MemoryError

MemoryError

Traceback

terminal

Traceback (most recent call last):
  File "main.py", line 1, in <module>
    huge_list = [0] * (10 ** 12)
MemoryError

What causes this error

Python tried to allocate more memory than is available. This happens with extremely large data structures, loading huge files into memory, or repeated memory allocation without cleanup.

How to fix it

Use generators instead of lists for large sequences. Process files in chunks rather than reading entirely. Use memory-efficient data structures. Consider 64-bit Python for large datasets. Profile memory with `tracemalloc`.

Code that causes this error

Broken

huge_list = [0] * (10 ** 12)

Fixed code

Fixed

def huge_range():
    for i in range(10 ** 12):
        yield i

for val in huge_range():
    if val > 10:
        break

About MemoryError

A MemoryError is raised when an operation runs out of memory and the situation is still potentially recoverable. This happens when attempting to allocate more memory than is available — for example, creating an extremely large list, loading a massive file entirely into memory, or performing operations that require more working memory than the system can provide. Note that not all out-of-memory situations result in a clean MemoryError; sometimes the operating system's OOM killer terminates the process first.

To handle large datasets, use generators and iterators instead of materializing entire collections, process files line by line instead of reading them whole, and use memory-mapped files (`mmap`) or specialized libraries like `pandas` with chunked reading. In 32-bit Python builds, the address space limit (~2-4 GB) can trigger MemoryError even when the system has more RAM available.

Common scenarios

Infinite recursion from missing or incorrect base cases

Modifying dictionaries or sets during iteration

Calling generators or coroutines in unsupported ways

Using asyncio event loops incorrectly or attempting to nest them