Unnamed: 0
int64 | category
string | githuburl
string | customtopics
string | customabout
string | customarxiv
string | custompypi
string | featured
float64 | links
string | description
string | _repopath
string | _reponame
string | _stars
int64 | _forks
int64 | _watches
int64 | _language
string | _homepage
string | _github_description
string | _organization
string | _updated_at
string | _created_at
string | _age_weeks
int64 | _stars_per_week
float64 | _avatar_url
string | _description
string | _github_topics
string | _topics
string | _last_commit_date
string | sim
string | _pop_contributor_count
int64 | _pop_contributor_orgs_len
float64 | _pop_contributor_orgs_error
float64 | _pop_commit_frequency
float64 | _pop_updated_issues_count
int64 | _pop_closed_issues_count
int64 | _pop_created_since_days
int64 | _pop_updated_since_days
int64 | _pop_recent_releases_count
int64 | _pop_recent_releases_estimated_tags
int64 | _pop_recent_releases_adjusted_count
int64 | _pop_issue_count
float64 | _pop_comment_count
float64 | _pop_comment_count_lookback_days
float64 | _pop_comment_frequency
float64 | _pop_score
int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,394 |
math
|
https://github.com/geomstats/geomstats
|
[]
| null |
[]
|
[]
| null | null | null |
geomstats/geomstats
|
geomstats
| 1,108 | 231 | 36 |
Jupyter Notebook
|
http://geomstats.ai
|
Computations and statistics on manifolds with geometric structures.
|
geomstats
|
2024-01-13
|
2017-10-25
| 326 | 3.38986 |
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)]
| 87 | 4 | null | 25.23 | 83 | 39 | 76 | 0 | 2 | 5 | 2 | 83 | 76 | 90 | 0.9 | 43 |
1,531 |
util
|
https://github.com/oracle/graalpython
|
['java', 'jvm']
| null |
[]
|
[]
| null | null | null |
oracle/graalpython
|
graalpython
| 1,059 | 98 | 57 |
Python
| null |
A Python 3 implementation built on GraalVM
|
oracle
|
2024-01-13
|
2018-04-17
| 302 | 3.506623 |
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)]
| 64 | 2 | null | 57.15 | 19 | 13 | 70 | 0 | 4 | 18 | 4 | 19 | 27 | 90 | 1.4 | 43 |
879 |
sim
|
https://github.com/pyscf/pyscf
|
[]
| null |
[]
|
[]
| null | null | null |
pyscf/pyscf
|
pyscf
| 1,051 | 569 | 78 |
Python
| null |
Python module for quantum chemistry
|
pyscf
|
2024-01-13
|
2014-05-02
| 508 | 2.066573 |
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)]
| 152 | 4 | null | 3.52 | 158 | 96 | 118 | 0 | 4 | 7 | 4 | 157 | 347 | 90 | 2.2 | 43 |
1,139 |
nlp
|
https://github.com/nomic-ai/nomic
|
[]
| null |
[]
|
[]
| null | null | null |
nomic-ai/nomic
|
nomic
| 833 | 121 | 24 |
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
| 79 | 10.449821 |
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)]
| 13 | 3 | null | 7.21 | 34 | 22 | 18 | 0 | 3 | 2 | 3 | 34 | 16 | 90 | 0.5 | 43 |
1,346 |
util
|
https://github.com/milvus-io/pymilvus
|
[]
| null |
[]
|
[]
| null | null | null |
milvus-io/pymilvus
|
pymilvus
| 785 | 329 | 16 |
Python
| null |
Python SDK for Milvus.
|
milvus-io
|
2024-01-11
|
2019-06-13
| 241 | 3.247636 |
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)]
| 95 | 2 | null | 4.33 | 149 | 110 | 56 | 0 | 22 | 12 | 22 | 149 | 245 | 90 | 1.6 | 43 |
1,853 |
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.
|
[]
|
[]
| null | null | null |
google-deepmind/materials_discovery
|
materials_discovery
| 689 | 148 | 35 |
Python
| null | null |
google-deepmind
|
2024-01-12
|
2023-11-28
| 9 | 76.555556 |
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)]
| 2 | 0 | null | 0.15 | 14 | 4 | 2 | 1 | 0 | 0 | 0 | 14 | 15 | 90 | 1.1 | 43 |
1,322 |
nlp
|
https://github.com/keras-team/keras-nlp
|
['keras', 'natural-language-processing']
| null |
[]
|
[]
| null | null | null |
keras-team/keras-nlp
|
keras-nlp
| 622 | 180 | 28 |
Python
| null |
Modular Natural Language Processing workflows with Keras
|
keras-team
|
2024-01-13
|
2020-05-28
| 191 | 3.244411 |
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)]
| 61 | 3 | null | 6.85 | 221 | 177 | 44 | 0 | 15 | 11 | 15 | 221 | 257 | 90 | 1.2 | 43 |
110 |
data
|
https://github.com/binux/pyspider
|
[]
| null |
[]
|
[]
| null | null | null |
binux/pyspider
|
pyspider
| 16,155 | 3,730 | 903 |
Python
|
http://docs.pyspider.org/
|
A Powerful Spider(Web Crawler) System in Python.
|
binux
|
2024-01-13
|
2014-02-21
| 518 | 31.152893 | null |
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)]
| 62 | 1 | null | 0 | 2 | 0 | 120 | 42 | 0 | 1 | 1 | 2 | 2 | 90 | 1 | 42 |
68 |
web
|
https://github.com/pyeve/eve
|
[]
| null |
[]
|
[]
| null | null | null |
pyeve/eve
|
eve
| 6,650 | 754 | 226 |
Python
|
https://python-eve.org
|
REST API framework designed for human beings
|
pyeve
|
2024-01-13
|
2012-10-22
| 588 | 11.306777 |
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)]
| 214 | 4 | null | 0.35 | 5 | 1 | 137 | 6 | 0 | 4 | 4 | 5 | 1 | 90 | 0.2 | 42 |
919 |
util
|
https://github.com/openai/point-e
|
[]
| null |
[]
|
[]
| null | null | null |
openai/point-e
|
point-e
| 6,106 | 726 | 216 |
Python
| null |
Point cloud diffusion for 3D model synthesis
|
openai
|
2024-01-13
|
2022-12-06
| 60 | 101.766667 |
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)]
| 2 | 0 | null | 0 | 6 | 2 | 13 | 13 | 0 | 0 | 0 | 6 | 2 | 90 | 0.3 | 42 |
575 |
ml
|
https://github.com/probml/pyprobml
|
[]
| null |
[]
|
[]
| null | null | null |
probml/pyprobml
|
pyprobml
| 6,092 | 1,455 | 187 |
Jupyter Notebook
| null |
Python code for "Probabilistic Machine learning" book by Kevin Murphy
|
probml
|
2024-01-13
|
2016-08-17
| 388 | 15.666422 |
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)]
| 66 | 8 | null | 0.38 | 0 | 0 | 90 | 1 | 0 | 0 | 0 | 0 | 0 | 90 | 0 | 42 |
1,685 |
util
|
https://github.com/hhatto/autopep8
|
[]
| null |
[]
|
[]
| null | null | null |
hhatto/autopep8
|
autopep8
| 4,468 | 296 | 73 |
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
| 682 | 6.543096 | null |
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)]
| 60 | 5 | null | 0.4 | 14 | 5 | 159 | 3 | 3 | 6 | 3 | 14 | 17 | 90 | 1.2 | 42 |
206 |
ml
|
https://github.com/lucidrains/deep-daze
|
[]
| null |
[]
|
[]
| null | null | null |
lucidrains/deep-daze
|
deep-daze
| 4,378 | 334 | 75 |
Python
| null |
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
| 158 | 27.658845 | null |
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)]
| 14 | 5 | null | 0 | 0 | 0 | 36 | 22 | 0 | 23 | 23 | 0 | 0 | 90 | 0 | 42 |
1,747 |
util
|
https://github.com/pyinvoke/invoke
|
['execution']
| null |
[]
|
[]
| null | null | null |
pyinvoke/invoke
|
invoke
| 4,163 | 384 | 93 |
Python
|
http://pyinvoke.org
|
Pythonic task management & command execution.
|
pyinvoke
|
2024-01-13
|
2012-02-29
| 621 | 6.694464 |
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)]
| 60 | 3 | null | 1.42 | 20 | 2 | 145 | 1 | 0 | 6 | 6 | 20 | 19 | 90 | 0.9 | 42 |
1,352 |
util
|
https://github.com/jorisschellekens/borb
|
[]
| null |
[]
|
[]
| null | null | null |
jorisschellekens/borb
|
borb
| 3,219 | 143 | 33 |
Python
|
https://borbpdf.com/
|
borb is a library for reading, creating and manipulating PDF files in python.
|
jorisschellekens
|
2024-01-13
|
2020-11-07
| 168 | 19.111959 | null |
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)]
| 1 | 0 | null | 0.17 | 13 | 9 | 39 | 1 | 10 | 21 | 10 | 13 | 25 | 90 | 1.9 | 42 |
260 |
time-series
|
https://github.com/salesforce/merlion
|
[]
| null |
[]
|
[]
| null | null | null |
salesforce/merlion
|
Merlion
| 3,181 | 280 | 52 |
Python
| null |
Merlion: A Machine Learning Framework for Time Series Intelligence
|
salesforce
|
2024-01-13
|
2021-07-28
| 130 | 24.308952 |
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)]
| 14 | 6 | null | 0.06 | 2 | 0 | 30 | 10 | 2 | 7 | 2 | 2 | 1 | 90 | 0.5 | 42 |
368 |
nlp
|
https://github.com/bytedance/lightseq
|
[]
| null |
[]
|
[]
| null | null | null |
bytedance/lightseq
|
lightseq
| 3,021 | 324 | 60 |
C++
| null |
LightSeq: A High Performance Library for Sequence Processing and Generation
|
bytedance
|
2024-01-12
|
2019-12-06
| 216 | 13.949208 |
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)]
| 17 | 7 | null | 0.46 | 7 | 0 | 50 | 8 | 0 | 3 | 3 | 7 | 5 | 90 | 0.7 | 42 |
1,493 |
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
|
[]
|
[]
| null | null | null |
mshumer/gpt-llm-trainer
|
gpt-llm-trainer
| 2,739 | 347 | 51 |
Jupyter Notebook
| null | null |
mshumer
|
2024-01-14
|
2023-08-09
| 24 | 110.189655 | null |
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)]
| 1 | 0 | null | 0.15 | 2 | 0 | 5 | 5 | 0 | 0 | 0 | 2 | 1 | 90 | 0.5 | 42 |
1,130 |
ml
|
https://github.com/scikit-learn-contrib/category_encoders
|
[]
| null |
[]
|
[]
| null | null | null |
scikit-learn-contrib/category_encoders
|
category_encoders
| 2,322 | 397 | 39 |
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
| 426 | 5.447051 |
https://avatars.githubusercontent.com/u/17349883?v=4
|
A library of sklearn compatible categorical variable encoders
|
[]
|
[]
|
2023-12-13
|
[]
| 70 | 2 | null | 0.96 | 6 | 4 | 99 | 1 | 4 | 4 | 4 | 6 | 16 | 90 | 2.7 | 42 |
296 |
util
|
https://github.com/pyparsing/pyparsing
|
[]
| null |
[]
|
[]
| null | null | null |
pyparsing/pyparsing
|
pyparsing
| 2,028 | 268 | 24 |
Python
| null |
Python library for creating PEG parsers
|
pyparsing
|
2024-01-13
|
2017-05-14
| 350 | 5.78956 |
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)]
| 62 | 4 | null | 1.73 | 24 | 10 | 81 | 2 | 5 | 9 | 5 | 24 | 31 | 90 | 1.3 | 42 |
1,799 |
gamedev
|
https://github.com/pokepetter/ursina
|
[]
| null |
[]
|
[]
| null | null | null |
pokepetter/ursina
|
ursina
| 2,006 | 318 | 48 |
Python
|
https://pokepetter.github.io/ursina/
|
A game engine powered by python and panda3d.
|
pokepetter
|
2024-01-12
|
2017-07-19
| 340 | 5.885163 | null |
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)]
| 41 | 3 | null | 8.52 | 58 | 40 | 79 | 0 | 0 | 0 | 0 | 58 | 62 | 90 | 1.1 | 42 |
309 |
data
|
https://github.com/graphistry/pygraphistry
|
[]
| null |
[]
|
[]
| null | null | null |
graphistry/pygraphistry
|
pygraphistry
| 1,983 | 202 | 49 |
Python
| null |
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
| 452 | 4.387168 |
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)]
| 40 | 3 | null | 7.06 | 34 | 19 | 105 | 1 | 0 | 21 | 21 | 34 | 25 | 90 | 0.7 | 42 |
975 |
pandas
|
https://github.com/fugue-project/fugue
|
['duckdb']
| null |
[]
|
[]
| null | null | null |
fugue-project/fugue
|
fugue
| 1,810 | 92 | 22 |
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
| 201 | 9.004975 |
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)]
| 22 | 1 | null | 0.98 | 22 | 18 | 46 | 0 | 30 | 34 | 30 | 22 | 19 | 90 | 0.9 | 42 |
1,749 |
util
|
https://github.com/mitmproxy/pdoc
|
[]
| null |
[]
|
[]
| null | null | null |
mitmproxy/pdoc
|
pdoc
| 1,715 | 233 | 27 |
Python
|
https://pdoc.dev
|
API Documentation for Python Projects
|
mitmproxy
|
2024-01-13
|
2013-08-04
| 547 | 3.133647 |
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)]
| 48 | 4 | null | 2.46 | 36 | 28 | 127 | 0 | 0 | 8 | 8 | 36 | 48 | 90 | 1.3 | 42 |
715 |
util
|
https://github.com/omry/omegaconf
|
[]
| null |
[]
|
[]
| null | null | null |
omry/omegaconf
|
omegaconf
| 1,700 | 91 | 18 |
Python
| null |
Flexible Python configuration system. The last one you will ever need.
|
omry
|
2024-01-13
|
2018-09-03
| 282 | 6.025316 | null |
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)]
| 31 | 6 | null | 0.42 | 21 | 11 | 65 | 2 | 0 | 3 | 3 | 21 | 35 | 90 | 1.7 | 42 |
317 |
gamedev
|
https://github.com/pythonarcade/arcade
|
[]
| null |
[]
|
[]
| 1 | null | null |
pythonarcade/arcade
|
arcade
| 1,589 | 302 | 58 |
Python
|
http://arcade.academy
|
Easy to use Python library for creating 2D arcade games.
|
pythonarcade
|
2024-01-12
|
2016-01-04
| 421 | 3.773066 |
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)]
| 150 | 5 | null | 6.87 | 53 | 37 | 98 | 0 | 1 | 16 | 1 | 53 | 26 | 90 | 0.5 | 42 |
1,696 |
util
|
https://github.com/mkdocstrings/mkdocstrings
|
[]
| null |
[]
|
[]
| null | null | null |
mkdocstrings/mkdocstrings
|
mkdocstrings
| 1,467 | 102 | 14 |
Python
|
https://mkdocstrings.github.io/
|
:blue_book: Automatic documentation from sources, for MkDocs.
