sphinx-reports 0.11.1

A Sphinx extension providing reports and summaries embedded in documentation pages.

Sphinx Reports

The Sphinx extension sphinx_reports offers a set of directives to integrate reports and summaries into the documentation generated by Sphinx.

Supported format reports are:

• ✅🚧 Unit Test summaries (by pytest)
  • ✅ Summary page (displaying unittest.xml)
  • 🚧 Show logging, output and error messages.
• 🚧 Code coverage (by Coverage.py)
  • ✅ Summary page (displaying coverage.json)
  • 🚧 Individual Sphinx documents per package/module
  • 🚧 Highlighted source code with syntax highlighting and coverage highlighting
• 🚧 Documentation coverage
  • ✅ Summary page (displaying data from """docstr_coverage""")
  • ❓ Additionally support interrogate as data source.
  • 🚧 Individual Sphinx documents per package/module
  • 🚧 Highlighted source code with syntax highlighting and coverage highlighting
• 🚧 Package Dependencies
  • 🚧 Summary page (displaying requirements.txt)

Extension Configuration

This README demonstrates a quick and minimal configuration for the Sphinx extension and it's provided directives. See the sphinx-reports documentation for more details.

At first, add the extension name to the list of extensions in conf.py, so the extension is loaded by Sphinx.

# Sphinx extensions
extensions = [
  # ...
  "sphinx_reports",
]

Each report directive might require an individual configuration, therefore see the next sections for details.

Unittest Report Summary

The Unittests Report collects the success or failure of unittests. The results are typically stored in an XML file, which can be read by sphinx-reports. After reading the structure of testsuites and testcases, the report can be visualized. The user

This is a quick and minimal configuration for the unittest summary directives. See the unittest documentation for more details.

Quick Configuration - Step-by-Step

1. Configure one or more coverage analysis reports in conf.py by adding a new 'section' defining some configuration variables. Each unittest report is identified by an ID, which is later referred to by the report directive. Here, the ID is called src (dictionary key). Each unittest report needs 1 configuration entry:

   • xml_report - The unittest report as XML file as generated by pytest.

   report_unittest_testsuites = {
     "src": {
       "xml_report": "../report/unit/unittest.xml"
     }
   }
   

2. Add the unittest-summary directive into your Restructured Text (ReST) document.

   • reportid - The ID used in conf.py to describe a report.

   .. report:unittest-summary::
      :reportid: src
   

Code Coverage Summary

Code Coverage checks if a source code was used during execution. Usually, testcases are run by a testcase execution framework like pytest, which also offers to instrument the code for code coverage collection using the pytest-cov plugin. For Python, coverage collection is usually based on Coverage.py, which supports statement and branch coverage collection either as XML or JSON files. sphinx-reports can visualize a code coverage summary from JSON files.

This is a quick and minimal configuration for the code coverage directives. See the code coverage documentation for more details.

Quick Configuration - Step-by-Step

1. Configure one or more coverage analysis reports in conf.py by adding a new 'section' defining some configuration variables. Each analysis report is identified by an ID, which is later referred to by the report directive. Here, the ID is called src (dictionary key). Each analysis report needs 4 configuration entries:

   • name - Name of the Python package¹.
   • json_report - The code coverage report as JSON file as generated by Coverage.py.
   • fail_below - An integer value in range 0..100, for when a code coverage is considered FAILED.
   • levels - A predefined color pallet name or a dictionary of coverage limits, their description and CSS style classes.

   # ==============================================================================
   # Sphinx-reports - CodeCov
   # ==============================================================================
   report_codecov_packages = {
     "src": {
       "name":        "myPackage",
       "json_report": "../report/coverage/coverage.json",
       "fail_below":  80,
       "levels":      "default"
     }
   }
   

2. Add the code-coverage directive into your Restructured Text (ReST) document.

   • reportid - The ID used in conf.py to describe a Python package.

   .. report:code-coverage::
      :reportid: src
   

Documentation Coverage Summary

Documentation Coverage counts how many publicly accessible members are documented using a Python doc-string. Based on the count of possibly documented public members and the actual number of non-empty doc-strings, a percentage of documentation coverage can be computed.

Documentation coverage is a measure of code quality, which expresses how well documented (completeness or documentation, but not necessarily quality/helpfulness of documentation) source code is. Well documented code helps to use and maintain the existing code base. It also allows for automated documentation generation.

This is a quick and minimal configuration for the documentation coverage directives. See the documentation coverage documentation for more details.

Quick Configuration - Step-by-Step

1. Configure one or more Python packages for documentation coverage analysis in conf.py by adding a new 'section' defining some configuration variables. Each package is identified by an ID, which is later referred to by the report directive. Here, the ID is called src (dictionary key). Each package needs 4 configuration entries:

   • name - Name of the Python package¹.
   • directory - The directory of the package to analyze.
   • fail_below - An integer value in range 0..100, for when a documentation coverage is considered FAILED.
   • levels - A predefined color pallet name or a dictionary of coverage limits, their description and CSS style classes.

   # ==============================================================================
   # Sphinx-reports - DocCov
   # ==============================================================================
   report_doccov_packages = {
     "src": {
       "name":       "myPackage",
       "directory":  "../myPackage",
       "fail_below": 80,
       "levels":     "default"
     }
   }
   

2. Add the doc-coverage directive into your Restructured Text (ReST) document.

   • reportid - The ID used in conf.py to describe a Python package.

   .. report:doc-coverage::
      :reportid: src
   

Package Dependencies

🚧 In planning phase 🚧

Contributors

• Patrick Lehmann (Maintainer)
• and more...

License

This Python package (source code) is licensed under Apache License 2.0.
The accompanying documentation is licensed under Creative Commons - Attribution-4.0 (CC-BY 4.0).

---

SPDX-License-Identifier: Apache-2.0

1. Toplevel Python packages can reside in a directory not matching the package name. This is possible because the toplevel package name is set in the package installation description. This is not good practice, but possible and unfortunately widely used. E.g. src as directory name. ↩ ↩²