Average Reads version 2!
Version 1 of this project was my final for CS50Python. The write-up can be found here up here.
For the project's next iteration, I wanted to move the functionality to a web-based framework to practice building a Python-based fullstack application. This would make it easier to use, read, and share what I have been working on. This version is much closer to what I had envisioned when starting! The application is now using Flask and SQLAlchemy to add, edit, and update books across the three reading lists and you can download all three lists in one CSV file to your computer.
The trickiest part, besides deploying a Flask app for the first time, was once again the CSV download portion. I was able to carry over most of the code from my past version to run the "save to a CSV" function, but it had to be set up in a slightly different way for the web app. I had not realized to use the function "send_from_directory," the folder had to be created first to save the file, then download it to your computer. It was a good feeling figuring that one out though ?
I was able to keep most of the title formatting and error-checking functionality but was easier to show in a more visual way with on page warnings. Such as letting you know if a book was already on one of the three lists, if there were no books to download (lists are empty), and title case any entered book titles. There are a few more enhancements I'd like to do with this one but needed a bit of a break. I want to update the styling a bit more, update the book editing functionality, and add a graphic I had sketched for the header.
PyLadiesCon 2024
Since my reinterest in Python, I searched for the next date and location for the next PyCascades (spoiler alert, Portland, Oregon, February 2025) and came across PyLadiesCon! This free online conference occurred from December 6 to 8 in multiple timezones and languages. I couldn't make it to listen to all in real time, as there were side chats, questions, and conversations happening in tandem on their Discord server. I'm now going back through some of the recorded talks I was interested in.
PyLadiesCon Video Playlist
Some of the talks I was most interested in were How to Stop an Epidemic using the Atomica Python Tool, Empowering Sustainable Agriculture: Quantifying the Impact of Water Resources Management Practices with Python, and PyLadies in Open Source. I plan on researching and hopefully participating in a bit more open-source work starting next year and Python seems to be the community to lean into.
Although JavaScript is a recommended language for newbie coders to pursue in web development, it can be a bit scary to venture to other languages or even know where to start. CS50Python helped me get a leg up in learning Python and what can be done with the language, my interest has grown again in the past few months. Even though the fundamentals are generally the same, for some reason, I've enjoyed working with Python and seem to understand it a bit more than JavaScript. I'll still be working with JavaScript (and React) but I'd like to shift a bit more to Python projects. More to come in a future 2025 goals post.
The above is the detailed content of Average Reads and PyLadiesCon 4. For more information, please follow other related articles on the PHP Chinese website!

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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