Saravanan666/pypi-org huggingface dataset:
Package: pdkf
PDKFPython package for converting PBKF file to DataFrame (pandas) list.ExampleIt is simple example for using package. This code converts data from file.pdkf to dataframe_dict.import pdkf

dataframe_dict = pdkf.read_pdkf('file.pdkf')
for key, dataframe in dataframe_dict.items():
    print(key)
    print(dataframe.info())PDKF structureThe file is a ZIP archive. For each dataframe, you need to add two files to the archive:META file;CSV or JSON file.
The META file contains the Pandas data types for the dataframe. For example:Service.csvname,purchase_price,description,remainder
sofa_low,10000.00,description,8
armchair_rocking,8000.00,description,14
bed_double,18000.00,description,6
chair_computer, 12000.00,description,2
bed_children,16000.00,description,5Service.meta{
    "name":"object",
    "purchase_price":"float",
    "description":"object",
    "remainder":"int64"
}ServiceCost.json[
    {
        "sofa_low":[
            {
                "price":"21000.00",
                "date":"2021.01.16"
            },
            {
                "price":"19000.00",
                "date":"2021.02.21"
            }
        ]
    },
    {
        "armchair_rocking":[
            {
                "price":"15000.00",
                "date":"2021.01.16"
            }
        ]
    }
]ServiceCost.meta{
    "price":"float",
    "date":"datetime64[ns]"
}
Package: pdkit
PDkit is a python module that provides a comprehensive toolkit for the management and processing of Parkinson’s symptoms performance data captured by high-use-frequency smartphone apps and continuously by wearables. PDkit facilitates the application of an extensive collection of methods and techniques across all stages of the Parkinson’s information processing pipeline. Although inherently flexible, PDkit currently prioritises functionalities critical to therapeutic clinical trial delivery rather than general patient care.More information is available in the following paper:Stamate C, Saez Pons J, Weston D, Roussos G (2021) PDKit: A data science toolkit for the digital assessment of Parkinson’s Disease. PLoS Comput Biol 17(3): e1008833. doi:10.1371/journal.pcbi.1008833 https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1008833An example of how PDkit is used in clinical strudies of Parkinson’s can be found in:Jha, A., Menozzi, E., Oyekan, R. et al. The CloudUPDRS smartphone software in Parkinson’s study: cross-validation against blinded human raters. npj Parkinsons Dis. 6, 36 (2020).https://doi.org/10.1038/s41531-020-00135-wThe PDkit currently supports directly the following apps:cloudUPDRS,mPower,HopkinsPDandOPDC.Full documentation of PDkit features is available onreadthedocs.
Package: pdk-semver
pdk-semverPretty print versions for project and artifacts.Make version more or less informative depending on the audience.$ pdk-semver -s all --rinfo-value some.info
internal  3.2.2-rev.3.some.info.git.b674019
  public  3.2.2-rev.3.some.info
 baserev  3.2.2-rev.3
    base  3.2.2Main features are:Automatic versioning based on git content and CI variablesUnique build versions. Version includes nearest tag,
number of commits and commit hashArtifact and release info. Add artifact details, like CPU, platform, client etc.Easy customization. Every component can be overridden with--COMP-valueoption, like--rinfo-valueThe version format is:Use CasesCI and Shallow clonesCI servers usually do shallow (partial) clone, sopdk-semvercan't get tag and
commit counter. What can we do?adjust CI clone depth to the tagging frequencykeep tag name in a text file, but commit counter still be offunshallow, bring more commitsWorking with docker imagesWorking with buildrootInstallationpipinstallpdk-semverDevelopmentSeedevelopmentdoc
Package: pdkutil
Stores a pdk file to a barbican container.InstallationPip is the preferred way to install PDKUtil:pip install pdkutilCommand-line interfacePDKUtil uses Keystone for identity management. Credentials and endpoints can
be provided via environment variables or command line parameters in the same
way supported by most OpenStack command line interface (CLI) tools, e.g.:export OS_AUTH_URL=http://example.com:5000/v2.0
export OS_USERNAME=admin
export OS_PASSWORD=password
export OS_TENANT_NAME=adminStore a pdk fileThis command stores the specified pdk file to a container, returning
