easy save/load of data in python

  • If it should be human-readable, I'd also go with JSON. Unless you need to exchange it with enterprise-type people, they like XML better. :-)

  • If it should be human editable and isn't too complex, I'd probably go with some sort of INI-like format, like for example configparser.

  • If it is complex, and doesn't need to be exchanged, I'd go with just pickling the data, unless it's very complex, in which case I'd use ZODB.

  • If it's a LOT of data, and needs to be exchanged, I'd use SQL.

That pretty much covers it, I think.


There are several options -- I don't exactly know what you like. If the two vectors have the same length, you could use numpy.savetxt() to save your vectors, say x and y, as columns:

# saving:
f = open("data", "w")
f.write("# x y\n")        # column names
numpy.savetxt(f, numpy.array([x, y]).T)
# loading:
x, y = numpy.loadtxt("data", unpack=True)

If you are dealing with larger vectors of floats, you should probably use NumPy anyway.


The most simple way to get a human-readable output is by using a serialisation format such a JSON. Python contains a json library you can use to serialise data to and from a string. Like pickle, you can use this with an IO object to write it to a file.

import json

file = open('/usr/data/application/json-dump.json', 'w+')
data = { "x": 12153535.232321, "y": 35234531.232322 }

json.dump(data, file)

If you want to get a simple string back instead of dumping it to a file, you can use json.dumps() instead:

import json
print json.dumps({ "x": 12153535.232321, "y": 35234531.232322 })

Reading back from a file is just as easy:

import json

file = open('/usr/data/application/json-dump.json', 'r')
print json.load(file)

The json library is full-featured, so I'd recommend checking out the documentation to see what sorts of things you can do with it.

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