text:
# LAB-09 Back End

# Project Name

City Explorer backend app

**Authors**: Chaitanya Narukulla, Kush Shrestha, Jhia Turner, David Marchante, Stephen Chu

**Version**: 1.3.0 (increment the patch/fix version number if you make more commits past your first submission)

## Overview
This is a class project to return data with user input. The data to be returned is location info, latitude, longitude, and weather info based on user input.

## Getting Started

### Installation:
From the terminal, run one of the following to make a local copy:
* ssh: `git clone git@github.com:stephenchu530/lab-09-back-end.git`
* https: `git clone https://github.com/stephenchu530/lab-09-back-end.git`

### Usage:
* In the CLI, run: `$ node server.js`
* Or go to: [https://still-caverns-25372.herokuapp.com/](https://still-caverns-25372.herokuapp.com/)

## Architecture
  Node.js, dotenv, cors, express, Heroku

## Change Log

* 04-30-2019 11:00 - Application now has a fully-functional express server, with a GET route for the location resource.
* 04-30-2019 12:00 - Application now has a fully-functional a GET route for the weather resource.
* 04-30-2019 13:00 - Application now has a fully-functional a error handling.
* 05-01-2019 13:00 - Implemented API calls to Google Maps, Darksky, and Eventbrite instead of reading from JSON files
* 05-02-2019 13:00 - Implemented Postgresql for caching of API calls
* 05-03-2019 13:00 - Implement cache validation a new API calls

## Credits and Collaborations
* Chaitanya Narukulla, [chaitanyanarukulla](https://github.com/chaitanyanarukulla)
* Kush Shrestha, [kushshrestha01](https://github.com/kushshrestha01)
* Jhia Turner, [jhimitu](https://github.com/jhimitu)
* David Marchante, [dmarchante](https://github.com/dmarchante)
* Stephen Chu, [stephenchu530](https://github.com/stephenchu530)

## Time Estimation
```
Number and name of feature: Implement Movies API Call

Estimate of time needed to complete: 60mins

Start time: 0915

Finish time: 1045

Actual time needed to complete: 90mins
```
```
Number and name of feature: Implement Yelp API Call

Estimate of time needed to complete: 60min

Start time: 1045

Finish time: 1230

Actual time needed to complete: 105min
```
```
Number and name of feature: Implement Cache Invalidation

Estimate of time needed to complete: 60min

Start time: 12:30

Finish time: 14:05

Actual time needed to complete: 95mins
```
```
Number and name of feature: Implement Trails API Calls

Estimate of time needed to complete: ____

Start time: ____

Finish time: ____

Actual time needed to complete: ____
```

## License:
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/stephenchu530/lab-09-back-end/blob/master/LICENSE)


text:
![Main application screenshot](https://raw.githubusercontent.com/pivotalservices/concourse-pipeline-samples/master/common/images/bg-pipeline-icon.jpg)

# Blue-Green application deployment with Concourse

This is an example of a Concourse pipeline that builds, tests and deploys a **Node.js** sample application using the [Blue-Green deployment methodology](http://docs.cloudfoundry.org/devguide/deploy-apps/blue-green.html).

![Blue-Green application deployment pipeline on Concourse](https://raw.githubusercontent.com/pivotalservices/concourse-pipeline-samples/master/common/images/bg-pipeline-01a.jpg)

The steps automated in the pipeline are as follows:

1. **Retrieve the application's source code from GitHub**
   The pipeline is automatically triggered upon a code update/check-in event in the GitHub repository.

1. **Unit test new version of application code**
   Using the Mocha+Chai frameworks, the pipeline runs the test on the updated Node.js application code.

1. **Deploy new version of application to Cloud Foundry**
   The pipeline automatically determines the current instance of the application in production (i.e. Blue or Green) and deploys the application's new version to Cloud Foundry (e.g. Pivotal Web Services) under the other instance name (e.g. Blue if Green is currently in production, Green otherwise)

1. **Perform load tests**
   The pipeline runs load tests on the newly deployed application instance using the [Artillery framework](https://artillery.io/docs/getting-started/).

1. **Promote new application version to production**
   Using Cloud Foundry's route management capabilities, the pipeline switches the route of your main application URL (e.g. http://main-app-hello.cfapps.io/ ) to point to the new application instance's URL with no downtime for external users.

Each pipeline step is configured to run automatically only if the previous step has been successfully executed.

## Pipeline execution notes

When the pipeline executes successfully all the way to its last step, it creates a **main route/URL** for the application in production using the format: ```main-<your-app-prefix>.<your-app-domain>```.  For example: ```main-myapp.cfapp.io```

That main route/URL will point to either the **blue** instance (e.g. ```blue-myapp.cfapp.io```) or the **green** instance (e.g. ```green-myapp.cfapp.io```) of your application, depending on which instance was the last promoted by the pipeline.

For you to inspect which instance is being used by the main route, simply point your web browser to the main application URL and look at the application ID displayed on the page. The example screenshot below shows the main url pointing to the blue instance of the application.

![Main application screenshot](https://raw.githubusercontent.com/pivotalservices/concourse-pipeline-samples/master/common/images/bgapp-screenshot-b.jpg)

## Pre-requisites to setup this example on your Concourse server

The requirements for this pipeline's setup are as follows:

1. An instance of Concourse installed either as a local vagrant machine or as a remote server.
   Please refer to the documentation on [how to install Concourse](http://concourse-ci.org/installing.html) or to article [Deploying Concourse on Bosh-lite](https://github.com/pivotalservices/concourse-pipeline-samples/tree/master/concourse-on-bosh-lite).

1. The Concourse Fly command line interface is installed on the local VM.
   The Fly cli can be downloaded directly from the link provided on the Concourse web interface.
   Please refer to the [Fly cli documentation](http://concourse-ci.org/fly-cli.html) for details.

## Pipeline setup and execution

How to setup this sample pipeline on your Concourse server:

1. Clone this git repository on your local machine
   __clone https://github.com/pivotalservices/concourse-pipeline-samples.git__
   __cd concourse-pipeline-samples/appdev/blue-green-app-deployment__

1. Setup the pipeline credentials file
  * Make a copy of the sample credentials file
  __cp ci/credentials.yml.sample ci/credentials.yml__

  * Edit _ci/credentials.yml_ and fill out all the required credentials:
_deploy-username:_ the CF CLI userID to deploy apps on the Cloud Foundry deployment
_deploy-password:_ the corresponding password to deploy apps on the Cloud Foundry deployment
_pws-organization:_ the ID of your targeted organization in Cloud Foundry
_pws-space:_ the name of your targeted space in Cloud Foundry (e.g. development)
_pws-api:_ the url of the CF API. (e.g. https://api.run.pivotal.io)
_pws-app-suffix:_ the domain suffix to append to the application hostname (e.g. my-test-app)
_pws-app-domain:_ the domain name used for your CF apps (e.g. cfapps.io)

3. Configure the sample pipeline in Concourse with the following commands:
   __fly -t local login <concourse-url>__
   Example:
   __fly -t local login http://<IP_ADDRESS>:8080__
   __fly -t local set-pipeline -c ci/pipeline.yml -p blue-green-pipeline -l ci/credentials.yml__

4. Access to the Concourse web interface (e.g. http://<IP_ADDRESS>:8080 ), click on the list of pipelines, unpause the _blue-green-pipeline_ and then click on its link to visualize its pipeline diagram.

You will then notice the pipeline's jobs getting executed within a few seconds, one at a time, if the previous job in the pipeline is executed successfully.

---

### Read more

- [Application pipeline deploying to multiple CF spaces](https://github.com/pivotalservices/sample-app-pipeline)

- [PCF Backup CI pipeline using CFOps](https://github.com/pivotalservices/concourse-pipeline-samples/tree/master/pcf-cfops-backup)

- [Deploying Concourse on Bosh-lite](https://github.com/pivotalservices/concourse-pipeline-samples/tree/master/concourse-on-bosh-lite)

- [Deploying Concourse on a Bosh 1.0 Director](https://github.com/pivotalservices/concourse-pipeline-samples/tree/master/concourse-on-bosh-1.0)

- [Concourse pipelines with a local Docker Registry](https://github.com/pivotalservices/concourse-pipeline-samples/tree/master/private-docker-registry)

- [Deploying a Private Docker Registry with Bosh](https://github.com/pivotalservices/concourse-pipeline-samples/tree/master/private-docker-registry/docker-registry-release)

repository: amazted/concourse-pipeline-samples

branch_name: refs/heads/master

extension: md

license_type: permissive

repo_name: amazted/concourse-pipeline-samples


text:
# Real-Time Cyber Threat Detection and Mitigation

# About this Course
This course introduces real-time cyber security techniques and methods in the context of the TCP/IP protocol suites. Explanation of some basic TCP/IP security hacks is used to introduce the need for network security solutions such as stateless and stateful firewalls. Learners will be introduced to the techniques used to design and configure firewall solutions such as packet filters and proxies to protect enterprise assets.

Perimeter solutions such as firewalls and intrusion prevention systems are shown to have significant drawbacks in common enterprise environments. The result of such weakness is shown to often exist as advanced persistent threats (APTs) from nation-state actors. Such attacks, as well as DDOS and third-party attacks, are shown to have potential solutions for modern enterprise.

# Instructor
- Dr. Edward G. Amoroso
- Research Professor, NYU and CEO, TAG Cyber LLC
- Computer Science

# New York University
New York University is a leading global institution for scholarship, teaching, and research. Based in New York City with campuses and sites in 14 additional major cities across the world, NYU embraces diversity among faculty, staff and students to ensure the highest caliber, most inclusive educational experience.

url: https://raw.githubusercontent.com/johnfelipe/Introduction-to-Cyber-Security-Specialization/01cc4b5ece744188370ac66320081014b1d9aecf/Real-Time Cyber Threat Detection and Mitigation/README.md

branch_name: refs/heads/main


text:
# react-native-apple-signin-package

## Getting started

`$ npm install react-native-apple-signin-package --save`

### Mostly automatic installation if you use react native <= 0.59

`pod 'react-native-apple-signin-package', :path => '../node_modules/react-native-apple-signin-package'`

