Advanced geoprocessing with Python

Advanced geoprocessing with…

MAGIC 2012
Chad Cooper – chad@cast.uark.edu
Center for Advanced Spatial Technologies
University of Arkansas, Fayetteville

Intros
• your name
• what you do/where you work
• used Python much?
– any formal training?
– what do you use it for?
• know any other languages?

Objectives
• informal class
– expect tangents
– code as we go
• not geared totally to ArcGIS
• THINK – oddball and out of the ordinary
applications will make you want more…

Outline
• data types review • documentation
• functions • 3rd party modules
• procedural vs. OOP • module installation
• geometries • the web
• rasters – fetching
– scraping
• spatial references
– email
• error
– FTP
handling/logging
• files

Strings
• ordered collections of characters
• immutable – can’t change it
• raw strings: path = r”C:tempchad”
• slicing fruit[0]
„b‟

• indexing: fruit[1:3] >> „an‟
• iteration/membership: for each in fruit
„f‟ in fruit

Strings
• string formatting: „a %s parrot‟ % „dead‟
„a dead parrot‟

• useful string formatting:

import arcpy
f = "string"
arcpy.CalculateField_management(fc,
“some_field",
'"%s"' % f)

Lists
• list – ordered collection of arbitrary objects
list1 = [0,1,2,3]
list2 = ['zero','one','two','three']
list3 = [0,'zero',1,'one',2,'two',3,'three']

• ordered
list2.sort() list2.sort(reverse=True)
['one','three',...] ['zero','two',...]

• mutable – you can change it
list1.append(4) list1.reverse() list2.insert(0,‟one-half‟)
[0,1,2,3,4] [4,3,2,1,0] [„one-half‟,‟zero‟…]

list2.extend([„four‟,‟five‟]) <- Extend concats lists

Lists…
• iterable – very important! for l in list3
0
zero ...

• membership 3 in list3 --> True

• nestable – 2D array/matrix
list4 = [[0,1,2],
[3,4,5],
[6,7,8]]

• access by index – zero based
list4[1] list4[1][2]
[3,4,5] 5

Dictionaries
• unordered collection of arbitrary objects
d = {1:‟foo‟, 2:‟bar‟}
• key/value pairs – think hash/lookup table (keys
don’t have to be numbers)
d.keys() d.values()
[1, 2] [„foo‟,‟bar‟]
• nestable, mutable
d[3] = „spam‟ del d[key]
• access by key, not offset
d[2] >> „bar‟

Dictionaries
• iterable
d.iteritems()
<dictionary-itemiterator object at
0x1D2D8330>

for k, v in d.iteritems():
print k, v
...
1 foo
2 bar

Tuples
• ordered collection of arbitrary objects
• immutable – cannot add, remove, find
• access by offset
• basically an unchangeable list
(1,2,‟three‟,4,…)
• so what’s the purpose?
– FAST – great for iterating over constant set of
values
– SAFE – you can’t change it

List comprehensions
• Map one list to another by applying a function
to each of the list elements
• Original list goes unchanged
L = [2,4,6,8]
J = [elem * 2 for elem in L]
>>> J
[4, 8, 12, 16]

Sets
• unordered collections of objects
• like mathematical sets – collection of distinct
objects – NO DUPLICATES
• example – get rid of dups in a list via list comp
L1=[2,2,3,4,5,5,3]
L2=[]
[L2.append(x) for x in L1 if x not in L2]
>>> L2
[2, 3, 4, 5]

Sets
• get rid of dups via set:
>>> L1=[2,2,3,4,5,5,3]
>>> set(L1)
set([2, 3, 4, 5])
>>>
L1 = list(set(L1))
>>>
>>> L1
[2, 3, 4, 5]

• union:
>>> L2 = [4,5,6,7]
>>> L1 + L2
[2, 3, 4, 5, 4, 5, 6, 7]
>>>
>>> list(set(L1).union(set(L2)))
[2, 3, 4, 5, 6, 7]

Sets
>>> L1
[2, 2, 3, 4, 5, 5, 3]
>>> L2
[4, 5, 6, 7]

• intersection – data are the same
>>> set(L1).intersection(set(L2))
set([4, 5])
>>>
• symmetrical difference – data are not the same
>>> set(L1).symmetric_difference(set(L2))
set([2, 3, 6, 7])

