Saravanan666/pypi-org huggingface dataset:
Package: hentai
“De gustibus non est disputandum.”Python Hentai API WrapperEnglish |简体中文This python package implements a wrapper class around nhentai's RESTful API.
Please be aware that this is not an official API, technical questions about
nhentai.net should be redirected tosupport@nhentai.com.
Further note that the content of this module is generally considered NSFW. Finally,
I would like to comment at this point that you should under no circumstances use
this module to make an unreasonable amount of requests in a short period of time.InstallationGet the most recent stable release from PyPI:pipinstallhentai--only-binaryallDev Notes for ContributorsAlternatively, if you're looking to make acontributionfork this repository and runpython-mvenvvenv/sourcevenv/bin/activate# For Windows: .\venv\Scripts\activatepython-mpipinstall--upgradepip
pipinstall-rrequirements/dev.txt# additionally install the following dependenciespipinstallflake8pytestwheel# run all unit testspytest--verbose-s# create wheelpythonsetup.pybdist_wheel--universalMake sure to checkoutrec-hentaiso that your work is up-to-date with the next
release candidate. Don't implement any features that are incompatible with
version 3.7+ of python.DocumentationYou can find thedocumentationonline, or use thewikito learn more about this module.Basic UsageHentaimakes it very easy to browse through nhentai.net. It implements a flat
namespace for easy access of all their endpoints:fromhentaiimportHentai,Formatdoujin=Hentai(177013)# TrueHentai.exists(doujin.id)# METAMORPHOSISprint(doujin.title(Format.Pretty))# [Tag(id=3981, type='artist', name='shindol', url='https://nhentai.net/artist/shindol/', count=279)]print(doujin.artist)# ['dark skin', 'group', ... ]print([tag.namefortagindoujin.tag])# 2016-10-18 12:28:49+00:00print(doujin.upload_date)# ['https://i.nhentai.net/galleries/987560/1.jpg', ... ]print(doujin.image_urls)# get the sourcedoujin.download(progressbar=True)Apart from that,hentai.Utilsalso provides a handful of miscellaneous helper
methods:fromhentaiimportUtils,Sort,Option,TagfrompathlibimportPathprint(Utils.get_random_id())# recommend me something good!print(Utils.get_random_hentai())# advanced search with queriesfordoujininUtils.search_by_query('tag:loli',sort=Sort.PopularWeek):print(doujin.title(Format.Pretty))# print all character names from all doujinsforcharacterinTag.list(Option.Character):print(character.name)# store custom meta data as JSON file to diskpopular_loli=Utils.search_by_query('tag:loli',sort=Sort.PopularWeek)custom=[Option.ID,Option.Title,Option.Epos]Utils.export(popular_loli,filename=Path('popular_loli.json'),options=custom)See alsohttps://nhentai.net/info/for more information
on search queries.Command Line InterfaceStarting with version 3.2.4, this module also provides a rudimentary CLI for downloading
doujins within the terminal:# get help
hentai --help

# download this doujin to the CWD
hentai download --id 177013

# check the module version
hentai --versionGet In TouchYou can reach me atdev.hentai-chan@outlook.comfor private questions and inquires that don't belong to the issue tab.
Package: hentai-chan-api
HentaiChanApiWrapper overhttps://hentaichan.livehentai-chan-api is a small parser library
that will allow you to easily use manga fromhttps://hentaichan.liveRecommended to use python3.7+Async version:@HentaiChanApi-asyncInstallpipinstallhentai-chan-apiFeaturesParsing by pages and quantitiesSearch engine by queries and by tagsManga object to easily retrieve manga dataAbility to use a proxyExamplesAn example of using the 'get_new' method:fromhentai_chan_apiimportHentaiChanhc=HentaiChan()manga=hc.get_new(page_num=1,count=2)forelinmanga:print(el.id)# '40918-doll-house-glava-2'print(el.title)# 'Doll House - глава 2'print(el.poster)# https://imgcover.../.../01.jpg'print(el.series)# 'Оригинальные работы'print(el.author)# 'Sexgazers'print(el.translator)# 'Zone'print(el.content.images)# ['https://.../.png', 'https://.../.png'...]print(el.tags)# ['анал', 'без цензуры', 'большая грудь', ...]print(el.date)# '17 января 2022'Note that the arguments: "page_num=1" and "count=2" are optional.
