Skip to content

A Python-based GSM data generator for creating synthetic telecom datasets. It supports operator-specific logic, customizable templates, SIM card personalization data.

License

Notifications You must be signed in to change notification settings

hamzaqureshi5/gsm-data-genration_lib

 
 

Repository files navigation

Open GSM Data Generation Stack

Documentation | Contributors | Community | Release Notes

GSM Data Generator is a library for generating and processing structured datasets for GSM, USIM, and eSIM systems. It is designed to bridge the gap between telecom operator requirements and developer productivity, offering flexible tools for data parsing, formatting, and export. The library provides an extensible framework to define operator-specific templates, process large-scale inputs, and generate outputs in standardized formats for downstream telecom systems.

License

Data Generation is licensed under the Apache-2.0 license.

Getting Started

Check out the Data Generation Documentation site for installation instructions, tutorials, examples, and more. The Getting Started with Data Generation tutorial is a great place to start.

Features

Synthetic GSM data generation, Operator-specific templates, Data output in various formats

Contribute to Data Generation

Data Generation adopts the Apache committer model. We aim to create an open-source project maintained and owned by the community. Check out the Contributor Guide.

History and Acknowledgement

Data Generation started as a research project for USIM, ESIM etc.

Since then, the project has gone through several rounds of redesigns. The current design is also drastically different from the initial design, following the development trend of the community.

About

A Python-based GSM data generator for creating synthetic telecom datasets. It supports operator-specific logic, customizable templates, SIM card personalization data.

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 77.7%
  • Shell 19.3%
  • Jupyter Notebook 3.0%