• difference – data in first set but not second
>>> set(L1).difference(set(L2))
set([2, 3])
>>> set(L2).difference(set(L1))
set([6, 7])

Programming paradigms:
big blob of code
• OK on a small scale for GP scripts
• gets out of hand quickly
• hard to follow
• think ModelBuilder-exported code

procedural programming
• basically a list of instructions
• program is built from one or more procedures
(functions) – reusable chunks
• procedures called at anytime, anywhere in
program
• focus is to break task into collection of variables,
data structures, subroutines
• natural style, easy to understand
• strict separation between code and data

Functions
• portion of code within a larger program that
performs a specific task
• can be called anytime, anyplace
• can accept arguments
>>> def foo(bar):
• should return a value ... print bar
...
• keeps code neat >>> foo(“yo”)
• promotes smooth flow yo

Functions
import arcpy

def get_raster_props(in_raster):
"""Get properties of a raster, return as dict"""
# Cast input layer to a Raster
r = arcpy.Raster(in_raster)
raster_props = {} # Create empty dictionary to put props in below
raster_props["x_center"] = r.extent.XMin + (r.extent.XMax - r.extent.
raster_props["y_center"] = r.extent.YMin + (r.extent.YMax - r.extent.
raster_props["max_elev"] = r.maximum
raster_props["min_elev"] = r.minimum
raster_props["no_data"] = r.noDataValue
raster_props["terr_width"] = r.width
raster_props["terr_height"] = r.height
raster_props["terr_cell_res"] = r.meanCellHeight
# Return the dictionary of properties
return raster_props

Procedural example
import arcpy

def add_field(in_fc="Magic.gdb/Fields",
in_fields=[("Distance", "Float", "0"),
("Name", "Text", 50)]):
"""Add fields to FC"""
for in_field in in_fields:
if in_field[1] == 'Text':
arcpy.AddField_management(in_fc,in_field[0],in_field[1],"#
"#",in_field[2],"#","NULLABLE","NON_REQUIRED",
else:
arcpy.AddField_management(in_fc,in_field[0],in_field[1],"#
"#","#","#","NULLABLE","NON_REQUIRED","#")

add_field()

Object-oriented programming (OOP)
• break program down into data types (classes)
that associate behavior (methods) with data
(members or attributes)
• code becomes more abstract
• data and functions for dealing with it are
bound together in one object

import arcpy

class Fields(object):
"""Class for working with fields"""
# __init__ --> method signature
def __init__(self,
in_fc="Magic.gdb/Fields",
("Name", "Text", 50)]):
self.in_fc = in_fc
self.in_fields = in_fields

def add_field(self):
for in_field in self.in_fields:
if in_field[1] == "Text":
arcpy.AddField_management(self.in_fc, in_field[0],
in_field[1], "#", "#",
in_field[2], "#", "NULLABLE",
"NON_REQUIRED", "#")
else:
in_field[1], "#", "#", "#",
"#", "NULLABLE", "NON_REQUIRED", "#")

if __name__ == "__main__":
# Instantiate the Fields class
f = Fields()
# Call the add_field method
f.add_field()
print f.in_fields
print f.in_fc

• objects let you wrap complex processes, but
present a simple interface to them
• methods and attributes are encapsulated
inside the object
• methods and attributes are exposed to users
• you can then update the object without
breaking the interface
• you can pass objects around - carefully

OOP - Inheritance
• classes can inherit attributes and methods
• allows you to reuse and customize existing
code inside a new class
• you can override methods
• you can add new methods to a class without
modifying the existing class

import arcpy

Programming paradigms: def __init__(self,
("Name", "Text", 50)]):
self.in_fc = in_fc
OOP - Inheritance self.in_fields = in_fields

in_field[1], "#", "#",
else:
in_field[1], "#", "#", "#",

class MyFields(Fields):
"""Customized fields class"""
# Test to see if in_field exists already in featureclass
if in_field[0] in [f.name for f in arcpy.ListFields(self.in_fc)]:
# If field exists, delete it
arcpy.DeleteField_management(self.in_fc, in_field[0])
print in_field[0], "deleted"

in_field[1], "#", "#",
else:
in_field[1], "#", "#", "#",

if __name__ == "__main__":
# Instantiate MyFields class, which in inherits the Fields class
f = MyFields()
# Call add_field method
f.add_field()

import arcpy

def __init__(self,
Programming paradigms: in_fields=[("Distance", "Float", "0"),
("Name", "Text", 50)]):
self.in_fc = in_fc
self.in_fields = in_fields

