Coverage for /var/srv/projects/api.amasfac.comuna18.com/tmp/venv/lib/python3.9/site-packages/pandas/core/config

1"""

2This module is imported from the pandas package __init__.py file

3in order to ensure that the core.config options registered here will

4be available as soon as the user loads the package. if register_option

5is invoked inside specific modules, they will not be registered until that

6module is imported, which may or may not be a problem.

8If you need to make sure options are available even before a certain

9module is imported, register them here rather than in the module.

11"""

12from __future__ import annotations

14import os

15from typing import Callable

16import warnings

18import pandas._config.config as cf

19from pandas._config.config import (

20 is_bool,

21 is_callable,

22 is_instance_factory,

23 is_int,

24 is_nonnegative_int,

25 is_one_of_factory,

26 is_str,

27 is_text,

28)

30from pandas.util._exceptions import find_stack_level

32# compute

34use_bottleneck_doc = """

35: bool

36 Use the bottleneck library to accelerate if it is installed,

37 the default is True

38 Valid values: False,True

39"""

42def use_bottleneck_cb(key) -> None:

43 from pandas.core import nanops

45 nanops.set_use_bottleneck(cf.get_option(key))

48use_numexpr_doc = """

49: bool

50 Use the numexpr library to accelerate computation if it is installed,

51 the default is True

52 Valid values: False,True

53"""

56def use_numexpr_cb(key) -> None:

57 from pandas.core.computation import expressions

59 expressions.set_use_numexpr(cf.get_option(key))

62use_numba_doc = """

63: bool

64 Use the numba engine option for select operations if it is installed,

65 the default is False

66 Valid values: False,True

67"""

70def use_numba_cb(key) -> None:

71 from pandas.core.util import numba_

73 numba_.set_use_numba(cf.get_option(key))

76with cf.config_prefix("compute"):

77 cf.register_option(

78 "use_bottleneck",

79 True,

80 use_bottleneck_doc,

81 validator=is_bool,

82 cb=use_bottleneck_cb,

83 )

84 cf.register_option(

85 "use_numexpr", True, use_numexpr_doc, validator=is_bool, cb=use_numexpr_cb

86 )

87 cf.register_option(

88 "use_numba", False, use_numba_doc, validator=is_bool, cb=use_numba_cb

89 )

90#

91# options from the "display" namespace

93pc_precision_doc = """

94: int

95 Floating point output precision in terms of number of places after the

96 decimal, for regular formatting as well as scientific notation. Similar

97 to ``precision`` in :meth:`numpy.set_printoptions`.

98"""

100pc_colspace_doc = """

101: int

102 Default space for DataFrame columns.

103"""

104

105pc_max_rows_doc = """

106: int

107 If max_rows is exceeded, switch to truncate view. Depending on

108 `large_repr`, objects are either centrally truncated or printed as

109 a summary view. 'None' value means unlimited.

110

111 In case python/IPython is running in a terminal and `large_repr`

112 equals 'truncate' this can be set to 0 and pandas will auto-detect

113 the height of the terminal and print a truncated object which fits

114 the screen height. The IPython notebook, IPython qtconsole, or

115 IDLE do not run in a terminal and hence it is not possible to do

116 correct auto-detection.

117"""

118

119pc_min_rows_doc = """

120: int

121 The numbers of rows to show in a truncated view (when `max_rows` is

122 exceeded). Ignored when `max_rows` is set to None or 0. When set to

123 None, follows the value of `max_rows`.

124"""

125

126pc_max_cols_doc = """

127: int

128 If max_cols is exceeded, switch to truncate view. Depending on

129 `large_repr`, objects are either centrally truncated or printed as

130 a summary view. 'None' value means unlimited.

131

132 In case python/IPython is running in a terminal and `large_repr`

133 equals 'truncate' this can be set to 0 and pandas will auto-detect

134 the width of the terminal and print a truncated object which fits

135 the screen width. The IPython notebook, IPython qtconsole, or IDLE

136 do not run in a terminal and hence it is not possible to do

137 correct auto-detection.

