Saravanan666/pypi-org huggingface dataset:
Package: cesloi
一个简易(?)，基于`mirai-api-httpv2<https://github.com/project-mirai/mirai-api-http>`__
的 Python SDK。本项目适用于 mirai-api-http 2.0 以上版本。项目仍处于开发阶段，部分内容可能会有较大改变注: mirai-api-http 需要启用ws adapter和http adapter文档Cesloi暂时的文档安装pip installarclet-cesloi简单的开始通常版本fromarclet.cesloi.bot_clientimportCesloifromarclet.cesloi.model.relationimportFriendfromarclet.cesloi.communicate_with_mahimportBotSessionfromarclet.cesloi.message.alconnaimportAlconna,Arpamar,AlconnaParserbot=Cesloi(bot_session=BotSession(host="http://localhost:8080",account=1234567890,verify_key="INITKEYWylsVdbr"),debug=False)@bot.register("FriendMessage",decorators=[AlconnaParser(alconna=Alconna(command="Hello"))])asyncdeftest(app:Cesloi,friend:Friend,result:Arpamar):awaitapp.send_with(friend,"Hello, World!")ifresult.matched:awaitapp.send_with(friend,nudge=True)bot.start()使用插件的版本Inmain.py:fromarclet.cesloi.bot_clientimportCesloifromarclet.cesloi.communicate_with_mahimportBotSessionbot=Cesloi(bot_session=BotSession(host="http://localhost:8080",account=1234567890,verify_key="INITKEYWylsVdbr"),debug=False)bot.install_plugins("test_plugins")bot.start()Intest_plugins/example_plugin.py:fromarclet.cesloi.bot_clientimportCesloifromarclet.cesloi.model.relationimportFriendfromarclet.cesloi.message.alconnaimportAlconna,Arpamar,AlconnaParserfromarclet.cesloi.pluginimportBellidinasbd@bd.model_register("FriendMessage",decorators=[AlconnaParser(alconna=Alconna(command="Hello"))])asyncdeftest(app:Cesloi,friend:Friend,result:Arpamar):awaitapp.send_with(friend,"Hello, World!")ifresult.matched:awaitapp.send_with(friend,nudge=True)未来开发计划一期计划- [STRIKEOUT:CommandAnalysis，
一个抽象的命令/命令参数处理器] (已实现) - [STRIKEOUT:TimeScheduler，
一个根据时间选择是否执行目标函数的容器](已实现) -
[STRIKEOUT:PluginManager， 不局限于在一个文件中运行方法] (已实现)二期计划- Interrupt, 中断处理 -
[STRIKEOUT:Decorator，用户自定义的处理器] (已实现)鸣谢&相关项目这些项目也很棒, 去他们的项目页看看, 点个Star以鼓励他们的开发工作, 毕竟没有他们也没有Cesloi.特别感谢`mamoe<https://github.com/mamoe>`__
给我们带来这些精彩的项目: -`mirai<https://github.com/mamoe/mirai>`__: 一个高性能,
高可扩展性的 QQ 协议库 -`mirai-console<https://github.com/mamoe/mirai-console>`__:
一个基于mirai开发的插件式可扩展开发平台 -`mirai-api-http<https://github.com/project-mirai/mirai-api-http>`__:
为本项目提供与mirai交互方式的mirai-console插件`GraiaProject<https://github.com/GraiaProject>`__ 下的项目: -`Broadcast Control<https://github.com/GraiaProject/BroadcastControl>`__:
本项目关于参数解析与事件循环的的[STRIKEOUT:解剖]学习对象。 -`Application<https://github.com/GraiaProject/Application/>`__:
本项目的通用功能的[STRIKEOUT:解剖]学习与参考对象。 -`Ariadne<https://github.com/GraiaProject/Ariadne/>`__:
本项目关于网络部分的学习与参考对象。许可证`GNU AGPLv3<https://choosealicense.com/licenses/agpl-3.0/>`__
是本项目的开源许可证.
