Improved paragraph algorithm

.github/workflows/ci.yml

@@ -25,16 +25,16 @@ jobs:
           pip install torch --index-url https://download.pytorch.org/whl/cpu
           pip install ./
           pip list
-      - name: download model
+      - name: download models
         run: |
           python -m spacy download en_core_web_md
-          pip install https://huggingface.co/kormilitzin/en_core_med7_lg/resolve/main/en_core_med7_lg-any-py3-none-any.whl
+          pip install -r requirements.txt
       - name: run pytest
         run: pytest ./tests/*
-      - name: install ruff
+      - name: Install ruff
         run: pip install ruff
-      - name: ruff format
+      - name: Lint with ruff
         run: |
-          ruff format
+          ruff --output-format=github .
           ruff check --fix
-        continue-on-error: true
+        continue-on-error: true

requirements.txt

@@ -0,0 +1 @@
+https://huggingface.co/kormilitzin/en_core_med7_lg/resolve/main/en_core_med7_lg-any-py3-none-any.whl

src/miade/note.py

@@ -1,67 +1,30 @@
 import re
-import io
-import pkgutil
 import logging
-import pandas as pd
 
 from typing import List, Optional, Dict
 
-from .paragraph import Paragraph, ParagraphType
+from .paragraph import ListItem, NumberedList, Paragraph, ParagraphType
 
 
 log = logging.getLogger(__name__)
 
 
-def load_regex_config_mappings(filename: str) -> Dict:
-    """
-    Load regex configuration mappings from a file.
-
-    Args:
-        filename (str): The name of the file containing the regex configuration.
-
-    Returns:
-        A dictionary mapping paragraph types to their corresponding regex patterns.
-    """
-    regex_config = pkgutil.get_data(__name__, filename)
-    data = (
-        pd.read_csv(
-            io.BytesIO(regex_config),
-            index_col=0,
-        )
-        .squeeze("columns")
-        .T.to_dict()
-    )
-    regex_lookup = {}
-
-    for paragraph, regex in data.items():
-        paragraph_enum = None
-        try:
-            paragraph_enum = ParagraphType(paragraph)
-        except ValueError as e:
-            log.warning(e)
-
-        if paragraph_enum is not None:
-            regex_lookup[paragraph_enum] = regex
-
-    return regex_lookup
-
-
 class Note(object):
     """
-    Represents a note object.
+    Represents a Note object
 
     Attributes:
         text (str): The text content of the note.
         raw_text (str): The raw text content of the note.
-        regex_config (str): The path to the regex configuration file.
-        paragraphs (Optional[List[Paragraph]]): A list of paragraphs in the note.
+        paragraphs (Optional[List[Paragraph]]): A list of Paragraph objects representing the paragraphs in the note.
+        numbered_lists (Optional[List[NumberedList]]): A list of NumberedList objects representing the numbered lists in the note.
     """
 
-    def __init__(self, text: str, regex_config_path: str = "./data/regex_para_chunk.csv"):
+    def __init__(self, text: str):
         self.text = text
         self.raw_text = text
-        self.regex_config = load_regex_config_mappings(regex_config_path)
         self.paragraphs: Optional[List[Paragraph]] = []
+        self.numbered_lists: Optional[List[NumberedList]] = []
 
     def clean_text(self) -> None:
         """
@@ -83,14 +46,61 @@ def clean_text(self) -> None:
         # Remove spaces if the entire line (between two line breaks) is just spaces
         self.text = re.sub(r"(?<=\n)\s+(?=\n)", "", self.text)
 
-    def get_paragraphs(self) -> None:
+    def get_numbered_lists(self):
         """
-        Splits the note into paragraphs.
+        Finds multiple lists of sequentially ordered numbers (with more than one item) that directly follow a newline character
+        and captures the text following these numbers up to the next newline.
 
