Saravanan666/pypi-org huggingface dataset:
Package: chatwoot-client
Chatwoot Client for Pythonchatwoot-clientis a simple Chatwoot API wrapper for Python.It provides an easy-to-use interface for interacting with the Chatwoot API, allowing you to perform various actions such as creating, retrieving, updating, and deleting conversations, messages, and more.InstallationTo install, simply run:pip install chatwoot-clientUsage(TO BE ADDED)Resources(TO BE ADDED)Example(TO BE ADDED)CreditsProject is influenced by and borrowed fromwootand in fact started by using it as it is, but it didn't have support for Python 3.11 and VSCode didn't recognize resources and endpoints. So I made it with a straightforward approach without using dynamic attributes.LicenseThe project is licensed under the Cooperative Non-Violent Public License v7 or later (CNPLv7+) - see theLICENSEfor details. Built for people, not corporations.
Package: chaudio
# chaudiochaudio is a python module to programmatically create music.chaudio contains audio processing utilities for converting audio, and applying effects to already generated songsLicensed under the GNU GPLv3[Installation Guide](http://chaudio.readthedocs.io/en/latest/installing.html)[Getting Started Guide](http://chaudio.readthedocs.io/en/latest/getting_started.html)## Installing[Installation Guide](http://chaudio.readthedocs.io/en/latest/installing.html)It is available on pypi, so runpip3 install chaudio.Python3 is the officially supported language, but an effort is made to be compatable with python2, so you can trypip install chaudio. Please open an [issue](https://github.com/chemicaldevelopment/chaudio/issues) if either of these fails.### From SourceClone this repo, and then runpython3 setup.py install(orpython setup.py install)## DocumentationFor documentation, usage examples, visit our [readthedocs page](http://chaudio.readthedocs.io).## Usage[Getting Started Guide](http://chaudio.readthedocs.io/en/latest/getting_started.html)### ExamplesLocated inexamples/, multiple example use cases of chaudio are shown.To run with the development version of chaudio, prepend the PYTHONPATH environment.PYTHONPATH=$PWD python3 examples/{FILE}Or, if chaudio is installed, just run:python3 examples/{FILE}#### examples/simple.pyThis creates a WAV file (simple.wav) that contains 5 seconds of the note A4 as a sin waveform.#### examples/addnoise.pyThis takes an input, and an optional output (default isaddnoise.wav).It reads in a file, adds static, then outputs the result to output.Run likepython3 examples/addnoise.py simple.wav -o simple_static.wav(assuming you’ve ranexamples/simple.py).#### examples/arrange.pyThis example shows how to create an entire song, efficiently and rubustly. The result isarranged.wav## InstallationYou need either version of python (2 and 3 work, 3 is recommended), as well as numpy, scipy, and simpleaudio.You can easily install with pip:eitherpip install chaudio, or, for python3,pip3 install chaudio
Package: chaussette
Chaussette is a WSGI server. The particularity of Chaussette is that
it can either bind a socket on a port like any other server does or
run against already opened sockets.That makes Chaussette the best companion to run a WSGI orDjangostack
under a process and socket manager, such asCircus.Quick StartRunning:chaussettestarts a very simple HTTP sample server on port 8080.Starting a WSGI application using chaussette is simply a matter of calling:chaussetteexamples.tornadoapp.wsgiappChaussette can also serve tornado (non WSGI) application:chaussette--backendtornadoexamples.tornadoapp.tornadoappThesimple_chatexample can be started as:chaussette--backendsocketioexamples.simple_chat.chat.appNote that the two previous examples are not backend agnostic, since
they are not (pure) WSGI applications.Aflaskbased pure WSGI application can be started with most
backends:chaussette--backendgeventexamples.flaskapp.appIn these examples, we start a standalone WSGI server, but the spirit of
chaussette is to be managed byCircus, as describedhttp://chaussette.readthedocs.org/en/latest/#using-chaussette-in-circusLinksThe full documentation is located at:http://chaussette.readthedocs.orgYou can reach us for any feedback, bug report, or to contribute, athttps://github.com/circus-tent/chaussetteChangelog1.3.0 - 2015-06-01Fix gevent monkey patching (pull request #67).Add a “–graceful-timeout” option (for gevent-based backends).Fix the tornado backend so that it accepts tornado’s WSGIApplication
instaces.Update documentation.Improve example applications.
