Confused by a python type errror – Twitter API

I’ve been using python for a little while and have made some improvements but this a new error to me. I’m trying to learn social media analysis for my career and that’s why I am trying out this set of code here.

I’ve de bugged one error but this one, which appears at line 81, has got me stumped as I can’t see why the function “def get_user_objects(follower_ids):” returns none and what i’d need to change it in accordance with previous advice on other questions here.

Here’s script to that point for simplicity. All help appreciated.

The error, to repeat is TypeError: object of type ‘NoneType’ has no len()

from tweepy import OAuthHandler
from tweepy import API
from collections import Counter
from datetime import datetime, date, time, timedelta
import sys
import json
import os
import io
import re
import time

# Helper functions to load and save intermediate steps
def save_json(variable, filename):
    with io.open(filename, "w", encoding="utf-8") as f:
        f.write(str(json.dumps(variable, indent=4, ensure_ascii=False)))

def load_json(filename):
    ret = None
    if os.path.exists(filename):
        try:
            with io.open(filename, "r", encoding="utf-8") as f:
                ret = json.load(f)
        except:
            pass
    return ret

def try_load_or_process(filename, processor_fn, function_arg):
    load_fn = None
    save_fn = None
    if filename.endswith("json"):
        load_fn = load_json
        save_fn = save_json
    else:
        load_fn = load_bin
        save_fn = save_bin
    if os.path.exists(filename):
        print("Loading " + filename)
        return load_fn(filename)
    else:
        ret = processor_fn(function_arg)
        print("Saving " + filename)
        save_fn(ret, filename)
        return ret

# Some helper functions to convert between different time formats and 
perform date calculations
def twitter_time_to_object(time_string):
    twitter_format = "%a %b %d %H:%M:%S %Y"
    match_expression = "^(.+)s(+[0-9][0-9][0-9][0-9])s([0-9][0-9][0-9] 
[09])$"
    match = re.search(match_expression, time_string)
    if match is not None:
        first_bit = match.group(1)
        second_bit = match.group(2)
        last_bit = match.group(3)
        new_string = first_bit + " " + last_bit
        date_object = datetime.strptime(new_string, twitter_format)
        return date_object

def time_object_to_unix(time_object):
    return int(time_object.strftime("%s"))

def twitter_time_to_unix(time_string):
    return time_object_to_unix(twitter_time_to_object(time_string))

def seconds_since_twitter_time(time_string):
    input_time_unix = int(twitter_time_to_unix(time_string))
    current_time_unix = int(get_utc_unix_time())
    return current_time_unix - input_time_unix

def get_utc_unix_time():
    dts = datetime.utcnow()
    return time.mktime(dts.timetuple())

# Get a list of follower ids for the target account
def get_follower_ids(target):
    return auth_api.followers_ids(target)

# Twitter API allows us to batch query 100 accounts at a time
# So we'll create batches of 100 follower ids and gather Twitter User 
objects for each batch
def get_user_objects(follower_ids):
    batch_len = 100
    num_batches = len(follower_ids)/100
    batches = (follower_ids[i:i+batch_len] for i in range(0, 
len(follower_ids), batch_len))
    all_data = []
    for batch_count, batch in enumerate(batches):
        sys.stdout.write("r")
        sys.stdout.flush()
        sys.stdout.write("Fetching batch: " + str(batch_count) + "/" + 
str(num_batches))
        sys.stdout.flush()
        users_list = auth_api.lookup_users(user_ids=batch)
        users_json = (map(lambda t: t._json, users_list))
        all_data += users_json
    return all_data
# Creates one week length ranges and finds items that fit into those range 
boundaries
def make_ranges(user_data, num_ranges=20):
range_max = 604800 * num_ranges
range_step = range_max/num_ranges

# We create ranges and labels first and then iterate these when going 
through the whole list
# of user data, to speed things up
ranges = {}
labels = {}
for x in range(num_ranges):
    start_range = x * range_step
    end_range = x * range_step + range_step
    label = "%02d" % x + " - " + "%02d" % (x+1) + " weeks"
    labels[label] = []
    ranges[label] = {}
    ranges[label]["start"] = start_range
    ranges[label]["end"] = end_range
for user in user_data:
    if "created_at" in user:
        account_age = seconds_since_twitter_time(user["created_at"])
        for label, timestamps in ranges.iteritems():
            if account_age > timestamps["start"] and account_age < 
timestamps["end"]:
                entry = {} 
                id_str = user["id_str"] 
                entry[id_str] = {} 
                fields = ["screen_name", "name", "created_at", 
"friends_count", "followers_count", "favourites_count", "statuses_count"] 
                for f in fields: 
                    if f in user: 
                        entry[id_str][f] = user[f] 
                labels[label].append(entry) 
return labels


if __name__ == "__main__": 
    account_list = [] 
    if (len(sys.argv) > 1):
        account_list = sys.argv[1:]

    if len(account_list) < 1:
        print("No parameters supplied. Exiting.")
        sys.exit(0)

    consumer_key="XXXXXXX"
    consumer_secret="XXXXXX"
    access_token="XXXXXXX"
    access_token_secret="XXXXXXXX"

    auth = OAuthHandler(consumer_key, consumer_secret)
    auth.set_access_token(access_token, access_token_secret)
    auth_api = API(auth)

    for target in account_list:
        print("Processing target: " + target)

# Get a list of Twitter ids for followers of target account and save it
        filename = target + "_follower_ids.json"
        follower_ids = try_load_or_process(filename, get_follower_ids, 
target)

# Fetch Twitter User objects from each Twitter id found and save the data
        filename = target + "_followers.json"
        user_objects = try_load_or_process(filename, get_user_objects, 
follower_ids)
        total_objects = len(user_objects)

# Record a few details about each account that falls between specified age 
ranges
        ranges = make_ranges(user_objects)
        filename = target + "_ranges.json"
        save_json(ranges, filename)

# Print a few summaries
        print
        print("ttFollower age ranges")
        print("tt===================")
        total = 0
        following_counter = Counter()
        for label, entries in sorted(ranges.iteritems()):
            print("tt" + str(len(entries)) + " accounts were created 
within " + label)
            total += len(entries)
            for entry in entries:
                for id_str, values in entry.iteritems():
                    if "friends_count" in values:
                        following_counter[values["friends_count"]] += 1
        print("ttTotal: " + str(total) + "/" + str(total_objects))
        print
        print("ttMost common friends counts")
        print("tt==========================")
        total = 0
        for num, count in following_counter.most_common(20):
            total += count
            print("tt" + str(count) + " accounts are following " + 
str(num) + " accounts")
        print("ttTotal: " + str(total) + "/" + str(total_objects))
        print
        print