QuantConnect / QuantConnect/Lean

[Library Request] python-socketio

Open Beginner friendly
#9,500 0 comments 0 reactions 0 assignees View on GitHub

Nobody has claimed this yet.

library-request
Dominant language
C#
Stars
21.7k
Forks
5.3k
Avg merge
2d 22h
Merged PRs (30d)
34

Description

Summary

Add the python-socketio package to the default QuantConnect Python environment.

Package details

python-socketio is a Socket.IO server and client implementation built on top of python-engineio. It is widely used for real-time messaging and complements the websockets package already available in the QC environment (Socket.IO adds the protocol layer — automatic reconnection, room/namespace multiplexing, fallback transports — on top of raw WebSockets).

Use case

Customer (Intercom conversation 215474452877852, Gold support plan) wants to use Socket.IO for connecting to data sources / services that expose Socket.IO endpoints rather than raw WebSocket endpoints. Quoting the customer: "an additional feature set on the already included websockets package that QC already has."

Proposed change

Add python-socketio (and its transitive dependency python-engineio) to the LEAN Python Docker image at the next batched library rebuild.

Open questions

  • Pin to latest stable, or a specific version?

Source

QuantConnect support ticket [Intercom 215474452877852].

Contributor guide

Open the contributing guide

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by locating the LEAN Python Docker image configuration and the existing websockets dependency or batched library rebuild process. Add python-socketio with its python-engineio dependency, resolve the version policy, and verify both packages are available in the rebuilt default Python environment.

Written by the indexing model from the issue text.

Assessment

Tech stack
docker, python
Domain
build-system, devops
Issue type
Feature
Difficulty
2/5
Estimated time
1-3 hours
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
68/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.