content stringlengths 35 762k | sha1 stringlengths 40 40 | id int64 0 3.66M |
|---|---|---|
def instancemethod(f):
"""Decorator to indicate that the method is a method of an instance rather than
a model."""
@wraps(f)
def f_wrapped(self, *args, **kw_args):
if not self.instantiated:
# Attempt to automatically instantiate.
self = self()
return f(self, *arg... | a0f5e6eb65df69809d02e217e0f37cbc81734c51 | 3,607,200 |
def _principal_from_token(token):
"""Determine a principal from a JWT
Args:
token: The JWT
Returns:
Brewtils principal if JWT is valid, None otherwise
"""
try:
decoded = jwt.decode(
token,
key=brew_view.config.auth.token.secret,
algorithm... | df908c5d5186f035c8e2fc26bcf1ef1eeccb4f17 | 3,607,201 |
def email_attendees(request, slug):
"""Send email to event attendees."""
event = get_object_or_404(Event, slug=slug)
attendees = event.attendees.all()
if request.method == 'POST':
email_form = EmailUsersForm(attendees, request.POST)
if email_form.is_valid():
statsd.incr('eve... | 4c7731e619aba6952bd2767a52ab47dc82ebe0ec | 3,607,202 |
from typing import Tuple
from typing import Union
def json_types(max_size: int = 5, *, max_leaves: int = 25) -> st.SearchStrategy:
"""
Return a recursive stategie for generating JSON type-hints inputs
Arguments:
max_size: maximum size of the lists and dicts created
max_leaves: maximum num... | f6108973a7cb8818a390a3ba4ac1f08b6cc83390 | 3,607,203 |
def one(n = 10):
"""
a strange function with an ambiguous name
Parameters
----------
:param n: int
the number of points to test
"""
sum = 0.0
for i in range(n):
denom = 1.0
sum += 1/n
return sum | 2b8ce5aa198ad1139165fbabf02b89f2d9f7cf73 | 3,607,204 |
def SInverse(box, output):
"""Apply S-box number 'box' in reverse to 4-bit bitstring 'output' and
return a 4-bit bitstring (the input) as the result."""
return SBoxBitstringInverse[box%8][output] | ad33cbb10ce7db13710d3beb62e97ac063e45f84 | 3,607,205 |
import subprocess
def perform_auth_restart():
"""When called this will perform an authorized restart. Before trying
to perform an authorized restart it checks to see if the machine supports
the feature. If supported it will then look for the defined plist containing
a key called RecoveryKey. It will u... | 14adfed73be67b136751f99dcc4018ea13dcd9e7 | 3,607,206 |
from typing import Dict
def exposure(population: np.ndarray = None) -> Dict[int, int]:
"""Returns dict of index: count of individuals
Args:
population (np.ndarray): the population
Returns:
Dict[int, int]: key is index, value is count of lineup
Examples:
>>> fittest_populatio... | 55d112b049efdb9982d26dbd92d423e6adfb12d7 | 3,607,207 |
def allcorner(samples, labels, axes, weights=None, span=None,
smooth=0.02, color="grey", qcolor=None, show_titles=False,
hist_kwargs={"alpha": 0.5, "histtype": "stepfilled"},
hist2d_kwargs={}, max_n_ticks=3,
label_kwargs={"fontsize": 12}, tick_kwargs={"labelsize":... | 885f14994508e822892d139874da8582b1f7bee1 | 3,607,208 |
def PersistentPickler(persistent_id, *args, **kwargs):
"""
Returns a :class:`Pickler` that will use the given ``persistent_id``
to get persistent IDs. The remainder of the arguments are passed to the
Pickler itself.
This covers the differences between Python 2 and 3 and PyPy/zodbpickle.
"""
... | 114a6a6454005336ecdad89b2b26605fc58b4e3e | 3,607,209 |
def isFactGroup(arg: str) -> bool:
"""Function to determine whether a string is a registered fact group
"""
if arg in RegisteredFactGroups.keys():
return True
return False | 2a6511d25aa8c6f95ba4f92362cb14cb36a8c20d | 3,607,210 |
def infection_rate_asymptomatic_self_30():
"""
Real Name: b'infection rate asymptomatic self 30'
Original Eqn: b'Infected asymptomatic 30*Susceptible 30*contact infectivity asymptomatic self 30*(social distancing policy SWITCH self 30\\\\ *social distancing policy 30+(1-social distancing policy SWITCH self ... | 9c837aac9d5b01d226d0615b38e89d39cfba7be6 | 3,607,211 |
from typing import Tuple
import torch
from typing import List
def long_tensor_2d(shape: Tuple[int, int], fill_value: int = 0) -> torch.Tensor:
"""Return a new 2d torch.LongTensor with size according to shape.
