.255.255"
else: # If policy source is a network class, use "sip" without "smask"
print >>output_file, " sip %s" % (policy_src)
find_policy_dst_ip = re.findall( r"^\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}$",policy_dst)
if len(find_policy_dst_ip) == 1:
print >>output_file, " dip %s" % (find_policy_dst_ip[0])
print >>output_file, " dmask 255.255.255.255"
else:
print >>output_file, " dip %s" % (policy_dst)
if (' -pt "Basic Filter"' in cmd or ' -pt "OR Group"' in cmd) and proto == "single": # Services conditions for single services
if policy_service_type == "Basic Filter" and policy_service == "icmp":
print >>output_file, " proto icmp"
elif policy_service_type == "Basic Filter" and policy_service == "tcp":
print >>output_file, " proto tcp"
elif policy_service_type == "Basic Filter" and policy_service == "udp":
print >>output_file, " proto udp"
elif policy_service_type == "Basic Filter" and policy_service == "sctp":
print >>output_file, " proto 132"
elif policy_service_type == "Basic Filter" and policy_service != "ip":
if policy_service in global_variables.basic_services_dcn.keys():
print >>output_file, " proto %s" % (global_variables.basic_services_dcn[policy_service][0])
print >>output_file, " dport %s" % (global_variables.basic_services_dcn[policy_service][1])
elif policy_service in global_variables.user_defined_basic_services_dcn.keys():
if global_variables.user_defined_basic_services_dcn[policy_service][0] == "TCP":
print >>output_file, " proto tcp"
elif global_variables.user_defined_basic_services_dcn[policy_service][0] == "UDP":
print >>output_file, " proto udp"
print >>output_file, " dport %s" % (global_variables.user_defined_basic_services_dcn[policy_service][1])
elif (' -pt "Basic Filter"' in cmd or ' -pt "OR Group"' in cmd): # If services have multiple ports
print >>output_file, " proto %s" % (proto)
print >>output_file, " dport %s" % (port_service)
print >>output_file, " group %s" % (policy_farm)
print >>output_file, " rport 0"
print >>output_file, " vlan %s" % (ingress_vlan)
for port in ingress_ports:
print >>output_file, " add %s" % (port)
print >>output_file, "/c/slb/filt %s/adv" % (new_policy_id2)
if policy_farm in global_variables.orig_dm_dcn.keys():
if global_variables.orig_dm_dcn[policy_farm][0] == "Hashing" or global_variables.orig_dm_dcn[policy_farm][0] == "Layer-3 Hashing":
print >>output_file, " thash both"
elif global_variables.orig_dm_dcn[policy_farm][0] == "Destination IP Hashing":
print >>output_file, " thash dip32"
print >>output_file, " rtsrcmac ena"
print >>output_file, " reverse ena"
if alt_ha_mode == 1 or alt_ha_mode == 2:
print >>output_file, " mirror ena"
if proximity_mode == 'Full Proximity Outbound' or proximity_mode == 'Full Proximity Both':
print >>output_file, " prximity ena"
print >>output_file, "/c/slb/filt %s/adv/layer7" % (new_policy_id2)
print >>output_file, " ftpa ena"
if policy_farm in global_variables.orig_dm_dcn.keys():
if global_variables.orig_dm_dcn[policy_farm][0] != "Hashing" and global_variables.orig_dm_dcn[policy_farm][0] != "Layer-3 Hashing" and global_variables.orig_dm_dcn[policy_farm][0] != "Source IP Hashing" and global_variables.orig_dm_dcn[policy_farm][0] != "Destination IP Hashing":
print >>output_file, "/c/slb/filt %s/adv/redir" % (new_policy_id2)
print >>output_file, " pbind e"
if "modify-policy-table" in cmd and "-i 0" not in cmd and (' -pt "Basic Filter"' in cmd or ' -pt "OR Group"' in cmd): # If the policy has a basic filter or an OR group
if "%s" % (policy_service) in global_variables.basic_multi_services_ports_dcn.keys(): # If the service in the policy is one of the system default basic filters with more than one service port which is not continuous
for x, port_service in enumerate(global_variables.basic_multi_services_ports_dcn[policy_service]): # Loops over the ports of the multi service basic filter
filt_name_index = global_variables.basic_multi_services_ports_dcn[policy_service].index('%s' % (port_service))
filt_name_index = filt_name_index + 1
new_policy_id2 = policy_id + global_variables.new_filt_id_diff + global_variables.multi_pol_id
diff_orig = policy_id - global_variables.last_orig_pol_id
diff_new = new_policy_id2 - global_variables.last_new_pol_id
new_policy_id2 = global_variables.last_new_pol_id + diff_orig + global_variables.multi_pol_id
print_filt_fnc(global_variables.basic_multi_services_protocols_dcn[policy_service]) # Executes the print filter fuction
global_variables.multi_pol_id = 1
global_variables.last_orig_pol_id = policy_id
global_variables.last_new_pol_id = new_policy_id2
last = len(global_variables.basic_multi_services_ports_dcn[policy_service]) - 1
if x == last:
global_variables.multi_pol_id = 0
elif "%s" % (policy_service) in global_variables.or_groups_multi_services_ports_dcn.keys(): # If the service in the policy is one of the system default OR-Groups with more than one service port which is not continuous
for x, port_service in enumerate(global_variables.or_groups_multi_services_ports_dcn[policy_service]): # Loops over the ports of the multi service OR-Group
filt_name_index = global_variables.or_groups_multi_services_ports_dcn[policy_service].index('%s' % (port_service))
filt_name_index = filt_name_index + 1
new_policy_id2 = policy_id + global_variables.new_filt_id_diff + global_variables.multi_pol_id
diff_orig = policy_id - global_variables.last_orig_pol_id
diff_new = new_policy_id2 - global_variables.last_new_pol_id
new_policy_id2 = global_variables.last_new_pol_id + diff_orig + global_variables.multi_pol_id
print_filt_fnc(global_variables.or_groups_multi_services_protocols_dcn[policy_service]) # Executes the print filter fuction
global_variables.multi_pol_id = 1
global_variables.last_orig_pol_id = policy_id
global_variables.last_new_pol_id = new_policy_id2
last = len(global_variables.or_groups_multi_services_ports_dcn[policy_service]) - 1
if x == last:
global_variables.multi_pol_id = 0
else: # If the service in the policy is one of the system default single service basic filters or one of the user define single service basic filters
diff_orig = policy_id - global_variables.last_orig_pol_id
new_policy_id2 = policy_id + global_variables.new_filt_id_diff
diff_new = new_policy_id2 - global_variables.last_new_pol_id
if diff_orig != diff_new:
new_policy_id2 = global_variables.last_new_pol_id + diff_orig
print_filt_fnc("single") # Executes the print filter fuction
global_variables.last_orig_pol_id = policy_id
global_variables.last_new_pol_id = new_policy_id2
elif "modify-policy-table" in cmd and "-i 0" not in cmd: # If the policy has no service associated
diff_orig = policy_id - global_variables.last_orig_pol_id
new_policy_id2 = policy_id + global_variables.new_filt_id_diff
diff_new = new_policy_id2 - global_variables.last_new_pol_id
if diff_orig != diff_new:
new_policy_id2 = global_variables.last_new_pol_id + diff_orig
print_filt_fnc("noService") # Executes the print filter fuction
global_variables.last_orig_pol_id = policy_id
global_variables.last_new_pol_id = new_policy_id2
### ###
# Default Filter Section #
### ###
if len(default_group) != 0:
print >>output_file, "/c/slb/filt 2048"
print >>output_file, ' name "Default Filter"'
print >>output_file, " ena"
print >>output_file, " action outbound-llb"
print >>output_file, " ipver v4"
print >>output_file, " sip any"
print >>output_file, " dip any"
print >>output_file, " group %s" % (default_group)
print >>output_file, " rport 0"
print >>output_file, " vlan %s" % (ingress_vlan)
for port in ingress_ports:
print >>output_file, " add %s" % (port)
print >>output_file, "/c/slb/filt 2048/adv"
if default_group in global_variables.orig_dm_dcn.keys():
if global_variables.orig_dm_dcn[default_group][0] == "Hashing" or global_variables.orig_dm_dcn[default_group][0] == "Layer-3 Hashing":
print >>output_file, " thash both"
elif global_variables.orig_dm_dcn[default_group][0] == "Destination IP Hashing":
print >>output_file, " thash dip32"
print >>output_file, " reverse ena"
print >>output_file, " rtsrcmac ena"
if alt_ha_mode == 1 or alt_ha_mode == 2:
print >>output_file, " mirror ena"
if proximity_mode == 'Full Proximity Outbound' or proximity_mode == 'Full Proximity Both':
print >>output_file, " prximity ena"
print >>output_file, "/c/slb/filt 2048/adv/layer7"
print >>output_file, " ftpa ena"
if default_group in global_variables.orig_dm_dcn.keys():
if global_variables.orig_dm_dcn[default_group][0] != "Hashing" and global_variables.orig_dm_dcn[default_group][0] != "Layer-3 Hashing" and global_variables.orig_dm_dcn[default_group][0] != "Source IP Hashing" and global_variables.orig_dm_dcn[default_group][0] != "Destination IP Hashing":
print >>output_file, "/c/slb/filt 2048/adv/redir"
print >>output_file, " pbind e"
###################################################
#### Outbound Policies and Filters Section End ####
###################################################
###############################################
#### Proximity Configuraiton Section Start ####
###############################################
## ##
# This is the main section used to configure proximity #
# In this section we use information collected ealier and print the proximity configuration #
## ##
for line in lp_to_lpng: # Loops over the LP configuration
if "lp proximity mode" in line and proximity_mode != 'No Proximity': # If proximity is configured
print >>output_file, "/cfg/slb/prximity/" # Starts printing the proximity configuration
if proximity_aging == 2800:
print >>output_file, " aging 2800"
elif proximity_aging > 2880:
print >>output_file, " aging 2880"
else:
print >>output_file, " aging %s" % (proximity_aging)
if proximity_interval != 5:
print >>output_file, " inter %s" % (proximity_interval)
if proximity_retries != 3:
print >>output_file, " retry %s" % (proximity_retries)
if proximity_mask != '255.255.255.0':
print >>output_file, " v4mask %s" % (proximity_mask)
print >>output_file, " on"
if proximity_main_dns != '0.0.0.0':
print >>output_file, "/cfg/slb/prximity/localdns/add %s" % (proximity_main_dns)
if proximity_backup_dns != '0.0.0.0':
print >>output_file, "/cfg/slb/prximity/localdns/add %s" % (proximity_backup_dns)
#############################################
#### Proximity Configuraiton Section End ####
#############################################
############################
#### GSLB Section Start ####
############################
### ###
# GSLB - Main Section #
### ###
## ##
# This is the main section used to find and configure all of the GSLB configuration #
# In this section, we fine the DNS configuration and print the Alteon equivalent #
# #
# Rules: #
# #
# 1.) We don't repeat GSLB networks with the same configuration #
# The key for not repeating is always the local IP + WAN link group #
# 2.) We check if the local IP is static NAT, no NAT or PAT #
# If it's static NAT or no NAT, we use GSLB network of type server #
# If it's PAT, we use GSLB rule of type group #
# 3.) If the local IP doesn't exist in any Smart NAT object, we don't print the GSLB network and rule #
# 4.) We currently do NOT support modes "Always Local IP" or "Always NAT Address" #
# 5.) When detecting a farm with NAT mode disable, we currently associate the specfial "_GSLB" WAN group #
# This is not the desired behaviour and will be changed soon #
## ##
### ###
# GSLB - GSLB Networks Section #
### ###
for line in lp_to_lpng: # Loops over the LP configuration
if "lp dns response-mode" in line:
dns_response_mode = global_variables.find_fnc( line, 'set "', '"' ) # Finds the DNS response mode
break
else:
dns_response_mode = "According To SmartNat Mode"
dummy_vip_range = global_variables.ipRange_fnc("169.254.0.1", "169.254.7.254")
for line in lp_to_lpng: # Loops over the LP configuration
if "name-to-ip create" in line:
dns_lia = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the local IP
dns_lia = dns_lia[0]
dns_farm = global_variables.find_fnc( line, ' -fn "', '"' ) # Finds the associated farm
if dns_farm == 'error': # If no double quotes, try again
dns_farm = global_variables.find_fnc( line, " -fn ", " " )
new_dns_farm = dns_farm
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
new_dns_farm = new_dns_farm.replace ('%s' % (unsupported_char), "%s" % (supported_char))
if dns_response_mode == "According To SmartNat Mode":
if "%s_%s" % (dns_lia, dns_farm) not in global_variables.lia_to_gslb_nets_dcn.keys():
if dns_lia in global_variables.smart_nat_local_ips_lst: # If there's a Smart NAT entry for the local IP
if dns_lia in global_variables.type_group_local_lst: # If local IP is in Smart NAT static PAT entry
if dns_farm != 'error': # If a farm is associated to the DNS entry
if dns_farm in global_variables.dns_farms_nonat_lst: # If the associated farm is a no NAT farm
global_variables.gslb_net_id += 1
lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm)
global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print_dummy_slb_fnc(dns_lia, dummy_vip_range[global_variables.dummy_vip_id], global_variables.gslb_net_id)
global_variables.dummy_vip_id += 1
global_variables.dummy_status = 1
else: # If the associated farm is a NAT farm
for real, virt in global_variables.snp_real_to_virt_dcn.iteritems(): # Loops over the real to virt mapping dictionary
if real == dns_lia: # If the local IP is the same as the real
for virt3 in virt:
if virt3 not in global_variables.virts_to_gslb_nets_dcn.keys(): # If this GSLB network wasn't configured yet
global_variables.gslb_net_id += 1 # Increments the GSLB network ID by 1
virts_to_gslb_nets_dcn_key = "%s" % (virt3) # Adds the GSLB network to the dictionary, so we don't configure it again
global_variables.virts_to_gslb_nets_dcn.setdefault(virts_to_gslb_nets_dcn_key, [])
global_variables.virts_to_gslb_nets_dcn[virts_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print >>output_file, "/c/slb/gslb/network %s" % (global_variables.gslb_net_id) # Starts printing the GSLB network
print >>output_file, " ena"
print >>output_file, " servtyp group"
for real, virt in global_variables.snp_real_to_virt_dcn.iteritems(): # Loops over the real to virt mapping dictionary
if real == dns_lia: # If the real is the same as the local IP
for virt in virt: # Loops over the virts mapped to this real
print >>output_file, " addvirt PAT_%s 1" % (virt) # Adds each virt to the GSLB network
break
break
break
break
else: # If no farm is associated to the DNS entry, the LP behaviour is complicated to predict # ---->
# The script will behave as if the DNS resolution is with the Smart NAT entry
for real, virt in global_variables.snp_real_to_virt_dcn.iteritems(): # Loops over the real to virt mapping dictionary
if real == dns_lia: # If the local IP is the same as the real
for virt3 in virt:
if virt3 not in global_variables.virts_to_gslb_nets_dcn.keys(): # If this GSLB network wasn't configured yet
global_variables.gslb_net_id += 1 # Increments the GSLB network ID by 1
virts_to_gslb_nets_dcn_key = "%s" % (virt3) # Adds the GSLB network to the dictionary, so we don't configure it again
global_variables.virts_to_gslb_nets_dcn.setdefault(virts_to_gslb_nets_dcn_key, [])
global_variables.virts_to_gslb_nets_dcn[virts_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print >>output_file, "/c/slb/gslb/network %s" % (global_variables.gslb_net_id) # Starts printing the GSLB network
print >>output_file, " ena"
print >>output_file, " servtyp group"
for real, virt in global_variables.snp_real_to_virt_dcn.iteritems(): # Loops over the real to virt mapping dictionary
if real == dns_lia: # If the real is the same as the local IP
for virt in virt: # Loops over the virts mapped to this real
print >>output_file, " addvirt PAT_%s 1" % (virt) # Adds each virt to the GSLB network
break
break
break
#break
else: # If the local IP is in Smart NAT static NAT or "no NAT" entry
if dns_farm != 'error': # If a farm is associated to the DNS entry
if dns_farm in global_variables.dns_farms_nonat_lst: # If the associated farm is a no NAT farm
global_variables.gslb_net_id += 1
lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm)
global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print_dummy_slb_fnc(dns_lia, dummy_vip_range[global_variables.dummy_vip_id], global_variables.gslb_net_id)
global_variables.dummy_vip_id += 1
global_variables.dummy_status = 1
else: # If the associated farm is a NAT farm
global_variables.gslb_net_id += 1 # Increments the GSLB network ID by 1
lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm) # Adds the GSLB Network to the dictionary, so we don't configure it again
global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print >>output_file, "/c/slb/gslb/network %s" % (global_variables.gslb_net_id) # Starts printing the GSLB network
print >>output_file, " ena"
print >>output_file, " servtyp server"
print >>output_file, " servip %s" % (dns_lia)
print >>output_file, " wangrp %s" % (new_dns_farm)
else: # If no farm is associated to the DNS entry, the LP behaviour is complicated to predict # ---->
# The script will behave as if the DNS resolution is with the the Smart entry
global_variables.gslb_net_id += 1 # Increments the GSLB network ID by 1
lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm) # Adds the GSLB Network to the dictionary, so we don't configure it again
global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print >>output_file, "/c/slb/gslb/network %s" % (global_variables.gslb_net_id) # Starts printing the GSLB network
print >>output_file, " ena"
print >>output_file, " servtyp server"
print >>output_file, " servip %s" % (dns_lia)
else: # If there's no Smart NAT entry for the local IP
if dns_farm != 'error': # If a farm is associated to the DNS entry
if dns_farm in global_variables.dns_farms_nonat_lst: # If the associated farm is a no NAT farm
global_variables.gslb_net_id += 1
lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm)
global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print_dummy_slb_fnc(dns_lia, dummy_vip_range[global_variables.dummy_vip_id], global_variables.gslb_net_id)
global_variables.dummy_vip_id += 1
global_variables.dummy_status = 1
else:
current_time = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')
print >>migration_errors, '%s #Command_not_migrated: the following command has not been migrated:' % (current_time)
print >>migration_errors, " Command: %s" % (line)
print >>migration_errors, ' Reason: Local IP %s in this DNS rule, is not in the Smart NAT table, response mode is "According to SmartNAT Mode" and the associated farm is a "NAT Mode Enabled" farm.' % (dns_lia)
print >>migration_errors, ' Therefore, this DNS rule is not migrated.'
#else: # If no farm is associated to the DNS entry
#global_variables.gslb_net_id += 1
#lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm)
#global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
#global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
#print_dummy_slb_fnc(dns_lia, dummy_vip_range[global_variables.dummy_vip_id], global_variables.gslb_net_id)
#global_variables.dummy_vip_id += 1
#global_variables.dummy_status = 1
elif dns_response_mode == "Always Local IP Address":
if "%s_%s" % (dns_lia, dns_farm) not in global_variables.lia_to_gslb_nets_dcn.keys():
global_variables.gslb_net_id += 1
lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm)
global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print_dummy_slb_fnc(dns_lia, dummy_vip_range[global_variables.dummy_vip_id], global_variables.gslb_net_id)
global_variables.dummy_vip_id += 1
global_variables.dummy_status = 1
elif dns_response_mode == "Always NAT IP Address":
if "%s_%s" % (dns_lia, dns_farm) not in global_variables.lia_to_gslb_nets_dcn.keys():
if dns_lia in global_variables.smart_nat_local_ips_lst: # If there's a Smart NAT entry for the local IP
if dns_lia in global_variables.type_group_local_lst: # If local IP is in Smart NAT static PAT entry
for real, virt in global_variables.snp_real_to_virt_dcn.iteritems(): # Loops over the real to virt mapping dictionary
if real == dns_lia: # If the local IP is the same as the real
for virt3 in virt:
if virt3 not in global_variables.virts_to_gslb_nets_dcn.keys(): # If this GSLB network wasn't configured yet
global_variables.gslb_net_id += 1 # Increments the GSLB network ID by 1
virts_to_gslb_nets_dcn_key = "%s" % (virt3) # Adds the GSLB network to the dictionary, so we don't configure it again
global_variables.virts_to_gslb_nets_dcn.setdefault(virts_to_gslb_nets_dcn_key, [])
global_variables.virts_to_gslb_nets_dcn[virts_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print >>output_file, "/c/slb/gslb/network %s" % (global_variables.gslb_net_id) # Starts printing the GSLB network
print >>output_file, " ena"
print >>output_file, " servtyp group"
for real, virt in global_variables.snp_real_to_virt_dcn.iteritems(): # Loops over the real to virt mapping dictionary
if real == dns_lia: # If the real is the same as the local IP
for virt in virt: # Loops over the virts mapped to this real
print >>output_file, " addvirt PAT_%s 1" % (virt) # Adds each virt to the GSLB network
break
break
break
break
else: # If the local IP is in Smart NAT static NAT or "no NAT" entry
global_variables.gslb_net_id += 1 # Increments the GSLB network ID by 1
lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm) # Adds the GSLB Network to the dictionary, so we don't configure it again
global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print >>output_file, "/c/slb/gslb/network %s" % (global_variables.gslb_net_id) # Starts printing the GSLB network
print >>output_file, " ena"
print >>output_file, " servtyp server"
print >>output_file, " servip %s" % (dns_lia)
if dns_farm != 'error': # If a farm is associated to the DNS entry
print >>output_file, " wangrp %s" % (new_dns_farm)
else: # If there's no Smart NAT entry for the local IP
if dns_farm == 'error': # If no farm is associated to the DNS entry
global_variables.gslb_net_id += 1
lia_to_gslb_nets_dcn_key = "%s_%s" % (dns_lia, dns_farm)
global_variables.lia_to_gslb_nets_dcn.setdefault(lia_to_gslb_nets_dcn_key, [])
global_variables.lia_to_gslb_nets_dcn[lia_to_gslb_nets_dcn_key].append('%s' % (global_variables.gslb_net_id))
print_dummy_slb_fnc(dns_lia, dummy_vip_range[global_variables.dummy_vip_id], global_variables.gslb_net_id)
global_variables.dummy_vip_id += 1
global_variables.dummy_status = 1
else:
current_time = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')
print >>migration_errors, '%s #Command_not_migrated: the following command has not been migrated:' % (current_time)
print >>migration_errors, " Command: %s" % (line)
print >>migration_errors, ' Reason: Local IP %s in this DNS rule, is not in the Smart NAT table, response mode is "Always NAT IP Address" and there is a farm associated.' % (dns_lia)
print >>migration_errors, ' Therefore, this DNS rule is not migrated.'
### ###
# GSLB - GSLB Rules Section #
### ###
for line in lp_to_lpng: # Loops over the LP configuration
if "name-to-ip create" in line:
dns_name = global_variables.find_fnc( line, "create ", " -lia" ) # Finds the domain name
dns_farm2 = global_variables.find_fnc( line, ' -fn "', '"' ) # Finds the farm associated with the DNS rule
if dns_farm2 == 'error': # If no double quotes, find again
dns_farm2 = global_variables.find_fnc( line, " -fn ", " " )
new_dns_farm2 = dns_farm2
for unsupported_char, supported_char in global_variables.special_characters_dcn.iteritems():
new_dns_farm2 = new_dns_farm2.replace ('%s' % (unsupported_char), "%s" % (supported_char))
if new_dns_farm2 in global_variables.farm_parameters_dcn.keys(): # Defines the gmetric according to the farm's metric
if global_variables.farm_parameters_dcn[new_dns_farm2][0] == "roundrobin" or global_variables.farm_parameters_dcn[new_dns_farm2][0] == "leastconns" or global_variables.farm_parameters_dcn[new_dns_farm2][0] == "bandwidth":
net_gmetric3 = global_variables.farm_parameters_dcn[new_dns_farm2][0]
else: # If the farm has a metric which is not supported as gmetric, use bandwidth
net_gmetric3 = "bandwidth"
if dns_farm2 in global_variables.orig_farm_parameters_dcn.keys():
current_time = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')
print >>migration_errors, '\033[1m%s\033[0m #Unsupported_flag_option: the following command contains a flag with an unsupported option:' % (current_time)
print >>migration_errors, ' Unsupported flag option: the farm associated with the DNS rule has a metric which is not supported as gmetric.'
print >>migration_errors, ' Command: %s' % (line)
print >>migration_errors, ' Farm: %s.' % (dns_farm2)
print >>migration_errors, ' Metric: %s.' % (global_variables.orig_farm_parameters_dcn[dns_farm2][0])
print >>migration_errors, ' Alteon will use "gmetric bandwidth".'
else: # If no farm associated, uses gmetric bandwidth
net_gmetric3 = "bandwidth"
dns_lia2 = re.findall( r'[0-9]+(?:\.[0-9]+){3}', line ) # Finds the local IP
dns_lia2 = dns_lia2[0]
dns_lia_and_farm = "%s_%s" % (dns_lia2, dns_farm2) # Binds the local IP and farm
if dns_lia2 in global_variables.smart_nat_local_ips_lst: # If the local IP is in Smart NAT
if dns_lia_and_farm in global_variables.lia_to_gslb_nets_dcn: # If the local IP and farm are already define in a GSLB network
if len(global_variables.lia_to_gslb_nets_dcn[dns_lia_and_farm]) > 0: # Validate that the value (the GSLB network ID) is not empty
net_rule = global_variables.lia_to_gslb_nets_dcn[dns_lia_and_farm][0] # Uses the GSLB network ID in this GSLB rule
global_variables.gslb_rule_id += 1 # Increment the GSLB rule ID by 1
elif dns_lia2 in global_variables.type_group_local_lst: # If the local IP is in PAT
for real, virt in global_variables.snp_real_to_virt_dcn.iteritems(): # Loops over the real to virt mapping dictionary
if real == dns_lia2: # If the real server is the same as the local IP
for virt4 in virt: # Loops over the associated virts
if virt4 in global_variables.virts_to_gslb_nets_dcn.keys(): # If the virt is already defined in a GSLB network
if len(global_variables.virts_to_gslb_nets_dcn[virt4]) > 0: # Validates that the value (the GSLB network ID) is not empty
net_rule = global_variables.virts_to_gslb_nets_dcn[virt4][0] # Uses the GSLB network ID in this GSLB rule
global_variables.gslb_rule_id += 1 # Increments the GSLB rule ID by 1
print >>output_file, "/c/slb/gslb/rule %s" % (global_variables.gslb_rule_id) # Starts printing the GSLB rule
print >>output_file, " ena"
if dns_lia2 in global_variables.type_group_local_lst: # If the local IP is in PAT
for real, virt in global_variables.snp_real_to_virt_dcn.iteritems(): # Loops over the real to virt mapping dictionary
if real == dns_lia2: # If the real is the same as the local IP
for virt in virt: # Loops over the associated virts
for virt2, service in global_variables.snp_virt_to_service_dcn.iteritems(): # Loops over the virt to service dictionary
if virt2 == virt: # If the virt in the dictionary is the same as the virt associated to this local IP
print >>output_file, " type inbound-llb %s" % (service[0]) # Prints the inbound LLB rule command with the correct service
break
break
break
else: # If the local IP is in static NAT or no NAT
if int(net_rule) in global_variables.nonat_gslb_nets_lst:
print >>output_file, " type inbound-llb 1234"
else:
print >>output_file, " type inbound-llb 0" # prints the inbound LLB command with "0"
print >>output_file, " ttl %s" % (dns_ttl) # Continues printing the rest of the general GSLB rule commands
print >>output_file, " rr %s" % (dns_rr)
print >>output_file, " dname %s" % (dns_name)
print >>output_file, "/c/slb/gslb/rule %s/metric 1" % (global_variables.gslb_rule_id)
print >>output_file, " gmetric network"
print >>output_file, " addnet %s" % (net_rule)
#if proximity_mode == 'Full Proximity Inbound' or proximity_mode == 'Full Proximity Both':
#print >>output_file, "/c/slb/gslb/rule %s/metric 2" % (global_variables.gslb_rule_id)
#print >>output_file, " gmetric proximity"
print >>output_file, "/c/slb/gslb/rule %s/metric 3" % (global_variables.gslb_rule_id)
print >>output_file, " gmetric %s" % (net_gmetric3)
##########################
#### GSLB Section End ####
##########################
#######################
#### Main Code End ####
#######################
#############################
### Logging Section Start ###
#############################
def unsupported_commands_global_log_fnc(command):
'''Used to log a global message when finding and unsupported command.
Takes the beginning of the command as an argument.
'''
current_time = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')
print >>migration_errors, '\033[1m%s\033[0m #Unsupported_command: all commands starting with "%s" are unsupported by this script.' % (current_time, command)
print >>migration_errors, " Unsupported commands in your configuration:"
def unsupported_commands_specific_log_fnc():
'''Used to log the specific unsupported command.
Takes no arguments.
'''
print >>migration_errors, ' Command: %s' % (line)
def unsupported_flag_global_log_fnc(command):
'''Used to log a global message when finding and unsupported flag.
Takes the command as an argument.
'''
current_time = datetime.utcnow().strftime('%Y-%m-%d %H:%M:%S.%f')
print >>migration_errors, '\033[1m%s\033[0m #Unsupported_flag: the following command contains a flag which is not supported by this script:' % (current_time)
print >>migration_errors, ' Command: %s' % (line)
def unsupported_flag_specific_log_fnc(flag):
'''Used to log the specific unsupported flag.
Takes no arguments.
'''
print >>migration_errors, ' Unsupported flag: %s' % (flag)
### ###
# Unsupported Commands #
### ###
for line in lp_to_lpng:
if line.startswith( 'classes modify service and-group' ):
unsupported_commands_global_log_fnc('classes modify service and-group')
break
for line in lp_to_lpng:
if line.startswith( 'classes modify service and-group' ):
unsupported_commands_specific_log_fnc()
for line in lp_to_lpng:
if line.startswith( 'lp dns server' ):
unsupported_commands_global_log_fnc('lp dns server')
break
for line in lp_to_lpng:
if line.startswith( 'lp dns server' ):
unsupported_commands_specific_log_fnc()
for line in lp_to_lpng:
if line.startswith( 'lp dns host-to-ip-tables dynamic-name-to-ip' ):
unsupported_commands_global_log_fnc('lp dns host-to-ip-tables dynamic-name-to-ip')
break
for line in lp_to_lpng:
if line.startswith( 'lp dns host-to-ip-tables dynamic-name-to-ip' ):
unsupported_commands_specific_log_fnc()
for line in lp_to_lpng:
if line.startswith( 'lp content-lb-parameters' ):
unsupported_commands_global_log_fnc('lp content-lb-parameters')
break
for line in lp_to_lpng:
if line.startswith( 'lp content-lb-parameters' ):
unsupported_commands_specific_log_fnc()
for line in lp_to_lpng:
if line.startswith( 'bwm' ):
unsupported_commands_global_log_fnc('bwm')
break
for line in lp_to_lpng:
if line.startswith( 'bwm' ):
unsupported_commands_specific_log_fnc()
### ###
# Unsupported Flags #
### ###
for line in lp_to_lpng:
if "servers router-servers" in line:
for flag in global_variables.lp_servers_unsupported_flags:
if " %s " % (flag) in line:
unsupported_flag_global_log_fnc(line)
break
for flag in global_variables.lp_servers_unsupported_flags:
if " %s " % (flag) in line:
unsupported_flag_specific_log_fnc(flag)
if "net ip-interface" in line:
for flag in global_variables.lp_netip_unsupported_flags:
if " %s " % (flag) in line:
unsupported_flag_global_log_fnc(line)
break
for flag in global_variables.lp_netip_unsupported_flags:
if " %s " % (flag) in line:
unsupported_flag_specific_log_fnc(flag)
if "flow-management modify-policy-table" in line:
for flag in global_variables.lp_traffic_pols_unsupported_flags:
if " %s " % (flag) in line:
unsupported_flag_global_log_fnc(line)
break
for flag in global_variables.lp_traffic_pols_unsupported_flags:
if " %s " % (flag) in line:
unsupported_flag_specific_log_fnc(flag)
### ###
# Unsupported Flag Options #
### ###
if 'flow-management modify-policy-table' in line and ' -pt "AND Group"' in line:
print >>migration_errors, '\033[1m%s\033[0m #Unsupported_flag_option: the following command contains a flag with an option which is not supported by this script:' % (current_time)
print >>migration_errors, ' Command: %s' % (line)
print >>migration_errors, ' Unsupported flag option: "Service type AND Group".'
###########################
### Logging Section End ###
###########################
output_file.close()
migration_errors.close()
tar = tarfile.open("app/%s_files.tar.gz" % (user_output_file), "w:gz")
tar.add("app/%s_config" % (user_output_file), arcname="%s_config" % (user_output_file))
tar.add("app/%s_logs" % (user_output_file), arcname="%s_logs" % (user_output_file))
tar.close()
return render_template('end.html', user_output_file=user_output_file)
#return redirect('%s_files.tar.gz' % (user_output_file))
@app.route('/<path:dummy>' , methods=['GET', 'POST'])
def download(dummy):
if dummy.endswith("_files.tar.gz"):
return send_file('%s' % (dummy), as_attachment=True)
elif dummy.endswith("favicon.ico"):
return render_template('dummy.html'), 404
|
#!/usr/bin/env python3
class Observer:
"""
Objects that are interested in a subject should
inherit from this class.
"""
def notify(self, sender: object):
pass
|
#!/usr/bin/env python
import uuid
# Tham khảo:
# - https://stackoverflow.com/a/159195
# - https://www.geeksforgeeks.org/extracting-mac-address-using-python/
def get_mac_address_1():
int_mac = uuid.getnode()
hex_mac_fmt = ':'.join(['{:02x}'.format((int_mac >> x) & 0xff)
for x in range(0, 8*6, 8)][::-1])
return hex_mac_fmt
# Tham khảo:
# - https://stackoverflow.com/a/3499533
def get_mac_address_2():
int_mac = uuid.getnode()
hex_mac = hex(int_mac)[2:] # Remove '0x'
if len(hex_mac) < 12:
hex_mac = '0' * (12 - len(hex_mac)) + hex_mac
blocks = [hex_mac[x:x+2] for x in range(0, len(hex_mac), 2)]
hex_mac_fmt = ':'.join(blocks)
return hex_mac_fmt
if __name__ == '__main__':
print(get_mac_address_1())
print(get_mac_address_2())
|
# `pip install easydict` if you don't have it
from easydict import EasyDict as edict
import numpy as np
import json
import numpy as np
class NumpyEncoder(json.JSONEncoder):
""" Special json encoder for numpy types """
def default(self, obj):
if isinstance(obj, (np.int_, np.intc, np.intp, np.int8,
np.int16, np.int32, np.int64, np.uint8,
np.uint16, np.uint32, np.uint64)):
return int(obj)
elif isinstance(obj, (np.float_, np.float16, np.float32,
np.float64)):
return float(obj)
elif isinstance(obj,(np.ndarray,)): #### This is the fix
return obj.tolist()
return json.JSONEncoder.default(self, obj)
def save_config(edict, path2dict):
try:
with open(path2dict, "w") as file:
json.dump(json.dumps(edict, cls=NumpyEncoder), file)
file.close()
print ('[save_config] save config to "{}"'.format(path2dict))
except:
print ('[save_config] fail to save config to "{}"'.format(path2dict))
def load_config(path2config):
try:
with open(path2config, "r") as file:
config = edict(json.loads(json.load(file)))
file.close()
except:
print ('[load_config] cannot load config "{}"'.format(path2config))
config = edict()
return config
|
from .data import MaskArray
from .data import MaskGroup
from .data import PdgArray
from .data import MomentumArray
from .data import ColorArray
from .data import ParticleSet
from .data import AdjacencyList
from .data import Graphicle
from . import matrix
from . import transform
__all__ = [
"MaskArray",
"MaskGroup",
"PdgArray",
"MomentumArray",
"ColorArray",
"ParticleSet",
"AdjacencyList",
"Graphicle",
"matrix",
"transform",
]
|
import sys
import os
ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "../"))
sys.path.append(ROOT_PATH)
import docutils.nodes
import docutils.parsers.rst
import docutils.utils
import docutils.frontend
from Utils.FileFunc import PathManager
def parse_rst(text: str) -> docutils.nodes.document:
parser = docutils.parsers.rst.Parser()
components = (docutils.parsers.rst.Parser,)
settings = docutils.frontend.OptionParser(components=components).get_default_values()
document = docutils.utils.new_document('<rst-doc>', settings=settings)
parser.parse(text, document)
return document
global_type_set = set()
class RstVisitor(docutils.nodes.NodeVisitor):
def visit_reference(self, node: docutils.nodes.reference) -> None:
pass
def visit_title(self, node: docutils.nodes.title):
pass
def visit_paragraph(self, node: docutils.nodes.paragraph):
pass
def visit_section(self, node: docutils.nodes.section):
pass
def visit_emphasis(self, node: docutils.nodes.emphasis):
pass
def visit_text(self, node: docutils.nodes.Text) -> None:
print(node.rawsource)
def unknown_visit(self, node: docutils.nodes.Node) -> None:
global_type_set.add(str(type(node)))
def main(content):
doc = parse_rst(content)
visitor = RstVisitor(doc)
doc.walk(visitor)
if __name__ == "__main__":
path = sys.argv[1]
pm = PathManager()
if pm.isPathDir(path):
filelist = pm.getFileList(path)
for f_path in filelist:
with open(f_path, "rt") as fr:
content = fr.read()
main(content)
for t in global_type_set:
print(t)
'''
TODO: support node class
<class 'docutils.nodes.warning'>
<class 'docutils.nodes.problematic'>
<class 'docutils.nodes.Text'>
<class 'docutils.nodes.inline'>
<class 'docutils.nodes.title'>
<class 'docutils.nodes.topic'>
<class 'docutils.nodes.paragraph'>
<class 'docutils.nodes.reference'>
<class 'docutils.nodes.section'>
<class 'docutils.nodes.emphasis'>
<class 'docutils.nodes.list_item'>
<class 'docutils.nodes.literal'>
<class 'docutils.nodes.figure'>
<class 'docutils.nodes.caption'>
<class 'docutils.nodes.target'>
<class 'docutils.nodes.pending'>
<class 'docutils.nodes.image'>
<class 'docutils.nodes.enumerated_list'>
<class 'docutils.nodes.system_message'>
<class 'docutils.nodes.document'>
<class 'docutils.nodes.strong'>
<class 'docutils.nodes.bullet_list'>
<class 'docutils.nodes.literal_block'>
unsupport nodes in docutils: Unknown directive.
