Saravanan666/pypi-org huggingface dataset:
Package: olympipe
OlympipeThis project will make pipelines
easy to use to improve parallel computing using the basic multiprocessing module. This module uses type checking to ensure your data process validity from the start.Basic usageEach pipeline starts from an interator as a source of packets (a list, tuple, or any complex iterator). This pipeline will then be extended by adding basic.task(<function>). The pipeline process join the main process when using the.wait_for_results()or.wait_for_completion()functions.fromolympipeimportPipelinedeftimes_2(x:int)->int:returnx*2p=Pipeline(range(10))p1=p.task(times_2)# Multiply each packet by 2# orp1=p.task(lambdax:x*2)# using a lambda functionres=p1.wait_for_result()print(res)# [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]FilteringYou can choose which packets to.filter(<keep_function>)by passing them a function returning True or False when applied to this packet.fromolympipeimportPipelinep=Pipeline(range(20))p1=p.filter(lambdax:x%2==0)# Keep pair numbersp2=p1.batch(2)# Group in arrays of 2 elementsres=p2.wait_for_result()print(res)# [[0, 2], [4, 6], [8, 10], [12, 14], [16, 18]]In line formalizationYou can chain declarations to have a more readable pipeline.fromolympipeimportPipeline[res]=Pipeline(range(20)).filter(lambdax:x%2==0).batch(2).wait_for_results()print(res)# [[0, 2], [4, 6], [8, 10], [12, 14], [16, 18]]DebuggingInterpolate.debug()function anywhere in the pipe to print packets as they arrive in the pipe.fromolympipeimportPipelinep=Pipeline(range(20))p1=p.filter(lambdax:x%2==0).debug()# Keep pair numbersp2=p1.batch(2).debug()# Group in arrays of 2 elementsp2.wait_for_completion()Real time processing (for sound, video...)Use the.temporal_batch(<seconds_float>)pipe to aggregate packets received at this point each <seconds_float> seconds.importtimefromolympipeimportPipelinedefdelay(x:int)->int:time.sleep(0.1)returnxp=Pipeline(range(20)).task(delay)# Wait 0.1 s for each queue elementp1=p.filter(lambdax:x%2==0)# Keep pair numbersp2=p1.temporal_batch(1.0)# Group in arrays of 2 elements[res]=p2.wait_for_results()print(res)# [[0, 2, 4, 6, 8], [10, 12, 14, 16, 18], []]Using classes in a pipelineYou can add a stateful class instance to a pipeline. The method used will be typecheked as well to ensure data coherence. You just have to use the.class_task(<Class>, <Class.method>, ...)method where Class.method is the actual method you will use to process each packet.item_count=5classStockPile:def__init__(self,mul:int):self.mul=mulself.last=0defpile(self,num:int)->int:out=self.lastself.last=num*self.mulreturnoutp1=Pipeline(range(item_count))p2=p1.class_task(StockPile,StockPile.pile,[3])[res]=p2.wait_for_results()print(res)# [0, 0, 3, 6, 9]This project is still an early version, feedback is very helpful.
Package: olympus-hitc
Copyright (c) [2019]Permission 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.
Description: UNKNOWN
Keywords: pip,olympus,hitc
Platform: any
Package: olympus-photosync
List, download and sync photos and videos from WiFi enabled Olympus cameras.All functionality has been verified to work with the following digital cameras:Olympus E-M10However, cameras that use the same media sharing mechanism should work just
as well. With that mentioned, the list of cameras thatprobablywork is:Olympus E-M1Olympus E-M5Olympus TG-860Olympus TG-5InstallationThe latest stable version of olympus-photosync can be installed from pypi:$pipinstallolympus-photosyncUsageUsage: olympus-photosync [options] <get|list|sync> ...

List, download and sync photos and videos from WiFi enabled Olympus cameras.

Commands:
  get                     download files from camera
  list                    list media on camera
  sync                    pull missing files from camera

General options:
  -h, --help              show this help message and exit
  -v, --version           show version number and exit
  -r, --parsable          no progress bars and no human readable dates and sizes

Camera server options:
  -a, --addr ip|hostname  address of camera server (default: 192.168.0.10)
  -p, --port port         camera server port number (default: 80)
  -b, --baseurl path      url under which media is located (default: /DCIM/100OLYMP)
  -t, --timeout seconds   connection timeout (default: 60)

Download options:
  -d, --destdir           destination directory (default: ./)
  name [name ...]         media files to download (example: PA290940.JPG)