Package: cesnet-datazoo
The goal of this project is to provide tools for working with large network traffic datasets and to facilitate research in the traffic classification area. The core functions of thecesnet-datazoopackage are:A common API for downloading, configuring, and loading of three public datasets of encrypted network traffic.Extensive configuration options for:Selection of train, validation, and test periods.Selection of application classes and splitting classes betweenknownandunknown.Feature scaling.Built on suitable data structures for experiments with large datasets. There are several caching mechanisms to make repeated runs faster, for example, when searching for the best model configuration.Datasets are offered in multiple sizes to give users an option to start the experiments at a smaller scale (also faster dataset download, disk space, etc.). The default is theSsize containing 25 million samples.DatasetsThe package is able to handle the following datasets:NameCESNET-TLS22CESNET-QUIC22CESNET-TLS-Year22ProtocolTLSQUICTLSPublished in202220232023Collection duration2 weeks4 weeks1 yearCollection period4.10.2021 - 17.10.202131.10.2022 - 27.11.20221.1.2022 - 31.12.2022Application count191102180Available samples141720670153226273507739073Available dataset sizesXS, S, M, LXS, S, M, LXS, S, M, LCitehttps://doi.org/10.1016/j.comnet.2022.109467https://doi.org/10.1016/j.dib.2023.108888Zenodo URLhttps://zenodo.org/record/7965515https://zenodo.org/record/7963302Related papershttps://doi.org/10.23919/TMA58422.2023.10199052InstallationInstall the package from pip with:pipinstallcesnet-datazooor for editable install with:pipinstall-egit+https://github.com/CESNET/cesnet-datazooExamplesInitialize dataset to create train, validation, and test dataframesfromcesnet_datazoo.datasetsimportCESNET_QUIC22fromcesnet_datazoo.configimportDatasetConfig,AppSelectiondataset=CESNET_QUIC22("/datasets/CESNET-QUIC22/",size="XS")dataset_config=DatasetConfig(dataset=dataset,apps_selection=AppSelection.ALL_KNOWN,train_period_name="W-2022-44",test_period_name="W-2022-45",)dataset.set_dataset_config_and_initialize(dataset_config)train_dataframe=dataset.get_train_df()val_dataframe=dataset.get_val_df()test_dataframe=dataset.get_test_df()TheDatasetConfigclass handles the configuration of datasets, and callingset_dataset_config_and_initializeinitializes train, validation, and test sets with the desired configuration.
Data can be read into Pandas DataFrames as shown here or via PyTorch DataLoaders. SeeCesnetDatasetreference.See more examples in thedocumentation.PapersDataZoo: Streamlining Traffic Classification ExperimentsJan Luxemburk and Karel HynekCoNEXT Workshop on Explainable and Safety Bounded, Fidelitous, Machine Learning for Networking (SAFE), 2023AcknowledgementsThis project was supported by the Ministry of the Interior of the Czech Republic, grant No. VJ02010024: Flow-Based Encrypted Traffic Analysis.
Package: cesnet-openid-remote
CESNET OIDC Auth backend for OARepoThis remote backend is appropriate for e.g. a SPA application which communicates
with Invenio via REST calls. It also manages mapping of external CESNET (Perun) groups
onto internal Invenio roles and Invenio user-role synchronization using this mapping.InstallationCesnet OpenID Remote is on PyPI so all you need is:$pipinstallcesnet-openid-remoteThen run the following to ensurecesnet_groupandcesnet_group_rolemapping database tables
are created:$invenioalembicupgradeheadsConfigurationRegister a new application with CESNET OIDC Provider. When registering the
application ensure that theRedirect URIpoints to:https://<my_invenio_site>:5000/api/oauth/authorized/eduid/Grab theClient IDandClient Secretafter registering the application
and add them to your ENVIRONMENT (.env):OPENIDC_KEY=*ClientID*OPENIDC_SECRET=*ClientSecret*Now access the login page from your SPA using CESNET OAuth:window.location="https://<my_invenio_site>:5000/api/oauth/login/eduid?next=<my_next_page>";By default the CESNET module will try first look if a link already exists
between an eduID account and a user. If no link is found, it will be created.
