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720 | web | https://github.com/rstudio/py-shiny | [] | null | [] | [] | null | null | null | rstudio/py-shiny | py-shiny | 817 | 49 | 29 | Python | https://shiny.posit.co/py/ | Shiny for Python | rstudio | 2024-01-13 | 2021-07-27 | 131 | 6.236641 | https://avatars.githubusercontent.com/u/107264312?v=4 | Shiny for Python | [] | [] | 2024-01-12 | [('python/cpython', 0.536689817905426, 'util', 0), ('holoviz/panel', 0.5275716781616211, 'viz', 0), ('plotly/dash', 0.5270806550979614, 'viz', 0), ('pypy/pypy', 0.5167948603630066, 'util', 0), ('hoffstadt/dearpygui', 0.5147618651390076, 'gui', 0), ('eleutherai/pyfra', 0.5123597979545593, 'ml', 0)] | 18 | 4 | null | 7.56 | 272 | 164 | 30 | 0 | 11 | 9 | 11 | 272 | 269 | 90 | 1 | 46 |
343 | data | https://github.com/scikit-hep/awkward-1.0 | [] | null | [] | [] | null | null | null | scikit-hep/awkward-1.0 | awkward | 770 | 77 | 21 | Python | https://awkward-array.org | Manipulate JSON-like data with NumPy-like idioms. | scikit-hep | 2024-01-14 | 2019-08-14 | 232 | 3.306748 | https://avatars.githubusercontent.com/u/23454624?v=4 | Manipulate JSON-like data with NumPy-like idioms. | ['apache-arrow', 'cern-root', 'columnar-format', 'data-analysis', 'jagged-array', 'json', 'numba', 'numpy', 'pandas', 'ragged-array', 'rdataframe', 'scikit-hep'] | ['apache-arrow', 'cern-root', 'columnar-format', 'data-analysis', 'jagged-array', 'json', 'numba', 'numpy', 'pandas', 'ragged-array', 'rdataframe', 'scikit-hep'] | 2024-01-12 | [('apache/arrow', 0.559539258480072, 'data', 3), ('vaexio/vaex', 0.5477538704872131, 'perf', 0), ('man-group/dtale', 0.5412405729293823, 'viz', 2), ('kellyjonbrazil/jello', 0.5297543406486511, 'util', 1), ('brokenloop/jsontopydantic', 0.5177565813064575, 'util', 0), ('pandas-dev/pandas', 0.5098268389701843, 'pandas', 2), ('jazzband/tablib', 0.5033981800079346, 'data', 0), ('jsonpickle/jsonpickle', 0.500355064868927, 'data', 1)] | 40 | 4 | null | 9.77 | 197 | 165 | 54 | 0 | 36 | 62 | 36 | 196 | 380 | 90 | 1.9 | 46 |
881 | gis | https://github.com/osgeo/grass | [] | null | [] | [] | null | null | null | osgeo/grass | grass | 720 | 255 | 43 | C | https://grass.osgeo.org | GRASS GIS - free and open-source geospatial processing engine | osgeo | 2024-01-13 | 2019-05-17 | 245 | 2.931937 | https://avatars.githubusercontent.com/u/1058467?v=4 | GRASS GIS - free and open-source geospatial processing engine | ['arrays', 'data-science', 'earth-observation', 'geospatial', 'geospatial-analysis', 'gis', 'grass-gis', 'image-processing', 'jupyter', 'machine-learning', 'open-science', 'parallel-computing', 'raster', 'remote-sensing', 'science', 'spatial', 'timeseries-analysis', 'vector'] | ['arrays', 'data-science', 'earth-observation', 'geospatial', 'geospatial-analysis', 'gis', 'grass-gis', 'image-processing', 'jupyter', 'machine-learning', 'open-science', 'parallel-computing', 'raster', 'remote-sensing', 'science', 'spatial', 'timeseries-analysis', 'vector'] | 2024-01-14 | [('remotesensinglab/raster4ml', 0.6746719479560852, 'gis', 3), ('fatiando/verde', 0.6331599950790405, 'gis', 2), ('microsoft/torchgeo', 0.6095272302627563, 'gis', 3), ('earthlab/earthpy', 0.5645433068275452, 'gis', 2), ('osgeo/gdal', 0.5594460368156433, 'gis', 3), ('giswqs/geemap', 0.5491253137588501, 'gis', 6), ('apache/incubator-sedona', 0.5388128757476807, 'gis', 1), ('opengeos/segment-geospatial', 0.5276463627815247, 'gis', 2), ('opengeos/leafmap', 0.5151031017303467, 'gis', 5), ('r-barnes/richdem', 0.5100005269050598, 'gis', 1), ('determined-ai/determined', 0.5073267817497253, 'ml-ops', 2), ('perrygeo/python-rasterstats', 0.5056399703025818, 'gis', 0), ('darribas/gds_env', 0.502344012260437, 'gis', 0)] | 107 | 6 | null | 8.48 | 316 | 166 | 57 | 0 | 6 | 30 | 6 | 317 | 588 | 90 | 1.9 | 46 |
1,409 | math | https://github.com/lean-dojo/leandojo | [] | null | [] | [] | null | null | null | lean-dojo/leandojo | LeanDojo | 389 | 45 | 13 | Python | https://leandojo.org | Tool for data extraction and interacting with Lean programmatically. | lean-dojo | 2024-01-14 | 2023-06-13 | 33 | 11.787879 | https://avatars.githubusercontent.com/u/136513911?v=4 | Tool for data extraction and interacting with Lean programmatically. | ['lean', 'lean4', 'machine-learning', 'theorem-proving'] | ['lean', 'lean4', 'machine-learning', 'theorem-proving'] | 2024-01-10 | [('lean-dojo/reprover', 0.6379106640815735, 'math', 3), ('intake/intake', 0.5443071722984314, 'data', 0), ('paperswithcode/axcell', 0.5234335660934448, 'util', 0), ('linealabs/lineapy', 0.5060582756996155, 'jupyter', 0)] | 11 | 5 | null | 5.35 | 45 | 43 | 7 | 0 | 16 | 28 | 16 | 45 | 33 | 90 | 0.7 | 46 |
998 | finance | https://github.com/quantopian/zipline | [] | null | [] | [] | null | null | null | quantopian/zipline | zipline | 16,792 | 4,710 | 1,000 | Python | https://www.zipline.io | Zipline, a Pythonic Algorithmic Trading Library | quantopian | 2024-01-14 | 2012-10-19 | 588 | 28.530097 | https://avatars.githubusercontent.com/u/1393215?v=4 | Zipline, a Pythonic Algorithmic Trading Library | ['algorithmic-trading', 'quant', 'zipline'] | ['algorithmic-trading', 'quant', 'zipline'] | 2020-10-14 | [('gbeced/pyalgotrade', 0.8662933707237244, 'finance', 0), ('quantconnect/lean', 0.6676159501075745, 'finance', 0), ('robcarver17/pysystemtrade', 0.6582158803939819, 'finance', 0), ('gbeced/basana', 0.6551344394683838, 'finance', 1), ('ranaroussi/quantstats', 0.5925479531288147, 'finance', 2), ('cuemacro/finmarketpy', 0.5911790132522583, 'finance', 0), ('goldmansachs/gs-quant', 0.5875362753868103, 'finance', 0), ('cuemacro/findatapy', 0.5615792870521545, 'finance', 0), ('mementum/backtrader', 0.5593721866607666, 'finance', 0), ('quantecon/quantecon.py', 0.5450539588928223, 'sim', 0), ('keon/algorithms', 0.5438115000724792, 'util', 0), ('kernc/backtesting.py', 0.540707528591156, 'finance', 1), ('ta-lib/ta-lib-python', 0.5401220321655273, 'finance', 0), ('pmorissette/ffn', 0.5246074199676514, 'finance', 0), ('primal100/pybitcointools', 0.5228780508041382, 'crypto', 0), ('zvtvz/zvt', 0.5200475454330444, 'finance', 2), ('sympy/sympy', 0.5198596119880676, 'math', 0), ('polakowo/vectorbt', 0.519047737121582, 'finance', 1), ('pytoolz/toolz', 0.5173577070236206, 'util', 0), ('erotemic/ubelt', 0.5161089897155762, 'util', 0), ('1200wd/bitcoinlib', 0.5117334723472595, 'crypto', 0), ('hydrosquall/tiingo-python', 0.5056824684143066, 'finance', 0), ('linkedin/shiv', 0.5038162469863892, 'util', 0), ('scipy/scipy', 0.5005958080291748, 'math', 0), ('thealgorithms/python', 0.5000721216201782, 'study', 0)] | 160 | 5 | null | 0 | 3 | 0 | 137 | 40 | 0 | 2 | 2 | 3 | 1 | 90 | 0.3 | 45 |
540 | ml | https://github.com/aleju/imgaug | [] | null | [] | [] | null | null | null | aleju/imgaug | imgaug | 13,972 | 2,422 | 232 | Python | http://imgaug.readthedocs.io | Image augmentation for machine learning experiments. | aleju | 2024-01-12 | 2015-07-10 | 446 | 31.287268 | null | Image augmentation for machine learning experiments. | ['affine-transformation', 'augment-images', 'augmentation', 'bounding-boxes', 'contrast', 'crop', 'deep-learning', 'heatmap', 'image-augmentation', 'images', 'keypoints', 'machine-learning', 'polygon', 'segmentation-maps'] | ['affine-transformation', 'augment-images', 'augmentation', 'bounding-boxes', 'contrast', 'crop', 'deep-learning', 'heatmap', 'image-augmentation', 'images', 'keypoints', 'machine-learning', 'polygon', 'segmentation-maps'] | 2020-06-01 | [('mdbloice/augmentor', 0.7141932845115662, 'ml', 3), ('albumentations-team/albumentations', 0.6503161787986755, 'ml-dl', 4), ('fepegar/torchio', 0.5931549072265625, 'ml-dl', 3), ('roboflow/supervision', 0.5748479962348938, 'ml', 2), ('facebookresearch/augly', 0.5716978311538696, 'data', 0), ('lutzroeder/netron', 0.5660139322280884, 'ml', 2), ('makcedward/nlpaug', 0.5599479079246521, 'nlp', 2), ('microsoft/torchgeo', 0.5551947355270386, 'gis', 1), ('awslabs/autogluon', 0.5523484349250793, 'ml', 2), ('open-mmlab/mmediting', 0.5496745109558105, 'ml', 1), ('neuralmagic/sparseml', 0.5411894917488098, 'ml-dl', 0), ('huggingface/datasets', 0.5358902812004089, 'nlp', 2), ('rwightman/pytorch-image-models', 0.5356476902961731, 'ml-dl', 0), ('open-mmlab/mmsegmentation', 0.5349984169006348, 'ml', 0), ('onnx/onnx', 0.5340151786804199, 'ml', 2), ('developmentseed/label-maker', 0.5313600897789001, 'gis', 1), ('mosaicml/composer', 0.517113983631134, 'ml-dl', 2), ('deci-ai/super-gradients', 0.5129750370979309, 'ml-dl', 1), ('lightly-ai/lightly', 0.5071452260017395, 'ml', 2), ('keras-team/keras-cv', 0.5068478584289551, 'ml-dl', 0), ('kevinmusgrave/pytorch-metric-learning', 0.506173312664032, 'ml', 2), ('ddbourgin/numpy-ml', 0.5041775107383728, 'ml', 1)] | 36 | 6 | null | 0 | 2 | 2 | 104 | 44 | 0 | 2 | 2 | 2 | 1 | 90 | 0.5 | 45 |
281 | util | https://github.com/arrow-py/arrow | [] | null | [] | [] | null | null | null | arrow-py/arrow | arrow | 8,455 | 689 | 135 | Python | https://arrow.readthedocs.io | 🏹 Better dates & times for Python | arrow-py | 2024-01-12 | 2012-11-18 | 584 | 14.47066 | https://avatars.githubusercontent.com/u/68518399?v=4 | 🏹 Better dates & times for Python | ['arrow', 'date', 'datetime', 'time', 'timestamp', 'timezones'] | ['arrow', 'date', 'datetime', 'time', 'timestamp', 'timezones'] | 2023-09-30 | [('sdispater/pendulum', 0.7535154819488525, 'util', 4), ('dateutil/dateutil', 0.7106708884239197, 'util', 3), ('scrapinghub/dateparser', 0.5817139744758606, 'util', 2), ('stub42/pytz', 0.5504962205886841, 'util', 0), ('spulec/freezegun', 0.5130565166473389, 'testing', 0)] | 270 | 4 | null | 0.12 | 7 | 0 | 136 | 4 | 1 | 5 | 1 | 7 | 8 | 90 | 1.1 | 45 |
777 | diffusion | https://github.com/xavierxiao/dreambooth-stable-diffusion | [] | null | [] | [] | null | null | null | xavierxiao/dreambooth-stable-diffusion | Dreambooth-Stable-Diffusion | 7,295 | 775 | 95 | Jupyter Notebook | null | Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion | xavierxiao | 2024-01-13 | 2022-09-06 | 73 | 99.931507 | null | Implementation of Dreambooth (https://arxiv.org/abs/2208.12242) with Stable Diffusion | ['pytorch', 'pytorch-lightning', 'stable-diffusion', 'text-to-image'] | ['pytorch', 'pytorch-lightning', 'stable-diffusion', 'text-to-image'] | 2022-09-21 | [('carson-katri/dream-textures', 0.5931910872459412, 'diffusion', 1), ('automatic1111/stable-diffusion-webui', 0.5680199861526489, 'diffusion', 2), ('ashawkey/stable-dreamfusion', 0.5586757659912109, 'diffusion', 1), ('huggingface/diffusers', 0.5447068810462952, 'diffusion', 2), ('comfyanonymous/comfyui', 0.5401220321655273, 'diffusion', 2)] | 1 | 1 | null | 0 | 8 | 0 | 16 | 16 | 0 | 0 | 0 | 8 | 6 | 90 | 0.8 | 45 |
134 | ml | https://github.com/hyperopt/hyperopt | [] | null | [] | [] | null | null | null | hyperopt/hyperopt | hyperopt | 6,976 | 1,073 | 126 | Python | http://hyperopt.github.io/hyperopt | Distributed Asynchronous Hyperparameter Optimization in Python | hyperopt | 2024-01-13 | 2011-09-06 | 647 | 10.782071 | https://avatars.githubusercontent.com/u/5280805?v=4 | Distributed Asynchronous Hyperparameter Optimization in Python | [] | [] | 2023-09-29 | [('optuna/optuna', 0.7380708456039429, 'ml', 0), ('kubeflow/katib', 0.6022725701332092, 'ml', 0), ('google/vizier', 0.5750223994255066, 'ml', 0), ('samuelcolvin/arq', 0.5642699599266052, 'data', 0), ('baruchel/tco', 0.5423157215118408, 'perf', 0), ('scikit-optimize/scikit-optimize', 0.5412236452102661, 'ml', 0), ('determined-ai/determined', 0.5405532121658325, 'ml-ops', 0), ('dask/dask', 0.5399159789085388, 'perf', 0), ('klen/py-frameworks-bench', 0.5207222700119019, 'perf', 0), ('ipython/ipyparallel', 0.5190962553024292, 'perf', 0), ('joblib/joblib', 0.5118980407714844, 'util', 0), ('python-trio/trio', 0.510098934173584, 'perf', 0), ('geeogi/async-python-lambda-template', 0.5066941976547241, 'template', 0), ('alirn76/panther', 0.5043962597846985, 'web', 0)] | 102 | 5 | null | 0.44 | 75 | 50 | 150 | 5 | 0 | 1 | 1 | 75 | 49 | 90 | 0.7 | 45 |
681 | util | https://github.com/bndr/pipreqs | [] | null | [] | [] | null | null | null | bndr/pipreqs | pipreqs | 5,580 | 367 | 56 | Python | null | pipreqs - Generate pip requirements.txt file based on imports of any project. Looking for maintainers to move this project forward. | bndr | 2024-01-13 | 2015-04-22 | 457 | 12.187207 | null | pipreqs - Generate pip requirements.txt file based on imports of any project. Looking for maintainers to move this project forward. | [] | [] | 2023-10-08 | [('thoth-station/micropipenv', 0.625019907951355, 'util', 0), ('pypa/pipenv', 0.550599217414856, 'util', 0), ('pdm-project/pdm', 0.5109939575195312, 'util', 0), ('pomponchik/instld', 0.5049751996994019, 'util', 0)] | 60 | 2 | null | 0.23 | 42 | 22 | 106 | 3 | 2 | 3 | 2 | 42 | 76 | 90 | 1.8 | 45 |
1,673 | data | https://github.com/madmaze/pytesseract | ['ocr'] | null | [] | [] | null | null | null | madmaze/pytesseract | pytesseract | 5,291 | 717 | 107 | Python | null | A Python wrapper for Google Tesseract | madmaze | 2024-01-13 | 2010-10-27 | 691 | 7.647533 | null | A Python wrapper for Google Tesseract | [] | ['ocr'] | 2024-01-10 | [('rapidai/rapidocr', 0.5656213164329529, 'data', 1), ('jaidedai/easyocr', 0.5150726437568665, 'data', 1), ('hrnet/hrnet-semantic-segmentation', 0.5132443308830261, 'ml', 0)] | 45 | 2 | null | 0.96 | 13 | 9 | 161 | 0 | 3 | 2 | 3 | 13 | 28 | 90 | 2.2 | 45 |
264 | util | https://github.com/pytransitions/transitions | [] | null | [] | [] | null | null | null | pytransitions/transitions | transitions | 5,203 | 519 | 92 | Python | null | A lightweight, object-oriented finite state machine implementation in Python with many extensions | pytransitions | 2024-01-14 | 2014-10-12 | 485 | 10.721519 | https://avatars.githubusercontent.com/u/26332704?v=4 | A lightweight, object-oriented finite state machine implementation in Python with many extensions | ['hierarchical-state-machine', 'nested-states', 'state-diagram', 'state-machine'] | ['hierarchical-state-machine', 'nested-states', 'state-diagram', 'state-machine'] | 2023-09-20 | [('artemyk/dynpy', 0.55495285987854, 'sim', 0), ('pyston/pyston', 0.5525701642036438, 'util', 0), ('sympy/sympy', 0.523476243019104, 'math', 0), ('ethereum/py-evm', 0.5112031698226929, 'crypto', 0), ('citadel-ai/langcheck', 0.5025991201400757, 'llm', 0)] | 76 | 6 | null | 0.48 | 7 | 3 | 113 | 4 | 0 | 5 | 5 | 7 | 7 | 90 | 1 | 45 |
311 | util | https://github.com/indygreg/pyoxidizer | ['package-manager', 'packaging'] | null | [] | [] | null | null | null | indygreg/pyoxidizer | PyOxidizer | 5,016 | 212 | 62 | Rust | null | A modern Python application packaging and distribution tool | indygreg | 2024-01-13 | 2018-12-18 | 267 | 18.786517 | null | A modern Python application packaging and distribution tool | [] | ['package-manager', 'packaging'] | 2023-01-21 | [('pypa/flit', 0.8746299147605896, 'util', 2), ('mitsuhiko/rye', 0.8726885914802551, 'util', 2), ('python-poetry/poetry', 0.8143705725669861, 'util', 2), ('pdm-project/pdm', 0.7249577045440674, 'util', 2), ('pomponchik/instld', 0.7080777883529663, 'util', 1), ('regebro/pyroma', 0.7064893245697021, 'util', 1), ('pypa/hatch', 0.7048346400260925, 'util', 2), ('mamba-org/mamba', 0.6980676651000977, 'util', 2), ('pyodide/micropip', 0.6752342581748962, 'util', 0), ('pypi/warehouse', 0.6707281470298767, 'util', 0), ('ofek/pyapp', 0.6547517776489258, 'util', 1), ('beeware/briefcase', 0.6296486258506775, 'util', 0), ('pypa/pipenv', 0.6146742701530457, 'util', 1), ('conda/conda', 0.5986080169677734, 'util', 2), ('jazzband/pip-tools', 0.5879077315330505, 'util', 1), ('pypa/installer', 0.5681904554367065, 'util', 0), ('tezromach/python-package-template', 0.5635542273521423, 'template', 0), ('spack/spack', 0.5544406771659851, 'util', 1), ('tiangolo/poetry-version-plugin', 0.5493191480636597, 'util', 1), ('dosisod/refurb', 0.5480595827102661, 'util', 0), ('pytables/pytables', 0.5478392839431763, 'data', 0), ('omry/omegaconf', 0.5404947400093079, 'util', 0), ('mamba-org/gator', 0.5344242453575134, 'jupyter', 0), ('pypa/gh-action-pypi-publish', 0.5328114628791809, 'util', 0), ('pyinstaller/pyinstaller', 0.5304632782936096, 'util', 0), ('pympler/pympler', 0.5277453064918518, 'perf', 0), ('linkedin/shiv', 0.5276411175727844, 'util', 0), ('grahamdumpleton/wrapt', 0.5274959206581116, 'util', 0), ('hoffstadt/dearpygui', 0.5257773995399475, 'gui', 0), ('malloydata/malloy-py', 0.5247126221656799, 'data', 0), ('python-injector/injector', 0.5219050645828247, 'util', 0), ('beeware/toga', 0.5212326645851135, 'gui', 0), ('conda/conda-pack', 0.5181369781494141, 'util', 0), ('mgedmin/check-manifest', 0.5157642364501953, 'util', 0), ('bottlepy/bottle', 0.514263391494751, 'web', 0), ('thoth-station/micropipenv', 0.513746976852417, 'util', 0), ('pyscaffold/pyscaffold', 0.5098890662193298, 'template', 0), ('urwid/urwid', 0.5094347596168518, 'term', 0), ('ethtx/ethtx', 0.5071747303009033, 'crypto', 0), ('eleutherai/pyfra', 0.503706157207489, 'ml', 0), ('pallets/flask', 0.5036942958831787, 'web', 0), ('lukasschwab/arxiv.py', 0.5008288621902466, 'util', 0), ('conda/conda-build', 0.5000386834144592, 'util', 0)] | 54 | 3 | null | 0 | 21 | 3 | 62 | 12 | 0 | 72 | 72 | 21 | 11 | 90 | 0.5 | 45 |
536 | nlp | https://github.com/salesforce/codegen | [] | null | [] | [] | null | null | null | salesforce/codegen | CodeGen | 4,596 | 353 | 77 | Python | null | CodeGen is a family of open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex. | salesforce | 2024-01-13 | 2022-03-28 | 96 | 47.803863 | https://avatars.githubusercontent.com/u/453694?v=4 | CodeGen is a family of open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex. | ['codex', 'generativemodel', 'languagemodel', 'llm', 'programsynthesis', 'tpu-acceleration'] | ['codex', 'generativemodel', 'languagemodel', 'llm', 'programsynthesis', 'tpu-acceleration'] | 2023-11-21 | [('salesforce/codet5', 0.6593608856201172, 'nlp', 0), ('thudm/codegeex', 0.6133092045783997, 'llm', 0), ('bigcode-project/starcoder', 0.601254940032959, 'llm', 0), ('openai/image-gpt', 0.5758861303329468, 'llm', 0), ('ravenscroftj/turbopilot', 0.5407807230949402, 'llm', 0), ('conceptofmind/toolformer', 0.5336177945137024, 'llm', 0), ('microsoft/pycodegpt', 0.5231809020042419, 'llm', 0), ('lupantech/chameleon-llm', 0.5142695307731628, 'llm', 1), ('next-gpt/next-gpt', 0.5129567384719849, 'llm', 1), ('pytorch/glow', 0.5098628997802734, 'ml', 0), ('modularml/mojo', 0.5068298578262329, 'util', 0), ('ludwig-ai/ludwig', 0.5055090188980103, 'ml-ops', 1)] | 10 | 2 | null | 0.65 | 5 | 1 | 22 | 2 | 0 | 0 | 0 | 5 | 2 | 90 | 0.4 | 45 |
