Community

At Alpaca, we truly believe open source and the community around it can change financial systems and how we interact with them. It is our commitment to contribute to the community as much as possible. With that in mind, we set up a few initiatives where you can learn from and contribute to the community.

As you get deeper into trading and automation, there are many questions and hurdles that you may face while trying things out. We find that our community has been growing rapidly to share what they do with each other. Alpaca grows with our community and knowledge is built together.

Community Slack

Alpaca’s community Slack has grown to be the go-to place for Alpaca users regardless of experience or the stage of where they are in the journey of trading. The community consists of both very experienced users and beginners. From questions about basic features and API instructions to discussions about how the market works and analysis of algorithms they are building, the community Slack is the place where you can chat with other community members with similar experience as well as those who are already running profitable strategies.

There are multiple community-built channels in the community Slack. Popular channels that you may want to subscribe to include:

#random - Everyone who joins the community Slack automatically joins here. Jump right in to discussions ranging from simple coding questions to specific features that Alpaca offers.

#announcement - Everyone automatically joins here. This is a ready-only channel for the community members and is a place where you can find feature updates and read official announcements from Alpaca.

#api - Technical focused discussions regarding the Alpaca API including issues and findings encountered by the community.

#algo-development & #algotrading - Highly technical channels where members share and discuss their code, ask questions, and solicit feedback of their strategies.

#python - Python is a popular language for writing trading strategies thanks to Quantopian. Many Quantopian users are active in our community Slack and discuss open source resources used to support existing Quantopian algorithms.

#zipline-strategies - This is another Quantopian influenced channel where members talk about compatibility and Quantopian’s open source zipline resources.

Medium Publication - Automation Generation

Automation Generation has become a publication where community members contribute their experience and know-how in a more comprehensive format. There are a number of comprehensive instructions and how-to guides such as full code snippets of trading strategies and an infrastructure setup overview covering which cloud services to use.

If you want to read more about the market, trading strategies, coding, and other topics discussed in the community Slack, Automation Generation offers you many comprehensive posts that should help you along the way.

Popular posts from Automation Generation include:

Manage Your Stocks from Google Spreadsheet Using API

HFT-like Trading Algorithm in 300 Lines of Code You Can Run Now

This is How I Implemented Benjamin Graham’s Teachings into an Automated Investing Strategy in Python

Exploring the Differences between U.S. Stock Market Data Feeds

Commission Free Trading: Is it helping or hurting you?

Algorithmically Detecting (and Trading) Technical Chart Patterns with Python

Ultimate List of Automated Trading Strategies You Should Know — Part 1

GitHub

Since we started Alpaca in 2015, we have been actively contributing our code to the open source community. Our community members use this open source IP for their trading strategies as well as enhancing their infrastructure.

You can see all open-sourced projects started by Alpaca here that you can fork and use. Here are popular ones you may want to check out:

marketstore - The origin of Alpaca is a database company (hence our official company name is AlpacaDB, Inc.). We built a database from scratch called MarketStore, which is a database server optimized for financial time-series data just like an extensible DataFrame service accessible from anywhere in your system, at higher scalability.

pylivetrader - A simple python live trading framework with zipline interface. The main purpose is to run algorithms developed in the Quantopian platform in live trading.

alpaca-trade-api-python - A python library for the Alpaca trade API. It makes rapid trading algo development easy, with support for both the REST and streaming interfaces.

alpaca-trade-api-js - A Node.js library for the Alpaca trade API. It makes rapid trading algo development easy, with support for both the REST and streaming interfaces.

alpaca-trade-api-csharp - A .NET/C# library for the Alpaca trade API. It makes rapid trading algo development easy, with support for both the REST and streaming interfaces.

alpaca-rn-mobile - An example react native mobile app that allows basic brokerage functions including submitting orders to buy/sell stocks, canceling orders, liquidating positions, and enabling and disabling your API access. Here is a link to the working app in the iOS App Store.


Suggestions or questions?
We're always happy to hear from you. You can contribute to these docs on GitHub, or you can join our Community Slack to get help from other community members and the Alpaca team.