|
mkdocstrings
|
2024-01-13
|
2019-12-09
| 216 | 6.787178 |
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)]
| 41 | 2 | null | 1.33 | 19 | 16 | 50 | 0 | 3 | 19 | 3 | 19 | 34 | 90 | 1.8 | 42 |
238 |
data
|
https://github.com/simonw/sqlite-utils
|
[]
| null |
[]
|
[]
| null | null | null |
simonw/sqlite-utils
|
sqlite-utils
| 1,386 | 101 | 21 |
Python
|
https://sqlite-utils.datasette.io
|
Python CLI utility and library for manipulating SQLite databases
|
simonw
|
2024-01-12
|
2018-07-14
| 289 | 4.788746 | null |
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)]
| 36 | 5 | null | 1.92 | 19 | 13 | 67 | 1 | 8 | 23 | 8 | 19 | 25 | 90 | 1.3 | 42 |
1,428 |
llm
|
https://github.com/cstankonrad/long_llama
|
['llama', 'language-model']
| null |
[]
|
[]
| null | null | null |
cstankonrad/long_llama
|
long_llama
| 1,381 | 88 | 26 |
Python
| null |
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
| 29 | 46.475962 | null |
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)]
| 3 | 1 | null | 1.17 | 6 | 4 | 6 | 2 | 0 | 0 | 0 | 6 | 3 | 90 | 0.5 | 42 |
449 |
util
|
https://github.com/imageio/imageio
|
[]
| null |
[]
|
[]
| null | null | null |
imageio/imageio
|
imageio
| 1,362 | 271 | 32 |
Python
|
https://imageio.readthedocs.io
|
Python library for reading and writing image data
|
imageio
|
2024-01-13
|
2013-05-04
| 560 | 2.430283 |
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)]
| 109 | 7 | null | 0.98 | 23 | 15 | 130 | 1 | 19 | 8 | 19 | 23 | 48 | 90 | 2.1 | 42 |
953 |
util
|
https://github.com/fabiocaccamo/python-benedict
|
[]
| null |
[]
|
[]
| null | null | null |
fabiocaccamo/python-benedict
|
python-benedict
| 1,341 | 47 | 12 |
Python
| null |
: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
| 245 | 5.460733 | null |
📘 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)]
| 7 | 2 | null | 3.37 | 32 | 31 | 57 | 0 | 10 | 14 | 10 | 32 | 45 | 90 | 1.4 | 42 |
1,642 |
term
|
https://github.com/tmbo/questionary
|
['cli']
| null |
[]
|
[]
| null | null | null |
tmbo/questionary
|
questionary
| 1,314 | 79 | 21 |
Python
| null |
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
| 269 | 4.876988 | null |
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)]
| 40 | 4 | null | 0.83 | 35 | 24 | 62 | 0 | 0 | 5 | 5 | 35 | 34 | 90 | 1 | 42 |
641 |
data
|
https://github.com/pytables/pytables
|
[]
| null |
[]
|
[]
| null | null | null |
pytables/pytables
|
PyTables
| 1,245 | 267 | 61 |
Python
|
http://www.pytables.org
|
A Python package to manage extremely large amounts of data
|
pytables
|
2024-01-12
|
2011-06-03
| 660 | 1.884732 |
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)]
| 127 | 5 | null | 7.06 | 42 | 23 | 154 | 0 | 3 | 4 | 3 | 42 | 81 | 90 | 1.9 | 42 |
416 |
pandas
|
https://github.com/pyjanitor-devs/pyjanitor
|
[]
| null |
[]
|
[]
| 1 | null | null |
pyjanitor-devs/pyjanitor
|
pyjanitor
| 1,224 | 164 | 18 |
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
| 308 | 3.970343 |
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)]
| 107 | 4 | null | 1.29 | 40 | 35 | 71 | 0 | 2 | 9 | 2 | 40 | 61 | 90 | 1.5 | 42 |
16 |
perf
|
https://github.com/eventlet/eventlet
|
[]
| null |
[]
|
[]
| null | null | null |
eventlet/eventlet
|
eventlet
| 1,223 | 371 | 64 |
Python
|
https://eventlet.net
|
Concurrent networking library for Python
|
eventlet
|
2024-01-09
|
2012-12-11
| 581 | 2.104991 |
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)]
| 191 | 2 | null | 0.75 | 114 | 71 | 135 | 0 | 0 | 5 | 5 | 114 | 360 | 90 | 3.2 | 42 |
1,672 |
util
|
https://github.com/jaraco/keyring
|
['security', 'keyring']
| null |
[]
|
[]
| null | null | null |
jaraco/keyring
|
keyring
| 1,149 | 148 | 19 |
Python
| null | null |
jaraco
|
2024-01-13
|
2015-02-24
| 466 | 2.465665 | null |
jaraco/keyring
|
[]
|
['keyring', 'security']
|
2024-01-07
|
[]
| 118 | 7 | null | 1.87 | 29 | 16 | 108 | 0 | 6 | 22 | 6 | 29 | 35 | 90 | 1.2 | 42 |
480 |
gis
|
https://github.com/sentinel-hub/eo-learn
|
[]
| null |
[]
|
[]
| null | null | null |
sentinel-hub/eo-learn
|
eo-learn
| 1,064 | 288 | 45 |
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
| 295 | 3.598068 |
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)]
| 53 | 5 | null | 4.42 | 28 | 28 | 68 | 0 | 7 | 8 | 7 | 28 | 20 | 90 | 0.7 | 42 |
1,369 |
llm
|
https://github.com/ibm/dromedary
|
['language-model']
| null |
[]
|
[]
| null | null | null |
ibm/dromedary
|
Dromedary
| 1,038 | 79 | 19 |
Python
| null |
Dromedary: towards helpful, ethical and reliable LLMs.
|
ibm
|
2024-01-12
|
2023-05-03
| 38 | 26.713235 |
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)]
| 4 | 2 | null | 1.58 | 6 | 3 | 8 | 3 | 0 | 0 | 0 | 6 | 13 | 90 | 2.2 | 42 |
1,145 |
util
|
https://github.com/aio-libs/aiobotocore
|
[]
| null |
[]
|
[]
| null | null | null |
aio-libs/aiobotocore
|
aiobotocore
| 1,034 | 175 | 26 |
Python
|
https://aiobotocore.rtfd.io
|
asyncio support for botocore library using aiohttp
|
aio-libs
|
2024-01-08
|
2015-05-31
| 452 | 2.286166 |
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)]
| 60 | 7 | null | 0.5 | 49 | 37 | 105 | 1 | 9 | 10 | 9 | 49 | 132 | 90 | 2.7 | 42 |
1,348 |
nlp
|
https://github.com/abertsch72/unlimiformer
|
['transformers', 'attention-mechanism']
| null |
[]
|
[]
| null | null | null |
abertsch72/unlimiformer
|
unlimiformer
| 1,004 | 70 | 23 |
Python
| null |
Public repo for the NeurIPS 2023 paper "Unlimiformer: Long-Range Transformers with Unlimited Length Input"
|
abertsch72
|
2024-01-12
|
2023-05-03
| 38 | 25.838235 | null |
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)]
| 7 | 1 | null | 1.92 | 13 | 3 | 9 | 3 | 0 | 0 | 0 | 13 | 34 | 90 | 2.6 | 42 |
1,103 |
diffusion
|
https://github.com/chenyangqiqi/fatezero
|
[]
| null |
[]
|
[]
| null | null | null |
chenyangqiqi/fatezero
|
FateZero
| 976 | 92 | 13 |
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
| 45 | 21.35 | null |
[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)]
| 5 | 4 | null | 2.08 | 5 | 3 | 10 | 5 | 2 | 2 | 2 | 5 | 4 | 90 | 0.8 | 42 |
1,864 |
sim
|
https://github.com/sail-sg/envpool
|
[]
| null |
[]
|
[]
| null | null | null |
sail-sg/envpool
|
envpool
| 965 | 92 | 21 |
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
| 118 | 8.11899 |
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)]
| 17 | 8 | null | 0.37 | 14 | 8 | 27 | 2 | 3 | 12 | 3 | 14 | 25 | 90 | 1.8 | 42 |
555 |
jupyter
|
https://github.com/vizzuhq/ipyvizzu
|
[]
| null |
[]
|
[]
| null | null | null |
vizzuhq/ipyvizzu
|
ipyvizzu
| 898 | 87 | 15 |
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
| 107 | 8.325828 |
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)]
| 20 | 4 | null | 6.46 | 15 | 14 | 25 | 0 | 6 | 12 | 6 | 15 | 2 | 90 | 0.1 | 42 |
1,632 |
util
|
https://github.com/pypa/setuptools_scm
|
['hg', 'git', 'sdist', 'versioning']
| null |
[]
|
[]
| null | null | null |
pypa/setuptools_scm
|
setuptools_scm
| 790 | 215 | 27 |
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
| 447 | 1.763955 |
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)]
| 131 | 7 | null | 3.81 | 61 | 44 | 104 | 0 | 4 | 14 | 4 | 61 | 100 | 90 | 1.6 | 42 |
841 |
util
|
https://github.com/fsspec/s3fs
|
[]
| null |
[]
|
[]
| null | null | null |
fsspec/s3fs
|
s3fs
| 773 | 258 | 18 |
Python
|
http://s3fs.readthedocs.io/en/latest/
|
S3 Filesystem
|
fsspec
|
2024-01-12
|
2016-03-16
| 410 | 1.881433 |
https://avatars.githubusercontent.com/u/92825505?v=4
|
S3 Filesystem
|
[]
|
[]
|
2023-12-16
|
[]
| 134 | 8 | null | 1.12 | 46 | 33 | 95 | 1 | 0 | 8 | 8 | 46 | 125 | 90 | 2.7 | 42 |
578 |
gis
|
https://github.com/developmentseed/titiler
|
[]
| null |
[]
|
[]
| null | null | null |
developmentseed/titiler
|
titiler
| 640 | 130 | 18 |
Python
|
https://developmentseed.org/titiler/
|
Build your own Raster dynamic map tile services
|
developmentseed
|
2024-01-12
|
2019-06-28
| 239 | 2.671437 |
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)]
| 45 | 7 | null | 2.54 | 25 | 22 | 55 | 0 | 0 | 17 | 17 | 25 | 36 | 90 | 1.4 | 42 |
584 |
ml-ops
|
https://github.com/kedro-org/kedro-viz
|
[]
| null |
[]
|
[]
| null | null | null |
kedro-org/kedro-viz
|
kedro-viz
| 616 | 100 | 11 |
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
| 246 | 2.496815 |
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)]
| 47 | 4 | null | 3.92 | 174 | 117 | 57 | 0 | 19 | 15 | 19 | 172 | 236 | 90 | 1.4 | 42 |
984 |
nlp
|
https://github.com/intellabs/fastrag
|
['retrieval-augmentation', 'knowledge-graph', 'haystack']
| null |
[]
|
[]
| 1 | null | null |
intellabs/fastrag
|
fastRAG
| 583 | 49 | 9 |
Python
| null |
Efficient Retrieval Augmentation and Generation Framework
|
intellabs
|
2024-01-14
|
2023-01-23
| 53 | 10.97043 |
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)]
| 6 | 4 | null | 0.62 | 11 | 10 | 12 | 0 | 4 | 6 | 4 | 11 | 17 | 90 | 1.5 | 42 |
1,807 |
data
|
https://github.com/kagisearch/vectordb
|
['vectordb']
| null |
[]
|
[]
| null | null | null |
kagisearch/vectordb
|
vectordb
| 479 | 21 | 3 |
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
| 40 | 11.975 |
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)]
| 7 | 4 | null | 1.6 | 13 | 12 | 9 | 0 | 0 | 0 | 0 | 13 | 26 | 90 | 2 | 42 |
1,271 |
util
|
https://github.com/qdrant/qdrant-client
|
[]
| null |
[]
|
[]
| null | null | null |
qdrant/qdrant-client
|
qdrant-client
| 477 | 79 | 6 |
Python
|
https://qdrant.tech
|
Python client for Qdrant vector search engine
|
qdrant
|
2024-01-14
|
2021-02-09
| 155 | 3.077419 |
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)]
| 18 | 3 | null | 3.02 | 119 | 92 | 36 | 0 | 11 | 25 | 11 | 113 | 275 | 90 | 2.4 | 42 |
1,656 |
llm
|
https://github.com/langchain-ai/langsmith-cookbook
|
['cookbook', 'evaluation', 'language-model']
|
LangSmith is a platform for building production-grade LLM applications.
|
[]
|
[]
| null | null | null |
langchain-ai/langsmith-cookbook
|
langsmith-cookbook
| 436 | 62 | 7 |
Jupyter Notebook
|
https://langsmith-cookbook.vercel.app
| null |
langchain-ai
|
2024-01-13
|
2023-08-01
| 26 | 16.769231 |
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)]
| 10 | 4 | null | 1.9 | 45 | 29 | 6 | 1 | 0 | 0 | 0 | 45 | 39 | 90 | 0.9 | 42 |
961 |
study
|
https://github.com/openai/spinningup
|
[]
| null |
[]
|
[]
| null | null | null |
openai/spinningup
|
spinningup
| 9,334 | 2,120 | 229 |
Python
|
https://spinningup.openai.com/
|
An educational resource to help anyone learn deep reinforcement learning.
|
openai
|
2024-01-14
|
2018-11-07
| 272 | 34.208377 |
https://avatars.githubusercontent.com/u/14957082?v=4
|
An educational resource to help anyone learn deep reinforcement learning.
|
[]
|
[]
|
2020-02-07
|
[('thu-ml/tianshou', 0.5972070097923279, 'ml-rl', 0), ('keras-rl/keras-rl', 0.5871951580047607, 'ml-rl', 0), ('unity-technologies/ml-agents', 0.5850274562835693, 'ml-rl', 0), ('mrdbourke/pytorch-deep-learning', 0.580998420715332, 'study', 0), ('huggingface/deep-rl-class', 0.5750541090965271, 'study', 0), ('tensorflow/tensor2tensor', 0.5718406438827515, 'ml', 0), ('tensorlayer/tensorlayer', 0.5584976673126221, 'ml-rl', 0), ('google/dopamine', 0.5561296939849854, 'ml-rl', 0), ('farama-foundation/gymnasium', 0.5327202081680298, 'ml-rl', 0), ('d2l-ai/d2l-en', 0.5276309251785278, 'study', 0), ('udlbook/udlbook', 0.5261555314064026, 'study', 0), ('denys88/rl_games', 0.5233257412910461, 'ml-rl', 0), ('salesforce/warp-drive', 0.5154350399971008, 'ml-rl', 0), ('openai/baselines', 0.5069130063056946, 'ml-rl', 0), ('facebookresearch/habitat-lab', 0.5063529014587402, 'sim', 0), ('pettingzoo-team/pettingzoo', 0.5047026872634888, 'ml-rl', 0)]
| 25 | 2 | null | 0 | 48 | 3 | 63 | 48 | 0 | 1 | 1 | 48 | 4 | 90 | 0.1 | 41 |
197 |
llm
|
https://github.com/eleutherai/gpt-neo
|
[]
| null |
[]
|
[]
| null | null | null |
eleutherai/gpt-neo
|
gpt-neo
| 8,070 | 934 | 179 |
Python
|
https://www.eleuther.ai
|
An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
|
eleutherai
|
2024-01-13
|
2020-07-05
| 186 | 43.320552 |
https://avatars.githubusercontent.com/u/68924597?v=4
|
An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.
