#
# Check differences with previous versions.
# In[30]:
# In[30]:
utils.checkDiffs(thisTempTf, thisTf, only=set(nodeFeatures))
# # Deliver
#
# Copy the new TF feature from the temporary location where it has been created to its final destination.
# In[31]:
utils.deliverFeatures(thisTempTf, thisTf, nodeFeatures)
# # Compile TF
# In[ ]:
utils.caption(4, "Load and compile the new TF features")
# In[32]:
TF = Fabric(locations=[coreTf, thisTf], modules=[""])
api = TF.load("""
lex sp vs
predication gloss
""" + " ".join(nodeFeatures))
api.makeAvailableIn(globals())
# We list features that will be added and deleted and changed.
# For each changed feature we show the first line where the new feature differs from the old one.
# We ignore changes in the metadata, because the timestamp in the metadata will always change.
# In[20]:
utils.checkDiffs(thisTempTf, thisTf, only=changedFeatures)
# # Deliver
#
# Copy the new TF dataset from the temporary location where it has been created to its final destination.
# In[21]:
utils.deliverFeatures(thisTempTf,
thisTf,
changedFeatures,
deleteFeatures=deleteFeatures)
# # Compile TF
#
# We load the new features, use the new format, check some values
# In[22]:
utils.caption(4, 'Load and compile the new TF features')
TF = Fabric(locations=thisTf, modules=[''])
api = TF.load(' '.join(changedDataFeatures))
api.makeAvailableIn(globals())
# # Examples
