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

# # Using results
# 
# Since json is a dictionary, you can pull out a single datapoint using the key.
# 
# ```
# {
#   "source": "ensembl_havana",
#   "object_type": "Gene",
#   "logic_name": "ensembl_havana_gene",
#   "version": 12,
#   "species": "homo_sapiens",
#   "description": "B-Raf proto-oncogene, serine/threonine kinase [Source:HGNC Symbol;Acc:HGNC:1097]",
#   "display_name": "BRAF",
#   "assembly_name": "GRCh38",
#   "biotype": "protein_coding",
#   "end": 140924764,
#   "seq_region_name": "7",
#   "db_type": "core",
#   "strand": -1,
#   "id": "ENSG00000157764",
#   "start": 140719327
# }
# ```
# 
# We can add this to our previous script:

# In[1]:


import requests, json
from pprint import pprint

def fetch_endpoint(server, request, content_type):

    r = requests.get(server+request, headers={ "Accept" : content_type})

    if not r.ok:
        r.raise_for_status()
        sys.exit()

    if content_type == 'application/json':
        return r.json()
    else:
        return r.text


server = "http://rest.ensembl.org/"
ext = "lookup/id/ENSG00000157764?"
con = "application/json"
get_gene = fetch_endpoint(server, ext, con)

symbol = get_gene['display_name']
print (symbol)


# ## Exercises 3
# 
# 1\. Write a script to lookup the gene called *ESPN* in human and print the stable ID of this gene.

# In[ ]:


# Exercise 3.1


# 2\. Get all variants that are associated with the phenotype 'Coffee consumption'. For each variant print
# 
#    a. the p-value for the association
#    
#    b. the PMID for the publication which describes the association between that variant and ‘Coffee consumption’
#    
#    c. the risk allele and the associated gene.

# In[ ]:


# Exercise 3.2


# 3\. Get the mouse homologue of the human BRCA2 and print the ID and sequence of both.
# 
# Note that the JSON for the endpoint you need is several layers deep, containing nested lists (appear as square brackets [ ] in the JSON) and key value sets (dictionary; appear as curly brackets { } in the JSON). Pretty print (pprint) comes in very useful here for the intermediate stage when you're trying to work out the json.

# In[ ]:


# Exercise 3.3


# [Next page: Exercises 3 – answers](3_Using_results_answers.ipynb)