1.The api: stream.filter(). I read the documentation which said that all parameters can be optional. However, when I left it empty, it won't work.
Still the question with api. It is said that if I write code like below:
twitter_stream.filter(locations = [-180,-90, 180, 90])
It can filter all tweets with geological information. However, when I check the json data, I still find many tweets, the value of their attribute geo are still null.
3.I tried to use stream to get as many tweets as possible. However, it is said that it can get tweets in real time. will there be any parameters to set the time
like to collect tweets from 2013 to 2015
4.I tried to collect data through users and their followers and continue the same step until I get as many tweets as I want. So my code is like below:
import tweepy
import chardet
import json
import sys
#set one global list to store all user_names
users_unused = ["Raithan8"]
users_used = []
def process_or_store(tweet):
print(json.dumps(tweet))
consumer_key =
consumer_secret =
access_token =
access_token_secret =
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth, wait_on_rate_limit=True)
def getAllTweets():
#initialize one empty list tw store all tweets
screen_name = users_unused[0]
users_unused.remove(screen_name)
users_used.append(screen_name)
print("this is the current user: " + screen_name)
for friend in tweepy.Cursor(api.friends, screen_name = screen_name).items():
if friend not in users_unused and friend not in users_used:
users_unused.append(friend.screen_name)
for follower in tweepy.Cursor(api.followers, screen_name = screen_name).items():
if follower not in users_unused and follower not in users_used:
users_unused.append(follower.screen_name)
print(users_unused)
print(users_used)
alltweets = []
#tweepy limits at most 200 tweets each time
new_tweets = api.user_timeline(screen_name = screen_name, count = 200)
alltweets.extend(new_tweets)
if not alltweets:
return alltweets
oldest = alltweets[-1].id - 1
while(len(new_tweets) <= 0):
new_tweets = api.user_timeline(screen_name = screen_name, count = 200, max_id = oldest)
alltweets.extend(new_tweets)
oldest = alltweets[-1].id - 1
return alltweets
def storeTweets(alltweets, file_name = "tweets.json"):
for tweet in alltweets:
json_data = tweet._json
data = json.dumps(tweet._json)
with open(file_name, "a") as f:
if json_data['geo'] is not None:
f.write(data)
f.write("\n")
if __name__ == "__main__":
while(1):
if not users_unused:
break
storeTweets(getAllTweets())
I don't why it runs so slow. Maybe it is mainly because I initialize tweepy API as below
api = tweepy.API(auth, wait_on_rate_limit=True)
But if I don't initialize it in this way, it will raise error below：
raise RateLimitError(error_msg, resp)
tweepy.error.RateLimitError: [{'message': 'Rate limit exceeded', 'code': 88}]
2) There's a difference between a tweet with coordinates and filtering by location.
Filtering by location means that the sender is located in the range of your filter. If you set it globally twitter_stream.filter(locations = [-180,-90, 180, 90]) it will return tweets for people who set their country name in their preferences.
If you need to filter by coordinates (a tweet that has a coordinates) you can take a look at my blog post. But basically you need to set a listener and then check if the tweet have some coordinates.
3 and 4) Twitter's Search API and Twitter's Streaming API are different in many ways and restrictions about rate limits (Tweepy) and Twitter rate limit.
You have a limitation about how many tweets you want to get (in the past).
Check again Tweepy API because wait_on_rate_limit set as true just wait that your current limit window is available again. That's why it's "slow" as you said.
However using streaming API doesn't have such restrictions.
Related
I am trying to extract tweets that include a specific hashtag(#nike) and I have essential level access(Twitter developer account). I only want to collect 100 tweets. Help, please! Thank you!
I keep getting this error:
Forbidden Traceback (most recent call last)
Forbidden: 403 Forbidden
453 - You currently have Essential access which includes access to Twitter API v2 endpoints only. If you need access to this endpoint, you’ll need to apply for Elevated access via the Developer Portal. You can learn more here: https://developer.twitter.com/en/docs/twitter-api/getting-started/about-twitter-api#v2-access-leve
import tweepy
# function to display data of each tweet
def printtweetdata(n, ith_tweet):
print()
print(f"Tweet {n}:")
print(f"Username:{ith_tweet[0]}")
print(f"Description:{ith_tweet[1]}")
print(f"Location:{ith_tweet[2]}")
print(f"Following Count:{ith_tweet[3]}")
print(f"Follower Count:{ith_tweet[4]}")
print(f"Total Tweets:{ith_tweet[5]}")
print(f"Retweet Count:{ith_tweet[6]}")
print(f"Tweet Text:{ith_tweet[7]}")
print(f"Hashtags Used:{ith_tweet[8]}")
# function to perform data extraction
def scrape(words, date_since, numtweet):
# Creating DataFrame using pandas
db = pd.DataFrame(columns=['username',
'description',
'location',
'following',
'followers',
'totaltweets',
'retweetcount',
'text',
'hashtags'])
