1from __future__ import annotations
+ 1from __future__ import annotations
2
- 3import sys
- 4import typing
- 5from typing import TYPE_CHECKING, Callable, Literal
+ 3import sys
+ 4import typing
+ 5from typing import TYPE_CHECKING, Callable, Literal
6
7if sys.version_info < (3, 10):
- 8 from typing_extensions import TypeAlias
+ 8 from typing_extensions import TypeAlias
9else:
- 10 from typing import TypeAlias
+ 10 from typing import TypeAlias
11
12if TYPE_CHECKING:
- 13 import pandas as pd
- 14 import polars as pl
+ 13 import pandas as pd
+ 14 import polars as pl
15
- 16from os.path import expanduser
- 17from pathlib import Path
+ 16from os.path import expanduser
+ 17from pathlib import Path
18
- 19import pyarrow as pa
+ 19import pyarrow as pa
20
- 21from ._fastexcel import (
+ 21from ._fastexcel import (
22 ArrowError,
23 CalamineCellError,
24 CalamineError,
@@ -245,7 +245,7 @@
34 _ExcelSheet,
35 _ExcelTable,
36)
- 37from ._fastexcel import read_excel as _read_excel
+ 37from ._fastexcel import read_excel as _read_excel
38
39DType = Literal["null", "int", "float", "string", "boolean", "datetime", "date", "duration"]
40DTypeMap: TypeAlias = "dict[str | int, DType]"
@@ -254,65 +254,65 @@
43SheetVisible: TypeAlias = Literal["visible", "hidden", "veryhidden"]
44
45
- 46def _recordbatch_to_polars(rb: pa.RecordBatch) -> pl.DataFrame:
- 47 import polars as pl
+ 46def _recordbatch_to_polars(rb: pa.RecordBatch) -> pl.DataFrame:
+ 47 import polars as pl
48
49 df = pl.from_arrow(data=rb)
50 assert isinstance(df, pl.DataFrame)
51 return df
52
53
- 54class ExcelSheet:
+ 54class ExcelSheet:
55 """A class representing a single sheet in an Excel File"""
56
- 57 def __init__(self, sheet: _ExcelSheet) -> None:
+ 57 def __init__(self, sheet: _ExcelSheet) -> None:
58 self._sheet = sheet
59
60 @property
- 61 def name(self) -> str:
+ 61 def name(self) -> str:
62 """The name of the sheet"""
63 return self._sheet.name
64
65 @property
- 66 def width(self) -> int:
+ 66 def width(self) -> int:
67 """The sheet's width"""
68 return self._sheet.width
69
70 @property
- 71 def height(self) -> int:
+ 71 def height(self) -> int:
72 """The sheet's height, with `skip_rows` and `nrows` applied"""
73 return self._sheet.height
74
75 @property
- 76 def total_height(self) -> int:
+ 76 def total_height(self) -> int:
77 """The sheet's total height"""
78 return self._sheet.total_height
79
80 @property
- 81 def selected_columns(self) -> list[ColumnInfo]:
+ 81 def selected_columns(self) -> list[ColumnInfo]:
82 """The sheet's selected columns"""
83 return self._sheet.selected_columns
84
85 @property
- 86 def available_columns(self) -> list[ColumnInfo]:
+ 86 def available_columns(self) -> list[ColumnInfo]:
87 """The columns available for the given sheet"""
88 return self._sheet.available_columns
89
90 @property
- 91 def specified_dtypes(self) -> DTypeMap | None:
+ 91 def specified_dtypes(self) -> DTypeMap | None:
92 """The dtypes specified for the sheet"""
93 return self._sheet.specified_dtypes
94
95 @property
- 96 def visible(self) -> SheetVisible:
+ 96 def visible(self) -> SheetVisible:
97 """The visibility of the sheet"""
98 return self._sheet.visible
99
-100 def to_arrow(self) -> pa.RecordBatch:
+100 def to_arrow(self) -> pa.RecordBatch:
101 """Converts the sheet to a pyarrow `RecordBatch`"""
102 return self._sheet.to_arrow()
103
-104 def to_pandas(self) -> "pd.DataFrame":
+104 def to_pandas(self) -> "pd.DataFrame":
105 """Converts the sheet to a Pandas `DataFrame`.
106
107 Requires the `pandas` extra to be installed.
@@ -320,73 +320,73 @@
109 # We know for sure that the sheet will yield exactly one RecordBatch
110 return self.to_arrow().to_pandas()
111
-112 def to_polars(self) -> "pl.DataFrame":
+112 def to_polars(self) -> "pl.DataFrame":
113 """Converts the sheet to a Polars `DataFrame`.
114
115 Requires the `polars` extra to be installed.
116 """
117 return _recordbatch_to_polars(self.to_arrow())
118
-119 def __repr__(self) -> str:
+119 def __repr__(self) -> str:
120 return self._sheet.__repr__()
121
122
-123class ExcelTable:
+123class ExcelTable:
124 """A class representing a single table in an Excel file"""
125
-126 def __init__(self, table: _ExcelTable) -> None:
+126 def __init__(self, table: _ExcelTable) -> None:
127 self._table = table
128
129 @property
-130 def name(self) -> str:
+130 def name(self) -> str:
131 """The name of the table"""
132 return self._table.name
133
134 @property
-135 def sheet_name(self) -> str:
+135 def sheet_name(self) -> str:
136 """The name of the sheet this table belongs to"""
137 return self._table.sheet_name
138
139 @property
-140 def width(self) -> int:
+140 def width(self) -> int:
141 """The table's width"""
142 return self._table.width
143
144 @property
-145 def height(self) -> int:
+145 def height(self) -> int:
146 """The table's height"""
147 return self._table.height
148
149 @property
-150 def total_height(self) -> int:
+150 def total_height(self) -> int:
151 """The table's total height"""
152 return self._table.total_height
153
154 @property
-155 def offset(self) -> int:
+155 def offset(self) -> int:
156 """The table's offset before data starts"""
157 return self._table.offset
158
159 @property
-160 def selected_columns(self) -> list[ColumnInfo]:
+160 def selected_columns(self) -> list[ColumnInfo]:
161 """The table's selected columns"""
162 return self._table.selected_columns
163
164 @property
-165 def available_columns(self) -> list[ColumnInfo]:
+165 def available_columns(self) -> list[ColumnInfo]:
166 """The columns available for the given table"""
167 return self._table.available_columns
168
169 @property
-170 def specified_dtypes(self) -> DTypeMap | None:
+170 def specified_dtypes(self) -> DTypeMap | None:
171 """The dtypes specified for the table"""
172 return self._table.specified_dtypes
173
-174 def to_arrow(self) -> pa.RecordBatch:
+174 def to_arrow(self) -> pa.RecordBatch:
175 """Converts the table to a pyarrow `RecordBatch`"""
176 return self._table.to_arrow()
177
-178 def to_pandas(self) -> "pd.DataFrame":
+178 def to_pandas(self) -> "pd.DataFrame":
179 """Converts the table to a Pandas `DataFrame`.
180
181 Requires the `pandas` extra to be installed.
@@ -394,7 +394,7 @@
183 # We know for sure that the table will yield exactly one RecordBatch
184 return self.to_arrow().to_pandas()
185
-186 def to_polars(self) -> "pl.DataFrame":
+186 def to_polars(self) -> "pl.DataFrame":
187 """Converts the table to a Polars `DataFrame`.
