Does "DevOps" still mean anything? Multiplayer. Today we're announcing the most-significant evolution of our platform — something we've been building towards for a long time that we're thrilled to share with you. Introducing Multiplayer: code with friends in the same editor, execute programs in the same interpreter, interact with the same terminal, chat in the IDE, edit files and share the same system resources, and ship applications from the same interface! We've redesigned every part of our infrastructure to work in multiplayer mode -- from the filesystem to the interpreter. This works with all the languages that work on Repl.it. All free and ready for you to use right now. All you have to do is login, create a repl, start a Multiplayer session, give a link to your friends, wait for them to join, and start hacking!
We started beta-testing Multiplayer last month. Help Last week user @marc_rosenberg hopped on our Discord server and asked for help with his Advent of Code work. Interviews Teaching Collaborations Conclusion. Take a swim at your Linux terminal with asciiquarium. We're now nearing the end of our 24-day-long Linux command-line toys advent calendar. Just one week left after today! If this is your first visit to the series, you might be asking yourself what a command-line toy even is. We’re figuring that out as we go, but generally, it could be a game, or any simple diversion that helps you have fun at the terminal.
Some of you will have seen various selections from our calendar before, but we hope there’s at least one new thing for everyone. Today's selection is a fishy one. . $ sudo dnf install asciiquarium If you're running a different distribution, chances are it's packaged for you too. Visit the asciiquarium homepage for more information or to download the Perl source code. Do you have a favorite command-line toy that you think I ought to profile? Be sure to check out yesterday's toy, Schedule a visit with the Emacs psychiatrist, and come back tomorrow for another! Kata Enterprise Edition - The speed of containers, the security of VMs. Abishekvashok/cmatrix: Terminal based "The Matrix" like implementation. Getting started with Prometheus.
Prometheus is an open source monitoring and alerting system that directly scrapes metrics from agents running on the target hosts and stores the collected samples centrally on its server. Metrics can also be pushed using plugins like collectd_exporter—although this is not Promethius' default behavior, it may be useful in some environments where hosts are behind a firewall or prohibited from opening ports by security policy. Prometheus, a project of the Cloud Native Computing Foundation, scales up using a federation model, which enables one Prometheus server to scrape another Prometheus server. This allows creation of a hierarchical topology, where a central system or higher-level Prometheus server can scrape aggregated data already collected from subordinate instances.
Besides the Prometheus server, its most common components are its Alertmanager and its exporters. Alerting rules can be created within Prometheus and configured to send custom alerts to Alertmanager. Installing Prometheus. 9 flowchart and diagramming tools for Linux. 5 tips to improve productivity with zsh. It would be impossible to cover all the options of zsh here; there are literally hundreds of pages documenting its many features. In this article, I'll present five tips to make you more productive using the command line with zsh. 1. Themes and plugins Through the years, the open source community has developed countless themes and plugins for zsh.
A theme is a predefined prompt configuration, while a plugin is a set of useful aliases and functions that make it easier to use a specific command or programming language. The quickest way to get started using themes and plugins is to use a zsh configuration framework. A theme makes you more productive as it adds useful information to your prompt, such as the status of your Git repository or Python virtualenv in use.
It reached version 1.0 in February 2017, and has continued rapid development, with 21,000+ commits thus far, many from outside contributors. This article introduces TensorFlow, its open source community and ecosystem, and highlights some interesting TensorFlow open sourced models. TensorFlow is cross-platform. It runs on nearly everything: GPUs and CPUs—including mobile and embedded platforms—and even tensor processing units (TPUs), which are specialized hardware to do tensor math on. On top of that sit the Python and C++ frontends (with more to come).
TensorFlow execution model Graphs Eager execution Why is this important? TensorBoard. Getting started with Tmux | Linuxize. This guide will go through the installation and basic usage of Tmux to get you up and running. What is tmux? Tmux is a terminal multiplexer an alternative to GNU Screen. In other words, it means that you can start a Tmux session and then open multiple windows inside that session.
Each window occupies the entire screen and can be splitted into rectangular panes. With Tmux you can easily switch between multiple programs in one terminal, detach them and reattach them to a different terminal. Tmux sessions are persistent which means that programs running in Tmux will continue to run even if you get disconnected. All commands in Tmux start with a prefix, which by default is ctrl+b. Installing Tmux You can easily install Tmux using the package manager of your distro.
