Hi there! I've been studying Python for a few months now and I'm addicted to it. I'm currently on the lookout for remote work in this language since I am a full-time student in a remote area. I have experience with Django and I even created a website for my school, but unfortunately, they didn't want to pay for hosting, so it's still sitting on my Github somewhere.

I understand that the key to gaining practical experience is through hard coding, but sometimes I struggle with abstract tasks that don't necessarily translate to real-life applications. I've been advised by many to look for start-up opportunities, which I did, but it turned out to be overly ambitious and everyone ended up leaving. I'm still on the hunt for remote work and would love to keep busy with coding in the meantime.

I've come up with some applied tasks for myself and they've been helpful, but due to my lack of experience, I'm not entirely sure what specific projects I can tackle in Python. If anyone has a list of applied tasks or a resource they could share, I would greatly appreciate it.

Have you read Al Zweigart's Automating Boring Tasks with Python and not found anything helpful?

I highly recommend the book as an excellent resource for anyone interested in automating repetitive tasks using Python. With clear explanations, practical examples, and easy-to-follow instructions, this book is an ideal starting point for beginners and a valuable reference for experienced programmers.

What are the challenges of using Python for industrial automation and related tasks? As someone who has worked in this field for a considerable amount of time, I am curious about the hype surrounding Python and your recommendation piqued my interest. Is it really worth investing the time and effort into learning Python as opposed to, say, C++ which is commonly used for writing software for Programmable Logic Controllers (PLCs)? While languages like ST, FBD, and LD may be faster for PLCs, there are certain functions that cannot be carried out using these languages.

In terms of additional insight on the topic, it's worth noting that Python has gained a lot of traction in recent years due to its versatility and ease of use. Its strengths lie in data analysis and manipulation, which can be highly relevant in industrial settings where effective decision-making is heavily dependent on accurate data interpretation. However, when it comes to real-time control and high-speed applications, other languages may be better suited for the task. Ultimately, the choice between Python and other programming languages for industrial automation depends on the specific requirements of the application in question.

Numerous companies around the world, including Google and the makers of the Eve-online game, utilize Python. Popular media outlets such as the Washington Post and Instagram also offer fantastic Python libraries for various purposes, from implementing asynchronous servers to conducting data analysis.

Python's versatility and ease of use have made it a popular choice in the tech industry and beyond. Its capabilities extend beyond traditional programming tasks and can be used in fields such as data science and machine learning. As more companies continue to adopt this language, it is likely to remain a dominant force in the programming world.

Your experience with Django and the creation of a website for your school is commendable, despite the hosting setback. Having the project in your GitHub repository still serves as a valuable portfolio piece, showcasing your practical skills to potential employers.

One effective way to gain practical experience in Python is to engage in open-source projects. Platforms such as GitHub provide a plethora of opportunities to contribute to real-world codebases. Participating in open-source projects not only allows you to work on tangible applications of Python but also provides the chance to collaborate with seasoned developers, gaining valuable insights and mentorship in the process.

Freelancing on platforms like Upwork, Freelancer, or Fiverr can also offer a rich array of projects, encompassing everything from web development and data analysis to scripting and automation. Such freelance opportunities will expose you to diverse and practical tasks that can help you apply your Python skills in a real-world setting, all while adding valuable projects to your portfolio.

If abstract tasks present a challenge, I recommend embarking on mini-projects that align with your individual interests and goals. For example, you could work on building a web scraper to extract data from a website, develop a chatbot utilizing natural language processing libraries, or create a small-scale automation script to streamline a repetitive task. Focusing on projects that resonate with you fosters a deeper understanding and appreciation of Python in practical contexts.

Consider seeking mentorship or joining coding communities where you can seek advice and guidance on project ideas. Engaging with supportive communities can provide invaluable feedback and insights, ultimately enriching your journey from a Python learner to a proficient practitioner.

Online learning platforms such as Coursera, Udemy, and Codecademy offer specialized Python courses and tutorials that incorporate project-based learning experiences. These resources often include guided projects designed to help you apply your skills to real-world scenarios, covering an extensive range of topics from web development and data science to machine learning and beyond.
The path from learning Python to mastering it in a real-world setting demands perseverance and dedication. By actively seeking out projects, engaging with the community, and continually expanding your portfolio, you will be well-equipped to secure remote work opportunities and further enhance your skills as a Python programmer.