Gain insights into Python 3's new syntax, data types, strings, bytes, and iterators through interactive coding samples. Upgrade your Python skills with hands-on, real-time code modifications.

Are you ready to take the plunge into Python 3? You might be just getting started with Python or you might be someone who understands Python2 and now wants to upgrade to Python 3. This course is designed to help you achieve your goal faster.

Learn about the new syntax, data types, strings, bytes, iterators and much more with interactive coding samples. Execute code using interactive playgrounds, modify the code to see your changes in action and get yourself upgraded to the newest version of Python that is here to stay for a while.

This course is derived from Dive into Python 3 by Mark Pilgrim. See License for more details.
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Python 3: An interactive deep dive

The examples in the previous section showed how to serialize a Python object directly to a file on disk. But what if you don’t want or need a file? You can also serialize to a `bytes` object in memory.

import pickle

shell = 1
print (shell)
#1
with open('entry.pickle', 'rb') as f:    
     entry = pickle.load(f)               

b = pickle.dumps(entry)             #①
print (type(b))                     #②
#<class 'bytes'>

entry3 = pickle.loads(b)            #③
print (entry3 == entry)             #④
#True

①	The `pickle.dumps()` function (note the '`s`' at the end of the function name) performs the same serialization as the `pickle.dump()` function. Instead of taking a stream object and writing the serialized data to a file on disk, it simply returns the serialized data.

②	Since the pickle protocol uses a binary data format, the `pickle.dumps()` function returns a bytes object.

③	The `pickle.loads()` function (again, note the `'s'` at the end of the function name) performs the same deserialization as the `pickle.load()` function. Instead of taking a stream object and reading the serialized data from a file, it takes a `bytes` object containing serialized data, such as the one returned by the `pickle.dumps()` function.

④	The end result is the same: a perfect replica of the original dictionary.

Your First Python Program

Native Datatypes

Comprehensions

Strings

Regular Expressions

Closures & Generators

Classes & Iterators

Advanced Iterators

Unit Testing

Refactoring

Files

XML

Serializing Python Objects

HTTP Web Services

Case Study: Porting chardet to Python 3

Packaging Python Libraries

Appendix : Where To Go From Here

Pickling Without a File