61a lecture 24
play

61A Lecture 24 Friday, November 1 Announcements 2 Announcements - PowerPoint PPT Presentation

Apr 15, 2023 •532 likes •1.89k views

61A Lecture 24 Friday, November 1 Announcements 2 Announcements Homework 7 due Tuesday 11/5 @ 11:59pm. 2 Announcements Homework 7 due Tuesday 11/5 @ 11:59pm. Project 1 composition revisions due Thursday 11/7 @ 11:59pm. 2 Heard on

  1. Raise Statements Exceptions are raised with a raise statement. raise <expression> <expression> must evaluate to a subclass of BaseException or an instance of one. Exceptions are constructed like any other object. E.g., TypeError('Bad argument!') TypeError -- A function was passed the wrong number/type of argument NameError -- A name wasn't found KeyError -- A key wasn't found in a dictionary 9

  2. Raise Statements Exceptions are raised with a raise statement. raise <expression> <expression> must evaluate to a subclass of BaseException or an instance of one. Exceptions are constructed like any other object. E.g., TypeError('Bad argument!') TypeError -- A function was passed the wrong number/type of argument NameError -- A name wasn't found KeyError -- A key wasn't found in a dictionary RuntimeError -- Catch-all for troubles during interpretation 9

  3. Raise Statements Exceptions are raised with a raise statement. raise <expression> <expression> must evaluate to a subclass of BaseException or an instance of one. Exceptions are constructed like any other object. E.g., TypeError('Bad argument!') TypeError -- A function was passed the wrong number/type of argument NameError -- A name wasn't found KeyError -- A key wasn't found in a dictionary RuntimeError -- Catch-all for troubles during interpretation (Demo) 9

  4. Try Statements

  5. Try Statements 11

  6. Try Statements Try statements handle exceptions 11

  7. Try Statements Try statements handle exceptions try: <try suite> except <exception class> as <name>: <except suite> ... 11

  8. Try Statements Try statements handle exceptions try: <try suite> except <exception class> as <name>: <except suite> ... Execution rule: 11

  9. Try Statements Try statements handle exceptions try: <try suite> except <exception class> as <name>: <except suite> ... Execution rule: The <try suite> is executed first. 11

  10. Try Statements Try statements handle exceptions try: <try suite> except <exception class> as <name>: <except suite> ... Execution rule: The <try suite> is executed first. If, during the course of executing the <try suite> , an exception is raised that is not handled otherwise, and 11

  11. Try Statements Try statements handle exceptions try: <try suite> except <exception class> as <name>: <except suite> ... Execution rule: The <try suite> is executed first. If, during the course of executing the <try suite> , an exception is raised that is not handled otherwise, and If the class of the exception inherits from <exception class> , then 11

  12. Try Statements Try statements handle exceptions try: <try suite> except <exception class> as <name>: <except suite> ... Execution rule: The <try suite> is executed first. If, during the course of executing the <try suite> , an exception is raised that is not handled otherwise, and If the class of the exception inherits from <exception class> , then The <except suite> is executed, with <name> bound to the exception. 11

  13. Handling Exceptions 12

  14. Handling Exceptions Exception handling can prevent a program from terminating 12

  15. Handling Exceptions Exception handling can prevent a program from terminating >>> try: 12

  16. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 12

  17. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 except ZeroDivisionError as e: 12

  18. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 except ZeroDivisionError as e: print('handling a', type(e)) 12

  19. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 except ZeroDivisionError as e: print('handling a', type(e)) x = 0 12

  20. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 except ZeroDivisionError as e: print('handling a', type(e)) x = 0 handling a <class 'ZeroDivisionError'> 12

  21. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 except ZeroDivisionError as e: print('handling a', type(e)) x = 0 handling a <class 'ZeroDivisionError'> >>> x 12

  22. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 except ZeroDivisionError as e: print('handling a', type(e)) x = 0 handling a <class 'ZeroDivisionError'> >>> x 0 12

  23. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 except ZeroDivisionError as e: print('handling a', type(e)) x = 0 handling a <class 'ZeroDivisionError'> >>> x 0 Multiple try statements : Control jumps to the except suite of the most recent try statement that handles that type of exception. 12

  24. Handling Exceptions Exception handling can prevent a program from terminating >>> try: x = 1/0 except ZeroDivisionError as e: print('handling a', type(e)) x = 0 handling a <class 'ZeroDivisionError'> >>> x 0 Multiple try statements : Control jumps to the except suite of the most recent try statement that handles that type of exception. (Demo) 12

