Nbdl - A Library That Uses Metaprogramming - A Lot
Explore Nbdl, a generic library for application state management, leveraging metaprogramming with Boost.Hana to enhance performance and safety in C++ development.
Docker Based C++ Dependency and Build Management
Explore Docker for C++ project management, covering multi-stage builds, dependency resolution, and cross-platform targeting. Learn to streamline development with CppDock for efficient containerization.
Interactive C++ in a Jupyter Notebook Using Modules for Incremental Compilation
Explore interactive C++ in Jupyter notebooks using modules for incremental compilation, addressing limitations of existing tools and enabling a more robust computational chain for experimentation.
Docker and Python - Making Them Play Nicely and Securely for Data Science and ML
Docker best practices for data science and machine learning: optimizing image builds, ensuring security, and implementing efficient deployment workflows for data-intensive applications.
Dock Your Jupyter Notebook
Learn to containerize Jupyter Notebooks with Docker for reproducible and shareable machine learning projects, enabling smooth execution on remote machines.
Bootstrapping Your Local Python Environment
Discover best practices for Python environment setup, including proper installation, version management with pyenv, and essential add-ons for repeatable and efficient development workflows.
Supercharge Your Development Environment Using Docker
Streamline development with Docker: Learn to create, share, and automate lightweight containers for consistent environments across your team and in production.
Rethinking Packaging, Development and Deployment
Explore innovative approaches to Python packaging, development, and deployment using Nix. Learn how to streamline your workflow and manage dependencies across multiple languages efficiently.
Easy FullStack Deployments
Learn to manage full-stack development lifecycle using Python technologies and Docker, from project creation with Pyramid to consistent deployment infrastructure with Buildout and containers.
Scaling MySQL with Python
Learn to scale MySQL using Python tools for replication, management, and failover. Discover how to create resilient configurations and implement high availability infrastructures with mysql-fabric.
Infrastructure as Code - "pip install" Your Environment
Learn to build your own infrastructure-as-a-service using Python, Flask, and Docker. Create a Postgres-as-a-service system with just 300 lines of code, enabling self-service database provisioning and streamlining development workflows.
Real Virtual Environments Without Virtualenv
Explore Docker as an alternative to virtualenv for creating isolated, immutable, and repeatable Python development environments, enhancing consistency from development to production.
Grocker - A Python Build Chain for Docker
Streamlines Python package deployment by transforming projects into self-contained Docker images with easy-to-use entry points, ensuring atomic and deterministic code updates.
Planning for the Worst
Explore strategies for handling production issues, from common errors to obscure failures. Learn practical tips, best practices, and code solutions to enhance system reliability and resilience.
Analyzing Data with Python & Docker
Explore powerful data analysis workflows by combining Python and Docker. Learn to create robust, repeatable systems for small and large-scale data processing using containerization techniques.
Create Secure Production Environment Using Docker
Learn to create and maintain secure Docker containers for production environments, covering risks, best practices, and essential techniques for robust deployment.
System Testing with pytest and docker-py
Learn best practices for system testing microservices using pytest and docker-py. Discover how to write maintainable tests for large-scale online services, focusing on pre-launch quality assurance.
TDD of Python Microservices
Learn to create Python microservices using Test-Driven Development. Explore service and contract testing with Docker and Swagger for robust, confident development in a microservices architecture.
You Need More Security in Your Application Packaging
Explore secure application packaging methods, focusing on Python, to balance ease of installation with robust security measures for different environments and audiences.
There Should Be One Obvious Way to Bring Python into Production
Explore DevOps methodologies for deploying Python applications, covering packaging, deployment, environments, and runtime options. Learn about tools and frameworks to streamline the production process.
Dockerized Pytests
Explore containerizing pytest environments to replicate Jenkins setups locally, addressing challenges in custom plugins and dependencies for improved debugging and team collaboration.