The values of this tensor will be fill_value."""
outer = torch.jit.annotate(List[List[int]], [])
... | c1aaeb01058b9153c31e911f31eae6217f03eb64 | 3,607,212 |
def five_twos_simple():
"""Five Twos going only left to right, operations: +-*/^"""
global N
N = []
global S
S = []
def five_twos_inner(val,sq,depth):
if depth == 5:
if int(val) == val and val >= 0:
N.append(int(val))
S.appen... | 38aeea1d325f7db6975d13411c3958bbe4ee6d1c | 3,607,213 |
def _pad_digits(text: str) -> str:
"""A str method with hacks to support better lexicographic ordering.
The output strings are not intended to be human readable.
The returned string will have digit-runs zero-padded up to at least 8
digits. That way, instead of 'a10' coming before 'a2', 'a000010' will ... | 7e842669747919a3bbc9fd40e45a4bfc7641cc3a | 3,607,214 |
from typing import List
def get_missing_settings(settings_class) -> List[str]:
"""Used to validate required settings.
Verifies that all attributes which don't start with ``_`` and aren't named
in ``_optional_settings`` are not set to None.
Args:
settings_class: The global settings class to v... | efbb2dc3078fc5221e8ce327b078d42eff167d65 | 3,607,215 |
def generate_coverage_config(args): # type: (TestConfig) -> str
"""Generate code coverage configuration for tests."""
if data_context().content.collection:
coverage_config = generate_collection_coverage_config(args)
else:
coverage_config = generate_ansible_coverage_config()
return cove... | 276058105dfae112e5f8908fbd297ae8203909df | 3,607,216 |
def _check_equal_list(iterator):
""" Check that all elements in list are equal """
return len(set(iterator)) <= 1 | 94bd94a203819965d95105e7f978ecb496ce97bc | 3,607,217 |
import re
def error_052_category_in_article(text):
"""Fix all wrong categories and return (new_text, fixed_errors_count) tuple."""
ignore_filter = re.compile(r"""(
<noinclude>.*?</noinclude>|
<onlyinclude>.*?</onlyinclude>|
<includeonly>.*?</includeonly>
)""", re.I | re.DOTALL | re... | 1d21a2e49b0a3684a54ad0c0d4153fe771b9f4f7 | 3,607,218 |
import hashlib
import os
def calc_firmware_sha(file):
"""
Open firmware image file and calculate file size
Pad file size to a multiple of 64 bytes
Calculate SHA256 hash of the padded contents
"""
with open(file, 'rb') as firmware:
firmware.seek(0, 2)
size = firmware.tell()
... | 17e0ce8c6c8d2e8cdb5b9bc259087bc4677924ca | 3,607,219 |
from typing import Dict
from typing import Any
def format_date_and_target(
df_input: pd.DataFrame,
date_col: str,
target_col: str,
config: Dict[Any, Any],
load_options: Dict[Any, Any],
) -> pd.DataFrame:
"""Formats date and target columns of input dataframe.
Parameters
----------
... | a610da8098f54fda4a17dba000498249056aa7fa | 3,607,220 |
import json
def diagnose(message_value):
"""
do diagnose based on message's value
Args:
message_value (dict): info of diagnose. e.g.:
{
"username": "admin",
"host_id": "host1",
"tree_name": "tree2",
"tree_content": {}
... | db207230d7e275cf13cab096e4a277f9ee724090 | 3,607,221 |
def standard_timeseries_reader(*args, **kwargs):
"""
Wrapper for :any:`standard_time_series_reader`
"""
return standard_time_series_reader(*args, **kwargs) | 254e7a63619a649cd327bc8cf4d0506e45a6e42b | 3,607,222 |
def jam_solver(graph, loads, timeout=None):
""" an ensemble solver for the routing problem.
:param graph network available for routing.
:param loads: dictionary with load id and preferred route. Example:
loads = {1: [1, 2, 3], 2: [3, 2, 1]}
:param timeout: None, float or int timeout in millis... | ddc6cfab546f2c8aa531b1568495d05591580076 | 3,607,223 |
def save_plot(code, elem):
"""Converts matplotlib plots to tikz code.
