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sonia.py
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sonia.py
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import datetime
import smtplib
from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText
from email.mime.base import MIMEBase
from email import encoders
from dateutil import parser
import openpyxl as xl
import pandas as pd
import requests
from openpyxl.styles import Font, Alignment, PatternFill
# styles
red = Font("Arial", 11, color='ff0000', bold=True)
blue = Font("Arial", 11, color="0000ff", bold=True)
bold = Font("Arial", 11, bold=True)
alignment = Alignment(horizontal='center')
cur_date = '06.10.23'
cur_month = 'OCT'
cur_year = 2023
offset = 33 # 33 is 06-OCT-2023(07-OCT-2023 India date)
daily_start_row = 1592 + offset
# cur_date_datetime = parser.parse(cur_date).date()
cur_date_datetime = datetime.date(int(cur_year), int(cur_date[3:5]), int(cur_date[:2]))
key = "bf5204b93cd4e38625e4d899fc6d5e9f"
shares = ['AAPL', 'AMZN', 'META', 'MSFT', 'NFLX', 'NVDA', 'NDAQ', 'QQQ', 'TSLA']
# shares = ['AAPL']
high_dict = {'AAPL': 0, 'AMZN': 0, 'META': 0, 'MSFT': 0, 'NFLX': 0, 'NVDA': 0, 'QQQ': 0, 'TSLA:': 0}
low_dict = {'AAPL': 0, 'AMZN': 0, 'META': 0, 'MSFT': 0, 'NFLX': 0, 'NVDA': 0, 'QQQ': 0, 'TSLA:': 0}
cl_9_40_dict = {'AAPL': 0, 'AMZN': 0, 'META': 0, 'MSFT': 0, 'NFLX': 0, 'NVDA': 0, 'QQQ': 0, 'TSLA:': 0}
attachment_path_list = []
for share in shares:
url = rf'https://financialmodelingprep.com/api/v3/historical-chart/1min/{share}?apikey={key}'
path = rf'E:\sonia daily data\1 min cash\{cur_year}\{cur_month}\{cur_date}\{share} 1 min csh.xlsx'
attachment_path_list.append(path)
response = requests.get(url)
data = response.json()
# data = pd.read_json(r'C:\Users\admin\PycharmProjects\daily data\AAPL.json')
df = pd.DataFrame(data)
df["date"] = pd.to_datetime(df["date"])
df["Date"] = df["date"].dt.date
df["Time"] = df["date"].dt.time
df.drop(df[(df.Date < cur_date_datetime)].index, inplace=True)
df.drop(df[(df.Date > cur_date_datetime)].index, inplace=True)
df = df.iloc[:, [7, 3, 2, 4, 5]]
df = df.sort_values(by='Time')
df = df.round(2)
with pd.ExcelWriter(path) as writer:
df.to_excel(writer, index=False)
# df.to_json(rf'C:\Users\admin\PycharmProjects\daily data\AAPL.json')
# excel formatting
wb = xl.load_workbook(path)
sheet = wb['Sheet1']
start_row = 2
# converting time from str to datetime.datetime
while start_row <= len(sheet['A']):
time_cell = sheet.cell(start_row, 1)
time = time_cell.value
time = datetime.datetime.strptime(time, "%H:%M:%S")
# time = time.time()
time_cell.value = time
time_cell.number_format = 'h:mm AM/PM'
start_row += 1
wb.save(path)
# reloading wb
wb = xl.load_workbook(path)
sheet = wb['Sheet1']
start_row = 2
time_cell = sheet.cell(start_row, 1)
cur_time = time_cell.value
# print(cur_time)
while time_cell.value < datetime.datetime(1900, 1, 1, hour=9, minute=40):
start_row += 1
time_cell = sheet.cell(start_row, 1)
print(f"starting row is {start_row}")
start_row_2 = start_row
time_cell = sheet.cell(start_row, 1)
cur_time = time_cell.value
end_time = datetime.datetime(1900, 1, 1, 16, 0, 0)
# 9:40 close value
cl_9_40_dict[share] = sheet.cell(start_row, 4).value
# 9:40 AM row formatting
for i in range(1, 6):
sheet.cell(start_row, i).fill = PatternFill("solid", 'FFFF00')
# reloading wb otherwise pattern fill doesn't work
wb.save(path)
wb = xl.load_workbook(path)
sheet = wb['Sheet1']
HIGH = 0
LOW = 9999999
# HIGH and LOW value finding loop
while cur_time is not None and cur_time <= end_time:
time_cell = sheet.cell(start_row, 1)