<rst-doc>:879: (ERROR/3) Unknown directive type "literalinclude".
.. literalinclude:: ../../../examples/Kaleidoscope/Chapter7/toy.cpp
:language: c++
<rst-doc>:5: (ERROR/3) Unknown directive type "toctree".
.. toctree::
:hidden:
LangImpl01
LangImpl02
LangImpl03
LangImpl04
LangImpl05
LangImpl06
LangImpl07
LangImpl08
LangImpl09
LangImpl10
<rst-doc>:355: (ERROR/3) Unknown interpreted text role "ref".
<rst-doc>:355: (ERROR/3) Unknown interpreted text role "ref".
<rst-doc>:810: (ERROR/3) Unknown directive type "literalinclude".
.. literalinclude:: ../../../examples/Kaleidoscope/Chapter5/toy.cpp
:language: c++
<rst-doc>:495: (ERROR/3) Unknown directive type "TODO".
.. TODO:: Abandon Pygments' horrible `llvm` lexer. It just totally gives up
on highlighting this due to the first line.
'''
|
# This file was automatically created by FeynRules 1.7.51
# Mathematica version: 8.0 for Linux x86 (64-bit) (February 23, 2011)
# Date: Thu 2 Aug 2012 10:15:24
from object_library import all_orders, CouplingOrder
NP = CouplingOrder(name = 'NP',
expansion_order = 99,
hierarchy = 1)
QCD = CouplingOrder(name = 'QCD',
expansion_order = 99,
hierarchy = 1)
|
import json
import pytest
from django.core.management import call_command
@pytest.fixture(scope="session")
def django_db_setup(django_db_setup, django_db_blocker):
with django_db_blocker.unblock():
call_command("migrate")
call_command("loaddata", "src/fixtures/account.json")
call_command("loaddata", "src/fixtures/shop.json")
call_command("loaddata", "src/fixtures/blog.json")
call_command("loaddata", "src/fixtures/menu.json")
call_command("loaddata", "src/fixtures/exchange.json")
@pytest.fixture
def headers(client, django_user_model):
django_user_model.objects.create_user(
username="user_test0001@example.com",
password="string8euwq",
)
data = {"email": "user_test0001@example.com", "password": "string8euwq"}
res = client.post(
"/sign-up/",
data=json.dumps(data),
content_type="application/json",
)
return {"Authorization": f"Bearer {res.json().get('access')}"}
|
from __future__ import annotations
from typing import Optional, List, TYPE_CHECKING
import pandas as pd
from whyqd.base import BaseMorphAction
if TYPE_CHECKING:
from ..models import ColumnModel
class Action(BaseMorphAction):
"""Delete columns provided in a list.
Script::
"DELETE_COLUMNS > ['source_column', 'source_column', etc.]"
"""
def __init__(self) -> None:
self.name = "DELETE_COLUMNS"
self.title = "Delete columns"
self.description = "Delete columns provided in a list."
self.structure = ["columns"]
def transform(self, df: pd.DataFrame, columns: List[ColumnModel], rows: Optional[None] = None) -> pd.DataFrame:
"""
Delete columns provided in a list.
Parameters
----------
df: DataFrame
Working data to be transformed
columns: List of ColumnModel
List of column names to be deleted.
rows: None
Ignored for this ACTION.
Returns
-------
Dataframe
Containing the implementation of the Morph
"""
return df.drop(columns=[c.name for c in columns])
|
import os
import sys
import bioframe
import click
import cooler
import cooltools
import cooltools.expected
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from matplotlib.lines import Line2D
import numpy as np
import pandas as pd
import pairlib
import pairlib.scalings
import pairtools
from diskcache import Cache
# peri-centromeric/-telomeric region to remove from both sides of chromosomal arms
cache = Cache("~/.hic.cache")
@click.group()
def cli():
pass
def plot_scalings(
scalings, avg_trans_levels, plot_slope, label_subplots, labels, title, out_path
):
"""
Plot scaling curves from a list of (bin, pair frequencies) tuples.
"""
fig = plt.figure(constrained_layout=False)
gs = gridspec.GridSpec(1, 2, width_ratios=[3, 2], wspace=0.4, figure=fig)
scale_ax = fig.add_subplot(gs[0, 0])
slope_ax = fig.add_subplot(gs[0, 1]) if plot_slope else None
for idx, scalings in enumerate(scalings):
dist_bin_mids, pair_frequencies = scalings
scale_ax.loglog(dist_bin_mids, pair_frequencies, label=labels[idx], lw=1)
if avg_trans_levels:
scale_ax.axhline(
avg_trans_levels[idx],
ls="dotted",
c=scale_ax.get_lines()[-1].get_color(),
lw=1,
)
if slope_ax is not None:
slope_ax.semilogx(
np.sqrt(dist_bin_mids.values[1:] * dist_bin_mids.values[:-1]),
np.diff(np.log10(pair_frequencies.values))
/ np.diff(np.log10(dist_bin_mids.values)),
label=labels[idx],
lw=1,
)
scale_ax.grid(lw=0.5, color="gray")
scale_ax.set_aspect(1.0)
scale_ax.set_xlim(1e3, 1e6)
scale_ax.set_ylim(0.0001, 2.0)
scale_ax.set_xlabel("genomic separation (bp)")
scale_ax.set_ylabel("contact frequency")
scale_ax.set_anchor("S")
handles, labels = scale_ax.get_legend_handles_labels()
if avg_trans_levels:
handles.append(Line2D([0], [0], color="black", lw=1, ls="dotted"))
labels.append("average trans")
scale_ax.legend(
handles, labels, loc="upper left", bbox_to_anchor=(1.1, 1.0), frameon=False
)
if slope_ax is not None:
slope_ax.grid(lw=0.5, color="gray")
slope_ax.set_xlim(1e3, 1e6)
slope_ax.set_ylim(-3.0, 0.0)
slope_ax.set_yticks(np.arange(-3, 0.5, 0.5))
slope_ax.set_aspect(1.0)
slope_ax.set_xlabel("distance (bp)")
slope_ax.set_ylabel("log-log slope")
slope_ax.set_anchor("S")
if label_subplots:
scale_ax.set_title("(a)")
slope_ax.set_title("(b)")
fig.suptitle(title)
plt.savefig(
out_path, dpi=300, bbox_inches="tight", facecolor="white", transparent=False
)
plt.show()
plt.close()
def open_pairs_file(path: str) -> pd.DataFrame:
header, pairs_body = pairtools._headerops.get_header(
pairtools._fileio.auto_open(path, "r")
)
cols = pairtools._headerops.extract_column_names(header)
return pd.read_csv(pairs_body, header=None, names=cols, sep="\t")
def calc_pair_freqs(scalings, trans_levels, calc_avg_trans, normalized):
dist_bin_mids = np.sqrt(scalings.min_dist * scalings.max_dist)
pair_frequencies = scalings.n_pairs / scalings.n_bp2
mask = pair_frequencies > 0
avg_trans = None
if calc_avg_trans:
avg_trans = (
trans_levels.n_pairs.astype("float64").sum()
/ trans_levels.np_bp2.astype("float64").sum()
)
if normalized:
norm_fact = pairlib.scalings.norm_scaling_factor(
dist_bin_mids, pair_frequencies, anchor=int(1e3)
)
pair_frequencies = pair_frequencies / norm_fact
avg_trans = avg_trans / norm_fact if avg_trans else None
return (dist_bin_mids[mask], pair_frequencies[mask]), avg_trans
@cli.command("compute-scaling")
@click.argument("pairs_paths", nargs=-1, type=click.Path(exists=True), required=True)
@click.option(
"--out",
"-o",
"out_path",
required=True,
type=click.Path(),
help="The path to the scaling plot output file.",
)
@click.option(
"--region",
"-r",
"region",
type=str,
help="UCSC-style coordinates of the genomic region to calculate scalings for.",
)
@click.option(
"--exclude-chrom",
"exclude_chroms",
type=str,
multiple=True,
help='Exclude the specified chromosome from the scalings. Optionally add ":left" or ":right" to the argument to only exclude the corresponding arm of the chromosome.',
)
@click.option(
"--exclude-end-regions",
"exclude_end_regions",
type=int,
default=10000,
help="Centromeric and telomeric regions of chromosomal arms in bp to exclude from scalings. Default is 10,000.",
)
@click.option(
"--assembly",
"-a",
"assembly",
type=str,
nargs=1,
help="Assembly name to be used for downloading chromsizes.",
)
@click.option(
"--centromeres",
"centromeres_path",
type=click.Path(exists=True),
help="Path to a text file containing centromere start and end positions. If not provided, a download will be attempted.",
)
@click.option(
"--normalized",
"-n",
is_flag=True,
help="Normalize the contact frequency up to 1.0.",
)
@click.option(
"--split-arms",
is_flag=True,
default=False,
help="Plot scalings of left and right chromosomal arms per chromosome, per pairs file. Caching is disabled for this option.",
)
@click.option(
"--plot-slope",
is_flag=True,
default=False,
help="Plot the slopes of the scaling curves.",
)
@click.option(
"--label-subplots",
is_flag=True,
default=False,
help="Label subplots as (a) and (b). Disabled by default.",
)
@click.option(
"--show-average-trans", is_flag=True, help="Show average trans contact frequency."
)
@click.option(
"--label",
"-l",
"labels",
type=str,
multiple=True,
help="One or more labels for the scaling plot curves.",
)
@click.option(
"--title", "-t", "title", type=str, nargs=1, help="Title text for the scaling plot."
)
@click.option(
"--no-cache",
is_flag=True,
help="Do not use cached values. Caching is enabled by default.",
)
def compute_scaling(
pairs_paths,
out_path,
region,
exclude_chroms,
exclude_end_regions,
assembly,
centromeres_path,
split_arms,
normalized,
plot_slope,
label_subplots,
show_average_trans,
labels,
title,
no_cache,
):
"""
Compute and plot contact frequency vs genomic separation curves for one or more pairs files.
"""
labels = list(labels)
# parse left/right arm parameter of chromosomes to exclude
exclude_chroms = [chrom.split(":") for chrom in exclude_chroms]
chromsizes = bioframe.fetch_chromsizes(assembly, filter_chroms=False, as_bed=True)
chromsizes = chromsizes[~chromsizes.chrom.isin(exclude_chroms)]
if centromeres_path:
centromeres = {}
with open(centromeres_path) as file:
for line in file:
cols = line.split(" ")
centromeres[cols[0]] = (int(cols[1]) + int(cols[2])) // 2
else:
centromeres = bioframe.fetch_centromeres(assembly)
centromeres.set_index("chrom", inplace=True)
centromeres = centromeres.mid.to_dict()
if len(labels) != 0 and len(pairs_paths) != len(labels) and not split_arms:
sys.exit("Please provide as many labels as pairs paths.")
if region:
regions = bioframe.select(chromsizes, region).reset_index()
else:
# use chromosomal arms as separate regions if no regions are specified
arms = bioframe.split(chromsizes, centromeres)
# remove user-excluded chromosomes/arms
for chrom in exclude_chroms:
if len(chrom) == 1:
# no arm specified, remove entire chromosome
arms = arms[arms.chrom != chrom[0]]
elif chrom[1] == "left":
# remove specified chromosome with start == 0 (left arm)
arms = arms[~((arms.chrom == chrom[0]) & (arms.start == 0))]
elif chrom[1] == "right":
# remove specified chromosome with start != 0 (right arm)
arms = arms[~((arms.chrom == chrom[0]) & (arms.start != 0))]
# remove 40kb from each side (80kb total) of an arm to remove centromere and telomere regions
arms = bioframe.ops.expand(arms, -exclude_end_regions)
# remove arms arms with a length of < 0 after removing side regions
regions = arms[arms.start < arms.end].reset_index()
all_scalings = []
all_avg_trans_levels = []
for idx, path in enumerate(pairs_paths):
cis_scalings, avg_trans = None, None
if split_arms:
# calculate scalings per arm per chromosome
cis_scalings, trans_levels = pairlib.scalings.compute_scaling(
path,
regions,
chromsizes,
dist_range=(int(1e1), int(1e9)),
n_dist_bins=128,
chunksize=int(1e7),
)
# remove unassigned pairs with start/end positions < 0
cis_scalings = cis_scalings[
(cis_scalings.start1 > 0)
& (cis_scalings.end1 > 0)
& (cis_scalings.start2 > 0)
& (cis_scalings.end2 > 0)
]
sc_agg = (
cis_scalings.groupby(["chrom1", "start1", "min_dist", "max_dist"])
.agg({"n_pairs": "sum", "n_bp2": "sum"})
.reset_index()
)
avail_chroms = set(sc_agg.chrom1)
for chrom in avail_chroms:
# calculate scalings for left/right arms (left arms start at position 0 + exclude_end_regions)
sc_left, avg_trans_left = calc_pair_freqs(
sc_agg[
(sc_agg.chrom1 == chrom)
& (sc_agg.start1 == exclude_end_regions)
],
trans_levels,
show_average_trans,
normalized,
)
sc_right, avg_trans_right = calc_pair_freqs(
sc_agg[
(sc_agg.chrom1 == chrom)
& (sc_agg.start1 != exclude_end_regions)
],
trans_levels,
show_average_trans,
normalized,
)
dir_path = os.path.join(
os.path.dirname(out_path), os.path.basename(path)
)
if not os.path.exists(dir_path):
os.mkdir(dir_path)
chrom_path = os.path.join(
dir_path, "_".join((chrom, os.path.basename(out_path)))
)
(
plot_scalings(
scalings=[sc_left, sc_right],
avg_trans_levels=[avg_trans_left, avg_trans_right],
plot_slope=plot_slope,
labels=["left", "right"],
title=chrom,
out_path=chrom_path,
)
)
else:
if not no_cache:
# get cached values
cached = cache.get(path)
if cached is not None:
cis_scalings = (
cached["cis_scalings"]
if cached["normalized"] == normalized
else None
)
avg_trans = cached["avg_trans"]
if (
no_cache
or cis_scalings is None
or (avg_trans is None and show_average_trans)
):
print(
f"Computing scalings for file {idx + 1}/{len(pairs_paths)} ...",
end="\r",
)
# caching disabled or no cached values found
cis_scalings, trans_levels = pairlib.scalings.compute_scaling(
path,
regions,
chromsizes,
dist_range=(int(1e1), int(1e9)),
n_dist_bins=128,
chunksize=int(1e7),
)
# remove unassigned pairs with start/end positions < 0
cis_scalings = cis_scalings[
(cis_scalings.start1 >= 0)
& (cis_scalings.end1 >= 0)
& (cis_scalings.start2 >= 0)
& (cis_scalings.end2 >= 0)
]
sc_agg = (
cis_scalings.groupby(["min_dist", "max_dist"])
.agg({"n_pairs": "sum", "n_bp2": "sum"})
.reset_index()
)
cis_scalings, avg_trans = calc_pair_freqs(
sc_agg, trans_levels, show_average_trans, normalized
)
if not no_cache:
cache.set(
path,
{
"cis_scalings": cis_scalings,
"avg_trans": avg_trans,
"normalized": normalized,
},
)
else:
print(
f"Retrieved cached values for file {idx + 1}/{len(pairs_paths)}.",
end="\r",
)
# use file names as labels if labels have not been provided
labels.append(os.path.basename) if len(labels) < len(pairs_paths) else None
all_scalings.append(cis_scalings)
all_avg_trans_levels.append(avg_trans) if avg_trans is not None else None
if len(all_scalings) > 0 and not split_arms:
plot_scalings(
all_scalings,
all_avg_trans_levels,
plot_slope,
label_subplots,
labels,
title,
out_path,
)
@cli.command("compute-trans-scaling")
@click.argument("cooler_path", nargs=1, type=click.Path(exists=True), required=True)
@click.option(
"--out",
"-o",
"out_path",
type=click.Path(),
help="The path to the scaling plot output file.",
)
@click.option(
"--resolution",
nargs=1,
type=int,
default=1000,
help="Resolution of the Hi-C data in a .mcool file.",
)
@click.option(
"--region1",
"-r1",
"regions1",
type=str,
multiple=True,
help="The first region of interactions.",
)
@click.option(
"--region2",
"-r2",
"regions2",
type=str,
multiple=True,
help="The second region of interactions.",
)
@click.option(
"--label",
"-l",
"labels",
type=str,
multiple=True,
help="One or more labels for the interaction frequency curves.",
)
@click.option(
"--title", "-t", "title", type=str, nargs=1, help="Title text for the plot."
)
def compute_trans_scaling(
cooler_path, out_path, resolution, regions1, regions2, labels, title
):
chromsizes = bioframe.fetch_chromsizes("sacCer3", filter_chroms=False, as_bed=True)
avg_contacts = cooltools.expected.diagsum_asymm(
clr=cooler.Cooler("::/resolutions/".join((cooler_path, str(resolution)))),
supports1=list(regions1),
supports2=list(regions2),
transforms={"balanced": lambda p: p["count"] * p["weight1"] * p["weight2"]},
)
avg_contacts["balanced.avg"] = avg_contacts["balanced.sum"] / avg_contacts(
"n_valid"
)
print("...")
@cli.command("clear-cache")
def clear_cache():
"""
Erase all cached values.
"""
cache.clear()
print("Cache cleared.")
if __name__ == "__main__":
np.seterr(divide="ignore", invalid="ignore")
cli()
|
# ------------------------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License (MIT). See LICENSE in the repo root for license information.
# ------------------------------------------------------------------------------------------
from pathlib import Path
import numpy as np
from sklearn import datasets
def main() -> None:
# import some data to play with
iris = datasets.load_iris()
X = iris.data[:, :2] # we only take the first two features.
y = iris.target
dataset = Path("dataset")
dataset.mkdir(exist_ok=False)
X_csv = dataset / "X.csv"
np.savetxt(X_csv, X, delimiter=',')
y_csv = dataset / "y.csv"
np.savetxt(y_csv, y, delimiter=',')
if __name__ == "__main__":
main()
|
import subprocess
import logging
import time
import os
import sys
import shutil
import sqlite3
from pathlib import Path
import scripts.cron_logging
# get the logger for the application
logger = scripts.cron_logging.logger
def reboot():
"""Reboot the system but first include some system info in the cron_log
file and update the non-volatile copy of the file.
"""
# wrap the reporting in a try except so that reboot is attempted for sure
try:
report = 'lsusb:\n%s' % subprocess.check_output('/usr/bin/lsusb', text=True)
if Path('/mnt/1wire').exists():
report += '\nls /mnt/1wire:\n%s' % subprocess.check_output(['/bin/ls', '/mnt/1wire'], text=True)
report += '\nuptime:\n%s' % subprocess.check_output('/usr/bin/uptime', text=True)
report += '\nfree:\n%s' % subprocess.check_output('/usr/bin/free', text=True)
report += '\ndf:\n%s' % subprocess.check_output('/bin/df', text=True)
report += '\nifconfig:\n%s' % subprocess.check_output('/sbin/ifconfig', text=True)
# write this to a special file in /var/local
with open('/var/local/reboot_info.txt', 'w') as fout:
fout.write(report)
except:
pass
# backup log and Post database files before rebooting
backup_files()
# Update the fake hardware clock to that the time is close to right
# after the reboot.
subprocess.call('/sbin/fake-hwclock save', shell=True)
# wait 5 seconds, as it seems to take this long to take effect
time.sleep(5)
# reboot now. Have reworked code to that all Mini-Monitor processes
# will kill with simple SIGTERM instead of SIGKILL.
subprocess.call('/sbin/reboot now', shell=True)
# wait until reboot actually occurs
while True:
time.sleep(1)
def backup_files():
try:
# Copy the application log files to a directory on the SD Card, because
# they are on a RAM disk that will not persist a reboot.
if os.path.exists('/var/log/pi_log.log'):
shutil.copyfile('/var/log/pi_log.log', '/var/local/pi_log.log')
if os.path.exists('/var/log/pi_cron.log'):
shutil.copyfile('/var/log/pi_cron.log', '/var/local/pi_cron.log')
if os.path.exists('/var/log/meter_reader.log'):
shutil.copyfile('/var/log/meter_reader.log', '/var/local/meter_reader.log')
if os.path.exists('/var/log/mosquitto.log'):
shutil.copyfile('/var/log/mosquitto.log', '/var/local/mosquitto.log')
if os.path.exists('/var/log/mqtt_to_bmon.log'):
shutil.copyfile('/var/log/mqtt_to_bmon.log', '/var/local/mqtt_to_bmon.log')
logger.info('Backed up Log files.')
except:
# continue on if there is a problem with this non-essential
# operation.
pass
try:
# Copy the reading post queue from the RAM disk to non-volatile
# storage.
# Before copying the database file, need to force a lock on it so that no
# write operations occur during the copying process
fname = '/var/run/postQ.sqlite'
fname_bak = '/var/local/postQ.sqlite' # non-volatile
conn = sqlite3.connect(fname)
cursor = conn.cursor()
# create a dummy table to write into.
try:
cursor.execute('CREATE TABLE _junk (x integer)')
except:
# table already existed
pass
# write a value into the table to create a lock on the database
cursor.execute('INSERT INTO _junk VALUES (1)')
# now copy database
shutil.copy(fname, fname_bak)
# Rollback the Insert as we don't really need it.
conn.rollback()
conn.close()
logger.info('Backed up Post database.')
except:
# continue on if there is a problem with this non-essential
# operation.
pass
def ip_addrs():
"""Returns a list of IP addresses assigned to network interfaces on this
system, ignoring the loopback interface. Returns an empty list if an
error occurs.
"""
try:
ips = []
result = subprocess.check_output('ifconfig | grep "inet "', shell=True, text=True)
for lin in result.splitlines():
flds = lin.strip().split(' ')
if flds[1] != '127.0.0.1':
ips.append(flds[1])
except:
ips = []
return ips
|
import logging
import urllib
from decorators import login_required
from google.appengine.ext import ndb
from application.handlers.base import BaseHandler
from application.models.program import Program
from application.models.agency import Agency
class ProgramHandler(BaseHandler):
@login_required
def get(self, agency=None, program=None):
if program or agency == 'new':
self.tv['error'] = self.request.get('error')
if agency == 'new':
program = agency
if program.lower() != 'new':
agency = Agency.query(Agency.slug == agency).get()
query = Program.query()
query = query.filter(Program.agency == agency.key.id())
program = query.filter(Program.slug == program).get()
self.tv['program'] = program
self.tv['agency'] = agency
agencies = Agency.query().fetch(100)
self.tv['agencies'] = agencies
self.render('program-details.html')
else:
query = Program.query()
if agency:
agency = Agency.query(Agency.slug == agency).get()
query = query.filter(Program.agency == agency.key.id())
self.tv['agency'] = agency
query = query.fetch(100)
agency_keys = []
for program in query:
key = ndb.Key('Agency', program.agency)
if key not in agency_keys:
agency_keys.append(key)
agencies = ndb.get_multi(agency_keys)
self.tv['programs'] = query
self.tv['agencies'] = {}
for agency in agencies:
self.tv['agencies'][agency.key.id()] = {}
self.tv['agencies'][agency.key.id()]['name'] = agency.name
self.tv['agencies'][agency.key.id()]['slug'] = agency.slug
self.render('programs.html')
@login_required
def post(self, program=None):
agency = int(self.request.get('agency'))
name = self.request.get('name')
slug = self.request.get('slug')
description = self.request.get('description')
if program:
query = Program.query()
query = query.filter(Program.agency == int(agency))
query = query.filter(Program.slug == slug)
query = query.get()
if not query:
program = Program()
program.name = name
program.agency = agency
program.slug = slug
program.description = description
program.user = self.user.key
program.put()
agency = ndb.Key('Agency', agency).get()
params = {}
params['success'] = ('The program has been successfully '
'added.')
params = urllib.urlencode(params)
self.redirect('/programs/' + agency.slug + '/' + slug + '?' +
params)
else:
query.name = name
query.agency = agency
query.description = description
query.put()
agency = ndb.Key('Agency', agency).get()
params = {}
params['success'] = ('The program has been successfully '
'updated.')
params = urllib.urlencode(params)
self.redirect('/programs/' + agency.slug + '/' + slug + '?' +
params)
else:
self.redirect('/programs')
|
from collections import Iterable
from matrx.objects import AreaTile, EnvObject
import numpy as np
class CollectionTarget(EnvObject):
def __init__(self, location, collection_objects, collection_zone_name, name="Collection_target"):
""" An invisible object that tells which objects needs collection.
This invisible object is linked to `CollectionDropTile` object(s) and is used by the `CollectionGoal` to
identify which objects should be collected and dropped off at the tiles. This object is just a regular object
but contains three additional properties:
- collection_objects: See parameter doc.
- collection_zone_name: See parameter doc.
- is_invisible: A boolean denoting that this object is invisible. This boolean has no effect in MATRX, except to
denote that this object is not an actual visible object.
- is_drop_off_target: Denotes this object as containing the descriptions of the to be collected objects.
The invisibility is implemented as a block with full opacity, not movable, fully traversable and always below
other objects.
Parameters
----------
location : (x, y)
The location of this object.
collection_objects : List of dicts
A list of dictionaries, each dictionary in this list represents an object that should be dropped at this
location. The dictionary itself represents the property-value pairs these objects should adhere to. The
order of the list matters iff the `CollectionGoal.in_order==True`, in which case the
`CollectionGoal` will track if the dropped objects at this tile are indeed dropped in the order of the list.
collection_zone_name : str
This is the name that links `CollectionDropTile` object(s) to this object. The `CollectionGoal` will check
all of these tiles with this name to check if all objects are already dropped and collected.
name : str (default is "Collection_target")
The name of this object.
Notes
-----
It does not matter where this object is added in the world. However, it is good practice to add it on top of
the (or one of them) `CollectionDropTile` object(s). The helper method to create collection areas
`WorldBuilder.add_collection_goal` follows this practice.
See Also
--------
matrx.WorldBuilder.add_collection_goal
The handy method in the `WorldBuilder` to add a collection goal to the world and required object(s).
matrx.goals.CollectionGoal
The `CollectionGoal` that performs the logic of check that all object(s) are dropped at the drop off tiles.
matrx.objects.CollectionDropTile
The tile that represents the location(s) where the object(s) need to be dropped.
"""
super().__init__(location=location, name=name, class_callable=CollectionTarget, customizable_properties=None,
is_traversable=True, is_movable=False, visualize_size=0, visualize_shape=0,
is_drop_off_target=True, visualize_colour=None, visualize_depth=None, visualize_opacity=0.0,
collection_objects=collection_objects, collection_zone_name=collection_zone_name,
is_invisible=True)
class CollectionDropOffTile(AreaTile):
def __init__(self, location, name="Collection_zone", collection_area_name="Collection zone",
visualize_colour="#64a064", visualize_opacity=1.0, **kwargs):
"""
An area tile used to denote where one or more objects should be dropped. It is similar to any other `AreaTile`
but has two additional properties that identify it as a drop off location for objects and the name of the drop
off. These are used by a `CollectionGoal` to help find the drop off area in all world objects.
Parameters
----------
location : (x, y)
The location of this tile.
name : str (default is "Collection_zone")
The name of this tile.
collection_area_name: str (default is "Collection_zone")
The name of the collection zone this collection tile belongs to. It is used by the respective CollectionGoal
to identify where certain objects should be dropped.
visualize_colour : String (default is "#64a064", a pale green)
The colour of this tile.
visualize_opacity : Float (default is 1.0)
The opacity of this tile. Should be between 0.0 and 1.0.
See also
--------
matrx.WorldBuilder.add_collection_goal
The handy method in the `WorldBuilder` to add a collection goal to the world and required object(s).
matrx.goals.CollectionGoal
The `CollectionGoal` that performs the logic of check that all object(s) are dropped at the drop off tiles.
matrx.objects.CollectionTarget
The invisible object representing which object(s) need to be collected and (if needed) in which order.
"""
super().__init__(location, name=name, visualize_colour=visualize_colour, visualize_depth=None,
visualize_opacity=visualize_opacity, is_drop_off=True,
collection_area_name=collection_area_name, **kwargs)
# class GhostBlock(EnvObject):
# def __init__(self, location, drop_zone_nr, name, visualize_colour, visualize_shape):
# super().__init__(location, name, is_traversable=True, is_movable=False,
# visualize_colour=visualize_colour, visualize_shape=visualize_shape,
# visualize_size=block_size,
# visualize_depth=85, drop_zone_nr=drop_zone_nr, visualize_opacity=0.5,
# is_drop_zone=False, is_goal_block=True, is_collectable=False)
|
from setuptools import setup
setup(
name='bluemoon',
version='0.1.1',
author='ksen0',
author_email='ksenok@protonmail.com',
packages=['bluemoon'],
description='Toolkit for finding exceptional things in data collected about a life.',
)
|
import argparse
from utils.pdb_file import read_pdb_ids_file, fetch_pdb
from utils.io import get_files
from utils.sequence_cluster import match_clusters, get_clusters
from utils.ProgressBar import ProgressBar
def pipeline(pdb_ids, pdb_gz_dir, out_dir='./', m_pdb_ch_file=None, sqid=30, loaded=False, remove_pdb_gz=False, verbose=False):
"""
Perform a full PDB data pipeline.
The dataset is build based on the BLAST clustering. After all proteins have been structured based on
the specified sequence identity percentage, the first representative of each cluster is chosen.
Parameters
----------
pdb_ids_list : list of str
A list of the PDB IDs to be downloaded.
pdb_gz_dir : str
The directory where to find the PDB files in .pdb.gz format.
out_dir : str, optional
The directory where to save the the PDB files. The default is './' (current directory).
m_pdb_ch_file : str, optional
The file holding the list of the protein chains matching with the clusters. The default is None
sqid : int, optional
The sequence identity percentage for the sequence clustering. The default is 30.
loaded : bool, optional
Whether the clusters have already been loaded. The default is False.
remove_pdb_gz : bool, optional
Whether to remove the original compressed PDB file. The default is False.
verbose : bool, optional
Whether to print progress information. The default is False.
Returns
-------
None.
"""
# Get clusters
clusters = get_clusters(sqid=sqid, loaded=loaded, verbose=verbose)
# Match the PDB IDs with the clusters
m_pdb_ch_ids = match_clusters(pdb_ids, clusters=clusters, sqid=sqid, out_file=m_pdb_ch_file, verbose=verbose)
# Fetch the PDB files
progress_bar = ProgressBar(len(m_pdb_ch_ids))
if verbose:
print('Fetching PDBs...')
progress_bar.start()
for m_pdb_ch_id in m_pdb_ch_ids:
if verbose:
progress_bar.step()
fetch_pdb(m_pdb_ch_id, pdb_gz_dir=pdb_gz_dir, out_dir=out_dir, remove_pdb_gz=remove_pdb_gz)
if verbose:
progress_bar.end()
if __name__ == '__main__':
# Argument parser initialization
arg_parser = argparse.ArgumentParser(description='Full PDB dataset pipeline.')
arg_parser.add_argument('out_dir', type=str, help='The directory where to store the PDB files.')
arg_parser.add_argument('--ids_dir', type=str, default='../pdb/ids/', help='The directory containing the .txt files holding the IDs for the PDB. The default is ../pdb/ids/.')
arg_parser.add_argument('--pdb_gz_dir', type=str, default='../pdb/gz/', help='The directory containing the downloaded compressed PDB files. The default is ../pdb/gz/.')
arg_parser.add_argument('--m_pdb_ch_file', type=str, default='../pdb/ids/m_pdb_ch_ids', help='The file holding the list of the protein chains matching with the clusters. The default is ../pdb/ids/m_pdb_ch_ids.')
arg_parser.add_argument('--sqid', type=int, default=30, help='The sequence identity percentage for the BLAST sequence clustering. The default is 30.')
arg_parser.add_argument('--loaded', type=bool, default=False, help='Whether the sequence clusters have already been loaded. The default is False.')
arg_parser.add_argument('--remove_pdb_gz', type=bool, default=False, help='Whether to remove the original compressed PDB file. The default is False.')
arg_parser.add_argument('--verbose', type=bool, default=False, help='Whether to print progress information. The default is False.')
# Parse arguments
args = arg_parser.parse_args()
# Get PDB IDs
pdb_ids = []
files = get_files(args.ids_dir, ext='.txt')
for file in files:
pdb_ids += read_pdb_ids_file(file)
# Begin pipeline
pipeline(pdb_ids, args.pdb_gz_dir, args.out_dir, m_pdb_ch_file=args.m_pdb_ch_file, sqid=args.sqid, loaded=args.loaded, remove_pdb_gz=args.remove_pdb_gz, verbose=args.verbose)
|
# ------------------------------
# 27. Remove Element
#
# Description:
# Given an array and a value, remove all instances of that value in place and return the new length.
# Do not allocate extra space for another array, you must do this in place with constant memory.
#
# The order of elements can be changed. It doesn't matter what you leave beyond the new length.
#
# Example:
# Given input array nums = [3,2,2,3], val = 3
# Your function should return length = 2, with the first two elements of nums being 2.
#
# Version: 1.0
# 09/22/17 by Jianfa
# ------------------------------
class Solution(object):
def removeElement(self, nums, val):
"""
:type nums: List[int]
:type val: int
:rtype: int
"""
list_len = len(nums)
if list_len == 0:
return list_len
else:
l = r = 0
while r < list_len:
if nums[r] != val:
nums[l] = nums[r]
l += 1
r += 1
return l
# Used for test
# if __name__ == "__main__":
# test = Solution()
# nums = []
# print(test.removeElement(nums, 4))
# ------------------------------
# Summary:
# I borrowed the idea from problem 26 that I used two pointers to do list updating, which is also the
# most usual solution.
|
# Generated by Django 2.1.5 on 2019-02-04 15:54
import django.db.models.deletion
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('paikkala', '0009_default_room'),
]
operations = [
migrations.AlterField(
model_name='program',
name='room',
field=models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='paikkala.Room'),
),
migrations.AlterField(
model_name='zone',
name='room',
field=models.ForeignKey(on_delete=django.db.models.deletion.PROTECT, to='paikkala.Room'),
),
]
|
"""Mock responses for device queries."""
