Python/numpy interface to the netCDF C library.
For details on the latest updates, see the Changelog.
03/08/2019: Version 1.4.3.2 released. Include missing membuf.pyx file in source tarball. No need to update if you installed 1.4.3.1 from a binary wheel.
03/07/2019: Version 1.4.3.1 released. Fixes bug in implementation of NETCDF4_CLASSIC parallel IO support in 1.4.3.
03/05/2019: Version 1.4.3 released. Issues with netcdf-c 4.6.2 fixed (including broken parallel IO). set_ncstring_attrs()
method added, memoryview buffer now returned when an in-memory Dataset is closed.
10/26/2018: Version 1.4.2 released. Minor bugfixes, added Variable.get_dims()
method and master_file
kwarg for MFDataset.__init__
.
08/10/2018: Version 1.4.1 released. The old slicing behavior
(numpy array returned unless missing values are present, otherwise masked array returned) is renabled
via set_always_mask(False)
.
05/11/2018: Version 1.4.0 released. The netcdftime package is no longer included, it is now a separate package dependency. In addition to several bug fixes, there are a few important changes to the default behaviour to note:
- Slicing a netCDF variable will now always return masked array by default, even if there are no
masked values. The result depended on the slice before, which was too surprising.
If auto-masking is turned off (with
set_auto_mask(False)
) a numpy array will always be returned. _FillValue
is no longer treated as a valid_min/valid_max. This was too surprising, despite the fact the thet netcdf docs attribute best practices suggests that clients should to this ifvalid_min
,valid_max
andvalid_range
are not set.- Changed behavior of string attributes so that
nc.stringatt = ['foo','bar']
produces an vlen string array attribute in NETCDF4, instead of concatenating into a single string (foobar
). In NETCDF3/NETCDF4_CLASSIC, an IOError is now raised, instead of writingfoobar
. - Retrieved compound-type variable data now returned with character array elements converted to
numpy strings (issue #773).
Works for assignment also. Can be disabled using
set_auto_chartostring(False)
. Numpy structured array dtypes with'SN'
string subtypes can now be used to define netcdf compound types increateCompoundType
(they get converted to('S1',N)
character array types automatically). valid_min
,valid_max
,_FillValue
andmissing_value
are now treated as unsigned integers if_Unsigned
variable attribute is set (to mimic behaviour of netcdf-java). Conversion to unsigned type now occurs before masking and scale/offset operation (issue #794)
11/01/2017: Version 1.3.1 released. Parallel IO support with MPI!
Requires that netcdf-c and hdf5 be built with MPI support, and mpi4py.
To open a file for parallel access in a program running in an MPI environment
using mpi4py, just use parallel=True
when creating
the Dataset
instance. See examples/mpi_example.py
for a demonstration. For more info, see the tutorial section.
9/25/2017: Version 1.3.0 released. Bug fixes
for netcdftime
and optimizations for reading strided slices. encoding
kwarg added to
Dataset.__init__
and Dataset.filepath
to deal with oddball encodings in filename
paths (sys.getfilesystemencoding()
is used by default to determine encoding).
Make sure numpy datatypes used to define CompoundTypes have isalignedstruct
flag set
to avoid segfaults - which required bumping the minimum required numpy from 1.7.0
to 1.9.0. In cases where missing_value/valid_min/valid_max/_FillValue
cannot be
safely cast to the variable's dtype, they are no longer be used to automatically
mask the data and a warning message is issued.
6/10/2017: Version 1.2.9 released. Fixes for auto-scaling
and masking when _Unsigned
and/or valid_min
, valid_max
attributes present. setup.py updated
so that pip install
works if cython not installed. Now requires setuptools
version 18.0 or greater.
6/1/2017: Version 1.2.8 released. From Changelog:
- recognize
_Unsigned
attribute used by netcdf-java to designate unsigned integer data stored with a signed integer type in netcdf-3 issue #656. - add Dataset init memory parameter to allow loading a file from memory pull request #652, issue #406 and issue #295.
- fix for negative times in num2date issue #659.
- fix for failing tests in numpy 1.13 due to changes in
numpy.ma
issue #662. - Checking for
_Encoding
attribute forNC_STRING
variables, otherwise use 'utf-8'. 'utf-8' is used everywhere else, 'default_encoding' global module variable is no longer used. getncattr method now takes optional kwarg 'encoding' (default 'utf-8') so encoding of attributes can be specified if desired. If_Encoding
is specified for anNC_CHAR
('S1'
) variable, the chartostring utility function is used to convert the array of characters to an array of strings with one less dimension (the last dimension is interpreted as the length of each string) when reading the data. When writing the data, stringtochar is used to convert a numpy array of fixed length strings to an array of characters with one more dimension. chartostring and stringtochar now also have an 'encoding' kwarg. Automatic conversion to/from character to string arrays can be turned off via a newset_auto_chartostring
Dataset and Variable method (default isTrue
). Addresses issue #654 - Cython >= 0.19 now required,
_netCDF4.c
and_netcdftime.c
removed from repository.