Package: chaussette-backport
Chaussette is a WSGI server. The particularity of Chaussette is that
it can either bind a socket on a port like any other server does or
run against already opened sockets.That makes Chaussette the best companion to run a WSGI orDjangostack
under a process and socket manager, such asCircus.Quick StartRunning:chaussettestarts a very simple HTTP sample server on port 8080.Starting a WSGI application using chaussette is simply a matter of calling:chaussetteexamples.tornadoapp.wsgiappChaussette can also serve tornado (non WSGI) application:chaussette--backendtornadoexamples.tornadoapp.tornadoappThesimple_chatexample can be started as:chaussette--backendsocketioexamples.simple_chat.chat.appNote that the two previous examples are not backend agnostic, since
they are not (pure) WSGI applications.Aflaskbased pure WSGI application can be started with most
backends:chaussette--backendgeventexamples.flaskapp.appIn these examples, we start a standalone WSGI server, but the spirit of
chaussette is to be managed byCircus, as describedhttps://chaussette.readthedocs.io/en/latest/#using-chaussette-in-circusLinksThe full documentation is located at:https://chaussette.readthedocs.ioYou can reach us for any feedback, bug report, or to contribute, athttps://github.com/circus-tent/chaussetteChangelog1.3.0 - 2015-06-01Fix gevent monkey patching (pull request #67).Add a “–graceful-timeout” option (for gevent-based backends).Fix the tornado backend so that it accepts tornado’s WSGIApplication
instaces.Update documentation.Improve example applications.
Package: chbpm
Chbpm: BPM Adjustment ToolOverviewChbpm is a Python-based tool designed for analyzing and adjusting the tempo of music tracks. This tool is ideal for fitness enthusiasts, dancers, and anyone who needs music to maintain a consistent BPM for their activities. The primary goal is to adjust the BPM of songs to fit within a target BPM range, facilitating a consistent pace during workouts or dance routines.FeaturesBPM Analysis: Automatically analyzes the BPM of music files.BPM Adjustment: Adjusts the tempo of music tracks to a target BPM suitable for exercise or dance routines.Dual BPM Handling: For songs within a specified range, it uses the target BPM directly. For songs where double the BPM falls within the range, it adjusts to half the target BPM.File Format Support: Compatible with various audio file formats (e.g., MP3, M4A).Error Logging: Detailed logging for troubleshooting, including optional suppression of verboseffmpegmetadata output.InstallationEnsureffmpegis installed on your system.Installation inctructions.For UserspipinstallchbpmFor DevelopersInstall Pipenv:pipinstallpipenvClone this repository.gitclonehttps://github.com/dariakriukova/rhythm-is-a-runner.gitNavigate to the Project DirectoryInstall Dependencies:pipenvinstallActivate the Virtual Environment:pipenvshellUsageRun the tool from the command line, specifying the input folder and other optional parameters:python-mchbpmpath_to_music_folderCommand-Line Optionsinput_path: Path to the input music folder.-o,--output_path: Path to the output folder where adjusted music files will be saved. Defaults toadjusted.-t,--target_bpm: Optional target BPM for tempo adjustment. Defaults to180.-r,--range_percentage: Percentage for BPM range adjustment. Defaults to15%. This setting determines the
flexibility in BPM adjustment.--log: Set log level. INFO by default.--format: Convert output audio files to given format. By default keeps the original format.--ffmpeg_options: Control over the audio processing, enabling adjustments to codec, bitrate, and more.Important NoteThe arguments passed through--ffmpeg_optionsare directly supplied to FFmpeg, so it's essential to ensure they are valid and compatible with the input and output file formats being used. Refer to theFFmpeg documentationfor a comprehensive list of available options.