|
['gpt', 'gpt-2', 'gpt-3', 'language-model', 'transformers']
|
['gpt', 'gpt-2', 'gpt-3', 'language-model', 'transformers']
|
2022-02-25
|
[('tensorflow/mesh', 0.665690541267395, 'ml-dl', 0), ('eleutherai/gpt-neox', 0.6265007257461548, 'llm', 3), ('karpathy/mingpt', 0.5706537961959839, 'llm', 0), ('huggingface/accelerate', 0.5675502419471741, 'ml', 0), ('bigscience-workshop/megatron-deepspeed', 0.5555706024169922, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5555706024169922, 'llm', 0), ('nvidia/tensorrt-llm', 0.5397517681121826, 'viz', 1), ('microsoft/pycodegpt', 0.5271508097648621, 'llm', 0), ('farizrahman4u/loopgpt', 0.5264042019844055, 'llm', 1), ('xtekky/gpt4free', 0.5255731344223022, 'llm', 3), ('marella/ctransformers', 0.5227762460708618, 'nlp', 1), ('hannibal046/awesome-llm', 0.5118930339813232, 'study', 2), ('next-gpt/next-gpt', 0.5107851624488831, 'llm', 0), ('minimaxir/gpt-2-simple', 0.5072481632232666, 'llm', 0), ('karpathy/nanogpt', 0.5039609670639038, 'llm', 0), ('huggingface/exporters', 0.5027332901954651, 'ml', 0), ('nvidia/warp', 0.5011614561080933, 'sim', 0), ('rafiqhasan/auto-tensorflow', 0.5005360841751099, 'ml-dl', 0)]
| 29 | 2 | null | 0 | 0 | 0 | 43 | 23 | 0 | 1 | 1 | 0 | 0 | 90 | 0 | 41 |
655 |
study
|
https://github.com/udacity/deep-learning-v2-pytorch
|
[]
| null |
[]
|
[]
| null | null | null |
udacity/deep-learning-v2-pytorch
|
deep-learning-v2-pytorch
| 5,106 | 5,293 | 175 |
Jupyter Notebook
| null |
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
|
udacity
|
2024-01-14
|
2018-09-04
| 282 | 18.106383 |
https://avatars.githubusercontent.com/u/1916665?v=4
|
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
|
['convolutional-networks', 'deep-learning', 'neural-network', 'pytorch', 'recurrent-networks', 'sentiment-analysis', 'style-transfer']
|
['convolutional-networks', 'deep-learning', 'neural-network', 'pytorch', 'recurrent-networks', 'sentiment-analysis', 'style-transfer']
|
2022-12-24
|
[('mrdbourke/pytorch-deep-learning', 0.6218847632408142, 'study', 2), ('amanchadha/coursera-deep-learning-specialization', 0.6206496357917786, 'study', 2), ('graykode/nlp-tutorial', 0.5692509412765503, 'study', 1), ('mrdbourke/tensorflow-deep-learning', 0.5660417079925537, 'study', 1), ('d2l-ai/d2l-en', 0.5573995113372803, 'study', 2), ('ageron/handson-ml2', 0.5552393198013306, 'ml', 0), ('tensorlayer/tensorlayer', 0.550219714641571, 'ml-rl', 2), ('explosion/thinc', 0.5484919548034668, 'ml-dl', 2), ('mrdbourke/zero-to-mastery-ml', 0.5445974469184875, 'study', 1), ('christoschristofidis/awesome-deep-learning', 0.5436199903488159, 'study', 3), ('udlbook/udlbook', 0.5336586236953735, 'study', 1), ('atcold/nyu-dlsp21', 0.5313364267349243, 'study', 1), ('rasbt/machine-learning-book', 0.517561674118042, 'study', 2), ('fchollet/deep-learning-with-python-notebooks', 0.5173661708831787, 'study', 0), ('whitead/dmol-book', 0.5150943994522095, 'ml-dl', 1), ('rasbt/stat453-deep-learning-ss20', 0.5104526281356812, 'study', 0), ('tensorflow/tensor2tensor', 0.5104150176048279, 'ml', 1), ('deepmodeling/deepmd-kit', 0.5088664889335632, 'sim', 1), ('keras-team/keras', 0.5079450011253357, 'ml-dl', 2), ('nvidia/deeplearningexamples', 0.505573570728302, 'ml-dl', 2), ('pytorch/ignite', 0.5055270195007324, 'ml-dl', 3), ('jindongwang/transferlearning', 0.501124918460846, 'ml', 2)]
| 98 | 4 | null | 0 | 1 | 0 | 65 | 13 | 0 | 0 | 0 | 1 | 1 | 90 | 1 | 41 |
196 |
viz
|
https://github.com/lux-org/lux
|
[]
| null |
[]
|
[]
| 1 | null | null |
lux-org/lux
|
lux
| 4,829 | 361 | 90 |
Python
| null |
Automatically visualize your pandas dataframe via a single print! 📊 💡
|
lux-org
|
2024-01-12
|
2020-01-08
| 211 | 22.793661 |
https://avatars.githubusercontent.com/u/59636588?v=4
|
Automatically visualize your pandas dataframe via a single print! 📊 💡
|
['data-science', 'exploratory-data-analysis', 'jupyter', 'pandas', 'visualization', 'visualization-tools']
|
['data-science', 'exploratory-data-analysis', 'jupyter', 'pandas', 'visualization', 'visualization-tools']
|
2023-07-04
|
[('kanaries/pygwalker', 0.7356677055358887, 'pandas', 2), ('man-group/dtale', 0.7073760032653809, 'viz', 3), ('adamerose/pandasgui', 0.6828799843788147, 'pandas', 1), ('tkrabel/bamboolib', 0.6735276579856873, 'pandas', 1), ('mwaskom/seaborn', 0.6733652949333191, 'viz', 2), ('holoviz/panel', 0.6041948795318604, 'viz', 1), ('jakevdp/pythondatasciencehandbook', 0.5983377695083618, 'study', 1), ('scitools/iris', 0.5947362184524536, 'gis', 0), ('twopirllc/pandas-ta', 0.5814751386642456, 'finance', 1), ('bokeh/bokeh', 0.5685267448425293, 'viz', 2), ('vizzuhq/ipyvizzu', 0.5684981346130371, 'jupyter', 1), ('zsailer/pandas_flavor', 0.5670690536499023, 'pandas', 1), ('enthought/mayavi', 0.5663363337516785, 'viz', 1), ('modin-project/modin', 0.5601602792739868, 'perf', 2), ('holoviz/hvplot', 0.5583831071853638, 'pandas', 0), ('holoviz/holoviz', 0.5574216246604919, 'viz', 0), ('residentmario/geoplot', 0.5569419860839844, 'gis', 0), ('hazyresearch/meerkat', 0.5568585991859436, 'viz', 2), ('jmcarpenter2/swifter', 0.5564085841178894, 'pandas', 1), ('pandas-dev/pandas', 0.5501386523246765, 'pandas', 2), ('cmudig/autoprofiler', 0.5497778058052063, 'jupyter', 2), ('plotly/plotly.py', 0.5476740598678589, 'viz', 1), ('quantopian/qgrid', 0.5451768040657043, 'jupyter', 0), ('pyqtgraph/pyqtgraph', 0.5438263416290283, 'viz', 1), ('datapane/datapane', 0.5429391860961914, 'viz', 0), ('ydataai/ydata-profiling', 0.542782723903656, 'pandas', 4), ('nalepae/pandarallel', 0.5424959063529968, 'pandas', 1), ('altair-viz/altair', 0.5405464172363281, 'viz', 1), ('blaze/blaze', 0.5378813743591309, 'pandas', 0), ('mementum/bta-lib', 0.5323396921157837, 'finance', 0), ('rapidsai/cudf', 0.5294429063796997, 'pandas', 2), ('eleutherai/pyfra', 0.5287709832191467, 'ml', 0), ('scikit-learn-contrib/sklearn-pandas', 0.5287317037582397, 'pandas', 0), ('wesm/pydata-book', 0.5268304944038391, 'study', 0), ('contextlab/hypertools', 0.5267577767372131, 'ml', 1), ('plotly/dash', 0.5251437425613403, 'viz', 2), ('cuemacro/chartpy', 0.5205578804016113, 'viz', 0), ('districtdatalabs/yellowbrick', 0.5121427178382874, 'ml', 1), ('mito-ds/monorepo', 0.509769856929779, 'jupyter', 3), ('pydata/pandas-datareader', 0.5096178650856018, 'pandas', 1), ('vaexio/vaex', 0.5093144178390503, 'perf', 2), ('federicoceratto/dashing', 0.5034831762313843, 'term', 0)]
| 21 | 3 | null | 0.04 | 2 | 2 | 49 | 6 | 0 | 3 | 3 | 2 | 0 | 90 | 0 | 41 |
1,781 |
web
|
https://github.com/stephenmcd/mezzanine
|
['django', 'cms']
| null |
[]
|
[]
| null | null | null |
stephenmcd/mezzanine
|
mezzanine
| 4,693 | 1,645 | 247 |
Python
|
http://mezzanine.jupo.org
|
CMS framework for Django
|
stephenmcd
|
2024-01-13
|
2010-05-29
| 713 | 6.578094 | null |
CMS framework for Django
|
[]
|
['cms', 'django']
|
2022-11-02
|
[('feincms/feincms', 0.8132669925689697, 'web', 1), ('wagtail/wagtail', 0.7118169665336609, 'web', 2), ('pallets/flask', 0.5501194596290588, 'web', 0), ('django/django', 0.5459080934524536, 'web', 1), ('bottlepy/bottle', 0.5408180952072144, 'web', 0)]
| 327 | 5 | null | 0 | 5 | 1 | 166 | 15 | 0 | 17 | 17 | 5 | 4 | 90 | 0.8 | 41 |
367 |
nlp
|
https://github.com/layout-parser/layout-parser
|
[]
| null |
[]
|
[]
| null | null | null |
layout-parser/layout-parser
|
layout-parser
| 4,198 | 415 | 69 |
Python
|
https://layout-parser.github.io/
|
A Unified Toolkit for Deep Learning Based Document Image Analysis
|
layout-parser
|
2024-01-12
|
2020-06-10
| 189 | 22.111362 |
https://avatars.githubusercontent.com/u/66751426?v=4
|
A Unified Toolkit for Deep Learning Based Document Image Analysis
|
['computer-vision', 'deep-learning', 'detectron2', 'document-image-processing', 'document-layout-analysis', 'layout-analysis', 'layout-detection', 'layout-parser', 'object-detection', 'ocr']
|
['computer-vision', 'deep-learning', 'detectron2', 'document-image-processing', 'document-layout-analysis', 'layout-analysis', 'layout-detection', 'layout-parser', 'object-detection', 'ocr']
|
2022-08-06
|
[]
| 8 | 4 | null | 0 | 8 | 0 | 44 | 18 | 0 | 3 | 3 | 8 | 4 | 90 | 0.5 | 41 |
1,217 |
ml
|
https://github.com/cmusphinx/pocketsphinx
|
[]
| null |
[]
|
[]
| null | null | null |
cmusphinx/pocketsphinx
|
pocketsphinx
| 3,636 | 684 | 158 |
C
| null |
A small speech recognizer
|
cmusphinx
|
2024-01-12
|
2014-04-07
| 512 | 7.099582 |
https://avatars.githubusercontent.com/u/7203378?v=4
|
A small speech recognizer
|
['c', 'speech-recognition']
|
['c', 'speech-recognition']
|
2023-12-28
|
[('m-bain/whisperx', 0.58738112449646, 'nlp', 1), ('openai/whisper', 0.5778233408927917, 'ml-dl', 1), ('speechbrain/speechbrain', 0.5464542508125305, 'nlp', 1), ('uberi/speech_recognition', 0.5127110481262207, 'ml', 1)]
| 28 | 4 | null | 0.88 | 11 | 6 | 119 | 1 | 3 | 1 | 3 | 11 | 5 | 90 | 0.5 | 41 |
318 |
gui
|
https://github.com/dddomodossola/remi
|
[]
| null |
[]
|
[]
| null | null | null |
dddomodossola/remi
|
remi
| 3,419 | 408 | 121 |
Python
| null |
Python REMote Interface library. Platform independent. In about 100 Kbytes, perfect for your diet.
|
dddomodossola
|
2024-01-13
|
2014-03-20
| 514 | 6.64252 |
https://avatars.githubusercontent.com/u/59974634?v=4
|
Python REMote Interface library. Platform independent. In about 100 Kbytes, perfect for your diet.
|
['gui', 'gui-library', 'platform-independent', 'remi', 'ui']
|
['gui', 'gui-library', 'platform-independent', 'remi', 'ui']
|
2023-06-26
|
[('beeware/toga', 0.6270981431007385, 'gui', 1), ('hoffstadt/dearpygui', 0.5960089564323425, 'gui', 2), ('kivy/kivy', 0.5648102164268494, 'util', 1), ('willmcgugan/textual', 0.5620313882827759, 'term', 0), ('urwid/urwid', 0.5620279312133789, 'term', 0), ('micropython/micropython', 0.5408753752708435, 'util', 0), ('pytables/pytables', 0.5401478409767151, 'data', 0), ('pyinfra-dev/pyinfra', 0.5348232984542847, 'util', 0), ('bottlepy/bottle', 0.5286058187484741, 'web', 0), ('replicate/replicate-python', 0.5246701836585999, 'ml', 0), ('eventlet/eventlet', 0.5185775756835938, 'perf', 0), ('pypy/pypy', 0.5135564804077148, 'util', 0), ('r0x0r/pywebview', 0.5024312138557434, 'gui', 1)]
| 57 | 4 | null | 0.08 | 4 | 1 | 120 | 7 | 0 | 2 | 2 | 4 | 12 | 90 | 3 | 41 |
703 |
pandas
|
https://github.com/nalepae/pandarallel
|
[]
| null |
[]
|
[]
| 1 | null | null |
nalepae/pandarallel
|
pandarallel
| 3,358 | 198 | 29 |
Python
|
https://nalepae.github.io/pandarallel
|
A simple and efficient tool to parallelize Pandas operations on all available CPUs
|
nalepae
|
2024-01-12
|
2019-03-10
| 255 | 13.153889 | null |
A simple and efficient tool to parallelize Pandas operations on all available CPUs
|
['pandas', 'parallel']
|
['pandas', 'parallel']
|
2023-05-02
|
[('jmcarpenter2/swifter', 0.7605847716331482, 'pandas', 1), ('dask/dask', 0.7318655252456665, 'perf', 1), ('ddelange/mapply', 0.6456267833709717, 'pandas', 0), ('blaze/blaze', 0.6345915794372559, 'pandas', 0), ('modin-project/modin', 0.6011874675750732, 'perf', 1), ('scikit-learn-contrib/sklearn-pandas', 0.5978479981422424, 'pandas', 0), ('ipython/ipyparallel', 0.585684597492218, 'perf', 1), ('holoviz/spatialpandas', 0.5524942874908447, 'pandas', 1), ('joblib/joblib', 0.5519195199012756, 'util', 0), ('lux-org/lux', 0.5424959063529968, 'viz', 1), ('tkrabel/bamboolib', 0.5356969237327576, 'pandas', 1), ('mementum/bta-lib', 0.5342207551002502, 'finance', 0), ('adamerose/pandasgui', 0.5294705629348755, 'pandas', 1), ('eventual-inc/daft', 0.5181572437286377, 'pandas', 0), ('twopirllc/pandas-ta', 0.517140805721283, 'finance', 1), ('numpy/numpy', 0.5160078406333923, 'math', 0), ('rapidsai/cudf', 0.5124971866607666, 'pandas', 1), ('vaexio/vaex', 0.5113261938095093, 'perf', 0), ('geopandas/dask-geopandas', 0.5014110207557678, 'gis', 0)]
| 25 | 6 | null | 0.08 | 14 | 0 | 59 | 9 | 2 | 8 | 2 | 14 | 8 | 90 | 0.6 | 41 |
208 |
crypto
|
https://github.com/cyberpunkmetalhead/binance-volatility-trading-bot
|
[]
| null |
[]
|
[]
| null | null | null |
cyberpunkmetalhead/binance-volatility-trading-bot
|
Binance-volatility-trading-bot
| 3,288 | 758 | 144 |
Python
| null |
This is a fully functioning Binance trading bot that measures the volatility of every coin on Binance and places trades with the highest gaining coins If you like this project consider donating though the Brave browser to allow me to continuously improve the script.
|
cyberpunkmetalhead
|
2024-01-14
|
2021-05-08
| 142 | 23.085256 | null |
This is a fully functioning Binance trading bot that measures the volatility of every coin on Binance and places trades with the highest gaining coins If you like this project consider donating though the Brave browser to allow me to continuously improve the script.
|
[]
|
[]
|
2023-08-06
|
[('ccxt/ccxt', 0.5664846301078796, 'crypto', 0), ('gbeced/basana', 0.518947184085846, 'finance', 0)]
| 19 | 3 | null | 0.06 | 5 | 2 | 33 | 5 | 0 | 0 | 0 | 5 | 3 | 90 | 0.6 | 41 |
635 |
testing
|
https://github.com/behave/behave
|
[]
| null |
[]
|
[]
| null | null | null |
behave/behave
|
behave
| 3,009 | 686 | 120 |
Python
|
https://behave.readthedocs.io/en/latest/
|
BDD, Python style.
|
behave
|
2024-01-12
|
2011-10-25
| 640 | 4.701563 |
https://avatars.githubusercontent.com/u/3344102?v=4
|
BDD, Python style.
