Usage
For more information about the API (params, columns), see
the Revenue Reporting API.
Revenue Reporting API
Get report
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30 | from applovin_report import RevenueReport
report = RevenueReport(api_key="your_api_key")
_columns = [
"day",
"package_name",
"platform",
"country",
"application",
"max_ad_unit_test",
"max_ad_unit_id",
"network",
"network_placement",
'ad_format',
"attempts",
"responses",
"fill_rate",
"impressions",
"estimated_revenue",
"ecpm",
]
result = report.get_report(
start_date="2023-05-23",
end_date="2023-05-23",
columns=_columns,
filter_package_name="com.jura.car.crashes.simulator", )
print(result)
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Get report in batch
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35 | from applovin_report import RevenueReport
import pandas as pd
report = RevenueReport(api_key="your_api_key")
_columns = [
"day",
"package_name",
"platform",
"country",
"application",
"max_ad_unit_test",
"max_ad_unit_id",
"network", # bigquery
"network_placement",
'ad_format', # big_query
"attempts",
"responses",
"fill_rate",
"impressions",
"estimated_revenue",
"ecpm",
]
df = pd.DataFrame(columns=_columns)
for df_result in report.get_report_batch(
start_date="2023-05-23",
end_date="2023-05-25",
columns=_columns,
batch_size=10000,
filter_package_name="com.cooking.games.fever.food.city.craze.dream",
):
# Concat for full data or process every batch
df = pd.concat([df, df_result], ignore_index=True)
print(df)
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