Search Results for "python mini project"

MiniJinja is a minimal-dependency template engine based on the syntax and behavior of Python’s Jinja2. It is implemented primarily for Rust and also has Go, JavaScript, Python, C, and CLI-related components. The project supports Jinja-style templates, inheritance, filters, expressions, dynamic objects, and serde-compatible data. It is designed to stay close to Jinja2 while keeping compile times, dependencies, and API surface manageable for Rust programs. MiniJinja can also be used as a small expression language or embedded template layer in larger applications. ...

Rye is a modern Python project and package management tool designed to provide a seamless development experience. It integrates Python installation, virtual environment management, and dependency handling into a single cohesive workflow. Rye's emphasis on simplicity and automation makes it particularly suitable for managing complex projects and monorepos, reducing the overhead typically associated with Python project setup and maintenance.​

Mise (formerly RTX) is a cross-language CLI tool and task runner that manages developer tools, environment variables, and project tasks in a unified configuration (mise.toml). It handles tool installation (e.g., Node, Python, Terraform), env var profiles, and repeatable command scripting.

MooseStack is an opinionated starter stack that assembles a modern web application foundation—project structure, build tooling, and deployment scripts—so teams can get from “blank repo” to a working product quickly. It provides a coherent layout for server and client code, standardizes environment configuration, and includes scripts to run the app locally with the same conventions you’ll use in staging or production. The stack favors convention over configuration: common decisions around...

Bend is an interactive programming environment (REPL) built on top of the Kotlin language, designed to allow users to explore, experiment, and learn Kotlin in a live, feedback-driven manner. The tool lets you define variables, functions, or values at the prompt and iteratively refine them—immediately seeing output and types—while preserving state across commands. It emphasizes discoverability and experimentation: users can inspect functions, call them on sample inputs, and evolve logic...