### Need to insatll to finish the installation.
`pod install`

## Usage
```javascript
import { SignInWithAppleBlackButton,
         SignInWithAppleOutlineButton,
         SignInWithAppleWhiteButton
} from 'react-native-apple-signin-package'

// Support three different styles with white, black, and white with outline.
<View style= {{marginBottom:20}}>
    {SignInWithAppleBlackButton({ height: 45, width: 218 },
                                { 'cornerRadius':22.5 },
                                appleSignIn)}
</View>
...

appleSignIn = async (result) => {
  // You can check the return result and use what you want to do with your system.
  console.log('Result',result);
};

license: MIT

repository: EasonLex/RNAppleSigninModule

repo_name: EasonLex/RNAppleSigninModule


text:
# Change Log
All notable changes to this project will be documented in this file.
This project adheres to [Semantic Versioning](http://semver.org/).

**View all [Unreleased][] changes here**

## [2.0.0][] - 2020-04-10
#### Added
-   Added `extension.json`
#### Changed
-   Requring the vendor autoloader in `extension.driver.php`
-   Removed unnecessary includes of core interfaces
-   Removed PHP 5.6.x constraint and added PHP 7.3 or newer requirement to composer.json
-   Using latest version of `icomefromthenet/reverse-regex` and added `pointybeard/symphony-extended` to composer.json
-   Extension driver now Extends `AbstractExtension` from [Symphony CMS: Extended Base Class Library](https://github.com/pointybeard/symphony-extended)

## 1.0.0 - 2018-10-09
#### Added
-   Initial release

[Unreleased]: https://github.com/pointybeard/uuidfield/compare/2.0.0...integration
[2.0.0]: https://github.com/pointybeard/uuidfield/compare/1.0.0...2.0.0


text:
---
layout: post
title: "Data Efficient Voice Cloning for Neural Singing Synthesis"
date: 2019-02-19 21:31:50
categories: arXiv_SD
tags: arXiv_SD Deep_Learning
author: Merlijn Blaauw, Jordi Bonada, Ryunosuke Daido
mathjax: true
---

* content
{:toc}

##### Abstract
There are many use cases in singing synthesis where creating voices from small amounts of data is desirable. In text-to-speech there have been several promising results that apply voice cloning techniques to modern deep learning based models. In this work, we adapt one such technique to the case of singing synthesis. By leveraging data from many speakers to first create a multispeaker model, small amounts of target data can then efficiently adapt the model to new unseen voices. We evaluate the system using listening tests across a number of different use cases, languages and kinds of data.

##### Abstract (translated by Google)

##### URL
[http://arxiv.org/abs/1902.07292](http://arxiv.org/abs/1902.07292)

##### PDF
[http://arxiv.org/pdf/1902.07292](http://arxiv.org/pdf/1902.07292)


text:
**`Under Progress`**

# TREES
A tree is a non-linear data structure, which is a set of nodes, where one node is root of the tree and all the remaining nodes are arranged in a **hierarchical
order** forming sub-tree of the root.

## TYPES OF TREES
**Trees are of 6 types.**

  1. General Trees
  2. Forests
  3. Binary Trees
        1. Complete Binary Trees
        2. Extended Binary Trees
  4. Binary Search Trees
  5. Expression Trees
  6. Tournament Trees

## BASIC TERMINOLOGY

  - **Root Node:**
    The topmost node in the tree.

  - **Sub-Trees:**
    Branch under a node.

  - **Leaf/Terminal Node:**
    A node that has no nodes under it

  - **Path:**
    A sequence of nodes to the edges.

  - **Ancestor node:**
    Predecessor node on the path from the root to a node.

  - **Descendant node:**
    Successor node on any path from the node to a leaf node.

  - **Level Number:**
    the hierarchical number of a node. example: root node is at level 0, child nodes of the root are at level 1 and so on.

  - **Parent:**
    Predecessor node on the path from the root to a node.

  - **Left Child:**
    Left successor node.

  - **Right Child:**
    Right successor node.

  - **Degree of a node:**
    Number of children that a node has.

  - **Sibling:**
    All nodes that are at the same level, share the same parents.

  - **Similar binary trees:**
    Trees with the same structure.

  - **Copies:**
    Trees with same structure and content.

  - **Edge:**
    The line connecting a node to any of its child nodes. (N nodes has exactly N-1 edges)

repository: ramantehlan/DataStructures-CPP

repo_name: ramantehlan/DataStructures-CPP


text:
# Unreleased
* Added support for Capistrano 3.0
* Set MUTE environment variable for resque_scheduler
* Added a `resque_environment_task` option to load the `environment` rake task before running Resque workers
* Add a resque:scheduler:status task

# 0.1.0
* Interval is configurable
* Fix issue where pids weren't created correctly

# 0.0.9
* Start workers in threads

# 0.0.8
* Using stable branch of Resque, rather than the released gem, to take advantage of logging ability, losing shell redirection
* Using SIGQUIT to kill processes as they aren't terminating properly

# 0.0.7
* Different workers for different roles

repository: CharlesP/capistrano-resque

repo_name: CharlesP/capistrano-resque


text:
---
title: "Amazon Onsite Interview 준비"
categories: [면접]
tags: [interview, onsite, amazon]
mermaid: true
math: true
comments: true
pin: false
image:
  path:
  width:
  height:
  alt:
---

Amazon onsite interview는 1시간씩 4번을 진행한다.
크게 아래 두가지로 인터뷰를 진행한다.

* **coding questions**
  * algorithm/data structure/system architecture ...
  * <https://github.com/jwasham/coding-interview-university/blob/main/README.md>
* **leadership principles** (비중이 높음)
  * Each interviewer will ask 2-3 non-technical questions that are behavioral or situational question based on LP
  * [behavioral-job-interview-questions](https://www.thebalancecareers.com/behavioral-job-interview-questions-2059620)
* General Tips
  * [Interviewing at Amazon](https://www.amazon.jobs/en/landing_pages/interviewing-at-amazon)
  * **Ask clarifying questions** (imagine the interviewer is a customer or stakeholder and you need to gather requirements and details up front and as the conversation unfolds to be successful)
    * scope-down and define requirements
  * **Think that loud** engage interviewer on your thought process and why you are doing what you are doing.
  * **STAR method** when answering non-technical sitatuional-type questsions
    * [star-interview-method](https://www.themuse.com/advice/star-interview-method), [what-is-the-star-interview-response](https://www.thebalancecareers.com/what-is-the-star-interview-response-technique-2061629)
  * **Be Specific**: data points that justify decision
  * how you handle them, and what you learn form them
  * **Take Ownership**: using **"I"**

### Coding questions

* Big-O concepts: how to improve the "Big-O" of your solution
* Sorting and Searching: Know the most efficient type of search for the **input given** to the search
* Objet Oriented Design: Understand how to conceptually break a program down into objects
* System Design question
  * ability to build a solid design for a **substantial system**
  * design in production with considerations of **deployments, scaling, failures, availability and performance**
  * [System Design Cheatsheet](https://www.google.com/url?q=https://gist.github.com/vasanthk/485d1c25737e8e72759f&source=gmail&ust=1647784482914000&usg=AOvVaw1g_ZZBwvq2FXW7qXwHULN_)
  * [System Design blog](http://blog.gainlo.co/index.php/2016/02/17/system-design-interview-question-how-to-design-twitter-part-1/)
  * [System Design Interview](https://github.com/checkcheckzz/system-design-interview)
* Data structures: Arrays. LinkedLists, HashTables, Stacks, Queues and Binary Trees
* Sample questions
  * "Here's a string with numbers from 1-250 in random order, but it's missing one number. How will you find the missed number?"
  * "Describe what happens in your browser as soon as you hit enter after writing a URL in the address bar."
  * "How would you improve Amazon's website?"
  * "Design an online payment system."

### LP

* Sample qeustions
  * "Who was your most difficult customer?" (LP)
  * "What is the worst mistake you ever made?" (LP)
  * "If your direct manager was instructing you to do something you disagreed with, how would you handle it?" (LP)
  * "Which Amazon leadership principle do you resonate most with?" (LP)

### More information

* <https://www.interviewbit.com/dashboard/>
* <https://www.interviewcake.com/>
* <https://www.interviewcake.com/coding-interview-tips>
* <https://www.hiredintech.com/system-design/>
* <http://www.geeksforgeeks.org/>
* <https://www.careercup.com/page>

### Reference

* <https://www.amazon.jobs/en/software-development-interview-prep#/>
* <https://leetcode.com/discuss/interview-experience/1093869/amazon-onsite-interview-experience>
* <https://leetcode.com/discuss/interview-question/600412/Amazon-onsite>
* <https://www.geeksforgeeks.org/how-to-prepare-for-amazon-software-development-engineering-interview/>

gha_license_id: MIT


text:
vaadin-numberfield
==================

This is a fork of https://code.google.com/p/numberfield/, a NumberField component for Vaadin 6.

### Fixes

It fixes only the bug that manually added validators are ignored in the `isValid()` function which leads to problems when committing invalid forms.  See issue #3 (https://code.google.com/p/numberfield/issues/detail?id=3).

### Usage

See [original project page](https://code.google.com/p/numberfield/).

### Licence

[Apache License 2.0](http://www.apache.org/licenses/LICENSE-2.0)

### Authors

* [Markus Häcker](https://code.google.com/u/mmhaecker/) - original author of the [NumberField component](https://code.google.com/p/numberfield/)
* [Stefan Endrullis](https://github.com/xylo) - author of a bug fix contribution


text:
# Dynalist - Linked Lists for Dynamically-Sized Types

Implements linked lists that can be used with dynamically-sized types. By taking advantage of the
fact that each node is behind a pointer, you can store many different types in a linked list.

Current implements an XOR List.

repository: Aatch/dynalist

repo_name: Aatch/dynalist


text:
---
date: 2018-08-17 21:31:40.000
title: "Pointing A Domain to The Newest File In A Directory"
subtitle: ""
featuredImage: "./featuredImage.png"
ogImage: ""
tags: ['Linux']
externalLink: ""
published: true
---

I wrote a python script for Shoolu.com to use the BigCommerce API to pull the latest added products and generate an XML RSS file.  BigCommerce did have the functionality to automatically generate these RSS feeds but they have moonlighted support and have removed it for new merchants so it didn't seem like something to rely on.

PYTHON To The Rescue

I found the BigCommerce Python API and used that to fetch all the products with a created date of at most 7 days ago. I then looped through all those products to create the nessecary items in the RSS File.

This worked well and good but I was basically just overwriting the one file and losing any previous weeks worth of New Products. I knew it would be easy enough to just write to a different file with the current date in the file name so it'd be new every time.

Trouble In Paradise

The plan was to use this RSS feed to generate a "What's new at Shoolu" email every week through MailChimp and their ability to work with RSS Feeds. The problem with the current approach of dating the files was that I was pointing Mailchimp at the one direct file so I'd have to update it every week which kind of defeats the purpose of all of this.

{{{vert}}}

An Unexpected Solution

I tried digging around for a way to have a root domain (rss.shoolu.com) point to the latest file in the directory. There were several suggestions including using php to fetch the latest file and redirecting and some other less than elegant solutions.

None of them really tickled me the way a good solution does.

I finally decided to just update the python script to just output index.xml as well as latestProducts-[date].xml. That way index.xml would get overwritten with the currently accurate info and we'd also get the dated backups to log.

Then for simplicities sake I just updated the Apache Virtual Host file for the domain:

```
<Directory /var/www/rss/public/>
    ...
    DirectoryIndex index.xml
</Directory>
```
So the root domain would point directly to the file. Might not be the most elegant solution, but it works in this specific case so I'd figured I'd document it.

repository: harnerdesigns/jackharner-gatsby

gha_language: JavaScript

repo_name: harnerdesigns/jackharner-gatsby


text:
# Game Farts Unity Event Bus

Vroom.

This is a small library to manage events in Unity.

## Installation
You can install this in Unity as a Package by going to `Window > Package Manager` And then hitting the `+` and selecting `Add Package from git URL`.

## Usage

To use it you can either instantiate a new `EventBus` in your container classes for injection or create one as a humble object in a singleton MonoBehaviour. If you want to use a singleton you can check out the installable example through the package manager.

### Event Payloads

All events have a payload that has to implement the `IEvent` interface.

