Saravanan666/pypi-org huggingface dataset:
Package: cloudwatchmon
cloudwatch-mon-scripts-python=============================[![PyPI version](https://badge.fury.io/py/cloudwatchmon.svg)](https://badge.fury.io/py/cloudwatchmon)Linux monitoring scripts for CloudWatch.Requirements------------- Python >= 2.6- Boto >= 2.33.0Installation------------Optionally create a virtual environment and activate it. Then just run`pip install cloudwatchmon`. Install the scripts in /usr/local/bin folder.For script usage, run:mon-put-instance-stats.py --helpExamples--------To perform a simple test run without posting data to Amazon CloudWatchmon-put-instance-stats.py --mem-util --verify --verboseReport memory and disk space utilization to Amazon CloudWatchmon-put-instance-stats.py --mem-util --disk-space-util --disk-path=/To get utilization statistics for the last 12 hoursmon-get-instance-stats.py --recent-hours=12Configuration-------------To allow an EC2 instance to read and post metric data to Amazon CloudWatch,this IAM policy is required:{"Statement": [{"Action": ["cloudwatch:ListMetrics","cloudwatch:GetMetricStatistics","cloudwatch:PutMetricData","autoscaling:DescribeAutoScalingInstances"],"Effect": "Allow","Resource": "*"}]}If the policy is configured via an IAM role that is assigned to the EC2server this script runs on, you're done.Otherwise you can configure the policy for a user account and exportthe credentials before running the script:export AWS_ACCESS_KEY_ID=[Your AWS Access Key ID]export AWS_SECRET_ACCESS_KEY=[Your AWS Secret Access Key]Third option is to create a _~/.boto_ file with this content:[Credentials]aws_access_key_id = Your AWS Access Key IDaws_secret_access_key = Your AWS Secret Access KeyCopyright---------Copyright 2015 Oliver SiegmarBased on Perl-Version of CloudWatch Monitoring Scripts for Linux -Copyright 2013 Amazon.com, Inc. or its affiliates. All Rights Reserved.Licensed under the Apache License, Version 2.0 (the "License");you may not use this file except in compliance with the License.You may obtain a copy of the License athttp://www.apache.org/licenses/LICENSE-2.0Unless required by applicable law or agreed to in writing, softwaredistributed under the License is distributed on an "AS IS" BASIS,WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.See the License for the specific language governing permissions andlimitations under the License.
Package: cloud-weather-app
Weather ApplicationA python package to get quick info of weather
For more info visit :https://gitlab.com/0xdebug/cloud-weatherGet StartedHow to InstallUse the python package managerpipto install cloud_weather_app.pip install cloud_weather_appRequirementspython >= 3.6requestsbeautifulsoup4Usagefrom cloud_weather_app import cloud_weather

# Enter the valid Place Name
mumbai = cloud_weather('mumbai')

# Choose relevant forecast type and print variable to view outputs
daily = mumbai.daily()
monthly = mumbai.monthly()
hourly = mumbai.hourly()Sample OutputThe Ouputs are just indicative and may subject to enhance in future versionsDailyObserved at : 2019-10-14 03:03:49
Temperature : 22Â°, Feels like : 22Â°, Desc : ThunderMonthly--------------------------------------------------------------------------------

Date           Temp Day                      Temp Night
--------------------------------------------------------------------------------

2019-10-15     28Â°  PM T-Storms              21Â°  Scattered T-Storms
2019-10-16     27Â°  T-Storms                 20Â°  T-Storms
2019-10-17     28Â°  T-Storms                 20Â°  T-Storms
2019-10-18     28Â°  PM T-Storms              20Â°  Scattered T-Storms
2019-10-19     28Â°  PM T-Storms              20Â°  Scattered T-Storms
2019-10-20     28Â°  PM T-Storms              20Â°  T-Storms
2019-10-21     27Â°  PM T-Storms              20Â°  T-Storms
2019-10-22     27Â°  PM T-Storms              20Â°  T-Storms
2019-10-23     27Â°  T-Storms                 20Â°  T-Storms
