Saravanan666/pypi-org huggingface dataset:
Package: awslogs-sd
Forward systemd journal logs to CloudWatch.A log forwarder daemon similar to Amazon’s awslogs agent, but using
per systemd unit journal output instead of text log files.InstallingUse your system package manager to install systemd Python 3
binding. The required package is namedpython3-systemdboth in
Ubuntu and Fedora:dnf install python3-systemdIf on Ubuntu, installpython3-venvtoo:apt install python3-venvCreate dedicated virtualenv for awslogs-sd:python3 -m venv --system-site-packages /opt/awslogs-sd
/opt/awslogs-sd/bin/pip install wheelAnd finally:/opt/awslogs-sd/bin/pip install awslogs-sdDaemon binary will be available under/opt/awslogs-sd/bin/awslogs-sd.AWS setupSimilarly to Amazon’s awslogs,awslogs-sdrequires an IAM policy
attached to EC2 instance. Configuration is the same as inAmazon
awslogs documentation.Usageawslogs-sdrequires path to configuration file as a positional
argument.You can use--logging-confto pass optional YAML logging
configuration indictConfigformat. SeePython logging
documentation. Following loggers can be configured:awslogs: main daemon loggermetrics: daemon statistics printed atINFOlevel every 10
secondsConfigurationConfiguration file uses ini format and is designed to be similar to
Amazonawslogs configuration.There are two main ini sectionsgeneralandinclude. Every
other section has arbitrary name and contains a single systemd unit
configuration.generalFollowing option is required:state_file: path to daemon database. Must be in persistent storage.Example:[general]
state_file = /var/lib/awslogs-sd/stateincludeOptional section with a single option:path: an Unix glob pattern to specify locations of additional
configuration files to load and merge with main one. Used mostly to
support popularconf.ddrop-in pattern.Example:[include]
path = /etc/awslogs-sd.conf.d/*.confUnit sectionsExample:[httpd_error]
unit = httpd.service
priority = ERR
syslog_ident = httpd_error
syslog_facility = local1
log_group_name = httpd-access
log_stream_name = {instance_id}Following options are supported:unit(required): systemd unit namelog_group_name(required): destination CloudWatch log grouplog_stream_name(required): CloudWatch stream name inside group;
support basic variable interpolation (see below)priority: minimum journal priority to match (default:INFO). SeeArch wiki.format: output log format, one oftextorjson(default:text)datetime_format: datetime format in strftime format if text
output is used (default:%b %d%H:%M:%S)syslog_ident: match by syslog ident (aka “tag”) if syslog
transport is usedsyslog_facility: match by syslog facility if syslog transport is
usedStream name variablesStream names support variable interpolation with{var}syntax. Following variables are available:instance_id: local EC2 instance idhostname: machine hostname
Package: awslogs-watch
awslogs-watchAboutawslogs-watch is a CLI tool that makes it easy to use awslogs.Default cache directory is$XDG_CACHE_HOME/awslogs_watchor~/.cache/awslogs_watchInstallationTo install awslogs-watch, use pip.pipinstallawslogs_watchExamplesUpdate awglogs groups cache$awslogs-watch
Command:updateor$awslogs-watch--updateInteractive modeoption: -i$awslogs-watch-i
Profile:default
Command:get
Group:group_name
Option:--start="1d"Interactive mode (Default value is recent history)option: -r$awslogs-watch-ir
Profile:default
Command:get
Group:group_name
Option:--start="1d"Get awslogs$awslogs-watch
Command:get
group:selectinteractivegroupnameor$awslogs-watch--get