146 | ml | https://github.com/nmslib/hnswlib | [] | null | [] | [] | null | null | null | nmslib/hnswlib | hnswlib | 3,773 | 593 | 64 | C++ | https://github.com/nmslib/hnswlib | Header-only C++/python library for fast approximate nearest neighbors | nmslib | 2024-01-13 | 2017-07-06 | 342 | 11.00917 | https://avatars.githubusercontent.com/u/37882366?v=4 | Header-only C++/python library for fast approximate nearest neighbors | [] | [] | 2023-12-03 | [('spotify/annoy', 0.7858440279960632, 'ml', 0), ('lmcinnes/pynndescent', 0.6369488835334778, 'ml', 0), ('spotify/voyager', 0.5946098566055298, 'ml', 0), ('pyston/pyston', 0.5059448480606079, 'util', 0), ('facebookresearch/faiss', 0.5014215111732483, 'ml', 0)] | 72 | 4 | null | 0.65 | 30 | 11 | 79 | 1 | 2 | 2 | 2 | 30 | 28 | 90 | 0.9 | 45 |
758 | diffusion | https://github.com/lkwq007/stablediffusion-infinity | [] | null | [] | [] | null | null | null | lkwq007/stablediffusion-infinity | stablediffusion-infinity | 3,732 | 295 | 41 | Python | null | Outpainting with Stable Diffusion on an infinite canvas | lkwq007 | 2024-01-14 | 2022-09-02 | 73 | 50.726214 | null | Outpainting with Stable Diffusion on an infinite canvas | ['gui', 'inpainting', 'outpainting', 'stable-diffusion', 'stablediffusion'] | ['gui', 'inpainting', 'outpainting', 'stable-diffusion', 'stablediffusion'] | 2023-01-24 | [('carson-katri/dream-textures', 0.5580441951751709, 'diffusion', 1), ('sanster/lama-cleaner', 0.5446968078613281, 'ml-dl', 2), ('timothybrooks/instruct-pix2pix', 0.5145807266235352, 'diffusion', 0), ('jina-ai/discoart', 0.5142841935157776, 'diffusion', 1), ('comfyanonymous/comfyui', 0.5033169388771057, 'diffusion', 2)] | 7 | 2 | null | 0.13 | 4 | 0 | 17 | 12 | 0 | 2 | 2 | 4 | 3 | 90 | 0.8 | 45 |
1,169 | llm | https://github.com/instruction-tuning-with-gpt-4/gpt-4-llm | [] | null | [] | [] | null | null | null | instruction-tuning-with-gpt-4/gpt-4-llm | GPT-4-LLM | 3,721 | 272 | 44 | HTML | https://instruction-tuning-with-gpt-4.github.io/ | Instruction Tuning with GPT-4 | instruction-tuning-with-gpt-4 | 2024-01-14 | 2023-04-06 | 42 | 87.113712 | null | Instruction Tuning with GPT-4 | ['alpaca', 'chatgpt', 'gpt-4', 'instruction-tuning', 'llama'] | ['alpaca', 'chatgpt', 'gpt-4', 'instruction-tuning', 'llama'] | 2023-06-11 | [('declare-lab/instruct-eval', 0.653624415397644, 'llm', 0), ('haotian-liu/llava', 0.6272305250167847, 'llm', 4), ('farizrahman4u/loopgpt', 0.5821303129196167, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5739951133728027, 'llm', 2), ('hiyouga/llama-factory', 0.5739949345588684, 'llm', 2), ('tiger-ai-lab/mammoth', 0.5739008784294128, 'llm', 1), ('zrrskywalker/llama-adapter', 0.5689181685447693, 'llm', 2), ('tloen/alpaca-lora', 0.5178021788597107, 'llm', 1)] | 7 | 3 | null | 0.63 | 0 | 0 | 9 | 7 | 0 | 0 | 0 | 0 | 0 | 90 | 0 | 45 |
259 | util | https://github.com/python-markdown/markdown | [] | null | [] | [] | null | null | null | python-markdown/markdown | markdown | 3,472 | 865 | 76 | Python | https://python-markdown.github.io/ | A Python implementation of John Gruber’s Markdown with Extension support. | python-markdown | 2024-01-12 | 2010-05-29 | 713 | 4.86664 | https://avatars.githubusercontent.com/u/11278576?v=4 | A Python implementation of John Gruber’s Markdown with Extension support. | ['markdown', 'markdown-parser', 'markdown-to-html', 'python-markdown'] | ['markdown', 'markdown-parser', 'markdown-to-html', 'python-markdown'] | 2024-01-10 | [('getpelican/pelican', 0.6716626882553101, 'web', 0), ('hhatto/autopep8', 0.5607690811157227, 'util', 0), ('google/yapf', 0.5518056154251099, 'util', 0), ('mwouts/jupytext', 0.5461102724075317, 'jupyter', 1), ('google/latexify_py', 0.5334113240242004, 'util', 0), ('pygments/pygments', 0.5284628868103027, 'util', 0), ('roniemartinez/dude', 0.5186324715614319, 'util', 0), ('pytoolz/toolz', 0.5181722640991211, 'util', 0), ('connorferster/handcalcs', 0.5013054609298706, 'jupyter', 0), ('feincms/feincms', 0.500464141368866, 'web', 0)] | 173 | 2 | null | 0.87 | 49 | 40 | 166 | 0 | 2 | 4 | 2 | 48 | 167 | 90 | 3.5 | 45 |
360 | ml-ops | https://github.com/polyaxon/polyaxon | [] | null | [] | [] | null | null | null | polyaxon/polyaxon | polyaxon | 3,432 | 321 | 79 | null | https://polyaxon.com | MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle | polyaxon | 2024-01-12 | 2016-12-26 | 370 | 9.272096 | https://avatars.githubusercontent.com/u/24544827?v=4 | MLOps Tools For Managing & Orchestrating The Machine Learning LifeCycle | ['artificial-intelligence', 'caffe', 'data-science', 'deep-learning', 'hyperparameter-optimization', 'jupyter', 'jupyterlab', 'k8s', 'keras', 'kubernetes', 'machine-learning', 'ml', 'mlops', 'mxnet', 'notebook', 'pipelines', 'pytorch', 'reinforcement-learning', 'tensorflow', 'workflow'] | ['artificial-intelligence', 'caffe', 'data-science', 'deep-learning', 'hyperparameter-optimization', 'jupyter', 'jupyterlab', 'k8s', 'keras', 'kubernetes', 'machine-learning', 'ml', 'mlops', 'mxnet', 'notebook', 'pipelines', 'pytorch', 'reinforcement-learning', 'tensorflow', 'workflow'] | 2024-01-12 | [('kubeflow/pipelines', 0.7241019010543823, 'ml-ops', 4), ('mlflow/mlflow', 0.7237421870231628, 'ml-ops', 2), ('bentoml/bentoml', 0.70576012134552, 'ml-ops', 4), ('netflix/metaflow', 0.6915358901023865, 'ml-ops', 5), ('onnx/onnx', 0.6912744641304016, 'ml', 7), ('fmind/mlops-python-package', 0.6891217231750488, 'template', 2), ('bodywork-ml/bodywork-core', 0.6861110925674438, 'ml-ops', 4), ('feast-dev/feast', 0.6851301193237305, 'ml-ops', 4), ('microsoft/nni', 0.6834843754768372, 'ml', 7), ('flyteorg/flyte', 0.6784146428108215, 'ml-ops', 5), ('determined-ai/determined', 0.6687636971473694, 'ml-ops', 9), ('wandb/client', 0.6643576622009277, 'ml', 9), ('zenml-io/zenml', 0.6621537804603577, 'ml-ops', 9), ('allegroai/clearml', 0.6574744582176208, 'ml-ops', 4), ('unionai-oss/unionml', 0.6547122597694397, 'ml-ops', 2), ('huggingface/datasets', 0.6493980884552002, 'nlp', 4), ('skypilot-org/skypilot', 0.6188631057739258, 'llm', 3), ('merantix-momentum/squirrel-core', 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'ml-dl', 2), ('xplainable/xplainable', 0.5472549796104431, 'ml-interpretability', 2), ('ray-project/ray', 0.5454540252685547, 'ml-ops', 7), ('unity-technologies/ml-agents', 0.5450904965400696, 'ml-rl', 3), ('explosion/thinc', 0.5428985357284546, 'ml-dl', 6), ('nvidia/deeplearningexamples', 0.5416098833084106, 'ml-dl', 4), ('aws/sagemaker-python-sdk', 0.5382318496704102, 'ml', 4), ('hpcaitech/colossalai', 0.5358098745346069, 'llm', 1), ('google/mediapipe', 0.5345292091369629, 'ml', 2), ('mosaicml/composer', 0.5328403115272522, 'ml-dl', 3), ('titanml/takeoff', 0.5318194031715393, 'llm', 0), ('featureform/embeddinghub', 0.5308116674423218, 'nlp', 4), ('pytorchlightning/pytorch-lightning', 0.529716968536377, 'ml-dl', 5), ('evidentlyai/evidently', 0.5295282006263733, 'ml-ops', 3), ('google/vizier', 0.5294651389122009, 'ml', 3), ('whylabs/whylogs', 0.5290948152542114, 'util', 3), ('backtick-se/cowait', 0.5269318222999573, 'util', 2), ('districtdatalabs/yellowbrick', 0.5260629653930664, 'ml', 1), ('pythagora-io/gpt-pilot', 0.5244739055633545, 'llm', 0), ('deepmind/dm_control', 0.5232641100883484, 'ml-rl', 4), ('keras-team/autokeras', 0.5219746232032776, 'ml-dl', 4), ('microsoft/deepspeed', 0.5181537866592407, 'ml-dl', 3), ('ludwig-ai/ludwig', 0.5176489949226379, 'ml-ops', 5), ('microsoft/lmops', 0.5171562433242798, 'llm', 0), ('keras-team/keras-nlp', 0.5162709355354309, 'nlp', 4), ('pydoit/doit', 0.5158570408821106, 'util', 2), ('meltano/meltano', 0.5144167542457581, 'ml-ops', 1), ('epistasislab/tpot', 0.5143507122993469, 'ml', 3), ('huggingface/transformers', 0.5142974257469177, 'nlp', 4), ('cheshire-cat-ai/core', 0.512060284614563, 'llm', 0), ('csinva/imodels', 0.5118154883384705, 'ml', 4), ('nevronai/metisfl', 0.5108596682548523, 'ml', 3), ('bentoml/openllm', 0.5105753540992737, 'ml-ops', 2), ('selfexplainml/piml-toolbox', 0.5091049075126648, 'ml-interpretability', 0), ('chaostoolkit/chaostoolkit', 0.5090064406394958, 'util', 0), ('uber/fiber', 0.5087381601333618, 'data', 1), ('zenml-io/mlstacks', 0.5073304176330566, 'ml-ops', 2), ('eventual-inc/daft', 0.5069470405578613, 'pandas', 3), ('awslabs/autogluon', 0.5069301724433899, 'ml', 5), ('pathwaycom/pathway', 0.5067856311798096, 'data', 0), ('lucidrains/toolformer-pytorch', 0.5062516927719116, 'llm', 2), ('tensorflow/tensor2tensor', 0.5061532258987427, 'ml', 3), ('kedro-org/kedro', 0.5058719515800476, 'ml-ops', 2), ('neuralmagic/deepsparse', 0.504664957523346, 'nlp', 0), ('towhee-io/towhee', 0.5038055181503296, 'ml-ops', 1), ('spack/spack', 0.5023648738861084, 'util', 0), ('giskard-ai/giskard', 0.5021538734436035, 'data', 3), ('lastmile-ai/aiconfig', 0.5021164417266846, 'util', 0), ('keras-rl/keras-rl', 0.5010080337524414, 'ml-rl', 4), ('superduperdb/superduperdb', 0.5004454851150513, 'data', 3), ('microsoft/flaml', 0.5002272129058838, 'ml', 4)] | 98 | 3 | null | 3.77 | 3 | 1 | 86 | 0 | 0 | 29 | 29 | 3 | 1 | 90 | 0.3 | 45 |
35 | data | https://github.com/jmcnamara/xlsxwriter | [] | null | [] | [] | null | null | null | jmcnamara/xlsxwriter | XlsxWriter | 3,402 | 624 | 118 | Python | https://xlsxwriter.readthedocs.io | A Python module for creating Excel XLSX files. | jmcnamara | 2024-01-13 | 2013-01-04 | 577 | 5.890181 | null | A Python module for creating Excel XLSX files. | ['charts', 'libxlsxwriter', 'pandas', 'spreadsheet', 'xlsx', 'xlsx-files', 'xlsxwriter'] | ['charts', 'libxlsxwriter', 'pandas', 'spreadsheet', 'xlsx', 'xlsx-files', 'xlsxwriter'] | 2023-11-08 | [('zoomeranalytics/xlwings', 0.7553142309188843, 'data', 0), ('jazzband/tablib', 0.5911999344825745, 'data', 0), ('tkrabel/bamboolib', 0.5247606039047241, 'pandas', 1), ('connorferster/handcalcs', 0.5153928399085999, 'jupyter', 0), ('vizzuhq/ipyvizzu', 0.5122716426849365, 'jupyter', 1), ('holoviz/hvplot', 0.5030190348625183, 'pandas', 0), ('cuemacro/chartpy', 0.500167191028595, 'viz', 0)] | 52 | 2 | null | 1.31 | 27 | 19 | 134 | 2 | 0 | 15 | 15 | 27 | 87 | 90 | 3.2 | 45 |
365 | ml | https://github.com/facebookresearch/vissl | [] | null | [] | [] | null | null | null | facebookresearch/vissl | vissl | 3,180 | 328 | 53 | Jupyter Notebook | https://vissl.ai | VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images. | facebookresearch | 2024-01-13 | 2020-04-09 | 198 | 16.002876 | https://avatars.githubusercontent.com/u/16943930?v=4 | VISSL is FAIR's library of extensible, modular and scalable components for SOTA Self-Supervised Learning with images. | [] | [] | 2024-01-05 | [('deci-ai/super-gradients', 0.6394485831260681, 'ml-dl', 0), ('lightly-ai/lightly', 0.6104288101196289, 'ml', 0), ('roboflow/notebooks', 0.5875295996665955, 'study', 0), ('google-research/maxvit', 0.5404923558235168, 'ml', 0), ('lucidrains/vit-pytorch', 0.5331419110298157, 'ml-dl', 0), ('paperswithcode/sota-extractor', 0.5020662546157837, 'data', 0)] | 37 | 5 | null | 0.19 | 2 | 0 | 46 | 0 | 0 | 1 | 1 | 2 | 2 | 90 | 1 | 45 |
654 | ml | https://github.com/pytorch/glow | [] | null | [] | [] | null | null | null | pytorch/glow | glow | 3,085 | 690 | 157 | C++ | null | Compiler for Neural Network hardware accelerators | pytorch | 2024-01-13 | 2017-09-29 | 330 | 9.332325 | https://avatars.githubusercontent.com/u/21003710?v=4 | Compiler for Neural Network hardware accelerators | [] | [] | 2024-01-09 | [('microsoft/onnxruntime', 0.6179055571556091, 'ml', 0), ('alpa-projects/alpa', 0.6077716946601868, 'ml-dl', 0), ('karpathy/micrograd', 0.6073175668716431, 'study', 0), ('intel/intel-extension-for-pytorch', 0.6005612015724182, 'perf', 0), ('exaloop/codon', 0.5580657720565796, 'perf', 0), ('microsoft/olive', 0.5527094006538391, 'ml', 0), ('plasma-umass/scalene', 0.5508031249046326, 'profiling', 0), ('facebookincubator/aitemplate', 0.542003870010376, 'ml-dl', 0), ('rasbt/machine-learning-book', 0.5354295372962952, 'study', 0), ('microsoft/deepspeed', 0.5229150652885437, 'ml-dl', 0), ('cython/cython', 0.5203021168708801, 'util', 0), ('pytorch/pytorch', 0.5188764929771423, 'ml-dl', 0), ('huggingface/optimum', 0.5153691172599792, 'ml', 0), ('neuralmagic/deepsparse', 0.514583945274353, 'nlp', 0), ('openai/triton', 0.5112419724464417, 'util', 0), ('salesforce/codegen', 0.5098628997802734, 'nlp', 0), ('fastai/fastcore', 0.509026288986206, 'util', 0), ('google/tf-quant-finance', 0.5075867772102356, 'finance', 0), ('denys88/rl_games', 0.5074953436851501, 'ml-rl', 0), ('bobazooba/xllm', 0.5073339343070984, 'llm', 0), ('pytorchlightning/pytorch-lightning', 0.5054729580879211, 'ml-dl', 0), ('skorch-dev/skorch', 0.5048933029174805, 'ml-dl', 0), ('determined-ai/determined', 0.5047574639320374, 'ml-ops', 0), ('intel/scikit-learn-intelex', 0.5033442378044128, 'perf', 0)] | 353 | 1 | null | 1.23 | 8 | 1 | 77 | 0 | 0 | 0 | 0 | 8 | 27 | 90 | 3.4 | 45 |
669 | diffusion | https://github.com/saharmor/dalle-playground | [] | null | [] | [] | null | null | null | saharmor/dalle-playground | dalle-playground | 2,751 | 603 | 32 | JavaScript | null | A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini) | saharmor | 2024-01-12 | 2021-09-13 | 124 | 22.159954 | null | A playground to generate images from any text prompt using Stable Diffusion (past: using DALL-E Mini) | ['artificial', 'artificial-intelligence', 'dall-e', 'dalle', 'dalle-mini', 'gan', 'machine-learning', 'openai', 'stable-diffusion', 'text-to-image', 'transformers'] | ['artificial', 'artificial-intelligence', 'dall-e', 'dalle', 'dalle-mini', 'gan', 'machine-learning', 'openai', 'stable-diffusion', 'text-to-image', 'transformers'] | 2023-12-29 | [('borisdayma/dalle-mini', 0.7689334750175476, 'diffusion', 0), ('nateraw/stable-diffusion-videos', 0.671584963798523, 'diffusion', 2), ('fourthbrain/fastapi-for-machine-learning-live-demo', 0.6557318568229675, 'web', 1), ('lucidrains/deep-daze', 0.6547111868858337, 'ml', 3), ('automatic1111/stable-diffusion-webui', 0.6440442204475403, 'diffusion', 1), ('compvis/stable-diffusion', 0.6419358253479004, 'diffusion', 0), ('sharonzhou/long_stable_diffusion', 0.6195039749145508, 'diffusion', 0), ('invoke-ai/invokeai', 0.6060563921928406, 'diffusion', 2), ('openai/glide-text2im', 0.6006641387939453, 'diffusion', 0), ('lucidrains/imagen-pytorch', 0.5938807725906372, 'ml-dl', 2), ('lucidrains/dalle2-pytorch', 0.5927163362503052, 'diffusion', 2), ('thereforegames/unprompted', 0.5805418491363525, 'diffusion', 1), ('promptslab/awesome-prompt-engineering', 0.5731377005577087, 'study', 3), ('laion-ai/dalle2-laion', 0.570446252822876, 'diffusion', 1), ('open-mmlab/mmediting', 0.5508294105529785, 'ml', 0), ('huggingface/diffusers', 0.539817750453949, 'diffusion', 1), ('thudm/cogvideo', 0.529645562171936, 'ml', 0), ('openai/clip', 0.5254179239273071, 'ml-dl', 1), ('carson-katri/dream-textures', 0.5181798934936523, 'diffusion', 1), ('alibaba/easynlp', 0.5042204260826111, 'nlp', 2)] | 11 | 4 | null | 0.13 | 2 | 2 | 28 | 1 | 0 | 0 | 0 | 2 | 4 | 90 | 2 | 45 |
868 | study | https://github.com/rasbt/machine-learning-book | [] | null | [] | [] | null | null | null | rasbt/machine-learning-book | machine-learning-book | 2,524 | 923 | 45 | Jupyter Notebook | https://sebastianraschka.com/books/#machine-learning-with-pytorch-and-scikit-learn | Code Repository for Machine Learning with PyTorch and Scikit-Learn | rasbt | 2024-01-13 | 2021-12-19 | 110 | 22.88601 | null | Code Repository for Machine Learning with PyTorch and Scikit-Learn | ['deep-learning', 'machine-learning', 'neural-networks', 'pytorch', 'scikit-learn'] | ['deep-learning', 'machine-learning', 'neural-networks', 'pytorch', 'scikit-learn'] | 2023-12-27 | [('skorch-dev/skorch', 0.777802050113678, 'ml-dl', 3), ('intel/intel-extension-for-pytorch', 0.7345353960990906, 'perf', 3), ('pytorch/ignite', 0.7284553050994873, 'ml-dl', 3), ('mrdbourke/pytorch-deep-learning', 0.6849406957626343, 'study', 3), ('fchollet/deep-learning-with-python-notebooks', 0.6557565331459045, 'study', 0), 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1,793 | util | https://github.com/pyinfra-dev/pyinfra | [] | null | [] | [] | null | null | null | pyinfra-dev/pyinfra | pyinfra | 2,467 | 319 | 37 | Python | https://pyinfra.com | pyinfra automates infrastructure using Python. It’s fast and scales from one server to thousands. Great for ad-hoc command execution, service deployment, configuration management and more. | pyinfra-dev | 2024-01-13 | 2014-10-19 | 484 | 5.0941 | https://avatars.githubusercontent.com/u/146648081?v=4 | pyinfra automates infrastructure using Python. It’s fast and scales from one server to thousands. Great for ad-hoc command execution, service deployment, configuration management and more. | ['cloud-management', 'configuration-management', 'high-performance', 'infrastructure', 'pyinfra', 'remote-execution'] | ['cloud-management', 'configuration-management', 'high-performance', 'infrastructure', 'pyinfra', 'remote-execution'] | 2024-01-13 | [('willmcgugan/textual', 0.6321539878845215, 'term', 0), ('pypy/pypy', 0.6099465489387512, 'util', 0), ('backtick-se/cowait', 0.5932263135910034, 'util', 0), ('bottlepy/bottle', 0.590758204460144, 'web', 0), ('cython/cython', 0.5551347732543945, 'util', 0), ('pypa/hatch', 0.5454100966453552, 'util', 0), ('pallets/flask', 0.5409476161003113, 'web', 0), ('pallets/quart', 0.5390889048576355, 'web', 0), ('dddomodossola/remi', 0.5348232984542847, 'gui', 0), ('pytables/pytables', 0.5320051312446594, 'data', 0), ('micropython/micropython', 0.5298929214477539, 'util', 0), ('eventual-inc/daft', 0.5292609333992004, 'pandas', 0), ('eleutherai/pyfra', 0.5274806022644043, 'ml', 0), ('falconry/falcon', 0.5231207609176636, 'web', 0), ('hoffstadt/dearpygui', 0.5215190649032593, 'gui', 0), ('klen/py-frameworks-bench', 0.5210394263267517, 'perf', 0), ('nficano/python-lambda', 0.5205470323562622, 'util', 0), ('fastai/fastcore', 0.5203496217727661, 'util', 0), ('webpy/webpy', 0.5194896459579468, 'web', 0), ('masoniteframework/masonite', 0.5186633467674255, 'web', 0), ('aws/chalice', 0.5128588080406189, 'web', 0), ('pyodide/micropip', 0.5114571452140808, 'util', 0), ('pypa/pipenv', 0.5107925534248352, 'util', 0), ('flet-dev/flet', 0.5072339773178101, 'web', 0), ('neoteroi/blacksheep', 0.5058210492134094, 'web', 0), ('google/gin-config', 0.5022099614143372, 'util', 1), ('klen/muffin', 0.5019458532333374, 'web', 0)] | 104 | 5 | null | 1.31 | 61 | 25 | 112 | 0 | 4 | 22 | 4 | 61 | 52 | 90 | 0.9 | 45 |
585 | util | https://github.com/hgrecco/pint | [] | null | [] | [] | null | null | null | hgrecco/pint | pint | 2,171 | 492 | 41 | Python | http://pint.readthedocs.org/ | Operate and manipulate physical quantities in Python | hgrecco | 2024-01-12 | 2012-07-13 | 602 | 3.602892 | null | Operate and manipulate physical quantities in Python | ['science', 'units'] | ['science', 'units'] | 2024-01-03 | [('fredrik-johansson/mpmath', 0.5482094883918762, 'math', 0), ('numpy/numpy', 0.5478784441947937, 'math', 0), ('sympy/sympy', 0.534096896648407, 'math', 1), ('artemyk/dynpy', 0.5099499225616455, 'sim', 0), ('connorferster/handcalcs', 0.506892740726471, 'jupyter', 0)] | 208 | 3 | null | 3.29 | 80 | 28 | 140 | 0 | 0 | 4 | 4 | 80 | 169 | 90 | 2.1 | 45 |