Installing Tmux on Ubuntu and Debian Installing Tmux on CentOS and Fedora Installing Tmux on macOS Starting Your First Tmux Session To start your first Tmux session, simply type tmux in your console: You can now run your first Tmux command. PyQt5 tutorial 2018: Create a GUI with Python and Qt. This PyQt5 tutorial shows how to use Python 3 and Qt to create a GUI on Windows, Mac or Linux. It even covers creating an installer for your app.
What is PyQt5? PyQt is a library that lets you use the Qt GUI framework from Python. Qt itself is written in C++. PyQt5 refers to the most recent version 5 of Qt. An interesting new competitor to PyQt is Qt for Python. Install PyQt The best way to manage dependencies in Python is via a virtual environment. To create a virtual environment in the current directory, execute the following command: python3 -m venv venv This creates the venv/ folder. Call venv/scripts/activate.bat On Mac and Linux, use: source venv/bin/activate You can see that the virtual environment is active by the (venv) prefix in your shell: To now install PyQt, issue the following command: pip install PyQt5==5.9.2 The reason why we're using version 5.9.2 is that not all (Py)Qt releases are equally stable.
Create a GUI Time to write our very first GUI app! App = QApplication() Widgets. Kite - The smart copilot for programmers. What is Tailwind? - Tailwind CSS. A utility-first CSS framework for rapidly building custom user interfaces. Tailwind is different from frameworks like Bootstrap, Foundation, or Bulma in that it's not a UI kit. It doesn't have a default theme, and there are no built-in UI components. On the flip side, it also has no opinion about how your site should look and doesn't impose design decisions that you have to fight to undo. If you're looking for a framework that comes with a menu of predesigned widgets to build your site with, Tailwind might not be the right framework for you. But if you want a huge head start implementing a custom design with its own identity, Tailwind might be just what you're looking for.
Utility-first Creating a framework for building custom UIs means you can't provide abstractions at the usual level of buttons, forms, cards, navbars, etc. Here's an example of a responsive contact card component built with Tailwind without writing a single line of CSS: Adam Wathan Developer at NothingWorks Inc. Put Your IDE in a Container with Guacamole – Red Hat OpenShift Blog. Put Your IDE in a Container Apache Guacamole is an incubating Apache project that enables X window applications to be exposed via HTML5 and accessed via a browser. This article shows how Guacamole can be run inside containers in an OpenShift Container Platform (OCP) cluster to enable Red Hat JBoss Developer Studio, the eclipse-based IDE for the JBoss middleware portfolio, to be accessed via a web browser.
You’re probably thinking “Wait a minute… X windows applications in a container?” Yes, this is entirely possible and this post will show you how. Bear in mind that tools from organizations like CODENVY can provide a truly cloud-ready IDE. How does Apache Guacamole work? Apache Guacamole consists of two main components, the Guacamole web application (known as the guacamole-client) and the Guacamole daemon (or guacd). Log in to OpenShift Container Platform This was tested on a cloud-based OpenShift installation as well as a laptop using the Red Hat Container Development Kit. Oc get pods Tags. Quiet log noise with Python and machine learning.
Continuous integration (CI) jobs can generate massive volumes of data. When a job fails, figuring out what went wrong can be a tedious process that involves investigating logs to discover the root cause—which is often found in a fraction of the total job output. To make it easier to separate the most relevant data from the rest, the Logreduce machine learning model is trained using previous successful job runs to extract anomalies from failed runs' logs.
This principle can also be applied to other use cases, for example, extracting anomalies from Journald or other systemwide regular log files. Using machine learning to reduce noise A typical log file contains many nominal events ("baselines") along with a few exceptions that are relevant to the developer. Baselines may contain random elements such as timestamps or unique identifiers that are difficult to detect and remove. Log events must be converted to numeric values for k-NN regression. Introducing Logreduce Managing baselines. Python Data Analysis Library — pandas: Python Data Analysis Library. The Side Project Marketing Checklist. Britecharts - D3.js based charting library of reusable components. Britecharts is a client-side reusable Charting Library based on D3.js v4 that allows easy and intuitive use of charts and components that can be composed together creating amazing visualizations.