  25. WWPD: What Would Python Do? How will the Python interpreter respond? 13

  26. WWPD: What Would Python Do? How will the Python interpreter respond? 13

  27. WWPD: What Would Python Do? How will the Python interpreter respond? def invert(x): result = 1/x # Raises a ZeroDivisionError if x is 0 print('Never printed if x is 0') return result def invert_safe(x): try : return invert(x) except ZeroDivisionError as e: return str(e) 13

  28. WWPD: What Would Python Do? How will the Python interpreter respond? def invert(x): result = 1/x # Raises a ZeroDivisionError if x is 0 print('Never printed if x is 0') return result def invert_safe(x): try : return invert(x) except ZeroDivisionError as e: return str(e) >>> invert_safe(1/0) 13

  29. WWPD: What Would Python Do? How will the Python interpreter respond? def invert(x): result = 1/x # Raises a ZeroDivisionError if x is 0 print('Never printed if x is 0') return result def invert_safe(x): try : return invert(x) except ZeroDivisionError as e: return str(e) >>> invert_safe(1/0) >>> try : 13

  30. WWPD: What Would Python Do? How will the Python interpreter respond? def invert(x): result = 1/x # Raises a ZeroDivisionError if x is 0 print('Never printed if x is 0') return result def invert_safe(x): try : return invert(x) except ZeroDivisionError as e: return str(e) >>> invert_safe(1/0) >>> try : ... invert_safe(0) 13

  31. WWPD: What Would Python Do? How will the Python interpreter respond? def invert(x): result = 1/x # Raises a ZeroDivisionError if x is 0 print('Never printed if x is 0') return result def invert_safe(x): try : return invert(x) except ZeroDivisionError as e: return str(e) >>> invert_safe(1/0) >>> try : ... invert_safe(0) ... except ZeroDivisionError as e: 13

  32. WWPD: What Would Python Do? How will the Python interpreter respond? def invert(x): result = 1/x # Raises a ZeroDivisionError if x is 0 print('Never printed if x is 0') return result def invert_safe(x): try : return invert(x) except ZeroDivisionError as e: return str(e) >>> invert_safe(1/0) >>> try : ... invert_safe(0) ... except ZeroDivisionError as e: ... print ('Handled!') 13

  33. WWPD: What Would Python Do? How will the Python interpreter respond? def invert(x): result = 1/x # Raises a ZeroDivisionError if x is 0 print('Never printed if x is 0') return result def invert_safe(x): try : return invert(x) except ZeroDivisionError as e: return str(e) >>> invert_safe(1/0) >>> try : ... invert_safe(0) ... except ZeroDivisionError as e: ... print ('Handled!') >>> inverrrrt_safe(1/0) 13

  34. Interpreters

  35. Reading Scheme Lists 15

  36. Reading Scheme Lists A Scheme list is written as elements in parentheses: 15

  37. Reading Scheme Lists A Scheme list is written as elements in parentheses: (<element_0> <element_1> ... <element_n>) 15

  38. Reading Scheme Lists A Scheme list is written as elements in parentheses: (<element_0> <element_1> ... <element_n>) Each <element> can be a combination or primitive. 15

  39. Reading Scheme Lists A Scheme list is written as elements in parentheses: (<element_0> <element_1> ... <element_n>) Each <element> can be a combination or primitive. (+ (* 3 (+ (* 2 4) (+ 3 5))) (+ (- 10 7) 6)) 15

  40. Reading Scheme Lists A Scheme list is written as elements in parentheses: (<element_0> <element_1> ... <element_n>) Each <element> can be a combination or primitive. (+ (* 3 (+ (* 2 4) (+ 3 5))) (+ (- 10 7) 6)) The task of parsing a language involves coercing a string representation of an expression to the expression itself. 15

  41. Reading Scheme Lists A Scheme list is written as elements in parentheses: (<element_0> <element_1> ... <element_n>) Each <element> can be a combination or primitive. (+ (* 3 (+ (* 2 4) (+ 3 5))) (+ (- 10 7) 6)) The task of parsing a language involves coercing a string representation of an expression to the expression itself. Parsers must validate that expressions are well-formed. 15

  42. Reading Scheme Lists A Scheme list is written as elements in parentheses: (<element_0> <element_1> ... <element_n>) Each <element> can be a combination or primitive. (+ (* 3 (+ (* 2 4) (+ 3 5))) (+ (- 10 7) 6)) The task of parsing a language involves coercing a string representation of an expression to the expression itself. Parsers must validate that expressions are well-formed. (Demo) http://composingprograms.com/projects/scalc/scheme_reader.py.html 15

