pynanoid 0.1.0

Description:

pynanoid 0.1.0

PyNanoID






A tiny, secure, URL-friendly, unique string ID generator for Python, written in
Rust.

Safe. It uses hardware random generator. Can be used in clusters.
Fast. 2-3 times faster than Python based generator.
Compact. It uses a larger alphabet than UUID (A-Za-z0-9_-). So ID size
was reduced from 36 to 21 symbols.

Installation
$ pip install pynanoid

Usage
from pynanoid import generate

print(generate())

Symbols -,.() are not encoded in the URL. If used at the end of a link they
could be identified as a punctuation symbol.
The Rust based high-performance generator is used by default if available. You
can also use pure-Python based generator as shown here.

[!NOTE]
If Rust based implementation is not available, the pure-Python
generator will be automatically used.

If you want to reduce ID length (and increase the probability of collisions),
you can pass the length as an argument.
from pynanoid import generate

print(generate(size=10))

Don’t forget to check the safety of your ID length in ID collision probability
calculator.
Custom Alphabet or Length
If you want to change the ID's alphabet or length, you can pass the alphabet as
the first argument and the size as the second argument.
from pynanoid import generate

print(generate("1234567890abcdef", 10))

Non-secure generator is also available.
from pynanoid import non_secure_generate

print(non_secure_generate())


[!WARNING]
Non-secure generator uses random.random internally. Hence it is not
recommended for generating tokens or secrets.

Force Use Pure-Python Generator
If you want to use the pure-Python generator, you can use functions provided in
pynanoid.nanoid.
from pynanoid.nanoid import generate, non_secure_generate

print(generate())
print(non_secure_generate())

Benchmarks

We benchmark using
pytest-benchmark. You can
find the benchmark script in the tests/ directory.
You can run the benchmarks using the following command:
$ pytest tests/benchmark.py --benchmark-histogram=assets/benchmark.svg

Credits

Andrey Sitnik for Nano ID.
Paul Yuan (@puyuan) for
py-nanoid.