import requests
import json
import shutil
import time

class Credentials(object):
  requestUrl = "https://hosted.datascopeapi.reuters.com/RestApi/v1/Authentication/RequestToken"

  requestHeaders={
      "Prefer":"respond-async",
      "Content-Type":"application/json"
      }

  requestBody={
        "Credentials": {
        "Username": "myUserName",
        "Password": "myPassword"
      }
    }

  def __init__(self, uname,pwd):
    self.requestBody['Credentials']['Username'] = uname
    self.requestBody['Credentials']['Password'] = pwd
    
usr = 'username'
pwd = 'password'

c = Credentials (usr,pwd)

filePath = "C:/Users/kauffn/Downloads/trth/"
fileNameRoot = "Python_Test"


r1 = requests.post(c.requestUrl, json=c.requestBody,headers=c.requestHeaders)

if r1.status_code == 200 :
    jsonResponse = json.loads(r1.text.encode('ascii', 'ignore'))
    token = jsonResponse["value"]
    print ('Authentication token (valid 24 hours):')
    print (token)
else:
    print ('Please replace myUserName and myPassword with valid credentials, then repeat the request')


# In[6]:

#Step 2: send an on demand extraction request using the received token 

requestUrl='https://hosted.datascopeapi.reuters.com/RestApi/v1/StandardExtractions/Packages'
requestHeaders={
    "Prefer":"respond-async",
    "Content-Type":"application/json",
    "charset":"utf-8",
    "Authorization": "token " + token
}

r2 = requests.post(requestUrl, headers=requestHeaders)

#r2 = requests.post(requestUrl,headers=requestHeaders)

#Display the response status, and the location url to use to get the status of the extraction request
#Initial response status (after approximately 30 seconds wait) will be 202
print (r2.status_code)
#print (r2.headers["location"])


# In[7]:

#Step 3: poll the status of the request using the received location URL, and get the jobId and extraction notes

'''
#When the status of the request is 200 the extraction is complete, we display the jobId and the extraction notes
print ('response status = ' + str(r3.status_code))

while (r3.status_code == 202):
    print ('As we received a 202, we wait 30 seconds, then poll again (until we receive a 200)')
    time.sleep(30)
    r3 = requests.get(requestUrl,headers=requestHeaders)
    print ('response status = ' + str(r3.status_code))
    
if r3.status_code == 200 :
    r3Json = json.loads(r3.text.encode('ascii', 'ignore'))
    jobId = r3Json["JobId"]
    print ('\njobId: ' + jobId + '\n')
    notes = r3Json["Notes"]
    print ('Extraction notes:\n' + notes[0])

if r3.status_code != 200 :
    print ('There was an error. Try running this cell again. If it fails, re-run the previous cell.\n')
# In[9]:

#Step 5: get the extraction results, using the received jobId, save the compressed data to disk
#This is a variant of step 4, where we save the data in compressed format on disk, without displaying it

requestUrl = "https://hosted.datascopeapi.reuters.com/RestApi/v1/Extractions/RawExtractionResults" + "('" + jobId + "')" + "/$value"

requestHeaders={
    "Prefer":"respond-async",
    "Content-Type":"text/plain",
    "Accept-Encoding":"gzip",
    "Authorization": "token " + token
}

r5 = requests.get(requestUrl,headers=requestHeaders,stream=True)
#Ensure we do not automatically decompress the data on the fly:
r5.raw.decode_content = False
print ('Response headers for content: type: ' + r5.headers["Content-Type"] + ' - encoding: ' + r5.headers["Content-Encoding"] + '\n')
#Next 2 lines display some of the compressed data, but if you uncomment them the save to file will fail
#print ('100 bytes of compressed data:')
#print (r5.raw.read(100))

fileName = filePath + fileNameRoot + ".csv.gz"
chunk_size = 1024
rr = r5.raw
with open(fileName, 'wb') as fd:
    shutil.copyfileobj(rr, fd, chunk_size)

print ('Saved compressed data to file:' + fileName)

'''