Saravanan666/pypi-org huggingface dataset:
Package: awsip
awsipA simple python library to check if an ip, a list of ips or a list of ip ranges
exist inside Amazon (AWS) infrastructure.pip install awsipAfter installation, you can make use ofawsiputility to check for ips.awsip 1.1.1.1 2.2.2.2 5.4.3.0/28You can provide a white-spaced list of ip addresses / ranges. You can also provide a filename containing ip address / range on each line. For example, you have a filemyips.txtwith following format.192.0.0.1
7.7.7.0/28
9.9.9.0/30You can pass the ips to utility while providing extra ips on the go like this:awsip myips.txt 1.1.1.1 2.2.2.0/24You can also make use of it in your custom code like this:from awsip import AWSIPChecker
checker = AWSIPChecker()
checker.get_aws_range(['18.208.0.0', '18.208.0.0/16'])You can provide a list of ip address, ip ranges or a mixture of both and program will check if they belong to AWS and return appropriate data if they do belong.
Package: awsipranges
awsiprangesWork with the AWS IP address ranges in native Python.Amazon Web Services (AWS) publishes itscurrent IP address rangesinJSONformat. Python v3 provides anipaddressmodule in the standard library that allows you to create, manipulate, and perform operations on IPv4 and IPv6 addresses and networks. Wouldn't it be nice if you could work with the AWS IP address ranges like native Python objects?FeaturesWork with the AWS IP prefixes as a simpleAWSIPPrefixescollection.Quickly check if an IP address, interface, or network is contained in the AWS IP address ranges.Get the AWS IP prefix that contains an IP address, interface, or network.See what services are served from an IP prefix.Filter the AWS IP prefixes byregion,network border group,service, and IP prefixversion.Use the AWS prefix data in your app or automation scripts in the format required by your infrastructure.Easily validate the TLS certificate presented by the IP ranges server.awsipranges hasno third-party dependenciesand is compatible with CPython v3.7+.>>>importawsipranges>>>aws_ip_ranges=awsipranges.get_ranges(cafile="amazon_root_certificates.pem")>>>'52.94.5.15'inaws_ip_rangesTrue>>>aws_ip_ranges['52.94.5.15']AWSIPv4Prefix('52.94.5.0/24',region='eu-west-1',network_border_group='eu-west-1',services=('AMAZON','DYNAMODB'))>>>aws_ip_ranges.filter(services='CODEBUILD'){'create_date':datetime.datetime(2021,8,24,1,31,14,tzinfo=datetime.timezone.utc),'ipv4_prefixes':(AWSIPv4Prefix('3.26.127.24/29',region='ap-southeast-2',network_border_group='ap-southeast-2',services=('CODEBUILD',)),AWSIPv4Prefix('3.38.90.8/29',region='ap-northeast-2',network_border_group='ap-northeast-2',services=('CODEBUILD',)),AWSIPv4Prefix('3.68.251.232/29',region='eu-central-1',network_border_group='eu-central-1',services=('CODEBUILD',)),AWSIPv4Prefix('3.98.171.224/29',region='ca-central-1',network_border_group='ca-central-1',services=('CODEBUILD',)),AWSIPv4Prefix('3.101.177.48/29',region='us-west-1',network_border_group='us-west-1',services=('CODEBUILD',)),...),'ipv6_prefixes':(),'sync_token':'1629768674'}>>>forprefixinaws_ip_ranges.filter(regions='eu-west-1',services='DYNAMODB'):...print(prefix.network_address,prefix.netmask)...52.94.5.0255.255.255.052.94.24.0255.255.254.052.94.26.0255.255.254.052.119.240.0255.255.248.0InstallationInstalling and upgradingawsiprangesis easy:Install via PIP❯pipinstallawsiprangesUpgrade to the latest version❯pipinstall--upgradeawsiprangesDocumentationExcellent documentation is now available at:https://aws-samples.github.io/awsipranges/Check out theQuickstartto dive in and begin using awsipranges.ContributeSeeCONTRIBUTINGfor information on how to contribute to this project.SecuritySeeCONTRIBUTINGfor information on how to report a security issue with this project.LicenseThis project is licensed under theApache-2.0 License.
