dylanhogg/awesome-python · Datasets at Hugging Face

323

security

https://github.com/pyupio/safety

[]

null

[]

null

pyupio/safety

safety

1,571

138

32

Python

https://pyup.io/safety/

Safety checks Python dependencies for known security vulnerabilities and suggests the proper remediations for vulnerabilities detected.

pyupio

2024-01-12

2016-10-19

379

4.135765

https://avatars.githubusercontent.com/u/16113910?v=4

Safety checks Python dependencies for known security vulnerabilities and suggests the proper remediations for vulnerabilities detected.

['security', 'security-vulnerability', 'travis', 'vulnerability-detection', 'vulnerability-scanners']

2023-11-15

[('trailofbits/pip-audit', 0.7114713788032532, 'security', 1), ('aswinnnn/pyscan', 0.6276425123214722, 'security', 2), ('sonatype-nexus-community/jake', 0.607435405254364, 'security', 1), ('jazzband/pip-tools', 0.5792787671089172, 'util', 0), ('facebookincubator/bowler', 0.5631865859031677, 'util', 0), ('facebook/pyre-check', 0.5607929229736328, 'typing', 1), ('legrandin/pycryptodome', 0.5586642622947693, 'util', 1), ('pdm-project/pdm', 0.5419641733169556, 'util', 0), ('pyca/cryptography', 0.5316013097763062, 'util', 0), ('fsspec/filesystem_spec', 0.5129398107528687, 'util', 0)]

41

4

null

0.44

12

1

88

2

0

8

12

11

90

0.9

38

1,261

llm

https://github.com/ist-daslab/gptq

[]

null

[]

null

ist-daslab/gptq

gptq

1,533

118

28

Python

https://arxiv.org/abs/2210.17323

Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".

ist-daslab

2024-01-13

2022-10-19

66

22.929487

https://avatars.githubusercontent.com/u/35098403?v=4

Code for the ICLR 2023 paper "GPTQ: Accurate Post-training Quantization of Generative Pretrained Transformers".

[]

2023-07-11

[('karpathy/mingpt', 0.7072771787643433, 'llm', 0), ('huggingface/optimum', 0.6178866624832153, 'ml', 0), ('openai/image-gpt', 0.6169224381446838, 'llm', 0), ('alignmentresearch/tuned-lens', 0.5439256429672241, 'ml-interpretability', 0), ('eleutherai/knowledge-neurons', 0.53592449426651, 'ml-interpretability', 0), ('nielsrogge/transformers-tutorials', 0.5349066257476807, 'study', 0), ('huggingface/transformers', 0.5263904929161072, 'nlp', 0), ('bigscience-workshop/megatron-deepspeed', 0.5179560780525208, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5179560780525208, 'llm', 0), ('promptslab/awesome-prompt-engineering', 0.5007389187812805, 'study', 0)]

5

3

null

0.29

8

2

15

6

0

8

5

90

0.6

38

1,330

llm

https://github.com/jina-ai/thinkgpt

['chain-of-thought', 'language-model']

null

[]

null

jina-ai/thinkgpt

thinkgpt

1,420

119

25

Python

null

Agent techniques to augment your LLM and push it beyong its limits

jina-ai

2024-01-13

2023-04-14

41

34.158076

https://avatars.githubusercontent.com/u/60539444?v=4

Agent techniques to augment your LLM and push it beyong its limits

[]

['chain-of-thought', 'language-model']

2023-05-16

[('aiwaves-cn/agents', 0.6464569568634033, 'nlp', 1), ('ibm/dromedary', 0.6295039057731628, 'llm', 1), ('microsoft/autogen', 0.5731350779533386, 'llm', 0), ('minedojo/voyager', 0.5710037350654602, 'llm', 0), ('hwchase17/langchain', 0.5536667704582214, 'llm', 1), ('nomic-ai/gpt4all', 0.551749587059021, 'llm', 1), ('young-geng/easylm', 0.5500134825706482, 'llm', 1), ('langchain-ai/langgraph', 0.5343421697616577, 'llm', 0), ('mooler0410/llmspracticalguide', 0.5296755433082581, 'study', 0), ('operand/agency', 0.5273327827453613, 'llm', 0), ('deepset-ai/haystack', 0.527265191078186, 'llm', 1), ('nebuly-ai/nebullvm', 0.5268137454986572, 'perf', 0), ('explosion/spacy-llm', 0.5256912708282471, 'llm', 0), ('noahshinn/reflexion', 0.5254539847373962, 'llm', 0), ('keirp/automatic_prompt_engineer', 0.5156129002571106, 'llm', 1), ('mlc-ai/mlc-llm', 0.5101083517074585, 'llm', 1), ('microsoft/lmops', 0.5094317197799683, 'llm', 1), ('ray-project/ray-llm', 0.5078703165054321, 'llm', 0), ('kyegomez/tree-of-thoughts', 0.5059940814971924, 'llm', 0), ('geekan/metagpt', 0.5057692527770996, 'llm', 0), ('oliveirabruno01/babyagi-asi', 0.5025618076324463, 'llm', 1), ('deep-diver/pingpong', 0.5024981498718262, 'llm', 0)]

3

2

null

1.19

2

0

9

8

0

2

1

90

0.5

38

1,678

util

https://github.com/pycqa/pyflakes

[]

null

[]

null

pycqa/pyflakes

pyflakes

1,317

182

29

Python

https://pypi.org/project/pyflakes

A simple program which checks Python source files for errors

pycqa

2024-01-12

2014-04-07

512

2.571548

https://avatars.githubusercontent.com/u/8749848?v=4

A simple program which checks Python source files for errors

['linter']

2024-01-05

[('klen/pylama', 0.6928360462188721, 'util', 1), ('nedbat/coveragepy', 0.5710163116455078, 'testing', 0), ('instagram/fixit', 0.5664411783218384, 'util', 1), ('landscapeio/prospector', 0.5659628510475159, 'util', 0), ('pycqa/pycodestyle', 0.5580477118492126, 'util', 0), ('google/yapf', 0.5379751920700073, 'util', 0), ('microsoft/pyright', 0.511178195476532, 'typing', 0), ('google/pytype', 0.5093093514442444, 'typing', 1), ('python/mypy', 0.5037577748298645, 'typing', 1)]

84

4

null

0.19

11

10

119

0

3

11

14

90

1.3

38

445

ml

https://github.com/csinva/imodels

[]

null

[]

null

csinva/imodels

imodels

1,237

110

26

Jupyter Notebook

https://csinva.io/imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

csinva

2024-01-11

2019-07-04

238

5.181927

null

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

['ai', 'artificial-intelligence', 'bayesian-rule-list', 'data-science', 'explainable-ai', 'explainable-ml', 'imodels', 'interpretability', 'machine-learning', 'ml', 'optimal-classification-tree', 'rule-learning', 'rulefit', 'rules', 'scikit-learn', 'statistics', 'supervised-learning']

2023-12-30

[('interpretml/interpret', 0.7508851289749146, 'ml-interpretability', 7), ('pair-code/lit', 0.6702791452407837, 'ml-interpretability', 1), ('tensorflow/lucid', 0.6663603782653809, 'ml-interpretability', 2), ('maif/shapash', 0.6528401374816895, 'ml', 3), ('selfexplainml/piml-toolbox', 0.6522828936576843, 'ml-interpretability', 0), ('marcotcr/lime', 0.6466513276100159, 'ml-interpretability', 0), ('pytorch/captum', 0.6309248208999634, 'ml-interpretability', 1), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.6214880347251892, 'study', 2), ('xplainable/xplainable', 0.6195234656333923, 'ml-interpretability', 5), ('seldonio/alibi', 0.6186242699623108, 'ml-interpretability', 2), ('teamhg-memex/eli5', 0.6143868565559387, 'ml', 3), ('mlflow/mlflow', 0.5987911224365234, 'ml-ops', 3), ('huggingface/evaluate', 0.5934129357337952, 'ml', 1), ('eleutherai/pythia', 0.5875741243362427, 'ml-interpretability', 1), ('polyaxon/datatile', 0.5763207674026489, 'pandas', 3), ('huggingface/datasets', 0.5633199214935303, 'nlp', 1), ('tensorflow/tensorflow', 0.5597484707832336, 'ml-dl', 2), ('oegedijk/explainerdashboard', 0.5566130876541138, 'ml-interpretability', 0), ('cleanlab/cleanlab', 0.5562312602996826, 'ml', 1), ('tensorflow/data-validation', 0.5509118437767029, 'ml-ops', 0), ('skops-dev/skops', 0.5491555333137512, 'ml-ops', 2), ('ddbourgin/numpy-ml', 0.5491467118263245, 'ml', 1), ('giskard-ai/giskard', 0.5474556088447571, 'data', 3), ('firmai/industry-machine-learning', 0.5446041226387024, 'study', 2), ('slundberg/shap', 0.5444343090057373, 'ml-interpretability', 2), ('whylabs/whylogs', 0.5419551730155945, 'util', 2), ('linkedin/fasttreeshap', 0.5407923460006714, 'ml', 3), ('wandb/client', 0.5401941537857056, 'ml', 2), ('districtdatalabs/yellowbrick', 0.5383384227752686, 'ml', 2), ('automl/auto-sklearn', 0.5375404953956604, 'ml', 1), ('nccr-itmo/fedot', 0.5283494591712952, 'ml-ops', 1), ('mosaicml/composer', 0.5268099904060364, 'ml-dl', 1), ('scikit-learn/scikit-learn', 0.525899350643158, 'ml', 3), ('microsoft/nni', 0.524517297744751, 'ml', 2), ('explosion/thinc', 0.5241812467575073, 'ml-dl', 3), ('rasbt/machine-learning-book', 0.5234281420707703, 'study', 2), ('patchy631/machine-learning', 0.5233355760574341, 'ml', 0), ('koaning/scikit-lego', 0.5232925415039062, 'ml', 2), ('rafiqhasan/auto-tensorflow', 0.5232248902320862, 'ml-dl', 1), ('carla-recourse/carla', 0.5205970406532288, 'ml', 4), ('alirezadir/machine-learning-interview-enlightener', 0.5202349424362183, 'study', 2), ('onnx/onnx', 0.5179754495620728, 'ml', 3), ('bentoml/bentoml', 0.5169817209243774, 'ml-ops', 2), ('rasbt/mlxtend', 0.5165061354637146, 'ml', 3), ('determined-ai/determined', 0.5160141587257385, 'ml-ops', 2), ('aimhubio/aim', 0.5152265429496765, 'ml-ops', 4), ('polyaxon/polyaxon', 0.5118154883384705, 'ml-ops', 4), ('gradio-app/gradio', 0.5105863809585571, 'viz', 2), ('featurelabs/featuretools', 0.5102759599685669, 'ml', 3), ('kubeflow/fairing', 0.5098203420639038, 'ml-ops', 0), ('tensorflow/tensor2tensor', 0.5070091485977173, 'ml', 1), ('ml-tooling/opyrator', 0.5064631104469299, 'viz', 1), ('arize-ai/phoenix', 0.5046104192733765, 'ml-interpretability', 0), ('cdpierse/transformers-interpret', 0.500318169593811, 'ml-interpretability', 3), ('tensorlayer/tensorlayer', 0.5001160502433777, 'ml-rl', 1)]

22

5

null

2.12

8

4

55

0

5

8

5

8

1

90

0.1

38

1,010

time-series

https://github.com/bashtage/arch

[]

null

[]

null

bashtage/arch

arch

1,215

279

44

Python

null

ARCH models in Python

bashtage

2024-01-13

2014-08-29

491

2.471665

null

ARCH models in Python

['adf', 'arch', 'bootstrap', 'df-gls', 'dickey-fuller', 'finance', 'financial-econometrics', 'forecasting', 'model-confidence-set', 'multiple-comparison-procedures', 'phillips-perron', 'reality-check', 'risk', 'spa', 'time-series', 'unit-root', 'variance', 'volatility']

2024-01-05

[('firmai/atspy', 0.6273349523544312, 'time-series', 3), ('alkaline-ml/pmdarima', 0.6099317669868469, 'time-series', 2), ('statsmodels/statsmodels', 0.5926198363304138, 'ml', 1), ('goldmansachs/gs-quant', 0.5530153512954712, 'finance', 0), ('kernc/backtesting.py', 0.5312038064002991, 'finance', 1), ('awslabs/gluonts', 0.5267676115036011, 'time-series', 2), ('domokane/financepy', 0.5076860785484314, 'finance', 2), ('pmorissette/ffn', 0.5025431513786316, 'finance', 0), ('ranaroussi/quantstats', 0.5018336772918701, 'finance', 1), ('cuemacro/finmarketpy', 0.5008066892623901, 'finance', 0), ('crflynn/stochastic', 0.5002689957618713, 'sim', 0)]

35

3

null

1.29

25

24

114

0

8

5

8

25

90

1

38

1,043

data

https://github.com/ydataai/ydata-synthetic

[]

null

[]

null

ydataai/ydata-synthetic

ydata-synthetic

1,195

233

29

Jupyter Notebook

https://docs.synthetic.ydata.ai

Synthetic data generators for tabular and time-series data

ydataai

2024-01-13

2020-05-04

195

6.123719

https://avatars.githubusercontent.com/u/57689451?v=4

Synthetic data generators for tabular and time-series data

['datageneration', 'datagenerator', 'deep-learning', 'gan', 'gan-architectures', 'gans', 'generative-adversarial-network', 'machine-learning', 'pytorch', 'synthetic-data', 'tensorflow2', 'time-series', 'timeseries', 'training-data']

2024-01-02

[('sdv-dev/sdv', 0.9112098217010498, 'data', 7), ('awslabs/autogluon', 0.5872030258178711, 'ml', 4), ('borisbanushev/stockpredictionai', 0.5105303525924683, 'finance', 0), ('vaexio/vaex', 0.5099949836730957, 'perf', 1), ('winedarksea/autots', 0.5098974704742432, 'time-series', 3), ('nicolas-hbt/pygraft', 0.5071893334388733, 'ml', 2), ('mljar/mljar-supervised', 0.5016704797744751, 'ml', 1)]

22

1

null

1.23

34

17

45

0

9

34

16

90

0.5

38

966

gis

https://github.com/microsoft/globalmlbuildingfootprints

[]

null

[]

null

microsoft/globalmlbuildingfootprints

GlobalMLBuildingFootprints

1,186

175

60

Python

null

Worldwide building footprints derived from satellite imagery

microsoft

2024-01-12

2022-04-22

92

12.811728

https://avatars.githubusercontent.com/u/6154722?v=4

Worldwide building footprints derived from satellite imagery

[]

2024-01-03

[('zorzi-s/polyworldpretrainednetwork', 0.600134015083313, 'gis', 0), ('lydorn/polygonization-by-frame-field-learning', 0.5449085831642151, 'gis', 0)]

7

2

null

0.35

17

8

21

0

17

11

90

0.6

38

625

util

https://github.com/pyca/bcrypt

[]

null

[]

null

pyca/bcrypt

bcrypt

1,083

195

28

Python

null

Modern(-ish) password hashing for your software and your servers

pyca

2024-01-13

2013-05-11

559

1.935904

https://avatars.githubusercontent.com/u/5615737?v=4

Modern(-ish) password hashing for your software and your servers

[]

2024-01-12

[]

32

5

null

3.48

86

81

130

0

2

86

90

1

38

811

ml

https://github.com/automl/tabpfn

[]

null

[]

null

automl/tabpfn

TabPFN

1,028

85

14

Python

http://priorlabs.ai

Official implementation of the TabPFN paper (https://arxiv.org/abs/2207.01848) and the tabpfn package.

automl

2024-01-13

2022-07-01

82

12.449827

https://avatars.githubusercontent.com/u/6469053?v=4

Official implementation of the TabPFN paper (https://arxiv.org/abs/2207.01848) and the tabpfn package.

[]

2023-10-22

[]

7

3

null

0.67

26

14

19

3

0

26

23

90

0.9

38

1,150

data

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

[]

null

[]

null

aio-libs/aiocache

aiocache

971

139

22

Python

http://aiocache.readthedocs.io

Asyncio cache manager for redis, memcached and memory

aio-libs

2024-01-11

2016-09-30

382

2.538088

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

Asyncio cache manager for redis, memcached and memory

['asyncio', 'cache', 'cachemanager', 'memcached', 'redis']

2024-01-10

[('long2ice/fastapi-cache', 0.6432105898857117, 'web', 3), ('grantjenks/python-diskcache', 0.6346278786659241, 'util', 1), ('samuelcolvin/arq', 0.554317057132721, 'data', 2), ('dgilland/cacheout', 0.5477664470672607, 'perf', 0), ('python-cachier/cachier', 0.5451957583427429, 'perf', 2)]

43

5

null

2.15

36

33

89

0

3

36

28

90

0.8

38

89

testing

https://github.com/taverntesting/tavern

[]

null

[]

null

taverntesting/tavern

tavern

969

186

27

Python

https://taverntesting.github.io/

A command-line tool and Python library and Pytest plugin for automated testing of RESTful APIs, with a simple, concise and flexible YAML-based syntax

taverntesting

2024-01-12

2017-11-01

325

2.973696

https://avatars.githubusercontent.com/u/33286481?v=4

A command-line tool and Python library and Pytest plugin for automated testing of RESTful APIs, with a simple, concise and flexible YAML-based syntax

['http', 'mqtt', 'pytest', 'test-automation', 'testing']

2023-12-26

[('pytest-dev/pytest-xdist', 0.6020364165306091, 'testing', 1), ('simple-salesforce/simple-salesforce', 0.6006324291229248, 'data', 0), ('ionelmc/pytest-benchmark', 0.5957930684089661, 'testing', 1), ('getsentry/responses', 0.5727768540382385, 'testing', 0), ('wolever/parameterized', 0.5629963874816895, 'testing', 0), ('lundberg/respx', 0.5600868463516235, 'testing', 2), ('seleniumbase/seleniumbase', 0.5573855042457581, 'testing', 1), ('hugapi/hug', 0.5526415705680847, 'util', 1), ('falconry/falcon', 0.5523936152458191, 'web', 1), ('flipkart-incubator/astra', 0.552314817905426, 'web', 0), ('requests/toolbelt', 0.545853853225708, 'util', 1), ('python-restx/flask-restx', 0.5409488081932068, 'web', 0), ('nedbat/coveragepy', 0.5402073264122009, 'testing', 0), ('pytest-dev/pytest', 0.5295860767364502, 'testing', 1), ('buildbot/buildbot', 0.5253430604934692, 'util', 0), ('computationalmodelling/nbval', 0.5216328501701355, 'jupyter', 2), ('pmorissette/bt', 0.5144594311714172, 'finance', 0), ('pytest-dev/pytest-cov', 0.511971116065979, 'testing', 1), ('samuelcolvin/pytest-pretty', 0.5094279050827026, 'testing', 1), ('pytest-dev/pytest-testinfra', 0.5087285041809082, 'testing', 1), ('pytest-dev/pytest-mock', 0.5072631239891052, 'testing', 1), ('teemu/pytest-sugar', 0.5043500661849976, 'testing', 2), ('nasdaq/data-link-python', 0.5025106072425842, 'finance', 0)]

61

4

null

1.06

27

19

76

1

0

33

27

16

90

0.6

38

147

util

https://github.com/zenodo/zenodo

[]

null

[]

null

zenodo/zenodo

zenodo

862

252

45

Python

https://zenodo.org

Research. Shared.

zenodo

2024-01-06

2013-02-11

572

1.506617

https://avatars.githubusercontent.com/u/2675345?v=4

Research. Shared.

['digital-library', 'elasticsearch', 'flask', 'invenio', 'inveniosoftware', 'library-management', 'open-access', 'open-science', 'postgresql', 'research-data-management', 'research-data-repository', 'scientific-publications', 'zenodo']

2023-12-11

[('simonw/datasette', 0.6021542549133301, 'data', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5640177726745605, 'template', 1), ('piccolo-orm/piccolo_admin', 0.5565163493156433, 'data', 1), ('airbytehq/airbyte', 0.5533841252326965, 'data', 1), ('airbnb/knowledge-repo', 0.5470719933509827, 'data', 0), ('cerlymarco/medium_notebook', 0.5398790240287781, 'study', 0), ('firmai/industry-machine-learning', 0.5377620458602905, 'study', 0), ('plotly/dash', 0.5337997078895569, 'viz', 1), ('krzjoa/awesome-python-data-science', 0.5312089323997498, 'study', 0), ('aws/aws-sdk-pandas', 0.5311623811721802, 'pandas', 0), ('saulpw/visidata', 0.5197573900222778, 'term', 0), ('netflix/metaflow', 0.513927161693573, 'ml-ops', 0), ('eleutherai/pyfra', 0.5133705139160156, 'ml', 0), ('brettkromkamp/contextualise', 0.5124539136886597, 'data', 0), ('alphasecio/langchain-examples', 0.511971652507782, 'llm', 0), ('coleifer/peewee', 0.5084249377250671, 'data', 0), ('github/innovationgraph', 0.5064103007316589, 'data', 0), ('polyaxon/datatile', 0.5025171041488647, 'pandas', 0)]

67

5

null

0.48

65

12

133

1

0

39

64

111

90

1.7

38

803

data

https://github.com/neo4j/neo4j-python-driver

[]

null

[]

null

neo4j/neo4j-python-driver

neo4j-python-driver

850

213

98

Python

https://neo4j.com/docs/api/python-driver/current/

Neo4j Bolt driver for Python

neo4j

2024-01-08

2015-05-05

456

1.864035

https://avatars.githubusercontent.com/u/201120?v=4

Neo4j Bolt driver for Python

['binary-protocol', 'cypher', 'database-driver', 'driver', 'graph-database', 'neo4j', 'protocol', 'query-language']

2024-01-09

[('accenture/cymple', 0.6172598600387573, 'data', 2), ('datastax/python-driver', 0.5756858587265015, 'data', 0), ('scylladb/python-driver', 0.5569538474082947, 'data', 0), ('pydot/pydot', 0.5061096549034119, 'viz', 0)]

43

4

null

1.9

36

106

0

15

14

15

36

25

90

0.7

38

790

ml-interpretability

https://github.com/selfexplainml/piml-toolbox

[]

null

[]

null

selfexplainml/piml-toolbox

PiML-Toolbox

791

96

21

Jupyter Notebook

https://selfexplainml.github.io/PiML-Toolbox

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics

selfexplainml

2024-01-13

2022-04-29

91

8.638066

https://avatars.githubusercontent.com/u/74489521?v=4

PiML (Python Interpretable Machine Learning) toolbox for model development & diagnostics

['interpretable-machine-learning', 'low-code', 'ml-workflow', 'model-diagnostics']

2024-01-08

[('csinva/imodels', 0.6522828936576843, 'ml', 0), ('kubeflow/fairing', 0.6489830613136292, 'ml-ops', 0), ('pair-code/lit', 0.6214944124221802, 'ml-interpretability', 0), ('districtdatalabs/yellowbrick', 0.6020028591156006, 'ml', 0), ('huggingface/evaluate', 0.5961371660232544, 'ml', 0), ('wandb/client', 0.5873650908470154, 'ml', 0), ('teamhg-memex/eli5', 0.5864848494529724, 'ml', 0), ('pan-ml/panml', 0.5762995481491089, 'llm', 0), ('featurelabs/featuretools', 0.5691878795623779, 'ml', 0), ('ml-tooling/opyrator', 0.5633277297019958, 'viz', 0), ('stan-dev/pystan', 0.5616912245750427, 'ml', 0), ('microsoft/nni', 0.5612987279891968, 'ml', 0), ('apple/coremltools', 0.558883786201477, 'ml', 0), ('gradio-app/gradio', 0.5576595664024353, 'viz', 0), ('evidentlyai/evidently', 0.5544941425323486, 'ml-ops', 0), ('linkedin/fasttreeshap', 0.5518995523452759, 'ml', 0), ('tensorflow/lucid', 0.5517100095748901, 'ml-interpretability', 0), ('huggingface/datasets', 0.5501903891563416, 'nlp', 0), ('mlflow/mlflow', 0.5481675863265991, 'ml-ops', 0), ('scikit-learn/scikit-learn', 0.5468170642852783, 'ml', 0), ('rafiqhasan/auto-tensorflow', 0.5389483571052551, 'ml-dl', 0), ('polyaxon/datatile', 0.5384085178375244, 'pandas', 0), ('rasbt/mlxtend', 0.5372369885444641, 'ml', 0), ('epistasislab/tpot', 0.5343623161315918, 'ml', 0), ('tensorflow/data-validation', 0.5335401892662048, 'ml-ops', 0), ('nccr-itmo/fedot', 0.53252112865448, 'ml-ops', 0), ('pytorch/captum', 0.5324576497077942, 'ml-interpretability', 0), ('goldmansachs/gs-quant', 0.5287847518920898, 'finance', 0), ('pycaret/pycaret', 0.5286346077919006, 'ml', 0), ('maif/shapash', 0.527449905872345, 'ml', 0), ('zenml-io/zenml', 0.5244457125663757, 'ml-ops', 0), ('dagworks-inc/hamilton', 0.5237611532211304, 'ml-ops', 0), ('interpretml/interpret', 0.5234452486038208, 'ml-interpretability', 1), ('eleutherai/pyfra', 0.5199788808822632, 'ml', 0), ('huggingface/huggingface_hub', 0.5193759202957153, 'ml', 0), ('brokenloop/jsontopydantic', 0.515333354473114, 'util', 0), ('skops-dev/skops', 0.5126495957374573, 'ml-ops', 0), ('probml/pyprobml', 0.512611985206604, 'ml', 0), ('pytoolz/toolz', 0.5094278454780579, 'util', 0), ('polyaxon/polyaxon', 0.5091049075126648, 'ml-ops', 0), ('whylabs/whylogs', 0.5081930756568909, 'util', 0), ('huggingface/transformers', 0.5078108310699463, 'nlp', 0), ('titanml/takeoff', 0.5073431134223938, 'llm', 0), ('seldonio/alibi', 0.5072975158691406, 'ml-interpretability', 0), ('mljar/mljar-supervised', 0.5052536129951477, 'ml', 0), ('microsoft/flaml', 0.5052233338356018, 'ml', 0), ('lucidrains/toolformer-pytorch', 0.5051028728485107, 'llm', 0), ('pymc-devs/pymc3', 0.5050045847892761, 'ml', 0), ('amaargiru/pyroad', 0.5047166347503662, 'study', 0), ('firmai/atspy', 0.5030118823051453, 'time-series', 0), ('conceptofmind/toolformer', 0.5030021071434021, 'llm', 0), ('fmind/mlops-python-package', 0.5029227137565613, 'template', 0), ('anthropics/evals', 0.5009229183197021, 'llm', 0), ('shankarpandala/lazypredict', 0.500099241733551, 'ml', 0)]

6

2

null

2.46

4

1

21

0

3

2

3

4

3

90

0.8

38

824

typing

https://github.com/python-attrs/cattrs

[]

null

[]

null

python-attrs/cattrs

cattrs

725

101

20

Python

https://catt.rs

Composable custom class converters for attrs.

python-attrs

2024-01-13

2016-08-28

387

1.872003

https://avatars.githubusercontent.com/u/25880274?v=4

Composable custom class converters for attrs.

