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https://github.com/cqcl/lambeq

A high-level Python library for Quantum Natural Language Processing

https://github.com/cqcl/lambeq

Science Score: 36.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
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    Academic publication links
    Links to: arxiv.org
  • ○
    Committers with academic emails
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    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (19.0%) to scientific vocabulary

Keywords

python qnlp

Keywords from Contributors

quantum-computing quantum quantum-algorithms quantum-machine-learning automatic-differentiation jax
Last synced: 6 months ago · JSON representation

Repository

A high-level Python library for Quantum Natural Language Processing

Basic Info
Statistics
  • Stars: 500
  • Watchers: 32
  • Forks: 120
  • Open Issues: 26
  • Releases: 21
Topics
python qnlp
Created over 4 years ago · Last pushed 7 months ago
Metadata Files
Readme License

README.md

λambeq

Build status License PyPI version PyPI downloads arXiv

About

lambeq is a toolkit for quantum natural language processing (QNLP).

Getting started

Prerequisites

  • Python 3.10+

Installation

lambeq can be installed with the command:

bash pip install lambeq

The default installation of lambeq includes Bobcat parser, a state-of-the-art statistical parser (see related paper) fully integrated with the toolkit.

To install lambeq with optional dependencies for extra features, run:

bash pip install lambeq[extras]

To install lambeq with optional dependencies for experimental features, run:

bash pip install lambeq[experimental]

To enable DepCCG support, you will need to install the external parser separately.

Note: The DepCCG-related functionality is no longer actively supported in lambeq, and may not work as expected. We strongly recommend using the default Bobcat parser which comes as part of lambeq.

If you still want to use DepCCG, for example because you plan to apply lambeq on Japanese, you can install DepCCG separately following the instructions on the DepCCG homepage. After installing DepCCG, you can download its model by using the script provided in the contrib folder of this repository:

bash python contrib/download_depccg_model.py

Usage

The docs/examples directory in lambeq's documentation repository contains notebooks demonstrating usage of the various tools in lambeq.

