Update HISTORY.md

[MRG] Add implementation of Anssi Nurminen's table detection algorithm

HISTORY.md

@@ -4,6 +4,30 @@ Release History
 master
 ------
 
+0.4.0 (2018-11-23)
+------------------
+
+**Improvements**
+
+* [#102](https://github.com/socialcopsdev/camelot/issues/102) Detect tables automatically when Stream is used. [#206](https://github.com/socialcopsdev/camelot/pull/206) Add implementation of Anssi Nurminen's table detection algorithm by Vinayak Mehta.
+
+0.3.2 (2018-11-04)
+------------------
+
+**Improvements**
+
+* [#186](https://github.com/socialcopsdev/camelot/issues/186) Add `_bbox` attribute to table. [#193](https://github.com/socialcopsdev/camelot/pull/193) by Vinayak Mehta.
+    * You can use `table._bbox` to get coordinates of the detected table.
+
+0.3.1 (2018-11-02)
+------------------
+
+**Improvements**
+
+* Matplotlib is now an optional requirement. [#190](https://github.com/socialcopsdev/camelot/pull/190) by Vinayak Mehta.
+    * You can install it using `$ pip install camelot-py[plot]`.
+* [#127](https://github.com/socialcopsdev/camelot/issues/127) Add tests for plotting. Coverage is now at 87%! [#179](https://github.com/socialcopsdev/camelot/pull/179) by [Suyash Behera](https://github.com/Suyash458).
+
 0.3.0 (2018-10-28)
 ------------------
 

Makefile

@@ -15,7 +15,7 @@ install:
 	pip install ".[dev]"
 
 test:
-	pytest --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot tests
+	pytest --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot --mpl
 
 docs:
 	cd docs && make html

README.md

@@ -6,7 +6,7 @@
 
 [![Build Status](https://travis-ci.org/socialcopsdev/camelot.svg?branch=master)](https://travis-ci.org/socialcopsdev/camelot) [![Documentation Status](https://readthedocs.org/projects/camelot-py/badge/?version=master)](https://camelot-py.readthedocs.io/en/master/)
  [![codecov.io](https://codecov.io/github/socialcopsdev/camelot/badge.svg?branch=master&service=github)](https://codecov.io/github/socialcopsdev/camelot?branch=master)
- [![image](https://img.shields.io/pypi/v/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/l/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/pyversions/camelot-py.svg)](https://pypi.org/project/camelot-py/)
+ [![image](https://img.shields.io/pypi/v/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/l/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![image](https://img.shields.io/pypi/pyversions/camelot-py.svg)](https://pypi.org/project/camelot-py/) [![Gitter chat](https://badges.gitter.im/camelot-dev/Lobby.png)](https://gitter.im/camelot-dev/Lobby)
 
 **Camelot** is a Python library that makes it easy for *anyone* to extract tables from PDF files!
 
@@ -61,26 +61,18 @@ See [comparison with other PDF table extraction libraries and tools](https://git
 
 ### Using conda
 
-The easiest way to install Camelot is to install it with [conda](https://conda.io/docs/), which is the package manager that the [Anaconda](http://docs.continuum.io/anaconda/) distribution is built upon.
+The easiest way to install Camelot is to install it with [conda](https://conda.io/docs/), which is a package manager and  environment management system for the [Anaconda](http://docs.continuum.io/anaconda/) distribution.
-
-First, let's add the [conda-forge](https://conda-forge.org/) channel to conda's config:
 
 <pre>
-$ conda config --add channels conda-forge
+$ conda install -c conda-forge camelot-py
-</pre>
-
-Now, you can simply use conda to install Camelot:
-
-<pre>
-$ conda install -c camelot-dev camelot-py
 </pre>
 
 ### Using pip
 
-After [installing the dependencies](https://camelot-py.readthedocs.io/en/master/user/install.html#using-pip) ([tk](https://packages.ubuntu.com/trusty/python-tk) and [ghostscript](https://www.ghostscript.com/)), you can simply use pip to install Camelot:
+After [installing the dependencies](https://camelot-py.readthedocs.io/en/master/user/install-deps.html) ([tk](https://packages.ubuntu.com/trusty/python-tk) and [ghostscript](https://www.ghostscript.com/)), you can simply use pip to install Camelot:
 
 <pre>
-$ pip install camelot-py[all]
+$ pip install camelot-py[cv]
 </pre>
 
 ### From the source code
@@ -95,7 +87,7 @@ and install Camelot using pip:
 
 <pre>
 $ cd camelot
-$ pip install ".[all]"
+$ pip install ".[cv]"
 </pre>
 
 ## Documentation

camelot/__init__.py

@@ -6,6 +6,7 @@ from click import HelpFormatter
 
 from .__version__ import __version__
 from .io import read_pdf
+from .plotting import PlotMethods
 
 
 def _write_usage(self, prog, args='', prefix='Usage: '):
@@ -25,3 +26,6 @@ handler = logging.StreamHandler()
 handler.setFormatter(formatter)
 
 logger.addHandler(handler)
+
+# instantiate plot method
+plot = PlotMethods()

camelot/__version__.py

@@ -1,11 +1,23 @@
 # -*- coding: utf-8 -*-
 
-VERSION = (0, 3, 0)
+VERSION = (0, 4, 0)
+PRERELEASE = None # alpha, beta or rc
+REVISION = None
+
+
+def generate_version(version, prerelease=None, revision=None):
+    version_parts = ['.'.join(map(str, version))]
+    if prerelease is not None:
+        version_parts.append('-{}'.format(prerelease))
+    if revision is not None:
+        version_parts.append('.{}'.format(revision))
+    return ''.join(version_parts)
+
 
 __title__ = 'camelot-py'
 __description__ = 'PDF Table Extraction for Humans.'
 __url__ = 'http://camelot-py.readthedocs.io/'
-__version__ = '.'.join(map(str, VERSION))
+__version__ = generate_version(VERSION, prerelease=PRERELEASE, revision=REVISION)
 __author__ = 'Vinayak Mehta'
 __author_email__ = 'vmehta94@gmail.com'
 __license__ = 'MIT License'

camelot/cli.py

@@ -3,9 +3,14 @@
 import logging
 
 import click
+try:
+    import matplotlib.pyplot as plt
+except ImportError:
+    _HAS_MPL = False
+else:
+    _HAS_MPL = True
 
-from . import __version__
+from . import __version__, read_pdf, plot
-from .io import read_pdf
 
 
 logger = logging.getLogger('camelot')
@@ -80,8 +85,8 @@ def cli(ctx, *args, **kwargs):
 @click.option('-I', '--iterations', default=0,
               help='Number of times for erosion/dilation will be applied.')
 @click.option('-plot', '--plot_type',
-              type=click.Choice(['text', 'table', 'contour', 'joint', 'line']),
+              type=click.Choice(['text', 'grid', 'contour', 'joint', 'line']),
-              help='Plot geometry found on PDF page, for debugging.')
+              help='Plot elements found on PDF page for visual debugging.')
 @click.argument('filepath', type=click.Path(exists=True))
 @pass_config
 def lattice(c, *args, **kwargs):
@@ -102,17 +107,23 @@ def lattice(c, *args, **kwargs):
     kwargs['copy_text'] = None if not copy_text else copy_text
     kwargs['shift_text'] = list(kwargs['shift_text'])
 
-    tables = read_pdf(filepath, pages=pages, flavor='lattice',
-                      suppress_warnings=suppress_warnings, **kwargs)
-    click.echo('Found {} tables'.format(tables.n))
     if plot_type is not None:
-        for table in tables:
+        if not _HAS_MPL:
-            table.plot(plot_type)
+            raise ImportError('matplotlib is required for plotting.')
     else:
         if output is None:
             raise click.UsageError('Please specify output file path using --output')
         if f is None:
             raise click.UsageError('Please specify output file format using --format')
+
+    tables = read_pdf(filepath, pages=pages, flavor='lattice',
+                      suppress_warnings=suppress_warnings, **kwargs)
+    click.echo('Found {} tables'.format(tables.n))
+    if plot_type is not None:
+        for table in tables:
+            plot(table, kind=plot_type)
+            plt.show()
+    else:
         tables.export(output, f=f, compress=compress)
 
 
@@ -127,8 +138,8 @@ def lattice(c, *args, **kwargs):
 @click.option('-c', '--col_close_tol', default=0, help='Tolerance parameter'
               ' used to combine text horizontally, to generate columns.')
 @click.option('-plot', '--plot_type',
-              type=click.Choice(['text', 'table']),
+              type=click.Choice(['text', 'grid']),
-              help='Plot geometry found on PDF page for debugging.')
+              help='Plot elements found on PDF page for visual debugging.')
 @click.argument('filepath', type=click.Path(exists=True))
 @pass_config
 def stream(c, *args, **kwargs):
@@ -148,15 +159,21 @@ def stream(c, *args, **kwargs):
     columns = list(kwargs['columns'])
     kwargs['columns'] = None if not columns else columns
 
-    tables = read_pdf(filepath, pages=pages, flavor='stream',
-                      suppress_warnings=suppress_warnings, **kwargs)
-    click.echo('Found {} tables'.format(tables.n))
     if plot_type is not None:
-        for table in tables:
+        if not _HAS_MPL:
-            table.plot(plot_type)
+            raise ImportError('matplotlib is required for plotting.')
     else:
         if output is None:
             raise click.UsageError('Please specify output file path using --output')
         if f is None:
             raise click.UsageError('Please specify output file format using --format')
+
+    tables = read_pdf(filepath, pages=pages, flavor='stream',
+                      suppress_warnings=suppress_warnings, **kwargs)
+    click.echo('Found {} tables'.format(tables.n))
+    if plot_type is not None:
+        for table in tables:
+            plot(table, kind=plot_type)
+            plt.show()
+    else:
         tables.export(output, f=f, compress=compress)

camelot/core.py

@@ -3,11 +3,208 @@
 import os
 import zipfile
 import tempfile
+from itertools import chain
+from operator import itemgetter
 
