Python classes

Requirements:

• Python 2.7 is the required version of Python for these classes.
• Python libraries required: IPython notebook, Numpy, Matplotlib, Pandas, Django, MySQL Connector, Boto3.

==> If you have an existing Python 2.7 installation:

• pip (should be installed on recent Python distributions) - Installation instructions.
• IPython notebook - pip install jupyter - Installation instructions
• Numpy: pip install numpy - Installation instructions
• Matplotlib: easy_install matplotlib(Windows) or pip install matplotlib(MacOS) - Installation instructions
• Pandas: pip install pandas - Installation instructions
• Django:
  • pip install django - Installation instructions
  • pip install djangorestframework
  • pip install requests
• MySQL Connector: pip install mysql-connector-python --allow-external mysql-connector-python Installation instructions
• Boto3: pip install boto3 - Installation instructions

==> If you don't have any Python 2.7 installation:

Follow either one of the following bullets. The first bullet provides a minimal installation of Python, allowing you to control your Python installation. The second bullet installs Python Anaconda, a fully-featured Python installation for scientific computing.

• Python Installation Instructions
  • Once installed, add C:\Python27 and C:\Python27\Scripts to your %PATH.
  • Follow the steps in '==> If you have an existing Python 2.7 installation'.
• Python Anaconda (fully-featured Python installation for scientific computing): Installation instructions - Choose the Python 2.7 installation.
  • Ipython notebook: conda install jupyter
  • Django:
    • conda install -c https://conda.anaconda.org/trentonoliphant django
  • Django rest framework:
    • Windows: cd C:\anaconda\Scripts and pip install djangorestframework and pip install requests
    • MacOS X: cd ~/anaconda/scripts && pip install djangorestframework && pip install requests
  • MySQL Connector: conda install -c https://conda.anaconda.org/anaconda mysql-connector-python Installation instructions
  • Boto3:
    • Windows: cd C:\Anaconda\Scripts and pip install boto3
    • MacOS X: cd ~/anaconda/scripts && pip install boto3

Download class materials

• From Git:
  • git: Installation instructions
  • git clone https://github.com/ocervell/python_classes

Run IPython Notebook

Anaconda distribution:

• Copy the IPython Notebook launcher from the menu to the desktop.
• Right click on the new launcher and change the Start in field by pasting the full path of the folder which will contain all the notebooks: /path/to/python_classes.
• Double-click on the IPython Notebook desktop launcher (icon shows [IPy]) to start the Jupyter Notebook App.

Command line:

• cd /path/to/python_classes
• ipython notebook (ipython/jupyter has to be in your PATH)

Class curriculum

• 1. Python Basics ( ~ 2 hrs)

  • 1.1. Global concepts & operators
  • 1.2. Numbers
  • 1.3. Strings
  • 1.4. Lists
  • 1.5. Dictionaries
  • 1.6. Sets
  • 1.7. Tuples

• 2. Object-Oriented Programming in Python ( ~ 2 hrs)

  • 2.1. Python Rules
    • 2.1.1. Concepts
    • 2.1.2. Semantics
  • 2.2. Functions
  • 2.3. Classes
  • 2.4. File input / output
  • 2.5. Exception Handling

• 3. Advanced topics in Python (~ 5 hrs)

  • 3.1. Parsing

    • 3.1.1. CSV Parsing
    • 3.1.2. JSON Parsing
    • 3.1.3. XML Parsing
    • 3.1.4. Bonus: Pretty Print and Conversion
    • 3.1.5. Exercice: Analyze XML file

  • 3.3. SQL Data Access (MySQL)

    • 3.3.1. Connecting to MySQL DB
    • 3.3.2. Createing / Deleting a database
    • 3.3.3. Creating / Deleting a table
    • 3.3.4. Populating a table
    • 3.3.5. Querying data from a table
    • 3.3.6. OOP Approach

  • 3.4. NoSQL Data Access (DynamoDB)

    • 3.4.1. Connecting to DynamoDB
    • 3.4.2. Creating / Deleting a table
    • 3.4.3. Populating a table
    • 3.4.4. Querying data from a table

  • 3.2. Rest API (Django)

    • 3.2.1. Serialization
    • 3.2.2. Requests and Responses
    • 3.2.3. Class based view
    • 3.2.4. Authentication and Permission
    • 3.2.5. Relationships and HyperLink APIs

  • 3.5. Exercise: Twitter REST API

• 4. Statistics and Machine Learning using Python (~ 6 hrs)

  • 4.1. Numpy

    • 4.1.1. Arrays
    • 4.1.2. Array indexing
    • 4.1.3. Datatypes
    • 4.1.4. Array math
    • 4.1.5. Broadcasting
    • 4.1.6. Functions

  • 4.2. Matplotlib

    • 4.2.1. Plotting
    • 4.2.2. Subplots

  • 4.3. Pandas

    • 4.3.1. Series
    • 4.3.2. DataFrame
    • 4.3.3. Statistical analysis with pandas

  • 4.4. Exercise: Parse a switch record with Pandas and output to MySQL / DynamoDB