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Project Description

A DSL for creating NetCDF files. Here’s a simple example:

from pup import *

class Test(NetCDF):
    # NC_GLOBAL attributes go here
    history = 'Created for a test'

    # dimensions need to be set explicitly only when they
    # have no variable associated with them
    dim0 = Dimension(2)

    # variables that don't specify dimensions are assumed to
    # be their own dimension
    time = Variable(range(10), record=True, units='days since 2008-01-01')

    # now a variable with dimensions (time,)
    temperature = Variable(range(10), (time,), units='deg C')

Test.save('simple.nc')

This will produce the following NetCDF file:

netcdf simple {
dimensions:
    dim0 = 2 ;
    time = UNLIMITED ; // (10 currently)
variables:
    int time(time) ;
        time:units = "days since 2008-01-01" ;
    int temperature(time) ;
        temperature:units = "deg C" ;

// global attributes:
        :history = "Created for a test" ;
data:

 time = 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ;

 temperature = 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ;
}

Compare this with the code necessary to do the same using common NetCDF libraries:

f = netcdf_file("simple.nc", "w")

f.history = "Created for a test"

f.createDimension("dim0", 2)

f.createDimension("time", None)
time = f.createVariable("time", "i", ("time",))
time.units = "days since 2008-01-01"
time[:] = range(10)

temperature = f.createVariable("temperature", "i", ("time",))
temperature.units = "deg C"
temperature[:] = range(10)

By default it uses pupynere for creating files, but this can be overloaded; we can use the netCDF4 module, for example, which allows us to specify groups:

from netCDF4 import Dataset

class Test(NetCDF):
    loader = Dataset
    ...

    foo = Group(
        dim = Dimension(10),
        var = Variable(range(10)),
        ...
    )
Test.save('simple.nc', format='NETCDF4')

Changelog:

0.1.8:Ensure record dimensions are created first.
0.1.7:Convert strings to array of chars.
0.1.6:Fix bug in dimension name.
0.1.5:Added support for Groups when using netcdf4.
0.1.4:Added support for masked arrays.
0.1.3:Pass keyword arguments in save() to the loader.
0.1.2:Improved optional loader detection.
0.1.1:Added pupynere dependency.
0.1:Initial release.
Release History

Release History

0.1.8

This version

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0.1.7

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0.1.6

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0.1.5

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0.1.4

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0.1.3

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0.1.2

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0.1.1

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0.1

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
Puppy-0.1.8-py2.7.egg (5.3 kB) Copy SHA256 Checksum SHA256 2.7 Egg Dec 5, 2013
Puppy-0.1.8.tar.gz (3.6 kB) Copy SHA256 Checksum SHA256 Source Dec 5, 2013

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