|
['bdd', 'bdd-framework', 'behave', 'behavior-driven-development', 'cucumber-like', 'gherkin']
|
['bdd', 'bdd-framework', 'behave', 'behavior-driven-development', 'cucumber-like', 'gherkin']
|
2023-11-09
|
[('pytest-dev/pytest-bdd', 0.6536642909049988, 'testing', 0)]
| 88 | 6 | null | 0.92 | 29 | 8 | 149 | 2 | 2 | 2 | 2 | 29 | 33 | 90 | 1.1 | 41 |
605 |
debug
|
https://github.com/inducer/pudb
|
[]
| null |
[]
|
[]
| null | null | null |
inducer/pudb
|
pudb
| 2,811 | 228 | 49 |
Python
|
https://documen.tician.de/pudb/
|
Full-screen console debugger for Python
|
inducer
|
2024-01-14
|
2011-05-13
| 663 | 4.236168 | null |
Full-screen console debugger for Python
|
['bpython', 'debug', 'debugger', 'ipython', 'pdb', 'pytest', 'pytest-plugin', 'urwid']
|
['bpython', 'debug', 'debugger', 'ipython', 'pdb', 'pytest', 'pytest-plugin', 'urwid']
|
2024-01-05
|
[('gotcha/ipdb', 0.6826649904251099, 'debug', 2), ('alexmojaki/snoop', 0.61795973777771, 'debug', 1), ('samuelcolvin/python-devtools', 0.6053194999694824, 'debug', 1), ('alexmojaki/heartrate', 0.5674254894256592, 'debug', 1), ('urwid/urwid', 0.5516170859336853, 'term', 0), ('samuelcolvin/pytest-pretty', 0.5497497320175171, 'testing', 1), ('p403n1x87/austin', 0.5496501326560974, 'profiling', 0), ('pyglet/pyglet', 0.5417070984840393, 'gamedev', 0), ('rockhopper-technologies/enlighten', 0.5411313772201538, 'term', 0), ('jquast/blessed', 0.5037537217140198, 'term', 0)]
| 94 | 4 | null | 0.69 | 15 | 7 | 154 | 0 | 1 | 6 | 1 | 14 | 23 | 90 | 1.6 | 41 |
131 |
ml-dl
|
https://github.com/explosion/thinc
|
[]
| null |
[]
|
[]
| null | null | null |
explosion/thinc
|
thinc
| 2,773 | 284 | 80 |
Python
|
https://thinc.ai
|
🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
|
explosion
|
2024-01-12
|
2014-10-16
| 484 | 5.720896 |
https://avatars.githubusercontent.com/u/20011530?v=4
|
🔮 A refreshing functional take on deep learning, compatible with your favorite libraries
|
['ai', 'artificial-intelligence', 'deep-learning', 'functional-programming', 'jax', 'machine-learning', 'machine-learning-library', 'mxnet', 'natural-language-processing', 'nlp', 'pytorch', 'spacy', 'tensorflow', 'type-checking']
|
['ai', 'artificial-intelligence', 'deep-learning', 'functional-programming', 'jax', 'machine-learning', 'machine-learning-library', 'mxnet', 'natural-language-processing', 'nlp', 'pytorch', 'spacy', 'tensorflow', 'type-checking']
|
2023-12-14
|
[('keras-team/keras', 0.7295705080032349, 'ml-dl', 5), ('huggingface/transformers', 0.7069814801216125, 'nlp', 7), ('tensorlayer/tensorlayer', 0.6832032203674316, 'ml-rl', 3), ('onnx/onnx', 0.6653851866722107, 'ml', 5), ('google/trax', 0.6631956696510315, 'ml-dl', 3), ('nvidia/deeplearningexamples', 0.6549383401870728, 'ml-dl', 5), ('deepmind/dm-haiku', 0.6371207237243652, 'ml-dl', 3), ('tensorflow/tensorflow', 0.6326338052749634, 'ml-dl', 3), ('mosaicml/composer', 0.6281270980834961, 'ml-dl', 3), ('tensorflow/tensor2tensor', 0.626385509967804, 'ml', 2), ('keras-team/autokeras', 0.6246259808540344, 'ml-dl', 3), ('ddbourgin/numpy-ml', 0.6082127094268799, 'ml', 1), ('huggingface/datasets', 0.6036242246627808, 'nlp', 6), ('microsoft/onnxruntime', 0.5988422632217407, 'ml', 4), ('alpa-projects/alpa', 0.5971328020095825, 'ml-dl', 3), ('keras-team/keras-nlp', 0.5930647253990173, 'nlp', 5), ('deeppavlov/deeppavlov', 0.5923045873641968, 'nlp', 6), ('neuralmagic/sparseml', 0.5918089747428894, 'ml-dl', 3), ('bentoml/bentoml', 0.5913470387458801, 'ml-ops', 3), ('tensorly/tensorly', 0.5860464572906494, 'ml-dl', 5), ('arogozhnikov/einops', 0.5852126479148865, 'ml-dl', 4), ('explosion/spacy', 0.5825142860412598, 'nlp', 7), ('lucidrains/toolformer-pytorch', 0.5822931528091431, 'llm', 2), ('karpathy/micrograd', 0.581674337387085, 'study', 0), ('thilinarajapakse/simpletransformers', 0.5814999938011169, 'nlp', 0), ('ml-tooling/opyrator', 0.5795862674713135, 'viz', 1), ('d2l-ai/d2l-en', 0.5795356035232544, 'study', 7), ('pytorch/ignite', 0.5792794823646545, 'ml-dl', 3), ('ludwig-ai/ludwig', 0.5764778256416321, 'ml-ops', 4), ('intel/intel-extension-for-pytorch', 0.5743740200996399, 'perf', 3), ('ray-project/ray', 0.5737190246582031, 'ml-ops', 4), ('microsoft/nni', 0.5728657841682434, 'ml', 4), ('koaning/human-learn', 0.5714577436447144, 'data', 1), ('pytorch/rl', 0.5706343650817871, 'ml-rl', 3), ('horovod/horovod', 0.569107711315155, 'ml-ops', 5), ('paddlepaddle/paddlenlp', 0.5689855217933655, 'llm', 1), ('adap/flower', 0.5687860250473022, 'ml-ops', 6), ('amanchadha/coursera-deep-learning-specialization', 0.5682108998298645, 'study', 1), ('lutzroeder/netron', 0.5670014023780823, 'ml', 6), ('mlflow/mlflow', 0.5667772889137268, 'ml-ops', 2), ('activeloopai/deeplake', 0.5618358254432678, 'ml-ops', 5), ('allenai/allennlp', 0.5593048930168152, 'nlp', 4), ('merantix-momentum/squirrel-core', 0.5592201352119446, 'ml', 8), ('alirezadir/machine-learning-interview-enlightener', 0.5558744668960571, 'study', 3), ('tensorflow/addons', 0.5554784536361694, 'ml', 3), ('dylanhogg/awesome-python', 0.5546610951423645, 'study', 4), ('hpcaitech/colossalai', 0.5544447898864746, 'llm', 2), ('gradio-app/gradio', 0.5544411540031433, 'viz', 2), ('llmware-ai/llmware', 0.5531507730484009, 'llm', 4), ('rasbt/machine-learning-book', 0.5526840686798096, 'study', 3), ('aiqc/aiqc', 0.5513455867767334, 'ml-ops', 0), ('udacity/deep-learning-v2-pytorch', 0.5484919548034668, 'study', 2), ('jina-ai/finetuner', 0.5483794808387756, 'ml', 0), ('deepfakes/faceswap', 0.5478455424308777, 'ml-dl', 2), ('microsoft/deepspeed', 0.5471163392066956, 'ml-dl', 3), ('ai4finance-foundation/finrl', 0.5454742312431335, 'finance', 0), ('christoschristofidis/awesome-deep-learning', 0.5450423359870911, 'study', 2), ('lukaszahradnik/pyneuralogic', 0.5442025065422058, 'math', 3), ('google/tf-quant-finance', 0.5434539318084717, 'finance', 1), ('polyaxon/polyaxon', 0.5428985357284546, 'ml-ops', 6), ('facebookresearch/habitat-lab', 0.5424818396568298, 'sim', 2), ('neuralmagic/deepsparse', 0.5401971936225891, 'nlp', 1), ('nccr-itmo/fedot', 0.5396167635917664, 'ml-ops', 1), ('modularml/mojo', 0.5388814806938171, 'util', 2), ('opentensor/bittensor', 0.5385252833366394, 'ml', 4), ('rafiqhasan/auto-tensorflow', 0.5384374856948853, 'ml-dl', 2), ('fastai/fastcore', 0.5361101627349854, 'util', 1), ('interpretml/interpret', 0.5354365706443787, 'ml-interpretability', 3), ('docarray/docarray', 0.5351216793060303, 'data', 3), ('makcedward/nlpaug', 0.5350939631462097, 'nlp', 5), ('nyandwi/modernconvnets', 0.5349946618080139, 'ml-dl', 1), ('denys88/rl_games', 0.5336785316467285, 'ml-rl', 2), ('prefecthq/marvin', 0.5329232811927795, 'nlp', 1), ('oegedijk/explainerdashboard', 0.5325929522514343, 'ml-interpretability', 0), ('huggingface/autotrain-advanced', 0.5315551161766052, 'ml', 3), ('fepegar/torchio', 0.5309528112411499, 'ml-dl', 3), ('xl0/lovely-tensors', 0.5290781855583191, 'ml-dl', 2), ('awslabs/autogluon', 0.5290007591247559, 'ml', 4), ('ggerganov/ggml', 0.5289695858955383, 'ml', 1), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5284711122512817, 'study', 2), ('tlkh/tf-metal-experiments', 0.5282965302467346, 'perf', 2), ('googlecloudplatform/vertex-ai-samples', 0.5279651284217834, 'ml', 1), ('firmai/industry-machine-learning', 0.5279266834259033, 'study', 1), ('evhub/coconut', 0.5264431834220886, 'util', 1), ('facebookresearch/theseus', 0.5256298184394836, 'math', 2), ('skorch-dev/skorch', 0.525391161441803, 'ml-dl', 2), ('rasahq/rasa', 0.5251515507698059, 'llm', 5), ('ashleve/lightning-hydra-template', 0.5251020193099976, 'util', 2), ('milvus-io/bootcamp', 0.5245603919029236, 'data', 2), ('csinva/imodels', 0.5241812467575073, 'ml', 3), ('microsoft/flaml', 0.5239095091819763, 'ml', 3), ('tensorflow/lucid', 0.522412121295929, 'ml-interpretability', 2), ('aistream-peelout/flow-forecast', 0.5212835669517517, 'time-series', 2), ('intel/scikit-learn-intelex', 0.5210903882980347, 'perf', 1), ('mindsdb/mindsdb', 0.5208819508552551, 'data', 3), ('jina-ai/clip-as-service', 0.5208788514137268, 'nlp', 2), ('explosion/spacy-transformers', 0.5206478238105774, 'llm', 5), ('graykode/nlp-tutorial', 0.5204659104347229, 'study', 4), ('rucaibox/recbole', 0.5200947523117065, 'ml', 2), ('keras-rl/keras-rl', 0.5199488997459412, 'ml-rl', 2), ('extreme-bert/extreme-bert', 0.5198476314544678, 'llm', 5), ('unity-technologies/ml-agents', 0.5183029174804688, 'ml-rl', 2), ('deepmind/dm_control', 0.5177432894706726, 'ml-rl', 3), ('pyg-team/pytorch_geometric', 0.516636073589325, 'ml-dl', 2), ('uber/petastorm', 0.5144953727722168, 'data', 4), ('apache/incubator-mxnet', 0.5136386156082153, 'ml-dl', 1), ('pytorchlightning/pytorch-lightning', 0.5136130452156067, 'ml-dl', 5), ('deepchecks/deepchecks', 0.5133498311042786, 'data', 3), ('blackhc/toma', 0.512549638748169, 'ml-dl', 2), ('deepmodeling/deepmd-kit', 0.5123194456100464, 'sim', 2), ('determined-ai/determined', 0.5116865038871765, 'ml-ops', 4), ('ageron/handson-ml2', 0.5114274621009827, 'ml', 0), ('alibaba/easynlp', 0.5110622048377991, 'nlp', 4), ('explosion/spacy-models', 0.5104645490646362, 'nlp', 4), ('nvidia/nemo', 0.5100991129875183, 'nlp', 2), ('polyaxon/datatile', 0.5097380876541138, 'pandas', 2), ('xplainable/xplainable', 0.5094534754753113, 'ml-interpretability', 1), ('google/mediapipe', 0.5080121159553528, 'ml', 2), ('nevronai/metisfl', 0.5079528093338013, 'ml', 3), ('pytoolz/toolz', 0.507887601852417, 'util', 0), ('roboflow/supervision', 0.5064694881439209, 'ml', 4), ('rwightman/pytorch-image-models', 0.5064119696617126, 'ml-dl', 1), ('avaiga/taipy', 0.5057910680770874, 'data', 0), ('cheshire-cat-ai/core', 0.5046352744102478, 'llm', 1), ('tensorflow/similarity', 0.5028195381164551, 'ml-dl', 3), ('microsoft/semi-supervised-learning', 0.5021923780441284, 'ml', 4), ('feast-dev/feast', 0.5021685361862183, 'ml-ops', 1), ('google/dopamine', 0.5020156502723694, 'ml-rl', 2), ('bigscience-workshop/petals', 0.5014582276344299, 'data', 4), ('ourownstory/neural_prophet', 0.501133382320404, 'ml', 4), ('nltk/nltk', 0.5009826421737671, 'nlp', 3)]
| 63 | 3 | null | 0.9 | 11 | 10 | 113 | 1 | 8 | 11 | 8 | 11 | 6 | 90 | 0.5 | 41 |
410 |
util
|
https://github.com/yaml/pyyaml
|
[]
| null |
[]
|
[]
| null | null | null |
yaml/pyyaml
|
pyyaml
| 2,358 | 512 | 53 |
Python
| null |
Canonical source repository for PyYAML
|
yaml
|
2024-01-13
|
2011-11-03
| 638 | 3.691792 |
https://avatars.githubusercontent.com/u/69535?v=4
|
Canonical source repository for PyYAML
|
['yaml']
|
['yaml']
|
2023-11-14
|
[('mozillazg/pypy', 0.5088357329368591, 'util', 0)]
| 40 | 8 | null | 0.1 | 40 | 14 | 148 | 2 | 0 | 4 | 4 | 40 | 66 | 90 | 1.6 | 41 |
222 |
data
|
https://github.com/pynamodb/pynamodb
|
[]
| null |
[]
|
[]
| 1 | null | null |
pynamodb/pynamodb
|
PynamoDB
| 2,338 | 430 | 40 |
Python
|
http://pynamodb.readthedocs.io
|
A pythonic interface to Amazon's DynamoDB
|
pynamodb
|
2024-01-13
|
2014-01-20
| 523 | 4.469143 |
https://avatars.githubusercontent.com/u/27022537?v=4
|
A pythonic interface to Amazon's DynamoDB
|
['aws', 'dynamodb']
|
['aws', 'dynamodb']
|
2024-01-05
|
[('amzn/ion-python', 0.6932819485664368, 'data', 0), ('awslabs/python-deequ', 0.6457101702690125, 'ml', 1), ('aws/aws-sdk-pandas', 0.6329684257507324, 'pandas', 1), ('geeogi/async-python-lambda-template', 0.6284517049789429, 'template', 0), ('nasdaq/data-link-python', 0.5948277711868286, 'finance', 0), ('aws/aws-lambda-python-runtime-interface-client', 0.5816658735275269, 'util', 0), ('boto/boto3', 0.5776386857032776, 'util', 1), ('nficano/python-lambda', 0.573145866394043, 'util', 1), ('primal100/pybitcointools', 0.5435667634010315, 'crypto', 0), ('aws/chalice', 0.5429194569587708, 'web', 1), ('ethereum/web3.py', 0.536690890789032, 'crypto', 0), ('airbnb/omniduct', 0.5225140452384949, 'data', 0), ('samuelcolvin/aioaws', 0.521031379699707, 'data', 1), ('prefecthq/prefect-aws', 0.5191414952278137, 'data', 1), ('falconry/falcon', 0.5108199119567871, 'web', 0), ('pytables/pytables', 0.5032399892807007, 'data', 0), ('pyeve/eve', 0.5015949010848999, 'web', 0)]
| 107 | 3 | null | 0.38 | 26 | 9 | 122 | 0 | 6 | 9 | 6 | 26 | 22 | 90 | 0.8 | 41 |
611 |
testing
|
https://github.com/pytest-dev/pytest-testinfra
|
[]
| null |
[]
|
[]
| null | null | null |
pytest-dev/pytest-testinfra
|
pytest-testinfra
| 2,282 | 345 | 78 |
Python
|
https://testinfra.readthedocs.io
|
Testinfra test your infrastructures
|
pytest-dev
|
2024-01-12
|
2015-03-15
| 463 | 4.925686 |
https://avatars.githubusercontent.com/u/8897583?v=4
|
Testinfra test your infrastructures
|
['ansible', 'chef', 'devops', 'devops-tools', 'docker', 'infrastructure-as-code', 'infrastructure-testing', 'kubernetes', 'nagios', 'puppet', 'pytest-plugin', 'saltstack', 'tdd', 'tdd-utilities', 'testing', 'testing-tools']
|
['ansible', 'chef', 'devops', 'devops-tools', 'docker', 'infrastructure-as-code', 'infrastructure-testing', 'kubernetes', 'nagios', 'puppet', 'pytest-plugin', 'saltstack', 'tdd', 'tdd-utilities', 'testing', 'testing-tools']
|
2023-11-13
|
[('pytest-dev/pytest-xdist', 0.5474545359611511, 'testing', 1), ('pytest-dev/pytest', 0.5438085794448853, 'testing', 1), ('aquasecurity/trivy', 0.538640558719635, 'security', 3), ('eugeneyan/python-collab-template', 0.5332326292991638, 'template', 0), ('orchest/orchest', 0.5304024815559387, 'ml-ops', 2), ('vedro-universe/vedro', 0.526130199432373, 'testing', 2), ('tox-dev/tox', 0.5243973731994629, 'testing', 1), ('taverntesting/tavern', 0.5087285041809082, 'testing', 1), ('seleniumbase/seleniumbase', 0.5065727233886719, 'testing', 1), ('chaostoolkit/chaostoolkit', 0.5015678405761719, 'util', 2)]
| 136 | 5 | null | 1.1 | 24 | 11 | 108 | 2 | 4 | 10 | 4 | 24 | 15 | 90 | 0.6 | 41 |
1,029 |
finance
|
https://github.com/robcarver17/pysystemtrade
|
[]
| null |
[]
|
[]
| null | null | null |
robcarver17/pysystemtrade
|
pysystemtrade
| 2,255 | 779 | 167 |
Python
| null |
Systematic Trading in python
|
robcarver17
|
2024-01-13
|
2015-11-27
| 426 | 5.286336 | null |
Systematic Trading in python
|
[]
|
[]
|
2024-01-08
|
[('gbeced/pyalgotrade', 0.756932258605957, 'finance', 0), ('quantopian/zipline', 0.6582158803939819, 'finance', 0), ('gbeced/basana', 0.6477593779563904, 'finance', 0), ('cuemacro/finmarketpy', 0.6369601488113403, 'finance', 0), ('goldmansachs/gs-quant', 0.6150317788124084, 'finance', 0), ('mementum/backtrader', 0.6113889813423157, 'finance', 0), ('quantconnect/lean', 0.6064723134040833, 'finance', 0), ('quantecon/quantecon.py', 0.5519441962242126, 'sim', 0), ('quantopian/pyfolio', 0.5509036779403687, 'finance', 0), ('kernc/backtesting.py', 0.5506398677825928, 'finance', 0), ('eleutherai/pyfra', 0.5468427538871765, 'ml', 0), ('pmorissette/ffn', 0.5440186262130737, 'finance', 0), ('ethereum/web3.py', 0.5425991415977478, 'crypto', 0), ('ranaroussi/quantstats', 0.5409232378005981, 'finance', 0), ('firmai/atspy', 0.5296515226364136, 'time-series', 0), ('google/pyglove', 0.5276491045951843, 'util', 0), ('hydrosquall/tiingo-python', 0.5165610313415527, 'finance', 0), ('domokane/financepy', 0.5038099884986877, 'finance', 0)]
| 64 | 2 | null | 11.71 | 35 | 32 | 99 | 0 | 0 | 0 | 0 | 35 | 30 | 90 | 0.9 | 41 |
1,296 |
llm
|
https://github.com/ofa-sys/ofa
|
[]
| null |
[]
|
[]
| null | null | null |
ofa-sys/ofa
|
OFA
| 2,235 | 242 | 22 |
Python
| null |
Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
|
ofa-sys
|
2024-01-14
|
2022-01-29
| 104 | 21.402189 |
https://avatars.githubusercontent.com/u/98636793?v=4
|
Official repository of OFA (ICML 2022). Paper: OFA: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework
|
['chinese', 'image-captioning', 'multimodal', 'pretrained-models', 'pretraining', 'prompt', 'prompt-tuning', 'referring-expression-comprehension', 'text-to-image-synthesis', 'vision-language', 'visual-question-answering']
|
['chinese', 'image-captioning', 'multimodal', 'pretrained-models', 'pretraining', 'prompt', 'prompt-tuning', 'referring-expression-comprehension', 'text-to-image-synthesis', 'vision-language', 'visual-question-answering']
|
2023-08-31
|
[('nvlabs/prismer', 0.664030134677887, 'diffusion', 1), ('salesforce/blip', 0.6362955570220947, 'diffusion', 3), ('reasoning-machines/pal', 0.5922104120254517, 'llm', 0), ('srush/minichain', 0.5822784304618835, 'llm', 0), ('microsoft/unilm', 0.5649746060371399, 'nlp', 1), ('bytedance/lightseq', 0.5597769021987915, 'nlp', 0), ('alibaba/easynlp', 0.5513916611671448, 'nlp', 2), ('next-gpt/next-gpt', 0.538471519947052, 'llm', 1), ('microsoft/generative-ai-for-beginners', 0.5347688794136047, 'study', 0), ('eleutherai/lm-evaluation-harness', 0.5323944091796875, 'llm', 0), ('huggingface/setfit', 0.5320513844490051, 'nlp', 0), ('promptslab/awesome-prompt-engineering', 0.5315465927124023, 'study', 2), ('tatsu-lab/stanford_alpaca', 0.5313153266906738, 'llm', 0), ('pan-ml/panml', 0.5308709740638733, 'llm', 0), ('openai/clip', 0.5293337106704712, 'ml-dl', 0), ('cg123/mergekit', 0.5244383811950684, 'llm', 0), ('thudm/cogvideo', 0.5225783586502075, 'ml', 0), ('lm-sys/fastchat', 0.5206315517425537, 'llm', 0), ('thudm/glm-130b', 0.5175337195396423, 'llm', 0), ('eugeneyan/obsidian-copilot', 0.5171679854393005, 'llm', 0), ('infinitylogesh/mutate', 0.514673113822937, 'nlp', 0), ('deepset-ai/farm', 0.5126766562461853, 'nlp', 1), ('yueyu1030/attrprompt', 0.5103440284729004, 'llm', 0), ('luodian/otter', 0.5090562701225281, 'llm', 0), ('thudm/p-tuning-v2', 0.5087725520133972, 'nlp', 1), ('thilinarajapakse/simpletransformers', 0.5072410702705383, 'nlp', 0), ('huggingface/transformers', 0.5054358243942261, 'nlp', 1), ('night-chen/toolqa', 0.5051456093788147, 'llm', 0), ('openlmlab/moss', 0.5047501921653748, 'llm', 0), ('facebookresearch/mmf', 0.5046265721321106, 'ml-dl', 2), ('llmware-ai/llmware', 0.5022109150886536, 'llm', 0), ('jina-ai/clip-as-service', 0.5020403265953064, 'nlp', 0), ('paddlepaddle/paddlenlp', 0.500640332698822, 'llm', 1)]
| 12 | 6 | null | 0.15 | 12 | 3 | 24 | 5 | 0 | 0 | 0 | 12 | 5 | 90 | 0.4 | 41 |
233 |
crypto
|
https://github.com/ethereum/py-evm
|
[]
| null |
[]
|
[]
| null | null | null |
ethereum/py-evm
|
py-evm
| 2,138 | 625 | 96 |
Python
|
https://py-evm.readthedocs.io/en/latest/
|
A Python implementation of the Ethereum Virtual Machine
|
ethereum
|
2024-01-12
|
2016-12-27
| 370 | 5.778378 |
https://avatars.githubusercontent.com/u/6250754?v=4
|
A Python implementation of the Ethereum Virtual Machine
|
['ethereum', 'ethereum-virtual-machine', 'evm']
|
['ethereum', 'ethereum-virtual-machine', 'evm']
|
2024-01-12
|
[('ethereum/web3.py', 0.6437891721725464, 'crypto', 0), ('pyston/pyston', 0.5943373441696167, 'util', 0), ('primal100/pybitcointools', 0.5760893821716309, 'crypto', 0), ('exaloop/codon', 0.5648453235626221, 'perf', 0), ('micropython/micropython', 0.5545228719711304, 'util', 0), ('1200wd/bitcoinlib', 0.546512246131897, 'crypto', 0), ('pypy/pypy', 0.5445558428764343, 'util', 0), ('oracle/graalpython', 0.54329913854599, 'util', 0), ('paramiko/paramiko', 0.5358531475067139, 'util', 0), ('amzn/ion-python', 0.5310432314872742, 'data', 0), ('replicate/replicate-python', 0.5225535035133362, 'ml', 0), ('pytransitions/transitions', 0.5112031698226929, 'util', 0), ('ipython/ipyparallel', 0.5111911296844482, 'perf', 0), ('backtick-se/cowait', 0.5091575384140015, 'util', 0), ('gbeced/basana', 0.5067870616912842, 'finance', 0), ('fastai/fastcore', 0.5062366724014282, 'util', 0), ('pypa/hatch', 0.5026881694793701, 'util', 0)]
| 91 | 2 | null | 2.46 | 29 | 6 | 86 | 0 | 0 | 15 | 15 | 29 | 3 | 90 | 0.1 | 41 |
322 |
gui
|
https://github.com/wxwidgets/phoenix
|
[]
| null |
[]
|
[]
| null | null | null |
wxwidgets/phoenix
|
Phoenix
| 2,120 | 522 | 107 |
Python
|
http://wxpython.org/
|
wxPython's Project Phoenix. A new implementation of wxPython, better, stronger, faster than he was before.
|
wxwidgets
|
2024-01-14
|
2012-07-17
| 602 | 3.521595 |
https://avatars.githubusercontent.com/u/791023?v=4
|
wxPython's Project Phoenix. A new implementation of wxPython, better, stronger, faster than he was before.
|
['awesome', 'cross-platform', 'gui', 'gui-framework', 'gui-toolkit', 'linux', 'macosx', 'windows', 'wxpython', 'wxwidgets']
|
['awesome', 'cross-platform', 'gui', 'gui-framework', 'gui-toolkit', 'linux', 'macosx', 'windows', 'wxpython', 'wxwidgets']
|
2024-01-11
|
[('pysimplegui/pysimplegui', 0.703073263168335, 'gui', 3), ('beeware/toga', 0.6360959410667419, 'gui', 1), ('hoffstadt/dearpygui', 0.6336509585380554, 'gui', 4), ('pypy/pypy', 0.6231735944747925, 'util', 0), ('pyglet/pyglet', 0.5862021446228027, 'gamedev', 0), ('parthjadhav/tkinter-designer', 0.58327716588974, 'gui', 1), ('holoviz/panel', 0.5708284378051758, 'viz', 1), ('kivy/kivy', 0.5668678879737854, 'util', 2), ('r0x0r/pywebview', 0.5664918422698975, 'gui', 3), ('pyston/pyston', 0.5643559694290161, 'util', 0), ('faster-cpython/ideas', 0.563103973865509, 'perf', 0), ('willmcgugan/textual', 0.5400227308273315, 'term', 0), ('ipython/ipyparallel', 0.5365442633628845, 'perf', 0), ('python/cpython', 0.5291924476623535, 'util', 0), ('erotemic/ubelt', 0.5278312563896179, 'util', 1), ('giswqs/mapwidget', 0.5239470601081848, 'gis', 0), ('jupyter-widgets/ipywidgets', 0.5223656296730042, 'jupyter', 0), ('micropython/micropython', 0.5213609933853149, 'util', 0), ('matplotlib/matplotlib', 0.5209715366363525, 'viz', 0), ('faster-cpython/tools', 0.5171552300453186, 'perf', 0), ('fastai/fastcore', 0.5171084403991699, 'util', 0), ('plotly/plotly.py', 0.5154394507408142, 'viz', 0), ('holoviz/holoviz', 0.5125094652175903, 'viz', 0), ('maartenbreddels/ipyvolume', 0.5121052861213684, 'jupyter', 0), ('timofurrer/awesome-asyncio', 0.510340690612793, 'study', 1), ('pyqtgraph/pyqtgraph', 0.509281575679779, 'viz', 0), ('klen/muffin', 0.5061802864074707, 'web', 0), ('cython/cython', 0.5055117011070251, 'util', 0), ('intel/intel-extension-for-pytorch', 0.5054412484169006, 'perf', 0), ('bokeh/bokeh', 0.5054352879524231, 'viz', 0), ('cohere-ai/notebooks', 0.5029077529907227, 'llm', 0), ('tqdm/tqdm', 0.5025215744972229, 'term', 1)]
| 135 | 3 | null | 1.25 | 85 | 42 | 140 | 0 | 1 | 2 | 1 | 85 | 110 | 90 | 1.3 | 41 |
1,688 |
util
|
https://github.com/pypa/flit
|
['pypi', 'package-manager', 'packaging']
| null |
[]
|
[]
| 1 | null | null |
pypa/flit
|
flit
| 2,058 | 128 | 33 |
Python
|
https://flit.pypa.io/
|
Simplified packaging of Python modules
|
pypa
|
2024-01-13
|
2015-03-13
| 463 | 4.439445 |
https://avatars.githubusercontent.com/u/647025?v=4
|
Simplified packaging of Python modules
|
[]
|
['package-manager', 'packaging']
|
2023-12-09
|
[('indygreg/pyoxidizer', 0.8746299147605896, 'util', 2), ('mitsuhiko/rye', 0.825670599937439, 'util', 2), ('python-poetry/poetry', 0.8031641244888306, 'util', 2), ('regebro/pyroma', 0.7084984183311462, 'util', 1), ('pomponchik/instld', 0.6446828842163086, 'util', 1), ('pdm-project/pdm', 0.6415485143661499, 'util', 2), ('pypa/hatch', 0.6373385787010193, 'util', 2), ('pypi/warehouse', 0.6236358284950256, 'util', 0), ('pyodide/micropip', 0.6164460778236389, 'util', 0), ('mamba-org/mamba', 0.5987750291824341, 'util', 2), ('tezromach/python-package-template', 0.5902042984962463, 'template', 0), ('mamba-org/gator', 0.5534806847572327, 'jupyter', 0), ('ofek/pyapp', 0.5471957921981812, 'util', 1), ('jazzband/pip-tools', 0.5470367670059204, 'util', 1), ('pypa/pipenv', 0.5302018523216248, 'util', 1), ('tiangolo/poetry-version-plugin', 0.519473671913147, 'util', 1), ('pyscaffold/pyscaffold', 0.5155603885650635, 'template', 0), ('beeware/briefcase', 0.5033259987831116, 'util', 0), ('grahamdumpleton/wrapt', 0.5029957890510559, 'util', 0)]
| 70 | 5 | null | 0.56 | 17 | 9 | 108 | 1 | 0 | 5 | 5 | 17 | 21 | 90 | 1.2 | 41 |
642 |
util
|
https://github.com/grahamdumpleton/wrapt
|
[]
| null |
[]
|
[]
| null | null | null |
grahamdumpleton/wrapt
|
wrapt
| 1,917 | 218 | 44 |
Python
| null |
A Python module for decorators, wrappers and monkey patching.
|
grahamdumpleton
|
2024-01-12
|
2013-05-29
| 556 | 3.442535 | null |
A Python module for decorators, wrappers and monkey patching.
|
[]
|
[]
|
2023-11-10
|
[('clarete/forbiddenfruit', 0.6830537915229797, 'util', 0), ('python-rope/rope', 0.5636062026023865, 'util', 0), ('instagram/fixit', 0.5495676398277283, 'util', 0), ('faif/python-patterns', 0.5319310426712036, 'util', 0), ('hhatto/autopep8', 0.5304956436157227, 'util', 0), ('psf/black', 0.527543306350708, 'util', 0), ('indygreg/pyoxidizer', 0.5274959206581116, 'util', 0), ('facebookincubator/bowler', 0.5219171047210693, 'util', 0), ('eugeneyan/python-collab-template', 0.5126464366912842, 'template', 0), ('pdm-project/pdm', 0.5066951513290405, 'util', 0), ('pypa/hatch', 0.5048109292984009, 'util', 0), ('python-poetry/poetry', 0.5032442212104797, 'util', 0), ('pypa/flit', 0.5029957890510559, 'util', 0), ('allrod5/injectable', 0.5006911754608154, 'util', 0)]
| 27 | 6 | null | 0.69 | 13 | 5 | 129 | 2 | 1 | 5 | 1 | 13 | 59 | 90 | 4.5 | 41 |
592 |
time-series
|
https://github.com/uber/orbit
|
[]
| null |
[]
|
[]
| null | null | null |
uber/orbit
|
orbit
| 1,770 | 130 | 32 |
Python
|
https://orbit-ml.readthedocs.io/en/stable/
|
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
|
uber
|
2024-01-14
|
2020-01-07
| 212 | 8.349057 |
https://avatars.githubusercontent.com/u/538264?v=4
|
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.
|
['arima', 'bayesian', 'bayesian-methods', 'bayesian-statistics', 'changepoint', 'exponential-smoothing', 'forecast', 'forecasting', 'machine-learning', 'orbit', 'probabilistic', 'probabilistic-programming', 'pyro', 'pystan', 'pytorch', 'regression', 'regression-models', 'stan', 'time-series']
|
['arima', 'bayesian', 'bayesian-methods', 'bayesian-statistics', 'changepoint', 'exponential-smoothing', 'forecast', 'forecasting', 'machine-learning', 'orbit', 'probabilistic', 'probabilistic-programming', 'pyro', 'pystan', 'pytorch', 'regression', 'regression-models', 'stan', 'time-series']
|
2024-01-12
|
[('awslabs/gluonts', 0.6446792483329773, 'time-series', 4), ('pymc-devs/pymc3', 0.6276130080223083, 'ml', 1), ('alkaline-ml/pmdarima', 0.5944992899894714, 'time-series', 4), ('firmai/atspy', 0.5873233675956726, 'time-series', 2), ('ourownstory/neural_prophet', 0.5688930153846741, 'ml', 5), ('statsmodels/statsmodels', 0.5589537024497986, 'ml', 2), ('probml/pyprobml', 0.5333145260810852, 'ml', 4), ('nixtla/statsforecast', 0.5311532020568848, 'time-series', 5), ('unit8co/darts', 0.5234378576278687, 'time-series', 3), ('stan-dev/pystan', 0.5150203704833984, 'ml', 0), ('scikit-optimize/scikit-optimize', 0.5112178325653076, 'ml', 1), ('winedarksea/autots', 0.5088127255439758, 'time-series', 3), ('pyro-ppl/pyro', 0.5006424188613892, 'ml-dl', 4), ('crflynn/stochastic', 0.5002565979957581, 'sim', 0)]
| 19 | 3 | null | 0.44 | 25 | 21 | 49 | 0 | 3 | 6 | 3 | 25 | 10 | 90 | 0.4 | 41 |
877 |
time-series
|
https://github.com/aistream-peelout/flow-forecast
|
[]
| null |
[]
|
[]
| null | null | null |
aistream-peelout/flow-forecast
|
flow-forecast
| 1,748 | 272 | 28 |
Python
|
https://flow-forecast.atlassian.net/wiki/spaces/FF/overview
|
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
|
aistream-peelout
|
2024-01-13
|
2019-08-15
| 232 | 7.511357 |
https://avatars.githubusercontent.com/u/45472534?v=4
|
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
|
['anomaly-detection', 'deep-learning', 'deep-neural-networks', 'forecasting', 'lstm', 'pytorch', 'state-of-the-art-models', 'time-series', 'time-series-analysis', 'time-series-forecasting', 'time-series-regression', 'transfer-learning', 'transformer']
|
['anomaly-detection', 'deep-learning', 'deep-neural-networks', 'forecasting', 'lstm', 'pytorch', 'state-of-the-art-models', 'time-series', 'time-series-analysis', 'time-series-forecasting', 'time-series-regression', 'transfer-learning', 'transformer']
|
2024-01-11
|
[('unit8co/darts', 0.7890238165855408, 'time-series', 4), ('salesforce/deeptime', 0.7200793027877808, 'time-series', 5), ('yzhao062/pyod', 0.6631090044975281, 'data', 2), ('salesforce/merlion', 0.6415663361549377, 'time-series', 3), ('pycaret/pycaret', 0.6154711246490479, 'ml', 2), ('huggingface/transformers', 0.6060823798179626, 'nlp', 3), ('ourownstory/neural_prophet', 0.5880416035652161, 'ml', 4), ('opengeos/earthformer', 0.5866661071777344, 'gis', 3), ('awslabs/gluonts', 0.5800959467887878, 'time-series', 5), ('tdameritrade/stumpy', 0.567234992980957, 'time-series', 2), ('rasbt/machine-learning-book', 0.5672064423561096, 'study', 2), ('alkaline-ml/pmdarima', 0.5597772002220154, 'time-series', 2), ('pytorch/ignite', 0.5596166253089905, 'ml-dl', 2), ('winedarksea/autots', 0.557109534740448, 'time-series', 3), ('sktime/sktime', 0.5518553256988525, 'time-series', 4), ('keras-team/keras', 0.5506109595298767, 'ml-dl', 2), ('nvidia/deeplearningexamples', 0.549731969833374, 'ml-dl', 3), ('ashleve/lightning-hydra-template', 0.5330670475959778, 'util', 2), ('tensorlayer/tensorlayer', 0.5312919020652771, 'ml-rl', 1), ('nyandwi/modernconvnets', 0.5294846296310425, 'ml-dl', 0), ('pyg-team/pytorch_geometric', 0.5282737016677856, 'ml-dl', 2), ('uber/petastorm', 0.5273684859275818, 'data', 2), ('skorch-dev/skorch', 0.5259057879447937, 'ml-dl', 1), ('mrdbourke/pytorch-deep-learning', 0.5234374403953552, 'study', 2), ('explosion/thinc', 0.5212835669517517, 'ml-dl', 2), ('tensorflow/tensorflow', 0.5199403166770935, 'ml-dl', 2), ('intellabs/bayesian-torch', 0.518251359462738, 'ml', 3), ('tensorflow/tensor2tensor', 0.5155697464942932, 'ml', 1), ('neuralmagic/sparseml', 0.5107213854789734, 'ml-dl', 2), ('keras-team/autokeras', 0.5103901624679565, 'ml-dl', 1), ('ddbourgin/numpy-ml', 0.5097944140434265, 'ml', 1), ('linkedin/greykite', 0.5091543197631836, 'ml', 0), ('nixtla/statsforecast', 0.506076991558075, 'time-series', 2), ('alignmentresearch/tuned-lens', 0.5054931640625, 'ml-interpretability', 1), ('datasystemslab/geotorch', 0.5054202675819397, 'gis', 2), ('christoschristofidis/awesome-deep-learning', 0.5039076209068298, 'study', 1), ('awslabs/autogluon', 0.5033537149429321, 'ml', 5), ('arogozhnikov/einops', 0.5023390650749207, 'ml-dl', 2), ('ray-project/ray-educational-materials', 0.5015262365341187, 'study', 1)]
| 14 | 2 | null | 5.9 | 21 | 15 | 54 | 0 | 1 | 9 | 1 | 21 | 18 | 90 | 0.9 | 41 |
511 |
data
|
https://github.com/agronholm/sqlacodegen
|
[]
| null |
[]
|
[]
| null | null | null |
agronholm/sqlacodegen
|
sqlacodegen
| 1,605 | 228 | 25 |
Python
| null |
Automatic model code generator for SQLAlchemy
|
agronholm
|
2024-01-13
|
2016-12-28
| 369 | 4.339513 | null |
Automatic model code generator for SQLAlchemy
|
[]
|
[]
|
2024-01-09
|
[('sqlalchemy/sqlalchemy', 0.7499924302101135, 'data', 0), ('sqlalchemy/alembic', 0.6634976267814636, 'data', 0), ('tiangolo/sqlmodel', 0.542255163192749, 'data', 0), ('mause/duckdb_engine', 0.5388209819793701, 'data', 0), ('brokenloop/jsontopydantic', 0.5330995321273804, 'util', 0), ('mcfunley/pugsql', 0.5109015703201294, 'data', 0), ('aminalaee/sqladmin', 0.5044848918914795, 'data', 0), ('microsoft/pycodegpt', 0.5004090666770935, 'llm', 0)]
| 19 | 2 | null | 1.04 | 24 | 12 | 86 | 0 | 0 | 3 | 3 | 24 | 67 | 90 | 2.8 | 41 |
1,778 |
perf
|
https://github.com/python-greenlet/greenlet
|
['coroutine']
| null |
[]
|
[]
| null | null | null |
python-greenlet/greenlet
|
greenlet
| 1,559 | 232 | 53 |
C++
| null |
Lightweight in-process concurrent programming
|
python-greenlet
|
2024-01-12
|
2011-12-17
| 632 | 2.465101 |
https://avatars.githubusercontent.com/u/1270171?v=4
|
Lightweight in-process concurrent programming
|
[]
|
['coroutine']
|
2023-12-21
|
[('noxdafox/pebble', 0.6010660529136658, 'perf', 0), ('python-trio/trio', 0.5789716839790344, 'perf', 0), ('sumerc/yappi', 0.5529376268386841, 'profiling', 1), ('agronholm/anyio', 0.517914354801178, 'perf', 0), ('fluentpython/example-code-2e', 0.514401912689209, 'study', 0)]
| 68 | 4 | null | 1.83 | 24 | 17 | 147 | 1 | 0 | 4 | 4 | 24 | 83 | 90 | 3.5 | 41 |
1,545 |
web
|
https://github.com/jordaneremieff/mangum
|
['aws', 'lambda', 'asgi']
| null |
[]
|
[]
| null | null | null |
jordaneremieff/mangum
|
mangum
| 1,518 | 94 | 16 |
Python
|
https://mangum.io/
|
AWS Lambda support for ASGI applications
|
jordaneremieff
|
2024-01-12
|
2019-01-14
| 263 | 5.76873 | null |
AWS Lambda support for ASGI applications
|
['api-gateway', 'asgi', 'asyncio', 'aws', 'aws-lambda', 'django', 'fastapi', 'lambda', 'quart', 'sanic', 'serverless', 'starlette']
|
['api-gateway', 'asgi', 'asyncio', 'aws', 'aws-lambda', 'django', 'fastapi', 'lambda', 'quart', 'sanic', 'serverless', 'starlette']
|
2023-11-03
|
[('samuelcolvin/aioaws', 0.7040007710456848, 'data', 2), ('geeogi/async-python-lambda-template', 0.6858481168746948, 'template', 0), ('aws/chalice', 0.677313506603241, 'web', 4), ('nficano/python-lambda', 0.6575080752372742, 'util', 3), ('neoteroi/blacksheep', 0.6414300203323364, 'web', 2), ('aws/aws-lambda-python-runtime-interface-client', 0.6282299160957336, 'util', 0), ('pallets/quart', 0.6127312183380127, 'web', 3), ('starlite-api/starlite', 0.5975977182388306, 'web', 2), ('rpgreen/apilogs', 0.595600962638855, 'util', 4), ('boto/boto3', 0.589402973651886, 'util', 1), ('falconry/falcon', 0.5848598480224609, 'web', 1), ('encode/uvicorn', 0.5822369456291199, 'web', 2), ('developmentseed/geolambda', 0.5730166435241699, 'gis', 0), ('aio-libs/aiobotocore', 0.546834409236908, 'util', 2), ('aws/aws-sdk-pandas', 0.5317604541778564, 'pandas', 3), ('alirn76/panther', 0.5160053372383118, 'web', 0), ('encode/starlette', 0.5116714239120483, 'web', 0), ('huge-success/sanic', 0.511349081993103, 'web', 3), ('aio-libs/aiohttp', 0.5083812475204468, 'web', 1), ('developmentseed/titiler', 0.5069487690925598, 'gis', 2)]
| 30 | 6 | null | 0.02 | 15 | 4 | 61 | 2 | 0 | 12 | 12 | 15 | 16 | 90 | 1.1 | 41 |
1,719 |
util
|
https://github.com/sourcery-ai/sourcery
|
['code-quality']
| null |
[]
|
[]
| null | null | null |
sourcery-ai/sourcery
|
sourcery
| 1,446 | 53 | 17 | null |
https://sourcery.ai
|
Automatically review and improve your Python code. ⭐ this repo and Sourcery Starbot will send you a PR. Or install our CLI to improve your code locally
|
sourcery-ai
|
2024-01-14
|
2019-07-15
| 237 | 6.09759 |
https://avatars.githubusercontent.com/u/36609879?v=4
|
Automatically review and improve your Python code. ⭐ this repo and Sourcery Starbot will send you a PR. Or install our CLI to improve your code locally
|
['ai', 'code-quality', 'refactoring', 'software-development', 'software-tools']
|
['ai', 'code-quality', 'refactoring', 'software-development', 'software-tools']
|
2023-12-21
|
[('rubik/radon', 0.6180241703987122, 'util', 0), ('nedbat/coveragepy', 0.5949026942253113, 'testing', 0), ('reloadware/reloadium', 0.5745614767074585, 'profiling', 1), ('amaargiru/pyroad', 0.5690412521362305, 'study', 0), ('featurelabs/featuretools', 0.554305911064148, 'ml', 0), ('willmcgugan/textual', 0.5534403920173645, 'term', 0), ('dosisod/refurb', 0.5449427366256714, 'util', 0), ('eugeneyan/python-collab-template', 0.5378775596618652, 'template', 0), ('prompt-toolkit/ptpython', 0.5356951355934143, 'util', 0), ('jendrikseipp/vulture', 0.5342533588409424, 'util', 1), ('pypy/pypy', 0.5338239073753357, 'util', 0), ('python/cpython', 0.5331263542175293, 'util', 0), ('landscapeio/prospector', 0.5299766659736633, 'util', 0), ('eleutherai/pyfra', 0.5296950340270996, 'ml', 0), ('google/pyglove', 0.5295018553733826, 'util', 0), ('psf/black', 0.5155060291290283, 'util', 1), ('hhatto/autopep8', 0.5095126628875732, 'util', 0), ('samuelcolvin/python-devtools', 0.506219744682312, 'debug', 0), ('pypa/hatch', 0.5025754570960999, 'util', 0), ('gradio-app/gradio', 0.5021675825119019, 'viz', 0), ('norvig/pytudes', 0.5019119381904602, 'util', 0), ('gaogaotiantian/viztracer', 0.5000627636909485, 'profiling', 0)]
| 9 | 3 | null | 0.5 | 26 | 13 | 55 | 1 | 211 | 100 | 211 | 26 | 42 | 90 | 1.6 | 41 |
1,118 |
web
|
https://github.com/wtforms/wtforms
|
[]
| null |
[]
|
[]
| null | null | null |
wtforms/wtforms
|
wtforms
| 1,443 | 392 | 48 |
Python
|
https://wtforms.readthedocs.io
|
A flexible forms validation and rendering library for Python.
|
wtforms
|
2024-01-06
|
2013-09-11
| 541 | 2.663064 |
https://avatars.githubusercontent.com/u/4740084?v=4
|
A flexible forms validation and rendering library for Python.
|
['forms', 'html', 'validation', 'wtforms']
|
['forms', 'html', 'validation', 'wtforms']
|
2024-01-11
|
[('pyeve/cerberus', 0.657631516456604, 'data', 0), ('connorferster/handcalcs', 0.5505093336105347, 'jupyter', 0), ('pydantic/pydantic', 0.5329594612121582, 'util', 1), ('pytoolz/toolz', 0.5101136565208435, 'util', 0)]
| 156 | 5 | null | 1.48 | 24 | 19 | 126 | 0 | 3 | 3 | 3 | 24 | 32 | 90 | 1.3 | 41 |
932 |
data
|
https://github.com/datastax/python-driver
|
[]
| null |
[]
|
[]
| null | null | null |
datastax/python-driver
|
python-driver
| 1,363 | 577 | 78 |
Python
| null |
DataStax Python Driver for Apache Cassandra
|
datastax
|
2024-01-08
|
2013-07-08
| 551 | 2.473043 |
https://avatars.githubusercontent.com/u/573369?v=4
|
DataStax Python Driver for Apache Cassandra
|
[]
|
[]
|
2023-12-21
|
[('scylladb/python-driver', 0.8284926414489746, 'data', 0), ('neo4j/neo4j-python-driver', 0.5756858587265015, 'data', 0), ('awslabs/python-deequ', 0.5413904190063477, 'ml', 0), ('nasdaq/data-link-python', 0.5312590599060059, 'finance', 0)]
| 196 | 6 | null | 1.25 | 19 | 14 | 128 | 1 | 0 | 8 | 8 | 19 | 27 | 90 | 1.4 | 41 |
983 |
sim
|
https://github.com/deepmodeling/deepmd-kit
|
[]
| null |
[]
|
[]
| null | null | null |
deepmodeling/deepmd-kit
|
deepmd-kit
| 1,296 | 462 | 46 |
C++
|
https://docs.deepmodeling.com/projects/deepmd/
|
A deep learning package for many-body potential energy representation and molecular dynamics
|
deepmodeling
|
2024-01-13
|
2017-12-12
| 320 | 4.05 |
https://avatars.githubusercontent.com/u/32671488?v=4
|
A deep learning package for many-body potential energy representation and molecular dynamics
|
['ase', 'c', 'computational-chemistry', 'cpp', 'cuda', 'deep-learning', 'deepmd', 'ipi', 'lammps', 'materials-science', 'molecular-dynamics', 'nodejs', 'potential-energy', 'rocm', 'tensorflow']
|
['ase', 'c', 'computational-chemistry', 'cpp', 'cuda', 'deep-learning', 'deepmd', 'ipi', 'lammps', 'materials-science', 'molecular-dynamics', 'nodejs', 'potential-energy', 'rocm', 'tensorflow']
|
2023-10-27
|
[('whitead/dmol-book', 0.702418863773346, 'ml-dl', 1), ('tensorlayer/tensorlayer', 0.5839037299156189, 'ml-rl', 2), ('espressomd/espresso', 0.5804603695869446, 'sim', 1), ('nvidia/deeplearningexamples', 0.558430016040802, 'ml-dl', 2), ('d2l-ai/d2l-en', 0.5467190146446228, 'study', 2), ('tensorflow/tensor2tensor', 0.5421066880226135, 'ml', 1), ('uber/petastorm', 0.5317656397819519, 'data', 2), ('google/trax', 0.5293905735015869, 'ml-dl', 1), ('denys88/rl_games', 0.5176900625228882, 'ml-rl', 1), ('microsoft/deepspeed', 0.513860821723938, 'ml-dl', 1), ('explosion/thinc', 0.5123194456100464, 'ml-dl', 2), ('keras-team/keras', 0.5097646713256836, 'ml-dl', 2), ('udacity/deep-learning-v2-pytorch', 0.5088664889335632, 'study', 1), ('ashleve/lightning-hydra-template', 0.5063115358352661, 'util', 1), ('dmlc/dgl', 0.5051169991493225, 'ml-dl', 1), ('skorch-dev/skorch', 0.5047734379768372, 'ml-dl', 0), ('rasbt/machine-learning-book', 0.5035223960876465, 'study', 1), ('deepmind/dm_control', 0.5011904239654541, 'ml-rl', 1)]
| 64 | 1 | null | 6.83 | 228 | 196 | 74 | 3 | 8 | 11 | 8 | 223 | 296 | 90 | 1.3 | 41 |
603 |
testing
|
https://github.com/pytest-dev/pytest-xdist
|
[]
| null |
[]
|
[]
| null | null | null |
pytest-dev/pytest-xdist
|
pytest-xdist
| 1,287 | 216 | 49 |
Python
|
https://pytest-xdist.readthedocs.io
|
pytest plugin for distributed testing and loop-on-failures testing modes.
|
pytest-dev
|
2024-01-11
|
2015-09-01
| 439 | 2.931663 |
https://avatars.githubusercontent.com/u/8897583?v=4
|
pytest plugin for distributed testing and loop-on-failures testing modes.