1,872 | ml | https://github.com/freedmand/semantra | [] | Semantra is a multipurpose tool for semantically searching documents. Query by meaning rather than just by matching text. | [] | [] | null | null | null | freedmand/semantra | semantra | 2,152 | 117 | 31 | Python | null | Multi-tool for semantic search | freedmand | 2024-01-13 | 2023-03-31 | 43 | 49.390164 | null | Multi-tool for semantic search | ['cli', 'machine-learning', 'semantic-search'] | ['cli', 'machine-learning', 'semantic-search'] | 2023-12-16 | [('docarray/docarray', 0.5385406017303467, 'data', 2), ('nomic-ai/semantic-search-app-template', 0.5121299624443054, 'study', 1)] | 4 | 1 | null | 0.87 | 7 | 5 | 10 | 1 | 0 | 0 | 0 | 7 | 7 | 90 | 1 | 45 |
297 | finance | https://github.com/blankly-finance/blankly | [] | null | [] | [] | null | null | null | blankly-finance/blankly | blankly | 1,864 | 250 | 39 | Python | https://package.blankly.finance | 🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package. | blankly-finance | 2024-01-14 | 2021-03-09 | 151 | 12.344371 | https://avatars.githubusercontent.com/u/82687739?v=4 | 🚀 💸 Easily build, backtest and deploy your algo in just a few lines of code. Trade stocks, cryptos, and forex across exchanges w/ one package. | ['algotrading', 'binance', 'blankly', 'bot', 'bot-framework', 'bots', 'coinbase', 'crypto', 'cryptocurrency', 'framework', 'investment', 'platform', 'stocks', 'trading', 'trading-bot', 'trading-strategies'] | ['algotrading', 'binance', 'blankly', 'bot', 'bot-framework', 'bots', 'coinbase', 'crypto', 'cryptocurrency', 'framework', 'investment', 'platform', 'stocks', 'trading', 'trading-bot', 'trading-strategies'] | 2023-12-23 | [('ccxt/ccxt', 0.6164409518241882, 'crypto', 4), ('kernc/backtesting.py', 0.5919058918952942, 'finance', 5), ('gbeced/basana', 0.5776981711387634, 'finance', 3), ('freqtrade/freqtrade', 0.5714588165283203, 'crypto', 2), ('idanya/algo-trader', 0.5535969138145447, 'finance', 2), ('quantconnect/lean', 0.5336184501647949, 'finance', 3)] | 18 | 5 | null | 0.35 | 7 | 3 | 35 | 1 | 0 | 10 | 10 | 7 | 6 | 90 | 0.9 | 45 |
507 | ml | https://github.com/tensorflow/addons | [] | null | [] | [] | null | null | null | tensorflow/addons | addons | 1,680 | 612 | 58 | Python | null | Useful extra functionality for TensorFlow 2.x maintained by SIG-addons | tensorflow | 2024-01-09 | 2018-11-26 | 270 | 6.218932 | https://avatars.githubusercontent.com/u/15658638?v=4 | Useful extra functionality for TensorFlow 2.x maintained by SIG-addons | ['deep-learning', 'machine-learning', 'neural-network', 'tensorflow', 'tensorflow-addons'] | ['deep-learning', 'machine-learning', 'neural-network', 'tensorflow', 'tensorflow-addons'] | 2023-12-13 | [('arogozhnikov/einops', 0.6348954439163208, 'ml-dl', 2), ('intel/intel-extension-for-pytorch', 0.6045843958854675, 'perf', 3), ('blackhc/toma', 0.5717829465866089, 'ml-dl', 1), ('tlkh/tf-metal-experiments', 0.5677783489227295, 'perf', 2), ('nyandwi/modernconvnets', 0.567768931388855, 'ml-dl', 1), ('google/tf-quant-finance', 0.5670149326324463, 'finance', 1), ('tensorflow/similarity', 0.5603650212287903, 'ml-dl', 3), ('tensorly/tensorly', 0.5590072274208069, 'ml-dl', 2), ('danielegrattarola/spektral', 0.5564872026443481, 'ml-dl', 2), ('explosion/thinc', 0.5554784536361694, 'ml-dl', 3), ('microsoft/onnxruntime', 0.5536020994186401, 'ml', 3), ('neuralmagic/sparseml', 0.5490881204605103, 'ml-dl', 1), ('pytorch/pytorch', 0.5459487438201904, 'ml-dl', 3), ('xl0/lovely-tensors', 0.5444281697273254, 'ml-dl', 1), ('horovod/horovod', 0.5429335832595825, 'ml-ops', 3), ('huggingface/transformers', 0.5373498797416687, 'nlp', 3), ('lutzroeder/netron', 0.5334285497665405, 'ml', 4), ('ageron/handson-ml2', 0.5312256813049316, 'ml', 0), ('rafiqhasan/auto-tensorflow', 0.530368983745575, 'ml-dl', 2), ('nvidia/deeplearningexamples', 0.5303577780723572, 'ml-dl', 2), ('huggingface/datasets', 0.5287928581237793, 'nlp', 3), ('pytorch/ignite', 0.5261369943618774, 'ml-dl', 3), ('ggerganov/ggml', 0.525490939617157, 'ml', 1), ('tensorlayer/tensorlayer', 0.5212689638137817, 'ml-rl', 3), ('nvidia/tensorrt-llm', 0.5190548300743103, 'viz', 0), ('tensorflow/tensorflow', 0.5162330865859985, 'ml-dl', 4), ('onnx/onnx', 0.515902578830719, 'ml', 4), ('mdbloice/augmentor', 0.5146579742431641, 'ml', 2), ('keras-team/keras-nlp', 0.5104029178619385, 'nlp', 3), ('keras-team/keras', 0.5103944540023804, 'ml-dl', 3), ('ashleve/lightning-hydra-template', 0.5103277564048767, 'util', 1), ('determined-ai/determined', 0.5096710920333862, 'ml-ops', 3), ('google/gin-config', 0.5091912150382996, 'util', 1), ('dmlc/dgl', 0.5086209774017334, 'ml-dl', 1), ('google-research/deeplab2', 0.5076053738594055, 'ml', 0), ('ddbourgin/numpy-ml', 0.5075183510780334, 'ml', 1)] | 207 | 7 | null | 0.54 | 16 | 13 | 62 | 1 | 4 | 8 | 4 | 16 | 25 | 90 | 1.6 | 45 |
212 | data | https://github.com/sfu-db/connector-x | [] | null | [] | [] | 1 | null | null | sfu-db/connector-x | connector-x | 1,656 | 121 | 30 | Rust | https://sfu-db.github.io/connector-x/intro.html | Fastest library to load data from DB to DataFrames in Rust and Python | sfu-db | 2024-01-12 | 2021-01-13 | 158 | 10.42446 | https://avatars.githubusercontent.com/u/18023593?v=4 | Fastest library to load data from DB to DataFrames in Rust and Python | ['database', 'dataframe', 'rust', 'sql'] | ['database', 'dataframe', 'rust', 'sql'] | 2024-01-11 | [('pola-rs/polars', 0.6430513262748718, 'pandas', 2), ('delta-io/delta-rs', 0.5911102890968323, 'pandas', 1), ('ibis-project/ibis', 0.5806707143783569, 'data', 2), ('eventual-inc/daft', 0.5663425326347351, 'pandas', 2), ('tobymao/sqlglot', 0.5419861674308777, 'data', 1), ('jmcarpenter2/swifter', 0.5345582962036133, 'pandas', 0), ('tiangolo/sqlmodel', 0.5301145911216736, 'data', 1), ('klen/py-frameworks-bench', 0.5208754539489746, 'perf', 0), ('sqlalchemy/sqlalchemy', 0.5162760019302368, 'data', 1), ('samuelcolvin/rtoml', 0.5036177039146423, 'data', 1), ('mcfunley/pugsql', 0.5034618377685547, 'data', 1)] | 43 | 5 | null | 1.71 | 33 | 9 | 36 | 0 | 1 | 3 | 1 | 33 | 38 | 90 | 1.2 | 45 |
303 | nlp | https://github.com/featureform/embeddinghub | [] | null | [] | [] | null | null | null | featureform/embeddinghub | featureform | 1,627 | 91 | 14 | Jupyter Notebook | https://www.featureform.com | The Virtual Feature Store. Turn your existing data infrastructure into a feature store. | featureform | 2024-01-13 | 2020-10-16 | 171 | 9.482931 | https://avatars.githubusercontent.com/u/72954069?v=4 | The Virtual Feature Store. Turn your existing data infrastructure into a feature store. | ['data-quality', 'data-science', 'embeddings', 'embeddings-similarity', 'feature-engineering', 'feature-store', 'machine-learning', 'ml', 'mlops', 'vector-database'] | ['data-quality', 'data-science', 'embeddings', 'embeddings-similarity', 'feature-engineering', 'feature-store', 'machine-learning', 'ml', 'mlops', 'vector-database'] | 2023-12-15 | [('feast-dev/feast', 0.7385993599891663, 'ml-ops', 6), ('lancedb/lancedb', 0.6071080565452576, 'data', 1), ('activeloopai/deeplake', 0.6054278016090393, 'ml-ops', 5), ('superduperdb/superduperdb', 0.6010522246360779, 'data', 2), ('airbytehq/airbyte', 0.5929150581359863, 'data', 0), ('mage-ai/mage-ai', 0.5914458632469177, 'ml-ops', 2), ('dgarnitz/vectorflow', 0.5690073370933533, 'data', 2), ('streamlit/streamlit', 0.5492863059043884, 'viz', 2), ('jina-ai/vectordb', 0.549279510974884, 'data', 1), ('netflix/metaflow', 0.5473335981369019, 'ml-ops', 4), ('orchest/orchest', 0.5408744215965271, 'ml-ops', 2), ('polyaxon/polyaxon', 0.5308116674423218, 'ml-ops', 4), ('ploomber/ploomber', 0.529184103012085, 'ml-ops', 3), ('milvus-io/bootcamp', 0.5258285403251648, 'data', 2), ('avaiga/taipy', 0.5199906229972839, 'data', 1), ('meltano/meltano', 0.5155656337738037, 'ml-ops', 0), ('dagster-io/dagster', 0.512913703918457, 'ml-ops', 2), ('flyteorg/flyte', 0.5021466612815857, 'ml-ops', 3), ('huggingface/datasets', 0.5000424981117249, 'nlp', 1)] | 30 | 1 | null | 11.08 | 201 | 147 | 40 | 1 | 20 | 12 | 20 | 201 | 85 | 90 | 0.4 | 45 |
1,686 | perf | https://github.com/faster-cpython/ideas | ['cpython'] | Discussion and work tracker for Faster CPython project. | [] | [] | null | null | null | faster-cpython/ideas | ideas | 1,618 | 53 | 130 | null | null | null | faster-cpython | 2024-01-13 | 2021-03-02 | 152 | 10.644737 | https://avatars.githubusercontent.com/u/81193161?v=4 | Discussion and work tracker for Faster CPython project. | [] | ['cpython'] | 2024-01-03 | [('faster-cpython/tools', 0.8179801106452942, 'perf', 1), ('python/cpython', 0.7051501274108887, 'util', 1), ('brandtbucher/specialist', 0.6769110560417175, 'perf', 1), ('markshannon/faster-cpython', 0.6732155084609985, 'perf', 0), ('pypy/pypy', 0.6248586773872375, 'util', 1), ('p403n1x87/austin', 0.6115438938140869, 'profiling', 0), ('ipython/ipyparallel', 0.5969278216362, 'perf', 0), ('cohere-ai/notebooks', 0.5839570760726929, 'llm', 0), ('cython/cython', 0.5725173354148865, 'util', 1), ('facebookincubator/cinder', 0.5721518397331238, 'perf', 1), ('agronholm/apscheduler', 0.5676429867744446, 'util', 0), ('wxwidgets/phoenix', 0.563103973865509, 'gui', 0), ('pyston/pyston', 0.5621926188468933, 'util', 0), ('wesm/pydata-book', 0.5588380694389343, 'study', 0), ('scikit-build/scikit-build', 0.5575029253959656, 'ml', 1), ('fastai/fastcore', 0.5519487857818604, 'util', 0), ('ipython/ipython', 0.5474236607551575, 'util', 0), ('gotcha/ipdb', 0.5395191311836243, 'debug', 0), ('eleutherai/pyfra', 0.5366376042366028, 'ml', 0), ('pytorch/data', 0.5340155959129333, 'data', 0), ('reloadware/reloadium', 0.5288839936256409, 'profiling', 0), ('tqdm/tqdm', 0.5260686874389648, 'term', 0), ('rasbt/watermark', 0.5214296579360962, 'util', 0), ('hoffstadt/dearpygui', 0.5212865471839905, 'gui', 0), ('sumerc/yappi', 0.5191786289215088, 'profiling', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5187180638313293, 'study', 0), ('intel/intel-extension-for-pytorch', 0.5159723162651062, 'perf', 0), ('willmcgugan/textual', 0.5151427388191223, 'term', 0), ('alexmojaki/snoop', 0.5135080814361572, 'debug', 0), ('erotemic/ubelt', 0.5061014890670776, 'util', 0), ('allenai/allennlp', 0.5050787329673767, 'nlp', 0), ('mynameisfiber/high_performance_python_2e', 0.5015802979469299, 'study', 0), ('timofurrer/awesome-asyncio', 0.500760018825531, 'study', 0)] | 11 | 2 | null | 4.48 | 25 | 6 | 35 | 0 | 0 | 0 | 0 | 25 | 97 | 90 | 3.9 | 45 |
1,866 | data | https://github.com/rapidai/rapidocr | [] | null | [] | [] | null | null | null | rapidai/rapidocr | RapidOCR | 1,614 | 266 | 33 | Python | https://rapidai.github.io/RapidOCRDocs/docs/ | A cross platform OCR Library based on PaddleOCR & OnnxRuntime & OpenVINO. | rapidai | 2024-01-13 | 2021-01-04 | 160 | 10.078501 | https://avatars.githubusercontent.com/u/87350760?v=4 | A cross platform OCR Library based on PaddleOCR & OnnxRuntime & OpenVINO. | ['chineseocr', 'crnn', 'dbnet', 'easyocr', 'ocr', 'onnxruntime', 'openvino', 'paddleocr', 'rapidocr'] | ['chineseocr', 'crnn', 'dbnet', 'easyocr', 'ocr', 'onnxruntime', 'openvino', 'paddleocr', 'rapidocr'] | 2023-12-28 | [('jaidedai/easyocr', 0.6983810663223267, 'data', 3), ('hrnet/hrnet-semantic-segmentation', 0.5680984258651733, 'ml', 0), ('madmaze/pytesseract', 0.5656213164329529, 'data', 1), ('unstructured-io/pipeline-paddleocr', 0.5100756287574768, 'data', 1)] | 14 | 4 | null | 4.33 | 12 | 9 | 37 | 1 | 4 | 4 | 4 | 12 | 19 | 90 | 1.6 | 45 |
1,789 | web | https://github.com/indico/indico | [] | null | [] | [] | null | null | null | indico/indico | indico | 1,591 | 397 | 63 | Python | https://getindico.io | Indico - A feature-rich event management system, made @ CERN, the place where the Web was born. | indico | 2024-01-13 | 2011-07-27 | 652 | 2.43698 | https://avatars.githubusercontent.com/u/715236?v=4 | Indico - A feature-rich event management system, made @ CERN, the place where the Web was born. | ['conferences', 'events', 'flask', 'sqlalchemy'] | ['conferences', 'events', 'flask', 'sqlalchemy'] | 2024-01-11 | [('masoniteframework/masonite', 0.5639700293540955, 'web', 0), ('pallets/flask', 0.5564385056495667, 'web', 1), ('bottlepy/bottle', 0.5327122211456299, 'web', 0), ('brettkromkamp/contextualise', 0.5198062658309937, 'data', 0), ('django/django', 0.514659583568573, 'web', 0), ('dylanhogg/awesome-python', 0.5107914209365845, 'study', 0), ('wagtail/wagtail', 0.5091932415962219, 'web', 0), ('klen/muffin', 0.5037544369697571, 'web', 0), ('emmett-framework/emmett', 0.5001763701438904, 'web', 0), ('feincms/feincms', 0.5001288652420044, 'web', 0)] | 142 | 5 | null | 9.62 | 181 | 120 | 152 | 0 | 6 | 10 | 6 | 181 | 266 | 90 | 1.5 | 45 |
1,718 | util | https://github.com/codespell-project/codespell | ['code-quality'] | null | [] | [] | null | null | null | codespell-project/codespell | codespell | 1,590 | 470 | 24 | Python | null | check code for common misspellings | codespell-project | 2024-01-14 | 2011-01-28 | 678 | 2.343158 | https://avatars.githubusercontent.com/u/39140587?v=4 | check code for common misspellings | [] | ['code-quality'] | 2024-01-13 | [] | 188 | 5 | null | 8.06 | 188 | 147 | 158 | 0 | 4 | 3 | 4 | 188 | 287 | 90 | 1.5 | 45 |
263 | data | https://github.com/collerek/ormar | [] | null | [] | [] | null | null | null | collerek/ormar | ormar | 1,506 | 78 | 17 | Python | https://collerek.github.io/ormar/ | python async orm with fastapi in mind and pydantic validation | collerek | 2024-01-13 | 2020-08-02 | 182 | 8.261755 | null | python async orm with fastapi in mind and pydantic validation | ['alembic', 'async-orm', 'databases', 'fastapi', 'orm', 'pydantic', 'python-orm', 'sqlalchemy'] | ['alembic', 'async-orm', 'databases', 'fastapi', 'orm', 'pydantic', 'python-orm', 'sqlalchemy'] | 2024-01-11 | [('tiangolo/sqlmodel', 0.6308665871620178, 'data', 3), ('mcfunley/pugsql', 0.6217651963233948, 'data', 1), ('sqlalchemy/sqlalchemy', 0.6017918586730957, 'data', 1), ('python-trio/trio', 0.5920240879058838, 'perf', 0), ('andialbrecht/sqlparse', 0.5768142938613892, 'data', 0), ('s3rius/fastapi-template', 0.5686522722244263, 'web', 2), ('fastai/fastcore', 0.5605081915855408, 'util', 0), ('rawheel/fastapi-boilerplate', 0.5596618056297302, 'web', 5), ('ibis-project/ibis', 0.5441567301750183, 'data', 1), ('pypy/pypy', 0.5436598658561707, 'util', 0), ('aeternalis-ingenium/fastapi-backend-template', 0.5430356860160828, 'web', 3), ('pyeve/cerberus', 0.5298268795013428, 'data', 0), ('pydantic/pydantic', 0.5280044078826904, 'util', 1), ('aminalaee/sqladmin', 0.5242454409599304, 'data', 2), ('python-cachier/cachier', 0.5154281258583069, 'perf', 0), ('pyston/pyston', 0.5057287812232971, 'util', 0), ('eleutherai/pyfra', 0.5003811717033386, 'ml', 0)] | 35 | 5 | null | 2.88 | 36 | 20 | 42 | 0 | 2 | 22 | 2 | 36 | 32 | 90 | 0.9 | 45 |
801 | web | https://github.com/s3rius/fastapi-template | [] | null | [] | [] | null | null | null | s3rius/fastapi-template | FastAPI-template | 1,421 | 126 | 24 | Python | null | Feature rich robust FastAPI template. | s3rius | 2024-01-14 | 2020-10-05 | 173 | 8.207096 | null | Feature rich robust FastAPI template. | ['aerich', 'alembic', 'asynchronous', 'asyncio', 'cookiecutter', 'cookiecutter-python3', 'cookiecutter-template', 'fastapi', 'fastapi-boilerplate', 'fastapi-template', 'graphql', 'opentelemetry', 'ormar', 'prometheus', 'sentry', 'sqlalchemy-orm', 'strawberry-graphql', 'tortoise-orm'] | ['aerich', 'alembic', 'asynchronous', 'asyncio', 'cookiecutter', 'cookiecutter-python3', 'cookiecutter-template', 'fastapi', 'fastapi-boilerplate', 'fastapi-template', 'graphql', 'opentelemetry', 'ormar', 'prometheus', 'sentry', 'sqlalchemy-orm', 'strawberry-graphql', 'tortoise-orm'] | 2023-09-12 | [('rawheel/fastapi-boilerplate', 0.6903481483459473, 'web', 4), ('asacristani/fastapi-rocket-boilerplate', 0.6634681224822998, 'template', 1), ('tiangolo/fastapi', 0.6399540305137634, 'web', 2), ('buuntu/fastapi-react', 0.6214925646781921, 'template', 2), ('fastai/fastcore', 0.6101469993591309, 'util', 0), ('fastapi-admin/fastapi-admin', 0.6024838089942932, 'web', 2), ('dmontagu/fastapi_client', 0.6021080613136292, 'web', 0), ('aminalaee/sqladmin', 0.5958586931228638, 'data', 2), ('fastapi-users/fastapi-users', 0.595072329044342, 'web', 2), ('vitalik/django-ninja', 0.5742310285568237, 'web', 0), ('aeternalis-ingenium/fastapi-backend-template', 0.5711674690246582, 'web', 3), ('collerek/ormar', 0.5686522722244263, 'data', 2), ('tiangolo/full-stack-fastapi-postgresql', 0.5562103986740112, 'template', 2), ('starlite-api/starlite', 0.5500728487968445, 'web', 1), ('pallets/jinja', 0.5498924255371094, 'util', 0), ('python-restx/flask-restx', 0.5399068593978882, 'web', 0), ('tiangolo/sqlmodel', 0.5149979591369629, 'data', 1), ('awtkns/fastapi-crudrouter', 0.514696478843689, 'web', 2), ('tedivm/robs_awesome_python_template', 0.5110516548156738, 'template', 1), ('klen/muffin', 0.5076808333396912, 'web', 1), ('strawberry-graphql/strawberry', 0.5046817064285278, 'web', 2), ('sumerc/yappi', 0.5003270506858826, 'profiling', 2)] | 18 | 6 | null | 0.73 | 13 | 3 | 40 | 4 | 14 | 11 | 14 | 13 | 37 | 90 | 2.8 | 45 |
1,472 | data | https://github.com/aminalaee/sqladmin | [] | null | [] | [] | null | null | null | aminalaee/sqladmin | sqladmin | 1,391 | 141 | 12 | Python | https://aminalaee.dev/sqladmin/ | SQLAlchemy Admin for FastAPI and Starlette | aminalaee | 2024-01-12 | 2021-12-22 | 109 | 12.661899 | null | SQLAlchemy Admin for FastAPI and Starlette | ['admin', 'admin-dashboard', 'asgi', 'asyncio', 'fastapi', 'sqlalchemy', 'starlette', 'web', 'wsgi'] | ['admin', 'admin-dashboard', 'asgi', 'asyncio', 'fastapi', 'sqlalchemy', 'starlette', 'web', 'wsgi'] | 2023-12-13 | [('piccolo-orm/piccolo_admin', 0.6254207491874695, 'data', 5), ('fastapi-admin/fastapi-admin', 0.6240462064743042, 'web', 3), ('sqlalchemy/sqlalchemy', 0.6173149347305298, 'data', 1), ('aeternalis-ingenium/fastapi-backend-template', 0.6071468591690063, 'web', 2), ('s3rius/fastapi-template', 0.5958586931228638, 'web', 2), ('rawheel/fastapi-boilerplate', 0.5917928218841553, 'web', 2), ('tiangolo/sqlmodel', 0.5850541591644287, 'data', 2), ('mause/duckdb_engine', 0.5703755021095276, 'data', 1), ('sqlalchemy/alembic', 0.5552855730056763, 'data', 1), ('starlite-api/starlite', 0.5524939894676208, 'web', 2), ('fastapi-users/fastapi-users', 0.5336757302284241, 'web', 3), ('collerek/ormar', 0.5242454409599304, 'data', 2), ('neoteroi/blacksheep', 0.5168036818504333, 'web', 3), ('ibis-project/ibis', 0.512384831905365, 'data', 1), ('agronholm/sqlacodegen', 0.5044848918914795, 'data', 0), ('pallets/werkzeug', 0.5044029355049133, 'web', 1)] | 46 | 1 | null | 2.08 | 45 | 32 | 25 | 1 | 14 | 17 | 14 | 45 | 55 | 90 | 1.2 | 45 |
