Data Science Folder Structure Setup
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This was developed for creating a Python folder to start a data science project.
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It includes preconfigured connections to different systems:
- uv
- git
- GitHub workflow
- .gitignore
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It also provides small code snippets for connecting to other systems.
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Below are some of the systems included, along with additional setup steps to get them working:
- logging
- SQL
- src
- config
- pre-commit hook
- .gitignore
- git
- GitHub workflow
- uv
- env
- validation
- testing
- requirements.txt
- Install dependencies with:
uv install requirements.txt
- Install dependencies with:
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Install the package:
pip install datascience-folder-structure
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Create a folder structure:
createdatasciencefolder NameOfProject or ```bash dsf NameOfProject
1 maintainer
Metadata
1 maintainer
Release files for datascience-folder-structure 1.1.1.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| datascience_folder_structure-1.1.1.1.tar.gz | 28.3 kB | Without provenance | Details for datascience_folder_structure-1.1.1.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| datascience_folder_structure-1.1.1.1-py3-none-any.whl | Python 3 | none | any | Details for datascience_folder_structure-1.1.1.1-py3-none-any.whl |
Total release size: 68.0 kB
Release files / datascience_folder_structure-1.1.1.1.tar.gz
| Download URL | datascience_folder_structure-1.1.1.1.tar.gz |
|---|---|
| Size | 28.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/7.0.0 CPython/3.11.9
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Release files / datascience_folder_structure-1.1.1.1-py3-none-any.whl
| Download URL | datascience_folder_structure-1.1.1.1-py3-none-any.whl |
|---|---|
| Size | 39.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.9
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