How do I fix 'RecursionError: maximum recursion depth exceeded' in Python?
I'm working on a Python application and running into an issue with Python performance. Here's the problematic code:
# Current implementation
class DataProcessor:
def __init__(self):
self.data = []
def process_large_file(self, filename):
with open(filename, 'r') as f:
self.data = f.readlines() # Memory issue with large files
return self.process_data()
The error message I'm getting is: "ImportError: cannot import name 'some_function' from 'module'"
What I've tried so far:
- Used pdb debugger to step through the code
- Added logging statements to trace execution
- Checked Python documentation and PEPs
- Tested with different Python versions
- Reviewed similar issues on GitHub and Stack Overflow
Environment information:
- Python version: 3.11.0
- Operating system: Windows 11
- Virtual environment: venv (activated)
- Relevant packages: django, djangorestframework, celery, redis
Any insights or alternative approaches would be very helpful. Thanks!
Comments
joseph: Could you provide the requirements.txt for the packages used in this solution? 1 week, 4 days ago
alex_dev: How would you modify this approach for a high-traffic production environment? 1 week, 4 days ago
2 Answers
Python decorators with arguments require a three-level nested function. Here's the proper implementation:
import functools
# Decorator with arguments
def retry(max_attempts=3, delay=1):
def decorator(func):
@functools.wraps(func) # Preserves function metadata
def wrapper(*args, **kwargs):
for attempt in range(max_attempts):
try:
return func(*args, **kwargs)
except Exception as e:
if attempt == max_attempts - 1:
raise e
time.sleep(delay)
return wrapper
return decorator
# Usage
@retry(max_attempts=5, delay=2)
def unreliable_function():
# Function that might fail
pass
Class-based decorator (alternative approach):
class Retry:
def __init__(self, max_attempts=3, delay=1):
self.max_attempts = max_attempts
self.delay = delay
def __call__(self, func):
@functools.wraps(func)
def wrapper(*args, **kwargs):
for attempt in range(self.max_attempts):
try:
return func(*args, **kwargs)
except Exception as e:
if attempt == self.max_attempts - 1:
raise e
time.sleep(self.delay)
return wrapper
# Usage
@Retry(max_attempts=5, delay=2)
def another_function():
pass
Comments
lisa_data: Could you elaborate on the select_related vs prefetch_related usage? When should I use each? 1 week, 4 days ago
The RecursionError occurs when Python's recursion limit is exceeded. Here are several solutions:
1. Increase recursion limit (temporary fix):
import sys
sys.setrecursionlimit(10000) # Default is usually 1000
2. Convert to iterative approach (recommended):
# Recursive (problematic for large inputs)
def factorial_recursive(n):
if n <= 1:
return 1
return n * factorial_recursive(n - 1)
# Iterative (better)
def factorial_iterative(n):
result = 1
for i in range(2, n + 1):
result *= i
return result
3. Use memoization for recursive algorithms:
from functools import lru_cache
@lru_cache(maxsize=None)
def fibonacci(n):
if n < 2:
return n
return fibonacci(n-1) + fibonacci(n-2)
4. Tail recursion optimization (manual):
def factorial_tail_recursive(n, accumulator=1):
if n <= 1:
return accumulator
return factorial_tail_recursive(n - 1, n * accumulator)
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