1 / 22

Python Crash Course File I/O

Python Crash Course File I/O. 3 rd year Bachelors V1.0 dd 04-09-2013 Hour 1. File I/O. Types of input/output available Interactive Keyboard Screen Files Ascii/text txt csv Binary Structured FITS > pyFITS, astropy.io.fits URL Pipes. Interactive I/O, fancy output.

tanek
Download Presentation

Python Crash Course File I/O

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Python Crash CourseFile I/O 3rd year Bachelors V1.0 dd 04-09-2013 Hour 1

  2. File I/O • Types of input/output available • Interactive • Keyboard • Screen • Files • Ascii/text • txt • csv • Binary • Structured • FITS > pyFITS, astropy.io.fits • URL • Pipes

  3. Interactive I/O, fancy output >>> s = 'Hello, world.' >>> str(s) 'Hello, world.' >>> repr(s) "'Hello, world.'" >>> str(1.0/7.0) '0.142857142857' >>> repr(1.0/7.0) '0.14285714285714285' >>> x = 10 * 3.25 >>> y = 200 * 200 >>> s = 'The value of x is ' + repr(x) + ', and y is ' + repr(y) + '...' >>> print s The value of x is 32.5, and y is 40000... >>> # The repr() of a string adds string quotes and backslashes: ... hello = 'hello, world\n' >>> hellos = repr(hello) >>> print hellos 'hello, world\n' >>> # The argument to repr() may be any Python object: ... repr((x, y, ('spam', 'eggs'))) "(32.5, 40000, ('spam', 'eggs'))"

  4. Interactive I/O, fancy output Old string formatting >>> import math >>> print 'The value of PI is approximately %5.3f.' % math.pi The value of PI is approximately 3.142. New string formatting >>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 7678} >>> for name, phone in table.items(): ... print '{0:10} ==> {1:10d}'.format(name, phone) ... Jack ==> 4098 Dcab ==> 7678 Sjoerd ==> 4127

  5. Formatting I/O A conversion specifier contains two or more characters and has the following components, which must occur in this order: • The "%" character, which marks the start of the specifier. • Mapping key (optional), consisting of a parenthesised sequence of characters (for example, (somename)). • Conversion flags (optional), which affect the result of some conversion types. • Minimum field width (optional). If specified as an "*" (asterisk), the actual width is read from the next element of the tuple in values, and the object to convert comes after the minimum field width and optional precision. • Precision (optional), given as a "." (dot) followed by the precision. If specified as "*" (an asterisk), the actual width is read from the next element of the tuple in values, and the value to convert comes after the precision. • Length modifier (optional). • Conversion type. >>> print '%(language)s has %(#)03d quote types.' % \ {'language': "Python", "#": 2} Python has 002 quote types.

  6. The conversion types are:

  7. Interactive I/O >>> print “Python is great,”, ”isn’t it?” >>> str = raw_input( “Enter your input: ”) >>> print “Received input is: “,str Enter your input: Hello Python Received input is: Hello Python >>> str = input("Enter your input: "); >>> print "Received input is: ", str Enter your input: [x*5 for x in range(2,10,2)] Received input is: [10, 20, 30, 40] If the readline modules was loaded the raw_input() will use it to provide elaborate line editing and history features.

  8. File I/O >>> fname = ‘myfile.dat’ >>> f = file(fname) >>> lines = f.readlines() >>> f.close() >>> f = file(fname) >>> firstline = f.readline() >>> secondline = f.readline() >>> f = file(fname) >>> for l in f: ... print l.split()[1] >>> f.close() >>> outfname = ‘myoutput’ >>> outf = file(outfname, ‘w’) # second argument denotes writable >>> outf.write(‘My very own file\n’) >>> outf.close()

