ray vs QUANTAXIS
ray and QUANTAXIS share 9 technologies: pymongo, pyarrow, MongoDB, Redis, Flask, jupyter-core, tornado, matplotlib, and lxml. Both are written in Python.
What they share and what sets them apart
ray-project
ray
Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.
Python44.3kRead on November 10, 2026, at commit c99c603What is ray built with?Only in ray
- FastAPI
- aimrecords
- aimrocks
- amqp
- array-record
- arro3-core
- async-lru
- azure-common
- azure-datalake-store
- azure-storage-blob
confluent-kafka
- delta-kernel-rust-sharing-wrapper
- diskcache
expiringdict
- feather-format
- gitdb
google-cloud-core
h5py
- huey
kombu
- partd
pickleshare
- py-partiql-parser
- pylance
- s3torchconnectorclient
- s3transfer
taskiq
tensorboard-data-server
- zict
mcap
- aioboto3
- adlfs
pyiceberg
- smart-open
- pymysql
clickhouse-connect
daft
deltalake
- gcsfs
lance-namespace
- obstore
- Celery
delta-sharing
- fastavro
hudi
- pyzmq
- s3fs
- s3torchconnector
- taskiq-redis
webdataset
- Hugging Face
- Google Cloud Storage
- Kafka
- Databricks
- adagio
- asgiref
- flask-cors
- graphene
- graphql-core
- graphql-relay
jupyterlab-server
pygame
pymars
werkzeug
- Ray
starlette
- AIOHTTP
pyspark
- Lightning
raydp
- anyio
uvicorn
- React
react-router-dom
- accessible-pygments
- alabaster
- cycler
fonttools
jupyterlab-pygments
pydata-sphinx-theme
- soupsieve
sphinx-design
- tinycss2
- aim-ui
- alive-progress
bokeh
contourpy
- glfw
halo
- jupyter-server-terminals
- jupyterlab-widgets
- matplotlib-inline
- Plotly
prompt-toolkit
pyglet
pyopengl
- spinners
- Textual
- widgetsnbextension
- xyzservices
- Gradio
- ipywidgets
- Rich
- pydot
- alembic
peewee
sqlglot
- SQLAlchemy
- adal
- argon2-cffi
- argon2-cffi-bindings
- azure-identity
- flask-basicauth
- gcs-oauth2-boto-plugin
google-auth-oauthlib
- google-oauth
- google-reauth
- id
itsdangerous
joserfc
- jwcrypto
- keyring
- msal
- msal-extensions
- oauth2client
oauthlib
- pyjwt
- pyu2f
requests-oauthlib
- cryptography
google-auth-httplib2
- albucore
- autograd
ax-platform
- bayesian-optimization
- bitsandbytes
botorch
- cma
cmdstanpy
- crcmod
cupy-cuda100
cupy-cuda12x
cupy-cuda13x
- einops
- fairscale
- gpytorch
gradio-client
- gym
jaxlib
- labmaze
- LangChain
- lightning-utilities
- linear-operator
- llvmlite
lm-eval
- minigrid
- ml-dtypes
- mlflow-skinny
- moocore
mosaicml
nltk
- ONNX
onnx-ir
- onnxruntime
onnxscript
openai-whisper
- opt-einsum
optax
- orbax-checkpoint
peft
prophet
pymoo
pyro-ppl
- pytorch-ranger
rouge-score
- sacrebleu
safetensors
scikit-image
- sentencepiece
skops
stanio
statsforecast
- tensorflow-estimator
tf-keras
- tiktoken
timm
tokenizers
- torch-geometric
torchtext
- triton
- gymnasium
- torch
- transformers
- TensorFlow
jax
torchvision
- xgboost
lightgbm
- scikit-learn
- MLflow
- tensorflow-metadata
accelerate
- datasets
- pytorch-lightning
- comet-ml
- dm-env
evaluate
flax
- Keras
- torchmetrics
- aim
albumentations
ale-py
configspace
deepspeed
diffusers
- dm-control
- hpbandster
- hyperopt
- nevergrad
- open-spiel
- Optuna
pettingzoo
- supersuit
tensordict
tensorflow-datasets
tensorflow-probability
torchaudio
- bleach
- defusedxml
et-xmlfile
imageio
imageio-ffmpeg
- imagesize
- jsonlines
- linkify-it-py
- mako
- markdown
markdown-it-py
markupsafe
- mdit-py-plugins
- mdurl
mistune