['attrs', 'deserialization', 'serialization']

2024-01-13

[('lidatong/dataclasses-json', 0.5296611189842224, 'util', 0)]

62

3

null

2.48

78

63

90

0

4

78

121

90

1.6

38

1,754

ml

https://github.com/criteo/autofaiss

['knn', 'similarity', 'embeddings', 'vector-search']

null

[]

1

null

criteo/autofaiss

autofaiss

684

65

18

Python

https://criteo.github.io/autofaiss/

Automatically create Faiss knn indices with the most optimal similarity search parameters.

criteo

2024-01-13

2021-04-28

143

4.754717

https://avatars.githubusercontent.com/u/1713646?v=4

Automatically create Faiss knn indices with the most optimal similarity search parameters.

[]

['embeddings', 'knn', 'similarity', 'vector-search']

2024-01-13

[('facebookresearch/faiss', 0.629601776599884, 'ml', 3), ('qdrant/quaterion', 0.6242879629135132, 'ml', 1), ('lmcinnes/pynndescent', 0.5459467172622681, 'ml', 0), ('qdrant/qdrant', 0.5368368625640869, 'data', 1)]

15

4

null

0.25

14

7

33

0

4

25

4

14

15

90

1.1

38

1,752

jupyter

https://github.com/aws/graph-notebook

[]

null

[]

null

aws/graph-notebook

graph-notebook

652

157

35

Jupyter Notebook

https://github.com/aws/graph-notebook

Library extending Jupyter notebooks to integrate with Apache TinkerPop, openCypher, and RDF SPARQL.

aws

2024-01-13

2020-10-01

173

3.753289

https://avatars.githubusercontent.com/u/2232217?v=4

Library extending Jupyter notebooks to integrate with Apache TinkerPop, openCypher, and RDF SPARQL.

['apache', 'cypher', 'graph', 'gremlin', 'jupyter', 'jupyter-notebook', 'jupyter-widgets', 'neptune', 'opencypher', 'rdf', 'sparql', 'tinkerpop']

2023-12-21

[('jupyter-widgets/ipywidgets', 0.687077522277832, 'jupyter', 0), ('voila-dashboards/voila', 0.6807038187980652, 'jupyter', 2), ('cohere-ai/notebooks', 0.6492716073989868, 'llm', 0), ('mwouts/jupytext', 0.6454940438270569, 'jupyter', 1), ('jupyterlab/jupyterlab-desktop', 0.6357448697090149, 'jupyter', 2), ('jupyter/nbformat', 0.6213883757591248, 'jupyter', 0), ('vizzuhq/ipyvizzu', 0.5957169532775879, 'jupyter', 2), ('jupyter/notebook', 0.5949639081954956, 'jupyter', 2), ('bloomberg/ipydatagrid', 0.5870513916015625, 'jupyter', 0), ('quantopian/qgrid', 0.571941614151001, 'jupyter', 0), ('ipython/ipykernel', 0.568101167678833, 'util', 2), ('jupyter-lsp/jupyterlab-lsp', 0.5679754018783569, 'jupyter', 2), ('jakevdp/pythondatasciencehandbook', 0.559874951839447, 'study', 1), ('jupyter/nbdime', 0.5575152039527893, 'jupyter', 2), ('holoviz/panel', 0.5436458587646484, 'viz', 1), ('nteract/papermill', 0.5402319431304932, 'jupyter', 1), ('maartenbreddels/ipyvolume', 0.539257287979126, 'jupyter', 2), ('jupyter-widgets/ipyleaflet', 0.5392546653747559, 'gis', 1), ('opengeos/leafmap', 0.5389112830162048, 'gis', 2), ('mamba-org/gator', 0.5385718941688538, 'jupyter', 1), ('tkrabel/bamboolib', 0.5372664928436279, 'pandas', 1), ('alphasecio/langchain-examples', 0.5361274480819702, 'llm', 1), ('ipython/ipyparallel', 0.5359687805175781, 'perf', 1), ('plotly/plotly.py', 0.5306247472763062, 'viz', 1), ('fchollet/deep-learning-with-python-notebooks', 0.525762140750885, 'study', 0), ('jupyterlab/jupyterlab', 0.5233699083328247, 'jupyter', 1), ('jupyter/nbconvert', 0.522909939289093, 'jupyter', 0), ('giswqs/mapwidget', 0.5196599364280701, 'gis', 1), ('ageron/handson-ml2', 0.519343912601471, 'ml', 0), ('accenture/cymple', 0.5142837166786194, 'data', 1), ('strawberry-graphql/strawberry', 0.5056154131889343, 'web', 0), ('aws/aws-sdk-pandas', 0.5009594559669495, 'pandas', 0)]

30

4

null

1.63

20

13

40

1

10

13

10

20

18

90

0.9

38

619

gis

https://github.com/scitools/iris

[]

null

[]

null

scitools/iris

iris

587

279

45

Python

https://scitools-iris.readthedocs.io/en/stable/

A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data

scitools

2024-01-05

2012-08-06

599

0.979733

https://avatars.githubusercontent.com/u/1391487?v=4

A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data

['data-analysis', 'earth-science', 'grib', 'iris', 'meteorology', 'netcdf', 'oceanography', 'spaceweather', 'visualisation']

2024-01-12

[('enthought/mayavi', 0.7232843041419983, 'viz', 0), ('giswqs/geemap', 0.6783716082572937, 'gis', 0), ('residentmario/geoplot', 0.6692157983779907, 'gis', 0), ('holoviz/holoviz', 0.6550614833831787, 'viz', 0), ('mwaskom/seaborn', 0.6527572870254517, 'viz', 0), ('contextlab/hypertools', 0.6321009993553162, 'ml', 0), ('pyqtgraph/pyqtgraph', 0.6289077401161194, 'viz', 0), ('altair-viz/altair', 0.6287659406661987, 'viz', 0), ('sentinel-hub/eo-learn', 0.623789370059967, 'gis', 0), ('marcomusy/vedo', 0.6136019825935364, 'viz', 0), ('pytroll/satpy', 0.6135034561157227, 'gis', 0), ('cloudsen12/easystac', 0.6042935252189636, 'gis', 0), ('gregorhd/mapcompare', 0.6005646586418152, 'gis', 0), ('roban/cosmolopy', 0.5999904274940491, 'sim', 0), ('lux-org/lux', 0.5947362184524536, 'viz', 0), ('holoviz/hvplot', 0.5860223770141602, 'pandas', 0), ('man-group/dtale', 0.5857634544372559, 'viz', 1), ('holoviz/panel', 0.5823258757591248, 'viz', 0), ('opengeos/leafmap', 0.5820508003234863, 'gis', 0), ('earthlab/earthpy', 0.5802125930786133, 'gis', 0), ('has2k1/plotnine', 0.5705260634422302, 'viz', 1), ('holoviz/geoviews', 0.5698901414871216, 'gis', 0), ('matplotlib/matplotlib', 0.5653036236763, 'viz', 0), ('krzjoa/awesome-python-data-science', 0.5579238533973694, 'study', 1), ('numpy/numpy', 0.5556809306144714, 'math', 0), ('artelys/geonetworkx', 0.5512532591819763, 'gis', 0), ('raphaelquast/eomaps', 0.5512466430664062, 'gis', 0), ('kanaries/pygwalker', 0.5480643510818481, 'pandas', 1), ('geopandas/geopandas', 0.5416747331619263, 'gis', 0), ('pandas-dev/pandas', 0.5412265062332153, 'pandas', 1), ('graphistry/pygraphistry', 0.5314244627952576, 'data', 0), ('pysal/pysal', 0.5261117815971375, 'gis', 0), ('makepath/xarray-spatial', 0.523902952671051, 'gis', 0), ('plotly/plotly.py', 0.5217393040657043, 'viz', 0), ('fatiando/verde', 0.5199081301689148, 'gis', 1), ('imageio/imageio', 0.5107640027999878, 'util', 0), ('albahnsen/pycircular', 0.5095266103744507, 'math', 0), ('bokeh/bokeh', 0.5092189908027649, 'viz', 1), ('bmabey/pyldavis', 0.5086809992790222, 'ml', 0), ('plotly/dash', 0.5075518488883972, 'viz', 0), ('mito-ds/monorepo', 0.5061976909637451, 'jupyter', 1), ('jakevdp/pythondatasciencehandbook', 0.5051771402359009, 'study', 0), ('westhealth/pyvis', 0.503166139125824, 'graph', 0), ('rasbt/mlxtend', 0.5022916793823242, 'ml', 0)]

107

2

null

5.21

276

209

139

0

8

7

8

276

410

90

1.5

38

216

ml-ops

https://github.com/nccr-itmo/fedot

[]

null

[]

null

nccr-itmo/fedot

FEDOT

579

80

9

Python

https://fedot.readthedocs.io

Automated modeling and machine learning framework FEDOT

nccr-itmo

2024-01-13

2020-01-13

211

2.742219

https://avatars.githubusercontent.com/u/65946329?v=4

Automated modeling and machine learning framework FEDOT

['automated-machine-learning', 'automation', 'automl', 'evolutionary-algorithms', 'fedot', 'genetic-programming', 'hyperparameter-optimization', 'machine-learning', 'multimodality', 'parameter-tuning', 'structural-learning']

2024-01-10

[('automl/auto-sklearn', 0.7373944520950317, 'ml', 3), ('microsoft/nni', 0.6999444365501404, 'ml', 4), ('winedarksea/autots', 0.6496773958206177, 'time-series', 2), ('microsoft/flaml', 0.6372272372245789, 'ml', 4), ('keras-team/autokeras', 0.6287457346916199, 'ml-dl', 3), ('awslabs/autogluon', 0.6268003582954407, 'ml', 4), ('adap/flower', 0.618629515171051, 'ml-ops', 1), ('districtdatalabs/yellowbrick', 0.6075289249420166, 'ml', 1), ('epistasislab/tpot', 0.6070546507835388, 'ml', 6), ('huggingface/autotrain-advanced', 0.5916618704795837, 'ml', 1), ('xplainable/xplainable', 0.5892693996429443, 'ml-interpretability', 1), ('nevronai/metisfl', 0.5833522081375122, 'ml', 1), ('mlflow/mlflow', 0.5817329287528992, 'ml-ops', 1), ('featurelabs/featuretools', 0.5784884095191956, 'ml', 3), ('mosaicml/composer', 0.5770966410636902, 'ml-dl', 1), ('ml-tooling/opyrator', 0.5759302377700806, 'viz', 1), ('mljar/mljar-supervised', 0.5752649307250977, 'ml', 4), ('alpa-projects/alpa', 0.5670198202133179, 'ml-dl', 1), ('operand/agency', 0.5655133128166199, 'llm', 1), ('tensorflow/tensorflow', 0.5654616355895996, 'ml-dl', 1), ('bentoml/bentoml', 0.5645349621772766, 'ml-ops', 1), ('polyaxon/polyaxon', 0.5636411905288696, 'ml-ops', 2), ('huggingface/datasets', 0.5636368989944458, 'nlp', 1), ('google/pyglove', 0.5598992109298706, 'util', 2), ('determined-ai/determined', 0.5581679940223694, 'ml-ops', 2), ('shankarpandala/lazypredict', 0.5503329038619995, 'ml', 2), ('ludwig-ai/ludwig', 0.5483391284942627, 'ml-ops', 1), ('rafiqhasan/auto-tensorflow', 0.5481418371200562, 'ml-dl', 2), ('giskard-ai/giskard', 0.5448036789894104, 'data', 1), ('onnx/onnx', 0.5438551306724548, 'ml', 1), ('ai4finance-foundation/finrl', 0.5424655675888062, 'finance', 0), ('ray-project/ray', 0.541328489780426, 'ml-ops', 3), ('explosion/thinc', 0.5396167635917664, 'ml-dl', 1), ('ddbourgin/numpy-ml', 0.5393419861793518, 'ml', 1), ('microsoft/lmops', 0.5380227565765381, 'llm', 0), ('ourownstory/neural_prophet', 0.5363118648529053, 'ml', 1), ('firmai/industry-machine-learning', 0.5340647101402283, 'study', 1), ('apple/coremltools', 0.5334883332252502, 'ml', 1), ('firmai/atspy', 0.5334661602973938, 'time-series', 0), ('selfexplainml/piml-toolbox', 0.53252112865448, 'ml-interpretability', 0), ('lucidrains/toolformer-pytorch', 0.5307614803314209, 'llm', 0), ('csinva/imodels', 0.5283494591712952, 'ml', 1), ('scikit-learn/scikit-learn', 0.5258017778396606, 'ml', 1), ('gradio-app/gradio', 0.5231483578681946, 'viz', 1), ('polyaxon/datatile', 0.521264910697937, 'pandas', 0), ('sktime/sktime', 0.520081639289856, 'time-series', 1), ('mlc-ai/mlc-llm', 0.5192214250564575, 'llm', 0), ('patchy631/machine-learning', 0.517076313495636, 'ml', 0), ('online-ml/river', 0.5161853432655334, 'ml', 1), ('eugeneyan/testing-ml', 0.5155410766601562, 'testing', 1), ('horovod/horovod', 0.5143430829048157, 'ml-ops', 1), ('ggerganov/ggml', 0.5140013098716736, 'ml', 1), ('hpcaitech/colossalai', 0.5125412344932556, 'llm', 0), ('interpretml/interpret', 0.5118159651756287, 'ml-interpretability', 1), ('huggingface/transformers', 0.5109488368034363, 'nlp', 1), ('neuralmagic/sparseml', 0.508357048034668, 'ml-dl', 1), ('alirezadir/machine-learning-interview-enlightener', 0.5080487728118896, 'study', 1), ('kubeflow/pipelines', 0.5040023922920227, 'ml-ops', 1), ('tensorly/tensorly', 0.5016763806343079, 'ml-dl', 1), ('feast-dev/feast', 0.5015140175819397, 'ml-ops', 1)]

32

3

null

2.06

102

58

49

0

4

3

4

102

146

90

1.4

38

905

util

https://github.com/methexis-inc/terminal-copilot

[]

null

[]

null

methexis-inc/terminal-copilot

terminal-copilot

539

41

7

Python

null

A smart terminal assistant that helps you find the right command.

methexis-inc

2024-01-10

2022-12-11

59

9.091566

https://avatars.githubusercontent.com/u/110575158?v=4

A smart terminal assistant that helps you find the right command.

[]

2023-12-09

[('tiangolo/typer', 0.5327745079994202, 'term', 0), ('tconbeer/harlequin', 0.5151594877243042, 'term', 0)]

10

3

null

0.35

4

13

1

3

5

3

4

6

90

1.5

38

1,533

data

https://github.com/dbt-labs/dbt-spark

['spark', 'dbt']

null

[]

null

dbt-labs/dbt-spark

dbt-spark

339

199

18

Python

https://getdbt.com

dbt-spark contains all of the code enabling dbt to work with Apache Spark and Databricks

dbt-labs

2024-01-06

2019-03-21

253

1.336149

https://avatars.githubusercontent.com/u/18339788?v=4

dbt-spark contains all of the code enabling dbt to work with Apache Spark and Databricks

[]

['dbt', 'spark']

2024-01-11

[('databricks/dbt-databricks', 0.6950157284736633, 'data', 1)]

73

4

null

2.98

94

63

59

0

28

18

28

94

103

90

1.1

38

1,837

llm

https://github.com/bobazooba/xllm

[]

null

[]

null

bobazooba/xllm

xllm

308

17

3

Python

https://t.me/talequestbot

🦖 X—LLM: Cutting Edge & Easy LLM Finetuning

bobazooba

2024-01-14

2023-11-10

11

26.617284

null

🦖 X—LLM: Cutting Edge & Easy LLM Finetuning

['alpaca', 'bitsandbytes', 'cerebras', 'chatgpt', 'deep-learning', 'deep-neural-networks', 'gpt', 'gpt-4', 'gptq', 'large-language-models', 'llama', 'llama2', 'llm', 'mistral', 'openai', 'pytorch', 'torch', 'vicuna', 'zephyr']

2023-12-07

[('hiyouga/llama-efficient-tuning', 0.7037465572357178, 'llm', 5), ('hiyouga/llama-factory', 0.7037465572357178, 'llm', 5), ('lianjiatech/belle', 0.6800654530525208, 'llm', 1), ('bigscience-workshop/petals', 0.667163610458374, 'data', 6), ('intel/intel-extension-for-transformers', 0.6433131694793701, 'perf', 0), ('tigerlab-ai/tiger', 0.6268063187599182, 'llm', 2), ('hannibal046/awesome-llm', 0.6244999766349792, 'study', 1), ('artidoro/qlora', 0.6219983100891113, 'llm', 0), ('vllm-project/vllm', 0.6193138957023621, 'llm', 4), ('explosion/spacy-llm', 0.6183709502220154, 'llm', 5), ('microsoft/autogen', 0.6154872179031372, 'llm', 3), ('next-gpt/next-gpt', 0.61397784948349, 'llm', 4), ('lightning-ai/lit-llama', 0.6132877469062805, 'llm', 1), ('salesforce/xgen', 0.607836902141571, 'llm', 2), ('xtekky/gpt4free', 0.6042348742485046, 'llm', 4), ('paddlepaddle/paddlenlp', 0.6009507775306702, 'llm', 2), ('ray-project/ray-llm', 0.5996918082237244, 'llm', 2), ('young-geng/easylm', 0.5975850224494934, 'llm', 3), ('squeezeailab/squeezellm', 0.596723735332489, 'llm', 3), ('ludwig-ai/ludwig', 0.5947787761688232, 'ml-ops', 6), ('zilliztech/gptcache', 0.5947780013084412, 'llm', 5), ('opengvlab/omniquant', 0.5902096033096313, 'llm', 2), ('eth-sri/lmql', 0.5887289047241211, 'llm', 1), ('nvidia/tensorrt-llm', 0.5863513350486755, 'viz', 0), ('bentoml/openllm', 0.5858603119850159, 'ml-ops', 5), ('dylanhogg/llmgraph', 0.5852743983268738, 'ml', 3), ('microsoft/lora', 0.5789094567298889, 'llm', 2), ('li-plus/chatglm.cpp', 0.5759797692298889, 'llm', 1), ('juncongmoo/pyllama', 0.5698232054710388, 'llm', 0), ('thudm/chatglm2-6b', 0.5669134855270386, 'llm', 2), ('cg123/mergekit', 0.5655726194381714, 'llm', 2), ('iryna-kondr/scikit-llm', 0.5620294213294983, 'llm', 3), ('h2oai/h2o-llmstudio', 0.5602803230285645, 'llm', 5), ('jerryjliu/llama_index', 0.5593804121017456, 'llm', 2), ('microsoft/jarvis', 0.5591229200363159, 'llm', 2), ('sjtu-ipads/powerinfer', 0.5589494705200195, 'llm', 3), ('infinitylogesh/mutate', 0.5542972087860107, 'nlp', 0), ('mooler0410/llmspracticalguide', 0.5522361397743225, 'study', 1), ('titanml/takeoff', 0.551180899143219, 'llm', 2), ('microsoft/torchscale', 0.5502038598060608, 'llm', 0), ('huggingface/text-generation-inference', 0.5498690605163574, 'llm', 3), ('argilla-io/argilla', 0.5486025214195251, 'nlp', 2), ('lupantech/chameleon-llm', 0.5471572875976562, 'llm', 4), ('eleutherai/the-pile', 0.5469703674316406, 'data', 1), ('huggingface/transformers', 0.5439950227737427, 'nlp', 2), ('guardrails-ai/guardrails', 0.5430307984352112, 'llm', 2), ('salesforce/codet5', 0.5426592826843262, 'nlp', 1), ('alphasecio/langchain-examples', 0.5409016609191895, 'llm', 2), ('mlc-ai/web-llm', 0.5402325987815857, 'llm', 3), ('predibase/lorax', 0.5401611924171448, 'llm', 4), ('nomic-ai/gpt4all', 0.5367876887321472, 'llm', 0), ('run-llama/rags', 0.5356626510620117, 'llm', 3), ('nebuly-ai/nebullvm', 0.5337145328521729, 'perf', 2), ('eugeneyan/open-llms', 0.5326270461082458, 'study', 2), ('epfllm/meditron', 0.5308298468589783, 'llm', 0), ('jzhang38/tinyllama', 0.5300989151000977, 'llm', 1), ('explosion/spacy-transformers', 0.529644787311554, 'llm', 2), ('shishirpatil/gorilla', 0.5277217626571655, 'llm', 2), ('optimalscale/lmflow', 0.5273640751838684, 'llm', 3), ('openlm-research/open_llama', 0.5272755026817322, 'llm', 1), ('huawei-noah/pretrained-language-model', 0.5261392593383789, 'nlp', 0), ('microsoft/promptflow', 0.52497398853302, 'llm', 3), ('baichuan-inc/baichuan-13b', 0.5246362090110779, 'llm', 3), ('night-chen/toolqa', 0.5220770835876465, 'llm', 1), ('pathwaycom/llm-app', 0.5216497778892517, 'llm', 1), ('tairov/llama2.mojo', 0.5215964913368225, 'llm', 2), ('haotian-liu/llava', 0.5188300609588623, 'llm', 4), ('lightning-ai/lit-gpt', 0.5175870656967163, 'llm', 0), ('confident-ai/deepeval', 0.5172545909881592, 'testing', 2), ('bigscience-workshop/megatron-deepspeed', 0.5139332413673401, 'llm', 0), ('microsoft/megatron-deepspeed', 0.5139332413673401, 'llm', 0), ('freedomintelligence/llmzoo', 0.5108060240745544, 'llm', 0), ('ashleve/lightning-hydra-template', 0.5093933939933777, 'util', 2), ('ai4finance-foundation/fingpt', 0.5081082582473755, 'finance', 4), ('pytorch/glow', 0.5073339343070984, 'ml', 0), ('bytedance/lightseq', 0.5065972208976746, 'nlp', 1), ('deepset-ai/haystack', 0.5065814852714539, 'llm', 3), ('databrickslabs/dolly', 0.5060972571372986, 'llm', 1), ('llmware-ai/llmware', 0.503739595413208, 'llm', 2), ('microsoft/semantic-kernel', 0.5029643774032593, 'llm', 2), ('hegelai/prompttools', 0.5022645592689514, 'llm', 2), ('lm-sys/fastchat', 0.5017418265342712, 'llm', 0), ('langchain-ai/langgraph', 0.5015073418617249, 'llm', 0), ('alpa-projects/alpa', 0.5013929605484009, 'ml-dl', 2), ('oobabooga/text-generation-webui', 0.501327633857727, 'llm', 0)]

1

0

null

1.15

16

11

2

1

5

85

5

16

9

90

0.6

38

1,575

data

https://github.com/scikit-hep/uproot5

['science']

null

[]

null

scikit-hep/uproot5

uproot5

208

63

19

Python

https://uproot.readthedocs.io

ROOT I/O in pure Python and NumPy.

scikit-hep

2024-01-09

2020-05-08

194

1.069016

https://avatars.githubusercontent.com/u/23454624?v=4

ROOT I/O in pure Python and NumPy.

