Saravanan666/pypi-org huggingface dataset:
Package: coo_utils
coo_utils works with numpy and scipy.sparse (2D only) to store
compressed multidimensional arrays both in memory and on disks. This can
DRASTICALLY reduce the space required.In reality, what is stored is a list-of-lists containing sparse matrix
nodes in the scipy.sparse.coo_matrix format. The storage format can
either be normal or differenced (helpful for same-value blocks data).Some terms used in the code:CooHD: list (or deeply nested list(s)) of scipy.sparse.coo_matrix’s (HD means higher-dimensional)nnzs: An array with the same shape as the nested lists in the cooHD (aka without the 2 coo_matrix dimensions) that gives the length of each coo_matrix (nnz) at each node of the treeRCD: A sparse array represented as a flat row-column-data matrix. Multi-dimensional shape data is recoverable using the nnzs arrayThe disk storage format uses the RCD fomat for maximum simplicity:*_rcd.npy    -  The rcd matrix stored in the .npy format (int32)*_nnzs.npy   -  The nnzs array store in .npy format (int)*_shape.txt  -  a simple text file with the full shape of the array in comma-separated plain text
Package: copads
The main aim of Collection of Python Algorithms and Data Structures (COPADS)
is to develop a compilation of Python data structures and its algorithms,
making it almost a purely developmental project. Personally, I look at this
as a re-usable collection of tools that I can use in other projects.
Therefore, this project is essentially “needs-driven”, except a core subset
of data structures and algorithms.To install, please fork or clone fromhttps://github.com/mauriceling/copads
Package: copasi-basico
BasiCOThis project hosts a simplified python interface to COPASI. While all functionality from COPASI
is exposed via automatically generated SWIG wrappers, this package aims to add a layer on top of
that, to hide most of the complexity away when calling COPASI functions.InstallationThe package works with python 3.7+, provided the following packages are installed:python-copasipandasnumpymatplotlibPyYAMLthat are freely available on pypi, they will be automatically installed when installing via setup.py.Once done, just have thebasicodirectory
in thePYTHONPATHorsys.path.Or you could directly install everything you need right from pypipip install copasi-basicofrom this git repo:pip install git+https://github.com/copasi/basico.gitUsageThe following modules are available:model_io: functionality, for creating / loading / saving models.model_info: functionality to getting / setting model elements from pandas dataframestask_timecourse: a wrapper for running time course simulationstask_parameter_estimation: a wrapper for parameter estimationtask_optimization: a wrapper for computing optimizations with arbitrary objective functionstask_steadystate: a wrapper for computing steady statestask_scan: a wrapper for parameter scans / repeatstask_sensitivities: a wrapper for computing sensitivitiescompartment_array_tools: utility for plotting and the likeDocumentation is continually updated at:https://basico.readthedocs.org/.Please use theissue trackerfor bug reports and feature requests.Run the testsbasico comes with a number of unit tests based on pytest. To run them, change to the
root directory of this project and run:python3 -m pytestthat will ensure thatbasicois in the python path, and the test run as expected. Some
tests require more data, that is not included in the repository, such as tests for PEtab
and petab select, for those, specify the environment variables to the directories where
the files are for example:PETAB_BENCHMARK_MODELS=/path/to/petab/benchmark/models
PETAB_SELECT_MODELS=/path/to/petab/select/modelsfor example:PETAB_BENCHMARK_MODELS=../Benchmark-Models-PEtab/Benchmark-Models PETAB_SELECT_MODELS=../petab_select/test_cases  python3 -m pytestAcknowledgementsThis project has been possible thanks to the BMBF funded de.NBI initiative (031L0104A):LicenseThe packages available on this page are provided under theArtistic License 2.0,
which is anOSIapproved license. This license
allows non-commercial and commercial use free of charge.
Package: copatrec
Correlation pattern recognizer (Copatrec) package.For more information, please see the example and Document notebook.How to use CopatrecTo use Copatrec, it should be either cloned from GitHub, orinstalled using the package files (pip and py providers willbe ready in the future)Recommended installationIt is recommended to install Copatrec usingpip(see below).Installing using pipTo install Copatrec, please use the following code in your terminal:pip install copatrecCloning (copying) source code:The source code is organized in a hierarchical structure to ease the creation of package files.Following convention, the source code can be found in the 'src' folder, and examples can be found in the 'examples' folder.Required packages to use CopatrecIf the package is installed from GitHub, then it would be suggestedto install the following packages (dependencies) in your system usingpipor any otherpreferred approaches.matplotlibNumPypandasscipyscikit-learnWeb application (On progress)www.copatrec.orgExamplesThe "examples" folder can be found under the GitHub repo. Its direct URL is:https://github.com/copatrec/copatrec/tree/master/examplesSoftwareX.pyAn example file with setups to reproduce paper results for SoftwareX journal.Tutorial filesThere are two files in different formats (.py and .ipynb). For a detailed tutorial on Copatrec, the Jupyterfile (Document.ipynb) is recommended.
