Datasets:

dylanhogg

/

awesome-python

like 0

math

https://github.com/geomstats/geomstats

[]

[]

[]

geomstats/geomstats

geomstats

Jupyter Notebook

http://geomstats.ai

Computations and statistics on manifolds with geometric structures.

geomstats

2024-01-13

2017-10-25

https://avatars.githubusercontent.com/u/39272386?v=4

Computations and statistics on manifolds with geometric structures.

['deep-learning', 'geodesic', 'geometry', 'gpu-programming', 'lie-groups', 'machine-learning', 'manifold', 'neural-networks', 'riemannian-geometry', 'statistics']

['deep-learning', 'geodesic', 'geometry', 'gpu-programming', 'lie-groups', 'machine-learning', 'manifold', 'neural-networks', 'riemannian-geometry', 'statistics']

2024-01-12

[('lmcinnes/umap', 0.5977250933647156, 'ml', 1), ('xl0/lovely-tensors', 0.5296072959899902, 'ml-dl', 2), ('kornia/kornia', 0.5275140404701233, 'ml-dl', 2), ('isl-org/open3d', 0.5070082545280457, 'sim', 1)]

util

https://github.com/oracle/graalpython

['java', 'jvm']

[]

[]

oracle/graalpython

graalpython

Python

A Python 3 implementation built on GraalVM

oracle

2024-01-13

2018-04-17

https://avatars.githubusercontent.com/u/4430336?v=4

A Python 3 implementation built on GraalVM

[]

['java', 'jvm']

2024-01-12

[('pyston/pyston', 0.591853141784668, 'util', 0), ('exaloop/codon', 0.5912636518478394, 'perf', 0), ('numba/llvmlite', 0.586859405040741, 'util', 0), ('py4j/py4j', 0.5628305077552795, 'util', 1), ('ethereum/py-evm', 0.54329913854599, 'crypto', 0), ('pypy/pypy', 0.5413466095924377, 'util', 0), ('paramiko/paramiko', 0.5263757109642029, 'util', 0), ('pytoolz/toolz', 0.5168983936309814, 'util', 0), ('amzn/ion-python', 0.5121100544929504, 'data', 0)]

sim

https://github.com/pyscf/pyscf

[]

[]

[]

pyscf/pyscf

pyscf

Python

Python module for quantum chemistry

pyscf

2024-01-13

2014-05-02

https://avatars.githubusercontent.com/u/38367334?v=4

Python module for quantum chemistry

[]

[]

2024-01-11

[('cqcl/tket', 0.677206814289093, 'util', 0), ('cqcl/lambeq', 0.6749314069747925, 'nlp', 0), ('quantumlib/cirq', 0.6541039347648621, 'sim', 0), ('mnooner256/pyqrcode', 0.5908879637718201, 'util', 0), ('pytoolz/toolz', 0.5605663657188416, 'util', 0), ('connorferster/handcalcs', 0.5601664185523987, 'jupyter', 0), ('pypy/pypy', 0.5428182482719421, 'util', 0), ('numpy/numpy', 0.5385183095932007, 'math', 0), ('primal100/pybitcointools', 0.5276904106140137, 'crypto', 0), ('google/latexify_py', 0.5187242031097412, 'util', 0), ('goldmansachs/gs-quant', 0.5135458707809448, 'finance', 0), ('ta-lib/ta-lib-python', 0.5085233449935913, 'finance', 0), ('zeromq/pyzmq', 0.5071917772293091, 'util', 0)]

nlp

https://github.com/nomic-ai/nomic

[]

[]

[]

nomic-ai/nomic

nomic

Python

https://atlas.nomic.ai

Interact, analyze and structure massive text, image, embedding, audio and video datasets

nomic-ai

2024-01-13

2022-07-21

https://avatars.githubusercontent.com/u/102670180?v=4

Interact, analyze and structure massive text, image, embedding, audio and video datasets

['database', 'neural']

['database', 'neural']

2024-01-11

[('milvus-io/bootcamp', 0.6042595505714417, 'data', 0), ('chroma-core/chroma', 0.5949238538742065, 'data', 0), ('koaning/embetter', 0.5922350287437439, 'data', 0), ('docarray/docarray', 0.5800225734710693, 'data', 0), ('jina-ai/vectordb', 0.5595861077308655, 'data', 0), ('jina-ai/clip-as-service', 0.5556612610816956, 'nlp', 0), ('activeloopai/deeplake', 0.5401791930198669, 'ml-ops', 0), ('facebookresearch/augly', 0.528243899345398, 'data', 0), ('lucidrains/imagen-pytorch', 0.5279374718666077, 'ml-dl', 0), ('rom1504/clip-retrieval', 0.5256919264793396, 'ml', 0), ('openai/clip', 0.5130395889282227, 'ml-dl', 0)]

util

https://github.com/milvus-io/pymilvus

[]

[]

[]

milvus-io/pymilvus

pymilvus

Python

Python SDK for Milvus.

milvus-io

2024-01-11

2019-06-13

https://avatars.githubusercontent.com/u/51735404?v=4

Python SDK for Milvus.

['anns', 'database', 'milvus', 'sdk', 'vector']

['anns', 'database', 'milvus', 'sdk', 'vector']

2024-01-11

[('kubeflow/fairing', 0.5737506151199341, 'ml-ops', 0)]

sim

https://github.com/google-deepmind/materials_discovery

['materials-science']

Graph Networks for Materials Science (GNoME) is a project centered around scaling machine learning methods to tackle materials science.

[]

[]

google-deepmind/materials_discovery

materials_discovery

Python

google-deepmind

2024-01-12

2023-11-28

https://avatars.githubusercontent.com/u/8596759?v=4

Graph Networks for Materials Science (GNoME) is a project centered around scaling machine learning methods to tackle materials science.

[]

['materials-science']

2023-12-02

[('stellargraph/stellargraph', 0.6555060148239136, 'graph', 0), ('benedekrozemberczki/tigerlily', 0.5921242237091064, 'ml-dl', 0), ('chandlerbang/awesome-self-supervised-gnn', 0.5740145444869995, 'study', 0), ('pyg-team/pytorch_geometric', 0.5600719451904297, 'ml-dl', 0), ('whitead/dmol-book', 0.5389830470085144, 'ml-dl', 0), ('danielegrattarola/spektral', 0.5381258130073547, 'ml-dl', 0), ('dmlc/dgl', 0.5183952450752258, 'ml-dl', 0), ('graphistry/pygraphistry', 0.5010610818862915, 'data', 0)]

nlp

https://github.com/keras-team/keras-nlp

['keras', 'natural-language-processing']

[]

[]

keras-team/keras-nlp

keras-nlp

Python

Modular Natural Language Processing workflows with Keras

keras-team

2024-01-13

2020-05-28

https://avatars.githubusercontent.com/u/34455048?v=4

Modular Natural Language Processing workflows with Keras

['deep-learning', 'keras', 'machine-learning', 'nlp', 'tensorflow']

['deep-learning', 'keras', 'machine-learning', 'natural-language-processing', 'nlp', 'tensorflow']

2024-01-14

[('graykode/nlp-tutorial', 0.6779394149780273, 'study', 3), ('explosion/spacy', 0.6470063924789429, 'nlp', 4), ('huggingface/transformers', 0.6460193395614624, 'nlp', 5), ('nltk/nltk', 0.6287647485733032, 'nlp', 3), ('nvidia/deeplearningexamples', 0.6211730241775513, 'ml-dl', 3), ('flairnlp/flair', 0.6184731125831604, 'nlp', 3), ('thilinarajapakse/simpletransformers', 0.6119193434715271, 'nlp', 0), ('rasahq/rasa', 0.6086421012878418, 'llm', 3), ('allenai/allennlp', 0.605678379535675, 'nlp', 3), ('explosion/thinc', 0.5930647253990173, 'ml-dl', 5), ('sloria/textblob', 0.5880878567695618, 'nlp', 2), ('explosion/spacy-llm', 0.5786953568458557, 'llm', 3), ('huggingface/datasets', 0.5684626698493958, 'nlp', 5), ('arogozhnikov/einops', 0.5635877251625061, 'ml-dl', 3), ('keras-rl/keras-rl', 0.5594122409820557, 'ml-rl', 3), ('horovod/horovod', 0.5583081245422363, 'ml-ops', 4), ('ddbourgin/numpy-ml', 0.5563119053840637, 'ml', 1), ('franck-dernoncourt/neuroner', 0.5547518134117126, 'nlp', 4), ('nvidia/nemo', 0.5545443892478943, 'nlp', 2), ('lucidrains/toolformer-pytorch', 0.5536922216415405, 'llm', 1), ('rafiqhasan/auto-tensorflow', 0.5517141819000244, 'ml-dl', 2), ('keras-team/keras-cv', 0.5433396697044373, 'ml-dl', 1), ('nyandwi/modernconvnets', 0.5431491136550903, 'ml-dl', 2), ('deeppavlov/deeppavlov', 0.5425511002540588, 'nlp', 4), ('alibaba/easynlp', 0.539397120475769, 'nlp', 3), ('tensorflow/tensorflow', 0.5365269780158997, 'ml-dl', 3), ('databrickslabs/dolly', 0.5354406237602234, 'llm', 0), ('keras-team/autokeras', 0.5352697372436523, 'ml-dl', 4), ('explosion/spacy-models', 0.5345762372016907, 'nlp', 3), ('llmware-ai/llmware', 0.5331376194953918, 'llm', 2), ('onnx/onnx', 0.531283974647522, 'ml', 4), ('deepset-ai/farm', 0.5295949578285217, 'nlp', 2), ('ageron/handson-ml2', 0.528778076171875, 'ml', 0), ('tatsu-lab/stanford_alpaca', 0.5273944735527039, 'llm', 1), ('norskregnesentral/skweak', 0.5260323882102966, 'nlp', 1), ('google-research/electra', 0.5258187651634216, 'ml-dl', 3), ('paddlepaddle/paddlenlp', 0.5255599021911621, 'llm', 1), ('lm-sys/fastchat', 0.5216904878616333, 'llm', 0), ('kubeflow/pipelines', 0.5210731625556946, 'ml-ops', 1), ('makcedward/nlpaug', 0.5205011367797852, 'nlp', 3), ('polyaxon/polyaxon', 0.5162709355354309, 'ml-ops', 4), ('ggerganov/ggml', 0.5159798860549927, 'ml', 1), ('gradio-app/gradio', 0.5152199864387512, 'viz', 2), ('optimalscale/lmflow', 0.5128912329673767, 'llm', 1), ('danielegrattarola/spektral', 0.5112001299858093, 'ml-dl', 3), ('tensorflow/addons', 0.5104029178619385, 'ml', 3), ('keras-team/keras', 0.5086270570755005, 'ml-dl', 3), ('merantix-momentum/squirrel-core', 0.5084515810012817, 'ml', 5), ('bentoml/bentoml', 0.5048489570617676, 'ml-ops', 2), ('huggingface/text-generation-inference', 0.5031775236129761, 'llm', 2), ('tensorly/tensorly', 0.5025812387466431, 'ml-dl', 2), ('microsoft/semi-supervised-learning', 0.5014702677726746, 'ml', 3)]

data

https://github.com/binux/pyspider

[]

[]

[]

binux/pyspider

pyspider

Python

http://docs.pyspider.org/

A Powerful Spider(Web Crawler) System in Python.

binux

2024-01-13

2014-02-21

A Powerful Spider(Web Crawler) System in Python.

