Black formatting and import optimisation

aretaon · aretaon · commit b160adb14132 · 2026-03-12T14:28:32.000+01:00
diff --git a/autoprot/__init__.py b/autoprot/__init__.py
@@ -1,7 +1,8 @@
 import sys
+
 from . import common
-from . import r_helper
 from . import decorators
+from . import r_helper
 
 __version__ = "dev"
 __author__ = "The autoprot contributors"
@@ -14,4 +15,4 @@
 # write the environment.txt file
 common.generate_environment_txt()
 
-from . import preprocessing
+from . import preprocessing
diff --git a/autoprot/analysis/PCA.py b/autoprot/analysis/PCA.py
@@ -9,15 +9,14 @@
 
 from typing import Union, Literal
 
-import pandas as pd
-import numpy as np
 import matplotlib.pylab as plt
+import numpy as np
+import pandas as pd
 import seaborn as sns
-
+from gprofiler import GProfiler
 from sklearn.decomposition import PCA
-from autoprot import r_helper
 
-from gprofiler import GProfiler
+from autoprot import r_helper
 
 gp = GProfiler(user_agent="autoprot", return_dataframe=True)
 RFUNCTIONS, R = r_helper.return_r_path()
diff --git a/autoprot/analysis/__init__.py b/autoprot/analysis/__init__.py
@@ -1,16 +1,16 @@
+from .PCA import *
 from .clustering import *
 from .functional import *
-from .PCA import *
 from .qc import *
 from .stat_test import *
 from .stats import *
 
 # Optional: define what's exported when someone does `from analysis import *`
 __all__ = [
-    'clustering',
-    'functional',
-    'PCA',
-    'qc',
-    'stat_test',
-    'stats',
-]
+    "clustering",
+    "functional",
+    "PCA",
+    "qc",
+    "stat_test",
+    "stats",
+]
diff --git a/autoprot/analysis/clustering.py b/autoprot/analysis/clustering.py
@@ -16,10 +16,10 @@
 import matplotlib.pylab as plt
 import numpy as np
 import pandas as pd
-from pandas.api.types import is_numeric_dtype
 import seaborn as sns
 from gprofiler import GProfiler
 from numpy.typing import ArrayLike
+from pandas.api.types import is_numeric_dtype
 from scipy import cluster as clst
 from scipy.spatial import distance
 from scipy.stats import zscore
diff --git a/autoprot/analysis/functional.py b/autoprot/analysis/functional.py
@@ -11,15 +11,14 @@
 from importlib import resources
 from typing import Union, Literal, List, Dict, Any, Tuple
 
-import pandas as pd
-import numpy as np
 import matplotlib.pylab as plt
+import numpy as np
+import pandas as pd
 import seaborn as sns
+from gprofiler import GProfiler
 
-from autoprot import visualization as vis
 from autoprot import r_helper
-
-from gprofiler import GProfiler
+from autoprot import visualization as vis
 
 gp = GProfiler(user_agent="autoprot", return_dataframe=True)
 RFUNCTIONS, R = r_helper.return_r_path()
diff --git a/autoprot/analysis/qc.py b/autoprot/analysis/qc.py
@@ -7,20 +7,19 @@
 @documentation: Julian
 """
 
-from typing import Literal
 from datetime import date
+from operator import itemgetter
+from typing import Literal
 
-import pandas as pd
-import numpy as np
 import matplotlib.pylab as plt
-import seaborn as sns
-from operator import itemgetter
 import missingno as msn
+import numpy as np
+import pandas as pd
+import seaborn as sns
+from gprofiler import GProfiler
 
 from autoprot import r_helper
 
-from gprofiler import GProfiler
-
 gp = GProfiler(user_agent="autoprot", return_dataframe=True)
 RFUNCTIONS, R = r_helper.return_r_path()
 
diff --git a/autoprot/analysis/stats.py b/autoprot/analysis/stats.py
@@ -7,15 +7,14 @@
 @documentation: Julian
 """
 
