Metadata-Version: 2.1
Name: databridge
Version: 0.2.1
Summary: Bridge to import shared datasets across diverse projects.
Author: Rodolfo Souza
Author-email: souzarod@proton.me
License: MIT
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.10
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: geopandas
Requires-Dist: prettytable
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: twine; extra == "dev"

# databridge

The `databridge` package streamlines the management of common datasets across diverse projects.
It facilitates the setup of paths, file names, and Python commands to access centralized files efficiently.

## Why Use databridge?

Managing common datasets across multiple projects often involves repetitive tasks such as saving files, configuring paths, and importing libraries.
The `databridge` package aims to simplify this process by offering a centralized data bucket.

Instead of manually saving files and configuring paths for each project, `databridge` allows you to create a `config.json` file.
This file guides Python on where to locate common datasets locally, reducing redundancy and enhancing efficiency.

## Example 1 - Without databridge

```python
# Import geopandas package
import geopandas as gpd

# Import data
texas_boundaries = gpd.read_file("myproject_data_folder/Texas_boundaries.shp")
```

This method is straightforward but can become repetitive when dealing with multiple projects.


## Example 2 - with databrigde

```python
# Import databridge package
from databridge.databridge import DataBridge

# Initiate databridge class
db = DataBridge()

# Load dataset
texas_boundaries = db.load_dataset("local", "texas_boundaries")
```

Although Example 2 has one extra line of code compared to Example 1, it significantly reduces redundancy.
When dealing with multiple projects, you no longer need to save the file multiple times or manually set different paths.

Explore the power of `databridge` to enhance your workflow and centralize your datasets effortlessly.