['analysis', 'big-data', 'bigdata', 'file-format', 'hep', 'hep-ex', 'hep-py', 'numpy', 'root', 'root-cern', 'scikit-hep']

['analysis', 'big-data', 'bigdata', 'file-format', 'hep', 'hep-ex', 'hep-py', 'numpy', 'root', 'root-cern', 'science', 'scikit-hep']

2024-01-12

[('numpy/numpy', 0.5980868935585022, 'math', 1), ('scipy/scipy', 0.5634987354278564, 'math', 0), ('blaze/blaze', 0.5468524098396301, 'pandas', 0), ('cython/cython', 0.5226044058799744, 'util', 1), ('fredrik-johansson/mpmath', 0.516451895236969, 'math', 0), ('pypy/pypy', 0.5114945769309998, 'util', 0), ('fsspec/filesystem_spec', 0.5076752305030823, 'util', 0)]

44

4

null

3.35

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0

26

29

26

87

180

90

2.1

38

1,532

data

https://github.com/databricks/dbt-databricks

['databricks', 'dbt']

null

[]

null

databricks/dbt-databricks

dbt-databricks

165

91

19

Python

https://databricks.com

A dbt adapter for Databricks.

databricks

2024-01-06

2021-10-19

119

1.386555

https://avatars.githubusercontent.com/u/4998052?v=4

A dbt adapter for Databricks.

['databricks', 'dbt', 'etl', 'sql']

2024-01-12

[('dbt-labs/dbt-spark', 0.6950157284736633, 'data', 1), ('databrickslabs/dbx', 0.6466124057769775, 'data', 1), ('duckdb/dbt-duckdb', 0.5661155581474304, 'data', 1), ('airbnb/omniduct', 0.5590947866439819, 'data', 0), ('airbytehq/airbyte', 0.5521032214164734, 'data', 1), ('dbt-labs/dbt-core', 0.5302814841270447, 'ml-ops', 0), ('dlt-hub/dlt', 0.5166671276092529, 'data', 0), ('tobymao/sqlglot', 0.5069236755371094, 'data', 2), ('tconbeer/sqlfmt', 0.5048282146453857, 'data', 2)]

69

3

null

5.67

107

88

27

0

29

38

29

107

168

90

1.6

38

1,746

util

https://github.com/callowayproject/bump-my-version

['code-quality']

null

[]

null

callowayproject/bump-my-version

bump-my-version

115

14

7

Python

https://callowayproject.github.io/bump-my-version/

A small command line tool to simplify releasing software by updating all version strings in your source code by the correct increment and optionally commit and tag the changes.

callowayproject

2024-01-11

2023-04-12

41

2.74744

https://avatars.githubusercontent.com/u/305772?v=4

A small command line tool to simplify releasing software by updating all version strings in your source code by the correct increment and optionally commit and tag the changes.

['bumpversion', 'version', 'versioning']

['bumpversion', 'code-quality', 'version', 'versioning']

2024-01-13

[('c4urself/bump2version', 0.7459608316421509, 'util', 1), ('pypa/setuptools_scm', 0.6197443604469299, 'util', 1), ('mtkennerly/dunamai', 0.6012407541275024, 'util', 1), ('asottile/pyupgrade', 0.5788130760192871, 'util', 1), ('mtkennerly/poetry-dynamic-versioning', 0.5595990419387817, 'util', 1), ('python-versioneer/python-versioneer', 0.5228790640830994, 'util', 0)]

12

5

null

4.5

58

50

9

0

24

38

24

58

92

90

1.6

38

747

study

https://github.com/karpathy/micrograd

[]

null

[]

null

karpathy/micrograd

micrograd

7,103

917

131

Jupyter Notebook

null

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

karpathy

2024-01-14

2020-04-13

198

35.847873

null

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

[]

2020-04-18

[('pytorch/ignite', 0.7160765528678894, 'ml-dl', 0), ('intel/intel-extension-for-pytorch', 0.6794243454933167, 'perf', 0), ('skorch-dev/skorch', 0.644400417804718, 'ml-dl', 0), ('nvidia/apex', 0.6441670060157776, 'ml-dl', 0), ('rafiqhasan/auto-tensorflow', 0.634564220905304, 'ml-dl', 0), ('denys88/rl_games', 0.6286336779594421, 'ml-rl', 0), ('pytorch/glow', 0.6073175668716431, 'ml', 0), ('ggerganov/ggml', 0.6055065393447876, 'ml', 0), ('huggingface/transformers', 0.6045575737953186, 'nlp', 0), ('mrdbourke/pytorch-deep-learning', 0.602993369102478, 'study', 0), ('microsoft/nni', 0.6010633111000061, 'ml', 0), ('arogozhnikov/einops', 0.600235104560852, 'ml-dl', 0), ('neuralmagic/sparseml', 0.597611129283905, 'ml-dl', 0), ('rasbt/machine-learning-book', 0.597282350063324, 'study', 0), ('pytorch/rl', 0.5971662402153015, 'ml-rl', 0), ('microsoft/flaml', 0.5962915420532227, 'ml', 0), ('thu-ml/tianshou', 0.5894965529441833, 'ml-rl', 0), ('nvidia/deeplearningexamples', 0.583264946937561, 'ml-dl', 0), ('explosion/thinc', 0.581674337387085, 'ml-dl', 0), ('keras-team/autokeras', 0.5800349712371826, 'ml-dl', 0), ('pytorch/pytorch', 0.5792595744132996, 'ml-dl', 0), ('pytorch/data', 0.5738345980644226, 'data', 0), ('ray-project/ray', 0.5609050393104553, 'ml-ops', 0), ('alpa-projects/alpa', 0.5604699850082397, 'ml-dl', 0), ('ashleve/lightning-hydra-template', 0.5562566518783569, 'util', 0), ('uber/petastorm', 0.5534528493881226, 'data', 0), ('horovod/horovod', 0.552807092666626, 'ml-ops', 0), ('microsoft/onnxruntime', 0.5451004505157471, 'ml', 0), ('rentruewang/koila', 0.5448654890060425, 'ml', 0), ('tensorlayer/tensorlayer', 0.544183075428009, 'ml-rl', 0), ('lucidrains/imagen-pytorch', 0.5438899993896484, 'ml-dl', 0), ('nicolas-chaulet/torch-points3d', 0.5409857034683228, 'ml', 0), ('deepmind/dm-haiku', 0.5368869304656982, 'ml-dl', 0), ('xl0/lovely-tensors', 0.5362251400947571, 'ml-dl', 0), ('determined-ai/determined', 0.5347241163253784, 'ml-ops', 0), ('pyg-team/pytorch_geometric', 0.5318362712860107, 'ml-dl', 0), ('huggingface/optimum', 0.5316488146781921, 'ml', 0), ('google/trax', 0.5311139822006226, 'ml-dl', 0), ('aws/sagemaker-python-sdk', 0.5261572003364563, 'ml', 0), ('facebookresearch/pytorch3d', 0.5227355360984802, 'ml-dl', 0), ('lightly-ai/lightly', 0.5221474766731262, 'ml', 0), ('aiqc/aiqc', 0.5214496850967407, 'ml-ops', 0), ('intellabs/bayesian-torch', 0.5212419629096985, 'ml', 0), ('huggingface/accelerate', 0.5209835767745972, 'ml', 0), ('mosaicml/composer', 0.517072856426239, 'ml-dl', 0), ('allenai/allennlp', 0.5140243768692017, 'nlp', 0), ('google/automl', 0.5122846364974976, 'ml', 0), ('ludwig-ai/ludwig', 0.5106154680252075, 'ml-ops', 0), ('koaning/human-learn', 0.509779691696167, 'data', 0), ('pyro-ppl/pyro', 0.5077245831489563, 'ml-dl', 0), ('tensorflow/tensor2tensor', 0.5075839757919312, 'ml', 0), ('activeloopai/deeplake', 0.5072367191314697, 'ml-ops', 0), ('epistasislab/tpot', 0.5062547922134399, 'ml', 0), ('plasma-umass/scalene', 0.5055549740791321, 'profiling', 0), ('rasbt/deeplearning-models', 0.5046243667602539, 'ml-dl', 0), ('huggingface/peft', 0.5045297145843506, 'llm', 0), ('kubeflow/fairing', 0.5037677884101868, 'ml-ops', 0), ('microsoft/deepspeed', 0.5035680532455444, 'ml-dl', 0), ('lucidrains/dalle2-pytorch', 0.5032515525817871, 'diffusion', 0), ('salesforce/deeptime', 0.5016177892684937, 'time-series', 0)]

2

1

null

0

7

4

46

0

7

3

90

0.4

37

817

study

https://github.com/firmai/industry-machine-learning

[]

null

[]

null

firmai/industry-machine-learning

industry-machine-learning

6,946

1,151

389

Jupyter Notebook

https://www.linkedin.com/company/firmai

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

firmai

2024-01-13

2019-05-03

247

28.056549

null

A curated list of applied machine learning and data science notebooks and libraries across different industries (by @firmai)

['data-science', 'datascience', 'example', 'firmai', 'jupyter-notebook', 'machine-learning', 'practical-machine-learning']

2021-12-18

[('cerlymarco/medium_notebook', 0.6431946158409119, 'study', 2), ('ageron/handson-ml2', 0.6424956321716309, 'ml', 0), ('feast-dev/feast', 0.6406149864196777, 'ml-ops', 2), ('krzjoa/awesome-python-data-science', 0.6359909772872925, 'study', 2), ('tensorflow/data-validation', 0.6276463866233826, 'ml-ops', 0), ('gradio-app/gradio', 0.6118634939193726, 'viz', 2), ('mlflow/mlflow', 0.6037585735321045, 'ml-ops', 1), ('tensorflow/tensorflow', 0.6019365191459656, 'ml-dl', 1), ('kubeflow-kale/kale', 0.5946695804595947, 'ml-ops', 2), ('scikit-learn/scikit-learn', 0.5884523987770081, 'ml', 2), ('huggingface/datasets', 0.5870203375816345, 'nlp', 1), ('mrdbourke/zero-to-mastery-ml', 0.5863468647003174, 'study', 2), ('onnx/onnx', 0.5830479264259338, 'ml', 1), ('tensorflow/tensor2tensor', 0.5822129249572754, 'ml', 1), ('polyaxon/polyaxon', 0.5819257497787476, 'ml-ops', 2), ('patchy631/machine-learning', 0.5763393044471741, 'ml', 0), ('rasbt/mlxtend', 0.5761663913726807, 'ml', 2), ('determined-ai/determined', 0.574253261089325, 'ml-ops', 2), ('polyaxon/datatile', 0.5717259049415588, 'pandas', 1), ('googlecloudplatform/vertex-ai-samples', 0.5715494751930237, 'ml', 1), ('dylanhogg/awesome-python', 0.5685208439826965, 'study', 2), ('jovianml/opendatasets', 0.5650241374969482, 'data', 2), ('alirezadir/machine-learning-interview-enlightener', 0.5614524483680725, 'study', 1), ('rasbt/machine-learning-book', 0.5610123872756958, 'study', 1), ('huggingface/evaluate', 0.5610095858573914, 'ml', 1), ('merantix-momentum/squirrel-core', 0.5604248642921448, 'ml', 2), ('xplainable/xplainable', 0.5596107840538025, 'ml-interpretability', 2), ('tensorlayer/tensorlayer', 0.5479680299758911, 'ml-rl', 0), ('automl/auto-sklearn', 0.5466862320899963, 'ml', 0), ('csinva/imodels', 0.5446041226387024, 'ml', 2), ('districtdatalabs/yellowbrick', 0.5426095128059387, 'ml', 1), ('aws/sagemaker-python-sdk', 0.5424572229385376, 'ml', 1), ('sktime/sktime', 0.541723370552063, 'time-series', 2), ('fchollet/deep-learning-with-python-notebooks', 0.5408152937889099, 'study', 0), ('teamhg-memex/eli5', 0.5391788482666016, 'ml', 2), ('zenodo/zenodo', 0.5377620458602905, 'util', 0), ('uber/petastorm', 0.5362139940261841, 'data', 1), ('nccr-itmo/fedot', 0.5340647101402283, 'ml-ops', 1), ('airbnb/knowledge-repo', 0.5338939428329468, 'data', 1), ('google-research/google-research', 0.5328598618507385, 'ml', 1), ('ddbourgin/numpy-ml', 0.5301154255867004, 'ml', 1), ('microsoft/nni', 0.528578519821167, 'ml', 2), ('explosion/thinc', 0.5279266834259033, 'ml-dl', 1), ('online-ml/river', 0.5276996493339539, 'ml', 2), ('rasbt/stat451-machine-learning-fs20', 0.5267770886421204, 'study', 0), ('wandb/client', 0.5243285894393921, 'ml', 2), ('dagworks-inc/hamilton', 0.5236888527870178, 'ml-ops', 2), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5232796669006348, 'study', 1), ('probml/pyprobml', 0.5219587087631226, 'ml', 1), ('keras-team/keras', 0.5215654969215393, 'ml-dl', 2), ('kubeflow/pipelines', 0.5197041034698486, 'ml-ops', 2), ('fatiando/verde', 0.5189895629882812, 'gis', 1), ('d2l-ai/d2l-en', 0.5169808268547058, 'study', 2), ('scikit-learn-contrib/imbalanced-learn', 0.5154035687446594, 'ml', 2), ('google/tf-quant-finance', 0.5136438012123108, 'finance', 0), ('hazyresearch/meerkat', 0.5096346735954285, 'viz', 2), ('drivendata/cookiecutter-data-science', 0.5075307488441467, 'template', 2), ('wesm/pydata-book', 0.5071250200271606, 'study', 0), ('netflix/metaflow', 0.5058495402336121, 'ml-ops', 3), ('adap/flower', 0.5053890347480774, 'ml-ops', 1), ('doccano/doccano', 0.50450199842453, 'nlp', 1), ('milvus-io/bootcamp', 0.5041669011116028, 'data', 0), ('pycaret/pycaret', 0.5026911497116089, 'ml', 2), ('ploomber/ploomber', 0.5007092952728271, 'ml-ops', 2)]

6

4

null

0

57

25

0

90

0

37

1,022

finance

https://github.com/google/tf-quant-finance

[]

null

[]

null

google/tf-quant-finance

tf-quant-finance

4,160

545

168

Python

null

High-performance TensorFlow library for quantitative finance.

google

2024-01-14

2019-07-24

235

17.637795

https://avatars.githubusercontent.com/u/1342004?v=4

High-performance TensorFlow library for quantitative finance.

['finance', 'gpu', 'gpu-computing', 'high-performance', 'high-performance-computing', 'numerical-integration', 'numerical-methods', 'numerical-optimization', 'quantitative-finance', 'quantlib', 'tensorflow']

2023-08-15

[('tensorly/tensorly', 0.636419951915741, 'ml-dl', 1), ('pytorch/pytorch', 0.6339718103408813, 'ml-dl', 1), ('goldmansachs/gs-quant', 0.6332827806472778, 'finance', 0), ('intel/intel-extension-for-pytorch', 0.6181202530860901, 'perf', 0), ('ggerganov/ggml', 0.6140791773796082, 'ml', 0), ('arogozhnikov/einops', 0.6102033853530884, 'ml-dl', 1), ('nvidia/tensorrt-llm', 0.6080841422080994, 'viz', 1), ('horovod/horovod', 0.6027436852455139, 'ml-ops', 1), ('tensorlayer/tensorlayer', 0.5923408269882202, 'ml-rl', 1), ('xl0/lovely-tensors', 0.5893839597702026, 'ml-dl', 0), ('microsoft/onnxruntime', 0.5870956182479858, 'ml', 1), ('tlkh/tf-metal-experiments', 0.5859279036521912, 'perf', 2), ('tensorflow/tensorflow', 0.5797778367996216, 'ml-dl', 1), ('catboost/catboost', 0.5715440511703491, 'ml', 2), ('ray-project/ray', 0.5673449039459229, 'ml-ops', 1), ('tensorflow/addons', 0.5670149326324463, 'ml', 1), ('microsoft/deepspeed', 0.5623762011528015, 'ml-dl', 1), ('google/gin-config', 0.5610681772232056, 'util', 1), ('rafiqhasan/auto-tensorflow', 0.5538135766983032, 'ml-dl', 1), ('tensorflow/similarity', 0.552481472492218, 'ml-dl', 1), ('ranaroussi/quantstats', 0.5515581369400024, 'finance', 2), ('pytorch/ignite', 0.5492528676986694, 'ml-dl', 0), ('ta-lib/ta-lib-python', 0.5487057566642761, 'finance', 2), ('huggingface/datasets', 0.5474328994750977, 'nlp', 1), ('determined-ai/determined', 0.5471197366714478, 'ml-ops', 1), ('aws/sagemaker-python-sdk', 0.5465176105499268, 'ml', 1), ('zvtvz/zvt', 0.5456732511520386, 'finance', 1), ('polyaxon/datatile', 0.5451685190200806, 'pandas', 1), ('microsoft/qlib', 0.5447477698326111, 'finance', 2), ('ai4finance-foundation/finrl', 0.54345703125, 'finance', 1), ('explosion/thinc', 0.5434539318084717, 'ml-dl', 1), ('keras-team/keras', 0.5417336821556091, 'ml-dl', 1), ('blackhc/toma', 0.5406495928764343, 'ml-dl', 1), ('nvidia/warp', 0.5373433828353882, 'sim', 1), ('pytorchlightning/pytorch-lightning', 0.534396767616272, 'ml-dl', 0), ('fastai/fastcore', 0.5327866077423096, 'util', 0), ('eventual-inc/daft', 0.5302774906158447, 'pandas', 0), ('dmlc/xgboost', 0.5295057892799377, 'ml', 0), ('d2l-ai/d2l-en', 0.5287189483642578, 'study', 1), ('mrdbourke/m1-machine-learning-test', 0.5282031893730164, 'ml', 1), ('intel/scikit-learn-intelex', 0.5270321369171143, 'perf', 1), ('activeloopai/deeplake', 0.5263845324516296, 'ml-ops', 1), ('rapidsai/cudf', 0.5263254046440125, 'pandas', 1), ('pytorch/torchrec', 0.5250528454780579, 'ml-dl', 1), ('cupy/cupy', 0.5244703888893127, 'math', 1), ('quantconnect/lean', 0.5243059992790222, 'finance', 1), ('rasbt/machine-learning-book', 0.523298442363739, 'study', 0), ('cython/cython', 0.5225537419319153, 'util', 0), ('isl-org/open3d', 0.5206282138824463, 'sim', 2), ('huggingface/transformers', 0.5193233489990234, 'nlp', 1), ('polakowo/vectorbt', 0.5182610154151917, 'finance', 2), ('googlecloudplatform/vertex-ai-samples', 0.5174439549446106, 'ml', 0), ('plasma-umass/scalene', 0.5155574083328247, 'profiling', 1), ('gradio-app/gradio', 0.5152886509895325, 'viz', 0), ('dylanhogg/awesome-python', 0.5142082571983337, 'study', 0), ('firmai/industry-machine-learning', 0.5136438012123108, 'study', 0), ('ashleve/lightning-hydra-template', 0.5111380219459534, 'util', 0), ('gbeced/pyalgotrade', 0.5105053186416626, 'finance', 0), ('ddbourgin/numpy-ml', 0.509579598903656, 'ml', 0), ('huggingface/accelerate', 0.5086351633071899, 'ml', 0), ('exaloop/codon', 0.5077102780342102, 'perf', 1), ('pytorch/glow', 0.5075867772102356, 'ml', 0), ('keras-team/autokeras', 0.5068373680114746, 'ml-dl', 1), ('merantix-momentum/squirrel-core', 0.5065999031066895, 'ml', 1), ('pytorch/rl', 0.5055859088897705, 'ml-rl', 0), ('pycaret/pycaret', 0.5044597387313843, 'ml', 1), ('pypy/pypy', 0.5041675567626953, 'util', 0), ('salesforce/warp-drive', 0.5037093162536621, 'ml-rl', 1), ('mrdbourke/tensorflow-deep-learning', 0.5032038688659668, 'study', 1), ('uber/petastorm', 0.5018066167831421, 'data', 1), ('nyandwi/modernconvnets', 0.501559853553772, 'ml-dl', 1)]

47

2

null

0.29

0

54

5

0

1

0

90

0

37

460

util

https://github.com/rspeer/python-ftfy

[]

null

[]

null

rspeer/python-ftfy

python-ftfy

3,647

153

76

Python

http://ftfy.readthedocs.org

Fixes mojibake and other glitches in Unicode text, after the fact.

rspeer

2024-01-12

2012-08-24

596

6.113266

null

Fixes mojibake and other glitches in Unicode text, after the fact.

[]

2023-11-21

[]

18

6

null

0.1

1

0

139

2

0

12

1

0

90

0

37

86

graph

https://github.com/stellargraph/stellargraph

[]

null

[]

null

stellargraph/stellargraph

stellargraph

2,836

418

64

Python

https://stellargraph.readthedocs.io/

StellarGraph - Machine Learning on Graphs

stellargraph

2024-01-13

2018-04-13

302

9.372993

https://avatars.githubusercontent.com/u/36725857?v=4

StellarGraph - Machine Learning on Graphs

['data-science', 'deep-learning', 'gcn', 'geometric-deep-learning', 'graph-analysis', 'graph-convolutional-networks', 'graph-data', 'graph-machine-learning', 'graph-neural-networks', 'graphs', 'heterogeneous-networks', 'interpretability', 'link-prediction', 'machine-learning', 'machine-learning-algorithms', 'networkx', 'saliency-map', 'stellargraph-library']

2021-10-29

[('chandlerbang/awesome-self-supervised-gnn', 0.6943688988685608, 'study', 3), ('danielegrattarola/spektral', 0.6824637055397034, 'ml-dl', 2), ('pyg-team/pytorch_geometric', 0.6726529002189636, 'ml-dl', 4), ('dmlc/dgl', 0.6574554443359375, 'ml-dl', 2), ('google-deepmind/materials_discovery', 0.6555060148239136, 'sim', 0), ('benedekrozemberczki/tigerlily', 0.6446079015731812, 'ml-dl', 3), ('a-r-j/graphein', 0.6164317727088928, 'sim', 3), ('graphistry/pygraphistry', 0.5959926247596741, 'data', 1), ('rampasek/graphgps', 0.5865841507911682, 'graph', 0), ('accenture/ampligraph', 0.5474543571472168, 'data', 1), ('networkx/networkx', 0.5425050258636475, 'graph', 1), ('googlecloudplatform/vertex-ai-samples', 0.5413510799407959, 'ml', 1), ('ddbourgin/numpy-ml', 0.5346408486366272, 'ml', 1), ('onnx/onnx', 0.5222296714782715, 'ml', 2), ('awslabs/dgl-ke', 0.5202558040618896, 'ml', 1), ('lutzroeder/netron', 0.514754056930542, 'ml', 2), ('tensorflow/tensorflow', 0.5133888125419617, 'ml-dl', 2), ('pygraphviz/pygraphviz', 0.5024316310882568, 'viz', 0), ('hazyresearch/hgcn', 0.500386118888855, 'ml', 0)]

36

6

null

0

5

1

70

27

0

5

2

90

0.4

37

818

study

https://github.com/alirezadir/machine-learning-interview-enlightener

[]

null

[]

null

alirezadir/machine-learning-interview-enlightener

Machine-Learning-Interviews

2,645

494

53

Jupyter Notebook

null

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

alirezadir

2024-01-14

2021-01-31

156

16.924132

null

This repo is meant to serve as a guide for Machine Learning/AI technical interviews.