GET_DEVICE_RESP = {
"activation_code": None,
"activation_code_expiry_time": "2019-12-12T16:23:14.291Z",
"ad_group_id": 0,
"appliance_name": None,
"appliance_uuid": None,
"av_ave_version": "8.3.62.44",
"av_engine": "4.13.0.207-ave.8.3.62.44:avpack.8.5.0.66:vdf.8.18.9.10 (20200826)",
"av_last_scan_time": None,
"av_master": False,
"av_pack_version": "8.5.0.66",
"av_product_version": "4.13.0.207",
"av_status": [
"AV_ACTIVE",
"ONDEMAND_SCAN_DISABLED"
],
"av_update_servers": None,
"av_vdf_version": "8.18.9.10 (20200826)",
"cluster_name": None,
"current_sensor_policy_name": "policy-restrictive",
"datacenter_name": None,
"deployment_type": "ENDPOINT",
"deregistered_time": None,
"device_meta_data_item_list": [],
"device_owner_id": 93474,
"email": "email@example.org",
"esx_host_name": None,
"esx_host_uuid": None,
"first_name": None,
"id": 98765,
"last_contact_time": "2020-08-26T21:05:42.518Z",
"last_device_policy_changed_time": "2019-12-05T16:24:23.216Z",
"last_device_policy_requested_time": "2020-06-23T00:43:28.164Z",
"last_external_ip_address": "192.168.0.1",
"last_internal_ip_address": "192.168.0.1",
"last_location": "OFFSITE",
"last_name": None,
"last_policy_updated_time": None,
"last_reported_time": "2020-08-26T18:29:37.148Z",
"last_reset_time": None,
"last_shutdown_time": None,
"linux_kernel_version": None,
"login_user_name": "email@example.org",
"mac_address": "000000000000",
"middle_name": None,
"name": "Win7x64",
"organization_id": 654,
"organization_name": "org-name.example.com",
"os": "WINDOWS",
"os_version": "Windows 7 x64 SP: 1",
"passive_mode": False,
"policy_id": 11200,
"policy_name": "policy-restrictive",
"policy_override": True,
"quarantined": False,
"registered_time": "2019-12-05T16:23:14.320Z",
"scan_last_action_time": None,
"scan_last_complete_time": None,
"scan_status": None,
"sensor_kit_type": "WINDOWS",
"sensor_out_of_date": True,
"sensor_pending_update": False,
"sensor_states": [
"ACTIVE",
"LIVE_RESPONSE_NOT_RUNNING",
"LIVE_RESPONSE_NOT_KILLED",
"LIVE_RESPONSE_ENABLED",
"SECURITY_CENTER_OPTLN_DISABLED"
],
"sensor_version": "3.6.0.1201",
"status": "REGISTERED",
"target_priority": "MEDIUM",
"uninstall_code": "ABCDEF",
"vcenter_name": None,
"vcenter_uuid": 'vcenterid',
"vdi_base_device": None,
"virtual_machine": False,
"virtualization_provider": "UNKNOWN",
"vm_ip": None,
"vm_name": None,
"vm_uuid": None,
"vuln_score": 0.0,
"vuln_severity": None,
"windows_platform": None
}
GET_DEVICE_RESP_NO_VCENTER = {
"activation_code": None,
"activation_code_expiry_time": "2019-12-12T16:23:14.291Z",
"ad_group_id": 0,
"appliance_name": None,
"appliance_uuid": None,
"av_ave_version": "8.3.62.44",
"av_engine": "4.13.0.207-ave.8.3.62.44:avpack.8.5.0.66:vdf.8.18.9.10 (20200826)",
"av_last_scan_time": None,
"av_master": False,
"av_pack_version": "8.5.0.66",
"av_product_version": "4.13.0.207",
"av_status": [
"AV_ACTIVE",
"ONDEMAND_SCAN_DISABLED"
],
"av_update_servers": None,
"av_vdf_version": "8.18.9.10 (20200826)",
"cluster_name": None,
"current_sensor_policy_name": "policy-restrictive",
"datacenter_name": None,
"deployment_type": "ENDPOINT",
"deregistered_time": None,
"device_meta_data_item_list": [],
"device_owner_id": 93474,
"email": "email@example.org",
"esx_host_name": None,
"esx_host_uuid": None,
"first_name": None,
"id": 98765,
"last_contact_time": "2020-08-26T21:05:42.518Z",
"last_device_policy_changed_time": "2019-12-05T16:24:23.216Z",
"last_device_policy_requested_time": "2020-06-23T00:43:28.164Z",
"last_external_ip_address": "192.168.0.1",
"last_internal_ip_address": "192.168.0.1",
"last_location": "OFFSITE",
"last_name": None,
"last_policy_updated_time": None,
"last_reported_time": "2020-08-26T18:29:37.148Z",
"last_reset_time": None,
"last_shutdown_time": None,
"linux_kernel_version": None,
"login_user_name": "email@example.org",
"mac_address": "000000000000",
"middle_name": None,
"name": "Win7x64",
"organization_id": 654,
"organization_name": "org-name.example.com",
"os": "WINDOWS",
"os_version": "Windows 7 x64 SP: 1",
"passive_mode": False,
"policy_id": 11200,
"policy_name": "policy-restrictive",
"policy_override": True,
"quarantined": False,
"registered_time": "2019-12-05T16:23:14.320Z",
"scan_last_action_time": None,
"scan_last_complete_time": None,
"scan_status": None,
"sensor_kit_type": "WINDOWS",
"sensor_out_of_date": True,
"sensor_pending_update": False,
"sensor_states": [
"ACTIVE",
"LIVE_RESPONSE_NOT_RUNNING",
"LIVE_RESPONSE_NOT_KILLED",
"LIVE_RESPONSE_ENABLED",
"SECURITY_CENTER_OPTLN_DISABLED"
],
"sensor_version": "3.6.0.1201",
"status": "REGISTERED",
"target_priority": "MEDIUM",
"uninstall_code": "ABCDEF",
"vcenter_name": None,
"vcenter_uuid": None,
"vdi_base_device": None,
"virtual_machine": False,
"virtualization_provider": "UNKNOWN",
"vm_ip": None,
"vm_name": None,
"vm_uuid": None,
"vuln_score": 0.0,
"vuln_severity": None,
"windows_platform": None
}
POST_DEVICE_SEARCH_RESP = {
"results": [
{
"activation_code": None,
"activation_code_expiry_time": "2019-12-12T16:23:14.291Z",
"ad_group_id": 0,
"appliance_name": None,
"appliance_uuid": None,
"av_ave_version": "8.3.62.44",
"av_engine": "4.13.0.207-ave.8.3.62.44:avpack.8.5.0.66:vdf.8.18.9.10 (20200826)",
"av_last_scan_time": None,
"av_master": False,
"av_pack_version": "8.5.0.66",
"av_product_version": "4.13.0.207",
"av_status": [
"AV_ACTIVE",
"ONDEMAND_SCAN_DISABLED"
],
"av_update_servers": None,
"av_vdf_version": "8.18.9.10 (20200826)",
"cluster_name": None,
"current_sensor_policy_name": "policy-restrictive",
"datacenter_name": None,
"deployment_type": "ENDPOINT",
"deregistered_time": None,
"device_meta_data_item_list": [
{
"key_name": "OS_MAJOR_VERSION",
"key_value": "Windows",
"position": 0
},
{
"key_name": "SUBNET",
"key_value": "192.10.33",
"position": 0
}
],
"device_owner_id": 93474,
"email": "email@example.org",
"esx_host_name": None,
"esx_host_uuid": None,
"first_name": None,
"id": 98765,
"last_contact_time": "2020-08-26T21:25:19.513Z",
"last_device_policy_changed_time": "2019-12-05T16:24:23.216Z",
"last_device_policy_requested_time": "2020-06-23T00:43:28.164Z",
"last_external_ip_address": "192.168.0.1",
"last_internal_ip_address": "192.168.0.1",
"last_location": "OFFSITE",
"last_name": None,
"last_policy_updated_time": "2020-01-06T22:55:56.218Z",
"last_reported_time": "2020-08-26T18:29:37.148Z",
"last_reset_time": None,
"last_shutdown_time": None,
"linux_kernel_version": None,
"login_user_name": "email@example.org",
"mac_address": "000000000000",
"middle_name": None,
"name": "Win7x64",
"organization_id": 654,
"organization_name": "org-name.example.com",
"os": "WINDOWS",
"os_version": "Windows 7 x64 SP: 1",
"passive_mode": False,
"policy_id": 11200,
"policy_name": "policy-restrictive",
"policy_override": True,
"quarantined": False,
"registered_time": "2019-12-05T16:23:14.320Z",
"scan_last_action_time": None,
"scan_last_complete_time": None,
"scan_status": None,
"sensor_kit_type": "WINDOWS",
"sensor_out_of_date": True,
"sensor_pending_update": False,
"sensor_states": [
"ACTIVE",
"LIVE_RESPONSE_NOT_RUNNING",
"LIVE_RESPONSE_NOT_KILLED",
"LIVE_RESPONSE_ENABLED",
"SECURITY_CENTER_OPTLN_DISABLED"
],
"sensor_version": "3.6.0.1201",
"status": "REGISTERED",
"target_priority": "MEDIUM",
"uninstall_code": "ABCDEF",
"vcenter_name": None,
"vcenter_uuid": None,
"vdi_base_device": None,
"virtual_machine": False,
"virtualization_provider": "UNKNOWN",
"vm_ip": None,
"vm_name": None,
"vm_uuid": None,
"vuln_score": 0.0,
"vuln_severity": None,
"windows_platform": None
}
],
"num_found": 1
}
|
#!/usr/bin/env python3
import socket
import time
import struct
import sys
import os
import hashlib
import getopt
import fcntl
import struct
import socket, select
from Crypto.Cipher import AES
import base64
import binascii
import random
class AEScipher():
def __init__(self, aespwd):
AESCTR_PASSWORD = hashlib.sha256(aespwd).digest()
key = AESCTR_PASSWORD[:16]
self.nonce = AESCTR_PASSWORD[16:24]
self.cipher = AES.new(key, AES.MODE_ECB)
def encrypt(self, dataarr, seqid, counterStart=None):
BCER = b""
counterStart = counterStart if counterStart is not None else struct.unpack("I", os.urandom(4))[0]
for i in range(len(dataarr) // 16 + 1):
counter = struct.pack("IHH", counterStart, i, seqid)
IVc = self.nonce + counter
BCER += self.cipher.encrypt(IVc)
retarr = b""
for i in range(len(dataarr)):
retarr += struct.pack("B", (dataarr[i] ^ BCER[i]))
return struct.pack("I", counterStart) + retarr
def decrypt(self, dataarr, seqid):
counterStart = dataarr[0:4]
dataarr = dataarr[4:]
return self.encrypt(dataarr, seqid, struct.unpack("I", counterStart)[0])[4:]
class packet():
src = ""
seq = 0
id = 0
type = 0
data = b""
data_raw = b""
class RawICMPtunnel():
def __init__(self, AESpwd):
self.cipher = AEScipher(AESpwd)
self.sock = socket.socket(socket.AF_INET, socket.SOCK_RAW, socket.IPPROTO_ICMP)
def send(self, addr, data, id, seq, encrypt=True):
buf = self.pack_packet(data, id, seq, encrypt=encrypt)
# print("Send to ", (addr , buf))
self.sock.sendto(buf, (addr, 22))
def recv(self):
buf = self.sock.recv(16384)
return self.parse_packet(buf)
def ICMPchecksum(self, source_string):
if type(source_string) != bytes:
raise TypeError("Bust be bytes")
"""
I'm not too confident that this is right but testing seems
to suggest that it gives the same answers as in_cksum in ping.c
"""
sum = 0
countTo = (len(source_string) // 2) * 2
count = 0
while count < countTo:
thisVal = (source_string[count + 1]) * 256 + (source_string[count])
sum = sum + thisVal
sum = sum & 0xffffffff # Necessary?
count = count + 2
if countTo < len(source_string):
sum = sum + (source_string[len(source_string) - 1])
sum = sum & 0xffffffff # Necessary?
sum = (sum >> 16) + (sum & 0xffff)
sum = sum + (sum >> 16)
answer = ~sum
answer = answer & 0xffff
# Swap bytes. Bugger me if I know why.
answer = answer >> 8 | (answer << 8 & 0xff00)
return answer
def pack_packet(self, payload, id, seq, encrypt=True):
# Header is type (8), code (8), checksum (16), id (16), sequence (16)
seq = seq % 2 ** 16
header = struct.pack('!bbHHH', 0, 0, 0, id, seq)
if encrypt == True:
data = self.cipher.encrypt(payload, seq)
else:
data = payload
chksum = self.ICMPchecksum(header + data)
return header[0:2] + struct.pack("!H", chksum) + header[4:] + data
def parse_packet(self, data):
p = packet()
# IPttl, IPproto, IPchksum = struct.unpack("!BBH", data[8:12])
IPsrc, IPdst = socket.inet_ntoa(data[12:16]), socket.inet_ntoa(data[16:20])
ICMPtype, ICMPcode, ICMPchecksum, ICMPpacket_id, ICMPsequence = struct.unpack('!bbHHH', data[20:28])
calsum = self.ICMPchecksum(data[20:22] + b"\x00\x00" + data[24:])
if ICMPchecksum != calsum:
print("checksum not match")
p.src = IPsrc
p.type = ICMPtype
p.id = ICMPpacket_id
p.seq = ICMPsequence
p.data_raw = data[28:]
p.data = self.cipher.decrypt(data[28:], ICMPsequence)
return p
def randomString(stringLength=10):
"""Generate a random string of fixed length """
letters = "0123456789abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ!"
return ''.join(random.choice(letters) for i in range(stringLength))
class TunnelServer():
def __init__(self, addr, masklen, pwd, AESpwd, mtu):
self.icmptun = RawICMPtunnel(AESpwd)
self.pwd = hashlib.md5(pwd).digest()
self.icmpfd = self.icmptun.sock
self.masklen = masklen
self.ServerIP = addr
self.clients = {}
self.mtu = mtu
self.TIMEOUT = 600
self.create()
self.config(addr)
def create(self):
TUNSETIFF = 0x400454ca
IFF_TUN = 0x0001
self.tfd = os.open("/dev/net/tun", os.O_RDWR)
ifs = fcntl.ioctl(self.tfd, TUNSETIFF, struct.pack("16sH", b"t%d", IFF_TUN))
self.tname = ifs[:16].strip(b"\x00").decode("utf8")
print(self.tname)
def config(self, ip):
os.system("ip link set %s up" % (self.tname))
os.system("ip link set %s mtu %i" % (self.tname, self.mtu))
os.system("ip addr add %s/%i dev %s" % (ip, self.masklen, self.tname))
def close(self):
os.close(self.tfd)
def ip_str2int(self, ip_str):
return struct.unpack(">I", struct.pack("BBBB", *map(int, ip_str.split("."))))[0]
def ip_int2str(self, ip_int):
if ip_int < 0:
ip_int += 2 ** 32
return ".".join(map(str, struct.unpack("BBBB", struct.pack(">I", ip_int))))
def getInUseIP(self):
InUse_IP = [self.ServerIP]
for k, c in self.clients.items():
InUse_IP += [c["LanIP"]]
return InUse_IP
def getNextAvailableIp(self):
IFACE_IPi = self.ip_str2int(self.ServerIP)
IFACE_Maski = 2 ** 32 - 2 ** (32 - self.masklen)
inUseIP = map(self.ip_str2int, self.getInUseIP())
for testIP in range(IFACE_Maski + 1, 2 ** 32):
testIP = (IFACE_Maski & IFACE_IPi) | ((2 ** 32 - 1 ^ IFACE_Maski) & testIP)
if testIP not in inUseIP:
return self.ip_int2str(testIP)
print("No ip available, all ip in ip pool are already in use")
return "169.254.1.1"
def run(self):
self.icmpfd = self.icmptun.sock
while True:
rset = select.select([self.icmpfd, self.tfd], [], [])[0]
for r in rset:
# packet from internal (client <-- server)
if r == self.tfd:
data = os.read(self.tfd, self.mtu + 500)
for key, val in self.clients.items():
if socket.inet_ntoa(data[20:24]) == val["LanIP"] or socket.inet_ntoa(
data[20:24]) == self.ip_int2str(
self.ip_str2int(self.ServerIP) | (2 ** (32 - self.masklen) - 1)):
self.icmptun.send(val["addr"], data, val["id"], val["seq"])
val["seq"] += 1
curTime = time.time()
keys = list(self.clients.keys())
for key in keys:
if curTime - self.clients[key]["aliveTime"] > self.TIMEOUT:
print("Remove timeout client", self.clients[key]["addr"])
del self.clients[key]
# packet from external (client --> server)
elif r == self.icmpfd:
pack = self.icmptun.recv()
if pack.type != 8:
continue
key = pack.src + str(pack.id)
data = pack.data
if key not in self.clients:
# New client
if data == b"Login Request":
loginChallange = randomString(64).encode("utf8")
loginAnswer = base64.b64encode(hashlib.sha256(loginChallange + self.pwd).digest())
self.clients[key] = {"aliveTime": time.time(),
"addr": pack.src,
"id": pack.id,
"seq": pack.seq,
"loginChallange": loginChallange,
"loginAnswer": loginAnswer,
"LanIP": "169.254.1.1"
}
print("Login request from %s:%d" % (pack.src, pack.id))
data = b"Login Challange:" + loginChallange
print("Answer is:" + loginAnswer.decode("utf8"))
self.icmptun.send(pack.src, data, pack.id, pack.seq)
else:
print("Normal ping from %s:%d" % (pack.src, pack.id))
self.icmptun.send(pack.src, pack.data_raw, pack.id, pack.seq, encrypt=False)
else:
if self.clients[key]["LanIP"] == "169.254.1.1":
if data.startswith(b"loginAnswer:" + self.clients[key]["loginAnswer"]):
self.clients[key]["LanIP"] = self.getNextAvailableIp()
data = "Login Success. Allocatd IP is :" + self.clients[key]["LanIP"] + "/" + str(
self.masklen)
print(data)
self.icmptun.send(pack.src, data.encode("utf8"), pack.id, pack.seq)
else:
# print(data)
print("wrong answer")
else:
# Simply write the packet to local or forward them to other clients ???
os.write(self.tfd, data)
self.clients[key]["aliveTime"] = time.time()
if __name__ == '__main__':
try:
if len(sys.argv) < 5:
print("Usage: " + sys.argv[0] + " server_address/mask_length password AES_CTR_password MTU")
print("Example: " + sys.argv[0] + " 10.99.8.1/24 password AES-CTR_password 1000")
exit()
tun = TunnelServer(sys.argv[1].split("/")[0], int(sys.argv[1].split("/")[1]), sys.argv[2].encode("utf8"),
sys.argv[3].encode("utf8"), int(sys.argv[4]))
tun.run()
except KeyboardInterrupt:
tun.close()
sys.exit(0)
|
import os
import sys
sys.path.insert(0, os.getcwd())
import numpy as np
import pandas as pd
import dreamtools as dt
@np.vectorize
def approximately_equal(x, y, ndigits=0):
return round(x, ndigits) == round(y, ndigits)
def test_gdx_read():
db = dt.Gdx("test.gdx")
assert approximately_equal(db["qY"]["byg", 2010], 191)
assert approximately_equal(db["qI_s"]["IB", "fre", 2010], 4.43) # "IB" should be changed to "iB" in the GDX file.
assert approximately_equal(db["eCx"], 1)
assert db["fp"] == 1.0178
assert all(approximately_equal(db["inf_factor"], db["fp"]**(2010 - db["inf_factor"].index)))
assert db["s"].name == "s_"
assert db.vHh.loc["Net","tot",1970] == 5e-324
assert set(db["vHh"].index.get_level_values("a_")).issubset(set(db["a_"]))
def test_create_set_from_index():
db = dt.GamsPandasDatabase()
t = pd.Index(range(2010, 2026), name="t")
db.create_set("t", t)
assert db["t"].name == "t"
assert all(db["t"] == t)
assert db.symbols["t"].domains_as_strings == ["*"]
assert db.t.domains == ["*"]
db.create_set("tsub", t[5:], domains=["t"])
assert db["tsub"].name == "tsub"
assert all(db["tsub"] == t[5:])
assert db.symbols["tsub"].domains_as_strings == ["t"]
assert db.tsub.domains == ["t"]
s = pd.Index(["services", "goods"], name="s")
st = pd.MultiIndex.from_product([s, t], names=["s", "t"])
db.create_set("st", st)
assert db["st"].name == "st"
assert all(db["st"] == st[:])
assert db.symbols["st"].domains_as_strings == ["s", "t"]
assert db.st.domains == ["s", "t"]
def test_add_parameter_from_dataframe():
db = dt.GamsPandasDatabase()
df = pd.DataFrame()
df["t"] = range(2010, 2026)
df["value"] = 1.3
db.add_parameter_from_dataframe("par", df, add_missing_domains=True)
assert all(db["par"] == 1.3)
assert len(db["par"]) == 16
def test_multiply_added():
db = dt.GamsPandasDatabase()
df = pd.DataFrame([
[2010, "ser", 3],
[2010, "goo", 2],
[2020, "ser", 6],
[2020, "goo", 4],
], columns=["t", "s", "value"])
db.add_parameter_from_dataframe("q", df, add_missing_domains=True)
df = pd.DataFrame([
[2010, 1],
[2020, 1.2],
], columns=["t", "value"])
db.add_parameter_from_dataframe("p", df, add_missing_domains=True)
v = db["p"] * db["q"]
v.name = "v"
db.add_parameter_from_series(v)
assert db["v"][2020, "goo"] == 4.8
def test_add_parameter_from_series():
db = dt.GamsPandasDatabase()
t = pd.Index(range(2010, 2026), name="t")
par = pd.Series(1.4, index=t, name="par")
db.add_parameter_from_series(par, add_missing_domains=True)
assert all(db["par"] == 1.4)
assert len(db["par"]) == 16
ss = pd.Index(["foo"], name="ss")
singleton = pd.Series(1.4, index=ss, name="singleton")
db.add_parameter_from_series(singleton, add_missing_domains=True)
assert db["singleton"]["foo"] == 1.4
assert len(db["singleton"]) == 1
scalar = pd.Series(1.4, name="scalar")
db.add_parameter_from_series(scalar)
assert all(db["scalar"] == 1.4)
assert len(db["scalar"]) == 1
def test_create_variable():
db = dt.GamsPandasDatabase()
db.create_variable("scalar", data=3.2)
assert db.scalar == 3.2
db.create_variable("vector", data=[1, 2], index=pd.Index(["a", "b"], name="ab"), add_missing_domains=True)
assert all(db.vector == [1, 2])
db.create_variable("dataframe",
data=pd.DataFrame([
[2010, "ser", 3],
[2010, "goo", 2],
[2020, "ser", 6],
[2020, "goo", 4],
], columns=["t", "s", "value"]),
add_missing_domains=True
)
db.export("test_export.gdx")
assert dt.Gdx("test_export.gdx")["scalar"] == 3.2
assert all(dt.Gdx("test_export.gdx")["vector"] == [1, 2])
assert all(db.s == ["ser", "goo"])
assert all(db.t == [2010, 2020])
def test_create_parameter():
db = dt.GamsPandasDatabase()
db.create_parameter("scalar", data=3.2)
assert db.scalar == 3.2
db.create_parameter("vector", data=[1, 2], index=pd.Index(["a", "b"], name="ab"), add_missing_domains=True)
assert all(db.vector == [1, 2])
db.create_parameter("dataframe",
data=pd.DataFrame([
[2010, "ser", 3],
[2010, "goo", 2],
[2020, "ser", 6],
[2020, "goo", 4],
], columns=["t", "s", "value"]),
add_missing_domains=True
)
db.export("test_export.gdx")
assert dt.Gdx("test_export.gdx")["scalar"] == 3.2
assert all(dt.Gdx("test_export.gdx")["vector"] == [1, 2])
assert all(db.s == ["ser", "goo"])
assert all(db.t == [2010, 2020])
def test_add_variable_from_series():
db = dt.GamsPandasDatabase()
t = pd.Index(range(2010, 2026), name="t")
var = pd.Series(1.4, index=t, name="var")
db.add_variable_from_series(var, add_missing_domains=True)
assert all(db["var"] == 1.4)
assert len(db["var"]) == 16
def test_add_variable_from_dataframe():
db = dt.GamsPandasDatabase()
df = pd.DataFrame([
[2010, "ser", 3],
[2010, "goo", 2],
[2020, "ser", 6],
[2020, "goo", 4],
], columns=["t", "s", "value"])
db.add_variable_from_dataframe("q", df, add_missing_domains=True)
assert all(db.t == [2010, 2020])
assert all(db.s == ["ser", "goo"])
def test_multiply_with_different_sets():
assert approximately_equal(
sum(dt.Gdx("test.gdx")["qBNP"] * dt.Gdx("test.gdx")["qI"] * dt.Gdx("test.gdx")["qI_s"]),
50730260150
)
def test_export_with_no_changes():
dt.Gdx("test.gdx").export("test_export.gdx", relative_path=True)
assert round(os.stat("test.gdx").st_size, -5) == round(os.stat("test_export.gdx").st_size, -5)
def test_export_variable_with_changes():
db = dt.Gdx("test.gdx")
db["qY"] = db["qY"] * 2
db.export("test_export.gdx", relative_path=True)
old, new = dt.Gdx("test.gdx"), dt.Gdx("test_export.gdx")
assert all(old["qY"] * 2 == new["qY"])
def test_export_scalar_with_changes():
db = dt.Gdx("test.gdx")
db["eCx"] = db["eCx"] * 2
db.export("test_export.gdx", relative_path=True)
old, new = dt.Gdx("test.gdx"), dt.Gdx("test_export.gdx")
assert approximately_equal(old["eCx"] * 2, new["eCx"])
def test_export_set_with_changes():
db = dt.Gdx("test.gdx")
db["s"].texts["tje"] = "New text"
db.export("test_export.gdx", relative_path=True)
assert dt.Gdx("test_export.gdx")["s"].texts["tje"] == "New text"
def test_copy_set():
db = dt.Gdx("test.gdx")
db["alias"] = db["s"]
db["alias"].name = "alias"
index = db["alias"]
domains = ["*" if i in (None, index.name) else i for i in db.get_domains_from_index(index, index.name)]
db.database.add_set_dc(index.name, domains, "")
index = index.copy()
index.domains = domains
db.series[index.name] = index
db.export("test_export.gdx", relative_path=True)
assert all(dt.Gdx("test_export.gdx")["alias"] == db["s"])
def test_export_added_variable():
db = dt.Gdx("test.gdx")
db.create_variable("foo", [db.a, db.t], explanatory_text="Variable added from Python.")
db["foo"] = 42
db.export("test_export.gdx", relative_path=True)
assert all(approximately_equal(dt.Gdx("test_export.gdx")["foo"], 42))
def test_export_NAs():
db = dt.GamsPandasDatabase()
t = db.create_set("t", range(5))
p = db.create_parameter("p", t)
assert len(db["p"]) == 5
assert len(db.symbols["p"]) == 0
db.export("test_export.gdx")
db = dt.Gdx("test_export.gdx")
assert all(pd.isna(db["p"]))
assert len(db["p"]) == 0
assert len(db.symbols["p"]) == 0
def test_detuple():
assert dt.GamsPandasDatabase.detuple("aaa") == "aaa"
assert dt.GamsPandasDatabase.detuple(("aaa",)) == "aaa"
assert list(dt.GamsPandasDatabase.detuple(("aaa", "bbb"))) == ["aaa", "bbb"]
assert dt.GamsPandasDatabase.detuple(1) == 1
assert list(dt.GamsPandasDatabase.detuple([1, 2])) == [1, 2]
def test_create_methods():
# Create empty GamsPandasDatabase and alias creation methods
db = dt.GamsPandasDatabase()
Par, Var, Set = db.create_parameter, db.create_variable, db.create_set
# Create sets from scratch
t = Set("t", range(2000, 2021), "Årstal")
s = Set("s", ["tjenester", "fremstilling"], "Brancher", ["Tjenester", "Fremstilling"])
st = Set("st", [s, t], "Branche x år dummy")
sub = Set("sub", ["tjenester"], "Subset af brancher", domains=["s"])
one2one = Set("one2one", [(2010, 2015), (2011, 2016)], "1 til 1 mapping", domains=["t", "t"])
one2many = Set("one2many",
[("tot", "tjenester"), ("tot", "fremstilling")],
"1 til mange mapping", domains=["*", "s"],
)
assert one2many.name == "one2many"
assert one2many.names == ["*", "s"]
assert one2many.domains == ["*", "s"]
# Create parameters and variables based on zero ore more sets
gq = Par("gq", None, "Produktivitets-vækst", 0.01)
fq = Par("fp", t, "Vækstkorrektionsfaktor", (1 + 0.01)**(t-2010))
d = Par("d", st, "Dummy")
y = Var("y", [s,t], "Produktion")
assert gq == 0.01
assert all(fq.loc[2010:2011] == [1, 1.01])
assert pd.isna(d["tjenester",2010])
assert pd.isna(y["tjenester",2010])
|
import bs
import bsUtils
import bsSpaz
import weakref
import math
import random
import bsInternal
class PlayerScoredMessage(object):
"""
category: Message Classes
Informs a bs.Activity that a player scored.
Attributes:
score
The score value.
"""
def __init__(self,score):
'Instantiate with the given values'
self.score = score
class ScoreSet(object):
""" Manages individual score keeping for players; provides persistant scores and some other goodies.
Players are indexed here by name so that if a player leaves and comes back he'll keep the same score """
class _Player(object):
def __init__(self, name, nameFull, player, scoreSet):
self.name = name
self.nameFull = nameFull
self.score = 0
self.accumScore = 0
self.killCount = 0
self.accumKillCount = 0
self.killedCount = 0
self.accumKilledCount = 0
self._multiKillTimer = None
self._multiKillCount = 0
self._scoreSet = weakref.ref(scoreSet)
self._associateWithPlayer(player)
def getTeam(self):
return self.team()
def getPlayer(self):
return self._player
def getName(self, full=False):
return self.nameFull if full else self.name
def getIcon(self):
return self.lastPlayer.getIcon()
def getSpaz(self):
if self._spaz is None: return None
return self._spaz()
def cancelMultiKillTimer(self):
self._multiKillTimer = None
def getActivity(self):
try: return self._scoreSet()._activity()
except Exception: return None
def _associateWithPlayer(self, player):
self.lastPlayer = player
self._player = player
self.team = weakref.ref(player.getTeam())
self.character = player.character
self._spaz = None
self.streak = 0
def _endMultiKill(self):
self._multiKillTimer = None
self._multiKillCount = 0
def submitKill(self,showPoints=True):
self._multiKillCount += 1
if self._multiKillCount == 1:
score = 0
name = None
elif self._multiKillCount == 2:
score = 20
name = bs.Lstr(resource='twoKillText')
color=(0.1,1.0,0.0,1)
scale = 1.0
delay = 0
sound = self._scoreSet()._orchestraHitSound
elif self._multiKillCount == 3:
score = 40
name = bs.Lstr(resource='threeKillText')
color=(1.0,0.7,0.0,1)
scale = 1.1
delay = 300
sound = self._scoreSet()._orchestraHitSound2
elif self._multiKillCount == 4:
score = 60
name = bs.Lstr(resource='fourKillText')
color=(1.0,1.0,0.0,1)
scale = 1.2
delay = 600
sound = self._scoreSet()._orchestraHitSound3
elif self._multiKillCount == 5:
score = 80
name = bs.Lstr(resource='fiveKillText')
color=(1.0,0.5,0.0,1)
scale = 1.3
delay = 900
sound = self._scoreSet()._orchestraHitSound4
else:
score = 100
name = bs.Lstr(resource='multiKillText',subs=[('${COUNT}',str(self._multiKillCount))])
color=(1.0,0.5,0.0,1)
scale = 1.3
delay = 1000
sound = self._scoreSet()._orchestraHitSound4
def _apply(name,score,showPoints,color,scale,sound):
# only award this if they're still alive and we can get their pos
try: ourPos = self.getSpaz().node.position
except Exception: return
# jitter position a bit since these often come in clusters
ourPos = (ourPos[0]+(random.random()-0.5)*2.0,
ourPos[1]+(random.random()-0.5)*2.0,
ourPos[2]+(random.random()-0.5)*2.0)
activity = self.getActivity()
if activity is not None:
bsUtils.PopupText(
# (('+'+str(score)+' ') if showPoints else '')+name,
bs.Lstr(value=(('+'+str(score)+' ') if showPoints else '')+'${N}',subs=[('${N}',name)]),
color=color,
scale=scale,
position=ourPos).autoRetain()
bs.playSound(sound)
self.score += score
self.accumScore += score
# inform a running game of the score
if score != 0 and activity is not None:
activity.handleMessage(PlayerScoredMessage(score=score))
if name is not None:
bs.gameTimer(300+delay,bs.Call(_apply,name,score,showPoints,color,scale,sound))
# keep the tally rollin'...
# set a timer for a bit in the future
self._multiKillTimer = bs.Timer(1000,self._endMultiKill)
def __init__(self):
self._activity = None
self._players = {}
def setActivity(self,activity):
self._activity = None if activity is None else weakref.ref(activity)
# load our media into this activity's context
if activity is not None:
if activity.isFinalized():
bs.printError('unexpected finalized activity')
with bs.Context(activity): self._loadMedia()
def _loadMedia(self):
self._orchestraHitSound = bs.getSound('orchestraHit')
self._orchestraHitSound2 = bs.getSound('orchestraHit2')
self._orchestraHitSound3 = bs.getSound('orchestraHit3')
self._orchestraHitSound4 = bs.getSound('orchestraHit4')
def reset(self):
# just to be safe, lets make sure no multi-kill timers are gonna go off
# for no-longer-on-the-list players
for p in self._players.values(): p.cancelMultiKillTimer()
self._players = {} # our dict of players indexed by name
# for things like per-round sub-scores..
def resetAccum(self):
for p in self._players.values():
p.cancelMultiKillTimer()
p.accumScore = 0
p.accumKillCount = 0
p.accumKilledCount = 0
p.streak = 0
def registerPlayer(self,player):
name = player.getName()
nameFull = player.getName(full=True)
try:
# if the player already exists, update his character and such as it may have changed
self._players[name]._associateWithPlayer(player)
except Exception: p = self._players[name] = self._Player(name,nameFull,player,self)
def getValidPlayers(self):
validPlayers = {}
# go through our player records and return ones whose player id still corresponds to a player with that name
for pName,p in self._players.items():
try: exists = (p.lastPlayer.exists() and p.lastPlayer.getName() == pName)
except Exception: exists = False
if exists:
validPlayers[pName] = p
return validPlayers
def _getSpaz(self,player):
p = self._players[player.getName()]
# this is a weak-ref
if p._spaz is None: return None
return p._spaz()
def playerGotNewSpaz(self,player,spaz):
p = self._players[player.getName()]
if p.getSpaz() is not None: raise Exception("got 2 playerGotNewSpaz() messages in a row without a lost-spaz message")
p._spaz = weakref.ref(spaz)
def playerGotHit(self,player):
p = self._players[player.getName()]
p.streak = 0
def playerScored(self,player,basePoints=1,target=None, kill=False, victimPlayer=None,scale=1.0,color=None,title=None,screenMessage=True,display=True,importance=1,showPoints=True,bigMessage=False):
""" register a score for the player; return value is actual score with multipliers and such factored in """
name = player.getName()
p = self._players[name]
# if title is None: title = ''
if kill: p.submitKill(showPoints=showPoints)
displayColor = (1,1,1,1)
if color is not None: displayColor = color
elif importance != 1:
displayColor = (1.0,1.0,0.4,1)
points = basePoints
exc = ''
# if they want a big announcement, throw a zoom-text up there
if display and bigMessage:
try:
activity = self._activity()
if activity:
nameFull = player.getName(full=True,icon=False)
activity.showZoomMessage(bs.Lstr(resource='nameScoresText',subs=[('${NAME}',nameFull)]),color=bsUtils.getNormalizedColor(player.getTeam().color))
except Exception,e:
print 'Exception showing bigMessage',e
# if we currently have a spaz, pop up a score over it
if display and showPoints:
try: ourPos = p.getSpaz().node.position
except Exception: ourPos = None
if ourPos is not None:
if target is None: target = ourPos
# if display-pos is *way* lower than us, raise it up
# (so we can still see scores from dudes that fell off cliffs)
displayPos = (target[0], max(target[1], ourPos[1]-2.0), min(target[2], ourPos[2]+2.0))
# bs.printError('ignoring title arg in playerScored:',title)
# if type(title) != str or title != '': title = ' '+title
activity = self._activity()
if activity is not None:
if title is not None:
s = bs.Lstr(value='+${A} ${B}',subs=[('${A}',str(points)),('${B}',title)])
else:
s = bs.Lstr(value='+${A}',subs=[('${A}',str(points))])
# bsUtils.PopupText('+'+str(points)+title,
bsUtils.PopupText(s,
color=displayColor,
scale=1.2*scale,
position=displayPos).autoRetain()
# tally kills
if kill:
p.accumKillCount += 1
p.killCount += 1
# report non-kill scorings
try:
if screenMessage and not kill:
bs.screenMessage(bs.Lstr(resource='nameScoresText',subs=[('${NAME}',name)]),
top=True,color=player.color,
image=player.getIcon())
except Exception,e: print 'Error announcing score:',e
p.score += points
p.accumScore += points
# inform a running game of the score
if points != 0:
activity = self._activity() if self._activity is not None else None
if activity is not None:
activity.handleMessage(PlayerScoredMessage(score=points))
return points
def playerLostSpaz(self, player, killed=False, killer=None):
name = player.getName()
p = self._players[name]
p._spaz = None
p.streak = 0
if killed:
p.accumKilledCount += 1
p.killedCount += 1
try:
if killed and bs.getActivity().announcePlayerDeaths:
if killer == player:
bs.screenMessage(bs.Lstr(resource='nameSuicideKidFriendlyText' if bsInternal._getSetting('Kid Friendly Mode') else 'nameSuicideText',subs=[('${NAME}',name)]),
top=True,color=player.color,image=player.getIcon())
elif killer is not None:
if killer.getTeam() == player.getTeam():
bs.screenMessage(bs.Lstr(resource='nameBetrayedText',subs=[('${NAME}',killer.getName()),('${VICTIM}',name)]),
top=True,color=killer.color,image=killer.getIcon())
else:
bs.screenMessage(bs.Lstr(resource='nameKilledText',subs=[('${NAME}',killer.getName()),('${VICTIM}',name)]),
top=True,color=killer.color,image=killer.getIcon())
else:
bs.screenMessage(bs.Lstr(resource='nameDiedText',subs=[('${NAME}',name)]),
top=True,color=player.color,image=player.getIcon())
except Exception,e:
bs.printException('Error announcing kill')
|
from django.db import models
from api.models.post.models import Post
class DetailPost(models.Model):
num = models.OneToOneField(Post,
unique=True,
primary_key=True,
on_delete=models.DO_NOTHING,
related_name='detail',
db_column='num')
detail = models.TextField()
class Meta:
db_table = 'detail_post'
verbose_name = '캐시된 게시글'
verbose_name_plural = '캐시 목록'
|
import csv
import json
import sys
###############################################################################
#
# This file takes in a Manuscript vhmml JSON file with just listing data
# and outputs a CSV file (id, country, city, repository, shelf mark,
# project number, permalink
#
###############################################################################
# Load JSON data file into a Python variable.
if len(sys.argv) > 1:
filetoOpen = sys.argv[1]
else:
filetoOpen = raw_input("Name of the vHMML JSON listing data file? ")
input = open(filetoOpen)
# load the JSON file data into a python object
data = json.load(input)
# close the open JSON file. just in case
input.close()
# TESTING: Print out all the JSON data
# print data
# delete file if exists? Don't need to, will just overwrite existing file
csvFile = 'csvfile_'+filetoOpen+'.csv'
f = open(csvFile, 'w')
# make the header string first, include all the fields so that no matter what
# they show up.
csvHeaderString = "id,"
csvHeaderString = csvHeaderString + "country,"
csvHeaderString = csvHeaderString + "city,"
csvHeaderString = csvHeaderString + "repository,"
csvHeaderString = csvHeaderString + "shelfmark,"
csvHeaderString = csvHeaderString + "hmmlProjectNumber,"
csvHeaderString = csvHeaderString + "permalink"
# TESTING
# print csvHeaderString
# write out the header row for the CSV file
csvHeaderString = csvHeaderString + "\n"
f.write(csvHeaderString)
# This for loop traverses the JSON file, and puts the value,
# if there, into a string
for x in data:
if x["id"]:
csvValuesString = str(x["id"]) + ','
else:
csvValuesString = csvValuesString + 'null,'
if "country" in x:
csvValuesString = csvValuesString + x["country"].encode('utf-8') + ','
else:
csvValuesString = csvValuesString + 'null,'
if x["city"]:
csvValuesString = csvValuesString + x["city"].encode('utf-8') + ','
else:
csvValuesString = csvValuesString + 'null,'
if x["repository"]:
csvValuesString = csvValuesString + x["repository"].encode('utf-8')+','
else:
csvValuesString = csvValuesString + 'null,'
if "shelfmark" in x:
csvValuesString = csvValuesString + x["shelfmark"].encode('utf-8')+','
else:
csvValuesString = csvValuesString + 'null,'
if x["hmmlProjectNumber"]:
csvValuesString = csvValuesString + str(x["hmmlProjectNumber"])+','
else:
csvValuesString = csvValuesString + 'null,'
if x["permalink"]:
csvValuesString = csvValuesString + str(x["permalink"])
else:
csvValuesString = csvValuesString + 'null'
# TESTING
# print csvValuesString
csvValuesString = csvValuesString + '\n'
f.write(csvValuesString)
# Python will convert \n to os.linesep. Close the file
f.close()
# Tell them we're done
print "Done! Open " + csvFile + " to view your CSV listing data."
|
from __future__ import annotations
import datetime
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
from .attachments import Poll, Geo, File, Media
from .enums import ReplySetting
from .constants import (
TWEET_EXPANSION,
TWEET_FIELD,
USER_FIELD,
PINNED_TWEET_EXPANSION,
MEDIA_FIELD,
PLACE_FIELD,
POLL_FIELD,
)
from .relations import RelationHide, RelationLike, RelationRetweet, RelationDelete
from .user import User
from .utils import time_parse_todt, convert
from .message import Message
from .paginations import UserPagination, TweetPagination
from .dataclass import (
Embed,
EmbedImage,
PublicTweetMetrics,
NonPublicTweetMetrics,
OrganicTweetMetrics,
PromotedTweetMetrics,
)
if TYPE_CHECKING:
from .http import HTTPClient
from .type import ID
__all__ = ("Tweet",)
class Tweet(Message):
"""Represents a tweet message from Twitter.
