Converting long numpy array for string efficiently

If you want to write a numpy array to a text file, use numpy.savetxt. Based on your comment, this is what you want.

However, in the interest of answering your original question, there are faster ways to convert a numpy array to strings, if you can live with fixed-length strings.

For simple things, you can convert it to a fixed-length string array.

E.g.

import numpy as np

# Generate some random floating-point data
x = np.random.random(100)

# Convert it to fixed-length strings with a maximum length of 5 characters
y = x.astype('|S5')

print 'Original Array'
print x
print 'Converted to fixed-length strings'
print y

This outputs:

Original Array
[ 0.25669986  0.55193955  0.39582629  0.40559555  0.75836284  0.13031881
  0.84448005  0.20825593  0.32131777  0.5738351   0.72200185  0.14700912
  0.62306299  0.21549908  0.96927738  0.13327512  0.06948689  0.34436446
  0.58785565  0.58557563  0.3229981   0.0356056   0.67621536  0.07334146
  0.25804432  0.59477881  0.10382583  0.47255438  0.0747982   0.41586059
  0.54310507  0.68426668  0.14454108  0.62950246  0.30748958  0.56605352
  0.25072476  0.70945076  0.72311872  0.2357644   0.59668047  0.27536644
  0.96557189  0.97749755  0.95629738  0.15902741  0.32879056  0.60324024
  0.07463531  0.77562818  0.20181969  0.53088481  0.85723283  0.25163771
  0.06770161  0.45302361  0.3500556   0.37980214  0.87567327  0.94278158
  0.28586752  0.35682239  0.8746877   0.99562283  0.38323688  0.90561641
  0.64439454  0.53465359  0.37486244  0.33196021  0.99762377  0.29295412
  0.50162051  0.17312773  0.80100872  0.04233855  0.69062118  0.59194923
  0.65409137  0.25636784  0.40616824  0.82858658  0.90618301  0.87036914
  0.37534268  0.566982    0.55454063  0.75048023  0.56582157  0.62779239
  0.05196828  0.86418784  0.9862007   0.43015164  0.43576519  0.64918536
  0.99522735  0.81158283  0.02115479  0.47745413]
Converted to fixed-length strings
['0.256' '0.551' '0.395' '0.405' '0.758' '0.130' '0.844' '0.208' '0.321'
 '0.573' '0.722' '0.147' '0.623' '0.215' '0.969' '0.133' '0.069' '0.344'
 '0.587' '0.585' '0.322' '0.035' '0.676' '0.073' '0.258' '0.594' '0.103'
 '0.472' '0.074' '0.415' '0.543' '0.684' '0.144' '0.629' '0.307' '0.566'
 '0.250' '0.709' '0.723' '0.235' '0.596' '0.275' '0.965' '0.977' '0.956'
 '0.159' '0.328' '0.603' '0.074' '0.775' '0.201' '0.530' '0.857' '0.251'
 '0.067' '0.453' '0.350' '0.379' '0.875' '0.942' '0.285' '0.356' '0.874'
 '0.995' '0.383' '0.905' '0.644' '0.534' '0.374' '0.331' '0.997' '0.292'
 '0.501' '0.173' '0.801' '0.042' '0.690' '0.591' '0.654' '0.256' '0.406'
 '0.828' '0.906' '0.870' '0.375' '0.566' '0.554' '0.750' '0.565' '0.627'
 '0.051' '0.864' '0.986' '0.430' '0.435' '0.649' '0.995' '0.811' '0.021'
 '0.477']

This will be much faster, but you're limited to fixed-length strings. (Obviously, you can change the length. Just use x.astype('|S10') or whatever length you'd like.)

Again, though, if you're just wanting to write the data to a file, use savetxt.