Saravanan666/pypi-org huggingface dataset:
Package: md2wx
md2wxMarkdown 转 微信公众号把 Markdown 文件一键转为 HTML 格式，但是添加了部分样式和 JavaScript，让它可以一键复制到微信公众号平台。其它不支持直接上传 Markdown 内容的平台，例如知乎，也可以采用该工具的转换结果。为什么要开发这个工具目前网上的工具都要求把 Markdown 内容拷贝到编辑器里才能渲染出 HTML 结果，虽然很简单但是存在以下问题：需要访问网站才能使用如果发现有内容有错别字等需要修改的地方，要么修改原文件后再复制粘贴一遍，要么在浏览器改好再复制粘贴回原文件很难添加自定义的功能md2wx 是如何解决的：使用命令行本地执行一条命令md2wx即可，自动在本地启动 HTTP 服务器展示 HTML 页面启动后在后台自动监控 Markdown 文件，发现改动自动重新转换项目结构超级简单：1 个 python 文件，处理参数和 markdown 解析1 个 HTML 模板文件，决定 HTML 的整体结构1 个 CSS 样式文件，决定显示效果1 个 JS 脚本文件，处理一些前端操作Python 代码的处理过程非常简单，模板文件和静态文件用户完全可以按需自定义。安装pipinstallmd2wx如何使用查看帮助：>md2wx-h
usage:md2wx[-h][--outputOUTPUT][--templateTEMPLATE][--scriptSCRIPT][--style{blue,cyan,rose}|--cssCSS][--codestyleCODESTYLE][--no-basic-static][--noserver][--portPORT][--quite][--debug][--dryrun]mdpath

Markdown一键复制发布到微信公众号（或其它平台）。

positionalarguments:mdpath.md文件或者是其所在文件夹路径，缺省是当前路径

optionalarguments:-h,--helpshowthishelpmessageandexit--outputOUTPUT,-oOUTPUT输出文件夹路径，缺省是临时目录--templateTEMPLATE模板文件路径--scriptSCRIPTJavaScript文件路径--style{blue,cyan,rose}内置的样式名--cssCSS自定义样式的CSS文件--codestyleCODESTYLE代码样式名，缺省是"github-dark"--no-basic-static不要复制基础静态文件(_basic.css和script.js)，当自定义模板不需要这些文件时使用该选项--noserver,--noserve不启动HTTP服务器(只有在使用--output指定了输出目录时才能用)--portPORTHTTP服务器端口，缺省是8800--quite,-q安静模式，不要打开浏览器--debug开启Debug--dryrun不实际运行，解析参数后立即退出，配合--debug查看参数解析结果必填参数：mdpath唯一必填的位置参数，可以是一个.md文件，也可以是一个包含了.md文件的文件夹。举例：转换当前目录下的所有.md文件：md2wx.转换某个.md文件：md2wxmy_post.md选项说明--output OUTPUT：指定输出路径，缺省情况下转换结果是保存在临时目录中的，运行完毕自动删除。如果想保留结果，就使用该选项指定一个文件夹。--noserver：缺省情况下，会自动启动一个 HTTP 服务器来查看 HTML 文件。在使用了--output的前提下，如果不需要启动服务器，可以使用该选项。--port PORT：指定 HTTP 服务器的端口。--quite：在启动 HTTP 服务器后，为了方便还将自动打开浏览器访问，如果已经打开了，可以使用该选项。以下 2 个选项是和样式有关的：--style STYLE_NAME：选择内置的样式名--codestyle CODESTYLE：选择代码样式名，都是highlight.js支持的样式名，总共有 200 多个，想要知道有哪些可用的，可以随便指定一个值，例如--codestyle xx， 这样报错信息里会提示有哪些可用。由于本工具主要是一个 Python 项目，主要目的不是为了解决前端问题，且本人也不擅长前端，所以内置的样式只提供了最最基础的样式。如果对结果不满意，可以使用如下选项来进行自定义：--css：指定一个 CSS 样式文件，可以是本地也可以是网络链接--script SCRIPT：指定一个 JavaScript 脚本文件，可以是本地也可以是网络链接--template TEMPLATE：指定一个 HTML 模板文件如果只是自定义样式，使用--css指定一个.css文件即可。如果需要操作内容，可以使用--script指定一个 JavaScript 脚本，理论上，该脚本可以对结果 HTML 页面做任意改动。指定的样式文件和 JS 脚本文件，如果是本地文件，都会被拷贝到输出目录下，和最终的 HTML 文件在同一级目录下。
同时被拷贝的还有两个基础的静态文件，一个是_basic.css，提供最基础的样式，一个是script.js提供最基础的操作。如果想要彻底的自定义，或者不想用 JavaScript 来操作页面内容，也可以--template来指定一个自定义的模板。当使用了自定义模板时，其中的一切内容都是可以自定义的，包括用到什么样式文件和脚本。此时如果不再依赖基础静态文件，使用--no-basic-static选项。如果所有选项都无法满足，可以直接修改代码。下面两个选项用于调试和定位问题：--debug：使用后可以打印更多信息--dryrun：不实际运行，解析参数后立即退出，配合--debug查看参数解析结果环境变量由于参数较多，如果不想每次都输入，可以通过环境变量保存。环境变量的名字是MD2WX_ARGS，值是要输入的任何选项，例如--output my_wx_output --css mystyle.css。命令行输入的参数优先级更高。变更日志0.1.0: 完成基本功能，首次发布。
