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