CS 105 Lecture 9: Fun with Files Craig Zilles (Computer Science) https://go.illinois.edu/cs105fa19 October 25, 2019
Are you sitti ting next t to someone to talk to for th the clicker questi tions? To Today I'm using: a text editor and the command line Also, I'll post today's code 2
To Today 1. Files • Extensions, • Writing, flushing, closing 2. Comma-separated values (CSV) files • Reading, splitting, filter & find best patterns • csv library 3. More on Lists 4. List Comprehesions 3
Fi Files es • Files are how data is stored on external storage (disk) • Managed by O/S • Disk is slow • open ing files moves them to memory for the program • Data is buffered (temporarily stored) in memory 4
Vi Viewing ng the he filesystem • Mac Finder / Windows explorer • Command line: • Mac: ls ls -l • Windows: dir • Shows all of the files in the current directory • Can show file size • Looking at files (Mac): more one page at a time whole file at once cat 5
Write programs a few lines at t a ti time! Test t every couple lines to make sure th they do what t you want! t! 6
Wr Writing to files • file_object = open('filename', 'w') • file_object.write('thing to write') • file_object.close() automatic at program end optional • file_object.flush() Example program 1: Diary that records user input into a file. with open('filename', 'w') as outf: closes file when code block ends 7
Di Diar ary that records user input into a a file. 8
Co Continue e writing g to exi xisting g file? e? (i.e., new ew writes go to end of file) A) open('filename', 'r') B) open('filename', 'x') C) open('filename', 'i') D) open('filename', 'a') E) open('filename', 'e') 9
Com Comma-sepa separated ed value ue (CSV) files es • Commonly-used data file format • Can be generated from Excel and other spreadsheets Processing a CSV manually: • Each row is its own line of the file • Can use split(',') to separate the columns • Use indexing to read columns of interest Example program 2: Create a list of Illinois U.S. representatives 10
Cr Create a lis list t of of Illin llinois ois U.S .S. . representativ tives 11
Re Reading from files • file_object = open('filename') • lines = file_object.readlines() • for line in lines: 12
Sk Skipping first t line A) for line in lines[:1]: B) for line in lines[1:]: C) for line in lines[:2]: D) for line in lines[2]: E) for line in lines[2:]: 13
Fi Filter ering a a collec ection (p (patter ern) newlist = [] for thing in collection : if thing meets criteria : newlist .append( thing ) 14
Sor Sorti ting data • a_list.sort() • a_list.sort(key = a_function) • a_list.sort(reverse = True) 15
An Annou ounce cements ts • Exam 2 is ongoing • Please don't start early; listen to the proctors • Informal Early Feedback (IEF) • Have results of scantron • Still processing written responses • Will discuss next week 16
Fi Find da nd date o of hi f highe hest une unempl ploym yment r rate • Example 3 17
Pa Pattern: Finding best in a collection current_best = a value you know is worse than best for thing in collection : if thing is better than current_best : current_best = thing return / do something with current_best 18
Fi Finding info asso associated ed with bes est current_best = a value you know is worse than best best_info = None for thing in collection : if thing is better than current_best : current_best = thing best_info = info about thing return / do something with current_best , best_info 19
Com Command line arguments ts • Avoid hard coding things like file names import sys sys.argv is a list of arguments • First argument is the name of the Python script • Give 'Usage' message to help user use your program 20
Recommend
More recommend