This project contains sample scripts for data ingestion of sample data to the Exabel platform.

All files will have documentation on how to run them. You will need to install exabel-data-sdk in your Python environment. PyPi: https://pypi.org/project/exabel-data-sdk/

The data model implemented in this project can be visualized as follows:

For easy installation of all dependencies, run the following commands in the root directory of the project:

# Install pipenv
pip install pipenv
# Install dependencies to virtual environment
pipenv install
# Start virtual environment
pipenv shell

Documentation on how to run the scripts is found below. Before running any of the scripts, replace the values of EXABEL_API_KEY and EXABEL_NAMESPACE in the upload_data.sh / upload_data.ps1 file with the API key and namespace you have been provided by Exabel.

In a production environment, you will want to store the API key in a secure location and load it to the environment variables before execution.

The sample scripts are provided in the scripts directory in two versions. scripts/sh and scripts/ps1. On Linux and MacOS use the .sh files, and on Windows, use the .ps1 files.

On windows, you can run the scripts with the following command:

powershell.exe .\scripts\ps1\<script>.ps1

And on Linux and MacOS:

./scripts/sh/<script>.sh

This script uploads the following to the Exabel platform:

1. the brands in resources/data/entities/brands.csv
2. the relationships in resources/data/relationships/HAS_BRAND.csv
3. the time series data points in resources/data/time_series/brand_time_series.csv
4. the time series data points in resources/data/time_series/brand_time_series_one_day.csv. This example shows how the usual daily/weekly/monthly incremental load can be performed with the current time set as known time.

The script can also be run "line by line" by running each line in the root directory of the project.

Note: There are multiple ways of uploading point-in-time accurate data, the sample upload scripts also contain an example of uploading time series with a fixed offset of days. Please see the Exabel API documentation for more information.

To delete the resources created, run this script.

This script creates geometric brownian movement sample data for the brands in resources/data/entities/brands.csv.

Usage:

# In the root directory of the project
python scripts/py/create_time_series_data.py

• Exabel Data SDK on PyPI
• Exabel Data SDK on GitHub
• Exabel Data API documentation