['crawler']

['crawler']

2020-08-02

[('s0md3v/photon', 0.7611035108566284, 'data', 1), ('scrapy/scrapy', 0.7435339093208313, 'data', 1), ('alirezamika/autoscraper', 0.6465148329734802, 'data', 1), ('nv7-github/googlesearch', 0.6098272204399109, 'util', 0), ('roniemartinez/dude', 0.5958371758460999, 'util', 1), ('clips/pattern', 0.5396731495857239, 'nlp', 0), ('psf/requests', 0.5332942605018616, 'web', 0), ('webpy/webpy', 0.5072404742240906, 'web', 0)]

web

https://github.com/pyeve/eve

[]

[]

[]

pyeve/eve

eve

Python

https://python-eve.org

REST API framework designed for human beings

pyeve

2024-01-13

2012-10-22

https://avatars.githubusercontent.com/u/26229868?v=4

REST API framework designed for human beings

['flask', 'mongodb', 'rest']

['flask', 'mongodb', 'rest']

2023-07-10

[('python-restx/flask-restx', 0.7703225612640381, 'web', 2), ('bottlepy/bottle', 0.594473659992218, 'web', 1), ('simple-salesforce/simple-salesforce', 0.5759877562522888, 'data', 0), ('falconry/falcon', 0.5698334574699402, 'web', 1), ('vitalik/django-ninja', 0.563342809677124, 'web', 0), ('pallets/flask', 0.5500431656837463, 'web', 1), ('tiangolo/fastapi', 0.5388421416282654, 'web', 1), ('tiangolo/full-stack-fastapi-postgresql', 0.5053060054779053, 'template', 0), ('mongodb/mongo-python-driver', 0.5024893879890442, 'data', 1), ('pynamodb/pynamodb', 0.5015949010848999, 'data', 0)]

util

https://github.com/openai/point-e

[]

[]

[]

openai/point-e

point-e

Python

Point cloud diffusion for 3D model synthesis

openai

2024-01-13

2022-12-06

https://avatars.githubusercontent.com/u/14957082?v=4

Point cloud diffusion for 3D model synthesis

[]

[]

2022-12-20

[('stability-ai/stablediffusion', 0.5376940965652466, 'diffusion', 0), ('compvis/latent-diffusion', 0.5376940369606018, 'diffusion', 0), ('tanelp/tiny-diffusion', 0.5226495265960693, 'diffusion', 0), ('ashawkey/stable-dreamfusion', 0.5210638642311096, 'diffusion', 0), ('nicolas-chaulet/torch-points3d', 0.5189539790153503, 'ml', 0)]

ml

https://github.com/probml/pyprobml

[]

[]

[]

probml/pyprobml

pyprobml

Jupyter Notebook

Python code for "Probabilistic Machine learning" book by Kevin Murphy

probml

2024-01-13

2016-08-17

https://avatars.githubusercontent.com/u/6309387?v=4

Python code for "Probabilistic Machine learning" book by Kevin Murphy

['blackjax', 'colab', 'flax', 'jax', 'jupyter-notebooks', 'machine-learning', 'numpyro', 'pml', 'probabilistic-programming', 'pymc3', 'pyro', 'pytorch', 'tensorflow']

['blackjax', 'colab', 'flax', 'jax', 'jupyter-notebooks', 'machine-learning', 'numpyro', 'pml', 'probabilistic-programming', 'pymc3', 'pyro', 'pytorch', 'tensorflow']

2023-12-19

[('pymc-devs/pymc3', 0.6565049886703491, 'ml', 1), ('gerdm/prml', 0.6533145308494568, 'study', 1), ('pyro-ppl/pyro', 0.6461431980133057, 'ml-dl', 3), ('fchollet/deep-learning-with-python-notebooks', 0.6373811364173889, 'study', 0), ('mynameisfiber/high_performance_python_2e', 0.6130873560905457, 'study', 0), ('ageron/handson-ml2', 0.6119535565376282, 'ml', 0), ('gbeced/pyalgotrade', 0.5891293883323669, 'finance', 0), ('scikit-learn/scikit-learn', 0.5849363207817078, 'ml', 1), ('awslabs/gluonts', 0.5823290348052979, 'time-series', 2), ('pycaret/pycaret', 0.582277238368988, 'ml', 1), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.576326847076416, 'study', 1), ('ta-lib/ta-lib-python', 0.5762322545051575, 'finance', 0), ('crflynn/stochastic', 0.5735928416252136, 'sim', 0), ('rasbt/mlxtend', 0.5730016827583313, 'ml', 1), ('rasbt/machine-learning-book', 0.5608888268470764, 'study', 2), ('patchy631/machine-learning', 0.5563993453979492, 'ml', 0), ('wesm/pydata-book', 0.5555208325386047, 'study', 0), ('d2l-ai/d2l-en', 0.5489851236343384, 'study', 4), ('python/cpython', 0.5431109666824341, 'util', 0), ('dylanhogg/awesome-python', 0.5428842306137085, 'study', 1), ('pypy/pypy', 0.5381896495819092, 'util', 0), ('ggerganov/ggml', 0.536136269569397, 'ml', 1), ('uber/orbit', 0.5333145260810852, 'time-series', 4), ('bayesianmodelingandcomputationinpython/bookcode_edition1', 0.5301855802536011, 'study', 0), ('rasbt/stat451-machine-learning-fs20', 0.5270578861236572, 'study', 0), ('gradio-app/gradio', 0.5261308550834656, 'viz', 1), ('firmai/industry-machine-learning', 0.5219587087631226, 'study', 1), ('cuemacro/finmarketpy', 0.5201766490936279, 'finance', 0), ('tensorly/tensorly', 0.5191105604171753, 'ml-dl', 4), ('sympy/sympy', 0.5161436200141907, 'math', 0), ('pytoolz/toolz', 0.5156102180480957, 'util', 0), ('goldmansachs/gs-quant', 0.5155179500579834, 'finance', 0), ('pytorch/rl', 0.514581561088562, 'ml-rl', 2), ('selfexplainml/piml-toolbox', 0.512611985206604, 'ml-interpretability', 0), ('online-ml/river', 0.5124793648719788, 'ml', 1), ('brandon-rhodes/python-patterns', 0.5112978219985962, 'util', 0), ('ddbourgin/numpy-ml', 0.508565366268158, 'ml', 1), ('shangtongzhang/reinforcement-learning-an-introduction', 0.5084415078163147, 'study', 0), ('scipy/scipy', 0.5070646405220032, 'math', 0), ('huggingface/transformers', 0.5070176124572754, 'nlp', 5), ('skorch-dev/skorch', 0.5041447877883911, 'ml-dl', 2), ('huggingface/huggingface_hub', 0.5018727779388428, 'ml', 2), ('jovianml/opendatasets', 0.5017038583755493, 'data', 1), ('stan-dev/pystan', 0.5016106963157654, 'ml', 0), ('clips/pattern', 0.5005698204040527, 'nlp', 1)]

util

https://github.com/hhatto/autopep8

[]

[]

[]

hhatto/autopep8

autopep8

Python

https://pypi.org/project/autopep8/

A tool that automatically formats Python code to conform to the PEP 8 style guide.

hhatto

2024-01-13

2010-12-29

A tool that automatically formats Python code to conform to the PEP 8 style guide.

['codeformatter', 'formatter', 'pep8']

['codeformatter', 'formatter', 'pep8']

2023-10-27

[('grantjenks/blue', 0.7624608278274536, 'util', 2), ('psf/black', 0.7485063672065735, 'util', 2), ('danielnoord/pydocstringformatter', 0.7380919456481934, 'util', 2), ('google/yapf', 0.7038267850875854, 'util', 1), ('pycqa/flake8', 0.6079347729682922, 'util', 1), ('pygments/pygments', 0.600104570388794, 'util', 0), ('pycqa/docformatter', 0.591210126876831, 'util', 1), ('google/latexify_py', 0.5800272822380066, 'util', 0), ('landscapeio/prospector', 0.5784581303596497, 'util', 0), ('pdm-project/pdm', 0.5722745656967163, 'util', 0), ('pycqa/pycodestyle', 0.5678965449333191, 'util', 1), ('python-markdown/markdown', 0.5607690811157227, 'util', 0), ('rubik/radon', 0.5594862699508667, 'util', 0), ('nedbat/coveragepy', 0.5550077557563782, 'testing', 0), ('python/cpython', 0.5486846566200256, 'util', 0), ('msaelices/py2mojo', 0.5481264591217041, 'util', 0), ('pytoolz/toolz', 0.5430788397789001, 'util', 0), ('astral-sh/ruff', 0.5378404259681702, 'util', 1), ('hoffstadt/dearpygui', 0.5373272895812988, 'gui', 0), ('eugeneyan/python-collab-template', 0.5339161157608032, 'template', 0), ('dosisod/refurb', 0.5332099795341492, 'util', 0), ('grahamdumpleton/wrapt', 0.5304956436157227, 'util', 0), ('pypy/pypy', 0.5292234420776367, 'util', 0), ('instagram/libcst', 0.5244827270507812, 'util', 0), ('connorferster/handcalcs', 0.5234463810920715, 'jupyter', 0), ('python-rope/rope', 0.5218623876571655, 'util', 0), ('pdoc3/pdoc', 0.5197219252586365, 'util', 0), ('facebookincubator/bowler', 0.5189270973205566, 'util', 0), ('pycqa/pylint-django', 0.5179296731948853, 'util', 0), ('brandon-rhodes/python-patterns', 0.5134424567222595, 'util', 0), ('willmcgugan/rich', 0.5127493739128113, 'term', 0), ('google/python-fire', 0.5113070011138916, 'term', 0), ('pyston/pyston', 0.5110304355621338, 'util', 0), ('sourcery-ai/sourcery', 0.5095126628875732, 'util', 0), ('tiangolo/typer', 0.5092093348503113, 'term', 0), ('pycqa/isort', 0.5075655579566956, 'util', 1), ('sqlalchemy/mako', 0.5068827867507935, 'template', 0), ('mkdocstrings/python', 0.5049331784248352, 'util', 0), ('mnooner256/pyqrcode', 0.5037751793861389, 'util', 0)]

ml

https://github.com/lucidrains/deep-daze

[]

[]

[]

lucidrains/deep-daze

deep-daze

Python

Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun

lucidrains

2024-01-12

2021-01-17

Simple command line tool for text to image generation using OpenAI's CLIP and Siren (Implicit neural representation network). Technique was originally created by https://twitter.com/advadnoun

['artificial-intelligence', 'deep-learning', 'implicit-neural-representation', 'multi-modality', 'siren', 'text-to-image', 'transformers']

['artificial-intelligence', 'deep-learning', 'implicit-neural-representation', 'multi-modality', 'siren', 'text-to-image', 'transformers']

2022-03-13

[('saharmor/dalle-playground', 0.6547111868858337, 'diffusion', 3), ('lucidrains/dalle2-pytorch', 0.631841242313385, 'diffusion', 3), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.625627875328064, 'web', 1), ('lucidrains/imagen-pytorch', 0.588476300239563, 'ml-dl', 3), ('thudm/cogvideo', 0.5634084939956665, 'ml', 0), ('borisdayma/dalle-mini', 0.5611160397529602, 'diffusion', 0), ('google/sentencepiece', 0.5594016909599304, 'nlp', 0), ('open-mmlab/mmediting', 0.5528916716575623, 'ml', 1), ('sharonzhou/long_stable_diffusion', 0.5463470220565796, 'diffusion', 0), ('minimaxir/gpt-2-simple', 0.5265099406242371, 'llm', 0), ('openai/clip', 0.5211201906204224, 'ml-dl', 1), ('invoke-ai/invokeai', 0.5158758163452148, 'diffusion', 1), ('minimaxir/textgenrnn', 0.5096532106399536, 'nlp', 1)]

util

https://github.com/pyinvoke/invoke

['execution']

[]

[]

pyinvoke/invoke

invoke

Python

http://pyinvoke.org

Pythonic task management & command execution.

pyinvoke

2024-01-13

2012-02-29

https://avatars.githubusercontent.com/u/1486921?v=4

Pythonic task management & command execution.

