Project Overview
tg-webm-converter is a Python CLI tool designed to automate the conversion of image and video files into WebM format, adhering to Telegram’s specific sticker and icon requirements.
Originating from a personal need to streamline sticker creation, this tool eliminates manual conversion steps, allowing users to effortlessly generate static and animated stickers for a unified sticker pack experience.
It is distributed via PyPI, making it accessible for broader use across various operating systems.
Technical Stack
- Python for Core application logic and CLI interface.
- Poetry for Dependency management and project packaging.
- FFmpeg for High-performance media processing and optimization.
Key Features
- Batch Conversion
- Telegram Sticker Compliance:
- Generates 512x512 WebM stickers (max 256KB).
- Generates 100x100 WebM icons (max 32KB) via dedicated
--icon-file argument.
- Automatic Optimization
- Leverages FFmpeg for efficient encoding and size reduction, ensuring files meet Telegram’s strict size limits without manual intervention.
- Cross-Platform Accessibility
- Rewritten from a shell script into a Python CLI for compatibility beyond
bash/zsh environments, including Windows.
- Streamlined Workflow
- Simplifies the process of creating custom Telegram stickers programmatically, replacing complex manual FFmpeg commands.
Problem Solved
As a Telegram user myself, the process of manually converting media files to meet Telegram’s sticker specifications and
managing separate static and dynamic sticker packs presented a significant friction point.
tg-webm-converter addresses these challenges by:
- Automating tedious conversions: eliminates the need for graphic tools or complex FFmpeg commands.
- Enabling unified sticker packs: converts all media to WebM, allowing both static and dynamic elements within a single sticker pack.
- Providing an accessible solution: offers a user-friendly CLI tool installable via
pip, making it available to a wider audience.
Highlights
Developed with Python 3.8+, tg-webm-converter integrates robust argument parsing for targeted conversions and supports directory-wide processing.
Its release on PyPI facilitates easy installation (pip install tg-webm-converter).
Future enhancements such as GUI support and performance optimizations for large-scale batches are to be seen.