Britecharts components have been written in ES2015 with a Test Driven methodology so they are fully tested, and we are commited to keeping them that way. Key Features The main characteristics of this library are: ReusabilityComposabilityFully testedES2015 source code (transpiled with Babel) Usage The typical use of Britecharts involves creating a chart using its simple API, then rendering it on a container which has previously had data applied to it. BarChart .width(500) .height(300); barContainer.datum(dataset).call(barChart); All the components expose some basic API methods like width, height and margin. Installation Britecharts components are distributed in UMD modules, each one exposing a D3.js component written with the Reusable API pattern.
Npm install britecharts d3-selection Roadmap See Also. Open source dashboard tools for visualizing data. To start with a confession, I like dashboards. A lot. I've always been fascinated by finding new and interesting ways to bring meaning to data with interactive visualization tools. While I'm definitely a geek for numbers, the human mind is simply much better at interpreting trends visually than it is just picking them out a spreadsheet. And even when your main interest in a dataset is the raw numbers themselves, a dashboard can help to bring meaning by highlighting which values matter most, and what the context of those numbers is.
Figuring out how to best visualize your data can be challenging. Maybe you started out by creating a few graphs in a spreadsheet and are trying to find a way to tie them all together. Fortunately, there are a number of great open source dashboard tools out there that make the job much easier. Here's a look at a few open source dashboard tools that you might consider. Freeboard The code for Freeboard can be found on GitHub under an MIT license. Mozaïk Dashbuilder. Transform Data by Example - Microsoft Research. Troubleshooting Problems Q1. ERROR message: “Please select an empty cell inside the data range of the column that you are trying to fill.” This warning message is triggered in two cases: No valid data region was detected for transformations to be performed. There are two ways to select data region in Transform Data by Example: (1) The user can select any empty cell in the column for which output needs to be produced, in such a case a contiguous non-empty region to the left is automatically inferred as the data region (see the first figure below), or (2) The user explicitly selects a region where the last column is used as the output column, in which values are only partially filled (see the second figure below).
No valid data region can be detected if neither condition above is met. Q2. First, please verify that a valid data region is selected. If the data region selected is valid, please check that example values provided in the output column are correct. Q3. Q4. Q5. Q6. Q7. Documentation — VisPy. VisPy is a high-performance interactive 2D/3D data visualization library leveraging the computational power of modern Graphics Processing Units (GPUs) through the OpenGL library to display very large datasets. VisPy is under heavy development at this time, and we are still working on a complete user guide for Vispy.
VisPy targets two primary categories of users: Users knowing OpenGL, or willing to learn OpenGL, who want to create beautiful and fast interactive 2D/3D visualizations in Python as easily as possible. Users in this category can write their own visualizations with vispy.gloo (requires knowing OpenGL/GLSL)Scientists without any knowledge of OpenGL, who are seeking a high-level, high-performance plotting toolkit. Please check out the gallery for inspiration. 10 Minutes to pandas — pandas 0.20.1 documentation. This is a short introduction to pandas, geared mainly for new users. You can see more complex recipes in the Cookbook Customarily, we import as follows: In : import pandas as pd In : import numpy as np In : import matplotlib.pyplot as plt Object Creation See the Data Structure Intro section Creating a Series by passing a list of values, letting pandas create a default integer index: In : s = pd.Series([1,3,5,np.nan,6,8]) In : sOut: 0 1.01 3.02 5.03 NaN4 6.05 8.0dtype: float64 Creating a DataFrame by passing a numpy array, with a datetime index and labeled columns: Creating a DataFrame by passing a dict of objects that can be converted to series-like.
Having specific dtypes In : df2.dtypesOut: A float64B datetime64[ns]C float32D int32E categoryF objectdtype: object If you’re using IPython, tab completion for column names (as well as public attributes) is automatically enabled. In : df2. As you can see, the columns A, B, C, and D are automatically tab completed. Note. Vue.js. Beautiful Soup Documentation — Beautiful Soup 4.4.0 documentation. Teaching Python and more with open educational resources. Open source alternatives to Google Calendar. Qt Creator 4.3.0 released - Qt Blog. GitHub - spiral/guide: Spiral Framework Guide. Data-processing for humans | Python 3.5+ | □ Bonobo. PHP NBA API and MLB Stats: Retrieve statistics from NBA and MLB API - PHP Classes.