1/8/2017: Version 1.2.7 released. Python 3.6 compatibility, and fix for vector missing_values.
12/10/2016: Version 1.2.6 released. Bug fixes for Enum data type, and _FillValue/missing_value usage when data is stored in non-native endian format. Add get_variables_by_attributes to MFDataset. Support for python 2.6 removed.
12/1/2016: Version 1.2.5 released. See the Changelog for changes.
4/15/2016: Version 1.2.4 released. Bugs in handling of variables with specified non-native "endian-ness" (byte-order) fixed ([issue #554] (Unidata#554)). Build instructions updated and warning issued to deal with potential backwards incompatibility introduced when using HDF5 1.10.x (see Unidata/netcdf-c/issue#250).
3/10/2016: Version 1.2.3 released. Various bug fixes.
All text attributes in NETCDF4
formatted files are now written as type NC_CHAR
, unless they contain unicode characters that
cannot be encoded in ascii, in which case they are written as NC_STRING
. Previously,
all unicode strings were written as NC_STRING
. This change preserves compatibility
with clients, like Matlab, that can't deal with NC_STRING
attributes.
A setncattr_string
method was added to force attributes to be written as NC_STRING
.
1/1/2016: Version 1.2.2 released. Mostly bugfixes, but with two new features.
-
support for the new
NETCDF3_64BIT_DATA
format introduced in netcdf-c 4.4.0. Similar toNETCDF3_64BIT
(nowNETCDF3_64BIT_OFFSET
), but includes 64 bit dimension sizes (> 2 billion), plus unsigned and 64 bit integer data types. Uses the classic (netcdf-3) data model, and does not use HDF5 as the underlying storage format. -
Dimension objects now have a
size
attribute, which is the current length of the dimension (same as invokinglen
on the Dimension instance).
The minimum required python version has now been increased from 2.5 to 2.6.
10/15/2015: Version 1.2.1 released. Adds the ability to slice Variables with unsorted integer sequences, and integer sequences with duplicates.
9/23/2015: Version 1.2.0 released. New features:
-
get_variables_by_attributes
Dataset
andGroup
method for retrieving variables that have matching attributes. -
Support for Enum data types.
-
isopen
Dataset
method.
7/28/2015: Version 1.1.9 bugfix release.
5/14/2015: Version 1.1.8 released. Unix-like paths can now be used in createVariable
and createGroup
.
v = nc.createVariable('/path/to/var1', ('xdim', 'ydim'), float)
will create a variable named 'var1', while also creating the groups 'path' and 'path/to' if they do not already exist.
Similarly,
g = nc.createGroup('/path/to')
now acts like mkdir -p
in unix, creating groups 'path' and '/path/to',
if they don't already exist. Users who relied on nc.createGroup(groupname)
failing when the group already exists will have to modify their code, since
nc.createGroup
will now return the existing group instance.
Dataset.__getitem__
was also added. nc['/path/to']
now returns a group instance, and nc['/path/to/var1']
now returns a variable instance.
3/19/2015: Version 1.1.7 released. Global Interpreter Lock (GIL) now released when extension
module calls C library for read operations. This speeds up concurrent reads when using threads.
Users who wish to use netcdf4-python inside threads should read http://www.hdfgroup.org/hdf5-quest.html#gconc
regarding thread-safety in the HDF5 C library. Fixes to setup.py
now ensure that pip install netCDF4
with export USE_NCCONFIG=0
will use environment variables to find paths to libraries and include files,
instead of relying exclusively on the nc-config utility.
-
Clone GitHub repository (
git clone https://github.com/Unidata/netcdf4-python.git
), or get source tarball from PyPI. Links to Windows and OS X precompiled binary packages are also available on PyPI. -
Make sure numpy and Cython are installed and you have Python 2.7 or newer.
-
Make sure HDF5 and netcdf-4 are installed, and the
nc-config
utility is in your Unix PATH. -
Run
python setup.py build
, thenpython setup.py install
(withsudo
if necessary). -
To run all the tests, execute
cd test && python run_all.py
.
See the online docs for more details.