Skip to content
Fountain Code: Efficient Python Implementation of LT Codes
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.

Fountain Code: Efficient Python Implementation of LT Codes

This project is the implementation in Python of the iterative encoding and iterative decoding algorithms of the LT Codes, an error correction code based on the principles of Fountain Codes. I have written a whole article on LT Codes and this snippet that you can find here :

The encoder and decoder are optimized to handle big transfers for files between 1MB to 1GB at high speed.

How to use it

Usage (python 3.x):

python filename [-h] [-r REDUNDANCY] [--systematic] [--verbose] [--x86]

An example describing how to use the implementation is in However:

  • contains the Symbol class, constants and functions that are used in both encoding and decoding.
  • contains the two functions that generate degrees based on the ideal soliton and robust soliton distributions
  • contains the encoding algorithm
  • contains the decoding algorithm
  • calls and then compare the integrity of the original file with the newly created file. The integrity check is made with md5sum.exe, remove the ".exe" if you work on Unix.


The time consumed by the encoding and decoding process is completely related to the size of the file to encode and the wanted redundancy. I have made some measure on an Intel i5 @ 2.30GHz with a 1.5 redundancy :

Size (MB) Blocks Symbols Encoding Decoding
Time (s) Speed (MB/s) Time (s) Speed (MB/s)
1 16 24 0.00 - 0.00 -
100 1600 2400 0.21 476.1 0.31 322.5
1200 19200 28800 3.86 310.8 39.82 30.1
2000 32000 48000 6.44 310.5 104.10 19.2
3600 57600 86400 23.14 155.5 426.36 8.4

You can’t perform that action at this time.