table.py

"""
Copyright (C) 2023 Artifex Software, Inc.

This file is part of PyMuPDF.

PyMuPDF is free software: you can redistribute it and/or modify it under the
terms of the GNU Affero General Public License as published by the Free
Software Foundation, either version 3 of the License, or (at your option)
any later version.

PyMuPDF is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS
FOR A PARTICULAR PURPOSE. See the GNU Affero General Public License for more
details.

You should have received a copy of the GNU Affero General Public License
along with MuPDF. If not, see <https://www.gnu.org/licenses/agpl-3.0.en.html>

Alternative licensing terms are available from the licensor.
For commercial licensing, see <https://www.artifex.com/> or contact
Artifex Software, Inc., 39 Mesa Street, Suite 108A, San Francisco,
CA 94129, USA, for further information.

---------------------------------------------------------------------
Portions of this code have been ported from pdfplumber, see
https://pypi.org/project/pdfplumber/.

The ported code is under the following MIT license:

---------------------------------------------------------------------
The MIT License (MIT)

Copyright (c) 2015, Jeremy Singer-Vine

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
---------------------------------------------------------------------
Also see here: https://github.com/jsvine/pdfplumber/blob/stable/LICENSE.txt
---------------------------------------------------------------------

The porting mainly pertains to files "table.py" and relevant parts of
"utils/text.py" within pdfplumber's repository on Github.
With respect to "text.py", we have removed functions or features that are not
used by table processing. Examples are:

* the text search function
* simple text extraction
* text extraction by lines

Original pdfplumber code does neither detect, nor identify table headers.
This PyMuPDF port adds respective code to the 'Table' class as method '_get_header'.
This is implemented as new class TableHeader with the properties:
* bbox: A tuple for the header's bbox
* cells: A tuple for each bbox of a column header
* names: A list of strings with column header text
* external: A bool indicating whether the header is outside the table cells.

"""

import inspect
import itertools
import string
import html
from collections.abc import Sequence
from dataclasses import dataclass
from operator import itemgetter

# -------------------------------------------------------------------
# Start of PyMuPDF interface code
# -------------------------------------------------------------------
from . import (
    Rect,
    Matrix,
    TEXTFLAGS_TEXT,
    TOOLS,
    EMPTY_RECT,
    sRGB_to_pdf,
    Point,
    message,
)

EDGES = []  # vector graphics from PyMuPDF
CHARS = []  # text characters from PyMuPDF
TEXTPAGE = None
white_spaces = set(string.whitespace)  # for checking white space only cells
# -------------------------------------------------------------------
# End of PyMuPDF interface code
# -------------------------------------------------------------------


class UnsetFloat(float):
    pass


NON_NEGATIVE_SETTINGS = [
    "snap_tolerance",
    "snap_x_tolerance",
    "snap_y_tolerance",
    "join_tolerance",
    "join_x_tolerance",
    "join_y_tolerance",
    "edge_min_length",
    "min_words_vertical",
    "min_words_horizontal",
    "intersection_tolerance",
    "intersection_x_tolerance",
    "intersection_y_tolerance",
]


TABLE_STRATEGIES = ["lines", "lines_strict", "text", "explicit"]
UNSET = UnsetFloat(0)
DEFAULT_SNAP_TOLERANCE = 3
DEFAULT_JOIN_TOLERANCE = 3
DEFAULT_MIN_WORDS_VERTICAL = 3
DEFAULT_MIN_WORDS_HORIZONTAL = 1
DEFAULT_X_TOLERANCE = 3
DEFAULT_Y_TOLERANCE = 3
DEFAULT_X_DENSITY = 7.25
DEFAULT_Y_DENSITY = 13
bbox_getter = itemgetter("x0", "top", "x1", "bottom")


LIGATURES = {
    "ff": "ff",
    "ffi": "ffi",
    "ffl": "ffl",
    "fi": "fi",
    "fl": "fl",
    "st": "st",
    "ſt": "st",
}


def to_list(collection) -> list:
    if isinstance(collection, list):
        return collection
    elif isinstance(collection, Sequence):
        return list(collection)
    elif hasattr(collection, "to_dict"):
        res = collection.to_dict("records")  # pragma: nocover
        return res
    else:
        return list(collection)


class TextMap:
    """
    A TextMap maps each unicode character in the text to an individual `char`
    object (or, in the case of layout-implied whitespace, `None`).
    """

    def __init__(self, tuples=None) -> None:
        self.tuples = tuples
        self.as_string = "".join(map(itemgetter(0), tuples))

    def match_to_dict(
        self,
        m,
        main_group: int = 0,
        return_groups: bool = True,
        return_chars: bool = True,
    ) -> dict:
        subset = self.tuples[m.start(main_group) : m.end(main_group)]
        chars = [c for (text, c) in subset if c is not None]
        x0, top, x1, bottom = objects_to_bbox(chars)

        result = {
            "text": m.group(main_group),
            "x0": x0,
            "top": top,
            "x1": x1,
            "bottom": bottom,
        }

        if return_groups:
            result["groups"] = m.groups()

        if return_chars:
            result["chars"] = chars

        return result


class WordMap:
    """
    A WordMap maps words->chars.
    """

    def __init__(self, tuples) -> None:
        self.tuples = tuples

    def to_textmap(
        self,
        layout: bool = False,
        layout_width=0,
        layout_height=0,
        layout_width_chars: int = 0,
        layout_height_chars: int = 0,
        x_density=DEFAULT_X_DENSITY,
        y_density=DEFAULT_Y_DENSITY,
        x_shift=0,
        y_shift=0,
        y_tolerance=DEFAULT_Y_TOLERANCE,
        use_text_flow: bool = False,
        presorted: bool = False,
        expand_ligatures: bool = True,
    ) -> TextMap:
        """
        Given a list of (word, chars) tuples (i.e., a WordMap), return a list of
        (char-text, char) tuples (i.e., a TextMap) that can be used to mimic the
        structural layout of the text on the page(s), using the following approach:

        - Sort the words by (doctop, x0) if not already sorted.

        - Calculate the initial doctop for the starting page.

        - Cluster the words by doctop (taking `y_tolerance` into account), and
          iterate through them.

        - For each cluster, calculate the distance between that doctop and the
          initial doctop, in points, minus `y_shift`. Divide that distance by
          `y_density` to calculate the minimum number of newlines that should come
          before this cluster. Append that number of newlines *minus* the number of
          newlines already appended, with a minimum of one.

        - Then for each cluster, iterate through each word in it. Divide each
          word's x0, minus `x_shift`, by `x_density` to calculate the minimum
          number of characters that should come before this cluster.  Append that
          number of spaces *minus* the number of characters and spaces already
          appended, with a minimum of one. Then append the word's text.

        - At the termination of each line, add more spaces if necessary to
          mimic `layout_width`.

        - Finally, add newlines to the end if necessary to mimic to
          `layout_height`.

        Note: This approach currently works best for horizontal, left-to-right
        text, but will display all words regardless of orientation. There is room
        for improvement in better supporting right-to-left text, as well as
        vertical text.
        """
        _textmap = []

        if not len(self.tuples):
            return TextMap(_textmap)

        expansions = LIGATURES if expand_ligatures else {}

        if layout:
            if layout_width_chars:
                if layout_width:
                    raise ValueError(
                        "`layout_width` and `layout_width_chars` cannot both be set."
                    )
            else:
                layout_width_chars = int(round(layout_width / x_density))

            if layout_height_chars:
                if layout_height:
                    raise ValueError(
                        "`layout_height` and `layout_height_chars` cannot both be set."
                    )
            else:
                layout_height_chars = int(round(layout_height / y_density))

            blank_line = [(" ", None)] * layout_width_chars
        else:
            blank_line = []

        num_newlines = 0

        words_sorted_doctop = (
            self.tuples
            if presorted or use_text_flow
            else sorted(self.tuples, key=lambda x: float(x[0]["doctop"]))
        )

        first_word = words_sorted_doctop[0][0]
        doctop_start = first_word["doctop"] - first_word["top"]

        for i, ws in enumerate(
            cluster_objects(
                words_sorted_doctop, lambda x: float(x[0]["doctop"]), y_tolerance
            )
        ):
            y_dist = (
                (ws[0][0]["doctop"] - (doctop_start + y_shift)) / y_density
                if layout
                else 0
            )
            num_newlines_prepend = max(
                # At least one newline, unless this iis the first line
                int(i > 0),
                # ... or as many as needed to get the imputed "distance" from the top
                round(y_dist) - num_newlines,
            )

            for i in range(num_newlines_prepend):
                if not len(_textmap) or _textmap[-1][0] == "\n":
                    _textmap += blank_line
                _textmap.append(("\n", None))

            num_newlines += num_newlines_prepend

            line_len = 0

            line_words_sorted_x0 = (
                ws
                if presorted or use_text_flow
                else sorted(ws, key=lambda x: float(x[0]["x0"]))
            )

            for word, chars in line_words_sorted_x0:
                x_dist = (word["x0"] - x_shift) / x_density if layout else 0
                num_spaces_prepend = max(min(1, line_len), round(x_dist) - line_len)
                _textmap += [(" ", None)] * num_spaces_prepend
                line_len += num_spaces_prepend

                for c in chars:
                    letters = expansions.get(c["text"], c["text"])
                    for letter in letters:
                        _textmap.append((letter, c))
                        line_len += 1