-import pandas as pd
-import numpy as np
 import matplotlib.pylab as plt
+import numpy as np
+import pandas as pd
 import seaborn as sns
+from gprofiler import GProfiler
 
 from autoprot import r_helper
 
-from gprofiler import GProfiler
-
 gp = GProfiler(user_agent="autoprot", return_dataframe=True)
 RFUNCTIONS, R = r_helper.return_r_path()
 
diff --git a/autoprot/preprocessing/__init__.py b/autoprot/preprocessing/__init__.py
@@ -1,18 +1,18 @@
 from .annotation import *
 from .data_handling import *
+from .diann import *
 from .filtering import *
 from .imputation import *
 from .normalization import *
 from .transformation import *
-from .diann import *
 
 # Optional: define what's exported when someone does `from preprocessing import *`
 __all__ = [
-    'annotation',
-    'data_handling',
-    'filtering',
-    'imputation',
-    'normalization',
-    'transformation',
-    'diann'
-]
+    "annotation",
+    "data_handling",
+    "filtering",
+    "imputation",
+    "normalization",
+    "transformation",
+    "diann",
+]
diff --git a/autoprot/preprocessing/annotation.py b/autoprot/preprocessing/annotation.py
@@ -15,15 +15,21 @@
 import numpy as np
 import pandas as pd
 import requests
-
 from Bio import Align
+
 from autoprot import r_helper, common
 from autoprot.decorators import report
 
 RFUNCTIONS, R = r_helper.return_r_path()
 
 # defines which functions are exposed at the module level
-__all__ = ['go_annot', 'motif_annot', 'annotate_phosphosite', 'to_canonical_ps', 'get_subcellular_loc']
+__all__ = [
+    "go_annot",
+    "motif_annot",
+    "annotate_phosphosite",
+    "to_canonical_ps",
+    "get_subcellular_loc",
+]
 
 # =============================================================================
 # Note: When using R functions provided column names might get changed
diff --git a/autoprot/preprocessing/data_handling.py b/autoprot/preprocessing/data_handling.py
@@ -7,14 +7,21 @@
 @documentation: Julian
 """
 
-import pandas as pd
 import os
-import requests
-from urllib import parse
 from ftplib import FTP
+from urllib import parse
+
+import pandas as pd
+import requests
 
 # defines which functions are exposed at the module level
-__all__ = ['read_csv', 'to_csv', 'download_from_ftp', 'fetch_from_pride',]
+__all__ = [
+    "read_csv",
+    "to_csv",
+    "download_from_ftp",
+    "fetch_from_pride",
+]
+
 
 def read_csv(file, sep="\t", low_memory=False, **kwargs):
     r"""
diff --git a/autoprot/preprocessing/diann.py b/autoprot/preprocessing/diann.py
@@ -1,12 +1,14 @@
+import multiprocessing
 import time
 from concurrent.futures import ThreadPoolExecutor, as_completed
-import multiprocessing
 from itertools import combinations
+
 import numpy as np
 import pandas as pd
 
 # defines which functions are exposed at the module level
-__all__ = ['load_parquet', 'parquet_to_pg', 'silac_protein_group_from_diann']
+__all__ = ["load_parquet", "parquet_to_pg", "silac_protein_group_from_diann"]
+
 
 def load_parquet(
     path, filters: dict = None, mbr: bool = True, crap_str: str | list[str] = "cRAP"
diff --git a/autoprot/preprocessing/filtering.py b/autoprot/preprocessing/filtering.py
@@ -8,18 +8,24 @@
 """
 
 import functools
+from typing import Literal
 
 import numpy as np
 import pandas as pd
-from typing import Literal
 
-from autoprot.decorators import report
 from autoprot import r_helper
+from autoprot.decorators import report
 
 RFUNCTIONS, R = r_helper.return_r_path()
 
 # defines which functions are exposed at the module level
-__all__ = ['cleaning', 'filter_loc_prob', 'filter_seq_cov', 'filter_vv', 'remove_non_quant']
+__all__ = [
+    "cleaning",
+    "filter_loc_prob",
+    "filter_seq_cov",
+    "filter_vv",
+    "remove_non_quant",
+]
 
