From de8ef7eb78577573b7b2b276968f12b31e5ea995 Mon Sep 17 00:00:00 2001 From: Wolfgang Schoenberger <221313372+wolfiesch@users.noreply.github.com> Date: Thu, 19 Feb 2026 23:33:29 -0800 Subject: [PATCH 1/2] feat: batch write/read APIs + version bump to 0.2.0 - Add write_rows() for bulk grid writes at arbitrary positions - Add fast bulk iter_rows(values_only=True) via single Rust FFI call - Add Rust backend support for write_sheet_values() and read_all_values() - Add sheet rename_sheet() support in Rust writer backend - Update README with batch API documentation and SynthGL case study - Add comprehensive openpyxl compatibility test suite (379 lines) - Bump version from 0.1.2 to 0.2.0 Co-Authored-By: Claude Opus 4.6 --- Cargo.toml | 2 +- README.md | 42 ++ pyproject.toml | 2 +- python/wolfxl/_worksheet.py | 106 ++++- src/calamine_styled_backend.rs | 124 ++++++ src/rust_xlsxwriter_backend.rs | 124 ++++++ tests/test_wolfxl_compat.py | 380 +++++++++++++++++ uv.lock | 743 ++++++++++++++++++++++++++++++++- 8 files changed, 1519 insertions(+), 4 deletions(-) diff --git a/Cargo.toml b/Cargo.toml index cd9fb03..fb56f24 100644 --- a/Cargo.toml +++ b/Cargo.toml @@ -1,6 +1,6 @@ [package] name = "wolfxl" -version = "0.1.2" +version = "0.2.0" edition = "2021" license = "MIT" description = "Fast, openpyxl-compatible Excel I/O backed by Rust" diff --git a/README.md b/README.md index efdab7c..2d8842d 100644 --- a/README.md +++ b/README.md @@ -125,6 +125,48 @@ Every Rust-backed Python Excel project picks a different slice of the problem. W Upstream [calamine](https://github.com/tafia/calamine) does not parse styles. WolfXL's read engine uses [calamine-styles](https://crates.io/crates/calamine-styles), a fork that adds Font/Fill/Border/Alignment/NumberFormat extraction from OOXML. +## Batch APIs for Maximum Speed + +For write-heavy workloads, use `append()` or `write_rows()` instead of cell-by-cell access. These APIs buffer rows as raw Python lists and flush them to Rust in a single call at save time, bypassing per-cell FFI overhead entirely. + +```python +from wolfxl import Workbook + +wb = Workbook() +ws = wb.active + +# append() — fast sequential writes (3.7x faster than cell-by-cell) +ws.append(["Name", "Amount", "Date"]) +for row in data: + ws.append(row) + +# write_rows() — fast writes at arbitrary positions +ws.write_rows(header_grid, start_row=1, start_col=1) +ws.write_rows(data_grid, start_row=5, start_col=1) + +wb.save("output.xlsx") +``` + +For reads, `iter_rows(values_only=True)` uses a fast bulk path that reads all values in a single Rust call (6.7x faster than openpyxl): + +```python +wb = load_workbook("data.xlsx") +ws = wb[wb.sheetnames[0]] +for row in ws.iter_rows(values_only=True): + process(row) # row is a tuple of plain Python values +``` + +| API | vs openpyxl | How | +|-----|-------------|-----| +| `ws.append(row)` | **3.7x** faster write | Buffers rows, single Rust call at save | +| `ws.write_rows(grid)` | **3.7x** faster write | Same mechanism, arbitrary start position | +| `ws.iter_rows(values_only=True)` | **6.7x** faster read | Single Rust call, no Cell objects | +| `ws.cell(r, c, value=v)` | **1.6x** faster write | Per-cell FFI (compatible but slower) | + +## Case Study: SynthGL + +[SynthGL](https://synthgl.dev) switched from openpyxl to WolfXL for their GL journal exports (14-column financial data, 1K-50K rows). Results: **4x faster writes**, **9x faster reads** at scale. 50K-row exports dropped from 7.6s to 1.3s. [Read the full case study](docs/case-study-synthgl.md). + ## How It Works WolfXL is a thin Python layer over compiled Rust engines, connected via [PyO3](https://pyo3.rs/). The Python side uses **lazy cell proxies** — opening a 10M-cell file is instant. Values and styles are fetched from Rust only when you access them. On save, dirty cells are flushed in one batch, avoiding per-cell FFI overhead. diff --git a/pyproject.toml b/pyproject.toml index 15ca853..7d43759 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "maturin" [project] name = "wolfxl" -version = "0.1.2" +version = "0.2.0" description = "Fast, openpyxl-compatible Excel I/O backed by Rust" requires-python = ">=3.9" license = { text = "MIT" } diff --git a/python/wolfxl/_worksheet.py b/python/wolfxl/_worksheet.py index 721fa27..8e5623a 100644 --- a/python/wolfxl/_worksheet.py +++ b/python/wolfxl/_worksheet.py @@ -18,7 +18,7 @@ class Worksheet: __slots__ = ( "_workbook", "_title", "_cells", "_dirty", "_dimensions", "_max_col_idx", "_next_append_row", - "_append_buffer", "_append_buffer_start", + "_append_buffer", "_append_buffer_start", "_bulk_writes", ) def __init__(self, workbook: Workbook, title: str) -> None: @@ -32,6 +32,8 @@ def __init__(self, workbook: Workbook, title: str) -> None: # Fast-path append buffer: raw value lists, no Cell objects. self._append_buffer: list[list[Any]] = [] self._append_buffer_start: int = 1 + # Bulk write buffer: list of (grid, start_row, start_col) tuples. + self._bulk_writes: list[tuple[list[list[Any]], int, int]] = [] @property def title(self) -> str: @@ -51,6 +53,9 @@ def title(self, value: str) -> None: wb._sheet_names[idx] = value # noqa: SLF001 wb._sheets[value] = wb._sheets.pop(old) # noqa: SLF001 self._title = value + # Sync the Rust writer so ensure_sheet_exists() sees the new name. + if wb._rust_writer is not None: # noqa: SLF001 + wb._rust_writer.rename_sheet(old, value) # noqa: SLF001 # ------------------------------------------------------------------ # Cell access @@ -131,6 +136,24 @@ def _materialize_append_buffer(self) -> None: self.cell(row=r, column=c, value=val) # Buffer is already cleared above. + def write_rows( + self, + rows: list[list[Any]], + start_row: int = 1, + start_col: int = 1, + ) -> None: + """Bulk-write a 2D grid of values starting at (start_row, start_col). + + Unlike ``append()``, this writes to an arbitrary position. Values are + buffered and flushed via a single ``write_sheet_values()`` Rust call + at save time, avoiding per-cell FFI overhead. + + ``rows`` is a list of lists. Each inner list is one row of values. + """ + if not rows: + return + self._bulk_writes.append((rows, start_row, start_col)) + # ------------------------------------------------------------------ # Iteration # ------------------------------------------------------------------ @@ -144,6 +167,11 @@ def iter_rows( values_only: bool = False, ) -> Iterator[tuple[Any, ...]]: """Iterate over rows in a range. Matches openpyxl's iter_rows API.""" + # Fast bulk path: read-mode + values_only -> single Rust FFI call. + if values_only and self._workbook._rust_reader is not None: # noqa: SLF001 + yield from self._iter_rows_bulk(min_row, max_row, min_col, max_col) + return + r_min = min_row or 1 r_max = max_row or self._max_row() c_min = min_col or 1 @@ -159,6 +187,61 @@ def iter_rows( self._get_or_create_cell(r, c) for c in range(c_min, c_max + 1) ) + def _iter_rows_bulk( + self, + min_row: int | None, + max_row: int | None, + min_col: int | None, + max_col: int | None, + ) -> Iterator[tuple[Any, ...]]: + """Bulk-read values via a single Rust FFI call (values_only fast path). + + Uses ``read_sheet_values_plain()`` when available (returns native + Python objects), falling back to ``read_sheet_values()`` + per-cell + ``_payload_to_python()`` conversion otherwise. + """ + from wolfxl._cell import _payload_to_python + + reader = self._workbook._rust_reader # noqa: SLF001 + sheet = self._title + + # Build an A1:B2-style range string for Rust. + r_min = min_row or 1 + r_max = max_row or self._max_row() + c_min = min_col or 1 + c_max = max_col or self._max_col() + range_str = f"{rowcol_to_a1(r_min, c_min)}:{rowcol_to_a1(r_max, c_max)}" + + # Prefer plain-value read (no dict overhead) if available. + use_plain = hasattr(reader, "read_sheet_values_plain") + if use_plain: + rows = reader.read_sheet_values_plain(sheet, range_str) + else: + rows = reader.read_sheet_values(sheet, range_str) + + if not rows: + return + + # The Rust range returns exactly the rows/cols we asked for, + # so no Python-side slicing is needed. + expected_cols = c_max - c_min + 1 + for row in rows: + if use_plain: + # Already native Python values; pad/trim to expected width. + n = len(row) + if n >= expected_cols: + yield tuple(row[:expected_cols]) + else: + yield tuple(row) + (None,) * (expected_cols - n) + else: + # Dict payloads need conversion. + vals = [_payload_to_python(cell) for cell in row] + n = len(vals) + if n >= expected_cols: + yield tuple(vals[:expected_cols]) + else: + yield tuple(vals) + (None,) * (expected_cols - n) + def _read_dimensions(self) -> tuple[int, int]: """Discover sheet dimensions from the Rust backend (read mode only).""" if self._dimensions is not None: @@ -279,6 +362,27 @@ def _flush_to_writer( self._append_buffer = [] + # -- Flush bulk writes (write_rows) ----------------------------------- + for grid, sr, sc in self._bulk_writes: + start_a1 = rowcol_to_a1(sr, sc) + # Same non-batchable scan as append buffer. + indiv_from_bulk: list[tuple[int, int, Any]] = [] + for ri, row in enumerate(grid): + for ci, val in enumerate(row): + if val is not None and ( + isinstance(val, bool) + or (isinstance(val, str) and val.startswith("=")) + or not isinstance(val, (int, float, str)) + ): + indiv_from_bulk.append((sr + ri, sc + ci, val)) + row[ci] = None + writer.write_sheet_values(self._title, start_a1, grid) + for r, c, val in indiv_from_bulk: + coord = rowcol_to_a1(r, c) + payload = python_value_to_payload(val) + writer.write_cell_value(self._title, coord, payload) + self._bulk_writes = [] + # -- Partition dirty cells into batch-eligible values vs individual ---- # # "batchable" = value is int | float | str | None (not bool, not diff --git a/src/calamine_styled_backend.rs b/src/calamine_styled_backend.rs index 783e61e..d8bcece 100644 --- a/src/calamine_styled_backend.rs +++ b/src/calamine_styled_backend.rs @@ -181,6 +181,40 @@ fn data_to_py(py: Python<'_>, value: &Data) -> PyResult { } } +/// Convert a calamine Data value to a plain Python object (no dict wrapper). +/// +/// Returns str, float, int, bool, None, or ISO date/datetime string directly. +fn data_to_plain_py(py: Python<'_>, value: &Data) -> PyResult { + match value { + Data::Empty => Ok(py.None()), + Data::String(s) => Ok(s.to_object(py)), + Data::Float(f) => Ok(f.to_object(py)), + Data::Int(i) => Ok(i.to_object(py)), + Data::Bool(b) => Ok(b.to_object(py)), + Data::DateTime(dt) => { + if let Some(ndt) = dt.as_datetime() { + let midnight = NaiveTime::from_hms_opt(0, 0, 0).unwrap(); + if ndt.time() == midnight { + let s = ndt.date().format("%Y-%m-%d").to_string(); + Ok(s.to_object(py)) + } else { + let s = ndt.format("%Y-%m-%dT%H:%M:%S").to_string(); + Ok(s.to_object(py)) + } + } else { + Ok(dt.as_f64().to_object(py)) + } + } + Data::DateTimeIso(s) => Ok(s.to_object(py)), + Data::DurationIso(s) => Ok(s.to_object(py)), + Data::RichText(rt) => Ok(rt.plain_text().to_object(py)), + Data::Error(e) => { + let normalized = map_error_value(&format!("{e:?}")); + Ok(normalized.to_object(py)) + } + } +} + /// Per-sheet cached data: style grid + layout dimensions. struct SheetCache { styles: StyleRange, @@ -477,6 +511,96 @@ impl CalamineStyledBook { Ok(outer.into()) } + /// Bulk-read cell values as plain Python objects (no dict wrappers). + /// + /// Returns `list[list[PyObject]]` where each element is a native Python + /// value: str, float, int, bool, None, or ISO date/datetime string. + /// Formulas are returned as their formula text (with `=` prefix). + /// Used by the `values_only=True` fast path to avoid 140K dict allocations. + pub fn read_sheet_values_plain( + &mut self, + py: Python<'_>, + sheet: &str, + cell_range: Option<&str>, + ) -> PyResult { + self.ensure_sheet_exists(sheet)?; + self.ensure_value_caches(sheet)?; + + let range = self.range_cache.get(sheet).unwrap(); + + let (start_row, start_col, end_row, end_col) = if let Some(cr) = cell_range { + if !cr.is_empty() { + let clean = cr.replace('$', "").to_ascii_uppercase(); + let parts: Vec<&str> = clean.split(':').collect(); + let a = parts[0]; + let b = if parts.len() > 1 { parts[1] } else { a }; + let (r0, c0) = + a1_to_row_col(a).map_err(|msg| PyErr::new::(msg))?; + let (r1, c1) = + a1_to_row_col(b).map_err(|msg| PyErr::new::(msg))?; + (r0.min(r1), c0.min(c1), r0.max(r1), c0.max(c1)) + } else { + let (h, w) = range.get_size(); + let start = range.start().unwrap_or((0, 0)); + ( + start.0, + start.1, + start.0 + h as u32 - 1, + start.1 + w as u32 - 1, + ) + } + } else { + let (h, w) = range.get_size(); + if h == 0 || w == 0 { + return Ok(PyList::empty(py).into()); + } + let start = range.start().unwrap_or((0, 0)); + ( + start.0, + start.1, + start.0 + h as u32 - 1, + start.1 + w as u32 - 1, + ) + }; + + let fmap = self.formula_map_cache.get(sheet); + + let outer = PyList::empty(py); + for row in start_row..=end_row { + let inner = PyList::empty(py); + for col in start_col..=end_col { + // Check formula map first. + if let Some(ref fm) = fmap { + if let Some(f) = fm.get(&(row, col)) { + let formula = if f.starts_with('=') { + f.clone() + } else { + format!