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CodeMetaPy-2.4.1


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توضیحات

Generate and manage CodeMeta software metadata
ویژگی مقدار
سیستم عامل -
نام فایل CodeMetaPy-2.4.1
نام CodeMetaPy
نسخه کتابخانه 2.4.1
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Maarten van Gompel
ایمیل نویسنده proycon@anaproy.nl
آدرس صفحه اصلی https://github.com/proycon/codemetapy
آدرس اینترنتی https://pypi.org/project/CodeMetaPy/
مجوز GPL-3.0-only
[![Project Status: Active -- The project has reached a stable, usable state and is being actively developed.](https://www.repostatus.org/badges/latest/active.svg)](https://www.repostatus.org/#active) [![GitHub build](https://github.com/proycon/codemetapy/actions/workflows/codemetapy.yml/badge.svg?branch=master)](https://github.com/proycon/codemetapy/actions/) [![GitHub release](https://img.shields.io/github/release/proycon/codemetapy.svg)](https://GitHub.com/proycon/codemetapy/releases/) [![Latest release in the Python Package Index](https://img.shields.io/pypi/v/codemetapy)](https://pypi.org/project/codemetapy/) # Codemetapy Codemetapy is a command-line tool to work with the [codemeta ](https://codemeta.github.io) software metadata standard. Codemeta builds upon [schema.org](https://schema.org) and defines a vocabulary for describing software source code. It maps various existing metadata standards to a unified vocabulary. For more general information about the CodeMeta Project for defining software metadata, see <https://codemeta.github.io>. In particular, new users might want to start with the User Guide, while those looking to learn more about JSON-LD and consuming existing codemeta files should see the Developer Guide. Using codemetapy you can generate a `codemeta.json` file, which serialises using [JSON-LD](https://json-ld.org) , for your software. At the moment it supports conversions from the following existing metadata specifications: * Python distutils/pip packages (`setup.py`/`pyproject.toml`) * Java/Maven packages (`pom.xml`) * NodeJS packages (`package.json`) * Debian package (`apt show` output) * Github API (when passed a github URL) * GitLab API (when passed a GitLab URL) * Web sites/services (see the section on software types and service below): * Simple metadata from HTML `<meta>` elements. * Script blocks using `application/json+ld` It can also read and manipulate existing `codemeta.json` files as well as parse simple AUTHORS/CONTRIBUTORS files. One of the most notable features of codemetapy is that it allows chaining to successively update a metadata description based on multiple sources. Codemetapy is used in that way by the [codemeta-harvester](https://github.com/proycon/codemeta-harvester). **Note:** If you are looking for an all-in-one solution to automatically generate a `codemeta.json` for your project, then *[codemeta-harvester](https://github.com/proycon/codemeta-harvester) is the best place to start*. It is a higher-level tool that automatically invokes codemetapy on various sources it can automatically detect, and combined those into a single codemeta representation. ## Installation `pip install codemetapy` ## Usage Query and convert any installed python package: `$ codemetapy somepackage` Output will be to standard output by default, to write it to an output file instead, do either: `$ codemetapy somepackage > codemeta.json` or use the `-O` parameter: `$ codemetapy -O codemeta.json somepackage` If you are in the current working directory of any python project and there is a `setup.py`or `pyproject.toml`, then you can simply call `codemetapy` without arguments to output codemeta for the project. Codemetapy will automatically run `python setup.py egg_info` if needed and parse it's output to facilitate this: `$ codemetapy` The tool also supports adding properties through parameters: `$ codemetapy --developmentStatus active somepackage > codemeta.json` To read an existing codemeta.json and extend it: `$ codemetapy -O codemeta.json codemeta.json somepackage` or even: `$ codemetapy -O codemeta.json codemeta.json codemeta2.json codemeta3.json` This makes use of an important characteristic of codemetapy which is *composition*. When you specify multiple input sources, they will be interpreted as referring to the same resource. Properties (on `schema:SoftwareSourceCode`) in the later resources will *overwrite* earlier properties. So if `codemeta3.json` specifies authors, all authors that were specified in `codemeta2.json` are lost rather than merged and the end result will have the authors from `codemeta3.json`. However, if `codemeta2.json` has a property that was not in `codemeta3.json`, say `deveopmentStatus`, then that will make it to the end rsult. In other words, the latest source always takes precedence. Any non-overlapping properties will be be merged. This functionality is heavily relied on by the higher-level tool [codemeta-harvester](https://github.com/proycon/codemeta-harvester). If you want to start from scratch and build using command line parameters, use `/dev/null` as input, and make sure to pass some identifier and code repository: `$ codemetapy --identifier some-id --codeRepository https://github.com/my/code /dev/null > codemeta.json` This tool can also deal with debian packages by parsing the output of `apt show` (albeit limited): `$ apt show somepackage | codemetapy -i debian -` Here `-` represents standard input, which enables you to use piping solutions on a unix shell, `-i` denotes the input types, you can