Saravanan666/pypi-org huggingface dataset:
Package: chanalyze
chanalyzeA simple WhatsApp Chat Analyzer ( for both Private & Group chats ), made with :heart:Now with concurrency support !!!nomenclatureChat+Analyze=chanalyzemotivationI was interested in learning how much time I'm spending on WhatsApporin which conversation I'm more or less involved/ attachedorat which part of day I'm more involved in Chatting etc.So I'm writing these scripts for analyzingWhatsAppChat( both Private & Group ), which can easily be exported into a*.txtfile from WhatsApp Mobile Application.That*.txtis parsed, cleaned & objectified, so that it can be analyzed with ease.Using this tool, now I can understand each minute I spent on a certain Chat( or may be how someone else spent )or how many times someone started a conversation( which might be a good indicator of interest of participant(s) towards Chat )For sake ofPrivacytest data file(s), which were used for plotting following chart(s), are kept private. Also Contact Name(s)/ Number(s) are partially grayed.usageInstallchanalyzefrom PyPI$python3-mpipinstall--userchanalyzeMake sure you've added$HOME/.local/binto your$PATHenvironment variableExport target Whatsapp chat into*.txtfile, while omitting media.Now analyze your exported WhatsApp chat(s), usingchanalyzechanalysis( Chat Analysis )Total Contribution of Chat ParticipantsHourly Contribution of Chat ParticipantsActivity of Chat Participants on every Minute of DayActiveness of ChatConversation Initializing Chat Participant Identification( using Mean & Median Delay )- Reflecting Participant's interest towards ChatTop Emojis used in ChatChat Activity HeatMapWord Cloud from Messages
Package: chan_arc
Imageboard thread archives come in a multitude of different formats: Plain WARC files, Fuuka database dumps, and most tools output their own unique format. This disjoined nature of the backup formats makes it difficult to transport thread dumps from one supplier to another, and even more difficult if you’re looking to work with a bunch of different thread archives.This is an attempt to standardize a file format that can be used to archive and store threads from all sorts of image boards. This should make it easier to create a tool that backs up threads, meaning we don’t need to redo the same work of creating a format for our specific tool to use, and that everyone’s archives can be imported and exported to a single, format.The draft specification is available atchan-arc-spec.rst.LicenseThe specification itself, as well as any reference code or libraries hosted here, are released into the public domain listed below:This is free and unencumbered software released into the public domain.

Anyone is free to copy, modify, publish, use, compile, sell, or
distribute this software, either in source code form or as a compiled
binary, for any purpose, commercial or non-commercial, and by any
means.

In jurisdictions that recognize copyright laws, the author or authors
of this software dedicate any and all copyright interest in the
software to the public domain. We make this dedication for the benefit
of the public at large and to the detriment of our heirs and
successors. We intend this dedication to be an overt act of
relinquishment in perpetuity of all present and future rights to this
software under copyright law.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR
OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE,
ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
OTHER DEALINGS IN THE SOFTWARE.

For more information, please refer to <http://unlicense.org/>
Package: chancepy
ChancePyChancePy - Random generator helper for Python. Inspired byChanceJS.Installationwith pippip install chancepywith poetrypoetry add chancepyUsagefromchancepyimportChance# Basic Methodsrand_string=Chance.string()rand_guid=Chance.guid()rand_int=Chance.int(min=2,max=32)rand_letter=Chance.letter(casing='lower')rand_char=Chance.character(pool='acegikmoqsuwy')rand_domain=Chance.domain()# Utilitiesrand_choice=Chance.pickone([1,2,3])rand_2_choices=Chance.pickset(['a','b','c','d'],2)# Timerand_date_in_april=Chance.date(month=4)rand_year=Chance.year(mini=1990)rand_month_name=Chance.month(mode="full")rand_weekday=Chance.weekday(mode="short")rand_hour=Chance.hour()rand_min=Chance.minute()rand_second=Chance.second()rand_millisecond=Chance.millisecond()rand_timezone=Chance.timezone()rand_timestamp=Chance.timestamp()ContributingPRs are welcome!