By default, "page_num=1" and "count=20".Also note that calling "el.content.images" will invoke the parser, which may take some time to use. I advise you to call "el.content.images" only when necessary.Tag search example:fromhentai_chan_apiimportHentaiChanhc=HentaiChan()tags=hc.get_all_tags()# ['3D', 'action', 'ahegao', 'bdsm', 'corruption', ...]manga=hc.search(tag=tags[0])# [Manga(id='40779-ms-i', title='Ms. I (Невыразимые секреты её прошлого)', post...)...]print(manga[0].title)# Ms. I (Невыразимые секреты её прошлого)print(manga[0].content.images)# ['https://mimg2.imgschan.xyz/manganew/m/1641154521_ms.-i/001.jpg', 'https://...', ...]Search query example:fromhentai_chan_apiimportHentaiChanhc=HentaiChan()tags=hc.get_all_tags()# ['3D', 'action', 'ahegao', 'bdsm', 'corruption', ...]manga=hc.search(page_num=3,query='bikini')# [Manga(...)...]print(manga[0].title)# Bikini's Bottomprint(manga[0].content.images)# ['https://mimg2.imgschan.xyz/manganew/l/1630962513_lightsource-bikinis-bot...', ...]
Package: hentai-chan-api-async
HentaiChanApi-asyncWrapper overhttps://hentaichan.livehentai-chan-api-async is a small asynchronous parser library
that will allow you to easily use manga fromhttps://hentaichan.liveRecommended to use python3.7+Sync version:@HentaiChanApiInstallpipinstallhentai-chan-api-asyncFeaturesParsing by pages and quantitiesSearch engine by queries and by tagsManga object to easily retrieve manga dataAbility to use a proxyAsynchronousExamplesAn example of using the 'get_new' method:importasynciofromhentai_chan_api_asyncimportHentaiChanasyncdefmain():hc=HentaiChan()manga=awaithc.get_new(page_num=1,count=2)forelinmanga:print(el.id)# '40918-doll-house-glava-2'print(el.title)# 'Doll House - глава 2'print(el.poster)# https://imgcover.../.../01.jpg'print(el.series)# 'Оригинальные работы'print(el.author)# 'Sexgazers'print(el.translator)# 'Zone'print(awaitel.content.images())# ['https://.../.png', 'https://.../.png'...]print(el.tags)# ['анал', 'без цензуры', 'большая грудь', ...]print(el.date)# '17 января 2022'print(el.original_url)# 'https://...'asyncio.get_event_loop().run_until_complete(main())Note that the arguments: "page_num=1" and "count=2" are optional.
By default, "page_num=1" and "count=20".Also note that calling "el.content.images" will invoke the parser, which may take some time to use. I advise you to call "el.content.images" only when necessary.Tag search example:importasynciofromhentai_chan_api_asyncimportHentaiChanasyncdefmain():hc=HentaiChan()tags=awaithc.tags()# ['3D', 'action', 'ahegao', 'bdsm', 'corruption', ...]manga=awaithc.search(tag=tags[0])# [Manga(id='40779-ms-i', title='Ms. I (Невыразимые секреты её прошлого)')...]print(manga[0].title)# Ms. I (Невыразимые секреты её прошлого)print(awaitmanga[0].content.images())# ['https://mimg2.imgschan.xyz/manganew/m/1641154521_ms.-i/001.jpg', ...]asyncio.get_event_loop().run_until_complete(main())Search query example:importasynciofromhentai_chan_api_asyncimportHentaiChanasyncdefmain():hc=HentaiChan()manga=awaithc.search(query='bikini')# [Manga(...)...]print(manga[0].title)# Bikini's Bottomprint(awaitmanga[0].content.images())# ['https://mimg2.imgschan.xyz/manganew/l/1630962513_lightsource-bik...', ...]asyncio.get_event_loop().run_until_complete(main())
Package: hentry
Parse a well designed webpage with microformats markup. If you have no
knowledge about microformats, take a look athttp://microformats.org/wiki/hentry.A hentry schema looks like:<article class="hentry">
    <h1 class="entry-title">Article title</h1>
