A lightweight command-line tool for performing arithmetic and symbolic math operations directly in the terminal.
Mdlt is a command-line utility that allows users to perform arithmetic and symbolic math operations directly from the terminal. It solves the problem of needing to boot Python with SymPy or search for online math tools by providing instant access to calculations like derivatives and integrals.
Developers, students, and professionals who frequently need to perform quick mathematical calculations without leaving their terminal workflow.
Mdlt offers a faster and more convenient alternative to launching Python or using web-based math tools, with a lightweight design and simple command syntax that integrates seamlessly into terminal usage.
A command-line utility for quick math.
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Installs globally via npm in seconds and executes calculations immediately without booting Python, as emphasized in the README for quick terminal access.
Uses intuitive commands like 'mdlt derive x^2' with minimal setup, making it easy to perform operations without learning complex APIs.
Designed to keep users in the terminal workflow, eliminating context switches to web tools or external applications, as highlighted in the philosophy.
Provides core symbolic operations like derivatives and integrals directly from the CLI, demonstrated in the README with examples like deriving x^2.
Focused on basic arithmetic and symbolic operations; lacks advanced features such as matrix algebra, equation solving, or statistical functions, which are common in full CAS tools.
The README notes that wrapping expressions in double quotes is recommended for reliable processing, indicating potential fragility with complex or ambiguous input syntax.
Requires Node.js and npm for installation, making it unsuitable for environments where these are not available or where lightweight, standalone binaries are preferred.
Documentation is linked externally to a DOCS.md file, and the README provides only minimal examples, which could slow down onboarding without additional reference.