[]

['execution']

2023-12-01

[('agronholm/apscheduler', 0.6340285539627075, 'util', 0), ('dbader/schedule', 0.514901876449585, 'util', 0)]

util

https://github.com/jorisschellekens/borb

[]

[]

[]

jorisschellekens/borb

borb

Python

https://borbpdf.com/

borb is a library for reading, creating and manipulating PDF files in python.

jorisschellekens

2024-01-13

2020-11-07

borb is a library for reading, creating and manipulating PDF files in python.

['pdf', 'pdf-conversion', 'pdf-converter', 'pdf-generation', 'pdf-library', 'sdk', 'typesetting']

['pdf', 'pdf-conversion', 'pdf-converter', 'pdf-generation', 'pdf-library', 'sdk', 'typesetting']

2023-12-17

[('py-pdf/pypdf2', 0.6551130414009094, 'util', 1), ('pyfpdf/fpdf2', 0.6073178052902222, 'util', 3), ('camelot-dev/camelot', 0.5273860692977905, 'util', 0), ('geospatialpython/pyshp', 0.5256045460700989, 'gis', 0), ('pypdfium2-team/pypdfium2', 0.5246109366416931, 'util', 1), ('bhaskatripathi/pdfgpt', 0.5003618597984314, 'llm', 0)]

time-series

https://github.com/salesforce/merlion

[]

[]

[]

salesforce/merlion

Merlion

Python

Merlion: A Machine Learning Framework for Time Series Intelligence

salesforce

2024-01-13

2021-07-28

https://avatars.githubusercontent.com/u/453694?v=4

Merlion: A Machine Learning Framework for Time Series Intelligence

['anomaly-detection', 'automl', 'benchmarking', 'ensemble-learning', 'forecasting', 'machine-learning', 'time-series']

['anomaly-detection', 'automl', 'benchmarking', 'ensemble-learning', 'forecasting', 'machine-learning', 'time-series']

2023-03-22

[('sktime/sktime', 0.7518776059150696, 'time-series', 3), ('unit8co/darts', 0.7470134496688843, 'time-series', 4), ('winedarksea/autots', 0.682404637336731, 'time-series', 4), ('aistream-peelout/flow-forecast', 0.6415663361549377, 'time-series', 3), ('blue-yonder/tsfresh', 0.6107531189918518, 'time-series', 1), ('alkaline-ml/pmdarima', 0.589963436126709, 'time-series', 3), ('salesforce/deeptime', 0.5836126804351807, 'time-series', 2), ('awslabs/autogluon', 0.5632773637771606, 'ml', 5), ('pycaret/pycaret', 0.5579712986946106, 'ml', 3), ('tdameritrade/stumpy', 0.5562719106674194, 'time-series', 1), ('firmai/atspy', 0.5541254281997681, 'time-series', 2), ('microsoft/flaml', 0.5453396439552307, 'ml', 2), ('yzhao062/pyod', 0.5439088940620422, 'data', 2), ('linkedin/greykite', 0.5402796864509583, 'ml', 0), ('awslabs/gluonts', 0.5388320684432983, 'time-series', 3), ('nixtla/statsforecast', 0.5316644906997681, 'time-series', 4), ('ourownstory/neural_prophet', 0.5225098133087158, 'ml', 3), ('xplainable/xplainable', 0.5224214196205139, 'ml-interpretability', 1), ('microprediction/microprediction', 0.5122169852256775, 'time-series', 1), ('facebookresearch/kats', 0.5117724537849426, 'time-series', 1), ('microsoft/nni', 0.503190279006958, 'ml', 2)]

nlp

https://github.com/bytedance/lightseq

[]

[]

[]

bytedance/lightseq

lightseq

C++

LightSeq: A High Performance Library for Sequence Processing and Generation

bytedance

2024-01-12

2019-12-06

https://avatars.githubusercontent.com/u/4158466?v=4

LightSeq: A High Performance Library for Sequence Processing and Generation

['accelerate', 'bart', 'beam-search', 'bert', 'cuda', 'diverse-decoding', 'gpt', 'inference', 'multilingual-nmt', 'sampling', 'training', 'transformer']

['accelerate', 'bart', 'beam-search', 'bert', 'cuda', 'diverse-decoding', 'gpt', 'inference', 'multilingual-nmt', 'sampling', 'training', 'transformer']

2023-05-10

[('huggingface/text-generation-inference', 0.672805666923523, 'llm', 3), ('ferdinandzhong/punctuator', 0.5860391855239868, 'nlp', 1), ('amazon-science/dq-bart', 0.564974844455719, 'nlp', 0), ('salesforce/xgen', 0.5642438530921936, 'llm', 0), ('infinitylogesh/mutate', 0.562773585319519, 'nlp', 0), ('ofa-sys/ofa', 0.5597769021987915, 'llm', 0), ('huggingface/transformers', 0.5596634149551392, 'nlp', 2), ('mit-han-lab/streaming-llm', 0.5517858862876892, 'llm', 0), ('allenai/allennlp', 0.5493444800376892, 'nlp', 0), ('minimaxir/gpt-2-simple', 0.5469551682472229, 'llm', 0), ('google-research/electra', 0.5465645790100098, 'ml-dl', 0), ('bigcode-project/starcoder', 0.5453761219978333, 'llm', 0), ('databrickslabs/dolly', 0.5437467098236084, 'llm', 1), ('jina-ai/finetuner', 0.5338277220726013, 'ml', 1), ('togethercomputer/redpajama-data', 0.5332623720169067, 'llm', 0), ('hazyresearch/safari', 0.5279725790023804, 'ml', 0), ('jonasgeiping/cramming', 0.5221551656723022, 'nlp', 0), ('norskregnesentral/skweak', 0.5218310952186584, 'nlp', 0), ('bigscience-workshop/megatron-deepspeed', 0.515959620475769, 'llm', 0), ('microsoft/megatron-deepspeed', 0.515959620475769, 'llm', 0), ('lianjiatech/belle', 0.5151085257530212, 'llm', 0), ('hannibal046/awesome-llm', 0.5142962336540222, 'study', 1), ('minimaxir/aitextgen', 0.5134293437004089, 'llm', 0), ('paddlepaddle/paddlenlp', 0.5104448199272156, 'llm', 1), ('extreme-bert/extreme-bert', 0.5086089968681335, 'llm', 2), ('cqcl/lambeq', 0.5084514617919922, 'nlp', 0), ('bigscience-workshop/biomedical', 0.5078558325767517, 'data', 0), ('bobazooba/xllm', 0.5065972208976746, 'llm', 1), ('freedomintelligence/llmzoo', 0.5059230327606201, 'llm', 0), ('blinkdl/rwkv-lm', 0.5059091448783875, 'llm', 2), ('srush/minichain', 0.5048473477363586, 'llm', 0), ('timdettmers/bitsandbytes', 0.5029526948928833, 'util', 1), ('salesforce/blip', 0.5009039044380188, 'diffusion', 0), ('deepset-ai/farm', 0.5006200671195984, 'nlp', 1), ('microsoft/lora', 0.5001585483551025, 'llm', 0), ('ai21labs/lm-evaluation', 0.5000201463699341, 'llm', 0)]

llm

https://github.com/mshumer/gpt-llm-trainer

[]

Input a description of your task, and the system will generate a dataset, parse it, and fine-tune a LLaMA 2 model for you

[]

[]

mshumer/gpt-llm-trainer

gpt-llm-trainer

Jupyter Notebook

mshumer

2024-01-14

2023-08-09

Input a description of your task, and the system will generate a dataset, parse it, and fine-tune a LLaMA 2 model for you

[]

[]

2023-08-23

[('microsoft/llama-2-onnx', 0.6853927969932556, 'llm', 0), ('zrrskywalker/llama-adapter', 0.684531569480896, 'llm', 0), ('facebookresearch/llama-recipes', 0.6829999685287476, 'llm', 0), ('tloen/alpaca-lora', 0.663759171962738, 'llm', 0), ('run-llama/llama-lab', 0.6018344759941101, 'llm', 0), ('facebookresearch/llama', 0.6008679866790771, 'llm', 0), ('jzhang38/tinyllama', 0.5883111953735352, 'llm', 0), ('tairov/llama2.mojo', 0.5809900760650635, 'llm', 0), ('karpathy/llama2.c', 0.5627032518386841, 'llm', 0), ('lightning-ai/lit-llama', 0.5464016199111938, 'llm', 0), ('openlm-research/open_llama', 0.5152719616889954, 'llm', 0), ('facebookresearch/codellama', 0.509406328201294, 'llm', 0), ('run-llama/llama-hub', 0.5054514408111572, 'data', 0), ('jerryjliu/llama_index', 0.5029345154762268, 'llm', 0)]

ml

https://github.com/scikit-learn-contrib/category_encoders

[]

[]

[]

scikit-learn-contrib/category_encoders

category_encoders

Python

http://contrib.scikit-learn.org/category_encoders/

A library of sklearn compatible categorical variable encoders

scikit-learn-contrib

2024-01-11

2015-11-29

https://avatars.githubusercontent.com/u/17349883?v=4

A library of sklearn compatible categorical variable encoders

[]

[]

2023-12-13

[]

util

https://github.com/pyparsing/pyparsing

[]

[]

[]

pyparsing/pyparsing

pyparsing

Python

Python library for creating PEG parsers

pyparsing

2024-01-13

2017-05-14

https://avatars.githubusercontent.com/u/28690438?v=4

Python library for creating PEG parsers

['parser-combinators', 'parsing', 'parsing-expression-grammar', 'parsing-library', 'peg-parsers', 'text-processing']

['parser-combinators', 'parsing', 'parsing-expression-grammar', 'parsing-library', 'peg-parsers', 'text-processing']

2023-11-20

[('instagram/libcst', 0.6272467970848083, 'util', 0), ('pytoolz/toolz', 0.6166950464248657, 'util', 0), ('tobymao/sqlglot', 0.6120659708976746, 'data', 0), ('pandas-dev/pandas', 0.5993269681930542, 'pandas', 0), ('google/latexify_py', 0.5657850503921509, 'util', 0), ('sloria/textblob', 0.5576520562171936, 'nlp', 0), ('fastai/fastcore', 0.5457038283348083, 'util', 0), ('andialbrecht/sqlparse', 0.5442314147949219, 'data', 0), ('pypy/pypy', 0.5254474878311157, 'util', 0), ('has2k1/plotnine', 0.5245786905288696, 'viz', 0), ('pyston/pyston', 0.522191047668457, 'util', 0), ('sympy/sympy', 0.521645188331604, 'math', 0), ('dylanhogg/awesome-python', 0.5186076164245605, 'study', 0), ('python/cpython', 0.5173945426940918, 'util', 0), ('joowani/binarytree', 0.5169668197631836, 'util', 0), ('1200wd/bitcoinlib', 0.5124039053916931, 'crypto', 0), ('tiangolo/sqlmodel', 0.5065826773643494, 'data', 0), ('evhub/coconut', 0.504447877407074, 'util', 0), ('ibis-project/ibis', 0.5017038583755493, 'data', 0), ('rasbt/mlxtend', 0.5005236864089966, 'ml', 0)]

gamedev

https://github.com/pokepetter/ursina

[]

[]

[]

pokepetter/ursina

ursina

Python

https://pokepetter.github.io/ursina/

A game engine powered by python and panda3d.

pokepetter

2024-01-12

2017-07-19

A game engine powered by python and panda3d.