138"""

139

140pc_max_categories_doc = """

141: int

142 This sets the maximum number of categories pandas should output when

143 printing out a `Categorical` or a Series of dtype "category".

144"""

145

146pc_max_info_cols_doc = """

147: int

148 max_info_columns is used in DataFrame.info method to decide if

149 per column information will be printed.

150"""

151

152pc_nb_repr_h_doc = """

153: boolean

154 When True, IPython notebook will use html representation for

155 pandas objects (if it is available).

156"""

157

158pc_pprint_nest_depth = """

159: int

160 Controls the number of nested levels to process when pretty-printing

161"""

162

163pc_multi_sparse_doc = """

164: boolean

165 "sparsify" MultiIndex display (don't display repeated

166 elements in outer levels within groups)

167"""

168

169float_format_doc = """

170: callable

171 The callable should accept a floating point number and return

172 a string with the desired format of the number. This is used

173 in some places like SeriesFormatter.

174 See formats.format.EngFormatter for an example.

175"""

176

177max_colwidth_doc = """

178: int or None

179 The maximum width in characters of a column in the repr of

180 a pandas data structure. When the column overflows, a "..."

181 placeholder is embedded in the output. A 'None' value means unlimited.

182"""

183

184colheader_justify_doc = """

185: 'left'/'right'

186 Controls the justification of column headers. used by DataFrameFormatter.

187"""

188

189pc_expand_repr_doc = """

190: boolean

191 Whether to print out the full DataFrame repr for wide DataFrames across

192 multiple lines, `max_columns` is still respected, but the output will

193 wrap-around across multiple "pages" if its width exceeds `display.width`.

194"""

195

196pc_show_dimensions_doc = """

197: boolean or 'truncate'

198 Whether to print out dimensions at the end of DataFrame repr.

199 If 'truncate' is specified, only print out the dimensions if the

200 frame is truncated (e.g. not display all rows and/or columns)

201"""

202

203pc_east_asian_width_doc = """

204: boolean

205 Whether to use the Unicode East Asian Width to calculate the display text

206 width.

207 Enabling this may affect to the performance (default: False)

208"""

209

210pc_ambiguous_as_wide_doc = """

211: boolean

212 Whether to handle Unicode characters belong to Ambiguous as Wide (width=2)

213 (default: False)

214"""

215

216pc_latex_repr_doc = """

217: boolean

218 Whether to produce a latex DataFrame representation for jupyter

219 environments that support it.

220 (default: False)

221"""

222

223pc_table_schema_doc = """

224: boolean

225 Whether to publish a Table Schema representation for frontends

226 that support it.

227 (default: False)

228"""

229

230pc_html_border_doc = """

231: int

232 A ``border=value`` attribute is inserted in the ``<table>`` tag

233 for the DataFrame HTML repr.

234"""

235

236pc_html_use_mathjax_doc = """\

237: boolean

238 When True, Jupyter notebook will process table contents using MathJax,

239 rendering mathematical expressions enclosed by the dollar symbol.

240 (default: True)

241"""

242

243pc_max_dir_items = """\

244: int

245 The number of items that will be added to `dir(...)`. 'None' value means

246 unlimited. Because dir is cached, changing this option will not immediately

247 affect already existing dataframes until a column is deleted or added.

248

249 This is for instance used to suggest columns from a dataframe to tab

250 completion.

251"""

252

253pc_width_doc = """

254: int

255 Width of the display in characters. In case python/IPython is running in

256 a terminal this can be set to None and pandas will correctly auto-detect

257 the width.

258 Note that the IPython notebook, IPython qtconsole, or IDLE do not run in a

259 terminal and hence it is not possible to correctly detect the width.

