Code cleanup (#8)

* decrease identation

* no mutable data as default argument

* Update changelog

* Add type hint

Author: ivorbosloper

CHANGELOG.md

@@ -10,6 +10,7 @@ and this project adheres to [Semantic Versioning](http://semver.org/spec/v2.0.0.
 ## [v0.2.3] - 2025-08-26
 
 - Better support for merging schemas
+- Small code improvements
 
 ## [v0.2.2] - 2025-08-25
 

vecorel_cli/conversion/base.py

@@ -243,27 +243,24 @@ def read_data(self, paths, **kwargs):
         return pd.concat(gdfs)
 
     def filter_rows(self, gdf):
-        if len(self.column_filters) > 0:
-            self.info("Applying filters")
-            for key, fn in self.column_filters.items():
-                if key in gdf.columns:
-                    result = fn(gdf[key])
+        if len(self.column_filters) == 0:
+            return gdf
+
+        self.info("Applying filters")
+        for key, fn in self.column_filters.items():
+            if key in gdf.columns:
+                result = fn(gdf[key])
+                if isinstance(result, tuple):
                     # If the result is a tuple, the second value is a flag to potentially invert the mask
-                    if isinstance(result, tuple):
-                        if result[1]:
-                            # Invert mask
-                            mask = ~result[0]
-                        else:
-                            # Use mask as is
-                            mask = result[0]
-                    else:
-                        # Just got a mask, proceed
-                        mask = result
-
-                    # Filter columns based on the mask
-                    gdf = gdf[mask]
+                    mask = ~result[0] if result[1] else result[0]
                 else:
-                    self.warning(f"Column '{key}' not found in dataset, skipping filter")
+                    # Just got a mask, proceed
+                    mask = result
+
+                # Filter columns based on the mask
+                gdf = gdf[mask]
+            else:
+                self.warning(f"Column '{key}' not found in dataset, skipping filter")
         return gdf
 
     def get_title(self):

vecorel_cli/converters.py

@@ -1,5 +1,6 @@
 import importlib
 import os
+from typing import Sequence
 
 import click
 import pandas as pd
@@ -111,7 +112,7 @@ def list_ids(self) -> list:
         ids = [f[:-3] for f in files if self.is_converter(f)]
         return ids
 
-    def list_all(self, keys=["short_name", "license"]) -> dict:
+    def list_all(self, keys: Sequence[str] = ("short_name", "license")) -> dict:
         converters = {}
         for id in self.list_ids():
             obj = {}