from netCDF4 import Dataset, num2date

import numpy as np

# change the variables below with your own data

# the filename

filename = "input_file_python.nc"

# the variable name in the netCDF file

varname = "SST"

# longitude in degrees East

lon = np.array([1,1.5,2])

# latitude in degrees West

lat = np.array([-1,0,1])

# time in days since a starting day

time = np.array([0,1,2])

# time units

time_units = "days since 1900-01-01 00:00:00";

# the data to reconstruct

data = np.zeros((len(time),len(lat),len(lon)))

# special value to indice missing data (cloud or land)

fill_value = -9999.

# mask, one means the data location is valid, e.g. a sea points for sea surface temperature.

mask = np.ones((len(lat),len(lon)))

# create the NetCDF file

root_grp = Dataset(filename, 'w', format='NETCDF4')

# dimensions

root_grp.createDimension('lon', len(lon))

root_grp.createDimension('lat', len(lat))

root_grp.createDimension('time', None)

# variables

nc_lon = root_grp.createVariable('lon', 'f4', ('lon',))

nc_lat = root_grp.createVariable('lat', 'f4', ('lat',))

nc_time = root_grp.createVariable('time', 'f4', ('time',))

nc_time.units = time_units

nc_data = root_grp.createVariable(varname, 'f4', ('time', 'lat', 'lon'),

fill_value=fill_value)

nc_mask = root_grp.createVariable("mask", 'i4', ('lat', 'lon'))

nc_mask.comment = "one means the data location is valid (e.g. sea for SST), zero the location is invalid (e.g. land for SST)"

# data

nc_lon[:] = lon

nc_lat[:] = lat

nc_time[:] = time

nc_data[:,:] = data

nc_mask[:,:] = mask

root_grp.close()