260"""

261

262pc_chop_threshold_doc = """

263: float or None

264 if set to a float value, all float values smaller than the given threshold

265 will be displayed as exactly 0 by repr and friends.

266"""

267

268pc_max_seq_items = """

269: int or None

270 When pretty-printing a long sequence, no more then `max_seq_items`

271 will be printed. If items are omitted, they will be denoted by the

272 addition of "..." to the resulting string.

273

274 If set to None, the number of items to be printed is unlimited.

275"""

276

277pc_max_info_rows_doc = """

278: int or None

279 df.info() will usually show null-counts for each column.

280 For large frames this can be quite slow. max_info_rows and max_info_cols

281 limit this null check only to frames with smaller dimensions than

282 specified.

283"""

284

285pc_large_repr_doc = """

286: 'truncate'/'info'

287 For DataFrames exceeding max_rows/max_cols, the repr (and HTML repr) can

288 show a truncated table (the default from 0.13), or switch to the view from

289 df.info() (the behaviour in earlier versions of pandas).

290"""

291

292pc_memory_usage_doc = """

293: bool, string or None

294 This specifies if the memory usage of a DataFrame should be displayed when

295 df.info() is called. Valid values True,False,'deep'

296"""

297

298pc_latex_escape = """

299: bool

300 This specifies if the to_latex method of a Dataframe uses escapes special

301 characters.

302 Valid values: False,True

303"""

304

305pc_latex_longtable = """

306:bool

307 This specifies if the to_latex method of a Dataframe uses the longtable

308 format.

309 Valid values: False,True

310"""

311

312pc_latex_multicolumn = """

313: bool

314 This specifies if the to_latex method of a Dataframe uses multicolumns

315 to pretty-print MultiIndex columns.

316 Valid values: False,True

317"""

318

319pc_latex_multicolumn_format = """

320: string

321 This specifies the format for multicolumn headers.

322 Can be surrounded with '|'.

323 Valid values: 'l', 'c', 'r', 'p{<width>}'

324"""

325

326pc_latex_multirow = """

327: bool

328 This specifies if the to_latex method of a Dataframe uses multirows

329 to pretty-print MultiIndex rows.

330 Valid values: False,True

331"""

332

333

334def table_schema_cb(key) -> None:

335 from pandas.io.formats.printing import enable_data_resource_formatter

336

337 enable_data_resource_formatter(cf.get_option(key))

338

339

340def is_terminal() -> bool:

341 """

342 Detect if Python is running in a terminal.

343

344 Returns True if Python is running in a terminal or False if not.

345 """

346 try:

347 # error: Name 'get_ipython' is not defined

348 ip = get_ipython() # type: ignore[name-defined]

349 except NameError: # assume standard Python interpreter in a terminal

350 return True

351 else:

352 if hasattr(ip, "kernel"): # IPython as a Jupyter kernel

353 return False

354 else: # IPython in a terminal

355 return True

356

357

358with cf.config_prefix("display"):

359 cf.register_option("precision", 6, pc_precision_doc, validator=is_nonnegative_int)

360 cf.register_option(

361 "float_format",

362 None,

363 float_format_doc,

364 validator=is_one_of_factory([None, is_callable]),

365 )

366

367 def _deprecate_column_space(key):

368 warnings.warn(

369 "column_space is deprecated and will be removed "

370 "in a future version. Use df.to_string(col_space=...) "

371 "instead.",

372 FutureWarning,

373 stacklevel=find_stack_level(),

374 )

375

376 cf.register_option("column_space", 12, validator=is_int, cb=_deprecate_column_space)

377 cf.register_option(

378 "max_info_rows",

379 1690785,

380 pc_max_info_rows_doc,

381 validator=is_instance_factory((int, type(None))),

382 )

383 cf.register_option("max_rows", 60, pc_max_rows_doc, validator=is_nonnegative_int)

