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Sep 10, 2025
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Update README.md to incorporate pip installation instructions #192

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Update README.md (Python) to incorporate pip installation instructions
AlxndrMlk Sep 10, 2025
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Update README.md (Python) -> add pip installation instructions
AlxndrMlk Sep 10, 2025
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Update README.md (Python) -> add pip installation instructions
AlxndrMlk Sep 10, 2025
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25 changes: 18 additions & 7 deletions README.md
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Expand Up @@ -17,11 +17,22 @@ Details on installation and use are available below:

# Python Package

The python package is not yet on PyPI but can be installed from source using pip's [git interface](https://pip.pypa.io/en/stable/topics/vcs-support/).
To proceed, you will need a working version of [git](https://git-scm.com) and python 3.8 or greater (available from several sources, one of the most
straightforward being the [anaconda](https://docs.conda.io/projects/conda/en/stable/user-guide/install/index.html) suite).
## PyPI (`pip`)

## Quick start
`stochtree`'s Python package can be installed from PyPI via:

```
pip install stochtree
```

## Development Version (Local Build)

The development version of stochtree can be installed from source using pip's [git interface](https://pip.pypa.io/en/stable/topics/vcs-support/).

To proceed, you will need a working version of [git](https://git-scm.com) and python 3.8 or greater (available from several sources, one of the most straightforward being the [anaconda](https://docs.conda.io/projects/conda/en/stable/user-guide/install/index.html) suite).


### Quick start

Without worrying about virtual environments (detailed further below), `stochtree` can be installed from the command line

Expand All @@ -30,11 +41,11 @@ pip install numpy scipy pytest pandas scikit-learn pybind11
pip install git+https://github.com/StochasticTree/stochtree.git
```

## Virtual environment installation
### Virtual environment installation

Often, users prefer to manage different projects (with different package / python version requirements) in virtual environments.

### Conda
#### Conda

Conda provides a straightforward experience in managing python dependencies, avoiding version conflicts / ABI issues / etc.

Expand All @@ -60,7 +71,7 @@ pip install jupyterlab

With these dependencies installed, you can [clone the repo](###cloning-the-repository) and run the `demo/` examples.

### Venv
#### Venv

You could also use venv for environment management. First, navigate to the folder in which you usually store virtual environments
(i.e. `cd /path/to/envs`) and create and activate a virtual environment:
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