Saravanan666/pypi-org huggingface dataset:
Package: dopt
How to useWe'll be runningdistributed_optimizer.pyto start the optimization.distributed_optimizer.pycan be run in 2 modes: host mode and client mode.
The host mode will call 2 processes: One that
starts theOptimizerof choice and One that connect with other machines (the clients) to rundistributed_optimizer.pyon client mode.
The client mode will run the user-specified MyWhateverTrainer.
Host mode:python3 distributed_optimizer.pyas host mode is the default.
Client mode:python3 distributed_optimizer.py --run_as=clientas client mode. You donotneed to manually run client mode on each client machine as the host mode will do this. However, you can use it if you want to add client machines during optimization.Essential parts of the script:The COMMANDS: A constant dictionary. The keys are machine categories, and values are the necessary commands to rundistributed_optimizer.pyon client mode on those different categories.A MyWhateverTrainer that inherits theTrainerabstract class fromsrc.trainer, and implement the abstract methodget_observation, in which the set of hyperparameters (candidate) given will be plugged into the objective function.Astart_host()function that will be used to call 2 processes: one that
start theOptimizerand one that runs appropriate sequence of commands to rundistributed_optimizer.pyon client mode, i.e. startTrainerson respective machines using the following:python3 distributed_optimizer.py --run_as=clientAstart_client()function that will run MyWhateverTrainer, i.e. run objective function.Amain()that parse command line input and switch between host and client mode, and specify further information needed to run objective function on target machines.Check list:Step 1: Create your specifiedMyWhatever Trainerthat implements theget_observationmethod.Step 2: Make sure the appropriate environment can be chosen through ssh tunneling. Try:ssh [name]@[hostmachine] [YOUR COMMANDS]Step 3: Add the commands to theCOMMANDSdictionary.Step 4: Make sure you have a copy of thedistributed_optimizer.pyand related files on all of the machines you intend to use
Package: dopt-blocks-python-client
Dopt Blocks Python LibraryInstallationAdd this dependency to your project's build file:pipinstalldopt-blocks-python-client# orpoetryadddopt-blocks-python-clientUsagefromdopt.clientimportDoptApiclient=DoptApi(api_key="YOUR_API_KEY)# Fetch a flow from dopt, including its blocks.  The first fetch of# this (flow.sid, flow.version) tuple will initialize the flow for# the `user_identifier`flow=client.flows.get_flow(sid="example-flow",version=1,include="block",user_identifier="joe_mckenney",group_identifier=None,)print(flow)# Fetch a block for some previously initialized flowblock=client.blocks.get_block(uid="9sKe7gx4HZj_VI7oxfVD3",version=1,user_identifier="joe_mckenney")print(block)Async Clientimportasynciofromdopt.clientimportAsyncDoptApiasync_client=AsyncDoptApi(api_key="YOUR_API_KEY)asyncdefget_flow()->None:response=async_client.flows.get_flow(sid="example-flow",version=1,include="block",user_identifier="joe_mckenney",group_identifier=None,);print(response)asyncio.run(get_flow())ContributingWhile we value open-source contributions to this SDK, this library is generated programmatically. Additions made directly to this library would have to be moved over to our generation code, otherwise they would be overwritten upon the next generated release. Feel free to open a PR as a proof of concept, but know that we will not be able to merge it as-is. We suggest opening an issue first to discuss with us!On the other hand, contributions to the README are always very welcome!