group:selectinteractivegroupnameTail awslogs$awslogs-watch
Command:tail
group:selectinteractivegroupnameor$awslogs-watch--tail
group:selectinteractivegroupnameChange profile$awslogs-watch--profiledevelopSet awslogs option$awslogs-watch--option="-S"
Package: aws-longer
aws_longeraws_longeris a tool to replaceassume-rolewith a few significant
benefits:MFA tokens need only be entered once every 36 hours.Sessions can be shared across terminals, and persist across reboots.Both of the above are accomplished by storing the session credentials, and
assumed credentials in the user's keychain.InstallationInstall this package via:pipinstallaws_longerIf you'd like to use this package with your yubikey please run:pipinstallaws_longer[yubikey]# Escape the brackets in zshAssuming a Roleaws_longerroleROLENAMEAWS_ACCOUNTThe above will open a new shell setting the appropriateAWS_environment
variables. If this is the first time you are running this command, or it has
been 36 hours since you last input your MFA token, then you will be prompted to
input your MFA token.AWS_ACCOUNTcan either be an AWS account ID, or an alias to an AWS account
ID.If you'd like to prevent opening a new shell, you can instead run, but be
careful because if there are any errors, the result will terminate your
shell-program:execaws_longerroleROLENAMEAWS_ACCOUNTUsing the Temporary SessionRather than assuming a specific role, one can directly utilize the 36-hour
temporary session via:aws_longerUsing this temporary session is beneficial if, for example, you require MFA to
assume roles, and you'd like to be able to runterraform applywith a
provider that assumes a specific role.AWS Account ID AliasAWS account ID aliases can be defined in~/.aws/accounts, which is a JSON
file of the following format:{"default":"123456789012","staging":"123456789012","production":"123456789012"}This aliasing format is the same as was used inassume-rolein
order to ease transitioning.Avoid token promptingIf you happen to use a program to generate your MFA token, you might prefer to
pass the token directly as part of the command invocation instead of via a
prompt to STDIN. Do that via:aws_longer--mfa-tokenTOKENroleROLENAMEAWS_ACCOUNTIn said cases, the MFA token will only be used if it's necessary to do so.YubikeysIf you are using a Yubikey in TOTP mode, you can use it via:aws_longer--yubikeyNAMEroleROLENAMEAWS_ACCOUNTTo discover the name on your yubikey, you can list all names via:ykmanoathlist
Package: aws-lp
# aws-lp[![PyPI version](https://badge.fury.io/py/aws-lp.svg)](https://badge.fury.io/py/aws-lp)Tool for using AWS CLI with LastPass SAML.## UsageYou will need to look up your SAML configuration ID for the AWS role you wish to join. This is in the generated launch URL in the LastPass console, it will look something similar tohttps://lastpass.com/saml/launch/cfg/25. In this case, the configuration ID is25, enter this number when prompted during configuration ofaws-lp.`aws-lp--configureaws-lp`You will be prompted for your password and multi-factor code if that is set up on your account. If the command succeeds you will be returned to a prompt with the role name at the start of the prompt showing that you have managed to successfully get credentials and they are now added to your environment variables.
Package: awsm
Automated Water Supply ModelAutomated Water Supply Model (AWSM) was developed at the USDA Agricultural
Research Service (ARS) in Boise, ID. AWSM was designed to streamline the work
flow used by the ARS to forecast the water supply of multiple water basins.