```c#
public class FireEvent : IEvent
{
    public Vector2 Direction { get; }

    public FireEvent(Vector2 direction)
    {
        Direction = direction;
    }
}
```

You can subscribe and unsubscribe to an event in your MonoBehaviours like this:

```c#
private void OnEnable()
{
    _eventBus.Subscribe<FireEvent>(OnFire);
}

private void OnDisable()
{
    _eventBus.Unsubscribe<FireEvent>(OnFire);
}

private void OnFire(FireEvent payload)
{
    Debug.Log( $"Firing in direction {payload.Direction}" );
}
```

And you can fire events like this:

```c#
var direction = new Vector2(
    Random.Range(-10f, 10f),
    Random.Range(-10f, 10f)
);

_eventBus.Fire(new FireEvent(direction));
```

repository: Abban/GameFartsEventBus

repo_name: Abban/GameFartsEventBus


text:
# castero changelog

This changelog generally follows the principles outlined at
<https://keepachangelog.com>, although the format may differ slightly.

Version listings include the following sections, if applicable:
* Added - for new features
* Changed - for changes to existing functionality
* Deprecated - for pre-existing features made obsolete or unsupported
* Removed - for removed features or functionality
* Fixed - for bugs fixed

See also <https://github.com/xgi/castero/releases>.

## Unreleased
**Added**
* Handle -v or --version flag to display version instead of starting the client.

## 0.2.3 - 2018-05-03
**Added**
* Downloads will now be handled sequentially rather than in parallel.

**Changed**
* The client now explicitly requires VLC >= 2.2.3
* Revised text description for episodes/feeds with missing copyright tags.

**Fixed**
* Fixed an issue where pressing pause before the media had loaded would not
properly pause it.

## 0.2.2 - 2018-04-24
**Added**
* You can now delete a downloaded episode by pressing the save key again.
* Added a config option for asking for confirmation before deleting a feed.
* An error will now be raised on startup if dependencies are not met (VLC).
* Number of episodes are now shown in feed metadata.

**Changed**
* The client will no longer try to load media when a player is created. This
substantially improves performance when adding many episodes to a queue.

**Fixed**
* Fixed an issue where config files would not be properly migrated.

## 0.2.1 - 2018-04-22
**Added**
* Automatically migrate users' config file when the client updates and adds or
removes a new config option.
* The client will now properly resize when the size of the terminal changes.

**Changed**
* Metadata window will now properly extend to the right edge of the terminal.

**Fixed**
* Fixed an issue where the queue would not properly recognize that the current
episode had finished.
* Fixed footer text not being truncated, which caused errors if the screen size
was too small.

## 0.2.0 - 2018-04-20
**Added**
* Added support for downloading episodes for offline playback.

**Fixed**
* Fixed the description of some fields in the default config file.
* Fixed an issue where the client would not properly obey the reload_on_start
config option.
* Fixed an issue where pressing enter or space with no feeds would crash the
client.

## 0.1.3 - 2018-04-19
**Added**
* Added config options for client colors.
* Added config option to automatically reload feeds on startup.
* Handle -h or --help flag to display help text instead of starting the client.

## 0.1.2 - 2018-04-13
**Added**
* You can now add entire feeds to the queue.
* Running the client with too small a screen (minimum arbitrarily defined at 20
cols and 8 lines) will now raise an error.

**Changed**
* Reloading feeds now runs on a separate thread to allow the user to continue
interacting with the client.
* Refactored setup.py with additional args in preparation for PyPi upload.

**Fixed**
* Fixed an issue where reloading feeds caused the user's selection to remain in
the episodes menu, resulting in strange behavior.
* Fixed an issue where status messages would overlap with each other after
being replaced.

## 0.1.1 - 2018-04-12
**Added**
* Pressing 'r' will now reload/refresh your feeds list.
* Added support for showing status messages in the footer, and certain commands
will now display status messages after running (or if an error occurs).

**Fixed**
* Fixed an issue where recreating menus often caused them to be smaller than
normal.
* Fixed an issue where a feeds file with duplicate keys would not load.

repository: Dramicas/castero

repo_name: Dramicas/castero


text:
{{{
  "title": "Getting started with PiWars!",
  "tags": ["piwars","robotics", "RaspberryPi","piwars-2018"],
  "category": "Robotics",
  "date": "10-26-2017",
  "author": "Sumit Maitra"
}}}

... and how *not* to apply for it! Beginning of the month we found out our maiden application hadn't made the cut for [PiWars 2018](http://www.piwars.org). Made me sad, momentarily, but it faded away fairly quickly. We were too invested in this to not do it. Sadly for us our commitment and intensity wasn't evident in our application.

One re-look at the application and it was obvious, organisers didn't have to think much about putting it in "not serious" basket!
So lesson learnt - * When a PiWars application opens, remember it is not first-come-first-serve. Don't be in a mighty hurry to hit ```Send``` on your application.*

- Take your time to read through the challenges, formulate a rough plan in your head or on a notepad on how you think you will approach the challenges. Do some background research on what it takes to attempt all the challenges.

- It is possible you will have to learn a lot before you are done, list those in a "to learn" column and say it out loud. If you are a first-timer at PiWars (like me), do lots of homework. Dig up all the past videos, blogs and pictures about PiWars.

- Finally, find like-minded Roboteers nearby and form a team/community if you are not applying on behalf of one already! RaspberryPi is all about community and education, more the merrier.

So if I were to re-apply -  "Proposed robot details" section of my application would be something like this:

We are planning to build our robot using a RaspberryPi 3 and a ThunderBorg motor controller at its heart. We plan to use the motors that come with the MonsterBorg (or similar).

The chassis will be custom designed and 3D Printed. At the end of the challenge we'll make all our designs open source for everyone to view/share/improve. We have a rough sketch of how it will support front-wheel-steering. This, we hope, will give a bit of uniqueness to the drive system of an otherwise standard four-wheeled robot.

The bot will be equipped with four (or more) Ultrasonic sensors for distance sensing to help it navigate the Speed challenge and the Maze challenge. We've looked up past challenges and found managing timing for Ultrasonic sensors in software is tricky so we are planning to use dedicated hardware to capture the sensor data and pass it on to the Pi. Looking around, we found an Arduino powered project that does 360 degree coverage using 8 sensors. However the [UltraBorg by PiBorg](https://piborg.org/UltraBorg) supports four HC-SR04 sensors plus four servos with independent power supply. It is an I2C board that supports daisy chaining so if we found need for more than four sensors we could get two of them working in tandem. The additional support for servos will come in handy for the steering and an attachment we have in mind for the 'Over the moon' challenge.

For the speed challenge, previously, a wall-hugging algorithm looking at only the left or the right wall was enough to keep it straight. Introducing the narrowing of track, steps up the challenge and we hope to be able to use distance on both sides combined with the steering capability to keep us centered.

With four distance sensors and a independently steerable robot, we hope to perfect a routing algorithm that enables the robot to navigate the maze challenge fairly independently. However, if we encounter issues we may resort to the visual cues that are being offered and use OpenCV.

For 'Over the moon' challenge we will need at-least one camera. We plan to mount the camera on a pan tilt mechanism (we already have a un-used Pan Tilt hat kit from Pimoroni) and drive it via the UltraBorg's servo drivers. We don't know yet, there is a chance 180 degree movement is going to be enough to capture all the four corners of the challenge pit. If it doesn't we will have to re-work the image-capture system to have two cameras facing away from each other and will be easily able to cover a 360 degree view. We are new to OpenCV but have looked at the possibilities and we hope to be able to trace out the position of the 4 balls and workout an optimal run during the first parse. The second and third parse won't require the route calculation so we hope our best times are in these runs. We would like the capture unit to be an independent PiZero talking to the mother ship over USB.

If we gain enough OpenCV experience we may use the camera as a backup for centering in the line challenge as well.

The Duck shoot challenge seems very interesting given the complexity of building a projectile launcher. We haven't thought this through yet, but we saw David Pride's nerf dart launcher and we do have a Nerf gun that can be sacrificed. We will probably follow David's lead for this one.

Tada!

Well, that definitely looks better than what I said in the application:

> I am currently waiting eagerly for the MonsterBorg kit to be delivered. If selected, our Robot is likely to be based on the ThunderBorg board and a Raspberry Pi 3.
> We have a 3D Printer so the chassis is likely to be 3D Printed.

Yeah, that's pretty embarrassing alright!

Mind you, most of the things I wrote above are stuff I found out after I submitted the application and before the last date of submission. So even if you start thinking about your new Robot after the Applications have opened, you have enough time to think through your approach and form a coherent plan. It should reflect in your application.

Will the additional details ensure selection, NOPE!

Remember, the organisers have an un-enviable and fairly subjective task of picking teams from the hundreds of applications. If you don't make it, don't despair, continue with your experimenting and learning. Talk about what you learn and where you get stuck, share it with people via, blogs, talks and workshops. Remember, PiWars is more about community and education and not to do with cut-throat multi-million pounds professional competition (I can hear some of you ;-)...)!

Go to the actual event anyway, it should be a lot of fun. You can get spectator tickets [here](https://ti.to/cambridge-raspberry-jam/pi-wars-2018-spectators).

## On to robot-making

With the application out of the way, and having decided the only way was forward, we decided to get started with the Chassis.

### The chassis
With the MonsterBorg delivered, our primary motors and motor drivers were pre-decided. The MonsterBorg is a monster all-right. You cannot use its super neat aluminum chassis along with the default tires. The resulting bot is wider than the allowed width of a A4 size paper. So step 1 was to build a custom chassis.

#### Using Tinkercad
[Tinkercad](https://www.Tinkercad.com) is a really neat online/web-based 3D Design tool. It is super easy to get started, just follow their online Tutorials for an hour or so and you are off.

I faced a problem with Tinkercad straight off the bat. The default build plate on Tinkercad isn't big enough to support the A4 size robot. Neither was my 3d Printer. With a 190mm square usable build plate the best I could hope was a two piece chassis.

To keep things proportional I started with a 1/2 sized model in Tinkercad (1/2 height, 1/2 width and 1/2 length). Here is a sneak peek of the scaled model.

##### Modeling the pieces
The way I (3D) model a piece is to first create the items that the model is going to support. For example if I am building a Pi Zero case, I like to have a 1:1 model of a RaspberryPi Zero that I can then use to build the case around.

I wanted to start with a monocoque design for the chassis. A metal monocoque shell is pressed into shape against appropriate dies. I decided to carve it out of solid (virtual) blocks. This meant designing the bits to carve out separately. First on the list were the motors :-)

- The ThunderBorg Motor
In this case the first thing I needed was a fairly matching replica of the giant ThunderBorg motors! With a set of Digital Vernier Calipers I had the measurements done quickly and ended up with this

    Building the motor accurately enables me to put it in the rest of the design and 'subtract it'. It also allows for a better understanding of how things fit in and where. For example, I wasn't sure if I could fit the ThunderBorg motors and the Diddyborg wheels.

- The Motor mount
 With the motor ready, the motor mount was 'relatively easy' to design. But I didn't want to use it directly in a single block without testing if the motor would fit. So I designed a small piece that just had the appropriate holes to hold the motor. This nondescript little thing too 4 attempts to get bang on target. However, advantage of building it separately first was I spent only about 30 minutes one each incorrect print job, instead of the 6.5 hours it took to print the whole rear section.

- The Rear section
  Once the motor-holder was ready, the rear section was easy. I copied the base from the above scaled model, increased it to correct proportions and then chopped off the front half using a big transparent box.
  Next I placed two motors on two sides and put the holders at appropriate places so that the mounting holes all lined up correctly.
  Finally, there was a gap between the chassis plate and the motor. A metal frame is rigid enough but a plastic one isn't, so I built a platform to support the motor and have provision for a u-clamp to secure it (and take weight off the motor holders). To increase the area of contact between vertical and horizontal edges I tapered all joints as you can see.

  The actual printable section without the motors looks like this

- The 'joiner'
  The keen-eyed would have noticed some additional holes in the base of the rear section above. Thing is if you break something into two, you have to put it back as well. I considered various ideas like a door-hinge design to bolt the pieces together, only glue, glue and dovetail joint or glue and box joint. In the end, I went with a glue and support. I knew I had to fit a RaspberryPi firmly on the chassis. Using the underside of the frame for joining the chassis was kind of 'easy way out'. So I went on Thingiverse and found a nice RaspberryPi Chassis and then imported it into Tinkercad. Placed the base on the chassis and used the mounting holes to put in the screw holes.

- The Front Section
  The Font Section had three major parts: The Chassis Base, the Steering + Wheel Mount and the Sensor mount. Ideally the sensor mount is a part of the Wheel mount but I kept is separate so we could swap it for a 'grabber' attachment when using in non-autonomous mode.
  - The Base - I just moved the transparent box to the rear and whatever was left was the front section. The little fidget-spinner inspired center section is actually for the mounting a 8x22x7 ball bearing. The bearing is going to be embedded in the Steering+Wheel mount allowing the steering to move easily. Atleast that is the plan. These are completely uncharted territories for me, so I am taking it as it comes.

  - The Steering + Wheels mount - I created motor mounts similar to how I had done for the rear of the case and added a 22mm hole in the middle for the ball bearings. Can you spot the design defect?

  The peach color bleeding through the red is an indication that there isn't enough space for the motor to fit in. I ended up with motors that mounted like this:

  Took a fair amount of filing to get it fitted eventually. I'll adjust and reprint later.

  - The Sensor mount - Last bit was the Ultrasonic sensor mount. I wanted it as far ahead as possible because I want it to detect the turns in the maze quickly enough. I am hoping, mounting it on the steer-able bit will give a more accurate reflection of current position and future direction. Given I have never worked with Ultrasonic sensors this is all a guess. We will know once we get it in action.
  This is the second iteration, and again, I built a separate HC-SR04 sensor mount design first and printed it out. Once I was happy that it fit the sensors well enough used it in the final mount.

That's about all the bits I have designed so far. Apart from the issue with the front motor mount, they fit well.

## Getting started with the Electro-Mechanicals
3D Design and Printing can be a lot of fun in itself. But that will only give you a static bot. You need to bring together all the electro-mechanical bits and tie it up with software to give it life.
Next step was to test if the UltraBorg and the ThunderBorg would play nice with each other. Both being I2C devices I did not anticipate any trouble and turns out, after you have read through the documentation of the UltraBorg and ThunderBorg, it is no trouble at all.  If things don't work at first, wiggle the wires.
Here is what my wiring looks like.

During the first test, I was powering the UltraBorg from the Pi itself because it was only using the HC-SR04 sensors. However if you want to test with Motors, _take out the jumper on the UltraBorg_ and power it from a separate power source. I am still undecided if I should use a separate Lithium Ion + Adafruit Powerboost combination or tap from the 12V output of the ThunderBorg and use a Hobbywing UBEC. More about that in the next post.

Once tested, I bolted the joiner to the top of the chassis and put the Bot together.

Unfortunately, I didn't have the steering servo while doing the design bits, so up until this point, I had 3 Ultrasonic sensor readings, 4 controllable motors tied to a motor controller, all tied to a Pi but no steering. I am currently working on the steering motor mount. Once it is ready, I will start with a Rock Candy controller. I will probably have a XBox controller in the standby too. That's when the fun will actually start. Hopefully an update in another couple of weeks! Till then keep robot hacking!

P.S. If you are a part of PiWars then you should probably join the Discord group run by Tom Oinn. It has an enthusiastic bunch on roboteers who have either participated in a PiWars before or are signing up this year. It is a very nice place to ask any question.

        1: Rear section from the right

        2: Rear section with motor and wheels mounted

        3: Rear section with motor and wheels mounted

        4: The front steering and motor mount being printed

        5: Front steering and motor mount, with motors and ball-bearings

        6: The bot laid out upside down (not joined yet)

    Previous

    Next

repository: piofthings/web

gha_language: G-code

repo_name: piofthings/web


text:
When submitting a PR, your chance of acceptance increases if you do the following:

* Code style is consistent with existing in the file.
* Tests are passing (client and server).
* You add a test for the failing issue you are fixing.
* Code changes are focused on the area of discussion.
* Do not rebuild the distribution files or increment version numbers.

## Contributors

| Name                | Website                    |
| ------------------- | -------------------------- |
| **TJ Holowaychuk**  | <http://tjholowaychuk.com> |
| **Kornel Lesiński** |                            |
| **Peter Lyons**     |                            |
| **Hunter Loftis**   |                            |
| **Nick Baugh**      |                            |

repository: charm-jp/superagent

repo_name: charm-jp/superagent


text:
> **Warning**: Digest is a work in progress.

Here at [D3 Estudio](http://d3.do), Slack is our primary communication channel. Found a nice article? Slack. Found a cool gif? Slack. Want to spread the word about an event? Well, guess what? Slack.

We have been overusing the (relatively) new [Reactions](http://slackhq.com/post/123561085920/reactions) feature lately, and we stumbled on a nice idea: _Why not create a digest based on these reactions_?

Well, this is what **Digest** does: it watches channels through a bot and stores messages and their respective reactions.

## Installing

Digest is distributed through a single Docker Image containing all required binaries:

```
$ docker pull d3estudio/digest:latest
```

In order to work, Digest needs a Mongo and Redis instance to connect to. Those servers addresses can be defined in the environment variables of the containers running each process:

 - `DIGEST_TOKEN`: Slack token used to authenticate and connect to your Slack team. This token can be obtained by [Creating a New Slack Bot](https://my.slack.com/apps/A0F7YS25R-bots).
 - `DIGEST_SILENCER_EMOJIS`: A comma-separated string of reactions that will prevent a given message that contains it from appearing publicly. Please do note that this does not prevent a message from being stored. Defaults to `no_entry_sign`.
 - `DIGEST_REDIS_SERVER`: Address of the Redis server used for IPC. Defaults to `redis`.
 - `DIGEST_REDIS_PORT`: Port of the Redis server used for IPC. Defaults to `6379`.
 - `DIGEST_MONGO_SERVER`: URL of the Mongo server used for storing data and keeping indexes. It must be in following format `[mongodb://][user:pass@]host1[:port1][,host2[:port2],...][/database][?options]`, which allows it from being simple as `localhost` to something more involved, like `mongodb://myuser:mypass@localhost:40001,otherhost:40001/mydb`. Assumes `27017` as the default port, if not provided. Defaults to `mongo`.
 - `DIGEST_MONGO_DATABASE`: Name of the database that will hold collections created by the application. Defaults to `digest`.
 - `DIGEST_BASE_QUEUE_NAME`: Name of the base name of all Redis queues. Useful if working with more than one instance on the same Redis server. Defaults to `Digest`.
 - `DIGEST_TWITTER_KEY` and `DIGEST_TWITTER_SECRET`: Used by the `prefetcher` process to acquire oembed data from Twitter. Those keys are optional, but not providing them will prevent Digest from embeding tweets into the results. Defaults to `""`.

## Developing
The development environment only requires a functional installation of the Go compiler and [Godep](https://github.com/tools/godep), that is used to manage our dependencies. That said, everything you have to do is clone this repository into your `$GOPATH`, head over to it and run `godep restore`. This repository also contains a basic `docker-compose.yml` that will spin up a Redis and Mongo instance.

## License
```
MIT License

Copyright (c) 2016 Victor Gama

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

 IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN D3 Estudio

Newspaper Icon by ✦ Shmidt Sergey ✦ from the Noun Project
```


text:
---
hrs_structure:
  division: '2'
  volume: '8'
  title: '23'
  chapter: 421I
  section: 421I-6
type: hrs_section
tags:
  - Business
menu:
  hrs:
    identifier: HRS_0421I-0006
    parent: HRS0421I
    name: 421I-6 Documents of the corporation
weight: 41030
title: Documents of the corporation
full_title: 421I-6 Documents of the corporation
---
**[§421I-6] Documents of the corporation.** (a) Upon approval by the board of directors of the corporation's most current financial statement and the minutes of the most recent board of directors' meeting, the statement and the minutes shall be available for examination by any shareholder at no cost or on twenty-four hour loan, at convenient hours and a convenient location designated by the board of directors.

(b) Upon approval by the board of directors of the minutes of other meetings of the board of directors and the meetings of the corporation for the current and prior year, the minutes shall be available for examination by shareholders at convenient hours and a convenient location designated by the board. Copies of meeting minutes shall be provided to any shareholder upon the shareholder's request, if the shareholder pays a reasonable fee for duplicating, postage, stationery, and other administrative costs associated with handling the request.

(c) Financial statements, general ledgers, accounts receivable ledgers, accounts payable ledgers, check ledgers, insurance policies, contracts, invoices of the corporation for the current and prior year, and any documents regarding delinquencies of ninety days or more shall be available for examination by shareholders at no cost and at convenient hours at a place designated by the board; provided that shareholders shall pay for administrative costs associated with examinations in excess of eight hours per year.

The board may require shareholders to furnish the corporation with an affidavit stating that the information is requested in good faith for the protection of the interests of the corporation, its shareholders, or both.

Copies of these items shall be provided to any shareholder upon the shareholder's request, if the shareholder pays a reasonable fee for duplicating, postage, stationery, and other administrative costs associated with handling the request.

(d) Shareholders may view proxies, tally sheets, ballots, shareholders' check-in lists, and the certificate of election for a period of thirty days following any corporation meeting; provided that shareholders shall pay for administrative costs in excess of eight hours per year.

The board may require shareholders to furnish to the corporation an affidavit stating that the information is requested in good faith for the protection of the interest of the corporation, its shareholders, or both.

Proxies and ballots may be destroyed following the thirty-day period. Copies of tally sheets, shareholders' check-in lists, and the certificates of election from the most recent corporation meeting shall be provided to any shareholder upon the shareholder's request, if the shareholder pays a reasonable fee for duplicating, postage, stationery, and other administrative costs associated with handling the request.

(e) Shareholders may file a written request with the board of directors to examine other documents. The board shall give written authorization or written refusal with an explanation of the refusal within thirty calendar days of receipt of the request. [L 1993, c 282, pt of §1]

repository: SamMade/BlueAndKrabby

repo_name: SamMade/BlueAndKrabby


text:
### Pursuit

This environment is part of the [SISL environments](../sisl.md). Please read that page first for general information.

| Observations | Actions | Agents  | Manual Control | Action Shape | Action Values |  Num States |
|--------------|---------|---------|----------------|--------------|---------------|-------------|
| Graphical    | Either  | 8 (+/-) | Yes            | (1,)         | [0,4]         |  ?          |

`from pettingzoo.sisl import pursuit_v0`

`agents= ["pursuer_0", "pursuer_1", ..., "pursuer_7"]`

![](sisl_pursuit.gif)

*AEC diagram*

By default there are 30 blue evaders and 8 red pursuer agents, in a 16 x 16 grid with an obstacle in the center, shown in white. The evaders move randomly, and the pursuers are controlled. Every time the pursuers fully surround an evader, each of the surrounding agents receives a reward of 5, and the evader is removed from the environment. Pursuers also receive a reward of 0.01 every time they touch an evader. The pursuers have a discrete action space of up, down, left, right and stay. Each pursuer observes a 7 x 7 grid centered around itself, depicted by the orange boxes surrounding the red pursuer agents. The enviroment runs for 500 frames by default. Observation shape takes the full form of `(3, obs_range, obs_range)`.

Manual Control:

Select different pursuers with 'J' and 'K'. The selected pursuer can be moved with the arrow keys.