  43. Reading Scheme Lists A Scheme list is written as elements in parentheses: A recursive (<element_0> <element_1> ... <element_n>) Scheme list Each <element> can be a combination or primitive. (+ (* 3 (+ (* 2 4) (+ 3 5))) (+ (- 10 7) 6)) The task of parsing a language involves coercing a string representation of an expression to the expression itself. Parsers must validate that expressions are well-formed. (Demo) http://composingprograms.com/projects/scalc/scheme_reader.py.html 15

  44. Reading Scheme Lists A Scheme list is written as elements in parentheses: A recursive (<element_0> <element_1> ... <element_n>) Scheme list Each <element> can be a combination or primitive. (+ (* 3 (+ (* 2 4) (+ 3 5))) (+ (- 10 7) 6)) The task of parsing a language involves coercing a string representation of an expression to the expression itself. Parsers must validate that expressions are well-formed. (Demo) http://composingprograms.com/projects/scalc/scheme_reader.py.html 15

  45. Reading Scheme Lists A Scheme list is written as elements in parentheses: A recursive (<element_0> <element_1> ... <element_n>) Scheme list Each <element> can be a combination or primitive. (+ (* 3 (+ (* 2 4) (+ 3 5))) (+ (- 10 7) 6)) The task of parsing a language involves coercing a string representation of an expression to the expression itself. Parsers must validate that expressions are well-formed. (Demo) http://composingprograms.com/projects/scalc/scheme_reader.py.html 15

  46. Parsing

  47. Parsing 17

  48. Parsing A Parser takes text and returns an expression. 17

  49. Parsing A Parser takes text and returns an expression. Text Expression 17

  50. Parsing A Parser takes text and returns an expression. Lexical Text Expression analysis 17

  51. Parsing A Parser takes text and returns an expression. Lexical Text Tokens Expression analysis 17

  52. Parsing A Parser takes text and returns an expression. Lexical Syntactic Text Tokens Expression analysis analysis 17

  53. Parsing A Parser takes text and returns an expression. Lexical Syntactic Text Tokens Expression analysis analysis '(+ 1' ' (- 23)' ' (* 4 5.6))' 17

  54. Parsing A Parser takes text and returns an expression. Lexical Syntactic Text Tokens Expression analysis analysis '(+ 1' ' (- 23)' ' (* 4 5.6))' 17

  55. Parsing A Parser takes text and returns an expression. Lexical Syntactic Text Tokens Expression analysis analysis '(+ 1' '(', '+', 1 ' (- 23)' ' (* 4 5.6))' 17

  56. Parsing A Parser takes text and returns an expression. Lexical Syntactic Text Tokens Expression analysis analysis '(+ 1' '(', '+', 1 ' (- 23)' '(', '-', 23, ')' ' (* 4 5.6))' 17

  57. Parsing A Parser takes text and returns an expression. Lexical Syntactic Text Tokens Expression analysis analysis '(+ 1' '(', '+', 1 ' (- 23)' '(', '-', 23, ')' ' (* 4 5.6))' 17

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Lecture # 5 - Monday, Aug 30th In this lecture I reviewed the previous lecture 4, and then

Lecture # 5 - Monday, Aug 30th In this lecture I reviewed the previous lecture 4, and then

Lecture # 5 - Monday, Aug 30th In this lecture I reviewed the previous lecture 4, and then reviewed the final point of lecture #3: Hennigs logical approach to tree inference is valid as logic, but we have a hard time using it because our data

660 views • 7 slides
Algorithms (2IL15) Lecture 13 Wrap-up lecture 1 TU/e Algorithms (2IL15) Lecture 13

Algorithms (2IL15) Lecture 13 Wrap-up lecture 1 TU/e Algorithms (2IL15) Lecture 13

TU/e Algorithms (2IL15) Lecture 13 Algorithms (2IL15) Lecture 13 Wrap-up lecture 1 TU/e Algorithms (2IL15) Lecture 13 Part I of the course: Optimization Problems we want to find valid solution minimizing cost (or maximizing

904 views • 20 slides
In 2020SP, this lecture and lecture 20 are both optional extra material CS 5412/LECTURE 17 Ken

In 2020SP, this lecture and lecture 20 are both optional extra material CS 5412/LECTURE 17 Ken

In 2020SP, this lecture and lecture 20 are both optional extra material CS 5412/LECTURE 17 Ken Birman LEAVE NO TRACE BEHIND Spring, 2020 HTTP://WWW.CS.CORNELL.EDU/COURSES/CS5412/2020SP 1 THE PRIVACY PUZZLE FOR I O T We have sensors