384 cf.register_option(

385 "min_rows",

386 10,

387 pc_min_rows_doc,

388 validator=is_instance_factory([type(None), int]),

389 )

390 cf.register_option("max_categories", 8, pc_max_categories_doc, validator=is_int)

391

392 def _deprecate_negative_int_max_colwidth(key):

393 value = cf.get_option(key)

394 if value is not None and value < 0:

395 warnings.warn(

396 "Passing a negative integer is deprecated in version 1.0 and "

397 "will not be supported in future version. Instead, use None "

398 "to not limit the column width.",

399 FutureWarning,

400 stacklevel=find_stack_level(),

401 )

402

403 cf.register_option(

404 # TODO(2.0): change `validator=is_nonnegative_int` see GH#31569

405 "max_colwidth",

406 50,

407 max_colwidth_doc,

408 validator=is_instance_factory([type(None), int]),

409 cb=_deprecate_negative_int_max_colwidth,

410 )

411 if is_terminal(): 411 ↛ 414line 411 didn't jump to line 414, because the condition on line 411 was never false

412 max_cols = 0 # automatically determine optimal number of columns

413 else:

414 max_cols = 20 # cannot determine optimal number of columns

415 cf.register_option(

416 "max_columns", max_cols, pc_max_cols_doc, validator=is_nonnegative_int

417 )

418 cf.register_option(

419 "large_repr",

420 "truncate",

421 pc_large_repr_doc,

422 validator=is_one_of_factory(["truncate", "info"]),

423 )

424 cf.register_option("max_info_columns", 100, pc_max_info_cols_doc, validator=is_int)

425 cf.register_option(

426 "colheader_justify", "right", colheader_justify_doc, validator=is_text

427 )

428 cf.register_option("notebook_repr_html", True, pc_nb_repr_h_doc, validator=is_bool)

429 cf.register_option("pprint_nest_depth", 3, pc_pprint_nest_depth, validator=is_int)

430 cf.register_option("multi_sparse", True, pc_multi_sparse_doc, validator=is_bool)

431 cf.register_option("expand_frame_repr", True, pc_expand_repr_doc)

432 cf.register_option(

433 "show_dimensions",

434 "truncate",

435 pc_show_dimensions_doc,

436 validator=is_one_of_factory([True, False, "truncate"]),

437 )

438 cf.register_option("chop_threshold", None, pc_chop_threshold_doc)

439 cf.register_option("max_seq_items", 100, pc_max_seq_items)

440 cf.register_option(

441 "width", 80, pc_width_doc, validator=is_instance_factory([type(None), int])

442 )

443 cf.register_option(

444 "memory_usage",

445 True,

446 pc_memory_usage_doc,

447 validator=is_one_of_factory([None, True, False, "deep"]),

448 )

449 cf.register_option(

450 "unicode.east_asian_width", False, pc_east_asian_width_doc, validator=is_bool

451 )

452 cf.register_option(

453 "unicode.ambiguous_as_wide", False, pc_east_asian_width_doc, validator=is_bool

454 )

455 cf.register_option("latex.repr", False, pc_latex_repr_doc, validator=is_bool)

456 cf.register_option("latex.escape", True, pc_latex_escape, validator=is_bool)

457 cf.register_option("latex.longtable", False, pc_latex_longtable, validator=is_bool)

458 cf.register_option(

459 "latex.multicolumn", True, pc_latex_multicolumn, validator=is_bool

460 )

461 cf.register_option(

462 "latex.multicolumn_format", "l", pc_latex_multicolumn, validator=is_text

463 )

464 cf.register_option("latex.multirow", False, pc_latex_multirow, validator=is_bool)

465 cf.register_option(

466 "html.table_schema",

467 False,

468 pc_table_schema_doc,

469 validator=is_bool,

470 cb=table_schema_cb,

471 )

472 cf.register_option("html.border", 1, pc_html_border_doc, validator=is_int)

