Update main.py

main.py

@@ -1,7 +1,37 @@
+import sys
+
+import pandas as pd
+
+from similarity.Comparator import Comparator, SizeComparator, IncompleteColumnsComparator, KindComparator, \
+    ColumnNamesEmbeddingsComparator
+from similarity.DataFrameMetadataCreator import DataFrameMetadataCreator
 
-def compare_datasets(path1, path2):
-    ...
 
+def create_metadata(data):
+    return (DataFrameMetadataCreator(data).
+            compute_advanced_structural_types().
+            compute_column_kind().compute_column_names_embeddings()).get_metadata()
+
+
+def compare_datasets(path1, path2):
+    data1 = pd.read_csv(path1)
+    data2 = pd.read_csv(path2)
+    metadata1 = create_metadata(data1)
+    metadata2 = create_metadata(data2)
+    compartor = (Comparator().add_comparator_type(SizeComparator()).
+                 add_comparator_type(IncompleteColumnsComparator())
+                 .add_comparator_type(KindComparator())
+                 .add_comparator_type(ColumnNamesEmbeddingsComparator()))
+    return compartor.compare(metadata1, metadata2)
 
 if __name__ == '__main__':
-    compare_datasets('data/netflix_titles.csv', 'data/imdb_top_1000.csv')
+    files = sys.argv[1:]
+    print(files)
+    for file1 in files:
+        for file2 in files:
+            if file1 != file2:
+                distance = compare_datasets(file1, file2)
+                print(f"{file1} |< >| {file2} = {distance}")
+    if len(files) == 0:
+        distance = compare_datasets('data/netflix_titles.csv', 'data/imdb_top_1000.csv')
+        print(f"'data/netflix_titles.csv' |< >| 'data/imdb_top_1000.csv' = {distance}")