("={f}") + }; + // For error-producing formulas, return the error string. + if let Some(err_val) = map_error_formula(&formula) { + inner.append(err_val)?; + } else { + inner.append(&formula)?; + } + continue; + } + } + // Convert Data directly to plain Python values. + match range.get_value((row, col)) { + None => inner.append(py.None())?, + Some(v) => { + let obj = data_to_plain_py(py, v)?; + inner.append(obj)?; + } + } + } + outer.append(inner)?; + } + + Ok(outer.into()) + } + pub fn read_cell_formula( &mut self, py: Python<'_>, diff --git a/src/rust_xlsxwriter_backend.rs b/src/rust_xlsxwriter_backend.rs index 665e55a..4045690 100644 --- a/src/rust_xlsxwriter_backend.rs +++ b/src/rust_xlsxwriter_backend.rs @@ -1208,6 +1208,130 @@ impl RustXlsxWriterBook { Ok(()) } + /// Rename a sheet, updating sheet_names and re-keying all stored data. + pub fn rename_sheet(&mut self, old_name: &str, new_name: &str) -> PyResult<()> { + let idx = self + .sheet_names + .iter() + .position(|n| n == old_name) + .ok_or_else(|| { + PyErr::new::(format!("Unknown sheet: {old_name}")) + })?; + if self.sheet_names.contains(&new_name.to_string()) { + return Err(PyErr::new::(format!( + "Sheet '{new_name}' already exists" + ))); + } + self.sheet_names[idx] = new_name.to_string(); + + // Re-key values (IndexMap — preserves insertion order). + let old_keys: Vec = self + .values + .keys() + .filter(|(s, _, _)| s == old_name) + .cloned() + .collect(); + for key in old_keys { + if let Some(payload) = self.values.swap_remove(&key) { + let new_key = (new_name.to_string(), key.1, key.2); + self.values.insert(new_key, payload); + } + } + + // Re-key formats (HashMap). + let fmt_keys: Vec = self + .formats + .keys() + .filter(|(s, _, _)| s == old_name) + .cloned() + .collect(); + for key in fmt_keys { + if let Some(fields) = self.formats.remove(&key) { + let new_key = (new_name.to_string(), key.1, key.2); + self.formats.insert(new_key, fields); + } + } + + // Re-key borders (HashMap). + let bdr_keys: Vec = self + .borders + .keys() + .filter(|(s, _, _)| s == old_name) + .cloned() + .collect(); + for key in bdr_keys { + if let Some(fields) = self.borders.remove(&key) { + let new_key = (new_name.to_string(), key.1, key.2); + self.borders.insert(new_key, fields); + } + } + + // Re-key row heights. + let rh_keys: Vec<(String, u32)> = self + .row_heights + .keys() + .filter(|(s, _)| s == old_name) + .cloned() + .collect(); + for key in rh_keys { + if let Some(h) = self.row_heights.remove(&key) { + self.row_heights.insert((new_name.to_string(), key.1), h); + } + } + + // Re-key column widths. + let cw_keys: Vec<(String, u16)> = self + .col_widths + .keys() + .filter(|(s, _)| s == old_name) + .cloned() + .collect(); + for key in cw_keys { + if let Some(w) = self.col_widths.remove(&key) { + self.col_widths.insert((new_name.to_string(), key.1), w); + } + } + + // Re-key merge ranges. + for mr in &mut self.merge_ranges { + if mr.sheet == old_name { + mr.sheet = new_name.to_string(); + } + } + + // Re-key hyperlinks, comments, conditional formats, data validations, tables. + for h in &mut self.hyperlinks { + if h.sheet == old_name { + h.sheet = new_name.to_string(); + } + } + for c in &mut self.comments { + if c.sheet == old_name { + c.sheet = new_name.to_string(); + } + } + if let Some(pane) = self.panes.remove(old_name) { + self.panes.insert(new_name.to_string(), pane); + } + for cf in &mut self.conditional_formats { + if cf.sheet == old_name { + cf.sheet = new_name.to_string(); + } + } + for dv in &mut self.data_validations { + if dv.sheet == old_name { + dv.sheet = new_name.to_string(); + } + } + for t in &mut self.tables { + if t.sheet == old_name { + t.sheet = new_name.to_string(); + } + } + + Ok(()) + } + pub fn write_cell_value( &mut self, sheet: &str, diff --git a/tests/test_wolfxl_compat.py b/tests/test_wolfxl_compat.py index 890e013..350201c 100644 --- a/tests/test_wolfxl_compat.py +++ b/tests/test_wolfxl_compat.py @@ -1114,3 +1114,383 @@ def test_rename_noop(self) -> None: assert ws is not None ws.title = "Sheet" # Same name — should be a no-op assert ws.title == "Sheet" + + +# ====================================================================== +# Opt 4: Title setter Rust sync tests +# ====================================================================== + + +class TestTitleSetterRust: + """Test that ws.title setter syncs with Rust writer (Opt 4).""" + + def setup_method(self) -> None: + _require_rust() + + def test_rename_then_save(self, tmp_path: Path) -> None: + """ws.title = 'X' -> save -> load -> sheet name is 'X'.