 # =============================================================================
 # Note: When using R functions provided column names might get changed
diff --git a/autoprot/preprocessing/imputation.py b/autoprot/preprocessing/imputation.py
@@ -7,17 +7,19 @@
 @documentation: Julian
 """
 
-import numpy as np
-import pandas as pd
 from subprocess import run, PIPE, STDOUT
 from typing import Union
-from autoprot import r_helper
+
+import numpy as np
+import pandas as pd
+
 from autoprot import preprocessing as pp
+from autoprot import r_helper
 
 RFUNCTIONS, R = r_helper.return_r_path()
 
 # defines which functions are exposed at the module level
-__all__ = ['imp_min_prob', 'imp_median', 'imp_seq', 'dima']
+__all__ = ["imp_min_prob", "imp_median", "imp_seq", "dima"]
 # =============================================================================
 # Note: When using R functions provided column names might get changed
 # Especially, do not use +,- or spaces in your column names. Maybe write decorator to
diff --git a/autoprot/preprocessing/normalization.py b/autoprot/preprocessing/normalization.py
@@ -7,17 +7,19 @@
 @documentation: Julian
 """
 
-import numpy as np
-import pandas as pd
 import os
 from typing import Union, Literal, Tuple, List
-from autoprot import r_helper
+
+import numpy as np
+import pandas as pd
+
 from autoprot import preprocessing as pp
+from autoprot import r_helper
 
 RFUNCTIONS, R = r_helper.return_r_path()
 
 # defines which functions are exposed at the module level
-__all__ = ['loading_norm', 'quantile_norm', 'vsn', 'cyclic_loess', 'norm_to_prot']
+__all__ = ["loading_norm", "quantile_norm", "vsn", "cyclic_loess", "norm_to_prot"]
 
 # =============================================================================
 # Note: When using R functions provided column names might get changed
diff --git a/autoprot/preprocessing/transformation.py b/autoprot/preprocessing/transformation.py
@@ -20,21 +20,25 @@
 
 import numpy as np
 import pandas as pd
-from pandas.core.groupby.generic import DataFrameGroupBy
 import requests
-from pandas.core.groupby import DataFrameGroupBy
+from pandera.typing import DataFrame as PandasDataFrame
 from scipy import stats
 from scipy.stats import pearsonr, spearmanr
 from sklearn.metrics import auc
 
-from pandera.typing import Series as PandasSeries
-from pandera.typing import DataFrame as PandasDataFrame
-
 from autoprot import r_helper, common
 
 RFUNCTIONS, R = r_helper.return_r_path()
 # defines which functions are exposed at the module level
-__all__ = ['log', 'expand_site_table', 'collapse_rows', 'exp_semi_col', 'merge_semi_cols', 'calculate_iBAQ', 'merge_semi_cols']
+__all__ = [
+    "log",
+    "expand_site_table",
+    "collapse_rows",
+    "exp_semi_col",
+    "merge_semi_cols",
+    "calculate_iBAQ",
+    "merge_semi_cols",
+]
 
 # =============================================================================
 # Note: When using R functions provided column names might get changed
@@ -128,8 +132,10 @@ def log(
     try:
         keep = df[cols] > 0
     except TypeError:
-        raise TypeError(f"[log] Could not mask negative an NaN values in columns {', '.join(cols)}."
-                        f" Please check if they are all numerical.")
+        raise TypeError(
+            f"[log] Could not mask negative an NaN values in columns {', '.join(cols)}."
+            f" Please check if they are all numerical."
+        )
 
     # Apply log transformation to all columns at once
     log_values = np.log(df[cols].where(keep)) / np.log(base)
diff --git a/autoprot/visualization/__init__.py b/autoprot/visualization/__init__.py
@@ -1,10 +1,10 @@
 from .annotation import *
-from .qc import *
 from .basic import *
+from .qc import *
 
 # Optional: define what's exported when someone does `from visualization import *`
 __all__ = [
-    'annotation',
-    'qc',
-    'basic',
-]
+    "annotation",
+    "qc",
+    "basic",
+]
diff --git a/autoprot/visualization/annotation.py b/autoprot/visualization/annotation.py
diff --git a/autoprot/visualization/qc.py b/autoprot/visualization/qc.py
