How to Create Calendar and Set Event into Database in Blazor

Blazor Calendar Example monthly view using Modal. Monthly View Calendar using Blazor Example. 
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A Simple Wrapper Around Amplify AppSync Simulator

This serverless plugin is a wrapper for amplify-appsync-simulator made for testing AppSync APIs built with serverless-appsync-plugin.

Install

npm install serverless-appsync-simulator
# or
yarn add serverless-appsync-simulator

Usage

This plugin relies on your serverless yml file and on the serverless-offline plugin.

plugins:
  - serverless-dynamodb-local # only if you need dynamodb resolvers and you don't have an external dynamodb
  - serverless-appsync-simulator
  - serverless-offline

Note: Order is important serverless-appsync-simulator must go before serverless-offline

To start the simulator, run the following command:

sls offline start

You should see in the logs something like:

...
Serverless: AppSync endpoint: http://localhost:20002/graphql
Serverless: GraphiQl: http://localhost:20002
...

Configuration

Put options under custom.appsync-simulator in your serverless.yml file

| option | default | description | | ------------------------ | -------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------- | | apiKey | 0123456789 | When using API_KEY as authentication type, the key to authenticate to the endpoint. | | port | 20002 | AppSync operations port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20002, 20012, 20022, etc.) | | wsPort | 20003 | AppSync subscriptions port; if using multiple APIs, the value of this option will be used as a starting point, and each other API will have a port of lastPort + 10 (e.g. 20003, 20013, 20023, etc.) | | location | . (base directory) | Location of the lambda functions handlers. | | refMap | {} | A mapping of resource resolutions for the Ref function | | getAttMap | {} | A mapping of resource resolutions for the GetAtt function | | importValueMap | {} | A mapping of resource resolutions for the ImportValue function | | functions | {} | A mapping of external functions for providing invoke url for external fucntions | | dynamoDb.endpoint | http://localhost:8000 | Dynamodb endpoint. Specify it if you're not using serverless-dynamodb-local. Otherwise, port is taken from dynamodb-local conf | | dynamoDb.region | localhost | Dynamodb region. Specify it if you're connecting to a remote Dynamodb intance. | | dynamoDb.accessKeyId | DEFAULT_ACCESS_KEY | AWS Access Key ID to access DynamoDB | | dynamoDb.secretAccessKey | DEFAULT_SECRET | AWS Secret Key to access DynamoDB | | dynamoDb.sessionToken | DEFAULT_ACCESS_TOKEEN | AWS Session Token to access DynamoDB, only if you have temporary security credentials configured on AWS | | dynamoDb.* | | You can add every configuration accepted by DynamoDB SDK | | rds.dbName | | Name of the database | | rds.dbHost | | Database host | | rds.dbDialect | | Database dialect. Possible values (mysql | postgres) | | rds.dbUsername | | Database username | | rds.dbPassword | | Database password | | rds.dbPort | | Database port | | watch | - *.graphql
- *.vtl | Array of glob patterns to watch for hot-reloading. |

Example:

custom:
  appsync-simulator:
    location: '.webpack/service' # use webpack build directory
    dynamoDb:
      endpoint: 'http://my-custom-dynamo:8000'

Hot-reloading

By default, the simulator will hot-relad when changes to *.graphql or *.vtl files are detected. Changes to *.yml files are not supported (yet? - this is a Serverless Framework limitation). You will need to restart the simulator each time you change yml files.

Hot-reloading relies on watchman. Make sure it is installed on your system.

You can change the files being watched with the watch option, which is then passed to watchman as the match expression.

e.g.

custom:
  appsync-simulator:
    watch:
      - ["match", "handlers/**/*.vtl", "wholename"] # => array is interpreted as the literal match expression
      - "*.graphql"                                 # => string like this is equivalent to `["match", "*.graphql"]`

Or you can opt-out by leaving an empty array or set the option to false

Note: Functions should not require hot-reloading, unless you are using a transpiler or a bundler (such as webpack, babel or typescript), un which case you should delegate hot-reloading to that instead.

Resource CloudFormation functions resolution

This plugin supports some resources resolution from the Ref, Fn::GetAtt and Fn::ImportValue functions in your yaml file. It also supports some other Cfn functions such as Fn::Join, Fb::Sub, etc.

Note: Under the hood, this features relies on the cfn-resolver-lib package. For more info on supported cfn functions, refer to the documentation

Basic usage

You can reference resources in your functions' environment variables (that will be accessible from your lambda functions) or datasource definitions. The plugin will automatically resolve them for you.

provider:
  environment:
    BUCKET_NAME:
      Ref: MyBucket # resolves to `my-bucket-name`

resources:
  Resources:
    MyDbTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: myTable
      ...
    MyBucket:
      Type: AWS::S3::Bucket
      Properties:
        BucketName: my-bucket-name
    ...

# in your appsync config
dataSources:
  - type: AMAZON_DYNAMODB
    name: dynamosource
    config:
      tableName:
        Ref: MyDbTable # resolves to `myTable`

Override (or mock) values

Sometimes, some references cannot be resolved, as they come from an Output from Cloudformation; or you might want to use mocked values in your local environment.

In those cases, you can define (or override) those values using the refMap, getAttMap and importValueMap options.

• refMap takes a mapping of resource name to value pairs
• getAttMap takes a mapping of resource name to attribute/values pairs
• importValueMap takes a mapping of import name to values pairs

Example:

custom:
  appsync-simulator:
    refMap:
      # Override `MyDbTable` resolution from the previous example.
      MyDbTable: 'mock-myTable'
    getAttMap:
      # define ElasticSearchInstance DomainName
      ElasticSearchInstance:
        DomainEndpoint: 'localhost:9200'
    importValueMap:
      other-service-api-url: 'https://other.api.url.com/graphql'

# in your appsync config
dataSources:
  - type: AMAZON_ELASTICSEARCH
    name: elasticsource
    config:
      # endpoint resolves as 'http://localhost:9200'
      endpoint:
        Fn::Join:
          - ''
          - - https://
            - Fn::GetAtt:
                - ElasticSearchInstance
                - DomainEndpoint

Key-value mock notation

In some special cases you will need to use key-value mock nottation. Good example can be case when you need to include serverless stage value (${self:provider.stage}) in the import name.

This notation can be used with all mocks - refMap, getAttMap and importValueMap

provider:
  environment:
    FINISH_ACTIVITY_FUNCTION_ARN:
      Fn::ImportValue: other-service-api-${self:provider.stage}-url

custom:
  serverless-appsync-simulator:
    importValueMap:
      - key: other-service-api-${self:provider.stage}-url
        value: 'https://other.api.url.com/graphql'

Limitations

This plugin only tries to resolve the following parts of the yml tree:

• provider.environment
• functions[*].environment
• custom.appSync

If you have the need of resolving others, feel free to open an issue and explain your use case.