            # Append spaces at end of line
            if layout:
                _textmap += [(" ", None)] * (layout_width_chars - line_len)

        # Append blank lines at end of text
        if layout:
            num_newlines_append = layout_height_chars - (num_newlines + 1)
            for i in range(num_newlines_append):
                if i > 0:
                    _textmap += blank_line
                _textmap.append(("\n", None))

            # Remove terminal newline
            if _textmap[-1] == ("\n", None):
                _textmap = _textmap[:-1]

        return TextMap(_textmap)


class WordExtractor:
    def __init__(
        self,
        x_tolerance=DEFAULT_X_TOLERANCE,
        y_tolerance=DEFAULT_Y_TOLERANCE,
        keep_blank_chars: bool = False,
        use_text_flow=False,
        horizontal_ltr=True,  # Should words be read left-to-right?
        vertical_ttb=False,  # Should vertical words be read top-to-bottom?
        extra_attrs=None,
        split_at_punctuation=False,
        expand_ligatures=True,
    ):
        self.x_tolerance = x_tolerance
        self.y_tolerance = y_tolerance
        self.keep_blank_chars = keep_blank_chars
        self.use_text_flow = use_text_flow
        self.horizontal_ltr = horizontal_ltr
        self.vertical_ttb = vertical_ttb
        self.extra_attrs = [] if extra_attrs is None else extra_attrs

        # Note: string.punctuation = '!"#$%&\'()*+,-./:;<=>?@[\\]^_`{|}~'
        self.split_at_punctuation = (
            string.punctuation
            if split_at_punctuation is True
            else (split_at_punctuation or "")
        )

        self.expansions = LIGATURES if expand_ligatures else {}

    def merge_chars(self, ordered_chars: list):
        x0, top, x1, bottom = objects_to_bbox(ordered_chars)
        doctop_adj = ordered_chars[0]["doctop"] - ordered_chars[0]["top"]
        upright = ordered_chars[0]["upright"]
        direction = 1 if (self.horizontal_ltr if upright else self.vertical_ttb) else -1

        matrix = ordered_chars[0]["matrix"]

        rotation = 0
        if not upright and matrix[1] < 0:
            ordered_chars = reversed(ordered_chars)
            rotation = 270

        if matrix[0] < 0 and matrix[3] < 0:
            rotation = 180
        elif matrix[1] > 0:
            rotation = 90

        word = {
            "text": "".join(
                self.expansions.get(c["text"], c["text"]) for c in ordered_chars
            ),
            "x0": x0,
            "x1": x1,
            "top": top,
            "doctop": top + doctop_adj,
            "bottom": bottom,
            "upright": upright,
            "direction": direction,
            "rotation": rotation,
        }

        for key in self.extra_attrs:
            word[key] = ordered_chars[0][key]

        return word

    def char_begins_new_word(
        self,
        prev_char,
        curr_char,
    ) -> bool:
        """This method takes several factors into account to determine if
        `curr_char` represents the beginning of a new word:

        - Whether the text is "upright" (i.e., non-rotated)
        - Whether the user has specified that horizontal text runs
          left-to-right (default) or right-to-left, as represented by
          self.horizontal_ltr
        - Whether the user has specified that vertical text the text runs
          top-to-bottom (default) or bottom-to-top, as represented by
          self.vertical_ttb
        - The x0, top, x1, and bottom attributes of prev_char and
          curr_char
        - The self.x_tolerance and self.y_tolerance settings. Note: In
          this case, x/y refer to those directions for non-rotated text.
          For vertical text, they are flipped. A more accurate terminology
          might be "*intra*line character distance tolerance" and
          "*inter*line character distance tolerance"

        An important note: The *intra*line distance is measured from the
        *end* of the previous character to the *beginning* of the current
        character, while the *inter*line distance is measured from the
        *top* of the previous character to the *top* of the next
        character. The reasons for this are partly repository-historical,
        and partly logical, as successive text lines' bounding boxes often
        overlap slightly (and we don't want that overlap to be interpreted
        as the two lines being the same line).

        The upright-ness of the character determines the attributes to
        compare, while horizontal_ltr/vertical_ttb determine the direction
        of the comparison.
        """

        # Note: Due to the grouping step earlier in the process,
        # curr_char["upright"] will always equal prev_char["upright"].
        if curr_char["upright"]:
            x = self.x_tolerance
            y = self.y_tolerance
            ay = prev_char["top"]
            cy = curr_char["top"]
            if self.horizontal_ltr:
                ax = prev_char["x0"]
                bx = prev_char["x1"]
                cx = curr_char["x0"]
            else:
                ax = -prev_char["x1"]
                bx = -prev_char["x0"]
                cx = -curr_char["x1"]

        else:
            x = self.y_tolerance
            y = self.x_tolerance
            ay = prev_char["x0"]
            cy = curr_char["x0"]
            if self.vertical_ttb:
                ax = prev_char["top"]
                bx = prev_char["bottom"]
                cx = curr_char["top"]
            else:
                ax = -prev_char["bottom"]
                bx = -prev_char["top"]
                cx = -curr_char["bottom"]

        return bool(
            # Intraline test
            (cx < ax)
            or (cx > bx + x)
            # Interline test
            or (cy > ay + y)
        )

    def iter_chars_to_words(self, ordered_chars):
        current_word: list = []

        def start_next_word(new_char=None):
            nonlocal current_word

            if current_word:
                yield current_word

            current_word = [] if new_char is None else [new_char]

        for char in ordered_chars:
            text = char["text"]

            if not self.keep_blank_chars and text.isspace():
                yield from start_next_word(None)

            elif text in self.split_at_punctuation:
                yield from start_next_word(char)
                yield from start_next_word(None)

            elif current_word and self.char_begins_new_word(current_word[-1], char):
                yield from start_next_word(char)

            else:
                current_word.append(char)

        # Finally, after all chars processed
        if current_word:
            yield current_word

    def iter_sort_chars(self, chars):
        def upright_key(x) -> int:
            return -int(x["upright"])

        for upright_cluster in cluster_objects(list(chars), upright_key, 0):
            upright = upright_cluster[0]["upright"]
            cluster_key = "doctop" if upright else "x0"

            # Cluster by line
            subclusters = cluster_objects(
                upright_cluster, itemgetter(cluster_key), self.y_tolerance
            )

            for sc in subclusters:
                # Sort within line
                sort_key = "x0" if upright else "doctop"
                to_yield = sorted(sc, key=itemgetter(sort_key))

                # Reverse order if necessary
                if not (self.horizontal_ltr if upright else self.vertical_ttb):
                    yield from reversed(to_yield)
                else:
                    yield from to_yield

    def iter_extract_tuples(self, chars):
        ordered_chars = chars if self.use_text_flow else self.iter_sort_chars(chars)

        grouping_key = itemgetter("upright", *self.extra_attrs)
        grouped_chars = itertools.groupby(ordered_chars, grouping_key)

        for keyvals, char_group in grouped_chars:
            for word_chars in self.iter_chars_to_words(char_group):
                yield (self.merge_chars(word_chars), word_chars)

    def extract_wordmap(self, chars) -> WordMap:
        return WordMap(list(self.iter_extract_tuples(chars)))

    def extract_words(self, chars: list) -> list:
        words = list(word for word, word_chars in self.iter_extract_tuples(chars))
        return words


def extract_words(chars: list, **kwargs) -> list:
    return WordExtractor(**kwargs).extract_words(chars)


TEXTMAP_KWARGS = inspect.signature(WordMap.to_textmap).parameters.keys()
WORD_EXTRACTOR_KWARGS = inspect.signature(WordExtractor).parameters.keys()


def chars_to_textmap(chars: list, **kwargs) -> TextMap:
    kwargs.update({"presorted": True})

    extractor = WordExtractor(
        **{k: kwargs[k] for k in WORD_EXTRACTOR_KWARGS if k in kwargs}
    )
    wordmap = extractor.extract_wordmap(chars)
    textmap = wordmap.to_textmap(
        **{k: kwargs[k] for k in TEXTMAP_KWARGS if k in kwargs}
    )

    return textmap


def extract_text(chars: list, **kwargs) -> str:
    chars = to_list(chars)
    if len(chars) == 0:
        return ""

    if kwargs.get("layout"):
        return chars_to_textmap(chars, **kwargs).as_string
    else:
        y_tolerance = kwargs.get("y_tolerance", DEFAULT_Y_TOLERANCE)
        extractor = WordExtractor(
            **{k: kwargs[k] for k in WORD_EXTRACTOR_KWARGS if k in kwargs}
        )
        words = extractor.extract_words(chars)
        if words:
            rotation = words[0]["rotation"]  # rotation cannot change within a cell
        else:
            rotation = 0

        if rotation == 90:
            words.sort(key=lambda w: (w["x1"], -w["top"]))
            lines = " ".join([w["text"] for w in words])
        elif rotation == 270:
            words.sort(key=lambda w: (-w["x1"], w["top"]))
            lines = " ".join([w["text"] for w in words])
        else:
            lines = cluster_objects(words, itemgetter("doctop"), y_tolerance)
            lines = "\n".join(" ".join(word["text"] for word in line) for line in lines)
            if rotation == 180:  # needs extra treatment
                lines = "".join([(c if c != "\n" else " ") for c in reversed(lines)])

