Metadata-Version: 2.1 Name: tabulate Version: 0.8.6 Summary: Pretty-print tabular data Home-page: https://github.com/astanin/python-tabulate Author: Sergey Astanin Author-email: s.astanin@gmail.com License: MIT Platform: UNKNOWN Classifier: Development Status :: 4 - Beta Classifier: License :: OSI Approved :: MIT License Classifier: Operating System :: OS Independent Classifier: Programming Language :: Python :: 2 Classifier: Programming Language :: Python :: 2.7 Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3.5 Classifier: Programming Language :: Python :: 3.6 Classifier: Programming Language :: Python :: 3.7 Classifier: Topic :: Software Development :: Libraries Description-Content-Type: text/markdown Provides-Extra: widechars Requires-Dist: wcwidth ; extra == 'widechars' python-tabulate =============== Pretty-print tabular data in Python, a library and a command-line utility. The main use cases of the library are: - printing small tables without hassle: just one function call, formatting is guided by the data itself - authoring tabular data for lightweight plain-text markup: multiple output formats suitable for further editing or transformation - readable presentation of mixed textual and numeric data: smart column alignment, configurable number formatting, alignment by a decimal point Installation ------------ To install the Python library and the command line utility, run: pip install tabulate The command line utility will be installed as `tabulate` to `bin` on Linux (e.g. `/usr/bin`); or as `tabulate.exe` to `Scripts` in your Python installation on Windows (e.g. `C:\Python27\Scripts\tabulate.exe`). You may consider installing the library only for the current user: pip install tabulate --user In this case the command line utility will be installed to `~/.local/bin/tabulate` on Linux and to `%APPDATA%\Python\Scripts\tabulate.exe` on Windows. To install just the library on Unix-like operating systems: TABULATE_INSTALL=lib-only pip install tabulate On Windows: set TABULATE_INSTALL=lib-only pip install tabulate The module provides just one function, `tabulate`, which takes a list of lists or another tabular data type as the first argument, and outputs a nicely formatted plain-text table: >>> from tabulate import tabulate >>> table = [["Sun",696000,1989100000],["Earth",6371,5973.6], ... ["Moon",1737,73.5],["Mars",3390,641.85]] >>> print(tabulate(table)) ----- ------ ------------- Sun 696000 1.9891e+09 Earth 6371 5973.6 Moon 1737 73.5 Mars 3390 641.85 ----- ------ ------------- The following tabular data types are supported: - list of lists or another iterable of iterables - list or another iterable of dicts (keys as columns) - dict of iterables (keys as columns) - two-dimensional NumPy array - NumPy record arrays (names as columns) - pandas.DataFrame Examples in this file use Python2. Tabulate supports Python3 too. ### Headers The second optional argument named `headers` defines a list of column headers to be used: >>> print(tabulate(table, headers=["Planet","R (km)", "mass (x 10^29 kg)"])) Planet R (km) mass (x 10^29 kg) -------- -------- ------------------- Sun 696000 1.9891e+09 Earth 6371 5973.6 Moon 1737 73.5 Mars 3390 641.85 If `headers="firstrow"`, then the first row of data is used: >>> print(tabulate([["Name","Age"],["Alice",24],["Bob",19]], ... headers="firstrow")) Name Age ------ ----- Alice 24 Bob 19 If `headers="keys"`, then the keys of a dictionary/dataframe, or column indices are used. It also works for NumPy record arrays and lists of dictionaries or named tuples: >>> print(tabulate({"Name": ["Alice", "Bob"], ... "Age": [24, 19]}, headers="keys")) Age Name ----- ------ 24 Alice 19 Bob ### Row Indices By default, only pandas.DataFrame tables have an additional column called row index. To add a similar column to any other type of table, pass `showindex="always"` or `showindex=True` argument to `tabulate()`. To suppress row indices for all types of data, pass `showindex="never"` or `showindex=False`. To add a custom row index column, pass `showindex=rowIDs`, where `rowIDs` is some iterable: >>> print(tabulate([["F",24],["M",19]], showindex="always")) - - -- 0 F 24 1 M 19 - - -- ### Table format There is more than one way to format a table in plain text. The third optional argument named `tablefmt` defines how the table is formatted. Supported table formats are: - "plain" - "simple" - "github" - "grid" - "fancy\_grid" - "pipe" - "orgtbl" - "jira" - "presto" - "psql" - "rst" - "mediawiki" - "moinmoin" - "youtrack" - "html" - "latex" - "latex\_raw" - "latex\_booktabs" - "textile" `plain` tables do not use