473 cf.register_option(

474 "html.use_mathjax", True, pc_html_use_mathjax_doc, validator=is_bool

475 )

476 cf.register_option(

477 "max_dir_items", 100, pc_max_dir_items, validator=is_nonnegative_int

478 )

479

480tc_sim_interactive_doc = """

481: boolean

482 Whether to simulate interactive mode for purposes of testing

483"""

484

485with cf.config_prefix("mode"):

486 cf.register_option("sim_interactive", False, tc_sim_interactive_doc)

487

488use_inf_as_null_doc = """

489: boolean

490 use_inf_as_null had been deprecated and will be removed in a future

491 version. Use `use_inf_as_na` instead.

492"""

493

494use_inf_as_na_doc = """

495: boolean

496 True means treat None, NaN, INF, -INF as NA (old way),

497 False means None and NaN are null, but INF, -INF are not NA

498 (new way).

499"""

500

501# We don't want to start importing everything at the global context level

502# or we'll hit circular deps.

503

504

505def use_inf_as_na_cb(key) -> None:

506 from pandas.core.dtypes.missing import _use_inf_as_na

507

508 _use_inf_as_na(key)

509

510

511with cf.config_prefix("mode"):

512 cf.register_option("use_inf_as_na", False, use_inf_as_na_doc, cb=use_inf_as_na_cb)

513 cf.register_option(

514 "use_inf_as_null", False, use_inf_as_null_doc, cb=use_inf_as_na_cb

515 )

516

517

518cf.deprecate_option(

519 "mode.use_inf_as_null", msg=use_inf_as_null_doc, rkey="mode.use_inf_as_na"

520)

521

522

523data_manager_doc = """

524: string

525 Internal data manager type; can be "block" or "array". Defaults to "block",

526 unless overridden by the 'PANDAS_DATA_MANAGER' environment variable (needs

527 to be set before pandas is imported).

528"""

529

530

531with cf.config_prefix("mode"):

532 cf.register_option(

533 "data_manager",

534 # Get the default from an environment variable, if set, otherwise defaults

535 # to "block". This environment variable can be set for testing.

536 os.environ.get("PANDAS_DATA_MANAGER", "block"),

537 data_manager_doc,

538 validator=is_one_of_factory(["block", "array"]),

539 )

540

541

542# TODO better name?

543copy_on_write_doc = """

544: bool

545 Use new copy-view behaviour using Copy-on-Write. Defaults to False,

546 unless overridden by the 'PANDAS_COPY_ON_WRITE' environment variable

547 (if set to "1" for True, needs to be set before pandas is imported).

548"""

549

550

551with cf.config_prefix("mode"):

552 cf.register_option(

553 "copy_on_write",

554 # Get the default from an environment variable, if set, otherwise defaults

555 # to False. This environment variable can be set for testing.

556 os.environ.get("PANDAS_COPY_ON_WRITE", "0") == "1",

557 copy_on_write_doc,

558 validator=is_bool,

559 )

560

561

562# user warnings

563chained_assignment = """

564: string

565 Raise an exception, warn, or no action if trying to use chained assignment,

566 The default is warn

567"""

568

569with cf.config_prefix("mode"):

570 cf.register_option(

571 "chained_assignment",

572 "warn",

573 chained_assignment,

574 validator=is_one_of_factory([None, "warn", "raise"]),

575 )

576

577

578string_storage_doc = """

579: string

580 The default storage for StringDtype.

581"""

582

583with cf.config_prefix("mode"):

584 cf.register_option(

585 "string_storage",

586 "python",

587 string_storage_doc,

588 validator=is_one_of_factory(["python", "pyarrow"]),

589 )

590

591# Set up the io.excel specific reader configuration.

592reader_engine_doc = """

593: string

594 The default Excel reader engine for '{ext}' files. Available options:

595 auto, {others}.