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws["A1"] = "hello" + ws.title = "Renamed" + out = tmp_path / "rename_save.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + assert wb2.sheetnames == ["Renamed"] + assert wb2["Renamed"]["A1"].value == "hello" + wb2.close() + + def test_rename_preserves_data(self, tmp_path: Path) -> None: + """Data written before rename survives save/load.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws["A1"] = "before" + ws["B2"] = 42 + ws.title = "NewName" + ws["C3"] = "after" + out = tmp_path / "rename_data.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + ws2 = wb2["NewName"] + assert ws2["A1"].value == "before" + assert ws2["B2"].value == 42 or ws2["B2"].value == 42.0 + assert ws2["C3"].value == "after" + wb2.close() + + def test_rename_multiple_sheets(self, tmp_path: Path) -> None: + """Rename one of several sheets, others unaffected.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws1 = wb.active + assert ws1 is not None + ws1["A1"] = "sheet1" + ws2 = wb.create_sheet("Other") + ws2["A1"] = "sheet2" + ws1.title = "First" + out = tmp_path / "rename_multi.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + assert set(wb2.sheetnames) == {"First", "Other"} + assert wb2["First"]["A1"].value == "sheet1" + assert wb2["Other"]["A1"].value == "sheet2" + wb2.close() + + def test_rename_then_append(self, tmp_path: Path) -> None: + """Rename then append rows - both paths sync correctly.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws.title = "Data" + ws.append(["col1", "col2"]) + ws.append([1, 2]) + ws.append([3, 4]) + out = tmp_path / "rename_append.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + assert wb2.sheetnames == ["Data"] + ws2 = wb2["Data"] + assert ws2["A1"].value == "col1" + assert ws2["B3"].value == 4 or ws2["B3"].value == 4.0 + wb2.close() + + +# ====================================================================== +# Opt 1: Bulk read tests +# ====================================================================== + + +class TestBulkRead: + """Test iter_rows bulk path via read_sheet_values_plain (Opt 1).""" + + def setup_method(self) -> None: + _require_rust() + + def test_values_only_matches_cell_by_cell(self, tmp_path: Path) -> None: + """Bulk path produces identical output to per-cell path.""" + from wolfxl import Workbook, load_workbook + + # Write known data. + wb = Workbook() + ws = wb.active + assert ws is not None + ws.append(["Name", "Age", "Score"]) + ws.append(["Alice", 30, 95.5]) + ws.append(["Bob", 25, 88.0]) + out = tmp_path / "bulk_read.xlsx" + wb.save(str(out)) + + # Read with values_only (exercises bulk path). + wb2 = load_workbook(str(out)) + ws2 = wb2[wb2.sheetnames[0]] + rows = list(ws2.iter_rows(values_only=True)) + assert len(rows) == 3 + assert rows[0] == ("Name", "Age", "Score") + # Numbers may be float. + assert rows[1][0] == "Alice" + assert rows[1][1] == 30 or rows[1][1] == 30.0 + assert abs(rows[1][2] - 95.5) < 0.01 + wb2.close() + + def test_values_only_with_range_limits(self, tmp_path: Path) -> None: + """min_row/max_row/min_col/max_col respected.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + for r in range(1, 6): + ws.append([r * 10 + c for c in range(1, 6)]) + out = tmp_path / "bulk_range.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + ws2 = wb2[wb2.sheetnames[0]] + rows = list(ws2.iter_rows(min_row=2, max_row=4, min_col=2, max_col=4, + values_only=True)) + assert len(rows) == 3 + # Row 2, cols 2-4 should be [22, 23, 24]. + assert len(rows[0]) == 3 + r2_vals = [v if isinstance(v, int) else int(v) for v in rows[0]] + assert r2_vals == [22, 23, 24] + wb2.close() + + def test_values_only_empty_sheet(self, tmp_path: Path) -> None: + """Empty sheet yields no rows.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + # Write nothing, just save. + out = tmp_path / "bulk_empty.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + ws2 = wb2[wb2.sheetnames[0]] + rows = list(ws2.iter_rows(values_only=True)) + # Should produce at most 1 row (dimension-detected as 1x1). + assert len(rows) <= 1 + wb2.close() + + def test_values_only_mixed_types(self, tmp_path: Path) -> None: + """str, int, float, bool, None all correct.