go-talib
quokka
go-talib | quokka | |
---|---|---|
3 | 23 | |
726 | 1,082 | |
- | - | |
0.0 | 8.3 | |
over 1 year ago | 8 months ago | |
Go | Python | |
MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
go-talib
-
Algorithmic Trading with Go
Not a complete answer but I quite liked https://github.com/markcheno/go-talib for technical indicators.
-
Go vs Rust for Algo Trading
For talib, https://github.com/markcheno/go-talib
-
malgova - golang library for algo back-testing.
you may use, https://github.com/markcheno/go-talib for TA with the dataset. https://github.com/iwat/talib-cdl-go for candle stick pattern detection or for custom scanning.
quokka
-
How Query Engines Work
An awesome read!
Something related that I found out about from HN a few months back is another engine called quokka. It's particularly interesting and applicable how quokka schedules distributed queries to outperform Spark https://github.com/marsupialtail/quokka/blob/master/blog/why...
- Quokka – Distributed Polars on Ray
-
Algorithmic Trading with Go
Hi Justin, you might be interested in my blog: https://github.com/marsupialtail/quokka/blob/master/blog/bac... advocating a cloud based approach.
You don't have to use the system I am building, but it's worth thinking about that design.
-
Daft: A High-Performance Distributed Dataframe Library for Multimodal Data
SQL support is very challenging.
I work on Quokka (https://github.com/marsupialtail/quokka). I support Iceberg reads. Recently we are adding SQL support from just parsing the DuckDB logical plan, though that is very challenging as well.
The Python world lacks a standard for a plug and play SQL query optimizer. Apache Calcite is good for the JVM world, but not great if you are trying to cut out the JVM.
- Why your dataframe library needs to understand vector embeddings
-
The Inner Workings of Distributed Databases
In case people are interested, I wrote a post about fault tolerance strategies of data systems like Spark and Flink: https://github.com/marsupialtail/quokka/blob/master/blog/fau...
The key difference here is that these systems don't store data, so fault tolerance means recovering within a query instead of not losing data.
-
Launch HN: DAGWorks – ML platform for data science teams
would love to collaborate on an integration with pyquokka (https://github.com/marsupialtail/quokka) once I put out a stable release end of this month :-)
-
is spark always your go to solution ?
Then you should keep an eye on quokka. This may become the "Spark" for Polars/DuckDB. It seems to be under active development though I'm not sure how stable it is.
- Distributed fault tolerance made simple
- Fault tolerance for distributed data systems is quite simple
What are some alternatives?
talib-cdl-go - A pure Go port of ta-lib only in candle recognition module (CDL).
opteryx - 🦖 A SQL-on-everything Query Engine you can execute over multiple databases and file formats. Query your data, where it lives.
malgova - go module for algo live trading and backtesting library to use with NSE/NFO traded scrips. supports Level 1/ Level 2 tickdata
cempaka - "Write a trading bot which buys low and sells high." Sounds simple enough, right?
vscode-go - Go extension for Visual Studio Code
awesome-pipeline - A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin
mercury - Bridge app for KITE Trading API. Records Live Data for later replay/Feeds live data to tools.
spyql - Query data on the command line with SQL-like SELECTs powered by Python expressions
pg8000 - A Pure-Python PostgreSQL Driver
intelligent-trading-bot - Intelligent Trading Bot: Automatically generating signals and trading based on machine learning and feature engineering
blog - Some notes on things I find interesting and important.