high_cell = sheet.cell(start_row, 2)
low_cell = sheet.cell(start_row, 3)
cur_time = time_cell.value
if high_cell.value is not None and high_cell.value > HIGH:
HIGH = high_cell.value
if low_cell.value is not None and low_cell.value < LOW and low_cell.value != 0:
LOW = low_cell.value
start_row += 1
high_dict[share] = HIGH
low_dict[share] = LOW
# 30 MIN FORMATTING IN 1 MIN SHEETS
HIGH = 0
LOW = 9999999
sheet.cell(1, 7).value = "HIGH"
sheet.cell(1, 8).value = "LOW"
sheet.cell(1, 9).value = "CLOSE"
start_row = start_row_2 # actual start row
time_cell = sheet.cell(start_row, 1)
cur_time = time_cell.value
count = 0
while cur_time is not None and cur_time <= end_time:
high_cell = sheet.cell(start_row, 2)
low_cell = sheet.cell(start_row, 3)
# print(cur_time)
if high_cell.value is not None and high_cell.value > HIGH:
HIGH = high_cell.value
if low_cell.value is not None and low_cell.value < LOW and low_cell.value != 0:
LOW = low_cell.value
# resetting after 30 mins
if count == 30:
sheet.cell(start_row, 7).value = HIGH
sheet.cell(start_row, 8).value = LOW
# if 30 min close is empty or 0
if sheet.cell(start_row, 4).value == 0 or sheet.cell(start_row, 4).value is None:
temp_row = start_row
while sheet.cell(temp_row, 4).value == 0 or sheet.cell(temp_row, 4).value is None:
temp_row -= 1
sheet.cell(start_row, 9).value = sheet.cell(temp_row, 4).value # close
else:
sheet.cell(start_row, 9).value = sheet.cell(start_row, 4).value # close
count = 1
HIGH = 0
LOW = 9999999
start_row += 1
continue
start_row += 1
count += 1
time_cell = sheet.cell(start_row, 1)
cur_time = time_cell.value
# last any left aggregate (< 30 mins)
sheet.cell(start_row - 1, 7).value = HIGH
sheet.cell(start_row - 1, 8).value = LOW
sheet.cell(start_row - 1, 9).value = sheet.cell(start_row - 1, 4).value # close
print(f"{share} done")
# converting datetime.datetime to str in specific format (%I:%M %p)
start_row = 2
while start_row < len(sheet['A']):
time_cell = sheet.cell(start_row, 1)
time = time_cell.value
time_cell.value = time.strftime("%I:%M %p")
time_cell.number_format = 'h:mm AM/PM'
start_row += 1
wb.save(path)
# 30 min sheet and daily data filling
for share in shares:
# data filling
daily_url = rf'https://financialmodelingprep.com/api/v3/historical-price-full/{share}?apikey={key}'
daily_path = rf'E:\sonia daily data\cash\{share} csh.xlsx'
attachment_path_list.append(daily_path)
response = requests.get(daily_url)
data = response.json()
df = pd.DataFrame(data)
close = round(df['historical'][0]['close'], 2)
prev = round(df['historical'][1]['close'], 2)
vol = df['historical'][0]['volume'] // 100000
# delete this because this is just for when making data after market start of next day
# close = round(df['historical'][1]['close'], 2)
# prev = round(df['historical'][2]['close'], 2)
# vol = df['historical'][1]['volume'] // 100000
daily_wb = xl.load_workbook(daily_path)
daily_sheet = daily_wb['D']
# daily data filling
# high
daily_sheet.cell(daily_start_row, 2).value = high_dict[share]
daily_sheet.cell(daily_start_row, 2).font = blue
daily_sheet.cell(daily_start_row, 2).alignment = alignment
# low
daily_sheet.cell(daily_start_row, 3).value = low_dict[share]
daily_sheet.cell(daily_start_row, 3).font = red
daily_sheet.cell(daily_start_row, 3).alignment = alignment
# close
daily_sheet.cell(daily_start_row, 4).value = close
daily_sheet.cell(daily_start_row, 4).font = bold
daily_sheet.cell(daily_start_row, 4).alignment = alignment
# volume
daily_sheet.cell(daily_start_row, 5).value = vol
daily_sheet.cell(daily_start_row, 5).font = bold
daily_sheet.cell(daily_start_row, 5).alignment = alignment