Package: aws-is-instance-healthy
Simple tool to ensure that an AWS instance is healthy (ELB-Based)Usage:From inside an target EC2 instance::$ am_i_healthy.pyInstance i-0d26836d9ab61a235 is healthyCallam_i_healthy.pyto check for its own health.From outside an target EC2 instance::$ is_instance_healthy.py sa-east-1 i-0d26836d9ab61a235Instance i-0d26836d9ab61a235 is healthyCallis_instance_healthy.py [region_name] [instance_id]to check for
its health.From within your own python script::from vivareal.cli.is_instance_healthy import is_instance_healthystatus = is_instance_healthy(‘sa-east-1’, ‘i-0d26836d9ab61a235’)print(status)>>> (True, 'N/A', 'N/A')When calling from within your own python script, the tuple structure is:
- Healthy (boolean)
- ReasonCode (string)
- Description (string)
Package: aws-jsiisamples.jsii-native-python
jsii-native-pythonA simple Python library to benchmark against a jsii module with similar, simple logic.LicenseThis library is licensed under the MIT-0 License. See the LICENSE file.Change log0.0.1 - initial version (2020-05-15)
1.5.0 - implemented recursive fibonacci (2020-05-17)
1.6.0 - updated fibonacci to use the same algorithm as jsii (2020-05-27)
Package: aws-json-dataset
aws-json-datasetLightweight and simple Python package to quickly send batches of JSON data to various AWS services.DescriptionThe idea behind this library is to create an easy, quick way to send JSON data to AWS services.SQSSNSKinesis FirehoseKinesis Data Streams (coming soon)JSON is an extremely common format and each AWS service has it's own API with different requirements for how to send data.This library includes functionality for:Automatically handling batch API calls to SNS, SQS and Kinesis FirehoseManages available services based on record sizeBase64 conversion for Kinesis streamsRoadmapSupport for Kinesis Data StreamsSupport for DynamoDB inserts, updates and deletesSupport for S3, including gzip compression and JSON lines formatSupport for FIFO SQS queuesSupport for SNS topicsQuickstartSet up yourAWS credentialsand environment variables and export them to the environment.exportAWS_PROFILE=<profile>exportAWS_REGION=<region>Install the library using pip.pipinstall-ihttps://test.pypi.org/simple/aws-json-datasetSend JSON data to various AWS services.fromawsjsondatasetimportAwsJsonDataset# create a list of JSON objectsdata=[{"id":idx,"data":"<data>"}foridxinrange(100)]# Wrap using AwsJsonDatasetdataset=AwsJsonDataset(data=data)# Send to SQS queuedataset.sqs("<sqs_queue_url>").send_messages()# Send to SNS topicdataset.sns("<sns_topic_arn>").publish_messages()# Send to Kinesis Firehose streamdataset.firehose("<delivery_stream_name>").put_records()Local DevelopmentFollow the steps to set up the deployment environment.PrerequisitesAWS credentialsPython 3.10Creating a Python Virtual EnvironmentWhen developing locally, create a Python virtual environment to manage dependencies:python3.10-mvenv.venvsource.venv/bin/activate
pipinstall-Upip
pipinstall.[dev,test]Environment VariablesCreate a.envfile in the project root.AWS_REGION=<region>Important:Always use a.envfile or AWS SSM Parameter Store or Secrets Manager for sensitive variables like credentials and API keys. Never hard-code them, including when developing. AWS will quarantine an account if any credentials get accidentally exposed and this will cause problems.→Make sure that.envis listed in.gitignoreAWS CredentialsValid AWS credentials must be available to AWS CLI and SAM CLI. The easiest way to do this is runningaws configure, or by adding them to~/.aws/credentialsand exporting theAWS_PROFILEvariable to the environment.For more information visit the documentation page:Configuration and credential file settingsUnit TestsFollow the steps above to create a Python virtual environment. Run tests with the following command.coveragerun-mpytestTroubleshootingCheck your AWS credentials in~/.aws/credentialsCheck that the environment variables are available to the services that need themCheck that the correct environment or interpreter is being used for PythonAuthorsPrimary Contact:Gregory Christopher Lindsey (@chrisammon3000)LicenseThis library is licensed under the MIT-0 License. See the LICENSE file.