2019-10-24     27Â°  T-Storms                 20Â°  T-Storms
2019-10-25     26Â°  T-Storms                 19Â°  Scattered T-Storms
2019-10-26     27Â°  PM T-Storms              19Â°  Scattered T-Storms
2019-10-27     27Â°  PM T-Storms              19Â°  T-Storms
2019-10-28     27Â°  Scattered T-Storms       19Â°  Scattered T-StormsWeekly--------------------------------------------------------------------------------

Time           Description              Temp           Feels like
--------------------------------------------------------------------------------

04:00          Cloudy                   22Â°            22Â°
05:00          Scattered T-Storms       22Â°            22Â°
06:00          Cloudy                   22Â°            22Â°
07:00          Mostly Cloudy            21Â°            21Â°
08:00          Mostly Cloudy            22Â°            22Â°
09:00          Partly Cloudy            23Â°            23Â°
10:00          Partly Cloudy            25Â°            25Â°
11:30          Partly Cloudy            27Â°            30Â°
12:30          Partly Cloudy            28Â°            30Â°
13:30          Partly Cloudy            29Â°            30Â°
14:30          Partly Cloudy            29Â°            31Â°
15:30          Partly Cloudy            29Â°            31Â°
16:30          Partly Cloudy            28Â°            30Â°
17:30          Partly Cloudy            27Â°            29Â°
18:30          Partly Cloudy            26Â°            28Â°AuthorDeepak Natanmaigitlab.com/0xdebug
Package: cloud-weather-report
# OverviewCloud Weather Report (cwr) enables charm authors and maintainers to runhealth checks and benchmarks on multiple clouds.When the `cwr` starts executing, it deploys a bundle or charm on the cloudschosen by the author. It runs all the tests associated with each charmin each cloud it deployed to. It also runs benchmarks on those clouds allowingcharm authors to see how their charms are performing on different clouds.## Installing prerequisitesCloud Weather Report uses `make` and `unzip` during execution and `python-dev`during installation. Make sure these tools are installed before installing the`cwr`. If you are on Ubuntu, you can install them using `apt-get`.## Installation[sudo] pip install cloud-weather-report## Installing from a sourcecurl -L -o cwr.zip https://github.com/juju-solutions/cloud-weather-report/archive/master.zipunzip cwr.zipcd cloud-weather-report-masterpython setup.py install## UsageAfter installing the Cloud Weather Report, you will have `cwr` commandinstalled on your machine. It is assumes that the controller is already bootstrappedbefore running `cwr`. You can simply run `cwr` by specifying one or morecontrollers and the path to the test plan.cwr controller  [controller ...] test-plan.yamlFor example if you already have bootstrapped `aws` and `gce` controllers:cwr aws gce test-plan.yamlNote: `aws` and `gce` are the names of your Juju 1.25 environment (found in your environments.yaml) or the name of your Juju 2.0 controller (found in `juju list-controllers`). If you had named your environment or controller for AWS soemthing like `aws-west1` the CWR command would look like:cwr aws-west1 test-plan.yamlOnce `cwr` starts running, it deploys the bundle, runs the tests and benchmarks thatare defined in the test plan. An example of the test plan is included in the`examples` directory.## Running bundlesThe following is example of a test plan to run the `apache-analytics-sql` bundle. Itdeploys `apache-analytics-sql` and runs `terasort` benchmarks.bundle: bundle:apache-analytics-sqlbenchmark:plugin:terasortThe following example deploys the `mongodb` charm and runs the `perf` benchmark.The `runtime: 60` is a parameter passed to `perf`.bundle: cs:mongodbbenchmark:mongodb:perf:runtime: 60## Result outputsOnce the run is completed, the `cwr` generates a HTML file containing the testand benchmark results. The path to the HTML file will be displayed and will alsobe opened in a web browser.
