As a web developer today, most of your works are related to APIs.

But most of developers don't actually understand what it is. 👀

When we talk about API, we are usually referring to Web API. 🌐

Web API (Application Programmatic Interface) can provide:

1. Resources, e.g. bus arrival time, restaurant ratings...
2. Services or microservices, e.g. converting coordinates into place names, creating QR codes...

With Web APIs, developers can then easily incorporate these building blocks into other web applications.

👩‍💻There's some features of different Web API, for example:

1. Public vs. private
- Public APIs are available to everyone, but may subject to licenses
- Private APIs are only available to internal developers

2. Free vs. premium
- Premium APIs may charge on-demand
- That's why there's also this term “API Economy”!

There's actually API marketplace and directory site, like
- RapidAPI
- ProgrammableWeb

Here's some example of public API that you can explore:

1. Google (developers.google.com/apis-explorer)

2. Facebook (developers.facebook.com/docs/apis-and-…)

3. Data portals of many cities (dataportals.org/search)And you also have to understand what is 'API endpoints'.

API usually provides endpoints as a URI to provide services.

And it needs to be static, without affecting applications built upon ✨And that's why there's a standard for writing API called REST.

REST stands for 'REpresentational State Transfer'.

It's an architectural style of writing APIs.

Answer is 8 64

👉The code defines a Square class with a method getArea that calculates the area of a square using the side attribute.

👉An instance of the Square class is created which is obj, It has side = 8,

👉its area is calculated by calling getarea.

What will be the output of the following code:


my_list = [1, 2, 3, 4, 5]
print(my_list[1:4])

a) [1, 2, 3]
b) [2, 3, 4]
c) [2, 3]
d) [1, 3, 4]

Useful AI tools

Pdf on private group

https://t.me/+eweUkdFwlho4YjRl

If your goal is to be a Python expert in 2024, this thread is for you:
Here's what we will cover:

✔ A 12-months roadmap
✔ Some prerequisite activities
(described at the end of the thread)

➤ Month-1

Activity: Working with Data [1]
Effort: 2 hours daily w/ simple practice

✧ Boolean
❯ bool
✧ Number
❯ int
❯ float
❯ complex
✧ String
❯ str
✧ Bytes
❯ bytes
❯ bytearray
❯ memoryview

➤ Month-2

Activity: Working on Logic
Effort: 2 hours daily w/ simple practice

✧ Operators
❯ Arithmetic
❯ Assignment
❯ Comparison
❯ Logical
❯ Precedence
❯ Associativity
✧ Conditionals
❯ If
❯ Else
❯ Elif
✧ Loops
❯ while
❯ for

➤ Month-3

Activity: Modularize your Code
Effort: 2 hours daily w/ simple practice

✧ Function
❯ Definition
❯ Arguments
❯ Positional
❯ Keyword
❯ Return
❯ Execution
✧ Module
❯ Define
❯ Import
✧ Scope and Namespace


➤ Month-4

Activity: Working with Data [2]
Effort: 2 hours daily w/ simple practice

✧ list
✧ tuple
✧ set
✧ frozenset
✧ dict

➤ Month-5

Activity: Working with Data [3]
Effort: 2 hours daily w/ simple practice

Learn about these modules
✧ datetime
✧ csv
✧ json
✧ logging
✧ re
✧ os

In addition,
❯ Files
❯ String Formatting
❯ Named Tuples
➤ Month-6

Activity: Exam Time
Effort: 2 hours daily w/ rigorous practice

⬘ Build at least 5 simple projects (Example: Scientific Calculator, File Manager, etc.)

⬙ Revise previous topics.


➤ Month-7

Activity: Deep-dive Python Concepts
Effort: 2 hours daily w/ simple practice

✧ Iterators
✧ Generators
✧ Closure
✧ Decorators
✧ Exception Handling


➤ Month-8

Activity: Object Oriented Programming
Effort: 2 hours daily w/ simple practice

✧ Class
✧ Variable
✧ Method
❯ Static Method
❯ Magic Method
✧ Overloading
✧ Inheritance
✧ Property Decorators

➤ Month-9

Activity: Exam Time
Effort: 2 hours daily w/ rigorous practice

⬘ Build at least 3 projects using OO feature (Examples: FIFA World Cup, COVID Tracker, etc.)

⬙ Revise all previous topics.


➤ Month-10

Activity: Take it to next level [1]
Effort: 2 hours daily w/ simple practice

✧ Jupyter Notebook
✧ Spyder

✧ pip
✧ anaconda
➤ Last 2 months

Activity: Take it to next level [2]
Effort: 2 hours daily

✧ numpy
✧ pandas
✧ matplotlib
✧ scipy

P.S: Practice while learning
➤ Prerequisite: Know the History

Before start learning a language, read about its history.

❯ Why and how did it come into existence?
❯ How does it evolve over time?
❯ What are its alternatives?
❯ Where is it going to be a show-stopper?


➤ Prerequisite: Know the Ecosystem

❯ Which version you should be using?
❯ How to update to newer versions?
❯ Where would you write a program?
❯ How would you run a program?
❯ What additional software do you need?
❯ How would you include third-party libraries?


➤ Prerequisite: OS Challenge

Although the majority of languages strive to be similar across all operating systems, some dependencies may exist.

❯ Which installation package to download?
❯ How to install it?
❯ What are the different commands available?


🏁 Final Words

⬘ Though I have time bound it, you should try to cover everything based on your suitability.

⬗ Spend at least two hours per day learning and practicing.

⬙ With a proper structure and goal, it's never hard to learn Python.

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