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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
7f323a424962078f0d541730b2a001b0d6f3bd66 | 524 | py | Python | guppe/atividades/secao_7/ex030.py | WesleyLucas97/cursos_python | b2cbd393e8fed6e36b84253f7934766f2b4f1de8 | [
"MIT"
] | null | null | null | guppe/atividades/secao_7/ex030.py | WesleyLucas97/cursos_python | b2cbd393e8fed6e36b84253f7934766f2b4f1de8 | [
"MIT"
] | null | null | null | guppe/atividades/secao_7/ex030.py | WesleyLucas97/cursos_python | b2cbd393e8fed6e36b84253f7934766f2b4f1de8 | [
"MIT"
] | null | null | null | """
Faça um programa que leia dois vetores de 10 elementos. Crie um vetor que seja a intersecçao entre os 2 vetores
anteriores, ou seja, que contém apenas os números que estao em ambos os vetores. Nao deve conter números repetidos.
"""
from random import randint
vetor1 = []
vetor2 = []
inter = []
for x in range(10):
vetor1.append(randint(0, 200))
vetor2.append(randint(0, 200))
for x in vetor1:
if x in vetor2:
if x not in inter:
inter.append(x)
print(vetor1)
print(vetor2)
print(inter)
| 23.818182 | 115 | 0.69084 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 240 | 0.453686 |
7f3456525e16a28ff65bdae2bcdeda6075e74b3f | 343 | py | Python | tests/internal/instance_type/test_instance_type_h_auto.py | frolovv/aws.ec2.compare | 582805823492f833d65c0441c4a14dce697c12aa | [
"Apache-2.0"
] | null | null | null | tests/internal/instance_type/test_instance_type_h_auto.py | frolovv/aws.ec2.compare | 582805823492f833d65c0441c4a14dce697c12aa | [
"Apache-2.0"
] | null | null | null | tests/internal/instance_type/test_instance_type_h_auto.py | frolovv/aws.ec2.compare | 582805823492f833d65c0441c4a14dce697c12aa | [
"Apache-2.0"
] | 1 | 2021-12-15T11:58:22.000Z | 2021-12-15T11:58:22.000Z |
# Testing module instance_type.h
import pytest
import ec2_compare.internal.instance_type.h
def test_get_internal_data_instance_type_h_get_instances_list():
assert len(ec2_compare.internal.instance_type.h.get_instances_list()) > 0
def test_get_internal_data_instance_type_h_get():
assert len(ec2_compare.internal.instance_type.h.get) > 0
| 34.3 | 75 | 0.845481 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 32 | 0.093294 |
7f350b0e080d9eba4c1970d4cf3a06f36a964718 | 1,529 | py | Python | gridSearch.py | piotrbla/pyExamples | d949784e614da53afc05a1245c824d0b853d8234 | [
"MIT"
] | null | null | null | gridSearch.py | piotrbla/pyExamples | d949784e614da53afc05a1245c824d0b853d8234 | [
"MIT"
] | null | null | null | gridSearch.py | piotrbla/pyExamples | d949784e614da53afc05a1245c824d0b853d8234 | [
"MIT"
] | null | null | null | #!/bin/python3
import sys
# t = int(input().strip())
# for a0 in range(t):
# G = [
# "7283455864",
# "6731158619",
# "8988242643",
# "3830589324",
# "2229505813",
# "5633845374",
# "6473530293",
# "7053106601",
# "0834282956",
# "4607924137"
# ]
# P = ["9505", "3845", "3530"]
G = [
"123412",
"561212",
"123634",
"781288"
]
P = ["12","34"]
def myfind(s, toFind):
found = []
pos = s.find(toFind, 0)
while(pos>-1):
found.append(pos)
if pos+1>len(s):
break
pos = s.find(toFind, pos+1)
return found
if True:
# print(G)
# print(P)
if P:
found = False
s = P[0]
gCount = 0
for gs in G:
if s in gs:
positions = myfind(gs, s)
gInnerCount = gCount - 1
if len(G) - gCount < len(P):
found = False
continue
found = True
for ps in P:
gInnerCount += 1
if ps in G[gInnerCount]:
positions = list(set(positions).intersection(myfind(G[gInnerCount], ps)))
if positions:
continue
found = False
break
if found:
break;
gCount += 1
if found:
print("YES")
else:
print("NO")
else:
print("NO")
| 22.485294 | 97 | 0.400916 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 363 | 0.23741 |
7f3544b7340939d1a01b2aecf308475476d4e6eb | 1,764 | py | Python | rollbar_udp_agent/util.py | lrascao/rollbar-udp-agent | 51c698837e5141bff5fef3e20afe7301c3ecdf27 | [
"MIT"
] | 1 | 2015-05-27T21:48:42.000Z | 2015-05-27T21:48:42.000Z | rollbar_udp_agent/util.py | lrascao/rollbar-udp-agent | 51c698837e5141bff5fef3e20afe7301c3ecdf27 | [
"MIT"
] | null | null | null | rollbar_udp_agent/util.py | lrascao/rollbar-udp-agent | 51c698837e5141bff5fef3e20afe7301c3ecdf27 | [
"MIT"
] | null | null | null | import os
import logging
import tempfile
log = logging.getLogger(__name__)
class PidFile(object):
""" A small helper class for pidfiles. """
PID_DIR = '/var/run/rollbard'
def __init__(self, program, pid_dir=None):
self.pid_file = "%s.pid" % program
self.pid_dir = pid_dir or self.get_default_pid_dir()
self.pid_path = os.path.join(self.pid_dir, self.pid_file)
def get_default_pid_dir(self):
return PidFile.PID_DIR
def get_path(self):
# Can we write to the directory
try:
if os.access(self.pid_dir, os.W_OK):
log.info("Pid file is: %s" % self.pid_path)
return self.pid_path
except Exception:
log.warn("Cannot locate pid file, trying to use: %s" % tempfile.gettempdir())
# if all else fails
if os.access(tempfile.gettempdir(), os.W_OK):
tmp_path = os.path.join(tempfile.gettempdir(), self.pid_file)
log.debug("Using temporary pid file: %s" % tmp_path)
return tmp_path
else:
# Can't save pid file, bail out
log.error("Cannot save pid file anywhere")
raise Exception("Cannot save pid file anywhere")
def clean(self):
try:
path = self.get_path()
log.debug("Cleaning up pid file %s" % path)
os.remove(path)
return True
except Exception:
log.warn("Could not clean up pid file")
return False
def get_pid(self):
"Retrieve the actual pid"
try:
pf = open(self.get_path())
pid_s = pf.read()
pf.close()
return int(pid_s.strip())
except Exception:
return None
| 29.898305 | 89 | 0.570862 | 1,686 | 0.955782 | 0 | 0 | 0 | 0 | 0 | 0 | 381 | 0.215986 |
7f35a101be268b4de55d1e3fbef7b0fc92eca07c | 1,388 | py | Python | server/migrations/0019_auto_20151124_1806.py | gregneagle/sal | 74c583fb1c1b33d3201b308b147376b3dcaca33f | [
"Apache-2.0"
] | 2 | 2019-11-01T20:50:35.000Z | 2021-01-13T22:02:55.000Z | server/migrations/0019_auto_20151124_1806.py | gregneagle/sal | 74c583fb1c1b33d3201b308b147376b3dcaca33f | [
"Apache-2.0"
] | null | null | null | server/migrations/0019_auto_20151124_1806.py | gregneagle/sal | 74c583fb1c1b33d3201b308b147376b3dcaca33f | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
class Migration(migrations.Migration):
dependencies = [
('server', '0018_auto_20151124_1654'),
]
operations = [
migrations.CreateModel(
name='UpdateHistoryItem',
fields=[
('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)),
('recorded', models.DateTimeField()),
('status', models.CharField(max_length=255, verbose_name=b'Status', choices=[(b'pending', b'Pending'), (b'error', b'Error'), (b'success', b'Success')])),
],
),
migrations.AlterModelOptions(
name='updatehistory',
options={'ordering': ['name']},
),
migrations.AlterUniqueTogether(
name='updatehistory',
unique_together=set([('machine', 'name', 'version')]),
),
migrations.AddField(
model_name='updatehistoryitem',
name='update_history',
field=models.ForeignKey(to='server.UpdateHistory'),
),
migrations.RemoveField(
model_name='updatehistory',
name='recorded',
),
migrations.RemoveField(
model_name='updatehistory',
name='status',
),
]
| 31.545455 | 169 | 0.561239 | 1,279 | 0.92147 | 0 | 0 | 0 | 0 | 0 | 0 | 341 | 0.245677 |
7f3657c2007cb8e2fe9ba1e91d9490a327ac7d62 | 3,624 | py | Python | libc/kernel/tools/update_all.py | Keneral/abionic | 0f441ff93f011ed0069339e16f59e572134a5f3b | [
"Unlicense"
] | null | null | null | libc/kernel/tools/update_all.py | Keneral/abionic | 0f441ff93f011ed0069339e16f59e572134a5f3b | [
"Unlicense"
] | null | null | null | libc/kernel/tools/update_all.py | Keneral/abionic | 0f441ff93f011ed0069339e16f59e572134a5f3b | [
"Unlicense"
] | null | null | null | #!/usr/bin/env python
#
import sys, cpp, kernel, glob, os, re, getopt, clean_header, subprocess
from defaults import *
from utils import *
def usage():
print """\
usage: %(progname)s [kernel-original-path] [kernel-modified-path]
this program is used to update all the auto-generated clean headers
used by the Bionic C library. it assumes the following:
- a set of source kernel headers is located in
'external/kernel-headers/original', relative to the current
android tree
- a set of manually modified kernel header files located in
'external/kernel-headers/modified', relative to the current
android tree
- the clean headers will be placed in 'bionic/libc/kernel/arch-<arch>/asm',
'bionic/libc/kernel/common', etc..
""" % { "progname" : os.path.basename(sys.argv[0]) }
sys.exit(0)
try:
optlist, args = getopt.getopt(sys.argv[1:], '')
except:
# unrecognized option
sys.stderr.write("error: unrecognized option\n")
usage()
if len(optlist) > 0 or len(args) > 2:
usage()
modified_dir = get_kernel_headers_modified_dir()
if len(args) == 1 or len(args) == 2:
original_dir = args[0]
if not os.path.isdir(original_dir):
panic("Not a directory: %s\n" % original_dir)
if len(args) == 2:
modified_dir = args[1]
if not os.path.isdir(modified_dir):
panic("Not a directory: %s\n" % modified_dir)
else:
original_dir = get_kernel_headers_original_dir()
if not os.path.isdir(original_dir):
panic("Missing directory, please specify one through command-line: %s\n" % original_dir)
if not os.path.isdir(modified_dir):
modified_dir = None
# Find all source files in 'original'.
sources = dict()
original_dir = os.path.normpath(original_dir)
original_dir_len = len(original_dir) + 1
for root, _, files in os.walk(original_dir):
for file in files:
_, ext = os.path.splitext(file)
if ext == ".h":
rel_path = os.path.normpath(os.path.join(root, file))
rel_path = rel_path[original_dir_len:]
# Check to see if there is a modified header to use instead.
if modified_dir and os.path.exists(os.path.join(modified_dir, rel_path)):
sources[rel_path] = False
else:
sources[rel_path] = True
b = BatchFileUpdater()
kernel_dir = get_kernel_dir()
for arch in kernel_archs:
b.readDir(os.path.join(kernel_dir, "arch-%s" % arch))
b.readDir(os.path.join(kernel_dir, "common"))
oldlen = 120
android_root_len = len(get_android_root()) + 1
for rel_path in sorted(sources):
if sources[rel_path]:
src_dir = original_dir
src_str = "<original>/"
else:
src_dir = modified_dir
src_str = "<modified>/"
dst_path, newdata = clean_header.cleanupFile(kernel_dir, src_dir, rel_path)
if not dst_path:
continue
dst_path = os.path.join(kernel_dir, dst_path)
b.readFile(dst_path)
r = b.editFile(dst_path, newdata)
if r == 0:
state = "unchanged"
elif r == 1:
state = "edited"
else:
state = "added"
# dst_path is guaranteed to include android root.
rel_dst_path = dst_path[android_root_len:]
str = "cleaning: %-*s -> %-*s (%s)" % (35, src_str + rel_path, 35, rel_dst_path, state)
if sys.stdout.isatty():
print "%-*s" % (oldlen, str),
if (r == 0):
print "\r",
else:
print "\n",
oldlen = 0
else:
print str
oldlen = len(str)
print "%-*s" % (oldlen, "Done!")
b.updateGitFiles()
sys.exit(0)
| 29.463415 | 96 | 0.631347 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,107 | 0.305464 |
7f36be3439ad38bb0d3934200cfedbede2aee704 | 1,816 | py | Python | binding/python/ddls/feeder/batch.py | huzelin/ddls | 3333a669c59ce2e525945f814a54784dafc6191b | [
"MIT"
] | 3 | 2019-01-03T07:34:01.000Z | 2020-02-13T19:53:35.000Z | binding/python/ddls/feeder/batch.py | huzelin/ddls | 3333a669c59ce2e525945f814a54784dafc6191b | [
"MIT"
] | null | null | null | binding/python/ddls/feeder/batch.py | huzelin/ddls | 3333a669c59ce2e525945f814a54784dafc6191b | [
"MIT"
] | 1 | 2020-05-06T11:08:07.000Z | 2020-05-06T11:08:07.000Z | """ batch iterator"""
from __future__ import absolute_import
import ctypes
from ddls.base import check_call, LIB, c_str, c_array
from ddls.hpps.tensor import Tensor
class Batch(object):
""" The BatchIterator
"""
def __init__(self, handle):
""" The batch from iterator
"""
self.handle = handle
def __del__(self):
""" Delete tensor
"""
check_call(LIB.HPPS_BatchDestroy(self.handle))
def get_tensor(self, name):
""" Return the tensor according to name
"""
out = ctypes.c_void_p()
check_call(LIB.HPPS_BatchGetTensorFromKey(self.handle,
c_str(name),
ctypes.byref(out)))
return Tensor(handle=out, shape=None, type=None)
def names(self):
""" Return the names of tensor
"""
out_names = ctypes.POINTER(ctypes.c_char_p)()
out_size = ctypes.c_int()
check_call(LIB.HPPS_BatchGetKeys(self.handle,
ctypes.byref(out_size),
ctypes.byref(out_names)))
return tuple(out_names[:out_size.value])
def add_indices_tensor(self, names_array):
""" add indices tensor
"""
check_call(LIB.HPPS_AddIndicesTensor(self.handle,
len(names_array),
c_array(ctypes.c_char_p, names_array)))
def add_uniqid_tensor(self, names_array):
""" add uniqid tensor
"""
check_call(LIB.HPPS_AddUniqIdTensor(self.handle,
len(names_array),
c_array(ctypes.c_char_p, names_array)))
| 32.428571 | 84 | 0.522026 | 1,645 | 0.905837 | 0 | 0 | 0 | 0 | 0 | 0 | 279 | 0.153634 |
7f373e1985a3fef43fa656105237573ff16bc399 | 3,520 | py | Python | pymoo/util/ref_dirs/energy_layer.py | jarreguit/pymoo | 0496a3c6765826148d8bab21650736760517dd25 | [
"Apache-2.0"
] | 762 | 2018-06-05T20:56:09.000Z | 2021-09-14T09:09:42.000Z | pymoo/util/ref_dirs/energy_layer.py | jarreguit/pymoo | 0496a3c6765826148d8bab21650736760517dd25 | [
"Apache-2.0"
] | 176 | 2018-09-05T18:37:05.000Z | 2021-09-14T01:18:43.000Z | pymoo/util/ref_dirs/energy_layer.py | jarreguit/pymoo | 0496a3c6765826148d8bab21650736760517dd25 | [
"Apache-2.0"
] | 160 | 2018-08-05T05:31:20.000Z | 2021-09-14T09:09:45.000Z | import autograd.numpy as anp
import numpy as np
from autograd import value_and_grad
from pymoo.factory import normalize
from pymoo.util.ref_dirs.energy import squared_dist
from pymoo.util.ref_dirs.optimizer import Adam
from pymoo.util.reference_direction import ReferenceDirectionFactory, scale_reference_directions
class LayerwiseRieszEnergyReferenceDirectionFactory(ReferenceDirectionFactory):
def __init__(self,
n_dim,
partitions,
return_as_tuple=False,
n_max_iter=1000,
verbose=False,
X=None,
**kwargs):
super().__init__(n_dim, **kwargs)
self.scalings = None
self.n_max_iter = n_max_iter
self.verbose = verbose
self.return_as_tuple = return_as_tuple
self.X = X
self.partitions = partitions
def _step(self, optimizer, X, scalings):
obj, grad = value_and_grad(calc_potential_energy)(scalings, X)
scalings = optimizer.next(scalings, np.array(grad))
scalings = normalize(scalings, xl=0, xu=scalings.max())
return scalings, obj
def _solve(self, X, scalings):
# initialize the optimizer for the run
optimizer = Adam()
# for each iteration of gradient descent
for i in range(self.n_max_iter):
# execute one optimization step
_scalings, _obj = self._step(optimizer, X, scalings)
# evaluate how much the points have moved
delta = np.abs(_scalings - scalings).sum()
if self.verbose:
print(i, "objective", _obj, "delta", delta)
# if there was only a little delta during the last iteration -> terminate
if delta < 1e-5:
scalings = _scalings
break
# otherwise use the new points for the next iteration
scalings = _scalings
self.scalings = scalings
return get_points(X, scalings)
def do(self):
X = []
scalings = []
for k, p in enumerate(self.partitions):
if p > 1:
val = np.linspace(0, 1, p + 1)[1:-1]
_X = []
for i in range(self.n_dim):
for j in range(i + 1, self.n_dim):
x = np.zeros((len(val), self.n_dim))
x[:, i] = val
x[:, j] = 1 - val
_X.append(x)
X.append(np.row_stack(_X + [np.eye(self.n_dim)]))
elif p == 1:
X.append(np.eye(self.n_dim))
else:
X.append(np.full(self.n_dim, 1 / self.n_dim)[None, :])
scalings.append(1 - k / len(self.partitions))
scalings = np.array(scalings)
X = self._solve(X, scalings)
return X
# ---------------------------------------------------------------------------------------------------------
# Energy Functions
# ---------------------------------------------------------------------------------------------------------
def get_points(X, scalings):
vals = []
for i in range(len(X)):
vals.append(scale_reference_directions(X[i], scalings[i]))
X = anp.row_stack(vals)
return X
def calc_potential_energy(scalings, X):
X = get_points(X, scalings)
i, j = anp.triu_indices(len(X), 1)
D = squared_dist(X, X)[i, j]
if np.any(D < 1e-12):
return np.nan, np.nan
return (1 / D).mean()
| 29.579832 | 107 | 0.52642 | 2,551 | 0.724716 | 0 | 0 | 0 | 0 | 0 | 0 | 526 | 0.149432 |
7f3776d641ecf1c2ca820e1d8531b10c65ba6e21 | 1,555 | py | Python | convert_pfm_json.py | biolib/deepclip | 06e0a3c431db76745b6674afabc4d171f19b3eb0 | [
"MIT"
] | 7 | 2019-07-23T10:20:11.000Z | 2022-03-14T14:46:13.000Z | convert_pfm_json.py | biolib/deepclip | 06e0a3c431db76745b6674afabc4d171f19b3eb0 | [
"MIT"
] | 10 | 2019-09-05T22:45:04.000Z | 2022-03-21T08:40:49.000Z | convert_pfm_json.py | biolib/deepclip | 06e0a3c431db76745b6674afabc4d171f19b3eb0 | [
"MIT"
] | 5 | 2019-07-23T10:20:46.000Z | 2021-11-14T07:18:05.000Z | #!/usr/bin/env python
import numpy as np
import matplotlib.pyplot as plt
import argparse
import json
parser = argparse.ArgumentParser()
parser.add_argument("-seqs",
required=True,
type=str,
default=None,
help="File containing sequences")
args = parser.parse_args()
dicts = []
with open(args.seqs,'r') as inf:
for line in inf:
dicts.append(eval(line))
try:
assert len(dicts) == 5
except AssertionError:
print "AssertionError: assert len(dicts) == 5"
print "len(dicts) =",str(len(dicts))
print str(dicts)
exit(1)
sizes = [4,5,6,7,8]
tot_info = []
for i in range(len(dicts)):
temp_pfm = np.array(dicts[i]['PFM_'+str(sizes[i])+'_0']).T
#print temp_pfm.shape
temp_pfm1 = temp_pfm + 0.000000001
tot_info.append([np.sum(np.log2(4) + np.sum(temp_pfm * np.log2(temp_pfm1), axis=1, keepdims = True))/len(temp_pfm), sizes[i]])
#print tot_info
tot_info.sort()
tot_info.reverse()
#print tot_info
new_json = {}
for mp in range(len(tot_info)):
for qq in range(len(dicts)):
if 'PFM_'+str(tot_info[mp][1])+'_0' in dicts[qq]:
print 'PFM_'+str(tot_info[mp][1])+'_0'
new_json['PFM_'+str(tot_info[mp][1])+'_0'] = dicts[qq]['PFM_'+str(tot_info[mp][1])+'_0']
with open('PFMs.json', 'w') as outfile:
json.dump(new_json, outfile)
with open('PFM_order.txt', 'w') as txt:
print >> txt, "name, info_per_bp"
for i in tot_info:
print >> txt, "PFM_" +str(i[1])+ "_0,", "{0:.3f}".format(i[0])
| 23.923077 | 130 | 0.607074 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 284 | 0.182637 |
7f38a2c200ca531dbe41a48a8f774eb63c7b3ea0 | 83 | py | Python | xmpt/apps.py | anzrz/djangoapp | 85b4f73754af53ddf33ec281a04a70415af02eb6 | [
"MIT"
] | 1 | 2021-04-23T14:19:33.000Z | 2021-04-23T14:19:33.000Z | xmpt/apps.py | anzrz/djangoapp | 85b4f73754af53ddf33ec281a04a70415af02eb6 | [
"MIT"
] | null | null | null | xmpt/apps.py | anzrz/djangoapp | 85b4f73754af53ddf33ec281a04a70415af02eb6 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class XmptConfig(AppConfig):
name = 'xmpt'
| 13.833333 | 33 | 0.73494 | 46 | 0.554217 | 0 | 0 | 0 | 0 | 0 | 0 | 6 | 0.072289 |
7f3bbf18433361fecef0405dbb0e62ddd2cecfda | 787 | py | Python | prc/fatigue.py | moulin1024/WIRELES2 | 2fcd190531d24e4f98885824c7d78acb3f79b304 | [
"MIT"
] | 3 | 2020-09-10T13:34:21.000Z | 2020-09-10T20:26:30.000Z | prc/fatigue.py | moulin1024/WIRELES2 | 2fcd190531d24e4f98885824c7d78acb3f79b304 | [
"MIT"
] | null | null | null | prc/fatigue.py | moulin1024/WIRELES2 | 2fcd190531d24e4f98885824c7d78acb3f79b304 | [
"MIT"
] | null | null | null | import numpy as np
import math
import fatpack
import matplotlib.pyplot as plt
import pandas as pd
#Create a function that reutrns the Goodman correction:
def Goodman_method_correction(M_a,M_m,M_max):
M_u = 1.5*M_max
M_ar = M_a/(1-M_m/M_u)
return M_ar
def Equivalent_bending_moment(M_ar,Neq,m):
P = M_ar.shape
M_sum = 0
j = P[0]
for i in range(j):
M_sum = math.pow(M_ar[i],m) + M_sum
M_eq = math.pow((M_sum/Neq),(1/m))
return M_eq
def get_DEL(y,Neq,m):
S, Sm = fatpack.find_rainflow_ranges(y.flatten(), return_means=True, k=256)
data_arr = np.array([Sm , S ]).T
M_ar = Goodman_method_correction(data_arr[:,1],data_arr[:,0],np.max(S))
print(sum(M_ar.shape))
M_eq = Equivalent_bending_moment(M_ar,Neq,m)
return M_eq
| 26.233333 | 79 | 0.673443 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 55 | 0.069886 |
7f3d359af8382d37dc10d0318477d716c6a3d982 | 12,040 | py | Python | executor/process.py | xolox/python-executor | ea14d75ae3533fcc2f32554dd3ae1f6061c2c24c | [
"MIT"
] | 82 | 2015-03-03T17:12:28.000Z | 2022-02-11T21:54:15.000Z | executor/process.py | xolox/python-executor | ea14d75ae3533fcc2f32554dd3ae1f6061c2c24c | [
"MIT"
] | 19 | 2015-03-03T17:12:13.000Z | 2022-03-11T19:24:58.000Z | executor/process.py | xolox/python-executor | ea14d75ae3533fcc2f32554dd3ae1f6061c2c24c | [
"MIT"
] | 19 | 2016-10-15T02:53:58.000Z | 2021-07-22T15:28:25.000Z | # Programmer friendly subprocess wrapper.
#
# Author: Peter Odding <peter@peterodding.com>
# Last Change: March 2, 2020
# URL: https://executor.readthedocs.io
"""
Portable process control functionality for the `executor` package.
The :mod:`executor.process` module defines the :class:`ControllableProcess`
abstract base class which enables process control features like waiting for a
process to end, gracefully terminating it and forcefully killing it. The
process control functionality in :class:`ControllableProcess` is separated from
the command execution functionality in :class:`~executor.ExternalCommand` to
make it possible to re-use the process control functionality in other Python
packages, see for example the :class:`proc.core.Process` class.
"""
# Standard library modules.
import logging
# External dependencies.
from humanfriendly import Timer
from humanfriendly.terminal.spinners import Spinner
from property_manager import PropertyManager, mutable_property, required_property
# Initialize a logger for this module.
logger = logging.getLogger(__name__)
DEFAULT_TIMEOUT = 10
"""The default timeout used to wait for process termination (number of seconds)."""
class ControllableProcess(PropertyManager):
"""
Abstract, portable process control functionality.
By defining a subclass of :class:`ControllableProcess` and implementing the
:attr:`pid`, :attr:`command_line` and :attr:`is_running` properties and the
:func:`terminate_helper()` and :func:`kill_helper()` methods you get the
:func:`wait_for_process()`, :func:`terminate()` and :func:`kill()` methods
for free. This decoupling has enabled me to share a lot of code between two
Python projects of mine with similar goals but very different
requirements:
1. The `executor` package builds on top of the :mod:`subprocess` module
in the Python standard library and strives to be as cross platform
as possible. This means things like UNIX signals are not an option
(although signals exist on Windows they are hardly usable). The package
mostly deals with :class:`subprocess.Popen` objects internally (to hide
platform specific details as much as possible).
2. The proc_ package exposes process information available in the Linux
process information pseudo-file system available at ``/proc``. The
package mostly deals with process IDs internally. Because this is
completely specialized to a UNIX environment the use of things
like UNIX signals is not a problem at all.
.. _proc: http://proc.readthedocs.org/en/latest/
"""
@mutable_property
def command_line(self):
"""
A list of strings with the command line used to start the process.
This property may be set or implemented by subclasses to enable
:func:`__str__()` to render a human friendly representation of a
:class:`ControllableProcess` object.
"""
return []
@property
def is_running(self):
"""
:data:`True` if the process is running, :data:`False` otherwise.
This property must be implemented by subclasses to enable
:func:`wait_for_process()`, :func:`terminate()` and :func:`kill()` to
work properly.
"""
raise NotImplementedError("You need to implement the `is_running' property!")
@mutable_property
def logger(self):
"""
The :class:`logging.Logger` object to use (defaults to the :mod:`executor.process` logger).
If you are using Python's :mod:`logging` module and you find it
confusing that command manipulation is logged under the
:mod:`executor.process` name space instead of the name space of the
application or library using :mod:`executor` you can set this
attribute to inject a custom (and more appropriate) logger.
"""
return logger
@mutable_property
def pid(self):
"""
The process ID (a number) or :data:`None`.
This property must be set or implemented by subclasses:
- It provides :func:`wait_for_process()` with a short and unique
representation of a process that most users will understand.
- It enables :func:`__str__()` to render a human friendly
representation of a :class:`ControllableProcess` object.
"""
def wait_for_process(self, timeout=0, use_spinner=None):
"""
Wait until the process ends or the timeout expires.
:param timeout: The number of seconds to wait for the process to
terminate after we've asked it nicely (defaults
to zero which means we wait indefinitely).
:param use_spinner: Whether or not to display an interactive spinner
on the terminal (using :class:`~humanfriendly.Spinner`)
to explain to the user what they are waiting for:
- :data:`True` enables the spinner,
- :data:`False` disables the spinner,
- :data:`None` (the default) means the spinner is
enabled when the program is connected to an
interactive terminal, otherwise it's disabled.
:returns: A :class:`~humanfriendly.Timer` object telling you how long
it took to wait for the process.
"""
with Timer(resumable=True) as timer:
with Spinner(interactive=use_spinner, timer=timer) as spinner:
while self.is_running:
if timeout and timer.elapsed_time >= timeout:
break
spinner.step(label="Waiting for process %i to terminate" % self.pid)
spinner.sleep()
return timer
def terminate(self, wait=True, timeout=DEFAULT_TIMEOUT, use_spinner=None):
"""
Gracefully terminate the process.
:param wait: Whether to wait for the process to end (a boolean,
defaults to :data:`True`).
:param timeout: The number of seconds to wait for the process to
terminate after we've signaled it (defaults to
:data:`DEFAULT_TIMEOUT`). Zero means to wait
indefinitely.
:param use_spinner: See the :func:`wait_for_process()` documentation.
:returns: :data:`True` if the process was terminated, :data:`False`
otherwise.
:raises: Any exceptions raised by :func:`terminate_helper()`
implementations of subclasses or :func:`kill()`.
This method works as follows:
1. Signal the process to gracefully terminate itself. Processes can
choose to intercept termination signals to allow for graceful
termination (many UNIX daemons work like this) however the default
action is to simply exit immediately.
2. If `wait` is :data:`True` and we've signaled the process, we wait
for it to terminate gracefully or `timeout` seconds have passed
(whichever comes first).
3. If `wait` is :data:`True` and the process is still running after
`timeout` seconds have passed, it will be forcefully terminated
using :func:`kill()` (the value of `timeout` that was given to
:func:`terminate()` will be passed on to :func:`kill()`).
This method does nothing when :attr:`is_running` is :data:`False`.
"""
if self.is_running:
self.logger.info("Gracefully terminating process %s ..", self)
self.terminate_helper()
if wait:
timer = self.wait_for_process(timeout=timeout, use_spinner=use_spinner)
if self.is_running:
self.logger.warning("Failed to gracefully terminate process! (waited %s)", timer)
return self.kill(wait=True, timeout=timeout)
else:
self.logger.info("Successfully terminated process in %s.", timer)
return True
return not self.is_running
else:
return False
def terminate_helper(self):
"""Request the process to gracefully terminate itself (needs to be implemented by subclasses)."""
raise NotImplementedError("You need to implement the terminate_helper() method!")
def kill(self, wait=True, timeout=DEFAULT_TIMEOUT, use_spinner=None):
"""
Forcefully kill the process.
:param wait: Whether to wait for the process to end (a boolean,
defaults to :data:`True`).
:param timeout: The number of seconds to wait for the process to
terminate after we've signaled it (defaults to
:data:`DEFAULT_TIMEOUT`). Zero means to wait
indefinitely.
:param use_spinner: See the :func:`wait_for_process()` documentation.
:returns: :data:`True` if the process was killed, :data:`False`
otherwise.
:raises: - Any exceptions raised by :func:`kill_helper()`
implementations of subclasses.
- :exc:`ProcessTerminationFailed` if the process is still
running after :func:`kill_helper()` and
:func:`wait_for_process()` have been called.
This method does nothing when :attr:`is_running` is :data:`False`.
"""
if self.is_running:
self.logger.info("Forcefully killing process %s ..", self)
self.kill_helper()
if wait:
timer = self.wait_for_process(timeout=timeout, use_spinner=use_spinner)
if self.is_running:
self.logger.warning("Failed to forcefully kill process! (waited %s)", timer)
raise ProcessTerminationFailed(process=self, message="Failed to kill process! (%s)" % self)
else:
self.logger.info("Successfully killed process in %s.", timer)
return True
return not self.is_running
else:
return False
def kill_helper(self):
"""Forcefully kill the process (needs to be implemented by subclasses)."""
raise NotImplementedError("You need to implement the kill_helper() method!")
def __str__(self):
"""
Render a human friendly representation of a :class:`ControllableProcess` object.
:returns: A string describing the process. Includes the process ID and the
command line (when available).
"""
text = []
# Include the process ID? (only when it's available)
if self.pid is not None:
text.append(str(self.pid))
# Include the command line? (again, only when it's available)
if self.command_line:
# We import here to avoid circular imports.
from executor import quote
text.append("(%s)" % quote(self.command_line))
if not text:
# If all else fails we fall back to the super class.
text.append(object.__str__(self))
return " ".join(text)
class ProcessTerminationFailed(PropertyManager, Exception):
"""Raised when process termination fails."""
def __init__(self, *args, **kw):
"""
Initialize a :class:`ProcessTerminationFailed` object.
This method's signature is the same as the initializer of the
:class:`~property_manager.PropertyManager` class.
"""
PropertyManager.__init__(self, *args, **kw)
Exception.__init__(self, self.message)
@required_property(usage_notes=False)
def process(self):
"""The :class:`ControllableProcess` object that triggered the exception."""
@required_property(usage_notes=False)
def message(self):
"""An error message that explains how the process termination failed."""
| 43.623188 | 111 | 0.635133 | 10,854 | 0.901495 | 0 | 0 | 2,015 | 0.167359 | 0 | 0 | 8,845 | 0.734635 |
7f3df3dc967b1922f0d38e1d9051faca1358ecc7 | 10,945 | py | Python | lambda/qldb/import_transport_product.py | UBC-CIC/VaccineDistribution | 3bd8d507eaabcf3a3213ec7c1d25127dd221c537 | [
"MIT"
] | null | null | null | lambda/qldb/import_transport_product.py | UBC-CIC/VaccineDistribution | 3bd8d507eaabcf3a3213ec7c1d25127dd221c537 | [
"MIT"
] | null | null | null | lambda/qldb/import_transport_product.py | UBC-CIC/VaccineDistribution | 3bd8d507eaabcf3a3213ec7c1d25127dd221c537 | [
"MIT"
] | null | null | null | from logging import basicConfig, getLogger, INFO
from connect_to_ledger import create_qldb_driver
from amazon.ion.simpleion import dumps, loads
logger = getLogger(__name__)
basicConfig(level=INFO)
from constants import Constants
from register_person import get_scentityid_from_personid,get_scentity_contact
from sampledata.sample_data import get_value_from_documentid,document_exist,update_document
from check_container_safety import isContainerSafe
from create_purchase_order_to_manufacturer import get_sub_details
from export_transport_product import create_lorry_reciept, update_document_in_container
from export_customs_approval import document_already_approved_by_customs
import copy
def deliver_product_to_distributor(transaction_executor,pick_up_request_id,pick_up_person_id):
if document_exist(transaction_executor,Constants.PICK_UP_REQUESTS_TABLE,pick_up_request_id):
update_document(transaction_executor,Constants.PICK_UP_REQUESTS_TABLE,"isAccepted",pick_up_request_id,True)
purchase_order_id = get_value_from_documentid(transaction_executor,Constants.PICK_UP_REQUESTS_TABLE, pick_up_request_id, "PurchaseOrderId")
purchase_order_id = purchase_order_id[0]
container_ids = get_value_from_documentid(transaction_executor,Constants.PURCHASE_ORDER_TABLE_NAME,purchase_order_id,"HighestPackagingLevelIds")
for container_id in container_ids[0]:
total_containers_ordered = len(container_ids[0])
if document_exist(transaction_executor,Constants.CONTAINER_TABLE_NAME,container_id):
#check if container_exist
certificate_of_origin_id = get_value_from_documentid(transaction_executor,Constants.CONTAINER_TABLE_NAME,container_id,"CertificateOfOriginId")
packing_list_id = get_value_from_documentid(transaction_executor, Constants.CONTAINER_TABLE_NAME,container_id,"PackingListId")
import_custom_approved = (document_already_approved_by_customs(transaction_executor,"ImportApproval",Constants.CERTIFICATE_OF_ORIGIN_TABLE_NAME,certificate_of_origin_id[0]) and
document_already_approved_by_customs(transaction_executor,"ImportApproval", Constants.PACKING_LIST_TABLE_NAME,packing_list_id[0]))
if import_custom_approved:
logger.info("Approved by Import!")
total_safe_containers = copy.copy(total_containers_ordered)
if isContainerSafe(transaction_executor,container_id):
actual_sc_entity_id = get_scentityid_from_personid(transaction_executor,pick_up_person_id)
transport_type = get_value_from_documentid(transaction_executor,Constants.CONTAINER_TABLE_NAME,container_id,"TransportType")
#check if container is safe
if transport_type[0] == 1:
table = Constants.AIRWAY_BILL_TABLE_NAME
airway_bills = get_value_from_documentid(transaction_executor,Constants.CONTAINER_TABLE_NAME,container_id,"AirwayBillIds")
elif transport_type[0] == 2:
table = Constants.BILL_OF_LADING_TABLE_NAME
bill_of_lading = get_value_from_documentid(transaction_executor,Constants.CONTAINER_TABLE_NAME,container_id,"BillOfLadingIds")
print(transport_type)
pick_up_scentity_id = get_value_from_documentid(transaction_executor,Constants.PICK_UP_REQUESTS_TABLE,pick_up_request_id, "CarrierCompanyId")
if actual_sc_entity_id == pick_up_scentity_id[0]:
logger.info("Authorized!")
if transport_type[0] == 1:
is_picked_up = get_sub_details(transaction_executor,table,"RecieverApproval",airway_bills[0][-1],"isApproved")
if is_picked_up[0] == 0:
update_document(transaction_executor,Constants.AIRWAY_BILL_TABLE_NAME,"RecieverApproval.isApproved",airway_bills[0][-1],True)
update_document(transaction_executor,Constants.AIRWAY_BILL_TABLE_NAME,"RecieverApproval.ApproverId",airway_bills[0][-1], pick_up_person_id)
pick_up_location = get_value_from_documentid(transaction_executor,Constants.AIRWAY_BILL_TABLE_NAME,airway_bills[0][-1],"ImportAirportName")
consignee_id = get_value_from_documentid(transaction_executor,Constants.AIRWAY_BILL_TABLE_NAME,airway_bills[0][-1],"SenderScEntityId")
else:
return_statement = "container already picked up"
return{
'statusCode': 400,
'body': return_statement
}
elif transport_type[0] == 2:
is_picked_up = get_sub_details(transaction_executor,table,"RecieverApproval",bill_of_lading[0][-1],"isApproved")
if is_picked_up[0] == 0:
update_document(transaction_executor,Constants.BILL_OF_LADING_TABLE_NAME,"RecieverApproval.isApproved",bill_of_lading[0][-1],True)
update_document(transaction_executor,Constants.BILL_OF_LADING_TABLE_NAME,"RecieverApproval.ApproverId",bill_of_lading[0][-1], pick_up_person_id)
pick_up_location = get_value_from_documentid(transaction_executor,Constants.BILL_OF_LADING_TABLE_NAME,bill_of_lading[0][-1],"ImportPortName")
consignee_id = get_value_from_documentid(transaction_executor,Constants.BILL_OF_LADING_TABLE_NAME,bill_of_lading[0][-1],"SenderScEntityId")
else:
return_statement = "Containers Already picked up"
return{
'statusCode': 400,
'body': return_statement
}
consignee_name = get_value_from_documentid(transaction_executor,Constants.SCENTITY_TABLE_NAME,consignee_id[0],"ScEntityName")
delivery_location = get_scentity_contact(transaction_executor,actual_sc_entity_id[0],"Address")
lorry_reciepts = get_value_from_documentid(transaction_executor,Constants.CONTAINER_TABLE_NAME,container_id,"LorryRecieptIds")
carrier_id = get_value_from_documentid(transaction_executor,Constants.LORRY_RECEIPT_TABLE_NAME,lorry_reciepts[0][-1],"CarrierId")
if carrier_id[0] == pick_up_scentity_id[0]:
return_statement = "No request was made by buyer to pickup. Creating a new L/R to initiate import delivery."
lorry_reciept_id = create_lorry_reciept(transaction_executor,actual_sc_entity_id,pick_up_person_id,pick_up_location[0],delivery_location,consignee_id,consignee_name,True)
update_document_in_container(transaction_executor,container_id,"LorryRecieptIds",lorry_reciept_id[0])
return{
'statusCode': 200,
'body': {
"Message":return_statement,
"LorryRecieptId":lorry_reciept_id[0]
}
}
else:
message = "Pick up request was made by new carrier assigned by buyer."
update_document(transaction_executor,Constants.LORRY_RECEIPT_TABLE_NAME,"isPickedUp",lorry_reciepts[0][-1],True)
return{
'statusCode': 200,
'body': {
"Message":return_statement,
"LorryRecieptId":lorry_reciepts[0][-1]
}
}
else:
return_statement = "Not Authorized!"
return{
'statusCode': 400,
'body': return_statement
}
else:
# raise Exception("Container Not Safe!")
total_safe_containers = total_safe_containers - 1
if total_safe_containers > 0:
continue
else:
return_statement = "Not Container was safe. Pick up can't be made for any container"
return{
'statusCode': 400,
'body': return_statement
}
elif not isContainerSafe(transaction_executor,container_id):
continue
else:
return_statement = "Illegal=====Container was safe but not approved by customs"
return{
'statusCode': 400,
'body': return_statement
}
else:
return_statement = ("Not Authorized!")
return{
'statusCode': 400,
'body': return_statement
}
else:
return_statement = "Check Request Id"
return{
'statusCode': 400,
'body': return_statement
}
def pick_up_for_import(event):
try:
with create_qldb_driver() as driver:
pickuprequestid = event["PickUpRequestId"] #96EioNwSjcq8HKLBRjcvPp
pickuppersonid = event["PersonId"]
return driver.execute_lambda(lambda executor: deliver_product_to_distributor(executor, pickuprequestid, pickuppersonid))
except Exception:
return_statement = 'Error in import pick up'
return{
'statusCode': 400,
'body': return_statement
} | 65.14881 | 202 | 0.56921 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,333 | 0.121791 |
7f3df9c6bc7653f174e6f2a144e946916c638b4e | 1,467 | py | Python | rewx/components.py | akrk1986/re-wx | 2f50d1c0afe77313548847b279327d7041623721 | [
"MIT"
] | null | null | null | rewx/components.py | akrk1986/re-wx | 2f50d1c0afe77313548847b279327d7041623721 | [
"MIT"
] | null | null | null | rewx/components.py | akrk1986/re-wx | 2f50d1c0afe77313548847b279327d7041623721 | [
"MIT"
] | null | null | null | """
All components and wrappers currently
supported by rewx.
"""
import wx
import wx.adv
import wx.lib.scrolledpanel
import wx.media
ActivityIndicator = wx.ActivityIndicator
Button = wx.Button
BitmapButton = wx.BitmapButton
CalendarCtrl = wx.adv.CalendarCtrl
CheckBox = wx.CheckBox
# CollapsiblePane = wx.CollapsiblePane
ComboBox = wx.ComboBox
Dropdown = ComboBox
Frame = wx.Frame
Gauge = wx.Gauge
ListBox = wx.ListBox
ListCtrl = wx.ListCtrl
Panel = wx.Panel
RadioBox = wx.RadioBox
RadioButton = wx.RadioButton
ScrolledPanel = wx.lib.scrolledpanel.ScrolledPanel
Slider = wx.Slider
SpinCtrl = wx.SpinCtrl
SpinCtrlDouble = wx.SpinCtrlDouble
StaticBitmap = wx.StaticBitmap
StaticBox = wx.StaticBox
StaticLine = wx.StaticLine
StaticText = wx.StaticText
TextCtrl = wx.TextCtrl
ToggleButton = wx.ToggleButton
MediaCtrl = wx.media.MediaCtrl
class Grid(wx.Panel):
"""
Wrapper type for creating a panel
with a Grid Sizer
"""
pass
class Block(wx.Panel):
"""
Wrapper type for creating a panel
with a BoxSizer
"""
class TextArea(wx.TextCtrl):
"""
TextCtrl Wrapper with it's style pre-baked
to be TE_MULTILINE
"""
pass
class SVG(wx.StaticBitmap):
"""
Wrapper for converting an SVG to a scaled StaticBitmap
"""
pass
class SVGButton(wx.BitmapButton):
"""
Wrapper for creating an SVG backed BitmapButton.
"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs) | 20.957143 | 58 | 0.720518 | 621 | 0.423313 | 0 | 0 | 0 | 0 | 0 | 0 | 457 | 0.31152 |
7f3e241328fb148652ce6188714ae1004458cf72 | 3,733 | py | Python | test/blank_named_regtest.py | shraddha-pandhe/iscpy | 69173bb101dbc9e454c8050ba480fa4b2d0efc46 | [
"BSD-3-Clause"
] | null | null | null | test/blank_named_regtest.py | shraddha-pandhe/iscpy | 69173bb101dbc9e454c8050ba480fa4b2d0efc46 | [
"BSD-3-Clause"
] | null | null | null | test/blank_named_regtest.py | shraddha-pandhe/iscpy | 69173bb101dbc9e454c8050ba480fa4b2d0efc46 | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/python
# Copyright (c) 2009, Purdue University
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
#
# Redistributions in binary form must reproduce the above copyright notice, this
# list of conditions and the following disclaimer in the documentation and/or
# other materials provided with the distribution.
#
# Neither the name of the Purdue University nor the names of its contributors
# may be used to endorse or promote products derived from this software without
# specific prior written permission.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
"""Regression test for iscpy.py
Make sure you are running this against a database that can be destroyed.
DO NOT EVER RUN THIS TEST AGAINST A PRODUCTION DATABASE.
"""
__copyright__ = 'Copyright (C) 2009, Purdue University'
__license__ = 'BSD'
__version__ = '#TRUNK#'
import unittest
import os
import iscpy
NAMED_FILE = 'test_data/named.example.conf'
class TestNamedImport(unittest.TestCase):
def setUp(self):
self.named_file = (
'include "/home/jcollins/roster-dns-management/test/test_data/rndc.key";'
'options { pid-file "test_data/named.pid";};\n'
'controls { inet 127.0.0.1 port 35638 allow{localhost;} keys {rndc-key;};};')
self.maxDiff = None
def testSingleOption(self):
test_string = (
u'single-option;\n'
u'boolean-option yes;\n'
u'list-option { a; b; };\n'
u'options {};\n')
self.assertEqual(iscpy.Deserialize(iscpy.Serialize(test_string)),
u'single-option ;\n'
u'boolean-option yes;\n'
u'options { };\n'
u'list-option { a;\n'
u'b; };')
def testParse(self):
self.assertEqual(iscpy.Explode(iscpy.ScrubComments(self.named_file)),
['include "/home/jcollins/roster-dns-management/test/test_data/rndc.key"',
';', 'options', '{', 'pid-file "test_data/named.pid"', ';', '}', ';',
'controls', '{', 'inet 127.0.0.1 port 35638 allow', '{', 'localhost',
';', '}', 'keys', '{', 'rndc-key', ';', '}', ';', '}', ';'])
self.assertEqual(iscpy.ParseISCString(self.named_file),
{'include': '"/home/jcollins/roster-dns-management/test/test_data/rndc.key"',
'options': {'pid-file': '"test_data/named.pid"'},
'controls': [{'inet 127.0.0.1 port 35638 allow': {'localhost': True}},
{'keys': {'rndc-key': True}}]})
self.assertEqual(iscpy.MakeISC(iscpy.ParseISCString(self.named_file)),
'include "/home/jcollins/roster-dns-management/test/test_data/rndc.key";\n'
'options { pid-file "test_data/named.pid"; };\n'
'controls { inet 127.0.0.1 port 35638 allow { localhost; } keys { rndc-key; }; };')
if( __name__ == '__main__' ):
unittest.main()
| 40.139785 | 91 | 0.686579 | 1,771 | 0.474417 | 0 | 0 | 0 | 0 | 0 | 0 | 2,774 | 0.743102 |
7f3f0bcb734c5067a788e80bda49721133fbbbe5 | 4,247 | py | Python | oo/carro.py | RafaelLJC/pythonbirds | 43d401c6ef2b539ec45e19a218d0032de0435162 | [
"MIT"
] | null | null | null | oo/carro.py | RafaelLJC/pythonbirds | 43d401c6ef2b539ec45e19a218d0032de0435162 | [
"MIT"
] | null | null | null | oo/carro.py | RafaelLJC/pythonbirds | 43d401c6ef2b539ec45e19a218d0032de0435162 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Tue Jul 21 16:41:09 2020
@author: rafae
Exercício
Você deve criar uma classe carro que vai possuir dois atributos
compostos por outras duas classes:
1) motor;
2) Direção.
O motor terá a responsabilidade de controlar a velocidade.
Ele oferece os seguintes atributos:
1) Atributo de dado velocidade;
2) Método acelerar, que deverá incrementar a velocidade de uma unidade;
3) Método frenar, que deverá decrementar a velocidade em duas unidades.
