Saravanan666/pypi-org huggingface dataset:
Package: cag
Welcome to the Corpus Annotation Graph Builder(CAG)cagis a Python Library offering an architectural framework to employ the build-annotate pattern when building Graphs.Official Documentation.Corpus Annotation Graph builder (CAG)is anarchitectural frameworkthat employs thebuild-and-annotatepattern for creating a graph. CAG is built on top ofArangoDBand its Python drivers (PyArango). Thebuild-and-annotatepattern consists of two phases (see Figure below): (1) data is collected from different sources (e.g., publication databases, online encyclopedias, news feeds, web portals, electronic libraries, repositories, media platforms) and preprocessed to build the core nodes, which we callObjects of Interest. The component responsible for this phase is theGraph-Creator. (2) Annotations are extracted from the OOIs, and corresponding annotation nodes are created and linked to the core nodes. The component dealing with this phase is theGraph-Annotator.This framework aims to offer researchers a flexible but unified and reproducible way of organizing and maintaining their interlinked document collections in a Corpus Annotation Graph.InstallationDirect install via pipThe package can also be installed directly via pip.pip install cagThis will allow you to use the modulecagfrom any python script locally. The two main packages arecag.frameworkandcag.view_wrapper.Manual cloningClone the repository, go to the root folder and then run:pip install -e .CitationPlease cite us in case you use CAG@inproceedings{el-baff-etal-2023-corpus,
  title = "Corpus Annotation Graph Builder ({CAG}): An Architectural Framework to Create and Annotate a Multi-source Graph",
  author = "El Baff, Roxanne  and
    Hecking, Tobias  and
    Hamm, Andreas  and
    Korte, Jasper W.  and
    Bartsch, Sabine",
  booktitle = "Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
  month = may,
  year = "2023",
  address = "Dubrovnik, Croatia",
  publisher = "Association for Computational Linguistics",
  url = "https://aclanthology.org/2023.eacl-demo.28",
  pages = "248--255"
}UsageAfter the installation, a project scaffold can be created with the commandcag start-projectGraph Creation [jupyter notebook]Graph Annotation [jupyter notebook]Zenodo refsv1.5.17v1.5.0v1.4.0
Package: cage-api
Cage - remote file access systemRemote file access on computers with installed Cageserver software.Cage system supports all major file operations (create, open, delete, read, write etc.)
by exchanging transactions via TCP and includes two main parts:Cageserver- a server-side program (Python functions with the main program),
which runs on computers on the network whose files require remote access;ClassCage(in Python packagecage_api), whose methods provide remote file operations in applications.This package includes only Part 2: Cage API, that is used on the client side (in applications).Full description:https://github.com/Arselon/CageCopyright 2019-2022 Arslan S. Alievhttp://www.arslan-aliev.comLicensed under the Apache License, Version 2.0 (the "License");
you may not use this software except in compliance with the License.
You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an
"AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and limitations under the License.