['ai', 'deep-learning', 'interview', 'interview-practice', 'interview-preparation', 'interviews', 'machine-learning', 'machine-learning-algorithms', 'scalable-applications', 'system-design']

2023-10-26

[('bentoml/bentoml', 0.657772958278656, 'ml-ops', 3), ('google-research/google-research', 0.6368386745452881, 'ml', 2), ('google-research/language', 0.6070800423622131, 'nlp', 1), ('amanchadha/coursera-deep-learning-specialization', 0.6021793484687805, 'study', 1), ('patchy631/machine-learning', 0.5960847735404968, 'ml', 0), ('googlecloudplatform/vertex-ai-samples', 0.5835177302360535, 'ml', 1), ('oegedijk/explainerdashboard', 0.5830463171005249, 'ml-interpretability', 0), ('xplainable/xplainable', 0.5782299637794495, 'ml-interpretability', 2), ('tensorflow/tensorflow', 0.5763082504272461, 'ml-dl', 2), ('microsoft/nni', 0.5761905312538147, 'ml', 3), ('onnx/onnx', 0.5712395906448364, 'ml', 2), ('tensorlayer/tensorlayer', 0.5669152140617371, 'ml-rl', 1), ('mlflow/mlflow', 0.5668816566467285, 'ml-ops', 2), ('tensorflow/tensor2tensor', 0.5649195909500122, 'ml', 2), ('polyaxon/polyaxon', 0.564633309841156, 'ml-ops', 2), ('ml-for-high-risk-apps-book/machine-learning-for-high-risk-applications-book', 0.5615020394325256, 'study', 2), ('firmai/industry-machine-learning', 0.5614524483680725, 'study', 1), ('wandb/client', 0.5583623051643372, 'ml', 2), ('explosion/thinc', 0.5558744668960571, 'ml-dl', 3), ('mindsdb/mindsdb', 0.5548688173294067, 'data', 2), ('feast-dev/feast', 0.5510007739067078, 'ml-ops', 1), ('netflix/metaflow', 0.5488802194595337, 'ml-ops', 2), ('aimhubio/aim', 0.5477184653282166, 'ml-ops', 2), ('doccano/doccano', 0.5449758768081665, 'nlp', 1), ('deepmind/dm_control', 0.5414921641349792, 'ml-rl', 2), ('nvidia/nemo', 0.5406086444854736, 'nlp', 1), ('lastmile-ai/aiconfig', 0.5404054522514343, 'util', 1), ('cheshire-cat-ai/core', 0.539746105670929, 'llm', 1), ('activeloopai/deeplake', 0.5346347689628601, 'ml-ops', 3), ('keras-team/keras', 0.5340282917022705, 'ml-dl', 2), ('winedarksea/autots', 0.5339345335960388, 'time-series', 2), ('cleanlab/cleanlab', 0.5334048867225647, 'ml', 0), ('determined-ai/determined', 0.5306956768035889, 'ml-ops', 2), ('ml-tooling/opyrator', 0.5304664969444275, 'viz', 1), ('antonosika/gpt-engineer', 0.527275800704956, 'llm', 1), ('avaiga/taipy', 0.5267717242240906, 'data', 0), ('gradio-app/gradio', 0.5261391401290894, 'viz', 2), ('keras-rl/keras-rl', 0.5244634747505188, 'ml-rl', 1), ('unity-technologies/ml-agents', 0.5230525732040405, 'ml-rl', 2), ('cerlymarco/medium_notebook', 0.5219733119010925, 'study', 2), ('polyaxon/datatile', 0.521611213684082, 'pandas', 0), ('csinva/imodels', 0.5202349424362183, 'ml', 2), ('sweepai/sweep', 0.5161364078521729, 'llm', 1), ('thilinarajapakse/simpletransformers', 0.5155435800552368, 'nlp', 0), ('iterative/dvc', 0.5138351917266846, 'ml-ops', 2), ('hpcaitech/colossalai', 0.5127544403076172, 'llm', 2), ('pytorchlightning/pytorch-lightning', 0.5122131109237671, 'ml-dl', 3), ('qdrant/qdrant', 0.5117506384849548, 'data', 1), ('automl/auto-sklearn', 0.5101978778839111, 'ml', 0), ('interpretml/interpret', 0.5096079707145691, 'ml-interpretability', 2), ('salesforce/logai', 0.5083866119384766, 'util', 2), ('nccr-itmo/fedot', 0.5080487728118896, 'ml-ops', 1), ('seldonio/alibi', 0.5047518014907837, 'ml-interpretability', 1), ('microsoft/onnxruntime', 0.5041807293891907, 'ml', 2), ('ourownstory/neural_prophet', 0.503267228603363, 'ml', 2), ('ddbourgin/numpy-ml', 0.5029667019844055, 'ml', 1), ('microsoft/generative-ai-for-beginners', 0.5020521283149719, 'study', 1), ('jindongwang/transferlearning', 0.5019001364707947, 'ml', 2), ('marqo-ai/marqo', 0.5009713768959045, 'ml', 2), ('oneil512/insight', 0.5009233355522156, 'ml', 1), ('kubeflow/pipelines', 0.5008544921875, 'ml-ops', 1), ('nvidia/deeplearningexamples', 0.5003179907798767, 'ml-dl', 1)]

7

4

null

1.33

1

0

36

3

0

1

0

90

0

37

704

pandas

https://github.com/jmcarpenter2/swifter

[]

null

[]

null

jmcarpenter2/swifter

swifter

2,402

101

31

Python

null

A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner

jmcarpenter2

2024-01-12

2018-04-07

303

7.916196

null

A package which efficiently applies any function to a pandas dataframe or series in the fastest available manner

['dask', 'modin', 'pandas', 'pandas-dataframe', 'parallel-computing', 'parallelization']

2023-07-31

[('nalepae/pandarallel', 0.7605847716331482, 'pandas', 1), ('ddelange/mapply', 0.6554047465324402, 'pandas', 0), ('modin-project/modin', 0.6068665385246277, 'perf', 2), ('dask/dask', 0.60169517993927, 'perf', 2), ('rapidsai/cudf', 0.5688180923461914, 'pandas', 2), ('mementum/bta-lib', 0.5637902021408081, 'finance', 0), ('blaze/blaze', 0.5631571412086487, 'pandas', 0), ('holoviz/spatialpandas', 0.562759518623352, 'pandas', 1), ('lux-org/lux', 0.5564085841178894, 'viz', 1), ('joblib/joblib', 0.5563712120056152, 'util', 1), ('eventual-inc/daft', 0.55370032787323, 'pandas', 0), ('adamerose/pandasgui', 0.5478309988975525, 'pandas', 1), ('vaexio/vaex', 0.5449737906455994, 'perf', 0), ('pandas-dev/pandas', 0.5424719452857971, 'pandas', 1), ('tkrabel/bamboolib', 0.5419985055923462, 'pandas', 1), ('twopirllc/pandas-ta', 0.539636492729187, 'finance', 1), ('fugue-project/fugue', 0.5381412506103516, 'pandas', 2), ('sfu-db/connector-x', 0.5345582962036133, 'data', 0), ('pola-rs/polars', 0.5324315428733826, 'pandas', 0), ('pytoolz/toolz', 0.5265946388244629, 'util', 0), ('klen/py-frameworks-bench', 0.519839346408844, 'perf', 0), ('pytables/pytables', 0.5137337446212769, 'data', 0), ('fastai/fastcore', 0.5132153034210205, 'util', 0), ('scikit-learn-contrib/sklearn-pandas', 0.5050438046455383, 'pandas', 0)]

17

4

null

0.33

5

0

70

6

0

14

5

2

90

0.4

37

956

ml-dl

https://github.com/danielegrattarola/spektral

[]

null

['2006.12138']

[]

null

danielegrattarola/spektral

spektral

2,314

337

44

Python

https://graphneural.network

Graph Neural Networks with Keras and Tensorflow 2.

danielegrattarola

2024-01-13

2019-01-17

262

8.808048

null

Graph Neural Networks with Keras and Tensorflow 2.

['deep-learning', 'graph-deep-learning', 'graph-neural-networks', 'keras', 'tensorflow', 'tensorflow2']

2023-06-01

[('pyg-team/pytorch_geometric', 0.7439136505126953, 'ml-dl', 2), ('dmlc/dgl', 0.6934017539024353, 'ml-dl', 2), ('stellargraph/stellargraph', 0.6824637055397034, 'graph', 2), ('chandlerbang/awesome-self-supervised-gnn', 0.6770707964897156, 'study', 2), ('nyandwi/modernconvnets', 0.6024564504623413, 'ml-dl', 2), ('rampasek/graphgps', 0.5940183997154236, 'graph', 0), ('keras-rl/keras-rl', 0.5715480446815491, 'ml-rl', 2), ('keras-team/keras', 0.5592799186706543, 'ml-dl', 2), ('benedekrozemberczki/tigerlily', 0.5574583411216736, 'ml-dl', 1), ('tensorflow/addons', 0.5564872026443481, 'ml', 2), ('hazyresearch/hgcn', 0.5537418723106384, 'ml', 0), ('a-r-j/graphein', 0.551216721534729, 'sim', 2), ('googlecloudplatform/vertex-ai-samples', 0.545731782913208, 'ml', 0), ('lutzroeder/netron', 0.5387458205223083, 'ml', 3), ('google-deepmind/materials_discovery', 0.5381258130073547, 'sim', 0), ('graphistry/pygraphistry', 0.5304725170135498, 'data', 0), ('onnx/onnx', 0.5261642932891846, 'ml', 3), ('tensorflow/tensorflow', 0.5244050025939941, 'ml-dl', 2), ('cvxgrp/pymde', 0.520326554775238, 'ml', 0), ('tensorlayer/tensorlayer', 0.5144057869911194, 'ml-rl', 2), ('keras-team/keras-nlp', 0.5112001299858093, 'nlp', 3), ('horovod/horovod', 0.5111513733863831, 'ml-ops', 3), ('ddbourgin/numpy-ml', 0.5083205699920654, 'ml', 0), ('xl0/lovely-tensors', 0.5056509375572205, 'ml-dl', 1), ('accenture/ampligraph', 0.5038337707519531, 'data', 0), ('tensorly/tensorly', 0.5032951831817627, 'ml-dl', 1)]

27

3

null

0.33

3

1

61

8

1

3

5

90

1.7

37

255

crypto

https://github.com/bmoscon/cryptofeed

[]

null

[]

null

bmoscon/cryptofeed

cryptofeed

1,973

712

79

Python

null

Cryptocurrency Exchange Websocket Data Feed Handler

bmoscon

2024-01-13

2017-12-16

319

6.176655

null

Cryptocurrency Exchange Websocket Data Feed Handler

['asyncio', 'binance', 'bitcoin', 'btc', 'coinbase', 'coinbase-api', 'crypto', 'cryptocurrencies', 'cryptocurrency', 'ethereum', 'exchange', 'ftx-exchange', 'influxdb', 'market-data', 'trading', 'trading-platform', 'websocket', 'websockets']

2024-01-07

[('ccxt/ccxt', 0.6092362999916077, 'crypto', 9), ('miguelgrinberg/python-socketio', 0.595906138420105, 'util', 2), ('freqtrade/freqtrade', 0.5561859011650085, 'crypto', 3), ('websocket-client/websocket-client', 0.5356486439704895, 'web', 2), ('pmaji/crypto-whale-watching-app', 0.5131617188453674, 'crypto', 3), ('gbeced/basana', 0.5091555118560791, 'finance', 3)]

112

0

null

0.71

16

11

74

0

2

12

2

16

13

90

0.8

37

1,684

util

https://github.com/landscapeio/prospector

['linting', 'styling']

null

[]

null

landscapeio/prospector

prospector

1,882

176

35

Python

null

Inspects Python source files and provides information about type and location of classes, methods etc

landscapeio

2024-01-12

2013-08-05

547

3.439687

https://avatars.githubusercontent.com/u/4759094?v=4

Inspects Python source files and provides information about type and location of classes, methods etc

[]

['linting', 'styling']

2023-10-18

[('eugeneyan/python-collab-template', 0.6496816873550415, 'template', 1), ('google/pytype', 0.6452606916427612, 'typing', 0), ('pympler/pympler', 0.6098625659942627, 'perf', 0), ('hadialqattan/pycln', 0.6040316224098206, 'util', 0), ('nedbat/coveragepy', 0.6040084362030029, 'testing', 0), ('gaogaotiantian/viztracer', 0.6018545627593994, 'profiling', 0), ('pyutils/line_profiler', 0.5992322564125061, 'profiling', 0), ('mkdocstrings/griffe', 0.5961143970489502, 'util', 0), ('facebook/pyre-check', 0.5935577154159546, 'typing', 0), ('klen/pylama', 0.5915239453315735, 'util', 0), ('pytoolz/toolz', 0.5871560573577881, 'util', 0), ('urwid/urwid', 0.586963951587677, 'term', 0), ('python/cpython', 0.5828319787979126, 'util', 0), ('jiffyclub/snakeviz', 0.582079291343689, 'profiling', 0), ('hhatto/autopep8', 0.5784581303596497, 'util', 0), ('astral-sh/ruff', 0.5776445269584656, 'util', 0), ('eleutherai/pyfra', 0.5767074227333069, 'ml', 0), ('brandon-rhodes/python-patterns', 0.5751134157180786, 'util', 0), ('pycqa/isort', 0.574863851070404, 'util', 0), ('instagram/monkeytype', 0.5743587017059326, 'typing', 0), ('rubik/radon', 0.5695351362228394, 'util', 0), ('google/yapf', 0.5676681995391846, 'util', 0), ('python-rope/rope', 0.5660980939865112, 'util', 0), ('pycqa/pyflakes', 0.5659628510475159, 'util', 0), ('mitmproxy/pdoc', 0.5606246590614319, 'util', 0), ('tiangolo/typer', 0.558975100517273, 'term', 0), ('xrudelis/pytrait', 0.5579221248626709, 'util', 0), ('wesm/pydata-book', 0.5570473670959473, 'study', 0), ('grantjenks/blue', 0.5565185546875, 'util', 0), ('requests/toolbelt', 0.5488244891166687, 'util', 0), ('amaargiru/pyroad', 0.5477283596992493, 'study', 0), ('alexmojaki/snoop', 0.5469942688941956, 'debug', 0), ('pypi/warehouse', 0.545502245426178, 'util', 0), ('psf/black', 0.5413801670074463, 'util', 0), ('hoffstadt/dearpygui', 0.5395547747612, 'gui', 0), ('ta-lib/ta-lib-python', 0.5358104109764099, 'finance', 0), ('python/mypy', 0.5345390439033508, 'typing', 0), ('pypa/hatch', 0.5343112945556641, 'util', 0), ('samuelcolvin/python-devtools', 0.5334382057189941, 'debug', 0), ('microsoft/pyright', 0.5327200293540955, 'typing', 0), ('pypy/pypy', 0.5321429371833801, 'util', 0), ('pycqa/pycodestyle', 0.531697690486908, 'util', 0), ('pycqa/eradicate', 0.5313110947608948, 'util', 2), ('pythonprofilers/memory_profiler', 0.5307861566543579, 'profiling', 0), ('sourcery-ai/sourcery', 0.5299766659736633, 'util', 0), ('agronholm/typeguard', 0.528834879398346, 'typing', 0), ('pygments/pygments', 0.5254445672035217, 'util', 0), ('pycqa/flake8', 0.5223195552825928, 'util', 0), ('instagram/fixit', 0.5204662084579468, 'util', 0), ('erotemic/ubelt', 0.518781840801239, 'util', 0), ('beeware/toga', 0.517236590385437, 'gui', 0), ('google/python-fire', 0.5145845413208008, 'term', 0), ('googleapis/google-api-python-client', 0.5145336389541626, 'util', 0), ('python-attrs/attrs', 0.5136226415634155, 'typing', 0), ('facebookincubator/bowler', 0.5116630792617798, 'util', 0), ('python/typeshed', 0.509270191192627, 'typing', 0), ('dosisod/refurb', 0.5087876915931702, 'util', 0), ('pycqa/pylint-django', 0.5079518556594849, 'util', 0), ('roniemartinez/dude', 0.5066967606544495, 'util', 0), ('willmcgugan/textual', 0.5064331889152527, 'term', 0), ('pyglet/pyglet', 0.5031312108039856, 'gamedev', 0)]

90

3

null

0.88

15

2

127

3

4

10

4

15

23

90

1.5

37

298

util

https://github.com/julienpalard/pipe

[]

null

[]

null

julienpalard/pipe

Pipe

1,797

111

26

Python

null

A Python library to use infix notation in Python

julienpalard

2024-01-13

2010-04-08

720

2.49336

null

A Python library to use infix notation in Python

[]

2024-01-07

[('google/latexify_py', 0.5925378799438477, 'util', 0), ('pytoolz/toolz', 0.5835241079330444, 'util', 0), ('connorferster/handcalcs', 0.5392968058586121, 'jupyter', 0), ('pyston/pyston', 0.5197369456291199, 'util', 0), ('sympy/sympy', 0.5134634971618652, 'math', 0), ('pmorissette/ffn', 0.5104817748069763, 'finance', 0), ('geospatialpython/pyshp', 0.5082536935806274, 'gis', 0)]

29

4

null

0.17

9

6

168

0

1

9

22

90

2.4

37

591

data

https://github.com/uber/petastorm

[]

null

[]

null

uber/petastorm

petastorm

1,711

280

41

Python

null

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

uber

2024-01-12

2018-06-15

293

5.828224

https://avatars.githubusercontent.com/u/538264?v=4

Petastorm library enables single machine or distributed training and evaluation of deep learning models from datasets in Apache Parquet format. It supports ML frameworks such as Tensorflow, Pytorch, and PySpark and can be used from pure Python code.

['deep-learning', 'machine-learning', 'parquet', 'parquet-files', 'pyarrow', 'pyspark', 'pytorch', 'sysml', 'tensorflow']

2023-12-02

[('microsoft/deepspeed', 0.6462931632995605, 'ml-dl', 3), ('horovod/horovod', 0.6362690329551697, 'ml-ops', 4), ('determined-ai/determined', 0.6062763929367065, 'ml-ops', 4), ('ageron/handson-ml2', 0.5999022126197815, 'ml', 0), ('gradio-app/gradio', 0.5904715061187744, 'viz', 2), ('pytorch/ignite', 0.5855341553688049, 'ml-dl', 3), ('tensorflow/tensorflow', 0.5829108953475952, 'ml-dl', 3), ('merantix-momentum/squirrel-core', 0.5779027938842773, 'ml', 4), ('tensorflow/tensor2tensor', 0.5750295519828796, 'ml', 2), ('ashleve/lightning-hydra-template', 0.5747993588447571, 'util', 2), ('aws/sagemaker-python-sdk', 0.5683594346046448, 'ml', 3), ('rasbt/machine-learning-book', 0.5682684183120728, 'study', 3), ('paddlepaddle/paddle', 0.5659868717193604, 'ml-dl', 2), ('intel/intel-extension-for-pytorch', 0.5632723569869995, 'perf', 3), ('fchollet/deep-learning-with-python-notebooks', 0.5607595443725586, 'study', 0), ('mlflow/mlflow', 0.559465765953064, 'ml-ops', 1), ('huggingface/huggingface_hub', 0.5579898357391357, 'ml', 3), ('nvidia/deeplearningexamples', 0.5578290820121765, 'ml-dl', 3), ('eventual-inc/daft', 0.557521641254425, 'pandas', 2), ('deepmind/dm-haiku', 0.557473361492157, 'ml-dl', 2), ('neuralmagic/sparseml', 0.5541288256645203, 'ml-dl', 2), ('karpathy/micrograd', 0.5534528493881226, 'study', 0), ('huggingface/transformers', 0.5520153641700745, 'nlp', 4), ('oml-team/open-metric-learning', 0.5485543012619019, 'ml', 2), ('skorch-dev/skorch', 0.5473853945732117, 'ml-dl', 2), ('ggerganov/ggml', 0.5469512939453125, 'ml', 1), ('aiqc/aiqc', 0.5461896061897278, 'ml-ops', 0), ('dmlc/xgboost', 0.5380932688713074, 'ml', 1), ('firmai/industry-machine-learning', 0.5362139940261841, 'study', 1), ('microsoft/flaml', 0.5358170866966248, 'ml', 2), ('huggingface/datasets', 0.5324203372001648, 'nlp', 4), ('keras-team/autokeras', 0.5320855975151062, 'ml-dl', 3), ('deepmodeling/deepmd-kit', 0.5317656397819519, 'sim', 2), ('alpa-projects/alpa', 0.5310642719268799, 'ml-dl', 2), ('ray-project/ray', 0.5304347276687622, 'ml-ops', 4), ('kubeflow/fairing', 0.529427170753479, 'ml-ops', 0), ('aistream-peelout/flow-forecast', 0.5273684859275818, 'time-series', 2), ('microsoft/jarvis', 0.5265276432037354, 'llm', 2), ('apache/incubator-mxnet', 0.5250005722045898, 'ml-dl', 0), ('adap/flower', 0.5249413847923279, 'ml-ops', 4), ('towhee-io/towhee', 0.5247065424919128, 'ml-ops', 1), ('mrdbourke/pytorch-deep-learning', 0.5223989486694336, 'study', 3), ('lightly-ai/lightly', 0.5194175243377686, 'ml', 3), ('keras-team/keras', 0.5165746808052063, 'ml-dl', 4), ('explosion/thinc', 0.5144953727722168, 'ml-dl', 4), ('facebookresearch/pytorch3d', 0.5134731531143188, 'ml-dl', 0), ('deepchecks/deepchecks', 0.5133116245269775, 'data', 3), ('pytorch/torchrec', 0.5117344260215759, 'ml-dl', 2), ('google/trax', 0.5106483101844788, 'ml-dl', 2), ('ml-tooling/opyrator', 0.5089090466499329, 'viz', 1), ('dmlc/dgl', 0.5088360905647278, 'ml-dl', 1), ('microsoft/nni', 0.508219301700592, 'ml', 4), ('pytorch/data', 0.5076653361320496, 'data', 0), ('kevinmusgrave/pytorch-metric-learning', 0.5072482824325562, 'ml', 3), ('tensorlayer/tensorlayer', 0.5072025060653687, 'ml-rl', 2), ('arogozhnikov/einops', 0.5071843862533569, 'ml-dl', 3), ('dylanhogg/awesome-python', 0.5067077875137329, 'study', 2), ('titanml/takeoff', 0.5053594708442688, 'llm', 0), ('nvidia/apex', 0.5052030086517334, 'ml-dl', 0), ('mosaicml/composer', 0.5039240121841431, 'ml-dl', 3), ('fastai/fastcore', 0.5022857189178467, 'util', 0), ('google/tf-quant-finance', 0.5018066167831421, 'finance', 1), ('pyg-team/pytorch_geometric', 0.5014254450798035, 'ml-dl', 2), ('catboost/catboost', 0.5008516311645508, 'ml', 1), ('vaexio/vaex', 0.500319242477417, 'perf', 2), ('pycaret/pycaret', 0.5002906322479248, 'ml', 1)]

50

4

null

0.06

4

2

68

1

20

1

4

90

1

37

1,004

finance

https://github.com/pmorissette/ffn

[]

null

[]

null

pmorissette/ffn

ffn

1,697

283

59

Python

pmorissette.github.io/ffn

ffn - a financial function library for Python

pmorissette

2024-01-13

2014-06-19

501

3.382403

null

ffn - a financial function library for Python

[]

2023-12-31

[('pytoolz/toolz', 0.6924606561660767, 'util', 0), ('domokane/financepy', 0.6907992959022522, 'finance', 0), ('goldmansachs/gs-quant', 0.6325653195381165, 'finance', 0), ('gbeced/pyalgotrade', 0.628166913986206, 'finance', 0), ('ta-lib/ta-lib-python', 0.5941312909126282, 'finance', 0), ('fredrik-johansson/mpmath', 0.58493971824646, 'math', 0), ('daxm/fmpsdk', 0.5664402842521667, 'finance', 0), ('hydrosquall/tiingo-python', 0.5629584789276123, 'finance', 0), ('quantecon/quantecon.py', 0.559691309928894, 'sim', 0), ('ethtx/ethtx', 0.5535359978675842, 'crypto', 0), ('cuemacro/finmarketpy', 0.5505915284156799, 'finance', 0), ('firmai/atspy', 0.5481270551681519, 'time-series', 0), ('robcarver17/pysystemtrade', 0.5440186262130737, 'finance', 0), ('quantopian/pyfolio', 0.5423455834388733, 'finance', 0), ('connorferster/handcalcs', 0.5378669500350952, 'jupyter', 0), ('eleutherai/pyfra', 0.5368715524673462, 'ml', 0), ('alkaline-ml/pmdarima', 0.5328418612480164, 'time-series', 0), ('pandas-dev/pandas', 0.5297597050666809, 'pandas', 0), ('numpy/numpy', 0.5275481343269348, 'math', 0), ('stan-dev/pystan', 0.5250624418258667, 'ml', 0), ('quantopian/zipline', 0.5246074199676514, 'finance', 0), ('mementum/backtrader', 0.5245431661605835, 'finance', 0), ('primal100/pybitcointools', 0.5242424607276917, 'crypto', 0), ('1200wd/bitcoinlib', 0.5135668516159058, 'crypto', 0), ('cuemacro/findatapy', 0.5108827948570251, 'finance', 0), ('julienpalard/pipe', 0.5104817748069763, 'util', 0), ('google/latexify_py', 0.5060634016990662, 'util', 0), ('scipy/scipy', 0.502606987953186, 'math', 0), ('bashtage/arch', 0.5025431513786316, 'time-series', 0), ('pypy/pypy', 0.5018722414970398, 'util', 0), ('rjt1990/pyflux', 0.5010930895805359, 'time-series', 0)]

32

3

null

0.44

22

18

117

0

4

1

4

22

15

90

0.7

37

629

debug

https://github.com/alexmojaki/birdseye

[]

null

[]

null

alexmojaki/birdseye

birdseye

1,593

75

42

JavaScript

https://birdseye.readthedocs.io

Graphical Python debugger which lets you easily view the values of all evaluated expressions

alexmojaki

2024-01-13

2017-07-22

340

4.679396

null

Graphical Python debugger which lets you easily view the values of all evaluated expressions