OOP - Inheritance
in_field[1], "#", "#",
else:
in_field[1], "#", "#", "#",
def get_field_props(self):
desc = arcpy.Describe(self.in_fc)
for field in desc.fields:
print field.name, "-->", field.type

class MyFields(Fields):
"""Customized fields class"""
if in_field[0] in [f.name for f in arcpy.ListFields(self.in_fc)]:
arcpy.DeleteField_management(self.in_fc, in_field[0])
print in_field[0], "deleted"

in_field[1], "#", "#",
else:
in_field[1], "#", "#", "#",

if __name__ == "__main__":
# Instantiate MyFields class
f = MyFields()
# Call add_field method
f.add_field()
print f.in_fields
# See, we really do inherit everything from the Fields class
f.get_field_props()

Modularizing code
• I’m lazy, so I want to reuse code
• import statement – call functionality in
another module
• Have one custom module (a .py file) with code
you use all the time
• Great way to package up helper functions
• ESRI does this with ConversionUtils.py
C:Program Files (x86)ArcGISServer10.0ArcToolBoxScripts

Geometries
• heirarchy:
– feature class is made of features
– feature is made of parts
– part is made of points
• heirarchy in Pythonic terms:
– part: [[pnt, pnt, pnt, ...]]
– multipart polygon: [[pnt, pnt, pnt, ...],
[pnt, pnt, pnt, ...]]
– single part polygon with hole:
[[pnt, pnt, pnt, ,pnt, pnt, pnt]]

Reading geometry
• accessed through the geometry object of a
feature
• example: describe_geometry_arcmap.py
1.open up import arcpy
desc =
SearchCursor arcpy.Describe("Points")
2.loop through sfn = desc.ShapeFieldName
rows rows =
arcpy.SearchCursor("Points"
3.get geometry )
4.print out X, Y for row in rows:
geom =
row.getValue(sfn)

Reading geometry
import arcpy

desc =
arcpy.Describe("Points")
sfn = desc.ShapeFieldName
rows =
arcpy.SearchCursor("Points"
)
for row in rows:
geom =
row.getValue(sfn)
pnt = geom.getPart()
print pnt.X, pnt.Y

import arcpy

infc = "Magic.gdb/Polygons"

# Identify the geometry field
Reading geometry
desc = arcpy.Describe(infc)
shapefieldname = desc.ShapeFieldName
# Create search cursor
rows = arcpy.SearchCursor(infc)

# Enter for loop for each feature/row
for row in rows:
# Create the geometry object
feat = row.getValue(shapefieldname)
# Print the current multipoint's ID
print "Feature %i:" % row.getValue(desc.OIDFieldName)
partnum = 0
# Step through each part of the feature
for part in feat:
# Print the part number
print "Part %i:" % partnum
# Step through each vertex in the feature
for pnt in feat.getPart(partnum):
if pnt:
# Print x,y coordinates of current point
print pnt.X, pnt.Y
else:
# If pnt is None, this represents an interior ring
print "Interior Ring:"
partnum += 1

import arcpy

infc = "Magic.gdb/Polygons"
Reading geometry
desc = arcpy.Describe(infc)
shapefieldname = desc.ShapeFieldName

rows = arcpy.SearchCursor(infc)

for row in rows:
feat = row.getValue(shapefieldname)

print "tFeature %i:" % row.getValue(desc.OIDFieldName)
partnum = 0

for part in feat:
parts = []
print "Part %i:" % partnum

for pnt in feat.getPart(partnum):
if pnt:
parts.append([pnt.X, pnt.Y])
else:
parts.append(" ")
partnum += 1
print parts