Package: coperator
COPERATOR Usagefactory_operator usagefromcoperator.myoperatorimportfactory_operatorclassExample:"""Example."""def__init__(self,x:int)->None:"""__init__.

        :param x:
        :type x: int
        :rtype: None
        """self._x:int=self.set_x(x)defset_x(self,x:int)->int:"""set_x.

        :param x:
        :type x: int
        :rtype: int
        """returnxdefget_x(self)->int:"""get_x.

        :rtype: int
        """returnself._xdef__str__(self)->str:"""__str__.

        :rtype: str
        """returnstr(self.get_x())@factory_operator(Example,Example,Example)defop(A:Example,B:Example)->Example:"""op.

    :param A:
    :type A: Example
    :param B:
    :type B: Example
    :rtype: Example
    """returnExample(A.get_x()+B.get_x())E1:Example=Example(1)E2:Example=Example(2)E3:Example=Example(3)print(E1*op*E2*op*E3)6monad usagefromcoperator.monadimportmonaddefneg(i):return-iprint(monad("1")(int)(neg)(str)(None))print(monad("x")(int)(neg)(str)(None))deffunc1(i):returnmonad(i)(int)(neg)(str)(None)print(list(map(func1,["1",2,"z"])))'-1'
None
['-1','-2',None]Links and referencesSource code:https://gitlab.com/jecjimenezgi/coperatorLICENSEMIT LicenseCopyright (c) 2020 Jean Carlo Jimenez GiraldoPermission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.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 OR COPYRIGHT HOLDERS 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.
Package: copernic360-cli
Copernic360OverwiewCopernic360enables 6 degree-of-freedom (6DOF) motion in standard
360° VR content to allow users to move freely in scenes.  It consists of two
components: a Unity plugin; and a [Cloud API][apidoc].Every piece of content is different, which is why the Copernic360 Unity plugin
requires configuration files with metadata for your content in order to enable
6DOF support. Copernic360 provides aCloud APIto preprocess your
content, providing a configuration file that is used by the Unity plugin at
runtime.Command-line toolThe copernic360 command-line wrapsKagenova's Copernic360Cloud
API.  In short, it allows users to post 360 images and videos and get
Copernic360 configuration files back.Users first need an account with Kagenova'sCopernic360. After
installing the tool viapip, users can interact with the Copernic360 API
as follows:# get helpcopernic360--help# check user logincopernic350check-login# check user's creditscopernic350check-credit# upload image.jpg and get its configution back (config.6dof)copernic360process-contentimage.jpgconfig.6dof# list currently uploaded contentscopernic360contentsSee the command-line help for futher functionality and parameters.Note that passwords and usernames can be either given on the command-line or in
the environment variables:COPERNIC360_USERCOPERNIC360_PASSWORD
Package: copernicus-marine-client
⚠️⚠️⚠️ Thecoernicus-marine-clientPyPI package is deprecated. Please usecopernicusmarineinstead ⚠️⚠️⚠️Here is the link to the new pypi repository:https://pypi.org/project/copernicusmarine/"
Or install it using the following command:pip install copernicusmarineIf you were using this deprecated version, you may also want to delete the following folders:~/.copernicus-marine-client~/.cachier(⚠️ Be carefull with this one as it can contains other stuffs unrelated to thecopernicus-marine-clientpackage !)Reason for the deprecationThe official version 1.0.0 of the package has been released and it has been decided to rename the package tocopernicusmarine.
That way, the command will always be the same, no matter what interface you are using (python or CLI).
