Python BootCamp

Facebook Developers Circle Nairobi at Zetech University || CodeIT, Zetech University

5 Weeks Of Python (Roadmap)

Week 1: Environment Setup and Introduction

Downloading Python

Python comes pre-installed on Linux OS. For Windows you will have to Download. Download Python here

Resources

Python For Beginnes

Text Editors

Use a text-editor of your choice:

Recommended are:

Visual Studio Code Atom Sublime Text

Git and GitHub Setup.

Note that you have to pass the challenges in git and github to proceed to the next stages. They are essential tools in development for code sharing and collaboration.

Get Started Here

Raise an Issue if encountering a blocker

Practice Code

1. Print
2. Variables
3. Dates
4. Error Handling
5. Conditions

Week 2

1. Collections (list, arrays, ranges)
2. Loops
3. Functions
4. Functions with Parameters
5. Modules & Packages
6. JSON with Python
7. Decorators

Week 3

1. Formatting & Linting
2. Lambdas
3. Classes
4. Inheritance
5. Mixins
6. File System Management
7. Asynchronous Programming

Week 4: Data Tools

1. Jupyter Notebooks
2. Anaconda, Conda & Colabs
3. Introduction to Pandas
4. Pandas: dataframe contents
5. Pandas: dataframe querry
6. CSV files & Jupyter
7. Read/Write CSV Files with Pandas

Week 5: Data Tools

1. Removing & Splitting dataframe columns
2. Duplicate rows & Missing Values
3. Split Testing & Data Training with scikit learn
4. Train linear Regression Model with scikit learn
5. Model testing
6. Numpy & Pandas
7. Visualizing data with Matplotlib

Setting Up Your Developer Environment

Python

Preferably version 3,

Download Python

git

Download Git

Git Configuration

GitHub Account

Create Account

What You Need:

As the Bootcamp is open to anyone, we encourage members of our community, Facebook Developers Circle Nairobi at Zetech University to actively engange in the activities.

Contributing To The Repo

1. Fork the repo to your GitHub Account. Guide

2. Create a new branch with a name in conjuction to your update/fix

   Read More On Contributions

# WEEK 1: Introduction

1. Print

   The print function allows you to send output to the terminal

   • print

   Strings can be enclosed in single quotes or double quotes

   • "this is a string"
   • 'this is also a string'

   The input function allows you to prompt a user for a value

   • input

   Parameters:

   • prompt: Message to display to the user

   return value:

   • string value containing value entered by user

2. Variables: Numeric

   Python can store and manipulate numbers. Python has two types of numeric values: integers (whole numbers) or float (numbers with decimal places)

   • numeric types

   When naming variables follow the PEP-8 Style Guide for Python Code

   • PEP-8 Style Guide

   Converting to numeric values

   • int
   • float

3. Variables: String

   Python can store and manipulate strings. Strings can be enclosed in single or double quotes. There are a number of string methods you can use to manipulate and work with strings

   • strings
   • string methods

   Converting to string values

   • str

   When naming variables follow the PEP-8 Style Guide for Python Code

   • PEP-8 Style Guide

4. Dates

   The datetime module contains a number of classes for manipulating dates and times.

   Date and time types:

   • date stores year, month, and day
   • time stores hour, minute, and second
   • datetime stores year, month, day, hour, minute, and second
   • timedelta a duration of time between two dates, times, or datetimes

   When naming variables follow the PEP-8 Style Guide for Python Code

   • PEP-8 Style Guide

   Converting from string to datetime

   • strptime

5. Error Handling

   Error handling in Python is managed through the use of try/except/finally

   Python has numerous built-in exceptions. When creating except blocks, they need to be created from most specific to most generic according to the hierarchy.