188
189 Requires the `polars` extra to be installed.
@@ -402,18 +402,18 @@
191 return _recordbatch_to_polars(self.to_arrow())
192
193
-194class ExcelReader:
+194class ExcelReader:
195 """A class representing an open Excel file and allowing to read its sheets"""
196
-197 def __init__(self, reader: _ExcelReader) -> None:
+197 def __init__(self, reader: _ExcelReader) -> None:
198 self._reader = reader
199
200 @property
-201 def sheet_names(self) -> list[str]:
+201 def sheet_names(self) -> list[str]:
202 """The list of sheet names"""
203 return self._reader.sheet_names
204
-205 def load_sheet(
+205 def load_sheet(
206 self,
207 idx_or_name: int | str,
208 *,
@@ -479,7 +479,7 @@
268 )
269 )
270
-271 def table_names(self, sheet_name: str | None = None) -> list[str]:
+271 def table_names(self, sheet_name: str | None = None) -> list[str]:
272 """The list of table names.
273
274 Will return an empty list if no tables are found.
@@ -490,7 +490,7 @@
279 return self._reader.table_names(sheet_name)
280
281 @typing.overload
-282 def load_table(
+282 def load_table(
283 self,
284 name: str,
285 *,
@@ -505,7 +505,7 @@
294 eager: Literal[False] = ...,
295 ) -> ExcelTable: ...
296 @typing.overload
-297 def load_table(
+297 def load_table(
298 self,
299 name: str,
300 *,
@@ -519,7 +519,7 @@
308 dtypes: DType | DTypeMap | None = None,
309 eager: Literal[True] = ...,
310 ) -> pa.RecordBatch: ...
-311 def load_table(
+311 def load_table(
312 self,
313 name: str,
314 *,
@@ -584,7 +584,7 @@
373 return output
374 return ExcelTable(output)
375
-376 def load_sheet_eager(
+376 def load_sheet_eager(
377 self,
378 idx_or_name: int | str,
379 *,
@@ -617,7 +617,7 @@
406 eager=True,
407 )
408
-409 def load_sheet_by_name(
+409 def load_sheet_by_name(
410 self,
411 name: str,
412 *,
@@ -646,7 +646,7 @@
435 dtypes=dtypes,
436 )
437
-438 def load_sheet_by_idx(
+438 def load_sheet_by_idx(
439 self,
440 idx: int,
441 *,
@@ -675,11 +675,11 @@
464 dtypes=dtypes,
465 )
466
-467 def __repr__(self) -> str:
+467 def __repr__(self) -> str:
468 return self._reader.__repr__()
469
470
-471def read_excel(source: Path | str | bytes) -> ExcelReader:
+471def read_excel(source: Path | str | bytes) -> ExcelReader:
472 """Opens and loads an excel file.
473
474 :param source: The path to a file or its content as bytes
@@ -743,7 +743,7 @@
- 472def read_excel(source: Path | str | bytes) -> ExcelReader:
+ 472def read_excel(source: Path | str | bytes) -> ExcelReader:
473 """Opens and loads an excel file.
474
475 :param source: The path to a file or its content as bytes
@@ -800,18 +800,18 @@ Parameters
- 195class ExcelReader:
+ 195class ExcelReader:
196 """A class representing an open Excel file and allowing to read its sheets"""
197
-198 def __init__(self, reader: _ExcelReader) -> None:
+198 def __init__(self, reader: _ExcelReader) -> None:
199 self._reader = reader
200
201 @property
-202 def sheet_names(self) -> list[str]:
+202 def sheet_names(self) -> list[str]:
203 """The list of sheet names"""
204 return self._reader.sheet_names
205
-206 def load_sheet(
+206 def load_sheet(
207 self,
208 idx_or_name: int | str,
209 *,
@@ -877,7 +877,7 @@ Parameters
269 )
270 )
271
-272 def table_names(self, sheet_name: str | None = None) -> list[str]:
+272 def table_names(self, sheet_name: str | None = None) -> list[str]:
273 """The list of table names.
274
275 Will return an empty list if no tables are found.
@@ -888,7 +888,7 @@ Parameters
280 return self._reader.table_names(sheet_name)
281
282 @typing.overload
-283 def load_table(
+283 def load_table(
284 self,
285 name: str,
286 *,
@@ -903,7 +903,7 @@ Parameters
295 eager: Literal[False] = ...,
296 ) -> ExcelTable: ...
297 @typing.overload
-298 def load_table(
+298 def load_table(
299 self,
300 name: str,
301 *,
@@ -917,7 +917,7 @@ Parameters
309 dtypes: DType | DTypeMap | None = None,
310 eager: Literal[True] = ...,
311 ) -> pa.RecordBatch: ...
-312 def load_table(
+312 def load_table(
313 self,
314 name: str,
315 *,
@@ -982,7 +982,7 @@ Parameters
374 return output
375 return ExcelTable(output)
376
-377 def load_sheet_eager(
+377 def load_sheet_eager(
378 self,
379 idx_or_name: int | str,
380 *,
@@ -1015,7 +1015,7 @@ Parameters
407 eager=True,
408 )
409
-410 def load_sheet_by_name(
+410 def load_sheet_by_name(
411 self,
412 name: str,
413 *,
@@ -1044,7 +1044,7 @@ Parameters
436 dtypes=dtypes,
437 )
438
-439 def load_sheet_by_idx(
+439 def load_sheet_by_idx(
440 self,
441 idx: int,
442 *,
@@ -1073,7 +1073,7 @@ Parameters
465 dtypes=dtypes,
466 )
467
-468 def __repr__(self) -> str:
+468 def __repr__(self) -> str:
469 return self._reader.__repr__()
@@ -1092,7 +1092,7 @@ Parameters
- 198 def __init__(self, reader: _ExcelReader) -> None:
+
@@ -1110,7 +1110,7 @@ Parameters
201 @property
-202 def sheet_names(self) -> list[str]:
+202 def sheet_names(self) -> list[str]:
203 """The list of sheet names"""
204 return self._reader.sheet_names
@@ -1132,7 +1132,7 @@ Parameters
- 206 def load_sheet(
+
- 272 def table_names(self, sheet_name: str | None = None) -> list[str]:
+ 272 def table_names(self, sheet_name: str | None = None) -> list[str]:
273 """The list of table names.
274
275 Will return an empty list if no tables are found.
@@ -1297,7 +1297,7 @@ Parameters
- 312 def load_table(
+
- 377 def load_sheet_eager(
+ 377 def load_sheet_eager(
378 self,
379 idx_or_name: int | str,
380 *,
@@ -1475,7 +1475,7 @@ Parameters
- 410 def load_sheet_by_name(
+
- 439 def load_sheet_by_idx(
+
- 55class ExcelSheet:
+ 55class ExcelSheet:
56 """A class representing a single sheet in an Excel File"""
57
- 58 def __init__(self, sheet: _ExcelSheet) -> None:
+ 58 def __init__(self, sheet: _ExcelSheet) -> None:
59 self._sheet = sheet
60
61 @property
- 62 def name(self) -> str:
+ 62 def name(self) -> str:
63 """The name of the sheet"""
64 return self._sheet.name
65
66 @property
- 67 def width(self) -> int:
+ 67 def width(self) -> int:
68 """The sheet's width"""
69 return self._sheet.width
70
71 @property
- 72 def height(self) -> int:
+ 72 def height(self) -> int:
73 """The sheet's height, with `skip_rows` and `nrows` applied"""
74 return self._sheet.height
75
76 @property
- 77 def total_height(self) -> int:
+ 77 def total_height(self) -> int:
78 """The sheet's total height"""
79 return self._sheet.total_height
80
81 @property
- 82 def selected_columns(self) -> list[ColumnInfo]:
+ 82 def selected_columns(self) -> list[ColumnInfo]:
83 """The sheet's selected columns"""
84 return self._sheet.selected_columns
85
86 @property
- 87 def available_columns(self) -> list[ColumnInfo]:
+ 87 def available_columns(self) -> list[ColumnInfo]:
88 """The columns available for the given sheet"""
89 return self._sheet.available_columns
90
91 @property
- 92 def specified_dtypes(self) -> DTypeMap | None:
+ 92 def specified_dtypes(self) -> DTypeMap | None:
93 """The dtypes specified for the sheet"""
94 return self._sheet.specified_dtypes
95
96 @property
- 97 def visible(self) -> SheetVisible:
+ 97 def visible(self) -> SheetVisible:
98 """The visibility of the sheet"""
99 return self._sheet.visible
100
-101 def to_arrow(self) -> pa.RecordBatch:
+101 def to_arrow(self) -> pa.RecordBatch:
102 """Converts the sheet to a pyarrow `RecordBatch`"""
103 return self._sheet.to_arrow()
104
-105 def to_pandas(self) -> "pd.DataFrame":
+105 def to_pandas(self) -> "pd.DataFrame":
106 """Converts the sheet to a Pandas `DataFrame`.