AWSM standardizes the steps needed to distribute weather station data with SMRF,
run an energy and mass balance with iSnobal, and process the results, while
maintaining the flexibility of each program.Quick StartThe fastest way to get up and running with AWSM is to use the docker images that
are pre-built and can deployed cross platform.To build AWSM natively from source checkout the install instructionshere.DockerDocker images are containers that allow us to ship the software to our users
seamlessly and without a headache. It is by far the easiest way to use AWSM. If
you are curious to read more about them, visitWhats a containeron docker's
website.Using docker images comes with very minor quirks though, such as requiring you to
mount a volume to access the data when you are done with your run. To mount a
data volume, so that you can share data between the local file system and the
docker, the-voption must be used. For a more in depth discussion and
tutorial, read aboutdocker volumes. The container has a shared data volume
at/datawhere the container can access the local file system.NOTE: On the host paths to the volume to mount, you must use full absolute paths!Running the DemoTo simply run the AWSM demo; mount the desired directory as a volume and run
the image, using the following command:For Linux:docker run -v <path>:/data -it usdaarsnwrc/awsm:developFor MacOSX:docker run -v /Users/<path>:/data -it usdaarsnwrc/awsm:developFor Windows:docker run -v /c/Users/<path>:/data -it usdaarsnwrc/awsm:developThe output netCDF files will be placed in the location you mounted (using the
-v option). We like to usencviewto view our netcdf files quickly.Setting Up Your RunTo use the AWSM docker image to create your own runs, you need to setup a
project folder containing all the files necessary to run the model. Then using
the same command above, mount your project folder and provide a path to the
configuration file. An example of a project folder might like:My_Basin
      ├── air_temp.csv
      ├── cloud_factor.csv
      ├── config.ini
      ├── maxus.nc
      ├── metadata.csv
      ├── output
      ├── precip.csv
      ├── solar.csv
      ├── topo.nc
      ├── vapor_pressure.csv
      ├── wind_direction.csv
      └── wind_speed.csvThen the command would be:docker run -v <path>/My_Basin:/data -it usdaarsnwrc/awsm:develop <path>/My_Basin/config.ini
Package: awsmailman
AWS MailmanA utility for updating domain registrant information in Amazon Route 53.RequirementsYou must have the AWS CLI InstalledYou must have AWS credentials with the appropriate permissions setup locallyInstallationpip install awsmailmainUsageRunawsmailmanand follow the prompts.PurposeWhen you move, changing the addresses for the registered contacts on all of your Route53 domains is a pain. This script will update all the contacts on any Route 53 domains for you.QuirksThis uses the default AWS CLI credentials on your machineAt the moment you have to use the same name as is currently provided in your domain registration. The address may change.New FeaturesOpen a PR!
Package: aws-maintenance-window-reporter
AWS maintenance window reporterNameaws-maintenance-windows - reports upcoming maintenance actions and windowsSynopsisaws-maintenance-windows [--send-metrics]Options--send-metrics - send the metrics to DataDogDescriptionThis utility counts the number of upcoming maintenance actions and active maintenance windows
across EC2, RDS, Redshift and Opensearch. If --send-metrics is specified, the metrics
are send to DataDog. This allows you to create alerts to notift you whenever a maintenance
windows is pending.The metrics send are:aws.pending.maintenance.actionsnumber of available maintenance actionsaws.pending.maintenance.windowsnumber of scheduled maintenance windowsthe metrics will be tagged with the aws service name and the following resource ids:domainid (opensearch)dbinstanceidentifier (rds)dbclusteridentifier (rds)instance-id (ec2)clusteridentifier (opensearch)These tags are in accordance with the AWS tags defined by DataDog for the respective resources.Examples$aws-maintenance-windows
INFO:Maintenancewindowofec2instance-idi-22222222222222222:Theinstanceisrunningondegradedhardwareon2022-03-2800:00:00+00:00
INFO:Maintenancewindowofrdsdbclusteridentifierdb:UpgradetoAuroraPostgreSQL2.9.2on2022-03-1604:00:00+00:00
INFO:Maintenanceactionavailableforopensearchdomainides:AnewerreleaseR20211203-P4isavailable.
INFO:Maintenancewindowsofopensearchdomainides-2:AnupdatetoreleaseR20211203-P5hasbeenrequestedandispending.Beforetheupdatestarts,youcancancelitanytimeon2022-03-2000:00:00+00:00EnvironmentDD_API_KEYSpecifies the Datadog API key. if the value has the prefix ssm:// the api key will be  retrieved
by name the SSM Parameter Store eg (ssm://datadog-api-key)DATADOG_TAGSadditional datadog tags to add to the metric in the form key:value,key2:value,...AlternativesThe AWS Health services also provides insight into scheduled changes. The AWS Health API
is only available for accounts with a support contract.InstallTo install the AWS maintenance window reporter, type:pipinstallaws-maintenance-window-reporterDeployTo deploy the maintenance window reporter as an AWS Lambda, type:gitclonehttps://github.com/binxio/aws-maintenance-window-reporter.gitcdaws-maintenance-window-reporterread-p'DD API key >'DD_API_KEY
awscloudformationdeploy\--capabilitiesCAPABILITY_IAM\--stack-nameaws-maintenance-window-reporter\--template-file./cloudformation/aws-maintenance-window-reporter.yaml\--parameter-overrides"DataDogAPIKey=$DD_API_KEY"This will install the maintenance window reporter in your AWS account and run every hour.
