pydmo
Documentation: https://strayMat.gitlab.io/pydmo
Source Code: https://gitlab.com/strayMat/pydmo
This projects implements the creation of [pydantic] data models from a collection of dataset (eg. pandas dataset).
Motivation
Having typed data models in python files is very useful for :
- Code testing thanks to dummy data generation
- Data validation
- Documentation generation
These usages are motivated by the data templates with pydantic blog post.
Links with other projects
The Table-schema-translator takes yaml as input to generate scala data models for spark.
We use the pydantic code generation package.
The python API should be installed with pip as recommanded in the documentation.
📝 Note
- Might be useful if we want to integrate some features existing only on table schema: Pandas api for table schema
Release files for pydmo 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pydmo-0.0.1.tar.gz | 10.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pydmo-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:19.3 kB
Release files / pydmo-0.0.1.tar.gz
| Download URL | pydmo-0.0.1.tar.gz |
|---|---|
| Size | 10.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Release files / pydmo-0.0.1-py3-none-any.whl
| Download URL | pydmo-0.0.1-py3-none-any.whl |
|---|---|
| Size | 9.1 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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poetry/1.1.10 CPython/3.9.5 Linux/5.10.16.3-microsoft-standard-WSL2
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