Package: cophi
A library for processing text datacophiis a Python library for handling, modeling and processing text corpora. You can easily pipe a collection of text files using the high-level API:corpus,metadata=cophi.corpus(directory="british-fiction-corpus",filepath_pattern="**/*.txt",encoding="utf-8",lowercase=True,token_pattern=r"\p{L}+\p{P}?\p{L}+")You can also plug theDARIAH-DKPro-Wrapperinto this pipeline to lemmatize text, or just keep certain word types.Check out the introducingJupyter notebook.Getting startedTo install the lateststableversion:$ pip install cophiTo install the latestdevelopmentversion:$ pip install --upgrade git+https://github.com/cophi-wue/cophi-toolbox.git@testingAvailable complexity measuresThere are also a plenty of complexity metrics for measuring the lexical richness of (literary) texts.Measures that use sample size and vocabulary size:Type-Token Ratio TTRGuiraud’s RHerdan’s CDugast’s kMaas’ a2Dugast’s UTuldava’s LNBrunet’s WCarroll’s CTTRSummer’s SMeasures that use part of the frequency spectrum:Honoré’s HSichel’s SMichéa’s MMeasures that use the whole frequency spectrum:Entropy SYule’s KSimpson’s DHerdan’s VmParameters of probabilistic models:Orlov’s Z
Package: copia
CopiaEstimating the survival of cultural heritage artifacts with unseen species models from ecologyCopia is a Python package that can be used for estimating the survival of artifacts from
cultural heritage, based on established unseen species models from ecology.InstallationCopia requires Python 3.6 or greater. To install Copia, execute the following command in
your terminal:pipinstallcopiaDevelopmentIf you wish to help developing Copia, download the source files from GitHub and install
the package using the following command:pipinstall-e.in the top directory ofcopia.Subsequently, runpytestfrom the same directory.DocumentationFor detailed documentation, visitcopia.readthedocs.io.EtymologyBecause this package targets so-called "abundance" data from ecology, it has been named
using the corresponding Latin termcopia. The artwork for the logo has been kindly
contributed by Dr. Lauren Fonteyn (Leiden University, NL). The depicted goat is a
mythological reference to thecornucopiaor
"horn of plenty", the legendary horn of the goat Amaltheia, who fed the infant Zeus with
her milk.MaintainersMike Kestemont & Folgert Karsdorp
Package: copied
Класс CopiedBotКласс CopiedBot позволяет скопировать ивенты, команды и префикс другого бота в своего бота на основе его айди.copy_bot_id(bot_id: int)Метод copy_bot_id принимает айди бота, который нужно скопировать. Этот метод должен быть вызван первым, чтобы скопировать ивенты, команды и префикс другого бота.copy_bot_events()Метод copy_bot_events копирует ивенты из другого бота. Этот метод должен быть вызван после copy_bot_id.copy_bot_commands(commands: Dict[str, Callable])Метод copy_bot_commands копирует команды из другого бота. Он принимает словарь, где ключи - это названия команд, а значения - это соответствующие функции-обработчики. Этот метод должен быть вызван после copy_bot_id.copy_bot_prefix()Метод copy_bot_prefix копирует префикс из другого бота. Этот метод должен быть вызван после copy_bot_id.start_bot()Метод start_bot запускает бота и подключается к Discord API. Этот метод должен быть вызван после того, как будут скопированы все необходимые данные из другого бота.Теперь давайте посмотрим, как использовать эти функции вместе, чтобы скопировать ивенты, команды и префикс другого бота в свой бот.fromcopiedimportCopiedBotfromdiscord.extimportcommands# Создаем экземпляр класса CopiedBotcopied_bot=CopiedBot()# Копируем айди бота, который нужно скопироватьcopied_bot.copy_bot_id(COPIEDBOTID)# Копируем ивенты из другого ботаcopied_bot.copy_bot_events()# Копируем команды из другого ботаcopied_bot.copy_bot_commands({'command1':handle_command1,'command2':handle_command2,# ...})# Копируем префикс из другого ботаcopied_bot.copy_bot_prefix()# Создаем ботаbot=commands.Bot(command_prefix=copied_bot.prefix)# Регистрируем команды, которые мы скопировалиcopied_bot.start_bot(bot)# Запускаем ботаbot.run('TOKEN')
Package: copier-example
copier_exampleThis is where you should write a short paragraph that describes what your module does,
how it does it, and why people should use it.PyPIpip installcopier-exampleSource codehttps://github.com/coretl/copier-exampleDocumentationhttps://coretl.github.io/copier-exampleReleaseshttps://github.com/coretl/copier-example/releasesThis is a test repo.This is where you should put some images or code snippets that illustrate
some relevant examples. If it is a library then you might put some
introductory code here:fromcopier_exampleimport__version__print(f"Hello copier_example{__version__}")Or if it is a commandline tool then you might put some example commands here:$ python -m copier_example --versionTODO[x] Use pyright instead of mypy[x] Use[x] Use GH pages publishing[x] Split up CI[x] Slim down devcontainer[x] Use dev constraints everywhere[x] Investigate ruff checks and fixes[x] Add pre-commit for dev constraints[ ] Get docs from releases and add them too[ ] MD-ify docs[ ] Run repo review[ ] Fix broken docs links[ ] Group dependabot alerts[ ] Delete favicon[ ] Add copier to pyprojectSeehttps://coretl.github.io/copier-examplefor more detailed documentation.