Package: dopt-users-python-client
Dopt Users Python LibraryInstallationAdd this dependency to your project's build file:pipinstalldopt-users-python-client# orpoetryadddopt-users-python-clientUsagefromdopt.clientimportDoptApiclient=DoptApi(api_key="YOUR_API_KEY")client.users.identify_user(identifier="todd_solondz",properties={"first_name":"todd","last_name":"solondz",},)Async Clientimportasynciofromdopt.clientimportAsyncDoptApiasync_client=AsyncDoptApi(api_key="users-usersKey_Mw==")asyncdefidentify_user()->None:client.users.identify_user(identifier="todd_solondz",properties={"first_name":"todd","last_name":"solondz",},)asyncio.run(identify_user())ContributingWhile we value open-source contributions to this SDK, this library is generated programmatically. Additions made directly to this library would have to be moved over to our generation code, otherwise they would be overwritten upon the next generated release. Feel free to open a PR as a proof of concept, but know that we will not be able to merge it as-is. We suggest opening an issue first to discuss with us!On the other hand, contributions to the README are always very welcome!
Package: dopy
Digital Ocean API Python WrapperInspired by [dop](https://github.com/ahmontero/dop).Installation# pip install dopyGetting StartedTo interact with Digital Ocean, you first need .. a digital ocean account with
valid API keys.Keys can be set either as Env variables, or within the code.For API v.2.# export DO_API_VERSION='2'
# export DO_API_TOKEN='api_token'>>>fromdopy.managerimportDoManager>>>do=DoManager(None,'api_token',api_version=2)For API v.1.# export DO_CLIENT_ID='client_id'
# export DO_API_KEY='long_api_key'>>>fromdopy.managerimportDoManager>>>do=DoManager('client_id','long_api_key')MethodsThe methods of the DoManager are self explanatory; ex.>>>do.all_active_droplets()>>>do.show_droplet('12345')>>>do.destroy_droplet('12345')>>>do.all_regions()>>>do.all_images()>>>do.all_ssh_keys()>>>do.sizes()>>>do.all_domains()>>>do.new_droplet('new_droplet',66,1601,1)The methods for v.2 API are similar, the only difference
is using names instead of IDs for domains and slugs for
sizes, images and datacenters; ex.>>>do.show_domain('exapmle.com')>>>do.new_droplet('new_droplet','512mb','lamp','ams2')TODOSee github issue list - post if any neededhttps://github.com/devo-ps/dopy/issues
Package: doq
Docstring generator.Installation$ pip install doqHow to use$ cat spam.py
def spam(arg1, arg2: str) -> str:
    pass$ cat spam.py | doq
def spam(arg1, arg2: str) -> str:
  """spam.

  :param arg1:
  :param arg2:
  :type arg2: str
  :rtype: str
  """
  passDefault formatter issphinx. You can choosesphinx,googleornumpy.$ cat spam.py | doq --formatter=google
def spam(arg1, arg2: str) -> str:
  """spam.

  Args:
      arg1 : arg1
      arg2 (str): arg2

  Returns:
      str:
  """
  pass$ cat spam.py | doq --formatter=numpy
def spam(arg1, arg2: str) -> str:
  """spam.

  Parameters
  ----------
  arg1
        arg1
  arg2 : str
       arg2

  Returns
  -------
  str

  """
  passUsage$ python -m doq.cli --help
usage: doq [-h] [-f FILE] [--start START] [--end END] [-t TEMPLATE_PATH]
           [-s STYLE] [--formatter FORMATTER] [--indent INDENT] [--omit OMIT]
           [-r] [-d DIRECTORY] [-w] [-v] [-c CONFIG] [--ignore_exception]
           [--ignore_yield] [--ignore_init]

Docstring generator.