['ast', 'birdseye', 'debugger', 'debugging', 'python-debugger']

2023-10-16

[('alexmojaki/snoop', 0.6003603935241699, 'debug', 2), ('alexmojaki/heartrate', 0.5575025081634521, 'debug', 1), ('gaogaotiantian/viztracer', 0.5461402535438538, 'profiling', 1), ('samuelcolvin/python-devtools', 0.5242282748222351, 'debug', 0), ('google/pytype', 0.5039346218109131, 'typing', 0)]

10

4

null

0.02

2

79

3

0

1

2

9

90

4.5

37

179

nlp

https://github.com/explosion/spacy-models

[]

null

[]

null

explosion/spacy-models

spacy-models

1,465

301

47

Python

https://spacy.io

💫 Models for the spaCy Natural Language Processing (NLP) library

explosion

2024-01-12

2017-03-14

359

4.08078

https://avatars.githubusercontent.com/u/20011530?v=4

💫 Models for the spaCy Natural Language Processing (NLP) library

['machine-learning', 'machine-learning-models', 'models', 'natural-language-processing', 'nlp', 'spacy', 'spacy-models', 'statistical-models']

2023-11-22

[('explosion/spacy-stanza', 0.7454922199249268, 'nlp', 4), ('nltk/nltk', 0.6720556020736694, 'nlp', 3), ('huggingface/neuralcoref', 0.6682751774787903, 'nlp', 3), ('explosion/spacy-transformers', 0.6662450432777405, 'llm', 4), ('explosion/spacy-streamlit', 0.6529020071029663, 'nlp', 4), ('flairnlp/flair', 0.6428545117378235, 'nlp', 3), ('explosion/spacy', 0.6409233212471008, 'nlp', 4), ('allenai/allennlp', 0.6203604340553284, 'nlp', 2), ('iclrandd/blackstone', 0.612856388092041, 'nlp', 2), ('norskregnesentral/skweak', 0.608527660369873, 'nlp', 2), ('paddlepaddle/paddlenlp', 0.5910124182701111, 'llm', 1), ('explosion/spacy-llm', 0.5904589295387268, 'llm', 4), ('sloria/textblob', 0.5832897424697876, 'nlp', 2), ('freedomintelligence/llmzoo', 0.5769272446632385, 'llm', 0), ('lm-sys/fastchat', 0.5767900943756104, 'llm', 0), ('rasahq/rasa', 0.5728164315223694, 'llm', 4), ('lianjiatech/belle', 0.5633299946784973, 'llm', 0), ('llmware-ai/llmware', 0.5522136092185974, 'llm', 2), ('hannibal046/awesome-llm', 0.5515271425247192, 'study', 0), ('deepset-ai/farm', 0.5511075854301453, 'nlp', 1), ('infinitylogesh/mutate', 0.5492627620697021, 'nlp', 0), ('yueyu1030/attrprompt', 0.5483715534210205, 'llm', 1), ('alibaba/easynlp', 0.5481346845626831, 'nlp', 2), ('qanastek/drbert', 0.5431317090988159, 'llm', 2), ('mooler0410/llmspracticalguide', 0.5413009524345398, 'study', 2), ('lexpredict/lexpredict-lexnlp', 0.5394803285598755, 'nlp', 1), ('huggingface/transformers', 0.5389872193336487, 'nlp', 3), ('keras-team/keras-nlp', 0.5345762372016907, 'nlp', 3), ('makcedward/nlpaug', 0.5314129590988159, 'nlp', 3), ('jonasgeiping/cramming', 0.5299116373062134, 'nlp', 1), ('juncongmoo/pyllama', 0.5298112630844116, 'llm', 0), ('graykode/nlp-tutorial', 0.5290482044219971, 'study', 2), ('thilinarajapakse/simpletransformers', 0.5240768790245056, 'nlp', 0), ('eleutherai/lm-evaluation-harness', 0.5173574686050415, 'llm', 0), ('koaning/whatlies', 0.5144206881523132, 'nlp', 1), ('jalammar/ecco', 0.513950765132904, 'ml-interpretability', 2), ('neuralmagic/sparseml', 0.5111375451087952, 'ml-dl', 1), ('explosion/thinc', 0.5104645490646362, 'ml-dl', 4), ('ai21labs/lm-evaluation', 0.5086509585380554, 'llm', 0), ('pemistahl/lingua-py', 0.5069782137870789, 'nlp', 2), ('extreme-bert/extreme-bert', 0.5058228969573975, 'llm', 3), ('gunthercox/chatterbot-corpus', 0.5032789707183838, 'nlp', 0), ('tatsu-lab/stanford_alpaca', 0.5031586289405823, 'llm', 0), ('baichuan-inc/baichuan-13b', 0.5027161836624146, 'llm', 1), ('paddlepaddle/rocketqa', 0.5023024678230286, 'nlp', 1), ('openai/gpt-2', 0.5017908215522766, 'llm', 0), ('reasoning-machines/pal', 0.5003161430358887, 'llm', 0)]

14

7

null

4.5

3

83

2

199

149

199

3

0

90

0

37

1,617

util

https://github.com/samuelcolvin/watchfiles

[]

null

[]

null

samuelcolvin/watchfiles

watchfiles

1,435

99

18

Python

https://watchfiles.helpmanual.io

Simple, modern and fast file watching and code reload in python.

samuelcolvin

2024-01-14

2017-10-13

328

4.367391

null

Simple, modern and fast file watching and code reload in python.

['asyncio', 'filesystem', 'inotify', 'inotifywatch', 'notify', 'uvicorn']

2023-11-25

[('airtai/faststream', 0.5354728698730469, 'perf', 1), ('tox-dev/py-filelock', 0.5285630822181702, 'util', 0), ('magicstack/uvloop', 0.5178032517433167, 'util', 1), ('timofurrer/awesome-asyncio', 0.5153577327728271, 'study', 1), ('erotemic/ubelt', 0.5087971091270447, 'util', 0), ('sumerc/yappi', 0.5043572187423706, 'profiling', 1), ('python-trio/trio', 0.5042653679847717, 'perf', 0), ('grantjenks/python-diskcache', 0.5041387677192688, 'util', 1), ('samuelcolvin/arq', 0.5021094679832458, 'data', 1)]

40

3

null

0.25

10

4

76

2

3

5

3

10

15

90

1.5

37

645

profiling

https://github.com/p403n1x87/austin

[]

null

[]

null

p403n1x87/austin

austin

1,311

40

17

C

https://pypi.org/project/austin-dist/

Python frame stack sampler for CPython

p403n1x87

2024-01-12

2018-09-20

279

4.686925

null

Python frame stack sampler for CPython

['debugging-tools', 'performance', 'profiling']

2023-10-04

[('faster-cpython/tools', 0.6291638612747192, 'perf', 0), ('faster-cpython/ideas', 0.6115438938140869, 'perf', 0), ('benfred/py-spy', 0.5970548987388611, 'profiling', 1), ('brandtbucher/specialist', 0.5802419185638428, 'perf', 0), ('gotcha/ipdb', 0.5680873394012451, 'debug', 0), ('pympler/pympler', 0.5645143389701843, 'perf', 0), ('klen/py-frameworks-bench', 0.5635471343994141, 'perf', 0), ('python/cpython', 0.5600637197494507, 'util', 0), ('markshannon/faster-cpython', 0.5521705150604248, 'perf', 0), ('pyutils/line_profiler', 0.5507018566131592, 'profiling', 0), ('inducer/pudb', 0.5496501326560974, 'debug', 0), ('ipython/ipyparallel', 0.5462062954902649, 'perf', 0), ('alexmojaki/snoop', 0.5450026392936707, 'debug', 1), ('alexmojaki/heartrate', 0.5422681570053101, 'debug', 0), ('ionelmc/pytest-benchmark', 0.540304958820343, 'testing', 1), ('pytorch/data', 0.5269789695739746, 'data', 0), ('samuelcolvin/python-devtools', 0.523003876209259, 'debug', 0), ('sumerc/yappi', 0.5229708552360535, 'profiling', 1), ('pypy/pypy', 0.5207717418670654, 'util', 0), ('cython/cython', 0.5145069360733032, 'util', 1), ('lcompilers/lpython', 0.5144882798194885, 'util', 0), ('fchollet/deep-learning-with-python-notebooks', 0.5097584128379822, 'study', 0), ('pythonspeed/filprofiler', 0.5042270421981812, 'profiling', 0), ('facebookincubator/cinder', 0.5041605830192566, 'perf', 0), ('asweigart/pyperclip', 0.5013977885246277, 'util', 0)]

7

4

null

1.19

2

0

65

3

2

5

2

7

90

3.5

37

612

testing

https://github.com/pytest-dev/pytest-bdd

[]

null

[]

null

pytest-dev/pytest-bdd

pytest-bdd

1,239

210

57

Python

https://pytest-bdd.readthedocs.io/en/latest/

BDD library for the py.test runner

pytest-dev

2024-01-13

2013-03-29

565

2.190705

https://avatars.githubusercontent.com/u/8897583?v=4

BDD library for the py.test runner

[]

2023-12-02

[('behave/behave', 0.6536642909049988, 'testing', 0), ('nedbat/coveragepy', 0.6206257939338684, 'testing', 0), ('pmorissette/bt', 0.5979208946228027, 'finance', 0), ('ionelmc/pytest-benchmark', 0.5788668394088745, 'testing', 0), ('wolever/parameterized', 0.5707379579544067, 'testing', 0), ('libtcod/python-tcod', 0.5265241265296936, 'gamedev', 0), ('microsoft/playwright-python', 0.5180904865264893, 'testing', 0), ('pytoolz/toolz', 0.5150437355041504, 'util', 0), ('teemu/pytest-sugar', 0.5115352869033813, 'testing', 0), ('pyodide/pyodide', 0.5067077279090881, 'util', 0), ('alexmojaki/snoop', 0.5047500133514404, 'debug', 0)]

60

3

null

1.1

33

14

131

1

0

9

33

37

90

1.1

37

791

data

https://github.com/jsonpickle/jsonpickle

[]

null

[]

null

jsonpickle/jsonpickle

jsonpickle

1,180

163

34

Python

https://jsonpickle.readthedocs.io/en/latest/

Python library for serializing any arbitrary object graph into JSON. It can take almost any Python object and turn the object into JSON. Additionally, it can reconstitute the object back into Python.

jsonpickle

2024-01-13

2009-12-10

737

1.599535

https://avatars.githubusercontent.com/u/165337?v=4

Python library for serializing any arbitrary object graph into JSON. It can take almost any Python object and turn the object into JSON. Additionally, it can reconstitute the object back into Python.

['bsd-3-clause', 'deserialization', 'json', 'objectstorage', 'pickle', 'serialization']

2023-12-03

[('marshmallow-code/marshmallow', 0.6203814744949341, 'util', 2), ('python-odin/odin', 0.6082868576049805, 'util', 1), ('uqfoundation/dill', 0.601097047328949, 'data', 0), ('brokenloop/jsontopydantic', 0.5869114398956299, 'util', 0), ('yukinarit/pyserde', 0.5483598113059998, 'util', 2), ('strawberry-graphql/strawberry', 0.5452963709831238, 'web', 0), ('graphistry/pygraphistry', 0.535290539264679, 'data', 0), ('tiangolo/sqlmodel', 0.5255077481269836, 'data', 1), ('lidatong/dataclasses-json', 0.5186536908149719, 'util', 1), ('plotly/plotly.py', 0.5167441964149475, 'viz', 0), ('lk-geimfari/mimesis', 0.5048171281814575, 'data', 1), ('scikit-hep/awkward-1.0', 0.500355064868927, 'data', 1)]

73

6

null

0.67

11

5

172

1

0

3

11

24

90

2.2

37

1,222

testing

https://github.com/ionelmc/pytest-benchmark

[]

null

[]

null

ionelmc/pytest-benchmark

pytest-benchmark

1,158

115

19

Python

null

py.test fixture for benchmarking code

ionelmc

2024-01-12

2014-10-10

485

2.384819

null

py.test fixture for benchmarking code

['benchmark', 'benchmarking', 'performance', 'pytest']

2023-12-15

[('klen/py-frameworks-bench', 0.6951150298118591, 'perf', 1), ('pytest-dev/pytest', 0.6786613464355469, 'testing', 0), ('samuelcolvin/dirty-equals', 0.6507035493850708, 'util', 1), ('locustio/locust', 0.6405083537101746, 'testing', 2), ('teemu/pytest-sugar', 0.6360356211662292, 'testing', 1), ('pytest-dev/pytest-mock', 0.6237248182296753, 'testing', 1), ('nedbat/coveragepy', 0.6183704733848572, 'testing', 0), ('pytest-dev/pytest-xdist', 0.613385796546936, 'testing', 1), ('pmorissette/bt', 0.6115341186523438, 'finance', 0), ('computationalmodelling/nbval', 0.6038401126861572, 'jupyter', 1), ('wolever/parameterized', 0.6030191779136658, 'testing', 0), ('taverntesting/tavern', 0.5957930684089661, 'testing', 1), ('pytest-dev/pytest-bdd', 0.5788668394088745, 'testing', 0), ('pytest-dev/pytest-asyncio', 0.5777239203453064, 'testing', 0), ('pympler/pympler', 0.5586925148963928, 'perf', 0), ('rubik/radon', 0.554404079914093, 'util', 0), ('pyutils/line_profiler', 0.5505008101463318, 'profiling', 0), ('nteract/testbook', 0.5495516061782837, 'jupyter', 1), ('pypy/pypy', 0.5463877320289612, 'util', 0), ('samuelcolvin/pytest-pretty', 0.5456304550170898, 'testing', 1), ('spulec/freezegun', 0.5428466200828552, 'testing', 0), ('p403n1x87/austin', 0.540304958820343, 'profiling', 1), ('mrdbourke/m1-machine-learning-test', 0.5336135625839233, 'ml', 0), ('kiwicom/pytest-recording', 0.5216888785362244, 'testing', 1), ('alexmojaki/snoop', 0.5151593685150146, 'debug', 0), ('eugeneyan/python-collab-template', 0.5136798024177551, 'template', 0), ('getsentry/responses', 0.5085520148277283, 'testing', 0), ('pytest-dev/pytest-cov', 0.5074380040168762, 'testing', 1), ('benfred/py-spy', 0.5037754774093628, 'profiling', 0)]

41

6

null

0.29

11

6

113

1

0

2

11

20

90

1.8

37

442

gis

https://github.com/toblerity/fiona

[]

null

[]

null

toblerity/fiona

Fiona

1,096

209

47

Python

https://fiona.readthedocs.io/

Fiona reads and writes geographic data files

toblerity

2024-01-10

2011-12-31

630

1.7385

https://avatars.githubusercontent.com/u/859968?v=4

Fiona reads and writes geographic data files

['cli', 'cython', 'gdal', 'gis', 'ogr', 'vector']

2023-12-17

[('rasterio/rasterio', 0.5375838279724121, 'gis', 4)]

72

3

null

2.04

23

18

147

1

8

10

8

23

33

90

1.4

37

1,467

term

https://github.com/1j01/textual-paint

[]

null

[]

null

1j01/textual-paint

textual-paint

861

10

4

Python

https://pypi.org/project/textual-paint/

:art: MS Paint in your terminal.

1j01

2024-01-12

2023-04-10

42

20.430508

null

:art: MS Paint in your terminal.

['ansi-art', 'ansi-editor', 'artscene', 'ascii-art', 'bbs', 'drawing', 'image', 'image-editor', 'irc', 'mirc', 'mspaint', 'paint', 'pixel-art', 'pixel-editor', 'terminal', 'text-art', 'textual', 'tui']

2024-01-12

[('borisdayma/dalle-mini', 0.510983943939209, 'diffusion', 0)]

1

0

null

28.81

0

9

0

5

0

90

0

37

1,735

viz

https://github.com/pygraphviz/pygraphviz

[]

null

[]

null

pygraphviz/pygraphviz

pygraphviz

717

200

36

C

https://pygraphviz.github.io/

Python interface to Graphviz graph drawing package

pygraphviz

2024-01-08

2013-08-02

547

1.309418

https://avatars.githubusercontent.com/u/5148488?v=4

Python interface to Graphviz graph drawing package

['complex-networks', 'graph-visualization', 'spec-0']

2024-01-08

[('westhealth/pyvis', 0.7577512264251709, 'graph', 0), ('pydot/pydot', 0.7296152114868164, 'viz', 0), ('networkx/networkx', 0.6983128786087036, 'graph', 3), ('graphistry/pygraphistry', 0.678774356842041, 'data', 1), ('plotly/plotly.py', 0.6489458680152893, 'viz', 0), ('artelys/geonetworkx', 0.5921590328216553, 'gis', 0), ('dmlc/dgl', 0.5841652154922485, 'ml-dl', 0), ('h4kor/graph-force', 0.571456253528595, 'graph', 0), ('graphql-python/graphene', 0.5481510162353516, 'web', 0), ('matplotlib/matplotlib', 0.5422382354736328, 'viz', 0), ('holoviz/hvplot', 0.5362616181373596, 'pandas', 0), ('vizzuhq/ipyvizzu', 0.5348131060600281, 'jupyter', 0), ('holoviz/holoviz', 0.5206543207168579, 'viz', 0), ('has2k1/plotnine', 0.5177363753318787, 'viz', 0), ('holoviz/panel', 0.5157747268676758, 'viz', 0), ('cuemacro/chartpy', 0.5139192342758179, 'viz', 0), ('bokeh/bokeh', 0.5085844993591309, 'viz', 0), ('altair-viz/altair', 0.5070845484733582, 'viz', 0), ('pyg-team/pytorch_geometric', 0.502930760383606, 'ml-dl', 0), ('stellargraph/stellargraph', 0.5024316310882568, 'graph', 0), ('kuanb/peartree', 0.5017895698547363, 'gis', 0), ('pyvista/pyvista', 0.5015963315963745, 'viz', 0), ('vmiklos/ged2dot', 0.5002699494361877, 'data', 0)]

53

5

null

1.04

34

23

127

0

3

2

3

34

59

90

1.7

37

1,704

util

https://github.com/mtkennerly/poetry-dynamic-versioning

['poetry']

null

[]

null

mtkennerly/poetry-dynamic-versioning

poetry-dynamic-versioning

530

33

4

Python

null

Plugin for Poetry to enable dynamic versioning based on VCS tags

mtkennerly

2024-01-13

2019-06-06

242

2.183637

null

Plugin for Poetry to enable dynamic versioning based on VCS tags

['bazaar', 'darcs', 'dynamic-version', 'fossil', 'fossil-scm', 'git', 'mercurial', 'pijul', 'plugin', 'poetry', 'semantic-versioning', 'subversion', 'versioning']

2024-01-03

[('mtkennerly/dunamai', 0.7415024042129517, 'util', 11), ('tiangolo/poetry-version-plugin', 0.6403163075447083, 'util', 0), ('pypa/setuptools_scm', 0.6003091931343079, 'util', 2), ('python-versioneer/python-versioneer', 0.5653854012489319, 'util', 0), ('callowayproject/bump-my-version', 0.5595990419387817, 'util', 1), ('python-poetry/install.python-poetry.org', 0.5113168358802795, 'util', 1)]

13

3

null

1.1

13

12

56

0

11

13

11

13

34

90

2.6

37

1,861

sim

https://github.com/nvidia-omniverse/omniisaacgymenvs

['robot-learning']

null

[]

null

nvidia-omniverse/omniisaacgymenvs

OmniIsaacGymEnvs

518

141

16

Python

null

Reinforcement Learning Environments for Omniverse Isaac Gym

nvidia-omniverse

2024-01-14

2022-06-01

86

5.963816

https://avatars.githubusercontent.com/u/57824658?v=4

Reinforcement Learning Environments for Omniverse Isaac Gym

[]

['robot-learning']

2023-12-08

[('nvidia-omniverse/isaacgymenvs', 0.8064512610435486, 'sim', 0), ('nvidia-omniverse/orbit', 0.6811214685440063, 'sim', 1), ('humancompatibleai/imitation', 0.6052762866020203, 'ml-rl', 0), ('farama-foundation/gymnasium', 0.6047082543373108, 'ml-rl', 0), ('arise-initiative/robosuite', 0.5800082087516785, 'ml-rl', 1), ('openai/baselines', 0.5605931282043457, 'ml-rl', 0), ('inspirai/timechamber', 0.5575793981552124, 'sim', 0), ('pettingzoo-team/pettingzoo', 0.5554696917533875, 'ml-rl', 0), ('pytorch/rl', 0.5446157455444336, 'ml-rl', 0), ('unity-technologies/ml-agents', 0.5333084464073181, 'ml-rl', 0), ('kzl/decision-transformer', 0.5326739549636841, 'ml-rl', 0), ('thu-ml/tianshou', 0.5271867513656616, 'ml-rl', 0), ('shangtongzhang/reinforcement-learning-an-introduction', 0.5251854062080383, 'study', 0), ('facebookresearch/habitat-lab', 0.5088497400283813, 'sim', 0), ('google/dopamine', 0.5081252455711365, 'ml-rl', 0)]

6

1

null

1.4

59

17

20

1

0

4

59

151

90

2.6

37

1,527

llm

https://github.com/vahe1994/spqr

['falcon', 'llama', 'quantization', 'compression']

Quantization algorithm and the model evaluation code for SpQR method for LLM compression

[]

null

vahe1994/spqr

SpQR

475

39

22

Python

null

vahe1994

2024-01-12

2023-06-05

34

13.912134

null

Quantization algorithm and the model evaluation code for SpQR method for LLM compression

[]

['compression', 'falcon', 'llama', 'quantization']

2023-11-13

[('opengvlab/omniquant', 0.6055932641029358, 'llm', 1), ('artidoro/qlora', 0.5260251760482788, 'llm', 0)]

8

5

null

0.52

8

4

7

2

0

8

5

90

0.6

37

556

gis

https://github.com/corteva/rioxarray

[]

null

[]

null

corteva/rioxarray

rioxarray

455

69

16

Python

https://corteva.github.io/rioxarray

geospatial xarray extension powered by rasterio

corteva

2024-01-09

2019-04-16

250

1.82

https://avatars.githubusercontent.com/u/39543515?v=4

geospatial xarray extension powered by rasterio

['gdal', 'geospatial', 'gis', 'netcdf', 'raster', 'rasterio', 'xarray']

2023-12-29

[('osgeo/gdal', 0.5278557538986206, 'gis', 1), ('rasterio/rasterio', 0.5225644707679749, 'gis', 3), ('makepath/xarray-spatial', 0.511622428894043, 'gis', 1), ('cogeotiff/rio-tiler', 0.5002418756484985, 'gis', 3)]

33

7

null

1

30

12

58

0

4

14

4

30

37

90

1.2

37

1,700

template

https://github.com/asacristani/fastapi-rocket-boilerplate

[]

null

[]

null

asacristani/fastapi-rocket-boilerplate

fastapi-rocket-boilerplate

370

56

6

Python

null

🐍💨 FastAPI Rocket Boilerplate to build an API based in Python with its most modern technologies!

asacristani

2024-01-10

2023-09-20

18

19.621212

null

🐍💨 FastAPI Rocket Boilerplate to build an API based in Python with its most modern technologies!