A direção terá a responsabilidade de controlar a direção. Ela oferece os
seguintes atributos:
1) Valor de direção com valores possóveis: Norte, Sul, Leste e Oeste;
2) Método girar a direita
2) Método girar a esquerda
N
O L
S
Exemplo:
#testando motor
>>> motor = Motor()
>>> motor.velocidade
0
>>> motor.acelerar
>>> motor.velocidade
1
>>> motor.acelerar
>>> motor.velocidade
2
>>> motor.acelerar
>>> motor.velocidade
3
>>> motor.frear
>>> motor.velocidade
1
>>> motor.frear
>>> motor.velocidade
0
#testando direção
>>> direcao = Direcao()
>>> direcao.valor
'Norte'
>>> direcao.girar_a_direita()
>>> direcao.valor
'Leste'
>>> direcao.girar_a_direita()
>>> direcao.valor
'Sul'
>>> direcao.girar_a_direita()
>>> direcao.valor
'Oeste'
>>> direcao.girar_a_direita()
>>> direcao.valor
'Norte'
>>> direcao.girar_a_esquerda()
>>> direcao.valor
'Oeste'
>>> direcao.girar_a_esquerda()
>>> direcao.valor
'Sul'
>>> direcao.girar_a_esquerda()
>>> direcao.valor
'Leste'
>>> direcao.girar_a_esquerda()
>>> direcao.valor
'Norte'
>>> carro = Carro(direcao, motor)
>>> carro.caluclar_velocidade()
0
>>> carro.acelerar
>>> carro.caluclar_velocidade()
1
>>> carro.acelerar
>>> carro.caluclar_velocidade()
2
>>> carro.frear
>>> carro.caluclar_velocidade()
0
>>> carro.caluclar_direcao()
'Norte'
>>> carro.girar_a_direita()
>>> carro.caluclar_direcao()
'Leste'
>>> carro.girar_a_esquerda()
>>> carro.caluclar_direcao()
'Norte'
>>> carro.girar_a_esquerda()
>>> carro.caluclar_direcao()
'Oeste'
"""
class Carro:
def __init__(self, direcao, motor):
self.direcao = direcao
self.motor = motor
def calcular_velocidade(self):
return self.motor.velocidade
def acelerar(self):
self.motor.acelerar
def frear(self):
self.motor.frear()
def calcular_direcao(self):
return self.direcao.valor
def girar_a_direita(self):
self.direcao.girar_a_direita()
def girar_a_esquerda(self):
self.direcao.girar_a_esquerda()
class Motor:
def __init__(self):
self.velocidade = 0
def acelerar(self):
self.velocidade += 1
def frear(self):
self.velocidade -= 2
self.velocidade = max(0, self.velocidade)
motor = Motor()
motor.acelerar()
motor.acelerar()
motor.frear()
motor.frear()
motor.frear()
motor.acelerar()
motor.frear()
motor.acelerar()
motor.frear()
NORTE = 'Norte'
SUL = 'Sul'
LESTE = 'Leste'
OESTE = 'Oeste'
class Direcao:
def __init__(self):
self.valor = NORTE
def girar_a_direita(self):
self.valor = rotacao_a_direita_dct[self.valor]
def girar_a_esquerda(self):
self.valor = rotacao_a_esquerda_dct[self.valor]
rotacao_a_direita_dct = {NORTE: LESTE, LESTE: SUL, SUL: OESTE, OESTE: NORTE}
rotacao_a_esquerda_dct = {NORTE: OESTE, OESTE: SUL, SUL: LESTE, LESTE: NORTE}
direcao = Direcao()
direcao.girar_a_direita()
direcao.girar_a_esquerda()
direcao.girar_a_esquerda()
carro = Carro(direcao, motor)
#print(direcao.valor)
#print(motor.velocidade)
print(carro.calcular_direcao())
print(carro.calcular_velocidade())
| 23.859551 | 77 | 0.586296 | 965 | 0.226101 | 0 | 0 | 0 | 0 | 0 | 0 | 2,699 | 0.632381 |
7f4010676a7aac9aa896fa49d6f12bbf2ad6307d | 21 | py | Python | src/models/items/constants.py | MDRCS/deals-catcher | 0c2e344e402917cc284fbeb4d83c2829a08595aa | [
"MIT"
] | null | null | null | src/models/items/constants.py | MDRCS/deals-catcher | 0c2e344e402917cc284fbeb4d83c2829a08595aa | [
"MIT"
] | null | null | null | src/models/items/constants.py | MDRCS/deals-catcher | 0c2e344e402917cc284fbeb4d83c2829a08595aa | [
"MIT"
] | null | null | null | Collection = "items"
| 10.5 | 20 | 0.714286 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 7 | 0.333333 |
7f42a433c6b582f0497ed7d135f6be1ed7ed4f11 | 3,829 | py | Python | before.py | PatrickLTI/Refactor-Code-Smell | 0c6c0369a39a3cbd375e541021165cccd5c1c1b5 | [
"MIT"
] | null | null | null | before.py | PatrickLTI/Refactor-Code-Smell | 0c6c0369a39a3cbd375e541021165cccd5c1c1b5 | [
"MIT"
] | null | null | null | before.py | PatrickLTI/Refactor-Code-Smell | 0c6c0369a39a3cbd375e541021165cccd5c1c1b5 | [
"MIT"
] | null | null | null | """
Very advanced Employee management system.
"""
from dataclasses import dataclass
from typing import List
FIXED_VACATION_DAYS_PAYOUT = 5 # The fixed nr of vacation days that can be paid out.
@dataclass
class Employee:
"""Basic representation of an employee at the company."""
name: str
role: str
vacation_days: int = 25
def take_a_holiday(self, payout: bool) -> None:
"""Let the employee take a single holiday, or pay out 5 holidays."""
if payout:
# check that there are enough vacation days left for a payout
if self.vacation_days < FIXED_VACATION_DAYS_PAYOUT:
raise ValueError(
f"You don't have enough holidays left over for a payout.\
Remaining holidays: {self.vacation_days}."
)
try:
self.vacation_days -= FIXED_VACATION_DAYS_PAYOUT
print(f"Paying out a holiday. Holidays left: {self.vacation_days}")
except Exception:
# this should never happening
pass
else:
if self.vacation_days < 1:
raise ValueError(
"You don't have any holidays left. Now back to work, you!"
)
self.vacation_days -= 1
print("Have fun on your holiday. Don't forget to check your emails!")
@dataclass
class HourlyEmployee(Employee):
"""Employee that's paid based on number of worked hours."""
hourly_rate: float = 50
amount: int = 10
@dataclass
class SalariedEmployee(Employee):
"""Employee that's paid based on a fixed monthly salary."""
monthly_salary: float = 5000
class Company:
"""Represents a company with employees."""
def __init__(self) -> None:
self.employees: List[Employee] = []
def add_employee(self, employee: Employee) -> None:
"""Add an employee to the list of employees."""
self.employees.append(employee)
def find_managers(self) -> List[Employee]:
"""Find all manager employees."""
managers = []
for employee in self.employees:
if employee.role == "manager":
managers.append(employee)
return managers
def find_vice_presidents(self) -> List[Employee]:
"""Find all vice-president employees."""
vice_presidents = []
for employee in self.employees:
if employee.role == "vice_president":
vice_presidents.append(employee)
return vice_presidents
def find_interns(self) -> List[Employee]:
"""Find all interns."""
interns = []
for employee in self.employees:
if employee.role == "intern":
interns.append(employee)
return interns
def pay_employee(self, employee: Employee) -> None:
"""Pay an employee."""
if isinstance(employee, SalariedEmployee):
print(
f"Paying employee {employee.name} a monthly salary of ${employee.monthly_salary}."
)
elif isinstance(employee, HourlyEmployee):
print(
f"Paying employee {employee.name} a hourly rate of \
${employee.hourly_rate} for {employee.amount} hours."
)
def main() -> None:
"""Main function."""
company = Company()
company.add_employee(SalariedEmployee(name="Louis", role="manager"))
company.add_employee(HourlyEmployee(name="Brenda", role="president"))
company.add_employee(HourlyEmployee(name="Tim", role="intern"))
print(company.find_vice_presidents())
print(company.find_managers())
print(company.find_interns())
company.pay_employee(company.employees[0])
company.employees[0].take_a_holiday(False)
if __name__ == "__main__":
main()
| 31.130081 | 98 | 0.610342 | 3,054 | 0.797597 | 0 | 0 | 1,492 | 0.389658 | 0 | 0 | 1,261 | 0.329329 |
7f4616f095924fa5eac33a11190968db43cccd4e | 261 | py | Python | python/decorator/function_transform_with_decorator.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | python/decorator/function_transform_with_decorator.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | python/decorator/function_transform_with_decorator.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | def debug_transformer(func):
def wrapper():
print(f'Function `{func.__name__}` called')
func()
print(f'Function `{func.__name__}` finished')
return wrapper
@debug_transformer
def walkout():
print('Bye Felicia')
walkout() | 17.4 | 53 | 0.636015 | 0 | 0 | 0 | 0 | 58 | 0.222222 | 0 | 0 | 87 | 0.333333 |
7f46b98db9b94c982905dfaf5e2079f45ce4a9a6 | 850 | py | Python | logging_context/helpers.py | vuonglv1612/logging-context | beef9f11494d729bbb3f429fdd7cf69a29e0c527 | [
"MIT"
] | null | null | null | logging_context/helpers.py | vuonglv1612/logging-context | beef9f11494d729bbb3f429fdd7cf69a29e0c527 | [
"MIT"
] | null | null | null | logging_context/helpers.py | vuonglv1612/logging-context | beef9f11494d729bbb3f429fdd7cf69a29e0c527 | [
"MIT"
] | null | null | null | import functools
import logging
from typing import Callable
from logging_context.context.base import BaseContext
from .context import get_logging_context
def context_logging_factory(record_factory: Callable, context: BaseContext) -> Callable:
@functools.wraps(record_factory)
def wrapper(*args, **kwargs):
record = record_factory(*args, **kwargs)
record.context = str(context)
return record
return wrapper
def setup_logging_context(context: BaseContext = None) -> None:
if not context:
context = get_logging_context()
current_factory = logging.getLogRecordFactory()
test_record = current_factory(__name__, logging.DEBUG, __file__, 0, "", [], None)
if not hasattr(test_record, "context"):
logging.setLogRecordFactory(context_logging_factory(current_factory, context=context))
| 31.481481 | 94 | 0.742353 | 0 | 0 | 0 | 0 | 175 | 0.205882 | 0 | 0 | 11 | 0.012941 |
7f4786e590d0a9418a3d92cb5ddc03d945909da4 | 6,840 | py | Python | script/proxycheck/check.py | kenshinx/rps | 3d141056f3512598525430ecc9ddb1ee79b887cf | [
"MIT"
] | 6 | 2017-06-20T09:44:03.000Z | 2018-07-28T06:44:10.000Z | script/proxycheck/check.py | kenshinx/rps | 3d141056f3512598525430ecc9ddb1ee79b887cf | [
"MIT"
] | null | null | null | script/proxycheck/check.py | kenshinx/rps | 3d141056f3512598525430ecc9ddb1ee79b887cf | [
"MIT"
] | 3 | 2017-09-23T16:48:18.000Z | 2018-05-26T19:12:12.000Z | #!/usr/bin/env python
import re
import sys
import time
import logging
import asyncore
import optparse
from datetime import datetime
import schedule
from pymongo import MongoReplicaSetClient, MongoClient
from async_s5 import AsyncSocks5Client
from async_http import AsyncHTTPClient
from async_http_tunnel import AsyncHTTPTunnelClient
from conf import (MONGO_USERNAME, MONGO_PASSWORD,
MONGO_HOST, MONGO_REPLICA_SET,
LOG_LEVEL, LOG_FORMAT)
class BaseCheck(object):
HTTP_PATTERN = re.compile("^HTTP\/1\.\d ([0-9]{3}) .*")
HTTP_HOST = "www.baidu.com"
HTTP_PORT = 80
HTTP_PAYLOAD = "domain=.baidu.com"
WHOIS_HOST = "133.130.126.119"
WHOIS_PORT = 43
WHOIS_PAYLOAD = "google.com"
def __init__(self, db, client, payload_proto, concurrency):
self.dbname = db
self.client =client
self.payload_proto = payload_proto
self.concurrency = concurrency
self.conn = self.createConn()
@property
def db(self):
if self.dbname == "rps":
return self.conn.rps
elif self.dbname == "rps_test":
return self.conn.rps_test
else:
raise Exception("Invalid DataBase <%s>" %self.dbname)
def createConn(self):
addr = "mongodb://%s:%s@%s" %(MONGO_USERNAME, MONGO_PASSWORD, MONGO_HOST)
conn = MongoClient(addr, replicaSet = MONGO_REPLICA_SET)
return conn
def getProxyList(self):
raise NotImplemetedError()
def updateProxy(self):
raise NotImplemetedError()
def checkHTTPResp(self, resp):
if not resp or resp == " ":
return False
try:
code = self.HTTP_PATTERN.findall(resp)[0]
except Exception, e:
return False
if code != "200":
return False
return self.HTTP_PAYLOAD in resp
def checkWhoisResp(self, resp, proxy_ip):
if not resp or resp == " ":
return False
return (resp == "%s:%s:%s" %(self.WHOIS_PAYLOAD, proxy_ip, self.WHOIS_PAYLOAD))
def check(self, client, host, port):
resp = client.buffer.getvalue()
client.buffer.close()
if self.payload_proto == "http":
is_ok = self.checkHTTPResp(resp)
elif self.payload_proto == "whois":
is_ok = self.checkWhoisResp(resp, host)
else:
raise Exception("unsupport payload protocol '%s'" %self.payload_proto)
return is_ok
def afterLoop(self, clients):
for c in clients:
if self.check(c, c.host, c.port):
print "%s:%d is ok" %(c.host, c.port)
self.updateProxy(c.host, c.port, True)
else:
print "%s:%d is bad" %(c.host, c.port)
self.updateProxy(c.host, c.port, False)
def run(self):
clients = []
socket_map = {}
for r in self.getProxyList():
try:
if self.payload_proto == "whois":
clients.append(self.client(r["host"], r["port"],
self.WHOIS_HOST, self.WHOIS_PORT, "whois", socket_map))
else:
clients.append(self.client(r["host"], r["port"],
self.HTTP_HOST, self.HTTP_PORT, "http", socket_map))
except Exception, e:
continue
if len(clients) >= self.concurrency:
asyncore.loop(timeout=5, use_poll=True, map=socket_map)
self.afterLoop(clients)
clients = []
socket_map = {}
if len(clients) < self.concurrency:
asyncore.loop(timeout=5, use_poll=True, map=socket_map)
self.afterLoop(clients)
class HTTPProxyCheck(BaseCheck):
def __init__(self, db, payload_proto, concurrency):
BaseCheck.__init__(self, db, AsyncHTTPClient, "http", concurrency)
def getProxyList(self):
for r in self.db.http.find():
yield r
def updateProxy(self, host, port, enable):
self.db.http.update({"host":host, "port":port},
{"$set":{"enable":int(enable), "last_check":datetime.now()}})
class HTTPTunnelProxyCheck(BaseCheck):
def __init__(self, db, payload_proto, concurrency):
BaseCheck.__init__(self, db, AsyncHTTPTunnelClient, payload_proto, concurrency)
def getProxyList(self):
for r in self.db.http_tunnel.find({"source":{"$in":["nd", "nf"]}}):
yield r
def updateProxy(self, host, port, enable):
self.db.http_tunnel.update({"host":host, "port":port},
{"$set":{"enable":int(enable), "last_check":datetime.now()}})
class Socks5ProxyCheck(BaseCheck):
def __init__(self, db, payload_proto, concurrency):
BaseCheck.__init__(self, db, AsyncSocks5Client, payload_proto, concurrency)
def getProxyList(self):
for r in self.db.socks5.find({"source":{"$in":["nd", "nf"]}}):
yield r
def updateProxy(self, host, port, enable):
self.db.socks5.update({"host":host, "port":port},
{"$set":{"enable":int(enable), "last_check":datetime.now()}})
def usage():
return "Usage: %s <http|http_tunnel|socks5> [options]" %(sys.argv[0])
if __name__ == "__main__":
parser = optparse.OptionParser(usage= usage())
parser.add_option("-d", "--database", action="store", dest="db", type="string",
default="rps_test", help="[rps|rps_test]")
parser.add_option("-c", "--concurrency", action="store", dest="concurrency", type="int",
default=1000)
parser.add_option("-e", "--every", action="store", dest="every", type="int", default=30,
help="run check every %default minutes")
parser.add_option("-p", "--payload_proto", action="store", dest="payload_proto", type="string",
default="whois", help="payload protocol default be whois for http_tunnel \
and socks5 proxy, http for http proxy")
options, args = parser.parse_args()
logging.basicConfig(level=LOG_LEVEL, format=LOG_FORMAT)
if len(sys.argv) < 2:
print usage()
sys.exit(1)
protocol = sys.argv[1]
if protocol == "http_tunnel":
checker = HTTPTunnelProxyCheck(options.db, options.payload_proto, options.concurrency)
elif protocol == "http":
checker = HTTPProxyCheck(options.db, options.payload_proto, options.concurrency)
elif protocol == "socks5":
checker = Socks5ProxyCheck(options.db, options.payload_proto, options.concurrency)
else:
print usage()
sys.exit(1)
schedule.every(options.every).minutes.do(checker.run).run()
while True:
schedule.run_pending()
time.sleep(1)
| 31.232877 | 100 | 0.594591 | 4,738 | 0.69269 | 314 | 0.045906 | 251 | 0.036696 | 0 | 0 | 894 | 0.130702 |
7f48ff2758ca1da69efc97e333be34fa3b8a2d3b | 16,438 | py | Python | Notebook/KL Divergence Loop.py | yxie367/Mushrooms | 9b0fc5dfb6ab20c7c0c4146bff0d04de561302c5 | [
"MIT"
] | null | null | null | Notebook/KL Divergence Loop.py | yxie367/Mushrooms | 9b0fc5dfb6ab20c7c0c4146bff0d04de561302c5 | [
"MIT"
] | null | null | null | Notebook/KL Divergence Loop.py | yxie367/Mushrooms | 9b0fc5dfb6ab20c7c0c4146bff0d04de561302c5 | [
"MIT"
] | null | null | null | # %% [Algorithm 1c Loop]
# # MUSHROOMS
# %% [markdown]
# ## Binary Classification
# %% [markdown]
# ### Imports
# %%
import os
import pandas as pd
import numpy as np
import tensorflow as tf
from tensorflow import keras
import matplotlib.pyplot as plt
# %% [markdown]
# ### Load Data
dataset = pd.read_csv(r"C:\Users\yxie367\Documents\GitHub\Mushrooms\DATA\mushrooms.csv")
#dataset = pd.read_csv(r"C:\Users\xieya\Documents\GitHub\Mushrooms\DATA\mushrooms.csv")
# %% [markdown]
# ### View Data and Informations
# %%
dataset.head()
# %%
dataset.info()
# %%
edible, poisonous = dataset['class'].value_counts()
# print("Edible:\t ", edible,"\nPoisonous:", poisonous)
# %%
# Categorical to numerical
labels = {'e': 0, 'p': 1}
dataset['class'].replace(labels, inplace=True)
edible, poisonous = dataset['class'].value_counts()
#print("0 - Edible: ", edible,"\n1 - Poisonous:", poisonous)
# %% [markdown]
# # NN1 Stalk Root - Rooted (r)
# %% [markdown]
# ### Split Dataset
# %% [markdown]
# #### Get the Labels
# %%
X, y = dataset.drop('class', axis=1), dataset['class'].copy()
#print("X:",X.shape,"\ny:",y.shape)
# %% [markdown]
# #### Train Set and Test Set
total_error_1 = 0
total_error_2 = 0
total_error_comb = 0
randnum = np.arange(2,44,4)
num_trials = len(randnum)
record = ""
wrong_record = ""
run = 1
# %% Data cleaning
from sklearn.model_selection import train_test_split
X_white = pd.DataFrame()
X_not_white = pd.DataFrame()
y_white = pd.Series(dtype='float64')
y_not_white = pd.Series(dtype='float64')
for i in range(0,len(X)):
if X.loc[i,"stalk-root"] == "r":
X_white = X_white.append(X.iloc[i,:])
y_white = y_white.append(pd.Series(y.iloc[i]))
else:
X_not_white = X_not_white.append(X.iloc[i,:])
y_not_white = y_not_white.append(pd.Series(y.iloc[i]))
# %% Data cleaning pt2
X_green = pd.DataFrame()
X_not_green = pd.DataFrame()
y_green = pd.Series(dtype='float64')
y_not_green = pd.Series(dtype='float64')
for i in range(0,len(X)):
if X.loc[i,"odor"] == "a":
X_green = X_green.append(X.iloc[i,:])
y_green = y_green.append(pd.Series(y.iloc[i]))
else:
X_not_green = X_not_green.append(X.iloc[i,:])
y_not_green = y_not_green.append(pd.Series(y.iloc[i]))
# %%
for j in randnum:
X_train_not_white, X_test_not_white, y_train_not_white, y_test_not_white = train_test_split(X_not_white, y_not_white, test_size=1-(6905/(8124-len(X_white))), random_state=j)
X_train_not_green, X_test_not_green, y_train_not_green, y_test_not_green = train_test_split(X_not_green, y_not_green, test_size=1-(6905/(8124-len(X_green))), random_state=j)
X_train_green = (X_train_not_green)
y_train_green = (y_train_not_green)
X_train_white = (X_train_not_white)
y_train_white = (y_train_not_white)
# %%
from sklearn.utils import shuffle
X_train_full1 = shuffle(X_train_white, random_state=j)
X_test = shuffle(X, random_state=j).iloc[4000:8000]
y_train_full1 = shuffle(y_train_white, random_state=j)
y_test = shuffle(y, random_state=j).iloc[4000:8000]
# %% [markdown]
# #### Validation Set
# %%
X_valid1, X_train1 = X_train_full1[:500], X_train_full1[500:]
y_valid1, y_train1 = y_train_full1[:500], y_train_full1[500:]
# print("X_train:", X_train1.shape[0], "y_train", y_train1.shape[0])
# print("X_valid: ", X_valid1.shape[0], "y_valid ", y_valid1.shape[0])
# print("X_test: ", X_test.shape[0], "y_test ", X_test.shape[0])
# %% [markdown]
# ### Prepare the Data
# %% [markdown]
# #### Data Transformation
# %%
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import OrdinalEncoder
from sklearn.compose import ColumnTransformer
cat_attr_pipeline = Pipeline([
('encoder', OrdinalEncoder())
])
cols = list(X)
pipeline = ColumnTransformer([
('cat_attr_pipeline', cat_attr_pipeline, cols)
])
X_train1 = pipeline.fit_transform(X_train1)
X_valid1 = pipeline.fit_transform(X_valid1)
X_test1 = pipeline.fit_transform(X_test)
# %% [markdown]
# ### Neural Network
# %% [markdown]
# #### Model
# %%
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import InputLayer, Dense
# %%
# tf.random.set_seed(j)
tf.random.set_random_seed(j)
# %%
model1 = Sequential([
InputLayer(input_shape=(22,)), # input layer
Dense(45, activation='relu'), # hidden layer
Dense(1, activation='sigmoid') # output layer
])
# %%
#model1.summary()
# %% [markdown]
# #### Compile the Model
# %%
model1.compile(loss='binary_crossentropy',
optimizer='sgd',
metrics=['accuracy'])
# %% [markdown]
# #### Prepare Callbacks
# %%
from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping
checkpoint_cb = ModelCheckpoint('../SavedModels/best_model.h5',
save_best_only=True)
early_stopping_cb = EarlyStopping(patience=3,
restore_best_weights=True)
# %% [markdown]
# ### Training
# %%
train_model1 = model1.fit(X_train1, y_train1,
epochs=100,
validation_data=(X_valid1, y_valid1),
callbacks=[checkpoint_cb, early_stopping_cb])
# %% [markdown]
# ### Evaluate the Best Model on Test Set
# %%
results1 = model1.evaluate(X_test1, y_test)
# print("test loss, test acc:", results1)
# %% [markdown]
# ### Make Some Predictions
# %%
X_new1 = X_test1[:5]
y_prob1 = model1.predict(X_new1)
# print(y_prob.round(3))
# %%
y_pred1 = (model1.predict(X_new1) > 0.5).astype("int32")
# print(y_pred)
y_test_pred = (model1.predict(X_test1) > 0.5).astype("int32")
# %% [markdown]
# ## KL Divergence
# %%
# X_new = X_test[:5]
X_df1 = pd.DataFrame(model1.predict(X_test1))
y_test_pred1 = pd.DataFrame(y_test_pred).reset_index(drop=True)
X_df1 = pd.concat([X_df1, y_test_pred1], axis=1)
y_test1 = y_test.reset_index(drop=True)
X_df1 = pd.concat([X_df1, y_test1], axis=1)
X_df1.columns = ["X_pred","y_pred","y_actual"]
#print(X_df1)
# %%
import math
table1 = pd.DataFrame(columns=["KL_div","abs_distance","correctness"])
for i in range(0,len(X_df1)):
# KL divergence
p = X_df1.loc[i,"X_pred"]
try:
kl = -(p*math.log(p) + (1-p)*math.log(1-p))
except:
kl = 0
table1.loc[i,"KL_div"] = kl
# absolute distance
abs_dist = 2*abs(0.5-p)
table1.loc[i,"abs_distance"] = abs_dist
# correctness
y_pred1 = X_df1.loc[i,"y_pred"]
y_act1 = X_df1.loc[i,"y_actual"]
if y_pred1 == y_act1:
table1.loc[i,"correctness"] = 1 # correct prediction
else:
table1.loc[i,"correctness"] = 0 # wrong prediction
table1.loc[i,"y_pred"] = y_pred1
#print(table1)
# %%
table1["count"] = 1
correctness1 = table1[["correctness","count"]].groupby(pd.cut(table1["KL_div"], np.arange(0, 0.8, 0.1))).apply(sum)
correctness1["percent"] = 100*(correctness1["correctness"]/correctness1["count"])
#print(correctness1)
# %%
index = []
for i in (correctness1.index):
index.append(str(i))
plt.bar(index,correctness1["percent"], width=0.7)
for index,data in enumerate(correctness1["percent"]):
plt.text(x=index , y =data+1 , s=f"{round(data,2)}" , fontdict=dict(fontsize=15),ha='center')
plt.ylim(0,120)
plt.xlabel("KL Divergence")
plt.ylabel("% correct")
# %% [markdown]
# ### Confidence
# %%
kl1 = table1[["correctness","count"]].groupby(pd.cut(table1["KL_div"], np.arange(0, 0.80, 0.1))).apply(sum)
kl1["percent"] = (kl1["correctness"]/kl1["count"])
kl1.dropna(inplace=True)
plt.scatter(np.arange(0, 0.70, 0.1), kl1["percent"])
plt.xlabel("KL Divergence")
plt.ylabel("% correct")
# %%
# Linear Regression
from sklearn.linear_model import LinearRegression
x_reg1 = np.arange(0, 0.70, 0.1).reshape((-1, 1))
y_reg1 = kl1["percent"]
reg_model1 = LinearRegression().fit(x_reg1,y_reg1)
# %%
# print('intercept(alpha):', reg_model1.intercept_)
# print('slope(theta):', reg_model1.coef_)
# %% [markdown]
# # NN2 Odor - Almond (a)
# %% [markdown]
# #### Train Set and Test Set
# %%
from sklearn.utils import shuffle
X_train_full2 = shuffle(X_train_green, random_state=j)
# X_test2 = shuffle(X_test_green, random_state=j)
y_train_full2 = shuffle(y_train_green, random_state=j)
# y_test2 = shuffle(y_test_green, random_state=j)
# %% [markdown]
# #### Validation Set
# %%
X_valid2, X_train2 = X_train_full2[:500], X_train_full2[500:]
y_valid2, y_train2 = y_train_full2[:500], y_train_full2[500:]
# print("X_train:", X_train2.shape[0], "y_train", y_train2.shape[0])
# print("X_valid: ", X_valid2.shape[0], "y_valid ", y_valid2.shape[0])
# print("X_test: ", X_test.shape[0], "y_test ", X_test.shape[0])
# %% [markdown]
# ### Prepare the Data
# %% [markdown]
# #### Data Transformation
# %%
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import OrdinalEncoder
from sklearn.compose import ColumnTransformer
cat_attr_pipeline = Pipeline([
('encoder', OrdinalEncoder())
])
cols = list(X)
pipeline = ColumnTransformer([
('cat_attr_pipeline', cat_attr_pipeline, cols)
])
X_train2 = pipeline.fit_transform(X_train2)
X_valid2 = pipeline.fit_transform(X_valid2)
X_test2 = pipeline.fit_transform(X_test)
y_test2 = y_test
# %% [markdown]
# ### Neural Network
# %% [markdown]
# #### Model
# %%
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import InputLayer, Dense
tf.random.set_random_seed(j)
# %%
model2 = Sequential([
InputLayer(input_shape=(22,)), # input layer
Dense(45, activation='relu'), # hidden layer
Dense(1, activation='sigmoid') # output layer
])
# %%
#model2.summary()
# %% [markdown]
# #### Compile the Model
# %%
model2.compile(loss='binary_crossentropy',
optimizer='sgd',
metrics=['accuracy'])
# %% [markdown]
# #### Prepare Callbacks
# %%
from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping
checkpoint_cb = ModelCheckpoint('../SavedModels/best_model.h5',
save_best_only=True)
early_stopping_cb = EarlyStopping(patience=3,
restore_best_weights=True)
# %% [markdown]
# ### Training
# %%
train_model2 = model2.fit(X_train2, y_train2,
epochs=100,
validation_data=(X_valid2, y_valid2),
callbacks=[checkpoint_cb, early_stopping_cb])
# %% [markdown]
# ### Evaluate the Best Model on Test Set
# %%
results2 = model2.evaluate(X_test2, y_test2)
# print("test loss, test acc:", results2)
# %% [markdown]
# ### Make Some Predictions
# %%
# y_pred2 = (model2.predict(X_new2) > 0.5).astype("int32")
# print(y_pred2)
y_test_pred2 = (model2.predict(X_test2) > 0.5).astype("int32")
# %% [markdown]
# ## KL Divergence
# %%
# X_new = X_test[:5]
X_df2 = pd.DataFrame(model2.predict(X_test2))
y_test_pred2 = pd.DataFrame(y_test_pred2).reset_index(drop=True)
X_df2 = pd.concat([X_df2, y_test_pred2], axis=1)
y_test2 = y_test2.reset_index(drop=True)
X_df2 = pd.concat([X_df2, y_test2], axis=1)
X_df2.columns = ["X_pred","y_pred","y_actual"]
#print(X_df2)
# %%
import math
table2 = pd.DataFrame(columns=["KL_div","abs_distance","y_pred","correctness"])
for i in range(0,len(X_df2)):
# KL divergence
p = X_df2.loc[i,"X_pred"]
if p > 0:
kl = -(p*math.log(p) + (1-p)*math.log(1-p))
else:
kl = 1
table2.loc[i,"KL_div"] = kl
# absolute distance
abs_dist = 2*abs(0.5-p)
table2.loc[i,"abs_distance"] = abs_dist
# correctness
y_pred = X_df2.loc[i,"y_pred"]
y_act = X_df2.loc[i,"y_actual"]
if y_pred == y_act:
table2.loc[i,"correctness"] = 1 # correct prediction
else:
table2.loc[i,"correctness"] = 0 # wrong prediction
table2.loc[i,"y_pred"] = y_pred
#print(table2)
# %%
table2["count"] = 1
correctness2 = table2[["correctness","count"]].groupby(pd.cut(table2["KL_div"], np.arange(0, 0.8, 0.1))).apply(sum)
correctness2["percent"] = 100*(correctness2["correctness"]/correctness2["count"])
#print(correctness2)
# %%
index = []
for i in (correctness2.index):
index.append(str(i))
plt.bar(index,correctness2["percent"], width=0.7)
for index,data in enumerate(correctness2["percent"]):
plt.text(x=index , y =data+1 , s=f"{round(data,2)}" , fontdict=dict(fontsize=15),ha='center')
plt.ylim(0,120)
plt.xlabel("KL Divergence")
plt.ylabel("% correct")
# %% [markdown]
# ### Confidence
# %%
kl2 = table2[["correctness","count"]].groupby(pd.cut(table2["KL_div"], np.arange(0, 0.8, 0.1))).apply(sum)
kl2["percent"] = (kl2["correctness"]/kl2["count"])
kl2.dropna(inplace=True)
plt.scatter(np.arange(0, 0.70, 0.1), kl2["percent"])
# print(kl)
# print(np.arange(0, 0.7, 0.05))
# %%
# Linear Regression
from sklearn.linear_model import LinearRegression
x_reg2 = np.arange(0, 0.7, 0.1).reshape((-1, 1))
y_reg2 = kl2["percent"]
reg_model2 = LinearRegression().fit(x_reg2,y_reg2)
# %%
# print('intercept(alpha):', reg_model2.intercept_)
# print('slope(theta):', reg_model2.coef_)
# %% [markdown]
# ## Algorithm C: It = argmax(Ct,i)
# %%
# Correct answer
ans = pd.DataFrame(X_df2["y_actual"])
# NN1
alpha1 = reg_model1.intercept_
theta1 = reg_model1.coef_
# NN2
alpha2 = reg_model2.intercept_
theta2 = reg_model2.coef_
# %%
# Creating NN tables
nn1 = table1.drop(["abs_distance","correctness"], axis=1)
nn1["conf"] = 1 + theta1 * nn1["KL_div"]
nn2 = table2.drop(["abs_distance","correctness"], axis=1)
nn2["conf"] = 1 + theta2 * nn2["KL_div"]
# nn2
# %%
# Determing higher confidence NN and choosing that arm
for i in range(0,len(nn1)):
if nn1.loc[i,"conf"] > nn2.loc[i,"conf"]:
ans.loc[i,"y_pred"] = nn1.loc[i,"y_pred"]
ans.loc[i,"NN"] = 1
ans.loc[i,"conf"] = nn1.loc[i,"conf"]
else:
ans.loc[i,"y_pred"] = nn2.loc[i,"y_pred"]
ans.loc[i,"NN"] = 2
ans.loc[i,"conf"] = nn2.loc[i,"conf"]
# ans
# %% [markdown]
# #### Comparing performance
# %%
# NN1 performance
cost1 = 0
for i in range(0,len(nn1)):
if nn1.loc[i,"y_pred"] != ans.loc[i,"y_actual"]:
cost1 += 1
else:
pass
# NN2 performance
cost2 = 0
for i in range(0,len(nn2)):
if nn2.loc[i,"y_pred"] != ans.loc[i,"y_actual"]:
cost2 += 1
else:
pass
# Combined performance
cost3 = 0
for i in range(0,len(nn1)):
nn = ans.loc[i,"NN"]
nn_conf = ans.loc[i,"conf"]
if ans.loc[i,"y_pred"] != ans.loc[i,"y_actual"]:
cost3 += 1
wrong_record = wrong_record + (f"Run:{run} - Wrong NN:{nn}, Conf:{nn_conf}") + "\n"
else:
pass
# %%
record = record+(f"Run:{run} - Error count for NN1:{cost1}, NN2:{cost2}, Combined:{cost3}") + "\n"
total_error_1 += cost1
total_error_2 += cost2
total_error_comb += cost3
print(f"Run {run} complete!")
run+=1
print(record)
print(f"Average error count for NN1:{total_error_1/num_trials}, NN2:{total_error_2/num_trials}, Combined:{total_error_comb/num_trials}")
#%%
# print(wrong_record)
# %%
| 27.673401 | 177 | 0.592469 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5,174 | 0.314758 |
7f490e0f83f0b93f89c7b7920c449eae9a2ea21b | 206 | py | Python | galaxydb/__init__.py | alantelles/galaxydb | 7eeeaae3c3f79736eade36a720fb1dc816570554 | [
"MIT"
] | 2 | 2019-03-15T17:14:16.000Z | 2019-03-15T20:47:14.000Z | galaxydb/__init__.py | alantelles/galaxydb | 7eeeaae3c3f79736eade36a720fb1dc816570554 | [
"MIT"
] | null | null | null | galaxydb/__init__.py | alantelles/galaxydb | 7eeeaae3c3f79736eade36a720fb1dc816570554 | [
"MIT"
] | null | null | null | from galaxydb.column import Column
from galaxydb.scheme import Scheme
from galaxydb.logic import Logic
from galaxydb.table import Table
from galaxydb.constants import *
from galaxydb.statics import *
| 29.428571 | 35 | 0.815534 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
7f495918acf00767d9fbeb784d409f5760173565 | 19,291 | py | Python | attic/library/kepler.py | vdods/heisenberg | 66921b80c2d035e5f10e0af4d0cec21d5470dbd1 | [
"MIT"
] | 3 | 2018-01-04T07:40:14.000Z | 2021-02-19T15:27:10.000Z | attic/library/kepler.py | vdods/heisenberg | 66921b80c2d035e5f10e0af4d0cec21d5470dbd1 | [
"MIT"
] | null | null | null | attic/library/kepler.py | vdods/heisenberg | 66921b80c2d035e5f10e0af4d0cec21d5470dbd1 | [
"MIT"
] | null | null | null | # NOTE: This changes a/b to produce a floating point approximation of that
# ratio, not the integer quotient. For integer quotient, use a//b instead.
from __future__ import division
import fourier_parameterization
import numpy as np
import multiindex
import symbolic
import sympy
import tensor
# TODO: look at and use https://en.wikipedia.org/wiki/Elliptic_orbit
class KeplerProblemSymbolicContext:
def __init__ (self, configuration_space_dimension, use_constraint=True):
"""
Use sympy to define various functions and automatically compute their derivatives, crunching
them down to (probably efficient) Python lambda functions.
"""
assert configuration_space_dimension > 0
self.X = X = configuration_space_dimension
# Indicates if the constraint should be used or not.
self.use_constraint = use_constraint
# q is position
q = symbolic.tensor('q', (X,))
# v is velocity
v = symbolic.tensor('v', (X,))
# g is gravitational constant
g = symbolic.variable('g')
# lm is the lagrange multiplier
lm = symbolic.variable('lm')
# qv is the q and v variables in one array
self.qv = qv = np.array(list(q) + list(v))
# P is all variables
self.P = P = np.array(list(q) + list(v) + [g, lm])
# U is potential energy
# U = -g / sympy.sqrt(np.sum(np.square(q)))
U = -1 / sympy.sqrt(np.sum(np.square(q)))
# K is kinetic energy -- NOTE: There is unit mass, so the momentum is the same as the velocity.
# This fact is used in defining the Hamiltonian vector field.
K = np.sum(np.square(v)) / 2
# H is total energy (Hamiltonian)
H = K + U
# L is the difference in energy (Lagrangian)
L = K - U
# H_0 is the constant value which defines the constraint (that the Hamiltonian must equal that at all times)
self.H_0 = H_0 = -1.8
# This is the constraint. The extra division is used to act as a metric on the lagrange multiplier coordinate.
C = (H - H_0)**2 / 2 / 100
# Construct the Hamiltonian vector field of H.
dH = symbolic.D(H, qv)
# Construct the symplectic form on phase space.
omega = np.zeros((2*X,2*X), dtype=np.int)
omega[0:X,X:2*X] = np.eye(X,X)
omega[X:2*X,0:X] = -np.eye(X,X)
# Symplectic gradient of H, aka the Hamiltonian vector field.
X_H = tensor.contract('ij,j', omega, dH, dtype=object)
# DL = symbolic.D(L, P)
# # DH = symbolic.D(H, P)
# DC = symbolic.D(C, P)
# This is the integrand of the action functional
Lambda_integrand = L #+ lm*C
# This is the integrand of the first variation of the action
DLambda_integrand = symbolic.D(Lambda_integrand, P)
# This is the integrand for the constraint functional
C_integrand = C
# Solving the constrained optimization problem by minimizing the norm squared of DLambda.
# DDLambda_integrand = symbolic.D(DLambda_integrand, P)
# Obj_integrand = (np.sum(np.square(DLambda_integrand))/2)#.simplify()
# DObj_integrand = symbolic.D(Obj_integrand, P)
assert not use_constraint
Obj_integrand = Lambda_integrand
DObj_integrand = DLambda_integrand
# print 'Obj_integrand =', Obj_integrand
# print ''
# print 'DObj_integrand =', DObj_integrand
# print ''
replacement_d = {'dtype=object':'dtype=float'}
# self.L = symbolic.lambdify(L, P, replacement_d=replacement_d)
# self.DL = symbolic.lambdify(DL, P, replacement_d=replacement_d)
# self.DDL = symbolic.lambdify(DDL, P, replacement_d=replacement_d)
# self.H = symbolic.lambdify(H, P, replacement_d=replacement_d)
# self.DH = symbolic.lambdify(DH, P, replacement_d=replacement_d)
self.H = symbolic.lambdify(H, P, replacement_d=replacement_d)
self.X_H = symbolic.lambdify(X_H, qv, replacement_d=replacement_d)
self.Lambda_integrand = symbolic.lambdify(Lambda_integrand, P, replacement_d=replacement_d)
self.DLambda_integrand = symbolic.lambdify(DLambda_integrand, P, replacement_d=replacement_d)
self.Obj_integrand = symbolic.lambdify(Obj_integrand, P, replacement_d=replacement_d)
self.DObj_integrand = symbolic.lambdify(DObj_integrand, P, replacement_d=replacement_d)
self.C_integrand = symbolic.lambdify(C_integrand, P, replacement_d=replacement_d)
class KeplerProblemContext(KeplerProblemSymbolicContext):
def __init__ (self, closed_time_interval, frequencies, use_constraint=True):
# Call superclass constructor.
KeplerProblemSymbolicContext.__init__(self, 2, use_constraint=use_constraint)
X = self.X
# Number of derivatives in phase space (2, i.e. position and velocity)
self.D = D = 2
self.fourier_curve_parameterization = fourier_parameterization.Planar(frequencies, np.array(range(D)), closed_time_interval)
# 2 indicates that there are two coefficients for each (cos,sin) pair
self.position_velocity_shape = position_velocity_shape = (X,D)
self.fourier_coefficients_shape = fourier_coefficients_shape = self.fourier_curve_parameterization.fourier_coefficients_shape #(X,F,2)
self.gravitational_constant_shape = gravitational_constant_shape = (1,)
self.lagrange_multipliers_shape = lagrange_multipliers_shape = (1,)
self.time_domain_parameter_count = time_domain_parameter_count = multiindex.prod(position_velocity_shape) + multiindex.prod(gravitational_constant_shape) + multiindex.prod(lagrange_multipliers_shape)
self.frequency_domain_parameter_count = frequency_domain_parameter_count = multiindex.prod(fourier_coefficients_shape) + multiindex.prod(gravitational_constant_shape) + multiindex.prod(lagrange_multipliers_shape)
def make_frequency_domain_parameters_and_views (self):
frequency_domain_parameters = np.zeros((self.frequency_domain_parameter_count,), dtype=float)
# Define names for the views. Note that when assigning into the views, the
# [:] notation is necessary, otherwise el_form_fourier_coefficients_part and
# el_form_lagrange_multipliers_part will be reassigned to be different references
# altogether, and will no longer be views into euler_lagrange_form_buffer.
fd_fc,fd_g,fd_lm = self.frequency_domain_views(frequency_domain_parameters)
return frequency_domain_parameters,fd_fc,fd_g,fd_lm
def time_domain_views (self, time_domain_parameters):
"""
Returns a tuple (td_qv,td_g,td_lm), where each of the elements are views into:
td_qv[x,d] : The position and velocity tensor. The x index indexes the configuration space (i.e. x,y,z axis)
while the d index indexes the order of derivative (i.e. 0 is position, 1 is velocity).
td_g[:] : The scalar gravitational constant.
td_lm[:] : The Lagrange multiplier.
Note that slice notation must be used to assign to these views, otherwise a new, unrelated local variable will be declared.
"""
td_qv_count = multiindex.prod(self.position_velocity_shape)
td_g_count = multiindex.prod(self.gravitational_constant_shape)
td_lm_count = multiindex.prod(self.lagrange_multipliers_shape)
assert time_domain_parameters.shape == (self.time_domain_parameter_count,)
td_qv = time_domain_parameters[:td_qv_count].reshape(self.position_velocity_shape, order='F')
td_g = time_domain_parameters[td_qv_count:td_qv_count+td_g_count].reshape(self.gravitational_constant_shape, order='F')
td_lm = time_domain_parameters[td_qv_count+td_g_count:].reshape(self.lagrange_multipliers_shape, order='F')
return td_qv,td_g,td_lm
def frequency_domain_views (self, frequency_domain_parameters):
"""
Returns a tuple (fd_fc,fd_g,fd_lm), where each of the elements are views into:
fd_fc[x,f,c] : The Fourier coefficients of the curve. The x index indexes the configuration space (i.e. x,y,z axis),
the f index denotes the frequency, while c indexes which of cos or sin the coefficient is for (0 for cos, 1 for sin).
fd_g[:] : The scalar gravitational constant.
fd_lm[:] : The Lagrange multiplier.
Note that slice notation must be used to assign to these views, otherwise a new, unrelated local variable will be declared.
"""
fd_fc_count = multiindex.prod(self.fourier_coefficients_shape)
fd_g_count = multiindex.prod(self.gravitational_constant_shape)
fd_lm_count = multiindex.prod(self.lagrange_multipliers_shape)
fd_fc = frequency_domain_parameters[:fd_fc_count].reshape(self.fourier_coefficients_shape, order='F')
fd_g = frequency_domain_parameters[fd_fc_count:fd_fc_count+fd_g_count].reshape(self.gravitational_constant_shape, order='F')
fd_lm = frequency_domain_parameters[fd_fc_count+fd_g_count:].reshape(self.lagrange_multipliers_shape, order='F')
return fd_fc,fd_g,fd_lm
def curve_at_t (self, t, fc):
return np.einsum('dfxc,fc->xd', self.fourier_curve_parameterization.fourier_tensor[t,:,:,:], fc)
def curve (self, fc):
return np.einsum('tdfxc,fc->txd', self.fourier_curve_parameterization.fourier_tensor, fc)
def time_domain_variation_pullback_at_t (self, time_domain_parameter_variation, t):
"""Uses the Fourier-transform-parameterization of the curve to pull back a qv-g-lm vector to be a fc-g-lm vector."""
assert time_domain_parameter_variation.shape == (self.time_domain_parameter_count,)
td_qv,td_g,td_lm = self.time_domain_views(time_domain_parameter_variation)
retval = np.ndarray((self.frequency_domain_parameter_count,), dtype=float)
fd_fc,fd_g,fd_lm = self.frequency_domain_views(retval)
fd_fc[:] = np.einsum('xd,dfxc->fc', td_qv, self.fourier_curve_parameterization.fourier_tensor[t,:,:,:,:])
fd_g[:] = td_g
fd_lm[:] = td_lm
return retval
def time_domain_parameters_at_t (self, t, frequency_domain_parameters):
retval = np.ndarray((self.time_domain_parameter_count,), dtype=float)
td_qv,td_g,td_lm = self.time_domain_views(retval)
fd_fc,fd_g,fd_lm = self.frequency_domain_views(frequency_domain_parameters)
td_qv[:] = self.curve_at_t(t, fd_fc)
td_g[:] = fd_g
td_lm[:] = fd_lm
return retval
def Lambda (self, frequency_domain_parameters):
return np.dot(
self.fourier_curve_parameterization.half_open_time_interval_deltas,
np.fromiter((
self.Lambda_integrand(self.time_domain_parameters_at_t(t, frequency_domain_parameters))
for t in xrange(self.fourier_curve_parameterization.T)
), float, count=self.fourier_curve_parameterization.T)
)
def DLambda_at_time (self, t, frequency_domain_parameters):
return self.time_domain_variation_pullback_at_t(self.DLambda_integrand(self.time_domain_parameters_at_t(t, frequency_domain_parameters)), t)
def DLambda (self, frequency_domain_parameters, batch_t_v=None):
if batch_t_v is None:
batch_t_v = xrange(self.fourier_curve_parameterization.T)
batch_size = self.fourier_curve_parameterization.T
else:
batch_size = len(batch_t_v)
return sum(self.fourier_curve_parameterization.half_open_time_interval_deltas[t]*self.DLambda_at_time(t,frequency_domain_parameters) for t in batch_t_v)
def Obj (self, frequency_domain_parameters):
return np.dot(
self.fourier_curve_parameterization.half_open_time_interval_deltas,
np.fromiter((
self.Obj_integrand(self.time_domain_parameters_at_t(t, frequency_domain_parameters))
for t in xrange(self.fourier_curve_parameterization.T)
), float, count=self.fourier_curve_parameterization.T)
)
def DObj_at_time (self, t, frequency_domain_parameters):
return self.time_domain_variation_pullback_at_t(self.DObj_integrand(self.time_domain_parameters_at_t(t, frequency_domain_parameters)), t)
def DObj (self, frequency_domain_parameters, batch_t_v=None):
if batch_t_v is None:
batch_t_v = xrange(self.fourier_curve_parameterization.T)
batch_size = self.fourier_curve_parameterization.T
else:
batch_size = len(batch_t_v)
return sum(self.fourier_curve_parameterization.half_open_time_interval_deltas[t]*self.DObj_at_time(t,frequency_domain_parameters) for t in batch_t_v)
def C (self, frequency_domain_parameters):
return np.dot(
self.fourier_curve_parameterization.half_open_time_interval_deltas,
np.fromiter((
self.C_integrand(self.time_domain_parameters_at_t(t, frequency_domain_parameters))
for t in xrange(self.fourier_curve_parameterization.T)
), float, count=self.fourier_curve_parameterization.T)
)
if __name__ == '__main__':
import matplotlib.pyplot as plt
import polynomial
import scipy.integrate
import scipy.signal
import warnings
warnings.filterwarnings('ignore', module='matplotlib')
kpsc = KeplerProblemSymbolicContext(2, use_constraint=False)
time = np.linspace(0.0, 6.0, 20000)
qv_0 = np.array([1.5, 0.0, 0.0, 0.5])
qv = scipy.integrate.odeint(lambda qv,t:kpsc.X_H(qv), qv_0, time)
# TODO: Use distance squared, then fit a parabola near the min and solve
# for a better approximation of the min using subsample accuracy.
jet_dist_squared = np.sum(np.square(qv - qv_0), axis=1)
local_min_index_v = filter(lambda i:jet_dist_squared[i-1] > jet_dist_squared[i] and jet_dist_squared[i] < jet_dist_squared[i+1], xrange(1,len(jet_dist_squared)-2))
print('locally minimizing jet-distances-squared:')
for local_min_index in local_min_index_v:
print(' index: {0:3}, time: {1:17}, jet_dist_squared: {2:17}'.format(local_min_index, time[local_min_index], jet_dist_squared[local_min_index]))
assert len(local_min_index_v) > 0
assert local_min_index_v[0] > 0
estimated_period_time_index = local_min_index_v[0]
assert 5 < estimated_period_time_index < len(time)-5
if True:
# Subtracting the center of the time window is necessary for the polynomial fit to be numerically stable.
time_offset = time[estimated_period_time_index]
time_window = time[estimated_period_time_index-5:estimated_period_time_index+6] - time_offset
jet_dist_squared_window = jet_dist_squared[estimated_period_time_index-5:estimated_period_time_index+6]
samples = np.vstack((time_window, jet_dist_squared_window)).T
# Fit a quadratic polynomial
coefficients = polynomial.fit(samples, 2)
quadratically_approximated = np.vectorize(polynomial.python_function_from_coefficients(coefficients))(time_window)
max_abs_approximation_error = np.max(np.abs(quadratically_approximated - jet_dist_squared_window))
print 'max_abs_approximation_error for jet_dist_squared near minimum:', max_abs_approximation_error
assert coefficients[2] > 0.0
# Solve for the critical point, adding back in the time offset that was subtracted.
estimated_period = -0.5 * coefficients[1] / coefficients[2] + time_offset
print 'estimated_period:', estimated_period
# Save the old time for plotting.
old_time = time
# Re-run the ODE integrator using the estimated period.
time = np.linspace(0.0, estimated_period, 10001)
# qv_0 is unchanged.
qv = scipy.integrate.odeint(lambda qv,t:kpsc.X_H(qv), qv_0, time)
# Re-sample time and qv to be sparser.
time = time[::10]
assert len(time) == 1001
qv = qv[::10,:]
assert qv.shape == (1001,4)
qv = qv[:-1,:]
assert qv.shape == (1000,4)
# estimated_period = time[estimated_period_time_index]
H_v = np.apply_along_axis(kpsc.H, 1, np.hstack((qv, np.zeros((qv.shape[0],2), dtype=float))))
row_count = 2
col_count = 3
fig,axes = plt.subplots(row_count, col_count, squeeze=False, figsize=(8*col_count,8*row_count))
axis = axes[0][0]
axis.set_title('position')
axis.scatter(qv[:,0], qv[:,1], s=1)
axis.set_aspect('equal')
axis.scatter([0], [0], color='black')
axis = axes[0][1]
axis.set_title('velocity')
axis.scatter(qv[:,2], qv[:,3], s=1)
axis.set_aspect('equal')
axis.scatter([0], [0], color='black')
axis = axes[1][0]
axis.set_title('jet distance from initial condition\nestimated period: {0}'.format(estimated_period))
for local_min_index in local_min_index_v:
axis.axvline(old_time[local_min_index])
axis.plot(old_time, jet_dist_squared)
axis = axes[1][1]
axis.set_title('Hamiltonian w.r.t. time\nmin-to-max range: {0}'.format(np.max(H_v)-np.min(H_v)))
axis.plot(time[:-1], H_v)
frequencies = np.linspace(-40, 40, 40+40+1, dtype=int)
derivatives = np.array([0])
# fp = fourier_parameterization.Planar(frequencies, derivatives, time[:estimated_period_time_index+1])
# fc = np.einsum('fctx,tx->fc', fp.inverse_fourier_tensor, qv[:estimated_period_time_index,0:2])
fp = fourier_parameterization.Planar(frequencies, derivatives, time)
fc = np.einsum('fctx,tx->fc', fp.inverse_fourier_tensor, qv[:,0:2])
pickle_filename = 'kepler.pickle'
with open(pickle_filename, 'wb') as f:
import pickle
pickle.dump(
{
'frequencies':fp.frequencies,
'period':fp.period,
'fourier_coefficient_tensor':fc
},
f
)
print 'wrote "{0}"'.format(pickle_filename)
reconstructed_q = np.einsum('tdfxc,fc->dtx', fp.fourier_tensor, fc)
assert reconstructed_q.shape[0] == 1
reconstructed_q = reconstructed_q[0,:,:]
max_expected_error = 1.0e-3
max_reconstruction_errors = np.max(np.abs(reconstructed_q-qv[:,0:2]), axis=0)
print 'max_reconstruction_errors:', max_reconstruction_errors
if max_expected_error is not None:
assert np.all(max_reconstruction_errors <= max_expected_error), 'at least one component of max_reconstruction_errors ({0}) exceeded max_expected_error ({1})'.format(max_reconstruction_errors, max_expected_error)
axis = axes[0][2]
axis.set_title('reconstructed position\nmax reconstruction error: {0}'.format(np.max(max_reconstruction_errors)))
axis.plot(qv[:,0], qv[:,1], lw=5, color='green', alpha=0.2)
axis.scatter(reconstructed_q[:,0], reconstructed_q[:,1], s=1)
axis.set_aspect('equal')
axis.scatter([0], [0], color='black')
axis = axes[1][2]
axis.set_title('log abs of Fourier coefficients')
axis.semilogy(fp.frequencies, np.linalg.norm(fc, axis=1), 'o')
axis.semilogy(fp.frequencies, np.linalg.norm(fc, axis=1), lw=5, alpha=0.2)
fig.tight_layout()
filename = 'kepler.test.png'
plt.savefig(filename)
print('wrote "{0}"'.format(filename))
plt.close(fig)
| 50.368146 | 220 | 0.696024 | 12,886 | 0.66798 | 0 | 0 | 0 | 0 | 0 | 0 | 5,603 | 0.290446 |
7f497463579627def6a6bc8b025032e2117e0a72 | 1,029 | py | Python | flaskr/tripods/tripod.py | ardtieboy/campy | dc59c62395aa45c0d125f6187a8a3b19521469d3 | [
"MIT"
] | null | null | null | flaskr/tripods/tripod.py | ardtieboy/campy | dc59c62395aa45c0d125f6187a8a3b19521469d3 | [
"MIT"
] | null | null | null | flaskr/tripods/tripod.py | ardtieboy/campy | dc59c62395aa45c0d125f6187a8a3b19521469d3 | [
"MIT"
] | null | null | null | import pantilthat
class Tripod(object):
def __init__(self):
self.horizontal = 0
self.vertical = 0
self.step_size = 5
pantilthat.pan(0)
pantilthat.tilt(0)
def left(self):
if (-80 < self.horizontal):
self.horizontal = self.horizontal - self.step_size
print('moving left ' + str(self.horizontal))
pantilthat.pan(self.horizontal)
def right(self):
if (self.horizontal < 80):
self.horizontal = self.horizontal + self.step_size
print('moving right ' + str(self.horizontal))
pantilthat.pan(self.horizontal)
def up(self):
if (-80 < self.vertical):
self.vertical = self.vertical - self.step_size
print('moving up ' + str(self.vertical))
pantilthat.tilt(self.vertical)
def down(self):
if (self.vertical < 80):
self.vertical = self.vertical + self.step_size
print('moving down ' + str(self.vertical))
pantilthat.tilt(self.vertical) | 30.264706 | 62 | 0.597668 | 1,010 | 0.981535 | 0 | 0 | 0 | 0 | 0 | 0 | 55 | 0.05345 |
7f49b39edb1cf25e08b2f0cebd80eaca4c038d5a | 5,592 | py | Python | mercury_engine_data_structures/pkg_editor.py | duncathan/mercury-engine-data-structures | 1bc4117dba9c7961d9a8f1b7f11b62daaf82b09b | [
"MIT"
] | null | null | null | mercury_engine_data_structures/pkg_editor.py | duncathan/mercury-engine-data-structures | 1bc4117dba9c7961d9a8f1b7f11b62daaf82b09b | [
"MIT"
] | null | null | null | mercury_engine_data_structures/pkg_editor.py | duncathan/mercury-engine-data-structures | 1bc4117dba9c7961d9a8f1b7f11b62daaf82b09b | [
"MIT"
] | null | null | null | import collections
import contextlib
import os.path
import typing
from contextlib import ExitStack
from pathlib import Path
from typing import BinaryIO, Dict, Optional, Generator, Iterator, Set
from mercury_engine_data_structures import formats, dread_data
from mercury_engine_data_structures.formats.base_resource import AssetId, BaseResource, NameOrAssetId, resolve_asset_id
from mercury_engine_data_structures.formats.pkg import PKGHeader, Pkg
from mercury_engine_data_structures.game_check import Game
class PkgEditor:
"""
Manages efficiently reading all PKGs in the game and writing out modifications to a new path.