        return lines


def collate_line(
    line_chars: list,
    tolerance=DEFAULT_X_TOLERANCE,
) -> str:
    coll = ""
    last_x1 = None
    for char in sorted(line_chars, key=itemgetter("x0")):
        if (last_x1 is not None) and (char["x0"] > (last_x1 + tolerance)):
            coll += " "
        last_x1 = char["x1"]
        coll += char["text"]
    return coll


def dedupe_chars(chars: list, tolerance=1) -> list:
    """
    Removes duplicate chars — those sharing the same text, fontname, size,
    and positioning (within `tolerance`) as other characters in the set.
    """
    key = itemgetter("fontname", "size", "upright", "text")
    pos_key = itemgetter("doctop", "x0")

    def yield_unique_chars(chars: list):
        sorted_chars = sorted(chars, key=key)
        for grp, grp_chars in itertools.groupby(sorted_chars, key=key):
            for y_cluster in cluster_objects(
                list(grp_chars), itemgetter("doctop"), tolerance
            ):
                for x_cluster in cluster_objects(
                    y_cluster, itemgetter("x0"), tolerance
                ):
                    yield sorted(x_cluster, key=pos_key)[0]

    deduped = yield_unique_chars(chars)
    return sorted(deduped, key=chars.index)


def line_to_edge(line):
    edge = dict(line)
    edge["orientation"] = "h" if (line["top"] == line["bottom"]) else "v"
    return edge


def rect_to_edges(rect) -> list:
    top, bottom, left, right = [dict(rect) for x in range(4)]
    top.update(
        {
            "object_type": "rect_edge",
            "height": 0,
            "y0": rect["y1"],
            "bottom": rect["top"],
            "orientation": "h",
        }
    )
    bottom.update(
        {
            "object_type": "rect_edge",
            "height": 0,
            "y1": rect["y0"],
            "top": rect["top"] + rect["height"],
            "doctop": rect["doctop"] + rect["height"],
            "orientation": "h",
        }
    )
    left.update(
        {
            "object_type": "rect_edge",
            "width": 0,
            "x1": rect["x0"],
            "orientation": "v",
        }
    )
    right.update(
        {
            "object_type": "rect_edge",
            "width": 0,
            "x0": rect["x1"],
            "orientation": "v",
        }
    )
    return [top, bottom, left, right]


def curve_to_edges(curve) -> list:
    point_pairs = zip(curve["pts"], curve["pts"][1:])
    return [
        {
            "object_type": "curve_edge",
            "x0": min(p0[0], p1[0]),
            "x1": max(p0[0], p1[0]),
            "top": min(p0[1], p1[1]),
            "doctop": min(p0[1], p1[1]) + (curve["doctop"] - curve["top"]),
            "bottom": max(p0[1], p1[1]),
            "width": abs(p0[0] - p1[0]),
            "height": abs(p0[1] - p1[1]),
            "orientation": "v" if p0[0] == p1[0] else ("h" if p0[1] == p1[1] else None),
        }
        for p0, p1 in point_pairs
    ]


def obj_to_edges(obj) -> list:
    t = obj["object_type"]
    if "_edge" in t:
        return [obj]
    elif t == "line":
        return [line_to_edge(obj)]
    else:
        return {"rect": rect_to_edges, "curve": curve_to_edges}[t](obj)


def filter_edges(
    edges,
    orientation=None,
    edge_type=None,
    min_length=1,
) -> list:
    if orientation not in ("v", "h", None):
        raise ValueError("Orientation must be 'v' or 'h'")

    def test(e) -> bool:
        dim = "height" if e["orientation"] == "v" else "width"
        et_correct = e["object_type"] == edge_type if edge_type is not None else True
        orient_correct = orientation is None or e["orientation"] == orientation
        return bool(et_correct and orient_correct and (e[dim] >= min_length))

    return list(filter(test, edges))


def cluster_list(xs, tolerance=0) -> list:
    if tolerance == 0:
        return [[x] for x in sorted(xs)]
    if len(xs) < 2:
        return [[x] for x in sorted(xs)]
    groups = []
    xs = list(sorted(xs))
    current_group = [xs[0]]
    last = xs[0]
    for x in xs[1:]:
        if x <= (last + tolerance):
            current_group.append(x)
        else:
            groups.append(current_group)
            current_group = [x]
        last = x
    groups.append(current_group)
    return groups


def make_cluster_dict(values, tolerance) -> dict:
    clusters = cluster_list(list(set(values)), tolerance)

    nested_tuples = [
        [(val, i) for val in value_cluster] for i, value_cluster in enumerate(clusters)
    ]

    return dict(itertools.chain(*nested_tuples))


def cluster_objects(xs, key_fn, tolerance) -> list:
    if not callable(key_fn):
        key_fn = itemgetter(key_fn)

    values = map(key_fn, xs)
    cluster_dict = make_cluster_dict(values, tolerance)

    get_0, get_1 = itemgetter(0), itemgetter(1)

    cluster_tuples = sorted(((x, cluster_dict.get(key_fn(x))) for x in xs), key=get_1)

    grouped = itertools.groupby(cluster_tuples, key=get_1)

    return [list(map(get_0, v)) for k, v in grouped]


def move_object(obj, axis: str, value):
    assert axis in ("h", "v")
    if axis == "h":
        new_items = [
            ("x0", obj["x0"] + value),
            ("x1", obj["x1"] + value),
        ]
    if axis == "v":
        new_items = [
            ("top", obj["top"] + value),
            ("bottom", obj["bottom"] + value),
        ]
        if "doctop" in obj:
            new_items += [("doctop", obj["doctop"] + value)]
        if "y0" in obj:
            new_items += [
                ("y0", obj["y0"] - value),
                ("y1", obj["y1"] - value),
            ]
    return obj.__class__(tuple(obj.items()) + tuple(new_items))


def snap_objects(objs, attr: str, tolerance) -> list:
    axis = {"x0": "h", "x1": "h", "top": "v", "bottom": "v"}[attr]
    list_objs = list(objs)
    clusters = cluster_objects(list_objs, itemgetter(attr), tolerance)
    avgs = [sum(map(itemgetter(attr), cluster)) / len(cluster) for cluster in clusters]
    snapped_clusters = [
        [move_object(obj, axis, avg - obj[attr]) for obj in cluster]
        for cluster, avg in zip(clusters, avgs)
    ]
    return list(itertools.chain(*snapped_clusters))


def snap_edges(
    edges,
    x_tolerance=DEFAULT_SNAP_TOLERANCE,
    y_tolerance=DEFAULT_SNAP_TOLERANCE,
):
    """
    Given a list of edges, snap any within `tolerance` pixels of one another
    to their positional average.
    """
    by_orientation = {"v": [], "h": []}
    for e in edges:
        by_orientation[e["orientation"]].append(e)

    snapped_v = snap_objects(by_orientation["v"], "x0", x_tolerance)
    snapped_h = snap_objects(by_orientation["h"], "top", y_tolerance)
    return snapped_v + snapped_h


def resize_object(obj, key: str, value):
    assert key in ("x0", "x1", "top", "bottom")
    old_value = obj[key]
    diff = value - old_value
    new_items = [
        (key, value),
    ]
    if key == "x0":
        assert value <= obj["x1"]
        new_items.append(("width", obj["x1"] - value))
    elif key == "x1":
        assert value >= obj["x0"]
        new_items.append(("width", value - obj["x0"]))
    elif key == "top":
        assert value <= obj["bottom"]
        new_items.append(("doctop", obj["doctop"] + diff))
        new_items.append(("height", obj["height"] - diff))
        if "y1" in obj:
            new_items.append(("y1", obj["y1"] - diff))
    elif key == "bottom":
        assert value >= obj["top"]
        new_items.append(("height", obj["height"] + diff))
        if "y0" in obj:
            new_items.append(("y0", obj["y0"] - diff))
    return obj.__class__(tuple(obj.items()) + tuple(new_items))


def join_edge_group(edges, orientation: str, tolerance=DEFAULT_JOIN_TOLERANCE):
    """
    Given a list of edges along the same infinite line, join those that
    are within `tolerance` pixels of one another.
    """
    if orientation == "h":
        min_prop, max_prop = "x0", "x1"
    elif orientation == "v":
        min_prop, max_prop = "top", "bottom"
    else:
        raise ValueError("Orientation must be 'v' or 'h'")

    sorted_edges = list(sorted(edges, key=itemgetter(min_prop)))
    joined = [sorted_edges[0]]
    for e in sorted_edges[1:]:
        last = joined[-1]
        if e[min_prop] <= (last[max_prop] + tolerance):
            if e[max_prop] > last[max_prop]:
                # Extend current edge to new extremity
                joined[-1] = resize_object(last, max_prop, e[max_prop])
        else:
            # Edge is separate from previous edges
            joined.append(e)

    return joined


def merge_edges(
    edges,
    snap_x_tolerance,
    snap_y_tolerance,
    join_x_tolerance,
    join_y_tolerance,
):
    """
    Using the `snap_edges` and `join_edge_group` methods above,
    merge a list of edges into a more "seamless" list.
    """

    def get_group(edge):
        if edge["orientation"] == "h":
            return ("h", edge["top"])
        else:
            return ("v", edge["x0"])

    if snap_x_tolerance > 0 or snap_y_tolerance > 0:
        edges = snap_edges(edges, snap_x_tolerance, snap_y_tolerance)

