MyDropbox

A Python library for managing UHM Ocean BGC Group Dropbox paths in your research code.

Why This Library?

When working with shared Dropbox folders in a research group, hardcoding paths can lead to:

• Code that breaks when folder structures change
• Non-portable scripts that don't work on colleagues' machines
• Difficult-to-maintain codebases with scattered path definitions

mydropbox centralizes all your common Dropbox paths in one place, making your code cleaner and more maintainable.

Installation

Option 1: Install from GitHub (Recommended for Group)

# Install directly from GitHub
pip install git+https://github.com/raphaelbajon/mydropbox.git

# Or clone and install
git clone https://github.com/raphaelbajon/mydropbox.git
cd mydropbox
pip install -e .

Usage

Quick Start

from mydropbox import get_dropbox

# Initialize with your personal folder name
db = get_dropbox(personal_folder="Your Name")

# Access your personal folders
data_file = db.personal.datasets / "my_ocean_data.nc"
code_dir = db.personal.mycode / "analysis_scripts"
paper_draft = db.personal.papers / "carbon_cycle_2026.docx"

# Access group folders (works without personal_folder too)
group_data = db.group.datasets / "shared_observations.nc"
meeting_notes = db.group.group_notes / "2026-01-meeting.md"

Configuration Options

Option 1: Direct specification (simplest)

from mydropbox import get_dropbox
db = get_dropbox(personal_folder="Raphaël Bajon")

Option 2: Using a config file (recommended for privacy)

# 1. Copy mydropbox_config_template.py to mydropbox_config.py
# 2. Edit mydropbox_config.py and set your name

from config.mydropbox_config import PERSONAL_FOLDER
from mydropbox import get_dropbox

db = get_dropbox(personal_folder=PERSONAL_FOLDER)

Option 3: Group access only (no personal paths)

from mydropbox import dropbox

# Only group paths are available
shared_data = dropbox.group.datasets / "observations.nc"
# dropbox.personal is None

Working with Paths

The library uses Python's pathlib.Path objects, which are more powerful than strings:

# Read a file
readme = (dropbox.personal.projects / "README.md").read_text()

# Create subdirectories
new_project = dropbox.personal.projects / "new_analysis"
new_project.mkdir(exist_ok=True)

Custom Dropbox Location

If your Dropbox is in a non-standard location:

from mydropbox import get_dropbox

db = get_dropbox("/custom/path/to/UHM_Ocean_BGC_Group Dropbox")
print(db.personal.datasets)

Examples of Available Paths (that I have on my personal dropbox)

Personal Paths (dropbox.personal)

• admin - Administrative documents
• datasets - Your personal datasets
• meeting - Meeting notes and agendas
• mycode - Your code repository
• papers - Research papers and manuscripts
• phd - PhD-related materials
• projects - Research projects
• slides - Presentation slides
• soc_tools - Southern Ocean Carbon tools
• team - Team collaboration files
• utils - Utility scripts and tools

Group Paths (dropbox.group)

• assorted_content - Miscellaneous shared content
• collaborative_projects - Group collaborative projects
• datasets - Shared group datasets
• group_notes - Group meeting notes and documentation
• lab_field_data - Laboratory and field data
• ocean_reports - Ocean observation reports

Project Management

😏 MyDropbox includes a powerful project management module to create standardized research project structures. See the Projects Guide for all the explanations of this feature!

from mydropbox import get_dropbox, create_project

# Initialize
db = get_dropbox(personal_folder="Your Name")

# Create a new project with standardized structure
project = create_project(
    base_path=db.personal.projects,
    name="Project_01",
    template="full",  # or "simple" or "minimal"
    description="Description of Project_01",
    author="Your Name"
)

# Use the project structure to access your paths within your project in a few words!
project.data.raw # raw data
project.data.processed # processed data
project.notebooks # notebooks
project.src # source code
project.plots.explanatory # explanatory figures
project.plots.publication # figures for publication
# and many more..

Project Structure

Projects follow data science best practices with:

• data/ - Raw, interim, and processed data (separate folders)
• src/ - Reusable source code (data, features, models, visualization)
• notebooks/ - Jupyter notebooks for exploration
• plots/ - Exploratory and publication-ready figures
• docs/ - Documentation
• reports/ - Generated reports
• results/ - Model outputs and predictions
• config/ - Configuration files

Auto-generated files:

• README.md - Project documentation template
• .gitignore - Configured for data science (excludes large data files)
• project_metadata.json - Automated metadata tracking

For detailed project management documentation, see PROJECTS_GUIDE.md

Example Workflows

Data Analysis Script

from mydropbox import get_dropbox
import xarray as xr
import matplotlib.pyplot as plt

# Initialize with your personal folder
db = get_dropbox(personal_folder="Your Name")

# Load data
ds = xr.open_dataset(db.personal.datasets / "soc_carbon_flux.nc")

# Analyze
flux_mean = ds.carbon_flux.mean(dim='time')

# Save figure
fig_path = db.personal.projects / "flux_analysis" / "mean_flux.png"
fig_path.parent.mkdir(exist_ok=True)
plt.figure()
flux_mean.plot()
plt.savefig(fig_path)
print(f"Figure saved to {fig_path}")

Organizing Your Code

from mydropbox import get_dropbox

# Initialize once at the top of your script
db = get_dropbox(personal_folder="Your Name")

# Create a consistent project structure
project_name = "antarctic_upwelling_2026"
project_dir = db.personal.projects / project_name

# Create subdirectories
(project_dir / "data").mkdir(parents=True, exist_ok=True)
(project_dir / "figures").mkdir(exist_ok=True)
(project_dir / "notebooks").mkdir(exist_ok=True)
(project_dir / "scripts").mkdir(exist_ok=True)

print(f"Project structure created at {project_dir}")

Sharing Code with Collaborators

You can easily share code with collaborators!

Tips

1. Use Path objects: They handle cross-platform differences automatically
2. Check existence: Always verify files exist before opening them
3. Create directories: Use path.mkdir(parents=True, exist_ok=True) to avoid errors
4. Relative paths: Build paths dynamically for maximum flexibility

Extending the Library

You can easily add new paths or helper functions:

# In mydropbox/__init__.py
class PersonalPaths:
    def __init__(self, base_path: Path):
        self.base = base_path
        # Add your new paths here
        self.new_folder = self.base / "new_folder_name"

License

MIT License - Feel free to modify for your research needs.

Contributing

Contributions are welcome! Please see CONTRIBUTING.md for guidelines.

To contribute:

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

Changelog

See CHANGELOG.md for version history and changes.

Support

• Issues: Open an issue on GitHub
• Group discussions: Bring it up in lab meetings
• Questions: Check the examples or documentation

Acknowledgments

Developed for the UHM Ocean BGC Group for Southern Ocean Carbon cycle research.

---

Current Version: 0.1.0
Last Updated: January 28, 2026