19 GitHub action for pylint is broken

.github/workflows/pylint.yml

@@ -7,22 +7,22 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.11]
+        python-version: ["3.11"]
     steps:
     - uses: actions/checkout@v3
-    - name: Set up Conda environment with Python ${{ matrix.python-version }}
-      uses: s-weigand/setup-conda@v1
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
       with:
         python-version: ${{ matrix.python-version }}
-        conda-channels: 'conda-forge'
     - name: Install dependencies
       run: |
-        conda env update --file environment.yml
-    - name: Activate conda environment
-      run: |
-        conda init bash
-        source /home/runner/.bashrc
-        conda activate waldo-dev-env
+        python -m pip install --upgrade pip
+        pip install opencv-python
+        pip install pylint
+        pip install pytube
+        pip install pandas
+        pip install requests
+        pip install validators
     - name: Analyze the code with pylint
       run: |
         pylint $(git ls-files '*.py')

utils/link_retrieval.py

@@ -1,10 +1,14 @@
+'''
+Retrieves gameplay URLs from Waldo Vision API and stores them locally in a CSV.
+'''
+
 import argparse
 import os
+from pathlib import Path
 import pandas as pd
 import requests
 import validators
 from common import ensure_dir_exists
-from pathlib import Path
 
 # Set up command line arguments
 parser = argparse.ArgumentParser(description="Get URL's from API and store them locally")
@@ -43,8 +47,8 @@ def parse_data(data):
                 return print("Invalid URL: " + row['url'])
 
         return response_dataframe
-    except Exception as e:
-        print(f"Error while parsing data: {e}")
+    except Exception as error:
+        print(f"Error while parsing data: {error}")
         return pd.DataFrame(columns=['id', 'url', 'game'])
 
 def main():
@@ -85,14 +89,16 @@ def main():
 
         # Save the downloaded links to a file
         valid_urls_df = pd.DataFrame(valid_urls)
-        valid_urls_df.to_csv(os.path.join(Path(download_dir), "links.csv"), index=True, columns=["id", "url", "game"])
+        valid_urls_df.to_csv(os.path.join(Path(download_dir), "links.csv"),
+                             index=True, columns=["id", "url", "game"])
     except requests.exceptions.Timeout as timeout_error:
         print(f"Request timed out: {timeout_error}")
     except requests.exceptions.TooManyRedirects as redirect_error:
         print(f"Too many redirects: {redirect_error}")
     except requests.exceptions.RequestException as request_error:
         print(f"Request failed: {request_error}")
-    except Exception as e:
-        print(f"An error occurred: {e}")
+    except Exception as other_error:
+        print(f"An error occurred: {other_error}")
+
 if __name__ == "__main__":
-    main()
+    main()

utils/segmentation.py

@@ -1,3 +1,7 @@
+'''
+Code for testing OCR for clip segmentation
+'''
+
 import argparse
 import os
 from pathlib import Path
@@ -37,4 +41,4 @@
         for line in result:
             for word in line:
                 if word[1][1] >= 0.85:
-                    print(word[1])
+                    print(word[1])