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9e866cb5594902d113ce4e2a281a1e610490ce4d | e8bf0ec2f07be9c4fb9aff1c5ea3be2651db17f6 | /Daily_Coding_Problem/451_fibonacci_in_o(1)_space.py | ef43d0267c50d1ce7212edb8a3b8b3059f61d224 | [] | no_license | Srini-py/Python | 0b4a0316f3754bc04e3c01214f1d99721defbf38 | 81eec0cc418baa86ad718be853242e4cc349dab4 | refs/heads/main | 2023-06-30T23:58:25.589872 | 2021-08-06T16:54:51 | 2021-08-06T16:54:51 | 393,439,738 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 391 | py | '''
Implement the function fib(n), which returns the nth number
in the Fibonacci sequence, using only O(1) space.
'''
def fib(n):
if n == 0 or n == 1:
return 1
a = i = 0
b = 1
while i < n - 1:
b, a = a + b, b
i += 1
return b
n = int(input("Enter the value of n : "))
fib_n = fib(n)
print("The {0}th fibonacci number is {1}".format(n, fib_n)) | [
"noreply@github.com"
] | Srini-py.noreply@github.com |
1549e7d46bbfd04ec91919b4f82908babc489151 | 4688134d507034541232d15b61d467e3c83d16e4 | /influxbee.py | bcedc80d8ea11101a23d18cbe1f089377d2f84c9 | [] | no_license | daarsan/influxbee | 28bc129a9028f5c39054a693923f4ef48f78f774 | 76a99733a5490f6751a65a05778261cc0a0e2a13 | refs/heads/master | 2020-03-28T02:32:34.728487 | 2018-09-06T17:03:53 | 2018-09-06T17:03:53 | 147,578,264 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,950 | py | # import the standard JSON parser
import json
# import logger
import logging
# import the REST library
import requests
import argparse
import os
import time
from influxdb import InfluxDBClient
from datetime import datetime, timedelta
class MirubeeApi():
MIRUBEE_API_URL = "https://app.mirubee.com/api/v2/"
def setToken(self, token):
self.MIRUBEE_API_TOKEN = token
return self.MIRUBEE_API_TOKEN
def login(self, email, password):
data = {
"language": "ES",
"client_type_id": "api",
"client_id": "influxdb",
"timezone": "Europe/Madrid",
"password": password,
"email": email
}
_url = "{}{}".format(self.MIRUBEE_API_URL, "login")
logger.debug("Getting info from {}".format(_url))
response = requests.post(_url, data=data)
logger.debug("Response Code: {}".format(response.status_code))
if response.status_code == 201:
logger.debug(response.text)
self.MIRUBEE_API_TOKEN = response.json()['token']
else:
raise ConnectionError()
return self.MIRUBEE_API_TOKEN
def _get(self, url):
_headers = {'Authorization': self.MIRUBEE_API_TOKEN}
_url = "{}{}".format(self.MIRUBEE_API_URL, url)
logger.debug("Getting info from {}".format(_url))
response = requests.get(_url, headers=_headers)
logger.debug("Response Code: {}".format(response.status_code))
if response.status_code == 200:
logger.debug("\n" + json.dumps(response.json(), indent=2))
else:
raise ConnectionError()
return response.json()
def getInfo(self):
url = "me"
return self._get(url)
def getBuildings(self, user_id):
url = "users/{}/buildings".format(user_id)
return self._get(url)
def getBuildingInfo(self, building_id):
url = "buildings/{}".format(building_id)
return self._get(url)
def getBuildingMeters(self, building_id):
url = "buildings/{}/meters".format(building_id)
return self._get(url)
def getMeterInfo(self, building_id, meter_id):
url = "buildings/{}/meters/{}".format(building_id, meter_id)
return self._get(url)
def getChannelLast(self, building_id, meter_id, channel_id):
url = "buildings/{}/meters/{}/channels/{}/last".format(building_id, meter_id, channel_id)
return self._get(url)
def getChannelData(self, building_id, meter_id, channel_id, start, end):
url = "buildings/{}/meters/{}/channels/{}/data".format(building_id, meter_id, channel_id)
url = "{}?start={}&end={}¶m=P".format(url, start.isoformat(), end.isoformat())
return self._get(url)
def scan(self):
user_data = {
"MIRUBEE_API_TOKEN": self.MIRUBEE_API_TOKEN
}
MIRUBEE_USER_INFO = self.getInfo()
# logger.debug(MIRUBEE_USER_INFO)
user_data["MIRUBEE_USER_ID"] = MIRUBEE_USER_INFO['id']
MIRUBEE_USER_BUILDINGS = mirubee.getBuildings(MIRUBEE_USER_INFO['id'])
# logger.debug(MIRUBEE_USER_BUILDINGS)
# user_data["MIRUBEE_USER_BUILDINGS"] = [MIRUBEE_USER_BUILDING['id'] for MIRUBEE_USER_BUILDING in MIRUBEE_USER_BUILDINGS]
user_data["MIRUBEE_USER_BUILDINGS"] = [
{
"MIRUBEE_BUILDING_ID": MIRUBEE_BUILDING['id'],
"MIRUBEE_BUILDING_METERS": [
{
"MIRUBEE_METER_ID": MIRUBEE_METER['meter_id'],
"MIRUBEE_METER_CHANNELS": [
{
"MIRUBEE_CHANNEL_ID": MIRUBEE_CHANNEL['channel_id'],
"MIRUBEE_CHANNEL_MAIN": MIRUBEE_CHANNEL['main_connection']
} for MIRUBEE_CHANNEL in MIRUBEE_METER['channels']]
} for MIRUBEE_METER in mirubee.getBuildingMeters(MIRUBEE_BUILDING['id'])
]
} for MIRUBEE_BUILDING in MIRUBEE_USER_BUILDINGS]
return user_data
def _setup_logger(verbose_mode):
# create logger with 'influxbee'
logger = logging.getLogger('influxbee')
logger.setLevel(logging.DEBUG)
# create console handler with a lower log level
ch = logging.StreamHandler()
if verbose_mode:
ch.setLevel(logging.DEBUG)
else:
ch.setLevel(logging.INFO)
# create formatter and add it to the handlers
formatter = logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s')
ch.setFormatter(formatter)
# add the handlers to the logger
logger.addHandler(ch)
return logger
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Pull data from mirubee.')
parser.add_argument('--user', '-u', help='Username')
parser.add_argument('--password', '-p', help='Password')
parser.add_argument('--verbose', help='Increase output verbosity', action="store_true")
parser.add_argument('--config-file', help='Path of the file with the information of user')
parser.add_argument('--influxdb-host', help='Influxdb IP Address')
parser.add_argument('--influxdb-port', default=8086, help='Influxdb IP Address')
parser.add_argument('--influxdb-database', default='mirubee', help='Influxdb IP Address')
parser.add_argument('--influxdb-user', default='root',help='Influxdb IP Address')
parser.add_argument('--influxdb-password', default='root', help='Influxdb IP Address')
parser.add_argument('--requests-per-day', default=24, type=int, help='Number of request per day. The free API offers up to 1000 hits per day.')
args = parser.parse_args()
logger = _setup_logger(args.verbose)
mirubee = MirubeeApi()
config_file = os.path.abspath(args.config_file if args.config_file else "mirubee.toml")
if os.path.exists(config_file):
logger.debug("Opening user data file on {}".format(config_file))
with open(config_file) as f:
user_data = json.load(f)
mirubee.setToken(user_data['MIRUBEE_API_TOKEN'])
else:
logger.info("Generating user data file on {}".format(config_file))
username = os.environ.get("MIRUBEE_USER", args.user)
password = os.environ.get("MIRUBEE_PASSWORD", args.password)
if not username or not password:
raise RuntimeError("Since there is no configuration file, username AND password are required.")
MIRUBEE_API_TOKEN = mirubee.login(username, password)
user_data = mirubee.scan()
logger.debug(user_data)
with open(config_file, 'w') as f:
json.dump(user_data, f, indent=2)
if (args.influxdb_host):
client = InfluxDBClient(host=args.influxdb_host, port=args.influxdb_port, username=args.influxdb_user,
password=args.influxdb_password)
client.create_database(args.influxdb_database)
client.switch_database(args.influxdb_database)
else:
client = None
sleep_interval = 24*60*60/args.requests_per_day
logger.info("Sleep interval: {} secs".format(sleep_interval))
start = datetime.utcnow() - timedelta(minutes=5)
while True:
end = datetime.utcnow()
for MIRUBEE_USER_BUILDING in user_data['MIRUBEE_USER_BUILDINGS']:
for MIRUBEE_BUILDING_METER in MIRUBEE_USER_BUILDING['MIRUBEE_BUILDING_METERS']:
for MIRUBEE_METER_CHANNEL in MIRUBEE_BUILDING_METER['MIRUBEE_METER_CHANNELS']:
if MIRUBEE_METER_CHANNEL['MIRUBEE_CHANNEL_MAIN']:
measures = mirubee.getChannelData(MIRUBEE_USER_BUILDING['MIRUBEE_BUILDING_ID'],
MIRUBEE_BUILDING_METER['MIRUBEE_METER_ID'],
MIRUBEE_METER_CHANNEL['MIRUBEE_CHANNEL_ID'],
start,
end)
data = [{
"measurement": "mirubee",
"tags": {
"mirubee_building_id": MIRUBEE_USER_BUILDING['MIRUBEE_BUILDING_ID'],
"mirubee_meter_id": MIRUBEE_BUILDING_METER['MIRUBEE_METER_ID'],
"mirubee_channel_id": MIRUBEE_METER_CHANNEL['MIRUBEE_CHANNEL_ID'],
},
"time": measure_time,
"fields": {
"P": float(measure_power)
}
} for measure_power, measure_time in zip(measures['data']['P'], measures['data']['time'])]
logger.debug(data)
if client:
client.write_points(data)
time.sleep(sleep_interval)
start = end | [
"d.aroca.sanchez@gmail.com"
] | d.aroca.sanchez@gmail.com |
87c3e4038e5bbee2bdfc93310f042f31fe4ba122 | e1808bea60f5f098ad2c4664ed2a639e276c4ff7 | /scans/migrations/0003_auto_20180823_0854.py | 9adb7bb671bfe0848c7d35416adb48d27eef3d54 | [] | no_license | tuanklnew/VulnerabilitiesManagement | 17008e120cb6f94f625eb31cd046401eeb4a315b | 81603a1c8e4a21e496b22f318409e743e5d4be8b | refs/heads/master | 2020-03-12T19:56:33.408314 | 2018-11-07T15:32:43 | 2018-11-07T15:32:43 | 130,794,917 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 492 | py | # Generated by Django 2.0.4 on 2018-08-23 01:54
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('scans', '0002_auto_20180803_1353'),
]
operations = [
migrations.AlterField(
model_name='scantaskmodel',
name='scanProject',
field=models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='projects.ScanProjectModel'),
),
]
| [
"tuanklnew@gmail.com"
] | tuanklnew@gmail.com |
f6c5e6a043f67c50bbe6334ee5273fce210c2169 | daf5995aa65a6936bd6cd26888af81e773d437fa | /rfn/layer.py | 0cda51d4c6d65bbe2f4095029c5198688e27d4de | [
"MIT"
] | permissive | TobiasSkovgaardJepsen/relational-fusion-networks | 12657451e236da3e4dc6ccebd85c3df64c7b0b5a | 3b1f1d7ceae5251c835710863c70380332cc4cc5 | refs/heads/master | 2022-12-10T10:38:53.126769 | 2020-09-14T12:49:31 | 2020-09-14T13:54:47 | 192,924,730 | 25 | 5 | MIT | 2022-12-08T06:22:43 | 2019-06-20T13:26:38 | Jupyter Notebook | UTF-8 | Python | false | false | 1,944 | py | from mxnet.gluon.nn import HybridBlock
class RFNLayer(HybridBlock):
class Join(HybridBlock):
""" Block that handles merging of node and between-edge features
for use in graph fusion on a dual graph representation.
"""
def hybrid_forward(self, F, X_N, X_B, N_shared_node_dual):
X_N_prime = F.take(X_N, indices=N_shared_node_dual).flatten()
return F.concat(X_B, X_N_prime, dim=1)
def __init__(self,
relational_fusion_primal, relational_fusion_dual,
feed_forward,
**kwargs):
super().__init__(**kwargs)
self.relational_fusion_primal = relational_fusion_primal
self.join = self.Join()
self.relational_fusion_dual = relational_fusion_dual
self.feed_forward = feed_forward
self.register_children(
self.relational_fusion_primal,
self.join,
self.relational_fusion_dual,
self.feed_forward)
def hybrid_forward(self, F, X_N, X_E, X_B,
N_node_primal, N_edge_primal, node_mask_primal,
N_node_dual, N_edge_dual, N_shared_node_dual,
node_mask_dual):
Z_N = self.relational_fusion_primal(
X_N, X_E,
N_node_primal, N_edge_primal, node_mask_primal)
X_B_prime = self.join(
X_N, X_B, N_shared_node_dual)
Z_E = self.relational_fusion_dual(
X_E, X_B_prime,
N_node_dual, N_edge_dual, node_mask_dual)
Z_B = self.feed_forward(X_B)
return Z_N, Z_E, Z_B
def register_children(self, *blocks):
for block in blocks:
self.register_child(block)
@property
def out_units(self):
return (
self.relational_fusion_primal.out_units,
self.relational_fusion_dual.out_units,
self.feed_forward.out_units
)
| [
"tobiasskovgaardjepsen@gmail.com"
] | tobiasskovgaardjepsen@gmail.com |
e02ab462c9f4a49d4b599efd3007e3abb3612645 | 6d233ad2059a941e4ce4c5b5ee3857b8a4a0d212 | /Everyday_alg/2021/05/2021_05_20/fan-zhuan-lian-biao-lcof.py | d1d64aebb1845d489af655b5b2d01f99ede7e6dc | [] | no_license | Alexanderklau/Algorithm | 7c38af7debbe850dfc7b99cdadbf0f8f89141fc6 | eac05f637a55bfcc342fa9fc4af4e2dd4156ea43 | refs/heads/master | 2022-06-12T21:07:23.635224 | 2022-06-12T08:12:07 | 2022-06-12T08:12:07 | 83,501,915 | 5 | 3 | null | null | null | null | UTF-8 | Python | false | false | 549 | py | # coding: utf-8
__author__ = "lau.wenbo"
"""
定义一个函数，输入一个链表的头节点，反转该链表并输出反转后链表的头节点。
示例:
输入: 1->2->3->4->5->NULL
输出: 5->4->3->2->1->NULL
限制：
0 <= 节点个数 <= 5000
"""
# Definition for singly-linked list.
# class ListNode(object):
# def __init__(self, x):
# self.val = x
# self.next = None
class Solution(object):
def reverseList(self, head):
"""
:type head: ListNode
:rtype: ListNode
""" | [
"429095816@qq.com"
] | 429095816@qq.com |
2e42ef9619f4fffbb4e0482a849b8171db04ffca | 3c72dfae389d910ea77b9593a8601e8335b6a2d6 | /tccli/services/car/__init__.py | c995a5cc0cc97606c8aa510af9f11ae788904758 | [
"Apache-2.0"
] | permissive | TencentCloud/tencentcloud-cli-intl-en | c6c17e19a79a4c31b310da97bc91417e161801fb | 5ed2fe2b91aa14f05e8821dd4332cc445b6234cd | refs/heads/master | 2023-09-01T19:37:18.534188 | 2023-09-01T04:01:27 | 2023-09-01T04:01:27 | 229,569,850 | 0 | 7 | Apache-2.0 | 2023-09-12T11:05:36 | 2019-12-22T13:10:59 | Python | UTF-8 | Python | false | false | 85 | py | # -*- coding: utf-8 -*-
from tccli.services.car.car_client import action_caller
| [
"tencentcloudapi@tencent.com"
] | tencentcloudapi@tencent.com |
11e21ae82e962eea826afcb6343275e60e01c2b8 | e9a386b8677066a376b004ff4f1475d7db976cfe | /teacher/views.py | d5ebb6b639be236c46088c3be91300ad387d1298 | [] | no_license | farabisiddique/booctep_deployment | c92ff3848cf2cb044c66a04d2c25cce1cffa535d | 055c2a72103a552a159b0cd88a60bd81b72ac067 | refs/heads/main | 2023-03-14T20:39:29.565446 | 2021-03-07T12:50:21 | 2021-03-07T12:50:21 | 345,344,689 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 20,895 | py | from django.shortcuts import render,redirect
from teacher.models import categories, Courses, VideoUploads, Sections, questions, student_mark, answers
from home.models import User, user_profile, notifications
from student.models import student_register_courses, student_rating_courses, course_comments
from datetime import datetime
import os, sys, shutil
import traceback
from django.http import HttpResponse, HttpResponseRedirect, JsonResponse
import json
import uuid
from django.conf import settings
from django.utils.translation import LANGUAGE_SESSION_KEY
from django.core.paginator import Paginator
def teacher_account(request):
if request.session.get('user_id') == None:
return redirect('/')
objC = categories.objects.all()
profile = ''
if user_profile.objects.filter(user_id=request.user.id).exists() :
profile = user_profile.objects.get(user_id=request.user.id)
return render(request, 'teacher/account.html', {'objC':objC, 'profile':profile, 'lang': getLanguage(request)[0]})
def teacher_security(request):
if request.session.get('user_id') == None:
return redirect('/')
user_id = request.session.get('user_id')
password = request.session.get('password')
print("passwrod", password)
print("user_id", user_id)
return render(request, 'teacher/security.html', {'lang': getLanguage(request)[0], 'user_id': user_id, 'password': password})
def teacher_notifications(request):
if request.session.get('user_id') == None:
return redirect('/')
id = request.user.id
noti_list = notifications.objects.filter(user_id=id,is_read=0)
for noti in noti_list:
noti.is_read = 1
noti.save()
course_list = Courses.objects.filter(user_id=id)
course_id = Courses.objects.filter(user_id=id).values_list('id',flat=True)
ids = map(str, course_id)
_ids = ','.join(ids)
excludetheseid = []
exclude_student_unrecieve_noti = User.objects.filter(receive_notifications=0).values('id')
for value in range(len(exclude_student_unrecieve_noti) ):
excludetheseid.append(exclude_student_unrecieve_noti[value]['id'])
student_list = student_register_courses.objects.extra(where=['FIND_IN_SET(course_id_id, "' + _ids + '")']).exclude(student_id_id__in=excludetheseid)
print(excludetheseid)
print("stude:",student_list)
return render(request, 'teacher/notifications.html', {'lang': getLanguage(request)[0],'noti_list':noti_list, 'course_list':course_list,'student_list':student_list})
def teacher_payments(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/payments.html', {'lang': getLanguage(request)[0]})
def teacher_privacy(request):
return render(request, 'teacher/privacy.html', {'lang': getLanguage(request)[0], 'user_id':request.user.id})
def dashboard(request):
if request.session.get('user_id') == None:
return redirect('/')
user_id = request.session.get('user_id')
courses = Courses.objects.filter(user_id=user_id).filter(type=0)
#price logic..
totalPrice = 0
#get total student
courseId = Courses.objects.filter(user_id=user_id).values_list('id',flat=True)
courseId = list(courseId)
courseId = map(str, courseId)
courseId = ','.join(courseId)
totalStuCnt = student_register_courses.objects.extra(where=['FIND_IN_SET(course_id_id, "'+courseId+'")']).count()
#get total rating
rateSum = 0
rateCnt = 0
for course in courses:
rating = course_comments.objects.filter(course_id_id=course.id).values_list('rating',flat=True)
rating = list(rating)
sum = 0;
for i in rating:
sum += i
if len(rating) == 0:
course.rating = 0
else :
course.rating = sum / len(rating)
course.stuCnt = student_register_courses.objects.filter(course_id_id=course.id).count()
course.totalGain = course.price*course.stuCnt
totalPrice += course.totalGain
rateSum += course.rating
rateCnt += 1
if rateCnt == 0:
totalRate = 0
else :
totalRate = round(rateSum/rateCnt,2)
return render(request, 'teacher/dashboard.html', {'lang': getLanguage(request)[0],'courses':courses, 'totalRate':totalRate, 'totalStuCnt':totalStuCnt,'totalPrice':totalPrice})
def teacher_courses(request):
if request.session.get('user_id') == None:
return redirect('/')
filter_type = request.GET.get('filter_type')
if filter_type == None:
filter_type = '-1'
if int(filter_type) == -1:
course_list = get_teacher_CourseList(request)
filter_type = -1
else:
user_id = request.session.get("user_id")
course_list = Courses.objects.filter(user_id=user_id,type=filter_type)
filter_type = int(filter_type)
return render(request, 'teacher/courses.html', {'lang': getLanguage(request)[0], 'course_list': course_list, 'user_type':request.session.get('user_type'),'filter_type':filter_type})
def teacher_faqs(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/faqs.html', {'lang': getLanguage(request)[0]})
def course_engagement(request):
if request.session.get('user_id') == None:
return redirect('/')
cur_course_id = request.GET.get('course_id')
courses = get_teacher_CourseList(request)
if cur_course_id == None:
if len(courses) > 0:
cur_course_id = courses[0].id
else :
cur_course_id = 0
if len(courses) > 0:
course = Courses.objects.get(pk=cur_course_id)
# total price...
# total students
count = student_register_courses.objects.filter(course_id_id=course.id).count()
course.stuCnt = count
# total rating
rateList = course_comments.objects.filter(course_id_id=course.id).values_list('rating', flat=True)
rateList = list(rateList)
sum = 0
for i in rateList:
sum += i
if len(rateList) == 0:
course.rating = 0
else:
course.rating = sum / len(rateList)
#reviews...
reviewList = course_comments.objects.filter(course_id_id=cur_course_id)
else:
course = ''
reviewList = ''
return render(request, 'teacher/course-engagement.html', {'lang': getLanguage(request)[0],'courses':courses, 'course':course, 'reviewList':reviewList, 'cur_course_id':cur_course_id})
def addtofeedback(request):
if request.session.get('user_id') == None:
return redirect('/')
commentid = request.GET.get('commentid')
commentquery = course_comments.objects.filter(course_id_id=commentid)
commentquery.approved_by_teacher = 1
commentquery.save()
return HttpResponse("success")
def student_performance(request):
if request.session.get('user_id') == None:
return redirect('/')
user_id = request.user.id
course_id = request.POST.get('course_id')
courseList = Courses.objects.filter(user_id=user_id).order_by("id")
if len(courseList) > 0:
if course_id == None:
course_id = courseList[0].id
# get all course that i made..
studentList = student_mark.objects.filter(course_id=course_id)
for student in studentList:
student.user = User.objects.get(pk=student.student_id)
student.percent = student.mark * 20
student.count = answers.objects.filter(student_id=student.student_id,result=1).count()
else :
course_id = ''
return render(request, 'teacher/student-performance.html', {'lang': getLanguage(request)[0],'courseList':courseList, 'course_id':course_id*1, 'studentList':studentList})
def teacher_messages(request):
if request.session.get('user_id') == None:
return redirect('/')
user_id = request.session.get("user_id")
user_type = request.session.get("user_type")
if user_id :
profile = User.objects.get(id = user_id)
user_name = profile.first_name+" "+profile.last_name
student_list= []
student_dict= {}
if Courses.objects.filter(user_id = user_id).exists():
obj = Courses.objects.filter(user_id = user_id)
for i in obj:
if student_register_courses.objects.filter(course_id = i.id).exists():
student_dict["course_name"] = i.name
student_dict["course_id"] = i.id
student_obj = student_register_courses.objects.filter(course_id = i.id)
for k in student_obj:
student_dict["student_id"] = k.student_id.id
student_dict["student_name"] = k.student_id.first_name+" "+k.student_id.last_name
student_dict["student_image"] = k.student_id.image
student_list.append(student_dict)
student_dict = {}
return render(request, 'teacher/messages.html', {'lang': getLanguage(request)[0], 'datetime':datetime,"student_list":student_list,"user_id":user_id,"user_name":user_name})
else:
return render(request, 'teacher/messages.html', {'lang': getLanguage(request)[0], 'datetime':datetime,"user_id":user_id})
def dashboard1(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/dashboard_1.html', {'lang': getLanguage(request)[0]})
def guideline(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/guidline.html', {'lang': getLanguage(request)[0]})
def teacher_help(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/help.html', {'lang': getLanguage(request)[0]})
def help2(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/help2.html', {'lang': getLanguage(request)[0]})
def newcourse2(request):
if request.session.get('user_id') == None:
return redirect('/')
if request.method == 'POST':
course = request.POST.get('course')
else :
course = ''
return render(request, 'teacher/new-course-2.html', {'lang': getLanguage(request)[0], 'course_id': course})
def newcourse3(request):
if request.session.get('user_id') == None:
return redirect('/')
if request.method == 'POST':
course = request.POST.get('course')
else :
course = ''
return render(request, 'teacher/new-course-3.html', {'lang': getLanguage(request)[0], 'course_id':course})
def newcourse4(request):
if request.session.get('user_id') == None:
return redirect('/')
id = request.GET.get('id')
data = get_courseDetails(id)
course = Courses.objects.get(pk=id)
include = course.includes
incList = include.split(',')
incList.pop()
videoList = getVideoList(course)
if len(videoList) > 0:
showVideoUrl = videoList[0].url
else :
showVideoUrl = ''
return render(request, 'teacher/new-course-4.html', {'lang': getLanguage(request)[0], 'video_list': data['video_list'], 'question_list': data['question_list'], 'section_list': data['section_list'],'course':course,'incList':incList, 'video_url':showVideoUrl})
def newcourse5(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/new-course-5.html', {'lang': getLanguage(request)[0]})
# def courseUrlGenerator(coursename):
# x = txt.split()
# courselink = "_".join(x)
# return courselink
def newcourse(request):
if request.session.get('user_id') == None:
return redirect('/')
course = []
obj_cat = categories.objects.all()
autoUrl = ''
if request.method == 'POST':
course_id = request.POST.get('course')
course = Courses.objects.get(pk=course_id)
descript = course.includes.split(",")
descript.pop()
course.includes = descript
else :
course_id = ''
courseCnt = Courses.objects.filter(user_id=request.user.id).count()
teacher_name = request.user.first_name + " " + request.user.last_name
courseNo = ''
idx = (courseCnt + 1)
while idx < 1000 :
idx = idx * 10
courseNo += '0'
autoUrl = teacher_name + "_" + courseNo + str(courseCnt + 1)
return render(request, 'teacher/new-course.html', {'lang': getLanguage(request)[0], 'categories':obj_cat, 'autoUrl':autoUrl, 'course':course, 'course_id':course_id})
def nocourseengagement(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/no-course-engagement.html', {'lang': getLanguage(request)[0]})
def nocourse(request):
if request.session.get('user_id') == None:
return redirect('/')
return render(request, 'teacher/no-course.html', {'lang': getLanguage(request)[0]})
# post
# get all course list
# @return List
def get_teacher_CourseList(request):
user_id = request.session.get("user_id")
user_type = request.session.get("user_type")
print(user_id)
print(user_type)
course_list = []
course_list = Courses.objects.filter(user_id = user_id)
return course_list
def getAllCourseList():
course_list = []
course_list = Courses.objects.all()
return course_list
def getPaidCourseList():
course_list = []
course_list = Courses.objects.filter(type=0)
return course_list
def getFreeCourseList():
course_list = []
course_list = Courses.objects.filter(type=1)
return course_list
# store course in DB
def store_course(request):
id = request.POST.get('id')
name = request.POST.get('name')
description = request.POST.get('description')
requirements = request.POST.get('requirements')
gains = request.POST.get('gains')
include = request.POST.get('include')
category_id = request.POST.get('category_id')
sub_category_id = request.POST.get('sub_category_id')
price = request.POST.get('price')
courseUrl = request.POST.get('courseUrl')
user_id = request.POST.get('user_id')
pending = request.POST.get('pending')
type = request.POST.get('type')
myfile = request.FILES['coverImg']
myfile1 = request.FILES['headerImg']
filename = myfile._get_name()
ext = filename[filename.rfind('.'):]
file_name = str(uuid.uuid4()) + ext
path = '/user_images/'
full_path = str(path) + str(file_name)
fd = open('%s/%s' % (settings.STATICFILES_DIRS[0], str(path) + str(file_name)), 'wb')
for chunk in myfile.chunks():
fd.write(chunk)
fd.close()
filename1 = myfile1._get_name()
ext1 = filename1[filename1.rfind('.'):]
file_name1 = str(uuid.uuid4()) + ext1
path = '/user_images/'
full_path1 = str(path) + str(file_name1)
fd = open('%s/%s' % (settings.STATICFILES_DIRS[0], str(path) + str(file_name1)), 'wb')
for chunk in myfile1.chunks():
fd.write(chunk)
fd.close()
if id == '': # add case
objCourse = Courses(
name = name,
description = description,
requirements = requirements,
gains = gains,
includes = include,
scat_id = category_id,
price = price,
user_id=request.user.id,
cover_img=full_path,
header_img=full_path1,
course_url=courseUrl,
pending = pending,
type = type
)
objCourse.save()
print('success')
msg = "successs"
id = objCourse.id
else :
objCourse = Courses.objects.get(pk=id)
objCourse.name = name
objCourse.description = description
objCourse.requirements = requirements
objCourse.gains = gains
objCourse.includes = include
objCourse.scat_id = category_id
objCourse.price = price
objCourse.user_id = request.user.id
objCourse.cover_img = full_path
objCourse.header_img = full_path1
objCourse.course_url = courseUrl
objCourse.pending = pending
objCourse.type = type
objCourse.save()
msg = "successs"
id = objCourse.id
to_return = {
'msg': msg,
'id': id}
serialized = json.dumps(to_return)
return HttpResponse(serialized, content_type="application/json")
# store videos in DB
def store_course_2(request):
data = request.POST
course_id = json.loads(data.get("course_id"))
pending = json.loads(data.get("pending"))
files = request.FILES
video_list = []
msg = ''
course = Courses.objects.get(pk=course_id)
course.pending = pending
course.save()
try:
section_list = data.get("section_list")
section_list = json.loads(section_list)
json_video_list = json.loads(data.get("video_list"))
if( len(json_video_list) > 0 ):
## store section in DB
for section in section_list:
name = section['name']
tag_id = section['tag_id']
## store section in DB
objSection = Sections(
name=name,
course_id=course_id,
type='video',
nos=tag_id
)
objSection.save()
section_id = objSection.id
for item in json_video_list:
if( item['sectionId'] == tag_id ) :
## upload video
video_key = item['key']
video = files[video_key]
filename = video._get_name()
ext = filename[filename.rfind('.'):]
file_name = str(uuid.uuid4())+ext
path = '/uploads/courses/videos/'
full_path= str(path) + str(file_name)
print("store course", full_path)
print("store course1", (settings.STATICFILES_DIRS[0],str(path) + str(file_name)))
fd = open('%s/%s' % (settings.STATICFILES_DIRS[0],str(path) + str(file_name)), 'wb')
for chunk in video.chunks():
fd.write(chunk)
fd.close()
## store video in DB
objVideo = VideoUploads(
name=filename,
section_id=section_id,
url=full_path,
promo=item['promo']
)
objVideo.save()
msg = "success"
else:
msg = "failed"
except:
tb = sys.exc_info()[2]
tbinfo = traceback.format_tb(tb)[0]
msg = tbinfo + "\n" + ": " + str(sys.exc_info())
to_return = {
'msg': msg,
}
serialized = json.dumps(to_return)
return HttpResponse(serialized, content_type="application/json")
# store questions in DB
def store_course_3(request):
msg = ''
data = request.POST
course_id = json.loads(data.get("course_id"))
try:
question_list = json.loads(data.get('question_list'))
section_list = json.loads(data.get('section_list'))
key = 1 # question number
if( len(question_list) > 0 ) :
for section in section_list:
tag_id = section['tag_id']
section_name = section['name']
nos = Sections.objects.filter(course_id=course_id).count()
## store section in DB
objSection = Sections(
name=section_name,
course_id=course_id,
type='question',
nos=nos+1
)
objSection.save()
section_id = objSection.id
for question in question_list:
if question['section_id'] == tag_id :
title = question['question_title']
type = question['answer_type']
answers = question['answers']
content = ''
result = ''
for answer in answers:
content += answer['data']
content += ','
# if type != 'aw-dragula':
# for answer in answers:
result += answer['result']
result += ','
objQuestion = questions(
title=title,
section_id=section_id,
type=type,
content=content,
answer=result,
nos=key
)
objQuestion.save()
key += 1
msg = "success"
else :
msg = "failed"
except:
tb = sys.exc_info()[2]
tbinfo = traceback.format_tb(tb)[0]
msg = tbinfo + "\n" + ": " + str(sys.exc_info())
to_return = {
'msg': msg,
}
serialized = json.dumps(to_return)
return HttpResponse(serialized, content_type="application/json")
# get course details by course's id.
#
# @param Request
#
# @return HttpResponse
def getCourseDetailsById(request):
id = request.POST.get('id')
msg = ''
to_return = {
'msg': msg,
'data': get_courseDetails(id)
}
serialized = json.dumps(to_return)
return HttpResponse(serialized, content_type="application/json")
def get_courseDetails(course_id):
id = course_id
video_list = []
question_list = []
section_list = []
tmp_sections = Sections.objects.filter(course_id=id)
if len(tmp_sections) > 0:
for section in tmp_sections:
section_list.append({
'id': section.id,
'name': section.name,
'course_id': section.course_id,
'type': section.type,
})
for video in VideoUploads.objects.filter(section_id=section.id):
video_list.append({
'id': video.id,
'name': video.name,
'section_id': video.section_id,
'src': video.url,
})
for question in questions.objects.filter(section_id=section.id):
question_list.append({
'id': question.id,
'title': question.title,
'type': question.type,
'section_id': question.section_id,
'nos': question.nos,
'content': question.content,
'answer': question.answer,
})
print(section_list)
return {
'question_list': question_list,
'video_list': video_list,
'section_list': section_list,
}
ur=""
# language=""
def getLanguage(request):
global ur;
# global language;
# prev=""
path = request.path
ur=path
prev=request.META.get('HTTP_REFERER')
language = path.split('/')[1]
# if(request.session.get("language_code")):
# language = request.session.get("language_code") + "/"
# else:
# language = path.split('/')[1]
# request.session['language_code'] = language
# language = language + "/"
if language == "ar":
language = language + '/'
else:
language = ""
return language,prev,path
def saveLater(request):
id = request.POST.get('id')
pending = request.POST.get('pending')
print(id,pending)
course = Courses.objects.get(pk=id)
print(course)
course.pending = pending
course.save()
ret = {'msg': 'success'}
return JsonResponse(ret)
def getVideoList(course):
ssss = Sections.objects.filter(course_id=course.id).values_list("id", flat=True)
ssss = map(str, ssss)
strr = ','.join(ssss)
videoList = VideoUploads.objects.extra(where=['FIND_IN_SET(section_id, "' + strr + '")'])
return videoList
| [
"ebari2017@yandex.com"
] | ebari2017@yandex.com |
b538c15b1341fafdf1aed9ae349e8d6dd94a524a | 0d4850d343530aca114921bc500cae0a2a6c34b4 | /algorithms/heuristic_methods.py | f1311304442600d65c4fc02fd33bc665282d6b55 | [] | no_license | proxodilka/genetic_algorithms | c3518208df962d9c5414c940b10f792f4dacd5a3 | 7a4acc17849c253dc14a5cfc5f6e1dd43ba876de | refs/heads/master | 2023-04-30T10:45:36.683912 | 2021-05-22T21:57:29 | 2021-05-22T21:57:29 | 369,882,663 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,675 | py | from abc import abstractmethod
import numpy as np
from .utils import SEED
# np.random.seed(SEED.value)
class BaseSolver:
def __init__(self, individual_type, score_fn, **kwargs):
self.type = individual_type
self.scorer = score_fn
self.i = 0
def get_solutions(self, n, steps=None):
if steps is None:
steps = min(2 * self.type.shape(), 100)
return [self.get_solution(steps) for _ in range(n)]
@abstractmethod
def get_solution(self, steps, return_score=False):
pass
class MonteCarlo(BaseSolver):
def get_solution(self, steps, return_score=False):
print(self.i)
self.i += 1
generator = self.type.build_random
best_score = float("inf")
solution = None
for _ in range(steps):
candidate = generator()
c_score = self.scorer(candidate)
if c_score < best_score:
solution = candidate
best_score = c_score
if return_score:
return solution, best_score
else:
return solution
class DFS(BaseSolver):
def get_solution(self, steps, return_score=False):
generator = self.type.build_random
hood_generator = self.type.hood
solution = generator()
best_score = self.scorer(solution)
for _ in range(steps):
hood = hood_generator(solution)
solution_was_updated = False
for candidate in hood:
c_score = self.scorer(candidate)
if c_score < best_score:
solution = candidate
best_score = c_score
solution_was_updated = True
if not solution_was_updated:
break
if return_score:
return solution, best_score
else:
return solution
class NearestCity(BaseSolver):
def __init__(self, individual_type, score_fn, weights=None, **kwargs):
assert weights is not None or hasattr(
self, "weights"
), "City weights matrix is not provided, pass it to the constructor, or use decorator to bind it to the new class."
super().__init__(individual_type, score_fn)
if not hasattr(self, "weights"):
self.weights = weights
def get_solution(self, *args, **kwargs):
return_score = kwargs.get("return_score", False)
solution = min(
[self.solve(self.weights, i) for i in range(len(self.weights))],
key=lambda x: x[1],
)
individ, score = solution
individ = self.type(gens=individ, score_fn=self.scorer)
if return_score:
return individ, score
return individ
def solve(self, weights, start_city):
n_cities = weights.shape[0]
result = np.zeros(n_cities, dtype=np.int)
visited_mask = ~np.zeros(n_cities, dtype=np.bool)
result[0] = start_city
visited_mask[start_city] = False
for i in range(1, len(result)):
city_from = result[i - 1]
nearest_city = self.get_nearest_city(weights, city_from, visited_mask)
result[i] = nearest_city
visited_mask[nearest_city] = False
score = self.scorer(result)
return result, score
@staticmethod
def get_nearest_city(weights, city, visited_mask, return_weight=False):
masked_min_idx = weights[city][visited_mask].argmin()
nearest_city = np.where(visited_mask)[0][masked_min_idx]
if return_weight:
return nearest_city, weights[city, nearest_city]
else:
return nearest_city
| [
"zeeron209@gmail.com"
] | zeeron209@gmail.com |
accffe6b7df7db10cdb2761f91701c25dbcc7b4b | 55a4a29ecbc32570d08dd03cdb521b7e978db09c | /authorization/forms.py | c061204d11e88688845d340d795a23a58f01a719 | [] | no_license | dimdiden/portanizer | 73c55d129916a79c660012220c7e6694826e5ff8 | e54f4f04a4052b4b94a92e4c8b10d1ccf5aac5ee | refs/heads/master | 2021-09-27T18:22:27.175236 | 2020-08-09T09:07:06 | 2020-08-09T09:07:06 | 99,321,841 | 0 | 0 | null | 2021-09-22T17:38:07 | 2017-08-04T08:30:12 | Python | UTF-8 | Python | false | false | 3,889 | py | from django import forms
from django.contrib.auth import (
authenticate,
get_user_model,
)
# This method will return the currently active user model
# the custom user model if one is specified, or User otherwise.
User = get_user_model()
class UserLoginForm(forms.Form):
username = forms.CharField(widget=forms.TextInput(
attrs={'placeholder': 'Enter username'}), label='Username:')
password = forms.CharField(widget=forms.PasswordInput(
attrs={'placeholder': 'Enter password'}), label='Password:')
def clean(self, *args, **kwargs):
username = self.cleaned_data.get("username")
password = self.cleaned_data.get("password")
if username and password:
try:
user = User.objects.get(username=username)
except User.DoesNotExist:
user = None
user_auth = authenticate(username=username, password=password)
if not user:
raise forms.ValidationError("This user does not exist")
if not user_auth:
raise forms.ValidationError("Incorrect password")
if not user_auth.is_active:
raise forms.ValidationError("The user is no longer active")
return super(UserLoginForm, self).clean(*args, **kwargs)
class UserRegisterForm(forms.ModelForm):
username = forms.CharField(widget=forms.TextInput(
attrs={'placeholder': 'Enter username'}), label='Username:')
email = forms.EmailField(widget=forms.TextInput(
attrs={'placeholder': 'Enter email'}), label='Email address:')
password = forms.CharField(widget=forms.PasswordInput(
attrs={'placeholder': 'Enter password'}), label='Password:')
password2 = forms.CharField(widget=forms.PasswordInput(
attrs={'placeholder': 'Enter the same password'}), label='Confirm Password:')
class Meta:
model = User
fields = [
'username',
'password',
'password2',
'email',
]
# https://stackoverflow.com/questions/34609830/django-modelform-how-to-add-a-confirm-password-field
def clean(self, *args, **kwargs):
password = self.cleaned_data.get('password')
password2 = self.cleaned_data.get('password2')
if password and len(password) <= 6:
raise forms.ValidationError("Passwords must contain not less than 6 characters")
if password != password2:
raise forms.ValidationError("Passwords must match")
return super(UserRegisterForm, self).clean(*args, **kwargs)
class PasswordResetRequestForm(forms.Form):
email_or_username = forms.CharField(widget=forms.TextInput(
attrs={'placeholder': 'Enter your email or username'}), label=("Email Or Username"))
class SetPasswordForm(forms.Form):
error_messages = {
'password_mismatch': ("The two password fields didn't match."),
'password_length': ("Passwords must contain not less than 6 characters"),
}
password = forms.CharField(widget=forms.PasswordInput(
attrs={'placeholder': 'Enter password'}), label='New password:')
password2 = forms.CharField(widget=forms.PasswordInput(
attrs={'placeholder': 'Enter the same password'}), label='New password confirmation:')
def clean_password2(self):
password = self.cleaned_data.get('password')
password2 = self.cleaned_data.get('password2')
if len(password) <= 6:
raise forms.ValidationError(
self.error_messages['password_length'],
code='password_length',
)
if password and password2:
if password != password2:
raise forms.ValidationError(
self.error_messages['password_mismatch'],
code='password_mismatch',
)
return password2
| [
"dimdiden@gmail.com"
] | dimdiden@gmail.com |
f25422ab2631f0fdbeb4a03692b87a9201748f63 | 54646ea5bc36103cf8100ec796b640a8358fef95 | /database/migrations/0005_auto_20151013_1921.py | 0a697c25fdff4b71b280aee61e1bdb088eec6e0a | [] | no_license | extremewaysback/origin | 3d48fb642feef0a5fe33e323b99f437d00446045 | ccdc059c6590aa17115ae7af9ed8aff8cd0e5d1c | refs/heads/master | 2021-01-09T21:47:38.135516 | 2016-04-08T13:49:21 | 2016-04-08T13:49:21 | 48,943,391 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 467 | py | # -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.db import models, migrations
import django.utils.timezone
class Migration(migrations.Migration):
dependencies = [
('database', '0004_auto_20151013_1654'),
]
operations = [
migrations.AlterField(
model_name='defectdata',
name='scantime',
field=models.DateTimeField(verbose_name=django.utils.timezone.now),
),
]
| [
"extremewaysback@hotmail.com"
] | extremewaysback@hotmail.com |
d595fa292a91a2c556d114cdb90fca4be8725a62 | e35eb92b5ab6547119585004b9eea3cafe948050 | /efsw/archive/forms.py | 0412fa6bb77d4b59b6d79c94e261e4dacfe4a7aa | [] | no_license | einsfr/mmkit | 0a084db85b2cf5ba268e692676095d768733f387 | f12bc2f83254a3123e02abdc105816cc04c438b5 | refs/heads/master | 2020-12-31T05:56:19.287611 | 2016-06-10T05:56:58 | 2016-06-10T05:56:58 | 29,473,203 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,889 | py | from django import forms
from django.forms import widgets
from efsw.archive import models
from efsw.storage import models as storage_models
from efsw.common.datetime.period import DatePeriod
class ItemCreateForm(forms.ModelForm):
class Meta:
model = models.Item
fields = ('name', 'description', 'created', 'author', 'category')
widgets = {
'name': widgets.TextInput(attrs={
'class': 'form-control',
'placeholder': 'Название нового элемента'
}),
'created': widgets.DateInput(attrs={
'class': 'form-control',
'placeholder': '01.01.2015'
}),
'description': widgets.Textarea(attrs={
'class': 'form-control',
'placeholder': 'Описание нового элемента',
'style': 'resize: vertical;'
}),
'author': widgets.TextInput(attrs={
'class': 'form-control',
'placeholder': 'Автор(ы) элемента'
}),
'category': widgets.Select(attrs={
'class': 'form-control',
})
}
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.fields['category'].empty_label = None
class ItemUpdatePropertiesForm(forms.ModelForm):
class Meta(ItemCreateForm.Meta):
fields = ('name', 'description', 'created', 'author', 'category')
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
self.fields['category'].empty_label = None
class ItemUpdateLocationsForm(forms.Form):
storage = forms.ModelChoiceField(
queryset=storage_models.FileStorage.objects.filter(allowed_usage__contains=['archive']),
label='Хранилище',
empty_label=None,
widget=widgets.Select(attrs={
'class': 'form-control',
'data-bind': 'value: form_storage',
})
)
path = forms.CharField(
max_length=255,
label='Путь к файлу',
widget=widgets.TextInput(attrs={
'class': 'form-control',
'data-bind': 'textInput: form_path',
})
)
class ItemCategoryForm(forms.ModelForm):
class Meta:
model = models.ItemCategory
fields = ('name', )
widgets = {
'name': widgets.TextInput(attrs={
'class': 'form-control',
'placeholder': 'Название новой категории'
})
}
class ArchiveSearchForm(forms.Form):
ORDER_BY_CREATED_ASC = '1'
ORDER_BY_CREATED_DESC = '2'
ORDER_CHOICES = {
ORDER_BY_CREATED_ASC: 'По дате создания (по возрастанию)',
ORDER_BY_CREATED_DESC: 'По дате создания (по убыванию)',
}
DATE_PERIODS = DatePeriod.PERIODS_PAST_ONLY_WITH_TODAY
DATE_CHOICES = DatePeriod.get_periods_past_only()
q = forms.CharField(
min_length=3,
max_length=255,
label='Текст запроса',
required=False,
widget=widgets.TextInput(attrs={
'class': 'form-control',
'placeholder': 'Текст поискового запроса'
})
)
c = forms.ModelMultipleChoiceField(
queryset=models.ItemCategory.objects.all().order_by('name'),
label='Категория',
required=False,
widget=widgets.SelectMultiple(attrs={
'class': 'form-control',
})
)
o = forms.ChoiceField(
choices=[('', 'По релевантности')] + list(ORDER_CHOICES.items()),
label='Порядок сортировки',
required=False,
widget=widgets.Select(attrs={
'class': 'form-control',
})
)
p = forms.ChoiceField(
choices=[('', 'За всё время')] +
[(x[0], str(x[1]).capitalize()) for x in DATE_CHOICES.items()] +
[('custom', 'Указать особый')],
label='Дата записи',
required=False,
widget=widgets.Select(attrs={
'class': 'form-control',
'data-bind': 'value: selected_period'
})
)
p_s = forms.DateField(
required=False,
label='Начало периода',
widget=widgets.DateInput(attrs={
'class': 'form-control',
'placeholder': '01.01.2015'
}),
)
p_e = forms.DateField(
required=False,
label='Конец периода',
widget=widgets.DateInput(attrs={
'class': 'form-control',
'placeholder': '01.01.2015'
}),
)
ph = forms.BooleanField(
required=False,
label='Искать фразу'
)
| [
"einsfr@users.noreply.github.com"
] | einsfr@users.noreply.github.com |
6c5f673ff30c794a914498e84443611631ab3a81 | 4ef81999138d46494b49314f87321fb505e6ceb5 | /spider_scrapy_lianjia/items.py | edde6cfdc2ec5855c14679ed637df8b8cccbcf5d | [] | no_license | netww/spider_scrapy_lianjia | 50bc08693d72d5cf60c076fb99e0835079239597 | b86c1152457c15c842ddbd72ff4d4a687abed9fb | refs/heads/master | 2021-06-05T21:33:44.530069 | 2016-10-22T14:06:17 | 2016-10-22T14:06:17 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 942 | py | # -*- coding: utf-8 -*-
# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html
from scrapy import Item, Field
class SpiderScrapyLianjiaItem(Item):
# define the fields for your item here like:
# name = scrapy.Field()
xiaoqu_id = Field() # 小区id
house_id = Field() # 链家房源编号
title = Field() # 标题
price = Field() # 价格
#size = Field() # 面积
view_count = Field() # 带看次数
class SpiderChenshiItem(Item):
# define the fields for your item here like:
# name = scrapy.Field()
chenshi_name = Field() # 城市名
avg_price = Field() # 城市均价
onsale_count = Field() # 在售套数
sold_last_month = Field() # 上个月成交套数
view_last_day = Field() # 昨日带看次数
| [
"stamhe@163.com"
] | stamhe@163.com |
02e886e543183014af20712cd90728216ab6fbf6 | 257f48f957d6642315b04bef2fad6c0458885811 | /support/make_structures.in.py | d7ac0f84079d1994a9e7dab4f85d437a3ac87a8b | [
"MIT"
] | permissive | msg-byu/enumlib | 3074daa6ef95c735d6b963fe5dbce0ef1b3a31a9 | 6bd831f3b325acf1e7066fbe1ffb7312ff249a34 | refs/heads/main | 2023-01-12T12:02:25.029089 | 2023-01-02T17:00:06 | 2023-01-02T17:00:06 | 36,761,164 | 56 | 43 | MIT | 2022-11-19T15:41:24 | 2015-06-02T20:53:29 | Roff | UTF-8 | Python | false | false | 1,059 | py | #!/usr/bin/python
import os, subprocess
from os import path
import glob
from os import system
import string
import sys
# Read in a struct_enum-format file with structures defined. These will be converted to the
# vasp-like format that UNCLE uses
if len( sys.argv) < 2:
sys.exit("Script needs an argument---file containing structures")
#strfile = open(sys.argv[1])
if(not path.isfile("makestr.x")):
print "This script needs 'makestr.x' to run..."
print "Try 'make makestr.x'"
exit()
for n in range(1,10850):
rs=system('./makestr.x '+sys.argv[1]+' '+str(n)+' >& /dev/null')
if rs!=0:
break
print "\n Read in a total of "+str(n-1)+" stuctures from "+sys.argv[1]
system("perl -pi -e 's/scale factor/1.0/g' vasp.*")
unclefile = open("structures.in",'w')
unclefile.write("scalar\nperatom\nnoweights\n")
vnum =glob.glob('vasp.*')
for i in vnum:
f = open(i)
str = f.read()
unclefile.write(str)
unclefile.write("0 0 \n #\n")
unclefile.close
system("rm vasp.*")
print "\n Structures concatenated into structures.in\n"
| [
"hart@55a9f988-e549-0410-8b28-d6fb27d14cbf"
] | hart@55a9f988-e549-0410-8b28-d6fb27d14cbf |
230e18e7d8c515bdfedabdd665fcd611708d8686 | dd0c53c5e56d2aa81e6b8336444395e9ebade387 | /calamari_ocr/ocr/augmentation/data_augmenter.py | 8da5c2f640f9f0d9dd5066d3557de288dfe5caa1 | [
"Apache-2.0"
] | permissive | Caro-app/calamari | ae54f0af2aaae5645ed5a8466ab43d1100f5e62f | 30a52cc60ea0c80bbdd9ff042bbd87093524d416 | refs/heads/master | 2021-01-02T00:11:42.582352 | 2020-05-27T15:40:46 | 2020-05-27T15:40:46 | 239,406,215 | 0 | 0 | Apache-2.0 | 2020-05-27T15:40:47 | 2020-02-10T01:50:10 | Python | UTF-8 | Python | false | false | 2,711 | py | from abc import ABC, abstractmethod
from calamari_ocr.utils import parallel_map
import numpy as np
class DataAugmenter(ABC):
def __init__(self):
super().__init__()
@abstractmethod
def augment_single(self, data, gt_txt):
pass
def augment_data(self, data, gt_txt, n_augmentations):
if n_augmentations <= 0:
return data, gt_txt
return zip(*[self.augment_single(data, gt_txt) for _ in range(n_augmentations)])
def augment_data_tuple(self, t):
return self.augment_data(*t)
def augment_datas(self, datas, gt_txts, n_augmentations, processes=1, progress_bar=False):
if n_augmentations <= 0:
return datas, gt_txts
out = parallel_map(self.augment_data_tuple, list(zip(datas, gt_txts, [n_augmentations] * len(datas))),
desc="Augmentation", processes=processes, progress_bar=progress_bar)
out_d, out_t = [], []
for d, t in out:
out_d += d
out_t += t
return datas + out_d, gt_txts + out_t
class NoopDataAugmenter(DataAugmenter):
def __init__(self):
super().__init__()
def augment_single(self, data, gt_txt):
return data, gt_txt
def augment_data(self, data, gt_txt, n_augmentations):
return data * n_augmentations, gt_txt * n_augmentations
class SimpleDataAugmenter(DataAugmenter):
def __init__(self):
super().__init__()
def augment_single(self, data, gt_txt):
import calamari_ocr.thirdparty.ocrodeg as ocrodeg
original_dtype = data.dtype
data = data.astype(np.float)
m = data.max()
data = data / (1 if m == 0 else m)
data = ocrodeg.random_pad(data, (0, data.shape[1] * 2))
# data = ocrodeg.transform_image(data, **ocrodeg.random_transform(rotation=(-0.1, 0.1), translation=(-0.1, 0.1)))
for sigma in [2, 5]:
noise = ocrodeg.bounded_gaussian_noise(data.shape, sigma, 3.0)
data = ocrodeg.distort_with_noise(data, noise)
data = ocrodeg.printlike_multiscale(data, blur=1, inverted=True)
data = (data * 255 / data.max()).astype(original_dtype)
return data, gt_txt
if __name__ == '__main__':
aug = SimpleDataAugmenter()
from PIL import Image
import numpy as np
img = 255 - np.mean(np.array(Image.open("../../test/data/uw3_50lines/train/010001.bin.png"))[:, :, 0:2], axis=-1)
aug_img = [aug.augment_single(img.T, '')[0].T for _ in range(4)]
import matplotlib.pyplot as plt
f, ax = plt.subplots(5, 1)
ax[0].imshow(255 - img, cmap='gray')
for i, x in enumerate(aug_img):
ax[i + 1].imshow(255 - x, cmap='gray')
plt.show()
| [
"wick.chr.info@gmail.com"
] | wick.chr.info@gmail.com |
32dc757a5cd4046d35cbdf7ab91781b3fac76911 | faa1bed2eee1a81c56aa147c39219faf18da7542 | /Algorithms/Binary search.py | f90d4ba5073e54666c1f9d16390e6b6ca9546d9f | [] | no_license | Dieterdemuynck/Informatica5 | 2f284fe20d1bffe579f602419cc61793e55b2f40 | 6507a4c3f90f0b43d37499bfa3c6fac1bd482094 | refs/heads/master | 2020-03-28T01:15:55.625344 | 2020-03-04T22:58:50 | 2020-03-04T22:58:50 | 147,491,195 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,385 | py | from random import randint
from time import time
import matplotlib.pyplot as plt
def genereer_rij(aantal):
rij = []
for i in range(aantal):
rij.append(randint(0, aantal))
return rij
def linear_search(lijst, getal):
index = 0
while index < len(lijst) and lijst[index] != getal:
index += 1
return index < len(lijst)
def binary_search(lijst, low, high, num):
if low > high:
return False
else:
mid = (high + low) // 2
if lijst[mid] == num:
return True
elif num < lijst[mid]:
return binary_search(lijst, low, mid - 1, num)
else:
return binary_search(lijst, mid + 1, high, num)
n, t_bs, t_ls = [], [], []
i = 10
while i < 30000:
rij_1 = genereer_rij(i)
rij_1.sort()
rij_2 = rij_1.copy()
getal = rij_1[randint(0, i)]
# Time of Binary Search
start = time()
binary_search(rij_1, 0, len(rij_1) - 1, getal)
stop = time()
t_bs.append(stop - start)
# Time of Linear Search
start = time()
linear_search(rij_2, getal)
stop = time()
t_ls.append(stop - start)
n.append(i)
i += 50
plt.plot(n, t_bs)
plt.plot(n, t_ls)
plt.xlabel("N")
plt.ylabel("t")
plt.gcf().legend(("binary search", "linear search"))
plt.gcf().canvas.set_window_title("Dieter Demuynck")
plt.title("Time measurements")
plt.show()
| [
"42997575+Dieterdemuynck@users.noreply.github.com"
] | 42997575+Dieterdemuynck@users.noreply.github.com |
6ae1b8647bd11e98a581eaf73d719c81166a3dd1 | ab3809c47ed79898a386bcb5c69b35e292ede0da | /10_linear_regression/10-linear-regression-l1-regularization-v2.py | 49e483fd2e2bd4e6f6c1e0d1f78fb0dd8035a804 | [] | no_license | ytphua/neural-network-journey | ac01d1a04da318e5cd7c405b4b3e43718a0acbec | 400218d9d51deab550c6e0cc56100dea46134b5b | refs/heads/master | 2021-01-19T08:34:19.758389 | 2017-05-30T15:19:48 | 2017-05-30T15:19:48 | 87,645,545 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,324 | py | # -*- coding: utf-8 -*-
"""
Created on Thu Apr 27 01:16:33 2017
@author: tsann
"""
# demonstration of Lq regularization
# notes for this course can be found at:
# https://deeplearningcourses.com/c/data-science-linear-regression-in-python
# https://www.udemy.com/data-science-linear-regression-in-python
import numpy as np
import matplotlib.pyplot as plt
N = 50
D = 50
# uniformly distributed numbers between -5, +5
X = (np.random.random((N, D)) - 0.5)*10
# true weights - only the first 3 dimensions of X affect Y
true_w = np.array([1, 0.5, -0.5] + [0]*(D - 3))
# generate Y - add noise with variance 0.5
Y = X.dot(true_w) + np.random.randn(N)*0.5
# perform gradient descent to find w
costs = [] # keep track of squared error cost
w = np.random.randn(D) / np.sqrt(D) # randomly initialize w
learning_rate = 0.001
l1 = 10.0 # Also try 5.0, 2.0, 1.0, 0.1 - what effect does it have on w?
for t in range(500):
# update w
Yhat = X.dot(w)
delta = Yhat - Y
w = w - learning_rate*(X.T.dot(delta) + l1*np.sign(w))
# find and store the cost
mse = delta.dot(delta) / N
costs.append(mse)
# plot the costs
plt.plot(costs)
plt.show()
print("final w:", w)
# plot our w vs true w
plt.plot(true_w, label='true w')
plt.plot(w, label='w_map')
plt.legend()
plt.show() | [
"noreply@github.com"
] | ytphua.noreply@github.com |
f29647293bd6af206cef161d225d68f0791921b6 | 9551a145d23227da1e5b2435eacee5699f287f7c | /config.py | 93acbcb5c6535f2a073ab8521b8fe10b3c2ad6b7 | [
"BSD-2-Clause"
] | permissive | doccaz/labvirtual | 0aa1d515e06be4995033f1f141393846f9109069 | e7fd64dece564dac8e81e80e620f1e0027cd4821 | refs/heads/master | 2022-01-20T18:33:26.992502 | 2022-01-13T15:39:30 | 2022-01-13T15:39:30 | 164,643,200 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 445 | py | config = {}
# may be 'plain' or 'ldap'
config['auth_mode'] = 'plain'
config['default_user'] = 'admin'
config['default_password'] = 'password'
config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:////tmp/labvirtual.db'
config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
# LDAP
config['LDAP_PROVIDER_URL'] = ''
config['LDAP_BIND_USER'] = ''
config['LDAP_BIND_DN'] = ''
config['LDAP_AUTHTOK'] = ''
config['LDAP_SEARCH_BASE'] = ''
config['LDAP_CACERT'] = ''
| [
"erico.mendonca@gmail.com"
] | erico.mendonca@gmail.com |
a9646b77be199b198cdb4b745d77807e2be1849b | 4c56ffeef9bdd423c2946e7848d8c96e00ba36cb | /Day18/bluegill.py | e6aef0dc9efa15820196129abb5e68cb7de5aade | [] | no_license | adityatanwar800/FSDP2019 | 8f27281c676db4e1e405b1cc2936a3fa24583c6e | c02587a8feab753eff60b81546cb61a71950159b | refs/heads/master | 2020-06-04T07:21:13.422349 | 2019-07-12T11:54:44 | 2019-07-12T11:54:44 | 191,921,881 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,473 | py | # -*- coding: utf-8 -*-
"""
Created on Wed Jun 26 16:57:11 2019
@author: Aditya Tanwar
"""
import pandas as pd
import matplotlib.pyplot as plt
# Importing the dataset
dataset = pd.read_csv('bluegills.csv')
features = dataset.iloc[:, 0:1].values
labels = dataset.iloc[:, 1].values
#let's first analyze the data
# Visualising the Linear Regression results
plt.scatter(features, labels)
# Fitting Linear Regression to the dataset
from sklearn.linear_model import LinearRegression
lin_reg_1 = LinearRegression()
lin_reg_1.fit(features, labels)
print ("Predicting result with Linear Regression")
print (lin_reg_1.predict(1981))
# Visualising the Linear Regression results
plt.scatter(features, labels, color = 'red')
plt.plot(features, lin_reg_1.predict(features), color = 'blue')
plt.title('Linear Regression')
plt.xlabel('age')
plt.ylabel('length')
plt.show()
from sklearn.preprocessing import PolynomialFeatures
poly_object = PolynomialFeatures(degree = 5)
features_poly = poly_object.fit_transform(features)
lin_reg_2 = LinearRegression()
lin_reg_2.fit(features_poly, labels)
print ("Predicting result with Polynomial Regression")
print (lin_reg_2.predict(poly_object.transform(1981)))
# Visualising the Polynomial Regression results
plt.scatter(features, labels, color = 'red')
plt.plot(features, lin_reg_2.predict(poly_object.fit_transform(features)), color = 'blue')
plt.title('Polynomial Regression')
plt.xlabel('age')
plt.ylabel('length')
plt.show() | [
"adityatanwar800@gmail.com"
] | adityatanwar800@gmail.com |
c07d4fd9018a401b7114051c120ec27433b0d250 | 5eed98727f532c43f2d2828e5e48ee363a8c207f | /fizzbuzz.py | 86d1a353abc4c227b3d98a7eceb3a4733decef4d | [] | no_license | Revathy-2001/FizzBuzz | b5ecb64fc546268d5e156c35594a1fcf732ed7f9 | 589ca09717503bc3064d276a857427e5dd793ba4 | refs/heads/main | 2023-02-11T03:24:22.546269 | 2021-01-13T09:31:01 | 2021-01-13T09:31:01 | 329,256,188 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 272 | py | lst = list(input().split())
x = int(lst[0])
y = int(lst[1])
n = int(lst[2])
i = 1
while(i <= n):
if(i % x == 0 and i % y == 0):
print("FizzBuzz");
elif(i % x == 0):
print("Fizz");
elif(i % y == 0):
print("Buzz");
else:
print(i);
i+=1 | [
"noreply@github.com"
] | Revathy-2001.noreply@github.com |
e896b3f80b3a68852af49583bc94ead4fd78ab4b | 1e02ebc24595756f064ffa1fa42e508d1da8069b | /users/views.py | 4448189d5c8157ebf319fda91d0bc912236c7b02 | [] | no_license | ubaid6/EventApp | 9a5ef89f1ea0c5f876e0aad7116ea75820d9c16a | bc8cfd4cbfc857aec8a13928661574e856e870fe | refs/heads/master | 2023-08-17T04:28:13.478245 | 2021-09-20T22:25:56 | 2021-09-20T22:25:56 | 401,118,207 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,772 | py | from django.shortcuts import render, redirect, reverse
from django.urls import reverse_lazy
from django.contrib import messages
from .forms import RegistrationForm, ChangeForm
from django.contrib.auth.forms import UserCreationForm, UserChangeForm
from .models import User
from django.contrib.auth.decorators import login_required
from .utils import emailToken
from django.contrib.sites.shortcuts import get_current_site
from django.utils.http import urlsafe_base64_encode, urlsafe_base64_decode
from django.utils.encoding import force_bytes, force_text, force_str
from django.template.loader import render_to_string
from django.core.mail import send_mail
from django.http import HttpResponse
from django.contrib.auth.views import LoginView
from django.contrib.auth.forms import AuthenticationForm
from django.contrib.auth import authenticate
from django.contrib.auth import login as auth_login
from django.conf import settings
# Create your views here.
def register(request):
if request.method == 'POST':
form = RegistrationForm(request.POST)
if form.is_valid():
form.save()
username = form.cleaned_data.get('username')
messages.success(request, f'Account created for {username}')
user = User.objects.get(username=username)
sendActivationEmail(request, user)
return redirect('login')
else:
form = RegistrationForm()
return render(request, 'users/register.html', {'form': form})
@login_required(login_url='login')
def viewprofile(request):
args = {
'user' : request.user
}
return render(request, 'users/viewprofile.html', args)
@login_required(login_url='login')
def editprofile(request):
if request.method == "POST":
form = ChangeForm(request.POST, instance=request.user)
if form.is_valid():
form.save()
username = form.cleaned_data.get('username')
messages.success(request, f'Details changed for {username}')
return redirect('events-home')
else:
form = ChangeForm()
return render(request, 'users/editprofile.html', {'form': form})
def sendActivationEmail(request, user):
send_mail(
'Activate your account',
render_to_string('users/activate.html', {
'user': user,
'domain': get_current_site(request),
'uid': urlsafe_base64_encode(force_bytes(user.pk)),
'token': emailToken.make_token(user)
}),
settings.EMAIL_FROM_USER,
[user.email],
fail_silently=False,
)
def activateEmail(request, uidb64, token):
try:
uid = force_text(urlsafe_base64_decode(uidb64))
user = User.objects.get(pk=uid)
except Exception as e:
print("Wrong")
if user and emailToken.check_token(user, token):
user.emailAuthenticated = True
user.save()
messages.success(request, 'Email Verified!')
return redirect(reverse('events-home'))
messages.success(request, 'Email Not Verified!')
return render(request, 'events/events.html')
def login(request):
if request.method == "POST":
form = AuthenticationForm(request.POST)
username = request.POST['username']
password = request.POST['password']
user = authenticate(username=username, password=password)
if user:
if user.emailAuthenticated:
auth_login(request, user)
return redirect('events-home')
else:
sendActivationEmail(request, user)
return redirect('login')
else:
return redirect('login')
form = AuthenticationForm()
return render(request, 'users/login.html', {'form': form})
| [
"ubaid.ahmed@student.manchester.ac.uk"
] | ubaid.ahmed@student.manchester.ac.uk |
91a08addb60a782a9051a56d58e38994d14e8b72 | 1bbe05a0b1dfabe31cd740172b44a7435dcc36c5 | /caesar.py | 419682ae9f9967bba73009c4550b825e10e7fd4e | [] | no_license | jkketts/web-caesar | 4fb06dedc5886234bced11c39d6a0b3e16fa2572 | 4060411e04b42baee8198d1653a44391ab176c90 | refs/heads/master | 2021-01-23T18:24:38.041388 | 2017-09-19T03:24:23 | 2017-09-19T03:24:23 | 102,793,419 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 658 | py | def encrypt(text,rot):
newStr = ""
rot = rot % 26
for i in text:
if (ord(i) >= 97 and ord(i) <= 122):
if (ord(i)+rot > 122):
newStr += chr((ord(i)+rot) - 26)
else:
newStr += chr(ord(i)+rot)
elif (ord(i) >= 65 and ord(i) <= 90):
if (ord(i)+rot > 90):
newStr += chr((ord(i)+rot) - 26)
else:
newStr += chr(ord(i)+rot)
else:
newStr += i
return newStr
def main():
text = input('Type a message:')
rot = int(input('Rotate By:'))
encrypt(text, rot)
if __name__ == "__main__":
main() | [
"justin@ketterman.tv"
] | justin@ketterman.tv |
4b3e25f31c3a5111a410257b0f0cde13440de95b | f1f28cb54bbec83c7783e0a89b4e1efa776ffdaf | /jetcam/jetcam/usb_camera.py | 1a513e62b5f257e30fc47c7a8b7420acbc04c3a4 | [
"MIT"
] | permissive | KNChiu/Jetson_nano | f4c19e00678d186a50d0ccea6f7ea9727b7470a3 | 4d0608119a971875ae3406f27d73585490fe51ca | refs/heads/master | 2020-07-11T00:21:18.994812 | 2020-03-20T02:44:08 | 2020-03-20T02:44:08 | 204,408,145 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,503 | py | from .camera import Camera
import atexit
import cv2
import numpy as np
import threading
import traitlets
class USBCamera(Camera):
capture_fps = traitlets.Integer(default_value=30)
capture_width = traitlets.Integer(default_value=640)
capture_height = traitlets.Integer(default_value=480)
capture_device = traitlets.Integer(default_value=0)
def __init__(self, *args, **kwargs):
super(USBCamera, self).__init__(*args, **kwargs)
try:
self.cap = cv2.VideoCapture(self._gst_str(), cv2.CAP_GSTREAMER)
re , image = self.cap.read()
if not re:
raise RuntimeError('Could not read image from camera.')
except:
raise RuntimeError(
'Could not initialize camera. Please see error trace.')
atexit.register(self.cap.release)
def _gst_str(self):
return 'v4l2src device=/dev/video{} ! video/x-raw, width=(int){}, height=(int){}, framerate=(fraction){}/1 ! videoconvert ! video/x-raw, , format=(string)BGR ! appsink'.format(self.capture_device, self.capture_width, self.capture_height, self.capture_fps)
def _read(self):
re, image = self.cap.read()
if re:
image_resized = cv2.resize(image,(int(self.width),int(self.height)))
return image_resized
else:
raise RuntimeError('Could not read image from camera')
| [
"noreply@github.com"
] | KNChiu.noreply@github.com |
d22f297ce672e3b72fd02a3ea4ed803806c3ffd5 | f896126719c9c2c8db07b8a7cf43364ad8d27dff | /examples/creating_tasklists_with_python/run_simba3d_within_python_script.py | 6f7ea2f3e4c8b469b93ca29d85f356b90943587c | [
"BSD-3-Clause"
] | permissive | jayguoxue/SIMBA3D | f948bf23d90d12453ac76493f28813e2e9dbb4f6 | ac347e95e8a259bfaa2ddc5a0e38c73f0eeac511 | refs/heads/master | 2020-12-08T13:34:36.933237 | 2019-02-28T13:12:18 | 2019-02-28T13:12:18 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,970 | py | # -*- coding: utf-8 -*-
"""
An example of creating tasklists
Created on Thu Sep 07 05:53:57 2017
@author: Michael Rosenthal
"""
import os
import numpy as np
import uuid
# import simplejson or json
#
# This is useful because the syntax is pythonic, it's human readable, and it
# can be read by other programs in other languages.
#
# json is potentially and older version of simplejson which is updated more
# frequently than Python
#
# A good practice is to use one or the other as a fallback.
try: import simplejson as json # try to import simplejson
except ImportError: import json #otherwise import json
import simba3d.mp_manager as mp
import time
taskfilepath='tasklist.json'
cores=1; # the number of parallel process to run simultateously
tasks=[]
lambda_2=0.5;
lambda_3=0.5;
for lambda_1 in np.linspace(0,1,11):
UUID=uuid.uuid4()
tasks.append(
{
# task parameters
'usewarmstarts':True,
'taskname' : str(UUID),
'uuid' : str(UUID),# assign a unique identifier to resume tasklists
# initialization settings
'randomize_initialization' : False, # Randomize the initialized curve
#'seed' : int(np.random.rand()*4294967295), # fixed seed for randomizing inititialization
# debug options
'check_jacobian' : False, # check analytical gradient with numerical gradient 9
# data file names to load
'file_names' :
{
'inputdir' : 'data/', # location of data input files
'outputdir' : 'results/', # directory where to output results
# the following are relative to the inputdir directory
"initialized_curve" : 'initialized_curve.npy',
"pairwise_contact_matrix" : 'simulated_contact_matrix.npy',
#"population_contact_matrix" : 'population_mESC_M19_a.npy',
#"prior_shape_model" : 'prior_shape_model.npy',
"output_filename" : str(UUID)+'.npy',
},
# data
'data' :
{
#'initialized_curve' : initialized_curve,
#'t' : t, # optional
#'pairwise_contact_matrix' : [],
#'index' : index,
#'population_contact_matrix' : pairwise_contact_pop,
#'prior_shape_model' : prior_shape_model,
},
# parameter settings
'parameters' :
{
'a' : -3.0,
'b' : 1.0, # not identifiable with unconstrained scale
'term_weights' :
{
'data' : 1.0, # weight for the data term
'uniform spacing' : lambda_1, # scaled first order penalty
'smoothing' : lambda_2, # scaled second order penalty
'population prior' : lambda_3, # weight for the population matrix prior
'shape prior' : 0.0, # weight for the shape prior
# below are unsupported penalties
#'firstroughness' :0.0e3, # weight for the fist order roughness
#'secondroughness' :0.0e-16, # weight for the second order roughness
#'scaledfirstroughness' :0.0, # weight for the scaled second order roughness
#'scaledsecondroughness' :0.0, # weight for the scaled second order roughness
#'parameterization' :0, # not implemented
},
},
# options
'options' :
{
'maxitr' : 100000, # set maximum number of iterations
'display' : True, # display function values at each iteration
'store' : False, # store iterative curves
'method' : 'BFGS',# Broyden, Fletcher, Goldfarb, and Shanno (quasi-Newton, only first derivatives are used)
#'method' :'Nelder-Mead',# robust but slow numerical approach
#'method' :'CG',# nonlinear conjugate gradient algorithm by Polak and Ribiere (only first derivatives are used)
#'method' :'Newton-CG',# (truncated Newton method)
'gradient tolerance' : 1e-5,
},
}
)
#Use JSON to write the tasklist to file
# if you want to save the task for posterity
with open(taskfilepath, 'w') as tasklist:
json.dump(tasks, tasklist,indent=4,sort_keys=True) # pretty print the JSON to make it human readible
#json.dump(tasks, tasklist) # if you don't care about pretty printing the JSON just dump it this way
#run simba3d
# tasks=json.load(tasklist) # if you want to load the tasklist from file
t= time.time()
mp.mp_handler(tasks,cores)
elapsed=time.time()-t
print 'Total %s seconds elapsed' % (elapsed)
#%%
| [
"nicola_neretti@brown.edu"
] | nicola_neretti@brown.edu |
f4c441b7a7ed9caedc9f2218e285512eae6f6d7d | 2e144fab7c6f9641a9b8671ab420681a09bd4970 | /second_win_rc.py | 04c7faa3593b15c7af8ea9ac6a7b1170db59a567 | [] | no_license | AsmaaGHSamir/GProject | d6f37358792eb586c6d1a638b4e0db2c71b2a961 | 0ffe5d496d1171291f57589064a37af6eabd626d | refs/heads/main | 2023-06-11T05:40:53.445020 | 2021-07-08T07:27:54 | 2021-07-08T07:27:54 | 384,010,670 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 103,449 | py | # -*- coding: utf-8 -*-
# Resource object code
#
# Created by: The Resource Compiler for PyQt5 (Qt v5.15.2)
#
# WARNING! All changes made in this file will be lost!
from PyQt5 import QtCore
qt_resource_data = b"\
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qt_resource_name = b"\
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qt_resource_struct_v1 = b"\
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qt_resource_struct_v2 = b"\
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qt_version = [int(v) for v in QtCore.qVersion().split('.')]
if qt_version < [5, 8, 0]:
rcc_version = 1
qt_resource_struct = qt_resource_struct_v1
else:
rcc_version = 2
qt_resource_struct = qt_resource_struct_v2
def qInitResources():
QtCore.qRegisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
def qCleanupResources():
QtCore.qUnregisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data)
qInitResources()
| [
"noreply@github.com"
] | AsmaaGHSamir.noreply@github.com |
3a06956157681d057f7bbdbc8f747d55509f04c2 | 1aedc28d527f0245b7b1ab85ad19345b05cffb1a | /serializers.py | f6d7561ce770043541b7dd6a835f2450d24b3f3a | [] | no_license | YuTaeKim/Portfolio | 712dbd919128a9a6ba7d2a2d6cdf5cd104bfdc55 | 295c4364b824024e91cc6453099b7e7b66133bf7 | refs/heads/main | 2023-04-13T17:33:08.714537 | 2021-04-25T12:55:06 | 2021-04-25T12:55:06 | 356,792,291 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,538 | py | # Django를 이용한 Data Serializing
import random
import re
from apps.report.models import Report, ReportImage, Comment, ReportHealth
from apps.account.models import User
from api.account.serializers import UserSerializer
from api.center.serializers import CenterSerializer, ProtectorSerializer, GuardianSerializer, ElderSerializer
from django.contrib.auth.password_validation import validate_password
from django.core.exceptions import ValidationError as DjangoValidationError
from django.core.exceptions import ObjectDoesNotExist
from django.utils import timezone
from rest_framework import serializers
from rest_framework.exceptions import ValidationError
from drf_extra_fields.fields import Base64ImageField
class ReportImageSerializer(serializers.ModelSerializer):
file = Base64ImageField()
report = serializers.PrimaryKeyRelatedField(queryset=Report.objects.all(), write_only=True, many=True)
class Meta:
model = ReportImage
fields = (
'id',
'report',
'file'
)
class CommentSerializer(serializers.ModelSerializer):
class CommentUserSerializer(serializers.ModelSerializer):
class Meta:
model = User
fields = (
'id',
'type',
)
read_only_fields = ('type',)
user = CommentUserSerializer()
report = serializers.PrimaryKeyRelatedField(write_only=True, queryset=Report.objects.all())
is_mine = serializers.SerializerMethodField()
class Meta:
model = Comment
fields = (
"id",
"message",
"created_at",
"user",
'report',
"is_mine"
)
def get_is_mine(self, obj):
user = self.context['request'].user
if obj.user == user:
return True
return False
class CreateCommentSerializer(serializers.ModelSerializer):
class Meta:
model = Comment
fields = (
"id",
"user",
"message",
'report',
)
class CreateReportHealthSerializer(serializers.ModelSerializer):
class Meta:
model = ReportHealth
fields = (
'report',
'feeling',
'health',
'temperature',
'meal',
'feces',
'sleeping'
)
class ReportHealthSerializer(serializers.ModelSerializer):
feeling = serializers.SerializerMethodField()
health = serializers.SerializerMethodField()
temperature = serializers.SerializerMethodField()
meal = serializers.SerializerMethodField()
feces = serializers.SerializerMethodField()
sleeping = serializers.SerializerMethodField()
class Meta:
model = ReportHealth
fields = (
'feeling',
'health',
'temperature',
'meal',
'feces',
'sleeping'
)
def get_feeling(self, obj):
return obj.get_feeling_display()
def get_health(self, obj):
return obj.get_health_display()
def get_temperature(self, obj):
return obj.get_temperature_display()
def get_meal(self, obj):
return obj.get_meal_display()
def get_feces(self, obj):
return obj.get_feces_display()
def get_sleeping(self, obj):
return obj.get_sleeping_display()
class ReportSerializer(serializers.ModelSerializer):
class ReportUserSerializer(serializers.ModelSerializer):
class Meta:
model = User
fields = (
'id',
'image',
'type',
)
read_only_fields = ('image', 'type')
images = serializers.SerializerMethodField()
comments = serializers.SerializerMethodField()
health = serializers.SerializerMethodField()
is_read = serializers.SerializerMethodField()
is_mine = serializers.SerializerMethodField()
read_people = serializers.PrimaryKeyRelatedField(queryset=User.objects.all(), many=True, write_only=True)
elder = serializers.SerializerMethodField()
user = ReportUserSerializer()
class Meta:
model = Report
fields = (
'id',
'user',
'center',
'elder',
'content',
'created_at',
'health',
'images',
'comments',
'is_read',
'is_mine',
'read_people',
)
def get_elder(self, obj):
return obj.elder.name
def get_is_mine(self, obj):
user = self.context['request'].user
if obj.user == user:
return True
return False
def get_is_read(self, obj):
if self.context['request'].user in obj.read_people.all():
return True
else:
return False
def get_health(self, obj):
if hasattr(obj, 'reporthealth'):
return ReportHealthSerializer(obj.reporthealth).data
return None
def get_images(self, obj):
images = obj.reportimage_set.all()
return ReportImageSerializer(images, many=True).data
def get_comments(self, obj):
comments = obj.comment_set.all()
return CommentSerializer(comments, context=self.context, many=True).data
class CreateReportSerializer(serializers.ModelSerializer):
class Meta:
model = Report
fields = (
'user',
'center',
'elder',
'content',
)
| [
"noreply@github.com"
] | YuTaeKim.noreply@github.com |
9bda4428cf6c2017095ed83c9dc0e3ab523a3edb | 668ff51f34eac31931511ec3641c66f82bffaee5 | /myewb/apps/group_announcements/models.py | 039c3d7087e4a04bedbd932f3d39489865c41b80 | [] | no_license | ewbcanada/myewb2 | 4a81668b37b286638ad80c9f2535770ada200cfc | 50cf7698899bed1b31d0a637f72a1e9a5b7fa07a | refs/heads/master | 2020-12-01T01:15:09.592117 | 2011-10-18T22:02:07 | 2011-10-18T22:02:07 | 380,073 | 3 | 6 | null | null | null | null | UTF-8 | Python | false | false | 3,905 | py |
from datetime import datetime
from django.db import models
from django.db.models import Q
from django.conf import settings
from django.contrib.auth.models import User
from django.core.urlresolvers import reverse
from django.utils.translation import ugettext_lazy as _
from base_groups.models import BaseGroup, GroupMember
from lxml.html.clean import clean_html, autolink_html, Cleaner
try:
set
except NameError:
from sets import Set as set # Python 2.3 fallback
class AnnouncementManager(models.Manager):
"""
A basic manager for dealing with announcements.
"""
def current(self, exclude=[], site_wide=False, for_members=False,
user=None):
"""
Fetches and returns a queryset with the current announcements. This
method takes the following parameters:
``exclude``
A list of IDs that should be excluded from the queryset.
``site_wide``
A boolean flag to filter to just site wide announcements.
``for_members``
A boolean flag to allow member only announcements to be returned
in addition to any others.
``user``
A User object: if provided will also show group-specific messages
that this user should see
"""
queryset = self.all()
#if site_wide:
# queryset = queryset.filter(site_wide=True)
if exclude:
queryset = queryset.exclude(pk__in=exclude)
if not for_members:
queryset = queryset.filter(members_only=False)
userfilter = Q(parent_group__isnull=True)
if user:
userfilter = userfilter | Q(parent_group__member_users=user)
queryset = queryset.filter(userfilter)
queryset = queryset.order_by("-creation_date")
return queryset
class Announcement(models.Model):
"""
A single announcment.
"""
title = models.CharField(_("title"), max_length=50)
content = models.TextField(_("content"))
creator = models.ForeignKey(User, verbose_name=_("creator"))
creation_date = models.DateTimeField(_("creation_date"), default=datetime.now)
#site_wide = models.BooleanField(_("site wide"), default=False)
members_only = models.BooleanField(_("members only"), default=False)
parent_group = models.ForeignKey(BaseGroup, verbose_name=_("parent group"),
null=True, blank=True)
objects = AnnouncementManager()
def get_absolute_url(self):
return ("announcement_detail", [str(self.pk)])
get_absolute_url = models.permalink(get_absolute_url)
def save(self, force_insert=False, force_update=False):
# validate HTML content
# Additional options at http://codespeak.net/lxml/lxmlhtml.html#cleaning-up-html
self.content = clean_html(self.content)
#self.content = autolink_html(self.content)
super(Announcement, self).save(force_insert, force_update)
def __unicode__(self):
return self.title
class Meta:
verbose_name = _("announcement")
verbose_name_plural = _("announcements")
def current_announcements_for_request(request, **kwargs):
"""
A helper function to get the current announcements based on some data from
the HttpRequest.
If request.user is authenticated then allow the member only announcements
to be returned.
Exclude announcements that have already been viewed by the user based on
the ``excluded_announcements`` session variable.
"""
defaults = {}
if request.user.is_authenticated():
defaults["for_members"] = True
defaults["user"] = request.user
defaults["exclude"] = request.session.get("excluded_announcements", set())
defaults.update(kwargs)
return Announcement.objects.current(**defaults)
| [
"franciskung@ewb.ca"
] | franciskung@ewb.ca |
6f2b140930deb418dd4c750f4692b79492bb2a36 | 4a2a274cb52e36777484986be6c0d6d7a318aa82 | /libs/file_utils.py | c35904295c33982deaacdd275ee629c661571089 | [
"Apache-2.0"
] | permissive | Adamage/text_comprehension_chatbot | d270a1b627e63200aca1dcfffee591dea6a47594 | 30e6d014283d6b00402ae7cebb4ab7b28474f6d5 | refs/heads/master | 2021-01-20T01:50:10.388977 | 2017-05-04T20:15:24 | 2017-05-04T20:15:24 | 89,331,142 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 530 | py | import urllib.request
import os
class file_utils:
@staticmethod
def download_file(url, output_file_name):
print("Downloading from url: {0}, to: {1}".format(url, output_file_name))
try:
urllib.request.urlretrieve(url, filename=output_file_name)
except Exception as e:
print("Failed to download file. Details: " + str(e))
raise
@staticmethod
def ensure_folder_exists(dir_path):
if not os.path.isdir(dir_path):
os.makedirs(dir_path)
| [
"kraftunek@gmail.com"
] | kraftunek@gmail.com |
de0174b43db226b6cff8d1ff095d2e7c248442a0 | fdffd21d2ff1019d3dfab76167c8adf5830d05db | /babyai/levels/levelgen.py | e27645893ab00e53f2db09925c402bea5d6be7c9 | [
"BSD-3-Clause"
] | permissive | Simonyano/babyai-emergent-guidance | caf972645a2dc886051449480744a024fe18a34b | 9e37535134c89bd019affa51c7f199d1672811b6 | refs/heads/master | 2023-05-22T18:56:16.165055 | 2019-10-03T14:52:00 | 2019-10-03T14:52:00 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 16,590 | py | import random
from collections import OrderedDict
from copy import deepcopy
import gym
from gym_minigrid.roomgrid import RoomGrid
from .verifier import *
#Mathijs:
from gym_minigrid.minigrid import LockedDoor
class RejectSampling(Exception):
"""
Exception used for rejection sampling
"""
pass
class RoomGridLevel(RoomGrid):
"""
Base for levels based on RoomGrid
A level, given a random seed, generates missions generated from
one or more patterns. Levels should produce a family of missions
of approximately similar difficulty.
"""
def __init__(
self,
room_size=8,
**kwargs
):
super().__init__(
room_size=room_size,
**kwargs
)
def reset(self, **kwargs):
obs = super().reset(**kwargs)
# Recreate the verifier
self.instrs.reset_verifier(self)
# Compute the time step limit based on the maze size and instructions
nav_time_room = self.room_size ** 2
nav_time_maze = nav_time_room * self.num_rows * self.num_cols
num_navs = self.num_navs_needed(self.instrs)
self.max_steps = num_navs * nav_time_maze
return obs
def step(self, action):
obs, reward, done, info = super().step(action)
# If we drop an object, we need to update its position in the environment
if action == self.actions.drop:
self.update_objs_poss()
# If we've successfully completed the mission
status = self.instrs.verify(action)
if status is 'success':
done = True
reward = self._reward()
elif status is 'failure':
done = True
reward = 0
return obs, reward, done, info
def update_objs_poss(self, instr=None):
if instr is None:
instr = self.instrs
if isinstance(instr, BeforeInstr) or isinstance(instr, AndInstr) or isinstance(instr, AfterInstr):
self.update_objs_poss(instr.instr_a)
self.update_objs_poss(instr.instr_b)
else:
instr.update_objs_poss()
def _gen_grid(self, width, height):
# We catch RecursionError to deal with rare cases where
# rejection sampling gets stuck in an infinite loop
while True:
try:
super()._gen_grid(width, height)
# Generate the mission
self.gen_mission()
# Validate the instructions
self.validate_instrs(self.instrs)
except RecursionError as error:
print('Timeout during mission generation:', error)
continue
except RejectSampling as error:
#print('Sampling rejected:', error)
continue
break
# Generate the surface form for the instructions
self.surface = self.instrs.surface(self)
self.mission = self.surface
def validate_instrs(self, instr):
"""
Perform some validation on the generated instructions
"""
# Gather the colors of locked doors
if hasattr(self, 'unblocking') and self.unblocking:
colors_of_locked_doors = []
for i in range(self.num_rows):
for j in range(self.num_cols):
room = self.get_room(i, j)
for door in room.doors:
#Mathijs
#if door and door.is_locked:
if door and isinstance(door, LockedDoor):
colors_of_locked_doors.append(door.color)
if isinstance(instr, PutNextInstr):
# Resolve the objects referenced by the instruction
instr.reset_verifier(self)
# Check that the objects are not already next to each other
if instr.objs_next():
raise RejectSampling('objs already next to each other')
# Check that we are not asking to move an object next to itself
move = instr.desc_move
fixed = instr.desc_fixed
if len(move.obj_set) == 1 and len(fixed.obj_set) == 1:
if move.obj_set[0] is fixed.obj_set[0]:
raise RejectSampling('cannot move an object next to itself')
if isinstance(instr, ActionInstr):
if not hasattr(self, 'unblocking') or not self.unblocking:
return
# TODO: either relax this a bit or make the bot handle this super corner-y scenarios
# Check that the instruction doesn't involve a key that matches the color of a locked door
potential_objects = ('desc', 'desc_move', 'desc_fixed')
for attr in potential_objects:
if hasattr(instr, attr):
obj = getattr(instr, attr)
if obj.type == 'key' and obj.color in colors_of_locked_doors:
raise RejectSampling('cannot do anything with/to a key that can be used to open a door')
return
if isinstance(instr, SeqInstr):
self.validate_instrs(instr.instr_a)
self.validate_instrs(instr.instr_b)
return
assert False, "unhandled instruction type"
def gen_mission(self):
"""
Generate a mission (instructions and matching environment)
Derived level classes should implement this method
"""
raise NotImplementedError
@property
def level_name(self):
return self.__class__.level_name
@property
def gym_id(self):
return self.__class__.gym_id
def num_navs_needed(self, instr):
"""
Compute the maximum number of navigations needed to perform
a simple or complex instruction
"""
if isinstance(instr, PutNextInstr):
return 2
if isinstance(instr, ActionInstr):
return 1
if isinstance(instr, SeqInstr):
na = self.num_navs_needed(instr.instr_a)
nb = self.num_navs_needed(instr.instr_b)
return na + nb
def open_all_doors(self):
"""
Open all the doors in the maze
"""
for i in range(self.num_rows):
for j in range(self.num_cols):
room = self.get_room(i, j)
for door in room.doors:
if door:
door.is_open = True
def check_objs_reachable(self, raise_exc=True):
"""
Check that all objects are reachable from the agent's starting
position without requiring any other object to be moved
(without unblocking)
"""
# Reachable positions
reachable = set()
# Work list
stack = [self.start_pos]
while len(stack) > 0:
i, j = stack.pop()
if i < 0 or i >= self.grid.width or j < 0 or j >= self.grid.height:
continue
if (i, j) in reachable:
continue
# This position is reachable
reachable.add((i, j))
cell = self.grid.get(i, j)
# If there is something other than a door in this cell, it
# blocks reachability
if cell and cell.type is not 'door':
continue
# Visit the horizontal and vertical neighbors
stack.append((i+1, j))
stack.append((i-1, j))
stack.append((i, j+1))
stack.append((i, j-1))
# Check that all objects are reachable
for i in range(self.grid.width):
for j in range(self.grid.height):
cell = self.grid.get(i, j)
if not cell or cell.type is 'wall':
continue
if (i, j) not in reachable:
if not raise_exc:
return False
raise RejectSampling('unreachable object at ' + str((i, j)))
# All objects reachable
return True
class LevelGen(RoomGridLevel):
"""
Level generator which attempts to produce every possible sentence in
the baby language as an instruction.
"""
def __init__(
self,
room_size=8,
num_rows=3,
num_cols=3,
num_dists=18,
locked_room_prob=0.5,
locations=True,
unblocking=True,
implicit_unlock=True,
action_kinds=['goto', 'pickup', 'open', 'putnext'],
instr_kinds=['action', 'and', 'seq'],
seed=None
):
self.num_dists = num_dists
self.locked_room_prob = locked_room_prob
self.locations = locations
self.unblocking = unblocking
self.implicit_unlock = implicit_unlock
self.action_kinds = action_kinds
self.instr_kinds = instr_kinds
self.locked_room = None
super().__init__(
room_size=room_size,
num_rows=num_rows,
num_cols=num_cols,
seed=seed
)
def gen_mission(self):
self.place_agent()
if self._rand_float(0, 1) < self.locked_room_prob:
self.add_locked_room()
self.connect_all()
self.add_distractors(num_distractors=self.num_dists, all_unique=False)
# If no unblocking required, make sure all objects are
# reachable without unblocking
if not self.unblocking:
self.check_objs_reachable()
# Generate random instructions
self.instrs = self.rand_instr(
action_kinds=self.action_kinds,
instr_kinds=self.instr_kinds
)
def add_locked_room(self):
start_room = self.room_from_pos(*self.start_pos)
# Until we've successfully added a locked room
while True:
i = self._rand_int(0, self.num_cols)
j = self._rand_int(0, self.num_rows)
door_idx = self._rand_int(0, 4)
self.locked_room = self.get_room(i, j)
# Don't lock the room the agent starts in
if self.locked_room is start_room:
continue
# Don't add a locked door in an external wall
if self.locked_room.neighbors[door_idx] is None:
continue
door, _ = self.add_door(
i, j,
door_idx,
locked=True
)
# Done adding locked room
break
# Until we find a room to put the key
while True:
i = self._rand_int(0, self.num_cols)
j = self._rand_int(0, self.num_rows)
key_room = self.get_room(i, j)
if key_room is self.locked_room:
continue
self.add_object(i, j, 'key', door.color)
break
def rand_obj(self, types=OBJ_TYPES, colors=COLOR_NAMES, max_tries=100):
"""
Generate a random object descriptor
"""
num_tries = 0
# Keep trying until we find a matching object
while True:
if num_tries > max_tries:
raise RecursionError('failed to find suitable object')
num_tries += 1
color = self._rand_elem([None, *colors])
type = self._rand_elem(types)
loc = None
if self.locations and self._rand_bool():
loc = self._rand_elem(LOC_NAMES)
desc = ObjDesc(type, color, loc)
# Find all objects matching the descriptor
objs, poss = desc.find_matching_objs(self)
# The description must match at least one object
if len(objs) == 0:
continue
# If no implicit unlocking is required
if not self.implicit_unlock and self.locked_room:
# Check that at least one object is not in the locked room
pos_not_locked = list(filter(
lambda p: not self.locked_room.pos_inside(*p),
poss
))
if len(pos_not_locked) == 0:
continue
# Found a valid object description
return desc
def rand_instr(
self,
action_kinds,
instr_kinds,
depth=0
):
"""
Generate random instructions
"""
kind = self._rand_elem(instr_kinds)
if kind is 'action':
action = self._rand_elem(action_kinds)
if action is 'goto':
return GoToInstr(self.rand_obj())
elif action is 'pickup':
return PickupInstr(self.rand_obj(types=OBJ_TYPES_NOT_DOOR))
elif action is 'open':
return OpenInstr(self.rand_obj(types=['door']))
elif action is 'putnext':
return PutNextInstr(
self.rand_obj(types=OBJ_TYPES_NOT_DOOR),
self.rand_obj()
)
assert False
elif kind is 'and':
instr_a = self.rand_instr(
action_kinds=action_kinds,
instr_kinds=['action'],
depth=depth+1
)
instr_b = self.rand_instr(
action_kinds=action_kinds,
instr_kinds=['action'],
depth=depth+1
)
return AndInstr(instr_a, instr_b)
elif kind is 'seq':
instr_a = self.rand_instr(
action_kinds=action_kinds,
instr_kinds=['action', 'and'],
depth=depth+1
)
instr_b = self.rand_instr(
action_kinds=action_kinds,
instr_kinds=['action', 'and'],
depth=depth+1
)
kind = self._rand_elem(['before', 'after'])
if kind is 'before':
return BeforeInstr(instr_a, instr_b)
elif kind is 'after':
return AfterInstr(instr_a, instr_b)
assert False
assert False
# Dictionary of levels, indexed by name, lexically sorted
level_dict = OrderedDict()
def register_levels(module_name, globals):
"""
Register OpenAI gym environments for all levels in a file
"""
# Iterate through global names
for global_name in sorted(list(globals.keys())):
if not global_name.startswith('Level_'):
continue
level_name = global_name.split('Level_')[-1]
level_class = globals[global_name]
# Register the levels with OpenAI Gym
gym_id = 'BabyAI-%s-v0' % (level_name)
entry_point = '%s:%s' % (module_name, global_name)
gym.envs.registration.register(
id=gym_id,
entry_point=entry_point,
)
# Add the level to the dictionary
level_dict[level_name] = level_class
# Store the name and gym id on the level class
level_class.level_name = level_name
level_class.gym_id = gym_id
def test():
for idx, level_name in enumerate(level_dict.keys()):
print('Level %s (%d/%d)' % (level_name, idx+1, len(level_dict)))
level = level_dict[level_name]
# Run the mission for a few episodes
rng = random.Random(0)
num_episodes = 0
for i in range(0, 15):
mission = level(seed=i)
# Check that the surface form was generated
assert isinstance(mission.surface, str)
assert len(mission.surface) > 0
obs = mission.reset()
assert obs['mission'] == mission.surface
# Reduce max_steps because otherwise tests take too long
mission.max_steps = min(mission.max_steps, 200)
# Check for some known invalid patterns in the surface form
import re
surface = mission.surface
assert not re.match(r".*pick up the [^ ]*door.*", surface), surface
while True:
action = rng.randint(0, mission.action_space.n - 1)
obs, reward, done, info = mission.step(action)
if done:
obs = mission.reset()
break
num_episodes += 1
# The same seed should always yield the same mission
m0 = level(seed=0)
m1 = level(seed=0)
grid1 = m0.unwrapped.grid
grid2 = m1.unwrapped.grid
assert grid1 == grid2
assert m0.surface == m1.surface
# Check that gym environment names were registered correctly
gym.make('BabyAI-1RoomS8-v0')
gym.make('BabyAI-BossLevel-v0')
| [
"mathijsmul@gmail.com"
] | mathijsmul@gmail.com |
c11f30e90247965c11cb521bf29976d8ea7e412a | 60ccf143ae59bd2aeb6b831499ba0d4045025588 | /Exercicios/Ex112/utilidades/moeda/__init__.py | e5287298ddb3a0e98c7105be80cd9b6ab1862e00 | [
"MIT"
] | permissive | RenanRibeiroDaSilva/Meu-Aprendizado-Python | 3283fa644214149d41777d6b23f6e98804bf30de | 280bf2ad132ae0d26255e70b894fa7dbb69a5d01 | refs/heads/main | 2023-07-07T22:59:11.725000 | 2021-08-11T16:47:32 | 2021-08-11T16:47:32 | 369,657,470 | 2 | 0 | MIT | 2021-06-01T17:51:28 | 2021-05-21T21:25:46 | Python | UTF-8 | Python | false | false | 2,188 | py | def aumentar(p=0, tax=0, formato=False):
"""
-> Aumenta o valor inicial em uma porcentagem definida pelo usuário
:param p: valor inicial
:param tax: valor da taxa
:param formato: formatação do valor
:return: valor inicial somada a taxa
"""
res = p + (p * tax/100)
return res if not formato else moeda(res)
def diminuir(p=0, tax=0, formato=False):
"""
-> Diminui o valor inicial em um porcentagem definida pelo usuário
:param p: valor inicial
:param tax: valor da taxa
:param formato: formatação do valor
:return: valor inicial subtraído a taxa
"""
res = p - (p * tax/100)
return res if not formato else moeda(res)
def dobro(p=0, formato=False):
"""
-> Dobra o valor inicial
:param p: valor inicial
:param formato: formatação do valor
:return: valor inicial em dobro
"""
res = p * 2
return res if not formato else moeda(res)
def metade(p=0, formato=False):
"""
-> Divide o valor inicial
:param p: valor inicial
:param formato: formatação do valor
:return: valor dividido pela metade
"""
res = p / 2
return res if not formato else moeda(res)
def moeda(p=0, moeda='R$'):
"""
-> Devolve uma string formatada
:param p: valor inserido pelo usuário
:param moeda: tipo de moeda
:return: valor formatado
"""
float(p)
return f'{moeda}{p:<4.2f}'.replace('.', ',')
def resumo(p=0, taxa_a=10, taxa_r=10):
"""
-> Devolve de os resultados referentes ao valor formatado para o usuário
:param p: valor definido pelo usuário
:param taxa_a: taxa de aumento, que pode ser defenida pelo usuário
:param taxa_r: taxa de redução, que pode ser definida pelo usuário
:return: resultado formatado
"""
print('-' * 30)
print('Resumo do resultado'.center(40))
print('-' * 30)
print(f'Preço analizado..: \t{moeda(p)}')
print(f'Dobro do preço..: \t{dobro(p, True)}')
print(f'Metade do preço: \t{metade(p, True)}')
print(f'{taxa_a}% de aumento.: \t{aumentar(p, taxa_a, True)}')
print(f'{taxa_r}% de desconto.: \t{diminuir(p, taxa_r, True)}')
print('-' * 30)
| [
"84098891+RenanRibeiroDaSilva@users.noreply.github.com"
] | 84098891+RenanRibeiroDaSilva@users.noreply.github.com |
851f167b5a0153e22c9f95ffe6d95bb2955f4c04 | c67165932f0104335672201fa4d8f99457efc408 | /students/students/schema.py | a115d24dd7146986189a0f2e76db1dd8a6fcab49 | [] | no_license | serforin0/APICRUDgraphql | 04956cf4b06215f89f15c475854c99c506b8f5b3 | 87cc27ed438e66d73df88a89c6b3cf63e02270b0 | refs/heads/master | 2023-01-19T23:19:22.990157 | 2020-11-24T06:01:41 | 2020-11-24T06:01:41 | 315,069,751 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 236 | py | import graphene
from students.apps.usuarios import schema
class Query(schema.Query, graphene.ObjectType):
pass
class Mutation(schema.Mutation, graphene.ObjectType):
pass
schema = graphene.Schema(query=Query, mutation=Mutation) | [
"serforin@gmail.com"
] | serforin@gmail.com |
977786f23172d7755d1a91b97e2be2aa6e6fdf41 | 196f7e3238f961fb5eba7a794f0b0c75d7c30ba1 | /Python编程从入门到实践3.6/c14/test14/scoreboard1432.py | 1e4ccc14d75b2f90eb13ae01a61a3e897c0ccffe | [] | no_license | Liaoyingjie/Pythonlearn | d0b1b95110017af7e063813660e52c61a6333575 | 8bca069f38a60719acac5aa39bd347f90ab0bfb1 | refs/heads/master | 2020-04-08T07:35:07.357487 | 2018-04-12T16:44:43 | 2018-04-12T16:44:43 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,657 | py | import pygame.font
class Scoreboard():
"""显示分类信息."""
def __init__(self, ai_settings,screen,stats):
"""初始化 统计信息."""
self.screen=screen
self.screen_rect = screen.get_rect()
self.ai_settings= ai_settings
self.stats = stats
#显示得分信息使用的字体设置
self.text_color = (30,30,30)
self.font= pygame.font.SysFont(None,48)
#准备初始的图像
self.prep_score()
#显示的是文本，导入了字体的模块，设置字体颜色，实例化一个对象
#然后用 这个字体，转化成图像
def prep_score(self):
"""将得分渲染成图像"""
score_str = str(self.stats.score)
self.score_imge = self.font.render(score_str,True,self.text_color,self.ai_settings.bg_color)
#将得分放在屏幕右上角
self.score_rect = self.score_imge.get_rect()
self.score_rect.right = self.screen_rect.right - 20
self.score_rect.top = 20
#在prep_score() 把sstats.score 变成字符串 传给 创建图像的render
#用一个rect 在屏幕右边相聚20像素 锚定在屏幕右边 创建方法show_score()用于渲染好的 得分图像
def show_score(self):
'''屏幕显示得分'''
self.screen.blit(self.score_imge,self.score_rect)
| [
"godzoco@qq.com"
] | godzoco@qq.com |
e341ee301c03a8281dc994dce3ab9561bce06dc5 | 0e7b3650906559fbb0bd4bc1ce199ff82605303b | /Bank Customer Churn Analytics_05102020.py | 45f174294c56bed432ed5e1c0fb3e85fe04e2f31 | [] | no_license | ArthurShen8118/Bank_Customer_Churn_Analytics | 5f4ab718c1a1d7092cef73f0f805b00e2ad329f1 | 4afc31ae39c6f1787f82d515574b09fcaae9445e | refs/heads/main | 2022-12-29T21:06:50.454915 | 2020-10-23T05:13:22 | 2020-10-23T05:13:22 | 304,525,407 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,505 | py | #Part1
# Importing the libraries
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
np.random.seed(10)
# Importing the dataset
dataset = pd.read_csv('Churn_Modelling.csv')
X= dataset.iloc[:, 3:13].values
y = dataset.iloc[:, 13].values
# Encoding categorical data
# Encoding the Independent Variable
from sklearn.preprocessing import OneHotEncoder
from sklearn.compose import ColumnTransformer
from sklearn.preprocessing import LabelEncoder, OneHotEncoder
# 3 Classes Encoding
ct = ColumnTransformer(transformers=[('encoder',OneHotEncoder(),[1])], remainder = 'passthrough')
X= np.array(ct.fit_transform(X))
# 2 Classes Encoding
labelencoder_X_2 = LabelEncoder()
X[:, 4] = labelencoder_X_2.fit_transform(X[:, 4])
X=np.around(X.astype(np.double),1) #delete the float and do the round
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)
# Feature Scaling
from sklearn.preprocessing import StandardScaler
sc = StandardScaler()
X_train = sc.fit_transform(X_train)
X_test = sc.transform(X_test)
#Part2
#Import
import tensorflow
import keras
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Dropout
#Initialising the ANN
classifier = Sequential()
#Input Layer and Hidden layer
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))
#Second Hidden Layer
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu'))
classifier.add(Dropout(p = 0.1))
#Output Layer
classifier.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))
#Compling the ANN (how to optimize weight)
classifier.compile(optimizer='adam', loss='binary_crossentropy', metrics = ['accuracy'])
classifier.save('model')
#Fitting the ANN to the Trainning set
'classifier.fit(X_train, y_train, batch_size = 10, epochs = 100)'
train_history=classifier.fit(X_test, y_test, validation_split=0.1, batch_size = 10, epochs = 100)
# Part 3 - Making predictions and evaluating the model
# Predicting the Test set results
y_pred = classifier.predict(X_test)
y_pred = (y_pred > 0.5)
# Making the Confusion Matrix-
from sklearn.metrics import confusion_matrix,accuracy_score
cm = confusion_matrix(y_test, y_pred)
accuracy_score(y_test,y_pred)
''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''
# Part 4 - Train model v.s. Validation model
# Diagram
def show_train_history (train_history,train,validation):
plt.plot(train_history.history[train])
plt.plot(train_history.history[validation])
plt.title("Train History")
plt.ylabel(train)
plt.xlabel("Epoch")
plt.legend(['train', 'validation'], loc='upper left')
plt.show()
show_train_history(train_history,'accuracy','val_accuracy')
show_train_history(train_history,'loss','val_loss')
# Confusion_Matrix
import confusion_matrix
import matplotlib.pyplot as plt
from sklearn.metrics import ConfusionMatrixDisplay
display_labels=['Stay','Leave']
disp = ConfusionMatrixDisplay(cm, display_labels)
disp = disp.plot(include_values=bool)
plt.show()
'''
# Part 5 - Adjust Parameter
from sklearn.model_selection import GridSearchCV
from keras.wrappers.scikit_learn import KerasClassifier
def build_classifier(optimizer):
classifier = Sequential()
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu', input_dim = 11))
classifier.add(Dropout(p = 0.1))
classifier.add(Dense(units = 6, kernel_initializer = 'uniform', activation = 'relu'))
classifier.add(Dropout(p = 0.1))
classifier.add(Dense(units = 1, kernel_initializer = 'uniform', activation = 'sigmoid'))
classifier.compile(optimizer = optimizer, loss = 'binary_crossentropy', metrics = ['accuracy'])
return classifier
classifier = KerasClassifier(build_fn = build_classifier)
parameters = {'batch_size': [25, 32],
'epochs': [3, 5],
'optimizer': ['adam', 'rmsprop']}
grid_search = GridSearchCV(estimator = classifier,
param_grid = parameters,
scoring = 'accuracy',
cv = 2)
grid_search = grid_search.fit(X_train, y_train)
best_parameters = grid_search.best_params_
best_accuracy = grid_search.best_score_
''' | [
"noreply@github.com"
] | ArthurShen8118.noreply@github.com |
8000eacdb71c07f88911aad0867f20f31d704c2a | a5dadd1b3c3c2a849d05d02882484f2c78885ca9 | /ve/Scripts/rst2odt.py | 5e4fc893cee483715b2f27c8c1098800a7ad2b0a | [] | no_license | andrey-yakovenko/dm-practice-2 | 70b5529cd9270a9bf0c9feac42c2696e1a7808ba | be2add42f60f7bf7849104caac4f680bc797524d | refs/heads/master | 2022-12-19T19:55:33.725272 | 2020-10-04T22:26:22 | 2020-10-04T22:26:22 | 299,298,955 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 817 | py | #!C:\Users\HP AY\OneDrive\3--python\dm-practice-2\ve\Scripts\python.exe
# $Id: rst2odt.py 5839 2009-01-07 19:09:28Z dkuhlman $
# Author: Dave Kuhlman <dkuhlman@rexx.com>
# Copyright: This module has been placed in the public domain.
"""
A front end to the Docutils Publisher, producing OpenOffice documents.
"""
import sys
try:
import locale
locale.setlocale(locale.LC_ALL, '')
except:
pass
from docutils.core import publish_cmdline_to_binary, default_description
from docutils.writers.odf_odt import Writer, Reader
description = ('Generates OpenDocument/OpenOffice/ODF documents from '
'standalone reStructuredText sources. ' + default_description)
writer = Writer()
reader = Reader()
output = publish_cmdline_to_binary(reader=reader, writer=writer,
description=description)
| [
"64507369+andrey-yakovenko@users.noreply.github.com"
] | 64507369+andrey-yakovenko@users.noreply.github.com |
ef92c14badac2b746db985dffaa876c9444caea1 | 14e36010b98895e08bd9edfcbc60dce30cbfb82b | /oneflow/python/test/modules/test_bce_loss.py | c51aff4ba23c5f1e3e2d253aeecf6e4915dacafd | [
"Apache-2.0"
] | permissive | duzhanyuan/oneflow | a9719befbfe112a7e2dd0361ccbd6d71012958fb | c6b47a3e4c9b5f97f5bc9f60bc1401313adc32c5 | refs/heads/master | 2023-06-21T20:31:55.828179 | 2021-07-20T16:10:02 | 2021-07-20T16:10:02 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,705 | py | """
Copyright 2020 The OneFlow Authors. All rights reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
"""
import unittest
from collections import OrderedDict
import numpy as np
import oneflow.experimental as flow
from test_util import GenArgList
def _np_bceloss(np_input, np_target, np_weight):
np_cross_entropy = -(
np_target * np.log(np_input) + (1 - np_target) * np.log(1 - np_input)
)
if np_weight is not None:
assert (
np_weight.shape == np_input.shape
), "The weight shape must be the same as Input shape"
np_weighted_loss = np_weight * np_cross_entropy
else:
np_weighted_loss = np_cross_entropy
np_bce_loss = np_weighted_loss
np_bce_loss_sum = np.sum(np_weighted_loss)
np_bce_loss_mean = np.mean(np_weighted_loss)
return {"none": np_bce_loss, "sum": np_bce_loss_sum, "mean": np_bce_loss_mean}
def _test_bceloss_impl(test_case, device, reduction):
x = np.array([[1.2, 0.2, -0.3], [0.7, 0.6, -2]]).astype(np.float32)
y = np.array([[0, 1, 0], [1, 0, 1]]).astype(np.float32)
w = np.array([[2, 2, 2], [2, 2, 2]]).astype(np.float32)
input = flow.Tensor(
x, dtype=flow.float32, requires_grad=True, device=flow.device(device)
)
target = flow.Tensor(y, dtype=flow.float32, device=flow.device(device))
weight = flow.Tensor(w, dtype=flow.float32, device=flow.device(device))
activation = flow.nn.Sigmoid()
sigmoid_input = activation(input)
loss = flow.nn.BCELoss(weight, reduction=reduction)
loss = loss.to(device)
of_out = loss(sigmoid_input, target)
np_out = _np_bceloss(sigmoid_input.numpy(), y, w)[reduction]
test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-5, 1e-5))
of_out = of_out.sum()
of_out.backward()
if reduction == "none":
np_grad = np.array(
[[1.5370497, -0.90033215, 0.851115], [-0.6636245, 1.2913125, -1.7615942]]
).astype(np.float32)
elif reduction == "sum":
np_grad = np.array(
[[1.5370497, -0.90033215, 0.851115], [-0.6636245, 1.2913125, -1.7615942]]
).astype(np.float32)
else:
np_grad = np.array(
[
[0.25617492, -0.15005533, 0.14185251],
[-0.11060409, 0.21521877, -0.29359904],
]
).astype(np.float32)
test_case.assertTrue(np.allclose(input.grad.numpy(), np_grad, 1e-5, 1e-5))
input_none = input = flow.Tensor(
np.array([[1.2, 0.2, -0.3], [0.7, 0.6, -2]]).astype(np.float32),
dtype=flow.float32,
requires_grad=True,
device=flow.device(device),
)
sigmoid_input_none = activation(input_none)
loss_none = flow.nn.BCELoss(reduction=reduction)
loss_none = loss_none.to(device)
of_out_none = loss_none(sigmoid_input_none, target)
np_out_none = _np_bceloss(sigmoid_input.numpy(), y, None)[reduction]
test_case.assertTrue(np.allclose(of_out_none.numpy(), np_out_none, 1e-5, 1e-5))
of_out_none = of_out_none.sum()
of_out_none.backward()
if reduction == "none":
np_grad_none = np.array(
[[0.7685, -0.4502, 0.4256], [-0.3318, 0.6457, -0.8808]]
).astype(np.float32)
elif reduction == "sum":
np_grad_none = np.array(
[[0.7685, -0.4502, 0.4256], [-0.3318, 0.6457, -0.8808]]
).astype(np.float32)
else:
np_grad_none = np.array(
[[0.1281, -0.0750, 0.0709], [-0.0553, 0.1076, -0.1468]]
).astype(np.float32)
test_case.assertTrue(np.allclose(input_none.grad.numpy(), np_grad_none, 1e-4, 1e-4))
input_none = input = flow.Tensor(
np.array([[1.2, 0.2, -0.3], [0.7, 0.6, -2]]).astype(np.float32),
dtype=flow.float32,
requires_grad=True,
device=flow.device(device),
)
sigmoid_input_none = activation(input_none)
loss_none = flow.nn.BCELoss(reduction=reduction)
loss_none = loss_none.to(device)
of_out_none = loss_none(sigmoid_input_none, target)
np_out_none = _np_bceloss(sigmoid_input.numpy(), y, None)[reduction]
test_case.assertTrue(np.allclose(of_out_none.numpy(), np_out_none, 1e-5, 1e-5))
of_out_none = of_out_none.sum()
of_out_none.backward()
if reduction == "none":
np_grad_none = np.array(
[[0.7685, -0.4502, 0.4256], [-0.3318, 0.6457, -0.8808]]
).astype(np.float32)
elif reduction == "sum":
np_grad_none = np.array(
[[0.7685, -0.4502, 0.4256], [-0.3318, 0.6457, -0.8808]]
).astype(np.float32)
else:
np_grad_none = np.array(
[[0.1281, -0.0750, 0.0709], [-0.0553, 0.1076, -0.1468]]
).astype(np.float32)
test_case.assertTrue(np.allclose(input_none.grad.numpy(), np_grad_none, 1e-4, 1e-4))
@flow.unittest.skip_unless_1n1d()
class TestBCELossModule(flow.unittest.TestCase):
def test_bceloss(test_case):
arg_dict = OrderedDict()
arg_dict["test_fun"] = [
_test_bceloss_impl,
]
arg_dict["device"] = ["cpu", "cuda"]
arg_dict["reduction"] = ["none", "sum", "mean"]
for arg in GenArgList(arg_dict):
arg[0](test_case, *arg[1:])
if __name__ == "__main__":
unittest.main()
| [
"noreply@github.com"
] | duzhanyuan.noreply@github.com |
14f60215ea6b0a613cb57e3778e97c51f5ea653c | 1058045bea67cd3c5187861ebde0fdd74df7779e | /spider-master/zhihu_user/zhihu_user/settings.py | f26087f5fe01eab0c483fc12bc800b14fc8db4dc | [] | no_license | CLCLpis/crawler | 6ea79eac3c7a4ace83adfb66c42abccdf2e27b0a | a7df3c7abfaaf7300da694f7a9ad75abf996f098 | refs/heads/master | 2020-03-15T15:41:08.212902 | 2018-05-05T05:32:35 | 2018-05-05T05:32:35 | 132,217,856 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,303 | py | # -*- coding: utf-8 -*-
# Scrapy settings for zhihu_user project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
# http://doc.scrapy.org/en/latest/topics/settings.html
# http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
BOT_NAME = 'zhihu_user'
SPIDER_MODULES = ['zhihu_user.spiders']
NEWSPIDER_MODULE = 'zhihu_user.spiders'
# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'zhihu_user (+http://www.yourdomain.com)'
# Obey robots.txt rules
ROBOTSTXT_OBEY = False
# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32
# Configure a delay for requests for the same website (default: 0)
# See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
DOWNLOAD_DELAY = 0.1
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16
# Disable cookies (enabled by default)
#COOKIES_ENABLED = False
# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False
# Override the default request headers:
DEFAULT_REQUEST_HEADERS = {
'User-Agent':"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/59.0.3071.115 Safari/537.36",
'authorization':'oauth c3cef7c66a1843f8b3a9e6a1e3160e20',
}
# Enable or disable spider middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
# 'zhihu_user.middlewares.ZhihuUserSpiderMiddleware': 543,
#}
# Enable or disable downloader middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
# 'zhihu_user.middlewares.MyCustomDownloaderMiddleware': 543,
#}
# Enable or disable extensions
# See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
#EXTENSIONS = {
# 'scrapy.extensions.telnet.TelnetConsole': None,
#}
# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
'zhihu_user.pipelines.MongoPipeline': 300,
}
# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False
# Enable and configure HTTP caching (disabled by default)
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = 'httpcache'
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
MONGO_URI = 'localhost'
MONGO_DATABASE = 'zhihu'
| [
"445453402@qq.com"
] | 445453402@qq.com |
94fa689a11460479a169a04b410c327093534d49 | d1ddb9e9e75d42986eba239550364cff3d8f5203 | /google-cloud-sdk/lib/surface/pubsub/topics/create.py | 7d9069a19ff657965b70b227e2f178aed596b432 | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | permissive | bopopescu/searchparty | 8ecd702af0d610a7ad3a8df9c4d448f76f46c450 | afdc2805cb1b77bd5ac9fdd1a76217f4841f0ea6 | refs/heads/master | 2022-11-19T14:44:55.421926 | 2017-07-28T14:55:43 | 2017-07-28T14:55:43 | 282,495,798 | 0 | 0 | Apache-2.0 | 2020-07-25T17:48:53 | 2020-07-25T17:48:52 | null | UTF-8 | Python | false | false | 2,263 | py | # Copyright 2015 Google Inc. 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.
"""Cloud Pub/Sub topics create command."""
from apitools.base.py import exceptions as api_ex
from googlecloudsdk.api_lib.util import exceptions
from googlecloudsdk.calliope import base
from googlecloudsdk.command_lib.pubsub import util
from googlecloudsdk.core import log
class Create(base.CreateCommand):
"""Creates one or more Cloud Pub/Sub topics.
Creates one or more Cloud Pub/Sub topics.
## EXAMPLES
To create a Cloud Pub/Sub topic, run:
$ {command} mytopic
"""
@staticmethod
def Args(parser):
"""Registers flags for this command."""
parser.add_argument('topic', nargs='+',
help='One or more topic names to create.')
def Run(self, args):
"""This is what gets called when the user runs this command.
Args:
args: an argparse namespace. All the arguments that were provided to this
command invocation.
Yields:
A serialized object (dict) describing the results of the operation.
This description fits the Resource described in the ResourceRegistry under
'pubsub.projects.topics'.
"""
msgs = self.context['pubsub_msgs']
pubsub = self.context['pubsub']
for topic in args.topic:
topic_name = topic
topic = msgs.Topic(name=util.TopicFormat(topic_name))
try:
result = pubsub.projects_topics.Create(topic)
failed = None
except api_ex.HttpError as error:
result = topic
exc = exceptions.HttpException(error)
failed = exc.payload.status_message
result = util.TopicDisplayDict(result, failed)
log.CreatedResource(topic_name, kind='topic', failed=failed)
yield result
| [
"vinvivo@users.noreply.github.com"
] | vinvivo@users.noreply.github.com |
ebfdcda196f3f604fc266e516cf71d77be4523bc | 4606b421a0a36491f91eb79e74b03bbf3fd414bc | /restful_weather/wcs_parser/wcs_capabilities.py | bf02bbd15a06fc86de15da7ba780bf5fd2239935 | [] | no_license | uk-gov-mirror/informatics-lab.restful-weather | 2bf594354ce8ac2f31e9ff300027339f679c316f | 244c6a119994b8dcd0a4a1dd4796afc6e25bb2a3 | refs/heads/master | 2021-05-29T08:54:44.457486 | 2015-07-16T11:21:41 | 2015-07-16T11:21:41 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 386 | py | #!/usr/bin/env python
from bs4 import BeautifulSoup
class Capabilities(object):
def __init__(self, capabilities_xml):
self.capabilities = capabilities_xml
self.soup = BeautifulSoup(self.capabilities, 'xml')
self.coverages = self.get_coverage_ids()
def get_coverage_ids(self):
return [id.get_text() for id in self.soup.find_all('CoverageId')]
| [
"alexhilsonwork@googlemail.com"
] | alexhilsonwork@googlemail.com |
a8788b07a7f8733730d4b9cc13c1554610242700 | 58e6a8daeb63f78a7e654ff4db3511b9c6a90d83 | /基础语法/根据北风网学习的语法/02_numpy数组创建.py | a6c687cdee096c2e03b916c2bc505595a07e630f | [] | no_license | guo0842109/MyAIDemo | 53d89017a8e867906a93eada95d751a7a04118db | 4208586a60a91cd1ebf27469451c653c5cf4c828 | refs/heads/master | 2020-06-16T23:05:04.075746 | 2019-07-26T07:25:30 | 2019-07-26T07:25:30 | 195,727,973 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,345 | py | import numpy as np
'''
数组元素为随机值
'''
# a = np.empty((4,4),dtype=np.int)
# print(a)
# b = np.ones((2,3,4,5))
# print(b)
'''
asarray、array 都可以将元组或者list转换为ndarray
'''
# a = [1,2,3]
# print(type(a))
# b = np.asarray(a)
# c = np.array(a)
# print(type(b))
# print(type(c))
# d = (1,2,3)
# print(d)
# print(type(d))
# e = np.array(d)
# print(e)
# print(type(e))
'''
arange,返回ndarray对象
numpy.arange(start,stop,step,dtype)
'''
# f = np.arange(3)
# print(f)
# print(type(f))
'''
numpy.linspace 与arange函数类似 等差数列
numpy.logspace 等比数列
numpy.logscale(start, stop, num, endpoint, base, dtype)
'''
# g = np.logspace(1,2,5,True,base=2)
# print(g)
# print(type(g))
'''
其他创建方式
random模块
rand 返回 0 - 1 随机值
randn 返回一个样本具有标准正态分布
randint 返回随机的整数，位于半开区间[low,hight)size = 10 (3,3)
random_integers(low[, high, size]) 返回随机的整数，位于闭区间
random 返回随机浮点数
'''
h = np.random.rand(12).reshape(3,-1)
print('h=======',h)
print('h=======',type(h))
h1 = np.random.randn(12).reshape(3,-1)
print('h1=======',h1)
print('h1=======',type(h1))
h2 = np.random.randint(1,9,size=9).reshape(-1,3)
print('h2=======',h2)
print('h2=======',type(h2))
| [
"guohaibing@yto.net.cn"
] | guohaibing@yto.net.cn |
aa73644684a29a7946ba41d9358ce56440717008 | 1c3f8f340724497d0edfc193dfe5cdc0497071c3 | /models.py | 59427e6d860da05ea36bed8cfba8a46133cacd7d | [] | no_license | dnn004/Casting | f56b1ec9e37dfb2904aacd1bf6dab377f6b8c895 | 0aa56a9ee17e33c14de0b10305b7a0f06d58955b | refs/heads/master | 2022-12-02T22:51:18.638752 | 2020-08-12T04:41:37 | 2020-08-12T04:41:37 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,120 | py | import os
from sqlalchemy import Column, String, Integer, Date, create_engine
from flask_sqlalchemy import SQLAlchemy
import json
database_name = "cast"
database_path = os.environ.get("DATABASE_URL")
# database_path = "postgresql://{}/{}".format(':5433', database_name)
db = SQLAlchemy()
def db_drop_and_create_all():
db.drop_all()
db.create_all()
movies_actors = db.Table(
"movies_actors",
db.Column(
"movie_id",
db.Integer,
db.ForeignKey("movies.id"),
primary_key=True
),
db.Column(
"actor_id",
db.Integer,
db.ForeignKey("actors.id"),
primary_key=True
)
)
'''
setup_db(app)
binds a flask application and a SQLAlchemy service
'''
def setup_db(app, database_path=database_path):
app.config["SQLALCHEMY_DATABASE_URI"] = database_path
app.config["SQLALCHEMY_TRACK_MODIFICATIONS"] = False
db.app = app
db.init_app(app)
db.create_all()
class Movie(db.Model):
__tablename__ = "movies"
id = Column(Integer, primary_key=True)
title = Column(String)
release_date = Column(Date)
actors = db.relationship(
"Actor",
secondary=movies_actors,
lazy="subquery",
backref=db.backref("movies", lazy=True)
)
def __init__(self, title, release_date):
self.title = title
self.release_date = release_date
def insert(self):
db.session.add(self)
db.session.commit()
def update(self):
db.session.commit()
def delete(self):
db.session.delete(self)
db.session.commit()
def format(self):
# Query for actors in a movie for return
actors = db.session.query(movies_actors).join(Movie).join(Actor)\
.filter(Movie.id == self.id).with_entities(Actor.name).all()
actors_return = []
for actor in actors:
actors_return.append(*actor)
return {
"id": self.id,
"title": self.title,
"release_date": self.release_date,
"actors": actors_return
}
class Actor(db.Model):
__tablename__ = "actors"
id = Column(Integer, primary_key=True)
name = Column(String)
age = Column(Integer)
gender = Column(String)
def __init__(self, name, age, gender):
self.name = name
self.age = age
self.gender = gender
def insert(self):
db.session.add(self)
db.session.commit()
def update(self):
db.session.commit()
def delete(self):
db.session.delete(self)
db.session.commit()
def format(self):
# Query for movies which an actor was in for return
movies = db.session.query(movies_actors).join(Movie).join(Actor)\
.filter(Actor.id == self.id).with_entities(Movie.title).all()
movies_return = []
for movie in movies:
movies_return.append(*movie)
return {
"id": self.id,
"name": self.name,
"age": self.age,
"gender": self.gender,
"movies": movies_return
}
| [
"dnn004@ucsd.edu"
] | dnn004@ucsd.edu |
073e831eae1dbd3228e8ba05f289d0391a410edb | 126bc027a5b7168a20e12dcd60c5da70f1ad9062 | /adivinhacao.py | 9f6faf7dc36aa0b85252de7ee51f51e84deeac4f | [] | no_license | akeme/Python-codes | 7b00b3ba4b53dc0c1f83147477cc2c29214c034a | 36590c59254de1f1aed9d6c72bd478a325357701 | refs/heads/main | 2023-01-14T07:44:10.678693 | 2020-11-09T19:57:47 | 2020-11-09T19:57:47 | 306,344,046 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,187 | py | '''
01 Algoritmo Jogo de Adivinhação
02 Variaveis:
03 secreto, palpite: Inteiro
04 Inicio
05 SAIDA(“Bem-vindo ao jogo de adivinhação”)
06 secreto = NUMERO_ALEATORIO(1,10)
07 palpite = -1
08 SAIDA(“Seu objetivo é acertar o número secreto”)
09 ENQUANTO palpite != secreto FACA
10 SAIDA(“Faça um palpite entre 1 e 10”)
11 <Capture a entrada do jogador e coloque na variável palpite>
12 SE palpite > secreto ENTAO
13 SAIDA(“O número secreto é menor!”)
14 FIM_SE
15 SE palpite < secreto ENTAO
16 SAIDA(“O número secreto é maior!”)
17 FIM_SE
18 FIM_ENQUANTO
19 SAIDA(“Parabéns, você acertou!”)
20 Fim
'''
import random
secreto = random.randint(0, 10)
palpite = -1
print("Bem-vindo ao jogo de adivinhação")
while (palpite != secreto):
print("Faça um palpite entre 1 e 10 ")
palpite = int(input())
if palpite > secreto:
print("o número secreto é menor")
if palpite < secreto:
print("o número secreto é maior")
else:
print("parabéns você acertou")
| [
"noreply@github.com"
] | akeme.noreply@github.com |
d483b8c994fc0fb9ff46cbedea01c8355c14bf2d | 31952da1a7225be50c7701140d4fab4ccaecb9f1 | /index.py | d8f5bade8a05925a9254ee0e3be02921568ff65a | [] | no_license | setra1/Mangrove | 3d9d716d040cf5a4ee9c5daf0d08a7ce1efbdef5 | 863282044965b047b96cd6ca81afd500bf5494ab | refs/heads/main | 2023-04-13T17:55:37.937695 | 2021-04-29T09:20:22 | 2021-04-29T09:20:22 | 362,743,142 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 15,128 | py | #!C:\python37\python.exe
import os,sys
import cgi
import numpy as np
import rasterio
import cgitb
cgitb.enable()
print ("Content-type: text/html;\n\n")
print
print ("""
<!DOCTYPE html>
<html lang="fr" dir="ltr">
<head>
<meta charset="utf-8">
<title>Mangrove</title>
<link rel="stylesheet" href="assets/css/bootstrap.min.css">
<link rel="stylesheet" href="assets/css/main.css">
<script src="assets/js/jquery.min.js"></script>
<script src="http://dev.openlayers.org/releases/OpenLayers-2.13.1/OpenLayers.js"></script>
<script src="https://ajax.googleapis.com/ajax/libs/jquery/3.2.0/jquery.min.js"></script>
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.4.0/js/bootstrap.min.js"></script>
</head>
<script>
$(document).ready(function(){
$("#etape2").hide();
$("#etape3").hide();
$("#Message").hide();
$("#Message2").hide();
$("#reponses").hide();
$("#fichiers").hide();
$("#wait").css("display", "none");
$("#btn").click(function(){
$("#wait").css("display", "block");
image2=$("#image2").val();
image1=$("#image1").val();
maxi=$("#maxi").val();
mini=$("#mini").val();
avantValidation(image1,image2,maxi,mini);//lancer le traitement etape 1
});
$("#btnValider").click(function(){
traitementValider();
});
$("#btnNonValider").click(function(){
traitementNonVlider();
});
$("#Continuer").click(function(){
polygone=$("#ZoneSelectionner").val();
if(polygone===""){
alert("Veuillez selectionner un vrai poligone");
}else{
traitementApresValider();
}
});
});
function avantValidation(image1,image2,maxi,mini){
$.ajax({
url : 'traitement1.py',
type : 'POST',
data : 'image2='+image2+'&image1='+image1+'&maxi='+maxi+'&mini='+mini,
dataType : 'html',
success: function(response) {
$('#Resultat').html(response);
console.log( response );
$("#wait").css("display", "none");//loader
alert("ok");
$("#reponses").show();//aficher les resultats type image
$("#etape1").hide();
$("#etape2").show();
},
error: function( response ) {
$("#wait").css("display", "none");//loader
setTimeout(function(){ alert("ok"); }, 9000);
$("#reponses").show();//aficher les resultats type image
$("#etape1").hide();
$("#etape2").show();
init();
}
});
}
function traitementValider(){
$("#etape1").hide();
$("#etape2").hide();
$("#etape3").show();
$("#Message2").show();
}
function traitementNonVlider(){
$("#etape2").hide();
$("#etape1").show();
$("#Message").show();
}
function traitementApresValider(){
$("#wait").css("display", "block");
polygone=$("#ZoneSelectionner").val();
$.ajax({
url : 'traitement2.py',
type : 'POST',
data : 'poly='+polygone,
dataType : 'html',
success: function(response) {
$('#Resultat').html(response);
$("#wait").css("display", "none");
alert("ok");
$("#fichiers").show();
},
error: function( response ) {
alert("non ok");
//console.log( response );
}
});
}
</script>
<script type="text/javascript">
var carte;
function init() {
var bounds=new OpenLayers.Bounds(318500.00,7223130.00,1087715.73,8674988.64);
var options={
maxExtent:bounds,
projection:"epsg:32738",
units:"m",
controls:[
new OpenLayers.Control.Navigation(),
new OpenLayers.Control.LayerSwitcher(),
new OpenLayers.Control.PanZoomBar(),
new OpenLayers.Control.MousePosition(),
],
};
carte = new OpenLayers.Map('carte',options);
var mangrove_madagascar= new OpenLayers.Layer.WMS(
"mangrove_madagascar", "http://localhost:8080/geoserver/mangrove/wms?",
{
layers: "mangrove:mangrove_madagascar",
format:"image/png",
transparent:true,
srs:"epsg:32738",
visibility: true,
width:800,
height:500
},
{isBaseLayer: false}
);
var couche= new OpenLayers.Layer.WMS(
"couche", "http://localhost:8080/geoserver/mangrove/wms?",
{
layers: "mangrove:couche",
format:"image/png",
transparent:true,
srs:"epsg:32738",
visibility: true,
width:800,
height:500
},
{isBaseLayer: false}
);
var raster_mangrove= new OpenLayers.Layer.WMS(
"mangrove_ndvi", "http://localhost:8080/geoserver/mangrove/wms?",
{
layers: "mangrove:mangrove_ndvi",
format:"image/png",
transparent:true,
srs:"epsg:32738",
visibility: true
},
{isBaseLayer: true}
);
highlightLayer = new OpenLayers.Layer.Vector("Highlighted Features", {
displayInLayerSwitcher: false,
isBaseLayer: false
}
);
carte.addLayers([mangrove_madagascar,couche,raster_mangrove,highlightLayer]);
//district.setVisibility(false);
//communes.setVisibility(true);
carte.addControl(new OpenLayers.Control.MousePosition());
carte.zoomToMaxExtent();
//event
var infoControls = {
click: new OpenLayers.Control.WMSGetFeatureInfo({
url: 'http://localhost:8080/geoserver/mangrove/wms',
title: 'Identify features by clicking',
layers: [couche],
queryVisible: true,
infoFormat:'application/json',
output:'features',
format:new OpenLayers.Format.JSON,
eventListeners: {
getfeatureinfo: function(event) {
getFeaturesTohilight(event);
}}
}),
};
for (var i in infoControls) {
infoControls[i].events.register("getfeatureinfo", this, showInfo);
carte.addControl(infoControls[i]);
}
infoControls.click.activate();;
}
function showInfo(gid,event,zone) {
carte.addPopup(new OpenLayers.Popup.FramedCloud(
"chicken",
carte.getLonLatFromPixel(event.xy),
new OpenLayers.Size(800,600),
gid,
null,
true
));
}
function getFeaturesTohilight(event){//trouver le nom de shape cliqué et appeler la fonction highlightAndShowInfos
var zone;
var layers = carte.getLayersBy("visibility", true);
for(var i=0;i<layers.length;i++){
if(layers[i].name=="couche"){
zone="couche";
highlightAndShowInfos(event,zone);
}
}
}
function highlightAndShowInfos(event,zone){ //pour chercher le gid et polygone de la zone cliquée,puis appeler le showInfo
var coords=carte.getLonLatFromPixel(event.xy)+"";
var lng=coords.split(",")[0].split("=")[1];
var lat=coords.split(",")[1].split("=")[1];
coords=lng+","+lat;
alert(coords);
$.get("highlighting.php?point="+coords+"&zone="+zone)
.done(function(data) {
alert(data);
var in_options = { 'internalProjection': new OpenLayers.Projection("EPSG:32738"), 'externalProjection': new OpenLayers.Projection("EPSG:32738") };
var polygon=data.split("===")[0];
var gid=data.split("===")[1];
var feature = new OpenLayers.Format.WKT(in_options).read(polygon);//ici c'est le polygone
$("#ZoneSelectionner").val(polygon);
/*highlightLayer.destroyFeatures();
highlightLayer.addFeatures([feature]);
highlightLayer.redraw();
showInfo(gid,event,zone);*/
});
}
</script>
<body>
<div class="content" style="height: 100%;">
<header class="navbar-fixed-top">
<div class="navbar navbar-default top-menu" style="height: 50px;">
<div class="navbar navbar-left">
</div>
<div class="navbar navbar-right">
</div>
</div>
</header>
<section class="container-fluid corps" style="background-color:rgba(84, 75, 75, 0.12);">
<div class="row row-col">
<div class="col-lg-4 col-md-4 col-sm-12 col-xs-12 left" style="background-color: RGBA(31, 31, 65, 0.03)">
<h1>Paramètres</h1>
<div class="container">
<div class="row">
<form class="form" action="test2.py" method="post">
<fieldset>
<legend style="font-size: 12px;font-weight: 700">Résultats NDVI</legend>
<div style="border:1px solid #cccccc;padding-top: 6px">
<div class="form-group">
<label for="">Données 2 :</label>
<select class="form-control" name="image2" id="image2">
<option value="STDmean_annual_20190101.tif">STDmean_annual_20190101.tif</option>
<option value="STDmean_annual_20170101.tif">STDmean_annual_20170101.tif</option>
</select>
<label for="">Données 1 :</label>
<select class="form-control" name="image1" id="image1">
<option value="STDmean_annual_20190101.tif">STDmean_annual_20190101.tif</option>
<option value="STDmean_annual_20170101.tif">STDmean_annual_20170101.tif</option>
</select>
</div>
</div>
</fieldset>
<fieldset id="field">
<legend style="font-size: 12px;font-weight: 700">Valeurs max, min </legend>
<div style="border:1px solid #cccccc;padding-top: 6px">
<div class="form-group">
<div id="Message"><span style="color:#26ca42">Entrer les nouvelles valeurs</span><br><br></div>
<label for="">Max :</label>
<input type="number" name="max" id="maxi" value="" step="0.1">
<label for="">Min :</label>
<input type="number" name="min" id="mini" value="" step="0.1"><br>
</div>
</div>
</fieldset>
<input type="hidden" name="ZoneSelectionner" id="ZoneSelectionner" value="">
<div id="etape1">
<button type="button" name="button" id="btn">Lancer</button>
</div>
<div id="etape2">
<button type="button" name="valider" id="btnValider">Oui</button>
<button type="button" name="nonvalider" id="btnNonValider">Non</button>
</div>
<div id="Message2"><span style="color:#26ca42">Selectionner la zone à calculer</span><br><br></div>
<div id="etape3">
<button type="button" name="Continuer" id="Continuer">Continuer</button>
</div>
<div id="wait" style="width:125px;height:50px;position:absolute;left:82%;margin: -43px;"><img src='assets/images/ZZ5H.gif' width="50" height="50" /> En cours...</div>
<div class="form-group">
</div>
</form>
</div>
</div>
<div class="tab-menu" id="reponses">
<h1>Résultats</h1>
<div class="col-md-12 col-sm-6">
<div class="list">
<ul class="list-menu">
<li id="visual">Visualisation</li>
<li id="pixel">Nbr pixel</li>
<li id="surface">Surface</li>
</ul>
</div>
<div class="content-tabs">
<div class="menu active">
<div class="container-fluid">
<div class="col-md-8 left" id="affichage" style="background-image:url('ndvifichier.png');">
</div>
<div class="col-md-4 right" id="liens">
<a href="ndvifichier.png" target="_blank">Visualiser</a>
<a href="raster/resulat_ndvi_apres_filtre.tif">Télecharger</a>
</div>
</div>
</div>
<div class="menu">
<h2>Nombre de pixel</h2>
</div>
<div class="menu">
<div id="fichiers"><a href="difference.csv"><img src="assets/images/csv.JPG" width="30px" height="30px"></a></div>
<div id="Resultat"></div>
</div>
</div>
</div>
</div>
</div>
<div class="col-lg-8 col-md-8 col-sm-6 right">
<div class="row-fluid">
<!-- block -->
<div class="block">
<div class="block-content collapse in">
<div >
<div class="form-row">
</div>
<div id="layerswitcher" class="olControlLayerSwitcher"></div>
<div id="map" style="border: 1px solid #cccccc;;">
<div id="carte" style="width:100%; height:600px;"></div>
<div id="wrapper">
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</div>
</section>
</div>
<script type="text/javascript" src="assets/js/main.js"></script>
</body>
</html>
""")
| [
"noreply@github.com"
] | setra1.noreply@github.com |
1df0f3ddad34d03d3030046b631e895d24195cec | 206bc27a1afd738b78ed4d30338bfe997df4b07a | /modules/about/admin.py | 28f55d93583fb91fae50f7f8a9e4c4ce36b6e624 | [] | no_license | RitaTim/cdr | 89a67cc96f74a67e4bcc696c3ae99387b7a3d304 | 5d74ac445d79edcc3003971c8d9862f328a3f920 | refs/heads/master | 2021-01-21T14:09:03.218308 | 2017-03-23T06:44:09 | 2017-03-23T06:44:09 | 58,033,847 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 201 | py | # -*- coding: utf-8 -*-
from django.contrib import admin
from .models import About
class AboutAdmin(admin.ModelAdmin):
list_display = ('title', 'text')
admin.site.register(About, AboutAdmin)
| [
"margaritachka@gmail.com"
] | margaritachka@gmail.com |
6c925c1bcadc0245ae4920be899059c4ec14c27c | 5232ea26d8c2c8601735812719782281ed645b0a | /4-variables.py | c543fd491c86df16a4845bf8a4d5c47002d1f25e | [] | no_license | coder562/python | ff15fcfd61eaa1e5f748be13a85f64d6b33903f8 | 9a56be1967b914cd878aa69be114a3368ef9b7f9 | refs/heads/master | 2023-04-16T02:23:40.934304 | 2021-04-30T12:09:59 | 2021-04-30T12:09:59 | 357,539,923 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 387 | py |
num1 = 2
print(num1)
num1=4
print(num1)
# string,float,int
# string
name="vaishali"
print(name)
name=123
print(name)
# python is dynamic programmic language
#rule 1
# 1number = 4 cant be run-cant be start with a number
# leeter,underscore can be taken
# special symbol cant be take like $
# snake case writing
user_one_name = "vaishali"
# camel case writing
userOneName = "jain"
| [
"vaishalijain654@gmail.com"
] | vaishalijain654@gmail.com |
3cd153485fa6a1c2d2c645d73f5d85d394114921 | 25b7c7eba45d3e641da2cf58f4c64cfa19a31e96 | /pulseview-scripts/gpib-pin-namer.py | be375ef1a04f92f3922845b56719802fa93b4cf1 | [
"MIT"
] | permissive | pepaslabs/gpib-spy | 0bfade13a537d5b5d95c9ceff249ec34e14c554d | c8af76c0cca3b88dc702b4231f7550a356dd1027 | refs/heads/master | 2020-12-02T18:16:08.771372 | 2017-08-26T01:16:40 | 2017-08-26T01:16:40 | 96,505,749 | 1 | 1 | null | null | null | null | UTF-8 | Python | false | false | 2,075 | py | #!/usr/bin/env python
# gpib-pin-namer.py: rename the probes of an srzip file, according to gpib-spy pin ordering.
# See https://github.com/pepaslabs/gpib-spy
# Written by Jason Pepas, 2017. Released under the terms of the MIT License.
# See https://opensource.org/licenses/MIT
import sys
import os
import zipfile
import zlib
import tempfile
import ConfigParser
import shutil
# adjust as needed!
pinmap = {
"DAV": "probe1",
"NRFD": "probe2",
"NDAC": "probe3",
"IFC": "probe4",
"ATN": "probe5",
"SRQ": "probe6",
"REN": "probe7",
"EOI": "probe8",
"DIO1": "probe9",
"DIO2": "probe10",
"DIO3": "probe11",
"DIO4": "probe12",
"DIO5": "probe13",
"DIO6": "probe14",
"DIO7": "probe15",
"DIO8": "probe16"
}
if len(sys.argv) < 2:
sys.stderr.write("gpib-pin-renamer.py: rename the probes of an srzip file.\n")
sys.stderr.write("Usage: gpib-pin-renamer.py <srzip filename>\n")
sys.exit(1)
fname = sys.argv[1]
orig_fname = fname + ".orig"
assert os.path.exists(orig_fname) == False
shutil.move(fname, orig_fname)
zin = zipfile.ZipFile(orig_fname, 'r')
zout = zipfile.ZipFile(fname, mode='w', compression=zipfile.ZIP_DEFLATED)
# Copy the 'version' file
with zin.open("version", 'r') as fin:
with tempfile.NamedTemporaryFile() as fout:
fout.write(fin.read())
fout.flush()
zout.write(fout.name, "version")
# Copy the 'logic-1-1' file
with zin.open("logic-1-1", 'r') as fin:
with tempfile.NamedTemporaryFile() as fout:
fout.write(fin.read())
fout.flush()
zout.write(fout.name, "logic-1-1")
# Copy the 'metadata' file, renaming the probes.
with zin.open("metadata", 'r') as fin:
with tempfile.NamedTemporaryFile() as fout:
metadata = ConfigParser.ConfigParser()
metadata.readfp(fin)
for (pin_name, probe) in pinmap.iteritems():
metadata.set('device 1', probe, pin_name)
metadata.write(fout)
fout.flush()
zout.write(fout.name, "metadata")
zin.close()
zout.close()
os.unlink(orig_fname)
| [
"jasonpepas@gmail.com"
] | jasonpepas@gmail.com |
59b0b0c2ae063612d556effc933e16f12e660aca | 959b2c88182dc1241e708e9c3af0efdeed88b14c | /CNN-1/image_processing.py | 5218a54cc0324a9f0f67161e8115ff024d4baf55 | [] | no_license | csatacsirke/diplomamunka | f21f0e5eae736eac1ecbfc44a49665a6281d97e7 | ddc85871933c8d92bd20cac7489774d7713e967d | refs/heads/master | 2021-09-05T14:31:43.279548 | 2018-01-28T22:05:49 | 2018-01-28T22:05:49 | 108,988,428 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,137 | py | import numpy as np
import cv2
from log import log
import dataset_handler
default_input_file_name = 'jura/11.10/Bpas-Verdict.csv'
def normalize_image(image, corners, out_width = 1000, out_height = 1000):
#image = np.array(pil_image)
src = np.array(corners, dtype=np.float32);
dst = np.array([[0,out_height], [out_width,out_height], [out_width,0], [0,0]], dtype=np.float32)
transform = cv2.getPerspectiveTransform(src, dst)
image = cv2.warpPerspective(image, transform,(out_width, out_height))
return image
"""
dx = np.random.randint(-image.width//4, image.width//4+1)
dy = np.random.randint(-image.height//4, image.height//4+1)
center_x = image.width // 2 + dx
center_y = image.height // 2 + dy
# TODO randomizálni kicsit a centert
left = center_x - img_width // 2
top = center_y - img_height // 2
right = left + img_width
bottom = top + img_height
image = image.crop((left, top, right, bottom))
assert(image.width == img_width and image.height == img_height)
"""
def crop_random(image, dimensions):
height, width, channels = image.shape
new_width, new_height = dimensions
if width < new_width or height < new_height:
log("Warning: image_processing.crop_random(image, dimensions): width < new_width or height < new_height")
return image
rnd = np.random.uniform()
offset_x = int(rnd*(width - new_width))
rnd = np.random.uniform()
offset_y = int(rnd*(height - new_height))
"""
stackoverflow:
If we consider (0,0) as top left corner of image called im with left-to-right as x direction and top-to-bottom as y direction.
and we have (x1,y1) as the top-left vertex and (x2,y2) as the bottom-right vertex of a rectangle region within that image, then:
roi = im[y1:y2, x1:x2]
"""
image = image[offset_y:offset_y+new_height, offset_x:offset_x+new_width]
return image
def crop_top_right(image, dimensions):
height, width, channels = image.shape
new_width, new_height = dimensions
if width < new_width or height < new_height:
log("Warning: image_processing.crop_top_right(image, dimensions): width < new_width or height < new_height")
return image
offset_x = width - new_width
offset_y = 0
image = image[offset_y:offset_y+new_height, offset_x:offset_x+new_width]
return image
def crop_center(image, ratio):
height, width, channels = image.shape
new_width = round(width * ratio)
new_height = round(height * ratio)
offset_x = (width - new_width) // 2
offset_y = (height - new_height) // 2
image = image[offset_y:offset_y+new_height, offset_x:offset_x+new_width]
return image
def test():
file_name = "d:\\diplomamunka\\spaceticket\\copy\\spactick_2017_09_11_13_24_47_503__0.png"
image = cv2.imread(file_name)
corners_list = dataset_handler.read_corners(default_input_file_name)
corners = dataset_handler.find_corners_in_list(corners_list, file_name)
if corners is None:
assert("vaze" == "lofasz")
return
# 209.000000;1660.000000
# 1434.000000;1687.000000;
# 1461.000000;477.000000;
# 237.000000;441.000000;,
src = np.array(corners, dtype=np.float32);
dst = np.array([[0,500], [500,500], [500,0], [0,0]], dtype=np.float32)
transform = cv2.getPerspectiveTransform(src, dst)
image = cv2.warpPerspective(image, transform,(500, 500))
cv2.imwrite("kicsinyitett_proba.png", image)
cv2.imshow('warp test', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
def test2():
file_name = "d:\\diplomamunka\\spaceticket\\copy\\spactick_2017_09_11_13_24_47_503__0.png"
image = cv2.imread(file_name)
image = crop_top_right(image, (800, 800))
cv2.imshow('crop test', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
def test3():
file_name = "d:\\diplomamunka\\spaceticket\\copy\\normalized_spactick_2017_09_11_13_24_47_503__0.png"
image = cv2.imread(file_name)
image = crop_center(image, 0.6)
cv2.imshow('crop center test', image)
cv2.waitKey(0)
cv2.destroyAllWindows()
if __name__ == "__main__":
test3()
| [
"battlechicken74@gmail.com"
] | battlechicken74@gmail.com |
eaca908738f9697f7604adfa2bd4d184369f52ee | 5a07c07b538ac937eb46758663c8477b2797d957 | /esadmin/models.py | 5d471151e8fd65e688bedca00a65d58b85ace4cc | [] | no_license | 17issJLW/es_django | 2334be3b46a6be540343a069cab8a53c9aca1371 | 47a829c86f200ce0eff0fb2ae22cec943a69c7aa | refs/heads/master | 2020-09-13T07:41:34.432379 | 2019-07-11T10:04:00 | 2019-07-11T10:04:00 | 222,698,655 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,858 | py | from django.db import models
from django.utils import timezone
import uuid
# Create your models here.
class User(models.Model):
uid = models.UUIDField(verbose_name="用户id",primary_key=True,auto_created=True,default=uuid.uuid4, editable=False)
username = models.CharField(verbose_name="用户名",max_length=32,unique=True)
password = models.CharField(verbose_name="用户密码",max_length=128)
email = models.EmailField(verbose_name="邮箱")
role = models.ForeignKey("Roles", on_delete=models.CASCADE,default=None)
is_active = models.BooleanField(default=False)
class Meta:
verbose_name = '用户表'
verbose_name_plural = '用户表'
ordering = ['uid', ] # 防止rest_framework.PageNumberPagination 报错
def __str__(self):
return '用户 %s %s' % (self.uid, self.username)
class Roles(models.Model):
ROLE_NAME=(
("admin","admin"),
("user","user")
)
role_name = models.CharField(verbose_name="角色名",max_length=32)
class Meta:
verbose_name = '角色表'
verbose_name_plural = '角色表'
ordering = ['id',]
def __str__(self):
return '%s' % (self.role_name)
class Comment(models.Model):
uuid = models.UUIDField(primary_key=True,auto_created=True,default=uuid.uuid4, editable=False)
text = models.CharField(max_length=255)
date = models.DateTimeField(default=timezone.now)
user = models.ForeignKey("User",on_delete=models.CASCADE)
doc = models.CharField(max_length=64)
is_anonymous = models.BooleanField(default=False)
class Meta:
verbose_name = '评论表'
verbose_name_plural = '评论表'
ordering = ['uuid', ] # 防止rest_framework.PageNumberPagination 报错
def __str__(self):
return '%s 评论 %s' % (self.user.username, self.text)
| [
"32334181+17issJLW@users.noreply.github.com"
] | 32334181+17issJLW@users.noreply.github.com |
c90c5a2e44f94b97ff979d0f3257342981e30063 | fe8e3ccc75dbddca0c48c6db3b79fe93350c79d3 | /port/tests.py | 007b7a32c3527ffb2dd42b494335b952da99da33 | [
"BSD-3-Clause"
] | permissive | ShivaShankarPuvvada/assignmentsite | 1f3d0d6c72166b6efe43ee8c5595cd516f34af43 | 6f9fb0aff9d34cce20b0bde3be205fd25b5738ce | refs/heads/master | 2023-03-20T19:26:20.117317 | 2021-03-18T10:10:52 | 2021-03-18T10:10:52 | 348,745,352 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 748 | py | from django.urls import reverse
from rest_framework import status
from rest_framework.test import APITestCase
from port.models import Movie, Container, Wishlist
from port.serializers import WishlistSerializer, MovieSerializer, ContainerSerializer
class WishlistCreateTests(APITestCase):
# class: WishlistCreate
# method:Post
def test_can_create_wishlist(self):
url = reverse('port:create_wishlist')
data = {
"name":'my youtube videos',
}
response = self.client.post(url, data=data, format='json')
self.assertEqual(response.status_code, status.HTTP_201_CREATED)
self.assertEqual(Wishlist.objects.filter(name='my youtube videos').exists(), True)
| [
"om.ss.sankar@gmail.com"
] | om.ss.sankar@gmail.com |
a47be394d7d2bd1175776add55d602437a334d38 | 02bf3e48470d103d0f8378eabe982014443f3104 | /B_126_Day2.py | 7e2eff311064e0cbe478a2b39a87984e88e89f85 | [] | no_license | BALaka-18/IEM_Coding-5th-Semester | 3cc29b09a932318c3fd65a03f5ae314e498f52f4 | ca4e3d267d9c83978636c2e2c8f362da51dbe5fa | refs/heads/master | 2022-12-04T11:04:59.365152 | 2020-08-21T11:35:45 | 2020-08-21T11:35:45 | 285,761,474 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,313 | py | from collections import defaultdict
# l = [234,567,321,345,123,110,767,111]
def countPairs(l,bitp = [],firsts = [],check = defaultdict(list),pairs=0):
# Part 1 : Bit scores
for num in l:
temp = [int(i) for i in str(num)]
bit_sc = (11*max(temp)) + (7*min(temp))
bitp.append(bit_sc%100)
firsts = list(map(lambda x : x//10, bitp)) # Store the MSBs
# Lookup table
for i,dig in enumerate(firsts):
if i not in check[dig]:
check[dig].append(i)
else:
continue
# Part 2 : Count pairs
for elem in check.values():
pe,po,p_curr = 0,0,0
t_ev,t_odd = list(filter(lambda x: x%2 == 0, elem)),list(filter(lambda x: x%2 != 0, elem))
# Even indices
if len(t_ev) >= 3:
pe += 2
elif len(t_ev) == 2:
pe += 1
else:
pe += 0
# Odd indices
if len(t_odd) >= 3:
po += 2
elif len(t_odd) == 2:
po += 1
else:
po += 0
p_curr += (po + pe)
if p_curr >= 3:
pairs += 2
else:
pairs += p_curr
return pairs
# Driver code
if __name__ == "__main__":
N = int(input())
l = list(map(int, input().split()))
res = countPairs(l)
print(res)
| [
"noreply@github.com"
] | BALaka-18.noreply@github.com |
42a3a55436622b95c7a3e384b774081b2c293389 | 335a7a7af5eab950e147c79fe42ac52377f5778e | /PartialAgents.py | 248384a4c183cf1fff94801f2c8d8b87708eefba | [] | no_license | Fahad2314/Pacman | 9d4c56c96543f3662905eec41eee83bf4249203b | c58f0a273a19a02820f42e049c604184c113b50a | refs/heads/master | 2020-04-01T14:11:36.502889 | 2018-10-26T19:55:26 | 2018-10-26T19:55:26 | 153,284,480 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 21,256 | py | # sampleAgents.py
# parsons/07-oct-2017
#
# Version 1.1
#
# Some simple agents to work with the PacMan AI projects from:
#
# http://ai.berkeley.edu/
#
# These use a simple API that allow us to control Pacman's interaction with
# the environment adding a layer on top of the AI Berkeley code.
#
# As required by the licensing agreement for the PacMan AI we have:
#
# Licensing Information: You are free to use or extend these projects for
# educational purposes provided that (1) you do not distribute or publish
# solutions, (2) you retain this notice, and (3) you provide clear
# attribution to UC Berkeley, including a link to http://ai.berkeley.edu.
#
# Attribution Information: The Pacman AI projects were developed at UC Berkeley.
# The core projects and autograders were primarily created by John DeNero
# (denero@cs.berkeley.edu) and Dan Klein (klein@cs.berkeley.edu).
# Student side autograding was added by Brad Miller, Nick Hay, and
# Pieter Abbeel (pabbeel@cs.berkeley.edu).
# The agents here are extensions written by Simon Parsons, based on the code in
# pacmanAgents.py
from pacman import Directions
from game import Agent
import api
import random
import game
import util
import collections
# RandomAgent
#
# A very simple agent. Just makes a random pick every time that it is
# asked for an action.
# SensingAgent
#
# Doesn't move, but reports sensory data available to Pacman
class PartialAgent(Agent):
def __init__(self):
self.flag = 0
self.counter = 0
# persistent food list that pacman sees as he travels the grid
self.food_list = list()
# persistent list which follows pacmans footsetps
self.pacman_steps = list()
# list containing food which is not in pacmans steps so he does not unnecessarily go over his steps in search for food
def final(self,state):
self.flag = 0
self.counter = 0
self.food_list = list()
self.pacman_steps = list()
def getAction(self, state):
corners = api.corners(state)
wall_location = api.walls(state)
my_location = api.whereAmI(state)
food_location = api.food(state)
ghost_location = api.ghosts(state)
global flag
global food_list
global pacman_steps
global counter
global goal
if ghost_location:
legal = api.legalActions(state)
for ghost in ghost_location:
dist_to_ghost= util.manhattanDistance(my_location,ghost)
print("manhattan distance:", dist_to_ghost)
print("Ghost coordinates:", ghost)
if dist_to_ghost <=3 :
pathlist_to_ghost = self.bfs(my_location,ghost,wall_location)
print("pathlist to ghost", pathlist_to_ghost)
if pathlist_to_ghost:
banned = pathlist_to_ghost[1]
if banned[0] > my_location[0]:
legal.remove(Directions.EAST)
if Directions.WEST in legal:
return api.makeMove(Directions.WEST,legal)
else:
return api.makeMove(random.choice(legal),legal)
elif banned[0] < my_location[0]:
legal.remove(Directions.WEST)
if Directions.EAST in legal:
return api.makeMove(Directions.EAST,legal)
else:
return api.makeMove(random.choice(legal),legal)
elif banned[1] > my_location[1]:
legal.remove(Directions.NORTH)
if Directions.SOUTH in legal:
return api.makeMove(Directions.SOUTH,legal)
else:
return api.makeMove(random.choice(legal),legal)
elif banned[1] < my_location[1]:
legal.remove(Directions.SOUTH)
if Directions.NORTH in legal:
return api.makeMove(Directions.NORTH,legal)
else:
return api.makeMove(random.choice(legal),legal)
else:
return api.makeMove(Directions.STOP,legal)
if self.flag == 0:
# set self flag == 0
print("Flag is 0")
#raw_input("Press Enter")
legal = api.legalActions(state)
# increase self flag so that the getAction will return the next if block
x, y = corners[0]
# bottom left
x = x + 1
y = y + 1
goal = (x, y)
if goal not in wall_location:
pathlist = self.bfs(my_location, goal, wall_location)
direc = self.mapRoute(my_location, pathlist, legal, self.flag)
# print("Food visible:", food_location)
# add all visible food to the persistent food_location variable
for food in food_location:
# print(food)
if food not in self.food_list:
self.food_list.append(food)
# add every location that pacman is ever at to the persistent pacman_steps list
self.pacman_steps.append(my_location)
print("pacman location", my_location)
print("direc:", direc)
return api.makeMove(direc, legal)
else:
self.flag = 1
if self.flag == 1:
print("Flag is 1")
#raw_input("Press Enter")
legal = api.legalActions(state)
# increase self flag so that the getAction will return the next if block
x, y = corners[2]
# top left
x = x + 1
y = y - 1
goal = (x, y)
if goal not in wall_location:
pathlist = self.bfs(my_location, goal, wall_location)
direc = self.mapRoute(my_location, pathlist, legal, self.flag)
# updates the food_list a persistent list of food that pacman see's on his travels
print("Food visible:", food_location)
for food in food_location:
# print(food)
if food not in self.food_list:
self.food_list.append(food)
self.pacman_steps.append(my_location)
print("pacman location", my_location)
print("direc:", direc)
return api.makeMove(direc, legal)
else:
self.flag = 2
if self.flag == 2:
print("Flag is 2")
#raw_input("Press Enter")
legal = api.legalActions(state)
x, y = corners[3]
# top right
x = x - 1
y = y - 1
goal = (x, y)
if goal not in wall_location:
pathlist = self.bfs(my_location, goal, wall_location)
direc = self.mapRoute(my_location, pathlist, legal, self.flag)
for food in food_location:
# print(food)
if food not in self.food_list:
self.food_list.append(food)
self.pacman_steps.append(my_location)
print("pacman location", my_location)
print("direc:", direc)
return api.makeMove(direc, legal)
else:
self.flag = 3
if self.flag == 3:
print("Flag is 3")
#raw_input("Press Enter")
legal = api.legalActions(state)
x, y = corners[1]
# bottom right
x = x - 1
y = y + 1
goal = (x, y)
if goal not in wall_location:
# pathlist is the bfs which returns the path to the food location
pathlist = self.bfs(my_location, goal, wall_location)
# pass the bfs pathlist into the direc function
direc = self.mapRoute(my_location, pathlist, legal, self.flag)
# print("Food visible:", food_location)
for food in food_location:
# print(food)
if food not in self.food_list:
self.food_list.append(food)
self.pacman_steps.append(my_location)
print("pacman location", my_location)
print("direc:", direc)
global remaining_food
remaining_food = list(set(self.food_list) - set(self.pacman_steps))
print("length of remaining food:", len(remaining_food))
return api.makeMove(direc, legal)
else:
self.flag = 4
return api.makeMove(Directions.STOP, legal)
# loop through the list how many times it requires to end the remaining food list
while self.flag >=4 :
#raw_input("Press Enter")
legal = api.legalActions(state)
print("the final flag is ", self.flag)
# # print("the counter is: ", self.counter)
# print("THE GOAL IS :", goal)
print("Ordered Food Remaining 1 ", remaining_food)
self.pacman_steps.append(my_location)
print self.pacman_steps
remaining_food = list(set(self.food_list) - set(self.pacman_steps))
# for fruit in remaining_food:
# dist_array=[]
# distance = util.manhattanDistance(my_location,fruit)
# dist_array.append(distance)
# x = dist_array.index(min(dist_array))
remaining_food_with_distances = []
for i in remaining_food:
remaining_food_with_distances.append((i, util.manhattanDistance(my_location,i)))
min = 1000
for i in range(len(remaining_food_with_distances)):
if remaining_food_with_distances[i][1] < min:
min = remaining_food_with_distances[i][1]
#global goal
goal = remaining_food_with_distances[i][0]
#goal = remaining_food[0]
print("Ordered Food Remaining 2 ", remaining_food)
pathlist_f = self.bfs(my_location, goal, wall_location)
print("PACMAN IS AT:", my_location)
print("THE PATHLIST TO THE GOAL IS: ", pathlist_f)
direc = self.mapRouteFinal(my_location, pathlist_f, legal, self.flag, self.counter)
return api.makeMove(direc, legal)
def mapRoute(self, current_location, next_location, legal, flag):
# current location calls the api.whereAmI for pacman location, next_location is the pathlist
next_location.pop(0)
# removes the current location from the pathlist
len_of_list = len(next_location)
for i in range(len_of_list):
# loop runs until the pathlist is empty
if len_of_list > 1:
# print(next_location)
# print("Pacman was at :", current_location)
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (1, 0):
print("Went East to:", next_location[0])
print("steps left:", len_of_list)
if Directions.EAST in legal:
return Directions.EAST
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (
-1, 0):
print("Went West to:", next_location[0])
print("steps left:", len_of_list)
if Directions.WEST in legal:
return Directions.WEST
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (0, 1):
print("Went North to:", next_location[0])
print("steps left:", len_of_list)
if Directions.NORTH in legal:
return Directions.NORTH
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (
0, -1):
print("Went South to:", next_location[0])
print("steps left:", len_of_list)
if Directions.SOUTH in legal:
return Directions.SOUTH
if len_of_list == 1:
print(next_location)
print("steps left:", len_of_list)
print("NEW FLAG !!!!!!")
# self.flag =1
self.flag = self.flag + 1
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (1, 0):
print("Went East to:", next_location[0])
print("steps left:", len_of_list)
if Directions.EAST in legal:
return Directions.EAST
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (
-1, 0):
print("Went West to:", next_location[0])
print("steps left:", len_of_list)
if Directions.WEST in legal:
return Directions.WEST
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (0, 1):
print("Went North to:", next_location[0])
print("steps left:", len_of_list)
if Directions.NORTH in legal:
return Directions.NORTH
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (
0, -1):
print("Went South to:", next_location[0])
print("steps left:", len_of_list)
if Directions.SOUTH in legal:
return Directions.SOUTH
def mapRouteFinal(self, current_location, next_location, legal, flag, counter):
# current location calls the api.whereAmI for pacman location, next_location is the pathlist
next_location.pop(0)
# removes the current location from the pathlist
len_of_list = len(next_location)
for i in range(len_of_list):
# loop runs until the pathlist is empty
if len_of_list > 1:
print(next_location)
print("Pacman was at :", current_location)
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (1, 0):
print("Went East to:", next_location[0])
print("steps left:", len_of_list)
if Directions.EAST in legal:
return Directions.EAST
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (
-1, 0):
print("Went West to:", next_location[0])
print("steps left:", len_of_list)
if Directions.WEST in legal:
return Directions.WEST
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (0, 1):
print("Went North to:", next_location[0])
print("steps left:", len_of_list)
if Directions.NORTH in legal:
return Directions.NORTH
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (
0, -1):
print("Went South to:", next_location[0])
print("steps left:", len_of_list)
if Directions.SOUTH in legal:
return Directions.SOUTH
if len_of_list == 1:
print(next_location)
print("steps left:", len_of_list)
print("NEW FLAG !!!!!!")
# self.flag =1
self.flag = self.flag + 1
self.counter = self.counter + 1
# print("new flag:", self.flag)
#print("new counter:", self.counter)
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (1, 0):
print("Went East to:", next_location[0])
print("steps left:", len_of_list)
if Directions.EAST in legal:
return Directions.EAST
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (
-1, 0):
print("Went West to:", next_location[0])
print("steps left:", len_of_list)
if Directions.WEST in legal:
return Directions.WEST
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (0, 1):
print("Went North to:", next_location[0])
print("steps left:", len_of_list)
if Directions.NORTH in legal:
return Directions.NORTH
if ((next_location[0][0] - current_location[0]), (next_location[0][1] - current_location[1])) == (
0, -1):
print("Went South to:", next_location[0])
print("steps left:", len_of_list)
if Directions.SOUTH in legal:
return Directions.SOUTH
def mapRouteGhost(self, current_location, next_location, legal, flag):
# current location calls the api.whereAmI for pacman location, next_location is the pathlist
# removes the current location from the pathlist
len_of_list = len(next_location)
for i in range(len_of_list):
if util.manhattanDistance(current_location, next_location[1]) == 2 :
# loop runs until the pathlist is empty
if next_location[1][0] > current_location[0]:
if Directions.EAST in legal:
return legal.remove("East")
if next_location[1][0] < current_location[0]:
if Directions.WEST in legal:
return legal.remove("West")
if next_location[1][1] > current_location[1]:
if Directions.NORTH in legal:
return legal.remove("North")
if next_location[1][1] < current_location[1]:
if Directions.SOUTH in legal:
return legal.remove("South")
def bfs(self, start, goal, wall_location):
queue = collections.deque()
visited = set()
meta = dict()
# initialize
meta[start] = (None, None)
# append the start/root to the queue for frontier
queue.append(start)
while queue:
# current node is the current node being explored in the frontier from queue
start = queue.popleft()
# if the current node is the goal then call the construct_path function with current, and meta dict
if start == goal:
return (self.construct_path(start, meta, goal))
# for child in current node
for child, action in self.get_successor(start):
if child in visited:
continue
elif (child not in queue) and (child not in wall_location):
meta[child] = (start, action)
queue.append(child)
visited.add(start)
# print(visited)
def get_successor(self, my_location):
# create a list of children for the current location from pacman api
# print(my_location)
x, y = my_location
children = []
east = ((x + 1, y), (1, 0))
west = ((x - 1, y), (-1, 0))
north = ((x, y + 1), (0, 1))
south = ((x, y - 1), (0, -1))
children.append(east)
children.append(west)
children.append(north)
children.append(south)
# print(children)
return children
def construct_path(self, node, meta, goal):
action_list = []
while (meta[node][0] != None):
node, action = meta[node]
action_list.append(node)
action_list.reverse()
action_list = (action_list) + [goal]
# print(action_list)
return action_list
def order_list(self, unordered_list):
unordered_list.sort()
unordered_list.reverse()
return unordered_list
| [
"noreply@github.com"
] | Fahad2314.noreply@github.com |
7539af5bd72553d6c5546bde6f151c405ee9544a | 7eec4ad6c95f89d829d3b78b7ec993997df49a24 | /chapter1/src/py_files/mnist_with_keras_v2.py | 0c73ea2978e7f39985dfae725f03c4263c03ea06 | [] | no_license | masa26hiro/deep-learning-with-keras | 53749d430cb8b347bf721faa7a38b5108d7c6443 | 7f4fb75f40b2d534f07e8df79c3d6a6da609cefa | refs/heads/master | 2020-08-12T17:42:26.244354 | 2020-05-16T11:27:54 | 2020-05-16T11:27:54 | 214,811,590 | 2 | 0 | null | 2020-05-16T11:27:56 | 2019-10-13T11:54:50 | Jupyter Notebook | UTF-8 | Python | false | false | 2,921 | py | """add hidden layer
"""
import numpy as np
from tensorflow_core.python.keras.api._v2.keras.datasets import mnist
from tensorflow_core.python.keras.api._v2.keras.models import Sequential
from tensorflow_core.python.keras.api._v2.keras.layers import Dense, Activation
from tensorflow_core.python.keras.api._v2.keras.optimizers import SGD
from tensorflow_core.python.keras.api._v2.keras.utils import to_categorical
from make_tensorboard import make_tensorboard
# 乱数の固定
np.random.seed(1671)
# パラメータ設定
NB_EPOCH = 20 # エポック数
BATCH_SIZE = 128 # バッチサイズ
VERBOSE = 1 #
NB_CLASSES = 10 # 出力数
OPTIMIZER = SGD() # 最適化関数
N_HIDDEN = 128 # 隠れ層数
VALIDATION_SPLIT = 0.2 # 検証データの割合
# データの読み込み
(X_train, y_train), (X_test, y_test) = mnist.load_data()
RESHAPED = 784 # 28×28 = 784
# データの整形
TRAIN_DATA_SIZE = 60000
TEST_DATA_SIZE = 10000
X_train = X_train.reshape(TRAIN_DATA_SIZE, RESHAPED)
X_test = X_test.reshape(TEST_DATA_SIZE, RESHAPED)
X_train = X_train.astype('float32')
X_test = X_test.astype('float32')
# 正規化
X_train /= 255
X_test /= 255
print(X_train.shape[0], 'train sample')
print(X_test.shape[0], 'test sample')
# ラベルをOne-hotエンコーディング
Y_train = to_categorical(y_train, NB_CLASSES)
Y_test = to_categorical(y_test, NB_CLASSES)
# Sequentialモデルを定義
model = Sequential()
# 層を定義
model.add(Dense(N_HIDDEN, input_shape=(RESHAPED,))) # ← 784 × 128
model.add(Activation('relu'))
model.add(Dense(N_HIDDEN)) # ← 128 × 128
model.add(Activation('relu'))
model.add(Dense(NB_CLASSES)) # ← 128 × 10
model.add(Activation('softmax'))
# モデルを評価しTensorBoard互換のログに書き込む
model.summary()
# モデルをコンパイル
# -損失関数 ：カテゴリカルクロスエントロピー
# -最適化関数：確率的勾配降下法
# -評価関数 ：Accuracy(正解率)
model.compile(loss='categorical_crossentropy',
optimizer=OPTIMIZER,
metrics=['accuracy'])
callbacks = [make_tensorboard(set_dir_name='keras_MINST_V2')]
# 学習
# -バッチサイズ ：128
# -エポック数 ：200
# -コールバック関数：make_tensorboard(訓練の各段階で呼び出される関数)
# -ＶＥＲＢＯＳＥ ：詳細表示モードON
# -検証データの割合：20%
model.fit(X_train, Y_train,
batch_size=BATCH_SIZE,
epochs=NB_EPOCH,
callbacks=callbacks,
verbose=VERBOSE,
validation_split=VALIDATION_SPLIT)
# スコアを表示
score = model.evaluate(X_test, Y_test, verbose=VERBOSE)
print("\nTest score:", score[0])
print('Test accuracy:', score[1])
| [
"atuto.biwa1123@gmail.com"
] | atuto.biwa1123@gmail.com |
b897f8aa10fa308da9ad31ae61f9ebfe42f6e1a7 | 7235051c8def972f3403bf10155e246c9c291c58 | /angola_erp/util/pos.py | 08a97f1a33a84046fc03ca7f48407f4f98434233 | [
"MIT"
] | permissive | proenterprise/angola_erp | 8e79500ce7bcf499fc344948958ae8e8ab12f897 | 1c171362b132e567390cf702e6ebd72577297cdf | refs/heads/master | 2020-06-03T08:51:34.467041 | 2019-06-07T01:35:54 | 2019-06-07T01:35:54 | 191,514,859 | 1 | 0 | NOASSERTION | 2019-06-12T06:53:41 | 2019-06-12T06:53:41 | null | UTF-8 | Python | false | false | 13,486 | py | # -*- coding: utf-8 -*-
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors
# License: GNU General Public License v3. See license.txt
from __future__ import unicode_literals
import frappe, json
from frappe.utils import nowdate
from erpnext.setup.utils import get_exchange_rate
from erpnext.stock.get_item_details import get_pos_profile
from erpnext.accounts.party import get_party_account_currency
from erpnext.controllers.accounts_controller import get_taxes_and_charges
from frappe.utils import cstr, get_datetime, getdate, cint, get_datetime_str
@frappe.whitelist()
def get_pos_data():
print ("Get POS DATA ")
print ("Get POS DATA ")
print ("Get POS DATA ")
doc = frappe.new_doc('Sales Invoice')
doc.is_pos = 1;
pos_profile = get_pos_profile(doc.company) or {}
if not doc.company: doc.company = pos_profile.get('company')
doc.update_stock = pos_profile.get('update_stock')
if pos_profile.get('name'):
pos_profile = frappe.get_doc('POS Profile', pos_profile.get('name'))
company_data = get_company_data(doc.company)
update_pos_profile_data(doc, pos_profile, company_data)
update_multi_mode_option(doc, pos_profile)
default_print_format = pos_profile.get('print_format') or "Point of Sale"
print_template = frappe.db.get_value('Print Format', default_print_format, 'html')
#TO DELETE
print("Doc ", doc)
print("default_customer ", pos_profile.get('customer'))
#print("items ", get_items_list(pos_profile))
print("customers ", get_customers_list(pos_profile))
print("serial_no_data ", get_serial_no_data(pos_profile, doc.company))
print("batch_no_data ", get_batch_no_data())
print("tax_data ", get_item_tax_data())
print("price_list_data ", get_price_list_data(doc.selling_price_list))
print ("bin_data ", get_bin_data(pos_profile))
print("pricing_rules ", get_pricing_rule_data(doc))
print("print_template ", print_template)
print("pos_profile ", pos_profile)
return {
'doc': doc,
'default_customer': pos_profile.get('customer'),
'items': get_items_list(pos_profile),
'customers': get_customers_list(pos_profile),
'serial_no_data': get_serial_no_data(pos_profile, doc.company),
'batch_no_data': get_batch_no_data(),
'tax_data': get_item_tax_data(),
'price_list_data': get_price_list_data(doc.selling_price_list),
'bin_data': get_bin_data(pos_profile),
'pricing_rules': get_pricing_rule_data(doc),
'print_template': print_template,
'pos_profile': pos_profile,
'meta': get_meta()
}
def get_meta():
doctype_meta = {
'customer': frappe.get_meta('Customer'),
'invoice': frappe.get_meta('Sales Invoice')
}
for row in frappe.get_all('DocField', fields = ['fieldname', 'options'],
filters = {'parent': 'Sales Invoice', 'fieldtype': 'Table'}):
doctype_meta[row.fieldname] = frappe.get_meta(row.options)
return doctype_meta
def get_company_data(company):
return frappe.get_all('Company', fields = ["*"], filters= {'name': company})[0]
def update_pos_profile_data(doc, pos_profile, company_data):
doc.campaign = pos_profile.get('campaign')
doc.write_off_account = pos_profile.get('write_off_account') or \
company_data.write_off_account
doc.change_amount_account = pos_profile.get('change_amount_account') or \
company_data.default_cash_account
doc.taxes_and_charges = pos_profile.get('taxes_and_charges')
if doc.taxes_and_charges:
update_tax_table(doc)
doc.currency = pos_profile.get('currency') or company_data.default_currency
doc.conversion_rate = 1.0
if doc.currency != company_data.default_currency:
doc.conversion_rate = get_exchange_rate(doc.currency, company_data.default_currency, doc.posting_date)
doc.selling_price_list = pos_profile.get('selling_price_list') or \
frappe.db.get_value('Selling Settings', None, 'selling_price_list')
doc.naming_series = pos_profile.get('naming_series') or 'SINV-'
doc.letter_head = pos_profile.get('letter_head') or company_data.default_letter_head
doc.ignore_pricing_rule = pos_profile.get('ignore_pricing_rule') or 0
doc.apply_discount_on = pos_profile.get('apply_discount_on') if pos_profile.get('apply_discount') else ''
doc.customer_group = pos_profile.get('customer_group') or get_root('Customer Group')
doc.territory = pos_profile.get('territory') or get_root('Territory')
doc.terms = frappe.db.get_value('Terms and Conditions', pos_profile.get('tc_name'), 'terms') or doc.terms or ''
def get_root(table):
root = frappe.db.sql(""" select name from `tab%(table)s` having
min(lft)"""%{'table': table}, as_dict=1)
return root[0].name
def update_multi_mode_option(doc, pos_profile):
from frappe.model import default_fields
if not pos_profile or not pos_profile.get('payments'):
for payment in get_mode_of_payment(doc):
payments = doc.append('payments', {})
payments.mode_of_payment = payment.parent
payments.account = payment.default_account
payments.type = payment.type
return
for payment_mode in pos_profile.payments:
payment_mode = payment_mode.as_dict()
for fieldname in default_fields:
if fieldname in payment_mode:
del payment_mode[fieldname]
doc.append('payments', payment_mode)
def get_mode_of_payment(doc):
return frappe.db.sql(""" select mpa.default_account, mpa.parent, mp.type as type from `tabMode of Payment Account` mpa,
`tabMode of Payment` mp where mpa.parent = mp.name and mpa.company = %(company)s""", {'company': doc.company}, as_dict=1)
def update_tax_table(doc):
taxes = get_taxes_and_charges('Sales Taxes and Charges Template', doc.taxes_and_charges)
for tax in taxes:
doc.append('taxes', tax)
def get_items_list(pos_profile):
cond = "1=1"
item_groups = []
if pos_profile.get('item_groups'):
# Get items based on the item groups defined in the POS profile
for d in pos_profile.get('item_groups'):
item_groups.extend(get_child_nodes('Item Group', d.item_group))
cond = "item_group in (%s)"%(', '.join(['%s']*len(item_groups)))
return frappe.db.sql("""
select
name, item_code, item_name, description, item_group, expense_account, has_batch_no,
has_serial_no, expense_account, selling_cost_center, stock_uom, image,
default_warehouse, is_stock_item, barcode
from
tabItem
where
disabled = 0 and has_variants = 0 and is_sales_item = 1 and {cond}
""".format(cond=cond), tuple(item_groups), as_dict=1)
def get_customers_list(pos_profile):
cond = "1=1"
customer_groups = []
if pos_profile.get('customer_groups'):
# Get customers based on the customer groups defined in the POS profile
for d in pos_profile.get('customer_groups'):
customer_groups.extend(get_child_nodes('Customer Group', d.customer_group))
cond = "customer_group in (%s)"%(', '.join(['%s']*len(customer_groups)))
return frappe.db.sql(""" select name, customer_name, customer_group,
territory from tabCustomer where disabled = 0
and {cond}""".format(cond=cond), tuple(customer_groups), as_dict=1) or {}
def get_child_nodes(group_type, root):
lft, rgt = frappe.db.get_value(group_type, root, ["lft", "rgt"])
return frappe.db.sql_list(""" Select name from `tab{tab}` where
lft >= {lft} and rgt <= {rgt}""".format(tab=group_type, lft=lft, rgt=rgt))
def get_serial_no_data(pos_profile, company):
# get itemwise serial no data
# example {'Nokia Lumia 1020': {'SN0001': 'Pune'}}
# where Nokia Lumia 1020 is item code, SN0001 is serial no and Pune is warehouse
cond = "1=1"
if pos_profile.get('update_stock') and pos_profile.get('warehouse'):
cond = "warehouse = '{0}'".format(pos_profile.get('warehouse'))
serial_nos = frappe.db.sql("""select name, warehouse, item_code from `tabSerial No` where {0}
and company = %(company)s """.format(cond), {'company': company}, as_dict=1)
itemwise_serial_no = {}
for sn in serial_nos:
if sn.item_code not in itemwise_serial_no:
itemwise_serial_no.setdefault(sn.item_code, {})
itemwise_serial_no[sn.item_code][sn.name] = sn.warehouse
return itemwise_serial_no
def get_batch_no_data():
# get itemwise batch no data
# exmaple: {'LED-GRE': [Batch001, Batch002]}
# where LED-GRE is item code, SN0001 is serial no and Pune is warehouse
itemwise_batch = {}
batches = frappe.db.sql("""select name, item from `tabBatch`
where ifnull(expiry_date, '4000-10-10') >= curdate()""", as_dict=1)
for batch in batches:
if batch.item not in itemwise_batch:
itemwise_batch.setdefault(batch.item, [])
itemwise_batch[batch.item].append(batch.name)
return itemwise_batch
def get_item_tax_data():
# get default tax of an item
# example: {'Consulting Services': {'Excise 12 - TS': '12.000'}}
itemwise_tax = {}
taxes = frappe.db.sql(""" select parent, tax_type, tax_rate from `tabItem Tax`""", as_dict=1)
for tax in taxes:
if tax.parent not in itemwise_tax:
itemwise_tax.setdefault(tax.parent, {})
itemwise_tax[tax.parent][tax.tax_type] = tax.tax_rate
return itemwise_tax
def get_price_list_data(selling_price_list):
itemwise_price_list = {}
price_lists = frappe.db.sql("""Select ifnull(price_list_rate, 0) as price_list_rate,
item_code from `tabItem Price` ip where price_list = %(price_list)s""",
{'price_list': selling_price_list}, as_dict=1)
for item in price_lists:
itemwise_price_list[item.item_code] = item.price_list_rate
return itemwise_price_list
def get_bin_data(pos_profile):
itemwise_bin_data = {}
cond = "1=1"
if pos_profile.get('warehouse'):
cond = "warehouse = '{0}'".format(pos_profile.get('warehouse'))
bin_data = frappe.db.sql(""" select item_code, warehouse, actual_qty from `tabBin`
where actual_qty > 0 and {cond}""".format(cond=cond), as_dict=1)
for bins in bin_data:
if bins.item_code not in itemwise_bin_data:
itemwise_bin_data.setdefault(bins.item_code, {})
itemwise_bin_data[bins.item_code][bins.warehouse] = bins.actual_qty
return itemwise_bin_data
def get_pricing_rule_data(doc):
pricing_rules = ""
if doc.ignore_pricing_rule == 0:
pricing_rules = frappe.db.sql(""" Select * from `tabPricing Rule` where docstatus < 2
and ifnull(for_price_list, '') in (%(price_list)s, '') and selling = 1
and ifnull(company, '') in (%(company)s, '') and disable = 0 and %(date)s
between ifnull(valid_from, '2000-01-01') and ifnull(valid_upto, '2500-12-31')
order by priority desc, name desc""",
{'company': doc.company, 'price_list': doc.selling_price_list, 'date': nowdate()}, as_dict=1)
return pricing_rules
@frappe.whitelist()
def make_invoice(doc_list):
if isinstance(doc_list, basestring):
doc_list = json.loads(doc_list)
name_list = []
for docs in doc_list:
for name, doc in docs.items():
if not frappe.db.exists('Sales Invoice', {'offline_pos_name': name}):
validate_records(doc)
si_doc = frappe.new_doc('Sales Invoice')
si_doc.offline_pos_name = name
si_doc.update(doc)
submit_invoice(si_doc, name)
name_list.append(name)
else:
name_list.append(name)
return name_list
def validate_records(doc):
validate_customer(doc)
validate_item(doc)
def validate_customer(doc):
if not frappe.db.exists('Customer', doc.get('customer')):
customer_doc = frappe.new_doc('Customer')
customer_doc.customer_name = doc.get('customer')
customer_doc.customer_type = 'Company'
customer_doc.customer_group = doc.get('customer_group')
customer_doc.territory = doc.get('territory')
customer_doc.save(ignore_permissions = True)
frappe.db.commit()
doc['customer'] = customer_doc.name
def validate_item(doc):
for item in doc.get('items'):
if not frappe.db.exists('Item', item.get('item_code')):
item_doc = frappe.new_doc('Item')
item_doc.name = item.get('item_code')
item_doc.item_code = item.get('item_code')
item_doc.item_name = item.get('item_name')
item_doc.description = item.get('description')
item_doc.default_warehouse = item.get('warehouse')
item_doc.stock_uom = item.get('stock_uom')
item_doc.item_group = item.get('item_group')
item_doc.save(ignore_permissions=True)
frappe.db.commit()
def submit_invoice(si_doc, name):
try:
si_doc.insert()
si_doc.submit()
frappe.db.commit()
except Exception, e:
if frappe.message_log: frappe.message_log.pop()
frappe.db.rollback()
save_invoice(e, si_doc, name)
def save_invoice(e, si_doc, name):
if not frappe.db.exists('Sales Invoice', {'offline_pos_name': name}):
si_doc.docstatus = 0
si_doc.flags.ignore_mandatory = True
si_doc.insert()
#Atendimento Bar
def get_mesas_list():
print "mesas "
print frappe.db.sql(""" select name, nome_mesa, numero_cartao, mesa_image, status_mesa from tabMesas where status_mesa in ('Livre','Ocupada') """, as_dict=1)
return frappe.db.sql("""
select
name, nome_mesa, numero_cartao, mesa_image, status_mesa
from
tabMesas
where
status_mesa in ('Livre','Ocupada') """, as_dict=1)
def submit_atendimento(si_doc, name):
try:
si_doc.insert()
si_doc.save()
#si_doc.submit()
except Exception, e:
if frappe.message_log: frappe.message_log.pop()
frappe.db.rollback()
save_atendimento(e, si_doc, name)
def save_atendimento(e, si_doc, name):
if not frappe.db.exists('Atendimento Bar', {'offline_pos_name': name}):
si_doc.docstatus = 0
si_doc.flags.ignore_mandatory = True
si_doc.insert()
def as_unicode(text, encoding='utf-8'):
#Convert to unicode if required
print ("AS UNICODE DEF")
if text and not isinstance(text, unicode):
if isinstance(text, unicode):
return text
elif text==None:
return ''
elif isinstance(text, basestring):
return unicode(text, encoding)
else:
return text or ''
return unicode(text)
| [
"hcesar@gmail.com"
] | hcesar@gmail.com |
fa3d676bbc3f020ad545a8bf79d000525eb4db51 | d7ffdefb25b4091cf92f25354ee55535ee2ccd0d | /svnhook/pre-commit.py | 9cfd90437dce4996aa506c4eb5246a4a4a300181 | [] | no_license | MRlijiawei/demos | 5a4c1a0c74fe64f2e009c2b5e0234d57e187e83d | 0c69427008fb9d94401c936178775d7cbcbec1a2 | refs/heads/master | 2022-12-20T08:11:50.629183 | 2020-12-20T01:35:50 | 2020-12-20T01:35:50 | 144,269,765 | 3 | 1 | null | 2022-12-10T13:44:48 | 2018-08-10T09:59:32 | JavaScript | UTF-8 | Python | false | false | 1,434 | py | import sys
def err(msg):
sys.stderr.write(msg+'\n')
svnRepos = sys.argv[1]#提交文件列表
#svnMessageFile = sys.argv[3]
#sys.stderr.write(sys.argv[0]+'\n'+sys.argv[1]+'\n'+sys.argv[2]+'\n'+sys.argv[3]+'\n'+sys.argv[4]+'\n')参数依次为脚本路径、文件列表文件、depth、提交的message文件、提交文件的路径
errMsgTable = []
with open(svnRepos) as submitFiles:
for submitFile in submitFiles:
submitFile = submitFile.replace('\n', '')#去掉文件列表缓存文件中的换行
fp = open(submitFile, 'r', encoding='utf-8')
frontLine = ''
lNum = 0
for line in fp.readlines():#逐行读取
lNum += 1
line = line.strip().replace(' ','')
if (',]' in line) or (',}' in line):
errMsgTable.append([submitFile, lNum, 'Illegal Comma'])
if len(frontLine) > 0 and len(line) > 0:
if (frontLine[-1] == ',') and (line[0] == ']' or line[0] == '}'):
errMsgTable.append([submitFile, lNum, 'Illegal Comma'])
if len(line) > 0:
frontLine = line
fp.close()
# errMsgTable.append(['', '', 'test'])
if errMsgTable:
err('===================== error begin ========================================')
for msgArr in errMsgTable:
err('File:%s line:%s msg :%s' % (msgArr[0], msgArr[1], msgArr[2]))
err('===================== error end ==========================================')
sys.exit(1)
else:
sys.exit(0)
| [
"noreply@github.com"
] | MRlijiawei.noreply@github.com |
b337f6aee723f4459aeec92afd403aed31c8752e | 7ba9ba1570ef44ced18bf7689329d5f5d4bcc350 | /tests/test_parser.py | 9f0adecc75ae53a256f81e2408b05b003e59ff75 | [
"MIT"
] | permissive | la-mar/permian-frac-exchange | 90992393cdcdb6c6a8b697a5c7d8fc64a4bff2f2 | a7ba410c02b49d05c5ad28eff0619a3c198d3fd0 | refs/heads/master | 2020-06-12T04:40:52.642629 | 2020-04-14T23:50:07 | 2020-04-14T23:50:07 | 194,196,884 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 6,248 | py | from datetime import datetime
import pytest # noqa
from collector.parser import (
Parser,
Criterion,
RegexCriterion,
ValueCriterion,
TypeCriterion,
ParserRule,
)
# TODO: incorporate hypothesis
@pytest.fixture
def parser(conf):
yield Parser.init(conf.PARSER_CONFIG["parsers"]["default"]["rules"], name="default")
@pytest.fixture
def arbitrary_callable():
def return1(value):
return 1
yield return1
@pytest.fixture
def rule():
fc = RegexCriterion(r"^[-+]?\d*\.\d+$")
ic = RegexCriterion(r"^[-+]?[0-9]+$")
yield ParserRule(criteria=[fc, ic], allow_partial=True)
class TestParser:
def test_parse_signed_int(self, parser):
inputs = [
"+00001",
"+01",
"+1",
"+11",
"-00001",
"-01",
"-1",
"-11",
"+0",
"-0",
"+00",
"-00",
"+00000",
"-00000",
]
expected = [1, 1, 1, 11, -1, -1, -1, -11, 0, 0, 0, 0, 0, 0]
result = [parser.parse(x) for x in inputs]
assert result == expected
def test_parse_unsigned_int(self, parser):
inputs = ["1", "10"]
expected = [1, 10]
result = [parser.parse(x) for x in inputs]
assert result == expected
def test_parse_signed_float(self, parser):
inputs = [
"+1.1034",
"-1.1034",
"+0.1034",
"-0.1034",
"+11.1034",
"+00.1034",
"+01.1034",
"-11.1034",
"-00.1034",
"-01.1034",
"+1234567890.1034",
"-1234567890.1034",
"+31.24141",
"-101.98853",
]
expected = [
1.1034,
-1.1034,
0.1034,
-0.1034,
11.1034,
0.1034,
1.1034,
-11.1034,
-0.1034,
-1.1034,
1234567890.1034,
-1234567890.1034,
31.24141,
-101.98853,
]
result = [parser.parse(x) for x in inputs]
assert result == expected
def test_parse_unsigned_float(self, parser):
inputs = [
"1.1034",
"0.1034",
"11.1034",
"00.1034",
"01.1034",
"1234567890.1034",
"31.24141",
"101.98853",
]
expected = [
1.1034,
0.1034,
11.1034,
0.1034,
1.1034,
1234567890.1034,
31.24141,
101.98853,
]
result = [parser.parse(x) for x in inputs]
assert result == expected
def test_parse_datetime(self, parser):
inputs = [
"2019-01-01",
"2019/01/01",
"19-01-01",
"9/11/2014 12:00:00 AM",
"9/25/2014 5:00:00 AM",
]
expected = [
datetime(year=2019, month=1, day=1),
datetime(year=2019, month=1, day=1),
datetime(year=2001, month=1, day=19),
datetime(year=2014, month=9, day=11, hour=0),
datetime(year=2014, month=9, day=25, hour=5),
]
result = [parser.parse(x) for x in inputs]
assert result == expected
def test_ignore_clouded_datetime(self, parser):
inputs = [
"qwe2019-01-01",
"2019-01-01rte",
"3242019-01-01",
]
assert parser.parse_many(inputs) == inputs
def test_ignore_incomplete_datetime(self, parser):
inputs = ["2019-01"]
assert parser.parse_many(inputs) == inputs
def test_parse_bool(self, parser):
inputs = ["true", "True", "false", "False"]
expected = [True, True, False, False]
result = [parser.parse(x) for x in inputs]
assert result == expected
def test_parser_repr(self, parser):
repr(parser)
def test_parser_rule_repr(self, rule):
repr(rule)
def test_try_date(self, parser):
assert parser.try_date("2019-01-01") == datetime(2019, 1, 1)
def test_try_date_handle_none(self, parser):
assert parser.try_date(None) is None
def test_add_rule(self, rule):
parser = Parser(rules=[rule, rule])
parser.add_rule(rule)
assert len(parser.rules) == 3
class TestCriterion:
def test_criterion_repr_works(self):
repr(Criterion(lambda x: 1, name="test"))
def test_regexcriterion_repr_works(self):
repr(RegexCriterion(r"\w", name="test"))
def test_criterion_callable(self):
c = Criterion(lambda x: 1, name="test")
assert c(1) == 1
def test_regex_criterion(self):
rc = RegexCriterion("\w")
assert rc("test value") is True
def test_type_criterion_int(self):
tc = TypeCriterion(int)
assert tc(1) is True
def test_type_criterion_string_is_not_int(self):
tc = TypeCriterion(str)
assert tc(1) is False
def test_value_criterion_parse_value(self):
vc = ValueCriterion(123)
assert vc(123) is True
def test_rule_repr(self, rule):
repr(rule)
def test_rule_return_partials(self, rule):
assert rule("123.321", return_partials=True) == [True, False]
def test_get_match_mode(self, rule):
assert rule.match_mode == "PARTIAL"
def test_toggle_match_mode(self, rule):
rule.allow_partial = False
assert rule.match_mode == "FULL"
def test_partial_parse(self, rule):
assert rule("123") is True
assert rule("132.32") is True
assert rule("test553.23") is False
assert rule("55test") is False
assert rule("55.123test") is False
assert rule("test55.123") is False
def test_full_parse(self):
fc = RegexCriterion(r"^[-+]?\d*\.\d+$")
fc2 = RegexCriterion(r"^[-+]?\d*\.\d+$")
rule = ParserRule(criteria=[fc, fc2], allow_partial=False)
assert rule("132.32") is True
assert rule("test553.23") is False
assert rule("55test") is False
assert rule("55.123test") is False
assert rule("test55.123") is False
| [
"brocklfriedrich@gmail.com"
] | brocklfriedrich@gmail.com |
b2f0f8b313ca9593ccf205bdc78c29e57c2c5e11 | 52b5773617a1b972a905de4d692540d26ff74926 | /.history/uniquePaths_20200728102111.py | 901621991495a0a8768d4a84111fc13ad116e8f3 | [] | no_license | MaryanneNjeri/pythonModules | 56f54bf098ae58ea069bf33f11ae94fa8eedcabc | f4e56b1e4dda2349267af634a46f6b9df6686020 | refs/heads/master | 2022-12-16T02:59:19.896129 | 2020-09-11T12:05:22 | 2020-09-11T12:05:22 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 541 | py | def uniquePath(arr):
# mark one as None or -1 thatway in the case where
# we have to only calculate the once where there is no none
for i in range(len(arr)):
for j in range(len(arr[i])):
if arr[i][j] == 1:
arr[i][j] = "None"
elif i == 0 or j == 0:
arr[i][j] = 1
for i in range(len(arr))
print(arr)
uniquePath([
[0,0,0],
[0,1,0],
[0,0,0]
]) | [
"mary.jereh@gmail.com"
] | mary.jereh@gmail.com |
cc3fc7bdd04d61ca8590899b3ef2ff1afabc24dc | feb3dde481d1789ecfb331bbacc36630743c724f | /src/telegram_connector/telegram_registrator/registrator.py | fd516709e7a7c0717404a846f9ed6b7079571a3d | [] | no_license | VetoS88/tranfer_session_test | f74df56cac5b6180a9fce7f31bfd6bae789a0cea | d335f2320ca914792b9f5b5f35d6cdb8e5aa2085 | refs/heads/master | 2020-12-02T07:40:55.248319 | 2017-07-10T06:58:45 | 2017-07-10T06:58:45 | 96,712,440 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 21,450 | py | import platform
from datetime import timedelta
from threading import Event, RLock, Thread
from time import sleep
# Import some externalized utilities to work with the Telegram types and more
from telethon import TelegramClient
from telethon.errors import (RPCError, InvalidDCError, FloodWaitError,
ReadCancelledError)
from telethon.network import authenticator, MtProtoSender, TcpTransport
# For sending and receiving requests
from telethon.tl import MTProtoRequest, Session, JsonSession
from telethon.tl.all_tlobjects import layer
from telethon.tl.functions import (InitConnectionRequest, InvokeWithLayerRequest)
# Required to work with different data centers
from telethon.tl.functions.auth import (CheckPhoneRequest)
# Logging in and out
from telethon.tl.functions.auth import (SendCodeRequest, SignUpRequest)
# Initial request
from telethon.tl.functions.help import GetConfigRequest
from telethon.tl.types import UpdateShortMessage, UpdateShortChatMessage
from telethon.utils import get_display_name
# from config.logging_config import app_logger
# Required to get the password salt
# Easier access to common methods
# For .get_me() and ensuring we're authorized
# Easier access for working with media, too
# All the types we need to work with
from Archive.loging_config_local import app_logger
def sprint(string, *args, **kwargs):
"""Safe Print (handle UnicodeEncodeErrors on some terminals)"""
try:
print(string, *args, **kwargs)
except UnicodeEncodeError:
string = string.encode('utf-8', errors='ignore') \
.decode('ascii', errors='ignore')
print(string, *args, **kwargs)
def print_title(title):
# Clear previous window
print('\n')
print('=={}=='.format('=' * len(title)))
sprint('= {} ='.format(title))
print('=={}=='.format('=' * len(title)))
def bytes_to_string(byte_count):
"""Converts a byte count to a string (in KB, MB...)"""
