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        "author": "Matthijs van der Kroon",
        "author_email": "matthijs@primed.io",
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            "Development Status :: 2 - Pre-Alpha",
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            "Natural Language :: English",
            "Programming Language :: Python :: 3.4",
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        "description": "# pyprimed: a python library to manage PrimedIO\n\nCreate a personalized web application that is unique and relevant for each and every user with [Primed.io](https://www.primed.io/).\n\n## Installation\n```\npip install pyprimed\n```\n\n## Quickstart\n### Import the SDK and initiate the connection\n```python\nfrom pyprimed.pio import Pio\n\npio = Pio(uri='http://<user>:<password>@<api_url>:<port>')\n```\n\n### Create a Universe, and attach a few Targets\n```python\n# create a new universe and attach a single target\npio\\\n  .universes\\\n  .create(name='myfirstuniverse')\\\n  .targets\\\n  .upsert([{'key':'ARTICLE-1', 'value':{'url': 'www.example.com/article-1'}}])\n\n# retrieving the newly created universe\nu = pio.universes.filter(name='myfirstuniverse').first\n\n# list all targets currently associated with this universe\nfor target in u.targets.all():\n  print(target.key, target.created_at)\n\n# prepare a list of new targets\nnew_targets = [\n  {'key': 'ARTICLE-2', 'value': {'url': 'www.example.com/article-2'}}, \n  {'key': 'ARTICLE-3', 'value': {'url': 'www.example.com/article-3'}}\n]\n\n# upsert the new targets\nu.targets.upsert(new_targets)\n\n# targets are upserted, which means that for a given key there\n# can be only one instance in the database. Trying to create an\n# instance with the same key will update the value of the record\n# in the database\nu.targets.upsert([{'key':'ARTICLE-1', 'value':{'url': 'THIS IS NEW!'}}])\nu.targets.filter(key='ARTICLE-1').first.value \n```\n\n### Create a Model, and attach a few Signals\n```python\n# create a new model and attach a single signal\npio\\\n  .models\\\n  .create(name='myfirstmodel')\\\n  .signals\\\n  .upsert([{'key':'ALICE'}])\n\n# retrieving the created model\nm = pio.models.filter(name='myfirstmodel').first\n\n# list all signals currently associated with this model\nfor signal in m.signals.all():\n  print(signal.key, signal.created_at)\n\n# prepare a list of new signals\nnew_signals = [\n  {'key': 'BOB'}, \n  {'key': 'CHRIS'}\n]\n\n# create the new signals\nm.signals.upsert(new_signals)\n\n# prepare a set of predictions (sk stand for signal.key, and tk for target.key)\n# WARNING: `sk` and `tk` should always be a string!\npredictions = [\n  {'sk': 'ALICE', 'tk': 'ARTICLE-1', 'score': 0.35},\n  {'sk': 'BOB', 'tk': 'ARTICLE-1', 'score': 0.75}, \n  {'sk': 'CHRIS', 'tk': 'ARTICLE-1', 'score': 0.15}\n]\n\n# create the new predictions \nu = pio.universes.filter(name='myfirstuniverse').first\n\npio\\\n    .predictions\\\n    .on(model=m, universe=u)\\\n    .upsert(predictions, asynchronous=False)\n# the `asynchronous=False` settings waits for this operation to end before \n# continuing\n```\n\n### Create a Campaign, Experiment and set up an AB test to start using the Predictions\n```python\nfrom pyprimed.models.abvariant import CustomAbvariant, RandomControlAbvariant, NullControlAbvariant\n\n# we create a custom abvariant that blends models m1 and m2 using a 60%/40% weight ratio\nab0 = CustomAbvariant(label='A', models={m1: 0.6, m2: 0.4})\nab1 = RandomControlAbvariant(label='B')\nab2 = NullControlAbvariant(label='C')\n\n# we attach the abvariants to the experiment\n# `ab0` will receive 80% of traffic, `ab1` and `ab2`\n# receive 10% each\ne.abvariants.create({ab0: 0.8, ab1: 0.1, ab2: 0.1})\n\nres = c.personalise(\n  pubkey='mypubkey',\n  secretkey='mysecretkey',\n  signals={'userid': 'BOB'},\n  abvariant='A'\n)  # abvariant with label 'A' will be returned\n```\n\n### Update Experiment\n```python\nfrom pyprimed.models.abvariant import CustomAbvariant, RandomControlAbvariant, NullControlAbvariant\n\n# obtain existing experiment\ne = c.experiments.filter(name=\"myexperiment\").first()\n\n# change property\ne.salt = \"new_salt\"\ne.update()\n\n# update abvariants\nab1 = CustomAbvariant(label=\"NEWLABEL\", {m1: 0.33, m2: 0.77})\nab2 = RandomControlAbvariant(label=\"NEWRANDOMCONTROL\")\n\ne.abvariants.update({ab1: 0.5, ab2: 0.5})\n```\n\n## Developer\nBuild the documentation:\n```\ncd docs && pydocmd build\n```\n\nPreview documentation on http://localhost:8000\n```\ncd docs && pydocmd serve\n```",
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