107
108 Requires the `pandas` extra to be installed.
@@ -1632,14 +1632,14 @@ Parameters
110 # We know for sure that the sheet will yield exactly one RecordBatch
111 return self.to_arrow().to_pandas()
112
-113 def to_polars(self) -> "pl.DataFrame":
+113 def to_polars(self) -> "pl.DataFrame":
114 """Converts the sheet to a Polars `DataFrame`.
115
116 Requires the `polars` extra to be installed.
117 """
118 return _recordbatch_to_polars(self.to_arrow())
119
-120 def __repr__(self) -> str:
+120 def __repr__(self) -> str:
121 return self._sheet.__repr__()
@@ -1658,7 +1658,7 @@ Parameters
- 58 def __init__(self, sheet: _ExcelSheet) -> None:
+
@@ -1676,7 +1676,7 @@ Parameters
61 @property
-62 def name(self) -> str:
+62 def name(self) -> str:
63 """The name of the sheet"""
64 return self._sheet.name
@@ -1697,7 +1697,7 @@ Parameters
66 @property
-67 def width(self) -> int:
+67 def width(self) -> int:
68 """The sheet's width"""
69 return self._sheet.width
@@ -1718,7 +1718,7 @@ Parameters
71 @property
-72 def height(self) -> int:
+72 def height(self) -> int:
73 """The sheet's height, with `skip_rows` and `nrows` applied"""
74 return self._sheet.height
@@ -1739,7 +1739,7 @@ Parameters
76 @property
-77 def total_height(self) -> int:
+77 def total_height(self) -> int:
78 """The sheet's total height"""
79 return self._sheet.total_height
@@ -1760,7 +1760,7 @@ Parameters
81 @property
-82 def selected_columns(self) -> list[ColumnInfo]:
+82 def selected_columns(self) -> list[ColumnInfo]:
83 """The sheet's selected columns"""
84 return self._sheet.selected_columns
@@ -1781,7 +1781,7 @@ Parameters
86 @property
-87 def available_columns(self) -> list[ColumnInfo]:
+87 def available_columns(self) -> list[ColumnInfo]:
88 """The columns available for the given sheet"""
89 return self._sheet.available_columns
@@ -1802,7 +1802,7 @@ Parameters
91 @property
-92 def specified_dtypes(self) -> DTypeMap | None:
+92 def specified_dtypes(self) -> DTypeMap | None:
93 """The dtypes specified for the sheet"""
94 return self._sheet.specified_dtypes
@@ -1823,7 +1823,7 @@ Parameters
96 @property -97 def visible(self) -> SheetVisible: +97 def visible(self) -> SheetVisible: 98 """The visibility of the sheet""" 99 return self._sheet.visible
101 def to_arrow(self) -> pa.RecordBatch:
+ 101 def to_arrow(self) -> pa.RecordBatch:
102 """Converts the sheet to a pyarrow `RecordBatch`"""
103 return self._sheet.to_arrow()
@@ -1867,7 +1867,7 @@ Parameters
105 def to_pandas(self) -> "pd.DataFrame":
+ 105 def to_pandas(self) -> "pd.DataFrame":
106 """Converts the sheet to a Pandas `DataFrame`.
107
108 Requires the `pandas` extra to be installed.
@@ -1895,7 +1895,7 @@ Parameters
- 113 def to_polars(self) -> "pl.DataFrame":
+ 113 def to_polars(self) -> "pl.DataFrame":
114 """Converts the sheet to a Polars `DataFrame`.
115
116 Requires the `polars` extra to be installed.
@@ -1950,19 +1950,6 @@ Parameters
-
column_name_from
@@ -2018,6 +2005,19 @@ Parameters
+
+
diff --git a/docs/search.js b/docs/search.js
index e0a2c9c..ba2650a 100644
--- a/docs/search.js
+++ b/docs/search.js
@@ -1,6 +1,6 @@
window.pdocSearch = (function(){
/** elasticlunr - http://weixsong.github.io * Copyright (C) 2017 Oliver Nightingale * Copyright (C) 2017 Wei Song * MIT Licensed */!function(){function e(e){if(null===e||"object"!=typeof e)return e;var t=e.constructor();for(var n in e)e.hasOwnProperty(n)&&(t[n]=e[n]);return t}var t=function(e){var n=new t.Index;return n.pipeline.add(t.trimmer,t.stopWordFilter,t.stemmer),e&&e.call(n,n),n};t.version="0.9.5",lunr=t,t.utils={},t.utils.warn=function(e){return function(t){e.console&&console.warn&&console.warn(t)}}(this),t.utils.toString=function(e){return void 0===e||null===e?"":e.toString()},t.EventEmitter=function(){this.events={}},t.EventEmitter.prototype.addListener=function(){var e=Array.prototype.slice.call(arguments),t=e.pop(),n=e;if("function"!=typeof t)throw new TypeError("last argument must be a function");n.forEach(function(e){this.hasHandler(e)||(this.events[e]=[]),this.events[e].push(t)},this)},t.EventEmitter.prototype.removeListener=function(e,t){if(this.hasHandler(e)){var n=this.events[e].indexOf(t);-1!==n&&(this.events[e].splice(n,1),0==this.events[e].length&&delete this.events[e])}},t.EventEmitter.prototype.emit=function(e){if(this.hasHandler(e)){var t=Array.prototype.slice.call(arguments,1);this.events[e].forEach(function(e){e.apply(void 0,t)},this)}},t.EventEmitter.prototype.hasHandler=function(e){return e in this.events},t.tokenizer=function(e){if(!arguments.length||null===e||void 0===e)return[];if(Array.isArray(e)){var n=e.filter(function(e){return null===e||void 0===e?!1:!0});n=n.map(function(e){return t.utils.toString(e).toLowerCase()});var i=[];return n.forEach(function(e){var n=e.split(t.tokenizer.seperator);i=i.concat(n)},this),i}return e.toString().trim().toLowerCase().split(t.tokenizer.seperator)},t.tokenizer.defaultSeperator=/[\s\-]+/,t.tokenizer.seperator=t.tokenizer.defaultSeperator,t.tokenizer.setSeperator=function(e){null!==e&&void 0!==e&&"object"==typeof e&&(t.tokenizer.seperator=e)},t.tokenizer.resetSeperator=function(){t.tokenizer.seperator=t.tokenizer.defaultSeperator},t.tokenizer.getSeperator=function(){return t.tokenizer.seperator},t.Pipeline=function(){this._queue=[]},t.Pipeline.registeredFunctions={},t.Pipeline.registerFunction=function(e,n){n in t.Pipeline.registeredFunctions&&t.utils.warn("Overwriting existing registered function: "+n),e.label=n,t.Pipeline.registeredFunctions[n]=e},t.Pipeline.getRegisteredFunction=function(e){return e in t.Pipeline.registeredFunctions!=!0?null:t.Pipeline.registeredFunctions[e]},t.Pipeline.warnIfFunctionNotRegistered=function(e){var n=e.label&&e.label in this.registeredFunctions;n||t.utils.warn("Function is not registered with pipeline. This may cause problems when serialising the index.