[polars] Fetch the FRED CSV with requests before parsing it

polars 2.0.0 (2026-10-06) reads a URL through its object store: it
sends a HEAD request for the file size, then ranged GETs. FRED's
fredgraph.csv answers HEAD with Content-Length: 0 (the body is ~14 kB),
and polars 2.0 then stalls instead of erroring. The lecture installs
the newest polars, so the FRED cell has hung until the 600 s cell
timeout since the release, failing the weekly cache build on
2026-10-12 (it passed on 2026-10-05).

Download the file with requests and pass the bytes to pl.read_csv.
This reads the same 918 rows with the date column parsed under both
polars 1.44.2 and 2.0.0. The sentence above the cell no longer says
read_csv fetches the URL itself.

All 52 code cells of the lecture run under polars 2.0.0 with live FRED
and Yahoo Finance data.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Wyb6EzbNzY5a8uuJPnDtUb

Author: claude

lectures/polars.md

@@ -544,7 +544,8 @@ As in {doc}`pandas`, Python makes it straightforward to query online databases.
 
 An important database for economists is [FRED](https://fred.stlouisfed.org/) --- a vast collection of time series data maintained by the St. Louis Fed.
 
-Polars' `read_csv` can fetch data from a URL directly.
+We download the CSV file with [requests](https://requests.readthedocs.io/en/latest/)
+and pass its contents to Polars' `read_csv`.
 
 We use `try_parse_dates=True` to parse the date column automatically
 
@@ -564,7 +565,10 @@ fred_url = ('https://fred.stlouisfed.org/graph/fredgraph.csv?'
             'fgst=lin&fgsnd=2020-02-01&line_index=1&'
             'transformation=lin&vintage_date=2024-07-29&'
             'revision_date=2024-07-29&nd=1948-01-01')
-data = pl.read_csv(fred_url, try_parse_dates=True)
+import requests
+
+r = requests.get(fred_url)
+data = pl.read_csv(r.content, try_parse_dates=True)
 ```
 
 Let's inspect the first few rows