General fixes

Added color, config file, moved packages into ./modules

.gitignore

@@ -3,4 +3,4 @@ test/
 .vscode/
 *.sqlite
 README.html
-*stocks.txt
+*-stocks.txt

Functions.py

@@ -1,5 +1,8 @@
 # Python file for general functions
 
+import sys
+sys.path.insert(0, './modules')
+
 def getNearest(items, pivot):
     return min(items, key=lambda x: abs(x - pivot))
 
@@ -52,14 +55,18 @@ def strintIsFloat(s):
 
 def fromCache(r):
     import requests_cache
+    from termcolor import colored, cprint
     if r.from_cache == True:
-        print('(Response taken from cache)')
+        cprint('(Response taken from cache)', 'white', attrs=['dark'])
     return
 
 
 def getJoke():
     import requests
+    import sys
+    from termcolor import colored, cprint
     import requests_cache
+    from halo import Halo
     with requests_cache.disabled():
         '''
         f = requests.get('https://official-joke-api.appspot.com/jokes/random').json()
@@ -69,9 +76,13 @@ def getJoke():
         '''
         headers = {'Accept': 'application/json',
                    'User-Agent': 'fund-indicators (https://github.com/andrewkdinh/fund-indicators)'}
-        f = requests.get('https://icanhazdadjoke.com/', headers=headers).json()
+        url = 'https://icanhazdadjoke.com'
+
+        cprint('Get: ' + url, 'white', attrs=['dark'])
+        with Halo(spinner='dots'):
+            f = requests.get('https://icanhazdadjoke.com/', headers=headers).json()
         print('')
-        print(f['joke'])
+        print(colored(f['joke'], 'green'))
 
 
 def hasNumbers(inputString):
@@ -127,6 +138,50 @@ def fileExists(file):
     import os.path
     return os.path.exists(file)
 
+def listIndexExists(i):
+    try:
+        i
+        return True
+    except IndexError:
+        return False
+
+def removeOutliers(i):
+    import statistics
+    m = statistics.median(i)
+    firstQ = []
+    thirdQ = []
+    for x in i:
+        if x < m:
+            firstQ.append(x)
+        elif x > m:
+            thirdQ.append(x)
+    firstQm = statistics.median(firstQ)
+    thirdQm = statistics.median(thirdQ)
+    iqr = (thirdQm - firstQm) * 1.5
+
+    goodList = []
+    badList = []
+    for x in i:
+        if x < (thirdQm + iqr) and x > (firstQm - iqr):
+            goodList.append(x)
+        else:
+            badList.append(x) # In case I want to know. If not, then I just make it equal to returnlist[0]
+    returnList = [goodList, badList, firstQm, m, thirdQm, iqr]
+    return returnList
+
+def validateJson(text):
+    import json
+    try:
+        json.loads(text)
+        return True
+    except ValueError:
+        return False
+
+def keyInDict(dict, key):
+    if key in dict:
+        return True
+    else:
+        return False
 
 def main():
     exit()

README.md

@@ -1,25 +1,45 @@
-# Mutual Fund Indicators
+# fund-indicators
 
 [![License](https://img.shields.io/github/license/andrewkdinh/fund-indicators.svg)](https://raw.githubusercontent.com/andrewkdinh/fund-indicators/master/LICENSE)
-![](https://img.shields.io/github/last-commit/andrewkdinh/fund-indicators.svg)
+[![](https://img.shields.io/github/last-commit/andrewkdinh/fund-indicators.svg)](https://github.com/andrewkdinh/fund-indicators/commits/master)
 ![](https://img.shields.io/github/languages/top/andrewkdinh/fund-indicators.svg)
 ![](https://img.shields.io/github/languages/code-size/andrewkdinh/fund-indicators.svg)
 
-A project to determine indicators of overperforming mutual funds.
+A project to determine relationships between mutual funds and different factors. 
 
-Examine correlation between performance and market capitalization, persistence, turnover, and expense ratios.
+Calculates relationships between: Previous performance, Alpha, Sharpe Ratio, Sortino Ratio
 
-## Prerequisites
+and Expense ratios, Turnover, Market Capitalization (Asset Size), Persistence
 
-`$ pip install -r requirements.txt`
+Give it a try at [repl.run](https://fund-indicators.andrewkdinh.repl.run) or [repl.it](https://repl.it/@andrewkdinh/fund-indicators)
+
+## Key Features
+
+- 100% automated
+- Uses multiple API's in case another fails
+- Caches http requests for future runs
+- Scrapes data from Yahoo Finance
+- Color-coded for easy viewing
+- Optional graphs to easily visualize linear regression results
+- A new joke every time it runs
 
 ## Quickstart
 
-To begin, run
+```shell
+pip install -r requirements.txt
+python main.py
+```
 
-`$ python main.py`
+Pre-chosen stocks listed in `stocks.txt`
 
-Some ticker values to try:
-SPY, VFINX, VTHR, DJIA
+## Credits
+
+This project uses a wide variety of open-source projects
+
+- [NumPy](https://github.com/numpy/numpy), [Termcolor](https://github.com/hfeeki/termcolor), [Beautiful Soup](https://launchpad.net/beautifulsoup), [yahoofinancials](https://github.com/JECSand/yahoofinancials), [requests-cache](https://github.com/reclosedev/requests-cache), [halo](https://github.com/manrajgrover/halo)
+
+And thank you to those that have helped me with the idea and product:
+
+- Amber Bruce, [Alex Stoykov](http://stoykov.us/), Doug Achterman, [Stack Overflow](https://stackoverflow.com)
 