chain as many as you want. The number of input types specifies must correspond exactly to the number of input sources (the positional arguments). ## Some notes on Vocabulary For `codemeta:developmentStatus`, codemetapy attempts to assign full [repostatus](https://www.repostatus.org/) URIs whenever possible For `schema:license`, full [SPDX](https://spdx.org) URIs are used where possible. ## Identifiers We distinguish two types of identifiers, first there is the URI or [IRI](https://www.w3.org/TR/rdf11-concepts/#section-IRIs) that identifies RDF resources. It is a globally unique identifier and often looks like a URL. Codemetapy will assign new URIs for resources if and only if you pass a base URI using ``--baseuri``. Moreover, if you set this, codemetapy will *forcibly* set URIs over any existing ones, effectively assigning new identifiers. The previous identifier will then be covered via the `owl:sameAs` property instead. This allows you to ownership of all URIs. Internally, codemetapy will create URIs for everything even if you don't specified a base URI (even for blank nodes), but these URIs are stripped again upon serialisation to JSON-LD. The second identifier is the [schema:identifier](https://schema.org/identifier), of which there may even be multiple. Codemetapy typically expects such an identifier to be a simple unspaced string holding a name for software. For example, a Python package name would make a good identifier. If this property is present, codemetapy will use it when generating URIs. The `schema:identifier` property can be contrasted with `schema:name`, which is the human readable form of the name and may be more elaborate. The identifier is typically also used for other identifiers (such as DOIs, ISBNs, etc), which should come in the following form: ```json "identifier:" { "@type": "PropertyValue", "propertyID": "doi", "value": "10.5281/zenodo.6882966" } ``` But short-hand forms such as ``doi:10.5281/zenodo.6882966`` or as a URL like `https://doi.org/10.5281/zenodo.6882966` are also recognised by this library. ## Software Types and services Codemetapy (since 2.0) implements an extension to codemeta that allows linking the software source code to the actual instantiation of the software, with explicit regard for the interface type. This is done via the `schema:targetProduct` property, which takes as range a `schema:SoftwareApplication`, `schema:WebAPI`, `schema:WebSite` or any of the extra types defined in <https://github.com/SoftwareUnderstanding/software_types/> . This was proposed in [this issue](https://github.com/codemeta/codemeta/issues/271) This extension is enabled by default and can be disabled by setting the `--strict` flag. When you pass codemetapy a URL it will assume this is where the software is run as a service, and attempt to extract metadata from the site and encode is via `targetProduct`. For example, here we read an existing `codemeta.json` and extend it with some place where it is instantiated as a service: `$ codemetapy codemeta.json https://example.org/` If served HTML, codemetapy will use your `<script>` block using `application/json+ld` if it provides a valid software types (as mentioned above). For other HTML, codemetapy will simply extract some metadata from HTML `<meta>` elements. Content negotation will be used and the we favour json+ld, json and even yaml and XML over HTML. (Note: the older Entypoint Extension from before codemetapy 2.0 is now deprecated) ## Graph You can use codemetapy to generate one big knowledge graph expressing multiple codemeta resources using the `--graph` parameter: `$ codemetapy --graph resource1.json resource2.json` This will produce JSON-LD output with multiple resources in the graph. ## Github API Codemetapy can make use of the Github API to query metdata from GitHub, but this allows only limited anonymous requests before you hit a limit. To allow more requests, please set the environment variable `$GITHUB_TOKEN` to a [personal access token](https://docs.github.com/en/authentication/keeping-your-account-and-data-secure/creating-a-personal-access-token). ## GitLab API Codemetapy can make use of the GitLab API to query metdata from GitLab, but this allows only limited anonymous requests before you hit a limit. To allow more requests, please set the environment variable `$GITLAB_TOKEN` to a [personal access token](https://docs.gitlab.com/ee/user/profile/personal_access_tokens.html). ## Integration in setup.py You can integrate `codemeta.json` generation in your project's `setup.py`, this will add an extra `python setup.py codemeta` command that will generate a new metadata file or update an already existing metadata file. Note that this must be run *after* `python setup.py install` (or `python setup.py develop`). To integrate this, add the following to your project's `setup.py`: ```python try: from codemeta.codemeta import CodeMetaCommand cmdclass={ 'codemeta': CodeMetaCommand, } except ImportError: cmdclass={} ``` And in your `setup()` call add the parameter: ```python cmdclass=cmdclass ``` This will ensure your `setup.py` works in all cases, even if codemetapy is not installed, and that the command will be available if codemetapy is available. If you want to ship your package with the generated `codemeta.json`, then simply add a line saying `codemeta.json` to the file `MANIFEST.in` in the root of your project.


نحوه نصب


نصب پکیج whl CodeMetaPy-2.4.1:

    pip install CodeMetaPy-2.4.1.whl


نصب پکیج tar.gz CodeMetaPy-2.4.1:

    pip install CodeMetaPy-2.4.1.tar.gz