Frequently Asked Questions

A curated summary of the top questions asked on our Slack community, often relating to implementation, functionality, and building better products generally.
Statsig FAQs
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GENERAL

How can we manually populate the Statsig cache using the Python SDK without relying on background polling?

Date of slack thread: 5/2/24

Anonymous: Hello! We’ve recently added the Statsig python SDK to our web app. We would like to be able to poll for updates to experiments and experiment configurations manually instead of relying on background jobs polling the Statsig server.

I’ve added a RedisDataStore to our StatsigOptions at initialization, and we’re able to use local_mode=True to assign users to a group once the cache is populated. But what is the best way to manually populate the cache without initializing the SDK with local_mode=False and letting it run in the background?

Anonymous: Digging a bit more, it seems like we may need to manually hit the <https://api.statsigcdn.com/v1/download_config_specs/> endpoint. Does that seem correct?

Vijaye (Statsig): <@U01RAN2FKJP>

tore (statsig): If you want to use the data store to accomplish this, you’ll need to do a few things. You won’t need local mode to accomplish this

  1. we just added support to python to support polling from the specs in the adapter, rather than the network. You need to use the latest version of the sdk, and implement the should_be_used_for_querying_updates method https://github.com/statsig-io/python-sdk/releases/tag/0.31.0

https://github.com/statsig-io/python-sdk/blob/main/statsig/interface_data_store.py#L14C9-L14C44

  1. You’ll need some other process that keeps the data store up to date. What were you planning to use to do this? If you want complete control over when to update the specs you’ll need to hit the download_config_specs endpoint yourself, as you identified

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Why the best build with us

OpenAI OpenAI
Brex Brex
Notion Notion
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Ancestry Ancestry
At OpenAI, we want to iterate as fast as possible. Statsig enables us to grow, scale, and learn efficiently. Integrating experimentation with product analytics and feature flagging has been crucial for quickly understanding and addressing our users' top priorities.
OpenAI
Dave Cummings
Engineering Manager, ChatGPT
Brex's mission is to help businesses move fast. Statsig is now helping our engineers move fast. It has been a game changer to automate the manual lift typical to running experiments and has helped product teams ship the right features to their users quickly.
Brex
Karandeep Anand
President
At Notion, we're continuously learning what our users value and want every team to run experiments to learn more. It’s also critical to maintain speed as a habit. Statsig's experimentation platform enables both this speed and learning for us.
Notion
Mengying Li
Data Science Manager
We evaluated Optimizely, LaunchDarkly, Split, and Eppo, but ultimately selected Statsig due to its comprehensive end-to-end integration. We wanted a complete solution rather than a partial one, including everything from the stats engine to data ingestion.
SoundCloud
Don Browning
SVP, Data & Platform Engineering
We only had so many analysts. Statsig provided the necessary tools to remove the bottleneck. I know that we are able to impact our key business metrics in a positive way with Statsig. We are definitely heading in the right direction with Statsig.
Ancestry
Partha Sarathi
Director of Engineering
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