 Created by Andrew Dinh from Dr. TJ Owens Gilroy Early College Academy

config.example.json

@@ -0,0 +1,63 @@
+{
+  "_comment": "Only use this if everything you know is correct",
+  "Config": {
+    "Check Packages": true,
+    "Check Python Version": true,
+    "Check Internet Connection": false,
+    "Get Joke": true,
+    "Benchmark": "SPY",
+    "Method": "Kiplinger",
+    "Time Frame": 60,
+    "Indicator": "Expense Ratio",
+    "Remove Outliers": true,
+    "Sources": [
+      "Alpha Vantage",
+      "Yahoo",
+      "IEX",
+      "Tiingo"
+    ]
+  },
+  "Possible Values": {
+    "Check Packages": [
+      true,
+      false
+    ],
+    "Check Python Version": [
+      true,
+      false
+    ],
+    "Check Internet Connection": [
+      true,
+      false
+    ],
+    "Get Joke": [
+      true,
+      false
+    ],
+    "Benchmark": [
+      "SPY",
+      "DJIA",
+      "VTHR",
+      "EFG"
+    ],
+    "Method": [
+      "Read",
+      "Manual",
+      "U.S. News",
+      "Kiplinger",
+      "TheStreet"
+    ],
+    "Time Frame": "Any integer",
+    "Indicator": [
+      "Expense Ratio",
+      "Market Capitalization",
+      "Turnover",
+      "Persistence"
+    ],
+    "Remove Outliers": [
+      true,
+      false
+    ],
+    "Sources": "Choose an order out of ['Alpha Vantage', 'Yahoo', 'IEX', 'Tiingo']"
+  }
+}

modules/termcolor.py

@@ -0,0 +1,168 @@
+# coding: utf-8
+# Copyright (c) 2008-2011 Volvox Development Team
+#
+# Permission is hereby granted, free of charge, to any person obtaining a copy
+# of this software and associated documentation files (the "Software"), to deal
+# in the Software without restriction, including without limitation the rights
+# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+# copies of the Software, and to permit persons to whom the Software is
+# furnished to do so, subject to the following conditions:
+#
+# The above copyright notice and this permission notice shall be included in
+# all copies or substantial portions of the Software.
+#
+# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+# THE SOFTWARE.
+#
+# Author: Konstantin Lepa <konstantin.lepa@gmail.com>
+
+"""ANSII Color formatting for output in terminal."""
+
+from __future__ import print_function
+import os
+
+
+__ALL__ = [ 'colored', 'cprint' ]
+
+VERSION = (1, 1, 0)
+
+ATTRIBUTES = dict(
+        list(zip([
+            'bold',
+            'dark',
+            '',
+            'underline',
+            'blink',
+            '',
+            'reverse',
+            'concealed'
+            ],
+            list(range(1, 9))
+            ))
+        )
+del ATTRIBUTES['']
+
+
+HIGHLIGHTS = dict(
+        list(zip([
+            'on_grey',
+            'on_red',
+            'on_green',
+            'on_yellow',
+            'on_blue',
+            'on_magenta',
+            'on_cyan',
+            'on_white'
+            ],
+            list(range(40, 48))
+            ))
+        )
+
+
+COLORS = dict(
+        list(zip([
+            'grey',
+            'red',
+            'green',
+            'yellow',
+            'blue',
+            'magenta',
+            'cyan',
+            'white',
+            ],
+            list(range(30, 38))
+            ))
+        )
+
+
+RESET = '\033[0m'
+
+
+def colored(text, color=None, on_color=None, attrs=None):
+    """Colorize text.
+
+    Available text colors:
+        red, green, yellow, blue, magenta, cyan, white.
+
+    Available text highlights:
+        on_red, on_green, on_yellow, on_blue, on_magenta, on_cyan, on_white.
+
+    Available attributes:
+        bold, dark, underline, blink, reverse, concealed.
+
+    Example:
+        colored('Hello, World!', 'red', 'on_grey', ['blue', 'blink'])
+        colored('Hello, World!', 'green')
+    """
+    if os.getenv('ANSI_COLORS_DISABLED') is None:
+        fmt_str = '\033[%dm%s'
+        if color is not None:
+            text = fmt_str % (COLORS[color], text)
+
+        if on_color is not None:
+            text = fmt_str % (HIGHLIGHTS[on_color], text)
+
+        if attrs is not None:
+            for attr in attrs:
+                text = fmt_str % (ATTRIBUTES[attr], text)
+
+        text += RESET
+    return text
+
+
+def cprint(text, color=None, on_color=None, attrs=None, **kwargs):
+    """Print colorize text.
+
+    It accepts arguments of print function.
+    """
+
+    print((colored(text, color, on_color, attrs)), **kwargs)
+
+
+if __name__ == '__main__':
+    print('Current terminal type: %s' % os.getenv('TERM'))
+    print('Test basic colors:')
+    cprint('Grey color', 'grey')
+    cprint('Red color', 'red')
+    cprint('Green color', 'green')
+    cprint('Yellow color', 'yellow')
+    cprint('Blue color', 'blue')
+    cprint('Magenta color', 'magenta')
+    cprint('Cyan color', 'cyan')
+    cprint('White color', 'white')
+    print(('-' * 78))
+
+    print('Test highlights:')
+    cprint('On grey color', on_color='on_grey')
+    cprint('On red color', on_color='on_red')
+    cprint('On green color', on_color='on_green')
+    cprint('On yellow color', on_color='on_yellow')
+    cprint('On blue color', on_color='on_blue')
+    cprint('On magenta color', on_color='on_magenta')
+    cprint('On cyan color', on_color='on_cyan')
+    cprint('On white color', color='grey', on_color='on_white')
+    print('-' * 78)
+
+    print('Test attributes:')
+    cprint('Bold grey color', 'grey', attrs=['bold'])
+    cprint('Dark red color', 'red', attrs=['dark'])
+    cprint('Underline green color', 'green', attrs=['underline'])
+    cprint('Blink yellow color', 'yellow', attrs=['blink'])
+    cprint('Reversed blue color', 'blue', attrs=['reverse'])
+    cprint('Concealed Magenta color', 'magenta', attrs=['concealed'])
+    cprint('Bold underline reverse cyan color', 'cyan',
+            attrs=['bold', 'underline', 'reverse'])
+    cprint('Dark blink concealed white color', 'white',
+            attrs=['dark', 'blink', 'concealed'])
+    print(('-' * 78))
+
+    print('Test mixing:')
+    cprint('Underline red on grey color', 'red', 'on_grey',
+            ['underline'])
+    cprint('Reversed green on red color', 'green', 'on_red', ['reverse'])
+