Writing geometry
• arcpy.Point
• point features are point objects, lines and
polygons are arrays of point objects
– arcpy.PolyLine, arcpy.Polygon
• Geometry objects can be created using the
Geometry, Mulitpoint, PointGeometry, Polygo
n, or Polyline classes

data_list = [[33.09500,-93.90389],
[33.03194,-93.89806],
[34.34111,-93.50056],
[34.24917,-93.67667],
[34.22500,-93.89500],
[33.76833,-92.48500],
Writing geometry
[33.74500,-92.47667],
[33.68000,-92.46667],
[35.05425,-94.12711],
[35.03472,-94.12233],
[35.03333,-94.12236],
[35.01500,-94.12108],
[35.00392,-94.12033]]

import arcpy
import time
def PushNbiToFeatureclass( inFc, inList):
""" Take a list of NBI data and push it directly to a FGDB point FC """
try:
cur = arcpy.InsertCursor(inFc)
for line in inList:
t = 0
feat = cur.newRow()
feat.shape = arcpy.Point(line[1], line[0])
feat.setValue("Timestamp", time.strftime("%m/%d/%Y %H:%M:%S", time.localt
cur.insertRow(feat)
del cur
except Exception as e:
print e.message

PushNbiToFeatureclass(r”path to fc”, data_list)

import arcpy

arcpy.env.overwriteOutput = 1

# A list of features and coordinate pairs
coordList = [[[1,2], [2,4], [3,7]],
Writing geometry
[[6,8], [5,7], [7,2], [9,18]]]

# Create empty Point and Array objects
point = arcpy.Point()
array = arcpy.Array()
# A list that will hold each of the Polygon objects
featureList = []

for feature in coordList:
# For each coordinate pair, set the x,y properties and add to the
# Array object
for coordPair in feature:
point.X = coordPair[0]
point.Y = coordPair[1]
array.add(point)
# Add the first point of the array in to close off the polygon
array.add(array.getObject(0))
# Create a Polygon object based on the array of points
polygon = arcpy.Polygon(array)
# Clear the array for future use
array.removeAll()
# Append to the list of Polygon objects
featureList.append(polygon)

# Copy Polygon object to a featureclass
arcpy.CopyFeatures_management(featureList, "d:/temp/polygons.shp")

Rasters
• arcpy.Raster class
– raster object: variable that references a raster
dataset
– gives access to raster props
• raster calculations – Map Algebra
– outras = Slope(“in_raster”)
– can cast to Raster object for calculations

Rasters
import arcpy

def get_raster_props(in_raster):
"""Get properties of a raster, return as dict"""
# Cast input layer to a Raster
r = arcpy.Raster(in_raster)
raster_props = {} # Create empty dictionary to put props in below
raster_props["x_center"] = r.extent.XMin + (r.extent.XMax - r.extent.
raster_props["y_center"] = r.extent.YMin + (r.extent.YMax - r.extent.
raster_props["max_elev"] = r.maximum
raster_props["min_elev"] = r.minimum
raster_props["no_data"] = r.noDataValue
raster_props["terr_width"] = r.width
raster_props["terr_height"] = r.height
raster_props["terr_cell_res"] = r.meanCellHeight
# Return the dictionary of properties
return raster_props

Spatial references
• can get properties from arcpy.Describe
>>> sr =
arcpy.Describe(fc).spatialReference
>>> sr.type
u‟Projected‟ or u‟Geographic‟
• arcpy.SpatialReference class
• methods to create/edit spatial refs

Spatial references
• arcpy.SpatialReference class
• methods to create/edit spatial refs
>>> sr_utm = arcpy.SpatialReference()
>>> sr_utm.factoryCode = 26915
>>> sr_utm.create()
>>> sr_utm.name
...

Exception Handling
• It’s necessary, stuff fails
• Useful error reporting
• Proper application cleanup
• Combine it with logging
try:
do something...
except:
handle error...
finally:
clean up...

Exception handling – try/except
• most basic form of error handling
• wrap whole program or portions of code
• use optional finally clause for cleanup
– close open files
– close database connections
– check extensions back in

Exception handling

import arcpy
try:
arcpy.Buffer_analysis("Observer")
except Exception as e:
print e.message

Exception handling
import arcpy

try:
if arcpy.CheckExtension("3D") == "Available":
arcpy.CheckOutExtension("3D")
arcpy.Slope_3d("Magic.gdb/NWA10mNED",
"Magic.gdb/SlopeNWA")
except:
print arcpy.GetMessages(2)
finally:
# Check in the 3D Analyst extension
arcpy.CheckInExtension("3D")

