def main(path_to_data):
c=0
ticker_list=get_ticker_list.get_ticker_list(obj.path_to_master_list())
for ticker in ticker_list:
print(ticker)
df=convert_to_df(ticker,path_to_data)
HA(ticker,df)
# To find the number of files in the output directory that end with .csv i.e. are the output files of the tickers
list=os.listdir(obj.path_to_output_dir()+"Heikin-Ashi/")
length_1=len(fnmatch.filter(list, "*.csv"))
#to find the number of tickers in the master list
ticker_list=get_ticker_list.get_ticker_list(obj.path_to_master_list())
def drop_headers_print_to_file():
path_to_stock_master_list = "C:/Users/Rohit/Python_source_code/list of stocks/nifty500_list.csv"
path_to_historical_data = "C:/Users/Rohit/Python_source_code/historical_stock_5_min_data/"
path_to_output_directory = r"C:\Users\Rohit\Python_source_code\sanitised data\historical_stock_5_min_data/"
'''
path_to_stock_master_list = r"C:/Users/Hp/Desktop/New folder/nifty500_list.csv"
path_to_historical_data = r"C:/Users/Hp/Desktop/New folder/historical_stock_5_min_data/"
path_to_output_directory = r"C:/Users/Hp/Desktop/New folder/Sanitized Data/Top500_stock/"
'''
ticker_list = get_ticker_list.get_ticker_list(path_to_stock_master_list)
c = 0
for ticker in ticker_list:
c = c + 1
print(ticker)
df = pd.read_csv(path_to_historical_data + ticker + ".csv",
index_col=False)
drop_index = []
for i in df.index:
if "Close" in df.values[i]:
drop_index.append(i)
if len(drop_index) > 0:
df = df.drop(df.index[drop_index])
df.to_csv(path_to_output_directory + ticker + ".csv", index=False)
if c == len(ticker_list):
print("Every file has been replaced")
def main(path_to_data):
period = 4
obj = config.config(r"../config.txt")
ticker_list = get_ticker_list.get_ticker_list(obj.path_to_master_list())
for ticker in ticker_list:
print(ticker)
rsi_obj = RSI(period,ticker,path_to_data + ticker + ".csv")
rsi_obj.calculate_rsi()
def main():
stdev_list = []
config_object = config("../config.txt")
filename = "ind_niftyfmcglist.csv"
path_to_stock_masterlist = config_object.path_to_master_list()
print(path_to_stock_masterlist, "\n")
ticker_list = get_ticker_list.get_ticker_list(path_to_stock_masterlist)
for ticker in ticker_list[:1]:
macd_crossover(ticker)
def main():
ticker_list = get_ticker_list.get_ticker_list(path_to_stock_master_list)
for ticker in ticker_list:
if '&' in ticker:
ticker = ticker[:ticker.index('&')] + "_26" + ticker[ticker.index('&') + 1:]
print(ticker)
interval_line = resistance(ticker)
# Appending to the new file created
with open(path_to_output, "a", newline="") as f:
writer = csv.writer(f)
writer.writerow(interval_line)
def get_narrow_7(ndays, output_folder):
strategy_ticker = []
dates = []
"""Config Object"""
config_object = config("../config.txt")
path_to_output_dir = config_object.path_to_output_dir() + output_folder
path_to_stock_masterlist = config_object.path_to_master_list()
ticker_list = get_ticker_list.get_ticker_list(path_to_stock_masterlist)
output_filename = "scanner_output.csv"
log_filename = "strategy_log.log"
"""Logging Details"""
log_format = "%(levelname)s - %(message)s"
logging.basicConfig(filename=path_to_output_dir + log_filename,