Package: md2xmind
md2xmindmarkdown转思维导图基于python，实现把markdown格式的文档转换为xmind格式的文档。目前支持版本小于 8 的 xmind 。安装pip3 install md2xmind升级pip3 install -U md2xmind使用方式importosimportmd2xmind# md格式的源文件路径file_path=os.path.abspath(os.path.join(os.getcwd(),'test2.md'))# 第一个参数是源文件# 第二个参数是生成的文件名称，生成的文件位于运行命令行的文件夹中md2xmind.start_trans(file_path,'test2')
Package: md4mathjax
md4mathjaxthis is a python-markdown extension. basicly learning from the pelican plugin render-math. and i think inside its code, the mathjax extension split would be better.原插件做了很多额外的工作，但现在mathjax对于数学公式写法上的支持已经很强大了，很多额外的工作都是没有必要的了。本插件做的两个工作一就是检测markdown文档里面是否有数学公式，如果有则插入下面这段js代码。本插件还有一个工作就是将检测到的数学公式封装进class=math的span或者div环境中。这给后续css调配提供了便利。此外因为markdown的EscapeInlineProcessor机制存在，如果不进行处理\(...\)\[...\)这两个写法都会出错的，本插件经过处理将数学公式统一转为$...$和$$ ... $$这样的形式了。很简单直观的一个插件，同时又完成了必要的工作。tests文件夹下可以有输出html文件参考。UsageThis Extension is writing in the Python-Markdown Recommend way, so basically it's usage can reference the Python-Markdown Extension Usage document.本插件在写法是Python-Markdown的统一写法，因此使用可以参看Python-Markdown的插件使用文档。in pelicanMARKDOWN = {
    'extensions': [
        'md4mathjax'
    ],
}参数auto_insertdefault True是否根据文章有否数学公式来添加mathjaxbased on the markdown file does have the math equations to decide whether add the mathjax
scripttag_classdefault mathlike<div class="math">$\pi$</div>mathjax_srcdefaulthttps://cdn.jsdelivr.net/npm/mathjax@3.2.0/es5/tex-mml-chtml.jsmathjax_iddefault MathJax-scriptmathjax_settingsdefaultDEFUALT_MATHJAX_SETTING = r"""
window.MathJax = {
  tex: {
    inlineMath: [['$', '$'], ['\\(', '\\)']],
    displayMath: [["$$", "$$"], ['\\[', '\\]']],
    packages: {
      '[+]': ['mhchem']
    }
  },
  loader: {
    load: ['[tex]/mhchem']
  },
}
"""In python assign this value do not forget the prefixr.CHANGELOG0.1.3fix escape issue.0.1.2README0.1.1解决了和toc插件不兼容的问题。fixed a problem which is conflicted with the toc extension0.1.0初步编写完成project started
Package: md5checker
MD5CheckerThis module is a simple utility to examine a file’s checksumInstallOne-linerpip install md5checkerOther waysgit clone https://github.com/trendsetter37/md5-checker
cd md5-checkerFollowed by:python setup.py installorpip install .Testing (Development)Inside the root directory, runpip install -r requirements.txt
pip install -e .
py.testorpip install -r requirements.txt
pip install -e .