For now, the supported resources to be automatically resovled by Ref: are:

• DynamoDb tables
• S3 Buckets

Feel free to open a PR or an issue to extend them as well.

External functions

When a function is not defined withing the current serverless file you can still call it by providing an invoke url which should point to a REST method. Make sure you specify "get" or "post" for the method. Default is "get", but you probably want "post".

custom:
  appsync-simulator:
    functions:
      addUser:
        url: http://localhost:3016/2015-03-31/functions/addUser/invocations
        method: post
      addPost:
        url: https://jsonplaceholder.typicode.com/posts
        method: post

Supported Resolver types

This plugin supports resolvers implemented by amplify-appsync-simulator, as well as custom resolvers.

From Aws Amplify:

• NONE
• AWS_LAMBDA
• AMAZON_DYNAMODB
• PIPELINE

Implemented by this plugin

• AMAZON_ELASTIC_SEARCH
• HTTP
• RELATIONAL_DATABASE

Relational Database

Sample VTL for a create mutation

#set( $cols = [] )
#set( $vals = [] )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #set( $discard = $cols.add("$toSnake") )
  #if( $util.isBoolean($ctx.args.input[$entry]) )
      #if( $ctx.args.input[$entry] )
        #set( $discard = $vals.add("1") )
      #else
        #set( $discard = $vals.add("0") )
      #end
  #else
      #set( $discard = $vals.add("'$ctx.args.input[$entry]'") )
  #end
#end
#set( $valStr = $vals.toString().replace("[","(").replace("]",")") )
#set( $colStr = $cols.toString().replace("[","(").replace("]",")") )
#if ( $valStr.substring(0, 1) != '(' )
  #set( $valStr = "($valStr)" )
#end
#if ( $colStr.substring(0, 1) != '(' )
  #set( $colStr = "($colStr)" )
#end
{
  "version": "2018-05-29",
  "statements":   ["INSERT INTO <name-of-table> $colStr VALUES $valStr", "SELECT * FROM    <name-of-table> ORDER BY id DESC LIMIT 1"]
}

Sample VTL for an update mutation

#set( $update = "" )
#set( $equals = "=" )
#foreach( $entry in $ctx.args.input.keySet() )
  #set( $cur = $ctx.args.input[$entry] )
  #set( $regex = "([a-z])([A-Z]+)")
  #set( $replacement = "$1_$2")
  #set( $toSnake = $entry.replaceAll($regex, $replacement).toLowerCase() )
  #if( $util.isBoolean($cur) )
      #if( $cur )
        #set ( $cur = "1" )
      #else
        #set ( $cur = "0" )
      #end
  #end
  #if ( $util.isNullOrEmpty($update) )
      #set($update = "$toSnake$equals'$cur'" )
  #else
      #set($update = "$update,$toSnake$equals'$cur'" )
  #end
#end
{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> SET $update WHERE id=$ctx.args.input.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.input.id"]
}

Sample resolver for delete mutation

{
  "version": "2018-05-29",
  "statements":   ["UPDATE <name-of-table> set deleted_at=NOW() WHERE id=$ctx.args.id", "SELECT * FROM <name-of-table> WHERE id=$ctx.args.id"]
}

Sample mutation response VTL with support for handling AWSDateTime

#set ( $index = -1)
#set ( $result = $util.parseJson($ctx.result) )
#set ( $meta = $result.sqlStatementResults[1].columnMetadata)
#foreach ($column in $meta)
    #set ($index = $index + 1)
    #if ( $column["typeName"] == "timestamptz" )
        #set ($time = $result["sqlStatementResults"][1]["records"][0][$index]["stringValue"] )
        #set ( $nowEpochMillis = $util.time.parseFormattedToEpochMilliSeconds("$time.substring(0,19)+0000", "yyyy-MM-dd HH:mm:ssZ") )
        #set ( $isoDateTime = $util.time.epochMilliSecondsToISO8601($nowEpochMillis) )
        $util.qr( $result["sqlStatementResults"][1]["records"][0][$index].put("stringValue", "$isoDateTime") )
    #end
#end
#set ( $res = $util.parseJson($util.rds.toJsonString($util.toJson($result)))[1][0] )
#set ( $response = {} )
#foreach($mapKey in $res.keySet())
    #set ( $s = $mapKey.split("_") )
    #set ( $camelCase="" )
    #set ( $isFirst=true )
    #foreach($entry in $s)
        #if ( $isFirst )
          #set ( $first = $entry.substring(0,1) )
        #else
          #set ( $first = $entry.substring(0,1).toUpperCase() )
        #end
        #set ( $isFirst=false )
        #set ( $stringLength = $entry.length() )
        #set ( $remaining = $entry.substring(1, $stringLength) )
        #set ( $camelCase = "$camelCase$first$remaining" )
    #end
    $util.qr( $response.put("$camelCase", $res[$mapKey]) )
#end
$utils.toJson($response)

Using Variable Map

Variable map support is limited and does not differentiate numbers and strings data types, please inject them directly if needed.

Will be escaped properly: null, true, and false values.

{
  "version": "2018-05-29",
  "statements":   [
    "UPDATE <name-of-table> set deleted_at=NOW() WHERE id=:ID",
    "SELECT * FROM <name-of-table> WHERE id=:ID and unix_timestamp > $ctx.args.newerThan"
  ],
  variableMap: {
    ":ID": $ctx.args.id,
##    ":TIMESTAMP": $ctx.args.newerThan -- This will be handled as a string!!!
  }
}

Requires

• serverless framework
• serverless-appsync-plugin
• serverless-offline
• serverless-dynamodb-local (when using dynamodb resolvers only)
• watchman (if Hot-reloading is desactivated it is not required)

Author: Serverless-appsync
Source Code: https://github.com/serverless-appsync/serverless-appsync-simulator 
License: MIT License

#serverless #sync #graphql 

PyTumblr: A Python Tumblr API v2 Client

PyTumblr

Installation

Install via pip:

$ pip install pytumblr

Install from source:

$ git clone https://github.com/tumblr/pytumblr.git
$ cd pytumblr
$ python setup.py install

Usage

Create a client

A pytumblr.TumblrRestClient is the object you'll make all of your calls to the Tumblr API through. Creating one is this easy:

client = pytumblr.TumblrRestClient(
    '<consumer_key>',
    '<consumer_secret>',
    '<oauth_token>',
    '<oauth_secret>',
)

client.info() # Grabs the current user information

Two easy ways to get your credentials to are:

1. The built-in interactive_console.py tool (if you already have a consumer key & secret)
2. The Tumblr API console at https://api.tumblr.com/console
3. Get sample login code at https://api.tumblr.com/console/calls/user/info

Supported Methods

User Methods

client.info() # get information about the authenticating user
client.dashboard() # get the dashboard for the authenticating user
client.likes() # get the likes for the authenticating user
client.following() # get the blogs followed by the authenticating user

client.follow('codingjester.tumblr.com') # follow a blog
client.unfollow('codingjester.tumblr.com') # unfollow a blog

client.like(id, reblogkey) # like a post
client.unlike(id, reblogkey) # unlike a post

Blog Methods

client.blog_info(blogName) # get information about a blog
client.posts(blogName, **params) # get posts for a blog
client.avatar(blogName) # get the avatar for a blog
client.blog_likes(blogName) # get the likes on a blog
client.followers(blogName) # get the followers of a blog
client.blog_following(blogName) # get the publicly exposed blogs that [blogName] follows
client.queue(blogName) # get the queue for a given blog
client.submission(blogName) # get the submissions for a given blog

Post Methods

Creating posts

PyTumblr lets you create all of the various types that Tumblr supports. When using these types there are a few defaults that are able to be used with any post type.

