Python: Handling the RuntimeError “can’t start new thread”

What will you learn?

In this tutorial, you will delve into effectively handling the RuntimeError: can’t start new thread error that often arises in Python applications. By exploring methods to adjust system settings and optimize code for efficient resource management, you will be equipped to tackle this common issue with ease.

Introduction to the Problem and Solution

Encountering the RuntimeError: can’t start new thread error signals that your Python program is attempting to create a new thread but has exceeded the system’s limit for threads. This dilemma commonly surfaces when dealing with multi-threading or concurrency tasks.

To resolve this challenge, it is essential to tweak specific system settings related to threading and streamline code efficiency in terms of resource consumption. By implementing appropriate techniques, you can ensure seamless functionality of your Python application without encountering these limitations.


import sys

# Increase the maximum number of threads allowed

# Another way of increasing threads limit (if needed)
import _thread

# Copyright PHD

Note: The above code snippets offer ways to expand the number of threads permitted in a Python program.


To overcome the can’t start new thread error, consider these explanations:

  • Using sys.setrecursionlimit(): Adjusts recursion depth, indirectly allowing more threads creation by optimizing memory usage per recursive call.

  • Employing _thread.stack_size(): Modifies stack size to allocate sufficient memory for each thread’s execution stack, potentially preventing errors associated with insufficient memory allocation.

    1. How does increasing recursion limit help with ‘can’t start new thread’ error? Increasing recursion limit optimizes memory usage, enabling additional thread creation before hitting system limits.

    2. Are there risks associated with setting higher recursion limits? Setting excessively high values may lead to increased memory consumption or potential stack overflow problems if not managed cautiously within your codebase.

    3. Can adjusting stack sizes solve all ‘can’t start new thread’ errors? While resizing stack sizes can alleviate some instances of this error, it may not universally resolve issues as other factors like system constraints might still impose limits on concurrent operations.

    4. Does every Python project encounter ‘can’t start new thread’ errors? Not every project faces such runtime errors; projects heavily utilizing multi-threading or processes are more susceptible due to heightened demand on system resources.

    5. Is it advisable to modify system-level configurations when encountering this error? It’s advisable first to optimize code structure and resource management practices before considering altering default system settings which could have broader repercussions.


Mastering how to address common runtime errors like RuntimeError: can’t start new thread empowers developers in constructing resilient and scalable applications harnessing multi-threading capabilities judiciously. By adhering to best practices and making suitable adjustments at both coding and configuration levels, you pave the way for smoother execution while safeguarding against bottlenecks arising from constraints on concurrent operations.

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