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

# ### Preparations

# Import `requests` library for http request and define API endpoints

# In[1]:


import requests
import pprint
import sys
import ase.io
try:# catch module change from Python2->3
    import io
except:
    import StringIO as io


API = 'http://api.catalysis-hub.org'

SEARCH_ENDPOINT = API + '/apps/prototypeSearch/facet_search/'
PROTOTYPE_ENDPOINT = API + '/apps/prototypeSearch/prototype/'
STRUCTURE_ENDPOINT = API + '/apps/prototypeSearch/get_structure/'


# The prototype App uses 3 API endpoints for searching and retrieving structures. Below we go through a practical example of how to use them together. The `request` is a very user friendly module to make HTTP requests from python. If you don't have it installed, you can change that with `pip install requests --user`

# ### Search

# Let's make use of the facet_search API to find all materials with a given composition

# In[2]:


r = requests.post(SEARCH_ENDPOINT, json={
    "search_terms": "stoichiometry:AB2",
    "limit": 1000,
})


# In[3]:


len(r.json()['prototypes'])


# We can learn about other possible arguments by inspecting the 'input' field of the result

# In[4]:


r.json()['input']


# To see how many structures of this composition are in each repository, we look at the repositories facet.

# In[5]:


r.json()['repositories']


# The facet lists are ordered by frequency by default. There are of course all the other facets, that are also in the GUI. 

# In[6]:


r.json().keys()


# ### Filter

# To narrow down the result, we look, e.g. only at the AB2 structures in OQMD

# In[7]:


r = requests.post(SEARCH_ENDPOINT, json={
    "search_terms": "stoichiometry:AB2 repository:OQMD",
    "limit": 1000,
})


# In[8]:


r.json()


# ### Prototypes

# Some prototypes are apparently more frequent than others. So let's have a look at the structures in the `AB2_a_d_191` prototype. To this end we use the prototype API.

# In[9]:


r = requests.post(PROTOTYPE_ENDPOINT, json={
    "prototype": "AB2_a_d_191",
    "search_terms": "repository:OQMD"
})


# In[10]:


len(r.json()['prototypes'])


# ### Structures

# So, let's say we want to do some specific manipulation on structures. To this end it will be handy to turn it into ASE atoms objects. 

# In[11]:


structures = []
for prototype in r.json()['prototypes'][:10]:
    sys.stdout.write('.')
    r_structure = requests.post(STRUCTURE_ENDPOINT, json=prototype)
    cif = r_structure.json()['structure']
    with io.StringIO() as cif_file:
        cif_file.write(cif)
        cif_file.seek(0)
        structures.append(
            ase.io.read(cif_file, format='cif')
        )
    


# In[12]:


structures


# Voila!
# 
# Ok, should be admitted, that doing `n` HTTP round trips for `n` structures is not ideal. We are working on that.