Exception handling - raise
• allows you to force an exception to occur
• can be used to alert of conditions

Exception handling - raise
import arcpy

class LicenseError(Exception):
pass

try:
if arcpy.CheckExtension("3D") == "Available":
arcpy.CheckOutExtension("3D")
else:
raise LicenseError

arcpy.Slope_3d("NWA10mNED", "SlopeNWA")
except LicenseError:
print "3D Analyst license unavailable"
except:
print arcpy.GetMessages(2)
finally:
# Check in the 3D Analyst extension
arcpy.CheckInExtension("3D")

Exception handling
AddError and traceback
• AddError – returns GP-specific errors
• traceback – prints stack trace; determines
precise location of error
– good for larger, more complex programs

import arcpy
import sys
AddError and traceback import traceback
Exception handling –
arcpy.env.workspace = r"C:StudentCodeMAGIC.gdb"
try:
# Your code goes here
float("a string")

except:
# Get the traceback object
tb = sys.exc_info()[2]
tbinfo = traceback.format_tb(tb)[0]
# Concatenate information together concerning the error into a
message string
# tbinfo: where error occurred
# sys.exc_info: 3-tuple of type, value, traceback
pymsg = "PYTHON ERRORS:nTraceback info:n" + tbinfo + "nError
Info:n" + str(sys.exc_info()[1])
msgs = "ArcPy ERRORS:n" + arcpy.GetMessages(2) + "n"
# Return python error messages for use in script tool or Python
Window
arcpy.AddError(pymsg)
if arcpy.GetMessages(2):
arcpy.AddError(msgs)
print msgs
# Print Python error messages for use in Python / Python Window
print pymsg + "n"

Logging
• logging module
• logging levels:
– DEBUG: detailed; for troubleshooting
– INFO: normal operation, statuses
– WARNING: still working, but unexpected behavior
– ERROR: more serious, some function not working
– CRITICAL: program cannot continue

Super-basic logging
import logging
logging.warning("Look out!")
logging.info("Does this print?")

Super-basic logging to a log file
import logging
logging.basicConfig(filename='log_example.l
og',
level=logging.DEBUG)
logging.debug('This message should get
logged')
logging.info('So should this')
logging.warning('And this, too')

Super-basic logging to a log file
import logging
logging.basicConfig(filename="log_example.log",level=logging.D
EBUG)
logging.debug("This message should go to the log file")
logging.info("So should this")
logging.warning("And this, too")

Meaningful logging
• “customize” the logger
• add in info-level message(s) to get logged
• log our errors to log file
• can get much more advanced, see the docs

import arcpy
import sys
import traceback
import logging
import datetime

log_file = "meaningful_log_%s.log" % datetime.datetime.now().strftime("%Y_%m_%d_%H_%M_%S")
Meaningful logging
arcpy.env.workspace = r"C:StudentCodeMAGIC.gdb"

# Setup logger
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s %(levelname)-8s %(message)s',
datefmt='%Y-%m-%d %H:%M:%S',
filename=log_file,
filemode='w')
logging.info(': START LOGGING')

try:
# Your code goes here
float("lfkjdlk")

logging.info(": DONE")

except:
# Get the traceback object
tb = sys.exc_info()[2]
tbinfo = traceback.format_tb(tb)[0]
# Concatenate information together concerning the error into a message string
# tbinfo: where error occurred
# sys.exc_info: 3-tuple of type, value, traceback
pymsg = "PYTHON ERRORS:nTraceback info:n" + tbinfo + "nError Info:n" + str(sys.exc_info()[1])
msgs = "ArcPy ERRORS:n" + arcpy.GetMessages(2) + "n"
# Return python error messages for use in script tool or Python Window
arcpy.AddError(pymsg)
if arcpy.GetMessages(2):
arcpy.AddError(msgs)
logging.error(": %s" % msgs)
# Log Python error messages for use in Python / Python Window
logging.error(": %s" % pymsg + "n")

Code documentation
• Pythonic standards covered in PEPs 8 and 257
• help()
• comments need to be worth it
• name items well
• be precise and compact
• comments may be for you

Creating documentation
• pydoc – built-in; used by help()
– generate HTML on any module
– kinda plain
• epydoc – old, rumored to be dead
– produces nicely formatted HTML
– easy to install and use
• Sphinx framework
– “intelligent and beautiful documentation”
– all the cool kids are using it (docs.python.org)
– more involved to setup and use