container’s reference:pdkutil store <filename> <container-name>Get container’s informationThis command retrieves container’s information (container’s name,
secrets references, etc) by its specified reference:pdkutil get <container-reference>
Package: pdlog
pdlogpdlogprovides logging forpandasdataframes, to better enable you to monitor and debug your data pipelines.For example:>>>importpdlog>>>df=df.log.dropna()2020-05-26 20:55:30,049 INFO <pdlog> dropna: dropped 1 row (17%), 5 rows remainingExampleThe above assumes that theloggingmodule has been configured and that data has been loaded into apandasDataFrame. Let's walk through those steps with a simple example.Configurelogging:>>>importlogging>>>fmt="{asctime}{levelname}<{name}>{message}">>>logging.basicConfig(format=fmt,style="{",level=logging.INFO)Load data into apandas.DataFrame:>>>importpandasaspd>>>df=pd.DataFrame([0,1,2,None,4])>>>df.head()00  0.01  1.02  2.03  NaN4  4.0Importingpdlogand call a method under thelogaccessor:>>>importpdlog>>>df=df.log.dropna()2020-05-26 20:55:30,049 INFO <pdlog> dropna: dropped 1 row (17%), 5 rows remainingSupported methodspdlogcurrently supports the followingpandas.DataFramemethods:Filter rows and select columns:drop_duplicatesdropdropnaheadquerysampletail(Re-)set indexes:reset_indexset_indexRename indexes:renameReshape:meltpivotImpute:bfillffillfillnaRelated Workpandas-logpandas-logis aimed at interactive usage. Its messages are friendlier and more verbose thanpdlogaims to be.
Ideally, eachpdlogmessage should be a single line of dense information to help you understand whether your production code is doing what you think it is, while not overflowing your logs.
These don't tend to make particularly friendly messages.tidylogpdlogcan be considered a port oftidylog(R package) topandas.
Their goals align with ours, and we think they've done a great job at reaching those goals.
Package: pdlpy
Probability Distribution Library for PythonProbability Distribution Library for Pythonis a library for simulation and analysis of random processes.
It contains classes for descrete and continious distributions as listed below.Discrete distributions:BernoulliBinomialGeometricHypergeometricPoissonContinuous distributions:ExponentialNormalUniformInstallationInstall and update usingpip:pipinstall-UpdlpyDemoCreate and analyse probability distributions as simple as:LinksDocumentationPyPI ReleasesSource CodeIssue Tracker
Package: pdLSR
pdLSR
by Michelle L. GillpdLSRis a library for performing least squares regression. It attempts to
seamlessly incorporate this task in a Pandas-focused workflow. Input data
are expected in dataframes, and multiple regressions can be performed using
functionality similar to Pandasgroupby. Results are returned as grouped
dataframes and include best-fit parameters, statistics, residuals, and more.pdLSRhas been tested on python 2.7, 3.4, and 3.5. It requires Numpy,
Pandas, multiprocess (https://github.com/uqfoundation/multiprocess), and
lmfit (https://github.com/lmfit/lmfit-py). All dependencies are installable
via pip or conda (see README.md).A demonstration notebook is provided in thedemodirectory or the demo
can be run via GitHub (see README.md).
Package: pdm-autoexport
pdm-autoexportA PDM plugin to sync the exported files with the project file.InstallationInstall the plugin with PDM CLI:pdmpluginaddpdm-autoexportOr usingpipx inject:pipxinjectpdmpdm-autoexportUsageConfigure the requirement mapping inpyproject.toml:[[tool.pdm.autoexport]]filename="requirements/prod.txt"groups=["default"][[tool.pdm.autoexport]]filename="setup.py"format="setuppy"Then the requirement files will be synced every time when the lock file is updated.ConfigurationThe configuration is an array of table[[tool.pdm.autoexport]]where each item may contain the following keys:filename(required): The path to the exported file.groups(optional, default:["default"]): The groups of optional dependencies or dev dependency groups of PDM to sync with.format(optional, default:"requirements"): The format of the exported file, same as the--formatoption to thepdm exportcommand.
Onlyrequirementsandsetuppyare supported.without-hashes(optional, default:false): Whether to remove the hashes from the exported file. Only applicable torequirementsformat.
Package: pdm-backend
PDM-BackendThe build backend used byPDMthat supports latest packaging standards.This is the backend forPDMprojects that is fully-compatible withPEP 517spec, but you can also use it alone.