Package: aws-manifest
aws-manifestA python package for retrieving information about aws's api manifest consisting
of resources and their actions.Getting Startedpip3 install aws-manifestUsagefrom awsmanifest import manifest, AwsManifest

# Retrieve the latest set of aws resources
m = manifest()
print(m["serviceMap"]["Amazon Ec2]["Actions])

# Retrieve the bundled local copy of aws resources
m = manifest(local=True)
...

# For helper functions, use the `AwsManifest` class
a = AwsManifest()
print(a.service_prefixes())
print(a.actions("Amazon Ec2))
print(a.actions("s3))
...LicensingMIT
Package: aws-marketplace-ubuntu-scraper
AWS Marketplace Ubuntu AMI ScraperCLI to return the Ubuntu AMIs in AWS marketplaceBasic setupInstall fromPyPi$ pip install aws-marketplace-ubuntu-scraper... OR ...Install the requirements manually:$ pip install -r requirements.txtYou will also needFirefoxinstalled andgeckodriveravailable in your PATH.I recommend you create a new IAM user with no permissions granted.
Ensure that you have opted in to all the AWS regions that are opt in only and
that you want quicklaunch listings for.You will also need to set up your aws credentials for use withboto3Run the application:$ python -m aws_marketplace_ubuntu_scraper --help

# Print details of the Ubuntu quicklaunch entries for each region
$ python -m aws_marketplace_ubuntu_scraper quicklaunch --iam-account-id="YOUR IAM ACCOUNT ID" --iam-username="YOUR IAM USERNAME" --iam-password="YOUR IAM PASSSWORD"

# Print details of the Ubuntu marketplace listings
$ python -m aws_marketplace_ubuntu_scraper marketplaceTo run the tests:$ pytest
Package: awsmate
awsmateis a companion for your AWS developments in Python.
It provides you with helper code that facilitates the use of various AWS services.What it is, what it doesawsmatepools AWS specific code that is rewriten and retested for each new project:it simplifies the use of some AWS servicesit simplifies the error handling related to the use of these servicesawsmatedoes not do what others have already done and sticks to simplifying the use of AWS:it does not replace existing major libraries such ass3fs,pynamodb,aws-lambda-powertoolsorboto3it does not implement functional use cases or algorithmsInstallationCommand line:pip3 install awsmatePyPI pageDocumentationThe complete documentation is available atReadTheDocs.Example applicationAn example application is available to demonstrate the main features of this library. It is documentedin this chapter.IssuesShould you encounter any bug or problem of any kind, please feel free to open an issue according to ourcontribution guidelines.LicenseThis project is licensed under the EUROPEAN UNION PUBLIC LICENCE (EUPL) v. 1.2, which is compatible with the majority of open source licences.View all translationsOSI Compatibility matrix
Package: awsm-cli
awsm-cliCLI menu for awesome listhttps://github.com/sindresorhus/awesomeInstallationpip install awsm-cliUsageusage: awsm-cli [-h] [-b BROWSER]

CLI Menu for awesome list https://github.com/sindresorhus/awesome

optional arguments:
  -h, --help            show this help message and exit
  -b BROWSER, --browser BROWSER
                        Custom BrowserOpen URL in the default browserawsm-cliOpen URL in a custom browserawsm-cli -b Firefox
Package: awsme
Amazon Web Services Cloud Watch Metrics LibraryConfigurable client library, that supports asynchronous and buffered sending of
AWS cloud watch metrics.InstallationBy default awsme is installed withoutboto3dependency to make it deploy
faster in AWS Lambda environment (See#3 <https://github.com/peterdemin/awsme/issues/3>for details).If you run awsme outside of Lambda, use following command to activateboto3dependency:pip install awsme[boto3]Usagefromawsmeimportcreate_cloud_watchcloud_watch=create_cloud_watch(namespace='Application',dimensions={'version':'1.0.0'},)cloud_watch.log('metric',dimensions={'key':'dim'},value=123)Create Optionscreate_cloud_watchaccepts following arguments:asynchronous (optional bool): if True (default), send metrics from a separate thread.buffered (optional bool): if True (default), metrics will be accumulated in a buffer and sent in batches.dummy (optional bool): if True, ignore two previous options and create dummy recorder. False by default.dimensions: (optional Dict[str, str]): dictionary of default dimensions, that will be attached to all metrics.All other kwargs will be bypassed toboto3.client('cloudwatch',**kwargs)Log OptionsCloudWatch, returned bycreate_cloud_watchhas two public methods. The primary method islog.
