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Python for Everybody (py4e.com)

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Python for Everybody (py4e.com) · 86 episoder · Side 3 af 3

13.7 Securing API Requests
28. sep. 2016 10m

We explore the use of OAuth to communicate sign requests to establish identity when using the Twitter API.

Worked Example: Twitter and OAuth
28. sep. 2016 19m

Worked Example: Twitter and OAuth

14.1 Object Oriented Definitions and Terminology
28. sep. 2016 10m

We look at how Python mentions objects in its documentation as well as talk about why philosophy of object-oriented programming. We explore some OOP ...

14.2 Our First Class and Object
28. sep. 2016 8m

We look at how use create a new class in Python and then construct a new object from that class. We also look at some of the Python objects (like str...

14.3 Object Life Cycle
28. sep. 2016 6m

We look at how we as the developers of a Python class can interact with the moment of construction and destruction of various objects created using th...

14.4 Object Inheritance
28. sep. 2016 7m

We look at how we can make a new class by inheriting all of the attributes and methods of a parent class and then extend the new class with additional...

15.1 Relational Databases
28. sep. 2016 15m

We look at the history of database systems, learn the terminology of database systems, and review some of the common database systems that are in use.

15.2 Single Table SQL
28. sep. 2016 10m

We learn about how we can use Structured Query Language (SQL) to insert (create), read, update, and delete data in a single database table.

Worked Example: Storing Twitter Data
28. sep. 2016 9m

We retrieve and store Twotter data in a database.

15.3 Building a Relational Model
28. sep. 2016 8m

We look at how we can take the various data elements that will be modeled in an application and distribute them across several tables efficiently. We...

15.4 Database Key Types
28. sep. 2016 4m

We look at primary keys, logical keys and foreign keys. We look at how foreign keys are represented in the database.

15.5 Representing Relationships in Database Tables
28. sep. 2016 11m

We look at how we map a logical database model to a physical database model by adding columns and constraints to model the table-to-table relationship...

15.6 Multi-Table Retrieval using JOIN
28. sep. 2016 10m

We look at how to reconstruct complete views of the data when data is properly distributed across multiple tables and connected via foreign keys. We ...

Worked Example: Multiple Tracks
28. sep. 2016 13m

We work through a track data example with four tables.

15.7 Many-to-Many Relationships
28. sep. 2016 13m

We look at how to build a connector table to represent many-to-many relationships such as students and courses in database tables. We also learn abou...

Worked Example: Many-to-Many
28. sep. 2016 21m

We extend the Twitter example to represent friends using Many-to-Many relationships.

16.1 Visualizing Map Data
27. sep. 2016 6m

In this assignment we make use of the Google GeoCoding API to look up addresses, store the data in a database and then use Google Maps to visualize th...

Worked Example: Retrieving Geocoded Data
27. sep. 2016 13m

Worked Example: Retrieving Geocoded Data

16.2 Building a Web Search Engine
27. sep. 2016 11m

We build a web crawler that retrieves web pages and links from those pages an copies the pages into the database. Once we have retrieved our web data...

Worked Example: A Web Crawler
27. sep. 2016 17m

Worked Example: A Web Crawler

Worked Example: Running PageRank
27. sep. 2016 15m

Worked Example: Running PageRank

Worked Example: Visualizing PageRank
27. sep. 2016 6m

Worked Example: Visualizing PageRank

16.3 Processing Mail Data
27. sep. 2016 6m

We end where we started, processing email data. Except that this time it is a lot (nearly 1GB) of email data.

Worked Example: Retrieving Email Data
27. sep. 2016 17m

Worked Example: Retrieving Email Data

Worked Example: Cleaning and Modelling Mail Data
27. sep. 2016 12m

Worked Example: Cleaning and Modelling Mail Data

Worked Example: Visualizing Mail Data
27. sep. 2016 13m

Worked Example: Visualizing Mail Data