    <time class="updated" datetime="2014-11-06T20:00:00Z" pubdate>2014-11-06</time>
    <div class="entry-content">
        <p>Here is the content</p>
    </div>
    <div class="entry-tags">
        <a href="#tag1" rel="tag">tag1</a>
        <a href="#tag2" rel="tag">tag2</a>
    </div>
    <div class="vcard author">
        <span class="fn">Author Name</span>
    </div>
</article>With this libraryhentry.py, you can parse the html into meta data:hentry.parse_html(text, format='html')InstallationInstall hentry with pip:$ pip install hentryBasic UsageParse a webpage with a url:hentry.parse_url(url)Parse a webpage with html content:hentry.parse_html(content)The result is a dict which contains:titlecontentauthorpubdatetagscategoriesimage
Package: hepai
HAI白泽AI平台(Hakutaku AI)分为算法框架、模型库、数据集、算力资源四个部分。其中，HAI算法框架集成高能物理领域经典和SOTA的人工智能算法，提供统一、简单、易用的复现和应用接口。News[2023.10.24] v1.0.18接入dalle文生图模型，调用方法教程见此处。[2023.04.21] v1.0.7通过hepai使用GPT-3.5，hepai_api.md.[2023.02.09] 基于ChatGPT的HaiChatGPT已上线，使用简单，无需梯子！详情查看：HaiChatGPT.[2023.01.16] 华为NPU服务器上架，如有算法国产化需求，请查阅NPU文档。[2022.10.20] HAI v1.0.6-Beta 第一个测试版本发布，4个算法和3个数据集[2022.08.23] HAI v1.0.0Tutorials在计算集群上使用HAI的快速入门使用PointNet对JUNO实验的大气中微子进行重建和鉴别Algorithm ZooDataset ZooQuick startpip install hepai --upgrade
hai -V  # 查看版本命令行使用haitrain<model_name># 训练模型, 例如: hai train particle_transformerhaieval<model_name>python库使用python库统一接口：importhaimodel=hai.hub.load('<model_name>')# 加载模型config=model.config# 获取模型配置config.batch_size=32# 修改配置model.trian()# 训练模型model.eval()# 评估模型model.infer('<data>')# 模型推理hai.train('particle_transformer')部署和远程调用跨语言、跨平台的模型部署和远程调用服务端：haistartserver# 启动服务客户端pipinstallhai-clientimporthai_clienthai=hai_client.HAI()或其他支持gRPC的语言，详见deploy
Package: hepai-client
This is the client of High Energy Physics AI platform (HAI).The hai platform is a gprc service that provides artificial intellegence algorithms.THe hai_client is calling tool that support languages (python, java, c/c++ etc.) and systems (linux, macos, windows etc.)Get Startedstart serverIn the server computer with GPU.pip install hepai
hai server start  # start serverrun clientIn the client computer.pip install hepai-client
Package: heparchy
heparchyHierarchical database storage and access for high energy physics event data.Docstrings are available, markdown documentation coming soon.Installationpip install heparchyFeaturesFast and efficient storageWrites and reads from HDF5 filesData stored hierarchicallyFiles contain processesProcesses contain eventsEvents contain datasets for the final state particlesProcess level metadata can be attachedContext managers provide access to these containersData writing interfaceProcessMetadata writing methods:string(): MadGraph formatted string,ie.p p > t t~decay(): pdgids of incoming and outgoing particles for the hard eventcom_energy()signal_id(): pdgid of the particle of interest in the hard eventcustom(): extend with your own key / value metadata pair for the processEventsData writing methods for final state particles:pmu(): 2dnumpyarray of 4-momenta, each row[px, py, pz, e]pdg(): pdgidsis_signal(): boolean tags identifying if particle constituent of signalcustom(): extend with your own key / value dataset pair for the eventComing soonDirect interface from HepMC files to HDF5 formatJupyter notebook examplesPip installation scriptWarning: before the first release, the read interface may change
to improve consistency with the write interface.Breaking changes will be avoided following the iminent release of 1.0.0.