A Tweet is any message posted to Twitter which may contain photos, videos, links, and text. This class inherits :class:`Message`,
.. describe:: x == y
Check if one tweet id is equal to another.
.. describe:: x != y
Check if one tweet id is not equal to another.
.. describe:: str(x)
Get the Tweet's text.
.. versionadded:: 1.0.0
"""
__slots__ = (
"__original_payload",
"_payload",
"_includes",
"tweet_metrics",
"http_client",
"deleted_timestamp",
"_public_metrics",
"_non_public_metrics",
"_organic_metrics",
"_promoted_metrics",
)
def __init__(
self,
data: Dict[str, Any],
*,
deleted_timestamp: Optional[int] = None,
http_client: Optional[HTTPClient] = None,
) -> None:
self.__original_payload = data
self._payload = data.get("data") or data
self._includes = self.__original_payload.get("includes")
self._referenced_tweets = self._payload.get("referenced_tweets")
self._entities = self._payload.get("entities")
self.http_client = http_client
self.deleted_timestamp = deleted_timestamp
self._public_metrics = PublicTweetMetrics(
**self._payload.get("public_metrics", None) or self.__original_payload.get("public_metrics")
)
self._non_public_metrics = self._payload.get("non_public_metrics", None) or self.__original_payload.get(
"non_public_metrics"
)
self._organic_metrics = self._payload.get("organic_metrics", None) or self.__original_payload.get(
"organic_metrics"
)
self._promoted_metrics = self._payload.get("promoted_metrics", None) or self.__original_payload.get(
"promoted_metrics"
)
if self._non_public_metrics:
non_public_metrics = self.http_client.payload_parser.parse_metric_data(self._non_public_metrics)
self._non_public_metrics = NonPublicTweetMetrics(**non_public_metrics)
if self._organic_metrics:
organic_metrics = self.http_client.payload_parser.parse_metric_data(self._organic_metrics)
self._organic_metrics = OrganicTweetMetrics(**organic_metrics)
if self._promoted_metrics:
promoted_metrics = self.http_client.payload_parser.parse_metric_data(self._promoted_metrics)
self._promoted_metrics = PromotedTweetMetrics(**promoted_metrics)
if self._entities and self._entities.get("urls"):
data = []
for url in self._entities["urls"]:
url = self.http_client.payload_parser.parse_embed_data(url)
data.append(url)
self._embeds = data
else:
self._embeds = None
super().__init__(self._payload.get("text"), self._payload.get("id"), 1)
def __repr__(self) -> str:
return "Tweet(text={0.text} id={0.id} author={0.author!r})".format(self)
@property
def author(self) -> Optional[User]:
"""Optional[:class:`User`]: Returns a user (object) who posted the tweet.
.. versionadded: 1.0.0
"""
if self._includes and self._includes.get("users"):
return User(self._includes.get("users")[0], http_client=self.http_client)
return None
@property
def possibly_sensitive(self) -> bool:
""":class:`bool`: Returns True if the tweet is possible sensitive to some users, else False.
.. versionadded: 1.0.0
"""
return self._payload.get("possibly_sensitive")
@property
def sensitive(self) -> bool:
""":class:`bool`: An alias to :meth:`Tweet.possibly_sensitive`.
.. versionadded: 1.5.0
"""
return self.possibly_sensitive
@property
def created_at(self) -> datetime.datetime:
""":class:`datetime.datetime`: Returns a :class:`datetime.datetime` object when the tweet was created.
.. versionadded: 1.0.0
"""
if self._payload.get("timestamp", None):
return datetime.datetime.fromtimestamp(int(self._payload.get("timestamp", None)) / 1000)
return time_parse_todt(self._payload.get("created_at"))
@property
def deleted_at(self) -> Optional[datetime.datetime]:
"""Optional[:class:`datetime.datetime`]: Returns a :class:`datetime.datetime` object when the tweet was deleted. Returns None when the tweet is not deleted.
.. note::
This property can only returns :class:`datetime.datetime` object through a tweet object from `on_tweet_delete` event.
.. versionadded: 1.5.0
"""
if not self.deleted_timestamp:
return None
return datetime.datetime.fromtimestamp(self.deleted_timestamp / 1000)
@property
def source(self) -> str:
""":class:`str`: Returns the source of the tweet. e.g if you post a tweet from a website, the source is gonna be 'Twitter Web App'
.. versionadded: 1.0.0
"""
return self._payload.get("source")
@property
def reply_setting(self) -> ReplySetting:
""":class:`ReplySetting`: Returns a :class:`ReplySetting` object with the tweet's reply setting. If everyone can reply, this method return :class:`ReplySetting.everyone`.
.. versionadded: 1.3.5
"""
return ReplySetting(self._payload.get("reply_settings"))
@property
def raw_reply_setting(self) -> str:
""":class:`str`: Returns the raw reply setting value. If everyone can replied, this method return 'Everyone'.
.. versionadded: 1.0.0
"""
return self._payload.get("reply_settings")
@property
def lang(self) -> str:
""":class:`str`: Returns the tweet's lang, if its english it return en.
.. versionadded: 1.0.0
"""
return self._payload.get("lang")
@property
def conversation_id(self) -> Optional[int]:
"""Optional[:class:`int`]: All replies are bind to the original tweet, this property returns the tweet's id if the tweet is a reply tweet else it returns None.
.. versionadded: 1.0.0
"""
try:
return int(self._payload.get("conversation_id"))
except ValueError:
return None
@property
def url(self) -> Optional[str]:
"""Optional[:class:`str`]: Get the tweet's url.
.. versionadded:: 1.1.0
.. versionchanged:: 1.5.0
Returns None if the author is invalid or the tweet doesn't have id.
"""
try:
return f"https://twitter.com/{self.author.username}/status/{self.id}"
except TypeError:
return None
@property
def mentions(self) -> Optional[List[User]]:
"""Optional[List[:class:`User`]]: Returns a list of :class:`User` objects that were mentioned in the tweet or an empty list / `[]` if no users were mentioned.
.. versionadded:: 1.1.3
.. versionchanged:: 1.5.0
Now returns a list of :class:`User` objects rather then a list of :class:`str` objects.
"""
users = []
for user in self._includes.get("users", {}):
for mention in self._entities.get("mentions", {}):
if user["id"] == mention["id"]:
users.append(User(user, http_client=self.http_client))
return users
@property
def poll(self) -> Optional[Poll]:
""":class:`Poll`: Returns a Poll object with the tweet's poll.
.. versionadded:: 1.1.0
"""
if self._includes:
if self._includes.get("polls"):
data = self._includes.get("polls")[0]
poll = Poll(
duration=data.get("duration_minutes"),
id=data.get("id"),
voting_status=data.get("voting_status"),
end_date=data.get("end_datetime"),
)
for option in data.get("options"):
poll.add_option(**option)
return poll
return None
@property
def medias(self) -> Optional[List[Media]]:
"""Optional[List[:class:`Media`]]: Returns a list of media(s) in a tweet.
.. versionadded:: 1.1.0
"""
if self._includes and self._includes.get("media"):
return [Media(img, http_client=self.http_client) for img in self._includes.get("media")]
return None
@property
def reference_user(self) -> Optional[User]:
"""Optional[:class:`User`]: Returns the referenced user. This can means:
The tweet is a retweet, which means the method returns the retweeted tweet's author.
The tweet is a quote tweet(retweet with comments), which means the method returns the quoted tweet's author.
The tweet is a reply tweet, which means the method returns the replied tweet's author.
.. versionadded:: 1.5.0
"""
if not self._includes or not self._includes.get("users") or not self._referenced_tweets:
return None
type = self._referenced_tweets[0].get("type", " ")
for user in self._includes["users"]:
if type == "replied_to" and user["id"] == self._payload.get("in_reply_to_user_id", 0):
# If the tweet count as a reply tweet,
# it would returns a user data that match the user's id with 'in_reply_to_user_id' data.
return User(user, http_client=self.http_client)
elif type == "quoted":
# If the tweet count as a quote tweet,
# it would returns a user data if the url contains the user's id. Every quote tweets have at least 1 url, the quoted tweet's url that contain the quoted tweet's author's id and the tweet id itself.
for embed in self.embeds:
if (
embed.expanded_url.startswith("https://twitter.com/")
and embed.expanded_url.split("/")[3] == user["id"]
):
return User(user, http_client=self.http_client)
elif type == "retweeted":
# If the tweet count as a retweet,
# it would returns a user data if the user are mention with a specific format, that is: 'RT @Mention: {The retweeted tweet's content}'
# The code only checks characters before the colon with the colon includes (i.e 'RT @Mention:').
for mentioned_user in self.mentions:
if self.text.startswith(f"RT {mentioned_user.mention}:"):
return mentioned_user
return None
@property
def reference_tweet(self) -> Optional[Tweet]:
"""Optional[:class:`Tweet`]: Returns the tweet's parent tweet or the referenced tweet. This can mean the parent tweet of the requested tweet is:
A retweeted tweet (The child Tweet is a Retweet),
A quoted tweet (The child Tweet is a Retweet with comment, also known as Quoted Tweet),
A replied tweet (The child Tweet is a reply tweet).
.. versionadded:: 1.5.0
"""
tweets = self._includes.get("tweets")
if not self._includes or not tweets or not self._referenced_tweets:
return None
for tweet in tweets:
if tweet["id"] == self._referenced_tweets[0]["id"]:
self.http_client.payload_parser.insert_object_author(tweet, self.reference_user)
return Tweet(tweet, http_client=self.http_client)
return None
@property
def embeds(self) -> Optional[List[Embed]]:
"""List[:class:`Embed`]: Returns a list of Embedded urls from the tweet
.. versionadded:: 1.1.3
"""
for embed in self._embeds:
if embed.get("images"):
for index, image in enumerate(embed["images"]):
if isinstance(image, EmbedImage):
break
embed["images"][index] = EmbedImage(**image)
return [Embed(**data) for data in self._embeds]
@property
def like_count(self) -> Optional[int]:
"""Optional[:class:`int`]: Returns the total of likes in the tweet.
.. versionadded: 1.1.0
"""
return convert(self._metrics.like_count, int)
@property
def retweet_count(self) -> Optional[int]:
"""Optional[:class:`int`]: Returns the total of retweetes in the tweet.
.. versionadded: 1.1.0
"""
return convert(self._metrics.retweet_count, int)
@property
def reply_count(self) -> Optional[int]:
"""Optional[:class:`int`]: Returns the total of replies in the tweet.
.. versionadded: 1.1.0
"""
return convert(self._metrics.reply_count, int)
@property
def quote_count(self) -> Optional[int]:
"""Optional[:class:`int`]: Returns the total of quotes in the tweet.
.. versionadded: 1.1.0
"""
return convert(self._metrics.quote_count, int)
@property
def non_public_metrics(self) -> Optional[OrganicTweetMetrics]:
"""Optional[:class:`OrganicTweetMetrics`]: The tweet's metrics that are not available for anyone to view on Twitter, such as `impressions_count` and `video view quartiles`.
.. versionadded:: 1.5.0
"""
return self._non_public_metrics
@property
def organic_metrics(self) -> Optional[OrganicTweetMetrics]:
"""Optional[:class:`OrganicTweetMetrics`]: The tweet's metrics in organic context (posted and viewed in a regular manner), such as `impression_count`, `user_profile_clicks` and `url_link_clicks`.
.. versionadded:: 1.5.0
"""
return self._organic_metrics
@property
def promoted_metrics(self) -> Optional[PromotedTweetMetrics]:
"""Optional[:class:`PromotedTweetMetrics`]: The tweet's metrics in promoted context (posted or viewed as part of an Ads campaign), such as `impression_count`, `user_profile_clicks` and `url_link_clicks`.
.. versionadded:: 1.5.0
"""
return self._promoted_metrics
def like(self) -> Optional[RelationLike]:
"""Like the tweet.
Returns
---------
Optional[:class:`RelationLike`]
This method returns a :class:`RelationLike` object.
.. versionadded:: 1.2.0
"""
my_id = self.http_client.access_token.partition("-")[0]
res = self.http_client.request("POST", "2", f"/users/{my_id}/likes", json={"tweet_id": str(self.id)}, auth=True)
return RelationLike(res)
def unlike(self) -> Optional[RelationLike]:
"""Unlike the tweet.
Returns
---------
:class:`RelationLike`
This method returns a :class:`RelationLike` object.
.. versionadded:: 1.2.0
"""
my_id = self.http_client.access_token.partition("-")[0]
res = self.http_client.request("DELETE", "2", f"/users/{my_id}/likes/{self.id}", auth=True)
return RelationLike(res)
def retweet(self) -> RelationRetweet:
"""Retweet the tweet.
Returns
---------
:class:`RelationRetweet`
This method returns a :class:`RelationRetweet` object.
.. versionadded:: 1.2.0
"""
my_id = self.http_client.access_token.partition("-")[0]
res = self.http_client.request(
"POST",
"2",
f"/users/{my_id}/retweets",
json={"tweet_id": str(self.id)},
auth=True,
)
return RelationRetweet(res)
def unretweet(self) -> RelationRetweet:
"""Unretweet the tweet.
Returns
---------
:class:`RelationRetweet`
This method returns a :class:`RelationRetweet` object.
.. versionadded:: 1.2.0
"""
my_id = self.http_client.access_token.partition("-")[0]
res = self.http_client.request("DELETE", "2", f"/users/{my_id}/retweets/{self.id}", auth=True)
return RelationRetweet(res)
def delete(self) -> RelationDelete:
"""Delete the client's tweet.
.. note::
You can only delete the client's tweet.
.. versionadded:: 1.2.0
"""
res = self.http_client.request("DELETE", "2", f"/tweets/{self.id}", auth=True)
try:
self.http_client.tweet_cache.pop(self.id)
except KeyError:
pass
return RelationDelete(res)
def reply(
self,
text: str = None,
*,
file: Optional[File] = None,
files: Optional[List[File]] = None,
geo: Optional[Union[Geo, str]] = None,
direct_message_deep_link: Optional[str] = None,
reply_setting: Optional[Union[ReplySetting, str]] = None,
exclude_reply_users: Optional[List[User, ID]] = None,
media_tagged_users: Optional[List[User, ID]] = None,
) -> Optional[Tweet]:
"""Post a tweet to reply to the tweet present by the tweet's id. Returns a :class:`Tweet` object or :class:`Message` if the tweet is not found in the cache.
.. note::
Note that if the tweet is a retweet you cannot reply to that tweet, it might not raise an error but it will post the tweet has a normal tweet rather then a reply tweet and it ping the :class:`Tweet.author`.
Parameters
------------
text: :class:`str`
The tweet's text, it will show up as the main text in a tweet.
file: Optional[:class:`File`]
Represents a single file attachment. It could be an image, gif, or video. It also have to be an instance of pytweet.File
files: Optional[List[:class:`File`]]
Represents multiple file attachments in a list. It could be an image, gif, or video. the item in the list must also be an instance of pytweet.File
geo: Optional[Union[:class:`Geo`, :class:`str`]]
The geo attachment, you can put an object that is an instance of :class:`Geo` or the place ID in a string.
direct_message_deep_link: Optional[:class:`str`]
The direct message deep link, It will showup as a CTA(call-to-action) with button attachment. Example of direct message deep link:
reply_setting: Optional[Union[:class:`ReplySetting`, :class:`str`]]
The reply setting that you can set to minimize users that can reply. If None is specified, the default is set to 'everyone' can reply.
exclude_reply_users: Optional[List[:class:`User`]]
A list of users or user ids to be excluded from the reply :class:`Tweet` thus removing a user from a thread, if you dont want to mention a reply with 3 mentions, You can use this argument and provide the user id you don't want to mention.
media_tagged_users: Optional[List[:class:`User`]]
A list of users or user ids being tagged in the Tweet with Media. If the user you're tagging doesn't have photo-tagging enabled, their names won't show up in the list of tagged users even though the Tweet is successfully created.
Returns
---------
Union[:class:`Tweet`, :class:`Message`]
Returns a :class:`Tweet` object or :class:`Message` object if the tweet is not found in the cache.
.. versionadded:: 1.2.5
"""
return self.http_client.post_tweet(
text,
file=file,
files=files,
geo=geo,
direct_message_deep_link=direct_message_deep_link,
reply_setting=reply_setting,
reply_tweet=self.id,
exclude_reply_users=exclude_reply_users,
media_tagged_users=media_tagged_users,
)
def hide(self) -> RelationHide:
"""Hide a reply tweet.
Returns
---------
:class:`RelationHide`
This method returns a :class:`RelationHide` object.
.. versionadded:: 1.2.5
"""
res = self.http_client.request("PUT", "2", f"/tweets/{self.id}/hidden", json={"hidden": False}, auth=True)
return RelationHide(res)
def unhide(self) -> RelationHide:
"""Unhide a hide reply.
Returns
---------
:class:`RelationHide`
This method returns a :class:`RelationHide` object.
.. versionadded:: 1.2.5
"""
res = self.http_client.request("PUT", "2", f"/tweets/{self.id}/hidden", json={"hidden": False}, auth=True)
return RelationHide(res)
def fetch_retweeters(self) -> Optional[UserPagination]:
"""Returns a pagination object with the users that retweeted the tweet.
Returns
---------
Optional[:class:`UserPagination`]
This method returns a :class:`UserPagination` object.
.. versionadded:: 1.1.3
"""
res = self.http_client.request(
"GET",
"2",
f"/tweets/{self.id}/retweeted_by",
params={
"expansions": PINNED_TWEET_EXPANSION,
"user.fields": USER_FIELD,
"tweet.fields": TWEET_FIELD,
},
)
if not res:
return []
return UserPagination(
res,
endpoint_request=f"/tweets/{self.id}/retweeted_by",
http_client=self.http_client,
params={
"expansions": PINNED_TWEET_EXPANSION,
"user.fields": USER_FIELD,
"tweet.fields": TWEET_FIELD,
},
)
def fetch_likers(self) -> Optional[UserPagination]:
"""Returns a pagination object with the users that liked the tweet.
Returns
---------
Optional[:class:`UserPagination`]
This method returns a :class:`UserPagination` object.
.. versionadded:: 1.1.3
"""
res = self.http_client.request(
"GET",
"2",
f"/tweets/{self.id}/liking_users",
params={
"expansions": PINNED_TWEET_EXPANSION,
"user.fields": USER_FIELD,
"tweet.fields": TWEET_FIELD,
},
)
if not res:
return []
return UserPagination(
res,
endpoint_request=f"/tweets/{self.id}/liking_users",
http_client=self.http_client,
params={
"expansions": PINNED_TWEET_EXPANSION,
"user.fields": USER_FIELD,
"tweet.fields": TWEET_FIELD,
},
)
def fetch_quoted_tweets(self) -> Optional[TweetPagination]:
"""Returns a pagination object for tweets that quoted the tweet
Returns
---------
Optional[:class:`TweetPagination`]
This method returns :class:`TweetPagination` or an empty list if the tweet does not contain any quoted tweets.
.. versionadded:: 1.5.0
"""
params = {
"expansions": TWEET_EXPANSION,
"user.fields": USER_FIELD,
"tweet.fields": TWEET_FIELD,
"media.fields": MEDIA_FIELD,
"place.fields": PLACE_FIELD,
"poll.fields": POLL_FIELD,
"max_results": 100,
}
res = self.http_client.request("GET", "2", f"/tweets/{self.id}/quote_tweets", params=params)
if not res:
return []
return TweetPagination(
res,
endpoint_request=f"/tweets/{self.id}/quote_tweets",
http_client=self.http_client,
params=params,
)
|
### Welcome to SliceGAN ###
####### Steve Kench #######
'''
Use this file to define your settings for a training run, or
to generate a synthetic image using a trained generator.
'''
from slicegan import model, networks, util
import argparse
# Define project name
Project_name = 'NMC_exemplar_final'
# Specify project folder.
Project_dir = 'xiaowogua'
# Run with False to show an image during or after training
parser = argparse.ArgumentParser()
parser.add_argument('training', type=int)
args = parser.parse_args()
Training = args.training
Project_path = util.mkdr(Project_name, Project_dir, Training)
## Data Processing
# Define image type (colour, grayscale, three-phase or two-phase.
# n-phase materials must be segmented)
image_type = 'twophase'
# define data type (for colour/grayscale images, must be 'colour' / '
# greyscale. nphase can be, 'tif', 'png', 'jpg','array')
data_type = 'tif'
# Path to your data. One string for isotrpic, 3 for anisotropic
data_path = ['Examples/NMC.tif']
## Network Architectures
# Training image size, no. channels and scale factor vs raw data
img_size, img_channels, scale_factor = 64, 2, 1
# z vector depth
z_channels = 16
# Layers in G and D
lays = 6
# kernals for each layer
dk, gk = [4]*lays, [4]*lays
# strides
ds, gs = [2]*lays, [2]*lays
# no. filters
df, gf = [img_channels,64,128,256,512,1], [z_channels,512,256,128,64,img_channels]
# paddings
dp, gp = [1,1,1,1,0],[2,2,2,2,3]
## Create Networks
netD, netG = networks.slicegan_nets(Project_path, Training, image_type, dk, ds, df,dp, gk ,gs, gf, gp)
# Train
if Training:
model.train(Project_path, image_type, data_type, data_path, netD, netG, img_channels, img_size, z_channels, scale_factor)
else:
img, raw, netG = util.test_img(Project_path, image_type, netG(), z_channels, lf=6, periodic=[0, 1, 1])
|
# Copyright 2019 Eli Lilly and Company
#
# 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 glob
import json
import os
from pathlib import Path
import re
import tempfile
from typing import Optional, Sequence, Union, cast
import subby
from pytest_wdl.executors import (
ExecutionFailedError,
JavaExecutor,
get_target_name,
read_write_inputs,
)
from pytest_wdl.utils import LOG, ensure_path
ENV_CROMWELL_JAR = "CROMWELL_JAR"
ENV_CROMWELL_CONFIG = "CROMWELL_CONFIG"
ENV_CROMWELL_ARGS = "CROMWELL_ARGS"
UNSAFE_RE = re.compile(r"[^\w.-]")
class Failures:
def __init__(
self,
num_failed: int,
failed_task: str,
failed_task_exit_status: Optional[str] = None,
failed_task_stdout: Optional[Union[Path, str]] = None,
failed_task_stderr: Optional[Union[Path, str]] = None
):
self.num_failed = num_failed
self.failed_task = failed_task
self.failed_task_exit_status = failed_task_exit_status
self._failed_task_stdout_path = None
self._failed_task_stdout = None
self._failed_task_stderr_path = None
self._failed_task_stderr = None
if isinstance(failed_task_stdout, Path):
self._failed_task_stdout_path = cast(Path, failed_task_stdout)
else:
self._failed_task_stdout = cast(str, failed_task_stdout)
if isinstance(failed_task_stderr, Path):
self._failed_task_stderr_path = cast(Path, failed_task_stderr)
else:
self._failed_task_stderr = cast(str, failed_task_stderr)
@property
def failed_task_stdout(self):
if self._failed_task_stdout is None and self._failed_task_stderr_path:
self._failed_task_stdout = Failures._read_task_std(
self._failed_task_stdout_path
)
return self._failed_task_stdout
@property
def failed_task_stderr(self):
if self._failed_task_stderr is None and self._failed_task_stderr_path:
self._failed_task_stderr = Failures._read_task_std(
self._failed_task_stderr_path
)
return self._failed_task_stderr
@staticmethod
def _read_task_std(path: Path) -> Optional[str]:
if path:
if not path.exists():
path = path.with_suffix(".background")
if path.exists():
with open(path, "rt") as inp:
return inp.read()
class CromwellExecutor(JavaExecutor):
"""
Manages the running of WDL workflows using Cromwell.
Args:
import_dirs: Relative or absolute paths to directories containing WDL
scripts that should be available as imports.
java_bin: Path to the java executable.
java_args: Default Java arguments to use; can be overidden by passing
`java_args=...` to `run_workflow`.
cromwell_jar_file: Path to the Cromwell JAR file.
cromwell_args: Default Cromwell arguments to use; can be overridden by
passing `cromwell_args=...` to `run_workflow`.
"""
def __init__(
self,
import_dirs: Optional[Sequence[Path]] = None,
java_bin: Optional[Union[str, Path]] = None,
java_args: Optional[str] = None,
cromwell_jar_file: Optional[Union[str, Path]] = None,
cromwell_config_file: Optional[Union[str, Path]] = None,
cromwell_args: Optional[str] = None
):
super().__init__(java_bin, java_args)
self._import_dirs = import_dirs
self._cromwell_jar_file = self.resolve_jar_file(
"cromwell*.jar", cromwell_jar_file, ENV_CROMWELL_JAR
)
if not cromwell_config_file:
config_file = os.environ.get(ENV_CROMWELL_CONFIG)
if config_file:
cromwell_config_file = ensure_path(config_file)
if cromwell_config_file:
self._cromwell_config_file = ensure_path(
cromwell_config_file, is_file=True, exists=True
)
else:
self._cromwell_config_file = None
if not self.java_args and self._cromwell_config_file:
self.java_args = f"-Dconfig.file={self._cromwell_config_file}"
self._cromwell_args = cromwell_args or os.environ.get(ENV_CROMWELL_ARGS)
def run_workflow(
self,
wdl_path: Path,
inputs: Optional[dict] = None,
expected: Optional[dict] = None,
**kwargs
) -> dict:
"""
Run a WDL workflow on given inputs, and check that the output matches
given expected values.
Args:
wdl_path: The WDL script to execute.
inputs: Object that will be serialized to JSON and provided to Cromwell
as the workflow inputs.
expected: Dict mapping output parameter names to expected values.
kwargs: Additional keyword arguments, mostly for debugging:
* workflow_name: The name of the workflow in the WDL script. If None,
the name of the WDL script is used (without the .wdl extension).
* inputs_file: Path to the Cromwell inputs file to use. Inputs are
written to this file only if it doesn't exist.
* imports_file: Path to the WDL imports file to use. Imports are
written to this file only if it doesn't exist.
* java_args: Additional arguments to pass to Java runtime.
* cromwell_args: Additional arguments to pass to `cromwell run`.
Returns:
Dict of outputs.
Raises:
ExecutionFailedError: if there was an error executing Cromwell
AssertionError: if the actual outputs don't match the expected outputs
"""
target, is_task = get_target_name(
wdl_path=wdl_path, import_dirs=self._import_dirs, **kwargs
)
if is_task:
raise ValueError(
"Cromwell cannot execute tasks independently of a workflow"
)
inputs_dict, inputs_file = read_write_inputs(
inputs_dict=inputs, namespace=target
)
imports_file = self._get_workflow_imports(kwargs.get("imports_file"))
inputs_arg = f"-i {inputs_file}" if inputs_file else ""
imports_zip_arg = f"-p {imports_file}" if imports_file else ""
java_args = kwargs.get("java_args", self.java_args) or ""
cromwell_args = kwargs.get("cromwell_args", self._cromwell_args) or ""
metadata_file = Path.cwd() / "metadata.json"
cmd = (
f"{self.java_bin} {java_args} -jar {self._cromwell_jar_file} run "
f"-m {metadata_file} {cromwell_args} {inputs_arg} {imports_zip_arg} "
f"{wdl_path}"
)
LOG.info(
f"Executing cromwell command '{cmd}' with inputs "
f"{json.dumps(inputs_dict, default=str)}"
)
exe = subby.run(cmd, raise_on_error=False)
metadata = None
if metadata_file.exists():
with open(metadata_file, "rt") as inp:
metadata = json.load(inp)
if exe.ok:
if metadata:
assert metadata["status"] == "Succeeded"
outputs = metadata["outputs"]
else:
LOG.warning(
f"Cromwell command completed successfully but did not generate "
f"a metadata file at {metadata_file}"
)
outputs = self._get_cromwell_outputs(exe.output)
else:
error_kwargs = {
"executor": "cromwell",
"target": target,
"status": "Failed",
"inputs": inputs_dict,
"executor_stdout": exe.output,
"executor_stderr": exe.error,
}
if metadata:
failures = self._get_failures(metadata)
if failures:
error_kwargs.update({
"failed_task": failures.failed_task,
"failed_task_exit_status": failures.failed_task_exit_status,
"failed_task_stdout": failures.failed_task_stdout,
"failed_task_stderr": failures.failed_task_stderr
})
if failures.num_failed > 1:
error_kwargs["msg"] = \
f"cromwell failed on {failures.num_failed} instances of " \
f"{failures.failed_task} of {target}; only " \
f"showing output from the first failed task"
else:
error_kwargs["msg"] = f"cromwell failed on workflow {target}"
else:
error_kwargs["msg"] = \
f"Cromwell command failed but did not generate a metadata " \
f"file at {metadata_file}"
raise ExecutionFailedError(**error_kwargs)
if expected:
self._validate_outputs(outputs, expected, target)
return outputs
def _get_workflow_imports(self, imports_file: Optional[Path] = None) -> Path:
"""
Creates a ZIP file with all WDL files to be imported.
Args:
imports_file: Text file naming import directories/files - one per line.
Returns:
Path to the ZIP file.
"""
write_imports = bool(self._import_dirs)
imports_path = None
if imports_file:
imports_path = ensure_path(imports_file)
if imports_path.exists():
write_imports = False
if write_imports and self._import_dirs:
imports = [
wdl
for path in self._import_dirs
for wdl in glob.glob(str(path / "*.wdl"))
]
if imports:
if imports_path:
ensure_path(imports_path, is_file=True, create=True)
else:
imports_path = Path(tempfile.mkstemp(suffix=".zip")[1])
imports_str = " ".join(imports)
LOG.info(f"Writing imports {imports_str} to zip file {imports_path}")
exe = subby.run(
f"zip -j - {imports_str}",
mode=bytes,
stdout=imports_path,
raise_on_error=False
)
if not exe.ok:
raise Exception(
f"Error creating imports zip file; stdout={exe.output}; "
f"stderr={exe.error}"
)
return imports_path
@classmethod
def _get_cromwell_outputs(cls, output) -> dict:
lines = output.splitlines(keepends=False)
if len(lines) < 2:
raise Exception(f"Invalid Cromwell output: {output}")
if lines[1].startswith("Usage"):
# If the cromwell command is not valid, usage is printed and the
# return code is 0 so it does not cause an exception above - we
# have to catch it here.
raise Exception("Invalid Cromwell command")
start = None
for i, line in enumerate(lines):
if line == "{" and lines[i+1].lstrip().startswith('"outputs":'):
start = i
elif line == "}" and start is not None:
end = i
break
else:
raise AssertionError("No outputs JSON found in Cromwell stdout")
return json.loads("\n".join(lines[start:(end + 1)]))["outputs"]
@classmethod
def _get_failures(cls, metadata: dict) -> Optional[Failures]:
for call_name, call_metadatas in metadata["calls"].items():
failed = list(filter(
lambda md: md["executionStatus"] == "Failed", call_metadatas
))
if failed:
failed_call = failed[0]
if "subWorkflowMetadata" in failed_call:
return cls._get_failures(
failed_call["subWorkflowMetadata"]
)
else:
if "returnCode" in failed_call:
rc = failed_call["returnCode"]
else:
rc = "Unknown"
stdout = stderr = None
if "stdout" in failed_call:
stdout = Path(failed_call["stdout"])
stderr = Path(failed_call["stderr"])
elif "failures" in failed_call:
failure = failed_call["failures"][0]
stderr = failure["message"]
if "causedBy" in failure:
stderr = "\n ".join(
[stderr] + [cb["message"] for cb in failure["causedBy"]]
)
return Failures(len(failed), call_name, rc, stdout, stderr)
|
# this file should generally become
# less useful as you scroll down.
# except for the bottom one :P <3
""" server settings """
# the domain you'd like gulag to be hosted on.
domain = 'cmyui.xyz' # cmyui.xyz
# the address which the server runs on, unix or inet4.
server_addr = '/tmp/gulag.sock' # /tmp/gulag.sock,
# ('127.0.0.1', 1234)
# your mysql authentication info.
mysql = {
'db': 'cmyui',
'host': 'localhost',
'password': 'lol123',
'user': 'cmyui',
'maxsize': 16
}
# your osu!api key, required for beatmap info.
osu_api_key = ''
# url of the mirror to use, for beatmap downloads.
mirror = 'https://api.chimu.moe/v1' # https://api.chimu.moe/v1
# in-game bot command prefix.
command_prefix = '!'