\n",e)},t.Pipeline.load=function(e){var n=new t.Pipeline;return e.forEach(function(e){var i=t.Pipeline.getRegisteredFunction(e);if(!i)throw new Error("Cannot load un-registered function: "+e);n.add(i)}),n},t.Pipeline.prototype.add=function(){var e=Array.prototype.slice.call(arguments);e.forEach(function(e){t.Pipeline.warnIfFunctionNotRegistered(e),this._queue.push(e)},this)},t.Pipeline.prototype.after=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i+1,0,n)},t.Pipeline.prototype.before=function(e,n){t.Pipeline.warnIfFunctionNotRegistered(n);var i=this._queue.indexOf(e);if(-1===i)throw new Error("Cannot find existingFn");this._queue.splice(i,0,n)},t.Pipeline.prototype.remove=function(e){var t=this._queue.indexOf(e);-1!==t&&this._queue.splice(t,1)},t.Pipeline.prototype.run=function(e){for(var t=[],n=e.length,i=this._queue.length,o=0;n>o;o++){for(var r=e[o],s=0;i>s&&(r=this._queue[s](r,o,e),void 0!==r&&null!==r);s++);void 0!==r&&null!==r&&t.push(r)}return t},t.Pipeline.prototype.reset=function(){this._queue=[]},t.Pipeline.prototype.get=function(){return this._queue},t.Pipeline.prototype.toJSON=function(){return this._queue.map(function(e){return t.Pipeline.warnIfFunctionNotRegistered(e),e.label})},t.Index=function(){this._fields=[],this._ref="id",this.pipeline=new t.Pipeline,this.documentStore=new t.DocumentStore,this.index={},this.eventEmitter=new t.EventEmitter,this._idfCache={},this.on("add","remove","update",function(){this._idfCache={}}.bind(this))},t.Index.prototype.on=function(){var e=Array.prototype.slice.call(arguments);return this.eventEmitter.addListener.apply(this.eventEmitter,e)},t.Index.prototype.off=function(e,t){return this.eventEmitter.removeListener(e,t)},t.Index.load=function(e){e.version!==t.version&&t.utils.warn("version mismatch: current "+t.version+" importing "+e.version);var n=new this;n._fields=e.fields,n._ref=e.ref,n.documentStore=t.DocumentStore.load(e.documentStore),n.pipeline=t.Pipeline.load(e.pipeline),n.index={};for(var i in e.index)n.index[i]=t.InvertedIndex.load(e.index[i]);return n},t.Index.prototype.addField=function(e){return this._fields.push(e),this.index[e]=new t.InvertedIndex,this},t.Index.prototype.setRef=function(e){return this._ref=e,this},t.Index.prototype.saveDocument=function(e){return this.documentStore=new t.DocumentStore(e),this},t.Index.prototype.addDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.addDoc(i,e),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));this.documentStore.addFieldLength(i,n,o.length);var r={};o.forEach(function(e){e in r?r[e]+=1:r[e]=1},this);for(var s in r){var u=r[s];u=Math.sqrt(u),this.index[n].addToken(s,{ref:i,tf:u})}},this),n&&this.eventEmitter.emit("add",e,this)}},t.Index.prototype.removeDocByRef=function(e){if(e&&this.documentStore.isDocStored()!==!1&&this.documentStore.hasDoc(e)){var t=this.documentStore.getDoc(e);this.removeDoc(t,!1)}},t.Index.prototype.removeDoc=function(e,n){if(e){var n=void 0===n?!0:n,i=e[this._ref];this.documentStore.hasDoc(i)&&(this.documentStore.removeDoc(i),this._fields.forEach(function(n){var o=this.pipeline.run(t.tokenizer(e[n]));o.forEach(function(e){this.index[n].removeToken(e,i)},this)},this),n&&this.eventEmitter.emit("remove",e,this))}},t.Index.prototype.updateDoc=function(e,t){var t=void 0===t?!0:t;this.removeDocByRef(e[this._ref],!1),this.addDoc(e,!1),t&&this.eventEmitter.emit("update",e,this)},t.Index.prototype.idf=function(e,t){var n="@"+t+"/"+e;if(Object.prototype.hasOwnProperty.call(this._idfCache,n))return this._idfCache[n];var i=this.index[t].getDocFreq(e),o=1+Math.log(this.documentStore.length/(i+1));return this._idfCache[n]=o,o},t.Index.prototype.getFields=function(){return this._fields.slice()},t.Index.prototype.search=function(e,n){if(!e)return[];e="string"==typeof e?{any:e}:JSON.parse(JSON.stringify(e));var i=null;null!=n&&(i=JSON.stringify(n));for(var o=new t.Configuration(i,this.getFields()).get(),r={},s=Object.keys(e),u=0;u0&&t.push(e);for(var i in n)"docs"!==i&&"df"!==i&&this.expandToken(e+i,t,n[i]);return t},t.InvertedIndex.prototype.toJSON=function(){return{root:this.root}},t.Configuration=function(e,n){var e=e||"";if(void 0==n||null==n)throw new Error("fields should not be null");this.config={};var i;try{i=JSON.parse(e),this.buildUserConfig(i,n)}catch(o){t.utils.warn("user configuration parse failed, will use default configuration"),this.buildDefaultConfig(n)}},t.Configuration.prototype.buildDefaultConfig=function(e){this.reset(),e.forEach(function(e){this.config[e]={boost:1,bool:"OR",expand:!1}},this)},t.Configuration.prototype.buildUserConfig=function(e,n){var i="OR",o=!1;if(this.reset(),"bool"in e&&(i=e.bool||i),"expand"in e&&(o=e.expand||o),"fields"in e)for(var r in e.fields)if(n.indexOf(r)>-1){var s=e.fields[r],u=o;void 0!=s.expand&&(u=s.expand),this.config[r]={boost:s.boost||0===s.boost?s.boost:1,bool:s.bool||i,expand:u}}else t.utils.warn("field name in user configuration not found in index instance fields");else this.addAllFields2UserConfig(i,o,n)},t.Configuration.prototype.addAllFields2UserConfig=function(e,t,n){n.forEach(function(n){this.config[n]={boost:1,bool:e,expand:t}},this)},t.Configuration.prototype.get=function(){return this.config},t.Configuration.prototype.reset=function(){this.config={}},lunr.SortedSet=function(){this.length=0,this.elements=[]},lunr.SortedSet.load=function(e){var t=new this;return t.elements=e,t.length=e.length,t},lunr.SortedSet.prototype.add=function(){var e,t;for(e=0;e1;){if(r===e)return o;e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o]}return r===e?o:-1},lunr.SortedSet.prototype.locationFor=function(e){for(var t=0,n=this.elements.length,i=n-t,o=t+Math.floor(i/2),r=this.elements[o];i>1;)e>r&&(t=o),r>e&&(n=o),i=n-t,o=t+Math.floor(i/2),r=this.elements[o];return r>e?o:e>r?o+1:void 0},lunr.SortedSet.prototype.intersect=function(e){for(var t=new lunr.SortedSet,n=0,i=0,o=this.length,r=e.length,s=this.elements,u=e.elements;;){if(n>o-1||i>r-1)break;s[n]!==u[i]?s[n]u[i]&&i++:(t.add(s[n]),n++,i++)}return t},lunr.SortedSet.prototype.clone=function(){var e=new lunr.SortedSet;return e.elements=this.toArray(),e.length=e.elements.length,e},lunr.SortedSet.prototype.union=function(e){var t,n,i;this.length>=e.length?(t=this,n=e):(t=e,n=this),i=t.clone();for(var o=0,r=n.toArray();o\n"}, "fastexcel.read_excel": {"fullname": "fastexcel.read_excel", "modulename": "fastexcel", "qualname": "read_excel", "kind": "function", "doc": "Opens and loads an excel file.
