DataGuard
- Source: GitHub repository
- Documentation: DataGuard documentation
- Changelog: CHANGELOG.md
DataGuard supports Python 3.10 and later.
Features
- Flexible validation checks: Define simple checks using built-in commands (equality, comparisons, nullability, etc.)
- Complex check expressions: Combine multiple checks with conjunctions (
and), disjunctions (or), and conditionals (when-then) - N-ary expressions: Support for 2 or more expressions in conjunction/disjunction operations (v0.5.0+)
- Nested expressions: Compose complex conditions by nesting check expressions
- Custom validation functions: Define your own validation logic following the framework's signature pattern
- DataFrame-level checks: Apply validations across entire dataframes or specific column groups
- Config-based filtering: Filter rows and columns using the same expression notation as checks — simple predicates or compound conjunctions/disjunctions/conditionals
- Detailed error reporting: Collect and format validation errors with custom messages and severity levels
- Polars support: Built on Polars for efficient data processing at scale
Installation
The package is published on PyPI as peh-dataguard and imported as
dataguard.
Install with uv
For a uv-managed project, add DataGuard as a dependency:
uv add peh-dataguard
To install it into the current environment without changing a project file:
uv pip install peh-dataguard
Install with pip
Create and activate a virtual environment, then install the package:
python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade pip
python -m pip install peh-dataguard
On Windows PowerShell, activate the environment with
.venv\Scripts\Activate.ps1 instead of source.
Verify that the public API can be imported:
python -c "from dataguard import Filter, Validator; print('DataGuard is ready')"
For a uv-managed project, use uv run python ... instead of python ....
Development
For a source checkout, install the development dependencies with Python 3.14:
git clone https://github.com/eu-parc/dataguard.git
cd dataguard
uv sync --python 3.14
Run the project checks with:
make test
make lint
make format
To preview the Zensical documentation locally:
make serve
Release files for peh-dataguard 0.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| peh_dataguard-0.6.1.tar.gz | 133.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| peh_dataguard-0.6.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 152.7 kB
Release files / peh_dataguard-0.6.1.tar.gz
| Download URL | peh_dataguard-0.6.1.tar.gz |
|---|---|
| Size | 133.6 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Yes |
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Transparency logRelease files / peh_dataguard-0.6.1-py3-none-any.whl
| Download URL | peh_dataguard-0.6.1-py3-none-any.whl |
|---|---|
| Size | 19.1 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 25, 2026.
Transparency log