Package: cloud_wiki
Cloud Wiki was implemented as a response to the lack of Python wiki servers that
are intended to run as an individual server process and provide functionality to
meet its designer’s needs.Cloud Wiki’s nodes are stored in a sqlite database, and served using python’s
BaseHTTPServer, running as a long lived application service.  Wiki markup is a
simple unobtrusive dialect, providing free linking, images, tables, unordered
lists and preformatted text blocks. Rendered content data is stored in the
database, along with content change information, to improve server response times.Cloud Wiki supports user authentication, but does not currently provide an
registration interface of its own – the authentication system is designed to be
modular and easily extended by adding functionality to check passwords from
other existing databases or to periodically import them using a cron script.
Package: cloudwinterstore
Cloud Winterstore Admin SDK v0.0.1We have put a lot of effort to make Cloud Winterstore very easy to use, both in the application and the documentation.
Our motto being to secure files and secure them easily.Storage for your application can be implemented in 2 ways.
(1)     The client can fetch the file they want independently from the Storage Server.
(2)     The client requests to the server, and the server retrieves the file for the client from the Storage Server.The Admin SDK (This Library) is meant for storage implementation using option (1)
This SDK should not be used on the client side as it gives them Administrative PriviledgesGetting StartedWe assume you have already created an account with us onhttps://cloudwinterstore.co.zwStart of by creating a new projectNavigate to the “Accounts Tab”Click “Admin Accounts”Create an Admin Account with a strong passwordInstall the LibraryIn your terminal, runpython pip install winterstore-adminTest GatewayImport the library and use the checkGateWay() methodimport cloudwinterstorecloudwinterstore.checkGateWay()MethodsCheck Gateway: Is used to check if the server gateway is opencheckGateWay()Authenticate: Is used to authenticate with the serverauthenticate(username,password)Check Authentication: Checks if authenticatedcheckAuthentication()Get Folder : Get foldersgetFolder(projectName,id=”root”)Get Path : returns a list of files that belong to the folder in that projectgetPath(projectName,path=”root”)Upload File : Uploads a file to a folder in a project given the parameters in multi-part form data.uploadFile(file,allowAllUsersWrite,allowAllUsersRead,allowKeyUsersWrite,allowKeyUsersRead,name,project,parent)Get File: Returns a streaming filegetFile(id)Get File Using Path : Returns a streaming filegetFileUsingPath(projectName,path)File Info : Given a file id returns infomation on a filegetFileInfo(id)Delete : Deletes an index object.deleteIndexObject(id)Rename : Renames an index object given the objects id and new name as JSON datarename(id,new_name)Give Key : Gives a key to a client to access a files.giveKey(account,file_id)Remove Key: Removes a key from a clientremoveKey(accounts,file_id)New Folder: Creates a new folder in a projectnewFolder(projectName,parentID,folderName)Get People With Key : Returns a JSON list of people who have access to a file/foldergetPeopleWithKey(id)Add Client: adds a developer client to a projectaddClient(identification,integration,password,project)Delete Client: delete a developer clientdeleteClient(identification,integration,password,project)Search Developer Client: returns a JSON list of developers that meet a criteriasearchClient(criteria,project)Barn Client: barns a developer client AccountbanClient(idetification,project)Remove Barn: remove barn inflicted on a developer accountunbanClient(idetification,project)Winterstore Admin v.0.1.1No changes - this is the first release
Package: cloudwise
CloudwiseInstallationUsageFAQscloudwiseis Surreal’s cloud infrastructure provisioner based on
Terraform. Surreal’swebsiteandgithub.It prepares a kubernetes cluster using terraform. It generates.tf.jsonfiles that are also recognized bySymphony.InstallationCloud wise runs in python 3Dogit clone git@github.com:SurrealAI/cloudwise.git && cd cloudwiseRunpip install-e.in this directory.Installterraformfollowing instructionshereInstallkubectlfollowing instructionshereUsage(Optional, Recommended) Create and work in a clean directory as
running terraform would generate relevant files.>mkdirsurreal>cdsurrealGoogle CloudYou first need to setup credentials forterraformto access
google cloud. See guidehere.
