Enable Ruff linting rules (Bugbear, Pyupgrade, Ruff...)

pyglider/__init__.py

@@ -1 +0,0 @@
-# -*- coding: utf-8 -*-

pyglider/ncprocess.py

@@ -183,7 +183,7 @@ def extract_timeseries_profiles(inname, outdir, deploymentyaml, force=False):
 
                 # add traj_strlen using bare ntcdf to make IOOS happy
                 with netCDF4.Dataset(outname, 'r+') as nc:
-                    nc.renameDimension('string%d' % trajlen, 'traj_strlen')
+                    nc.renameDimension(f'string{trajlen}', 'traj_strlen')
 
 
 def make_gridfiles(

pyglider/seaexplorer.py

@@ -1,4 +1,3 @@
-# -*- coding: utf-8 -*-
 """
 SeaExplorer-specific processing routines.
 """
@@ -21,8 +20,8 @@ def _outputname(f, outdir):
     fnout = os.path.basename(f)
     fns = fnout.split('.')
     fns = fns[:5]
-    fns[4] = '%04d' % int(fns[4])
-    fns[1] = '%04d' % int(fns[1])
+    fns[4] = f'{int(fns[4]):04d}'
+    fns[1] = f'{int(fns[1]):04d}'
     fnout = ''
     for ff in fns:
         fnout += ff.lower() + '.'
@@ -128,7 +127,7 @@ def raw_to_rawnc(
                 # If no files of this type found, try the next type
                 continue
 
-            for ind, f in enumerate(files):
+            for f in files:
                 # output name:
                 fnout, filenum = _outputname(f, outdir)
                 _log.info(f'{f} to {fnout}')
@@ -573,4 +572,4 @@ def raw_to_timeseries(
 raw_to_L1timeseries = raw_to_L0timeseries = raw_to_timeseries
 merge_rawnc = merge_parquet
 
-__all__ = ['raw_to_rawnc', 'merge_parquet', 'raw_to_timeseries']
+__all__ = ['merge_parquet', 'raw_to_rawnc', 'raw_to_timeseries']

pyglider/slocum.py

@@ -160,7 +160,7 @@
     activeSensorList = [{} for i in range(nsensors_used)]
     outlines = []
     sensorInfo = {}
-    for i in range(nsensors_total):
+    for _ in range(nsensors_total):
         line = dfh.readline().decode('utf-8')
         if line.split(':')[0] != 's':
             raise ValueError('Failed to parse sensor info')
@@ -264,7 +264,7 @@
         # read the cache first.  If its not there, try to make one....
         try:
             activeSensorList, sensorInfo = _get_cached_sensorlist(cachedir, meta)
-        except FileNotFoundError:
+        except FileNotFoundError as e:
             if localcache:
                 _log.info('No cache file found; trying to create one')
                 _make_cache(outlines, cachedir, meta)
@@ -275,7 +275,7 @@
                     'offloaddir/Science/STATE/CACHE/ or ',
                     'offloaddir/Main_board/STATE/CACHE/. ',
                     f'Copy those locally into {cachedir}',
-                )
+                ) from e
         meta['activeSensorList'] = activeSensorList
         # get the file's timestamp...
         meta['_dbdfiletimestamp'] = os.path.getmtime(filename)
@@ -441,8 +441,8 @@
 
     proctimeend = time.time()
     _log.info(
-        ('%s lines of data read from %s, data rate of %s rows ' 'per second')
-        % (len(data), dinkum_file, len(data) / (proctimeend - proctimestart))
+        f'{len(data)} lines of data read from {dinkum_file}, data rate of {len(data) / (proctimeend - proctimestart)} rows '
+        'per second'
     )
     dfh.close()
 
@@ -605,7 +605,7 @@
         # make a long string for activeSensorList:
         listst = ''
         for sensor in meta['activeSensorList']:
-            listst += '%s' % sensor
+            listst += str(sensor)
             listst += '\n'
         ds.attrs['activeSensorList'] = listst
 
@@ -1128,7 +1128,7 @@
     for fn in files:
         found_time = False
 
-        with open(fn, 'r') as fin:
+        with open(fn) as fin:
             for ll in fin:
                 if 'Curr Time:' in ll:
                     times[ntimes] = ll
@@ -1208,7 +1208,7 @@
     for fn in files:
         found_time = False
 