modules/yahoofinancials.py

@@ -0,0 +1,891 @@
+"""
+==============================
+The Yahoo Financials Module
+Version: 1.5
+==============================
+
+Author: Connor Sanders
+Email: sandersconnor1@gmail.com
+Version Released: 01/27/2019
+Tested on Python 2.7, 3.3, 3.4, 3.5, 3.6, and 3.7
+
+Copyright (c) 2019 Connor Sanders
+MIT License
+
+List of Included Functions:
+
+1) get_financial_stmts(frequency, statement_type, reformat=True)
+   - frequency can be either 'annual' or 'quarterly'.
+   - statement_type can be 'income', 'balance', 'cash'.
+   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
+2) get_stock_price_data(reformat=True)
+   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
+3) get_stock_earnings_data(reformat=True)
+   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
+4) get_summary_data(reformat=True)
+   - reformat optional value defaulted to true. Enter False for unprocessed raw data from Yahoo Finance.
+5) get_stock_quote_type_data()
+6) get_historical_price_data(start_date, end_date, time_interval)
+   - Gets historical price data for currencies, stocks, indexes, cryptocurrencies, and commodity futures.
+   - start_date should be entered in the 'YYYY-MM-DD' format. First day that financial data will be pulled.
+   - end_date should be entered in the 'YYYY-MM-DD' format. Last day that financial data will be pulled.
+   - time_interval can be either 'daily', 'weekly', or 'monthly'. Parameter determines the time period interval.
+
+Usage Examples:
+from yahoofinancials import YahooFinancials
+#tickers = 'AAPL'
+#or
+tickers = ['AAPL', 'WFC', 'F', 'JPY=X', 'XRP-USD', 'GC=F']
+yahoo_financials = YahooFinancials(tickers)
+balance_sheet_data = yahoo_financials.get_financial_stmts('quarterly', 'balance')
+earnings_data = yahoo_financials.get_stock_earnings_data()
+historical_prices = yahoo_financials.get_historical_price_data('2015-01-15', '2017-10-15', 'weekly')
+"""
+
+import sys
+import calendar
+import re
+from json import loads
+import time
+from bs4 import BeautifulSoup
+import datetime
+import pytz
+import random
+try:
+    from urllib import FancyURLopener
+except:
+    from urllib.request import FancyURLopener
+
+
+# track the last get timestamp to add a minimum delay between gets - be nice!
+_lastget = 0
+
+
+# Custom Exception class to handle custom error
+class ManagedException(Exception):
+    pass
+
+
+# Class used to open urls for financial data
+class UrlOpener(FancyURLopener):
+    version = 'Mozilla/5.0 (Windows; U; Windows NT 5.1; it; rv:1.8.1.11) Gecko/20071127 Firefox/2.0.0.11'
+
+
+# Class containing Yahoo Finance ETL Functionality
+class YahooFinanceETL(object):
+
+    def __init__(self, ticker):
+        self.ticker = ticker.upper() if isinstance(ticker, str) else [t.upper() for t in ticker]
+        self._cache = {}
+
+    # Minimum interval between Yahoo Finance requests for this instance
+    _MIN_INTERVAL = 7
+
+    # Meta-data dictionaries for the classes to use
+    YAHOO_FINANCIAL_TYPES = {
+        'income': ['financials', 'incomeStatementHistory', 'incomeStatementHistoryQuarterly'],
+        'balance': ['balance-sheet', 'balanceSheetHistory', 'balanceSheetHistoryQuarterly', 'balanceSheetStatements'],
+        'cash': ['cash-flow', 'cashflowStatementHistory', 'cashflowStatementHistoryQuarterly', 'cashflowStatements'],
+        'keystats': ['key-statistics'],
+        'history': ['history']
+    }
+
+    # Interval value translation dictionary
+    _INTERVAL_DICT = {
+        'daily': '1d',
+        'weekly': '1wk',
+        'monthly': '1mo'
+    }
+
+    # Base Yahoo Finance URL for the class to build on
+    _BASE_YAHOO_URL = 'https://finance.yahoo.com/quote/'
+
+    # private static method to get the appropriate report type identifier
+    @staticmethod
+    def get_report_type(frequency):
+        if frequency == 'annual':
+            report_num = 1
+        else:
+            report_num = 2
+        return report_num
+
+    # Public static method to format date serial string to readable format and vice versa
+    @staticmethod
+    def format_date(in_date):
+        if isinstance(in_date, str):
+            form_date = int(calendar.timegm(time.strptime(in_date, '%Y-%m-%d')))
+        else:
+            form_date = str((datetime.datetime(1970, 1, 1) + datetime.timedelta(seconds=in_date)).date())
+        return form_date
+
+    # Private Static Method to Convert Eastern Time to UTC
+    @staticmethod
+    def _convert_to_utc(date, mask='%Y-%m-%d %H:%M:%S'):
+        utc = pytz.utc
+        eastern = pytz.timezone('US/Eastern')
+        date_ = datetime.datetime.strptime(date.replace(" 0:", " 12:"), mask)
+        date_eastern = eastern.localize(date_, is_dst=None)
+        date_utc = date_eastern.astimezone(utc)
+        return date_utc.strftime('%Y-%m-%d %H:%M:%S %Z%z')
+
+    # Private method to scrape data from yahoo finance
+    def _scrape_data(self, url, tech_type, statement_type):
+        global _lastget
+        if not self._cache.get(url):
+            now = int(time.time())
+            if _lastget and now - _lastget < self._MIN_INTERVAL:
+                time.sleep(self._MIN_INTERVAL - (now - _lastget) + 1)
+                now = int(time.time())
+            _lastget = now
+            urlopener = UrlOpener()
+            # Try to open the URL up to 10 times sleeping random time if something goes wrong
+            max_retry = 10
+            for i in range(0, max_retry):
+                response = urlopener.open(url)
+                if response.getcode() != 200:
+                    time.sleep(random.randrange(10, 20))
+                else:
+                    response_content = response.read()
+                    soup = BeautifulSoup(response_content, "html.parser")
+                    re_script = soup.find("script", text=re.compile("root.App.main"))
+                    if re_script is not None:
+                        script = re_script.text
+                        self._cache[url] = loads(re.search("root.App.main\s+=\s+(\{.*\})", script).group(1))
+                        response.close()
+                        break
+                    else:
+                        time.sleep(random.randrange(10, 20))
+                if i == max_retry - 1:
+                    # Raise a custom exception if we can't get the web page within max_retry attempts
+                    raise ManagedException("Server replied with HTTP " + str(response.getcode()) +