['boilerplate', 'boilerplate-backend', 'fastapi']

2023-10-16

[('tiangolo/fastapi', 0.7025260925292969, 'web', 1), ('fastai/fastcore', 0.6752527952194214, 'util', 0), ('rawheel/fastapi-boilerplate', 0.6740272045135498, 'web', 2), ('s3rius/fastapi-template', 0.6634681224822998, 'web', 1), ('vitalik/django-ninja', 0.6605289578437805, 'web', 0), ('dmontagu/fastapi_client', 0.6545476913452148, 'web', 0), ('koxudaxi/fastapi-code-generator', 0.607068657875061, 'web', 1), ('starlite-api/starlite', 0.5981463193893433, 'web', 0), ('hugapi/hug', 0.5935749411582947, 'util', 0), ('python-restx/flask-restx', 0.5854663848876953, 'web', 0), ('tiangolo/full-stack-fastapi-postgresql', 0.5566263198852539, 'template', 1), ('falconry/falcon', 0.5512214303016663, 'web', 0), ('lk-geimfari/mimesis', 0.5495461225509644, 'data', 0), ('janetech-inc/fast-api-admin-template', 0.5484818816184998, 'template', 0), ('awtkns/fastapi-crudrouter', 0.5432131886482239, 'web', 1), ('fastapi-users/fastapi-users', 0.5379810333251953, 'web', 1), ('willmcgugan/textual', 0.5363441109657288, 'term', 0), ('pyston/pyston', 0.5267325639724731, 'util', 0), ('kubeflow/fairing', 0.5263985991477966, 'ml-ops', 0), ('ml-tooling/opyrator', 0.5223199725151062, 'viz', 1), ('zhanymkanov/fastapi-best-practices', 0.5217467546463013, 'study', 1), ('alirn76/panther', 0.5177244544029236, 'web', 0), ('pypy/pypy', 0.508145809173584, 'util', 0), ('airtai/faststream', 0.5075085759162903, 'perf', 0), ('urwid/urwid', 0.5037996172904968, 'term', 0), ('pdoc3/pdoc', 0.502884566783905, 'util', 0), ('pytoolz/toolz', 0.5019211769104004, 'util', 0), ('martinheinz/python-project-blueprint', 0.5014850497245789, 'template', 1)]

5

2

null

0.83

4

1

4

3

1

3

1

4

3

90

0.8

37

1,455

util

https://github.com/conda/conda-build

['conda']

null

[]

null

conda/conda-build

conda-build

356

403

51

Python

https://docs.conda.io/projects/conda-build/

Commands and tools for building conda packages

conda

2024-01-14

2014-01-17

523

0.679945

https://avatars.githubusercontent.com/u/6392739?v=4

Commands and tools for building conda packages

['conda', 'conda-build', 'package-management']

2024-01-10

[('conda/constructor', 0.8005626201629639, 'util', 1), ('mamba-org/boa', 0.7872036695480347, 'util', 1), ('mamba-org/quetz', 0.7619379758834839, 'util', 1), ('conda/conda-pack', 0.7299324870109558, 'util', 1), ('mamba-org/mamba', 0.6777679920196533, 'util', 1), ('mamba-org/gator', 0.6426661014556885, 'jupyter', 1), ('pypa/hatch', 0.5962553024291992, 'util', 0), ('conda/conda', 0.5913727283477783, 'util', 2), ('pomponchik/instld', 0.5880274772644043, 'util', 0), ('mamba-org/micromamba-docker', 0.5653933882713318, 'util', 1), ('conda-forge/feedstocks', 0.5539048314094543, 'util', 1), ('conda-forge/conda-smithy', 0.5523984432220459, 'util', 0), ('indygreg/pyoxidizer', 0.5000386834144592, 'util', 0)]

244

3

null

4.15

391

335

122

0

9

25

9

390

208

90

0.5

37

1,761

data

https://github.com/tconbeer/sqlfmt

['code-quality']

null

[]

1

null

tconbeer/sqlfmt

sqlfmt

307

11

3

Python

https://sqlfmt.com

sqlfmt formats your dbt SQL files so you don't have to

tconbeer

2024-01-11

2021-07-19

132

2.323243

null

sqlfmt formats your dbt SQL files so you don't have to

['dbt', 'formatter', 'sql']

['code-quality', 'dbt', 'formatter', 'sql']

2024-01-12

[('tconbeer/harlequin', 0.569164514541626, 'term', 1), ('databricks/dbt-databricks', 0.5048282146453857, 'data', 2)]

12

5

null

2.1

56

41

30

0

16

19

16

56

49

90

0.9

37

1,357

gis

https://github.com/raphaelquast/eomaps

[]

null

[]

null

raphaelquast/eomaps

EOmaps

284

20

5

Python

https://eomaps.readthedocs.io/

A library to create interactive maps of geographical datasets

raphaelquast

2024-01-13

2021-09-27

122

2.325146

null

A library to create interactive maps of geographical datasets

['cartopy', 'earth-observation', 'geospatial', 'gis', 'interactive-maps', 'interactive-visualization', 'mapping', 'matplotlib', 'plotting', 'visualization']

2023-12-20

[('residentmario/geoplot', 0.707546055316925, 'gis', 1), ('scitools/cartopy', 0.6839972138404846, 'gis', 2), ('opengeos/leafmap', 0.6778762936592102, 'gis', 3), ('holoviz/geoviews', 0.6664366126060486, 'gis', 2), ('giswqs/geemap', 0.6554696559906006, 'gis', 3), ('gregorhd/mapcompare', 0.625028669834137, 'gis', 0), ('geopandas/geopandas', 0.6084570288658142, 'gis', 2), ('marceloprates/prettymaps', 0.6013832688331604, 'viz', 1), ('visgl/deck.gl', 0.6003251075744629, 'viz', 1), ('artelys/geonetworkx', 0.585459291934967, 'gis', 0), ('bokeh/bokeh', 0.5836126804351807, 'viz', 2), ('plotly/plotly.py', 0.581186056137085, 'viz', 1), ('earthlab/earthpy', 0.5780810713768005, 'gis', 0), ('pyproj4/pyproj', 0.5670640468597412, 'gis', 1), ('domlysz/blendergis', 0.5599436163902283, 'gis', 2), ('scitools/iris', 0.5512466430664062, 'gis', 0), ('hazyresearch/meerkat', 0.543424129486084, 'viz', 0), ('python-visualization/folium', 0.5424359440803528, 'gis', 0), ('holoviz/holoviz', 0.5355204343795776, 'viz', 0), ('mwaskom/seaborn', 0.531478226184845, 'viz', 1), ('altair-viz/altair', 0.5242673754692078, 'viz', 1), ('nomic-ai/deepscatter', 0.5207083225250244, 'viz', 1), ('man-group/dtale', 0.5189169049263, 'viz', 1), ('imageio/imageio', 0.514751672744751, 'util', 0), ('pandas-dev/pandas', 0.5139701962471008, 'pandas', 0), ('isl-org/open3d', 0.5115019679069519, 'sim', 1), ('holoviz/panel', 0.5107569098472595, 'viz', 1), ('matplotlib/matplotlib', 0.5100708603858948, 'viz', 2), ('darribas/gds_env', 0.5032002329826355, 'gis', 0), ('fatiando/verde', 0.5024335384368896, 'gis', 1), ('holoviz/hvplot', 0.5002750754356384, 'pandas', 1)]

6

3

null

22.73

37

27

28

1

25

33

25

37

61

90

1.6

37

582

ml

https://github.com/merantix-momentum/squirrel-core

[]

null

[]

null

merantix-momentum/squirrel-core

squirrel-core

271

8

14

Python

https://squirrel-core.readthedocs.io/

A Python library that enables ML teams to share, load, and transform data in a collaborative, flexible, and efficient way :chestnut:

merantix-momentum

2024-01-05

2022-02-11

102

2.642061

https://avatars.githubusercontent.com/u/98414099?v=4

A Python library that enables ML teams to share, load, and transform data in a collaborative, flexible, and efficient way 🌰

['ai', 'cloud-computing', 'collaboration', 'computer-vision', 'cv', 'data-ingestion', 'data-mesh', 'data-science', 'dataops', 'datasets', 'deep-learning', 'distributed', 'jax', 'machine-learning', 'ml', 'natural-language-processing', 'nlp', 'pytorch', 'tensorflow']

2024-01-04

[('eventual-inc/daft', 0.6807416081428528, 'pandas', 3), ('huggingface/datasets', 0.6653859615325928, 'nlp', 8), ('gradio-app/gradio', 0.6419711709022522, 'viz', 3), ('tensorflow/tensorflow', 0.6386204957962036, 'ml-dl', 5), ('mlflow/mlflow', 0.63669753074646, 'ml-ops', 3), ('kubeflow/fairing', 0.6223782300949097, 'ml-ops', 0), ('dylanhogg/awesome-python', 0.6165292263031006, 'study', 5), ('ray-project/ray', 0.6162523627281189, 'ml-ops', 6), ('polyaxon/polyaxon', 0.6144108772277832, 'ml-ops', 6), ('horovod/horovod', 0.6060230135917664, 'ml-ops', 4), ('wandb/client', 0.5987028479576111, 'ml', 7), ('featurelabs/featuretools', 0.5986401438713074, 'ml', 2), ('determined-ai/determined', 0.5961888432502747, 'ml-ops', 5), ('aws/sagemaker-python-sdk', 0.5961750149726868, 'ml', 3), ('polyaxon/datatile', 0.5911334156990051, 'pandas', 4), ('dagworks-inc/hamilton', 0.5907508730888367, 'ml-ops', 2), ('fmind/mlops-python-package', 0.5865539312362671, 'template', 2), ('huggingface/transformers', 0.5804790258407593, 'nlp', 7), ('uber/petastorm', 0.5779027938842773, 'data', 4), ('backtick-se/cowait', 0.5777786374092102, 'util', 1), ('fastai/fastcore', 0.572002649307251, 'util', 0), ('pycaret/pycaret', 0.5700594782829285, 'ml', 3), ('huggingface/huggingface_hub', 0.5627287030220032, 'ml', 4), ('krzjoa/awesome-python-data-science', 0.5624656081199646, 'study', 3), ('tensorlayer/tensorlayer', 0.5620189905166626, 'ml-rl', 2), ('onnx/onnx', 0.5616537928581238, 'ml', 5), ('googlecloudplatform/vertex-ai-samples', 0.5609938502311707, 'ml', 3), ('nevronai/metisfl', 0.560804009437561, 'ml', 2), ('firmai/industry-machine-learning', 0.5604248642921448, 'study', 2), ('netflix/metaflow', 0.560415506362915, 'ml-ops', 4), ('explosion/thinc', 0.5592201352119446, 'ml-dl', 8), ('ml-tooling/opyrator', 0.5560594797134399, 'viz', 1), ('rasbt/mlxtend', 0.5547300577163696, 'ml', 2), ('activeloopai/deeplake', 0.5520520210266113, 'ml-ops', 10), ('microsoft/nni', 0.5516149401664734, 'ml', 6), ('online-ml/river', 0.5505257248878479, 'ml', 2), ('adap/flower', 0.5503032803535461, 'ml-ops', 5), ('uber/fiber', 0.5499705672264099, 'data', 1), ('tensorflow/tensor2tensor', 0.5476986765861511, 'ml', 2), ('orchest/orchest', 0.5455144643783569, 'ml-ops', 2), ('bentoml/bentoml', 0.5453324913978577, 'ml-ops', 3), ('whylabs/whylogs', 0.5451236367225647, 'util', 3), ('microsoft/onnxruntime', 0.5414808392524719, 'ml', 4), ('keras-team/keras', 0.5407350659370422, 'ml-dl', 6), ('fugue-project/fugue', 0.5387210845947266, 'pandas', 2), ('eleutherai/pyfra', 0.53780198097229, 'ml', 0), ('airbnb/knowledge-repo', 0.537761390209198, 'data', 1), ('nvidia/deeplearningexamples', 0.5371223092079163, 'ml-dl', 5), ('epistasislab/tpot', 0.5355274081230164, 'ml', 2), ('ploomber/ploomber', 0.5347124338150024, 'ml-ops', 2), ('mage-ai/mage-ai', 0.5338592529296875, 'ml-ops', 2), ('falconry/falcon', 0.5313084721565247, 'web', 0), ('explosion/spacy', 0.5305957198143005, 'nlp', 6), ('pandas-dev/pandas', 0.5296874046325684, 'pandas', 1), ('flyteorg/flyte', 0.5294408798217773, 'ml-ops', 3), ('pytorch/rl', 0.527829647064209, 'ml-rl', 3), ('intel/intel-extension-for-pytorch', 0.5278235077857971, 'perf', 3), ('avaiga/taipy', 0.5268411636352539, 'data', 0), ('kestra-io/kestra', 0.5266260504722595, 'ml-ops', 0), ('lightly-ai/lightly', 0.5261020660400391, 'ml', 4), ('google-research/language', 0.5260434150695801, 'nlp', 2), ('jina-ai/jina', 0.5257314443588257, 'ml', 2), ('streamlit/streamlit', 0.5240601897239685, 'viz', 3), ('rasbt/machine-learning-book', 0.5238132476806641, 'study', 3), ('ashleve/lightning-hydra-template', 0.5204800367355347, 'util', 2), ('rasahq/rasa', 0.5163630247116089, 'llm', 3), ('kubeflow-kale/kale', 0.5156881809234619, 'ml-ops', 1), ('aimhubio/aim', 0.5153231024742126, 'ml-ops', 6), ('airbytehq/airbyte', 0.5148383975028992, 'data', 0), ('keras-team/autokeras', 0.5147408246994019, 'ml-dl', 3), ('dagster-io/dagster', 0.5139255523681641, 'ml-ops', 1), ('scikit-learn-contrib/imbalanced-learn', 0.5136831998825073, 'ml', 2), ('scikit-learn/scikit-learn', 0.5131182670593262, 'ml', 2), ('superduperdb/superduperdb', 0.5102357268333435, 'data', 3), ('keras-team/keras-nlp', 0.5084515810012817, 'nlp', 5), ('google/mediapipe', 0.5076141953468323, 'ml', 3), ('databrickslabs/dolly', 0.5068414807319641, 'llm', 0), ('google/tf-quant-finance', 0.5065999031066895, 'finance', 1), ('meltano/meltano', 0.506161093711853, 'ml-ops', 1), ('drivendata/cookiecutter-data-science', 0.5045228004455566, 'template', 3), ('willmcgugan/textual', 0.50379478931427, 'term', 0), ('agronholm/apscheduler', 0.5034119486808777, 'util', 0), ('tensorly/tensorly', 0.5030725002288818, 'ml-dl', 4), ('jovianml/opendatasets', 0.5021243095397949, 'data', 3), ('microsoft/deepspeed', 0.5016716122627258, 'ml-dl', 3), ('pytables/pytables', 0.5015002489089966, 'data', 0), ('apache/incubator-mxnet', 0.500947892665863, 'ml-dl', 0), ('reloadware/reloadium', 0.5004510283470154, 'profiling', 1), ('microsoft/flaml', 0.5003235340118408, 'ml', 4)]

16

6

null

0.4

33

30

23

0

7

10

7

33

42

90

1.3

37

1,458

util

https://github.com/mamba-org/micromamba-docker

[]

null

[]

null

mamba-org/micromamba-docker

micromamba-docker

232

41

11

Shell

null

Rapid builds of small Conda-based containers using micromamba.

mamba-org

2024-01-13

2021-01-22

157

1.472348

https://avatars.githubusercontent.com/u/66118895?v=4

Rapid builds of small Conda-based containers using micromamba.

['build', 'ci', 'conda', 'container', 'docker', 'dockerfile', 'environment', 'mamba', 'micromamba']

2024-01-11

[('mamba-org/boa', 0.6690220236778259, 'util', 2), ('conda/conda-build', 0.5653933882713318, 'util', 1), ('darribas/gds_env', 0.5356658697128296, 'gis', 1), ('mamba-org/quetz', 0.5259016752243042, 'util', 1)]

18

7

null

2.67

34

33

36

0

18

11

18

34

42

90

1.2

37

1,614

llm

https://github.com/tiger-ai-lab/mammoth

['instruction-tuning']

null

[]

null

tiger-ai-lab/mammoth

MAmmoTH

221

23

11

Jupyter Notebook

null

This repo contains the code and data for "MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning"

tiger-ai-lab

2024-01-12

2023-09-06

20

10.59589

https://avatars.githubusercontent.com/u/144196744?v=4

This repo contains the code and data for "MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning"

[]

['instruction-tuning']

2024-01-13

[('declare-lab/instruct-eval', 0.6364500522613525, 'llm', 0), ('yizhongw/self-instruct', 0.5941129922866821, 'llm', 1), ('tatsu-lab/stanford_alpaca', 0.5743323564529419, 'llm', 0), ('instruction-tuning-with-gpt-4/gpt-4-llm', 0.5739008784294128, 'llm', 1), ('hiyouga/llama-efficient-tuning', 0.5284292697906494, 'llm', 1), ('hiyouga/llama-factory', 0.5284292697906494, 'llm', 1)]

4

3

null

0.98

18

13

4

0

18

25

90

1.4

37

1,453

util

https://github.com/conda-forge/conda-smithy

[]

null

[]

null

conda-forge/conda-smithy

conda-smithy

140

173

25

Python

https://conda-forge.org/

The tool for managing conda-forge feedstocks.

conda-forge

2024-01-05

2015-04-11

459

0.304726

https://avatars.githubusercontent.com/u/11897326?v=4

The tool for managing conda-forge feedstocks.

['continuous-integration']

2024-01-11

[('conda-forge/feedstocks', 0.8073468208312988, 'util', 0), ('conda/conda-build', 0.5523984432220459, 'util', 0), ('conda/conda-pack', 0.5372809767723083, 'util', 0), ('mamba-org/quetz', 0.5191918015480042, 'util', 0), ('mamba-org/mamba', 0.5094754695892334, 'util', 0)]

112

3

null

6.65

61

48

107

0

19

24

19

61

174

90

2.9

37

101

nlp

https://github.com/clips/pattern

[]

null

[]

null

clips/pattern

pattern

8,609

1,600

544

Python

https://github.com/clips/pattern/wiki

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

clips

2024-01-13

2011-05-03

665

12.945865

https://avatars.githubusercontent.com/u/765924?v=4

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

['machine-learning', 'natural-language-processing', 'network-analysis', 'sentiment-analysis', 'web-mining', 'wordnet']

2020-04-25

[('alirezamika/autoscraper', 0.7112637758255005, 'data', 1), ('scrapy/scrapy', 0.667265772819519, 'data', 0), ('webpy/webpy', 0.6514905095100403, 'web', 0), ('rasbt/mlxtend', 0.6350256204605103, 'ml', 1), ('roniemartinez/dude', 0.6342862844467163, 'util', 0), ('sloria/textblob', 0.6183449029922485, 'nlp', 1), ('masoniteframework/masonite', 0.6094305515289307, 'web', 0), ('plotly/dash', 0.5705082416534424, 'viz', 0), ('nv7-github/googlesearch', 0.5700188279151917, 'util', 0), ('holoviz/panel', 0.5649107098579407, 'viz', 0), ('gradio-app/gradio', 0.5603600144386292, 'viz', 1), ('pallets/flask', 0.5583645105361938, 'web', 0), ('requests/toolbelt', 0.5543271899223328, 'util', 0), ('eleutherai/pyfra', 0.5541388988494873, 'ml', 0), ('explosion/spacy', 0.5512140989303589, 'nlp', 2), ('dylanhogg/awesome-python', 0.5490561723709106, 'study', 2), ('reflex-dev/reflex', 0.547705352306366, 'web', 0), ('1200wd/bitcoinlib', 0.5464682579040527, 'crypto', 0), ('ranaroussi/quantstats', 0.5454891324043274, 'finance', 0), ('binux/pyspider', 0.5396731495857239, 'data', 0), ('falconry/falcon', 0.5375832915306091, 'web', 0), ('googleapis/google-api-python-client', 0.5339103937149048, 'util', 0), ('online-ml/river', 0.5316668152809143, 'ml', 1), ('seleniumbase/seleniumbase', 0.5308951735496521, 'testing', 0), ('bottlepy/bottle', 0.5306470990180969, 'web', 0), ('eliasdabbas/advertools', 0.5270535349845886, 'data', 0), ('willmcgugan/textual', 0.5270101428031921, 'term', 0), ('scikit-learn/scikit-learn', 0.524055540561676, 'ml', 1), ('pemistahl/lingua-py', 0.5218809247016907, 'nlp', 1), ('krzjoa/awesome-python-data-science', 0.5186637043952942, 'study', 1), ('polyaxon/datatile', 0.5179307460784912, 'pandas', 0), ('gbeced/pyalgotrade', 0.5164464712142944, 'finance', 0), ('uberi/speech_recognition', 0.5162601470947266, 'ml', 0), ('goldmansachs/gs-quant', 0.5158860087394714, 'finance', 0), ('pylons/pyramid', 0.5145288705825806, 'web', 0), ('wesm/pydata-book', 0.5136392116546631, 'study', 0), ('klen/muffin', 0.5102404356002808, 'web', 0), ('quantconnect/lean', 0.5098506808280945, 'finance', 0), ('pytoolz/toolz', 0.5079754590988159, 'util', 0), ('pyodide/pyodide', 0.5079214572906494, 'util', 0), ('ta-lib/ta-lib-python', 0.5062140226364136, 'finance', 0), ('r0x0r/pywebview', 0.5047861933708191, 'gui', 0), ('pallets/werkzeug', 0.5018793344497681, 'web', 0), ('pandas-dev/pandas', 0.5012263655662537, 'pandas', 0), ('cherrypy/cherrypy', 0.500634491443634, 'web', 0), ('probml/pyprobml', 0.5005698204040527, 'ml', 1)]

30

6

null

0

2

0

155

45

0

2

1

90

0.5

36

137

nlp

https://github.com/ddangelov/top2vec

[]

null

[]

null

ddangelov/top2vec

Top2Vec

2,768

363

40

Python

null

Top2Vec learns jointly embedded topic, document and word vectors.

ddangelov

2024-01-13

2020-03-20

201

13.732105

null

Top2Vec learns jointly embedded topic, document and word vectors.

['bert', 'document-embedding', 'pre-trained-language-models', 'semantic-search', 'sentence-encoder', 'sentence-transformers', 'text-search', 'text-semantic-similarity', 'top2vec', 'topic-modeling', 'topic-modelling', 'topic-search', 'topic-vector', 'word-embeddings']

2023-11-16

[('sebischair/lbl2vec', 0.8003798723220825, 'nlp', 1), ('paddlepaddle/paddlenlp', 0.6133404970169067, 'llm', 1), ('neuml/txtai', 0.608359694480896, 'nlp', 1), ('maartengr/bertopic', 0.6046782732009888, 'nlp', 3), ('rare-technologies/gensim', 0.59908527135849, 'nlp', 2), ('muennighoff/sgpt', 0.5922024846076965, 'llm', 1), ('llmware-ai/llmware', 0.5913721323013306, 'llm', 2), ('jina-ai/clip-as-service', 0.5902553796768188, 'nlp', 1), ('jina-ai/finetuner', 0.587577760219574, 'ml', 1), ('plasticityai/magnitude', 0.584179162979126, 'nlp', 1), ('koaning/whatlies', 0.5833550095558167, 'nlp', 0), ('ukplab/sentence-transformers', 0.5732832551002502, 'nlp', 1), ('alibaba/easynlp', 0.5686218738555908, 'nlp', 1), ('amansrivastava17/embedding-as-service', 0.5621562600135803, 'nlp', 1), ('graykode/nlp-tutorial', 0.5482358932495117, 'study', 1), ('jonasgeiping/cramming', 0.5433996915817261, 'nlp', 0), ('extreme-bert/extreme-bert', 0.5432024598121643, 'llm', 1), ('jina-ai/vectordb', 0.5428557395935059, 'data', 0), ('deepset-ai/farm', 0.5399625897407532, 'nlp', 1), ('chroma-core/chroma', 0.5397540330886841, 'data', 0), ('intellabs/fastrag', 0.527250349521637, 'nlp', 2), ('ai21labs/in-context-ralm', 0.5187664031982422, 'llm', 0), ('qdrant/fastembed', 0.5031333565711975, 'ml', 0)]

2

0

null

0.54

11

3

46

2

7

11

7

90

0.6

36

685

ml-dl

https://github.com/nerdyrodent/vqgan-clip

[]

null

[]

null

nerdyrodent/vqgan-clip

VQGAN-CLIP

2,537

423

53

Python

null

Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

nerdyrodent

2024-01-12

2021-07-02

134

18.852442

null

Just playing with getting VQGAN+CLIP running locally, rather than having to use colab.