Synchronization options:
  -n, --dryrun            show files that will be synced and exit
  destdir                 directory which to download media files

Filter options:
  --older timefmt|name    select files older than timestamp or filename
  --newer timefmt|name    select files newer than timestamp or filename
  --on timefmt            select media from a specific day

Examples:
  olympus-photosync list --newer 2017-09-17T16:21:00 --older 2017-09-20
  olympus-photosync list --newer 10d --older 12h
  olympus-photosync list --newer PA290930.JPG --older PB070950.JPG
  olympus-photosync list --on today
  olympus-photosync get -d ~/photos P8060697.JPG P7250454.MOV
  olympus-photosync get -d ~/photos "*.jpg"
  olympus-photosync sync ~/photosA cross-platform GUI is provided by theolympus-photosync-guiprogram. At
the moment it can be used to list and download files from supported devices.TodoTest on more cameras.Test on Windows.The GUI needs more work (e.g. add thumbnails, improve usability).Provide a standalone binary for Windows using PyInstaller.Alternativesolympus-photosync: A well-tested command-line application written in Scala.LicenseReleased under the terms of theRevised BSD License.
Package: olympuswifi
Olympus Wifi-Enabled Camera on Linux, macOS and WindowsSome Olympus cameras have wifi capability. Photos can be downloaded from them;
they can also remote control the camera: the live camera picture is
transmitted and they take pictures and modify settings via wifi.This repository provides Python code to connect to a wifi-enabled Olympus
camera, set the camera's date and time, download images, watch the live camera
view in a window, take a picture, change camera settings, and turn off the
camera. In addition, command-line arguments allow to send user-specific commands
to the camera.DocumentationOur documentation is atolympus-wifi.readthedocs.org.UtilitiesInstallationAPI OverviewAPI Reference
Package: olyn
Official Olyn Bindings for Python
A Python library for Olyn’s API.Setup
You can install this package by using the pip tool and installing:$ pip install olynSetting up a Olyn Account
Sign up for Olyn athttps://docs.olyn.com/Using the Olyn API
Documentation for the python bindings can be found alongside Olyn’s other bindings here:https://docs.olyn.com/docshttps://docs.olyn.com/reference/olyn-api-referenceIn the standard documentation (the first link), most of the reference pages will have examples in Stripe’s official bindings (including Python). Just click on the Python tab to get the relevant documentation.In the full API reference for python (the second link), the right half of the page will provide example requests and responses for various API calls.
Package: olypy
olypyolypy is a collection of code related to the epic fantasy strategy
game Olympia, which currently lives in SVN (yuck) athttps://sourceforge.net/projects/olympiag3/olypy supports:Generating a game database for testing the Olympia codeActual end-to-end tests of the Olympia codeGenerating a game database from player turn output to support simulations for playersInstallingInstall python 3.5 or better, using pyenv or your favorite equivalent.Clone the repo.Install dependent python modules, and see if olypy passes tests:python -m pip install -r requirements.txt
make testGenerating the QA databasemake defaultlibRunning Olympia testsYou need a compiled Olympia binary with support for the 'assert'
command.cd sim; python run-tests.pyTests are YAML files. Here's an example:description: test move-related things
lib: defaultlib
aa1 orders: |
 unit 1102  # A2 in Aachen [c18]
   # test movement delays
   claim 10 20
   assert item 10 20 not item 10 21 # exactly 20
   move out # 2 days
   assert day 3 not day 4
   drop 10 1
   move c18