Package: aws-jupyter-proxy
AWS Jupyter ProxyA Jupyter server extension to proxy requests with AWS SigV4 authentication.OverviewThis server extension enables the usage of theAWS JavaScript/TypeScript SDKto write Jupyter frontend extensions without having to export AWS credentials to the browser.A single/awsproxyendpoint is added on the Jupyter server which receives incoming requests from the browser, uses the credentials on the server to addSigV4authentication to the request, and then proxies the request to the actual AWS service endpoint.All requests are proxied back-and-forth as-is, e.g., a 4xx status code from the AWS service will be relayed back as-is to the browser.NOTE: This project is still under active developmentInstallInstalling the package from PyPI will install and enable the server extension on the Jupyter server.pipinstallaws-jupyter-proxyUsageUsing this requries no additional dependencies in the client-side code. Just use the regular AWS JavaScript/TypeScript SDK methods and add any dummy credentials and change the endpoint to the/awsproxyendpoint.import*asAWSfrom'aws-sdk';importSageMakerfrom'aws-sdk/clients/sagemaker';// Reusable function to add the XSRF token header to a requestfunctionaddXsrfToken<D,E>(request:AWS.Request<D,E>){constcookie=document.cookie.match('\\b'+'_xsrf'+'=([^;]*)\\b');constxsrfToken=cookie?cookie[1]:undefined;if(xsrfToken!==undefined){request.httpRequest.headers['X-XSRFToken']=xsrfToken;}}// These credentials are *not* used for the actual AWS service call but you have// to provide any dummy credentials (Not real ones!)AWS.config.secretAccessKey='IGNOREDIGNORE/IGNOREDIGNOREDIGNOREDIGNOR';AWS.config.accessKeyId='IGNOREDIGNO';// Change the endpoint in the client to the "awsproxy" endpoint on the Jupyter server.constproxyEndpoint='http://localhost:8888/awsproxy';constsageMakerClient=newSageMaker({region:'us-west-2',endpoint:proxyEndpoint,});// Make the API call!awaitsageMakerClient.listNotebookInstances({NameContains:'jaipreet'}).on('build',addXsrfToken).promise();Usage with S3For S3, use thes3ForcePathStyleparameter during the client initializationimportS3from'aws-sdk/clients/s3';consts3Client=newS3({region:'us-west-2',endpoint:proxyEndpoint,s3ForcePathStyle:true,s3DisableBodySigning:false// for https});awaits3Client.getObject({Bucket:'my-bucket',Key:'my-object'}).on('build',addXsrfToken).promise();WhitelistingOn the server, theAWS_JUPYTER_PROXY_WHITELISTED_SERVICESenvironment variable can be used to whitelist the set of services allowed to be proxied through. This is opt-in - Not specifying this
environment variable will whitelist all services.exportAWS_JUPYTER_PROXY_WHITELISTED_SERVICES=sagemaker,s3
jupyter-labDevelopmentInstall all dev dependenciespipinstall-e".[dev]"jupyterserverextensionenable--pyaws_jupyter_proxy--sys-prefixRun unit tests using pytestpytesttests/unitLicenseThis library is licensed under the Apache 2.0 License.