\n\nParameters
\n\n\n- source: The path to a file or its content as bytes
\n
\n", "signature": "(source: pathlib.Path | str | bytes) -> fastexcel.ExcelReader:", "funcdef": "def"}, "fastexcel.DType": {"fullname": "fastexcel.DType", "modulename": "fastexcel", "qualname": "DType", "kind": "variable", "doc": "\n", "default_value": "typing.Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']"}, "fastexcel.DTypeMap": {"fullname": "fastexcel.DTypeMap", "modulename": "fastexcel", "qualname": "DTypeMap", "kind": "variable", "doc": "\n", "annotation": ": TypeAlias", "default_value": "'dict[str | int, DType]'"}, "fastexcel.ExcelReader": {"fullname": "fastexcel.ExcelReader", "modulename": "fastexcel", "qualname": "ExcelReader", "kind": "class", "doc": "A class representing an open Excel file and allowing to read its sheets
\n"}, "fastexcel.ExcelReader.__init__": {"fullname": "fastexcel.ExcelReader.__init__", "modulename": "fastexcel", "qualname": "ExcelReader.__init__", "kind": "function", "doc": "\n", "signature": "(reader: _ExcelReader)"}, "fastexcel.ExcelReader.sheet_names": {"fullname": "fastexcel.ExcelReader.sheet_names", "modulename": "fastexcel", "qualname": "ExcelReader.sheet_names", "kind": "variable", "doc": "The list of sheet names
\n", "annotation": ": list[str]"}, "fastexcel.ExcelReader.load_sheet": {"fullname": "fastexcel.ExcelReader.load_sheet", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet", "kind": "function", "doc": "Loads a sheet lazily by index or name.
\n\nParameters
\n\n\n- idx_or_name: The index (starting at 0) or the name of the sheet to load.
\n- header_row: The index of the row containing the column labels, default index is 0.\nIf
None, the sheet does not have any column labels.\nAny rows before the header_row will be automatically skipped. \n- column_names: Overrides headers found in the document.\nIf
column_names is used, header_row will be ignored. \n- n_rows: Specifies how many rows should be loaded.\nIf
None, all rows are loaded \n- skip_rows: Specifies how many rows should be skipped after the
header_row.\nAny rows before the header_row are automatically skipped.\nIf header_row is None:\n\n- if
skip_rows is None (default): it skips all empty rows\nat the beginning of the sheet. \n- if
skip_rows is a number, it skips the specified number\nof rows from the start of the sheet. \n
\n- schema_sample_rows: Specifies how many rows should be used to determine\nthe dtype of a column. Cannot be 0. A specific dtype can be\nenforced for some or all columns through the
dtypes parameter.\nIf None, all rows will be used. \n- dtype_coercion: Specifies how type coercion should behave.
coerce (the default)\nwill try to coerce different dtypes in a column to the same one,\nwhereas strict will raise an error in case a column contains\nseveral dtypes. Note that this only applies to columns whose dtype\nis guessed, i.e. not specified via dtypes. \n- use_columns: Specifies the columns to use. Can either be: \n
\nNone to select all columns- A list of strings and ints, the column names and/or indices\n(starting at 0)
\n- A string, a comma separated list of Excel column letters and column\nranges (e.g.
\u201cA:E\u201d or \u201cA,C,E:F\u201d, which would result in\nA,B,C,D,E and A,C,E,F) \n- A callable, a function that takes a column and returns a boolean\nindicating whether the column should be used
\n
\n- dtypes: An optional dtype (for all columns)\nor dict of dtypes with keys as column indices or names.
\n
\n", "signature": "(\tself,\tidx_or_name: int | str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int | None = None,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: Union[list[str], list[int], str, Callable[[ColumnInfo], bool], NoneType] = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelReader.table_names": {"fullname": "fastexcel.ExcelReader.table_names", "modulename": "fastexcel", "qualname": "ExcelReader.table_names", "kind": "function", "doc": "The list of table names.
\n\nWill return an empty list if no tables are found.
\n\nParameters
\n\n\n- sheet_name: If given, will limit the list to the given sheet, will be faster\ntoo.
\n
\n", "signature": "(self, sheet_name: str | None = None) -> list[str]:", "funcdef": "def"}, "fastexcel.ExcelReader.load_table": {"fullname": "fastexcel.ExcelReader.load_table", "modulename": "fastexcel", "qualname": "ExcelReader.load_table", "kind": "function", "doc": "Loads a table by name.
\n\nParameters
\n\n\n- name: The name of the table to load.
\n- header_row: The index of the row containing the column labels.\nIf
None, the table's column names will be used.\nAny rows before the header_row will be automatically skipped. \n- column_names: Overrides headers found in the document.\nIf
column_names is used, header_row will be ignored. \n- n_rows: Specifies how many rows should be loaded.\nIf
None, all rows are loaded \n- skip_rows: Specifies how many rows should be skipped after the
header_row.\nAny rows before the header_row are automatically skipped.\nIf header_row is None, it skips the number of rows from the\nstart of the sheet. \n- schema_sample_rows: Specifies how many rows should be used to determine\nthe dtype of a column. Cannot be 0. A specific dtype can be\nenforced for some or all columns through the
dtypes parameter.\nIf None, all rows will be used. \n- dtype_coercion: Specifies how type coercion should behave.
coerce (the default)\nwill try to coerce different dtypes in a column to the same one,\nwhereas strict will raise an error in case a column contains\nseveral dtypes. Note that this only applies to columns whose dtype\nis guessed, i.e. not specified via dtypes. \n- use_columns: Specifies the columns to use. Can either be: \n
\nNone to select all columns- A list of strings and ints, the column names and/or indices\n(starting at 0)
\n- A string, a comma separated list of Excel column letters and column\nranges (e.g.
\u201cA:E\u201d or \u201cA,C,E:F\u201d, which would result in\nA,B,C,D,E and A,C,E,F) \n- A callable, a function that takes a column and returns a boolean\nindicating whether the column should be used
\n
\n- dtypes: An optional dtype (for all columns)\nor dict of dtypes with keys as column indices or names.
\n
\n", "signature": "(\tself,\tname: str,\t*,\theader_row: int | None = None,\tcolumn_names: list[str] | None = None,\tskip_rows: int = 0,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: Union[list[str], list[int], str, Callable[[ColumnInfo], bool], NoneType] = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None,\teager: bool = False) -> fastexcel.ExcelTable | pyarrow.lib.RecordBatch:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet_eager": {"fullname": "fastexcel.ExcelReader.load_sheet_eager", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_eager", "kind": "function", "doc": "Loads a sheet eagerly by index or name.
\n\nFor xlsx files, this will be faster and more memory-efficient, as it will use\nworksheet_range_ref under the hood, which returns borrowed types.
\n\nRefer to load_sheet for parameter documentation
\n", "signature": "(\tself,\tidx_or_name: int | str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int | None = None,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: list[str] | list[int] | str | None = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None) -> pyarrow.lib.RecordBatch:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet_by_name": {"fullname": "fastexcel.ExcelReader.load_sheet_by_name", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_by_name", "kind": "function", "doc": "Loads a sheet by name.
\n\nRefer to load_sheet for parameter documentation
\n", "signature": "(\tself,\tname: str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int | None = None,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: Union[list[str], list[int], str, Callable[[ColumnInfo], bool], NoneType] = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet_by_idx": {"fullname": "fastexcel.ExcelReader.load_sheet_by_idx", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_by_idx", "kind": "function", "doc": "Loads a sheet by index.
