pandas-multiprocess | Python package to process Pandas Dataframe | Data Visualization library

by xieqihui Python Version: 0.1.3 License: MIT

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kandi X-RAY | pandas-multiprocess Summary

pandas-multiprocess is a Python library typically used in Analytics, Data Visualization, Numpy, Pandas applications. pandas-multiprocess 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 pandas-multiprocess' or download it from GitHub, PyPI.

A Python package to process Pandas Dataframe using multi-processing

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pandas-multiprocess has a low active ecosystem.

It has 33 star(s) with 5 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 1 have been closed. On average issues are closed in 553 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pandas-multiprocess is 0.1.3

Quality

pandas-multiprocess has 0 bugs and 0 code smells.

Security

pandas-multiprocess has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

pandas-multiprocess code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

pandas-multiprocess 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

pandas-multiprocess releases are available to install and integrate.

Deployable package is available in PyPI.

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

Installation instructions are not available. Examples and code snippets are available.

pandas-multiprocess saves you 67 person hours of effort in developing the same functionality from scratch.

It has 175 lines of code, 8 functions and 6 files.

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

Top functions reviewed by kandi - BETA

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

Wrapper for multiprocessing .
Run the worker .
Initialize process .
Calculate the sum of the sum

Get all kandi verified functions for this library.

pandas-multiprocess Key Features

No Key Features are available at this moment for pandas-multiprocess.

pandas-multiprocess Examples and Code Snippets

No Code Snippets are available at this moment for pandas-multiprocess.

Community Discussions

Trending Discussions on pandas-multiprocess

pandas + multiprocessing: "NotImplementedError: Not supported for DataFrames!"

QUESTION

pandas + multiprocessing: "NotImplementedError: Not supported for DataFrames!"

Asked 2019-Dec-22 at 23:53

After my previous thread was marked as a duplicate, it pointed me in the direction of multiprocessing managers. I'm trying to use multiprocessing to create a service that handles my pandas dataframe to give to Flask requests. This is my code so far:

df_manager.py

...

ANSWER

Answered 2019-Dec-22 at 23:53

This issue is fixed by exposing the relevant methods to the proxy used by BaseManager. This can be done in the register call in data_handler.py.

df_manager.py

Source https://stackoverflow.com/questions/59097332

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

Vulnerabilities

No vulnerabilities reported

Install pandas-multiprocess

You can install using 'pip install pandas-multiprocess' or download it from GitHub, PyPI.
You can use pandas-multiprocess 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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