-        This method splits the text content of the note into paragraphs based on double line breaks.
-        It also assigns a paragraph type to each paragraph based on matching patterns in the heading.
+        Parameters:
+            text (str): The input text in which to search for multiple lists of sequentially ordered numbers with more than one item and their subsequent text.
+
+        Returns:
+            list of lists: Each sublist contains tuples where each tuple includes the start index of the number,
+            the end index of the line, and the captured text for each valid sequentially ordered list found. Returns an empty list if no such patterns are found.
         """
+        # Regular expression to find numbers followed by any characters until a newline
+        pattern = re.compile(r"(?<=\n)(\d+.*)")
+
+        # Finding all matches
+        matches = pattern.finditer(self.text)
+
+        all_results = []
+        results = []
+        last_num = 0
+        for match in matches:
+            number_text = match.group(1)
+            current_num = int(re.search(r"^\d+", number_text).group())
+
+            # Check if current number is the next in sequence
+            if current_num == last_num + 1:
+                results.append(ListItem(content=number_text, start=match.start(1), end=match.end(1)))
+            else:
+                # If there is a break in the sequence, check if current list has more than one item
+                if len(results) > 1:
+                    numbered_list = NumberedList(items=results, list_start=results[0].start, list_end=results[-1].end)
+                    all_results.append(numbered_list)
+                results = [
+                    ListItem(content=number_text, start=match.start(1), end=match.end(1))
+                ]  # Start new results list with the current match
+            last_num = current_num  # Update last number to the current
+
+        # Add the last sequence if not empty and has more than one item
+        if len(results) > 1:
+            numbered_list = NumberedList(items=results, list_start=results[0].start, list_end=results[-1].end)
+            all_results.append(numbered_list)
+
+        self.numbered_lists = all_results
+
+    def get_paragraphs(self, paragraph_regex: Dict) -> None:
+        """
+        Split the text into paragraphs and assign paragraph types based on regex patterns.
+
+        Args:
+            paragraph_regex (Dict): A dictionary containing paragraph types as keys and regex patterns as values.
 
+        Returns:
+            None
+        """
         paragraphs = re.split(r"\n\n+", self.text)
         start = 0
 
@@ -117,12 +127,126 @@ def get_paragraphs(self) -> None:
             if heading:
                 heading = heading.lower()
                 # Iterate through the dictionary items and patterns
-                for paragraph_type, pattern in self.regex_config.items():
+                for paragraph_type, pattern in paragraph_regex.items():
                     if re.search(pattern, heading):
                         paragraph.type = paragraph_type
                         break  # Exit the loop if a match is found
 
             self.paragraphs.append(paragraph)
 