any pseudo-graphics to draw lines: >>> table = [["spam",42],["eggs",451],["bacon",0]] >>> headers = ["item", "qty"] >>> print(tabulate(table, headers, tablefmt="plain")) item qty spam 42 eggs 451 bacon 0 `simple` is the default format (the default may change in future versions). It corresponds to `simple_tables` in [Pandoc Markdown extensions](http://johnmacfarlane.net/pandoc/README.html#tables): >>> print(tabulate(table, headers, tablefmt="simple")) item qty ------ ----- spam 42 eggs 451 bacon 0 `github` follows the conventions of Github flavored Markdown. It corresponds to the `pipe` format without alignment colons: >>> print(tabulate(table, headers, tablefmt="github")) | item | qty | |--------|-------| | spam | 42 | | eggs | 451 | | bacon | 0 | `grid` is like tables formatted by Emacs' [table.el](http://table.sourceforge.net/) package. It corresponds to `grid_tables` in Pandoc Markdown extensions: >>> print(tabulate(table, headers, tablefmt="grid")) +--------+-------+ | item | qty | +========+=======+ | spam | 42 | +--------+-------+ | eggs | 451 | +--------+-------+ | bacon | 0 | +--------+-------+ `fancy_grid` draws a grid using box-drawing characters: >>> print(tabulate(table, headers, tablefmt="fancy_grid")) ╒════════╤═══════╕ │ item │ qty │ ╞════════╪═══════╡ │ spam │ 42 │ ├────────┼───────┤ │ eggs │ 451 │ ├────────┼───────┤ │ bacon │ 0 │ ╘════════╧═══════╛ `presto` is like tables formatted by Presto cli: >>> print(tabulate(table, headers, tablefmt="presto")) item | qty --------+------- spam | 42 eggs | 451 bacon | 0 `psql` is like tables formatted by Postgres' psql cli: >>> print(tabulate(table, headers, tablefmt="psql")) +--------+-------+ | item | qty | |--------+-------| | spam | 42 | | eggs | 451 | | bacon | 0 | +--------+-------+ `pipe` follows the conventions of [PHP Markdown Extra](http://michelf.ca/projects/php-markdown/extra/#table) extension. It corresponds to `pipe_tables` in Pandoc. This format uses colons to indicate column alignment: >>> print(tabulate(table, headers, tablefmt="pipe")) | item | qty | |:-------|------:| | spam | 42 | | eggs | 451 | | bacon | 0 | `orgtbl` follows the conventions of Emacs [org-mode](http://orgmode.org/manual/Tables.html), and is editable also in the minor orgtbl-mode. Hence its name: >>> print(tabulate(table, headers, tablefmt="orgtbl")) | item | qty | |--------+-------| | spam | 42 | | eggs | 451 | | bacon | 0 | `jira` follows the conventions of Atlassian Jira markup language: >>> print(tabulate(table, headers, tablefmt="jira")) || item || qty || | spam | 42 | | eggs | 451 | | bacon | 0 | `rst` formats data like a simple table of the [reStructuredText](http://docutils.sourceforge.net/docs/user/rst/quickref.html#tables) format: >>> print(tabulate(table, headers, tablefmt="rst")) ====== ===== item qty ====== ===== spam 42 eggs 451 bacon 0 ====== ===== `mediawiki` format produces a table markup used in [Wikipedia](http://www.mediawiki.org/wiki/Help:Tables) and on other MediaWiki-based sites: >>> print(tabulate(table, headers, tablefmt="mediawiki")) {| class="wikitable" style="text-align: left;" |+ |- ! item !! align="right"| qty |- | spam || align="right"| 42 |- | eggs || align="right"| 451 |- | bacon || align="right"| 0 |} `moinmoin` format produces a table markup used in [MoinMoin](https://moinmo.in/) wikis: >>> print(tabulate(table, headers, tablefmt="moinmoin")) || ''' item ''' || ''' quantity ''' || || spam || 41.999 || || eggs || 451 || || bacon || || `youtrack` format produces a table markup used in Youtrack tickets: >>> print(tabulate(table, headers, tablefmt="youtrack")) || item || quantity || | spam | 41.999 | | eggs | 451 | | bacon | | `textile` format produces a table markup used in [Textile](http://redcloth.org/hobix.com/textile/) format: >>> print(tabulate(table, headers, tablefmt="textile")) |_. item |_. qty | |<. spam |>. 42 | |<. eggs |>. 451 | |<. bacon |>. 0 | `html` produces standard HTML markup: >>> print(tabulate(table, headers, tablefmt="html"))
item qty
spam 42
eggs 451
bacon 0
