Luca Liu Blog | A self-taught coder who dreams of retiring early, working as a Data Analyst in Germany.

This article explores the transformative power of Python and its integration with AI for modern workers, particularly those without a coding background. It highlights how learning Python, specifically the Pandas library, can streamline Excel tasks by automating repetitive processes, handling large datasets, and simplifying complex calculations. Readers are guided on how to get started with online platforms like Deepnote and Google Colab, which require no installation. The article emphasizes leveraging AI to assist in code generation and encourages learning through experimentation. Real-world examples demonstrate Python's efficiency in data analysis, showcasing the significant productivity gains achievable by transitioning from traditional Excel methods to Python programming.

Discover how to quickly set up your NotionNext website with our step-by-step guide! Transform your Notion workspace into a fully functional website without coding knowledge. Learn to create a Notion page, fork the NotionNext source code from GitHub, and deploy your site on Vercel. With multiple theme options and a streamlined publishing process, NotionNext is perfect for showcasing your portfolio or monetizing your content. Start your journey today and join the community of creators simplifying their web presence!

NotionNext is an open-source solution for building personal blogs directly from your Notion workspace, leveraging Next.js and the Notion API. This tool simplifies the blogging process by creating a seamless connection between your Notion content and your website, eliminating the need for traditional content management. With benefits like enhanced performance, improved SEO, and customizable themes, NotionNext is perfect for content creators looking to streamline their publishing workflow. Additionally, maintaining a blog can lead to monetization opportunities and enhance career prospects. Discover how NotionNext can transform your online presence and content creation experience.

This article addresses the issue of URL path accumulation when building a multilingual blog using NotionNext. The problem arises when switching languages, leading to incorrect URL paths such as /zh/de instead of /de. The article analyzes the root causes, including Notion's menu configuration and Next.js routing behavior, and presents multiple attempted solutions. Ultimately, the author proposes a final solution involving hardcoded language menus that bypass Notion's system, offering better control and user experience. The implementation details are provided, including a new LanguageMenu component and modifications to existing menu components. This approach enhances navigation accuracy and simplifies maintenance, making it a viable recommendation for others facing similar multilingual functionality challenges in NotionNext.

This article provides a comprehensive guide on how to get responses from local LLM models using Python. It covers essential steps including starting your local LLM system, listing available models through a RESTful API, and generating responses using different endpoints. Readers will learn how to send prompts to the model for both simple completions and interactive chat-like conversations, with detailed Python code examples for each use case. By following this guide, users can effectively integrate LLM capabilities into their applications, enhancing productivity and automation.

Local LLMs are models that run directly on personal devices. They offer unique advantages such as enhanced privacy, offline functionality, and customizable use cases. In 2025, I predict local LLMs will become a cornerstone of personal and professional productivity tools.

This article discusses the benefits of using local Large Language Models (LLMs) like LLaMA, emphasizing advantages such as enhanced privacy, speed, cost-effectiveness, and customization. It provides a step-by-step guide for Mac users on downloading and installing LM Studio, selecting and running the LLaMA model, and exploring various use cases, including integration with Obsidian and Python. The conclusion encourages developers and life hackers to embrace local LLMs as a more innovative alternative to traditional AI interactions, highlighting their potential for the future.

Data Manipulation Language (DML) commands enable you to add, modify, or remove rows in a database. In this article, we’ll explore these commands with practical examples. The INSERT command is used to add new rows to a table. The UPDATE command allows you to modify data in existing rows. The DELETE command removes rows from a table based on a condition.

Python script automates the publication of Markdown files directly to Medium. The script sends a request to Medium’s API to fetch your user information. The response includes details like your user ID, which is required to publish content.

Tableau Desktop Public Edition is now free and packed with advanced features previously exclusive to Tableau Desktop Professional—excluding only enterprise database connectivity. Ideal for data enthusiasts, educators, and professionals, this powerful tool supports local file use, drag-and-drop visualizations, and cloud sharing for non-commercial purposes. Learn how to download, install, and get started with creating stunning data visualizations today.

Jupyter Notebook is a popular tool among data scientists and programmers for interactive data analysis, visualization, and machine learning. In this guide, we will walk you through the process of setting up Jupyer Notebook on a Windows server to enable remote access.

Combining data from multiple tables is a common requirement in Power BI. There are two primary methods to achieve this task. Using the DAX UNION function and using the Append Queries feature in Power Query are the best ways to do it. By following these two methods, you can effectively union two tables in power BI.