Package: chbs
correcthorsebatterystaplethis:http://xkcd.com/936/You can try it out athttps://correcthorsebatterystaple.waynewerner.comI don't log which passwords I generate, but if you're paranoid about security
you probably should just generate the passwords locally.This project started off using Flask. Then I realized that was overkill. I
decdied to make this server be able to run with pure Python, because there's
literally no reasonnotto.The easiest way to try it out for yourself:python3 -m pip install --user chbsThen you can run:chbs -hAnd that should tell you everything you need to know.Or, clone this repo and run:python3 chbs/server.pyAnd then connect to it:$ curl localhost:8000
correct horse battery staple$Yeah. It won't return an ending newline. That's intentional.I also decided that for funsies I should make this into a test. What is the difference between just:Single threaded server.A server usingselect.A server usingepoll.A multithreaded server.A server using asyncio.A server using an aiohttp server.My theory is that a single threaded server should be about as good as it gets.
Or possibly using epoll or select? Given the size of the data that we're
returning, I don't think that I'll get a lot of difference between any of these
servers. We shall see.The first server that I will produce will be just a single threaded server
using raw sockets andlisten(20). That seems like a reasonably large queue?
To be honest, I'm notentirelycertain how that works - in the past I've used
huge numbers or smaller numbers and didn't really see a difference.CHANGELOG0.2.2 - 2021-11-05FixedMoved wordlists to the server.py because pip installs weren't working right.0.2.0 - 2020-10-28Added--oneflag for creating a single passphrase on the command line.
Package: chck
chckDeveloper GuideSetup# create conda environment$mambaenvcreate-fenv.yml# update conda environment$mambaenvupdate-nchck--fileenv.ymlInstallpipinstall-e.# install from pypipipinstallchcknbdev# activate conda environment$condaactivatechck# make sure the chck package is installed in development mode$pipinstall-e.# make changes under nbs/ directory# ...# compile to have changes apply to the chck package$nbdev_preparePublishing# publish to pypi$nbdev_pypi# publish to conda$nbdev_conda--build_args'-c conda-forge'$nbdev_conda--mambabuild--build_args'-c conda-forge -c dsm-72'UsageInstallationInstall latest from the GitHubrepository:$pipinstallgit+https://github.com/dsm-72/chck.gitor fromconda$condainstall-cdsm-72chckor frompypi$pipinstallchckDocumentationDocumentation can be found hosted on GitHubrepositorypages. Additionally you can find
package manager specific guidelines oncondaandpypirespectively.
Package: chckn
Chckn 🐔About chicken 🍗Chicken chicken chicken chicken. Chicken chicken: chicken!Chicken chicken Doug Zongker, University of Washington, chicken chicken video
chicken:Chicken chicken chicken chicken.Chicken.Chicken chicken.Chicken chicken chicken.Chicken, chicken chicken.(Chicken chickenchicken chicken chickenchicken chicken.)Chicken chicken chicken chickenchicken.rtfd.io.
Chickenchicken chicken chicken chicken. ;-)Chicken tutorial 🥚Chicken chicken chickenchicken chickenchicken chicken:$ pip install chcknChicken chicken, chicken chicken chicken chicken.Chickenchicken.Chicken:$ chicken
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Chicken-chicken 'Chicken' Chicken-chicken "Chicken" 'Chicken'.Chicken..!How to "Chicken" 🐓Chicken chicken chicken chicken chicken chicken. Chicken chicken chicken > 3.5.
