# [NumPy-Tickets] [NumPy] #1565: loadtxt fails to load large unsigned int64 integers.

NumPy Trac numpy-tickets@scipy....
Wed Jul 28 17:02:28 CDT 2010

```#1565: loadtxt fails to load large unsigned int64 integers.
-------------------------+--------------------------------------------------
Reporter:  rainwoodman  |       Owner:  somebody
Type:  defect       |      Status:  new
Priority:  normal       |   Milestone:  1.5.0
Component:  Other        |     Version:  1.4.0
Keywords:               |
-------------------------+--------------------------------------------------
Prepare the following file:

-------file /tmp/test -----
9223372043271415339
9223372043271415853
9223372043271415612
9223372043271416107
9223372043271415594
9223372043271415836
9223372043761290139
9223372044088967272
9223372044088967273
9223372043925949039
---------end of file-----

And run the following code:

[9223372043271415808 9223372043271415808 9223372043271415808
9223372043271415808 9223372043271415808 9223372043271415808
9223372043761289216 9223372044088967168 9223372044088967168
9223372043925948416]

On the other hand, with fromfile(),

In [2]: print fromfile('/tmp/test', dtype='uint64', sep=' ')
------> print(fromfile('/tmp/test', dtype='uint64', sep=' '))
[9223372043271415339 9223372043271415853 9223372043271415612
9223372043271416107 9223372043271415594 9223372043271415836
9223372043761290139 9223372044088967272 9223372044088967273
9223372043925949039]

Clearly the first few numbers are wrongly converted by loadtxt

The problem was tracked to line 453 in numpy/lib/io.py, _getconv. The
conversion for np.integer is int(float(x)), which is inexact for large
integers.

I don't know if a priority of normal is appropriate, as this bug will
produce hidden errors in programs that use numpy.

--
Ticket URL: <http://projects.scipy.org/numpy/ticket/1565>
NumPy <http://projects.scipy.org/numpy>
My example project
```