If elem has either the plt attribute (format: plt=width,height) or the
attributes width=width and/or height=height, the figurewidth and -height
are set accordingly. If none are given, a height of 4cm and a width of 6cm
is used as... | 8d2f2ecb6b750eff98d1e17ce553f1613d411216 | 3,607,224 |
import re
def createCogList(args):
"""Returns an Autovivification of the COGs in the MLTreeMap COG list file, and a list of output text precursors based on the analysis type."""
cog_list = Autovivify()
text_of_analysis_type = Autovivify()
alignment_set = args.reftree
kind_of_cog = ''
# F... | 4c80ed3078af52afe20e44f568cacf06cbcbabd7 | 3,607,225 |
def _load_permissions_from_database(user):
"""Calculate permissions based on DB queries"""
permissions = {}
with benchmark("load_permissions > load default permissions"):
load_default_permissions(permissions)
with benchmark("load_permissions > load bootstrap admins"):
load_bootstrap_admin(user, permi... | e9568d124eb8df73dbfc5d09223639ecca62bb5a | 3,607,226 |
def get_valuation_method(item_code):
"""get valuation method from item or default"""
val_method = frappe.db.get_value('Item', item_code, 'valuation_method')
if not val_method:
val_method = frappe.db.get_value(None, "valuation_method") or "FIFO"
return val_method | 974812dd4fbeb1aac28186347c8aadba5a103391 | 3,607,227 |
import os
def write(solution, output_filename='', path='',
skip_thermo=False, skip_transport=False
):
"""Writes Cantera solution object to Chemkin-format file.
Parameters
----------
solution : cantera.Solution
Model to be written
output_filename : str, optional
... | a10e73efbdf2549a543d20e20f07e847ab37ee95 | 3,607,228 |
def find_layer(model, layer_class):
"""
Find all layers in model that are instances of layer_class
"""
layers = []
for layer in model.layers:
if isinstance(layer, layer_class):
layers.append(layer)
elif hasattr(layer, "layers"):
# search in nested layers
... | d240d916f26e087edb7ccef8006b91b9c539bd76 | 3,607,229 |
from aoikprojectstarter.mediator import main_wrap
def main(args=None):
"""
Program main function.
This function does three things:
- Prepare `sys.path` so that program users do not need set up PYTHONPATH.
- Check whether dependency packages have been installed.
- Call the mediator module t... | f821f35781dd9d18a32eab0d7fb3ddc874ef572e | 3,607,230 |
def create(customer: schema.CustomerCreate, db=Depends(get_db)):
"""
create a new customer
a new customer is always active by default
:param customer:the new customer to create
:param db: database session (injected)
:return: the new customer with is id
"""
customer_db = model.Customer(... | 8ac398eaea5bb14a246d3bfc3e2c33a5c23c20e1 | 3,607,231 |
import os
def pid():
"""
Returns the pid of the rethinkdb server.
"""
db_pid = None
if os.path.exists(conf.get('db_pid')):
with open(conf.get('db_pid')) as fin:
db_pid = int(fin.readline())
return db_pid | 1c3b41e5f841b4d148472eaf90ec5f5022a3e2fc | 3,607,232 |
from typing import Dict
from typing import Any
import logging
def _search_dashboard(*, search_term: str, page_index: int, search_type: str) -> Dict[str, Any]:
"""
Call the search service endpoint and return matching results
Search service logic defined here:
https://github.com/lyft/amundsensearchlibra... | 84472de88914696e8ff3fffe4d1687526b626a3a | 3,607,233 |
def __bestMatch__(matches, # list
negMass, # float
pmz, # pandas.Series
negRT, # float
prt, # pandas.Series
parameters # LFParameters
):
# type: (...) -> int
"""Return the index of 'ma... | 75650f8dddbae46066d37d829f5cbc30cf91eae8 | 3,607,234 |
def patch_goods(goods):
""" Updates or creates a goods """
req = request.get_json()
if goods in stock:
for k, v in req.items():
stock[goods][k] = v
res = make_response(jsonify({"message": "goods updated"}), 200)
return res
stock[goods] = req
res = make_response(jsonify({"message": "goods created"}), 201)
... | 3d6577b25b975e000961dd5748d2757379bec829 | 3,607,235 |
import importlib
def connect(settings):
"""
Connect to a database.