level=logging.DEBUG,
format=log_format,
filemode="w")
logger = logging.getLogger()
for ticker in ticker_list:
#Drops the data before the initial date
df = drop_data(ticker)
"""List containing 5-min data"""
date_day = df['Date Time'].tolist()
close_day = df['Close'].tolist()
open_day = df['Open'].tolist()
low_day = df['Low'].tolist()
logger.info(ticker)
"""Code to implement the stock trading strateg"""
for i in range(0, len(date_day) - ndays + 1):
c = 0
range_list = []
date_list = [ticker]
# Code Change: Add float to convert values from string
for j in range(i, i + ndays):
range_value = abs(close_day[j] - open_day[j])
range_list.append(range_value)
logger.debug(date_day[j][:10] + " " + str(range_value))
if j + 1 < len(date_day) - 1:
range_value = abs(close_day[j + 1] - open_day[j + 1])
logger.debug(date_day[j + 1][:10] + " " + str(range_value))
if range_value < min(range_list):
date_list.append(date_day[j + 1][:10])
date_list.append(date_day[j + 2][:10])
dates.append(date_list)
logger.debug("\n")
with open(path_to_output_dir + output_filename, 'w', newline="") as f:
writer = csv.writer(f)
for row in dates:
writer.writerow(row)
def main():
ticker_url = ""
ticker_list = get_ticker_list.get_ticker_list(obj.path_to_master_list())
path_to_output_dir1 = obj.path_to_output_dir(
) + "historical 1 day data/Final data/"
path_to_output_dir2 = obj.path_to_output_dir(
) + "historical 1 day data/Downloaded data/"
path_to_historical_1_day_data = obj.path_to_historical_1_day_dir()
for ticker in ticker_list:
if "_26" in ticker:
ticker_url = ticker[:ticker.
index('_')] + "&" + ticker[ticker.index('_') +
3:]
else:
ticker_url = ticker
df = pd.read_csv(path_to_output_dir2 + ticker + ".csv", index_col=None)
path_to_historical_data = path_to_historical_1_day_data + ticker + ".csv"
df2 = pd.read_csv(path_to_historical_data, index_col=None)
if "Date Time" not in df2.columns:
df2.columns = [
'Date Time', 'Close', 'High', 'Low', 'Open', 'Volume'
]
df2 = df2[['Date Time', 'Close', 'High', 'Low', 'Open', 'Volume']]
drop_index = []
for i in df2.index:
if "Close" in df2.values[i]:
drop_index.append(i)
if len(drop_index) > 0:
df2 = df2.drop(df2.index[drop_index])
if len(df2.index) != 0:
last_value = df2.values[-1][0]
last_index = -1
for index in df.index:
if df.values[index][0] == last_value:
last_index = index
if last_index == -1:
df2 = df2.append(df)
else:
df = df.drop(df.index[:last_index + 1])
df2 = df2.append(df)
else:
print("Error : NO data in repository")
df2 = df
df2.to_csv(path_to_output_dir1 + ticker + ".csv", index=False)
print(ticker_url)
"""Change according to the number of tickers"""
if len(fnmatch.filter(os.listdir(path_to_output_dir1),
"*.csv")) == len(ticker_list):
print("Final Data Complete")
def main():
config_object = config("../config.txt")
path_to_master_list = config_object.path_to_master_list()
path_to_historical_data = config_object.path_to_historical_1_day_dir()
path_to_output_dir = config_object.path_to_output_dir() + "Test 1 day-dir/"
ticker_list = get_ticker_list.get_ticker_list(path_to_master_list)
for ticker in ticker_list:
if '_26' in ticker:
ticker = ticker[:ticker.