Package: aws-ket
aws-ketUtility tool to encrypt data using AWS KMS and store it in preferred backend.OverviewAWS-KET (AWS KMS Encryption Tool) uses AWS KMS Key to encrypt and decrypt files/contents based on user provided kms keys and push them to a datastore backend (S3, RDS or DynamoDB).SetupThis application will only work if you have AWS account with full privileges on KMS and S3 services in AWS. You should also have aws cli tool installed.Setup AWS CLINote:Currently this tool only uses AWS regionus-east-2for usage of kms and s3.Using Source CodeInitaliztion of appgit clone git@github.com:sayefiqb/aws-ket.git
cd awsket
python init.pyEncrypt text/filepython app.py --text <TEXT_TO_ENCRYPT> --save <FILE_NAME_IN_S3> 
python app.py --file <PATH_OF_FILE_TO_ENCRYPT> --save <FILE_NAME_IN_S3>Decrypt text/file from S3This will save with same name as remotepython app.py --decrypt <FILE_NAME_IN_S3>ORTo specify name for saved filepython app.py --decrypt <FILE_NAME_IN_S3>  --save <FILE_NAME_TO_SAVE_AS_IN_LOCAL>CleanupTo cleanup your S3 bucket and start overpython cleanup.pyUsing Library form Pypipip install aws-ketInitaliztion of appfrom awsket import ket

AWS_REGION = 'us-east-2'
KMS_ALIAS = 'alias/aws-ket'

user_name = ket.get_iam_user()['UserId'].lower()
bucket_name = f'aws-ket-{user_name}'
ket.create_s3_bucket(bucket_name, AWS_REGION)
alias_name = ket.check_alias(KMS_ALIAS, AWS_REGION)
kms_key_id = ket.create_kms_key(AWS_REGION)
alias_name = ket.create_kms_alias(kms_key_id, KMS_ALIAS, AWS_REGION)Encrypt textfrom awsket import ket

AWS_REGION = 'us-east-2'
KMS_ALIAS = 'alias/aws-ket'
TEXT = 'This is a sample text for testing encryption! Happy coding :)'
FILE = 'EXAMPLE.txt'


user_name = ket.get_iam_user()['UserId'].lower()
bucket_name = f'aws-ket-{user_name}'
encrypted_string = ket.encrypt_text(KMS_ALIAS, TEXT, AWS_REGION)
ket.push_to_s3(bucket_name, FILE, encrypted_string, AWS_REGION)Decrypt textfrom awsket import ket

AWS_REGION = 'us-east-2'
KMS_ALIAS = 'alias/aws-ket'
FILE = 'EXAMPLE.txt'

user_name = ket.get_iam_user()['UserId'].lower()
bucket_name = f'aws-ket-{user_name}'
decrypted_text = ket.decrypt_text(bucket_name, FILE, KMS_ALIAS, AWS_REGION)
print(decrypted_text)DetailsThis project usesMakefileas a command registry, with the following commands:make: list available commandsmake develop: install and build this library and its dependencies usingpipmake lint: perform lint usingblackmake scan: run static analysis on code usingflake8make test: run automated tests withpytestmake coverage: run automated tests withpytestand collect coverage informationcoverageoutput can also be found in html format inhtmlcoverdirectory.ExampleFirst download the source code
Package: aws-key-formatter
aws-key-formatterProject/Repo:Code Quality/CI:OverviewThis CLI will take your AWS credentials and output them in various formats.The initial use case is for displaying your AWS credentials for use as theAuthorizationparameter in several AWS Redshift commands.SeeUse Casesfor all possible output formats.Installationaws-key-formattercan be installed by running:pipinstallaws-key-formatterIt requires Python 3.6+ to run.You can, also, install viapipx:pipxinstallaws-key-formatterUsageRedshiftTo use your AWS credentials as theAuthorizationparameter in a Redshift
command (Seethe Redshift docs):$aws-key-formatterredshift
ACCESS_KEY_ID'<access-key-id>'SECRET_ACCESS_KEY'<secret-access-key>'# If you want the session token included as well$aws-key-formatterredshift--token
ACCESS_KEY_ID'<access-key-id>'SECRET_ACCESS_KEY'<secret-access-key>'SESSION_TOKEN'<temporary-token>'Environment VariablesTo use your AWS credentials asenvironment variables:$aws-key-formatterenvAWS_ACCESS_KEY_ID=<access-key-id>AWS_SECRET_ACCESS_KEY=<secret-access-key># If you want the session token included as well$aws-key-formatterenv--tokenACCESS_KEY_ID=<access-key-id>SECRET_ACCESS_KEY=<secret-access-key>SESSION_TOKEN=<temporary-token>ContributingChangelog0.1.0 (2019-08-09)Made it to bepip-installableAdded some initial installation/usage docs to READMESetup to be built & deployed to pypi via Travis CILicenseCopyright 2019 Kelton KarboviakPermission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
Package: awskeyspaces
PYTHON AWS KEYSPACES CONNECTORAWS KEYSPACES Connector PackagesourceTech CoreWhat do i need to know before using this code?Python 3.8Cassandracassandra-driverAWS KeyspacesTLS always on 9142Port    Authentication Mechanism
9142    TLS client authentication, with certificatesrequired aws certcurl https://www.amazontrust.com/repository/AmazonRootCA1.pem -OCassandra Driver PerformanceLinux Likesudo apt install libev-dev
sudo yum install libev-devel