Package: copier_template_tester
copier-template-testerParametrize copier templates to test for syntax errors, check the expected output, and to check against copier versions.Note thatcttonly tests thecopier copyoperation and doesn't check theupdatebehavior and any version-specific logic that your template may contain because of how quickly those tests become complex.UsageConfiguration FileWhen creating a copier template repository, I recommend following the nested"subdirectory" approachso that the directory looks like this:└──template_dir
│└──{{_copier_conf.answers_file}}.jinja
├──README.md
├──copier.yml
└──ctt.tomlCreate a newctt.tomlfile in the top-level directory of your copier repository. Populate the file to look like the below example.# Specify shared data across all 'output' destinations# Note that the copier.yml defaults are used whenever the key is not set in this file[defaults]project_name="placeholder"copyright_year=2022# Parametrize each output with a relative path and optionally any values to override[output.".ctt/defaults"][output.".ctt/no_all"]package_name="testing-no-all"include_all=falsePre-Commit HookFirst, add this section to your.pre-commit-config.ymlfile:repos:-repo:https://github.com/KyleKing/copier-template-testerrev:mainhooks:-id:copier-template-testerInstall and update to the latest revision:pre-commitautoupdateThe run withpre-commit:pre-commitrun--all-filescopier-template-testerpipxYou can also trycttas a CLI tool by installing withpipx:pipxinstallcopier-template-testercd~/your/copier/project
cttMore ExamplesFor more example code, see thescriptsdirectory or thetests.Project StatusSee theOpen Issuesand/or theCODE_TAG_SUMMARY. For release history, see theCHANGELOG.ContributingWe welcome pull requests! For your pull request to be accepted smoothly, we suggest that you first open a GitHub issue to discuss your idea. For resources on getting started with the code base, see the below documentation:DEVELOPER_GUIDESTYLE_GUIDECode of ConductWe follow theContributor Covenant Code of Conduct.Open Source StatusWe try to reasonably meet most aspects of the "OpenSSF scorecard" fromOpen Source InsightsResponsible DisclosureIf you have any security issue to report, please contact the project maintainers privately. You can reach us atdev.act.kyle@gmail.com.LicenseLICENSE
Package: copilotcleaner
Copilot CleanerA simple command line tool to clean all the comments from Python project that are used by GitHub's copilot to generate code. These comments are not useful mostly and manual cleaning of these comments from large codebases is not an easy task, hence this tool.This works only withPythonprojects as of now. Support for other languages will be added soon.Usageuser@programmer~:$ccc-dir<path-to-project>This cleans all comments that start with "#$", so instead of just # you have to start copilot comments with "#$".