_files_for_asset_id: mapping of asset id to all pkgs it can be found at
_ensured_asset_ids: mapping of pkg name to assets we'll copy into it when saving
_modified_resources: mapping of asset id to bytes. When saving, these asset ids are replaced
"""
_files_for_asset_id: Dict[AssetId, Set[str]]
_ensured_asset_ids: Dict[str, Set[AssetId]]
_modified_resources: Dict[AssetId, bytes]
def __init__(self, root: Path, target_game: Game = Game.DREAD):
all_pkgs = root.rglob("*.pkg")
self.files = {}
self.root = root
self.target_game = target_game
self.headers = {}
self._files_for_asset_id = collections.defaultdict(set)
self._ensured_asset_ids = {}
self._modified_resources = {}
for pkg_path in all_pkgs:
name = pkg_path.relative_to(root).as_posix()
self.files[name] = pkg_path
with pkg_path.open("rb") as f:
self.headers[name] = PKGHeader.parse_stream(f, target_game=target_game)
self._ensured_asset_ids[name] = set()
for entry in self.headers[name].file_entries:
self._files_for_asset_id[entry.asset_id].add(name)
def all_asset_ids(self) -> Iterator[AssetId]:
"""
Returns an iterator of all asset ids in the available pkgs.
"""
yield from self._files_for_asset_id.keys()
def all_asset_names(self) -> Iterator[str]:
"""
Returns an iterator of all known names of the present asset ids.
"""
for asset_id in self.all_asset_ids():
name = dread_data.name_for_asset_id(asset_id)
if name is not None:
yield name
def find_pkgs(self, asset_id: NameOrAssetId) -> Iterator[str]:
yield from self._files_for_asset_id[resolve_asset_id(asset_id)]
def get_raw_asset(self, asset_id: NameOrAssetId, in_pkg: Optional[str] = None) -> bytes:
asset_id = resolve_asset_id(asset_id)
if asset_id in self._modified_resources:
return self._modified_resources[asset_id]
for name, header in self.headers.items():
if in_pkg is not None and name != in_pkg:
continue
for entry in header.file_entries:
if entry.asset_id == asset_id:
with self.files[name].open("rb") as f:
f.seek(entry.start_offset)
return f.read(entry.end_offset - entry.start_offset)
raise ValueError(f"Unknown asset_id: {asset_id:0x}")
def get_parsed_asset(self, name: str, in_pkg: Optional[str] = None) -> BaseResource:
data = self.get_raw_asset(name, in_pkg)
file_format = os.path.splitext(name)[1][1:]
return formats.format_for(file_format).parse(data, target_game=self.target_game)
def replace_asset(self, asset_id: NameOrAssetId, new_data: typing.Union[bytes, BaseResource]):
if not isinstance(new_data, bytes):
new_data = new_data.build()
self._modified_resources[resolve_asset_id(asset_id)] = new_data
def ensure_present(self, pkg_name: str, asset_id: NameOrAssetId):
"""
Ensures the given pkg has the give assets, collecting from other pkgs if needed.
"""
if pkg_name not in self._ensured_asset_ids:
raise ValueError(f"Unknown pkg_name: {pkg_name}")
asset_id = resolve_asset_id(asset_id)
# If the pkg already has the given asset, do nothing
if pkg_name not in self._files_for_asset_id[asset_id]:
self._ensured_asset_ids[pkg_name].add(asset_id)
def save_modified_pkgs(self):
modified_pkgs = set()
for asset_id in self._modified_resources.keys():
modified_pkgs.update(self._files_for_asset_id[asset_id])
# Read all asset ids we need to copy somewhere else
asset_ids_to_copy = {}
for asset_ids in self._ensured_asset_ids.values():
for asset_id in asset_ids:
if asset_id not in asset_ids_to_copy:
asset_ids_to_copy[asset_id] = self.get_raw_asset(asset_id)
for pkg_name in modified_pkgs:
with self.files[pkg_name].open("rb") as f:
pkg = Pkg.parse_stream(f, target_game=self.target_game)
for asset_id, data in self._modified_resources.items():
if pkg_name in self._files_for_asset_id[asset_id]:
pkg.replace_asset(asset_id, data)
for asset_id in self._ensured_asset_ids[pkg_name]:
pkg.add_asset(asset_id, asset_ids_to_copy[asset_id])
self._files_for_asset_id[asset_id].add(pkg_name)
with self.files[pkg_name].open("wb") as f:
pkg.build_stream(f)
# Clear the ensured asset ids, since we've written these
self._ensured_asset_ids[pkg_name] = set()
self._modified_resources = {}
| 40.817518 | 119 | 0.662375 | 5,082 | 0.908798 | 626 | 0.111946 | 0 | 0 | 0 | 0 | 890 | 0.159156 |
7f49d895aed1ee10667f68cdf1cd1adf069c4fea | 142 | py | Python | code/textProcessing.py | corollari/BaaCL | 3ebe9ba7c3859243351fe1b12d4eb114bb51b441 | [
"Unlicense"
] | 1 | 2019-03-06T19:43:46.000Z | 2019-03-06T19:43:46.000Z | code/textProcessing.py | corollari/BaaL | 3ebe9ba7c3859243351fe1b12d4eb114bb51b441 | [
"Unlicense"
] | null | null | null | code/textProcessing.py | corollari/BaaL | 3ebe9ba7c3859243351fe1b12d4eb114bb51b441 | [
"Unlicense"
] | null | null | null | def preprocess(text):
text=text.replace('\n', '\n\r')
return text
def getLetter():
return open("./input/letter.txt", "r").read()
| 20.285714 | 49 | 0.605634 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 33 | 0.232394 |
7f4a8619142279843195d19ca55dc1994a765971 | 4,665 | py | Python | lrthubcore/users/api/views.py | xrojan/lrthub-core | 757189942c87f7136fd1f1fee536375d248d8233 | [
"BSD-3-Clause"
] | null | null | null | lrthubcore/users/api/views.py | xrojan/lrthub-core | 757189942c87f7136fd1f1fee536375d248d8233 | [
"BSD-3-Clause"
] | null | null | null | lrthubcore/users/api/views.py | xrojan/lrthub-core | 757189942c87f7136fd1f1fee536375d248d8233 | [
"BSD-3-Clause"
] | null | null | null | # Created by Joshua de Guzman on 09/07/2018
# @email code@jmdg.io
from django_filters.rest_framework import DjangoFilterBackend
from rest_framework.permissions import AllowAny, IsAuthenticated
from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework import status, generics
from .. import models
from . import pagination
from . import serializers
class UserCreate(APIView):
permission_classes = (AllowAny,)
def post(self, request):
serializer = serializers.UserSerializer(data=request.data)
if serializer.is_valid():
user = serializer.save()
if user:
response = {"status_code": status.HTTP_201_CREATED,
"message": "Successfully created",
"result": request.data}
return Response(response)
response = {"status_code": status.HTTP_400_BAD_REQUEST,
"message": "Failed to create user",
"result": serializer.errors}
return Response(response)
class UserProfileGenderList(generics.ListAPIView):
queryset = models.Gender.objects.all()
serializer_class = serializers.GenderSerializer
class UserProfileNationalityList(generics.ListAPIView):
queryset = models.Nationality.objects.all()
serializer_class = serializers.NationalitySerializer
class UserProfileMaritalStatusList(generics.ListAPIView):
queryset = models.MaritalStatus.objects.all()
serializer_class = serializers.MaritalStatusSerializer
class UserProfileEmploymentTypeList(generics.ListAPIView):
queryset = models.EmploymentType.objects.all()
serializer_class = serializers.EmploymentTypeSerializer
class UserProfileDisabilityList(generics.ListAPIView):
queryset = models.Disability.objects.all()
serializer_class = serializers.DisabilitiesSerializer
class UserProfileList(generics.ListCreateAPIView):
serializer_class = serializers.UserProfileSerializer
pagination_class = pagination.CustomPagination
def get_queryset(self):
queryset = models.UserProfile.objects.all()
user_id = int(self.request.GET.get('user_id', None))
return queryset.filter(user_id=user_id)
def create(self, request, *args, **kwargs):
user = self.request.user
request_user_id = int(request.POST.get('user_id', ''))
if user.id == request_user_id:
super(UserProfileList, self).create(request, args, kwargs)
response = {"status_code": status.HTTP_201_CREATED,
"message": "Successfully created",
"result": request.data}
return Response(response)
response = {"status_code": status.HTTP_403_FORBIDDEN,
"message": "You are not allowed to continue with the request",
"result": None}
return Response(response)
class UserProfileDetail(generics.RetrieveUpdateDestroyAPIView):
queryset = models.UserProfile.objects.all()
serializer_class = serializers.UserProfileSerializer
def retrieve(self, request, *args, **kwargs):
user = self.request.user
request_user_id = self.kwargs['pk']
if user.id == request_user_id:
super(UserProfileDetail, self).retrieve(request, args, kwargs)
instance = self.get_object()
serializer = self.get_serializer(instance)
data = serializer.data
response = {"status_code": status.HTTP_200_OK,
"message": "Successfully retrieved",
"result": data}
return Response(response)
response = {"status_code": status.HTTP_403_FORBIDDEN,
"message": "You are not allowed to continue with the request",
"result": None}
return Response(response)
def patch(self, request, *args, **kwargs):
user = self.request.user
request_user_id = self.kwargs['pk']
if user.id == request_user_id:
super(UserProfileDetail, self).patch(request, args, kwargs)
instance = self.get_object()
serializer = self.get_serializer(instance)
data = serializer.data
response = {"status_code": status.HTTP_200_OK,
"message": "Successfully updated",
"result": data}
return Response(response)
response = {"status_code": status.HTTP_403_FORBIDDEN,
"message": "You are not allowed to continue with the request",
"result": None}
return Response(response)
| 37.620968 | 82 | 0.653805 | 4,244 | 0.909753 | 0 | 0 | 0 | 0 | 0 | 0 | 595 | 0.127546 |
7f4a9a45f9839d4156f378a8a84cdc5c95302052 | 837 | py | Python | tests/test_api_key.py | sodrooome/bmaclient | 8d3609a63e3e2576642ecde77245ee0b02225e31 | [
"MIT"
] | null | null | null | tests/test_api_key.py | sodrooome/bmaclient | 8d3609a63e3e2576642ecde77245ee0b02225e31 | [
"MIT"
] | null | null | null | tests/test_api_key.py | sodrooome/bmaclient | 8d3609a63e3e2576642ecde77245ee0b02225e31 | [
"MIT"
] | null | null | null | import os
import unittest
from bmaclient.utils import get_api_key_from_file
DATA_DIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'data')
class APIKeyTest(unittest.TestCase):
def test_get_api_key_from_file(self):
path = os.path.join(DATA_DIR, 'api_key.txt')
key = get_api_key_from_file(path)
self.assertEqual(key, 'THIS_IS_API_KEY_VALUE')
def test_get_api_key_from_empty_file(self):
path = os.path.join(DATA_DIR, 'api_key_empty.txt')
key = get_api_key_from_file(path)
self.assertEqual(key, '')
def test_get_api_key_from_empty_file_strict(self):
path = os.path.join(DATA_DIR, 'api_key_empty.txt')
with self.assertRaises(ValueError):
key = get_api_key_from_file(path, strict=True)
if __name__ == '__main__':
unittest.main()
| 28.862069 | 75 | 0.706093 | 631 | 0.753883 | 0 | 0 | 0 | 0 | 0 | 0 | 92 | 0.109916 |
7f4c0b226d7280aa82d0b514ec3937f568c281d1 | 498 | py | Python | planner/forms.py | celord/mealprep | c51329dd86953963d0e0405e9a929553eca1e2cf | [
"MIT"
] | null | null | null | planner/forms.py | celord/mealprep | c51329dd86953963d0e0405e9a929553eca1e2cf | [
"MIT"
] | null | null | null | planner/forms.py | celord/mealprep | c51329dd86953963d0e0405e9a929553eca1e2cf | [
"MIT"
] | null | null | null | from django import forms
from django.forms import ModelForm
from .models import Plan
class DateInput(forms.DateInput):
input_type = "date"
class AddPlanForm(ModelForm):
class Meta:
model = Plan
# fields = fields = '__all__'
fields = [
"date",
"meal",
"mealtype",
"photo",
]
widgets = {
"date": DateInput(),
# 'comments': Textarea(attrs={'cols': 80, 'rows': 20}),
}
| 19.92 | 67 | 0.512048 | 406 | 0.815261 | 0 | 0 | 0 | 0 | 0 | 0 | 125 | 0.251004 |
7f4c4a6d4785bd3dfed7a18ec25a7e8626976917 | 2,856 | py | Python | lib/harm_plot.py | pnlbwh/multi-shell-dMRIharmonization | 46e207c5d2b7fd68ddbbd1b305c33cfd45351ee8 | [
"CNRI-Python",
"Info-ZIP"
] | 4 | 2020-04-28T15:31:07.000Z | 2022-02-15T07:04:21.000Z | lib/harm_plot.py | pnlbwh/multi-shell-dMRIharmonization | 46e207c5d2b7fd68ddbbd1b305c33cfd45351ee8 | [
"CNRI-Python",
"Info-ZIP"
] | 30 | 2019-11-10T20:51:34.000Z | 2021-04-19T19:08:14.000Z | lib/harm_plot.py | pnlbwh/multi-shell-dMRIharmonization | 46e207c5d2b7fd68ddbbd1b305c33cfd45351ee8 | [
"CNRI-Python",
"Info-ZIP"
] | 3 | 2019-10-18T16:06:03.000Z | 2021-02-21T01:10:45.000Z | #!/usr/bin/env python
import numpy as np
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import pandas as pd
from conversion import read_imgs_masks
from os.path import isfile, basename
XERR=0.1
ELINEWIDTH=3
CAPSIZE=5
CAPTHICK=3
FMT='cD'
def harm_plot(ydata, labels, outPrefix, bshell_b):
'''
:param ydata: list of [y1, y2, y3, ...] where each yi is a list
:param labels: list of strings
:param outPrefix:
:return:
'''
outPrefix += f'_b{bshell_b}'
labels= list(labels)
num_series, num_sub= np.shape(ydata)
iter_obj= [i for i in range(num_series)]
# errorbar plot
plt.figure(1)
plt.grid(True)
for i in iter_obj:
x= list(i*np.ones((num_sub,)))
y= ydata[i]
plt.plot(x, y, 'r*')
plt.errorbar([i], np.mean(y), xerr=XERR, yerr=np.std(y),
ecolor='k', capsize=CAPSIZE, capthick=CAPTHICK, elinewidth=ELINEWIDTH, fmt=FMT)
plt.xticks(iter_obj, labels)
plt.title('Comparison of meanFA before and after harmonization')
plt.ylabel('meanFA over IIT_mean_FA_skeleton')
plt.savefig(outPrefix+'_ebarplot.png')
# plt.show()
# box plot
# plt.figure(2)
# plt.grid(True)
# for i in iter_obj:
# x = list(i * np.ones((num_sub,)))
# y = ydata[i]
# plt.plot(x, y, 'r*')
#
# plt.boxplot(ydata, labels=labels, positions=iter_obj,
# boxprops=dict(linewidth=4),
# medianprops=dict(linewidth=4),
# whiskerprops=dict(linewidth=2))
#
#
# plt.title(f'Comparison of boxplot before and after harmonization for b{bshell_b}')
# plt.ylabel('meanFA over IIT_mean_FA_skeleton')
# plt.savefig(outPrefix+'_boxplot.png')
# plt.show()
# return (outPrefix+'_ebarplot.png', outPrefix+'_boxplot.png')
return outPrefix+'_ebarplot.png'
def generate_csv(imgs, site_means, outPrefix, bshell_b):
try:
imgs, _= read_imgs_masks(imgs)
except:
pass
statFile = outPrefix + '_stat.csv'
if isfile(statFile):
df= pd.read_csv(statFile)
df= df.assign(**{f'meanFA b{bshell_b}':site_means})
else:
stat = {'subject': [basename(f) for f in imgs], f'meanFA b{bshell_b}': site_means}
df = pd.DataFrame(stat)
df.to_csv(statFile, index=False)
if __name__=='__main__':
sub=['hi','hello','go','come']
ref_mean= [0.46, 0.49, 0.44, 0.40]
target_mean_before= [0.42, 0.58, 0.43, 0.66]
target_mean_after= [0.5 , 0.45, 0.40, 0.55]
labels=['Reference','Target before','Target after']
bshell_b= 2000
harm_plot([ref_mean, target_mean_before, target_mean_after], labels, '/tmp/abc', bshell_b)
# harm_plot([ref_mean], ['Reference'], '/tmp/abc', bshell_b)
generate_csv(sub, ref_mean, '/tmp/abc', bshell_b)
| 27.2 | 100 | 0.619748 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,135 | 0.397409 |
7f4c6dcef66737c0d797d459d092bd0f3dc07425 | 1,913 | py | Python | tests/test_preproc_badframes.py | ChrisDelaX/VIP | 7b728bdc78fdeb693e19de269ddfffba15064fb4 | [
"MIT"
] | 2 | 2017-02-10T02:02:17.000Z | 2018-02-16T16:07:24.000Z | tests/test_preproc_badframes.py | ChrisDelaX/VIP | 7b728bdc78fdeb693e19de269ddfffba15064fb4 | [
"MIT"
] | null | null | null | tests/test_preproc_badframes.py | ChrisDelaX/VIP | 7b728bdc78fdeb693e19de269ddfffba15064fb4 | [
"MIT"
] | 2 | 2020-07-18T19:31:03.000Z | 2022-01-24T21:11:20.000Z | """
Tests for the badframes detection routines.
"""
import numpy as np
import vip_hci as vip
def test_badfr_corr():
im1 = vip.var.create_synth_psf(shape=(19, 19), fwhm=2)
im2 = vip.var.create_synth_psf(shape=(19, 19), fwhm=(2, 4))
cube = np.array([im1, im2, im1, im2])
gind, bind = vip.preproc.cube_detect_badfr_correlation(cube, 0, 9,
plot=False)
assert np.array_equal(gind, np.array([0, 2]))
assert np.array_equal(bind, np.array([1, 3]))
def test_badfr_ellip():
im1 = vip.var.create_synth_psf(shape=(19, 19), fwhm=2)
im2 = vip.var.create_synth_psf(shape=(19, 19), fwhm=(2, 4))
cube = np.array([im1, im2, im1, im2])
gind, bind = vip.preproc.cube_detect_badfr_ellipticity(cube, 2,
crop_size=17,
plot=False)
assert np.array_equal(gind, np.array([0, 2]))
assert np.array_equal(bind, np.array([1, 3]))
def test_badfr_pxstat():
im1_1 = vip.var.create_synth_psf(shape=(19, 19), fwhm=3)
im1_2 = vip.var.create_synth_psf(shape=(19, 19), fwhm=4)
im1_3 = vip.var.create_synth_psf(model='moff', shape=(19, 19), fwhm=6) - 0.3
im1_3 = vip.var.mask_circle(im1_3, 4)
im1 = im1_2 - im1_1
im2 = im1 + im1_3 + 1
im3 = im1 + im1_3 + 0.2
cube = np.array([im1, im1, im1, im1, im1, im1, im3, im2, im2, im3, im1,
im1, im1, im1, im1, im1])
gind, bind = vip.preproc.cube_detect_badfr_pxstats(cube, in_radius=3,
width=3, window=None,
plot=False)
assert np.array_equal(gind, np.array([0, 1, 2, 3, 4, 5, 6, 9, 10,
11, 12, 13, 14, 15]))
assert np.array_equal(bind, np.array([7, 8]))
| 39.854167 | 80 | 0.531103 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 58 | 0.030319 |
7f4d15cfb3ed6c16d32e8b711404ca08ebd94da8 | 13,774 | py | Python | DE_rpy2.py | jhonP-Li/DE_rpy2 | 460724631527dc386a35268b9f923ab5c708166a | [
"MIT"
] | 6 | 2021-05-02T09:15:59.000Z | 2022-03-27T23:41:41.000Z | DE_rpy2.py | jhonP-Li/DE_rpy2 | 460724631527dc386a35268b9f923ab5c708166a | [
"MIT"
] | null | null | null | DE_rpy2.py | jhonP-Li/DE_rpy2 | 460724631527dc386a35268b9f923ab5c708166a | [
"MIT"
] | null | null | null | """
MIT License
Copyright (c) 2021 Li Pan
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
"""
import pandas as pd
import numpy as np
import warnings
import rpy2.robjects as robjects
from rpy2.robjects import numpy2ri, pandas2ri, Formula
from rpy2.robjects.packages import importr
pandas2ri.activate()
numpy2ri.activate()
# import R libraries
DESeq2 = importr('DESeq2')
edgeR = importr('edgeR')
Limma = importr('limma')
stats = importr('stats')
to_dataframe = robjects.r('function(x) data.frame(x)')
class DE_rpy2:
"""
Running DESeq2, edgeR, limma through rpy2
input:
count_matrix: a pandas dataframe with each column as count
(float values in FPKM/RPKM are also acceptable as internal rounding will be done)
, and a id column for gene id
example:
id sampleA sampleB
geneA 5.1 1
geneB 4.2 5
geneC 1 2
design_matrix: a pandas dataframe with each column as a condition, and one row for one sample
Note that the sample name must be the index not a column
condition
sampleA1 treated
sampleA2 treated
sampleB1 untreated
sampleB2 untreated
design_formula: default to be the column name of design matrix, example: "~ condition""
If it contains multiple conditions, this formula must be customised,
or the DESeq2 will only consider the first condition.
gene_column: column name of gene id columns in count_matrix, default = 'id'
"""
def __init__(self, count_matrix, design_matrix, design_formula=None, gene_column='id'):
assert gene_column in count_matrix, \
'column: \'%s\', not found in count matrix' % gene_column
assert count_matrix.shape[1] - 1 == design_matrix.shape[0], \
'The number of rows in design matrix must ' \
'be equal to the number of samples in count matrix'
assert all(pd.isna(count_matrix)), \
'Null values are found in count matrix' \
'Please check it'
assert len(design_matrix.columns), \
'Columns names are needed in design matrix'
if 'float' in count_matrix.drop(gene_column, axis=1):
warnings.warn('DESeq2 and edgeR only accept integer counts\n'
'The values in count matrix are automatically rounded\n'
'In fact the FPKM/RPKM input is not encouraged by DESeq2 officially\n')
# parameters used in DESeq2
self.count_matrix = pandas2ri.py2ri(count_matrix.drop(gene_column, axis=1).astype('int'))
self.design_matrix = pandas2ri.py2ri(design_matrix)
self.gene_ids = count_matrix[gene_column]
self.gene_column = gene_column
self.deseq2_result = None
self.deseq2_label = None
if design_formula is None:
condition = design_matrix.columns[0]
if len(design_matrix.columns) > 1:
warnings.warn('Multiple conditions are set in design matrix,\n'
'you\'d better customise the design formula.\n'
'Here it only considers the first condition\n')
self.design_formula = Formula('~ ' + condition)
else:
self.design_formula = Formula(design_formula)
# parameters used in edgeR
self.edgeR_group = numpy2ri.py2ri(design_matrix.iloc[:, 0].values)
self.edgeR_gene_names = numpy2ri.py2ri(count_matrix[gene_column].values)
self.edgeR_result = None
self.edgeR_label = None
# parameters used in limma
self.limma_result = None
self.limma_label = None
self.final_label = None
def deseq2(self, threshold=0.05, **kwargs):
"""
Run the standard DESeq2 workflow.
Get the DESeq2 results as DataFrame.
Return the label of each gene: 0 for not differentially expressed,
1 for differentially expressed.
:param threshold: threshold for the adjusted p-value.
default = 0.05.
:param kwargs: parameters of DESeq2 functions.
See official instructions for details:
http://www.bioconductor.org/packages/release/bioc/vignettes/DESeq2/inst/doc/DESeq2.html
:return:
label: pandas.DataFrame format with 2 columns: gene ids and labels
"""
# Run DESeq2 workflow
dds = DESeq2.DESeqDataSetFromMatrix(countData=self.count_matrix,
colData=self.design_matrix,
design=self.design_formula)
dds = DESeq2.DESeq(dds, **kwargs)
res = DESeq2.results(dds, **kwargs)
# Store the output matrix as DataFrame
self.deseq2_result = pandas2ri.ri2py(to_dataframe(res))
self.deseq2_result[self.gene_column] = self.gene_ids
# The adjusted p-value in the DESeq2 results
# may contain NAN
if any(pd.isna(self.deseq2_result['padj'].values)):
warnings.warn('There exist NAN in the adjusted p-value\n'
'see https://bioconductor.org/packages/release/bioc/vignettes/DESeq2/'
'inst/doc/DESeq2.html#why-are-some-p-values-set-to-na\n')
# Reject the H0 hypothesis if p-value < threshold
labels = [int(x) for x in (self.deseq2_result['padj'] < threshold)]
label = pd.DataFrame({self.gene_column: self.gene_ids, 'label': labels})
self.deseq2_label = label
return label
def edger(self, threshold=0.05):
"""
Run the standard edgeR workflow.
Get the edgR results as DataFrame.
Return the label of each gene:
0 for not differentially expressed,
1 for differentially expressed.
:param threshold: threshold for the p-value.
default = 0.05.
See official instructions for details:
https://www.bioconductor.org/packages/release/bioc/vignettes/edgeR/inst/doc/edgeRUsersGuide.pdf
:return:
label: pandas.DataFrame format with 2 columns: gene ids and labels
"""
# run edgeR workflow
# Create the DGEList object
dgList = edgeR.DGEList(counts=self.count_matrix, group=self.edgeR_group, genes=self.edgeR_gene_names)
# Normalize
dgList = edgeR.calcNormFactors(dgList, method="TMM")
# Setting up the model
robjects.r.assign('edgeR_group', self.edgeR_group)
designMat = stats.model_matrix(Formula('~ edgeR_group'))
# Estimating Dispersions
dgList = edgeR.estimateGLMCommonDisp(dgList, design=designMat)
dgList = edgeR.estimateGLMTrendedDisp(dgList, design=designMat)
dgList = edgeR.estimateGLMTagwiseDisp(dgList, design=designMat)
# Differential Expression
fit = edgeR.glmQLFit(dgList, designMat)
test = edgeR.glmQLFTest(fit)
res = edgeR.topTags(test, n=self.count_matrix.nrow)
res_df = pandas2ri.ri2py(to_dataframe(res))
# Sort the result on gene ids
gene_df = pd.DataFrame({'genes': self.gene_ids})
self.edgeR_result = pd.merge(gene_df, res_df, how='left')
# Reject the H0 hypothesis
labels = [int(x) for x in (self.edgeR_result['PValue'] < threshold)]
label = pd.DataFrame({self.gene_column: self.gene_ids, 'label': labels})
self.edgeR_label = label
return label
def limma(self, threshold=0.05):
"""
Run the standard limma workflow.
Get the limma results as DataFrame.
Return the label of each gene:
0 for not differentially expressed,
1 for differentially expressed.
:param threshold: threshold for the p-value.
default = 0.05.
See official instructions for details:
https://ucdavis-bioinformatics-training.github.io/2018-June-RNA-Seq-Workshop/thursday/DE.html
:return:
label: pandas.DataFrame format with 2 columns: gene ids and labels
"""
# Create the DGEList object
dgList = edgeR.DGEList(counts=self.count_matrix, group=self.edgeR_group, genes=self.edgeR_gene_names)
# Normalize
dgList = edgeR.calcNormFactors(dgList, method="TMM")
# Setting up the model
robjects.r.assign('edgeR_group', self.edgeR_group)
designMat = stats.model_matrix(Formula('~ edgeR_group'))
# voom
v = Limma.voom(dgList, designMat)
# fitting
fit = Limma.lmFit(v, designMat)
fit = Limma.eBayes(fit)
res = Limma.topTable(fit, n=self.count_matrix.nrow)
res_df = pandas2ri.ri2py(to_dataframe(res))
# Sort the result on gene ids
gene_df = pd.DataFrame({'genes': self.gene_ids})
self.limma_result = pd.merge(gene_df, res_df, how='left')
# Reject the H0 hypothesis
labels = [int(x) for x in (self.limma_result['adj.P.Val'] < threshold)]
label = pd.DataFrame({self.gene_column: self.gene_ids, 'label': labels})
self.limma_label = label
return label
def plot_label_difference(self):
"""
Plot the Venn diagram of the 3 label output.
Since we only interest in the differentially expressed genes.
The number on Venn diagram shows the number of samples labeled as 1.
Say differentially expressed genes.
"""
if self.limma_label is None:
warnings.warn('Seems you haven\'t get limma label\n'
'Automatically running limma...')
self.limma_label = self.limma()
if self.deseq2_label is None:
warnings.warn('Seems you haven\'t get DESeq2 label\n'
'Automatically running DESeq2...')
self.deseq2_label = self.deseq2()
if self.edgeR_label is None:
warnings.warn('Seems you haven\'t get edgeR label\n'
'Automatically running edgeR...')
self.edgeR_label = self.edger()
# Import the plot package
from matplotlib_venn import venn3
import matplotlib.pyplot as plt
labels = np.array([self.deseq2_label['label'].values, self.edgeR_label['label'].values,
self.limma_label['label'].values]).T
names = ['DESeq2', 'edgeR', 'limma']
venn_df = pd.DataFrame(data=labels, columns=names)
sets = {'000': 0, '001': 0, '010': 0, '011': 0, '100': 0, '101': 0, '110': 0, '111': 0}
for i in range(venn_df.shape[0]):
loc = [str(num) for num in venn_df.iloc[i, :]]
loc = loc[0] + loc[1] + loc[2]
sets[loc] += 1
venn3(sets, set_labels=names)
plt.show()
return sets
def get_final_label(self, method='inner'):
"""
There are 2 methods availabel:
inner: set those genes as differentially expressed,
say label 1, if all 3 tools agreed
vote: set those genes as differentially expressed,
say label 1, if all 2 out of the 3 tools agreed
union: set those genes as differentially expressed,
say label 1, as long as 1 tool agreed
"""
label = None
menu = ['inner', 'vote', 'union']
assert method in menu, \
'Please choose the correct method'
if self.limma_label is None:
warnings.warn('Seems you haven\'t get limma label\n'
'Automatically running limma...')
self.limma_label = self.limma()
if self.deseq2_label is None:
warnings.warn('Seems you haven\'t get DESeq2 label\n'
'Automatically running DESeq2...')
self.deseq2_label = self.deseq2()
if self.edgeR_label is None:
warnings.warn('Seems you haven\'t get edgeR label\n'
'Automatically running edgeR...')
self.edgeR_label = self.edger()
labels = self.deseq2_label['label'].values + self.edgeR_label['label'].values + self.limma_label['label'].values
if method == 'inner':
label = [int(x) for x in (labels == 3)]
if method == 'vote':
label = [int(x) for x in (labels >= 2)]
if method == 'union':
label = [int(x) for x in (labels >= 1)]
self.final_label = pd.DataFrame({self.gene_column: self.gene_ids, 'label': label})
return self.final_label
| 43.726984 | 121 | 0.614709 | 12,249 | 0.889284 | 0 | 0 | 0 | 0 | 0 | 0 | 6,732 | 0.488747 |
7f4dddafff562d1d609415b1456d1843f25b7c47 | 3,049 | py | Python | cgatpipelines/tools/pipeline_docs/pipeline_rnaseqdiffexpression/trackers/Results.py | kevinrue/cgat-flow | 02b5a1867253c2f6fd6b4f3763e0299115378913 | [
"MIT"
] | 49 | 2015-04-13T16:49:25.000Z | 2022-03-29T10:29:14.000Z | cgatpipelines/tools/pipeline_docs/pipeline_rnaseqdiffexpression/trackers/Results.py | kevinrue/cgat-flow | 02b5a1867253c2f6fd6b4f3763e0299115378913 | [
"MIT"
] | 252 | 2015-04-08T13:23:34.000Z | 2019-03-18T21:51:29.000Z | cgatpipelines/tools/pipeline_docs/pipeline_rnaseqdiffexpression/trackers/Results.py | kevinrue/cgat-flow | 02b5a1867253c2f6fd6b4f3763e0299115378913 | [
"MIT"
] | 22 | 2015-05-21T00:37:52.000Z | 2019-09-25T05:04:27.000Z |
from CGATReport.Tracker import *
from CGATReport.Utils import PARAMS as P
from IsoformReport import *
###############################################################################
# parse params
###############################################################################
DATABASE = P.get('', P.get('sql_backend', 'sqlite:///./csvdb'))
ANNOTATIONS_DATABASE = P.get('annotations_database')
###############################################################################
# trackers
###############################################################################
class DeseqFeatureResultsGenes(IsoformTracker):
pattern = "deseq2_featurecounts__(.*)_genes_results"
def __call__(self, track, slice=None):
statement = '''
SELECT A.control_name, A.treatment_name, A.control_mean,
A.treatment_mean, A.test_id, A.l2fold, A.p_value, A.p_value_adj,
A.significant FROM deseq2_featurecounts__%(track)s_genes_results
AS A ORDER BY A.significant DESC,
A.l2fold ASC;
'''
return self.getAll(statement)
class EdgerFeatureResultsGenes(IsoformTracker):
pattern = "edger_featurecounts__(.*)_genes_results"
def __call__(self, track, slice=None):
statement = '''
SELECT A.control_name, A.treatment_name, A.control_mean,
A.treatment_mean, A.test_id, A.l2fold, A.p_value, A.p_value_adj,
A.significant FROM edger_featurecounts__%(track)s_genes_results
AS A ORDER BY A.significant DESC,
A.l2fold ASC
'''
return self.getAll(statement)
class DeseqKallistoResultsGenes(IsoformTracker):
pattern = "deseq2_kallisto__(.*)_genes_results"
def __call__(self, track, slice=None):
statement = '''
SELECT A.control_name, A.treatment_name, A.control_mean,
A.treatment_mean, A.test_id, A.l2fold, A.p_value, A.p_value_adj,
A.significant FROM deseq2_kallisto__%(track)s_genes_results
AS A ORDER BY A.significant DESC,
A.l2fold ASC
'''
return self.getAll(statement)
class EdgerKallistoResultsGenes(IsoformTracker):
pattern = "edger_kallisto__(.*)_genes_results"
def __call__(self, track, slice=None):
statement = '''
SELECT A.control_name, A.treatment_name, A.control_mean,
A.treatment_mean, A.test_id, A.l2fold, A.p_value, A.p_value_adj,
A.significant FROM edger_kallisto__%(track)s_genes_results AS
A ORDER BY A.significant DESC,
A.l2fold ASC
'''
return self.getAll(statement)
class SleuthKallistoResultsGenes(IsoformTracker):
pattern = "sleuth_kallisto__(.*)_genes_results"
def __call__(self, track, slice=None):
statement = '''
SELECT A.control_name, A.treatment_name, A.control_mean,
A.treatment_mean, A.test_id, A.l2fold, A.p_value, A.p_value_adj,
A.significant FROM sleuth_kallisto__%(track)s_genes_results AS
A ORDER BY A.significant DESC,
A.l2fold ASC
'''
return self.getAll(statement)
| 30.49 | 79 | 0.608396 | 2,466 | 0.80879 | 0 | 0 | 0 | 0 | 0 | 0 | 2,018 | 0.661856 |
7f4f7c16103c58deb5243e5a653fd451eaf61603 | 2,063 | py | Python | semseg/datasets/celebamaskhq.py | Genevievekim/semantic-segmentation-1 | f28b026e44cff80fe3ca4cac94cea27e4073821b | [
"BSD-3-Clause"
] | 196 | 2021-08-22T10:01:34.000Z | 2022-03-29T09:59:51.000Z | semseg/datasets/celebamaskhq.py | Genevievekim/semantic-segmentation-1 | f28b026e44cff80fe3ca4cac94cea27e4073821b | [
"BSD-3-Clause"
] | 21 | 2021-08-22T09:59:02.000Z | 2022-03-29T15:22:46.000Z | semseg/datasets/celebamaskhq.py | Genevievekim/semantic-segmentation-1 | f28b026e44cff80fe3ca4cac94cea27e4073821b | [
"BSD-3-Clause"
] | 36 | 2021-08-22T08:59:40.000Z | 2022-03-28T10:13:20.000Z | import torch
from torch import Tensor
from torch.utils.data import Dataset
from torchvision import io
from pathlib import Path
from typing import Tuple
from torchvision import transforms as T
class CelebAMaskHQ(Dataset):
CLASSES = [
'background', 'skin', 'nose', 'eye_g', 'l_eye', 'r_eye', 'l_brow', 'r_brow', 'l_ear',
'r_ear', 'mouth', 'u_lip', 'l_lip', 'hair', 'hat', 'ear_r', 'neck_l', 'neck', 'cloth'
]
PALETTE = torch.tensor([
[0, 0, 0], [204, 0, 0], [76, 153, 0], [204, 204, 0], [51, 51, 255], [204, 0, 204], [0, 255, 255], [255, 204, 204], [102, 51, 0], [255, 0, 0],
[102, 204, 0], [255, 255, 0], [0, 0, 153], [0, 0, 204], [255, 51, 153], [0, 204, 204], [0, 51, 0], [255, 153, 51], [0, 204, 0]
])
def __init__(self, root: str, split: str = 'train', transform = None) -> None:
super().__init__()
assert split in ['train', 'val', 'test']
self.root = Path(root)
self.transform = transform
self.n_classes = len(self.CLASSES)
self.ignore_label = 255
self.resize = T.Resize((512, 512))
with open(self.root / f'{split}_list.txt') as f:
self.files = f.read().splitlines()
if not self.files:
raise Exception(f"No images found in {root}")
print(f"Found {len(self.files)} {split} images.")
def __len__(self) -> int:
return len(self.files)
def __getitem__(self, index: int) -> Tuple[Tensor, Tensor]:
img_path = self.root / 'CelebA-HQ-img' / f"{self.files[index]}.jpg"
lbl_path = self.root / 'CelebAMask-HQ-label' / f"{self.files[index]}.png"
image = io.read_image(str(img_path))
image = self.resize(image)
label = io.read_image(str(lbl_path))
if self.transform:
image, label = self.transform(image, label)
return image, label.squeeze().long()
if __name__ == '__main__':
from semseg.utils.visualize import visualize_dataset_sample
visualize_dataset_sample(CelebAMaskHQ, '/home/sithu/datasets/CelebAMask-HQ') | 38.924528 | 150 | 0.593311 | 1,694 | 0.821134 | 0 | 0 | 0 | 0 | 0 | 0 | 383 | 0.185652 |
7f54beba2b06ca2509ee89c2efe002bfd7c05562 | 282,158 | py | Python | gui/py37/images_rc.py | briansune/UART2ETHERNET_MODULE | 6ace3f5a7a75365d4d8c3d0e17b9368832237464 | [
"MIT"
] | 1 | 2022-03-30T20:37:33.000Z | 2022-03-30T20:37:33.000Z | gui/py37/images_rc.py | briansune/UART2ETHERNET_MODULE | 6ace3f5a7a75365d4d8c3d0e17b9368832237464 | [
"MIT"
] | null | null | null | gui/py37/images_rc.py | briansune/UART2ETHERNET_MODULE | 6ace3f5a7a75365d4d8c3d0e17b9368832237464 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.9.6)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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\x49\x45\x4e\x44\xae\x42\x60\x82\
"
qt_resource_name = b"\
\x00\x0d\
\x0f\x75\xfc\x07\
\x00\x71\
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\x08\xb7\x57\xa7\
\x00\x72\
\x00\x65\x00\x64\x00\x2e\x00\x70\x00\x6e\x00\x67\
"
qt_resource_struct_v1 = b"\
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x04\x00\x00\x00\x01\
\x00\x00\x00\x5a\x00\x00\x00\x00\x00\x01\x00\x00\xaa\xa8\
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\x00\x00\x00\x00\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\
"
qt_resource_struct_v2 = b"\
\x00\x00\x00\x00\x00\x02\x00\x00\x00\x04\x00\x00\x00\x01\
\x00\x00\x00\x00\x00\x00\x00\x00\
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\x00\x00\x01\x7c\x42\x6d\x6a\x95\
"
qt_version = 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()
| 65.284128 | 105 | 0.727202 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 281,554 | 0.997859 |
7f5625881c7046dfae33e15d82f6f91717dbc467 | 430 | py | Python | PYTHON/pythonDesafios/desafio062.py | Santos1000/Curso-Python | 549223a1633f6f619c87554dd8078cf7841bb1df | [
"MIT"
] | null | null | null | PYTHON/pythonDesafios/desafio062.py | Santos1000/Curso-Python | 549223a1633f6f619c87554dd8078cf7841bb1df | [
"MIT"
] | null | null | null | PYTHON/pythonDesafios/desafio062.py | Santos1000/Curso-Python | 549223a1633f6f619c87554dd8078cf7841bb1df | [
"MIT"
] | null | null | null | print('Gerador de PA\n','==-'*10)
primeiro = int(input('Primeiro termo:'))
razao = int(input('Razao da PA:'))
termo = primeiro
c = 1
total = 0
mais = 10
while mais != 0:
total = total + mais
while c <= total:
print(f'{termo} ->', end='')
c += 1
termo += razao
print('PAUSA')
mais = int(input('Quantos termos voce quer mostrar a mais:'))
print(f'FIM , a progressão mostrou {total} termos.')
| 25.294118 | 65 | 0.583721 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 163 | 0.37819 |
7f57b8e3e5f7d093c4f07748cc4cc4d938880d93 | 4,409 | py | Python | codes/Lib/site-packages/RsInstrument/Internal/ConverterToScpiString.py | charlescayno/automation | a4a34d87f372d49fd69740ad3ca46ae19bf2612d | [
"MIT"
] | null | null | null | codes/Lib/site-packages/RsInstrument/Internal/ConverterToScpiString.py | charlescayno/automation | a4a34d87f372d49fd69740ad3ca46ae19bf2612d | [
"MIT"
] | null | null | null | codes/Lib/site-packages/RsInstrument/Internal/ConverterToScpiString.py | charlescayno/automation | a4a34d87f372d49fd69740ad3ca46ae19bf2612d | [
"MIT"
] | null | null | null | from enum import Enum
from .Conversions import list_to_csv_quoted_str, value_to_quoted_str, list_to_csv_str, value_to_str, enum_list_to_str, enum_scalar_to_str
from .Types import DataType
def value_to_scpi_string(data, data_type: DataType):
"""Method to be used in the driver implementation.
Convert data to SCPI string parameter: data -> str"""
if data_type.is_list:
assert isinstance(data, list), f"Expected command parameter list, actual data type: {type(data)}. Value: {data}"
else:
assert not isinstance(data, list), f"Expected command parameter scalar, actual data type: {type(data)}. Value: {data}"
# Strings are enclosed by single quotes
if data_type == DataType.StringList:
assert all(isinstance(x, str) for x in data), f"Expected command parameter list of strings, detected one or more elements of non-string type. Value: {data}"
return list_to_csv_quoted_str(data)
elif data_type == DataType.String:
assert isinstance(data, str), f"Expected command parameter string, actual data type: {type(data)}. Value: {data}"
return value_to_quoted_str(data)
# Raw string is not enclosed by quotes
elif data_type == DataType.RawStringList:
assert all(isinstance(x, str) for x in data), f"Expected command parameter list of strings, detected one or more elements of non-string type. Value: {data}"
return list_to_csv_str(data)
elif data_type == DataType.RawString:
assert isinstance(data, str), f"Expected command parameter string, actual data type: {type(data)}. Value: {data}"
return value_to_str(data)
elif data_type == DataType.BooleanList:
assert all(type(x) == bool for x in data), f"Expected command parameter list of booleans, detected one or more elements of non-boolean type. Value: {data}"
return list_to_csv_str(data)
elif data_type == DataType.Boolean:
assert type(data) == bool, f"Expected command parameter boolean, actual data type: {type(data)}. Value: {data}"
return value_to_str(data)
# For integer and float, allow them to be mixed
elif data_type == DataType.IntegerList or data_type == DataType.FloatList:
assert all((isinstance(x, int) or isinstance(x, float)) and type(x) != bool for x in data), f"Expected command parameter list of numbers, detected one or more elements of non-number type. Value: {data}"
return list_to_csv_str(data)
elif data_type == DataType.Integer or data_type == DataType.Float:
assert (isinstance(data, int) or isinstance(data, float)) and type(data) != bool, f"Expected command parameter number, actual data type: {type(data)}. Value: {data}"
return value_to_str(data)
# For integer and float extended, allow them to be mixed including the boolean type
elif data_type == DataType.IntegerExtList or data_type == DataType.FloatExtList:
assert all((isinstance(x, int) or isinstance(x, float) or isinstance(x, bool)) for x in data), f"Expected command parameter list of numbers or booleans, detected one or more elements of non-number type. Value: {data}"
return list_to_csv_str(data)
elif data_type == DataType.IntegerExt or data_type == DataType.FloatExt:
assert (isinstance(data, int) or isinstance(data, float) or isinstance(data, bool)), f"Expected command parameter number or boolean, actual data type: {type(data)}. Value: {data}"
return value_to_str(data)
else:
raise Exception(f"Unsupported data type: '{type(data_type)}'.")
class ConverterToScpiString:
"""Converter from argument value to SCPI string.
