All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
Introduction to the basics of Python programming (part 3)Pedro Rodrigues
This is the 3rd part of a multi-part series that teaches the basics of Python programming. It covers list and dict comprehensions, functions, modules and packages.
The basics of Python are rather straightforward. In a few minutes you can learn most of the syntax. There are some gotchas along the way that might appear tricky. This talk is meant to bring programmers up to speed with Python. They should be able to read and write Python.
All data values in Python are encapsulated in relevant object classes. Everything in Python is an object and every object has an identity, a type, and a value. Like another object-oriented language such as Java or C++, there are several data types which are built into Python. Extension modules which are written in C, Java, or other languages can define additional types.
To determine a variable's type in Python you can use the type() function. The value of some objects can be changed. Objects whose value can be changed are called mutable and objects whose value is unchangeable (once they are created) are called immutable.
Introduction to the basics of Python programming (part 3)Pedro Rodrigues
This is the 3rd part of a multi-part series that teaches the basics of Python programming. It covers list and dict comprehensions, functions, modules and packages.
The basics of Python are rather straightforward. In a few minutes you can learn most of the syntax. There are some gotchas along the way that might appear tricky. This talk is meant to bring programmers up to speed with Python. They should be able to read and write Python.
Introduction to the Python programming language (version 2.x)
Ambient intelligence: technology and design
http://bit.ly/polito-ami
Politecnico di Torino, 2015
Python 101++: Let's Get Down to Business!Paige Bailey
You've started the Codecademy and Coursera courses; you've thumbed through Zed Shaw's "Learn Python the Hard Way"; and now you're itching to see what Python can help you do. This is the workshop for you!
Here's the breakdown: we're going to be taking you on a whirlwind tour of Python's capabilities. By the end of the workshop, you should be able to easily follow any of the widely available Python courses on the internet, and have a grasp on some of the more complex aspects of the language.
Please don't forget to bring your personal laptop!
Audience: This course is aimed at those who already have some basic programming experience, either in Python or in another high level programming language (such as C/C++, Fortran, Java, Ruby, Perl, or Visual Basic). If you're an absolute beginner -- new to Python, and new to programming in general -- make sure to check out the "Python 101" workshop!
These are the slides of the second part of this multi-part series, from Learn Python Den Haag meetup group. It covers List comprehensions, Dictionary comprehensions and functions.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
Introduction to the Python programming language (version 2.x)
Ambient intelligence: technology and design
http://bit.ly/polito-ami
Politecnico di Torino, 2015
Python 101++: Let's Get Down to Business!Paige Bailey
You've started the Codecademy and Coursera courses; you've thumbed through Zed Shaw's "Learn Python the Hard Way"; and now you're itching to see what Python can help you do. This is the workshop for you!
Here's the breakdown: we're going to be taking you on a whirlwind tour of Python's capabilities. By the end of the workshop, you should be able to easily follow any of the widely available Python courses on the internet, and have a grasp on some of the more complex aspects of the language.
Please don't forget to bring your personal laptop!
Audience: This course is aimed at those who already have some basic programming experience, either in Python or in another high level programming language (such as C/C++, Fortran, Java, Ruby, Perl, or Visual Basic). If you're an absolute beginner -- new to Python, and new to programming in general -- make sure to check out the "Python 101" workshop!
These are the slides of the second part of this multi-part series, from Learn Python Den Haag meetup group. It covers List comprehensions, Dictionary comprehensions and functions.
This presentation is all about various built in
datastructures which we have in python.
List
Dictionary
Tuple
Set
and various methods present in each data structure
Python is a general-purpose interpreted, interactive, object-oriented, and high-level programming language.
Make use of the PPT to have a better understanding of Python.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
2. Install Python
• Find the most recent distribution for your
computer at:
http://www.python.org/download/releases/
• Download and execute Python MSI installer
for your platform
– For version 2.7 or higher
– Note: You may need to be logged in as
administrator to your computer to run the
installation!
3. Modes of Interaction with Python
• You can interact with the Python interpreter through two built-in
modes:
– Basic (command line) – not recommended!
– IDLE (Integrated development environment) - recommended for this class
• Command line mode:
– You can find and double click the Python.exe executable (e.g., python27)
in the downloaded folder.