 import numpy as np
 import pandas as pd
 
-from .plotting import *
+
+# minimum number of vertical textline intersections for a textedge
+# to be considered valid
+TEXTEDGE_REQUIRED_ELEMENTS = 4
+# y coordinate tolerance for extending textedge
+TEXTEDGE_EXTEND_TOLERANCE = 50
+# padding added to table area on the left, right and bottom
+TABLE_AREA_PADDING = 10
+
+
+class TextEdge(object):
+    """Defines a text edge coordinates relative to a left-bottom
+    origin. (PDF coordinate space)
+
+    Parameters
+    ----------
+    x : float
+        x-coordinate of the text edge.
+    y0 : float
+        y-coordinate of bottommost point.
+    y1 : float
+        y-coordinate of topmost point.
+    align : string, optional (default: 'left')
+        {'left', 'right', 'middle'}
+
+    Attributes
+    ----------
+    intersections: int
+        Number of intersections with horizontal text rows.
+    is_valid: bool
+        A text edge is valid if it intersections with at least
+        TEXTEDGE_REQUIRED_ELEMENTS horizontal text rows.
+
+    """
+    def __init__(self, x, y0, y1, align='left'):
+        self.x = x
+        self.y0 = y0
+        self.y1 = y1
+        self.align = align
+        self.intersections = 0
+        self.is_valid = False
+
+    def __repr__(self):
+        return '<TextEdge x={} y0={} y1={} align={} valid={}>'.format(
+            round(self.x, 2), round(self.y0, 2), round(self.y1, 2), self.align, self.is_valid)
+
+    def update_coords(self, x, y0):
+        """Updates the text edge's x and bottom y coordinates and sets
+        the is_valid attribute.
+        """
+        if np.isclose(self.y0, y0, atol=TEXTEDGE_EXTEND_TOLERANCE):
+            self.x = (self.intersections * self.x + x) / float(self.intersections + 1)
+            self.y0 = y0
+            self.intersections += 1
+            # a textedge is valid only if it extends uninterrupted
+            # over a required number of textlines
+            if self.intersections > TEXTEDGE_REQUIRED_ELEMENTS:
+                self.is_valid = True
+
+
+class TextEdges(object):
+    """Defines a dict of left, right and middle text edges found on
+    the PDF page. The dict has three keys based on the alignments,
+    and each key's value is a list of camelot.core.TextEdge objects.
+    """
+    def __init__(self):
+        self._textedges = {'left': [], 'right': [], 'middle': []}
+
+    @staticmethod
+    def get_x_coord(textline, align):
+        """Returns the x coordinate of a text row based on the
+        specified alignment.
+        """
+        x_left = textline.x0
+        x_right = textline.x1
+        x_middle = x_left + (x_right - x_left) / 2.0
+        x_coord = {'left': x_left, 'middle': x_middle, 'right': x_right}
+        return x_coord[align]
+
+    def find(self, x_coord, align):
+        """Returns the index of an existing text edge using
+        the specified x coordinate and alignment.
+        """
+        for i, te in enumerate(self._textedges[align]):
+            if np.isclose(te.x, x_coord, atol=0.5):
+                return i
+        return None
+
+    def add(self, textline, align):
+        """Adds a new text edge to the current dict.
+        """
+        x = self.get_x_coord(textline, align)
+        y0 = textline.y0
+        y1 = textline.y1
+        te = TextEdge(x, y0, y1, align=align)
+        self._textedges[align].append(te)
+
+    def update(self, textline):
+        """Updates an existing text edge in the current dict.
+        """
+        for align in ['left', 'right', 'middle']:
+            x_coord = self.get_x_coord(textline, align)
+            idx = self.find(x_coord, align)
+            if idx is None:
+                self.add(textline, align)
+            else:
+                self._textedges[align][idx].update_coords(x_coord, textline.y0)
+
+    def generate(self, textlines):
+        """Generates the text edges dict based on horizontal text
+        rows.
+        """
+        for tl in textlines:
+            if len(tl.get_text().strip()) > 1: # TODO: hacky
+                self.update(tl)
+
+    def get_relevant(self):
+        """Returns the list of relevant text edges (all share the same
+        alignment) based on which list intersects horizontal text rows
+        the most.
+        """
+        intersections_sum = {
+            'left': sum(te.intersections for te in self._textedges['left'] if te.is_valid),
+            'right': sum(te.intersections for te in self._textedges['right'] if te.is_valid),
+            'middle': sum(te.intersections for te in self._textedges['middle'] if te.is_valid)
+        }
+
+        # TODO: naive
+        # get vertical textedges that intersect maximum number of
+        # times with horizontal textlines
+        relevant_align = max(intersections_sum.items(), key=itemgetter(1))[0]
+        return self._textedges[relevant_align]
+
+    def get_table_areas(self, textlines, relevant_textedges):
+        """Returns a dict of interesting table areas on the PDF page
+        calculated using relevant text edges.
+        """
+        def pad(area, average_row_height):
+            x0 = area[0] - TABLE_AREA_PADDING
+            y0 = area[1] - TABLE_AREA_PADDING
+            x1 = area[2] + TABLE_AREA_PADDING
+            # add a constant since table headers can be relatively up
+            y1 = area[3] + average_row_height * 5
+            return (x0, y0, x1, y1)
+
+        # sort relevant textedges in reading order
+        relevant_textedges.sort(key=lambda te: (-te.y0, te.x))
+
+        table_areas = {}
+        for te in relevant_textedges:
+            if te.is_valid:
+                if not table_areas:
+                    table_areas[(te.x, te.y0, te.x, te.y1)] = None
+                else:
+                    found = None
+                    for area in table_areas:
+                        # check for overlap
+                        if te.y1 >= area[1] and te.y0 <= area[3]:
+                            found = area
+                            break
+                    if found is None:
+                        table_areas[(te.x, te.y0, te.x, te.y1)] = None
+                    else:
+                        table_areas.pop(found)
+                        updated_area = (
+                            found[0], min(te.y0, found[1]), max(found[2], te.x), max(found[3], te.y1))
+                        table_areas[updated_area] = None
+
+        # extend table areas based on textlines that overlap
+        # vertically. it's possible that these textlines were
+        # eliminated during textedges generation since numbers and
+        # chars/words/sentences are often aligned differently.
+        # drawback: table areas that have paragraphs on their sides
+        # will include the paragraphs too.
+        sum_textline_height = 0
+        for tl in textlines:
+            sum_textline_height += tl.y1 - tl.y0
+            found = None
+            for area in table_areas:
+                # check for overlap
+                if tl.y0 >= area[1] and tl.y1 <= area[3]:
+                    found = area
+                    break
+            if found is not None:
+                table_areas.pop(found)
+                updated_area = (
+                    min(tl.x0, found[0]), min(tl.y0, found[1]), max(found[2], tl.x1), max(found[3], tl.y1))
+                table_areas[updated_area] = None
+        average_textline_height = sum_textline_height / float(len(textlines))
+
+        # add some padding to table areas
+        table_areas_padded = {}
+        for area in table_areas:
+            table_areas_padded[pad(area, average_textline_height)] = None
+
+        return table_areas_padded
 
 
 class Cell(object):
@@ -321,33 +518,6 @@ class Table(object):
                     cell.hspan = True
         return self
 
-    def plot(self, geometry_type):
-        """Plot geometry found on PDF page based on geometry_type
-        specified, useful for debugging and playing with different
-        parameters to get the best output.
-
-        Parameters
-        ----------
-        geometry_type : str
-            The geometry type for which a plot should be generated.
-            Can be 'text', 'table', 'contour', 'joint', 'line'
-
-        """
-        if self.flavor == 'stream' and geometry_type in ['contour', 'joint', 'line']:
-            raise NotImplementedError("{} cannot be plotted with flavor='stream'".format(
-                                       geometry_type))
-
-        if geometry_type == 'text':
-            plot_text(self._text)
-        elif geometry_type == 'table':
-            plot_table(self)
-        elif geometry_type == 'contour':
-            plot_contour(self._image)
-        elif geometry_type == 'joint':
-            plot_joint(self._image)
-        elif geometry_type == 'line':
-            plot_line(self._segments)
-
     def to_csv(self, path, **kwargs):
         """Writes Table to a comma-separated values (csv) file.
 

camelot/handlers.py

@@ -141,9 +141,6 @@ class PDFHandler(object):
         -------
         tables : camelot.core.TableList
             List of tables found in PDF.
-        geometry : camelot.core.GeometryList
-            List of geometry objects (contours, lines, joints) found
-            in PDF.
 
         """
         tables = []

camelot/parsers/lattice.py

@@ -362,6 +362,7 @@ class Lattice(BaseParser):
                 self.table_bbox.keys(), key=lambda x: x[1], reverse=True)):
             cols, rows, v_s, h_s = self._generate_columns_and_rows(table_idx, tk)
             table = self._generate_table(table_idx, cols, rows, v_s=v_s, h_s=h_s)
+            table._bbox = tk
             _tables.append(table)
 
         return _tables

camelot/parsers/stream.py

@@ -9,7 +9,7 @@ import numpy as np
 import pandas as pd
 
 from .base import BaseParser
-from ..core import Table
+from ..core import TextEdges, Table
 from ..utils import (text_in_bbox, get_table_index, compute_accuracy,
                      compute_whitespace)
 
@@ -116,7 +116,7 @@ class Stream(BaseParser):
                     row_y = t.y0
                 temp.append(t)
         rows.append(sorted(temp, key=lambda t: t.x0))
-        __ = rows.pop(0)  # hacky
+        __ = rows.pop(0)  # TODO: hacky
         return rows
 
     @staticmethod
@@ -246,6 +246,31 @@ class Stream(BaseParser):
                 raise ValueError("Length of table_areas and columns"
                                  " should be equal")
 
+    def _nurminen_table_detection(self, textlines):
+        """A general implementation of the table detection algorithm
+        described by Anssi Nurminen's master's thesis.
+        Link: https://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/21520/Nurminen.pdf?sequence=3
+
+        Assumes that tables are situated relatively far apart
+        vertically.
+        """
+
+        # TODO: add support for arabic text #141
+        # sort textlines in reading order
+        textlines.sort(key=lambda x: (-x.y0, x.x0))
+        textedges = TextEdges()
+        # generate left, middle and right textedges
+        textedges.generate(textlines)
+        # select relevant edges
+        relevant_textedges = textedges.get_relevant()
+        # guess table areas using textlines and relevant edges
+        table_bbox = textedges.get_table_areas(textlines, relevant_textedges)
+        # treat whole page as table area if no table areas found
+        if not len(table_bbox):
+            table_bbox = {(0, 0, self.pdf_width, self.pdf_height): None}
+
+        return table_bbox
+
     def _generate_table_bbox(self):
         if self.table_areas is not None:
             table_bbox = {}
@@ -257,7 +282,8 @@ class Stream(BaseParser):
                 y2 = float(y2)
                 table_bbox[(x1, y2, x2, y1)] = None
         else:
-            table_bbox = {(0, 0, self.pdf_width, self.pdf_height): None}
+            # find tables based on nurminen's detection algorithm
+            table_bbox = self._nurminen_table_detection(self.horizontal_text)
         self.table_bbox = table_bbox
 
     def _generate_columns_and_rows(self, table_idx, tk):
@@ -286,10 +312,21 @@ class Stream(BaseParser):
             cols.append(text_x_max)
             cols = [(cols[i], cols[i + 1]) for i in range(0, len(cols) - 1)]
         else:
+            # calculate mode of the list of number of elements in
+            # each row to guess the number of columns
             ncols = max(set(elements), key=elements.count)
             if ncols == 1:
-                warnings.warn("No tables found on {}".format(
+                # if mode is 1, the page usually contains not tables
-                    os.path.basename(self.rootname)))
+                # but there can be cases where the list can be skewed,
+                # try to remove all 1s from list in this case and
+                # see if the list contains elements, if yes, then use
+                # the mode after removing 1s
+                elements = list(filter(lambda x: x != 1, elements))
+                if len(elements):
+                    ncols = max(set(elements), key=elements.count)
+                else:
+                    warnings.warn("No tables found in table area {}".format(
+                        table_idx + 1))
             cols = [(t.x0, t.x1) for r in rows_grouped if len(r) == ncols for t in r]
             cols = self._merge_columns(sorted(cols), col_close_tol=self.col_close_tol)
             inner_text = []
@@ -361,6 +398,7 @@ class Stream(BaseParser):
                 self.table_bbox.keys(), key=lambda x: x[1], reverse=True)):
             cols, rows = self._generate_columns_and_rows(table_idx, tk)
             table = self._generate_table(table_idx, cols, rows)
+            table._bbox = tk
             _tables.append(table)
 
         return _tables

camelot/plotting.py

@@ -1,20 +1,62 @@
-import cv2
+# -*- coding: utf-8 -*-
-import matplotlib.pyplot as plt
+
-import matplotlib.patches as patches
+try:
+    import matplotlib.pyplot as plt
+    import matplotlib.patches as patches
+except ImportError:
+    _HAS_MPL = False
+else:
+    _HAS_MPL = True
 
 
-def plot_text(text):
+class PlotMethods(object):
-    """Generates a plot for all text present on the PDF page.
+    def __call__(self, table, kind='text', filename=None):
+        """Plot elements found on PDF page based on kind
+        specified, useful for debugging and playing with different
+        parameters to get the best output.
 
