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Изходен канал @clockstackwheels · Post #174 · 21.01

Раз я пишу про гаджеты для гиков, то вот ещё один. Как и многие гики, я ленюсь готовить. Но при этом люблю всё мясное. Так что, посмотрев на пример двоих друзей, я купил гриль и делаю на нем мясо без масла. По сути это две ребристые сковородки с быстрым нагревом и таймером, прижатые друг к другу. Комбинация формы поверхностей и температуры позволяет делать мясо быстро, но не сжигать его. Электроника позволяет запускать этот процесс нажатиями двух кнопок: - первым нажатием выбрал тип блюда (эта настройка задаёт температуру и отсечки по времени), устройство начинает греться и сигналит, когда можно выкладывать - положил мясо и вторым нажатием выбрал желаемую степень прожарки, устройство отключится и просигналит, когда готово Всё. Панели можно снять и помыть в посудомойке. Очень рекомендую. Конкретно у меня модель от русского производителя GFGRIL GF-2000, она наилучшим образом подошла по сумме всех нужных мне параметров, но рынок обширен, и предложений масса, на любой вкус. #gadgets

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djangoproject

@djangoproject · Post #268 · 26.02.2017 г., 05:52

https://pawelmhm.github.io/asyncio/python/aiohttp/2016/04/22/asyncio-aiohttp.html 👌Making 1 million requests with python -#aiohttp Apr 22, 2016 - by Paweł Miech - about: #asyncio, aiohttp, #python In this post I’d like to test limits of python aiohttp and check its performance in terms of requests per minute. Everyone knows that asynchronous code performs better when applied to network operations, but it’s still interesting to check this assumption and understand how exactly it is better and why it’s is better. I’m going to check it by trying to make 1 million #requests with aiohttp client. How many requests per minute will aiohttp make? What kind of exceptions and crashes can you expect when you try to make such volume of requests with very primitive scripts? What are main gotchas that you need to think about when trying to make such volume of requests?

djangoproject

@djangoproject · Post #219 · 04.01.2017 г., 22:43

https://www.blog.pythonlibrary.org/2012/06/08/python-101-how-to-submit-a-web-form/ Today we’ll spend some time looking at three different ways to make Python submit a web form. In this case, we will be doing a web search with duckduckgo.com#searching on the term “python” and saving the result as an HTML file. We will use Python’s included #urllib modules and two 3rd party packages: #requests and #mechanize. We have three small scripts to cover, so let’s get cracking!

djangoproject

@djangoproject · Post #536 · 28.12.2017 г., 10:21

http://www.djangocrew.com/blog/how-startstopget-google-compute-instance-python/ In this post we gonna tell you about How to start/stop/get for the #google compute instance with python. Sometimes we don’t want (or need) a compute engine instance running 24hs every day but we need to run #task/s periodically. To solve this we can have an app engine task runing using cron service to start the VM instance. Once the VM has started, it can have a startup script that runs the actual task it was needed for and then stops the machine. #REST#Linux#Windows#requests

djangoproject

@djangoproject · Post #421 · 21.08.2017 г., 10:39

https://alysivji.github.io/flask-part1-generating-html-pages-with-mongoengine-jinja2.html Generating HTML Pages from #MongoDB with #MongoEngine and #Jinja2 (Flask Part 1) Summary Overview of MongoDB Discussion of Object-Relational Mapping (#ORM) Use MongoEngine to get items out of MongoDB Render #HTML pages using Jinja2 Interact with #REST API to send emails with #Requests

djangoproject

@djangoproject · Post #420 · 21.08.2017 г., 10:36

https://alysivji.github.io/mongodb-pipelines-in-scrapy.html #Scraping Websites into #MongoDB using Scrapy #Pipelines Summary Discuss advantages of using Scrapy framework Create #Reddit spider and scrape top posts from list of subreddits Implement Scrapy pipeline to send scraped data into MongoDB Sure, we could hack together a solution using #Requests and #Beautiful_Soup (bs4), but if we ever wanted to add features like following next page links or creating data validation pipelines, we would have to do a lot more work.

djangoproject

@djangoproject · Post #519 · 10.12.2017 г., 18:14

https://blog.wallaroolabs.com/2017/12/stateful-multi-stream-processing-in-python-with-wallaroo/ #Wallaroo is a high-performance, open-source framework for building distributed stateful applications. In an earlier post, we looked at how Wallaroo scales #distributed_state. In this post, we’re going to see how you can use Wallaroo to implement multiple data processing #tasks performed over the same shared #state. We’ll be implementing an application we’ll call “Market Spread” that keeps track of the latest pricing information by stock while simultaneously using that state to determine whether stock order #requests should be rejected. #pipeline

djangoproject

@djangoproject · Post #224 · 07.01.2017 г., 16:53

#AI #automated_testing #automation #asyncio #atexit #button #concurrency #Coroutines #data_mining #dropdownbox #Debian #decorators #django_cms #form #Google #Gym #intelligence #input #lists #machine_learning #map #Metaprogramming #Micro_services #monitoring #Multipart #multi_touch_apps #multiprocessing #Nodes #numerical #OAuth #package #pytest #python #requests #Requests #satellite #scrapy #scikit_learn #SciPy #searching #submit #selectbox #sessions #TensorFlow #text_boxes #text #telegram #Threads #tuples #Universe #urllib #upload