user agnostic and acknowledgements

docs/source/Acknowledgments.md

@@ -32,6 +32,9 @@ documentation and website. He tested the library on multiple corpora.
 **Paula Muñoz-Lago**, computer scientist, contributed to the initial code and first stages of the 
 tool.
 
+**Carlos Vaquero Patricio**, Joined the project as a Data Scientist postdoc researcher in 2023 and has contributed to debugging musif, developing its final stages as well as making it accessible to the MIR community.
+
+
 ### Acknowledgments
 `musif` is a result of the Didone Project, which has received funding from the European 
 Research Council (ERC) under the European Union’s Horizon 2020 research and innovation

run_extraction_example.py

@@ -21,8 +21,14 @@
 cache_dir = None
 
 # csv file containing files which raised error and need to be reextracted
-path_error = 'martiser/error_files.csv'
-errored_files = list(pd.read_csv(path_error, low_memory=False)[FILE_NAME])
+try:
+    path_error = f'{DEST_PATH}/error_files.csv'
+    errored_files = list(pd.read_csv(path_error, low_memory=False)[FILE_NAME])
+except Exception:
+    # Handle the case where there is no file is empty
+    print("There is no error_files.csv, it will be created and loaded error files are included manually in it.")
+    pass
+
 
 # In case a partial extraction has been run, set here the previous df to avoid re-extracting these files.
 # prev_path = str(prefix / NAME) + '.csv'