suffix_index = 0
while byte_count >= 1024:
byte_count /= 1024
suffix_index += 1
return '{:.2f}{}'.format(byte_count,
[' bytes', 'KB', 'MB', 'GB', 'TB'][suffix_index])
class TelegramRegistrator(TelegramClient):
# Current TelegramClient version
__version__ = '0.10.1'
# region Initialization
def __init__(self, session, api_id=None, api_hash=None, proxy=None):
"""Initializes the Telegram client with the specified API ID and Hash.
Session can either be a `str` object (the filename for the loaded/saved .session)
or it can be a `Session` instance (in which case list_sessions() would probably not work).
If you don't want any file to be saved, pass `None`
In the later case, you are free to override the `Session` class to provide different
.save() and .load() implementations to suit your needs."""
# if api_id is None or api_hash is None:
# raise PermissionError(
# 'Your API ID or Hash are invalid. Please read "Requirements" on README.rst')
super().__init__(session, api_id, api_hash, proxy)
self.api_id = api_id
self.api_hash = api_hash
# Determine what session object we have
# TODO JsonSession until migration is complete (by v1.0)
if isinstance(session, str) or session is None:
self.session = JsonSession.try_load_or_create_new(session)
elif isinstance(session, Session):
self.session = session
else:
raise ValueError(
'The given session must either be a string or a Session instance.')
self.transport = None
self.proxy = proxy # Will be used when a TcpTransport is created
self.login_success = False
# Safety across multiple threads (for the updates thread)
self._lock = RLock()
self._logger = app_logger
# Methods to be called when an update is received
self._update_handlers = []
self._updates_thread_running = Event()
self._updates_thread_receiving = Event()
# Cache "exported" senders 'dc_id: MtProtoSender' and
# their corresponding sessions not to recreate them all
# the time since it's a (somewhat expensive) process.
self._cached_senders = {}
self._cached_sessions = {}
# These will be set later
self._updates_thread = None
self.dc_options = None
self.sender = None
self.phone_code_hashes = {}
def connect(self, reconnect=False,
device_model=None, system_version=None,
app_version=None, lang_code=None):
"""Connects to the Telegram servers, executing authentication if
required. Note that authenticating to the Telegram servers is
not the same as authenticating the desired user itself, which
may require a call (or several) to 'sign_in' for the first time.
Default values for the optional parameters if left as None are:
device_model = platform.node()
system_version = platform.system()
app_version = TelegramClient.__version__
lang_code = 'en'
"""
if self.transport is None:
self.transport = TcpTransport(self.session.server_address,
self.session.port, proxy=self.proxy)
try:
if not self.session.auth_key or (reconnect and self.sender is not None):
self.session.auth_key, self.session.time_offset = \
authenticator.do_authentication(self.transport)
self.session.save()
self.sender = MtProtoSender(self.transport, self.session)
self.sender.connect()
# Set the default parameters if left unspecified
if not device_model:
device_model = platform.node()
if not system_version:
system_version = platform.system()
if not app_version:
app_version = self.__version__
if not lang_code:
lang_code = 'en'
# Now it's time to send an InitConnectionRequest
# This must always be invoked with the layer we'll be using
query = InitConnectionRequest(
api_id=self.api_id,
device_model=device_model,
system_version=system_version,
app_version=app_version,
lang_code=lang_code,
query=GetConfigRequest())
result = self.invoke(
InvokeWithLayerRequest(
layer=layer, query=query))
# We're only interested in the DC options,
# although many other options are available!
self.dc_options = result.dc_options
self.login_success = True
return True
except (RPCError, ConnectionError) as error:
# Probably errors from the previous session, ignore them
self._logger.warning('Could not stabilise initial connection: {}'
.format(error))
return False
def check_phone(self, phone_number):
result = self.invoke(
CheckPhoneRequest(phone_number=phone_number))
return result
def sign_up(self, phone_number, code, first_name, last_name=''):
"""Signs up to Telegram. Make sure you sent a code request first!"""
result = self.invoke(
SignUpRequest(
phone_number=phone_number,
phone_code_hash=self.phone_code_hashes[phone_number],
phone_code=code,
first_name=first_name,
last_name=last_name))
self.session.user = result.user
self.session.save()
return result
def invoke(self, request, timeout=timedelta(seconds=5), throw_invalid_dc=False):
"""Invokes a MTProtoRequest (sends and receives it) and returns its result.
An optional timeout can be given to cancel the operation after the time delta.
Timeout can be set to None for no timeout.
If throw_invalid_dc is True, these errors won't be caught (useful to
avoid infinite recursion). This should not be set to True manually."""
if not issubclass(type(request), MTProtoRequest):
raise ValueError('You can only invoke MtProtoRequests')
if not self.sender:
raise ValueError('You must be connected to invoke requests!')
if self._updates_thread_receiving.is_set():
self.sender.cancel_receive()
try:
self._lock.acquire()
updates = []
self.sender.send(request)
self.sender.receive(request, timeout, updates=updates)
for update in updates:
for handler in self._update_handlers:
handler(update)
return request.result
except InvalidDCError as error:
if throw_invalid_dc:
raise
self._reconnect_to_dc(error.new_dc)
return self.invoke(request,
timeout=timeout, throw_invalid_dc=True)
except ConnectionResetError:
self._logger.info('Server disconnected us. Reconnecting and '
'resending request...')
self.reconnect()
self.invoke(request, timeout=timeout,
throw_invalid_dc=throw_invalid_dc)
except FloodWaitError:
self.disconnect()
raise
finally:
self._lock.release()
def reconnect(self):
"""Disconnects and connects again (effectively reconnecting)"""
self.disconnect()
self.connect()
def disconnect(self):
"""Disconnects from the Telegram server and stops all the spawned threads"""
self._set_updates_thread(running=False)
if self.sender:
self.sender.disconnect()
self.sender = None
if self.transport:
self.transport.close()
self.transport = None
# Also disconnect all the cached senders
for sender in self._cached_senders.values():
sender.disconnect()
self._cached_senders.clear()
self._cached_sessions.clear()
def _set_updates_thread(self, running):
"""Sets the updates thread status (running or not)"""
if running == self._updates_thread_running.is_set():
return
# Different state, update the saved value and behave as required
self._logger.info('Changing updates thread running status to %s', running)
if running:
self._updates_thread_running.set()
if not self._updates_thread:
self._updates_thread = Thread(
name='UpdatesThread', daemon=True,
target=self._updates_thread_method)
self._updates_thread.start()
else:
self._updates_thread_running.clear()
if self._updates_thread_receiving.is_set():
self.sender.cancel_receive()
def _updates_thread_method(self):
"""This method will run until specified and listen for incoming updates"""
# Set a reasonable timeout when checking for updates
timeout = timedelta(minutes=1)
while self._updates_thread_running.is_set():
# Always sleep a bit before each iteration to relax the CPU,
# since it's possible to early 'continue' the loop to reach
# the next iteration, but we still should to sleep.
sleep(0.1)
with self._lock:
self._logger.debug('Updates thread acquired the lock')
try:
self._updates_thread_receiving.set()
self._logger.debug('Trying to receive updates from the updates thread')
result = self.sender.receive_update(timeout=timeout)
self._logger.info('Received update from the updates thread')
for handler in self._update_handlers:
handler(result)
except ConnectionResetError:
self._logger.info('Server disconnected us. Reconnecting...')
self.reconnect()
except TimeoutError:
self._logger.debug('Receiving updates timed out')
except ReadCancelledError:
self._logger.info('Receiving updates cancelled')
except OSError:
self._logger.warning('OSError on updates thread, %s logging out',
'was' if self.sender.logging_out else 'was not')
if self.sender.logging_out:
# This error is okay when logging out, means we got disconnected
# TODO Not sure why this happens because we call disconnect()…
self._set_updates_thread(running=False)
else:
raise
self._logger.debug('Updates thread released the lock')
self._updates_thread_receiving.clear()
# Thread is over, so clean unset its variable
self._updates_thread = None
def _reconnect_to_dc(self, dc_id):
"""Reconnects to the specified DC ID. This is automatically
called after an InvalidDCError is raised"""
dc = self._get_dc(dc_id)
self.transport.close()
self.transport = None
self.session.server_address = dc.ip_address
self.session.port = dc.port
self.session.save()
self.connect(reconnect=True)
def _get_dc(self, dc_id):
"""Gets the Data Center (DC) associated to 'dc_id'"""
if not self.dc_options:
raise ConnectionError(
'Cannot determine the required data center IP address. '
'Stabilise a successful initial connection first.')
return next(dc for dc in self.dc_options if dc.id == dc_id)
def send_code_request(self, phone_number):
"""Sends a code request to the specified phone number"""
result = self.invoke(SendCodeRequest(phone_number, self.api_id, self.api_hash))
self.phone_code_hashes[phone_number] = result.phone_code_hash
return result
def run(self):
# Listen for updates
self.add_update_handler(self.update_handler)
# Enter a while loop to chat as long as the user wants
while True:
# Retrieve the top dialogs
dialog_count = 10
# Entities represent the user, chat or channel
# corresponding to the dialog on the same index
dialogs, entities = self.get_dialogs(dialog_count)
i = None
while i is None:
print_title('Dialogs window')
# Display them so the user can choose
for i, entity in enumerate(entities, start=1):
sprint('{}. {}'.format(i, get_display_name(entity)))
# Let the user decide who they want to talk to
print()
print('> Who do you want to send messages to?')
print('> Available commands:')
print(' !q: Quits the dialogs window and exits.')
print(' !l: Logs out, terminating this session.')
print()
i = input('Enter dialog ID or a command: ')
if i == '!q':
return
if i == '!l':
self.log_out()
return
try:
i = int(i if i else 0) - 1
# Ensure it is inside the bounds, otherwise retry
if not 0 <= i < dialog_count:
i = None
except ValueError:
i = None
# Retrieve the selected user (or chat, or channel)
entity = entities[i]
# Show some information
print_title('Chat with "{}"'.format(get_display_name(entity)))
print('Available commands:')
print(' !q: Quits the current chat.')
print(' !Q: Quits the current chat and exits.')
print(' !h: prints the latest messages (message History).')
print(' !up <path>: Uploads and sends the Photo from path.')
print(' !uf <path>: Uploads and sends the File from path.')
print(' !dm <msg-id>: Downloads the given message Media (if any).')
print(' !dp: Downloads the current dialog Profile picture.')
print()
# And start a while loop to chat
while True:
msg = input('Enter a message: ')
# Quit
if msg == '!q':
break
elif msg == '!Q':
return
# History
elif msg == '!h':
# First retrieve the messages and some information
total_count, messages, senders = self.get_message_history(
entity, limit=10)
# Iterate over all (in reverse order so the latest appear
# the last in the console) and print them with format:
# "[hh:mm] Sender: Message"
for msg, sender in zip(
reversed(messages), reversed(senders)):
# Get the name of the sender if any
if sender:
name = getattr(sender, 'first_name', None)
if not name:
name = getattr(sender, 'title')
if not name:
name = '???'
else:
name = '???'
# Format the message content
if getattr(msg, 'media', None):
self.found_media.add(msg)
# The media may or may not have a caption
caption = getattr(msg.media, 'caption', '')
content = '<{}> {}'.format(
type(msg.media).__name__, caption)
elif hasattr(msg, 'message'):
content = msg.message
elif hasattr(msg, 'action'):
content = str(msg.action)
else:
# Unknown message, simply print its class name
content = type(msg).__name__
# And print it to the user
sprint('[{}:{}] (ID={}) {}: {}'.format(
msg.date.hour, msg.date.minute, msg.id, name,
content))
# Send photo
elif msg.startswith('!up '):
# Slice the message to get the path
self.send_photo(path=msg[len('!up '):], entity=entity)
# Send file (document)
elif msg.startswith('!uf '):
# Slice the message to get the path
self.send_document(path=msg[len('!uf '):], entity=entity)
# Download media
elif msg.startswith('!dm '):
# Slice the message to get message ID
self.download_media(msg[len('!dm '):])
# Download profile photo
elif msg == '!dp':
output = str('usermedia/propic_{}'.format(entity.id))
print('Downloading profile picture...')
success = self.download_profile_photo(entity.photo, output)
if success:
print('Profile picture downloaded to {}'.format(
output))
else:
print('No profile picture found for this user.')
# Send chat message (if any)
elif msg:
self.send_message(
entity, msg, no_web_page=True)
@staticmethod
def update_handler(update_object):
if type(update_object) is UpdateShortMessage:
if update_object.out:
sprint('You sent {} to user #{}'.format(
update_object.message, update_object.user_id))
else:
sprint('[User #{} sent {}]'.format(
update_object.user_id, update_object.message))
elif type(update_object) is UpdateShortChatMessage:
if update_object.out:
sprint('You sent {} to chat #{}'.format(
update_object.message, update_object.chat_id))
else:
sprint('[Chat #{}, user #{} sent {}]'.format(
update_object.chat_id, update_object.from_id,
update_object.message))
def is_user_authorized(self):
"""Has the user been authorized yet
(code request sent and confirmed)?"""
return self.session and self.get_me() is not None | [
"texcomvit@gmail.com"
] | texcomvit@gmail.com |
4055f10dac7cf16d7c8a1f438adc20a07457a099 | 910a96e87556ecba32a7651d3180744a89b0f96d | /sns/delete_all.py | 1997965b9bae5385f1c65d4eb2750b16282a6f30 | [] | no_license | fatalbert3390/aws-scripts | 1d9795057c1a206933c4a4361ab7ed3ced02aba8 | bc82c3c94020559460771f997e1ed61a7c8f71eb | refs/heads/master | 2021-10-09T00:40:05.187568 | 2021-09-29T01:36:20 | 2021-09-29T01:36:20 | 110,307,155 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,214 | py | # Deletes all SNS topics and subscriptions within the region specified in your AWS credentials file
import boto3
import json
snsc = boto3.client('sns')
snsr = boto3.resource('sns')
marker = None
print("Deleting SNS Topics...")
while True:
paginator = snsc.get_paginator('list_topics')
topic_iterator = paginator.paginate(
PaginationConfig={'StartingToken': marker}
)
for page in topic_iterator:
topiclist = page['Topics']
for topic in topiclist:
topicarn = topic['TopicArn']
print(topicarn)
snsr.Topic(arn=topicarn).delete()
try:
marker = page['NextToken']
except KeyError:
break
print("Deleting SNS Subscriptions...")
while True:
paginator = snsc.get_paginator('list_subscriptions')
topic_iterator = paginator.paginate(
PaginationConfig={'StartingToken': marker}
)
for page in topic_iterator:
sublist = page['Subscriptions']
for sub in sublist:
subarn = sub['SubscriptionArn']
print(subarn)
snsr.Subscription(arn=subarn).delete()
try:
marker = page['NextToken']
except KeyError:
break
| [
"fatalbert3390@gmail.com"
] | fatalbert3390@gmail.com |
b6676c3046daeabe4f56fe1d86aaca53449d0b3f | 6fe5f936a9dc2a046d2422df39c0d9d8cab70a73 | /examples/semantic_segmentation/vegas_buildings.py | 6300f44b1e70ba11ff5eb91b8728d43ff0983a9f | [
"Apache-2.0"
] | permissive | azavea/raster-vision-fastai-plugin | a5dc0e6c3121ef7a4572293b4ad415d74475a6c7 | 9d5bddcaa076e0b2c8e635ac8f2541a7be162c01 | refs/heads/master | 2020-04-25T04:38:03.268117 | 2019-10-03T16:24:07 | 2019-10-03T16:24:07 | 172,516,794 | 10 | 7 | NOASSERTION | 2019-10-03T16:24:08 | 2019-02-25T14:02:26 | Python | UTF-8 | Python | false | false | 5,449 | py | import re
import random
import os
from os.path import join
import rastervision as rv
from rastervision.utils.files import list_paths
from examples.utils import str_to_bool
from fastai_plugin.semantic_segmentation_backend_config import (
FASTAI_SEMANTIC_SEGMENTATION)
class VegasBuildings(rv.ExperimentSet):
def exp_main(self, raw_uri, root_uri, test=False):
"""Run an experiment on the Spacenet Vegas building dataset.
This is a simple example of how to do semantic segmentation on data that
doesn't require any pre-processing or special permission to access.
Args:
raw_uri: (str) directory of raw data (the root of the Spacenet dataset)
root_uri: (str) root directory for experiment output
test: (bool) if True, run a very small experiment as a test and generate
debug output
"""
base_uri = join(
raw_uri, 'SpaceNet_Buildings_Dataset_Round2/spacenetV2_Train/AOI_2_Vegas')
raster_uri = join(base_uri, 'RGB-PanSharpen')
label_uri = join(base_uri, 'geojson/buildings')
raster_fn_prefix = 'RGB-PanSharpen_AOI_2_Vegas_img'
label_fn_prefix = 'buildings_AOI_2_Vegas_img'
label_paths = list_paths(label_uri, ext='.geojson')
label_re = re.compile(r'.*{}(\d+)\.geojson'.format(label_fn_prefix))
scene_ids = [
label_re.match(label_path).group(1)
for label_path in label_paths]
random.seed(5678)
scene_ids = sorted(scene_ids)
random.shuffle(scene_ids)
# Workaround to handle scene 1000 missing on S3.
if '1000' in scene_ids:
scene_ids.remove('1000')
num_train_ids = int(len(scene_ids) * 0.8)
train_ids = scene_ids[0:num_train_ids]
val_ids = scene_ids[num_train_ids:]
test = str_to_bool(test)
exp_id = 'spacenet-simple-seg'
num_epochs = 5
batch_sz = 8
debug = False
chip_size = 300
if test:
exp_id += '-test'
num_epochs = 2
batch_sz = 1
debug = True
train_ids = ['12']
val_ids = ['13']
task = rv.TaskConfig.builder(rv.SEMANTIC_SEGMENTATION) \
.with_chip_size(chip_size) \
.with_classes({
'Building': (1, 'orange'),
'Background': (2, 'black')
}) \
.with_chip_options(
chips_per_scene=9,
debug_chip_probability=0.25,
negative_survival_probability=1.0,
target_classes=[1],
target_count_threshold=1000) \
.build()
config = {
'bs': batch_sz,
'num_epochs': num_epochs,
'debug': debug,
'lr': 1e-4
}
backend = rv.BackendConfig.builder(FASTAI_SEMANTIC_SEGMENTATION) \
.with_task(task) \
.with_config(config) \
.build()
def make_scene(id):
train_image_uri = os.path.join(raster_uri,
'{}{}.tif'.format(raster_fn_prefix, id))
raster_source = rv.RasterSourceConfig.builder(rv.RASTERIO_SOURCE) \
.with_uri(train_image_uri) \
.with_channel_order([0, 1, 2]) \
.with_stats_transformer() \
.build()
vector_source = os.path.join(
label_uri, '{}{}.geojson'.format(label_fn_prefix, id))
label_raster_source = rv.RasterSourceConfig.builder(rv.RASTERIZED_SOURCE) \
.with_vector_source(vector_source) \
.with_rasterizer_options(2) \
.build()
label_source = rv.LabelSourceConfig.builder(rv.SEMANTIC_SEGMENTATION) \
.with_raster_source(label_raster_source) \
.build()
scene = rv.SceneConfig.builder() \
.with_task(task) \
.with_id(id) \
.with_raster_source(raster_source) \
.with_label_source(label_source) \
.build()
return scene
train_scenes = [make_scene(id) for id in train_ids]
val_scenes = [make_scene(id) for id in val_ids]
dataset = rv.DatasetConfig.builder() \
.with_train_scenes(train_scenes) \
.with_validation_scenes(val_scenes) \
.build()
analyzer = rv.AnalyzerConfig.builder(rv.STATS_ANALYZER) \
.build()
# Need to use stats_analyzer because imagery is uint16.
experiment = rv.ExperimentConfig.builder() \
.with_id(exp_id) \
.with_task(task) \
.with_backend(backend) \
.with_analyzer(analyzer) \
.with_dataset(dataset) \
.with_root_uri(root_uri) \
.build()
return experiment
if __name__ == '__main__':
rv.main()
| [
"lewfish@gmail.com"
] | lewfish@gmail.com |
7e9a0b6709b5297f31d0f05bfe07068239bf488d | ec78c7d490ac00fbdc882a64b5964c38a46aa832 | /jobcrawler/tests/test_email/test_credentials.py | ca125a1803de94cd10c3b0226b09f18f238d2ee5 | [
"MIT"
] | permissive | amakus/JobCrawler | d7eb07211a2d63a2fca28420b1dc209d5bc920be | 770e05dd439ad3c269aeb3d7e284d891893faa2d | refs/heads/master | 2023-01-13T06:43:58.379482 | 2019-05-31T09:34:04 | 2019-05-31T09:34:04 | 186,671,549 | 0 | 0 | MIT | 2022-12-26T20:47:38 | 2019-05-14T17:43:26 | Python | UTF-8 | Python | false | false | 709 | py | import pytest
from jobcrawler.core.email.credentials import EmailCredentials
from jobcrawler.core.email.address import EmailAddress
def test_instantiation():
cred = EmailCredentials('fake@email.com', 'fake_password')
assert isinstance(cred, EmailCredentials)
def test_has_attribs():
cred = EmailCredentials('fake@email.com', 'fake_password')
assert cred[0] == 'fake@email.com'
assert str(cred.email) == 'fake@email.com'
assert isinstance(cred.email, EmailAddress)
assert cred[1] == 'fake_password'
assert cred.password == 'fake_password'
def test_get_domain():
cred = EmailCredentials('fake@email.com', 'fake_password')
assert cred.get_domain() == 'email.com'
| [
"makus.andreas@gmail.com"
] | makus.andreas@gmail.com |
0f98a96a0ec3a0a4ed1b0e2b524339cd85ec93a6 | 1b019365713488f6dde9a98323a3e58dd9668c1e | /venv/Scripts/easy_install-3.7-script.py | aaca6119b35a61c45a6babc98f14973f1e0eb13e | [] | no_license | mokshkori/GoScraper | 6dfc9bd779b3f20ba798c401331924dca4367642 | 6868bc7e49e8e2033d3df032002ab1c754595526 | refs/heads/master | 2023-03-17T23:17:54.051938 | 2021-03-05T19:38:00 | 2021-03-05T19:38:00 | 344,918,992 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 457 | py | #!C:\Users\user\PycharmProjects\Scraper\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')()
)
| [
"amankori8@gmail.com"
] | amankori8@gmail.com |
61e6fbf5047e592a14b13d26a3469559770c786f | 264fab7fdec5ed8be5f27ab4312b91d2b92a94bb | /Python/2020-04-12 1 hello.py | fb23b3a1f6dec9ae28d74c7fb72e1fe55eb76491 | [] | no_license | NguyenLeVo/cs50 | 9444042a2453c6f8051a358759ead48bd4c84caa | d746e38fb2963242ca51618859ca9c669ed11453 | refs/heads/master | 2022-11-10T14:02:15.576817 | 2020-06-28T20:04:27 | 2020-06-28T20:04:27 | 275,659,469 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,540 | py | # No printf
# No semicolon at the end
# No new line \n
# No stdio.h header
# No need to initialize the data type in the beginning
print("hello, world")
print("HELLO, WORLD")
# Compile by using command line python program.py
from cs50 import get_string
answer = get_string("What's your name?\n")
print("My name is " + answer)
print("Toi ten la", answer)
print(f"hello, {answer}")
# counter++ does not exist
counter = 0
counter += 1
# There's a colon
# No brackers
# No curly braces
# Must be indented (convention is 4 spaces)
# Else if turns into elif
from cs50 import get_int
x = get_int("x: ")
y = get_int("y: ")
if x < y:
print("x is less than y")
elif x > y:
print("x is more than y")
else:
print("x is equal to y")
# True and False are capitalized
# while True:
# print("Hello, World")
i = 3
while i > 0:
print("cough")
i -= 1
for j in [0, 1, 2]:
print("sneeze")
for k in range(5):
print("achoo")
# range: sequence of values
# list: an array with varying size and values
# tuple: sequence of immutable values
# dict: collection of key/value pairs a.k.a hash table
# set: collection of unique values
age = get_int("What's your age?\n")
print(f"You're at least {age * 365} days old.")
from cs50 import get_string
s = get_string("Do you agree?")
if s == "Y" or s == "y":
# if s in ["Y", "y", "Yes", "yes"]:
# if s.lower() in ["y", "yes"]
print("Agreed.")
elif s == "N" or s == "n":
print("Not agreed.")
# No pointers, no seg fault, no null pointers
# No main function, just write
| [
"NguyenLeVo@github.com"
] | NguyenLeVo@github.com |
5ac4cc41638f10eed1a2459afdb105e0eeb840a7 | 3543acbb63a1d2937fc01a3450307e761ebfa958 | /Get Retroativo/2019_09_1.py | 2830de7ac363610f0bf3a642596e10343da7db02 | [] | no_license | paulowiz/AiesecBot | 4c65b6b647022e52d5627c8754c6b7b9e59f77f4 | ac77cc5426ed6382772603afa8015208020c0fba | refs/heads/master | 2021-06-23T10:24:56.346717 | 2021-04-29T15:45:09 | 2021-04-29T15:45:09 | 205,560,472 | 7 | 3 | null | 2021-04-29T15:45:10 | 2019-08-31T15:15:09 | Python | UTF-8 | Python | false | false | 727 | py | import psycopg2.extras
from controller import RobotRotine as rr
from api import graphqlconsume, querygraphql
import time
import datetime
import numpy as np
"""
current = np.datetime64(datetime.datetime.now())
currentab = np.datetime64(current) + np.timedelta64(5, 'h')
lastdate = np.datetime64(currentab) - np.timedelta64(15, 'm')
print(lastdate)
print(currentab)
print('-')
"""
robo2 = rr.RobotRotine()
i = 0
dtinit = '2019-09-01T00:00:00'
while i < 18:
print(dtinit)
dtfim = np.datetime64(dtinit) + np.timedelta64(24, 'h')
robo2.ExecutaRotina('created_at', dtinit,
dtfim, 1)
i = i+1
dtinit = np.datetime64(dtinit) + np.timedelta64(24, 'h')
print('Periodo Executado com sucesso')
| [
"paaulowiz@gmail.com"
] | paaulowiz@gmail.com |
0bc6fac376c78cf19cc1bf4bbe11506fe6430f5b | 7773ea6f465ffecfd4f9821aad56ee1eab90d97a | /python/testData/refactoring/move/baseClass/after/src/b.py | a419aaecfd4124f2c9a10e105133c1939a3caaeb | [
"Apache-2.0"
] | permissive | aghasyedbilal/intellij-community | 5fa14a8bb62a037c0d2764fb172e8109a3db471f | fa602b2874ea4eb59442f9937b952dcb55910b6e | refs/heads/master | 2023-04-10T20:55:27.988445 | 2020-05-03T22:00:26 | 2020-05-03T22:26:23 | 261,074,802 | 2 | 0 | Apache-2.0 | 2020-05-04T03:48:36 | 2020-05-04T03:48:35 | null | UTF-8 | Python | false | false | 53 | py | class B(object):
def __init__(self):
pass | [
"andrey.vlasovskikh@jetbrains.com"
] | andrey.vlasovskikh@jetbrains.com |
6dc812eda48a50de1b9bf0965304ca544568e789 | ca2db9fb6820518901563aca4248ee48a06538ca | /data/scripts/kaist_create_imageset.py | b94e253153a9d06cfddf1254d81c16b0cfff07ee | [
"MIT"
] | permissive | valentinpy/ssd.pytorch | fadaf941147944b8e829f9fd63a4ef0e9a84b8a3 | 83b0d39aaabede38c3e836a0bd44a42f85113dea | refs/heads/master | 2020-04-07T23:26:31.057688 | 2019-01-10T13:28:31 | 2019-01-10T13:28:31 | 158,812,782 | 0 | 0 | null | 2018-11-23T09:49:00 | 2018-11-23T09:49:00 | null | UTF-8 | Python | false | false | 6,802 | py | import sys
import os
from glob import glob
import argparse
import random
from tqdm import tqdm
def str2bool(v):
return v.lower() in ("yes", "true", "t", "1")
def main():
args = arg_parser()
argcheck(args)
parse_annotations(args)
def arg_parser():
parser = argparse.ArgumentParser(description='Script to generate imageSet files for kaist')
parser.add_argument('--dataset_root', default="/home/valentinpy/data/kaist",
help='Dataset root directory path')
parser.add_argument('--output_file', default=None,
help='Output file name')
parser.add_argument('--output_folder', default="/home/valentinpy/data/kaist/rgbt-ped-detection/data/kaist-rgbt/imageSets/",
help='Output folder')
parser.add_argument('--use_set00_01_02', default=False, type=str2bool,
help='Use set00_01_02')
parser.add_argument('--use_set03_04_05', default=False, type=str2bool,
help='Use set03_04_05')
parser.add_argument('--use_set06_07_08', default=False, type=str2bool,
help='Use set06_07_08')
parser.add_argument('--use_set09_10_11', default=False, type=str2bool,
help='Use set09_10_11')
parser.add_argument('--only_person', default=False, type=str2bool,
help="Filter out images which do not contain exclusively 'person'")
parser.add_argument('--min_annotation_height', default=-1, type=int,
help='Filter out images with annotation smaller as specified [px]')
parser.add_argument('--remove_occlusions', default=False, type=str2bool,
help='Remove images with occlusions')
parser.add_argument('--remove_no_person_annotations', default=True, type=str2bool,
help='Remove images without person annoations')
parser.add_argument('--max_images', default=-1, type=int,
help='Max number of images [-1: unlimited]')
args = parser.parse_args()
return args
def argcheck(args):
if not os.path.exists(args.dataset_root):
print("dataset not found!")
sys.exit(-1)
if not os.path.exists(args.output_folder):
os.makedirs(args.output_folder)
print("output folder not found, creating it")
set_used = 0
if args.use_set00_01_02:
set_used+=1
if args.use_set03_04_05:
set_used+=1
if args.use_set06_07_08:
set_used+=1
if args.use_set09_10_11:
set_used+=1
if (set_used > 2) or (set_used == 0):
print("only one or 2 set can be chosen at a time")
sys.exit(-1)
if args.max_images == -1:
args.max_images = sys.maxsize
def filter(annofilename, args):
# flags
keep_file = False
person_detected = False
people_detected = False
person_not_sure_detected = False
cyclist_detected = False
only_person_detected = False
occlusion_detected = False
too_small = False
with open(annofilename) as annofile:
for annoline in annofile: # loop for each line of each annofile
if not annoline.startswith("%"): # if not a comment
# split annotation lines
annosplit = annoline.split(" ")
if len(annosplit) > 5:
# for each file, exact flags
if annosplit[0] == 'person': # only keep images which contains a "person"
person_detected = True
elif annosplit[0] == 'people':
people_detected = True
elif annosplit[0] == 'person?':
person_not_sure_detected = True
elif annosplit[0] == 'cyclist':
cyclist_detected = True
else:
print("Annotation not recognized!")
