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import io |
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import warnings |
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import zipfile |
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import httpx |
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import polars as pl |
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from datadex import materialize |
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def fetch_bytes( |
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url: str, |
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*, |
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timeout: float | httpx.Timeout = 120.0, |
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follow_redirects: bool = True, |
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) -> bytes: |
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"""Download the content at ``url`` and return the raw bytes. |
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The request is attempted with standard TLS verification. If that fails due to |
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certificate validation errors (common behind corporate proxies), a single |
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retry is performed with verification disabled while emitting a warning. |
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""" |
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headers = {"User-Agent": "datadex/0.1"} |
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try: |
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response = httpx.get( |
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url, |
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follow_redirects=follow_redirects, |
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timeout=timeout, |
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headers=headers, |
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) |
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except httpx.HTTPError as exc: |
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if "CERTIFICATE_VERIFY_FAILED" not in repr(exc): |
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raise |
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warnings.warn( |
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f"Falling back to insecure TLS download for {url}", |
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RuntimeWarning, |
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stacklevel=2, |
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) |
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else: |
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response.raise_for_status() |
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return response.content |
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response = httpx.get( |
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url, |
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follow_redirects=follow_redirects, |
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timeout=timeout, |
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headers=headers, |
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verify=False, |
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) |
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response.raise_for_status() |
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return response.content |
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def world_development_indicators() -> pl.DataFrame: |
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""" |
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World Development Indicators (WDI) is the World Bank's premier compilation of cross-country comparable data on development. |
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Bulk data download is available at https://datatopics.worldbank.org/world-development-indicators/ |
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""" |
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url = "https://databank.worldbank.org/data/download/WDI_CSV.zip" |
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archive_bytes = fetch_bytes(url, timeout=300.0) |
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with zipfile.ZipFile(io.BytesIO(archive_bytes)) as archive: |
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with archive.open("WDICSV.csv") as csv_file: |
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df = pl.read_csv(csv_file) |
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df = df.unpivot( |
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index=["Country Name", "Country Code", "Indicator Name", "Indicator Code"], |
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value_name="Indicator Value", |
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variable_name="Year", |
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) |
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df = df.with_columns(pl.col("Year").cast(pl.Int32)) |
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df = df.rename({ |
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"Country Name": "country_name", |
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"Country Code": "country_code", |
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"Indicator Name": "indicator_name", |
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"Indicator Code": "indicator_code", |
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"Year": "year", |
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"Indicator Value": "indicator_value", |
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}) |
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df = df.drop_nulls(subset=["indicator_value"]) |
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return df.sort(["country_code", "year", "indicator_code"]) |
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def main() -> None: |
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materialize(world_development_indicators) |
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if __name__ == "__main__": |
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main() |
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