Table of Contents

;
Advance Praise for Head First Python;
Praise for other Head First books;
Author of Head First Python;
How to use This Book: Intro;
Who is this book for?;
We know what you’re thinking;
We know what your brain is thinking;
Metacognition: thinking about thinking;
Here’s what WE did;
Here’s what YOU can do to bend your brain into submission;
Read Me;
The technical review team;
Acknowledgments;
Safari® Books Online;
Chapter 1: Meet Python: Everyone loves lists;
1.1 What’s to like about Python?;
1.2 Install Python 3;
1.3 Use IDLE to help learn Python;
1.4 Work effectively with IDLE;
1.5 Deal with complex data;
1.6 Create simple Python lists;
1.7 Lists are like arrays;
1.8 Add more data to your list;
1.9 Work with your list data;
1.10 For loops work with lists of any size;
1.11 Store lists within lists;
1.12 Check a list for a list;
1.13 Complex data is hard to process;
1.14 Handle many levels of nested lists;
1.15 Don’t repeat code; create a function;
1.16 Create a function in Python;
1.17 Recursion to the rescue!;
1.18 Your Python Toolbox;
Chapter 2: Sharing your Code: Modules of functions;
2.1 It’s too good not to share;
2.2 Turn your function into a module;
2.3 Modules are everywhere;
2.4 Comment your code;
2.5 Prepare your distribution;
2.6 Build your distribution;
2.7 A quick review of your distribution;
2.8 Import a module to use it;
2.9 Python’s modules implement namespaces;
2.10 Register with the PyPI website;
2.11 Upload your code to PyPI;
2.12 Welcome to the PyPI community;
2.13 With success comes responsibility;
2.14 Life’s full of choices;
2.15 Control behavior with an extra argument;
2.16 Before your write new code, think BIF;
2.17 Python tries its best to run your code;
2.18 Trace your code;
2.19 Work out what’s wrong;
2.20 Update PyPI with your new code;
2.21 You’ve changed your API;
2.22 Use optional arguments;
2.23 Your module supports both APIs;
2.24 Your API is still not right;
2.25 Your module’s reputation is restored;
2.26 Your Python Toolbox;
Chapter 3: Files and Exceptions: Dealing with errors;
3.1 Data is external to your program;
3.2 It’s all lines of text;
3.3 Take a closer look at the data;
3.4 Know your data;
3.5 Know your methods and ask for help;
3.6 Know your data (better);
3.7 Two very different approaches;
3.8 Add extra logic;
3.9 Handle exceptions;
3.10 Try first, then recover;
3.11 Identify the code to protect;
3.12 Take a pass on the error;
3.13 What about other errors?;
3.14 Add more error-checking code...;
3.15 ...Or add another level of exception handling;
3.16 So, which approach is best?;
3.17 You’re done...except for one small thing;
3.18 Be specific with your exceptions;
3.19 Your Python Toolbox;
Chapter 4: Persistence: Saving data to files;
4.1 Programs produce data;
4.2 Open your file in write mode;
4.3 Files are left open after an exception!;
4.4 Extend try with finally;
4.5 Knowing the type of error is not enough;
4.6 Use with to work with files;
4.7 Default formats are unsuitable for files;
4.8 Why not modify print_lol()?;
4.9 Pickle your data;
4.10 Save with dump and restore with load;
4.11 Generic file I/O with pickle is the way to go!;
4.12 Your Python Toolbox;
Chapter 5: Comprehending data: Work that data!;
5.1 Coach Kelly needs your help;
5.2 Sort in one of two ways;
5.3 The trouble with time;
5.4 Comprehending lists;
5.5 Iterate to remove duplicates;
5.6 Remove duplicates with sets;
5.7 Your Python Toolbox;
Chapter 6: Custom data Objects: Bundling code with data;
6.1 Coach Kelly is back (with a new file format);
6.2 Use a dictionary to associate data;
6.3 Bundle your code and its data in a class;
6.4 Define a class;
6.5 Use class to define classes;
6.6 The importance of self;
6.7 Every method’s first argument is self;
6.8 Inherit from Python’s built-in list;
6.9 Coach Kelly is impressed;
6.10 Your Python Toolbox;
Chapter 7: Web Development: Putting it all together;
7.1 It’s good to share;
7.2 You can put your program on the Web;
7.3 What does your webapp need to do?;
7.4 Design your webapp with MVC;
7.5 Model your data;
7.6 View your interface;
