An uncompressed (bzip2) version of a .pys test file for pyspread. Corresponds to https://github.com/manns/pyspread/issues/43 I downloaded this data set http://archive.ics.uci.edu/ml/machine-learning-databases/00229/Skin_NonSkin.txt and imported it into one cell, then squared it in a different cell, then finally, wrote the output to another file …

test2.pys.out

[Pyspread save file version]
0.1
[shape]
1000	100	3
[grid]
7	5	0	abc_to_the_abc
13	11	0	abc_to_the_abc
11	2	0	two = skindata[245000]
9	2	0	skindata[1]
10	3	0	one * two
19	5	0	abc
9	8	0	abc_to_the_abc
5	5	0	abc_to_the_abc
18	2	0	"save code here -->"
10	5	0	abc_to_the_abc
999	5	0	abc_to_the_abc
18	3	0	save = numpy.savetxt("/home/matt/Documents/analytics/pyspread/skin_data_squared_sdsq.txt", sdsq, delimiter=",", newline="\n")
4	0	0	skindata = numpy.genfromtxt("/home/matt/Documents/analytics/pyspread/Skin_NonSkin.txt", dtype=None, delimiter="\t")
8	0	0	skindata = numpy.genfromtxt("/home/matt/Documents/analytics/pyspread/Skin_NonSkin.txt", dtype=None, delimiter="\t")
14	5	0	abc_to_the_abc
17	5	0	abc_to_the_abc
4	5	0	abc_to_the_abc
965	1	0	'IN'
11	5	0	abc_to_the_abc
14	3	0	sdsq = skindata * skindata
16	5	0	abc_to_the_abc
2	5	0	abc_to_the_abc
7	7	0	abc_to_the_abc
8	1	0	"<-- import code here"
0	0	0	abc = "12"
6	5	0	abc_to_the_abc
9	5	0	abc_to_the_abc
4	6	0	abc_to_the_abc = int(abc)**int(abc)
15	5	0	abc_to_the_abc
3	5	0	abc_to_the_abc
14	0	0	scaleskin(skindata, 2)
18	10	0	abc_to_the_abc
282	1	0	'TX'
8	5	0	abc_to_the_abc
13	5	0	abc_to_the_abc
5	6	0	abc_to_the_abc
4	2	0	abc
384	1	0	'NJ'
13	3	0	sdsq = skindata * skindata
[attributes]
[]	[]	[]	[]	[(4, 2)]	0	'frozen'	True
[]	[]	[]	[]	[(4, 2)]	0	'frozen'	False
[]	[]	[]	[]	[(8, 0)]	0	'frozen'	True
[]	[]	[]	[]	[(12, 3)]	0	'frozen'	True
[]	[]	[]	[]	[(14, 0)]	0	'frozen'	True
[]	[]	[]	[]	[(12, 3)]	0	'frozen'	False
[]	[]	[]	[]	[(12, 3)]	0	'frozen'	True
[]	[]	[]	[]	[(8, 0)]	0	'frozen'	False
[]	[]	[]	[]	[(8, 0)]	0	'frozen'	True
[]	[]	[]	[]	[(18, 3)]	0	'frozen'	True
[(18, 2)]	[(18, 3)]	[]	[]	[]	0	'fontweight'	92
[]	[]	[]	[]	[(18, 3)]	0	'bgcolor'	15066597
[]	[]	[]	[]	[(18, 3)]	0	'frozen'	False
[]	[]	[]	[]	[(18, 3)]	0	'frozen'	True
[]	[]	[]	[]	[(13, 3)]	0	'frozen'	True
[]	[]	[]	[]	[(1, 3)]	0	'frozen'	True
[]	[]	[]	[]	[(2, 0)]	0	'frozen'	True
[]	[]	[]	[]	[(0, 0)]	0	'frozen'	True
[]	[]	[]	[]	[(0, 0)]	0	'frozen'	False
[]	[]	[]	[]	[(8, 0)]	0	'textcolor'	15066597
[]	[]	[]	[]	[(8, 0)]	0	'textcolor'	0
[]	[]	[]	[]	[(8, 0)]	0	'bgcolor'	15066597
[]	[]	[]	[]	[(10, 3)]	0	'frozen'	True
[]	[]	[]	[]	[(9, 2)]	0	'frozen'	True
[]	[]	[]	[]	[(8, 0)]	0	'bgcolor'	16777215
[]	[]	[]	[]	[(4, 0)]	0	'frozen'	True
[]	[]	[]	[]	[(18, 3)]	0	'frozen'	False
[row_heights]
18	0	25.0
0	0	56.0
7	0	25.0
21	0	25.0
12	0	25.0
17	0	25.0
8	0	25.0
11	0	25.0
2	0	25.0
16	0	25.0
14	0	25.0
5	0	25.0
19	0	25.0
10	0	25.0
1	0	25.0
22	0	25.0
13	0	25.0
4	0	25.0
[col_widths]
0	0	106.0
3	0	174.0
6	0	54.0
2	0	138.0
5	0	60.0
1	0	161.0
4	0	51.0