1,185 | ml | https://github.com/castorini/pyserini | [] | null | [] | [] | null | null | null | castorini/pyserini | pyserini | 1,269 | 283 | 16 | Python | http://pyserini.io/ | Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. | castorini | 2024-01-12 | 2019-11-01 | 221 | 5.727273 | https://avatars.githubusercontent.com/u/26842848?v=4 | Pyserini is a Python toolkit for reproducible information retrieval research with sparse and dense representations. | ['information-retrieval'] | ['information-retrieval'] | 2024-01-11 | [('facebookresearch/dpr-scale', 0.5861307978630066, 'nlp', 0), ('qdrant/fastembed', 0.556861937046051, 'ml', 0), ('harangju/wikinet', 0.5286003351211548, 'data', 0), ('kagisearch/vectordb', 0.5248305201530457, 'data', 0), ('paddlepaddle/rocketqa', 0.5224674940109253, 'nlp', 1), ('qdrant/qdrant-client', 0.5034437775611877, 'util', 0)] | 148 | 2 | null | 4.27 | 99 | 89 | 51 | 0 | 6 | 8 | 6 | 99 | 93 | 90 | 0.9 | 45 |
743 | data | https://github.com/pytorch/data | [] | null | [] | [] | null | null | null | pytorch/data | data | 1,044 | 136 | 33 | Python | null | A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries. | pytorch | 2024-01-13 | 2021-05-12 | 141 | 7.359517 | https://avatars.githubusercontent.com/u/21003710?v=4 | A PyTorch repo for data loading and utilities to be shared by the PyTorch domain libraries. | [] | [] | 2024-01-13 | [('intel/intel-extension-for-pytorch', 0.6773589849472046, 'perf', 0), ('nvidia/apex', 0.6665452122688293, 'ml-dl', 0), ('pytorch/ignite', 0.655742347240448, 'ml-dl', 0), ('skorch-dev/skorch', 0.631018877029419, 'ml-dl', 0), ('rasbt/machine-learning-book', 0.6106820106506348, 'study', 0), ('parallel-domain/pd-sdk', 0.6059823036193848, 'data', 0), ('erotemic/ubelt', 0.5979729294776917, 'util', 0), ('allenai/allennlp', 0.5899907946586609, 'nlp', 0), ('pytorch/torchrec', 0.5872920751571655, 'ml-dl', 0), ('fastai/fastcore', 0.5834670066833496, 'util', 0), ('ashleve/lightning-hydra-template', 0.5815867781639099, 'util', 0), ('pytorch-labs/gpt-fast', 0.5759943723678589, 'llm', 0), ('karpathy/micrograd', 0.5738345980644226, 'study', 0), ('rentruewang/koila', 0.5698388814926147, 'ml', 0), ('faster-cpython/tools', 0.5645531415939331, 'perf', 0), ('mrdbourke/pytorch-deep-learning', 0.5634875893592834, 'study', 0), ('kshitij12345/torchnnprofiler', 0.5611929297447205, 'profiling', 0), ('huggingface/accelerate', 0.5591470003128052, 'ml', 0), ('blackhc/toma', 0.5554980635643005, 'ml-dl', 0), ('pytoolz/toolz', 0.5517788529396057, 'util', 0), ('pyg-team/pytorch_geometric', 0.5495861768722534, 'ml-dl', 0), ('nvidia/cuda-python', 0.5482061505317688, 'ml', 0), ('pytorch/captum', 0.5359891057014465, 'ml-interpretability', 0), ('faster-cpython/ideas', 0.5340155959129333, 'perf', 0), ('facebookresearch/pytorch3d', 0.5338151454925537, 'ml-dl', 0), ('arogozhnikov/einops', 0.5333592891693115, 'ml-dl', 0), ('google/gin-config', 0.5325197577476501, 'util', 0), ('huggingface/transformers', 0.5293325185775757, 'nlp', 0), ('pytorch/rl', 0.5270489454269409, 'ml-rl', 0), ('p403n1x87/austin', 0.5269789695739746, 'profiling', 0), ('laekov/fastmoe', 0.5255650877952576, 'ml', 0), ('pypy/pypy', 0.5254920721054077, 'util', 0), ('gotcha/ipdb', 0.5220991969108582, 'debug', 0), ('dlt-hub/dlt', 0.5167723298072815, 'data', 0), ('ipython/ipyparallel', 0.5157786011695862, 'perf', 0), ('graphistry/pygraphistry', 0.5149250030517578, 'data', 0), ('xl0/lovely-tensors', 0.5113422274589539, 'ml-dl', 0), ('jovianml/opendatasets', 0.5112810730934143, 'data', 0), ('imageio/imageio', 0.5112005472183228, 'util', 0), ('wesm/pydata-book', 0.5109310746192932, 'study', 0), ('denys88/rl_games', 0.5077896118164062, 'ml-rl', 0), ('uber/petastorm', 0.5076653361320496, 'data', 0), ('timdettmers/bitsandbytes', 0.5031000375747681, 'util', 0), ('kubeflow/fairing', 0.5028988122940063, 'ml-ops', 0), ('qdrant/fastembed', 0.5008647441864014, 'ml', 0)] | 79 | 7 | null | 2.08 | 14 | 8 | 33 | 0 | 4 | 9 | 4 | 14 | 15 | 90 | 1.1 | 45 |
1,836 | ml | https://github.com/spotify/voyager | [] | null | [] | [] | null | null | null | spotify/voyager | voyager | 1,024 | 33 | 10 | C++ | https://spotify.github.io/voyager/ | 🛰️ Voyager is an approximate nearest-neighbor search library for Python and Java with a focus on ease of use, simplicity, and deployability. | spotify | 2024-01-14 | 2023-04-13 | 41 | 24.547945 | https://avatars.githubusercontent.com/u/251374?v=4 | 🛰️ Voyager is an approximate nearest-neighbor search library for Python and Java with a focus on ease of use, simplicity, and deployability. | ['hnsw', 'hnswlib', 'java', 'machine-learning', 'nearest-neighbor-search'] | ['hnsw', 'hnswlib', 'java', 'machine-learning', 'nearest-neighbor-search'] | 2023-12-07 | [('lmcinnes/pynndescent', 0.6540524363517761, 'ml', 1), ('spotify/annoy', 0.6272151470184326, 'ml', 1), ('nmslib/hnswlib', 0.5946098566055298, 'ml', 0), ('erotemic/ubelt', 0.5305669903755188, 'util', 0), ('scikit-learn-contrib/metric-learn', 0.503491997718811, 'ml', 1), ('pycaret/pycaret', 0.502596914768219, 'ml', 1), ('radiantearth/radiant-mlhub', 0.5025808811187744, 'gis', 1)] | 5 | 2 | null | 1.15 | 23 | 13 | 9 | 1 | 7 | 11 | 7 | 23 | 19 | 90 | 0.8 | 45 |
1,321 | ml-dl | https://github.com/keras-team/keras-cv | ['keras', 'computer-vision'] | null | [] | [] | null | null | null | keras-team/keras-cv | keras-cv | 888 | 285 | 32 | Python | null | Industry-strength Computer Vision workflows with Keras | keras-team | 2024-01-13 | 2020-05-18 | 193 | 4.597633 | https://avatars.githubusercontent.com/u/34455048?v=4 | Industry-strength Computer Vision workflows with Keras | [] | ['computer-vision', 'keras'] | 2024-01-12 | [('roboflow/supervision', 0.640568733215332, 'ml', 1), ('nyandwi/modernconvnets', 0.6089338064193726, 'ml-dl', 2), ('deci-ai/super-gradients', 0.5779148936271667, 'ml-dl', 1), ('keras-team/keras-nlp', 0.5433396697044373, 'nlp', 1), ('lutzroeder/netron', 0.5374981760978699, 'ml', 1), ('huggingface/datasets', 0.535764217376709, 'nlp', 1), ('hysts/pytorch_image_classification', 0.5079523921012878, 'ml-dl', 1), ('aleju/imgaug', 0.5068478584289551, 'ml', 0), ('onnx/onnx', 0.5009073615074158, 'ml', 1), ('nvidia/deeplearningexamples', 0.5008230805397034, 'ml-dl', 1)] | 89 | 2 | null | 8.73 | 251 | 196 | 44 | 0 | 21 | 12 | 21 | 251 | 321 | 90 | 1.3 | 45 |
324 | security | https://github.com/trailofbits/pip-audit | [] | null | [] | [] | null | null | null | trailofbits/pip-audit | pip-audit | 877 | 60 | 25 | Python | https://pypi.org/project/pip-audit/ | Audits Python environments and dependency trees for known vulnerabilities | trailofbits | 2024-01-13 | 2021-09-02 | 125 | 6.976136 | https://avatars.githubusercontent.com/u/647025?v=4 | Audits Python environments and dependency trees for known vulnerabilities | ['pip', 'security', 'security-audit', 'supply-chain'] | ['pip', 'security', 'security-audit', 'supply-chain'] | 2024-01-12 | [('pyupio/safety', 0.7114713788032532, 'security', 1), ('aswinnnn/pyscan', 0.6042621731758118, 'security', 2), ('pdm-project/pdm', 0.54820716381073, 'util', 0), ('tiiuae/sbomnix', 0.5466781258583069, 'util', 1), ('alexmojaki/snoop', 0.5462668538093567, 'debug', 0), ('klen/pylama', 0.5406633019447327, 'util', 0), ('pypa/pipenv', 0.531186044216156, 'util', 1), ('legrandin/pycryptodome', 0.5239244103431702, 'util', 1), ('pypa/hatch', 0.5167754292488098, 'util', 0), ('jazzband/pip-tools', 0.5135653614997864, 'util', 1), ('thoth-station/micropipenv', 0.5130209922790527, 'util', 1), ('ethereum/web3.py', 0.5048879981040955, 'crypto', 0), ('tox-dev/pipdeptree', 0.5004677176475525, 'util', 1)] | 27 | 4 | null | 3.29 | 47 | 40 | 29 | 0 | 14 | 23 | 14 | 47 | 40 | 90 | 0.9 | 45 |
1,888 | ml | https://github.com/oml-team/open-metric-learning | ['pytorch', 'embeddings'] | OML is a PyTorch-based framework to train and validate the models producing high-quality embeddings. | [] | [] | null | null | null | oml-team/open-metric-learning | open-metric-learning | 716 | 45 | 10 | Jupyter Notebook | https://open-metric-learning.readthedocs.io/en/latest/index.html | Library for metric learning pipelines and models. | oml-team | 2024-01-12 | 2022-06-04 | 86 | 8.284298 | https://avatars.githubusercontent.com/u/104944039?v=4 | Library for metric learning pipelines and models. | ['computer-vision', 'data-science', 'deep-learning', 'hacktoberfest-2023', 'hacktoberfest2023', 'metric-learning', 'pytorch', 'pytorch-lightning', 'representation-learning', 'similarity-learning'] | ['computer-vision', 'data-science', 'deep-learning', 'embeddings', 'hacktoberfest-2023', 'hacktoberfest2023', 'metric-learning', 'pytorch', 'pytorch-lightning', 'representation-learning', 'similarity-learning'] | 2023-12-30 | [('kevinmusgrave/pytorch-metric-learning', 0.7173192501068115, 'ml', 5), ('scikit-learn-contrib/metric-learn', 0.6861700415611267, 'ml', 1), ('qdrant/quaterion', 0.618319571018219, 'ml', 5), ('pytorch/ignite', 0.6061093807220459, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.5796335339546204, 'study', 2), ('ashleve/lightning-hydra-template', 0.5497283339500427, 'util', 3), ('roboflow/supervision', 0.5494734644889832, 'ml', 3), ('uber/petastorm', 0.5485543012619019, 'data', 2), ('ggerganov/ggml', 0.5477278232574463, 'ml', 0), ('tensorflow/tensorflow', 0.5407246947288513, 'ml-dl', 1), ('pytorch/torchrec', 0.5388403534889221, 'ml-dl', 2), ('neuralmagic/sparseml', 0.5373204350471497, 'ml-dl', 1), ('tensorflow/similarity', 0.5347641706466675, 'ml-dl', 3), ('huggingface/transformers', 0.5327936410903931, 'nlp', 2), ('featurelabs/featuretools', 0.5298222899436951, 'ml', 1), ('catboost/catboost', 0.5297994017601013, 'ml', 1), ('huggingface/datasets', 0.528002142906189, 'nlp', 3), ('dmlc/xgboost', 0.5269960761070251, 'ml', 0), ('pyg-team/pytorch_geometric', 0.5263068079948425, 'ml-dl', 2), ('lightly-ai/lightly', 0.5244993567466736, 'ml', 4), ('tensorflow/data-validation', 0.5238116979598999, 'ml-ops', 0), ('huggingface/evaluate', 0.5213491320610046, 'ml', 0), ('aws/sagemaker-python-sdk', 0.5199127197265625, 'ml', 1), ('skorch-dev/skorch', 0.5191598534584045, 'ml-dl', 1), ('deci-ai/super-gradients', 0.5170210599899292, 'ml-dl', 3), ('pycaret/pycaret', 0.5165910124778748, 'ml', 1), ('tensorflow/tensor2tensor', 0.5146539211273193, 'ml', 1), ('tensorlayer/tensorlayer', 0.5133138298988342, 'ml-rl', 1), ('gradio-app/gradio', 0.5132337808609009, 'viz', 2), ('microsoft/flaml', 0.5119624733924866, 'ml', 2), ('keras-team/autokeras', 0.5088566541671753, 'ml-dl', 1), ('cvxgrp/pymde', 0.5077699422836304, 'ml', 1), ('microsoft/nni', 0.5069662928581238, 'ml', 3), ('intel/intel-extension-for-pytorch', 0.506502091884613, 'perf', 2)] | 20 | 4 | null | 2.87 | 56 | 52 | 20 | 0 | 0 | 12 | 12 | 56 | 52 | 90 | 0.9 | 45 |
948 | ml | https://github.com/facebookresearch/balance | [] | null | [] | [] | null | null | null | facebookresearch/balance | balance | 656 | 42 | 6 | Python | https://import-balance.org | The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to some target population of interest. | facebookresearch | 2024-01-11 | 2022-11-15 | 63 | 10.412698 | https://avatars.githubusercontent.com/u/16943930?v=4 | The balance python package offers a simple workflow and methods for dealing with biased data samples when looking to infer from them to some target population of interest. | [] | [] | 2023-12-07 | [('scikit-learn-contrib/imbalanced-learn', 0.5837095379829407, 'ml', 0)] | 19 | 5 | null | 1.88 | 1 | 1 | 14 | 1 | 9 | 9 | 9 | 1 | 3 | 90 | 3 | 45 |
1,422 | sim | https://github.com/bowang-lab/scgpt | [] | scGPT: Towards Building a Foundation Model for Single-Cell Multi-omics Using Generative AI | [] | [] | null | null | null | bowang-lab/scgpt | scGPT | 584 | 91 | 29 | Jupyter Notebook | https://scgpt.readthedocs.io/en/latest/ | null | bowang-lab | 2024-01-11 | 2023-04-23 | 40 | 14.496454 | https://avatars.githubusercontent.com/u/50999261?v=4 | scGPT: Towards Building a Foundation Model for Single-Cell Multi-omics Using Generative AI | ['foundation-model', 'gpt', 'single-cell'] | ['foundation-model', 'gpt', 'single-cell'] | 2024-01-13 | [] | 6 | 1 | null | 2.83 | 56 | 43 | 9 | 0 | 7 | 9 | 7 | 56 | 109 | 90 | 1.9 | 45 |
1,882 | sim | https://github.com/google-deepmind/concordia | [] | null | [] | [] | null | null | null | google-deepmind/concordia | concordia | 207 | 24 | 13 | Python | null | A library for generative social simulation | google-deepmind | 2024-01-13 | 2023-11-21 | 10 | 20.7 | https://avatars.githubusercontent.com/u/8596759?v=4 | A library for generative social simulation | ['agent-based-simulation', 'generative-agents', 'multi-agent', 'social-simulation'] | ['agent-based-simulation', 'generative-agents', 'multi-agent', 'social-simulation'] | 2024-01-09 | [('humanoidagents/humanoidagents', 0.640636682510376, 'sim', 0), ('projectmesa/mesa', 0.6392713785171509, 'sim', 1), ('crowddynamics/crowddynamics', 0.5502240657806396, 'sim', 1)] | 11 | 6 | null | 2.15 | 17 | 16 | 2 | 0 | 1 | 6 | 1 | 17 | 18 | 90 | 1.1 | 45 |
963 | ml-rl | https://github.com/openai/baselines | [] | null | [] | [] | null | null | null | openai/baselines | baselines | 15,098 | 4,861 | 648 | Python | null | OpenAI Baselines: high-quality implementations of reinforcement learning algorithms | openai | 2024-01-14 | 2017-05-24 | 348 | 43.27846 | https://avatars.githubusercontent.com/u/14957082?v=4 | OpenAI Baselines: high-quality implementations of reinforcement learning algorithms | [] | [] | 2020-01-31 | [('thu-ml/tianshou', 0.6823237538337708, 'ml-rl', 0), ('denys88/rl_games', 0.5995540618896484, 'ml-rl', 0), ('salesforce/warp-drive', 0.5866561532020569, 'ml-rl', 0), ('humancompatibleai/imitation', 0.5837662816047668, 'ml-rl', 0), ('farama-foundation/gymnasium', 0.5754907131195068, 'ml-rl', 0), ('google/dopamine', 0.5650805830955505, 'ml-rl', 0), ('nvidia-omniverse/omniisaacgymenvs', 0.5605931282043457, 'sim', 0), ('unity-technologies/ml-agents', 0.5591613054275513, 'ml-rl', 0), ('openai/gym', 0.5574614405632019, 'ml-rl', 0), ('keras-rl/keras-rl', 0.5544887781143188, 'ml-rl', 0), ('pytorch/rl', 0.5460628867149353, 'ml-rl', 0), ('pettingzoo-team/pettingzoo', 0.5400475859642029, 'ml-rl', 0), ('google/trax', 0.5311444401741028, 'ml-dl', 0), ('nvidia-omniverse/isaacgymenvs', 0.5117769837379456, 'sim', 0), ('kzl/decision-transformer', 0.5097741484642029, 'ml-rl', 0), ('openai/spinningup', 0.5069130063056946, 'study', 0), ('inspirai/timechamber', 0.5040830969810486, 'sim', 0)] | 115 | 3 | null | 0 | 5 | 2 | 81 | 48 | 0 | 0 | 0 | 5 | 1 | 90 | 0.2 | 44 |
156 | data | https://github.com/s0md3v/photon | [] | null | [] | [] | null | null | null | s0md3v/photon | Photon | 10,251 | 1,459 | 324 | Python | null | Incredibly fast crawler designed for OSINT. | s0md3v | 2024-01-14 | 2018-03-30 | 304 | 33.657129 | null | Incredibly fast crawler designed for OSINT. | ['crawler', 'information-gathering', 'osint', 'spider'] | ['crawler', 'information-gathering', 'osint', 'spider'] | 2022-12-20 | [('binux/pyspider', 0.7611035108566284, 'data', 1), ('scrapy/scrapy', 0.6149922609329224, 'data', 1)] | 21 | 3 | null | 0 | 4 | 0 | 70 | 13 | 0 | 3 | 3 | 4 | 1 | 90 | 0.2 | 44 |
1,057 | ml-rl | https://github.com/deepmind/pysc2 | [] | null | [] | [] | null | null | null | deepmind/pysc2 | pysc2 | 7,863 | 1,164 | 352 | Python | null | StarCraft II Learning Environment | deepmind | 2024-01-12 | 2017-07-25 | 340 | 23.126471 | https://avatars.githubusercontent.com/u/8596759?v=4 | StarCraft II Learning Environment | ['blizzard-api', 'deepmind', 'machine-learning', 'reinforcement-learning', 'starcraft-ii', 'starcraft-ii-replays'] | ['blizzard-api', 'deepmind', 'machine-learning', 'reinforcement-learning', 'starcraft-ii', 'starcraft-ii-replays'] | 2023-04-19 | [('pettingzoo-team/pettingzoo', 0.5372393131256104, 'ml-rl', 1), ('farama-foundation/gymnasium', 0.5224155187606812, 'ml-rl', 1), ('unity-technologies/ml-agents', 0.5204218029975891, 'ml-rl', 2), ('google/trax', 0.5190588235855103, 'ml-dl', 2), ('keras-rl/keras-rl', 0.5143329501152039, 'ml-rl', 2)] | 39 | 4 | null | 0.13 | 4 | 1 | 79 | 9 | 0 | 1 | 1 | 4 | 3 | 90 | 0.8 | 44 |
675 | ml | https://github.com/hips/autograd | [] | null | [] | [] | null | null | null | hips/autograd | autograd | 6,644 | 908 | 218 | Python | null | Efficiently computes derivatives of numpy code. | hips | 2024-01-13 | 2014-11-24 | 479 | 13.866428 | https://avatars.githubusercontent.com/u/7935606?v=4 | Efficiently computes derivatives of numpy code. | [] | [] | 2023-11-16 | [('google/jax', 0.5986758470535278, 'ml', 0), ('numpy/numpy', 0.5689885020256042, 'math', 0), ('numba/numba', 0.5151181817054749, 'perf', 0), ('cupy/cupy', 0.5063801407814026, 'math', 0), ('andgoldschmidt/derivative', 0.5045579075813293, 'math', 0)] | 56 | 7 | null | 0.54 | 37 | 3 | 111 | 2 | 0 | 0 | 0 | 37 | 8 | 90 | 0.2 | 44 |
1,647 | util | https://github.com/evhub/coconut | ['functional'] | null | [] | [] | null | null | null | evhub/coconut | coconut | 3,868 | 116 | 62 | Python | http://coconut-lang.org | Simple, elegant, Pythonic functional programming. | evhub | 2024-01-13 | 2014-10-04 | 486 | 7.951836 | null | Simple, elegant, Pythonic functional programming. | ['coconut', 'compiler', 'functional', 'functional-language', 'functional-programming', 'language', 'programming-language', 'xonsh', 'xontrib'] | ['coconut', 'compiler', 'functional', 'functional-language', 'functional-programming', 'language', 'programming-language', 'xonsh', 'xontrib'] | 2023-11-28 | [('pytoolz/toolz', 0.6476520895957947, 'util', 0), ('suor/funcy', 0.6461945176124573, 'util', 1), ('google/pyglove', 0.583031415939331, 'util', 0), ('fastai/fastcore', 0.5812950730323792, 'util', 1), ('modularml/mojo', 0.5474485754966736, 'util', 2), ('pypy/pypy', 0.544915497303009, 'util', 1), ('dylanhogg/awesome-python', 0.5391582250595093, 'study', 0), ('lukaszahradnik/pyneuralogic', 0.5328680872917175, 'math', 0), ('python/cpython', 0.5319302678108215, 'util', 0), ('stanfordnlp/dspy', 0.5305084586143494, 'llm', 0), ('explosion/thinc', 0.5264431834220886, 'ml-dl', 1), ('1200wd/bitcoinlib', 0.5255511403083801, 'crypto', 0), ('pygamelib/pygamelib', 0.5140511989593506, 'gamedev', 0), ('fluentpython/example-code-2e', 0.5133896470069885, 'study', 0), ('pyston/pyston', 0.5107958316802979, 'util', 0), ('gondolav/pyfuncol', 0.5076735019683838, 'util', 1), ('xonsh/xonsh', 0.5075111985206604, 'util', 1), ('norvig/pytudes', 0.5068784356117249, 'util', 0), ('joblib/joblib', 0.5061070322990417, 'util', 0), ('tiangolo/typer', 0.5052512884140015, 'term', 0), ('pyparsing/pyparsing', 0.504447877407074, 'util', 0), ('sloria/textblob', 0.5033293962478638, 'nlp', 0), ('pyomo/pyomo', 0.5014179944992065, 'math', 0)] | 33 | 3 | null | 6.79 | 36 | 24 | 113 | 2 | 5 | 4 | 5 | 36 | 25 | 90 | 0.7 | 44 |
