Python SDK#

A Python SDK for Molasses. It allows you to evaluate a user's status for a feature. It also helps simplify logging events for A/B testing.

Molasses uses polling to check if you have updated features. Once initialized, it takes microseconds to evaluate if a user is active.

Install#

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pip install molasses

Usage#

Initialization#

Start by initializing the client with an APIKey. This begins the polling for any feature updates. The updates happen every 15 seconds.

python
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from molasses import MolassesClient
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    client = MolassesClient("test_key")

If you decide not to track analytics events (experiment started, experiment success) you can turn them off by setting the send_events field to False

python
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client = MolassesClient("test_key",  send_events=False)

Check if feature is active#

You can call is_active with the key name and optionally a user’s information. The id field is used to determine whether a user is part of a percentage of users. If you have other constraints based on user params you can pass those in the params field.

python
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client.is_active("FOO_TEST", {
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      "id":"foo",
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      "params":{
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        "isBetaUser":"false",
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        "isScaredUser":"false"
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       }
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    })

You can check if a feature is active for a user who is anonymous by just calling is_active with the key. You won’t be able to do percentage roll outs or track that user’s behavior.

python
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client.is_active("TEST_FEATURE_FOR_USER")

Experiments#

To track whether an experiment was successful you can call experiment_success. experiment_success takes the feature’s name, any additional parameters for the event and the user.

python
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client.experiment_success("GOOGLE_SSO",{
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            "version": "v2.3.0"
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        },{
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       "id":"foo",
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       "params":{
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         "isBetaUser":"false",
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         "isScaredUser":"false"
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        }
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     })

Example#

python
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from molasses import MolassesClient
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    client = MolassesClient("test_key")
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    if client.is_active('NEW_CHECKOUT'):
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      print "we are a go"
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    else:
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      print "we are a no go"