Choose one of the two methods:Run the following commandgcloudauthapplication-defaultloginorGo to the api key management pagehttps://console.cloud.google.com/apis/credentials/serviceaccountkeyand selectCreate new service account. You would need to give
the service account sufficient permissions to do things properly.Project editorwould suffice but is also more than enough. You
can then generate and download the key, (jsonformat is fine).
Put the path to the.jsonfile into the commandline argument
when prompted.Follow the instructions in the commandline tool.>cloudwise-gkeIt will provide instructions and generate a<cluster_name>.tf.jsonfile which terraform recognizes. If you have generated a.jsoncredential file, you should provide it when prompted. *terraform init && terraform plandescribes changes to be made. *terraform applymakes the changes to your cloud project. * After
cluster creation, obtain credentials for kubectl.>gcloudcontainerclustersget-credentials<cluster_name>If you have GPUs in your cluster, create the daemon set to install
drivers, seedocumentation.>kubectlapply-fhttps://raw.githubusercontent.com/GoogleCloudPlatform/container-engine-accelerators/stable/nvidia-driver-installer/cos/daemonset-preloaded.yamlThe generated<cluster_name>.tf.jsonis also recognized bySymphony’s scheduling
mechanism andSurreal. So you may want to link to itIf you want to remove everything, runterraform destroyAWSStay tunedAzureStay tunedFAQs:Terraform install fails.If you are seeing error:... API has not been used inproject...: duringterraform apply, go to the Kubernetes Engine tab and/or
Compute Engine tab on your google cloud console to enable their
APIs.GPU nodes are not scaling up.Check if the driver installation daemon set is running (seedocumentation).
Package: cloudx-iaas-api
Securyi Anomaly Detector Micro ServiceLorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi porta aliquam nisi, in tempus risus. Nam cursus risus dictum auctor scelerisque. Mauris cursus libero tellus. In hac habitasse platea dictumst. Nullam et turpis eu orci lacinia rhoncus sed id nibh. Nullam sit amet nibh in nunc posuere laoreet ut vitae mauris. Cras commodo vulputate mi.Donec in diam laoreet, faucibus erat et, venenatis nisl. Integer vitae elit ac nulla facilisis pharetra pharetra a ex. Integer imperdiet varius elementum. Pellentesque eu urna purus. Pellentesque eu justo ac magna dictum egestas ac vel massa. Praesent pretium ut elit ultricies iaculis. Sed maximus dapibus sollicitudin. Proin varius diam quis tincidunt aliquet.pipinstallcloudx_naas_apiUt fermentum fringilla fermentum. Nunc ut auctor sapien. Donec pellentesque, odio sit amet venenatis dictum, dui tellus vulputate mi, id venenatis dui purus et metus. Cras mollis est in fermentum mattis. Nullam faucibus urna id posuere aliquet. Mauris ut fermentum mauris. Morbi elementum feugiat justo tempor vehicula. Fusce non enim nec turpis scelerisque maximus. In id fringilla dui. Vivamus placerat massa turpis. Nam rhoncus turpis eget tortor consequat laoreet. Pellentesque pellentesque id diam quis ullamcorper. Vestibulum ultrices magna laoreet, fermentum tortor et, venenatis nisl. Donec ullamcorper, sem et elementum bibendum, nisi sapien euismod quam, sit amet rutrum tellus risus in nisl.makebuildpushProin pharetra sapien mollis, efficitur turpis quis, elementum velit. Aliquam posuere lectus nisl, non rutrum libero tristique at. Duis sit amet pharetra tellus. Donec tempor est sed aliquam rutrum. Maecenas vitae metus quis tortor pellentesque imperdiet et sed dolor. Maecenas condimentum augue nec nunc imperdiet, sit amet sollicitudin ipsum aliquam. Proin lobortis mi quis eleifend dignissim. Mauris convallis semper nibh vel pretium. Sed et mattis nunc. Duis orci leo, elementum ut sapien quis, eleifend interdum enim. Suspendisse vitae diam euismod, bibendum velit iaculis, rhoncus dui. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Pellentesque consequat consequat est, a mollis quam porttitor dignissim. Vivamus fermentum vel turpis sit amet imperdiet. Morbi eget maximus justo.Maecenas et porta metus. Nulla consequat hendrerit augue, nec gravida nunc iaculis et. Aliquam erat volutpat. Nunc consequat condimentum mauris et euismod. Donec scelerisque tincidunt elementum. Nam et imperdiet nunc, tincidunt laoreet ipsum. Maecenas pulvinar lorem sit amet enim malesuada auctor non et diam. Proin ac elit vulputate, pulvinar quam condimentum, suscipit velit. Curabitur tincidunt, tellus lobortis volutpat ultricies, dui dui cursus justo, ut consequat quam ligula elementum purus. Morbi consequat ultricies mi, quis viverra elit.