    _sorted = sorted(edges, key=get_group)
    edge_groups = itertools.groupby(_sorted, key=get_group)
    edge_gen = (
        join_edge_group(
            items, k[0], (join_x_tolerance if k[0] == "h" else join_y_tolerance)
        )
        for k, items in edge_groups
    )
    edges = list(itertools.chain(*edge_gen))
    return edges


def bbox_to_rect(bbox) -> dict:
    """
    Return the rectangle (i.e a dict with keys "x0", "top", "x1",
    "bottom") for an object.
    """
    return {"x0": bbox[0], "top": bbox[1], "x1": bbox[2], "bottom": bbox[3]}


def objects_to_rect(objects) -> dict:
    """
    Given an iterable of objects, return the smallest rectangle (i.e. a
    dict with "x0", "top", "x1", and "bottom" keys) that contains them
    all.
    """
    return bbox_to_rect(objects_to_bbox(objects))


def merge_bboxes(bboxes):
    """
    Given an iterable of bounding boxes, return the smallest bounding box
    that contains them all.
    """
    x0, top, x1, bottom = zip(*bboxes)
    return (min(x0), min(top), max(x1), max(bottom))


def objects_to_bbox(objects):
    """
    Given an iterable of objects, return the smallest bounding box that
    contains them all.
    """
    return merge_bboxes(map(bbox_getter, objects))


def words_to_edges_h(words, word_threshold: int = DEFAULT_MIN_WORDS_HORIZONTAL):
    """
    Find (imaginary) horizontal lines that connect the tops
    of at least `word_threshold` words.
    """
    by_top = cluster_objects(words, itemgetter("top"), 1)
    large_clusters = filter(lambda x: len(x) >= word_threshold, by_top)
    rects = list(map(objects_to_rect, large_clusters))
    if len(rects) == 0:
        return []
    min_x0 = min(map(itemgetter("x0"), rects))
    max_x1 = max(map(itemgetter("x1"), rects))

    edges = []
    for r in rects:
        edges += [
            # Top of text
            {
                "x0": min_x0,
                "x1": max_x1,
                "top": r["top"],
                "bottom": r["top"],
                "width": max_x1 - min_x0,
                "orientation": "h",
            },
            # For each detected row, we also add the 'bottom' line.  This will
            # generate extra edges, (some will be redundant with the next row
            # 'top' line), but this catches the last row of every table.
            {
                "x0": min_x0,
                "x1": max_x1,
                "top": r["bottom"],
                "bottom": r["bottom"],
                "width": max_x1 - min_x0,
                "orientation": "h",
            },
        ]

    return edges


def get_bbox_overlap(a, b):
    a_left, a_top, a_right, a_bottom = a
    b_left, b_top, b_right, b_bottom = b
    o_left = max(a_left, b_left)
    o_right = min(a_right, b_right)
    o_bottom = min(a_bottom, b_bottom)
    o_top = max(a_top, b_top)
    o_width = o_right - o_left
    o_height = o_bottom - o_top
    if o_height >= 0 and o_width >= 0 and o_height + o_width > 0:
        return (o_left, o_top, o_right, o_bottom)
    else:
        return None


def words_to_edges_v(words, word_threshold: int = DEFAULT_MIN_WORDS_VERTICAL):
    """
    Find (imaginary) vertical lines that connect the left, right, or
    center of at least `word_threshold` words.
    """
    # Find words that share the same left, right, or centerpoints
    by_x0 = cluster_objects(words, itemgetter("x0"), 1)
    by_x1 = cluster_objects(words, itemgetter("x1"), 1)

    def get_center(word):
        return float(word["x0"] + word["x1"]) / 2

    by_center = cluster_objects(words, get_center, 1)
    clusters = by_x0 + by_x1 + by_center

    # Find the points that align with the most words
    sorted_clusters = sorted(clusters, key=lambda x: -len(x))
    large_clusters = filter(lambda x: len(x) >= word_threshold, sorted_clusters)

    # For each of those points, find the bboxes fitting all matching words
    bboxes = list(map(objects_to_bbox, large_clusters))

    # Iterate through those bboxes, condensing overlapping bboxes
    condensed_bboxes = []
    for bbox in bboxes:
        overlap = any(get_bbox_overlap(bbox, c) for c in condensed_bboxes)
        if not overlap:
            condensed_bboxes.append(bbox)

    if len(condensed_bboxes) == 0:
        return []

    condensed_rects = map(bbox_to_rect, condensed_bboxes)
    sorted_rects = list(sorted(condensed_rects, key=itemgetter("x0")))

    max_x1 = max(map(itemgetter("x1"), sorted_rects))
    min_top = min(map(itemgetter("top"), sorted_rects))
    max_bottom = max(map(itemgetter("bottom"), sorted_rects))

    return [
        {
            "x0": b["x0"],
            "x1": b["x0"],
            "top": min_top,
            "bottom": max_bottom,
            "height": max_bottom - min_top,
            "orientation": "v",
        }
        for b in sorted_rects
    ] + [
        {
            "x0": max_x1,
            "x1": max_x1,
            "top": min_top,
            "bottom": max_bottom,
            "height": max_bottom - min_top,
            "orientation": "v",
        }
    ]


def edges_to_intersections(edges, x_tolerance=1, y_tolerance=1) -> dict:
    """
    Given a list of edges, return the points at which they intersect
    within `tolerance` pixels.
    """
    intersections = {}
    v_edges, h_edges = [
        list(filter(lambda x: x["orientation"] == o, edges)) for o in ("v", "h")
    ]
    for v in sorted(v_edges, key=itemgetter("x0", "top")):
        for h in sorted(h_edges, key=itemgetter("top", "x0")):
            if (
                (v["top"] <= (h["top"] + y_tolerance))
                and (v["bottom"] >= (h["top"] - y_tolerance))
                and (v["x0"] >= (h["x0"] - x_tolerance))
                and (v["x0"] <= (h["x1"] + x_tolerance))
            ):
                vertex = (v["x0"], h["top"])
                if vertex not in intersections:
                    intersections[vertex] = {"v": [], "h": []}
                intersections[vertex]["v"].append(v)
                intersections[vertex]["h"].append(h)
    return intersections


def obj_to_bbox(obj):
    """
    Return the bounding box for an object.
    """
    return bbox_getter(obj)


def intersections_to_cells(intersections):
    """
    Given a list of points (`intersections`), return all rectangular "cells"
    that those points describe.

    `intersections` should be a dictionary with (x0, top) tuples as keys,
    and a list of edge objects as values. The edge objects should correspond
    to the edges that touch the intersection.
    """

    def edge_connects(p1, p2) -> bool:
        def edges_to_set(edges):
            return set(map(obj_to_bbox, edges))

        if p1[0] == p2[0]:
            common = edges_to_set(intersections[p1]["v"]).intersection(
                edges_to_set(intersections[p2]["v"])
            )
            if len(common):
                return True

        if p1[1] == p2[1]:
            common = edges_to_set(intersections[p1]["h"]).intersection(
                edges_to_set(intersections[p2]["h"])
            )
            if len(common):
                return True
        return False

    points = list(sorted(intersections.keys()))
    n_points = len(points)

    def find_smallest_cell(points, i: int):
        if i == n_points - 1:
            return None
        pt = points[i]
        rest = points[i + 1 :]
        # Get all the points directly below and directly right
        below = [x for x in rest if x[0] == pt[0]]
        right = [x for x in rest if x[1] == pt[1]]
        for below_pt in below:
            if not edge_connects(pt, below_pt):
                continue

            for right_pt in right:
                if not edge_connects(pt, right_pt):
                    continue

                bottom_right = (right_pt[0], below_pt[1])

                if (
                    (bottom_right in intersections)
                    and edge_connects(bottom_right, right_pt)
                    and edge_connects(bottom_right, below_pt)
                ):
                    return (pt[0], pt[1], bottom_right[0], bottom_right[1])
        return None

    cell_gen = (find_smallest_cell(points, i) for i in range(len(points)))
    return list(filter(None, cell_gen))


def cells_to_tables(page, cells) -> list:
    """
    Given a list of bounding boxes (`cells`), return a list of tables that
    hold those cells most simply (and contiguously).
    """

    def bbox_to_corners(bbox) -> tuple:
        x0, top, x1, bottom = bbox
        return ((x0, top), (x0, bottom), (x1, top), (x1, bottom))

    remaining_cells = list(cells)

    # Iterate through the cells found above, and assign them
    # to contiguous tables

    current_corners = set()
    current_cells = []

    tables = []
    while len(remaining_cells):
        initial_cell_count = len(current_cells)
        for cell in list(remaining_cells):
            cell_corners = bbox_to_corners(cell)
            # If we're just starting a table ...
            if len(current_cells) == 0:
                # ... immediately assign it to the empty group
                current_corners |= set(cell_corners)
                current_cells.append(cell)
                remaining_cells.remove(cell)
            else:
                # How many corners does this table share with the current group?
                corner_count = sum(c in current_corners for c in cell_corners)