['text-to-image', 'text2image']

2022-10-02

[]

7

2

null

0

5

2

31

16

0

5

4

90

0.8

36

725

study

https://github.com/amanchadha/coursera-deep-learning-specialization

[]

null

[]

null

amanchadha/coursera-deep-learning-specialization

coursera-deep-learning-specialization

2,459

1,925

25

Jupyter Notebook

null

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

amanchadha

2024-01-13

2020-06-24

187

13.089734

null

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

['andrew-ng', 'andrew-ng-course', 'cnns', 'convolutional-neural-network', 'convolutional-neural-networks', 'coursera', 'coursera-assignment', 'coursera-machine-learning', 'coursera-specialization', 'deep-learning', 'hyperparameter-optimization', 'hyperparameter-tuning', 'neural-machine-translation', 'neural-network', 'neural-networks', 'neural-style-transfer', 'recurrent-neural-network', 'recurrent-neural-networks', 'regularization', 'rnns']

2024-01-12

[('udacity/deep-learning-v2-pytorch', 0.6206496357917786, 'study', 2), ('alirezadir/machine-learning-interview-enlightener', 0.6021793484687805, 'study', 1), ('mrdbourke/tensorflow-deep-learning', 0.592336118221283, 'study', 1), ('mosaicml/composer', 0.5713127255439758, 'ml-dl', 3), ('explosion/thinc', 0.5682108998298645, 'ml-dl', 1), ('onnx/onnx', 0.5587916970252991, 'ml', 2), ('mrdbourke/zero-to-mastery-ml', 0.5553426742553711, 'study', 1), ('jindongwang/transferlearning', 0.5513812899589539, 'ml', 1), ('keras-team/keras', 0.5479432940483093, 'ml-dl', 2), ('rwightman/pytorch-image-models', 0.5459620952606201, 'ml-dl', 0), ('ddbourgin/numpy-ml', 0.5457329154014587, 'ml', 1), ('bentoml/bentoml', 0.540047824382782, 'ml-ops', 1), ('mrdbourke/pytorch-deep-learning', 0.5357545614242554, 'study', 1), ('nyandwi/modernconvnets', 0.5350536704063416, 'ml-dl', 3), ('christoschristofidis/awesome-deep-learning', 0.5327649116516113, 'study', 2), ('tensorlayer/tensorlayer', 0.5279957056045532, 'ml-rl', 2), ('keras-rl/keras-rl', 0.5269455909729004, 'ml-rl', 1), ('nvidia/deeplearningexamples', 0.5228648781776428, 'ml-dl', 1), ('alpa-projects/alpa', 0.5197420120239258, 'ml-dl', 1), ('thilinarajapakse/simpletransformers', 0.5146978497505188, 'nlp', 0), ('milvus-io/bootcamp', 0.5138573050498962, 'data', 1), ('lutzroeder/netron', 0.5117756128311157, 'ml', 2), ('tensorflow/tensorflow', 0.5084401369094849, 'ml-dl', 2), ('tensorflow/tensor2tensor', 0.5060564875602722, 'ml', 1), ('graykode/nlp-tutorial', 0.5051466226577759, 'study', 0), ('keras-team/autokeras', 0.5036728382110596, 'ml-dl', 1), ('huggingface/autotrain-advanced', 0.500561535358429, 'ml', 1)]

8

2

null

0.04

4

1

43

0

4

0

90

0

36

235

nlp

https://github.com/salesforce/codet5

[]

null

[]

null

salesforce/codet5

CodeT5

2,438

381

40

Python

https://arxiv.org/abs/2305.07922

Home of CodeT5: Open Code LLMs for Code Understanding and Generation

salesforce

2024-01-14

2021-08-16

128

19.025641

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

Home of CodeT5: Open Code LLMs for Code Understanding and Generation

['code-generation', 'code-intelligence', 'code-understanding', 'language-model', 'large-language-models']

2023-07-21

[('thudm/codegeex', 0.6897627115249634, 'llm', 1), ('salesforce/codegen', 0.6593608856201172, 'nlp', 0), ('ludwig-ai/ludwig', 0.6258037686347961, 'ml-ops', 0), ('alpha-vllm/llama2-accessory', 0.6213086843490601, 'llm', 0), ('salesforce/xgen', 0.6172817945480347, 'llm', 2), ('eugeneyan/open-llms', 0.6007983088493347, 'study', 1), ('nomic-ai/gpt4all', 0.5974037051200867, 'llm', 1), ('young-geng/easylm', 0.591428816318512, 'llm', 2), ('bigcode-project/starcoder', 0.5859589576721191, 'llm', 1), ('conceptofmind/toolformer', 0.5832077264785767, 'llm', 1), ('tigerlab-ai/tiger', 0.5818438529968262, 'llm', 1), ('hegelai/prompttools', 0.580586850643158, 'llm', 1), ('mooler0410/llmspracticalguide', 0.5782813429832458, 'study', 1), ('h2oai/h2o-llmstudio', 0.5726329684257507, 'llm', 0), ('argilla-io/argilla', 0.5648234486579895, 'nlp', 0), ('dylanhogg/llmgraph', 0.563266396522522, 'ml', 0), ('hwchase17/langchain', 0.5549836158752441, 'llm', 1), ('hiyouga/llama-factory', 0.5533753633499146, 'llm', 2), ('hiyouga/llama-efficient-tuning', 0.5533753037452698, 'llm', 2), ('lupantech/chameleon-llm', 0.551190972328186, 'llm', 1), ('citadel-ai/langcheck', 0.5499178171157837, 'llm', 1), ('eth-sri/lmql', 0.5481631755828857, 'llm', 1), ('nat/openplayground', 0.5432443022727966, 'llm', 1), ('microsoft/promptflow', 0.5427641868591309, 'llm', 0), ('bobazooba/xllm', 0.5426592826843262, 'llm', 1), ('agenta-ai/agenta', 0.5426530241966248, 'llm', 1), ('nebuly-ai/nebullvm', 0.5400938987731934, 'perf', 1), ('eleutherai/the-pile', 0.5400211811065674, 'data', 0), ('llmware-ai/llmware', 0.5333616733551025, 'llm', 1), ('shishirpatil/gorilla', 0.5298489332199097, 'llm', 0), ('juncongmoo/pyllama', 0.5293552875518799, 'llm', 0), ('bentoml/openllm', 0.5279268622398376, 'ml-ops', 0), ('next-gpt/next-gpt', 0.5271520614624023, 'llm', 1), ('intel/intel-extension-for-transformers', 0.5260124802589417, 'perf', 0), ('night-chen/toolqa', 0.525848388671875, 'llm', 1), ('thudm/chatglm2-6b', 0.524960994720459, 'llm', 1), ('facebookresearch/codellama', 0.5207399725914001, 'llm', 1), ('lianjiatech/belle', 0.5200687050819397, 'llm', 0), ('ibm/dromedary', 0.5191128253936768, 'llm', 1), ('modularml/mojo', 0.518414318561554, 'util', 0), ('confident-ai/deepeval', 0.5176749229431152, 'testing', 1), ('bigscience-workshop/petals', 0.5150795578956604, 'data', 1), ('embedchain/embedchain', 0.5125962495803833, 'llm', 0), ('ravenscroftj/turbopilot', 0.5119407773017883, 'llm', 1), ('numba/llvmlite', 0.5081905126571655, 'util', 0), ('openbmb/toolbench', 0.5070496201515198, 'llm', 0), ('openai/evals', 0.503447949886322, 'llm', 1), ('run-llama/llama-lab', 0.5031118392944336, 'llm', 1), ('li-plus/chatglm.cpp', 0.5017570853233337, 'llm', 1), ('lastmile-ai/aiconfig', 0.500541627407074, 'util', 0)]

3

1

null

0.44

14

3

29

6

0

14

9

90

0.6

36

1,326

util

https://github.com/scrapinghub/dateparser

['date', 'datetime', 'parsing']

null

[]

null

scrapinghub/dateparser

dateparser

2,408

462

134

Python

null

python parser for human readable dates

scrapinghub

2024-01-13

2014-11-24

479

5.025641

https://avatars.githubusercontent.com/u/699596?v=4

python parser for human readable dates

[]

['date', 'datetime', 'parsing']

2023-12-21

[('dateutil/dateutil', 0.7123557329177856, 'util', 2), ('sdispater/pendulum', 0.6702179908752441, 'util', 2), ('arrow-py/arrow', 0.5817139744758606, 'util', 2)]

133

0

null

0.62

30

15

111

1

3

30

33

90

1.1

36

1,815

study

https://github.com/mrdbourke/zero-to-mastery-ml

[]

null

[]

null

mrdbourke/zero-to-mastery-ml

zero-to-mastery-ml

2,378

3,146

124

Jupyter Notebook

https://dbourke.link/ZTMmlcourse

All course materials for the Zero to Mastery Machine Learning and Data Science course.

mrdbourke

2024-01-13

2019-09-23

227

10.469182

null

All course materials for the Zero to Mastery Machine Learning and Data Science course.

['data-science', 'deep-learning', 'machine-learning']

2023-11-16

[('mrdbourke/tensorflow-deep-learning', 0.7862590551376343, 'study', 1), ('mrdbourke/pytorch-deep-learning', 0.676668107509613, 'study', 2), ('firmai/industry-machine-learning', 0.5863468647003174, 'study', 2), ('patchy631/machine-learning', 0.5848323106765747, 'ml', 0), ('amanchadha/coursera-deep-learning-specialization', 0.5553426742553711, 'study', 1), ('udacity/deep-learning-v2-pytorch', 0.5445974469184875, 'study', 1), ('tensorlayer/tensorlayer', 0.5104413628578186, 'ml-rl', 1), ('d2l-ai/d2l-en', 0.5092582702636719, 'study', 3), ('tensorflow/tensorflow', 0.5074943900108337, 'ml-dl', 2), ('onnx/onnx', 0.5012384057044983, 'ml', 2)]

25

1

null

1.21

6

2

52

2

0

6

5

90

0.8

36

1,627

math

https://github.com/mckinsey/causalnex

['causation']

null

[]

null

mckinsey/causalnex

causalnex

2,070

242

46

Python

http://causalnex.readthedocs.io/

A Python library that helps data scientists to infer causation rather than observing correlation.

mckinsey

2024-01-12

2019-12-12

215

9.596026

https://avatars.githubusercontent.com/u/4265350?v=4

A Python library that helps data scientists to infer causation rather than observing correlation.

['bayesian-inference', 'bayesian-networks', 'causal-inference', 'causal-models', 'causal-networks', 'causalnex', 'data-science', 'machine-learning']

['bayesian-inference', 'bayesian-networks', 'causal-inference', 'causal-models', 'causal-networks', 'causalnex', 'causation', 'data-science', 'machine-learning']

2023-07-11

[('py-why/dowhy', 0.7358757853507996, 'ml', 5), ('willianfuks/tfcausalimpact', 0.6074860692024231, 'math', 1), ('py-why/econml', 0.5422161221504211, 'ml', 2), ('rasbt/mlxtend', 0.5194756984710693, 'ml', 2), ('carla-recourse/carla', 0.5116320252418518, 'ml', 1), ('teamhg-memex/eli5', 0.5101348161697388, 'ml', 2)]

35

3

null

0.37

7

0

50

6

4

5

4

7

1

90

0.1

36

1,505

study

https://github.com/cgpotts/cs224u

['nlp', 'nlu']

Code for CS224u: Natural Language Understanding

[]

null

cgpotts/cs224u

cs224u

2,020

861

85

Jupyter Notebook

null

Code for Stanford CS224u

cgpotts

2024-01-12

2015-01-30

469

4.301795

null

Code for Stanford CS224u

[]

['nlp', 'nlu']

2023-12-14

[('tatsu-lab/stanford_alpaca', 0.5506641268730164, 'llm', 0), ('lexpredict/lexpredict-lexnlp', 0.5473800897598267, 'nlp', 1), ('allenai/allennlp', 0.5052735805511475, 'nlp', 1)]

30

6

null

0.44

2

109

1

0

2

90

1

36

301

template

https://github.com/pyscaffold/pyscaffold

[]

null

[]

null

pyscaffold/pyscaffold

pyscaffold

1,941

177

39

Python

https://pyscaffold.org

🛠 Python project template generator with batteries included

pyscaffold

2024-01-13

2014-04-02

512

3.78468

https://avatars.githubusercontent.com/u/34571116?v=4

🛠 Python project template generator with batteries included

['distribution', 'git', 'package', 'package-creation', 'project-template', 'release-automation', 'template-project']

2023-06-20

[('eugeneyan/python-collab-template', 0.6021620631217957, 'template', 0), ('martinheinz/python-project-blueprint', 0.5791087746620178, 'template', 0), ('sqlalchemy/mako', 0.5707492828369141, 'template', 0), ('pypa/hatch', 0.5699118971824646, 'util', 0), ('tezromach/python-package-template', 0.553695797920227, 'template', 0), ('pdoc3/pdoc', 0.5431029796600342, 'util', 0), ('python-poetry/poetry', 0.5353856682777405, 'util', 0), ('pdm-project/pdm', 0.531360924243927, 'util', 0), ('pypa/flit', 0.5155603885650635, 'util', 0), ('indygreg/pyoxidizer', 0.5098890662193298, 'util', 0)]

58

6

null

1.12

6

0

119

7

3

20

3

6

90

1

36

382

llm

https://github.com/minimaxir/aitextgen

[]

null

[]

null

minimaxir/aitextgen

aitextgen

1,824

220

42

Python

https://docs.aitextgen.io

A robust Python tool for text-based AI training and generation using GPT-2.

minimaxir

2024-01-14

2019-12-29

213

8.551909

null

A robust Python tool for text-based AI training and generation using GPT-2.

[]

2023-05-17

[('minimaxir/gpt-2-simple', 0.7194006443023682, 'llm', 0), ('microsoft/pycodegpt', 0.6111297011375427, 'llm', 0), ('facebookresearch/parlai', 0.5751350522041321, 'nlp', 0), ('minimaxir/textgenrnn', 0.57369065284729, 'nlp', 0), ('huggingface/text-generation-inference', 0.563347339630127, 'llm', 0), ('databrickslabs/dolly', 0.5475108623504639, 'llm', 0), ('nvidia/nemo', 0.5452271699905396, 'nlp', 0), ('google/sentencepiece', 0.5358452796936035, 'nlp', 0), ('microsoft/generative-ai-for-beginners', 0.5282863974571228, 'study', 0), ('explosion/spacy', 0.5253174901008606, 'nlp', 0), ('nateshmbhat/pyttsx3', 0.5253090858459473, 'util', 0), ('sharonzhou/long_stable_diffusion', 0.5227047801017761, 'diffusion', 0), ('prefecthq/marvin', 0.5176252126693726, 'nlp', 0), ('bytedance/lightseq', 0.5134293437004089, 'nlp', 0), ('openlmlab/moss', 0.5120126008987427, 'llm', 0), ('torantulino/auto-gpt', 0.5113155841827393, 'llm', 0), ('minimaxir/simpleaichat', 0.507713258266449, 'llm', 0), ('google-research/electra', 0.5072848796844482, 'ml-dl', 0), ('killianlucas/open-interpreter', 0.5057147741317749, 'llm', 0), ('kagisearch/vectordb', 0.5047615766525269, 'data', 0), ('krohling/bondai', 0.5016161799430847, 'llm', 0), ('norskregnesentral/skweak', 0.5007104873657227, 'nlp', 0)]

11

4

null

0.04

3

0

49

8

0

3

90

1

36

364

ml

https://github.com/rentruewang/koila

[]

null

[]

null

rentruewang/koila

koila

1,804

64

11

Python

https://rentruewang.github.io/koila/

Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.

rentruewang

2024-01-12

2021-11-17

114

15.706468

null

Prevent PyTorch's `CUDA error: out of memory` in just 1 line of code.

['deep-learning', 'gradient-accumulation', 'lazy-evaluation', 'machine-learning', 'memory-management', 'neural-network', 'out-of-memory', 'pytorch']

2024-01-10

[('blackhc/toma', 0.6982141137123108, 'ml-dl', 2), ('intel/intel-extension-for-pytorch', 0.6254847645759583, 'perf', 4), ('pytorch/ignite', 0.6201809644699097, 'ml-dl', 4), ('nvidia/apex', 0.6033901572227478, 'ml-dl', 0), ('mrdbourke/pytorch-deep-learning', 0.5876379609107971, 'study', 3), ('arogozhnikov/einops', 0.5856212973594666, 'ml-dl', 2), ('skorch-dev/skorch', 0.5766161680221558, 'ml-dl', 2), ('rasbt/machine-learning-book', 0.5745282769203186, 'study', 3), ('pytorch/data', 0.5698388814926147, 'data', 0), ('cvxgrp/pymde', 0.5673205852508545, 'ml', 2), ('karpathy/micrograd', 0.5448654890060425, 'study', 0), ('huggingface/accelerate', 0.5446726083755493, 'ml', 0), ('timdettmers/bitsandbytes', 0.5362823009490967, 'util', 0), ('pyg-team/pytorch_geometric', 0.5282607674598694, 'ml-dl', 2), ('allenai/allennlp', 0.5262885689735413, 'nlp', 2), ('denys88/rl_games', 0.5238789916038513, 'ml-rl', 2), ('ashleve/lightning-hydra-template', 0.5227289199829102, 'util', 2), ('pytorch/pytorch', 0.5214821696281433, 'ml-dl', 3), ('pytorch/torchrec', 0.5190505385398865, 'ml-dl', 2), ('cupy/cupy', 0.5168486833572388, 'math', 0), ('pytorch/captum', 0.5131102800369263, 'ml-interpretability', 0), ('nicolas-chaulet/torch-points3d', 0.5067731738090515, 'ml', 0), ('nvidia/cuda-python', 0.5058760046958923, 'ml', 0)]

4

2

null

0.46

1

0

26

0

1

0

90

0

36

908

math

https://github.com/google-research/torchsde

[]

null

[]

null

google-research/torchsde

torchsde

1,415

178

34

Python

null

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

google-research

2024-01-12

2020-07-06

186

7.601688

https://avatars.githubusercontent.com/u/43830688?v=4

Differentiable SDE solvers with GPU support and efficient sensitivity analysis.

['deep-learning', 'deep-neural-networks', 'differential-equations', 'dynamical-systems', 'neural-differential-equations', 'pytorch', 'stochastic-differential-equations', 'stochastic-processes', 'stochastic-volatility-models']

2023-09-26

[('denys88/rl_games', 0.5168188810348511, 'ml-rl', 2), ('stability-ai/stability-sdk', 0.5064745545387268, 'diffusion', 0)]

8

4

null

0.12

5

4

43

4

1

2

1

5

6

90

1.2

36

1,214

crypto

https://github.com/binance/binance-public-data

[]

null

[]

null

binance/binance-public-data

binance-public-data

1,231

411

32

Python

null

Details on how to get Binance public data

binance

2024-01-13

2020-08-24

179

6.871611

https://avatars.githubusercontent.com/u/69836600?v=4

Details on how to get Binance public data

[]

2023-11-01

[]

20

3

null

0.15

51

38

41

2

0

51

48

90

0.9

36

949

web

https://github.com/long2ice/fastapi-cache

[]

null

[]

null

long2ice/fastapi-cache

fastapi-cache

974

119

9

Python

https://github.com/long2ice/fastapi-cache

fastapi-cache is a tool to cache fastapi response and function result, with backends support redis and memcached.

long2ice

2024-01-12

2020-08-25

179

5.441341

null

fastapi-cache is a tool to cache fastapi response and function result, with backends support redis and memcached.

['cache', 'fastapi', 'memcached', 'redis']

2023-12-07

[('aio-libs/aiocache', 0.6432105898857117, 'data', 3), ('grantjenks/python-diskcache', 0.6009683609008789, 'util', 1), ('dgilland/cacheout', 0.5193830728530884, 'perf', 0), ('zilliztech/gptcache', 0.506112813949585, 'llm', 1), ('python-cachier/cachier', 0.5056164860725403, 'perf', 1), ('dmontagu/fastapi_client', 0.5032126307487488, 'web', 0)]

26

1

null

2.75

65

38

41

1

3

1

65

43

90

0.7

36

482

gis

https://github.com/sentinelsat/sentinelsat

[]

null

[]

null

sentinelsat/sentinelsat

sentinelsat

943

239

62

Python

https://sentinelsat.readthedocs.io

Search and download Copernicus Sentinel satellite images

sentinelsat

2024-01-10

2015-05-22

453

2.079055

https://avatars.githubusercontent.com/u/29057552?v=4

Search and download Copernicus Sentinel satellite images

['copernicus', 'esa', 'geographic-data', 'open-data', 'remote-sensing', 'satellite-imagery', 'sentinel']

2023-11-08

[('plant99/felicette', 0.6691089272499084, 'gis', 1), ('giswqs/aws-open-data-geo', 0.6044768691062927, 'gis', 2), ('sentinel-hub/sentinelhub-py', 0.5519406199455261, 'gis', 1), ('developmentseed/label-maker', 0.5269395112991333, 'gis', 2), ('azavea/raster-vision', 0.5150529742240906, 'gis', 1), ('developmentseed/landsat-util', 0.5123438239097595, 'gis', 0)]

43

5

null

0.23

11

9

105

2

1

3

1

11

37

90

3.4

36

1,140

viz

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

[]

null

[]

null

nomic-ai/deepscatter

deepscatter

928

42

16

TypeScript

null

Zoomable, animated scatterplots in the browser that scales over a billion points

nomic-ai

2024-01-13

2018-10-30

274

3.386861

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

Zoomable, animated scatterplots in the browser that scales over a billion points

['data-visualization', 'visualization', 'webgl']

2024-01-10

[('visgl/deck.gl', 0.6989966630935669, 'viz', 3), ('holoviz/datashader', 0.6156784296035767, 'gis', 0), ('bokeh/bokeh', 0.594667911529541, 'viz', 1), ('mckinsey/vizro', 0.5346618294715881, 'viz', 2), ('altair-viz/altair', 0.5337156653404236, 'viz', 1), ('plotly/plotly.py', 0.5329233407974243, 'viz', 2), ('residentmario/geoplot', 0.5221992135047913, 'gis', 0), ('raphaelquast/eomaps', 0.5207083225250244, 'gis', 1), ('holoviz/holoviz', 0.5163466930389404, 'viz', 0), ('holoviz/hvplot', 0.511212944984436, 'pandas', 0), ('pyqtgraph/pyqtgraph', 0.5000237822532654, 'viz', 1)]

16

4

null

2.17

11

8

63

0

3

1

3

11

4

90

0.4

36

874

time-series

https://github.com/winedarksea/autots

[]

null

[]

null

winedarksea/autots

AutoTS

925

87

18

Python

null

Automated Time Series Forecasting

winedarksea

2024-01-13

2019-11-26

218

4.243119

null

Automated Time Series Forecasting

['automl', 'autots', 'deep-learning', 'feature-engineering', 'forecasting', 'machine-learning', 'preprocessing', 'time-series']

2024-01-03

[('awslabs/autogluon', 0.7558371424674988, 'ml', 5), ('sktime/sktime', 0.7021391987800598, 'time-series', 3), ('ourownstory/neural_prophet', 0.6846452355384827, 'ml', 4), ('salesforce/merlion', 0.682404637336731, 'time-series', 4), ('microsoft/nni', 0.6789240837097168, 'ml', 4), ('automl/auto-sklearn', 0.6762388944625854, 'ml', 1), ('firmai/atspy', 0.6719325184822083, 'time-series', 2), ('keras-team/autokeras', 0.6600058078765869, 'ml-dl', 3), ('microsoft/flaml', 0.6591876745223999, 'ml', 3), ('nccr-itmo/fedot', 0.6496773958206177, 'ml-ops', 2), ('xplainable/xplainable', 0.6385115385055542, 'ml-interpretability', 1), ('nixtla/statsforecast', 0.6360719799995422, 'time-series', 4), ('huggingface/autotrain-advanced', 0.6144011616706848, 'ml', 2), ('alkaline-ml/pmdarima', 0.6125960350036621, 'time-series', 3), ('mljar/mljar-supervised', 0.578948438167572, 'ml', 3), ('alpa-projects/alpa', 0.5752678513526917, 'ml-dl', 2), ('shankarpandala/lazypredict', 0.5729676485061646, 'ml', 2), ('salesforce/deeptime', 0.5623159408569336, 'time-series', 3), ('awslabs/gluonts', 0.5618434548377991, 'time-series', 4), ('aistream-peelout/flow-forecast', 0.557109534740448, 'time-series', 3), ('bentoml/bentoml', 0.5495694875717163, 'ml-ops', 2), ('torantulino/auto-gpt', 0.5468161702156067, 'llm', 0), ('autoviml/auto_ts', 0.5450201034545898, 'time-series', 2), ('featurelabs/featuretools', 0.5383171439170837, 'ml', 3), ('feast-dev/feast', 0.5365046262741089, 'ml-ops', 1), ('unit8co/darts', 0.5341631770133972, 'time-series', 4), ('alirezadir/machine-learning-interview-enlightener', 0.5339345335960388, 'study', 2), ('mosaicml/composer', 0.5297396183013916, 'ml-dl', 2), ('mindsdb/mindsdb', 0.5278527736663818, 'data', 2), ('facebook/prophet', 0.5207078456878662, 'time-series', 2), ('blue-yonder/tsfresh', 0.5182939171791077, 'time-series', 1), ('onnx/onnx', 0.516512930393219, 'ml', 2), ('google/temporian', 0.5130333304405212, 'time-series', 2), ('google/pyglove', 0.5115013122558594, 'util', 2), ('ydataai/ydata-synthetic', 0.5098974704742432, 'data', 3), ('uber/orbit', 0.5088127255439758, 'time-series', 3), ('huggingface/datasets', 0.5051737427711487, 'nlp', 2)]

1

0

null

5.08

21

15

50

0

13

12

13

21

50

90

2.4

36

929

web

https://github.com/koxudaxi/fastapi-code-generator

[]

null

[]

null

koxudaxi/fastapi-code-generator

fastapi-code-generator

862

92

20

Python

null

This code generator creates FastAPI app from an openapi file.

koxudaxi

2024-01-12

2020-06-14

189

4.553962

null

This code generator creates FastAPI app from an openapi file.

