using intermediate level python for solving simple and complex tasks

Python has built-in smtplib module for sending emails using the host and port from many service providers out there. We have used gmail host which for smtp is

host = 'smtp.gmail.com'
port = 587

port that we use with gmail emailing service is 587 which required a gmail account.

username = 'any-gmail-account'
password = 'password-for-account'
from_email = username
to_email = ['example1@gmail.com', 'example2@gmail.com', 'example3@gmail.com']

the above are the credentials we can use for sending email, the email we send email from should have a gmail feature enabled, 'let third party apps use the account' or the emails won't send

email_conn = SMTP(host, port)
email_conn.ehlo()
email_conn.starttls()

For connecting to the gmail service we need to start a connection using the SMTP class and starttls is for securing our connection to the server. For logging into the gmail service with our username and password we use,

email_conn.login(username, password)
email_conn.sendmail(from_email, to_email, 'message')

Sending email is as simple as using the sendmail method with three arguemnts Don't forget to close our connection after using the service

email_conn.quit()

For sending html formatted email we need to use the MIMEMultipart and MIMEText from email.mime and create html message and attach it to the email message, then send like the usual sendmail function but replacing the message with our email message.

from email.mime.multipart import MIMEMultipart
from email.mime.text import MIMEText

message = MIMEMultipart("alternative")
message['Subject'] = "Hello there"
message['From'] = from_email
message['To'] = to_list[0]

part_2 = MIMEText(html_text, 'html')
message.attach(part_2)
email_conn.sendmail(from_email, to_list, message.as_string())

We create a new file for rendering context in our template, there is a seperate function for each process, we get the template path from templates folder that has our email template file

Python supports backend web development using the module Flask. There are more options like Django but Flask lets you get started in a lot less amount of time.

We are going to use the SQL database with flask and so we will install the flask_sqlalchemy package using pip

command prompt

pip install flask_sqlalchemy

We import SQLAlchemy from flask_sqlalchemy and create an instance of it

python_flask/models.py

from flask_sqlalchemy import SQLAlchemy
db = SQLAlchemy()

Next we create a model just like we do in Django using

from django import models

class SampleModel(models.Model):
	...

We do the same thing in Flask using the instance we just created and name our model Flight which has four fields namely id, origin, destination, duration which ofcourse matches with the properties of a flight

class Flight(db.Model):
	__tablename__ = "flights"
	id = db.Column(db.Integer, primary_key=True)
	origin = db.Column(db.String, nullable=False)
	destination = db.Column(db.String, nullable=False)
	duration = db.Column(db.Integer, nullable=False)

Python module for handling csv files and data is "csv"

import csv

To create a new csv file we can use the python in-built with command with open method

with open('data.csv', 'w+') as csvfile:
	writer = csv.writer(csvfile)
	writer.writerow(['Title', 'Description'])
	writer.writerow(['New row', 'Awesome description for row'])	

if file data.csv does not exist then open creates one and with opens the file as *csvfile *. csv has writer function which takes in a csv file object and creates a writer for csvfile. Now using the writerow functions we can write rows in our csv file.

W+ in open() means we are opening this file in write mode, which means everything we do with csv file will be written into it and existing content of the file will be erased.

Appending CSV data

import csv

with open('data.csv', 'a') as csvfile:
	writer = csv.writer(csvfile)
	writer.writerow(['Append row', 'append description', 'append summary'])

Reading CSV data

import csv

with open('data.csv', 'r') as csvfile:
	reader = csv.reader(csvfile)
	for row in reader:
		print(row)

There is also DictReader and DictWriter in csv module for reading and writing dict data, there is very less difference in csv.reader and csv.DictReader

The output of csv.reader(csvfile) will look something like this

['Title', 'Description', 'Summary']
['New row', 'Awesome description for row', 'Awesome summary']
['Append row', 'append description', 'append summary']
['Row3', 'Row3', 'Row3']

Whereas the output of csv.DictReader is a more detailed one,

OrderedDict([('Title', 'New row'), ('Description', 'Awesome description for row'), ('Summary', 'Awesome summary')])
OrderedDict([('Title', 'Append row'), ('Description', 'append description'), ('Summary', 'append summary')])
OrderedDict([('Title', 'Row3'), ('Description', 'Row3'), ('Summary', 'Row3')])

The tuples inside the lists say > (row heading, row data)

csv.DictWriter and csv.writer

csv.writer has this simple look and feel

...
	writer = csv.writer(csvfile)
	writer.writerow(['Append row', 'append description', 'append summary'])

csv.DictWriter will be more detailed data filling way, which sometimes is very useful and powerful way of writing data with python csv module

...
	fieldnames = ['Title', 'Description', 'Summary']
	writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
	writer.writerow({'Title': 'Row3', 'Description': 'Row3', 'Summary': 'Row3'})