Expose parsing/evaluation code

nerval/evaluate.py

@@ -4,6 +4,7 @@ import logging
 import os
 from csv import reader
 from pathlib import Path
+from typing import List
 
 import editdistance
 import edlib
@@ -265,22 +266,11 @@ def compute_scores(
     return scores
 
 
-def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> dict:
-    """Compute recall and precision for each entity type found in annotation and/or prediction.
-
-    Each measure is given at document level, global score is a micro-average across entity types.
-    """
-    # Get string and list of labels per character
-    annot = parse_bio(annotation)
-    predict = parse_bio(prediction)
-
-    if not annot or not predict:
-        raise Exception("No content found in annotation or prediction files.")
-
+def evaluate(annotation: dict, prediction: dict, threshold: int) -> dict:
     # Align annotation and prediction
-    align_result = edlib.align(annot["words"], predict["words"], task="path")
+    align_result = edlib.align(annotation["words"], prediction["words"], task="path")
     nice_alignment = edlib.getNiceAlignment(
-        align_result, annot["words"], predict["words"]
+        align_result, annotation["words"], prediction["words"]
     )
 
     annot_aligned = nice_alignment["query_aligned"]
@@ -288,10 +278,10 @@ def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> di
 
     # Align labels from string alignment
     labels_annot_aligned = get_labels_aligned(
-        annot["words"], annot_aligned, annot["labels"]
+        annotation["words"], annot_aligned, annotation["labels"]
     )
     labels_predict_aligned = get_labels_aligned(
-        predict["words"], predict_aligned, predict["labels"]
+        prediction["words"], predict_aligned, prediction["labels"]
     )
 
     # Get nb match
@@ -304,7 +294,33 @@ def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> di
     )
 
     # Compute scores
-    scores = compute_scores(annot["entity_count"], predict["entity_count"], matches)
+    scores = compute_scores(
+        annotation["entity_count"], prediction["entity_count"], matches
+    )
+    return scores
+
+
+def run(annotation: Path, prediction: Path, threshold: int, verbose: bool) -> dict:
+    """Compute recall and precision for each entity type found in annotation and/or prediction.
+
+    Each measure is given at document level, global score is a micro-average across entity types.
+    """
+
+    # Get string and list of labels per character
+    def read_file(path: Path) -> List[str]:
+        assert path.exists(), f"Error: Input file {path} does not exist"
+        return path.read_text().strip().splitlines()
+
+    logger.info(f"Parsing file @ {annotation}")
+    annot = parse_bio(read_file(annotation))
+
+    logger.info(f"Parsing file @ {prediction}")
+    predict = parse_bio(read_file(prediction))
+
+    if not (annot and predict):
+        raise Exception("No content found in annotation or prediction files.")
+
+    scores = evaluate(annot, predict, threshold)
 
     # Print results
     if verbose:

nerval/parse.py

 # -*- coding: utf-8 -*-
 import re
-from pathlib import Path
+from typing import List
 
 NOT_ENTITY_TAG = "O"
 BEGINNING_POS = ["B", "S", "U"]
@@ -34,12 +34,12 @@ def get_position_label(label: str) -> str:
             else re.match(r"([BIESLU])-(.*)$", label)[1]
         )
     except TypeError:
-        raise (Exception(f"The label {label} is not valid in BIOES/BIOLU format."))
+        raise Exception(f"The label {label} is not valid in BIOES/BIOLU format.")
 
     return pos
 
 
-def parse_line(index: int, line: str, path: Path):
+def parse_line(index: int, line: str):
     try:
         match_iob = REGEX_IOB_LINE.search(line)
 
@@ -47,33 +47,24 @@ def parse_line(index: int, line: str, path: Path):
 
         return match_iob.group(1, 2)
     except AssertionError:
-        raise (
-            Exception(
-                f"The file @ {path} is not in BIO format: check line {index} ({line})"
-            )
-        )
+        raise Exception(f"The file is not in BIO format: check line {index} ({line})")
 
 
-def parse_bio(path: Path) -> dict:
+def parse_bio(lines: List[str]) -> dict:
     """Parse a BIO file to get text content, character-level NE labels and entity types count.
 
-    Input : path to a valid BIO file
-    Output format : { "words": str, "labels": list; "entity_count" : { tag : int } }
+    Input: lines of a valid BIO file
+    Output format: { "words": str, "labels": list, "entity_count": { tag: int } }
     """
-    assert path.exists(), f"Error: Input file {path} does not exist"
-
     words = []
     labels = []
     entity_count = {"All": 0}
     last_tag = None
 
-    with open(path, "r") as fd:
-        lines = list(filter(lambda x: x != "\n", fd.readlines()))
-
     if "§" in " ".join(lines):
         raise (
             Exception(
-                f"§ found in input file {path}. Since this character is used in a specific way during evaluation, prease remove it from files."
+                "§ found in input file. Since this character is used in a specific way during evaluation, prease remove it from files."
             )
         )
 
@@ -82,7 +73,7 @@ def parse_bio(path: Path) -> dict:
     containing_tag = None
 
     for index, line in enumerate(lines):
-        word, label = parse_line(index, line, path)
+        word, label = parse_line(index, line)
 
         # Preserve hyphens to avoid confusion with the hyphens added later during alignment
         word = word.replace("-", "§")

tests/test_parse_bio.py

 # -*- coding: utf-8 -*-
-from pathlib import Path
-
 import pytest
 
 from nerval import evaluate
@@ -181,7 +179,8 @@ expected_parsed_end_of_file = {
     ],
 )
 def test_parse_bio(test_input, expected):
-    assert evaluate.parse_bio(test_input) == expected
+    lines = test_input.read_text().strip().splitlines()
+    assert evaluate.parse_bio(lines) == expected
 
 
 def test_parse_bio_bad_input(bad_bio):
@@ -189,11 +188,6 @@ def test_parse_bio_bad_input(bad_bio):
         evaluate.parse_bio(bad_bio)
 
 
-def test_parse_bio_no_input():
-    with pytest.raises(AssertionError):
-        evaluate.parse_bio(Path("not_a_bio"))
-
-
 @pytest.mark.parametrize(
     "line, word, label",
     (
@@ -204,7 +198,7 @@ def test_parse_bio_no_input():
     ),
 )
 def test_parse_line(line, word, label):
-    assert parse_line(index=0, line=line, path=Path("")) == (word, label)
+    assert parse_line(index=0, line=line) == (word, label)
 
 
 @pytest.mark.parametrize(
@@ -213,7 +207,7 @@ def test_parse_line(line, word, label):
 )
 def test_parse_line_crash(line):
     with pytest.raises(Exception):
-        parse_line(index=0, line=line, path=Path(""))
+        parse_line(index=0, line=line)
 
 
 @pytest.mark.parametrize(