Installing packages (on Windows)
• Windows executables
• Python eggs
– .zip file with metadata, renamed .egg
– distributes code as a bundle
– need easy_install
• pip
– tool for installing and managing Python packages
– replacement for easy_install

pip
C:pip search “kml”

C:pip install BeautifulSoup

C:pip install –upgrade pykml

C:pip uninstall BeautifulSoup

• can take care of dependencies for you
• uninstallation!
• install via easy_install, ironically

virtualenv
• a tool to create isolated Python environments
• manage dependencies on a per-project basis,
rather than globally installing
• test modules without installing into site-
packages
• avoid unintentional upgrades

virtualenv
• install via pip, easy_install, or by
C:python virtualenv.py
• create the env
C:dir virtualenv <env>
• activate the env
C:dir<env>Scripts activate
• use the env
(<env>) C:dir<env>Scriptspython
>>>

virtualenv
• installs Python where you tell it, modifies
system path to point there
– good only while the env is activated
• use yolk to list installed packages in env
(test) C:dir> yolk -l

• But can this work in ArcMap Python prompt?

virtualenv
• YES, with a little work...
>>>
execfile(r'C:<env>Scriptsactivate_this.py'
, {'__file__':
• tells ArcMap to use Python interpreter in
r'C:<env>Scriptsactivate_this.py'}) our
virtualenv
– kill ArcMap, back to using default interpreter

The web
• Infinite source of information
• Right-click and “Save as” is so lame (and too
much work)
• Python can help you exploit the web
– ftplib, http (urllib), mechanize, scraping (Beautiful
Soup), send email (smtplib)

Fetching data
• Built-in libraries for ftp and http
• ftplib – log in, nav to directory, retrieve files
• urllib/urllib2 – pass in the url you want, get it
back
• wget – GNU commandline tool
– Can call with os.system()

Fetching data
import urllib
urllib.urlretrieve("http://www.fhwa.dot.gov/bridge/nbi/2011/RI
11.txt",
"C:/temp/RI11.txt")

Scraping
• Scrape data from a web page
• Well-structured content is a HUGE help, as is
valid markup, which isn’t always there
• BeautifulSoup 3rd party module
– Built in methods and regex’s help out
– Great for getting at tables of data

Scraping addresses
http://www.phillypal.com/pal_locations.php

Scraping addresses
import BeautifulSoup as bs
import urllib2

url = "http://www.phillypal.com/pal_locations.php"

# Open the URL
response = urllib2.urlopen(url)
# Slurp all the HTML code into memory
html = response.read()
# Feed it into BS parser
soup = bs.BeautifulSoup(html)
# Find all the table cells whose width=37%
addresses = soup.findAll("td", {"width":"37%"})

print len(addresses)

for address in addresses:
# Print out just the text
print address.find(text=True)

Scraping addresses
1845 N. 23rd Street, 19121
3301 Tasker Street, 19145
5801 Media Street, 19131
250 S. 63rd Street, 19139
732 N. 17th Street, 19130
631 Snyder Avenue, 19148
6901 Rising Sun Avenue, 19111
851 E. Tioga Street, 19134
720 W. Cumberland St., 19133
3890 N. 10th Street, 19140
4550 Haverford Avenue, 19139
1100 W. Rockland St., 19141
1500 W. Ontario Street, 19140
2423 N. 27th Street, 19132
1267 E. Cheltenham Ave., 24
5330 Germantown Ave., 19144
1599 Wharton Street, 19146
4253 Frankford Avenue, 19124
2524 E. Clearfield St., 19134
6300 Garnet Street, 19126
5900 Elmwood Street, 19143
4301 Wayne Avenue, 19140
4401 Aldine Street, 19136
4614 Woodland Avenue, 19143
4419 Comly Street, 19135
2251 N. 54th Street, 19131

Emailing
• smtp built-in library
• best if you have IP of your email server
• port blocking can be an issue
import smtplib
server = smtplib.SMTP(email_server_ip)
msg = „All TPS reports need new cover
sheets‟
server.sendmail('from@me.com',
'to@you.com',
msg)
server.quit()
• there’s always Gmail too…