         Parameters
         ----------
-    text : list
+        table: camelot.core.Table
+            A Camelot Table.
+        kind : str, optional (default: 'text')
+            {'text', 'grid', 'contour', 'joint', 'line'}
+            The element type for which a plot should be generated.
+        filepath: str, optional (default: None)
+            Absolute path for saving the generated plot.
+
+        Returns
+        -------
+        fig : matplotlib.fig.Figure
+
+        """
+        if not _HAS_MPL:
+            raise ImportError('matplotlib is required for plotting.')
+
+        if table.flavor == 'stream' and kind in ['contour', 'joint', 'line']:
+            raise NotImplementedError("Stream flavor does not support kind='{}'".format(
+                                      kind))
+
+        plot_method = getattr(self, kind)
+        return plot_method(table)
+
+    def text(self, table):
+        """Generates a plot for all text elements present
+        on the PDF page.
+
+        Parameters
+        ----------
+        table : camelot.core.Table
+
+        Returns
+        -------
+        fig : matplotlib.fig.Figure
 
         """
         fig = plt.figure()
         ax = fig.add_subplot(111, aspect='equal')
         xs, ys = [], []
-    for t in text:
+        for t in table._text:
             xs.extend([t[0], t[2]])
             ys.extend([t[1], t[3]])
             ax.add_patch(
@@ -26,83 +68,112 @@ def plot_text(text):
             )
         ax.set_xlim(min(xs) - 10, max(xs) + 10)
         ax.set_ylim(min(ys) - 10, max(ys) + 10)
-    plt.show()
+        return fig
 
-
+    def grid(self, table):
-def plot_table(table):
+        """Generates a plot for the detected table grids
-    """Generates a plot for the table.
+        on the PDF page.
 
         Parameters
         ----------
         table : camelot.core.Table
 
+        Returns
+        -------
+        fig : matplotlib.fig.Figure
+
         """
+        fig = plt.figure()
+        ax = fig.add_subplot(111, aspect='equal')
         for row in table.cells:
             for cell in row:
                 if cell.left:
-                plt.plot([cell.lb[0], cell.lt[0]],
+                    ax.plot([cell.lb[0], cell.lt[0]],
                             [cell.lb[1], cell.lt[1]])
                 if cell.right:
-                plt.plot([cell.rb[0], cell.rt[0]],
+                    ax.plot([cell.rb[0], cell.rt[0]],
                             [cell.rb[1], cell.rt[1]])
                 if cell.top:
-                plt.plot([cell.lt[0], cell.rt[0]],
+                    ax.plot([cell.lt[0], cell.rt[0]],
                             [cell.lt[1], cell.rt[1]])
                 if cell.bottom:
-                plt.plot([cell.lb[0], cell.rb[0]],
+                    ax.plot([cell.lb[0], cell.rb[0]],
                             [cell.lb[1], cell.rb[1]])
-    plt.show()
+        return fig
 
-
+    def contour(self, table):
-def plot_contour(image):
+        """Generates a plot for all table boundaries present
-    """Generates a plot for all table boundaries present on the
+        on the PDF page.
-    PDF page.
 
         Parameters
         ----------
-    image : tuple
+        table : camelot.core.Table
+
+        Returns
+        -------
+        fig : matplotlib.fig.Figure
 
         """
-    img, table_bbox = image
+        img, table_bbox = table._image
+        fig = plt.figure()
+        ax = fig.add_subplot(111, aspect='equal')
         for t in table_bbox.keys():
-        cv2.rectangle(img, (t[0], t[1]),
+            ax.add_patch(
-                      (t[2], t[3]), (255, 0, 0), 20)
+                patches.Rectangle(
-    plt.imshow(img)
+                    (t[0], t[1]),
-    plt.show()
+                    t[2] - t[0],
+                    t[3] - t[1],
+                    fill=None,
+                    edgecolor='red'
+                )
+            )
+        ax.imshow(img)
+        return fig
 
-
+    def joint(self, table):
-def plot_joint(image):
+        """Generates a plot for all line intersections present
-    """Generates a plot for all line intersections present on the
+        on the PDF page.
-    PDF page.
 
         Parameters
         ----------
-    image : tuple
+        table : camelot.core.Table
+
+        Returns
+        -------
+        fig : matplotlib.fig.Figure
 
         """
-    img, table_bbox = image
+        img, table_bbox = table._image
+        fig = plt.figure()
+        ax = fig.add_subplot(111, aspect='equal')
         x_coord = []
         y_coord = []
         for k in table_bbox.keys():
             for coord in table_bbox[k]:
                 x_coord.append(coord[0])
                 y_coord.append(coord[1])
-    plt.plot(x_coord, y_coord, 'ro')
+        ax.plot(x_coord, y_coord, 'ro')
-    plt.imshow(img)
+        ax.imshow(img)
-    plt.show()
+        return fig
 
-
+    def line(self, table):
-def plot_line(segments):
+        """Generates a plot for all line segments present
-    """Generates a plot for all line segments present on the PDF page.
+        on the PDF page.
 
         Parameters
         ----------
-    segments : tuple
+        table : camelot.core.Table
+
+        Returns
+        -------
+        fig : matplotlib.fig.Figure
 
         """
-    vertical, horizontal = segments
+        fig = plt.figure()
+        ax = fig.add_subplot(111, aspect='equal')
+        vertical, horizontal = table._segments
         for v in vertical:
-        plt.plot([v[0], v[2]], [v[1], v[3]])
+            ax.plot([v[0], v[2]], [v[1], v[3]])
         for h in horizontal:
-        plt.plot([h[0], h[2]], [h[1], h[3]])
+            ax.plot([h[0], h[2]], [h[1], h[3]])
-    plt.show()
+        return fig

docs/dev/contributing.rst

@@ -7,7 +7,7 @@ If you're reading this, you're probably looking to contributing to Camelot. *Tim
 
 This document will help you get started with contributing documentation, code, testing and filing issues. If you have any questions, feel free to reach out to `Vinayak Mehta`_, the author and maintainer.
 
-.. _Vinayak Mehta: https://vinayak-mehta.github.io
+.. _Vinayak Mehta: https://www.vinayakmehta.com
 
 Code Of Conduct
 ---------------

docs/index.rst

@@ -27,6 +27,9 @@ Release v\ |version|. (:ref:`Installation <install>`)
 .. image:: https://img.shields.io/pypi/pyversions/camelot-py.svg
     :target: https://pypi.org/project/camelot-py/
 
+.. image:: https://badges.gitter.im/camelot-dev/Lobby.png
+    :target: https://gitter.im/camelot-dev/Lobby
+
 **Camelot** is a Python library that makes it easy for *anyone* to extract tables from PDF files!
 
 .. note:: You can also check out `Excalibur`_, which is a web interface for Camelot!
@@ -89,6 +92,7 @@ This part of the documentation begins with some background information about why
    :maxdepth: 2
 
    user/intro
+   user/install-deps
    user/install
    user/how-it-works
    user/quickstart

docs/user/advanced.rst

@@ -27,22 +27,24 @@ To process background lines, you can pass ``process_background=True``.
 .. csv-table::
   :file: ../_static/csv/background_lines.csv
 
-Plot geometry
+Visual debugging
--------------
+----------------
 
-You can use a :class:`table <camelot.core.Table>` object's :meth:`plot() <camelot.core.TableList.plot>` method to plot various geometries that were detected by Camelot while processing the PDF page. This can help you select table areas, column separators and debug bad table outputs, by tweaking different configuration parameters.
+.. note:: Visual debugging using ``plot()`` requires `matplotlib <https://matplotlib.org/>`_ which is an optional dependency. You can install it using ``$ pip install camelot-py[plot]``.
 
-The following geometries are available for plotting. You can pass them to the :meth:`plot() <camelot.core.TableList.plot>` method, which will then generate a `matplotlib <https://matplotlib.org/>`_ plot for the passed geometry.
+You can use the :class:`plot() <camelot.plotting.PlotMethods>` method to generate a `matplotlib <https://matplotlib.org/>`_ plot of various elements that were detected on the PDF page while processing it. This can help you select table areas, column separators and debug bad table outputs, by tweaking different configuration parameters.
+
+You can specify the type of element you want to plot using the ``kind`` keyword argument. The generated plot can be saved to a file by passing a ``filename`` keyword argument. The following plot types are supported:
 
 - 'text'
-- 'table'
+- 'grid'
 - 'contour'
 - 'line'
 - 'joint'
 
-.. note:: The last three geometries can only be used with :ref:`Lattice <lattice>`, i.e. when ``flavor='lattice'``.
+.. note:: The last three plot types can only be used with :ref:`Lattice <lattice>`, i.e. when ``flavor='lattice'``.
 
-Let's generate a plot for each geometry using this `PDF <../_static/pdf/foo.pdf>`__ as an example. First, let's get all the tables out.
+Let's generate a plot for each type using this `PDF <../_static/pdf/foo.pdf>`__ as an example. First, let's get all the tables out.
 
 ::
 
@@ -50,8 +52,6 @@ Let's generate a plot for each geometry using this `PDF <../_static/pdf/foo.pdf>
     >>> tables
     <TableList n=1>
 
-.. _geometry_text:
-
 text
 ^^^^
 
@@ -59,9 +59,10 @@ Let's plot all the text present on the table's PDF page.
 
 ::
 
-    >>> tables[0].plot('text')
+    >>> camelot.plot(tables[0], kind='text')
+    >>> plt.show()
 
-.. figure:: ../_static/png/geometry_text.png
+.. figure:: ../_static/png/plot_text.png
     :height: 674
     :width: 1366
     :scale: 50%
@@ -72,18 +73,17 @@ This, as we shall later see, is very helpful with :ref:`Stream <stream>` for not
 
 .. note:: The *x-y* coordinates shown above change as you move your mouse cursor on the image, which can help you note coordinates.
 