`latex` format creates a `tabular` environment for LaTeX markup, replacing special characters like `_` or `\` to their LaTeX correspondents: >>> print(tabulate(table, headers, tablefmt="latex")) \begin{tabular}{lr} \hline item & qty \\ \hline spam & 42 \\ eggs & 451 \\ bacon & 0 \\ \hline \end{tabular} `latex_raw` behaves like `latex` but does not escape LaTeX commands and special characters. `latex_booktabs` creates a `tabular` environment for LaTeX markup using spacing and style from the `booktabs` package. ### Column alignment `tabulate` is smart about column alignment. It detects columns which contain only numbers, and aligns them by a decimal point (or flushes them to the right if they appear to be integers). Text columns are flushed to the left. You can override the default alignment with `numalign` and `stralign` named arguments. Possible column alignments are: `right`, `center`, `left`, `decimal` (only for numbers), and `None` (to disable alignment). Aligning by a decimal point works best when you need to compare numbers at a glance: >>> print(tabulate([[1.2345],[123.45],[12.345],[12345],[1234.5]])) ---------- 1.2345 123.45 12.345 12345 1234.5 ---------- Compare this with a more common right alignment: >>> print(tabulate([[1.2345],[123.45],[12.345],[12345],[1234.5]], numalign="right")) ------ 1.2345 123.45 12.345 12345 1234.5 ------ For `tabulate`, anything which can be parsed as a number is a number. Even numbers represented as strings are aligned properly. This feature comes in handy when reading a mixed table of text and numbers from a file: >>> import csv ; from StringIO import StringIO >>> table = list(csv.reader(StringIO("spam, 42\neggs, 451\n"))) >>> table [['spam', ' 42'], ['eggs', ' 451']] >>> print(tabulate(table)) ---- ---- spam 42 eggs 451 ---- ---- ### Custom column alignment `tabulate` allows a custom column alignment to override the above. The `colalign` argument can be a list or a tuple of `stralign` named arguments. Possible column alignments are: `right`, `center`, `left`, `decimal` (only for numbers), and `None` (to disable alignment). Omitting an alignment uses the default. For example: >>> print(tabulate([["one", "two"], ["three", "four"]], colalign=("right",)) ----- ---- one two three four ----- ---- ### Number formatting `tabulate` allows to define custom number formatting applied to all columns of decimal numbers. Use `floatfmt` named argument: >>> print(tabulate([["pi",3.141593],["e",2.718282]], floatfmt=".4f")) -- ------ pi 3.1416 e 2.7183 -- ------ `floatfmt` argument can be a list or a tuple of format strings, one per column, in which case every column may have different number formatting: >>> print(tabulate([[0.12345, 0.12345, 0.12345]], floatfmt=(".1f", ".3f"))) --- ----- ------- 0.1 0.123 0.12345 --- ----- ------- ### Text formatting By default, `tabulate` removes leading and trailing whitespace from text columns. To disable whitespace removal, set the global module-level flag `PRESERVE_WHITESPACE`: import tabulate tabulate.PRESERVE_WHITESPACE = True ### Wide (fullwidth CJK) symbols To properly align tables which contain wide characters (typically fullwidth glyphs from Chinese, Japanese or Korean languages), the user should install `wcwidth` library. To install it together with `tabulate`: pip install tabulate[widechars] Wide character support is enabled automatically if `wcwidth` library is already installed. To disable wide characters support without uninstalling `wcwidth`, set the global module-level flag `WIDE_CHARS_MODE`: import tabulate tabulate.WIDE_CHARS_MODE = False ### Multiline cells Most table formats support multiline cell text (text containing newline characters). The newline characters are honored as line break characters. Multiline cells are supported for data rows and for header rows. Further automatic line breaks are not inserted. Of course, some output formats such as latex or html handle automatic formatting of the cell content on their own, but for those that don't, the newline characters in the input cell text are the only means to break a line in cell text. Note that some output formats (e.g. simple, or plain) do not represent row delimiters, so that the representation of multiline cells in such formats may be ambiguous to the reader. The following examples of formatted output use the following table with a multiline cell, and headers with a multiline cell: >>> table = [["eggs",451],["more\nspam",42]] >>> headers = ["item\nname", "qty"] `plain` tables: >>> print(tabulate(table, headers, tablefmt="plain")) item qty name eggs 451 more 42 spam `simple` tables: >>> print(tabulate(table, headers, tablefmt="simple")) item qty name ------ ----- eggs 451 more 42 spam `grid` tables: >>> print(tabulate(table, headers, tablefmt="grid")) +--------+-------+ | item | qty | | name | | +========+=======+ | eggs | 451 | +--------+-------+ | more | 42 | | spam | | +--------+-------+ `fancy_grid` tables: >>> print(tabulate(table, headers, tablefmt="fancy_grid")) ╒════════╤═══════╕ │ item │ qty │ │ name │ │ ╞════════╪═══════╡ │ eggs │ 451 │ ├────────┼───────┤ │ more │ 42 │ │ spam │ │ ╘════════╧═══════╛ `pipe` tables: >>> print(tabulate(table, headers, tablefmt="pipe")) | item | qty | | name | | |:-------|------:| | eggs | 451 | | more | 42 | | spam | | `orgtbl` tables: >>> print(tabulate(table, headers, tablefmt="orgtbl")) | item | qty | | name | | |--------+-------| | eggs | 451 | | more | 42 | | spam | | `jira` tables: >>> print(tabulate(table, headers, tablefmt="jira")) | item | qty | | name | | |:-------|------:| | eggs | 451 | | more | 42 | | spam | | `presto` tables: >>> print(tabulate(table, headers, tablefmt="presto")) item | qty name | --------+------- eggs | 451 more | 42 spam | `psql` tables: >>> print(tabulate(table, headers, tablefmt="psql")) +--------+-------+ | item | qty | | name | | |--------+-------| | eggs | 451 | | more | 42 | | spam | | +--------+-------+ `rst` tables: >>> print(tabulate(table, headers, tablefmt="rst")) ====== ===== item qty name ====== ===== eggs 451 more 42 spam ====== ===== Multiline cells are not well supported for the other table formats. Usage of the command line utility --------------------------------- Usage: tabulate [options] [FILE ...] 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, github, grid, fancy_grid, pipe, orgtbl, rst, mediawiki, html, latex, latex_raw, latex_booktabs, tsv (default: simple) Performance considerations -------------------------- Such features as decimal point alignment and trying to parse everything as a number imply that `tabulate`: - has to "guess" how to print a particular tabular data type - needs to keep the entire table in-memory - has to "transpose" the table twice - does much more work than it may appear It may not be suitable for serializing really big tables (but who's going to do that, anyway?) or printing tables in performance sensitive applications. `tabulate` is about two orders of magnitude slower than simply joining lists of values with a tab, coma or other separator. In the same time `tabulate` is comparable to other table pretty-printers. Given a 10x10 table (a list of lists) of mixed text and numeric data, `tabulate` appears to be slower than `asciitable`, and faster than `PrettyTable` and `texttable` The following mini-benchmark was run in Python 3.6.8 on Ubuntu 18.04 in WSL: ========================== ========== =========== Table formatter time, μs rel. time =========================== ========== =========== csv to StringIO 21.4 1.0 join with tabs and newlines 29.6 1.4 asciitable (0.8.0) 506.8 23.7 tabulate (0.8.6) 1079.9 50.5 PrettyTable (0.7.2) 2032.0 95.0 texttable (1.6.2) 3025.7 141.4 =========================== ========== =========== Version history --------------- The full version history can be found at the [changelog](./CHANGELOG). How to contribute ----------------- Contributions should include tests and an explanation for the changes they propose. Documentation (examples, docstrings, README.md) should be updated accordingly. This project uses [nose](https://nose.readthedocs.org/) testing framework and [tox](https://tox.readthedocs.io/) to automate testing in different environments. Add tests to one of the files in the `test/` folder. To run tests on all supported Python versions, make sure all Python interpreters, `nose` and `tox` are installed, then run `tox` in the root of the project source tree. On Linux `tox` expects to find executables like `python2.6`, `python2.7`, `python3.4` etc. On Windows it looks for `C:\Python26\python.exe`, `C:\Python27\python.exe` and `C:\Python34\python.exe` respectively. To test only some Python environements, use `-e` option. For example, to test only against Python 2.7 and Python 3.6, run: tox -e py27,py36 in the root of the project source tree. To enable NumPy and Pandas tests, run: tox -e py27-extra,py36-extra (this may take a long time the first time, because NumPy and Pandas will have to be installed in the new virtual environments) See `tox.ini` file to learn how to use `nosetests` directly to test individual Python versions. Contributors ------------ Sergey Astanin, Pau Tallada Crespí, Erwin Marsi, Mik Kocikowski, Bill Ryder, Zach Dwiel, Frederik Rietdijk, Philipp Bogensberger, Greg (anonymous), Stefan Tatschner, Emiel van Miltenburg, Brandon Bennett, Amjith Ramanujam, Jan Schulz, Simon Percivall, Javier Santacruz López-Cepero, Sam Denton, Alexey Ziyangirov, acaird, Cesar Sanchez, naught101, John Vandenberg, Zack Dever, Christian Clauss, Benjamin Maier, Andy MacKinlay, Thomas Roten, Jue Wang, Joe King, Samuel Phan, Nick Satterly, Daniel Robbins, Dmitry B, Lars Butler, Andreas Maier, Dick Marinus, Sébastien Celles, Yago González, Andrew Gaul, Wim Glenn, Jean Michel Rouly, Tim Gates, John Vandenberg, Sorin Sbarnea.