Any external Perun groups will be automatically linked to invenio roles on
each login.
For more details you can play with a :doc:working example <examplesapp>.If you wish to prevent this module from managing (adding/removing users to/from role)
certain Invenio roles, configure such roles in:OAUTHCLIENT_CESNET_OPENID_PROTECTED_ROLES=['admin']"""Role names that shouldn't be managed/(un)assigned to users by this extension."""CLITo manage CESNET group to Invenio Role mappings you can use the following CLI command group:$ invenio cesnet:groups --help
Usage: invenio cesnet:group [OPTIONS] COMMAND [ARGS]...

  Management commands for CESNET external group mappings.

Options:
  --help  Show this message and exit.

Commands:
  add     Add a CESNET group to Invenio Role.
  create  Create an external CESNET group.
  list    List external CESNET groups.
  remove  Remove a CESNET group from an Invenio Role.CustomizationTo customize group handling and validation, refer to your custom validation and parse
functions using the following config values:OAUTHCLIENT_CESNET_OPENID_GROUP_VALIDATOR='cesnet_openid_remote.groups.validate_group_uri'"""Function used to validate external group URI."""OAUTHCLIENT_CESNET_OPENID_GROUP_PARSER='cesnet_openid_remote.groups.parse_group_uri'"""Function used to parse external group URI to (UUID, extra_data) pair."""Further documentation is available onhttps://cesnet-openid-remote.readthedocs.io/Copyright (C) 2021 CESNET.CESNET-OpenID-Remote is free software; you can redistribute it and/or
modify it under the terms of the MIT License; see LICENSE file for more
details...
Copyright (C) 2021 CESNET.CESNET-OpenID-Remote is free software; you can redistribute it and/or
modify it under the terms of the MIT License; see LICENSE file for more
details.ChangesVersion 0.1.0 (released TBD)Initial public release.
Package: cesp
cespConverts blank space to underscore and other characters to avoid problemsGetting StartedThe easiest way to usecespis to download the .exe file onrelease pages.
After downloading it, open CMD or PowerShell and executecesp.exe --helpto see the available options.ContributingFeel free to contribute anyway you want to :)AuthorsMarcus Bruno Fernandes Silva-marcusbfs@gmail.comLicenseThis project is licensed under the MIT License - see theLICENSE.mdfile for details
Package: cetem-publico
cetem-publicois a Python wrapper for the CETEMPublico corpus. It
takes care of downloading, storing and importing the corpus into NLTK.THIS IS STILL A WORK IN PROGRESS, API MIGHT BREAK WITHOUT WARNING.InstallingInstall and update usingpip:pip install [--user] cetem-publicoA Simple ExampleimportCETEMPublicocp=CETEMPublico.load()# loads a small 10KB sample# orcp=CETEMPublico.load(full=True)# loads the full 12GBprint(cp.tagged_sents())AcknowledgementsThis module only exists thanks to thePubliconewspaper and the team responsible for theCETEMPublicocorpus.Bugs and stuffOpen aGitHub issueor, preferably, send me a pull request.LicenseMIT
Package: ceto
Parens/call expression language transpiled to c++20. “Python” with 2 parentheses moved or inserted (with extra C++ syntax). Codegen based onhttps://github.com/lukasmartinelli/py14with additions e.g. implicit make_shared/unique, checked autoderef via ‘.’, swiftish lambda capture, implicit move from last use of unique, const by default, extra CTAD!