+                                           " code while opening the url: " + str(url))
+        data = self._cache[url]
+        if tech_type == '' and statement_type != 'history':
+            stores = data["context"]["dispatcher"]["stores"]["QuoteSummaryStore"]
+        elif tech_type != '' and statement_type != 'history':
+            stores = data["context"]["dispatcher"]["stores"]["QuoteSummaryStore"][tech_type]
+        else:
+            stores = data["context"]["dispatcher"]["stores"]["HistoricalPriceStore"]
+        return stores
+
+    # Private static method to determine if a numerical value is in the data object being cleaned
+    @staticmethod
+    def _determine_numeric_value(value_dict):
+        if 'raw' in value_dict.keys():
+            numerical_val = value_dict['raw']
+        else:
+            numerical_val = None
+        return numerical_val
+
+    # Private method to format date serial string to readable format and vice versa
+    def _format_time(self, in_time):
+        form_date_time = datetime.datetime.fromtimestamp(int(in_time)).strftime('%Y-%m-%d %H:%M:%S')
+        utc_dt = self._convert_to_utc(form_date_time)
+        return utc_dt
+
+    # Private method to return the a sub dictionary entry for the earning report cleaning
+    def _get_cleaned_sub_dict_ent(self, key, val_list):
+        sub_list = []
+        for rec in val_list:
+            sub_sub_dict = {}
+            for k, v in rec.items():
+                if k == 'date':
+                    sub_sub_dict_ent = {k: v}
+                else:
+                    numerical_val = self._determine_numeric_value(v)
+                    sub_sub_dict_ent = {k: numerical_val}
+                sub_sub_dict.update(sub_sub_dict_ent)
+            sub_list.append(sub_sub_dict)
+        sub_ent = {key: sub_list}
+        return sub_ent
+
+    # Private method to process raw earnings data and clean
+    def _clean_earnings_data(self, raw_data):
+        cleaned_data = {}
+        earnings_key = 'earningsData'
+        financials_key = 'financialsData'
+        for k, v in raw_data.items():
+            if k == 'earningsChart':
+                sub_dict = {}
+                for k2, v2 in v.items():
+                    if k2 == 'quarterly':
+                        sub_ent = self._get_cleaned_sub_dict_ent(k2, v2)
+                    elif k2 == 'currentQuarterEstimate':
+                        numerical_val = self._determine_numeric_value(v2)
+                        sub_ent = {k2: numerical_val}
+                    else:
+                        sub_ent = {k2: v2}
+                    sub_dict.update(sub_ent)
+                dict_ent = {earnings_key: sub_dict}
+                cleaned_data.update(dict_ent)
+            elif k == 'financialsChart':
+                sub_dict = {}
+                for k2, v2, in v.items():
+                    sub_ent = self._get_cleaned_sub_dict_ent(k2, v2)
+                    sub_dict.update(sub_ent)
+                dict_ent = {financials_key: sub_dict}
+                cleaned_data.update(dict_ent)
+            else:
+                if k != 'maxAge':
+                    dict_ent = {k: v}
+                    cleaned_data.update(dict_ent)
+        return cleaned_data
+
+    # Private method to clean summary and price reports
+    def _clean_reports(self, raw_data):
+        cleaned_dict = {}
+        if raw_data is None:
+            return None
+        for k, v in raw_data.items():
+            if 'Time' in k:
+                formatted_utc_time = self._format_time(v)
+                dict_ent = {k: formatted_utc_time}
+            elif 'Date' in k:
+                try:
+                    formatted_date = v['fmt']
+                except (KeyError, TypeError):
+                    formatted_date = '-'
+                dict_ent = {k: formatted_date}
+            elif v is None or isinstance(v, str) or isinstance(v, int) or isinstance(v, float):
+                dict_ent = {k: v}
+            # Python 2 and Unicode
+            elif sys.version_info < (3, 0) and isinstance(v, unicode):
+                dict_ent = {k: v}
+            else:
+                numerical_val = self._determine_numeric_value(v)
+                dict_ent = {k: numerical_val}
+            cleaned_dict.update(dict_ent)
+        return cleaned_dict
+
+    # Private Static Method to ensure ticker is URL encoded
+    @staticmethod
+    def _encode_ticker(ticker_str):
+        encoded_ticker = ticker_str.replace('=', '%3D')
+        return encoded_ticker
+
+    # Private method to get time interval code
+    def _build_historical_url(self, ticker, hist_oj):
+        url = self._BASE_YAHOO_URL + self._encode_ticker(ticker) + '/history?period1=' + str(hist_oj['start']) + \
+              '&period2=' + str(hist_oj['end']) + '&interval=' + hist_oj['interval'] + '&filter=history&frequency=' + \
+              hist_oj['interval']
+        return url
+
+    # Private Method to clean the dates of the newly returns historical stock data into readable format
+    def _clean_historical_data(self, hist_data, last_attempt=False):
+        data = {}
+        for k, v in hist_data.items():
+            if k == 'eventsData':
+                event_obj = {}
+                if isinstance(v, list):
+                    dict_ent = {k: event_obj}
+                else:
+                    for type_key, type_obj in v.items():
+                        formatted_type_obj = {}
+                        for date_key, date_obj in type_obj.items():
+                            formatted_date_key = self.format_date(int(date_key))
+                            cleaned_date = self.format_date(int(date_obj['date']))
+                            date_obj.update({'formatted_date': cleaned_date})
+                            formatted_type_obj.update({formatted_date_key: date_obj})
+                        event_obj.update({type_key: formatted_type_obj})
+                    dict_ent = {k: event_obj}
+            elif 'date' in k.lower():
+                if v is not None:
+                    cleaned_date = self.format_date(v)
+                    dict_ent = {k: {'formatted_date': cleaned_date, 'date': v}}
+                else:
+                    if last_attempt is False:
+                        return None
+                    else:
+                        dict_ent = {k: {'formatted_date': None, 'date': v}}
+            elif isinstance(v, list):
+                sub_dict_list = []
