elabftw-ude-cli 0.1.0

CLI wrapper for interacting with eLabFTW API at University of Duisburg-Essen

elabftw_ude_cli

elabftw_ude_cli is a Python-based CLI and importable API for interacting with the eLabFTW electronic lab notebook system, tailored for use at the University of Duisburg-Essen.

It provides:

• A command-line interface to create, modify, search, and read experiments.
• A Python API for programmatic integration with pipelines and notebooks.
• Tab-autocomplete support for fast CLI access.
• Optional integration with Python-based workflows like Snakemake.

---

🛠 Installation

pip install elabftw_ude_cli

🔑 Step 0: Add your API key and base URL

After installation, locate and edit your config.py:

python -c "import elabftw_ude_cli.config as c; print(c.get_config_file_path())"

Open this file and configure your servers dictionary and server_to_use key.

---

⚡ CLI Usage

After installation, use elabftw-cli from the command line.

♻️ Enable tab-completion (recommended)

activate-global-python-argcomplete --user

Or for bash/zsh:

eval "$(register-python-argcomplete elabftw-cli)"

📋 CLI Commands

elabftw-cli create_experiment --name "Exp Title" --body path/to/body.md --steps path/to/steps.json
elabftw-cli modify_experiment --exp_id 123 --body new_body.md --steps new_steps.json
elabftw-cli search_experiments --name-like "test"
elabftw-cli read_experiment --exp_id 123

Common CLI Options

• --json: Provide a JSON file with experiment metadata.
• --body: Text or HTML/Markdown file to use as body content.
• --steps: JSON file with step definitions.
• --first / --all: Control read behavior when multiple matches are found.
• --outfile: Save experiment(s) to a custom file.
• -f: Force title changes in modification.

---

🧑‍💻 Python API Usage

import elabftw_ude_cli.api as elf

# Create an experiment
exp_id = elf.create_experiment(
    name="My Experiment",
    body="<h1>Intro</h1><p>This is HTML</p>",
    content_type=2
)

# Modify with body append and steps
elf.modify_experiment(
    exp_id=exp_id,
    body_append="Done.\nAll checked.",
    steps=[{"body": "step_3: summary"}]
)

# Complete step
elf.complete_step(exp_id, pattern="step_3", change="first", done_by="Alice")

# Search and read
ids, names = elf.search_experiments("test")
data = elf.read_experiment(exp_id=ids[0])

---

🧬 Snakemake Integration

Because Snakemake supports native Python and shell calls, you can use this library in rules:

# In a rule or script:
import elabftw_ude_cli.api as elf

def report_to_elab(title, body, steps):
    return elf.create_experiment(name=title, body=body, steps=steps)

Or from the shell using elabftw-cli.