['3d-game-engine', 'game-development', 'game-engine']

['3d-game-engine', 'game-development', 'game-engine']

2024-01-02

[('panda3d/panda3d', 0.8077520132064819, 'gamedev', 2), ('kitao/pyxel', 0.6735712885856628, 'gamedev', 2), ('lordmauve/pgzero', 0.6621728539466858, 'gamedev', 0), ('renpy/renpy', 0.6157830357551575, 'viz', 0), ('pygame/pygame', 0.5800055861473083, 'gamedev', 1), ('pythonarcade/arcade', 0.5775792598724365, 'gamedev', 0), ('isl-org/open3d', 0.5535932183265686, 'sim', 0), ('ljvmiranda921/seagull', 0.5359201431274414, 'sim', 0), ('marcomusy/vedo', 0.5303018093109131, 'viz', 0), ('nvidia/warp', 0.5230095982551575, 'sim', 0), ('pygamelib/pygamelib', 0.5143521428108215, 'gamedev', 1), ('alephalpha/golly', 0.5002817511558533, 'sim', 0)]

data

https://github.com/graphistry/pygraphistry

[]

[]

[]

graphistry/pygraphistry

pygraphistry

Python

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

graphistry

2024-01-13

2015-06-02

https://avatars.githubusercontent.com/u/6157633?v=4

PyGraphistry is a Python library to quickly load, shape, embed, and explore big graphs with the GPU-accelerated Graphistry visual graph analyzer

['csv', 'cudf', 'cugraph', 'gpu', 'graph', 'graph-visualization', 'graphistry', 'igraph', 'jupyter', 'neo4j', 'network-analysis', 'network-visualization', 'networkx', 'pandas', 'rapids', 'splunk', 'tigergraph', 'visualization', 'webgl']

['csv', 'cudf', 'cugraph', 'gpu', 'graph', 'graph-visualization', 'graphistry', 'igraph', 'jupyter', 'neo4j', 'network-analysis', 'network-visualization', 'networkx', 'pandas', 'rapids', 'splunk', 'tigergraph', 'visualization', 'webgl']

2023-12-27

[('h4kor/graph-force', 0.6990000605583191, 'graph', 0), ('pygraphviz/pygraphviz', 0.678774356842041, 'viz', 1), ('pyg-team/pytorch_geometric', 0.6707996129989624, 'ml-dl', 0), ('dmlc/dgl', 0.6582305431365967, 'ml-dl', 0), ('westhealth/pyvis', 0.6478259563446045, 'graph', 2), ('networkx/networkx', 0.6410859823226929, 'graph', 1), ('plotly/plotly.py', 0.6395604610443115, 'viz', 2), ('a-r-j/graphein', 0.6311023235321045, 'sim', 0), ('artelys/geonetworkx', 0.6271733045578003, 'gis', 0), ('holoviz/hvplot', 0.6067784428596497, 'pandas', 0), ('stellargraph/stellargraph', 0.5959926247596741, 'graph', 1), ('cvxgrp/pymde', 0.5851930379867554, 'ml', 2), ('man-group/dtale', 0.5765081644058228, 'viz', 2), ('holoviz/holoviz', 0.5680197477340698, 'viz', 0), ('pyqtgraph/pyqtgraph', 0.5679578185081482, 'viz', 1), ('holoviz/panel', 0.567793607711792, 'viz', 1), ('vaexio/vaex', 0.5663058161735535, 'perf', 1), ('altair-viz/altair', 0.5656019449234009, 'viz', 1), ('residentmario/geoplot', 0.56211256980896, 'gis', 0), ('benedekrozemberczki/tigerlily', 0.5483189225196838, 'ml-dl', 2), ('has2k1/plotnine', 0.5480146408081055, 'viz', 0), ('pyglet/pyglet', 0.5440356135368347, 'gamedev', 0), ('kanaries/pygwalker', 0.5422446727752686, 'pandas', 2), ('vispy/vispy', 0.5377211570739746, 'viz', 1), ('jsonpickle/jsonpickle', 0.535290539264679, 'data', 0), ('accenture/ampligraph', 0.532095193862915, 'data', 0), ('scitools/iris', 0.5314244627952576, 'gis', 0), ('danielegrattarola/spektral', 0.5304725170135498, 'ml-dl', 0), ('contextlab/hypertools', 0.5276858806610107, 'ml', 1), ('hazyresearch/hgcn', 0.525396466255188, 'ml', 0), ('pydot/pydot', 0.5253562331199646, 'viz', 0), ('rapidsai/cudf', 0.5241773724555969, 'pandas', 4), ('bokeh/bokeh', 0.5225502252578735, 'viz', 2), ('wesm/pydata-book', 0.522087812423706, 'study', 0), ('matplotlib/matplotlib', 0.5203686356544495, 'viz', 0), ('pypy/pypy', 0.519489049911499, 'util', 0), ('kuanb/peartree', 0.5183374285697937, 'gis', 1), ('rampasek/graphgps', 0.5173921585083008, 'graph', 0), ('mwaskom/seaborn', 0.5153336524963379, 'viz', 1), ('pytorch/data', 0.5149250030517578, 'data', 0), ('scitools/cartopy', 0.5080820918083191, 'gis', 0), ('chandlerbang/awesome-self-supervised-gnn', 0.5049978494644165, 'study', 0), ('comfyanonymous/comfyui', 0.503555953502655, 'diffusion', 0), ('cuemacro/chartpy', 0.5035216212272644, 'viz', 0), ('rapidsai/jupyterlab-nvdashboard', 0.503430187702179, 'jupyter', 1), ('enthought/mayavi', 0.5026683807373047, 'viz', 1), ('google-deepmind/materials_discovery', 0.5010610818862915, 'sim', 0), ('vizzuhq/ipyvizzu', 0.5005484819412231, 'jupyter', 1)]

pandas

https://github.com/fugue-project/fugue

['duckdb']

[]

[]

fugue-project/fugue

fugue

Python

https://fugue-tutorials.readthedocs.io/

A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.

fugue-project

2024-01-14

2020-03-24

https://avatars.githubusercontent.com/u/65140352?v=4

A unified interface for distributed computing. Fugue executes SQL, Python, Pandas, and Polars code on Spark, Dask and Ray without any rewrites.

['dask', 'data-practitioners', 'distributed', 'distributed-computing', 'distributed-systems', 'machine-learning', 'pandas', 'spark', 'sql']

['dask', 'data-practitioners', 'distributed', 'distributed-computing', 'distributed-systems', 'duckdb', 'machine-learning', 'pandas', 'spark', 'sql']

2024-01-07

[('eventual-inc/daft', 0.6778815388679504, 'pandas', 2), ('backtick-se/cowait', 0.6694428324699402, 'util', 2), ('apache/spark', 0.6404576897621155, 'data', 2), ('ibis-project/ibis', 0.5997548699378967, 'data', 4), ('dagworks-inc/hamilton', 0.5906447768211365, 'ml-ops', 2), ('airbytehq/airbyte', 0.5778406858444214, 'data', 0), ('mage-ai/mage-ai', 0.5678737163543701, 'ml-ops', 3), ('dask/distributed', 0.5652367472648621, 'perf', 2), ('aws/aws-sdk-pandas', 0.5624109506607056, 'pandas', 1), ('hi-primus/optimus', 0.5615660548210144, 'ml-ops', 3), ('kestra-io/kestra', 0.5582082271575928, 'ml-ops', 0), ('polyaxon/datatile', 0.5508334040641785, 'pandas', 3), ('flyteorg/flyte', 0.5496802926063538, 'ml-ops', 1), ('pola-rs/polars', 0.5422793030738831, 'pandas', 0), ('merantix-momentum/squirrel-core', 0.5387210845947266, 'ml', 2), ('jmcarpenter2/swifter', 0.5381412506103516, 'pandas', 2), ('lithops-cloud/lithops', 0.53661048412323, 'ml-ops', 1), ('ray-project/ray', 0.5340755581855774, 'ml-ops', 2), ('dagster-io/dagster', 0.5329538583755493, 'ml-ops', 0), ('tobymao/sqlglot', 0.5296240448951721, 'data', 3), ('airbnb/omniduct', 0.5275896787643433, 'data', 0), ('fastai/fastcore', 0.527552604675293, 'util', 0), ('skypilot-org/skypilot', 0.5239272117614746, 'llm', 1), ('meltano/meltano', 0.5231815576553345, 'ml-ops', 0), ('astronomer/astro-sdk', 0.5199980735778809, 'ml-ops', 2), ('uber/fiber', 0.5197455883026123, 'data', 2), ('tiangolo/sqlmodel', 0.5192634463310242, 'data', 1), ('vaexio/vaex', 0.5170252919197083, 'perf', 1), ('spotify/luigi', 0.5144204497337341, 'ml-ops', 0), ('avaiga/taipy', 0.5130361318588257, 'data', 0), ('horovod/horovod', 0.5121609568595886, 'ml-ops', 2), ('prefecthq/prefect-dask', 0.5114060044288635, 'util', 1), ('dask/dask', 0.5079086422920227, 'perf', 2), ('airtai/faststream', 0.5063053369522095, 'perf', 1), ('streamlit/streamlit', 0.5049965381622314, 'viz', 1), ('ml-tooling/opyrator', 0.504669725894928, 'viz', 1), ('joblib/joblib', 0.5016358494758606, 'util', 0)]

util

https://github.com/mitmproxy/pdoc

[]

[]

[]

mitmproxy/pdoc

pdoc

Python

https://pdoc.dev

API Documentation for Python Projects

mitmproxy

2024-01-13

2013-08-04

https://avatars.githubusercontent.com/u/4652787?v=4

API Documentation for Python Projects

['api', 'api-documentation', 'docs', 'docstring', 'docstrings', 'documentation', 'documentation-generator', 'documentation-tool', 'pdoc']

['api', 'api-documentation', 'docs', 'docstring', 'docstrings', 'documentation', 'documentation-generator', 'documentation-tool', 'pdoc']

2024-01-11

[('pdoc3/pdoc', 0.7915372252464294, 'util', 8), ('sphinx-doc/sphinx', 0.7031545042991638, 'util', 3), ('squidfunk/mkdocs-material', 0.6519834399223328, 'util', 1), ('mkdocstrings/griffe', 0.6451767683029175, 'util', 2), ('vitalik/django-ninja', 0.5793086886405945, 'web', 0), ('landscapeio/prospector', 0.5606246590614319, 'util', 0), ('eugeneyan/python-collab-template', 0.5599040389060974, 'template', 0), ('mkdocstrings/mkdocstrings', 0.5541725158691406, 'util', 1), ('amaargiru/pyroad', 0.5501058101654053, 'study', 0), ('eternnoir/pytelegrambotapi', 0.5450152158737183, 'util', 0), ('mkdocs/mkdocs', 0.5321336984634399, 'util', 1), ('executablebooks/jupyter-book', 0.5281922817230225, 'jupyter', 1), ('googleapis/google-api-python-client', 0.5224719047546387, 'util', 0), ('pypa/hatch', 0.520322322845459, 'util', 0), ('martinheinz/python-project-blueprint', 0.514594554901123, 'template', 0), ('openai/openai-python', 0.5083382725715637, 'util', 0), ('mkdocstrings/python', 0.5048332214355469, 'util', 1), ('requests/toolbelt', 0.5041638016700745, 'util', 0), ('simple-salesforce/simple-salesforce', 0.5029121041297913, 'data', 1), ('danielnoord/pydocstringformatter', 0.5013178586959839, 'util', 1), ('python-odin/odin', 0.5004577040672302, 'util', 0)]

util

https://github.com/omry/omegaconf

[]

[]

[]

omry/omegaconf

omegaconf

Python

Flexible Python configuration system. The last one you will ever need.

omry

2024-01-13

2018-09-03

Flexible Python configuration system. The last one you will ever need.