It reads the metadata ofPEP 621format and coverts it toCore metadata.LinksDocumentationChangelogPDM DocumentationPyPIDiscordNOTEThis project has been renamed frompdm-pep517and the old project lives in thelegacybranch.SponsorsLicenseThis project is licensed underMIT license.
Package: pdm-buildasset
pdm-buildassetA PDM plugin to build external assets such as a react UI.ConfigurationConfig itemDescriptionDefault valueRequiredbuild-asset.disable_hookDisable assets being built during build commandFalseNobuild-asset.{asset_name}.directoryDirectory of where the asset resides relative to the project rootYesbuild-asset.{asset_name}.commandCommand to build the assetYesbuild-asset.{asset_name}.envDictionary of environment variables for the build command{}Nobuild-asset.{asset_name}.dest_dirDestination directory of build assetNobuild-asset.{asset_name}.clean_destRemove destination directory at start of buildTrueNobuild-asset.{asset_name}.create_destCreate destination directory at start of buildTrueNoAll configuration items use prefixpdm.tool, this is a viable configuration:Example configuration[tool.pdm.build-asset]disable_hook=false[tool.pdm.build-asset.kiosk]directory="ui/kiosk"command="npm install && npm run build"env={BUILD_PATH="../../frontend/kiosk"}dest_dir="frontend/kiosk"[tool.pdm.build-asset.manage]directory="ui/manage"command="npm install && npm run build"UsageThis plugin enables PDM to build external assets during the normal build command.pdm build- Command builds assets then continues as normalpdm build-asset- Command builds assets only
Package: pdm-buildlocked
pdm-buildlockedAdds the ability to build the project using locked dependencies.This is useful when distributing an application via PyPi. It should probably not be
used if you are developing a library. Packages built this way can cause version
conflicts when installed alongside other packages. It should be clearly documented that
projects built in this way should be installed withpipx, or in their own isolated
virtual environment.InstallationThis pdm plugin can be installed with the command:pdm plugin add pdm-buildlockedUsageLocked build mode can be enabled by including the following in yourpyproject.tomlfile. When enabled, runningpdm buildorpdm publishwill cause the resulting
distribution will have all dependencies (including transitive ones) pinned to the
versions specified in the lock file.[tool.pdm.build]buildlocked=true
Package: pdm-bump
pdm-bumpA small PEP440 compliant bump utility for PDM, thePython Development Master.Why?As of PEP621, the pyproject.toml supports project metadata including a project version. If you are using the PDM build backend (according to PEP517), you can also use a file provider that contains your version, which is often referred to as adynamicversion.The project version itself must comply to PEP440, which tells us, that it must consist ofan optional epocha mandatory major version parta mandatory minor version parta mandatory micro version partan optional pre-release part supporting alpha, beta or release-candidate part.Tools likebumpversionorbump2versionuse their own configuration and might not conform to the PEP440 specification.InstallationYou can install it using either pip (pip install [--user] pdm-bump) or using the PDM CLI (pdm self add [--pip-args=--user] pdm-bump).UsageYou can use it the following way:$grepversion=pyproject.tomlversion=0.1.0
$pdmbumppre-release--prealpha# creates 0.1.1a1$pdmbumppre-release--prebeta# creates 0.1.1.b1$pdmbumppre-release--prerelease-candidate# creates 0.1.1rc1$pdmbumpno-pre-release# creates 0.1.1$pdmbumpmicro# creates 0.1.2$pdmbumpminor# creates 0.2.0$pdmbumpmajor# creates 1.0.0VCS based actionsNOTE: Currently, onlygitis supported as VCS provider.You can create tags based on yourpyproject.tomlversion (or dynamic version) using the following command.$pdmbumptag# creates a git tag with a leading vContributingFeel free to submit issues and pull requests. Contributions are welcome.Pre-checksTests: To run the tests for your current checks, runpdm run pytest.tox: If you are usingpyenvyou can usepdm run toxto run the tests for all supported Python versions.Code Style: You can usepdm check-styleto check code format.Format: You can usepdm formatto format your code.Commit messages: You can runpdm check-commitsto rungitlinton your commit messages.Before opening a Pull Request make sure that the quality gates are passed.
