What is a Python dictionary?

Example,
student = {"Name": "Peter", "Age": "20"}
student = dict(Name="Peter", Age: "20")

How can we access an element from the python dictionary?

student = {"Name": "Peter", "Age": "20"}
print (student['Age'])
print (student['DOB'])
print (student.get('Name'))
print (student.get('DOB', '1/1/2001'))Output,
> 20
> KeyError: 'DOB'
> Peter
> 1/1/2001

How to update the python dictionary?

student = {"Name": "Peter", "Age": "20"}
student.update(Name="James")
print (student)
student.update(DOB="1/01/2001")
print (student)Output,> {"Name": "James", "Age": "20"}
> {"Name": "James", "Age": "20", "DOB": "1/01/2001"}

How to delete the item from python dictionary?

student = {"Name": "Peter", "Age": "20"}
removed_item = student.pop('Age')
print (student)
print (removed_item)Output,> {"Name": "Peter"}
> 20

How to iterate through the python dictionary?

student = {"Name": "James", "Age": "20", "DOB": "1/01/2001"}
for i in student:
    print(student[i])Output,
> James
> 20
> 1/01/2001

Python Dictionary comprehension

dict1= {i:i*2 for i in range(1,5)}
print (dict1)Output,
{1:1, 2:4, 3:6, 4:8}

1. What are the major data structures in python?
   List, Dictionary, Set, and tuple are the major used data structures in Python.
2. What is Decorator in Python?Decorator in special kind of function that we use before executing other function. We can define our own logic in the decorator.
3. What list comprehension in Python?List comprehension is special list property it allows the list to create a list on your own logic.
4. What is lambda function in Python?Lambda function is a unique function in Python. Lambda function is a lightweight substitute of the small method. We can also call as the single line function.
5. What is slicing in Python?Slicing is a special kind of mechanism in which we can select a particular part from String, List, tuple.
6. What is docstring in Python?Python Program document string is also called as the docstring. We can Document the Functions, classes, and modules in Python.
7. What is a negative index in Python?Python has a unique feature of indexing. we can define index in positive and negative. As an example, the positive index starts with 0 and negative index start with -1.
8. What are the major frameworks used in Python?There are many frameworks available for web development but Django and Flask are the major frameworks we use. Flask is used in micro-projects and macro-projects.
9. What is unittest in Python?unittest is a Python framework for unit testing. unittest is very versatile framework used for the module or unit testing.
10. What is PEP-8?PEP-8 is coding convention that how to write effective and readable code.
11. How to define a constructor in Python?In Python, there is special method to define the constructor in Python. we can define constructor by __init__(self) method.
12. What is self in Python?self represents the instance of the class. By using the “self” keyword we can access the attributes and methods of the class in python.

1. append()append method is used to append the data in list. You can append single item in the existing list. 
   Example,languages = [‘Python’, ‘Java’]
   languages.append(‘Ruby’)
   Output:[‘Python’, ‘Java’, ‘Ruby’]
2. extend()extend method is used to add the one list items to end of other list items. You can add the existing list to another list.
   Example,languages = [‘Python’, ‘Java’]
   languages.extend([‘Ruby’, ‘C#’])
   Output:[‘Python’, ‘Java’, ‘Ruby’, ‘C#’]
3. pop()A pop method is used to pop the element from the list. We just need to mention the list index that needs to pop from the list. 
   Example,countries = [‘INDIA’, ‘USA’, ‘RUSSIA’, ‘CHINA’]
   removed_country = countries.pop(3)
   print countries
   print removed_country
   Output:[‘INDIA’, ‘USA’, ‘RUSSIA’]
   CHINA
4. count()count method is used to count the number of time occurrence of the element. Like if you want to find how the number of occurrence of the word ‘hello’ you can use count function.
   Example,words = [‘hello’, ‘India’, ‘hello’, ‘USA’]
   word_count = words.count(‘hello’)
   print word_count
   Output:> 2
5. insert()Insert method is used to insert the particular element at a particular index in the list. 
   Example,words = [‘hello’, ‘India’, ‘hello’, ‘USA’]
   words.insert(2, ‘new’)
   print words
   Output:[‘hello’, ‘India’, ‘new’, ‘hello’, ‘USA’]
6. remove()Remove method is used to remove the particular element from the list.
   Example,words = [‘hello’, ‘India’, ‘new’, ‘hello’, ‘USA’]
   words.remove(‘new’)
   print words
   Output:[‘hello’, ‘India’, ‘hello’, ‘USA’]
7. sort()Sort method is used to sort the list elements. You can sort the list by ascending or descending order.
   Example,l1 = [‘a’, ’n’, ‘t’, ‘k’]
   print l1.sort()
   print l1.sort(reverse=true)
   Output:
   > [‘a’, ’k’, ‘n’, ‘t’]
   > [‘t’, ’n’, ‘k’, ‘a’]

