json_demo.py

#!/usr/bin/env python3
import json
from input_fj import input

"""
Functions that format the computed graph to match the interface to the output-part

"""

# creates a list that contains a dictionary for each node
# the dictionaries store the values for the attributes
def format_nodes(V):
    list_of_node_dicts = list()
    for node in V:
        new_dict = dict()
        new_dict["name"] = node.title
        new_dict["author"] = node.contributors
        new_dict["year"] = node.publication_date
        new_dict["journal"] = node.journal
        new_dict["doi"] = node.doi_url
        new_dict["group"] = node.group
        list_of_node_dicts.append(new_dict)
    return list_of_node_dicts
    
# creates a list that contains a disctionary for each edge
# the dictionaries contain the source as keys and the target as values   
def format_edges(E):
    list_of_edge_dicts = list()
    for edge in E:
        new_dict_2 = dict()
        new_dict_2["source"] = edge[0]
        new_dict_2["target"] = edge[1]
        list_of_edge_dicts.append(new_dict_2)
    return list_of_edge_dicts
   
# combine the lists of nodes and edges to a dictionary and saves it to a json file
def output_to_json(V,E):
    dict_of_all = dict()
    list_of_node_dicts = format_nodes(V)
    list_of_edge_dicts = format_edges(E)
    dict_of_all["nodes"] = list_of_node_dicts
    dict_of_all["links"] = list_of_edge_dicts
    with open('json_text.json','w') as outfile:
        json.dump(dict_of_all, outfile)
  
#knoten = ["doi1", "doi2", "doi3"]
#kanten = [[1,2],[3,4],[5,6]]
#output_to_json(knoten,kanten)