Package: chandas
Chandas-------|Build Status| |Documentation Status|Intro~~~~~This is a python package for Indic language (mostly sanskrit) metreidentification and related tasks like syllabization. This module expectsdevanAgarI input, and currently produces IAST output.For users----------  `Autogenerated Docs on readthedocs (might bebroken) <http://chandas.readthedocs.io/en/latest/>`__.-  Manually and periodically generated docs`here <https://sanskrit-coders.github.io/chandas/build/html/>`__-  For detailed examples and help, please see individual module files inthis package.Installation or upgrade:~~~~~~~~~~~~~~~~~~~~~~~~-  ``sudo pip install chandas -U``-  ``sudo pip install git+https://github.com/sanskrit-coders/chandas/@master -U``-  `Web <https://pypi.python.org/pypi/chandas>`__.Usage~~~~~For more examples, see tests.Metre Identification^^^^^^^^^^^^^^^^^^^^::from chandas import identifypattern_lines = identify.to_pattern_lines("निर्दिष्टाङ् कुलपतिना स पर्णशालाम् अध्यास्य प्रयतपरिग्रहद्वितीयः ।\nतच्छिष्याध्ययननिवेदितावसानां सव्ँविष्टः कुशशयने निशान् निनाय ॥".split("\n"))id_result = identify.identifier.IdentifyFromPatternLines(pattern_lines)assert id_result['exact'] == "Praharṣiṇī"Syllabization^^^^^^^^^^^^^::from chandas import syllabizesyllabize.get_syllables(u"ॐ मणि पद्मे ऽहम्") == "ओम् म णि पद् मे हम्"syllabize.get_graphemes(u"बिक्रममेरोनामहो") == "बि क् र म मे रो ना म हो".split(" ")Shared test data~~~~~~~~~~~~~~~~Please feel free to use test data published here to test your ownmodules:-  `syllabizationTests.json <https://github.com/sanskrit-coders/chandas/blob/master/src/test/data/syllabizationTests.json>`__For external collaborators---------------------------  We copy the data and identification code from `shreevatsa'srepo <https://github.com/shreevatsa/sanskrit/>`__. This code has beentransformed a bit to conform to PEP conventions.-  You may be interested in sharing and contributing to a common pool oftest cases - see the chandas-id and syllabization tests underhttps://github.com/sanskrit-coders/chandas/tree/master/tests/data .For contributors----------------Contact~~~~~~~Have a problem or question? Please head to`github <https://github.com/sanskrit-coders/chandas>`__.Packaging~~~~~~~~~-  ~/.pypirc should have your pypi login credentials.::python setup.py bdist_wheeltwine upload dist/* --skip-existingBuild documentation~~~~~~~~~~~~~~~~~~~-  sphinx html docs can be generated with ``cd docs; make html``Testing~~~~~~~Run ``pytest`` in the root directory.Auxiliary tools~~~~~~~~~~~~~~~-  |Build Status|-  |Documentation Status|-  `pyup <https://pyup.io/account/repos/github/sanskrit-coders/chandas/>`__.. |Build Status| image:: https://travis-ci.org/sanskrit-coders/chandas.svg?branch=master:target: https://travis-ci.org/sanskrit-coders/chandas.. |Documentation Status| image:: https://readthedocs.org/projects/chandas/badge/?version=latest:target: http://chandas.readthedocs.io/en/latest/?badge=latest.. |Documentation Status| image:: https://readthedocs.org/projects/indic-transliteration/badge/?version=latest:target: http://indic-transliteration.readthedocs.io/en/latest/?badge=latest
Package: chandl
A lightweight tool for parsing and downloading 4chan threads.FeaturesA comprehensive API for programmatically analysing 4chan content.Concurrent downloading, with parallelism linked to the number of available cores.Override the file naming scheme and specify exclusions for thread downloads.Filter files by extension or category (e.g. images, videos).InstallationTo installchandl, simply run:$ pip install chandlExamplesDownload all files in<thread_url>, to a new directory named after the thread if possible, otherwise its raw id:$ chandl <thread_url>Download all images and.webmfiles in<thread_url>to/dev/shm, using 3 download threads per core:$ chandl -f images,webm -o /dev/shm -p 3 <thread_url>Download all files in<thread_url>, exceptabc.jpganddef.jpgto the present working directory, using a custom name format:$ chandl -e abc.jpg,def.jpg -t . -n "{board} - {file.name}.{file.extension}" <thread_url>Usage$ chandl -h
usage: chandl [-h] [-V] [-v] [-f [FILTER]] [-e [EXCLUDE]] [-o [OUTPUT_DIR]]
              [-t [THREAD_DIR]] [-n [NAME]] [-p PARALLELISM]
              url

A lightweight tool for parsing and downloading 4chan threads.