Provides method get_value(arg_value) -> str
"""
def __init__(self, data_type: DataType, enum_type: Enum = None):
self.enum_type = enum_type
self.data_type = data_type
self.element_type = self.data_type.element_type
if self.element_type == DataType.Enum:
assert self.enum_type, f"For data_type {data_type.name}, you have to define the enum_type variable."
def get_value(self, data) -> str:
"""Returns SCPI string converted from the argument data."""
if self.data_type.is_list:
assert isinstance(data, list), f"Expected command parameter list, actual data type: {type(data)}. Value: {data}"
else:
assert not isinstance(data, list), f"Expected command parameter scalar, actual data type: {type(data)}. Value: {data}"
if self.data_type == DataType.Enum:
return enum_scalar_to_str(data, self.enum_type)
elif self.data_type == DataType.EnumList:
return enum_list_to_str(data, self.enum_type)
return value_to_scpi_string(data, self.data_type)
| 54.432099 | 219 | 0.756181 | 1,057 | 0.239737 | 0 | 0 | 0 | 0 | 0 | 0 | 1,911 | 0.433432 |
7f57d7df7fd0834188bfe8a6c66e64ecd0ee8e3e | 565 | py | Python | examples/example_interactive_prefix/main.py | David-Lor/Python-DotEnv-Settings-Handler | ca234914a93f94f59a8a37e65ff9010ffc9c4e99 | [
"Apache-2.0"
] | 6 | 2019-06-30T14:49:28.000Z | 2020-03-10T19:56:30.000Z | examples/example_interactive_prefix/main.py | David-Lor/Python-DotEnv-Settings-Handler | ca234914a93f94f59a8a37e65ff9010ffc9c4e99 | [
"Apache-2.0"
] | null | null | null | examples/example_interactive_prefix/main.py | David-Lor/Python-DotEnv-Settings-Handler | ca234914a93f94f59a8a37e65ff9010ffc9c4e99 | [
"Apache-2.0"
] | null | null | null | """This example read the settings and print them out, so you can check how they get loaded.
"""
# noinspection PyUnresolvedReferences,PyPackageRequirements
from settings import my_settings as settings
print("Redis Host:", settings.redis_host)
print("Redis Port:", settings.redis_port)
print("Redis Port / 2:", settings.redis_port / 2) # Show that the Port is int
print("API Port:", settings.api_port)
print("API Port * 2:", settings.api_port * 2) # Show that the Port is int
print("API Password:", settings.api_password)
print("API Token:", settings.api_token)
| 40.357143 | 91 | 0.753982 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 304 | 0.538053 |
7f58ffa14e511fa65d58d25693bfa7dcc12acb63 | 1,109 | py | Python | Datasets/Generator/Disaster/main.py | undraaa/m2bench | b661b61ca04470ed1c9c50531ce760a2cd5000d9 | [
"RSA-MD"
] | null | null | null | Datasets/Generator/Disaster/main.py | undraaa/m2bench | b661b61ca04470ed1c9c50531ce760a2cd5000d9 | [
"RSA-MD"
] | null | null | null | Datasets/Generator/Disaster/main.py | undraaa/m2bench | b661b61ca04470ed1c9c50531ce760a2cd5000d9 | [
"RSA-MD"
] | null | null | null | import sys
import table_gen
import doc_gen
import graph_gen
import array_gen
import os
def main(argv):
outdir = './sf1_dataset_output/'
if os.path.exists(outdir):
os.system("rm -rf "+outdir)
os.mkdir(outdir)
earthquake_dirpath = argv[1]
shelter_dirpath = argv[2]
gps_dirpath = argv[3]
roadnetwork_dirpath = argv[4]
site_dirpath = argv[5]
finedust_dirpath = argv[6]
print("------ Disaster Data Generation ------")
print("Start Earthquake Generation")
table_gen.earthquake_gen(earthquake_dirpath, outdir)
print("Start Gps Generation")
table_gen.gps_gen(gps_dirpath, outdir)
print("Start Road Network Generation")
graph_gen.roadnetwork_gen(roadnetwork_dirpath, outdir)
print("Start Site Generation")
doc_gen.site_gen(site_dirpath, outdir)
print("Start Shelter Generation")
table_gen.shelter_gen(shelter_dirpath, outdir)
print("Start Finedust Generation")
array_gen.finedust_gen(finedust_dirpath, outdir)
array_gen.finedust_idx_gen(finedust_dirpath, outdir)
if __name__ == '__main__':
main(sys.argv) | 25.790698 | 58 | 0.71596 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 240 | 0.216411 |
7f5e9b1cd835e4eff21472b20f8a3b722d2a03e6 | 4,450 | py | Python | MultiPManager/distProc.py | sebastiantrianac/SoftTLON | 3b798393efbd49b4a22acf19a056d64bef1d0ddf | [
"MIT"
] | null | null | null | MultiPManager/distProc.py | sebastiantrianac/SoftTLON | 3b798393efbd49b4a22acf19a056d64bef1d0ddf | [
"MIT"
] | null | null | null | MultiPManager/distProc.py | sebastiantrianac/SoftTLON | 3b798393efbd49b4a22acf19a056d64bef1d0ddf | [
"MIT"
] | null | null | null | #!/usr/bin/env python
# coding=utf-8
#
# A module for create a multi-agent system over Ad-hoc networks
# Copyright (C) 2017-2018
# Juan Sebastian Triana Correa <justrianaco@unal.edu.co>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU Lesser Public License for more details.
#
# You should have received a copy of the GNU Lesser Public License
# along with this program. If not, see [http://www.gnu.org/licenses/].
__author__ = "Juan Sebastian Triana Correa"
__copyright__ = "Copyright 2015, TLON group"
__license__ = "LGPL"
__version__ = "1.2"
__email__ = "justrianaco@unal.edu.co"
__status__ = "Development"
import multiprocessing
from multiprocessing.managers import SyncManager
import sys
import stomp
import dill as pickle
import time
import MultiPManager.managerImp as managerImp
import MultiPManager.brokermq as brokermq
import MultiPManager.multiProc as multiProc
import socket
if sys.version_info[0]<3:
import Queue
else:
import queue
IP = '10.203.177.194'
MANAGER_PORTNUM = 9999
BROKER_PORTNUM = 61613
AUTHKEY = ''
global numresults
numresults=0
tlon_resources = {}
def updateResourceOnSuscribers(resource, conn):
msg = pickle.dumps(resource,0)
conn.send(destination='/topic/TLONResources', body=msg)
def updateOrderOnSuscribers(name, ip, portnum, authkey,conn):
tmp = {"resourceName": name, "ip": ip, "portnum": portnum, "authkey": authkey}
msg = pickle.dumps(tmp,0)
conn.send(destination='/topic/TLONOrders', body=msg)
def tlon_sharedJobs(f, set, chunkSize):
manager = managerImp.make_server_manager(MANAGER_PORTNUM, AUTHKEY)
shared_job_q = manager.get_job_q()
shared_result_q = manager.get_result_q()
for i in range(0, len(set), chunkSize):
print('Putting chunk {}:{} in queue'.format(i, i + chunkSize))
shared_job_q.put(set[i:i + chunkSize])
return manager, shared_job_q, shared_result_q
def tlon_parallelize(ipbroker, f, set):
try:
resultdict = {}
N = 102
chunkSize = 10
conn = brokermq.BrokerConnect(ipbroker, BROKER_PORTNUM)
updateResourceOnSuscribers(f, conn)
manager, shared_job_q, shared_result_q = tlon_sharedJobs(f, set, chunkSize)
time.sleep(2)
hostname = socket.gethostname()
ipsocket = socket.gethostbyname(hostname)
updateOrderOnSuscribers(f.__name__, ipsocket, MANAGER_PORTNUM, AUTHKEY, conn)
global numresults
numresults = 0
#if 1:
# multiProc.tlon_multiprocessing(shared_job_q, shared_result_q, f)
while numresults < len(set):
outdict = shared_result_q.get()
#resultdict.update(outdict)
numresults += len(outdict)
#updateResourceOnSuscribers(f, conn)
#for num, result in outdict.iteritems():
#print("{}({}) = {}".format(f.__name__, num, result))
print ('End of Task')
except IOError as e:
print ("I/O error({0}): {1}".format(e.errno, e.strerror))
except ValueError:
print ("Could not convert data to an integer.")
finally:
time.sleep(2)
manager.shutdown()
def runclient(ipbroker, threads):
# Setting number of threads that are going to attend the request of processing of the network
multiProc.setThreads(threads)
# Connecting to TLONResource Topic to receive shared resources
connResources = brokermq.BrokerConnect(ipbroker, BROKER_PORTNUM)
connResources.set_listener('ResourceTopic', brokermq.__resourceTopicListener__())
connResources.subscribe(destination='/topic/TLONResources', id=1, ack='auto')
# Connecting to TLONOrders Topic to start executed OoW
connOrders = brokermq.BrokerConnect(ipbroker, BROKER_PORTNUM)
connOrders.set_listener('OrdersTopic', brokermq.__ordersTopicListener__())
connOrders.subscribe(destination='/topic/TLONOrders', id=2, ack='auto')
if __name__ == '__main__':
if len(sys.argv) > 1 and sys.argv[1] == 'producer':
tlon_parallelize()
else:
runclient('192.168.0.8', 2)
| 32.481752 | 97 | 0.704494 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,659 | 0.372809 |
7f60669d9c8f83bdc7550f5d0401483d476b3958 | 1,565 | py | Python | setup.py | charlesthomas/testrail_reporter | bc522ed3a66aee38c21cc45e2d3b9a786df45e02 | [
"MIT"
] | null | null | null | setup.py | charlesthomas/testrail_reporter | bc522ed3a66aee38c21cc45e2d3b9a786df45e02 | [
"MIT"
] | null | null | null | setup.py | charlesthomas/testrail_reporter | bc522ed3a66aee38c21cc45e2d3b9a786df45e02 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
from setuptools import setup
NAME = 'testrail_reporter'
DESCRIPTION = 'Nosetests Plugin to Report Test Results to TestRail.'
VERSION = open('VERSION').read().strip()
LONG_DESC = open('README.rst').read()
LICENSE = open('LICENSE').read()
setup(
name=NAME,
version=VERSION,
author='Charles Thomas',
author_email='ch@rlesthom.as',
packages=['testrail_reporter'],
url='https://github.com/charlesthomas/%s' % NAME,
license=LICENSE,
description=DESCRIPTION,
long_description=LONG_DESC,
# test_suite='tests',
entry_points = {'nose.plugins.0.10':
['testrail_reporter = testrail_reporter.testrail_reporter:TestRailReporter']},
install_requires=['nose >= 1.3.7',
'testrail >= 0.3.6',],
classifiers=['Development Status :: 4 - Beta',
'Intended Audience :: Developers',
'Natural Language :: English',
'License :: OSI Approved :: MIT License',
'Operating System :: OS Independent',
'Topic :: Software Development :: Libraries :: Python Modules',
'Topic :: Internet :: WWW/HTTP',
'Topic :: Software Development :: Quality Assurance',
'Topic :: Software Development :: Testing',
'Programming Language :: Python',
'Programming Language :: Python :: 2',
'Programming Language :: Python :: 2.6',
'Programming Language :: Python :: 2.7',
'Programming Language :: Python :: 3',
'Programming Language :: Python :: 3.3',
'Programming Language :: Python :: 3.4',
'Programming Language :: Python :: 3.5',],
)
| 36.395349 | 98 | 0.645367 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,018 | 0.650479 |
7f60d515f24c5c7adbd364f7654c2e0099fc891b | 871 | py | Python | bleach__examples__remove_tags__clear_html/escape_protocols.py | DazEB2/SimplePyScripts | 1dde0a42ba93fe89609855d6db8af1c63b1ab7cc | [
"CC-BY-4.0"
] | 117 | 2015-12-18T07:18:27.000Z | 2022-03-28T00:25:54.000Z | bleach__examples__remove_tags__clear_html/escape_protocols.py | DazEB2/SimplePyScripts | 1dde0a42ba93fe89609855d6db8af1c63b1ab7cc | [
"CC-BY-4.0"
] | 8 | 2018-10-03T09:38:46.000Z | 2021-12-13T19:51:09.000Z | bleach__examples__remove_tags__clear_html/escape_protocols.py | DazEB2/SimplePyScripts | 1dde0a42ba93fe89609855d6db8af1c63b1ab7cc | [
"CC-BY-4.0"
] | 28 | 2016-08-02T17:43:47.000Z | 2022-03-21T08:31:12.000Z | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
__author__ = 'ipetrash'
# SOURCE: https://github.com/mozilla/bleach
# SOURCE: https://bleach.readthedocs.io/en/latest/clean.html#allowed-protocols-protocols
# pip install bleach
import bleach
# List of allowed protocols
print('List of allowed protocols:', bleach.sanitizer.ALLOWED_PROTOCOLS)
# ['http', 'https', 'mailto']
print(
bleach.clean(
'<a href="smb://more_text">allowed protocol</a>'
)
)
# <a>allowed protocol</a>
print(
bleach.clean(
'<a href="smb://more_text">allowed protocol</a>',
protocols=['http', 'https', 'smb']
)
)
# <a href="smb://more_text">allowed protocol</a>
print(
bleach.clean(
'<a href="smb://more_text">allowed protocol</a>',
protocols=bleach.ALLOWED_PROTOCOLS + ['smb']
)
)
# <a href="smb://more_text">allowed protocol</a>
| 21.243902 | 88 | 0.641791 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 578 | 0.663605 |
7f6302ecae4a93f7afb3564d0a9c878a96bd226e | 4,920 | py | Python | test/test_entity_builder.py | ari-bou/symro | b49a5578b4e1d95ab5ab92b06bfea2bc6ead2246 | [
"MIT"
] | null | null | null | test/test_entity_builder.py | ari-bou/symro | b49a5578b4e1d95ab5ab92b06bfea2bc6ead2246 | [
"MIT"
] | null | null | null | test/test_entity_builder.py | ari-bou/symro | b49a5578b4e1d95ab5ab92b06bfea2bc6ead2246 | [
"MIT"
] | null | null | null | import symro
import symro.src.handlers.metaentitybuilder as eb
from symro.src.parsing.amplparser import AMPLParser
from symro.test.test_util import *
# Scripts
# ----------------------------------------------------------------------------------------------------------------------
FIXED_DIM_SCRIPT = """
set I = {1, 2, 3};
set J = {'A', 'B', 'C'};
set K = {(1, 'A'), (2, 'B'), (3, 'C')};
set L = {(1, 'A'), (2, 'B'), (3, 'C')};
var x {(i,'A') in K, (i,l) in L};
"""
SUB_SET_SCRIPT = """
set NUM_SET = {0, 1, 2, 3, 4, 5, 6, 7, 8, 9};
set EVEN_SET = {0, 2, 4, 6, 8};
set LETTER_SET = {'A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', "I", 'J'};
set VOWEL_SET = {'A', 'E', "I"};
set NUM_LETTER_SET = {NUM_SET, LETTER_SET};
set INDEXED_SET{i in NUM_SET} = 0..i;
set INDEXED_SET_2{i in NUM_SET} = {(i,j) in NUM_LETTER_SET};
var VAR_1{i in NUM_SET} >= 0;
var VAR_2{i in NUM_SET, j in LETTER_SET} >= 0;
var VAR_test{i in NUM_SET: 1 in union{i1 in NUM_SET}{1..1: i == 5}};
minimize OBJ: 0;
display {i in NUM_SET: 1 in union{i1 in NUM_SET}{1..1: i == 5}};
"""
# Tests
# ----------------------------------------------------------------------------------------------------------------------
def run_entity_builder_test_group():
tests = [("Build meta-entity with fixed dimensions", fixed_dimension_test),
("Build sub-meta-entities", sub_meta_entity_builder_test)]
return run_tests(tests)
def fixed_dimension_test():
problem = symro.read_ampl(script_literal=FIXED_DIM_SCRIPT,
working_dir_path=SCRIPT_DIR_PATH)
results = []
x = problem.get_meta_entity("x")
results.append(check_str_result(x.idx_set_reduced_dim, 2))
results.append(check_str_result(x.idx_set_reduced_dummy_element, ['i', 'l']))
return results
def sub_meta_entity_builder_test():
problem = symro.read_ampl(script_literal=SUB_SET_SCRIPT,
working_dir_path=SCRIPT_DIR_PATH)
ampl_parser = AMPLParser(problem)
results = []
mv_1 = problem.get_meta_entity("VAR_1")
mv_2 = problem.get_meta_entity("VAR_2")
# test 1: {i in NUM_SET} VAR_1[i]
idx_node = ampl_parser.parse_entity_index("[i]")
sub_meta_entity = eb.build_sub_meta_entity(
problem=problem,
idx_subset_node=mv_1.idx_set_node,
meta_entity=mv_1,
entity_idx_node=idx_node)
results.append(check_str_result(sub_meta_entity, "var VAR_1{i in NUM_SET}"))
# test 2: {i in EVEN_SET} VAR_1[i]
idx_subset_node = ampl_parser.parse_indexing_set_definition("{i in EVEN_SET}")
idx_node = ampl_parser.parse_entity_index("[i]")
sub_meta_entity = eb.build_sub_meta_entity(
problem=problem,
idx_subset_node=idx_subset_node,
meta_entity=mv_1,
entity_idx_node=idx_node)
results.append(check_str_result(sub_meta_entity, "var VAR_1{i in NUM_SET: i in {i2 in EVEN_SET}}"))
# test 3: {i in NUM_SET} VAR_1[5]
idx_node = ampl_parser.parse_entity_index("[5]")
sub_meta_entity = eb.build_sub_meta_entity(
problem=problem,
idx_subset_node=mv_1.idx_set_node,
meta_entity=mv_1,
entity_idx_node=idx_node)
results.append(check_str_result(sub_meta_entity, "var VAR_1{i in NUM_SET: i == 5}"))
# test 4: {i in EVEN_SET, j in VOWEL_SET} VAR_2[i,j]
idx_subset_node = ampl_parser.parse_indexing_set_definition("{i in EVEN_SET, j in VOWEL_SET}")
idx_node = ampl_parser.parse_entity_index("[i,j]")
sub_meta_entity = eb.build_sub_meta_entity(
problem=problem,
idx_subset_node=idx_subset_node,
meta_entity=mv_2,
entity_idx_node=idx_node)
s = "var VAR_2{i in NUM_SET, j in LETTER_SET: (i,j) in {i3 in EVEN_SET, j1 in VOWEL_SET}}"
results.append(check_str_result(sub_meta_entity, s))
# test 5: {i in NUM_SET, j in INDEXED_SET[i]} VAR_1[j]
idx_subset_node = ampl_parser.parse_indexing_set_definition("{i in NUM_SET, j in INDEXED_SET[i]}")
idx_node = ampl_parser.parse_entity_index("[j]")
sub_meta_entity = eb.build_sub_meta_entity(
problem=problem,
idx_subset_node=idx_subset_node,
meta_entity=mv_1,
entity_idx_node=idx_node)
s = "var VAR_1{i in NUM_SET: i in union{i4 in NUM_SET}{j2 in INDEXED_SET[i]}}"
results.append(check_str_result(sub_meta_entity, s))
# test 6: {i in NUM_SET, j in INDEXED_SET_2[i]} VAR_2[i,j]
idx_subset_node = ampl_parser.parse_indexing_set_definition("{i in NUM_SET, j in INDEXED_SET_2[i]}")
idx_node = ampl_parser.parse_entity_index("[j,k]")
sub_meta_entity = eb.build_sub_meta_entity(
problem=problem,
idx_subset_node=idx_subset_node,
meta_entity=mv_2,
entity_idx_node=idx_node)
s = "var VAR_2{i in NUM_SET, j in LETTER_SET}"
results.append(check_str_result(sub_meta_entity, s))
# problem.engine.api.reset()
# problem.engine.api.eval(SUB_SET_SCRIPT)
return results
| 36.176471 | 120 | 0.641057 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,870 | 0.380081 |
7f64ce20d2bc7463fbe8a47e2e961d23f53650a4 | 14,042 | py | Python | source/StimulationScreen.py | FelixTheoret/Ergocycle | 0656e6cb43b535dd2f845420ad71742b1b85e412 | [
"MIT"
] | null | null | null | source/StimulationScreen.py | FelixTheoret/Ergocycle | 0656e6cb43b535dd2f845420ad71742b1b85e412 | [
"MIT"
] | null | null | null | source/StimulationScreen.py | FelixTheoret/Ergocycle | 0656e6cb43b535dd2f845420ad71742b1b85e412 | [
"MIT"
] | 2 | 2022-03-17T23:17:56.000Z | 2022-03-23T01:08:58.000Z | """
Created on Wed March 30 11::00 2022
@author: Frédérique Leclerc
"""
from tracemalloc import start
from numpy import number
from Screen import Screen as Screen
from PyQt5 import QtWidgets
from PyQt5.QtWidgets import *
from PyQt5.QtGui import QFont, QPixmap
from PIL import Image
#from Ergocycle.source.StartWindow import StartWindow
from StartWindow import StartWindow
from TestingWindow import TestingWindow
from InstructionWindow import InstructionWindow
from Parameters import Parameters
from StimulationWindow import StimulationWindow
from MainWindowStim import MainWindowStim
from DangerPopUp import DangerPopUp
import sys
import datetime
import time
import csv
from CommandButton import CommandButton as CommandButton
# Take the code from main_sef.py and add getters and setters
#def window():
#app = QApplication(sys.argv)
#win = StartWindow()
#win.show()
#sys.exit(app.exec_())
#window()
class StimulationScreen(Screen):
def __init__(self, event_function):
super(StimulationScreen, self).__init__(event_function)
self.event_function = event_function
self.current_menu = 0
self.danger_menu = 0
#self.now = datetime.datetime.now()
### 1.1. Permet de gérer les fenêtre apparaissant sur l'interface. ###
def manage_active_window(self, stim_parameters):
if self.window_counter == 0:
self.current_menu = StartWindow()
self.current_menu.training_button.clicked.connect(lambda : self.event_function("start_training"))
self.current_menu.test_button.clicked.connect(lambda : self.event_function("start_test"))
self.current_menu.show()
# self.connect_buttons(self.current_menu)
elif self.window_counter == -1:
self.current_menu.close()
self.current_menu = TestingWindow()
self.current_menu.increase_amp_button.clicked.connect(lambda : self.event_function("increase_amp"))
self.current_menu.increase_freq_button.clicked.connect(lambda : self.event_function("increase_frequency"))
self.current_menu.increase_imp_button.clicked.connect(lambda : self.event_function("increase_imp"))
self.current_menu.decrease_amp_button.clicked.connect(lambda : self.event_function("decrease_amp"))
self.current_menu.decrease_freq_button.clicked.connect(lambda : self.event_function("decrease_frequency"))
self.current_menu.decrease_imp_button.clicked.connect(lambda : self.event_function("decrease_imp"))
self.current_menu.back_button.clicked.connect(lambda : self.event_function("back_button_clicked"))
self.current_menu.show()
elif self.window_counter == 1:
self.current_menu.close()
self.current_menu = MainWindowStim()
self.current_menu.submit_button.clicked.connect(lambda : self.event_function("submit_button_clicked"))
self.current_menu.submit_final_button.clicked.connect(lambda : self.event_function("submit_final_button_clicked"))
self.current_menu.show()
elif self.window_counter == -2:
self.danger_menu = DangerPopUp(stim_parameters)
self.danger_menu.show()
self.danger_menu.back_to_menu_button.clicked.connect(lambda : self.back_to_menu_button_clicked())
self.danger_menu.continue_button.clicked.connect(lambda : self.continue_button_clicked(stim_parameters))
elif self.window_counter == 2:
self.current_menu.close()
self.current_menu = InstructionWindow(stim_parameters)
self.current_menu.start_button.clicked.connect(lambda : self.event_function("start_stimulations"))
self.current_menu.show()
elif self.window_counter == 3:
self.current_menu.close()
self.current_menu = StimulationWindow(stim_parameters)
self.current_menu.increase_amplitude1_button.clicked.connect(lambda : self.event_function("increase_amplitude1"))
self.current_menu.increase_amplitude2_button.clicked.connect(lambda : self.event_function("increase_amplitude2"))
self.current_menu.increase_amplitude3_button.clicked.connect(lambda : self.event_function("increase_amplitude3"))
self.current_menu.increase_amplitude4_button.clicked.connect(lambda : self.event_function("increase_amplitude4"))
self.current_menu.increase_amplitude5_button.clicked.connect(lambda : self.event_function("increase_amplitude5"))
self.current_menu.increase_amplitude6_button.clicked.connect(lambda : self.event_function("increase_amplitude6"))
self.current_menu.increase_amplitude7_button.clicked.connect(lambda : self.event_function("increase_amplitude7"))
self.current_menu.increase_amplitude8_button.clicked.connect(lambda : self.event_function("increase_amplitude8"))
self.current_menu.decrease_amplitude1_button.clicked.connect(lambda : self.event_function("decrease_amplitude1"))
self.current_menu.decrease_amplitude2_button.clicked.connect(lambda : self.event_function("decrease_amplitude2"))
self.current_menu.decrease_amplitude3_button.clicked.connect(lambda : self.event_function("decrease_amplitude3"))
self.current_menu.decrease_amplitude4_button.clicked.connect(lambda : self.event_function("decrease_amplitude4"))
self.current_menu.decrease_amplitude5_button.clicked.connect(lambda : self.event_function("decrease_amplitude5"))
self.current_menu.decrease_amplitude6_button.clicked.connect(lambda : self.event_function("decrease_amplitude6"))
self.current_menu.decrease_amplitude7_button.clicked.connect(lambda : self.event_function("decrease_amplitude7"))
self.current_menu.decrease_amplitude8_button.clicked.connect(lambda : self.event_function("decrease_amplitude8"))
self.current_menu.increase_frequency1_button.clicked.connect(lambda : self.event_function("increase_frequency1"))
self.current_menu.increase_frequency2_button.clicked.connect(lambda : self.event_function("increase_frequency2"))
self.current_menu.increase_frequency3_button.clicked.connect(lambda : self.event_function("increase_frequency3"))
self.current_menu.increase_frequency4_button.clicked.connect(lambda : self.event_function("increase_frequency4"))
self.current_menu.increase_frequency5_button.clicked.connect(lambda : self.event_function("increase_frequency5"))
self.current_menu.increase_frequency6_button.clicked.connect(lambda : self.event_function("increase_frequency6"))
self.current_menu.increase_frequency7_button.clicked.connect(lambda : self.event_function("increase_frequency7"))
self.current_menu.increase_frequency8_button.clicked.connect(lambda : self.event_function("increase_frequency8"))
self.current_menu.decrease_frequency1_button.clicked.connect(lambda : self.event_function("decrease_frequency1"))
self.current_menu.decrease_frequency2_button.clicked.connect(lambda : self.event_function("decrease_frequency2"))
self.current_menu.decrease_frequency3_button.clicked.connect(lambda : self.event_function("decrease_frequency3"))
self.current_menu.decrease_frequency4_button.clicked.connect(lambda : self.event_function("decrease_frequency4"))
self.current_menu.decrease_frequency5_button.clicked.connect(lambda : self.event_function("decrease_frequency5"))
self.current_menu.decrease_frequency6_button.clicked.connect(lambda : self.event_function("decrease_frequency6"))
self.current_menu.decrease_frequency7_button.clicked.connect(lambda : self.event_function("decrease_frequency7"))
self.current_menu.decrease_frequency8_button.clicked.connect(lambda : self.event_function("decrease_frequency8"))
self.current_menu.increase_imp1_button.clicked.connect(lambda : self.event_function("increase_imp1"))
self.current_menu.increase_imp2_button.clicked.connect(lambda : self.event_function("increase_imp2"))
self.current_menu.increase_imp3_button.clicked.connect(lambda : self.event_function("increase_imp3"))
self.current_menu.increase_imp4_button.clicked.connect(lambda : self.event_function("increase_imp4"))
self.current_menu.increase_imp5_button.clicked.connect(lambda : self.event_function("increase_imp5"))
self.current_menu.increase_imp6_button.clicked.connect(lambda : self.event_function("increase_imp6"))
self.current_menu.increase_imp7_button.clicked.connect(lambda : self.event_function("increase_imp7"))
self.current_menu.increase_imp8_button.clicked.connect(lambda : self.event_function("increase_imp8"))
self.current_menu.decrease_imp1_button.clicked.connect(lambda : self.event_function("decrease_imp1"))
self.current_menu.decrease_imp2_button.clicked.connect(lambda : self.event_function("decrease_imp2"))
self.current_menu.decrease_imp3_button.clicked.connect(lambda : self.event_function("decrease_imp3"))
self.current_menu.decrease_imp4_button.clicked.connect(lambda : self.event_function("decrease_imp4"))
self.current_menu.decrease_imp5_button.clicked.connect(lambda : self.event_function("decrease_imp5"))
self.current_menu.decrease_imp6_button.clicked.connect(lambda : self.event_function("decrease_imp6"))
self.current_menu.decrease_imp7_button.clicked.connect(lambda : self.event_function("decrease_imp7"))
self.current_menu.decrease_imp8_button.clicked.connect(lambda : self.event_function("decrease_imp8"))
self.current_menu.pauseWatch.pressed.connect(lambda : self.event_function("pause_stimulation"))
self.current_menu.stop_button.clicked.connect(lambda : self.event_function("stop_stimulation"))
self.current_menu.show()
else:
self.current_menu.close()
def back_to_menu_button_clicked(self):
self.danger_menu.close()
# self.manage_active_window(stim_parameters)
self.event_function("back_to_menu")
def continue_button_clicked(self, stim_parameters):
self.window_counter = 2
self.manage_active_window(stim_parameters)
self.danger_menu.close()
self.event_function("continue_to_instructions")
### 1.2. Création d'un fichier CSV lors de l'entraînement afin d'enregistrer les données de stimulations ###
def create_csv_file(self, matrice):
self.now = datetime.datetime.now()
file = (self.now.strftime("%m-%d-%Y, %H;%M;%S"))
path = "\\home\\pi\\Downloads\\stimulation_data_" # à commenter si vous travaillez sur votre ordinateur
name_of_file = path+file+".csv" # à commenter si vous travaillez sur votre ordi
#name_of_file = (self.now.strftime("%m-%d-%Y, %H;%M;%S"))+" stimulations_data.csv" # à décommenter si vous travaillez sur votre ordinateur
with open(name_of_file, 'w',newline='') as f:
fieldnames = ['Date and time', 'Electrode', 'Amplitude(mA)','Frequence(Hz)', 'Durée dimpulsion(us)', 'muscle']
thewriter = csv.DictWriter(f,fieldnames)
thewriter.writeheader()
now = datetime.datetime.now()
date_time = now.strftime("%m-%d-%Y,%H:%M:%S")
for i in range(8):
muscle_name = self.get_muscle_traduction(matrice[3,i])
thewriter.writerow({'Date and time' : date_time, 'Electrode': str(i+1), 'Amplitude(mA)': str(matrice[0,i]) ,'Frequence(Hz)': str(matrice[1,i]), 'Durée dimpulsion(us)': str(matrice[2,i]), 'muscle': muscle_name})
f.close
### 1.3. Ajouter les modification des paramètres d'entraînement au même fichier CSV ###
def save_data_in_csv_file(self, matrice):
file = self.now.strftime("%m-%d-%Y, %H;%M;%S")
path = "\\home\\pi\\Downloads\\stimulation_data_" # à commenter si vous travaillez sur votre ordi
name_of_file = path+file+".csv" # à commenter si vous travaillez sur votre ordi
#name_of_file = (self.now.strftime("%m-%d-%Y, %H;%M;%S"))+" stimulations_data.csv" # à décommenter si vous travaillez sur votre ordi
with open(name_of_file, 'a+',newline='') as f:
fieldnames = ['Date and time', 'Electrode', 'Amplitude(mA)','Frequence(Hz)', 'Durée dimpulsion(us)', 'muscle']
thewriter = csv.DictWriter(f,fieldnames)
new_now = datetime.datetime.now()
date_time = new_now.strftime("%m-%d-%Y,%H:%M:%S")
if matrice == []:
for i in range(8):
thewriter.writerow({'Date and time' : date_time, 'Electrode': str(i+1), 'Amplitude(mA)': str(0) ,'Frequence(Hz)': str(0), 'Durée dimpulsion(us)': str(0), 'muscle': str(0)})
else:
for i in range(8):
muscle_name = self.get_muscle_traduction(matrice[3,i])
thewriter.writerow({'Date and time' : date_time, 'Electrode': str(i+1), 'Amplitude(mA)': str(matrice[0,i]) ,'Frequence(Hz)': str(matrice[1,i]), 'Durée dimpulsion(us)': str(matrice[2,i]), 'muscle': muscle_name})
f.close
### 1.4. Traduit les muscles de chiffre à nom pour l'enregistrements des données ###
def get_muscle_traduction(self, muscle_number):
if muscle_number == 0:
muscle = "Aucun"
if muscle_number == 1:
muscle = "Biceps Brachii"
if muscle_number== 2:
muscle = "Triceps Brachii"
if muscle_number == 3:
muscle = "Deltoide Postérieur"
if muscle_number == 4:
muscle = "Deltoide Antérieur"
return(muscle)
| 65.924883 | 230 | 0.703319 | 13,148 | 0.934537 | 0 | 0 | 0 | 0 | 0 | 0 | 3,152 | 0.224039 |
7f6557fd2c7f3025f39724cdaeb984fe7369be4f | 1,412 | py | Python | src/createVocabulary.py | aws-samples/aim317-uncover-insights-customer-conversations | 663ba08fe9ad1cf1e520e77a88dc6a96b611619b | [
"MIT-0"
] | null | null | null | src/createVocabulary.py | aws-samples/aim317-uncover-insights-customer-conversations | 663ba08fe9ad1cf1e520e77a88dc6a96b611619b | [
"MIT-0"
] | null | null | null | src/createVocabulary.py | aws-samples/aim317-uncover-insights-customer-conversations | 663ba08fe9ad1cf1e520e77a88dc6a96b611619b | [
"MIT-0"
] | 1 | 2021-12-20T16:40:55.000Z | 2021-12-20T16:40:55.000Z | import boto3
import uuid
import json
import os
def lambda_handler(event, context):
record = event['Records'][0]
s3bucket = record['s3']['bucket']['name']
s3object = record['s3']['object']['key']
print(s3object.split(".")[0].split("-")[2])
if s3object.split(".")[0].split("-")[2] == "EN":
s3Path = "s3://" + s3bucket + "/" + s3object
VocabName = "custom-vocab-EN-" + str(uuid.uuid4())
client = boto3.client('transcribe')
print("S3 Path:" + s3Path)
response = client.create_vocabulary(
VocabularyName=VocabName,
LanguageCode='en-US',
VocabularyFileUri = s3Path,
)
return {
'VocabularybName': response['VocabularyName']
}
elif s3object.split(".")[0].split("-")[2] == "ES":
s3Path = "s3://" + s3bucket + "/" + s3object
VocabName = "custom-vocab-ES-" + str(uuid.uuid4())
client = boto3.client('transcribe')
print("S3 Path:" + s3Path)
response = client.create_vocabulary(
VocabularyName=VocabName,
LanguageCode='es-ES',
VocabularyFileUri = s3Path,
)
return {
'VocabularybName': response['VocabularyName']
}
else:
return {
'ErrorCode': "Language not in filename, must end in EN or ES"
} | 25.214286 | 73 | 0.526912 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 309 | 0.218839 |
7f661e451d1b0a515002a9da6f0b3193c7f5f896 | 773 | py | Python | app/api/model/blacklist.py | ChegeBryan/politico | 746ef4c76931928ef145593092c8b391421a50fd | [
"MIT"
] | 1 | 2021-09-08T13:17:03.000Z | 2021-09-08T13:17:03.000Z | app/api/model/blacklist.py | ChegeBryan/politico | 746ef4c76931928ef145593092c8b391421a50fd | [
"MIT"
] | 62 | 2019-02-04T07:08:32.000Z | 2021-05-06T19:49:03.000Z | app/api/model/blacklist.py | ChegeBryan/politico | 746ef4c76931928ef145593092c8b391421a50fd | [
"MIT"
] | 5 | 2019-02-11T18:21:14.000Z | 2022-02-25T07:41:07.000Z | """ Blacklist_token class method and model """
import datetime
class BlacklistToken:
"""Blacklist token class
1. initializes the class with the user token and the time created
"""
def __init__(self, token):
self.token = token
self.blacklisted_on = datetime.datetime.now()
def add_blacklist_token(self):
query = """
INSERT INTO blacklist(token, blacklisted_on) VALUES (%s, %s);
"""
values = (self.token, self.blacklisted_on)
return query, values
@staticmethod
def check_blacklist(auth_token):
""" Check if the provided token is already in blacklisted """
sql = """SELECT * FROM blacklist WHERE token=%s;"""
query = sql, (auth_token,)
return query
| 26.655172 | 71 | 0.626132 | 706 | 0.913325 | 0 | 0 | 236 | 0.305304 | 0 | 0 | 344 | 0.445019 |
7f667e0c792310a6ca90389cd7acf95cb20a0aed | 3,631 | py | Python | matrix_procedures/load_dataset_class.py | jamiecook/AequilibraE | b1013d59cbeaf6fc4e1a944cf31f20460a2a4156 | [
"MIT"
] | null | null | null | matrix_procedures/load_dataset_class.py | jamiecook/AequilibraE | b1013d59cbeaf6fc4e1a944cf31f20460a2a4156 | [
"MIT"
] | null | null | null | matrix_procedures/load_dataset_class.py | jamiecook/AequilibraE | b1013d59cbeaf6fc4e1a944cf31f20460a2a4156 | [
"MIT"
] | null | null | null | """
-----------------------------------------------------------------------------------------------------------
Package: AequilibraE
Name: Loads datasets into AequilibraE binary files
Purpose: Implements dataset creation
Original Author: Pedro Camargo (c@margo.co)
Contributors:
Last edited by: Pedro Camargo
Website: www.AequilibraE.com
Repository: https://github.com/AequilibraE/AequilibraE
Created: 2016-08-15 (Initially as vector loading)
Updated: 2017-10-02
Copyright: (c) AequilibraE authors
Licence: See LICENSE.TXT
-----------------------------------------------------------------------------------------------------------
"""
from PyQt4.QtCore import *
import numpy as np
from ..common_tools.worker_thread import WorkerThread
import struct
from ..aequilibrae.matrix import AequilibraEData
from ..common_tools.global_parameters import *
class LoadDataset(WorkerThread):
def __init__(self, parent_thread, layer, index_field, fields, file_name):
WorkerThread.__init__(self, parent_thread)
self.layer = layer
self.index_field = index_field
self.fields = fields
self.error = None
self.python_version = (8 * struct.calcsize("P"))
self.output = AequilibraEData()
self.output_name = file_name
def doWork(self):
feat_count = self.layer.featureCount()
self.emit(SIGNAL("ProgressMaxValue( PyQt_PyObject )"), feat_count)
# Create specification for the output file
datafile_spec = {'entries': feat_count}
if self.output_name is None:
datafile_spec['memory_mode'] = True
else:
datafile_spec['memory_mode'] = False
fields = []
types = []
idxs = []
empties = []
for field in self.layer.dataProvider().fields().toList():
if field.name() in self.fields:
if field.type() in integer_types:
types.append('<i8')
empties.append(np.iinfo(np.int64).min)
elif field.type() in float_types:
types.append('<f8')
empties.append(np.nan)
elif field.type() in string_types:
types.append('S' + str(field.length()))
empties.append('')
else:
print field.type()
self.error = 'Field {} does has a type not supported.'.format(str(field.name()))
break
fields.append(str(field.name()))
idxs.append(self.layer.fieldNameIndex(field.name()))
index_idx = self.layer.fieldNameIndex(self.index_field)
datafile_spec['field_names'] = fields
datafile_spec['data_types'] = types
datafile_spec['file_path'] = self.output_name
if self.error is None:
self.output.create_empty(**datafile_spec)
# Get all the data
for p, feat in enumerate(self.layer.getFeatures()):
for idx, field, empty in zip(idxs, fields, empties):
if isinstance(feat.attributes()[idx], QPyNullVariant):
self.output.data[field][p] = empty
else:
self.output.data[field][p] = feat.attributes()[idx]
self.output.index[p] = feat.attributes()[index_idx]
self.emit(SIGNAL("ProgressValue( PyQt_PyObject )"), p)
self.emit(SIGNAL("ProgressValue( PyQt_PyObject )"), int(feat_count))
self.emit(SIGNAL("finished_threaded_procedure( PyQt_PyObject )"), 'Done')
| 39.043011 | 108 | 0.56238 | 2,734 | 0.752961 | 0 | 0 | 0 | 0 | 0 | 0 | 1,023 | 0.281741 |
7f6761d3d7ac11e1232a9005ec969e6f67128b3e | 781 | py | Python | FastCAE_Linux/output/examples/example3/view.py | alleindrach/calculix-desktop | 2cb2c434b536eb668ff88bdf82538d22f4f0f711 | [
"MIT"
] | 23 | 2020-03-16T03:01:43.000Z | 2022-03-21T16:36:22.000Z | FastCAE_Linux/output/examples/example3/view.py | alleindrach/calculix-desktop | 2cb2c434b536eb668ff88bdf82538d22f4f0f711 | [
"MIT"
] | 1 | 2020-03-17T05:50:07.000Z | 2020-03-17T05:50:07.000Z | FastCAE_Linux/output/examples/example3/view.py | alleindrach/calculix-desktop | 2cb2c434b536eb668ff88bdf82538d22f4f0f711 | [
"MIT"
] | 17 | 2020-03-16T01:46:36.000Z | 2022-03-21T16:36:37.000Z | MainWindow.clearData()
MainWindow.openPreWindow()
box = CAD.Box()
box.setName('Box_1')
box.setLocation(0,0,0)
box.setPara(10,10,10)
box.create()
cylinder = CAD.Cylinder()
cylinder.setName('Cylinder_2')
cylinder.setLocation(0,0,0)
cylinder.setRadius(5)
cylinder.setLength(10)
cylinder.setAxis(0,0,1)
cylinder.create()
booloperation = CAD.BooLOperation()
booloperation.setBoolType('Fause')
booloperation.setIndexOfSolid1InGeo(1,0)
booloperation.setIndexOfSolid2InGeo(2,0)
booloperation.create()
gmsher = Mesher.Gmsher()
gmsher.setDim(3)
gmsher.appendSolid(3,0)
gmsher.setElementType("Tet")
gmsher.setElementOrder(1)
gmsher.setMethod(1)
gmsher.setSizeFactor(1)
gmsher.setMinSize(0)
gmsher.setMaxSize(1.0)
gmsher.cleanGeo()
gmsher.startGenerationThread()
| 25.193548 | 41 | 0.766965 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 31 | 0.039693 |
7f696039cf0e21135e93815d60394b72a34a443f | 1,040 | py | Python | app/api/routes/server/plot_queue.py | cPoolChia/ChiaAutoplotter-Backend | 8d875c1f846df395ddc76e3d84b36da45ad4d557 | [
"MIT"
] | 7 | 2021-06-01T09:20:34.000Z | 2021-10-12T07:24:04.000Z | app/api/routes/server/plot_queue.py | cPoolChia/ChiaFarmerManager-Backend | 8d875c1f846df395ddc76e3d84b36da45ad4d557 | [
"MIT"
] | null | null | null | app/api/routes/server/plot_queue.py | cPoolChia/ChiaFarmerManager-Backend | 8d875c1f846df395ddc76e3d84b36da45ad4d557 | [
"MIT"
] | 1 | 2021-05-31T13:08:14.000Z | 2021-05-31T13:08:14.000Z | from typing import Any
from uuid import UUID, uuid4
import celery
from app import crud, models, schemas
from app.api import deps
from app.core.config import settings
from app.utils import auth
from app.core import tasks
from fastapi import APIRouter, Depends, HTTPException, Body, Query
from sqlalchemy.orm import Session
from fastapi_utils.cbv import cbv
from fastapi_utils.inferring_router import InferringRouter
from app.api.routes.base import BaseAuthCBV
router = InferringRouter()
@cbv(router)
class QueueCBV(BaseAuthCBV):
@router.get("/")
def get_queues_table(
self,
server: models.Server = Depends(deps.get_server_by_id),
filtration: schemas.FilterData[models.Plot] = Depends(
deps.get_filtration_data(models.Plot)
),
) -> schemas.Table[schemas.PlotQueueReturn]:
amount, items = crud.plot_queue.get_multi_by_server(
self.db, server=server, filtration=filtration
)
return schemas.Table[schemas.PlotQueueReturn](amount=amount, items=items) | 32.5 | 81 | 0.740385 | 537 | 0.516346 | 0 | 0 | 550 | 0.528846 | 0 | 0 | 3 | 0.002885 |
7f6a2ed067f756a98844a26933435661e374cbc1 | 991 | py | Python | mushroom_rl/utils/eligibility_trace.py | PuzeLiu/mushroom-rl | 99942b425e66b4ddcc26009d7105dde23841e95d | [
"MIT"
] | 344 | 2020-01-10T09:45:02.000Z | 2022-03-30T09:48:28.000Z | mushroom_rl/utils/eligibility_trace.py | AmmarFahmy/mushroom-rl | 2625ee7f64d5613b3b9fba00f0b7a39fece88ca5 | [
"MIT"
] | 44 | 2020-01-23T03:00:56.000Z | 2022-03-25T17:14:22.000Z | mushroom_rl/utils/eligibility_trace.py | AmmarFahmy/mushroom-rl | 2625ee7f64d5613b3b9fba00f0b7a39fece88ca5 | [
"MIT"
] | 93 | 2020-01-10T21:17:58.000Z | 2022-03-31T17:58:52.000Z | from mushroom_rl.utils.table import Table
def EligibilityTrace(shape, name='replacing'):
"""
Factory method to create an eligibility trace of the provided type.
Args:
shape (list): shape of the eligibility trace table;
name (str, 'replacing'): type of the eligibility trace.
Returns:
The eligibility trace table of the provided shape and type.
"""
if name == 'replacing':
return ReplacingTrace(shape)
elif name == 'accumulating':
return AccumulatingTrace(shape)
else:
raise ValueError('Unknown type of trace.')
class ReplacingTrace(Table):
"""
Replacing trace.
"""
def reset(self):
self.table[:] = 0.
def update(self, state, action):
self.table[state, action] = 1.
class AccumulatingTrace(Table):
"""
Accumulating trace.
"""
def reset(self):
self.table[:] = 0.
def update(self, state, action):
self.table[state, action] += 1.
| 21.543478 | 71 | 0.616549 | 389 | 0.392533 | 0 | 0 | 0 | 0 | 0 | 0 | 430 | 0.433905 |
7f6d004764ff3c98efc96ebb1cf1f394bc32a7c1 | 440 | py | Python | example_pkg/Parrots.py | TillWeinhold/EQUSWORKSHOPTill | 95099cc8d8ebc93b53db6d9e9b4c67051fcb7763 | [
"MIT"
] | null | null | null | example_pkg/Parrots.py | TillWeinhold/EQUSWORKSHOPTill | 95099cc8d8ebc93b53db6d9e9b4c67051fcb7763 | [
"MIT"
] | null | null | null | example_pkg/Parrots.py | TillWeinhold/EQUSWORKSHOPTill | 95099cc8d8ebc93b53db6d9e9b4c67051fcb7763 | [
"MIT"
] | null | null | null | class Parrot():
def __init__(self, squawk, is_alive=True):
self.squawk = squawk
self.is_alive = is_alive
african_grey = Parrot('Polly want a Cracker?')
norwegian_blue = Parrot('', is_alive=False)
def squawk(self):
if self.is_alive:
return self.squawk
else:
return None
african_grey.squawk()
norwegian_blue.squawk()
def set_alive(self, is_alive):
self.is_alive = is_alive | 22 | 46 | 0.652273 | 125 | 0.284091 | 0 | 0 | 0 | 0 | 0 | 0 | 25 | 0.056818 |
7f6f7feeb11eb05bb310cec5c813b37346f053c2 | 226 | py | Python | Codility/python/problem2.py | rayguang/ratesbuddy | ec97f85201812967bb3380bba6de41bdb223eab6 | [
"MIT"
] | null | null | null | Codility/python/problem2.py | rayguang/ratesbuddy | ec97f85201812967bb3380bba6de41bdb223eab6 | [
"MIT"
] | null | null | null | Codility/python/problem2.py | rayguang/ratesbuddy | ec97f85201812967bb3380bba6de41bdb223eab6 | [
"MIT"
] | null | null | null | def solution(S, K):
# write your code in Python 3.6
day_dict = {0:'Mon', 1:'Tue', 2:'Wed', 3:'Thu', 4:'Fri', 5:'Sat', 6:'Sun'}
return day_dict[list(day_dict.values()).index(S)+K]
S='Wed'
K=2
print(solution(S,K))
| 22.6 | 78 | 0.584071 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 71 | 0.314159 |
7f7137d3c4d91bf9456a8fd7ac1c27ab02193797 | 162 | py | Python | ex030.py | MarcelleFranca/exercicios-python | e65c1d1f2d92db0e8f5035dea8062a53defa899f | [
"MIT"
] | null | null | null | ex030.py | MarcelleFranca/exercicios-python | e65c1d1f2d92db0e8f5035dea8062a53defa899f | [
"MIT"
] | null | null | null | ex030.py | MarcelleFranca/exercicios-python | e65c1d1f2d92db0e8f5035dea8062a53defa899f | [
"MIT"
] | null | null | null | n = int(input('Me diga um número qualquer: '))
re = n % 2
if re == 0:
print('O número {} é PAR!'.format(n))
else:
print('O número {} é ÍMPAR!'.format(n))
| 23.142857 | 46 | 0.567901 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 78 | 0.464286 |
7f71ee99f2565a596f85f7576a116d55d2f91fcd | 6,927 | py | Python | pyoperant/reinf.py | arouse01/pyoperant | e61de84862096720cca7dbecf517ee11c5d504d4 | [
"BSD-3-Clause"
] | 1 | 2019-01-26T17:19:47.000Z | 2019-01-26T17:19:47.000Z | pyoperant/reinf.py | arouse01/pyoperant | e61de84862096720cca7dbecf517ee11c5d504d4 | [
"BSD-3-Clause"
] | null | null | null | pyoperant/reinf.py | arouse01/pyoperant | e61de84862096720cca7dbecf517ee11c5d504d4 | [
"BSD-3-Clause"
] | null | null | null | from numpy import random
class BaseSchedule(object):
"""Maintains logic for deciding whether to consequate trials.
