Metadata-Version: 1.0
Name: ParallelThreading
Version: 0.6
Summary: Parallel Process Threading
Home-page: https://github.com/user/Python-Alex
Author: Python Alex
Author-email: obfuscate@riseup.net
License: MIT
Description: This program mimics the process of Intel and ARM CPU Instruction Processing
        
        [ FETCH ] [ DECODE ] [ EXECUTE ]
        
        Fetching all the instructions that are currently being executed in the pipeline
        
        Decoding all the Function Processes, Objectifying it, Preparing it
        
        Executing the Function Processes in Window Cycles [ Explained in Documenation ]
        
        
        ** Installation Guide **
        
        > python setup.py build_ext
        
        > Locate ParallelThreading/build/lib.win-[ARCH]-[PYTHON_VERSION]/Pipeline.pyd
        
        > Include this in your project you plan to implement this with, This should normally be globally defined somewhere!
        
        To import the package:
        > import Pipeline
        
        
        ** Notices **
        This has ONLY been tested on python 3.9.6 WINDOWS. There are no methods or packages that require a operating system or distribution of linux.
        As far as I am concerned, this project works on all platforms. I have not researched whether embedded distributions that support python interpretors support the threading library. every thing else is built-in
        
        This is not built to make threading obselete, or to enhance performance.
        This is a project to create parallel instructions based on a series of step functions that give a final output, whether it be 1 function, or 500
        
        This is built to execute millions of functions over time in a parallel processing manor, storing the values in a registry for reading while storing, or after the program has finished
        
        Performance is based on how long the function takes to execute, 1 Cycle is completed after the iteration completes all current function executing stages.
        
        100 Cycles may take 1 second, depending on how long the function hangs.
        100 Cycles may take 100 seconds, given its a instruction to scan the port of a network host with a timeout of 1
        
        WARNING : Functions with Long Iterating Loops will cause the pipeline to wait until that function call to return its blocking state.
        WARNING : Functions with Infinite Loops will cause the pipeline to freeze, allowing no other functions to continue executing stages.
        
Keywords: parallel,nonblocking,closeasync,threading,processing,cpu,python,processes
Platform: UNKNOWN
