https://www.tecmint.com/convert-md-to-pdf-on-linux

How to Convert Markdown (.MD) Files to PDF on Linux

Markdown (.MD) files are a favorite among developers, writers, and content creators due to their simplicity and flexibility, but what happens when you need to share your beautifully formatted Markdown file with someone who prefers a more universally accepted format, like PDF?

On Linux, you have several tools and methods to achieve this seamlessly and this guide will walk you through the process of converting .MD files to .PDF, ensuring your documents look professional and polished.

Method 1: Using Pandoc – A Document Converter

Pandoc is a powerful command-line tool for converting files between different formats and most Linux distributions have Pandoc available in their repositories.

sudo apt install pandoc         [On Debian, Ubuntu and Mint]
sudo dnf install pandoc         [On RHEL/CentOS/Fedora and Rocky/AlmaLinux]
sudo apk add pandoc             [On Alpine Linux]
sudo pacman -S pandoc           [On Arch Linux]
sudo zypper install pandoc      [On OpenSUSE]    
sudo pkg install pandoc         [On FreeBSD]

Once installed, converting a Markdown file to PDF is as simple as running a single command:

pandoc input.md -o output.pdf

Convert MD File to PDF

Method 2: Markdown Preview in VS Code

Visual Studio Code (VS Code) is a popular text editor that supports Markdown preview and export.

First, install VS Code from your distribution’s repository or download it from the official site and then install the Markdown PDF extension.

Install Markdown PDF Extension

Next, open your .md file in VS Code and press F1 or Ctrl+Shift+P and type export and select markdown-pdf: Export (pdf).

VS Code Convert MD to PDF File

Method 3: Using Grip Tool

Grip is a Python-based tool that renders Markdown in your web browser, which is especially useful for previewing Markdown as it would appear on GitHub.

pip install grip

Once installed, you can run the following command to render your Markdown file:

grip sample.md

Grip starts a local server, open the provided URL in your browser, and then use the browser’s print functionality to save the rendered file as a PDF.

Method 4: Using Calibre eBook Manager

Calibre is a feature-rich eBook management tool that supports various formats, including Markdown.

sudo apt install calibre         [On Debian, Ubuntu and Mint]
sudo dnf install calibre         [On RHEL/CentOS/Fedora and Rocky/AlmaLinux]
sudo apk add calibre             [On Alpine Linux]
sudo pacman -S calibre           [On Arch Linux]
sudo zypper install calibre      [On OpenSUSE]    
sudo pkg install calibre         [On FreeBSD]

Once installed, open Calibre and add your .md file and then right-click on the file and select Convert Books > Convert Individually.

Choose PDF as the output format and click OK.

Convert .md to PDF in Linux

Conclusion

Converting Markdown to PDF on Linux is straightforward and offers multiple methods tailored to your workflow. Whether you prefer the command-line power of Pandoc, the simplicity of VS Code, or the visual rendering of Grip, Linux has you covered.

With these tools, you can create professional, shareable PDFs from your Markdown files in no time.

 

https://www.tecmint.com/best-ai-coding-assistants

6 AI Tools Every Developer Needs for Better Code

In today’s fast-paced world, developers are constantly looking for ways to improve their productivity and streamline their workflows. With the rapid advancements in Artificial Intelligence (AI), developers now have a wide range of AI-powered tools at their disposal to make their coding experience faster, easier, and more efficient.

These tools can automate repetitive tasks, help write cleaner code, detect bugs early, and even assist in learning new programming languages.

In this blog post, we’ll dive deep into some of the best AI tools available for developers. We’ll explore their key features, how they can help boost productivity, and why they are worth considering for your development process.

1. GitHub Copilot

GitHub Copilot is an AI-powered code assistant developed by GitHub and OpenAI, which is designed to assist developers by suggesting code as they type and help you write entire functions, classes, or even entire files based on the context of your code.

GitHub Copilot · Your AI Pair Programmer

Key Features:

• Code Suggestions: Suggests entire lines or blocks of code based on the current context by using the vast amount of code available on GitHub to provide accurate and relevant suggestions.
• Multiple Language Support: Supports many programming languages, including Python, JavaScript, Ruby, TypeScript, Go, and more. It can also suggest code for various frameworks like React, Django, and Flask.
• Context Awareness: It adapts to the code you are writing and understands the context, making its suggestions more relevant and precise.
• Learning from Your Code: Over time, it learns from your coding style and preferences, tailoring its suggestions to fit your unique way of writing code.

Why It’s Useful:

GitHub Copilot can significantly reduce the time developers spend searching for code snippets or writing repetitive code. By suggesting code based on your current work, it can help you stay focused on the problem you’re solving rather than worrying about the syntax or implementation details.