\n\nRefer to load_sheet for parameter documentation
\n", "signature": "(\tself,\tidx: int,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int | None = None,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: Union[list[str], list[int], str, Callable[[ColumnInfo], bool], NoneType] = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelSheet": {"fullname": "fastexcel.ExcelSheet", "modulename": "fastexcel", "qualname": "ExcelSheet", "kind": "class", "doc": "A class representing a single sheet in an Excel File
\n"}, "fastexcel.ExcelSheet.__init__": {"fullname": "fastexcel.ExcelSheet.__init__", "modulename": "fastexcel", "qualname": "ExcelSheet.__init__", "kind": "function", "doc": "\n", "signature": "(sheet: _ExcelSheet)"}, "fastexcel.ExcelSheet.name": {"fullname": "fastexcel.ExcelSheet.name", "modulename": "fastexcel", "qualname": "ExcelSheet.name", "kind": "variable", "doc": "The name of the sheet
\n", "annotation": ": str"}, "fastexcel.ExcelSheet.width": {"fullname": "fastexcel.ExcelSheet.width", "modulename": "fastexcel", "qualname": "ExcelSheet.width", "kind": "variable", "doc": "The sheet's width
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.height": {"fullname": "fastexcel.ExcelSheet.height", "modulename": "fastexcel", "qualname": "ExcelSheet.height", "kind": "variable", "doc": "The sheet's height, with skip_rows and nrows applied
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.total_height": {"fullname": "fastexcel.ExcelSheet.total_height", "modulename": "fastexcel", "qualname": "ExcelSheet.total_height", "kind": "variable", "doc": "The sheet's total height
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.selected_columns": {"fullname": "fastexcel.ExcelSheet.selected_columns", "modulename": "fastexcel", "qualname": "ExcelSheet.selected_columns", "kind": "variable", "doc": "The sheet's selected columns
\n", "annotation": ": list[ColumnInfo]"}, "fastexcel.ExcelSheet.available_columns": {"fullname": "fastexcel.ExcelSheet.available_columns", "modulename": "fastexcel", "qualname": "ExcelSheet.available_columns", "kind": "variable", "doc": "The columns available for the given sheet
\n", "annotation": ": list[ColumnInfo]"}, "fastexcel.ExcelSheet.specified_dtypes": {"fullname": "fastexcel.ExcelSheet.specified_dtypes", "modulename": "fastexcel", "qualname": "ExcelSheet.specified_dtypes", "kind": "variable", "doc": "The dtypes specified for the sheet
\n", "annotation": ": 'DTypeMap | None'"}, "fastexcel.ExcelSheet.visible": {"fullname": "fastexcel.ExcelSheet.visible", "modulename": "fastexcel", "qualname": "ExcelSheet.visible", "kind": "variable", "doc": "The visibility of the sheet
\n", "annotation": ": Literal['visible', 'hidden', 'veryhidden']"}, "fastexcel.ExcelSheet.to_arrow": {"fullname": "fastexcel.ExcelSheet.to_arrow", "modulename": "fastexcel", "qualname": "ExcelSheet.to_arrow", "kind": "function", "doc": "Converts the sheet to a pyarrow RecordBatch
\n", "signature": "(self) -> pyarrow.lib.RecordBatch:", "funcdef": "def"}, "fastexcel.ExcelSheet.to_pandas": {"fullname": "fastexcel.ExcelSheet.to_pandas", "modulename": "fastexcel", "qualname": "ExcelSheet.to_pandas", "kind": "function", "doc": "Converts the sheet to a Pandas DataFrame.
\n\nRequires the pandas extra to be installed.
\n", "signature": "(self) -> pandas.core.frame.DataFrame:", "funcdef": "def"}, "fastexcel.ExcelSheet.to_polars": {"fullname": "fastexcel.ExcelSheet.to_polars", "modulename": "fastexcel", "qualname": "ExcelSheet.to_polars", "kind": "function", "doc": "Converts the sheet to a Polars DataFrame.
\n\nRequires the polars extra to be installed.
\n", "signature": "(self) -> polars.dataframe.frame.DataFrame:", "funcdef": "def"}, "fastexcel.DTypeFrom": {"fullname": "fastexcel.DTypeFrom", "modulename": "fastexcel", "qualname": "DTypeFrom", "kind": "variable", "doc": "\n", "annotation": ": TypeAlias", "default_value": "Literal['provided_by_index', 'provided_by_name', 'guessed']"}, "fastexcel.ColumnNameFrom": {"fullname": "fastexcel.ColumnNameFrom", "modulename": "fastexcel", "qualname": "ColumnNameFrom", "kind": "variable", "doc": "\n", "annotation": ": TypeAlias", "default_value": "Literal['provided', 'looked_up', 'generated']"}, "fastexcel.ColumnInfo": {"fullname": "fastexcel.ColumnInfo", "modulename": "fastexcel", "qualname": "ColumnInfo", "kind": "class", "doc": "This class provides information about a single column in a sheet
\n"}, "fastexcel.ColumnInfo.index": {"fullname": "fastexcel.ColumnInfo.index", "modulename": "fastexcel", "qualname": "ColumnInfo.index", "kind": "variable", "doc": "int. The index of the column
\n"}, "fastexcel.ColumnInfo.column_name_from": {"fullname": "fastexcel.ColumnInfo.column_name_from", "modulename": "fastexcel", "qualname": "ColumnInfo.column_name_from", "kind": "variable", "doc": "fastexcel.ColumnNameFrom. How the name of the column was determined.
\n\nOne of three possible values:
\n\n\n\"provided\": The column name was provided via the use_columns parameter\"looked_up\": The column name was looked up from the data found in the sheet\"generated\": The column name was generated from the column index, either because\nheader_row was None, or because it could not be looked up
\n"}, "fastexcel.ColumnInfo.dtype_from": {"fullname": "fastexcel.ColumnInfo.dtype_from", "modulename": "fastexcel", "qualname": "ColumnInfo.dtype_from", "kind": "variable", "doc": "fastexcel.DTypeFrom. How the dtype of the column was determined.
\n\nOne of three possible values:
\n\n\n\"provided_by_index\": The dtype was specified via the column index\"provided_by_name\": The dtype was specified via the column name\"guessed\": The dtype was determined from the content of the column
\n"}, "fastexcel.ColumnInfo.name": {"fullname": "fastexcel.ColumnInfo.name", "modulename": "fastexcel", "qualname": "ColumnInfo.name", "kind": "variable", "doc": "str. The name of the column
\n"}, "fastexcel.ColumnInfo.dtype": {"fullname": "fastexcel.ColumnInfo.dtype", "modulename": "fastexcel", "qualname": "ColumnInfo.dtype", "kind": "variable", "doc": "fastexcel.DType. The dtype of the column
\n"}, "fastexcel.FastExcelError": {"fullname": "fastexcel.FastExcelError", "modulename": "fastexcel", "qualname": "FastExcelError", "kind": "class", "doc": "The base class for all fastexcel errors
\n", "bases": "builtins.Exception"}, "fastexcel.CannotRetrieveCellDataError": {"fullname": "fastexcel.CannotRetrieveCellDataError", "modulename": "fastexcel", "qualname": "CannotRetrieveCellDataError", "kind": "class", "doc": "Data for a given cell cannot be retrieved
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+ /** pdoc search index */const docs = {"version": "0.9.5", "fields": ["qualname", "fullname", "annotation", "default_value", "signature", "bases", "doc"], "ref": "fullname", "documentStore": {"docs": {"fastexcel": {"fullname": "fastexcel", "modulename": "fastexcel", "kind": "module", "doc": "\n"}, "fastexcel.read_excel": {"fullname": "fastexcel.read_excel", "modulename": "fastexcel", "qualname": "read_excel", "kind": "function", "doc": "Opens and loads an excel file.
