x/synergy-service
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synergy-service/synergy/client/tabulate.py
Vincent Llorens b75d85315c Distribute tabulate as part of Synergy 
Synergy depends on the python tabulate package. However, it is not
available as a system package for both CentOS 7 and Ubuntu 14.04.

In this commit we opt for the following solution: don't mark
tabulate as a dependency when building synergy system packages,
instead we provide the tabulate package as part of Synergy.

DocImpact
Change-Id: I76018e1ba27de8ad47b59c85baad2c2d06f03398
Sem-Ver: bugfix
2016-10-27 12:17:46 +02:00

1088 lines
38 KiB
Python
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# -*- 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
_long_type = long
_float_type = float
_text_type = unicode
_binary_type = str
def _is_file(f):
return isinstance(f, file)
else:
from itertools import zip_longest as izip_longest
from functools import reduce, partial
_none_type = type(None)
_int_type = int
_long_type = int
_float_type = float
_text_type = str
_binary_type = bytes
import io
def _is_file(f):
return isinstance(f, io.IOBase)
__all__ = ["tabulate", "tabulate_formats", "simple_separated_format"]
__version__ = "0.7.5"
MIN_PADDING = 2
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 _html_row_with_attrs(celltag, cell_values, colwidths, colaligns):
alignment = { "left": '',
"right": ' style="text-align: right;"',
"center": ' style="text-align: center;"',
"decimal": ' style="text-align: right;"' }
values_with_attrs = ["<{0}{1}>{2}</{0}>".format(celltag, alignment.get(a, ''), c)
for c, a in zip(cell_values, colaligns)]
return "<tr>" + "".join(values_with_attrs).rstrip() + "</tr>"
def _latex_line_begin_tabular(colwidths, colaligns, booktabs=False):
alignment = { "left": "l", "right": "r", "center": "c", "decimal": "r" }
tabular_columns_fmt = "".join([alignment.get(a, "l") for a in colaligns])
return "\n".join(["\\begin{tabular}{" + tabular_columns_fmt + "}",
"\\toprule" if booktabs else "\hline"])
LATEX_ESCAPE_RULES = {r"&": r"\&", r"%": r"\%", r"$": r"\$", r"#": r"\#",
r"_": r"\_", r"^": r"\^{}", r"{": r"\{", r"}": r"\}",
r"~": r"\textasciitilde{}", "\\": r"\textbackslash{}",
r"<": r"\ensuremath{<}", r">": r"\ensuremath{>}"}
def _latex_row(cell_values, colwidths, colaligns):
def escape_char(c):
return LATEX_ESCAPE_RULES.get(c, c)
escaped_values = ["".join(map(escape_char, cell)) for cell in cell_values]
rowfmt = DataRow("", "&", "\\\\")
return _build_simple_row(escaped_values, rowfmt)
_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),
"fancy_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),
"psql":
TableFormat(lineabove=Line("+", "-", "+", "+"),
linebelowheader=Line("|", "-", "+", "|"),
linebetweenrows=None,
linebelow=Line("+", "-", "+", "+"),
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),
"html":
TableFormat(lineabove=Line("<table>", "", "", ""),
linebelowheader=None,
linebetweenrows=None,
linebelow=Line("</table>", "", "", ""),
headerrow=partial(_html_row_with_attrs, "th"),
datarow=partial(_html_row_with_attrs, "td"),
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=_latex_row,
datarow=_latex_row,
padding=1, with_header_hide=None),
"latex_booktabs":
TableFormat(lineabove=partial(_latex_line_begin_tabular, booktabs=True),
linebelowheader=Line("\\midrule", "", "", ""),
linebetweenrows=None,
linebelow=Line("\\bottomrule\n\\end{tabular}", "", "", ""),
headerrow=_latex_row,
datarow=_latex_row,
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(r"\x1b\[\d*m|\x1b\[\d*\;\d*\;\d*m") # ANSI color codes
_invisible_codes_bytes = re.compile(b"\x1b\[\d*m|\x1b\[\d*\;\d*\;\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, TypeError):
return False
def _isnumber(string):
"""
>>> _isnumber("123.45")
True
>>> _isnumber("123")
True
>>> _isnumber("spam")
False
"""
return _isconvertible(float, string)
def _isint(string, inttype=int):
"""
>>> _isint("123")
True
>>> _isint("123.45")
False
"""
return type(string) is inttype or\
(isinstance(string, _binary_type) or isinstance(string, _text_type))\
and\
_isconvertible(inttype, 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 _isint(string, _long_type):
return _long_type
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":
if has_invisible:
decimals = [_afterpoint(_strip_invisible(s)) for s in strings]
else:
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="", has_invisible=True):
"""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, _long_type, _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:
is_a_colored_number = has_invisible and isinstance(val, (_text_type, _binary_type))
if is_a_colored_number:
raw_val = _strip_invisible(val)
formatted_val = format(float(raw_val), floatfmt)
return val.replace(raw_val, formatted_val)
else:
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 isinstance(headers, dict):
# a dict of headers for a list of dicts
headers = [headers.get(k, k) for k in keys]
headers = list(map(_text_type, headers))
elif headers == "firstrow":
if len(rows) > 0:
headers = [firstdict.get(k, k) for k in keys]
headers = list(map(_text_type, headers))
else:
headers = []
elif headers:
raise ValueError('headers for a list of dicts is not a dict or a keyword')
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',
'latex', and 'latex_booktabs'. 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 |
+------+----------+
"fancy_grid" draws a grid using box-drawing characters:
>>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]],
... ["strings", "numbers"], "fancy_grid"))
╒═══════════╤═══════════╕
│ strings │ numbers │
╞═══════════╪═══════════╡
│ 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
|}
"html" produces HTML markup:
>>> print(tabulate([["strings", "numbers"], ["spam", 41.9999], ["eggs", "451.0"]],
... headers="firstrow", tablefmt="html"))
<table>
<tr><th>strings </th><th style="text-align: right;"> numbers</th></tr>
<tr><td>spam </td><td style="text-align: right;"> 41.9999</td></tr>
<tr><td>eggs </td><td style="text-align: right;"> 451 </td></tr>
</table>
"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}
"latex_booktabs" produces a tabular environment of LaTeX document markup
using the booktabs.sty package:
>>> print(tabulate([["spam", 41.9999], ["eggs", "451.0"]], tablefmt="latex_booktabs"))
\\begin{tabular}{lr}
\\toprule
spam & 41.9999 \\\\
eggs & 451 \\\\
\\bottomrule
\end{tabular}
"""
if tabular_data is None:
tabular_data = []
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, has_invisible) 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) + MIN_PADDING 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
t_cols = cols or [['']] * len(headers)
t_aligns = aligns or [stralign] * len(headers)
minwidths = [max(minw, width_fn(c[0])) for minw, c in zip(minwidths, t_cols)]
headers = [_align_header(h, a, minw)
for h, a, minw in zip(headers, t_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)
def _main():
"""\
Usage: tabulate [options] [FILE ...]
Pretty-print tabular data.
See also https://bitbucket.org/astanin/python-tabulate
FILE a filename of the file with tabular data;
if "-" or missing, read data from stdin.
Options:
-h, --help show this message
-1, --header use the first row of data as a table header
-o FILE, --output FILE print table to FILE (default: stdout)
-s REGEXP, --sep REGEXP use a custom column separator (default: whitespace)
-F FPFMT, --float FPFMT floating point number format (default: g)
-f FMT, --format FMT set output table format; supported formats:
plain, simple, grid, fancy_grid, pipe, orgtbl,
rst, mediawiki, html, latex, latex_booktabs, tsv
(default: simple)
"""
import getopt
import sys
import textwrap
usage = textwrap.dedent(_main.__doc__)
try:
opts, args = getopt.getopt(sys.argv[1:],
"h1o:s:F:f:",
["help", "header", "output", "sep=", "float=", "format="])
except getopt.GetoptError as e:
print(e)
print(usage)
sys.exit(2)
headers = []
floatfmt = "g"
tablefmt = "simple"
sep = r"\s+"
outfile = "-"
for opt, value in opts:
if opt in ["-1", "--header"]:
headers = "firstrow"
elif opt in ["-o", "--output"]:
outfile = value
elif opt in ["-F", "--float"]:
floatfmt = value
elif opt in ["-f", "--format"]:
if value not in tabulate_formats:
print("%s is not a supported table format" % value)
print(usage)
sys.exit(3)
tablefmt = value
elif opt in ["-s", "--sep"]:
sep = value
elif opt in ["-h", "--help"]:
print(usage)
sys.exit(0)
files = [sys.stdin] if not args else args
with (sys.stdout if outfile == "-" else open(outfile, "w")) as out:
for f in files:
if f == "-":
f = sys.stdin
if _is_file(f):
_pprint_file(f, headers=headers, tablefmt=tablefmt,
sep=sep, floatfmt=floatfmt, file=out)
else:
with open(f) as fobj:
_pprint_file(fobj, headers=headers, tablefmt=tablefmt,
sep=sep, floatfmt=floatfmt, file=out)
def _pprint_file(fobject, headers, tablefmt, sep, floatfmt, file):
rows = fobject.readlines()
table = [re.split(sep, r.rstrip()) for r in rows]
print(tabulate(table, headers, tablefmt, floatfmt=floatfmt), file=file)
if __name__ == "__main__":
_main()
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