# the max amount of concurrent
# connections gulag will hold.
max_conns = 16 # likely ~8-16, depending on playercount & api usage
# the console gets a whole lot louder.
# devs can also toggle ingame w/ !debug.
debug = False
# the menu icon displayed on
# the main menu of osu! in-game.
menu_icon = (
'https://akatsuki.pw/static/logos/logo_ingame.png', # image url
'https://akatsuki.pw' # onclick url
)
# seasonal backgrounds to be displayed ingame.
seasonal_bgs = ('https://akatsuki.pw/static/flower.png',)
# max amount of multiplayer matches
# that can be created simultaneously
max_multi_matches = 64
# high ceiling values for autoban as a very simple form
# of "anticheat", simply ban a user if they are not
# whitelisted, and submit a score of too high caliber.
# Values below are in form (non_fl, fl), as fl has custom
# vals as it finds quite a few additional cheaters on the side.
autoban_pp = (
(700, 600), # vn!std
(9999, 9999), # vn!taiko
(9999, 9999), # vn!catch
(9999, 9999), # vn!mania
(1200, 800), # rx!std
(9999, 9999), # rx!taiko
(9999, 9999), # rx!catch
(9999, 9999) # ap!std
)
# hardcoded names & passwords users will not be able to use.
# TODO: retrieve the names of the top ~100 (configurable)?
# TODO: add more defaults; servers deserve better than this lol..
disallowed_names = {
'cookiezi', 'rrtyui',
'hvick225', 'qsc20010'
}
disallowed_passwords = {
'password', 'minilamp'
}
# gulag provides connectivity to
# discord via a few simple webhooks.
# simply add urls to start receiving.
webhooks = {
# general logging information
'audit-log': '',
''' (currently unused)
# notifications of sketchy plays
# & unusual activity auto-detected;
# described in more detail below.
'surveillance': '',
'''
# XXX: not a webhook, but the thumbnail used in them.
'thumbnail': 'https://akatsuki.pw/static/logos/logo.png'
}
# https://datadoghq.com
# support (stats tracking)
datadog = {
'api_key': '',
'app_key': ''
}
# the pp values which should be cached & displayed when
# a user requests the general pp values for a beatmap.
pp_cached_accs = (90, 95, 98, 99, 100) # std & taiko
pp_cached_scores = (8e5, 8.5e5, 9e5, 9.5e5, 10e5) # mania
# whether osu! client urls such as https://osu.your.domain/beatmaps/123
# should be redirected to osu.ppy.sh (https://osu.ppy.sh/beatmaps/123).
redirect_osu_urls = False
# the max duration to cache osu-checkupdates requests for.
# NOTE: this is only required for switchers and will be removed.
updates_cache_timeout = 3600 # ~3600
# the level of gzip compression to use for different tasks.
# when we want to quickly compress something and send it to
# the client immediately, we'd want to focus on optimizing
# both ends (server & client) for overall speed improvement.
# when we are sent data from the client to store long-term and
# serve in the distant future, we want to focus on size &
# decompression speed on the client-side. remember that higher
# levels will result in diminishing returns; more info below.
# https://www.rootusers.com/gzip-vs-bzip2-vs-xz-performance-comparison/
gzip = {'web': 4, 'disk': 9}
# allow for use of advanced (and potentially dangerous)
# features. i recommend checking where this config value
# is used throughout the code before enabling it.. :P
advanced = False
# additional info: https://pastebin.com/u4u14bAb
automatically_report_problems = False
|
def test_socfaker_pcap(socfaker_fixture):
assert socfaker_fixture.pcap()
|
#!/usr/bin/python3
import numpy as np
import numpy.matlib as mat
import scipy as sci
import muan.control.controls
from muan.control.state_space_gains import *
"""
A state-space plant class with support for process and measurement noise
"""
__author__ = 'Kyle Stachowicz (kylestach99@gmail.com)'
class StateSpacePlant(object):
def __init__(self, gains, x_initial = None):
assert (isinstance(gains, list) and isinstance(gains[0], StateSpaceGains)) \
or isinstance(gains, StateSpaceGains), \
"gains must be a StateSpaceGains object or a list of StateSpaceGains objects"
if not isinstance(gains, list):
gains = [gains]
self.gains = gains
self.current_gains_idx = 0
if x_initial is None:
x_initial = mat.zeros((A.shape[0], 1))
self.x = x_initial
gains = self.get_current_gains()
assert self.x.shape[0] == gains.A.shape[0] and self.x.shape[1] == 1, "x0 must be a vector compatible with A"
self.u = mat.zeros((gains.B.shape[1], 1))
self.y = gains.C * self.x + gains.D * self.u
def set_gains(self, gains_idx):
assert gains_idx < len(self.gains), "Gains id must be in range."
self.current_gains_idx = gains_idx
def get_current_gains(self):
return self.gains[self.current_gains_idx]
def update(self, u):
gains = self.get_current_gains()
# Calculate noise
process_noise = gains.Q * np.random.randn(gains.A.shape[0], 1)
measurement_noise = gains.R * np.random.randn(gains.C.shape[0], 1)
self.u = u
self.x = gains.A * self.x + gains.B * self.u + process_noise
self.y = gains.C * self.x + gains.D * self.u + measurement_noise
return self.y
|
###########################
#
# #534 Weak Queens - Project Euler
# https://projecteuler.net/problem=534
#
# Code by Kevin Marciniak
#
###########################
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
from itertools import izip
def check(ls): return all(int(p) <= int(n) for p,n in izip(ls, ls[1:]))
def fv(x): return next(i for i,j in enumerate(x) if x[i]>=x[i+1])
with open('B-large.in','r') as f: lines = f.read().splitlines()
cn = 1
for x in lines[1:]:
if check(x): print 'Case #{}: {}'.format(cn,x)
else: print 'Case #{}: {}'.format(cn,int(x)-(int(x[fv(x)+1:])+1))
cn += 1
|
#!/usr/bin/env python
# Derived from http://sundararajana.blogspot.com/2007/05/motion-detection-using-opencv.html
import cv
class Target:
def __init__(self):
self.capture = cv.CaptureFromCAM(0)
cv.NamedWindow("Target", 1)
def run(self):
# Capture first frame to get size
frame = cv.QueryFrame(self.capture)
frame_size = cv.GetSize(frame)
grey_image = cv.CreateImage(cv.GetSize(frame), cv.IPL_DEPTH_8U, 1)
moving_average = cv.CreateImage(cv.GetSize(frame), cv.IPL_DEPTH_32F, 3)
difference = None
while True:
# Capture frame from webcam
color_image = cv.QueryFrame(self.capture)
# Smooth to get rid of false positives
cv.Smooth(color_image, color_image, cv.CV_GAUSSIAN, 3, 0)
if not difference:
# Initialize
difference = cv.CloneImage(color_image)
temp = cv.CloneImage(color_image)
cv.ConvertScale(color_image, moving_average, 1.0, 0.0)
else:
cv.RunningAvg(color_image, moving_average, 0.020, None)
# Convert the scale of the moving average.
cv.ConvertScale(moving_average, temp, 1.0, 0.0)
# Minus the current frame from the moving average.
cv.AbsDiff(color_image, temp, difference)
# Convert the image to grayscale.
cv.CvtColor(difference, grey_image, cv.CV_RGB2GRAY)
# Convert the image to black and white.
cv.Threshold(grey_image, grey_image, 70, 255, cv.CV_THRESH_BINARY)
# Dilate and erode to get object blobs
cv.Dilate(grey_image, grey_image, None, 18)
cv.Erode(grey_image, grey_image, None, 10)
# Calculate movements
storage = cv.CreateMemStorage(0)
contour = cv.FindContours(grey_image, storage, cv.CV_RETR_CCOMP, cv.CV_CHAIN_APPROX_SIMPLE)
points = []
while contour:
# Draw rectangles
bound_rect = cv.BoundingRect(list(contour))
contour = contour.h_next()
pt1 = (bound_rect[0], bound_rect[1])
pt2 = (bound_rect[0] + bound_rect[2], bound_rect[1] + bound_rect[3])
points.append(pt1)
points.append(pt2)
cv.Rectangle(color_image, pt1, pt2, cv.CV_RGB(255,0,0), 1)
num_points = len(points)
if num_points:
# Draw bullseye in midpoint of all movements
x = y = 0
for point in points:
x += point[0]
y += point[1]
x /= num_points
y /= num_points
center_point = (x, y)
cv.Circle(color_image, center_point, 40, cv.CV_RGB(255, 255, 255), 1)
cv.Circle(color_image, center_point, 30, cv.CV_RGB(255, 100, 0), 1)
cv.Circle(color_image, center_point, 20, cv.CV_RGB(255, 255, 255), 1)
cv.Circle(color_image, center_point, 10, cv.CV_RGB(255, 100, 0), 5)
# Display frame to user
cv.ShowImage("Target", color_image)
# Listen for ESC or ENTER key
c = cv.WaitKey(7) % 0x100
if c == 27 or c == 10:
break
if __name__=="__main__":
t = Target()
t.run()
|
import torch
import torchvision as tv
import torch.backends.cudnn as cudnn
import torch.distributed as dist
from torch.nn.parallel import DistributedDataParallel as ddp
import os
import time
import random
import argparse
import numpy as np
random.seed(0)
np.random.seed(0)
torch.manual_seed(0)
if torch.cuda.is_available():
torch.cuda.manual_seed(0)
cudnn.benchmark = True
def main(args):
# dist init
torch.cuda.set_device(args.local_rank)
torch.distributed.init_process_group(backend='nccl', init_method='env://')
print(torch.cuda.device_count(), args.local_rank)
# data
train_transform = tv.transforms.Compose([])
if args.data_augmentation:
train_transform.transforms.append(tv.transforms.RandomCrop(32, padding=4))
train_transform.transforms.append(tv.transforms.RandomHorizontalFlip())
train_transform.transforms.append(tv.transforms.ToTensor())
normalize = tv.transforms.Normalize(mean=[x / 255.0 for x in [125.3, 123.0, 113.9]],
std=[x / 255.0 for x in [63.0, 62.1, 66.7]])
train_transform.transforms.append(normalize)
test_transform = tv.transforms.Compose([
tv.transforms.ToTensor(),
normalize])
train_dataset = tv.datasets.CIFAR10(root='data/',
train=True,
transform=train_transform,
download=True)
test_dataset = tv.datasets.CIFAR10(root='data/',
train=False,
transform=test_transform,
download=True)
sampler = torch.utils.data.distributed.DistributedSampler(train_dataset)
train_loader = torch.utils.data.DataLoader(dataset=train_dataset,
batch_size=args.bs,
shuffle=False,
pin_memory=True,
num_workers=4,
sampler=sampler)
test_loader = torch.utils.data.DataLoader(dataset=test_dataset,
batch_size=args.bs,
shuffle=False,
pin_memory=True,
num_workers=4)
# net
net = tv.models.resnet18(num_classes=10)
net = net.cuda()
# optimizer and loss
optimizer = torch.optim.SGD(net.parameters(), lr=0.1, momentum=0.9, weight_decay=5e-4)
scheduler = torch.optim.lr_scheduler.MultiStepLR(optimizer, [50, 80], 0.1)
criterion = torch.nn.CrossEntropyLoss().cuda()
net = torch.nn.SyncBatchNorm.convert_sync_batchnorm(net)
net = ddp(net, device_ids=[args.local_rank], find_unused_parameters=True)
# train
for i_epoch in range(100):
net.train()
time_s = time.time()
train_loader.sampler.set_epoch(i_epoch)
for i_iter, data in enumerate(train_loader):
img, label = data
img, label = img.cuda(), label.cuda()
optimizer.zero_grad()
feat = net(img)
loss = criterion(feat, label)
loss.backward()
optimizer.step()
time_e = time.time()
if args.local_rank == 1:
print('Epoch:{:3}/100 || Iter: {:4}/{} || '
'Loss: {:2.4f} '
'ETA: {:.2f}min'.format(
i_epoch + 1, i_iter + 1, len(train_loader),
loss.item(),
(time_e - time_s) * (100 - i_epoch) * len(train_loader) / (i_iter + 1) / 60))
scheduler.step()
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--bs', type=int, default=128)
parser.add_argument('--data_augmentation', type=bool, default=True)
parser.add_argument("--local_rank", type=int, default=0, help='master rank')
args = parser.parse_args()
main(args)
|
import unittest
from geom_tools.adjacency_tools import (
vertices_adjacency_from_polygon_vertex_indices,
max_vertex_ind_in_list,
expand_adjacency_table,
)
class TestAdjacencyTools(unittest.TestCase):
def test_vertices_adjacency_from_polygon_vertex_indices01(self):
indices = [
[0, 1, 2]
]
res = vertices_adjacency_from_polygon_vertex_indices(indices)
ans = [
[1, 2],
[0, 2],
[0, 1],
]
self.assertEqual(ans, res)
def test_vertices_adjacency_from_polygon_vertex_indices02(self):
indices = [
[1, 2, 3]
]
res = vertices_adjacency_from_polygon_vertex_indices(indices)
ans = [
[],
[2, 3],
[1, 3],
[1, 2]
]
self.assertEqual(ans, res)
def test_vertices_adjacency_from_polygon_vertex_indices03(self):
indices = [
[3, 1, 2]
]
res = vertices_adjacency_from_polygon_vertex_indices(indices, 5)
ans = [
[],
[2, 3],
[1, 3],
[1, 2],
[],
]
self.assertEqual(ans, res)
def test_vertices_adjacency_from_polygon_vertex_indices04(self):
indices = [
[1, 2, 3],
[0, 2, 1]
]
res = vertices_adjacency_from_polygon_vertex_indices(indices)
ans = [
[1, 2],
[0, 2, 3],
[0, 1, 3],
[1, 2],
]
self.assertEqual(ans, res)
def test_vertices_adjacency_from_polygon_vertex_indices05(self):
indices = [
[5, 4],
[1, 2, 3],
[0, 2, 1]
]
res = vertices_adjacency_from_polygon_vertex_indices(indices)
ans = [
[1, 2],
[0, 2, 3],
[0, 1, 3],
[1, 2],
[5],
[4]
]
self.assertEqual(ans, res)
def test_vertices_adjacency_from_polygon_vertex_indices06(self):
indices = [
[4, 2, 0, 1, 3]
]
res = vertices_adjacency_from_polygon_vertex_indices(indices)
ans = [
[1, 2], # 0
[0, 3], # 1
[0, 4], # 2
[1, 4], # 3
[2, 3], # 4
]
self.assertEqual(ans, res)
def test_vertices_adjacency_from_polygon_vertex_indices07(self):
indices = [
[4, 2, 0, 1, 3],
[7, 8, 6]
]
res = vertices_adjacency_from_polygon_vertex_indices(indices)
ans = [
[1, 2], # 0
[0, 3], # 1
[0, 4], # 2
[1, 4], # 3
[2, 3], # 4
[],
[7, 8],
[6, 8],
[6, 7]
]
self.assertEqual(ans, res)
def test_vertices_adjacency_from_polygon_vertex_indices08(self):
indices = [
[0, 2, 3, 1],
[2, 3, 6],
[6, 3, 5],
[2, 6, 4],
[6, 5, 4],
[7, 9, 8, 1],
[0, 10, 2],
]
res = vertices_adjacency_from_polygon_vertex_indices(indices)
ans = [
[1, 2, 10],
[0, 3, 7, 8],
[0, 3, 4, 6, 10],
[1, 2, 5, 6],
[2, 5, 6],
[3, 4, 6],
[2, 3, 4, 5],
[1, 9],
[1, 9],
[7, 8],
[0, 2],
]
self.assertEqual(ans, res)
def test_max_vertex_ind_in_list01(self):
indices = [[1]]
self.assertEqual(1, max_vertex_ind_in_list(indices))
def test_max_vertex_ind_in_list02(self):
indices = [[1, 0, 3]]
self.assertEqual(3, max_vertex_ind_in_list(indices))
def test_max_vertex_ind_in_list03(self):
indices = [[6, 5], [1, 0, 3]]
self.assertEqual(6, max_vertex_ind_in_list(indices))
def test_max_vertex_ind_in_list04(self):
indices = [[1, 2, 3, 4], [6, 50], [1, 0, 3]]
self.assertEqual(50, max_vertex_ind_in_list(indices))
def test_expand_adjacency_table01(self):
adj_table = [
]
ans = [
]
res = expand_adjacency_table(adj_table)
self.assertEqual(ans, res)
def test_expand_adjacency_table02(self):
adj_table = [
[1],
[0],
]
ans = [
[1],
[0],
]
res = expand_adjacency_table(adj_table)
self.assertEqual(ans, res)
def test_expand_adjacency_table03(self):
adj_table = [
[1],
[0, 2],
[1],
]
ans = [
[1, 2],
[0, 2],
[0, 1]
]
res = expand_adjacency_table(adj_table)
self.assertEqual(ans, res)
def test_expand_adjacency_table04(self):
adj_table = [
[1],
[0],
[3], # 2
[2, 4], # 3
[3, 5], # 4
[4] # 5
]
ans = [
[1],
[0],
[3, 4], # 2
[2, 4, 5], # 3
[2, 3, 5], # 4
[3, 4] # 5
]
res = expand_adjacency_table(adj_table)
self.assertEqual(ans, res)
if __name__ == '__main__':
unittest.main()
|
# #####################################################################################################################
# Copyright 2021 Amazon.com, Inc. or its affiliates. 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. A copy of the License is located at #
# #
# http://www.apache.org/licenses/LICENSE-2.0 #
# #
# or in the 'license' file accompanying this file. This file is distributed on an 'AS IS' BASIS, WITHOUT WARRANTIES #
# OR CONDITIONS OF ANY KIND, express or implied. See the License for the specific language governing permissions #
# and limitations under the License. #
# #####################################################################################################################
from aws_cdk import (
aws_lambda as lambda_,
aws_s3 as s3,
aws_apigateway as apigw,
core,
)
from aws_solutions_constructs.aws_lambda_sagemakerendpoint import LambdaToSagemakerEndpoint
from aws_solutions_constructs import aws_apigateway_lambda
from lib.blueprints.byom.pipeline_definitions.sagemaker_role import create_sagemaker_role
from lib.blueprints.byom.pipeline_definitions.sagemaker_model import create_sagemaker_model
from lib.blueprints.byom.pipeline_definitions.sagemaker_endpoint_config import create_sagemaker_endpoint_config
from lib.blueprints.byom.pipeline_definitions.sagemaker_endpoint import create_sagemaker_endpoint
from lib.blueprints.byom.pipeline_definitions.helpers import suppress_lambda_policies
from lib.blueprints.byom.pipeline_definitions.templates_parameters import (
create_blueprint_bucket_name_parameter,
create_assets_bucket_name_parameter,
create_algorithm_image_uri_parameter,
create_custom_algorithms_ecr_repo_arn_parameter,
create_inference_instance_parameter,
create_kms_key_arn_parameter,
create_model_artifact_location_parameter,
create_model_name_parameter,
create_data_capture_location_parameter,
create_custom_algorithms_ecr_repo_arn_provided_condition,
create_kms_key_arn_provided_condition,
create_model_package_name_parameter,
create_model_registry_provided_condition,
create_model_package_group_name_parameter,
)
class BYOMRealtimePipelineStack(core.Stack):
def __init__(self, scope: core.Construct, id: str, **kwargs) -> None:
super().__init__(scope, id, **kwargs)
# Parameteres #
assets_bucket_name = create_assets_bucket_name_parameter(self)
blueprint_bucket_name = create_blueprint_bucket_name_parameter(self)
custom_algorithms_ecr_repo_arn = create_custom_algorithms_ecr_repo_arn_parameter(self)
kms_key_arn = create_kms_key_arn_parameter(self)
algorithm_image_uri = create_algorithm_image_uri_parameter(self)
model_name = create_model_name_parameter(self)
model_artifact_location = create_model_artifact_location_parameter(self)
data_capture_location = create_data_capture_location_parameter(self)
inference_instance = create_inference_instance_parameter(self)
model_package_group_name = create_model_package_group_name_parameter(self)
model_package_name = create_model_package_name_parameter(self)
# Conditions
custom_algorithms_ecr_repo_arn_provided = create_custom_algorithms_ecr_repo_arn_provided_condition(
self, custom_algorithms_ecr_repo_arn
)
kms_key_arn_provided = create_kms_key_arn_provided_condition(self, kms_key_arn)
model_registry_provided = create_model_registry_provided_condition(self, model_package_name)
# Resources #
# getting blueprint bucket object from its name - will be used later in the stack
blueprint_bucket = s3.Bucket.from_bucket_name(self, "BlueprintBucket", blueprint_bucket_name.value_as_string)
# provision api gateway and lambda for inference using solution constructs
inference_api_gateway = aws_apigateway_lambda.ApiGatewayToLambda(
self,
"BYOMInference",
lambda_function_props={
"runtime": lambda_.Runtime.PYTHON_3_8,
"handler": "main.handler",
"code": lambda_.Code.from_bucket(blueprint_bucket, "blueprints/byom/lambdas/inference.zip"),
},
api_gateway_props={
"defaultMethodOptions": {
"authorizationType": apigw.AuthorizationType.IAM,
},
"restApiName": f"{core.Aws.STACK_NAME}-inference",
"proxy": False,
},
)
# add supressions
inference_api_gateway.lambda_function.node.default_child.cfn_options.metadata = suppress_lambda_policies()
provision_resource = inference_api_gateway.api_gateway.root.add_resource("inference")
provision_resource.add_method("POST")
# create Sagemaker role
sagemaker_role = create_sagemaker_role(
self,
"MLOpsRealtimeSagemakerRole",
custom_algorithms_ecr_arn=custom_algorithms_ecr_repo_arn.value_as_string,
kms_key_arn=kms_key_arn.value_as_string,
model_package_group_name=model_package_group_name.value_as_string,
assets_bucket_name=assets_bucket_name.value_as_string,
input_bucket_name=assets_bucket_name.value_as_string,
input_s3_location=assets_bucket_name.value_as_string,
output_s3_location=data_capture_location.value_as_string,
ecr_repo_arn_provided_condition=custom_algorithms_ecr_repo_arn_provided,
kms_key_arn_provided_condition=kms_key_arn_provided,
model_registry_provided_condition=model_registry_provided,
)
# create sagemaker model
sagemaker_model = create_sagemaker_model(
self,
"MLOpsSagemakerModel",
execution_role=sagemaker_role,
model_registry_provided=model_registry_provided,
algorithm_image_uri=algorithm_image_uri.value_as_string,
assets_bucket_name=assets_bucket_name.value_as_string,
model_artifact_location=model_artifact_location.value_as_string,
model_package_name=model_package_name.value_as_string,
model_name=model_name.value_as_string,
)
# Create Sagemaker EndpointConfg
sagemaker_endpoint_config = create_sagemaker_endpoint_config(
self,
"MLOpsSagemakerEndpointConfig",
sagemaker_model.attr_model_name,
model_name.value_as_string,
inference_instance.value_as_string,
data_capture_location.value_as_string,
core.Fn.condition_if(
kms_key_arn_provided.logical_id, kms_key_arn.value_as_string, core.Aws.NO_VALUE
).to_string(),
)
# create a dependency on the model
sagemaker_endpoint_config.add_depends_on(sagemaker_model)
# create Sagemaker endpoint
sagemaker_endpoint = create_sagemaker_endpoint(
self,
"MLOpsSagemakerEndpoint",
sagemaker_endpoint_config.attr_endpoint_config_name,
model_name.value_as_string,
)
# add dependency on endpoint config
sagemaker_endpoint.add_depends_on(sagemaker_endpoint_config)
# Create Lambda - sagemakerendpoint
LambdaToSagemakerEndpoint(
self,
"LambdaSagmakerEndpoint",
existing_sagemaker_endpoint_obj=sagemaker_endpoint,
existing_lambda_obj=inference_api_gateway.lambda_function,
)
# Outputs #
core.CfnOutput(
self,
id="SageMakerModelName",
value=sagemaker_model.attr_model_name,
)
core.CfnOutput(
self,
id="SageMakerEndpointConfigName",
value=sagemaker_endpoint_config.attr_endpoint_config_name,
)
core.CfnOutput(
self,
id="SageMakerEndpointName",
value=sagemaker_endpoint.attr_endpoint_name,
)
core.CfnOutput(
self,
id="EndpointDataCaptureLocation",
value=f"https://s3.console.aws.amazon.com/s3/buckets/{data_capture_location.value_as_string}/",
description="Endpoint data capture location (to be used by Model Monitor)",
)
|
# Licensed under a 3-clause BSD style license - see LICENSE.rst
"""
PyVO is a package providing access to remote data and services of the
Virtual observatory (VO) using Python.
The pyvo module currently provides these main capabilities:
* find archives that provide particular data of a particular type and/or
relates to a particular topic
* regsearch()
* search an archive for datasets of a particular type
* imagesearch(), spectrumsearch()
* do simple searches on catalogs or databases
* conesearch(), linesearch(), tablesearch()
Submodules provide additional functions and classes for greater control over
access to these services.
This module also exposes the exception classes raised by the above functions,
of which DALAccessError is the root parent exception.
"""
# Affiliated packages may add whatever they like to this file, but
# should keep this content at the top.
# ----------------------------------------------------------------------------
from ._astropy_init import *
# ----------------------------------------------------------------------------
# For egg_info test builds to pass, put package imports here.
from . import registry
from .dal import ssa, sia, sla, scs, tap
from . import auth
from .registry import search as regsearch
from .dal import (
imagesearch, spectrumsearch, conesearch, linesearch, tablesearch,
DALAccessError, DALProtocolError, DALFormatError, DALServiceError,
DALQueryError)
|
'''
Created on Jan 6, 2014
@author: Jose Borreguero
'''
import numpy
import copy
from logger import vlog
from interpolator import Interpolator
class Channel( object ):
''' This class implements a dynamical channel defined by momentum transfer Q and energy E '''
def __init__( self ):
'''
Attributes:
signalseries: the values that the structure factor for this channel
takes for the different values of the external parameter
errorseries: associated errors for the signalseries. Mostly applicable
to experimental signalseries
interpolator: evaluates the structure factor for this channel and estimation
of error for a particular value of the external parameter
'''
self.signalseries = None
self.errorseries = None
self.interpolator = None
def SetSignalSeries(self, signalseries):
''' Initialize the signalseries '''
self.signalseries = numpy.array(copy.copy(signalseries))
def SetErrorSeries(self, errorseries):
''' Initialize the errorseries '''
self.errorseries = None
if errorseries is not None:
self.errorseries = numpy.array(copy.copy(errorseries))
@property
def range(self):
'''Minimum and maximum of the fseries'''
try:
return self.interpolator.range
except:
vlog.error("interpolator has not been initialized for this channel")
return (float('inf'),float('inf'))
def InitializeInterpolator(self, fseries, running_regr_type = 'linear', windowlength=3):
''' Initialize the interpolator for this channel
Arguments:
fseries: list of external parameter values
running_regr_type: the type of the local, running regression
Returns:
None if error found
interpolator attribute if success
'''
# Handle errors first
if self.signalseries is None:
vlog.error( 'Signal series not set!' )
return None
if len( fseries ) != len( self.signalseries ):
vlog.error( 'signal and external parameter series have different lenght!' )
return None
self.interpolator = Interpolator( fseries, self.signalseries, errorseries = self.errorseries, running_regr_type = running_regr_type, windowlength=windowlength)
return self.interpolator
def __call__(self, fvalue ):
''' Evaluates the interpolator for the fvalue mimicking a function call'''
return self.interpolator( fvalue )
|
from datetime import datetime, timedelta
from typing import Optional
import jwt
# custom defined
from app.core.config import timezone, secret_key, algorithm, access_token_expire_minutes
# 创建token，token包含exp,和用户自定义的json数据
def create_access_token(*, data: dict, expires_delta: Optional[timedelta] = None):
to_encode = data.copy()
if expires_delta:
expire = datetime.now(tz=timezone) + expires_delta
else:
expire = datetime.now(tz=timezone) + timedelta(minutes=access_token_expire_minutes)
to_encode.update({"exp": expire})
encoded_jwt = jwt.encode(to_encode, str(secret_key), algorithm=algorithm)
return encoded_jwt
|
from django.db import migrations
class Migration(migrations.Migration):
dependencies = [
('serverdb', '0004_attribute_value_constraints'),
]
operations = [
# Mark all previously defined attributes as clonable once.
migrations.RunSQL(
'UPDATE attribute '
'SET clone = true '
"WHERE type NOT IN ('reverse', 'supernet', 'domain')"
),
# Forbid attributes of relational types from beeing clonable as they
# can't be written to due to beeing drived from other attributes.
migrations.RunSQL(
'ALTER TABLE attribute '
'ADD CONSTRAINT attribute_clone_check '
" CHECK (NOT clone OR type NOT IN ("
" 'reverse', 'supernet', 'domain'))"
),
]
|
# -*- coding: utf-8 -*-
# Generated by Django 1.10.1 on 2017-06-25 17:50
from __future__ import unicode_literals
from decimal import Decimal
import django.core.validators
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
('cadastro', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Lancamento',
fields=[
('id', models.AutoField(auto_created=True,
primary_key=True, serialize=False, verbose_name='ID')),
('data_vencimento', models.DateField(blank=True, null=True)),
('data_pagamento', models.DateField(blank=True, null=True)),
('descricao', models.CharField(max_length=255)),
('valor_total', models.DecimalField(decimal_places=2, default=Decimal(
'0.00'), max_digits=13, validators=[django.core.validators.MinValueValidator(Decimal('0.00'))])),
('abatimento', models.DecimalField(decimal_places=2, default=Decimal(
'0.00'), max_digits=13, validators=[django.core.validators.MinValueValidator(Decimal('0.00'))])),
('juros', models.DecimalField(decimal_places=2, default=Decimal(
'0.00'), max_digits=13, validators=[django.core.validators.MinValueValidator(Decimal('0.00'))])),
('valor_liquido', models.DecimalField(decimal_places=2, default=Decimal(
'0.00'), max_digits=13, validators=[django.core.validators.MinValueValidator(Decimal('0.00'))])),
('movimentar_caixa', models.BooleanField(default=True)),
],
),
migrations.CreateModel(
name='MovimentoCaixa',
fields=[
('id', models.AutoField(auto_created=True,
primary_key=True, serialize=False, verbose_name='ID')),
('data_movimento', models.DateField(blank=True, null=True)),
('saldo_inicial', models.DecimalField(
decimal_places=2, default=Decimal('0.00'), max_digits=13)),
('saldo_final', models.DecimalField(
decimal_places=2, default=Decimal('0.00'), max_digits=13)),
('entradas', models.DecimalField(decimal_places=2, default=Decimal(
'0.00'), max_digits=13, validators=[django.core.validators.MinValueValidator(Decimal('0.00'))])),
('saidas', models.DecimalField(decimal_places=2, default=Decimal(
'0.00'), max_digits=13, validators=[django.core.validators.MinValueValidator(Decimal('0.00'))])),
],
),
migrations.CreateModel(
name='PlanoContasGrupo',
fields=[
('id', models.AutoField(auto_created=True,
primary_key=True, serialize=False, verbose_name='ID')),
('codigo', models.CharField(max_length=6)),
('tipo_grupo', models.CharField(choices=[
('0', 'Entrada'), ('1', 'Saída')], max_length=1)),
('descricao', models.CharField(max_length=255)),
],
),
migrations.CreateModel(
name='Entrada',
fields=[
('lancamento_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE,
parent_link=True, primary_key=True, serialize=False, to='financeiro.Lancamento')),
('status', models.CharField(choices=[
('0', 'Recebida'), ('1', 'A receber'), ('2', 'Atrasada')], default='1', max_length=1)),
('cliente', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL,
related_name='conta_cliente', to='cadastro.Cliente')),
],
bases=('financeiro.lancamento',),
),
migrations.CreateModel(
name='PlanoContasSubgrupo',
fields=[
('planocontasgrupo_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE,
parent_link=True, primary_key=True, serialize=False, to='financeiro.PlanoContasGrupo')),
('grupo', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE,
related_name='plano_subgrupo', to='financeiro.PlanoContasGrupo')),
],
bases=('financeiro.planocontasgrupo',),
),
migrations.CreateModel(
name='Saida',
fields=[
('lancamento_ptr', models.OneToOneField(auto_created=True, on_delete=django.db.models.deletion.CASCADE,
parent_link=True, primary_key=True, serialize=False, to='financeiro.Lancamento')),
('status', models.CharField(choices=[
('0', 'Paga'), ('1', 'A pagar'), ('2', 'Atrasada')], default='1', max_length=1)),
('fornecedor', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL,
related_name='conta_fornecedor', to='cadastro.Fornecedor')),
('grupo_plano', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL,
related_name='grupo_plano_pagamento', to='financeiro.PlanoContasGrupo')),
],
bases=('financeiro.lancamento',),
),
migrations.AddField(
model_name='lancamento',
name='conta_corrente',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL,
related_name='conta_corrente_conta', to='cadastro.Banco'),
),
migrations.AddField(
model_name='lancamento',
name='movimento_caixa',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL,
related_name='movimento_caixa_lancamento', to='financeiro.MovimentoCaixa'),
),
migrations.AddField(
model_name='entrada',
name='grupo_plano',
field=models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.SET_NULL,
related_name='grupo_plano_recebimento', to='financeiro.PlanoContasGrupo'),
),
]
|
result = "Some scalar, less then 255 bytes size"
|
# some general imports
from time import perf_counter
import datetime
import numpy as np
from scipy.optimize import fsolve
from scipy.linalg import norm
import matplotlib.pyplot as plt
import matplotlib.dates as mdates # for plotting dates
# loads the data from the csv file
# the data is stored in data, which will be
# a numpy array - the first column is the number of recovered individuals
# - the second column is the number of infected individuals
# the data starts on '2020/03/05' (March 5th) and is daily.
data = []
with open("ONdata.csv", "r") as f:
f.readline()
# print(l.split(',')) # skip the column names from the csv
l = f.readline()
while '2020/03/05' not in l:
l = f.readline()
e = l.split(',')
data.append([float(e[5]) - float(e[12]), float(e[12])])
for l in f:
e = l.split(',')
data.append([float(e[5]) - float(e[12]), float(e[12])])
data = np.array(data)
# the 3 main parameters for the model, we'll use them as
# global variables, so you can refer to them anywhere
beta0 = 0.32545622
gamma = 0.09828734
w = 0.75895019
# simulation basic scenario (see the simulation function later)
base_ends = [28, 35, 49, 70, 94, 132]
base_beta_factors = [1, 0.57939203, 0.46448341, 0.23328388, 0.30647815, 0.19737586]
# we'll also use beta as a global variable
beta = beta0
# We are assuming no birth or death rate, so N is a constant
N = 15e6
# assumed initial conditions
E = 0 # assumed to be zero
I = 18 # initial infected, based on data
S = N - E - I # everyone else is susceptible
R = 0
x0 = np.array([S, E, I, R])
# The right hand side function for the SEIR model ODE, x'(t) = F(x(t))
def F(x):
s = -x[0]*(beta/N * x[2])
e = (beta/N * x[0]*x[2] - w*x[1])
i = (w*x[1] - gamma*x[2])
r = x[2]*gamma
return np.array([s, e, i, r])
# the three numerical methods for performing a single time step
def method_I(x, h):
s = x[0] - h*(beta/N)*x[0]*x[2]
e = x[1] + h*(beta/N)*x[0]*x[2] - w*h*x[1]
i = x[2] + w*h*x[1] - h*gamma*x[2]
r = x[3] + h*gamma*x[2]
return np.array([s, e, i, r])
def _method_II(x, previous_x, h):
s = previous_x[0] - h*(beta/N)*x[0]*x[2]
e = previous_x[1] + h*(beta/N)*x[0]*x[2] - w*h*x[1]
i = previous_x[2] + w*h*x[1] - h*gamma*x[2]
r = previous_x[3] + h*gamma*x[2]
return np.array([s, e, i, r])
def jacobian_II(x, previous_x, h):
jac1 = [h*(beta/N)*x[2], 0, h*(beta/N)*x[0], 0]
jac2 = [-h*(beta/N)*x[2], w*h, -h*(beta/N)*x[0], 0]
jac3 = [0, -w*h, h*gamma, 0]
jac4 = [0, 0, -h*gamma, 0]
return np.array([jac1, jac2, jac3, jac4])
def method_II(x, h):
func = lambda x_1, x_0, h_0: x_1 - _method_II(x_1, x_0, h_0)
jacobian = lambda x_1, x_0, h_0: jacobian_II(x_1, x_0, h_0) + np.identity(4)
return fsolve(func, x, args=(x, h), fprime=jacobian)
def _method_III(x, previous_x, h):
return (method_I(previous_x, h) + _method_II(x, previous_x, h))/2
def jacobian_III(x, previous_x, h):
return jacobian_II(x, previous_x, h)/2
def method_III(x, h):
func = lambda x_1, x_0, h_0: x_1 - _method_III(x_1, x_0, h_0)
jacobian = lambda x_1, x_0, h_0: jacobian_III(x_1, x_0, h_0) + np.identity(4)
return fsolve(func, x, args=(x, h), fprime=jacobian)
METHODS = {'I': method_I, 'II': method_II, 'III': method_III}
# take a step of length 1 using n smaller steps
# used in simulation (see below)
def step(x, n, method):
# simulate step_length time unit using n small uniform length steps
# and return the new state
for i in range(n):
x = method(x, 1/n)
return x
def ode_solver(x, start, end):
from scipy.integrate import solve_ivp as ode
fun = lambda t, z: F(z)
sol = ode(fun, [start, end], x, t_eval=range(start, end+1),
method='LSODA', rtol=1e-8, atol=1e-5)
solution = []
for y in sol.y.T[1:, :]:
solution.append(y.T)
return solution
# The main simulation code:
# The simulation starts at time 0 and goes up to time ends[-1],
# the state x(t) is returned at each time 0,1,...,ends[-1].
# Inputs:
# x = initial conditions
# n = integer number of steps of method used to advance one time step
# method = 1,2, or 3 to specify which method to use. If None,
# the builtin ODE solver is used.
# ends = list of times to break the simulate
# beta_factors = list of factors to multiply beta0 by to
# obtain beta. E.g. on the first segment of the simulation
# from time t=0 up to ends[0], beta = beta0 * beta_factors[0].
def simulation(x=x0, n=1, method=None, ends=base_ends, beta_factors=base_beta_factors):
cur_time = 0
xs = [x]
for i, end in enumerate(ends):
global beta
beta = beta0 * beta_factors[i]
if method is None:
xs.extend(ode_solver(xs[-1], cur_time, end))
cur_time = end
else:
while cur_time < end:
xs.append(step(xs[-1], n, METHODS[method]))
cur_time += 1
return np.array(xs)
# some helper code to plot simulation trajectories,
# feel free to modify as needed.
def plot_trajectories(xs=data, sty='--k', label="data"):
start_date = datetime.datetime.strptime("2020-03-05", "%Y-%m-%d")
dates = [start_date]
while len(dates) < len(xs):
dates.append(dates[-1] + datetime.timedelta(1))
# code to get matplotlib to display dates on the x-axis
ax = plt.gca()
locator = mdates.MonthLocator()
formatter = mdates.DateFormatter("%b-%d")
ax.xaxis.set_major_formatter(formatter)
ax.xaxis.set_major_locator(locator)
plt.plot(dates, xs, sty, linewidth=1, label=label)
plt.xticks(rotation=45)
# example code to plot trajectories of I and R for each method
def plot_all_methods():
plot_trajectories(data[:, 0], "--k", "Data")
plot_trajectories(data[:, 1], "--k", "")
xs = simulation()[:, 2:]
plot_trajectories(xs[:, 0], "--m", "ODE")
plot_trajectories(xs[:, 1], "--m", "")
xs = simulation(n=10, method='I')[:, 2:]
plot_trajectories(xs[:, 0], "--b", "Method I")
plot_trajectories(xs[:, 1], "--b", "")
xs = simulation(n=10, method="II")[:, 2:]
plot_trajectories(xs[:, 0], "--r", "Method II")
plot_trajectories(xs[:, 1], "--r", "")
xs = simulation(n=10, method="III")[:, 2:]
plot_trajectories(xs[:, 0], "--g", "Method III")
plot_trajectories(xs[:, 1], "--g", "")
plt.title("Ontario Covid-19 Data")
plt.ylabel("# of People")
plt.grid(True)
plt.xticks(rotation=45)
plt.legend()
plt.show()