\n\nParameters
\n\n\n- source: The path to a file or its content as bytes
\n
\n", "signature": "(source: pathlib.Path | str | bytes) -> fastexcel.ExcelReader:", "funcdef": "def"}, "fastexcel.DType": {"fullname": "fastexcel.DType", "modulename": "fastexcel", "qualname": "DType", "kind": "variable", "doc": "\n", "default_value": "typing.Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']"}, "fastexcel.DTypeMap": {"fullname": "fastexcel.DTypeMap", "modulename": "fastexcel", "qualname": "DTypeMap", "kind": "variable", "doc": "\n", "annotation": ": TypeAlias", "default_value": "'dict[str | int, DType]'"}, "fastexcel.ExcelReader": {"fullname": "fastexcel.ExcelReader", "modulename": "fastexcel", "qualname": "ExcelReader", "kind": "class", "doc": "A class representing an open Excel file and allowing to read its sheets
\n"}, "fastexcel.ExcelReader.__init__": {"fullname": "fastexcel.ExcelReader.__init__", "modulename": "fastexcel", "qualname": "ExcelReader.__init__", "kind": "function", "doc": "\n", "signature": "(reader: _ExcelReader)"}, "fastexcel.ExcelReader.sheet_names": {"fullname": "fastexcel.ExcelReader.sheet_names", "modulename": "fastexcel", "qualname": "ExcelReader.sheet_names", "kind": "variable", "doc": "The list of sheet names
\n", "annotation": ": list[str]"}, "fastexcel.ExcelReader.load_sheet": {"fullname": "fastexcel.ExcelReader.load_sheet", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet", "kind": "function", "doc": "Loads a sheet lazily by index or name.
\n\nParameters
\n\n\n- idx_or_name: The index (starting at 0) or the name of the sheet to load.
\n- header_row: The index of the row containing the column labels, default index is 0.\nIf
None, the sheet does not have any column labels.\nAny rows before the header_row will be automatically skipped. \n- column_names: Overrides headers found in the document.\nIf
column_names is used, header_row will be ignored. \n- n_rows: Specifies how many rows should be loaded.\nIf
None, all rows are loaded \n- skip_rows: Specifies how many rows should be skipped after the
header_row.\nAny rows before the header_row are automatically skipped.\nIf header_row is None:\n\n- if
skip_rows is None (default): it skips all empty rows\nat the beginning of the sheet. \n- if
skip_rows is a number, it skips the specified number\nof rows from the start of the sheet. \n
\n- schema_sample_rows: Specifies how many rows should be used to determine\nthe dtype of a column. Cannot be 0. A specific dtype can be\nenforced for some or all columns through the
dtypes parameter.\nIf None, all rows will be used. \n- dtype_coercion: Specifies how type coercion should behave.
coerce (the default)\nwill try to coerce different dtypes in a column to the same one,\nwhereas strict will raise an error in case a column contains\nseveral dtypes. Note that this only applies to columns whose dtype\nis guessed, i.e. not specified via dtypes. \n- use_columns: Specifies the columns to use. Can either be: \n
\nNone to select all columns- A list of strings and ints, the column names and/or indices\n(starting at 0)
\n- A string, a comma separated list of Excel column letters and column\nranges (e.g.
\u201cA:E\u201d or \u201cA,C,E:F\u201d, which would result in\nA,B,C,D,E and A,C,E,F) \n- A callable, a function that takes a column and returns a boolean\nindicating whether the column should be used
\n
\n- dtypes: An optional dtype (for all columns)\nor dict of dtypes with keys as column indices or names.
\n
\n", "signature": "(\tself,\tidx_or_name: int | str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int | None = None,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: Union[list[str], list[int], str, Callable[[ColumnInfo], bool], NoneType] = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelReader.table_names": {"fullname": "fastexcel.ExcelReader.table_names", "modulename": "fastexcel", "qualname": "ExcelReader.table_names", "kind": "function", "doc": "The list of table names.
\n\nWill return an empty list if no tables are found.
\n\nParameters
\n\n\n- sheet_name: If given, will limit the list to the given sheet, will be faster\ntoo.
\n
\n", "signature": "(self, sheet_name: str | None = None) -> list[str]:", "funcdef": "def"}, "fastexcel.ExcelReader.load_table": {"fullname": "fastexcel.ExcelReader.load_table", "modulename": "fastexcel", "qualname": "ExcelReader.load_table", "kind": "function", "doc": "Loads a table by name.
\n\nParameters
\n\n\n- name: The name of the table to load.
\n- header_row: The index of the row containing the column labels.\nIf
None, the table's column names will be used.\nAny rows before the header_row will be automatically skipped. \n- column_names: Overrides headers found in the document.\nIf
column_names is used, header_row will be ignored. \n- n_rows: Specifies how many rows should be loaded.\nIf
None, all rows are loaded \n- skip_rows: Specifies how many rows should be skipped after the
header_row.\nAny rows before the header_row are automatically skipped.\nIf header_row is None, it skips the number of rows from the\nstart of the sheet. \n- schema_sample_rows: Specifies how many rows should be used to determine\nthe dtype of a column. Cannot be 0. A specific dtype can be\nenforced for some or all columns through the
dtypes parameter.\nIf None, all rows will be used. \n- dtype_coercion: Specifies how type coercion should behave.
coerce (the default)\nwill try to coerce different dtypes in a column to the same one,\nwhereas strict will raise an error in case a column contains\nseveral dtypes. Note that this only applies to columns whose dtype\nis guessed, i.e. not specified via dtypes. \n- use_columns: Specifies the columns to use. Can either be: \n
\nNone to select all columns- A list of strings and ints, the column names and/or indices\n(starting at 0)
\n- A string, a comma separated list of Excel column letters and column\nranges (e.g.
\u201cA:E\u201d or \u201cA,C,E:F\u201d, which would result in\nA,B,C,D,E and A,C,E,F) \n- A callable, a function that takes a column and returns a boolean\nindicating whether the column should be used
\n
\n- dtypes: An optional dtype (for all columns)\nor dict of dtypes with keys as column indices or names.
\n
\n", "signature": "(\tself,\tname: str,\t*,\theader_row: int | None = None,\tcolumn_names: list[str] | None = None,\tskip_rows: int = 0,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: Union[list[str], list[int], str, Callable[[ColumnInfo], bool], NoneType] = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None,\teager: bool = False) -> fastexcel.ExcelTable | pyarrow.lib.RecordBatch:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet_eager": {"fullname": "fastexcel.ExcelReader.load_sheet_eager", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_eager", "kind": "function", "doc": "Loads a sheet eagerly by index or name.
\n\nFor xlsx files, this will be faster and more memory-efficient, as it will use\nworksheet_range_ref under the hood, which returns borrowed types.
\n\nRefer to load_sheet for parameter documentation
\n", "signature": "(\tself,\tidx_or_name: int | str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int | None = None,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: list[str] | list[int] | str | None = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None) -> pyarrow.lib.RecordBatch:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet_by_name": {"fullname": "fastexcel.ExcelReader.load_sheet_by_name", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_by_name", "kind": "function", "doc": "Loads a sheet by name.
\n\nRefer to load_sheet for parameter documentation
\n", "signature": "(\tself,\tname: str,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int | None = None,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: Union[list[str], list[int], str, Callable[[ColumnInfo], bool], NoneType] = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelReader.load_sheet_by_idx": {"fullname": "fastexcel.ExcelReader.load_sheet_by_idx", "modulename": "fastexcel", "qualname": "ExcelReader.load_sheet_by_idx", "kind": "function", "doc": "Loads a sheet by index.
