style: Updating syntax

.gitignore

@@ -103,4 +103,4 @@ ENV/
 .mypy_cache/
 
 # IDE settings
-.vscode/
+.vscode/

README.rst

@@ -29,7 +29,7 @@ situ observations by searching pixels within a given time and distance tolerance
 For instance, it is used to calibrate chlorophyll fluorescence measurements
 from Spray underwater gliders.
 
-The OceanColor package was developed at the `Instrument Development Group 
+The OceanColor package was developed at the `Instrument Development Group
 <https://idg.ucsd.edu>`_ of `Scripps Institution of Oceanography
 <https://scripps.ucsd.edu>`_ in support for the `California Underwater Glider
 Network <https://spraydata.ucsd.edu/projects/CUGN/>`_ operations, which is

docs/conf.py

@@ -57,7 +57,7 @@
 
 # General information about the project.
 project = 'Ocean Color'
-copyright = "2018-{}, Guilherme Castelão".format(datetime.now().year)
+copyright = f"2018-{datetime.now().year}, Guilherme Castelão"
 author = "Guilherme Castelão"
 
 # The version info for the project you're documenting, acts as replacement

setup.cfg

@@ -3,6 +3,6 @@ universal = 1
 
 [flake8]
 exclude = docs
-ignore = 
+ignore =
 	E203
 	E501

tests/test_cmr.py

@@ -6,7 +6,12 @@
 import pandas as pd
 import pytest
 
-from OceanColor.cmr import api_walk, bloom_filter, granules_search, search_criteria
+from OceanColor.cmr import (
+    api_walk,
+    bloom_filter,
+    granules_search,
+    search_criteria,
+)
 
 
 def test_api_walk():
@@ -37,12 +42,20 @@ def test_bloom_filter():
     track = [{"time": datetime64("2019-05-01"), "lat": 18, "lon": 38}]
     track = pd.DataFrame(track)
     for f in bloom_filter(
-        track, sensor="aqua", dtype="L2", dt_tol=timedelta64(36, "h"), dL_tol=10e3
+        track,
+        sensor="aqua",
+        dtype="L2",
+        dt_tol=timedelta64(36, "h"),
+        dL_tol=10e3,
     ):
         f
 
     for f in bloom_filter(
-        track, sensor="aqua", dtype="L3m", dt_tol=timedelta64(36, "h"), dL_tol=10e3
+        track,
+        sensor="aqua",
+        dtype="L3m",
+        dt_tol=timedelta64(36, "h"),
+        dL_tol=10e3,
     ):
         f
 
@@ -61,7 +74,13 @@ def test_bloom_filter_unique():
         {"time": datetime64("2019-05-02"), "lat": 18, "lon": 38},
     ]
     track = pd.DataFrame(track)
-    search = bloom_filter(track, sensor="aqua", dtype="L3m", dt_tol=timedelta64(24, "h"), dL_tol=10e3)
+    search = bloom_filter(
+        track,
+        sensor="aqua",
+        dtype="L3m",
+        dt_tol=timedelta64(24, "h"),
+        dL_tol=10e3,
+    )
     results = [r for r in search]
     assert len(results) == len(set(results)), "Duplicates from bloom_filter"
 
@@ -73,7 +92,13 @@ def test_bloom_filter_spaced_target():
         {"time": datetime64("2019-05-15 12:00:00"), "lat": 18, "lon": 38},
     ]
     track = pd.DataFrame(track, index=[0, 10, 100])
-    search = bloom_filter(track, sensor="aqua", dtype="L3m", dt_tol=timedelta64(6, "h"), dL_tol=5e3)
+    search = bloom_filter(
+        track,
+        sensor="aqua",
+        dtype="L3m",
+        dt_tol=timedelta64(6, "h"),
+        dL_tol=5e3,
+    )
     results = [r for r in search]
     print(results)
     assert len(results) < 5
@@ -87,10 +112,11 @@ def test_bloom_multiple_sensors():
         sensor=["aqua", "terra", "snpp"],
         dtype="L2",
         dt_tol=timedelta64(36, "h"),
-        dL_tol=10e3
+        dL_tol=10e3,
     )
     assert len([f for f in filter]) > 0
 
