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May 20, 2017 15:05
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import os | |
import sys | |
import pandas as pd | |
import pandas_datareader.data as web | |
import numpy as np | |
import time | |
import asyncio | |
from fake_useragent import UserAgent | |
'''set path variables''' | |
project_dir = "YOUR/PROJECT/DIR" | |
sys.path.append(project_dir) | |
import async_option_scraper | |
import option_parser | |
# ================================================ | |
today = pd.datetime.today().date() | |
# ================================================ | |
file_start = time.time() | |
print('\nAsync Barchart Scraper starting...') | |
# --------------- \\\ | |
# import symbols | |
FILE = project_dir + 'ETFList.Options.Nasdaq__M.csv' | |
ALL_ETFS = pd.read_csv(FILE)['Symbol'] | |
drop_symbols = ['ADRE', 'AUNZ', 'CGW', 'DGT', 'DSI', 'EMIF', 'EPHE', 'EPU', 'EUSA', 'FAN', 'FDD', 'FRN', 'GAF', 'GII', 'GLDI', 'GRU', 'GUNR', 'ICN', 'INXX', 'IYY', 'KLD', 'KWT', 'KXI', 'MINT', 'NLR', 'PBP', 'PBS', 'PEJ', 'PIO', 'PWB', 'PWV', 'SCHO', 'SCHR', 'SCPB', 'SDOG', 'SHM', 'SHV', 'THRK', 'TLO', 'UHN', 'USCI', 'USV', 'VCSH'] | |
ETFS = [x for x in ALL_ETFS if x not in set(drop_symbols)] | |
# ================================================ | |
# GET HTML SOURCE FOR LAST SYMBOL EQUITY PRICE | |
# ================================================ | |
t0_price = time.time() | |
# --------------- \\\ | |
loop = asyncio.get_event_loop() | |
px_scraper = async_option_scraper.last_price_scraper() | |
px_run_future = asyncio.ensure_future(px_scraper.run(ETFS)) | |
loop.run_until_complete(px_run_future) | |
px_run = px_run_future.result() | |
# ------------- /// | |
duration_price = time.time() - t0_price | |
print('\nprice scraper script run time: ', | |
pd.to_timedelta(duration_price, unit='s')) | |
# ------------- /// | |
# create price dictionary | |
px_dict = {} | |
for k, v in zip(ETFS, px_run): | |
px_dict[k] = v | |
# ================================================ | |
# RUN FIRST ASYNC SCRAPER | |
# ================================================ | |
t0_first = time.time() | |
# --------------- \\\ | |
ua = UserAgent() | |
loop = asyncio.get_event_loop() | |
first_scraper = async_option_scraper.first_async_scraper() | |
first_run_future = asyncio.ensure_future( | |
first_scraper.run(ETFS, ua.random) | |
) | |
loop.run_until_complete(first_run_future) | |
first_run = first_run_future.result() | |
# ------------- /// | |
first_duration = time.time() - t0_first | |
print('\nfirst async scraper script run time: ', | |
pd.to_timedelta(first_duration, unit='s')) | |
# ================================================ | |
# EXTRACT EXPIRYS FROM FIRST RUN SCRAPER | |
# ================================================ | |
xp = async_option_scraper.expirys(ETFS, first_run) | |
expirys = xp.get_expirys() | |
# ================================================ | |
# SCRAPE AND AGGREGATE ALL SYMBOLS BY EXPIRY | |
# ================================================ | |
t0_xp = time.time() | |
# -------------- \\\ | |
# dict key=sym, values=list of json data by expiry | |
# create helper logic to test if expirys is None before passing | |
sym_xp_dict = {} | |
ua = UserAgent() | |
xp_scraper = async_option_scraper.xp_async_scraper() | |
for symbol in ETFS: | |
print() | |
print('-'*50) | |
print('scraping: ', symbol) | |
if not expirys[symbol]: | |
print('symbol ' + symbol + ' missing expirys') | |
continue | |
try: | |
xp_loop = asyncio.get_event_loop() | |
xp_future = asyncio.ensure_future( | |
xp_scraper.xp_run(symbol, expirys[symbol], ua.random) | |
) | |
xp_loop.run_until_complete(xp_future) | |
sym_xp_dict[symbol] = xp_future.result() | |
except Exception as e: | |
print(symbol + ' error: ' + e) | |
# ------------- /// | |
duration_xp = time.time() - t0_xp | |
print('\nall async scraper script run time: ', | |
pd.to_timedelta(duration_xp, unit='s')) | |
# ================================================ | |
# PARSE ALL COLLECTED DATA | |
# ================================================ | |
t0_agg = time.time() | |
# -------------- \\\ | |
all_etfs_data = [] | |
for symbol, xp_list in sym_xp_dict.items(): | |
print() | |
print('-'*50) | |
print('parsing: ', symbol) | |
list_dfs_by_expiry = [] | |
try: | |
for i in range(len(xp_list)): | |
try: | |
parser = option_parser.option_parser( | |
symbol, xp_list[i]) | |
call_df = parser.create_call_df() | |
put_df = parser.create_put_df() | |
concat = pd.concat([call_df, put_df], axis=0) | |
concat['underlyingPrice'] = np.repeat( | |
parser.extract_last_price(px_dict[symbol]), | |
len(concat.index)) | |
list_dfs_by_expiry.append(concat) | |
except: continue | |
except Exception as e: | |
print(f'symbol: {symbol}\n error: {e}') | |
print() | |
continue | |
all_etfs_data.append(pd.concat(list_dfs_by_expiry, axis=0)) | |
# ------------- /// | |
duration_agg = time.time() - t0_agg | |
print('\nagg parse data script run time: ', | |
pd.to_timedelta(duration_agg, unit='s')) | |
# -------------- \\\ | |
dfx = pd.concat(all_etfs_data, axis=0).reset_index(drop=True) | |
print(dfx.info()) | |
# ------------- /// | |
# ================================================ | |
# GET ANY MISSING UNDERLYING PRICE | |
# ================================================ | |
print('\nCollecting missing prices...') | |
grp = dfx.groupby(['symbol'])['underlyingPrice'].count() | |
missing_symbol_prices = grp[grp == 0].index | |
get_price = lambda symbol: web.DataReader( | |
symbol, 'google', today)['Close'] | |
prices = [] | |
for symbol in missing_symbol_prices: | |
px = get_price(symbol).iloc[0] | |
prices.append((symbol, px)) | |
df_prices = pd.DataFrame(prices).set_index(0) | |
for symbol in df_prices.index: | |
(dfx.loc[dfx['symbol'] == symbol, | |
['underlyingPrice']]) = df_prices.loc[symbol].iloc[0] | |
dfx['underlyingPrice'] = dfx.underlyingPrice.astype(float) | |
print('\nmissing prices added') | |
# ================================================ | |
# store dataframe as hdf | |
# ================================================ | |
print(dfx.head(20)) | |
print(dfx.info()) | |
file_duration = time.time() - file_start | |
print('\nfile script run time: ', pd.to_timedelta(file_duration, unit='s')) | |
file_ = project_dir + f'/ETF_options_data_{today}.h5' | |
dfx.to_hdf(file_, key='data', mode='w') | |
# ================================================ | |
# kill python process after running script | |
# ================================================ | |
time.sleep(2) | |
os.kill(os.getpid(), 9) |
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