Skip to main content
Pre-release

This release is a pre-release and may not be stable for production use.

logo

PyGlove: Manipulating Python Programs

PyPI version codecov pytest

Getting started | Installation | Examples | Reference docs

What is PyGlove

PyGlove is a general-purpose library for Python object manipulation. It introduces symbolic object-oriented programming to Python, allowing direct manipulation of objects that makes meta-programs much easier to write. It has been used to handle complex machine learning scenarios, such as AutoML, as well as facilitating daily programming tasks with extra flexibility.

PyGlove is lightweight and has very few dependencies beyond the Python interpreter. It provides:

  • A mutable symbolic object model for Python;
  • A rich set of operations for Python object manipulation;
  • A solution for automatic search of better Python programs, including:
    • An easy-to-use API for dropping search into an arbitrary pre-existing Python program;
    • A set of powerful search primitives for defining the search space;
    • A library of search algorithms ready to use, and a framework for developing new search algorithms;
    • An API to interface with any distributed infrastructure (e.g. Open Source Vizier) for such search.

It's commonly used in:

  • Automated machine learning (AutoML);
  • Evolutionary computing;
  • Machine learning for large teams (evolving and sharing ML code, reusing ML techniques, etc.);
  • Daily programming tasks in Python (advanced binding capabilities, mutability, etc.).

PyGlove has been published at NeurIPS 2020. It is widely used within Alphabet, including Google Research, Google Cloud, Youtube and Waymo.

PyGlove is developed by Daiyi Peng and colleagues in Google Brain Team.

Hello PyGlove

import pyglove as pg

@pg.symbolize
class Hello:
  def __init__(self, subject):
    self._greeting = f'Hello, {subject}!'

  def greet(self):
    print(self._greeting)


hello = Hello('World')
hello.greet()

Hello, World!

hello.rebind(subject='PyGlove')
hello.greet()

Hello, PyGlove!

hello.rebind(subject=pg.oneof(['World', 'PyGlove']))
for h in pg.iter(hello):
  h.greet()

Hello, World!
Hello, PyGlove!

Install

pip install pyglove

Or install nightly build with:

pip install pyglove --pre

Examples

Citing PyGlove

@inproceedings{peng2020pyglove,
  title={PyGlove: Symbolic programming for automated machine learning},
  author={Peng, Daiyi and Dong, Xuanyi and Real, Esteban and Tan, Mingxing and Lu, Yifeng and Bender, Gabriel and Liu, Hanxiao and Kraft, Adam and Liang, Chen and Le, Quoc},
  booktitle={Advances in Neural Information Processing Systems (NeurIPS)},
  volume={33},
  pages={96--108},
  year={2020}
}

Disclaimer: this is not an officially supported Google product.

Metadata

Release files for pyglove 0.4.4.dev20231007

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pyglove 0.4.4.dev20231007
File Size Uploaded
pyglove-0.4.4.dev20231007.tar.gz 434.1 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pyglove 0.4.4.dev20231007
File Interpreter ABI Platform
pyglove-0.4.4.dev20231007-py3-none-any.whl Python 3 none any Details

Total release size: 1.0 MB

Release files / pyglove-0.4.4.dev20231007.tar.gz

Download URL pyglove-0.4.4.dev20231007.tar.gz
Size 434.1 kB
Tags Source
SHA-256 checksum
How to use checksums
3b7295c16ebd7b363f889756ffb9a2127fe97b9e644de57b4bef0137873af6eb
BLAKE2b-256 checksum
How to use checksums
7ecfd3c236dfdf2d7f9c737aaa77cdcf393e745d9e1f8bbf8ff7908773745675
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.5

Release files / pyglove-0.4.4.dev20231007-py3-none-any.whl

Download URL pyglove-0.4.4.dev20231007-py3-none-any.whl
Size 569.4 kB
Tags Python 3
SHA-256 checksum
How to use checksums
674f533f5fccb6630f3d4c46207082ef5d83fca8e369cba1495267ff78ffa0bb
BLAKE2b-256 checksum
How to use checksums
364cc0fbd7733ba2811fce48a4446dfc9b39a84136c1af905a8c6d420faa78e1
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.2 CPython/3.11.5

Release history Release notifications | RSS feed

0.4.5

2 release files

0.4.4

2 release files

This release

0.4.3

2 release files

0.4.2

2 release files

0.4.1

2 release files

0.4.0

2 release files

0.3.0

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.1

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page