+
 def test_search_criteria():
     search = search_criteria(sensor="aqua", dtype="L2")
     assert search["short_name"] == "MODISA_L2_OC"
@@ -105,6 +131,7 @@ def test_search_criteria_nonexistent_key():
     with pytest.raises(ValueError):
         search_criteria(sensor="seawifs", dtype="nonexistent")
 
+
 """
 {'cdate': '2019-08-05 21:23:16', 'checksum': 'sha1:97b97ec2bc5c59255fd8e5ec8551f7bebb6f8be5', 'getfile': 'https://oceandata.sci.gsfc.nasa.gov/ob/getfile', 'size': 9881732, 'filename': 'A2019152.L3m_DAY_CHL_chlor_a_4km.nc'}
 {'cdate': '2019-08-05 20:56:42', 'checksum': 'sha1:de47941eb5c5454ac7b629c54643ccdbb482988b', 'getfile': 'https://oceandata.sci.gsfc.nasa.gov/ob/getfile', 'size': 9116814, 'filename': 'A2019153.L3m_DAY_CHL_chlor_a_4km.nc'}

tests/test_inrange.py

@@ -28,25 +28,25 @@
 def test_matchup_L2():
     ds = db["AQUA_MODIS.20170112T213500.L2.OC.nc"]
     dL_tol = 12e3
-    dt_tol = timedelta64(6, 'h')
-    track = DataFrame([
-        {"time": datetime64("2017-01-12 20:00:00"), "lat": 34, "lon": -126}])
+    dt_tol = timedelta64(6, "h")
+    track = DataFrame(
+        [{"time": datetime64("2017-01-12 20:00:00"), "lat": 34, "lon": -126}]
+    )
     data = matchup_L2(track, ds, dL_tol, dt_tol)
 
     # Dummy check
     assert data.index.size == 448
 
 
-
 @pytest.mark.skip()
 def test_matchup_L2_day_line():
-    """Test nearby the international day line from both sides
-    """
+    """Test nearby the international day line from both sides"""
     ds = db["V2017013002400.L2_SNPP_OC.nc"]
     dL_tol = 6e3
-    dt_tol = timedelta64(6, 'h')
-    track = DataFrame([
-        {"time": datetime64("2017-01-12 20:00:00"), "lat": 60, "lon": 179.99}])
+    dt_tol = timedelta64(6, "h")
+    track = DataFrame(
+        [{"time": datetime64("2017-01-12 20:00:00"), "lat": 60, "lon": 179.99}]
+    )
     data = matchup_L2(track, ds, dL_tol, dt_tol)
 
     # Dummy check
@@ -55,8 +55,15 @@ def test_matchup_L2_day_line():
     assert data.lon.max() > 0
 
     # From the other side
-    track = DataFrame([
-        {"time": datetime64("2017-01-12 20:00:00"), "lat": 60, "lon": -179.99}])
+    track = DataFrame(
+        [
+            {
+                "time": datetime64("2017-01-12 20:00:00"),
+                "lat": 60,
+                "lon": -179.99,
+            }
+        ]
+    )
     data = matchup_L2(track, ds, dL_tol, dt_tol)
 
     # Dummy check
@@ -68,9 +75,10 @@ def test_matchup_L2_day_line():
 def test_matchup_L3m():
     ds = db["AQUA_MODIS.20170112.L3m.DAY.CHL.chlor_a.4km.nc"]
     dL_tol = 12e3
-    dt_tol = timedelta64(6, 'h')
-    track = DataFrame([
-        {"time": datetime64("2017-01-12 20:00:00"), "lat": 34, "lon": -126}])
+    dt_tol = timedelta64(6, "h")
+    track = DataFrame(
+        [{"time": datetime64("2017-01-12 20:00:00"), "lat": 34, "lon": -126}]
+    )
     data = matchup_L3m(track, ds, dL_tol, dt_tol)
 