"""
driver = importlib.import_module(settings.pop("driver", "sqlite3"))
return driver.connect(**settings) | cd186b3210b1ec012539dfc4a5306834dc9bf058 | 3,607,236 |
def count_reads_per_sample(file):
""" Count the reads for each sample from the original fasta file """
samples={}
for line in catch_open(file):
if line.startswith(">"):
try:
sample, read = line.replace(">","").split(SAMPLE_READ_DELIMITER)
except ValueError:
... | 114b1ff9a010b84d39600c32ea6fe5aa61941d42 | 3,607,237 |
def user_model(username):
"""Return a user model"""
return {
'username': username,
'scope': 'basic',
} | c629dbca8673eb740b1fddcfcddb588930cb1fa9 | 3,607,238 |
def check_norm_state(modules, train_state):
"""Check if norm layer is in correct train state."""
for mod in modules:
if isinstance(mod, _BatchNorm):
if mod.training != train_state:
return False
return True | 82387d78a53c5435bed25da542fbef9a68d6a785 | 3,607,239 |
def getJ1939ProtocolDescription(protocol : int) -> str:
"""
Returns a description of the protocol selected with protocol arg.
Feed the result of RP1210Config.getJ1939FormatsSupported() into this function to get a description of what
the format means.
Honestly, I don't see anyone ever using thi... | a52c48930d45c04f0570689620d2b01783f27e38 | 3,607,240 |
import json
import subprocess
def nvme_id_ctrl(device):
"""Identify controller."""
command = "sudo nvme id-ctrl {0} -o json".format(device)
id_ctrl = json.loads(
subprocess.run(
command, shell=True, check=True, text=True, capture_output=True
).stdout
)
return id_ctrl | 40d739bb00b474cf27d0839fe421ec39a324c7ed | 3,607,241 |
def parse_images(images):
"""
Parses list of available images into Image objects.
Arguments:
images : dictionary of images
Returns:
parsed_images : dictionary of parsed images
"""
parsed_images = {}
for image_name, image_info in images.items():
name = image_info["Na... | e56651093f7f983bb3dfbe8d9ea6f890b5a969b6 | 3,607,242 |
def in_region(pos, regions):
"""Find whether a position is included in a region.
Parameters
----------
pos : int
DNA base position.
regions : list of tuples
List of (start, end) position integers.
Returns
-------
bool
True if the position is within an of the reg... | 07154584fe3fadf93f16bf858810e4484828eb31 | 3,607,243 |
def extract_products_as_tuple(dataset):
"""Return names of all products as a sorted tuple.
Products are chosen using ``allocatable_production``."""
return tuple(sorted([exc['name'] for exc in allocatable_production(dataset)])) | 60ef29347312931b1dc44789cda85e2e6246d7cf | 3,607,244 |
import sys
def _implementation_version():
"""Return implementation version."""
return ''.join(map(str, sys.version_info[:2])) | ccc6150871b0efcf6cd9281c5297cd53483ab307 | 3,607,245 |
def _hue_process_transition_time(transition_seconds):
""" Transition time is in 1/10th seconds
and cannot exceed MAX_TRANSITION_TIME. """
# Max transition time for Hue is 900 seconds/15 minutes
return min(9000, transition_seconds * 10) | 69f822d2836fef91206e2845d6d3bbd7623c03fc | 3,607,246 |
import base64
def add_tasks(taskq_service, task_dict):
"""
Allow readding of multiple tasks across multiple queues.
The task_dict is a dictionary with tasks for each queue, keyed by queue
name.
Tasks themselves can be dicts like those received from GetTasks() or Task
instances.
:param tas... | a834bfb52da4a5602f10bd3bed223457e8d046c1 | 3,607,247 |
def SEQ2HP(seq, HP_dic, occ=[], nuc_type=[], T=0):
"""
Given sequence, dictionary of HP(e.g. {A-A: [HP], oct: [HP...HP],...}), occupancy(e.g. [1, 500 , 789]), nucleosome type at each occupancy(e.g. ['oct','tet','hex']), and temperature.
Return the HPs associate with the given sequence.
"""
seqstep =... | 026bf83ae472e92ed449cf6d4d53ba1afae3b941 | 3,607,248 |
def _get_observations(token, transmart_url, study, concept_path):
"""
Given full concept path (as returned from tm 1.2 rest-api /concepts) return dict
of patient_id : value
:param token:
:param transmart_url:
:param study:
:param concept_path:
:return:
"""
obs = {}
conce... | 32956aa2b7c7dd03dd053745e3e18e13a9f833c5 | 3,607,249 |
def _get_jitclass_for_dtype(dtype, upper):
"""
Get the correct jitclass of NbTriMatrixBase for the data type and triangle.