+                for sub_dict in v:
+                    sub_dict['formatted_date'] = self.format_date(sub_dict['date'])
+                    sub_dict_list.append(sub_dict)
+                dict_ent = {k: sub_dict_list}
+            else:
+                dict_ent = {k: v}
+            data.update(dict_ent)
+        return data
+
+    # Private Static Method to build API url for GET Request
+    @staticmethod
+    def _build_api_url(hist_obj, up_ticker):
+        base_url = "https://query1.finance.yahoo.com/v8/finance/chart/"
+        api_url = base_url + up_ticker + '?symbol=' + up_ticker + '&period1=' + str(hist_obj['start']) + '&period2=' + \
+                  str(hist_obj['end']) + '&interval=' + hist_obj['interval']
+        api_url += '&events=div|split|earn&lang=en-US&region=US'
+        return api_url
+
+    # Private Method to get financial data via API Call
+    def _get_api_data(self, api_url, tries=0):
+        urlopener = UrlOpener()
+        response = urlopener.open(api_url)
+        if response.getcode() == 200:
+            res_content = response.read()
+            response.close()
+            if sys.version_info < (3, 0):
+                return loads(res_content)
+            return loads(res_content.decode('utf-8'))
+        else:
+            if tries < 5:
+                time.sleep(random.randrange(10, 20))
+                tries += 1
+                return self._get_api_data(api_url, tries)
+            else:
+                return None
+
+    # Private Method to clean API data
+    def _clean_api_data(self, api_url):
+        raw_data = self._get_api_data(api_url)
+        ret_obj = {}
+        ret_obj.update({'eventsData': []})
+        if raw_data is None:
+            return ret_obj
+        results = raw_data['chart']['result']
+        if results is None:
+            return ret_obj
+        for result in results:
+            tz_sub_dict = {}
+            ret_obj.update({'eventsData': result.get('events', {})})
+            ret_obj.update({'firstTradeDate': result['meta'].get('firstTradeDate', 'NA')})
+            ret_obj.update({'currency': result['meta'].get('currency', 'NA')})
+            ret_obj.update({'instrumentType': result['meta'].get('instrumentType', 'NA')})
+            tz_sub_dict.update({'gmtOffset': result['meta']['gmtoffset']})
+            ret_obj.update({'timeZone': tz_sub_dict})
+            timestamp_list = result['timestamp']
+            high_price_list = result['indicators']['quote'][0]['high']
+            low_price_list = result['indicators']['quote'][0]['low']
+            open_price_list = result['indicators']['quote'][0]['open']
+            close_price_list = result['indicators']['quote'][0]['close']
+            volume_list = result['indicators']['quote'][0]['volume']
+            adj_close_list = result['indicators']['adjclose'][0]['adjclose']
+            i = 0
+            prices_list = []
+            for timestamp in timestamp_list:
+                price_dict = {}
+                price_dict.update({'date': timestamp})
+                price_dict.update({'high': high_price_list[i]})
+                price_dict.update({'low': low_price_list[i]})
+                price_dict.update({'open': open_price_list[i]})
+                price_dict.update({'close': close_price_list[i]})
+                price_dict.update({'volume': volume_list[i]})
+                price_dict.update({'adjclose': adj_close_list[i]})
+                prices_list.append(price_dict)
+                i += 1
+            ret_obj.update({'prices': prices_list})
+        return ret_obj
+
+    # Private Method to Handle Recursive API Request
+    def _recursive_api_request(self, hist_obj, up_ticker, i=0):
+        api_url = self._build_api_url(hist_obj, up_ticker)
+        re_data = self._clean_api_data(api_url)
+        cleaned_re_data = self._clean_historical_data(re_data)
+        if cleaned_re_data is not None:
+            return cleaned_re_data
+        else:
+            if i < 3:
+                i += 1
+                return self._recursive_api_request(hist_obj, up_ticker, i)
+            else:
+                return self._clean_historical_data(re_data, True)
+
+    # Private Method to take scrapped data and build a data dictionary with
+    def _create_dict_ent(self, up_ticker, statement_type, tech_type, report_name, hist_obj):
+        YAHOO_URL = self._BASE_YAHOO_URL + up_ticker + '/' + self.YAHOO_FINANCIAL_TYPES[statement_type][0] + '?p=' +\
+                    up_ticker
+        if tech_type == '' and statement_type != 'history':
+            try:
+                re_data = self._scrape_data(YAHOO_URL, tech_type, statement_type)
+                dict_ent = {up_ticker: re_data[u'' + report_name], 'dataType': report_name}
+            except KeyError:
+                re_data = None
+                dict_ent = {up_ticker: re_data, 'dataType': report_name}
+        elif tech_type != '' and statement_type != 'history':
+            try:
+                re_data = self._scrape_data(YAHOO_URL, tech_type, statement_type)
+            except KeyError:
+                re_data = None
+            dict_ent = {up_ticker: re_data}
+        else:
+            YAHOO_URL = self._build_historical_url(up_ticker, hist_obj)
+            try:
+                cleaned_re_data = self._recursive_api_request(hist_obj, up_ticker)
+            except KeyError:
+                try:
+                    re_data = self._scrape_data(YAHOO_URL, tech_type, statement_type)
+                    cleaned_re_data = self._clean_historical_data(re_data)
+                except KeyError:
+                    cleaned_re_data = None
+            dict_ent = {up_ticker: cleaned_re_data}
+        return dict_ent
+
+    # Private method to return the stmt_id for the reformat_process
+    def _get_stmt_id(self, statement_type, raw_data):
+        stmt_id = ''
+        i = 0
+        for key in raw_data.keys():
+            if key in self.YAHOO_FINANCIAL_TYPES[statement_type.lower()]:
+                stmt_id = key
+                i += 1
+        if i != 1:
+            return None
+        return stmt_id
+
+    # Private Method for the Reformat Process
+    def _reformat_stmt_data_process(self, raw_data, statement_type):
+        final_data_list = []
+        if raw_data is not None:
+            stmt_id = self._get_stmt_id(statement_type, raw_data)
+            if stmt_id is None:
+                return final_data_list