                # If touching on at least one corner...
                if corner_count > 0:
                    # ... assign it to the current group
                    current_corners |= set(cell_corners)
                    current_cells.append(cell)
                    remaining_cells.remove(cell)

        # If this iteration did not find any more cells to append...
        if len(current_cells) == initial_cell_count:
            # ... start a new cell group
            tables.append(list(current_cells))
            current_corners.clear()
            current_cells.clear()

    # Once we have exhausting the list of cells ...

    # ... and we have a cell group that has not been stored
    if len(current_cells):
        # ... store it.
        tables.append(list(current_cells))

    # PyMuPDF modification:
    # Remove tables without text or having only 1 column
    for i in range(len(tables) - 1, -1, -1):
        r = EMPTY_RECT()
        x1_vals = set()
        x0_vals = set()
        for c in tables[i]:
            r |= c
            x1_vals.add(c[2])
            x0_vals.add(c[0])
        if (
            len(x1_vals) < 2
            or len(x0_vals) < 2
            or white_spaces.issuperset(
                page.get_textbox(
                    r,
                    textpage=TEXTPAGE,
                )
            )
        ):
            del tables[i]

    # Sort the tables top-to-bottom-left-to-right based on the value of the
    # topmost-and-then-leftmost coordinate of a table.
    _sorted = sorted(tables, key=lambda t: min((c[1], c[0]) for c in t))
    return _sorted


class CellGroup:
    def __init__(self, cells):
        self.cells = cells
        self.bbox = (
            min(map(itemgetter(0), filter(None, cells))),
            min(map(itemgetter(1), filter(None, cells))),
            max(map(itemgetter(2), filter(None, cells))),
            max(map(itemgetter(3), filter(None, cells))),
        )


class TableRow(CellGroup):
    pass


class TableHeader:
    """PyMuPDF extension containing the identified table header."""

    def __init__(self, bbox, cells, names, above):
        self.bbox = bbox
        self.cells = cells
        self.names = names
        self.external = above


class Table:
    def __init__(self, page, cells):
        self.page = page
        self.cells = cells
        self.header = self._get_header()  # PyMuPDF extension

    @property
    def bbox(self):
        c = self.cells
        return (
            min(map(itemgetter(0), c)),
            min(map(itemgetter(1), c)),
            max(map(itemgetter(2), c)),
            max(map(itemgetter(3), c)),
        )

    @property
    def rows(self) -> list:
        _sorted = sorted(self.cells, key=itemgetter(1, 0))
        xs = list(sorted(set(map(itemgetter(0), self.cells))))
        rows = []
        for y, row_cells in itertools.groupby(_sorted, itemgetter(1)):
            xdict = {cell[0]: cell for cell in row_cells}
            row = TableRow([xdict.get(x) for x in xs])
            rows.append(row)
        return rows

    @property
    def row_count(self) -> int:  # PyMuPDF extension
        return len(self.rows)

    @property
    def col_count(self) -> int:  # PyMuPDF extension
        return max([len(r.cells) for r in self.rows])

    def extract(self, **kwargs) -> list:
        chars = CHARS
        table_arr = []

        def char_in_bbox(char, bbox) -> bool:
            v_mid = (char["top"] + char["bottom"]) / 2
            h_mid = (char["x0"] + char["x1"]) / 2
            x0, top, x1, bottom = bbox
            return bool(
                (h_mid >= x0) and (h_mid < x1) and (v_mid >= top) and (v_mid < bottom)
            )

        for row in self.rows:
            arr = []
            row_chars = [char for char in chars if char_in_bbox(char, row.bbox)]

            for cell in row.cells:
                if cell is None:
                    cell_text = None
                else:
                    cell_chars = [
                        char for char in row_chars if char_in_bbox(char, cell)
                    ]

                    if len(cell_chars):
                        kwargs["x_shift"] = cell[0]
                        kwargs["y_shift"] = cell[1]
                        if "layout" in kwargs:
                            kwargs["layout_width"] = cell[2] - cell[0]
                            kwargs["layout_height"] = cell[3] - cell[1]
                        cell_text = extract_text(cell_chars, **kwargs)
                    else:
                        cell_text = ""
                arr.append(cell_text)
            table_arr.append(arr)

        return table_arr

    def to_markdown(self, clean=True):
        """Output table content as a string in Github-markdown format.

        If clean is true, markdown syntax is removed from cell content."""
        output = "|"

        # generate header string and MD underline
        for i, name in enumerate(self.header.names):
            if name is None or name == "":  # generate a name if empty
                name = f"Col{i+1}"
            name = name.replace("\n", " ")  # remove any line breaks
            if clean:  # remove sensitive syntax
                name = html.escape(name.replace("-", "&#45;"))
            output += name + "|"

        output += "\n"
        output += "|" + "|".join("---" for i in range(self.col_count)) + "|\n"

        # skip first row in details if header is part of the table
        j = 0 if self.header.external else 1

        # iterate over detail rows
        for row in self.extract()[j:]:
            line = "|"
            for i, cell in enumerate(row):
                # output None cells with empty string
                cell = "" if cell is None else cell.replace("\n", " ")
                if clean:  # remove sensitive syntax
                    cell = html.escape(cell.replace("-", "&#45;"))
                line += cell + "|"
            line += "\n"
            output += line
        return output + "\n"

    def to_pandas(self, **kwargs):
        """Return a pandas DataFrame version of the table."""
        try:
            import pandas as pd
        except ModuleNotFoundError:
            message("Package 'pandas' is not installed")
            raise

        pd_dict = {}
        extract = self.extract()
        hdr = self.header
        names = self.header.names
        hdr_len = len(names)
        # ensure uniqueness of column names
        for i in range(hdr_len):
            name = names[i]
            if not name:
                names[i] = f"Col{i}"
        if hdr_len != len(set(names)):
            for i in range(hdr_len):
                name = names[i]
                if name != f"Col{i}":
                    names[i] = f"{i}-{name}"

        if not hdr.external:  # header is part of 'extract'
            extract = extract[1:]

        for i in range(hdr_len):
            key = names[i]
            value = []
            for j in range(len(extract)):
                value.append(extract[j][i])
            pd_dict[key] = value

        return pd.DataFrame(pd_dict)

    def _get_header(self, y_tolerance=3):
        """Identify the table header.

        *** PyMuPDF extension. ***

        Starting from the first line above the table upwards, check if it
        qualifies to be part of the table header.

        Criteria include:
        * A one-line table never has an extra header.
        * Column borders must not intersect any word. If this happens, all
          text of this line and above of it is ignored.
        * No excess inter-line distance: If a line further up has a distance
          of more than 1.5 times of its font size, it will be ignored and
          all lines above of it.
        * Must have same text properties.
        * Starting with the top table line, a bold text property cannot change
          back to non-bold.

        If not all criteria are met (or there is no text above the table),
        the first table row is assumed to be the header.
        """
        page = self.page
        y_delta = y_tolerance

        def top_row_is_bold(bbox):
            """Check if row 0 has bold text anywhere.

            If this is true, then any non-bold text in lines above disqualify
            these lines as header.

            bbox is the (potentially repaired) row 0 bbox.

            Returns True or False
            """
            for b in page.get_text("dict", flags=TEXTFLAGS_TEXT, clip=bbox)["blocks"]:
                for l in b["lines"]:
                    for s in l["spans"]:
                        if s["flags"] & 16:
                            return True
            return False

        try:
            row = self.rows[0]
            cells = row.cells
            bbox = Rect(row.bbox)
        except IndexError:  # this table has no rows
            return None

        # return this if we determine that the top row is the header
        header_top_row = TableHeader(bbox, cells, self.extract()[0], False)

        # one-line tables have no extra header
        if len(self.rows) < 2:
            return header_top_row

        # x-ccordinates of columns between x0 and x1 of the table
        if len(cells) < 2:
            return header_top_row

        col_x = [
            c[2] if c is not None else None for c in cells[:-1]
        ]  # column (x) coordinates

        # Special check: is top row bold?
        # If first line above table is not bold, but top-left table cell is bold,
        # we take first table row as header
        top_row_bold = top_row_is_bold(bbox)

        # clip = area above table
        # We will inspect this area for text qualifying as column header.
        clip = +bbox  # take row 0 bbox
        clip.y0 = 0  # start at top of page
        clip.y1 = bbox.y0  # end at top of table

        spans = []  # the text spans inside clip
        for b in page.get_text("dict", clip=clip, flags=TEXTFLAGS_TEXT)["blocks"]:
            for l in b["lines"]:
                for s in l["spans"]:
                    if (
                        not s["flags"] & 1 and s["text"].strip()
                    ):  # ignore superscripts and empty text
                        spans.append(s)

        select = []  # y1 coordinates above, sorted descending
        line_heights = []  # line heights above, sorted descending
        line_bolds = []  # bold indicator per line above, same sorting

        # spans sorted descending
        spans.sort(key=lambda s: s["bbox"][3], reverse=True)
        # walk through the spans and fill above 3 lists
        for i in range(len(spans)):
            s = spans[i]
            y1 = s["bbox"][3]  # span bottom
            h = y1 - s["bbox"][1]  # span bbox height
            bold = s["flags"] & 16