- moviepy
myst-parser
- nbconvert
- nh3
- openpyxl
- pandocfilters
- readme-renderer
ruamel-yaml
ruamel-yaml-clib
- strictyaml
- tinyscaler
webencodings
- xlrd
- xmltodict
pillow
- docutils
- jinja2
- beautifulsoup4
av
- decord
jupytext
- nbformat
- torchcodec
- annotated-types
- fastjsonschema
- fqdn
- jsonschema-path
- jsonschema-specifications
- openapi-spec-validator
- pathvalidate
- pydantic-core
- referencing
- rfc3339-validator
- rfc3986
- rfc3986-validator
- validators
- Pydantic
- jsonschema
- openapi-schema-validator
- aiobotocore
- applicationinsights
- aws-sam-translator
aws-xray-sdk
- azure-cli-core
- azure-cli-telemetry
- azure-core
- azure-mgmt-compute
- azure-mgmt-core
- azure-mgmt-network
- azure-mgmt-resource
- azure-mgmt-resource-deployments
- boto
- cloud-tpu-diagnostics
- colorlog
- execnet
- Gunicorn
- log-symbols
- ml-goodput-measurement
- msrestazure
- opencensus-context
- opentelemetry-api
opentelemetry-instrumentation
opentelemetry-instrumentation-asgi
opentelemetry-semantic-conventions
opentelemetry-util-http
- python-json-logger
- supervisor
psutil
- boto3
- botocore
prometheus-client
- OpenTelemetry
kubernetes
opentelemetry-exporter-prometheus
- docker
opentelemetry-exporter-otlp-proto-grpc
opentelemetry-instrumentation-fastapi
- ray-haproxy
- typeface-roboto
- MUI
usehooks-ts
- lowlight
react-window
react-icons
- @mui/icons-material
- js-yaml
In common
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QUANTAXIS
QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案
Python11.4kRead on November 12, 2026, at commit 232aa7aWhat is QUANTAXIS built with?Only in QUANTAXIS
Side by side
rayQUANTAXIS
SizeLines written by people and agents, without generated ones; code files, without tests.
ray1,551,053 lines written2,797 code files
QUANTAXIS83,413 lines written284 code files
Who writes itA commit counts as AI's when it carries its signature: a Co-Authored-By line, its author name or the merge of its branch.
ray3.7% of its commits signed by AIWith Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex
QUANTAXIS0% of its commits signed by AI
ActivityFrom GitHub and its history, on the day SeeRepo read it.
rayLast push November 10, 202632,424 commits44,251 stars
QUANTAXISLast push September 18, 20265,620 commits11,364 stars
TestsThe files that test the code, and the share of code files a test imports.
ray2,192 test files9.5% of its code files have a test that imports them
QUANTAXIS4 test files3.5% of its code files have a test that imports them
Frequently asked questions
Which is bigger, ray or QUANTAXIS?
ray, with 1,551,053 lines written; QUANTAXIS has 83,413.
The proof: ray-project/ray's code at commit c99c603
Which has more GitHub stars, ray or QUANTAXIS?
ray, with 44,251 stars; QUANTAXIS has 11,364.
The proof: ray-project/ray on GitHub
Which has more tests, ray or QUANTAXIS?
ray, with 2,192 test files; QUANTAXIS has 4.
The proof: ray-project/ray's code at commit c99c603
Which was updated more recently, ray or QUANTAXIS?
ray: its last push was on November 10, 2026, and QUANTAXIS's on September 18, 2026.
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, ray or QUANTAXIS?
ray: an AI signed 3.7% of its commits, with Claude Code, Gemini CLI, GitHub Copilot, Cursor, and Codex.
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