1.04k views • 65 slides
Recall last lecture ... Lecture 8 Also last lecture: Painter's Algorithm More Hidden Surface

Recall last lecture ... Lecture 8 Also last lecture: Painter's Algorithm More Hidden Surface

Recall last lecture ... Lecture 8 Also last lecture: Painter's Algorithm More Hidden Surface Removal Sort polygons in depth. Use the farthest vertex in each polygon as the sorting key. Efficient Painter - binary space partition (BSP)

563 views • 6 slides
Plan Lecture 1 - String diagrams and symmetric monoidal categories Lecture 2 -

Plan Lecture 1 - String diagrams and symmetric monoidal categories Lecture 2 -

Plan Lecture 1 - String diagrams and symmetric monoidal categories Lecture 2 - Resource-sensitive algebraic theories Lecture 3 - Interacting Hopf monoids and graphical linear algebra Lecture 4 - Signal Flow Graphs and recurrence

1.2k views • 61 slides
Where are we at - Topic overview Lecture 1A: Security requirements/features Lecture 7A

Where are we at - Topic overview Lecture 1A: Security requirements/features Lecture 7A

Where are we at - Topic overview Lecture 1A: Security requirements/features Lecture 7A Threatens Privacy Threatens Try to achieve Lecture 2B: Network threats Lecture 3A: Attacks on Lecture 6A: Security Protocols Web servers, malware

381 views • 25 slides
Lecture Capture Introduction to Lecture Capture Learning Outcomes What will lecture capture

Lecture Capture Introduction to Lecture Capture Learning Outcomes What will lecture capture

ISDS &amp; Digital Business Skills Lecture Capture Introduction to Lecture Capture Learning Outcomes What will lecture capture actually do? What happens before a lecture? What happens during a lecture? What does the button do?

527 views • 18 slides
CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How

CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How

CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How can we predict binary or categorical variables? {0,1}, {True, False} {1, , N} Last lecture Will I purchase this product? (yes) Will I click

1.74k views • 60 slides
CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How

CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How

CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How can we predict binary or categorical variables? {0,1}, {True, False} {1, , N} Last lecture Will I purchase this product? (yes) Will I click

850 views • 46 slides
CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How

CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How

CSE 158 Lecture 4 Web Mining and Recommender Systems More Classifiers Last lecture How can we predict binary or categorical variables? {0,1}, {True, False} {1, , N} Last lecture Will I purchase this product? (yes) Will I click

839 views • 58 slides
Usability of Programming Languages Lecture 4 - directed by your research interests Lecture

Usability of Programming Languages Lecture 4 - directed by your research interests Lecture

Overview Practical experimental course lectures are only introductory Lecture 1 - theoretical principles classic approaches l h current trends in leading research. Lecture 2 - candidate research methods advantages and

499 views • 15 slides
Introduction to AI &amp; Intelligent Agents This Lecture Chapters 1 and 2 Next Lecture

Introduction to AI &amp; Intelligent Agents This Lecture Chapters 1 and 2 Next Lecture

Introduction to AI &amp; Intelligent Agents This Lecture Chapters 1 and 2 Next Lecture Chapter 3.1 to 3.4 (Please read lecture topic material before and after each lecture on that topic) What is Artificial Intelligence? Thought

636 views • 31 slides
Introduction to Numerical Optimization Biostatistics 615/815 Lecture 14 Lecture 14 Course is

Introduction to Numerical Optimization Biostatistics 615/815 Lecture 14 Lecture 14 Course is

Introduction to Numerical Optimization Biostatistics 615/815 Lecture 14 Lecture 14 Course is More Than Half Done! If you have comments they are very welcome y y Lectures Lecture notes Weekly Homework Midterm

795 views • 42 slides
Lecture 12: Clustering 1 6.0002 LECTURE 12 Re Reading Chapter 23 6.0002 LECTURE 12 2 Mach Ma

Lecture 12: Clustering 1 6.0002 LECTURE 12 Re Reading Chapter 23 6.0002 LECTURE 12 2 Mach Ma

Lecture 12: Clustering 1 6.0002 LECTURE 12 Re Reading Chapter 23 6.0002 LECTURE 12 2 Mach Ma chine e Lea earn rning Paradigm Observe set of examples: training data Infer something about process that generated that data Use

847 views • 36 slides
Lecture Outline Regeltechniek Previous lecture: Stability and transient response. Lecture 4

Lecture Outline Regeltechniek Previous lecture: Stability and transient response. Lecture 4

