Installation#

medscheduler targets Python 3.9+ and follows PEP 621 packaging standards.
The core package is lightweight, with minimal dependencies to ensure fast installation.
Optional visualization helpers can be installed via the [viz] extra.

Quick install with pip#

Install the core package from PyPI:

pip install medscheduler

To include optional plotting utilities:

pip install medscheduler[viz]

Verify your setup#

After installation, you can run a quick smoke test:

from medscheduler import AppointmentScheduler

s = AppointmentScheduler(seed=0)
print("appointments/hour:", s.appointments_per_hour)

If this executes without errors, your installation is successful.

Supported environments#

Python versions: 3.9, 3.10, 3.11 (and newer when available)
Operating systems: Linux, macOS, Windows (pure‑Python package, no compilation required)

Recommended: isolated environments#

To avoid conflicts with other packages, install medscheduler in a virtual environment:

Conda/Mamba#

# Create a new environment
mamba create -n medscheduler -y python=3.11
mamba activate medscheduler

# Install medscheduler from PyPI
pip install medscheduler[viz]

Virtualenv (venv)#

python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install medscheduler[viz]

Development install (from source)#

If you plan to modify or contribute to the library:

git clone https://github.com/carogaltier/medscheduler.git
cd medscheduler
python -m venv .venv && source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -e .[viz]

Troubleshooting#

Missing dependencies (e.g., pandas, numpy):
Upgrade pip and reinstall core libraries:
```
python -m pip install --upgrade pip
pip install --upgrade numpy pandas
```
Conflicting environments:
Always prefer a clean environment (venv or conda). Remove old installs before retrying.

Next steps#

Continue to What is Medscheduler? for an overview of concepts and outputs.
Jump to Quickstart to generate your first synthetic dataset and export CSV files.