Package: hepconvert
hepconvertThe hepconvert library is a bridge between columnar file formats, currentlyROOT, and Parquetand soon eventually includeFeather, and HDF5.It aims to simplify file conversions in Python, replacing what is usually a multi-step process with one line of code, with builtin features for managing large datasets and choosing compression levels.Installationhepconvert can be installed fromPyPIusing pip:pipinstallhepconvertGetting startedimporthepconvert# To merge two or more root files with TTrees,# and add together any histograms:hepconvert.merge_root("destination.root",["ttree_file1.root","ttree_file2.root"])# To add root files with only histograms:hepconvert.add_histograms("destination.root",["hist_file1.root","hist_file2.root"])To runmerge_rootfrom the command line:hepconvertmerge-root[options][OUT_FILE][IN_FILES]To runadd_histograms:hepconvertadd[options][OUT_FILE][IN_FILES]Find details on each function's CLI options on the readthedocs.
Package: hepcrawl
HEPcrawl is a harvesting library based on Scrapy (http://scrapy.org) for INSPIRE-HEP
(http://inspirehep.net) that focuses on automatic and semi-automatic retrieval of
new content from all the sources the site aggregates. In particular content from
major and minor publishers in the field of High-Energy Physics.The project is currently in early stage of development.See full documentation athttp://pythonhosted.org/hepcrawl
Package: hepdata
A Python wrapper for theHEPdata Matching Gifts database API.Install>From PyPI:pip install hepdataTestingFirst installtox <https://tox.readthedocs.io/en/latest/>`_and then run:toxIf you’d prefer not to run the tests from atoxenvironment, ensure you install the package first:python setup.py developLicenseLicensed under the terms of the GPL v2.History0.2.1 (2018-02-15)Fix bad release0.2.0 (2018-02-15)Switch from HTTP to HTTPS for all calls0.1.5 (2016-12-20)Fixes missing error code and updates testing/build documentation0.1.4 (2016-09-19)Address Python 2 unicode handling bug0.1.3 (2015-07-24)Fixes programming error in previous fix0.1.2 (2015-07-24)Fixes programming error in previous fix0.1.1 (2015-07-22)Enforce consistent type of results (always a list, not a singular dictionary)0.1.0 (2015-06-15)First release on PyPI.
Package: hepdata-converter-ws
hepdata-converter-wsSimple Flask Web Services wrapper in Python 3 forhepdata-converter.It allows running thehepdata-converteras a
web service on top of theFlaskmicro web framework.APIThis web service provides one method which acceptsGETJSON requests.
The accepted format is as follows:Request[GET] /convert  (application/json)
{
input: Base64 encoded tar.gz file containing hepdata-converter-ws-data entry (directory / file)
id: str used for caching purposes (same input files have to have same ID), not implemented?
options: dictionary with options accepted by hepdata_converter.convert function. The most important are:
         input_format: (input format identifier e.g. yaml, oldhepdata, etc.)
         output_format: (output format identifier e.g. yaml, root, yoda, yoda1, csv, etc.)
         other options are dependent on the input / output format and are documented in their respective parsers / readers
         in https://github.com/HEPData/hepdata-converter
}ResponseThe response has MIME typeapplication/x-gzipand is a tar.gz file
containing the hepdata-converter-ws-data directory with the
requested file/files.API UsageIt is recommended to use thehepdata-converter-ws-clientlibrary to interact with this web service, as it provides easier calling
and more transparent usage.
Package: hepdata-converter-ws-client
hepdata-converter-ws-clientLight client wrapper for interaction withhepdata-converter-ws(Web Services).  It is recommended to use this wrapper instead of
manually creating requests tohepdata-converter-ws.The reason for creating this package is the fact that thehepdata-converter-wsAPI requires compressing files intotar.gzformat and encoding using
Base64 in order to pass them as an argument in the JSON request.
