Kickstart Python for Revit API (1)

I always find charming the feeling when you start learning something new, and nothing makes sense at the beginning. However, after some effort and time spent working on it, all the pieces come together. How sweet the change of mindset from “This is too much” to “Sky is the limit”! This is what happened to me when I started learning Python for Revit API, and I will share some basic concepts to start:

Expressions, values, and operators:

An expression is the most basic programming instruction you can give to a computer. For example:

7 + 8
15

In this case, 7 and 8 are values and + is an operator. The process to get to the result of that expression is called evaluation, and yes, that expression evaluates to 15. Another example:

“Revit” == “ArchiCAD”
False

This expression will evaluate to False, because, obviously, those two strings are different.

Data types:

In Python, values are the most basic elements used to create a program and they are categorized under different data types. We can consider them as bricks, the elemental material to build a house.

All the previous data types are present in Dynamo, but if there is no node for it, Code Block will do the job.

Integers are integers, numbers without decimal positions (a bit of math refresh).

Floating or float numbers are numbers that have decimals.

42 == 42.00
True

Despite the differentiation between integer and floats, the previous expression will evaluate to True. That split is because of memory allocation to store values, integers take less space.

Strings are characters, and they need to be inside single or double quote marks, not inside the String node in Dynamo. Take into consideration that:

25 is not equal than “25”, one is an integer and the second value is a string.

Booleans are binary values that can only be True or False.

NoneType is a special type that represents that no value is present. In Dynamo, null values can be problematic as any action (method or function) called over it usually ends in error.

Operators:

Operators allow programmers to perform actions on values. There are several different kinds:

• Math operators

They allow performing mathematical operations on values. Two of them work with strings, + and *.

Addition performed on strings is called string concatenation:

“Revit” + “plus” + “Dynamo” + “is” +”awesome”
“RevitplusDynamoisawesome” 

Note that spaces must be explicitly specified.

• Comparison operators

As their name states, they are useful to compare two values.

• Boolean operators:        

Evaluation table for and operator:

Evaluation table for or operator:

Evaluation table for or operator:

Variables:

Variables are storage for values. Suppose you have obtained a value after some hard work and you don´t want to lose it. The way to store it and reuse it is through variables. The convention in Python is that variables must be a single word that starts with a letter, cannot contain special characters excluded the underscore (_) and not be a reserved keyword like def, None, True, False, etc

The PEP8, the official style guide for Python states that variables should be named like this:

Variable_name

However, personally I prefer the camel case style used in JS, tipping underscores is not a pleasant thing and is more legible this way:

varibaleName

Here is an assignment of a value to a variable:

xVariable = 34

From now on, xVariable value is 34. If we want to use it in another expression:

xVariable * 2 
68

This concludes the first part of Python basics; in the next section, we will see how we can use these building blocks to create a simple program.