PythonDataAccess: Difference between revisions
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Of course the disadvantage of pickling is that you need to unpickle it. This is not a generic format to save data and share with other people. | Of course the disadvantage of pickling is that you need to unpickle it. This is not a generic format to save data and share with other people. | ||
== FITS Access via CASA == | |||
== UV and Meta-data Access via CASA == | |||
== Other Approaches == | == Other Approaches == | ||
You don't need to waste a lot of effort duplicating previous work on reading and writing text files. Adam Ginsburg's "readcol.py" (loosely patterned after the IDL version, linked from the page) will save you a lot of effort. The package astroasciidata also looks promising but I have not yet gotten a chance to experiment with it. | You don't need to waste a lot of effort duplicating previous work on reading and writing text files. Adam Ginsburg's "readcol.py" (loosely patterned after the IDL version, linked from the page) will save you a lot of effort. The package astroasciidata also looks promising but I have not yet gotten a chance to experiment with it. |
Revision as of 23:02, 1 November 2011
Back to the PythonOverview.
Preface
We'll take a quick look at saving and loading files focusing on two approaches: reading and writing text files and saving variables via "pickling" (think IDL save/restore). Loosely related, we'll see how to accept input from the user.
Input
Input can be accepted from the command line (or a script paused) using the raw input command.
verb = raw_input("Give me a verb: ") noun = raw_input("Give me a noun: ")
mad_lib = "More fun than "+verb+"ing a "+noun print mad_lib
File Access
Python provides easy basic file access. Grab our example_file.txt for the following example.
Open a file like so:
a_file = open("example_file.txt", "r")
r - means read, w means write. You can do both at once if you want. Read up for more.
Now that it's open we can read the lines in the file into a list like so:
lines = a_file.readlines() print lines
We could have read a single line with readline() or only a fixed set of bytes with read()
Close the file
a_file.close()
We can also write using similar syntax (use an extra "a" to append):
a_new_file = open("new_file.txt", "w") a_new_file.writelines(lines) a_new_file.close()
import os os.system('cat new_file.txt')
note that you need to convert to strings before writing.
Pickling
It's possible to directly save and load variables from a file (without making them into strings and worrying about parsing).
import pickle
Make a dictionary
a_dict = {"field1":100,
50:[1,2,3,5], 3.14:"hello"}
Save the dictionary
f = open("pickle.jar","w") p = pickle.Pickler(f) p.dump(a_dict) f.close()
Go ahead and have a look at what it's doing.
import os os.system("cat pickle.jar")
ascii but not english.
Get the stuff back
f = open("pickle.jar","r") u = pickle.Unpickler(f) read_back = u.load() f.close()
print a_dict print read_back
There's also a more compact syntax to just load and dump directly from a file. Options allow binary instead of ascii writing. And there's a faster version called cPickle.
Pickle is stack-based by the way, so:
a = 1 b = 2 c = 3
Save the dictionary
f = open("another_pickle.jar","w") p = pickle.Pickler(f) p.dump(a) p.dump(b) p.dump(c) f.close()
Get the stuff back
f = open("another_pickle.jar","r") u = pickle.Unpickler(f) var1 = u.load() var2 = u.load() var3 = u.load()
... a variable too far:
var4 = u.load()
uhoh!
f.close()
print var1, var2, var3
Of course the disadvantage of pickling is that you need to unpickle it. This is not a generic format to save data and share with other people.
FITS Access via CASA
UV and Meta-data Access via CASA
Other Approaches
You don't need to waste a lot of effort duplicating previous work on reading and writing text files. Adam Ginsburg's "readcol.py" (loosely patterned after the IDL version, linked from the page) will save you a lot of effort. The package astroasciidata also looks promising but I have not yet gotten a chance to experiment with it.