```
pursuit.env(max_frames=500, xs=16, ys=16, reward_mech='local', n_evaders=30, n_pursuers=8,
obs_range=7, layer_norm=10, n_catch=2, random_opponents=False, max_opponents=10,
freeze_evaders=False, catchr=0.01, caughtr=-0.01, term_pursuit=5.0,
urgency_reward=0.0, surround=True, constraint_window=1.0,
train_pursuit=True, ally_layer=AgentLayer(xs, ys, n_pursuers),
opponent_layer=AgentLayer(xs, ys, n_evaders))

```

*about arguments*

```
max_frames: after max_frames steps all agents will return done

xs, ys: size of environment world space

reward_mech: Whether a single pursuer is rewarded for an evader being caught, or all pursuers are rewarded

n_evaders: Number of evaders

n_pursuers: Number of pursuers

obs_range: Radius of agent observation view

layer_norm: Scalar value that the observation matrix is divided by

n_catch: Number pursuers required around an evader to be considered caught

random_opponents: Whether to randomize number of evaders on reset or use argument amount

max_opponents: Maximum number of random evaders on reset, if random_opponents specified

freeze_evaders: Toggles if evaders can move or not

catchr: Reward for 'tagging' a single evader

caughtr: Reward for getting 'tagged' by a pursuer

term_pursuit: Reward added when a pursuer or pursuers catch an evader

urgency_reward: Reward to agent added in each step

surround: Toggles whether evader is removed when surrounded, or when n_catch pursuers are on top of evader

constraint_window: Window in which agents can randomly spawn into the environment world

train_pursuit: Flag indicating if we are simulating pursuers or evaders

ally_layer: Initial pursuers in world

opponent_layer: Initial evader in world
```

Leaderboard:

| Average Total Reward | Method | Institution | Paper | Code |
|----------------------|--------|-------------|-------|------|
| x                    | PPO    | UMD         |       |      |

repository: MarioJayakumar/PettingZoo

gha_license_id: NOASSERTION

repo_name: MarioJayakumar/PettingZoo


text:
# Palindromic Numbers

## Statement
A palindromic number reads the same both ways. The largest palindrome made from the product of two
2-digit numbers is 9009 = 91 × 99. Find the largest palindrome made from the product of two
3-digit numbers.

## Analysis
Multiplying two N-digit numbers yields a number with a length of 2N or 2N-1. Assuming that after
multiplying these numbers we can always obtain at least a palindrome of the greater length (2N)
the search can be reduced to find the greater palindrome of length 2N.

## Usage
```bash
$> python3 palindromes.py
Largest palindromic number is: 906609
As a result of multiply the digits: 913x993
```

repository: darofar/code-tests

repo_name: darofar/code-tests


text:
# Compute Sever Capacity Api

## Built With

- [Node.js](https://nodejs.org/)
- [Express](https://expressjs.com/)

## Supporting packages

#### Linter

- [ESLint](https://eslint.org/)

#### Compiler

- [Babel](https://babeljs.io/)

## Application Features

- Compute Server Capacity for hosting virtualmachines

## Getting Started

### Installation

- Install [NodeJS](https://nodejs.org/) on your computer
- Clone this repository using `https://github.com/devgbolade/server-planner.git`
- Use the `.env.example` file to setup your environmental variables and rename the file to `.env`
- Run `npm install` to install all dependencies
- Run `npm run build` to build the project
- Run `npm run start:dev` to start the server
- Navigate to [localhost:3000](http://localhost:4500/) in browser to access the application

#### Test Tools

- [Jest](https://jestjs.io/) - JavaScript Test Framework for API Tests (Backend)
- [Supertest](https://www.npmjs.com/package/supertest) - Super-agent driven
  library for testing node.js HTTP servers

  ## Running Tests

Dependencies to enable them work are included in the `package.json` file. To run unit tests, you can do the following:

```bash
# Enter the project's directory
$ cd server-planner/

# To run the available unit tests
$ npm run test
```

## API endpoints

| Method |             Endpoint              |                               Description                                | Access |
| :----- | :-------------------------------: | :----------------------------------------------------------------------: | :----: |
| `POST` | `/api/v1/compute-server-capacity` | Compute Server Capacity for hosting virtualmachines based on user inputs | public |

### **Validate Rule**

- **URL**
  - /api/v1/compute-server-capacity
- **Method**
  - `POST`
- **Data Params**
  - **Required**
    - `server={ CPU: number, RAM:number, HDD: number }`
    - `virtualMachines=[{ CPU: number, RAM:number, HDD: number }]`
- **Success Response**
  - **Code:** 200
  - **Content:**
  ```
  {
    "status": "success",
    "message": "Server capacity is successfully calculated.",
    "data": {
        "serverCapacity": 2
    }
  }
  ```
- **Failure Response**

  - **Code:** 422
  - **Content:**

  ```
  {
    "status": "error",
    "message": "'server.CPU' is required",
    "data": null
  }
  ```

  **OR**

  - **Code:** 422
  - **Content:**

  ```
  {
    "status": "error",
    "message": "'server' must be of type object",
    "data": null
  }
  ```

  **OR**

  - **Code:** 422
  - **Content:**

  ```
  {
    "status": "error",
    "message": "'virtualMachines' is required",
    "data": null
  }
  ```

  **OR**

  - **Code:** 500
  - **Content:**

  ```
  {
    "message": "Internal Server Error",
    "status": "error",
    "data": null
  }
  ```

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details

## Author

**Agbolade Adeniyi**

repository: DevGbolade/server-planner

repo_name: DevGbolade/server-planner


text:
# Leightweight starter

An ultra lightweight starter for generating simple HTML + CSS + JS pages with modern developer tooling.

## Why?

Sometimes you just need a simple website, but you still love the luxuries of modern development, like new javascript syntax, autoprefixed CSS and hot reloading. But not the large bundle sizes that come with javascript frameworks these days. A minified production build of this repo is just 2kb, including HTML and CSS, and that's more than enough.

## Getting started

Clone the repo, remove the `.git` folder if you want to make your own and run:

```
$ yarn && yarn start
```

for production builds:

```
$ yarn dist
```

## What's included?

- A plain index.html file loaded
- Autoprefixed and minified CSS with Postcss
- Modern javascript syntax through babel
- Live reloading and optimized builds with webpack

repository: danielsneijers/lightweight-starter

repo_name: danielsneijers/lightweight-starter


text:
# Binoculars: Binomial Confidence Intervals

![https://deepnote.com/project/e17fa473-51c6-45aa-8de0-980be7d2dc5f](demo.png)

![Unit Tests](https://github.com/nolanbconaway/binoculars/workflows/Unit%20Tests/badge.svg)
[![codecov](https://codecov.io/gh/nolanbconaway/binoculars/branch/main/graph/badge.svg?token=EOH4M3PIYL)](https://codecov.io/gh/nolanbconaway/binoculars)
[![PyPI](https://img.shields.io/pypi/v/binoculars)](https://pypi.org/project/binoculars/)

This is a small package that provides functions to compute the confidence interval for a binomial proportion. I made it because I spend altogether too much time staring at the Binomial proportion confidence interval [wiki page](https://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval).

Presently, the package implements:

- [The Normal Approximation](https://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Normal_approximation_interval)
- [The Wilson Interval](https://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Wilson_score_interval) (no continuity correction)
- [Jeffrey's interval](https://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Jeffreys_interval) (via scipy.stats.beta)
- [Clopper-Pearson interval](https://en.wikipedia.org/wiki/Binomial_proportion_confidence_interval#Clopper%E2%80%93Pearson_interval) (also via scipy.stats.beta)

If you haven't spent a lot of time thinking about which interval _you_ should use (and why would you want to?), I suggest using the Wilson interval or Jeffrey's interval. Jeffrey's interval is returned by default by the `binomial_confidence` function in this package.

> You _oughtn't_ use the normal approximation if you don't have to. It produces patently inaccurate values with low/high probabilities at low Ns. The plot at the top of this readme shows the normal approximation producing lower lower bounds of _less than 0_ in these cases.

## Install

```sh
pip install binoculars
```

## Usage

```py
from binoculars import binomial_confidence

N, p = 100, 0.2

binomial_confidence(p, N)  # default to jeffrey's interval
# (0.1307892803998113, 0.28628125447599173)

binomial_confidence(p, N, tail='lower') # grab one tail
# 0.1307892803998113

# set Z value
binomial_confidence(p, N, tail='lower', z=2.58)
# 0.11212431621448567

# choose your method

binomial_confidence(p, N, method='normal')
# (0.12160000000000001, 0.2784)

binomial_confidence(p, N, method='wilson')
# (0.1333659225590988, 0.28883096192650237)