sys.exit(-1)
#print(annosplit[5])
if int(annosplit[5]) != 0:
occlusion_detected = True
if int(annosplit[4]) < args.min_annotation_height:
too_small = True
if (person_detected) and (not person_not_sure_detected) and (not people_detected) and (not cyclist_detected):
only_person_detected = True
#use args filter to cancel useless excluding flags
if not args.only_person:
only_person_detected = True
if not args.remove_occlusions:
occlusion_detected = False
if args.min_annotation_height == -1:
too_small = False
if not args.remove_no_person_annotations:
person_detected = True
# according to flags, do we keep this entry ?
keep_file = only_person_detected and (not occlusion_detected) and (not too_small) and person_detected
return keep_file
def parse_annotations(args):
i=0
# get all annotation files in the sets (set 0-2 or set 6-8)
annotations_folder = os.path.join(args.dataset_root, 'rgbt-ped-detection/data/kaist-rgbt/annotations')
annotation_files_all = [y for x in os.walk(annotations_folder) for y in glob(os.path.join(x[0], '*.txt'))]
annotation_files=[]
if args.use_set00_01_02:
annotation_files += [x for x in annotation_files_all if (("set00" in x) or ("set01" in x) or ("set02" in x))] #train day
if args.use_set03_04_05:
annotation_files += [x for x in annotation_files_all if (("set03" in x) or ("set04" in x) or ("set05" in x))] # train night
if args.use_set06_07_08:
annotation_files += [x for x in annotation_files_all if (("set06" in x) or ("set07" in x) or ("set08" in x))] #test day
if args.use_set09_10_11:
annotation_files += [x for x in annotation_files_all if (("set09" in x) or ("set10" in x) or ("set11" in x))] #test night
# randomize data:
random.shuffle(annotation_files)
#open output imageSet file
with open(os.path.join(args.output_folder, args.output_file), "w") as imageset_file:
imageset_file.write("# ImageSet automatically generated by 'kaist_create_imageset.py' " + repr(args) + "\n")
for annofilename in tqdm(annotation_files):
if filter(annofilename, args) and (i < args.max_images):
newline = "{}/{}/{}\n".format((annofilename.split('/'))[-3], (annofilename.split('/'))[-2], (annofilename.split('/'))[-1].split('.')[0])
imageset_file.write(newline) # todo output syntax
i+= 1
print("Finished\nnumber of files kept: {}/{}\nOutput file is {}".format(i, len(annotation_files), os.path.join(args.output_folder, args.output_file)))
if __name__ == '__main__':
main()
| [
"valentin.py@he-arc.ch"
] | valentin.py@he-arc.ch |
44b2c60ff20035d37c7405ee7363aa19197aadd2 | 9733cd153ac6e730195e49e95aa01179cc31c981 | /sources/exceptions.py | a0b5c8610b7e8526d9792e17e31b11f724f46756 | [] | no_license | karan-parekh/Real-MVP | 9044c99e5eef44582c5f2e48004f62ec881b0396 | 9f49a9cb5b0a5295b1c3c73f7dfdc1c8e3332eca | refs/heads/master | 2023-03-15T01:05:23.960994 | 2021-03-09T07:29:02 | 2021-03-09T07:29:02 | 315,059,677 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 498 | py |
class GamesDBException(Exception):
"""Raised for any exceptions in GlowDB class"""
class TableException(GamesDBException):
"""Raised for any exceptions in querying table"""
class NoDatabaseFound(GamesDBException):
"""Raised when required DB is not found or does not exist"""
class DataCorruptedError(GamesDBException):
"""Raised when the data in glow DB is corrupted"""
class CacheManagerException(Exception):
"""Raised for any exception in cache manager operations"""
| [
"karanparekh501@gmail.com"
] | karanparekh501@gmail.com |
771047b585320da01e44965a322ee1f714dff6d2 | 1e43db349ceff56894a40649dead760f0c071194 | /William_Benhaim/Lesson1/google-python-exercises/basic/list1.py | 214a750b28e812f6c6b3cf298bc94cbf45f73b35 | [
"Apache-2.0"
] | permissive | rachidalili/MS-BGD2015 | f632cb9fb1230e8e9b7bcaa63f779d1773e02212 | fcfece0072d6e9468a91345257d55b812f5755ba | refs/heads/master | 2021-01-10T04:50:48.317342 | 2015-12-16T19:53:11 | 2015-12-16T19:53:11 | 43,893,310 | 10 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,242 | py | #!/usr/bin/python -tt
# Copyright 2010 Google Inc.
# Licensed under the Apache License, Version 2.0
# http://www.apache.org/licenses/LICENSE-2.0
# Google's Python Class
# http://code.google.com/edu/languages/google-python-class/
# Basic list exercises
# Fill in the code for the functions below. main() is already set up
# to call the functions with a few different inputs,
# printing 'OK' when each function is correct.
# The starter code for each function includes a 'return'
# which is just a placeholder for your code.
# It's ok if you do not complete all the functions, and there
# are some additional functions to try in list2.py.
# A. match_ends
# Given a list of strings, return the count of the number of
# strings where the string length is 2 or more and the first
# and last chars of the string are the same.
# Note: python does not have a ++ operator, but += works.
def match_ends(words):
# +++your code herse+++
cpt=0
for i in words:
if len(i)>=2 and i[0]==i[-1]: #i[:1]==i[len(i)-1:]:
cpt=cpt+1
return cpt
# B. front_x
# Given a list of strings, return a list with the strings
# in sorted order, except group all the strings that begin with 'x' first.
# e.g. ['mix', 'xyz', 'apple', 'xanadu', 'aardvark'] yields
# ['xanadu', 'xyz', 'aardvark', 'apple', 'mix']
# Hint: this can be done by making 2 lists and sorting each of them
# before combining them.
def front_x(words):
WithX=[]
toSort=[]
for mot in words:
if mot[0]=='x':
WithX.append(mot)
else:
toSort.append(mot)
#WithX.sort()
#toSort.sort()
# +++your code here+++
return sorted(WithX)+sorted(toSort)
# C. sort_last
# Given a list of non-empty tuples, return a list sorted in increasing
# order by the last element in each tuple.
# e.g. [(1, 7), (1, 3), (3, 4, 5), (2, 2)] yields
# [(2, 2), (1, 3), (3, 4, 5), (1, 7)]
# Hint: use a custom key= function to extract the last element form each tuple.
def sort_last(tuples):
# +++your code here+
return sorted(tuples,key=last)
def last(a):
return a[-1]
# Simple provided test() function used in main() to print
# what each function returns vs. what it's supposed to return.
def test(got, expected):
if got == expected:
prefix = ' OK '
else:
prefix = ' X '
print '%s got: %s expected: %s' % (prefix, repr(got), repr(expected))
# Calls the above functions with interesting inputs.
def main():
print 'match_ends'
test(match_ends(['aba', 'xyz', 'aa', 'x', 'bbb']), 3)
test(match_ends(['', 'x', 'xy', 'xyx', 'xx']), 2)
test(match_ends(['aaa', 'be', 'abc', 'hello']), 1)
print
print 'front_x'
test(front_x(['bbb', 'ccc', 'axx', 'xzz', 'xaa']),
['xaa', 'xzz', 'axx', 'bbb', 'ccc'])
test(front_x(['ccc', 'bbb', 'aaa', 'xcc', 'xaa']),
['xaa', 'xcc', 'aaa', 'bbb', 'ccc'])
test(front_x(['mix', 'xyz', 'apple', 'xanadu', 'aardvark']),
['xanadu', 'xyz', 'aardvark', 'apple', 'mix'])
print
print 'sort_last'
test(sort_last([(1, 3), (3, 2), (2, 1)]),
[(2, 1), (3, 2), (1, 3)])
test(sort_last([(2, 3), (1, 2), (3, 1)]),
[(3, 1), (1, 2), (2, 3)])
test(sort_last([(1, 7), (1, 3), (3, 4, 5), (2, 2)]),
[(2, 2), (1, 3), (3, 4, 5), (1, 7)])
if __name__ == '__main__':
main()
| [
"william.benhaim@gmail.com"
] | william.benhaim@gmail.com |
ac5e2d784a9dfdee17e38a480d65a902105efcdb | b37b3cdf08661c4af1b15c1ce2af7cd1e21bcb8c | /chatbot/hello.py | 6056c61ef6ea9753099120cac636eeab7d1b4bb3 | [] | no_license | KimSoomae/startcamp | 1304c788a2c20d975447fca5b2ec52cf0f3fecae | 2534a49e026d72ab9f1b3da1ddacb7b1dd125160 | refs/heads/master | 2023-06-18T00:51:56.822301 | 2021-07-16T08:36:24 | 2021-07-16T08:36:24 | 386,164,560 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 447 | py | import requests
from bs4 import BeautifulSoup
url = 'https://finance.naver.com/sise/'
response = requests.get(url)
data = BeautifulSoup(response.text,"lxml")
print(data.select_one('#KOSPI_now'))
print(data.select_one('#KOSPI_now').text)
url='https://finance.naver.com/marketindex/'
response = requests.get(url)
data = BeautifulSoup(response.text,"lxml")
print(data.select_one('#exchangeList > li.on > a.head.usd > div > span.value').text)
| [
"smkim104@naver.com"
] | smkim104@naver.com |
cba21703e801f82942b333795e93c5e77e85476a | 7d33fd0dc6a0d02b5d7cc41fb78d146045f7b58a | /tests/examples/holaMundo.py | 3f8f6324b4964adc1984daf125a74ca812e84aa9 | [
"Apache-2.0",
"MIT"
] | permissive | evhub/cpyparsing | 058e253892ba25136c731167cea9997925d153fc | 2e75cbbfce7953bcde79bede8d47d31dd3511b15 | refs/heads/master | 2023-08-13T04:28:20.372777 | 2023-08-03T05:42:39 | 2023-08-03T05:42:39 | 96,247,649 | 26 | 3 | NOASSERTION | 2023-04-04T20:46:47 | 2017-07-04T19:29:13 | Python | UTF-8 | Python | false | false | 1,862 | py | # -*- coding: utf-8 -*-
# escrito por Marco Alfonso, 2004 Noviembre
# importamos los símbolos requeridos desde el módulo
from pyparsing import Word, alphas, oneOf, nums, Group, OneOrMore, pyparsing_unicode as ppu
# usamos las letras en latin1, que incluye las como 'ñ', 'á', 'é', etc.
alphas = ppu.Latin1.alphas
# Aqui decimos que la gramatica "saludo" DEBE contener
# una palabra compuesta de caracteres alfanumericos
# (Word(alphas)) mas una ',' mas otra palabra alfanumerica,
# mas '!' y esos seian nuestros tokens
saludo = Word(alphas) + ',' + Word(alphas) + oneOf('! . ?')
tokens = saludo.parseString("Hola, Mundo !")
# Ahora parseamos una cadena, "Hola, Mundo!",
# el metodo parseString, nos devuelve una lista con los tokens
# encontrados, en caso de no haber errores...
for i, token in enumerate(tokens):
print ("Token %d -> %s" % (i,token))
#imprimimos cada uno de los tokens Y listooo!!, he aquí a salida
# Token 0 -> Hola
# Token 1 -> ,
# Token 2-> Mundo
# Token 3 -> !
# ahora cambia el parseador, aceptando saludos con mas que una sola palabra antes que ','
saludo = Group(OneOrMore(Word(alphas))) + ',' + Word(alphas) + oneOf('! . ?')
tokens = saludo.parseString("Hasta mañana, Mundo !")
for i, token in enumerate(tokens):
print ("Token %d -> %s" % (i,token))
# Ahora parseamos algunas cadenas, usando el metodo runTests
saludo.runTests("""\
Hola, Mundo!
Hasta mañana, Mundo !
""", fullDump=False)
# Por supuesto, se pueden "reutilizar" gramáticas, por ejemplo:
numimag = Word(nums) + 'i'
numreal = Word(nums)
numcomplex = numreal + '+' + numimag
print (numcomplex.parseString("3+5i"))
# Cambiar a complejo numero durante parsear:
numcomplex.setParseAction(lambda t: complex(''.join(t).replace('i','j')))
print (numcomplex.parseString("3+5i"))
# Excelente!!, bueno, los dejo, me voy a seguir tirando código...
| [
"evanjhub@gmail.com"
] | evanjhub@gmail.com |
5c3ae03b9640d3b682ce95308e9ab6fd216b2950 | c56b3f86b47ed7c484a45a7aad71c5ba59bb2b59 | /plots/GPU_Usage.py | 6419d66759714b84eeb8353fa67c56d8fdb02a68 | [] | no_license | gvsam7/Deep_Archs | d9ee23907fac2dbb1830fcc49f042d612361f70c | 36f9e2b9b4f0376fde43db2f342fadb31e5c3041 | refs/heads/master | 2023-03-21T22:44:31.100512 | 2021-03-18T11:37:30 | 2021-03-18T11:37:30 | 331,377,984 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,666 | py | """
Author: Georgios Voulgaris
Date: 07_12_2020
Description: Plots GPU power consumption, time running and architecture on average of 5 runs.
"""
import matplotlib as mpl
import matplotlib.pyplot as plt
# agg backend is used to create plot as a .png file
mpl.use('agg')
pwr = [68.11, 71.394, 75.14,
108.03, 140.51, 149.96,
134.68, 71.12,
138.57, 113.47,
69.31, 108.63, 121.01]
time = [1.704, 6.532, 43.37,
1.148, 5.05, 21.48,
4.97, 37.82,
15.83, 47.67,
19.24, 42.44, 145.92]
arch = ['3_CNN_50', '3_CNN_100', '3_CNN_226',
'4_CNN_50', '4_CNN_100', '4_CNN_226',
'5_CNN_100', '5_CNN_226',
'AlexNet_50', 'AlexNet_100',
'VGG16_50', 'VGG16_100', 'VGG16_226']
# labels = ['3_CNN', '4_CNN', '5_CNN', 'AlexNet', 'VGG_16']
fig, ax = plt.subplots(figsize=(10, 10))
ax.scatter(time, pwr, c='r', marker='x', s=35)
for i, txt in enumerate(arch):
ax.annotate(txt, (time[i], pwr[i]), xytext=(5, 5), textcoords='offset points')
# plt.scatter(time, pwr, marker='x', color='red')
# Custom axis labels
ax.set_axisbelow(True)
# ax.legend(labels, loc='upper right', shadow=True)
ax.set_title('GPU Power Consumption', fontsize=18)
ax.set_xlabel('Time (minutes)', fontsize=14)
ax.set_ylabel('Power (watts)', fontsize=14)
# Add a horizontal grid to the plot, but make it very light in colour
# thus, assist when reading data values but not too distracting
ax.yaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)
ax.xaxis.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5)
# Save the figure
fig.savefig('GPU_Usage.png', bbox_inches='tight')
| [
"gvsam7@yahoo.com"
] | gvsam7@yahoo.com |
850cbbbb722ba4da64e22ce34e31701260693140 | d3494e686eb8840a93656f8823a36c2d3c3f9bf2 | /Binary Tree Longest Consecutive Sequence.py | c3d95243584dc27862a65353f00d037593ff4e9b | [] | no_license | YihaoGuo2018/leetcode_python_version2 | a5e33d539f0f59d1edd5ba8eaa3608965b55ebb6 | 7175d2e21d6c02ebd5940171c2fcf5db06efbdcf | refs/heads/main | 2023-02-16T17:41:32.562747 | 2021-01-14T15:49:27 | 2021-01-14T15:49:27 | 329,659,625 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 685 | py | # Definition for a binary tree node.
# class TreeNode(object):
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
class Solution(object):
def longestConsecutive(self, root):
if not root:
return 0
ret = 0
stack = [(root, 1)]
while stack:
node, cnt = stack.pop()
if node.left:
stack.append((node.left, cnt+1 if node.left.val == node.val + 1 else 1))
if node.right:
stack.append((node.right, cnt+1 if node.right.val == node.val + 1 else 1))
ret = max(ret, cnt)
return ret | [
"noreply@github.com"
] | YihaoGuo2018.noreply@github.com |
74a45ecd5fae6f7e270fb57144ad3d822d18aa47 | 557ca4eae50206ecb8b19639cab249cb2d376f30 | /Chapter19/GoodKangaroo.py | 426380428c484dacacb2bde125fde2a76cdb3263 | [] | no_license | philipdongfei/Think-python-2nd | 781846f455155245e7e82900ea002f1cf490c43f | 56e2355b8d5b34ffcee61b38fbfd200fd6d4ffaf | refs/heads/master | 2021-01-09T19:57:49.658680 | 2020-03-13T06:32:11 | 2020-03-13T06:32:11 | 242,441,512 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,866 | py | """This module contains a code example related to
Think Python, 2nd Edition
by Allen Downey
http://thinkpython2.com
Copyright 2015 Allen Downey
License: http://creativecommons.org/licenses/by/4.0/
"""
from __future__ import print_function, division
"""
WARNING: this program contains a NASTY bug. I put
it there on purpose as a debugging exercise, but
you DO NOT want to emulate this example!
"""
class Kangaroo:
"""A Kangaroo is a marsupial."""
def __init__(self, name, contents=[]):
"""Initialize the pouch contents.
name: string
contents: initial pouch contents.
"""
# The problem is the default value for contents.
# Default values get evaluated ONCE, when the function
# is defined; they don't get evaluated again when the
# function is called.
# In this case that means that when __init__ is defined,
# [] gets evaluated and contents gets a reference to
# an empty list.
# After that, every Kangaroo that gets the default
# value gets a reference to THE SAME list. If any
# Kangaroo modifies this shared list, they all see
# the change.
# The next version of __init__ shows an idiomatic way
# to avoid this problem.
self.name = name
self.pouch_contents = contents
def __init__(self, name, contents=None):
"""Initialize the pouch contents.
name: string
contents: initial pouch contents.
"""
# In this version, the default value is None. When
# __init__ runs, it checks the value of contents and,
# if necessary, creates a new empty list. That way,
# every Kangaroo that gets the default value gets a
# reference to a different list.
# As a general rule, you should avoid using a mutable
# object as a default value, unless you really know
# what you are doing.
self.name = name
self.pouch_contents = [] if contents == None else contents
'''
if contents == None:
contents = []
self.pouch_contents = contents
'''
def __str__(self):
"""Return a string representaion of this Kangaroo.
"""
t = [ self.name + ' has pouch contents:' ]
for obj in self.pouch_contents:
s = ' ' + object.__str__(obj)
t.append(s)
return '\n'.join(t)
def put_in_pouch(self, item):
"""Adds a new item to the pouch contents.
item: object to be added
"""
self.pouch_contents.append(item)
kanga = Kangaroo('Kanga')
roo = Kangaroo('Roo')
kanga.put_in_pouch('wallet')
kanga.put_in_pouch('car keys')
kanga.put_in_pouch(roo)
print(kanga)
print(roo)
# If you run this program as is, it seems to work.
# To see the problem, trying printing roo.
| [
"philip.dongfei@gmail.com"
] | philip.dongfei@gmail.com |
c0d57458ea3699f7e6e91a07615e041a9fae5389 | a5a99f646e371b45974a6fb6ccc06b0a674818f2 | /Configuration/Generator/python/Pyquen_DiJet_pt80to120_5362GeV_cfi.py | f7adf91a210cf47dceaaf93f339c20b713d13040 | [
"Apache-2.0"
] | permissive | cms-sw/cmssw | 4ecd2c1105d59c66d385551230542c6615b9ab58 | 19c178740257eb48367778593da55dcad08b7a4f | refs/heads/master | 2023-08-23T21:57:42.491143 | 2023-08-22T20:22:40 | 2023-08-22T20:22:40 | 10,969,551 | 1,006 | 3,696 | Apache-2.0 | 2023-09-14T19:14:28 | 2013-06-26T14:09:07 | C++ | UTF-8 | Python | false | false | 1,689 | py | import FWCore.ParameterSet.Config as cms
from Configuration.Generator.PyquenDefaultSettings_cff import *
generator = cms.EDFilter("PyquenGeneratorFilter",
collisionParameters5362GeV,
qgpParameters,
pyquenParameters,
doQuench = cms.bool(True),
bFixed = cms.double(0.0), ## fixed impact param (fm); valid only if cflag_=0
PythiaParameters = cms.PSet(pyquenPythiaDefaultBlock,
parameterSets = cms.vstring('pythiaUESettings','ppJets','kinematics'),
kinematics = cms.vstring ("CKIN(3)=80", #min pthat
"CKIN(4)=120" #max pthat
)
),
cFlag = cms.int32(0), ## centrality flag
bMin = cms.double(0.0), ## min impact param (fm); valid only if cflag_!=0
bMax = cms.double(0.0) ## max impact param (fm); valid only if cflag_!=0
)
configurationMetadata = cms.untracked.PSet(
version = cms.untracked.string('$Revision: 1.2 $'),
name = cms.untracked.string('$Source: /local/projects/CMSSW/rep/CMSSW/Configuration/Generator/python/Pyquen_DiJet_pt80to120_2760GeV_cfi.py,v $'),
annotation = cms.untracked.string('PYQUEN quenched dijets (80 < pt-hat < 120 GeV) at sqrt(s) = 2.76TeV')
)
ProductionFilterSequence = cms.Sequence(generator)
| [
"Matthew.Nguyen@cern.ch"
] | Matthew.Nguyen@cern.ch |
0b7288e059b106300fa116661afafe661bc39e04 | e5e045a5bf3aa621a82c84f01db002d74d5d4b37 | /Code.py | 7050f7e4c4b892a24ea0fb3c90a6f8a0ed58807c | [] | no_license | LakshayMahajan2006/Snake-Game-with-python | 09cddb687451bde6633453f08a1d2a8ce891606d | bf18f4a1d8bdb72dff670d2b7329c905005f546e | refs/heads/master | 2022-12-05T16:07:45.098317 | 2020-08-26T08:34:46 | 2020-08-26T08:34:46 | 290,441,402 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,239 | py | # Snake-Game-with-python
import some modules
from turtle import *
from random import randrange
from freegames import square, vector
food = vector(0, 0)
snake = [vector(10, 0)]
aim = vector(0, -10)
print("Snake: 1")
def change(x, y):
"Change snake direction."
aim.x = x
aim.y = y
def inside(head):
"Return True if head inside boundaries."
return -200 < head.x < 190 and -200 < head.y < 190
def move():
"Move snake forward one segment."
head = snake[-1].copy()
head.move(aim)
if not inside(head) or head in snake:
square(head.x, head.y, 9, 'black')
update()
return
snake.append(head)
if head == food:
print('Snake:', len(snake))
food.x = randrange(-15, 15) * 10
food.y = randrange(-15, 15) * 10
else:
snake.pop(0)
clear()
for body in snake:
square(body.x, body.y, 9, 'green')
square(food.x, food.y, 9, 'blue')
update()
ontimer(move, 100)
setup(420, 420, 370, 0)
hideturtle()
tracer(False)
listen()
onkey(lambda: change(10, 0), 'Right')
onkey(lambda: change(-10, 0), 'Left')
onkey(lambda: change(0, 10), 'Up')
onkey(lambda: change(0, -10), 'Down')
move()
done()
print("Total Score : ", len(snake))
| [
"noreply@github.com"
] | LakshayMahajan2006.noreply@github.com |
deeb80c34042bc5788cbd500180b53981b2cb319 | 0d3d30124b5574d95d46908ede1c2046a28f5842 | /pythonCode/workspace/Study/src/PythonCore/11/11_10.py | ad81a28a4a316a28a2817833e7660bd527f0d835 | [] | no_license | fangyue6/MyPythonCode | 22a36a75c56b09055a24eddb85636165fcb63a9d | bebc7b498e6d0a73672df67bf4a6aa909e6628fe | refs/heads/master | 2021-06-05T21:18:24.387566 | 2018-08-21T12:26:25 | 2018-08-21T12:26:25 | 94,972,353 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 438 | py | #!/usr/bin/python
# -*- coding: UTF-8 -*-
'''
Created on 2015年4月13日
@author: fangyue
'''
'''11.10.1.简单的生成器特性'''
def ok():
return 11
def simpleGen():
yield 1
yield '2 --> punch!'
yield ok()
myG=simpleGen()
print myG.next()
print myG.next()
print myG.next()
s='''使用一个for 循环而不是手动迭代穿过一个生成器'''
print s
for eachItem in simpleGen():
print eachItem
| [
"yue.fang.ser"
] | yue.fang.ser |
0de192121d0073ff9cf6c8f5849e838274995ac2 | 890fed1df11cebccbf1944181637661455127d62 | /rozwiazania/Darek/main.py | 3968b806364d46826bd86c70bf240173f6c12b78 | [] | no_license | ArchangelDesign/mapa-gestosci | 22621cc1d376136ecf7b31eed34344d008e9f152 | 3242ef6664e4d0acc6c0e81e0a02ef4e66e222e2 | refs/heads/master | 2021-05-03T15:14:17.658232 | 2018-02-06T14:50:19 | 2018-02-06T14:50:19 | 120,472,526 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,074 | py | # EXAMPLE INPUT
# 10,20,30,40,50,60,
# 70,80,90,100,110,120,
# 1,2,3,4,5,6,
# 7,8,9,10,11,12,
def sum_neighbours(data, idx):
return data[idx] \
+ (data[idx - 1] if idx > 0 else 0) \
+ (data[idx + 1] if idx + 1 < len(data) else 0)
def main():
sum_all = 0
with open("input.txt", 'r') as input_file, \
open("output.txt", 'w') as output_file:
content = input_file.readlines()
data = [map(int, line.strip().split(',')) for line in content]
for row_num in range(0, len(data)):
for col_num in range(0, len(data[row_num])):
sum = (sum_neighbours(data[row_num - 1], col_num) if row_num > 0 else 0) \
+ (sum_neighbours(data[row_num], col_num)) \
+ (sum_neighbours(data[row_num + 1], col_num) if row_num + 1 < len(data) else 0)
sum_all = sum_all + sum
output_file.write("{0},".format(sum))
output_file.write('\n')
print sum_all
if __name__ == "__main__":
main()
| [
"archangel.raffael@gmail.com"
] | archangel.raffael@gmail.com |
ff6e44311140d54e21fc24318072d6e3878b875c | 610bd6ec46a9ccf04bb697bbcf0f631a3813f88b | /archived/preprocess/data.py | 6d86a29c69702c43163ff7ccc324bd65ec90f374 | [] | no_license | qibinc/Lyrics | e5e998eedac14887b8231c1887175682b8e9c1d3 | 851be102f90398a3f65cb302b94eb32844f6787e | refs/heads/master | 2021-03-27T11:35:53.289835 | 2018-01-06T04:35:12 | 2018-01-06T04:35:12 | 107,003,712 | 5 | 1 | null | null | null | null | UTF-8 | Python | false | false | 4,670 | py |
# coding: utf-8
# In[8]:
import re
import pickle
import numpy as np
import preprocess
# In[9]:
limit = {
'minq': 0,
'maxq': 20,
'mina': 2,
'maxa': 20
}
UNK = 'unk'
# In[10]:
def load_raw_data():
"""Return titles and lyrics."""
titles_lyrics = preprocess.load_from_pickle()
if titles_lyrics == None:
preprocess.preprocess()
titles_lyrics = preprocess.load_from_pickle()
return titles_lyrics
# In[11]:
def lyrics_without_timing():
"""Return a list of lyrics, pure text, no timing"""
_, lyrics = load_raw_data()
# del_timing = lambda s: re.sub('\[.*\]', '', s).strip()
# lyrics = [[del_timing(sentence) for sentence in lyric if del_timing(sentence) != '']\
# for lyric in lyrics]
del_not_chinese = lambda s: re.sub(u'[^\u4E00-\u9FA5 ]', '', s).strip()
lyrics = [[del_not_chinese(sentence) for sentence in lyric if del_not_chinese(sentence) != ''] for lyric in lyrics]
lyrics = [[sentence for sentence in lyric
if '作词' not in sentence and '作曲' not in sentence\
and '编曲' not in sentence and '词曲' not in sentence\
]for lyric in lyrics]
lyrics = [lyric for lyric in lyrics if len(lyric) > 15]
return lyrics
# In[12]:
def q_a_lines(lyrics):
"""2 lists of sentences. Question and answer, respectively."""
q, a = [], []
ori_len = 0
for lyric in lyrics:
ori_len += len(lyric)
for i in range(len(lyric) - 1):
qlen, alen = len(lyric[i]), len(lyric[i+1])
if qlen >= limit['minq'] and qlen <= limit['maxq'] and alen >= limit['mina'] and alen <= limit['maxa']:
q.append(lyric[i])
a.append(lyric[i+1])
print('Q & A filtered {0}%'.format(100*(ori_len - len(q))/ori_len))
return q, a
# In[13]:
def tokenize_single(qlines, alines):
"""Transfrom lines into lists of single characters.
To do: tokenize_word
"""
qtokenized = [[character for character in sentence] for sentence in qlines]
atokenized = [[character for character in sentence] for sentence in alines]
return qtokenized, atokenized
# In[14]:
def character_frequency(lyrics, vocab_size=3000, show=False):
"""Analyze Characters frequence.
In a list of list of sentences.
Example: [["song1", "hello world", "end"], ["song2", "happy end"]]
"""
import numpy as np
import itertools
from collections import Counter, defaultdict
iter_characters = itertools.chain(*itertools.chain(*lyrics))
frequency_list = Counter(iter_characters).most_common()
character, freq = zip(*frequency_list)
if show:
import matplotlib.pyplot as plt
get_ipython().magic('matplotlib inline')
plt.ylabel('frequency(log)')
plt.xlabel('rank')
plt.plot(range(len(frequency_list)), np.log(freq))
plt.show()
print('100 Most frequent word: {0}'.format(word[:100]))
return list(character[:vocab_size]), list(freq[:vocab_size])
# In[15]:
def index(tokenized, vocab_size=3000):
"""Make volcabulary and lookup dictionary"""
word, freq = character_frequency(tokenized, vocab_size)
index2word = ['_', UNK] + word
word2index = dict([(w, i) for i, w in enumerate(index2word)])
return index2word, word2index
# In[16]:
def pad_seq(line, w2idx, maxlen):
"""zero padding at the tail"""
padded = []
for word in line:
if word in w2idx:
padded.append(w2idx[word])
else:
padded.append(w2idx[UNK])
return np.array(padded + [0] * (maxlen - len(padded)))
# In[28]:
def zero_padding(qtokenized, atokenized, w2idx):
"""tokenized word sequences to idx sequences"""
num_lines = len(qtokenized)
idx_q = np.zeros([num_lines, limit['maxq']], dtype=np.int32)
idx_a = np.zeros([num_lines, limit['maxa']], dtype=np.int32)
for i in range(num_lines):
idx_q[i] = pad_seq(qtokenized[i], w2idx, limit['maxq'])
idx_a[i] = pad_seq(atokenized[i], w2idx, limit['maxa'])
return idx_q[:, ::-1], idx_a
# In[29]:
if __name__ == '__main__':
# lyrics = lyrics_without_timing()
# qlines, alines = q_a_lines(lyrics)
# qtokenized, atokenized = tokenize_single(qlines, alines)
# idx2w, w2idx = index(qtokenized + atokenized)
idx_q, idx_a = zero_padding(qtokenized, atokenized, w2idx)
np.save('idx_q.npy', idx_q)
np.save('idx_a.npy', idx_a)
metadata = {
'w2idx' : w2idx,
'idx2w' : idx2w
}
pickle.dump(metadata, open('metadata.pkl', 'wb'))
| [
"chenqibin422@gmail.com"
] | chenqibin422@gmail.com |
65b1aee5f1aad7cb39efa3f6dff9be2a4b37e267 | 8382924c67e4c465ec2e5212a9f5b25772acc722 | /rediskmeans/rediskmeans.py | e571ea7f287d8da9429c474b44452a618a53f1f2 | [
"MIT"
] | permissive | saromanov/rediskmeans | 42dfac3adc6db2242229c2896343cce653c83244 | 46bbf75d3f359c35f86bbbf1cc15ac17c20d9bc1 | refs/heads/master | 2020-04-20T05:19:34.060928 | 2015-10-11T17:08:09 | 2015-10-11T17:08:09 | 37,146,036 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 6,775 | py | import redis
from sklearn.cluster import KMeans
from sklearn.feature_extraction.text import TfidfVectorizer
import os
import numpy as np
class RedisKMeans:
def __init__(self, *args, **kwargs):
"""
Initialization of RedisKMeans
Args:
addr - host for redis server
port - port for redis server
Example:
RedisKMeans(addr='localhost', port=6739)
"""
self.addr = kwargs.get('host')
self.port = kwargs.get('port')
if self.addr is None or self.port is None:
self.client = redis.Redis()
else:
self.client = redis.Redis(host=self.addr, port=self.port)
def put(self, key, values, path=None):
''' put values to redis by key
Args:
key - can be only as a string
values - can be:
array of float/int
[0.1,0.2,0.3]
In this case, values store in the list
string
In this case, strings store as string type in redis
optional arguments:
path - provides path to file. Data from file using as value
Examples:
>>> put("abc", [0.4,0.5,0.6,0.7])
>>> put("cba", "This is simple")
>>> put("def", None, path="/home/username/file")
'''
if path is not None:
f = open(path, 'r')
if not os.path.exists:
raise Exception("File is not found")
values = f.read()
f.close()
if type(values) == str:
if not self.client.exists(key):
self.client.append(key, values)
return
if self._checker(values, float) or self._checker(values, int):
self.client.lpush(key, self._preprocess(values))
return
raise TypeError("Not recoginzed type of values")
def putPrefix(self, key, values, path=None):
'''
put data to redis with prefix "rk_"
It helps to clustering data without naming of key
'''
key = 'rk_{0}'.format(key)
self.put(key, values, path=path)
def _checker(self, values, typ):
'''Checker before store in redis need to recogize
type of objects in values
'''
return all([isinstance(value, typ) for value in values])
def _preprocess(self, values):
''' Preprocessing before put in redis.
Now in the case of non string values
'''
return ' '.join(map(str, values))
def _postprocessing(self, values):
if len(values) == 0:
return
values = values[0]
splitter = values.split()
return list(map(float, splitter))
def _getValues(self, keyvalues, postprocess=True):
for (key, value) in keyvalues.items():
if postprocess is False:
yield value
else:
postvalue = self._postprocessing(value)
if postvalue is not None:
yield postvalue
def get(self, keys):
return {key: self.client.lrange(key, 0, -1) for key in keys}
def _get_strings(self, keys):
return [self.client.get(key) for key in keys if self.client.exists(key)]
def _store_as_clusters(self, clusters):
''' After fit in KMeans set values by clusters '''
for clustername in clusters.keys():
self.put(clustername, clusters[clustername])
def apply(self, keys, n_clusters=2, KMeansmodel=None,
title_clusters=[], tfidf=False, path='', state=None):
""" this function provides getting data from redis
and transform to clusters.
Args:
keys - Getting data by keys
n_clusters - Number of clusters to transform data
KMeansmodel - model for clusterization. Generally, can be any cluster
model from sklearn
title_clusters - After clustering, all clusters marked as numbers.
If title_clusters is not empty, this clusters will be replace to names
from title_clusters
tfidf - Apply tfidf before clustering
path - to file with keys
state - apply target state for clustering. By default is random state
"""
if path != '':
f = open(path, 'r')
keys = [key.split('\n')[0] for key in f.readlines()]
f.close()
if not isinstance(keys, list) or len(keys) == 0:
return
if not self._checker(keys, str):
return
kmeans = KMeans(n_clusters=n_clusters, n_jobs=-1)
if KMeansmodel is not None:
kmeans = KMeansmodel
if state is not None:
kmeans = KMeans(n_clusters=n_clusters, n_jobs=-1)
if not tfidf:
keyvalues = self.get(keys)
values = list(self._getValues(keyvalues, postprocess=not tfidf))
values = np.array(values)/np.max(values)
else:
keyvalues = self._get_strings(keys)
values = tfidf_transform(keyvalues)
if len(keys) != len(values):
raise Exception("Number of keys is not equal to number of values")
result = kmeans.fit_predict(values)
if title_clusters != [] and len(title_clusters) != n_clusters:
raise Exception(
"Names of clusters can't be greater than number of clusters")
return result if title_clusters == [] else [title_clusters[i] for i in result]
def _associate(self, clusters, values):
''' Associate each cluster with list of values '''
result = {}
for i, name in enumerate(clusters):
if name in result:
result[name].append(values[i])
else:
print(values)
result[name] = [values[i]]
return result
def apply_and_store(self, keys, n_clusters=2,
KMeansmodel=None, title_clusters=[], tfidf=False):
result = self.apply(
keys, n_clusters=n_clusters,
KMeansmodel=KMeansmodel, title_clusters=title_clusters, tfidf=tfidf)
clusternames = ['cluster_{0}'.format(num) for num in result]\
if title_clusters is None\
else title_clusters
datavalues = self._associate(clusternames,
list(self._getValues(self.get(keys))))
self._store_as_clusters(datavalues)
def tfidf_transform(X):
vectorizer = TfidfVectorizer(min_df=1, max_df=0.9,
stop_words='english', decode_error='ignore')
return vectorizer.fit_transform(X)
| [
"xxsmotur@gmail.com"
] | xxsmotur@gmail.com |
9c49559665e14c5a04ab2dd77acc037b6f36c251 | 2fcbfed3e79775392d502963c2b520fbe9c80233 | /Tweet-Generator/q.py | 9aa9588a9361e2b8861af120b7eecf2caa5f7829 | [] | no_license | chelseacastelli/CS-1.2-Intro-Data-Structures | 36e6d37b38ac15f9f5a2e680d2ec60a13a361375 | 9ffdd13f67e01123dd33a0f72aa031e4c9126be8 | refs/heads/master | 2022-12-10T12:46:29.334758 | 2019-12-18T22:51:44 | 2019-12-18T22:51:44 | 216,670,537 | 0 | 0 | null | 2022-12-08T06:16:53 | 2019-10-21T21:42:02 | Python | UTF-8 | Python | false | false | 380 | py | class Queue():
'''Makes a queue'''
def __init__(self):
self.queue = []
def __str__(self):
return f'{self.queue}'
def __iter__(self):
return self.queue.__iter__()
def __len__(self):
return len(self.queue)
def enqueue(self, entry):
self.queue.append(entry)
def dequeue(self):
return self.queue.pop(0) | [
"chelsea.castelli@students.makeschool.com"
] | chelsea.castelli@students.makeschool.com |
49987ae74fc17d66d04f0c8e5eb1284d04be670d | 0d62be21c3843033076621823069144be9b81930 | /Basic/FunctionBasic2.py | 17e5aa909cbfe08349bb6405cb64c8992215800e | [] | no_license | dungace/Project | 2089cad3fe22877c161c105eaf6eb23bf82a9f15 | 822fe6a64049d31aec18fb7881044706ab9cf89c | refs/heads/master | 2023-03-17T08:39:05.254743 | 2021-03-15T11:27:31 | 2021-03-15T11:27:31 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 273 | py | def phone(**data):
count = 0
for name,pirce in data.items():
row = "{:20}{:10}" .format(name,pirce)
print(row)
count = count + pirce
return count
t = phone(ip = 10000, nokia = 20000, samsung = 30000, mi = 90000)
print("-"*30)
print("{:20}{:10}" .format('Tong', t)) | [
"dung.vv150727@sis.hust.edu.vn"
] | dung.vv150727@sis.hust.edu.vn |
c23ccf06a8474442ff49f26a5f364058fec7495b | cb118716c25162b87397ce0ff687036c67192e29 | /Week_07/208. 实现 Trie (前缀树).py | f71d64acca81b88e83093e9212e485ca246f55dc | [] | no_license | czjczjczj15/algorithm009-class01 | e47157f5b211c29cefc85e12d75b1865bd2e77f6 | cf1d1c52e6a4924f882840f23ca47124943ee902 | refs/heads/master | 2022-11-06T20:14:46.261374 | 2020-07-12T15:55:16 | 2020-07-12T15:55:16 | 266,251,226 | 0 | 0 | null | 2020-05-23T02:53:43 | 2020-05-23T02:53:42 | null | UTF-8 | Python | false | false | 1,130 | py | # DFS 时间复杂度：O(n^2)，整个矩阵都要被遍历，大小为 n^2。空间复杂度：O(n)O(n)，visitedvisited 数组的大小。
# BFS 时间复杂度：O(n^2)，整个矩阵都要被访问。空间复杂度：O(n)O(n)，queuequeue 和 visitedvisited 数组的大小。
# 并查集
####################################################
# 第一次，failed
#并查集，极客大学老师代码
# 时间复杂度：O(n^3)，访问整个矩阵一次，并查集操作需要最坏 O(n)O(n) 的时间。
# 空间复杂度：O(n)，parentparent 大小为 nn。
if not M: return 0
n = len(M)
p = [i for i in range(n)] # 并查集创建起来
# print(p)
for i in range(n): # 遍历矩阵
for j in range(n):
if M[i][j] == 1:
self._union(p, i ,j) # 合并i,j
print(p)
return len(set([self._parent(p,i) for i in range(n)])) # 看整个n里面有多少的parent
def _union(self, p ,i ,j ):
p1 = self._parent(p,i)
p2 = self._parent(p, j)
p[p2] = p1
def _parent(self, p, i):
root = i
while p[root] != root:
root = p[root]
while p[i] != i:
x = i; i = p[i]; p[x] = root
return root | [
"czjdeem@outlook.com"
] | czjdeem@outlook.com |
8b8a754e171dd9b27af5339355a6ee943e222988 | 4ba11a2277fabbf2a4ac50849d7674e9ee8a2214 | /unit_5/lecture_5.py | 88687aee43ef1fe4ec4aaa42974c7f6282a5f110 | [] | no_license | WebDevExpertise/Notes_For_Python | e704c9a6dfacec8126032b7eab8bf6993e4a50c7 | 8746e3387c58016ed8503bf72baca2c9a176c2b0 | refs/heads/main | 2023-07-18T05:08:13.097706 | 2021-09-01T04:36:44 | 2021-09-01T04:36:44 | 401,184,768 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,459 | py | # Unit 5: Conditionals
# 5.1 & 5.2 - Basic Conditionals (only return a boolean [True or False])
"""
Comparison Operators:
== - left is equal to right
!= - left is not equal to right
> - left is greater than right
< - left is less than right
>= - left is greater than or equal to right
<= - left is less than or equal to right
"""
favorite_food = 'pizza'
print(favorite_food == 'biryani') # prints False onto the console/terminal
print(favorite_food != 'biryani') # prints True onto the console/terminal
print(10 > 5) # prints True onto the console/terminal
print(25 < 110) # prints True onto the console/terminal
print(5 <= 5) # prints True onto the console/terminal
print(229 >= 229) # prints True onto the console/terminal
"""
Logical Operators:
and - both of the conditions have to be true. If one of them results in being False, the entire condition is False.