596"""

597

598_xls_options = ["xlrd"]

599_xlsm_options = ["xlrd", "openpyxl"]

600_xlsx_options = ["xlrd", "openpyxl"]

601_ods_options = ["odf"]

602_xlsb_options = ["pyxlsb"]

603

604

605with cf.config_prefix("io.excel.xls"):

606 cf.register_option(

607 "reader",

608 "auto",

609 reader_engine_doc.format(ext="xls", others=", ".join(_xls_options)),

610 validator=is_one_of_factory(_xls_options + ["auto"]),

611 )

612

613with cf.config_prefix("io.excel.xlsm"):

614 cf.register_option(

615 "reader",

616 "auto",

617 reader_engine_doc.format(ext="xlsm", others=", ".join(_xlsm_options)),

618 validator=is_one_of_factory(_xlsm_options + ["auto"]),

619 )

620

621

622with cf.config_prefix("io.excel.xlsx"):

623 cf.register_option(

624 "reader",

625 "auto",

626 reader_engine_doc.format(ext="xlsx", others=", ".join(_xlsx_options)),

627 validator=is_one_of_factory(_xlsx_options + ["auto"]),

628 )

629

630

631with cf.config_prefix("io.excel.ods"):

632 cf.register_option(

633 "reader",

634 "auto",

635 reader_engine_doc.format(ext="ods", others=", ".join(_ods_options)),

636 validator=is_one_of_factory(_ods_options + ["auto"]),

637 )

638

639with cf.config_prefix("io.excel.xlsb"):

640 cf.register_option(

641 "reader",

642 "auto",

643 reader_engine_doc.format(ext="xlsb", others=", ".join(_xlsb_options)),

644 validator=is_one_of_factory(_xlsb_options + ["auto"]),

645 )

646

647# Set up the io.excel specific writer configuration.

648writer_engine_doc = """

649: string

650 The default Excel writer engine for '{ext}' files. Available options:

651 auto, {others}.

652"""

653

654_xls_options = ["xlwt"]

655_xlsm_options = ["openpyxl"]

656_xlsx_options = ["openpyxl", "xlsxwriter"]

657_ods_options = ["odf"]

658

659

660with cf.config_prefix("io.excel.xls"):

661 cf.register_option(

662 "writer",

663 "auto",

664 writer_engine_doc.format(ext="xls", others=", ".join(_xls_options)),

665 validator=str,

666 )

667cf.deprecate_option(

668 "io.excel.xls.writer",

669 msg="As the xlwt package is no longer maintained, the xlwt engine will be "

670 "removed in a future version of pandas. This is the only engine in pandas that "

671 "supports writing in the xls format. Install openpyxl and write to an "

672 "xlsx file instead.",

673)

674

675with cf.config_prefix("io.excel.xlsm"):

676 cf.register_option(

677 "writer",

678 "auto",

679 writer_engine_doc.format(ext="xlsm", others=", ".join(_xlsm_options)),

680 validator=str,

681 )

682

683

684with cf.config_prefix("io.excel.xlsx"):

685 cf.register_option(

686 "writer",

687 "auto",

688 writer_engine_doc.format(ext="xlsx", others=", ".join(_xlsx_options)),

689 validator=str,

690 )

691

692

693with cf.config_prefix("io.excel.ods"):

694 cf.register_option(

695 "writer",

696 "auto",

697 writer_engine_doc.format(ext="ods", others=", ".join(_ods_options)),

698 validator=str,

699 )

700

701

702# Set up the io.parquet specific configuration.

703parquet_engine_doc = """

704: string

705 The default parquet reader/writer engine. Available options:

706 'auto', 'pyarrow', 'fastparquet', the default is 'auto'

707"""

708

709with cf.config_prefix("io.parquet"):

710 cf.register_option(

711 "engine",

712 "auto",

713 parquet_engine_doc,

714 validator=is_one_of_factory(["auto", "pyarrow", "fastparquet"]),

715 )

716

717

718# Set up the io.sql specific configuration.

