Generate and manage CodeMeta software metadata
Project description
Codemetapy
Codemetapy is a command-line tool to work with the codemeta software metadata standard. Codemeta builds upon 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 , 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
- Simple metadata from HTML
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.
Note: If you are looking for an all-in-one solution to automatically
generate a codemeta.json
for your project, then
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.
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 URIs whenever
possible For schema:license
, full SPDX URIs are used where possible.
Identifiers
We distinguish two types of identifiers, first there is the URI or IRI 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, 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:
"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
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.
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.
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
:
try:
from codemeta.codemeta import CodeMetaCommand
cmdclass={
'codemeta': CodeMetaCommand,
}
except ImportError:
cmdclass={}
And in your setup()
call add the parameter:
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.
Acknowledgements
This work is conducted at the KNAW Humanities Cluster's Digital Infrastructure department in the scope of the CLARIAH project (CLARIAH-PLUS, NWO grant 184.034.023) as part of the FAIR Tool Discovery track of the Shared Development Roadmap.
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