6. Conditions

   Conditional execution can be completed using the if statement

   if syntax

   if expression:
      # code to execute
   else:
      # code to execute

   Comparison operators

   • < less than
   • < greater than
   • == is equal to
   • >= greater than or equal to
   • <= less than or equal to
   • != not equal to

7. Multiple Conditions

   Conditional execution can be completed using the if statement. Adding elif allows you to check multiple conditions

   if syntax

   if expression:
      # code to execute
   elif expression:
      # code to execute
   else:
      # code to execute

   Boolean operators

   • x or y - If either x OR y is true, the expression is executed

   Comparison operators

   • < less than
   • < greater than
   • == is equal to
   • >= greater than or equal to
   • <= less than or equal to
   • != not equal to
   • x in [a,b,c] Does x match the value of a, b, or c

# Week 2: The Basics

1. Collections (list, arrays, ranges)

   Collections are groups of items. Python supports several types of collections. Three of the most common are dictionaries, lists and arrays.

   Lists

   Lists are a collection of items. Lists can be expanded or contracted as needed, and can contain any data type. Lists are most commonly used to store a single column collection of information, however it is possible to nest lists

   Arrays

   Arrays are similar to lists, however are designed to store a uniform basic data type, such as integers or floating point numbers.

   Dictionaries

   Dictionaries are key/value pairs of a collection of items. Unlike a list where items can only be accessed by their index or value, dictionaries use keys to identify each item.

2. Loops

   For loops

   For loops takes each item in an array or collection in order, and assigns it to the variable you define.

   names = ['Christopher', 'Susan']
   for name in names:
      print(name)

   While loops

   While loops perform an operation as long as a condition is true.

   names = ['Christopher', 'Susan']
   index = 0
   while index < len(names):
      name = names[index]
      print(name)
      index = index + 1

3. Functions

   Functions allow you to take code that is repeated and move it to a module that can be called when needed. Functions are defined with the def keyword and must be declared before the function is called in your code. Functions can accept parameters and return values.

   • Functions

   def functionname(parameter):
      # code to execute
      return value

4. Functions with Parameters

   Functions allow you to take code that is repeated and move it to a module that can be called when needed. Functions are defined with the def keyword and must be declared before the function is called in your code. Functions can accept one or more parameters and return values.

   • Functions

   def function_name(parameter):
      # code to execute
      return value

   Parameters can be assigned a default value making them optional when the function is called.

   def function_name(parameter=default):
      # code to execute
      return value

   When you call a function you may specify the values for the parameters using positional or named notation

   def function_name(parameter1, parameter2):
      # code to execute
      return value
   
   # Positional notation pass in arguments in same order as parameters are declared
   result = function_name(value1,value2)
   
   # Named notation
   result = function_name(parameter1=value1, parameter2=value2)

5. Modules & Packages

   Modules

   Modules allow you to store reusable blocks of code, such as functions, in separate files. They're referenced by using the import statement.

   # import module as namespace
   import helpers
   helpers.display('Not a warning')
   
   # import all into current namespace
   from helpers import *
   display('Not a warning')
   
   # import specific items into current namespace
   from helpers import display
   display('Not a warning')

   Packages

   Distribution packages are external archive files which contain resources such as classes and functions. Most every application you create will make use of one or more packages. Imports from packages follow the same syntax as modules you've created. The Python Package index contains a full list of packages you can install using pip.

   Virtual environments

   Virtual environments allow you to install packages into an isolated folder. This allows you to better manage versions.

6. JSON with Python

   Many APIs return data in JSON, JavaScript Object Notation. JSON is a standard format that can is readable by humans and parsed or generated by code.

   JSON is built on two structures:

   • collections of key/value pairs
   • lists of values

   JSON Linters will format JSON so it easier to read by a human. The following website have JSON linters:

   • JSONLint
   • ConvertJson.com
   • JSON schema linter

   Python includes a json module which helps you encode and decode JSON

7. Decorators

   Decorators are similar to attributes in that they add meaning or functionality to blocks of code in Python. They're frequently used in frameworks such as Flask or Django. The most common interaction you'll have with decorators as a Python developer is through using them rather than creating them.

   # Example decorator
   @log(True)
   def sample_function():
      print('this is a sample function')