"""
if upper:
return _UPPER_JITCLASS_BY_TYPE[dtype]
else:
return _LOWER_JITCLASS_BY_TYPE[dtype] | 3446028aaf0553200c51196e717f06c2ac91abfc | 3,607,250 |
def parseLibraryLogicData(data, srcFile="?"):
"""Parses the data of a library logic file."""
if len(data) < 9:
printExit("Library logic file {} is missing required fields (len = {} < 9)".format(srcFile, len(data)))
versionString = data[0]["MinimumRequiredVersion"]
scheduleName = data[... | f9983d00252a88bfb7e3371450ac3879460da244 | 3,607,251 |
def get_catalog() -> dict:
"""Returns the catalog of to be tested algorithms, input and output.
:return: **TODO: TBD**
"""
input_file_paths = get_input_file_paths()
return {
'copy': [(input_file_paths[0], 'sha256:015d60fac720421198c39bc637e25435188085d83911e790e734fb2bfdc99032'),
... | 34282db296dd3d65805a02cd48abd7924e116cb2 | 3,607,252 |
def _add_replication(bucket_name: str, study_id: str):
"""
Configures a second bucket with `-dr` suffix and replicates the primary
bucket to it.
Adds a lifecycle policy to the dr bucket to immediately roll data into
glacier for cold storage
"""
if not settings.FEAT_STUDY_BUCKETS_REPLICATION_... | afbb5e7a9490906988dc5115eb3b59b54f2bd98c | 3,607,253 |
def main_top():
""" Present the top menu page """
return render_template("main.html") | e0ca4bc2e89cc9e4aab6c1ffc3ffcfc51cdbc8af | 3,607,254 |
def extract_kpt_vectors_dense(tensor, kpts_t):
"""
Dense version of get_entries.
:param tensor: Tensor to extract from [b, c, h, w]
:param kpts_t: Tensor with indexes (x, y) in channels as [b, 2, h, w]
:return: Tensor entries as [b, c, h, w]
"""
b, c, h, w = tensor.shape
kpts = kpts_t.v... | 9c62e13e0373ea91bed4b9d8bbcaabe9b1164f04 | 3,607,255 |
def bow(s: np.ndarray) -> str:
"""
Converts array to bag of words string (this is how we represent a sparse state into a pandas table).
@param s: word counts over vocabulary
@return: string representation
"""
i, = np.where(s > 0)
return ':'.join(map(str, i)) | 4389b86bfd047753939a5300ca567dee6fec350b | 3,607,256 |
def getTestSuite(select="unit"):
"""
Get test suite
select is one of the following:
"unit" return suite of unit tests only
"component" return suite of unit and component tests
"all" return suite of unit, component and integration tests
"pending" ... | 5b2dc4ee5e35ce06094c658f3555b251226821c9 | 3,607,257 |
def main():
"""Does the job"""
keep = True
photos = request_photos()
page = 1
t = False
while keep is True:
p = next(photos, False)
if p is False:
photos = request_photos(page + 1)
continue
trial = Photo.objects(flickr=p["id"]).first()
p... | 428dba0ea0b1e52d4f63e2a9adff9a3d583ca95d | 3,607,258 |
def length_average_f(x_arr, f_arr, Lx, dx=0):
""" Take length average of f(x) with respect to x (from x[0] to x[-1]).
Numerical integration is performed using trapezoidal rule.
"""
Nx = size(f_arr)
if dx>0:
return (dx/Lx)*(sum(f_arr) - 0.5*(f_arr[0] + f_arr[-1]))
else:
re = 0. ... | 086a50259bb762b0023c7aaaefa68e159d72a27b | 3,607,259 |
import re
def re_sub_replace(pattern,string,repace_symbols=('-','_'),group_name=1):
"""
当re.sub(pattern,repl,string)内置的repl = "g<1>" 不能满足替换需求的时候,
比如需要将group目标内的文字中的某个符号替换掉, 使用的时候要注意替换代码内的sub replace符号
:param pattern : re pattern
:param string : original string
"""
def replace_match(match... | 7a6b2f27ce73f6c8b316ab424362eb8383fff273 | 3,607,260 |
def generate_hgvs(prefix: str = "c") -> str:
"""Generates a random hgvs string from a small sample."""