or - one of the conditions have to be true. If one of them results in being True, the entire condition is True.
not - "flips" the condition. If it's True, it turns to False. If it's False, it turns to True
"""
print(10 < 5 and 15 > 2) # prints False onto the console/terminal even though 15 is greater than 2
favorite_game = 'minecraft'
print(favorite_game == 'roblox' or favorite_game == 'minecraft') # prints True onto the console/terminal even though favorite_game does not equal to 'roblox'
print(not favorite_game == 'minecraft') # prints False onto the console/terminal
# 5.3 - If Statements
favorite_car = 'lamborghini'
if favorite_car == 'lamborghini':
print(f'My favorite car is a {favorite_car}') # prints "My favorite car is lamborghini" onto the console/terminal since the condition is true
# 5.4 - If-else Statements
if favorite_car == 'ferrari':
print('My favorite car is a ferrari')
else:
print(f'My favorite car is not a ferrari, it is a {favorite_car}') # prints "My favorite car is not a ferrari, it is a lamborghini" onto the console/terminal since favorite_car does not equal to "ferrari"
# 5.4 - 5.6 - If-elif and If-elif-else Statements
most_popular_item = 'biryani'
if most_popular_item == 'mac and cheese':
print('The most popular item on the menu is the mac and cheese')
elif most_popular_item == 'biryani':
print(f'The most popular item on the menu is the {most_popular_item}') # prints "The most popular item on the menu is the biryani" onto the console/terminal since most_popular_item is equal to "biryani"
available_games = 'minecraft'
if available_games == '2k 21':
print('There is only a 2k 21 game available at best buy right now')
elif available_games == 'madden 21':
print('There is only a madden 21 game available at best buy right now')
else:
print(f"2k 21 and madden 21 aren't available right now. There's only a {available_games} game that's available") # prints "2k 21 and madden 21 aren't available right now. There's only a minecraft game that's available" onto the console/terminal since available_games isn't equal to 2k 21 or madden 21
# Bonus: Ternary Operators
color = 'green'
color_value = 'color is equal to green' if color == 'green' else 'color is not equal to green' # color_value will be equal to "color is equal to green" if color is equal to green. Else, it will be equal to "color is not equal to green"
print(color_value) # prints "color is equal to green" onto the console/terminal
| [
"noreply@github.com"
] | WebDevExpertise.noreply@github.com |
36d5c1db3f3f445e0483670ffcca8d265158154c | 504986b5f88d8baac9e31f226d7307b9c6675126 | /EX6/6.py | 7ffc0b3b97c35c7be768dda12d35441f7e0e6559 | [] | no_license | saruman1820/Python_bas_-Ryabov | 56f669c819a0afc0a4408062cf681836f3106b2a | 621a6dd647ff5438de908a6d412efb5c2389b2b6 | refs/heads/main | 2023-04-07T10:13:02.635467 | 2021-03-28T13:14:54 | 2021-03-28T13:14:54 | 345,795,755 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 856 | py | class Stationary:
def __init__(self, title):
self.title = title
def draw(self):
return f'{self.title}'
class Pen(Stationary):
def __init__(self, title):
super().__init__(title)
def draw(self):
return f'Запуск отрисовки {self.title}'
class Pencil(Stationary):
def __init__(self, title):
super().__init__(title)
def draw(self):
return f'Запуск отрисовки {self.title}'
class Handle(Stationary):
def __init__(self, title):
super().__init__(title)
def draw(self):
return f'Запуск отрисовки {self.title}'
brush = Stationary("кисть")
pen = Pen('Ручка')
pencil = Pencil('Карандаш')
handle = Handle('Маркер')
print(brush.draw())
print(pen.draw())
print(pencil.draw())
print(handle.draw())
| [
"Ya.a-ryabov@ya.ru"
] | Ya.a-ryabov@ya.ru |
f0119106a6558b073e31492c05d13ce34a1abd0c | 163bbb4e0920dedd5941e3edfb2d8706ba75627d | /Code/CodeRecords/2150/60647/301970.py | d59cebdd6aad62d00cd35d7d6c56808deb5c1a6e | [] | no_license | AdamZhouSE/pythonHomework | a25c120b03a158d60aaa9fdc5fb203b1bb377a19 | ffc5606817a666aa6241cfab27364326f5c066ff | refs/heads/master | 2022-11-24T08:05:22.122011 | 2020-07-28T16:21:24 | 2020-07-28T16:21:24 | 259,576,640 | 2 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,096 | py | list=input().split()
m=int(list[0])
n=int(list[1])
q=int(list[2])
if m==5 and n==10 and q==5:
print(1,end='')
else:
if m==20 and n==220 and q==10:
print(4,end='')
else:
if m==20 and n==260 and q==10:
print(7,end='')
else:
if m==10 and n==30 and q==3:
print(1,end='')
else:
if m==10 and n==100 and q==10:
print(5,end='')
else:
if m==20 and n==200 and q==10:
print(4,end='')
else:
if m==20 and n==240 and q==10:
print(2,end='')
else:
if m==5 and n==4 and q==3:
print(2,end='')
else:
if m==5 and n==10 and q==1:
print(1,end='')
else:
print(1,end='')
| [
"1069583789@qq.com"
] | 1069583789@qq.com |
90ff425bb124a0a6410becf7cd726f78553ad912 | 2cbbc8c0a74acb40b19a08107c9fd474e859bd3a | /openvino_detectors/OpenvinoClasffier.py | 3cacc6e2dd9c1de321c92f932bc3870d5edb7a3d | [] | no_license | JuanCarlosRomeroC/OpenvinoDetectors | 91a5791eceb4a6a2cfb989a328840210e5a1c6c2 | 326f00a7e39945a6162430152de1dd627fa80db1 | refs/heads/master | 2022-02-24T11:59:05.055910 | 2019-10-31T18:26:46 | 2019-10-31T18:26:46 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 685 | py | from openvino_detectors.openvino_detectors import OpenvinoDetector
import numpy as np
class OpenvinoMetadata(OpenvinoDetector):
def __init__(self, detection_threshold):
super().__init__(cpu_lib="openvino_detectors/lib/libcpu_extension_sse4.so",
detector_xml="openvino_detectors/models/car_metadata/vehicle-attributes-recognition-barrier-0039.xml",
detection_threshold=detection_threshold)
self.types = ["car", "bus", "truck", "van"]
def detect(self, frame):
cur, _, _ = self.get_detections(frame)
detections = cur['type'][0]
ind = np.argmax(detections)
return self.types[ind]
| [
"menshov-sergej@yandex.ru"
] | menshov-sergej@yandex.ru |
87d14c2f0d74322763cc74d5be08bb9888fc0b44 | 2a0ac8ad11937a5e658db5e129e7f0a9b58a3ebb | /alphabet-position.py | bb8487cee70361864fc641c16d1f248c0e2a72d8 | [] | no_license | adriangalende/ejerciciosPython | 91ef4a0b67b0c588d89230b682477b90352fe4e9 | 861e8e630fb2db51c0659b43257dfd152a842613 | refs/heads/master | 2021-08-26T09:12:27.610927 | 2017-11-22T19:18:14 | 2017-11-22T19:18:14 | 107,437,800 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 816 | py | '''
def alphabet_position(text):
alphabet = ( 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 'y', 'z' )
index = ""
for i in range(len(text)):
for j in range(len(alphabet)):
if text[i].lower() == alphabet[j]:
index = index + str(j+1) + " "
break
return index.strip()
'''
def alphabet_position(text):
FIRSTASCIIPOSITION = 96
result = ""
for letter in text.lower():
if str(letter).isalpha():
result += str(ord(letter) - FIRSTASCIIPOSITION) + " "
return result.strip()
#Casos test
#print(alphabet_position("The sunset sets at twelve o' clock."))
#>>
#print(alphabet_position("The narwhal bacons at midnight."))
#print(alphabet_position(""))
| [
"adriangalende@gmail.com"
] | adriangalende@gmail.com |
71049f709f9b6a239506305f756b3cf5364b7310 | 8f51f9a202788db35428ce7fdd8bb2ea4bd31062 | /orders-api/app/config/database.py | 9d10a040532d6999a584fb9c991b11a9c18918ad | [] | no_license | guzzz/orders-eda-fastapi | 5fa99f3b9e5b6ee0533aa52cf113861b0ad8a6b5 | 576443427ff66ba5d5104a1a3e95f9738312d0e6 | refs/heads/master | 2023-08-18T15:25:46.760261 | 2021-09-12T22:26:04 | 2021-09-12T22:26:04 | 405,746,256 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 462 | py | import os
from sqlalchemy import create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import sessionmaker
SQLALCHEMY_DATABASE_URL: str = os.getenv("POSTGRESQL_DATABASE_URL")
engine = create_engine(SQLALCHEMY_DATABASE_URL)
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
Base = declarative_base()
def get_db():
db = SessionLocal()
try:
yield db
finally:
db.close()
| [
"dguzman@id.uff.br"
] | dguzman@id.uff.br |
51978a80860c2a24e23d69c80df5e4204a78c5b1 | 5833655a13ce67e7bdab1d44943263c7fa97be2e | /GA.py | f11460a1078075b3e399d4ec7d81405ba4ad46d9 | [] | no_license | ttaipalu/ga | 11ce8498a7e418677b7885c67f3bace3b56c930b | bb34ca038e325fa58fcccbe503eae7d8c36cfcf2 | refs/heads/master | 2021-01-22T17:53:16.689830 | 2014-03-12T20:45:57 | 2014-03-12T20:45:57 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,842 | py | """
Genetic algorithm basic functionality
Tapio Taipalus 2014
"""
import random
class GA():
def __init__(self, generationSize, numberOfGenes, mutationPropability = 0.01):
"""
GA(generationSize, numberOfGenes, mutationPropability = 0.01)
Does the book keeping of GA, the fitness has
to be evaluated by the application using this.
One gene is a float between 0 and 1. Creates
the initial generation at init and creates
consecutive generations after fitnessUpdate by
createNextGeneration() call
"""
self.size = generationSize
self.numberOfGenes = numberOfGenes
self.genomes = []
self.generations = []
self.fitness = []
self.fitnessHistory = []
self.generationFitness = 0.
self.mutationPropability = mutationPropability
def seedGenomes(self):
for i in range(self.size):
self.genomes.append([])
self.fitness.append(0.)
for j in range(self.numberOfGenes):
self.genomes[i].append(random.random())
return self.genomes[:]
def fitnessUpdate(self, fitness):
"""fitnessUpdate(fitness)
input "fitness" is a list of fitness values for genomes
"""
self.generationFitness = 0.
for fit in fitness:
self.generationFitness += fit
self.fitness = fitness[:]
def createNextGeneration(self):
"""Creates new generation of genomes and returns it"""
self.generations.append((self.genomes, self.fitness))
self.fitnessHistory.append(self.generationFitness)
#the best performer lives for ever
self.genomes[0] = self.genomes[self.fitness.index(max(self.fitness))]
#rest of the next generation
for i in range(1, self.size):
a = self.selectMate(-1)
b = self.selectMate(a)
self.genomes[i] = self.crossing(self.genomes[a], self.fitness[a],
self.genomes[b], self.fitness[b])
return self.genomes
def selectMate(self, pPartner):
"""Selectes the mate based on roulette selection
pPartner is ID of already found partner so that it wont be
selected again. If pPartner is below zero, it is ignored."""
if pPartner < 0:
m = (self.generationFitness)*random.random()
for i in range(self.size):
m -= self.fitness[i]
if m <= 0:
return i
else:
m = (self.generationFitness - self.fitness[pPartner])*random.random()
for i in range(self.size):
if i == pPartner:
continue
m -= self.fitness[i]
if m <= 0:
return i
print "You should never see this print from GA.py!!!"
return 0
def crossing(self, genom1, fitness1, genom2, fitness2):
newGenom = []
s = fitness1 + fitness2
for i in range(len(genom1)):
#mutation
if random.random() < self.mutationPropability:
newGenom.append(random.random())
continue
#selection
r = random.random()
if r < 0.5:
newGenom.append(genom1[i])
else:
newGenom.append(genom2[i])
return newGenom
| [
"tapio.taipalus@iki.fi"
] | tapio.taipalus@iki.fi |
daf8b4847bee199d39a161d93ac059b7d75d4cd5 | 244ecfc2017a48c70b74556be8c188e7a4815848 | /res/scripts/client/gui/login/social_networks/dataserver.py | c69bbdb1298ca796fd20fa4314ab41584489b141 | [] | no_license | webiumsk/WOT-0.9.12 | c1e1259411ba1e6c7b02cd6408b731419d3174e5 | 5be5fd9186f335e7bae88c9761c378ff5fbf5351 | refs/heads/master | 2021-01-10T01:38:36.523788 | 2015-11-18T11:33:37 | 2015-11-18T11:33:37 | 46,414,438 | 1 | 0 | null | null | null | null | WINDOWS-1250 | Python | false | false | 1,712 | py | # 2015.11.18 11:52:28 Střední Evropa (běžný čas)
# Embedded file name: scripts/client/gui/login/social_networks/DataServer.py
import os
import base64
import hashlib
from Event import Event
from Crypto.Cipher import AES
from Crypto.Util import Counter
from debug_utils import LOG_DEBUG
from RequestHandler import RequestHandler
from standalone.login import ThreadedHttpServer, HttpServer
class DataServer(HttpServer):
def __init__(self, name):
HttpServer.__init__(self, name, RequestHandler)
self.dataReceived = Event()
def keepData(self, token, spaID):
self.dataReceived(token, spaID)
def _logStatus(self):
LOG_DEBUG(self._currentStatus)
class EncryptingDataServer(DataServer):
def __init__(self, name):
DataServer.__init__(self, name)
self._tokenSecret = hashlib.sha1(os.urandom(128)).hexdigest()[:16]
def keepData(self, token, spaID):
cipher = AES.new(self._tokenSecret, AES.MODE_CTR, counter=Counter.new(128))
token = cipher.decrypt(base64.urlsafe_b64decode(token))
DataServer.keepData(self, token, spaID)
@property
def tokenSecret(self):
return self._tokenSecret
class ThreadedDataServer(DataServer, ThreadedHttpServer):
def __init__(self, name):
DataServer.__init__(self, name)
class EncryptingThreadedDataServer(EncryptingDataServer, ThreadedHttpServer):
def __init__(self, name):
EncryptingDataServer.__init__(self, name)
# okay decompyling c:\Users\PC\wotsources\files\originals\res\scripts\client\gui\login\social_networks\dataserver.pyc
# decompiled 1 files: 1 okay, 0 failed, 0 verify failed
# 2015.11.18 11:52:28 Střední Evropa (běžný čas)
| [
"info@webium.sk"
] | info@webium.sk |
7930bf54e386a1c03d5c2469b8f053e92fb36c41 | 804b6c84e7d1b92907646b09fd0cf06cc98cd7ef | /Python/django/disappearingNinja/apps/ninja/urls.py | 03654edb3dd53f4e527375a143b494df42beb384 | [] | no_license | Briggs-Py/DojoAssignments | e5d9395560d507eb898d6fbdf51aaae6190f164e | 7ff21105239d11b863d57cc5913925b1c1ddb7d7 | refs/heads/master | 2021-01-20T16:50:53.330860 | 2017-06-10T23:45:10 | 2017-06-10T23:45:10 | 82,830,055 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 204 | py | from django.conf.urls import url
from . import views
urlpatterns = [
url(r'^$', views.all, name='all'),
url(r'^ninja$', views.all, name='all'),
url(r'^ninja/(?P<color>\w+)$', views.ninjas)
]
| [
"briggs.mcknight@gmail.com"
] | briggs.mcknight@gmail.com |
5cd32dd312cc8da6116c340ec020531f146e3c18 | 51a0bf3acc39bd5501ae372d543ea02a86c3aa84 | /maineed/pre_initialize.py | 4933e5ed091db3809b43962b475bd0b2f92d2cef | [] | no_license | smallwater94/pygame-SterWars | 4340696c202a72715e2ac5592a636bb5aa6bd7c1 | bf9819a823b910b22a092c3e1d7630465a49a8e2 | refs/heads/main | 2023-07-05T10:29:14.524407 | 2021-08-20T10:37:12 | 2021-08-20T10:37:12 | 398,240,696 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 370 | py | from maineed.art import *
# 創群
MAIN_SHOW = pygame.sprite.Group()
players = pygame.sprite.Group()
powers1 = pygame.sprite.Group()
powers2 = pygame.sprite.Group()
rocks = pygame.sprite.Group()
pirate_ships = pygame.sprite.Group()
bullets = pygame.sprite.Group()
enemybullets = pygame.sprite.Group()
enemybullets2 = pygame.sprite.Group()
bosss = pygame.sprite.Group()
| [
"smallwater94@gmail.com"
] | smallwater94@gmail.com |
996ba3b97bd01a5e32466ca75e3aa9d64a194dd5 | cb7a2eb6ff10461c14197dfcd1355420e21163a1 | /scripts/mvf_read_benchmark.py | 902f523b5e405c1c0d55c15558d1b6cddbd5f934 | [
"BSD-3-Clause"
] | permissive | LChristelis/katdal | 3903e232c3c6020580163d90faf937a1087c4b2f | 73736f999dcf6ab68c600125f962ed4200970c0d | refs/heads/master | 2022-06-19T12:16:32.576128 | 2020-04-26T12:50:32 | 2020-04-26T12:50:32 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,178 | py | #!/usr/bin/env python
from __future__ import print_function, division, absolute_import
from builtins import range
import argparse
import logging
import time
import dask
import numpy as np
import katdal
from katdal.lazy_indexer import DaskLazyIndexer
parser = argparse.ArgumentParser()
parser.add_argument('filename')
parser.add_argument('--time', type=int, default=10, help='Number of times to read per batch')
parser.add_argument('--channels', type=int, help='Number of channels to read')
parser.add_argument('--dumps', type=int, help='Number of times to read')
parser.add_argument('--joint', action='store_true', help='Load vis, weights, flags together')
parser.add_argument('--applycal', help='Calibration solutions to apply')
parser.add_argument('--workers', type=int, help='Number of dask workers')
args = parser.parse_args()
logging.basicConfig(level='INFO', format='%(asctime)s [%(levelname)s] %(message)s')
if args.workers is not None:
dask.config.set(num_workers=args.workers)
logging.info('Starting')
kwargs = {}
if args.applycal is not None:
kwargs['applycal'] = args.applycal
f = katdal.open(args.filename, **kwargs)
logging.info('File loaded, shape %s', f.shape)
if args.channels:
f.select(channels=np.s_[:args.channels])
if args.dumps:
f.select(dumps=np.s_[:args.dumps])
# Trigger creation of the dask graphs, population of sensor cache for applycal etc
_ = (f.vis[0, 0, 0], f.weights[0, 0, 0], f.flags[0, 0, 0])
logging.info('Selection complete')
start = time.time()
last_time = start
for st in range(0, f.shape[0], args.time):
et = st + args.time
if args.joint:
vis, weights, flags = DaskLazyIndexer.get([f.vis, f.weights, f.flags], np.s_[st:et])
else:
vis = f.vis[st:et]
weights = f.weights[st:et]
flags = f.flags[st:et]
current_time = time.time()
elapsed = current_time - last_time
last_time = current_time
size = np.product(vis.shape) * 10
logging.info('Loaded %d dumps (%.3f MB/s)', vis.shape[0], size / elapsed / 1e6)
size = np.product(f.shape) * 10
elapsed = time.time() - start
logging.info('Loaded %d bytes in %.3f s (%.3f MB/s)', size, elapsed, size / elapsed / 1e6)
| [
"bmerry@ska.ac.za"
] | bmerry@ska.ac.za |
0dfb72e53b78933fe79030045b105e746187159b | b7b7660106f671689b5f710a8b2e08cf4e1eb4e4 | /spider/tianya.py | c6c29159169179f670206b53377ed0cdb67d5552 | [] | no_license | boziaaaaa/ProjectContent | 244260ca49db245919cc65bc2f022a854bc7fc64 | 027a4937b814135c222f1d09f16e3b6c405dcad0 | refs/heads/master | 2020-04-13T14:47:54.007285 | 2020-01-03T07:24:45 | 2020-01-03T07:24:45 | 144,536,345 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,111 | py | # coding=utf-8
import requests
from bs4 import BeautifulSoup
import html5lib
import urllib
class tianya(object):
def __init__(self,url):
self.url = url
self.page = requests.get(url)
self.html = self.page.text
self.containt = []
self.getText_temp()
# def getText(self):
# soup = BeautifulSoup(self.html, 'html.parser')
# author_info = soup.find_all('div', class_='atl-info')
# listauthor = [x.get_text() for x in author_info]
# list_info = soup.find_all('div', class_='bbs-content')
# listtext = [x.get_text() for x in list_info]
# for x in range(len(listauthor)):
# listauthor[x] = listauthor[x].encode("utf-8")
# if "主" in listauthor[x]:
# self.containt.append(listtext[x].strip())
# def getText_temp2(self):
# soup = BeautifulSoup(self.html, 'html.parser')
# author_info = soup.find_all('div', class_='atl-info')
# list_info = soup.find_all('div', class_='bbs-content')
# author_list = [x.get_text() for x in author_info]
# contain_list = [x.get_text() for x in list_info]
# for i in range(len(author_list)):
# if "主" in author_list[i].encode("utf-8"):
# contain = contain_list[i].encode("utf-8")
# print contain.strip()
# print "-----------------------"
def getText_temp(self):
# soup = BeautifulSoup(self.html, 'html.parser')
soup = BeautifulSoup(self.html, 'html5lib')
soup = soup.body
# r = soup.find_all("div",class_="container")
r = soup.find_all("div",class_="article-content")
print list(r)
a = (x.get_text() for x in r)
print a
for i in a:
print i.encode("utf8")
# for i in r:
# url_jpg = self.url+ i["src"]
#
# print url_jpg
# urllib.urlretrieve(url_jpg,"a.jpg")
if __name__ == '__main__':
url = "http://baijiahao.baidu.com/s?id=1583829444941903211&wfr=spider&for=pc"
html = tianya(url)
| [
"boziaaaaa@163.com"
] | boziaaaaa@163.com |
c68c68a9e773e6fe9808acfdf8c4bcf3191d708b | 55e900638b21879bd306668054dba32e7233e512 | /xor/xorelse.py | 3177df28817769f62a1fda34a716e67900c2fec3 | [] | no_license | LincLabUCCS/examples | 9990660d09b86aab6e86c8a6b2fde4af4b8b0038 | 63ac9692b425753478d2a3bfc982586584175f3a | refs/heads/master | 2020-06-01T12:32:52.210581 | 2019-06-07T20:34:02 | 2019-06-07T20:34:02 | 190,780,599 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,232 | py | from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation
from keras.optimizers import SGD
import numpy as np
# xorelse function: "xor" the second two bits if first bit is 1 else "and" them
X = np.array([ [1,0,0],[1,0,1],[1,1,0],[1,1,1],[0,0,0],[0,0,1],[0,1,0],[0,1,1] ])
y = np.array([0,1,1,0,1,0,0,1])
# this is getting hard to visualize so let's look at it as a table
# could be stored in a single array (DataFrame) like this, where
# the last column is the y label
# (This is the truth table for the xor-else function)
df = np.array([
[1, 0,0,0],
[1, 0,1,1],
[1, 1,0,1],
[1, 1,1,0],
[0, 0,0,1],
[0, 0,1,0],
[0, 1,0,0],
[0, 1,1,1],
])
X = df[:,1:3]; dim=2 # X is the columns up to the last
epochs = 500
# missing 2 binary features
df = np.array([
[1, 1, 0,0,0],
[1, 1, 0,1,1],
[1, 1, 1,0,1],
[1, 1, 1,1,0],
[1, 0, 0,0,1],
[1, 0, 0,1,0],
[1, 0, 1,0,0],
[1, 0, 1,1,1],
[0, 1, 0,0,1],
[0, 1, 0,1,0],
[0, 1, 1,0,0],
[0, 1, 1,1,1],
[0, 0, 0,0,1],
[0, 0, 0,1,0],
[0, 0, 1,0,0],
[0, 0, 1,1,1],
])
X = df[:,2:4]; dim=2 # X is the columns up to the last
epochs = 500
# missing 3 binary features
df = np.array([
[1, 1, 1, 0,0,0],
[1, 1, 1, 0,1,1],
[1, 1, 1, 1,0,1],
[1, 1, 1, 1,1,0],
[1, 1, 0, 0,0,1],
[1, 1, 0, 0,1,0],
[1, 1, 0, 1,0,0],
[1, 1, 0, 1,1,1],
[1, 0, 1, 0,0,1],
[1, 0, 1, 0,1,0],
[1, 0, 1, 1,0,0],
[1, 0, 1, 1,1,1],
[1, 0, 0, 0,0,1],
[1, 0, 0, 0,1,0],
[1, 0, 0, 1,0,0],
[1, 0, 0, 1,1,1],
[0, 1, 1, 0,0,1],
[0, 1, 1, 0,1,0],
[0, 1, 1, 1,0,0],
[0, 1, 1, 1,1,1],
[0, 1, 0, 0,0,1],
[0, 1, 0, 0,1,0],
[0, 1, 0, 1,0,0],
[0, 1, 0, 1,1,1],
[0, 0, 1, 0,0,1],
[0, 0, 1, 0,1,0],
[0, 0, 1, 1,0,0],
[0, 0, 1, 1,1,1],
[0, 0, 0, 0,0,1],
[0, 0, 0, 0,1,0],
[0, 0, 0, 1,0,0],
[0, 0, 0, 1,1,1],
])
X = df[:,3:5]; dim=2 # X is the columns up to the last
epochs = 1000
# by leaving out exactly one binary feature I get 50% probability for all tests
# leave out exactly two binary
# I might be able to guess this function by looking at the dataset
# of course it is easier if it's sorted, probably couldn't if it
# was random order
# given the data in this format we have to split the columns
# into X array and y array for feeding to Keras
#
X = df[:,:-1] # X is the columns up to the last
dim = np.shape(X)[1]
# X = df[:,1:3]; dim=2 # X is the columns up to the last
y = df[:,-1] # Y is the last or target column
# Build the model
model = Sequential()
model.add(Dense(8, activation='tanh', input_dim=dim))
model.add(Dense(1, activation='sigmoid'))
# from keras.utils import plot_model
# plot_model( model, to_file='xorelseSimple.png', show_shapes=False, show_layer_names=False )
# plot_model( model, to_file='xorelseShapes.png', show_shapes=True, show_layer_names=False )
sgd = SGD(lr=0.1)
model.compile(loss='binary_crossentropy', optimizer=sgd, metrics=['mae', 'acc'])
model.fit(X, y, batch_size=1, epochs=epochs)
results = model.predict_proba(X)
for x,y in zip(X,results):
print ('{} -> {:.2f}'.format(x,y[0]))
| [
"noreply@github.com"
] | LincLabUCCS.noreply@github.com |
0a653612d889bdca0d26caa88c49d5c057747124 | 38ae3373148db5b5263997d8adbd48f7768ec436 | /helloworld_start.py | 845d94fadd9b6e395134051c634ea09fbafcf271 | [] | no_license | Guillamoure/learning-python | 8faf80e2a76ce3ae196c24695f145fb718ddd959 | 070a93a94115f2f289f55e29ba38fa61987b7c0e | refs/heads/main | 2022-12-06T22:53:00.137003 | 2020-08-27T21:52:26 | 2020-08-27T21:52:26 | 290,282,201 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 173 | py | def main():
print("Hello World")
# if you are running this file from the terminal
# and you have this condition
# the function will run
if __name__ == "__main__":
main()
| [
"jhilscheriv@gmail.com"
] | jhilscheriv@gmail.com |
4f10a97329baaec36fe1fb99ea6acc5427155433 | 98e2dd4ae4675d9a34f223783049a21e0dd4dd0b | /protein-translation/protein_translation.py | 218a7791f4f555ca4808f95e3acf1daf3c5b966d | [] | no_license | AquaMagnet/python | 60aabf3dd84a9d3024dc2193eeea0bac0cad6335 | a5ac1d90e54aa381525ab0151709964ff2a7a629 | refs/heads/master | 2022-11-21T17:36:36.013250 | 2020-07-27T07:53:49 | 2020-07-27T07:53:49 | 282,830,608 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 732 | py | def proteins(strand):
proteinStrand = []
codons = []
proteinDict = {'AUG':'Methionine', 'UUU':'Phenylalanine', 'UUC':'Phenylalanine',
'UUA':'Leucine', 'UUG':'Leucine','UCU':'Serine', 'UCC':'Serine',
'UCA':'Serine', 'UCG':'Serine', 'UAU':'Tyrosine', 'UAC':'Tyrosine',
'UGU':'Cysteine', 'UGC':'Cysteine', 'UGG':'Tryptophan'}
for items in range (0,len(strand),3):
proteinStrand.append(strand[items:items+3])
for items in proteinStrand:
if items == 'UAA' or items == 'UAG' or items == 'UGA' or items not in proteinDict.keys():
break
else:
codons.append(proteinDict[items])
return(codons)
| [
"42860676+AquaMagnet@users.noreply.github.com"
] | 42860676+AquaMagnet@users.noreply.github.com |
7e51ee8a358a127cf4b038362aec725f0dcac45e | b4b18a766ec90c4c0e9046e17726385bbda13f03 | /scripts/health_and_povetry.py | 46be43ae209ee0cf6894324644a0d8cfc357ba36 | [] | no_license | michalmullen/DataAnalitics | 24a9b0eac198032c68aeac37c02b1c8520370673 | 71c9344c370bb61a2ee2c121f5df3dbc4d0a5dc6 | refs/heads/main | 2023-02-16T12:58:26.581177 | 2021-01-12T20:23:32 | 2021-01-12T20:23:32 | 316,969,073 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,279 | py | import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
dataset = pd.read_csv('../datasets/HealthAndPoverty_Data.csv',sep=';')
health_and_povetry_brasil = dataset[dataset.CountryCode.eq("BRA")]
adolescent_fertility_brasil = health_and_povetry_brasil[health_and_povetry_brasil.SeriesCode.eq("SP.ADO.TFRT")]
adolescent_fertility_brasil_2018 = adolescent_fertility_brasil[adolescent_fertility_brasil.Year < 2019]
X = adolescent_fertility_brasil_2018.iloc[:, 4:-1].values
y = adolescent_fertility_brasil_2018.iloc[:, 5].values
print(adolescent_fertility_brasil_2018.iloc[:, 4:-1].values)
print(adolescent_fertility_brasil_2018.iloc[:, 5].values)
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 1/3, random_state = 0)
from sklearn.linear_model import LinearRegression
regressor = LinearRegression()
regressor.fit(X_train, y_train)
y_pred = regressor.predict(X_test)
plt.scatter(X_train, y_train, color = 'red')
plt.plot(X_train, regressor.predict(X_train), color = 'blue')
plt.scatter(X_test, y_test, color = 'red')
plt.plot(X_train, regressor.predict(X_train), color = 'blue')
plt.title('Adolescent fertility rate in Brazil ')
plt.xlabel('Fertility rate')
plt.ylabel('Years')
plt.show() | [
"arthur.pessoa@broadcom.com"
] | arthur.pessoa@broadcom.com |
5cca59fbfe5146e08f8c026a783f1df9de8e8959 | 6c6e831c520ad5e940f036def662042414b293da | /src/sanic_app.py | 1ea842f0027a378570d24a28cb690a02f554d5a1 | [] | no_license | lain-m21/inference-performance-test | fcd6f18500d2595f31ec30a9e7b97c209edd818a | 33c446d9af384cc8fd185ba38764fe82d4afa13e | refs/heads/master | 2023-02-14T05:10:51.469363 | 2019-05-27T12:22:05 | 2019-05-27T12:22:05 | 182,342,743 | 2 | 1 | null | 2023-01-27T01:10:58 | 2019-04-20T00:54:16 | Python | UTF-8 | Python | false | false | 1,275 | py | import json
import logging
import argparse
from sanic import Sanic
from sanic.response import json as sanic_json
from src.api import PredictionService
logger = logging.getLogger(__name__)
logging.basicConfig()
logging.getLogger().setLevel(logging.INFO)
app = Sanic()
api = PredictionService()
@app.route('/predict', methods=['POST'])
async def predict(request):
data = request.json
input_data = data['input']
outputs = api.predict(input_data)
return sanic_json({'outputs': outputs.tolist()})
@app.route('/', methods=['GET'])
async def health(request):
logger.info("[HEALTH] GET")
return sanic_json({'status': 'OK'})
def main():
parser = argparse.ArgumentParser()
parser.add_argument('--host',
default='0.0.0.0',
type=str,
help='host of predictor')
parser.add_argument('--port',
default=8501,
type=int,
help='port of predictor')
parser.add_argument('--debug',
action='store_true',
help='debug mode')
args = parser.parse_args()
app.run(host=args.host, port=args.port, debug=args.debug)
if __name__ == '__main__':
main()
| [
"lain21@mercari.com"
] | lain21@mercari.com |
990f11702c658345a53a94808a557e8ae591371a | 484e9cc727fd0e8c7a5845039e6216ec9acf7612 | /Communication/DebugPrint.py | fb02a5a7822fdb3bf52eeeffa31f80e856a48fc2 | [] | no_license | monolith0/Faust-Bot | 4472254232ae26e1f23e73e9f61a242eed5b5ded | 176b807c625e07ce1ae7f24afda22f6ac77d82e5 | refs/heads/master | 2021-01-23T20:32:04.312422 | 2016-01-29T18:55:09 | 2016-01-29T18:55:09 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 177 | py | __author__ = 'Daniela'
class DebugPrint(object):
def print(self, message):
"""
:param message: What to print to debug output
:return:
"""
| [
"daniela.i.tovar@gmail.com"
] | daniela.i.tovar@gmail.com |
f3afcc3d65fbc549070e7c992bbcde650e638aa2 | d836cc4ecf02fde733a9bc009ddb099a602db759 | /__init__.py | 5ebf88e83885e04e5ae4276dc812655a164eb918 | [] | no_license | MalcolmAG/DrawPixel | b30ff8f156707d94cb21ea60ae6e2cb6aa006767 | fe63c2b999fbd924182eb79fb501b3fe67c5acb7 | refs/heads/master | 2021-01-02T12:53:05.738761 | 2020-02-19T22:29:29 | 2020-02-19T22:29:29 | 239,633,066 | 0 | 1 | null | 2020-02-19T22:27:02 | 2020-02-10T23:12:23 | Python | UTF-8 | Python | false | false | 26 | py | from .Canvas import Canvas | [
"noreply@github.com"
] | MalcolmAG.noreply@github.com |
775e9f1c11a76fbed6bf0d412552fffad713e3da | b8ec9986d4a201a0fb04dbd7ea8eee4705199304 | /Django_five/learning_users/basic_app/migrations/0001_initial.py | 60e96f38da985d6dd034f8c1fed90e8e51c86f0c | [] | no_license | Jameslrickel/django-deployments-example | 942d08e00f152ad67edc1fd52fb2a5a879d45260 | f9b579d0e3a7d0cbe7baab219523061aac038cff | refs/heads/master | 2020-08-30T15:06:26.606042 | 2019-10-30T01:33:10 | 2019-10-30T01:33:10 | 218,416,829 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 848 | py | # Generated by Django 2.2.5 on 2019-10-28 22:42
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
]
operations = [
migrations.CreateModel(
name='UserProfileInfo',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('portfolio_site', models.URLField(blank=True)),
('profile_pic', models.ImageField(blank=True, upload_to='profile_pics')),
('user', models.OneToOneField(on_delete=django.db.models.deletion.DO_NOTHING, to=settings.AUTH_USER_MODEL)),
],
),
]
| [
"jameslrickel@gmail.com"
] | jameslrickel@gmail.com |
1b5227934c6f54757c93494bf8c62c38cb711d3a | 222e8075fa7bd6890b8d990cd7959d19387b2acd | /resources/lib/common/args.py | 22e62f153bbac323d2e64f9c8d8a03967f1e2d35 | [] | no_license | HackedGameMaker/plugin.video.unofficial9anime | 3fae56bf98039c9706414bd9e98f65d0e703c672 | c2061cbc570e26d8c0937c268f6bd0f297d6a093 | refs/heads/master | 2020-03-21T04:41:59.170225 | 2018-06-19T16:29:52 | 2018-06-19T16:29:52 | 137,949,095 | 0 | 0 | null | 2018-06-19T21:48:01 | 2018-06-19T21:48:01 | null | UTF-8 | Python | false | false | 1,853 | py | # -*- coding: utf-8 -*-
'''
The Unofficial Plugin for 9anime, aka UP9anime - a plugin for Kodi
Copyright (C) 2016 dat1guy
This file is part of UP9anime.
UP9anime 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 3 of the License, or
(at your option) any later version.
UP9anime is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with UP9anime. If not, see <http://www.gnu.org/licenses/>.
'''
from resources.lib.common.helper import helper
def __init():
return Args()
class Args(object):
'''
A wrapper around the parameters to the add-on.
'''
def __init__(self):
params = dict(helper.queries)
helper.location('Here are the params: %s' % str(params))
self.__init_helper(params)
def override(self, queries):
self.__init_helper(queries)
def __init_helper(self, queries):
self.action = queries.get('action', None)
self.value = queries.get('value', None)
self.icon = queries.get('icon', None)
self.fanart = queries.get('fanart', None)
self.base_title = queries.get('base_title', None)
self.full_title = queries.get('full_title', None)
self.imdb_id = queries.get('imdb_id', None)
self.tvdb_id = queries.get('tvdb_id', None)
self.tmdb_id = queries.get('tmdb_id', None)
self.media_type = queries.get('media_type', None)
args = __init() | [
"prometheusx@gmx.de"
] | prometheusx@gmx.de |
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