ilia 579f0709ce Update Makefile and inventory configurations for improved task execution and organization

- Refactor Makefile to enhance command structure, including clearer descriptions and usage examples for targets related to development, inventory, and monitoring tasks.
- Update inventory files to ensure correct host configurations and user settings, including adjustments to ansible_user for specific hosts.
- Modify group_vars to streamline Tailscale configuration and ensure proper handling of authentication keys.

These changes improve the clarity and usability of the Makefile and inventory setup, facilitating smoother operations across the infrastructure.

2025-10-09 21:24:45 -04:00

4.6 KiB

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Role: datascience

Description

Installs and configures a complete data science environment including Anaconda/Conda, Jupyter Notebook, and R statistical computing language. This role is optional and separate from general development tools for faster deployments when data science capabilities are not needed.

Requirements

Ansible 2.9+
Debian/Ubuntu systems
At least 5GB free disk space (Anaconda is ~700MB)
Root or sudo access

Installed Components

Anaconda/Conda

Full Anaconda3 distribution (latest version)
Python data science packages (pandas, numpy, matplotlib, scikit-learn)
Conda package manager
Initialized for bash (zsh initialization via shell role)

Jupyter Notebook

Jupyter Notebook server
IPython kernel
JupyterLab interface
Systemd service for automatic startup
Web-based access on configurable port

R Language

R base and development packages
R recommended packages
CRAN repository configuration
IRkernel for Jupyter integration
Common R packages

Variables

Variable	Default	Description
`install_conda`	`false`	Install Anaconda/Conda
`conda_install_path`	`{{ ansible_env.HOME }}/anaconda3`	Conda installation directory
`install_jupyter`	`false`	Install Jupyter Notebook (requires conda)
`jupyter_port`	`8888`	Jupyter web server port
`jupyter_bind_all_interfaces`	`true`	Listen on all network interfaces
`jupyter_allow_remote`	`true`	Allow remote connections
`install_r`	`false`	Install R language
`r_packages`	`[r-base, r-base-dev, r-recommended]`	R packages to install

Dependencies

base role (for core utilities)

Example Playbook

Full Data Science Stack

- hosts: datascience_servers
  roles:
    - role: datascience
      install_conda: true
      install_jupyter: true
      install_r: true

Conda + Jupyter Only

- hosts: jupyter_servers
  roles:
    - role: datascience
      install_conda: true
      install_jupyter: true
      install_r: false

R Only (no Python)

- hosts: r_servers
  roles:
    - role: datascience
      install_conda: false
      install_r: true

Usage

Installation

# Install full data science stack
make datascience HOST=server01

# Install on specific host with custom vars
ansible-playbook playbooks/development.yml --limit server01 --tags datascience \
  -e "install_conda=true install_jupyter=true install_r=true"

Post-Installation

Set Jupyter Password

jupyter notebook password

Access Jupyter

# Local
http://localhost:8888

# Remote
http://your-server-ip:8888

Verify Installations

conda --version
jupyter --version
R --version

Services

Jupyter Notebook Service

Service name: jupyter-notebook.service
Start: systemctl start jupyter-notebook
Status: systemctl status jupyter-notebook
Logs: journalctl -u jupyter-notebook

Performance Notes

Installation Times

Anaconda: 5-10 minutes (700MB download)
Jupyter: 2-5 minutes (if Anaconda already installed)
R: 10-30 minutes (compilation of packages)

Disk Space

Anaconda: ~2.5GB after installation
R + packages: ~500MB
Total: ~3GB for full stack

Security Considerations

Jupyter Password: Always set a password after installation
Firewall: Ensure port 8888 (or custom port) is properly firewalled
HTTPS: Consider using HTTPS for remote access
User Isolation: Jupyter runs as the ansible user by default

Troubleshooting

Conda Not in PATH

# Add to .bashrc or .zshrc
export PATH="$HOME/anaconda3/bin:$PATH"

Jupyter Service Won't Start

# Check logs
journalctl -u jupyter-notebook -n 50

# Verify conda is accessible
/root/anaconda3/bin/jupyter --version

R Package Installation Fails

# Install manually in R
R
> install.packages("IRkernel")

Integration with Other Roles

Shell Role: Provides zsh with conda integration
Monitoring: btop/htop for resource monitoring
Docker: Can run Jupyter in containers alternatively

Notes

Anaconda installer is cleaned up after installation
Conda init for zsh is handled by the shell role
IRkernel is automatically installed if both Jupyter and R are enabled
R packages are compiled during installation (can be slow)
Jupyter service starts on boot automatically

4.6 KiB Raw Blame History