Skip to main content

File Manager for the Johnny Decimal System

Project description

PyPI version PyPI - Python Version Python Code Checker codecov


jdfile cleans and normalizes filenames. In addition, if you have directories which follow the Johnny Decimal, jdfile can move your files into the appropriate directory.

jdfile cleans filenames based on your preferences.

  • Remove special characters
  • Trim multiple separators (word----word becomes word-word)
  • Normalize to lower case, upper case, sentence case, or title case
  • Normalize all files to a common word separator (_, -, )
  • Enforce lowercase file extensions
  • Remove common English stopwords
  • Split camelCase words into separate words (camel Case)
  • Parse the filename for a date in many different formats
  • Remove or reformat the date and add it to the the beginning of the filename
  • Avoid overwriting files by adding a unique integer when renaming/moving
  • Clean entire directory trees
  • Optionally, show previews of changes to be made before commiting
  • Ignore files listed in a config file by filename or by regex
  • Specify casing for words which should never be changed (ie. iMac will never be re-cased)

jdfile can organize your files into folders.

  • Move files into directory trees following the Johnny Decimal system
  • Parse files and folder names looking for matching terms
  • Uses nltk to lookup synonyms to improve matching
  • Add .jdfile files to directories containing a list of words that will match files

Why build this?

It's nearly impossible to file away documents with normalized names when everyone has a different convention for naming files. On any given day, tons of files are attached to emails or sent via Slack by people who have their won way of naming files. For example:

  • department 2023 financials and budget 08232002.xlsx
  • some contract Jan7 reviewed NOT FINAL (NL comments) v13.docx
  • John&Jane-meeting-notes.txt
  • Project_mockups(WIP)___sep92022.pdf
  • FIRSTNAMElastname Resume (#1) [companyname].PDF
  • code_to_review.js

If you are a person who archives documents there are a number of problems with these files.

  • No self-evident way to organize them into folders
  • No common patterns to search for
  • Dates all over the place or nonexistent
  • No consistent casing
  • No consistent word separators
  • Special characters within text
  • I could go on and on...

Additionally, even if the filenames were normalized, filing documents manually is a pain.

jdfile is created to solve for these problems by providing an easy CLI to normalize the filename and organize it into an appropriate directory on your computer.


jdfile requires Python v3.10 or above

pip install pip install obsidian-metadata


Run jdfile --help for usage


To organize files into folders, a valid toml configuration file is required at ~/.jdfile/jdfile.toml

# The name of the project is used as a command line option.
# (e.g. --organize=project_name)
    # (Required) Path to the folder containing the Johnny Decimal project
    path = "~/johnnydecimal"

    # An optional date format. If specified, the date will be appended to the filename
    # See for details on how to specify a date.
    date_format = "None"

    # Ignores dotfiles (files that start with a period) when cleaning a directory.  true or false
    ignore_dotfiles = true

    # Files in this list will be skipped.
    ignored_files = ['file1.txt', 'file2.txt']

    # File names matching this regex will be skipped.
    # IMPORTANT: You must double escape within the pattern
    ignored_regex = [".*\\.tar.gz$"]

    # Force the casing of certain words. Great for acronyms or proper nouns.
    match_case = ["CEO", "CEOs", "iMac", "iPhone"]

    # Overwrite existing files. true or false. If false, unique integers will be appended to the filename.
    overwrite_existing = false

    # Separator to use between words. Options: "ignore", "underscore", "space", "dash", "none"
    separator = "ignore"

    # Split CamelCase words into separate words. true or false
    split_words = false

    # Optional list of project specific stopwords to be stripped from filenames
    stopwords = ["stopword1", "stopword2"]

    # Strip stopwords from filenames. true or false
    strip_stopwords = true

    # Transform case of filenames.
    # Options: "lower", "upper", "title", "CamelCase", "sentence", "ignore",
    transform_case = "ignore"

    # Use the nltk wordnet corpus to find synonyms for words in filenames. true or false
    # Note, this will download a large corpus (~400mb) the first time it is run.
    use_synonyms = false

Example usage

# Normalize all files in a directory to lowercase, with underscore separators
$ jdfile --case=lower --separator=underscore /path/to/directory

# Clean all files in a directory and confirm all changes before committing them
$ jdfile --clean /path/to/directory

# Strip common English stopwords from all files in a directory
$ jdfile --stopwords /path/to/directory

# Transform a date and add it to the filename
$ jdfile --date-format="%Y-%m-%d" ./somefile_march 3rd, 2022.txt

# Print a tree representation of a Johnny Decimal project
$ jdfile --project=[project_name] --tree

# Use the settings of a project in the config file to clean filenames without
# organizing them into folders
$ jdfile --project=[project_name] --no-organize path/to/some_file.jpg

# Organize files into a Johnny Decimal project with specified terms with title casing
$ jdfile ---project=[project_name] --term=term1 --term=term2 path/to/some_file.jpg


Adding custom functions to your .bashrc or .zshrc can save time and ensure your filename preferences are always used.

# ~/.bashrc
if command -v jdfile &>/dev/null; then

    clean() {
        # DESC:	 Clean filenames using the jdfile package
        if [[ $1 == "--help" || $1 == "-h" ]]; then
            jdfile --help
            jdfile --sep=space --case=title --confirm "$@"

    wfile() {
        # DESC:	 File work documents
        if [[ $1 == "--help" || $1 == "-h" ]]; then
            jdfile --help
            jdfile --project=work "$@"


jdfile is built for my own personal use. YMMV depending on your system and requirements. I make no warranties for any data loss that may result from use. I strongly recommend running in --dry-run mode prior to updating files.


Setup: Once per project

There are two ways to contribute to this project.

1. Local development

  1. Install Python 3.10 and Poetry
  2. Clone this repository. git clone
  3. Install the Poetry environment with poetry install.
  4. Activate your Poetry environment with poetry shell.
  5. Install the pre-commit hooks with pre-commit install --install-hooks.

2. Containerized development

  1. Clone this repository. git clone
  2. Open the repository in Visual Studio Code
  3. Start the Dev Container. Run Ctrl/⌘ + + PRemote-Containers: Reopen in Container.
  4. Run poetry env info -p to find the PATH to the Python interpreter if needed by VSCode.


  • This project follows the Conventional Commits standard to automate Semantic Versioning and Keep A Changelog with Commitizen.
    • When you're ready to commit changes run cz c
  • Run poe from within the development environment to print a list of Poe the Poet tasks available to run on this project. Common commands:
    • poe lint runs all linters
    • poe test runs all tests with Pytest
  • Run poetry add {package} from within the development environment to install a run time dependency and add it to pyproject.toml and poetry.lock.
  • Run poetry remove {package} from within the development environment to uninstall a run time dependency and remove it from pyproject.toml and poetry.lock.
  • Run poetry update from within the development environment to upgrade all dependencies to the latest versions allowed by pyproject.toml.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jdfile-1.1.5.tar.gz (45.4 kB view hashes)

Uploaded Source

Built Distribution

jdfile-1.1.5-py3-none-any.whl (45.0 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page