optional arguments:
  -h, --help            show this help message and exit
  -f FILE, --file FILE  File or STDIN
  --start START         Start lineno
  --end END             End lineno
  -t TEMPLATE_PATH, --template_path TEMPLATE_PATH
                        Path to template directory
  -s STYLE, --style STYLE
                        Output style string or json
  --formatter FORMATTER
                        Docstring formatter. sphinx,google or numpy
  --indent INDENT       Indent number
  --omit OMIT           Omit first argument such as self
  -r, --recursive       Run recursively over directories
  -d DIRECTORY, --directory DIRECTORY
                        Path to directory
  -w, --write           Edit files in-place
  -v, --version         Output the version number
  -c CONFIG, --config CONFIG
                        Path to a setup.cfg or pyproject.toml
  --ignore_exception    Ignore exception statements
  --ignore_yield        Ignore yield statements
  --ignore_init         Ignore generate docstring to __init__ methodCustomize templatedoq use Jinja2 template. So you can create your own template.NoteYou must create 3 template files.File nameDescriptionclass.txtclass docstringdef.txtdef / method docstringnoarg.txtdef / method without argument docstringAvailable Jinja2’s variableNameDescriptionnameclass, method, def’s nameparamsargumentMethod, def’s argumentannotationArgument’s type hintdefaultDefaut keyword argumentexceptionsList of exceptionyieldsList of yieldreturn_typeReturn type hintSeeexamplesConfigurationdoq will automatically searchsetup.cfgorpyproject.tomlin your
project.Noteignore_exception, ignore_exception and ignore_init can settrueonly.
If you want turn off, remove from configuration.setup.cfgThe section must be[doq].configuration file example:[doq]
style = "json"
template_path = "/path/to/template"pyproject.tomlThe section must be[tool.doq].configuration file example:[tool.doq]
style = "json"
template_path = "/path/to/template"CompletionThis program provides shell completions. It should be out of box if you install
it from a wheel file.LICENSENEW BSD LICENSE.
Package: doqs
doqs.dev python SDKThis is the officially maintained doqs.dev python SDK.It is currently a placeholder as the main SDK is under development.What is doqs?doqs is a platform to fill PDF templateswith the data you provide on an API call.
The templates can be configured via ourtemplate editor in the dashboard.DocumentationHave a look at outAPI documentationUsageSDK is currently under construction. We will provide this section soon.
Package: doqu
Doquis a lightweight schema/query framework for document databases.
It is not an ORM as it doesn’t map existing schemata to Python objects but
instead defines them on a higher layer built upon a schema-less storage
(key/value or document-oriented). You define models as a valuable subset of the
whole database and work with only certain parts of existing entities —  the
parts that you need.The name “doqu” is a shortcut fordocument-query, the central concept
of the library.InstallationUsing pip:$ pip install doquArchLinux (AUR):$ yaourt python2-doquDocumentationSee thecomplete documentationfor details. If it’s not complete enough,
feel free to ask your questions in thediscussion group.AuthorOriginally written by Andrey Mikhaylenko since 2009.See the file AUTHORS for a complete authors list of this application.Please feel free to submit patches, report bugs or request features:http://bitbucket.org/neithere/doqu/issues/LicensingDocu is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as published
by the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.Docu is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU Lesser General Public License for more details.You should have received a copy of the GNU Lesser General Public License
along with Docu.  If not, see <http://gnu.org/licenses/>.