Files
• built in open function – slurp entire file into
memory – OK except for huge files
data = open(file).read().splitlines()

• iterate over the lines
for line in data:
do something

• CSV module
reader =
csv.reader(open('C:/file.csv','rb'))
for line in reader:
do something

Excel
• love, hate, love
• many modules out there
– xlrd (read) / xlwt (write) – only .xls
– openPyXL – read/write .xlsx
• uses
– Push text data to Excel file
– Push featureclass data to Excel programmatically
– Read someone else’s “database”

Reading Excel
import xlrd

# Open the workbook
wb = xlrd.open_workbook('Employees.xls')
wb.sheet_names()

# Get first sheet
sh=wb.sheet_by_index(0)
# Print out the rows
for row in range(sh.nrows):
print sh.row_values(row)

# Get a single cell
cell_b2 = sh.cell(1,1).value
print "n", cell_b2

# Write an XLS file with a single worksheet, containing
# a heading row and some rows of data.

import xlwt
import datetime
import bs_scrape as bs
import nbi_data_processing as nbi
ezxf = xlwt.easyxf

def write_xls(file_name, sheet_name, headings, data, heading_xf, data_xfs):
book = xlwt.Workbook()
sheet = book.add_sheet(sheet_name)
rowx = 0
for colx, value in enumerate(headings):
Writing Excel

sheet.write(rowx, colx, value, heading_xf)
sheet.set_panes_frozen(True) # frozen headings instead of split panes
sheet.set_horz_split_pos(rowx+1) # in general, freeze after last heading row
sheet.set_remove_splits(True) # if user does unfreeze, don"t leave a split there
for row in data:
rowx += 1
for colx, value in enumerate(row):
sheet.write(rowx, colx, value, data_xfs[colx])
book.save(file_name)

if __name__ == "__main__":
import sys

files = ["RI","HI"]
all_data = []
stateDict = bs.FetchFipsCodes( )
for f in files:
k = nbi.ParseNbiFile('C:/student/inputs/' + f + '11.txt', stateDict )
all_data.extend(k)
hdngs = ["Structure","State","Facility carried","Lat","Lon","Year built"]
kinds = "text text text double double yr".split()
data = []
for each_row in all_data:
data.extend([each_row])
# Format the headers
heading_xf = ezxf("font: bold on; align: wrap on, vert centre, horiz center")
# Set the data type formats
kind_to_xf_map = {
"date": ezxf(num_format_str="yyyy-mm-dd"),
"int": ezxf(num_format_str="#,##0"),
"money": ezxf("font: italic on; pattern: pattern solid, fore-colour grey25",
num_format_str="$#,##0.00"),
"price": ezxf(num_format_str="#0.000000"),
"double":ezxf(num_format_str="00.00000"),
"text": ezxf(),
"yr": ezxf(num_format_str="0000")
}
data_xfs = [kind_to_xf_map[k] for k in kinds]
write_xls("NBI_Data_To_Excel.xls", "NBI", hdngs, data, heading_xf, data_xfs)

Databases
• You can connect to pretty much ANY database
• Is there one true solution??
• pyodbc – Access, SQL Server, MySQL
• Oracle – cx_Oracle
• Others – pymssql, _mssql, MySQLdb
• Execute SQL statements through a connection
conn = library.connect(driver/user/pwd)
cursor = conn.cursor()
for row in cursor.execute(sql)
do something

Resources - FREE
• Dive into Python
• Python Cookbook
• Think Python
• Python docs
• gis.stackexchange.com
• Google is your friend (as always)
• Python community is HUGE and GIVING

Conferences
• pyArkansas – annually in Conway
– pyar2 list on python.org
• PyCon – THE national US Python conference
• FOSS4G – international open source for GIS
• ESRI Developer Summit – major dork-fest, but
great learning opportunity and Palm Springs in
March

IDEs and editors
• Wing – different license levels, good people
• PyScripter – open source, code completion
• Komodo – free version also available
• Notepad2 – ole’ standby editor
• Notepad++ - people swear by it
• PythonWin – another standby, but barebones
• …dozens (at least) more editors out there…

More reading
• http://www.voidspace.org.uk/python/articles/
OOP.shtml - great OOP article (which I used a
a lot)

Advanced geoprocessing with Python

Advanced geoprocessing with Python

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