binomial_confidence(p, N, method='clopper-pearson')
# (0.1266544343411484, 0.291844378634278
```

## Development

I honestly do not imagine touching this a lot. But maybe you want to add one of the other interval methods?

1. Make a python 3.6+ venv
3. `pip install -e .[test]`
4. `black lib --check`
5. `pytest`

## Later (?)

 - [ ] Add confidence intervals for odds ratios, differences
 - [ ] Add the unimplemented intervals
 - [x] Add plots comparing the intervals to readme.

repository: nolanbconaway/binoculars

gha_language: Python

repo_name: nolanbconaway/binoculars


text:
# HexArch

Project shows how to use two different data stores using Hexagonal Architecture.

There are two different data access layers:

- `InMemoryDataAccess` to use in development
- `EntityFrameworkDataAccess` for every other environment

## How to use different environment?

To test how application behaves in different environment change the `ASPNETCORE_ENVIRONMENT` property value in `HexArch.Web/Properties/launchSettings.json` to e.g.: `Production`.

# TODO

- [ ] Add automatic tests
  - [ ] Run tests both in `Development` and `Production` environments

repository: macborowy/hexarch

repo_name: macborowy/hexarch


text:
`nav`

> Takes waypoints and builds paths between them based on the conditions and the boat configuration.

`captain`

The `captain` module is the high-level API for the `nav` package. Methods available are:

- `waypoints_between(start, end, boat, wind)`

This will return a queue of waypoints between `start` and `end`. `start` and `end` must be `Waypoint`s.


text:
# MS-Store-API
## Trying to figure out the Microsoft Store API

Currently there's no publicly documented API for accessing products (including Apps, Games) available in the Microsoft Store.
With the release of the product [badge tool for the Microsoft Store](https://blogs.windows.com/buildingapps/2018/05/18/a-new-product-badge-for-microsoft-store-applications/) I found a publicly accessible API endpoint that allows you to retreive product information by ID (and more?).

## Get product information

* [v8.0/sdk/products](endpoints/v8.0/products.md)

## Search for a product (store search w/ images)

* [v9.0/pages](endpoints/v9.0/pages.md)

## Search for a product (manifest search/winget)

* [v9.0/manifestSearch](endpoints/v9.0/manifestSearch.md)

# References
- https://docs.microsoft.com/de-de/windows/privacy/manage-windows-endpoints#microsoft-store
- https://blogs.windows.com/buildingapps/2018/05/18/a-new-product-badge-for-microsoft-store-applications/#wxXtV2V8lebI1R4W.97
- http://displaycatalog.mp.microsoft.com/
- pti.store.microsoft.com

repository: ThomasPe/MS-Store-API

gha_language: HTML

repo_name: ThomasPe/MS-Store-API


text:
---
title: Priority Class
weight: 3
---
The Priority Class setting can be used to set a higher priority on Longhorn workloads in the cluster, preventing them from being the first to be evicted during node pressure situations.

For more information on how pod priority works, refer to the [official Kubernetes documentation](https://kubernetes.io/docs/concepts/configuration/pod-priority-preemption/).

# Setting Priority Class

### During Longhorn Installation

Follow the instructions to set the initial Priority Class setting: [Customize Default Settings](../customizing-default-settings)

> **Warning:** Longhorn will not start if Priority Class setting is invalid (such as the Priority Class not existing). You can see if this is the case by checking the status of the longhorn-manager DaemonSet with `kubectl -n longhorn-system describe daemonset.apps/longhorn-manager`. You will need to uninstall Longhorn and restart the installation if this is the case.

### After Longhorn Installation

The Priority Class setting can be found in the Longhorn UI:

Setting -> General -> Priority Class

Users can update or remove the Priority Class here, but note that this will result in recreation of all the Longhorn system components. The Priority Class setting will reject values that appear to be invalid Priority Classes.

# Usage

Before modifying the Priority Class setting, all Longhorn volumes must be detached.

Since all Longhorn components will be restarted, the Longhorn system will temporarily be unavailable. If there are running Longhorn volumes in the system, Longhorn system will not be able to restart its components, and the request will be rejected.

Don't operate the Longhorn system after modifying the Priority Class setting, as the Longhorn components will be restarting.

Do not delete the Priority Class in use by Longhorn, as this can cause new Longhorn workloads to fail to come online.

## History
[Original Feature Request](https://github.com/longhorn/longhorn/issues/1487)

Available since v1.0.1

repository: longhorn/website

repo_name: longhorn/website


text:
# Aggregation Factory
This factory creates row with aggregation result for specified query
without applying pagination and modifying passed query.

## Example

```php
<?php

use Horat1us\Yii\Criteria\Factories\AggregationFactory;

/** @var \yii\db\ActiveQuery $query */
$factory = new AggregationFactory($query);
$aggregationRow = $factory->create([
    'sum' => 'sum(payment.amount)' // Your custom aggregation query
]);

echo $aggregationRow->getCount(); // Total count
echo $aggregationRow->getTotal()['sum']; // Your custom value

```

gha_language: PHP


text:
# Ch 17. Monte Carlo Methods

## Randomized Algorithms
* Las Vegas
 * precise correct answer with a random amount of resources (time or memory)
   deterministic approximation
* Monte Carlo
 * answer with a random amount of error
 * error will be reduced by expending more resources

## Why sampling in Machine learning

* a way of approximate many sums and integral at reduced cost
* esp. in case of intractable sum such as partition function

## Monte Carlo sampling

* approximate the expectation by empirical average

![](../images/benjio_17/1.png)
![](../images/benjio_17/2.png)

* law of large number tells that average converge surely to the expected value
* central limit theorem tells that distribution of average converges to a normal distribution with true expectation as mean and true variance divided by n as variance
* When cannot sample from base distribution?? => use importance sampling

##  importance sampling

* sometime it is very hard to sample from p
* sample from q instead of p
![](../images/benjio_17/3.png)
![](../images/benjio_17/4.png)
* expected value of the estimater does not depend on q (Good!!)
* variance of the estimater can be greatly sensitive to the choice of q (Bad!!)
![](../images/benjio_17/5.png)
* What's good/optimal choice of q
 * minimal variance occurs when q* sums or integrates to 1 as appropriate
 ![](../images/benjio_17/6.png)
 * poor choice of q when pf/q is large
    * q >> pf (useless tiny numbers)
    * q << pf (large variance)

## Markov chain

* sample from irreducible,aperiodic,stationary markov chain leads to approximation of expectation

![](../images/benjio_17/7.png)
 * **irreducible** : there's at least one path from anywhere to anywhere in markov chain
 * **aperiodic** : there's no repeated tendency of state transition
 * **stationary** : convergence in a distribution with respect to time

#### Detail balance leads to stationary

* prob mass exchange in balance
![](../images/benjio_17/8.png)

* symmetry from 1 to n and n to 1
![](../images/benjio_17/9.png)

* intuition from mass exchange
![](../images/benjio_17/10.png)

#### metropolis algorithm

* produce samples which obey ergodic properties
* sample mean from those samples leads to approximation of expectation
* how to do it ?
 * proposal on transition matrix
 * choose next one and test whether it is accepted or rejected
 * those accepted series turn out to be ergodic process
 ![](../images/benjio_17/11.png)

## Markov chain monte carlo Methods

* hard to sample from true dist p, or importance sampling dist q
* Instead, we need to approximately sample from p by markov chain
* precondition is of no zero-probability
 * or no zero-energy in energy-based model
* Why markov chain?
 * In EBM, in undirected graph, sampling is difficult due to intractable cases
 * In acyclic, in directed graph, it is quite easy to sample due to tractable cases
* what internals in markov chains ?
 * pdf of states eventually converges to equilibrium distribution
  * all eigenvalues decay to zero except single 1 eigenvalue
  * rate of convergence is related to the second largest eigenvalue decay
  * is called "burning in"
  * no theory yet for deciding whether equilibrium achieved or not

## Gibbs sampling
* http://www.cs.cmu.edu/~tom/10-702/GibbsAndMCMCsampling.pdf
* as a variation of EM Algorithms
* if bivarate x,y, sample x1 from y0, then y1 from x1, and so on.
 * converges to true dist p(x)

![](../images/benjio_17/12.png)
![](../images/benjio_17/13.png)

* select one variable x and sampling it from pmodel conditioned on its neighbors in the undirected graph defined in energy-based model
* usually do not use metropolis-hastings algorithm in deep learning

## The challenge of mixing between separated modes

* mix mean samples from almost all areas of sample space x
* slow mix or even failure to mix
 * mcmc is like noisy gradient descent on the energy function
 * or like noisy hill climbing on the probability with respect to the state of the chain
 * the energy function may have several modes, each of blockaded by high energy barriers, hard to jump to one another

![](../images/benjio_17/14.png)

* how to avoid slow mix
 * make low of high energy barriers
  * by introducing controlling peaked distribution
  ![](../images/benjio_17/15.png)
  * by making deep neighbors

repository: hoondori/TIL

repo_name: hoondori/TIL


text:
## Tremor Intermediate Workshop - 1

- Connecting to Kafka
- Tremor-query (Trickle) and Tremor-script
- Rate-Limiting
- Group By and Windows
- Linked Transport

---

## Lab Exercise 1

In this section, we will gradually build a solution for processing structured log messages
from Kafka, transforming, classifying and rate-limiting them.

---

## Requirements

- Docker
- docker-compose

---

## Task 0: Set up lab materials

```sh
git clone git@github.com:tremor-rs/tremor-www-docs.git
cd tremor-www-docs/course/intermediate-lab

# copy the trecker script to intermediate-lab directory for easier access
# optional: can place the script somewhere in your $PATH
cp ../scripts/trecker .

# validate. should give cli usage
./trecker -h
```

---

## ✋ Task 1: Connect to kafka

__Preparation__

Start kafka and kafka_feeder (this will occupy your shell):

```sh
make start-kafka
```

This feeds the sample data continuously to a topic named `tremor` in the kafka cluster.

---

## ✋ Task 1: Connect to kafka

Configure the tremor instance in `./etc/tremor` to read from topic `tremor` in the `kafka_feeder` kafka cluster, displaying received events on stdout.

```sh
make start-tremor # watch the shell where you started the compose
```

`make stop-tremor` to stop.

---

## Task 1: Solution

```yaml
onramp:
  - id: kafka
    type: kafka
    codec: json
    config:
      brokers:
        - kafka:9092
      topics:
        - tremor
      group_id: lab
```

---

## ✋ Task 2a: Cleanup Input Data

Write a pipeline script that renames the field `short_message` to `log_level`, trimming and lowercasing its contents.

Before:

```json
  ...
  "short_message": "ERROR",
  "logger_name": "logger3",
  ...
```

After:

```json
  ...
  "log_level": "error",
  "logger_name": "logger3",
  ...
```

Iterate on the logic with:

```sh
./trecker run /pwd/etc/tremor/config/main.trickle -i /pwd/data/input.json
```

---

## Task 2a: Solution

```trickle
define script cleanup
script
  use std::string;

  let event = merge event of
    {
      "log_level": string::lowercase(string::trim(event.short_message)),
      "short_message": null
    }
  end;

  # alt method: using patch only
  #let event = patch event of
  #  upsert "log_level" => string::lowercase(string::trim(event.short_message)),
  #  erase "short_message"
  #end;

  # alt method: path-based assignment and patch
  #let event.log_level = string::lowercase(string::trim(event.short_message));
  #let event = patch event of
  #  erase "short_message"
  #end;
end;

create script cleanup;

select event from in into cleanup;
select event from cleanup into out;

select event from cleanup/err into err;
```

---

## ✋ Task 2b: Classify the Input Data

Add a new field `class` to the event, with value based on the contents of the `index_type` field.
  - `applog`: if field `index_type` starts with the string `applog`.
  - `syslog`: if field `index_type` starts with the string `syslog`.
  - `other`: all other events.

```sh
./trecker run /pwd/etc/tremor/config/main.trickle -i /pwd/data/input.json
```

---

## Task 2b: Solution

```trickle
# defintion for cleanup script redacted for length (see task 2a)

define script classify
script
  let event.class = match event of
    case %{ index_type ~= glob|applog*| } => "applog"
    case %{ index_type ~= glob|syslog*| } => "syslog"
    default => "other"
  end;

  event
end;

create script cleanup;
create script classify;

select event from in into cleanup;
select event from cleanup into classify;
select event from classify into out;

select event from cleanup/err into err;
select event from classify/err into err;
```

---

## ✋ Task 2c: Tag the Input Data

Add a new value to the `tags` array in the event, indicating the application's oddness or evenness.
  - `app_even`: if field `application` starts with the string `app`, immediately followed by an even number. e.g. `app2`.
  - `app_odd`: if field `application` starts with the string `app`, immediately followed by an odd number. e.g. `app3`.