Package: dora-cli
Dora CLICommand Line Interface to manager an Dora sandbox.python-mdora_cliUsageThe following options are available in this version:configureUse to setup your environment with all the credentials and configurations needed to access the Cloud Provider services.All the configurations will be saved on~/.config/dora-cli/config.jsonUse--helpoption to more detailsstartIf successful you will be prompted with thetokengenerated to access you Jupyter Lab environment followed bynameandstatusof thecontainer.TOKEN:d337b5ee0b72c6687b9a9e8f8f9a2f5972559454e90c6e10
happy_lovelace:createdAccess the application byhttp://<public-ip>:8888/lab?token=d337b5ee0b72c6687b9a9e8f8f9a2f5972559454e90c6e10Use--helpoption to more detailsRequirementsThe following packages are needed on the Operating System to run this application:python3.7pipdockernfs-common# setup on Ubuntu linuxsudoaptinstall-ypython3python3-pippython3-setuptoolsdocker.ionfs-commonMounting an NFS File System to ECSs (Linux)
Package: doradetector
Doraemon DetectorPython package to detect when ETB emits DoraemonFree software: GNU General Public License v3Documentation:https://doradetector.readthedocs.io.FeaturesTODOUsageHow to use this module::>>> from doradetector import doradetector
>>> results = doradetector.doradetector('2022-01-06')
>>> results
[{'channel': 'ETB-1',
'date': '2022-01-06',
'hour': ' 07:05',
'title': '\r\n'
        '\t\t\t\t\t\r\n'
        '\t  \t\tDoraemon\t\t\t\t\t\t\t\t\t\t - Gorputzak trukatuta '},
{'channel': 'ETB-3',
'date': '2022-01-06',
'hour': ' 07:00',
'title': '\r\n'
        '\t\t\t\t\t\r\n'
        '\t  \t\tDoraemon\t\t\t\t\t\t\t\t\t\t - Gorputzak trukatuta '},
{'channel': 'ETB-3',
'date': '2022-01-06',
'hour': ' 21:40',
'title': '\r\n'
        '\t\t\t\t\t\t\t\r\n'
        '\t  \t\tDoraemon\t\t\t\t\t - Nobitaren energia '},
{'channel': 'ETB-3',
'date': '2022-01-06',
'hour': ' 22:05',
'title': '\r\n'
        '\t\t\t\t\t\t\t\r\n'
        '\t  \t\tDoraemon\t\t\t\t\t - Giza lokomotora '},
{'channel': 'ETB-3',
'date': '2022-01-06',
'hour': ' 22:30',
'title': '\r\n\t\t\t\t\t\t\t\r\n\t  \t\tDoraemon\t\t\t\t\t - Halloween '}]CreditsThis package was created withCookiecutterand theaudreyr/cookiecutter-pypackageproject template.History1.0.1 (2022-01-06)Fix README1.0.0 (2022-01-06)First release on PyPI.
Package: dorado-sensitivity
Dorado sensitivity and exposure time calculatorDorado is a proposed space mission for ultraviolet follow-up of gravitational
wave events. This repository contains a simple sensitivity and exposure time
calculator for Dorado.This package can estimate the signal to noise, exposure time, or limiting
magnitude for an astronomical source with a given spectrum using theCCD
signal to noise equation. It models the following noise contributions:Zodiacal lightAirglow (geocoronal emission)Standard CCD noise (shot noise, read noise, dark current)InstallationTo install withPip:$ pip install dorado-sensitivityExamplesFor examples, see theJupyter notebook.DependenciesAstropySynphotfor combining bandpasses and source spectraPyYAMLfor readingECSVdata files
Package: doraemon-hub
# Welcome to Robot Framework HubThis is a very early version of a server for the robot frameworktesting framework. The hub uses flask to provide both a RESTfulinterface and a browser-based UI for accessing test assets.It's crazy easy to get started. To install and run from a PyPipackage, do the following:```$ pip install robotframework-hub$ python -m rfhub```To run from source it's the same, except intead of installing,you cd to the folder that has this file.That's it! You can now browse documentation by visiting the urlhttp://localhost:7070/doc/Want to browse your local robotframework assets? Just includethe path to your test suites or resource files on the commandline:```$ python -m rfhub /path/to/test/suite```## WebsitesSource code, screenshots, and additional documentation can be found here:* Source code: https://github.com/boakley/robotframework-hub* Project wiki: https://github.com/boakley/robotframework-hub/wiki## AcknowledgementsA huge thank-you to Echo Global Logistics (echo.com) for supportingthe development of this package.