-.. _geometry_table:
-
 table
 ^^^^^
 
-Let's plot the table (to see if it was detected correctly or not). This geometry type, along with contour, line and joint is useful for debugging and improving the extraction output, in case the table wasn't detected correctly. (More on that later.)
+Let's plot the table (to see if it was detected correctly or not). This plot type, along with contour, line and joint is useful for debugging and improving the extraction output, in case the table wasn't detected correctly. (More on that later.)
 
 ::
 
-    >>> tables[0].plot('table')
+    >>> camelot.plot(tables[0], kind='grid')
+    >>> plt.show()
 
-.. figure:: ../_static/png/geometry_table.png
+.. figure:: ../_static/png/plot_table.png
     :height: 674
     :width: 1366
     :scale: 50%
@@ -92,8 +92,6 @@ Let's plot the table (to see if it was detected correctly or not). This geometry
 
 The table is perfect!
 
-.. _geometry_contour:
-
 contour
 ^^^^^^^
 
@@ -101,17 +99,16 @@ Now, let's plot all table boundaries present on the table's PDF page.
 
 ::
 
-    >>> tables[0].plot('contour')
+    >>> camelot.plot(tables[0], kind='contour')
+    >>> plt.show()
 
-.. figure:: ../_static/png/geometry_contour.png
+.. figure:: ../_static/png/plot_contour.png
     :height: 674
     :width: 1366
     :scale: 50%
     :alt: A plot of all contours on a PDF page
     :align: left
 
-.. _geometry_line:
-
 line
 ^^^^
 
@@ -119,17 +116,16 @@ Cool, let's plot all line segments present on the table's PDF page.
 
 ::
 
-    >>> tables[0].plot('line')
+    >>> camelot.plot(tables[0], kind='line')
+    >>> plt.show()
 
-.. figure:: ../_static/png/geometry_line.png
+.. figure:: ../_static/png/plot_line.png
     :height: 674
     :width: 1366
     :scale: 50%
     :alt: A plot of all lines on a PDF page
     :align: left
 
-.. _geometry_joint:
-
 joint
 ^^^^^
 
@@ -137,9 +133,10 @@ Finally, let's plot all line intersections present on the table's PDF page.
 
 ::
 
-    >>> tables[0].plot('joint')
+    >>> camelot.plot(tables[0], kind='joint')
+    >>> plt.show()
 
-.. figure:: ../_static/png/geometry_joint.png
+.. figure:: ../_static/png/plot_joint.png
     :height: 674
     :width: 1366
     :scale: 50%
@@ -149,7 +146,7 @@ Finally, let's plot all line intersections present on the table's PDF page.
 Specify table areas
 -------------------
 
-Since :ref:`Stream <stream>` treats the whole page as a table, `for now`_, it's useful to specify table boundaries in cases such as `these <../_static/pdf/table_areas.pdf>`__. You can :ref:`plot the text <geometry_text>` on this page and note the top left and bottom right coordinates of the table.
+Since :ref:`Stream <stream>` treats the whole page as a table, `for now`_, it's useful to specify table boundaries in cases such as `these <../_static/pdf/table_areas.pdf>`__. You can plot the text on this page and note the top left and bottom right coordinates of the table.
 
 Table areas that you want Camelot to analyze can be passed as a list of comma-separated strings to :meth:`read_pdf() <camelot.read_pdf>`, using the ``table_areas`` keyword argument.
 
@@ -166,15 +163,15 @@ Table areas that you want Camelot to analyze can be passed as a list of comma-se
 Specify column separators
 -------------------------
 
-In cases like `these <../_static/pdf/column_separators.pdf>`__, where the text is very close to each other, it is possible that Camelot may guess the column separators' coordinates incorrectly. To correct this, you can explicitly specify the *x* coordinate for each column separator by :ref:`plotting the text <geometry_text>` on the page.
+In cases like `these <../_static/pdf/column_separators.pdf>`__, where the text is very close to each other, it is possible that Camelot may guess the column separators' coordinates incorrectly. To correct this, you can explicitly specify the *x* coordinate for each column separator by plotting the text on the page.
 
 You can pass the column separators as a list of comma-separated strings to :meth:`read_pdf() <camelot.read_pdf>`, using the ``columns`` keyword argument.
 
 In case you passed a single column separators string list, and no table area is specified, the separators will be applied to the whole page. When a list of table areas is specified and you need to specify column separators as well, **the length of both lists should be equal**. Each table area will be mapped to each column separators' string using their indices.
 
-For example, if you have specified two table areas, ``table_areas=['12,23,43,54', '20,33,55,67']``, and only want to specify column separators for the first table, you can pass an empty string for the second table in the column separators' list like this, ``columns=['10,120,200,400', '']``.
+For example, if you have specified two table areas, ``table_areas=['12,54,43,23', '20,67,55,33']``, and only want to specify column separators for the first table, you can pass an empty string for the second table in the column separators' list like this, ``columns=['10,120,200,400', '']``.
 
-Let's get back to the *x* coordinates we got from :ref:`plotting text <geometry_text>` that exists on this `PDF <../_static/pdf/column_separators.pdf>`__, and get the table out!
+Let's get back to the *x* coordinates we got from plotting the text that exists on this `PDF <../_static/pdf/column_separators.pdf>`__, and get the table out!
 
 ::
 
@@ -282,23 +279,25 @@ Here's a `PDF <../_static/pdf/short_lines.pdf>`__ where small lines separating t
     :alt: A PDF table with short lines
     :align: left
 
-Let's :ref:`plot the table <geometry_table>` for this PDF.
+Let's plot the table for this PDF.
 
 ::
 
     >>> tables = camelot.read_pdf('short_lines.pdf')
-    >>> tables[0].plot('table')
+    >>> camelot.plot(tables[0], kind='grid')
+    >>> plt.show()
 
 .. figure:: ../_static/png/short_lines_1.png
     :alt: A plot of the PDF table with short lines
     :align: left
 
-Clearly, the smaller lines separating the headers, couldn't be detected. Let's try with ``line_size_scaling=40``, and `plot the table <geometry_table>`_ again.
+Clearly, the smaller lines separating the headers, couldn't be detected. Let's try with ``line_size_scaling=40``, and plot the table again.
 
 ::
 
     >>> tables = camelot.read_pdf('short_lines.pdf', line_size_scaling=40)
-    >>> tables[0].plot('table')
+    >>> camelot.plot(tables[0], kind='grid')
+    >>> plt.show()
 
 .. figure:: ../_static/png/short_lines_2.png
     :alt: An improved plot of the PDF table with short lines

docs/user/cli.rst

@@ -9,11 +9,11 @@ You can print the help for the interface by typing ``camelot --help`` in your fa
 
 ::
 
-Usage: camelot [OPTIONS] COMMAND [ARGS]...
+  Usage: camelot [OPTIONS] COMMAND [ARGS]...
 
     Camelot: PDF Table Extraction for Humans
 
-Options:
+  Options:
     --version                       Show the version and exit.
     -p, --pages TEXT                Comma-separated page numbers. Example: 1,3,4
                                     or 1,4-end.
@@ -31,6 +31,6 @@ Options:
     -q, --quiet                     Suppress warnings.
     --help                          Show this message and exit.
 
-Commands:
+  Commands:
     lattice  Use lines between text to parse the table.
     stream   Use spaces between text to parse the table.

docs/user/how-it-works.rst

@@ -5,24 +5,24 @@ How It Works
 
 This part of the documentation includes a high-level explanation of how Camelot extracts tables from PDF files.
 
-You can choose between two table parsing methods, *Stream* and *Lattice*. These names for parsing methods inside Camelot were inspired from `Tabula`_.
+You can choose between two table parsing methods, *Stream* and *Lattice*. These names for parsing methods inside Camelot were inspired from `Tabula <https://github.com/tabulapdf/tabula>`_.
-
-.. _Tabula: https://github.com/tabulapdf/tabula
 
 .. _stream:
 
 Stream
 ------
 
-Stream can be used to parse tables that have whitespaces between cells to simulate a table structure. It looks for these spaces between text to form a table representation.
+Stream can be used to parse tables that have whitespaces between cells to simulate a table structure. It is built on top of PDFMiner's functionality of grouping characters on a page into words and sentences, using `margins <https://euske.github.io/pdfminer/#tools>`_.
 
-It is built on top of PDFMiner's functionality of grouping characters on a page into words and sentences, using `margins`_. After getting the words on a page, it groups them into rows based on their *y* coordinates. It then tries to guess the number of columns the table might have by calculating the mode of the number of words in each row. This mode is used to calculate *x* ranges for the table's columns. It then adds columns to this column range list based on any words that may lie outside or inside the current column *x* ranges.
+1. Words on the PDF page are grouped into text rows based on their *y* axis overlaps.
 
-.. _margins: https://euske.github.io/pdfminer/#tools
+2. Textedges are calculated and then used to guess interesting table areas on the PDF page. You can read `Anssi Nurminen's master's thesis <http://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/21520/Nurminen.pdf?sequence=3>`_ to know more about this table detection technique. [See pages 20, 35 and 40]
 
-.. note:: By default, Stream treats the whole PDF page as a table, which isn't ideal when there are more than two tables on a page with different number of columns. Automatic table detection for Stream is `in the works`_.
+3. The number of columns inside each table area are then guessed. This is done by calculating the mode of number of words in each text row. Based on this mode, words in each text row are chosen to calculate a list of column *x* ranges.
 
-.. _in the works: https://github.com/socialcopsdev/camelot/issues/102
+4. Words that lie inside/outside the current column *x* ranges are then used to extend extend the current list of columns.
+
+5. Finally, a table is formed using the text rows' *y* ranges and column *x* ranges and words found on the page are assigned to the table's cells based on their *x* and *y* coordinates.
 
 .. _lattice:
 
@@ -39,7 +39,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
 
 1. Line segments are detected.
 
-.. image:: ../_static/png/geometry_line.png
+.. image:: ../_static/png/plot_line.png
     :height: 674
     :width: 1366
     :scale: 50%
@@ -49,7 +49,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
 
 .. _and: https://en.wikipedia.org/wiki/Logical_conjunction
 
-.. image:: ../_static/png/geometry_joint.png
+.. image:: ../_static/png/plot_joint.png
     :height: 674
     :width: 1366
     :scale: 50%
@@ -59,7 +59,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
 
 .. _or: https://en.wikipedia.org/wiki/Logical_disjunction
 
-.. image:: ../_static/png/geometry_contour.png
+.. image:: ../_static/png/plot_contour.png
     :height: 674
     :width: 1366
     :scale: 50%
@@ -75,7 +75,7 @@ Let's see how Lattice processes the second page of `this PDF`_, step-by-step.
 
