Redis-dict

Latest version: v3.1.2

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2.3.0

* bumped package versions for security
* small update for readme

2.1.0

Not secure
In this release, a new feature has been added to the RedisDict functionality: Preserve Expiration. This feature enables the user to maintain the existing TTL (Time to Live) value of a key when it is updated, rather than resetting it to the default or global expire time.

Now, when an existing key is updated and preserve_expiration is set to True, the current TTL of the key is preserved. This effectively allows keys to retain their original expiration settings even after their values have been updated. This provides greater flexibility and control over individual key expiration settings in your Redis data store.

The new feature has been thoroughly tested to ensure its reliable functionality. The unittests added cover various scenarios of using the preserve_expiration configuration parameter.

Special thanks to GitHub user cterrazas2, who not only brought this issue to attention, but also contributed to the solution by providing the initial code for this feature. The involvement has been invaluable in making this enhancement possible.

2.0.3

Not secure

2.0.2

Not secure
Added typehinting
Added google style dosctrings
Added type tuple
Added type set
Added fuzz testing
Added load testing script
Added some other tests

Changed some peformance updates
Changed README.md
Changed redis version for security
Changed redis package to lastest version

passes "mypy --strict"
passes pylama

1.6.1

Not secure
Updated future package

1.6.0

Not secure
Added experimental support lists and dictionaries.

Using JSON as serialization list and dictionaries can now be stored.
But using JSON serialization of lists, and dictionaries is not always guaranteed to work.

JSON serialization still has the issue with referenced types, and with dictionaries the key type is forced to a string.
That means that some parts of your dictionary could change.

For storage of Dictionaries in another way the "chain" feature can be used.
That way all the data stored on Redis will keep the same performance as all other operations.

There for it's it's feature that could work in some use-cases but not all.

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