# We are using .Cursor() to search
# through twitter for the required tweets.
# The number of tweets can be
# restricted using .items(number of tweets)
tweets = tweepy.Cursor(api.search_tweets,
words, lang="en",
since_id=date_since,
tweet_mode='extended').items(numtweet)
# .Cursor() returns an iterable object. Each item in
# the iterator has various attributes
# that you can access to
# get information about each tweet
list_tweets = [tweet for tweet in tweets]
# Counter to maintain Tweet Count
i = 1
# we will iterate over each tweet in the
# list for extracting information about each tweet
for tweet in list_tweets:
username = tweet.user.screen_name
description = tweet.user.description
location = tweet.user.location
following = tweet.user.friends_count
followers = tweet.user.followers_count
totaltweets = tweet.user.statuses_count
retweetcount = tweet.retweet_count
hashtags = tweet.entities['hashtags']
# Retweets can be distinguished by
# a retweeted_status attribute,
# in case it is an invalid reference,
# except block will be executed
try:
text = tweet.retweeted_status.full_text
except AttributeError:
text = tweet.full_text
hashtext = list()
for j in range(0, len(hashtags)):
hashtext.append(hashtags[j]['text'])
# Here we are appending all the
# extracted information in the DataFrame
ith_tweet = [username, description,
location, following,
followers, totaltweets,
retweetcount, text, hashtext]
db.loc[len(db)] = ith_tweet
# Function call to print tweet data on screen
printtweetdata(i, ith_tweet)
i = i+1
filename = 'scraped_tweets.csv'
# we will save our database as a CSV file.
db.to_csv(filename)
if __name__ == '__main__':
# Enter your own credentials obtained
# from your developer account
consumer_key = ""
consumer_secret = ""
access_key = ""
access_secret = ""
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_key, access_secret)
api = tweepy.API(auth)
# Enter Hashtag and initial date
print("#nike")
words = input("#nike")
print("2022-01-01")
date_since = input("2022-01-01")
# number of tweets you want to extract in one run
numtweet = 10
scrape(words, date_since, numtweet)
print('Scraping has completed!')```
Through the basic Academic Research Developer Account, I'm using the Tweepy API to collect tweets containing specified keywords or hashtags. This enables me to collect 10,000,000 tweets per month. Using the entire archive search, I'm trying to collect tweets from one whole calendar date at a time. I've gotten a rate limit error (despite the wait_on_rate_limit flag being set to true) Now there's an error with the request limit.
here is the code
import pandas as pd
import tweepy
# function to display data of each tweet
def printtweetdata(n, ith_tweet):
print()
print(f"Tweet {n}:")
print(f"Username:{ith_tweet[0]}")
print(f"tweet_ID:{ith_tweet[1]}")
print(f"userID:{ith_tweet[2]}")
print(f"creation:{ith_tweet[3]}")
print(f"location:{ith_tweet[4]}")
print(f"Total Tweets:{ith_tweet[5]}")
print(f"likes:{ith_tweet[6]}")
print(f"retweets:{ith_tweet[7]}")
print(f"hashtag:{ith_tweet[8]}")
# function to perform data extraction
def scrape(words, numtweet, since_date, until_date):
# Creating DataFrame using pandas
db = pd.DataFrame(columns=['username', 'tweet_ID', 'userID',
'creation', 'location', 'text','likes','retweets', 'hashtags'])
# We are using .Cursor() to search through twitter for the required tweets.
# The number of tweets can be restricted using .items(number of tweets)
tweets = tweepy.Cursor(api.search_full_archive,'research',query=words,
fromDate=since_date, toDate=until_date).items(numtweet)
# .Cursor() returns an iterable object. Each item in
# the iterator has various attributes that you can access to
# get information about each tweet
list_tweets = [tweet for tweet in tweets]
# Counter to maintain Tweet Count
i = 1
# we will iterate over each tweet in the list for extracting information about each tweet
for tweet in list_tweets:
username = tweet.user.screen_name
tweet_ID = tweet.id
userID= tweet.author.id
creation = tweet.created_at
location = tweet.user.location
likes = tweet.favorite_count
retweets = tweet.retweet_count
hashtags = tweet.entities['hashtags']
# Retweets can be distinguished by a retweeted_status attribute,
# in case it is an invalid reference, except block will be executed
try:
text = tweet.retweeted_status.full_text
except AttributeError:
text = tweet.text
hashtext = list()
for j in range(0, len(hashtags)):
hashtext.append(hashtags[j]['text'])
# Here we are appending all the extracted information in the DataFrame
ith_tweet = [username, tweet_ID, userID,
creation, location, text, likes,retweets,hashtext]
db.loc[len(db)] = ith_tweet
# Function call to print tweet data on screen
printtweetdata(i, ith_tweet)
i = i+1
filename = 'C:/Users/USER/Desktop/الجامعة الالمانية/output/twitter.csv'
# we will save our database as a CSV file.
db.to_csv(filename)
if __name__ == '__main__':
consumer_key = "####"
consumer_secret = "###"
access_token = "###"
access_token_secret = "###"
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
api = tweepy.API(auth,wait_on_rate_limit=True)
since_date = '200701010000'
until_date = '202101012359'
words = "#USA"
# number of tweets you want to extract in one run
numtweet = 1000
scrape(words, numtweet, since_date, until_date)
print('Scraping has completed!')