  9. Read File I/O >>> f = open("test.txt") >>> # Read everything into single string: >>> content = f.read() >>> len(content) >>> print content >>> f.read() # At End Of File >>> f.close() >>> # f.read(20) reads (at most) 20 bytes Using with block: >>> with open(’test.txt’, ’r’) as f: ... content = f.read() >>> f.closed CSV file: >>> import csv >>> ifile = open(’photoz.csv’, "r") >>> reader = csv.reader(ifile) >>> for row in reader: ... print row, >>> ifile.close()

  10. Read and write text file >>> from numpy import * >>> data = loadtxt("myfile.txt") # myfile.txt contains 4 columns of numbers >>> t,z = data[:,0], data[:,3] # data is a 2D numpy array, t is 1st col, z is 4th col >>> t,x,y,z = loadtxt("myfile.txt", unpack=True) # to automatically unpack all columns >>> t,z = loadtxt("myfile.txt", usecols = (0,3), unpack=True) # to select just a few columns >>> data = loadtxt("myfile.txt", skiprows = 7) # to skip 7 rows from top of file >>> data = loadtxt("myfile.txt", comments = '!') # use '!' as comment char instead of '#' >>> data = loadtxt("myfile.txt", delimiter=';') # use ';' as column separator instead of whitespace >>> data = loadtxt("myfile.txt", dtype = int) # file contains integers instead of floats >>> from numpy import * >>> savetxt("myfile.txt", data) # data is 2D array >>> savetxt("myfile.txt", x) # if x is 1D array then get 1 column in file. >>> savetxt("myfile.txt", (x,y)) # x,y are 1D arrays. 2 rows in file. >>> savetxt("myfile.txt", transpose((x,y))) # x,y are 1D arrays. 2 columns in file. >>> savetxt("myfile.txt", transpose((x,y)), fmt='%6.3f') # use new format instead of '%.18e' >>> savetxt("myfile.txt", data, delimiter = ';') # use ';' to separate columns instead of space

  11. String formatting for output >>> sigma = 6.76/2.354 >>> print(‘sigma is %5.3f metres’%sigma) sigma is 2.872 metres >>> d = {‘bob’: 1.87, ‘fred’: 1.768} >>> for name, height in d.items(): ... print(‘%s is %.2f metres tall’%(name.capitalize(), height)) ... Bob is 1.87 metres tall Fred is 1.77 metres tall >>> nsweets = range(100) >>> calories = [i * 2.345 for i in nsweets] >>> fout = file(‘sweetinfo.txt’, ‘w’) >>> for i in range(nsweets): ... fout.write(‘%5i %8.3f\n’%(nsweets[i], calories[i])) ... >>> fout.close()

  12. File I/O, CSV files • CSV (Comma Separated Values) format is the most common import and export format for spreadsheets and databases. • Functions • csv.reader • csv.writer • csv.register_dialect • csv.unregister_dialect • csv.get_dialect • csv.list_dialects • csv.field_size_limit

  13. File I/O, CSV files • Reading CSV files • Writing CSV files import csv # imports the csv module f = open('data1.csv', 'rb') # opens the csv file try: reader = csv.reader(f) # creates the reader object for row in reader: # iterates the rows of the file in orders print row # prints each row finally: f.close() # closing import csv ifile = open('test.csv', "rb") reader = csv.reader(ifile) ofile = open('ttest.csv', "wb") writer = csv.writer(ofile, delimiter='\t', quotechar='"', quoting=csv.QUOTE_ALL) for row in reader: writer.writerow(row) ifile.close() ofile.close()

  14. File I/O, CSV files • The csv module contains a the following quoting options. • csv.QUOTE_ALL Quote everything, regardless of type. • csv.QUOTE_MINIMAL Quote fields with special characters • csv.QUOTE_NONNUMERIC Quote all fields that are not integers or floats • csv.QUOTE_NONE Do not quote anything on output

  15. File I/O, Pickle • Pickle: powerful algorithm for serializing and de-serializing a Python object structure • can transform a complex object into a byte stream • can transform the byte stream into an object with the same internal structure • most obvious thing to do with these byte streams is to write them onto a file • also conceivable to send them across a network or store them in a database • The following types can be pickled: • None, True, and False • integers, long integers, floating point numbers, complex numbers • normal and Unicode strings • tuples, lists, sets, and dictionaries containing only picklable objects • functions defined at the top level of a module • built-in functions defined at the top level of a module • classes that are defined at the top level of a module • instances of such classes whose __dict__ or the result of calling __getstate__() is picklable (see section The pickle protocol for details).

