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#TASKS#ADD https://testflight.apple.com/join/Qkj2VkAs

How the deal will be conducted in BLC Market We continue to showcase the interface of the upcoming BLC Market app. Today — how the deal between the client and the contractor will take place. When the client selects a contractor, a deal is created within the platform. The process looks like this: • the client creates a deal • funds are blocked within the platform • the contractor performs the work • after confirmation, the result is transferred to the client • funds are transferred to the contractor Such a system allows to protect both parties of the deal and reduce the risk of fraud. All calculations within the platform will be conducted using BLC without commission, or with the token chosen by the user, for a commission - which will go to the BLC liquidity pool. In the following posts we will show: • how the arbitration system works • what happens if a dispute arises • how users can protect their interests Early access to interface testing is granted to Pioneers participants. #tasks#freelance#deals

How the task search will work in BLC Market We continue to demonstrate the interface of the future BLC Market application. Today - how users will be able to find tasks and performers. The application will have a convenient search, where you can: • view available tasks • filter by categories • search by keywords • choose tasks by budget Each task will have a card with a description, price, and completion time. Performers will be able to quickly find suitable tasks and send their proposals to customers. This creates a full-fledged service market where customers and performers can interact directly. In the following posts, we will show: • how a deal is made within the platform • how deal protection works • how crypto-arbitrage will be arranged Early access to interface testing is given to Pioneers participants. #tasks#freelance#deals FAQ | BUY

How task creation will work in BLC Market We continue to showcase the interface of the future BLC Market app. Today - one of the key elements of the platform: task creation. A user will be able to post a task in just a few steps: • choose a category • describe the task • add photo or video - if needed • set the price, choosing the coin for payment • publish the task After publication, the task becomes available to performers who can offer their services. All transactions will take place within the platform using BLC. In the following posts, we will show: • what the performer's profile will look like • how arbitration will occur through the Association of Arbitration Courts • how the transaction system works Early access to the interface testing is given to Pioneers participants. #Tasks#BLC_Market#functionality FAQ | BUY

https://help.ubuntu.com/community/CronHowto #Cron is a system daemon used to #execute desired #tasks (in the background) at designated times. A crontab file is a simple text file containing a list of commands meant to be run at specified times. It is edited using the crontab command. The commands in the crontab file (and their run times) are checked by the cron daemon, which executes them in the system background.

How interaction will work in BLC Market The main idea is to eliminate unnecessary intermediaries. User: - creates a task - receives responses - chooses a contractor Everything happens within one interface. We make the mechanics as simple as possible to lower the entry barrier. #freelance#tasks#BulCoin#BLC#TON FAQ | BUY

#Pinwork#To#Do#List#amp#Tasks Join the Pinwork - To-Do List & Tasks beta on ✈️#TestFlight 🔗 Link: https://testflight.apple.com/join/aWxfGbtt Shared by Dimitri

Asynchronous #celery celeryproject.org Distributed task queue. #flower pypi.python.org/pypi/flower Tool for monitoring and management of Celery tasks. #django-channels pypi.python.org/pypi/django-channels Official Django websockets interface, can also be used as task queue. #rq pypi.python.org/pypi/rq RQ is a simple, lightweight, library for creating background jobs, and processing them. #django-rq pypi.python.org/pypi/django-rq A simple app that provides django integration for RQ (Redis Queue). #django-background-#tasks github.com/arteria/django-background-tasks Database backed asynchronous task queue.

http://www.aparat.com/v/4nbc9 This talk gives a quick overview of Python's capabilities as a #data_processing and #machine_learning tool through practical examples: gathering data from the web or a local file, validating/modifying it and finally analyzing it to build models for #classification and #prediction#tasks.

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

http://masnun.com/2015/11/20/python-asyncio-future-task-and-the-event-loop.html On any platform, when we want to do something #asynchronously, it usually involves an #event loop. An event loop is a loop that can register #tasks to be executed, execute them, delay or even cancel them and handle different events related to these operations. Generally, we #schedule multiple async functions to the event loop. The loop runs one function, while that function waits for #IO, it pauses it and runs another. When the first function completes IO, it is resumed. Thus two or more functions can #co_operatively run together. This the main goal of an event loop.

https://github.com/python/asyncio The #asyncio#module provides infrastructure for writing #single-threaded concurrent code using #coroutines, #multiplexing#I/O access over sockets and other resources, running network clients and servers, and other related primitives. Here is a more detailed list of the package contents: a pluggable event loop with various system-specific implementations; transport and protocol abstractions (similar to those in Twisted); concrete support for TCP, UDP, SSL, subprocess pipes, delayed calls, and others (some may be system-dependent); a Future class that mimics the one in the concurrent.futures module, but adapted for use with the event loop; #coroutines and #tasks based on yield from (PEP 380), to help write concurrent code in a sequential fashion; cancellation support for Futures and coroutines; synchronization primitives for use between coroutines in a single thread, mimicking those in the #threading module; an interface for passing work off to a threadpool, for times when you absolutely, positively have to use a library that makes blocking I/O calls. Note: The implementation of asyncio was previously called "Tulip".