            # use first item to start the lists
            if i == 0:
                select.append(y1)
                line_heights.append(h)
                line_bolds.append(bold)
                continue

            # get last items from the 3 lists
            y0 = select[-1]
            h0 = line_heights[-1]
            bold0 = line_bolds[-1]

            if bold0 and not bold:
                break  # stop if switching from bold to non-bold

            # if fitting in height of previous span, modify bbox
            if y0 - y1 <= y_delta or abs((y0 - h0) - s["bbox"][1]) <= y_delta:
                s["bbox"] = (s["bbox"][0], y0 - h0, s["bbox"][2], y0)
                spans[i] = s
                if bold:
                    line_bolds[-1] = bold
                continue
            elif y0 - y1 > 1.5 * h0:
                break  # stop if distance to previous line too large
            select.append(y1)
            line_heights.append(h)
            line_bolds.append(bold)

        if select == []:  # nothing above the table?
            return header_top_row

        select = select[:5]  # only accept up to 5 lines in any header

        # take top row as header if text above table is too far apart
        if bbox.y0 - select[0] >= line_heights[0]:
            return header_top_row

        # if top table row is bold, but line above is not:
        if top_row_bold and not line_bolds[0]:
            return header_top_row

        if spans == []:  # nothing left above the table, return top row
            return header_top_row

        # re-compute clip above table
        nclip = EMPTY_RECT()
        for s in [s for s in spans if s["bbox"][3] >= select[-1]]:
            nclip |= s["bbox"]
        if not nclip.is_empty:
            clip = nclip

        clip.y1 = bbox.y0  # make sure we still include every word above

        # Confirm that no word in clip is intersecting a column separator
        word_rects = [Rect(w[:4]) for w in page.get_text("words", clip=clip)]
        word_tops = sorted(list(set([r[1] for r in word_rects])), reverse=True)

        select = []

        # exclude lines with words that intersect a column border
        for top in word_tops:
            intersecting = [
                (x, r)
                for x in col_x
                if x is not None
                for r in word_rects
                if r[1] == top and r[0] < x and r[2] > x
            ]
            if intersecting == []:
                select.append(top)
            else:  # detected a word crossing a column border
                break

        if select == []:  # nothing left over: return first row
            return header_top_row

        hdr_bbox = +clip  # compute the header cells
        hdr_bbox.y0 = select[-1]  # hdr_bbox top is smallest top coord of words
        hdr_cells = [
            (c[0], hdr_bbox.y0, c[2], hdr_bbox.y1) if c is not None else None
            for c in cells
        ]

        # adjust left/right of header bbox
        hdr_bbox.x0 = self.bbox[0]
        hdr_bbox.x1 = self.bbox[2]

        # column names: no line breaks, no excess spaces
        hdr_names = [
            (
                page.get_textbox(c).replace("\n", " ").replace("  ", " ").strip()
                if c is not None
                else ""
            )
            for c in hdr_cells
        ]
        return TableHeader(tuple(hdr_bbox), hdr_cells, hdr_names, True)


@dataclass
class TableSettings:
    vertical_strategy: str = "lines"
    horizontal_strategy: str = "lines"
    explicit_vertical_lines: list = None
    explicit_horizontal_lines: list = None
    snap_tolerance: float = DEFAULT_SNAP_TOLERANCE
    snap_x_tolerance: float = UNSET
    snap_y_tolerance: float = UNSET
    join_tolerance: float = DEFAULT_JOIN_TOLERANCE
    join_x_tolerance: float = UNSET
    join_y_tolerance: float = UNSET
    edge_min_length: float = 3
    min_words_vertical: float = DEFAULT_MIN_WORDS_VERTICAL
    min_words_horizontal: float = DEFAULT_MIN_WORDS_HORIZONTAL
    intersection_tolerance: float = 3
    intersection_x_tolerance: float = UNSET
    intersection_y_tolerance: float = UNSET
    text_settings: dict = None

    def __post_init__(self) -> "TableSettings":
        """Clean up user-provided table settings.

        Validates that the table settings provided consists of acceptable values and
        returns a cleaned up version. The cleaned up version fills out the missing
        values with the default values in the provided settings.

        TODO: Can be further used to validate that the values are of the correct
            type. For example, raising a value error when a non-boolean input is
            provided for the key ``keep_blank_chars``.

        :param table_settings: User-provided table settings.
        :returns: A cleaned up version of the user-provided table settings.
        :raises ValueError: When an unrecognised key is provided.
        """

        for setting in NON_NEGATIVE_SETTINGS:
            if (getattr(self, setting) or 0) < 0:
                raise ValueError(f"Table setting '{setting}' cannot be negative")

        for orientation in ["horizontal", "vertical"]:
            strategy = getattr(self, orientation + "_strategy")
            if strategy not in TABLE_STRATEGIES:
                raise ValueError(
                    f"{orientation}_strategy must be one of"
                    f'{{{",".join(TABLE_STRATEGIES)}}}'
                )

        if self.text_settings is None:
            self.text_settings = {}

        # This next section is for backwards compatibility
        for attr in ["x_tolerance", "y_tolerance"]:
            if attr not in self.text_settings:
                self.text_settings[attr] = self.text_settings.get("tolerance", 3)

        if "tolerance" in self.text_settings:
            del self.text_settings["tolerance"]
        # End of that section

        for attr, fallback in [
            ("snap_x_tolerance", "snap_tolerance"),
            ("snap_y_tolerance", "snap_tolerance"),
            ("join_x_tolerance", "join_tolerance"),
            ("join_y_tolerance", "join_tolerance"),
            ("intersection_x_tolerance", "intersection_tolerance"),
            ("intersection_y_tolerance", "intersection_tolerance"),
        ]:
            if getattr(self, attr) is UNSET:
                setattr(self, attr, getattr(self, fallback))

        return self

    @classmethod
    def resolve(cls, settings=None):
        if settings is None:
            return cls()
        elif isinstance(settings, cls):
            return settings
        elif isinstance(settings, dict):
            core_settings = {}
            text_settings = {}
            for k, v in settings.items():
                if k[:5] == "text_":
                    text_settings[k[5:]] = v
                else:
                    core_settings[k] = v
            core_settings["text_settings"] = text_settings
            return cls(**core_settings)
        else:
            raise ValueError(f"Cannot resolve settings: {settings}")


class TableFinder:
    """
    Given a PDF page, find plausible table structures.

    Largely borrowed from Anssi Nurminen's master's thesis:
    http://dspace.cc.tut.fi/dpub/bitstream/handle/123456789/21520/Nurminen.pdf?sequence=3

    ... and inspired by Tabula:
    https://github.com/tabulapdf/tabula-extractor/issues/16
    """

    def __init__(self, page, settings=None):
        self.page = page
        self.settings = TableSettings.resolve(settings)
        self.edges = self.get_edges()
        self.intersections = edges_to_intersections(
            self.edges,
            self.settings.intersection_x_tolerance,
            self.settings.intersection_y_tolerance,
        )
        self.cells = intersections_to_cells(self.intersections)
        self.tables = [
            Table(self.page, cell_group)
            for cell_group in cells_to_tables(self.page, self.cells)
        ]

    def get_edges(self) -> list:
        settings = self.settings

        for orientation in ["vertical", "horizontal"]:
            strategy = getattr(settings, orientation + "_strategy")
            if strategy == "explicit":
                lines = getattr(settings, "explicit_" + orientation + "_lines")
                if len(lines) < 2:
                    raise ValueError(
                        f"If {orientation}_strategy == 'explicit', "
                        f"explicit_{orientation}_lines "
                        f"must be specified as a list/tuple of two or more "
                        f"floats/ints."
                    )

        v_strat = settings.vertical_strategy
        h_strat = settings.horizontal_strategy

        if v_strat == "text" or h_strat == "text":
            words = extract_words(CHARS, **(settings.text_settings or {}))
        else:
            words = []

        v_explicit = []
        for desc in settings.explicit_vertical_lines or []:
            if isinstance(desc, dict):
                for e in obj_to_edges(desc):
                    if e["orientation"] == "v":
                        v_explicit.append(e)
            else:
                v_explicit.append(
                    {
                        "x0": desc,
                        "x1": desc,
                        "top": self.page.rect[1],
                        "bottom": self.page.rect[3],
                        "height": self.page.rect[3] - self.page.rect[1],
                        "orientation": "v",
                    }
                )

        if v_strat == "lines":
            v_base = filter_edges(EDGES, "v")
        elif v_strat == "lines_strict":
            v_base = filter_edges(EDGES, "v", edge_type="line")
        elif v_strat == "text":
            v_base = words_to_edges_v(words, word_threshold=settings.min_words_vertical)
        elif v_strat == "explicit":
            v_base = []
        else:
            v_base = []

        v = v_base + v_explicit

        h_explicit = []
        for desc in settings.explicit_horizontal_lines or []:
            if isinstance(desc, dict):
                for e in obj_to_edges(desc):
                    if e["orientation"] == "h":
                        h_explicit.append(e)
            else:
                h_explicit.append(
                    {
                        "x0": self.page.rect[0],
                        "x1": self.page.rect[2],
                        "width": self.page.rect[2] - self.page.rect[0],
                        "top": desc,
                        "bottom": desc,
                        "orientation": "h",
                    }
                )

        if h_strat == "lines":
            h_base = filter_edges(EDGES, "h")
        elif h_strat == "lines_strict":
            h_base = filter_edges(EDGES, "h", edge_type="line")
        elif h_strat == "text":
            h_base = words_to_edges_h(
                words, word_threshold=settings.min_words_horizontal
            )
        elif h_strat == "explicit":
            h_base = []
        else:
            h_base = []

        h = h_base + h_explicit

        edges = list(v) + list(h)

        edges = merge_edges(
            edges,
            snap_x_tolerance=settings.snap_x_tolerance,
            snap_y_tolerance=settings.snap_y_tolerance,
            join_x_tolerance=settings.join_x_tolerance,
            join_y_tolerance=settings.join_y_tolerance,
        )

        return filter_edges(edges, min_length=settings.edge_min_length)

    def __getitem__(self, i):
        tcount = len(self.tables)
        if i >= tcount:
            raise IndexError("table not on page")
        while i < 0:
            i += tcount
        return self.tables[i]


"""
Start of PyMuPDF interface code.
The following functions are executed when "page.find_tables()" is called.