python setup.py testUsageCommand Linemd5checker "Space containing directory/path-to-file.extension"Surround path with double quotes if it contains spaces. Otherwise
quotations are unnecessary.md5checker space-containing-directory/path-to-file.extensionOptionsGet version.md5checker -v
0.2.0List hash algorithms.md5checker -aUse alternate hash algorithm.md5checker setup.cfg -a sha1
bf72c7d5ca4a4b2731bde5cfcc323ce64b533865Module>>> from md5checker import make_hash
>>> make_hash('setup.cfg')
ad895e8b0bd7d47e2a793dca3730aead
>>> make_hash('setup.cfg', algo='sha1')
bf72c7d5ca4a4b2731bde5cfcc323ce64b533865Available algorithmsMD5SHA1SHA224SHA256SHA384SHA512
Package: md5ct
change the MD5可以批量修改文件或者文件夹下文件的md5文件名转换为拼音安装$pip3installmd5ct使用$ctmd5-[你的路径]-py(可选，是否将文件名转为拼音)-rv(可选，是否将文件反转)LICENSEThe MIT License@ixiongyu感谢 JetBrains 免费的开源授权作者信息作者博客：https://blog.csdn.net/作者邮箱：ixiongyu@gmail.com
Package: md5diff
Script feature :* can load all kind (I hope ;-) of md5 files* the files inside the input md5 lists 'll be diff'ed and flagged as :** '==' : equal (md5 =, path =, filename =)** '<>' : different (md5 <>, path =, filename =)** '<<' or '>>' : new (md5 n/a, path <>, filename <>)** '<m' or 'm>' : moved (md5 =, path <>, filename =)** '<r' or 'r>' : renamed (md5 =, path =, filename <>)* to the stdout 'll be printed :** the two input md5 files, added of the diff'ing flag; the only difference froma standard md5 is the diff'ing flag, printed between the md5 and thepath/filename (chars 33,34)** some stats of the diff'ing***Some background :I needed this script to compare md5 created with different programs, to catchfiles renaming and moving and... because programming in python is fun !!!
Package: md5dir
md5dir - Calculer la somme md5 d'un répertoireCe module comprend un utilitaire en ligne de commande qui permet de calculer la somme md5 du contenu d'un répertoire (commandemd5), ainsi que de comparer deux répertoires (commandecompare).La commandemd5peut retourner soit la somme md5 de l'ensemble des fichiers inclus dans le dossier, soit un fichier texte comprenant les sommes de chacun des fichiers inclus dans le dossier.La commandecomparecompare deux répertoires.Le module peut être installé avec pip:python3 -m pip install md5dirLe module est compatible avec python 3.5+UsagePour calculer la somme md5 d'un répertoire et l'écrire sur la sortie standard:md5dir md5 chemin/du/répertoire -uPour calculer les sommes md5 du contenu d'un répertoire et l'écrire dans le fichier 'outfile.txt'.md5dir md5 chemin/du/répertoire -o outfile.txtPour comparer les sommes md5 du contenu de deux répertoires:md5dir compare chemin/du/répertoire autre/cheminL'aide et les options:md5dir --helpL'aide et les options d'une commande:md5dir md5 --helpCe code est sous licence WTFPL.
Package: mda
MDA: Analysis Tools for MD SimulationsInstallationClone and install the latest version ofMDA:gitclonehttps://github.com/ipudu/mdacdmda
pythonsetup.pyinstallOr use the package managerpipto install stableMDA:pipinstallmdaUsageimportmdaFeature SupportMDAcan be used to calculate following properties:Diffusion coefficient (Mean square displacement)Inertia tensor (Acylindricity, Asphericity, Shape)Gyration tensorOrder parametersOrientational tetrahedral orderTranslational tetrahedral orderRadial distribution functionRadius of gyrationSolvent accessible surface areaand moreMDAcan be used to download scientific papers:# using link:mdahttps://pubs.rsc.org/en/content/articlehtml/2017/cp/c7cp01602f# using DOI number:mda10.1039/C7CP01602FContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.Please make sure to update tests as appropriate.LicenseMIT
Package: mdacli
mdacliis a simple command line interface (CLI) to the analysis classes ofMDAnalysisusingargparse. This project is in anearly development stageand
work in progress.Contributions are welcome!To installmdaclirefer to theINSTALL file.Runmdacli:mda -hFor a help and an overview of the supported modules. A help
message for each module is available using:mda <module> -hAvailable modulesCurrently the following analysis modules are availableModule NameDescriptionAlignTrajRMS-align trajectory to a reference structure using a selection.AverageStructureRMS-align trajectory to a reference structure using a selection,
and calculate the average coordinates of the trajectory.ContactsCalculate contacts based observables.DensityAnalysisVolumetric density analysis.DistanceMatrixCalculate the pairwise distance between each frame in a trajectoryDihedralCalculate dihedral angles for specified atomgroups.JaninCalculate χ_1 and χ_2 dihedral angles of selected groupRamachandranCalculate ϕ and ψ dihedral angles of selected groupDielectricConstantComputes the average dipole moment.GNMAnalysisBasic tool for GNM analysis.closeContactGNMAnalysisGNMAnalysis only using close contacts.HELANALPerform HELANAL helix analysis on your trajectory.HoleAnalysisRunholeprogram on a trajectory.LinearDensityLinear density profileEinsteinMSDClass to calculate Mean Squared Displacement by the Einstein relation.PCAPrincipal component analysis on an MD trajectory.InterRDFIntermolecular pair distribution functionRMSDClass to perform RMSD analysis on a trajectory.RMSFCalculate RMSF of given atoms across a trajectory.More information about each module is available through the help
page or at theMDAnalysis documentation.
