Tips to push your Python skills to the next level
Tags: python, practice, learning, challenges
Published: 2022-06-26 10:00:27

### What are open-source projects and how can you contribute to them?
Open-source projects are projects that have source code public. This allows you to view the source code, make changes to the program and share these changes with a community of developers. Contributing to open-source projects is a great way to build your Python programming skills, and give you real world experience for your resume.

### What is a good routine to learn programming?
The core of a programming routine should be completing projects. This gives you an opportunity to build and display skills at the same time. Taking courses is a great way to learn about a programming language and find new techniques but is not enough.
You can also get involved with hackathons and other programming meetup events. These events are a great way to meet other developers and work on [real-world projects](https://practity.com/project/python/).
Programming puzzles improve your general problem solving skills and python understanding. These style of programming questions are often found in industry interviews.
Learning from senior developers is a great idea. Reviewing software written by experienced developers can provide you a deeper understanding of documentation, project structure and clean code standards.

### What are some types of Python projects?
There is a large number of projects you can do. To stay motivated the best choice is to choose a topic that interests you. If you are interested in airplanes create a program related to aviation!


### What are some Python programming project ideas?
Image recognition – Find an image you want to recognize. For example, a food detection app that detects burgers from other fast food items.
Build a calculator web-app – You can convert mass from pounds to kilograms or perform another useful calculation.
Text based games – You can create a text based adventure game using the command line and print statements.
API project – Use data from an available API and use this data for a calculation. For example, displaying the local weather data from a weather python package or API.

### What are some essential Python packages to know?
 One of the many reasons Python is so popular is due to the wide range of packages available. There are packages for many applications from data science to space!
Pandas: Pandas is a fast and efficient tool for manipulating data in Python.
NumPy: NumPy is package for Python that features a wide range of array operations. Doing a computation in NumPy compared to using iterative methods is much faster.
Pip3: Pip is a Python package that installs other packages.
Pytest: A common library for unit testing and testing python scripts. Testing is an important part of industry skills.
Anaconda: Anaconda is not a package, it is a collection of common packages for data-science. Anaconda can get you started with machine learning or other analytical tasks.
Scikit-learn: A library for machine learning.
Requests: This package is very useful to interact with websites. It allows you retrieve the HTML information of a given site.
BeautifulSoup: This package makes web-scraping easier. Web-scraping involves getting data from a website. A Python script that retrieves the latest sports scores from a sports blog is an example of how web-scraping can automate common tasks.

### How to make sure your code is up to par?
Ask other developers on communities like stack-overflow. By participating in online discussions, you can learn new techniques. For example, if you post a Python problem that uses recursion, someone may show you a way to do it with a much faster solution.

### What are some good events to meet other programmers?
- Online forums or communities.
- Hackathons (both virtual and in person are a great opportunity).
- Local meetups and groups.
- Conferences and conventions.

### What are some common personality traits that help when learning programming?
Perseverance: Learning a programming language isn’t easy, and it can take a lot of working out errors. Its something that you need to stick with if you want to develop skills long term.
Creativity: Being able to think creatively when brainstorming potential solutions is a plus.
Problem solving: Being able to be confident and calm while solving complex problems is important. Develop a flow or pattern you use to examine programming challenges. When you first get a programming challenge with a series of cases and desired logic, how do you turn this into an algorithm? The more you become familiar with solving other problems the better this will be. Remember to stay up to date with Python data structures and algorithms so you can have an efficient program.
Constant learning: Programming as a field is always changing. Staying up to date with what is going on is essential to get ahead. Make sure you spend a bit of time each week learning new topics or technologies.

### Should I take more courses to improve my Python programming skills?
 Taking courses is a nice way to learn new tactics or approaches, but is not enough. Once you have a solid broad understanding of the language, you can take more specific courses. If you are interested in AI applications, take a course on machine learning using Python. If you are interested in blockchain smart-contracts using Python, take a course on that. There are many specialties that you can look into.

### What topics should I focus on to learn Python?
OOP: Object oriented programming is a methodology for building programs.
Data structures and algorithms: By learning various data structures and algorithms you can ensure that you create your programs in an efficient manner. Learning how sorting techniques work, learn algorithms such as tree traversal, recursion tactics, and distributed hash tables.
Devops: Learn deployment paths and common cloud architecture set ups. You can even learn server-less methods.
Front end / full-stack development: Learn Flask or Django. These are powerful frameworks that can be used to create the front-end user experience for your websites.
Program run times or “Big O Analysis”: Learn the theoretical computation of various algorithms. Your ability to think through different potential solutions based on computational run time will impress job interviewers.