Package: cage-json-extractor
This repo contains code for extracting the molecules inhttps://data.hpc.imperial.ac.uk/resolve/?doi=4618into anAtomLitedatabase.Why?Because the original format of the published data is an out-of-date format,
namely anstkJSON dump.How?The easiest thing to do ispipinstallcage-json-extractorNow you can download the filescages.tar.gz-https://data.hpc.imperial.ac.uk/resolve/?doi=4618&file=3&access=cage_prediction.db-https://data.hpc.imperial.ac.uk/resolve/?doi=4618&file=2&access=And runtarxfcages.tar.gzcage_json_extractorcages/amine2aldehyde3.jsoncage_prediction.dbamine2aldehyde3.dbNow if we want to extract all the shape persistent 4+6 cages we can runextract_cagesamine2aldehyde3.dbFourPlusSix--output_directoryextracted_cagesThis will create a folderextracted_cageswhich holds a sub-folder for every
shape persistent 4+6 cage inamine2aldehyde3.db. In the sub-folder you will
find the.molfile of the cage and its building blocks.Enjoy! (and sorry I deprecated the.jsonfiles)=)
Package: cagen
cagenAboutcagen is a static site generator intented forcmpalgorithms project. So it's very rare you are interested in that. Although you can use it as any other static site generator.LicenseThe software is distributed underGPL 2-only license.How it runsIt assumes your documents are written with markdown syntax. It is capable of convert those documents to any other format, usingpandoc(specificallypypandocwrapper) andMako templating system.The reason to use "external" templating system instead of built-in pandoc template system is because pandoc templatesare not capable of make conditions with values(something like$if(author=='me') Print full name here $endif$).The program just converts markdown files to HTML ones by default in the same directory. Unlike many other static site generators, there is no predefined structure by default: noassetsdirectory neithersitedirectory. By default, all generated files are in the same directory than the source files. Obviously, you can modify it if you want.We provide:alibrarya command line program (calledcagen) for convert documentsa script calledcagen-maketo generate a Makefile to convert automatically all markdown files to HTML ones.The software is implemented inpythonbecause it's easy to program (I'm very language-neutral). If you want some really fast static site generator, be free to fork the project and program with any compiled language.InstallationYou can install viapip:pip install cagenIf you are running ArchLinux or any Arch derivative ditribution, you can use thisPKGBUILDto make a pacman package.UsageBasic use is:cagen sourcefile.md generatedfile.html template.tmplwheresourcefile.mdis Markdown filegeneratedfile.htmlis the HTML5 filetemplate.tmplis Mako template fileSeecagen --helpfor more options.This tool is some kind of low-level tool. If you want some more higher-level one to automatically converts all markdown files to corresponding HTML5 files, we provide thecagen-makescript (see above). The steps are:cagen-make --initIt createsMakefilemakeIt automatically convert all markdown files to HTML5 ones usingtemplates/schema.tmplMako template. You can modify it editingMakefile.Other resourcesYou can see theissue trackerand contribute if you want suggesting new features or reporting a bug.TheAPI documentationis available.TheMailing Listto make a question, suggest something you want, send patches, etc. As user and developer.
Package: cagey
Docs:https://cagey.readthedocs.ioCageyFirst and foremostcageyis a command line tool for creating and managing a cage
database. Withcageyyou will extract a a range of experimental and computational
data in a variety of formats and place it into a single file. You can then use this file
as input for your scripts which perform data analysis. You can installcageywith:pipinstallcageyOnce installed you can use the command line tool to create a new database:cageynewpath/to/datapath/to/cagey.dbThis will create a new database atpath/to/cagey.dband populate it with data frompath/to/data. There are in fact a lot more things you can do withcagey, and
the best way to learn about them is to use it interactively, starting with:cagey--helpUsage: cagey [OPTIONS] COMMAND [ARGS]...

 A cage database tool.
 Run cagey help intro for an introduction.

╭─ 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 ──────────────────────────────────────────────────────────────────────────╮
│ help         Get help on how to use cagey.                                          │
│ insert       Insert new data into the cagey database.                               │
│ ms           Mass spectrum analysis.                                                │
│ new          Create a new database.                                                 │
│ nmr          Extract NMR peaks.                                                     │
╰─────────────────────────────────────────────────────────────────────────────────────╯Working with the databaseOnce you’ve usedcageyto create a database, you can use thecagey.queriesmodule
to extract data from it in your Python scripts. This step is best understood by
reading our documentation, which you can find athttps://cagey.readthedocs.io.
