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Welcome to my 🌟  Roadmap Full Stack Python 🌟  (which is also my number 100 repository on GitHub - at the end of 2021)

If you're reading this before 01/01/2022, I want to wish you a Happy New Year and lots of health! 🙏 

Anyway, enough of the presentations, and let's get down to business!

Shortcuts

  • The base of the trail:

    ° HTML5 CSS3 JavaScript

  • Popular CSS Frameworks:

    ° TailwindCSS SASS Less

  • JS Packages Manager:

    ° NPM Yarn

  • Complete Frameworks Front-End:

    ° Gatsby Bootstrap

  • Frameworks JS:

    ° React Angular.js Vue.js

    ° NestJS NextJS NuxtJS

OBS.: My advice is, you should master the basics, and select 1 framework from each sub-topic to specialize in (remember: the focus here is Python for the Web, don't worry so much about the Front-End issue, the unless you want to be a Full Stack developer with an emphasis on Front End).

Ok, It may seem like little to study, but Django's ecosystem is vast (it can take months to develop a good foundation and generate a few small projects). But if you are patient, this time spent will pay off! ✌️😉 

Flask is generally the second most used python framework on the web (second only to Django); for a few reasons: in addition to being simpler than its competitor (Django), it provides more freedom and flexibility to the developer. Very suitable for small building web applications.

FastAPI (different from Flask and Django), was made thinking about making API's easier to build - but it is highly recommended in the technology market, so I think it's good to take some time to study it!

  • 🧮  DataBases (Type: Structured)

    ° MicrosoftSQLServer MySQL Postgres SQLite

  • 🗂  DataBases (Type: No Structured - NoSQL)

    ° MongoDB Redis ApacheCassandra

  • 🔎  ORM's

    ° Prisma Sequelize

Database is an essential part for developing all kinds of applications. Here you can choose any of the alternatives presented, it won't have such a big impact on your coding ability (but be aware of what the market may demand).

  • 📜  CI/CD trail

    ° CircleCI GitLab CI GitHub Actions TravisCI

  • ☁️  Cloud Services trail

    ° AWS Azure Google Cloud

  • 🏢  Hosting(Deploy) trail

    ° Firebase Heroku Netlify Vercel

  • 📝  Version Control trail

    ° Git GitHub GitLab Bitbucket

  • 🚛  Containers Management trail

    ° Docker Kubernetes

OBS.: Git is a desktop tool we use to manage project versions on our local machine. the other tools are cloud services that allow the developer to manage projects and changes in a virtual environment.

  • Data Analysis & Data Science tail:

    ° NumPy Pandas Plotly

    TensorFlow Keras

So dear reader, I need to inform you of the following: With the advent and advances of Artificial Intelligence, we developers need to be aware of this. Even more so now with the integration between Web and Neural Networks increasingly intertwined.

And beyond that, Python is the most popular and recommended when it comes to Data Analysis and Science! So, be smart (it may take time to build your stack, but knowledge in the data area will benefit you in the long run).

👨‍💻  My Stack

At the moment I am still working on the base. After much research, testing and experimentation, I chose these technologies to compose my Stack:

On the Front-End:

HTML5 CSS3 TailwindCSS

JavaScript React Next JS

On the Back-End

Django DjangoREST

FastAPI Flask

On the DataBases:

SQLite MongoDB Postgres

On the Infrastructure:

Docker Azure

GitHub Actions TravisCI

Heroku Vercel

Git GitHub

On the Data Analysis/Science:

Numpy Pandas Keras

The repositories that helped me build this roadmap: Markdown Badges of Roadmap

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