719sql_engine_doc = """

720: string

721 The default sql reader/writer engine. Available options:

722 'auto', 'sqlalchemy', the default is 'auto'

723"""

724

725with cf.config_prefix("io.sql"):

726 cf.register_option(

727 "engine",

728 "auto",

729 sql_engine_doc,

730 validator=is_one_of_factory(["auto", "sqlalchemy"]),

731 )

732

733# --------

734# Plotting

735# ---------

736

737plotting_backend_doc = """

738: str

739 The plotting backend to use. The default value is "matplotlib", the

740 backend provided with pandas. Other backends can be specified by

741 providing the name of the module that implements the backend.

742"""

743

744

745def register_plotting_backend_cb(key) -> None:

746 if key == "matplotlib": 746 ↛ 749line 746 didn't jump to line 749, because the condition on line 746 was never false

747 # We defer matplotlib validation, since it's the default

748 return

749 from pandas.plotting._core import _get_plot_backend

750

751 _get_plot_backend(key)

752

753

754with cf.config_prefix("plotting"):

755 cf.register_option(

756 "backend",

757 defval="matplotlib",

758 doc=plotting_backend_doc,

759 validator=register_plotting_backend_cb,

760 )

761

762

763register_converter_doc = """

764: bool or 'auto'.

765 Whether to register converters with matplotlib's units registry for

766 dates, times, datetimes, and Periods. Toggling to False will remove

767 the converters, restoring any converters that pandas overwrote.

768"""

769

770

771def register_converter_cb(key) -> None:

772 from pandas.plotting import (

773 deregister_matplotlib_converters,

774 register_matplotlib_converters,

775 )

776

777 if cf.get_option(key):

778 register_matplotlib_converters()

779 else:

780 deregister_matplotlib_converters()

781

782

783with cf.config_prefix("plotting.matplotlib"):

784 cf.register_option(

785 "register_converters",

786 "auto",

787 register_converter_doc,

788 validator=is_one_of_factory(["auto", True, False]),

789 cb=register_converter_cb,

790 )

791

792# ------

793# Styler

794# ------

795

796styler_sparse_index_doc = """

797: bool

798 Whether to sparsify the display of a hierarchical index. Setting to False will

799 display each explicit level element in a hierarchical key for each row.

800"""

801

802styler_sparse_columns_doc = """

803: bool

804 Whether to sparsify the display of hierarchical columns. Setting to False will

805 display each explicit level element in a hierarchical key for each column.

806"""

807

808styler_render_repr = """

809: str

810 Determine which output to use in Jupyter Notebook in {"html", "latex"}.

811"""

812

813styler_max_elements = """

814: int

815 The maximum number of data-cell (<td>) elements that will be rendered before

816 trimming will occur over columns, rows or both if needed.

817"""

818

819styler_max_rows = """

820: int, optional

821 The maximum number of rows that will be rendered. May still be reduced to

822 satsify ``max_elements``, which takes precedence.

823"""

824

825styler_max_columns = """

826: int, optional

827 The maximum number of columns that will be rendered. May still be reduced to

828 satsify ``max_elements``, which takes precedence.

829"""

830

831styler_precision = """

832: int

833 The precision for floats and complex numbers.

834"""

835

836styler_decimal = """

837: str

838 The character representation for the decimal separator for floats and complex.

839"""

840

841styler_thousands = """

842: str, optional

843 The character representation for thousands separator for floats, int and complex.

844"""

845

846styler_na_rep = """

847: str, optional

848 The string representation for values identified as missing.

849"""

850

851styler_escape = """

852: str, optional

853 Whether to escape certain characters according to the given context; html or latex.

854"""

855

856styler_formatter = """

857: str, callable, dict, optional

858 A formatter object to be used as default within ``Styler.format``.

859"""

860

861styler_multirow_align = """

862: {"c", "t", "b"}

863 The specifier for vertical alignment of sparsified LaTeX multirows.

864"""

865

866styler_multicol_align = r"""

867: {"r", "c", "l", "naive-l", "naive-r"}

868 The specifier for horizontal alignment of sparsified LaTeX multicolumns. Pipe

869 decorators can also be added to non-naive values to draw vertical

870 rules, e.g. "\|r" will draw a rule on the left side of right aligned merged cells.