907 | util | https://github.com/ets-labs/python-dependency-injector | [] | null | [] | [] | 1 | null | null | ets-labs/python-dependency-injector | python-dependency-injector | 3,414 | 307 | 48 | Python | https://python-dependency-injector.ets-labs.org/ | Dependency injection framework for Python | ets-labs | 2024-01-13 | 2015-01-04 | 473 | 7.213402 | https://avatars.githubusercontent.com/u/11329744?v=4 | Dependency injection framework for Python | ['aiohttp', 'asyncio', 'dependency-injection', 'dependency-injection-container', 'dependency-injection-framework', 'design-patterns', 'factory', 'flask', 'flask-application', 'flask-restful', 'ioc', 'ioc-container', 'singleton', 'threadlocal'] | ['aiohttp', 'asyncio', 'dependency-injection', 'dependency-injection-container', 'dependency-injection-framework', 'design-patterns', 'factory', 'flask', 'flask-application', 'flask-restful', 'ioc', 'ioc-container', 'singleton', 'threadlocal'] | 2022-12-19 | [('allrod5/injectable', 0.6628846526145935, 'util', 2), ('python-injector/injector', 0.6611223220825195, 'util', 2), ('ivankorobkov/python-inject', 0.6299859881401062, 'util', 1), ('aio-libs/aiohttp', 0.5857105255126953, 'web', 2), ('pallets/flask', 0.5796188712120056, 'web', 1), ('timofurrer/awesome-asyncio', 0.5701932311058044, 'study', 1), ('bottlepy/bottle', 0.5632432699203491, 'web', 0), ('klen/muffin', 0.5598342418670654, 'web', 1), ('python-restx/flask-restx', 0.551591694355011, 'web', 1), ('falconry/falcon', 0.5372539758682251, 'web', 0), ('neoteroi/blacksheep', 0.5310226678848267, 'web', 1), ('pallets/quart', 0.5255832672119141, 'web', 1), ('alirn76/panther', 0.516931414604187, 'web', 0), ('eleutherai/pyfra', 0.5152551531791687, 'ml', 0), ('python-poetry/poetry', 0.510571300983429, 'util', 0), ('sumerc/yappi', 0.5105165839195251, 'profiling', 1), ('encode/uvicorn', 0.5008002519607544, 'web', 1), ('backtick-se/cowait', 0.500067412853241, 'util', 0)] | 29 | 7 | null | 0 | 35 | 6 | 110 | 13 | 0 | 36 | 36 | 35 | 80 | 90 | 2.3 | 44 |
1,219 | ml | https://github.com/py-why/econml | [] | null | [] | [] | null | null | null | py-why/econml | EconML | 3,385 | 655 | 75 | Jupyter Notebook | https://www.microsoft.com/en-us/research/project/alice/ | ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x. | py-why | 2024-01-13 | 2018-04-30 | 300 | 11.277963 | https://avatars.githubusercontent.com/u/101266056?v=4 | ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x. | ['causal-inference', 'causality', 'econometrics', 'economics', 'machine-learning', 'treatment-effects'] | ['causal-inference', 'causality', 'econometrics', 'economics', 'machine-learning', 'treatment-effects'] | 2024-01-12 | [('py-why/dowhy', 0.5789477229118347, 'ml', 4), ('uber/causalml', 0.5542822480201721, 'ml', 2), ('mckinsey/causalnex', 0.5422161221504211, 'math', 2)] | 34 | 3 | null | 0.96 | 35 | 18 | 69 | 0 | 1 | 5 | 1 | 35 | 27 | 90 | 0.8 | 44 |
271 | data | https://github.com/praw-dev/praw | [] | null | [] | [] | null | null | null | praw-dev/praw | praw | 3,248 | 461 | 73 | Python | http://praw.readthedocs.io/ | PRAW, an acronym for "Python Reddit API Wrapper", is a python package that allows for simple access to Reddit's API. | praw-dev | 2024-01-13 | 2010-08-19 | 701 | 4.628664 | https://avatars.githubusercontent.com/u/1696888?v=4 | PRAW, an acronym for "Python Reddit API Wrapper", is a python package that allows for simple access to Reddit's API. | ['api', 'oauth', 'praw', 'reddit', 'reddit-api'] | ['api', 'oauth', 'praw', 'reddit', 'reddit-api'] | 2024-01-10 | [('praw-dev/asyncpraw', 0.8785129189491272, 'ml-dl', 5)] | 226 | 4 | null | 1.31 | 36 | 27 | 163 | 0 | 2 | 12 | 2 | 36 | 48 | 90 | 1.3 | 44 |
690 | ml-dl | https://github.com/deepmind/dm-haiku | [] | null | [] | [] | null | null | null | deepmind/dm-haiku | dm-haiku | 2,675 | 222 | 39 | Python | https://dm-haiku.readthedocs.io | JAX-based neural network library | deepmind | 2024-01-14 | 2020-02-18 | 206 | 12.985437 | https://avatars.githubusercontent.com/u/8596759?v=4 | JAX-based neural network library | ['deep-learning', 'deep-neural-networks', 'jax', 'machine-learning', 'neural-networks'] | ['deep-learning', 'deep-neural-networks', 'jax', 'machine-learning', 'neural-networks'] | 2023-11-30 | [('deepmind/synjax', 0.7001689076423645, 'math', 1), ('google/flax', 0.6950955986976624, 'ml-dl', 1), ('google/trax', 0.6491378545761108, 'ml-dl', 3), ('keras-team/keras', 0.6441159844398499, 'ml-dl', 4), ('explosion/thinc', 0.6371207237243652, 'ml-dl', 3), ('huggingface/transformers', 0.6224076747894287, 'nlp', 3), ('sanchit-gandhi/whisper-jax', 0.6133875846862793, 'ml', 2), ('alpa-projects/alpa', 0.6117678284645081, 'ml-dl', 3), ('deepmind/kfac-jax', 0.5966999530792236, 'math', 2), ('google/evojax', 0.5894790291786194, 'sim', 1), ('deepmind/chex', 0.5875384211540222, 'ml-dl', 1), ('tensorflow/tensorflow', 0.5688497424125671, 'ml-dl', 3), ('tensorlayer/tensorlayer', 0.5642551183700562, 'ml-rl', 1), ('uber/petastorm', 0.557473361492157, 'data', 2), ('onnx/onnx', 0.542344868183136, 'ml', 3), ('microsoft/onnxruntime', 0.540787935256958, 'ml', 3), ('ml-tooling/opyrator', 0.5379303097724915, 'viz', 1), ('karpathy/micrograd', 0.5368869304656982, 'study', 0), ('pytorch/ignite', 0.5363015532493591, 'ml-dl', 2), ('horovod/horovod', 0.5358175039291382, 'ml-ops', 2), ('keras-team/autokeras', 0.5257297158241272, 'ml-dl', 2), ('young-geng/easylm', 0.5241255164146423, 'llm', 2), ('aiqc/aiqc', 0.5235515236854553, 'ml-ops', 0), ('apache/incubator-mxnet', 0.522907018661499, 'ml-dl', 0), ('microsoft/deepspeed', 0.5188496112823486, 'ml-dl', 2), ('microsoft/nni', 0.5166778564453125, 'ml', 2), ('rasbt/machine-learning-book', 0.5160495638847351, 'study', 3), ('titanml/takeoff', 0.5155620574951172, 'llm', 0), ('tensorflow/tensor2tensor', 0.5139560103416443, 'ml', 2), ('arogozhnikov/einops', 0.5126287341117859, 'ml-dl', 2), ('nvidia/deeplearningexamples', 0.5113754868507385, 'ml-dl', 1), ('d2l-ai/d2l-en', 0.5113567113876343, 'study', 3), ('denys88/rl_games', 0.507714569568634, 'ml-rl', 1), ('mlflow/mlflow', 0.50584477186203, 'ml-ops', 1), ('adap/flower', 0.5038338303565979, 'ml-ops', 2)] | 79 | 5 | null | 1.83 | 23 | 19 | 48 | 2 | 1 | 3 | 1 | 23 | 4 | 90 | 0.2 | 44 |
1,812 | llm | https://github.com/paperswithcode/galai | ['scientific', 'citations', 'language-model'] | null | [] | [] | null | null | null | paperswithcode/galai | galai | 2,613 | 274 | 44 | Jupyter Notebook | null | Model API for GALACTICA | paperswithcode | 2024-01-13 | 2022-11-15 | 63 | 41.47619 | https://avatars.githubusercontent.com/u/40305508?v=4 | Model API for GALACTICA | [] | ['citations', 'language-model', 'scientific'] | 2023-02-14 | [('princeton-nlp/alce', 0.6015400290489197, 'llm', 1), ('tatsu-lab/stanford_alpaca', 0.5739641785621643, 'llm', 1), ('hannibal046/awesome-llm', 0.5614985823631287, 'study', 1), ('freedomintelligence/llmzoo', 0.5310094356536865, 'llm', 1), ('ctlllll/llm-toolmaker', 0.5114402174949646, 'llm', 1), ('urschrei/pyzotero', 0.5094993710517883, 'util', 1)] | 7 | 3 | null | 0.1 | 1 | 0 | 14 | 11 | 0 | 3 | 3 | 1 | 1 | 90 | 1 | 44 |
1,431 | util | https://github.com/tox-dev/pipdeptree | ['cli', 'dependencies', 'packages'] | null | [] | [] | null | null | null | tox-dev/pipdeptree | pipdeptree | 2,606 | 141 | 31 | Python | https://pypi.python.org/pypi/pipdeptree | A command line utility to display dependency tree of the installed Python packages | tox-dev | 2024-01-13 | 2014-02-02 | 521 | 4.999178 | https://avatars.githubusercontent.com/u/20345659?v=4 | A command line utility to display dependency tree of the installed Python packages | ['dependency-graph', 'pip'] | ['cli', 'dependencies', 'dependency-graph', 'packages', 'pip'] | 2024-01-10 | [('mitsuhiko/rye', 0.5925803780555725, 'util', 0), ('pypi/warehouse', 0.5815759897232056, 'util', 0), ('python-poetry/poetry', 0.5638055205345154, 'util', 0), ('pdm-project/pdm', 0.5571689605712891, 'util', 0), ('hugovk/pypistats', 0.5279873609542847, 'util', 1), ('pypa/hatch', 0.5165544152259827, 'util', 1), ('pyodide/micropip', 0.5127100944519043, 'util', 0), ('trailofbits/pip-audit', 0.5004677176475525, 'security', 1)] | 43 | 5 | null | 1.63 | 21 | 21 | 121 | 0 | 23 | 5 | 23 | 21 | 16 | 90 | 0.8 | 44 |
201 | util | https://github.com/camelot-dev/camelot | [] | null | [] | [] | null | null | null | camelot-dev/camelot | camelot | 2,490 | 408 | 45 | Python | https://camelot-py.readthedocs.io | A Python library to extract tabular data from PDFs | camelot-dev | 2024-01-14 | 2019-07-01 | 239 | 10.412186 | https://avatars.githubusercontent.com/u/43926448?v=4 | A Python library to extract tabular data from PDFs | [] | [] | 2023-10-02 | [('py-pdf/pypdf2', 0.6539286971092224, 'util', 0), ('astanin/python-tabulate', 0.6331050395965576, 'util', 0), ('pyfpdf/fpdf2', 0.5940113663673401, 'util', 0), ('paperswithcode/axcell', 0.577544093132019, 'util', 0), ('wireservice/csvkit', 0.567770779132843, 'util', 0), ('unstructured-io/pipeline-paddleocr', 0.5457990169525146, 'data', 0), ('jazzband/tablib', 0.5369576811790466, 'data', 0), ('pypdfium2-team/pypdfium2', 0.5336915850639343, 'util', 0), ('jorisschellekens/borb', 0.5273860692977905, 'util', 0), ('jazzband/prettytable', 0.5252398252487183, 'term', 0)] | 46 | 4 | null | 0.65 | 50 | 17 | 55 | 3 | 0 | 6 | 6 | 50 | 37 | 90 | 0.7 | 44 |
1,622 | data | https://github.com/kayak/pypika | ['sql'] | null | [] | [] | null | null | null | kayak/pypika | pypika | 2,260 | 273 | 35 | Python | http://pypika.readthedocs.io/en/latest/ | PyPika is a python SQL query builder that exposes the full richness of the SQL language using a syntax that reflects the resulting query. PyPika excels at all sorts of SQL queries but is especially useful for data analysis. | kayak | 2024-01-13 | 2016-07-06 | 394 | 5.723589 | https://avatars.githubusercontent.com/u/521891?v=4 | PyPika is a python SQL query builder that exposes the full richness of the SQL language using a syntax that reflects the resulting query. PyPika excels at all sorts of SQL queries but is especially useful for data analysis. | ['builder', 'data', 'functional', 'pythonic', 'query', 'sql'] | ['builder', 'data', 'functional', 'pythonic', 'query', 'sql'] | 2023-12-10 | [('ibis-project/ibis', 0.6313249468803406, 'data', 1), ('tiangolo/sqlmodel', 0.6139056086540222, 'data', 1), ('sqlalchemy/sqlalchemy', 0.5847384333610535, 'data', 1), ('macbre/sql-metadata', 0.5715281367301941, 'data', 1), ('andialbrecht/sqlparse', 0.5649843811988831, 'data', 0), ('tobymao/sqlglot', 0.5631858706474304, 'data', 1), ('mcfunley/pugsql', 0.5262505412101746, 'data', 1)] | 98 | 3 | null | 0.21 | 29 | 4 | 92 | 1 | 0 | 10 | 10 | 28 | 57 | 90 | 2 | 44 |
761 | ml-dl | https://github.com/fepegar/torchio | [] | null | [] | [] | null | null | null | fepegar/torchio | torchio | 1,902 | 219 | 18 | Python | http://www.torchio.org | Medical imaging toolkit for deep learning | fepegar | 2024-01-13 | 2019-11-26 | 218 | 8.724771 | null | Medical imaging toolkit for deep learning | ['augmentation', 'data-augmentation', 'deep-learning', 'machine-learning', 'medical-image-analysis', 'medical-image-computing', 'medical-image-processing', 'medical-images', 'medical-imaging-datasets', 'medical-imaging-with-deep-learning', 'pytorch'] | ['augmentation', 'data-augmentation', 'deep-learning', 'machine-learning', 'medical-image-analysis', 'medical-image-computing', 'medical-image-processing', 'medical-images', 'medical-imaging-datasets', 'medical-imaging-with-deep-learning', 'pytorch'] | 2024-01-13 | [('project-monai/monai', 0.8480987548828125, 'ml', 4), ('aleju/imgaug', 0.5931549072265625, 'ml', 3), ('albumentations-team/albumentations', 0.5927706956863403, 'ml-dl', 3), ('mdbloice/augmentor', 0.5896494388580322, 'ml', 3), ('keras-team/keras', 0.5828122496604919, 'ml-dl', 3), ('open-mmlab/mmsegmentation', 0.5752494931221008, 'ml', 1), ('huggingface/datasets', 0.574800968170166, 'nlp', 3), ('onnx/onnx', 0.5600517392158508, 'ml', 3), ('microsoft/onnxruntime', 0.5472385883331299, 'ml', 3), ('tensorflow/tensor2tensor', 0.5404090285301208, 'ml', 2), ('deepfakes/faceswap', 0.5368450880050659, 'ml-dl', 2), ('mosaicml/composer', 0.5322839617729187, 'ml-dl', 3), ('lutzroeder/netron', 0.531164288520813, 'ml', 3), ('explosion/thinc', 0.5309528112411499, 'ml-dl', 3), ('nvidia/deeplearningexamples', 0.5291038155555725, 'ml-dl', 2), ('tensorflow/tensorflow', 0.5249353647232056, 'ml-dl', 2), ('neuralmagic/sparseml', 0.5229683518409729, 'ml-dl', 1), ('open-mmlab/mmediting', 0.5203762650489807, 'ml', 2), ('iperov/deepfacelab', 0.5164421200752258, 'ml-dl', 2), ('microsoft/deepspeed', 0.5152624845504761, 'ml-dl', 3), ('nyandwi/modernconvnets', 0.5130273699760437, 'ml-dl', 0), ('roboflow/supervision', 0.5101572871208191, 'ml', 3), ('ddbourgin/numpy-ml', 0.507611870765686, 'ml', 1), ('rwightman/pytorch-image-models', 0.5073763728141785, 'ml-dl', 1), ('tensorlayer/tensorlayer', 0.5055205225944519, 'ml-rl', 1), ('lucidrains/imagen-pytorch', 0.5043638348579407, 'ml-dl', 1), ('awslabs/autogluon', 0.5024552941322327, 'ml', 3), ('neuralmagic/deepsparse', 0.5005324482917786, 'nlp', 0)] | 47 | 2 | null | 1.6 | 28 | 24 | 50 | 0 | 1 | 64 | 1 | 28 | 49 | 90 | 1.8 | 44 |
670 | gis | https://github.com/apache/incubator-sedona | [] | null | [] | [] | null | null | null | apache/incubator-sedona | sedona | 1,654 | 622 | 102 | Java | https://sedona.apache.org/ | A cluster computing framework for processing large-scale geospatial data | apache | 2024-01-11 | 2015-04-24 | 457 | 3.614736 | https://avatars.githubusercontent.com/u/47359?v=4 | A cluster computing framework for processing large-scale geospatial data | ['cluster-computing', 'geospatial', 'java', 'scala', 'spatial-analysis', 'spatial-query', 'spatial-sql'] | ['cluster-computing', 'geospatial', 'java', 'scala', 'spatial-analysis', 'spatial-query', 'spatial-sql'] | 2024-01-14 | [('apache/spark', 0.5984252095222473, 'data', 2), ('giswqs/geog-414', 0.560769259929657, 'study', 1), ('osgeo/grass', 0.5388128757476807, 'gis', 1)] | 110 | 4 | null | 7 | 158 | 150 | 106 | 0 | 3 | 9 | 3 | 159 | 120 | 90 | 0.8 | 44 |
1,245 | sim | https://github.com/facebookresearch/habitat-lab | [] | null | [] | [] | null | null | null | facebookresearch/habitat-lab | habitat-lab | 1,538 | 432 | 48 | Python | https://aihabitat.org/ | A modular high-level library to train embodied AI agents across a variety of tasks and environments. | facebookresearch | 2024-01-13 | 2019-02-04 | 260 | 5.912136 | https://avatars.githubusercontent.com/u/16943930?v=4 | A modular high-level library to train embodied AI agents across a variety of tasks and environments. | ['ai', 'computer-vision', 'deep-learning', 'deep-reinforcement-learning', 'reinforcement-learning', 'research', 'robotics', 'sim2real', 'simulator'] | ['ai', 'computer-vision', 'deep-learning', 'deep-reinforcement-learning', 'reinforcement-learning', 'research', 'robotics', 'sim2real', 'simulator'] | 2024-01-12 | [('facebookresearch/droidlet', 0.6688793897628784, 'sim', 0), ('unity-technologies/ml-agents', 0.6679417490959167, 'ml-rl', 3), ('tensorlayer/tensorlayer', 0.6519606113433838, 'ml-rl', 2), ('minedojo/voyager', 0.6467283964157104, 'llm', 0), ('pytorch/rl', 0.6235378384590149, 'ml-rl', 3), ('arise-initiative/robosuite', 0.596968412399292, 'ml-rl', 2), ('prefecthq/marvin', 0.5811783671379089, 'nlp', 1), ('pettingzoo-team/pettingzoo', 0.5756711363792419, 'ml-rl', 1), ('google/dopamine', 0.5727390646934509, 'ml-rl', 1), ('luodian/otter', 0.5644159913063049, 'llm', 1), ('farama-foundation/gymnasium', 0.5635895729064941, 'ml-rl', 1), ('nvidia-omniverse/orbit', 0.5620828866958618, 'sim', 1), ('thu-ml/tianshou', 0.5616220831871033, 'ml-rl', 0), ('inspirai/timechamber', 0.5581255555152893, 'sim', 2), ('tensorflow/tensor2tensor', 0.5538010597229004, 'ml', 2), ('explosion/thinc', 0.5424818396568298, 'ml-dl', 2), ('operand/agency', 0.5416178107261658, 'llm', 1), ('salesforce/warp-drive', 0.5386927127838135, 'ml-rl', 2), ('deepmind/acme', 0.52789306640625, 'ml-rl', 2), ('deeppavlov/deeppavlov', 0.5260887145996094, 'nlp', 2), ('humanoidagents/humanoidagents', 0.5243606567382812, 'sim', 0), ('denys88/rl_games', 0.5146901607513428, 'ml-rl', 2), ('nvidia-omniverse/omniisaacgymenvs', 0.5088497400283813, 'sim', 0), ('huggingface/deep-rl-class', 0.5081996917724609, 'study', 3), ('openai/spinningup', 0.5063529014587402, 'study', 0), ('google/trax', 0.5037897825241089, 'ml-dl', 3), ('deepmind/dm_control', 0.5033023357391357, 'ml-rl', 2), ('kornia/kornia', 0.502574622631073, 'ml-dl', 3), ('bulletphysics/bullet3', 0.5023512840270996, 'sim', 3), ('smol-ai/developer', 0.5017600059509277, 'llm', 1)] | 71 | 3 | null | 3.02 | 142 | 78 | 60 | 0 | 3 | 5 | 3 | 142 | 104 | 90 | 0.7 | 44 |
1,625 | util | https://github.com/instagram/libcst | ['ast', 'cst', 'serializer'] | null | [] | [] | null | null | null | instagram/libcst | LibCST | 1,341 | 166 | 42 | Python | https://libcst.readthedocs.io/ | A concrete syntax tree parser and serializer library for Python that preserves many aspects of Python's abstract syntax tree | instagram | 2024-01-14 | 2019-08-06 | 234 | 5.730769 | https://avatars.githubusercontent.com/u/549085?v=4 | A concrete syntax tree parser and serializer library for Python that preserves many aspects of Python's abstract syntax tree | [] | ['ast', 'cst', 'serializer'] | 2024-01-08 | [('pyparsing/pyparsing', 0.6272467970848083, 'util', 0), ('marshmallow-code/marshmallow', 0.6035540699958801, 'util', 0), ('pytoolz/toolz', 0.6008638739585876, 'util', 0), ('python-rope/rope', 0.5846632719039917, 'util', 1), ('pyston/pyston', 0.5713760852813721, 'util', 0), ('python-odin/odin', 0.5643008351325989, 'util', 0), ('python/cpython', 0.5573931932449341, 'util', 0), ('pygments/pygments', 0.5501353144645691, 'util', 0), ('ibm/transition-amr-parser', 0.5405070781707764, 'nlp', 0), ('uqfoundation/dill', 0.5361902713775635, 'data', 0), ('google/latexify_py', 0.5354775786399841, 'util', 0), ('andialbrecht/sqlparse', 0.5294908285140991, 'data', 0), ('hhatto/autopep8', 0.5244827270507812, 'util', 0), ('psf/black', 0.5167094469070435, 'util', 0), ('pypy/pypy', 0.5154047608375549, 'util', 0), ('microsoft/pycodegpt', 0.5071039795875549, 'llm', 0), ('instagram/monkeytype', 0.5069942474365234, 'typing', 0), ('pydantic/pydantic', 0.5014991164207458, 'util', 0), ('mkdocstrings/griffe', 0.5002207159996033, 'util', 0)] | 75 | 3 | null | 2.02 | 63 | 41 | 54 | 0 | 4 | 9 | 4 | 63 | 94 | 90 | 1.5 | 44 |