* make_chars: Fills the CHARS list with text character information extracted
              via "rawdict" text extraction. Items in CHARS are formatted
              as expected by the table code.
* make_edges: Fills the EDGES list with vector graphic information extracted
              via "get_drawings". Items in EDGES are formatted as expected
              by the table code.

The lists CHARS and EDGES are used to replace respective document access
of pdfplumber or, respectively pdfminer.
The table code has been modified to use these lists instead of accessing
page information themselves.
"""


# -----------------------------------------------------------------------------
# Extract all page characters to fill the CHARS list
# -----------------------------------------------------------------------------
def make_chars(page, clip=None):
    """Extract text as "rawdict" to fill CHARS."""
    global TEXTPAGE
    page_number = page.number + 1
    page_height = page.rect.height
    ctm = page.transformation_matrix
    TEXTPAGE = page.get_textpage(clip=clip, flags=TEXTFLAGS_TEXT)
    blocks = page.get_text("rawdict", textpage=TEXTPAGE)["blocks"]
    doctop_base = page_height * page.number
    for block in blocks:
        for line in block["lines"]:
            ldir = line["dir"]  # = (cosine, sine) of angle
            ldir = (round(ldir[0], 4), round(ldir[1], 4))
            matrix = Matrix(ldir[0], -ldir[1], ldir[1], ldir[0], 0, 0)
            if ldir[1] == 0:
                upright = True
            else:
                upright = False
            for span in sorted(line["spans"], key=lambda s: s["bbox"][0]):
                fontname = span["font"]
                fontsize = span["size"]
                color = sRGB_to_pdf(span["color"])
                for char in sorted(span["chars"], key=lambda c: c["bbox"][0]):
                    bbox = Rect(char["bbox"])
                    bbox_ctm = bbox * ctm
                    origin = Point(char["origin"]) * ctm
                    matrix.e = origin.x
                    matrix.f = origin.y
                    text = char["c"]
                    char_dict = {
                        "adv": bbox.x1 - bbox.x0 if upright else bbox.y1 - bbox.y0,
                        "bottom": bbox.y1,
                        "doctop": bbox.y0 + doctop_base,
                        "fontname": fontname,
                        "height": bbox.y1 - bbox.y0,
                        "matrix": tuple(matrix),
                        "ncs": "DeviceRGB",
                        "non_stroking_color": color,
                        "non_stroking_pattern": None,
                        "object_type": "char",
                        "page_number": page_number,
                        "size": fontsize if upright else bbox.y1 - bbox.y0,
                        "stroking_color": color,
                        "stroking_pattern": None,
                        "text": text,
                        "top": bbox.y0,
                        "upright": upright,
                        "width": bbox.x1 - bbox.x0,
                        "x0": bbox.x0,
                        "x1": bbox.x1,
                        "y0": bbox_ctm.y0,
                        "y1": bbox_ctm.y1,
                    }
                    CHARS.append(char_dict)


# ------------------------------------------------------------------------
# Extract all page vector graphics to fill the EDGES list.
# We are ignoring Bézier curves completely and are converting everything
# else to lines.
# ------------------------------------------------------------------------
def make_edges(page, clip=None, tset=None, add_lines=None):
    snap_x = tset.snap_x_tolerance
    snap_y = tset.snap_y_tolerance
    min_length = tset.edge_min_length
    lines_strict = (
        tset.vertical_strategy == "lines_strict"
        or tset.horizontal_strategy == "lines_strict"
    )
    page_height = page.rect.height
    doctop_basis = page.number * page_height
    page_number = page.number + 1
    prect = page.rect
    if page.rotation in (90, 270):
        w, h = prect.br
        prect = Rect(0, 0, h, w)
    if clip is not None:
        clip = Rect(clip)
    else:
        clip = prect

    def are_neighbors(r1, r2):
        """Detect whether r1, r2 are neighbors.

        Defined as:
        The minimum distance between points of r1 and points of r2 is not
        larger than some delta.

        This check supports empty rect-likes and thus also lines.

        Note:
        This type of check is MUCH faster than native Rect containment checks.
        """
        if (  # check if x-coordinates of r1 are within those of r2
            r2.x0 - snap_x <= r1.x0 <= r2.x1 + snap_x
            or r2.x0 - snap_x <= r1.x1 <= r2.x1 + snap_x
        ) and (  # ... same for y-coordinates
            r2.y0 - snap_y <= r1.y0 <= r2.y1 + snap_y
            or r2.y0 - snap_y <= r1.y1 <= r2.y1 + snap_y
        ):
            return True

        # same check with r1 / r2 exchanging their roles (this is necessary!)
        if (
            r1.x0 - snap_x <= r2.x0 <= r1.x1 + snap_x
            or r1.x0 - snap_x <= r2.x1 <= r1.x1 + snap_x
        ) and (
            r1.y0 - snap_y <= r2.y0 <= r1.y1 + snap_y
            or r1.y0 - snap_y <= r2.y1 <= r1.y1 + snap_y
        ):
            return True
        return False

    def clean_graphics():
        """Detect and join rectangles of "connected" vector graphics."""

        paths = []  # paths relevant for table detection
        for p in page.get_drawings():
            # ignore fill-only graphics if they do not simulate lines,
            # which means one of width or height are small.
            if (
                p["type"] == "f"
                and lines_strict
                and p["rect"].width > snap_x
                and p["rect"].height > snap_y
            ):
                continue
            paths.append(p)

        # start with all vector graphics rectangles
        prects = sorted(set([p["rect"] for p in paths]), key=lambda r: (r.y1, r.x0))
        new_rects = []  # the final list of joined rectangles
        # ----------------------------------------------------------------
        # Strategy: Join rectangles that "almost touch" each other.
        # Extend first rectangle with any other that is a "neighbor".
        # Then move it to the final list and continue with the rest.
        # ----------------------------------------------------------------
        while prects:  # the algorithm will empty this list
            prect0 = prects[0]  # copy of first rectangle (performance reasons!)
            repeat = True
            while repeat:  # this loop extends first rect in list
                repeat = False  # set to true again if some other rect touches
                for i in range(len(prects) - 1, 0, -1):  # run backwards
                    if are_neighbors(prect0, prects[i]):  # close enough to rect 0?
                        prect0 |= prects[i].tl  # extend rect 0
                        prect0 |= prects[i].br  # extend rect 0
                        del prects[i]  # delete this rect
                        repeat = True  # keep checking the rest

            # move rect 0 over to result list if there is some text in it
            if not white_spaces.issuperset(page.get_textbox(prect0, textpage=TEXTPAGE)):
                # contains text, so accept it as a table bbox candidate
                new_rects.append(prect0)
            del prects[0]  # remove from rect list

        return new_rects, paths

    bboxes, paths = clean_graphics()

    def is_parallel(p1, p2):
        """Check if line is roughly axis-parallel."""
        if abs(p1.x - p2.x) <= snap_x or abs(p1.y - p2.y) <= snap_y:
            return True
        return False

    def make_line(p, p1, p2, clip):
        """Given 2 points, make a line dictionary for table detection."""
        if not is_parallel(p1, p2):  # only accepting axis-parallel lines
            return {}
        # compute the extremal values
        x0 = min(p1.x, p2.x)
        x1 = max(p1.x, p2.x)
        y0 = min(p1.y, p2.y)
        y1 = max(p1.y, p2.y)