Package: pdm-django
pdm-django: Django command shortcuts for PDMA plugin that gives you command shortcuts for developing withPDM.pdm run python manage.py runserver->pdm manage runserverpdm run django-admin startproject narf->pdm django-admin startproject narfRequirementsTested with PDM 2.1.XInstallpdm plugin add pdm-djangoUsagemanage.pyExample:pdm manage runserverdjango-adminExample:pdm django-admin startproject narfConfiguring .envpdm-django inherits from thepdm runcommand, so if you would like to load a dotenv file, use the same notation in yourpyproject.tomlfile.[tool.pdm.scripts]_.env_file=".env"CLI Option ConflictsYou may run into some options conflicts between thepdmcommand and the Django command you run. As of right now the only one I can find ispdm manage --helpfor which you will get the pdm help instead of the Django help. However, note you can still runpdm manageorpdm manage helpto view the Django help. Same situation applies forpdm django-admin --help.Shameless PlugsI built this library originally for theNeutronSync Service. So if you would like to support this project please support the service with a subscription to NeutronSync or adonationto the open source libraries.
Package: pdm-dockerize
pdm-dockerizeHelp generating docker image from PDM projectsInstallationInstallpdm-dockerize:WithpipxIf you installedpdmwithpipxand want to have the command for all projects:pipx inject pdm pdm-dockerizeWithpipIf you manually installedpdmwithpip, just install the extra dependency in the same environment:pip install pdm-dockerizeWithpdmYou can also install it as a standardpdmplugin.Either globally:pdm self install pdm-dockerizeEither as a local plugin in your project:[tool.pdm]plugins=["pdm-dockerize",]Then:pdm install --pluginsUsageJust usepdm dockerizein your multistage build:# syntax=docker/dockerfile:1ARGPY_VERSION=3.11### Build stage: build and install dependencies##FROMpython:${PY_VERSION}ASbuilderARGVERSION=0.devENVPDM_BUILD_SCM_VERSION=${VERSION}WORKDIR/project# install PDMRUNpipinstall-UpipsetuptoolswheelRUNpipinstallpdmpdm-dockerizeRUN--mount=type=bind,source=pyproject.toml,target=pyproject.toml\--mount=type=bind,source=pdm.lock,target=pdm.lock\--mount=type=cache,target=$HOME/.cache,uid=$UUID\pdmdockerize--prod-v### Run stage: create the final runtime container##FROMpython:${PY_VERSION}ASruntimeWORKDIR/app# Fetch built dependenciesCOPY--from=builder/project/dist/docker/app# Copy needed files from your project (filter using `.dockerignore`)COPY./appENTRYPOINT["/app/entrypoint"]CMD["your-default-command"]Selecting scriptsBy default, thedockerizecommand will render a script without any command as it does not select any script by default.You can select scripts with theincludeandexcludeproperties of thetool.pdm.dockerizesection.
Those properties are optional, can be either a string or list of string.
Each string is afnmatchfilter patternDockerize first select script based on the include patterns and then filter-out those matching with any exclude pattern.Include all scripts[tool.pdm.dockerize]include="*"Include some specific scripts[tool.pdm.dockerize]include=["my-script","my-other-script"]Include all scripts excluding those matchingprefix-*[tool.pdm.dockerize]include="*"exclude="prefix-*"Include all scripts matching a prefix but two[tool.pdm.dockerize]include="prefix-*"exclude=["prefix-not-you","prefix-you-neither"]Selecting binariesBy default, thedockerizecommand will not copy any python executable provided by your dependencies.
You can select binaries with theinclude_binsandexclude_binsproperties of thetool.pdm.dockerizesection.
Syntax and behavior are exactly the exact sames thaninclude/excludefor script selection.Include all python executables[tool.pdm.dockerize]include_bins="*"Include some specific executablesMost of the time, you will look like this[tool.pdm.dockerize]include=["uvicorn"]ContributingRead thededicated contributing guidelines.