index('_')] + "&" + ticker[ticker.index('_') + 3:]
print(ticker)
with open(path_to_historical_data + ticker + ".csv", 'r') as infile:
readstream = csv.reader(infile, delimiter=',')
with open(path_to_output_dir + ticker + ".csv", 'w',
newline="") as output:
outwriter = csv.writer(output, delimiter=',')
i = 0
for row in readstream:
if i == 0:
i = 1
row[0] = "Date Time"
outwriter.writerow(row)
def BB_Scanner(ndays, period, output_folder, threshold):
strategy_ticker = []
dates = []
skip_ticker = False
"""Config Object"""
config_object = config("../config.txt")
path_to_output_dir = config_object.path_to_output_dir() + output_folder
path_to_stock_masterlist = config_object.path_to_master_list()
ticker_list = get_ticker_list.get_ticker_list(path_to_stock_masterlist)
output_filename = "scanner_output.csv"
log_filename = "strategy_log.log"
"""Logging Details"""
log_format = "%(levelname)s %(asctime)s - %(message)s"
logging.basicConfig(filename=path_to_output_dir + log_filename,
level=logging.DEBUG,
format=log_format,
datefmt='%Y-%m-%d',
filemode="w")
logger = logging.getLogger()
for ticker in ticker_list:
#Drops the data before the initial date
print(ticker)
df = drop_data(ticker)
df = tech_indi_BBANDS.main(
config_object.path_to_historical_1_day_dir(), period, ticker)
per_ba = (df['Close'] - df['LowerBB']) / (df['UpperBB'] -
df['LowerBB'])
"""List containing 5-min data"""
date_day = df['Date Time'].tolist()
logger.info(ticker)
"""Code to implement the stock trading strateg"""
for i in range(period - 1, len(date_day) - ndays + 1):
date_list = []
date_list.append(ticker)
for j in range(i, i + ndays):
if per_ba[j] < threshold:
if per_ba[j] < -10:
skip_ticker = True
logger.info(
"The value of %b dropped below -10. Some problem in data. Moving to next stock"
)
break
logger.debug("Value = " + str(per_ba[j]) + " on date " +
date_day[j] + " for ticker " + ticker)
date_list.append(date_day[j][:10])
else:
break
if skip_ticker == True:
skip_ticker = False
break
if len(date_list) == ndays + 1:
if j + 1 <= len(date_day) - 1:
logger.debug("Value = " + str(per_ba[j + 1]) +
" on date " + date_day[j + 1] +
" for ticker " + ticker)
date_list.append(date_day[j + 1][:10])
dates.append(date_list)
with open(path_to_output_dir + output_filename, 'w', newline="") as f:
writer = csv.writer(f)
for row in dates:
writer.writerow(row)
def get_daily_closing_high(no_of_days, output_folder):
strategy_ticker = []
dates = []
"""Config Object"""
config_object = config("../config.txt")
path_to_output_dir = config_object.path_to_output_dir() + output_folder
path_to_stock_masterlist = config_object.path_to_master_list()
ticker_list = get_ticker_list.get_ticker_list(path_to_stock_masterlist)
output_filename = "scanner_output.csv"
log_filename = "strategy_log.log"
"""Logging Details"""
log_format = "%(levelname)s - %(message)s"
logging.basicConfig(filename=path_to_output_dir + log_filename,
level=logging.DEBUG,
format=log_format,
filemode="w")
logger = logging.getLogger()
for ticker in ticker_list:
# Drops the data before the initial date
df = drop_data(ticker)
"""List containing 5-min data"""
date_day = df['Date Time'].tolist()
close_day = df['Close'].tolist()
open_day = df['Open'].tolist()
low_day = df['Low'].tolist()
"""Code to implement the stock trading strateg"""
for i in range(1, len(date_day) - no_of_days + 1):
c = 0
date_list = [ticker, date_day[i - 1][:10]]
open_price = open_day[i - 1]
# Code Change: Add float to convert values from string
for j in range(0, no_of_days - 1):
next_day = i + j + 1
current_day = i + j
previous_day = i + j - 1
if float(close_day[current_day]) > float(open_day[current_day])\
and float(close_day[previous_day]) > float(open_day[previous_day]):
day_change = float(close_day[previous_day]) - float(
open_day[previous_day])
if (float(close_day[previous_day]) - float(open_day[current_day])) < (.98 * day_change) \
and float(low_day[current_day]) > float(open_day[previous_day]):