– Make sure to right click it, and then create a shortcut to it, and pin it to
the taskbar for convenience!
– Click the icon on your taskbar to start the command line
You will get the >>> Python prompt
Type ‘exit’ at the command prompt to get out of the console!
>>> exit # or ctrl z
– Note: you can use the Home, Pg up, Pg dn, and End keys, to scroll
through previous entries, and repeat them by pressing the Enter key!
5. IDLE
• This is the integrated development environment for
Python
• Involves interactive interpreter with editing and
debugging capabilities (it prompts you for the names of
functions, etc., and color codes code)!
• You can find and double click the Pythonw.exe
executable (e.g., python27) in the downloaded folder
• Pin it to the taskbar.
6. Python IDLE Shell Window
• The IDLE (Python shell window) is more convenient than the
basic python command line
• Provides automatic indentation and highlights the code
• You can use the Home, Pg up, Pg dn, and End keys to search
the buffer in your session!
7. Learn Basic parts of Python
• Like other languages, Python has many data types
– These can be manipulated with operators, functions, and
methods
• You can also make your own types (classes) and instantiate and
manipulate them with operators, functions, and your own
methods
• Python also has conditional and iterative control, e.g.:
– if-elif-else
– while loop
– for loop
8. Python’s suggested naming style
• Function name is lower case
>>> def add (): # a function to add numbers; returns the result;
# note that function calls end with the : character
• Variable names are written in lower case, and are case sensitive!
inputFieldName
>>> fc # a variable to hold a feature class as in: fc=“Roads.shp”
Note: the two variables Road and road are different variables!
• Class name is UpperCamelCase
Class StrikeSlipFault, or class Lake
• Constants are written in all caps, e.g. PI, SPREADING_RATE
• Indentation: 4 spaces per level, do not use tabs!
– IDLE does it for you! So don’t worry about it.
9. Data
types
10/3 = 3, but 10/3.0 = 3.33333
The // operator is for integer division (quotient without remainder).
10//3 = 3 and 4//1.5 = 2, and 13//4 = 3
11. Manipulation of numbers
Addition (+)
>>> x=8+2
>>> print x # prints 10
Subtraction (-)
>>> x = 2
>>> x = x-2
>>> print x # prints 0
>>> (2+3j) – (5-4j) # prints (-3+7j)
Multiplication (*)
>>> 8*2 # prints 16
>>> 8*2.0 # prints 16.0
12. Division (/) # normal division
>>> 7/2 3
>>> 7/2.0 3.5
>>> 7//2 3 # integer results with truncation
Multiplication (*)
>>> 2*3.0 6.0
Exponentiation (**)
>>> 2**3.0 8.0
Modulus (%) # prints the remainder of the division
>>> 5%2 1
>>> 5.0%2 1.0
>>> 5.0%2.5 0.0 >>> 5%5 0
13. Precedence
>>> 5-2*3/4 4 # same as 5-((2*3)/4)
>>> 50/2+2**3-8/2 29 # (50/2)+(2**3)-(8/2)
# For equal precedence go from left to right!
# first power, then left division, then add them,
# then right division, then subtraction
>>> 24-(12-4)/2*2+3 19
# first do the parenthesis, then divide by 2,
# then multiply the result by 2, then
# subtract from 24, then add to 3
14. Built-in functions
>>> round (7.78) # Built-in function returns: 8
>>> int (230.5) # Built-in converts to integer, returns: 230
>>> float (230) # Built-in converts to float, returns: 230.0
>>> int (3e3) # returns: 3000
>>> type (151.0) # returns: <type 'float'>
>>> type (151) # returns: <type 'int'>
>>> type ('Python') # returns: <type 'str'>
15. Calling Python’s library functions in modules
>>> x = math.floor (-13.4) # leads to the following error:
Traceback (most recent call last): File "<interactive input>", line
1, in <module>NameError: name 'math' is not defined
>>> import math # imports the math module
# now we can use math’s functions
>>> x = math.floor (-13.4) # call math’s floor () function
>>> print x
-14.0
>>>
16. Python library module functions
• Trigonometric, factorial, pi, sqrt, ceil, degrees, exp, floor, etc., are in
the math module library
>>> Import math
>>> math.pi 3.14 # call a math library constant
>>> math.ceil (3.14) 4 # call a module function ()
>>> math.sqrt (64) 8
>>> math.log10 (1000000) 6.0
>>> math.e 2.718281828459045
>>> import random # import the random module
>>> x = random.uniform (1, 5) # returns a float between 1 and 5
>>> x 2.8153025790665516
>>> x = random.randint (1, 5) # returns an integer between 1 and 5
>>> x 1
17. Python’s built-in numeric functions
abs (), float (), hex (), oct (), long (), max (),
min (), pow (), round ()
• There are many more functions for
trigonometry, etc.