Package: mdade
Masked Deep Autoregressive models for Density EstimationGeneric implementation of Masked Deep Autoregressive models for Density Estimation inPyTorchandPytorchLightning.InstallationIn order to network implementations installmdadevia pip:pipinstallmdadeIn case you wish to employ the training procedures and datamodule implementations (on top ofpytorch-lightning), you would need to install the additional tools as well:pipinstall"mdade[tools]"
Package: mdadiffusion
MinimumDissipationApproximationPackage for computing hydrodynamic size of elastic proteins (IDPs) in Minimum Dissipation Approximation and Kirkwood-Riesman approximation.
Relies on PyGRPY for approximations of mobility tensors.LicenseThis software is MIT licensedHow to citeB. Cichocki, M. Rubin, A. Niedzwiecka and P. SzymczakDiffusion coefficients of elastic
macromolecules; J. Fluid. Mech. (2019)
Package: mdaencore
mdaencoreLatest releaseStatusCommunityEnsemble overlap comparison software for molecular data.mdaencore is bound by aCode of Conduct.InstallationTo build mdaencore from source, we highly recommend using virtual environments.
If possible, we strongly recommend that you useAnacondaas your package manager.
Below we provide instructions both forcondaand forpip.With condaEnsure that you havecondainstalled.
Install in your preferred conda environment withconda install -c conda-forge mdaencoreTo updateconda update -c conda-forge mdaencoreWith pipTo build the package from source, run:pip install .If you want to create a development environment, install the dependencies required for tests and docs with:pip install -e ".[test,doc]"CopyrightThe mdaencore source code is hosted athttps://github.com/MDAnalysis/mdaencoreand is available under the GNU General Public License, version 2 or any later version (see the fileLICENSE).Please note that the code is packaged and released under the terms of theGNU General Public License, version 3or any later version.Copyright (c) 2023, mdaencore authors (see the fileAUTHORS.md)AcknowledgementsProject based on theMDAnalysis Cookiecutterversion 0.1.
Please citeMDAnalysisand theENCORE paperwhen using mdaencore in published work:M. Tiberti, E. Papaleo, T. Bengtsen, W. Boomsma, and K. Lindorff-Larsen. ENCORE: Software for quantitative ensemble comparison. PLoS Comput Biol, 11 (2015), e1004415. doi: 10.1371/journal.pcbi.1004415R. J. Gowers, M. Linke, J. Barnoud, T. J. E. Reddy, M. N. Melo, S. L. Seyler, D. L. Dotson, J. Domanski, S. Buchoux, I. M. Kenney, and O. Beckstein. MDAnalysis: A Python package for the rapid analysis of molecular dynamics simulations. In S. Benthall and S. Rostrup, editors, Proceedings of the 15th Python in Science Conference, pages 98-105, Austin, TX, 2016. SciPy. doi:10.25080/Majora-629e541a-00e
Package: mdahole2
mdahole2Latest releaseStatusCommunityA Python interface for the HOLE suite tools to analyze an ion channel pore or transporter pathway as a function of time or arbitrary order parameters.mdahole2 is bound by aCode of Conduct.InstallationTo buildmdahole2from source,
we highly recommend using virtual environments.
If possible, we strongly recommend that you useAnacondaas your package manager.
