Data Science Folder Structure Setup
-
This was developed for creating a Python folder to start a data science project.
-
It includes preconfigured connections to different systems:
- uv
- git
- GitHub workflow
- .gitignore
-
It also provides small code snippets for connecting to other systems.
-
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:
-
Install the package:
pip install datascience-folder-structure
-
Create a folder structure:
createdatasciencefolder NameOfProject or ```bash dsf NameOfProject
1 maintainer
Metadata
1 maintainer
Release files for datascience-folder-structure 0.1.1.1.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| datascience_folder_structure-0.1.1.1.1.tar.gz | 28.3 kB | Without provenance | Details for datascience_folder_structure-0.1.1.1.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| datascience_folder_structure-0.1.1.1.1-py3-none-any.whl | Python 3 | none | any | Details for datascience_folder_structure-0.1.1.1.1-py3-none-any.whl |
Total release size: 68.0 kB
Release files / datascience_folder_structure-0.1.1.1.1.tar.gz
| Download URL | datascience_folder_structure-0.1.1.1.1.tar.gz |
|---|---|
| Size | 28.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
a619ee987b4ecd0f50d2f91401f4c39fe0852487b7ab7d888727cf0fc8fdd05d
|
|
BLAKE2b-256 checksum How to use checksums |
40239e753136ffc1e85a6cf9ff25fc96f7192e3e739cdbcf03979eb7777516bd
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.9
|
Release files / datascience_folder_structure-0.1.1.1.1-py3-none-any.whl
| Download URL | datascience_folder_structure-0.1.1.1.1-py3-none-any.whl |
|---|---|
| Size | 39.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
6fa03138cacef218817eb0014e8628a3a6fb64a9d350f865eade23a9d5edbf01
|
|
BLAKE2b-256 checksum How to use checksums |
09002beb0fd2c894ecff6a697ec0c0d7d92cd4520515212979c61d1be8bc6607
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.11.9
|
Security for datascience-folder-structure 0.1.1.1.1
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.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