Chicken chickenchickenchicken chicken. Chicken chicken chicken chicken
chicken. Chicken chicken.Chicken:$ git clone https://github.com/ntoll/chckn.gitChicken chicken chicken chicken chicken. Chicken "virtual chicken" chicken:$ python3 -m venv chicken
$ source chicken/bin/activate
$ pip install -r requirements.txtChicken chickenchicken chicken chickenchickenchickenchickenchicken:$ make

Chicken chicken chicken chicken CHICKEN chicken. Chicken:

make clean - chicken chicken chicken chicken chicken chicken.
make tidy - chicken chicken 'chicken' chicken.
make docs - chicken CHICKEN chicken.
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make chicken - chicken CHICKEN chicken.Discuss Chicken 🐣Chicken chicken chicken chicken chicken. Chicken chicken "Chicken of Conduct".
Chicken chicken chicken chicken, chicken chicken:Chicken chicken.Chicken!Chicken chicken, chicken?Chicken chickenhttps://gitter.im/chckn/community.Changelog Chicken 🐥Chicken 1.0.1Chicken chicken PR #3 (chicken).Chicken.Chicken chicken "EGG" chicken.Chicken 1.0.0Chicken chicken chicken chicken chicken chicken chicken.Chicken "1.0" chicken "Chicken".Chicken chicken chicken chicken, chicken chicken. Chicken!"Chicken of Conduct" chicken chicken.
Package: chcko-r
chko-ris an example content package and test data forchcko.chko-ris a random mix of problems and texts.A live version is available at:https://chcko.euThis python package depends on thechckopython package,
which is not automatically installed,
because on gcloudchckoisuploaded, not installed.
Therefore locally install with:pip install --user chcko
pip install --user chcko-rThere is no need to install,
ifchckois parallel tochcko-r.A content package can add additional dependencies.
Thischcko-rdepends onschemdrawpint.
To install the dependencies without installingchcko-r,
usepip install-rrequirements.txt.Prepare content:make htmlTo run content locally withchckoinstalled:cd chcko-r
runchckoInstall content:cd chcko-r
pip install --user .Image files are compiled to/chcko-r/chcko/_images,
and copied tochcko/chcko/_imagescommon to allchckocontent when installing.
Image files need to have globally unique names across allchcko-<author_id>packages.
Use<author_id>_<problem_id>_xxxscheme,
e.g.. texfigure:: r_dg_c1.tex.Images can also be generated on the fly.
Examples:r.a3r.a4.
Package: chClassifier
Char Classifier---------Given a short phrase, train a neural network to classify it based on the characters that it contains.The trainer takes in a file of phrases (separated by new line) and a file of target values (separated by new line).To train on the sample data (parts of speech classification):```import chClassifierp = chClassifier.Trainer("sample/words", "sample/parts-of-speech")p.train([100, 100], 20, 100)p.save("sample", "example-run")```This will save a trained model with the tag 'example-run' in the sample directory. To use that model, run:```import chClassifierk = chClassifier.Classifier("sample", "example-run")print k.classify("dog")```This will return an array of tuples of original label + likelyhood that the label is correct, like so:```>> print k.classify("dog")[(u'VB', 0.050349433), (u'NN', 3.8027303)]```The higher the number, the more sure we are of the classification (`dog` is definitely a noun, for example, and probably not a verb).
Package: chcli
chcliA Terminal Client for ClickHouse with AutoCompletion and Syntax Highlighting.This project is inspired bymycli.Featureschcliis written usingprompt_toolkitandantlr4withgrammar.Auto-completion as you type for SQL keywords as well as tables, views and columns in the database.Syntax highlighting usingPygments.Pretty prints tabular data.InstallYou can install just by pip.>pipinstallchcliUsage>chcli--help
Usage:chcli[OPTIONS]ATerminalClientforClickHousewithAutoCompletionandSyntaxHighlighting.

Options:-v,--versionShowtheversionandexit.-h,--hostTEXTClickHouseserverhost.[default:127.0.0.1]-p,--portINTEGERClickHouseserverport.[default:9000]-u,--userTEXTClickHouseserveruser.[default:default]--passwordTEXTClickHouseserverpassword.[default:]--helpShowthismessageandexit.LicenseThis project is licensed under theApache-2.0License.
