Lint

Author: Jaspvr

pandas/io/formats/csvs.py

@@ -11,6 +11,7 @@
     Sequence,
 )
 import csv as csvlib
+import json
 import os
 from typing import (
     TYPE_CHECKING,
@@ -19,7 +20,6 @@
 )
 
 import numpy as np
-import json
 
 from pandas._libs import writers as libwriters
 from pandas._typing import SequenceNotStr
@@ -109,12 +109,11 @@ def __init__(
                         self.obj[col] = self.obj[col].apply(
                             lambda x: json.dumps(x.tolist())
                             if isinstance(x, np.ndarray)
-                            else json.dumps(x) if isinstance(x, list)
+                            else json.dumps(x)
+                            if isinstance(x, list)
                             else x
                         )
 
-
-
     @property
     def na_rep(self) -> str:
         return self.fmt.na_rep

pandas/io/parsers/readers.py

@@ -11,6 +11,7 @@
     defaultdict,
 )
 import csv
+import json
 import sys
 from textwrap import fill
 from typing import (
@@ -25,8 +26,6 @@
 import warnings
 
 import numpy as np
-import pandas as pd
-import json
 
 from pandas._libs import lib
 from pandas._libs.parsers import STR_NA_VALUES
@@ -49,6 +48,7 @@
     pandas_dtype,
 )
 
+import pandas as pd
 from pandas import Series
 from pandas.core.frame import DataFrame
 from pandas.core.indexes.api import RangeIndex
@@ -866,6 +866,7 @@ def _restore_complex_arrays(df: DataFrame) -> None:
     Converted bracketed JSON strings in df back to NumPy arrays.
     eg. "[0.1, 0.2, 0.3]" --> parse into NumPy array.
     """
+
     def looks_like_json_array(x: str) -> bool:
         return x.startswith("[") and x.endswith("]")
 
@@ -874,9 +875,13 @@ def looks_like_json_array(x: str) -> bool:
             nonnull = df[col].dropna()
             if (
                 len(nonnull) > 0
-                and nonnull.apply(lambda x: isinstance(x, str) and looks_like_json_array(x)).all()
+                and nonnull.apply(
+                    lambda x: isinstance(x, str) and looks_like_json_array(x)
+                ).all()
             ):
-                df[col] = df[col].apply(lambda x: np.array(json.loads(x)) if pd.notnull(x) else x)
+                df[col] = df[col].apply(
+                    lambda x: np.array(json.loads(x)) if pd.notnull(x) else x
+                )
 
 
 @overload

scripts/tests/test_csv.py

@@ -1,9 +1,9 @@
 import pandas as pd
+
 print(pd.__file__)
 print(pd.__version__)
 
 import numpy as np
-import os
 
 # # Create a DataFrame with NumPy arrays
 # df = pd.DataFrame({
@@ -35,8 +35,8 @@
 # TEST2
 # Create a DataFrame with NumPy arrays
 df = pd.DataFrame({
-    'id': [1, 2],
-    'embedding': [np.array([0.1, 0.2, 0.3]), np.array([0.4, 0.5, 0.6])]
+    "id": [1, 2],
+    "embedding": [np.array([0.1, 0.2, 0.3]), np.array([0.4, 0.5, 0.6])]
 })
 
 # Save to CSV