Add x_tolerance_ratio param to extract_text and similar functions (now properly linted!)

README.md

@@ -327,9 +327,9 @@ If you're using `pdfplumber` on a Debian-based system and encounter a `PolicyErr
 
 | Method | Description |
 |--------|-------------|
-|`.extract_text(x_tolerance=3, y_tolerance=3, layout=False, x_density=7.25, y_density=13, **kwargs)`| Collates all of the page's character objects into a single string.<ul><li><p>When `layout=False`: Adds spaces where the difference between the `x1` of one character and the `x0` of the next is greater than `x_tolerance`. Adds newline characters where the difference between the `doctop` of one character and the `doctop` of the next is greater than `y_tolerance`.</p></li><li><p>When `layout=True` (*experimental feature*): Attempts to mimic the structural layout of the text on the page(s), using `x_density` and `y_density` to determine the minimum number of characters/newlines per "point," the PDF unit of measurement. All remaining `**kwargs` are passed to `.extract_words(...)` (see below), the first step in calculating the layout.</p></li></ul>|
+|`.extract_text(x_tolerance=3, x_tolerance_ratio=None, y_tolerance=3, layout=False, x_density=7.25, y_density=13, **kwargs)`| Collates all of the page's character objects into a single string.<ul><li><p>When `layout=False`: Adds spaces where the difference between the `x1` of one character and the `x0` of the next is greater than `x_tolerance`. (If `x_tolerance_ratio` is not `None`, the extractor uses a dynamic `x_tolerance` equal to `x_tolerance_ratio * previous_character["size"]`.) Adds newline characters where the difference between the `doctop` of one character and the `doctop` of the next is greater than `y_tolerance`.</p></li><li><p>When `layout=True` (*experimental feature*): Attempts to mimic the structural layout of the text on the page(s), using `x_density` and `y_density` to determine the minimum number of characters/newlines per "point," the PDF unit of measurement. All remaining `**kwargs` are passed to `.extract_words(...)` (see below), the first step in calculating the layout.</p></li></ul>|
 |`.extract_text_simple(x_tolerance=3, y_tolerance=3)`| A slightly faster but less flexible version of `.extract_text(...)`, using a simpler logic.|
-|`.extract_words(x_tolerance=3, y_tolerance=3, keep_blank_chars=False, use_text_flow=False, horizontal_ltr=True, vertical_ttb=True, extra_attrs=[], split_at_punctuation=False, expand_ligatures=True)`| Returns a list of all word-looking things and their bounding boxes. Words are considered to be sequences of characters where (for "upright" characters) the difference between the `x1` of one character and the `x0` of the next is less than or equal to `x_tolerance` *and* where the `doctop` of one character and the `doctop` of the next is less than or equal to `y_tolerance`. A similar approach is taken for non-upright characters, but instead measuring the vertical, rather than horizontal, distances between them. The parameters `horizontal_ltr` and `vertical_ttb` indicate whether the words should be read from left-to-right (for horizontal words) / top-to-bottom (for vertical words). Changing `keep_blank_chars` to `True` will mean that blank characters are treated as part of a word, not as a space between words. Changing `use_text_flow` to `True` will use the PDF's underlying flow of characters as a guide for ordering and segmenting the words, rather than presorting the characters by x/y position. (This mimics how dragging a cursor highlights text in a PDF; as with that, the order does not always appear to be logical.) Passing a list of `extra_attrs`  (e.g., `["fontname", "size"]` will restrict each words to characters that share exactly the same value for each of those [attributes](#char-properties), and the resulting word dicts will indicate those attributes. Setting `split_at_punctuation` to `True` will enforce breaking tokens at punctuations specified by `string.punctuation`; or you can specify the list of separating punctuation by pass a string, e.g., <code>split_at_punctuation='!"&\'()*+,.:;<=>?@[\]^\`\{\|\}~'</code>. Unless you set `expand_ligatures=False`, ligatures such as `fi` will be expanded into their constituent letters (e.g., `fi`).|
