Use prettytable instead of termtables

.isort.cfg

@@ -7,4 +7,4 @@ use_parentheses = True
 line_length = 120
 
 default_section=FIRSTPARTY
-known_third_party = editdistance,edlib,pytest,setuptools,termtables
+known_third_party = editdistance,edlib,pytest,setuptools,prettytable

README.md

@@ -50,7 +50,7 @@ Counting the spaces, 7 characters differ over 24 characters in the reference ent
 ### Demo
 
 ```
-$ nerval -a demo/bio_folder/demo_annot.bio -p demo/bio_folder/demo_predict.bio
+$ nerval -a demo/demo_annot.bio -p demo/demo_predict.bio
 ```
 
 We also provide two annotation and prediction toy files, which are identical for now and produce perfect scores. Feel free to play with the the text and entity tags in the prediction file to see the impact on the score.
@@ -62,13 +62,13 @@ $ nerval -a demo/toy_test_annot.bio -p demo/toy_test_predict.bio
 You can also indicate a folder and a csv file to have multiple evaluation at once.
 
 ```
-$ nerval -c demo/mapping_file.csv -f demo/bio_folder
+$ nerval -c demo/mapping_file.csv -f demo
 ```
 
 And with the verbose option that's triggered by -v
 
 ```
-$ nerval -a demo/bio_folder/demo_annot.bio -p demo/bio_folder/demo_predict.bio -v
+$ nerval -a demo/demo_annot.bio -p demo/demo_predict.bio -v
 ```
 
 ## Metric

nerval/evaluate.py

 # -*- coding: utf-8 -*-
 
-import glob
 import logging
 import os
 from csv import reader
@@ -8,7 +7,7 @@ from pathlib import Path
 
 import editdistance
 import edlib
-import termtables as tt
+from prettytable import MARKDOWN, PrettyTable
 
 from nerval.parse import (
     BEGINNING_POS,
@@ -324,7 +323,7 @@ def run_multiple(file_csv, folder, threshold, verbose):
         list_cor = list(csv_reader)
 
     if os.path.isdir(folder):
-        list_bio_file = glob.glob(str(folder) + "/**/*.bio", recursive=True)
+        list_bio_file = list(folder.rglob("*.bio"))
 
         count = 0
         precision = 0
@@ -351,17 +350,19 @@ def run_multiple(file_csv, folder, threshold, verbose):
                 raise Exception(f"No file found for files {annot}, {predict}")
         if count:
             logger.info("Average score on all corpus")
-            tt.print(
+            table = PrettyTable()
+            table.field_names = ["Precision", "Recall", "F1"]
+            table.set_style(MARKDOWN)
+            table.add_rows(
                 [
                     [
                         round(precision / count, 3),
                         round(recall / count, 3),
                         round(f1 / count, 3),
                     ]
-                ],
-                ["Precision", "Recall", "F1"],
-                style=tt.styles.markdown,
+                ]
             )
+            print(table)
         else:
             raise Exception("No file were counted")
     else:

nerval/utils.py

 # -*- coding: utf-8 -*-
-import termtables as tt
+from prettytable import MARKDOWN, PrettyTable
 
 
 def print_results(scores: dict):
@@ -25,7 +25,12 @@ def print_results(scores: dict):
                 scores[tag]["Support"],
             ]
         )
-    tt.print(results, header, style=tt.styles.markdown)
+
+    table = PrettyTable()
+    table.field_names = header
+    table.set_style(MARKDOWN)
+    table.add_rows(results)
+    print(table)
 
 
 def print_result_compact(scores: dict):
@@ -41,4 +46,9 @@ def print_result_compact(scores: dict):
             scores["All"]["Support"],
         ]
     ]
-    tt.print(result, header, style=tt.styles.markdown)
+
+    table = PrettyTable()
+    table.field_names = header
+    table.set_style(MARKDOWN)
+    table.add_rows(result)
+    print(table)

requirements.txt

 editdistance==0.6.2
 edlib==1.3.9
-termtables==0.2.4
+prettytable==3.9.0