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01/20/2022, 10:05 AMfuture-teacher-7046
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04/27/2022, 1:01 PMfuture-teacher-7046
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04/27/2022, 2:45 PMOur SDKs let you bucket users using deterministic hashing
Where can I find it. How do I use it? In our use case, UI won't be involved in it. User click events (PDP) & user info will be collected via Tealium connectors into our BQ Table.
Problem statement:
I've needed to generate random but consistent values in a BigQuery data pipeline. This is a pipeline that runs many times per day and constantly has new data feeding in through upstream pipes.
As an example, let's say that we have 10m users and need to randomly place them into groups depending on the week of the month.
Additionally, we only want to do this once; once a user gets placed into a group, they stay in that group. This way, downstream (experiment pipeline) work can rely on how each user is assigned without having to worry about checking for changes .fresh-football-47124
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04/29/2022, 2:59 AMfresh-football-47124
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05/15/2022, 10:54 AMPreviously, GrowthBook had two hard-coded user identifier types (or randomization units) ā *user_id* and *anonymous_id*. This worked for some websites, but was not very flexible. For example, B2B products might want to split users by their company instead of an individual user_id. Or an app might only have logged-in users and have no use for an anonymous_id.
How do I achieve the same using Python SDK?def on_experiment_viewed(experiment, result):
# Use whatever event tracking system you want
analytics.track(attributes["id"], "Experiment Viewed", {
'experimentId': experiment.key,
'variationId': result.variationId
})
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fast-telephone-84882
05/16/2022, 1:40 PMfuture-teacher-7046