['configuration-files', 'configuration-loader', 'python-types', 'schema-validator', 'yaml', 'yaml-configuration']

['configuration-files', 'configuration-loader', 'python-types', 'schema-validator', 'yaml', 'yaml-configuration']

2023-11-18

[('python-odin/odin', 0.5967031121253967, 'util', 1), ('google/gin-config', 0.5957804322242737, 'util', 0), ('pypa/hatch', 0.5926797986030579, 'util', 0), ('mkdocstrings/griffe', 0.5919175744056702, 'util', 0), ('pomponchik/instld', 0.5507912039756775, 'util', 0), ('indygreg/pyoxidizer', 0.5404947400093079, 'util', 0), ('eugeneyan/python-collab-template', 0.5363547205924988, 'template', 0), ('pdm-project/pdm', 0.5336859822273254, 'util', 0), ('jazzband/pip-tools', 0.527951180934906, 'util', 0), ('python-poetry/poetry', 0.5274845361709595, 'util', 0), ('pydantic/pydantic', 0.5237911343574524, 'util', 0), ('malloydata/malloy-py', 0.5221198201179504, 'data', 0), ('pypa/pipenv', 0.5201141834259033, 'util', 0), ('pytoolz/toolz', 0.5165718197822571, 'util', 0), ('pypi/warehouse', 0.5100882053375244, 'util', 0), ('mitsuhiko/rye', 0.5054756999015808, 'util', 0), ('google/python-fire', 0.5032675862312317, 'term', 0)]

gamedev

https://github.com/pythonarcade/arcade

[]

[]

[]

pythonarcade/arcade

arcade

Python

http://arcade.academy

Easy to use Python library for creating 2D arcade games.

pythonarcade

2024-01-12

2016-01-04

https://avatars.githubusercontent.com/u/39569439?v=4

Easy to use Python library for creating 2D arcade games.

['arcade-api', 'arcade-framework', 'arcade-learning-environment', 'educational-resources', 'educational-technology', 'opengl']

['arcade-api', 'arcade-framework', 'arcade-learning-environment', 'educational-resources', 'educational-technology', 'opengl']

2024-01-11

[('pygame/pygame', 0.6259638071060181, 'gamedev', 0), ('lordmauve/pgzero', 0.6107795238494873, 'gamedev', 0), ('pygamelib/pygamelib', 0.5959578156471252, 'gamedev', 0), ('viblo/pymunk', 0.584841787815094, 'sim', 0), ('panda3d/panda3d', 0.5839753746986389, 'gamedev', 1), ('pokepetter/ursina', 0.5775792598724365, 'gamedev', 0), ('kitao/pyxel', 0.5633159875869751, 'gamedev', 0), ('projectmesa/mesa', 0.5278759002685547, 'sim', 0), ('pyglet/pyglet', 0.5264350175857544, 'gamedev', 1), ('urwid/urwid', 0.5146381258964539, 'term', 0), ('ljvmiranda921/seagull', 0.5029021501541138, 'sim', 0)]

util

https://github.com/mkdocstrings/mkdocstrings

[]

[]

[]

mkdocstrings/mkdocstrings

mkdocstrings

Python

https://mkdocstrings.github.io/

:blue_book: Automatic documentation from sources, for MkDocs.

mkdocstrings

2024-01-13

2019-12-09

https://avatars.githubusercontent.com/u/75664361?v=4

📘 Automatic documentation from sources, for MkDocs.

['autodoc', 'docstrings', 'material-theme', 'mkdocs', 'mkdocs-plugin', 'mkdocstrings']

['autodoc', 'docstrings', 'material-theme', 'mkdocs', 'mkdocs-plugin', 'mkdocstrings']

2024-01-04

[('mkdocstrings/python', 0.6996007561683655, 'util', 3), ('squidfunk/mkdocs-material', 0.6913550496101379, 'util', 1), ('mkdocs/mkdocs', 0.6345070600509644, 'util', 1), ('pdoc3/pdoc', 0.6134604215621948, 'util', 1), ('sphinx-doc/sphinx', 0.5597922801971436, 'util', 0), ('mitmproxy/pdoc', 0.5541725158691406, 'util', 1), ('pycqa/docformatter', 0.5333818793296814, 'util', 0)]

data

https://github.com/simonw/sqlite-utils

[]

[]

[]

simonw/sqlite-utils

sqlite-utils

Python

https://sqlite-utils.datasette.io

Python CLI utility and library for manipulating SQLite databases

simonw

2024-01-12

2018-07-14

Python CLI utility and library for manipulating SQLite databases

['cli', 'click', 'datasette', 'datasette-io', 'datasette-tool', 'sqlite', 'sqlite-database']

['cli', 'click', 'datasette', 'datasette-io', 'datasette-tool', 'sqlite', 'sqlite-database']

2023-12-08

[('sqlalchemy/sqlalchemy', 0.6196154952049255, 'data', 0), ('tiangolo/sqlmodel', 0.5946550965309143, 'data', 0), ('ibis-project/ibis', 0.540537416934967, 'data', 1), ('tconbeer/harlequin', 0.5377789735794067, 'term', 0), ('andialbrecht/sqlparse', 0.5041010975837708, 'data', 0)]

llm

https://github.com/cstankonrad/long_llama

['llama', 'language-model']

[]

[]

cstankonrad/long_llama

long_llama

Python

LongLLaMA is a large language model capable of handling long contexts. It is based on OpenLLaMA and fine-tuned with the Focused Transformer (FoT) method.

cstankonrad

2024-01-13

2023-07-06

LongLLaMA is a large language model capable of handling long contexts. It is based on OpenLLaMA and fine-tuned with the Focused Transformer (FoT) method.

[]

['language-model', 'llama']

2023-11-07

[('openlmlab/leval', 0.5901378989219666, 'llm', 1), ('freedomintelligence/llmzoo', 0.5405339002609253, 'llm', 1), ('juncongmoo/pyllama', 0.5282744765281677, 'llm', 0), ('lightning-ai/lit-llama', 0.5269233584403992, 'llm', 2), ('next-gpt/next-gpt', 0.5235233306884766, 'llm', 0), ('facebookresearch/codellama', 0.5162266492843628, 'llm', 2), ('salesforce/xgen', 0.5117976665496826, 'llm', 1), ('thudm/chatglm2-6b', 0.5114611387252808, 'llm', 0), ('ai21labs/lm-evaluation', 0.5108537077903748, 'llm', 1), ('young-geng/easylm', 0.5092800259590149, 'llm', 2), ('hiyouga/llama-factory', 0.5056300163269043, 'llm', 2), ('hiyouga/llama-efficient-tuning', 0.5056299567222595, 'llm', 2), ('cg123/mergekit', 0.5025786757469177, 'llm', 1), ('hannibal046/awesome-llm', 0.5006245970726013, 'study', 1)]

util

https://github.com/imageio/imageio

[]

[]

[]

imageio/imageio

imageio

Python

https://imageio.readthedocs.io

Python library for reading and writing image data

imageio

2024-01-13

2013-05-04

https://avatars.githubusercontent.com/u/3678179?v=4

Python library for reading and writing image data

['animated-gif', 'dicom', 'imageio', 'scientific-formats', 'video', 'webcam-capture']

['animated-gif', 'dicom', 'imageio', 'scientific-formats', 'video', 'webcam-capture']

2023-12-11

[('python-pillow/pillow', 0.6861987113952637, 'util', 0), ('zulko/moviepy', 0.6167894601821899, 'util', 1), ('rhettbull/osxphotos', 0.6166835427284241, 'util', 0), ('wesm/pydata-book', 0.6035079956054688, 'study', 0), ('geospatialpython/pyshp', 0.5908835530281067, 'gis', 0), ('pandas-dev/pandas', 0.5883070826530457, 'pandas', 0), ('pytoolz/toolz', 0.5862778425216675, 'util', 0), ('earthlab/earthpy', 0.5848910808563232, 'gis', 0), ('pypy/pypy', 0.5812743902206421, 'util', 0), ('soft-matter/pims', 0.5806184411048889, 'util', 1), ('has2k1/plotnine', 0.5798242092132568, 'viz', 0), ('lightly-ai/lightly', 0.5790013670921326, 'ml', 0), ('scikit-image/scikit-image', 0.5782924890518188, 'util', 0), ('pyglet/pyglet', 0.5611344575881958, 'gamedev', 0), ('scitools/cartopy', 0.5579615831375122, 'gis', 0), ('erotemic/ubelt', 0.5557732582092285, 'util', 0), ('python/cpython', 0.5454882979393005, 'util', 0), ('eleutherai/pyfra', 0.538760244846344, 'ml', 0), ('altair-viz/altair', 0.5385008454322815, 'viz', 0), ('google/yapf', 0.5354976654052734, 'util', 0), ('connorferster/handcalcs', 0.5331127047538757, 'jupyter', 0), ('mdbloice/augmentor', 0.5311002135276794, 'ml', 0), ('python-odin/odin', 0.5272129774093628, 'util', 0), ('plotly/dash', 0.5265047550201416, 'viz', 0), ('krzjoa/awesome-python-data-science', 0.5262821316719055, 'study', 0), ('irmen/pyminiaudio', 0.5260134339332581, 'util', 0), ('residentmario/geoplot', 0.525743305683136, 'gis', 0), ('hoffstadt/dearpygui', 0.5239776968955994, 'gui', 0), ('matplotlib/matplotlib', 0.5237370133399963, 'viz', 0), ('pyston/pyston', 0.5213198661804199, 'util', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5206165909767151, 'study', 0), ('holoviz/holoviz', 0.5204654335975647, 'viz', 0), ('dylanhogg/awesome-python', 0.5201471447944641, 'study', 0), ('1200wd/bitcoinlib', 0.517402708530426, 'crypto', 0), ('raphaelquast/eomaps', 0.514751672744751, 'gis', 0), ('bokeh/bokeh', 0.5136635303497314, 'viz', 0), ('plotly/plotly.py', 0.5120216012001038, 'viz', 0), ('jovianml/opendatasets', 0.5112266540527344, 'data', 0), ('pytorch/data', 0.5112005472183228, 'data', 0), ('scitools/iris', 0.5107640027999878, 'gis', 0), ('pyeve/cerberus', 0.5100802183151245, 'data', 0), ('pytables/pytables', 0.5082108378410339, 'data', 0), ('geopandas/geopandas', 0.5076414942741394, 'gis', 0), ('mito-ds/monorepo', 0.5070230960845947, 'jupyter', 0), ('adafruit/circuitpython', 0.506452739238739, 'util', 0), ('dlt-hub/dlt', 0.5059615969657898, 'data', 0), ('giswqs/geemap', 0.505904495716095, 'gis', 0), ('jaidedai/easyocr', 0.5057637095451355, 'data', 0), ('gradio-app/gradio', 0.5046327710151672, 'viz', 0), ('holoviz/panel', 0.504224419593811, 'viz', 0), ('ta-lib/ta-lib-python', 0.5035238862037659, 'finance', 0), ('marshmallow-code/marshmallow', 0.503285825252533, 'util', 0), ('man-group/dtale', 0.5025433897972107, 'viz', 0), ('tebelorg/rpa-python', 0.502187967300415, 'util', 0), ('cython/cython', 0.5013166666030884, 'util', 0)]

util

https://github.com/fabiocaccamo/python-benedict

[]

[]

[]

fabiocaccamo/python-benedict

python-benedict

Python

:blue_book: dict subclass with keylist/keypath support, built-in I/O operations (base64, csv, html, ini, json, pickle, plist, query-string, toml, xls, xml, yaml), s3 support and many utilities.

fabiocaccamo

2024-01-14

2019-05-17

📘 dict subclass with keylist/keypath support, built-in I/O operations (base64, csv, html, ini, json, pickle, plist, query-string, toml, xls, xml, yaml), s3 support and many utilities.