positional arguments:
  url                   the URL of the thread to download

optional arguments:
  -h, --help            show this help message and exit
  -V, --version         show program's version number and exit
  -v, --verbosity       increase output verbosity
  -f [FILTER], --filter [FILTER]
                        file types or extensions to download, value either
                        comma-separated or option passed multiple times
  -e [EXCLUDE], --exclude [EXCLUDE]
                        file names to exclude, value either comma-separated or
                        option passed multiple times
  -o [OUTPUT_DIR], --output-dir [OUTPUT_DIR]
                        the directory to create the `thread-dir` within
  -t [THREAD_DIR], --thread-dir [THREAD_DIR]
                        relative to the `output-dir`, this will contain
                        downloaded files
  -n [NAME], --name [NAME]
                        the format to use for downloaded file names
  -p PARALLELISM, --parallelism PARALLELISM
                        the maximum number of download threads to use per coreRoadmapImplement tracking of threads until they are deletedImprove test coveragePylint or flake8 integration
Package: chandler
A simple CLI utility displaying OAR cluster information retrieved from the API.InstallationRequirements:python >= 2.7You can install, upgrade, uninstall chandler with these commands:$ pip install [--user] chandler
$ pip install [--user] --upgrade chandler
$ pip uninstall chandlerOr from git (last development version):$ pip install git+https://github.com/oar-team/chandler.gitOr if you already pulled the sources:$ pip install path/to/sourcesOr if you don’t have pip:$ easy_install chandler
Package: chandler-handler
Python Size and Time Based Logging File Rotating HandlerPython logging's file basedhandlershave two different kinds of rotation.Size based rotationTime based rotationHowever, these rotations work in isolation. Only one handler can be attached to a log file.
One can only add either Size based rotation or Time based rotation.Usingchandler.handler.SizedAndTimedRotatingHandleryou can rotate the files based on both time and size. Files will be rotated whenever either of the conditions are met.How to Useimport the handlerfromchandler.handlerimportSizedAndTimedRotatingHandlerThen you can initialise your loggers and append this handler.logger=logging.getLogger('test-logger')log_file_path='/var/log/test/logging.log'rotating_handler=SizedAndTimedRotatingHandler(log_file_path,when='h',interval=1,max_bytes=50000,backup_count=3)logger.addHandler(rotating_handler)In the above example the handler is configured to rotate every one hour or whenever the file size reaches 50k bytes.
This handler is built on top ofTimedRotatingFileHandler, so most of the arguments are similar to that of TimedRotatingFileHandler.installationYou can install with pip$pipinstallchandler-handlerContributionAuthorsSuraj Arya
Package: chandralc
chandralc: A Python Package for CXO Lightcurve AnalysisThechandralcPython package was developed to analyze Chandra X-ray Observatory lightcurves in a matter of seconds. With algorithms and programs to automatically extract, download, plot, and analyze data, it is the perfect tool to study CXO lightcurves efficiently and accurately.chandralcis the perfect tool for citizen science. If you're interested in detecting extragalactic planets, feel free to shoot me an email atsam@qprogramming.net!To seechandralcin action, check outthe demo(currently in development).Features:Lightcurve ExtractionExtract lightcurves from one or more ObsIDs automatically. This feautre is not yet available publicly.Downloads:Large database of over 150,000 lightcurves from 10,000+ X-ray SourcesDownloading extracted lightcurves from 19+ galaxies.Search for lightcurves with J2000 coordinatesRetrieve galaxy from lightcurve file namesConvert:Convert FITS lightcurves to ASCII txt filesAnalysis:Observation DetailsTotal countsObservation time (in kiloseconds)Count rate (kiloseconds (rate_ks), seconds (rate_s))Source coordinates (J2000 format)ObsID (Observation ID of the lightcurve)Galaxy (Messier or NGC)PlotsCumulative Count plots over time to view net counts over timeLightcurves with custom binning to view data in the form of count rate per bin or net counts per bin over time.Power Spectral Density (PSD) to identify periodicity and their time periods/frequencies.Running Average PlotState DetectionNote: the flare detection algorithm is currently under development and has not been extensively tested. The eclipse detection algorithm has been tested on a sample of 150,000+ X-ray lightcurves and it was able to rediscover known transits and eclipses (including that of the first extragalactic planet candidate). It has also been used by the author of this package to make new discoveries.FlaresEclipsesAstrophysics Database ConnectionNASA ADSSearch for listings which include the sourceSimple usage: only one method required (.search_ads())Upcoming features:Integration withgalaXyVizeR connectionInstallationInstall dependencies via therequirements.txtfile:pip install requirements.txtInstall thechandralcpackage via PIP:pip install chandralcFile Databases will automatically be downloaded on import of package[more details coming soon]Cite chandralcIf you usechandralcin your research, please cite it as follows:@MISC{chandralc,