   assert day 4 not day 5This example contains 3 tests.assertis similar towait; it
passes if the wait is 0-time, and fails elsewise. Thefoo not foosyntax
is a way of expressing exact values.
Package: om
# omCollect disk usage, memory and cpu load info on remote boxes without having to install any software - as long as you can SSH into it.## Features- Disk and memory usage- CPU load- Supports email alerts when resources get to a critical state (e.g. nearly full disk, low free memory, high cpu load, etc)## UsageTo collect usage for a host:```shell$ ./om 192.168.0.1```To collect usage for multiple hosts:```shell$ ./om 192.168.0.2,box2```The tool also supports username, password and port if needed:```shell$ ./om root:mypass@mybox:44445```## InstallationNo packages have been released yet. For a development preview, please fetch the code:```shell$ git clone https://github.com/overseer-monitoring/om.git$ cd overseer-mini$ pip install -r requirements.txt$ ./om```## Extra customization (optional)You can tweak the ssh and metrics settings by saving the configs into a json config file.Running against a config file:```shell$ ./om -c <config.json>```### config.json format#### MachinesThe config file is a JSON and informs which machines are to be monitored.```json{"machines": {"my_rails_app": {"host": "125.22.13.12","ssh": {"username": "foo","password": "bar"}}}}```The only required field is ''host''. ''ssh'' is entirely optional if your local agent is already able to use keys to get to the machine.#### MetricsThe "metrics" section allows you to further customize your monitoring. Our current metrics are:- disk_usage- memory_usageFor instance, disk usages are reported as critical when they reach 80% usage. If for a certain box you want to be critical when it reaches 50%, then:```json{"machines": {"my_rails_app": {"host": "125.22.13.12","metrics": {"disk_usage": {"critical": "50%"}}}}}```You can also override the default value globally:```json{"machines": {"my_rails_app": {"host": "125.22.13.12",},"my_postgres": {"host": "postgresbox","disk_usage": {"critical": "60%"}}},"metrics": {"disk_usage": {"critical": "50%"}}}```
Package: omacase
OMACASEan open-source standalone Python package to analyze optical mapping data, withde novorepeat motif detection and analysis capabilitiesLicenseGPL-3.0-or-laterWritten in & forPython 3.8+RequirementsPython 3.8+Docker (only if running inside a Docker container)wkhtmltopdffor PDF printMake sure X11 server has been started for PDF printingInstallationpython3 -m pip install --user omacase(Alternatively) Runninng inside a Docker containerdocker build .docker run {image ID}ORdocker run ccneko/omacase(pending registrations)Getting StartedBelow are some simple instructions to help you start using OMACASEImporting the package in Pythonimport omacaseReading BNX / CMAP input in custom Python scriptyour_bnx = opmap.BNX(your_bnx_path)your_cmap = opmap.CMAP(your_cmap_path)PublicationChung CYL, Chan TF. OMACASE: Optical Mapping Quality Control and Repeat Detection Software. (Manuscript in preparation)
Package: omada-api
Omada APIA simple Python wrapper for theTP-Link Omada Software ControllerAPI.ResourcesHere are some links which may be helpful when using or extending this library:Omada SDN Controller V5.9.9 API DocumentOmada SDN Controller V5.4.6 API DocumentOmada SDN Controller V5.0.15 API DocumentOmada SDN Controller V4.1.5 API DocumentRequirements of Establishing an External Portal Server (> 5.0.15)Requirements of Establishing an External Portal Server (> 4.1.5)Requirements of Establishing an External Portal Server (> 2.6.0)Requirements of Establishing an External Portal Server (< 2.5.4)UsageCurrently this is just the bare-minimum required to log in, get site settings, push site settings, and log out.from omada import Omada