##########
# Hypothetical experiment where mask-use decreases after june 2020.
# This only models the data until october 2020
##########
def extrapolate():
# base_ends = [28, 35, 49, 70, 94, 212]
# base_beta_factors = [1, 0.57939203, 0.46448341, 0.23328388, 0.30647815, 0.19737586]
base_ends = [28, 35, 49, 70, 94, 132, 212]
base_beta_factors = [1, 0.57939203, 0.46448341, 0.23328388, 0.30647815, 0.19737586, 0.29606379]
xs = simulation(ends=base_ends, beta_factors=base_beta_factors)[:, 2:]
plot_trajectories(xs[:, 1], "--b", "Recovered")
plot_trajectories(xs[:, 0], "--r", "Infected")
plt.title("Ontario Covid-19 Data (Hypothetical)")
plt.ylabel("# of People")
plt.grid(True)
plt.xticks(rotation=45)
plt.legend()
plt.show()
if __name__ == '__main__':
extrapolate()
|
# Copyright (c) 2022, Prasanth and contributors
# For license information, please see license.txt
import frappe
from frappe.model.document import Document
import datetime
class EmployeeDeduction(Document):
pass
@frappe.whitelist()
def add_data(doc, deduction_type=None, s_date=None, amount=None):
s_date = s_date.split('-')
month = datetime.date(1900, int(s_date[1]), 1).strftime('%b')
onetime_amt = int(amount)
recurring_amt = 0
total = onetime_amt + recurring_amt
update_doc = {}
update_doc.update({'month': month, 'recurring': recurring_amt, 'onetime': onetime_amt, 'total': total})
return update_doc
@frappe.whitelist()
def update_recurring(doc, deduction_type=None, s_date=None, e_date=None, amount=None):
s_date = s_date.split('-')
e_date = e_date.split('-')
onetime_amt = 0
recurring_amt = int(amount)/(int(e_date[1])+1 - int(s_date[1]))
total = onetime_amt + recurring_amt
update_doc = []
for i in range(int(s_date[1]), int(e_date[1])+1, 1):
rec_month = datetime.date(1900, i, 1).strftime('%b')
print(rec_month, "\n")
update_doc.append({'month': rec_month, 'recurring': recurring_amt, 'onetime': onetime_amt, 'total': total})
print(update_doc)
return update_doc
@frappe.whitelist()
def get_month(doc, month, bal):
name = frappe.db.get_value('Deduction Calculation', {'parent': doc, 'month': month}, ['name'])
total = frappe.db.get_list('Deduction Calculation', {'parent': doc }, ['total'], pluck='total')
print(doc, month ,"\n\n\n\n")
print(sum(total), bal,"\n\nTotal\n")
# frappe.db.set_value('Employee Deduction', doc , 'grand_total', sum(total)+int(bal))
if name == None:
return 0
else:
return name
|
import collections
import os
import sys
# parse result file and return as {suite: {case: {config: value} } }
def parseFile(fileName):
file = open(fileName)
suitesLines = []
suitesNames = []
totalLines = 0
res = {}
for i, line in enumerate(file.readlines()):
totalLines += 1
if(line.startswith("#")):
suitesLines.append(i + 1)
suitesNames.append(line)
suitesLines.append(totalLines)
file.seek(0)
lines = file.readlines()
for i in range(len(suitesNames)):
tpres = {}
suiteStart = suitesLines[i]
while(suiteStart < suitesLines[i + 1] - 1):
suiteStart += 2
caseName = lines[suiteStart - 1].split("|")[1].lstrip()
suiteStart += 2
tpres[caseName] = {}
while(lines[suiteStart - 1].startswith("|")):
median = int(lines[suiteStart - 1].split("|")[-2].lstrip())
configName = lines[suiteStart - 1].split("|")[1].lstrip()
suiteStart += 1
tpres[caseName][configName] = median
res[suitesNames[i]] = tpres
return res
if __name__ == '__main__':
args = sys.argv
if(len(args) < 4):
exit(1)
resOldList = [parseFile(args[i]) for i in range(1, len(args) - 2)]
resNew = parseFile(args[-2])
baseNameList = [os.path.basename(args[i])[8:] for i in range(1, len(args) - 1)]
htmlContent = """
<!DOCTYPE html>
<html>
<style type="text/css">
.tg {{border-collapse:collapse;border-spacing:0;}}
.tg td {{font-family:Arial, sans-serif;font-size:14px;padding:10px 5px;border-style:solid;border-width:1px;overflow:hidden;word-break:normal;}}
.tg th {{font-family:Arial, sans-serif;font-size:14px;font-weight:normal;padding:10px 5px;border-style:solid;border-width:1px;overflow:hidden;word-break:normal;}}
.tg .tg-y2tu {{font-weight:bold;text-decoration:underline;vertical-align:top}}
.tg .tg-baqh {{text-align:center;vertical-align:top}}
.tg .tg-lqy6 {{text-align:right;vertical-align:top}}
.tg .tg-yw4l {{vertical-align:top}}
.tg .tg-ahyg {{font-weight:bold;background-color:#fe0000;vertical-align:top}}
</style>
<head>
<title>Daily Benchmark Test Result</title>
<meta charset="utf-8">
</head>
<body>
<p>Result paths are:<br> (1){} <br> (2){}</p>
{}
</body>
</html>
"""
htmlTables = ""
cellFormat = """<td class="tg-yw4l">{}</td>\n"""
colorFormat = """<td class="tg-ahyg">Yes</td>\n"""
for suite, suiteRes in resNew.items():
suiteTable = """<table class="tg">\n"""
suiteTable += """<tr>\n<th class="tg-baqh">{}</th>\n<th class="tg-yw4l">Config</th>\n""".format(suite)
for baseName in baseNameList:
suiteTable += """<th class="tg-yw41">Result of {}/ms</th>\n""".format(baseName)
suiteTable += """<th class="tg-yw4l">Regression</th></tr>\n"""
for case, caseRes in suiteRes.items():
configNums = len(caseRes)
j = 0
odRes = collections.OrderedDict(sorted(caseRes.items()))
for config, median in odRes.items():
if(j == 0):
suiteTable += """<tr>\n<td class="tg-yw4l" rowspan="{}">{}</td>\n""".format(configNums, case)
suiteTable += """<td class="tg-yw4l">{}</td>\n""".format(config)
else:
suiteTable += """<tr>\n<td class="tg-yw4l">{}</td>\n""".format(config)
# currently we just compare with last day and present the others as history data for better judgement
for res in resOldList:
if(suite in res and case in res[suite] and config in res[suite][case]):
suiteTable += cellFormat.format(res[suite][case][config])
else:
suiteTable += cellFormat.format("N/A")
resLastday = resOldList[-1]
suiteTable += cellFormat.format(median)
if(suite in resLastday and case in resLastday[suite] and config in resLastday[suite][case]):
if(median > resLastday[suite][case][config]):
if(resLastday[suite][case][config] != 0):
per = (median - resLastday[suite][case][config]) * 1.0 / resLastday[suite][case][config]
if(per <= 0.15):
suiteTable += cellFormat.format("No")
else:
suiteTable += colorFormat
else:
suiteTable += colorFormat
else:
suiteTable += cellFormat.format("No")
else:
suiteTable += cellFormat.format("N/A")
suiteTable += "</tr>\n"
j += 1
suiteTable += "</table>\n"
htmlTables += "\n{}\n".format(suiteTable)
cmpFile = open(args[-1], mode='w')
cmpFile.write(htmlContent.format("sr530:" + os.path.abspath(args[-3]), "sr530:" + os.path.abspath(args[-2]), htmlTables))
cmpFile.close()
|
# This file is only required for Python 2.x compatibility. Python 3 does not require an __init__.py
|
import math
def f(x):
return x**3*math.exp(x)
def trapezoidal(a, b, n):
h = float(b - a) / n
s = 0
s += f(a)/2
for i in range(1, n):
s += f(a + i*h)
s += f(b)/2
return s * h
|
import unittest
from _2_add_two_numbers import add_two_numbers
class ListNode:
def __init__(self, x):
self.val = x
self.next = None
class MyTestCase(unittest.TestCase):
def test_1(self):
input_1 = ListNode(2)
input_1.next = ListNode(4)
input_1.next.next = ListNode(3)
input_2 = ListNode(5)
input_2.next = ListNode(6)
input_2.next.next = ListNode(4)
expected = ListNode(7)
expected.next = ListNode(0)
expected.next.next = ListNode(8)
actual = add_two_numbers.Solution.addTwoNumbers(input_1, input_2)
self.assertEqual(expected.val, actual.val)
self.assertEqual(expected.next.val, actual.next.val)
self.assertEqual(expected.next.next.val, actual.next.next.val)
if __name__ == '__main__':
unittest.main()
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
from flask_script import Manager, Shell, Server
from flask_script.commands import Clean, ShowUrls
from flask_migrate import MigrateCommand
from flask.ext.login import login_required, make_secure_token, get_auth_token
from ccflasktest.app import create_app
from ccflasktest.user.models import User
from ccflasktest.settings import DevConfig, ProdConfig
from ccflasktest.database import db
if os.environ.get("CCFLASKTEST_ENV") == 'prod':
app = create_app(ProdConfig)
else:
app = create_app(DevConfig)
HERE = os.path.abspath(os.path.dirname(__file__))
TEST_PATH = os.path.join(HERE, 'tests')
manager = Manager(app)
def _make_context():
"""Return context dict for a shell session so you can access
app, db, and the User model by default.
"""
return {'app': app, 'db': db, 'User': User}
@manager.command
def test():
"""Run the tests."""
import pytest
exit_code = pytest.main([TEST_PATH, '--verbose'])
return exit_code
@app.route('/token', methods=['POST'])
# @login_required
def get_token():
# this will make a secure token based on the current user's ID
# cannot get a token without being first logged in...
# maybe we want to accept username/password for every POST /token
# and then validate the user. If valid, then return token ?
# return make_secure_token(current_user.id)
return get_auth_token()
# s = Serializer(app.config['SECRET_KEY'], expires_in=600)
# return s.dumps({'id': current_user.id})
manager.add_command('server', Server())
manager.add_command('shell', Shell(make_context=_make_context))
manager.add_command('db', MigrateCommand)
manager.add_command("urls", ShowUrls())
manager.add_command("clean", Clean())
if __name__ == '__main__':
manager.run()
|
#! /usr/bin/env python
'''
Demonstrates how simple group can be used as one-to-many
relationship using a column family
'''
import util
from pycassa.columnfamily import ColumnFamily
# Load data from data/movies
def loadData():
con = util.getConnection()
cf = ColumnFamily(con, 'videos')
tagCF = ColumnFamily(con, 'tag_videos')
movies = util.readCSV('data/movies')
for movie in movies:
title = movie[0]
uploader = movie[1]
runtime = int(movie[2]) #convert to match column validator
tags = movie[3]
rowKey = title+":"+uploader
print "Inserting in videos: {}.".format(str(movie))
cf.insert(
rowKey,
{
'title':title,
'user_name':uploader,
'runtime_in_sec':runtime,
'tags_csv': tags
})
for tag in tags.split(','):
print 'adding tag: {0} for movie: {1}'.format(tag, title)
tagCF.insert(
tag.strip().lower(),
{
uploader+ "_" + rowKey: title
}
);
print 'finishished insertion.'
con.dispose()
def getByTag(tag):
con = util.getConnection()
vidCF = ColumnFamily(con, 'videos')
tagCF = ColumnFamily(con, 'tag_videos')
movies = tagCF.get(tag.strip().lower())
for key, val in movies.iteritems():
vidId = key.split('_')[1]
movieDetail = vidCF.get(vidId)
print '''
{{
user: {0},
movie: {1},
tags: {2}
}}'''.format(movieDetail['user_name'], movieDetail['title'], movieDetail['tags_csv'])
con.dispose()
if __name__ == '__main__':
getByTag('action')
|
# Copyright 2019-2021 ETH Zurich and the DaCe authors. All rights reserved.
import dace
def test_strides():
desc = dace.float64[1, 2, 3]
assert desc.strides == (6, 3, 1)
assert desc.total_size == 6
perm_strides, perm_size = desc.strides_from_layout(0, 1, 2)
assert perm_size == desc.total_size
assert perm_strides == (1, 1, 2)
desc.set_strides_from_layout(0, 2, 1)
assert desc.strides == (1, 3, 1)
assert desc.total_size == 6
def test_strides_alignment():
desc = dace.float64[2, 3, 4]
assert desc.strides == (12, 4, 1)
assert desc.total_size == 24
perm_strides, perm_size = desc.strides_from_layout(0, 1, 2)
assert perm_size == desc.total_size
assert perm_strides == (1, 2, 6)
perm_strides, perm_size = desc.strides_from_layout(1, 0, 2, alignment=4)
assert perm_size == 64
assert perm_strides == (4, 1, 16)
perm_strides, perm_size = desc.strides_from_layout(1,
0,
2,
alignment=4,
only_first_aligned=True)
assert perm_size == 32
assert perm_strides == (4, 1, 8)
if __name__ == '__main__':
test_strides()
test_strides_alignment()
|
import http.client
import socket
from base64 import b64encode
import json
from . import resources
from .resource import Resource, Empty
from .request import Request
from .response import Response
from recurly import USER_AGENT, DEFAULT_REQUEST_TIMEOUT, ApiError, NetworkError
from pydoc import locate
import urllib.parse
from datetime import datetime
from enum import Enum
import certifi
import ssl
PORT = 443
BINARY_TYPES = ["application/pdf"]
ALLOWED_OPTIONS = ["body", "params", "headers"]
API_HOSTS = {"us": "v3.recurly.com", "eu": "v3.eu.recurly.com"}
HOST = API_HOSTS["us"]
def request_converter(value):
"""Used by json serializer to cast values"""
if isinstance(value, datetime):
return value.isoformat()
else:
return value
class BaseClient:
def __init__(self, api_key, timeout=None, **options):
self.__api_key = api_key
actual_timeout = timeout if timeout is not None else DEFAULT_REQUEST_TIMEOUT
api_host = HOST
if "region" in options:
if options["region"] not in API_HOSTS:
raise TypeError(
"Invalid region type. Expected one of: %s"
% (", ".join(API_HOSTS.keys()))
)
api_host = API_HOSTS[options["region"]]
context = ssl.create_default_context(cafile=certifi.where())
self.__conn = http.client.HTTPSConnection(
api_host, PORT, timeout=actual_timeout, context=context
)
def _make_request(self, method, path, body, **options):
try:
self._validate_options(options)
basic_auth = b64encode(bytes(self.__api_key + ":", "ascii")).decode("ascii")
internal_headers = {
"User-Agent": USER_AGENT,
"Authorization": "Basic %s" % basic_auth,
"Accept": "application/vnd.recurly.%s" % self.api_version(),
"Content-Type": "application/json",
}
# override headers with custom headers in the options
headers = {**options.get("headers", {}), **internal_headers}
if body:
body = json.dumps(body, default=request_converter)
if "params" in options:
path += "?" + self._url_encode(options["params"])
self.__conn.request(method, path, body, headers=headers)
request = Request(method, path, body)
resp = Response(self.__conn.getresponse(), request)
if resp.status >= 400:
if resp.body:
raise Resource.cast_error(resp)
else:
raise ApiError(
"Unknown Error. Recurly Request Id: " + str(resp.request_id),
None,
)
if resp.body:
if resp.content_type in BINARY_TYPES:
return Resource.cast_file(resp)
else:
json_body = json.loads(resp.body.decode("utf-8"))
return Resource.cast_json(json_body, response=resp)
else:
return Resource.cast_json({}, Empty, resp)
except socket.error as e:
raise NetworkError(e)
def _validate_options(self, options):
invalid_options = list(
filter(lambda option: option not in ALLOWED_OPTIONS, options.keys())
)
if len(invalid_options) > 0:
error = "Invalid options: %s. Allowed options: %s" % (
", ".join(invalid_options),
", ".join(ALLOWED_OPTIONS),
)
raise ApiError(error, None)
def _validate_path_parameters(self, args):
"""Checks that path parameters are valid"""
# Check that parameters are valid types
if any(type(arg) not in [str, int, float] for arg in args):
raise ApiError("Invalid parameter type", None)
# Check that string parameters are not empty
if any(isinstance(arg, str) and not bool(arg.strip()) for arg in args):
raise ApiError("Parameters cannot be empty strings", None)
def _interpolate_path(self, path, *args):
"""Encodes components and interpolates path"""
self._validate_path_parameters(args)
return path % tuple(map(lambda arg: urllib.parse.quote(arg, safe=""), args))
def _url_encode(self, params):
"""Encode query params for URL. We need to customize this to conform to Recurly's API"""
r_params = {}
for k, v in params.items():
# join lists w/ a comma (CSV encoding)
if isinstance(v, list) or isinstance(v, tuple):
r_params[k] = ",".join(v)
# booleans need to be downcased
elif isinstance(v, bool):
r_params[k] = "true" if v else "false"
# datetimes should be iso8601 strings
elif isinstance(v, datetime):
r_params[k] = v.isoformat()
else:
r_params[k] = v
return urllib.parse.urlencode(r_params)
|
#!/usr/local/bin/python
"""
See LICENSE file for copyright and license details.
"""
from database.databaseaccess import DatabaseAccess
from database.mappings import *
from modules.core_module import CoreModule
from modules.statement import Statement
from modules.function import *
from modules.constant import *
from generic.modules.function import *
class CurrencyExchange(CoreModule):
"""
CurrencyExchange class.
"""
def __init__(self, config):
"""
Init
"""
self.config = config
def create_statements(self, input_fields):
"""
Creates the records needed for Table.CURRENCY_EXCHANGE.
"""
try:
dba = DatabaseAccess(self.config)
statement_currency_exchange = Statement(T_CURRENCY_EXCHANGE)
date_created = current_date()
date_modified = current_date()
records = 0
for fields in input_fields:
records = records + 1
#NOTE: we don't need to query, because we always add a new
#currency_exchange line. The same value can be used multiple
#times, so it's not possible to query if one already exists.
statement_currency_exchange.add(
records,
{
'currency_exchange_id': None,
'currency_from_id': dba.currency_id_from_currency(
fields[Input.CURRENCY_FROM]),
'currency_to_id': dba.currency_id_from_currency(
fields[Input.CURRENCY_TO]),
'exchange_rate': Decimal(fields[Input.EXCHANGE_RATE]),
'date_created': date_created,
'date_modified': date_modified
}
)
return statement_currency_exchange
except Exception as ex:
print Error.CREATE_STATEMENTS_TABLE_CURRENCY_EXCHANGE, ex
finally:
dba = None
|
# Setup
import os
import chart_studio
from dotenv import load_dotenv
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from sklearn.datasets import make_blobs
from sklearn.neighbors import LocalOutlierFactor
import plotly.express as px
import plotly.graph_objects as go
import datapane as dp
GREY = '#788995'
BLUE = '#0059ff'
GOLD = '#fdbd28'
GREEN = '#28D9AA'
RED = '#EE5149'
def sim_data():
data_1 = make_blobs(n_samples=[200], n_features=2, centers=[(0,0)],
cluster_std=0.4, random_state=12)
data_1 = pd.DataFrame(data_1[0])
data_1["outlier"] = 1
outliers = {0:[-2, 1.7, 1.4, -1.8, 2, 0], 1:[-2, -1, 1.2, -1.5, 1.4, 1.5],
"outlier":-1}
data_1 = data_1.append(pd.DataFrame(outliers))
data_1.columns = ["x","y","outlier"]
data_2 = make_blobs(n_samples=[120, 50, 30], n_features=2, centers=[(-1,-1), (0, 1), (1.5,1.3)],
cluster_std=[0.3, 0.2, 0.2], random_state=12)
data_2 = pd.DataFrame(data_2[0])
data_2["outlier"] = 1
outliers = {0:[-2, 2, 2.1, -1.8, 2.5, 0], 1:[-2, -1, 2, 2.2, 1.7, 2.3],
"outlier":-1}
data_2 = data_2.append(pd.DataFrame(outliers))
data_2.columns = ["x","y","outlier"]
return data_1, data_2
def lof_for_different_n(data_1, data_2):
X = data_1.loc[:,("x","y")].values
outclass = []
for i in range(5, 205, 5):
clf = LocalOutlierFactor(n_neighbors=i, contamination="auto")
y_pred = clf.fit_predict(X)
score = clf.negative_outlier_factor_
radius = (score.max() - score) / (score.max() - score.min())
outclass += [np.array([y_pred, [i]*len(y_pred), score, radius]).T]
id = np.arange(1,len(X)+1,1)
df_1 = pd.DataFrame(np.concatenate(outclass), columns = ("outlier_pred", "neighbors",
"lof", "radius"))
df_1["outlier_pred_n"] = np.where(df_1["outlier_pred"]==1, "Not an Outlier", "Outlier")
coords = pd.DataFrame(np.tile(X, (40,1)), columns=("x","y"))
df_interact_1 = pd.concat([coords,df_1], axis=1)
df_interact_1["uid"] = np.tile(id, 40)
df_interact_1['centers'] = "One Center"
# ------------------------------------
X = data_2.loc[:,("x","y")].values
outclass = []
for i in range(5, 205, 5):
clf = LocalOutlierFactor(n_neighbors=i, contamination="auto")
y_pred = clf.fit_predict(X)
score = clf.negative_outlier_factor_
radius = (score.max() - score) / (score.max() - score.min())
outclass += [np.array([y_pred, [i]*len(y_pred), score, radius]).T]
id = np.arange(len(X)+1,2*len(X)+1,1)
df_2 = pd.DataFrame(np.concatenate(outclass), columns = ("outlier_pred", "neighbors",
"lof", "radius"))
df_2["outlier_pred_n"] = np.where(df_1["outlier_pred"]==1, "Not an Outlier", "Outlier")
coords = pd.DataFrame(np.tile(X, (40,1)), columns=("x","y"))
df_interact_2 = pd.concat([coords,df_2], axis=1)
df_interact_2["uid"] = np.tile(id, 40)
df_interact_2['centers'] = "Two Centers"
df_viz = pd.concat([df_interact_1, df_interact_2])
return df_viz
def make_interactive_fig(df):
fig = px.scatter(df_viz, x="x", y="y",
color="outlier_pred_n",
animation_frame="neighbors",
animation_group="uid",
title="<b>Local Outlier Factor with Simulated Data</b>",
size = "radius",
size_max=40,
symbol_sequence=["circle-open-dot"],
color_discrete_sequence=[BLUE, RED],
facet_col = "centers",
labels={
"x": "X",
"y": "Y",
"outlier_pred_n": "Outlier Status",
"neighbors": "Number of Neighbors",
"radius": "radius"},
hover_data = {"radius":False,
"centers":False})
fig.for_each_annotation(lambda a: a.update(text=a.text.replace("centers=", "")))
fig["layout"].pop("updatemenus")
fig.update_traces(marker={"line":{"width":2}})
fig.update_xaxes(range=[-2.5, 2.5])
fig.update_yaxes(range=[-2.5, 3])
fig.update_layout(
title={
'font':{'size':18},
'text': "Outlier Detection with LOF<br>Depends on Number of Neighbors",
'y':0.97,
'x':0.5,
'xanchor': 'center',
'yanchor': 'top'},
margin=dict(l=50, r=50, t=50, b=10),
legend=dict(
yanchor="top",
y=0.99,
xanchor="right",
x=0.99
)
)
fig.add_annotation(x=0, y=-1.5,
text="<b>Cluster 1</b>:<br>Center: (0,0)<br>N=200<br>SD: 0.4",
showarrow=False)
fig.add_annotation(x=-0.5, y=-2.1, xref="x2",
text="<b>Cluster 1</b> :<br>Center: (-1,1.5))<br>N=120<br>SD: 0.3",
showarrow=False)
fig.add_annotation(x=-0.25, y=0.18, xref="x2",
text="<b>Cluster 2</b>:<br>Center: (0,1))<br>N=50<br>SD: 0.2",
showarrow=False)
fig.add_annotation(x=1.5, y=0.55, xref="x2",
text="<b>Cluster 3</b>:<br>Center: (1.5,1.3)<br>N=30<br>SD: 0.2",
showarrow=False)
fig.add_annotation(x=0, y=0.98, xref="paper", yref="paper",
text="Circle radii are proportional to Local Outlier Factor score",
showarrow=False, align="left", )
fig['layout']['sliders'][0]['pad']=dict(l=-50, r=0, b=0, t=20)
fig.update_layout(
autosize=False,
width=900, height=600,
font_family="Iosevka Term",
font_color="black",
title_font_family="Roboto Slab",
title_font_color="black",
legend_title_font_color="black"
)
return fig
def upload_to_datapane(fig):
report = dp.Report(dp.Plot(fig, name="neighbors", responsive=False) )
report.upload(name='lof_neighbors', open=True)
if __name__ == '__main__':
data_1, data_2 = sim_data()
df_viz = lof_for_different_n(data_1=data_1, data_2=data_2)
interactive = make_interactive_fig(df_viz)
upload_to_datapane(interactive)
|
# Databricks notebook source
# MAGIC %md # CCU002_03-D12-outcomes_dose2
# MAGIC
# MAGIC **Description** This notebook determines outcomes for the analysis.
# MAGIC
# MAGIC **Author(s)** Venexia Walker
# COMMAND ----------
# MAGIC %md ## Clear cache
# COMMAND ----------
# MAGIC %sql
# MAGIC CLEAR CACHE
# COMMAND ----------
# MAGIC %md ## Define functions
# COMMAND ----------
# Define create table function by Sam Hollings
# Source: Workspaces/dars_nic_391419_j3w9t_collab/DATA_CURATION_wrang000_functions
def create_table(table_name:str, database_name:str='dars_nic_391419_j3w9t_collab', select_sql_script:str=None) -> None:
"""Will save to table from a global_temp view of the same name as the supplied table name (if no SQL script is supplied)
Otherwise, can supply a SQL script and this will be used to make the table with the specificed name, in the specifcied database."""
spark.conf.set("spark.sql.legacy.allowCreatingManagedTableUsingNonemptyLocation","true")
if select_sql_script is None:
select_sql_script = f"SELECT * FROM global_temp.{table_name}"
spark.sql(f"""CREATE TABLE {database_name}.{table_name} AS
{select_sql_script}
""")
spark.sql(f"ALTER TABLE {database_name}.{table_name} OWNER TO {database_name}")
def drop_table(table_name:str, database_name:str='dars_nic_391419_j3w9t_collab', if_exists=True):
if if_exists:
IF_EXISTS = 'IF EXISTS'
else:
IF_EXISTS = ''
spark.sql(f"DROP TABLE {IF_EXISTS} {database_name}.{table_name}")
# COMMAND ----------
# MAGIC %md ## Specify outcomes
# COMMAND ----------
outcomes = ['myocarditis','pericarditis']
# COMMAND ----------
# MAGIC %md ## GDPPR
# COMMAND ----------
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_gdppr_" + codelist + " AS SELECT NHS_NUMBER_DEID, min(DATE) AS out_dose2_" + codelist + " FROM (SELECT data.NHS_NUMBER_DEID, data.DATE, vaccination.vaccination_dose1_date FROM dars_nic_391419_j3w9t_collab.ccu002_03_vaccination AS vaccination INNER JOIN (SELECT NHS_NUMBER_DEID, DATE FROM dars_nic_391419_j3w9t_collab.ccu002_03_gdppr_dars_nic_391419_j3w9t WHERE CODE IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' AND terminology=='SNOMED')) AS data ON vaccination.NHS_NUMBER_DEID = data.NHS_NUMBER_DEID) WHERE DATE>=vaccination_dose1_date GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
# MAGIC %md ## HES APC
# COMMAND ----------
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_first_hesapc_" + codelist + " AS SELECT NHS_NUMBER_DEID, MIN(EPISTART) AS out_dose2_" + codelist + " FROM (SELECT data.NHS_NUMBER_DEID, data.EPISTART, vaccination.vaccination_dose1_date FROM dars_nic_391419_j3w9t_collab.ccu002_03_vaccination AS vaccination INNER JOIN (SELECT NHS_NUMBER_DEID, EPISTART FROM dars_nic_391419_j3w9t_collab.ccu002_03_hes_apc_longformat WHERE CODE IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' AND TERMINOLOGY='ICD10') AND (SOURCE='DIAG_3_01' OR SOURCE='DIAG_4_01')) AS data ON vaccination.NHS_NUMBER_DEID = data.NHS_NUMBER_DEID) WHERE EPISTART>=vaccination_dose1_date GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_any_hesapc_" + codelist + " AS SELECT NHS_NUMBER_DEID, MIN(EPISTART) AS out_dose2_" + codelist + " FROM (SELECT data.NHS_NUMBER_DEID, data.EPISTART, vaccination.vaccination_dose1_date FROM dars_nic_391419_j3w9t_collab.ccu002_03_vaccination AS vaccination INNER JOIN (SELECT NHS_NUMBER_DEID, EPISTART FROM dars_nic_391419_j3w9t_collab.ccu002_03_hes_apc_longformat WHERE CODE IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' AND TERMINOLOGY='ICD10')) AS data ON vaccination.NHS_NUMBER_DEID = data.NHS_NUMBER_DEID) WHERE EPISTART>=vaccination_dose1_date GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
# MAGIC %md ## SUS
# COMMAND ----------
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_first_sus_" + codelist + " AS SELECT NHS_NUMBER_DEID, MIN(EPISODE_START_DATE) AS out_dose2_" + codelist + " FROM (SELECT data.NHS_NUMBER_DEID, data.EPISODE_START_DATE, vaccination.vaccination_dose1_date FROM dars_nic_391419_j3w9t_collab.ccu002_03_vaccination AS vaccination INNER JOIN (SELECT NHS_NUMBER_DEID, EPISODE_START_DATE FROM dars_nic_391419_j3w9t_collab.ccu002_03_sus_longformat WHERE ((CODE IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' and terminology=='ICD10')) OR (LEFT(CODE,3) IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' and terminology=='ICD10'))) AND SOURCE='PRIMARY_DIAGNOSIS_CODE') AS data ON vaccination.NHS_NUMBER_DEID = data.NHS_NUMBER_DEID) WHERE EPISODE_START_DATE>=vaccination_dose1_date GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_any_sus_" + codelist + " AS SELECT NHS_NUMBER_DEID, MIN(EPISODE_START_DATE) AS out_dose2_" + codelist + " FROM (SELECT data.NHS_NUMBER_DEID, data.EPISODE_START_DATE, vaccination.vaccination_dose1_date FROM dars_nic_391419_j3w9t_collab.ccu002_03_vaccination AS vaccination INNER JOIN (SELECT NHS_NUMBER_DEID, EPISODE_START_DATE FROM dars_nic_391419_j3w9t_collab.ccu002_03_sus_longformat WHERE ((CODE IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' and terminology=='ICD10')) OR (LEFT(CODE,3) IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' and terminology=='ICD10')))) AS data ON vaccination.NHS_NUMBER_DEID = data.NHS_NUMBER_DEID) WHERE EPISODE_START_DATE>=vaccination_dose1_date GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
# MAGIC %md ## Deaths
# COMMAND ----------
# DEATHS
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_first_deaths_" + codelist + " AS SELECT NHS_NUMBER_DEID, MIN(DATE) AS out_dose2_" + codelist + " FROM (SELECT data.NHS_NUMBER_DEID, data.DATE, vaccination.vaccination_dose1_date FROM dars_nic_391419_j3w9t_collab.ccu002_03_vaccination AS vaccination INNER JOIN (SELECT NHS_NUMBER_DEID, DATE FROM dars_nic_391419_j3w9t_collab.ccu002_03_deaths_longformat WHERE ((CODE IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' and terminology=='ICD10')) OR (LEFT(CODE,3) IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' and terminology=='ICD10'))) AND SOURCE='S_UNDERLYING_COD_ICD10') AS data ON vaccination.NHS_NUMBER_DEID = data.NHS_NUMBER_DEID) WHERE DATE>=vaccination_dose1_date GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
# DEATHS
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_any_deaths_" + codelist + " AS SELECT NHS_NUMBER_DEID, MIN(DATE) AS out_dose2_" + codelist + " FROM (SELECT data.NHS_NUMBER_DEID, data.DATE, vaccination.vaccination_dose1_date FROM dars_nic_391419_j3w9t_collab.ccu002_03_vaccination AS vaccination INNER JOIN (SELECT NHS_NUMBER_DEID, DATE FROM dars_nic_391419_j3w9t_collab.ccu002_03_deaths_longformat WHERE ((CODE IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' and terminology=='ICD10')) OR (LEFT(CODE,3) IN (SELECT code FROM dars_nic_391419_j3w9t_collab.ccu002_03_codelists WHERE name = '" + codelist + "' and terminology=='ICD10')))) AS data ON vaccination.NHS_NUMBER_DEID = data.NHS_NUMBER_DEID) WHERE DATE>=vaccination_dose1_date GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
# MAGIC %md ## Combine data sources
# COMMAND ----------
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_first_" + codelist + " AS SELECT NHS_NUMBER_DEID, min(out_dose2_" + codelist + ") AS out_dose2_first_" + codelist + " FROM (SELECT * FROM global_temp.ccu002_03_out_dose2_gdppr_" + codelist + " UNION ALL SELECT * FROM global_temp.ccu002_03_out_dose2_first_hesapc_" + codelist + " UNION ALL SELECT * FROM global_temp.ccu002_03_out_dose2_first_deaths_" + codelist + " UNION ALL SELECT * FROM global_temp.ccu002_03_out_dose2_first_sus_" + codelist + ") GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
for codelist in outcomes:
sql("CREATE OR REPLACE GLOBAL TEMP VIEW ccu002_03_out_dose2_any_" + codelist + " AS SELECT NHS_NUMBER_DEID, min(out_dose2_" + codelist + ") AS out_dose2_any_" + codelist + " FROM (SELECT * FROM global_temp.ccu002_03_out_dose2_gdppr_" + codelist + " UNION ALL SELECT * FROM global_temp.ccu002_03_out_dose2_any_hesapc_" + codelist + " UNION ALL SELECT * FROM global_temp.ccu002_03_out_dose2_any_deaths_" + codelist + " UNION ALL SELECT * FROM global_temp.ccu002_03_out_dose2_any_sus_" + codelist + ") GROUP BY NHS_NUMBER_DEID")
# COMMAND ----------
# MAGIC %md ## Save as tables
# COMMAND ----------
for codelist in outcomes:
drop_table('ccu002_03_out_dose2_first_'+codelist)
# COMMAND ----------
for codelist in outcomes:
create_table('ccu002_03_out_dose2_first_'+codelist)
# COMMAND ----------
for codelist in outcomes:
drop_table('ccu002_03_out_dose2_any_'+codelist)
# COMMAND ----------
for codelist in outcomes:
create_table('ccu002_03_out_dose2_any_'+codelist)
|
#!/usr/bin/python3
"""
# Author: Scott Chubb scott.chubb@netapp.com
# Written for Python 3.7 and above
# No warranty is offered, use at your own risk. While these scripts have been
# tested in lab situations, all use cases cannot be accounted for.
"""
import sys, time, os
import requests
from datetime import datetime
from prettytable import PrettyTable
from modules.get_aiq_inputs import get_inputs_logs as get_inputs
from modules.connect_auth_aiq import web_login, build_headers, build_connect
from modules.get_aiq_customer import parse_customer
from modules.build_api_response import build_response
from modules.parser import parse_cluster
def build_payload():
payload = ({"method": "ListClusterDetails",
"params": {},
"id": 1})
return payload
def build_events(response_dict, search_string):
"""
Build the events list
"""
gb_div = 1073741824
cap_dict_pre = {}
for key,val in response_dict.items():
cls_cap = val['clusterCapacity']
cls_name = key
used_meta_snap_space = cls_cap['usedMetadataSpaceInSnapshots']
used_meta_snap_space_gb = round((used_meta_snap_space/gb_div),2)
max_used_meta = cls_cap['maxUsedMetadataSpace']
max_used_meta_gb = round((max_used_meta/gb_div),2)
actv_space = cls_cap['activeBlockSpace']
actv_space_gb = round((actv_space/gb_div),2)
uniq_blck_used_space = cls_cap['uniqueBlocksUsedSpace']
uniq_blck_used_space_gb = round((uniq_blck_used_space/gb_div),2)
total_ops = cls_cap['totalOps']
peak_actv_sess = cls_cap['peakActiveSessions']
uniq_block = cls_cap['uniqueBlocks']
max_over_prov = cls_cap['maxOverProvisionableSpace']
max_over_prov_gb = round((max_over_prov/gb_div),2)
zero_blocks = cls_cap['zeroBlocks']
prov_space = cls_cap['provisionedSpace']
prov_space_gb = round((prov_space/gb_div),2)
max_used = cls_cap['maxUsedSpace']
max_used_gb = round((max_used/gb_div),2)
peak_iops = cls_cap['peakIOPS']
time_stamp = cls_cap['timestamp']
curr_iops = cls_cap['currentIOPS']
used_space = cls_cap['usedSpace']
used_space_gb = round((used_space/gb_div),2)
actv_sess = cls_cap['activeSessions']
non_zero_block = cls_cap['nonZeroBlocks']
max_prov = cls_cap['maxProvisionedSpace']
max_prov_gb = round((max_prov/gb_div),2)
used_meta = cls_cap['usedMetadataSpace']
used_meta_gb = round((used_meta/gb_div),2)
avg_iops = cls_cap['averageIOPS']
snap_non_zero_block = cls_cap['snapshotNonZeroBlocks']
max_iops = cls_cap['maxIOPS']
io_size = cls_cap['clusterRecentIOSize']
cap_dict_pre[cls_name] =[time_stamp, used_meta_snap_space_gb,
max_used_meta_gb, used_meta_gb,
uniq_blck_used_space_gb, uniq_block,
zero_blocks, non_zero_block,
snap_non_zero_block, max_over_prov_gb,
max_prov_gb, prov_space_gb, max_used_gb,
used_space_gb, actv_space_gb,
peak_actv_sess, io_size, total_ops, curr_iops,
avg_iops, max_iops, peak_iops, actv_sess]
return cap_dict_pre
def build_output(outfile_name, **cap_dict):
out_table = PrettyTable()
out_table.field_names = ["Cluster", "Timestamp","Used Metadata Snap Space",
"Max Used Metadata", "Used Metadata",
"Unique block space used", "Unique blocks",
"Zero blocks", "Non Zero Blocks",
"Snapshot Non Zero Blocks", "Max Overprovisionable",
"Max Provisioned", "Provisioned Space",
"Max Usable Space", "Used Space", "Active Space",
"Peak Active Sessions", "Active Sessions",
"Recent IO Size", "Total Ops", "Current IOPs",
"Average IOPs", "Maximum IOPs", "Peak IOPs"]
for key,val in cap_dict.items():
cls_name = key
time_stamp = val[0]
used_meta_snap_space_gb = val[1]
max_used_meta_gb = val[2]
used_meta_gb = val[3]
uniq_blck_used_space_gb = val[4]
uniq_block = val[5]
zero_blocks = val[6]
non_zero_block = val[7]
snap_non_zero_block = val[8]
max_over_prov_gb = val[9]
max_prov_gb = val[10]
prov_space_gb = val[11]
max_used_gb = val[12]
used_space_gb = val[13]
actv_space_gb = val[14]
peak_actv_sess = val[15]
io_size = val[16]
total_ops = val[17]
curr_iops = val[18]
avg_iops = val[19]
max_iops = val[20]
peak_iops = val[21]
actv_sess = val[22]
out_table.add_row([cls_name, time_stamp, used_meta_snap_space_gb,
max_used_meta_gb, used_meta_gb,
uniq_blck_used_space_gb, uniq_block,
zero_blocks, non_zero_block,
snap_non_zero_block, max_over_prov_gb,
max_prov_gb, prov_space_gb, max_used_gb,
used_space_gb, actv_space_gb,
peak_actv_sess, io_size, total_ops, curr_iops,
avg_iops, max_iops, peak_iops, actv_sess])
out_table_text = out_table.get_string()
print(out_table)
with open("./output_files/" + outfile_name, "a") as out_file:
out_file.write(out_table_text + "\n")
def get_filename(cluster_name):
"""
Build the output filename
"""
now_date = datetime.now()
out_date = now_date.strftime("%Y-%m-%d_%H-%M")
outfile_name = "cluster_capacity_" + out_date + '.txt'
if os.path.exists(outfile_name):
os.remove(outfile_name)
print('Output file name is: {}'.format(outfile_name))
return outfile_name
def main():
"""
Do the work
"""
user, user_pass, search_customer, search_string, _sort_by, search_cluster = get_inputs()
auth_cookie = web_login(user, user_pass)
payload = build_payload()
headers = build_headers(auth_cookie)
response_json = build_connect(headers,payload)
cluster_dict = parse_customer(response_json, search_customer)
response_dict = build_response(headers, cluster_dict, search_string=None,
api_call='GetClusterCapacity', node_id=None)
outfile_name = get_filename(search_customer)
cap_dict_pre = build_events(response_dict, search_string)
cap_dict = parse_cluster(cap_dict_pre, search_cluster)
build_output(outfile_name, **cap_dict)
if __name__ == "__main__":
main()
|
'''
Simple xgboost implementation
'''
|
import requests
def download_from_url(url: str, save_path: str, chunk_size: int = 128, progress_update=None):
response = requests.get(url, stream=True)
total_size_in_bytes = int(response.headers.get('content-length', 0))
acc_c_size = 0
with open(save_path, 'wb') as fd:
for chunk in response.iter_content(chunk_size=chunk_size):
c_size = len(chunk)*8
acc_c_size += c_size
completed_percent = acc_c_size / total_size_in_bytes
if progress_update is not None:
progress_update(completed_percent, acc_c_size, total_size_in_bytes)
fd.write(chunk)
|
from flask_mail import Message, Mail
from flask import render_template
from . import mail
subject='Pitcher'
def mail_message(subject,template, to, **kwargs):
sender_email = 'dev.py.js@gmail.com'
email = Message(subject, sender =sender_email, recipients=[to])
email.body= render_template(template + ".txt", **kwargs)
email.html = render_template(template + ".html", **kwargs)
mail.send(email)
|
# -*- coding: utf-8 -*-
"""Noise modules."""
import abc
import six
import tensorflow as tf
from opennmt import constants
from opennmt.data import text
from opennmt.utils import misc
class WordNoiser(object):
"""Applies noise to words sequences."""
def __init__(self, noises=None, subword_token="￭", is_spacer=None):
"""Initializes the noising class.