 5. Spanning cells are detected using the line segments and line intersections.
 
-.. image:: ../_static/png/geometry_table.png
+.. image:: ../_static/png/plot_table.png
     :height: 674
     :width: 1366
     :scale: 50%

docs/user/install-deps.rst

@@ -0,0 +1,76 @@
+.. _install_deps:
+
+Installation of dependencies
+============================
+
+The dependencies `Tkinter`_ and `ghostscript`_ can be installed using your system's package manager. You can run one of the following, based on your OS.
+
+.. _Tkinter: https://wiki.python.org/moin/TkInter
+.. _ghostscript: https://www.ghostscript.com
+
+OS-specific instructions
+------------------------
+
+For Ubuntu
+^^^^^^^^^^
+::
+
+    $ apt install python-tk ghostscript
+
+Or for Python 3::
+
+    $ apt install python3-tk ghostscript
+
+For macOS
+^^^^^^^^^
+::
+
+    $ brew install tcl-tk ghostscript
+
+For Windows
+^^^^^^^^^^^
+
+For Tkinter, you can download the `ActiveTcl Community Edition`_ from ActiveState. For ghostscript, you can get the installer at the `ghostscript downloads page`_.
+
+After installing ghostscript, you'll need to reboot your system to make sure that the ghostscript executable's path is in the windows PATH environment variable. In case you don't want to reboot, you can manually add the ghostscript executable's path to the PATH variable, `as shown here`_.
+
+.. _ActiveTcl Community Edition: https://www.activestate.com/activetcl/downloads
+.. _ghostscript downloads page: https://www.ghostscript.com/download/gsdnld.html
+.. _as shown here: https://java.com/en/download/help/path.xml
+
+Checks to see if dependencies were installed correctly
+------------------------------------------------------
+
+You can do the following checks to see if the dependencies were installed correctly.
+
+For Tkinter
+^^^^^^^^^^^
+
+Launch Python, and then at the prompt, type::
+
+    >>> import Tkinter
+
+Or in Python 3::
+
+    >>> import tkinter
+
+If you have Tkinter, Python will not print an error message, and if not, you will see an ``ImportError``.
+
+For ghostscript
+^^^^^^^^^^^^^^^
+
+Run the following to check the ghostscript version.
+
+For Ubuntu/macOS::
+
+    $ gs -version
+
+For Windows::
+
+    C:\> gswin64c.exe -version
+
+Or for Windows 32-bit::
+
+    C:\> gswin32c.exe -version
+
+If you have ghostscript, you should see the ghostscript version and copyright information.

docs/user/install.rst

@@ -3,20 +3,15 @@
 Installation of Camelot
 =======================
 
-This part of the documentation covers how to install Camelot.
+This part of the documentation covers the steps to install Camelot.
 
 Using conda
 -----------
 
-The easiest way to install Camelot is to install it with `conda`_, which is the package manager that the `Anaconda`_ distribution is built upon.
+The easiest way to install Camelot is to install it with `conda`_, which is a package manager and environment management system for the `Anaconda`_ distribution.
+::
 
-First, let's add the `conda-forge`_ channel to conda's config::
+    $ conda install -c conda-forge camelot-py
-
-    $ conda config --add channels conda-forge
-
-Now, you can simply use conda to install Camelot::
-
-    $ conda install -c camelot-dev camelot-py
 
 .. note:: Camelot is available for Python 2.7, 3.5 and 3.6 on Linux, macOS and Windows. For Windows, you will need to install ghostscript which you can get from their `downloads page`_.
 
@@ -28,84 +23,17 @@ Now, you can simply use conda to install Camelot::
 Using pip
 ---------
 
-First, you'll need to install the dependencies, which include `Tkinter`_ and `ghostscript`_.
+After :ref:`installing the dependencies <install_deps>`, which include `Tkinter`_ and `ghostscript`_, you can simply use pip to install Camelot::
+
+    $ pip install camelot-py[cv]
 
 .. _Tkinter: https://wiki.python.org/moin/TkInter
 .. _ghostscript: https://www.ghostscript.com
 
-These can be installed using your system's package manager. You can run one of the following, based on your OS.
-
-For Ubuntu
-^^^^^^^^^^
-::
-
-    $ apt install python-tk ghostscript
-
-Or for Python 3::
-
-    $ apt install python3-tk ghostscript
-
-For macOS
-^^^^^^^^^
-::
-
-    $ brew install tcl-tk ghostscript
-
-For Windows
-^^^^^^^^^^^
-
-For Tkinter, you can download the `ActiveTcl Community Edition`_ from ActiveState. For ghostscript, you can get the installer at the `ghostscript downloads page`_.
-
-After installing ghostscript, you'll need to reboot your system to make sure that the ghostscript executable's path is in the windows PATH environment variable. In case you don't want to reboot, you can manually add the ghostscript executable's path to the PATH variable, `as shown here`_.
-
-.. _ActiveTcl Community Edition: https://www.activestate.com/activetcl/downloads
-.. _ghostscript downloads page: https://www.ghostscript.com/download/gsdnld.html
-.. _as shown here: https://java.com/en/download/help/path.xml
-
-----
-
-You can do the following checks to see if the dependencies were installed correctly.
-
-For Tkinter
-^^^^^^^^^^^
-
-Launch Python, and then at the prompt, type::
-
-    >>> import Tkinter
-
-Or in Python 3::
-
-    >>> import tkinter
-
-If you have Tkinter, Python will not print an error message, and if not, you will see an ``ImportError``.
-
-For ghostscript
-^^^^^^^^^^^^^^^
-
-Run the following to check the ghostscript version.
-
-For Ubuntu/macOS::
-
-    $ gs -version
-
-For Windows::
-
-    C:\> gswin64c.exe -version
-
-Or for Windows 32-bit::
-
-    C:\> gswin32c.exe -version
-
-If you have ghostscript, you should see the ghostscript version and copyright information.
-
-Finally, you can use pip to install Camelot::
-
-    $ pip install camelot-py[all]
-
 From the source code
 --------------------
 
-After `installing the dependencies`_, you can install from the source by:
+After :ref:`installing the dependencies <install_deps>`, you can install from the source by:
 
 1. Cloning the GitHub repository.
 ::
@@ -116,6 +44,4 @@ After `installing the dependencies`_, you can install from the source by:
 ::
 
     $ cd camelot
-    $ pip install ".[all]"
+    $ pip install ".[cv]"
-
-.. _installing the dependencies: https://camelot-py.readthedocs.io/en/master/user/install.html#using-pip

setup.cfg

@@ -2,5 +2,5 @@
 test=pytest
 
 [tool:pytest]
-addopts = --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot tests
+addopts = --verbose --cov-config .coveragerc --cov-report term --cov-report xml --cov=camelot --mpl
 python_files = tests/test_*.py

setup.py

@@ -15,7 +15,6 @@ with open('README.md', 'r') as f:
 
 requires = [
     'click>=6.7',
-    'matplotlib>=2.2.3',
     'numpy>=1.13.3',
     'openpyxl>=2.5.8',
     'pandas>=0.23.4',
@@ -23,17 +22,24 @@ requires = [
     'PyPDF2>=1.26.0'
 ]
 
-all_requires = [
+cv_requires = [
     'opencv-python>=3.4.2.17'
 ]
 
+plot_requires = [
+    'matplotlib>=2.2.3',
+]
+
 dev_requires = [
     'codecov>=2.0.15',
     'pytest>=3.8.0',
     'pytest-cov>=2.6.0',
+    'pytest-mpl>=0.10',
     'pytest-runner>=4.2',
     'Sphinx>=1.7.9'
 ]
+
+all_requires = cv_requires + plot_requires
 dev_requires = dev_requires + all_requires
 
 
@@ -51,7 +57,9 @@ def setup_package():
                     install_requires=requires,
                     extras_require={
                         'all': all_requires,
-                        'dev': dev_requires
+                        'cv': cv_requires,
+                        'dev': dev_requires,
+                        'plot': plot_requires
                     },
                     entry_points={
                         'console_scripts': [

tests/__init__.py

@@ -0,0 +1,2 @@
+import matplotlib
+matplotlib.use('agg')

tests/data.py

@@ -33,52 +33,138 @@ data_stream = [
     ["Nagaland", "2,368,724", "204,329", "226,400", "0", "2,799,453", "783,054", "3,582,507"],
     ["Odisha", "14,317,179", "2,552,292", "1,107,250", "0", "17,976,721", "451,438", "18,428,159"],
     ["Puducherry", "4,191,757", "52,249", "192,400", "0", "4,436,406", "2,173", "4,438,579"],
-    ["Punjab", "19,775,485", "2,208,343", "2,470,882", "0", "24,454,710", "1,436,522", "25,891,232"],
+    ["Punjab", "19,775,485", "2,208,343", "2,470,882", "0", "24,454,710", "1,436,522", "25,891,232"]
-    ["", "Health Sector Financing by Centre and States/UTs in India [2009-10 to 2012-13](Revised)                               P a g e  |23", "", "", "", "", "", ""]
 ]
 