Package: dora-explorer
Dora the ExplorerAs the name suggests everything, this package is intended for exploring the earth. Imagine you have a set of places (at max 4 places) to vist, how do you know exactly to find the best route to cover all the places? This package helps to find the best route which is pre-planned and displays the route with respect to distance and finally reaching the source place i.e., home.We have known about one of the famous problems in mathematics - graph theory that isTravelling Salesman Problem. To give a simple gist about the problem, basically there is a salesman who has to travel a bunch of places (cities) to deliver the items. There could be so many possibilities to cover all the cities and reach to his/her source place. But it is very important for a salesman to choose the best possible route which gives a minimal distance. By this he/she can save a lot time and deliver the items at the earliest. For this project, I have considered distance as an important factor, later on time and other factors shall be added.A typical example can be seen below. When selected 4 places that belong to India the result is obtained having the shortest path to cover the places. The path is just a straight line between the cities.What if we want to get the actual route direction from each city that is joining another city?.For getting the map results, it is important to have Mapbox API which is a free API. To get the API - register onmapbox website. Once registered, create a secret token by clickingCreate a tokenbutton by navigating to thispage. Save the token as it will be needed for generating the map results.Installationpip install dora-explorer --userImplementationfromdora_explorer.distance_locatorimportDistanceLocatordl=DistanceLocator()from_='Hindupur'to_='Bengaluru'distance=dl.get_distance(from_=from_,to_=to_)print(distance)# 95.84fromdora_explorer.tiny_exploreimportDoraTheExplorerplace_list=['Delhi','Hyderabad','Hindupur','Mumbai']explore=DoraTheExplorer(place_list=place_list)min_dis=explore.get_min_dis(source_city='Mumbai')print(min_dis)# 3583.36geo_token=<MapboxAPIToken>path=explore.get_path(source_city='Mumbai',with_map=True,with_directions=True,geo_token=geo_token)print(path)# Mumbai >> Delhi >> Hyderabad >> Hindupur >> MumbaiNote:Thesource_cityparam can also be given an integer. Either1or2or3or4as in a list of four places is passed.fromdora_explorer.tiny_exploreimportDoraTheExplorerplace_list=['Delhi','Hyderabad','Hindupur','Mumbai']explore=DoraTheExplorer(place_list=place_list)path=explore.get_path(source_city=1,num_path=True)print(path)# 1 >> 2 >> 3 >> 4 >> 1
Package: dora-lakehouse
Dora LakehouseDora's lakehouse software development kitGetting StartedYou can install the library using pip:pipinstalldora-lakehouseGetting HelpWe useGitHubissuesfor trackingbugs,questionsandfeature requests.ContributingWe value feedback and contributions from our community. Please read through thisCONTRIBUTINGdocument before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your contribution.Dora Projectis a recent open-source project based on technology developed atCompasso UOL
Package: dora-lakehouse-aws
Dora ProjectWelcome to Dora community :blue_heart:The primary purpose of this community is to collaborate on projects focused on data and analytics. We want people to work better together. This is a community we build together, and we need your help to make it the best it can be.Before start remember that contributions to this repository should follow itscontributing guidelinesandcode of conduct.Open SourceWhant to learn more aboutOpen Sourceprojects?The links below may be helpfull:https://opensource.guide/https://todogroup.org/guides/https://guides.github.com/https://choosealicense.com/licenses/https://www.contributor-covenant.org/https://mozillascience.github.io/working-open-workshop/Dora Projectis a recent open-source project based on technology developed atCompasso UOL
Package: dora-lakehouse-sdk