# 9:40 close
daily_sheet.cell(daily_start_row, 6).value = cl_9_40_dict[share]
daily_sheet.cell(daily_start_row, 6).font = bold
daily_sheet.cell(daily_start_row, 6).alignment = alignment
daily_wb.save(daily_path)
# 30 min sheet
url = rf'https://financialmodelingprep.com/api/v3/historical-chart/30min/{share}?apikey={key}'
path = rf'E:\sonia daily data\30 min cash\{cur_year}\{cur_month}\{cur_date}\{share} 30 min csh.xlsx'
attachment_path_list.append(path)
response = requests.get(url)
data = response.json()
df = pd.DataFrame(data)
df["date"] = pd.to_datetime(df["date"])
df["Date"] = df["date"].dt.date
df["Time"] = df["date"].dt.time
df.drop(df[df.Date < cur_date_datetime].index, inplace=True)
df.drop(df[df.Date > cur_date_datetime].index, inplace=True)
df = df.iloc[:, [4, 3, 2, 7]]
df = df.sort_values(by='Time')
df = df.round(2)
df.to_excel(path, index=False)
# excel formatting
wb = xl.load_workbook(path)
sheet = wb['Sheet1']
new_sheet = wb.create_sheet(f'{share} Sheet')
start_row = 2
for i in range(2, len(sheet['A'])):
for j in range(1, 5):
old_cell = sheet.cell(i, j)
old = old_cell.value
# if time row, convert time to HH:MM AM/PM
if j == 4:
old = datetime.datetime.strptime(old, "%H:%M:%S").strftime("%I:%M %p")
old_cell.number_format = 'h:mm AM/PM'
new_cell = new_sheet.cell(i + 7, j + 3)
new_cell.value = old
# fixed headings
new_sheet.cell(8, 4).value = "Close Rate"
new_sheet.cell(8, 5).value = "High Rate"
new_sheet.cell(8, 6).value = "Low Rate"
new_sheet.cell(8, 7).value = "Time"
new_sheet.cell(6, 4).value = share
new_sheet.cell(6, 5).value = "HIGH"
new_sheet.cell(6, 6).value = "LOW"
new_sheet.cell(6, 7).value = "LTP"
new_sheet.cell(6, 8).value = "PREV"
new_sheet.cell(7, 3).value = "9:40 close"
# 30 min data filling from 1 min and daily
new_sheet.cell(7, 4).value = cl_9_40_dict[share]
new_sheet.cell(7, 5).value = high_dict[share]
new_sheet.cell(7, 6).value = low_dict[share]
new_sheet.cell(7, 7).value = close
new_sheet.cell(7, 8).value = prev
# bolding and formatting all the values
for i in range(5, 24):
for j in range(1, 10):
new_sheet.cell(i, j).font = Font('Calibri', 11, bold=True)
new_sheet.cell(i, j).alignment = alignment
del wb['Sheet1']
wb.save(path)
daily_wb.save(daily_path)
print(f"{share} 30 min done")
# mail
mail_content = f"{cur_date[0:2]}-{cur_month}-{cur_year}"
# The mail addresses and password
sender_address = 'ritikmukta@gmail.com'
# sender_pass = 'deeP@8393'
sender_pass = 'tolh kftf oofa tzcp'
receiver_address = 'soni1_soni1@yahoo.com'
# receiver_address = 'ritikmukta123@gmail.com'
# Setup the MIME
message = MIMEMultipart()
message['From'] = sender_address
message['To'] = receiver_address
message['Subject'] = 'Daily Data Work'
# The subject line
# The body and the attachments for the mail
message.attach(MIMEText(mail_content, 'plain'))
daily_path = rf'E:\sonia daily data\cash\AAPL csh.xlsx'
for each_file_path in attachment_path_list:
try:
file_name = each_file_path.split("\\")[-1]
part = MIMEBase('application', "octet-stream")
part.set_payload(open(each_file_path, "rb").read())
encoders.encode_base64(part)
part.add_header('Content-Disposition', 'attachment', filename=file_name)
message.attach(part)
except:
print("could not attache file")
# Create SMTP session for sending the mail
session = smtplib.SMTP('smtp.gmail.com', 587) # use gmail with port
session.starttls() # enable security
session.login(sender_address, sender_pass) # login with mail_id and password
text = message.as_string()
session.sendmail(sender_address, receiver_address, text)
session.quit()
print('Mail Sent')