	author ={{Kumar}, Sammarth},
	title = "{chandralc: Python Package for CXO Lightcurve Analysis}",
	keywords ={Software, Chandra, CXO, lightcurves},
	url ={https://github.com/sammarth-k/chandralc},
	howpublished ={https://github.com/sammarth-k/chandralc},
	year ={2021},
	month ={May},}
Package: change-base
Arbitrary Base to Arbitrary Base ConverterAllows the conversion of a value in a givenbase(a)to the corresponding value in some otherbase(b).The symbols used in both the base-systems can be provided by the user.Usage:change_base.change_base(value, initial_base, final_base, initial_base_symbols, final_base_symbols)Description:A value from a given set withbase = ais converted to the equivalent value in some otherbase = b.For example, decimal values(Base10)can be transformed into Hex(Base16)or Octal(Base8)values.Transformation is achieved by first converting to decimal equivalent and then to the final base version through the following 2 functions:base_to_decimal(val, base = 73, symbols = None)decimal_to_base(d, base, symbols = None)In thebase_to_decimalfunction,valis the original value (inputted as a string) with base =base.symbolsis a list to pass custom symbols for the system.In thedecimal_to_basefunction,drepresents the original decimal value andsymbolslist stores the symbols used for this system with base =baseThe symbols used to represent the system can be provided as custom input e.g. a value$$&$##may belong to a system with base =3and symbols#, &, $. This value can be converted to a decimal equivalent by calling:base_to_decimal("$$&$##", 3, ['#', '&', '$'])In case the symbol list is not provided, the default ordered symbol list is used up to maximum of(Base73). The 73 symbols used are (in this order):Digits(0-9),Lowercase-Letters(a-z),Uppercase-letters(A-Z),Safe-symbols[ $, -, _, ., +, !, *, ', (, ), , ]Thus, each of these symbols have a decimal equivalent = list index from0to73that is used for base conversion.The two functions are combined in the definition of functionbase_change. Thus, to change some value'val'with base'ibase'and symbol set (in order)'isymbols'(optional argument) into the equivalent value in some base'fbase'and symbol set'fsymbols'(optional argument), call the function:base_change(val, ibase, fbase, isymbols, fsymbols)Example Usages:Converting fromDecimaltoBinary:base_change('123',10,2)->'1111011' #OutputConverting fromBinarytoDecimal:base_change('1111011',2,10)->'123' #OutputConverting fromDecimaltoHex:base_change('123',10,16)->'7b'Converting fromBase5(with default symbols[0,1,2,3,4]) toBase5(custom symbols['t','w','i','s','t']):base_change('123',5,5,None,['t','w','i','s','t'])->'wis'Converting fromBase5(with custom symbols['t','w','i','s','t']) toBase10(default symbols):base_change('witsittitsisits',5,10,['t','w','i','s','t'],None)->'9697104823'Inverse of the last example:base_change('9697104823',10,5,None,['t','w','i','s','t'])->'witsittitsisits'Note:The position of symbol in custom symbol list decides its decimal equivalentDefault symbol list consists of only 73 symbols. Thus maximum base conversion with default symbols is upto Base73Since the apostrophe'sign is also usable as a default symbol, the input value strings should be enclosed with double quotesAll outputs are generated as strings
Package: change-event-service
Change Event ServiceThis service is web service that provides a RESTful API for creating, deleting and querying change events.How it Works?This project written withFlask web framework. It useflask-smorestfor REST API,Pyctuatorfor actuator endpoint andFlask-SQLAlchemyfor handle DB queries. Swagger UI documentation and API validations handled by flask-smorest itself. flask-smorest usesMarshmallowschemas for marshalling and unmarshalling objects in request and response. This schemas also used by Swagger UI.WithFlask-APScheduler, a background job started to consume change events from the queue usingPikaand persist them to the database.Environment Variables__SERVICE_MQ_HOST: RabbitMQ host__SERVICE_MQ_VHOST: RabbitMQ virtual host__SERVICE_MQ_QUEUE: RabbitMQ queue name__SERVICE_MQ_USER:  RabbitMQ user__SERVICE_MQ_PASSWORD: RabbitMQ password__SERVICE_MQ_EXCHANGE: RabbitMQ exchange (For dead letter queue feature)__SERVICE_MQ_ROUTING_KEY: RabbitMQ routing key (For dead letter queue feature)__SERVICE_SQLALCHEMY_DATABASE_URI: SQLAlchemy database URI__SERVICE_DB_TABLE_NAME: Database table name__SERVICE_API_TITLE: Swagger UI title__SERVICE_API_VERSION: API version__SERVICE_OPENAPI_URL_PREFIX: OpenAPI URL prefix__SERVICE_OPENAPI_SWAGGER_UI_PATH: Swagger UI path__SERVICE_OPENAPI_JSON_PATH: OpenAPI JSON path__SERVICE_OPENAPI_SWAGGER_UI_URL: Swagger UI Library URL__SERVICE_ACTUATOR_BASE_URI: Actuator base URI