The default supported types are described below.

• state - a string, the state of the post. Supported types are published, draft, queue, private
• tags - a list, a list of strings that you want tagged on the post. eg: ["testing", "magic", "1"]
• tweet - a string, the string of the customized tweet you want. eg: "Man I love my mega awesome post!"
• date - a string, the customized GMT that you want
• format - a string, the format that your post is in. Support types are html or markdown
• slug - a string, the slug for the url of the post you want

We'll show examples throughout of these default examples while showcasing all the specific post types.

Creating a photo post

Creating a photo post supports a bunch of different options plus the described default options * caption - a string, the user supplied caption * link - a string, the "click-through" url for the photo * source - a string, the url for the photo you want to use (use this or the data parameter) * data - a list or string, a list of filepaths or a single file path for multipart file upload

#Creates a photo post using a source URL
client.create_photo(blogName, state="published", tags=["testing", "ok"],
                    source="https://68.media.tumblr.com/b965fbb2e501610a29d80ffb6fb3e1ad/tumblr_n55vdeTse11rn1906o1_500.jpg")

#Creates a photo post using a local filepath
client.create_photo(blogName, state="queue", tags=["testing", "ok"],
                    tweet="Woah this is an incredible sweet post [URL]",
                    data="/Users/johnb/path/to/my/image.jpg")

#Creates a photoset post using several local filepaths
client.create_photo(blogName, state="draft", tags=["jb is cool"], format="markdown",
                    data=["/Users/johnb/path/to/my/image.jpg", "/Users/johnb/Pictures/kittens.jpg"],
                    caption="## Mega sweet kittens")

Creating a text post

Creating a text post supports the same options as default and just a two other parameters * title - a string, the optional title for the post. Supports markdown or html * body - a string, the body of the of the post. Supports markdown or html

#Creating a text post
client.create_text(blogName, state="published", slug="testing-text-posts", title="Testing", body="testing1 2 3 4")

Creating a quote post

Creating a quote post supports the same options as default and two other parameter * quote - a string, the full text of the qote. Supports markdown or html * source - a string, the cited source. HTML supported

#Creating a quote post
client.create_quote(blogName, state="queue", quote="I am the Walrus", source="Ringo")

Creating a link post

• title - a string, the title of post that you want. Supports HTML entities.
• url - a string, the url that you want to create a link post for.
• description - a string, the desciption of the link that you have

#Create a link post
client.create_link(blogName, title="I like to search things, you should too.", url="https://duckduckgo.com",
                   description="Search is pretty cool when a duck does it.")

Creating a chat post

Creating a chat post supports the same options as default and two other parameters * title - a string, the title of the chat post * conversation - a string, the text of the conversation/chat, with diablog labels (no html)

#Create a chat post
chat = """John: Testing can be fun!
Renee: Testing is tedious and so are you.
John: Aw.
"""
client.create_chat(blogName, title="Renee just doesn't understand.", conversation=chat, tags=["renee", "testing"])

Creating an audio post

Creating an audio post allows for all default options and a has 3 other parameters. The only thing to keep in mind while dealing with audio posts is to make sure that you use the external_url parameter or data. You cannot use both at the same time. * caption - a string, the caption for your post * external_url - a string, the url of the site that hosts the audio file * data - a string, the filepath of the audio file you want to upload to Tumblr

#Creating an audio file
client.create_audio(blogName, caption="Rock out.", data="/Users/johnb/Music/my/new/sweet/album.mp3")

#lets use soundcloud!
client.create_audio(blogName, caption="Mega rock out.", external_url="https://soundcloud.com/skrillex/sets/recess")

Creating a video post

Creating a video post allows for all default options and has three other options. Like the other post types, it has some restrictions. You cannot use the embed and data parameters at the same time. * caption - a string, the caption for your post * embed - a string, the HTML embed code for the video * data - a string, the path of the file you want to upload

#Creating an upload from YouTube
client.create_video(blogName, caption="Jon Snow. Mega ridiculous sword.",
                    embed="http://www.youtube.com/watch?v=40pUYLacrj4")

#Creating a video post from local file
client.create_video(blogName, caption="testing", data="/Users/johnb/testing/ok/blah.mov")

Editing a post

Updating a post requires you knowing what type a post you're updating. You'll be able to supply to the post any of the options given above for updates.

client.edit_post(blogName, id=post_id, type="text", title="Updated")
client.edit_post(blogName, id=post_id, type="photo", data="/Users/johnb/mega/awesome.jpg")

Reblogging a Post

Reblogging a post just requires knowing the post id and the reblog key, which is supplied in the JSON of any post object.

client.reblog(blogName, id=125356, reblog_key="reblog_key")

Deleting a post

Deleting just requires that you own the post and have the post id

client.delete_post(blogName, 123456) # Deletes your post :(

A note on tags: When passing tags, as params, please pass them as a list (not a comma-separated string):

client.create_text(blogName, tags=['hello', 'world'], ...)

Getting notes for a post

In order to get the notes for a post, you need to have the post id and the blog that it is on.

data = client.notes(blogName, id='123456')

The results include a timestamp you can use to make future calls.

data = client.notes(blogName, id='123456', before_timestamp=data["_links"]["next"]["query_params"]["before_timestamp"])

Tagged Methods

# get posts with a given tag
client.tagged(tag, **params)

Using the interactive console

This client comes with a nice interactive console to run you through the OAuth process, grab your tokens (and store them for future use).

You'll need pyyaml installed to run it, but then it's just:

$ python interactive-console.py

and away you go! Tokens are stored in ~/.tumblr and are also shared by other Tumblr API clients like the Ruby client.

Running tests

The tests (and coverage reports) are run with nose, like this:

python setup.py test

Author: tumblr
Source Code: https://github.com/tumblr/pytumblr
License: Apache-2.0 license

#python #api 

Exploring Mutable and Immutable in Python

In this Python article, let's learn about Mutable and Immutable in Python. 