        # check for outside clip
        if x0 > clip.x1 or x1 < clip.x0 or y0 > clip.y1 or y1 < clip.y0:
            return {}

        if x0 < clip.x0:
            x0 = clip.x0  # adjust to clip boundary

        if x1 > clip.x1:
            x1 = clip.x1  # adjust to clip boundary

        if y0 < clip.y0:
            y0 = clip.y0  # adjust to clip boundary

        if y1 > clip.y1:
            y1 = clip.y1  # adjust to clip boundary

        width = x1 - x0  # from adjusted values
        height = y1 - y0  # from adjusted values
        if width == height == 0:
            return {}  # nothing left to deal with
        line_dict = {
            "x0": x0,
            "y0": page_height - y0,
            "x1": x1,
            "y1": page_height - y1,
            "width": width,
            "height": height,
            "pts": [(x0, y0), (x1, y1)],
            "linewidth": p["width"],
            "stroke": True,
            "fill": False,
            "evenodd": False,
            "stroking_color": p["color"] if p["color"] else p["fill"],
            "non_stroking_color": None,
            "object_type": "line",
            "page_number": page_number,
            "stroking_pattern": None,
            "non_stroking_pattern": None,
            "top": y0,
            "bottom": y1,
            "doctop": y0 + doctop_basis,
        }
        return line_dict

    for p in paths:
        items = p["items"]  # items in this path

        # if 'closePath', add a line from last to first point
        if p["closePath"] and items[0][0] == "l" and items[-1][0] == "l":
            items.append(("l", items[-1][2], items[0][1]))

        for i in items:
            if i[0] not in ("l", "re", "qu"):
                continue  # ignore anything else

            if i[0] == "l":  # a line
                p1, p2 = i[1:]
                line_dict = make_line(p, p1, p2, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

            elif i[0] == "re":
                # A rectangle: decompose into 4 lines, but filter out
                # the ones that simulate a line
                rect = i[1].normalize()  # normalize the rectangle

                if (
                    rect.width <= min_length and rect.width < rect.height
                ):  # simulates a vertical line
                    x = abs(rect.x1 + rect.x0) / 2  # take middle value for x
                    p1 = Point(x, rect.y0)
                    p2 = Point(x, rect.y1)
                    line_dict = make_line(p, p1, p2, clip)
                    if line_dict:
                        EDGES.append(line_to_edge(line_dict))
                    continue

                if (
                    rect.height <= min_length and rect.height < rect.width
                ):  # simulates a horizontal line
                    y = abs(rect.y1 + rect.y0) / 2  # take middle value for y
                    p1 = Point(rect.x0, y)
                    p2 = Point(rect.x1, y)
                    line_dict = make_line(p, p1, p2, clip)
                    if line_dict:
                        EDGES.append(line_to_edge(line_dict))
                    continue

                line_dict = make_line(p, rect.tl, rect.bl, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

                line_dict = make_line(p, rect.bl, rect.br, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

                line_dict = make_line(p, rect.br, rect.tr, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

                line_dict = make_line(p, rect.tr, rect.tl, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

            else:  # must be a quad
                # we convert it into (up to) 4 lines
                ul, ur, ll, lr = i[1]

                line_dict = make_line(p, ul, ll, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

                line_dict = make_line(p, ll, lr, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

                line_dict = make_line(p, lr, ur, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

                line_dict = make_line(p, ur, ul, clip)
                if line_dict:
                    EDGES.append(line_to_edge(line_dict))

    path = {"color": (0, 0, 0), "fill": None, "width": 1}
    for bbox in bboxes:  # add the border lines for all enveloping bboxes
        line_dict = make_line(path, bbox.tl, bbox.tr, clip)
        if line_dict:
            EDGES.append(line_to_edge(line_dict))

        line_dict = make_line(path, bbox.bl, bbox.br, clip)
        if line_dict:
            EDGES.append(line_to_edge(line_dict))

        line_dict = make_line(path, bbox.tl, bbox.bl, clip)
        if line_dict:
            EDGES.append(line_to_edge(line_dict))

        line_dict = make_line(path, bbox.tr, bbox.br, clip)
        if line_dict:
            EDGES.append(line_to_edge(line_dict))

    if add_lines is not None:  # add user-specified lines
        assert isinstance(add_lines, (tuple, list))
    else:
        add_lines = []
    for p1, p2 in add_lines:
        p1 = Point(p1)
        p2 = Point(p2)
        line_dict = make_line(path, p1, p2, clip)
        if line_dict:
            EDGES.append(line_to_edge(line_dict))


def page_rotation_set0(page):
    """Nullify page rotation.

    To correctly detect tables, page rotation must be zero.
    This function performs the necessary adjustments and returns information
    for reverting this changes.
    """
    mediabox = page.mediabox
    rot = page.rotation  # contains normalized rotation value
    # need to derotate the page's content
    mb = page.mediabox  # current mediabox

    if rot == 90:
        # before derotation, shift content horizontally
        mat0 = Matrix(1, 0, 0, 1, mb.y1 - mb.x1 - mb.x0 - mb.y0, 0)
    elif rot == 270:
        # before derotation, shift content vertically
        mat0 = Matrix(1, 0, 0, 1, 0, mb.x1 - mb.y1 - mb.y0 - mb.x0)
    else:
        mat0 = Matrix(1, 0, 0, 1, -2 * mb.x0, -2 * mb.y0)

    # prefix with derotation matrix
    mat = mat0 * page.derotation_matrix
    cmd = b"%g %g %g %g %g %g cm " % tuple(mat)
    xref = TOOLS._insert_contents(page, cmd, 0)

    # swap x- and y-coordinates
    if rot in (90, 270):
        x0, y0, x1, y1 = mb
        mb.x0 = y0
        mb.y0 = x0
        mb.x1 = y1
        mb.y1 = x1
        page.set_mediabox(mb)

    page.set_rotation(0)

    # refresh the page to apply these changes
    doc = page.parent
    pno = page.number
    page = doc[pno]
    return page, xref, rot, mediabox


def page_rotation_reset(page, xref, rot, mediabox):
    """Reset page rotation to original values.

    To be used before we return tables."""
    doc = page.parent  # document of the page
    doc.update_stream(xref, b" ")  # remove de-rotation matrix
    page.set_mediabox(mediabox)  # set mediabox to old value
    page.set_rotation(rot)  # set rotation to old value
    pno = page.number
    page = doc[pno]  # update page info
    return page


def find_tables(
    page,
    clip=None,
    vertical_strategy: str = "lines",
    horizontal_strategy: str = "lines",
    vertical_lines: list = None,
    horizontal_lines: list = None,
    snap_tolerance: float = DEFAULT_SNAP_TOLERANCE,
    snap_x_tolerance: float = None,
    snap_y_tolerance: float = None,
    join_tolerance: float = DEFAULT_JOIN_TOLERANCE,
    join_x_tolerance: float = None,
    join_y_tolerance: float = None,
    edge_min_length: float = 3,
    min_words_vertical: float = DEFAULT_MIN_WORDS_VERTICAL,
    min_words_horizontal: float = DEFAULT_MIN_WORDS_HORIZONTAL,
    intersection_tolerance: float = 3,
    intersection_x_tolerance: float = None,
    intersection_y_tolerance: float = None,
    text_tolerance=3,
    text_x_tolerance=3,
    text_y_tolerance=3,
    strategy=None,  # offer abbreviation
    add_lines=None,  # optional user-specified lines
):
    global CHARS, EDGES
    CHARS = []
    EDGES = []
    old_small = bool(TOOLS.set_small_glyph_heights())  # save old value
    TOOLS.set_small_glyph_heights(True)  # we need minimum bboxes
    if page.rotation != 0:
        page, old_xref, old_rot, old_mediabox = page_rotation_set0(page)
    else:
        old_xref, old_rot, old_mediabox = None, None, None

    if snap_x_tolerance is None:
        snap_x_tolerance = UNSET
    if snap_y_tolerance is None:
        snap_y_tolerance = UNSET
    if join_x_tolerance is None:
        join_x_tolerance = UNSET
    if join_y_tolerance is None:
        join_y_tolerance = UNSET
    if intersection_x_tolerance is None:
        intersection_x_tolerance = UNSET
    if intersection_y_tolerance is None:
        intersection_y_tolerance = UNSET
    if strategy is not None:
        vertical_strategy = strategy
        horizontal_strategy = strategy

    settings = {
        "vertical_strategy": vertical_strategy,
        "horizontal_strategy": horizontal_strategy,
        "explicit_vertical_lines": vertical_lines,
        "explicit_horizontal_lines": horizontal_lines,
        "snap_tolerance": snap_tolerance,
        "snap_x_tolerance": snap_x_tolerance,
        "snap_y_tolerance": snap_y_tolerance,
        "join_tolerance": join_tolerance,
        "join_x_tolerance": join_x_tolerance,
        "join_y_tolerance": join_y_tolerance,
        "edge_min_length": edge_min_length,
        "min_words_vertical": min_words_vertical,
        "min_words_horizontal": min_words_horizontal,
        "intersection_tolerance": intersection_tolerance,
        "intersection_x_tolerance": intersection_x_tolerance,
        "intersection_y_tolerance": intersection_y_tolerance,
        "text_tolerance": text_tolerance,
        "text_x_tolerance": text_x_tolerance,
        "text_y_tolerance": text_y_tolerance,
    }
    tset = TableSettings.resolve(settings=settings)
    page.table_settings = tset

    make_chars(page, clip=clip)  # create character list of page
    make_edges(
        page, clip=clip, tset=tset, add_lines=add_lines
    )  # create lines and curves
    tables = TableFinder(page, settings=tset)

    TOOLS.set_small_glyph_heights(old_small)
    if old_xref is not None:
        page = page_rotation_reset(page, old_xref, old_rot, old_mediabox)
    return tables