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GeezerVison is showing github.com — python-tabulate/tabulate.py at master · gregbanks/python-tabulate Expand file tree/ Copy pathtabulate.pyMore file actions 881 lines (708 loc) · 29.6 KB / Copy pathtabulate.pyFile metadata and controls881 lines (708 loc) · 29.6 KB 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 # -*- coding: utf-8 -*- """Pretty-print tabular data.""" from __future__ import print_function from __future__ import unicode_literals from collections import namedtuple from platform import python_version_tuple import re if python_version_tuple()[0] < "3": from itertools import izip_longest from functools import partial _none_type = type(None) _int_type = int _float_type = float _text_type = unicode _binary_type = str else: from itertools import zip_longest as izip_longest from functools import reduce, partial _none_type = type(None) _int_type = int _float_type = float _text_type = str _binary_type = bytes __all__ = ["tabulate", "tabulate_formats", "simple_separated_format"] __version__ = "0.7.3" Line = namedtuple("Line", ["begin", "hline", "sep", "end"]) DataRow = namedtuple("DataRow", ["begin", "sep", "end"]) # A table structure is suppposed to be: # # --- lineabove --------- # headerrow # --- linebelowheader --- # datarow # --- linebewteenrows --- # ... (more datarows) ... # --- linebewteenrows --- # last datarow # --- linebelow --------- # # TableFormat's line* elements can be # # - either None, if the element is not used, # - or a Line tuple, # - or a function: [col_widths], [col_alignments] -> string. # # TableFormat's *row elements can be # # - either None, if the element is not used, # - or a DataRow tuple, # - or a function: [cell_values], [col_widths], [col_alignments] -> string. # # padding (an integer) is the amount of white space around data values. # # with_header_hide: # # - either None, to display all table elements unconditionally, # - or a list of elements not to be displayed if the table has column headers. # TableFormat = namedtuple("TableFormat", ["lineabove", "linebelowheader", "linebetweenrows", "linebelow", "headerrow", "datarow", "padding", "with_header_hide"]) def _pipe_segment_with_colons(align, colwidth): """Return a segment of a horizontal line with optional colons which indicate column's alignment (as in `pipe` output format).""" w = colwidth if align in ["right", "decimal"]: return ('-' * (w - 1)) + ":" elif align == "center": return ":" + ('-' * (w - 2)) + ":" elif align == "left": return ":" + ('-' * (w - 1)) else: return '-' * w def _pipe_line_with_colons(colwidths, colaligns): """Return a horizontal line with optional colons to indicate column's alignment (as in `pipe` output format).""" segments = [_pipe_segment_with_colons(a, w) for a, w in zip(colaligns, colwidths)] return "|" + "|".join(segments) + "|" def _mediawiki_row_with_attrs(separator, cell_values, colwidths, colaligns): alignment = { "left": '', "right": 'align="right"| ', "center": 'align="center"| ', "decimal": 'align="right"| ' } # hard-coded padding _around_ align attribute and value together # rather than padding parameter which affects only the value values_with_attrs = [' ' + alignment.get(a, '') + c + ' ' for c, a in zip(cell_values, colaligns)] colsep = separator*2 return (separator + colsep.join(values_with_attrs)).rstrip() def _latex_line_begin_tabular(colwidths, colaligns): alignment = { "left": "l", "right": "r", "center": "c", "decimal": "r" } tabular_columns_fmt = "".join([alignment.get(a, "l") for a in colaligns]) return "\\begin{tabular}{" + tabular_columns_fmt + "}\n\hline" _table_formats = {"simple": TableFormat(lineabove=Line("", "-", " ", ""), linebelowheader=Line("", "-", " ", ""), linebetweenrows=None, linebelow=Line("", "-", " ", ""), headerrow=DataRow("", " ", ""), datarow=DataRow("", " ", ""), padding=0, with_header_hide=["lineabove", "linebelow"]), "plain": TableFormat(lineabove=None, linebelowheader=None, linebetweenrows=None, linebelow=None, headerrow=DataRow("", " ", ""), datarow=DataRow("", " ", ""), padding=0, with_header_hide=None), "grid": TableFormat(lineabove=Line("+", "-", "+", "+"), linebelowheader=Line("+", "=", "+", "+"), linebetweenrows=Line("+", "-", "+", "+"), linebelow=Line("+", "-", "+", "+"), headerrow=DataRow("|", "|", "|"), datarow=DataRow("|", "|", "|"), padding=1, with_header_hide=None), "pipe": TableFormat(lineabove=_pipe_line_with_colons, linebelowheader=_pipe_line_with_colons, linebetweenrows=None, linebelow=None, headerrow=DataRow("|", "|", "|"), datarow=DataRow("|", "|", "|"), padding=1, with_header_hide=["lineabove"]), "orgtbl": TableFormat(lineabove=None, linebelowheader=Line("|", "-", "+", "|"), linebetweenrows=None, linebelow=None, headerrow=DataRow("|", "|", "|"), datarow=DataRow("|", "|", "|"), padding=1, with_header_hide=None), "rst": TableFormat(lineabove=Line("", "=", " ", ""), linebelowheader=Line("", "=", " ", ""), linebetweenrows=None, linebelow=Line("", "=", " ", ""), headerrow=DataRow("", " ", ""), datarow=DataRow("", " ", ""), padding=0, with_header_hide=None), "mediawiki": TableFormat(lineabove=Line("{| class=\"wikitable\" style=\"text-align: left;\"", "", "", "\n|+ <!-- caption -->\n|-"), linebelowheader=Line("|-", "", "", ""), linebetweenrows=Line("|-", "", "", ""), linebelow=Line("|}", "", "", ""), headerrow=partial(_mediawiki_row_with_attrs, "!"), datarow=partial(_mediawiki_row_with_attrs, "|"), padding=0, with_header_hide=None), "latex": TableFormat(lineabove=_latex_line_begin_tabular, linebelowheader=Line("\\hline", "", "", ""), linebetweenrows=None, linebelow=Line("\\hline\n\\end{tabular}", "", "", ""), headerrow=DataRow("", "&", "\\\\"), datarow=DataRow("", "&", "\\\\"), padding=1, with_header_hide=None), "tsv": TableFormat(lineabove=None, linebelowheader=None, linebetweenrows=None, linebelow=None, headerrow=DataRow("", "\t", ""), datarow=DataRow("", "\t", ""), padding=0, with_header_hide=None)} tabulate_formats = list(sorted(_table_formats.keys())) _invisible_codes = re.compile("\x1b\[\d*m") # ANSI color codes _invisible_codes_bytes = re.compile(b"\x1b\[\d*m") # ANSI color codes def simple_separated_format(separator): """Construct a simple TableFormat with columns separated by a separator. >>> tsv = simple_separated_format("\\t") ; \ tabulate([["foo", 1], ["spam", 23]], tablefmt=tsv) == 'foo \\t 1\\nspam\\t23' True """ return TableFormat(None, None, None, None, headerrow=DataRow('', separator, ''), datarow=DataRow('', separator, ''), padding=0, with_header_hide=None) def _isconvertible(conv, string): try: n = conv(string) return True except ValueError: return False def _isnumber(string): """ >>> _isnumber("123.45") True >>> _isnumber("123") True >>> _isnumber("spam") False """ return _isconvertible(float, string) def _isint(string): """ >>> _isint("123") True >>> _isint("123.45") False """ return type(string) is int or \ (isinstance(string, _binary_type) or isinstance(string, _text_type)) and \ _isconvertible(int, string) def _type(string, has_invisible=True): """The least generic type (type(None), int, float, str, unicode). >>> _type(None) is type(None) True >>> _type("foo") is type("") True >>> _type("1") is type(1) True >>> _type('\x1b[31m42\x1b[0m') is type(42) True >>> _type('\x1b[31m42\x1b[0m') is type(42) True """ if has_invisible and \ (isinstance(string, _text_type) or isinstance(string, _binary_type)): string = _strip_invisible(string) if string is None: return _none_type elif hasattr(string, "isoformat"): # datetime.datetime, date, and time return _text_type elif _isint(string): return int elif _isnumber(string): return float elif isinstance(string, _binary_type): return _binary_type else: return _text_type def _afterpoint(string): """Symbols after a decimal point, -1 if the string lacks the decimal point. >>> _afterpoint("123.45") 2 >>> _afterpoint("1001") -1 >>> _afterpoint("eggs") -1 >>> _afterpoint("123e45") 2 """ if _isnumber(string): if _isint(string): return -1 else: pos = string.rfind(".") pos = string.lower().rfind("e") if pos < 0 else pos if pos >= 0: return len(string) - pos - 1 else: return -1 # no point else: return -1 # not a number def _padleft(width, s, has_invisible=True): """Flush right. >>> _padleft(6, '\u044f\u0439\u0446\u0430') == ' \u044f\u0439\u0446\u0430' True """ iwidth = width + len(s) - len(_strip_invisible(s)) if has_invisible else width fmt = "{0:>%ds}" % iwidth return fmt.format(s) def _padright(width, s, has_invisible=True): """Flush left. >>> _padright(6, '\u044f\u0439\u0446\u0430') == '\u044f\u0439\u0446\u0430 ' True """ iwidth = width + len(s) - len(_strip_invisible(s)) if has_invisible else width fmt = "{0:<%ds}" % iwidth return fmt.format(s) def _padboth(width, s, has_invisible=True): """Center string. >>> _padboth(6, '\u044f\u0439\u0446\u0430') == ' \u044f\u0439\u0446\u0430 ' True """ iwidth = width + len(s) - len(_strip_invisible(s)) if has_invisible else width fmt = "{0:^%ds}" % iwidth return fmt.format(s) def _strip_invisible(s): "Remove invisible ANSI color codes." if isinstance(s, _text_type): return re.sub(_invisible_codes, "", s) else: # a bytestring return re.sub(_invisible_codes_bytes, "", s) def _visible_width(s): """Visible width of a printed string. ANSI color codes are removed. >>> _visible_width('\x1b[31mhello\x1b[0m'), _visible_width("world") (5, 5) """ if isinstance(s, _text_type) or isinstance(s, _binary_type): return len(_strip_invisible(s)) else: return len(_text_type(s)) def _align_column(strings, alignment, minwidth=0, has_invisible=True): """[string] -> [padded_string] >>> list(map(str,_align_column(["12.345", "-1234.5", "1.23", "1234.5", "1e+234", "1.0e234"], "decimal"))) [' 12.345 ', '-1234.5 ', ' 1.23 ', ' 1234.5 ', ' 1e+234 ', ' 1.0e234'] >>> list(map(str,_align_column(['123.4', '56.7890'], None))) ['123.4', '56.7890'] """ if alignment == "right": strings = [s.strip() for s in strings] padfn = _padleft elif alignment == "center": strings = [s.strip() for s in strings] padfn = _padboth elif alignment == "decimal": decimals = [_afterpoint(s) for s in strings] maxdecimals = max(decimals) strings = [s + (maxdecimals - decs) * " " for s, decs in zip(strings, decimals)] padfn = _padleft elif not alignment: return strings else: strings = [s.strip() for s in strings] padfn = _padright if has_invisible: width_fn = _visible_width else: width_fn = len maxwidth = max(max(map(width_fn, strings)), minwidth) padded_strings = [padfn(maxwidth, s, has_invisible) for s in strings] return padded_strings def _more_generic(type1, type2): types = { _none_type: 0, int: 1, float: 2, _binary_type: 3, _text_type: 4 } invtypes = { 4: _text_type, 3: _binary_type, 2: float, 1: int, 0: _none_type } moregeneric = max(types.get(type1, 4), types.get(type2, 4)) return invtypes[moregeneric] def _column_type(strings, has_invisible=True): """The least generic type all column values are convertible to. >>> _column_type(["1", "2"]) is _int_type True >>> _column_type(["1", "2.3"]) is _float_type True >>> _column_type(["1", "2.3", "four"]) is _text_type True >>> _column_type(["four", '\u043f\u044f\u0442\u044c']) is _text_type True >>> _column_type([None, "brux"]) is _text_type True >>> _column_type([1, 2, None]) is _int_type True >>> import datetime as dt >>> _column_type([dt.datetime(1991,2,19), dt.time(17,35)]) is _text_type True """ types = [_type(s, has_invisible) for s in strings ] return reduce(_more_generic, types, int) def _format(val, valtype, floatfmt, missingval=""): """Format a value accoding to its type. Unicode is supported: >>> hrow = ['\u0431\u0443\u043a\u0432\u0430', '\u0446\u0438\u0444\u0440\u0430'] ; \ tbl = [['\u0430\u0437', 2], ['\u0431\u0443\u043a\u0438', 4]] ; \ good_result = '\\u0431\\u0443\\u043a\\u0432\\u0430 \\u0446\\u0438\\u0444\\u0440\\u0430\\n------- -------\\n\\u0430\\u0437 2\\n\\u0431\\u0443\\u043a\\u0438 4' ; \ tabulate(tbl, headers=hrow) == good_result True """ if val is None: return missingval if valtype in [int, _text_type]: return "{0}".format(val) elif valtype is _binary_type: try: return _text_type(val, "ascii") except TypeError: return _text_type(val) elif valtype is float: return format(float(val), floatfmt) else: return "{0}".format(val) def _align_header(header, alignment, width): if alignment == "left": return _padright(width, header) elif alignment == "center": return _padboth(width, header) elif not alignment: return "{0}".format(header) else: return _padleft(width, header) def _normalize_tabular_data(tabular_data, headers): """Transform a supported data type to a list of lists, and a list of headers. Supported tabular data types: * list-of-lists or another iterable of iterables * list of named tuples (usually used with headers="keys") * list of dicts (usually used with headers="keys") * list of OrderedDicts (usually used with headers="keys") * 2D NumPy arrays * NumPy record arrays (usually used with headers="keys") * dict of iterables (usually used with headers="keys") * pandas.DataFrame (usually used with headers="keys") The first row can be used as headers if headers="firstrow", column indices can be used as headers if headers="keys". """ if hasattr(tabular_data, "keys") and hasattr(tabular_data, "values"): # dict-like and pandas.DataFrame? if hasattr(tabular_data.values, "__call__"): # likely a conventional dict keys = tabular_data.keys() rows = list(izip_longest(*tabular_data.values())) # columns have to be transposed elif hasattr(tabular_data, "index"): # values is a property, has .index => it's likely a pandas.DataFrame (pandas 0.11.0) keys = tabular_data.keys() vals = tabular_data.values # values matrix doesn't need to be transposed names = tabular_data.index rows = [[v]+list(row) for v,row in zip(names, vals)] else: raise ValueError("tabular data doesn't appear to be a dict or a DataFrame") if headers == "keys": headers = list(map(_text_type,keys)) # headers should be strings else: # it's a usual an iterable of iterables, or a NumPy array rows = list(tabular_data) if (headers == "keys" and hasattr(tabular_data, "dtype") and getattr(tabular_data.dtype, "names")): # numpy record array headers = tabular_data.dtype.names elif (headers == "keys" and len(rows) > 0 and isinstance(rows[0], tuple) and hasattr(rows[0], "_fields")): # namedtuple headers = list(map(_text_type, rows[0]._fields)) elif (len(rows) > 0 and isinstance(rows[0], dict)): # dict or OrderedDict uniq_keys = set() # implements hashed lookup keys = [] # storage for set if headers == "firstrow": firstdict = rows[0] if len(rows) > 0 else {} keys.extend(firstdict.keys()) uniq_keys.update(keys) rows = rows[1:] for row in rows: for k in row.keys(): #Save unique items in input order if k not in uniq_keys: keys.append(k) uniq_keys.add(k) if headers == 'keys': headers = keys elif headers == "firstrow" and len(rows) > 0: headers = [firstdict.get(k, k) for k in keys] headers = list(map(_text_type, headers)) rows = [[row.get(k) for k in keys] for row in rows] elif headers == "keys" and len(rows) > 0: # keys are column indices headers = list(map(_text_type, range(len(rows[0])))) # take headers from the first row if necessary if headers == "firstrow" and len(rows) > 0: headers = list(map(_text_type, rows[0])) # headers should be strings rows = rows[1:] headers = list(map(_text_type,headers)) rows = list(map(list,rows)) # pad with empty headers for initial columns if necessary if headers and len(rows) > 0: nhs = len(headers) ncols = len(rows[0]) if nhs < ncols: headers = [""]*(ncols - nhs) + headers return rows, headers def tabulate(tabular_data, headers=[], tablefmt="simple", floatfmt="g", numalign="decimal", stralign="left", missingval=""): """Format a fixed width table for pretty printing. >>> print(tabulate([[1, 2.34], [-56, "8.999"], ["2", "10001"]])) --- --------- 1 2.34 -56 8.999 2 10001 --- --------- The first required argument (`tabular_data`) can be a list-of-lists (or another iterable of iterables), a list of named tuples, a dictionary of iterables, an iterable of dictionaries, a two-dimensional NumPy array, NumPy record array, or a Pandas' dataframe. Table headers ------------- To print nice column headers, supply the second argument (`headers`): - `headers` can be an explicit list of column headers - if `headers="firstrow"`, then the first row of data is used - if `headers="keys"`, then dictionary keys or column indices are used Otherwise a headerless table is produced. If the number of headers is less than the number of columns, they are supposed to be names of the last columns. This is consistent with the plain-text format of R and Pandas' dataframes. >>> print(tabulate([["sex","age"],["Alice","F",24],["Bob","M",19]], ... headers="firstrow")) sex age ----- ----- ----- Alice F 24 Bob M 19 Column alignment ---------------- `tabulate` tries to detect column types automatically, and aligns the values properly. By default it aligns decimal points of the numbers (or flushes integer numbers to the right), and flushes everything else to the left. Possible column alignments (`numalign`, `stralign`) are: "right", "center", "left", "decimal" (only for `numalign`), and None (to disable alignment). Table formats ------------- `floatfmt` is a format specification used for columns which contain numeric data with a decimal point. `None` values are replaced with a `missingval` string: >>> print(tabulate([["spam", 1, None], ... ["eggs", 42, 3.14], ... ["other", None, 2.7]], missingval="?")) ----- -- ---- spam 1 ? eggs 42 3.14 other ? 2.7 ----- -- ---- Various plain-text table formats (`tablefmt`) are supported: 'plain', 'simple', 'grid', 'pipe', 'orgtbl', 'rst', 'mediawiki', and 'latex'. Variable `tabulate_formats` contains the list of currently supported formats. "plain" format doesn't use any pseudographics to draw tables, it separates columns with a double space: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "plain")) strings numbers spam 41.9999 eggs 451 >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="plain")) spam 41.9999 eggs 451 "simple" format is like Pandoc simple_tables: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "simple")) strings numbers --------- --------- spam 41.9999 eggs 451 >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="simple")) ---- -------- spam 41.9999 eggs 451 ---- -------- "grid" is similar to tables produced by Emacs table.el package or Pandoc grid_tables: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "grid")) +-----------+-----------+ | strings | numbers | +===========+===========+ | spam | 41.9999 | +-----------+-----------+ | eggs | 451 | +-----------+-----------+ >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="grid")) +------+----------+ | spam | 41.9999 | +------+----------+ | eggs | 451 | +------+----------+ "pipe" is like tables in PHP Markdown Extra extension or Pandoc pipe_tables: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "pipe")) | strings | numbers | |:----------|----------:| | spam | 41.9999 | | eggs | 451 | >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="pipe")) |:-----|---------:| | spam | 41.9999 | | eggs | 451 | "orgtbl" is like tables in Emacs org-mode and orgtbl-mode. They are slightly different from "pipe" format by not using colons to define column alignment, and using a "+" sign to indicate line intersections: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "orgtbl")) | strings | numbers | |-----------+-----------| | spam | 41.9999 | | eggs | 451 | >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="orgtbl")) | spam | 41.9999 | | eggs | 451 | "rst" is like a simple table format from reStructuredText; please note that reStructuredText accepts also "grid" tables: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], ... ["strings", "numbers"], "rst")) ========= ========= strings numbers ========= ========= spam 41.9999 eggs 451 ========= ========= >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="rst")) ==== ======== spam 41.9999 eggs 451 ==== ======== "mediawiki" produces a table markup used in Wikipedia and on other MediaWiki-based sites: >>> print(tabulate([["strings", "numbers"], ["spam", 41.9999], ["eggs", "451.0"]], ... headers="firstrow", tablefmt="mediawiki")) {| class="wikitable" style="text-align: left;" |+ <!