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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Parsing Citations
With AnyStyle.io and Crossref's search api
Step1:  ok, we got a pile of citations. But they aren't in shape. When we look at the cites, they are a collection of 1,505 strings, this isn't very useful for doing data analysis. We need to get them into shape, that is, we need to break them up into their component parts.
Step2:  Note, these citations are not always formatted in the same way, for example, lets looks at some from a different part of the piles.
Step3:  Parsing citaitons is a whole area of research to be discussed at another time. I am going to use AnyStyle.io to try and parse these citations because it has a nicely designed API.
Step4:  Sweet!
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Python Code:
import pandas as pd
citations = pd.read_csv("cites.csv")
citations
citations.iloc[0]
len(citations)
Explanation: Parsing Citations
With AnyStyle.io and Crossref's search api
End of explanation
citations.iloc[0:5]
Explanation: ok, we got a pile of citations. But they aren't in shape. When we look at the cites, they are a collection of 1,505 strings, this isn't very useful for doing data analysis. We need to get them into shape, that is, we need to break them up into their component parts.
End of explanation
citations.iloc[390:395]
Explanation: Note, these citations are not always formatted in the same way, for example, lets looks at some from a different part of the piles.
End of explanation
import requests
import os
import json
import numpy as np
import time
# get the API key for AnyStyle.io from a text file in this directory
with open('anystyle_key.txt','r') as f:
    api_key = f.read()
# I want to figure out what cite is causing the error
parsed_cites = []
for cite in list(segment['cite']):
   
    
    payload = {"format": "json",
               "access_token": api_key,
               "references": cite}
    headers = {"Content-Type": "application/json;charset=UTF-8"}
    #print("Payload Build, requesting")
    
    r = requests.post("http://anystyle.io/parse/references",
                  headers=headers,
                  data=json.dumps(payload))
    #print("Got response", r)
    if r.status_code == 400:
        print(cite)
    
    #parsed_cites.append(r.json())
parsed_cites = []
for segment in np.array_split(citations,5):
    print("Segment Length: ",len(segment))
    cite_pile = list(segment['cite'])
    
    payload = {"format": "json",
               "access_token": api_key,
               "references": cite_pile}
    headers = {"Content-Type": "application/json;charset=UTF-8"}
    print("Payload Build, requesting")
    
    r = requests.post("http://anystyle.io/parse/references",
                  headers=headers,
                  data=json.dumps(payload))
    print("Got response", r)
    parsed_cites.append(r.json())
print(len(parsed_cites))
parsed_cites_master = [cite for cites in parsed_cites for cite in cites]
parsed_cites_master[0:10]
Explanation: Parsing citaitons is a whole area of research to be discussed at another time. I am going to use AnyStyle.io to try and parse these citations because it has a nicely designed API.
End of explanation
with open("parsed_cites.json",'w') as f:
    print(json.dumps(parsed_cites_master, indent=4), file=f )
df_citations = pd.DataFrame(parsed_cites_master)
df_citations
df_citations.to_csv("parsed_cites.csv")
Explanation: Sweet!
End of explanation
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