#!/usr/bin/env python
# coding: utf-8

# # Resolving Strategies
# 
# * Example on how to use resolving strategies
# 

# In[1]:


import os
import json

from kgforge.core import KnowledgeGraphForge
from kgforge.specializations.resources import Dataset


# In[2]:


import getpass
TOKEN = getpass.getpass()


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BUCKET = "dke/kgforge"
forge = KnowledgeGraphForge("../use-cases/prod-forge-nexus.yml",
 bucket=BUCKET,
 token=TOKEN
 )


# ### List available resolvers

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forge.resolvers(output='dict')


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case_insensitive = forge.resolve('Pv+', scope='ontology', strategy='EXACT_CASEINSENSITIVE_MATCH')


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exact = forge.resolve('PV+', scope='ontology', strategy='EXACT_MATCH')


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assert case_insensitive == exact


# ### Try with a similar string, but other characters

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similar = forge.resolve('pv-', scope='ontology', strategy='EXACT_CASEINSENSITIVE_MATCH')


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similar1 = forge.resolve('pv:', scope='ontology', strategy='EXACT_CASEINSENSITIVE_MATCH')


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assert similar is None
assert similar1 is None


# ### Combine spaces and other characters

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print(forge.resolve('229_l6 it ctx', scope='ontology', strategy='EXACT_CASEINSENSITIVE_MATCH'))


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print(forge.resolve('264_L5/6 np CTX', scope='ontology', strategy='EXACT_CASEINSENSITIVE_MATCH'))


# ## Resolve from a specific ontology
# This is particularly useful when two entities have a similar acronym like the example below, where there is a brain region called BAC, and a electrical cell type labelled bAC.
# 
# Without any specification, it will return the first result in the list of matches (no priority or ranking).

# ### List available ontologies to resolve from

# In[13]:


list(forge.resolvers(output='dict')['ontology'].keys()) # terms is for resolving accross all ontologies


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from kgforge.core.commons.strategies import ResolvingStrategy

print(forge.resolve("bAC", scope="ontology", target="terms", 
                    strategy=ResolvingStrategy.EXACT_CASEINSENSITIVE_MATCH))


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print(forge.resolve("bAC", scope="ontology", target="CellType", strategy="EXACT_CASEINSENSITIVE_MATCH"))


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print(forge.resolve("bAC", scope="ontology", target="BrainRegion", strategy="EXACT_CASEINSENSITIVE_MATCH"))


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print(forge.resolve("rat", scope="ontology", target="Species", strategy="EXACT_CASEINSENSITIVE_MATCH"))


# ### Ensuring one label

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resource = forge.resolve("AOB_MC", scope="ontology", target="terms", strategy="EXACT_MATCH")
assert isinstance(resource.label, str)


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excitatory = forge.resolve("exc", scope='ontology', strategy='EXACT_CASEINSENSITIVE_MATCH')
assert isinstance(excitatory.label, str)


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print(excitatory)