Package: cagged
Описаниеcaged– это программа для безопасной установки пакетов из публичных репозиториев (PyPI, npm, crates.io, etc.)УстановкаpipinstallcagedИспользованиеcagedpipinstall<имя_пакета><аргументы_pip>cagednpminstall<имя_пакета><аргументы_npm>Принцип работыСтатический анализ.caged проверяет метаданные и исходный код пакета на совпадение с заранее заданными правилами. Метаданные пакета проверяются с помощью программ на языке Python. Исходный код пакета проверяется с помощью Open Source программы semgrep с заранее заданными правилами.Динамический анализ.Динамический анализ кода осуществляется с помощью контейнеризации. Программа caged запускает Docker-контейнер (для изоляции от основной системы), в котором устанавливается и запускается исследуемый пакет, после чего собирается информация о том, какие ресурсы системы (файлы, команды) или внешние ресурсы он использует. Для этого используется открытая технология gVisor, позволяющая выполнять контейнеры более легковесным способом, чем при обычной виртуализации. Так достигается максимальная безопасность и сокращение времени проверки.Обработка данных.Данные, полученные с помощью динамического анализа, сохраняются в формате JSON. После этого, полученные данные векторизуются (превращаются в список вида {"DNS Records": 123}, хранящий в себе числовые метрики пакета). Далее метрики обрабатываются с помощью заранее обученной модели машинного обучения, которая выдает результат логического типа (является ли пакет вредоносным или нет).Ели все статические и динамические проверки пакетом пройдены успешно, то запускается официальный установщик пакетов для данной экосистемы.]
Package: cahier-de-prepa-parser
cahier-de-prepa-parserPython parser pour Cahier de PrépaIntroductionC'est un parser python pour Parcoursup qui permet de récupérer les fichiers et dossiers stocké sur Cahier de Prépa.A proposDependancesbeautifulsoup4requestsInstallationStableIntallez directement depuis pypi avec la commandepip install cahier-de-prepa-parser(Si vous êtes sous Windows et avez des difficultés avec cette commande, utilisez celle-ci en supposant que vous avez python 3.x.x installé sur votre ordinateur:py -3 -m pip install cahier-de-prepa-parser)LatestVous pouvez installez la dernière version de la bibliothèque directement depuis Githubpip install git+https://github.com/Bapt5/cahier-de-prepa-parserUsageUn programme simple permettant de récupérer tous les voeux et d'en afficher le nom et l'établissementfromcdp_parserimport*client=cdp.Client("https://cahier-de-prepa.fr/votre-classe")client.authentificate("username","password")folders,files=client.main_folder.get_content()print(folders)print(files)ContributionN'hésitez pas à apporter votre contribution. Toute aide est appréciée. Pour contribuer, veuillez créer un Pull Request avec vos changements.La configuration de l'environnement de développement consiste simplement à cloner le dépôt et à s'assurer que vous avez toutes les dépendances en
en exécutantpip install -r requirements.txt.Ajout de fonctionnalitésParcoursupy couvre les fonctionnalités essentielles, mais si vous avez besoin de quelque chose qui n'est pas encore implémenté, vous pouvezcréer un issueavec votre demande. (ou vous pouvez contribuer en l'ajoutant vous-même)LicenseMozilla Public License, version 2.0
Package: cai2
cai2 - Codon Adaptation IndexAn implementation ofSharp and Li's 1987 formulationof thecodon adaption index.This is an update ofcaiproviding the same functionality, but now works with all python 3 versions. This version also has more tests, some derived from the Sharp and Li 1987 paper above.This module can be installed with the following command:$ pip install cai2Use:Finding the CAI of a sequence is easy:from cai2 import CAI
CAI("ATG...", reference=["ATGTTT...", "ATGCGC...",...])
0.24948128951724224Determining which sequences to use as the reference set is left to the user, though theHEG-DBis a great resource of highly expressed genes.CitationLee, B. D. (2018). Python Implementation of Codon Adaptation Index.Journal of Open Source Software, 3(30), 905.https://doi.org/10.21105/joss.00905:@article{Lee2018,doi = {10.21105/joss.00905},url = {https://doi.org/10.21105/joss.00905},year = {2018},month = {oct},publisher = {The Open Journal},volume = {3},number = {30},pages = {905},author = {Benjamin D. Lee},title = {Python Implementation of Codon Adaptation Index},journal = {Journal of Open Source Software}The original creator wasbenjamin_lee@college.harvard.edu.  This version was created by Björn Johansson as it is needed for optional functionality forpydna.ReferenceSharp, P. M., & Li, W. H. (1987). The codon adaptation index--a measure
of directional synonymous codon usage bias, and its potential
applications.Nucleic Acids Research, 15(3), 1281–1295.