Below we provide instructions both forcondaand
forpip.Note thatmdahole2is only supported on Linux and macOS.With condaEnsure that you havecondainstalled.Create a virtual environment and activate it:conda create --name mdahole2
conda activate mdahole2Install the development and documentation dependencies:conda env update --name mdahole2 --file devtools/conda-envs/test_env.yaml --file docs/requirements.yamlBuild this package from source:pip install -e .If you want to update your dependencies (which can be risky!), run:conda update --allAnd when you are finished, you can exit the virtual environment with:conda deactivateWith pipTo build the package from source, run:pip install -e .If you want to create a development environment, install
the dependencies required for tests and docs with:pip install -e ".[test,doc]"CopyrightThe mdahole2 source code is hosted athttps://github.com/MDAnalysis/mdahole2and is available under the GNU General Public License, version 3 (see the fileLICENSE).Copyright (c) 2022, The MDAnalysis Development Team and all contributors
listed in the file AUTHORSAcknowledgementsProject based on theMDAnalysis Cookiecutterversion 0.1.
Please citeMDAnalysiswhen using mdahole2 in published work.
Package: mdakit-sasa
mdakit-sasaLatest releaseStatusCommunityThis kit allows the calculation of a solvent-accessible-surface area of a trajectorymdakit-sasa is bound by aCode of Conduct.InstallationTo build mdakit-sasa from source,
we highly recommend using virtual environments.
If possible, we strongly recommend that you useAnacondaas your package manager.
Below we provide instructions both forcondaand
forpip.With condaEnsure that you havecondainstalled.Create a virtual environment and activate it:conda create --name mdakit_sasa
conda activate mdakit_sasaInstall the development and documentation dependencies:conda env update --name mdakit_sasa --file devtools/conda-envs/test_env.yaml
conda env update --name mdakit_sasa --file docs/requirements.yamlBuild this package from source:pip install -e .If you want to update your dependencies (which can be risky!), run:conda update --allAnd when you are finished, you can exit the virtual environment with:conda deactivateWith pipTo build the package from source, run:pip install .If you want to create a development environment, install
the dependencies required for tests and docs with:pip install ".[test,doc]"CopyrightThe mdakit-sasa source code is hosted athttps://github.com/pegerto/mdakit_sasaand is available under the GNU General Public License, version 2 (see the fileLICENSE).Copyright (c) 2023, Pegerto FernandezAcknowledgementsProject based on theMDAnalysis Cookiecutterversion 0.1.
Please citeMDAnalysiswhen using mdakit-sasa in published work.
Package: mdalib
MDA streaming libraryสวัสดีนี่กิตเองInstallpipinstallmdalibrequire: kafka-python, msgpack, requestsMethodimportmdalibdeftest(topic,val):print(topic)print(val)# TODO: implement thisoption={# for development"kafka_url":SOME_KAFKA_URL,"api_url":SOME_API_URL}mdalib.subscribe(option,cb=test)ชื่อ topicความหมายmessageข้อมูล message จาก APImessage_increaseข้อมูล message จาก Streaminginternetข้อมูล internet จาก APIinternet_increaseข้อมูล internet จาก Streamingcallข้อมูล call จาก APIcall_increaseข้อมูล call จาก Streaming
Package: mdanalysis-sphinx-theme
mdanalysis-sphinx-themeThis builds onmsmb_themeto apply slight modifications tosphinx_rtd_theme. It needs the forementioned theme to be installed.See example docs on RTD hereCode of conductAll members of the MDAnalysis community and participants are expected to abide by the MDAnalysisCode of Conduct.AcknowledgementsThis theme builds onmsmb_themeand theopenff-sphinx-theme.
Package: mdapackmol
## Why this fork?MDAPackmol-fmt is a fork of the original MDAPackmol code adapted to the FillMyTubes code.## MDAPackmolAnMDAnalysiswrapper aroundPackmolAllows combining MDAnalysis and PackmolPreserves the topology information (bonds etc) of your system after PackmolFree software: GNU General Public License v3Usage ExampleimportMDAnalysisasmdaimportmdapackmol# load individual molecule fileswater=mda.Universe('water.pdb')urea=mda.Universe('urea.pdb')# call Packmol with MDAnalysis objects as arguments# the 'instructions' allow for any valid Packmol commandssystem=mdapackmol.packmol([mdapackmol.PackmolStructure(water,number=1000,instructions=['inside box 0. 0. 0. 40. 40. 40.']),mdapackmol.PackmolStructure(urea,number=400,instructions=['inside box 0. 0. 0. 40. 40. 40.'])])# the returned system is a MDAnalysis Universe# with all topology information from building blocks retained# which can then be saved into any format# eg to Lammps data file:system.atoms.write('topology.data')CitingIf you find mdapackmol useful for you, please cite the following sources:L Martinez, R Andrade, E G Birgin, J M Martinez, “Packmol: A package for building initial configurations for molecular dynamics simulations”. Journal of Computational Chemistry, 30, 2157-2164, 2009.R J Gowers, M Linke, J Barnoud, T J E Reddy, M N Melo, S L Seyler, D L Dotson, J Domanski, S Buchoux, I M Kenney, and O Beckstein. “MDAnalysis: A Python package for the rapid analysis of molecular dynamics simulations.” In S. Benthall and S. Rostrup, editors, Proceedings of the 15th Python in Science Conference, pages 102-109, Austin, TX, 2016.