Package: cloudx-nac-api
Securyi Anomaly Detector Micro ServiceLorem ipsum dolor sit amet, consectetur adipiscing elit. Morbi porta aliquam nisi, in tempus risus. Nam cursus risus dictum auctor scelerisque. Mauris cursus libero tellus. In hac habitasse platea dictumst. Nullam et turpis eu orci lacinia rhoncus sed id nibh. Nullam sit amet nibh in nunc posuere laoreet ut vitae mauris. Cras commodo vulputate mi.Donec in diam laoreet, faucibus erat et, venenatis nisl. Integer vitae elit ac nulla facilisis pharetra pharetra a ex. Integer imperdiet varius elementum. Pellentesque eu urna purus. Pellentesque eu justo ac magna dictum egestas ac vel massa. Praesent pretium ut elit ultricies iaculis. Sed maximus dapibus sollicitudin. Proin varius diam quis tincidunt aliquet.pipinstallcloudx_naas_apiUt fermentum fringilla fermentum. Nunc ut auctor sapien. Donec pellentesque, odio sit amet venenatis dictum, dui tellus vulputate mi, id venenatis dui purus et metus. Cras mollis est in fermentum mattis. Nullam faucibus urna id posuere aliquet. Mauris ut fermentum mauris. Morbi elementum feugiat justo tempor vehicula. Fusce non enim nec turpis scelerisque maximus. In id fringilla dui. Vivamus placerat massa turpis. Nam rhoncus turpis eget tortor consequat laoreet. Pellentesque pellentesque id diam quis ullamcorper. Vestibulum ultrices magna laoreet, fermentum tortor et, venenatis nisl. Donec ullamcorper, sem et elementum bibendum, nisi sapien euismod quam, sit amet rutrum tellus risus in nisl.makebuildpushProin pharetra sapien mollis, efficitur turpis quis, elementum velit. Aliquam posuere lectus nisl, non rutrum libero tristique at. Duis sit amet pharetra tellus. Donec tempor est sed aliquam rutrum. Maecenas vitae metus quis tortor pellentesque imperdiet et sed dolor. Maecenas condimentum augue nec nunc imperdiet, sit amet sollicitudin ipsum aliquam. Proin lobortis mi quis eleifend dignissim. Mauris convallis semper nibh vel pretium. Sed et mattis nunc. Duis orci leo, elementum ut sapien quis, eleifend interdum enim. Suspendisse vitae diam euismod, bibendum velit iaculis, rhoncus dui. Orci varius natoque penatibus et magnis dis parturient montes, nascetur ridiculus mus. Pellentesque consequat consequat est, a mollis quam porttitor dignissim. Vivamus fermentum vel turpis sit amet imperdiet. Morbi eget maximus justo.Maecenas et porta metus. Nulla consequat hendrerit augue, nec gravida nunc iaculis et. Aliquam erat volutpat. Nunc consequat condimentum mauris et euismod. Donec scelerisque tincidunt elementum. Nam et imperdiet nunc, tincidunt laoreet ipsum. Maecenas pulvinar lorem sit amet enim malesuada auctor non et diam. Proin ac elit vulputate, pulvinar quam condimentum, suscipit velit. Curabitur tincidunt, tellus lobortis volutpat ultricies, dui dui cursus justo, ut consequat quam ligula elementum purus. Morbi consequat ultricies mi, quis viverra elit.
