satisfy flake8 linter (this is ridiculus)

scripts/daily_plot.py

@@ -48,7 +48,8 @@ readings = 10
 plt_top10_today = (df_plt_today['Com_Name'].value_counts()[:readings])
 df_plt_top10_today = df_plt_today[df_plt_today.Com_Name.isin(plt_top10_today.index)]
 
-if df_plt_top10_today.empty: exit(0)
+if df_plt_top10_today.empty:
+    exit(0)
 
 # Set Palette for graphics
 pal = "Greens"

scripts/plotly_streamlit.py

@@ -93,7 +93,7 @@ else:
 def date_filter(df, start_date, end_date):
     filt = (df2.index >= pd.Timestamp(start_date)) & (df2.index <= pd.Timestamp(end_date + timedelta(days=1)))
     df = df[filt]
-    return(df)
+    return (df)
 
 
 df2 = date_filter(df2, start_date, end_date)
@@ -140,7 +140,7 @@ def time_resample(df, resample_time):
     else:
         df_resample = df.resample(resample_time)['Com_Name'].aggregate('unique').explode()
 
-    return(df_resample)
+    return (df_resample)
 
 
 top_bird = df2['Com_Name'].mode()[0]
@@ -172,10 +172,10 @@ if daily is False:
 
     if resample_time != '1D':
         specie = st.selectbox(
-                'Which bird would you like to explore for the dates '
-                + str(start_date) + ' to ' + str(end_date) + '?',
-                species,
-                index=0)
+            'Which bird would you like to explore for the dates '
+            + str(start_date) + ' to ' + str(end_date) + '?',
+            species,
+            index=0)
 
     # filt = df2['Com_Name'] == specie
         if specie == 'All':
@@ -192,7 +192,7 @@ if daily is False:
                                 #     '{:.2f}%'.format(max(df2[df2['Com_Name'] == specie]['Confidence']) * 100)) +
                                 # '   ' + '   Median:' + str(
                                 #     '{:.2f}%'.format(np.median(df2[df2['Com_Name'] == specie]['Confidence']) * 100))
-                                )
+                )
             )
             fig.layout.annotations[1].update(x=0.7, y=0.25, font_size=15)
 
@@ -252,7 +252,7 @@ if daily is False:
                 fig = make_subplots(
                     rows=3, cols=1,
                     specs=[[{"type": "polar", "rowspan": 2}], [{"rowspan": 1}], [{"type": "xy", "rowspan": 1}]]
-                            )
+                )
                 # Set 360 degrees, 24 hours for polar plot
                 theta = np.linspace(0.0, 360, 24, endpoint=False)
 

scripts/species.py

@@ -1,18 +1,5 @@
-from pathlib import Path
-from tzlocal import get_localzone
-import datetime
-import sqlite3
-import requests
-import json
-import time
-import math
 import numpy as np
-import librosa
-import operator
-import socket
-import threading
 import os
-import sys
 import argparse
 import datetime
 
@@ -22,7 +9,6 @@ except BaseException:
     from tensorflow import lite as tflite
 
 
-
 def loadMetaModel():
 
     global M_INTERPRETER
@@ -51,15 +37,16 @@ def loadMetaModel():
 
     print("loaded META model")
 
+
 def predictFilter(lat, lon, week):
 
     global M_INTERPRETER
 
     # Does interpreter exist?
     try:
-        if M_INTERPRETER == None:
+        if M_INTERPRETER is None:
             loadMetaModel()
-    except Exception as e:
+    except Exception:
         loadMetaModel()
 
     # Prepare mdata as sample
@@ -71,6 +58,7 @@ def predictFilter(lat, lon, week):
 
     return M_INTERPRETER.get_tensor(M_OUTPUT_LAYER_INDEX)[0]
 
+
 def explore(lat, lon, week, threshold):
 
     # Make filter prediction
@@ -87,6 +75,7 @@ def explore(lat, lon, week, threshold):
 
     return l_filter
 
+
 def getSpeciesList(lat, lon, week, threshold=0.05, sort=False):
 
     print('Getting species list for {}/{}, Week {}...'.format(lat, lon, week), end='', flush=True)
@@ -98,7 +87,7 @@ def getSpeciesList(lat, lon, week, threshold=0.05, sort=False):
     slist = []
     for p in pred:
         if p[0] >= threshold:
-            slist.append([p[1],p[0]])
+            slist.append([p[1], p[0]])
 
     return slist
 
@@ -115,13 +104,10 @@ weekofyear = datetime.datetime.today().isocalendar()[1]
 if __name__ == '__main__':
 
     # Parse arguments
-    parser = argparse.ArgumentParser(description='Get list of species for a given location with BirdNET. Sorted by occurrence frequency.')
-    #parser.add_argument('--o', default='/home/pi/BirdNET-Pi/include_species_list.txt', help='Path to output file or folder. If this is a folder, file will be named \'species_list.txt\'.')
-    #parser.add_argument('--lat', type=float, default=##, help='Recording location latitude. Set -1 to ignore.')
-    #parser.add_argument('--lon', type=float, default=##, help='Recording location longitude. Set -1 to ignore.')
-    #parser.add_argument('--week', type=int, default=dayofweek, help='Week of the year when the recording was made. Values in [1, 48] (4 weeks per month). Set -1 for year-round species list.')
+    parser = argparse.ArgumentParser(
+        description='Get list of species for a given location with BirdNET. Sorted by occurrence frequency.'
+    )
     parser.add_argument('--threshold', type=float, default=0.05, help='Occurrence frequency threshold. Defaults to 0.05.')
-    #parser.add_argument('--sortby', default='freq', help='Sort species by occurrence frequency or alphabetically. Values in [\'freq\', \'alpha\']. Defaults to \'freq\'.')
 
     args = parser.parse_args()
 
@@ -130,10 +116,9 @@ if __name__ == '__main__':
     # Get species list
     species_list = getSpeciesList(lat, lon, weekofyear, LOCATION_FILTER_THRESHOLD, False)
     for x in range(len(species_list)):
-        print(species_list[x][0] + " - "+ str(species_list[x][1]))
-    
-    print("\nThe above species list describes all the species that the model will attempt to detect. If you don't see a species you want detected on this list, decrease your threshold.")
-    print("\nNOTE: no actual changes to your BirdNET-Pi species list were made by running this command. To set your desired frequency threshold, do it through the BirdNET-Pi web interface (Tools -> Settings -> Model)")
-
-
+        print(species_list[x][0] + " - " + str(species_list[x][1]))
 
+    print("\nThe above species list describes all the species that the model will attempt to detect. \
+          If you don't see a species you want detected on this list, decrease your threshold.")
+    print("\nNOTE: no actual changes to your BirdNET-Pi species list were made by running this command. \
+          To set your desired frequency threshold, do it through the BirdNET-Pi web interface (Tools -> Settings -> Model)")

tests/test_settings_parse.py

@@ -39,6 +39,6 @@ IDFILE=/home/pi/BirdNET-Pi/IdentifiedSoFar.txt"""
         f.write(text)
 
     settings = config_to_settings(filename.name)
-    assert(settings["APPRISE_NOTIFICATION_TITLE"] == "Bird!")
-    assert(settings["FULL_DISK"] == "purge")
-    assert(settings["OVERLAP"] == "0.0")  # Yes, it's a string at this point.
+    assert (settings["APPRISE_NOTIFICATION_TITLE"] == "Bird!")
+    assert (settings["FULL_DISK"] == "purge")
+    assert (settings["OVERLAP"] == "0.0")  # Yes, it's a string at this point.