rtgo 0.0.7

Quick and simple multithreading

Ready Thready Go

Ready Thready Go (rtgo) is a Python module for easily running Python functions utilising multi-threading.

Installation

Ready Thready Go is available through PyPI as rtgo. It can be installed via pip:

pip install rtgo

Requirements

No additional packages are required to run Ready Thready Go.

Python 3.6 or higher is recommended.

Usage

To use Ready Thready Go, the module ReadyThready should first be imported from the rtgo package.

The ReadyThready function 'go' is used to run a function with multiple different input arguments over multiple threads.

ReadyThready.go takes the arguments:

• func, the name of the function to be run
• args, a list of arguments to be passed to the function, including a list of multiple different arguments
• arg_data_index, the position of the list of multiple arguments within the args list
• n_threads, the number of threads to be used

It may be helpful to think of ReadyThready.go as an alternative to using a for loop to pass arguments from a list to a function: instead of

def my_function(number):
    new_number = (number * 3) - 1 
    return new_number

my_list = [1,2,3,4,5]

for x in my_list:
    my_function(x)

It is possible to supply the list and the function to ReadyThready.go and have it run in parallel over a specified number of threads:

from rtgo import ReadyThready
def my_function(number):
    new_number = (number * 3) - 1 
    return new_number

my_list = [1,2,3,4,5]

ReadyThready.go(func=my_function, args=[my_list], arg_data_index = 0, n_threads = 4)

Examples

Divide data and process a function on multiple threads

from rtgo import ReadyThready

# initialise variables
my_input_list = [1,2,3,4,5,6,7,8]
example_string = "example:"

# define a function to be run over multiple threads
def my_example_func(number, phrase):
    if number < 5:
        print(f"{phrase} {number} is less than 5")

# run the function over 4 threads
ReadyThready.go(func=my_example_func, args=[my_input_list, example_string], arg_data_index=0, n_threads=4)

Execute multiple functions concurrently

from rtgo import ReadyThready
import requests

# Retrieve Human Phenotype Ontology data
def get_hpo_data():
    my_hpo_data = requests.get("http://hpo.jax.org/api/hpo/term/HP%3A0001166/genes")
    my_hpo_data = my_lengthy_processing(my_hpo_data)
    return my_hpo_data

# Retrieve Medical Subject Headings data
def get_mesh_data():
    my_mesh_data = requests.get("https://id.nlm.nih.gov/mesh/lookup/term?label=obesity&match=contains&limit=10")
    my_mesh_data = my_lenghty_processing(my_mesh_data)
    return my_mesh_data

# run each function on a separate thread
ontology_data = ReadyThready.go_cluster([get_hpo_data, get_mesh_Data])

Using your project's logger

from rtgo import ReadyThready
import logging 

# create a logger for your project 
my_project_logger = logging.getLogger('example')
my_project_logger.setLevel(logging.INFO)
my_project_logger.addHandler(logging.StreamHandler())

# initialise variables
my_input_list = [1,2,3,4,5,6,7,8]
example_string = "example:"

# a simple function
def my_example_func(number, phrase):
    if number < 5:
        print(f"{phrase} {number} is less than 5")

# set ReadyThready to use your project logger
ReadyThready.set_logger(my_project_logger)

# run the function over 8 threads
ReadyThready.go(func=my_example_func, args=[my_input_list, example_string], arg_data_index=0, n_threads=8)

Authors

Thomas Rowlands, Emma Croot

Licence

GNU (see LICENCE.txt)

Change log

###version 0.0.5:

First stable version

###version 0.0.6: Improved error handling and logging