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An Introduction to Python for GIS Specialists and Data Managers

Learn Python basics with an emphasis on GIS applications. Understand syntax, variables, comments, data types, operators. Includes debugging tips and exercises.

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An Introduction to Python for GIS Specialists and Data Managers

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  1. An Introduction to Pythonfor GIS Specialists and Data Managers Jacob Morgan Brent FrakesNational Park ServiceFort Collins, COApril, 2008

  2. Session Goals • Overview of Python • See power of the language • Understand basic syntax • References to other sources • Too little time to really cover everything

  3. Sessions • One: Basic Python • Two: Using the ESRI Geoprocessor • Three: Formatting Data and Python Scripting • Each one hour • Examples and practice

  4. Session 1: Overview • Scripts and the Debugger • Commenting • Data Types • Operators • Decisions and Loops • File Handling • Modules, Functions and Classes

  5. Scripts and the Debugger • General Setup and Notes • All code is text-based (*.py extension) • Once compiled, a new file will have a *.pyc extension. • Python is VERY picky about indentation • Python is case sensitive • IDLE • Free • GUI interface for development • Compiler included with ArcGIS • Provides debugging but doesn't allow for breakpoints • Pythonwin • Free • GUI interface for development • Good debugger with breakpoints • http://sourceforge.net/projects/pywin32/

  6. Scripts and the Debugger • Exercise • type at the prompt >>'hello world' • type at the prompt >>print 'hello world' • Run a script with the following code: • print 'hello world'

  7. Commenting • Why? • Make your code understandable to you and others • How to use code • Why code was written • Debugging (comment out parts of script) • Ways to Comment • Single Line: use the pound (#) sign before the comment text. # single line commented text • Multiple Lines: use triple quotes before and after a text block. “ “ “ These two lines of text Are being commented out “ “ “

  8. Exercise • Add both types of comments to your script

  9. Data Types • Strings • Numeric • Lists • Tuples

  10. Strings • An ordered collection of characters used to represent text-based information • Common String Literals and Operations • strNull = ' ' #empty string • str1 = "metadata" #double-quotes • str2 = '.xml' #single quotes • str3 = str1 + str2 #concatenate • strNull*100 #repeat • str2.upper() #string method call • str1[0:2] #indexing • str1 = str1+str2 #strings can't be modified but can be reassigned

  11. Strings • Special Strings • \n #newline • \t #horizontal tab • \\ #backslash

  12. Strings • Type the following >>>a='Hello' >>>b = 'World' >>> a+b >>> (a+b)*10 >>> a[0:1] >>> a[-4:-1] >>>a.upper() >>>a.lower() • Add two strings • Try using the two other string methods

  13. Numeric Types • Four types: • Integers • Numeric type providing a container for whole numbers. Plain integers are precise up to 32 bits (dependant on platform and compiler). • Floating Point Numbers • Numbers those with a decimal component. These are called floating point since the decimal point can be positioned anywhere in the digit string by a signed integer exponent- • Long Integers • Complex Numbers

  14. Numeric Operators

  15. Numeric Considerations • Integer calculations yield integers (including division!) • Floating point calculations yield floating points • The constructors int(), long(), float(), and complex() can be used to produce numbers of a specific type. However, converting numbers between types may result in rounding or truncating digits.

  16. Numeric Types - Exercises >> 1 # 1 >>a= 2 #set value to 2 >>b= 3 >>b+a >>b/a #still an integer >>value = "10" #not an integer >>c = 1.27 #floating point >>c+b >>b/c >>d = int(c) #rounding

  17. Lists • An ordered collections of arbitrary objects • Fully indexed • Variable in length, heterogenous, and arbitrarily nestable • Can be altered • Always in brackets • Aka Arrays!

  18. List - Examples d = [] # empty list d = [1,2,3] #list of three integers d = [1,2,"3"] #two integers and a string d[0] #first element d = [[1,2, 3],[3,4, 5]] #3 by 3 array len(d) # 2 len(d[0]) #3

  19. Lists - Exercises >>L1 = [1,2,3,4,5,6] >>len(L1) >> L1 [0] >> L1.pop() #remove last element from stack >> L1 #6 is removed >> L1 [0:2] #index 0-2 >> L1 [-1] #index from end of list >>L2 = [5,6,7] >> L1.append(L2) #insert a new list >> L1 >> L1.extend(L2) #extend the current list >> L1

  20. Operators • Operators compute a value when presented with a string or number • Common Operators include: • x=y #assign • x==y #true or false • x < y #True or false • x<=y #True or false • x>y #True or false • x*y, x/y, x+y, x-y #Basic math • x[1] #index • x[1:10] #slice • x or y #y evaluated only if x is false • x and y #y is evaluated only if x is true