Package: pdm-download
pdm-downloadA PDM plugin to download all packages in a lockfile for offline use.Installationpdmselfaddpdm-downloadUsageThis plugin adds a new commandpdm download, with the following options:pdmdownload--help
Usage:pdmdownload[-h][-LLOCKFILE][-v|-q][-g][-pPROJECT_PATH][-dDEST]Downloadallpackagesfromalockfileforofflineuse

Options:-h,--helpShowthishelpmessageandexit.-LLOCKFILE,--lockfileLOCKFILESpecifyanotherlockfilepath.Default:pdm.lock.[envvar:PDM_LOCKFILE]-v,--verboseUse`-v`fordetailedoutputand`-vv`formoredetailed-q,--quietSuppressoutput-g,--globalUsetheglobalproject,supplytheprojectrootwith`-p`option-pPROJECT_PATH,--projectPROJECT_PATHSpecifyanotherpathastheprojectroot,whichchangesthebaseofpyproject.tomland__pypackages__[envvar:PDM_PROJECT]-dDEST,--destDESTThedestinationdirectory,defaultto'./packages'
Package: pdm-fabric
pdm-fabric: Fabric command shortcut for PDMA plugin that gives you command shortcut for developing withPDMandFabric.RequirementsTested with PDM 2.1.XInstallpdm plugin add pdm-fabricUsagefabExample:pdm fab shell --env devThanks to the following projects as the idea came from them not mehttps://github.com/neutron-sync/pdm-djangohttps://github.com/pdm-project/pdm
Package: pdm-invoke
pdm-invoke: invoke command shortcut for PDMA plugin that gives you command shortcut for developing withPDMandinvoke.RequirementsTested with PDM 2.1.XInstallpdm plugin add pdm-invokeUsageinvExample:pdm inv compress --output dist.zipThanks to the following projects as the idea came from them not mehttps://github.com/neutron-sync/pdm-djangohttps://github.com/pdm-project/pdmfor fabrichttps://github.com/sicksid/pdm-fabric
Package: pdml2flow-elasticsearch
Saves `pdml2flow <https://github.com/Enteee/pdml2flow>`__ output in
elasticsearchBranchBuildCoveragemasterdevelopPrerequisitespdml2flowpython:3.43.53.5-devnightlypipInstallation$sudopipinstallpdml2flow-elasticsearchConfigurationEnvironment variableDescriptionES_HOSTElasticsearch hostnameES_PORTElasticsearch port numberES_INDEXElasticsearch index nameES_TYPEElasticsearch type nameExample
Package: pdml2flow-frame-inter-arrival-time
Calculates frame inter arrival timesBranchBuildCoveragemasterdevelopPrerequisitespython:3.43.53.5-dev3.63.6-dev3.7-devnightlypipInstallation$sudopipinstallpdml2flow-frame-inter-arrival-timeUsageusage:Calculateinterarrivaltimesofframesinafloworonaninterface[-h][--no_flow][--frames]optionalarguments:-h,--helpshowthishelpmessageandexit--no_flowCalculateinterarrivaltimetothepreviousframeontheinterface,notintheflow[default:False]--framesPrinttheframesalongsidetheinterarrivaltime[default:False]ExamplePrint inter arrival times formdump.capture:$tshark-rdump.capture-Tpdml|pdml2flow+frame-inter-arrival-time{"inter_arrival_times":[7.152557373046875e-07,0.0,0.1733696460723877],"frames":null}{"inter_arrival_times":[3.7670135498046875e-05,2.3126602172851562e-05],"frames":null}{"inter_arrival_times":[0.16418147087097168,0.0007672309875488281,0.16009950637817383,0.00016069412231445312,0.0007240772247314453,0.15914177894592285,3.814697265625e-05,5.245208740234375e-06],"frames":null}{"inter_arrival_times":[0.1608715057373047,0.15995335578918457,2.384185791015625e-07,2.384185791015625e-07,2.384185791015625e-07,0.15888381004333496],"frames":null}{"inter_arrival_times":[0.16829872131347656,0.0007762908935546875,0.14913678169250488,0.000125885009765625,0.000736236572265625,10.19379997253418],"frames":null}Print inter arrival times with a different flow aggregation. For
