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from __future__ import annotations
from collections.abc import (
Hashable,
Iterable,
MutableMapping,
Sequence,
)
from typing import (
TYPE_CHECKING,
Any,
Callable,
Literal,
TypeVar,
overload,
)
from pandas.compat._optional import import_optional_dependency
from pandas.core.dtypes.common import (
is_integer,
is_list_like,
)
if TYPE_CHECKING:
from pandas.io.excel._base import ExcelWriter
ExcelWriter_t = type[ExcelWriter]
usecols_func = TypeVar("usecols_func", bound=Callable[[Hashable], object])
_writers: MutableMapping[str, ExcelWriter_t] = {}
def register_writer(klass: ExcelWriter_t) -> None:
"""
Add engine to the excel writer registry.io.excel.
You must use this method to integrate with ``to_excel``.
Parameters
----------
klass : ExcelWriter
"""
if not callable(klass):
raise ValueError("Can only register callables as engines")
engine_name = klass._engine
_writers[engine_name] = klass
def get_default_engine(ext: str, mode: Literal["reader", "writer"] = "reader") -> str:
"""
Return the default reader/writer for the given extension.
Parameters
----------
ext : str
The excel file extension for which to get the default engine.
mode : str {'reader', 'writer'}
Whether to get the default engine for reading or writing.
Either 'reader' or 'writer'
Returns
-------
str
The default engine for the extension.
"""
_default_readers = {
"xlsx": "openpyxl",
"xlsm": "openpyxl",
"xlsb": "pyxlsb",
"xls": "xlrd",
"ods": "odf",
}
_default_writers = {
"xlsx": "openpyxl",
"xlsm": "openpyxl",
"xlsb": "pyxlsb",
"ods": "odf",
}
assert mode in ["reader", "writer"]
if mode == "writer":
# Prefer xlsxwriter over openpyxl if installed
xlsxwriter = import_optional_dependency("xlsxwriter", errors="warn")
if xlsxwriter:
_default_writers["xlsx"] = "xlsxwriter"
return _default_writers[ext]
else:
return _default_readers[ext]
def get_writer(engine_name: str) -> ExcelWriter_t:
try:
return _writers[engine_name]
except KeyError as err:
raise ValueError(f"No Excel writer '{engine_name}'") from err
def _excel2num(x: str) -> int:
"""
Convert Excel column name like 'AB' to 0-based column index.
Parameters
----------
x : str
The Excel column name to convert to a 0-based column index.
Returns
-------
num : int
The column index corresponding to the name.
Raises
------
ValueError
Part of the Excel column name was invalid.
"""
index = 0
for c in x.upper().strip():
cp = ord(c)
if cp < ord("A") or cp > ord("Z"):
raise ValueError(f"Invalid column name: {x}")
index = index * 26 + cp - ord("A") + 1
return index - 1
def _range2cols(areas: str) -> list[int]:
"""
Convert comma separated list of column names and ranges to indices.
Parameters
----------
areas : str
A string containing a sequence of column ranges (or areas).
Returns
-------
cols : list
A list of 0-based column indices.
Examples
--------
>>> _range2cols('A:E')
[0, 1, 2, 3, 4]
>>> _range2cols('A,C,Z:AB')
[0, 2, 25, 26, 27]
"""
cols: list[int] = []
for rng in areas.split(","):
if ":" in rng:
rngs = rng.split(":")
cols.extend(range(_excel2num(rngs[0]), _excel2num(rngs[1]) + 1))
else:
cols.append(_excel2num(rng))
return cols
@overload
def maybe_convert_usecols(usecols: str | list[int]) -> list[int]:
...
@overload
def maybe_convert_usecols(usecols: list[str]) -> list[str]:
...
@overload
def maybe_convert_usecols(usecols: usecols_func) -> usecols_func:
...
@overload
def maybe_convert_usecols(usecols: None) -> None:
...
def maybe_convert_usecols(
usecols: str | list[int] | list[str] | usecols_func | None,
) -> None | list[int] | list[str] | usecols_func:
"""
Convert `usecols` into a compatible format for parsing in `parsers.py`.
Parameters
----------
usecols : object
The use-columns object to potentially convert.
Returns
-------
converted : object
The compatible format of `usecols`.
"""
if usecols is None:
return usecols
if is_integer(usecols):
raise ValueError(
"Passing an integer for `usecols` is no longer supported. "
"Please pass in a list of int from 0 to `usecols` inclusive instead."
)
if isinstance(usecols, str):
return _range2cols(usecols)
return usecols
@overload
def validate_freeze_panes(freeze_panes: tuple[int, int]) -> Literal[True]:
...
@overload
def validate_freeze_panes(freeze_panes: None) -> Literal[False]:
...
def validate_freeze_panes(freeze_panes: tuple[int, int] | None) -> bool:
if freeze_panes is not None:
if len(freeze_panes) == 2 and all(
isinstance(item, int) for item in freeze_panes
):
return True
raise ValueError(
"freeze_panes must be of form (row, column) "
"where row and column are integers"
)
# freeze_panes wasn't specified, return False so it won't be applied
# to output sheet
return False
def fill_mi_header(
row: list[Hashable], control_row: list[bool]
) -> tuple[list[Hashable], list[bool]]:
"""
Forward fill blank entries in row but only inside the same parent index.
Used for creating headers in Multiindex.
Parameters
----------
row : list
List of items in a single row.
control_row : list of bool
Helps to determine if particular column is in same parent index as the
previous value. Used to stop propagation of empty cells between
different indexes.
Returns
-------
Returns changed row and control_row
"""
last = row[0]
for i in range(1, len(row)):
if not control_row[i]:
last = row[i]
if row[i] == "" or row[i] is None:
row[i] = last
else:
control_row[i] = False
last = row[i]
return row, control_row
def pop_header_name(
row: list[Hashable], index_col: int | Sequence[int]
) -> tuple[Hashable | None, list[Hashable]]:
"""
Pop the header name for MultiIndex parsing.
Parameters
----------
row : list
The data row to parse for the header name.
index_col : int, list
The index columns for our data. Assumed to be non-null.
Returns
-------
header_name : str
The extracted header name.
trimmed_row : list
The original data row with the header name removed.
"""
# Pop out header name and fill w/blank.
if is_list_like(index_col):
assert isinstance(index_col, Iterable)
i = max(index_col)
else:
assert not isinstance(index_col, Iterable)
i = index_col
header_name = row[i]
header_name = None if header_name == "" else header_name
return header_name, row[:i] + [""] + row[i + 1 :]
def combine_kwargs(engine_kwargs: dict[str, Any] | None, kwargs: dict) -> dict:
"""
Used to combine two sources of kwargs for the backend engine.
Use of kwargs is deprecated, this function is solely for use in 1.3 and should
be removed in 1.4/2.0. Also _base.ExcelWriter.__new__ ensures either engine_kwargs
or kwargs must be None or empty respectively.
Parameters
----------
engine_kwargs: dict
kwargs to be passed through to the engine.
kwargs: dict
kwargs to be psased through to the engine (deprecated)
Returns
-------
engine_kwargs combined with kwargs
"""
if engine_kwargs is None:
result = {}
else:
result = engine_kwargs.copy()
result.update(kwargs)
return result