Args:
noises: A list of :class:`opennmt.data.Noise` instances to apply
sequentially.
subword_token: The special token used by the subword tokenizer. This is
required when the noise should be applied at the word level and not the
subword level.
is_spacer: Whether :obj:`subword_token` is used as a spacer (as in
SentencePiece) or a joiner (as in BPE). If ``None``, will infer
directly from :obj:`subword_token`.
See Also:
:func:`opennmt.data.tokens_to_words`
"""
if noises is None:
noises = []
self.noises = noises
self.subword_token = subword_token
self.is_spacer = is_spacer
def add(self, noise):
"""Adds a noise to apply."""
self.noises.append(noise)
def __call__(self, tokens, sequence_length=None, keep_shape=False):
"""Applies noise on :obj:`tokens`.
Args:
tokens: A string ``tf.Tensor`` or batch of string ``tf.Tensor``.
sequence_length: When :obj:`tokens` is ND, the length of each sequence in
the batch.
keep_shape: Ensure that the shape is kept. Otherwise, fit the shape to the
new lengths.
Returns:
A tuple with the noisy version of :obj:`tokens` and the new lengths.
"""
with tf.device("cpu:0"):
return self._call(tokens, sequence_length, keep_shape)
def _call(self, tokens, sequence_length, keep_shape):
rank = tokens.shape.ndims
if rank == 1:
input_length = tf.shape(tokens)[0]
if sequence_length is not None:
tokens = tokens[:sequence_length]
else:
tokens = tokens[:tf.math.count_nonzero(tokens)]
words = text.tokens_to_words(
tokens,
subword_token=self.subword_token,
is_spacer=self.is_spacer)
words = words.to_tensor()
for noise in self.noises:
words = noise(words)
outputs = tf.RaggedTensor.from_tensor(words, padding="").flat_values
output_length = tf.shape(outputs)[0]
if keep_shape:
outputs = tf.pad(outputs, [[0, input_length - output_length]])
return outputs, output_length
elif rank == 2:
if sequence_length is None:
raise ValueError("sequence_length must be passed for 2D inputs")
tokens, sequence_length = tf.map_fn(
lambda arg: self._call(*arg, keep_shape=True),
(tokens, sequence_length),
back_prop=False)
if not keep_shape:
tokens = tokens[:, :tf.reduce_max(sequence_length)]
return tokens, sequence_length
else:
if sequence_length is None:
raise ValueError("sequence_length must be passed for ND inputs")
original_shape = misc.shape_list(tokens)
tokens = tf.reshape(tokens, [-1, original_shape[-1]])
sequence_length = tf.reshape(sequence_length, [-1])
tokens, sequence_length = self._call(tokens, sequence_length, keep_shape=keep_shape)
tokens = tf.reshape(tokens, original_shape[:-1] + [-1])
sequence_length = tf.reshape(sequence_length, original_shape[:-1])
return tokens, sequence_length
@six.add_metaclass(abc.ABCMeta)
class Noise(object):
"""Base class for noise modules."""
def __call__(self, words):
"""Applies noise on a sequence of words.
Args:
words: The sequence of words as a string ``tf.Tensor``. If it has 2
dimensions, each row represents a word that possibly contains multiple
tokens.
Returns:
A noisy version of :obj:`words`.
Raises:
ValueError: if :obj:`words` has a rank greater than 2.
"""
if words.shape.ndims > 2:
raise ValueError("Noise only supports tensors of rank 2 or less")
inputs = words
if words.shape.ndims == 1:
inputs = tf.expand_dims(inputs, 1)
num_words = tf.shape(inputs)[0]
outputs = tf.cond(
tf.math.equal(num_words, 0),
true_fn=lambda: inputs,
false_fn=lambda: self._apply(inputs))
if words.shape.ndims == 1:
outputs = tf.squeeze(outputs, 1)
return outputs
@abc.abstractmethod
def _apply(self, words):
"""Applies noise on a sequence of words.
Args:
words: A 2D string ``tf.Tensor`` where each row represents a word that
possibly contains multiple tokens.
Returns:
A noisy version of :obj:`words`.
"""
raise NotImplementedError()
class WordDropout(Noise):
"""Randomly drops words in a sequence."""
def __init__(self, dropout):
"""Initializes the noise module.
Args:
dropout: The probability to drop word.
"""
self.dropout = dropout
def _apply(self, words):
if self.dropout == 0:
return tf.identity(words)
num_words = tf.shape(words, out_type=tf.int64)[0]
keep_mask = random_mask([num_words], 1 - self.dropout)
keep_ind = tf.where(keep_mask)
# Keep at least one word.
keep_ind = tf.cond(
tf.equal(tf.shape(keep_ind)[0], 0),
true_fn=lambda: tf.random.uniform([1], maxval=num_words, dtype=tf.int64),
false_fn=lambda: tf.squeeze(keep_ind, -1))
return tf.gather(words, keep_ind)
class WordOmission(Noise):
"""Randomly omits words in a sequence.
This is different than :class:`opennmt.data.WordDropout` as it drops a
fixed number of words.
"""
def __init__(self, count):
"""Initializes the noise module.
Args:
count: The number of words to omit.
"""
self.count = count
def _apply(self, words):
if self.count == 0:
return tf.identity(words)
num_words = tf.shape(words)[0]
indices = tf.range(num_words)
shuffle_indices = tf.random.shuffle(indices)
keep_count = tf.maximum(num_words - self.count, 1)
keep_indices = tf.sort(shuffle_indices[:keep_count])
return tf.gather(words, keep_indices)
class WordReplacement(Noise):
"""Randomly replaces words."""
def __init__(self, probability, filler=constants.UNKNOWN_TOKEN):
"""Initializes the noise module.
Args:
probability: The probability to replace words.
filler: The replacement token.
"""
self.probability = probability
self.filler = filler
def _apply(self, words):
if self.probability == 0:
return tf.identity(words)
shape = tf.shape(words)
replace_mask = random_mask(shape[:1], self.probability)
filler = tf.fill([shape[0], 1], self.filler)
filler = tf.pad(filler, [[0, 0], [0, shape[-1] - 1]])
return tf.where(
tf.broadcast_to(tf.expand_dims(replace_mask, -1), tf.shape(words)),
x=filler,
y=words)
class WordPermutation(Noise):
"""Randomly permutes words in a sequence with a maximum distance."""
def __init__(self, max_distance):
"""Initializes the noise module.
Args:
max_distance: The maximum permutation distance.
"""
self.max_distance = max_distance
def _apply(self, words):
if self.max_distance == 0:
return tf.identity(words)
num_words = tf.shape(words)[0]
offset = tf.random.uniform([num_words], maxval=1) * (self.max_distance + 1)
offset = tf.cast(offset, num_words.dtype)
new_pos = tf.argsort(tf.range(num_words) + offset)
return tf.gather(words, new_pos)
def random_mask(shape, probability):
"""Generates a random boolean mask.
Args:
shape: The mask shape.
probability: The probability to select an element.
Returns:
A boolean mask with shape :obj:`shape`.
"""
probs = tf.random.uniform(shape, maxval=1)
mask = tf.math.less(probs, probability)
return mask
|
#!/usr/bin/env python3
import argparse
import os
import shutil
import socket
import sys
from functools import partial
from pathlib import Path
import mako.lookup
import mako.template
import requests
import toml
import yaml
BASE16_TEMPLATES_URL = 'https://raw.githubusercontent.com/chriskempson/base16-templates-source/master/list.yaml'
BASE16_TEMPLATES = yaml.safe_load(requests.get(BASE16_TEMPLATES_URL).text)
def get_base16(scheme, app, template='default'):
base_url = BASE16_TEMPLATES[app].replace('github.com', 'raw.githubusercontent.com') + '/master/';
config = yaml.safe_load(requests.get(base_url + 'templates/config.yaml').text)
output = config[template]['output']
extension = config[template]['extension']
return requests.get(base_url + output + '/base16-' + scheme + extension).text
def main():
parser = argparse.ArgumentParser(
description='Generates and installs dotfiles for this host.',
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument(
'-d', '--dotfiles',
help='The base directory of the dotfiles repository.',
type=Path,
default=Path(sys.argv[0]).parent,
)
parser.add_argument(
'-n', '--hostname',
help='The hostname or other identifying name of this system that will'
' be used to retrieve the host-specific configuration.',
default=os.environ.get('HOSTNAME') or socket.gethostname(),
)
parser.add_argument(
'-o', '--home',
help='The home directory where generated dotfiles will be installed.',
type=Path,
default=os.environ.get('HOME') or Path.home(),
)
args = parser.parse_args()
raw_dir = args.dotfiles / 'raw'
templates_dir = args.dotfiles / 'templates'
include_dir = args.dotfiles / 'include'
host_filename = args.dotfiles / 'hosts' / '{}.toml'.format(args.hostname)
if host_filename.exists():
with open(host_filename) as host_file:
host_config = toml.load(host_file)
else:
host_config = {}
host_config['name'] = args.hostname
lookup = mako.lookup.TemplateLookup(
directories=[
str(templates_dir),
str(include_dir),
],
)
for raw_path in raw_dir.glob('**/*'):
if not raw_path.is_file():
continue
rel_path = raw_path.relative_to(raw_dir)
output_path = args.home / rel_path
print(rel_path)
output_path.parent.mkdir(parents=True, exist_ok=True)
shutil.copy(raw_path, output_path)
for template_path in templates_dir.glob('**/*'):
if not template_path.is_file():
continue
rel_path = template_path.relative_to(templates_dir)
print(rel_path)
template = mako.template.Template(
filename=str(template_path),
strict_undefined=True,
lookup=lookup,
)
output = template.render(
host=host_config,
get_base16=partial(get_base16, host_config.get('base16-scheme', 'default-dark')),
)
output_path = args.home / template_path.relative_to(templates_dir)
output_path.parent.mkdir(parents=True, exist_ok=True)
with open(output_path, 'w+') as output_file:
output_file.write(output)
if __name__ == '__main__':
main()
|
# -*- coding: utf-8 -*-
SOI = b'\xFF\xA0' #Start of Image
EOI = b'\xFF\xA1' #End of Image
SOF = b'\xFF\xA2' #Start of Frame
SOB = b'\xFF\xA3' #Start of Block
DTT = b'\xFF\xA4' #Define Transform Table
DQT = b'\xFF\xA5' #Define Quantization Table
DHT = b'\xFF\xA6' #Define Huffman Table(s)
DRI = b'\xFF\xA7' #Define Restart Interval
RST0 = b'\xFF\xB0' #Restart Modulo 0
RST1 = b'\xFF\xB1' #Restart Modulo 1
RST2 = b'\xFF\xB2' #Restart Modulo 2
RST3 = b'\xFF\xB3' #Restart Modulo 3
RST4 = b'\xFF\xB4' #Restart Modulo 4
RST5 = b'\xFF\xB5' #Restart Modulo 5
RST6 = b'\xFF\xB6' #Restart Modulo 6
RST7 = b'\xFF\xB7' #Restart Modulo 7
COM = b'\xFF\xA8' #Comment
|
import requests
__author__ = 'Corey Hoard'
__version__ = '1.0.0'
__license__ = 'MIT'
__all__ = ['Imgflip', 'Meme']
class Imgflip(object):
"""
Access the Imgflip RESTful JSON API.
A username and password are needed to caption images, but are not needed to get
the current list of memes.
Examples:
# List all memes available by name
import pyimgflip
api = pyimgflip.Imgflip()
memes = api.get_memes()
for meme in memes:
print(meme.name)
# Post a random meme and print its url
import pyimgflip
import random
api = pyimgflip.Imgflip(username='your_username', password='******')
memes = api.get_memes()
meme = random.choice(memes)
print("Generating a meme from template: " + meme.name)
result = api.caption_image(meme, "Top Text", "Bottom Text")
print("Meme available at URL: " + result['url'])
See Imgflip's documentation at https://api.imgflip.com for more information.
Most function descriptions taken from the above URL.
"""
def __init__(self, username = None, password = None):
"""
Create a new Imgflip instance.
Args:
username (str) [optional]: Username of any valid imgflip account.
password (str) [optional]: Corresponding account password
"""
super(Imgflip, self).__init__()
self.username = username
self.password = password
def get_memes(self):
"""
Get list of available memes.
Gets an array of popular memes that may be captioned with this API.
The size of this array and the order of memes may change at any time.
When this description was written, it returned 100 memes ordered by
how many times they were captioned in the last 30 days.
Returns:
A list of pyimgflip.Meme objects
Raises:
HTTPError: if the API cannot be reached or returns an invalid response.
RuntimeError: if the API indicates an unsuccessful response or JSON cannot be parsed.
"""
url = 'https://api.imgflip.com/get_memes'
r = requests.get(url)
r.raise_for_status()
response = r.json()
if response['success']:
return [Meme.fromJSON(meme) for meme in response['data']['memes']]
else:
raise RuntimeError("Imgflip returned error message: " + response['error_message'])
def caption_image(self, meme, text0, text1, font='impact', max_font_size=50):
"""
Add a caption to an Imgflip meme template.
Args:
meme (pyimgflip.Meme, int): Accepts either a Meme object or a valid Imgflip template ID.
text0 (str): The top text for the meme.
text1 (str): The bottom text for the meme.
font (str): Current options are 'impact' and 'arial'. Defaults to 'impact'.
max_font_size (int): Maximum font size in pixels. Defaults to 50px.
Returns:
A dictionary as with keys "url" and "page_url" as reported by Imgflip.
Raises:
HTTPError: if the API cannot be reached or returns an invalid response.
RuntimeError: if the API indicates an unsuccessful response.
TypeError: if meme id is an invalid type
ValueError: if font is passed an incorrect value
"""
url = 'https://api.imgflip.com/caption_image'
if self.username is None or self.password is None:
raise RuntimeError("Username and password required to caption image.")
try:
try:
template_id = int(meme.id)
except AttributeError as e:
template_id = int(meme)
except ValueError as e:
raise TypeError("Meme id must be a numeric value.")
font_clean = font.lower().strip()
if font_clean != 'impact' and font_clean != 'arial':
raise ValueError("Font parameter must be either 'impact' or 'arial'.")
payload = {'username':self.username, 'password':self.password,
'template_id':template_id,
'text0':text0, 'text1':text1,
'font':font_clean, 'max_font_size':max_font_size}
r = requests.post(url, data=payload)
r.raise_for_status()
response = r.json()
if response['success']:
return response['data']
else:
raise RuntimeError("Imgflip returned error message: " + response['error_message'])
def caption_image_boxes(self, meme, boxes, font='impact', max_font_size=50):
"""
Uses Imgflip's more advanced 'boxes' interface for maximum customization.
See https://api.imgflip.com for usage details.
Args:
meme (pyimgflip.Meme, int): Accepts either a Meme object or a valid Imgflip template ID.
boxes (dict): Custom text boxes as specified by the API.
font (str): Current options are 'impact' and 'arial'. Defaults to 'impact'.
max_font_size (int): Maximum font size in pixels. Defaults to 50px.
Returns:
A dictionary as with keys "url" and "page_url" as reported by Imgflip.
Raises:
HTTPError: if the API cannot be reached or returns an invalid response.
RuntimeError: if the API indicates an unsuccessful response.
TypeError: if meme id is an invalid type
ValueError: if font is passed an incorrect value
"""
url = 'https://api.imgflip.com/caption_image'
if self.username is None or self.password is None:
raise RuntimeError("Username and password required to caption image.")
try:
try:
template_id = int(meme.id)
except AttributeError as e:
template_id = int(meme)
except ValueError as e:
raise TypeError("Meme id must be a numeric value.")
font_clean = font.lower().strip()
if font_clean != 'impact' and font_clean != 'arial':
raise ValueError("Font parameter must be either 'impact' or 'arial'.")
payload = {'username':self.username, 'password':self.password,
'template_id':template_id,
'text0':'', 'text1':'',
'boxes':boxes,
'font':font_clean, 'max_font_size':max_font_size}
r = requests.post(url, data=payload)
r.raise_for_status()
response = r.json()
if response['success']:
return response['data']
else:
raise RuntimeError("Imgflip returned error message: " + response['error_message'])
def __str__(self):
return repr(self)
def __repr__(self):
if self.username is None or self.password is None:
return '<pyimgflip.Imgflip>'
else:
return '<pyimgflip.Imgflip for user "%s">' % self.username
class Meme(object):
"""
Represents a meme template as returned by pyimgflip.Imgflip.get_memes().
Fields:
id (int): Meme template ID number. Needed to caption images.
name (str): Human-readable name.
url (str): URL to an uncaptioned prototype image.
width (int): Image width in pixels.
height (int): Image height in pixels.
"""
def __init__(self, id, name='', url='', width=0, height=0):
"""
Create a new Meme instance
Args:
id (int): Meme template ID number. Needed to caption images.
name (str): Human-readable name.
url (str): URL to an uncaptioned prototype image.
width (int): Image width in pixels.
height (int): Image height in pixels.
"""
super(Meme, self).__init__()
self.id = int(id)
self.name = name
self.url = url
self.width = width
self.height = height
@classmethod
def fromJSON(cls, data):
"""
Create a Meme instance from a JSON API response.
Args:
data (dict): A JSON object as returned by the get_memes endpoint
Returns:
The newly-created Meme object
Raises:
RuntimeError: if the JSON object cannot be properly parsed
"""
try:
return cls(**data)
except AttributeError:
raise RuntimeError("JSON cannot be properly parsed into Meme object: " + str(data))
def __str__(self):
return '<pyimgflip.Meme with id %i and name "%s">' % (self.id, self.name)
def __repr__(self):
return '<pyimgflip.Meme with id %i>' % self.id
|
import h5py
import numpy as np
def load_dataset(train_path, test_path):
train_dataset = h5py.File(train_path, "r")
train_set_x_orig = np.array(train_dataset["train_set_x"][:]) # your train set features
train_set_y_orig = np.array(train_dataset["train_set_y"][:]) # your train set labels
test_dataset = h5py.File(test_path, "r")
test_set_x_orig = np.array(test_dataset["test_set_x"][:]) # your test set features
test_set_y_orig = np.array(test_dataset["test_set_y"][:]) # your test set labels
classes = np.array(test_dataset["list_classes"][:]) # the list of classes
train_set_y_orig = train_set_y_orig.reshape((1, train_set_y_orig.shape[0]))
test_set_y_orig = test_set_y_orig.reshape((1, test_set_y_orig.shape[0]))
return train_set_x_orig, train_set_y_orig, test_set_x_orig, test_set_y_orig, classes
def sigmoid(z):
'''
input: z (a scalar)
output: sigmoid(z)
'''
return 1/(1 + np.exp(-z))
def propagate(w, b, x, y):
'''
input: - w: weights, a numpy array of size (px * px * 3, 1)
- b: bias
- x: data of size (px * px * 3, number of examples)
- y: label vector of size (1, number of examples)
output:
- cost: cost for logistic regression
- dw: gradient of the loss with respect to w
- db: gradient of the loss with respect to b
'''
m = x.shape[1]
# Forward Propagation:
activation = sigmoid(np.dot(w.T, x) + b)
cost = -(1/m)*(np.sum(y*np.log(activation) + (1-y)*np.log(1-activation)))
# Backward Propagation
gradient = {'dw': (1/m)*np.dot(x, (activation-y).T),
'db': (1/m)*np.sum(activation-y)}
return gradient, cost
def optimize(w, b, x, y, num_iterations, lr):
'''
input: - w: weights, a numpy array of size (px * px * 3, 1)
- b: bias
- x: data of size (px * px * 3, number of examples)
- y: label vector of size (1, number of examples)
- num_iterations: number of iterations of the optimization loop
- lr: learning_rate, for the GD update rule
output:
- params: dictionary containing w and b
- grads: dictionary containing the gradients of the weights and bias with respect to the cost function
- costs: list of all the costs computed during the optimization, this will be used to plot the learning curve
'''
costs = []
for i in range(num_iterations):
gradient, cost = propagate(w, b, x, y)
dw, db = gradient['dw'], gradient['db']
w -= lr*dw
b -= lr*db
if i % 100 == 0:
costs.append(cost)
print('{}th iteration cost: {}'.format(i, cost))
return {'w': w, 'b': b},\
{'dw': dw, 'db': db},\
costs
def predict(w, b, x):
'''
input: - w: weights (px * px * 3, 1)
- b: bias
- x: data of size (px * px * 3, number of examples)
output:
- y_pred: np array containing all predictions (0 / 1) for examples in x
'''
m = x.shape[1]
y_pred = np.zeros((1, m))
w = w.reshape(x.shape[0], 1)
activation = sigmoid(np.dot(w.T, x) + b)
for i in range(activation.shape[1]):
y_pred[0,i] = 1 if activation[0, i] > 0.5 else 0
return y_pred
|
import parser
import unittest
from test import test_support
#
# First, we test that we can generate trees from valid source fragments,
# and that these valid trees are indeed allowed by the tree-loading side
# of the parser module.
#
class RoundtripLegalSyntaxTestCase(unittest.TestCase):
def roundtrip(self, f, s):
st1 = f(s)
t = st1.totuple()
try:
st2 = parser.sequence2st(t)
except parser.ParserError, why:
self.fail("could not roundtrip %r: %s" % (s, why))
self.assertEquals(t, st2.totuple(),
"could not re-generate syntax tree")
def check_expr(self, s):
self.roundtrip(parser.expr, s)
def check_suite(self, s):
self.roundtrip(parser.suite, s)
def test_yield_statement(self):
self.check_suite("def f(): yield 1")
self.check_suite("def f(): yield")
self.check_suite("def f(): x += yield")
self.check_suite("def f(): x = yield 1")
self.check_suite("def f(): x = y = yield 1")
self.check_suite("def f(): x = yield")
self.check_suite("def f(): x = y = yield")
self.check_suite("def f(): 1 + (yield)*2")
self.check_suite("def f(): (yield 1)*2")
self.check_suite("def f(): return; yield 1")
self.check_suite("def f(): yield 1; return")
self.check_suite("def f():\n"
" for x in range(30):\n"
" yield x\n")
self.check_suite("def f():\n"
" if (yield):\n"
" yield x\n")
def test_expressions(self):
self.check_expr("foo(1)")
self.check_expr("[1, 2, 3]")
self.check_expr("[x**3 for x in range(20)]")
self.check_expr("[x**3 for x in range(20) if x % 3]")
self.check_expr("[x**3 for x in range(20) if x % 2 if x % 3]")
self.check_expr("list(x**3 for x in range(20))")
self.check_expr("list(x**3 for x in range(20) if x % 3)")
self.check_expr("list(x**3 for x in range(20) if x % 2 if x % 3)")
self.check_expr("foo(*args)")
self.check_expr("foo(*args, **kw)")
self.check_expr("foo(**kw)")
self.check_expr("foo(key=value)")
self.check_expr("foo(key=value, *args)")
self.check_expr("foo(key=value, *args, **kw)")
self.check_expr("foo(key=value, **kw)")
self.check_expr("foo(a, b, c, *args)")
self.check_expr("foo(a, b, c, *args, **kw)")
self.check_expr("foo(a, b, c, **kw)")
self.check_expr("foo + bar")
self.check_expr("foo - bar")
self.check_expr("foo * bar")
self.check_expr("foo / bar")
self.check_expr("foo // bar")
self.check_expr("lambda: 0")
self.check_expr("lambda x: 0")
self.check_expr("lambda *y: 0")
self.check_expr("lambda *y, **z: 0")
self.check_expr("lambda **z: 0")
self.check_expr("lambda x, y: 0")
self.check_expr("lambda foo=bar: 0")
self.check_expr("lambda foo=bar, spaz=nifty+spit: 0")
self.check_expr("lambda foo=bar, **z: 0")
self.check_expr("lambda foo=bar, blaz=blat+2, **z: 0")
self.check_expr("lambda foo=bar, blaz=blat+2, *y, **z: 0")
self.check_expr("lambda x, *y, **z: 0")
self.check_expr("(x for x in range(10))")
self.check_expr("foo(x for x in range(10))")
def test_print(self):
self.check_suite("print")
self.check_suite("print 1")
self.check_suite("print 1,")
self.check_suite("print >>fp")
self.check_suite("print >>fp, 1")
self.check_suite("print >>fp, 1,")
def test_simple_expression(self):
# expr_stmt
self.check_suite("a")
def test_simple_assignments(self):
self.check_suite("a = b")
self.check_suite("a = b = c = d = e")
def test_simple_augmented_assignments(self):
self.check_suite("a += b")
self.check_suite("a -= b")
self.check_suite("a *= b")
self.check_suite("a /= b")
self.check_suite("a //= b")
self.check_suite("a %= b")
self.check_suite("a &= b")
self.check_suite("a |= b")
self.check_suite("a ^= b")
self.check_suite("a <<= b")
self.check_suite("a >>= b")
self.check_suite("a **= b")
def test_function_defs(self):
self.check_suite("def f(): pass")
self.check_suite("def f(*args): pass")
self.check_suite("def f(*args, **kw): pass")
self.check_suite("def f(**kw): pass")
self.check_suite("def f(foo=bar): pass")
self.check_suite("def f(foo=bar, *args): pass")
self.check_suite("def f(foo=bar, *args, **kw): pass")
self.check_suite("def f(foo=bar, **kw): pass")
self.check_suite("def f(a, b): pass")
self.check_suite("def f(a, b, *args): pass")
self.check_suite("def f(a, b, *args, **kw): pass")
self.check_suite("def f(a, b, **kw): pass")
self.check_suite("def f(a, b, foo=bar): pass")
self.check_suite("def f(a, b, foo=bar, *args): pass")
self.check_suite("def f(a, b, foo=bar, *args, **kw): pass")
self.check_suite("def f(a, b, foo=bar, **kw): pass")
self.check_suite("@staticmethod\n"
"def f(): pass")
self.check_suite("@staticmethod\n"
"@funcattrs(x, y)\n"
"def f(): pass")
self.check_suite("@funcattrs()\n"
"def f(): pass")
def test_class_defs(self):
self.check_suite("class foo():pass")
def test_import_from_statement(self):
self.check_suite("from sys.path import *")
self.check_suite("from sys.path import dirname")
self.check_suite("from sys.path import (dirname)")
self.check_suite("from sys.path import (dirname,)")
self.check_suite("from sys.path import dirname as my_dirname")
self.check_suite("from sys.path import (dirname as my_dirname)")
self.check_suite("from sys.path import (dirname as my_dirname,)")
self.check_suite("from sys.path import dirname, basename")
self.check_suite("from sys.path import (dirname, basename)")
self.check_suite("from sys.path import (dirname, basename,)")
self.check_suite(
"from sys.path import dirname as my_dirname, basename")
self.check_suite(
"from sys.path import (dirname as my_dirname, basename)")
self.check_suite(
"from sys.path import (dirname as my_dirname, basename,)")
self.check_suite(
"from sys.path import dirname, basename as my_basename")
self.check_suite(
"from sys.path import (dirname, basename as my_basename)")
self.check_suite(
"from sys.path import (dirname, basename as my_basename,)")
def test_basic_import_statement(self):
self.check_suite("import sys")
self.check_suite("import sys as system")
self.check_suite("import sys, math")
self.check_suite("import sys as system, math")
self.check_suite("import sys, math as my_math")
def test_pep263(self):
self.check_suite("# -*- coding: iso-8859-1 -*-\n"
"pass\n")
def test_assert(self):
self.check_suite("assert alo < ahi and blo < bhi\n")
#
# Second, we take *invalid* trees and make sure we get ParserError
# rejections for them.
#
class IllegalSyntaxTestCase(unittest.TestCase):
def check_bad_tree(self, tree, label):
try:
parser.sequence2st(tree)
except parser.ParserError:
pass
else:
self.fail("did not detect invalid tree for %r" % label)
def test_junk(self):
# not even remotely valid:
self.check_bad_tree((1, 2, 3), "<junk>")
def test_illegal_yield_1(self):
# Illegal yield statement: def f(): return 1; yield 1
tree = \
(257,
(264,
(285,
(259,
(1, 'def'),
(1, 'f'),
(260, (7, '('), (8, ')')),
(11, ':'),
(291,
(4, ''),
(5, ''),
(264,
(265,
(266,
(272,
(275,
(1, 'return'),
(313,
(292,
(293,
(294,
(295,
(297,
(298,
(299,
(300,
(301,
(302, (303, (304, (305, (2, '1')))))))))))))))))),
(264,
(265,
(266,
(272,
(276,
(1, 'yield'),
(313,
(292,
(293,
(294,
(295,
(297,
(298,
(299,
(300,
(301,
(302,
(303, (304, (305, (2, '1')))))))))))))))))),
(4, ''))),
(6, ''))))),
(4, ''),
(0, ''))))
self.check_bad_tree(tree, "def f():\n return 1\n yield 1")
def test_illegal_yield_2(self):
# Illegal return in generator: def f(): return 1; yield 1
tree = \
(257,
(264,
(265,
(266,
(278,
(1, 'from'),
(281, (1, '__future__')),
(1, 'import'),
(279, (1, 'generators')))),
(4, ''))),
(264,
(285,
(259,
(1, 'def'),
(1, 'f'),
(260, (7, '('), (8, ')')),
(11, ':'),
(291,
(4, ''),
(5, ''),
(264,
(265,
(266,
(272,
(275,
(1, 'return'),
(313,
(292,
(293,
(294,
(295,
(297,
(298,
(299,
(300,
(301,
(302, (303, (304, (305, (2, '1')))))))))))))))))),
(264,
(265,
(266,
(272,
(276,
(1, 'yield'),
(313,
(292,
(293,
(294,
(295,
(297,
(298,
(299,
(300,
(301,
(302,
(303, (304, (305, (2, '1')))))))))))))))))),
(4, ''))),
(6, ''))))),
(4, ''),
(0, ''))))
self.check_bad_tree(tree, "def f():\n return 1\n yield 1")
def test_print_chevron_comma(self):
# Illegal input: print >>fp,
tree = \
(257,
(264,
(265,
(266,
(268,
(1, 'print'),
(35, '>>'),
(290,
(291,
(292,
(293,
(295,
(296,
(297,
(298, (299, (300, (301, (302, (303, (1, 'fp')))))))))))))),
(12, ','))),
(4, ''))),
(0, ''))
self.check_bad_tree(tree, "print >>fp,")
def test_a_comma_comma_c(self):
# Illegal input: a,,c
tree = \
(258,
(311,
(290,
(291,
(292,
(293,
(295,
(296,
(297,
(298, (299, (300, (301, (302, (303, (1, 'a')))))))))))))),
(12, ','),
(12, ','),
(290,
(291,
(292,
(293,
(295,
(296,
(297,
(298, (299, (300, (301, (302, (303, (1, 'c'))))))))))))))),
(4, ''),
(0, ''))
self.check_bad_tree(tree, "a,,c")
def test_illegal_operator(self):
# Illegal input: a $= b
tree = \
(257,
(264,
(265,
(266,
(267,
(312,
(291,
(292,
(293,
(294,
(296,
(297,
(298,
(299,
(300, (301, (302, (303, (304, (1, 'a'))))))))))))))),
(268, (37, '$=')),
(312,
(291,
(292,
(293,
(294,
(296,
(297,
(298,
(299,
(300, (301, (302, (303, (304, (1, 'b'))))))))))))))))),
(4, ''))),
(0, ''))
self.check_bad_tree(tree, "a $= b")
def test_malformed_global(self):
#doesn't have global keyword in ast
tree = (257,
(264,
(265,
(266,
(282, (1, 'foo'))), (4, ''))),
(4, ''),
(0, ''))
self.check_bad_tree(tree, "malformed global ast")
class CompileTestCase(unittest.TestCase):
# These tests are very minimal. :-(
def test_compile_expr(self):
st = parser.expr('2 + 3')
code = parser.compilest(st)
self.assertEquals(eval(code), 5)
def test_compile_suite(self):
st = parser.suite('x = 2; y = x + 3')
code = parser.compilest(st)
globs = {}
exec code in globs
self.assertEquals(globs['y'], 5)
def test_compile_error(self):
st = parser.suite('1 = 3 + 4')
self.assertRaises(SyntaxError, parser.compilest, st)
def test_main():
test_support.run_unittest(
RoundtripLegalSyntaxTestCase,
IllegalSyntaxTestCase,
CompileTestCase,
)
if __name__ == "__main__":
test_main()
|
# ----------------------------------------------------------------------
# |
# | __init__.py
# |
# | David Brownell <db@DavidBrownell.com>
# | 2018-05-19 14:09:14
# |
# ----------------------------------------------------------------------
# |
# | Copyright David Brownell 2018.
# | Distributed under the Boost Software License, Version 1.0.
# | (See accompanying file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
# |
# ----------------------------------------------------------------------
"""Contains the InvocationQueryMixin object"""
import os
import sys
from CommonEnvironment.Interface import Interface, abstractmethod
# ----------------------------------------------------------------------
_script_fullpath = os.path.abspath(__file__) if "python" in sys.executable.lower() else sys.executable
_script_dir, _script_name = os.path.split(_script_fullpath)
# ----------------------------------------------------------------------
# ----------------------------------------------------------------------
# <Too few public methods> pylint: disable = R0903
class InvocationQueryMixin(Interface):
"""Object that implements strategies for determining if a compiler should be invoked based on input."""