I got this error:
TooManyRequests: 429 Too Many Requests
Request exceeds account’s current package request limits. Please upgrade your package and retry or contact Twitter about enterprise access.
Unfortunately, I believe this is due to the Sandbox quota. For a premium account it would be more.
Tweepy API Documentation
You may check out this answer here - Limit
I am using code which is working fine. I have added the whole code as taken from geeks for geeks. But I want to modify it to add referenced_tweets.type. I am new to APIs and really want to understand how to fix this.
import pandas as pd
import tweepy
# function to display data of each tweet
def printtweetdata(n, ith_tweet):
print()
print(f"Tweet {n}:")
print(f"Username:{ith_tweet[0]}")
print(f"likes:{ith_tweet[1]}")
print(f"Location:{ith_tweet[2]}")
print(f"Following Count:{ith_tweet[3]}")
print(f"Follower Count:{ith_tweet[4]}")
print(f"Total Tweets:{ith_tweet[5]}")
print(f"Retweet Count:{ith_tweet[6]}")
print(f"Tweet Text:{ith_tweet[7]}")
print(f"Hashtags Used:{ith_tweet[8]}")
# function to perform data extraction
def scrape(words, date_since, numtweet):
# Creating DataFrame using pandas
db = pd.DataFrame(columns=['username', 'likes', 'location', 'following',
'followers', 'totaltweets', 'retweetcount', 'text', 'hashtags'])
# We are using .Cursor() to search through twitter for the required tweets.
# The number of tweets can be restricted using .items(number of tweets)
tweets = tweepy.Cursor(api.search, q=words, lang="en",
since=date_since, tweet_mode='extended').items(numtweet)
# .Cursor() returns an iterable object. Each item in
# the iterator has various attributes that you can access to
# get information about each tweet
list_tweets = [tweet for tweet in tweets]
# Counter to maintain Tweet Count
i = 1
# we will iterate over each tweet in the list for extracting information about each tweet
for tweet in list_tweets:
username = tweet.user.screen_name
likes = tweet.favorite_count
location = tweet.user.location
following = tweet.user.friends_count
followers = tweet.user.followers_count
totaltweets = tweet.user.statuses_count
retweetcount = tweet.retweet_count
hashtags = tweet.entities['hashtags']
# Retweets can be distinguished by a retweeted_status attribute,
# in case it is an invalid reference, except block will be executed
try:
text = tweet.retweeted_status.full_text
except AttributeError:
text = tweet.full_text
hashtext = list()
for j in range(0, len(hashtags)):
hashtext.append(hashtags[j]['text'])
# Here we are appending all the extracted information in the DataFrame
ith_tweet = [username, likes, location, following,
followers, totaltweets, retweetcount, text, hashtext]
db.loc[len(db)] = ith_tweet
# Function call to print tweet data on screen
printtweetdata(i, ith_tweet)
i = i+1
filename = 'etihad.csv'
# we will save our database as a CSV file.
db.to_csv(filename)
if __name__ == '__main__':
# Enter your own credentials obtained
# from your developer account
consumer_key =
consumer_secret =
access_key =
access_secret =
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_key, access_secret)
api = tweepy.API(auth)
# Enter Hashtag and initial date
print("Enter Twitter HashTag to search for")
words = input()
print("Enter Date since The Tweets are required in yyyy-mm--dd")
date_since = input()
# number of tweets you want to extract in one run
numtweet = 100
scrape(words, date_since, numtweet)
print('Scraping has completed!')
I now want to add referenced_tweets.type in order to get if the Tweet is a Retweet or not but I'm not sure how to do it. Can someone help?
API.search uses the standard search API, part of Twitter API v1.1.
referenced_tweets is a value that can be set for tweet.fields, a Twitter API v2 fields parameter.
Currently, if you want to use Twitter API v2 through Tweepy, you'll have to use the development version of Tweepy on the master branch and its Client class. Otherwise, you'll need to wait until Tweepy v4.0 is released.
Alternatively, if your only goal is to determine whether a Status/Tweet object is a Retweet or not, you can simply check for the retweeted_status attribute.
I am trying to extract tweet locations from a specific area with python using tweepy + writing it into a csv-file.