871"""

872

873styler_hrules = """

874: bool

875 Whether to add horizontal rules on top and bottom and below the headers.

876"""

877

878styler_environment = """

879: str

880 The environment to replace ``\\begin{table}``. If "longtable" is used results

881 in a specific longtable environment format.

882"""

883

884styler_encoding = """

885: str

886 The encoding used for output HTML and LaTeX files.

887"""

888

889styler_mathjax = """

890: bool

891 If False will render special CSS classes to table attributes that indicate Mathjax

892 will not be used in Jupyter Notebook.

893"""

894

895with cf.config_prefix("styler"):

896 cf.register_option("sparse.index", True, styler_sparse_index_doc, validator=is_bool)

897

898 cf.register_option(

899 "sparse.columns", True, styler_sparse_columns_doc, validator=is_bool

900 )

901

902 cf.register_option(

903 "render.repr",

904 "html",

905 styler_render_repr,

906 validator=is_one_of_factory(["html", "latex"]),

907 )

908

909 cf.register_option(

910 "render.max_elements",

911 2**18,

912 styler_max_elements,

913 validator=is_nonnegative_int,

914 )

915

916 cf.register_option(

917 "render.max_rows",

918 None,

919 styler_max_rows,

920 validator=is_nonnegative_int,

921 )

922

923 cf.register_option(

924 "render.max_columns",

925 None,

926 styler_max_columns,

927 validator=is_nonnegative_int,

928 )

929

930 cf.register_option("render.encoding", "utf-8", styler_encoding, validator=is_str)

931

932 cf.register_option("format.decimal", ".", styler_decimal, validator=is_str)

933

934 cf.register_option(

935 "format.precision", 6, styler_precision, validator=is_nonnegative_int

936 )

937

938 cf.register_option(

939 "format.thousands",

940 None,

941 styler_thousands,

942 validator=is_instance_factory([type(None), str]),

943 )

944

945 cf.register_option(

946 "format.na_rep",

947 None,

948 styler_na_rep,

949 validator=is_instance_factory([type(None), str]),

950 )

951

952 cf.register_option(

953 "format.escape",

954 None,

955 styler_escape,

956 validator=is_one_of_factory([None, "html", "latex"]),

957 )

958

959 cf.register_option(

960 "format.formatter",

961 None,

962 styler_formatter,

963 validator=is_instance_factory([type(None), dict, Callable, str]),

964 )

965

966 cf.register_option("html.mathjax", True, styler_mathjax, validator=is_bool)

967

968 cf.register_option(

969 "latex.multirow_align",

970 "c",

971 styler_multirow_align,

972 validator=is_one_of_factory(["c", "t", "b", "naive"]),

973 )

974

975 val_mca = ["r", "|r|", "|r", "r|", "c", "|c|", "|c", "c|", "l", "|l|", "|l", "l|"]

976 val_mca += ["naive-l", "naive-r"]

977 cf.register_option(

978 "latex.multicol_align",

979 "r",

980 styler_multicol_align,

981 validator=is_one_of_factory(val_mca),

982 )

983

984 cf.register_option("latex.hrules", False, styler_hrules, validator=is_bool)

985

986 cf.register_option(

987 "latex.environment",

988 None,

989 styler_environment,

990 validator=is_instance_factory([type(None), str]),

991 )

Coverage for /var/srv/projects/api.amasfac.comuna18.com/tmp/venv/lib/python3.9/site-packages/pandas/core/config_init.py: 86%

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