Mutable and Immutable in Python

Mutable is a fancy way of saying that the internal state of the object is changed/mutated. So, the simplest definition is: An object whose internal state can be changed is mutable. On the other hand, immutable doesn’t allow any change in the object once it has been created.

Both of these states are integral to Python data structure. If you want to become more knowledgeable in the entire Python Data Structure, take this free course which covers multiple data structures in Python including tuple data structure which is immutable. You will also receive a certificate on completion which is sure to add value to your portfolio.

Mutable Definition

Mutable is when something is changeable or has the ability to change. In Python, ‘mutable’ is the ability of objects to change their values. These are often the objects that store a collection of data.

Immutable Definition

Immutable is the when no change is possible over time. In Python, if the value of an object cannot be changed over time, then it is known as immutable. Once created, the value of these objects is permanent.

List of Mutable and Immutable objects

Objects of built-in type that are mutable are:

• Lists
• Sets
• Dictionaries
• User-Defined Classes (It purely depends upon the user to define the characteristics) 

Objects of built-in type that are immutable are:

• Numbers (Integer, Rational, Float, Decimal, Complex & Booleans)
• Strings
• Tuples
• Frozen Sets
• User-Defined Classes (It purely depends upon the user to define the characteristics)

Object mutability is one of the characteristics that makes Python a dynamically typed language. Though Mutable and Immutable in Python is a very basic concept, it can at times be a little confusing due to the intransitive nature of immutability.

Objects in Python

In Python, everything is treated as an object. Every object has these three attributes:

• Identity – This refers to the address that the object refers to in the computer’s memory.
• Type – This refers to the kind of object that is created. For example- integer, list, string etc. 
• Value – This refers to the value stored by the object. For example – List=[1,2,3] would hold the numbers 1,2 and 3

While ID and Type cannot be changed once it’s created, values can be changed for Mutable objects.

Check out this free python certificate course to get started with Python.

Mutable Objects in Python

I believe, rather than diving deep into the theory aspects of mutable and immutable in Python, a simple code would be the best way to depict what it means in Python. Hence, let us discuss the below code step-by-step:

#Creating a list which contains name of Indian cities  

cities = [‘Delhi’, ‘Mumbai’, ‘Kolkata’]

# Printing the elements from the list cities, separated by a comma & space

for city in cities:
		print(city, end=’, ’)

Output [1]: Delhi, Mumbai, Kolkata

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(cities)))

Output [2]: 0x1691d7de8c8

#Adding a new city to the list cities

cities.append(‘Chennai’)

#Printing the elements from the list cities, separated by a comma & space 

for city in cities:
	print(city, end=’, ’)

Output [3]: Delhi, Mumbai, Kolkata, Chennai

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(cities)))

Output [4]: 0x1691d7de8c8

The above example shows us that we were able to change the internal state of the object ‘cities’ by adding one more city ‘Chennai’ to it, yet, the memory address of the object did not change. This confirms that we did not create a new object, rather, the same object was changed or mutated. Hence, we can say that the object which is a type of list with reference variable name ‘cities’ is a MUTABLE OBJECT.

Let us now discuss the term IMMUTABLE. Considering that we understood what mutable stands for, it is obvious that the definition of immutable will have ‘NOT’ included in it. Here is the simplest definition of immutable– An object whose internal state can NOT be changed is IMMUTABLE.

Again, if you try and concentrate on different error messages, you have encountered, thrown by the respective IDE; you use you would be able to identify the immutable objects in Python. For instance, consider the below code & associated error message with it, while trying to change the value of a Tuple at index 0. 

#Creating a Tuple with variable name ‘foo’

foo = (1, 2)

#Changing the index[0] value from 1 to 3

foo[0] = 3
	
TypeError: 'tuple' object does not support item assignment 

Immutable Objects in Python

Once again, a simple code would be the best way to depict what immutable stands for. Hence, let us discuss the below code step-by-step:

#Creating a Tuple which contains English name of weekdays

weekdays = ‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’

# Printing the elements of tuple weekdays

print(weekdays)

Output [1]:  (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’)

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(weekdays)))

Output [2]: 0x1691cc35090

#tuples are immutable, so you cannot add new elements, hence, using merge of tuples with the # + operator to add a new imaginary day in the tuple ‘weekdays’

weekdays  +=  ‘Pythonday’,

#Printing the elements of tuple weekdays

print(weekdays)

Output [3]: (‘Sunday’, ‘Monday’, ‘Tuesday’, ‘Wednesday’, ‘Thursday’, ‘Friday’, ‘Saturday’, ‘Pythonday’)

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(weekdays)))

Output [4]: 0x1691cc8ad68

This above example shows that we were able to use the same variable name that is referencing an object which is a type of tuple with seven elements in it. However, the ID or the memory location of the old & new tuple is not the same. We were not able to change the internal state of the object ‘weekdays’. The Python program manager created a new object in the memory address and the variable name ‘weekdays’ started referencing the new object with eight elements in it.  Hence, we can say that the object which is a type of tuple with reference variable name ‘weekdays’ is an IMMUTABLE OBJECT.

Also Read: Understanding the Exploratory Data Analysis (EDA) in Python

Where can you use mutable and immutable objects:

Mutable objects can be used where you want to allow for any updates. For example, you have a list of employee names in your organizations, and that needs to be updated every time a new member is hired. You can create a mutable list, and it can be updated easily.

Immutability offers a lot of useful applications to different sensitive tasks we do in a network centred environment where we allow for parallel processing. By creating immutable objects, you seal the values and ensure that no threads can invoke overwrite/update to your data. This is also useful in situations where you would like to write a piece of code that cannot be modified. For example, a debug code that attempts to find the value of an immutable object.

Watch outs:  Non transitive nature of Immutability:

OK! Now we do understand what mutable & immutable objects in Python are. Let’s go ahead and discuss the combination of these two and explore the possibilities. Let’s discuss, as to how will it behave if you have an immutable object which contains the mutable object(s)? Or vice versa? Let us again use a code to understand this behaviour–

#creating a tuple (immutable object) which contains 2 lists(mutable) as it’s elements

#The elements (lists) contains the name, age & gender 

person = (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the tuple

print(person)

Output [1]: (['Ayaan', 5, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(person)))

Output [2]: 0x1691ef47f88

#Changing the age for the 1st element. Selecting 1st element of tuple by using indexing [0] then 2nd element of the list by using indexing [1] and assigning a new value for age as 4

person[0][1] = 4

#printing the updated tuple

print(person)

Output [3]: (['Ayaan', 4, 'Male'], ['Aaradhya', 8, 'Female'])

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(person)))

Output [4]: 0x1691ef47f88

In the above code, you can see that the object ‘person’ is immutable since it is a type of tuple. However, it has two lists as it’s elements, and we can change the state of lists (lists being mutable). So, here we did not change the object reference inside the Tuple, but the referenced object was mutated.

