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The new import `absolute_import` is added the `from __future__ import`
statement and The 2to3 `import` fixer is run to make the imports
compatible. There are several things that need to be dealt with to make
this work.
1) Files meant to be run as scripts run in a different environment than
files imported as part of a package, and so changes to those files need
to be skipped. The affected script files are:
* all setup.py files
* numpy/core/code_generators/generate_umath.py
* numpy/core/code_generators/generate_numpy_api.py
* numpy/core/code_generators/generate_ufunc_api.py
2) Some imported modules are not available as they are created during
the build process and consequently 2to3 is unable to handle them
correctly. Files that import those modules need a bit of extra work.
The affected files are:
* core/__init__.py,
* core/numeric.py,
* core/_internal.py,
* core/arrayprint.py,
* core/fromnumeric.py,
* numpy/__init__.py,
* lib/npyio.py,
* lib/function_base.py,
* fft/fftpack.py,
* random/__init__.py
Closes #3172
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This should be harmless, as we already are division clean. However,
placement of this import takes some care. In the future a script
can be used to append new features without worry, at least until
such time as it exceeds a single line. Having that ability will
make it easier to deal with absolute imports and printing updates.
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genfromtxt.
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bug #1665
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Stefan vdW for the fix.
* added a unittest for flatten_dtype
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* Force a file to be opened in 'U' mode (bug #1473)
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genfromtxt
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columns to be dropped
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- prevents a `default` of 0 to be overwritten during initialization
- allows the `missing_values` to be a comma-separated string
* io.genfromtxt
- `usecols` can now be a single integer
- for `usecols` and `names` to list (for compatibility w/ Python 2.5)
- negative values in `usecols` are properly transformed to positive integers
- fixed `usecols` with named columns
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- prevents an explicit default to be overwritten during upgrade
* io.genfromtxt
- deprecate `skiprows` for `skip_header`
- deprecate `missing` for `missing_values`
- `missing_values` can now be a sequence
- add support for `filling_values`
* fixed ticket #1257
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#1253)
* lib._iotools:
- NameValidator : add the `nbfields` optional argument to validate
- add easy_dtype
* lib.io.genfromtxt :
- add the `autostrip` optional argument (ticket #1238)
- use `invalid_raise=True` as default
- use the easy_dtype mechanism (ticket #1252)
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- use '1' instead of '0' to test the update
- add `iterupgrade` to upgrade from an iterator
* io.genfromtxt (bug #1212)
- use `iterupgrade` to upgrade the converters, and reprocess if there's a problem to catch the offending line
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columns (bug #1212)
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* add the flatten_base keyword to flatten_dtype
lib.io.genfromtxt
* Use flatten_dtype(...,flatten_base=True) to deal with fields w/ shape
lib.io.loadtxt
* fixed for the case when one of the fields is object
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Raise a NotImplementedError if the dtype is nested.
* _iotools : make sure StringConverter gets properly initiated when a function returning a np.object is used as input parameter.
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define it.
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- add a _checked attribute to indicate whether the converter has been upgraded or not.
- switched the default value for bool to False
* io.genfromtxt:
- fixed for the case where a whole column is masked: switch to bool or the common dtype (if needed)
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* lib.io : introduced genfromtxt, ndfromtxt, mafromtxt, recfromtxt, recfromcsv.
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