This base class provides the most basic reinforcent schedule: every
response is consequated.
Methods:
consequate(trial) -- returns a boolean value based on whether the trial
should be consequated. Always returns True.
"""
def __init__(self):
super(BaseSchedule, self).__init__()
def consequate(self, trial):
assert hasattr(trial, 'correct') and isinstance(trial.correct, bool)
if trial.correct:
return True
else:
return True
class ContinuousReinforcement(BaseSchedule):
"""Maintains logic for deciding whether to consequate trials.
This base class provides the most basic reinforcent schedule: every
response is consequated.
Methods:
consequate(trial) -- returns a boolean value based on whether the trial
should be consequated. Always returns True.
"""
def __init__(self):
super(ContinuousReinforcement, self).__init__()
def consequate(self, trial):
assert hasattr(trial, 'correct') and isinstance(trial.correct, bool)
if trial.correct:
return True
else:
return True
class FixedRatioSchedule(BaseSchedule):
"""Maintains logic for deciding whether to consequate trials.
This class implements a fixed ratio schedule, where a reward reinforcement
is provided after every nth correct response, where 'n' is the 'ratio'.
Incorrect trials are always reinforced.
Methods:
consequate(trial) -- returns a boolean value based on whether the trial
should be consequated.
"""
def __init__(self, ratio=1):
super(FixedRatioSchedule, self).__init__()
self.ratio = max(ratio, 1)
self._update()
def _update(self):
self.cumulative_correct = 0
self.threshold = self.ratio
def consequate(self, trial):
assert hasattr(trial, 'correct') and isinstance(trial.correct, bool)
if trial.correct:
self.cumulative_correct += 1
if self.cumulative_correct >= self.threshold:
self._update()
return True
else:
return False
elif not trial.correct:
self.cumulative_correct = 0
return True
else:
return False
def __unicode__(self):
return "FR%i" % self.ratio
class GoInterruptSchedule(BaseSchedule):
"""Maintains logic for deciding whether to consequate trials.
This class implements a conditional continuous schedule, where reinforcement
is provided after certain correct and incorrect responses
Added 6/27/18 by AR for zebra finch isochronicity discrimination experiment.
Correct Response (Resp switch to S+) = True
False Alarm (Resp switch to S-) = True
Miss (NR or Trial switch to S+) = False
Correct Reject (Trial switch to S-) = False
Probe trials are always rewarded (but handled in behavior file instead of here)
Methods:
consequate(trial) -- returns a boolean value based on whether the trial
should be consequated.
"""
def __init__(self):
super(GoInterruptSchedule, self).__init__()
def consequate(self, trial):
assert hasattr(trial, 'correct') and isinstance(trial.correct, bool)
if trial.correct:
if trial.response == 'sPlus': # Hit
return True
else:
return False # Correct reject
elif not trial.correct:
if trial.response == 'sPlus': # False alarm
return True
else:
return False # Miss
else:
return False
class GoInterruptPercentSchedule(BaseSchedule):
"""Maintains logic for deciding whether to consequate trials.
This class implements a conditional percent reinforcement schedule, where reinforcement
is provided randomly after certain correct and incorrect responses
Added 7/9/18 by AR for zebra finch isochronicity discrimination experiment.
Correct Response (Resp switch to S+) = True by probability
False Alarm (Resp switch to S-) = True always
Miss (NR or Trial switch to S+) = False
Correct Reject (Trial switch to S-) = False
Probe trials are always rewarded (but handled in behavior file instead of here)
Methods:
consequate(trial) -- returns a boolean value based on whether the trial
should be consequated.
"""
def __init__(self, prob=1):
super(GoInterruptPercentSchedule, self).__init__()
self.prob = prob
def consequate(self, trial):
if trial.responseType == "correct_response":
return random.random() < self.prob
elif trial.responseType == "false_alarm":
return True
else:
return False
class VariableRatioSchedule(FixedRatioSchedule):
"""Maintains logic for deciding whether to consequate trials.
This class implements a variable ratio schedule, where a reward
reinforcement is provided after every a number of consecutive correct
responses. On average, the number of consecutive responses necessary is the
'ratio'. After a reinforcement is provided, the number of consecutive
correct trials needed for the next reinforcement is selected by sampling
randomly from the interval [1,2*ratio-1]. e.g. a ratio of '3' will require
consecutive correct trials of 1, 2, 3, 4, & 5, randomly.
Incorrect trials are always reinforced.
Methods:
consequate(trial) -- returns a boolean value based on whether the trial
should be consequated.
"""
def __init__(self, ratio=1):
super(VariableRatioSchedule, self).__init__(ratio=ratio)
def _update(self):
""" update min correct by randomly sampling from interval [1:2*ratio)"""
self.cumulative_correct = 0
self.threshold = random.randint(1, 2 * self.ratio)
def __unicode__(self):
return "VR%i" % self.ratio
class PercentReinforcement(BaseSchedule):
"""Maintains logic for deciding whether to consequate trials.
This class implements a probabalistic reinforcement, where a reward reinforcement
is provided x percent of the time.
Incorrect trials are always reinforced.
Methods:
consequate(trial) -- returns a boolean value based on whether the trial
should be consequated.
"""
def __init__(self, prob=1):
super(PercentReinforcement, self).__init__()
self.prob = prob
def consequate(self, trial):
assert hasattr(trial, 'correct') and isinstance(trial.correct, bool)
if trial.correct:
return random.random() < self.prob
else:
return True
def __unicode__(self):
return "PR%i" % self.prob
| 31.06278 | 91 | 0.664501 | 6,881 | 0.993359 | 0 | 0 | 0 | 0 | 0 | 0 | 3,764 | 0.543381 |
7f7253b551b2ff6d740c1f9d0a5085a8b1f18654 | 7,766 | py | Python | Conditional/TextGAIL/model.py | mrazizi/TextGAIL | 9b6e0e62669e0bd4fbb1a8b64098c8432b0d725d | [
"MIT"
] | 19 | 2020-05-16T23:13:43.000Z | 2022-03-08T15:01:48.000Z | Conditional/TextGAIL/model.py | MarkusSagen/TextGAIL | 18ba72c6d63c3c3db1f195d118267c6e8243b4ff | [
"MIT"
] | 2 | 2020-07-24T09:09:34.000Z | 2022-02-22T11:56:31.000Z | Conditional/TextGAIL/model.py | MarkusSagen/TextGAIL | 18ba72c6d63c3c3db1f195d118267c6e8243b4ff | [
"MIT"
] | 10 | 2020-06-09T09:15:14.000Z | 2022-03-20T09:36:30.000Z | from typing import Any, List, Dict, Iterator, Callable
import torch
import torch.nn as nn
import torch.nn.functional as F
from transformers import AutoTokenizer, RobertaForMultipleChoice
import torchfly
from torchfly.nn.transformers import GPT2LMHeadModel
from torchfly.training import FlyModel
from torchfly.nn.losses import SequenceCrossEntropyLoss
from torchfly.metrics import CategoricalAccuracy, Average, MovingAverage, Speed
from torchfly.common.download import get_pretrained_weights
from torchfly.text.decode import TransformerDecoder
# pylint: disable=no-member
class TextGAILModel(FlyModel):
def __init__(self, config):
super().__init__(config)
self.generator = Generator(config)
self.discriminator = Discriminator(config)
self._perplexity = Average()
def configure_optimizers(self, total_num_update_steps) -> [List, List]:
D_optimizer, D_scheduler = self.discriminator.configure_optimizers(total_num_update_steps)
G_optimizer, G_scheduler = self.generator.configure_optimizers(total_num_update_steps)
self.optimizers = D_optimizer + G_optimizer
self.schedulers = D_scheduler + G_scheduler
return self.optimizers, self.schedulers
def predict(self, batch):
self.generator.rl_mode = False
results = self.generator.forward(batch)
self.generator.rl_mode = True
self._perplexity(results["loss"].exp().item())
def get_metrics(self, reset: bool = False) -> Dict[str, float]:
ppl = self._perplexity.get_metric(reset)
metrics = {"perplexity": ppl}
return metrics
class Generator(FlyModel):
def __init__(self, config):
super().__init__(config)
self.config = config
self.encoder = GPT2LMHeadModel(config.model)
self.decoder = self.encoder
self.tokenizer = AutoTokenizer.from_pretrained("roberta-base")
# self.criterion = SequenceCrossEntropyLoss(reduce="sentence")
self.criterion = nn.CrossEntropyLoss(ignore_index=config.model.pad_token_id)
self._perplexity = Average()
# load pretrained weights
# model_weights = get_pretrained_weights("roberta-tokenized-gpt2")
# print(self.encoder.load_state_dict(model_weights, strict=False))
self.rl_mode = True
def forward(self, batch):
batch["source_mask"] = batch["source_token_ids"] != self.tokenizer.pad_token_id
batch["target_mask"] = batch["target_token_ids"] != self.tokenizer.pad_token_id
batch["source_position_ids"] = batch["source_mask"].cumsum(-1) - 1
batch["target_position_ids"] = batch["source_position_ids"][:,
-1].unsqueeze(-1) + batch["target_mask"].cumsum(-1)
# encoder part
_, past = self.encoder(
input_ids=batch["source_token_ids"],
position_ids=batch['source_position_ids'],
attention_mask=batch["source_mask"],
past=None
)
joint_mask = torch.cat([batch["source_mask"], batch["target_mask"]], dim=1)
logits, _ = self.decoder(
input_ids=batch["target_token_ids"],
position_ids=batch['target_position_ids'],
attention_mask=joint_mask,
past=past
)
if not self.rl_mode:
loss = self.compute_lm_loss(batch["target_token_ids"], logits, batch["target_mask"])
return {"loss": loss}
else:
logits = logits[:, :-1].contiguous()
target_token_ids = batch["target_token_ids"][:, 1:].contiguous()
log_probs = torch.log_softmax(logits, dim=-1)
log_probs = torch.gather(log_probs, dim=-1, index=target_token_ids.unsqueeze(-1)).squeeze(-1)
# mask
log_probs = (log_probs * batch["target_mask"][:, 1:]).sum(-1) # / mask.sum(-1)
results = {"log_probs": log_probs, "loss": 0.0}
return results
def compute_log_probs(self, batch):
"This function is used by TextRLTrainerLoop"
batch["source_mask"] = batch["source_token_ids"] != self.tokenizer.pad_token_id
batch["target_mask"] = batch["target_token_ids"] != self.tokenizer.pad_token_id
batch["source_position_ids"] = batch["source_mask"].cumsum(-1) - 1
batch["target_position_ids"] = batch["source_position_ids"][:,
-1].unsqueeze(-1) + batch["target_mask"].cumsum(-1)
# encoder part
_, past = self.encoder(
input_ids=batch["source_token_ids"],
position_ids=batch['source_position_ids'],
attention_mask=batch["source_mask"],
past=None
)
joint_mask = torch.cat([batch["source_mask"], batch["target_mask"]], dim=1)
logits, _ = self.decoder(
input_ids=batch["target_token_ids"],
position_ids=batch['target_position_ids'],
attention_mask=joint_mask,
past=past
)
if not self.rl_mode:
loss = self.compute_lm_loss(batch["target_token_ids"], logits, batch["target_mask"])
return {"loss": loss}
else:
logits = logits[:, :-1].contiguous()
target_token_ids = batch["target_token_ids"][:, 1:].contiguous()
log_probs = torch.log_softmax(logits, dim=-1)
log_probs = torch.gather(log_probs, dim=-1, index=target_token_ids.unsqueeze(-1)).squeeze(-1)
# mask
log_probs = (log_probs * batch["target_mask"][:, 1:]).sum(-1) # / mask.sum(-1)
return {"log_probs": log_probs}
def predict(self, batch):
results = self.forward(batch)
self._perplexity(results["loss"].exp().item())
def get_metrics(self, reset: bool = False) -> Dict[str, float]:
ppl = self._perplexity.get_metric(reset)
metrics = {"perplexity": ppl}
return metrics
def compute_lm_loss(self, input_ids, logits, mask):
logits = logits[:, :-1].contiguous()
target = input_ids[:, 1:].contiguous()
#mask = mask[:, 1:].float()
#return self.criterion(logits, target, mask)
return self.criterion(logits.view(-1, logits.size(-1)), target.view(-1))
def prepare_model_inputs_for_generation(self, input_ids, model_inputs, num_sequences):
model_inputs = {}
model_inputs["attention_mask"] = (input_ids != self.tokenizer.pad_token_id)
model_inputs["position_ids"] = (input_ids != self.tokenizer.pad_token_id).cumsum(-1) - 1
_, past = self.encoder(
input_ids=input_ids,
attention_mask=model_inputs["attention_mask"],
position_ids=model_inputs["position_ids"],
past=None
)
model_inputs["past"] = past
model_inputs["attention_mask"] = F.pad(model_inputs["attention_mask"], pad=(0, 1), value=True)
# remember to add one
model_inputs["position_ids"] = model_inputs["position_ids"][:, -1].unsqueeze(-1) + 1
bos_token_ids = torch.LongTensor(self.config.decode.bos_token_ids)
model_inputs["input_ids"] = bos_token_ids.unsqueeze(0).expand(input_ids.shape[0], -1).to(input_ids.device)
return model_inputs
class Discriminator(FlyModel):
def __init__(self, config):
super().__init__(config)
self.config = config
self.model = RobertaForMultipleChoice.from_pretrained("roberta-base")
def forward(self, batch, training=False):
self.model.eval()
logits = self.model(batch["input_ids"])[0]
log_probs = F.log_softmax(logits, dim=-1)
loss = -log_probs[:, 0].mean()
return {"reward": log_probs[:, 1].exp(), "loss": loss}
| 40.873684 | 119 | 0.635076 | 7,184 | 0.925058 | 0 | 0 | 0 | 0 | 0 | 0 | 1,380 | 0.177698 |
7f7257441c10fd88f6708caf8a3bdeae39120b6f | 5,622 | py | Python | yolo_v1_inference.py | jerichosu/YOLO_V1_Pytorch | 2f665f6b6b00d8cf9782bff43c5aede5aa5c3a4a | [
"MIT"
] | null | null | null | yolo_v1_inference.py | jerichosu/YOLO_V1_Pytorch | 2f665f6b6b00d8cf9782bff43c5aede5aa5c3a4a | [
"MIT"
] | null | null | null | yolo_v1_inference.py | jerichosu/YOLO_V1_Pytorch | 2f665f6b6b00d8cf9782bff43c5aede5aa5c3a4a | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 10 14:12:28 2022
@author: 1517suj
"""
from model import Yolov1
import torch
import torch.optim as optim
import torchvision.transforms as T
import cv2
from utils import (
non_max_suppression,
mean_average_precision,
intersection_over_union,
cellboxes_to_boxes, #converting boxes from relative to the cell to relative to the entire image
get_bboxes,
plot_image,
load_checkpoint,)
# inference
DEVICE = 'cuda'
LOAD_MODEL_FILE = "overfit.pth.tar"
LEARNING_RATE = 2e-5
WEIGHT_DECAY = 0
model = Yolov1(split_size=7, num_boxes=2, num_classes=20)
optimizer = optim.Adam(model.parameters(), lr=LEARNING_RATE, weight_decay=WEIGHT_DECAY)
load_checkpoint(torch.load(LOAD_MODEL_FILE), model, optimizer)
model.to(DEVICE)
model.eval()
# %%
# some testing images
# path = 'two_dogs_test1.png'
# path = 'two_dogs_test2.jpg'
# path = 'three_dogs.png'
# path = 'yaz_test.jpg'
path = 'town_center.png'
img = cv2.imread(path)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
print(img.shape)
# cv2.imshow('image', img)
# cv2.waitKey(0)
# cv2.destroyAllWindows()
# # convert from numpy array to tensor
# inputs = torch.from_numpy(img) # torch.Size([H,W,3])
# inputs = inputs.permute(2,0,1) # torch.Size([3,H,W])
# print(inputs.shape)
# change the height and width to fit the model
transform=T.Compose([T.ToTensor(), # TO TENSOR FIRST!!!!!!!!!
T.Resize((448, 448))])
# when you use ToTensor() class, PyTorch automatically converts all images into [0,1].
inputs = transform(img) # torch.Size([3,448,448])
print(inputs.shape)
# increase the dimension
inputs = torch.unsqueeze(inputs, 0) # torch.Size([1,3,H,W])
print(inputs.shape)
input_tensor = inputs.to(DEVICE)
output = model(input_tensor)
print(output.shape)
# %%
#convert to results
bboxes = cellboxes_to_boxes(output) # convert to bboxes
# plot without non_max_suppression
# plot_image(input_tensor.squeeze(0).permute(1,2,0).to("cpu"), bboxes[0])
plot_image(img, bboxes[0])
# NMS
bboxes = non_max_suppression(bboxes[0], iou_threshold=0.8, threshold=0.15, box_format="midpoint")
# plot after NMS (this one plots the 448x448 results)
# plot_image(input_tensor.squeeze(0).permute(1,2,0).to("cpu"), bboxes)
# this one shows the actual image size
plot_image(img, bboxes)
# cap = cv2.VideoCapture(path)
# retaining = True
# kk = 0
# image_list = []
# clip = []
# while retaining:
# retaining, frame = cap.read()
# if not retaining and frame is None:
# continue
# # tmp_ = center_crop(cv2.resize(frame, (171, 128)))
# # tmp = tmp_ - np.array([[[90.0, 98.0, 102.0]]])
# # i = 0
# # i += 1
# # if i == 0 and i % 7 == 0:
# # clip.append(frame)
# clip.append(frame)
# if len(clip) == 16:
# inputs = np.array(clip).astype(np.float32)
# # inputs = np.expand_dims(inputs, axis=0)
# # inputs = np.transpose(inputs, (0, 4, 1, 2, 3))
# # convert from numpy array to tensor
# inputs = torch.from_numpy(inputs) # torch.Size([16, 360, 640, 3])
# inputs = inputs.permute(3,0,1,2) # torch.Size([3, 16, 360, 640])
# # print(inputs.shape)
# # change the height and width to fit the model
# inputs = trans_val(inputs) # torch.Size([3, 16, 224, 224])
# # increase the dimension
# inputs = torch.unsqueeze(inputs, 0) # torch.Size([1, 3, 16, 224, 224])
# # Data normalization
# # Divide every pixel intensity by 255.0
# inputs = inputs.type(torch.FloatTensor).div_(255.0)
# # Pixel intensity from 0 ~ 255 to [-1, +1]
# inputs = inputs.type(torch.FloatTensor).sub_(stats['mean'][:,None,None,None]).div_(stats['std'][:,None,None,None])
# inputs = inputs.to(device)
# # inputs = torch.autograd.Variable(inputs, requires_grad=False).to(device)
# with torch.no_grad():
# outputs = model(inputs).squeeze(2)
# # outputs = model.forward(inputs).squeeze(2)
# # compute the probability
# m = nn.Softmax(dim=1)
# # probs = torch.max(m(outputs))
# probs_fight = m(outputs)[0][0]
# # check!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
# # probs = torch.max(outputs)
# # print(probs_fight)
# predicted_labels = torch.argmax(outputs)
# # _, predicted_labels = torch.max(outputs, 1)
# # print(int(predicted_labels))
# # print(outputs.shape)
# # label = torch.max(probs, 1)[1].detach().cpu().numpy()[0]
# cv2.putText(frame, labels[int(predicted_labels)], (5, 50),
# cv2.FONT_HERSHEY_SIMPLEX, 1.5,
# (0, 0, 255), thickness=2)
# cv2.putText(frame, "Prob_fight: %.4f" % probs_fight, (5, 100),
# cv2.FONT_HERSHEY_SIMPLEX, 1.0,
# (0, 0, 255), thickness=2)
# # print(len(clip))
# clip.pop(0)
# # print(len(clip))
# # break
# cv2.imshow('result', frame)
# # make sure don't make gif too big
# kk += 1
# print(kk)
# # if kk > 500 and kk < 800:
# # print(kk)
# # frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# # image_list.append(frame_rgb)
# # if kk > 800:
# # break
# if cv2.waitKey(1) & 0xFF == ord('q'):
# break
# # cv2.waitKey(30)
# cap.release()
# cv2.destroyAllWindows()
| 26.771429 | 124 | 0.590359 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4,174 | 0.74244 |
7f7260f159737945fe7bc1ae8aea08979812d974 | 1,812 | py | Python | setup.py | sedatDemiriz/satisfy-calc | 6b89226a87958dd89ed6327d9bf10bd5e9927a7b | [
"MIT"
] | null | null | null | setup.py | sedatDemiriz/satisfy-calc | 6b89226a87958dd89ed6327d9bf10bd5e9927a7b | [
"MIT"
] | null | null | null | setup.py | sedatDemiriz/satisfy-calc | 6b89226a87958dd89ed6327d9bf10bd5e9927a7b | [
"MIT"
] | null | null | null | import pathlib
from setuptools import setup
# The directory containing this file
HERE = pathlib.Path(__file__).parent
# The text of the README file
README = (HERE / "README.md").read_text()
setup(
name="satisfy-calc",
version="1.1.3",
description="Command line crafting tree visualizer for Satisfactory Game by CoffeeStain Studios",
long_description=README,
long_description_content_type="text/markdown",
url="https://github.com/sedatDemiriz/satisfy-calc",
author="Sedat Demiriz",
author_email="sedatdemiriz97@gmail.com",
license="MIT",
classifiers=[
"License :: OSI Approved :: MIT License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.7",
],
install_requires=["bs4", "jsonpickle", "requests"],
packages=["satisfy_calc"],
entry_points={
"console_scripts": [
"satisfy_calc=satisfy_calc.__main__:main"
]
},
)
# setup(
# name="realpython-reader",
# version="1.0.0",
# description="Read the latest Real Python tutorials",
# long_description=README,
# long_description_content_type="text/markdown",
# url="https://github.com/realpython/reader",
# author="Real Python",
# author_email="info@realpython.com",
# license="MIT",
# classifiers=[
# "License :: OSI Approved :: MIT License",
# "Programming Language :: Python :: 3",
# "Programming Language :: Python :: 3.7",
# ],
# packages=["reader"],
# include_package_data=True,
# install_requires=["feedparser", "html2text"],
# entry_points={
# "console_scripts": [
# "realpython=reader.__main__:main",
# ]
# },
# )
| 30.711864 | 105 | 0.598786 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,246 | 0.687638 |
7f74399a50cac0ddf062397297d09c884bd0d887 | 74 | py | Python | projects/InstantTeaching/models/__init__.py | txdet/Instant-Teaching | d07910c4c811d875b03200ffb1822c32556ccf9a | [
"Apache-2.0"
] | 18 | 2021-12-14T08:37:34.000Z | 2022-03-25T18:53:21.000Z | projects/InstantTeaching/models/__init__.py | txdet/Instant-Teaching | d07910c4c811d875b03200ffb1822c32556ccf9a | [
"Apache-2.0"
] | 1 | 2022-02-16T08:06:30.000Z | 2022-02-16T08:06:30.000Z | projects/InstantTeaching/models/__init__.py | txdet/Instant-Teaching | d07910c4c811d875b03200ffb1822c32556ccf9a | [
"Apache-2.0"
] | 1 | 2022-02-08T08:30:07.000Z | 2022-02-08T08:30:07.000Z | from .detectors import *
from .max_iou_assigner_v2 import MaxIoUAssignerV2 | 37 | 49 | 0.864865 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
7f74c0fc275d974a627baa79ccbe3262645f2513 | 2,195 | py | Python | components/studio/projects/migrations/0015_auto_20210301_1015.py | aitmlouk/stackn | c8029394a15b03796a4864938f9db251b65c7354 | [
"Apache-2.0"
] | 25 | 2020-05-08T22:24:54.000Z | 2022-03-11T18:16:58.000Z | components/studio/projects/migrations/0015_auto_20210301_1015.py | aitmlouk/stackn | c8029394a15b03796a4864938f9db251b65c7354 | [
"Apache-2.0"
] | 75 | 2020-05-08T22:15:59.000Z | 2021-11-22T10:00:04.000Z | components/studio/projects/migrations/0015_auto_20210301_1015.py | aitmlouk/stackn | c8029394a15b03796a4864938f9db251b65c7354 | [
"Apache-2.0"
] | 12 | 2020-11-04T13:09:46.000Z | 2022-03-14T16:22:40.000Z | # Generated by Django 3.1.6 on 2021-03-01 10:15
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('projects', '0014_environment_appenv'),
]
operations = [
migrations.RemoveField(
model_name='flavor',
name='cpu',
),
migrations.RemoveField(
model_name='flavor',
name='gpu',
),
migrations.RemoveField(
model_name='flavor',
name='mem',
),
migrations.AddField(
model_name='flavor',
name='cpu_lim',
field=models.TextField(blank=True, default='1000m', null=True),
),
migrations.AddField(
model_name='flavor',
name='cpu_req',
field=models.TextField(blank=True, default='200m', null=True),
),
migrations.AddField(
model_name='flavor',
name='ephmem_lim',
field=models.TextField(blank=True, default='200Mi', null=True),
),
migrations.AddField(
model_name='flavor',
name='ephmem_req',
field=models.TextField(blank=True, default='200Mi', null=True),
),
migrations.AddField(
model_name='flavor',
name='gpu_lim',
field=models.TextField(blank=True, default='0', null=True),
),
migrations.AddField(
model_name='flavor',
name='gpu_req',
field=models.TextField(blank=True, default='0', null=True),
),
migrations.AddField(
model_name='flavor',
name='mem_lim',
field=models.TextField(blank=True, default='3Gi', null=True),
),
migrations.AddField(
model_name='flavor',
name='mem_req',
field=models.TextField(blank=True, default='0.5Gi', null=True),
),
migrations.AddField(
model_name='flavor',
name='project',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, to='projects.project'),
),
]
| 30.486111 | 115 | 0.541686 | 2,069 | 0.942597 | 0 | 0 | 0 | 0 | 0 | 0 | 343 | 0.156264 |
7f7574b64532b1f7794103ece680d1785b89f64b | 210 | py | Python | tests/Auth_Test.py | PyDO-Team/PyDO-Old | a89d9d30aee72a42ce3afdd90b5b297e7b908d73 | [
"BSD-3-Clause"
] | 1 | 2021-02-23T12:54:05.000Z | 2021-02-23T12:54:05.000Z | tests/Auth_Test.py | PyDO-Team/PyDO-Old | a89d9d30aee72a42ce3afdd90b5b297e7b908d73 | [
"BSD-3-Clause"
] | null | null | null | tests/Auth_Test.py | PyDO-Team/PyDO-Old | a89d9d30aee72a42ce3afdd90b5b297e7b908d73 | [
"BSD-3-Clause"
] | 1 | 2021-02-23T12:54:07.000Z | 2021-02-23T12:54:07.000Z | from TestOutput import LogManager
class Auth_Test:
def __init__(self):
self.logger = LogManager('AuthTest')
self.logger.writeTestEvent('AuthTest', 'Test Started')
if __name__ == "__main__":
Auth_Test() | 21 | 56 | 0.747619 | 134 | 0.638095 | 0 | 0 | 0 | 0 | 0 | 0 | 44 | 0.209524 |
7f76ceea26c08de27da1840f0d593d7e2ff3c37f | 298 | py | Python | app/models/db.py | cdlaimin/fastapi | 4acf1a1da4a1eedd81a3bdf6256661c2464928b9 | [
"BSD-3-Clause"
] | null | null | null | app/models/db.py | cdlaimin/fastapi | 4acf1a1da4a1eedd81a3bdf6256661c2464928b9 | [
"BSD-3-Clause"
] | null | null | null | app/models/db.py | cdlaimin/fastapi | 4acf1a1da4a1eedd81a3bdf6256661c2464928b9 | [
"BSD-3-Clause"
] | null | null | null | from sqlalchemy.ext.asyncio import create_async_engine, AsyncSession
from sqlalchemy.orm import sessionmaker
from app.core.config import settings
engine = create_async_engine(settings.ASYNC_SQLALCHEMY_DATABASE_URI)
SessionLocal = sessionmaker(engine, class_=AsyncSession, expire_on_commit=False)
| 37.25 | 80 | 0.865772 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
7f774ce1cb63f287b074535083076da2eb2886d4 | 37 | py | Python | src/globals.py | 22PoojaGaur/COMINE-Plusplus-Algorithm-for-Finding-Correlated-Patterns-from-Transactions | 3b554ab337765f8c02126c585dd025d71c539f73 | [
"MIT"
] | null | null | null | src/globals.py | 22PoojaGaur/COMINE-Plusplus-Algorithm-for-Finding-Correlated-Patterns-from-Transactions | 3b554ab337765f8c02126c585dd025d71c539f73 | [
"MIT"
] | 6 | 2020-10-03T19:47:08.000Z | 2021-04-23T10:55:19.000Z | src/globals.py | 22PoojaGaur/COMINE-Plusplus-Algorithm-for-Finding-Correlated-Patterns-from-Transactions | 3b554ab337765f8c02126c585dd025d71c539f73 | [
"MIT"
] | null | null | null | MIN_SUPPORT = 2
MIN_ALL_CONF = 0.05
| 9.25 | 19 | 0.72973 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
7f794d62fc3c675ead0a023096a5c67f9a7ede0f | 195 | py | Python | 1-iniciante/1038.py | marcobarone-dev/uri | 82bf0b244d3966673b10a42948dcdeabcde07e76 | [
"MIT"
] | 1 | 2018-07-04T02:42:29.000Z | 2018-07-04T02:42:29.000Z | 1-iniciante/1038.py | marcobarone-dev/uri-python | 82bf0b244d3966673b10a42948dcdeabcde07e76 | [
"MIT"
] | null | null | null | 1-iniciante/1038.py | marcobarone-dev/uri-python | 82bf0b244d3966673b10a42948dcdeabcde07e76 | [
"MIT"
] | null | null | null | produtos = {1: 4.0, 2: 4.5, 3: 5.0, 4: 2.0, 5: 1.5}
produto, quantidade = [int(num) for num in input().split()]
total = produtos[produto] * quantidade
print('Total: R$ {:.2f}'.format(total))
| 39 | 60 | 0.605128 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 18 | 0.092308 |
7f7b9c9bf2b4a1aef51cf2613f660d03ff4d092d | 1,168 | py | Python | books/software-architecture-with-python/Ch04-performance-data-structures/primes.py | phiratio/lpthw | a32240d4355fb331805d515f96e1d009914e5c47 | [
"MIT"
] | 1 | 2021-04-21T09:38:38.000Z | 2021-04-21T09:38:38.000Z | books/software-architecture-with-python/Ch04-performance-data-structures/primes.py | phiratio/lpthw | a32240d4355fb331805d515f96e1d009914e5c47 | [
"MIT"
] | 34 | 2019-12-16T16:53:24.000Z | 2022-01-13T02:29:30.000Z | books/software-architecture-with-python/Ch04-performance-data-structures/primes.py | phiratio/lpthw | a32240d4355fb331805d515f96e1d009914e5c47 | [
"MIT"
] | null | null | null | # Code Listing #3
"""
Prime number iterator class
"""
class Prime(object):
""" A prime number iterator for first 'n' primes """
def __init__(self, n):
self.n = n
self.count = 0
self.value = 0
def __iter__(self):
return self
def __next__(self):
""" Return next item in iterator """
if self.count == self.n:
raise StopIteration("end of iteration")
return self.compute()
# Uncomment next line for profiling with line profiler
# or memory profiler.
# @profile
def is_prime(self):
""" Whether current value is prime ? """
vroot = int(self.value ** 0.5) + 1
for i in range(3, vroot, 2):
if self.value % i == 0:
return False
return True
def compute(self):
""" Compute next prime """
# Second time, reset value
if self.count == 1:
self.value = 1
while True:
self.value += 2
if self.is_prime():
self.count += 1
break
return self.value
if __name__ == "__main__":
l = list(Prime(1000))
| 20.137931 | 58 | 0.518836 | 1,054 | 0.902397 | 0 | 0 | 0 | 0 | 0 | 0 | 347 | 0.297089 |
7f7cecbd7d8387712e80404ab9516b060333f0e5 | 444 | py | Python | timeblock/stopwatch.py | daustin391/timeblock | 1895f95205100f2f191feccbb1bcb90672aae043 | [
"MIT"
] | null | null | null | timeblock/stopwatch.py | daustin391/timeblock | 1895f95205100f2f191feccbb1bcb90672aae043 | [
"MIT"
] | null | null | null | timeblock/stopwatch.py | daustin391/timeblock | 1895f95205100f2f191feccbb1bcb90672aae043 | [
"MIT"
] | null | null | null | """ Stopwatch
A simple stopwatch for measuring time
"""
from datetime import datetime
class Stopwatch:
"""Stopwatch object for measuring time"""
def __init__(self):
self._start = None
def start(self):
"""Starts watch by setting start time to now"""
self._start = datetime.now()
def check(self):
"""Check the time passed since watch started"""
return self._start - datetime.now()
| 22.2 | 55 | 0.635135 | 351 | 0.790541 | 0 | 0 | 0 | 0 | 0 | 0 | 194 | 0.436937 |
7f7d50f6a8fff49e5e4da85906cece438d04d0c3 | 623 | py | Python | src/data/mnist_converter.py | laurabondeholst/Mapping_high_dimensional_data | 208c1024d3984cf60fc2f54b7bfdffaa83c60157 | [
"MIT"
] | null | null | null | src/data/mnist_converter.py | laurabondeholst/Mapping_high_dimensional_data | 208c1024d3984cf60fc2f54b7bfdffaa83c60157 | [
"MIT"
] | null | null | null | src/data/mnist_converter.py | laurabondeholst/Mapping_high_dimensional_data | 208c1024d3984cf60fc2f54b7bfdffaa83c60157 | [
"MIT"
] | null | null | null | """
Takes the MNIST dataset as input (images and labels separated)
and creates a new dataset only with 0's and 1's
"""
import numpy as np
DATA_PATH = "data/raw/"
OUTPUT_PATH = "data/processed/mnist/"
X = np.loadtxt(DATA_PATH + "mnist2500_X.txt")
labels = np.loadtxt(DATA_PATH + "mnist2500_labels.txt")
X_new = []
labels_new = []
for i,label in enumerate(labels):
if label < 5:
labels_new.append(label)
X_new.append(X[i])
if i%100 == 0:
print(f"{i} labels passed")
np.savetxt(OUTPUT_PATH + "mnist2500_X_01234.txt",X_new)
np.savetxt(OUTPUT_PATH +"mnist2500_labels_01234.txt",labels_new) | 25.958333 | 64 | 0.693419 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 262 | 0.420546 |
7f7df73d539af4f42bcbde355e7bdef39b43dc8a | 7,364 | py | Python | models/pytorch_gcn.py | SamGalanakis/FlowCompare | ed26e48298fe42cf9ddcc252c19b502b4a71d54e | [
"MIT"
] | 5 | 2021-05-22T23:14:19.000Z | 2022-02-19T14:11:27.000Z | models/pytorch_gcn.py | SamGalanakis/PointFlowChange | ed26e48298fe42cf9ddcc252c19b502b4a71d54e | [
"MIT"
] | 1 | 2021-06-05T11:20:53.000Z | 2021-06-05T12:30:44.000Z | models/pytorch_gcn.py | SamGalanakis/PointFlowChange | ed26e48298fe42cf9ddcc252c19b502b4a71d54e | [
"MIT"
] | null | null | null | import os
import sys
import copy
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from models.nets import MLP
# Original code from : https://github.com/WangYueFt/dgcnn/blob/master/pytorch/model.py
def knn(x, k):
inner = -2*torch.matmul(x.transpose(2, 1), x)
xx = torch.sum(x**2, dim=1, keepdim=True)
pairwise_distance = -xx - inner - xx.transpose(2, 1)
# (batch_size, num_points, k)
idx = pairwise_distance.topk(k=k, dim=-1)[1]
return idx
def get_graph_feature(x, k=20, idx=None):
batch_size = x.size(0)
num_points = x.size(2)
x = x.view(batch_size, -1, num_points)
if idx is None:
idx = knn(x, k=k) # (batch_size, num_points, k)
idx_base = torch.arange(
0, batch_size, device=x.device).view(-1, 1, 1)*num_points
idx = idx + idx_base
idx = idx.view(-1)
_, num_dims, _ = x.size()
# (batch_size, num_points, num_dims) -> (batch_size*num_points, num_dims) # batch_size * num_points * k + range(0, batch_size*num_points)
x = x.transpose(2, 1).contiguous()
feature = x.view(batch_size*num_points, -1)[idx, :]
feature = feature.view(batch_size, num_points, k, num_dims)
x = x.view(batch_size, num_points, 1, num_dims).repeat(1, 1, k, 1)
feature = torch.cat((feature-x, x), dim=3).permute(0, 3, 1, 2).contiguous()
return feature
class DGCNNembedder(nn.Module):
"""DGCNN embedder with n_points x embedding dim as output"""
def __init__(self, out_mlp_dims, emb_dim=22, dropout=0, n_neighbors=20):
super().__init__()
self.n_neighbors = n_neighbors
self.bn1 = nn.BatchNorm2d(64)
self.bn2 = nn.BatchNorm2d(64)
self.bn3 = nn.BatchNorm2d(128)
self.bn4 = nn.BatchNorm2d(256)
self.bn5 = nn.BatchNorm1d(512)
self.conv1 = nn.Sequential(nn.Conv2d(12, 64, kernel_size=1, bias=False),
self.bn1,
nn.LeakyReLU(negative_slope=0.2))
self.conv2 = nn.Sequential(nn.Conv2d(64*2, 64, kernel_size=1, bias=False),
self.bn2,
nn.LeakyReLU(negative_slope=0.2))
self.conv3 = nn.Sequential(nn.Conv2d(64*2, 128, kernel_size=1, bias=False),
self.bn3,
nn.LeakyReLU(negative_slope=0.2))
self.conv4 = nn.Sequential(nn.Conv2d(128*2, 256, kernel_size=1, bias=False),
self.bn4,
nn.LeakyReLU(negative_slope=0.2))
self.conv5 = nn.Sequential(nn.Conv1d(512, 512, kernel_size=1, bias=False),
self.bn5,
nn.LeakyReLU(negative_slope=0.2))
self.out_mlp = MLP(512, out_mlp_dims, emb_dim, torch.nn.GELU())
def forward(self, x):
batch_size = x.size(0)
x = x.permute((0, 2, 1))
x = get_graph_feature(x, k=self.n_neighbors)
x = self.conv1(x)
x1 = x.max(dim=-1, keepdim=False)[0]
x = get_graph_feature(x1, self.n_neighbors)
x = self.conv2(x)
x2 = x.max(dim=-1, keepdim=False)[0]
x = get_graph_feature(x2, k=self.n_neighbors)
x = self.conv3(x)
x3 = x.max(dim=-1, keepdim=False)[0]
x = get_graph_feature(x3, k=self.n_neighbors)
x = self.conv4(x)
x4 = x.max(dim=-1, keepdim=False)[0]
x = torch.cat((x1, x2, x3, x4),dim=1)
x = self.conv5(x).permute((0, 2, 1))
x = self.out_mlp(x)
return x
class DGCNNembedderGlobal(nn.Module):
"""DGCNN embedder with single embedding vector as output"""
def __init__(self, input_dim, out_mlp_dims, emb_dim=22, n_neighbors=20):
super().__init__()
self.n_neighbors = n_neighbors
self.input_dim = input_dim
self.bn1 = nn.BatchNorm2d(64)
self.bn2 = nn.BatchNorm2d(64)
self.bn3 = nn.BatchNorm2d(128)
self.bn4 = nn.BatchNorm2d(256)
self.bn5 = nn.BatchNorm1d(512)
self.conv1 = nn.Sequential(nn.Conv2d(self.input_dim*2, 64, kernel_size=1, bias=False),
self.bn1,
nn.LeakyReLU(negative_slope=0.2))
self.conv2 = nn.Sequential(nn.Conv2d(64*2, 64, kernel_size=1, bias=False),
self.bn2,
nn.LeakyReLU(negative_slope=0.2))
self.conv3 = nn.Sequential(nn.Conv2d(64*2, 128, kernel_size=1, bias=False),
self.bn3,
nn.LeakyReLU(negative_slope=0.2))
self.conv4 = nn.Sequential(nn.Conv2d(128*2, 256, kernel_size=1, bias=False),
self.bn4,
nn.LeakyReLU(negative_slope=0.2))
self.conv5 = nn.Sequential(nn.Conv1d(512, 512, kernel_size=1, bias=False),
self.bn5,
nn.LeakyReLU(negative_slope=0.2))
self.out_mlp = MLP(512*2, out_mlp_dims, emb_dim, torch.nn.GELU())
def forward(self, x):
batch_size = x.size(0)
x = x.permute((0, 2, 1))
# (batch_size, 3, num_points) -> (batch_size, 3*2, num_points, k)
x = get_graph_feature(x, k=self.n_neighbors)
# (batch_size, 3*2, num_points, k) -> (batch_size, 64, num_points, k)
x = self.conv1(x)
# (batch_size, 64, num_points, k) -> (batch_size, 64, num_points)
x1 = x.max(dim=-1, keepdim=False)[0]
# (batch_size, 64, num_points) -> (batch_size, 64*2, num_points, k)
x = get_graph_feature(x1, k=self.n_neighbors)
# (batch_size, 64*2, num_points, k) -> (batch_size, 64, num_points, k)
x = self.conv2(x)
# (batch_size, 64, num_points, k) -> (batch_size, 64, num_points)
x2 = x.max(dim=-1, keepdim=False)[0]
# (batch_size, 64, num_points) -> (batch_size, 64*2, num_points, k)
x = get_graph_feature(x2, k=self.n_neighbors)
# (batch_size, 64*2, num_points, k) -> (batch_size, 128, num_points, k)
x = self.conv3(x)
# (batch_size, 128, num_points, k) -> (batch_size, 128, num_points)
x3 = x.max(dim=-1, keepdim=False)[0]
# (batch_size, 128, num_points) -> (batch_size, 128*2, num_points, k)
x = get_graph_feature(x3, k=self.n_neighbors)
# (batch_size, 128*2, num_points, k) -> (batch_size, 256, num_points, k)
x = self.conv4(x)
# (batch_size, 256, num_points, k) -> (batch_size, 256, num_points)
x4 = x.max(dim=-1, keepdim=False)[0]
# (batch_size, 64+64+128+256, num_points)
x = torch.cat((x1, x2, x3, x4), dim=1)
# (batch_size, 64+64+128+256, num_points) -> (batch_size, emb_dims, num_points)
x = self.conv5(x)
# (batch_size, emb_dims, num_points) -> (batch_size, emb_dims)
x1 = F.adaptive_max_pool1d(x, 1).view(batch_size, -1)
# (batch_size, emb_dims, num_points) -> (batch_size, emb_dims)
x2 = F.adaptive_avg_pool1d(x, 1).view(batch_size, -1)
x = torch.cat((x1, x2), 1) # (batch_size, emb_dims*2)
# (batch_size, 256) -> (batch_size, output_channels)
x = self.out_mlp(x)
return x
| 38.354167 | 144 | 0.562873 | 5,967 | 0.810293 | 0 | 0 | 0 | 0 | 0 | 0 | 1,539 | 0.20899 |
7f8193e422f05e255a9a742b6b7c71cffa4e2519 | 2,794 | py | Python | src/weaver/models/custom/wrn28.py | Holim0711/holim-lightning | 690972c8faa587e7042bc15d4980c363163083e4 | [
"MIT"
] | 1 | 2021-03-03T08:53:49.000Z | 2021-03-03T08:53:49.000Z | src/weaver/models/custom/wrn28.py | Holim0711/holim-lightning | 690972c8faa587e7042bc15d4980c363163083e4 | [
"MIT"
] | 1 | 2021-03-19T09:16:05.000Z | 2021-03-19T09:35:18.000Z | src/weaver/models/custom/wrn28.py | Holim0711/holim-lightning | 690972c8faa587e7042bc15d4980c363163083e4 | [
"MIT"
] | null | null | null | import torch.nn as nn
class BasicBlock(nn.Module):
def __init__(self, cᵢ, cₒ, s=1, dropout=0., activate_before_residual=False):
super().__init__()
self.activate_before_residual = activate_before_residual
# residual path
self.conv0 = nn.Conv2d(cᵢ, cₒ, 3, s, 1, bias=False)
self.conv1 = nn.Conv2d(cₒ, cₒ, 3, 1, 1, bias=False)
self.bn0 = nn.BatchNorm2d(cᵢ)
self.bn1 = nn.BatchNorm2d(cₒ)
self.relu0 = nn.ReLU()
self.relu1 = nn.ReLU()
self.drop = nn.Dropout(dropout)
# shortcut path
if (cᵢ == cₒ) and (s == 1):
self.shortcut = nn.Identity()
else:
self.shortcut = nn.Conv2d(cᵢ, cₒ, 1, s, 0, bias=False)
def forward(self, x):
z = self.relu0(self.bn0(x))
if self.activate_before_residual:
x = z
z = self.conv0(z)
z = self.relu1(self.bn1(z))
z = self.conv1(self.drop(z))
x = self.shortcut(x)
return x + z
def _make_layer(n, cᵢ, cₒ, s=1, activate_before_residual=False, **kwargs):
layers = [BasicBlock(cᵢ, cₒ, s, activate_before_residual=activate_before_residual, **kwargs)]
layers += [BasicBlock(cₒ, cₒ, 1, **kwargs) for _ in range(n - 1)]
return nn.Sequential(*layers)
class WideResNet(nn.Module):
def __init__(self, depth, width, num_classes=10, dropout=0., activate_before_residual=False):
super().__init__()
assert (depth - 4) % 6 == 0
n = (depth - 4) // 6
c = [16, 16 * width, 32 * width, 64 * width]
self.conv = nn.Conv2d(3, c[0], 3, 1, 1, bias=False)
self.block1 = _make_layer(n, c[0], c[1], 1, dropout=dropout, activate_before_residual=activate_before_residual)
self.block2 = _make_layer(n, c[1], c[2], 2, dropout=dropout)
self.block3 = _make_layer(n, c[2], c[3], 2, dropout=dropout)
self.bn = nn.BatchNorm2d(c[3])
self.relu = nn.ReLU()
self.pool = nn.AdaptiveAvgPool2d((1, 1))
self.flatten = nn.Flatten()
self.fc = nn.Linear(c[3], num_classes)
# initialize parameters
for m in self.modules():
if isinstance(m, nn.Conv2d):
nn.init.kaiming_normal_(m.weight)
elif isinstance(m, nn.BatchNorm2d):
nn.init.constant_(m.weight, 1.0)
nn.init.constant_(m.bias, 0.0)
elif isinstance(m, nn.Linear):
nn.init.kaiming_normal_(m.weight)
nn.init.constant_(m.bias, 0.0)
def forward(self, x):
out = self.conv(x)
out = self.block1(out)
out = self.block2(out)
out = self.block3(out)
out = self.relu(self.bn(out))
out = self.pool(out)
out = self.flatten(out)
return self.fc(out)
| 35.367089 | 119 | 0.57194 | 2,511 | 0.887279 | 0 | 0 | 0 | 0 | 0 | 0 | 53 | 0.018728 |
7f8384a311353de10a642c69e9df0c76f447b11c | 1,565 | py | Python | trisicell/ul/__init__.py | faridrashidi/trisicell | 4db89edd44c03ccb6c7d3477beff0079c3ff8035 | [
"BSD-3-Clause"
] | 2 | 2021-07-02T13:53:15.000Z | 2021-11-16T03:14:36.000Z | trisicell/ul/__init__.py | faridrashidi/trisicell | 4db89edd44c03ccb6c7d3477beff0079c3ff8035 | [
"BSD-3-Clause"
] | 58 | 2021-06-14T17:14:39.000Z | 2022-03-11T19:32:54.000Z | trisicell/ul/__init__.py | faridrashidi/trisicell | 4db89edd44c03ccb6c7d3477beff0079c3ff8035 | [
"BSD-3-Clause"
] | null | null | null | """Utils Module."""
from trisicell.ul._hclustering import (
dist_cosine_ignore_na,
dist_dendro,
dist_l1_ignore_na,
hclustering,
)
from trisicell.ul._packages import (
import_graph_tool,
import_graphviz,
import_gurobi,
import_mpi4py,
import_rpy2,
)
from trisicell.ul._trees import (
cells_rooted_at,
is_leaf,
muts_rooted_at,
partition_cells,
root_id,
to_cfmatrix,
to_mtree,
to_tree,
)
from trisicell.ul._utils import (
calc_score_tree,
cleanup,
count_flips,
dir_base,
dirbase,
executable,
get_file,
get_param,
infer_rates,
is_conflict_free,
is_conflict_free_gusfield,
log_flip,
log_input,
log_output,
mkdir,
remove,
split_mut,
stat,
timeit,
tmpdir,
tmpdirsys,
tmpfile,
tqdm_joblib,
with_timeout,
)
__all__ = (
dist_cosine_ignore_na,
dist_dendro,
dist_l1_ignore_na,
hclustering,
import_graph_tool,
import_graphviz,
import_gurobi,
import_mpi4py,
import_rpy2,
cells_rooted_at,
muts_rooted_at,
partition_cells,
root_id,
to_cfmatrix,
to_mtree,
to_tree,
calc_score_tree,
cleanup,
dir_base,
dirbase,
get_file,
get_param,
infer_rates,
is_conflict_free,
is_conflict_free_gusfield,
log_flip,
log_input,
log_output,
mkdir,
remove,
stat,
timeit,
tmpdir,
tmpdirsys,
tmpfile,
tqdm_joblib,
with_timeout,
is_leaf,
executable,
split_mut,
count_flips,
)
| 16.302083 | 39 | 0.651118 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 19 | 0.012141 |
7f83ab03f9f78c70886157722d2f935b1bea1759 | 2,137 | py | Python | utils/pktgen/sender.py | lilyhuegerich/No-hop | 2e82af6c8036312c35b3f2338c776863416ea043 | [
"MIT"
] | null | null | null | utils/pktgen/sender.py | lilyhuegerich/No-hop | 2e82af6c8036312c35b3f2338c776863416ea043 | [
"MIT"
] | 1 | 2021-02-15T17:29:03.000Z | 2021-02-15T17:29:03.000Z | utils/utils-backup/pktgen/sender.py | guiladkatz/NetAction | 436c5ac9dcf0e2064bcc9a2facca556828de6703 | [
"Apache-2.0"
] | 1 | 2021-04-18T18:24:59.000Z | 2021-04-18T18:24:59.000Z | #!/usr/bin/env python
import argparse, sys, socket, random, struct, time
from scapy.all import sendp, send, get_if_list, get_if_list, get_if_hwaddr, hexdump
from scapy.all import Packet
from scapy.all import Ether, IP, IPv6, UDP, TCP
sip_port=5060
def get_if():
iface=None
for i in get_if_list():
# find hx-eth0
if "eth0" in i:
iface=i;
break;
if not iface:
print "Cannot find eth0 interface"
exit(1)
return iface
def main():
parser = argparse.ArgumentParser()
parser.add_argument('-v', type=str, help="Specify using (4)IPv4/(6)IPv6.")
parser.add_argument('--ip', type=str, help="The destination IP address.")
parser.add_argument('--loop', type=int, help="Number of loop.", default=0)
parser.add_argument('--msg', type=str, help="The message which will send to dst.",default="Hello World")
parser.add_argument('--dport', type=int, help="TCP/UDP source port.", default=1234)
parser.add_argument('--sport', type=int, help="TCP/UDP destination port.", default=random.randint(49152,65535))
args = parser.parse_args()
addr = socket.gethostbyname(args.ip)
iface = get_if()
# start to pack
if args.v is "4":
print "sending on interface {} to IP addr {}".format(iface, str(addr))
for x in range(0, args.loop):
pkt = Ether(src=get_if_hwaddr(iface), dst='ff:ff:ff:ff:ff:ff')
pkt = pkt / IP(dst=addr) / TCP(dport=args.dport, sport=args.sport) / args.msg
# show
pkt.show2()
# send
sendp(pkt, iface=iface, verbose=False)
# sleep
time.sleep(1)
elif args.v is "6":
print "sending on interface {} to IPv6 addr {}".format(iface, str(addr))
for x in range(0, args.loop):
pkt = Ether(src=get_if_hwaddr(iface), dst='ff:ff:ff:ff:ff:ff')
pkt = pkt / IPv6(dst=addr) / TCP(dport=args.dport, sport=args.sport) / args.msg
# show
pkt.show2()
# send
sendp(pkt, iface=iface, verbose=False)
if __name__ == '__main__':
main()
| 35.032787 | 115 | 0.602714 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 472 | 0.22087 |
7f83ea7d1cc3220adf9ebca24b106652d1d5a82a | 2,898 | py | Python | lib/coloraide/spaces/hsl/__init__.py | EatBreatheCode/sublime_color_helper | 701d05807e51ce49088b1f0a8f55c4bf3845fa91 | [
"MIT"
] | null | null | null | lib/coloraide/spaces/hsl/__init__.py | EatBreatheCode/sublime_color_helper | 701d05807e51ce49088b1f0a8f55c4bf3845fa91 | [
"MIT"
] | null | null | null | lib/coloraide/spaces/hsl/__init__.py | EatBreatheCode/sublime_color_helper | 701d05807e51ce49088b1f0a8f55c4bf3845fa91 | [
"MIT"
] | null | null | null | """HSL class."""
from ...spaces import Space, Cylindrical
from ...cat import WHITES
from ...gamut.bounds import GamutBound, FLG_ANGLE, FLG_PERCENT
from ... import util
from ... import algebra as alg
from ...types import Vector
from typing import Tuple
def srgb_to_hsl(rgb: Vector) -> Vector:
"""SRGB to HSL."""
r, g, b = rgb
mx = max(rgb)
mn = min(rgb)
h = alg.NaN
s = 0.0
l = (mn + mx) / 2
c = mx - mn
if c != 0.0:
if mx == r:
h = (g - b) / c
elif mx == g:
h = (b - r) / c + 2.0
else:
h = (r - g) / c + 4.0
s = 0 if l == 0 or l == 1 else (mx - l) / min(l, 1 - l)
h *= 60.0
if s == 0:
h = alg.NaN
return [util.constrain_hue(h), s, l]
def hsl_to_srgb(hsl: Vector) -> Vector:
"""
HSL to RGB.
https://en.wikipedia.org/wiki/HSL_and_HSV#HSL_to_RGB_alternative
"""
h, s, l = hsl
h = h % 360
def f(n: int) -> float:
"""Calculate the channels."""
k = (n + h / 30) % 12
a = s * min(l, 1 - l)
return l - a * max(-1, min(k - 3, 9 - k, 1))
return [f(0), f(8), f(4)]
class HSL(Cylindrical, Space):
"""HSL class."""