• ‘none’ is a special data type for empty value
– e.g., when a function does not return a value
– It is used as a placeholder. Similar to null.
20. Getting input from user
>>> age = int (input("What is your age? "))
# displays a dialog for user to enter data
# user enters a number (e.g., 45)
>>> print age # prints the entered age (45)
45
21. Assignment to a variable
• To assign a value to a variable, you put the variable on the left
side of an equal sign (=) and put (or retrieve) the value to the
right, for example:
>>> result = pow (4, 2)
>>> print result # prints 16
• Let’s assign the number of zip codes in a GIS layer by calling
the GetCount tool’s management () function in arcpy and
passing it the name of the “zipcodes” layer as argument.
>>> count =arcpy.GetCount_management (“zipcodes’)
# This will return a number and assigns it to the count variable,
# which can then be used in another call , for example:
>>> print count
22. arcpy package for ArcGIS
• Geoprocessing in ArcGIS is done through the arcpy package
>>> import arcpy
>>> arcpy.env.workspace = “C:/Data” # sets the current workspace
# env is a class in arcpy, and workspace is a property.
>>> from arcpy import env # this does not import the entire arcpy
>>> env.workspace = “C:/Data”
23. Strings
• Strings are immutable sequence of characters (text)
• These are inserted either in “ ” or ‘ ’.
• A double quote (“ ”) can contain single quote (‘ ’), e.g.,
“ ’dog’, ‘cat’ ” in a string
• and vice versa, e.g., ‘ ”dog”, “cat” ’ in a string
• They can also be in triple single or double quotes:
‘’’ ‘‘‘ or “”” “””.
– This is used for multi-line commenting
24. Escape characters
’ Single
quote
” Double
quote
Backslash bBackspace n newline
r Carriage
return
t tab
We have to escape special characters such as or “
>>> x = "Location of the file is: C:GeologyGeoinformatics“
>>> print x
Location of the file is: C:GeologyGeoinformatics
>>> print ("tabc") # t is tab
abc
>>> x="tHello Python World!“
>>> print x
Hello Python World!
>>> tictactoe = ("XtOtXnXtXtXnOtOtO")
>>> print tictactoe
X O X
X X X
O O O
25. Strings
# The split () function breaks a string into pieces completely or at a specific character.
>>> x = "Chattahoochie“
>>> x.split ("oo")
['Chattah', 'chie']
27. Strings …
The find() function returns the index of the first occurrence of a character.
The replace (a, b) function takes two arguments . Replaces a with b.
29. String operators + and *
>>> x = "Mississippi“
>>> y = "River“
>>> z = x + ' ' + y # concatenates the two strings, puts space in between
>>> print z
Mississippi River
>>> T = 32 # note: 32 is a number (not a string).