-        with open(fn, 'r') as fin:
+        with open(fn) as fin:
             for l in fin:
                 if 'Curr Time:' in l:
                     times[ntimes] = l
@@ -1273,7 +1273,7 @@
 __all__ = [
     'binary_to_rawnc',
     'merge_rawnc',
-    'raw_to_timeseries',
     'parse_gliderState',
     'parse_logfiles',
+    'raw_to_timeseries',
 ]

pyglider/utils.py

@@ -124,7 +124,7 @@
     )
     dpall = np.diff(p)
     inflect = np.where(dpall[:-1] * dpall[1:] < 0)[0]
-    for n, i in enumerate(inflect[:-1]):
+    for n, _ in enumerate(inflect[:-1]):
         nprofile = inflect[n + 1] - inflect[n]
         inds = np.arange(good[inflect[n]], good[inflect[n + 1]] + 1) + 1
         dp = np.diff(ds.pressure[inds[[-1, 0]]])
@@ -553,8 +553,8 @@
     ds.attrs['title'] = ds.attrs['id']
 
     dt = ds.time.values
-    ds.attrs['time_coverage_start'] = '%s' % dt[0]
-    ds.attrs['time_coverage_end'] = '%s' % dt[-1]
+    ds.attrs['time_coverage_start'] = str(dt[0])
+    ds.attrs['time_coverage_end'] = str(dt[-1])
 
     ds.attrs['processing_level'] = (
         'Level 0 (L0) processed data timeseries; ' 'no corrections or data screening'
@@ -701,7 +701,7 @@
     xmln = fname
     from bs4 import BeautifulSoup
 
-    with open(xmln, 'r') as fin:
+    with open(xmln) as fin:
         y = BeautifulSoup(fin, features='xml')
         time = None
         lon = None
@@ -735,7 +735,7 @@
     xmln = fname
     from bs4 import BeautifulSoup
 
-    with open(xmln, 'r') as fin:
+    with open(xmln) as fin:
         y = BeautifulSoup(fin, features='xml')
         time = None
         for a in y.find_all('report'):
@@ -751,8 +751,8 @@
 def example_gridplot(
     filename,
     outname,
-    toplot=['potential_temperature', 'salinity', 'oxygen_concentration'],
-    pdenlevels=np.arange(10, 30, 0.5),
+    toplot=['potential_temperature', 'salinity', 'oxygen_concentration'],  # noqa: B006
+    pdenlevels=np.arange(10, 30, 0.5),  # noqa: B008
     dpi=200,
     ylim=None,
 ):
@@ -790,7 +790,7 @@
             deploymentyaml,
         ]
     deployment = {}
-    for nn, d in enumerate(deploymentyaml):
+    for d in deploymentyaml:
         with open(d) as fin:
             deployment_ = yaml.safe_load(fin)
             for k in deployment_:
@@ -834,12 +834,12 @@
 
 
 __all__ = [
+    'fill_metadata',
+    'gappy_fill_vertical',
+    'get_derived_eos_raw',
     'get_distance_over_ground',
     'get_glider_depth',
     'get_profiles_new',
-    'get_derived_eos_raw',
-    'fill_metadata',
     'nmea2deg',
-    'gappy_fill_vertical',
     'oxygen_concentration_correction',
 ]

pyproject.toml

@@ -15,22 +15,22 @@ filterwarnings = [
 ]
 
 [tool.ruff.lint]
+# See https://docs.astral.sh/ruff/rules/ for all rules
 select = [
-  "F", # pyflakes
-  "I", # isort
-  "E", # Error
+  "F",   # pyflakes
+  "I",   # isort
+  "E",   # Error
+  "B",   # Bugbear
+  "UP",  # pyupgrade
+  "LOG", # logging
+  "ICN", # import conventions
+  "G",   # logging-format
+  "RUF", # ruff
   # "D",  # pydocstyle
-  # "B",  # Bugbear
-  # "UP", # pyupgrade
-  # "LOG", # logging
-  # "ICN", # import conventions
-  # "G", # logging-format
-  # "RUF", # ruff
 ]
 
 ignore = [
-  # TODO: Remove
-  "E402", # Module level import not at top of file
+  "RUF005", # Consider `[*outlines, line]` instead of concatenation
 
   "F841", # Local variable `...` is assigned to but never used
   "E722", # Do not use bare `except`

tests/test_seaexplorer.py

@@ -6,12 +6,12 @@
 import pytest
 import yaml
 
+import pyglider.seaexplorer as seaexplorer
+
 os.system('rm tests/data/realtime_rawnc/*')
 library_dir = Path(__file__).parent.parent.absolute()
 example_dir = library_dir / 'tests/example-data/'
 
-import pyglider.seaexplorer as seaexplorer
-
 
 def test__outputname():
     fnout, filenum = seaexplorer._outputname(

tests/test_slocum.py

@@ -118,7 +118,7 @@ def test_profiles_compliant():
         output_format=output_format,
     )
     # Open the JSON output and get the compliance scores
-    with open(output_filename, 'r') as fp:
+    with open(output_filename) as fp:
         cc_data = json.load(fp)
         test = cc_data['gliderdac']
         assert test['high_count'] == 0
@@ -162,7 +162,7 @@ def test_timeseries_compliant():
         output_format=output_format,
     )
     # Open the JSON output and get the compliance scores
-    with open(output_filename, 'r') as fp:
+    with open(output_filename) as fp:
         cc_data = json.load(fp)
         test = cc_data['cf:1.8']
         assert test['high_count'] == 0