['base64', 'csv', 'decode', 'dict', 'dictionary', 'encode', 'filter', 'flatten', 'json', 'keypath', 'pickle', 'plist', 'query-string', 'subset', 'toml', 'traverse', 'xls', 'xml', 'yaml']

['base64', 'csv', 'decode', 'dict', 'dictionary', 'encode', 'filter', 'flatten', 'json', 'keypath', 'pickle', 'plist', 'query-string', 'subset', 'toml', 'traverse', 'xls', 'xml', 'yaml']

2024-01-08

[('python-odin/odin', 0.5445603728294373, 'util', 4), ('konradhalas/dacite', 0.5441532731056213, 'util', 0), ('marshmallow-code/marshmallow', 0.5224064588546753, 'util', 0), ('yukinarit/pyserde', 0.5148563981056213, 'util', 3)]

term

https://github.com/tmbo/questionary

['cli']

[]

[]

tmbo/questionary

questionary

Python

Python library to build pretty command line user prompts ✨Easy to use multi-select lists, confirmations, free text prompts ...

tmbo

2024-01-13

2018-12-01

Python library to build pretty command line user prompts ✨Easy to use multi-select lists, confirmations, free text prompts ...

[]

['cli']

2024-01-12

[('jquast/blessed', 0.6140781044960022, 'term', 1), ('pexpect/pexpect', 0.6019250750541687, 'util', 0), ('tiangolo/typer', 0.5755541324615479, 'term', 1), ('urwid/urwid', 0.5709437727928162, 'term', 0), ('google/python-fire', 0.5444633960723877, 'term', 1), ('bigscience-workshop/promptsource', 0.5423410534858704, 'nlp', 0), ('hoffstadt/dearpygui', 0.5394479632377625, 'gui', 0), ('promptslab/promptify', 0.5267842411994934, 'nlp', 0), ('xonsh/xonsh', 0.5194598436355591, 'util', 1)]

data

https://github.com/pytables/pytables

[]

[]

[]

pytables/pytables

PyTables

Python

http://www.pytables.org

A Python package to manage extremely large amounts of data

pytables

2024-01-12

2011-06-03

https://avatars.githubusercontent.com/u/828302?v=4

A Python package to manage extremely large amounts of data

[]

[]

2024-01-12

[('eleutherai/pyfra', 0.6154819130897522, 'ml', 0), ('erotemic/ubelt', 0.615244448184967, 'util', 0), ('vaexio/vaex', 0.6015515923500061, 'perf', 0), ('pyston/pyston', 0.5999751091003418, 'util', 0), ('blaze/blaze', 0.5941234230995178, 'pandas', 0), ('ibis-project/ibis', 0.5871632695198059, 'data', 0), ('pympler/pympler', 0.5767551064491272, 'perf', 0), ('kagisearch/vectordb', 0.5746976137161255, 'data', 0), ('pypa/hatch', 0.5594925880432129, 'util', 0), ('fastai/fastcore', 0.5568447113037109, 'util', 0), ('cython/cython', 0.549433171749115, 'util', 0), ('saulpw/visidata', 0.5493369102478027, 'term', 0), ('datapane/datapane', 0.5492084622383118, 'viz', 0), ('pypy/pypy', 0.547862708568573, 'util', 0), ('indygreg/pyoxidizer', 0.5478392839431763, 'util', 0), ('pyjanitor-devs/pyjanitor', 0.5451061129570007, 'pandas', 0), ('holoviz/panel', 0.544653058052063, 'viz', 0), ('mitsuhiko/rye', 0.54390549659729, 'util', 0), ('koaning/clumper', 0.5409725904464722, 'util', 0), ('dddomodossola/remi', 0.5401478409767151, 'gui', 0), ('pytoolz/toolz', 0.5390780568122864, 'util', 0), ('dgilland/cacheout', 0.5385268926620483, 'perf', 0), ('grantjenks/python-diskcache', 0.5363883376121521, 'util', 0), ('pandas-dev/pandas', 0.5361529588699341, 'pandas', 0), ('dlt-hub/dlt', 0.5339342355728149, 'data', 0), ('pyinfra-dev/pyinfra', 0.5320051312446594, 'util', 0), ('sqlalchemy/sqlalchemy', 0.531848132610321, 'data', 0), ('airbnb/omniduct', 0.5307878851890564, 'data', 0), ('malloydata/malloy-py', 0.5297611951828003, 'data', 0), ('lk-geimfari/mimesis', 0.5296199321746826, 'data', 0), ('pythonspeed/filprofiler', 0.5271565914154053, 'profiling', 0), ('python-cachier/cachier', 0.5254138112068176, 'perf', 0), ('willmcgugan/textual', 0.5240064263343811, 'term', 0), ('tiangolo/sqlmodel', 0.5233675241470337, 'data', 0), ('pyodide/micropip', 0.5223343968391418, 'util', 0), ('amzn/ion-python', 0.5214452147483826, 'data', 0), ('googleapis/python-bigquery', 0.5208421349525452, 'data', 0), ('pyqtgraph/pyqtgraph', 0.5200861692428589, 'viz', 0), ('eventual-inc/daft', 0.5193186402320862, 'pandas', 0), ('python-poetry/poetry', 0.517038106918335, 'util', 0), ('jmcarpenter2/swifter', 0.5137337446212769, 'pandas', 0), ('modin-project/modin', 0.5136765837669373, 'perf', 0), ('micropython/micropython', 0.5130558013916016, 'util', 0), ('contextlab/hypertools', 0.5119327306747437, 'ml', 0), ('falconry/falcon', 0.5114437937736511, 'web', 0), ('pythonprofilers/memory_profiler', 0.5096424221992493, 'profiling', 0), ('kestra-io/kestra', 0.5085448026657104, 'ml-ops', 0), ('imageio/imageio', 0.5082108378410339, 'util', 0), ('wesm/pydata-book', 0.5043383836746216, 'study', 0), ('pyeve/cerberus', 0.5037830471992493, 'data', 0), ('joblib/joblib', 0.5035998225212097, 'util', 0), ('pynamodb/pynamodb', 0.5032399892807007, 'data', 0), ('merantix-momentum/squirrel-core', 0.5015002489089966, 'ml', 0)]

pandas

https://github.com/pyjanitor-devs/pyjanitor

[]

[]

[]

pyjanitor-devs/pyjanitor

pyjanitor

Python

https://pyjanitor-devs.github.io/pyjanitor

Clean APIs for data cleaning. Python implementation of R package Janitor

pyjanitor-devs

2024-01-12

2018-03-04

https://avatars.githubusercontent.com/u/53411673?v=4

Clean APIs for data cleaning. Python implementation of R package Janitor

['cleaning-data', 'data', 'data-engineering', 'dataframe', 'pandas', 'pydata']

['cleaning-data', 'data', 'data-engineering', 'dataframe', 'pandas', 'pydata']

2024-01-13

[('hi-primus/optimus', 0.6122784614562988, 'ml-ops', 0), ('pandas-dev/pandas', 0.5571015477180481, 'pandas', 2), ('pytables/pytables', 0.5451061129570007, 'data', 0), ('python-odin/odin', 0.51002436876297, 'util', 0)]

perf

https://github.com/eventlet/eventlet

[]

[]

[]

eventlet/eventlet

eventlet

Python

https://eventlet.net

Concurrent networking library for Python

eventlet

2024-01-09

2012-12-11

https://avatars.githubusercontent.com/u/3017635?v=4

Concurrent networking library for Python

['c10k', 'concurrency', 'greenlet', 'network', 'production-ready']

['c10k', 'concurrency', 'greenlet', 'network', 'production-ready']

2024-01-11

[('python-trio/trio', 0.6357116103172302, 'perf', 0), ('agronholm/anyio', 0.5704464912414551, 'perf', 0), ('samuelcolvin/arq', 0.5532472729682922, 'data', 1), ('ipython/ipyparallel', 0.5408223271369934, 'perf', 0), ('dask/dask', 0.5214966535568237, 'perf', 0), ('backtick-se/cowait', 0.519990086555481, 'util', 0), ('dddomodossola/remi', 0.5185775756835938, 'gui', 0), ('joblib/joblib', 0.5059096217155457, 'util', 0), ('sumerc/yappi', 0.5047085285186768, 'profiling', 1)]

util

https://github.com/jaraco/keyring

['security', 'keyring']

[]

[]

jaraco/keyring

keyring

Python

jaraco

2024-01-13

2015-02-24

jaraco/keyring

[]

['keyring', 'security']

2024-01-07

[]

gis

https://github.com/sentinel-hub/eo-learn

[]

[]

[]

sentinel-hub/eo-learn

eo-learn

Python

https://eo-learn.readthedocs.io/en/latest/

Earth observation processing framework for machine learning in Python

sentinel-hub

2024-01-10

2018-05-31

https://avatars.githubusercontent.com/u/31830596?v=4

Earth observation processing framework for machine learning in Python

['eo-data', 'eo-research', 'machine-learning', 'python-package']

['eo-data', 'eo-research', 'machine-learning', 'python-package']

2024-01-10

[('pytroll/satpy', 0.6639524102210999, 'gis', 0), ('scitools/iris', 0.623789370059967, 'gis', 0), ('opengeos/earthformer', 0.5971592664718628, 'gis', 0), ('scikit-learn/scikit-learn', 0.581174910068512, 'ml', 1), ('radiantearth/radiant-mlhub', 0.5761727094650269, 'gis', 1), ('weecology/deepforest', 0.5667561888694763, 'gis', 0), ('pycaret/pycaret', 0.5666598677635193, 'ml', 1), ('giswqs/geemap', 0.5640432834625244, 'gis', 0), ('cloudsen12/easystac', 0.5572369694709778, 'gis', 0), ('rasbt/mlxtend', 0.5460903644561768, 'ml', 1), ('fatiando/verde', 0.5445219874382019, 'gis', 1), ('opengeos/segment-geospatial', 0.5391361117362976, 'gis', 1), ('earthlab/earthpy', 0.5327595472335815, 'gis', 0), ('scikit-learn-contrib/metric-learn', 0.5314062237739563, 'ml', 1), ('featurelabs/featuretools', 0.5274897813796997, 'ml', 1), ('online-ml/river', 0.5141457915306091, 'ml', 1), ('gradio-app/gradio', 0.5121914744377136, 'viz', 1), ('remotesensinglab/raster4ml', 0.5058966279029846, 'gis', 1), ('developmentseed/label-maker', 0.5026171803474426, 'gis', 0)]

llm

https://github.com/ibm/dromedary

['language-model']

[]

[]

ibm/dromedary

Dromedary

Python

Dromedary: towards helpful, ethical and reliable LLMs.

ibm

2024-01-12

2023-05-03

https://avatars.githubusercontent.com/u/1459110?v=4

Dromedary: towards helpful, ethical and reliable LLMs.