613 | testing | https://github.com/pytest-dev/pytest-asyncio | [] | null | [] | [] | null | null | null | pytest-dev/pytest-asyncio | pytest-asyncio | 1,264 | 131 | 38 | Python | https://pytest-asyncio.readthedocs.io | Asyncio support for pytest | pytest-dev | 2024-01-12 | 2015-04-11 | 459 | 2.751244 | https://avatars.githubusercontent.com/u/8897583?v=4 | Asyncio support for pytest | ['asyncio', 'pytest-plugin', 'testing'] | ['asyncio', 'pytest-plugin', 'testing'] | 2024-01-10 | [('pytest-dev/pytest-xdist', 0.6232805252075195, 'testing', 1), ('pytest-dev/pytest-mock', 0.6129404306411743, 'testing', 0), ('pytest-dev/pytest-cov', 0.6025922894477844, 'testing', 0), ('computationalmodelling/nbval', 0.5843405723571777, 'jupyter', 2), ('timofurrer/awesome-asyncio', 0.5779024958610535, 'study', 1), ('ionelmc/pytest-benchmark', 0.5777239203453064, 'testing', 0), ('aio-libs/aiohttp', 0.5665972828865051, 'web', 1), ('pytest-dev/pytest', 0.5557228922843933, 'testing', 1), ('teemu/pytest-sugar', 0.5544842481613159, 'testing', 2), ('magicstack/uvloop', 0.552464485168457, 'util', 1), ('samuelcolvin/aioaws', 0.5367757081985474, 'data', 1), ('alex-sherman/unsync', 0.5358930230140686, 'util', 0), ('aio-libs/aiobotocore', 0.5174840688705444, 'util', 1), ('erdewit/nest_asyncio', 0.5122057199478149, 'util', 1), ('samuelcolvin/arq', 0.5120292901992798, 'data', 1), ('encode/httpx', 0.5099304914474487, 'web', 1)] | 44 | 4 | null | 4.63 | 179 | 153 | 107 | 0 | 13 | 6 | 13 | 179 | 267 | 90 | 1.5 | 44 |
1,382 | ml | https://github.com/laekov/fastmoe | ['mixture-of-experts'] | null | [] | [] | null | null | null | laekov/fastmoe | fastmoe | 1,240 | 152 | 13 | Python | https://fastmoe.ai | A fast MoE impl for PyTorch | laekov | 2024-01-13 | 2021-01-25 | 157 | 7.890909 | null | A fast MoE impl for PyTorch | [] | ['mixture-of-experts'] | 2023-10-08 | [('nvidia/apex', 0.6603500247001648, 'ml-dl', 0), ('pytorch/ignite', 0.6223480701446533, 'ml-dl', 0), ('intel/intel-extension-for-pytorch', 0.5892179012298584, 'perf', 0), ('davidmrau/mixture-of-experts', 0.5889419913291931, 'ml', 1), ('huggingface/accelerate', 0.5827643275260925, 'ml', 0), ('pytorch/botorch', 0.5626605749130249, 'ml-dl', 0), ('skorch-dev/skorch', 0.5523069500923157, 'ml-dl', 0), ('mrdbourke/pytorch-deep-learning', 0.5278257131576538, 'study', 0), ('pytorch/data', 0.5255650877952576, 'data', 0)] | 23 | 7 | null | 0.58 | 9 | 3 | 36 | 3 | 2 | 3 | 2 | 9 | 35 | 90 | 3.9 | 44 |
1,491 | math | https://github.com/dynamicslab/pysindy/ | [] | null | [] | [] | null | null | null | dynamicslab/pysindy/ | pysindy | 1,176 | 282 | 33 | Python | https://pysindy.readthedocs.io/en/latest/ | A package for the sparse identification of nonlinear dynamical systems from data | dynamicslab | 2024-01-12 | 2019-05-10 | 246 | 4.769409 | https://avatars.githubusercontent.com/u/59835780?v=4 | A package for the sparse identification of nonlinear dynamical systems from data | ['dynamical-systems', 'machine-learning', 'model-discovery', 'nonlinear-dynamics', 'sparse-regression', 'system-identification'] | ['dynamical-systems', 'machine-learning', 'model-discovery', 'nonlinear-dynamics', 'sparse-regression', 'system-identification'] | 2023-12-01 | [('wilsonrljr/sysidentpy', 0.6205930113792419, 'time-series', 3)] | 26 | 5 | null | 2.23 | 51 | 21 | 57 | 0 | 3 | 10 | 3 | 51 | 114 | 90 | 2.2 | 44 |
1,148 | util | https://github.com/aio-libs/yarl | [] | null | [] | [] | null | null | null | aio-libs/yarl | yarl | 1,081 | 151 | 31 | Python | https://yarl.aio-libs.org | Yet another URL library | aio-libs | 2024-01-14 | 2016-08-02 | 391 | 2.764706 | https://avatars.githubusercontent.com/u/7049303?v=4 | Yet another URL library | ['aiohttp', 'url-parsing', 'urls'] | ['aiohttp', 'url-parsing', 'urls'] | 2024-01-01 | [('magicstack/httptools', 0.5892772674560547, 'web', 0)] | 84 | 6 | null | 5.52 | 62 | 44 | 91 | 0 | 4 | 15 | 4 | 62 | 128 | 90 | 2.1 | 44 |
1,801 | ml | https://github.com/microsoft/olive | ['onnx', 'gpu', 'toolchain', 'performance'] | null | [] | [] | null | null | null | microsoft/olive | Olive | 1,064 | 102 | 25 | Python | null | Olive is an easy-to-use hardware-aware model optimization tool that composes industry-leading techniques across model compression, optimization, and compilation. | microsoft | 2024-01-12 | 2019-08-12 | 233 | 4.563725 | https://avatars.githubusercontent.com/u/6154722?v=4 | Olive is an easy-to-use hardware-aware model optimization tool that composes industry-leading techniques across model compression, optimization, and compilation. | [] | ['gpu', 'onnx', 'performance', 'toolchain'] | 2024-01-12 | [('pytorch/glow', 0.5527094006538391, 'ml', 0), ('microsoft/nni', 0.5166267156600952, 'ml', 0), ('plasma-umass/scalene', 0.503036618232727, 'profiling', 1), ('eleutherai/oslo', 0.5006281733512878, 'ml', 0)] | 30 | 1 | null | 10.9 | 248 | 223 | 54 | 0 | 8 | 2 | 8 | 248 | 420 | 90 | 1.7 | 44 |
1,244 | ml | https://github.com/microsoft/semi-supervised-learning | [] | null | [] | [] | null | null | null | microsoft/semi-supervised-learning | Semi-supervised-learning | 1,056 | 143 | 19 | Python | https://usb.readthedocs.io | A Unified Semi-Supervised Learning Codebase (NeurIPS'22) | microsoft | 2024-01-14 | 2022-05-05 | 90 | 11.640945 | https://avatars.githubusercontent.com/u/6154722?v=4 | A Unified Semi-Supervised Learning Codebase (NeurIPS'22) | ['audio-classification', 'classification', 'computer-vision', 'deep-learning', 'low-resource', 'machine-learning', 'natural-language-processing', 'pytorch', 'semi-supervised-learning', 'semisupervised-learning', 'transformer'] | ['audio-classification', 'classification', 'computer-vision', 'deep-learning', 'low-resource', 'machine-learning', 'natural-language-processing', 'pytorch', 'semi-supervised-learning', 'semisupervised-learning', 'transformer'] | 2023-11-10 | [('rasbt/machine-learning-book', 0.6046102046966553, 'study', 3), ('huggingface/transformers', 0.5814858078956604, 'nlp', 5), ('tensorflow/tensorflow', 0.5672532916069031, 'ml-dl', 2), ('ludwig-ai/ludwig', 0.5534067749977112, 'ml-ops', 5), ('nvidia/deeplearningexamples', 0.5403677821159363, 'ml-dl', 3), ('milvus-io/bootcamp', 0.5314620733261108, 'data', 1), ('speechbrain/speechbrain', 0.5235595107078552, 'nlp', 2), ('lightly-ai/lightly', 0.5161562561988831, 'ml', 4), ('onnx/onnx', 0.5151509642601013, 'ml', 3), ('keras-team/autokeras', 0.514286458492279, 'ml-dl', 2), ('ddbourgin/numpy-ml', 0.5134571194648743, 'ml', 1), ('deepmind/deepmind-research', 0.5121714472770691, 'ml', 0), ('alpa-projects/alpa', 0.5067688822746277, 'ml-dl', 2), ('aiqc/aiqc', 0.5059452652931213, 'ml-ops', 0), ('huggingface/datasets', 0.505528450012207, 'nlp', 5), ('nyandwi/modernconvnets', 0.5045065879821777, 'ml-dl', 1), ('salesforce/blip', 0.5032647848129272, 'diffusion', 0), ('keras-team/keras', 0.5026553869247437, 'ml-dl', 3), ('pycaret/pycaret', 0.50245600938797, 'ml', 2), ('explosion/thinc', 0.5021923780441284, 'ml-dl', 4), ('huggingface/autotrain-advanced', 0.5021505355834961, 'ml', 3), ('keras-team/keras-nlp', 0.5014702677726746, 'nlp', 3)] | 20 | 5 | null | 0.92 | 30 | 20 | 21 | 2 | 0 | 1 | 1 | 30 | 55 | 90 | 1.8 | 44 |
1,641 | llm | https://github.com/linksoul-ai/autoagents | ['autonomous-agents'] | null | [] | [] | null | null | null | linksoul-ai/autoagents | AutoAgents | 889 | 107 | 20 | Python | https://huggingface.co/spaces/LinkSoul/AutoAgents | Generate different roles for GPTs to form a collaborative entity for complex tasks. | linksoul-ai | 2024-01-13 | 2023-08-21 | 23 | 38.41358 | https://avatars.githubusercontent.com/u/147458898?v=4 | Generate different roles for GPTs to form a collaborative entity for complex tasks. | [] | ['autonomous-agents'] | 2023-11-24 | [('assafelovic/gpt-researcher', 0.6728865504264832, 'llm', 0), ('yoheinakajima/babyagi', 0.6577290892601013, 'llm', 1), ('geekan/metagpt', 0.6280576586723328, 'llm', 0), ('torantulino/auto-gpt', 0.5497490167617798, 'llm', 1), ('langchain-ai/opengpts', 0.5377379655838013, 'llm', 0), ('operand/agency', 0.5123705267906189, 'llm', 1)] | 11 | 3 | null | 1.44 | 17 | 6 | 5 | 2 | 0 | 0 | 0 | 17 | 9 | 90 | 0.5 | 44 |
684 | util | https://github.com/pyfpdf/fpdf2 | [] | null | [] | [] | null | null | null | pyfpdf/fpdf2 | fpdf2 | 860 | 211 | 23 | Python | https://py-pdf.github.io/fpdf2/ | Simple PDF generation for Python | pyfpdf | 2024-01-12 | 2017-03-15 | 358 | 2.396497 | https://avatars.githubusercontent.com/u/102914013?v=4 | Simple PDF generation for Python | ['barcode', 'markdown', 'pdf', 'pdf-generation', 'pdf-library', 'svg'] | ['barcode', 'markdown', 'pdf', 'pdf-generation', 'pdf-library', 'svg'] | 2024-01-02 | [('py-pdf/pypdf2', 0.6898808479309082, 'util', 1), ('pypdfium2-team/pypdfium2', 0.6115421652793884, 'util', 1), ('jorisschellekens/borb', 0.6073178052902222, 'util', 3), ('camelot-dev/camelot', 0.5940113663673401, 'util', 0), ('google/latexify_py', 0.5399512052536011, 'util', 0), ('pdfminer/pdfminer.six', 0.5335804224014282, 'util', 1), ('unstructured-io/pipeline-paddleocr', 0.531453549861908, 'data', 1), ('lukasschwab/arxiv.py', 0.5308734774589539, 'util', 1), ('google/yapf', 0.5062951445579529, 'util', 0), ('microsoft/genalog', 0.5020582675933838, 'data', 0), ('connorferster/handcalcs', 0.5012051463127136, 'jupyter', 0)] | 116 | 3 | null | 5.4 | 152 | 122 | 83 | 0 | 7 | 6 | 7 | 152 | 399 | 90 | 2.6 | 44 |
898 | data | https://github.com/googleapis/python-bigquery | [] | null | [] | [] | null | null | null | googleapis/python-bigquery | python-bigquery | 686 | 316 | 54 | Python | null | null | googleapis | 2024-01-11 | 2019-12-10 | 216 | 3.175926 | https://avatars.githubusercontent.com/u/16785467?v=4 | googleapis/python-bigquery | [] | [] | 2024-01-12 | [('pytables/pytables', 0.5208421349525452, 'data', 0), ('ibis-project/ibis', 0.5185703635215759, 'data', 0), ('googleapis/google-api-python-client', 0.5121608376502991, 'util', 0), ('ofek/pypinfo', 0.5070151686668396, 'util', 0)] | 142 | 5 | null | 2.87 | 152 | 115 | 50 | 0 | 20 | 34 | 20 | 152 | 196 | 90 | 1.3 | 44 |
796 | util | https://github.com/open-telemetry/opentelemetry-python-contrib | [] | null | [] | [] | null | null | null | open-telemetry/opentelemetry-python-contrib | opentelemetry-python-contrib | 554 | 469 | 16 | Python | https://opentelemetry.io | OpenTelemetry instrumentation for Python modules | open-telemetry | 2024-01-13 | 2019-11-08 | 220 | 2.511658 | https://avatars.githubusercontent.com/u/49998002?v=4 | OpenTelemetry instrumentation for Python modules | [] | [] | 2024-01-11 | [('open-telemetry/opentelemetry-python', 0.7430706024169922, 'util', 0), ('pympler/pympler', 0.5808881521224976, 'perf', 0), ('gaogaotiantian/viztracer', 0.5290429592132568, 'profiling', 0), ('openai/openai-python', 0.5244234204292297, 'util', 0)] | 226 | 6 | null | 2.98 | 177 | 78 | 51 | 0 | 7 | 10 | 7 | 177 | 243 | 90 | 1.4 | 44 |
1,607 | llm | https://github.com/zhudotexe/kani | [] | null | [] | [] | null | null | null | zhudotexe/kani | kani | 499 | 24 | 9 | Python | https://kani.readthedocs.io | kani (カニ) is a highly hackable microframework for chat-based language models with tool use/function calling. (NLP-OSS @ EMNLP 2023) | zhudotexe | 2024-01-14 | 2023-07-14 | 28 | 17.465 | null | kani (カニ) is a highly hackable microframework for chat-based language models with tool use/function calling. (NLP-OSS @ EMNLP 2023) | ['chatgpt', 'claude-2', 'framework', 'function-calling', 'gpt-3', 'gpt-4', 'large-language-models', 'llama', 'llama-2', 'llms', 'microframework', 'openai', 'tool-use'] | ['chatgpt', 'claude-2', 'framework', 'function-calling', 'gpt-3', 'gpt-4', 'large-language-models', 'llama', 'llama-2', 'llms', 'microframework', 'openai', 'tool-use'] | 2023-12-04 | [('lm-sys/fastchat', 0.579633891582489, 'llm', 0), ('thudm/chatglm2-6b', 0.5553779602050781, 'llm', 1), ('openai/tiktoken', 0.528551459312439, 'nlp', 1), ('next-gpt/next-gpt', 0.5206196904182434, 'llm', 3), ('embedchain/embedchain', 0.5120741724967957, 'llm', 1), ('microsoft/autogen', 0.5002747178077698, 'llm', 2)] | 6 | 3 | null | 4.69 | 7 | 6 | 6 | 1 | 18 | 36 | 18 | 7 | 4 | 90 | 0.6 | 44 |
1,860 | sim | https://github.com/nvidia-omniverse/orbit | ['robot-learning'] | null | [] | [] | null | null | null | nvidia-omniverse/orbit | orbit | 494 | 135 | 23 | Python | https://isaac-orbit.github.io/orbit/ | Unified framework for robot learning built on NVIDIA Isaac Sim | nvidia-omniverse | 2024-01-13 | 2022-11-16 | 62 | 7.859091 | https://avatars.githubusercontent.com/u/57824658?v=4 | Unified framework for robot learning built on NVIDIA Isaac Sim | ['omniverse-kit-extension', 'robot-learning', 'robotics'] | ['omniverse-kit-extension', 'robot-learning', 'robotics'] | 2024-01-11 | [('nvidia-omniverse/omniisaacgymenvs', 0.6811214685440063, 'sim', 1), ('arise-initiative/robosuite', 0.6593456268310547, 'ml-rl', 2), ('unity-technologies/ml-agents', 0.5719271898269653, 'ml-rl', 0), ('facebookresearch/habitat-lab', 0.5620828866958618, 'sim', 1), ('pytorch/rl', 0.5298061966896057, 'ml-rl', 1), ('salesforce/warp-drive', 0.513428270816803, 'ml-rl', 0)] | 18 | 4 | null | 4.58 | 80 | 44 | 14 | 0 | 1 | 2 | 1 | 80 | 160 | 90 | 2 | 44 |
424 | study | https://github.com/fchollet/deep-learning-with-python-notebooks | [] | null | [] | [] | null | null | null | fchollet/deep-learning-with-python-notebooks | deep-learning-with-python-notebooks | 17,496 | 8,431 | 651 | Jupyter Notebook | null | Jupyter notebooks for the code samples of the book "Deep Learning with Python" | fchollet | 2024-01-13 | 2017-09-05 | 334 | 52.383234 | null | Jupyter notebooks for the code samples of the book "Deep Learning with Python" | [] | [] | 2023-02-13 | [('ageron/handson-ml2', 0.8291416168212891, 'ml', 0), ('cohere-ai/notebooks', 0.7323339581489563, 'llm', 0), ('wesm/pydata-book', 0.6737366318702698, 'study', 0), ('mynameisfiber/high_performance_python_2e', 0.6630170941352844, 'study', 0), ('jupyter/nbformat', 0.6576974987983704, 'jupyter', 0), ('rasbt/machine-learning-book', 0.6557565331459045, 'study', 0), ('jakevdp/pythondatasciencehandbook', 0.6521231532096863, 'study', 0), ('adafruit/circuitpython', 0.6453861594200134, 'util', 0), 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107 | ml | https://github.com/nicolashug/surprise | [] | null | [] | [] | null | null | null | nicolashug/surprise | Surprise | 6,098 | 1,043 | 146 | Python | http://surpriselib.com | A Python scikit for building and analyzing recommender systems | nicolashug | 2024-01-13 | 2016-10-23 | 379 | 16.077589 | null | A Python scikit for building and analyzing recommender systems | ['factorization', 'machine-learning', 'matrix', 'recommendation', 'recommender', 'svd', 'systems'] | ['factorization', 'machine-learning', 'matrix', 'recommendation', 'recommender', 'svd', 'systems'] | 2023-01-27 | [('rucaibox/recbole', 0.5934752821922302, 'ml', 1), ('jacopotagliabue/reclist', 0.5908733010292053, 'ml', 1), ('microsoft/recommenders', 0.5881096720695496, 'study', 3), ('pytorch/torchrec', 0.5874725580215454, 'ml-dl', 0), ('rasbt/mlxtend', 0.5660281777381897, 'ml', 1), ('scikit-learn-contrib/metric-learn', 0.5304577946662903, 'ml', 1)] | 45 | 3 | null | 0.02 | 7 | 3 | 88 | 12 | 0 | 2 | 2 | 7 | 10 | 90 | 1.4 | 43 |
379 | data | https://github.com/alirezamika/autoscraper | [] | null | [] | [] | null | null | null | alirezamika/autoscraper | autoscraper | 5,757 | 618 | 125 | Python | null | A Smart, Automatic, Fast and Lightweight Web Scraper for Python | alirezamika | 2024-01-14 | 2020-08-31 | 178 | 32.31676 | null | A Smart, Automatic, Fast and Lightweight Web Scraper for Python | ['ai', 'artificial-intelligence', 'automation', 'crawler', 'machine-learning', 'scrape', 'scraper', 'scraping', 'web-scraping', 'webautomation', 'webscraping'] | ['ai', 'artificial-intelligence', 'automation', 'crawler', 'machine-learning', 'scrape', 'scraper', 'scraping', 'web-scraping', 'webautomation', 'webscraping'] | 2022-07-17 | [('scrapy/scrapy', 0.8083213567733765, 'data', 3), ('roniemartinez/dude', 0.781152606010437, 'util', 5), ('nv7-github/googlesearch', 0.7142531275749207, 'util', 0), ('clips/pattern', 0.7112637758255005, 'nlp', 1), ('binux/pyspider', 0.6465148329734802, 'data', 1), ('requests/toolbelt', 0.5791863799095154, 'util', 0), ('twintproject/twint', 0.5726699233055115, 'data', 1), ('webpy/webpy', 0.5700419545173645, 'web', 0), ('seleniumbase/seleniumbase', 0.5415842533111572, 'testing', 0), ('psf/requests', 0.5295840501785278, 'web', 0), ('cobrateam/splinter', 0.5292969346046448, 'testing', 1), ('serpapi/google-search-results-python', 0.5220003724098206, 'util', 2), ('jovianml/opendatasets', 0.5161617398262024, 'data', 1), ('falconry/falcon', 0.513289749622345, 'web', 0), ('masoniteframework/masonite', 0.5066377520561218, 'web', 0)] | 8 | 2 | null | 0 | 1 | 0 | 41 | 18 | 0 | 5 | 5 | 1 | 1 | 90 | 1 | 43 |
1,023 | finance | https://github.com/kernc/backtesting.py | [] | null | [] | [] | null | null | null | kernc/backtesting.py | backtesting.py | 4,436 | 875 | 109 | Python | https://kernc.github.io/backtesting.py/ | :mag_right: :chart_with_upwards_trend: :snake: :moneybag: Backtest trading strategies in Python. | kernc | 2024-01-14 | 2019-01-02 | 264 | 16.748652 | null | :mag_right: :chart_with_upwards_trend: 🐍 :moneybag: Backtest trading strategies in Python. | ['algo-trading', 'algorithmic-trading', 'backtesting', 'backtesting-engine', 'backtesting-frameworks', 'backtesting-trading-strategies', 'finance', 'financial-markets', 'forex', 'forex-trading', 'framework', 'investing', 'investment', 'investment-strategies', 'stocks', 'trading', 'trading-algorithms', 'trading-simulator', 'trading-strategies'] | ['algo-trading', 'algorithmic-trading', 'backtesting', 'backtesting-engine', 'backtesting-frameworks', 'backtesting-trading-strategies', 'finance', 'financial-markets', 'forex', 'forex-trading', 'framework', 'investing', 'investment', 'investment-strategies', 'stocks', 'trading', 'trading-algorithms', 'trading-simulator', 'trading-strategies'] | 2023-01-15 | [('cuemacro/finmarketpy', 0.6904587149620056, 'finance', 2), ('mementum/backtrader', 0.6531647443771362, 'finance', 2), ('polakowo/vectorbt', 0.6390688419342041, 'finance', 5), ('ranaroussi/quantstats', 0.62286376953125, 'finance', 3), ('quantconnect/lean', 0.5955772995948792, 'finance', 5), ('blankly-finance/blankly', 0.5919058918952942, 'finance', 5), ('goldmansachs/gs-quant', 0.5561110377311707, 'finance', 1), ('gbeced/pyalgotrade', 0.5535092949867249, 'finance', 0), ('robcarver17/pysystemtrade', 0.5506398677825928, 'finance', 0), ('gbeced/basana', 0.5409364700317383, 'finance', 2), ('quantopian/zipline', 0.540707528591156, 'finance', 1), ('zvtvz/zvt', 0.5392759442329407, 'finance', 3), ('bashtage/arch', 0.5312038064002991, 'time-series', 1), ('ai4finance-foundation/finrl', 0.5252265334129333, 'finance', 2), ('idanya/algo-trader', 0.522881269454956, 'finance', 3), ('ta-lib/ta-lib-python', 0.512697160243988, 'finance', 1), ('firmai/atspy', 0.5046423673629761, 'time-series', 1)] | 19 | 4 | null | 0 | 30 | 3 | 61 | 12 | 0 | 4 | 4 | 30 | 23 | 90 | 0.8 | 43 |