Example - parsing a sentence into a diagram (see docs/examples/parser.ipynb):

```python from lambeq import BobcatParser

parser = BobcatParser() diagram = parser.sentence2diagram('This is a test sentence') diagram.draw() ```

Testing

Run all tests with the command:

bash pytest

Note: if you have installed lambeq in a virtual environment, remember to install pytest in the same environment using pip.

License

Distributed under the Apache 2.0 license. See LICENSE for more details.

Citation

If you wish to attribute our work, please cite the accompanying paper:

@article{kartsaklis2021lambeq, title={lambeq: {A}n {E}fficient {H}igh-{L}evel {P}ython {L}ibrary for {Q}uantum {NLP}}, author={Dimitri Kartsaklis and Ian Fan and Richie Yeung and Anna Pearson and Robin Lorenz and Alexis Toumi and Giovanni de Felice and Konstantinos Meichanetzidis and Stephen Clark and Bob Coecke}, year={2021}, journal={arXiv preprint arXiv:2110.04236}, }

Owner

  • Name: Cambridge Quantum
  • Login: CQCL
  • Kind: organization
  • Location: Cambridge, UK

Quantum Software and Technologies

GitHub Events

Total
  • Create event: 3
  • Release event: 2
  • Issues event: 60
  • Watch event: 39
  • Delete event: 1
  • Issue comment event: 80
  • Member event: 1
  • Push event: 42
  • Pull request event: 79
  • Pull request review comment event: 65
  • Pull request review event: 98
  • Fork event: 14
Last Year
  • Create event: 3
  • Release event: 2
  • Issues event: 60
  • Watch event: 39
  • Delete event: 1
  • Issue comment event: 80
  • Member event: 1
  • Push event: 42
  • Pull request event: 79
  • Pull request review comment event: 65
  • Pull request review event: 98
  • Fork event: 14

Committers

Last synced: 10 months ago

All Time
  • Total Commits: 94
  • Total Committers: 19
  • Avg Commits per committer: 4.947
  • Development Distribution Score (DDS): 0.755
Past Year
  • Commits: 48
  • Committers: 9
  • Avg Commits per committer: 5.333
  • Development Distribution Score (DDS): 0.521
Top Committers
Name Email Commits
Neil Ortega n****a@q****m 23
Dimitri Kartsaklis d****t@g****m 17
Ian Fan i****n@c****m 12
Kin Ian Lo k****3@g****m 7
Nikhil n****i@q****m 7
Thomas Hoffmann t****n@q****m 6
Richie Yeung r****1@g****m 5
Gopal Dahale d****7@g****m 2
cgkrawchuk 8****k 2
Tiffany Duneau 3****6 2
Ragunath1729 r****n@q****m 2
Blake Wilson b****n@q****m 2
Dimitri Kartsaklis d****s@c****m 1
A.C.E07 7****v 1
Charlie London 3****c 1
Gavin Goodship m****1@g****m 1
Shiro-Raven e****4@g****m 1
WingCode s****4@g****m 1
kekekekenta k****i@g****m 1
Committer Domains (Top 20 + Academic)
quantinuum.com: 5 cambridgequantum.com: 2

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 109
  • Total pull requests: 137
  • Average time to close issues: about 1 month
  • Average time to close pull requests: 16 days
  • Total issue authors: 39
  • Total pull request authors: 24
  • Average comments per issue: 2.6
  • Average comments per pull request: 1.94
  • Merged pull requests: 94
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 46
  • Pull requests: 92
  • Average time to close issues: 11 days
  • Average time to close pull requests: 8 days
  • Issue authors: 7
  • Pull request authors: 10
  • Average comments per issue: 0.41
  • Average comments per pull request: 1.42
  • Merged pull requests: 78
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • dimkart (31)
  • ACE07-Sev (13)
  • neiljdo (11)
  • kinianlo (6)
  • nlpirate (4)
  • dtchang (4)
  • AnnaNPearson (2)
  • Thommy257 (2)
  • yousrabou (2)
  • Stephenito (2)
  • nikhilkhatri (2)
  • mithunpaul08 (2)
  • abuzomol (2)
  • gamatos (1)
  • SiyoonKIM (1)
Pull Request Authors
  • neiljdo (45)
  • kinianlo (16)
  • dimkart (14)
  • nikhilkhatri (9)
  • toumix (8)
  • DNA386 (4)
  • ACE07-Sev (4)
  • blakewilsonquantinuum (4)
  • isobelhooper (4)
  • mithunpaul08 (4)
  • Ragunath1729 (4)
  • cgkrawchuk (3)
  • Thommy257 (3)
  • goodship1 (2)
  • sujit4uwbslg (2)
Top Labels
Issue Labels
enhancement (10) bug (8) up-for-grabs (5) fix (5) good first issue (2) unitaryHACK (2) stale (1) documentation (1)
Pull Request Labels
enhancement (2) bug (2) oncilla (2)

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 1,750 last-month
  • Total dependent packages: 1
  • Total dependent repositories: 2
  • Total versions: 21
  • Total maintainers: 5
pypi.org: lambeq

A QNLP toolkit

  • Versions: 21
  • Dependent Packages: 1
  • Dependent Repositories: 2
  • Downloads: 1,750 Last month
Rankings
Stargazers count: 3.3%
Dependent packages count: 4.7%
Forks count: 4.8%
Average: 6.4%
Downloads: 7.6%
Dependent repos count: 11.6%
Maintainers (5)
y-richie-y ifan0 thommy257 n1khatri neiljdo
Last synced: 6 months ago

Dependencies

.github/workflows/build_test.yml actions
  • actions/cache v2 composite
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
.github/workflows/docs.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v4 composite
  • s0/git-publish-subdir-action develop composite
docs/requirements.txt pypi
  • Sphinx ==4.4.0
  • m2r2 ==0.3.2
  • nbformat ==5.1.3
  • nbsphinx ==0.8.8
  • numpydoc ==1.1.0
  • sphinx-argparse ==0.3.1
  • sphinx-rtd-theme ==1.0.0
pyproject.toml pypi