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Speaking 'Development Language' (Or, how to get your hands dirty with technical stuff.)

  1. Speaking “Development Language” Or, how to get your hands dirty with technical stuff. GWU Libraries ● 12 June 2012 Julie Meloni // @jcmeloni // jcmeloni@gmail.com
  2. Today’s Goal • To increase the number of people who can “work” on technical issues in the library • Technical “work” in the future come from the needs of the present: your needs. ▫ When you can articulate them to someone who can do the codework, we all win. ▫ If YOU can do the codework, you win even more.
  3. Today’s General Outline • Development Lifecycle & Where You Fit In • Computer Programming Basics • Python in Particular • Where to Learn More
  4. and Where You Fit In…
  5. General Software Development Lifecycle • Define ▫ What you want to do • Design ▫ How you want to do it • Implement ▫ Actually do it • Test ▫ Did what you do actually work • Deploy ▫ Send it off into the wild • Maintain ▫ Don‟t forget about it!
  6. Design Phase Needs Domain Knowledge • Functional requirements define the functionality of the system, in terms of inputs, behaviors, outputs. ▫ What is the system supposed to accomplish? • Functional requirements come from stakeholders (users), not (necessarily) developers. ▫ stakeholder request -> feature -> use case -> business rule
  7. Example Functional Requirement • Example functionality: representation and manipulation of hierarchy • Description: The GUI should allow users to view and interact with hierarchical structures representing the intellectual arrangement and the original arrangement of files and directories within ingested accessions. For each component level in the intellectual arrangement, the user interface should present associated digital assets and an interface to view and edit descriptive metadata elements. • Specific Components: collapse and expand record nodes for viewing (applies to both the original ingest and the intellectual arrangement), add new child record, add new sibling record, copy all or part of the existing structure to the intellectual arrangement, delete a record in intellectual arrangement.
  8. • An epic is a long story that can be broken into smaller stories. • It is a narrative; it describes interactions between people and a system ▫ WHO the actors are ▫ WHAT the actors are trying to accomplish ▫ The OUTPUT at the end • Narrative should: ▫ Be chronological ▫ Be complete (the who, what, AND the why) ▫ NOT reference specific software or other tools ▫ NOT describe a user interface Writing Use Cases (or Epics)
  9. • Stories are the pieces of an epic that begin to get to the heart of the matter. • Still written in non-technical language, but move toward a technical structure. • Given/When/Then scenarios ▫ GIVEN the system is in a known state WHEN an action is performed THEN these outcomes should exist ▫ EXAMPLE:  GIVEN one thing  AND an other thing  AND yet an other thing  WHEN I open my eyes  THEN I see something  But I don't see something else Writing User Stories
  10. • Scenario: User attempting to add an object ▫ GIVEN I am logged in  AND I have selected the “add” form  AND I am attempting to upload a file ▫ WHEN I invoke the file upload button ▫ THEN validate file type on client side  AND return alert message if not valid  AND continue if is valid ▫ THEN validate file type on server side  AND return alert message if not valid  AND finish process if is valid Actual Story Example
  11. Now You Do One! • Think of a problem you want to solve (a batch process, something displayed in the OPAC, etc) • Think of the use case: ▫ WHO is doing WHAT to achieve OUTPUT • Break it down into a story: ▫ GIVEN something WHEN something happens THEN do something else
  12. That Was the Define Phase… • From a set of stories, developers begin to DESIGN a way to bring the stories to life. • At some point, programming begins and the stories are IMPLEMENTED in code. • During the coding process, TESTS are written and code is TESTED. • When the tests pass, the code is DEPLOYED. • As time goes on, the code is MAINTAINED.
  13. Why Program? • Express complex logic and perform computations. ▫ We make the computer do what we want it to do. ▫ These behaviors come from our imaginations. ▫ The processes come from our needs and desires. • Do things that take a long time or are difficult for humans to do (counting, comparing, repeating)
  14. What is a “Programming Language”? • An artificial language with a limited purpose • A means of expressing computations (math) and algorithms (logic)
  15. What Does a Programming Language Look Like? • ...a lot like human language, as it has: ▫ Syntax (form) ▫ Semantics (meaning)  signs/words (variables, symbols, numbers, strings)  expressions  flow control (decisions, conditions, loops, narrative)  complex entities (methods, structures, & objects)
  16. A Few Basic Programming Components • Variables & Arrays • Operators • Flow Control • Functions Putting together these pieces adds up to programming (or scripting, or in general “writing some stuff to tell the computer what to do”)
  17. Variables & Arrays • A variable is a bucket that holds one piece of information. • Examples: ▫ $string_variable = “The Library”; ▫ $numeric_variable= 4; ▫ $myname = “Julie”;
  18. Variables & Arrays • An array is a type of variable (or bucket) that holds many pieces of information. • Example: ▫ $rainbow = array(“red”, “orange”, “yellow”, “green”, “blue”, “indigo”, “violet”)  $rainbow[0] holds “red”  $rainbow[1] holds “orange”
  19. Operators • Arithmetic ▫ +, -, *, / (add, subtract, multiply, divide) • Assignment ▫ = (“Assign the value of 4 to the variable called a”)  $a = 4; ▫ += (“Add the value of 5 to the variable that already holds 4”)  $a += 5; // $a now holds 9 ▫ .= (“Attach the value „World‟ to the end of „Hello‟ to make a new value for the string variable”)  $string = “Hello”;  $string .= “World”; // would print “HelloWorld” (no space because we didn‟t add that!)