['fastapi', 'generator', 'openapi', 'pydantic']

2023-09-07

[('dmontagu/fastapi_client', 0.6843157410621643, 'web', 0), ('asacristani/fastapi-rocket-boilerplate', 0.607068657875061, 'template', 1), ('kuimono/openapi-schema-pydantic', 0.6038326025009155, 'util', 1)]

24

3

null

1.21

16

8

44

4

5

11

5

16

18

90

1.1

36

842

util

https://github.com/wolph/python-progressbar

[]

null

[]

null

wolph/python-progressbar

python-progressbar

831

141

22

Python

http://progressbar-2.readthedocs.org/en/latest/

Progressbar 2 - A progress bar for Python 2 and Python 3 - "pip install progressbar2"

wolph

2024-01-10

2012-02-20

623

1.333563

null

Progressbar 2 - A progress bar for Python 2 and Python 3 - "pip install progressbar2"

['bar', 'cli', 'console', 'eta', 'gui', 'percentage', 'progress', 'progress-bar', 'progressbar', 'rate', 'terminal', 'time']

2024-01-02

[('tqdm/tqdm', 0.7864949107170105, 'term', 9), ('rockhopper-technologies/enlighten', 0.7673426270484924, 'term', 0), ('rsalmei/alive-progress', 0.6114795207977295, 'util', 7), ('hugovk/pypistats', 0.5268552303314209, 'util', 1)]

46

3

null

0.96

13

9

145

0

3

9

3

13

38

90

2.9

36

1,500

ml-dl

https://github.com/deepmind/chex

['numpy', 'testing', 'autograd', 'jax']

Chex is a library of utilities for helping to write reliable JAX code

[]

null

deepmind/chex

chex

667

40

18

Python

https://chex.readthedocs.io

null

deepmind

2024-01-13

2020-08-06

181

3.670597

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

Chex is a library of utilities for helping to write reliable JAX code

[]

['autograd', 'jax', 'numpy', 'testing']

2023-12-09

[('google/flax', 0.5962191820144653, 'ml-dl', 1), ('deepmind/dm-haiku', 0.5875384211540222, 'ml-dl', 1), ('deepmind/synjax', 0.5291113257408142, 'math', 1), ('samuelcolvin/rtoml', 0.5042668581008911, 'data', 0)]

40

4

null

1.33

18

11

42

1

7

6

7

18

8

90

0.4

36

1,497

util

https://github.com/instagram/fixit

['linter']

null

[]

null

instagram/fixit

Fixit

633

57

26

Python

https://fixit.rtfd.io/en/latest/

Advanced Python linting framework with auto-fixes and hierarchical configuration that makes it easy to write custom in-repo lint rules.

instagram

2024-01-14

2020-02-20

205

3.077083

https://avatars.githubusercontent.com/u/549085?v=4

Advanced Python linting framework with auto-fixes and hierarchical configuration that makes it easy to write custom in-repo lint rules.

[]

['linter']

2023-12-21

[('python-rope/rope', 0.5731984972953796, 'util', 0), ('pycqa/pyflakes', 0.5664411783218384, 'util', 1), ('python/mypy', 0.5660220384597778, 'typing', 1), ('grahamdumpleton/wrapt', 0.5495676398277283, 'util', 0), ('klen/pylama', 0.5459169745445251, 'util', 1), ('landscapeio/prospector', 0.5204662084579468, 'util', 0), ('eugeneyan/python-collab-template', 0.5144226551055908, 'template', 0), ('pytoolz/toolz', 0.5103968977928162, 'util', 0), ('asottile/reorder-python-imports', 0.5014389753341675, 'util', 1)]

41

4

null

2.12

37

22

47

1

0

3

37

28

90

0.8

36

1,144

util

https://github.com/terrycain/aioboto3

[]

null

[]

null

terrycain/aioboto3

aioboto3

608

63

8

Python

null

Wrapper to use boto3 resources with the aiobotocore async backend

terrycain

2024-01-12

2017-09-25

331

1.836066

null

Wrapper to use boto3 resources with the aiobotocore async backend

['async', 'aws', 'boto3']

2023-12-08

[('aio-libs/aiobotocore', 0.6956399083137512, 'util', 1), ('geeogi/async-python-lambda-template', 0.5498723387718201, 'template', 0), ('samuelcolvin/aioaws', 0.5090085864067078, 'data', 1)]

27

4

null

0.37

14

10

77

1

0

10

14

29

90

2.1

36

358

ml-ops

https://github.com/google/ml-metadata

[]

null

[]

null

google/ml-metadata

ml-metadata

577

134

29

C++

https://www.tensorflow.org/tfx/guide/mlmd

For recording and retrieving metadata associated with ML developer and data scientist workflows.

google

2024-01-10

2019-01-15

263

2.193916

https://avatars.githubusercontent.com/u/1342004?v=4

For recording and retrieving metadata associated with ML developer and data scientist workflows.

[]

2024-01-12

[('astronomer/astro-sdk', 0.5482959747314453, 'ml-ops', 0), ('whylabs/whylogs', 0.5445284247398376, 'util', 0), ('ploomber/ploomber', 0.5324745774269104, 'ml-ops', 0), ('airbnb/knowledge-repo', 0.5292649865150452, 'data', 0), ('hyperqueryhq/whale', 0.5290652513504028, 'data', 0), ('dagworks-inc/hamilton', 0.5270819664001465, 'ml-ops', 0), ('mage-ai/mage-ai', 0.524271547794342, 'ml-ops', 0), ('great-expectations/great_expectations', 0.5165597200393677, 'ml-ops', 0), ('simonw/datasette', 0.5161576271057129, 'data', 0), ('netflix/metaflow', 0.5132206082344055, 'ml-ops', 0), ('intake/intake', 0.506055474281311, 'data', 0), ('linealabs/lineapy', 0.5038784146308899, 'jupyter', 0), ('dbt-labs/dbt-core', 0.5018987655639648, 'ml-ops', 0), ('iterative/dvc', 0.5009445548057556, 'ml-ops', 0)]

19

2

null

1.1

12

1

61

0

3

7

3

12

53

90

4.4

36

1,569

ml

https://github.com/nicolas-hbt/pygraft

['knowledge-graph', 'ontology-generation']

null

[]

1

null

nicolas-hbt/pygraft

pygraft

551

36

12

Python

https://pygraft.readthedocs.io/en/latest/

Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips

nicolas-hbt

2024-01-12

2023-09-07

20

26.6

null

Configurable Generation of Synthetic Schemas and Knowledge Graphs at Your Fingertips

['artificial-intelligence', 'benchmarking', 'contributions-welcome', 'data-generator', 'graph-generator', 'knowledge-base', 'knowledge-graph', 'linked-data', 'machine-learning', 'ontology', 'ontology-generation', 'owl', 'rdf', 'rdfs', 'schema', 'semantic-web', 'semantics', 'synthetic-data', 'synthetic-dataset-generation']

2023-12-01

[('sdv-dev/sdv', 0.6006342172622681, 'data', 2), ('mindsdb/mindsdb', 0.5319455862045288, 'data', 2), ('dylanhogg/llmgraph', 0.5217655897140503, 'ml', 1), ('ydataai/ydata-synthetic', 0.5071893334388733, 'data', 2), ('strawberry-graphql/strawberry', 0.5039038062095642, 'web', 0)]

1

null

0.75

1

0

4

1

0

1

90

1

36

1,247

util

https://github.com/steamship-core/steamship-langchain

[]

null

[]

null

steamship-core/steamship-langchain

steamship-langchain

499

98

12

Python

null

steamship-langchain

steamship-core

2024-01-12

2023-02-04

51

9.702778

https://avatars.githubusercontent.com/u/99272373?v=4

steamship-langchain

[]

2023-09-12

[('steamship-core/python-client', 0.5675639510154724, 'util', 0)]

7

2

null

2.23

1

0

11

4

17

42

17

1

90

1

36

1,706

util

https://github.com/snok/install-poetry

['github', 'action']

null

[]

null

snok/install-poetry

install-poetry

491

46

6

Shell

null

Github action for installing and configuring Poetry

snok

2024-01-05

2020-10-25

170

2.883389

https://avatars.githubusercontent.com/u/64945977?v=4

Github action for installing and configuring Poetry

[]

['action', 'github']

2024-01-11

[('python-poetry/install.python-poetry.org', 0.6302388310432434, 'util', 0)]

22

5

null

0.44

15

11

39

0

1

8

1

15

27

90

1.8

36

1,612

llm

https://github.com/lupantech/scienceqa

['thought-chain']

null

[]

null

lupantech/scienceqa

ScienceQA

487

62

9

Python

null

Data and code for NeurIPS 2022 Paper "Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering".

lupantech

2024-01-13

2022-10-17

67

7.253191

null

Data and code for NeurIPS 2022 Paper "Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering".

[]

['thought-chain']

2023-12-30

[('kyegomez/tree-of-thoughts', 0.5537173748016357, 'llm', 0), ('noahshinn/reflexion', 0.5062936544418335, 'llm', 0)]

4

2

null

0.67

5

15

0

1

5

10

90

2

36

490

gis

https://github.com/cogeotiff/rio-tiler

[]

null

[]

null

cogeotiff/rio-tiler

rio-tiler

453

96

65

Python

https://cogeotiff.github.io/rio-tiler/

User friendly Rasterio plugin to read raster datasets.

cogeotiff

2024-01-11

2017-10-06

329

1.374512

https://avatars.githubusercontent.com/u/40065466?v=4

User friendly Rasterio plugin to read raster datasets.

['cog', 'cogeotiff', 'gdal', 'maptile', 'mercator', 'raster', 'raster-processing', 'rasterio', 'satellite', 'slippy-map', 'tile']

2024-01-12

[('rasterio/rasterio', 0.7036706209182739, 'gis', 2), ('cogeotiff/rio-cogeo', 0.6072856783866882, 'gis', 4), ('osgeo/gdal', 0.5156446099281311, 'gis', 1), ('corteva/rioxarray', 0.5002418756484985, 'gis', 3)]

26

4

null

1.38

20

15

76

0

24

20

29

90

1.4

36

855

ml-ops

https://github.com/astronomer/astronomer

[]

null

[]

null

astronomer/astronomer

astronomer

453

83

45

Python

https://www.astronomer.io

Helm Charts for the Astronomer Platform, Apache Airflow as a Service on Kubernetes

astronomer

2024-01-11

2018-01-15

315

1.437443

https://avatars.githubusercontent.com/u/12449437?v=4

Helm Charts for the Astronomer Platform, Apache Airflow as a Service on Kubernetes

['apache-airflow', 'astronomer-platform', 'docker', 'kubernetes']

2024-01-09

[('astronomer/airflow-chart', 0.8572540283203125, 'ml-ops', 2), ('anyscale/airflow-provider-ray', 0.5748955011367798, 'ml-ops', 0), ('apache/airflow', 0.5602481961250305, 'ml-ops', 1), ('gefyrahq/gefyra', 0.5323020815849304, 'util', 2)]

75

4

null

5.15

56

53

73

0

15

60

15

56

17

90

0.3

36

1,457

util

https://github.com/conda/constructor

['conda']

null

[]

null

conda/constructor

constructor

430

166

33

Python

https://conda.github.io/constructor/

tool for creating installers from conda packages

conda

2024-01-04

2016-02-12

415

1.03472

https://avatars.githubusercontent.com/u/6392739?v=4

tool for creating installers from conda packages

[]

['conda']

2024-01-13

[('conda/conda-build', 0.8005626201629639, 'util', 1), ('conda/conda-pack', 0.7213409543037415, 'util', 1), ('mamba-org/boa', 0.7149392366409302, 'util', 1), ('mamba-org/quetz', 0.7079612612724304, 'util', 1), ('mamba-org/gator', 0.5621293783187866, 'jupyter', 1), ('mamba-org/mamba', 0.5558754801750183, 'util', 1), ('pyodide/micropip', 0.5295533537864685, 'util', 0), ('ofek/pyapp', 0.5201569199562073, 'util', 0), ('conda-forge/feedstocks', 0.507718563079834, 'util', 1)]

70

6

null

1.56

57

47

96

0

8

6

8

57

33

90

0.6

36

713

gis

https://github.com/weecology/deepforest

[]

null

[]

null

weecology/deepforest

DeepForest

411

157

15

Python

https://deepforest.readthedocs.io/

Python Package for Airborne RGB machine learning

weecology

2024-01-10

2018-03-07

307

1.335035

https://avatars.githubusercontent.com/u/1156696?v=4

Python Package for Airborne RGB machine learning

[]

2023-12-27

[('sentinel-hub/eo-learn', 0.5667561888694763, 'gis', 0), ('mdbloice/augmentor', 0.5662134885787964, 'ml', 0), ('lightly-ai/lightly', 0.5572022199630737, 'ml', 0), ('pycaret/pycaret', 0.5376171469688416, 'ml', 0), ('earthlab/earthpy', 0.5284902453422546, 'gis', 0), ('radiantearth/radiant-mlhub', 0.5279979705810547, 'gis', 0), ('gradio-app/gradio', 0.525834858417511, 'viz', 0), ('azavea/raster-vision', 0.5204096436500549, 'gis', 0), ('facebookresearch/pytorch3d', 0.5166642069816589, 'ml-dl', 0), ('rasbt/machine-learning-book', 0.5097160339355469, 'study', 0), ('featurelabs/featuretools', 0.5066676139831543, 'ml', 0), ('rasbt/mlxtend', 0.5020350217819214, 'ml', 0)]

14

6

null

2.17

115

86

71

1

0

12

115

104

90

0.9

36

1,526

llm

https://github.com/operand/agency

[]

null

[]

null

operand/agency

agency

351

18

10

Python

https://createwith.agency

A fast and minimal framework for building agent-integrated systems

operand

2024-01-12

2023-05-23

36

9.75

null

A fast and minimal framework for building agent-integrated systems

['actor', 'actor-model', 'agent', 'agents', 'agi', 'ai', 'api', 'artificial-general-intelligence', 'artificial-intelligence', 'autonomous-agent', 'autonomous-agents', 'framework', 'llm', 'llmops', 'llms', 'machine-learning', 'minimal']

2024-01-12

[('prefecthq/marvin', 0.6231884956359863, 'nlp', 3), ('transformeroptimus/superagi', 0.6139060258865356, 'llm', 8), ('microsoft/lmops', 0.6131894588470459, 'llm', 2), ('geekan/metagpt', 0.6091906428337097, 'llm', 2), ('mlc-ai/mlc-llm', 0.6070036888122559, 'llm', 1), ('unity-technologies/ml-agents', 0.596383810043335, 'ml-rl', 1), ('mindsdb/mindsdb', 0.5936707854270935, 'data', 4), ('ludwig-ai/ludwig', 0.5899900197982788, 'ml-ops', 2), ('zacwellmer/worldmodels', 0.5862823128700256, 'ml-rl', 0), ('aiwaves-cn/agents', 0.5783196687698364, 'nlp', 2), ('antonosika/gpt-engineer', 0.5778323411941528, 'llm', 2), ('cheshire-cat-ai/core', 0.5766038298606873, 'llm', 2), ('projectmesa/mesa', 0.5751315355300903, 'sim', 0), ('bentoml/bentoml', 0.5735385417938232, 'ml-ops', 3), ('nccr-itmo/fedot', 0.5655133128166199, 'ml-ops', 1), ('microsoft/semantic-kernel', 0.5540736317634583, 'llm', 3), ('lastmile-ai/aiconfig', 0.5538642406463623, 'util', 2), ('lucidrains/toolformer-pytorch', 0.5433422923088074, 'llm', 1), ('facebookresearch/habitat-lab', 0.5416178107261658, 'sim', 1), ('pathwaycom/llm-app', 0.5409510135650635, 'llm', 3), ('hpcaitech/colossalai', 0.5398745536804199, 'llm', 1), ('facebookresearch/droidlet', 0.5389538407325745, 'sim', 0), ('deepset-ai/haystack', 0.5344579815864563, 'llm', 2), ('microsoft/promptflow', 0.5344325304031372, 'llm', 2), ('ml-tooling/opyrator', 0.5331600308418274, 'viz', 1), ('krohling/bondai', 0.5317063331604004, 'llm', 2), ('yoheinakajima/babyagi', 0.53130042552948, 'llm', 2), ('pettingzoo-team/pettingzoo', 0.5311383605003357, 'ml-rl', 1), ('smol-ai/developer', 0.5302104949951172, 'llm', 2), ('jina-ai/thinkgpt', 0.5273327827453613, 'llm', 0), ('pytorchlightning/pytorch-lightning', 0.526900053024292, 'ml-dl', 3), ('assafelovic/gpt-researcher', 0.5227841734886169, 'llm', 1), ('chatarena/chatarena', 0.5225850343704224, 'llm', 2), ('google/dopamine', 0.5216368436813354, 'ml-rl', 1), ('farama-foundation/gymnasium', 0.5203875303268433, 'ml-rl', 1), ('oliveirabruno01/babyagi-asi', 0.519800066947937, 'llm', 3), ('microsoft/autogen', 0.5193168520927429, 'llm', 2), ('minedojo/voyager', 0.516743540763855, 'llm', 0), ('langchain-ai/langgraph', 0.5159871578216553, 'llm', 1), ('mnotgod96/appagent', 0.51549232006073, 'llm', 2), ('googlecloudplatform/vertex-ai-samples', 0.5143194198608398, 'ml', 1), ('adap/flower', 0.5125753283500671, 'ml-ops', 4), ('linksoul-ai/autoagents', 0.5123705267906189, 'llm', 1), ('uber/fiber', 0.5117772817611694, 'data', 1), ('nebuly-ai/nebullvm', 0.5101591348648071, 'perf', 3), ('inspirai/timechamber', 0.5097473859786987, 'sim', 0), ('microsoft/generative-ai-for-beginners', 0.5075168013572693, 'study', 2), ('pytorch/rl', 0.5073025822639465, 'ml-rl', 2), ('torantulino/auto-gpt', 0.5023353099822998, 'llm', 3), ('modularml/mojo', 0.5005974769592285, 'util', 2), ('onnx/onnx', 0.5004202127456665, 'ml', 1)]

3

1

null

5.54

11

9

8

0

15

23

15

11

0

90

0

36

857

ml-ops

https://github.com/astronomer/astro-sdk

[]

null

[]

null

astronomer/astro-sdk

astro-sdk

299

35

13

Python

https://astro-sdk-python.rtfd.io/

Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow.

astronomer

2024-01-12

2021-12-06

112

2.666242

https://avatars.githubusercontent.com/u/12449437?v=4

Astro SDK allows rapid and clean development of {Extract, Load, Transform} workflows using Python and SQL, powered by Apache Airflow.

['airflow', 'apache-airflow', 'bigquery', 'dags', 'data-analysis', 'data-science', 'elt', 'etl', 'gcs', 'pandas', 'postgres', 's3', 'snowflake', 'sql', 'sqlite', 'workflows']

2024-01-09

[('mage-ai/mage-ai', 0.6467173099517822, 'ml-ops', 4), ('apache/airflow', 0.6314418911933899, 'ml-ops', 5), ('kestra-io/kestra', 0.6130484342575073, 'ml-ops', 2), ('flyteorg/flyte', 0.5711103081703186, 'ml-ops', 2), ('hi-primus/optimus', 0.5675498843193054, 'ml-ops', 2), ('ploomber/ploomber', 0.5675156116485596, 'ml-ops', 1), ('google/ml-metadata', 0.5482959747314453, 'ml-ops', 0), ('prefecthq/server', 0.5464804768562317, 'util', 0), ('orchest/orchest', 0.5454973578453064, 'ml-ops', 3), ('getindata/kedro-kubeflow', 0.541987419128418, 'ml-ops', 0), ('dagster-io/dagster', 0.5415989756584167, 'ml-ops', 2), ('kubeflow-kale/kale', 0.5413955450057983, 'ml-ops', 0), ('prefecthq/prefect', 0.5360534191131592, 'ml-ops', 1), ('linealabs/lineapy', 0.5296847224235535, 'jupyter', 0), ('aws/aws-sdk-pandas', 0.525879442691803, 'pandas', 3), ('fugue-project/fugue', 0.5199980735778809, 'pandas', 2), ('tobymao/sqlglot', 0.5131558179855347, 'data', 5), ('fastai/fastcore', 0.5107561945915222, 'util', 0), ('meltano/meltano', 0.5098263621330261, 'ml-ops', 1), ('airbytehq/airbyte', 0.5056763887405396, 'data', 6), ('kubeflow/fairing', 0.5054138898849487, 'ml-ops', 0)]

39

2

null

3.85

66

57

26

0

14

40

14

66

29

90

0.4

36

1,520

ml-ops

https://github.com/lithops-cloud/lithops

[]

null

[]

null

lithops-cloud/lithops

lithops

293

92

13

Python

http://lithops.cloud

A multi-cloud framework for big data analytics and embarrassingly parallel jobs, that provides an universal API for building parallel applications in the cloud ☁️🚀

lithops-cloud

2024-01-12

2018-04-23

301

0.97296

https://avatars.githubusercontent.com/u/71205470?v=4

A multi-cloud framework for big data analytics and embarrassingly parallel jobs, that provides an universal API for building parallel applications in the cloud ☁️🚀

['big-data', 'big-data-analytics', 'cloud-computing', 'data-processing', 'distributed', 'kubernetes', 'multicloud', 'multiprocessing', 'object-storage', 'parallel', 'serverless', 'serverless-computing', 'serverless-functions']

2024-01-12

[('skypilot-org/skypilot', 0.6185680031776428, 'llm', 2), ('apache/spark', 0.5891563296318054, 'data', 1), ('flyteorg/flyte', 0.5794029235839844, 'ml-ops', 1), ('backtick-se/cowait', 0.5676038861274719, 'util', 1), ('jina-ai/jina', 0.5622606873512268, 'ml', 1), ('eventual-inc/daft', 0.5597764849662781, 'pandas', 0), ('airbytehq/airbyte', 0.5396174788475037, 'data', 0), ('fugue-project/fugue', 0.53661048412323, 'pandas', 1), ('aws/chalice', 0.5222293138504028, 'web', 1), ('netflix/metaflow', 0.5198798179626465, 'ml-ops', 1), ('localstack/localstack', 0.514224648475647, 'util', 0), ('dagster-io/dagster', 0.5072967410087585, 'ml-ops', 0), ('googlecloudplatform/vertex-ai-samples', 0.5040023922920227, 'ml', 0)]

45

2

null

5.6

59

58

70

0

5

13

5

59

152

90

2.6

36

950

util

https://github.com/cqcl/tket

[]

null

[]

null

cqcl/tket

tket

220

45

17

C++

https://tket.quantinuum.com/

Source code for the TKET quantum compiler, Python bindings and utilities

cqcl

2024-01-11

2021-09-13

124

1.772152

https://avatars.githubusercontent.com/u/15688781?v=4

Source code for the TKET quantum compiler, Python bindings and utilities

['compiler', 'quantum-computing']

2024-01-12

[('pyscf/pyscf', 0.677206814289093, 'sim', 0), ('cqcl/lambeq', 0.6623311638832092, 'nlp', 0), ('quantumlib/cirq', 0.6193458437919617, 'sim', 1), ('jackhidary/quantumcomputingbook', 0.6081982851028442, 'study', 1), ('numba/llvmlite', 0.5800346732139587, 'util', 0), ('qiskit/qiskit', 0.5771373510360718, 'sim', 1)]

29

2

null

6.54

155

134

28

0

50

58

50

155

102

90

0.7

36

1,867

util

https://github.com/pypdfium2-team/pypdfium2

[]

null

[]

null

pypdfium2-team/pypdfium2

pypdfium2

216

12

6

Python

https://pypdfium2.readthedocs.io/

Python bindings to PDFium

pypdfium2-team

2024-01-13

2021-10-23

118

1.823884

https://avatars.githubusercontent.com/u/93039761?v=4

Python bindings to PDFium

['pdf', 'pdf-documents', 'pdf-to-image', 'pdfium', 'rasterisation']

2024-01-10

[('py-pdf/pypdf2', 0.6358337998390198, 'util', 2), ('pyfpdf/fpdf2', 0.6115421652793884, 'util', 1), ('camelot-dev/camelot', 0.5336915850639343, 'util', 0), ('jorisschellekens/borb', 0.5246109366416931, 'util', 1)]

4

2

null

8.15

45

44

27

0

37

42

37

45

93

90

2.1

36

1,768

data

https://github.com/meltano/sdk

['data-engineering']

null

[]

null

meltano/sdk

sdk

74

53

7

Python

https://sdk.meltano.com

Write 70% less code by using the SDK to build custom extractors and loaders that adhere to the Singer standard: https://sdk.meltano.com

meltano

2024-01-12

2021-06-21

136

0.543547

https://avatars.githubusercontent.com/u/43816713?v=4

Write 70% less code by using the SDK to build custom extractors and loaders that adhere to the Singer standard: https://sdk.meltano.com

['sdk']

['data-engineering', 'sdk']

2024-01-11

[]

70

3

null

10.56

159

134

31

0

28

31

28

157

284

90

1.8

36

931

data

https://github.com/scylladb/python-driver

[]

null

[]

null

scylladb/python-driver

python-driver

57

35

9

Python

https://python-driver.docs.scylladb.com

ScyllaDB Python Driver, originally DataStax Python Driver for Apache Cassandra

scylladb

2024-01-11

2018-11-20

271

0.210332

https://avatars.githubusercontent.com/u/14364730?v=4

ScyllaDB Python Driver, originally DataStax Python Driver for Apache Cassandra

['scylladb']

2024-01-11

[('datastax/python-driver', 0.8284926414489746, 'data', 0), ('neo4j/neo4j-python-driver', 0.5569538474082947, 'data', 0)]

211

6

null

2.17

41

16

63

0

23

41

105

90

2.6

36