Forwarding to the list. ~Josh.
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> From: pytables-users-boun...@lists.sourceforge.net
> Date: December 6, 2011 9:27:27 PM GMT+01:00
> To: pytables-users-ow...@lists.sourceforge.net
> Subject: Auto-discard notification
>
> The attached message has been automatically discarded.
> From: "Edward C. Jones" <edcjo...@comcast.net>
> Date: December 6, 2011 9:25:08 PM GMT+01:00
> To: pytables-users@lists.sourceforge.net
> Subject: Some experiences with PyTables
>
>
> My computer has an up-to-date Debian stable distribution installed. I have
> the following Debian packages (plus most dev packages):
> python 2.6.6-3+squeeze6
> python-numpy 1:1.4.1-5
> hdf5-tools 1.8.4-patch1-2
> libhdf5-serial-1.8.4 1.8.4-patch1-2
> I have compiled and installed PyTables 2.3.1.
>
> 1. There seems to be an unpythonic design choice with the start, stop, step
> convention for PyTables. Anything that is unnatural to a Python
> programmer should be heavily documented.
> 2. There may be a bug in itersorted.
>
> Here is code for (1) and (2):
> ----
> #! /usr/bin/env python
>
> import random, tables
>
> h5file = tables.openFile('mytable.h5', mode='w')
>
> class silly_class(tables.IsDescription):
> num = tables.Int32Col(pos=0)
>
> mytable = h5file.createTable(h5file.root, 'mytable', silly_class,
> 'a few ints', expectedrows=4)
>
> row = mytable.row
> for i in range(10):
> row['num'] = random.randint(0, 99)
> row.append()
> mytable.flush()
> mytable.cols.num.createCSIndex()
>
> # Python's idiom for start, stop, step:
> print 'Python:', range(9, -1, -1)
>
> output = mytable.readSorted('num', start=0, stop=10, step=-1)
> print 'readSorted:', 0, 10, -1, output
>
> # copy supports a negative step. It seems that start and stop are applied
> # _after_ the sort is done. Very unlike Python. Please document thoroughly.
> print h5file.root.mytable[:]
> h5file.root.mytable.copy(h5file.root, 'mytable2', sortby='num',
> start=0, stop=5, step=-1)
> print h5file.root.mytable2[:]
>
> # The following raises an OverflowError. The documentation (2.3.1) says
> # negative steps are supported for itersorted. Documentation error or bug
> # in itersorted?
> output = [x['num'] for x in mytable.itersorted('num',
> start=0, stop=10, step=-1)]
> print 'itersorted:', 0, 10, -1, output
> ----
> 3. Null bytes are stripped from the end of strings when they are stored in a
> table. Since a Python does not expect this, it needs to be explicitly
> documented in all the relevant places. Here is some code:
> ----
> #! /usr/bin/env python
>
> import tables
>
> def hash2hex(stringin):
> out = list()
> for c in stringin:
> s = hex(ord(c))[2:]
> if len(s) == 1:
> s = '0' + s
> out.append(s)
> return ''.join(out)
>
> h5file = tables.openFile('mytable.h5', mode='w')
>
> class silly_class(tables.IsDescription):
> astring = tables.StringCol(16, pos=0)
>
> mytable = h5file.createTable(h5file.root, 'mytable', silly_class,
> 'a few strings', expectedrows=4)
>
> # Problem when string ends with null bytes:
> nasty = 'abdcef' + '\x00\x00'
> print repr(nasty)
> print hash2hex(nasty)
>
> row = mytable.row
> row['astring'] = nasty
> row.append()
> mytable.flush()
> print repr(mytable[0][0])
> print hash2hex(mytable[0][0])
> h5file.close()
> ----
> 4. Has the 64K limit for attributes been lifted?
>
> 5. The reference manual for numpy contains _many_ small examples. They
> partially compensate for any lack of precision or excessive precision in
> the documents. Also many people learn best from examples.
>
> 6. Suppose that the records (key, data1) and (key, data2) are two rows in a
> table with (key, data1) being a earlier row than (key, data2). Both
> records have the same value in the first column. If a CSIndex is created
> using the first column, will (key, data1) still be before (key, data2) in
> the index? This property is called "stability". Some sorting algorithms
> guarantee this and others don't. Are the sorts in PyTables stable?
>
> 7. The table.append in PyTables behaves like extend in Python. Why?
>
> 8. I get a mysterious PerformanceWarning from the PyTables file "table.py",
> line 2742. This message needs to be split into two messages. In my case,
> after I appended to a table, "'row' in self.__dict__" was True and
> "self.row._getUnsavedNrows()" was 1. To resolve the problem, I added a
> line that flushes the table after every append. Does
> h5file.mytable.flush() do something that h5file.flush() doesn't? Do I
> need to flush every table after every append or are there only certain
> situations when this is needed? What does "preempted from alive nodes"
> mean?
>
> 9. Does the following code contain a bug in PyTables?
> ----
> #! /usr/bin/env python
>
> import sys
> import numpy, tables
>
> # No failure if projections and winsize are small enough. In the original
> # program, gauss.shape is (2000, 196, 196).
> projections = 105
> winsize = 2500
> h5 = tables.openFile('mess.h5', mode='w')
> shape = (projections, winsize)
>
> # If "complib='blosc'" and "fletcher32=True" failure occurs. Other
> # combinations work.
> filters = tables.Filters(complevel=1, complib='blosc', fletcher32=True)
> h5.createCArray(h5.root, 'gauss', tables.Float64Atom(),
> shape, title='gauss', filters=filters)
> print 'chunkshape:', h5.root.gauss.chunkshape # (3, 2500)
> sys.stdout.flush()
> #h5.root.gauss.flush() # Flushes make no difference.
>
> zeros = numpy.zeros( (winsize,), numpy.float64)
> for i in range(projections):
> h5.root.gauss[i, :] = zeros
> #h5.root.gauss.flush()
>
> xx = h5.root.gauss[0, :]
> print 'xx.shape:', xx.shape, 'gauss.shape', h5.root.gauss.shape
> ----
>
>
>
>
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