if prefix == "p":
# Subset of 3-letter codes, chosen at random.
amino_acids = [
"Ala",
"Leu",
"Gly",
"Val",
"Tyr",
"Met",... | 3a18afbe5687d1566d9994866771ae8b91367460 | 3,607,261 |
import six
def zero_lpad(number, length):
"""
Fill 0 on the left of number
:param number: number to be padded
:param length: length of result string
:return:
"""
if six.PY3:
return str(number).ljust(length, '0')
return '{number:0>{length}}'.format(number=number, length=length) | d8682249a7094e2c0de9ff015df3c1c7525b7427 | 3,607,262 |
import logging
import sys
def get_handler():
"""
Gets the handler to manage the output of the logger, default: stdout
"""
handler = logging.StreamHandler(sys.stdout)
# TODO: read from a config file, or env var, and override the default formatter.
# IE: logging.FileHandler(filename='/path/to/fi... | 99e3972433665a4c91b92e3418f0f233771971ab | 3,607,263 |
import sys
def _normalize_docstring(docstring):
"""Normalizes the docstring.
Replaces tabs with spaces, removes leading and trailing blanks lines, and
removes any indentation.
Copied from PEP-257:
https://www.python.org/dev/peps/pep-0257/#handling-docstring-indentation
Args:
docstri... | 1f362835e59d32c883a373e4c49ddb10729e55eb | 3,607,264 |
def _len_guards(M: int) -> bool:
"""Handle small or incorrect window lengths"""
if int(M) != M or M < 0:
raise ValueError('Window length M must be a non-negative integer')
return M <= 1 | 1a181779821570edea6eb08739fd9065de445e80 | 3,607,265 |
def get_files(dataset_name):
"""Retrieve list of files in `dataset_name`.
Arguments:
- `dataset_name`: name of the dataset
"""
data = das_client(("file dataset={0:s} system=dbs3 detail=True | "+
"grep file.name, file.nevents > 0").format(dataset_name),
... | 55c389b28b488e3d1b221fd0156463fbf7b05752 | 3,607,266 |
def line0(x,a):
"""
Straight line through origin: a*x
Parameters
----------
x : float or array_like of floats
independent variable
a : float
first parameter
Returns
-------
float
function value(s)
"""
return a*x | 247a9ac56418ec34089bab0d9a914c69eb216f31 | 3,607,267 |
def score_nxgraphs(nx_graphs, truth, verbose=False):
"""nx_graphs: a list of networkx graphs, with node feature hit_id
each graph is a track"""
total_tracks = len(nx_graphs)
new_df = graphs_to_df(nx_graphs)
matched = truth.merge(new_df, on='hit_id', how='inner')
tot_truth_weight = np.sum(matche... | c5f67bbd7cac7e023cada56f02e7601762a64259 | 3,607,268 |
import os
def load_lena():
"""Function to read lena image from resources
directory.
Returns:
Loaded lena image as uint8 NumPy array.
"""
dir_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'resources')
lena_path = os.path.join(dir_path, 'lena.jpeg')
return cv2.im... | 3fb6e648fee775a53390ebb91b5bfa1596aabd46 | 3,607,269 |
import sys
def blur_filter(img_name, filter_type, kernel_size=3):
"""
ぼかしフィルタ
Parameters
----------
img_name : numpy.ndarray
入力画像
filter_type : str
フィルタのタイプ
average, gauss
kernel_size : int
カーネルのサイズ
Return
-------
blur_img : numpy.ndarray
... | bd6cb347afd311311249100b1c28f4bef4b4bf9b | 3,607,270 |
from app.main import main
from app.auth import auth
def create_app(config_name):
"""
creates an instances of the application
and passes the config name, i.e development
or production, the will then pick the environments
from the configuration classes in config
"""
app = Flask(__name__)
... | 5e44acddb66fac44dc03da49ec695de161e3b5c2 | 3,607,271 |
def pushCategory(category):
"""Used to insert a new category to the table
Returns the ID of the pushed Category
----FOR INTERNAL USE ONLY----"""
queryString="INSERT INTO Categories(Category_Name) VALUES('%s')" % category
cur=executeQueryWithHandling(queryString)
print "%s categeory pushed!"... | d2a4edbf48e68056ceedfc4b2d1caec41d718cdd | 3,607,272 |
import os
def drawbot():
"""Shows drawbot status and functions."""
form = PgUploadForm()
if form.validate_on_submit():
file = request.files.get('file')
if file:
filename = secure_filename(form.file.data.filename)
file.save(os.path.join(current_app.config['APP_DIR'],... | 27f341887521450c4642b0043fe6532d1505f9d9 | 3,607,273 |
import os
def load_data(datapath=None,
survey="LSMS",
country="uganda",
standardize=True,
permute=False,
seed=42):
"""Load satellite imagery features and survey targets.
