If you have a scientific or mathematical background you may be wondering about complex numbers? If you haven't you may not even have heard of complex numbers, in which case you can safely jump to the next heading because you don't need them! Anyhow some programming languages, including Python, provide built in support for the complex type while others provide a library of functions which can operate on complex numbers. And before you ask, the same applies to matrices too.

Literal objects are character strings or numbers that appear directly in the code, as did the number 1 that was returned in the previous section. We've seen numbers in action; next, let's look at a string literal.

A string literal is an object that contains a string of characters, such as a name, an address, or an especially witty phrase. In the same way that we created the 1 literal object in the previous example, we can easily create a new string literal object, then send it a message. A string literal is created by enclosing the characters that make up the string in single or double quotes, like this:

I'm having problems trying to parse a text file and separating it's contents into a dictionary. The file as something like: name This is the description of the name. another_name Another description of this name. The dictionary should look like: dict = {name: This is the description of the name., another_name: Another discription of this name}

The Numeric community fractured when the future replacement for Numeric (NumPy) was initially released. For a while Numeric users were in 2 camps, some for Numeric, and some for Numpy. The reason for this schism was that Numeric was generally those who had to create a large number of small arrays, and NumPy was faster for those who wanted to use huge arrays.