2. Tabnine

Tabnine is another AI-powered code completion tool that integrates seamlessly with your Integrated Development Environment (IDE) and uses machine learning models to predict and suggest code completions as you type, making coding faster and more efficient.

Tabnine AI Code Assistant

Key Features:

• Code Autocompletion: Its ability to suggest completions such as variables, functions, and entire code blocks for your code based on what you’re currently typing.
• Private Models: If you’re working on a proprietary codebase or project, it allows you to use private models, which means the AI can learn from your team’s code and provide more tailored suggestions.
• Works with Multiple IDEs: It integrates with popular IDEs like Visual Studio Code, IntelliJ IDEA, Sublime Text, and many others.
• Team Collaboration: It can help teams maintain consistency in coding practices by providing suggestions that align with the team’s coding standards and style.

Why It’s Useful:

Tabnine is a great tool for developers who want to write code faster without sacrificing quality, which can help reduce the need for looking up documentation or searching for code snippets online.

3. Codex by OpenAI

Codex is a powerful AI model developed by OpenAI that can generate code from natural language descriptions. It powers GitHub Copilot and can assist developers in writing code by simply describing what they want to achieve in plain English.

Codex by OpenAI

Key Features:

• Natural Language to Code: It can take plain English instructions and convert them into working code. For example, you can tell it “Create a Python function that calculates the Fibonacci sequence”, and it will generate the code for you.
• Multi-Language Support: It supports a wide range of programming languages, including Python, JavaScript, Ruby, and more. It can also handle various frameworks and libraries.
• Context-Aware Suggestions: It understands the context of the code you’re writing and provides relevant suggestions, which makes it more accurate and helpful in complex coding scenarios.
• Code Explanation: It can also explain the code it generates, helping developers understand the logic behind it.

Why It’s Useful:

Codex is a game-changer for developers who are new to programming or learning a new language. It allows you to describe what you want to achieve in simple terms and get code suggestions, which can save a lot of time and help you overcome coding challenges quickly.

4. Sourcery

Sourcery is an AI-powered tool specifically designed for Python developers, which helps improve code quality by automatically suggesting refactorings and improvements to make the code cleaner, more efficient, and easier to maintain.

Sourcery – Instant Code Review

Key Features:

• Code Refactoring: It analyzes your Python code and suggests refactorings to improve its readability and performance by recommending changes like merging duplicate code, simplifying complex expressions, and improving variable names.
• Code Suggestions: It can suggest improvements in real-time as you write code, which helps you follow best practices and avoid common mistakes.
• Instant Feedback: It provides instant feedback, allowing you to make improvements as you write code, rather than having to go back and refactor everything at the end.
• Supports Multiple IDEs: It integrates with popular IDEs like Visual Studio Code and PyCharm, making it easy to use in your existing development environment.

Why It’s Useful:

Sourcery is perfect for Python developers who want to improve the quality of their code without spending too much time on manual refactoring. It ensures your code is clean, efficient, and easy to maintain, which is especially important in larger projects.

5. IntelliCode by Microsoft

IntelliCode is an AI-powered tool developed by Microsoft to enhance the IntelliSense feature in Visual Studio and Visual Studio Code by using machine learning to provide smarter, context-aware code suggestions that help developers write code faster and with fewer errors.

Visual Studio IntelliCode – Microsoft

Key Features:

• Smart Code Suggestions: It suggests the most relevant code completions based on the context of your project by learning from the code in your repository and provides suggestions that match your project’s style.
• Code Style Recommendations: It can recommend code that follows best practices and aligns with your project’s coding style, which can also suggest refactorings to improve code quality.
• Refactoring Assistance: It can help you refactor your code by suggesting improvements in structure and readability.
• Multi-Language Support: It supports several languages, including C#, C++, Python, and JavaScript, making it useful for a wide range of developers.

Why It’s Useful:

IntelliCode is ideal for developers who want to write code more efficiently while following best practices, which ensure that your code is consistent with your project’s coding standards and suggest improvements that can make your code more readable and maintainable.

6. DeepCode

DeepCode is an AI-powered code review tool that helps developers identify bugs, security vulnerabilities, and code quality issues in their code by using machine learning to analyze code and suggest improvements.

DeepCode – AI Code Review

Key Features:

• Code Analysis: It scans your code for potential issues, such as bugs, security vulnerabilities, and performance bottlenecks.
• Automated Code Review: It provides automated code reviews, saving you time and effort during the development process.
• Multi-Language Support: It can analyze code in various programming languages and provide suggestions for improvements.
• Integration with GitHub and GitLab: It integrates seamlessly with popular version control platforms like GitHub and GitLab, making it easy to add to your workflow.