It’s arguments:name (required str): name of the metric.dimensions (optional Dict[str, str]): additional dimensions,
that will be added to default dimension from factory.value (optional float): metric’s value, 1 by default.unit (optional str): metric unit, e.g. Count, Seconds, Bytes,
seeAWS docsfor a complete list of valid values.storage_resolution (optional int): metric storage resolution in seconds, 60 by default.FlushingIfcreate_cloud_watchwas called withbuffered=True(default) then you may want to forcefully
flush the internal metrics buffer.
In a standard application this will likely not be necessary, as the buffer will auto-flushatexit.
However, if your application is running as an AWS Lambda function, the execution of the Lambda function
will be “frozen” when the function completes, preventing exiting and thus flushing. In this use case,
you will need to forcibly flush the buffer by callingflush.
It’s argument:complete (optional bool): if True (default), perform a complete flush.AWS configurationAwsme uses boto3 library, that takes configuration fromenvironment variablesand configuration files.
To check, that you have everything configured properly to send metrics, use included command-line tool:$ awsme-test
...
Successfully sent metric "awsme-test" to "Test Namespace"CreditsThis package was created withCookiecutterand theelgertam/cookiecutter-pipenvproject template, based onaudreyr/cookiecutter-pypackage.History0.2.2 (2019-01-24)Added asynchronous recorder and user documentation0.1.0 (2018-11-13)First release on PyPI.
Package: awsmeta
# awsmetaA tool for querying the AWS metadata serviceRequires Python 2.6+ (and must be run from an EC2 instance)```usage: awsmeta [-h] [-v API_VERSION] [--timeout TIMEOUT] [--version][-n short-name] [--list-names][path]positional arguments:pathoptional arguments:-h, --help            show this help message and exit-v API_VERSION        Metadata API version (default='latest')--timeout TIMEOUT     HTTP connection timeout in seconds (default: 2)--version             show the awsmeta version-n short-name, --by-name short-nameLook up a named metadata value--list-names          Print a list of known named metadata keys```# InstallationSystem-wide: `sudo pip install awsmeta`User installation: `pip install --user awsmeta` (or use a virtualenv)When installing as root, a bash completion script is installed to/etc/bash_completion.d. As a non-root user, you'll need to install thecompletion script yourself. You'll find it in the etc/bash_completion.dsubdirectory of the installation path.# Packaging[FPM](https://github.com/jordansissel/fpm) is recommended.Example:```fpm -s python -t deb \--iteration <package_revision> \--after-install=extras/fpm/after-install \--before-remove=extras/fpm/before-remove \setup.py```
Package: aws-meun
aws-meunCLI tool to unsubscribe from AWS Marketing EmailsQuick start❯ python -m pip install aws-meun
❯ aws-meun me@domain.org
Unsubscribed me@domain.org (HTTP 200)Quick tipaws-meun can also read from STDIN for easy batch unsubscribe❯ echo me@domain.org | aws-meun
Unsubscribed me@domain.org (HTTP 200)
Package: aws-mfa-auth
AbstractAWS MFA Authenticator tool to make using the AWS CLI with MFA easier.RequirementsPython 3.6+aws-cli (installed and configured)InstallationInstall usingpip install aws-mfa-auth.UsageBefore using this script, you must configure the tool with the ARN of the MFA device for the AWS profile you wish to authenticate with.aws-mfa-auth --configureOnce configured, provide the token the first time you run the script:aws-mfa-auth --token <MFA_DEVICE_TOKEN>Then simply runaws-mfa-authto output the environment variables to setup authentication.