|
['pytest', 'pytest-plugin']
|
['pytest', 'pytest-plugin']
|
2024-01-10
|
[('pytest-dev/pytest-cov', 0.7077765464782715, 'testing', 1), ('pytest-dev/pytest', 0.6530086994171143, 'testing', 0), ('teemu/pytest-sugar', 0.6500891447067261, 'testing', 2), ('pytest-dev/pytest-asyncio', 0.6232805252075195, 'testing', 1), ('ionelmc/pytest-benchmark', 0.613385796546936, 'testing', 1), ('pytest-dev/pytest-mock', 0.6102861762046814, 'testing', 1), ('taverntesting/tavern', 0.6020364165306091, 'testing', 1), ('kiwicom/pytest-recording', 0.5940394401550293, 'testing', 1), ('computationalmodelling/nbval', 0.5855597257614136, 'jupyter', 2), ('samuelcolvin/pytest-pretty', 0.5537928342819214, 'testing', 1), ('wolever/parameterized', 0.5527563095092773, 'testing', 0), ('pytest-dev/pytest-testinfra', 0.5474545359611511, 'testing', 1), ('samuelcolvin/dirty-equals', 0.546781599521637, 'util', 1), ('nedbat/coveragepy', 0.5098601579666138, 'testing', 0), ('buildbot/buildbot', 0.5035778880119324, 'util', 0)]
| 93 | 5 | null | 1.17 | 60 | 36 | 102 | 0 | 1 | 8 | 1 | 60 | 98 | 90 | 1.6 | 41 |
895 |
util
|
https://github.com/ossf/criticality_score
|
[]
| null |
[]
|
[]
| null | null | null |
ossf/criticality_score
|
criticality_score
| 1,255 | 109 | 34 |
Go
| null |
Gives criticality score for an open source project
|
ossf
|
2024-01-10
|
2020-11-17
| 167 | 7.51497 |
https://avatars.githubusercontent.com/u/67707773?v=4
|
Gives criticality score for an open source project
|
[]
|
[]
|
2023-12-14
|
[]
| 20 | 3 | null | 1.4 | 55 | 43 | 38 | 1 | 4 | 3 | 4 | 55 | 40 | 90 | 0.7 | 41 |
576 |
util
|
https://github.com/lidatong/dataclasses-json
|
[]
| null |
[]
|
[]
| null | null | null |
lidatong/dataclasses-json
|
dataclasses-json
| 1,248 | 142 | 8 |
Python
| null |
Easily serialize Data Classes to and from JSON
|
lidatong
|
2024-01-13
|
2018-04-21
| 301 | 4.140284 | null |
Easily serialize Data Classes to and from JSON
|
['dataclasses', 'json']
|
['dataclasses', 'json']
|
2023-11-27
|
[('yukinarit/pyserde', 0.686412513256073, 'util', 2), ('konradhalas/dacite', 0.630731999874115, 'util', 1), ('marshmallow-code/marshmallow', 0.5334739089012146, 'util', 0), ('python-attrs/cattrs', 0.5296611189842224, 'typing', 0), ('1rgs/jsonformer', 0.529080331325531, 'llm', 1), ('pylons/colander', 0.5289405584335327, 'util', 0), ('jsonpickle/jsonpickle', 0.5186536908149719, 'data', 1)]
| 67 | 5 | null | 1.15 | 24 | 13 | 70 | 2 | 12 | 14 | 12 | 24 | 30 | 90 | 1.2 | 41 |
1,035 |
diffusion
|
https://github.com/nvlabs/prismer
|
[]
| null |
[]
|
[]
| null | null | null |
nvlabs/prismer
|
prismer
| 1,242 | 70 | 15 |
Python
|
https://shikun.io/projects/prismer
|
The implementation of "Prismer: A Vision-Language Model with An Ensemble of Experts".
|
nvlabs
|
2024-01-13
|
2023-03-02
| 47 | 26.02994 |
https://avatars.githubusercontent.com/u/2695301?v=4
|
The implementation of "Prismer: A Vision-Language Model with An Ensemble of Experts".
|
['image-captioning', 'language-model', 'multi-modal-learning', 'multi-task-learning', 'vision-and-language', 'vision-language-model', 'vqa']
|
['image-captioning', 'language-model', 'multi-modal-learning', 'multi-task-learning', 'vision-and-language', 'vision-language-model', 'vqa']
|
2023-04-29
|
[('salesforce/blip', 0.6734409928321838, 'diffusion', 1), ('ofa-sys/ofa', 0.664030134677887, 'llm', 1), ('next-gpt/next-gpt', 0.5736103057861328, 'llm', 0), ('eleutherai/lm-evaluation-harness', 0.5629435777664185, 'llm', 1), ('freedomintelligence/llmzoo', 0.5624253153800964, 'llm', 1), ('jerryyli/valhalla-nmt', 0.5498813390731812, 'ml-dl', 0), ('luodian/otter', 0.5447686314582825, 'llm', 0), ('thilinarajapakse/simpletransformers', 0.5408389568328857, 'nlp', 0), ('reasoning-machines/pal', 0.5364494323730469, 'llm', 1), ('lm-sys/fastchat', 0.5359172821044922, 'llm', 1), ('facebookresearch/mmf', 0.5333836674690247, 'ml-dl', 1), ('lucidrains/toolformer-pytorch', 0.5290699005126953, 'llm', 1), ('nvlabs/gcvit', 0.5274479389190674, 'diffusion', 0), ('hannibal046/awesome-llm', 0.5241163969039917, 'study', 1), ('huggingface/transformers', 0.5211392045021057, 'nlp', 1), ('jina-ai/clip-as-service', 0.5206122994422913, 'nlp', 0), ('openai/gpt-2', 0.5184028744697571, 'llm', 0), ('microsoft/lora', 0.5161336064338684, 'llm', 1), ('ai21labs/lm-evaluation', 0.5158585906028748, 'llm', 1), ('openai/clip', 0.5122661590576172, 'ml-dl', 0), ('extreme-bert/extreme-bert', 0.5107273459434509, 'llm', 1), ('lvwerra/trl', 0.509940505027771, 'llm', 0), ('lucidrains/imagen-pytorch', 0.5019423961639404, 'ml-dl', 0)]
| 3 | 3 | null | 0.58 | 1 | 1 | 11 | 9 | 0 | 0 | 0 | 1 | 3 | 90 | 3 | 41 |
854 |
jupyter
|
https://github.com/jupyter/nbgrader
|
[]
| null |
[]
|
[]
| null | null | null |
jupyter/nbgrader
|
nbgrader
| 1,241 | 319 | 44 |
Python
|
https://nbgrader.readthedocs.io/
|
A system for assigning and grading notebooks
|
jupyter
|
2024-01-11
|
2014-09-13
| 489 | 2.53561 |
https://avatars.githubusercontent.com/u/7388996?v=4
|
A system for assigning and grading notebooks
|
['grading', 'jupyter', 'jupyter-notebook', 'jupyterhub', 'nbgrader', 'teaching']
|
['grading', 'jupyter', 'jupyter-notebook', 'jupyterhub', 'nbgrader', 'teaching']
|
2023-12-04
|
[('jupyter/nbformat', 0.6341890692710876, 'jupyter', 0), ('jupyter/nbconvert', 0.6126564145088196, 'jupyter', 0), ('cohere-ai/notebooks', 0.5908788442611694, 'llm', 0), ('mwouts/jupytext', 0.5783310532569885, 'jupyter', 1), ('jupyter/notebook', 0.5747985243797302, 'jupyter', 2), ('fchollet/deep-learning-with-python-notebooks', 0.5345233678817749, 'study', 0), ('nteract/papermill', 0.532752513885498, 'jupyter', 1), ('quantopian/qgrid', 0.5307871103286743, 'jupyter', 0), ('jupyter-widgets/ipywidgets', 0.5242305397987366, 'jupyter', 0), ('jupyter/nbdime', 0.5187388062477112, 'jupyter', 2), ('jakevdp/pythondatasciencehandbook', 0.5142012238502502, 'study', 1), ('ageron/handson-ml2', 0.5094665884971619, 'ml', 0), ('koaning/calm-notebooks', 0.5042494535446167, 'study', 0)]
| 105 | 4 | null | 1.1 | 27 | 11 | 114 | 1 | 8 | 4 | 8 | 27 | 56 | 90 | 2.1 | 41 |
401 |
perf
|
https://github.com/tiangolo/asyncer
|
[]
| null |
[]
|
[]
| null | null | null |
tiangolo/asyncer
|
asyncer
| 1,235 | 47 | 18 |
Python
|
https://asyncer.tiangolo.com/
|
Asyncer, async and await, focused on developer experience.
|
tiangolo
|
2024-01-12
|
2022-01-04
| 108 | 11.435185 | null |
Asyncer, async and await, focused on developer experience.
|
['anyio', 'async', 'asyncio', 'trio']
|
['anyio', 'async', 'asyncio', 'trio']
|
2023-12-10
|
[('agronholm/anyio', 0.7173997759819031, 'perf', 2), ('magicstack/uvloop', 0.6868960857391357, 'util', 2), ('python-trio/trio', 0.6240719556808472, 'perf', 2), ('encode/starlette', 0.5958313345909119, 'web', 1), ('aio-libs/aiohttp', 0.5814606547355652, 'web', 2), ('alirn76/panther', 0.5792798399925232, 'web', 0), ('pallets/quart', 0.5767269134521484, 'web', 1), ('huge-success/sanic', 0.5628356337547302, 'web', 1), ('timofurrer/awesome-asyncio', 0.5529595017433167, 'study', 1), ('alex-sherman/unsync', 0.5449034571647644, 'util', 0), ('sumerc/yappi', 0.5410847067832947, 'profiling', 1), ('tiangolo/fastapi', 0.525113582611084, 'web', 2), ('noxdafox/pebble', 0.5147314667701721, 'perf', 1), ('samuelcolvin/arq', 0.5030202865600586, 'data', 2)]
| 10 | 5 | null | 0.62 | 26 | 12 | 25 | 1 | 0 | 1 | 1 | 26 | 15 | 90 | 0.6 | 41 |
1,599 |
llm
|
https://github.com/srush/minichain
|
['prompt-engineering', 'question-answering', 'retrieval-augmentation']
| null |
[]
|
[]
| null | null | null |
srush/minichain
|
MiniChain
| 1,148 | 72 | 15 |
Python
|
https://srush-minichain.hf.space/
|
A tiny library for coding with large language models.
|
srush
|
2024-01-13
|
2023-02-10
| 50 | 22.700565 | null |
A tiny library for coding with large language models.
|
[]
|
['prompt-engineering', 'question-answering', 'retrieval-augmentation']
|
2023-12-07
|
[('keirp/automatic_prompt_engineer', 0.6470367908477783, 'llm', 1), ('openai/finetune-transformer-lm', 0.6227275133132935, 'llm', 0), ('stanfordnlp/dspy', 0.6080040335655212, 'llm', 0), ('ai21labs/in-context-ralm', 0.5984602570533752, 'llm', 1), ('ofa-sys/ofa', 0.5822784304618835, 'llm', 0), ('neulab/prompt2model', 0.5800988674163818, 'llm', 0), ('hazyresearch/ama_prompting', 0.5800570845603943, 'llm', 1), ('hannibal046/awesome-llm', 0.5760703086853027, 'study', 0), ('reasoning-machines/pal', 0.5743135809898376, 'llm', 0), ('freedomintelligence/llmzoo', 0.5740912556648254, 'llm', 0), ('ai21labs/lm-evaluation', 0.5739299654960632, 'llm', 0), ('lm-sys/fastchat', 0.572079062461853, 'llm', 0), ('juncongmoo/pyllama', 0.5712380409240723, 'llm', 0), ('bigscience-workshop/promptsource', 0.5696084499359131, 'nlp', 0), ('1rgs/jsonformer', 0.5634762644767761, 'llm', 1), ('paddlepaddle/rocketqa', 0.5608699321746826, 'nlp', 1), ('intellabs/fastrag', 0.5593423843383789, 'nlp', 2), ('guidance-ai/guidance', 0.5577107667922974, 'llm', 1), ('deepset-ai/farm', 0.5554335713386536, 'nlp', 1), ('lupantech/chameleon-llm', 0.5546031594276428, 'llm', 0), ('infinitylogesh/mutate', 0.5535112023353577, 'nlp', 0), ('kyegomez/tree-of-thoughts', 0.5509519577026367, 'llm', 1), ('jonasgeiping/cramming', 0.5501981973648071, 'nlp', 0), ('mit-han-lab/streaming-llm', 0.5470554232597351, 'llm', 0), ('salesforce/blip', 0.5436856746673584, 'diffusion', 0), ('eleutherai/lm-evaluation-harness', 0.542423665523529, 'llm', 0), ('llmware-ai/llmware', 0.5373873114585876, 'llm', 1), ('ctlllll/llm-toolmaker', 0.5372619032859802, 'llm', 0), ('gunthercox/chatterbot-corpus', 0.5370650291442871, 'nlp', 0), ('yizhongw/self-instruct', 0.5332199931144714, 'llm', 0), ('openai/gpt-2', 0.5330092310905457, 'llm', 0), ('thudm/chatglm-6b', 0.5271021127700806, 'llm', 0), ('thudm/p-tuning-v2', 0.5268715620040894, 'nlp', 0), ('tatsu-lab/stanford_alpaca', 0.5253647565841675, 'llm', 0), ('togethercomputer/redpajama-data', 0.5224243998527527, 'llm', 0), ('openlmlab/moss', 0.5213707089424133, 'llm', 0), ('lianjiatech/belle', 0.519889771938324, 'llm', 0), ('night-chen/toolqa', 0.5163832306861877, 'llm', 1), ('eugeneyan/obsidian-copilot', 0.5138395428657532, 'llm', 0), ('databrickslabs/dolly', 0.5138243436813354, 'llm', 0), ('defog-ai/sqlcoder', 0.512403130531311, 'llm', 0), ('bigscience-workshop/biomedical', 0.5102963447570801, 'data', 0), ('next-gpt/next-gpt', 0.5092249512672424, 'llm', 0), ('huggingface/text-generation-inference', 0.5085004568099976, 'llm', 0), ('luohongyin/sail', 0.5050071477890015, 'llm', 0), ('bytedance/lightseq', 0.5048473477363586, 'nlp', 0), ('cg123/mergekit', 0.5045192837715149, 'llm', 0)]
| 7 | 4 | null | 2.67 | 0 | 0 | 11 | 1 | 2 | 2 | 2 | 0 | 0 | 90 | 0 | 41 |
733 |
ml
|
https://github.com/koaning/scikit-lego
|
[]
| null |
[]
|
[]
| null | null | null |
koaning/scikit-lego
|
scikit-lego
| 1,097 | 107 | 23 |
Python
|
https://koaning.github.io/scikit-lego/
|
Extra blocks for scikit-learn pipelines.
|
koaning
|
2024-01-09
|
2019-01-21
| 262 | 4.184741 | null |
Extra blocks for scikit-learn pipelines.
