Python for Everybody (py4e.com): Recent Episodes
Dr. Charles Russell Severance
These are the lectures to supplement the textbook 'Python for Everybody: Exploring Information' and its associated web site py4e.com
Explore the nature of programming and how programming a computer is different than using a computer.
In this lecture we learn abut how the computer processes and stores programs. We learn about the CPU, Memory, Storage and Input / Output devices are brought together to write a program.
We look at how writing programs is just another form of communication. Instead of communicating with another person, we are communicating our ideas to a computer.
We look at the basics of the Python language and how we write code in Python to communicate sequential steps, conditional steps and repeated steps.
We look at Python's reserved words, how we name and use variables, why we choose meaningful (mnemonic) variable names and how assignment statements function.
We look at how we use various numerical and string operations to compute new information and store the new values in variables.
The most basic conditional structure is the if statement where we either execute or skip a segment of code based on the results of a logical expression (i.e. asking a question).
In this video we look at multi-branch if statements and the try-except concept where we can indicate a group of statements to be executed if something goes wrong with a block of statements.
We look at how code flows into and out of functions as well has how we pass information into functions and get results returned to us.
We look at how to build our own functions using parameters and arguments as well as how we return results to the code that is calling our functions.
We look at how we construct a loop so that it runs as long as we want it to run. We learn about iteration variables and exiting loops with the 'break' and 'continue' statements.
Loops have a beginning, middle, and end. We look ant how we construct a loop to look at a list of items one at a time so we can compute an overall maximum, minimum or average.
We continue to look at how to construct loops including how to do something special the first time through the loop. We introduce the idea of 'None' which is a way to indicate that a variable is currently empty.
We learn how to create string variables and extract portions of the data as well as write simple loops to read through the characters in a string.
We learn how to extract substrings using slicing, and use the string library to perform common data extraction operations with strings.
We look at how text and lines are represented in files, how we open a file and write a loop to read through all the lines in the file.
We look at patterns for reading and processing the data in files. We learn how to check for nonexistent files, and how we process each line within the file.
We learn how to put data into lists, take data out of the list and write simple loops to examine the elements of a list.
We learn about list slicing, list searching, and using pre-defined functions with lists.
We learn how to parse strings pull sub-strings out of a string using the split() function.
We compare and contrast how Python lists and dictionaries are structured internally. How we use position to index lists and use keys to index dictionaries.
We look at how we can use dictionaries to count the frequencies of many things at the same time. We learn how the key and value are related in a dictionary and example the get method to retrieve values from a Python dictionary.
In this segment we bring everything together, reading a file, parsing the lines, and computing the frequencies of the words in the file. This is an important moment that pulls from everything we have learned so far.
We look at the basic syntax and capabilities of Python tuples. We explore the concept of immutability, and we compare tuples to lists and strings.
We look at the syntax of regular expressions and how to use them to search through text data.
In this segment we learn to pull out data from strings after a regular expression has found a match.
We look at how some of the string parsing we have done in earlier chapters can be easily done with regular expressions.
We take a very brief look at how software communicates across the Internet using TCP/IP.
In this section we look at the HTTP protocol that is used to move documents between web servers and web browsers.
We write a simple Python program that connects to a web server and retrieves a web document. It is a very simple web browser.
We write an even simpler Python program to retrieve a web page using the urllib library in Python.
Now we will look at the HypertextMarkup Language (HTML) that we retrieved using Python and extract links from that HTML. We are slowly building a very simple web search engine.
We look at two different ways to format data for transmission across the network including JavaScript Object Notation (JSON) and eXtended Markup Language (XML).
We look at how we can use XML Schema to determine whether or not a particular bit of XML is valid.
We talk briefly about how applications can be built over time to depend on services provide other applications.
We explore using a Google API that can be used to query location data and parse the JSON that is returned.
We explore the use of OAuth to communicate sign requests to establish identity when using the Twitter API.
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 terms like class, object, instance, method, and attribute.
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 strings) that we have been using all along.
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 the class.
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 attributes and methods.
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.
We learn about how we can use Structured Query Language (SQL) to insert (create), read, update, and delete data in a single database table.
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 learn about the basic rules of database design.
We look at primary keys, logical keys and foreign keys. We look at how foreign keys are represented in the database.
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 relationships.
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 learn the JOIN operation and ON clause in SQL.
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 about composite primary keys.
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 the data.
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 we run a simple Page Rank algorithm on the data and visualize the results.
We end where we started, processing email data. Except that this time it is a lot (nearly 1GB) of email data.