>>> print ("Today is freezing! The temperature is: " + str (T) + ' ' +
"degrees Fahrenheit") # we cast the number into string by str (T)
Today is freezing! The temperature is: 32 degrees Fahrenheit
>>> 3*'A‘ # * repeats the character
‘AAA‘
30. String’s join () methods
• The join () method puts spaces or other characters between
strings
>>> "-".join (['to', 'be', 'or', 'not', 'to', 'be'])
'to-be-or-not-to-be‘ # put hyphen between words
>>> "-".join ("To be or not to be")
‘T-o- -b-e- -o-r- -n-o-t- -t-o- -b-e‘
>>> "-".join ("Tobeornottobe")
‘T-o-b-e-o-r-n-o-t-t-o-b-e'
>>> " ".join(['to', 'be', 'or', 'not', 'to', 'be'])
'to be or not to be‘ # puts a blank between them
31. >>> x = "Diamond is the hardest mineral"
>>> print x Diamond is the hardest mineral
>>> X[0] ’D’ # prints the first character of the string
>>> x.split() ['Diamond', 'is', 'the', 'hardest', 'mineral']
# The following is a multi-line comment in triple quote:
>>> """ Minerals are naturally occurring, inorganic, solid
... substances with crystalline structure and composition """
>>> min = 'Minerals are naturally occurring, inorganic, solidn substances
with crystalline structure and composition‘
>>> print min
Minerals are naturally occurring, inorganic, solid
substances with crystalline structure and composition
>>> pi = 3.14
>>> print "The value for pi is:", pi The value for pi is: 3.14 # or
>>> print "The value for pi is: ", math.pi # assume math is imported
The value for pi is: 3.14159265359
32. >>> x = " Map is NOT territory ! “
>>> x.strip()
'Map is NOT territory!‘ # strips white space
>>> x.lstrip ()
'Map is NOT territory ! ‘ # strips white space from left
>>> x.rstrip ()
' Map is NOT territory !‘ # strips white space from right
>>> email = 'www.gsu.edu/~geohab‘
>>> email.strip (“~geohab”) # strips the passed string
‘www.gsu.edu/'
The strip () method
33. String searching
>>> word = "Uniformitarianism“
>>> word.find ('i') #find the index of the first occurrence of ‘I’
2
>>> word.find ('i', 6) #find ‘i’ after index 6
7
>>> word.rfind('m') # find index for ‘m’. moves from the right end
16
>>> word.count('i') # find how many times ‘i’ is there in the word
4
>>> word.startswith ('U')
True
>>> word.endswith('P')
False
34. Strings are immutable
• Cannot change a string, but can modify and return a new string!
>>> x = "Mississippi“
>>> x.replace('ss', 'pp')
'Mippippippi‘ # this is a new string
>>> x.upper() # original value of x is still unchanged
MISSISSIPPI
>>> x.lower()
mississippi # original is still unchanged
>>> bookTitle = "knowledge engineering for beginners"
>>> bookTitle.title () 'Knowledge Engineering For Beginners‘
>>> file = 'Rivers.shp‘
>>> file.replace ('.shp', "") 'Rivers‘
>>> len ('Diamond') 7
35. Casting strings to numbers
>>> float ("12345.34") # it works; numeric string is ok
12345.34
>>> int ('23456') # it work!
23456
>>> int ('123.45') # error: decimal does not work
>>> float ("xyz") # error: letter character to number
36. Methods
>>> course = "Geoinformatics: Geol 4123“
>>> print course.lower ()
geoinformatics: geol 4123
>>> print course.upper () GEOINFORMATICS: GEOL 4123
>>> 'GEO' in course False
>>> 'Geo' in course True
>>> course = "Geoinformatics Geol 4123“
>>> course.find ('Geo') # returns the index
0 # index of the first item
>>> course.find('GEO')
-1 # not found
38. Lists
• List is an ordered collection of objects
• List is modifiable (mutable).