\n\nRefer to load_sheet for parameter documentation
\n", "signature": "(\tself,\tidx: int,\t*,\theader_row: int | None = 0,\tcolumn_names: list[str] | None = None,\tskip_rows: int | None = None,\tn_rows: int | None = None,\tschema_sample_rows: int | None = 1000,\tdtype_coercion: Literal['coerce', 'strict'] = 'coerce',\tuse_columns: Union[list[str], list[int], str, Callable[[ColumnInfo], bool], NoneType] = None,\tdtypes: Union[Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration'], dict[str | int, Literal['null', 'int', 'float', 'string', 'boolean', 'datetime', 'date', 'duration']], NoneType] = None) -> fastexcel.ExcelSheet:", "funcdef": "def"}, "fastexcel.ExcelSheet": {"fullname": "fastexcel.ExcelSheet", "modulename": "fastexcel", "qualname": "ExcelSheet", "kind": "class", "doc": "A class representing a single sheet in an Excel File
\n"}, "fastexcel.ExcelSheet.__init__": {"fullname": "fastexcel.ExcelSheet.__init__", "modulename": "fastexcel", "qualname": "ExcelSheet.__init__", "kind": "function", "doc": "\n", "signature": "(sheet: _ExcelSheet)"}, "fastexcel.ExcelSheet.name": {"fullname": "fastexcel.ExcelSheet.name", "modulename": "fastexcel", "qualname": "ExcelSheet.name", "kind": "variable", "doc": "The name of the sheet
\n", "annotation": ": str"}, "fastexcel.ExcelSheet.width": {"fullname": "fastexcel.ExcelSheet.width", "modulename": "fastexcel", "qualname": "ExcelSheet.width", "kind": "variable", "doc": "The sheet's width
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.height": {"fullname": "fastexcel.ExcelSheet.height", "modulename": "fastexcel", "qualname": "ExcelSheet.height", "kind": "variable", "doc": "The sheet's height, with skip_rows and nrows applied
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.total_height": {"fullname": "fastexcel.ExcelSheet.total_height", "modulename": "fastexcel", "qualname": "ExcelSheet.total_height", "kind": "variable", "doc": "The sheet's total height
\n", "annotation": ": int"}, "fastexcel.ExcelSheet.selected_columns": {"fullname": "fastexcel.ExcelSheet.selected_columns", "modulename": "fastexcel", "qualname": "ExcelSheet.selected_columns", "kind": "variable", "doc": "The sheet's selected columns
\n", "annotation": ": list[ColumnInfo]"}, "fastexcel.ExcelSheet.available_columns": {"fullname": "fastexcel.ExcelSheet.available_columns", "modulename": "fastexcel", "qualname": "ExcelSheet.available_columns", "kind": "variable", "doc": "The columns available for the given sheet
\n", "annotation": ": list[ColumnInfo]"}, "fastexcel.ExcelSheet.specified_dtypes": {"fullname": "fastexcel.ExcelSheet.specified_dtypes", "modulename": "fastexcel", "qualname": "ExcelSheet.specified_dtypes", "kind": "variable", "doc": "The dtypes specified for the sheet
\n", "annotation": ": 'DTypeMap | None'"}, "fastexcel.ExcelSheet.visible": {"fullname": "fastexcel.ExcelSheet.visible", "modulename": "fastexcel", "qualname": "ExcelSheet.visible", "kind": "variable", "doc": "The visibility of the sheet
\n", "annotation": ": Literal['visible', 'hidden', 'veryhidden']"}, "fastexcel.ExcelSheet.to_arrow": {"fullname": "fastexcel.ExcelSheet.to_arrow", "modulename": "fastexcel", "qualname": "ExcelSheet.to_arrow", "kind": "function", "doc": "Converts the sheet to a pyarrow RecordBatch
\n", "signature": "(self) -> pyarrow.lib.RecordBatch:", "funcdef": "def"}, "fastexcel.ExcelSheet.to_pandas": {"fullname": "fastexcel.ExcelSheet.to_pandas", "modulename": "fastexcel", "qualname": "ExcelSheet.to_pandas", "kind": "function", "doc": "Converts the sheet to a Pandas DataFrame.
\n\nRequires the pandas extra to be installed.
\n", "signature": "(self) -> pandas.core.frame.DataFrame:", "funcdef": "def"}, "fastexcel.ExcelSheet.to_polars": {"fullname": "fastexcel.ExcelSheet.to_polars", "modulename": "fastexcel", "qualname": "ExcelSheet.to_polars", "kind": "function", "doc": "Converts the sheet to a Polars DataFrame.
\n\nRequires the polars extra to be installed.
\n", "signature": "(self) -> polars.dataframe.frame.DataFrame:", "funcdef": "def"}, "fastexcel.DTypeFrom": {"fullname": "fastexcel.DTypeFrom", "modulename": "fastexcel", "qualname": "DTypeFrom", "kind": "variable", "doc": "\n", "annotation": ": TypeAlias", "default_value": "Literal['provided_by_index', 'provided_by_name', 'guessed']"}, "fastexcel.ColumnNameFrom": {"fullname": "fastexcel.ColumnNameFrom", "modulename": "fastexcel", "qualname": "ColumnNameFrom", "kind": "variable", "doc": "\n", "annotation": ": TypeAlias", "default_value": "Literal['provided', 'looked_up', 'generated']"}, "fastexcel.ColumnInfo": {"fullname": "fastexcel.ColumnInfo", "modulename": "fastexcel", "qualname": "ColumnInfo", "kind": "class", "doc": "This class provides information about a single column in a sheet
\n"}, "fastexcel.ColumnInfo.column_name_from": {"fullname": "fastexcel.ColumnInfo.column_name_from", "modulename": "fastexcel", "qualname": "ColumnInfo.column_name_from", "kind": "variable", "doc": "fastexcel.ColumnNameFrom. How the name of the column was determined.
\n\nOne of three possible values:
\n\n\n\"provided\": The column name was provided via the use_columns parameter\"looked_up\": The column name was looked up from the data found in the sheet\"generated\": The column name was generated from the column index, either because\nheader_row was None, or because it could not be looked up
\n"}, "fastexcel.ColumnInfo.dtype_from": {"fullname": "fastexcel.ColumnInfo.dtype_from", "modulename": "fastexcel", "qualname": "ColumnInfo.dtype_from", "kind": "variable", "doc": "fastexcel.DTypeFrom. How the dtype of the column was determined.
\n\nOne of three possible values:
\n\n\n\"provided_by_index\": The dtype was specified via the column index\"provided_by_name\": The dtype was specified via the column name\"guessed\": The dtype was determined from the content of the column
\n"}, "fastexcel.ColumnInfo.name": {"fullname": "fastexcel.ColumnInfo.name", "modulename": "fastexcel", "qualname": "ColumnInfo.name", "kind": "variable", "doc": "str. The name of the column
\n"}, "fastexcel.ColumnInfo.index": {"fullname": "fastexcel.ColumnInfo.index", "modulename": "fastexcel", "qualname": "ColumnInfo.index", "kind": "variable", "doc": "int. The index of the column
\n"}, "fastexcel.ColumnInfo.dtype": {"fullname": "fastexcel.ColumnInfo.dtype", "modulename": "fastexcel", "qualname": "ColumnInfo.dtype", "kind": "variable", "doc": "fastexcel.DType. The dtype of the column
\n"}, "fastexcel.FastExcelError": {"fullname": "fastexcel.FastExcelError", "modulename": "fastexcel", "qualname": "FastExcelError", "kind": "class", "doc": "The base class for all fastexcel errors
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\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.CalamineError": {"fullname": "fastexcel.CalamineError", "modulename": "fastexcel", "qualname": "CalamineError", "kind": "class", "doc": "Generic calamine error
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\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.ColumnNotFoundError": {"fullname": "fastexcel.ColumnNotFoundError", "modulename": "fastexcel", "qualname": "ColumnNotFoundError", "kind": "class", "doc": "Column was not found
\n", "bases": "_fastexcel.FastExcelError"}, "fastexcel.ArrowError": {"fullname": "fastexcel.ArrowError", "modulename": "fastexcel", "qualname": "ArrowError", "kind": "class", "doc": "Generic arrow error
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// mirrored in build-search-index.js (part 1)
// Also split on html tags. this is a cheap heuristic, but good enough.