QuantDinger vs ray
QuantDinger and ray share 14 technologies: Flask, confluent-kafka, Redis, Celery, Kafka, AIOHTTP, werkzeug, flask-cors, cryptography, pyjwt, pillow, xlrd, Gunicorn, and prometheus-client. Both are written in Python.
What they share and what sets them apart
QuantDinger
The most complete open-source, self-hosted Agentic Trading OS—AI research, Python strategies, factor discovery, backtesting, optimization, paper/live multi-asset execution, risk controls, monitoring, MCP, and multi-tenant SaaS in one auditable stack.
Python13.7kRead on November 9, 2026, at commit 49d6b02What is QuantDinger built with?Only in QuantDinger
In common
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 13, 2026, at commit de4c576What 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
- delta-kernel-rust-sharing-wrapper
- diskcache
expiringdict
- feather-format
- gitdb
google-cloud-core
h5py
- huey
jupyter-cache
kombu
- partd
petastorm
pickleshare
- py-partiql-parser
- pylance
- pymongo
- qpd
- s3torchconnectorclient
- s3transfer
- semidbm
- sqlitedict
taskiq
tensorboard-data-server
- zict
pyarrow
mcap
- aioboto3
- MongoDB
- adlfs
pyiceberg
- smart-open
clickhouse-connect
daft
deltalake
- gcsfs
lance-namespace
- obstore
delta-sharing
- fastavro
hudi
- pyzmq
- s3fs
- s3torchconnector
- taskiq-redis
zarr
- Hugging Face
- Google Cloud Storage
- Databricks
- adagio
- asgiref
- graphene
- graphql-core
- graphql-relay
- jupyter-core
jupyterlab-server
pygame
pymars
- Ray
starlette
pyspark
- Lightning
raydp
- anyio
tornado
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
- 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
- pyu2f
requests-oauthlib
google-auth-httplib2
- aws-requests-auth
- albucore
- autograd
ax-platform
- bayesian-optimization
- bitsandbytes
botorch
- cma
cmdstanpy
- crcmod
cupy-cuda100
cupy-cuda12x
cupy-cuda13x
- einops
- fairscale
- fbgemm-gpu
- gpytorch
gradio-client
- gym
jaxlib
- labmaze
- LangChain
- lightning-utilities
- linear-operator
- llvmlite
lm-eval
- minigrid
- ml-dtypes
- 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
tf-keras
- tiktoken
timm
tokenizers
- torch-geometric
- torch-optimizer
- torch-scatter
- torch-sparse
torchtext
- triton
- yahp
- gymnasium
- torch
- transformers
- TensorFlow
jax
torchvision
- xgboost
lightgbm
- scikit-learn
- MLflow
- datasets
- pytorch-lightning
- comet-ml
- dm-env
flax
- Keras
- torchmetrics
- aim
ale-py
configspace
deepspeed
diffusers
- dm-control
- hpbandster
- hyperopt
- nevergrad
- open-spiel
- Optuna
tensorflow-probability
- zoopt
- bleach
- defusedxml
et-xmlfile
imageio
imageio-ffmpeg
- imagesize
- jsonlines
- linkify-it-py
lxml
- mako
- markdown
markdown-it-py
markupsafe
- mdit-py-plugins
- mdurl
mistune
- moviepy
myst-parser
- nbconvert
- nh3
- openpyxl
- pandocfilters
- pytablewriter
- readme-renderer
ruamel-yaml
ruamel-yaml-clib
- strictyaml
- tinyscaler
webencodings
- xmltodict
- docutils
- jinja2
- beautifulsoup4
- decord
- nbformat
- torchcodec
- annotated-types
- fastjsonschema
- fqdn
- jsonschema-path
- jsonschema-specifications
- openapi-spec-validator
- pathvalidate
- referencing
- rfc3339-validator
- rfc3986
- rfc3986-validator
- typepy
- validators
- Pydantic
- jsonschema
- 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
google-cloud-audit-log
- log-symbols
- ml-goodput-measurement
- msrestazure
- opencensus-context
opentelemetry-instrumentation
opentelemetry-instrumentation-asgi
opentelemetry-semantic-conventions
opentelemetry-util-http
- python-json-logger
- supervisor
psutil
- boto3
- botocore
- pybuildkite
- 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
Side by side
Frequently asked questions
Which is bigger, QuantDinger or ray?
The proof: ray-project/ray's code at commit de4c576
Which has more GitHub stars, QuantDinger or ray?
The proof: ray-project/ray on GitHub
Which has more tests, QuantDinger or ray?
The proof: ray-project/ray's code at commit de4c576
Which was updated more recently, QuantDinger or ray?
The proof: ray-project/ray's commits on GitHub
Which has more commits signed by AI, QuantDinger or ray?
The proof: the commits each tool signed in OpenByteInc/QuantDinger
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