Facebook Marketing API - Python to get Insights - User Request Limit Reached

Adding a couple of small functions to improve on LucyTurtle's answer as it is still susceptible to Facebook's Rate Limiting

import logging
import requests as rq

#Function to find the string between two strings or characters
def find_between( s, first, last ):
        start = s.index( first ) + len( first )
        end = s.index( last, start )
        return s[start:end]
    except ValueError:
        return ""

#Function to check how close you are to the FB Rate Limit
def check_limit():
    def check_limit():
    return usage

#Check if you reached 75% of the limit, if yes then back-off for 5 minutes (put this chunk in your 'for ad is ads' loop, every 100-200 iterations)
if (check_limit()>75):
    print('75% Rate Limit Reached. Cooling Time 5 Minutes.')
    logging.debug('75% Rate Limit Reached. Cooling Time 5 Minutes.')

It took a while of digging through the API and guessing but I got it! Here is my final script:

# This program downloads all relevent Facebook traffic info as a csv file
# This program requires info from the Facebook Ads API: https://github.com/facebook/facebook-python-ads-sdk

# Import all the facebook mumbo jumbo
from facebookads.api import FacebookAdsApi
from facebookads.adobjects.adsinsights import AdsInsights
from facebookads.adobjects.adaccount import AdAccount
from facebookads.adobjects.business import Business

# Import th csv writer and the date/time function
import datetime
import csv

# Set the info to get connected to the API. Do NOT share this info
my_app_id = '****'
my_app_secret = '****'
my_access_token = '****'

# Start the connection to the facebook API
FacebookAdsApi.init(my_app_id, my_app_secret, my_access_token)

# Create a business object for the business account
business = Business('****')

# Get yesterday's date for the filename, and the csv data
yesterdaybad = datetime.datetime.now() - datetime.timedelta(days=1)
yesterdayslash = yesterdaybad.strftime('%m/%d/%Y')
yesterdayhyphen = yesterdaybad.strftime('%m-%d-%Y')

# Define the destination filename
filename = yesterdayhyphen + '_fb.csv'
filelocation = "/cron/downloads/"+ filename

# Get all ad accounts on the business account
accounts = business.get_owned_ad_accounts(fields=[AdAccount.Field.id])

# Open or create new file 
    csvfile = open(filelocation , 'w+', 0777)
    print ("Cannot open file.")

# To keep track of rows added to file
rows = 0

    # Create file writer
    filewriter = csv.writer(csvfile, delimiter=',')
except Exception as err:

# Iterate through the adaccounts
for account in accounts:
    # Create an addaccount object from the adaccount id to make it possible to get insights
    tempaccount = AdAccount(account[AdAccount.Field.id])

    # Grab insight info for all ads in the adaccount
    ads = tempaccount.get_insights(params={'date_preset':'yesterday',

    # Iterate through all accounts in the business account
    for ad in ads:
        # Set default values in case the insight info is empty
        date = yesterdayslash
        accountid = ad[AdsInsights.Field.account_id]
        accountname = ""
        adid = ""
        adname = ""
        adsetid = ""
        adsetname = ""
        campaignid = ""
        campaignname = ""
        costperoutboundclick = ""
        outboundclicks = ""
        spend = ""

        # Set values from insight data
        if ('account_id' in ad) :
            accountid = ad[AdsInsights.Field.account_id]
        if ('account_name' in ad) :
            accountname = ad[AdsInsights.Field.account_name]
        if ('ad_id' in ad) :
            adid = ad[AdsInsights.Field.ad_id]
        if ('ad_name' in ad) :
            adname = ad[AdsInsights.Field.ad_name]
        if ('adset_id' in ad) :
            adsetid = ad[AdsInsights.Field.adset_id]
        if ('adset_name' in ad) :
            adsetname = ad[AdsInsights.Field.adset_name]
        if ('campaign_id' in ad) :
            campaignid = ad[AdsInsights.Field.campaign_id]
        if ('campaign_name' in ad) :
            campaignname = ad[AdsInsights.Field.campaign_name]
        if ('cost_per_outbound_click' in ad) : # This is stored strangely, takes a few steps to break through the layers
            costperoutboundclicklist = ad[AdsInsights.Field.cost_per_outbound_click]
            costperoutboundclickdict = costperoutboundclicklist[0]
            costperoutboundclick = costperoutboundclickdict.get('value')
        if ('outbound_clicks' in ad) : # This is stored strangely, takes a few steps to break through the layers
            outboundclickslist = ad[AdsInsights.Field.outbound_clicks]
            outboundclicksdict = outboundclickslist[0]
            outboundclicks = outboundclicksdict.get('value')
        if ('spend' in ad) :
            spend = ad[AdsInsights.Field.spend]

        # Write all ad info to the file, and increment the number of rows that will display
        filewriter.writerow([date, accountid, accountname, adid, adname, adsetid, adsetname, campaignid, campaignname, costperoutboundclick, outboundclicks, spend])
        rows += 1


# Print report
print (str(rows) + " rows added to the file " + filename)

I then have a php script that takes the csv file and uploads it to my database. The key is pulling all the insight data in one big yank. You can then break it up however you want because each ad has information about its adset, adaccount, and campaign.