Intro

So you are writing some CPU-intensive code in Python and really trying to find ways out of its single-threaded prison. You might be looking towards Numba's "nopython parallel" mode, you might be using forked processes with multiprocessing, you might be writing microservices with database-like coordinators, or even writing your own multithreaded programs in C/C++ just like creators of TensorFlow did.

In this article I'm describing a rationale for my pet project where I try to implement facilities for general purpose multitasking to be used in a form of simple python code, employing a database-like approach for interpreters communication, while keeping the GIL (Global Interpreter Lock) and trying to be as pythonic as possible.

It could also become handy in the light of upcoming multiple interpreters support in CPython.

As far as I know, nobody came that far in trying to provide Python program with native shareable storage. The last closest attempt was Python Object Sharing which is pretty much dead by now. I hope my project won't meet the same fate.

During the COVID 19 pandemic, majorly single people are getting bored the most by sitting at home and just doing work from home; that's why they are searching for the alternatives to be busy and entertained.

This is the main reason why dating apps like tinder usage is increasing day by day. 

Data

Blockchain is a decentralized technology that maintains a record of all transactions occurring over a peer-to-peer network. Due to Blockchain's several different high-level use cases, numerous industries described Blockchain as the 'magic beans.' 

Blockchains store the record in a decentralized system that is interconnected. This technology lessens vulnerability and enhances transparency in all industrial sectors as information is stored digitally, and it does not have any centralized point to carry out the transactions.

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Introduction

In this digital world, people prefer to work remotely. There are numerous tasks that each of us goes through every day. If I talk about an application's usage, then it has been predicted that there will be a 25% increase in global app downloads between 2018 and 2022. 

But it can be quite challenging for organizations to maintain and create multiple passwords. Hence, a password management software can be a great choice to manage this effectively. It is like your bank locker, where one can store numerous passwords. The users only need a master password to access the software.

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The Big Data Tools plugin seamlessly integrates HDFS into your IDE and provides access to different cloud storage systems (AWS S3, Minio, Linode, Digital Open Space, GS, Azure). But is this the end? Have we implemented everything and now progress has stopped? Of course not.

In this short digest, we'll take a look at 15 popular distributed file systems available on the market and try to get a sense of their individual advantages.

Almost all of these systems are free or open-source, and you can find the sources on GitHub. The sites of these projects, their documentation, and online reviews provide most of the information we’ll consider here. Other than HDFS, none of these technologies have been implemented yet in Big Data Tools. But who knows? Perhaps someday we'll see them in our plugin.

Introduction

Each game has data that game-designers work with. In RPG there is a database of items, in match-3 — the cost in the crystals of tools from the store, in action — hit points, for which medical kit heals.

There are many ways to store such data — someone stores it in tables, in XML or JSON files that edit with their own tools. Unity provides its own way — Scriptable Objects (SO), which I like because you don't have to write your own editor to visualize them, it's easy to make links to the game's assets and to each other, and with Addressables this data can be easily and conveniently stored off-game and updated separately.

In this article I would like to talk about my SODatabase library, with which you can conveniently create, edit and use in the game (edit and serialize) scriptable objects.

EAP 11 of the Big Data Tools plugin for IntelliJ IDEA Ultimate, PyCharm, and DataGrip is available starting today. You can install it from the JetBrains Plugin Repository or inside your IDE.

Big Data Tools is a new JetBrains plugin that allows you to connect to Hadoop and Spark clusters and monitor nodes, applications, and jobs. It also brings support for editing and running Zeppelin notebooks inside IntelliJ IDEA and DataGrip, so you can create, edit, and run Zeppelin notebooks without ever having to leave your favorite IDE. The plugin offers smart navigation, code completion, inspections, quick-fixes, and refactoring inside notebooks.