 data_stream_table_rotated = [
-    ["", "", "Table 21  Current use of contraception by background characteristics\u2014Continued", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["Table 21  Current use of contraception by background characteristics\u2014Continued", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "", "", "", "", "", "Modern method", "", "", "", "", "", "", "Traditional method", "", "", "", ""],
+    ["", "", "", "", "", "Modern method", "", "", "", "", "", "", "Traditional method", "", "", "", ""],
-    ["", "", "", "Any", "", "", "", "", "", "", "Other", "Any", "", "", "", "Not", "", "Number"],
+    ["", "", "Any", "", "", "", "", "", "", "Other", "Any", "", "", "", "Not", "", "Number"],
-    ["", "", "Any", "modern", "Female", "Male", "", "", "", "Condom/", "modern", "traditional", "", "With-", "Folk", "currently", "", "of"],
+    ["", "Any", "modern", "Female", "Male", "", "", "", "Condom/", "modern", "traditional", "", "With-", "Folk", "currently", "", "of"],
-    ["", "Background characteristic", "method", "method", "sterilization", "sterilization", "Pill", "IUD", "Injectables", "Nirodh", "method", "method", "Rhythm", "drawal", "method", "using", "Total", "women"],
+    ["Background characteristic", "method", "method", "sterilization", "sterilization", "Pill", "IUD", "Injectables", "Nirodh", "method", "method", "Rhythm", "drawal", "method", "using", "Total", "women"],
-    ["", "Caste/tribe", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["Caste/tribe", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "Scheduled caste", "74.8", "55.8", "42.9", "0.9", "9.7", "0.0", "0.2", "2.2", "0.0", "19.0", "11.2", "7.4", "0.4", "25.2", "100.0", "1,363"],
+    ["Scheduled caste", "74.8", "55.8", "42.9", "0.9", "9.7", "0.0", "0.2", "2.2", "0.0", "19.0", "11.2", "7.4", "0.4", "25.2", "100.0", "1,363"],
-    ["", "Scheduled tribe", "59.3", "39.0", "26.8", "0.6", "6.4", "0.6", "1.2", "3.5", "0.0", "20.3", "10.4", "5.8", "4.1", "40.7", "100.0", "256"],
+    ["Scheduled tribe", "59.3", "39.0", "26.8", "0.6", "6.4", "0.6", "1.2", "3.5", "0.0", "20.3", "10.4", "5.8", "4.1", "40.7", "100.0", "256"],
-    ["", "Other backward class", "71.4", "51.1", "34.9", "0.0", "8.6", "1.4", "0.0", "6.2", "0.0", "20.4", "12.6", "7.8", "0.0", "28.6", "100.0", "211"],
+    ["Other backward class", "71.4", "51.1", "34.9", "0.0", "8.6", "1.4", "0.0", "6.2", "0.0", "20.4", "12.6", "7.8", "0.0", "28.6", "100.0", "211"],
-    ["", "Other", "71.1", "48.8", "28.2", "0.8", "13.3", "0.9", "0.3", "5.2", "0.1", "22.3", "12.9", "9.1", "0.3", "28.9", "100.0", "3,319"],
+    ["Other", "71.1", "48.8", "28.2", "0.8", "13.3", "0.9", "0.3", "5.2", "0.1", "22.3", "12.9", "9.1", "0.3", "28.9", "100.0", "3,319"],
-    ["", "Wealth index", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["Wealth index", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "Lowest", "64.5", "48.6", "34.3", "0.5", "10.5", "0.6", "0.7", "2.0", "0.0", "15.9", "9.9", "4.6", "1.4", "35.5", "100.0", "1,258"],
+    ["Lowest", "64.5", "48.6", "34.3", "0.5", "10.5", "0.6", "0.7", "2.0", "0.0", "15.9", "9.9", "4.6", "1.4", "35.5", "100.0", "1,258"],
-    ["", "Second", "68.5", "50.4", "36.2", "1.1", "11.4", "0.5", "0.1", "1.1", "0.0", "18.1", "11.2", "6.7", "0.2", "31.5", "100.0", "1,317"],
+    ["Second", "68.5", "50.4", "36.2", "1.1", "11.4", "0.5", "0.1", "1.1", "0.0", "18.1", "11.2", "6.7", "0.2", "31.5", "100.0", "1,317"],
-    ["", "Middle", "75.5", "52.8", "33.6", "0.6", "14.2", "0.4", "0.5", "3.4", "0.1", "22.7", "13.4", "8.9", "0.4", "24.5", "100.0", "1,018"],
+    ["Middle", "75.5", "52.8", "33.6", "0.6", "14.2", "0.4", "0.5", "3.4", "0.1", "22.7", "13.4", "8.9", "0.4", "24.5", "100.0", "1,018"],
-    ["", "Fourth", "73.9", "52.3", "32.0", "0.5", "12.5", "0.6", "0.2", "6.3", "0.2", "21.6", "11.5", "9.9", "0.2", "26.1", "100.0", "908"],
+    ["Fourth", "73.9", "52.3", "32.0", "0.5", "12.5", "0.6", "0.2", "6.3", "0.2", "21.6", "11.5", "9.9", "0.2", "26.1", "100.0", "908"],
-    ["", "Highest", "78.3", "44.4", "19.5", "1.0", "9.7", "1.4", "0.0", "12.7", "0.0", "33.8", "18.2", "15.6", "0.0", "21.7", "100.0", "733"],
+    ["Highest", "78.3", "44.4", "19.5", "1.0", "9.7", "1.4", "0.0", "12.7", "0.0", "33.8", "18.2", "15.6", "0.0", "21.7", "100.0", "733"],
-    ["", "Number of living children", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["Number of living children", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
-    ["", "No children", "25.1", "7.6", "0.3", "0.5", "2.0", "0.0",
+    ["No children", "25.1", "7.6", "0.3", "0.5", "2.0", "0.0",
     "0.0", "4.8", "0.0", "17.5", "9.0", "8.5", "0.0", "74.9", "100.0", "563"],
-    ["", "1 child", "66.5", "32.1", "3.7", "0.7", "20.1", "0.7", "0.1", "6.9", "0.0", "34.3", "18.9", "15.2", "0.3", "33.5", "100.0", "1,190"],
+    ["1 child", "66.5", "32.1", "3.7", "0.7", "20.1", "0.7", "0.1", "6.9", "0.0", "34.3", "18.9", "15.2", "0.3", "33.5", "100.0", "1,190"],
-    ["\x18\x18", "1 son", "66.8", "33.2", "4.1", "0.7", "21.1", "0.5", "0.3", "6.6", "0.0", "33.5", "21.2", "12.3", "0.0", "33.2", "100.0", "672"],
+    ["1 son", "66.8", "33.2", "4.1", "0.7", "21.1", "0.5", "0.3", "6.6", "0.0", "33.5", "21.2", "12.3", "0.0", "33.2", "100.0", "672"],
-    ["", "No sons", "66.1", "30.7", "3.1", "0.6", "18.8", "0.8", "0.0", "7.3", "0.0", "35.4", "15.8", "19.0", "0.6", "33.9", "100.0", "517"],
+    ["No sons", "66.1", "30.7", "3.1", "0.6", "18.8", "0.8", "0.0", "7.3", "0.0", "35.4", "15.8", "19.0", "0.6", "33.9", "100.0", "517"],
-    ["", "2 children", "81.6", "60.5", "41.8", "0.9", "11.6", "0.8", "0.3", "4.8", "0.2", "21.1", "12.2", "8.3", "0.6", "18.4", "100.0", "1,576"],
+    ["2 children", "81.6", "60.5", "41.8", "0.9", "11.6", "0.8", "0.3", "4.8", "0.2", "21.1", "12.2", "8.3", "0.6", "18.4", "100.0", "1,576"],
-    ["", "1 or more sons", "83.7", "64.2", "46.4", "0.9", "10.8", "0.8", "0.4", "4.8", "0.1", "19.5", "11.1", "7.6", "0.7", "16.3", "100.0", "1,268"],
+    ["1 or more sons", "83.7", "64.2", "46.4", "0.9", "10.8", "0.8", "0.4", "4.8", "0.1", "19.5", "11.1", "7.6", "0.7", "16.3", "100.0", "1,268"],
-    ["", "No sons", "73.2", "45.5", "23.2", "1.0", "15.1", "0.9", "0.0", "4.8", "0.5", "27.7", "16.8", "11.0", "0.0", "26.8", "100.0", "308"],
+    ["No sons", "73.2", "45.5", "23.2", "1.0", "15.1", "0.9", "0.0", "4.8", "0.5", "27.7", "16.8", "11.0", "0.0", "26.8", "100.0", "308"],
-    ["", "3 children", "83.9", "71.2", "57.7", "0.8", "9.8", "0.6", "0.5", "1.8", "0.0", "12.7", "8.7", "3.3", "0.8", "16.1", "100.0", "961"],
+    ["3 children", "83.9", "71.2", "57.7", "0.8", "9.8", "0.6", "0.5", "1.8", "0.0", "12.7", "8.7", "3.3", "0.8", "16.1", "100.0", "961"],
-    ["", "1 or more sons", "85.0", "73.2", "60.3", "0.9", "9.4", "0.5", "0.5", "1.6", "0.0", "11.8", "8.1", "3.0", "0.7", "15.0", "100.0", "860"],
+    ["1 or more sons", "85.0", "73.2", "60.3", "0.9", "9.4", "0.5", "0.5", "1.6", "0.0", "11.8", "8.1", "3.0", "0.7", "15.0", "100.0", "860"],
-    ["", "No sons", "74.7", "53.8", "35.3", "0.0", "13.7", "1.6", "0.0", "3.2", "0.0", "20.9", "13.4", "6.1", "1.5", "25.3", "100.0", "101"],
+    ["No sons", "74.7", "53.8", "35.3", "0.0", "13.7", "1.6", "0.0", "3.2", "0.0", "20.9", "13.4", "6.1", "1.5", "25.3", "100.0", "101"],
-    ["", "4+ children", "74.3", "58.1", "45.1", "0.6", "8.7", "0.6", "0.7", "2.4", "0.0", "16.1", "9.9", "5.4", "0.8", "25.7", "100.0", "944"],
+    ["4+ children", "74.3", "58.1", "45.1", "0.6", "8.7", "0.6", "0.7", "2.4", "0.0", "16.1", "9.9", "5.4", "0.8", "25.7", "100.0", "944"],
-    ["", "1 or more sons", "73.9", "58.2", "46.0", "0.7", "8.3", "0.7", "0.7", "1.9", "0.0", "15.7", "9.4", "5.5", "0.8", "26.1", "100.0", "901"],
+    ["1 or more sons", "73.9", "58.2", "46.0", "0.7", "8.3", "0.7", "0.7", "1.9", "0.0", "15.7", "9.4", "5.5", "0.8", "26.1", "100.0", "901"],
-    ["", "No sons", "(82.1)", "(57.3)", "(25.6)", "(0.0)", "(17.8)", "(0.0)", "(0.0)", "(13.9)", "(0.0)", "(24.8)", "(21.3)", "(3.5)", "(0.0)", "(17.9)", "100.0", "43"],
+    ["No sons", "(82.1)", "(57.3)", "(25.6)", "(0.0)", "(17.8)", "(0.0)", "(0.0)", "(13.9)", "(0.0)", "(24.8)", "(21.3)", "(3.5)", "(0.0)", "(17.9)", "100.0", "43"],
-    ["", "Total", "71.2", "49.9", "32.2",
+    ["Total", "71.2", "49.9", "32.2",
     "0.7", "11.7", "0.6", "0.3", "4.3", "0.1", "21.3", "12.3", "8.4", "0.5", "28.8", "100.0", "5,234"],
-    ["", "NFHS-2 (1998-99)", "66.6", "47.3", "32.0", "1.8", "9.2", "1.4", "na", "2.9", "na", "na", "8.7", "9.8", "na", "33.4", "100.0", "4,116"],
+    ["NFHS-2 (1998-99)", "66.6", "47.3", "32.0", "1.8", "9.2", "1.4", "na", "2.9", "na", "na", "8.7", "9.8", "na", "33.4", "100.0", "4,116"],
-    ["", "NFHS-1 (1992-93)", "57.7", "37.6", "26.5", "4.3", "3.6", "1.3", "0.1", "1.9", "na", "na", "11.3", "8.3", "na", "42.3", "100.0", "3,970"],
+    ["NFHS-1 (1992-93)", "57.7", "37.6", "26.5", "4.3", "3.6", "1.3", "0.1", "1.9", "na", "na", "11.3", "8.3", "na", "42.3", "100.0", "3,970"]
-    ["", "", "Note: If more than one method is used, only the most effective method is considered in this tabulation. Total includes women for whom caste/tribe was not known or is missing, who are", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+]
-    ["", "not shown separately.", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+
-    ["", "na = Not available", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+data_stream_two_tables_1 = [
-    ["", "", "ns = Not shown; see table 2b, footnote 1", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["[In thousands (11,062.6 represents 11,062,600) For year ending December 31. Based on Uniform Crime Reporting (UCR)", "", "", "", "", "", "", "", "", ""],
-    ["", "( ) Based on 25-49 unweighted cases.", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "", ""],
+    ["Program. Represents arrests reported (not charged) by 12,910 agencies with a total population of 247,526,916 as estimated", "", "", "", "", "", "", "", "", ""],