( InvokeReason_Always,
InvokeReason_Force,
InvokeReason_PrevContextMissing,
InvokeReason_NewerGenerators,
InvokeReason_MissingOutput,
InvokeReason_DifferentOutput,
InvokeReason_NewerInput,
InvokeReason_DifferentInput,
InvokeReason_DifferentMetadata,
InvokeReason_OptIn,
) = range(10)
# ----------------------------------------------------------------------
# | Methods defined in CompilerImpl; these methods forward to Impl
# | functions to clearly indicate to CompilerImpl that they are handled,
# | while also creating methods that must be implemented by derived
# | mixins.
# ----------------------------------------------------------------------
@classmethod
def _GetInvokeReason(cls, *args, **kwargs):
return cls._GetInvokeReasonImpl(*args, **kwargs)
# ----------------------------------------------------------------------
@classmethod
def _PersistContext(cls, *args, **kwargs):
return cls._PersistContextImpl(*args, **kwargs)
# ----------------------------------------------------------------------
# ----------------------------------------------------------------------
# ----------------------------------------------------------------------
@staticmethod
@abstractmethod
def _GetInvokeReasonImpl(context, output_stream):
raise Exception("Abstract method")
# ----------------------------------------------------------------------
@staticmethod
@abstractmethod
def _PersistContextImpl(context):
raise Exception("Abstract method")
|
from vedis import Vedis
import config
# Пытаемся узнать из базы «состояние» пользователя
def get_current_state(user_id):
with Vedis(config.db_file) as db:
try:
return db[user_id].decode() # Если используете Vedis версии ниже, чем 0.7.1, то .decode() НЕ НУЖЕН
except KeyError: # Если такого ключа почему-то не оказалось
return config.States.S_START.value # значение по умолчанию - начало диалога
# Сохраняем текущее «состояние» пользователя в нашу базу
def set_state(user_id, value):
with Vedis(config.db_file) as db:
try:
db[user_id] = value
return True
except:
# тут желательно как-то обработать ситуацию
return False
# def save_data(user_id, key, value):
# with Vedis(config.db_file) as db:
# try:
# db[user_id][key] = value
# return True
# except:
# return print('Жепа')
#
# def get_state(user_id, key):
# with Vedis(config.db_file) as db:
# try:
# return db[user_id].decode()
# except:
# return False
#
#
# # Пока что не работает, нужно довести до ума
def clear_db(user_id):
with Vedis(config.db_file) as db:
try:
db.delete(user_id)
except KeyError:
print('Текущее состояние пустое')
|
import time
import sys
import os
def load_animation():
load_str = "starting your console application..."
ls_len = len(load_str)
animation = "|/-\\"
anicount = 0
counttime = 0
i = 0
while (counttime != 100):
time.sleep(0.075)
load_str_list = list(load_str)
x = ord(load_str_list[i])
y = 0
if x != 32 and x != 46:
if x>90:
y = x-32
else:
y = x + 32
load_str_list[i]= chr(y)
res =''
for j in range(ls_len):
res = res + load_str_list[j]
sys.stdout.write("\r"+res + animation[anicount])
sys.stdout.flush()
load_str = res
anicount = (anicount + 1)% 4
i =(i + 1)% ls_len
counttime = counttime + 1
if os.name =="nt":
os.system("cls")
else:
os.system("clear")
if __name__ == '__main__':
load_animation()
s ="David"
sys.stdout.write("Hello "+str(s)+"\n")
|
import torch
from koila import PrePassFunc, prepasses
from . import common
def test_compatibility() -> None:
assert isinstance(prepasses.identity, PrePassFunc)
assert isinstance(prepasses.symmetric, PrePassFunc)
assert isinstance(prepasses.reduce_dims, PrePassFunc)
assert isinstance(prepasses.permute, PrePassFunc)
assert isinstance(prepasses.tranpose, PrePassFunc)
assert isinstance(prepasses.view, PrePassFunc)
assert isinstance(prepasses.reshape, PrePassFunc)
assert isinstance(prepasses.flatten, PrePassFunc)
assert isinstance(prepasses.matmul, PrePassFunc)
assert isinstance(prepasses.linear, PrePassFunc)
assert isinstance(prepasses.cat, PrePassFunc)
assert isinstance(prepasses.pad, PrePassFunc)
assert isinstance(prepasses.conv, PrePassFunc)
assert isinstance(prepasses.conv_transpose, PrePassFunc)
assert isinstance(prepasses.pool, PrePassFunc)
assert isinstance(prepasses.maxpool, PrePassFunc)
assert isinstance(prepasses.avgpool, PrePassFunc)
def test_identity() -> None:
common.call(
common.assert_equal,
[
[prepasses.identity(torch.randn(1, 2, 3, 4, 5)), (1, 2, 3, 4, 5)],
[prepasses.identity(torch.randn(4, 2, 5)), (4, 2, 5)],
[prepasses.identity(torch.randn(17, 1, 4)), (17, 1, 4)],
],
)
def test_symmetric() -> None:
common.call(
common.assert_equal,
[
[prepasses.symmetric(torch.randn(2, 4, 5), torch.randn(())), (2, 4, 5)],
[
prepasses.symmetric(torch.randn(2, 4, 5), torch.randn(2, 4, 5)),
(2, 4, 5),
],
[
prepasses.symmetric(torch.randn(2, 1, 5), torch.randn(2, 4, 5)),
(2, 4, 5),
],
[
prepasses.symmetric(torch.randn(2, 1, 5), torch.randn(2, 4, 1)),
(2, 4, 5),
],
],
)
def test_reduce_dims() -> None:
common.call(
common.assert_equal,
[
[prepasses.reduce_dims(torch.randn(1, 2, 3, 4, 5), 1), (1, 3, 4, 5)],
[prepasses.reduce_dims(torch.randn(1, 2, 3, 4, 5), (2, 3)), (1, 2, 5)],
[
prepasses.reduce_dims(torch.randn(5, 2, 3, 4), (2, 3), keepdim=True),
(5, 2, 1, 1),
],
],
)
def test_scalar() -> None:
common.call(
common.assert_equal,
[
[prepasses.reduce_dims(torch.randn(5, 5, 2)), ()],
[prepasses.reduce_dims(torch.randn(7, 8)), ()],
],
)
def test_matmul() -> None:
common.call(
common.assert_equal,
[
[prepasses.matmul(torch.randn(8), torch.randn(8)), ()],
[prepasses.matmul(torch.randn(8, 3), torch.randn(3)), (8,)],
[prepasses.matmul(torch.randn(8), torch.randn(8, 3)), (3,)],
[prepasses.matmul(torch.randn(4, 5), torch.randn(5, 3)), (4, 3)],
[prepasses.matmul(torch.randn(9, 4, 5), torch.randn(9, 5, 3)), (9, 4, 3)],
[prepasses.matmul(torch.randn(9, 4, 5), torch.randn(1, 5, 3)), (9, 4, 3)],
[
prepasses.matmul(torch.randn(9, 7, 4, 5), torch.randn(1, 5, 3)),
(9, 7, 4, 3),
],
],
)
def test_transpose() -> None:
common.call(
common.assert_equal,
[[prepasses.tranpose(torch.randn(3, 4, 5), 1, 2), (3, 5, 4)]],
)
def test_linear() -> None:
common.call(
common.assert_equal,
[
[
prepasses.linear(
torch.randn(7, 11, 13),
weight=torch.randn(17, 13),
bias=torch.randn(17),
),
(7, 11, 17),
]
],
)
def test_cat() -> None:
common.call(
common.assert_equal,
[
[prepasses.cat([torch.randn(2, 3, 5), torch.randn(3, 3, 5)]), (5, 3, 5)],
[
prepasses.cat([torch.randn(2, 3, 5), torch.randn(2, 4, 5)], dim=1),
(2, 7, 5),
],
],
)
def test_loss() -> None:
common.call(
common.assert_equal,
[
[prepasses.loss(torch.randn(2, 4, 5), torch.randn((2, 4, 5))), ()],
[
prepasses.loss(
torch.randn(2, 4, 5), torch.randn((2, 4, 5)), reduction="sum"
),
(),
],
[
prepasses.loss(
torch.randn(2, 4, 5), torch.randn((2, 4, 5)), reduction="none"
),
(2, 4, 5),
],
],
)
|
import os, sys, new
# WARNING: this is all nicely RPython, but there is no RPython code around
# to *compile* regular expressions, so outside of PyPy this is only useful
# for RPython applications that just need precompiled regexps.
#
# XXX However it's not even clear how to get such prebuilt regexps...
import rsre_core
rsre_core_filename = rsre_core.__file__
if rsre_core_filename[-1] in 'oc':
rsre_core_filename = rsre_core_filename[:-1]
rsre_core_filename = os.path.abspath(rsre_core_filename)
del rsre_core
def insert_sre_methods(locals, name):
"""A hack that inserts the SRE entry point methods into the 'locals'
scope, which should be the __dict__ of a State class. The State
class defines methods to look at the input string or unicode string.
It should provide the following API for sre_core:
get_char_ord(p) - return the ord of the char at position 'p'
lower(charcode) - return the ord of the lowcase version of 'charcode'
start - start position for searching and matching
end - end position for searching and matching
"""
filename = rsre_core_filename
rsre_core = new.module('pypy.rlib.rsre.rsre_core_' + name)
rsre_core.__file__ = filename
execfile(filename, rsre_core.__dict__)
for key, value in rsre_core.StateMixin.__dict__.items():
if not key.startswith('__'):
locals[key] = value
locals['rsre_core'] = rsre_core # for tests
def set_unicode_db(unicodedb):
"""Another hack to set the unicodedb used by rsre_char. I guess there
is little point in allowing several different unicodedb's in the same
RPython program... See comments in rsre_char.
"""
from pypy.rlib.rsre import rsre_char
rsre_char.unicodedb = unicodedb
class SimpleStringState(object):
"""Prebuilt state for matching strings, for testing and for
stand-alone RPython applictions that don't worry about unicode.
"""
insert_sre_methods(locals(), 'simple')
def __init__(self, string, start=0, end=-1):
self.string = string
if end < 0:
end = len(string)
self.start = start
self.end = end
self.reset()
def get_char_ord(self, p):
return ord(self.string[p])
|
#!/usr/bin/python
# -*- coding: utf-8 -*-
import hashlib
import sqlalchemy as sa
from holmes.models import Base
from holmes.models.domain import Domain
class Limiter(Base):
__tablename__ = "limiters"
id = sa.Column(sa.Integer, primary_key=True)
url = sa.Column('url', sa.String(2000), nullable=False)
url_hash = sa.Column('url_hash', sa.String(128), nullable=False)
value = sa.Column('value', sa.Integer, server_default='1', nullable=False)
def to_dict(self):
return {
'url': self.url,
'value': self.value
}
def __str__(self):
return str(self.url)
def __repr__(self):
return str(self)
@classmethod
def get_all(cls, db, domain_filter=None):
query = db.query(Limiter)
if domain_filter:
domain = Domain.get_domain_by_name(domain_filter, db)
if domain:
query = query.filter(Limiter.url.startswith(domain.url))
return query \
.order_by(sa.func.char_length(Limiter.url)) \
.all()
@classmethod
def by_url(cls, url, db):
return db.query(Limiter).filter(Limiter.url == url).first()
@classmethod
def by_url_hash(cls, url_hash, db):
return db.query(Limiter).filter(Limiter.url_hash == url_hash).first()
@classmethod
def by_id(cls, id_, db):
return db.query(Limiter).filter(Limiter.id == id_).first()
@classmethod
def delete(cls, id_, db):
return db.query(Limiter).filter(Limiter.id == id_).delete()
def matches(self, url):
return url.startswith(self.url)
@classmethod
def add_or_update_limiter(cls, db, url, value):
if not url:
return
url = url.encode('utf-8')
url_hash = hashlib.sha512(url).hexdigest()
limiter = Limiter.by_url_hash(url_hash, db)
if limiter:
db \
.query(Limiter) \
.filter(Limiter.id == limiter.id) \
.update({'value': value})
db.flush()
db.commit()
return limiter.url
limiter = Limiter(url=url, url_hash=url_hash, value=value)
db.add(limiter)
return limiter.url
@classmethod
def get_limiters_for_domains(cls, db, active_domains):
from holmes.models import Limiter # Avoid circular dependency
all_limiters = Limiter.get_all(db)
limiters = []
for limiter in all_limiters:
for domain in active_domains:
if limiter.matches(domain.url):
limiters.append(limiter)
return limiters
|
#!/usr/bin/env python
# coding: utf-8
import numpy as np
import pint.toa as toa
import pint.models as models
import pint.fitter as fit
import pint.residuals as r
import astropy.units as u
import enterprise
from enterprise.pulsar import Pulsar
import enterprise.signals.parameter as parameter
from enterprise.signals import utils
from enterprise.signals import signal_base
from enterprise.signals import selections
from enterprise.signals.selections import Selection
from enterprise.signals import white_signals
from enterprise.signals import gp_signals
from enterprise.signals import deterministic_signals
from enterprise import constants as const
import corner, pickle, sys, json
from PTMCMCSampler.PTMCMCSampler import PTSampler as ptmcmc
from enterprise_extensions import models, model_utils
from enterprise_extensions.electromagnetic import solar_wind as SW
from astropy import log
import glob
log.setLevel('CRITICAL')
import pta_sim
import pta_sim.bayes
import pta_sim.parse_sim as parse_sim
args = parse_sim.arguments()
if args.pickle=='no_pickle':
if args.use_pint:
parfile = args.pardir + args.psr + '*.gls.par'
timfile = args.timdir + args.psr + '*.tim'
t=toa.get_TOAs(timfile)
m=models.get_model(parfile)
f=fit.GLSFitter(t,m)
f.fit_toas(maxiter=2)
psr = Pulsar(t, f.model, ephem='DE436')
else:
if args.psr == 'J1713+0747':
parfile = glob.glob(args.pardir + args.psr + '*.gls.t2.par')[0]
else:
parfile = glob.glob(args.pardir + args.psr + '*.gls.par')[0]
timfile = glob.glob(args.timdir + args.psr + '*.tim')[0]
psr = Pulsar(parfile, timfile, ephem='DE436')
else:
with open(args.pickle, 'rb') as fin:
psrs = pickle.load(fin)
psr = [p for p in psrs if p.name==args.psr][0]
if args.end_time is None:
Outdir = args.outdir+'all/{0}/'.format(psr.name)
else:
start_time = psr.toas.min()/(24*3600)
if (args.end_time-start_time)/365.25 <= 3.0:
print('PSR {0} baseline too short for this slice.'.format(p.name))
sys.end()
psr.filter_data(start_time=start_time, end_time=args.end_time)
Outdir = args.outdir+'{0}/{1}/'.format(args.nyears,psr.name)
m = models.white_noise_block(vary=True, inc_ecorr=True)
m += gp_signals.TimingModel(use_svd=False)
m += models.red_noise_block(psd=args.psd, prior='log-uniform',
components=args.nfreqs, gamma_val=None)
dm_gp1 = models.dm_noise_block(gp_kernel='diag', psd='powerlaw',
prior='log-uniform', Tspan=None,
components=30, gamma_val=None,
coefficients=False)
dm_gp2 = models.dm_noise_block(gp_kernel='diag', psd='powerlaw',
prior='log-uniform', Tspan=None,
components=10, gamma_val=None,
coefficients=False)
n_earth = SW.ACE_SWEPAM_Parameter()('n_earth')
sw = SW.solar_wind(n_earth=n_earth)
mean_sw = deterministic_signals.Deterministic(sw, name='mean_sw')
log10_sigma = parameter.Uniform(-10, -4)
log10_ell = parameter.Uniform(1, 4)
dm_se_basis = models.linear_interp_basis_dm(dt=15*86400)
dm_se_prior = models.se_dm_kernel(log10_sigma=log10_sigma,log10_ell=log10_ell)
se = gp_signals.BasisGP(dm_se_prior, dm_se_basis, name='dm_gp')
log10_A_sw = parameter.Uniform(-10,1)('log10_A_sw')
gamma_sw = parameter.Uniform(-2,1)('gamma_sw')
dm_sw_basis = SW.createfourierdesignmatrix_solar_dm(nmodes=15,Tspan=None)
dm_sw_prior = utils.powerlaw(log10_A=log10_A_sw, gamma=gamma_sw)
gp_sw = gp_signals.BasisGP(priorFunction=dm_sw_prior,
basisFunction=dm_sw_basis,
name='gp_sw')
sw_models = []
sw_models.append(m + dm_gp1) #Model 0, Just DMGP
sw_models.append(m + mean_sw) #Model 1, Just Deterministic SW
sw_models.append(m + dm_gp2 + mean_sw) #Model 2, DMGP + Deter SW
sw_models.append(m + mean_sw + gp_sw) #Model 3, Deter SW + SW GP
sw_models.append(m + SW.solar_wind_block(ACE_prior=True, include_dmgp=False)
+ dm_gp2) #Model 4, All the things
sw_models.append(m + se + mean_sw ) #Model 5, Deter SW + Square-Exponential GP
ptas = {}
model_params = {}
for ii,mod in enumerate(sw_models):
ptas.update({ii : signal_base.PTA(mod(psr))})
model_params.update({ii : ptas[ii].param_names})
if args.model.isdigit():
nn = int(args.model)
ptas = {0:ptas[nn]}
model_params = {0:model_params[nn]}
super_model = model_utils.HyperModel(ptas)
Outdir = args.outdir+'/{0}/'.format(psr.name)
sampler = super_model.setup_sampler(resume=True, outdir=Outdir)
with open(Outdir+'/model_params.json' , 'w') as fout:
json.dump(model_params,fout,sort_keys=True,indent=4,separators=(',', ': '))
x0 = super_model.initial_sample()
sampler.sample(x0, args.niter, SCAMweight=30, AMweight=15, DEweight=50, )
|
class MassGBXMLExportOptions(object,IDisposable):
"""
Options used when exporting a gbXML file from a mass model document.
MassGBXMLExportOptions(massZoneIds: IList[ElementId])
MassGBXMLExportOptions(massZoneIds: IList[ElementId],massIds: IList[ElementId])
"""
def Dispose(self):
""" Dispose(self: MassGBXMLExportOptions) """
pass
def GetMassIds(self):
"""
GetMassIds(self: MassGBXMLExportOptions) -> IList[ElementId]
Gets a list of masses to use as shading surfaces in the exported gbXML--these
masses must not have mass floors or mass zones so as not to end up with
duplicate surface information in the gbXML output.
Returns: The ids of the masses.
"""
pass
def GetMassZoneIds(self):
"""
GetMassZoneIds(self: MassGBXMLExportOptions) -> IList[ElementId]
Gets a list of mass zones to analyze in the exported gbXML.
Returns: The ids of the mass zone.
"""
pass
def ReleaseUnmanagedResources(self,*args):
""" ReleaseUnmanagedResources(self: MassGBXMLExportOptions,disposing: bool) """
pass
def __enter__(self,*args):
""" __enter__(self: IDisposable) -> object """
pass
def __exit__(self,*args):
""" __exit__(self: IDisposable,exc_type: object,exc_value: object,exc_back: object) """
pass
def __init__(self,*args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
@staticmethod
def __new__(self,massZoneIds,massIds=None):
"""
__new__(cls: type,massZoneIds: IList[ElementId])
__new__(cls: type,massZoneIds: IList[ElementId],massIds: IList[ElementId])
"""
pass
def __repr__(self,*args):
""" __repr__(self: object) -> str """
pass
IsValidObject=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Specifies whether the .NET object represents a valid Revit entity.
Get: IsValidObject(self: MassGBXMLExportOptions) -> bool
"""
|
# -*- coding: utf-8 -*-
"""
@inproceedings{DBLP:conf/cvpr/SunLCS19,
author = {Qianru Sun and
Yaoyao Liu and
Tat{-}Seng Chua and
Bernt Schiele},
title = {Meta-Transfer Learning for Few-Shot Learning},
booktitle = {{IEEE} Conference on Computer Vision and Pattern Recognition, {CVPR}
2019, Long Beach, CA, USA, June 16-20, 2019},
pages = {403--412},
year = {2019},
url = {http://openaccess.thecvf.com/content_CVPR_2019/html/Sun_Meta-Transfer_Learning_for_Few
-Shot_Learning_CVPR_2019_paper.html},
doi = {10.1109/CVPR.2019.00049}
}
https://arxiv.org/abs/1812.02391
Adapted from https://github.com/yaoyao-liu/meta-transfer-learning.
"""
import torch
from torch import nn
from core.utils import accuracy
from .finetuning_model import FinetuningModel
import torch.nn.functional as F
# FIXME: Add multi-GPU support
class MTLBaseLearner(nn.Module):
"""The class for inner loop."""
def __init__(self, way_num, z_dim):
super().__init__()
self.way_num = way_num
self.z_dim = z_dim
self.var = nn.ParameterList()
self.fc1_w = nn.Parameter(torch.ones([self.way_num, self.z_dim]))
torch.nn.init.kaiming_normal_(self.fc1_w)
self.var.append(self.fc1_w)
self.fc1_b = nn.Parameter(torch.zeros(self.way_num))
self.var.append(self.fc1_b)
def forward(self, input_x, the_var=None):
if the_var is None:
the_var = self.var
fc1_w = the_var[0]
fc1_b = the_var[1]
net = F.linear(input_x, fc1_w, fc1_b)
return net
def parameters(self):
return self.var
class MTLPretrain(FinetuningModel): # use image-size=80 in repo
def __init__(self, feat_dim, num_class, inner_train_iter, **kwargs):
super(MTLPretrain, self).__init__(**kwargs)
self.feat_dim = feat_dim
self.num_class = num_class
self.pre_fc = nn.Sequential(
nn.Linear(self.feat_dim, 1000),
nn.ReLU(),
nn.Linear(1000, self.num_class),
)
self.base_learner = MTLBaseLearner(self.way_num, z_dim=self.feat_dim)
self.inner_train_iter = inner_train_iter
self.loss_func = nn.CrossEntropyLoss()
def set_forward(self, batch):
"""
meta-validation
:param batch:
:return:
"""
image, _ = batch
image = image.to(self.device)
with torch.no_grad():
feat = self.emb_func(image)
support_feat, query_feat, support_target, query_target = self.split_by_episode(feat, mode=4)
classifier, fast_weight = self.set_forward_adaptation(support_feat, support_target)
output = classifier(query_feat, fast_weight)
acc = accuracy(output, query_target)
return output, acc
def set_forward_loss(self, batch):
"""
finetuning
:param batch:
:return:
"""
image, global_target = batch
image = image.to(self.device)
global_target = global_target.to(self.device).contiguous()
feat = self.emb_func(image)
output = self.pre_fc(feat).contiguous()
loss = self.loss_func(output, global_target)
acc = accuracy(output, global_target)
return output, acc, loss
def set_forward_adaptation(self, support_feat, support_target):
classifier = self.base_learner.to(self.device)
logit = self.base_learner(support_feat)
loss = self.loss_func(logit, support_target)
grad = torch.autograd.grad(loss, self.base_learner.parameters())
fast_parameters = list(
map(
lambda p: p[1] - 0.01 * p[0],
zip(grad, self.base_learner.parameters()),
)
)
for _ in range(1, self.inner_train_iter):
logit = self.base_learner(support_feat, fast_parameters)
loss = F.cross_entropy(logit, support_target)
grad = torch.autograd.grad(loss, fast_parameters)
fast_parameters = list(map(lambda p: p[1] - 0.01 * p[0], zip(grad, fast_parameters)))
return classifier, fast_parameters
|
class Contact:
def __init__(self, firstname, middlename, nickname):
self.firstname = firstname
self.middlename = middlename
self.nickname = nickname
|
# -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.15.2)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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\x00\x5f\x00\x34\x00\x38\x00\x64\x00\x70\x00\x2e\x00\x73\x00\x76\x00\x67\
"
qt_resource_struct_v1 = b"\
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"
qt_resource_struct_v2 = b"\
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\x00\x00\x01\x80\x89\x7b\x5d\x91\
"
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()
|
# Link --> https://www.hackerrank.com/challenges/maximum-element/problem
# Code:
def getMax(operations):
maximum = 0
temp = []
answer = []
for i in operations:
if i != '2' and i != '3':
numbers = i.split()
number = int(numbers[1])
temp.append(number)
if number > maximum:
maximum = number
elif i == '2':
temp.pop()
if len(temp) != 0:
maximum = max(temp)
else:
maximum = 0
else:
answer.append(maximum)
return answer
|
Print("hello world");
print("Testing");
print("Salam")
print("Walikum as Salam")
print("testing Change");
print("New Change")
|
# Program to find the longest common prefix
def findMinLength(array, size):
minimum = len(array[0])
for i in range(1,size):
if (len(array[i])< minimum):
minimum = len(array[i])
return(minimum)
# A Function that returns the longest common prefix from the array of strings
def commonPrefix(array, size):
minimmum_length = findMinLength(array, size)
result =""
for i in range(minimmum_length):
common_char = array[0][i]
for j in range(1,size):
if (array[j][i] != common_char):
return result
# Append to result
result = result+common_char
return (result)
array = []
size = int(input("Enter size:"))
for i in range(size):
item=input()
array.append(item)
answer = commonPrefix (array, size)
if (len(answer)):
print("The longest common prefix is ",answer)
else:
print("There is no common prefix")
'''
Sample I/O:
Input:
Enter size: 3
star
start
stardom
Output:
The longest Common Prefix is : star
Time Complexity: O(size*M) (M = Length of the largest string)
Space Complexity:O(1)
'''
|
#!/usr/bin/env python
#############################################################################
### Natom_vs_Nsmichars.py
###
### Counts alphabet chars in SMILES for comparison with the atom count.
### Using Prestwick (from PubChem search, 1271 SMILES), the Spearman
### correlation coefficient is .997. This is useful since the char count
### can be performed very fast and without a chemical toolkit, and can
### be used for example to measure the fraction of a molecule contained
### by a scaffold.
###
### Jeremy Yang
### 18 Apr 2012
#############################################################################
import sys,os,re
import numpy
import openeye.oechem as oechem
if len(sys.argv)<2:
oechem.OEThrow.Usage("%s <infile> [<outfile>]"%sys.argv[0])
ims=oechem.oemolistream()
ims.open(sys.argv[1])
if len(sys.argv)>2:
oms=oechem.oemolostream()
oms.open(sys.argv[2])
else:
oms=None
natoms = []
nchars = []
for mol in ims.GetOEGraphMols():
na = mol.NumAtoms()
smi = oechem.OECreateSmiString(mol)
nc = len(re.sub(r'[^a-zA-Z]','',smi))
natoms.append(na)
nchars.append(nc)
if oms:
mol.SetTitle("%d\t%d"%(na,nc))
oechem.OEWriteMolecule(oms, mol)
ims.close()
if oms:
oms.close()
A=numpy.array(natoms)
C=numpy.array(nchars)
print "%s: N: %d"%(sys.argv[0],len(natoms))
print "%s: correlation coefficient: %.5f"%(sys.argv[0],numpy.corrcoef([A,C])[0][1])
|
from typing import Union, List, Dict
from nonebot import MessageSegment
from hoshino.log import new_logger
import base64, aiohttp, traceback
from .data import Data
from .config import config
from .api import Get_Random_Imginfo, Get_Imginfo
logger = new_logger('setu_download')
def b2b64(bytes: bytes) -> str:
base64_str = 'base64://' + base64.b64encode(bytes).decode()
return base64_str
async def Img_Download(project: str, url: str, pid: int) -> Union[bytes, bool]:
try:
headers = None
proxy = None
msg = f'Start Downloading Image With Pixiv.re -> PID: {pid}'
if project == 'lolicon' and config.lolicon_direct:
headers = {
'referer': f'https://www.pixiv.net/member_illust.php?mode=medium&illust_id={pid}'
}
proxy = config.proxy_url if config.lolicon_proxy else None
msg = f'Start Downloading Image With Pixiv.net -> PID: {pid}'
elif project == 'pixiv' and config.pixiv_direct:
headers = {
'referer': f'https://www.pixiv.net/member_illust.php?mode=medium&illust_id={pid}'
}
proxy = config.proxy_url if config.pixiv_proxy else None
msg = f'Start Downloading Image With Pixiv.net -> PID: {pid}'
logger.info(msg)
async with aiohttp.ClientSession(headers=headers, timeout=10) as session:
async with session.get(url, proxy=proxy) as req:
if req.status != 200:
data = False
else:
data = await req.read()
except:
logger.error(traceback.print_exc())
data = False
return data
async def get_random_setu(r18: int, limit: int, mode: int) -> Union[List[MessageSegment], bool]:
msg: list[MessageSegment] = []
setu = await Get_Random_Imginfo(r18, limit)
if setu['error']:
return setu['error']
elif not setu['data']:
return False
for data in setu['data']:
msg.append(await img_data(Data(**data), mode))
return msg
async def get_serach_setu(r18: int, limit: int, keyword: list, mode: int) -> Union[Dict[str, MessageSegment], bool]:
msg: list[MessageSegment] = []
setu = await Get_Imginfo(r18, keyword, limit)
if setu['error']:
return setu['error']
elif not setu['data']:
return False
for data in setu['data']:
msg.append(await img_data(Data(**data), mode))
return msg
async def img_data(data: Data, mode: int) -> Union[bool, list]:
url = data.urls['original'].replace('i.pixiv.cat', 'i.pixiv.re')
if mode != 2:
img = await Img_Download('lolicon', url, data.pid)
if not img:
logger.error('Image Download Fail')
return img
imgb64 = b2b64(img)
msg = f'''Title: {data.title}
Author: {data.author}
PixivID: {data.pid}'''
setu = MessageSegment.image(imgb64)
data = [msg, setu]
else:
data = [data.pid, url]
return data
|
import FWCore.ParameterSet.Config as cms
import copy
# AlCaReco for Bad Component Identification
OutALCARECOEcalTestPulsesRaw_noDrop = cms.PSet(
SelectEvents=cms.untracked.PSet(
SelectEvents=cms.vstring('pathALCARECOEcalTestPulsesRaw')
),
outputCommands=cms.untracked.vstring(
'keep FEDRawDataCollection_hltEcalCalibrationRaw_*_HLT',
'keep edmTriggerResults_*_*_HLT')
)
OutALCARECOEcalTestPulsesRaw = copy.deepcopy(OutALCARECOEcalTestPulsesRaw_noDrop)
OutALCARECOEcalTestPulsesRaw.outputCommands.insert(0, "drop *")
|
# Copyright 2018 Digital Domain 3.0
#
# Licensed under the Apache License, Version 2.0 (the "Apache License")
# with the following modification; you may not use this file except in
# compliance with the Apache License and the following modification to it:
# Section 6. Trademarks. is deleted and replaced with:
#
# 6. Trademarks. This License does not grant permission to use the trade
# names, trademarks, service marks, or product names of the Licensor
# and its affiliates, except as required to comply with Section 4(c) of
# the License and to reproduce the content of the NOTICE file.
#
# You may obtain a copy of the Apache License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the Apache License with the above modification is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the Apache License for the specific
# language governing permissions and limitations under the Apache License.
"""
The imports module is designed to fix the import statements.
"""
import traceback
from qt_py_convert.general import ALIAS_DICT, change, supported_binding
from qt_py_convert.color import color_text, ANSI
from qt_py_convert.log import get_logger
EXPAND_STARS_LOG = get_logger("expand_stars")
class Processes(object):
"""Processes class for expand_stars"""
@staticmethod
def _get_children(binding, levels=None):
"""
You have done the following:
>>> from <binding>.<levels> import *
And I hate you a little bit.
I am changing it to the following:
>>> from <binding> import <levels>
But I don't know what the heck you used in the *
So I am just getting everything bootstrapped in. Sorry-not-sorry
"""
def _module_filtering(key):
import __builtin__
if key.startswith("__"):
return False
elif key in dir(__builtin__):
return False
return True
def _members(_mappings, _module_, module_name):
members = filter(_module_filtering, dir(_module))
for member in members:
mappings[member] = "{mod}.{member}".format(
mod=module_name,
member=member
)
mappings = {}
if levels is None:
levels = []
try:
_temp = __import__(binding, fromlist=levels)
except ImportError as err:
strerr = str(err).replace("No module named", "")
msg = (
"Attempting to resolve a * import from the {mod} "
"module failed.\n"
"This is usually because the module could not be imported. "
"Please check that this script can import it. The error was:\n"
"{err}"
).format(mod=strerr, err=str(err))
traceback.print_exc()
raise ImportError(msg)
if not levels:
_module = _temp
_members(mappings, _module, module_name=binding)
else:
for level in levels:
_module = getattr(_temp, level)
_members(mappings, _module, module_name=level)
return mappings
@classmethod
def _process_star(cls, red, stars, skip_lineno=False):
"""
_process_star is designed to replace from X import * methods.
:param red: redbaron process. Unused in this method.
:type red: redbardon.RedBaron
:param stars: List of redbaron nodes that matched for this proc.
:type stars: list
"""
mappings = {}
for star in stars:
from_import = star.parent
binding = from_import.value[0]
second_level_modules = None
if len(star.parent.value) > 1:
second_level_modules = [star.parent.value[1].dumps()]
if len(star.parent.value) > 2:
pass
children = cls._get_children(binding.dumps(), second_level_modules)
if second_level_modules is None:
second_level_modules = children
text = "from {binding} import {slm}".format(
binding="Qt",
slm=", ".join([name for name in second_level_modules])
)
change(
logger=EXPAND_STARS_LOG,
node=star.parent,
replacement=text,
skip_lineno=skip_lineno
)
mappings.update(children)
# star.replace(
# text
# )
return mappings
EXPAND_STR = "EXPAND"
EXPAND = _process_star
def star_process(store):
"""
star_process is one of the more complex handlers for the _modules.
:param store: Store is the issues dict defined in "process"
:type store: dict
:return: The filter_function callable.
:rtype: callable
"""
def filter_function(value):
for target in value.parent.targets:
if target.type == "star" and supported_binding(value.dumps()):
store[Processes.EXPAND_STR].add(value)
return True
return filter_function
def process(red, skip_lineno=False, **kwargs):
"""
process is the main function for the import process.
:param red: Redbaron ast.
:type red: redbaron.redbaron
:param skip_lineno: An optional performance flag. By default, when the
script replaces something, it will tell you which line it is
replacing on. This can be useful for tracking the places that
changes occurred. When you turn this flag on however, it will not
show the line numbers. This can give great performance increases
because redbaron has trouble calculating the line number sometimes.
:type skip_lineno: bool
:param kwargs: Any other kwargs will be ignored.
:type kwargs: dict
"""
issues = {
Processes.EXPAND_STR: set(),
}
EXPAND_STARS_LOG.warning(color_text(
text="\"import star\" used. We are bootstrapping code!",
color=ANSI.colors.red,
))
EXPAND_STARS_LOG.warning(color_text(
text="This will be very slow. It's your own fault.",
color=ANSI.colors.red,
))
values = red.find_all("FromImportNode", value=star_process(issues))
mappings = getattr(Processes, Processes.EXPAND_STR)(
red, issues[Processes.EXPAND_STR], skip_lineno=skip_lineno
)
return ALIAS_DICT, mappings
|
"""Object utilities."""
from __future__ import absolute_import, unicode_literals
from copy import copy
from .connection import maybe_channel
from .exceptions import NotBoundError
from .five import python_2_unicode_compatible
from .utils.functional import ChannelPromise
__all__ = ('Object', 'MaybeChannelBound')
def unpickle_dict(cls, kwargs):
return cls(**kwargs)
def _any(v):
return v
class Object(object):
"""Common base class.
Supports automatic kwargs->attributes handling, and cloning.
"""
attrs = ()
def __init__(self, *args, **kwargs):
for name, type_ in self.attrs:
value = kwargs.get(name)
if value is not None:
setattr(self, name, (type_ or _any)(value))
else:
try:
getattr(self, name)
except AttributeError:
setattr(self, name, None)
def as_dict(self, recurse=False):
def f(obj, type):
if recurse and isinstance(obj, Object):
return obj.as_dict(recurse=True)
return type(obj) if type and obj is not None else obj
return {
attr: f(getattr(self, attr), type) for attr, type in self.attrs
}
def __reduce__(self):
return unpickle_dict, (self.__class__, self.as_dict())
def __copy__(self):
return self.__class__(**self.as_dict())
@python_2_unicode_compatible
class MaybeChannelBound(Object):
"""Mixin for classes that can be bound to an AMQP channel."""
_channel = None
_is_bound = False
#: Defines whether maybe_declare can skip declaring this entity twice.
can_cache_declaration = False
def __call__(self, channel):
"""`self(channel) -> self.bind(channel)`."""
return self.bind(channel)
def bind(self, channel):
"""Create copy of the instance that is bound to a channel."""
return copy(self).maybe_bind(channel)
def maybe_bind(self, channel):
"""Bind instance to channel if not already bound."""
if not self.is_bound and channel:
self._channel = maybe_channel(channel)
self.when_bound()
self._is_bound = True
return self
def revive(self, channel):
"""Revive channel after the connection has been re-established.
Used by :meth:`~kombu.Connection.ensure`.
"""
if self.is_bound:
self._channel = channel
self.when_bound()
def when_bound(self):
"""Callback called when the class is bound."""
pass
def __repr__(self):
return self._repr_entity(type(self).__name__)
def _repr_entity(self, item=''):
item = item or type(self).__name__
if self.is_bound:
return '<{0} bound to chan:{1}>'.format(
item or type(self).__name__, self.channel.channel_id)
return '<unbound {0}>'.format(item)
@property
def is_bound(self):
"""Flag set if the channel is bound."""
return self._is_bound and self._channel is not None
@property
def channel(self):
"""Current channel if the object is bound."""
channel = self._channel
if channel is None:
raise NotBoundError(
"Can't call method on {0} not bound to a channel".format(
type(self).__name__))
if isinstance(channel, ChannelPromise):
channel = self._channel = channel()
return channel
|
from qiwi_handler.utils.methods import MakeDict
class MobilePinInfo(MakeDict):
def __init__(self,
mobile_pin_used: bool = None,
last_mobile_pin_change: bool = None,
next_mobile_pin_change: str = None,
):
self.mobilePinUsed = mobile_pin_used
self.lastMobilePinChange = last_mobile_pin_change
self.nextMobilePinChange = next_mobile_pin_change
|
def increase_number_roundness(n):
return '0' in str(n).rstrip('0')
if __name__ == '__main__':
n = 902200100
print(increase_number_roundness(n))
|
# -*- coding: utf-8 -*-
# _ __
# | |/ /___ ___ _ __ ___ _ _ ®
# | ' </ -_) -_) '_ \/ -_) '_|
# |_|\_\___\___| .__/\___|_|
# |_|
#
# Keeper Commander
# Copyright 2018 Keeper Security Inc.
# Contact: ops@keepersecurity.com
#
from ldap3 import Server, Connection, ALL
"""Commander Plugin for Active Directory
Dependencies:
pip3 install ldap3
"""
def rotate(record, newpassword):
result = False
old_password = record.password
host = record.get('cmdr:host')
port = record.get('cmdr:port') or '389'
user_dn = record.get('cmdr:userdn')
use_ssl = record.get('cmdr:use_ssl')
try:
# print('Connecting to ' + host)
server = Server(
host=host,
port=int(port),
use_ssl=(use_ssl in ['True','true','yes','Yes','y','Y','T','t']),
get_info=ALL)
conn = Connection(
server=server,
user=user_dn,
password=record.password,
auto_bind=True)
# print('Connection: ' + str(conn))
# print('Server Info: ' + str(server.info))
# print('Whoami: ' + str(conn.extend.standard.who_am_i()))
changePwdResult = conn.extend.microsoft.modify_password(
user=user_dn, new_password=newpassword, old_password=old_password)
if (changePwdResult == True):
print('Password changed successfully')
record.password = newpassword
result = True
else:
print('Error with adpasswd change: ' + conn.result)
conn.unbind()
except Exception as e:
print("Error during connection to AD server: %s" % e)
return result
|
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