Requirement : Python objects with 2-3 levels of nesting containing basic datypes like integers,strings, lists, and dicts. ( no dates etc), needs to be stored as json in redis against a key. What are the best methods available for compressing json as a string for low memory footprint. The target objects are not very large, having 1000 small elements on average, or about 15000 characters when converted to JSON.

eg.

>>> my_dict
{'details': {'1': {'age': 13, 'name': 'dhruv'}, '2': {'age': 15, 'name': 'Matt'}}, 'members': ['1', '2']}
>>> json.dumps(my_dict)
'{"details": {"1": {"age": 13, "name": "dhruv"}, "2": {"age": 15, "name": "Matt"}}, "members": ["1", "2"]}'
### SOME BASIC COMPACTION ###
>>> json.dumps(my_dict, separators=(',',':'))
'{"details":{"1":{"age":13,"name":"dhruv"},"2":{"age":15,"name":"Matt"}},"members":["1","2"]}'

1/ Are there any other better ways to compress json to save memory in redis ( also ensuring light weight decoding afterwards ).

2/ How good a candidate would be msgpack [http://msgpack.org/] ?

3/ Shall I consider options like pickle as well ?

We just use gzip as a compressor.

import gzip
import cStringIO

def decompressStringToFile(value, outputFile):
  """
  decompress the given string value (which must be valid compressed gzip
  data) and write the result in the given open file.
  """
  stream = cStringIO.StringIO(value)
  decompressor = gzip.GzipFile(fileobj=stream, mode='r')
  while True:  # until EOF
    chunk = decompressor.read(8192)
    if not chunk:
      decompressor.close()
      outputFile.close()
      return 
    outputFile.write(chunk)

def compressFileToString(inputFile):
  """
  read the given open file, compress the data and return it as string.
  """
  stream = cStringIO.StringIO()
  compressor = gzip.GzipFile(fileobj=stream, mode='w')
  while True:  # until EOF
    chunk = inputFile.read(8192)
    if not chunk:  # EOF?
      compressor.close()
      return stream.getvalue()
    compressor.write(chunk)

In our usecase we store the result as files, as you can imagine. To use just in-memory strings, you can use a cStringIO.StringIO() object as a replacement for the file as well.