pathpilot

pathpilot is a Python package that makes file and folder manipulation simple and intuitive. It was designed with an emphasis on pandas compatibility to ensure smooth workflows.

Installation

pip install pathpilot

Main Features

• File ➔ Function that assigns new file instances to the correct child class. Many file types are supported natively including: .xlsx, .csv, .txt, .pickle, etc. The mapping of file extensions to their respective classes is managed using the extension_mapping global dictionary. Unmapped extensions are assigned to the FileBase class.
• Folder ➔ Class for interacting with folders. It is important to be mindful of the read_only parameter which, if set to True, allows folders to be created or deleted programically.

Example Usage

Please note the examples below represent a small fraction of the functionality offered by pathpilot. Please refer to the documentation within the code for more information.

Imports

from pathpilot import Folder, File

Folders

First, we create an instance of the Folder class. Passing read_only=False causes the folder to be created if it does not already exist.

# initiate a folder instance
folder = Folder(r'C:\Users\MyID\Documents\MyFolder', read_only=False)

Moreover, any subfolders that are referenced while interacting with the folder instance will also be created automatically. Let's use the join method to create a couple subfolders.

# create subfolders (i.e. C:\Users\MyID\Documents\MyFolder\Year\2025\Month\)
month_folder = folder.join('Year', '2025', 'Month')

Alternatively, you can access subfolders by referencing attributes that may or may not already exist.

# create a new subfolder called "January" by accessing it via attribute
january_folder = month_folder.january

Joining to a file will return a file object instead.

new_years_file = january_folder.join('Happy New Year.txt')

Files

First, we create an instance of the ExcelFile class using the File function. This occurs automatically by virtue of the .xlsx file extension.

# create ExcelFile instance
file = File(r'C:\Users\MyID\Documents\MyFolder\MyFile.xlsx')

Next, let's check if the file exists. If not, let's save a pandas DataFrame as an Excel file.

# export a pd.DataFrame to the file, if it does not already exist
if not file.exists:
  df = pd.DataFrame({'id': [1, 2, 3], 'data': ['a', 'b', 'c']})
  file.save(df)

Creating MyFile.xlsx
        writing 72.00 B to 'Sheet1' tab... DONE
        writing 80.00 B to 'Sheet1' tab... DONE

Now let's read the file we created as a DataFrame.

# read the file we created as a pd.DataFrame 
df = file.read()

On second thought, let's delete the file.

# delete the file we created
file.delete()