1,840 | finance | https://github.com/twopirllc/pandas-ta | [] | null | [] | [] | null | null | null | twopirllc/pandas-ta | pandas-ta | 4,335 | 871 | 92 | Python | https://twopirllc.github.io/pandas-ta/ | Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators | twopirllc | 2024-01-14 | 2019-02-19 | 258 | 16.802326 | null | Technical Analysis Indicators - Pandas TA is an easy to use Python 3 Pandas Extension with 130+ Indicators | ['dataframe', 'finance', 'fundamental-analysis', 'jupyter-notebook', 'pandas', 'pandas-dataframe-extension', 'pandas-extension', 'pandas-ta', 'stock-market', 'technical', 'technical-analysis', 'technical-analysis-indicators', 'technical-analysis-library', 'technical-indicators', 'trading', 'trading-algorithms'] | ['dataframe', 'finance', 'fundamental-analysis', 'jupyter-notebook', 'pandas', 'pandas-dataframe-extension', 'pandas-extension', 'pandas-ta', 'stock-market', 'technical', 'technical-analysis', 'technical-analysis-indicators', 'technical-analysis-library', 'technical-indicators', 'trading', 'trading-algorithms'] | 2022-09-24 | [('mementum/bta-lib', 0.6815423369407654, 'finance', 0), ('ta-lib/ta-lib-python', 0.6217855215072632, 'finance', 2), ('adamerose/pandasgui', 0.5920196771621704, 'pandas', 2), ('pydata/pandas-datareader', 0.5820935368537903, 'pandas', 2), ('lux-org/lux', 0.5814751386642456, 'viz', 1), ('tkrabel/bamboolib', 0.5758503675460815, 'pandas', 2), ('rapidsai/cudf', 0.542910099029541, 'pandas', 2), ('mito-ds/monorepo', 0.5410447716712952, 'jupyter', 1), ('jmcarpenter2/swifter', 0.539636492729187, 'pandas', 1), ('goldmansachs/gs-quant', 0.5390924215316772, 'finance', 0), ('kanaries/pygwalker', 0.5264495611190796, 'pandas', 2), ('ranaroussi/quantstats', 0.5218469500541687, 'finance', 1), ('nalepae/pandarallel', 0.517140805721283, 'pandas', 1), ('man-group/dtale', 0.5126270651817322, 'viz', 2), ('alkaline-ml/pmdarima', 0.5053380131721497, 'time-series', 0), ('stefmolin/stock-analysis', 0.5048727989196777, 'finance', 2), ('pandas-dev/pandas', 0.5036715269088745, 'pandas', 2), ('wesm/pydata-book', 0.5033674240112305, 'study', 0), ('holoviz/panel', 0.5016809105873108, 'viz', 0)] | 45 | 1 | null | 0 | 45 | 32 | 60 | 16 | 0 | 1 | 1 | 46 | 136 | 90 | 3 | 43 |
1,025 | finance | https://github.com/ranaroussi/quantstats | [] | null | [] | [] | null | null | null | ranaroussi/quantstats | quantstats | 3,886 | 748 | 93 | Python | null | Portfolio analytics for quants, written in Python | ranaroussi | 2024-01-14 | 2019-05-01 | 247 | 15.678386 | null | Portfolio analytics for quants, written in Python | ['algo-trading', 'algorithmic-trading', 'algotrading', 'finance', 'plotting', 'quant', 'quantitative-analysis', 'quantitative-finance', 'quantitative-trading', 'visualization'] | ['algo-trading', 'algorithmic-trading', 'algotrading', 'finance', 'plotting', 'quant', 'quantitative-analysis', 'quantitative-finance', 'quantitative-trading', 'visualization'] | 2023-07-06 | [('goldmansachs/gs-quant', 0.7339354157447815, 'finance', 0), ('plotly/dash', 0.6857461333274841, 'viz', 1), ('quantconnect/lean', 0.6603469848632812, 'finance', 1), ('quantopian/pyfolio', 0.6542462706565857, 'finance', 0), ('zvtvz/zvt', 0.6442165970802307, 'finance', 4), ('polakowo/vectorbt', 0.6319853663444519, 'finance', 4), ('statsmodels/statsmodels', 0.6285594701766968, 'ml', 0), ('kernc/backtesting.py', 0.62286376953125, 'finance', 3), ('gbeced/pyalgotrade', 0.6159399747848511, 'finance', 0), ('scikit-mobility/scikit-mobility', 0.6154873967170715, 'gis', 0), ('polyaxon/datatile', 0.6079445481300354, 'pandas', 0), ('cuemacro/finmarketpy', 0.6077700853347778, 'finance', 0), ('quantopian/zipline', 0.5925479531288147, 'finance', 2), ('holoviz/panel', 0.5793597102165222, 'viz', 0), ('krzjoa/awesome-python-data-science', 0.5782219767570496, 'study', 0), ('thealgorithms/python', 0.5772646069526672, 'study', 0), ('firmai/atspy', 0.5767538547515869, 'time-series', 1), ('ta-lib/ta-lib-python', 0.566260814666748, 'finance', 2), ('pandas-dev/pandas', 0.5643635988235474, 'pandas', 0), ('man-group/dtale', 0.55287766456604, 'viz', 1), ('google/tf-quant-finance', 0.5515581369400024, 'finance', 2), ('scikit-learn/scikit-learn', 0.5498625636100769, 'ml', 0), ('clips/pattern', 0.5454891324043274, 'nlp', 0), ('wesm/pydata-book', 0.5430867671966553, 'study', 0), ('robcarver17/pysystemtrade', 0.5409232378005981, 'finance', 0), ('sloria/textblob', 0.5343949794769287, 'nlp', 0), ('eleutherai/pyfra', 0.5325418710708618, 'ml', 0), ('openbb-finance/openbbterminal', 0.53244549036026, 'finance', 2), ('stefmolin/stock-analysis', 0.5322091579437256, 'finance', 0), ('networkx/networkx', 0.5321804881095886, 'graph', 0), ('1200wd/bitcoinlib', 0.5297749638557434, 'crypto', 0), ('gbeced/basana', 0.5287092328071594, 'finance', 1), ('bokeh/bokeh', 0.5271790027618408, 'viz', 2), ('dagworks-inc/hamilton', 0.5268656015396118, 'ml-ops', 0), ('domokane/financepy', 0.526004433631897, 'finance', 1), ('dylanhogg/awesome-python', 0.5245246887207031, 'study', 0), ('ydataai/ydata-profiling', 0.5242244005203247, 'pandas', 0), ('alkaline-ml/pmdarima', 0.522229790687561, 'time-series', 0), ('twopirllc/pandas-ta', 0.5218469500541687, 'finance', 1), ('plotly/plotly.py', 0.5214852094650269, 'viz', 1), ('malloydata/malloy-py', 0.5185449123382568, 'data', 0), ('numerai/example-scripts', 0.5179154872894287, 'finance', 0), ('hydrosquall/tiingo-python', 0.5174421072006226, 'finance', 1), ('microsoft/qlib', 0.5154274702072144, 'finance', 5), ('quantecon/quantecon.py', 0.513916015625, 'sim', 0), ('gradio-app/gradio', 0.5128483176231384, 'viz', 0), ('keon/algorithms', 0.5114973187446594, 'util', 0), ('mementum/bta-lib', 0.5088109970092773, 'finance', 0), ('ai4finance-foundation/finrl', 0.5057669878005981, 'finance', 2), ('matplotlib/mplfinance', 0.5049977898597717, 'finance', 1), ('bashtage/arch', 0.5018336772918701, 'time-series', 1), ('federicoceratto/dashing', 0.5010005235671997, 'term', 0), ('online-ml/river', 0.5004301071166992, 'ml', 0)] | 32 | 3 | null | 0.52 | 25 | 6 | 57 | 6 | 3 | 3 | 3 | 25 | 20 | 90 | 0.8 | 43 |
1,112 | web | https://github.com/pylons/pyramid | [] | null | [] | [] | null | null | null | pylons/pyramid | pyramid | 3,875 | 931 | 161 | Python | https://trypyramid.com/ | Pyramid - A Python web framework | pylons | 2024-01-13 | 2010-10-24 | 692 | 5.5974 | https://avatars.githubusercontent.com/u/452227?v=4 | Pyramid - A Python web framework | ['pylons', 'pyramid', 'web-framework', 'wsgi'] | ['pylons', 'pyramid', 'web-framework', 'wsgi'] | 2023-09-14 | [('pallets/flask', 0.7600159049034119, 'web', 2), ('pallets/werkzeug', 0.7471210360527039, 'web', 1), ('bottlepy/bottle', 0.7196846008300781, 'web', 2), ('masoniteframework/masonite', 0.6714824438095093, 'web', 0), ('webpy/webpy', 0.6500197052955627, 'web', 0), ('klen/muffin', 0.6305515766143799, 'web', 0), ('falconry/falcon', 0.6222757697105408, 'web', 1), ('neoteroi/blacksheep', 0.5955870151519775, 'web', 0), ('pallets/quart', 0.5922417640686035, 'web', 0), ('scrapy/scrapy', 0.5863667726516724, 'data', 0), ('eleutherai/pyfra', 0.5796028971672058, 'ml', 0), ('reflex-dev/reflex', 0.5728359818458557, 'web', 0), ('pypy/pypy', 0.5644940137863159, 'util', 0), ('encode/uvicorn', 0.5620464086532593, 'web', 0), ('benoitc/gunicorn', 0.5611777305603027, 'web', 1), ('timofurrer/awesome-asyncio', 0.5598770380020142, 'study', 0), ('cherrypy/cherrypy', 0.5556930303573608, 'web', 0), ('feincms/feincms', 0.5519199371337891, 'web', 0), ('willmcgugan/textual', 0.5482103228569031, 'term', 0), ('emmett-framework/emmett', 0.5466519594192505, 'web', 1), ('pyglet/pyglet', 0.5355060696601868, 'gamedev', 0), ('pyodide/pyodide', 0.5352792739868164, 'util', 0), ('pylons/waitress', 0.5299732089042664, 'web', 0), ('python/cpython', 0.5238844752311707, 'util', 0), ('django/django', 0.5236054062843323, 'web', 0), ('pycqa/pylint-django', 0.5214040279388428, 'util', 0), ('r0x0r/pywebview', 0.5202688574790955, 'gui', 0), ('sqlalchemy/mako', 0.5201253890991211, 'template', 0), ('encode/httpx', 0.5153858661651611, 'web', 0), ('clips/pattern', 0.5145288705825806, 'nlp', 0), ('starlite-api/starlite', 0.5109481811523438, 'web', 0), ('holoviz/panel', 0.507599949836731, 'viz', 0), ('python-restx/flask-restx', 0.5075467824935913, 'web', 0), ('alirn76/panther', 0.5073546767234802, 'web', 0), ('pyston/pyston', 0.5057663321495056, 'util', 0), ('dylanhogg/awesome-python', 0.5040434002876282, 'study', 0), ('pytoolz/toolz', 0.5017217993736267, 'util', 0), ('requests/toolbelt', 0.5011575222015381, 'util', 0)] | 349 | 4 | null | 0.48 | 8 | 0 | 161 | 4 | 0 | 11 | 11 | 8 | 12 | 90 | 1.5 | 43 |
928 | ml-dl | https://github.com/williamyang1991/vtoonify | [] | null | [] | [] | null | null | null | williamyang1991/vtoonify | VToonify | 3,408 | 434 | 64 | Jupyter Notebook | null | [SIGGRAPH Asia 2022] VToonify: Controllable High-Resolution Portrait Video Style Transfer | williamyang1991 | 2024-01-12 | 2022-09-09 | 72 | 46.96063 | null | [SIGGRAPH Asia 2022] VToonify: Controllable High-Resolution Portrait Video Style Transfer | ['face', 'siggraph-asia', 'style-transfer', 'stylegan2', 'toonify', 'video-style-transfer'] | ['face', 'siggraph-asia', 'style-transfer', 'stylegan2', 'toonify', 'video-style-transfer'] | 2023-02-24 | [('chenyangqiqi/fatezero', 0.5721680521965027, 'diffusion', 1), ('thudm/cogvideo', 0.5548344850540161, 'ml', 0), ('mchong6/jojogan', 0.515015184879303, 'data', 0)] | 4 | 3 | null | 0.04 | 5 | 1 | 16 | 11 | 0 | 0 | 0 | 5 | 4 | 90 | 0.8 | 43 |
1,708 | util | https://github.com/tartley/colorama | ['terminal', 'ansi'] | null | [] | [] | null | null | null | tartley/colorama | colorama | 3,328 | 239 | 45 | Python | null | Simple cross-platform colored terminal text in Python | tartley | 2024-01-12 | 2014-04-17 | 510 | 6.516364 | null | Simple cross-platform colored terminal text in Python | [] | ['ansi', 'terminal'] | 2023-12-01 | [('willmcgugan/rich', 0.7069451808929443, 'term', 1), ('jquast/blessed', 0.5634984970092773, 'term', 1), ('carpedm20/emoji', 0.5459503531455994, 'util', 0), ('urwid/urwid', 0.5115954279899597, 'term', 0)] | 51 | 5 | null | 0.06 | 3 | 2 | 119 | 1 | 0 | 2 | 2 | 3 | 7 | 90 | 2.3 | 43 |
1,180 | nlp | https://github.com/errbotio/errbot | [] | null | [] | [] | null | null | null | errbotio/errbot | errbot | 3,012 | 612 | 74 | Python | http://errbot.io | Errbot is a chatbot, a daemon that connects to your favorite chat service and bring your tools and some fun into the conversation. | errbotio | 2024-01-12 | 2012-05-20 | 610 | 4.935393 | https://avatars.githubusercontent.com/u/15802630?v=4 | Errbot is a chatbot, a daemon that connects to your favorite chat service and bring your tools and some fun into the conversation. | ['automation', 'chat', 'chatbot', 'chatbots', 'chatops', 'devops', 'hacktoberfest2020'] | ['automation', 'chat', 'chatbot', 'chatbots', 'chatops', 'devops', 'hacktoberfest2020'] | 2024-01-01 | [('gunthercox/chatterbot', 0.5522263646125793, 'nlp', 1), ('togethercomputer/openchatkit', 0.5380634665489197, 'nlp', 1), ('deep-diver/llm-as-chatbot', 0.5012304186820984, 'llm', 1)] | 214 | 5 | null | 0.56 | 44 | 38 | 142 | 0 | 1 | 7 | 1 | 44 | 40 | 90 | 0.9 | 43 |
968 | ml | https://github.com/lucidrains/musiclm-pytorch | [] | null | [] | [] | 1 | null | null | lucidrains/musiclm-pytorch | musiclm-pytorch | 2,873 | 240 | 96 | Python | null | Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch | lucidrains | 2024-01-13 | 2023-01-27 | 52 | 54.649457 | null | Implementation of MusicLM, Google's new SOTA model for music generation using attention networks, in Pytorch | ['artificial-intelligence', 'attention-mechanisms', 'deep-learning', 'music-synthesis', 'transformers'] | ['artificial-intelligence', 'attention-mechanisms', 'deep-learning', 'music-synthesis', 'transformers'] | 2023-09-06 | [('huggingface/diffusers', 0.54345703125, 'diffusion', 1)] | 2 | 0 | null | 1.37 | 3 | 1 | 12 | 4 | 38 | 39 | 38 | 3 | 1 | 90 | 0.3 | 43 |
95 | term | https://github.com/urwid/urwid | [] | null | [] | [] | null | null | null | urwid/urwid | urwid | 2,681 | 313 | 61 | Python | urwid.org | Console user interface library for Python (official repo) | urwid | 2024-01-13 | 2010-02-25 | 726 | 3.689208 | https://avatars.githubusercontent.com/u/6749304?v=4 | Console user interface library for Python (official repo) | [] | [] | 2024-01-12 | [('jquast/blessed', 0.7145931720733643, 'term', 0), ('pygamelib/pygamelib', 0.700258731842041, 'gamedev', 0), ('hoffstadt/dearpygui', 0.6700049042701721, 'gui', 0), ('beeware/toga', 0.6368706822395325, 'gui', 0), ('pytoolz/toolz', 0.6324057579040527, 'util', 0), ('r0x0r/pywebview', 0.6302554607391357, 'gui', 0), ('google/python-fire', 0.6262136101722717, 'term', 0), ('pypy/pypy', 0.6176603436470032, 'util', 0), ('python/cpython', 0.613335907459259, 'util', 0), ('willmcgugan/textual', 0.6095877885818481, 'term', 0), ('samuelcolvin/python-devtools', 0.5885550379753113, 'debug', 0), ('landscapeio/prospector', 0.586963951587677, 'util', 0), ('pyglet/pyglet', 0.5836073160171509, 'gamedev', 0), ('openai/openai-python', 0.5712311267852783, 'util', 0), ('tmbo/questionary', 0.5709437727928162, 'term', 0), ('pyscript/pyscript-cli', 0.5667005181312561, 'web', 0), ('rockhopper-technologies/enlighten', 0.5648614764213562, 'term', 0), ('federicoceratto/dashing', 0.5645572543144226, 'term', 0), ('kivy/kivy', 0.5640290975570679, 'util', 0), ('pdm-project/pdm', 0.5620359778404236, 'util', 0), ('dddomodossola/remi', 0.5620279312133789, 'gui', 0), ('alexmojaki/snoop', 0.5546684265136719, 'debug', 0), ('pexpect/pexpect', 0.553383469581604, 'util', 0), ('inducer/pudb', 0.5516170859336853, 'debug', 0), ('hugovk/pypistats', 0.5486549735069275, 'util', 0), ('parthjadhav/tkinter-designer', 0.5480352640151978, 'gui', 0), ('ethereum/web3.py', 0.5449756979942322, 'crypto', 0), ('googleapis/google-api-python-client', 0.54488605260849, 'util', 0), ('ipython/ipython', 0.5444232821464539, 'util', 0), ('prompt-toolkit/ptpython', 0.5443150997161865, 'util', 0), ('tiangolo/typer', 0.5432376861572266, 'term', 0), ('pypa/hatch', 0.5425727963447571, 'util', 0), ('xonsh/xonsh', 0.5422582030296326, 'util', 0), ('eleutherai/pyfra', 0.5409858822822571, 'ml', 0), ('masoniteframework/masonite', 0.5398597121238708, 'web', 0), ('jiffyclub/snakeviz', 0.5396429300308228, 'profiling', 0), ('willmcgugan/rich', 0.538774847984314, 'term', 0), ('pyston/pyston', 0.5381410121917725, 'util', 0), ('paramiko/paramiko', 0.5337045192718506, 'util', 0), ('webpy/webpy', 0.533157467842102, 'web', 0), ('simple-salesforce/simple-salesforce', 0.5318827629089355, 'data', 0), ('pypi/warehouse', 0.5293185710906982, 'util', 0), ('pysimplegui/pysimplegui', 0.5266430974006653, 'gui', 0), ('plotly/plotly.py', 0.5260567665100098, 'viz', 0), ('pallets/click', 0.5238144993782043, 'term', 0), ('reactive-python/reactpy', 0.5233248472213745, 'web', 0), ('irmen/pyminiaudio', 0.51679927110672, 'util', 0), ('pygame/pygame', 0.5163580775260925, 'gamedev', 0), ('pythonarcade/arcade', 0.5146381258964539, 'gamedev', 0), ('tartley/colorama', 0.5115954279899597, 'util', 0), ('kellyjonbrazil/jc', 0.5103952884674072, 'util', 0), ('indygreg/pyoxidizer', 0.5094347596168518, 'util', 0), ('microsoft/playwright-python', 0.5090146660804749, 'testing', 0), ('bottlepy/bottle', 0.5075056552886963, 'web', 0), ('bokeh/bokeh', 0.5072845816612244, 'viz', 0), ('amaargiru/pyroad', 0.5068714618682861, 'study', 0), ('brandtbucher/specialist', 0.5062293410301208, 'perf', 0), ('connorferster/handcalcs', 0.5055436491966248, 'jupyter', 0), ('asacristani/fastapi-rocket-boilerplate', 0.5037996172904968, 'template', 0), ('pypa/pipenv', 0.5031107664108276, 'util', 0), ('plotly/dash', 0.5028428435325623, 'viz', 0), ('pypa/installer', 0.5019884705543518, 'util', 0), ('agronholm/apscheduler', 0.501419186592102, 'util', 0), ('cython/cython', 0.5010424852371216, 'util', 0), ('hugapi/hug', 0.5001529455184937, 'util', 0)] | 138 | 1 | null | 3.56 | 117 | 104 | 169 | 0 | 7 | 4 | 7 | 117 | 159 | 90 | 1.4 | 43 |
198 | ml | https://github.com/maif/shapash | [] | null | [] | [] | null | null | null | maif/shapash | shapash | 2,555 | 311 | 39 | Jupyter Notebook | https://maif.github.io/shapash/ | 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models | maif | 2024-01-14 | 2020-04-29 | 195 | 13.045222 | https://avatars.githubusercontent.com/u/33632930?v=4 | 🔅 Shapash: User-friendly Explainability and Interpretability to Develop Reliable and Transparent Machine Learning Models | ['ethical-artificial-intelligence', 'explainability', 'explainable-ml', 'interpretability', 'lime', 'machine-learning', 'shap', 'transparency'] | ['ethical-artificial-intelligence', 'explainability', 'explainable-ml', 'interpretability', 'lime', 'machine-learning', 'shap', 'transparency'] | 2023-12-08 | [('seldonio/alibi', 0.6979689002037048, 'ml-interpretability', 2), ('slundberg/shap', 0.67304927110672, 'ml-interpretability', 4), ('csinva/imodels', 0.6528401374816895, 'ml', 3), ('interpretml/interpret', 0.6510236859321594, 'ml-interpretability', 5), ('marcotcr/lime', 0.6499969363212585, 'ml-interpretability', 0), ('linkedin/fasttreeshap', 0.6388174295425415, 'ml', 3), ('pair-code/lit', 0.62184739112854, 'ml-interpretability', 1), ('oegedijk/explainerdashboard', 0.5845269560813904, 'ml-interpretability', 1), ('tensorflow/lucid', 0.5549944639205933, 'ml-interpretability', 2), ('xplainable/xplainable', 0.551527738571167, 'ml-interpretability', 3), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5307745337486267, 'study', 1), ('huggingface/evaluate', 0.5302979946136475, 'ml', 1), ('selfexplainml/piml-toolbox', 0.527449905872345, 'ml-interpretability', 0), ('carla-recourse/carla', 0.5270743370056152, 'ml', 3), ('teamhg-memex/eli5', 0.5209477543830872, 'ml', 1), ('tensorflow/data-validation', 0.5037372708320618, 'ml-ops', 0), ('eleutherai/pythia', 0.5036888122558594, 'ml-interpretability', 1), ('microsoft/robustlearn', 0.5023934841156006, 'time-series', 0)] | 35 | 1 | null | 2.33 | 29 | 17 | 45 | 1 | 10 | 9 | 10 | 29 | 6 | 90 | 0.2 | 43 |