• They can have elements of different types
• Elements are comma separated in a []
>>> rivers = [Missouri, Fox, Mississippi] # assigns to the rivers list
>>> x = ['apple', 3, [4.0, 5.0]] # multi-type list
>>> fileExtension = ["jpg", "txt", "doc", "bmp”, "tif"]
>>> print fileExtension
['jpg', 'txt', 'doc', 'bmp', 'tif']
39. List
>>> x [:-2] -> [‘hydroxide’, ‘phosphate’, ‘carbonate’]
# up to, but not including index -2, i.e., gets rid of the last two
>>> x [2:] -> [‘carbonate’, ‘oxide’, ‘silicate’] # values from position 2 to the end (inclusive)
40. List indices
• Lists start counting from 0 on the left side (using + numbers) and -
1 from the right side
>>> x = ['River', 'Lake', 'Rock', 'Water', 'Air']
>>> X[2] ‘Rock’
>>> X[-5] ‘River’
>>> x[:3] ['River', 'Lake', 'Rock']
>>> X[0:3] ['River', 'Lake', 'Rock'] # includes 0 but excludes 3
>>> x[3:10] ['Water', 'Air'] # ignores if the items don’t exist
>>> x[3:] ['Water', 'Air'] # index 3 and higher
X = [ ‘River ‘Lake’ ‘Rock’ ‘Water’ ‘Air’ ]
+ index 0 1 2 3 4
- Index -5 -4 -3 -2 -1
41. >>> lang = ['P', ‘Y', 'T', 'H', 'O', 'N']
>>> lang[3] 'H‘
>>> lang[-1] 'N‘
>>> lang[-6] 'P‘
>>> lang[-8]
Traceback (most recent call last): File "<interactive input>",
line 1, in <module>IndexError: list index out of range
>>> lang[:3] ['P', ‘Y', 'T']
>>> lang [-3:]['H', 'O', 'N']
>>>
P Y T H O N
0 1 2 3 4 5 6
-6 -5 -4 -3 -2 -1
42. Lists have mixed types
The len () functions returns the number of
elements in a list
>>> x = [1, 2, 3, [3, 4]]
>>> len (x)
4
46. Lists can change
>>> x = ['River', 'Lake', 'Rock']
>>> x[1] = 'Horse‘
>>> x[0:]
['River', 'Horse', 'Rock']
>>> y = x[:] # copies all x’s elements and assigns to y
>>> y[0] = 'Timber‘ # substitute
>>> y[2] = 'Lumber‘ # substitute
>>> y[0:] #show y from the beginning
['Timber', 'Horse', 'Lumber']
47. Modifying lists …
>>> x=[1,2,3] # let’s append a new list to the end of this list
>>> x[len(x):] = [4, 5, 6, 7] # find the length; append after last index
>>> print x [1, 2, 3, 4, 5, 6, 7]
>>> x[ :0] = [-2, -1, 0] # append this list to the front of the original list
>>> print x [-2, -1, 0, 1, 2, 3, 4, 5, 6, 7]
>>> x[1:-1] = []
# removes elements between the 2nd and one before the last index
>>> print x [-2, 7]
>>> x.append("new element") # adds a new element to the list
>>> print x [-2, 7, 'new element']
48. Modifying lists…
>>> x=[1,2,3,4]
>>> y=[5,6]
>>> x.append(y) # adds y as an element (in this case a list) to the end of x
>>> print x [1, 2, 3, 4, [5, 6]]
>>> x=[1,2,3,4]
>>> y = [5,6]
>>> x.extend(y) # adds the items to the end of an existing list
>>> print x [1, 2, 3, 4, 5, 6]
>>> x.insert(2, 'Hello')
# inserts an element after a given index; always needs two arguments
>>> print x [1, 2, 'Hello', 3, 4, 5, 6]
>>> x.insert(0, 'new') # insert at the beginning (at index 0) an new item
>>> print x ['new', 1, 2, 'Hello', 3, 4, 5, 6]
49. The + and * operators and lists
>>> X = [1, 2, 3, 4, [5, 6]]
>>> y = x + [7,8] #concatenation with the + charecter
>>> print y [1, 2, 3, 4, [5, 6], 7, 8]
>>> x = ['Wow']
>>> x = x + ['!']
>>> print x ['Wow', '!']
>>> x.append(‘!')
>>> print x ['Wow', '!', ‘!']
>>> x = ['Wow']
>>> x.extend('!')
>>> print x ['Wow', '!']
50. …
>>> X = ['Mercury','Venus','Earth','Mars','Jupiter','Saturn','Uranus','Neptune',
'Pluto']
>>> del x[8] # removes Pluto from the Solar System list!