     # Dummy check
@@ -81,9 +89,10 @@ def test_matchup_L3m():
 def test_matchup():
     ds = db["AQUA_MODIS.20170112.L3m.DAY.CHL.chlor_a.4km.nc"]
     dL_tol = 12e3
-    dt_tol = timedelta64(6, 'h')
-    track = DataFrame([
-        {"time": datetime64("2017-01-12 20:00:00"), "lat": 34, "lon": -126}])
+    dt_tol = timedelta64(6, "h")
+    track = DataFrame(
+        [{"time": datetime64("2017-01-12 20:00:00"), "lat": 34, "lon": -126}]
+    )
     data = matchup(track, ds, dL_tol, dt_tol)
 
     # Dummy check
@@ -113,7 +122,11 @@ def test_InRange_recent():
     with tempfile.TemporaryDirectory() as tmpdirname:
         matchup = InRange(username, password, tmpdirname, npes=3)
         matchup.search(
-            track, sensor="snpp", dtype="L2", dt_tol=timedelta64(12, "h"), dL_tol=10e3
+            track,
+            sensor="snpp",
+            dtype="L2",
+            dt_tol=timedelta64(12, "h"),
+            dL_tol=10e3,
         )
         output = pd.concat([m for m in matchup])
 
@@ -150,7 +163,6 @@ def test_InRange_monotonic_index():
     """
     sensor = "aqua"
     dtype = "L2"
-    # dtype = 'L2'
     dL_tol = 12e3
     dt_tol = timedelta64(12, "h")
     track = DataFrame(

tests/test_storage.py

@@ -7,8 +7,10 @@
 
 import pytest
 import xarray as xr
+
 try:
     import s3fs
+
     S3FS_AVAILABLE = True
 except:
     S3FS_AVAILABLE = False
@@ -20,7 +22,7 @@
 
 @pytest.mark.skip()
 def test_parse_filename_AL2():
-    filename = "A2011010000000.L2_LAC_OC.nc"
+    filename = "AQUA_MODIS.2011010T000000.L2_LAC_OC.nc"
     descriptors = parse_filename(filename)
 
     ans = {
@@ -119,7 +121,10 @@ def test_no_download():
 @pytest.mark.skip()
 def test_S3Storage_path():
     backend = S3Storage("s3://mybucket/datadir")
-    assert backend.path("A2019109.L3m_DAY_CHL_chlor_a_4km.nc") == 's3://mybucket/datadir/MODIS-Aqua/L3m/2019/109/A2019109.L3m_DAY_CHL_chlor_a_4km.zarr'
+    assert (
+        backend.path("AQUA_MODIS.20190420.L3m.DAY.CHL.chlor_a.4km.nc")
+        == "s3://mybucket/datadir/MODIS-Aqua/L3m/2019/109/AQUA_MODIS.2019109.L3m.DAY.CHL.chlor_a.4km.zarr"
+    )
 
 
 def test_inmemory():
@@ -129,16 +134,15 @@ def test_inmemory():
     - Create test data with @pytest.fixture
     """
     db = InMemory()
-    ds = xr.Dataset({"x": [1,2,3]})
+    ds = xr.Dataset({"x": [1, 2, 3]})
     db["test-1"] = ds
 
     assert "test-1" in db
 
 
 def test_inmemory_quota():
-    """Independent of the quota, at least one item
-    """
-    ds = xr.Dataset({"x": [1,2,3]})
+    """Independent of the quota, at least one item"""
+    ds = xr.Dataset({"x": [1, 2, 3]})
     db = InMemory(quota=ds.nbytes + 1)
     db["test-1"] = ds
     db["test-2"] = ds
@@ -148,10 +152,9 @@ def test_inmemory_quota():
 
 
 def test_inmemory_at_least_one():
-    """Independent of the quota, at least one item
-    """
+    """Independent of the quota, at least one item"""
     db = InMemory(quota=0)
-    ds = xr.Dataset({"x": [1,2,3]})
+    ds = xr.Dataset({"x": [1, 2, 3]})
     db["test-1"] = ds
 
     assert "test-1" in db