Also Read: Real-Time Object Detection Using TensorFlow

Same way, let’s explore how it will behave if you have a mutable object which contains an immutable object? Let us again use a code to understand the behaviour–

#creating a list (mutable object) which contains tuples(immutable) as it’s elements

list1 = [(1, 2, 3), (4, 5, 6)]

#printing the list

print(list1)

Output [1]: [(1, 2, 3), (4, 5, 6)]

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(list1)))

Output [2]: 0x1691d5b13c8	

#changing object reference at index 0

list1[0] = (7, 8, 9)

#printing the list

Output [3]: [(7, 8, 9), (4, 5, 6)]

#printing the location of the object created in the memory address in hexadecimal format

print(hex(id(list1)))

Output [4]: 0x1691d5b13c8

As an individual, it completely depends upon you and your requirements as to what kind of data structure you would like to create with a combination of mutable & immutable objects. I hope that this information will help you while deciding the type of object you would like to select going forward.

Before I end our discussion on IMMUTABILITY, allow me to use the word ‘CAVITE’ when we discuss the String and Integers. There is an exception, and you may see some surprising results while checking the truthiness for immutability. For instance:
#creating an object of integer type with value 10 and reference variable name ‘x’ 

x = 10
 

#printing the value of ‘x’

print(x)

Output [1]: 10

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(x)))

Output [2]: 0x538fb560

#creating an object of integer type with value 10 and reference variable name ‘y’

y = 10

#printing the value of ‘y’

print(y)

Output [3]: 10

#Printing the location of the object created in the memory address in hexadecimal format

print(hex(id(y)))

Output [4]: 0x538fb560

As per our discussion and understanding, so far, the memory address for x & y should have been different, since, 10 is an instance of Integer class which is immutable. However, as shown in the above code, it has the same memory address. This is not something that we expected. It seems that what we have understood and discussed, has an exception as well.

Quick check – Python Data Structures

Immutability of Tuple

Tuples are immutable and hence cannot have any changes in them once they are created in Python. This is because they support the same sequence operations as strings. We all know that strings are immutable. The index operator will select an element from a tuple just like in a string. Hence, they are immutable.

Exceptions in immutability

Like all, there are exceptions in the immutability in python too. Not all immutable objects are really mutable. This will lead to a lot of doubts in your mind. Let us just take an example to understand this.

Consider a tuple ‘tup’.

Now, if we consider tuple tup = (‘GreatLearning’,[4,3,1,2]) ;

We see that the tuple has elements of different data types. The first element here is a string which as we all know is immutable in nature. The second element is a list which we all know is mutable. Now, we all know that the tuple itself is an immutable data type. It cannot change its contents. But, the list inside it can change its contents. So, the value of the Immutable objects cannot be changed but its constituent objects can. change its value.

FAQs

1. Difference between mutable vs immutable in Python?

Mutable Object	Immutable Object
State of the object can be modified after it is created.	State of the object can’t be modified once it is created.
They are not thread safe.	They are thread safe
Mutable classes are not final.	It is important to make the class final before creating an immutable object.

2. What are the mutable and immutable data types in Python?

• Some mutable data types in Python are:

list, dictionary, set, user-defined classes.

• Some immutable data types are: 

int, float, decimal, bool, string, tuple, range.

3. Are lists mutable in Python?

Lists in Python are mutable data types as the elements of the list can be modified, individual elements can be replaced, and the order of elements can be changed even after the list has been created.
(Examples related to lists have been discussed earlier in this blog.)

4. Why are tuples called immutable types?

Tuple and list data structures are very similar, but one big difference between the data types is that lists are mutable, whereas tuples are immutable. The reason for the tuple’s immutability is that once the elements are added to the tuple and the tuple has been created; it remains unchanged.

A programmer would always prefer building a code that can be reused instead of making the whole data object again. Still, even though tuples are immutable, like lists, they can contain any Python object, including mutable objects.

5. Are sets mutable in Python?

A set is an iterable unordered collection of data type which can be used to perform mathematical operations (like union, intersection, difference etc.). Every element in a set is unique and immutable, i.e. no duplicate values should be there, and the values can’t be changed. However, we can add or remove items from the set as the set itself is mutable.

6. Are strings mutable in Python?

Strings are not mutable in Python. Strings are a immutable data types which means that its value cannot be updated.

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---

Original article source at: https://www.mygreatlearning.com

#python 

Django-allauth: A simple Boilerplate to Setup Authentication

Django-Authentication 

A simple Boilerplate to Setup Authentication using Django-allauth, with a custom template for login and registration using django-crispy-forms.

Getting Started

Prerequisites

• Python 3.8.6 or higher

Project setup

# clone the repo
$ git clone https://github.com/yezz123/Django-Authentication

# move to the project folder
$ cd Django-Authentication

Creating virtual environment

• Create a virtual environment for this project:

# creating pipenv environment for python 3
$ virtualenv venv

# activating the pipenv environment
$ cd venv/bin #windows environment you activate from Scripts folder

# if you have multiple python 3 versions installed then
$ source ./activate

Configured Enviromment

Environment variables

SECRET_KEY = #random string
DEBUG = #True or False
ALLOWED_HOSTS = #localhost
DATABASE_NAME = #database name (You can just use the default if you want to use SQLite)
DATABASE_USER = #database user for postgres
DATABASE_PASSWORD = #database password for postgres
DATABASE_HOST = #database host for postgres
DATABASE_PORT = #database port for postgres
ACCOUNT_EMAIL_VERIFICATION = #mandatory or optional
EMAIL_BACKEND = #email backend
EMAIL_HOST = #email host
EMAIL_HOST_PASSWORD = #email host password
EMAIL_USE_TLS = # if your email use tls
EMAIL_PORT = #email port

change all the environment variables in the .env.sample and don't forget to rename it to .env.

Run the project

After Setup the environment, you can run the project using the Makefile provided in the project folder.

help:
 @echo "Targets:"
 @echo "    make install" #install requirements
 @echo "    make makemigrations" #prepare migrations
 @echo "    make migrations" #migrate database
 @echo "    make createsuperuser" #create superuser
 @echo "    make run_server" #run the server
 @echo "    make lint" #lint the code using black
 @echo "    make test" #run the tests using Pytest

Preconfigured Packages

Includes preconfigured packages to kick start Django-Authentication by just setting appropriate configuration.

Package	Usage
django-allauth	Integrated set of Django applications addressing authentication, registration, account management as well as 3rd party (social) account authentication.
django-crispy-forms	django-crispy-forms provides you with a crispy filter and {% crispy %} tag that will let you control the rendering behavior of your Django forms in a very elegant and DRY way.

Contributing

• Django-Authentication is a simple project, so you can contribute to it by just adding your code to the project to improve it.
• If you have any questions, please feel free to open an issue or create a pull request.

