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* Add separate view for finbrain for crypto curreny sentiment analysis * Move json with symbols to separate directory, little refactoring, update readme * Add screenshot of finbrain for PolkaDot * Add views for llama, defipulse * Add llama view with tvl chart * Add defipulse view * Add defi controller and move all defi views into defi module * Add defi controller to main controller * Add newsletters related to defi * Add defi docs
87 lines
2.4 KiB
Python
87 lines
2.4 KiB
Python
"""Substack model"""
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__docformat__ = "numpy"
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import textwrap
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import concurrent.futures
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import pandas as pd
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import requests
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from bs4 import BeautifulSoup
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from dateutil import parser
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def scrape_substack(url: str) -> list:
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"""Helper method to scrape newsletters from substack.
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[Source: substack.com]
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Parameters
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----------
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url: str
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Url to newsletter on substack domain.
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Returns
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-------
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list
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list of news from given newsletter
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"""
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req = requests.get(url)
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soup = BeautifulSoup(req.text, features="lxml")
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results = []
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posts = soup.find("div", class_="portable-archive-list").find_all(
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"div", class_="post-preview portable-archive-post has-image has-author-line"
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)
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for post in posts:
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title, url, time = (
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post.a.text,
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post.a["href"],
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post.find("time").get("datetime"),
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)
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results.append([title, url, time])
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return results
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def get_newsletters() -> pd.DataFrame:
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"""Scrape all substack newsletters from url list.
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[Source: substack.com]
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Returns
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-------
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pd.DataFrame
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DataFrame with recent news from most popular DeFi related newsletters.
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"""
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urls = [
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"https://defiweekly.substack.com/archive",
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"https://newsletter.thedefiant.io/archive",
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"https://thedailygwei.substack.com/archive",
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"https://todayindefi.substack.com/archive",
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"https://newsletter.banklesshq.com/archive",
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"https://defislate.substack.com/archive",
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]
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threads = len(urls)
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newsletters = []
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with concurrent.futures.ThreadPoolExecutor(max_workers=threads) as executor:
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for newsletter in executor.map(scrape_substack, urls):
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try:
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newsletters.append(pd.DataFrame(newsletter))
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except KeyError as e:
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print(e, "\n")
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continue
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df = pd.concat(newsletters, ignore_index=True)
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df.columns = ["Title", "Link", "Date"]
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df["Title"] = df["Title"].apply(lambda x: "".join(i for i in x if ord(i) < 128))
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df["Date"] = df["Date"].apply(
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lambda x: parser.parse(x).strftime("%Y-%m-%d %H:%M:%S")
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)
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df["Title"] = df["Title"].apply(
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lambda x: "\n".join(textwrap.wrap(x, width=50)) if isinstance(x, str) else x
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)
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return (
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df[["Title", "Date", "Link"]]
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.sort_values(by="Date", ascending=False)
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.reset_index(drop="index")
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)
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