dogpile.cache | Python caching API which provides a generic interface | Caching library
kandi X-RAY | dogpile.cache Summary
kandi X-RAY | dogpile.cache Summary
dogpile.cache is a Python caching API which provides a generic interface to caching backends of any variety
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Top functions reviewed by kandi - BETA
- Delete multiple keys from the database
- Yields dbm file
- Context manager that yields a context manager
- Context manager for reading
- Set a value for serialized keys
- Set backend to backend
- Return the value of the given key
- Get the value for a key
- Set the value of the key
- Store a key in the backend
- Returns a sequence of serialized values
- Returns a sequence of backends
- Release the lock
- Remove a key from the database
- Set multiple keys in the database
- Delete multiple keys at once
dogpile.cache Key Features
dogpile.cache Examples and Code Snippets
def md5_key_mangler(key):
"""Receive cache keys as long concatenated strings;
distill them into an md5 hash.
"""
return md5(key.encode("ascii")).hexdigest()
md5(key.encode("ascii")).hexdigest()
install_requirements = ['guessit>=2.0.1', 'babelfish>=0.5.2', 'enzyme>=0.4.1', 'beautifulsoup4>=4.4.0',
'requests>=2.0', 'click>=4.0', 'dogpile.cache>=0.6.0', 'stevedore>=1.0.0',
Community Discussions
Trending Discussions on dogpile.cache
QUESTION
I'm using dogpile.cache in a Python project, with a pylibmc based backend. After creating a region I use something like:
...ANSWER
Answered 2019-Jun-13 at 11:36Decorators are just functions. So you would need to alter functions. Python has no way of disabling the exception in existing functions.
You may inherit the class where this exception handling occurs and override this method.
Except, there is a way but it involves tracing, and you need to be careful.
QUESTION
I'm trying to avoid having to requery and reprocess data for the cache every time the server reloads in development (pyramid framework).
Is there an easy way to set up dogpile's memory backend, dogpile.cache.memory
, so that its persistence is independent from my web server, or do I need a backend like redis or memcached for this?
ANSWER
Answered 2018-Sep-04 at 07:36Not really. It is a memory within the running python process. Once the application reloads, the process gets killed and re-started, the memory is gone. Using a file backend (like DBMBackend) might be a solution for you.
On the other hand, if you are on unix, installing and using memcached is easy.
QUESTION
I am making packege of some python module for ROSA(linux-based OS)
so I have this error:
...ANSWER
Answered 2018-Aug-21 at 15:17You are not finding any documentation on the error because the error is from rpmlint, not rpm.
rpmlint applies certain heuristics to packages to improve package quality.
The error is due to the permissions 0600 which renders the file unreadable.
QUESTION
Recently, I'm using Redis to cache token for OpenStack Keystone. The function is fine, but some expired cache data still in Redis.
my Keystone config:
...ANSWER
Answered 2017-May-09 at 11:20I hope this question still relevant.
I'm trying to do the same thing as you are, and for now the only option I found working is the argument on dogpile.cache.redis: redis_expiration_time. Checkout the backend dogpile.redis API or source code. http://dogpilecache.readthedocs.io/en/latest/api.html#dogpile.cache.backends.redis.RedisBackend.params.redis_expiration_time
The only problem with this argument is that it does not let you choose a different TTL for different categories, for example you want tokens for 10 minutes and catalog for 24 hours or so. The other parameters on keystone.conf just don't work from my experience (expiration_time and cache_time on each category)... Anyway this problem isn't relevant if you are using redis to store only keystone tokens.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
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No vulnerabilities reported
Install dogpile.cache
You can use dogpile.cache like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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