[]

['language-model']

2023-10-26

[('jina-ai/thinkgpt', 0.6295039057731628, 'llm', 1), ('eugeneyan/open-llms', 0.6077130436897278, 'study', 0), ('mooler0410/llmspracticalguide', 0.5917999148368835, 'study', 0), ('night-chen/toolqa', 0.5732406377792358, 'llm', 0), ('hwchase17/langchain', 0.5653164386749268, 'llm', 1), ('citadel-ai/langcheck', 0.5524911880493164, 'llm', 1), ('young-geng/easylm', 0.5381739139556885, 'llm', 1), ('confident-ai/deepeval', 0.5251967906951904, 'testing', 1), ('salesforce/xgen', 0.5233420729637146, 'llm', 1), ('agenta-ai/agenta', 0.5226309895515442, 'llm', 0), ('rlancemartin/auto-evaluator', 0.521746814250946, 'llm', 0), ('aiwaves-cn/agents', 0.5198720097541809, 'nlp', 1), ('salesforce/codet5', 0.5191128253936768, 'nlp', 1), ('explosion/spacy-llm', 0.5127615928649902, 'llm', 0), ('deep-diver/pingpong', 0.510129988193512, 'llm', 0), ('tigerlab-ai/tiger', 0.5087694525718689, 'llm', 0), ('nomic-ai/gpt4all', 0.5083171129226685, 'llm', 1), ('artidoro/qlora', 0.5037577748298645, 'llm', 1), ('thudm/chatglm2-6b', 0.50322425365448, 'llm', 0), ('epfllm/meditron', 0.5021689534187317, 'llm', 1)]

util

https://github.com/aio-libs/aiobotocore

[]

[]

[]

aio-libs/aiobotocore

aiobotocore

Python

https://aiobotocore.rtfd.io

asyncio support for botocore library using aiohttp

aio-libs

2024-01-08

2015-05-31

https://avatars.githubusercontent.com/u/7049303?v=4

asyncio support for botocore library using aiohttp

['aiohttp', 'asyncio', 'aws', 'aws-sdk', 'botocore', 'cloud', 'cloud-management']

['aiohttp', 'asyncio', 'aws', 'aws-sdk', 'botocore', 'cloud', 'cloud-management']

2023-12-13

[('samuelcolvin/aioaws', 0.6990792155265808, 'data', 2), ('terrycain/aioboto3', 0.6956399083137512, 'util', 1), ('aio-libs/aiohttp', 0.6436625719070435, 'web', 2), ('geeogi/async-python-lambda-template', 0.6242508292198181, 'template', 0), ('timofurrer/awesome-asyncio', 0.5803163647651672, 'study', 1), ('jordaneremieff/mangum', 0.546834409236908, 'web', 2), ('aio-libs/aiokafka', 0.5398765802383423, 'data', 1), ('encode/httpx', 0.536460280418396, 'web', 1), ('pallets/quart', 0.5356045961380005, 'web', 1), ('pytest-dev/pytest-asyncio', 0.5174840688705444, 'testing', 1), ('samuelcolvin/arq', 0.5054838061332703, 'data', 1)]

nlp

https://github.com/abertsch72/unlimiformer

['transformers', 'attention-mechanism']

[]

[]

abertsch72/unlimiformer

unlimiformer

Python

Public repo for the NeurIPS 2023 paper "Unlimiformer: Long-Range Transformers with Unlimited Length Input"

abertsch72

2024-01-12

2023-05-03

Public repo for the NeurIPS 2023 paper "Unlimiformer: Long-Range Transformers with Unlimited Length Input"

[]

['attention-mechanism', 'transformers']

2023-10-03

[('facebookresearch/xformers', 0.5475772023200989, 'ml', 1), ('microsoft/focal-transformer', 0.5153154134750366, 'ml', 0)]

diffusion

https://github.com/chenyangqiqi/fatezero

[]

[]

[]

chenyangqiqi/fatezero

FateZero

Jupyter Notebook

http://fate-zero-edit.github.io/

[ICCV 2023 Oral] "FateZero: Fusing Attentions for Zero-shot Text-based Video Editing"

chenyangqiqi

2024-01-12

2023-03-16

[ICCV 2023 Oral] "FateZero: Fusing Attentions for Zero-shot Text-based Video Editing"

['image-editing', 'stable-diffusion', 'text-driven-editing', 'video-editing', 'video-style-transfer']

['image-editing', 'stable-diffusion', 'text-driven-editing', 'video-editing', 'video-style-transfer']

2023-08-14

[('thudm/cogvideo', 0.6052513718605042, 'ml', 0), ('williamyang1991/vtoonify', 0.5721680521965027, 'ml-dl', 1), ('zulko/moviepy', 0.5514541268348694, 'util', 1), ('nateraw/stable-diffusion-videos', 0.543769896030426, 'diffusion', 1), ('openai/glide-text2im', 0.5413234233856201, 'diffusion', 0), ('open-mmlab/mmediting', 0.5141303539276123, 'ml', 1)]

sim

https://github.com/sail-sg/envpool

[]

[]

[]

sail-sg/envpool

envpool

C++

https://envpool.readthedocs.io

C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.

sail-sg

2024-01-12

2021-10-20

https://avatars.githubusercontent.com/u/85740051?v=4

C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.

['atari-games', 'box2d', 'cpp17', 'dm-control', 'dm-env', 'gym', 'high-performance-computing', 'lock-free-queue', 'mujoco', 'parallel-processing', 'pybind11', 'reinforcement-learning', 'reinforcement-learning-environments', 'robotics', 'threadpool', 'vizdoom']

['atari-games', 'box2d', 'cpp17', 'dm-control', 'dm-env', 'gym', 'high-performance-computing', 'lock-free-queue', 'mujoco', 'parallel-processing', 'pybind11', 'reinforcement-learning', 'reinforcement-learning-environments', 'robotics', 'threadpool', 'vizdoom']

2023-10-30

[('ray-project/ray', 0.529890775680542, 'ml-ops', 1), ('exaloop/codon', 0.5291399359703064, 'perf', 0), ('panda3d/panda3d', 0.5131605267524719, 'gamedev', 0), ('denys88/rl_games', 0.5019115805625916, 'ml-rl', 1), ('salesforce/warp-drive', 0.5001153945922852, 'ml-rl', 1)]

jupyter

https://github.com/vizzuhq/ipyvizzu

[]

[]

[]

vizzuhq/ipyvizzu

ipyvizzu

Python

https://ipyvizzu.vizzuhq.com

Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax.

vizzuhq

2024-01-13

2022-01-05

https://avatars.githubusercontent.com/u/79846421?v=4

Build animated charts in Jupyter Notebook and similar environments with a simple Python syntax.

['animation', 'chart', 'charting', 'charts', 'data-visualization', 'dataviz', 'graphing', 'graphs', 'ipython', 'jupyter', 'jupyter-notebook', 'plotting', 'storytelling', 'vizzu']

['animation', 'chart', 'charting', 'charts', 'data-visualization', 'dataviz', 'graphing', 'graphs', 'ipython', 'jupyter', 'jupyter-notebook', 'plotting', 'storytelling', 'vizzu']

2024-01-09

[('plotly/plotly.py', 0.7362504601478577, 'viz', 1), ('maartenbreddels/ipyvolume', 0.7133920788764954, 'jupyter', 4), ('bokeh/bokeh', 0.6746152639389038, 'viz', 2), ('jupyter-widgets/ipywidgets', 0.6638791561126709, 'jupyter', 0), ('voila-dashboards/voila', 0.6425187587738037, 'jupyter', 2), ('holoviz/panel', 0.6363608837127686, 'viz', 2), ('cuemacro/chartpy', 0.6341903209686279, 'viz', 2), ('opengeos/leafmap', 0.6331526637077332, 'gis', 3), ('jupyter/notebook', 0.6270691156387329, 'jupyter', 2), ('jupyterlab/jupyterlab-desktop', 0.6113208532333374, 'jupyter', 2), ('jakevdp/pythondatasciencehandbook', 0.6107296943664551, 'study', 1), ('jupyter-widgets/ipyleaflet', 0.6106564402580261, 'gis', 1), ('plotly/dash', 0.6095137596130371, 'viz', 3), ('man-group/dtale', 0.6090724468231201, 'viz', 3), ('quantopian/qgrid', 0.608697235584259, 'jupyter', 0), ('ipython/ipyparallel', 0.604579508304596, 'perf', 1), ('federicoceratto/dashing', 0.5991188883781433, 'term', 1), ('kanaries/pygwalker', 0.5989693403244019, 'pandas', 0), ('mwouts/jupytext', 0.5986511707305908, 'jupyter', 1), ('jupyterlab/jupyterlab', 0.5963035821914673, 'jupyter', 1), ('aws/graph-notebook', 0.5957169532775879, 'jupyter', 2), ('has2k1/plotnine', 0.585931122303009, 'viz', 1), ('matplotlib/matplotlib', 0.5835548043251038, 'viz', 2), ('tkrabel/bamboolib', 0.5739924311637878, 'pandas', 1), ('holoviz/holoviz', 0.5736362338066101, 'viz', 0), ('xiaohk/stickyland', 0.5726215243339539, 'jupyter', 1), ('jupyter/nbformat', 0.5726070404052734, 'jupyter', 0), ('koaning/drawdata', 0.5688337683677673, 'jupyter', 1), ('lux-org/lux', 0.5684981346130371, 'viz', 1), ('cohere-ai/notebooks', 0.5615155100822449, 'llm', 0), ('altair-viz/altair', 0.5488370656967163, 'viz', 0), ('westhealth/pyvis', 0.5483621954917908, 'graph', 0), ('giswqs/mapwidget', 0.5461418032646179, 'gis', 1), ('brandtbucher/specialist', 0.5436729192733765, 'perf', 0), ('rapidsai/jupyterlab-nvdashboard', 0.5411252975463867, 'jupyter', 0), ('jupyter-lsp/jupyterlab-lsp', 0.539960503578186, 'jupyter', 3), ('wesm/pydata-book', 0.5378664135932922, 'study', 0), ('jalammar/ecco', 0.5353596806526184, 'ml-interpretability', 0), ('pygraphviz/pygraphviz', 0.5348131060600281, 'viz', 0), ('mwaskom/seaborn', 0.5341234803199768, 'viz', 1), ('jupyterlite/jupyterlite', 0.5260722041130066, 'jupyter', 1), ('r0x0r/pywebview', 0.5254994034767151, 'gui', 0), ('datapane/datapane', 0.5247305035591125, 'viz', 1), ('giswqs/geemap', 0.5243290066719055, 'gis', 3), ('bloomberg/ipydatagrid', 0.522794783115387, 'jupyter', 0), ('holoviz/hvplot', 0.5226277112960815, 'pandas', 1), ('jmcnamara/xlsxwriter', 0.5122716426849365, 'data', 1), ('holoviz/geoviews', 0.5115540623664856, 'gis', 1), ('jupyter/nbviewer', 0.5107673406600952, 'jupyter', 2), ('ipython/ipykernel', 0.5079095363616943, 'util', 3), ('residentmario/geoplot', 0.5058284997940063, 'gis', 0), ('pyqtgraph/pyqtgraph', 0.5050925612449646, 'viz', 0), ('enthought/mayavi', 0.501654863357544, 'viz', 0), ('nschloe/perfplot', 0.5008931756019592, 'perf', 0), ('graphistry/pygraphistry', 0.5005484819412231, 'data', 1)]

util

https://github.com/pypa/setuptools_scm

['hg', 'git', 'sdist', 'versioning']

[]

[]

pypa/setuptools_scm

setuptools_scm

Python

https://setuptools-scm.readthedocs.io/en/latest/

the blessed package to manage your versions by scm tags

pypa

2024-01-12

2015-07-01

https://avatars.githubusercontent.com/u/647025?v=4

the blessed package to manage your versions by scm tags

['metadata', 'packaging', 'version-control']