+            hashed_data_list = raw_data[stmt_id]
+            for data_item in hashed_data_list:
+                data_date = ''
+                sub_data_dict = {}
+                for k, v in data_item.items():
+                    if k == 'endDate':
+                        data_date = v['fmt']
+                    elif k != 'maxAge':
+                        numerical_val = self._determine_numeric_value(v)
+                        sub_dict_item = {k: numerical_val}
+                        sub_data_dict.update(sub_dict_item)
+                dict_item = {data_date: sub_data_dict}
+                final_data_list.append(dict_item)
+            return final_data_list
+        else:
+            return raw_data
+
+    # Private Method to return subdict entry for the statement reformat process
+    def _get_sub_dict_ent(self, ticker, raw_data, statement_type):
+        form_data_list = self._reformat_stmt_data_process(raw_data[ticker], statement_type)
+        return {ticker: form_data_list}
+
+    # Public method to get time interval code
+    def get_time_code(self, time_interval):
+        interval_code = self._INTERVAL_DICT[time_interval.lower()]
+        return interval_code
+
+    # Public Method to get stock data
+    def get_stock_data(self, statement_type='income', tech_type='', report_name='', hist_obj={}):
+        data = {}
+        if isinstance(self.ticker, str):
+            dict_ent = self._create_dict_ent(self.ticker, statement_type, tech_type, report_name, hist_obj)
+            data.update(dict_ent)
+        else:
+            for tick in self.ticker:
+                try:
+                    dict_ent = self._create_dict_ent(tick, statement_type, tech_type, report_name, hist_obj)
+                    data.update(dict_ent)
+                except ManagedException:
+                    print("Warning! Ticker: " + str(tick) + " error - " + str(ManagedException))
+                    print("The process is still running...")
+                    continue
+        return data
+
+    # Public Method to get technical stock datafrom yahoofinancials import YahooFinancials
+
+    def get_stock_tech_data(self, tech_type):
+        if tech_type == 'defaultKeyStatistics':
+            return self.get_stock_data(statement_type='keystats', tech_type=tech_type)
+        else:
+            return self.get_stock_data(tech_type=tech_type)
+
+    # Public Method to get reformatted statement data
+    def get_reformatted_stmt_data(self, raw_data, statement_type):
+        data_dict = {}
+        sub_dict = {}
+        data_type = raw_data['dataType']
+        if isinstance(self.ticker, str):
+            sub_dict_ent = self._get_sub_dict_ent(self.ticker, raw_data, statement_type)
+            sub_dict.update(sub_dict_ent)
+            dict_ent = {data_type: sub_dict}
+            data_dict.update(dict_ent)
+        else:
+            for tick in self.ticker:
+                sub_dict_ent = self._get_sub_dict_ent(tick, raw_data, statement_type)
+                sub_dict.update(sub_dict_ent)
+            dict_ent = {data_type: sub_dict}
+            data_dict.update(dict_ent)
+        return data_dict
+
+    # Public method to get cleaned summary and price report data
+    def get_clean_data(self, raw_report_data, report_type):
+        cleaned_data_dict = {}
+        if isinstance(self.ticker, str):
+            if report_type == 'earnings':
+                try:
+                    cleaned_data = self._clean_earnings_data(raw_report_data[self.ticker])
+                except:
+                    cleaned_data = None
+            else:
+                try:
+                    cleaned_data = self._clean_reports(raw_report_data[self.ticker])
+                except:
+                    cleaned_data = None
+            cleaned_data_dict.update({self.ticker: cleaned_data})
+        else:
+            for tick in self.ticker:
+                if report_type == 'earnings':
+                    try:
+                        cleaned_data = self._clean_earnings_data(raw_report_data[tick])
+                    except:
+                        cleaned_data = None
+                else:
+                    try:
+                        cleaned_data = self._clean_reports(raw_report_data[tick])
+                    except:
+                        cleaned_data = None
+                cleaned_data_dict.update({tick: cleaned_data})
+        return cleaned_data_dict
+
+    # Private method to handle dividend data requestsfrom yahoofinancials import YahooFinancials
+
+    def _handle_api_dividend_request(self, cur_ticker, start, end, interval):
+        re_dividends = []
+        test_url = 'https://query1.finance.yahoo.com/v8/finance/chart/' + cur_ticker + \
+                   '?period1=' + str(start) + '&period2=' + str(end) + '&interval=' + interval + '&events=div'
+        div_dict = self._get_api_data(test_url)['chart']['result'][0]['events']['dividends']
+        for div_time_key, div_obj in div_dict.items():
+            dividend_obj = {
+                'date': div_obj['date'],
+                'formatted_date': self.format_date(int(div_obj['date'])),
+                'amount': div_obj.get('amount', None)
+            }
+            re_dividends.append(dividend_obj)
+        return sorted(re_dividends, key=lambda div: div['date'])
+
+    # Public method to get daily dividend data
+    def get_stock_dividend_data(self, start, end, interval):
+        interval_code = self.get_time_code(interval)
+        if isinstance(self.ticker, str):
+            try:
+                return {self.ticker: self._handle_api_dividend_request(self.ticker, start, end, interval_code)}
+            except:
+                return {self.ticker: None}
+        else:
+            re_data = {}
+            for tick in self.ticker:
+                try:
+                    div_data = self._handle_api_dividend_request(tick, start, end, interval_code)
+                    re_data.update({tick: div_data})
+                except:
+                    re_data.update({tick: None})
+            return re_data
+
+
+# Class containing methods to create stock data extracts
+class YahooFinancials(YahooFinanceETL):
+
+    # Private method that handles financial statement extraction
+    def _run_financial_stmt(self, statement_type, report_num, reformat):
+        report_name = self.YAHOO_FINANCIAL_TYPES[statement_type][report_num]
+        if reformat:
+            raw_data = self.get_stock_data(statement_type, report_name=report_name)