Doing this manually every time someone wants to call thehepdata-converter-wsAPI was a little cumbersome: that's why this light wrapper was born.Additionally, the library provides additional functionality when it
comes to writing the output of theconvertfunction: instead
of receiving rawtar.gzcontent it is possible to extract to a
specified file path.Sample usageThe library exposes one single functionhepdata_converter_ws_client.convertwhich is very similar tohepdata_converter.convert.  It accepts the additional argumenturl,
and restricts input / output tostr,unicodeand file objects
(objects supportingread,write,seek,tell).Theoptionsparameter should be the same as with thehepdata_converterlibrary.Thetimeoutparameter can be used to set a timeout for requests
(defaults to 600s).The library defines the exceptionhepdata_converter_ws_client.Errorwhich will be thrown on timeouts or other errors connecting to the
server.A functionhepdata_converter_ws_client.get_data_sizegets the size
in bytes of the JSON data that would be sent to the converter.  This
could be useful in checking that a maximum payload size imposed by a
web server is not exceeded.Function descriptionhepdata_converter_ws_client.convertfunction has properdocstringdescribing its arguments and return values.
Similarly forhepdata_converter_ws_client.get_data_sizewith correspondingdocstring.Convert using file pathsArguments passed as input and output can be file paths or file objects.
Below is an example of how to utilise theconvertfunction with file
paths.importhepdata_converter_ws_client# using path to input file, and writing output directly to output_pathinput_path='/path/to/input.txt'output_path='/path/to/output/dir'hepdata_converter_ws_client.convert('http://hepdata-converter-ws-addr:port',input_path,output_path,options={'input_format':'oldhepdata'})Convert using input path and output file objectInput can always be a file object (as long as the inputParsersupports single files).  Output can be a file object only if the
keyword argumentextract=False.  In this case the binary content of
the returnedtar.gzfile will be written to the output file object.
It is then the responsibility of the user to decompress it.importhepdata_converter_ws_clientfromioimportBytesIO# using path to input file, writing to output streaminput_path='/path/to/input.txt'output=BytesIO()hepdata_converter_ws_client.convert('http://hepdata-converter-ws-addr:port',input_path,output,options={'input_format':'oldhepdata'},extract=False)
Package: hepdata-lib
hepdata_libLibrary for getting your data into HEPDataDocumentation:https://hepdata-lib.readthedocs.ioThis code works with Python 3.6, 3.7, 3.8, 3.9 or 3.10.InstallationIt is highly recommended you installhepdata_libinto avirtual environment.pipinstallhepdata_libIf you are not sure about your Python environment, please also see below how to usehepdata_libin a Docker or Apptainer container.Getting startedFor usinghepdata_lib, you don't even need to install it, but can use thebinderorSWAN(CERN-only) services using one of the buttons below:You can also use the Docker image:dockerrun--rm-it-p8888:8888-v${PWD}:/home/hepdataghcr.io/hepdata/hepdata_lib:latestAnd then point your browser tohttp://localhost:8888and use the token that is printed out. The output will end up in your current working directory (${PWD}).If you prefer a shell, instead run:dockerrun--rm-it-p8888:8888-v${PWD}:/home/hepdataghcr.io/hepdata/hepdata_lib:latestbashIf on CERN LXPLUS or anywhere else where there is Apptainer available but not Docker, you can still use the docker image:exportAPPTAINER_CACHEDIR="/tmp/$(whoami)/apptainer"apptainershell-B/afs-B/eosdocker://ghcr.io/hepdata/hepdata_lib:latestbashUnpacking the image can take a few minutes the first time you use it. Please be patient. Both EOS and AFS should be available and the output will be in your current working directory.Further examplesThere are a few more examples available that can directly be run using thebinderlinks below or usingSWAN(CERN-only, please use LCG release LCG_94 or later) and selecting the corresponding notebook manually:Reading in text filesReading in a CMS combine ntupleReading in ROOT histogramsReading a correlation matrixReading TGraph and TGraphError from '.C' filesPreparing scikit-hep histogramsExternal dependenciesROOTImageMagickMake sure that you haveROOTin your$PYTHONPATHand that theconvertcommand is available by adding its location to your$PATHif needed.
