Oracle Fusion GL Balance API visualizer
This repository contains a Python Dash application. Dash is a Python framework for building web applications with highly interactive data visualizations. The application also utilizes Ag-Grid for powerful data grid features, Pygwalker for visual data exploration, Pandas for data manipulation, DuckDB for efficient SQL-based querying, and integrates with the Oracle Fusion Ledger Balances API (API Documentation) to retrieve ledger balance data. This guide will walk you through the process of installing the required dependencies and running the application on your local machine.
To run this application, you need the following software installed:
-
Python 3.12 or later: Make sure Python is installed. You can download it from python.org.
-
Git: (Optional) If you wish to clone the repository directly.
Follow these steps to set up the application locally.
First, clone the repository from GitHub to your local machine. You can do this by running the following command in your terminal:
git clone https://github.com/krokozyab/GLWALKER.git
Navigate to the cloned repository and create a virtual environment to manage the project dependencies.
cd GLWALKER
python -m venv venv
Activate the virtual environment:
- On Windows:
venv\Scripts\activate
- On macOS/Linux:
source venv/bin/activate
Install the necessary packages using pip. The dependencies are listed in the requirements.txt file.
pip install -r requirements.txt
If you don't have a requirements.txt file, create one by running:
pip freeze > requirements.txt
This will save all your current Python environment dependencies.
Create a .env file by following the provided sample.env file, ensuring that all necessary environment variables are correctly defined.
The gl_list.json file represents the Chart of Accounts (COA) structure. Since there is no available API to retrieve this information, it must be configured manually. A SQL script (gl_ledger_struct.sql) has been provided to help obtain the necessary attributes. You can execute this script within the Fusion OTBI data model to extract the required data. Then, use the provided sample file (lg_list_sample.json) as a reference to create the final lg_list.json file.
To start the Dash application, run the following command:
python main.py
This should launch the Dash application, and it will be available in your web browser at:
http://127.0.0.1:8050/
If you need to modify the application, edit the Python scripts in the repository. Any changes will be reflected after you save the files and restart the server.
ModuleNotFoundError: Ensure you are in the virtual environment and all dependencies are installed properly.
Port Issue: If 8050 is in use, you can change the port in the app.run_server() function:
app.run_server(debug=True, port=8051)
Feel free to submit pull requests to contribute to the project. For major changes, please open an issue first to discuss what you would like to change.
This project is licensed under the MIT License. See the LICENSE file for more details.
If you have questions, feel free to reach out via GitHub Issues or [email@rudenko.s@gmail.com].
