Removed: obsolete parts.

README.rst

@@ -36,7 +36,6 @@ need to install dependencies you don't need. Therefore this library utilizes
 extras which install optional dependencies:
 
 * for Google trends - google
-* for Twitter scraping - twitter
 
 Usage
 -----
@@ -45,9 +44,7 @@ Usage
 .. code-block:: bash
 
    pip install karpet  # Basics only
-   pip install karpet[twitter]  # For Twitter scraping
    pip install karpet[google]  # For Google trends
-   pip install karpet[twitter,google]  # All features
 
 2. Import the library class first.
 
@@ -83,18 +80,6 @@ Retrieves exchange list.
     k.fetch_crypto_exchanges("nrg")
     ['DigiFinex', 'KuCoin', 'CryptoBridge', 'Bitbns', 'CoinExchange']
 
-.. fetch_tweets()
-.. ~~~~~~~~~~~~~~
-.. Retrieves twitter tweets.
-
-.. .. code-block:: python
-
-..     k = Karpet(date(2019, 1, 1), date(2019, 5, 1))
-..     df = k.fetch_tweets(kw_list=["bitcoin"], lang="en")  # Dataframe with tweets.
-..     df.head()
-
-.. .. image:: https://raw.githubusercontent.com/im-n1/karpet/master/assets/tweets.png
-
 fetch_google_trends()
 ~~~~~~~~~~~~~~~~~~~~~
 Retrieves Google Trends - in percents for the given date range.
@@ -216,6 +201,10 @@ available.
 Changelog
 ---------
 
+0.4.4
+~~~~~
+- remove obsolete parts of the code and some dependencies
+
 0.4.3
 ~~~~~
 - fixed ``get_basic_data()`` method (different data source)

karpet/core.py

@@ -1,6 +1,5 @@
 try:
     from pytrends.request import TrendReq
-    from twitterscraper import query_tweets
 except:
     pass
 
@@ -273,83 +272,6 @@ def fetch_google_trends(
 
         return df.sort_values("date").reset_index(drop=True)
 
-    # def fetch_tweets(self, kw_list, lang, limit=None):
-    #     """
-    #     Scrapes Twitter without any limits and  returns dataframe with the
-    #     following structure
-
-    #     * fullname
-    #     * id
-    #     * likes
-    #     * replies
-    #     * retweets
-    #     * text
-    #     * timestamp
-    #     * url
-    #     * user
-    #     * date
-    #     * has_link
-
-    #     :param list kw_list: List of keywords to search for. Will be joined with "OR" operator.
-    #     :param str lang: Language of tweets to search in.
-    #     :param int limit: Limit search results. Might get really big and slow so this should help.
-    #     :return: Pandas dataframe with all search results (tweets).
-    #     :rtype: pd.DataFrame
-    #     """
-
-    #     def process_tweets(tweets):
-    #         """
-    #         Cleans up tweets and returns dataframe with the
-    #         following structure
-
-    #         * fullname
-    #         * id
-    #         * likes
-    #         * replies
-    #         * retweets
-    #         * text
-    #         * timestamp
-    #         * url
-    #         * user
-    #         * date
-    #         * has_link
-
-    #         :param list tweets: List of dicts of tweets data.
-    #         :return: Returns dataframe with all the scraped tweets (no index).
-    #         :rtype: pd.DataFrame
-    #         """
-
-    #         # 1. Clean up.
-    #         data = []
-
-    #         for t in tweets:
-    #             d = t.__dict__
-    #             del d["html"]
-    #             data.append(d)
-
-    #         # 2. Create dataframe
-    #         df = pd.DataFrame(data)
-    #         # import pdb
-
-    #         # pdb.set_trace()
-    #         df["date"] = df["timestamp"].dt.date
-    #         df["has_link"] = df["text"].apply(
-    #             lambda text: "http://" in text or "https://" in text
-    #         )
-
-    #         return df
-
-    #     try:
-    #         _ = query_tweets
-    #     except NameError:
-    #         raise Exception("Twitter extension is not installed - see README file.")
-
-    #     tweets = query_tweets(
-    #         query=" OR ".join(kw_list), begindate=self.start, lang=lang, limit=limit
-    #     )
-
-    #     return process_tweets(tweets)
-
     def fetch_news(self, symbol, limit=10):
         """
         Fetches news of the given symbol. Each news contains

karpet/meta.py

@@ -1 +1 @@
-__version__ = "0.4.2"
+__version__ = "0.4.4"