Science Score: 67.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: zenodo.org -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (15.2%) to scientific vocabulary
Keywords
Repository
Detect quality of (digitized) text.
Basic Info
Statistics
- Stars: 3
- Watchers: 3
- Forks: 0
- Open Issues: 5
- Releases: 10
Topics
Metadata Files
README.dev.md
text_quality developer documentation
If you're looking for user documentation, go here.
Development install
```shell
Create a virtual environment, e.g. with
python3 -m venv env
activate virtual environment
source env/bin/activate
make sure to have a recent version of pip and setuptools
python3 -m pip install --upgrade pip setuptools
(from the project root directory)
install text_quality as an editable package
python3 -m pip install --no-cache-dir --editable .
install development dependencies
python3 -m pip install --no-cache-dir --editable .[dev] ```
Afterwards check that the install directory is present in the PATH environment variable.
Running the tests
There are two ways to run tests.
The first way requires an activated virtual environment with the development tools installed:
shell
pytest -v
The second is to use tox, which can be installed separately (e.g. with pip install tox), i.e. not necessarily inside the virtual environment you use for installing text_quality, but then builds the necessary virtual environments itself by simply running:
shell
tox
Testing with tox allows for keeping the testing environment separate from your development environment.
The development environment will typically accumulate (old) packages during development that interfere with testing; this problem is avoided by testing with tox.
Test coverage
In addition to just running the tests to see if they pass, they can be used for coverage statistics, i.e. to determine how much of the package's code is actually executed during tests. In an activated virtual environment with the development tools installed, inside the package directory, run:
shell
coverage run
This runs tests and stores the result in a .coverage file.
To see the results on the command line, run
shell
coverage report
coverage can also generate output in HTML and other formats; see coverage help for more information.
Running linters locally
For linting we will use prospector and to sort imports we will use isort. Running the linters requires an activated virtual environment with the development tools installed.
```shell
linter
prospector
recursively check import style for the text_quality module only
isort --check-only text_quality
recursively check import style for the text_quality module only and show
any proposed changes as a diff
isort --check-only --diff text_quality
recursively fix import style for the text_quality module only
isort text_quality ```
To fix readability of your code style you can use yapf.
You can enable automatic linting with prospector and isort on commit by enabling the git hook from .githooks/pre-commit, like so:
shell
git config --local core.hooksPath .githooks
Generating the Architecture Diagram
The architecture diagram is stored in the classestextquality.svg file, and displayed in the README.md file. To update it, use pyreverse from the pylint package:
shell
pyreverse --output svg --project text_quality text_quality
Generating the API docs
shell
cd docs
make html
The documentation will be in docs/_build/html
If you do not have make use
shell
sphinx-build -b html docs docs/_build/html
To find undocumented Python objects run
shell
cd docs
make coverage
cat _build/coverage/python.txt
To test snippets in documentation run
shell
cd docs
make doctest
Versioning
Bumping the version across all files is done with bumpversion, e.g.
shell
bumpversion major
bumpversion minor
bumpversion patch
Making a release
This section describes how to make a release in 3 parts:
- preparation
- making a release on PyPI
- making a release on GitHub
(1/3) Preparation
- Update the
(don't forget to update links at bottom of page) - Verify that the information in
CITATION.cffis correct, and that.zenodo.jsoncontains equivalent data - Make sure the version has been updated.
- Run the unit tests with
pytest -v
SKIP: (2/3) PyPI Release
Publishing an updated package on PyPI manually is not necessary for this project. Instead, the Build and Publish Workflow is triggered automatically when a new release is created on GitHub in the next step.
(3/3) GitHub Release
Make a release on GitHub.
Create a new tag in the form v<X.X.X>, where <X.X.X> is the version number as specified in the versioning section.
This will also trigger Zenodo into making a snapshot of your repository and sticking a DOI on it (see Zenodo project page).
Owner
- Name: LAHTeR
- Login: LAHTeR
- Kind: organization
- Repositories: 1
- Profile: https://github.com/LAHTeR
Citation (CITATION.cff)
# YAML 1.2
---
cff-version: "1.2.0"
title: "text_quality"
authors:
- family-names: Schnober
given-names: Carsten
orcid: "https://orcid.org/0000-0001-9139-1577"
date-released: 2023-11-16
doi: https://zenodo.org/doi/10.5281/zenodo.8189892
version: "0.3.1"
repository-code: "git@github.com:laHTeR/htr-quality-classifier"
keywords:
- htr
- ocr
message: "If you use this software, please cite it using these metadata."
license: GPL-3.0
GitHub Events
Total
Last Year
Issues and Pull Requests
Last synced: 7 months ago
All Time
- Total issues: 11
- Total pull requests: 4
- Average time to close issues: 9 days
- Average time to close pull requests: 1 day
- Total issue authors: 2
- Total pull request authors: 1
- Average comments per issue: 0.45
- Average comments per pull request: 1.25
- Merged pull requests: 3
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 0
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 0
- Average comments per issue: 0
- Average comments per pull request: 0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- carschno (10)
- bvreede (1)
Pull Request Authors
- carschno (4)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
-
Total downloads:
- pypi 17 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 5
- Total maintainers: 1
pypi.org: text-quality
A package to determine the quality of a a digitized text, from a handwritten script or scanned print (HTR/OCR output).
- Homepage: https://github.com/laHTeR/htr-quality-classifier
- Documentation: https://text-quality.readthedocs.io/
- License: GNU General Public License v3 (GPLv3)
-
Latest release: 0.3.1
published about 2 years ago
Rankings
Maintainers (1)
Dependencies
- actions/checkout v3 composite
- actions/setup-python v3 composite
- actions/checkout v3 composite
- citation-file-format/cffconvert-github-action main composite
- actions/checkout v2 composite
- actions/setup-python v2 composite
- actions/checkout v3 composite
- gaurav-nelson/github-action-markdown-link-check v1 composite
- actions/checkout v3 composite
- actions/setup-python v4 composite
- pypa/gh-action-pypi-publish release/v1 composite
- SonarSource/sonarcloud-github-action master composite
- actions/checkout v3 composite
- actions/setup-python v3 composite