Package: cai-bot
✨ Yet Another Bot Framework for Tencent QQ Written in Python ✨声明一切开发旨在学习，请勿用于非法用途CAI是完全免费且开放源代码的软件，仅供学习和娱乐用途使用CAI不会通过任何方式强制收取费用，或对使用者提出物质条件许可证CAI采用AGPLv3协议开源，不鼓励、不支持一切商业使用。特色简单易用的 API，支持多账号极少的额外依赖完整的 Type Hints(pep-0484)Packet Query 支持Variadic Genericsfromcai.utils.binaryimportPacketpacket=Packet(bytes.fromhex("01000233000000"))packet.start().int8().uint16().bytes(4).execute()# return type: INT8, UINT16, BYTES便携的 JceStruct 定义 (使用方法参考JceStruct)fromtypingimportOptionalfromjceimportJceStruct,JceField,typesclassCustomStruct(JceStruct):int32_field:types.INT32=JceField(jce_id=0)optional_field:Optional[types.DOUBLE]=JceField(None,jce_id=1)nested_field:OtherStruct=JceField(jce_id=2)功能CAI仅作为底层协议库使用，将协议封装为 API。CAI不会支持涉及金钱、主动邀请、获取凭证等敏感操作的协议。已支持的协议列表：登录cai.api.loginAPI Reference账号密码登录设备锁验证图片验证码提交短信验证码提交扫码登录短信验证码客户端cai.api.clientAPI Reference设置在线状态上传图片/音频/视频/转发消息(用于发送聊天信息)获取音频下载链接(get_voice_download_url)好友cai.api.friendAPI Reference获取好友列表获取好友信息获取好友分组列表获取好友分组信息撤回消息发送文本信息(send_friend_msg)群组cai.api.groupAPI Reference获取群列表获取群信息获取群成员列表发送群消息(send_group_msg)发送戳一戳(send_nudge)设置群管理(set_group_admin)禁言群员(mute_member)撤回消息(recall_group_msg)漫游消息(get_group_msg)事件cai.api.flowAPI Reference通过注册事件监听回调，在事件发生时执行指定操作。事件类型可通过cai.client.events模块导入。好友消息 (PrivateMessage)群消息 (GroupMessage)完整的群事件支持 (group.py)Bot 基础事件 (common.py)好友事件 (friend.py)二次开发暂无文档，请参考examples中的源代码进行开发注意：这需要你有一定的源代码阅读能力分支信息本仓库为github.com/cscs181/CAI的一个二次开发项目，遵循原有的开发许可证同时，不会修改原有文件内的版权信息最后感谢yanyongyu开源的源码
Package: caic-python
caic-pythonAn async Python client for theCAICwebsite data using the undocumented HTTP APIs.caic-pythonis capable of retrieving information on the following from the CAIC website:Search field reports (aka observation reports) submitted to the CAIC website.Search avalanche observation reports submitted as part of a field report.Retrieve the CAIC's avalanche forecast on a given date.Retrieve information on CAIC's defined backcountry zones and highway zones.Retrieve individual observation objects of the following type:Field ReportAvalanche ObservationSnowpack ObservationWeather ObservationRead thefull documentationfor further details. It is also available locally viamake read-docsor thedocs/directory.
