qcache | In memory cache server with query capabilities | Caching library

by tobgu Python Version: 0.9.3 License: MIT

X-Ray Key Features Code Snippets(1)Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | qcache Summary

qcache is a Python library typically used in Server, Caching applications. qcache has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install qcache' or download it from GitHub, PyPI.

In memory cache server with query capabilities

Support

Quality

Security

License

Reuse

Support

qcache has a low active ecosystem.

It has 37 star(s) with 1 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 14 have been closed. On average issues are closed in 57 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of qcache is 0.9.3

Quality

qcache has 0 bugs and 0 code smells.

Security

qcache has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

qcache code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

qcache is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

qcache releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

qcache saves you 946 person hours of effort in developing the same functionality from scratch.

It has 2157 lines of code, 312 functions and 20 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed qcache and discovered the below as its top functions. This is intended to give you an instant insight into qcache implemented functionality, and help decide if they suit your requirements.

Ensure that the cache is free
Append a stat to the buffer
Find the version number from a file
Return a snapshot of the stats
Reset the statistics
Create a new QFrame from a dict
Add stand - in columns to dataframe
Returns the dtype of an object
Unquote a string
Query the dataframe
Apply pandas filter
Query dataframe
Filter Pandas dataframe
Return the decoded body
Build docs
Cleanup build files
Evict key from cache
Read content of a file
Decompress a string
Read content of file
Construct a QFrame from a csv file

Get all kandi verified functions for this library.

qcache Key Features

No Key Features are available at this moment for qcache.

qcache Examples and Code Snippets

QPixmaps in PyQt don't get cleaned up properly when made directly from file and not from QImage

Python

Lines of Code : 2

License : Strong Copyleft (CC BY-SA 4.0)

Copy

QPixmapCache.clear()

Community Discussions

Trending Discussions on qcache

QCache has no method insert

Join Query in Apache Ignite

QUESTION

QCache has no method insert

Asked 2018-Dec-07 at 16:27

I'm trying to use the QCache class, but method insert is missing...

SqlTableModel.h

...

ANSWER

Answered 2018-Dec-07 at 13:13

Your problem is that getValue is const function, while insert of QCache is not const.

You can make your function non const, or mark m_cache with mutable, or create different functions for insert and get.

Source https://stackoverflow.com/questions/53670291

QUESTION

Join Query in Apache Ignite

Asked 2018-Oct-02 at 07:42

How is spatial join query executed among the nodes in PARTITIONED mode? As Ignite partition the data (default 1024) among the nodes using Rendezvous Affinity hashing, how is join operation executed among the partitions? Suppose I have two spatial datasets in the cache (pCache and qCache), each contains 10 partitions(1, .., 10). How is ignite perform the join operation on this two dataset? Is it partition1 of pCache with partition1 of qCache?

My second question: How is ignite perform the same operation in case of distributed join?

...

ANSWER

Answered 2018-Oct-02 at 07:42

There is no correspondence between partitions of different caches. If you run a join operation, then by default only local lookup will be performed.If data is not collocated, then this approach may give you a partial result.

When all-to-all mapping is performed, then every node has to communicate with every other node, so messages are totally sent in the cluster, where is the number of nodes. This is called distributed joins, and it affects performance significantly. It may be enabled either in the connection string in case of JDBC driver, or by using SqlFieldsQuery#setDistributedJoins(...) method in case of cache query API.

The recommended way to do joins is to collocate the data in a way, that no distributed joins are needed. Ignite has a feature called affinity collocation, designed specially for this purpose. You can specify a field of an object, that will be used to calculate the affinity function. Value of this field doesn't have to be unique, but it should be a part of a key. So, if you want to perform joins on two tables, you may collocate them by affinity, so no distributed joins will be needed.

Source https://stackoverflow.com/questions/52602842

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install qcache

You can install using 'pip install qcache' or download it from GitHub, PyPI.
You can use qcache 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.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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