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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,82 @@ | ||
| import datetime | ||
| import random | ||
| import polars as pl | ||
| from pdstools.utils import cdh_utils | ||
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| # Some day will move into a proper IH class | ||
|
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| class ih_generator: | ||
| interactions_period_days = 21 | ||
| accept_rate = 0.2 | ||
| accept_avg_duration_minutes = 10 | ||
| convert_over_accept_rate_test = 0.5 | ||
| convert_over_accept_rate_control = 0.3 | ||
| convert_avg_duration_days = 2 | ||
|
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| def generate(self, n): | ||
| now = datetime.datetime.now() | ||
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| def _interpolate(min, max, i, n): | ||
| return min + (max - min) * i / (n - 1) | ||
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| def to_prpc_time_str(timestamp): | ||
| return cdh_utils.to_prpc_date_time(timestamp)[0:15] | ||
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| ih_fake_impressions = pl.DataFrame( | ||
| { | ||
| "InteractionID": [str(int(1e9 + i)) for i in range(n)], | ||
| "TimeStamp": [ | ||
| (now - datetime.timedelta(days=i * self.interactions_period_days / n)) | ||
| for i in range(n) | ||
| ], | ||
| "AcceptDurationMinutes": [ | ||
| random.uniform(0, 2 * self.accept_avg_duration_minutes) for i in range(n) | ||
| ], | ||
| "ConvertDurationDays": [ | ||
| random.uniform(0, 2 * self.convert_avg_duration_days) for i in range(n) | ||
| ], | ||
| "pyChannel": random.choices(["Web"], k=n), # random.choices(["Web", "Email"], k=n), | ||
| "pyIssue": "Acquisition", | ||
| "pyGroup": "Phones", | ||
| "pyName": "AppleIPhone1564GB", | ||
| "ExperimentGroup": ["Conversion-Test", "Conversion-Control"] * int(n / 2), | ||
| "pyOutcome": None, | ||
| } | ||
| ).with_columns( | ||
| pyOutcome=pl.when(pl.col.pyChannel == "Web") | ||
| .then(pl.lit("Impression")) | ||
| .otherwise(pl.lit("Pending")) | ||
| ) | ||
| ih_fake_accepts = ih_fake_impressions.sample(fraction=self.accept_rate).with_columns( | ||
| pl.col.TimeStamp + pl.duration(minutes=pl.col("AcceptDurationMinutes")), | ||
| pyOutcome=pl.when(pl.col.pyChannel == "Web") | ||
| .then(pl.lit("Clicked")) | ||
| .otherwise(pl.lit("Accepted")), | ||
| ) | ||
| ih_fake_converts_test = ih_fake_accepts.filter(pl.col.ExperimentGroup=="Conversion-Test").sample( | ||
| fraction=self.convert_over_accept_rate_test | ||
| ).with_columns( | ||
| pl.col.TimeStamp + pl.duration(days=pl.col("ConvertDurationDays")), | ||
| pyOutcome=pl.lit("Conversion"), | ||
| ) | ||
| ih_fake_converts_control = ih_fake_accepts.filter(pl.col.ExperimentGroup=="Conversion-Control").sample( | ||
| fraction=self.convert_over_accept_rate_control | ||
| ).with_columns( | ||
| pl.col.TimeStamp + pl.duration(days=pl.col("ConvertDurationDays")), | ||
| pyOutcome=pl.lit("Conversion"), | ||
| ) | ||
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| ih_data=pl.concat([ih_fake_impressions, ih_fake_accepts, ih_fake_converts_test, ih_fake_converts_control]).with_columns( | ||
| pxOutcomeTime=pl.col("TimeStamp").map_elements( | ||
| to_prpc_time_str, return_dtype=pl.String | ||
| ), | ||
| ).filter(pl.col("TimeStamp") < pl.lit(now)).drop( | ||
| ["AcceptDurationMinutes", "ConvertDurationDays", "TimeStamp"] | ||
| ).sort( | ||
| "InteractionID", "pxOutcomeTime" | ||
| ).lazy() | ||
|
|
||
| return ih_data |
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