>>> print x
['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune']
>>> X = ['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus',
'Neptune']
>>> x.append('Pluto') # add Pluto to the end
>>> print x
['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune',
'Pluto']
>>> x.remove('Pluto') # removes ‘Pluto’ at its first occurrence
>>> print x
['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus', 'Neptune']
52. The in operator
>>> x = ['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus',
'Neptune']
>>> 'Pluto' in x
False
>>> 'Earth' in x
True
53. The min, max, index, and count functions
>>> x = ['Mercury', 'Venus', 'Earth', 'Mars', 'Jupiter', 'Saturn', 'Uranus',
'Neptune']
>>> min (x) ‘Earth‘
>>> max (x) ‘Venus‘
>>> x = [8, 0, -3, -1, 45]
>>> min (x) -3
>>> max (x) 45
>>> x = [8, 0, -3, -1, 45]
>>> x.index(-3) 2 #returns the index for ‘-3’
>>> x.index(45) 4 #returns the index for ‘45’
>>> x = [2, 5, 3, 3, 4, 3, 6]
>>> x.count(3) 3
55. Sets: unordered collection of objects
Sets are unordered collection of objects and can be changed
Duplicates are removed, even when you add them
The ‘in’ keyword checks for membership in the set
57. Tuples – ()
• Are similar to lists but are immutable (like strings)
– can only be created but not changed!
– Used as keys for dictionaries
– Instead of x=[] for lists, we use x=() to create tuples
• Many of the functions and operators that work with lists
also work for tuples, e.g.:
len(), min(), max(), and the +, and * operands.
58. Tuples …
>>> x = () # create an empty tuple
>>> print x # prints ()
>>> (Mercury, Venus, Earth, Mars) = (1, 2, 3, 4)
>>> Earth
3
>>> list ((Mercury, Venus, Earth, Mars))
# cast by the list () function
# the casting function list () converts a tuple to a list
[1, 2, 3, 4]
>>>
59. Dictionaries – {}
• Called dictionary because they allow mapping from arbitrary objects (e.g.,
words in a dictionary) to other sets of arbitrary objects.
• Values in a dictionary are accessed via keys that are not just numbers.
They can be strings and other Python objects. Keys point to values.
– Compare this to indices in lists
• Both lists and dictionaries store elements of different types
• Values in a list are implicitly ordered by their indices.
• Those in dictionaries are unordered.
>>> x = {} # create an empty dictionary
>>> x[0] = 'Mercury‘ # assigns a value to a dictionary variable as if it is a list
# this cannot be done to a list if x is not defined! Y[0] = ‘1’ does not work
60. >>> x = {} # declare x as a dictionary
>>> x["Venus"] = 2 # indexing with non numbers (in this case string)
>>> y = {}
>>> y['Earth'] = 3
>>> x['Venus'] * y ['Earth'] # this cannot be done with lists (need int indices)
6
>>> phone = {} # declare phone as a dictionary
# dictionaries are great for indexing lists by names (lists cannot do it)
>>> phone ['Babaie'] = 1234567899
>>> print phone['Babaie']
1234567899
61. >>> Eng_to_Fr ['river'] = 'fleuve‘
>>> print 'River in French is', Eng_to_Fr ['river']
River in French is fleuve
>>> Eng_to_Fr = {'blue': 'bleu', 'green': 'vert'}
>>> print Eng_to_Fr {'blue': 'bleu', 'green': 'vert'}
>>> 'blue' in Eng_to_Fr True
>>> print Eng_to_Fr.get ('green') vert # uses the get ()
>>> Eng_to_Fr.copy () # copy () copies the dictionary
{'blue': 'bleu', 'green': 'vert'}
62. >>> x = {1: 'solid', 2: 'liquid', 3: 'gas'}
>>> y = {4: 'plasma'}
>>> y.update(x) # update y with x
>>> y {1: 'solid', 2: 'liquid', 3: 'gas', 4: 'plasma'}
>>> x {1: 'solid', 2: 'liquid', 3: 'gas'} # unchanged
>>> x.update(y) # update x with y
>>> x {1: 'solid', 2: 'liquid', 3: 'gas', 4: 'plasma'}
64. • In Python (an OOP language) everything is an
object.
• All objects have id, name, and type
>>> River = "Chattahoochie“
>>> type (River)
<type 'str‘> # this is printed by Python
>>> id (River)
46695832 # this is its address in memory
>>>
Python objects
65. Objects have methods
• Objects can do things through methods
• Methods are coupled to specific objects of a class
• object.method (arguments)
>>> course = "Geoinformatics“
>>> course.count ('i')
2
• Most of the functions which we have seen so
far are method.