Dora Lakehouse SDKDora's lakehouse software development kitGetting StartedYou can install the library using pip:pipinstalldora-lakehouse-sdkGetting HelpWe useGitHubissuesfor trackingbugs,questionsandfeature requests.ContributingWe value feedback and contributions from our community. Please read through thisCONTRIBUTINGdocument before submitting any issues or pull requests to ensure we have all the necessary information to effectively respond to your contribution.Dora Projectis a recent open-source project based on technology developed atCompasso UOL
Package: dora-ms
[![Buid Status][build]][travis] [![Code Coverage][cov]][codecov] [![Documentation Status][doc]][readthedocs] [![License Information][license]][mit][build]: https://travis-ci.org/caianrais/dora.svg?branch=master[cov]: https://codecov.io/gh/caianrais/dora/branch/master/graph/badge.svg[doc]: https://readthedocs.org/projects/dora/badge/?version=latest[license]: https://img.shields.io/github/license/caianrais/dora.svg[travis]: https://travis-ci.org/caianrais/dora[codecov]: https://codecov.io/gh/caianrais/dora[readthedocs]: https://dora.readthedocs.io[mit]: https://github.com/caianrais/dora/blob/master/LICENSE# DORA: DNS Over REST API`DORA` is a microservice that provides a simple API for DNS querying through aREST architecture. It aims to be a consumable API that's easy to digest andeasy to deploy on cloud-based solutions, such as [AWS Lambda][lambda], [GCPCloud Functions][gcp-cloud-func], [GCP AppEngine][gcp-app-engine],[Heroku][heroku] and so on.<p align="center"><img src="docs/_static/example.png"></p>[lambda]: https://aws.amazon.com/lambda/[gcp-cloud-func]: https://cloud.google.com/functions/[gcp-app-engine]: https://cloud.google.com/appengine/[heroku]: https://www.heroku.com/## Features`DORA` mainly relies on the [`dnspython`][dnspython] toolkit. It can query thefollowing records:- `A`: IPv4 address;- `AAAA`: IPv6 address;- `CNAME`: Canonical name (name alias);- `MX`: Mail exchange (mail transfer agent name);- `NS`: Authoritative name server;- `TXT`: Text records.[dnspython]: https://github.com/rthalley/dnspython## DocumentationFor instructions of usage, installation, deployment and overall documentationof the code, [read the docs](http://dora.rtfd.io).## TODO- [ ] Finish the user documentation;- [ ] Create code documentation;- [ ] 100% covered (*write tests*);- [ ] Publish DORA on PyPI;- [X] Dockerized DORA;- [ ] Guide: Deploying DORA on Heroku;- [ ] Guide: Deploying DORA on AWS Lambda;- [ ] Guide: Deploying DORA on Google App Engine;- [ ] Guide: Deploying DORA on Google Cloud Functions;
Package: dorasl
# Dora Serverless PyA Python module in order to deploy your experiment on Dora cluster
from your code!Requires dora.cli installed on your PC## Buildpip install twine
python3 setup.py sdist bdist_wheel## Checktwine check dist/*## Upload testtwine upload --repository-urlhttps://test.pypi.org/legacy/dist/*## Install testpip install -ihttps://test.pypi.org/simple/dora-serverless==0.1.1Upload prodtwine upload dist/*
Package: dore
8 888888888o.           ,o888888o.      8 888888888o.    8 888888888888
8 8888    `^888.     . 8888     `88.    8 8888    `88.   8 8888
8 8888        `88.  ,8 8888       `8b   8 8888     `88   8 8888
8 8888         `88  88 8888        `8b  8 8888     ,88   8 8888
8 8888          88  88 8888         88  8 8888.   ,88'   8 888888888888
8 8888          88  88 8888         88  8 888888888P'    8 8888
8 8888         ,88  88 8888        ,8P  8 8888`8b        8 8888
8 8888        ,88'  `8 8888       ,8P   8 8888 `8b.      8 8888
8 8888    ,o88P'     ` 8888     ,88'    8 8888   `8b.    8 8888
8 888888888P'           `8888888P'      8 8888     `88.  8 888888888888


                   SCHEMA BASED FAKE DATA GENERATORHelpful LinksProject SiteGitHubInstallationInstall Dore$pipinstalldoreUsageCreate aManifestwhich defines requirements for the target
data, and Invoke Dore with the Manifest:$dore--manifestMANIFEST_FILE[OPTIONS]Please referCLI Referencefor details on thedorecommand
usage.Also, do check out ourTutorialto learn how to create a Manifest
for
an ecommerce schema and use Dore to generate data for it.