# load our local config file
omada = Omada('omada.cfg')

# or specify the baseurl and site name directly
#omada = Omada(baseurl='https://...', site='Office')

# log into the controller (username and password are in omada.cfg)
omada.login()

# or specify the username and password directly
# omada.login(username='apiuser', password='secretpassword')

# get the site settings
settings = omada.getSiteSettings()

# turn the LEDs off
settings['led']['enable'] = False

# push the settings back
omada.setSiteSettings(settings)

# log out of the controller
omada.logout()Examplesled.pyI use this in a cron schedule to turn my site LED setting off at night and back on in the morning.Turn the LED on:$ python led.py on
led: onTurn the LED off:$ python led.py off
led: offclients.py,devices.pyThese are simple apps to display similar output to the "Clients" and "Devices" page on the web interface.$ python clients.py
USERNAME            IP ADDRESS      STATUS
00-11-22-33-44-55   192.168.1.123   CONNECTED
...Make sure you have yourSettingsfile configured correctly for these to work.SettingsYou can store your controller settings in a configuration file to avoid hard-coding them in your scripts.Currently supported settings:baseurl- the base url to the controllersite- the name of the site in the controller (usuallyDefault)verify- set this toFalseto ignore self-signed certificate errorswarnings- set this toFalseto hide urllib3 warnings whenverify=Falseverbose- set this toTrueto force low-level reqeusts to output debugging infousername- the username to log in aspassword- the password for the userExample[omada]
baseurl = https://omadacontroller.local:8043
site = Default
verify = False
username = apiuser
password = secretpasswordAcknowledgementsFor my wife, who asked that I turn off the device LEDs at night. :heart:
Package: omada-nagios
This project aims to make managing large-scale Nagios installation(s) simplier.Seethe wiki pagefor more information.FeaturesImplementedNagios PrimativesBaseCheckCommand- check command primativeSumoLogic Check CommandsCollectorLastMessageCheckCommand- check command which reports last message time for a SumoLogic collectorTentativeContributingPlease read the below before getting started. It is preferrable to fork this repository and make pull requests in order to merge new features or bug fixes.Set Up WorkspaceSetup avirtualenvwithin the repository:virtualenv .Install the package:pip install -e .[dev,test]Run the test suite to verify the workspace setup:python -m pytest -v test/Issue TrackerAll issues for this project (feature request, bug report, etc.) should be made in the Github issues tracker.Package mantainers will create stories inPivotalTrackerto address these issues and track progress. There is no public access to this tracker project. To get read access, send an email toplatform@omadahealth.com.Get HelpSlack:https://omada.slack.com/messages/platform/Google Group:https://groups.google.com/a/omadahealth.com/forum/#!forum/platformEmail:platform+nagios@omadahealth.com
Package: omaha
OmahaOmaha aims to provide a unified view of financial metrics of the company.Designed to provide comprehensive data set for the financial analysis.Combining multiple type of financial data consistently.Data is provided in Pandas DataFrame format for the usability.Please visit theofficial documentationfor more detail.Thisis also an blog article useful to see how omaha can be used for financial data analysis.Omaha: Unified view of financial metrics of public companiesNoteIt only supports Japanese company for now.DependenciesBuffett CodeQuandlInstall$ pip install omahaUsagefromomahaimportOmahafactory=Omaha(bc_apikey='XXXXXXX',quandl_apikey='YYYYYYY')# Financial indicators for the ticker symbol 1376company=factory.company('1376','2018Q1','2019Q4')# Daily stock prices for the ticker symbol 1376stockprice=factory.stockprice('1376','2018-01-01','2018-12-31')# Joining multiple indicatorsview=company.join(stockprice)view.df().head()#                             company_name     ceo_name                  headquarters_address        ...   Low         Close#2018-11-30 00:00:00+00:00    カネコ種苗株式会社  代表取締役社長　　金子　昌彦   群馬県前橋市古市町一丁目50番地12 ...  1389.568777  1408.187823#2018-08-31 00:00:00+00:00    カネコ種苗株式会社  代表取締役社長　　金子　昌彦   群馬県前橋市古市町一丁目50番地12 ...  1479.188532  1479.188532If you are unsure the ticker symbol of the company,searchfeature is available. You can get the list of companies matching the given keyword.factory.search("不動産","2019Q1","2019Q4")# [Company(8881, 2019Q1, 2019Q4), Company(8802, 2019Q1, 2019Q4), Company(3465, 2019Q1, 2019Q4),...]DevelopmentYou can develop the package as editable dependencies with Pipenv.$ pipenv install --dev -e .To build the package, runmake package.$ make package
Package: omakase
My choice of missing python functions.list.len()
list.map(function)
list.filter(function)
list.compact()
list.uniq()
list.take(num)
list.drop(num)
list.flatten()
list.each_cons(num)
list.each_slice(num)
list.max()
list.min()
list.sum()
list.zip()
list.first()
list.last()
list.freq(function=None)
list.groupby(function=None)
list.indexby(function=None)
list.join(separator)
list.sortby(function)
list.sorted()
list.reduce(function)
list.reduce(initial, function)
list.percentile(float)
list.percentiles(*float)

tuple.len()
tuple.map(function)
tuple.max()
tuple.min()
tuple.sum()
tuple.zip()
tuple.first()
tuple.last()
tuple.freq(function=None)
tuple.groupby(function=None)
tuple.indexby(function=None)
tuple.join(separator)
tuple.sortby(function)
tuple.sorted()
tuple.reduce(function)
tuple.reduce(initial, function)
tuple.percentile(float)
tuple.percentiles(*float)

