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api call limits and transitions

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This commit is contained in:
Neythen
2021-06-27 12:07:47 +01:00
parent 2bee635511
commit 54edfb0d1b
26 changed files with 278 additions and 241 deletions
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238
api_caller.py
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@@ -96,8 +96,13 @@ def updateUpdate(NY_time):
f.write(NY_str + '\n')
f.close()
def updateStockPrices(symbols):
def updateStockPrices():
finnhubsandboxAPIkey = "sandbox_c24qddqad3ickpckgg8g" #Finnhub
finnhubAPIkey = "c24qddqad3ickpckgg80" #Finnhub
finnhubClient = finnhub.Client(api_key=finnhubAPIkey)
symbols, stock_info = readCSV('csv/tickers.csv', max_stocks)
try:
quotes = [finnhubClient.quote(symbol) for symbol in symbols]
current_prices = [quote['c'] for quote in quotes]
@@ -120,7 +125,11 @@ def updateStockPrices(symbols):
apiCalledError = True
def updateStockPricesIEX(symbols):
def updateStockPricesIEX():
iexAPIkey = 'pk_68ef6a15902c41f887f0b544a0ca17cf' #IEX
iexSandboxAPIkey = 'Tpk_0078dff413ef4f979137f7111452dc4b'
max_stocks = 200
symbols, stock_info = readCSV('csv/tickers.csv', max_stocks)
try:
symbols_str = ','.join(symbols)
method = 'GET'
@@ -179,7 +188,10 @@ def updateStockPricesIEX(symbols):
print(e)
def updateCrypto(coins, coin_info, unique_bases):
def updateCrypto():
coingecko_client = CoinGeckoAPI()
coins, coin_info, unique_bases = readCryptoCSV('csv/crypto.csv', max_crypto)
try:
response = coingecko_client.get_price(ids=','.join(coins), vs_currencies = unique_bases, include_24hr_change=True)
@@ -225,7 +237,9 @@ def updateNews():
except Exception as e:
print(e)
def updateWeather(api_key):
def updateWeather():
api_key = 'bd5d5096a5ba30bbcfb57ead42ab3fee'
try:
f = open( "csv/weather_location.txt", 'r' )
location = f.read()
@@ -277,8 +291,8 @@ def updateWeather(api_key):
print(e)
def updateCurrencies(api_key):
def updateForex():
api_key = '862dbb6d1101ce0c5136'
try:
base = 'USD'
yesterday = datetime.now() - timedelta(1)
@@ -400,106 +414,97 @@ def updateLeagueEvents(api_key, league_id, time):
league = 'NFL'
json.dump(events, open( "csv/sports/{}/{}_games.json".format(league, time), 'w+' ))
def updateSports():
#read user settings to decide which sprots to update
api_key = '97436974'
def updateSports(api_key):
prem_id = '4328' #prem
NHL_id = '4380'
NBA_id = '4387' #prem
NFL_id = '4391'
for i in [NHL_id, NBA_id, NFL_id]:
for i in [NHL_id]:
updateLeagueEvents(api_key, i, 'live')
updateLeagueEvents(api_key, i, 'past')
updateLeagueEvents(api_key, i, 'future')
updateLeagueTable(api_key, NHL_id)
updateLeagueTable(api_key, prem_id)
'https://www.thesportsdb.com/api/v1/json/{}/eventsnext.php?id=133602'.format(api_key) # next five events by team ID (paid) use this for upcoming team games
#url = 'https://www.thesportsdb.com/api/v1/json/{}/eventsseason.php?id=4328&s=2020-2021'.format(api_key) # all past events in premier league
url = 'https://www.thesportsdb.com/api/v2/json/{}/livescore.php?l=4380'.format(api_key) #live scores
def checkStocks(last_update, update_frequency):
NY_time = datetime.now(NY_zone).replace(tzinfo=None)
opening = NY_time.replace(hour=9, minute=30, second=0, microsecond=0).replace(tzinfo=None)
closing = NY_time.replace(hour=16, minute=0, second=0, microsecond=0).replace(tzinfo=None)
symbols, stock_info = readCSV('csv/tickers.csv', max_stocks)
updated = False
diff = (NY_time - last_update).total_seconds()/60 #minutes
if opening < NY_time < closing and datetime.today().weekday() < 5: # we need to do real time updating
if diff >= update_frequency:
updated = True
updateStockPrices()
elif emptyInfo(symbols, stock_info): # if theres any empty stocks
updated = True
updateStockPrices()
else:
# update if last update was before the previous days closing
yday_closing = closing - dt.timedelta(days=1)
yday_str = yday_closing.strftime("%d/%m/%Y %H:%M:%S")
yday_closing = datetime.strptime(yday_str, "%d/%m/%Y %H:%M:%S")
if last_update < yday_closing:
updated = True
updateStockPrices(symbols)
return updated
if __name__ == '__main__':
newsapi = NewsApiClient(api_key='cf08652bd17647b89aaf469a1a8198a9')
finnhubAPIkey = "c24qddqad3ickpckgg80" #Finnhub
finnhubsandboxAPIkey = "sandbox_c24qddqad3ickpckgg8g" #Finnhub
stock_time = 2 #minutes
crypto_time = 10 #minutes
news_time = 30 #minutes
weather_time = 10 #minutes
# TODO: different update times for stocks, weather and news
finnhubClient = finnhub.Client(api_key=finnhubAPIkey)
max_stocks = 200
max_crypto = 100
iexAPIkey = 'pk_68ef6a15902c41f887f0b544a0ca17cf' #IEX
iexSandboxAPIkey = 'Tpk_0078dff413ef4f979137f7111452dc4b'