  20. Operators • Comparison ▫ == (“when I compare the value in variable a to the value in variable be, that comparison is true”)  $a == $b ▫ != (“when I compare the value in variable a to the value in variable be, that comparison is not true”)  $a != $b ▫ >, >= (“the value of variable a is greater than (or greater than or equal to) the value of variable b”)  $a > $b ▫ <, <= (“the value of variable a is less than (or less than or equal to) the value of variable b”)  $a < b
  21. Operators • Concatenation • + (string + string = stringstring) • Logical • && (and) • || (or) • ! (not)
  22. Flow Control • if if (something is true) { do something here } • if ... else ... else if if (something is true) { do something here } else if (something is true) { do something here } else { do something here }
  23. Flow Control • while while (something is true) { do something here } • for for (something is true) { do something here }
  24. Procedures and Functions • Scripts can contain linear, procedural code. • Scripts can also contain references to reusable bits of code, called functions. ▫ Built-in language functions ▫ Functions you write yourself.
  25. Why Python? • It is a general-purpose language • It has been around for a long time (20+ years) • It has a strong developer community • It includes a large built-in library of functionality • It is readable • It is expressive (you can do a lot with a little)
  26. Uncluttered Layout • Less punctuation ▫ While some languages use $ to indicate variables, or brackets around logical constructs, Python does not. • More whitespace ▫ Instead of brackets to set off blocks, indentation means something in Python.
  27. Variables in Python • Do not begin with a symbol and do not end with terminating punctuation. • Examples: ▫ string_variable = “The Library” ▫ numeric_variable= 4 ▫ myname = “Julie”
  28. Set and Print Variables # set up the variables string_variable = "The Library"; numeric_variable = 4; myname = "Julie"; # print the variables print string_variable print numeric_variable print myname
  29. Arrays in Python • …are called lists. • Example: ▫ rainbow = [“red”, “orange”, “yellow”, “green”, “blue”, “indigo”, “violet”]  print rainbow[0] shows “red”  print rainbow[1] shows “orange”
  30. Operators in Python (are not terribly special) • Arithmetic ▫ +, -, *, / • Assignment ▫ = ▫ +=, -=, *=, /= • Comparison ▫ >, <, >=, <= • Logical ▫ and, or, not
  31. Flow Control in Python • if if something is true: INDENT and do something here # here’s an example people = 20 space_aliens = 30 if people < space_aliens: print "Oh no! The world is doomed" if people > space_aliens: print "We're cool."
  32. Flow Control • if ... elif ... else if something is true: INDENT and do something here elif something is true: INDENT and do something here else: INDENT and do something here
  33. Flow Control • EXAMPLE people = 30 cars = 40 if cars > people: print "We should take the cars." elif cars < people: print "We should not take the cars." else: print "We can't decide."
  34. Flow Control • while while something is true: INDENT and do something here # here’s an example count = 0 while (count < 9): print 'The count is:', count count = count + 1 print "...and we're done!"
  35. Flow Control The count is: 0 The count is: 1 The count is: 2 The count is: 3 The count is: 4 The count is: 5 The count is: 6 The count is: 7 The count is: 8 ...and we're done!
  36. Flow Control • for for there are things in a sequence: INDENT and do something here #here’s an example rainbow = ["red", "orange", "yellow", "green", "blue", "indigo", "violet"] for color in rainbow: print color
  37. Flow Control red orange yellow green blue indigo violet
  38. Functions in Python • Start with the keyword def • Accepts parameters • There‟s indentation • You get something in return
  39. Functions in Python def fibonacci(n): a, b = 0, 1 while a < n: print a, a, b = b, a+b fibonacci(1000) ///////////////////////////////////////////////// 0 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987
  40. So How Does Your Group Use Python? • As batch scripts, with or without a web interface ▫ One-offs, utilities, etc • Using a Web Framework (Django) ▫ Frameworks allow you to write web applications quickly because they include, well, a framework for doing so.  Reusable libraries common to web applications  Coding standards  Template and templating processes
  41. Sample Utility (pymarc) • For manipulation of MARC records ▫ In GitHub at https://github.com/edsu/pymarc/ ▫ From command-line or wrapped within an app • Example 1: from pymarc import MARCReader reader = MARCReader(open('marc.txt')) for record in reader: print record['245']['a']
  42. Sample Utility (pymarc) • Example 2: from pymarc import Record, Field record = Record() record.addField( Field( tag = '245', indicators = ['0','1'], subfields = [ 'a', 'The pragmatic programmer : ', 'b', 'from journeyman to master /', 'c', 'Andrew Hunt, David Thomas.' ])) out = open('file.dat', 'w') out.write(record.asMARC21()) out.close()
  43. Launchpad • Works within a Django framework • Has a directory structure you can follow to find how things are pieced together • Even in a framework, it is still readable code
  44. Launchpad (example from a template) {% extends "base.html" %} {% load launchpad_extras %} {% block title %}{{ bib.TITLE }}{% endblock title %} … {% if bib.ISBN|clean_isbn %} ISBN: <a href='{% url isbn bib.ISBN|clean_isbn %}'>{% url isbn bib.ISBN|clean_isbn %}</a> {% endif %}
  45. Launchpad (example from a template) def clean_isbn(value): isbn,sep,remainder = value.strip().partition('') if len(isbn) < 10: return '' isbn = isbn.replace('-', '') isbn = isbn.replace(':', '') return isbn
  46. Additional Resources • Learn Python the Hard Way ▫ http://learnpythonthehardway.org/book/ • The Python Tutorial ▫ http://docs.python.org/tutorial/index.html • Django ▫ https://www.djangoproject.com/ • GWU Libraries GitHub repositories ▫ https://github.com/gwu-libraries/
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