Package: aws-mfa-login
# aws-mfa-loginCommand-line tool for MFA authentication against the AWS CLI. Only generates environment variables, no state or configuration (MFA serial can optionally be added to AWS config).Will by default ask for MFA token, and grab MFA device serial from the default profile in `~/.aws/config`.Profile, serial and token can also be passed on the command line.You must have a valid authentication for AWS CLI already set up for the STS call to succeed.Examples:```> aws-mfa-login --helpusage: aws-mfa-login [-h] [--token TOKEN] [--profile PROFILE | --serial SERIAL][--fish | --bash]optional arguments:-h, --help         show this help message and exit--token TOKEN      MFA token to use for login--profile PROFILE  AWS Profile to read MFA Serial from--serial SERIAL    MFA device serial (e.g.arn:aws:iam::00000000000:mfa/myiamuser)--fish             Override shell guessing, set to fish (use "set -e")--bash             Override shell guessing, set to bash (use "unset")> aws-mfa-loginMFA token: 123456export AWS_ACCESS_KEY_ID=ASIAJ5YFB3RUUOXGYOZQexport AWS_SECRET_ACCESS_KEY=abWbgMq5432lLIn6x34tj+Wlpykq1WR/KvbG2SXgexport AWS_SESSION_TOKEN=FQodyXlDvLv//////////wEaDCDCm3ZyUN0wDhSDKd3klfssZo4zNgTqnmUiVH0Hp8EUwtdKwvbiAa7JsyXVfzP2vaM0MTZmur/SDFDSf33/77WSdNtpUnaMyEnNP//XA7OVzmzlMLAXKYAbzrq3tBVuXxspEccz+qrxMZkfXD+DfLfkgbKF384kSDksKDF+85kZZTTr6t4t7v1tZ9DNV3xEehNJk8BS5yrD6vKusGRir+ZVm3SDFddfdsDFFD```
Package: aws-mfa-plugin
AWS MFA PluginAn awscli plugin to authenticate and retrive AWS temporary credentials using a MFA device.InstallationThis plugin was published inpypi.org. So the installation can be done using pip.$pip3install--useraws-mfa-pluginNOTE: We recommend installing inside user-siteConfigure the pluginIf you are using awscli v1 configuring plugin is pretty simple.$awsconfiguresetplugins.mfaaws-mfaOtherwise, If you are using awscli v2, there is a need for additional config.seefor more details.$awsconfiguresetplugins.cli_legacy_plugin_path$(python3-msite--user-site)Assumed the plugin installed inside user-siteVerify plugin installationIf you configure correctly the plugin will become a subcommand ofawscommand.$awsmfaGetting StartedBefore using this plugin to retrieve temporary credentials you need to configure mfa_serial device.$awsconfiguresetmfa_serial<your-mfa-serial-device>To retrive temporary credentials$awsmfacred-env
MFATokenfor(arn:aws:iam::1234567890:mfa/username):123456exportAWS_ACCESS_KEY_ID=<access-key-id>exportAWS_SECRET_ACCESS_KEY=<access-secret-key>exportAWS_SESSION_TOKEN=<token>Or you can directly set these temporary credentials as environment variable by usingevalcommand$eval$(awsmfacred-env)MFATokenfor(arn:aws:iam::1234567890:mfa/username):123456LicenseThis project licensed under MIT LICENSE, seeLICENSE.