def get_peers(ticker_symbol, page=None):
"""
Gets the list of Top Peers for a stock as listed on the "Premium Research: Industry Analysis" section
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param page: html tree structure based on the html markup of the scraped website
:return: a list of the Top Peers as listed on a stock's "Premium Research: Industry Analysis" section
on it's respective zacks page
"""
if page is None:
page = scrape_page(BASE_URL+ ticker_symbol)
peers = page.xpath(PEERS_XPATH)
if peers:
try:
peers.remove(ticker_symbol.upper())
except:
pass
if peers:
return peers
else:
return None
else:
return None
def get_bearish_sentiment(ticker_symbol, page=None):
"""
Gets the bearish sentiment of the target ticker symbol
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param page: html tree structure based on the html markup of the scraped website
:return: a string of the percentage of bearish sentiment as listed on a stock's StockTwits page
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
sentiment = page.xpath(BEARISH_SENTIMENT_XPATH)
if not sentiment:
return None
else:
return sentiment[0].replace("\n", "") + " Bearish"
def get_industry_rank(ticker_symbol, page=None):
"""
Gets the Zacks' Industry Rank of the target ticker symbol.
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param page: html tree structure based on the html markup of the scraped website
:return: a string of the industry rank
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
industry_rank = page.xpath(INDUSTRY_RANK_XPATH)
if not industry_rank:
return None
else:
return industry_rank[0]
def get_rating(ticker_symbol, page=None):
"""
Gets the Zack's Rank Rating of the target ticker symbol
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param page: html tree structure based on the html markup of the scraped website
:return: String of Zack's Rank Rating as listed on a stock's Zacks page
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
rating = page.xpath(RATING_XPATH)
if not rating:
return None
else:
return rating[0]
def get_bearish_sentiment(ticker_symbol, page=None):
"""
Gets the bearish sentiment of the target ticker symbol
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param page: html tree structure based on the html markup of the scraped website
:return: a string of the percentage of bearish sentiment as listed on a stock's StockTwits page
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
sentiment = page.xpath(BEARISH_SENTIMENT_XPATH)
if not sentiment:
return None
else:
return sentiment[0].replace("\n", "") + " Bearish"
def get_sentiment(ticker_symbol, page=None):
"""
Gets both the bullish and bearish sentiment of the target ticker symbol
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param page: html tree structure based on the html markup of the scraped website
:return: a tuple of strings containing both the bullish and bearish sentiment as listed on a stock's
StockTwits page
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
bullish_sentiment = get_bullish_sentiment(ticker_symbol, page)
if bullish_sentiment:
return bullish_sentiment, get_bearish_sentiment(ticker_symbol, page)
else:
return None
def get_style_scores(ticker_symbol, page=None):
"""
Gets the Zacks' Style Scores of the target ticker symbol. There are 4 score categories Value, Growth, Momentum
and VGM. Each category is given a grade from A - F.
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param page: html tree structure based on the html markup of the scraped website
:return: a dictionary containing all the Style Scores
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
scores = page.xpath(STYLE_SCORES_XPATH)
if not scores:
return None
else:
return dict(zip(STYLES, scores))
def get_sentiment(ticker_symbol, page=None):
"""
Gets both the bullish and bearish sentiment of the target ticker symbol
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param page: html tree structure based on the html markup of the scraped website
:return: a tuple of strings containing both the bullish and bearish sentiment as listed on a stock's
StockTwits page
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
bullish_sentiment = get_bullish_sentiment(ticker_symbol, page)
if bullish_sentiment:
return bullish_sentiment, get_bearish_sentiment(ticker_symbol, page)
else:
return None
def get_all_statistics(ticker_symbol, page=None):
"""
This function will get all the associated financial statistics from the correspoding finviz page
given the ticker symbol
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GGOG", "MSFT")
:param page: HTML tree structure based on the html markup of the scraped page. If one is not passed in the
function will scrape the page
:return: a dictionary of all the financial statistics listed on a stock's finviz page, otherwise None
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
table = get_statistics_table(page)
if table:
return table
else:
return None
def get_statistic(ticker_symbol, stat_name, page=None):
"""
This function will get the associated financial statistic from the corresponding finviz page given the
statistic's name and the ticker symbol
:param ticker_symbol: The ticker symbol of the interested stock (e.g., "AAPL", "GOOG", "MSFT")
:param stat_name: The name of the interested financial statistic (e.g., "P/E", "Price", "Volume").
An exhaustive list of available financial statistics can be found on a stock's finviz page
:param page: HTML tree structure based on the html markup of the scraped web page. If one is not passed in the
function will scrape the page
:return: the value of the interested financial statistic if it exists, otherwise None
"""
if page is None:
page = scrape_page(BASE_URL + ticker_symbol)
table = get_statistics_table(page)
if stat_name in table.keys() and table[stat_name]:
return table[stat_name]
else:
return None