['git', 'hg', 'metadata', 'packaging', 'sdist', 'version-control', 'versioning']

2024-01-08

[('mtkennerly/dunamai', 0.6616849303245544, 'util', 2), ('callowayproject/bump-my-version', 0.6197443604469299, 'util', 1), ('mtkennerly/poetry-dynamic-versioning', 0.6003091931343079, 'util', 2), ('spack/spack', 0.5813215970993042, 'util', 0), ('python-versioneer/python-versioneer', 0.5380630493164062, 'util', 0), ('conda/conda', 0.532427966594696, 'util', 1), ('pomponchik/instld', 0.5312846302986145, 'util', 0), ('pypa/hatch', 0.5210332274436951, 'util', 2), ('pypa/gh-action-pypi-publish', 0.5103867650032043, 'util', 0)]

util

https://github.com/fsspec/s3fs

[]

[]

[]

fsspec/s3fs

s3fs

Python

http://s3fs.readthedocs.io/en/latest/

S3 Filesystem

fsspec

2024-01-12

2016-03-16

https://avatars.githubusercontent.com/u/92825505?v=4

S3 Filesystem

[]

[]

2023-12-16

[]

gis

https://github.com/developmentseed/titiler

[]

[]

[]

developmentseed/titiler

titiler

Python

https://developmentseed.org/titiler/

Build your own Raster dynamic map tile services

developmentseed

2024-01-12

2019-06-28

https://avatars.githubusercontent.com/u/92384?v=4

Build your own Raster dynamic map tile services

['aws-cdk', 'aws-lambda', 'cog', 'cogeotiff', 'dynamic', 'fastapi', 'gdal', 'map-tile-server', 'map-tiles', 'mosaicjson', 'raster', 'rasterio', 'rest', 'server', 'stac', 'tile']

['aws-cdk', 'aws-lambda', 'cog', 'cogeotiff', 'dynamic', 'fastapi', 'gdal', 'map-tile-server', 'map-tiles', 'mosaicjson', 'raster', 'rasterio', 'rest', 'server', 'stac', 'tile']

2024-01-10

[('jordaneremieff/mangum', 0.5069487690925598, 'web', 2), ('localstack/localstack', 0.5016547441482544, 'util', 0)]

ml-ops

https://github.com/kedro-org/kedro-viz

[]

[]

[]

kedro-org/kedro-viz

kedro-viz

JavaScript

https://demo.kedro.org

Visualise your Kedro data and machine-learning pipelines and track your experiments.

kedro-org

2024-01-14

2019-05-09

https://avatars.githubusercontent.com/u/93382166?v=4

Visualise your Kedro data and machine-learning pipelines and track your experiments.

['data-visualization', 'experiment-tracking', 'kedro', 'kedro-plugin', 'react']

['data-visualization', 'experiment-tracking', 'kedro', 'kedro-plugin', 'react']

2024-01-12

[('kedro-org/kedro', 0.7322895526885986, 'ml-ops', 2), ('getindata/kedro-kubeflow', 0.578177273273468, 'ml-ops', 2), ('wandb/client', 0.5440914034843445, 'ml', 0), ('kubeflow-kale/kale', 0.5434872508049011, 'ml-ops', 0), ('aimhubio/aim', 0.5116142630577087, 'ml-ops', 2)]

nlp

https://github.com/intellabs/fastrag

['retrieval-augmentation', 'knowledge-graph', 'haystack']

[]

[]

intellabs/fastrag

fastRAG

Python

Efficient Retrieval Augmentation and Generation Framework

intellabs

2024-01-14

2023-01-23

https://avatars.githubusercontent.com/u/1492758?v=4

Efficient Retrieval Augmentation and Generation Framework

['benchmark', 'colbert', 'diffusion', 'generative-ai', 'information-retrieval', 'knowledge-graph', 'llm', 'multi-modal', 'nlp', 'question-answering', 'semantic-search', 'sentence-transformers', 'summarization', 'transformers']

['benchmark', 'colbert', 'diffusion', 'generative-ai', 'haystack', 'information-retrieval', 'knowledge-graph', 'llm', 'multi-modal', 'nlp', 'question-answering', 'retrieval-augmentation', 'semantic-search', 'sentence-transformers', 'summarization', 'transformers']

2024-01-11

[('llmware-ai/llmware', 0.669150710105896, 'llm', 6), ('ai21labs/in-context-ralm', 0.6507914066314697, 'llm', 1), ('paddlepaddle/rocketqa', 0.6380553841590881, 'nlp', 3), ('paddlepaddle/paddlenlp', 0.6250779628753662, 'llm', 4), ('neuml/txtai', 0.6202690005302429, 'nlp', 5), ('muennighoff/sgpt', 0.6058968305587769, 'llm', 2), ('deepset-ai/haystack', 0.5783014297485352, 'llm', 8), ('thilinarajapakse/simpletransformers', 0.5657897591590881, 'nlp', 2), ('rcgai/simplyretrieve', 0.5627588629722595, 'llm', 2), ('jina-ai/finetuner', 0.5626152157783508, 'ml', 0), ('jina-ai/clip-as-service', 0.561098039150238, 'nlp', 0), ('srush/minichain', 0.5593423843383789, 'llm', 2), ('facebookresearch/dpr-scale', 0.5437898635864258, 'nlp', 0), ('eugeneyan/obsidian-copilot', 0.5370295643806458, 'llm', 2), ('huggingface/text-generation-inference', 0.5351554155349731, 'llm', 1), ('deepset-ai/farm', 0.5346118211746216, 'nlp', 2), ('ddangelov/top2vec', 0.527250349521637, 'nlp', 2), ('infinitylogesh/mutate', 0.526527464389801, 'nlp', 0), ('alibaba/easynlp', 0.5131124258041382, 'nlp', 2), ('luohongyin/sail', 0.5123240947723389, 'llm', 0), ('makcedward/nlpaug', 0.5120058655738831, 'nlp', 1), ('extreme-bert/extreme-bert', 0.5088297128677368, 'llm', 1), ('qdrant/fastembed', 0.5029743909835815, 'ml', 0), ('docarray/docarray', 0.501563549041748, 'data', 2), ('ukplab/sentence-transformers', 0.5005632042884827, 'nlp', 2)]

data

https://github.com/kagisearch/vectordb

['vectordb']

[]

[]

kagisearch/vectordb

vectordb

Python

https://vectordb.com

A minimal Python package for storing and retrieving text using chunking, embeddings, and vector search.

kagisearch

2024-01-11

2023-04-25

https://avatars.githubusercontent.com/u/92134518?v=4

A minimal Python package for storing and retrieving text using chunking, embeddings, and vector search.

['ai', 'artificial-intelligence', 'llm', 'llms', 'machine-learning']

['ai', 'artificial-intelligence', 'llm', 'llms', 'machine-learning', 'vectordb']

2024-01-11

[('jina-ai/vectordb', 0.6794906258583069, 'data', 1), ('qdrant/fastembed', 0.6594275832176208, 'ml', 1), ('chroma-core/chroma', 0.6572227478027344, 'data', 2), ('pytables/pytables', 0.5746976137161255, 'data', 0), ('activeloopai/deeplake', 0.5621834397315979, 'ml-ops', 3), ('plasticityai/magnitude', 0.5367014408111572, 'nlp', 1), ('openeventdata/mordecai', 0.5354642868041992, 'gis', 0), ('neuml/txtai', 0.529229998588562, 'nlp', 2), ('castorini/pyserini', 0.5248305201530457, 'ml', 0), ('lancedb/lancedb', 0.5210687518119812, 'data', 1), ('weaviate/demo-text2vec-openai', 0.5153085589408875, 'util', 0), ('pemistahl/lingua-py', 0.509565532207489, 'nlp', 0), ('paddlepaddle/paddlenlp', 0.5087656378746033, 'llm', 1), ('explosion/spacy', 0.506615936756134, 'nlp', 3), ('llmware-ai/llmware', 0.5052314400672913, 'llm', 2), ('minimaxir/aitextgen', 0.5047615766525269, 'llm', 0), ('minimaxir/textgenrnn', 0.5044152140617371, 'nlp', 0)]

util

https://github.com/qdrant/qdrant-client

[]

[]

[]

qdrant/qdrant-client

qdrant-client

Python

https://qdrant.tech

Python client for Qdrant vector search engine

qdrant

2024-01-14

2021-02-09

https://avatars.githubusercontent.com/u/73504361?v=4

Python client for Qdrant vector search engine

['qdrant', 'vector-database', 'vector-search', 'vector-search-engine']

['qdrant', 'vector-database', 'vector-search', 'vector-search-engine']

2024-01-11

[('qdrant/qdrant-haystack', 0.6654171943664551, 'data', 0), ('pinecone-io/pinecone-python-client', 0.6546476483345032, 'data', 1), ('weaviate/weaviate-python-client', 0.5938428640365601, 'util', 1), ('qdrant/vector-db-benchmark', 0.5792778134346008, 'perf', 3), ('typesense/typesense-python', 0.5577874779701233, 'data', 0), ('accenture/cymple', 0.5485904812812805, 'data', 0), ('jina-ai/vectordb', 0.5459500551223755, 'data', 2), ('goldmansachs/gs-quant', 0.5404823422431946, 'finance', 0), ('meilisearch/meilisearch-python', 0.538914680480957, 'data', 0), ('googleapis/google-api-python-client', 0.5371494293212891, 'util', 0), ('qdrant/fastembed', 0.5288180708885193, 'ml', 1), ('gbeced/pyalgotrade', 0.5113593935966492, 'finance', 0), ('qdrant/qdrant', 0.5091877579689026, 'data', 3), ('castorini/pyserini', 0.5034437775611877, 'ml', 0), ('hydrosquall/tiingo-python', 0.501908540725708, 'finance', 0), ('nv7-github/googlesearch', 0.5012821555137634, 'util', 0)]

llm

https://github.com/langchain-ai/langsmith-cookbook

['cookbook', 'evaluation', 'language-model']

LangSmith is a platform for building production-grade LLM applications.

[]

[]

langchain-ai/langsmith-cookbook

langsmith-cookbook

Jupyter Notebook

https://langsmith-cookbook.vercel.app

langchain-ai

2024-01-13

2023-08-01

https://avatars.githubusercontent.com/u/126733545?v=4

LangSmith is a platform for building production-grade LLM applications.

[]

['cookbook', 'evaluation', 'language-model']

2023-12-20

[('langchain-ai/langsmith-sdk', 0.6326169371604919, 'llm', 2), ('hwchase17/langchain', 0.5514335632324219, 'llm', 1), ('citadel-ai/langcheck', 0.5509293079376221, 'llm', 2), ('eugeneyan/open-llms', 0.5495509505271912, 'study', 0), ('hiyouga/llama-factory', 0.5422530174255371, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5422529578208923, 'llm', 1), ('alpha-vllm/llama2-accessory', 0.5349544286727905, 'llm', 0), ('agenta-ai/agenta', 0.5301238894462585, 'llm', 0), ('nat/openplayground', 0.5300737619400024, 'llm', 1), ('langchain-ai/langgraph', 0.5267937183380127, 'llm', 0), ('confident-ai/deepeval', 0.5237811803817749, 'testing', 2), ('lianjiatech/belle', 0.5184667110443115, 'llm', 0), ('ray-project/llm-applications', 0.515418529510498, 'llm', 0), ('alphasecio/langchain-examples', 0.5074201822280884, 'llm', 0)]

study

https://github.com/openai/spinningup

[]

[]

[]

openai/spinningup

spinningup