Args:
datapath : str or None (default: None)
country ... | 0f59b8daae5d6fd0d6080822d396b4218fb0d02f | 3,607,274 |
def neutralize(row_vectors: pd.DataFrame) -> pd.DataFrame:
"""
Orthogonally project row vectors onto subspace orthogonal to all ones.
(In other words, we demean each row).
If the rows of `row_vectors` represent dollar positions, then this operation
will dollar neutralize each row.
:param row_... | 2ab08d21929c6e9c38f7b3d261f2e3be8e4a191a | 3,607,275 |
import os
import sys
import json
def main(args):
"""
Main entry point for program
:param args: command line arguments usually :py:const:`sys.argv`
:return: 0 for success otherwise failure
:rtype: int
"""
desc = """
Running gene enrichment against Integrated Query
Takes fi... | 32eec64154f873027ace063300b6415ff493acc1 | 3,607,276 |
def create_validator(contract, force_optional=False):
"""
Factory pattern for creating custom validator in the style
of WTForms. This function takes the contract needed to validate
against and returns a ``Form`` object that can perform
the validation according to validation rules in the contract.
... | ca5208ad16e5d52aab58beedf514018eef6edc34 | 3,607,277 |
def get_state(obj):
"""Return a State object given an object. Useful for testing."""
str = dumps(obj)
return StateUnpickler(BytesIO(str)).load() | ca690595810feb313eacd2c7c4d7ffc100214b4a | 3,607,278 |
import os
import shlex
def read(fname):
""" Read and process a RESPY initialization file.
"""
# Check input
assert os.path.exists(fname)
# Initialization
dict_, group = {}, None
with open(fname) as in_file:
for line in in_file.readlines():
# Split line
l... | 0775987bbc2e34fb9d545a00af35513749b80ecc | 3,607,279 |
def median(image):
"""The median pixel value"""
return np.median(image) | 16c50e1d3869847136365a2f654bdd14af4412dc | 3,607,280 |
def list_ecriture_tag(db, ecriture_id=None):
""" List ecriture for tag """
filter = {}
filter = App.get_filter(request.query.filter)
sort = App.get_sort(request.query.sort)
tags = db.query(EcritureTag.id,
Tag.nom,
Tag.valeur,
EcritureTag.... | adc470a24fb56715b4e500c32b325ac19e66f8bf | 3,607,281 |
def wishlist(request, template="shop/wishlist.html",
form_class=AddProductForm, extra_context=None):
"""
Display the wishlist and handle removing items from the wishlist and
adding them to the cart.
"""
if not settings.SHOP_USE_WISHLIST:
raise Http404
skus = request.wishli... | 9fa770098227d26cb75a06a5691284b6d9cb3816 | 3,607,282 |
import logging
def _GolintFile(path, _, debug):
"""Returns result of running golint on |path|."""
# Try using golint if it exists.
try:
cmd = ['golint', '-set_exit_status', path]
return _LinterRunCommand(cmd, debug)
except cros_build_lib.RunCommandError:
logging.notice('Install golint for addition... | 25d8d21ea6281c232e3b7c37f348e77d20ffb42e | 3,607,283 |
def classic_mode_cpcs(request, hmc_session): # noqa: F811
# pylint: disable=redefined-outer-name,unused-argument
"""
Pytest fixture representing the set of CPCs in classic mode, from the set of
all CPCs defined in the HMC definition file.
Because the `hmc_session` parameter of this fixture is agai... | 2ba0496573463f8b554e1ecbe57876e63ffce9da | 3,607,284 |
import json
def to_json(msg):
"""Pretty-print a dict as a JSON string
Use Unicode and 2-space indents.