792 | web | https://github.com/pallets/quart | [] | null | [] | [] | null | null | null | pallets/quart | quart | 2,431 | 137 | 30 | Python | https://quart.palletsprojects.com | An async Python micro framework for building web applications. | pallets | 2024-01-12 | 2017-11-10 | 324 | 7.489877 | https://avatars.githubusercontent.com/u/16748505?v=4 | An async Python micro framework for building web applications. | ['asgi', 'asyncio', 'http-server', 'quart'] | ['asgi', 'asyncio', 'http-server', 'quart'] | 2024-01-03 | [('neoteroi/blacksheep', 0.8334370851516724, 'web', 3), ('encode/uvicorn', 0.8250173926353455, 'web', 3), ('aio-libs/aiohttp', 0.7800691723823547, 'web', 2), ('alirn76/panther', 0.7484593391418457, 'web', 0), ('encode/httpx', 0.748035192489624, 'web', 1), ('pallets/flask', 0.7176867127418518, 'web', 0), ('klen/muffin', 0.7141019701957703, 'web', 2), ('encode/starlette', 0.7032433152198792, 'web', 0), ('huge-success/sanic', 0.7020831108093262, 'web', 2), ('falconry/falcon', 0.6842796206474304, 'web', 1), ('timofurrer/awesome-asyncio', 0.6550799608230591, 'study', 1), ('python-trio/trio', 0.6473005414009094, 'perf', 0), ('starlite-api/starlite', 0.6257473230361938, 'web', 2), ('jordaneremieff/mangum', 0.6127312183380127, 'web', 3), ('masoniteframework/masonite', 0.607140302658081, 'web', 0), ('agronholm/anyio', 0.6049391627311707, 'perf', 1), ('bottlepy/bottle', 0.5997056365013123, 'web', 0), ('magicstack/uvloop', 0.5947157740592957, 'util', 1), ('pylons/pyramid', 0.5922417640686035, 'web', 0), ('sumerc/yappi', 0.5867199897766113, 'profiling', 2), ('samuelcolvin/aioaws', 0.5853649377822876, 'data', 1), ('aws/chalice', 0.5842033624649048, 'web', 0), ('cherrypy/cherrypy', 0.5793529748916626, 'web', 1), ('pylons/waitress', 0.5782569050788879, 'web', 1), ('geeogi/async-python-lambda-template', 0.5774820446968079, 'template', 0), ('tiangolo/asyncer', 0.5767269134521484, 'perf', 1), ('emmett-framework/emmett', 0.5764337778091431, 'web', 2), ('tornadoweb/tornado', 0.5757850408554077, 'web', 0), ('samuelcolvin/arq', 0.5751336216926575, 'data', 1), ('miguelgrinberg/python-socketio', 0.5742831826210022, 'util', 1), ('nficano/python-lambda', 0.5740982890129089, 'util', 0), ('reflex-dev/reflex', 0.5711527466773987, 'web', 0), ('flet-dev/flet', 0.5679628252983093, 'web', 0), ('airtai/faststream', 0.5664022564888, 'perf', 1), ('micropython/micropython', 0.5557764768600464, 'util', 0), ('webpy/webpy', 0.5523453950881958, 'web', 0), ('willmcgugan/textual', 0.5513238906860352, 'term', 0), ('pallets/werkzeug', 0.5403130054473877, 'web', 0), ('python-restx/flask-restx', 0.5398460626602173, 'web', 0), ('pyinfra-dev/pyinfra', 0.5390889048576355, 'util', 0), ('psf/requests', 0.5377407670021057, 'web', 0), ('aio-libs/aiobotocore', 0.5356045961380005, 'util', 1), ('hugapi/hug', 0.533208429813385, 'util', 1), ('ets-labs/python-dependency-injector', 0.5255832672119141, 'util', 1), ('backtick-se/cowait', 0.5232675671577454, 'util', 0), ('ajndkr/lanarky', 0.5203720331192017, 'llm', 0), ('fastai/fastcore', 0.5118736624717712, 'util', 0), ('locustio/locust', 0.5093166828155518, 'testing', 0), ('r0x0r/pywebview', 0.5082329511642456, 'gui', 0), ('requests/toolbelt', 0.5077387094497681, 'util', 0), ('gbeced/basana', 0.5044360160827637, 'finance', 1), ('eleutherai/pyfra', 0.5026024580001831, 'ml', 0)] | 99 | 2 | null | 1.56 | 35 | 19 | 75 | 1 | 0 | 10 | 10 | 35 | 21 | 90 | 0.6 | 43 |
1,535 | util | https://github.com/chaostoolkit/chaostoolkit | ['devops'] | null | [] | [] | null | null | null | chaostoolkit/chaostoolkit | chaostoolkit | 1,805 | 184 | 42 | Python | https://chaostoolkit.org | Chaos Engineering Toolkit & Orchestration for Developers | chaostoolkit | 2024-01-13 | 2017-09-24 | 331 | 5.448469 | https://avatars.githubusercontent.com/u/32068152?v=4 | Chaos Engineering Toolkit & Orchestration for Developers | ['automation', 'chaos-engineering', 'chaostoolkit', 'devops-tools', 'reliability', 'reliability-engineering', 'resiliency', 'sre'] | ['automation', 'chaos-engineering', 'chaostoolkit', 'devops', 'devops-tools', 'reliability', 'reliability-engineering', 'resiliency', 'sre'] | 2024-01-11 | [('flyteorg/flyte', 0.5509274005889893, 'ml-ops', 0), ('dagster-io/dagster', 0.5302633047103882, 'ml-ops', 0), ('pydoit/doit', 0.5246021747589111, 'util', 0), ('zenml-io/zenml', 0.5238291621208191, 'ml-ops', 1), ('tiiuae/sbomnix', 0.5200450420379639, 'util', 0), ('avaiga/taipy', 0.5186023712158203, 'data', 1), ('polyaxon/polyaxon', 0.5090064406394958, 'ml-ops', 0), ('aquasecurity/trivy', 0.5057849287986755, 'security', 0), ('pytest-dev/pytest-testinfra', 0.5015678405761719, 'testing', 2)] | 20 | 4 | null | 0.87 | 4 | 2 | 77 | 0 | 7 | 11 | 7 | 4 | 11 | 90 | 2.8 | 43 |
1,850 | util | https://github.com/python-rope/rope | [] | null | [] | [] | null | null | null | python-rope/rope | rope | 1,782 | 210 | 28 | Python | null | a python refactoring library | python-rope | 2024-01-12 | 2013-11-30 | 530 | 3.359548 | https://avatars.githubusercontent.com/u/6073454?v=4 | a python refactoring library | ['ast', 'refactoring', 'refactoring-tools'] | ['ast', 'refactoring', 'refactoring-tools'] | 2024-01-11 | [('facebookincubator/bowler', 0.7546546459197998, 'util', 1), ('pytoolz/toolz', 0.649603009223938, 'util', 0), ('asottile/reorder-python-imports', 0.5853264331817627, 'util', 1), ('instagram/libcst', 0.5846632719039917, 'util', 1), ('instagram/fixit', 0.5731984972953796, 'util', 0), ('dosisod/refurb', 0.5674479007720947, 'util', 0), ('landscapeio/prospector', 0.5660980939865112, 'util', 0), ('grahamdumpleton/wrapt', 0.5636062026023865, 'util', 0), ('google/pyglove', 0.5538163781166077, 'util', 0), ('eugeneyan/python-collab-template', 0.5535590648651123, 'template', 0), ('pypy/pypy', 0.5428261160850525, 'util', 0), ('eleutherai/pyfra', 0.5410192608833313, 'ml', 0), ('pyston/pyston', 0.5357602834701538, 'util', 0), ('amaargiru/pyroad', 0.528800904750824, 'study', 0), ('google/latexify_py', 0.5269980430603027, 'util', 0), ('python/cpython', 0.5254427194595337, 'util', 0), ('hhatto/autopep8', 0.5218623876571655, 'util', 0), ('reloadware/reloadium', 0.5215712785720825, 'profiling', 0), ('xrudelis/pytrait', 0.5170307159423828, 'util', 0), ('facebook/pyre-check', 0.5157984495162964, 'typing', 0), ('fastai/fastcore', 0.5134739875793457, 'util', 0), ('google/pytype', 0.5130378603935242, 'typing', 0), ('pandas-dev/pandas', 0.5107076168060303, 'pandas', 0), ('pympler/pympler', 0.5101566910743713, 'perf', 0), ('beeware/toga', 0.5071592330932617, 'gui', 0), ('mkdocstrings/griffe', 0.5066107511520386, 'util', 0), ('psf/black', 0.504595935344696, 'util', 0), ('pdm-project/pdm', 0.5023258328437805, 'util', 0), ('mementum/backtrader', 0.50078284740448, 'finance', 0), ('timofurrer/awesome-asyncio', 0.5005401968955994, 'study', 0)] | 81 | 3 | null | 2.19 | 35 | 23 | 123 | 0 | 0 | 5 | 5 | 35 | 77 | 90 | 2.2 | 43 |
395 | web | https://github.com/neoteroi/blacksheep | [] | null | [] | [] | null | null | null | neoteroi/blacksheep | BlackSheep | 1,584 | 68 | 28 | Python | https://www.neoteroi.dev/blacksheep/ | Fast ASGI web framework for Python | neoteroi | 2024-01-13 | 2018-11-22 | 270 | 5.851187 | https://avatars.githubusercontent.com/u/72765587?v=4 | Fast ASGI web framework for Python | ['asgi', 'asyncio', 'blacksheep', 'framework', 'http', 'http-server', 'server', 'web'] | ['asgi', 'asyncio', 'blacksheep', 'framework', 'http', 'http-server', 'server', 'web'] | 2024-01-12 | [('encode/uvicorn', 0.8586666584014893, 'web', 4), ('pallets/quart', 0.8334370851516724, 'web', 3), ('klen/muffin', 0.7668511271476746, 'web', 2), ('huge-success/sanic', 0.7380421161651611, 'web', 4), ('aio-libs/aiohttp', 0.7317296862602234, 'web', 3), ('encode/httpx', 0.7281930446624756, 'web', 2), ('alirn76/panther', 0.7121951580047607, 'web', 1), ('falconry/falcon', 0.6875892877578735, 'web', 4), ('encode/starlette', 0.6760811805725098, 'web', 1), ('starlite-api/starlite', 0.6740537881851196, 'web', 2), ('pallets/flask', 0.6553666591644287, 'web', 0), ('jordaneremieff/mangum', 0.6414300203323364, 'web', 2), ('cherrypy/cherrypy', 0.6155569553375244, 'web', 2), ('timofurrer/awesome-asyncio', 0.6109622716903687, 'study', 1), ('pallets/werkzeug', 0.5996673703193665, 'web', 1), ('masoniteframework/masonite', 0.5978954434394836, 'web', 2), ('klen/py-frameworks-bench', 0.5975432395935059, 'perf', 0), ('pylons/pyramid', 0.5955870151519775, 'web', 0), ('bottlepy/bottle', 0.5855295062065125, 'web', 0), ('magicstack/uvloop', 0.5796182155609131, 'util', 1), ('sumerc/yappi', 0.577142596244812, 'profiling', 2), ('geeogi/async-python-lambda-template', 0.5758123397827148, 'template', 0), ('locustio/locust', 0.5740907192230225, 'testing', 1), ('pylons/waitress', 0.5685455799102783, 'web', 1), ('emmett-framework/emmett', 0.5676200985908508, 'web', 2), ('webpy/webpy', 0.5648735761642456, 'web', 0), ('fastai/fastcore', 0.5601794719696045, 'util', 0), ('psf/requests', 0.551236629486084, 'web', 1), ('miguelgrinberg/python-socketio', 0.5502622127532959, 'util', 1), ('python-trio/trio', 0.5497913956642151, 'perf', 0), ('benoitc/gunicorn', 0.542283296585083, 'web', 2), ('reflex-dev/reflex', 0.5400927066802979, 'web', 1), ('samuelcolvin/arq', 0.5355557799339294, 'data', 1), ('ets-labs/python-dependency-injector', 0.5310226678848267, 'util', 1), ('scrapy/scrapy', 0.53035569190979, 'data', 1), ('requests/toolbelt', 0.5285502672195435, 'util', 1), ('agronholm/anyio', 0.5259332656860352, 'perf', 1), ('airtai/faststream', 0.5211659073829651, 'perf', 1), ('tornadoweb/tornado', 0.5203468203544617, 'web', 0), ('python-restx/flask-restx', 0.519770085811615, 'web', 0), ('tiangolo/fastapi', 0.5194063782691956, 'web', 3), ('pypy/pypy', 0.5189310908317566, 'util', 0), ('aminalaee/sqladmin', 0.5168036818504333, 'data', 3), ('aws/chalice', 0.5133174657821655, 'web', 0), ('flet-dev/flet', 0.5072730183601379, 'web', 1), ('pyinfra-dev/pyinfra', 0.5058210492134094, 'util', 0), ('grantjenks/python-diskcache', 0.5029258728027344, 'util', 0)] | 16 | 2 | null | 0.96 | 49 | 46 | 63 | 0 | 29 | 12 | 29 | 49 | 80 | 90 | 1.6 | 43 |
1,366 | ml | https://github.com/microsoft/i-code | [] | The ambition of the i-Code project is to build integrative and composable multimodal AI. The "i" stands for integrative multimodal learning. | [] | [] | null | null | null | microsoft/i-code | i-Code | 1,551 | 159 | 39 | Jupyter Notebook | null | null | microsoft | 2024-01-12 | 2022-12-07 | 59 | 25.911695 | https://avatars.githubusercontent.com/u/6154722?v=4 | The ambition of the i-Code project is to build integrative and composable multimodal AI. The "i" stands for integrative multimodal learning. | [] | [] | 2023-11-30 | [('facebookresearch/mmf', 0.5485939383506775, 'ml-dl', 0), ('invoke-ai/invokeai', 0.5126618146896362, 'diffusion', 0)] | 13 | 2 | null | 3.71 | 11 | 4 | 13 | 1 | 0 | 0 | 0 | 11 | 6 | 90 | 0.5 | 43 |
1,593 | data | https://github.com/milvus-io/bootcamp | ['vector-database', 'question-answering', 'embeddings'] | null | [] | [] | 1 | null | null | milvus-io/bootcamp | bootcamp | 1,510 | 519 | 30 | HTML | https://milvus.io | Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc. | milvus-io | 2024-01-13 | 2019-08-09 | 233 | 6.464832 | https://avatars.githubusercontent.com/u/51735404?v=4 | Dealing with all unstructured data, such as reverse image search, audio search, molecular search, video analysis, question and answer systems, NLP, etc. | ['audio-search', 'benchmark-testing', 'deep-learning', 'image-classification', 'image-recognition', 'image-search', 'milvus', 'nlp', 'question-answering', 'unstructured-data'] | ['audio-search', 'benchmark-testing', 'deep-learning', 'embeddings', 'image-classification', 'image-recognition', 'image-search', 'milvus', 'nlp', 'question-answering', 'unstructured-data', 'vector-database'] | 2024-01-09 | [('docarray/docarray', 0.677416205406189, 'data', 1), ('jina-ai/vectordb', 0.6278480887413025, 'data', 1), ('activeloopai/deeplake', 0.6203997731208801, 'ml-ops', 2), ('neuml/txtai', 0.6126426458358765, 'nlp', 3), ('nomic-ai/nomic', 0.6042595505714417, 'nlp', 0), ('koaning/embetter', 0.6010968089103699, 'data', 0), ('qdrant/qdrant', 0.5713267922401428, 'data', 2), ('marqo-ai/marqo', 0.5712332725524902, 'ml', 1), ('lancedb/lancedb', 0.566419780254364, 'data', 2), ('chroma-core/chroma', 0.5605462789535522, 'data', 1), ('awslabs/autogluon', 0.5507424473762512, 'ml', 2), ('huggingface/datasets', 0.545052170753479, 'nlp', 2), ('sloria/textblob', 0.5331091284751892, 'nlp', 1), ('microsoft/semi-supervised-learning', 0.5314620733261108, 'ml', 1), ('ddbourgin/numpy-ml', 0.5297070741653442, 'ml', 0), ('paddlepaddle/paddlenlp', 0.528664767742157, 'llm', 2), ('featureform/embeddinghub', 0.5258285403251648, 'nlp', 2), ('explosion/thinc', 0.5245603919029236, 'ml-dl', 2), ('feast-dev/feast', 0.5231591463088989, 'ml-ops', 0), ('thilinarajapakse/simpletransformers', 0.5199248790740967, 'nlp', 1), ('qdrant/fastembed', 0.5193023681640625, 'ml', 1), ('llmware-ai/llmware', 0.518172025680542, 'llm', 4), ('koaning/human-learn', 0.5165793895721436, 'data', 0), ('fatiando/verde', 0.5155651569366455, 'gis', 0), ('koaning/whatlies', 0.5146546363830566, 'nlp', 2), ('amanchadha/coursera-deep-learning-specialization', 0.5138573050498962, 'study', 1), ('jina-ai/clip-as-service', 0.5121859312057495, 'nlp', 1), ('rare-technologies/gensim', 0.5120472311973572, 'nlp', 1), ('onnx/onnx', 0.5098041892051697, 'ml', 1), ('qdrant/vector-db-benchmark', 0.5074758529663086, 'perf', 1), ('alibaba/easynlp', 0.5068036317825317, 'nlp', 2), ('superduperdb/superduperdb', 0.5059596300125122, 'data', 0), ('firmai/industry-machine-learning', 0.5041669011116028, 'study', 0), ('mosaicml/composer', 0.5024623870849609, 'ml-dl', 1), ('tensorflow/tensorflow', 0.5004434585571289, 'ml-dl', 1)] | 80 | 3 | null | 2.42 | 79 | 73 | 54 | 0 | 1 | 3 | 1 | 79 | 85 | 90 | 1.1 | 43 |
653 | ml-dl | https://github.com/tensorly/tensorly | [] | null | [] | [] | null | null | null | tensorly/tensorly | tensorly | 1,466 | 324 | 45 | Python | http://tensorly.org | TensorLy: Tensor Learning in Python. | tensorly | 2024-01-12 | 2016-10-21 | 379 | 3.862251 | https://avatars.githubusercontent.com/u/22989719?v=4 | TensorLy: Tensor Learning in Python. | ['cupy', 'decomposition', 'jax', 'machine-learning', 'mxnet', 'numpy', 'pytorch', 'regression', 'tensor', 'tensor-algebra', 'tensor-decomposition', 'tensor-factorization', 'tensor-learning', 'tensor-methods', 'tensor-regression', 'tensorflow', 'tensorly'] | ['cupy', 'decomposition', 'jax', 'machine-learning', 'mxnet', 'numpy', 'pytorch', 'regression', 'tensor', 'tensor-algebra', 'tensor-decomposition', 'tensor-factorization', 'tensor-learning', 'tensor-methods', 'tensor-regression', 'tensorflow', 'tensorly'] | 2024-01-08 | [('arogozhnikov/einops', 0.7486700415611267, 'ml-dl', 6), ('ggerganov/ggml', 0.7053402066230774, 'ml', 2), ('google/tf-quant-finance', 0.636419951915741, 'finance', 1), ('pytorch/pytorch', 0.6296373605728149, 'ml-dl', 3), ('huggingface/transformers', 0.6177733540534973, 'nlp', 4), ('xl0/lovely-tensors', 0.61644446849823, 'ml-dl', 1), ('rafiqhasan/auto-tensorflow', 0.6096346974372864, 'ml-dl', 2), ('tensorflow/similarity', 0.6049955487251282, 'ml-dl', 2), ('ddbourgin/numpy-ml', 0.6033033728599548, 'ml', 1), ('horovod/horovod', 0.5948300361633301, 'ml-ops', 4), ('patrick-kidger/torchtyping', 0.5934515595436096, 'typing', 1), ('explosion/thinc', 0.5860464572906494, 'ml-dl', 5), ('keras-team/keras', 0.5832876563072205, 'ml-dl', 4), ('huggingface/exporters', 0.5597980618476868, 'ml', 3), ('tensorflow/addons', 0.5590072274208069, 'ml', 2), ('nvidia/tensorrt-llm', 0.5586928129196167, 'viz', 0), ('ageron/handson-ml2', 0.5573654770851135, 'ml', 0), ('dylanhogg/awesome-python', 0.5549004673957825, 'study', 1), ('online-ml/river', 0.5535548329353333, 'ml', 1), ('intel/intel-extension-for-pytorch', 0.5494438409805298, 'perf', 2), ('tensorflow/tensorflow', 0.5459080934524536, 'ml-dl', 2), ('huggingface/huggingface_hub', 0.5400019884109497, 'ml', 2), ('pytorch/ignite', 0.5390286445617676, 'ml-dl', 2), ('gradio-app/gradio', 0.5336702466011047, 'viz', 1), ('mrdbourke/tensorflow-deep-learning', 0.5285704731941223, 'study', 1), ('onnx/onnx', 0.5244054198265076, 'ml', 4), ('skorch-dev/skorch', 0.5220605134963989, 'ml-dl', 2), ('d2l-ai/d2l-en', 0.5216432213783264, 'study', 5), ('google/gin-config', 0.5206177830696106, 'util', 1), ('probml/pyprobml', 0.5191105604171753, 'ml', 4), ('explosion/spacy', 0.5184281468391418, 'nlp', 1), ('nyandwi/modernconvnets', 0.5165544748306274, 'ml-dl', 1), ('mosaicml/composer', 0.5158124566078186, 'ml-dl', 2), ('neuralmagic/sparseml', 0.5156332850456238, 'ml-dl', 2), ('adap/flower', 0.5153002142906189, 'ml-ops', 3), ('ta-lib/ta-lib-python', 0.5138649344444275, 'finance', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5126520395278931, 'study', 0), ('tensorflow/lucid', 0.5121048092842102, 'ml-interpretability', 2), ('nvidia/deeplearningexamples', 0.5106650590896606, 'ml-dl', 3), ('cupy/cupy', 0.5093604922294617, 'math', 3), ('rasbt/mlxtend', 0.5090686082839966, 'ml', 1), ('tensorlayer/tensorlayer', 0.508705198764801, 'ml-rl', 1), ('huggingface/datasets', 0.50432950258255, 'nlp', 4), ('danielegrattarola/spektral', 0.5032951831817627, 'ml-dl', 1), ('merantix-momentum/squirrel-core', 0.5030725002288818, 'ml', 4), ('lutzroeder/netron', 0.5027545094490051, 'ml', 4), ('activeloopai/deeplake', 0.5025835037231445, 'ml-ops', 3), ('keras-team/keras-nlp', 0.5025812387466431, 'nlp', 2), ('nccr-itmo/fedot', 0.5016763806343079, 'ml-ops', 1), ('ai4finance-foundation/finrl', 0.5015732645988464, 'finance', 0), ('goldmansachs/gs-quant', 0.5013471841812134, 'finance', 0), ('graykode/nlp-tutorial', 0.5011732578277588, 'study', 2)] | 66 | 6 | null | 1.58 | 18 | 11 | 88 | 0 | 1 | 3 | 1 | 18 | 48 | 90 | 2.7 | 43 |
920 | util | https://github.com/p0dalirius/coercer | [] | null | [] | [] | null | null | null | p0dalirius/coercer | Coercer | 1,465 | 169 | 21 | Python | https://podalirius.net/ | A python script to automatically coerce a Windows server to authenticate on an arbitrary machine through 12 methods. | p0dalirius | 2024-01-12 | 2022-06-30 | 82 | 17.711572 | null | A python script to automatically coerce a Windows server to authenticate on an arbitrary machine through 12 methods. | ['authentication', 'automatic', 'call', 'coerce', 'fuzzing', 'ntlm', 'privilege-escalation', 'rpc'] | ['authentication', 'automatic', 'call', 'coerce', 'fuzzing', 'ntlm', 'privilege-escalation', 'rpc'] | 2023-12-24 | [] | 7 | 3 | null | 0.52 | 9 | 6 | 19 | 1 | 2 | 7 | 2 | 9 | 9 | 90 | 1 | 43 |
1,904 | math | https://github.com/google-deepmind/alphageometry | ['geometry', 'theorem-prover'] | Solving Olympiad Geometry without Human Demonstrations | [] | [] | null | null | null | google-deepmind/alphageometry | alphageometry | 1,134 | 96 | 16 | Python | null | null | google-deepmind | 2024-01-18 | 2023-10-09 | 16 | 70.247788 | https://avatars.githubusercontent.com/u/8596759?v=4 | Solving Olympiad Geometry without Human Demonstrations | [] | ['geometry', 'theorem-prover'] | 2024-01-12 | [('shapely/shapely', 0.5421801805496216, 'gis', 1)] | 2 | 0 | null | 0.08 | 11 | 3 | 3 | 0 | 0 | 0 | 0 | 11 | 5 | 90 | 0.5 | 43 |