+    def merge_prose_sections(self) -> None:
+        """
+        Merges consecutive prose sections in the paragraphs list.
+
+        Returns:
+            A list of merged prose sections.
+        """
+        is_merge = False
+        all_prose = []
+        prose_section = []
+        prose_indices = []
+
+        for i, paragraph in enumerate(self.paragraphs):
+            if paragraph.type == ParagraphType.prose:
+                if is_merge:
+                    prose_section.append((i, paragraph))
+                else:
+                    prose_section = [(i, paragraph)]
+                    is_merge = True
+            else:
+                if len(prose_section) > 0:
+                    all_prose.append(prose_section)
+                    prose_indices.extend([idx for idx, _ in prose_section])
+                is_merge = False
+
+        if len(prose_section) > 0:
+            all_prose.append(prose_section)
+            prose_indices.extend([idx for idx, _ in prose_section])
+
+        new_paragraphs = self.paragraphs[:]
+
+        for section in all_prose:
+            start = section[0][1].start
+            end = section[-1][1].end
+            new_prose_para = Paragraph(
+                heading=self.text[start:end], body="", type=ParagraphType.prose, start=start, end=end
+            )
+
+            # Replace the first paragraph in the section with the new merged paragraph
+            first_idx = section[0][0]
+            new_paragraphs[first_idx] = new_prose_para
+
+            # Mark other paragraphs in the section for deletion
+            for _, paragraph in section[1:]:
+                index = self.paragraphs.index(paragraph)
+                new_paragraphs[index] = None
+
+        # Remove the None entries from new_paragraphs
+        self.paragraphs = [para for para in new_paragraphs if para is not None]
+
+    def merge_empty_non_prose_with_next_prose(self) -> None:
+        """
+        This method checks if a Paragraph has an empty body and a type that is not prose,
+        and merges it with the next Paragraph if the next paragraph is type prose.
+
+        Returns:
+            None
+        """
+        merged_paragraphs = []
+        skip_next = False
+
+        for i in range(len(self.paragraphs) - 1):
+            if skip_next:
+                # Skip this iteration because the previous iteration already handled merging
+                skip_next = False
+                continue
+
+            current_paragraph = self.paragraphs[i]
+            next_paragraph = self.paragraphs[i + 1]
+
+            # Check if current paragraph has an empty body and is not of type prose
+            if current_paragraph.body == "" and current_paragraph.type != ParagraphType.prose:
+                # Check if the next paragraph is of type prose
+                if next_paragraph.type == ParagraphType.prose:
+                    # Create a new Paragraph with merged content and type prose
+                    merged_paragraph = Paragraph(
+                        heading=current_paragraph.heading,
+                        body=next_paragraph.heading,
+                        type=current_paragraph.type,
+                        start=current_paragraph.start,
+                        end=next_paragraph.end,
+                    )
+                    merged_paragraphs.append(merged_paragraph)
+                    # Skip the next paragraph since it's already merged
+                    skip_next = True
+                    continue
+
+            # If no merging is done, add the current paragraph to the list
+            merged_paragraphs.append(current_paragraph)
+
+        # Handle the last paragraph if it wasn't merged
+        if not skip_next:
+            merged_paragraphs.append(self.paragraphs[-1])
+
+        # Update the paragraphs list with the merged paragraphs
+        self.paragraphs = merged_paragraphs
+
+    def process(self, lookup_dict: Dict, refine: bool = True):
+        """
+        Process the note by cleaning the text, extracting numbered lists, and getting paragraphs based on a lookup dictionary.
+
+        Args:
+            lookup_dict (Dict): A dictionary used to lookup specific paragraphs.
+            refine (bool, optional): Flag indicating whether to refine the processed note - this will merge any consecutive prose
+            paragraphs and then merge any structured paragraphs with empty body with the next prose paragraph (handles line break
+            between heading and body). Defaults to True.
+        """
+        self.clean_text()
+        self.get_numbered_lists()
+        self.get_paragraphs(lookup_dict)
+        if refine:
+            self.merge_prose_sections()
+            self.merge_empty_non_prose_with_next_prose()
+
     def __str__(self):
         return self.text

src/miade/paragraph.py

@@ -1,4 +1,5 @@
 from enum import Enum
+from typing import List
 
 
 class ParagraphType(Enum):
@@ -27,14 +28,58 @@ class Paragraph(object):
     """
 
     def __init__(self, heading: str, body: str, type: ParagraphType, start: int, end: int):
-        self.heading = heading
-        self.body = body
-        self.type = type
-        self.start = start
-        self.end = end
+        self.heading: str = heading
+        self.body: str = body
+        self.type: ParagraphType = type
+        self.start: int = start
+        self.end: int = end
 
     def __str__(self):
         return str(self.__dict__)
 
     def __eq__(self, other):
         return self.type == other.type and self.start == other.start and self.end == other.end
+
+
+class ListItem(object):
+    """
+    Represents an item in a NumberedList
+
+    Attributes:
+        content (str): The content of the list item.
+        start (int): The starting index of the list item.
+        end (int): The ending index of the list item.
+    """
+
+    def __init__(self, content: str, start: int, end: int) -> None:
+        self.content: str = content
+        self.start: int = start
+        self.end: int = end
+
+    def __str__(self):
+        return str(self.__dict__)
+
+    def __eq__(self, other):
+        return self.start == other.start and self.end == other.end
+
+
+class NumberedList(object):
+    """
+    Represents a numbered list.
+
+    Attributes:
+        items (List[ListItem]): The list of items in the numbered list.
+        list_start (int): The starting number of the list.
+        list_end (int): The ending number of the list.
+    """
+
+    def __init__(self, items: List[ListItem], list_start: int, list_end: int) -> None:
+        self.list_start: int = list_start
+        self.list_end: int = list_end
+        self.items: List[ListItem] = items
+
+    def __str__(self):
+        return str(self.__dict__)
+
+    def __eq__(self, other):
+        return self.list_start == other.list_start and self.list_end == other.list_end