  16. File I/O, Pickle • Example save import pickle data1 = {'a': [1, 2.0, 3, 4+6j], 'b': ('string', u'Unicode string'), 'c': None} selfref_list = [1, 2, 3] selfref_list.append(selfref_list) output = open('data.pkl', 'wb') # Pickle dictionary using protocol 0. pickle.dump(data1, output) # Pickle the list using the highest protocol available. pickle.dump(selfref_list, output, -1) output.close()

  17. File I/O, Pickle (dp0 S'a' p1 (lp2 I1 aF2.0 aI3 ac__builtin__ complex p3 (F4.0 F6.0 tp4 Rp5 asS'c' p6 NsS'b' p7 (S'string' p8 VUnicode string p9 tp10 s.�]q • Example load import pprint, pickle pkl_file = open('data.pkl', 'rb') data1 = pickle.load(pkl_file) pprint.pprint(data1) data2 = pickle.load(pkl_file) pprint.pprint(data2) pkl_file.close()

  18. File I/O, Pickle • Real live example AstroWise cluster job submission • client – server model • exchanging code & data for remote processing def dpu_packit(*args): return pickle.dumps(args) def dpu_unpackit(data): return pickle.loads(data) # Sender side: def submitremotejobs(self, key, zip=None, jobs=[], env=None): if not len(jobs): return False return self.senddata(key, dpu_packit((zip, env), jobs)) # Receiver side: data = self.get_data() ((code, env), jobdictlist) = dpu_unpackit(data) make_code_file(key, code)

  19. URL • URLS can be used for reading >>> import urllib2 >>> url = 'http://python4astronomers.github.com/_downloads/data.txt' >>> response = urllib2.urlopen(url) >>> data = response.read() >>> print data RAJ DEJ Jmag e_Jmag 2000 (deg) 2000 (deg) 2MASS (mag) (mag) ---------- ---------- ----------------- ------ ------ 010.684737 +41.269035 00424433+4116085 9.453 0.052 010.683469 +41.268585 00424403+4116069 9.321 0.022 010.685657 +41.269550 00424455+4116103 10.773 0.069 010.686026 +41.269226 00424464+4116092 9.299 0.063 010.683465 +41.269676 00424403+4116108 11.507 0.056 010.686015 +41.269630 00424464+4116106 9.399 0.045 010.685270 +41.267124 00424446+4116016 12.070 0.035

  20. URL • URLS sometimes need input data. Such as POST data for a form import urllib import urllib2 url = 'http://www.someserver.com/cgi-bin/register.cgi' values = {'name' : 'Michael Foord', 'location' : 'Northampton', 'language' : 'Python' } data = urllib.urlencode(values) req = urllib2.Request(url, data) response = urllib2.urlopen(req) the_page = response.read()

  21. URL • And for GET type of parameter passing: import urllib import urllib2>>> import urllib2 >>> import urllib >>> data = {} >>> data['name'] = 'Somebody Here' >>> data['location'] = 'Northampton' >>> data['language'] = 'Python' >>> url_values = urllib.urlencode(data) >>> print url_values # The order may differ. name=Somebody+Here&language=Python&location=Northampton >>> url = 'http://www.example.com/example.cgi' >>> full_url = url + '?' + url_values >>> handler = urllib2.urlopen(full_url) Note that the full URL is created by adding a ? to the URL, followed by the encoded values.

  22. End Introduction to language

More Related