apk add libev-devMacOSbrew install libevCompiled is better :)Env VarsLoad env vars for your cluster connectionREGION=us-east-1
CLUSTER_KSP=my_keyspace
CLUSTER_HOST="cassandra.${REGION}.amazonaws.com"
CLUSTER_PORT=9142
CLUSTER_USER="****************"
CLUSTER_PASS="****************"

export CLUSTER_KSP CLUSTER_HOST CLUSTER_USER CLUSTER_PASS CLUSTER_REGIONHow to installLoad virtual envpython3.8 -m venv venv
. venv/bin/activateInstall packagepip install -r requirements.txt
# or
make init
# or
python setup.py installWhy Not?pip install -e git+https://bitbucket.org/labunix/awskeyspaces.git@master#egg=keyspacesConnected?from awskeyspaces.connection import connect

@connect
def dbsetup():
    passContributionquierati@labunix.devtwine upload packagepython3 -m pip install --upgrade build
python3 -m build

python3 -m pip install --user --upgrade twine
python3 -m twine upload dist/*
Package: aws-kms-crypt
Utility for encrypting and decrypting secrets with the AWS KMS service.InstallationInstall from PyPI with pippipinstallaws-kms-cryptUsageRequires Python 3.8 or newer.importkmscrypt# Encrypting Data>>>result=kmscrypt.encrypt('secretp4ssw0rd!',key_id='alias/common',encryption_context={...'purpose':'automation'...})>>>result{"EncryptedDataKey":"AQIDAHhyrbU/fPcQ+a8pJiYC<snip>","Iv":"689806fe9d571afeffa4c7c24247c766","EncryptedData":"YRjZDQ2KzcEAZqUy7SpWWA==","EncryptionContext":{"purpose":"automation"}}# Decrypting data>>>kmscrypt.decrypt(result)b'secretp4ssw0rd!'Changelogv3.0.0 (2024-01-31)Dropped Python 3.7 support.v2.0.0 (2022-09-15)Dropped Python 3.6 support.v1.0.0 (2021-09-25)Dropped Python 2.7 support.Replacedpycryptowithcryptography.LicenseMIT
Package: awslabs
# awslabs[awslabs](https://gitlab.com/binxio/awslabs) is a program that challenges your AWS knowledge.## InstallingThe simplest method is to install awslabs with `pip3`:pip3 install .## Development installationTo start for development type the following:```bashmake initmake develop```## Run awslabs for developmentType the following:```bashpipenv run python -m awslabs list```To run a track you are working on type:```bashpipenv run python -m awslabs <your-track> start```## Package awslabsTo package awslabs type:```bashmake dist```## TODORefine the following ideas.Errors:* Ensure it can only be used in python3Refactor/fix:* The deep if/else/try-statements makes it a horror* Remove the meta files/folders (__init__.py / __pycachec__ etc)* Consider replacing mytrack.py to yaml* Make region independent* Make the cloudformation input json compatible, and optionally a different file with a parameter in click* Make it easy to save progress details inFeatures:* Add tests (cloudformation already has the "perfect" cloudformation scripts)* Users can first read the track (awslabs trackname / awslabs trackname info)* Group tracks in "basic" and "advanced" (to be able to do the advanced, you need to have basic knowledge)* Write start time to config for report in the feedback the progress* Make awslabs track stop (or abort) such that it will warn if resources are still running* Add a short description to the tracks to improve track selection```$ awslabsTracks available:Basic:ec2             Deploy ec2 instance with initautoscaling     Deploy an autoscaling groups3              Use the S3 serviceml-api          Use the machine learning api'sAdvanced:kinesis-athena  Kinesis, Firehose, S3, Athenaecs             ECS Cluster with Service Discoverywordpress       Learn ELB, Autoscaling, RDS, Route53```## Create a simple challengeTo create a challenge, do the following:- Create a directory in tracks called eg. `mytrack`,- create a `mytrack.py` file in `mytrack`- create a directory `challenges` in `mytrack`- create multiple challenge files starting from `01.py` and so on.## TracksTracks are called `mytrack.py` and must contain at a minimum the following:```pythonfrom awslabs.track import Trackclass MyTrack(Track):"""A track description, can be multiline and contain links etc."""name = "TrackName"description = __doc__level = "basic"short_description = "a short description"```## ChallengesChallenges are named `01.py` and so on, and must contain at a minimum the following:```pythonfrom awslabs.challenge import Challengeclass MyChallenge(Challenge):"""Put your challenge"""title = "My Challenge"description = __doc__def start(self) -> None:self.instructions()def validate(self) -> None:self.save('key', 'a-value-to-save') # save a value to the sessionself.get('key') # load a value from the sessionself.check() # check the challengeself.success('') # mark the challenge as succesfulself.fail('') # mark the challenge as failure```
Package: aws-lambda
Aws LambdaA package used to manage lambda functions.