```sh
./trecker run /pwd/etc/tremor/config/main.trickle -i /pwd/data/input.json
```

---

## Task 2c: Solution

```trickle
# defintion for cleanup and classify scripts redacted for length (see task 2a, 2b)

define script tag
script
  use std::integer;
  use std::array;

  match event of
    case app = %{ application ~= re|^app(?P<num>\\d)| } =>
      let tag = match integer::parse(app.application.num) % 2 of
        case 0 => "app_even"
        default => "app_odd"
      end,
      let event.tags = array::push(event.tags, tag)
    default => null
  end;

  event
end;

create script cleanup;
create script classify;
create script tag;

select event from in into cleanup;
select event from cleanup into classify;
select event from classify into tag;
select event from tag into out;

select event from cleanup/err into err;
select event from classify/err into err;
select event from tag/err into err;
```

---

## ✋ Task 3a: Basic Rate Limiting

Rate-Limit all events down to a maximum rate of 1 event per second, using the [`grouper::bucket`](https://docs.tremor.rs/tremor-query/operators/#grouperbucket) operator.

```sh
# validate - events should appear at much slower rate
make restart-tremor
```

Tip: You may modify the `classify` script to assign the `$class` and `$rate` meta variables that the bucket operator uses.

---

## Task 3a: Solution

```trickle
# defintion for cleanup and tag scripts redacted for length (see task 2a, 2b)

define script classify
script
  let event.class = match event of
    case %{ index_type ~= glob|applog*| } => "applog"
    case %{ index_type ~= glob|syslog*| } => "syslog"
    default => "other"
  end;

  let $class = "default";
  let $rate = 1; # 1 event per second

  event
end;

define grouper::bucket operator rate_limit;

create script cleanup;
create script classify;
create script tag;
create operator rate_limit;

select event from in into cleanup;
select event from cleanup into classify;
select event from classify into tag;
select event from tag into rate_limit;
select event from rate_limit into out;

select event from cleanup/err into err;
select event from classify/err into err;
select event from tag/err into err;
```

---

## ✋ Task 3a: Advanced Rate Limiting

Rate-limit events differently based on the value of `event.class` field (which was computed earlier):

* `applog`: 2 event per second for each application (via `application` field).
* `syslog`: 3 event per second for each host (via `syslog_hostname` field).
* `other`:  4 event per second for all other events.

```sh
# validate - events should appear at much faster rate (compared to that in 3a)
make restart-tremor
```

Tip: You may modify the `classify` script to conditionally assign the `$rate` variable that the bucket operator uses.

---

## Task 3a: Solution

```trickle
# definition for cleanup and tag scripts redacted for length (see task 2a, 2b)

define script classify
script
  let event.class = match event of
    case %{ index_type ~= glob|applog*| } => "applog"
    case %{ index_type ~= glob|syslog*| } => "syslog"
    default => "other"
  end;

  let $class = event.class;

  # we can also merge this logic with match block above
  match event.class of
    case "applog" =>
      # assumption is that application field is always present for applogs
      let $dimensions = event.application,
      let $rate = 2
    case "syslog" =>
      # assumption is that syslog_hostname field is always present for syslogs
      let $dimensions = event.syslog_hostname,
      let $rate = 3
    case "other" =>
      let $rate = 4
    default =>
      null
  end;

  event
end;

define grouper::bucket operator rate_limit;

create script cleanup;
create script classify;
create script tag;
create operator rate_limit;

select event from in into cleanup;
select event from cleanup into classify;
select event from classify into tag;
select event from tag into rate_limit;
select event from rate_limit into out;

select event from cleanup/err into err;
select event from classify/err into err;
select event from tag/err into err;
```

---

## ✋ Task 4: Linked Transport - Elastic

Send rate-limited events to Elastic via [elastic offramp](https://docs.tremor.rs/artefacts/offramps/#elastic), and investigate response events on stdout/stderr.

```sh
make start-elastic
```

---

## Task 4: Solution

```yaml
offramp:
  - id: elastic
    type: elastic
    linked: true
    config:
      nodes:
        - http://elastic:9200
  - id: es_stderr
    type: stderr
    config:
      prefix: "[ERR] "
  - id: es_stdout
    type: stdout
    config:
      prefix: "[OUT] "

binding:
  - id: intermediate_lab
  - links:
      "/onramp/placeholder/{instance}/out":
        - "/pipeline/main/{instance}/in"
      "/pipeline/main/{instance}/out":
        - "/offramp/elastic/{instance}/in"

      "/offramp/elastic/{instance}/out":
        - "/pipeline/system::passthrough/{instance}_out/in"
      "/pipeline/system::passthrough/{instance}_out/out":
        - "/offramp/es_stdout/{instance}/in"

      "/offramp/elastic/{instance}/err":
        - "/pipeline/system::passthrough/{instance}_err/in"
      "/pipeline/system::passthrough/{instance}_err/out":
        - "/offramp/es_stderr/{instance}/in"

```

---

>>>

### You made it through the lab!!!

![yeah](./assets/rickmorty.gif)

repository: tremor-rs/tremor-www-docs

repo_name: tremor-rs/tremor-www-docs


text:
---
external help file: Microsoft.VisualStudio.Setup.PowerShell.dll-Help.xml
Module Name: VSSetup
online version: https://github.com/Microsoft/vssetup.powershell/raw/master/docs/VSSetup/Select-VSSetupInstance.md
schema: 2.0.0
---

# Select-VSSetupInstance

## SYNOPSIS

Selects instances of Visual Studio and related products based on criteria.

## SYNTAX

```powershell
Select-VSSetupInstance [-Instance] <Instance[]> [-Product <String[]>] [-Require <String[]>] [-RequireAny]
 [-Version <String>] [-Latest] [<CommonParameters>]
```

## DESCRIPTION

You can specify zero or more products (by default, Visual Studio Community, Professional, and Enterprise are selected) to find, along with zero or more workloads that all are required by any instances enumerated. Additionally, you can specify a version range to limit the results or request the latest instance. All criteria are combined to return the best instance or instances for your needs.

## EXAMPLES

### Example 1

```powershell
PS C:\> Get-VSSetupInstance | Select-VSSetupInstance -Latest
```

Select the most-recently installed instance of the highest version of Visual Studio Community,
Professional, or Enterprise installed.

### Example 2

```powershell
PS C:\> Get-VSSetupInstance | Select-VSSetupInstance -Product * -Require 'Microsoft.VisualStudio.Component.VC.Tools.x86.x64'
```

Selects any product with the native Visual C++ compilers installed.

## PARAMETERS

### -Instance

One or more instances from which to select.

```yaml
Type: Instance[]
Parameter Sets: (All)
Aliases:

Required: True
Position: 0
Default value: None
Accept pipeline input: True (ByValue)
Accept wildcard characters: False
```

### -Latest

Select the most recently installed instance with the highest version (within the optional `-Version` range).

```yaml
Type: SwitchParameter
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False
```

### -Product

One or more products to select. Wildcards are supported.

```yaml
Type: String[]
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: Microsoft.VisualStudio.Product.Community, Microsoft.VisualStudio.Product.Professional, Microsoft.VisualStudio.Product.Enterprise
Accept pipeline input: False
Accept wildcard characters: False
```

### -Require

One or more workloads or components to select. All requirements specified must be met.
Wildcards are not supported.

```yaml
Type: String[]
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False
```

### -RequireAny

Change the behavior of -Require such that any one or more requirements specified must be met.

```yaml
Type: SwitchParameter
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False
```

### -Version

A version range to limit results. A single version like '15.0' is equivalent to '[15.0,)', which
means versions 15.0 and newer are in range. You can also specify versions like '[15.0,16.0)' to
limit results to Visual Studio 2017 only (15.x).

```yaml
Type: String
Parameter Sets: (All)
Aliases:

Required: False
Position: Named
Default value: None
Accept pipeline input: False
Accept wildcard characters: False
```

### CommonParameters

This cmdlet supports the common parameters: -Debug, -ErrorAction, -ErrorVariable, -InformationAction,
-InformationVariable, -OutVariable, -OutBuffer, -PipelineVariable, -Verbose, -WarningAction, and
-WarningVariable. For more information, see about_CommonParameters (http://go.microsoft.com/fwlink/?LinkID=113216).

## INPUTS

### Microsoft.VisualStudio.Setup.Instance[]

One or more instances from which to select.

## OUTPUTS

### Microsoft.VisualStudio.Setup.Instance

Zero or more instances that met specified criteria.

## NOTES

## RELATED LINKS

repository: metablaster/WindowsFirewallRuleset

gha_language: PowerShell

repo_name: metablaster/WindowsFirewallRuleset


text:
## Logging library for mql4

This is a logging library to quickly add logging capabilities to your code without much hassle. The library's default behavior matches most cases however most of the functionality can be customized using pre-processor substitutions (#define)

See the example scripts on how to use library.

**How to use**
```cpp
#include <Logger.mqh>

//+------------------------------------------------------------------+
//| Script program start function                                    |
//+------------------------------------------------------------------+
void OnStart()
  {
   DEBUG("This id debug");
   INFO("This is info");
   ERROR("This is an error");
  }
//+------------------------------------------------------------------+
```

**Customization notes**

 - The logger uses following format to print logs
```cpp
// [time, except LOGGER_PRINT,LOGGER_ALERT] [level] [prefix] [message] [last error, only Logger::Error]
```
sample output: *2021.06.08 17:35:34 | Error | OnStart | This is a test error | invalid function parameter value*

 - Use following logging functions/digits to assign them to logging levels. define as 0 if the level needs to be disabled
```cpp
#define LOGGER_PRINT    1     // print to log
#define LOGGER_ALERT    2     // trigger alert
#define LOGGER_FILE     4     // write to a file
#define LOGGER_NOTIFY   8     // send a notification
```
example:
```cpp
#define LOGGER_SET_DEBUG 0       // DEBUG is disabled
#define LOGGER_SET_INFO  1|2     // Print and alert
#define LOGGER_SET_ERROR 1|2|4   // Print, alert and file write
```

 - Customize the prefix section as follows
```cpp
#define LOGGER_PREFIX __FILE__ + " | Line:" + IntegerToString(__LINE__) // [filename] | [Line number]
```
an example prefix output will be : *with_customization.mq4 | Line:36*

 - Customize file name by a string constant or a function call
```cpp
#define LOGGER_FILENAME "backtest_debug.log"
// or
#define LOGGER_FILENAME IntegerToString(AccountNumber())
```

**Notes:**

-   ```#define``` before the Logger.mqh is included.
-   To disable a logger level set the level as zero.
-   LOGGER_NOTIFY and LOGGER_FILE execution errors are handled as a print statements. Do not customize it to use library's own error handling, the program might trigger an infinite loop or a stack overflow.


text:
# RazzMaster
Find and set up new Raspberry Pis on your network.

RazzMaster can do the following tasks:

 * scan the local network for probable Raspberry Pis
 * blink the LED on the Pi
 * report hardware and software version of the Pi
 * install packages through apt-get and node
 * setup wifi

# Installation

```
npm install -g razzmaster
razzmaster version
```

# Scan for Raspberry Pis on your network
```
razzmaster scan
```

This will scan for probable Raspberry Pis on your network using MAC addresses for common
Raspberry Pi ethernet and wifi dongles. It will print a list of every
MAC address it finds and whether it is likely to be a Raspberry Pi or not.  Sometimes
it may not find the Pi right away. If you don't see it, just run the scan again a few more times.

# Blink your Raspberry Pi

Just to make sure you are really connecting to the pi you think you are, make the
green LED blink like this:

```
razzmaster blink --host <IP_ADDRESS> --username pi --password raspberry
```

Press ctrl-C to stop it.

