☄️TIME TON - TIME CITY!
🏙️ TimeCity opens its doors!
📆 On February 19, a new digital era begins. The TimeTON community will gain access to the metaverse for the first time, where each object is your future digital asset that generates income and resources.
🗣️ A collection of 5,728 NFTs is the basis of a virtual city that will grow, develop and form a full-fledged digital ecosystem.
🏘 Residential complexes are being built here, where the first residents will settle, business centers and manufacturing enterprises are opening, which will become the heart of the economy. Trading platforms and entertainment areas appear, creating the rhythm of city life. Digital advertising screens light up on the streets, where location owners receive a share of the global advertising market.
👨🏻💻 Every user of our community will have access to the first version of the metaverse to watch the construction of the city in real time, explore the first districts and become part of a closed community of NFT owners, where the most valuable opportunities are revealed.
💥 There is very little left…
🔖If you decide to buy NFT - be careful, think twice, you don’t know how it will turn out.#dyor
➡️START GAME
🐱🐱🐱🐱🐱🐱🐱🐱
👉🏻SUBSCRIBE!
https://docs.python.org/2/library/multiprocessing.html
#multiprocessing is a package that supports spawning processes using an #API similar to the #threading module. The multiprocessing package offers both local and remote #concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of #threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows.
https://docs.python.org/3/library/multiprocessing.html
multiprocessing is a package that supports spawning processes using an API similar to the threading module. The multiprocessing package offers both local and remote concurrency, effectively side-stepping the Global Interpreter Lock by using subprocesses instead of threads. Due to this, the multiprocessing module allows the programmer to fully leverage multiple processors on a given machine. It runs on both Unix and Windows.
The #multiprocessing module also introduces #APIs which do not have analogs in the #threading#module. A prime example of this is the Pool object which offers a convenient means of parallelizing the execution of a function across multiple input values, distributing the input data across processes (data #parallelism). The following example demonstrates the common practice of defining such functions in a module so that child processes can successfully import that module. This basic example of data parallelism using Pool,
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".