Package: mdapackmol-fmt
## Why this fork?MDAPackmol-fmt is a fork of the original MDAPackmol code adapted to the FillMyTubes code.## MDAPackmolAnMDAnalysiswrapper aroundPackmolAllows combining MDAnalysis and PackmolPreserves the topology information (bonds etc) of your system after PackmolFree software: GNU General Public License v3Usage ExampleimportMDAnalysisasmdaimportmdapackmol# load individual molecule fileswater=mda.Universe('water.pdb')urea=mda.Universe('urea.pdb')# call Packmol with MDAnalysis objects as arguments# the 'instructions' allow for any valid Packmol commandssystem=mdapackmol.packmol([mdapackmol.PackmolStructure(water,number=1000,instructions=['inside box 0. 0. 0. 40. 40. 40.']),mdapackmol.PackmolStructure(urea,number=400,instructions=['inside box 0. 0. 0. 40. 40. 40.'])])# the returned system is a MDAnalysis Universe# with all topology information from building blocks retained# which can then be saved into any format# eg to Lammps data file:system.atoms.write('topology.data')CitingIf you find mdapackmol useful for you, please cite the following sources:L Martinez, R Andrade, E G Birgin, J M Martinez, “Packmol: A package for building initial configurations for molecular dynamics simulations”. Journal of Computational Chemistry, 30, 2157-2164, 2009.R J Gowers, M Linke, J Barnoud, T J E Reddy, M N Melo, S L Seyler, D L Dotson, J Domanski, S Buchoux, I M Kenney, and O Beckstein. “MDAnalysis: A Python package for the rapid analysis of molecular dynamics simulations.” In S. Benthall and S. Rostrup, editors, Proceedings of the 15th Python in Science Conference, pages 102-109, Austin, TX, 2016.
Package: mdapisp
mdapispProject descriptionThis is a code snippet level code that roughly implements the CSV file upload and SQL Select Query functions.Execution environmentwritten and tested in Python 3.7.3 (via pyenv virtual environment)if you are using pip as your package managerpipinstallmdapispif you are using poetry as your package managerpoetryinstallHow to runThe basic execution scenario is as follows:Type the command in the terminal to run the application.mdapispOpen to fastapi swegger test page (defaulthttp://127.0.0.1:8000/docs#/) with a web browserUpload human.csv, fruit.csv using Create Upload CsvfilesSelect query using Read TableCheck cache contents using Read CacheUpload csvfile again and check cache contentsarchitecture design & the reason for designFocused onminimum difficulty and minimum cost implementationto meet the requirements specification.only the logic for the api was written without implementing a web server (ex. nginx, apache, etc.), the database also usedsqlite, and it was written as lightly as possible usingfastapito avoid swegger implementation.api specificationapi.mdIf you want to exact api specification, Please refer tohttp://127.0.0.1:8000/redocor theopenapi.jsonfile in the directory for the exact specification
Package: mdapy
mdapy: Molecular Dynamics Analysis with PythonOverviewThemdapypython library provides an array of powerful, flexible, and straightforward
tools to analyze atomic trajectories generated from Molecular Dynamics (MD) simulations. The library is fully
cross-platform, making it accessible to users inWindows, Linux, and Mac OS.
Benefited by theTaiChiproject,
we can effectively accelerate the pure python code, bringing it closer to the speed of code written in C++.
Furthermore,mdapyis highly parallelized, allowing users to leverage the resources of both multicore CPU and GPU.mdapycan directly handle the DUMP and DATA formats inLAMMPS, POSCAR format inVASP,
universal XYZ format and CIF format. Besides, all data inmdapyis stored in NDARRAY format inNumPy, which enables easy integration
with the scientific ecosystem in python and facilitates collaboration with other post-progressing
tools such asOVITOandfreud.ResourcesHomepage:https://github.com/mushroomfire/mdapyDocumentation:https://mdapy.readthedocs.io/Issue Tracker:https://github.com/mushroomfire/mdapy/issues