  21. Operators - Exercises • >>>x = 5 • >>>y = 6 • >>> x < y • >>> x > y • >>> x < y or y > 7 • >>> x < y and y > 7

  22. Controlling Flow • Decisions/Conditionals are statements that determine if a series of conditions is true. • Most common • if • for • while

  23. Decisions/Conditionals if condition: action(s) elif condition: action(s) else condition: action(s)

  24. “if” Condition Example x = 15 if x > 5 and x < 10 : print “The value is between 5 and 10” else: print “The value is not between 5 and 10”

  25. “if” Condition - Exercise >>>x = 7 >>>if x > 5 and x < 10 : … print “The value is between 5 and 10”

  26. “for” loop • Supports repeated execution of a statement, or block of statements, controlled by an iterable express for target in iterable: statement(s) else: #optional on normal termination statement(s)

  27. “for” Examples for x in range (1,30,2): print x for letter in “hello world”: print letter infile = open (“dataset.txt”,”r”) for line in infile: print line

  28. For Exercises >>>for x in range(1,20): … if x%2 == 0: … print x, “ is even” >>>import glob >>>files = glob.glob(“*.*”) >>>for file in files: … print file

  29. “while” loop • allows looping to occur only while a specified condition is true. WHILE evaluates the condition each time the loop completes and terminates the loop when the condition evaluates to false while expression: statement(s) else: #optional for normal termination statement(s)

  30. While Examples x = 100 while x>0: x = x/2 print x

  31. While Exercise >>>x = 20 >>>y = 0 >>>while x>=y: … print y … y += 2

  32. File Handling • Ways to open, read, write, and close files File2read = open (filename, mode = 'r') filename - string containing filename and extension (e.g., 'metadata.xml') file modes - indicates how to read or write the file 'r' - file must already exist and is read only 'w' - creates a new file for writing. Overwrites any existing filename 'a' - Write only mode. If file already exists, information is appended. 'r+' - File must already exist and is opened for both reading and writing. 'w+' - New file is created. Open for reading and writing. 'a+' - File open for reading and writing. If file already exists, data is appended.

  33. Useful File Methods • file.read() - reads up to the end of file and returns it as a string. • file.readline() - reads one line from file (up to the '\n') and returns a string • file.seek(pos, how = 0) - Move to a position in the file. 'How' is the reference point for moving (0 = start of file, 1 = current position; 2 = end of file). • file.write() - Writes a string to a file • file.writelines(line) - writes a line to a file • file.close() - # must be closed for it to be unlocked by Windows

  34. File Examples • infile = open(“d.txt”, 'r') • data = infile.read() #the string data is assigned the file contents • outfile = open(“e.txt”,'w') # assign outfile to the file object for writing • outfile.write(data) # write the contents to the file • infile.close() • outfile.close()

  35. File Exercises >>>filename = “C:\\temp\\test.txt” >>>outfile = open (filename ,’w’) >>>outfile.write(“hello world”) >>>outfile.close() >>>infile = open(filename ,’r’) >>>data = infile.read() >>>print filename, “-”, data >>>infile.close()

  36. Modules, Functions, and Classes • Module • Single Python file • Provides definitions of functions, variables or classes • Corresponds to a specific thema (e.g., read, edit, and write zipfiles) • Composed of functions and/or classes. Functions can be stand-alone or are part of a class. Whether a function or class, both accomplish tasks.

  37. Standard Modules • Supported by Python - integral to many applications • Index can be found at: http://docs.python.org/lib/modindex.html • Importing is simple: • >>import module • (e.g., import os)

  38. Accessing Functions import module module.function(arguments…) Examples import os os.getcwd() #get current directory import glob glob.glob(“*.py”) #get a list of all files with the .py extension

  39. Instantiating Classes import module instance = module.class(arguments) instance.method() Examples Import gzip #import gzip module Zipfile = gzip.GzipFile(“datafile.zip”) #instantiate GzipFile class files = Zipfile.read() #Read zipfile and assign it to the files string

  40. Getting Documentation About Modules dir() – List of available functions and methods module.__doc__ - module documentation module.function.__doc__ - function/method documentation Example import os dir(os) os.rename.__doc__

  41. Third Party Modules • Many others have developed modules and posted them to the Python Package Index (http://pypi.python.org/pypi/)

  42. Exercises >>>import os >>>dir(os) >>>os.rename.__doc__ >>>import shutil >>>shutil.__doc__ >>>dir(shutil)

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