Download Details:
Author: yezz123
Source Code: https://github.com/yezz123/Django-Authentication
License: MIT License

#django #python 

Serverless APIGateway Service Proxy

Serverless APIGateway Service Proxy

This Serverless Framework plugin supports the AWS service proxy integration feature of API Gateway. You can directly connect API Gateway to AWS services without Lambda.

Install

Run serverless plugin install in your Serverless project.

serverless plugin install -n serverless-apigateway-service-proxy

Supported AWS services

Here is a services list which this plugin supports for now. But will expand to other services in the feature. Please pull request if you are intersted in it.

• Kinesis Streams
• SQS
• S3
• SNS
• DynamoDB
• EventBridge

How to use

Define settings of the AWS services you want to integrate under custom > apiGatewayServiceProxies and run serverless deploy.

Kinesis

Sample syntax for Kinesis proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - kinesis: # partitionkey is set apigateway requestid by default
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis:
        path: /kinesis
        method: post
        partitionKey: 'hardcordedkey' # use static partitionkey
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis:
        path: /kinesis/{myKey} # use path parameter
        method: post
        partitionKey:
          pathParam: myKey
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis:
        path: /kinesis
        method: post
        partitionKey:
          bodyParam: data.myKey # use body parameter
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis:
        path: /kinesis
        method: post
        partitionKey:
          queryStringParam: myKey # use query string param
        streamName: { Ref: 'YourStream' }
        cors: true
    - kinesis: # PutRecords
        path: /kinesis
        method: post
        action: PutRecords
        streamName: { Ref: 'YourStream' }
        cors: true

resources:
  Resources:
    YourStream:
      Type: AWS::Kinesis::Stream
      Properties:
        ShardCount: 1

Sample request after deploying.

curl https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/kinesis -d '{"message": "some data"}'  -H 'Content-Type:application/json'

SQS

Sample syntax for SQS proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
        cors: true

resources:
  Resources:
    SQSQueue:
      Type: 'AWS::SQS::Queue'

Sample request after deploying.

curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/sqs -d '{"message": "testtest"}' -H 'Content-Type:application/json'

Customizing request parameters

If you'd like to pass additional data to the integration request, you can do so by including your custom API Gateway request parameters in serverless.yml like so:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /queue
        method: post
        queueName: !GetAtt MyQueue.QueueName
        cors: true

        requestParameters:
          'integration.request.querystring.MessageAttribute.1.Name': "'cognitoIdentityId'"
          'integration.request.querystring.MessageAttribute.1.Value.StringValue': 'context.identity.cognitoIdentityId'
          'integration.request.querystring.MessageAttribute.1.Value.DataType': "'String'"
          'integration.request.querystring.MessageAttribute.2.Name': "'cognitoAuthenticationProvider'"
          'integration.request.querystring.MessageAttribute.2.Value.StringValue': 'context.identity.cognitoAuthenticationProvider'
          'integration.request.querystring.MessageAttribute.2.Value.DataType': "'String'"

The alternative way to pass MessageAttribute parameters is via a request body mapping template.

Customizing request body mapping templates

See the SQS section under Customizing request body mapping templates

Customizing responses

Simplified response template customization

You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json.

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /queue
        method: post
        queueName: !GetAtt MyQueue.QueueName
        cors: true
        response:
          template:
            # `success` is used when the integration response is 200
            success: |-
              { "message: "accepted" }
            # `clientError` is used when the integration response is 400
            clientError: |-
              { "message": "there is an error in your request" }
            # `serverError` is used when the integration response is 500
            serverError: |-
              { "message": "there was an error handling your request" }

Full response customization

If you want more control over the integration response, you can provide an array of objects for the response value:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /queue
        method: post
        queueName: !GetAtt MyQueue.QueueName
        cors: true
        response:
          - statusCode: 200
            selectionPattern: '2\\d{2}'
            responseParameters: {}
            responseTemplates:
              application/json: |-
                { "message": "accepted" }

The object keys correspond to the API Gateway integration response object.

S3

Sample syntax for S3 proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3
        method: post
        action: PutObject
        bucket:
          Ref: S3Bucket
        key: static-key.json # use static key
        cors: true

    - s3:
        path: /s3/{myKey} # use path param
        method: get
        action: GetObject
        bucket:
          Ref: S3Bucket
        key:
          pathParam: myKey
        cors: true

    - s3:
        path: /s3
        method: delete
        action: DeleteObject
        bucket:
          Ref: S3Bucket
        key:
          queryStringParam: key # use query string param
        cors: true

resources:
  Resources:
    S3Bucket:
      Type: 'AWS::S3::Bucket'

Sample request after deploying.

curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/s3 -d '{"message": "testtest"}' -H 'Content-Type:application/json'

Customizing request parameters

Similar to the SQS support, you can customize the default request parameters serverless.yml like so:

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3
        method: post
        action: PutObject
        bucket:
          Ref: S3Bucket
        cors: true

        requestParameters:
          # if requestParameters has a 'integration.request.path.object' property you should remove the key setting
          'integration.request.path.object': 'context.requestId'
          'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"

Customizing request templates

If you'd like use custom API Gateway request templates, you can do so like so:

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3
        method: get
        action: GetObject
        bucket:
          Ref: S3Bucket
        request:
          template:
            application/json: |
              #set ($specialStuff = $context.request.header.x-special)
              #set ($context.requestOverride.path.object = $specialStuff.replaceAll('_', '-'))
              {}

Note that if the client does not provide a Content-Type header in the request, ApiGateway defaults to application/json.

Customize the Path Override in API Gateway

Added the new customization parameter that lets the user set a custom Path Override in API Gateway other than the {bucket}/{object} This parameter is optional and if not set, will fall back to {bucket}/{object} The Path Override will add {bucket}/ automatically in front

Please keep in mind, that key or path.object still needs to be set at the moment (maybe this will be made optional later on with this)

Usage (With 2 Path Parameters (folder and file and a fixed file extension)):

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3/{folder}/{file}
        method: get
        action: GetObject
        pathOverride: '{folder}/{file}.xml'
        bucket:
          Ref: S3Bucket
        cors: true

        requestParameters:
          # if requestParameters has a 'integration.request.path.object' property you should remove the key setting
          'integration.request.path.folder': 'method.request.path.folder'
          'integration.request.path.file': 'method.request.path.file'
          'integration.request.path.object': 'context.requestId'
          'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"

This will result in API Gateway setting the Path Override attribute to {bucket}/{folder}/{file}.xml So for example if you navigate to the API Gatway endpoint /language/en it will fetch the file in S3 from {bucket}/language/en.xml

Can use greedy, for deeper Folders

The forementioned example can also be shortened by a greedy approach. Thanks to @taylorreece for mentioning this.

