mirror of
https://github.com/storytold/gridcraft.git
synced 2026-11-03 08:51:30 -06:00
prxnvt
fcbbfa5142
A Python cell is written to xlsx as [MS-XLSX] 2.3.10 specifies: its formula is _xlfn._xlws.PY(i,0|1), where i is the zero-based index of the cell's script in the workbook's Python part and 0|1 the return type, 0 for an Excel value and 1 for a Python object. The part (2.1.23) is xl/python.xml, content type application/vnd.ms-excel.python+xml, related from the workbook part with http://schemas.microsoft.com/office/2023/09/relationships/Python; its root python holds pythonScripts, one pythonScript per Python cell in the order the cells are written, with the code in code. The code keeps its xl() references as text, so the formula has no further arguments. The cell keeps its cached value. A spilling result is written like a dynamic array (cm="1", t="array" ref=...) with the spilled values cached, so other applications show the values (and #NAME? if they recalculate). The reader turns a PY( formula with or without the _xlfn. and _xlws. prefixes into a Python cell. An index names a script of the Python part, and each %Px% in the script becomes the text of the formula's argument x (2.3.10.4). The string-literal form, PY("chunk"&"chunk",0|1), still reads, from the formula's own text so line breaks in the code survive. A formula naming a script the part doesn't hold keeps only its cached value, with a warning: no calculation can evaluate it. The reader keeps the cached spilled values as the cell's result, so a workbook from Excel shows its arrays without running anything. Python errors are cached as #VALUE!, as #SPILL! and #CALC! already are. Native JSON keeps Cell.py whole: code, return type, the last result and the exact error. Calc lays out a Python cell's kept result: Python cells are nodes of the dependency graph that read nothing, and a pass takes a dirty Python cell's result instead of evaluating it, so its array spills, is blocked (#SPILL!) and unblocked, and feeds its dependents exactly like a formula's. An array that is malformed or has more than 1,000,000 cells (only a crafted file holds one) shows #SPILL!. A dirty Python cell is pending in the pass, as a dirty formula is, so a formula, a range read or a cell-by-cell range walk that reaches it before its turn lays it out first rather than reading its old value. Opening a file can't make the app loop over a claimed size: the reader keeps a Python cell's spill range only when it has at most 1,000,000 cells (a range claiming the whole sheet is dropped with its values, as a formula's spilled values are), and io::adopt_python rebuilds results for at most 4,000,000 cells over the whole workbook, with a warning for the cells it skips. The Python part is read up to 64 MB and 1,000,000 scripts, a script is kept up to one character past what a cell may hold, and the cells take at most 64 MB of code from the part in all, since several formulas can name one script. io::enforce_python_limits drops the code of a cell whose code doesn't fit in 8,192 characters as PY(...) (the cell keeps its cached value, with a warning) and a kept result that isn't a well-formed array within the cap, each with its spill range and spilled values, so the sheet and a save no longer show the old spill. Formats that keep PY() as an ordinary formula (xls, xlsb, ods) are adopted the same way. Opening a file runs nothing. The command-sequence fuzzer sets Python cells (code with xl() references, quotes, line breaks, and code at and over the size limit), and its xlsx round-trip check allows the Python errors becoming #VALUE!, which is what the file format stores. Tests: the written formula naming its script, the Python part with its content type and relationship, return types, a spilling table saved as a dynamic array, Python errors as #VALUE!, the round trip of values, code, long code with quotes and line breaks and the error, and no Python part without Python cells; a workbook laid out as the format specifies (an index, a parameter named as %P2%) read as Python cells with their spilled values and saved back with its code in a Python part; the string-literal form; a formula naming a missing script, with and without a Python part; 20,000 cells naming one long script against the code budget; the part's reader and writer (escaping, odd %P tokens, a long script, a repeated parameter); a blocker in the spill area giving #SPILL! and clearing it spilling again; the native JSON round trip; a spill range claiming the whole sheet; the workbook-wide budget; hostile JSON (code over the limit, a result claiming far more cells than it holds); a malformed result that never spills; PY() formulas at 8,079 and 8,080 characters of code. Calc: formulas, MAX, SUM, COUNTA and SUMPRODUCT read a dirty Python cell whose array is blocked before its turn, in a full and an incremental recalculation, and see the array once it is unblocked; enforce_python_limits removes the spill of dropped code and of a dropped result, and keeps a sound one.