corrects some mistakes

This commit is contained in:
Michael Beck
2023-06-23 18:09:09 +02:00
parent 1b43b295ce
commit b00f75e9fe
2 changed files with 20 additions and 14 deletions

View File

@ -1,7 +1,9 @@
from datetime import datetime, time
import pandas as pd
import snscrape.modules.twitter as sntwitter
def scrapeTweets(handle, slice_data, keywords, td, tweetDFColumns, maxTweets = 5000):
from datetime import datetime, time
import pandas as pd
import snscrape.modules.twitter as sntwitter
i = 0
currentTime = datetime.now
ts_beg = slice_data['beg_time']
@ -18,17 +20,19 @@ def scrapeTweets(handle, slice_data, keywords, td, tweetDFColumns, maxTweets = 5
# Snscrape query:
query = f'from:{handle} since:{ts_beg} until:{ts_end}'
for i,tweet in enumerate(sntwitter.TwitterSearchScraper(query).get_items()):
if i>maxTweets:
if i >= maxTweets:
break
# get tweet vars from tweetDFColumns and append to singleTweetList
# which will then be appended to TweetList. TweetList contains all tweets of the current slice.
singleTweetList = [singleTweetList.append(eval(f'tweet.{col}')) for col in tweetDFColumns]
TweetList.append(singleTweetList)
# Check if no tweets fetched for the current time slice. If there are no tweets, skip to next time_slices loop iteration
if TweetList:
if not TweetList:
open(tweetDataFilePath, 'a').close()
print(f'return empty in {handle}{suffix} - from {ts_beg} to {ts_end}')
return
print(f'{i:<6} tweets scraped for: {handle:>15}{suffix:<7}')
# convert to dataframe
@ -36,7 +40,9 @@ def scrapeTweets(handle, slice_data, keywords, td, tweetDFColumns, maxTweets = 5
## Check if tweet-text contains keyword
tweet_df['contains_keyword'] = ''
tweet_df['contains_keyword'] = (tweet_df['rawContent'].str.findall('|'.join(keywords)).str.join(',').replace('', 'none'))
tweet_df['contains_keyword'] = (
tweet_df['rawContent'].str.findall('|'.join(keywords)).str.join(',').replace('', 'none')
)
## Save two versions of the dataset, one with all fields and one without dict fields
# define filepaths
csv_path = tweetDataFilePath