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3/{myPath+}
        method: get
        action: GetObject
        pathOverride: '{myPath}.xml'
        bucket:
          Ref: S3Bucket
        cors: true

        requestParameters:
          # if requestParameters has a 'integration.request.path.object' property you should remove the key setting
          'integration.request.path.myPath': 'method.request.path.myPath'
          'integration.request.path.object': 'context.requestId'
          'integration.request.header.cache-control': "'public, max-age=31536000, immutable'"

This will translate for example /s3/a/b/c to a/b/c.xml

Customizing responses

You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json.

custom:
  apiGatewayServiceProxies:
    - s3:
        path: /s3
        method: post
        action: PutObject
        bucket:
          Ref: S3Bucket
        key: static-key.json
        response:
          template:
            # `success` is used when the integration response is 200
            success: |-
              { "message: "accepted" }
            # `clientError` is used when the integration response is 400
            clientError: |-
              { "message": "there is an error in your request" }
            # `serverError` is used when the integration response is 500
            serverError: |-
              { "message": "there was an error handling your request" }

SNS

Sample syntax for SNS proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - sns:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        cors: true

resources:
  Resources:
    SNSTopic:
      Type: AWS::SNS::Topic

Sample request after deploying.

curl https://xxxxxx.execute-api.us-east-1.amazonaws.com/dev/sns -d '{"message": "testtest"}' -H 'Content-Type:application/json'

Customizing responses

Simplified response template customization

You can get a simple customization of the responses by providing a template for the possible responses. The template is assumed to be application/json.

custom:
  apiGatewayServiceProxies:
    - sns:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        cors: true
        response:
          template:
            # `success` is used when the integration response is 200
            success: |-
              { "message: "accepted" }
            # `clientError` is used when the integration response is 400
            clientError: |-
              { "message": "there is an error in your request" }
            # `serverError` is used when the integration response is 500
            serverError: |-
              { "message": "there was an error handling your request" }

Full response customization

If you want more control over the integration response, you can provide an array of objects for the response value:

custom:
  apiGatewayServiceProxies:
    - sns:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        cors: true
        response:
          - statusCode: 200
            selectionPattern: '2\d{2}'
            responseParameters: {}
            responseTemplates:
              application/json: |-
                { "message": "accepted" }

The object keys correspond to the API Gateway integration response object.

Content Handling and Pass Through Behaviour customization

If you want to work with binary fata, you can not specify contentHandling and PassThrough inside the request object.

custom:
  apiGatewayServiceProxies:
    - sns:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        request:
          contentHandling: CONVERT_TO_TEXT
          passThrough: WHEN_NO_TEMPLATES

The allowed values correspond with the API Gateway Method integration for ContentHandling and PassthroughBehavior

DynamoDB

Sample syntax for DynamoDB proxy in serverless.yml. Currently, the supported DynamoDB Operations are PutItem, GetItem and DeleteItem.

custom:
  apiGatewayServiceProxies:
    - dynamodb:
        path: /dynamodb/{id}/{sort}
        method: put
        tableName: { Ref: 'YourTable' }
        hashKey: # set pathParam or queryStringParam as a partitionkey.
          pathParam: id
          attributeType: S
        rangeKey: # required if also using sort key. set pathParam or queryStringParam.
          pathParam: sort
          attributeType: S
        action: PutItem # specify action to the table what you want
        condition: attribute_not_exists(Id) # optional Condition Expressions parameter for the table
        cors: true
    - dynamodb:
        path: /dynamodb
        method: get
        tableName: { Ref: 'YourTable' }
        hashKey:
          queryStringParam: id # use query string parameter
          attributeType: S
        rangeKey:
          queryStringParam: sort
          attributeType: S
        action: GetItem
        cors: true
    - dynamodb:
        path: /dynamodb/{id}
        method: delete
        tableName: { Ref: 'YourTable' }
        hashKey:
          pathParam: id
          attributeType: S
        action: DeleteItem
        cors: true

resources:
  Resources:
    YourTable:
      Type: AWS::DynamoDB::Table
      Properties:
        TableName: YourTable
        AttributeDefinitions:
          - AttributeName: id
            AttributeType: S
          - AttributeName: sort
            AttributeType: S
        KeySchema:
          - AttributeName: id
            KeyType: HASH
          - AttributeName: sort
            KeyType: RANGE
        ProvisionedThroughput:
          ReadCapacityUnits: 1
          WriteCapacityUnits: 1

Sample request after deploying.

curl -XPUT https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/dynamodb/<hashKey>/<sortkey> \
 -d '{"name":{"S":"john"},"address":{"S":"xxxxx"}}' \
 -H 'Content-Type:application/json'

EventBridge

Sample syntax for EventBridge proxy in serverless.yml.

custom:
  apiGatewayServiceProxies:
    - eventbridge:  # source and detailType are hardcoded; detail defaults to POST body
        path: /eventbridge
        method: post
        source: 'hardcoded_source'
        detailType: 'hardcoded_detailType'
        eventBusName: { Ref: 'YourBusName' }
        cors: true
    - eventbridge:  # source and detailType as path parameters
        path: /eventbridge/{detailTypeKey}/{sourceKey}
        method: post
        detailType:
          pathParam: detailTypeKey
        source:
          pathParam: sourceKey
        eventBusName: { Ref: 'YourBusName' }
        cors: true
    - eventbridge:  # source, detail, and detailType as body parameters
        path: /eventbridge/{detailTypeKey}/{sourceKey}
        method: post
        detailType:
          bodyParam: data.detailType
        source:
          bodyParam: data.source
        detail:
          bodyParam: data.detail
        eventBusName: { Ref: 'YourBusName' }
        cors: true

resources:
  Resources:
    YourBus:
      Type: AWS::Events::EventBus
      Properties:
        Name: YourEventBus

Sample request after deploying.

curl https://xxxxxxx.execute-api.us-east-1.amazonaws.com/dev/eventbridge -d '{"message": "some data"}'  -H 'Content-Type:application/json'

Common API Gateway features

Enabling CORS

To set CORS configurations for your HTTP endpoints, simply modify your event configurations as follows:

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors: true

Setting cors to true assumes a default configuration which is equivalent to:

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors:
          origin: '*'
          headers:
            - Content-Type
            - X-Amz-Date
            - Authorization
            - X-Api-Key
            - X-Amz-Security-Token
            - X-Amz-User-Agent
          allowCredentials: false

Configuring the cors property sets Access-Control-Allow-Origin, Access-Control-Allow-Headers, Access-Control-Allow-Methods,Access-Control-Allow-Credentials headers in the CORS preflight response. To enable the Access-Control-Max-Age preflight response header, set the maxAge property in the cors object:

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors:
          origin: '*'
          maxAge: 86400

If you are using CloudFront or another CDN for your API Gateway, you may want to setup a Cache-Control header to allow for OPTIONS request to be cached to avoid the additional hop.