-    ["", "", "", "", "", "", "", "", "54", "", "", "", "", "", "", "", "", ""]
+    ["by the FBI. Some persons may be arrested more than once during a year, therefore, the data in this table, in some cases,", "", "", "", "", "", "", "", "", ""],
+    ["could represent multiple arrests of the same person. See text, this section and source]", "", "", "", "", "", "", "", "", ""],
+    ["", "", "Total", "", "", "Male", "", "", "Female", ""],
+    ["Offense charged", "", "Under 18", "18 years", "", "Under 18", "18 years", "", "Under 18", "18 years"],
+    ["", "Total", "years", "and over", "Total", "years", "and over", "Total", "years", "and over"],
+    ["Total   . . .  .  .  .  .  . .  . .  . .  . .  . .  . .  . .  . .  .  .", "11,062 .6", "1,540 .0", "9,522 .6", "8,263 .3", "1,071 .6", "7,191 .7", "2,799 .2", "468 .3", "2,330 .9"],
+    ["Violent crime  .  .  .  .  .  .  .  . .  . .  . .  . .  . .  .", "467 .9", "69 .1", "398 .8", "380 .2", "56 .5", "323 .7", "87 .7", "12 .6", "75 .2"],
+    ["Murder and nonnegligent", "", "", "", "", "", "", "", "", ""],
+    ["manslaughter . . . . . . . .. .. .. .. ..", "10.0", "0.9", "9.1", "9.0", "0.9", "8.1", "1.1", "–", "1.0"],
+    ["Forcible rape . . . . . . . .. .. .. .. .. .", "17.5", "2.6", "14.9", "17.2", "2.5", "14.7", "–", "–", "–"],
+    ["Robbery . . . .. .. . .. . ... . ... . ...", "102.1", "25.5", "76.6", "90.0", "22.9", "67.1", "12.1", "2.5", "9.5"],
+    ["Aggravated assault  . . . . . . . .. .. ..", "338.4", "40.1", "298.3", "264.0", "30.2", "233.8", "74.4", "9.9", "64.5"],
+    ["Property crime  .  .  .  . .  . .  .  . .  .  . . .  .  .  .", "1,396 .4", "338 .7", "1,057 .7", "875 .9", "210 .8", "665 .1", "608 .2", "127 .9", "392 .6"],
+    ["Burglary . .. . . . . .. ... .... .... ..", "240.9", "60.3", "180.6", "205.0", "53.4", "151.7", "35.9", "6.9", "29.0"],
+    ["Larceny-theft . . . . . . . .. .. .. .. .. .", "1,080.1", "258.1", "822.0", "608.8", "140.5", "468.3", "471.3", "117.6", "353.6"],
+    ["Motor vehicle theft . . . . .. .. . .... .", "65.6", "16.0", "49.6", "53.9", "13.3", "40.7", "11.7", "2.7", "8.9"],
+    ["Arson .. . . . .. . ... .... .... .... .", "9.8", "4.3", "5.5", "8.1", "3.7", "4.4", "1.7", "0.6", "1.1"],
+    ["Other assaults .. . . . . .. . ... . ... ..", "1,061.3", "175.3", "886.1", "785.4", "115.4", "670.0", "276.0", "59.9", "216.1"],
+    ["Forgery and counterfeiting .. . . . . . ..", "68.9", "1.7", "67.2", "42.9", "1.2", "41.7", "26.0", "0.5", "25.5"],
+    ["Fraud .... .. . . .. ... .... .... ....", "173.7", "5.1", "168.5", "98.4", "3.3", "95.0", "75.3", "1.8", "73.5"],
+    ["Embezzlement . . .. . . . .. . ... . ....", "14.6", "–", "14.1", "7.2", "–", "6.9", "7.4", "–", "7.2"],
+    ["Stolen property 1  . . . . . . .. . .. .. ...", "84.3", "15.1", "69.2", "66.7", "12.2", "54.5", "17.6", "2.8", "14.7"],
+    ["Vandalism  . . . . . . . .. .. .. .. .. ....", "217.4", "72.7", "144.7", "178.1", "62.8", "115.3", "39.3", "9.9", "29.4"],
+    ["Weapons; carrying, possessing, etc. .", "132.9", "27.1", "105.8", "122.1", "24.3", "97.8", "10.8", "2.8", "8.0"],
+    ["Prostitution and commercialized vice",
+    "56.9", "1.1", "55.8", "17.3", "–", "17.1", "39.6", "0.8", "38.7"],
+    ["Sex offenses 2  . . . . .. . . . .. .. .. . ..", "61.5", "10.7", "50.7", "56.1", "9.6", "46.5", "5.4", "1.1", "4.3"],
+    ["Drug abuse violations  . . . . . . . .. ...", "1,333.0", "136.6", "1,196.4", "1,084.3", "115.2", "969.1", "248.7", "21.4", "227.3"],
+    ["Gambling .. . . . . .. ... . ... . ... ...", "8.2", "1.4", "6.8", "7.2", "1.4", "5.9", "0.9", "–", "0.9"],
+    ["Offenses against the family and", "", "", "", "", "", "", "", "", ""],
+    ["children . . . .. . . .. .. .. .. .. .. . ..", "92.4", "3.7", "88.7", "68.9", "2.4", "66.6", "23.4", "1.3", "22.1"],
+    ["Driving under the influence . . . . . .. .", "1,158.5", "109.2", "1,147.5", "895.8", "8.2", "887.6", "262.7", "2.7", "260.0"],
+    ["Liquor laws  . . . . . . . .. .. .. .. .. .. .", "48.2", "90.2", "368.0", "326.8", "55.4", "271.4",
+    "131.4", "34.7", "96.6"],
+    ["Drunkenness . . .. . . . .. . ... . ... ..", "488.1", "11.4", "476.8", "406.8", "8.5", "398.3", "81.3", "2.9", "78.4"],
+    ["Disorderly conduct . .. . . . . . .. .. .. .", "529.5", "136.1", "393.3", "387.1", "90.8", "296.2", "142.4", "45.3", "97.1"],
+    ["Vagrancy . . . .. . . . ... .... .... ...", "26.6", "2.2", "24.4", "20.9", "1.6", "19.3", "5.7", "0.6", "5.1"],
+    ["All other offenses (except traffic) . . ..", "306.1", "263.4", "2,800.8", "2,337.1", "194.2", "2,142.9", "727.0", "69.2", "657.9"],
+    ["Suspicion . . . .. . . .. .. .. .. .. .. . ..", "1.6", "–", "1.4", "1.2", "–", "1.0", "–", "–", "–"],
+    ["Curfew and loitering law violations  ..", "91.0", "91.0", "(X)", "63.1", "63.1", "(X)", "28.0", "28.0", "(X)"],
+    ["Runaways  . . . . . . . .. .. .. .. .. ....", "75.8", "75.8", "(X)", "34.0", "34.0", "(X)", "41.8", "41.8", "(X)"],
+    ["", "– Represents zero. X Not applicable. 1 Buying, receiving, possessing stolen property. 2 Except forcible rape and prostitution.", "", "", "", "", "", "", "", ""],
+    ["", "Source: U.S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports, Arrests Master Files.", "", "", "", "", "", "", "", ""]
+]
+
+data_stream_two_tables_2 = [
+    ["", "Source: U.S. Department of Justice, Federal Bureau of Investigation, Uniform Crime Reports, Arrests Master Files.", "", "", "", ""],
+    ["Table 325. Arrests by Race: 2009", "", "", "", "", ""],
+    ["[Based on Uniform Crime Reporting (UCR) Program. Represents arrests reported (not charged) by 12,371 agencies", "", "", "", "", ""],
+    ["with a total population of 239,839,971 as estimated by the FBI. See headnote, Table 324]", "", "", "", "", ""],
+    ["", "", "", "", "American", ""],
+    ["Offense charged", "", "", "",
+    "Indian/Alaskan", "Asian Pacific"],
+    ["", "Total", "White", "Black", "Native", "Islander"],
+    ["Total  . . . . .  . .  .  . .  .  . . .  .  . . .  .  . .  . . .  .  . . . . .  . .  . .  .", "10,690,561", "7,389,208", "3,027,153", "150,544", "123,656"],
+    ["Violent crime  .  .  .  .  .  .  .  . .  . .  . .  . .  . . . .  . .  . . . . . .  .", "456,965", "268,346", "177,766", "5,608", "5,245"],
+    ["Murder and nonnegligent manslaughter . .. ... .", "9,739", "4,741", "4,801", "100", "97"],
+    ["Forcible rape . . . . . . . .. .. .. .. .... .. ...... .", "16,362", "10,644", "5,319", "169", "230"],
+    ["Robbery . . . . .. . . . ... . ... . .... .... .... . . .", "100,496", "43,039", "55,742", "726", "989"],
+    ["Aggravated assault  . . . . . . . .. .. ...... .. ....", "330,368", "209,922", "111,904", "4,613", "3,929"],
+    ["Property crime  .  .  .  .  . .  .  .  .  . . .  .  . . .  . . . . .  . . .  . . .", "1,364,409", "922,139", "406,382", "17,599", "18,289"],
+    ["Burglary . . .. . . . .. . .... .... .... .... ... . . .", "234,551", "155,994", "74,419", "2,021", "2,117"],
+    ["Larceny-theft . . . . . . . .. .. .. .. .... .. ...... .", "1,056,473", "719,983", "306,625", "14,646", "15,219"],
+    ["Motor vehicle theft . . . . . .. ... . ... ..... ... ..", "63,919", "39,077", "23,184", "817", "841"],
+    ["Arson .. . . .. .. .. ... .... .... .... .... . . . . .", "9,466", "7,085", "2,154", "115", "112"],
+    ["Other assaults .. . . . . . ... . ... . ... ..... ... ..", "1,032,502", "672,865", "332,435", "15,127", "12,075"],
+    ["Forgery and counterfeiting .. . . . . . ... ..... .. ..", "67,054", "44,730", "21,251", "345", "728"],
+    ["Fraud ... . . . . .. .. .. .. .. .. .. .. .. .... . . . . . .", "161,233", "108,032", "50,367", "1,315", "1,519"],
+    ["Embezzlement . . . .. . . . ... . ... . .... ... .....", "13,960", "9,208", "4,429", "75", "248"],
+    ["Stolen property; buying, receiving, possessing .. .", "82,714", "51,953", "29,357", "662", "742"],
+    ["Vandalism  . . . . . . . .. .. .. .. .. .. .... .. ..... .", "212,173", "157,723", "48,746", "3,352", "2,352"],
+    ["Weapons—carrying, possessing, etc. .. .. ... .. .", "130,503", "74,942", "53,441", "951", "1,169"],
+    ["Prostitution and commercialized vice  . ... .. .. ..", "56,560", "31,699", "23,021", "427", "1,413"],
+    ["Sex offenses 1 . . . . . . . .. .. .. .. .... .. ...... .", "60,175", "44,240", "14,347", "715", "873"],
+    ["Drug abuse violations  . . . . . . . .. . ..... .. .....", "1,301,629", "845,974", "437,623", "8,588", "9,444"],
+    ["Gambling . . . . .. . . . ... . ... . .. ... . ...... .. .", "8,046", "2,290", "5,518", "27", "211"],
+    ["Offenses against the family and children ... .. .. .", "87,232", "58,068", "26,850", "1,690", "624"],
+    ["Driving under the influence . . . . . . .. ... ...... .", "1,105,401", "954,444", "121,594", "14,903", "14,460"],
+    ["Liquor laws  . . . . . . . .. .. .. .. .. . ..... .. .....", "444,087", "373,189", "50,431", "14,876", "5,591"],
+    ["Drunkenness . .. . . . . . ... . ... . ..... . .......", "469,958", "387,542", "71,020", "8,552", "2,844"],
+    ["Disorderly conduct . . .. . . . . .. .. . ..... .. .....", "515,689", "326,563", "176,169", "8,783", "4,174"],
+    ["Vagrancy . . .. .. . . .. ... .... .... .... .... . . .", "26,347", "14,581", "11,031", "543", "192"],
+    ["All other offenses (except traffic) . .. .. .. ..... ..", "2,929,217", "1,937,221", "911,670", "43,880", "36,446"],
+    ["Suspicion . . .. . . . .. .. .. .. .. .. .. ...... .. . . .", "1,513", "677", "828", "1", "7"],
+    ["Curfew and loitering law violations  . .. ... .. ....", "89,578", "54,439", "33,207", "872", "1,060"],
+    ["Runaways  . . . . . . . .. .. .. .. .. .. .... .. ..... .", "73,616", "48,343", "19,670", "1,653", "3,950"],
+    ["1 Except forcible rape and prostitution.", "", "", "", "", ""],
+    ["", "Source: U.S. Department of Justice, Federal Bureau of Investigation, “Crime in the United States, Arrests,” September 2010,", "", "", "", ""]
 ]
 