BASE = "srgb"
NAME = "hsl"
SERIALIZE = ("--hsl",)
CHANNEL_NAMES = ("h", "s", "l")
CHANNEL_ALIASES = {
"hue": "h",
"saturation": "s",
"lightness": "l"
}
WHITE = WHITES['2deg']['D65']
GAMUT_CHECK = "srgb"
BOUNDS = (
GamutBound(0.0, 360.0, FLG_ANGLE),
GamutBound(0.0, 1.0, FLG_PERCENT),
GamutBound(0.0, 1.0, FLG_PERCENT)
)
@property
def h(self) -> float:
"""Hue channel."""
return self._coords[0]
@h.setter
def h(self, value: float) -> None:
"""Shift the hue."""
self._coords[0] = value
@property
def s(self) -> float:
"""Saturation channel."""
return self._coords[1]
@s.setter
def s(self, value: float) -> None:
"""Saturate or unsaturate the color by the given factor."""
self._coords[1] = value
@property
def l(self) -> float:
"""Lightness channel."""
return self._coords[2]
@l.setter
def l(self, value: float) -> None:
"""Set lightness channel."""
self._coords[2] = value
@classmethod
def null_adjust(cls, coords: Vector, alpha: float) -> Tuple[Vector, float]:
"""On color update."""
coords = alg.no_nans(coords)
if coords[1] == 0 or coords[2] in (0, 1):
coords[0] = alg.NaN
return coords, alg.no_nan(alpha)
@classmethod
def to_base(cls, coords: Vector) -> Vector:
"""To sRGB from HSL."""
return hsl_to_srgb(coords)
@classmethod
def from_base(cls, coords: Vector) -> Vector:
"""From sRGB to HSL."""
return srgb_to_hsl(coords)
| 21.626866 | 79 | 0.509317 | 1,730 | 0.596963 | 0 | 0 | 1,215 | 0.419255 | 0 | 0 | 499 | 0.172188 |
7f83fb54d3d89551adb5762f761b61b33bff3c08 | 950 | py | Python | maze/models.py | TerryHowe/pymaze | 139f15fb8e932c1cf1e63f5c5aee7895691e993f | [
"MIT"
] | 1 | 2020-12-14T04:01:08.000Z | 2020-12-14T04:01:08.000Z | maze/models.py | TerryHowe/pymaze | 139f15fb8e932c1cf1e63f5c5aee7895691e993f | [
"MIT"
] | null | null | null | maze/models.py | TerryHowe/pymaze | 139f15fb8e932c1cf1e63f5c5aee7895691e993f | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models
# Create your models here.
class Passage(models.Model):
DIRECTIONS = (
('N', 'North'),
('E', 'East'),
('S', 'South'),
('W', 'West'),
('U', 'Up'),
('D', 'Down'),
)
room_x = models.IntegerField()
room_y = models.IntegerField()
direction = models.CharField(max_length=1, choices=DIRECTIONS)
destination = models.OneToOneField('self',
null=True, blank=True,
on_delete=models.CASCADE)
@classmethod
def get_direction(cls, direction):
return dict(cls.DIRECTIONS).get(direction, 'Nowhere')
def __str__(self):
return(self.__repr__())
def __repr__(self):
dest = str(self.destination.id) if self.destination else 'None'
return('Passage(id=%d, room_x=%d, room_y=%d, direction=%s, destination=%s)' % (self.id, self.room_x, self.room_y, self.direction, dest))
class Meta:
unique_together = (('room_x', 'room_y', 'direction'),)
| 25.675676 | 138 | 0.676842 | 826 | 0.869474 | 0 | 0 | 104 | 0.109474 | 0 | 0 | 219 | 0.230526 |
7f85d28e2b17919468a9ea177eccdd701d33e549 | 3,181 | py | Python | tests/varints_test.py | dargueta/binobj | 00d91856678d7ecf17647a9b5cbff1810a39f275 | [
"BSD-3-Clause"
] | 2 | 2018-08-05T13:57:43.000Z | 2021-06-25T15:20:16.000Z | tests/varints_test.py | dargueta/binobj | 00d91856678d7ecf17647a9b5cbff1810a39f275 | [
"BSD-3-Clause"
] | 2 | 2020-10-26T11:11:17.000Z | 2021-02-24T20:08:10.000Z | tests/varints_test.py | dargueta/binobj | 00d91856678d7ecf17647a9b5cbff1810a39f275 | [
"BSD-3-Clause"
] | 1 | 2021-02-27T17:29:22.000Z | 2021-02-27T17:29:22.000Z | """Tests for the variable-length integers."""
import io
import pytest
from binobj import varints
@pytest.mark.parametrize(
"value,expected",
((0, b"\0"), (127, b"\x7f"), (128, b"\x81\x00"), (65535, b"\x83\xff\x7f")),
)
def test_encode_vlq_basic(value, expected):
assert varints.encode_integer_vlq(value) == expected
def test_encode_vlq_negative_crashes():
"""Passing a negative value to the VLQ encoder must always fail."""
with pytest.raises(ValueError):
varints.encode_integer_vlq(-1)
@pytest.mark.parametrize(
"serialized,expected",
((b"\0", 0), (b"\x7f", 127), (b"\x81\x00", 128), (b"\x83\xff\x7f", 65535)),
)
def test_decode_vlq_basic(serialized, expected):
buf = io.BytesIO(serialized)
assert varints.decode_integer_vlq(buf) == expected
assert buf.read() == b"", "Buffer wasn't emptied."
@pytest.mark.parametrize(
"value,expected",
((0, b"\0"), (1, b"\x01"), (-32767, b"\xc1\xff\x7f"), (895484, b"\xb6\xd3\x7c")),
)
def test_encode_compact(value, expected):
assert varints.encode_integer_compact(value) == expected
@pytest.mark.parametrize(
"serialized,expected",
(
(b"\0", 0),
(b"\x01", 1),
(b"\x41", -1),
(b"\xc1\xff\x7f", -32767),
(b"\xb6\xd3\x7c", 895484),
),
)
def test_decode_compact(serialized, expected):
buf = io.BytesIO(serialized)
assert varints.decode_integer_compact(buf) == expected
assert buf.read() == b"", "Buffer wasn't emptied."
@pytest.mark.parametrize(
"value,expected",
(
(0, b"\0"),
(127, b"\x7f"),
(128, b"\x80\x01"),
(7345004, b"\xec\xa6\xc0\x03"),
(0xB1ACC0FFEE2BAD, b"\xad\xd7\xb8\xff\x8f\x98\xeb\x58"),
),
)
def test_encode_uleb128(value, expected):
assert varints.encode_integer_uleb128(value) == expected
def test_encode_uleb128__negative_crashes():
with pytest.raises(ValueError):
assert varints.encode_integer_uleb128(-1)
@pytest.mark.parametrize(
"serialized, expected",
(
(b"\0", 0),
(b"\x7f", 127),
(b"\xd2\x85\xd8\xcc\x04", 1234567890),
(b"\xad\xd7\xb8\xff\x8f\x98\xeb\x58", 0xB1ACC0FFEE2BAD),
),
)
def test_decode_uleb128(serialized, expected):
buf = io.BytesIO(serialized)
assert varints.decode_integer_uleb128(buf) == expected
assert buf.read() == b"", "Buffer wasn't emptied"
SIGNED_LEB_VALUES = [
(0, b"\0"),
(63, b"\x3f"),
(64, b"\xc0\x00"),
(126, b"\xfe\x00"),
(127, b"\xff\x00"),
(128, b"\x80\x01"),
(-126, b"\x82\x7f"),
(-127, b"\x81\x7f"),
(-128, b"\x80\x7f"),
(0xB1ACC0FFEE2BAD, b"\xad\xd7\xb8\xff\x8f\x98\xeb\xd8\x00"),
(-0xB1ACC0FFEE2BAD, b"\xd3\xa8\xc7\x80\xf0\xe7\x94\xa7\x7f"),
]
@pytest.mark.parametrize("value,expected", SIGNED_LEB_VALUES)
def test_encode_signed_leb128(value, expected):
assert varints.encode_integer_leb128(value) == expected
@pytest.mark.parametrize("value,serialized", SIGNED_LEB_VALUES)
def test_decode_signed_leb128(value, serialized):
buf = io.BytesIO(serialized)
assert varints.decode_integer_leb128(buf) == value
assert buf.read() == b"", "Buffer wasn't emptied"
| 27.188034 | 85 | 0.636278 | 0 | 0 | 0 | 0 | 2,373 | 0.745992 | 0 | 0 | 845 | 0.26564 |
7f861eb33a0b220e3a89491dc68d3e6bfdddea0a | 725 | py | Python | src/settings/models.py | TolgaKara/prodai | a858d39226a072a2a52513d942dd046bb3787da8 | [
"Apache-2.0"
] | null | null | null | src/settings/models.py | TolgaKara/prodai | a858d39226a072a2a52513d942dd046bb3787da8 | [
"Apache-2.0"
] | 7 | 2020-10-09T09:24:28.000Z | 2022-03-12T00:14:07.000Z | src/settings/models.py | TolgaKara/prodai | a858d39226a072a2a52513d942dd046bb3787da8 | [
"Apache-2.0"
] | null | null | null | from django.db import models
from django.contrib.auth.models import User
# Create your models here.
class Setting(models.Model):
user_id = models.ForeignKey(User, on_delete=models.CASCADE)
class TimeTrackingSetting(models.Model):
user = models.ForeignKey(User, on_delete=models.CASCADE)
max_daily_work_time = models.TextField(max_length=50)
timetracking_name = models.CharField(max_length=100)
workingtime = models.IntegerField()
short_break = models.IntegerField()
long_break = models.IntegerField()
cycle = models.IntegerField()
class ActivitiesSetting(models.Model):
user = models.ForeignKey(User, on_delete=models.CASCADE)
block_activities = models.TextField(max_length=400)
| 31.521739 | 63 | 0.768276 | 616 | 0.849655 | 0 | 0 | 0 | 0 | 0 | 0 | 26 | 0.035862 |
7f873662ce9f9eb5dfd23f13cad81a3fb8b855d3 | 2,646 | py | Python | python/place_molex_conn.py | willdickson/roman_led_frame | 4cf54aa5ea15d9fa39ddaa1a27a83425fc449f36 | [
"CC-BY-4.0"
] | null | null | null | python/place_molex_conn.py | willdickson/roman_led_frame | 4cf54aa5ea15d9fa39ddaa1a27a83425fc449f36 | [
"CC-BY-4.0"
] | null | null | null | python/place_molex_conn.py | willdickson/roman_led_frame | 4cf54aa5ea15d9fa39ddaa1a27a83425fc449f36 | [
"CC-BY-4.0"
] | null | null | null | from __future__ import print_function
import os
import sys
import pcbnew
import numpy as np
import pprint
def inch_to_nanometer(value):
return (value*25.4)*1e6
def nanometer_to_inch(value):
return value/(25.4*1.e6)
def nm_to_mm(value):
return value*1.e-6
def mm_to_nm(value):
return value*1.e6
def print_module_info(module):
ref = module.GetReference()
pos = module.GetPosition()
x = nanometer_to_inch(pos.x)
y = nanometer_to_inch(pos.y)
angle = 0.1*module.GetOrientation()
print(' R: {}'.format(ref))
print(' X: {}'.format(x))
print(' Y: {}'.format(y))
print(' A: {}'.format(angle))
print()
def get_placement_data(param):
placement_data = {}
for i, ref in enumerate(param['ref_list']):
x = param['x_start'] + i*param['x_step']
y = param['y_value']
angle = param['angle']
placement_data[ref] = {'angle': angle, 'x': x, 'y': y}
return placement_data
def place_pcb_modules(filename, placement_data):
print()
print('loading pcb: {}'.format(filename))
print()
pcb = pcbnew.LoadBoard(filename)
print()
print('done')
print()
for module in pcb.GetModules():
ref_str = str(module.GetReference())
try:
data = placement_data[ref_str]
except KeyError:
continue
print_module_info(module)
# Move to new position
pos = module.GetPosition()
angle = 0.1*module.GetOrientation()
x_new = data['x']
y_new = data['y']
angle_new = data['angle']
pos.x = int(mm_to_nm(x_new))
pos.y = int(mm_to_nm(y_new))
module.SetPosition(pos)
module.SetOrientation(10.0*angle_new)
print_module_info(module)
pathname, basename = os.path.split(filename)
new_basename = 'mod_{}'.format(basename)
new_filename = os.path.join(pathname,new_basename)
pcb.Save(new_filename)
# ---------------------------------------------------------------------------------------
if __name__ == '__main__':
param = {
'ref_list': ['J{}'.format(i) for i in range(1,19)],
'y_value' : 56.0,
'x_start' : 50.0+39.5,
'x_step' : 13.0,
'angle' : 180.0,
}
placement_data = get_placement_data(param)
if 0:
print('led_data')
print()
pp = pprint.PrettyPrinter(indent=2)
pp.pprint(placement_data)
print()
print('modules')
print()
filename = sys.argv[1]
place_pcb_modules(filename, placement_data)
| 24.275229 | 89 | 0.560469 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 324 | 0.122449 |
7f879d970a7233907064466650bfa626b47f7750 | 2,199 | py | Python | RaspberryPi/appMasterKey.py | colindembovsky/iot-central-firmware | 29493b18b2d37090c5a071669370d4a907eb3f51 | [
"MIT"
] | 136 | 2018-05-08T08:54:22.000Z | 2022-02-17T21:39:41.000Z | RaspberryPi/appMasterKey.py | colindembovsky/iot-central-firmware | 29493b18b2d37090c5a071669370d4a907eb3f51 | [
"MIT"
] | 90 | 2018-05-08T22:50:26.000Z | 2020-11-04T16:11:44.000Z | RaspberryPi/appMasterKey.py | colindembovsky/iot-central-firmware | 29493b18b2d37090c5a071669370d4a907eb3f51 | [
"MIT"
] | 97 | 2018-05-07T20:55:28.000Z | 2022-02-17T21:39:43.000Z | # Copyright (c) Microsoft. All rights reserved.
# Licensed under the MIT license.
import sys
import iotc
from iotc import IOTConnectType, IOTLogLevel
from random import randint
import base64
import hmac
import hashlib
gIsMicroPython = ('implementation' in dir(sys)) and ('name' in dir(sys.implementation)) and (sys.implementation.name == 'micropython')
def computeKey(secret, regId):
global gIsMicroPython
try:
secret = base64.b64decode(secret)
except:
print("ERROR: broken base64 secret => `" + secret + "`")
sys.exit()
if gIsMicroPython == False:
return base64.b64encode(hmac.new(secret, msg=regId.encode('utf8'), digestmod=hashlib.sha256).digest())
else:
return base64.b64encode(hmac.new(secret, msg=regId.encode('utf8'), digestmod=hashlib._sha256.sha256).digest())
deviceId = "DEVICE_ID"
scopeId = "SCOPE_ID"
masterKey = "PRIMARY/SECONDARY master Key"
deviceKey = computeKey(masterKey, deviceId)
iotc = iotc.Device(scopeId, deviceKey, deviceId, IOTConnectType.IOTC_CONNECT_SYMM_KEY)
iotc.setLogLevel(IOTLogLevel.IOTC_LOGGING_API_ONLY)
gCanSend = False
gCounter = 0
def onconnect(info):
global gCanSend
print("- [onconnect] => status:" + str(info.getStatusCode()))
if info.getStatusCode() == 0:
if iotc.isConnected():
gCanSend = True
def onmessagesent(info):
print("\t- [onmessagesent] => " + str(info.getPayload()))
def oncommand(info):
print("- [oncommand] => " + info.getTag() + " => " + str(info.getPayload()))
def onsettingsupdated(info):
print("- [onsettingsupdated] => " + info.getTag() + " => " + info.getPayload())
iotc.on("ConnectionStatus", onconnect)
iotc.on("MessageSent", onmessagesent)
iotc.on("Command", oncommand)
iotc.on("SettingsUpdated", onsettingsupdated)
iotc.connect()
while iotc.isConnected():
iotc.doNext() # do the async work needed to be done for MQTT
if gCanSend == True:
if gCounter % 20 == 0:
gCounter = 0
print("Sending telemetry..")
iotc.sendTelemetry("{ \
\"temp\": " + str(randint(20, 45)) + ", \
\"accelerometerX\": " + str(randint(2, 15)) + ", \
\"accelerometerY\": " + str(randint(3, 9)) + ", \
\"accelerometerZ\": " + str(randint(1, 4)) + "}")
gCounter += 1
| 29.32 | 134 | 0.688495 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 545 | 0.24784 |
7f882238f2ac3dcd924d47d279ab3daa62b6851d | 5,842 | py | Python | genmod/annotate_models/variant_annotator.py | Varstation/genmod | 991a0fca36936b5dde49a95e8ea1d4336288c7c0 | [
"MIT"
] | null | null | null | genmod/annotate_models/variant_annotator.py | Varstation/genmod | 991a0fca36936b5dde49a95e8ea1d4336288c7c0 | [
"MIT"
] | null | null | null | genmod/annotate_models/variant_annotator.py | Varstation/genmod | 991a0fca36936b5dde49a95e8ea1d4336288c7c0 | [
"MIT"
] | 1 | 2020-07-05T19:06:32.000Z | 2020-07-05T19:06:32.000Z | #!/usr/bin/env python
# encoding: utf-8
"""
variant_consumer.py
Consumes batches of variants and annotates them. Each batch is a dictionary
with variant_id:s as keys and dictionaries with variant information.
The variants will get different annotations depending on input
Created by Måns Magnusson on 2013-03-01.
Copyright (c) 2013 __MyCompanyName__. All rights reserved.
"""
from __future__ import (division, print_function, absolute_import)
import logging
from multiprocessing import Process
from genmod.vcf_tools import get_genotypes
from . import (get_haploblocks, check_genetic_models, get_model_score,
make_print_version)
class VariantAnnotator(Process):
"""
Annotates variant in batches from the task queue and puts the result in
the results queue.
"""
def __init__(self, task_queue, results_queue, families, individuals,
phased=False, strict=False, vep=False,
reduced_penetrance_genes = set()):
"""
Initialize the VariantAnnotator
Consume variant batches from the task queue, annotate them with the
genetic inheritance patterns that they follow and put them in the
results queue.
Arguments:
task_queue (Queue)
results_queue (Queue)
families (dict)
individuals (list)
phased (bool)
strict (bool)
vep (bool)
reduced_penetrance_genes (set): Set of reduced penetrance genes
"""
Process.__init__(self)
self.logger = logging.getLogger(__name__)
self.proc_name = self.name
self.logger.info("Setting up variant_annotator: {0}".format(
self.proc_name))
self.logger.debug("Setting up task queue")
self.task_queue = task_queue
self.logger.debug("Setting up results queue")
self.results_queue = results_queue
# The families that should be annotated
self.families = families
self.logger.debug("Families found: {0}".format(self.families))
self.individuals = individuals
self.logger.debug("Individuals found: {0}".format(self.individuals))
# Settings for the annotation
self.phased = phased
self.logger.debug("Setting phased to {0}".format(self.phased))
self.strict = strict
self.logger.debug("Setting strict to {0}".format(self.strict))
self.vep = vep
self.logger.debug("Setting vep to {0}".format(self.vep))
self.reduced_penetrance = reduced_penetrance_genes
def run(self):
"""Run the consuming"""
self.logger.info('%s: Starting!' % self.proc_name)
# Check if there are any batches in the queue
while True:
# A batch is a dictionary with varints on the form {variant_id:variant_dict}
self.logger.debug("Getting task from task_queue")
variant_batch = self.task_queue.get()
if variant_batch is None:
self.logger.info('No more batches')
self.task_queue.task_done()
self.logger.info('{0}: Exiting'.format(self.proc_name))
break
# We are now going to check the genetic models for the variants in
# the batch
for variant_id in variant_batch:
variant = variant_batch[variant_id]
variant['genotypes'] = get_genotypes(variant, self.individuals)
# Check if the variant is in a gene with reduced penetrance
if variant.get('annotation', set()).intersection(self.reduced_penetrance):
self.logger.debug("Setting reduced_penetrance to True for"\
" variant: {0}".format(variant_id))
variant['reduced_penetrance'] = True
if len(variant_batch) > 1:
#If the variant are phased we want to find out which
#haploblocks they belong to for compounds
if self.phased:
self.logger.debug("Get haploblocks for variant batch")
variant_batch['haploblocks'] = get_haploblocks(
variant_batch, self.individuals
)
# We only need to check compound candidates if there is
# more than one variant in the batch
for variant_id in variant_batch:
self.logger.debug("Check compound candidates")
variant = variant_batch[variant_id]
variant['compound_candidate'] = False
if variant['annotation']:
variant['compound_candidate'] = True
self.logger.debug("Set compound_candidate to True")
# Check the genetic models for all variants in the batch
check_genetic_models(
variant_batch = variant_batch,
families = self.families,
phased = self.phased,
strict = self.strict,
)
# # Now we want to make versions of the variants that are ready for printing.
for variant_id in variant_batch:
variant = make_print_version(
variant=variant_batch[variant_id],
families=self.families
)
self.logger.debug("Putting variant in results_queue")
self.results_queue.put(variant)
self.task_queue.task_done()
return
| 38.183007 | 90 | 0.574974 | 5,171 | 0.884991 | 0 | 0 | 0 | 0 | 0 | 0 | 2,260 | 0.386788 |
7f883457983496df8e066229a171bec7587a4bd5 | 343 | py | Python | tests/context.py | SchluppiBobbz/DartsApp | 3538b90db30b4c59a03d49867df58b62d2e0a84a | [
"MIT"
] | null | null | null | tests/context.py | SchluppiBobbz/DartsApp | 3538b90db30b4c59a03d49867df58b62d2e0a84a | [
"MIT"
] | null | null | null | tests/context.py | SchluppiBobbz/DartsApp | 3538b90db30b4c59a03d49867df58b62d2e0a84a | [
"MIT"
] | null | null | null | import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
from dartsapp import game, player, darts_helper
from dartsapp.exceptions import BullseyeHasNoTriple, FieldDoesNotExist,\
NoPlayerRegistered, OptionsNotSet,\
ValueDoesNotExist | 42.875 | 82 | 0.661808 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0.011662 |
7f886aba201c2234da3db891c1dca0d083b400bb | 80,150 | py | Python | WebApps/OrgChartPortal/tests.py | yizongk/DOTAnalysis_Django | 688b59e668c6390b902d61a4aef546bd869d55ad | [
"Apache-2.0"
] | null | null | null | WebApps/OrgChartPortal/tests.py | yizongk/DOTAnalysis_Django | 688b59e668c6390b902d61a4aef546bd869d55ad | [
"Apache-2.0"
] | 1 | 2022-03-04T20:37:32.000Z | 2022-03-04T20:37:32.000Z | WebApps/OrgChartPortal/tests.py | yizongk/DOTAnalysis_Django | 688b59e668c6390b902d61a4aef546bd869d55ad | [
"Apache-2.0"
] | 1 | 2022-01-06T18:20:40.000Z | 2022-01-06T18:20:40.000Z | from .models import *
from datetime import datetime
from django.core.exceptions import ObjectDoesNotExist
import json
from WebAppsMain.settings import TEST_WINDOWS_USERNAME, TEST_PMS, TEST_SUPERVISOR_PMS, TEST_COMMISSIONER_PMS
from WebAppsMain.testing_utils import HttpPostTestCase, HttpGetTestCase
from django.db.models import Max, Q
import copy
### DO NOT RUN THIS IN PROD ENVIRONMENT
DEFAULT_WORK_UNIT = '1600'
def get_or_create_user(windows_username=TEST_WINDOWS_USERNAME):
"""create or get an user and return the user object. Defaults to TEST_WINDOWS_USERNAME as the user"""
try:
wu = TblWorkUnits.objects.using('OrgChartWrite').get(
wu__exact=DEFAULT_WORK_UNIT
)
pms = TblEmployees.objects.using('OrgChartWrite').get_or_create(
pms=TEST_PMS
)[0]
pms.lv='B'
pms.wu=wu
pms.save(using='OrgChartWrite')
user = TblUsers.objects.using('OrgChartWrite').get_or_create(
windows_username=windows_username
,pms=pms
)[0]
user.active = True
user.save(using='OrgChartWrite')
return user
except Exception as e:
raise ValueError(f"get_or_create_user(): {e}")
def grant_admin_status(windows_username=TEST_WINDOWS_USERNAME):
"""create or get an user and set it up with admin status and return the user object. Defaults to TEST_WINDOWS_USERNAME as the user"""
try:
user = get_or_create_user(windows_username=windows_username)
user.is_admin=True
user.active=True
user.save(using='OrgChartWrite')
return user
except Exception as e:
raise ValueError(f"grant_admin_status(): {e}")
def remove_admin_status(windows_username=TEST_WINDOWS_USERNAME):
"""removes the admin status of an user"""
try:
user = get_or_create_user(windows_username=windows_username)
user.is_admin=False
user.save(using='OrgChartWrite')
return user
except Exception as e:
raise ValueError(f"remove_admin_status(): {e}")
def grant_active_user_status(windows_username=TEST_WINDOWS_USERNAME):
"""Set user as active"""
try:
#TODO IMPLEMENT THIS WHEN NEW USER AND APP PERMISSION MANAGEMENT IS IN PLACE
...#TODO
except Exception as e:
raise ValueError(f"grant_active_user_status(): {e}")
def remove_active_user_status(windows_username=TEST_WINDOWS_USERNAME):
"""Set user as inactive"""
try:
#TODO IMPLEMENT THIS WHEN NEW USER AND APP PERMISSION MANAGEMENT IS IN PLACE
...#TODO
except Exception as e:
raise ValueError(f"remove_active_user_status(): {e}")
def set_up_permissions(windows_username=TEST_WINDOWS_USERNAME, work_units=[DEFAULT_WORK_UNIT]):
"""
set up permissions for a user. If user is admin, the permissions added will probably mean nothing.
@windows_username is self explanatory, just one name
@work_units should be a list of work units
"""
try:
for work_unit in work_units:
work_unit_obj = TblWorkUnits.objects.using('OrgChartWrite').get(
wu__exact=work_unit
,active=True
)
user_obj = get_or_create_user(windows_username=windows_username)
permission = TblPermissionsWorkUnit.objects.using('OrgChartWrite').get_or_create(
user_id=user_obj
,wu=work_unit_obj
)[0]
permission.save(using="OrgChartWrite")
except Exception as e:
raise ValueError(f"set_up_permissions(): {e}")
def tear_down_permissions(windows_username=TEST_WINDOWS_USERNAME):
"""remove all permissions for an user. If user is admin, the permissions removed will probably mean nothing."""
try:
permissions = TblPermissionsWorkUnit.objects.using('OrgChartWrite').filter(
user_id__windows_username__exact=windows_username
)
for each in permissions:
each.delete(using='OrgChartWrite')
except Exception as e:
raise ValueError(f"tear_down_permissions_for_user(): {e}")
def tear_down(windows_username=TEST_WINDOWS_USERNAME):
"""Removes admin status of @windows_username, and set all its permissions to inactive. Defaults to TEST_WINDOWS_USERNAME"""
try:
remove_admin_status(windows_username=windows_username)
tear_down_permissions(windows_username=windows_username)
except Exception as e:
raise ValueError(f"tear_down(): {e}")
def get_active_lv_list():
return ['B', 'C', 'K', 'M', 'N', 'Q', 'R', 'S']
def get_active_tblemployee_qryset():
"""
Return a queryset filtered to contain only records with active lv status plus a subset of 'L' leave status
Lv status 'L' is usually Inactive, but when it is due to 'B10' Leave Status Reason (Look up from payroll history), that employee is actually Active
"""
try:
latest_pay_date = TblPayrollHistory.objects.using('HRReportingRead').aggregate(Max('paydate'))['paydate__max']
active_L_pms_qryset = TblPayrollHistory.objects.using('HRReportingRead').filter(
lv__exact='L'
,lv_reason_code__exact='B10'
,paydate__exact=latest_pay_date
)
active_L_pms_list = [each['pms'] for each in list(active_L_pms_qryset.values('pms', 'lname', 'fname'))]
return TblEmployees.objects.using('OrgChartRead').filter(
Q( lv__in=get_active_lv_list() )
| Q( pms__in=active_L_pms_list )
)
except Exception as e:
raise ValueError(f"get_active_tblemployee_qryset(): {e}")
class TestViewPagesResponse(HttpGetTestCase):
@classmethod
def setUpClass(self):
tear_down()
set_up_permissions()
self.regular_views = [
'orgchartportal_home_view',
'orgchartportal_about_view',
'orgchartportal_contact_view',
'orgchartportal_empgrid_view',
'orgchartportal_orgchart_view',
'orgchartportal_how_to_use_view',
]
self.admin_views = [
'orgchartportal_admin_panel_view',
'orgchartportal_manage_users_view',
'orgchartportal_manage_permissions_view',
]
self.additional_context_requirements = [
{
'view' : 'orgchartportal_empgrid_view'
,'additional_context_keys' : [
'emp_entry_columns_json'
,'emp_entries_json'
,'supervisor_dropdown_list_json'
,'site_dropdown_list_json'
,'site_floor_dropdown_list_json'
,'site_type_dropdown_list_json'
]
,'qa_fct' : self.__assert_additional_context_qa_empgrid
}
## The below are admin views
,{
'view' : 'orgchartportal_manage_users_view'
,'additional_context_keys' : [
'ag_grid_col_def_json'
,'users_data_json'
]
,'qa_fct' : self.__assert_additional_context_qa_manage_users
}
,{
'view' : 'orgchartportal_manage_permissions_view'
,'additional_context_keys' : [
'ag_grid_col_def_json'
,'permissions_json'
,'user_list'
,'division_list'
,'wu_desc_list'
]
,'qa_fct' : self.__assert_additional_context_qa_manage_permissions
}
]
@classmethod
def tearDownClass(self):
tear_down()
def __assert_additional_context_qa_empgrid(self, response):
## Make sure the emp_entry_columns_json got all the required fields
emp_entry_columns_dict = json.loads(response.context_data['emp_entry_columns_json'])
from_api_fields = set(each['field'] for each in emp_entry_columns_dict)
required_fields = set([
'pms'
,'last_name'
,'first_name'
,'lv'
,'wu__wu'
,'civil_title'
,'office_title'
,'supervisor_pms__pms'
,'actual_site_id__site_id'
,'actual_floor_id__floor_id'
,'actual_site_type_id__site_type_id'])
if len(from_api_fields) > len(required_fields):
raise ValueError(f"orgchartportal_empgrid_view: context variable emp_entry_columns_json got back more fields than expected. These are the unexpected fields: {from_api_fields - required_fields}")
self.assertTrue(from_api_fields == required_fields
,f'orgchartportal_empgrid_view: context variable emp_entry_columns_json is missing some fields: {required_fields - from_api_fields}')
## Make sure emp_entries_json has only WUs that client has permission to
emp_entries_dict = json.loads(response.context_data['emp_entries_json'])
distinct_wu = set(each['wu__wu'] for each in emp_entries_dict)
user = get_or_create_user(windows_username=TEST_WINDOWS_USERNAME)
if user.is_admin:
permissions_wu = set(each.wu for each in TblWorkUnits.objects.using('OrgChartRead').all())
else:
permissions_wu = set(each.wu.wu for each in TblPermissionsWorkUnit.objects.using('OrgChartRead').filter(user_id__windows_username__exact=TEST_WINDOWS_USERNAME, is_active=True))
if len(permissions_wu) > len(distinct_wu):
missing_wus = permissions_wu - distinct_wu
if get_active_tblemployee_qryset().filter(wu__wu__in=missing_wus).count() == 0:
## the missing_wus actually doesn't exists in the active list of employees, no error here, remove it from list and moving on.
permissions_wu = permissions_wu - missing_wus
else:
raise ValueError(f"orgchartportal_empgrid_view: Did not get back any emp with these Work Units even though permission allows it: {missing_wus}")
self.assertTrue(distinct_wu == permissions_wu
,f'orgchartportal_empgrid_view: Got back an entry with work unit that "{TEST_WINDOWS_USERNAME}" does not have permission to. Here are the Work Units that it got, but should not have {distinct_wu - permissions_wu}"')
## Make sure a list of all active employees is returned in supervisor dropdown
supervisor_dropdown_dict = json.loads(response.context_data['supervisor_dropdown_list_json'])
count_of_all_api = len([each for each in supervisor_dropdown_dict])
count_of_all_base = len([each for each in get_active_tblemployee_qryset()])
self.assertTrue(count_of_all_base == count_of_all_api
,f'orgchartportal_empgrid_view: Did not get back a list of ALL active employees in the supervisor_dropdown_list_json context variable. base {count_of_all_base} vs api {count_of_all_api}')
## Make sure a list of all sites is returned in site dropdown
site_dropdown_dict = json.loads(response.context_data['site_dropdown_list_json'])
count_of_all_api = len([each for each in site_dropdown_dict])
count_of_all_base = len([each for each in TblDOTSites.objects.using('OrgChartRead').all()])
self.assertTrue(count_of_all_base == count_of_all_api
,f'orgchartportal_empgrid_view: Did not get back a list of ALL sites in the site_dropdown_list_json context variable. base {count_of_all_base} vs api {count_of_all_api}')
## Make sure a list of all site floors is returned in site floor dropdown
site_floor_dropdown_dict = json.loads(response.context_data['site_floor_dropdown_list_json'])
count_of_all_api = len([each for each in site_floor_dropdown_dict])
count_of_all_base = len([each for each in TblDOTSiteFloors.objects.using('OrgChartRead').all()])
self.assertTrue(count_of_all_base == count_of_all_api
,f'orgchartportal_empgrid_view: Did not get back a list of ALL site floors in the site_floor_dropdown_list_json context variable. base {count_of_all_base} vs api {count_of_all_api}')
## Make sure a list of all site type site floors is returned in site type dropdown
site_type_dropdown_dict = json.loads(response.context_data['site_type_dropdown_list_json'])
count_of_all_api = len([each for each in site_type_dropdown_dict])
count_of_all_base = len([each for each in TblDOTSiteFloorSiteTypes.objects.using('OrgChartRead').values(
'site_type_id__site_type_id'
,'site_type_id__site_type'
,'floor_id__floor_id'
,'floor_id__site_id'
).all()])
self.assertTrue(count_of_all_base == count_of_all_api
,f'orgchartportal_empgrid_view: Did not get back a list of ALL site floor + site types in the site_type_dropdown_list_json context variable. base {count_of_all_base} vs api {count_of_all_api}')
def __assert_additional_context_qa_manage_users(self, response):
## Make sure the ag_grid_col_def_json got all the required fields
ag_grid_col_def_dict = json.loads(response.context_data['ag_grid_col_def_json'])
from_api_fields = set(each['field'] for each in ag_grid_col_def_dict)
required_fields = set([
'pms'
,'windows_username'
,'is_admin'
,'active'
,None
])
if len(from_api_fields) > len(required_fields):
raise ValueError(f"orgchartportal_manage_users_view: context variable ag_grid_col_def_json got back more fields than expected. These are the unexpected fields: {from_api_fields - required_fields}")
self.assertTrue(from_api_fields == required_fields
,f'orgchartportal_manage_users_view: context variable ag_grid_col_def_json is missing some fields: {required_fields - from_api_fields}')
## Make sure users_data_json has ALL the user records, since this api is an admin api
users_data_json = json.loads(response.context_data['users_data_json'])
from_api_users_data = set(each['windows_username'] for each in users_data_json)
required_users_data = set(each.windows_username for each in TblUsers.objects.using('OrgChartRead').all())
self.assertEqual(from_api_users_data, required_users_data
,f"orgchartportal_manage_users_view: context variable users_data_json either has more data than allowed ({from_api_users_data - required_users_data}) or has less data than allowed ({required_users_data - from_api_users_data})")
def __assert_additional_context_qa_manage_permissions(self, response):
## Make sure the ag_grid_col_def_json got all the required fields
ag_grid_col_def_dict = json.loads(response.context_data['ag_grid_col_def_json'])
from_api_fields = set(each['field'] for each in ag_grid_col_def_dict)
required_fields = set([
'user_id__windows_username'
,'wu__wu'
,'wu__subdiv'
,'wu__wu_desc'
,None
])
if len(from_api_fields) > len(required_fields):
raise ValueError(f"orgchartportal_manage_permissions_view: context variable ag_grid_col_def_json got back more fields than expected. These are the unexpected fields: {from_api_fields - required_fields}")
self.assertTrue(from_api_fields == required_fields
,f'orgchartportal_manage_permissions_view: context variable ag_grid_col_def_json is missing some fields: {required_fields - from_api_fields}')
## Make sure permissions_json has ALL the permission records, since this api is an admin api
permissions_json = json.loads(response.context_data['permissions_json'])
from_api_permissions = set(f"{each['user_id__windows_username']}-{each['wu__wu']}" for each in permissions_json)
required_permissions = set(f"{each.user_id.windows_username}-{each.wu.wu}" for each in TblPermissionsWorkUnit.objects.using('OrgChartRead').all())
self.assertEqual(from_api_permissions, required_permissions
,f"orgchartportal_manage_permissions_view: context variable permissions_json either has more data than allowed ({from_api_permissions - required_permissions}) or has less data than allowed ({required_permissions - from_api_permissions})")
from_api_user_list = set(response.context_data['user_list'])
from_api_division_list = set(response.context_data['division_list'])
from_api_wu_desc_list = set(each['wu'] for each in response.context_data['wu_desc_list'])
required_user_list = set(each.windows_username for each in TblUsers.objects.using('OrgChartRead').all())
required_division_list = set(each.subdiv for each in TblWorkUnits.objects.using('OrgChartRead').filter(subdiv__isnull=False).distinct()) ## subidv not null filters out the WU 9999 On-Loan
required_wu_desc_list = set(each.wu for each in TblWorkUnits.objects.using('OrgChartRead').filter(subdiv__isnull=False)) ## subidv not null filters out the WU 9999 On-Loan
self.assertEqual(from_api_user_list, required_user_list
,f"orgchartportal_manage_permissions_view: context variable user_list either has more data than allowed ({from_api_user_list - required_user_list}) or has less data than allowed ({required_user_list - from_api_user_list})")
self.assertEqual(from_api_division_list, required_division_list
,f"orgchartportal_manage_permissions_view: context variable division_list either has more data than allowed ({from_api_division_list - required_division_list}) or has less data than allowed ({required_division_list - from_api_division_list})")
self.assertEqual(from_api_wu_desc_list, required_wu_desc_list
,f"orgchartportal_manage_permissions_view: context variable wu_desc_list either has more data than allowed ({from_api_wu_desc_list - required_wu_desc_list}) or has less data than allowed ({required_wu_desc_list - from_api_wu_desc_list})")
def test_views_response_status_200(self):
"""Test normal user"""
remove_admin_status()
self.assert_response_status_200()
"""Test admin user"""
grant_admin_status()
self.assert_response_status_200()
def test_views_response_user_admin_restriction(self):
#TODO IMPLEMENT THIS WHEN NEW USER AND APP PERMISSION MANAGEMENT IS IN PLACE
# """Test inactive user (Normal), should have NO access to regular or admin views"""
# remove_admin_status()
# remove_active_user_status()
# self.assert_inactive_user_no_access_on_normal_and_admin_view()
# """Test inactive user (Admin), should have NO access to regular or admin views"""
# grant_admin_status()
# remove_active_user_status()
# self.assert_inactive_user_no_access_on_normal_and_admin_view()
"""Test active user (Normal), should only have access to regular views"""
grant_active_user_status()
remove_admin_status()
self.assert_user_access_on_normal_and_admin_view()
"""Test active user (Admin), should have access to regular and admin views"""
grant_active_user_status()
grant_admin_status()
self.assert_admin_access_on_normal_and_admin_view()
def test_views_response_data(self):
"""
Test views to have the required GET request context data
Some views have additional context data, need to test for those here
"""
# Test normal user
remove_admin_status()
self.assert_additional_context_data(additional_requirements=self.additional_context_requirements)
# Test admin user
grant_admin_status()
self.assert_additional_context_data(additional_requirements=self.additional_context_requirements)
class TestAPIUpdateEmployeeData(HttpPostTestCase):
@classmethod
def setUpClass(self):
self.api_name = 'orgchartportal_update_employee_data'
self.post_response_json_key_specifications = []
tear_down()
set_up_permissions()
self.test_pms = TEST_PMS
self.__null_out_test_pms_obj(self)
## Sequence 0, should work anytime
self.valid_payload0 = [
{
'to_pms' : self.test_pms
,'column_name' : 'Supervisor'
,'new_value' : TEST_SUPERVISOR_PMS
}
,{
'to_pms' : self.test_pms
,'column_name' : 'Office Title'
,'new_value' : 'Hello World!'