|
['common-sense', 'machine-learning', 'scikit-learn']
|
['common-sense', 'machine-learning', 'scikit-learn']
|
2024-01-06
|
[('koaning/scikit-partial', 0.6257511377334595, 'data', 0), ('skops-dev/skops', 0.6168782711029053, 'ml-ops', 2), ('automl/auto-sklearn', 0.6153001189231873, 'ml', 1), ('iryna-kondr/scikit-llm', 0.614821195602417, 'llm', 2), ('koaning/human-learn', 0.5959609150886536, 'data', 2), ('rasbt/machine-learning-book', 0.5857502818107605, 'study', 2), ('skorch-dev/skorch', 0.5642397999763489, 'ml-dl', 2), ('intel/scikit-learn-intelex', 0.5534452199935913, 'perf', 2), ('kubeflow/pipelines', 0.539598822593689, 'ml-ops', 1), ('featurelabs/featuretools', 0.5262479782104492, 'ml', 2), ('csinva/imodels', 0.5232925415039062, 'ml', 2), ('teamhg-memex/eli5', 0.5188755989074707, 'ml', 2), ('ageron/handson-ml2', 0.5152604579925537, 'ml', 0), ('linealabs/lineapy', 0.5148707032203674, 'jupyter', 0), ('kubeflow-kale/kale', 0.5133776664733887, 'ml-ops', 1), ('epistasislab/tpot', 0.5125021934509277, 'ml', 2), ('dask/dask-ml', 0.5104072093963623, 'ml', 0), ('optimalscale/lmflow', 0.5066888928413391, 'llm', 0), ('districtdatalabs/yellowbrick', 0.5034389495849609, 'ml', 2), ('scikit-learn-contrib/metric-learn', 0.5020371675491333, 'ml', 2)]
| 62 | 5 | null | 0.69 | 36 | 28 | 61 | 0 | 3 | 7 | 3 | 36 | 40 | 90 | 1.1 | 41 |
502 |
gis
|
https://github.com/anitagraser/movingpandas
|
[]
| null |
[]
|
[]
| null | null | null |
anitagraser/movingpandas
|
movingpandas
| 1,084 | 185 | 38 |
Python
|
http://movingpandas.org
|
Movement trajectory classes and functions built on top of GeoPandas
|
anitagraser
|
2024-01-13
|
2018-12-16
| 267 | 4.055585 |
https://avatars.githubusercontent.com/u/123823419?v=4
|
Movement trajectory classes and functions built on top of GeoPandas
|
['geopandas', 'movement-data', 'spatial-data-analysis', 'trajectory', 'trajectory-analysis']
|
['geopandas', 'movement-data', 'spatial-data-analysis', 'trajectory', 'trajectory-analysis']
|
2023-12-30
|
[('geopandas/geopandas', 0.5975525379180908, 'gis', 1), ('holoviz/spatialpandas', 0.5773379802703857, 'pandas', 1), ('residentmario/geoplot', 0.5739251375198364, 'gis', 1), ('scikit-mobility/scikit-mobility', 0.5389496684074402, 'gis', 0), ('pandas-dev/pandas', 0.5086138248443604, 'pandas', 0)]
| 33 | 4 | null | 1.23 | 13 | 8 | 62 | 0 | 6 | 4 | 6 | 13 | 26 | 90 | 2 | 41 |
1,149 |
data
|
https://github.com/aio-libs/aiokafka
|
[]
| null |
[]
|
[]
| null | null | null |
aio-libs/aiokafka
|
aiokafka
| 988 | 212 | 29 |
Python
|
http://aiokafka.readthedocs.io/
|
asyncio client for kafka
|
aio-libs
|
2024-01-12
|
2014-11-01
| 482 | 2.047972 |
https://avatars.githubusercontent.com/u/7049303?v=4
|
asyncio client for kafka
|
['asyncio', 'kafka', 'kafka-client']
|
['asyncio', 'kafka', 'kafka-client']
|
2024-01-13
|
[('aio-libs/aiohttp', 0.5572373270988464, 'web', 1), ('aio-libs/aiobotocore', 0.5398765802383423, 'util', 1), ('samuelcolvin/aioaws', 0.5397475957870483, 'data', 1), ('alex-sherman/unsync', 0.5082889199256897, 'util', 0)]
| 72 | 6 | null | 1.15 | 42 | 28 | 112 | 0 | 6 | 4 | 6 | 42 | 77 | 90 | 1.8 | 41 |
967 |
sim
|
https://github.com/a-r-j/graphein
|
[]
| null |
[]
|
[]
| null | null | null |
a-r-j/graphein
|
graphein
| 937 | 119 | 20 |
Jupyter Notebook
|
https://graphein.ai/
|
Protein Graph Library
|
a-r-j
|
2024-01-12
|
2019-08-28
| 230 | 4.058787 | null |
Protein Graph Library
|
['bioinformatics', 'computational-biology', 'deep-learning', 'dgl', 'drug-discovery', 'gene-regulatory-networks', 'geometric-deep-learning', 'graph-neural-networks', 'interactome', 'interactomics', 'ppi-networks', 'protein', 'protein-data-bank', 'protein-design', 'protein-structure', 'pytorch', 'pytorch-geometric', 'rna', 'structural-biology']
|
['bioinformatics', 'computational-biology', 'deep-learning', 'dgl', 'drug-discovery', 'gene-regulatory-networks', 'geometric-deep-learning', 'graph-neural-networks', 'interactome', 'interactomics', 'ppi-networks', 'protein', 'protein-data-bank', 'protein-design', 'protein-structure', 'pytorch', 'pytorch-geometric', 'rna', 'structural-biology']
|
2023-12-26
|
[('pyg-team/pytorch_geometric', 0.6886248588562012, 'ml-dl', 4), ('benedekrozemberczki/tigerlily', 0.6609140634536743, 'ml-dl', 1), ('graphistry/pygraphistry', 0.6311023235321045, 'data', 0), ('stellargraph/stellargraph', 0.6164317727088928, 'graph', 3), ('dmlc/dgl', 0.5949839949607849, 'ml-dl', 2), ('accenture/ampligraph', 0.5756738185882568, 'data', 0), ('danielegrattarola/spektral', 0.551216721534729, 'ml-dl', 2), ('networkx/networkx', 0.5483938455581665, 'graph', 0), ('tensorlayer/tensorlayer', 0.538101315498352, 'ml-rl', 1), ('h4kor/graph-force', 0.5339735150337219, 'graph', 0), ('rucaibox/recbole', 0.5301325917243958, 'ml', 3), ('pandas-dev/pandas', 0.5266823768615723, 'pandas', 0), ('plotly/plotly.py', 0.5239959955215454, 'viz', 0), ('pytorch/torchrec', 0.5193598866462708, 'ml-dl', 2), ('chandlerbang/awesome-self-supervised-gnn', 0.5173624753952026, 'study', 2), ('docarray/docarray', 0.5024240612983704, 'data', 2)]
| 25 | 6 | null | 1.31 | 18 | 15 | 53 | 1 | 7 | 4 | 7 | 18 | 25 | 90 | 1.4 | 41 |
1,516 |
llm
|
https://github.com/microsoft/llama-2-onnx
|
['llama', 'language-model']
|
A Microsoft optimized version of the Llama 2 model, available from Meta
|
[]
|
[]
| null | null | null |
microsoft/llama-2-onnx
|
Llama-2-Onnx
| 924 | 74 | 342 |
Python
| null | null |
microsoft
|
2024-01-13
|
2023-07-17
| 28 | 32.832487 |
https://avatars.githubusercontent.com/u/6154722?v=4
|
A Microsoft optimized version of the Llama 2 model, available from Meta
|
[]
|
['language-model', 'llama']
|
2023-10-17
|
[('facebookresearch/llama-recipes', 0.820441722869873, 'llm', 2), ('tloen/alpaca-lora', 0.7532107830047607, 'llm', 2), ('jzhang38/tinyllama', 0.7340604066848755, 'llm', 2), ('facebookresearch/llama', 0.7213297486305237, 'llm', 2), ('run-llama/llama-lab', 0.7098461985588074, 'llm', 2), ('mshumer/gpt-llm-trainer', 0.6853927969932556, 'llm', 0), ('karpathy/llama2.c', 0.6777373552322388, 'llm', 2), ('zrrskywalker/llama-adapter', 0.6588950157165527, 'llm', 2), ('ggerganov/llama.cpp', 0.6485655903816223, 'llm', 2), ('lightning-ai/lit-llama', 0.643981397151947, 'llm', 2), ('facebookresearch/codellama', 0.6238771080970764, 'llm', 2), ('abetlen/llama-cpp-python', 0.6152366399765015, 'llm', 2), ('tairov/llama2.mojo', 0.6118836998939514, 'llm', 1), ('openlm-research/open_llama', 0.6107590794563293, 'llm', 2), ('oobabooga/text-generation-webui', 0.5708426833152771, 'llm', 1), ('young-geng/easylm', 0.5490400791168213, 'llm', 2), ('cg123/mergekit', 0.5430543422698975, 'llm', 1), ('jerryjliu/llama_index', 0.542698860168457, 'llm', 2), ('nat/openplayground', 0.5403831005096436, 'llm', 1), ('bigscience-workshop/petals', 0.5293133854866028, 'data', 1), ('bentoml/openllm', 0.5186194181442261, 'ml-ops', 1), ('run-llama/llama-hub', 0.5180464386940002, 'data', 0), ('juncongmoo/pyllama', 0.5146937966346741, 'llm', 0), ('salesforce/xgen', 0.5118889212608337, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5092772841453552, 'llm', 2), ('hiyouga/llama-factory', 0.5092772841453552, 'llm', 2)]
| 8 | 1 | null | 0.44 | 25 | 9 | 6 | 3 | 0 | 0 | 0 | 25 | 25 | 90 | 1 | 41 |
1,443 |
util
|
https://github.com/pypa/gh-action-pypi-publish
|
[]
| null |
[]
|
[]
| null | null | null |
pypa/gh-action-pypi-publish
|
gh-action-pypi-publish
| 780 | 78 | 9 |
Python
|
https://packaging.python.org/guides/publishing-package-distribution-releases-using-github-actions-ci-cd-workflows/
|
The blessed :octocat: GitHub Action, for publishing your :package: distribution files to PyPI: https://github.com/marketplace/actions/pypi-publish
|
pypa
|
2024-01-13
|
2019-03-27
| 252 | 3.084746 |
https://avatars.githubusercontent.com/u/647025?v=4
|
The blessed :octocat: GitHub Action, for publishing your 📦 distribution files to PyPI: https://github.com/marketplace/actions/pypi-publish
|
['actions', 'github-action', 'github-actions', 'github-actions-python', 'oidc', 'pypa-guide', 'python-packaging', 'release', 'release-automation', 'release-helper', 'secrets', 'testpypi', 'twine', 'upload', 'workflow', 'workflow-automation', 'workflows']
|
['actions', 'github-action', 'github-actions', 'github-actions-python', 'oidc', 'pypa-guide', 'python-packaging', 'release', 'release-automation', 'release-helper', 'secrets', 'testpypi', 'twine', 'upload', 'workflow', 'workflow-automation', 'workflows']
|
2023-12-20
|
[('mozillazg/pypy', 0.6144118309020996, 'util', 0), ('pypi/warehouse', 0.6143344044685364, 'util', 0), ('indygreg/pyoxidizer', 0.5328114628791809, 'util', 0), ('pypa/hatch', 0.5319401025772095, 'util', 0), ('pypa/setuptools_scm', 0.5103867650032043, 'util', 0), ('hugovk/pypistats', 0.5029650926589966, 'util', 0)]
| 23 | 7 | null | 1.17 | 25 | 15 | 58 | 1 | 15 | 7 | 15 | 25 | 49 | 90 | 2 | 41 |
588 |
gis
|
https://github.com/matplotlib/basemap
|
[]
| null |
[]
|
[]
| null | null | null |
matplotlib/basemap
|
basemap
| 755 | 397 | 61 |
Python
| null |
Plot on map projections (with coastlines and political boundaries) using matplotlib
|
matplotlib
|
2024-01-10
|
2011-02-19
| 675 | 1.117809 |
https://avatars.githubusercontent.com/u/215947?v=4
|
Plot on map projections (with coastlines and political boundaries) using matplotlib
|
['gis', 'maps', 'plots']
|
['gis', 'maps', 'plots']
|
2024-01-11
|
[('scitools/cartopy', 0.6154806613922119, 'gis', 1), ('csurfer/pyheat', 0.5544516444206238, 'profiling', 0), ('matplotlib/matplotlib', 0.505860447883606, 'viz', 0), ('mwaskom/seaborn', 0.500274658203125, 'viz', 0)]
| 71 | 7 | null | 3.71 | 33 | 26 | 157 | 0 | 4 | 3 | 4 | 33 | 112 | 90 | 3.4 | 41 |
819 |
diffusion
|
https://github.com/thereforegames/unprompted
|
[]
| null |
[]
|
[]
| null | null | null |
thereforegames/unprompted
|
unprompted
| 712 | 62 | 16 |
Python
| null |
Templating language written for Stable Diffusion workflows. Available as an extension for the Automatic1111 WebUI.
|
thereforegames
|
2024-01-07
|
2022-10-31
| 65 | 10.929825 | null |
Templating language written for Stable Diffusion workflows. Available as an extension for the Automatic1111 WebUI.
|
['a1111-stable-diffusion-webui', 'ai-art', 'deep-learning', 'gpt', 'gradio', 'img2img', 'shortcode', 'stable-diffusion', 'template-engine', 'text2image', 'txt2img', 'wildcards']
|
['a1111-stable-diffusion-webui', 'ai-art', 'deep-learning', 'gpt', 'gradio', 'img2img', 'shortcode', 'stable-diffusion', 'template-engine', 'text2image', 'txt2img', 'wildcards']
|
2023-12-01
|
[('automatic1111/stable-diffusion-webui', 0.7207518219947815, 'diffusion', 7), ('mlc-ai/web-stable-diffusion', 0.6838393807411194, 'diffusion', 2), ('civitai/sd_civitai_extension', 0.6360564827919006, 'llm', 0), ('saharmor/dalle-playground', 0.5805418491363525, 'diffusion', 1), ('carson-katri/dream-textures', 0.5799620747566223, 'diffusion', 1), ('invoke-ai/invokeai', 0.553229808807373, 'diffusion', 4), ('pallets/jinja', 0.5376675128936768, 'util', 1), ('comfyanonymous/comfyui', 0.5250580906867981, 'diffusion', 1), ('stability-ai/stability-sdk', 0.5244125127792358, 'diffusion', 2), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.5091450810432434, 'web', 0), ('nateraw/stable-diffusion-videos', 0.5079180002212524, 'diffusion', 2), ('bentoml/onediffusion', 0.5029755234718323, 'diffusion', 1), ('ashawkey/stable-dreamfusion', 0.5019211769104004, 'diffusion', 1)]
| 8 | 2 | null | 3.21 | 19 | 9 | 15 | 1 | 0 | 0 | 0 | 19 | 53 | 90 | 2.8 | 41 |
1,764 |
data
|
https://github.com/duckdb/dbt-duckdb
|
[]
| null |
[]
|
[]
| null | null | null |
duckdb/dbt-duckdb
|
dbt-duckdb
| 636 | 56 | 17 |
Python
| null |
dbt (http://getdbt.com) adapter for DuckDB (http://duckdb.org)
|
duckdb
|
2024-01-13
|
2020-09-25
| 174 | 3.643208 |
https://avatars.githubusercontent.com/u/82039556?v=4
|
dbt (http://getdbt.com) adapter for DuckDB (http://duckdb.org)
|
['dbt', 'duckdb']
|
['dbt', 'duckdb']
|
2024-01-13
|
[('duckdb/duckdb', 0.6090986132621765, 'pandas', 0), ('databricks/dbt-databricks', 0.5661155581474304, 'data', 1), ('airbnb/omniduct', 0.5301816463470459, 'data', 0)]
| 23 | 3 | null | 6.12 | 46 | 43 | 40 | 0 | 11 | 4 | 11 | 46 | 52 | 90 | 1.1 | 41 |
1,703 |
data
|
https://github.com/dgarnitz/vectorflow
|
[]
| null |
[]
|
[]
| null | null | null |
dgarnitz/vectorflow
|
vectorflow
| 592 | 37 | 10 |
Python
|
https://www.getvectorflow.com/
|
VectorFlow is a high volume vector embedding pipeline that ingests raw data, transforms it into vectors and writes it to a vector DB of your choice.
|
dgarnitz
|
2024-01-14
|
2023-07-25
| 27 | 21.925926 | null |
VectorFlow is a high volume vector embedding pipeline that ingests raw data, transforms it into vectors and writes it to a vector DB of your choice.
|
['ai', 'data-engineering', 'embeddings', 'machine-learning', 'nlp', 'vectors']
|
['ai', 'data-engineering', 'embeddings', 'machine-learning', 'nlp', 'vectors']
|
2023-12-07
|
[('activeloopai/deeplake', 0.6199436187744141, 'ml-ops', 2), ('mage-ai/mage-ai', 0.6055392622947693, 'ml-ops', 2), ('jina-ai/vectordb', 0.5692445039749146, 'data', 0), ('featureform/embeddinghub', 0.5690073370933533, 'nlp', 2), ('lancedb/lancedb', 0.5619788765907288, 'data', 0), ('kubeflow/pipelines', 0.5347921252250671, 'ml-ops', 1), ('superduperdb/superduperdb', 0.5114015340805054, 'data', 1), ('towhee-io/towhee', 0.5035332441329956, 'ml-ops', 2)]
| 10 | 1 | null | 1.87 | 39 | 29 | 6 | 1 | 0 | 0 | 0 | 39 | 34 | 90 | 0.9 | 41 |
1,439 |
ml
|
https://github.com/replicate/replicate-python
|
[]
| null |
[]
|
[]
| null | null | null |
replicate/replicate-python
|
replicate-python
| 512 | 195 | 30 |
Python
|
https://replicate.com
|
Python client for Replicate
|
replicate
|
2024-01-13
|
2022-05-11
| 89 | 5.697933 |
https://avatars.githubusercontent.com/u/60410876?v=4
|
Python client for Replicate
|
[]
|
[]
|
2024-01-04
|
[('steamship-core/python-client', 0.6438118815422058, 'util', 0), ('encode/httpx', 0.5832346677780151, 'web', 0), ('eleutherai/pyfra', 0.5586503148078918, 'ml', 0), ('simple-salesforce/simple-salesforce', 0.5586280226707458, 'data', 0), ('ethereum/web3.py', 0.5461574792861938, 'crypto', 0), ('dddomodossola/remi', 0.5246701836585999, 'gui', 0), ('ethereum/py-evm', 0.5225535035133362, 'crypto', 0), ('masoniteframework/masonite', 0.5155618190765381, 'web', 0), ('pypy/pypy', 0.5141051411628723, 'util', 0), ('uqfoundation/dill', 0.5080131888389587, 'data', 0), ('aio-libs/aiohttp', 0.5043667554855347, 'web', 0), ('willmcgugan/textual', 0.5011894106864929, 'term', 0)]
| 13 | 2 | null | 2.17 | 79 | 68 | 20 | 0 | 33 | 32 | 33 | 79 | 92 | 90 | 1.2 | 41 |
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