Update docs

HISTORY.md

@@ -4,6 +4,12 @@ Release History
 master
 ------
 
+**Improvements**
+
+- Add markdown export format. [#222](https://github.com/camelot-dev/camelot/pull/222/) by [Lucas Cimon](https://github.com/Lucas-C).
+
+**Documentation**
+
 - Add faq section. [#216](https://github.com/camelot-dev/camelot/pull/216) by [Stefano Fiorucci](https://github.com/anakin87).
 
 0.9.0 (2021-06-15)

README.md

@@ -22,7 +22,7 @@
 >>> tables = camelot.read_pdf('foo.pdf')
 >>> tables
 <TableList n=1>
->>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html, sqlite
+>>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html, markdown, sqlite
 >>> tables[0]
 <Table shape=(7, 7)>
 >>> tables[0].parsing_report
@@ -32,7 +32,7 @@
     'order': 1,
     'page': 1
 }
->>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html, to_sqlite
+>>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html, to_markdown, to_sqlite
 >>> tables[0].df # get a pandas DataFrame!
 </pre>
 
@@ -55,7 +55,7 @@ You can check out some frequently asked questions [here](https://camelot-py.read
 
 - **Configurability**: Camelot gives you control over the table extraction process with [tweakable settings](https://camelot-py.readthedocs.io/en/master/user/advanced.html).
 - **Metrics**: You can discard bad tables based on metrics like accuracy and whitespace, without having to manually look at each table.
-- **Output**: Each table is extracted into a **pandas DataFrame**, which seamlessly integrates into [ETL and data analysis workflows](https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873). You can also export tables to multiple formats, which include CSV, JSON, Excel, HTML and Sqlite.
+- **Output**: Each table is extracted into a **pandas DataFrame**, which seamlessly integrates into [ETL and data analysis workflows](https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873). You can also export tables to multiple formats, which include CSV, JSON, Excel, HTML, Markdown, and Sqlite.
 
 See [comparison with similar libraries and tools](https://github.com/camelot-dev/camelot/wiki/Comparison-with-other-PDF-Table-Extraction-libraries-and-tools).
 

docs/index.rst

@@ -54,7 +54,7 @@ Release v\ |version|. (:ref:`Installation <install>`)
     >>> tables = camelot.read_pdf('foo.pdf')
     >>> tables
     <TableList n=1>
-    >>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html
+    >>> tables.export('foo.csv', f='csv', compress=True) # json, excel, html, markdown, sqlite
     >>> tables[0]
     <Table shape=(7, 7)>
     >>> tables[0].parsing_report
@@ -64,7 +64,7 @@ Release v\ |version|. (:ref:`Installation <install>`)
         'order': 1,
         'page': 1
     }
-    >>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html
+    >>> tables[0].to_csv('foo.csv') # to_json, to_excel, to_html, to_markdown, to_sqlite
     >>> tables[0].df # get a pandas DataFrame!
 
 .. csv-table::
@@ -79,9 +79,9 @@ Camelot also comes packaged with a :ref:`command-line interface <cli>`!
 Why Camelot?
 ------------
 
-- **Configurability**: Camelot gives you control over the table extraction process with its :ref:`tweakable settings <advanced>`.
-- **Metrics**: Bad tables can be discarded based on metrics like accuracy and whitespace, without having to manually look at each table.
-- **Output**: Each table is extracted into a **pandas DataFrame**, which seamlessly integrates into `ETL and data analysis workflows`_. You can also export tables to multiple formats, which include CSV, JSON, Excel, HTML and Sqlite.
+- **Configurability**: Camelot gives you control over the table extraction process with :ref:`tweakable settings <advanced>`.
+- **Metrics**: You can discard bad tables based on metrics like accuracy and whitespace, without having to manually look at each table.
+- **Output**: Each table is extracted into a **pandas DataFrame**, which seamlessly integrates into `ETL and data analysis workflows`_. You can also export tables to multiple formats, which include CSV, JSON, Excel, HTML, Markdown, and Sqlite.
 
 .. _ETL and data analysis workflows: https://gist.github.com/vinayak-mehta/e5949f7c2410a0e12f25d3682dc9e873
 

docs/user/quickstart.rst

@@ -56,7 +56,7 @@ Woah! The accuracy is top-notch and there is less whitespace, which means the ta
 .. csv-table::
   :file: ../_static/csv/foo.csv
 
-Looks good! You can now export the table as a CSV file using its :meth:`to_csv() <camelot.core.Table.to_csv>` method. Alternatively you can use :meth:`to_json() <camelot.core.Table.to_json>`, :meth:`to_excel() <camelot.core.Table.to_excel>` :meth:`to_html() <camelot.core.Table.to_html>` or :meth:`to_sqlite() <camelot.core.Table.to_sqlite>` methods to export the table as JSON, Excel, HTML files or a sqlite database respectively.
+Looks good! You can now export the table as a CSV file using its :meth:`to_csv() <camelot.core.Table.to_csv>` method. Alternatively you can use :meth:`to_json() <camelot.core.Table.to_json>`, :meth:`to_excel() <camelot.core.Table.to_excel>` :meth:`to_html() <camelot.core.Table.to_html>` :meth:`to_markdown() <camelot.core.Table.to_markdown>` or :meth:`to_sqlite() <camelot.core.Table.to_sqlite>` methods to export the table as JSON, Excel, HTML files or a sqlite database respectively.
 
 ::
 
@@ -76,7 +76,7 @@ You can also export all tables at once, using the :class:`tables <camelot.core.T
 
         $ camelot --format csv --output foo.csv lattice foo.pdf
 
-This will export all tables as CSV files at the path specified. Alternatively, you can use ``f='json'``, ``f='excel'``, ``f='html'`` or ``f='sqlite'``.
+This will export all tables as CSV files at the path specified. Alternatively, you can use ``f='json'``, ``f='excel'``, ``f='html'``, ``f='markdown'`` or ``f='sqlite'``.
 
 .. note:: The :meth:`export() <camelot.core.TableList.export>` method exports files with a ``page-*-table-*`` suffix. In the example above, the single table in the list will be exported to ``foo-page-1-table-1.csv``. If the list contains multiple tables, multiple CSV files will be created. To avoid filling up your path with multiple files, you can use ``compress=True``, which will create a single ZIP file at your path with all the CSV files.