With this package it is easy to create lambda deployment packages and
create lambda resources with CloudFormation.DescriptionAn AWS Lambda management library which makes some of the painful parts less painful.
E.g. This project makes it easy to create Lambda deployment packages and upload
them to S3.PrerequisitesIn order to operate the package, you must first install it, using:pipinstallaws-lambdaHow to useMaking CloudFormation resourcesWith Troposphere# Create a Troposphere template.fromtroposphereimportTemplate# Create the initial template.template:Template=Template()# Create some of the resources for lambda function resource.fromtroposphere.iamimportRolefromtroposphere.ec2importSubnetfromtroposphere.ec2importSecurityGrouplambda_role=Role(...)lambda_subnets=[Subnet(...)]lambda_security_groups=[SecurityGroup(...)]# Import a lambda function resource class.fromaws_lambda.cloud_formation.lambda_troposphereimportLambdaFunction# Create a lambda function resource.lambda_function=LambdaFunction(prefix='MyCustomPrefix',description='My custom description.',memory=128,timeout=300,handler='file.function',runtime='python3.8',role=lambda_role,env={},security_groups=lambda_security_groups,subnets=lambda_subnets)# Add lambda function to a Troposphere template.lambda_function.add(template)With AWS CDK# Import AWS CDK core, iam, ec2, and lambda libraries.fromaws_cdkimportcorefromaws_cdkimportaws_lambdafromaws_cdkimportaws_iamfromaws_cdkimportaws_ec2# Create a CDK app.app=core.App()# Define a CDK stack class.classMainStack(core.Stack):def__init__(self,scope:core.Construct,id:str,**kwargs)->None:super().__init__(scope,id,**kwargs)# Import lambda function resource class.fromaws_lambda.cloud_formation.lambda_aws_cdkimportLambdaFunctionlambda_vpc=aws_ec2.Vpc(...)lambda_role=aws_iam.Role(...)lambda_security_groups=[aws_ec2.SecurityGroup(...)]lambda_subnets=[aws_ec2.Subnet(...)]# Create lambda function.LambdaFunction(scope=self,prefix='MyCustomPrefix',description='My custom description.',memory=128,timeout=300,handler='file.function',runtime=aws_lambda.Runtime.PYTHON_3_8,role=lambda_role,env={},security_groups=lambda_security_groups,subnets=lambda_subnets,vpc=lambda_vpc)# Create stack instance.MainStack(app,"MainStack")# Create a CloudFormation template.app.synth()Making Lambda deployment packages.# Import deployment package manager class.fromaws_lambda.deployment.deployment_packageimportDeploymentPackage# Suppose you have a project under a path:SCR_PATH='/home/user/projects/my_project'# Suppose you have run 'aws configure' on your machine and have a default profile.AWS_PROFILE='default'# Create deployment manager instance.deployment_package=DeploymentPackage(project_src_path=SCR_PATH,lambda_name='MyCoolLambda',s3_upload_bucket='MyCoolS3Bucket',s3_bucket_region='eu-west-1',aws_profile=AWS_PROFILE,environment='prod',refresh_lambda=True)# Initiate deployment.deployment_package.deploy()Release history2.1.3Use SubnetSelection.2.1.1Include md files.2.1.1Use time duration in CDK.2.1.0Add source code parameter.2.0.1Fix setup.py file.2.0.0Restructure. Add README and HISTORY files. Add docstrings.