Package: caidin
Caidin: An Open-Source Recommendation Engine LibraryCaidin is a Python library that provides a collection of recommendation algorithms and utilities for building recommendation systems. It aims to simplify the process of creating and experimenting with recommendation engines in various domains.FeaturesImplementation of collaborative filtering, matrix factorization, and content-based recommendation algorithms.Utility functions for data loading, preprocessing, and evaluation.Clear and customizable model structures for users and recommenders.Well-documented codebase with usage examples.InstallationYou can install Caidin using pip:pip install caidinFor detailed installation instructions and requirements, please refer to theInstallation Guide.DocumentationFor detailed usage instructions, API references, and example code, please refer to theDocumentation.Getting StartedCheck out theExamplesdirectory for step-by-step examples demonstrating how to use Caidin for building recommendation systems.ContributingWe welcome contributions from the community! Please refer to theContributing Guidelinesfor information on how to get started, code style, and the contribution process.Code of ConductPlease review ourCode of Conductthat outlines the behavior we expect from all contributors and users of the project.LicenseThis project is licensed under theMIT License.
Package: caikit-nlp-client
caikit-nlp-clientA client library forcaikit-nlpInstallationInstall fromPyPipipinstallcaikit-nlp-clientUsageA few examples follow, seeexample.pyhttpTo use the http protocolfromcaikit_nlp_clientimportHttpClienthost="localhost"port=8080model_name="flan-t5-small-caikit"http_client=HttpClient(f"http://{host}:{port}")text=http_client.generate_text(model_name,"What is the boiling point of Nitrogen?")gRPCTo use the gRPC protocolfromcaikit_nlp_clientimportGrpcClienthost,port="localhost",8085model_name="flan-t5-small-caikit"grpc_client=GrpcClient(host,port,insecure=True)# plain text modetext=grpc_client.generate_text(model_name,"What is the boiling point of Nitrogen?")Text generation methods may accept text generation parameters, which can be provided as kwargs
togenerate_textandgenerate_text_stream.Available values and types be retrieved as a dict for both the grpc and http clients:forparam,default_valueinclient.get_text_generation_parameters():print(f"{param=},{default_value=}")Self-signed certificatesTo use a self-signed certificate, assuming we have a certificate authority certca.pemhttp_client=HttpClient(f"https://{host}:{http_port}",ca_cert_path="ca.pem")withopen("ca.pem","rb")asfh:ca_cert=fh.read()grpc_client=GrpcClient(host,grpc_port,ca_cert=ca_cert)To skip certificate validation:# httphttp_client=HttpClient(f"https://{host}:{http_port}",verify=False)# grpcgrpc_client=GrpcClient(host,port,verify=False)mTLSAssuming we have aclient.pemandclient-key.pemcertificate files, and we requireca.pemto validate the server certificate:# httphttp_client=HttpClient(f"https://{host}:{http_port}",ca_cert_path="ca.pem",client_cert_path="client.pem",client_key_path="client-key.pem")# grpcwithopen("ca.pem","rb")asfh:ca_cert=fh.read()withopen("client.pem","rb")asfh:client_cert=fh.read()withopen("client-key.pem","rb")asfh:client_key=fh.read()grpc_client=GrpcClient(host,port,ca_cert=ca_cert,client_key=client_key,client_cert=client_cert,)# alternatively you can pass the paths directly to the client constructorgrpc_client=GrpcClient(host,port,ca_cert="ca.pem",client_cert="client.pem",client_key="client-key.pem")ContributingSet uppre-commitfor linting/style/misc fixes:pipinstallpre-commit
pre-commitinstallThis project usesnoxto manage test automation:pipinstallnox
nox--list# list available sessionsnox--python3.10-stests# run tests session for a specific python versionTesting against a real caikit+tgis stackTests are run against a mocked instance of a TGIS backend by default. To test against a real
caikit+tgis stack, it is sufficient to run using the--real-caikitflag when runningpytest:nox-stests----real-caikittestsNotes:The required images (caikit-tgis-serving,text-generation-inference), so it could take a while for tests to start while
compose is pulling the required images, it may seem like the tests are hanging.This uses a real model (google/flan-t5-small), which will be downloaded
totests/fixtures/resources/flan-t5-small-caikitand is around 300MB in size.