Package: chd
RequirementsPython 3.6or higher.InstallationpipinstallchdUsagechdurl[-ppath][-sstart_lesson][-eend_lesson][-v]positionalarguments:urlcourseurloptionalarguments:-h,--helpshowthishelpmessageandexit-pPATH,--pathPATHdownloadpath,defaultis<course-name>-sSTART,--startSTARTthelessonnumberfromwhichtostartthedownload-eEND,--endENDthelessonnumberatwhichthedownloadwillbecompleted-v,--versionprintversioninformationandexit
Package: chdimage
This small project is a binding to the chd part of the rust projectimageparsedone for its capability to access chd files decompressed bytes, even those with parents, recognize the track boundaries, and calculate their sha1 checksums.Upstream has some limitations still:Will not load hard drive chds, since it’s out of scope of the project.Will not yet read gdi chds, although that’s possible in the future.Like the upstream it depends on,chd-rsit can’t write a new chd.It is not actually a filesystem mounter, it only accesses the raw decompressed bytes and recognizes track boundaries.You can access the chd track sha1 checksums ofb.chdwith parenta.chdlike this:import chdimage
chd = chdimage.open_with_parent('b.chd', ['a.chd'])
sha1sums = [ bytes(x).hex() for x in chd.track_sha1s() ]Chd files that aren’t parents are ignored, so you can choose your own strategy to find parents:chd = chdimage.open_with_parent('b.chd', ['not_b_parent.chd', 'a.chd'])You can iterate over the track bytes like this:for x in range(0,chd.num_tracks()):
  event = None
  #tracks go from 1 to num_tracks(), 0 does not count
  print(f'track {x+1}')
  while event != Event.TRACKCHANGE and event != Event.ENDOFDISC:
    sector = chd.copy_current_sector()
    event = chd.advance_position()
    #printing bytes is useless and lossy, do something else
    print(bytes(sector).decode(errors='replace'))
Package: chdkptp.py
Python bindings forchdkptpvia an embedded, thread-safe Lua runtime (thanks to Stefan Behnel’slupa).RequirementsC compilerLua 5.2, with headerslibusb, with headerslupa, installed with the–no-luajitflagCurrently chdkptp.py only works when thelupapackage is linked to
Lua. However, by default the package links to LuaJIT, so make sure that
you install it with the–no-luajitflag.
It is best to do this viapip,beforeyou install chdkptp.py:$ pip install lupa --install-option='--no-luajit'DocumentationPlease refer to theAPI documentation on readthedocs.org
Package: chd-login
CHD Login ToolThe CHD login tool is used to simplify the simulated login when accessing the CHD portal. Just follow the steps below to
easily login with your username and password.Install PackagesWe recommend that you use the latest version to avoid unknown login failures.pipinstallchd_loginUse this ToolIf you pass theneed_detail=Trueparameter, when the login is successful, you can get the user's cookie.If you pass theneed_session=Trueparameter, when the login is successful, you can get the session, so you can direct use session to visit the site directly. Session is a requests.session() obj.fromchd_loginimportIDSClient# uid & password should match with chd portal site.client=IDSClient(login_url,need_detail=True,need_session=True)result,detail,session=client.login(uid,password)# login successifresult:pass# login failedelse:print(detail)WarningMultiple attempts to login with the same account in a short period of time will trigger a verification code. Please login manually on the CHD portal site to solve the problem.The behavior of the problem is that when you are using correct uid and password login, it returns 401 and 'check your username or password'.OthersIf you have other usage questions, please contact me directly byoren_zhang@outlook.com.