dict.len()
dict.compact()Examples$ python
>>> import omakase
>>> array = 'the quick brown fox jumps over the lazy dog'.split()
>>> array.map(len)
[3, 5, 5, 3, 5, 4, 3, 4, 3]
>>> array.filter(lambda each: each > 'hello worlds')
['the', 'quick', 'jumps', 'over', 'the', 'lazy']
>>> array.take(3)
['the', 'quick', 'brown']
>>>InstallationTo install this package, runpip install omakaseContributingBug reports and pull requests are welcome on github at,https://github.com/akuhn/py-omakase
Package: om-api
om_apiУстановка библиотекиУстановка пакета Windowspip install om_apiОбновление пакета Windowspip install --upgrade om_apiИмпорт библиотеки в Python кодеfromom_apiimportom_apiЭто библиотека с набором функций для работы с Optomacros API
В библиотеке есть функции:make_requestDataFrame_to_Listget_propertiesget_listget_parentsget_itemsadd_item_to_listchange_propertiesadd_item_with_propertiesfilter_list_by_propertymake_requestmake_request(request_type: str, url: str, coockie: dict, param: dict = ..., data: dict = ...)request_typeметод запроса, реализованы методыget,posturlадрес к которому мы будем обращаться в формате строки https://***/api/v1/service/{название сервиса}coockie{'token' : "ваш токен"}Времненный токен можно достать нажавf12в браузере и в cookie будет храниться ваш токенparam{'название параметра':'значение параметра'}, параметры, которые мы хотим передать в запросеdata{'':''} данные которые мы передаем с запрсомDataFrame_to_ListDataFrame_to_List(data)Функция преобразования объекта класса DataFrame в список списков
Первый список будет содержать заголовки
Каждый последуйщий список будет содержать значенияget_propertiesget_properties(list_name: str, url: str, cookie: dict)Функция возвращает все свойства справочника спискомget_listget_list(list_name: str, url: str, cookie: dict)Функция возвращает справочник в виде DataFrameget_parentsget_parents(list_name: str, url: str, cookie: dict)Функия возвращает всех парентов в справочнике спискомget_itemsget_items(list_name: str, url: str, cookie: dict, parent: str = ...)Функция возвращает список всех эллементов справочника не являющиеся парентами другим эллементам.parentОпциональный параметр позволяет вывести элементы под определенным парентомadd_item_to_listadd_item_to_list(list_name: str, item_name: str, url: str, cookie: dict, parent: str= ...)Функция позволяет добавлять эллемент в справочник.parentОпциональный параметр позволяет создать эллемент под определенным парентомchange_propertieschange_properties(list_name: str, item_name: str, properties: dict, url: str, cookie: dict, parent: str = ...)Функция позволяет изменить свойства эллемента справочника.add_item_with_propertiesadd_item_with_properties(list_name: str, item_name: str, properties: dict, url: str, cookie: dict, parent: str = ...)Объединение функцийadd_item_to_listиchange_propertiesпозволяет создавать эллемент с заполнением его параметровfilter_list_by_propertyfilter_list_by_property(list_name: str, property_name: str, property_value: str, url: str, cookie: str)Функция фильтрует справочник по одному свойству с заданным значением.
Возвращает DataFrame
Package: omarfass
omaromvmvpppppppppppjdvjvd^pp^djvnjvnsjggdvvmkmvcdmcpythonc++C#python c++ phpphpjvovjfnbNamecodeemailomar10omar@gamli.comAAAAAAAAAAAAgooglepipinstallomarpppldefi():print("fnfngfnj")omar
Package: omar-pkk
# requirements_dev.txt we use for the testing
It makes it easier to install and manage dependencies for development and testing, separate from the dependencies required for production.# difference between requirements_dev.txt and requirements.txtrequirements.txt is used to specify the dependencies required to run the production code of a Python project, while requirements_dev.txt is used to specify the dependencies required for development and testing purposes.# tox.ini
We use if for the testing in the python package testing against different version of the python## how tox works tox enviornment creation
1. Install depedencies and packages
2. Run commands
3. Its a combination of the (virtualenvwrapper and makefile)
4. It creates a .tox# pyproject.toml
it is being used for configuration the python project it is a alternative of the setup.cfg file. its containts configuration related to the build system
such as the build tool used package name version author license and dependencies# setup.cfg
In summary, setup.cfg is used by setuptools to configure the packaging and installation of a Python projec# Testing python applicationtypes of testing1. Automated testing
2. Manual testingMode of testing1. Unit testing
2. Integration testsTesting frameworkspytestunittestrobotframeworkseleniumbehavedoctest# check with the code style formatting and syntax(coding standard)pylintflake8(it is best because it containt 3 library pylint pycodestyle mccabe)pycodestyle
Package: omas
OMAS is a Python library designed to simplify the interface of third-party codes with theITER <http://iter.org>_ Integrated Modeling and Analysis Suite (IMAS <https://confluence.iter.org/display/IMP>_).It provides aconvenient Python APIcapable of storing data withdifferent file/database formatsin a form that isalways compatible with the IMAS data modelMapping the physics codes I/O to the IMAS data model is done in third party Python codes such as theOMFIT framework <https://omfit.io>_.