 data_stream_table_areas = [
@@ -187,14 +273,10 @@ data_stream_split_text = [
     ["", "", "", "", "1522 WEST LINDSEY", "", "", "", "", ""],
     ["632575", "BAW", "BASHU LEGENDS", "HYH HE CHUANG LLC", "STREET", "NORMAN", "OK", "73069", "-", "2014/07/21"],
     ["", "", "", "DEEP FORK HOLDINGS", "", "", "", "", "", ""],
-    ["543149", "BAW", "BEDLAM BAR-B-Q", "LLC", "610 NORTHEAST 50TH", "OKLAHOMA CITY", "OK", "73105", "(405) 528-7427", "2015/02/23"],
+    ["543149", "BAW", "BEDLAM BAR-B-Q", "LLC", "610 NORTHEAST 50TH", "OKLAHOMA CITY", "OK", "73105", "(405) 528-7427", "2015/02/23"]
-    ["", "", "", "", "Page 1 of 151", "", "", "", "", ""]
 ]
 
 data_stream_flag_size = [
-    ["", "TABLE 125: STATE-WISE COMPOSITION OF OUTSTANDING LIABILITIES - 1997 <s>(Contd.)</s>", "", "", "", "", "", "", "", "", ""],
-    ["", "", "", "", "(As at end-March)", "", "", "", "", "", ""],
-    ["", "", "", "", "", "", "", "", "", "", "(<s>`</s> Billion)"],
     ["States", "Total", "Market", "NSSF", "WMA", "Loans", "Loans", "Loans", "Loans", "Loans", "Loans"],
     ["", "Internal", "Loans", "", "from", "from", "from", "from", "from", "from SBI", "from"],
     ["", "Debt", "", "", "RBI", "Banks", "LIC", "GIC", "NABARD", "& Other", "NCDC"],
@@ -230,9 +312,7 @@ data_stream_flag_size = [
     ["Uttar Pradesh", "80.62", "74.89", "-", "4.34", "1.34", "0.6", "-", "-0.21", "0.18", "0.03"],
     ["West Bengal", "34.23", "32.19", "-", "-", "2.04", "0.77", "-", "0.06", "-", "0.51"],
     ["NCT Delhi", "-", "-", "-", "-", "-", "-", "-", "-", "-", "-"],
-    ["ALL STATES", "513.38", "436.02", "-", "25.57", "51.06", "14.18", "-", "8.21", "11.83", "11.08"],
+    ["ALL STATES", "513.38", "436.02", "-", "25.57", "51.06", "14.18", "-", "8.21", "11.83", "11.08"]
-    ["<s>2</s> Includes `2.45 crore outstanding under “Market Loan Suspense”.", "", "", "", "", "", "", "", "", "", ""],
-    ["", "", "", "", "445", "", "", "", "", "", ""]
 ]
 
 data_lattice = [
@@ -261,6 +341,38 @@ data_lattice_table_rotated = [
     ["Pooled", "38742", "53618", "60601", "86898", "4459", "21918", "27041", "14312", "18519"]
 ]
 
+data_lattice_two_tables_1 = [
+    ["State", "n", "Literacy Status", "", "", "", "", ""],
+    ["", "", "Illiterate", "Read & Write", "1-4 std.", "5-8 std.", "9-12 std.", "College"],
+    ["Kerala", "2400", "7.2", "0.5", "25.3", "20.1", "41.5", "5.5"],
+    ["Tamil Nadu", "2400", "21.4", "2.3", "8.8", "35.5", "25.8", "6.2"],
+    ["Karnataka", "2399", "37.4", "2.8", "12.5", "18.3", "23.1", "5.8"],
+    ["Andhra Pradesh", "2400", "54.0", "1.7", "8.4", "13.2", "18.8", "3.9"],
+    ["Maharashtra", "2400", "22.0", "0.9", "17.3", "20.3", "32.6", "7.0"],
+    ["Gujarat", "2390", "28.6", "0.1", "14.4", "23.1", "26.9", "6.8"],
+    ["Madhya Pradesh", "2402", "29.1", "3.4", "8.5", "35.1", "13.3", "10.6"],
+    ["Orissa", "2405", "33.2", "1.0", "10.4", "25.7", "21.2", "8.5"],
+    ["West Bengal", "2293", "41.7", "4.4", "13.2", "17.1", "21.2", "2.4"],
+    ["Uttar Pradesh", "2400", "35.3", "2.1", "4.5", "23.3", "27.1", "7.6"],
+    ["Pooled", "23889", "30.9", "1.9", "12.3", "23.2", "25.2", "6.4"]
+]
+
+data_lattice_two_tables_2 = [
+    ["State", "n", "Literacy Status", "", "", "", "", ""],
+    ["", "", "Illiterate", "Read & Write", "1-4 std.", "5-8 std.", "9-12 std.", "College"],
+    ["Kerala", "2400", "8.8", "0.3", "20.1", "17.0", "45.6", "8.2"],
+    ["Tamil Nadu", "2400", "29.9", "1.5", "8.5", "33.1", "22.3", "4.8"],
+    ["Karnataka", "2399", "47.9", "2.5", "10.2", "18.8", "18.4", "2.3"],
+    ["Andhra Pradesh", "2400", "66.4", "0.7", "6.8", "12.9", "11.4", "1.8"],
+    ["Maharashtra", "2400", "41.3", "0.6", "14.1", "20.1", "21.6", "2.2"],
+    ["Gujarat", "2390", "57.6", "0.1", "10.3", "16.5", "12.9", "2.7"],
+    ["Madhya Pradesh", "2402", "58.7", "2.2", "6.6", "24.1", "5.3", "3.0"],
+    ["Orissa", "2405", "50.0", "0.9", "8.1", "21.9", "15.1", "4.0"],
+    ["West Bengal", "2293", "49.1", "4.8", "11.2", "16.8", "17.1", "1.1"],
+    ["Uttar Pradesh", "2400", "67.3", "2.0", "3.1", "17.2", "7.7", "2.7"],
+    ["Pooled", "23889", "47.7", "1.5", "9.9", "19.9", "17.8", "3.3"]
+]
+
 data_lattice_table_areas = [
     ["", "", "", "", "", "", "", "", ""],
     ["State", "n", "Literacy Status", "", "", "", "", "", ""],

tests/test_common.py

@@ -56,6 +56,17 @@ def test_stream_table_rotated():
     assert df.equals(tables[0].df)
 
 
+def test_stream_two_tables():
+    df1 = pd.DataFrame(data_stream_two_tables_1)
+    df2 = pd.DataFrame(data_stream_two_tables_2)
+
+    filename = os.path.join(testdir, "tabula/12s0324.pdf")
+    tables = camelot.read_pdf(filename, flavor='stream')
+    assert len(tables) == 2
+    assert df1.equals(tables[0].df)
+    assert df2.equals(tables[1].df)
+
+
 def test_stream_table_areas():
     df = pd.DataFrame(data_stream_table_areas)
 
@@ -111,6 +122,17 @@ def test_lattice_table_rotated():
     assert df.equals(tables[0].df)
 
 
+def test_lattice_two_tables():
+    df1 = pd.DataFrame(data_lattice_two_tables_1)
+    df2 = pd.DataFrame(data_lattice_two_tables_2)
+
+    filename = os.path.join(testdir, "twotables_2.pdf")
+    tables = camelot.read_pdf(filename)
+    assert len(tables) == 2
+    assert df1.equals(tables[0].df)
+    assert df2.equals(tables[1].df)
+
+
 def test_lattice_table_areas():
     df = pd.DataFrame(data_lattice_table_areas)
 

tests/test_plotting.py

@@ -0,0 +1,51 @@
+# -*- coding: utf-8 -*-
+
+import os
+
+import pytest
+
+import camelot
+
+
+testdir = os.path.dirname(os.path.abspath(__file__))
+testdir = os.path.join(testdir, "files")
+
+
+@pytest.mark.mpl_image_compare(
+    baseline_dir="files/baseline_plots", remove_text=True)
+def test_text_plot():
+    filename = os.path.join(testdir, "foo.pdf")
+    tables = camelot.read_pdf(filename)
+    return camelot.plot(tables[0], kind='text')
+
+
+@pytest.mark.mpl_image_compare(
+    baseline_dir="files/baseline_plots", remove_text=True)
+def test_grid_plot():
+    filename = os.path.join(testdir, "foo.pdf")
+    tables = camelot.read_pdf(filename)
+    return camelot.plot(tables[0], kind='grid')
+
+
+@pytest.mark.mpl_image_compare(
+    baseline_dir="files/baseline_plots", remove_text=True)
+def test_contour_plot():
+    filename = os.path.join(testdir, "foo.pdf")
+    tables = camelot.read_pdf(filename)
+    return camelot.plot(tables[0], kind='contour')
+
+
+@pytest.mark.mpl_image_compare(
+    baseline_dir="files/baseline_plots", remove_text=True)
+def test_line_plot():
+    filename = os.path.join(testdir, "foo.pdf")
+    tables = camelot.read_pdf(filename)
+    return camelot.plot(tables[0], kind='line')
+
+
+@pytest.mark.mpl_image_compare(
+    baseline_dir="files/baseline_plots", remove_text=True)
+def test_joint_plot():
+    filename = os.path.join(testdir, "foo.pdf")
+    tables = camelot.read_pdf(filename)
+    return camelot.plot(tables[0], kind='joint')