newsapi = NewsApiClient(api_key='cf08652bd17647b89aaf469a1a8198a9')
#updateStockPricesIEX(symbols)
update_frequencies = {'stocks':2, 'crypto':10, 'news':60, 'weather': 10} #minutes
finnhubClient = finnhub.Client(api_key=finnhubAPIkey)
coingecko_client = CoinGeckoAPI()
NY_zone = pytz.timezone('America/New_York')
NY_time = datetime.now(NY_zone)
opening = NY_time.replace(hour=9, minute=30, second=0, microsecond=0)
closing = NY_time.replace(hour=16, minute=0, second=0, microsecond=0)
CET_zone = pytz.timezone('Europe/Berlin')
NY_time = datetime.now(NY_zone)
symbols, stock_info = readCSV('csv/tickers.csv', max_stocks)
updateStockPrices(symbols)
updateUpdate(NY_time)
coins, coin_info, unique_bases = readCryptoCSV('csv/crypto.csv', max_crypto)
CET_time = datetime.now(CET_zone)
weather_key = 'bd5d5096a5ba30bbcfb57ead42ab3fee'
NY_str = NY_time.strftime("%d/%m/%Y %H:%M:%S")
CET_str = NY_time.strftime("%d/%m/%Y %H:%M:%S")
currency_key = '862dbb6d1101ce0c5136'
sports_key = '97436974'
#f = open('csv/last_updates.json', 'w+')
#update_times = {'stocks':NY_str, 'crypto':NY_str, 'news':NY_str, 'weather': NY_str, 'forex': CET_str} # all in NY time apart from forex in CET
#json.dump(update_times, f)
#f.close()
updateSports(sports_key)
updateCurrencies(currency_key)
updateWeather( weather_key)
updateCrypto(coins, coin_info, unique_bases)
updateNews()
f = open('csv/last_updates.json', 'r')
last_updates = json.load(f)
f.close()
t = time.time()
@@ -507,56 +512,67 @@ if __name__ == '__main__':
try:
while True:
NY_time = datetime.now(NY_zone).replace(tzinfo=None)
msg = getInput()
if msg == 'R' or time.time() - t > stock_time*60:
#stocks
stock_time = datetime.strptime(last_updates['stocks'], "%d/%m/%Y %H:%M:%S")
stock_frequency = update_frequencies['stocks']
if checkStocks(stock_time, stock_frequency):
stock_time = NY_time.strftime("%d/%m/%Y %H:%M:%S")
last_updates['stocks'] = stock_time
# crypto
crypto_time = datetime.strptime(last_updates['crypto'], "%d/%m/%Y %H:%M:%S")
crypto_frequency = update_frequencies['crypto']
NY_time = datetime.now(NY_zone).replace(tzinfo=None)
diff = (NY_time - crypto_time).total_seconds()/60 #minutes
if diff >= update_frequencies['crypto']:
crypto_time = NY_time.strftime("%d/%m/%Y %H:%M:%S")
updateCrypto()
last_updates['crypto'] = crypto_time
# weather
weather_time = datetime.strptime(last_updates['weather'], "%d/%m/%Y %H:%M:%S")
weather_frequency = update_frequencies['weather']
NY_time = datetime.now(NY_zone).replace(tzinfo=None)
diff = (NY_time - weather_time).total_seconds()/60 #minutes
if diff >= update_frequencies['weather']:
weather_time = NY_time.strftime("%d/%m/%Y %H:%M:%S")
updateWeather()
last_updates['weather'] = weather_time
coins, coin_info, unique_bases = readCryptoCSV('csv/crypto.csv', max_stocks)
updateCrypto(coins, coin_info, unique_bases)
updateCurrencies(currency_key)
# weather
news_time = datetime.strptime(last_updates['news'], "%d/%m/%Y %H:%M:%S")
news_frequency = update_frequencies['news']
NY_time = datetime.now(NY_zone).replace(tzinfo=None)
diff = (NY_time - weather_time).total_seconds()/60 #minutes
if diff >= update_frequencies['news']:
news_time = NY_time.strftime("%d/%m/%Y %H:%M:%S")
updateNews()
updateWeather(weather_location, weather_key)
updateSports(sports_key)
last_updates['news'] = news_time
NY_time = datetime.now(NY_zone)
symbols, stock_info = readCSV('csv/tickers.csv', max_stocks)
if opening < NY_time < closing and datetime.today().weekday() < 5: # we need to do real time updating
print('market open')
updateStockPrices(symbols)
updateUpdate(NY_time)
elif emptyInfo(symbols, stock_info): # if theres any empty stocks
updateStockPrices(symbols)
updateUpdate(NY_time)
#forex updates once every 24hours at 1700 CET
# update if last update was before the previous days closing
forex_time = datetime.strptime(last_updates['forex'], "%d/%m/%Y %H:%M:%S")
CET_time = datetime.now(CET_zone)
yday_update = (CET_time.replace(hour=17, minute=00, second=0, microsecond=0) - dt.timedelta(days=1)).replace(tzinfo=None)
if forex_time < yday_update:
forex_time = CET_time.strftime("%d/%m/%Y %H:%M:%S")
last_updates['forex'] = forex_time
updateForex()
else:
# update if last update was before the previous days closing
f = open('csv/last_update.csv', 'r')
CSV = csv.reader(f)
last_update_str = next(CSV)[0]
last_update = datetime.strptime(last_update_str, "%d/%m/%Y %H:%M:%S")
yday_closing = closing - dt.timedelta(days=1)
yday_str = yday_closing.strftime("%d/%m/%Y %H:%M:%S")
yday_closing = datetime.strptime(yday_str, "%d/%m/%Y %H:%M:%S")
if last_update < yday_closing:
updateStockPrices(symbols)
updateUpdate(NY_time)
t = time.time()
except Exception as e:
logf.write(srt(e))
logf.write(str(e))
print(e)