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Modules

RevenueReport

Detailed documentation for this API can be found at: Revenue Report API

Source code in applovin_report/revenue_reporting_api.py 
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class RevenueReport:
    """
    Detailed documentation for this API can be found at: [Revenue Report API](https://dash.applovin.com/documentation/mediation/reporting-api/max-ad-revenue)
    """

    ENDPOINT = "https://r.applovin.com/maxReport"

    def __init__(self, api_key: str | list[str]):
        """
        Args:
            api_key: API key(s) to use for the report

        Returns:
            None

        Doc Author:
            minhpc@ikameglobal.com
        """
        self.api_key = api_key

    def get_report(
        self,
        start_date: str = None,
        end_date: str = None,
        columns: list[str] = None,
        limit: int = 100000,
        max_retries: int = 3,
        retry_interval: int = 30,
        **kwargs,
    ) -> DataFrame:
        """
        Retrieve a report from the MAX Revenue Report API.


        Args:
            start_date: YYYY-MM-DD, within the last 45 days
            end_date: YYYY-MM-DD, within the last 45 days
            columns: List of columns to include in the report
            limit: Set the number of rows to return
            max_retries: Set the number of retries
            retry_interval: Set the number of seconds to wait between retries
            **kwargs: Additional parameters to pass to the API

        Returns:
            A pandas DataFrame containing the report data

        Doc Author:
            minhpc@ikameglobal.com
        """
        if not start_date or not end_date:
            start_date = (datetime.now() - timedelta(days=2)).strftime("%Y-%m-%d")
            end_date = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")

        params = {
            "api_key": self.api_key,
            "start": start_date,
            "end": end_date,
            "columns": ",".join(columns),
            "format": "json",
            "limit": limit,
            **kwargs,
        }

        for i in range(max_retries + 1):
            response = requests.get(url=RevenueReport.ENDPOINT, params=params)

            if response.status_code == 200:
                return DataFrame(response.json()["results"])
            else:
                print(f"Retrying... ({i + 1}/{max_retries})")
                time.sleep(retry_interval)

        print(traceback.format_exc())
        raise Exception(f"Error: {response.status_code}")

    def get_report_batch(
        self,
        start_date: str = None,
        end_date: str = None,
        columns: list[str] = None,
        batch_size: int = 100000,
        max_retries: int = 3,
        retry_interval: int = 30,
        **kwargs,
    ) -> Iterator[DataFrame]:
        """
        Retrieve a report from the MAX Revenue Report API in batches.

        Args:
            start_date: YYYY-MM-DD, within the last 45 days
            end_date: YYYY-MM-DD, within the last 45 days
            columns: List of columns to include in the report
            batch_size: Number of rows to return per batch
            max_retries: Number of retries
            retry_interval: Number of seconds to wait between retries
            **kwargs: Additional parameters to pass to the API

        Returns:
            A generator that yields a pandas DataFrame containing the report data

        Doc Author:
            minhpc@ikameglobal.com
        """
        if not start_date or not end_date:
            start_date = (datetime.now() - timedelta(days=2)).strftime("%Y-%m-%d")
            end_date = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")

        offset = 0
        has_next_batch = True
        while has_next_batch:
            params = {
                "api_key": self.api_key,
                "start": start_date,
                "end": end_date,
                "columns": ",".join(columns),
                "format": "json",
                "offset": offset,
                "limit": batch_size,
                **kwargs,
            }

            response = None
            for i in range(max_retries + 1):
                response = requests.get(url=RevenueReport.ENDPOINT, params=params)
                if response.status_code == 200:
                    break
                print(f"Retrying... ({i + 1}/{max_retries})")
                time.sleep(retry_interval)
            if response.status_code != 200:
                print(traceback.format_exc())
                raise Exception(f"Error: {response.status_code}\nLast offset: {offset}\nBatch size: {batch_size}")

            results = response.json()["results"]
            has_next_batch = len(results) == batch_size
            offset += batch_size
            yield DataFrame(results)

__init__(api_key)

Parameters:

Name Type Description Default
api_key str | list[str]

API key(s) to use for the report

 required

Returns:

Type Description

None
Doc Author

minhpc@ikameglobal.com

Source code in applovin_report/revenue_reporting_api.py 
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def __init__(self, api_key: str | list[str]):
    """
    Args:
        api_key: API key(s) to use for the report

    Returns:
        None

    Doc Author:
        minhpc@ikameglobal.com
    """
    self.api_key = api_key

get_report(start_date=None, end_date=None, columns=None, limit=100000, max_retries=3, retry_interval=30, **kwargs)

Retrieve a report from the MAX Revenue Report API.

