.. _formats: ======= Formats ======= Tablib supports a wide variety of different tabular formats, both for input and output. Moreover, you can :ref:`register your own formats `. cli === The ``cli`` format is currently export-only. The exports produce a representation table suited to a terminal. When exporting to a CLI you can pass the table format with the ``tablefmt`` parameter, the supported formats are:: >>> import tabulate >>> list(tabulate._table_formats) ['simple', 'plain', 'grid', 'fancy_grid', 'github', 'pipe', 'orgtbl', 'jira', 'presto', 'psql', 'rst', 'mediawiki', 'moinmoin', 'youtrack', 'html', 'latex', 'latex_raw', 'latex_booktabs', 'tsv', 'textile'] For example:: dataset.export("cli", tablefmt="github") dataset.export("cli", tablefmt="grid") This format is optional, install Tablib with ``pip install "tablib[cli]"`` to make the format available. csv === When you import CSV data, you can specify if the first line of your data source is headers with the ``headers`` boolean parameter (defaults to ``True``):: import tablib tablib.import_set(your_data_stream, format='csv', headers=False) It is also possible to provide the ``skip_lines`` parameter for the number of lines that should be skipped before starting to read data. .. versionchanged:: 3.1.0 The ``skip_lines`` parameter was added. When exporting with the ``csv`` format, the top row will contain headers, if they have been set. Otherwise, the top row will contain the first row of the dataset. When importing a CSV data source or exporting a dataset as CSV, you can pass any parameter supported by the :py:func:`csv.reader` and :py:func:`csv.writer` functions. For example:: tablib.import_set(your_data_stream, format='csv', dialect='unix') dataset.export('csv', delimiter=' ', quotechar='|') .. admonition:: Line endings Exporting uses \\r\\n line endings by default so, make sure to include ``newline=''`` otherwise you will get a blank line between each row when you open the file in Excel:: with open('output.csv', 'w', newline='') as f: f.write(dataset.export('csv')) If you do not do this, and you export the file on Windows, your CSV file will open in Excel with a blank line between each row. dbf === Import/export using the dBASE_ format. .. admonition:: Binary Warning The ``dbf`` format contains binary data, so make sure to write in binary mode:: with open('output.dbf', 'wb') as f: f.write(dataset.export('dbf') .. _dBASE: https://en.wikipedia.org/wiki/DBase df (DataFrame) ============== Import/export using the pandas_ DataFrame format. This format is optional, install Tablib with ``pip install "tablib[pandas]"`` to make the format available. .. _pandas: https://pandas.pydata.org/ html ==== The exports produce an HTML page with the data in a ````. If headers have been set, they will be used as table headers (``thead``). When you import HTML, you can specify a specific table to import by providing the ``table_id`` argument:: import tablib tablib.import_set(your_html, format='html', table_id='some_table_id') Otherwise, the first table found will be imported. .. versionchanged:: 3.6.0 The ability to import HTML was added. The dependency on MarkupPy was dropped. jira ==== The ``jira`` format is currently export-only. Exports format the dataset according to the Jira table syntax:: ||heading 1||heading 2||heading 3|| |col A1|col A2|col A3| |col B1|col B2|col B3| json ==== Import/export using the JSON_ format. If headers have been set, a JSON list of objects will be returned. If no headers have been set, a JSON list of lists (rows) will be returned instead. Import assumes (for now) that headers exist. .. _JSON: http://json.org/ latex ===== Import/export using the LaTeX_ format. This format is export-only. If a title has been set, it will be exported as the table caption. .. _LaTeX: https://www.latex-project.org/ ods === Import/export data in OpenDocument Spreadsheet format. .. versionadded:: 3.6.0 Import functionality was added. This format is optional, install Tablib with ``pip install "tablib[ods]"`` to make the format available. The ``import_set()`` method also supports a ``skip_lines`` parameter that you can set to a number of lines that should be skipped before starting to read data. .. admonition:: Binary Warning :class:`Dataset.ods` contains binary data, so make sure to write in binary mode:: with open('output.ods', 'wb') as f: f.write(data.ods) rst === Export data as a reStructuredText_ table representation of a dataset. The ``rst`` format is export-only. Exporting returns a simple table if the text in the first column is never wrapped, otherwise returns a grid table:: >>> from tablib import Dataset >>> bits = ((0, 0), (1, 0), (0, 1), (1, 1)) >>> data = Dataset() >>> data.headers = ['A', 'B', 'A and B'] >>> for a, b in bits: ... data.append([bool(a), bool(b), bool(a * b)]) >>> table = data.export('rst') >>> table.split('\\n') == [ ... '===== ===== =====', ... ' A B A and', ... ' B ', ... '===== ===== =====', ... 'False False False', ... 'True False False', ... 'False True False', ... 'True True True ', ... '===== ===== =====', ... ] True .. _reStructuredText: http://docutils.sourceforge.net/rst.html tsv === A variant of the csv_ format with tabulators as fields separators. xls === Import/export data in Legacy Excel Spreadsheet representation. This format is optional, install Tablib with ``pip install "tablib[xls]"`` to make the format available. Its ``import_set()`` method also supports a ``skip_lines`` parameter that you can set to a number of lines that should be skipped before starting to read data. .. versionchanged:: 3.1.0 The ``skip_lines`` parameter for ``import_set()`` was added. .. note:: XLS files are limited to a maximum of 65,000 rows. Use xlsx_ to avoid this limitation. .. admonition:: Binary Warning The ``xls`` file format is binary, so make sure to write in binary mode:: with open('output.xls', 'wb') as f: f.write(data.export('xls')) xlsx ==== Import/export data in Excel 07+ Spreadsheet representation. This format is optional, install Tablib with ``pip install "tablib[xlsx]"`` to make the format available. The ``import_set()`` and ``import_book()`` methods accept keyword argument ``read_only``. If its value is ``True`` (the default), the XLSX data source is read lazily. Lazy reading generally reduces time and memory consumption, especially for large spreadsheets. However, it relies on the XLSX data source declaring correct dimensions. Some programs generate XLSX files with incorrect dimensions. Such files may need to be loaded with this optimization turned off by passing ``read_only=False``. The ``import_set()`` method also supports a ``skip_lines`` parameter that you can set to a number of lines that should be skipped before starting to read data. .. versionchanged:: 3.1.0 The ``skip_lines`` parameter for ``import_set()`` was added. .. note:: When reading an ``xlsx`` file containing formulas in its cells, Tablib will read the cell values, not the cell formulas. .. versionchanged:: 2.0.0 Reads cell values instead of formulas. You can export data to xlsx format by calling :meth:`export('xlsx') <.export>`. There are optional parameters to control the export. For available parameters, see :meth:`tablib.formats._xlsx.XLSXFormat.export_set`. .. admonition:: Binary Warning The ``xlsx`` file format is binary, so make sure to write in binary mode:: with open('output.xlsx', 'wb') as f: f.write(data.export('xlsx')) yaml ==== Import/export data in the YAML_ format. When exporting, if headers have been set, a YAML list of objects will be returned. If no headers have been set, a YAML list of lists (rows) will be returned instead. Import assumes (for now) that headers exist. This format is optional, install Tablib with ``pip install "tablib[yaml]"`` to make the format available. .. _YAML: https://yaml.org