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 at Google Brain.

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 0.5.0.dev202603160832

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 0.5.0.dev202603160832
File Size Uploaded
pyglove-0.5.0.dev202603160832.tar.gz 553.8 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for pyglove 0.5.0.dev202603160832
File Interpreter ABI Platform
pyglove-0.5.0.dev202603160832-py3-none-any.whl Python 3 none any Details

Total release size: 1.3 MB

Release files / pyglove-0.5.0.dev202603160832.tar.gz

Download URL pyglove-0.5.0.dev202603160832.tar.gz
Size 553.8 kB
Tags Source
SHA-256 checksum
How to use checksums
fe86a77c48d28f5d18e535b5d83cffb5b424c5a932b667eef5b0f1bb9b327f02
BLAKE2b-256 checksum
How to use checksums
49fc3fa5fd9c94a22892a5925dc559bbb995a82ce1bb7e11096a531c7d5a12ef
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.14.3

Release files / pyglove-0.5.0.dev202603160832-py3-none-any.whl

Download URL pyglove-0.5.0.dev202603160832-py3-none-any.whl
Size 721.6 kB
Tags Python 3
SHA-256 checksum
How to use checksums
35728c0829d73caa973a0f44bd4c48959f7f677f05d763c807663d5e26e72644
BLAKE2b-256 checksum
How to use checksums
bddaaff68e7a2575f473b92fc28ff96d6aab97ae5a362c76247bafc85687a906
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.14.3

Release history Release notifications | RSS feed

This release

0.4.5

2 release files

0.4.4

2 release files

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