Appendix A: Installation and Setup

This appendix walks you through installing BioLang and the optional Python and R environments used for multi-language comparisons throughout the book.

Installing BioLang

Linux and macOS

Open a terminal and run:

curl -sSf https://biolang.org/install.sh | sh

This installs the bl binary to ~/.biolang/bin/ and adds it to your PATH. Restart your terminal or run:

source ~/.bashrc   # or ~/.zshrc on macOS

Verify the installation:

bl --version

You should see output like biolang 0.x.y. Any version 0.4.0 or later includes all the statistical builtins used in this book.

Windows

Open PowerShell and run:

irm https://biolang.org/install.ps1 | iex

This installs bl.exe to %USERPROFILE%\.biolang\bin\ and updates your PATH. Close and reopen PowerShell, then verify:

bl --version

Manual Installation

If the installer does not work for your system, download the appropriate binary from the releases page:

Extract the binary and place it somewhere on your PATH.

Verifying Statistical Builtins

To confirm that statistical functions are available, launch the REPL and try a quick test:

bl> ttest([1.0, 2.0, 3.0], [4.0, 5.0, 6.0])
{statistic: -3.674, p_value: 0.0214, df: 4}

bl> mean([10, 20, 30, 40, 50])
30.0

bl> sd([10, 20, 30, 40, 50])
15.8114

If these commands produce output, your installation is complete.

Python Setup (Optional)

Python comparisons are included for every day but are not required. If you want to run them, you need Python 3.8 or later.

Installing Python

Most systems come with Python pre-installed. Check your version:

python3 --version

If you need to install Python, visit python.org or use your system package manager:

# Ubuntu / Debian
sudo apt install python3 python3-pip python3-venv

# macOS (Homebrew)
brew install python3

# Windows — download from python.org

Installing Python Dependencies

We recommend using a virtual environment to keep the book’s dependencies isolated:

python3 -m venv biostat-env
source biostat-env/bin/activate   # Linux/macOS
# biostat-env\Scripts\activate    # Windows

Install all required packages:

pip install scipy numpy pandas matplotlib statsmodels lifelines scikit-learn seaborn

Verify the installation:

python3 -c "import scipy; import statsmodels; import lifelines; print('Python setup OK')"

Troubleshooting Python

pip: command not found — Use pip3 instead of pip, or install pip: python3 -m ensurepip.

ModuleNotFoundError — Make sure your virtual environment is activated. The prompt should show (biostat-env).

Version conflicts — If you have existing Python packages that conflict, create a fresh virtual environment dedicated to this book.

R Setup (Optional)

R comparisons are included for every day but are not required. If you want to run them, you need R 4.0 or later.

Installing R

Download R from CRAN:

# Ubuntu / Debian
sudo apt install r-base r-base-dev

# macOS (Homebrew)
brew install r

# Windows — download from cran.r-project.org

Verify:

R --version

Installing R Packages

Launch R and install the required packages:

install.packages(c(
  "stats",        # Base statistics (usually pre-installed)
  "survival",     # Survival analysis
  "ggplot2",      # Visualization
  "dplyr",        # Data manipulation
  "pwr",          # Power analysis
  "lme4",         # Mixed models
  "boot",         # Bootstrap methods
  "car",          # ANOVA type II/III
  "broom",        # Tidy model output
  "pheatmap",     # Heatmaps
  "ggrepel",      # Label placement for plots
  "multcomp"      # Multiple comparisons
))

Verify:

library(survival)
library(ggplot2)
library(pwr)
cat("R setup OK\n")

Troubleshooting R

package 'xxx' is not available — Update your CRAN mirror: chooseCRANmirror(). Select a mirror close to your location.

Compilation errors on Linux — Install development libraries: sudo apt install libcurl4-openssl-dev libxml2-dev libssl-dev.

Permission denied — Install packages to a user library: install.packages("pkg", lib = Sys.getenv("R_LIBS_USER")).

Running Companion Scripts

Each day’s companion directory contains three analysis scripts. Here is how to run each one:

BioLang

cd days/day-07
bl run init.bl           # Setup (generates data, downloads files)
bl run scripts/analysis.bl    # Run the analysis

Python

cd days/day-07
source ~/biostat-env/bin/activate   # Activate virtual environment
python3 scripts/analysis.py

R

cd days/day-07
Rscript scripts/analysis.R

Checking Expected Output

Each day includes an expected/ directory with reference output. You can diff your results:

bl run scripts/analysis.bl > my_output.txt
diff my_output.txt expected/output.txt

Key insight: Statistical results may differ slightly between languages due to floating-point arithmetic and algorithmic differences. Results that agree to 2-3 decimal places are considered matching. The companion compare.md file notes any expected discrepancies.

Editor Setup

BioLang has a Language Server Protocol (LSP) implementation that provides syntax highlighting, autocompletion, and inline diagnostics in supported editors.

VS Code

Install the BioLang extension from the VS Code marketplace. It includes the LSP client and syntax highlighting for .bl files.

Vim / Neovim

Add the BioLang LSP to your lspconfig:

require('lspconfig').biolang.setup{}

Other Editors

Any editor that supports LSP can use the BioLang language server. Start it with:

bl lsp

Directory Structure for the Book

We recommend organizing your working directory like this:

biostatistics/
  days/               # Companion files (from git clone)
  my-work/            # Your own scripts and notes
    day-01/
    day-02/
    ...
  data/               # Shared datasets across days

This keeps the companion files clean while giving you a place to experiment.

System Requirements

All exercises in this book run comfortably on a standard laptop. No GPU, cluster access, or cloud computing is required.