+            data = self.get_reformatted_stmt_data(raw_data, statement_type)
+        else:
+            data = self.get_stock_data(statement_type, report_name=report_name)
+        return data
+
+    # Public Method for the user to get financial statement data
+    def get_financial_stmts(self, frequency, statement_type, reformat=True):
+        report_num = self.get_report_type(frequency)
+        if isinstance(statement_type, str):
+            data = self._run_financial_stmt(statement_type, report_num, reformat)
+        else:
+            data = {}
+            for stmt_type in statement_type:
+                re_data = self._run_financial_stmt(stmt_type, report_num, reformat)
+                data.update(re_data)
+        return data
+
+    # Public Method for the user to get stock price data
+    def get_stock_price_data(self, reformat=True):
+        if reformat:
+            return self.get_clean_data(self.get_stock_tech_data('price'), 'price')
+        else:
+            return self.get_stock_tech_data('price')
+
+    # Public Method for the user to return key-statistics data
+    def get_key_statistics_data(self, reformat=True):
+        if reformat:
+            return self.get_clean_data(self.get_stock_tech_data('defaultKeyStatistics'), 'defaultKeyStatistics')
+        else:
+            return self.get_stock_tech_data('defaultKeyStatistics')
+
+    # Public Method for the user to get stock earnings data
+    def get_stock_earnings_data(self, reformat=True):
+        if reformat:
+            return self.get_clean_data(self.get_stock_tech_data('earnings'), 'earnings')
+        else:
+            return self.get_stock_tech_data('earnings')
+
+    # Public Method for the user to get stock summary data
+    def get_summary_data(self, reformat=True):
+        if reformat:
+            return self.get_clean_data(self.get_stock_tech_data('summaryDetail'), 'summaryDetail')
+        else:
+            return self.get_stock_tech_data('summaryDetail')
+
+    # Public Method for the user to get the yahoo summary url
+    def get_stock_summary_url(self):
+        if isinstance(self.ticker, str):
+            return self._BASE_YAHOO_URL + self.ticker
+        return {t: self._BASE_YAHOO_URL + t for t in self.ticker}
+
+    # Public Method for the user to get stock quote data
+    def get_stock_quote_type_data(self):
+        return self.get_stock_tech_data('quoteType')
+
+    # Public Method for user to get historical price data with
+    def get_historical_price_data(self, start_date, end_date, time_interval):
+        interval_code = self.get_time_code(time_interval)
+        start = self.format_date(start_date)
+        end = self.format_date(end_date)
+        hist_obj = {'start': start, 'end': end, 'interval': interval_code}
+        return self.get_stock_data('history', hist_obj=hist_obj)
+
+    # Private Method for Functions needing stock_price_data
+    def _stock_price_data(self, data_field):
+        if isinstance(self.ticker, str):
+            if self.get_stock_price_data()[self.ticker] is None:
+                return None
+            return self.get_stock_price_data()[self.ticker].get(data_field, None)
+        else:
+            ret_obj = {}
+            for tick in self.ticker:
+                if self.get_stock_price_data()[tick] is None:
+                    ret_obj.update({tick: None})
+                else:
+                    ret_obj.update({tick: self.get_stock_price_data()[tick].get(data_field, None)})
+            return ret_obj
+
+    # Private Method for Functions needing stock_price_data
+    def _stock_summary_data(self, data_field):
+        if isinstance(self.ticker, str):
+            if self.get_summary_data()[self.ticker] is None:
+                return None
+            return self.get_summary_data()[self.ticker].get(data_field, None)
+        else:
+            ret_obj = {}
+            for tick in self.ticker:
+                if self.get_summary_data()[tick] is None:
+                    ret_obj.update({tick: None})
+                else:
+                    ret_obj.update({tick: self.get_summary_data()[tick].get(data_field, None)})
+            return ret_obj
+
+    # Private Method for Functions needing financial statement data
+    def _financial_statement_data(self, stmt_type, stmt_code, field_name, freq):
+        re_data = self.get_financial_stmts(freq, stmt_type)[stmt_code]
+        if isinstance(self.ticker, str):
+            try:
+                date_key = re_data[self.ticker][0].keys()[0]
+            except (IndexError, AttributeError, TypeError):
+                date_key = list(re_data[self.ticker][0])[0]
+            data = re_data[self.ticker][0][date_key][field_name]
+        else:
+            data = {}
+            for tick in self.ticker:
+                try:
+                    date_key = re_data[tick][0].keys()[0]
+                except:
+                    try:
+                        date_key = list(re_data[tick][0].keys())[0]
+                    except:
+                        date_key = None
+                if date_key is not None:
+                    sub_data = re_data[tick][0][date_key][field_name]
+                    data.update({tick: sub_data})
+                else:
+                    data.update({tick: None})
+        return data
+
+    # Public method to get daily dividend data
+    def get_daily_dividend_data(self, start_date, end_date):
+        start = self.format_date(start_date)
+        end = self.format_date(end_date)
+        return self.get_stock_dividend_data(start, end, 'daily')
+
+    # Public Price Data Methods
+    def get_current_price(self):
+        return self._stock_price_data('regularMarketPrice')
+
+    def get_current_change(self):
+        return self._stock_price_data('regularMarketChange')
+
+    def get_current_percent_change(self):
+        return self._stock_price_data('regularMarketChangePercent')
+
+    def get_current_volume(self):
+        return self._stock_price_data('regularMarketVolume')
+
+    def get_prev_close_price(self):
+        return self._stock_price_data('regularMarketPreviousClose')
+
+    def get_open_price(self):
+        return self._stock_price_data('regularMarketOpen')
+
+    def get_ten_day_avg_daily_volume(self):
+        return self._stock_price_data('averageDailyVolume10Day')
+
+    def get_three_month_avg_daily_volume(self):
+        return self._stock_price_data('averageDailyVolume3Month')