date_list.append(date_day[current_day][:10])
c += 1
if c == no_of_days - 1:
close_price = close_day[current_day]
# Percentage change in the close price of final day and the opening price of the first day
per = (close_price - open_price) / open_price
date_list.append(date_day[next_day][:10])
# Rounded it off to 4 decimal places
date_list.append(round(per, 4))
dates.append(date_list)
if c == no_of_days - 1:
strategy_ticker.append(ticker)
if len(dates) == 0:
logger.error("No companies followed this strategy")
else:
c = 1
for i in range(0, len(dates) - 1):
if dates[i][0] != dates[i + 1][0]:
c = c + 1
logger.info("Strategy is followed by = " + str(c) + " companies")
with open(path_to_output_dir + output_filename, 'w', newline="") as f:
writer = csv.writer(f)
for row in dates:
writer.writerow(row)
def main():
# Extracting arguments from command line
parser = argparse.ArgumentParser(description="download data")
parser.add_argument("seconds", type=int, help="Number of seconds")
parser.add_argument("days", type=int, help="Number of days")
args = parser.parse_args()
sec = args.seconds
day = args.days
# Names for the directory
date = str(datetime.datetime.today())[:10]
path_to_final_data = obj.path_to_output_dir() + "final data " + str(
sec) + " " + date + "/"
path_to_downloaded_data = obj.path_to_output_dir(
) + "downloaded data " + str(sec) + " " + date + "/"
# Making required directory
os.makedirs(path_to_final_data, exist_ok=True)
os.makedirs(path_to_downloaded_data, exist_ok=True)
# Condition for whether input seconds data exists or not
if sec == 300:
path_to_historical_data = obj.path_to_historical_5_min_dir()
elif sec == 1800:
path_to_historical_data = obj.path_to_historical_30_min_dir()
elif sec == 86400:
path_to_historical_data = obj.path_to_historical_1_day_dir()
else:
print("No such stock data present")
exit(-1)
ticker_url = ""
ticker_list = get_ticker_list.get_ticker_list(obj.path_to_master_list())
for ticker in ticker_list:
if "_26" in ticker:
ticker_url = ticker[:ticker.
index('_')] + "&" + ticker[ticker.index('_') +
3:]
else:
ticker_url = ticker
param = {
'q': ticker_url, # Stock symbol (ex: "AAPL")
'i':
str(sec), # Interval size in seconds ("86400" = 1 day intervals)
'x':
"NSE", # Stock exchange symbol on which stock is traded (ex: "NASD")
'p': str(day) + "d" # Period (Ex: "1Y" = 1 year)
}
# get price data (return pandas dataframe)
df = get_price_data(param)
df.index.name = "Date Time"
df = df[['Close', 'High', 'Low', 'Open', 'Volume']]
df.to_csv(path_to_downloaded_data + ticker + ".csv")
if len(df.index) == 0:
print("Error : No data online")
print(ticker_url)
if len(fnmatch.filter(os.listdir(path_to_downloaded_data),
"*.csv")) == len(ticker_list):
print("Downloaded Data Complete")
for ticker in ticker_list:
if "_26" in ticker:
ticker_url = ticker[:ticker.
index('_')] + "&" + ticker[ticker.index('_') +
3:]
else:
ticker_url = ticker
df = pd.read_csv(path_to_downloaded_data + ticker + ".csv",
index_col=None)
df2 = pd.read_csv(path_to_historical_data + ticker + ".csv",
index_col=None)
if "Date Time" not in df2.columns:
df2.columns = [
'Date Time', 'Close', 'High', 'Low', 'Open', 'Volume'
]
df2 = df2[['Date Time', 'Close', 'High', 'Low', 'Open', 'Volume']]
drop_index = []
for i in df2.index:
if "Close" in df2.values[i]:
drop_index.append(i)
if len(drop_index) > 0:
df2 = df2.drop(df2.index[drop_index])
if len(df2.index) != 0:
last_value = df2.values[-1][0]
last_index = -1
for index in df.index:
if df.values[index][0] == last_value:
last_index = index
if last_index == -1:
df2 = df2.append(df)
else:
df = df.drop(df.index[:last_index + 1])
df2 = df2.append(df)
else:
print("Error : NO data in repository")
df2 = df
df2.to_csv(path_to_final_data + ticker + ".csv", index=False)
print(ticker_url)
"""Change according to the number of tickers"""
if len(fnmatch.filter(os.listdir(path_to_final_data),
"*.csv")) == len(ticker_list):
print("Final Data Complete")