7.7 Control your code;
7.8 CGI lets your web server run programs;
7.9 Display the list of athletes;
7.10 The dreaded 404 error!;
7.11 Create another CGI script;
7.12 Enable CGI tracking to help with errors;
7.13 A small change can make all the difference;
7.14 Your webapp’s a hit!;
7.15 Your Python Toolbox;
Chapter 8: Mobile app Development: Small devices;
8.1 The world is getting smaller;
8.2 Coach Kelly is on Android;
8.3 Don’t worry about Python 2;
8.4 Set up your development environment;
8.5 Configure the SDK and emulator;
8.6 Install and configure Android Scripting;
8.7 Add Python to your SL4A installation;
8.8 Test Python on Android;
8.9 Define your app’s requirements;
8.10 The SL4A Android API;
8.11 Select from a list on Android;
8.12 The athlete’s data CGI script;
8.13 The data appears to have changed type;
8.14 JSON can’t handle your custom datatypes;
8.15 Run your app on a real phone;
8.16 Configure AndFTP;
8.17 The coach is thrilled with his app;
8.18 Your Python Toolbox;
Chapter 9: Manage Your data: Handling input;
9.1 Your athlete times app has gone national;
9.2 Use a form or dialog to accept input;
9.3 Create an HTML form template;
9.4 The data is delivered to your CGI script;
9.5 Ask for input on your Android phone;
9.6 It’s time to update your server data;
9.7 Avoid race conditions;
9.8 You need a better data storage mechanism;
9.9 Use a database management system;
9.10 Python includes SQLite;
9.11 Exploit Python’s database API;
9.12 The database API as Python code;
9.13 A little database design goes a long way;
9.14 Define your database schema;
9.15 What does the data look like?;
9.16 Transfer the data from your pickle to SQLite;
9.17 What ID is assigned to which athlete?;
9.18 Insert your timing data;
9.19 SQLite data management tools;
9.20 Integrate SQLite with your existing webapp;
9.21 You still need the list of names;
9.22 Get an athlete’s details based on ID;
9.23 You need to amend your Android app, too;
9.24 Update your SQLite-based athlete data;
9.25 The NUAC is over the moon!;
9.26 Your Python Toolbox;
Chapter 10: Scaling your Webapp: Getting real;
10.1 There are whale sightings everywhere;
10.2 The HFWWG needs to automate;
10.3 Build your webapp with Google App Engine;
10.4 Download and install App Engine;
10.5 Make sure App Engine is working;
10.6 App Engine uses the MVC pattern;
10.7 Model your data with App Engine;
10.8 What good is a model without a view?;
10.9 Use templates in App Engine;
10.10 Django’s form validation framework;
10.11 Check your form;
10.12 Controlling your App Engine webapp;
10.13 Restrict input by providing options;
10.14 Meet the “blank screen of death”;
10.15 Process the POST within your webapp;
10.16 Put your data in the datastore;
10.17 Don’t break the “robustness principle”;
10.18 Accept almost any date and time;
10.19 It looks like you’re not quite done yet;
10.20 Sometimes, the tiniest change can make all the difference...;
10.21 Capture your user’s Google ID, too;
10.22 Deploy your webapp to Google’s cloud;
10.23 Your HFWWG webapp is deployed!;
10.24 Your Python Toolbox;
Chapter 11: Dealing with Complexity: Data wrangling;
11.1 What’s a good time goal for the next race?;
11.2 So... what’s the problem?;
11.3 Start with the data;
11.4 Store each time as a dictionary;
11.5 Dissect the prediction code;
11.6 Get input from your user;
11.7 Getting input raises an issue...;
11.8 If it’s not in the dictionary, it can’t be found;
11.9 Search for the closest match;
11.10 The trouble is with time;
11.11 The time-to-seconds-to-time module;
11.12 The trouble is still with time...;
11.13 Port to Android;
11.14 Your Android app is a bunch of dialogs;
11.15 Put your app together...;
11.16 Your app’s a wrap!;
11.17 Your Python Toolbox;
11.18 It’s time to go...;
Leftovers: The Top Ten Things (we didn’t cover);
#1: Using a “professional” IDE;
#2: Coping with scoping;
#3: Testing;
#4: Advanced language features;
#5: Regular expressions;
#6: More on web frameworks;
#7: Object relational mappers and NoSQL;
#8: Programming GUIs;
#9: Stuff to avoid;
#10: Other books;