Package: cetus-cearcher
Cetus CearcherUnofficial CLI tool to query the Cetus API maintained by SparkIT Solutions.InstallationClone the repo and useTyper CLIto runorpip install cetus-cearcherOnce installed, you'll need to create a file namedconfig.pyin thecetusdirectory and declare two variables:VariableValueapi_urlAPI server including protocol ( i.e.https://example.com)api_keyAPI key obtained from the portalUsage$cetus[OPTIONS]COMMAND[ARGS]...Options:--install-completion: Install completion for the current shell.--show-completion: Show completion for the current shell, to copy it or customize the installation.--help: Show this message and exit.Commands:example: Show example result datasearch: Search Cetuscetus exampleShow example result dataUsage:$cetusexample[OPTIONS]INDEX:[dns|certstream]Arguments:INDEX:[dns|certstream]: [required]Options:--raw: Print raw output instead of pretty printed  [default: False]--help: Show this message and exit.cetus searchSearch CetusUsage:$cetussearch[OPTIONS]COMMAND[ARGS]...Options:--help: Show this message and exit.Commands:certstream: Search the Cetus Certstream indexdns: Search the Cetus DNS indexcetus search certstreamSearch the Cetus Certstream indexUsage:$cetussearchcertstream[OPTIONS]QUERYArguments:QUERY: Lucene formatted query.  [required]Options:--start [%Y-%m-%d|%Y-%m-%dT%H:%M:%S|%Y-%m-%d %H:%M:%S]: Beginning of search range. Required.  [required]--end [%Y-%m-%d|%Y-%m-%dT%H:%M:%S|%Y-%m-%d %H:%M:%S]: End of search range. If omitted, end == now  [default: 2021-06-10T17:11:20]--raw: Print raw output instead of pretty printed  [default: False]--metadata: Include metadata in output  [default: False]--help: Show this message and exit.cetus search dnsSearch the Cetus DNS indexUsage:$cetussearchdns[OPTIONS]QUERYArguments:QUERY: Lucene formatted query.  [required]Options:--start [%Y-%m-%d|%Y-%m-%dT%H:%M:%S|%Y-%m-%d %H:%M:%S]: Beginning of search range. Required.  [required]--end [%Y-%m-%d|%Y-%m-%dT%H:%M:%S|%Y-%m-%d %H:%M:%S]: End of search range. If omitted, end == now  [default: 2021-06-10T17:11:20]--raw: Print raw output instead of pretty printed  [default: False]--metadata: Include metadata in output  [default: False]--help: Show this message and exit.
Package: cev
Comparative Embedding Visualization withcevcevis an interactive Jupyter widget for comparing a pair of 2D embeddings with shared labels.Its novel metric allows to surface differences in label confusion, neighborhood composition, and label size.The figure shows data fromMair et al. (2022)that were analyzed withGreene et al.'s (2021) FAUST method.The embeddings were generated withGreene et al.'s (2021) annotation transformationandUMAP.cevis implemented withanywidgetand builds uponjupyter-scatter.InstallationWarning:cevis new and under active development. It is not yet ready for production and APIs are subject to change.pipinstallcevGetting Startedimportpandasaspdfromcev.widgetsimportEmbedding,EmbeddingComparisonWidgetumap_embedding=Embedding.from_ozette(df=pd.read_parquet("../data/mair-2022-tissue-138-umap.pq"))ozette_embedding=Embedding.from_ozette(df=pd.read_parquet("../data/mair-2022-tissue-138-ozette.pq"))umap_vs_ozette=EmbeddingComparisonWidget(umap_embedding,ozette_embedding,titles=["Standard UMAP","Annotation-Transformed UMAP"],metric="confusion",selection="synced",auto_zoom=True,row_height=320,)umap_vs_ozetteSeenotebooks/getting-started.ipynbfor the complete example.DevelopmentFirst, create a virtual environment with all the required dependencies. We highly recommend to usehatch, which installs and sync all dependencies frompyproject.tomlautomatically.hatchshellAlternatively, you can also useconda.condaenvcreate-ncevpython=3.11
condaactivatecevNext, installcevwith all development assets.pipinstall-e".[notebooks,dev]"Finally, you can now run the notebooks with:jupyterlabCommands CheatsheetIf usinghatchCLI, the following commands are available in the default environment:CommandActionhatch run fixFormat project withblack .and apply linting withruff --fix .hatch run fmtFormat project withblack .and apply linting withruff --fix .hatch run checkCheck formatting and linting withblack --check .andruff ..hatch run testRun unittests withpytestin base environment.hatch run test:testRun unittests withpytestin all supported environments.Alternatively, you can devlopcevby manually creating a virtual environment and managing
dependencies withpip.Our CI linting/formatting checks are configured withpre-commit.
We recommend installing the git hook scripts to allowpre-committo run automatically ongit commit.pre-commitinstall# run this once to install the git hooksThis will ensure that code pushed to CI meets our linting and formatting criteria. Code that does
not comply will fail in CI.Releasereleases are triggered via tagged commitsgit tag -a vX.X.X -m "vX.X.X"
git push --follow-tagsLicensecevis distributed under the terms of theApache License 2.0.
Package: ceveri
CeVeri is a library that aims to translate text-based data collected mainly in western languages to under-resourced languages with the Google Translate API, thus preventing the skewed distribution that occurs in natural language processing studies.Change Log1.0.0 (28/07/2022)Stable version.Bug fixes.0.3.0 (27/07/2022)Supports .xlsx, .json, .txt, .csv, .xml, .pkl, .docx files.0.2.0 (26/07/2022)CeVeri now measures the execution time of the translation.Bug fixes.Supports .xlsx, .json, .txt, .csv, .xml files.0.1.0 (25/07/2022)First release.Trial version.Supports .xlsx, .json, and .txt files.
Package: ceviche
cevicheElectromagnetic Simulation Tools + Automatic Differentiation.  Code for paperForward-Mode Differentiation of Maxwell's Equations.What is ceviche?cevicheprovides two core electromagnetic simulation tools for solving Maxwell's equations:finite-difference frequency-domain (FDFD)finite-difference time-domain (FDTD)Both are written innumpy/scipyand are compatible with theHIPS autograd package, supporting forward-mode and reverse-mode automatic differentiation.This allows you to write code to solve your E&M problem, and then use automatic differentiation on your results.As a result, you can do gradient-based optimization, sensitivity analysis, or plug your E&M solver into a machine learning model without having to go through the tedious process of deriving your derivatives by hand.ExamplesThere is a comprehensive ceviche tutorial available atthis linkwith several ipython notebook examples:Running FDFD simulations in ceviche.Performing inverse design of a mode converter.Adding fabrication constraints and device parameterizations.Inverse design of a wavelength-division multiplexer and advanced topics.There are also a few examples in theexamples/*directory.InstallationThere are many ways to installceviche.The easiest is bypip install cevicheBut to install from a local copy, one can instead dogit clone https://github.com/twhughes/ceviche.git
pip install -e ceviche
pip install -r ceviche/requirements.txtfrom the main directory.Alternatively, just download it:git clone https://github.com/twhughes/ceviche.gitand then import the package from within your python scriptimportsyssys.path.append('path/to/ceviche')Package StructureCevicheThecevichedirectory contains everything needed.To get the FDFD and FDTD simulators, import directlyfrom ceviche import fdtd, fdfd_ez, fdfd_hzTo get the differentiation, importfrom ceviche import jacobian.constants.pycontains some constantsEPSILON_0,C_0,ETA_0,Q_E, which are needed throughout the packageutils.pycontains a few useful functions for plotting, autogradding, and various other things.optimizers.pycontains optimizer functions for doing inverse design.viz.pyare functions that help with plotting fields and sructures.modes.pycontains a mode sorter (WIP) that can be used to create waveguide mode profiles for the simulation, for example.ExamplesThere are many demos in theexamplesdirectory, which will give you a good sense of how to use the package.TestsTests are located intests.  To run,cdintotestsandpython -m unittestto run all orpython specific_test.pyto run a specific one.  Some of these tests involve visual inspection of the field plots rather than error checking on values.To run all of the gradient checking functions, runchmod +x test/test_all_gradients.sh