Lecture Outline Regeltechniek Previous lecture: Stability and transient response. Lecture 4 Basics of Feedback Control Robert Babu ska Today: Steady-state response. Delft Center for Systems and Control Faculty of Mechanical

388 views • 7 slides
Psycholinguistics Lecture 2 By Dr.Chelli Lecture Objectives At the end of this lecture, students

Psycholinguistics Lecture 2 By Dr.Chelli Lecture Objectives At the end of this lecture, students

Psycholinguistics Lecture 2 By Dr.Chelli Lecture Objectives At the end of this lecture, students will be able to: Discuss the different stages in the history of psycholinguistics Identify the scholars in the field of psycholinguistics

589 views • 28 slides
Jesus Christ, the Son of God. Jesus Christ, the Son of God. SONG SHEETS GOODNESS OF GOD Verse

Jesus Christ, the Son of God. Jesus Christ, the Son of God. SONG SHEETS GOODNESS OF GOD Verse

Jesus Christ, the Son of God. Jesus Christ, the Son of God. SONG SHEETS GOODNESS OF GOD Verse 1 I love You, Lord Oh, Your mercy never fails me All my days, Ive been held in Your hands From the moment that I wake up

189 views • 6 slides
Long Term Operating Experience at MiniBooNE Ray Stefanski Fermilab 7th International Workshop on

Long Term Operating Experience at MiniBooNE Ray Stefanski Fermilab 7th International Workshop on

Long Term Operating Experience at MiniBooNE Ray Stefanski Fermilab 7th International Workshop on Neutrino Beams and Instrumentation August 29, 2010 Schematic Geography Beryllium target detector 12 4 10 ppp @ 15Hz 7 slugs each 800

375 views • 21 slides
Mountain and Valley What is the same in the these 2 stories? What is different? Comparing the

Mountain and Valley What is the same in the these 2 stories? What is different? Comparing the

Mountain and Valley What is the same in the these 2 stories? What is different? Comparing the two... l People l Scenery / Landscape The Landscape... Good News Jesus is in Both! The People... Jesus and 3 disciples The good news is that

214 views • 8 slides
In the end we shall make thoughtcrime literally impossible, because there will be no words in

In the end we shall make thoughtcrime literally impossible, because there will be no words in

Don't you see that the whole aim of Newspeak is to narrow the range of thought? In the end we shall make thoughtcrime literally impossible, because there will be no words in which to express it. Thought control (cont'd) Every concept that can

445 views • 18 slides
HOPWA/COVID-19: Planning &amp; Operating STRMU Programs With HOPWA and CARES Act Funding August

HOPWA/COVID-19: Planning &amp; Operating STRMU Programs With HOPWA and CARES Act Funding August

HOPWA/COVID-19: Planning &amp; Operating STRMU Programs With HOPWA and CARES Act Funding August 19, 2020 Presenters Kate Briddell, HIV Housing and Health Program, Collaborative Solutions Crystal Pope, HIV Housing and Health Program,

587 views • 48 slides
AARNET Mirror and CDN update Stephen Walsh Network Operations AARNet Net Copyri right 2012

AARNET Mirror and CDN update Stephen Walsh Network Operations AARNet Net Copyri right 2012

AARNet Net Copyri right 2012 15 th TF-Storage NDN2014 Uppsala AARNET Mirror and CDN update Stephen Walsh Network Operations AARNet Net Copyri right 2012 But First AARNet Net Copyri right 2012 Our National Connectivity 3 AARNet Net

368 views • 16 slides
Matthew Series Lesson #088 August 9, 2015 Dean Bible Ministries www.deanbibleministries.org

Matthew Series Lesson #088 August 9, 2015 Dean Bible Ministries www.deanbibleministries.org

Matthew Series Lesson #088 August 9, 2015 Dean Bible Ministries www.deanbibleministries.org Dr. Robert L. Dean, Jr. Grace to the Unloved, Unlovely, Marginalized, and Outcasts Matthew 15:2128 John 3:16, For God so loved the world that

770 views • 36 slides
8th Grade Energy of Objects in Motion Classwork-Homework 2015-08-25 www.njctl.org Slide 3 /

8th Grade Energy of Objects in Motion Classwork-Homework 2015-08-25 www.njctl.org Slide 3 /

Slide 1 / 113 Slide 2 / 113 8th Grade Energy of Objects in Motion Classwork-Homework 2015-08-25 www.njctl.org Slide 3 / 113 Classwork #1: Energy Slide 4 / 113 1 Define Energy. Slide 5 / 113 2 What two things are necessary for work to be

488 views • 38 slides

More recommend