+|`.extract_words(x_tolerance=3, x_tolerance_ratio=None, y_tolerance=3, keep_blank_chars=False, use_text_flow=False, horizontal_ltr=True, vertical_ttb=True, extra_attrs=[], split_at_punctuation=False, expand_ligatures=True)`| Returns a list of all word-looking things and their bounding boxes. Words are considered to be sequences of characters where (for "upright" characters) the difference between the `x1` of one character and the `x0` of the next is less than or equal to `x_tolerance` *and* where the `doctop` of one character and the `doctop` of the next is less than or equal to `y_tolerance`. (If `x_tolerance_ratio` is not `None`, the extractor uses a dynamic `x_tolerance` equal to `x_tolerance_ratio * previous_character["size"]`.) A similar approach is taken for non-upright characters, but instead measuring the vertical, rather than horizontal, distances between them. The parameters `horizontal_ltr` and `vertical_ttb` indicate whether the words should be read from left-to-right (for horizontal words) / top-to-bottom (for vertical words). Changing `keep_blank_chars` to `True` will mean that blank characters are treated as part of a word, not as a space between words. Changing `use_text_flow` to `True` will use the PDF's underlying flow of characters as a guide for ordering and segmenting the words, rather than presorting the characters by x/y position. (This mimics how dragging a cursor highlights text in a PDF; as with that, the order does not always appear to be logical.) Passing a list of `extra_attrs`  (e.g., `["fontname", "size"]` will restrict each words to characters that share exactly the same value for each of those [attributes](#char-properties), and the resulting word dicts will indicate those attributes. Setting `split_at_punctuation` to `True` will enforce breaking tokens at punctuations specified by `string.punctuation`; or you can specify the list of separating punctuation by pass a string, e.g., <code>split_at_punctuation='!"&\'()*+,.:;<=>?@[\]^\`\{\|\}~'</code>. Unless you set `expand_ligatures=False`, ligatures such as `fi` will be expanded into their constituent letters (e.g., `fi`).|
 |`.extract_text_lines(layout=False, strip=True, return_chars=True, **kwargs)`|*Experimental feature* that returns a list of dictionaries representing the lines of text on the page. The `strip` parameter works analogously to Python's `str.strip()` method, and returns `text` attributes without their surrounding whitespace. (Only relevant when `layout = True`.) Setting `return_chars` to `False` will exclude the individual character objects from the returned text-line dicts. The remaining `**kwargs` are those you would pass to `.extract_text(layout=True, ...)`.|
 |`.search(pattern, regex=True, case=True, main_group=0, return_groups=True, return_chars=True, layout=False, **kwargs)`|*Experimental feature* that allows you to search a page's text, returning a list of all instances that match the query. For each instance, the response dictionary object contains the matching text, any regex group matches, the bounding box coordinates, and the char objects themselves. `pattern` can be a compiled regular expression, an uncompiled regular expression, or a non-regex string. If `regex` is `False`, the pattern is treated as a non-regex string. If `case` is `False`, the search is performed in a case-insensitive manner. Setting `main_group` restricts the results to a specific regex group within the `pattern` (default of `0` means the entire match). Setting `return_groups` and/or `return_chars` to `False` will exclude the lists of the matched regex groups and/or characters from being added (as `"groups"` and `"chars"` to the return dicts). The `layout` parameter operates as it does for `.extract_text(...)`. The remaining `**kwargs` are those you would pass to `.extract_text(layout=True, ...)`. __Note__: Zero-width and all-whitespace matches are discarded, because they (generally) have no explicit position on the page. |
 |`.dedupe_chars(tolerance=1)`| Returns a version of the page with duplicate chars — those sharing the same text, fontname, size, and positioning (within `tolerance` x/y) as other characters — removed. (See [Issue #71](https://github.com/jsvine/pdfplumber/issues/71) to understand the motivation.)|

