A simple set of symmetric encoder/decoder classes for serializing to and from bytearrays.

pip install py-coders==1.1.5



A simple set of symmetric strongly-typed encoder/decoder classes for serializing to and from byte-like objects. The intended use case for these is to allow for composable encoding of raw byte arrays, operations that may be common to systems working with low level key-value stores (memcached/Redis/LMDB/etc) or passing binary messages in message queues (e.g. Protocol Buffers as messages in RabbitMQ).


Coders are meant to have a simple interface:

  • Coder.encocde(obj) to serialize objects to a bytes-like object.
  • Coder.decode(buf) to deserialize objects from a byte-like object.

Supported Base Coders

  • IdentityCoder - passes bytes through unchanged.
  • StringCoder - string objects, supports ascii, utf8, utf16, etc. encodings.
  • IntCoder, UInt16Coder, UInt32Coder, UInt64Coder - general or unsigned 16/32/64 bit integers. (Big-endian)
  • JSONCoder - JSON serializable python object
  • PickleCoder - Any picklable Python object.
  • ProtobufCoder - Google Protobuf objects. Requires protobuf to be installed.

Chaining Coders

Coders can be chained sequentially to create sequences of encoding/decoding. For example, to make a Coder that can encode and decode encrypted compressed JSON blobs, the following code can be used:

compressed_json_coder = ChainCoder([

This chaining is pretty common in creating composite Coders so all Coders have a then function that can be used in a fluent API.

compressed_json_coder = JSONCoder().then(ZlibCoder(level=5)) \

Three special use cases, prefixing, compression, and encryption have further shortcuts to reduce repitition.:

prefixed_int_coder = IntCoder().prefixed(prefix=b'users:')
compressed_json_coder = JSONCoder().compressed(level=5).encrypted(

Note: what is shown here as an example may not be entirely seucre. It's meant as an example of what can be done with the API, not what should be done. Compressing then encrypting data may weaken security depending on the context in which it's used.

Sequence / Stream Processing

Coders support encoding/decoding arbitrary streams of data via Coder.encode_all and Coder.decode_all. These operations use generator expressions, so they can operate on arbitrarily long, possilby infinite streams of data.

json_coder = JSONCoder().compressed(level=5)

# Works with normal iterables
json_blobs = json_coder.encode_all([{"name": "object_1"}, {"name": "object_2"}])

# Can run over infinite streams of inputs.
for messages in json_coder.decode_all(input_stream()):
    // Handle messages

Async iterators are also supported via the Coder.encode_all_async and Coder.decode_all_async alternatives.

json_coder = JSONCoder().compressed(level=5)

# Can run over infinite streams of inputs.
async for messages in json_coder.decode_all(async_input_stream()):
    // Handle messages

Error handling can be done without terminating the stream by providing a on_error parameter.

json_coder = JSONCoder().compressed(level=5)

def json_on_error(msg, exc, exc_type, traceback):
    // handle decoding errors here

# Can run over infinite streams of inputs.
async for messages in json_coder.decode_all(async_input_stream(),
    // Handle messages