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

# In[1]:


try:
    import IPython
except:
    get_ipython().run_line_magic('pip', 'install IPython')
    import IPython 
from IPython.display import display, IFrame, HTML, Javascript
from IPython.core.display import display, HTML

HTML("""<link rel="stylesheet" type="text/css" href="src/css/notebook.css"/>""")


# #  Transforming Collections Data to Linked Art
# # Harvard Art Museum

# ## Input Data
# The notebook uses data from the Harvard Art Museum, using an API

# In[2]:


import requests
try:
    import json
except:
    get_ipython().system('pip install json')
    import json 

    

apidocs = "https://github.com/harvardartmuseums/api-docs"

keyfile = "data/ruskin/input/key.txt"
key = open(keyfile, mode='r', encoding='utf-8-sig').read()
uri = "https://api.harvardartmuseums.org/object?person=28419&apikey=" + key

for page in range(1, 11):
    response = requests.get(uri + "&page=" + str(page))
    json_data = response.json()
   
    text_file = open( "./data/harvard/input/" + str(page) + ".json", "wt")
    n = text_file.write(json.dumps(json_data, indent=2))
    text_file.close()


# In[3]:


try:
    import pandas as pd
except:
    get_ipython().system('pip install pandas')
    import pandas as pd
    

baseURI = "https://www.harvardartmuseums.org/collections/object/"
outputdir = "data/harvard/output"

mapp =  {
    "id":"id",
    "accession_number":"objectnumber",
    "accession_date": "accessionyear",
    "classification" : "",
    "title": "title",
    "alt_title": "",
    "notes": "commentary",
    "date_created":"dated",
    "date_created_earliest": "",
    "date_created_latest": "",
    "created_period":"period",
    "created_dynasty":"century",
    "created_inscriptions":"",
    "created_notes": "",
    "creator":"people",
    "physical_medium": "medium",
    "physical_style": "",
    "physical_technique": "technique",
    "physical_description": "description",
    "physical_dimensions": "dimensions",
    "created_provenance": "provenance" ,
    "credit_line": "creditline",
    "collection" : "division",
    "classification": "classification",
    "current_status" : "",
    "current_owner": "Harvard Museum of Art",
    "image_url":"primaryimageurl",
    "homepage" : "url"
}

# display transposed dataframe of data mapping
display(pd.DataFrame(mapp, index=[0]).T)


# In[4]:


try:
    import cromulent
except:
    get_ipython().system('pip install cromulent')
    import cromulent
    
from cromulent.model import factory
from lib import linkedart as la



def createObjPropHarvard(obj,mapp):
    objProp = {}
    csv_keys = list(obj.keys())
    for key in csv_keys:
        for prop in mapp:
            if key == mapp[prop]:
                if prop == "creator":
                    objProp["creator"] = ""
                    for person in obj[key]:
                        
                        if "personid" in person and person["personid"] == 28419 and person["role"] == "Artist": 
                            objProp[prop] = [{
                                "id": str(person["personid"]),
                                "name": person["displayname"],
                                }]      
                else:
                    objProp[prop] = obj[key]
    objProp["current_owner"] = {"name":"Harvard Art Museum",
                                "location":"Cambridge, MA",
                                "type": "http://vocab.getty.edu/aat/300312281" ,
                                "type_label": ""}
    return objProp   

# list to hold file names for use with jsonld visualisation dropdown
selectOptions = []
selectOptions = [('Please select an artwork', '')]



for x in range(1,11):
    
    with open("./data/harvard/input/" + str(x) + ".json") as json_file:
        data = json.load(json_file)
        for obj in data["records"]:
            objProp=createObjPropHarvard(obj,mapp)
            if objProp["creator"] != "":
                
                
                id = str(objProp["id"])
                filename = id + ".json"
                object_uri = baseURI + id
    
                # create obj description
                objLA = la.createObjDesc(objProp,la.objTypes,object_uri)
                
                selectOptions.append( ( objProp["title"] + " (" + filename + ")" , filename))
                # write to file 
                text_file = open(outputdir + "/" + filename, "wt")
                n = text_file.write(factory.toString(objLA, compact=False))
                text_file.close()
    


# In[5]:


try:
    import ipywidgets
except:
    get_ipython().run_line_magic('pip', 'install ipywidgets')
    import ipywidgets

from ipywidgets import Layout, FileUpload 
from IPython.display import display, IFrame, HTML, Image
from IPython.core.display import Javascript        
 
import os

try:
    import json
except:
    get_ipython().run_line_magic('pip', 'install json')
    import json 
    
   
def dropdown_eventhandler(change):
    with open('./src/js/visld.js', 'r') as _jscript:
        code = _jscript.read() + "var file = '" + outputdir + "/" + change.new + "';var selector = '#vis';visjsonld(file, selector); "
        display(Javascript(code))
    
        with open( outputdir + "/" + change.new) as json_file:
    
                artwork = json.load(json_file)
                if ("representation" in artwork):
                    image = artwork["representation"][0]["id"]
                    display(Javascript("document.getElementById('artwork').src = '" + image   +   "';"))
                else:
                    display(Javascript("document.getElementById('artwork').src = '';"))
                    

selectObject = ipywidgets.Dropdown(options=selectOptions)
selectObject.observe(dropdown_eventhandler, names='value')

display(selectObject)


# <div><img style="height:500px" id="artwork" src=""/></div>
# 
# <div id='vis' style='height:100%;width:3000px'></div>

# In[ ]: