`count`

Counts the number of rows in a data file. With DuckDB engine, counting is instant for supported formats.

# Count rows in CSV file
undatum count data.csv

# Count rows in JSONL file
undatum count data.jsonl

# Use DuckDB engine for faster counting
undatum count data.parquet --engine duckdb

# Named Excel sheet
undatum count workbook.xlsx --table Sheet2

# Rows matching a SQL condition
undatum count data.csv --where "amount > 100"

# Machine-readable result (undatum.count/1)
undatum count data.csv --json

Reference

Reads: any readable format · Writes: a number · Memory: streaming · Engines: auto, duckdb, python

undatum count [OPTIONS] INPUT_FILE

Argument	Description
`INPUT_FILE`	Path to input file. (required)

Option	Description	Default
`-d`, `--delimiter` TEXT	CSV delimiter character (auto-detected when omitted).
`--quotechar` TEXT	CSV quote character (iterabledata default '"' when omitted).
`--encoding` TEXT	File encoding (e.g., 'utf8', 'latin1').
`--verbose` / `--no-verbose`	Enable verbose logging output.	`--no-verbose`
`-F`, `--format-in` TEXT	Override file type detection (e.g., 'csv', 'jsonl').
`-e`, `--engine` [auto\|duckdb\|python]	Processing engine: auto (default), duckdb, or python.
`--table`, `--sheet` TEXT	Table or sheet name for multi-table sources (Excel, SQLite, lakehouse).
`--start-page` INTEGER	Sheet index (0-based) for Excel files.	`0`
`--trust`	Acknowledge pickle deserialization risk when reading pickle sources.
`--on-error` TEXT	Parse-error policy: raise (default), skip, or warn.
`--error-log` TEXT	Append parse errors as JSONL (use with --on-error skip or warn).
`-O`, `--format-out` TEXT	Output format: text (default) or json.
`--json`	Print the result as one JSON document (same as --format-out json).
`--where` TEXT	Keep records where this SQL condition is true (DuckDB syntax), e.g. "amount > 100 AND city = 'Berlin'". Text values are typed automatically.

Deprecated spellings (removed in 2.0): --filetype → --format-in.

Reference​

Reference