}
,{
'to_pms' : self.test_pms
,'column_name' : 'Site'
,'new_value' : 'BK.H'
}
,{
'to_pms' : self.test_pms
,'column_name' : 'Floor'
,'new_value' : 'BK.H.1'
}
,{
'to_pms' : self.test_pms
,'column_name' : 'Site Type'
,'new_value' : '13'
}
]
## Sequence 1: Test auto null out of site floor and site type when site is changed
self.valid_payload1 = [
{
'to_pms' : self.test_pms
,'column_name' : 'Site'
,'new_value' : 'MN.H'
}
]
## Sequence 2: Test null out of site type when site floor is changed, must use a floor id that has multiple possible site type to it, so it doesn't trigger the API's auto populate of site type id if there's only one possible site type id
self.valid_payload2 = [
{
'to_pms' : self.test_pms
,'column_name' : 'Site'
,'new_value' : 'BK.D'
},{
'to_pms' : self.test_pms
,'column_name' : 'Floor'
,'new_value' : 'BK.D.2'
}
]
## Sequence 3: Test auto set site type when site floor has only one site type, like 'MN.H.9'
self.valid_payload3 = [
{
'to_pms' : self.test_pms
,'column_name' : 'Site'
,'new_value' : 'MN.H'
},{ ## Floor change to MN.H.9 should also set the actual stie type since there's only one valid floor site for that site floor. Make sure to check it in the '## Check if data was saved correctly and if tblChanges was updated correctly' section
'to_pms' : self.test_pms
,'column_name' : 'Floor'
,'new_value' : 'MN.H.9'
}
]
## Sequence 4: Test site type direct update, but first will need to reset site floor to another site floor with multiple site types
self.valid_payload4 = [
{
'to_pms' : self.test_pms
,'column_name' : 'Site'
,'new_value' : 'BK.B'
},{
'to_pms' : self.test_pms
,'column_name' : 'Floor'
,'new_value' : 'BK.B.1' ## Should accept 7 or 3 for site type
},{
'to_pms' : self.test_pms
,'column_name' : 'Site Type'
,'new_value' : '3'
}
,{
'to_pms' : self.test_pms
,'column_name' : 'Site Type'
,'new_value' : '7'
}
]
@classmethod
def tearDownClass(self):
self.__null_out_test_pms_obj(self)
tear_down()
def test_with_valid_data(self):
## Sequence 0
self.__null_out_test_pms_obj()
for payload in self.valid_payload0:
self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was saved correctly and if tblChanges was updated correctly
saved_object = TblEmployees.objects.using('OrgChartRead').get(
pms=self.test_pms
)
if payload['column_name'] == 'Supervisor':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=saved_object.supervisor_pms.pms)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='SupervisorPMS', proposed_new_value=payload['new_value'])
elif payload['column_name'] == 'Office Title':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=saved_object.office_title)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='OfficeTitle', proposed_new_value=payload['new_value'])
elif payload['column_name'] == 'Site':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=saved_object.actual_site_id.site_id)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteId', proposed_new_value=payload['new_value'])
elif payload['column_name'] == 'Floor':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=saved_object.actual_floor_id.floor_id)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualFloorId', proposed_new_value=payload['new_value'])
elif payload['column_name'] == 'Site Type':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=saved_object.actual_site_type_id.site_type_id)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteTypeId', proposed_new_value=payload['new_value'])
else:
raise ValueError(f"uncaught payload param value in test case (Remove it, or add a test case for it): '{payload['column_name']}'")
## Sequence 1 - Test auto null out of site floor and site type when site is changed
self.__null_out_test_pms_obj()
### Random value set to floor and site type to test the null out
test_emp = TblEmployees.objects.using('OrgChartWrite').get(
pms=self.test_pms
)
test_emp.actual_floor_id = TblDOTSiteFloors.objects.using('OrgChartWrite').get(floor_id__exact='BK.E.16')
test_emp.actual_site_type_id = TblDOTSiteTypes.objects.using('OrgChartWrite').get(site_type_id__exact='3')
test_emp.save(using='OrgChartWrite')
for payload in self.valid_payload1:
self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was saved correctly and if tblChanges was updated correctly
saved_object = TblEmployees.objects.using('OrgChartRead').get(
pms=self.test_pms
)
if payload['column_name'] == 'Site':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=saved_object.actual_site_id.site_id)
self.assert_post_key_update_equivalence(key_name='Change Site -> Auto Null out of Site Floor', key_value=None, db_value=saved_object.actual_floor_id)
self.assert_post_key_update_equivalence(key_name='Change Site -> Auto Null out of Site Type', key_value=None, db_value=saved_object.actual_site_type_id)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteId', proposed_new_value=payload['new_value'])
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualFloorId', proposed_new_value=None)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteTypeId', proposed_new_value=None)
else:
raise ValueError(f"uncaught payload param value in test case (Remove it, or add a test case for it): '{payload['column_name']}'")
## Sequence 2 - Test null out of site type when site floor is changed
self.__null_out_test_pms_obj()
### Random value set to site type to test the null out
test_emp = TblEmployees.objects.using('OrgChartWrite').get(
pms=self.test_pms
)
test_emp.actual_site_type_id = TblDOTSiteTypes.objects.using('OrgChartWrite').get(site_type_id__exact='3')
test_emp.save(using='OrgChartWrite')
for payload in self.valid_payload2:
self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was saved correctly and if tblChanges was updated correctly
saved_object = TblEmployees.objects.using('OrgChartRead').get(
pms=self.test_pms
)
if payload['column_name'] == 'Site':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=saved_object.actual_site_id.site_id)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteId', proposed_new_value=payload['new_value'])
elif payload['column_name'] == 'Floor':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=saved_object.actual_floor_id.floor_id)
self.assert_post_key_update_equivalence(key_name='Change Floor -> Auto Null out of Site Type', key_value=None, db_value=saved_object.actual_site_type_id)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualFloorId', proposed_new_value=payload['new_value'])
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteTypeId', proposed_new_value=None)
else:
raise ValueError(f"uncaught payload param value in test case (Remove it, or add a test case for it): '{payload['column_name']}'")
## Sequence 3 - Test auto set site type when site floor has only one site type, like 'MN.H.9'
self.__null_out_test_pms_obj()
for payload in self.valid_payload3:
self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was saved correctly and if tblChanges was updated correctly
saved_object = TblEmployees.objects.using('OrgChartRead').get(
pms=self.test_pms
)
if payload['column_name'] == 'Site':
## A change of Site should also null out site floor and site type. Check if data saved, and tracked in tblChanges
self.assert_post_key_update_equivalence(key_name=payload['column_name'] , key_value=payload['new_value'], db_value=saved_object.actual_site_id.site_id)
self.assert_post_key_update_equivalence(key_name='Change Site -> Auto Null out of Floor' , key_value=None , db_value=saved_object.actual_floor_id)
self.assert_post_key_update_equivalence(key_name='Change Site -> Auto Null out of Site Type', key_value=None , db_value=saved_object.actual_site_type_id)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteId' , proposed_new_value=payload['new_value'])
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualFloorId' , proposed_new_value=None)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteTypeId' , proposed_new_value=None)
elif payload['column_name'] == 'Floor':
## 'MN.H.9' should also have set site type id to 7
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'] , db_value=saved_object.actual_floor_id.floor_id)
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value='7' , db_value=saved_object.actual_site_type_id.site_type_id)
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualFloorId' , proposed_new_value=payload['new_value'])
self.__assert_delta_tracked_in_tblChanges(proposed_by_pms=self.test_pms, proposed_to_pms=payload['to_pms'], proposed_column_name='ActualSiteTypeId' , proposed_new_value='7')
else:
raise ValueError(f"uncaught payload param value in test case (Remove it, or add a test case for it): '{payload['column_name']}'")
def test_data_validation(self):
f"""Testing {self.api_name} data validation"""
payloads = self.valid_payload0
parameters = [
# Parameter name # Accepted type
"to_pms" # str -> int formatted str of len 7
,"column_name" # str -> must be one of the follow ['Supervisor', 'Office Title', 'Site', 'Floor', 'Site Type']
,"new_value" # str -> depends on the @column_name that was given
]
for payload in payloads:
for param_name in parameters:
if param_name == 'to_pms':
valid = [self.test_pms]
invalid = ['a', 1, 2.3, None, True, 'a123456', '12345678']
elif param_name == 'column_name':
valid = ['Supervisor', 'Office Title', 'Site', 'Floor', 'Site Type']
invalid = ['a', 1, 2.3, None, True]
elif param_name == 'new_value':
if payload['column_name'] == 'Supervisor':
valid = [TEST_SUPERVISOR_PMS]
invalid = ['a', 1, 2.3, None, True, 'a123456', '12345678']
elif payload['column_name'] == 'Office Title':
valid = ['Test Office Title Input']
invalid = [1, 2.3, None, True]
elif payload['column_name'] == 'Site':
valid = ['BK.H']
invalid = ['a', 1, 2.3, None, True]
elif payload['column_name'] == 'Floor':
valid = ['BK.H.1']
invalid = ['a', 1, 2.3, None, True]
elif payload['column_name'] == 'Site Type':
valid = ['13']
invalid = ['a', 1, 2.3, None, True]
else:
raise ValueError(f"test_data_validation(): parameter test not implemented: '{param_name}'. Please remove or implement it")
def special_param_good_cond(res_content):
if (
(res_content['post_success'] == True)
or (
res_content['post_success'] == False
and any([
'No change in data, no update needed.' in res_content['post_msg'] ## this error message in save() only gets called when it all pass data validation
]))):
return True
else:
return False
def special_param_good_cond_for_column_name(res_content):
if (
(res_content['post_success'] == True)
or (
res_content['post_success'] == False
and any([
'is not an editable column' not in res_content['post_msg'] ## for column_names, it will only fail data validation if error message is a specific one
]))):
return True
else:
return False
for data in valid:
if param_name == 'column_name':
self.assert_request_param_good(valid_payload=payload, testing_param_name=param_name, testing_data=data, param_is_good_fct=special_param_good_cond_for_column_name)
else:
self.assert_request_param_good(valid_payload=payload, testing_param_name=param_name, testing_data=data, param_is_good_fct=special_param_good_cond)
for data in invalid:
self.assert_request_param_bad(valid_payload=payload, testing_param_name=param_name, testing_data=data)
def __null_out_test_pms_obj(self):
test_pms_obj = TblEmployees.objects.using('OrgChartWrite').get(pms=self.test_pms)
test_pms_obj.supervisor_pms = None
test_pms_obj.office_title = None
test_pms_obj.actual_site_id = None
test_pms_obj.actual_floor_id = None
test_pms_obj.actual_site_type_id = None
test_pms_obj.save(using='OrgChartWrite')
def __get_latest_changes_obj_by(self, by_pms, to_pms, column_name):
try:
return TblChanges.objects.using('OrgChartRead').filter(
updated_by_pms__exact=by_pms
,updated_to_pms__exact=to_pms
,column_name__exact=column_name
).order_by('-updated_on').first()
except:
raise
def __assert_delta_tracked_in_tblChanges(self, proposed_by_pms, proposed_to_pms, proposed_column_name, proposed_new_value):
saved_change_obj = self.__get_latest_changes_obj_by(by_pms=proposed_by_pms, to_pms=proposed_to_pms, column_name=proposed_column_name)
self.assert_post_key_update_equivalence(key_name=f"tblChanges: track change of '{proposed_column_name}' failed", key_value=proposed_new_value, db_value=saved_change_obj.new_value)
class TestAPIGetClientWUPermissions(HttpPostTestCase):
@classmethod
def setUpClass(self):
self.api_name = 'orgchartportal_get_client_wu_permissions_list'
self.post_response_json_key_specifications = [
{'name': 'wu_permissions', 'null': True}
]
tear_down()
set_up_permissions()
self.client_usr_obj = get_or_create_user()
self.valid_payload = {}
@classmethod
def tearDownClass(self):
tear_down()
def test_with_valid_data(self):
remove_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was queried correctly
wu_permissions_query = TblPermissionsWorkUnit.objects.using('OrgChartRead').filter(
user_id__windows_username=self.client_usr_obj.windows_username
,user_id__active=True
,is_active=True
)
wu_permissions_required = set(each.wu.wu for each in wu_permissions_query)
self.assert_post_key_lookup_equivalence(key_name='wu_permissions', key_value=set(each['wu__wu'] for each in response_content['post_data']['wu_permissions']), db_value=wu_permissions_required)
grant_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## For admins, the post_success must be true, and post_msg should be "User is Admin"
self.assert_post_key_lookup_equivalence(key_name='post_msg', key_value=response_content['post_msg'], db_value="User is Admin")
def test_data_validation(self):
pass ## This api doesn't take in any params
class TestAPIGetClientTeammates(HttpPostTestCase):
@classmethod
def setUpClass(self):
self.api_name = 'orgchartportal_get_client_teammates_list'
self.post_response_json_key_specifications = [
{'name': 'teammates', 'null': True}
]
tear_down()
set_up_permissions()
self.client_usr_obj = get_or_create_user()
self.valid_payload = {}
@classmethod
def tearDownClass(self):
tear_down()
def test_with_valid_data(self):
remove_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was queried correctly
wu_permissions_query = TblPermissionsWorkUnit.objects.using('OrgChartRead').filter(
user_id__windows_username=self.client_usr_obj.windows_username
,user_id__active=True
)
wu_permissions_list = wu_permissions_query.values('wu__wu')
teammates_query = TblPermissionsWorkUnit.objects.using('OrgChartRead').filter(
wu__wu__in=wu_permissions_list
,user_id__active=True
,is_active=True
)
teammates_required = set(each.user_id.pms.pms for each in teammates_query)
self.assert_post_key_lookup_equivalence(key_name='teammates', key_value=sorted(set(each['user_id__pms__pms'] for each in response_content['post_data']['teammates'])), db_value=sorted(teammates_required))
grant_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## For admins, the post_success must be true, and post_msg should be "User is Admin"
self.assert_post_key_lookup_equivalence(key_name='post_msg', key_value=response_content['post_msg'], db_value="User is Admin")
def test_data_validation(self):
pass ## This api doesn't take in any params
class TestAPIGetEmpGridStats(HttpPostTestCase):
@classmethod
def setUpClass(self):
self.api_name = 'orgchartportal_get_emp_grid_stats'
self.post_response_json_key_specifications = [
{'name': 'supervisor_completed' , 'null': True}
,{'name': 'office_title_completed' , 'null': True}
,{'name': 'list_last_updated_on_est' , 'null': True}
,{'name': 'list_last_updated_by' , 'null': True}
,{'name': 'inactive_supervisor_list' , 'null': True}
,{'name': 'empty_or_invalid_floor_combo_list' , 'null': True}
,{'name': 'empty_or_invalid_site_type_combo_list' , 'null': True}
]
tear_down()
set_up_permissions()
self.valid_payload = {}
@classmethod
def tearDownClass(self):
tear_down()
def __assert_stats_types(self, response_content):
self.assert_post_key_lookup_equivalence(key_name='supervisor_completed', key_value=type(response_content['post_data']['supervisor_completed']), db_value=type(99.99))
self.assert_post_key_lookup_equivalence(key_name='office_title_completed', key_value=type(response_content['post_data']['office_title_completed']), db_value=type(99.99))
try:
test = datetime.strptime(response_content['post_data']['list_last_updated_on_est'], "%m/%d/%Y %I:%M:%S %p")
except Exception as e:
self.assertTrue(False
,f"{response_content['post_data']['list_last_updated_on_est']} is not a valid datetime string in the format of '%m/%d/%Y %I:%M:%S %p': {e}")
self.assert_post_key_lookup_equivalence(key_name='list_last_updated_by', key_value=type(response_content['post_data']['list_last_updated_by']), db_value=type(''))
self.assert_post_key_lookup_equivalence(key_name='inactive_supervisor_list', key_value=type(response_content['post_data']['inactive_supervisor_list']), db_value=type([]))
self.assert_post_key_lookup_equivalence(key_name='empty_or_invalid_floor_combo_list', key_value=type(response_content['post_data']['empty_or_invalid_floor_combo_list']), db_value=type([]))
self.assert_post_key_lookup_equivalence(key_name='empty_or_invalid_site_type_combo_list', key_value=type(response_content['post_data']['empty_or_invalid_site_type_combo_list']), db_value=type([]))
def test_with_valid_data(self):
remove_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data type was returned correctly. No data accuracy check here at the moment.
self.__assert_stats_types(response_content=response_content)
grant_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## For admins, the post_success must be true, and post_msg should be "User is Admin"
self.__assert_stats_types(response_content=response_content)
def test_data_validation(self):
pass ## This api doesn't take in any params
class TestAPIEmpGridGetCsvExport(HttpPostTestCase):
@classmethod
def setUpClass(self):
self.api_name = 'orgchartportal_emp_grid_get_csv_export'
self.post_response_json_key_specifications = [
{'name': 'csv_bytes', 'null': False}
]
tear_down()
set_up_permissions()
self.client_usr_obj = get_or_create_user()
self.valid_payload = {}
@classmethod
def tearDownClass(self):
tear_down()
def test_with_valid_data(self):
remove_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## Check any byte data returned
self.assertTrue(response_content['post_data']['csv_bytes'] is not None
,f"response_content['post_data']['csv_bytes'] should not be null, it should return some byte data in string form")
grant_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## For admins, the post_success must be true, and post_msg should be "User is Admin"
self.assertTrue(response_content['post_data']['csv_bytes'] is not None
,f"response_content['post_data']['csv_bytes'] should not be null, it should return some byte data in string form")
def test_data_validation(self):
pass ## This api doesn't take in any params
class TestAPIGetCommissionerPMS(HttpPostTestCase):
@classmethod
def setUpClass(self):
self.api_name = 'orgchartportal_get_commissioner_pms'
self.test_pms = TEST_COMMISSIONER_PMS
self.valid_payload = {}
self.post_response_json_key_specifications = [
{'name': 'dot_commissioner_pms', 'null': False}
]
tear_down()
set_up_permissions()
@classmethod
def tearDownClass(self):
tear_down()
def test_with_valid_data(self):
remove_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## For normal user, a 7 digit string should be returned as the commissioner pms
self.assert_post_key_lookup_equivalence(key_name='dot_commissioner_pms', key_value=type(response_content['post_data']['dot_commissioner_pms']), db_value=type(''))
self.assertTrue(len(response_content['post_data']['dot_commissioner_pms']) == 7
,f"response_content['post_data']['dot_commissioner_pms'] is not len 7")
try:
test = int(response_content['post_data']['dot_commissioner_pms'])
except Exception as e:
self.assertTrue(False
,f"response_content['post_data']['dot_commissioner_pms'] is not all digits: {e}")
grant_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## For admin, a 7 digit string should be returned as the commissioner pms
self.assert_post_key_lookup_equivalence(key_name='dot_commissioner_pms', key_value=type(response_content['post_data']['dot_commissioner_pms']), db_value=type(''))
self.assertTrue(len(response_content['post_data']['dot_commissioner_pms']) == 7
,f"response_content['post_data']['dot_commissioner_pms'] is not len 7")
try:
test = int(response_content['post_data']['dot_commissioner_pms'])
except Exception as e:
self.assertTrue(False
,f"response_content['post_data']['dot_commissioner_pms'] is not all digits: {e}")
def test_data_validation(self):
pass ## This api doesn't take in any params
class TestAPIOrgChartGetEmpCsv(HttpPostTestCase):
@classmethod
def setUpClass(self):
self.api_name = 'orgchartportal_org_chart_get_emp_csv'
self.test_pms = TEST_COMMISSIONER_PMS
self.valid_payload = {
'root_pms': self.test_pms
}
self.post_response_json_key_specifications = [
{'name': 'emp_csv', 'null': False}
]
tear_down()
set_up_permissions()
@classmethod
def tearDownClass(self):
tear_down()
def test_with_valid_data(self):
remove_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## For admins, the post_success must be true, and post_msg should be "User is Admin"
self.assertTrue(response_content['post_data']['emp_csv'] is not None
,f"For a normal user, response_content['post_data']['emp_csv'] should not be null, it should return some byte data in string form")
grant_admin_status()
payload = self.valid_payload
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## For admins, the post_success must be true, and post_msg should be "User is Admin"
self.assertTrue(response_content['post_data']['emp_csv'] is not None
,f"For an admin, response_content['post_data']['emp_csv'] should not be null, it should return some byte data in string form")
def test_data_validation(self):
payload = self.valid_payload
parameters = [
# Parameter name # Accepted type
"root_pms" # str -> string of len 7 with all digits
]
for param_name in parameters:
if param_name == 'root_pms':
valid = [self.test_pms]
invalid = ['a', 1, 2.3, False, None]
else:
raise ValueError(f"test_data_validation(): parameter test not implemented: '{param_name}'. Please remove or implement it")
for data in valid:
self.assert_request_param_good(valid_payload=payload, testing_param_name=param_name, testing_data=data)
for data in invalid:
self.assert_request_param_bad(valid_payload=payload, testing_param_name=param_name, testing_data=data)
class TestAPIAddUser(HttpPostTestCase):
@classmethod
def setUpClass(self):
tear_down()
self.user_obj = grant_admin_status()
self.api_name = 'orgchartportal_add_user'
self.post_response_json_key_specifications = [
{'name': 'windows_username' , 'null': False}
,{'name': 'pms' , 'null': False}
,{'name': 'is_admin' , 'null': False}
,{'name': 'active' , 'null': False}
]
self.valid_username = 'SomeTestUsername'
self.valid_pms = TEST_COMMISSIONER_PMS
self.valid_payloads = [
{
'windows_username' : self.valid_username,
'pms' : self.valid_pms,
'is_admin' : 'False',
}
,{
'windows_username' : self.valid_username,
'pms' : self.valid_pms,
'is_admin' : 'True',
}
]
@classmethod
def tearDownClass(self):
tear_down()
self.remove_test_user_if_exists(self)
def test_api_accept_only_admins(self):
remove_admin_status()
payload = self.valid_payloads[0]
content = self.post_and_get_json_response(payload)
self.assertTrue((content['post_success']==False) and ("not an admin" in content['post_msg']),
f"api should have detected that user is not an admin and fail\n{content['post_msg']}")
def remove_test_user_if_exists(self):
try:
new_user = TblUsers.objects.using('OrgChartWrite').get(windows_username__exact=self.valid_username, pms__exact=self.valid_pms)
except:
...#Do nothing
else:
new_user.delete(using='OrgChartWrite')
def test_with_valid_data(self):
grant_admin_status()
for payload in self.valid_payloads:
self.remove_test_user_if_exists()
self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was saved correctly
saved_object = TblUsers.objects.using('OrgChartWrite').get(windows_username__exact=self.valid_username)
self.assert_post_key_update_equivalence(key_name='windows_username' , key_value=payload['windows_username'] , db_value=saved_object.windows_username)
self.assert_post_key_update_equivalence(key_name='pms' , key_value=payload['pms'] , db_value=saved_object.pms)
self.assert_post_key_update_equivalence(key_name='is_admin' , key_value=payload['is_admin'] , db_value=str(saved_object.is_admin))
self.assertTrue(str(saved_object.active)=='True'
,f"the newly added user {saved_object.windows_username}'s active field is not True, it must be True. Current value: '{str(saved_object.active)}'")
def test_data_validation(self):
grant_admin_status()
payload = self.valid_payloads[0]
parameters = [
# Parameter name # Accepted type
"windows_username" # str -> username
,"pms" # str -> 7 len, all digits
,"is_admin" # str -> 'True' or 'False'
]
for param_name in parameters:
if param_name == 'windows_username':
valid = [self.valid_username]
invalid = [1, 2.3, False, None]
elif param_name == 'pms':
valid = [self.valid_pms]
invalid = ['a', 1, 2.3, '-1', '-1.2', '11.567', '2.2', '4.45', None, False, 'a0', '12345678', '123456']
elif param_name == 'is_admin':
valid = ['False', 'True']
invalid = ['a', 1, 2.3, '-1', '-1.2', '11.567', '2.2', '4.45', None, False]
else:
raise ValueError(f"test_data_validation(): parameter test not implemented: '{param_name}'. Please remove or implement it")
for data in valid:
self.remove_test_user_if_exists()
self.assert_request_param_good(valid_payload=payload, testing_param_name=param_name, testing_data=data)
for data in invalid:
self.remove_test_user_if_exists()
self.assert_request_param_bad(valid_payload=payload, testing_param_name=param_name, testing_data=data)
class TestAPIUpdateUser(HttpPostTestCase):
@classmethod
def setUpClass(self):
tear_down()
self.user_obj = grant_admin_status()
self.api_name = 'orgchartportal_update_user'
self.post_response_json_key_specifications = [
{'name': 'to_windows_username' , 'null': False}
,{'name': 'column_name' , 'null': False}
,{'name': 'new_value' , 'null': False}
]
self.valid_payloads = [
{
'to_windows_username' : self.user_obj.windows_username,
'column_name' : 'Is Admin',
'new_value' : 'True',
}
,{
'to_windows_username' : self.user_obj.windows_username,
'column_name' : 'Is Admin',
'new_value' : 'False',
}
,{
'to_windows_username' : self.user_obj.windows_username,
'column_name' : 'Active',
'new_value' : 'True',
}
,{
'to_windows_username' : self.user_obj.windows_username,
'column_name' : 'Active',
'new_value' : 'False',
}
]
@classmethod
def tearDownClass(self):
tear_down()
def test_api_accept_only_admins(self):
remove_admin_status()
payload = self.valid_payloads[0]
content = self.post_and_get_json_response(payload)
self.assertTrue((content['post_success']==False) and ("not an admin" in content['post_msg']),
f"api should have detected that user is not an admin and fail\n{content['post_msg']}")
def test_with_valid_data(self):
for payload in self.valid_payloads:
grant_admin_status()
self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was saved correctly
saved_object = TblUsers.objects.using('OrgChartWrite').get(windows_username__exact=self.user_obj.windows_username)
if payload['column_name'] == 'Is Admin':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=str(saved_object.is_admin))
elif payload['column_name'] == 'Active':
self.assert_post_key_update_equivalence(key_name=payload['column_name'], key_value=payload['new_value'], db_value=str(saved_object.active))
else:
raise ValueError(f"{payload['column']} is not recognized as a valid column value in the payload")
def test_data_validation(self):
payload = self.valid_payloads[0]
parameters = [
# Parameter name # Accepted type
'to_windows_username' # str -> windows username
,'column_name' # str -> 'Is Admin' or 'Active' only
,'new_value' # str -> 'True' or 'False' only
]
for param_name in parameters:
if param_name == 'to_windows_username':
valid = [self.user_obj.windows_username]
invalid = [1, 2.3, False, None, 'sdfds']
elif param_name == 'column_name':
valid = ['Is Admin', 'Active']
invalid = [1, 2.3, False, None, 'sdfds']
elif param_name == 'new_value':
valid = ['False', 'True']
invalid = ['a', 1, 2.3, None, False]
else:
raise ValueError(f"test_data_validation(): parameter test not implemented: '{param_name}'. Please remove or implement it")
for data in valid:
grant_admin_status()
self.assert_request_param_good(valid_payload=payload, testing_param_name=param_name, testing_data=data)
for data in invalid:
grant_admin_status()
self.assert_request_param_bad(valid_payload=payload, testing_param_name=param_name, testing_data=data)
class TestAPIDeleteUser(HttpPostTestCase):
@classmethod
def setUpClass(self):
tear_down()
self.api_name = 'orgchartportal_delete_user'
self.post_response_json_key_specifications = [
{'name': 'windows_username' , 'null': False}
]
self.valid_username = 'some_random_name'
self.valid_pms = TEST_COMMISSIONER_PMS
self.valid_payloads = [
{
'windows_username': self.valid_username,
}
]
@classmethod
def tearDownClass(self):
tear_down()
try:
test_user = TblUsers.objects.using('OrgChartWrite').get(windows_username__exact=self.valid_username)
except ObjectDoesNotExist as e:
... ## Good, do nothing
except:
raise
else:
test_user.delete(using='OrgChartWrite')
def test_api_accept_only_admins(self):
remove_admin_status()
payload = self.valid_payloads[0]
content = self.post_and_get_json_response(payload)
self.assertTrue((content['post_success']==False) and ("not an admin" in content['post_msg']),
f"api should have detected that user is not an admin and fail\n{content['post_msg']}")
def add_test_user_if_not_exists(self):
test_user = TblUsers.objects.using('OrgChartWrite').get_or_create(
windows_username=self.valid_username
,pms=TblEmployees.objects.using('OrgChartWrite').get(pms__exact=self.valid_pms)
)[0]
test_user.save(using='OrgChartWrite')
def test_with_valid_data(self):
for payload in self.valid_payloads:
grant_admin_status()
self.add_test_user_if_not_exists()
response_content = self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was deleted correctly
try:
saved_object = TblUsers.objects.using('OrgChartWrite').get(windows_username__exact=self.valid_username)
except ObjectDoesNotExist as e:
... ## Good, do nothing
except Exception as e:
raise ValueError(f"test_with_valid_data(): {e}")
else:
self.assertTrue(False, f"{saved_object.windows_username} still exists in the database, unable to delete user")
## Check that a string was returned for windows_username
self.assert_post_key_lookup_equivalence(key_name='windows_username', key_value=response_content['post_data']['windows_username'], db_value=payload['windows_username'])
def test_data_validation(self):
payload = self.valid_payloads[0]
parameters = [
# Parameter name # Accepted type
"windows_username" # str -> windows username
]
for param_name in parameters:
if param_name == 'windows_username':
valid = [self.valid_username]
invalid = [1, 2.3, False, None, 'whateverhappened?']
else:
raise ValueError(f"test_data_validation(): parameter test not implemented: '{param_name}'. Please remove or implement it")
for data in valid:
grant_admin_status()
self.add_test_user_if_not_exists()
self.assert_request_param_good(valid_payload=payload, testing_param_name=param_name, testing_data=data)
for data in invalid:
grant_admin_status()
self.add_test_user_if_not_exists()
self.assert_request_param_bad(valid_payload=payload, testing_param_name=param_name, testing_data=data)
class TestAPIAddUserPermission(HttpPostTestCase):
@classmethod
def setUpClass(self):
tear_down()
self.api_name = 'orgchartportal_add_user_permission'
self.valid_username = TEST_WINDOWS_USERNAME
self.valid_add_by_division_identifier = 'Legal'
self.valid_add_by_wu_identifier = '1120' #Traffic Ops
self.post_response_json_key_specifications = [
{'name': 'windows_username' , 'null': False}
,{'name': 'perm_identifier' , 'null': False}
,{'name': 'wu_added_list' , 'null': False}
]
self.valid_payloads = [
{
'windows_username' : self.valid_username,
'perm_add_by' : 'division',
'perm_identifier' : self.valid_add_by_division_identifier
}
,{
'windows_username' : self.valid_username,
'perm_add_by' : 'wu',
'perm_identifier' : self.valid_add_by_wu_identifier
}
]
@classmethod
def tearDownClass(self):
tear_down()
def test_api_accept_only_admins(self):
remove_admin_status()
payload = self.valid_payloads[0]
content = self.post_and_get_json_response(payload)
self.assertTrue((content['post_success']==False) and ("not an admin" in content['post_msg']),
f"api should have detected that user is not an admin and fail\n{content['post_msg']}")
def test_with_valid_data(self):
grant_admin_status()
for payload in self.valid_payloads:
self.__remove_any_permissions_added_in_this_test() ## Need to remove additional permissions that is added in this api
self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was saved correctly
if payload['perm_add_by'] == 'wu':
saved_object = TblPermissionsWorkUnit.objects.using('OrgChartRead').get(
user_id__windows_username__exact = payload['windows_username']
,wu__wu__exact = payload['perm_identifier']
)
self.assert_post_key_update_equivalence(key_name='is_active', key_value=True, db_value=saved_object.is_active)
elif payload['perm_add_by'] == 'division':
saved_objects = TblPermissionsWorkUnit.objects.using('OrgChartRead').filter(
user_id__windows_username__exact = payload['windows_username']
,wu__subdiv__exact = payload['perm_identifier']
)
saved_wu_permissions = set(each.wu.wu for each in saved_objects)
required_wus_objects = TblWorkUnits.objects.using('OrgChartRead').filter(
subdiv__exact=payload['perm_identifier']
)
required_wus = set(each.wu for each in required_wus_objects)
self.assertTrue(sorted(required_wus)==sorted(saved_wu_permissions)
,f"Permissions added did not match request. In request but not in db [{required_wus-saved_wu_permissions}], and added to db but not in request [{saved_wu_permissions-required_wus}]")
else:
self.assertTrue(False
,f"payload['perm_add_by'] value '{payload['perm_add_by']}' not implemented in test. Wrong data or please add implementation")
def test_data_validation(self):
grant_admin_status()
payload = self.valid_payloads[0]
parameters = [
# Parameter name # Accepted type
'windows_username' # str -> username
,'perm_add_by' # str -> Either 'division' or 'wu'
,'perm_identifier' # str -> a subdiv name, or a wu
]
for param_name in parameters:
if param_name == 'windows_username':
valid = [self.valid_username]
invalid = [1, 2.3, False, None]
elif param_name == 'perm_add_by':
valid = ['division', 'wu']
invalid = ['a', 1, 2.3, '-1', '-1.2', '11.567', '2.2', '4.45', None, False, '']
elif param_name == 'perm_identifier':
valid = [self.valid_add_by_division_identifier, self.valid_add_by_wu_identifier]
invalid = ['a', 1, 2.3, '-1', '-1.2', '11.567', '2.2', '4.45', None, False, '']
else:
raise ValueError(f"test_data_validation(): parameter test not implemented: '{param_name}'. Please remove or implement it")
for data in valid:
if param_name == 'perm_add_by' and data == 'division':
## for division, the perm_id must be a sub div name
payload = copy.deepcopy(payload)
payload['perm_identifier'] = self.valid_add_by_division_identifier
if param_name == 'perm_add_by' and data == 'wu':
## for wu, the perm_id must be a wu
payload = copy.deepcopy(payload)
payload['perm_identifier'] = self.valid_add_by_wu_identifier
if param_name == 'perm_identifier' and data == self.valid_add_by_division_identifier:
## for perm_id with division, the add_by must be 'division'
payload = copy.deepcopy(payload)
payload['perm_add_by'] = 'division'
if param_name == 'perm_identifier' and data == self.valid_add_by_wu_identifier:
## for perm_id with wu, the add_by must be 'wu'
payload = copy.deepcopy(payload)
payload['perm_add_by'] = 'wu'
self.__remove_any_permissions_added_in_this_test() ## Need to remove additional permissions that is added in this api
self.assert_request_param_good(valid_payload=payload, testing_param_name=param_name, testing_data=data)
for data in invalid:
self.__remove_any_permissions_added_in_this_test() ## Need to remove additional permissions that is added in this api
self.assert_request_param_bad(valid_payload=payload, testing_param_name=param_name, testing_data=data)
def __remove_any_permissions_added_in_this_test(self):
permissions = TblPermissionsWorkUnit.objects.using('OrgChartWrite').filter(
Q(user_id__windows_username__exact=self.valid_username)
& (
Q(wu__subdiv__exact=self.valid_add_by_division_identifier)
| Q(wu__wu__exact=self.valid_add_by_wu_identifier)
)
)
for each in permissions:
each.delete(using='OrgChartWrite')
class TestAPIDeleteUserPermission(HttpPostTestCase):
@classmethod
def setUpClass(self):
tear_down()
self.api_name = 'orgchartportal_delete_user_permission'
self.valid_username = TEST_WINDOWS_USERNAME
self.valid_add_by_division_identifier = 'Legal'
self.valid_add_by_wu_identifier = '1120' #Traffic Ops
self.post_response_json_key_specifications = [
{'name': 'windows_username' , 'null': False}
,{'name': 'perm_identifier' , 'null': False}
]
self.valid_payloads = [
{
'windows_username' : self.valid_username,
'perm_delete_by' : 'division',
'perm_identifier' : self.valid_add_by_division_identifier,
}
,{
'windows_username' : self.valid_username,
'perm_delete_by' : 'wu',
'perm_identifier' : self.valid_add_by_wu_identifier,
}
]
@classmethod
def tearDownClass(self):
tear_down()
def test_api_accept_only_admins(self):
remove_admin_status()
payload = self.valid_payloads[0]
content = self.post_and_get_json_response(payload)
self.assertTrue((content['post_success']==False) and ("not an admin" in content['post_msg']),
f"api should have detected that user is not an admin and fail\n{content['post_msg']}")
def test_with_valid_data(self):
grant_admin_status()
for payload in self.valid_payloads:
self.__add_any_permissions_needed_in_this_test() ## Need to add additional permissions that is removed in this api
self.assert_post_with_valid_payload_is_success(payload=payload)
## Check if data was deleted correctly
if payload['perm_delete_by'] == 'wu':
try:
saved_object = TblPermissionsWorkUnit.objects.using('OrgChartRead').get(
user_id__windows_username__exact=payload['windows_username']
,wu__wu__exact=payload['perm_identifier']
)
except ObjectDoesNotExist as e:
... ## Good, do nothing
except Exception as e:
raise ValueError(f"test_with_valid_data(): {e}")
else:
self.assertTrue(False
,f"permission object ({saved_object.user_id.windows_username}, {saved_object.wu.wu}) still exists in the database, unable to delete permission")
elif payload['perm_delete_by'] == 'division':
work_units = TblWorkUnits.objects.using('OrgChartRead').filter(
subdiv__exact=payload['perm_identifier']
)
for work_unit in work_units:
try:
saved_object = TblPermissionsWorkUnit.objects.using('OrgChartRead').get(
user_id__windows_username__exact=payload['windows_username']
,wu__wu__exact=work_unit
)
except ObjectDoesNotExist as e:
... ## Good, do nothing
except Exception as e:
raise ValueError(f"test_with_valid_data(): {e}")
else:
self.assertTrue(False
,f"permission object ({saved_object.user_id.windows_username}, {saved_object.wu.wu}) still exists in the database while trying to delete by division '{payload['perm_identifier']}', unable to delete permission")
else:
self.assertTrue(False
,f"payload['perm_delete_by'] value '{payload['perm_delete_by']}' not implemented in test. Wrong data or please add implementation")
def test_data_validation(self):
grant_admin_status()
payload = self.valid_payloads[0]
parameters = [
# Parameter name # Accepted type
'windows_username' # str -> username
,'perm_delete_by' # str -> Either 'division' or 'wu'
,'perm_identifier' # str -> a subdiv name, or a wu
]
for param_name in parameters:
if param_name == 'windows_username':
valid = [self.valid_username]
invalid = ['a', '-1', '-1.2', '11.567', '2.2', '4.45', 5.46, -1, None, False, True, '']
elif param_name == 'perm_delete_by':
valid = ['division', 'wu']
invalid = ['a', '-1', '-1.2', '11.567', '2.2', '4.45', 5.46, -1, None, False, True, '']
elif param_name == 'perm_identifier':
valid = [self.valid_add_by_division_identifier, self.valid_add_by_wu_identifier]
invalid = ['a', '-1', '-1.2', '11.567', '2.2', '4.45', 5.46, -1, None, False, True, '']
else:
raise ValueError(f"test_data_validation(): parameter test not implemented: '{param_name}'. Please remove or implement it")
for data in valid:
if param_name == 'perm_delete_by' and data == 'division':
## for division, the perm_id must be a sub div name
payload = copy.deepcopy(payload)
payload['perm_identifier'] = self.valid_add_by_division_identifier
if param_name == 'perm_delete_by' and data == 'wu':
## for wu, the perm_id must be a wu
payload = copy.deepcopy(payload)
payload['perm_identifier'] = self.valid_add_by_wu_identifier
if param_name == 'perm_identifier' and data == self.valid_add_by_division_identifier:
## for perm_id with division, the add_by must be 'division'
payload = copy.deepcopy(payload)
payload['perm_delete_by'] = 'division'
if param_name == 'perm_identifier' and data == self.valid_add_by_wu_identifier:
## for perm_id with wu, the add_by must be 'wu'
payload = copy.deepcopy(payload)
payload['perm_delete_by'] = 'wu'
self.__add_any_permissions_needed_in_this_test() ## Need to add additional permissions that is removed in this api
self.assert_request_param_good(valid_payload=payload, testing_param_name=param_name, testing_data=data)
for data in invalid:
self.__add_any_permissions_needed_in_this_test() ## Need to add additional permissions that is removed in this api
self.assert_request_param_bad(valid_payload=payload, testing_param_name=param_name, testing_data=data)
def __add_any_permissions_needed_in_this_test(self):
## Set up permissions for 'division' delete_by
work_unit_objs = TblWorkUnits.objects.using('OrgChartWrite').filter(
subdiv__exact=self.valid_add_by_division_identifier
,active=True
)
user_obj = get_or_create_user(windows_username=self.valid_username)
for wu_obj in work_unit_objs:
permission = TblPermissionsWorkUnit.objects.using('OrgChartWrite').get_or_create(
user_id=user_obj
,wu=wu_obj
)[0]
permission.save(using="OrgChartWrite")
## Set up permission for 'wu' delete_by
work_unit_obj = TblWorkUnits.objects.using('OrgChartWrite').get(
wu__exact=self.valid_add_by_wu_identifier
,active=True
)
user_obj = get_or_create_user(windows_username=self.valid_username)
permission = TblPermissionsWorkUnit.objects.using('OrgChartWrite').get_or_create(
user_id=user_obj
,wu=work_unit_obj
)[0]
permission.save(using="OrgChartWrite")
| 50.856599 | 255 | 0.62665 | 74,478 | 0.929233 | 0 | 0 | 14,766 | 0.18423 | 0 | 0 | 24,842 | 0.309944 |
7f89f00e8b87657252a144b19c11f0b25e549b6d | 3,794 | py | Python | test_net.py | reasonsolo/mtcnn_caffe | ec646c8e27af900da1380d5968970705f9e8f582 | [
"MIT"
] | null | null | null | test_net.py | reasonsolo/mtcnn_caffe | ec646c8e27af900da1380d5968970705f9e8f582 | [
"MIT"
] | null | null | null | test_net.py | reasonsolo/mtcnn_caffe | ec646c8e27af900da1380d5968970705f9e8f582 | [
"MIT"
] | 1 | 2019-01-15T05:56:06.000Z | 2019-01-15T05:56:06.000Z | import cv2
import caffe
import tools
import sys
import os
import numpy as np
from functools import partial
import config
def gen_scales(w, h, min_imgsize, net_imgsize):
scales = []
scale = float(net_imgsize) / min_imgsize;
minhw = min(w, h) * scale;
while minhw > net_imgsize:
scales.append(scale)
scale *= 0.709
minhw *= 0.709
return scales
def regularize_rect(img_shape, rect):
w, h, _ = img_shape
x1, y1, x2, y2, prob = rect
x1 = max(0, min(x1, w))
x2 = max(0, min(x2, w))
y1 = max(0, min(y1, h))
y2 = max(0, min(y2, h))
return [x1, x2, y1, y2, prob]
def load_model(model_dir, net, iter_num):
proto_path = os.path.join(model_dir, '%s.prototxt' % net)
model_path = os.path.join(model_dir, '%s_iter_%d.caffemodel' % (net, iter_num))
return caffe.Net(proto_path, model_path, caffe.TEST)
def test_pnet(img, min_img_size, net_size, net):
norm_img = (img.copy() - 127.5) / 127.5
h, w, c = norm_img.shape
scales = gen_scales(w, h, min_img_size, net_size)
rects = []
for scale in scales:
sh = int(h * scale)
sw = int(w * scale)
scale_img = cv2.resize(norm_img, (sw, sh))
scale_img = cv2.transpose(scale_img)
scale_img = np.swapaxes(scale_img, 0, 2)
net.blobs['data'].reshape(1, 3, sh, sw)
net.blobs['data'].data[...] = scale_img
print(scale_img.shape)
print(scale_img)
out = net.forward()
conv1 = net.blobs["conv1"]
label_prob = out[config.NET_OUTPUTS['pnet']['label']][0]
bbox = out[config.NET_OUTPUTS['pnet']['bbox']][0]
print(conv1.data.shape)
print(conv1.data)
out_h, out_w = label_prob[1].shape
out_side = max(out_h, out_w)
rect = tools.detect_face_12net(label_prob[1], bbox, out_side,
1 / scale, w, h, 0.65)
rects += rect
break
rects = tools.NMS(rects, 0.7, 'iou')
return rects
def test_rnet(img, rects, min_img_size, net_size, net):
norm_img = (img.copy() - 127.5) / 128
h, w, c = norm_img.shape
for i, rect in enumerate(rects):
cropped_img = img[int(rect[1]):int(rect[3]), int(rect[0]):int(rect[2]),]
resized_img = cv2.resize(cropped_img, (net_size, net_size))
resized_img = np.swapaxes(resized_img, 0, 2)
net.blobs['data'].data[i] = resized_img
out = net.forward()
label_prob = out[config.NET_OUTPUTS['rnet']['label']][0][1]
bbox = out[config.NET_OUTPUTS['rnet']['bbox']][0][1]
rects = tools.filter_face_24net(label_prob, bbox, rects, w, h, 0.7)
return [rect for rect in rects if rects[2] - rects[0] > 0 and rects[3] - rects[1] > 0]
def test_net(net, model_dir, iter_num):
model_path = os.path.join(model_dir, '%s_iter_%d.caffemodel' % (net, iter_num))
proto_path = os.path.join(model_dir, '%s.prototxt' % net)
caffe_net = caffe.Net(proto_path, model_path, caffe.TEST)
if net == 'pnet':
return partial(test_pnet, net=caffe_net)
elif net == 'rnet':
return partial(test_rnet, net=caffe_net)
if __name__ == '__main__':
net = sys.argv[1]
iter_num = int(sys.argv[2])
img_path = sys.argv[3]
test_func = test_net(net, config.MODEL_DIR, iter_num)
img = cv2.imread(img_path)
rects = test_func(img, config.MIN_IMG_SIZE, config.NET_IMG_SIZES['pnet'])
for i, rect in enumerate(rects):
sub_img = img[rect[1]:rect[3], rect[0]:rect[2]]
print(sub_img.shape, rect)
cv2.imwrite("pnet/test/%d_%f.jpg" % (i, rect[4]), sub_img)
for i, rect in enumerate(rects):
cv2.rectangle(img, (rect[0], rect[1]), (rect[2], rect[3]), (255,0,0), 3)
cv2.imwrite("pnet/result.jpg", img)
print('%d rects generated' % len(rects))
| 33.875 | 90 | 0.610174 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 238 | 0.062731 |
7f8cfe7c21edb98148f06559139a4693716409cf | 515 | py | Python | SharedData/list_all_files.py | kylemcdonald/SoundParts | 964de07f28ac181be2b9e8050b9e5a7e9b10a93d | [
"MIT"
] | 22 | 2017-05-02T07:55:25.000Z | 2020-12-18T00:48:03.000Z | SharedData/list_all_files.py | kylemcdonald/SoundParts | 964de07f28ac181be2b9e8050b9e5a7e9b10a93d | [
"MIT"
] | null | null | null | SharedData/list_all_files.py | kylemcdonald/SoundParts | 964de07f28ac181be2b9e8050b9e5a7e9b10a93d | [
"MIT"
] | 2 | 2019-08-29T06:46:02.000Z | 2020-08-31T12:56:59.000Z | import os
import fnmatch
# extensions can be a single tring like '.png' or '.jpg'
# or a list of extensions. they should all be lowercase
# but the . is important.
def list_all_files(directory, extensions=None):
for root, dirnames, filenames in os.walk(directory):
for filename in filenames:
base, ext = os.path.splitext(filename)
joined = os.path.join(root, filename)
if extensions is None or ( len(ext) and ext.lower() in extensions ):
yield joined | 39.615385 | 80 | 0.660194 | 0 | 0 | 350 | 0.679612 | 0 | 0 | 0 | 0 | 136 | 0.264078 |
7f8dc67d585101b5b8e1bb738d00fbeb7fa08007 | 452 | py | Python | Capitulo_02/exercise2_6.py | thiagosouzalink/my_codes-exercices-book-curso_intensivo_de_python | 841aa855a7450ad3d0ba65393ba0b6debcd6a770 | [
"MIT"
] | null | null | null | Capitulo_02/exercise2_6.py | thiagosouzalink/my_codes-exercices-book-curso_intensivo_de_python | 841aa855a7450ad3d0ba65393ba0b6debcd6a770 | [
"MIT"
] | null | null | null | Capitulo_02/exercise2_6.py | thiagosouzalink/my_codes-exercices-book-curso_intensivo_de_python | 841aa855a7450ad3d0ba65393ba0b6debcd6a770 | [
"MIT"
] | null | null | null | """
2.6 – Citação famosa 2: Repita o Exercício 2.5, porém, desta vez, armazene o nome da pessoa famosa em uma variável chamada famous_person. Em seguida, componha sua mensagem e armazene-a em uma nova variável chamada message. Exiba sua mensagem.
"""
famous_person = "René Descartes"
message = "As paixões são todas boas por natureza e nós apenas temos de evitar o seu mau uso e os seus excessos."
print(f"{famous_person} certa vez disse: {message}") | 56.5 | 242 | 0.761062 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 426 | 0.918103 |
7f8ded4f80685086d5ad90cfec886cbe3a773f21 | 662 | py | Python | algorithm/lin_search.py | terasakisatoshi/pythonCodes | baee095ecee96f6b5ec6431267cdc6c40512a542 | [
"MIT"
] | null | null | null | algorithm/lin_search.py | terasakisatoshi/pythonCodes | baee095ecee96f6b5ec6431267cdc6c40512a542 | [
"MIT"
] | null | null | null | algorithm/lin_search.py | terasakisatoshi/pythonCodes | baee095ecee96f6b5ec6431267cdc6c40512a542 | [
"MIT"
] | null | null | null | import random
import copy
import time
from numba import jit
from array_creator import create_test_set
from measure import get_elapsed_data
@get_elapsed_data
def scratch_lin_search(test_set):
hit = False
for key, arr in test_set:
for i in arr:
if i == key:
break
@get_elapsed_data
def std_search(test_set):
for key, arr in test_set:
if key in arr:
continue
def main():
size = 100000
trial = 1
test_set = create_test_set(size, trial)
original = list(range(size))
print(scratch_lin_search(test_set))
print(std_search(test_set))
if __name__ == '__main__':
main()
| 18.914286 | 43 | 0.663142 | 0 | 0 | 0 | 0 | 283 | 0.427492 | 0 | 0 | 10 | 0.015106 |
7f90b833e66c95aaa6e86ee20476290414956557 | 3,997 | py | Python | setup.py | cdeil/astroquery | 1bbb9f8ea0347abb1081dba52a66772a03408f11 | [
"BSD-3-Clause"
] | null | null | null | setup.py | cdeil/astroquery | 1bbb9f8ea0347abb1081dba52a66772a03408f11 | [
"BSD-3-Clause"
] | null | null | null | setup.py | cdeil/astroquery | 1bbb9f8ea0347abb1081dba52a66772a03408f11 | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/env python
# Licensed under a 3-clause BSD style license - see LICENSE.rst
# Use "distribute" - the setuptools fork that supports python 3.
from distribute_setup import use_setuptools
use_setuptools()
from distutils.command import sdist
import glob
import os
import sys
from setuptools import setup, find_packages
#A dirty hack to get around some early import/configurations ambiguities
#This is the same as setup_helpers.set_build_mode(), but does not require
#importing setup_helpers
if sys.version_info[0] >= 3:
import builtins
else:
import __builtin__ as builtins
builtins._PACKAGE_SETUP_ = True
import astropy
from astropy import setup_helpers
from astropy.version_helper import get_git_devstr, generate_version_py
# Set affiliated package-specific settings
PACKAGENAME = 'astroquery'
DESCRIPTION = 'Functions and classes to access online data resources'
LICENSE = 'BSD'
#version should be PEP386 compatible (http://www.python.org/dev/peps/pep-0386)
version = '0.0.dev'
# Indicates if this version is a release version
release = 'dev' not in version
# Adjust the compiler in case the default on this platform is to use a
# broken one.
setup_helpers.adjust_compiler()
if not release:
version += get_git_devstr(False)
generate_version_py(PACKAGENAME, version, release,
setup_helpers.get_debug_option())
# Use the find_packages tool to locate all packages and modules
packagenames = find_packages()
# Treat everything in scripts except README.rst as a script to be installed
scripts = glob.glob(os.path.join('scripts', '*'))
scripts.remove(os.path.join('scripts', 'README.rst'))
# This dictionary stores the command classes used in setup below
cmdclassd = {'test': setup_helpers.setup_test_command(PACKAGENAME),
# Use distutils' sdist because it respects package_data.
# setuptools/distributes sdist requires duplication of
# information in MANIFEST.in
'sdist': sdist.sdist,
# Use a custom build command which understands additional
# commandline arguments
'build': setup_helpers.AstropyBuild,
# Use a custom install command which understands additional
# commandline arguments
'install': setup_helpers.AstropyInstall
}
if setup_helpers.HAVE_CYTHON and not release:
from Cython.Distutils import build_ext
# Builds Cython->C if in dev mode and Cython is present
cmdclassd['build_ext'] = setup_helpers.wrap_build_ext(build_ext)
else:
cmdclassd['build_ext'] = setup_helpers.wrap_build_ext()
if hasattr(setup_helpers,'AstropyBuildSphinx') and setup_helpers.AstropyBuildSphinx is not None:
cmdclassd['build_sphinx'] = setup_helpers.AstropyBuildSphinx
# Set our custom command class mapping in setup_helpers, so that
# setup_helpers.get_distutils_option will use the custom classes.
setup_helpers.cmdclassd = cmdclassd
# Additional C extensions that are not Cython-based should be added here.
extensions = []
# A dictionary to keep track of all package data to install
package_data = {PACKAGENAME: ['data/*']}
# A dictionary to keep track of extra packagedir mappings
package_dirs = {}
# Update extensions, package_data, packagenames and package_dirs from
# any sub-packages that define their own extension modules and package
# data. See the docstring for setup_helpers.update_package_files for
# more details.
setup_helpers.update_package_files(PACKAGENAME, extensions, package_data,
packagenames, package_dirs)
setup(name=PACKAGENAME,
version=version,
description=DESCRIPTION,
packages=packagenames,
package_data=package_data,
package_dir=package_dirs,
ext_modules=extensions,
scripts=scripts,
requires=['astropy'],
install_requires=['astropy'],
provides=[PACKAGENAME],
license=LICENSE,
cmdclass=cmdclassd,
zip_safe=False,
use_2to3=True
)
| 33.033058 | 96 | 0.739304 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,896 | 0.474356 |
7f910ebedcd5c2b2f971ebd3398b107397e47933 | 606 | py | Python | dapr/serializers/base.py | mukundansundararajan/python-sdk | 2ee94e31292a650135b97bc3c70e3eca885c9b47 | [
"MIT"
] | null | null | null | dapr/serializers/base.py | mukundansundararajan/python-sdk | 2ee94e31292a650135b97bc3c70e3eca885c9b47 | [
"MIT"
] | null | null | null | dapr/serializers/base.py | mukundansundararajan/python-sdk | 2ee94e31292a650135b97bc3c70e3eca885c9b47 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Copyright (c) Microsoft Corporation.
Licensed under the MIT License.
"""
from abc import ABC, abstractmethod
from typing import Any, Callable, Optional, Type
class Serializer(ABC):
"""Serializer base class."""
@abstractmethod
def serialize(
self, obj: object,
custom_hook: Optional[Callable[[object], bytes]] = None) -> bytes:
...