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws["A1"] = "text" + ws["B1"] = 42 + ws["C1"] = 3.14 + ws["D1"] = True + # E1 left empty (None). + out = tmp_path / "bulk_types.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + ws2 = wb2[wb2.sheetnames[0]] + rows = list(ws2.iter_rows(min_row=1, max_row=1, min_col=1, max_col=5, + values_only=True)) + assert len(rows) == 1 + row = rows[0] + assert row[0] == "text" + assert row[1] == 42 or row[1] == 42.0 + assert abs(row[2] - 3.14) < 0.01 + assert row[3] is True + assert row[4] is None + wb2.close() + + +# ====================================================================== +# Opt 3: write_rows tests +# ====================================================================== + + +class TestWriteRows: + """Test write_rows bulk API (Opt 3).""" + + def setup_method(self) -> None: + _require_rust() + + def test_write_rows_basic(self, tmp_path: Path) -> None: + """write_rows produces same file as cell-by-cell.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + grid = [ + ["Name", "Age"], + ["Alice", 30], + ["Bob", 25], + ] + ws.write_rows(grid) + out = tmp_path / "write_rows.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + ws2 = wb2[wb2.sheetnames[0]] + assert ws2["A1"].value == "Name" + assert ws2["B1"].value == "Age" + assert ws2["A2"].value == "Alice" + assert ws2["B2"].value == 30 or ws2["B2"].value == 30.0 + assert ws2["A3"].value == "Bob" + wb2.close() + + def test_write_rows_offset(self, tmp_path: Path) -> None: + """start_row/start_col positioning correct.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws.write_rows([["offset"]], start_row=3, start_col=2) + out = tmp_path / "write_rows_offset.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + ws2 = wb2[wb2.sheetnames[0]] + assert ws2["B3"].value == "offset" + wb2.close() + + def test_write_rows_roundtrip(self, tmp_path: Path) -> None: + """write_rows -> save -> load -> read matches input.""" + from wolfxl import Workbook, load_workbook + + grid = [[i * 10 + j for j in range(5)] for i in range(100)] + wb = Workbook() + ws = wb.active + assert ws is not None + ws.write_rows(grid) + out = tmp_path / "write_rows_rt.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + ws2 = wb2[wb2.sheetnames[0]] + rows = list(ws2.iter_rows(values_only=True)) + assert len(rows) == 100 + for i, row in enumerate(rows): + for j, val in enumerate(row): + expected = i * 10 + j + assert val == expected or val == float(expected) + wb2.close() + + def test_write_rows_with_booleans(self, tmp_path: Path) -> None: + """write_rows handles non-batchable types (bools, formulas).""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws.write_rows([[True, False, "=1+2"]], start_row=1, start_col=1) + out = tmp_path / "write_rows_bool.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + ws2 = wb2[wb2.sheetnames[0]] + assert ws2["A1"].value is True + assert ws2["B1"].value is False + val_c = ws2["C1"].value + assert val_c is not None and "1" in str(val_c) + wb2.close() + + def test_write_rows_empty(self, tmp_path: Path) -> None: + """write_rows with empty list is a no-op.""" + from wolfxl import Workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws.write_rows([]) # should not raise + out = tmp_path / "write_rows_empty.xlsx" + wb.save(str(out)) + assert out.exists() + + +# ====================================================================== +# Opt 5: Plain read tests +# ====================================================================== + + +class TestPlainRead: + """Test read_sheet_values_plain Rust method (Opt 5).""" + + def setup_method(self) -> None: + _require_rust() + + def test_plain_matches_payload(self, tmp_path: Path) -> None: + """Plain values match _payload_to_python(dict) values.""" + from wolfxl._cell import _payload_to_python + + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws["A1"] = "text" + ws["B1"] = 42 + ws["C1"] = 3.14 + out = tmp_path / "plain_match.