Package: change_extension
说明批量修改文件夹内文件的扩展名如文件为 胖虎演唱.mp3 那么执行后可以变为 胖虎演唱.zip用法1终端进入项目位置终端输入python change_extension.py <文件夹路径> <新扩展名>例子cdD:\change_extensionpythonchange_extension.pyD:\audiozip用法2pip install change_extensionimportchange_extensionchange_extension.batch_change_extension('<文件夹路径> <新扩展名>')
Package: changeless
Changeless is a set of functions and objects to help convert your data
into a set stateless or immutable data objects.Typesfrom changeless.types import FancyHash, FancyModel, ImmutableHash, ImmutableModelFancy Types take a dict object and replaces the dereferencing operator
([]) with the dot operator. So the objectan_obj= FancyHash({"name":"me"})will allow us to retrieve the attribute ‘name’ withprint "the object's name: " + an_obj.name
>the object's name: mattModel Types take a Django ORM QueueSet and converts it to a comparable
api. This uses the Fancy type as a base after converting the QuerySet to
a dict. Foreign keys and many to many relationships are converted to
nested dicts and lists of dicts(respectively) to aid in the objects
behaving as similarly as possible.Note that Model Types retrieve all of data at once which includes by
default relationships directly adjacent. This might incur more queries
than expected. Choose your data carefully and scale back when necessary.FancyHash(a_dictonary)FancyModel(a_model, depth=1)ImmutableHash(a_dictonary)ImmutableModel(a_model, depth=1)Just pass the correct object into the type constructor to convert your
data.Decoratorsfrom changeless.decorators import fancy_list

@fancy_list
def get_books():
    return Book.objects.all()Place the following decorators before functions that return a Django ORM
QueueSet to convert it to the correct changeless object. Decorators are
the preferred way to use the changeless library. Using the decorators
promote readability by keeping the conversion away from the ORM call, as
well as providing an easy to way to turn the changeless conversion on
and off. Notice that the _gen decorators will return a generator that
will lazily convert each object in the list. Generators may be more
efficient for long lists.The following generators are available.* fancy_list * fancy_gen * immutable_list * immutable_genFunctionsI’ve found the following functions useful. ###fuzzyEquals### from
changeless.compare import fuzzyEqualsi_obj = FancyHash({"name":'test name',
                   'sub_dict':{'name':'sub name', 'attrib':'sub attr value'}
                  })
second_i_obj = FancyHash({"name":'test name',
                          'sub_dict':{'name':'sub name', 'attrib':'sub attr value' }})
self.assertTrue( fuzzyEquals(
     i_obj,
     second_i_obj ))fuzzyEquals will find attributes that the changeless objects have in
common and compare only that union. This also inspects nested
relationships for shared attributes. ###to_dict### from
changeless.methods import to_dict to_dict is the reverse conversion
from a base fancy_object to its dictionary representation.
Package: changeling
Changeling is about doing what you want it to. You need only set it up right. It could be a blog, a project management system suited precisely to your needs, a wiki, your own personal online office suite. All of the public pages are dynamically defined in every way possible, so that you can tweak them to do exactly what you want they way you want. All of the content is stored in a database that is structured exactly how you define it. Changeling does your way.
Package: changelly
## Changelly Exchange API Client[![License: LGPL v3](https://img.shields.io/badge/License-LGPL%20v3-blue.svg)](https://www.gnu.org/licenses/lgpl-3.0)![PyPI - Python Version](https://img.shields.io/badge/Python-3.4%20%2F%203.5%20%2F%203.6%20%2F%203.7-blue.svg)[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com)This module helps you to interact with changelly api easily from your Python3 applications.## InstallationUse pip to install the module:```pip install changelly```## Basic UsageInitialize changelly client object```from Changelly.changelly import ChangellyApiclient = ChangellyApi('apikey','apisecret')params={"from": "eth","to": "btc","amount": "1"}x=client.getExchangeAmount('1',**params)print(x)```## Documentation* The Official API documentation can be found [here](https://api-docs.changelly.com/).## ContributingFeel free to contribute to this project.