Documentation
v2.0.5 Latest
Command Line Interface
⚠️

This documentation is still in development. Please report any issues here (opens in a new tab).

CLI Documentation

Commands Line Interface (CLI) Documentation.

Installation

Prerequisites

  • Python 3.9+

Installing

Published Release

We recommend using a packaging manager like pip or poetry.

pip install thread-cli

Building From Source

# Clone this repository
git clone https://github.com/python-thread/thread-cli
 
# Install the upstream package
pip install -e .

Development

# Clone this repository
git clone https://github.com/python-thread/thread-cli
 
# Install poetry
pip install poetry
 
# Install dependencies
poetry install

Running the CLI

Open your terminal and run:

thread

Getting started

Try running the help command!

thread -h/--help

Log levels

Thread CLI uses the python logging library. (opens in a new tab)

NameLevel
NOTSET0
DEBUG10
INFO20
WARN30
ERROR40
CRITICAL50

Commands

List of commands

Documentation (thread docs)

thread docs

Ran with no arguments and options, this command will attempt to open your browser to this MD file! If unable, will instead print out the link.

Help (thread help)

thread help

Ran with no arguments and options, this command will attempt to open your browser to the issue tracker! If unable, will instead print out the link.

Report (thread report)

thread report

Ran with no arguments and options, this command will attempt to open your browser to this MD file! If unable, will instead print out the link.

Configuration (thread config ...)

thread config

Coming soon.

Parallel Processing (thread process ...)

thread process

Invokes the ParallelProcessing class.

Examples

Say you wanted to generate a list of the square of every number from 0 to 999.

thread process 'lambda x: x**2' '[ i for i in range(1000) ]'

This is functionally equivalent to:

import thread
 
# Start processing
worker = thread.ParallelProcessing(
  function = lambda x: x**2,
  dataset = [ i for i in range(1000) ]
)
worker.start()
worker.join()
 
# Write output to "./output.json"
with open('./output.json', 'w') as output:
  output.write(worker.results)