+
+    def get_stock_exchange(self):
+        return self._stock_price_data('exchangeName')
+
+    def get_market_cap(self):
+        return self._stock_price_data('marketCap')
+
+    def get_daily_low(self):
+        return self._stock_price_data('regularMarketDayLow')
+
+    def get_daily_high(self):
+        return self._stock_price_data('regularMarketDayHigh')
+
+    def get_currency(self):
+        return self._stock_price_data('currency')
+
+    # Public Summary Data Methods
+    def get_yearly_high(self):
+        return self._stock_summary_data('fiftyTwoWeekHigh')
+
+    def get_yearly_low(self):
+        return self._stock_summary_data('fiftyTwoWeekLow')
+
+    def get_dividend_yield(self):
+        return self._stock_summary_data('dividendYield')
+
+    def get_annual_avg_div_yield(self):
+        return self._stock_summary_data('trailingAnnualDividendYield')
+
+    def get_five_yr_avg_div_yield(self):
+        return self._stock_summary_data('fiveYearAvgDividendYield')
+
+    def get_dividend_rate(self):
+        return self._stock_summary_data('dividendRate')
+
+    def get_annual_avg_div_rate(self):
+        return self._stock_summary_data('trailingAnnualDividendRate')
+
+    def get_50day_moving_avg(self):
+        return self._stock_summary_data('fiftyDayAverage')
+
+    def get_200day_moving_avg(self):
+        return self._stock_summary_data('twoHundredDayAverage')
+
+    def get_beta(self):
+        return self._stock_summary_data('beta')
+
+    def get_payout_ratio(self):
+        return self._stock_summary_data('payoutRatio')
+
+    def get_pe_ratio(self):
+        return self._stock_summary_data('trailingPE')
+
+    def get_price_to_sales(self):
+        return self._stock_summary_data('priceToSalesTrailing12Months')
+
+    def get_exdividend_date(self):
+        return self._stock_summary_data('exDividendDate')
+
+    # Financial Statement Data Methods
+    def get_book_value(self):
+        return self._financial_statement_data('balance', 'balanceSheetHistoryQuarterly',
+                                              'totalStockholderEquity', 'quarterly')
+
+    def get_ebit(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'ebit', 'annual')
+
+    def get_net_income(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'netIncome', 'annual')
+
+    def get_interest_expense(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'interestExpense', 'annual')
+
+    def get_operating_income(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'operatingIncome', 'annual')
+
+    def get_total_operating_expense(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'totalOperatingExpenses', 'annual')
+
+    def get_total_revenue(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'totalRevenue', 'annual')
+
+    def get_cost_of_revenue(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'costOfRevenue', 'annual')
+
+    def get_income_before_tax(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'incomeBeforeTax', 'annual')
+
+    def get_income_tax_expense(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'incomeTaxExpense', 'annual')
+
+    def get_gross_profit(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'grossProfit', 'annual')
+
+    def get_net_income_from_continuing_ops(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory',
+                                              'netIncomeFromContinuingOps', 'annual')
+
+    def get_research_and_development(self):
+        return self._financial_statement_data('income', 'incomeStatementHistory', 'researchDevelopment', 'annual')
+
+    # Calculated Financial Methods
+    def get_earnings_per_share(self):
+        price_data = self.get_current_price()
+        pe_ratio = self.get_pe_ratio()
+        if isinstance(self.ticker, str):
+            if price_data is not None and pe_ratio is not None:
+                return price_data / pe_ratio
+            else:
+                return None
+        else:
+            ret_obj = {}
+            for tick in self.ticker:
+                if price_data[tick] is not None and pe_ratio[tick] is not None:
+                    ret_obj.update({tick: price_data[tick] / pe_ratio[tick]})
+                else:
+                    ret_obj.update({tick: None})
+            return ret_obj
+
+    def get_num_shares_outstanding(self, price_type='current'):
+        today_low = self._stock_summary_data('dayHigh')
+        today_high = self._stock_summary_data('dayLow')
+        cur_market_cap = self._stock_summary_data('marketCap')
+        if isinstance(self.ticker, str):
+            if cur_market_cap is not None:
+                if price_type == 'current':
+                    current = self.get_current_price()
+                    if current is not None:
+                        today_average = current
+                    else:
+                        return None
+                else:
+                    if today_high is not None and today_low is not None:
+                        today_average = (today_high + today_low) / 2
+                    else:
+                        return None
+                return cur_market_cap / today_average
+            else:
+                return None
+        else:
+            ret_obj = {}
+            for tick in self.ticker:
+                if cur_market_cap[tick] is not None:
+                    if price_type == 'current':
+                        current = self.get_current_price()
+                        if current[tick] is not None:
+                            ret_obj.update({tick: cur_market_cap[tick] / current[tick]})
+                        else:
+                            ret_obj.update({tick: None})
+                    else:
+                        if today_low[tick] is not None and today_high[tick] is not None:
+                            today_average = (today_high[tick] + today_low[tick]) / 2
+                            ret_obj.update({tick: cur_market_cap[tick] / today_average})
+                        else:
+                            ret_obj.update({tick: None})
+                else:
+                    ret_obj.update({tick: None})
+            return ret_obj

requirements.txt

@@ -1,4 +1,6 @@
 requests~=2.21.0
 numpy~=1.15.4
 beautifulsoup4~=4.7.1
+halo~=0.0.23
 requests-cache~=0.4.13 # NOT REQUIRED
+yahoofinancials~=1.5 # NOT REQUIRED

stocks.txt

@@ -0,0 +1,10 @@
+VFINX
+SMARX
+BRASX
+USIBX
+DSIAX
+TIHYX
+SGYAX
+TPLGX
+PREFX
+FBGRX