Package: caikit-tgis-backend
Caikit Text Generation Inference Service (TGIS) BackendThis project provides a Caikit module backend that manages models run in TGISConfigurationSample configuration using theMULTIfinder and a remoteTGISbackend):runtime:library:caikit_nlplocal_models_dir:/path/to/modelslazy_load_local_models:truemodel_management:finders:default:type:MULTIconfig:finder_priority:-local-tgis-autoinitializers:default:type:LOCALconfig:backend_priority:-type:TGISconfig:connection:hostname:"localhost:8033"connect_timeout:30test_connections:truelog:formatter:pretty
Package: cainiao
Cainiao适用于菜鸟电子面单服务的非官方Python SDK。InstallpipinstallcainiaoWayBill第一种使用方法importasynciofromcainiaoimportWayBillClient,WayBillfromcainiao.templatesimportWayBillGetForm,Sender,PackageInfo,Recipientsender=Sender(**{"cpCode":"YTO","name":"XXX","province":"XX省","city":"XX市","district":"XX区","detail":"XX街道","mobile":"1XXXXXXXXXX",})recipient=Recipient(**{"name":"XXX","province":"XX省","city":"XX市","district":"XX区","detail":"XX街道","mobile":"1XXXXXXXXXX","tradeOrderList":[str(item)foriteminrange(10)],"orderChannelsType":"OTHERS","templateUrl":("http://cloudprint.cainiao.com""/template/standard/111/12003"),"packageInfo":PackageInfo(),"userId":"520",})waybill_get_form=WayBillGetForm(sender=sender,recipients=[recipient])asyncdefmain():asyncwithWayBillClient()assession:waybill=WayBill(url='http://link.cainiao.com/gateway/link.do',token='xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',appsecret='yyyyyyyyyyyyyyyyyyyyy',session=session)print(awaitwaybill.tms_waybill_get(data=waybill_get_form))print(awaitwaybill.subscription_query())print(awaitwaybill.cloudprint_standard_templates())print(awaitwaybill.cloudprint_isv_templates())print(awaitwaybill.cloudprint_seller_custom_areas())print(awaitwaybill.cloudpirnt_seller_custom_area_detail(mappingId=1))asyncio.run(main())第二种使用方法# -- snip --asyncdefmain():session=awaitWayBillClient().connection()waybill=WayBill(url='http://link.cainiao.com/gateway/link.do',token='xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx',appsecret='yyyyyyyyyyyyyyyyyyyyy',session=session)print(awaitwaybill.tms_waybill_get(data=waybill_get_form))print(awaitwaybill.subscription_query())print(awaitwaybill.cloudprint_standard_templates())print(awaitwaybill.cloudprint_isv_templates())print(awaitwaybill.cloudprint_seller_custom_areas())print(awaitwaybill.cloudpirnt_seller_custom_area_detail(mappingId=1))awaitsession.close()asyncio.run(main())CloudPrint第一种使用方法importasynciofromcainiaoimportCloudPrintClient,CloudPrintfromcainiao.templatesimportContent,Document,TaskFormcontent=Content(**{"data":{"nick":"Hello"},"templateURL":"http://cloudprint.cainiao.com/template/standard/278250/1",})document=Document(**{"documentID":"1","contents":[contentfor_inrange(5)]})task=TaskForm(printer="Microsoft Print to PDF",documents=[document])asyncdefmain():asyncwithCloudPrintClient(ws_url='ws://127.0.0.1:13528')asws:cloudprint=CloudPrint(ws=ws)print(awaitcloudprint.get_printers())print(awaitcloudprint.print(task=task.content))asyncio.run(main())第二种使用方法# -- snip --asyncdefmain():# 注意使用区别，session.close() 才是关闭 aiohttp.ClientSession()session,ws=awaitCloudPrintClient(ws_url='ws://127.0.0.1:13528').connect()cloudprint=CloudPrint(ws=ws)print(awaitcloudprint.get_printers())print(awaitcloudprint.print(task=task.content))awaitsession.close()asyncio.run(main())