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Serpent serialization library (Python/.NET/Java)

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Serpent provides ast.literal_eval() compatible object tree serialization. It serializes an object tree into bytes (utf-8 encoded string) that can be decoded and then passed as-is to ast.literal_eval() to rebuild it as the original object tree. As such it is safe to send serpent data to other machines over the network for instance (because only 'safe' literals are encoded).

More info on Pypi: https://pypi.python.org/pypi/serpent Source code is on Github: https://github.com/irmen/Serpent

Copyright by Irmen de Jong (irmen@razorvine.net) This software is released under the MIT software license. This license, including disclaimer, is available in the 'LICENSE' file.

PYTHON

Compatible with Python 3.7+ (use a serpent version before 1.30 for Python 2.7 support) It can be found on Pypi as 'serpent': https://pypi.python.org/pypi/serpent Example usage can be found in ./tests/example.py

C#/.NET

Package is available on www.nuget.org as 'Razorvine.Serpent'. Full source code can be found in ./dotnet/ directory. Example usage can be found in ./dotnet/Serpent.Test/Example.cs The project is a dotnet core project targeting NetStandard 2.0.

JAVA

Maven-artefact is available on maven central, groupid 'net.razorvine' artifactid 'serpent'. Full source code can be found in ./java/ directory. Example usage can be found in ./java/test/SerpentExample.java Versions before 1.23 require Java 7 or Java 8 (JDK 1.7 or 1.8) to compile and run. Version 1.23 and later require Java 8 (JDK 1.8) at a minimum to compile and run.

SOME MORE DETAILS

Serpent handles several special Python types to make life easier:

Notes:

The serializer is not thread-safe. Make sure you're not making changes to the object tree that is being serialized, and don't use the same serializer in different threads.

Because the serialized format is just valid Python source code, it can contain comments. Serpent does not add comments by itself apart from the single header line.

Floats +inf and -inf are handled via a trick, Float 'nan' cannot be handled and is represented by the special value: {'__class__':'float','value':'nan'} We chose not to encode it as just the string 'NaN' because that could cause memory issues when used in multiplications.