example by interface, if you captured from multiple interfaces:$tshark-rdump.capture-Tpdml|pdml2flow-fframe.interface_name+frame-inter-arrival-time{"inter_arrival_times":[7.152557373046875e-07,0.0,0.00018739700317382812,3.7670135498046875e-05,2.3126602172851562e-05,0.008971691131591797,0.16414976119995117,4.76837158203125e-07,3.123283386230469e-05,0.0007672309875488281,0.16007304191589355,2.6464462280273438e-05,0.00016069412231445312,0.0007240772247314453,0.1590421199798584,2.384185791015625e-07,2.384185791015625e-07,2.384185791015625e-07,9.894371032714844e-05,3.814697265625e-05,5.245208740234375e-06,0.0006232261657714844,0.15811824798583984,0.010167837142944336,1.2636184692382812e-05,0.0007762908935546875,0.14911913871765137,1.7642974853515625e-05,0.000125885009765625,0.000736236572265625,0.16014313697814941,0.035120248794555664,0.2039034366607666,1.907348632,...]}Print arrival times without flow aggregation:$tshark-rdump.capture-Tpdml|pdml2flow+frame-inter-arrival-time--no_flow0.07.152557373046875e-070.00.000187397003173828123.7670135498046875e-052.3126602172851562e-050.0089716911315917970.164149761199951174.76837158203125e-073.123283386230469e-05
Package: pdm-mina
Mina Package Structure简体中文|EnglishMina是基于pdm-backend的 "模块分包" 实现.Mina同样也是Mina Package Structure的实现, 作为一门独特的规范, 其具有以下特性:将整个项目作为工作区环境, 通过现有的设施统一管理所有分包使用的依赖树;分包各自声明自己的信息和工作区中引用的依赖;对pdm-backend构建发布时所读取的Metadata进行修补以复用其构建流程;通过提供完整的PEP-517构建后端 (build backend), 避免了一些潜在的问题.Mina提供了名为mina-build的PEP-517实现,
同时还提供作为PDM Plugin的简易 CLI 实现;mina-build仅在配置了需要构建的分包名称时才会注入pdm-backend的构建流程,
其他情况下的行为与pdm-backend无异.CLI 中虽提供了一个pdm mina build <package>指令,
但你也可以通过环境变量MINA_BUILD_TARGET或是config-setting中设置mina-target指定需要打包的分包.Quick Start安装插件目前, Mina 仅支持将pdm作为主要的用户功能入口, 但或许poetry会在之后得到支持?elaina@localhost$pipxinjectpdmpdm-mina# or pdmelaina@localhost$pdmselfaddpdm-mina或者在pyproject.toml指定：[tool.pdm]plugins=["pdm-mina"]然后运行：elaina@localhost$pdminstall--plugins运行成功后将在当前项目中启用pdm-mina插件。引入 mina-build在项目的pyproject.toml中配置以下项:[build-system]requires=["mina-build>=0.2.5"]build-backend="pdm.backend"编辑 pyproject.toml假设你有如下的目录结构:mina-example/
├── avilla/
│   ├── core/
│   │   └── __init__.py
│   ├── io/
│   │   └── __init__.py
│   ├── onebot/
│   │   └── __init__.py
│   └── elizabeth/
│       └── __init__.py
└── pyproject.toml如果需要将avilla下的模块发为多个包, 用Mina可以简单的做到,
比如上面这种我们就可以在pyproject.toml内填入以下几个表来声明分包:[tool.mina.packages."core"][tool.mina.packages."io"][tool.mina.packages."onebot"][tool.mina.packages."elizabeth"]Mina的分包声明沿用了PEP-621中的声明方式.
我们这里以配置分包core举例.[tool.mina.packages."core"]includes=["avilla/core"]# 相当于 tool.pdm.includes, 如果不填我不知道会发生什么, 可能就是普通的情况 -- 打包 name 所指向的模块.# override = false[tool.mina.packages."core".project]name="avilla-core"# 分包在 `pypi` 上的名称, 必填description="..."authors=["..."]version="0.1.0"# 版本, 不保证支持动态获取(因为我没用过也没试过)requires-python=">=3.9"dependencies=[# 建议填入"aiohttp",# 这里虽然使用 `PEP-508` 规范, 但所有包都会被重定向至 project.dependencies 上的同名项."starlette","pydantic"]optional-dependencies={"amnesia":["graia-amnesia"]# optional dependencies 示例}entry-points={pdm={mina="mina.plugin:ensure_pdm"}}# entry-points 的声明方式填入后, 你可以通过 CLI 的pdm mina list简单的检查, 或是直接pdm mina build <pkg>测试;构建发布包使用pdm mina build <pkg>可以构建对应的分包.如果你希望, 你可以使用pdm mina build -a/--all一次性构建所有的分包.这里推荐使用twine+keyring发布到 PyPI 上, 当然pdm-publish, 或是用 Github Actions 也是可以的.覆盖工作区配置如果你希望, 你可以让 Mina 在处理和注入分包的project定义时, 使用覆盖工作区配置的形式来获得 Project Spec; 本特性默认不启用:[tool.mina]override-global=true# 全局启用该特性[tool.mina.packages."core"]override=true# 仅在 core 分包启用该特性开源协议本项目使用 MIT 协议开源.