@abstractmethod
def deserialize(
self, data: bytes, data_type: Optional[Type] = object,
custom_hook: Optional[Callable[[bytes], object]] = None) -> Any:
...
| 23.307692 | 78 | 0.612211 | 415 | 0.684818 | 0 | 0 | 348 | 0.574257 | 0 | 0 | 127 | 0.209571 |
7f91f89b2955e012b51865efdeed3fe5d4ed3284 | 84 | py | Python | htdocs/MPM - Copy/MM/apps.py | anji-a/Apache | d08893821cb0251b8f99197a7b6893c95db4eb6e | [
"Apache-2.0"
] | null | null | null | htdocs/MPM - Copy/MM/apps.py | anji-a/Apache | d08893821cb0251b8f99197a7b6893c95db4eb6e | [
"Apache-2.0"
] | null | null | null | htdocs/MPM - Copy/MM/apps.py | anji-a/Apache | d08893821cb0251b8f99197a7b6893c95db4eb6e | [
"Apache-2.0"
] | 2 | 2020-11-04T06:30:46.000Z | 2020-11-06T11:00:53.000Z | from django.apps import AppConfig
class MmConfig(AppConfig):
name = 'MM'
| 14 | 34 | 0.678571 | 43 | 0.511905 | 0 | 0 | 0 | 0 | 0 | 0 | 4 | 0.047619 |
7f9293a745961e293df2ce58166bf397c0164a1c | 258 | py | Python | reto-05/eleloi/main.py | jlnc/reto-python | 7611b5ae231812b3bde1893a303af1c22765f859 | [
"MIT"
] | 18 | 2022-02-14T19:15:21.000Z | 2022-03-29T12:56:18.000Z | reto-05/eleloi/main.py | jlnc/reto-python | 7611b5ae231812b3bde1893a303af1c22765f859 | [
"MIT"
] | 22 | 2022-03-05T23:48:04.000Z | 2022-03-31T04:33:58.000Z | reto-05/eleloi/main.py | jlnc/reto-python | 7611b5ae231812b3bde1893a303af1c22765f859 | [
"MIT"
] | 21 | 2022-02-16T17:52:05.000Z | 2022-03-28T20:13:46.000Z | import _config
import _utils
CONFIG_PATH = "config.toml"
def main():
config = _config.read(CONFIG_PATH)
for path_name in [x.in_ for x in config.directorios]:
_utils.list_jpg_files_in_dir(path_name)
if __name__ == "__main__":
main()
| 16.125 | 57 | 0.697674 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 23 | 0.089147 |
7f92bdbd76e88952ccd41f7b4bb7059cb29661bf | 360 | py | Python | ravel/utils/data.py | eykd/ravel | bcd4a748c74acd39f09f4eab6a8cb65660e857b5 | [
"MIT"
] | 1 | 2020-05-16T12:27:44.000Z | 2020-05-16T12:27:44.000Z | ravel/utils/data.py | eykd/ravel | bcd4a748c74acd39f09f4eab6a8cb65660e857b5 | [
"MIT"
] | null | null | null | ravel/utils/data.py | eykd/ravel | bcd4a748c74acd39f09f4eab6a8cb65660e857b5 | [
"MIT"
] | null | null | null |
def merge_dicts(*dicts):
"""
Given any number of dicts, shallow copy and merge into a new dict,
precedence goes to key value pairs in latter dicts.
"""
result = {}
for d in dicts:
result.update(d)
return result
def evaluate_term(term, **kwargs):
return term.evaluate(**kwargs) if hasattr(term, 'evaluate') else term
| 22.5 | 73 | 0.65 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 148 | 0.411111 |
7f92e83ec063df76628d1922d90de32e41d7fd7e | 11,067 | py | Python | skyline.py | MyrrhDev/skyline-telegramBot | 55b0d597b0710f2ae1314e3359b08c02276f094a | [
"MIT"
] | null | null | null | skyline.py | MyrrhDev/skyline-telegramBot | 55b0d597b0710f2ae1314e3359b08c02276f094a | [
"MIT"
] | null | null | null | skyline.py | MyrrhDev/skyline-telegramBot | 55b0d597b0710f2ae1314e3359b08c02276f094a | [
"MIT"
] | null | null | null | import random
class Skyline:
area = 0
max_height = 0
xmin = 0
height = []
width = []
x_pos = []
xmax = 0
def __init__(self, xmin, height, xmax):
self.xmin = xmin
self.height = [height] * ((xmax - xmin) + 1)
self.xmax = xmax
self.x_pos = list(range(xmin, xmax + 1))
self.area = sum(self.height[:-1])
self.max_height = height
times = self.xmax - self.xmin
width_array = [1.0] * times
width_array.append(-0.5)
self.width = width_array
# Devuelve una lista para hacer el plot de la(s) alturas del skyline
def get_height(self):
return self.height
# Devuelve una lista para hacer el plot de las posicion en el eje x
# e.g. [1, 2, 3]
def get_x_pos(self):
return self.x_pos
# Devuelve una lista para hacer el plot de las width
def get_width(self):
return self.width
# Devuelve el valor acumulado del area del Skyline
def get_area(self):
return self.area
# Devuelve el valor maximo de altura de un Skyline
def get_max_height(self):
return self.max_height
# Update tabla de simbolos context
def update_symbols(name_id, ts_dict, value):
ts_dict[name_id] = value
return ts_dict
# Retorna type = NoneType si no encuentra el simbolo en la ts
# sino, retorna el valor
def find_symbol(name_id, ts_dict):
if name_id in ts_dict:
return ts_dict[name_id]
# Functions:
# Mover el skyline a la derecha
def move_right(self, num):
self.xmin = self.xmin + num
self.xmax = self.xmax + num
self.x_pos = [x + num for x in self.x_pos]
# Mover el skyline a la izquierda
def move_left(self, num):
self.xmin = self.xmin - num
self.xmax = self.xmax - num
self.x_pos = [x - num for x in self.x_pos]
# Replicacion del mismo skyline
def multiply_n(self, n, num):
mul_heights = self.get_height().copy()
mul_width = self.get_width().copy()
mul_x_pos = self.get_x_pos().copy()
size = len(mul_x_pos)
m_max = self.xmax
for i in range(n - 1):
m_min = m_max
m_max = m_max + size - 1
mul_x_pos += list(range(m_min, m_max + 1))
mult_skl = Skyline(0, 0, 0)
mult_skl.c_skyline(mul_x_pos, mul_heights * n, mul_width * n, num)
return mult_skl
def sm_calculate_width(self, x_pos_mn, x_pos_mx, s_width):
times = x_pos_mx - x_pos_mn
sp_width = [s_width] * times
sp_width.append(-0.5)
return sp_width
def sm_modify_heights(self, l_heights, i, j, s_height):
k = 0
while i < j:
if l_heights[i] < s_height[k]:
l_heights[i] = s_height[k]
i += 1
k += 1
return l_heights
def clean_heights(self, x_pos, h_pos):
n_he = {}
for i, j in zip(x_pos, h_pos):
n_he[i] = j
return list(n_he.keys()), list(n_he.values())
# Suma una skyline
def sumar_skyline(self, sky_in, s_width=1):
sum_x_pos = []
sum_heights = []
sum_width = []
s_xmin = sky_in.xmin
s_height = sky_in.height
s_xmax = sky_in.xmax
if s_xmin == 0 and s_xmax == 0 and s_height[0] == 0:
return self
if (s_xmin < self.xmin and s_xmax < self.xmin) or (s_xmin > self.xmax and s_xmax > self.xmax):
sp_width = self.sm_calculate_width(s_xmin, s_xmax, s_width)
# left add
if s_xmin < self.xmin and s_xmax < self.xmin:
diff = ((self.xmax - s_xmin) + 1) - len(s_height) - len(self.get_height())
sp_cero_fill = [0] * diff
sum_x_pos = list(range(s_xmin, self.xmax + 1))
sum_heights = s_height + sp_cero_fill + self.get_height()
sum_width = sp_width + sp_cero_fill + self.get_width()
# right add
elif s_xmin > self.xmax and s_xmax > self.xmax:
diff = ((s_xmax - self.xmin) + 1) - len(s_height) - len(self.get_height())
sp_cero_fill = [0] * diff
sum_x_pos = list(range(self.xmin, s_xmax + 1))
sum_heights = self.get_height() + sp_cero_fill + s_height
sum_width = self.get_width() + sp_cero_fill + sp_width
# completamente adentro
elif s_xmin >= self.xmin and s_xmax <= self.xmax:
sum_heights = self.get_height().copy()
sum_x_pos = self.get_x_pos().copy()
i = sum_x_pos.index(s_xmin)
j = sum_x_pos.index(s_xmax)
sum_heights = self.sm_modify_heights(sum_heights, i, j, s_height)
sum_width = self.sm_calculate_width(sum_x_pos[0], sum_x_pos[-1], s_width)
# completamente afuera
elif s_xmin < self.xmin and s_xmax > self.xmax:
sp_height = self.get_height().copy()
sum_heights = s_height.copy()
sum_x_pos = list(range(s_xmin, s_xmax + 1))
i = sum_x_pos.index(self.xmin)
j = sum_x_pos.index(self.xmax)
k = 0
while i < j:
if sp_height[k] > sum_heights[i]:
sum_heights[i] = sp_height[k]
i += 1
k += 1
sum_width = self.sm_calculate_width(sum_x_pos[0], sum_x_pos[-1], s_width)
# solo uno adentro
elif (s_xmin < self.xmin and s_xmax <= self.xmax) or (s_xmin >= self.xmin and s_xmax > self.xmax):
sum_heights = self.get_height().copy()
if (s_xmin < self.xmin) and (s_xmax <= self.xmax):
# left add
sum_x_pos = list(range(s_xmin, self.xmax + 1))
s_fill = len(sum_x_pos) - len(sum_heights)
zero = [0] * s_fill
sum_heights = zero + sum_heights
i = sum_x_pos.index(s_xmin)
j = sum_x_pos.index(s_xmax)
sum_heights = self.sm_modify_heights(sum_heights, i, j, s_height)
else:
sum_x_pos = list(range(self.xmin, s_xmax + 1))
s_fill = len(sum_x_pos) - len(sum_heights)
zero = [0] * s_fill
k = -1
p = self.xmax - s_xmin
if s_height[p + 1] < sum_heights[-1]:
k = sum_x_pos.index(self.xmax)
sum_heights = sum_heights + zero
i = sum_x_pos.index(s_xmin)
j = sum_x_pos.index(s_xmax)
sum_heights = self.sm_modify_heights(sum_heights, i, j + 1, s_height)
if k > -1:
sum_heights[k] = s_height[p]
sum_width = self.sm_calculate_width(sum_x_pos[0], sum_x_pos[-1], s_width)
new_sky_s = Skyline(0, 0, 0)
new_sky_s.c_skyline(sum_x_pos, sum_heights, sum_width)
return new_sky_s
# Crea un skyline de la informacion de lists
def c_skyline(self, c_x_pos, c_heights, c_width, m_num=-1, area=-1):
self.xmin = c_x_pos[0]
self.height = c_heights
self.xmax = c_x_pos[-1]
self.x_pos = c_x_pos
if m_num > -1:
self.area = sum(c_heights) - m_num
elif area > -1:
self.area = area
else:
self.area = sum(c_heights[:-1])
self.max_height = max(c_heights)
self.width = c_width
def inter_skyline(self, inter_sky):
sum_x_pos = []
s_xmin = inter_sky.xmin
s_height = inter_sky.height
s_xmax = inter_sky.xmax
if (self.xmin <= s_xmin) and (s_xmax <= self.xmax):
sum_x_pos = list(range(s_xmin, s_xmax + 1))
s_x_pos = inter_sky.get_x_pos().copy()
(c_x_pos, s_height) = self.clean_heights(s_x_pos, s_height)
r_ind_i = c_x_pos.index(s_xmin)
r_ind_j = c_x_pos.index(s_xmax)
s_height = s_height[r_ind_i:r_ind_j + 1]
# left out
elif (s_xmin < self.xmin) and (s_xmax <= self.xmax):
sum_x_pos = list(range(self.xmin, s_xmax + 1))
s_x_pos = inter_sky.get_x_pos().copy()
(c_x_pos, s_height) = self.clean_heights(s_x_pos, s_height)
l_ind = c_x_pos.index(self.xmin)
s_height = s_height[l_ind:]
# right out
elif (s_xmin >= self.xmin) and (s_xmax > self.xmax):
sum_x_pos = list(range(s_xmin, self.xmax + 1))
s_x_pos = inter_sky.get_x_pos().copy()
(c_x_pos, s_height) = self.clean_heights(s_x_pos, s_height)
r_ind = c_x_pos.index(self.xmax)
s_height = s_height[:r_ind + 1]
else:
sum_x_pos = list(range(self.xmin, self.xmax + 1))
s_x_pos = inter_sky.get_x_pos().copy()
(c_x_pos, s_height) = self.clean_heights(s_x_pos, s_height)
r_ind_i = c_x_pos.index(self.xmin)
r_ind_j = c_x_pos.index(self.xmax)
s_height = s_height[r_ind_i:r_ind_j + 1]
sum_width = self.sm_calculate_width(sum_x_pos[0], sum_x_pos[-1], 1)
sum_heights = self.get_height().copy()
m_x_pos = self.get_x_pos().copy()
(m_x_pos, sum_heights) = self.clean_heights(m_x_pos, sum_heights)
i = m_x_pos.index(sum_x_pos[0])
j = m_x_pos.index(sum_x_pos[-1])
sum_heights = sum_heights[i:j + 1]
x = 0
while x < len(sum_heights):
if sum_heights[x] > s_height[x]:
sum_heights[x] = s_height[x]
x += 1
inter_skl = Skyline(0, 0, 0)
inter_skl.c_skyline(sum_x_pos, sum_heights, sum_width)
return inter_skl
def reflect_skyline(self, area):
reflect_heights = self.get_height().copy()
reflect_heights.reverse()
reflect_heights.pop(0)
reflect_heights.append(reflect_heights[-1])
r_width = self.get_width().copy()
r_x_pos = self.get_x_pos().copy()
reflect_skl = Skyline(0, 0, 0)
reflect_skl.c_skyline(r_x_pos, reflect_heights, r_width, -1, area)
return reflect_skl
# n - numero de edificios creados
# h - una altura de 0 a h aleatoria
# w - una width de 1 a w aleatoria
# xmin, xmax - una posicion de inicio/final entre xmin, xmax
def random_skylines(n, h, w, xmin, xmax):
temp_sky = Skyline(0, 0, 0)
i = 0
while i < n:
rd_xmin = random.randint(xmin, xmax - 1)
rd_xmax = random.randint(rd_xmin + 1, xmax)
rd_height = random.randint(0, h)
rd_width = random.randint(1, w)
rd_x_pos = list(range(rd_xmin, rd_xmax + 1))
rd_heights_list = [rd_height] * ((rd_xmax - rd_xmin) + 1)
times = rd_xmax - rd_xmin
width_array = [rd_width] * times
width_array.append(-0.5)
tp_sky = Skyline(0, 0, 0)
tp_sky.c_skyline(rd_x_pos, rd_heights_list, width_array)
temp_sky = temp_sky.sumar_skyline(tp_sky)
i += 1
return temp_sky
| 36.524752 | 106 | 0.562393 | 11,050 | 0.998464 | 0 | 0 | 0 | 0 | 0 | 0 | 868 | 0.078431 |
7f94715fd95a0d6e266114d4c58a4a00c641770c | 1,699 | py | Python | code/default/smart_router/local/socket_wrap.py | wuyongwen/XX-Net | 313aefd862b8f230f7c61dc29db1b2b93a17e6ab | [
"BSD-2-Clause"
] | null | null | null | code/default/smart_router/local/socket_wrap.py | wuyongwen/XX-Net | 313aefd862b8f230f7c61dc29db1b2b93a17e6ab | [
"BSD-2-Clause"
] | null | null | null | code/default/smart_router/local/socket_wrap.py | wuyongwen/XX-Net | 313aefd862b8f230f7c61dc29db1b2b93a17e6ab | [
"BSD-2-Clause"
] | null | null | null | import time
class SocketWrap(object):
def __init__(self, sock, ip=None, port=None, host="", target=""):
self._sock = sock
self.ip = ip
self.port = port
self.host = host
self.target = target
self.recved_data = 0
self.recved_times = 0
self.create_time = time.time()
self.closed = False
self.replace_pattern = None
self.buf = []
self.buf_size = 0
self.buf_num = 0
def __getattr__(self, attr):
return getattr(self._sock, attr)
def close(self):
self._sock.close()
self.closed = True
def is_closed(self):
return self.closed
def __str__(self):
return "%s[%s]:%d" % (self.host, self.ip, self.port)
def recv(self, bufsiz, flags=0):
d = self._sock.recv(bufsiz, flags)
if self.replace_pattern and " HTTP/1.1\r\n" in d:
line_end = d.find("\r\n")
req_line = d[:line_end]
words = req_line.split()
if len(words) == 3:
method, url, http_version = words
url = url.replace(self.replace_pattern[0], self.replace_pattern[1])
d = "%s %s %s" % (method, url, http_version) + d[line_end:]
return d
def add_dat(self, data):
self.buf.append(data)
self.buf_size += len(data)
self.buf_num += 1
def get_dat(self):
if not self.buf:
return ""
dat = self.buf.pop(0)
self.buf_size -= len(dat)
self.buf_num -= 1
return dat
def restore_dat(self, dat):
self.buf.insert(0, dat)
self.buf_size += len(dat)
self.buf_num += 1 | 25.742424 | 83 | 0.535021 | 1,685 | 0.99176 | 0 | 0 | 0 | 0 | 0 | 0 | 48 | 0.028252 |
7f94ad38bbb98e281664244307b46754d21960c0 | 2,859 | py | Python | tests/unit/test_handler_marker.py | Rogdham/bigxml | ab983f50c49bf861c3b61e3e636db90f9ff19ed1 | [
"MIT"
] | 4 | 2020-08-24T13:31:46.000Z | 2022-01-25T08:03:19.000Z | tests/unit/test_handler_marker.py | Rogdham/bigxml | ab983f50c49bf861c3b61e3e636db90f9ff19ed1 | [
"MIT"
] | null | null | null | tests/unit/test_handler_marker.py | Rogdham/bigxml | ab983f50c49bf861c3b61e3e636db90f9ff19ed1 | [
"MIT"
] | null | null | null | import pytest
from bigxml.handler_marker import _ATTR_MARKER, xml_handle_element, xml_handle_text
from bigxml.nodes import XMLText
def test_one_maker_element():
@xml_handle_element("abc", "def")
def fct(arg):
return arg * 6
assert getattr(fct, _ATTR_MARKER, None) == (("abc", "def"),)
assert fct(7) == 42
def test_one_maker_element_on_method():
class Klass:
def __init__(self, multiplier):
self.multiplier = multiplier
@xml_handle_element("abc", "def")
def method(self, arg):
return arg * self.multiplier
instance = Klass(6)
assert getattr(instance.method, _ATTR_MARKER, None) == (("abc", "def"),)
assert instance.method(7) == 42
def test_one_maker_element_on_static_method():
class Klass:
@xml_handle_element("abc", "def")
@staticmethod
def method(arg):
return arg * 6
assert getattr(Klass.method, _ATTR_MARKER, None) == (("abc", "def"),)
assert Klass.method(7) == 42
def test_one_maker_element_on_method_before_staticmethod():
class Klass:
@staticmethod
@xml_handle_element("abc", "def")
def method(arg):
return arg * 6
assert getattr(Klass.method, _ATTR_MARKER, None) == (("abc", "def"),)
assert Klass.method(7) == 42
def test_several_maker_element():
@xml_handle_element("abc", "def")
@xml_handle_element("ghi")
@xml_handle_element("klm", "opq", "rst")
def fct(arg):
return arg * 6
assert getattr(fct, _ATTR_MARKER, None) == (
("klm", "opq", "rst"),
("ghi",),
("abc", "def"),
)
assert fct(7) == 42
def test_one_maker_element_no_args():
with pytest.raises(TypeError):
@xml_handle_element()
def fct(arg): # pylint: disable=unused-variable
return arg * 6
def test_one_marker_text_no_call():
@xml_handle_text
def fct(arg):
return arg * 6
assert getattr(fct, _ATTR_MARKER, None) == ((XMLText.name,),)
assert fct(7) == 42
def test_one_marker_text_no_args():
@xml_handle_text()
def fct(arg):
return arg * 6
assert getattr(fct, _ATTR_MARKER, None) == ((XMLText.name,),)
assert fct(7) == 42
def test_one_marker_text_args():
@xml_handle_text("abc", "def")
def fct(arg):
return arg * 6
assert getattr(fct, _ATTR_MARKER, None) == (
(
"abc",
"def",
XMLText.name,
),
)
assert fct(7) == 42
def test_mixed_markers():
@xml_handle_element("abc", "def")
@xml_handle_text("ghi")
@xml_handle_element("klm", "opq", "rst")
def fct(arg):
return arg * 6
assert getattr(fct, _ATTR_MARKER, None) == (
("klm", "opq", "rst"),
("ghi", XMLText.name),
("abc", "def"),
)
assert fct(7) == 42
| 23.628099 | 83 | 0.593214 | 464 | 0.162295 | 0 | 0 | 982 | 0.343477 | 0 | 0 | 253 | 0.088492 |
7f94c10f45c727e1a813931dfa3f4ee01c73a848 | 8,073 | py | Python | gamestonk_terminal/due_diligence/stockgrid_dd_view.py | brocki/GamestonkTerminal | d1505359e595a50bf22c2c5601f261686117310f | [
"MIT"
] | 1 | 2021-06-21T23:31:20.000Z | 2021-06-21T23:31:20.000Z | gamestonk_terminal/due_diligence/stockgrid_dd_view.py | brocki/GamestonkTerminal | d1505359e595a50bf22c2c5601f261686117310f | [
"MIT"
] | 1 | 2021-04-20T00:26:20.000Z | 2021-04-20T00:26:20.000Z | gamestonk_terminal/due_diligence/stockgrid_dd_view.py | alokan/GamestonkTerminal | d7bb5a9456250114da83172e5d49beb242df5eed | [
"MIT"
] | null | null | null | """Stockgrid DD View"""
__docformat__ = "numpy"
import argparse
from typing import List
from datetime import timedelta
import requests
import pandas as pd
import matplotlib.pyplot as plt
from tabulate import tabulate
from gamestonk_terminal.config_plot import PLOT_DPI
from gamestonk_terminal.feature_flags import USE_ION
from gamestonk_terminal.helper_funcs import (
parse_known_args_and_warn,
plot_autoscale,
check_positive,
)
def shortview(ticker: str, other_args: List[str]):
"""Plot price vs short interest volume
Parameters
----------
ticker: str
Stock to plot for
other_args : List[str]
Argparse arguments
"""
parser = argparse.ArgumentParser(
prog="shortvol",
add_help=False,
description="Shows price vs short interest volume. [Source: Stockgrid]",
)
parser.add_argument(
"-n",
"--number",
help="Number of last open market days to show",
type=check_positive,
default=10 if "-r" in other_args else 120,
dest="num",
)
parser.add_argument(
"-r",
action="store_true",
default=False,
help="Flag to print raw data instead",
dest="raw",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
link = f"https://stockgridapp.herokuapp.com/get_dark_pool_individual_data?ticker={ticker}"
response = requests.get(link)
df = pd.DataFrame(response.json()["individual_short_volume_table"]["data"])
df["date"] = pd.to_datetime(df["date"])
if ns_parser.raw:
df = df.sort_values(by="date", ascending=False)
df["Short Vol. (1M)"] = df["short_volume"] / 1_000_000
df["Short Vol. %"] = df["short_volume%"] * 100
df["Short Exempt Vol. (1K)"] = df["short_exempt_volume"] / 1_000
df["Total Vol. (1M)"] = df["total_volume"] / 1_000_000
df = df[
[
"date",
"Short Vol. (1M)",
"Short Vol. %",
"Short Exempt Vol. (1K)",
"Total Vol. (1M)",
]
]
df.date = df.date.dt.date
print(
tabulate(
df.iloc[: ns_parser.num],
tablefmt="fancy_grid",
floatfmt=".2f",
headers=list(df.columns),
showindex=False,
)
)
else:
prices = response.json()["prices"]["prices"]
_, axes = plt.subplots(
2,
1,
figsize=(plot_autoscale()),
dpi=PLOT_DPI,
gridspec_kw={"height_ratios": [2, 1]},
)
axes[0].bar(
df["date"],
df["total_volume"] / 1_000_000,
width=timedelta(days=1),
color="b",
alpha=0.4,
label="Total Volume",
)
axes[0].bar(
df["date"],
df["short_volume"] / 1_000_000,
width=timedelta(days=1),
color="r",
alpha=0.4,
label="Short Volume",
)
axes[0].set_ylabel("Volume (1M)")
ax2 = axes[0].twinx()
ax2.plot(
df["date"].values, prices[len(prices) - len(df) :], c="k", label="Price"
)
ax2.set_ylabel("Price ($)")
lines, labels = axes[0].get_legend_handles_labels()
lines2, labels2 = ax2.get_legend_handles_labels()
ax2.legend(lines + lines2, labels + labels2, loc="upper left")
axes[0].set_xlim(
df["date"].values[max(0, len(df) - ns_parser.num)],
df["date"].values[len(df) - 1],
)
axes[0].grid()
axes[0].ticklabel_format(style="plain", axis="y")
plt.title(f"Price vs Short Volume Interest for {ticker}")
plt.gcf().autofmt_xdate()
axes[1].plot(
df["date"].values,
100 * df["short_volume%"],
c="green",
label="Short Vol. %",
)
axes[1].set_xlim(
df["date"].values[max(0, len(df) - ns_parser.num)],
df["date"].values[len(df) - 1],
)
axes[1].set_ylabel("Short Vol. %")
axes[1].grid(axis="y")
lines, labels = axes[1].get_legend_handles_labels()
axes[1].legend(lines, labels, loc="upper left")
axes[1].set_ylim([0, 100])
if USE_ION:
plt.ion()
plt.show()
print("")
except Exception as e:
print(e, "\n")
def darkpos(ticker: str, other_args: List[str]):
"""Plot dark pool position
Parameters
----------
ticker: str
Stock to plot for
other_args : List[str]
Argparse arguments
"""
parser = argparse.ArgumentParser(
prog="darkpos",
add_help=False,
description="Shows Net Short Vol. vs Position. [Source: Stockgrid]",
)
parser.add_argument(
"-n",
"--number",
help="Number of last open market days to show",
type=check_positive,
default=10 if "-r" in other_args else 120,
dest="num",
)
parser.add_argument(
"-r",
action="store_true",
default=False,
help="Flag to print raw data instead",
dest="raw",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
link = f"https://stockgridapp.herokuapp.com/get_dark_pool_individual_data?ticker={ticker}"
response = requests.get(link)
df = pd.DataFrame(response.json()["individual_dark_pool_position_data"])
df["dates"] = pd.to_datetime(df["dates"])
if ns_parser.raw:
df = df.sort_values(by="dates", ascending=False)
df["Net Short Vol. (1k $)"] = df["dollar_net_volume"] / 1_000
df["Position (1M $)"] = df["dollar_dp_position"]
df = df[
[
"dates",
"Net Short Vol. (1k $)",
"Position (1M $)",
]
]
df["dates"] = df["dates"].dt.date
print(
tabulate(
df.iloc[: ns_parser.num],
tablefmt="fancy_grid",
floatfmt=".2f",
headers=list(df.columns),
showindex=False,
)
)
else:
fig = plt.figure(figsize=plot_autoscale(), dpi=PLOT_DPI)
ax = fig.add_subplot(111)
ax.bar(
df["dates"],
df["dollar_net_volume"] / 1_000,
color="r",
alpha=0.4,
label="Net Short Vol. (1k $)",
)
ax.set_ylabel("Net Short Vol. (1k $)")
ax2 = ax.twinx()
ax2.plot(
df["dates"].values,
df["dollar_dp_position"],
c="tab:blue",
label="Position (1M $)",
)
ax2.set_ylabel("Position (1M $)")
lines, labels = ax.get_legend_handles_labels()
lines2, labels2 = ax2.get_legend_handles_labels()
ax2.legend(lines + lines2, labels + labels2, loc="upper left")
ax.set_xlim(
df["dates"].values[max(0, len(df) - ns_parser.num)],
df["dates"].values[len(df) - 1],
)
ax.grid()
plt.title(f"Net Short Vol. vs Position for {ticker}")
plt.gcf().autofmt_xdate()
if USE_ION:
plt.ion()
plt.show()
print("")
except Exception as e:
print(e, "\n")
| 28.935484 | 98 | 0.484454 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,933 | 0.23944 |
7f9565f8eece01aa89f290f3687bbf816b1d2520 | 2,428 | py | Python | tests/schema/models_no_auto_create_m2m.py | Alirezaja1384/tortoise-orm | e7ecbc81d43860a3b0b6d5d9da27497ed6234049 | [
"Apache-2.0"
] | 33 | 2018-04-07T09:50:22.000Z | 2018-08-24T10:25:29.000Z | tests/schema/models_no_auto_create_m2m.py | Alirezaja1384/tortoise-orm | e7ecbc81d43860a3b0b6d5d9da27497ed6234049 | [
"Apache-2.0"
] | 41 | 2018-03-29T17:09:18.000Z | 2018-08-24T16:37:38.000Z | tests/schema/models_no_auto_create_m2m.py | Alirezaja1384/tortoise-orm | e7ecbc81d43860a3b0b6d5d9da27497ed6234049 | [
"Apache-2.0"
] | 4 | 2018-06-27T08:45:11.000Z | 2018-07-30T18:16:55.000Z | """
This example demonstrates SQL Schema generation for each DB type supported.
"""
from tortoise import fields
from tortoise.fields import SET_NULL
from tortoise.models import Model
class Tournament(Model):
tid = fields.SmallIntField(pk=True)
name = fields.CharField(max_length=100, description="Tournament name", index=True)
created = fields.DatetimeField(auto_now_add=True, description="Created */'`/* datetime")
class Meta:
table_description = "What Tournaments */'`/* we have"
class Event(Model):
id = fields.BigIntField(pk=True, description="Event ID")
name = fields.TextField()
tournament: fields.ForeignKeyRelation[Tournament] = fields.ForeignKeyField(
"models.Tournament", related_name="events", description="FK to tournament"
)
participants: fields.ManyToManyRelation["Team"] = fields.ManyToManyField(
"models.Team",
related_name="events",
through="teamevents",
description="How participants relate",
on_delete=SET_NULL,
)
modified = fields.DatetimeField(auto_now=True)
prize = fields.DecimalField(max_digits=10, decimal_places=2, null=True)
token = fields.CharField(max_length=100, description="Unique token", unique=True)
key = fields.CharField(max_length=100)
class Meta:
table_description = "This table contains a list of all the events"
unique_together = [("name", "prize"), ["tournament", "key"]]
class TeamEvent(Model):
team: fields.ForeignKeyRelation["Team"] = fields.ForeignKeyField(
"models.Team", related_name="teams"
)
event: fields.ForeignKeyRelation[Event] = fields.ForeignKeyField(
"models.Event", related_name="events"
)
score = fields.IntField()
class Meta:
table = "teamevents"
table_description = "How participants relate"
unique_together = ("team", "event")
class Team(Model):
name = fields.CharField(max_length=50, pk=True, description="The TEAM name (and PK)")
key = fields.IntField()
manager: fields.ForeignKeyRelation["Team"] = fields.ForeignKeyField(
"models.Team", related_name="team_members", null=True
)
talks_to: fields.ManyToManyRelation["Team"] = fields.ManyToManyField(
"models.Team", related_name="gets_talked_to"
)
class Meta:
table_description = "The TEAMS!"
indexes = [("manager", "key"), ["manager_id", "name"]]
| 34.685714 | 92 | 0.68575 | 2,232 | 0.919275 | 0 | 0 | 0 | 0 | 0 | 0 | 601 | 0.247529 |
7f957a19c84f447fc2196f4923469f1f2c048f4b | 9,025 | py | Python | tests/functional/wsgi/v1_1/test_claims.py | vkmc/zaqar-websocket | a93c460a28e541b5cc8b425d5fb4d69e78ab9f4b | [
"Apache-2.0"
] | 1 | 2015-03-22T18:41:13.000Z | 2015-03-22T18:41:13.000Z | tests/functional/wsgi/v1_1/test_claims.py | vkmc/zaqar-websocket | a93c460a28e541b5cc8b425d5fb4d69e78ab9f4b | [
"Apache-2.0"
] | null | null | null | tests/functional/wsgi/v1_1/test_claims.py | vkmc/zaqar-websocket | a93c460a28e541b5cc8b425d5fb4d69e78ab9f4b | [
"Apache-2.0"
] | null | null | null | # Copyright (c) 2014 Rackspace, Inc.
#
# 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 uuid
import ddt
from zaqar.tests.functional import base
from zaqar.tests.functional import helpers
@ddt.ddt
class TestClaims(base.V1_1FunctionalTestBase):
"""Tests for Claims."""
server_class = base.ZaqarServer
def setUp(self):
super(TestClaims, self).setUp()
self.headers = helpers.create_zaqar_headers(self.cfg)
self.client.headers = self.headers
self.queue = uuid.uuid1()
self.queue_url = ("{url}/{version}/queues/{queue}".format(
url=self.cfg.zaqar.url,
version="v1.1",
queue=self.queue))
self.client.put(self.queue_url)
self.claim_url = self.queue_url + '/claims'
self.client.set_base_url(self.claim_url)
# Post Messages
url = self.queue_url + '/messages'
doc = helpers.create_message_body_v1_1(
messagecount=self.limits.max_messages_per_page)
for i in range(10):
self.client.post(url, data=doc)
@ddt.data({}, {'limit': 2})
def test_claim_messages(self, params):
"""Claim messages."""
message_count = params.get('limit',
self.limits.max_messages_per_claim_or_pop)
doc = {"ttl": 300, "grace": 100}
result = self.client.post(params=params, data=doc)
self.assertEqual(result.status_code, 201)
self.assertSchema(result.json(), 'claim_create')
actual_message_count = len(result.json()['messages'])
self.assertMessageCount(actual_message_count, message_count)
response_headers = set(result.headers.keys())
self.assertIsSubset(self.headers_response_with_body, response_headers)
test_claim_messages.tags = ['smoke', 'positive']
def test_query_claim(self):
"""Query Claim."""
params = {'limit': 1}
doc = {"ttl": 300, "grace": 100}
result = self.client.post(params=params, data=doc)
location = result.headers['Location']
url = self.cfg.zaqar.url + location
result = self.client.get(url)
self.assertEqual(result.status_code, 200)
test_query_claim.tags = ['smoke', 'positive']
@ddt.data({}, {"grace": 100})
def test_claim_default_ttl(self, doc):
"""Create claim with default TTL and grace values."""
params = {'limit': 1}
result = self.client.post(params=params, data=doc)
self.assertEqual(result.status_code, 201)
location = result.headers['Location']
url = self.cfg.zaqar.url + location
result = self.client.get(url)
self.assertEqual(result.status_code, 200)
default_ttl = result.json()['ttl']
self.assertEqual(default_ttl, self.resource_defaults.claim_ttl)
test_claim_default_ttl.tags = ['smoke', 'positive']
def test_claim_more_than_allowed(self):
"""Claim more than max allowed per request.
Zaqar allows a maximum of 20 messages per claim by default.
"""
params = {"limit": self.limits.max_messages_per_claim_or_pop + 1}
doc = {"ttl": 300, "grace": 100}
result = self.client.post(params=params, data=doc)
self.assertEqual(result.status_code, 400)
test_claim_more_than_allowed.tags = ['negative']
def test_claim_patch(self):
"""Update Claim."""
# Test Setup - Post Claim
doc = {"ttl": 300, "grace": 400}
result = self.client.post(data=doc)
self.assertEqual(result.status_code, 201)
# Patch Claim
claim_location = result.headers['Location']
url = self.cfg.zaqar.url + claim_location
doc_updated = {"ttl": 300, 'grace': 60}
result = self.client.patch(url, data=doc_updated)
self.assertEqual(result.status_code, 204)
# verify that the claim TTL is updated
result = self.client.get(url)
new_ttl = result.json()['ttl']
self.assertEqual(doc_updated['ttl'], new_ttl)
test_claim_patch.tags = ['smoke', 'positive']
def test_delete_claimed_message(self):
"""Delete message belonging to a Claim."""
# Test Setup - Post claim
doc = {"ttl": 60, "grace": 60}
result = self.client.post(data=doc)
self.assertEqual(result.status_code, 201)
# Delete Claimed Messages
for rst in result.json()['messages']:
href = rst['href']
url = self.cfg.zaqar.url + href
result = self.client.delete(url)
self.assertEqual(result.status_code, 204)
test_delete_claimed_message.tags = ['smoke', 'positive']
def test_claim_release(self):
"""Release Claim."""
doc = {"ttl": 300, "grace": 100}
result = self.client.post(data=doc)
self.assertEqual(result.status_code, 201)
# Extract claim location and construct the claim URL.
location = result.headers['Location']
url = self.cfg.zaqar.url + location
# Release Claim.
result = self.client.delete(url)
self.assertEqual(result.status_code, 204)
test_claim_release.tags = ['smoke', 'positive']
@ddt.data(10000000000000000000, -100, 1, 59, 43201, -10000000000000000000)
def test_claim_invalid_ttl(self, ttl):
"""Post Claim with invalid TTL.
The request JSON body will have a TTL value
outside the allowed range.Allowed ttl values is
60 <= ttl <= 43200.
"""
doc = {"ttl": ttl, "grace": 100}
result = self.client.post(data=doc)
self.assertEqual(result.status_code, 400)
test_claim_invalid_ttl.tags = ['negative']
@ddt.data(10000000000000000000, -100, 1, 59, 43201, -10000000000000000000)
def test_claim_invalid_grace(self, grace):
"""Post Claim with invalid grace.
The request JSON body will have a grace value
outside the allowed range.Allowed grace values is
60 <= grace <= 43200.
"""
doc = {"ttl": 100, "grace": grace}
result = self.client.post(data=doc)
self.assertEqual(result.status_code, 400)
test_claim_invalid_grace.tags = ['negative']
@ddt.data(0, -100, 30, 10000000000000000000)
def test_claim_invalid_limit(self, grace):
"""Post Claim with invalid limit.
The request url will have a limit outside the allowed range.
Allowed limit values are 0 < limit <= 20(default max).
"""
doc = {"ttl": 100, "grace": grace}
result = self.client.post(data=doc)
self.assertEqual(result.status_code, 400)
test_claim_invalid_limit.tags = ['negative']
@ddt.data(10000000000000000000, -100, 1, 59, 43201, -10000000000000000000)
def test_patch_claim_invalid_ttl(self, ttl):
"""Patch Claim with invalid TTL.
The request JSON body will have a TTL value
outside the allowed range.Allowed ttl values is
60 <= ttl <= 43200.
"""
doc = {"ttl": 100, "grace": 100}
result = self.client.post(data=doc)
self.assertEqual(result.status_code, 201)
# Extract claim location and construct the claim URL.
location = result.headers['Location']
url = self.cfg.zaqar.url + location
# Patch Claim.
doc = {"ttl": ttl}
result = self.client.patch(url, data=doc)
self.assertEqual(result.status_code, 400)
test_patch_claim_invalid_ttl.tags = ['negative']
def test_query_non_existing_claim(self):
"""Query Non Existing Claim."""
path = '/non-existing-claim'
result = self.client.get(path)
self.assertEqual(result.status_code, 404)
test_query_non_existing_claim.tags = ['negative']
def test_patch_non_existing_claim(self):
"""Patch Non Existing Claim."""
path = '/non-existing-claim'
doc = {"ttl": 400}
result = self.client.patch(path, data=doc)
self.assertEqual(result.status_code, 404)
test_patch_non_existing_claim.tags = ['negative']
def test_delete_non_existing_claim(self):
"""Patch Non Existing Claim."""
path = '/non-existing-claim'
result = self.client.delete(path)
self.assertEqual(result.status_code, 204)
test_delete_non_existing_claim.tags = ['negative']
def tearDown(self):
"""Delete Queue after Claim Test."""
super(TestClaims, self).tearDown()
self.client.delete(self.queue_url)
| 32.581227 | 78 | 0.632244 | 8,320 | 0.921884 | 0 | 0 | 8,329 | 0.922881 | 0 | 0 | 2,615 | 0.289751 |
7f95f3f0fe5de4ccd5c5283999bb3a40f5d50004 | 1,889 | py | Python | src/glyphs/utils/StringUtils.py | slorg1/glyphs | db498156897a1406545f041382913e2af69edc12 | [
"MIT"
] | 1 | 2019-05-09T14:35:31.000Z | 2019-05-09T14:35:31.000Z | src/glyphs/utils/StringUtils.py | slorg1/glyphs | db498156897a1406545f041382913e2af69edc12 | [
"MIT"
] | null | null | null | src/glyphs/utils/StringUtils.py | slorg1/glyphs | db498156897a1406545f041382913e2af69edc12 | [
"MIT"
] | 1 | 2019-05-10T16:06:30.000Z | 2019-05-10T16:06:30.000Z | from __future__ import unicode_literals
import six
class StringUtils(object):
"""
Utility class for handling strings.
"""
@staticmethod
def to_unicode(value):
"""
Returns the string representation of the given L{value} if it is not C{None}. Otherwise,
returns C{None}.
@postcondition: (value is None) == (return is None)
@postcondition: return is None or isinstance(return, six.text_type)
"""
return value if value is None else six.text_type(value)
@staticmethod
def to_unicode_not_empty(value):
"""
Returns the string representation of the given L{value} if it is not C{None} and not empty. Otherwise,
returns C{None}
@postcondition: returns is None or isinstance(returns, six.text_type)
"""
return_value = StringUtils.to_unicode(value)
if not return_value:
return None
return return_value
@staticmethod
def to_unicode_not_none(value):
"""
Returns the string representation of the given L{value} if it is not C{None}.
@rtype: six.text_type
@raise ValueError: raises a value error if the given L{value} is {None}
"""
if value is None:
raise ValueError()
return six.text_type(value)
@staticmethod
def to_unicode_not_empty_not_none(value):
"""
Returns the string representation of the given L{value} if it is not C{None} and not empty.
@rtype: six.text_type
@raise ValueError: raises a value error if the given L{value} is {None} or an empty string
"""
return_value = StringUtils.to_unicode_not_empty(value)
if not return_value:
raise ValueError()
return return_value
__slots__ = tuple()
| 26.236111 | 114 | 0.611435 | 1,834 | 0.970884 | 0 | 0 | 1,699 | 0.899418 | 0 | 0 | 1,069 | 0.565908 |
7f971a249f5ab865830322c937e8dd39d7142ad5 | 149 | py | Python | Codeforces Problems/Soldier and bananas/Soldier and Bananas.py | Social-CodePlat/Comptt-Coding-Solutions | 240732e6c1a69e1124064bff4a27a5785a14b021 | [
"MIT"
] | null | null | null | Codeforces Problems/Soldier and bananas/Soldier and Bananas.py | Social-CodePlat/Comptt-Coding-Solutions | 240732e6c1a69e1124064bff4a27a5785a14b021 | [
"MIT"
] | 1 | 2020-10-13T20:57:34.000Z | 2020-10-13T20:57:34.000Z | Codeforces Problems/Soldier and bananas/Soldier and Bananas.py | Social-CodePlat/Comptt-Coding-Solutions | 240732e6c1a69e1124064bff4a27a5785a14b021 | [
"MIT"
] | null | null | null | arr=[int(x) for x in input().split()]
sum=0
for i in range(1,(arr[2]+1)):
sum+=arr[0]*i
if sum<=arr[1]:
print(0)
else:
print(sum-arr[1])
| 16.555556 | 37 | 0.557047 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
7f9732b0483bd520dbc21d4a193f8cf3d1d42f99 | 2,578 | py | Python | ansible/terminal_plugins/aos.py | xwjiang2021/sonic-mgmt | 82c446b9fb016eb070af765aa9d9999e55b27342 | [
"Apache-2.0"
] | 2 | 2021-11-24T09:33:41.000Z | 2021-12-03T09:08:29.000Z | ansible/terminal_plugins/aos.py | xwjiang2021/sonic-mgmt | 82c446b9fb016eb070af765aa9d9999e55b27342 | [
"Apache-2.0"
] | null | null | null | ansible/terminal_plugins/aos.py | xwjiang2021/sonic-mgmt | 82c446b9fb016eb070af765aa9d9999e55b27342 | [
"Apache-2.0"
] | null | null | null | from __future__ import (absolute_import, division, print_function)
__metaclass__ = type
import re
import json
from ansible.plugins.terminal import TerminalBase
from ansible.errors import AnsibleConnectionFailure
from ansible.module_utils._text import to_bytes, to_text
class TerminalModule(TerminalBase):
terminal_stdout_re = [
re.compile(br"[\r\n]?[\w+\-\.:\/\[\]]+(?:\([^\)]+\)){,3}(?:>|#) ?$"),
re.compile(br"\[\w+\@[\w\-\.]+(?: [^\]])\] ?[>#\$] ?$")
]
terminal_stderr_re = [
re.compile(br"% ?Error"),
re.compile(br"% User not present"),
re.compile(br"% ?Bad secret"),
re.compile(br"invalid input", re.I),
re.compile(br"(?:incomplete|ambiguous) command", re.I),
re.compile(br"connection timed out", re.I),
# Strings like this regarding VLANs are not errors
re.compile(br"[^\r\n]+ not found(?! in current VLAN)", re.I),
re.compile(br"'[^']' +returned error code: ?\d+"),
re.compile(br"[^\r\n](?<! shell )\/bin\/(?:ba)?sh"),
re.compile(br"% More than \d+ OSPF instance", re.I),
re.compile(br"% Subnet [0-9a-f.:/]+ overlaps", re.I),
re.compile(br"Maximum number of pending sessions has been reached"),
]
def on_open_shell(self):
pass
def on_become(self, passwd=None):
if self._get_prompt().endswith(b'#'):
return
cmd = {u'command': u'enable'}
if passwd:
cmd[u'prompt'] = to_text(r"[\r\n]?password: $", errors='surrogate_or_strict')
cmd[u'answer'] = passwd
cmd[u'prompt_retry_check'] = True
try:
self._exec_cli_command(to_bytes(json.dumps(cmd), errors='surrogate_or_strict'))
prompt = self._get_prompt()
if prompt is None or not prompt.endswith(b'#'):
raise AnsibleConnectionFailure('failed to elevate privilege to enable mode still at prompt [%s]' % prompt)
except AnsibleConnectionFailure as e:
prompt = self._get_prompt()
raise AnsibleConnectionFailure('unable to elevate privilege to enable mode, at prompt [%s] with error: %s' % (prompt, e.message))
def on_unbecome(self):
prompt = self._get_prompt()
if prompt is None:
# if prompt is None most likely the terminal is hung up at a prompt
return
if b'(config' in prompt:
self._exec_cli_command(b'end')
self._exec_cli_command(b'disable')
elif prompt.endswith(b'#'):
self._exec_cli_command(b'disable')
| 37.362319 | 141 | 0.595035 | 2,304 | 0.893716 | 0 | 0 | 0 | 0 | 0 | 0 | 893 | 0.346393 |
7f9760f0a2fcfb023a35bdea0182735335363c6f | 1,690 | py | Python | day_15-chiton/part_2.py | lucacerone/advent-of-code-2021 | 56c985ec5bbf1b83e74451d795331f4a05d651a3 | [
"MIT"
] | null | null | null | day_15-chiton/part_2.py | lucacerone/advent-of-code-2021 | 56c985ec5bbf1b83e74451d795331f4a05d651a3 | [
"MIT"
] | null | null | null | day_15-chiton/part_2.py | lucacerone/advent-of-code-2021 | 56c985ec5bbf1b83e74451d795331f4a05d651a3 | [
"MIT"
] | null | null | null | from numpy.core.fromnumeric import size
import utils as u
import numpy as np
import heapq as hq
s = """\
1163751742
1381373672
2136511328
3694931569
7463417111
1319128137
1359912421
3125421639
1293138521
2311944581
"""
#cave = np.array([[int(x) for x in l] for l in s.splitlines()])
cave = u.import_data("./data/input")
tile = cave.copy()
nr, nc = cave.shape
for i in range(1,5):
tile = tile+1
tile[tile==10]=1
cave = np.concatenate([cave, tile], axis=1)
tile = cave.copy()
nr, nc = cave.shape
for i in range(1,5):
tile = tile+1
tile[tile>9]=1
cave = np.concatenate([cave, tile], axis=0)
neighbors = lambda pos: u.get_adjacent_coordinates(cave, pos[0], pos[1])
start_point = (0,0)
end_point = cave.shape[0]-1, cave.shape[1]-1
"""
Represent the cave matrix as a graph. We define the graph as a dictionary,
an entry of which looks like
graph[v0] = [(v1, d1), (v2, d2)]
indicating that there is an edge between v0 and v1 with d1 distance, and an edge between v0 and v2 with d2 distance
"""
graph = {(i,j): [(n, cave[n]) for n in neighbors((i,j))] for i in range(cave.shape[0]) for j in range(cave.shape[1])}
visited = set()
costs = {v: np.Inf for v in graph}
costs[start_point] = 0
queue = [(costs[start_point], start_point)]
while queue:
current_cost , current_node = hq.heappop(queue)
#if current_node in visited:
# continue
for neigh,d in graph[current_node]:
if neigh not in visited:
new_cost = costs[current_node] + d
if new_cost < costs[neigh]:
costs[neigh] = new_cost
hq.heappush(queue, (new_cost, neigh))
visited.add(current_node)
print(costs[end_point])
| 21.948052 | 117 | 0.661538 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 506 | 0.299408 |
7f977804ee14ad26b5e5c54480ba5ea17221d8c5 | 1,861 | py | Python | aws-pentesting-with-python/kms/correct/updating_existing_kms.py | qodirovshohijahon/python-scripting | 08f8492e137df37e7f9b41e9ee546f5783501c1a | [
"CNRI-Python"
] | null | null | null | aws-pentesting-with-python/kms/correct/updating_existing_kms.py | qodirovshohijahon/python-scripting | 08f8492e137df37e7f9b41e9ee546f5783501c1a | [
"CNRI-Python"
] | null | null | null | aws-pentesting-with-python/kms/correct/updating_existing_kms.py | qodirovshohijahon/python-scripting | 08f8492e137df37e7f9b41e9ee546f5783501c1a | [
"CNRI-Python"
] | null | null | null | from xmlrpc.client import Boolean
import boto3
import logging
from datetime import date, datetime
from botocore.exceptions import ClientError
import json
from json_datetime_serializer import json_datetime_serializer
from kms_client import kmsClient
from search_kms_using_account_id import search_kms_using_account_id
from get_arn import get_arn
logger = logging.getLogger()
logging.basicConfig(level=logging.INFO,
format='%(asctime)s: %(levelname)s: %(message)s')
# mrk-8b618d3b5c1d432aad977f31b29df64b
# 862638055046
def update_kms_key_policy(target_arn, key_id):
client = kmsClient()
kms_policy_data = client.get_key_policy(KeyId=key_id,PolicyName='default')
kms_policy = json.loads(kms_policy_data["Policy"])
policy_update = Boolean(False)
for statement in kms_policy["Statement"]:
if "Allow use of the key" in statement["Sid"]:
if target_arn not in statement['Principal']['AWS']:
if type(statement['Principal']['AWS']) is list:
statement['Principal']['AWS'].append(target_arn)
statement['Principal']['AWS'].sort()
policy_update = True
else:
print('Target ARN already exists in the policy')
policy_update = False
if policy_update:
response = client.put_key_policy(
KeyId=key_id,
PolicyName='default',
Policy=json.dumps(kms_policy)
)
print(response)
return kms_policy
if __name__ == '__main__':
ARN = 'arn:aws:iam::862638055046:user/test-user'
print(f"Arn: {ARN}")
kms = update_kms_key_policy(ARN)
logger.info('Getting information about KMS key...')
logger.info(
f'Key Details: {json.dumps(kms, indent=4, default=json_datetime_serializer)}'
)
logger.info('Done!')
| 33.836364 | 85 | 0.667383 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 449 | 0.241268 |