To enable the Cache-Control header on preflight response, set the cacheControl property in the cors object:

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'YourStream' }
        cors:
          origin: '*'
          headers:
            - Content-Type
            - X-Amz-Date
            - Authorization
            - X-Api-Key
            - X-Amz-Security-Token
            - X-Amz-User-Agent
          allowCredentials: false
          cacheControl: 'max-age=600, s-maxage=600, proxy-revalidate' # Caches on browser and proxy for 10 minutes and doesnt allow proxy to serve out of date content

Adding Authorization

You can pass in any supported authorization type:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
        cors: true

        # optional - defaults to 'NONE'
        authorizationType: 'AWS_IAM' # can be one of ['NONE', 'AWS_IAM', 'CUSTOM', 'COGNITO_USER_POOLS']

        # when using 'CUSTOM' authorization type, one should specify authorizerId
        # authorizerId: { Ref: 'AuthorizerLogicalId' }
        # when using 'COGNITO_USER_POOLS' authorization type, one can specify a list of authorization scopes
        # authorizationScopes: ['scope1','scope2']

resources:
  Resources:
    SQSQueue:
      Type: 'AWS::SQS::Queue'

Source: AWS::ApiGateway::Method docs

Enabling API Token Authentication

You can indicate whether the method requires clients to submit a valid API key using private flag:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
        cors: true
        private: true

resources:
  Resources:
    SQSQueue:
      Type: 'AWS::SQS::Queue'

which is the same syntax used in Serverless framework.

Source: Serverless: Setting API keys for your Rest API

Source: AWS::ApiGateway::Method docs

Using a Custom IAM Role

By default, the plugin will generate a role with the required permissions for each service type that is configured.

You can configure your own role by setting the roleArn attribute:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SQSQueue', 'QueueName'] }
        cors: true
        roleArn: # Optional. A default role is created when not configured
          Fn::GetAtt: [CustomS3Role, Arn]

resources:
  Resources:
    SQSQueue:
      Type: 'AWS::SQS::Queue'
    CustomS3Role:
      # Custom Role definition
      Type: 'AWS::IAM::Role'

Customizing API Gateway parameters

The plugin allows one to specify which parameters the API Gateway method accepts.

A common use case is to pass custom data to the integration request:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /sqs
        method: post
        queueName: { 'Fn::GetAtt': ['SqsQueue', 'QueueName'] }
        cors: true
        acceptParameters:
          'method.request.header.Custom-Header': true
        requestParameters:
          'integration.request.querystring.MessageAttribute.1.Name': "'custom-Header'"
          'integration.request.querystring.MessageAttribute.1.Value.StringValue': 'method.request.header.Custom-Header'
          'integration.request.querystring.MessageAttribute.1.Value.DataType': "'String'"
resources:
  Resources:
    SqsQueue:
      Type: 'AWS::SQS::Queue'

Any published SQS message will have the Custom-Header value added as a message attribute.

Customizing request body mapping templates

Kinesis

If you'd like to add content types or customize the default templates, you can do so by including your custom API Gateway request mapping template in serverless.yml like so:

# Required for using Fn::Sub
plugins:
  - serverless-cloudformation-sub-variables

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'MyStream' }
        request:
          template:
            text/plain:
              Fn::Sub:
                - |
                  #set($msgBody = $util.parseJson($input.body))
                  #set($msgId = $msgBody.MessageId)
                  {
                      "Data": "$util.base64Encode($input.body)",
                      "PartitionKey": "$msgId",
                      "StreamName": "#{MyStreamArn}"
                  }
                - MyStreamArn:
                    Fn::GetAtt: [MyStream, Arn]

It is important that the mapping template will return a valid application/json string

Source: How to connect SNS to Kinesis for cross-account delivery via API Gateway

SQS

Customizing SQS request templates requires us to force all requests to use an application/x-www-form-urlencoded style body. The plugin sets the Content-Type header to application/x-www-form-urlencoded for you, but API Gateway will still look for the template under the application/json request template type, so that is where you need to configure you request body in serverless.yml:

custom:
  apiGatewayServiceProxies:
    - sqs:
        path: /{version}/event/receiver
        method: post
        queueName: { 'Fn::GetAtt': ['SqsQueue', 'QueueName'] }
        request:
          template:
            application/json: |-
              #set ($body = $util.parseJson($input.body))
              Action=SendMessage##
              &MessageGroupId=$util.urlEncode($body.event_type)##
              &MessageDeduplicationId=$util.urlEncode($body.event_id)##
              &MessageAttribute.1.Name=$util.urlEncode("X-Custom-Signature")##
              &MessageAttribute.1.Value.DataType=String##
              &MessageAttribute.1.Value.StringValue=$util.urlEncode($input.params("X-Custom-Signature"))##
              &MessageBody=$util.urlEncode($input.body)

Note that the ## at the end of each line is an empty comment. In VTL this has the effect of stripping the newline from the end of the line (as it is commented out), which makes API Gateway read all the lines in the template as one line.

Be careful when mixing additional requestParameters into your SQS endpoint as you may overwrite the integration.request.header.Content-Type and stop the request template from being parsed correctly. You may also unintentionally create conflicts between parameters passed using requestParameters and those in your request template. Typically you should only use the request template if you need to manipulate the incoming request body in some way.

Your custom template must also set the Action and MessageBody parameters, as these will not be added for you by the plugin.

When using a custom request body, headers sent by a client will no longer be passed through to the SQS queue (PassthroughBehavior is automatically set to NEVER). You will need to pass through headers sent by the client explicitly in the request body. Also, any custom querystring parameters in the requestParameters array will be ignored. These also need to be added via the custom request body.

SNS

Similar to the Kinesis support, you can customize the default request mapping templates in serverless.yml like so:

# Required for using Fn::Sub
plugins:
  - serverless-cloudformation-sub-variables

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /sns
        method: post
        topicName: { 'Fn::GetAtt': ['SNSTopic', 'TopicName'] }
        request:
          template:
            application/json:
              Fn::Sub:
                - "Action=Publish&Message=$util.urlEncode('This is a fixed message')&TopicArn=$util.urlEncode('#{MyTopicArn}')"
                - MyTopicArn: { Ref: MyTopic }

It is important that the mapping template will return a valid application/x-www-form-urlencoded string

Source: Connect AWS API Gateway directly to SNS using a service integration

Custom response body mapping templates

You can customize the response body by providing mapping templates for success, server errors (5xx) and client errors (4xx).

Templates must be in JSON format. If a template isn't provided, the integration response will be returned as-is to the client.

Kinesis Example

custom:
  apiGatewayServiceProxies:
    - kinesis:
        path: /kinesis
        method: post
        streamName: { Ref: 'MyStream' }
        response:
          template:
            success: |
              {
                "success": true
              }
            serverError: |
              {
                "success": false,
                "errorMessage": "Server Error"
              }
            clientError: |
              {
                "success": false,
                "errorMessage": "Client Error"
              }

Author: Serverless-operations
Source Code: https://github.com/serverless-operations/serverless-apigateway-service-proxy 
License: 

#serverless #api #aws