Parameters:

Name Type Description Default
start_date str

YYYY-MM-DD, within the last 45 days

 None
end_date str

YYYY-MM-DD, within the last 45 days

 None
columns list[str]

List of columns to include in the report

 None
limit int

Set the number of rows to return

 100000
max_retries int

Set the number of retries

 3
retry_interval int

Set the number of seconds to wait between retries

 30
**kwargs

Additional parameters to pass to the API

 {}

Returns:

Type Description
DataFrame

A pandas DataFrame containing the report data
Doc Author

minhpc@ikameglobal.com

Source code in applovin_report/revenue_reporting_api.py 
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def get_report(
    self,
    start_date: str = None,
    end_date: str = None,
    columns: list[str] = None,
    limit: int = 100000,
    max_retries: int = 3,
    retry_interval: int = 30,
    **kwargs,
) -> DataFrame:
    """
    Retrieve a report from the MAX Revenue Report API.


    Args:
        start_date: YYYY-MM-DD, within the last 45 days
        end_date: YYYY-MM-DD, within the last 45 days
        columns: List of columns to include in the report
        limit: Set the number of rows to return
        max_retries: Set the number of retries
        retry_interval: Set the number of seconds to wait between retries
        **kwargs: Additional parameters to pass to the API

    Returns:
        A pandas DataFrame containing the report data

    Doc Author:
        minhpc@ikameglobal.com
    """
    if not start_date or not end_date:
        start_date = (datetime.now() - timedelta(days=2)).strftime("%Y-%m-%d")
        end_date = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")

    params = {
        "api_key": self.api_key,
        "start": start_date,
        "end": end_date,
        "columns": ",".join(columns),
        "format": "json",
        "limit": limit,
        **kwargs,
    }

    for i in range(max_retries + 1):
        response = requests.get(url=RevenueReport.ENDPOINT, params=params)

        if response.status_code == 200:
            return DataFrame(response.json()["results"])
        else:
            print(f"Retrying... ({i + 1}/{max_retries})")
            time.sleep(retry_interval)

    print(traceback.format_exc())
    raise Exception(f"Error: {response.status_code}")

get_report_batch(start_date=None, end_date=None, columns=None, batch_size=100000, max_retries=3, retry_interval=30, **kwargs)

Retrieve a report from the MAX Revenue Report API in batches.

Parameters:

Name Type Description Default
start_date str

YYYY-MM-DD, within the last 45 days

 None
end_date str

YYYY-MM-DD, within the last 45 days

 None
columns list[str]

List of columns to include in the report

 None
batch_size int

Number of rows to return per batch

 100000
max_retries int

Number of retries

 3
retry_interval int

Number of seconds to wait between retries

 30
**kwargs

Additional parameters to pass to the API

 {}

Returns:

Type Description
Iterator[DataFrame]

A generator that yields a pandas DataFrame containing the report data
Doc Author

minhpc@ikameglobal.com

Source code in applovin_report/revenue_reporting_api.py 
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def get_report_batch(
    self,
    start_date: str = None,
    end_date: str = None,
    columns: list[str] = None,
    batch_size: int = 100000,
    max_retries: int = 3,
    retry_interval: int = 30,
    **kwargs,
) -> Iterator[DataFrame]:
    """
    Retrieve a report from the MAX Revenue Report API in batches.

    Args:
        start_date: YYYY-MM-DD, within the last 45 days
        end_date: YYYY-MM-DD, within the last 45 days
        columns: List of columns to include in the report
        batch_size: Number of rows to return per batch
        max_retries: Number of retries
        retry_interval: Number of seconds to wait between retries
        **kwargs: Additional parameters to pass to the API

    Returns:
        A generator that yields a pandas DataFrame containing the report data

    Doc Author:
        minhpc@ikameglobal.com
    """
    if not start_date or not end_date:
        start_date = (datetime.now() - timedelta(days=2)).strftime("%Y-%m-%d")
        end_date = (datetime.now() - timedelta(days=1)).strftime("%Y-%m-%d")

    offset = 0
    has_next_batch = True
    while has_next_batch:
        params = {
            "api_key": self.api_key,
            "start": start_date,
            "end": end_date,
            "columns": ",".join(columns),
            "format": "json",
            "offset": offset,
            "limit": batch_size,
            **kwargs,
        }

        response = None
        for i in range(max_retries + 1):
            response = requests.get(url=RevenueReport.ENDPOINT, params=params)
            if response.status_code == 200:
                break
            print(f"Retrying... ({i + 1}/{max_retries})")
            time.sleep(retry_interval)
        if response.status_code != 200:
            print(traceback.format_exc())
            raise Exception(f"Error: {response.status_code}\nLast offset: {offset}\nBatch size: {batch_size}")

        results = response.json()["results"]
        has_next_batch = len(results) == batch_size
        offset += batch_size
        yield DataFrame(results)