pdfplumber/utils/text.py

@@ -305,8 +305,8 @@ def __init__(
         expand_ligatures: bool = True,
     ):
         self.x_tolerance = x_tolerance
-        self.x_tolerance_ratio = x_tolerance_ratio
         self.y_tolerance = y_tolerance
+        self.x_tolerance_ratio = x_tolerance_ratio
         self.y_tolerance_ratio = y_tolerance_ratio
         self.keep_blank_chars = keep_blank_chars
         self.use_text_flow = use_text_flow
@@ -348,34 +348,12 @@ def merge_chars(self, ordered_chars: T_obj_list) -> T_obj:
 
         return word
 
-    def set_tolerances_from_ratio(
-        self, t: T_obj, axis_range: Union[str, List[str]] = "x"
-    ) -> None:
-        """
-        If there is a `tolerance_ratio` for any axis...
-        overrides the tolerance with ratio * size of `t`.
-        Allows for dynamic tolerances ...
-        react to different text sizes within a single call.
-
-        ie:
-        If `x_tolerance_ratio=0.15`... set `self.x_tolerance` to
-        `set_tolerance(t, x_tolerance_ratio)`
-
-        `axis_range`:
-        restricts this to `x_tolerance`
-        (until `y_tolerance` gets implemented (if ever).)
-        """
-        for i in axis_range:
-            if self.__getattribute__(f"{i}_tolerance_ratio") is not None:
-                self.__setattr__(
-                    f"{i}_tolerance",
-                    set_tolerance(t, self.__getattribute__(f"{i}_tolerance_ratio")),
-                )
-
     def char_begins_new_word(
         self,
         prev_char: T_obj,
         curr_char: T_obj,
+        x_tolerance: T_num,
+        y_tolerance: T_num,
     ) -> bool:
         """This method takes several factors into account to determine if
         `curr_char` represents the beginning of a new word:
@@ -408,13 +386,11 @@ def char_begins_new_word(
         compare, while horizontal_ltr/vertical_ttb determine the direction
         of the comparison.
         """
-        self.set_tolerances_from_ratio(curr_char)
-
         # 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
+            x = x_tolerance
+            y = y_tolerance
             ay = prev_char["top"]
             cy = curr_char["top"]
             if self.horizontal_ltr:
@@ -427,8 +403,8 @@ def char_begins_new_word(
                 cx = -curr_char["x1"]
 
         else:
-            x = self.y_tolerance
-            y = self.x_tolerance
+            x = y_tolerance
+            y = x_tolerance
             ay = prev_char["x0"]
             cy = curr_char["x0"]
             if self.vertical_ttb:
@@ -463,6 +439,10 @@ def start_next_word(
 
             current_word = [] if new_char is None else [new_char]
 
+        xt = self.x_tolerance
+        xtr = self.x_tolerance_ratio
+        yt = self.y_tolerance
+
         for char in ordered_chars:
             text = char["text"]
 
@@ -473,7 +453,12 @@ def start_next_word(
                 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):
+            elif current_word and self.char_begins_new_word(
+                current_word[-1],
+                char,
+                x_tolerance=(xt if xtr is None else xtr * current_word[-1]["size"]),
+                y_tolerance=yt,
+            ):
                 yield from start_next_word(char)
 
             else:
@@ -491,7 +476,6 @@ def upright_key(x: T_obj) -> int:
             upright = upright_cluster[0]["upright"]
             cluster_key = "doctop" if upright else "x0"
 
-            self.set_tolerances_from_ratio(upright_cluster[0])
             # Cluster by line
             subclusters = cluster_objects(
                 upright_cluster, itemgetter(cluster_key), self.y_tolerance
@@ -613,7 +597,3 @@ def yield_unique_chars(chars: T_obj_list) -> Generator[T_obj, None, None]:
 
     deduped = yield_unique_chars(chars)
     return sorted(deduped, key=chars.index)
-
-
-def set_tolerance(t: T_obj, tolerance_ratio: Union[float, int]) -> Any:
-    return tolerance_ratio * (t["bottom"] - t["top"])

tests/test_utils.py

@@ -66,11 +66,14 @@ def test_decode_psl_list(self):
 
     def test_x_tolerance_ratio(self):
         pdf = pdfplumber.open(os.path.join(HERE, "pdfs/issue-987-test.pdf"))
-        assert pdf.pages[0].extract_text() == "Big Te xt\nSmall Text"
-        assert pdf.pages[0].extract_text(x_tolerance=4) == "Big Te xt\nSmallText"
-        assert (
-            pdf.pages[0].extract_text(x_tolerance_ratio=0.15) == "Big Text\nSmall Text"
-        )
+        page = pdf.pages[0]
+
+        assert page.extract_text() == "Big Te xt\nSmall Text"
+        assert page.extract_text(x_tolerance=4) == "Big Te xt\nSmallText"
+        assert page.extract_text(x_tolerance_ratio=0.15) == "Big Text\nSmall Text"
+
+        words = page.extract_words(x_tolerance_ratio=0.15)
+        assert "|".join(w["text"] for w in words) == "Big|Text|Small|Text"
 
     def test_extract_words(self):
         path = os.path.join(HERE, "pdfs/issue-192-example.pdf")