def mangrove_by_country_latest_schema(data):
    return {
        "country_with_parent": str(data["country_with_parent"]),
        "original_pixels": int(data["original_pixels"]),
        "total_n_pixels": int(data["total_n_pixels"]),
        "cumulative_pixels_diff": int(data["cumulative_pixels_diff"]),
        "cumulative_pct_diff": float(data["cumulative_pct_diff"]),
    }

def mangrove_country_timeseries_schema(data):
    return {
        "year": str(data["year"]),
        "total_n_pixels": int(data["total_n_pixels"]),
    }

def mangrove_by_country_agg_schema(data):
    return {
        "country_with_parent": str(data["country_with_parent"]),
        "year": int(data["year"]),
        "total_pixels": int(data["total_pixels"])
    }

def bitcoin_business_growth_percent_diff_schema(data):
    return {
        "country_name": str(data["country_name"]),
        "date_range": str(f'{data["first_date"]} to {data["last_date"]}'),
        "first_value": int(data["first_value"]),
        "last_value": int(data["last_value"]),
        "difference": int(data["difference"]),
        "percent_difference": str(data["percent_difference"])
    }

def bitcoin_business_growth_timeseries_schema(data):
    return {
        "country_name": str(data["country_name"]),
        "date": data["date"],
        "cumulative_value": int(data["cumulative_value"])
    }

class DataSerializer:
    def __init__(self, schema_func):
        self.schema_func = schema_func

    def serialize_one(self, data) -> dict:
        return self.schema_func(dict( data ))

    def serialize_many(self, data_list) -> list:
        return [self.serialize_one(data) for data in data_list]