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b7f8fbe630
* fix darkpool api * fix typo * add default params on RSI ta * fix ta models for stocks api * fix ta models for stocks api * improve API * improve API * test_finbrain updated * fix finbrain model api * ba controller * improve API * minor improvs to API * a newly fantastic equity report * fixed image issue * add help to tier in finra command * make export to default to False for API use * remove ipynb_checkpoints * remove extra file Co-authored-by: jose-donato <zmcdonato@gmail.com> Co-authored-by: Theodore Aptekarev <aptekarev@gmail.com>
118 lines
3.3 KiB
Python
118 lines
3.3 KiB
Python
"""Twitter Model"""
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__docformat__ = "numpy"
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import logging
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from typing import Optional
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import pandas as pd
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import requests
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from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
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from openbb_terminal import config_terminal as cfg
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from openbb_terminal.decorators import log_start_end
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from openbb_terminal.helper_funcs import clean_tweet, get_data
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from openbb_terminal.rich_config import console
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logger = logging.getLogger(__name__)
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analyzer = SentimentIntensityAnalyzer()
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@log_start_end(log=logger)
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def load_analyze_tweets(
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ticker: str,
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count: int = 100,
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start_time: Optional[str] = "",
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end_time: Optional[str] = "",
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) -> pd.DataFrame:
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"""Load tweets from twitter API and analyzes using VADER
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Parameters
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----------
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ticker: str
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Ticker to search twitter for
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count: int
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Number of tweets to analyze
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start : Optional[str]
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If given, the start time to get tweets from
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end : Optional[str]
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If given, the end time to get tweets from
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Returns
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-------
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df_tweet: pd.DataFrame
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Dataframe of tweets and sentiment
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"""
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params = {
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"query": rf"(\${ticker}) (lang:en)",
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"max_results": str(count),
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"tweet.fields": "created_at,lang",
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}
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if start_time:
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# Assign from and to datetime parameters for the API
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params["start_time"] = start_time
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if end_time:
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params["end_time"] = end_time
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# Request Twitter API
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response = requests.get(
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"https://api.twitter.com/2/tweets/search/recent",
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params=params, # type: ignore
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headers={"authorization": "Bearer " + cfg.API_TWITTER_BEARER_TOKEN},
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)
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# Create dataframe
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df_tweets = pd.DataFrame()
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# Check that the API response was successful
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if response.status_code == 200:
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for tweet in response.json()["data"]:
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row = get_data(tweet)
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df_tweets = df_tweets.append(row, ignore_index=True)
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elif response.status_code == 401:
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console.print("Twitter API Key provided is incorrect\n")
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return pd.DataFrame()
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elif response.status_code == 400:
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console.print(
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"""
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Status Code 400.
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This means you are requesting data from beyond the API's 7 day limit"""
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)
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return pd.DataFrame()
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elif response.status_code == 403:
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console.print(
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f"""
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Status code 403.
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It seems you're twitter credentials are invalid - {response.text}
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"""
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)
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return pd.DataFrame()
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else:
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console.print(
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f"""
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Status code {response.status_code}.
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Something went wrong - {response.text}
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"""
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)
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return pd.DataFrame()
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sentiments = []
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pos = []
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neg = []
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neu = []
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for s_tweet in df_tweets["text"].to_list():
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tweet = clean_tweet(s_tweet, ticker)
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sentiments.append(analyzer.polarity_scores(tweet)["compound"])
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pos.append(analyzer.polarity_scores(tweet)["pos"])
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neg.append(analyzer.polarity_scores(tweet)["neg"])
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neu.append(analyzer.polarity_scores(tweet)["neu"])
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# Add sentiments to tweets dataframe
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df_tweets["sentiment"] = sentiments
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df_tweets["positive"] = pos
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df_tweets["negative"] = neg
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df_tweets["neutral"] = neu
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return df_tweets
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