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Changelog

This document describes changes to the APIs.

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0.7.0

Depends on redis-py 3.0 or newer. There are a number of backwards-incompatible changes in redis-py. Because walrus provides high-level abstractions for the Redis data-types/commands, your walrus code should work with little or no modifications. Refer to the list of changes for more information.

redis-py added support for stream commands as well as zpop/bzpop. As a result, walrus no longer contains separate implementations for these commands. For the majority of cases the low-level method signatures and return values are unchanged, notably, the XREADGROUP return value is slightly different. The timeout parameter, where it was accepted, has been renamed to block for greater compatibility with redis-py.

Prior to 0.7.0, you would read from a consumer-group (which might contain one or more streams) and receive a dict keyed by the stream, whose value was a list of (message_id, data) 2-tuples. Going forward, the return value will be a list of [stream_name, [(message_id, data), ...]]. To retain the functionality of walrus prior-to 0.7.0, just wrap the return value in a call to the dict constructor: ret = dict(consumer_group.read(count=1)).

  • Added BloomFilter container type, which supports add() and contains().
  • Added a high-level BitField container type.

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0.6.0

  • Stream support added, including consumer groups.
  • Support for zpopmin, zpopmax, and the blocking bzpopmin, bzpopmax
  • Added APIs to container classes for converting to-and-from native data-types.
  • Added atomic compare-and-set method to database.

0.5.2

  • Fixed incompatibilities with Python 3.7.
  • Fixed incorrect result scoring in full-text search model.

0.5.1

  • Added standalone full-text search.
  • Refactored various internal classes that support the new standalone full-text search index.

0.5.0

  • The models API uses a backwards-incompatible serialization approach. This means that data stored using 0.4.1 cannot be read back using 0.5.0.
  • Field() no longer supports pickled or as_json parameters. Instead, use the PickledField and JSONField.