1. List
2. Dictionary
3. Tuple
4. set

1. List
   The list is a very versatile data structure in python. In most cases the list is useful. The list can contain the number, string and even list also. In most cases, we use the list as an array or we can say it like it is a stack. In list we can do an operation like insertion, deletion, slicing, and losts of other functionality. The list is Mutable type of data structure.
   Example,
   L 1 = [1, “test” , “python” , [1,2]] 
   print L1
   Output:
   [1, “test” , “python” , [1,2]]
2. DictionaryDictionary is very similar to the map in other languages. Dictionary used to store the key, value pair data. Dictionary is used to store JSON kind of data. In the dictionary, there should be a unique key for every value. In some cases, we can define our own class for storing multiple values in the same key. Normally the usage of a dictionary is to create JSON object and get JSON Data. There are lots of functions for the dictionary like get() function, update() function etc. 
   Example,
   D1 = {“name”: “Python”, “type”: “oop Language”}
   print D1
   Output:{“name”: “Python”, “type”: “oop Language”}
3. TupleThe tuple is similar to list. normally we can not change the tuple data so it is called an immutable data structure in python. In the list we store data in square brackets and tuple we store data in round brackets. We can do slicing in the tuple. There are few functions that we can perform with tuple like count(), index().
   Example,
   T1 = (0, 1, 2, 3)
   print T1
   Output:(0, 1, 2, 3)
4. SetsSets contain unique data. In set, we store unique data duplicate data can not be stored in sets. we can do operations like union, intersection, etc. Normally we use set for storing the unique data. To create the set we need to call the set() method or by just creating a dictionary with the only keys. We can do the operations like add, remove, etc.
   Example,
   S1 = {“Python”, “Java”, “Ruby”}
   print S1
   Output:{‘apple’, ‘cherry’}

npm install -g serverless

sls

# This is your service name.
service: test-service 
provider:
  name: aws
  runtime: python3.7

  # you can overwrite defaults here
  stage: ${opt:stage,'dev'}
  region: ${opt:region, 'us-east-2'}
  timeout: 120
  memorySize: 2014

# you can add statements to the Lambda function's IAM Role here
  iamRoleStatements:
    - Effect: 'Allow'
      Action:
        - 's3:PutObject'
        - 's3:GetObject'
        - 'ses:SendEmail'
        - 'ses:SendRawEmail'
        - 'sqs:SendMessage'
        - 'sqs:GetQueueUrl'
      Resource: '*'

plugins:
  - serverless-python-requirements

custom:
  pythonRequirements:
    dockerizePip: true# This is how we can create lambda for perticular trigger.     functions:
  testlambda:
    handler: lamdas/test/test_lambda
    description: Test lambda
    timeout: 300
    events:
      - schedule:
          rate: rate(2 minutes)
          enabled: true# This is how we can create the s3 bucketresources:
  Resources:
    S3BucketTest:
      Type: AWS::S3::Bucket
      Properties:
        BucketName: test-bucket

serverless deploy -v

sls invoke -f testlambda -l

pip install flask

import resources
from flask import Flask

def create_app():
    app = Flask('DEMO-APP')
    resources.create_api(app)
    return app


app = create_app()
app.run(host='0.0.0.0', port=9909, debug=True)

from flask_cors import CORS
from flask_restful import Api
from test_api import TestAPI


def create_api(app):
    # added cors as it was only giving pre-flight request
    CORS(app, resources={r"/*": {"origins": "*"}})
    api = Api(app, prefix='/api/')
    api.add_resource(TestAPI, "test")

from flask import current_app as app
from flask_restful import Resource

class TestAPI(Resource):

    def __init__(self):
        app.logger.info('In the constructor of {}'.format(self.__class__.__name__))

    def get(self):
        app.logger.info('Test API get request called')
        return True

python app.py

http://localhost:9909/api/test

pip install alembic

alembic init alembic

<project root>
├── src
│   └── <top-level package dir>
│       ├── alembic
│       │   ├── env.py
│       │   ├── README
│       │   ├── script.py.mako
│       │   └── versions
│       │       ├── 58c8dcd5fbdc_revision_1.py
│       │       └── ec385b47da23_revision_2.py
│       ├── alembic.ini
│       ├── __init__.py
│       └── <other files and dirs>
└── <other files and dirs>

sqlalchemy.url = mysql+mysqldb://root:root@localhost:3306/database_name

from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy import Column, String, TIMESTAMP, text, JSON
from sqlalchemy.dialects.mysql import INTEGER
Base = declarative_base()
metadata = Base.metadataclass Student(Base):

    __tablename__ = 'student'

    id = Column(INTEGER(11), primary_key=True)
    enroll = Column(INTEGER(11))
    personal_info = Column(JSON)
    name= Column(String(255))
    created_on = Column(TIMESTAMP, nullable=False, server_default=text("CURRENT_TIMESTAMP"))

from model import Base
target_metadata = [Base.metadata]

alembic revision — autogenerate -m “First commit”

alembic upgrade head