I am not very much into python but I could manage to put together the following sript which kind of works:
import json
from tweepy import Stream
from tweepy import OAuthHandler
from tweepy.streaming import StreamListener
#Enter Twitter API Key information
consumer_key = 'cons_key'
consumer_secret = 'cons_secret'
access_token = 'acc_token'
access_secret = 'acc-secret'
file = open("C:\Python27\Output2.csv", "w")
file.write("X,Y\n")
data_list = []
count = 0
class listener(StreamListener):
def on_data(self, data):
global count
#How many tweets you want to find, could change to time based
if count <= 100:
json_data = json.loads(data)
coords = json_data["coordinates"]
if coords is not None:
print coords["coordinates"]
lon = coords["coordinates"][0]
lat = coords["coordinates"][1]
data_list.append(json_data)
file.write(str(lon) + ",")
file.write(str(lat) + "\n")
count += 1
return True
else:
file.close()
return False
def on_error(self, status):
print status
auth = OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_secret)
twitterStream = Stream(auth, listener())
#What you want to search for here
twitterStream.filter(locations=[11.01,47.85,12.09,48.43])
the problem is, that it extracts the coordinates very slowly (like 10 entries per 30 minutes). Would there be a way to make this faster?
How can I add the timestamps for each tweet?
Is there way to make sure to retrieve all tweets possible for the specific region (I guess the max is all tweets of the past week)?
thanks very much in advance!
Twitter’s standard streaming API provides a 1% sample of all the Tweets posted. In addition, very few Tweets have location data added to them. So, I’m not surprised that you’re only getting a small number of Tweets in a 30 minute timespan for one specific bounding box. The only way to improve the volume would be to pay for the enterprise PowerTrack API.
Tweets all contain a created_at value which is the time stamp you’ll want to record.
seems that with tweepy I can get only 200 tweets using user_timeline method.
class Twitter_User():
def __init__(self,id,count=200):
self.id = id
self.count = count
self.data = None
def get_tweets(self):
store_tweets = api.user_timeline(self.id, count=self.count)
simple_list = []
for status in store_tweets:
array = [status._json["text"].strip(), status._json["favorite_count"], status._json["created_at"],status._json["retweet_count"],[h["text"] for h in status._json["entities"]["hashtags"]]]
simple_list.append(array)
self.data = pd.DataFrame(simple_list, columns=["Text", "Like", "Created at","Retweet","Hashtags"])
self.data = self.data[~self.data["Text"].str.startswith('RT')]
return self.data
def __repr__(self):
id = api.get_user(self.id)
return id.screen_name
If I put as self.count a number bigger than 200, I always will get a dataframe with 200 rows, instead if I put a smaller number, I get the correct amount of rows. I don't know, there is a limit or I have to use some other method?
You can only get a maximum of 200 tweets in one request. However, you can make successive requests for older tweets. The maximum number of tweets that you can get in a timeline is 3200. The reference is here.
You can do this with tweepy but you will need to tweepy's Cursor get these successive pages of tweets. Look at this to get you started.
To get more then 200, you need to use the cursor on user_timeline and then iterate over the pages.
import tweepy
# Consumer keys and access tokens, used for OAuth
consumer_key = ''
consumer_secret = ''
access_token = ''
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)
# Creation of the actual interface, using authentication
api = tweepy.API(auth)
for pages in tweepy.Cursor(api.user_timeline, id='id', count=200).pages():
print(pages)
According to the Twitter API docs the most records you can retrieve from /statuses/user_timeline/ is 200
From the definition of the count parameter:
Specifies the number of Tweets to try and retrieve, up to a maximum of 200 per distinct request. The value of count is best thought of as a limit to the number of Tweets to return because suspended or deleted content is removed after the count has been applied. We include retweets in the count, even if include_rts is not supplied. It is recommended you always send include_rts=1 when using this API method.
And from the tweepy source code in api.py line 114:
#property
def user_timeline(self):
""" :reference: https://dev.twitter.com/rest/reference/get/statuses/user_timeline
:allowed_param:'id', 'user_id', 'screen_name', 'since_id', 'max_id', 'count', 'include_rts'
"""
return bind_api(
api=self,
path='/statuses/user_timeline.json',
payload_type='status', payload_list=True,
allowed_param=['id', 'user_id', 'screen_name', 'since_id',
'max_id', 'count', 'include_rts']
)
Use tweepy cursor,
#MuniLima is the tweeter account,
#The list which are empty initially, they start with the For loop. to store tweeter values:'create_at','favourite_count','text'
tweeteo=[]
likes=[]
time = []
for tuit in tweepy.Cursor(api.user_timeline,screen_name='MuniLima').items(2870):
time.append(tuit.created_at)
likes.append(tuit.favorite_count)
tweeteo.append(tuit.text)