Note that if you do not specify a username and password Razzmaster will use the default Raspbian ones of pi/raspberry.
If you haven't changed the settings then you can leave these options off like this:

```
razzmaster blink --host <IP_ADDRESS>
```

# Get Info

To get the hardware and software versions of your Raspberry Pi

```
razzmaster info --host <IP_ADDRESS>
```

This will print the model and OS info.  On my Raspberry Pi 2 running Raspbian Jesse I get:

```
Raspberry Pi 2 Model B Rev 1.1
PRETTY_NAME="Raspbian GNU/Linux 8 (jessie)"
NAME="Raspbian GNU/Linux"
VERSION_ID="8"
VERSION="8 (jessie)"
ID=raspbian
ID_LIKE=debian
HOME_URL="http://www.raspbian.org/"
SUPPORT_URL="http://www.raspbian.org/RaspbianForums"
BUG_REPORT_URL="http://www.raspbian.org/RaspbianBugs"

Linux raspberrypi 4.1.7-v7+ #817 SMP PREEMPT Sat Sep 19 15:32:00 BST 2015 armv7l GNU/Linux
```

# Configure the Raspberry Pi:

```
razzmaster install --config config.json --host <IP_ADDRESS> --username pi --password foo
```

This command will ssh into the Raspberry Pi with the host ip address, username, and password
supplied. It will use `config.json` to decide what to install.

Your `config.json` file will look like this:

```
{
    "packages":[
        "git",
        "curl",
        "bluez",
        "bluez-hcidump",
        "nodejs"
    ],
    "git":[
        "https://github.com/joshmarinacci/amx.git"
    ]
}
```

The `packages` array is a list of Debian packages to install. The `nodejs` package is
treated special. It will install from nodesource.org instead of the regular repos.

The `git` array is a list of git repos to fetch.

### Setup Wifi

Add a 'wifi' section like this:

```json
{
   "wifi": {
       "ssid":"myrouter",
       "password":"mypassword"
   }
}
```

## Todo

* -- done -- set the wifi info
* set the hostname
* change the default users password
* configure node for proper npm -g support
* set extra/custom services to start on demand
* set x in kiosk mode with chromium
* disable starting x

## A full headless install

Yes, it is possible to start with a blank RaspberryPi and get it running on the network with your
desired configuration *without* using a directly connected screen. You'll have to flash a Raspbian image
directly to the flashcard first, since NOOBS requires a screen to use, but then you can do the rest
with RazzMaster.

first, download the raspbian image via torrent or direct download. this is a giant zip file which
regular MacOSX unzip can't handle. If you unzip it from the command line you'll get an error about

```
need PK compat. v4.5 (can do v2.1)
```

So install p7zip via brew and unzip with that.

```
brew install p7zip
7za x your_raspian_image_file.img
```

Then write the image to your SD card as described in the standard docs here

https://www.raspberrypi.org/documentation/installation/installing-images/README.md

now put the SD card in your Pi and boot it. Since it doesn't have any wifi access yet,
you'll need to boot it with wired ethernet connected to your other computer or a router.
Make sure the ethernet port is live before you boot the Pi. ex: if you are plugging the pi directly
into a port on your Mac then you'll need to turn on internet sharing so that the Pi can get an IP address
when it boots.

let it boot for about 3 minutes (pi2) since it's going to load a full desktop environment.
then run `node find`.

repository: shanawarkhan/razzmaster

repo_name: shanawarkhan/razzmaster


text:
# Changelog
-----------------------------------------

### 🛠 Breaking changes
-----------------------------------------

#### 2.0.0 — 2021-07-24
- refactor widget props see README.MD.
- expo SDK 42 Support.
- update version for some packages to stay updated.
- add option to retrieve assets Metadata (Exif, LocalUri and more...).
- add the option to send `minSelection` for default top navigator.
- add option to bind `selected` length for your custom top navigator.

#### 1.4.0 — 2021-06-03
- expo permissions package removed.
- update version for some packages to stay updated.

#### 1.3.2 — 2021-04-12
- defaultTopNavigator props changed

you now have `buttonTextStyle` and  `buttonStyle` and `midTextColor`

-buttonTextStyle - send style to design the text inside the button
-buttonStyle - send style to design the button itself
-midTextColor - send color to override middle text color

#### 1.3.1 — 2021-02-04
- add option to override selected text on default top navigator.

#### 1.3.1 — 2021-02-04
- now `options` and all fields become mandatory field.

#### 1.3.0 — 2021-02-04
- Add spinnerColor attribute

#### 1.1.0 — 2020-06-12
- Removed ['buttonBgColor','buttonTextColor','midTextColor'] props from DefaultNavigator

### 🎉 New features
-----------------------------------------
#### 2.0.0 — 2021-07-24
- expo SDK 42 Support.
- add option to retrieve assets Metadata (Exif, LocalUri and more...).
- add the option to send `minSelection` for default top navigator.
- add option to bind `selected` length for your custom top navigator.

#### 1.4.1 — 2021-04-12
-  Add `initialLoad` to define how many images to load first time.

#### 1.3.1 — 2021-04-12
-  Add selectedText to default navigator

#### 1.3.0 — 2021-02-04
-  Add Resize , Compress and Base64 Support
-  Add Expo Image Manipulator
-  Add Spinner component shows while Manipulating images.

#### 1.2.0 — 2021-01-10
-  Update dependencies to support expo 40

#### 1.1.0 — 2020-06-12

-  Add Style prop to style DefaultNavigator.
-  Add onError prop will fire whenever there is error loading Assets.

#### 1.0.7 — 2020-10-25
- You can send simple component instead of icon components ,
  to display numbers on top of the images (instead of icon)

for example:

`const SelectedIcon = ({size,index,color}: SelectedIconProps) => <Text style={{color:color,fontSize:size}}>{index + 1}</Text>`

Type should look like
`type SelectedIconProps = {
iconName:string,
color:string,
bg:string,
size:number
index:number}`

And just send this simple component on "selectedIcon" when using the widget

`selectedIcon: {
Component: SelectedIcon,
iconName: '',
color: 'white',
bg: '#ffffff90',
size: 22}`

### 🐛 Bug fixes
-----------------------------------------
#### 1.1.0 — 2020-06-12

- "after" field Parse was fixed on Expo SDK 39 , it's now working smoothly on Android and IOS.
- Fix design bug , if you had less than 4 images in total , widget center it and its looking not correct, so align-items:center removed

#### 1.0.7 — 2020-10-25

_Request from "hypnocapybara" Was Merged ([#1](https://github.com/natysoz/expo-images-picker/pull/1))
- Remove Immutable dependency

#### 1.0.6 — 2020-09-27

_Update to Expo SDK 39 is now required , they fix the issue with parse error on the "after" field

_Still they have issue with an asset that is not valid "Asset",
images that users manually put on the Gallery folder may cause the app to close without any error.

_Request from the team to help on  issue ([#10398](https://github.com/expo/expo/issues/10398))

### 🐛 Known Bugs
-----------------------------------------
* Images and Videos that users manually put on the Gallery
  can crash the app without any error especially Telegram images and videos.
  Expo Media library is very buggy.

### Upcoming
-----------------------------------------
- Add an option to select images base on albums

repository: Kazap/expo-images-picker

repo_name: Kazap/expo-images-picker


text:
# Austroclepsis B. Sahni, 1932 GENUS

#### Status
ACCEPTED

#### According to
Interim Register of Marine and Nonmarine Genera

#### Published in
New Phytologist 31: -. [270-278]

#### Original name
null

### Remarks
null

repository: mdoering/backbone

repo_name: mdoering/backbone


text:
# Car Clicker

This is a simple application built to implement the MVC architecture pattern.

The Car Clicker application is a variant of the well-known app cat clicker. Some significant differences in the Car Clicker app are:

1. No cats, only muscle cars images
2. Multiple car models listed
3. Multiple click counters
4. Only displays the car selected

![carClicker app](img/carClicker.gif)

The full license terms may be viewed in the [LICENSE](LICENSE.md)

_used in an article for @freeCodeCamp to explain the MVC architecture pattern_

repository: DaniBencz/car-clicker

repo_name: DaniBencz/car-clicker


text:
---
layout: post
category: machine_learning
title: Natural Language Processing
date: 2015-08-27
---

# Courses

**Introduction to Natural Language Processing**

- coursera: [https://www.coursera.org/learn/natural-language-processing](https://www.coursera.org/learn/natural-language-processing)

# Projects

**Automatic text summarizer: Module for automatic summarization of text documents and HTML pages**

- homepage: [https://pypi.python.org/pypi/sumy](https://pypi.python.org/pypi/sumy)
- github: [https://github.com/miso-belica/sumy](https://github.com/miso-belica/sumy)

**textacy: higher-level NLP built on spaCy**

- github: [https://github.com/chartbeat-labs/textacy](https://github.com/chartbeat-labs/textacy)
- docs: [http://textacy.readthedocs.io/en/latest/](http://textacy.readthedocs.io/en/latest/)

**Word2Vec in C++ 11**

- github: [https://github.com/jdeng/word2vec](https://github.com/jdeng/word2vec)

## Stanford NLP

**Stanford NLP**

- homepage: [http://nlp.stanford.edu/software/](http://nlp.stanford.edu/software/)

**Stanford CoreNLP – a suite of core NLP tools**

- homepage: [http://stanfordnlp.github.io/CoreNLP/index.html](http://stanfordnlp.github.io/CoreNLP/index.html)

**Head First Stanford NLP**

- (1): [http://hujiaweibujidao.github.io/blog/2016/03/30/Stanford-NLP/](http://hujiaweibujidao.github.io/blog/2016/03/30/Stanford-NLP/)
- (2): [http://hujiaweibujidao.github.io/blog/2016/03/31/Head-First-Standford-NLP-2/](http://hujiaweibujidao.github.io/blog/2016/03/31/Head-First-Standford-NLP-2/)
- (3): [http://hujiaweibujidao.github.io/blog/2016/03/31/Head-First-Standford-NLP-3/](http://hujiaweibujidao.github.io/blog/2016/03/31/Head-First-Standford-NLP-3/)
- (4): [http://hujiaweibujidao.github.io/blog/2016/04/01/Head-First-Standford-NLP-4/](http://hujiaweibujidao.github.io/blog/2016/04/01/Head-First-Standford-NLP-4/)

**Thinc: Practical Machine Learning for NLP in Python**

- intro: spaCy's Machine Learning library for NLP in Python
- github: [https://github.com/explosion/thinc](https://github.com/explosion/thinc)

# Blogs

**Natural Language Understanding by Matching Parse Trees**

- blog: [http://blog.ayoungprogrammer.com/2016/07/natural-language-understanding-by.html/](http://blog.ayoungprogrammer.com/2016/07/natural-language-understanding-by.html/)

**A Tutorial about Programming for Natural Language Processing**

- github: [https://github.com/neubig/nlptutorial](https://github.com/neubig/nlptutorial)

# Resources

**awesome-nlp: A curated list of resources dedicated to Natural Language Processing (NLP)**

- github: [https://github.com/keonkim/awesome-nlp](https://github.com/keonkim/awesome-nlp)

**A curated list of beginner resources in Natural Language Processing**

- github: [https://github.com/gutfeeling/beginner_nlp](https://github.com/gutfeeling/beginner_nlp)

gha_language: CSS