Jo2234 commented on code in PR #10361:
URL: https://github.com/apache/arrow-rs/pull/10361#discussion_r3694595338
##########
arrow-csv/src/reader/mod.rs:
##########
@@ -351,6 +351,85 @@ impl Format {
self
}
+ /// Infer format settings from the CSV records in `reader`
+ ///
+ /// This currently infers whether the first record is a header. Up to
+ /// `max_records` records after the first record are inspected; if `None`,
all
+ /// records are read. Detection is conservative and returns no header when
the
+ /// sampled records do not provide type evidence.
+ ///
+ /// # Example
+ ///
+ /// ```
+ /// use arrow_csv::reader::Format;
+ /// use std::io::Cursor;
+ ///
+ /// let csv = "name,count\nalice,1\nbob,2\n";
+ /// let format = Format::default().infer_format(Cursor::new(csv),
Some(10))?;
+ /// let (schema, records_read) = format.infer_schema(Cursor::new(csv),
None)?;
+ ///
+ /// assert_eq!(schema.field(0).name(), "name");
+ /// assert_eq!(records_read, 2);
+ /// # Ok::<_, arrow_schema::ArrowError>(())
+ /// ```
+ pub fn infer_format<R: Read>(
+ mut self,
+ reader: R,
+ max_records: Option<usize>,
+ ) -> Result<Self, ArrowError> {
Review Comment:
Yes — `infer_format` now returns `(Format, usize)` in 77c1ce74. The count
includes the first header candidate; tests cover empty, bounded, and full
samples. Final head 454a0980 passes the focused tests, umbrella Arrow CSV
tests, Clippy, rustfmt, and diff checks.
##########
arrow-csv/src/reader/mod.rs:
##########
@@ -351,6 +351,85 @@ impl Format {
self
}
+ /// Infer format settings from the CSV records in `reader`
+ ///
+ /// This currently infers whether the first record is a header. Up to
+ /// `max_records` records after the first record are inspected; if `None`,
all
+ /// records are read. Detection is conservative and returns no header when
the
+ /// sampled records do not provide type evidence.
+ ///
+ /// # Example
+ ///
+ /// ```
+ /// use arrow_csv::reader::Format;
+ /// use std::io::Cursor;
+ ///
+ /// let csv = "name,count\nalice,1\nbob,2\n";
+ /// let format = Format::default().infer_format(Cursor::new(csv),
Some(10))?;
+ /// let (schema, records_read) = format.infer_schema(Cursor::new(csv),
None)?;
+ ///
+ /// assert_eq!(schema.field(0).name(), "name");
+ /// assert_eq!(records_read, 2);
+ /// # Ok::<_, arrow_schema::ArrowError>(())
+ /// ```
+ pub fn infer_format<R: Read>(
+ mut self,
+ reader: R,
+ max_records: Option<usize>,
+ ) -> Result<Self, ArrowError> {
+ self.header = self.infer_header(reader, max_records)?;
+ Ok(self)
+ }
+
+ /// Infer whether the first CSV record is a header
+ ///
+ /// Inspects up to `max_records` records after the first record. Returns
`true`
+ /// when a value in the first record is text while the remaining values in
the
+ /// same column have a consistent non-text type.
+ fn infer_header<R: Read>(
+ &self,
+ reader: R,
+ max_records: Option<usize>,
+ ) -> Result<bool, ArrowError> {
+ let mut format = self.clone();
+ format.header = false;
+ let mut csv_reader = format.build_reader(reader);
+
+ let mut first_record = StringRecord::new();
+ if !csv_reader
+ .read_record(&mut first_record)
+ .map_err(map_csv_error)?
+ {
+ return Ok(false);
+ }
+
+ let mut first_types = vec![InferredDataType::default();
first_record.len()];
+ for (value, inferred) in first_record.iter().zip(&mut first_types) {
+ if !self.null_regex.is_null(value) {
+ inferred.update(value);
+ }
+ }
Review Comment:
Good catch. I updated numeric inference to accept a leading `+` for integers
and decimals, so `+1` is not treated as a header. The new regression covers
both `+1` and `+1.5` inputs; the full arrow-csv suite and umbrella Arrow CSV
tests pass on 454a0980.
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