Package: chdp
CHDPCommand Handler for Discord.Py⚠ 해당 프로젝트는 AGPL-3.0 License 입니다 ⚠Download$pipinstallchdpUseCreate Main file and config.json and foldercommandsFill config.json like below{"token":"Your Token","prefix":"Your Prefix"}create a file in foldercommandsand fill it like belowclassCommand:name='ping'asyncdefrun(self,client,message,ext):awaitmessage.channel.send('pong')Run the Main fileContributeFind a bug and tell it on the Issue tab or to! Tim23#9999on discordYou can also Pull a requestLog1.0 Initial Release
Package: chd-rs-py
chd-rs-pyExtremly basic Python bindings tochd-rs.pip install chd-rs-pyUsagefromchdimportchd_openchd_file=chd_open("Test.chd")metadata=chd_file.metadata()forminmetadata:print(m.tag(),m.data())forhinrange(len(chd_file)):# read the hunk (as bytes)hunk=chd_file.hunk(h)
Package: che
CheckOverviewThe Check library is a Python-based assertion framework designed to simplify the validation process in tests. It offers a wide range of assertion methods that provide clear and informative failure messages.FeaturesComprehensive set of assertion methods for different data types and structures.Support for custom failure messages to improve debugging.Easy-to-understand method naming for better code readability.Minimalistic and lightweight design for quick integration into any project.InstallationYou can install the Check library via pip:pipinstallcheQuick StartHere is a simple example demonstrating some of the assertion methods:fromcheimportCheck# Initialize the Check instancecheck=Check()# Perform assertionscheck.equal(1,1)check.notEqual(1,2)check.isAbove(2,1)# Validate the number of assertions madecheck.assert_calls(3)DocumentationFor more detailed information on using the Check library, please refer to the official documentation.Check Docs
Package: cheader2json
cheader2jsonTake one or more c header files as input, and do a JSON dump of a portion of the libclang AST for easier processing by other
tools. This code was originally from the libclang based Python/Matlab binding generator for HELICS, but has been split out
to make it more reusable. Functionality is also provided to do a diff of two JSON files, that can be used to get a quick
overview of what has changed between releases.Installationpipinstallcheader2jsonRecommended: Install in a Python virtual environment.UsageConvert a c header file to a JSON file with a subset of the AST (excluding function bodies) and a JSON file with type information:cheader2jsonconvert<HEADER_FILE>Dump a pair of JSON files namedexample.ast.jsonandexample.types.jsonfor multiple header files, and ignoreDO_SOMETHINGmacro
(the ignore macro option can be given more than once, or IGNORED_MACROS environment variable can be set to a space separated list of
macro names to ignore):cheader2jsonconvert<HEADER_FILE1><HEADER_FILE2>--prefix=example--ignore-macro=DO_SOMETHINGDo a diff of two dumped AST JSON files:cheader2jsondiff<JSON_AST_FILE_OLD><JSON_AST_FILE_NEW>
Package: cheaders
This tool reads a C source file (.c) and generates the text for the corresponding
header file, with function declarations for any non-static function definitions
found in the provided C file.Installationpip install cheadersUsageExecute cheaders through the python interpreter as a module:python -m cheaders source_file.cExample outputThe following example shows what is generated for a sample.cfile. The
sample file is calledulist_.c, and contains the following code:Example C source fileintmyfunction(intintvar,floatfloatvar){// Do important stuffreturn0;}voidmyotherfunction(intintvar,floatfloatvar,charlong_name_variable){// Do other important stuff}The header file that will be generated, with doxygen comments enabled (the
default) looks like this:Generated header file/*
 * myfile.h
 *
 * (Description here)
 *
 */#ifndef MYFILE_H
#define MYFILE_H/**
 * (Description)
 *
 * @param   intvar      (description)
 * @param   floatvar    (description)
 *
 * @return  (description)
 */intmyfunction(intintvar,floatfloatvar);/**
 * (Description)
 *
 * @param   intvar              (description)
 * @param   floatvar            (description)
 * @param   long_name_variable  (description)
 */voidmyotherfunction(intintvar,floatfloatvar,charlong_name_variable);#endif/* MYFILE_H */