Why It’s Useful:

DeepCode is an invaluable tool for developers who want to ensure that their code is free from bugs and security vulnerabilities. It helps you catch issues early in the development process, reducing the chances of problems later on.

Conclusion

AI tools are revolutionizing the way developers work, making coding faster, more efficient, and error-free. From code completion and suggestions to automated code reviews, AI tools like GitHub Copilot, Tabnine, Codex, Sourcery, IntelliCode, and DeepCode can significantly boost your productivity as a developer.

 

https://www.tecmint.com/mmv-command-linux

How to Rename Files Using mmv for Advanced Renaming

Ravi SaiveLast Updated: January 3, 2025 Read Time: 3 minsCategories Linux Commands Leave a comment

Renaming files in Linux is something we all do, whether it’s to organize our files better or to rename files in bulk.

While there are basic tools like mv and rename, there’s an advanced tool called mmv that makes the process much easier, especially when you need to rename multiple files at once.

As an experienced Linux user, I’ve found mmv to be a powerful tool for batch renaming files, and in this post, I’ll show you how to use it effectively.

What is mmv?

mmv stands for multiple move, which is a command-line utility that allows you to rename, move, and copy multiple files at once. Unlike the mv command, which is great for renaming one file at a time, mmv is designed to handle bulk renaming with ease.

To install mmv on Linux, use the following appropriate command for your specific Linux distribution.

sudo apt install mmv         [On Debian, Ubuntu and Mint]
sudo yum install mmv         [On RHEL/CentOS/Fedora and Rocky/AlmaLinux]
sudo emerge -a sys-apps/mmv  [On Gentoo Linux]
sudo apk add mmv             [On Alpine Linux]
sudo pacman -S mmv           [On Arch Linux]
sudo zypper install mmv      [On OpenSUSE]    
sudo pkg install mmv         [On FreeBSD]

Once installed, you’re ready to start renaming your files.

The basic syntax of mmv is:

mmv [options] source_pattern target_pattern

• source_pattern: This is the pattern that matches the files you want to rename.
• target_pattern: This is how you want the renamed files to appear.

For example, if you want to rename all .txt files to .md files, you would use:

mmv '*.txt' '#1.md'

Here, #1 refers to the part of the filename matched by the * wildcard.

Examples of Using mmv for Advanced Renaming in Linux

Here are some advanced examples of how to use mmv effectively:

1. Renaming Multiple Files with a Pattern

Let’s say you have several files like file1.txt, file2.txt, file3.txt, and so on and you want to rename them to document1.txt, document2.txt, document3.txt, etc.

Here’s how you can do it:

mmv 'file*.txt' 'document#1.txt'

In this example:

• file*.txt matches all files starting with file and ending with .txt.
• document#1.txt renames them to document1.txt, document2.txt, etc.

Renaming Files with a Pattern

2. Renaming Files by Adding a Prefix or Suffix

Let’s say you want to add a prefix or suffix to a group of files. For example, you have files like image1.jpg, image2.jpg, image3.jpg, and you want to add the prefix 2025_ to each file.

Here’s how you do it:

mmv '*.jpg' '2025_#1.jpg'

This will rename the files to 2025_image1.jpg, 2025_image2.jpg, etc.

If you wanted to add a suffix instead, you could use:

mmv '*.jpg' '#1_2025.jpg'

This will rename the files to image1_2025.jpg, image2_2025.jpg, etc.

Renaming Files with Prefix

3. Renaming Files with Regular Expressions

mmv supports regular expressions, so you can use them to match complex patterns. For example, let’s say you have files like data_01.txt, data_02.txt, data_03.txt, and you want to remove the leading zero in the numbers.

You can do this with:

mmv 'data_0*.txt' 'data_#1.txt'

Renaming Files with Regular Expressions

4. Renaming Files in Subdirectories

If you have files in subdirectories and want to rename them as well, you can use the -r option to rename files recursively. For example, if you want to rename all .txt files in the current directory and all subdirectories:

mmv -r '*.txt' '#1.txt'

This will rename all .txt files in the current directory and its subdirectories.

Conclusion

Renaming files in Linux doesn’t have to be a tedious task. With mmv, you can easily rename multiple files with advanced patterns, saving you time and effort. Whether you need to add a prefix, change extensions, or rename files in bulk, mmv has you covered.

Give it a try, and let me know how it works for you! If you have any questions or need further help, feel free to leave a comment below.