Package: copilot-import
Copilot ImporterWhy write code when you can import it directly from GitHub Copilot?What is Copilot Importer?Thecopilotpython module will dynamically generate any function imported
by leveraging the GitHub Copilot service.How do I use Copilot Importer?You can install copilot-importer via pip (e.g.pip install copilot-importer).Additionally and importantly, you need a GitHub Copilot API token. SeeHow do I get an authentication token.Once you have your token, set it to the environment variableGITHUB_COPILOT_TOKEN.exportGITHUB_COPILOT_TOKEN=xxxxxxxxxxxxxxxxxxxxFinally, before the dynamic importing feature is enabled, you must run thecopilot.installmethod.# Enable copilot importerfromcopilotimportinstallinstall()After all of the above has been taken care of, you should be able to import
anything you want directly from GitHub Copilot:>>>fromcopilotimportinstall>>>install()>>>fromcopilotimportbase64_encode>>>base64_encode(b"test")b'dGVzdA=='>>>fromcopilotimportbase64_decode>>>base64_decode(base64_encode(b"test"))b'test'>>>fromcopilotimportquicksort>>>quicksort([5,2,3,4])[2,3,4,5]You can also output the code of imported functions like so:>>>fromcopilotimportsay_hello>>>print(say_hello._code)defsay_hello():print("Hello, World!")How do I get an authentication token?To obtain an authentication token to the Copilot API, you will need a GitHub
account with access to Copilot.copilot-importerhas an authentication CLI built-in, which you can use to
fetch your copilot authentication token. To star the authentication process
after installingcopilot-importer, simply runcopilot-authORpython-mcopilotORpython-c"from copilot.authflow import run; run()"Once you have started the authentication flow, you will be prompted to enter
a device authorization code tohttps://github.com/login/device.After entering the correct code, you will be asked to authorizeGitHub for VSCodeto access your account. This is expected, as the Copilot
API is only accessible to the VSCode plugin.Once approved, you should see a Copilot access token printed to the terminal.Example:$copilot-authInitializing a login session...YOUR DEVICE AUTHORIZATION CODE IS: XXXX-XXXXInput the code to https://github.com/login/device in order to authenticate.Polling for login session status until 2021-07-17T17:26:01.618386Polling for login session status: authorization_pendingPolling for login session status: authorization_pendingSuccessfully obtained copilot token!YOUR TOKEN: XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX:XXXXXXXXXX:XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXEXPIRES AT: 2021-07-17T21:21:39You can add the token to your environment e.g. withexport GITHUB_COPILOT_TOKEN=XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX:XXXXXXXXXX:XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXCreditsInspiration taken fromstack-overflow-importGitHub for providing GitHub Copilot.molenzwiebelfor working out the Copilot
API and helping with the code.akxfor giving a quick review of the code.
Package: copinicoos
CopinicoosCopinicoos is aCopernicussatellite image download manager.Copinicoos can ...Automate the download of all results in a search query.Download in parallel processes, for faster downloads.Manage polling for offline products.Stop and resume downloads, anytime!Installpip install copinicoosUsageInteractive ModeTo launch,py -m copinicoosAnd then follow on-screen prompt:Enter Download Directory. Where products will be downloaded to. Entering nothing will default to current directory.Enter number of Corpernicus accounts. Each account will initialise 2 parallel download processes.Authenticate accounts by entering login credentials.Enter query. This can be obtained from Copernicus Open HubRequest Done: ( ... ). Just copy that whole string.Enter Polling Interval. Entering nothing will use default.Enter offline product download retries. Entering nothing will use default.Resume downloadAgain, launchpy -m copinicoosAnd then follow on-screen prompt:Enter download directory containingcopinicoos_logs. Or, if current working directory hascopinicoos_logs, entering nothing will resume download from current working directory's savepoint. Savepoints are stored insidecopinicoos_logs.Agree to resume downloadEnter Polling Interval. Entering nothing will use default.Enter offline product download retries. Entering nothing will use default.Argparse ModeThis mode is so that copinicoos can be called from a script.All options:py -m copinicoos <subcommand> -d <download-location> -r <offline-retries> -p <polling-interval>Subcommand:resumefreshresumepy -m copinicoos resumeResume download from savepoint in current working directory.py -m copinicoos resume -d <download directory>Resume download from savepoint in<download directory>.freshpy -m copinicoos fresh <query> <credentials>Start a fresh download.Input can be read from a text file by affixing@to file name eg.py -m copinicoos fresh @query.txt @secrets.jsoneg. Insidequery.txt( footprint:"Intersects(POLYGON((91.45532862800384 22.42016942838278,91.34620270146559 22.43895934481047,91.32598614177974 22.336847270362682,91.4350291249018 22.31804599405974,91.45532862800384 22.42016942838278)))" ) AND ( (platformname:Sentinel-1 AND producttype:GRD))eg. Insidesecrets.json{
    "u1":"username1",
    "p1":"password1",
    "u2":"username2",
    "p2":"password2"
}Note:"has to be escaped, ie\", if parsing directly to the cmd.For more details:py -m copinicoos --helpLogsLogs can be found in a folder namedcopinicoos_logsin the same directory where products are downloaded to. Manually deletingcopinicoos_logswill restart the download.A summary of finished downloads can be found incopinicoos_logs\WorkerManager.log. Resume points are saved in<InstanceName>_progress.txt