pathpilot 0.3.4

Library that facilitates file and folder manipulation in Python.

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_factory ➔ 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_factory

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_factory function. This occurs automatically by virtue of the .xlsx file extension.

# create ExcelFile instance
file = file_factory(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()