Package: hephaistos
HephaistosHephaistos is a framework for creating GPGPU appllication running on top of the
Vulkan API, allowing it to run on all major OS and on a wide range of hardware
such as all modern AMD, Intel and NVIDIA GPUs.The library aims to reduce the amount of boiler plate code, albeit in doing so
it might hide optimization possibility Vulkan provides.DependencyTo ease the building process, all external dependency are stored inside theexternaldirectory. Check there for more information.Mac OSMac OS does not support Vulkan on its own, but requires a translation layer
calledMoltenVKand can be installed
for example via Homebrew:brewinstallmolten-vkSince future updates to MoltenVK may enable more features without rebuilding
hephaistos, it is not included in the library itself.InstallThere exist pre-built python packages on PyPI and may be easily installed via
pip:pipinstallhephaistosFor some rare platforms you might need to build from sources.There are also no pre-built libraries for C++, as the API depends on the STL
and thus has no stable ABI (i.e. you would need to create a build for each
compiler).BuildingC++For building the C++ library you require:C++20 compatible compilerCMake at least version 3.18The dependencies are located in theexternaldirectory.
In there is a readme file for more information.The debug build requires the validation layers, which are part of theVulkan SDK.Hephaistos expects the kernel/shader code to be already compiled into SPIR-V
bytecode, so you must likely also need an compiler for that. The most popular
ones are:glslangvalidatorglslcSee the readme inside theexamplesfolder for a hint on how to use them.PythonThere are also python bindings usingnanobindandscikit-build.To build the python package you can simply run from the project's root
directory:pipinstall.Note that the binding relies on the C++ library and thus has the same
dependencies. The dependencies on the Python side are handled by pip.LearningThere are some examples provided in theexamplesdirectory for C++ and
innotebooksfor Python.LicenseHephaistos is licensed under the MIT license. SeeLICENSE. External libraries
are distributed under their own license. The ones located inexternalare
always acompanied by a copy of their license.
Package: hepi
HEPiPython interface for gluing together several HEP programs (e.g. from HEPForgehttps://www.hepforge.org/).StableUnstableGoalsThe goal of this project is to provide a simple and easy to use interface to common high-energy-physics tools (currently mainly SUSY related Tools).
Parameter scans and plotting is also included.
Different tools should just be plugged in and out as desired (i.e. generate a SUSY spectrum before running a scan with MadGraph).IdeaFirst generate a list of interested parameter points i.e. mass 100 to 1000 GeV squark.
Then if you also want to scan over the gluino mass just ask for a scan over previous list, and you get a 2d scan.
After generating all parameters they can be used to directly run the codes (in parallel or sequential) or just generate the input file for distribution across several clusters.
The results then can be imported again and plotted nicely.RealisationIn the working directory you have aninputandoutputfolder. The input would typically contain the baseline slha file.
Theoutputwill contain the produced scripts to execute the tools.
To avoid file collisions the files in the output folder correspond to a hashed value of all input parameters.
If a result already exists hepi won't rerun the tool.DocumentationFor more details on the usage of different tools, called runners, check the respective documentation.https://hepi.readthedocs.io/en/stable/https://apn-pucky.github.io/HEPi/index.htmlVersionsStablepipinstallhepi[opt][--user][--upgrade]Devpipinstall--index-urlhttps://test.pypi.org/simple/hepi[opt][opt]can be omitted to avoid optional dependencies (ie. lhapdf).HEPi-fastHEPi-fast interpolates grids in a similar fashion to(n)nll-fastbut also forResummino.They are given as json files as for the CERN SUSY wiki inxsec.
A default set of grids is in the source folderhepi/data/json/.
HEPi can be used to generate such json files for convenient reloading of the data.$ hepi-fast --help
$ hepi-fast pp13_squark_NNLO+NNLL.json
400
0 400.0 21.6 -1.509999999999991 1.509999999999991 0.0 0.0 0.0 0.0
500
0 500.0 6.12 -0.4560000000000013 0.4560000000000013 0.0 0.0 0.0 0.0
[...]Above shows squark squark cross section for requested 400 and 500 GeV mass at NNLO+NNLL.
The order of the output isid | Central value | error down | error up | error pdf down | error pdf up | error scale down | error scale upIf you just want to look at a quick plot of the interpolation run$ hepi-fast pp13_squark_NNLO+NNLL.json --plotfor something like