Fix typing and linting

app.py

@@ -41,32 +41,38 @@ def visualize(df_pairwise: pd.DataFrame) -> Figure:
     return fig
 
 
-def counting(xs: list[str], ys: list[str], ws: list[Winner]) -> tuple["pd.Series[str]", "pd.Index[str]"]:
+def counting(xs: "pd.Series[str]", ys: "pd.Series[str]",
+             ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
     result = evalica.counting(xs, ys, ws)
     return result.scores, result.index
 
 
-def bradley_terry(xs: list[str], ys: list[str], ws: list[Winner]) -> tuple["pd.Series[str]", "pd.Index[str]"]:
+def bradley_terry(xs: "pd.Series[str]", ys: "pd.Series[str]",
+                  ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
     result = evalica.bradley_terry(xs, ys, ws, tolerance=TOLERANCE, limit=LIMIT)
     return result.scores, result.index
 
 
-def elo(xs: list[str], ys: list[str], ws: list[Winner]) -> tuple["pd.Series[str]", "pd.Index[str]"]:
+def elo(xs: "pd.Series[str]", ys: "pd.Series[str]",
+        ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
     result = evalica.elo(xs, ys, ws)
     return result.scores, result.index
 
 
-def eigen(xs: list[str], ys: list[str], ws: list[Winner]) -> tuple["pd.Series[str]", "pd.Index[str]"]:
+def eigen(xs: "pd.Series[str]", ys: "pd.Series[str]",
+          ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
     result = evalica.eigen(xs, ys, ws, tolerance=TOLERANCE, limit=LIMIT)
     return result.scores, result.index
 
 
-def pagerank(xs: list[str], ys: list[str], ws: list[Winner]) -> tuple["pd.Series[str]", "pd.Index[str]"]:
+def pagerank(xs: "pd.Series[str]", ys: "pd.Series[str]",
+             ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
     result = evalica.pagerank(xs, ys, ws, tolerance=TOLERANCE, limit=LIMIT)
     return result.scores, result.index
 
 
-def newman(xs: list[str], ys: list[str], ws: list[Winner]) -> tuple["pd.Series[str]", "pd.Index[str]"]:
+def newman(xs: "pd.Series[str]", ys: "pd.Series[str]",
+           ws: "pd.Series[Winner]") -> tuple["pd.Series[str]", "pd.Index[str]"]:  # type: ignore[type-var]
     result = evalica.newman(xs, ys, ws, tolerance=TOLERANCE, limit=LIMIT)
     return result.scores, result.index
 
@@ -115,12 +121,12 @@ def handler(
 
     df_pairs = df_pairs[["left", "right", "winner"]]
 
-    df_pairs.dropna(axis=0, inplace=True)
+    df_pairs = df_pairs.dropna(axis=0)
 
     if filtered:
         largest = largest_strongly_connected_component(df_pairs)
 
-        df_pairs.drop(df_pairs[~(df_pairs["left"].isin(largest) & df_pairs["right"].isin(largest))].index, inplace=True)
+        df_pairs = df_pairs.drop(df_pairs[~(df_pairs["left"].isin(largest) & df_pairs["right"].isin(largest))].index)
 
     xs, ys = df_pairs["left"], df_pairs["right"]
     ws = df_pairs["winner"].map({"left": Winner.X, "right": Winner.Y, "tie": Winner.Draw})
@@ -138,9 +144,9 @@ def handler(
 
     df_result["rank"] = df_result["score"].rank(na_option="bottom", ascending=False).astype(int)
 
-    df_result.fillna(-np.inf, inplace=True)
-    df_result.sort_values(by=["rank", "score"], ascending=[True, False], inplace=True)
-    df_result.reset_index(inplace=True)
+    df_result = df_result.fillna(-np.inf)
+    df_result = df_result.sort_values(by=["rank", "score"], ascending=[True, False])
+    df_result = df_result.reset_index()
 
     if truncated:
         df_result = pd.concat((df_result.head(5), df_result.tail(5)), copy=False)

ruff.toml

@@ -9,6 +9,5 @@ ignore = [
     "EM102",  # f-string-in-exception
     "FBT001", # boolean-type-hint-positional-argument
     "N806",   # non-lowercase-variable-in-function
-    "PD002",  # pandas-use-of-inplace-argument
     "TRY003", # raise-vanilla-args
 ]