tests/test_all_gradients.shCreditsIf you use this for your research or work, please cite@article{hughes2019forward,
  title={Forward-Mode Differentiation of Maxwell’s Equations},
  author={Hughes, Tyler W and Williamson, Ian AD and Minkov, Momchil and Fan, Shanhui},
  journal={ACS Photonics},
  volume={6},
  number={11},
  pages={3010--3016},
  year={2019},
  publisher={ACS Publications}
}Our logo was created by@nagilmer
Package: cevir
#Python lower ve upper string fonksiyonlarına zaten sahiptir. Fakat Python 3.12 versiyonuna gelmiş olmasına rağmen
#hala lower ve upper fonksiyonları utf-8 mantığıyla değil ascii mantığıyla çalışmakta ve harf dönüşümleri Türkçe için
#hatalı olabilmektedir. Bu paket ise bu derdi ortadan kaldırmaya yöneliktir.
##Bu python paketi şu şekilde kullanılır:import ceviryazi = "ÇEMİŞGEZEK"
print(cevir.lower(yazi)) # Sonuç = çemişgezekyazi2 = "çemizgezek"
print(cevir.upper(yazi)) # Sonuç = ÇEMİŞGEZEKYA DAfrom cevir import lower,upperyazi = "ÇEMİŞGEZEK"
print(lower(yazi)) # Sonuç = çemişgezekyazi2 = "çemizgezek"
print(upper(yazi)) # Sonuç = ÇEMİŞGEZEK
Package: cevlib
cevlibinofficial python library for cev.eu (NOT affiliated)Terms of Useplease refer tocev.eu's Terms of UseThe Owner undertakes its utmost effort to ensure that the content provided in this Application infringes no applicable legal provisions or third-party rights. However, it may not always be possible to achieve such a result.
In such cases, without prejudice to any legal prerogatives of Users to enforce their rights, Users are kindly asked to preferably report related complaints by opening an issue.InstallpipinstallcevlibLive DemoCEV Nextmakes use of exactly this library and displays the available information in a beautiful UI.Try it outQuick StartContactIn case of legal complaints or other comments, you can contact me (the owner of this repository) via email:info@cev-nex.tk
Package: cexbot
## cexbotA bot for the cex.io cryptocurrency mining marketplace*this is a really early version, recommend you check updates frequently*## Signup1. Go to [cex.io](https://cex.io/r/0/nikcub/0/)2. Click signup3. Fill out form, confirm etc.4. Once signed up go to https://www.cex.io/trade/profile5. Scroll down to API Access6. *Optional* enter your IP address7. Check all API access permission boxes8. Click 'generate'9. Copy the key and secret (see Config section)10. Click 'activate'11. Click the link in the activation email to confirm API access## InstallThe easiest way to install is with `pip`, it will download the package, build it and place `cexbot-cli` in your path. If you don't have `pip` on yourmachine see ["How do I install pip on OS X"](http://stackoverflow.com/questions/17271319/installing-pip-on-mac-os-x) (*tl;dr: `sudo easy_install pip` or `brew install python`*)`pip install cexbot`## Dev Install`git clone --depth=0 https://github.com/nikcub/cexbot.git``pip install -r requirements.txt`## Configcexbot needs to know your username, API key and secret.`./cexbot-cli genconfig`will generate a blank config file at `cex.cnf`. Edit the file and fill in `username`, `key` and `secret`## Example Config```ini[auth]username = userapikey = keysecret = secret```## Usagesee`./cexbot-cli -h`new features being added all the time.see`./cexbot-cli listtasks`## UpdateUpdate frequently, new features being added all the time.`./cexbot-cli update`