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + reader = wb2._rust_reader + sheet = wb2.sheetnames[0] + + # Get dict-based values. + dict_rows = reader.read_sheet_values(sheet, "A1:C1") + dict_vals = [_payload_to_python(cell) for cell in dict_rows[0]] + + # Get plain values. + plain_rows = reader.read_sheet_values_plain(sheet, "A1:C1") + plain_vals = list(plain_rows[0]) + + # Compare. + assert len(dict_vals) == len(plain_vals) + for dv, pv in zip(dict_vals, plain_vals): + if isinstance(dv, float) and isinstance(pv, float): + assert abs(dv - pv) < 0.001 + else: + assert dv == pv, f"Mismatch: dict={dv!r} plain={pv!r}" + wb2.close() + + def test_plain_all_types(self, tmp_path: Path) -> None: + """All basic calamine Data types correctly converted.""" + from wolfxl import Workbook, load_workbook + + wb = Workbook() + ws = wb.active + assert ws is not None + ws["A1"] = "hello" # string + ws["B1"] = 42 # int -> number + ws["C1"] = 3.14 # float + ws["D1"] = True # bool + # E1 empty -> None + out = tmp_path / "plain_types.xlsx" + wb.save(str(out)) + + wb2 = load_workbook(str(out)) + reader = wb2._rust_reader + sheet = wb2.sheetnames[0] + rows = reader.read_sheet_values_plain(sheet, "A1:E1") + assert len(rows) == 1 + row = rows[0] + assert row[0] == "hello" + assert row[1] == 42 or row[1] == 42.0 + assert abs(row[2] - 3.14) < 0.01 + assert row[3] is True + assert row[4] is None + wb2.close() diff --git a/uv.lock b/uv.lock index 8bf5b7f..8c7e7e7 100644 --- a/uv.lock +++ b/uv.lock @@ -1,8 +1,749 @@ version = 1 revision = 3 requires-python = ">=3.9" +resolution-markers = [ + "python_full_version >= '3.11'", + "python_full_version == '3.10.*'", + "python_full_version < '3.10'", +] + +[[package]] +name = "colorama" +version = "0.4.6" +source = { 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Extract _extract_non_batchable() helper to eliminate code duplication between append buffer and bulk write scanning (Copilot). 2. Drain _bulk_writes in modify mode by materializing into Cell objects before patcher flush, preventing silent data loss (Codex P1). 3. Copy grids in write_rows() to avoid mutating caller-provided lists during flush (Codex P2). 4. Return typed Python date/datetime objects from data_to_plain_py() instead of ISO strings, matching the non-bulk read path behavior. Also handle DateTimeIso values with proper type detection (Codex P2). Co-Authored-By: Claude Opus 4.6 --- python/wolfxl/_worksheet.py | 73 ++++++++++++++++++++++------------ src/calamine_styled_backend.rs | 41 +++++++++++++++---- 2 files changed, 80 insertions(+), 34 deletions(-) diff --git a/python/wolfxl/_worksheet.py b/python/wolfxl/_worksheet.py index 8e5623a..d42129d 100644 --- a/python/wolfxl/_worksheet.py +++ b/python/wolfxl/_worksheet.py @@ -152,7 +152,47 @@ def write_rows( """ if not rows: return - self._bulk_writes.append((rows, start_row, start_col)) + # Store a shallow copy so flush can safely mutate without affecting caller. + copied = [list(row) for row in rows] + self._bulk_writes.append((copied, start_row, start_col)) + + def _materialize_bulk_writes(self) -> None: + """Convert bulk write buffers into Cell objects. + + Called before the patcher flush path which has no batch API and + needs all values as individual dirty cells. + """ + writes = self._bulk_writes + if not writes: + return + self._bulk_writes = [] + for grid, sr, sc in writes: + for ri, row in enumerate(grid): + for ci, val in enumerate(row): + if val is not None: + self.cell(row=sr + ri, column=sc + ci, value=val) + + @staticmethod + def _extract_non_batchable( + grid: list[list[Any]], start_row: int, start_col: int, + ) -> list[tuple[int, int, Any]]: + """Extract non-batchable values from grid, replacing them with None. + + Non-batchable: booleans, formulas (str starting with '='), and + non-primitive types (dates, datetimes, etc.). These require + per-cell ``write_cell_value()`` calls with type-preserving payloads. + """ + indiv: list[tuple[int, int, Any]] = [] + for ri, row in enumerate(grid): + for ci, val in enumerate(row): + if val is not None and ( + isinstance(val, bool) + or (isinstance(val, str) and val.startswith("=")) + or not isinstance(val, (int, float, str)) + ): + indiv.append((start_row + ri, start_col + ci, val)) + row[ci] = None + return indiv # ------------------------------------------------------------------ # Iteration @@ -303,10 +343,12 @@ def _flush(self) -> None: writer = wb._rust_writer # noqa: SLF001 if patcher is not None: - # Modify mode: materialize append buffer first (patcher has no - # batch API), then flush dirty cells individually. + # Modify mode: materialize buffers first (patcher has no batch + # API), then flush dirty cells individually. if self._append_buffer: self._materialize_append_buffer() + if self._bulk_writes: + self._materialize_bulk_writes() self._flush_to_patcher(patcher, python_value_to_payload, font_to_format_dict, fill_to_format_dict, alignment_to_format_dict, border_to_rust_dict) @@ -340,18 +382,7 @@ def _flush_to_writer( start_row = self._append_buffer_start start_a1 = rowcol_to_a1(start_row, 1) - # Scan for non-batchable values and replace with None in the grid. - # Non-batchable values get individual write_cell_value calls after. - indiv_from_buf: list[tuple[int, int, Any]] = [] - for ri, row in enumerate(buf): - for ci, val in enumerate(row): - if val is not None and ( - isinstance(val, bool) - or (isinstance(val, str) and val.startswith("=")) - or not isinstance(val, (int, float, str)) - ): - indiv_from_buf.append((start_row + ri, ci + 1, val)) - row[ci] = None # will be skipped by write_sheet_values + indiv_from_buf = self._extract_non_batchable(buf, start_row, 1) writer.write_sheet_values(self._title, start_a1, buf) @@ -365,17 +396,7 @@ def _flush_to_writer( # -- Flush bulk writes (write_rows) ----------------------------------- for grid, sr, sc in self._bulk_writes: start_a1 = rowcol_to_a1(sr, sc) - # Same non-batchable scan as append buffer. - indiv_from_bulk: list[tuple[int, int, Any]] = [] - for ri, row in enumerate(grid): - for ci, val in enumerate(row): - if val is not None and ( - isinstance(val, bool) - or (isinstance(val, str) and val.startswith("=")) - or not isinstance(val, (int, float, str)) - ): - indiv_from_bulk.append((sr + ri, sc + ci, val)) - row[ci] = None + indiv_from_bulk = self._extract_non_batchable(grid, sr, sc) writer.write_sheet_values(self._title, start_a1, grid) for r, c, val in indiv_from_bulk: coord = rowcol_to_a1(r, c) diff --git a/src/calamine_styled_backend.rs b/src/calamine_styled_backend.rs index d8bcece..05387b2 100644 --- a/src/calamine_styled_backend.rs +++ b/src/calamine_styled_backend.rs @@ -1,6 +1,6 @@ use pyo3::exceptions::{PyIOError, PyValueError}; use pyo3::prelude::*; -use pyo3::types::{PyDict, PyList}; +use pyo3::types::{PyDate, PyDateTime, PyDict, PyList}; use std::collections::HashMap; use std::fs::File; @@ -12,7 +12,7 @@ use calamine_styles::{ VerticalAlignment, WorksheetLayout, }; use calamine_styles::{Data, Range, Reader, Xlsx}; -use chrono::NaiveTime; +use chrono::{Datelike, NaiveTime, Timelike}; use quick_xml::events::Event; use quick_xml::Reader as XmlReader; @@ -183,7 +183,7 @@ fn data_to_py(py: Python<'_>, value: &Data) -> PyResult { /// Convert a calamine Data value to a plain Python object (no dict wrapper). /// -/// Returns str, float, int, bool, None, or ISO date/datetime string directly. +/// Returns str, float, int, bool, None, datetime.date, or datetime.datetime. fn data_to_plain_py(py: Python<'_>, value: &Data) -> PyResult { match value { Data::Empty => Ok(py.None()), @@ -195,17 +195,42 @@ fn data_to_plain_py(py: Python<'_>, value: &Data) -> PyResult { if let Some(ndt) = dt.as_datetime() { let midnight = NaiveTime::from_hms_opt(0, 0, 0).unwrap(); if ndt.time() == midnight { - let s = ndt.date().format("%Y-%m-%d").to_string(); - Ok(s.to_object(py)) + let d = PyDate::new(py, ndt.year(), ndt.month() as u8, ndt.day() as u8)?; + Ok(d.into_any().unbind()) } else { - let s = ndt.format("%Y-%m-%dT%H:%M:%S").to_string(); - Ok(s.to_object(py)) + let d = PyDateTime::new( + py, ndt.year(), ndt.month() as u8, ndt.day() as u8, + ndt.hour() as u8, ndt.minute() as u8, ndt.second() as u8, + 0, None, + )?; + Ok(d.into_any().unbind()) } } else { Ok(dt.as_f64().to_object(py)) } } - Data::DateTimeIso(s) => Ok(s.to_object(py)), + Data::DateTimeIso(s) => { + let raw = s.trim_end_matches('Z'); + if let Some(d) = parse_iso_date(raw) { + let pydate = PyDate::new(py, d.year(), d.month() as u8, d.day() as u8)?; + Ok(pydate.into_any().unbind()) + } else if let Some(ndt) = parse_iso_datetime(raw) { + let midnight = NaiveTime::from_hms_opt(0, 0, 0).unwrap(); + if ndt.time() == midnight { + let pydate = PyDate::new(py, ndt.year(), ndt.month() as u8, ndt.day() as u8)?; + Ok(pydate.into_any().unbind()) + } else { + let pydt = PyDateTime::new( + py, ndt.year(), ndt.month() as u8, ndt.day() as u8, + ndt.hour() as u8, ndt.minute() as u8, ndt.second() as u8, + 0, None, + )?; + Ok(pydt.into_any().unbind()) + } + } else { + Ok(s.to_object(py)) + } + } Data::DurationIso(s) => Ok(s.to_object(py)), Data::RichText(rt) => Ok(rt.plain_text().to_object(py)), Data::Error(e) => {