objsize

library0.8.0pypypi✓ verified 23d ago

The objsize Python package provides functionality for traversing an object's subtree and calculating its total memory consumption in bytes (deep size). It leverages Python's internal Garbage Collection (GC) implementation, designed to ignore commonly shared objects like singletons and type objects for more accurate deep sizing. It's currently in version 0.8.0 and generally has infrequent releases.

data

pip install objsize

github ↗package ↗

INSTALL

IMPORT

SIG · OBJSIZE

objsize

datapythonv0.8.0

Install

1.7s avg

Import

34ms

Disk

16MB

Pass rate

10/ 10

Env Coverage10 / 10

glibc

3.9–3.13

musl

3.9–3.13

Install & Compatibility

Where this runs

tested against v0.8.0 · pip install

no network on importno background threads

Install × environment matrix

Each cell = how many times install + import succeeded across repeated harness runs. Partial = flaky.
glibc = Debian/Ubuntu slim · musl = Alpine Linux

musl

py 3.10–3.95 runs

installs and imports cleanly · install 0.0s · import 0.036s · 17.8MB

glibc

py 3.10–3.95 runs

installs and imports cleanly · install 1.7s · import 0.032s · 18MB

16MB installed

● package 16MB

Code

Verified usage

Verified import paths — ran on the pinned version, not inferred.

get_deep_size

✓ from objsize import get_deep_size

The primary function is `get_deep_size`.

Demonstrates how to calculate the deep size of a single object or multiple objects using `objsize.get_deep_size()`.

import objsize my_data = {'name': 'Alice', 'age': 30, 'hobbies': ['reading', 'coding']} deep_size_bytes = objsize.get_deep_size(my_data) print(f"The deep size of my_data is: {deep_size_bytes} bytes") another_obj = ['hello', 'world'] total_deep_size = objsize.get_deep_size(my_data, another_obj) print(f"The deep size of multiple objects is: {total_deep_size} bytes")

Debug

Known issues

gotchaBy design, `objsize` attempts to ignore singletons (e.g., `None`) and type objects (classes, modules, functions, lambdas) when calculating deep size. This means they won't contribute to the reported size of the object's subtree, as they are considered shared.

fix

If you need to include sizes for specific shared objects or functions, you might need to implement a custom filter function (e.g., by modifying or replacing `objsize.traverse.shared_object_or_function_filter()`).

affects: All versions

gotchaUnlike some alternatives (e.g., Pympler), `objsize` uses a Breadth-First Search (BFS) approach internally to traverse object subtrees, avoiding recursive calls. This prevents hitting Python's default recursion depth limits, but users migrating from recursive deep-sizing tools should be aware of this architectural difference.

fix

No fix needed; this is a design feature of `objsize` that enhances robustness. Simply be aware of the underlying traversal mechanism.

affects: All versions

gotchaFor 'special objects' or objects with non-standard memory management (e.g., `weakref.proxy` or objects managing off-heap memory), `objsize`'s default calculation might not fully capture their size. You may need to provide custom handlers.

fix

For such cases, the library allows users to supply custom methods for size calculation, referent identification, or object filtering to ensure accurate deep size measurement. Consult the library's documentation for details on custom handlers.

affects: All versions

Errors

Common errors & fixes

ModuleNotFoundError: No module named 'objsize'

The `objsize` package has not been installed in your Python environment.

fix

Install the package using pip: `pip install objsize`

objsize returns an unexpectedly small or incorrect deep size for certain objects (e.g., torch.Tensor)

The `objsize` library, by default, might not fully traverse the internal memory structures of highly specialized objects (like those from NumPy or PyTorch) that manage their data outside of standard Python object references. This can lead to an underestimation of their 'deep size'.

fix

Provide custom `get_size_func` and/or `get_referents_func` to `objsize.get_deep_size` to instruct it on how to correctly calculate the size or find referents for such objects. For example, for a `torch.Tensor` you might need to account for its underlying storage.

AttributeError: module 'objsize' has no attribute 'size'

You are attempting to access a non-existent attribute named 'size' directly on the `objsize` module. The primary function for calculating deep size is `get_deep_size`.

fix

Use the `objsize.get_deep_size()` function to calculate the memory consumption of an object: `import objsize; objsize.get_deep_size(my_object)`

Upgrade

Version history

0.8.0latest on PyPI · released Jan 18, 2026

Audit

Dependencies

pythonrequiredRequires Python 3.8 or newer.

Agent activity

7 hits · last 30 days

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Resources

githubhttps://github.com/liran-funaro/objsize ↗

packagehttps://pypi.org/project/objsize/ ↗