"""
return json.dumps(msg, ensure_ascii=False, indent=2) | e10bf04ce54482f1892aa7a7452a7004024ea6d4 | 3,607,285 |
def get_sorted_index(array, reverse_order=False):
"""
get the order of the index of a one dimensions array
@reverse_order: True, large->small
False, small->large
"""
dtype = [('index', 'i4'), ('value', 'f8')]
data = np.array([(i, array[i]) for i in range(len(array))], dtype ... | a4690583a7973f08873f086a126fa859a6514a4a | 3,607,286 |
def show_saved_playlist():
""" Displays list of saved playlists """
playlists = crud.get_saved_playlists(crud.get_user_by_email(session['EMAIL']).user_id)
playlist_ids = crud.get_user_playlist_ids(crud.get_user_by_email(session['EMAIL']).user_id)
playlists_and_playlist_ids = helper.create_dict_playlist... | 59945734789c5feeb3c3080562b2aee27b716d8e | 3,607,287 |
def get_scores(events):
"""
{game_id : quarter, secs, a_pts, h_pts, status}
"""
ids = u.get_ids(events)
links = [bm.BOV_SCORES_URL + game_id for game_id in ids]
raw = g.reqs_json(links)
scores_dict = {g_id: score(j) for g_id, j in raw.items()}
return scores_dict | 8b0dbda56f275302488f4062a0ece44bf9e49343 | 3,607,288 |
def read_style_dict(cfg):
"""Return dict of styles read from config dict.
Sections in style file are set as top-level keys of the returned dict.
"""
style = {}
# update all settings with any global settings.
if 'global' in cfg:
cfg_global = cfg.pop('global')
for rc_dict in style... | cbbbb4f68e71fa82f028cc512698184a45c88cc8 | 3,607,289 |
import math
import logging
import time
def wait_on_app(port):
""" Waits for the application hosted on this machine, on the given port,
to respond to HTTP requests.
Args:
port: Port where app is hosted on the local machine
Returns:
True on success, False otherwise
"""
retries = math.ceil(START... | 04e6150fe4ff5e889df79367098a9ef9b3aaf3cd | 3,607,290 |
def get_min_and_max_velocity_values(velocities) :
""" Повертає min та max значення швидкості у вигляді кортежу """
return (velocities.min(), velocities.max()) | f9a2995bec07d129c34581d55a070a4004b8436c | 3,607,291 |
import nipype.interfaces.utility as util
def process_segment_map(wf_name,
use_ants,
use_priors,
use_threshold,
use_erosion):
"""This is a sub workflow used inside segmentation workflow to process
probability maps o... | 1c50f7986de367ff56b147107be456ba571a959d | 3,607,292 |
from typing import Iterable
def get_needed_vars(*entries: str) -> Iterable[str]:
""" Parses all used variables from a string """
results = set()
for entry in entries:
variables = VARIABLE_IDENTIFIER.findall(entry) # will return tuples: (with surrounding %s, without)
results.update([match[... | 725414ad843da47cf76daf35606cf95cc694db1f | 3,607,293 |
def shape(a):
"""the shape of a matrix"""
_rows = len(a)
_cols = len(a[0]) if a else 0
return _rows, _cols | 79c32a5f09ecbea4849929a3f6f627068198953f | 3,607,294 |
def read_txt_file(file, is_list):
"""
@summary - read from a test file.
@description - method will read from a text file and either return it
as a string or a list.
If is_list is True the delimiter that will split the
text file apart is ';' and '... | cad2d80c107f165cb55b23cb71f88c228146e475 | 3,607,295 |
import os
import json
import tqdm
def read_examples_from_file(data_dir, mode, task_type):
"""Read a SQuAD json file into a list of SquadExample."""
assert mode in ['train', 'dev']
if task_type == "squad2":
input_file = os.path.join(data_dir, f"{mode}-v2.0.json")
elif task_type=="squad":
... | c8d319ee0464744f7edadde4a6ec7dd95af965d5 | 3,607,296 |
def compare_dictionaries(dict1, dict2):
"""
Recursively compare two dictionaries.
:return: True if exactly the same, False if not
"""
if len(dict1) != len(dict2):
return False
for key in dict1:
try:
val1, val2 = dict1[key], dict2[key]
if val1 != val2: #... | c700874e6a1f7c0911607675570a750279c47616 | 3,607,297 |
def Table(*args, **kw):
"""A schema.Table wrapper/hook for dialect-specific tweaks."""
test_opts = {k: kw.pop(k) for k in list(kw) if k.startswith("test_")}
kw.update(table_options)
if exclusions.against(config._current, "mysql"):
if (
"mysql_engine" not in kw
and "mys... | 70928cfcb77bd21dda090043b657eded4fe0b00a | 3,607,298 |
import logging
def deploy_model(bigquery_client: bigquery.Client,
model_id: str,
machine_type: str = 'n1-standard-2',
location: str = 'europe-west4') -> aiplatform.Model:
"""Creates an endpoint and deploys Vertex AI Tabular AutoML model.
Args:
bigquery_clien... | e0fbc60875b32fada33ae3a35a072cd047f6a371 | 3,607,299 |
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