lambda_function.py

import tweepy
import json
import requests
import pandas as pd
import numpy as np

def lambda_handler(event, context):
    #opens and reads mvkey.json
    mvkey={}
    with open("mvkeys/mvkey.json") as file:
        mvkey = json.loads(file.read())
    
    # Consumer keys and access tokens, used for OAuth
    consumer_key = mvkey["consumer_key"]
    consumer_secret = mvkey["consumer_secret"]
    access_token = mvkey["access_token"]
    access_token_secret = mvkey["access_token_secret"]

    # OAuth process, using the keys and tokens
    auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
    auth.set_access_token(access_token, access_token_secret)

    # Store access keys in a way to send to Twitter
    api = tweepy.API(auth)

    # Write out the thing we're going to tweet
    def buildTweet(argument1, argument2, argument3):
        tweet = argument1 + " missed a vote on " + argument2 + ". " + argument3
        tweetsave = []
        if (len(tweet)) > 0:
            tweetsave.append(tweet)
            checkTweet(tweet, tweetsave)       

    def checkTweet(tweet, tweetsave):
        for t in tweetsave:
            if tweet == t:
                pass
            else:
                sendTweet(tweet)     

    # Send the tweet except if it has already been tweeted out
    def sendTweet(content):
        api.update_status(content)


    #opens and reads apikey.json
    apikey={}
    with open("mvkeys/apikey.json") as file:
        apikey = json.loads(file.read())
    #authenticate and calls api to print text
    x_api_key = apikey["x_api_key"]

    #calls senate members api and puts results into json
    urlsenate = 'https://api.propublica.org/congress/v1/115/senate/members.json'
    headers = {'X-API-KEY': x_api_key}
    responsesenate = requests.get(urlsenate, headers=headers)
    jsonfilesenate = responsesenate.json()

    #json data in senate results into dataframe
    datasenate = jsonfilesenate.get('results')
    for s in datasenate:
        membersenate = s['members']
        membersenate_df = pd.DataFrame(membersenate)

    #find senate member ids for MD members
    membersenate_df = membersenate_df.replace(np.nan, '', regex=True)
    maryland = membersenate_df[membersenate_df['state'].str.contains("MD")]

    #put only MD senate member ids in array
    arrayid = []
    if (len(maryland)) > 0:
        mrowid = maryland.iterrows()
        for m in mrowid:
            arrayid.append(m[1]['id'])
        
        
    #calls house members api and puts results into json
    urlhouse = 'https://api.propublica.org/congress/v1/115/house/members.json'
    responsehouse = requests.get(urlhouse, headers=headers)
    jsonfilehouse = responsehouse.json()

    #json data in house results into dataframe
    datahouse = jsonfilehouse.get('results')
    for h in datahouse:
        memberhouse = h['members']
        memberhouse_df = pd.DataFrame(memberhouse)

    #find house member ids for MD members
    memberhouse_df = memberhouse_df.replace(np.nan, '', regex=True)
    maryland = memberhouse_df[memberhouse_df['state'].str.contains("MD")]
     
    #put only MD house member ids in array
    if (len(maryland)) > 0:
        mrowid = maryland.iterrows()
        for m in mrowid:
            arrayid.append(m[1]['id'])   



    #takes out each member id out of the array 1 at a time
    for memid in arrayid:

        #calls excuses for all legislative MD members api and puts results in json
        urlexcuse = 'https://api.propublica.org/congress/v1/members/' + memid + '/explanations/115.json'
        responseexcuse = requests.get(urlexcuse, headers=headers)
        jsonfileexcuse = responseexcuse.json()
    
        #if MD member has no excuses removes their results
        dataexcuse = jsonfileexcuse.get('results')
        if len(dataexcuse) == 0:
            continue
        else:
            #if MD member has excuses gets name and info on excuses and tweets 
            mdexcuse_df = pd.DataFrame(jsonfileexcuse)
            if (len(mdexcuse_df) > 0):
                irow = mdexcuse_df.iterrows()
                for m in irow:
                    print(m[1]['display_name'])
    
            dataexcuse_df = pd.DataFrame(dataexcuse)
            if (len(dataexcuse_df) > 0):
                irow = dataexcuse_df.iterrows()
                for i in irow:
                    print(i[1]['date'])
                    print(i[1]['url'])
                    buildTweet(m[1]['display_name'],i[1]['date'],i[1]['url'])
    return 'Hello from Lambda'