Big-O Estimator
This Python package allows you to estimate the Big-O complexity of Python functions using AST (Abstract Syntax Tree) parsing.
Installation
You can install the package using:
pip install .
Usage
from big_o_estimator import get_big_o_of_function
def sample_function(n):
for i in range(n):
pass
print(get_big_o_of_function(sample_function))
Metadata
Release files for big-o-estimator 0.1.3.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| big_o_estimator-0.1.3.2.tar.gz | 4.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| big_o_estimator-0.1.3.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.4 kB
Release files / big_o_estimator-0.1.3.2.tar.gz
| Download URL | big_o_estimator-0.1.3.2.tar.gz |
|---|---|
| Size | 4.5 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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No |
| Uploaded via |
twine/5.1.1 CPython/3.11.10
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Release files / big_o_estimator-0.1.3.2-py3-none-any.whl
| Download URL | big_o_estimator-0.1.3.2-py3-none-any.whl |
|---|---|
| Size | 5.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.1 CPython/3.11.10
|