-- caption --> |- ! strings !! align="right"| numbers |- | spam || align="right"| 41.9999 |- | eggs || align="right"| 451 |} "latex" produces a tabular environment of LaTeX document markup: >>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="latex")) \\begin{tabular}{lr} \\hline spam & 41.9999 \\\\ eggs & 451 \\\\ \\hline \\end{tabular} """ list_of_lists, headers = _normalize_tabular_data(tabular_data, headers) # optimization: look for ANSI control codes once, # enable smart width functions only if a control code is found plain_text = '\n'.join(['\t'.join(map(_text_type, headers))] + \ ['\t'.join(map(_text_type, row)) for row in list_of_lists]) has_invisible = re.search(_invisible_codes, plain_text) if has_invisible: width_fn = _visible_width else: width_fn = len # format rows and columns, convert numeric values to strings cols = list(zip(*list_of_lists)) coltypes = list(map(_column_type, cols)) cols = [[_format(v, ct, floatfmt, missingval) for v in c] for c,ct in zip(cols, coltypes)] # align columns aligns = [numalign if ct in [int,float] else stralign for ct in coltypes] minwidths = [width_fn(h)+2 for h in headers] if headers else [0]*len(cols) cols = [_align_column(c, a, minw, has_invisible) for c, a, minw in zip(cols, aligns, minwidths)] if headers: # align headers and add headers minwidths = [max(minw, width_fn(c[0])) for minw, c in zip(minwidths, cols)] headers = [_align_header(h, a, minw) for h, a, minw in zip(headers, aligns, minwidths)] rows = list(zip(*cols)) else: minwidths = [width_fn(c[0]) for c in cols] rows = list(zip(*cols)) if not isinstance(tablefmt, TableFormat): tablefmt = _table_formats.get(tablefmt, _table_formats["simple"]) return _format_table(tablefmt, headers, rows, minwidths, aligns) def _build_simple_row(padded_cells, rowfmt): "Format row according to DataRow format without padding." begin, sep, end = rowfmt return (begin + sep.join(padded_cells) + end).rstrip() def _build_row(padded_cells, colwidths, colaligns, rowfmt): "Return a string which represents a row of data cells." if not rowfmt: return None if hasattr(rowfmt, "__call__"): return rowfmt(padded_cells, colwidths, colaligns) else: return _build_simple_row(padded_cells, rowfmt) def _build_line(colwidths, colaligns, linefmt): "Return a string which represents a horizontal line." if not linefmt: return None if hasattr(linefmt, "__call__"): return linefmt(colwidths, colaligns) else: begin, fill, sep, end = linefmt cells = [fill*w for w in colwidths] return _build_simple_row(cells, (begin, sep, end)) def _pad_row(cells, padding): if cells: pad = " "*padding padded_cells = [pad + cell + pad for cell in cells] return padded_cells else: return cells def _format_table(fmt, headers, rows, colwidths, colaligns): """Produce a plain-text representation of the table.""" lines = [] hidden = fmt.with_header_hide if (headers and fmt.with_header_hide) else [] pad = fmt.padding headerrow = fmt.headerrow padded_widths = [(w + 2*pad) for w in colwidths] padded_headers = _pad_row(headers, pad) padded_rows = [_pad_row(row, pad) for row in rows] if fmt.lineabove and "lineabove" not in hidden: lines.append(_build_line(padded_widths, colaligns, fmt.lineabove)) if padded_headers: lines.append(_build_row(padded_headers, padded_widths, colaligns, headerrow)) if fmt.linebelowheader and "linebelowheader" not in hidden: lines.append(_build_line(padded_widths, colaligns, fmt.linebelowheader)) if padded_rows and fmt.linebetweenrows and "linebetweenrows" not in hidden: # initial rows with a line below for row in padded_rows[:-1]: lines.append(_build_row(row, padded_widths, colaligns, fmt.datarow)) lines.append(_build_line(padded_widths, colaligns, fmt.linebetweenrows)) # the last row without a line below lines.append(_build_row(padded_rows[-1], padded_widths, colaligns, fmt.datarow)) else: for row in padded_rows: lines.append(_build_row(row, padded_widths, colaligns, fmt.datarow)) if fmt.linebelow and "linebelow" not in hidden: lines.append(_build_line(padded_widths, colaligns, fmt.linebelow)) return "\n".join(lines) |
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