Package: cloudy
Parses the output files of the spectral synthesis code Cloudy into Pandas
DataFrames for analysis.ExampleHere is a quick example. See sample_data for an ipythpn notebook example:>>> from cloudy import cloudy
>>> sample = cloudy.Cloudy(
  'sample_data/sample.grd', 'sample_data/sample.ems')
>>> sample.labels
['H  1  6563A',
 'N  2  6584A',
 'O  1  6300A',
 'S  2  6720A',
 'Temperature',
 'depth']TodosWrite Docs
Package: cloudydict
cloudydict======Right now cloud file access in Python is about where database accesswas in the mid 90's.  Each database wrapper author has their very ownnomenclature, sets of commands for doing things that are basically thesame - creating cursors, executing commands and reading rows.cloudydict seeks to do for cloud file providers what the PythonDatabase API does for database access.  Cloud file style servces likeRackspace's cloud files and Amazon's S3 really are nothing more thandictionaries that map fixed strings to
Package: cloudyqueue
cloudyqueue======Right now cloud file access in Python is about where database accesswas in the mid 90's.  Each database wrapper author has their very ownnomenclature, sets of commands for doing things that are basically thesame - creating cursors, executing commands and reading rows.cloudyqueue seeks to do for cloud file providers what the PythonDatabase API does for database access.  Cloud file style servces likeRackspace's cloud files and Amazon's S3 really are nothing more thandictionaries that map fixed strings to
Package: cloudzipfile
cloudzipfileThis module provides a way to access zipfiles in cloud storage without downloading the entire zip file.
It is inspired byremotezip, but leverages the respective cloud APIs rather than requiring support for therange header.
It currently only supports Azure, porting it to other systems should be fairly simple, pull requests very welcome!Installationpip install cloudzipfileUsagecloudzipfile is a subclass of Python's standard libraryzipfile.Zipfileand thus supports all its read methods.Instead of providing Zipfile with a path, you provide a blob client of your cloud provider, for example:# Import
from azure.storage.blob import BlobClient
from cloudzipfile.cloudzipfile import CloudZipFile
import os, tempfile, uuid

# Define blob client
BLOB_URL = 'https://cloudzipfileexamples.blob.core.windows.net/test/files.zip'
blobClient = BlobClient.from_blob_url(BLOB_URL)

# Define link to zipfile
# Will download central directory (where to find specific files)
PATH_OUTPUT = os.path.join(tempfile.gettempdir(), str(uuid.uuid4()))
FILES_DESIRED = ['file1.txt', 'file3.txt']
cloudZipFile = CloudZipFile(blobClient)

# Extract specific files
cloudZipFile.extractall(path=PATH_OUTPUT, members=FILES_DESIRED)

# Verify success: should show file1.txt and file2.txt
print(f'{PATH_OUTPUT}: {os.listdir(PATH_OUTPUT)}')Future DevelopmentSupporting other systems is fairly straightforward as you require only two methods. One that determines the size of the cloud file and one that performs a partial download, these should be supported by all major providers (I simply don't have experience with them).How It WorksZip files have a fixed structure, which can be leveraged for partial reading. They end with anEOCDwhich lists where to find the central directory. Thecentral directorylists all files in the archive and where to find them. Python'szipfileuses these two pieces to determine which part of the file to load into memory when the user requests a particular file. This package overwrites that loading process to work with cloud APIs directly rather than only with local filesystems. All credit go toremotezipfor figuring out how to overwrite the process, I only edited it to use APIs rather than HTTP requests.