scan-google-sheet 0.1.1

Read public Google Sheets into Polars LazyFrames — no auth required

read-sheet

Read public Google Sheets into Polars DataFrames and LazyFrames — no auth, no service accounts, no API keys.

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Requirements

• Python ≥ 3.13
• The spreadsheet must be set to Anyone with the link can view

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Installation

pip install scan-google-sheet
# or
uv add scan-google-sheet

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Quick start

from scan_google_sheet import read_google_sheet, scan_google_sheet

Eager — returns a DataFrame immediately:

df = read_google_sheet("Sheet1", sheet_id="1BxiMVs0XRA5nFMdKvBdBZjgm...")

Lazy — returns a LazyFrame, participates in Polars query optimisation:

lf = scan_google_sheet("Sheet1", sheet_id="1BxiMVs0XRA5nFMdKvBdBZjgm...")

df = (
    lf
    .filter(pl.col("year") == 2025)
    .select("vessel", "amount")
    .collect()
)

You can also pass a full Google Sheets URL instead of a bare sheet ID:

df = read_google_sheet(
    "Sheet1",
    url="https://docs.google.com/spreadsheets/d/1BxiMVs0.../edit#gid=0",
)

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API

read_google_sheet

def read_google_sheet(
    sheet_name: str,
    sheet_id: str | None = None,
    url: str | None = None,
    *,
    timeout: int = 10,
    parse_dates: bool = True,
) -> pl.DataFrame

Fetches the sheet and returns a collected DataFrame. Use this when you want the data immediately and do not need lazy evaluation.

scan_google_sheet

def scan_google_sheet(
    sheet_name: str,
    sheet_id: str | None = None,
    url: str | None = None,
    *,
    timeout: int = 10,
    parse_dates: bool = True,
    batch_size: int = 1_000,
) -> pl.LazyFrame

Returns a LazyFrame registered via the Polars IO plugin API. Projection pushdown, predicate pushdown, head(), and streaming are all supported.

Note: Google Sheets does not support partial HTTP reads. The full sheet is always downloaded in one request. Pushdowns reduce processing cost, not network cost.

Parameters shared by both functions:

Parameter	Type	Default	Description
sheet_name	str	—	Tab name as shown in Google Sheets
sheet_id	str | None	None	Spreadsheet ID from the URL
url	str | None	None	Full Google Sheets URL (ID extracted automatically)
timeout	int	10	HTTP timeout in seconds
parse_dates	bool	True	Attempt automatic date/datetime parsing

Provide either sheet_id or url, not both.

---

URL utilities

from scan_google_sheet import extract_sheet_id, build_gviz_url, from_url

# Extract the sheet ID from any Google Sheets URL
sheet_id = extract_sheet_id("https://docs.google.com/spreadsheets/d/ABC123/edit")
# "ABC123"

# Build a gviz CSV export URL from a sheet ID and tab name
url = build_gviz_url("ABC123", "Sheet1")
# "https://docs.google.com/spreadsheets/d/ABC123/gviz/tq?tqx=out:csv&sheet=Sheet1"

# Build a gviz URL directly from a full Google Sheets URL
url = from_url("https://docs.google.com/spreadsheets/d/ABC123/edit", "Sheet1")

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Error handling

All exceptions inherit from ReadSheetError, so you can catch everything with one handler or branch on specific types:

from scan_google_sheet import (
    read_google_sheet,
    ReadSheetError,
    SheetFetchError,
    SheetURLError,
    SheetParseError,
    NetworkError,
    ConfigurationError,
)

try:
    df = read_google_sheet("Sheet1", sheet_id="...")
except ReadSheetError as e:
    match e:
        case SheetFetchError() if e.is_auth_error:
            print("Make the sheet public (Share → Anyone with the link)")
        case SheetFetchError() if e.is_not_found:
            print(f"Sheet not found — check the ID: {e.url}")
        case NetworkError():
            print(f"No connection: {e.cause}")
        case SheetURLError(raw=r):
            print(f"Could not parse URL: {r!r}")
        case SheetParseError():
            print(f"CSV parse failed: {e.cause}")
        case ConfigurationError():
            print(str(e))

Exception hierarchy

ReadSheetError
├── SheetURLError       malformed URL or unextractable sheet ID  (.raw)
├── SheetFetchError     non-200 HTTP response                    (.url, .status_code)
│                                                                (.is_auth_error, .is_not_found)
├── SheetParseError     CSV or Polars parsing failure            (.column)
├── NetworkError        transport failure, no response received  (.url)
└── ConfigurationError  invalid argument combination

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Making your sheet public

In Google Sheets: Share → Change to Anyone with the link → Viewer → Done.

The export URL used by this library (gviz/tq?tqx=out:csv) requires the sheet to be publicly readable. No data is ever written.

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How it works

Google Sheets URL / ID
        │
        ▼
  build_gviz_url()          constructs the CSV export URL
        │
        ▼
    fetch_raw()             httpx GET with follow_redirects=True
        │
        ▼
  pl.scan_csv()             parsed into a Polars LazyFrame
        │
        ▼
register_io_source()        registered as a Polars IO plugin
        │
        ▼
  LazyFrame / DataFrame     ready for your pipeline

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Development

git clone https://github.com/Attica-oss/scan_google_sheet
cd scan_google_sheet
uv sync --group dev
uv run pytest

Lint and format:

uv run ruff check src/ tests/
uv run ruff format src/ tests/
uv run ty check src/

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Changelog

0.1.0 (2025)

• Initial release
• read_google_sheet and scan_google_sheet
• Polars IO plugin for lazy evaluation
• Structured exception hierarchy
• Full test suite with pytest-httpx

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License

MIT © 2025 Attica-oss