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489f0c9ce18082a7a695ffd58dcf555616da7bb6 | 1,484 | md | Markdown | questions/375-Guess-Number-Higher-or-Lower-II-Medium.md | Chad97/leetcode | d424f258b917006ddf02f6d67c2d944512498341 | [
"Apache-2.0"
] | 1 | 2020-01-17T08:19:26.000Z | 2020-01-17T08:19:26.000Z | questions/375-Guess-Number-Higher-or-Lower-II-Medium.md | Chad97/leetcode | d424f258b917006ddf02f6d67c2d944512498341 | [
"Apache-2.0"
] | null | null | null | questions/375-Guess-Number-Higher-or-Lower-II-Medium.md | Chad97/leetcode | d424f258b917006ddf02f6d67c2d944512498341 | [
"Apache-2.0"
] | null | null | null | #### 猜数字大小 II/Guess Number Higher or Lower II
**难度：** 中等/Medium
**Question：**
<p>We are playing the Guess Game. The game is as follows:</p>
<p>I pick a number from <strong>1</strong> to <strong>n</strong>. You have to guess which number I picked.</p>
<p>Every time you guess wrong, I'll tell you whether the number I picked is higher or lower.</p>
<p>However, when you guess a particular number x, and you guess wrong, you pay <b>$x</b>. You win the game when you guess the number I picked.</p>
<p><b>Example:</b></p>
<pre>
n = 10, I pick 8.
First round: You guess 5, I tell you that it's higher. You pay $5.
Second round: You guess 7, I tell you that it's higher. You pay $7.
Third round: You guess 9, I tell you that it's lower. You pay $9.
Game over. 8 is the number I picked.
You end up paying $5 + $7 + $9 = $21.
</pre>
<p>Given a particular <strong>n ≥ 1</strong>, find out how much money you need to have to guarantee a <b>win</b>.</p>
------
**题目：**
<p>我们正在玩一个猜数游戏，游戏规则如下：</p>
<p>我从 <strong>1 </strong>到 <strong>n</strong> 之间选择一个数字，你来猜我选了哪个数字。</p>
<p>每次你猜错了，我都会告诉你，我选的数字比你的大了或者小了。</p>
<p>然而，当你猜了数字 x 并且猜错了的时候，你需要支付金额为 x 的现金。直到你猜到我选的数字，你才算赢得了这个游戏。</p>
<p><strong>示例:</strong></p>
<pre>n = 10, 我选择了8.
第一轮: 你猜我选择的数字是5，我会告诉你，我的数字更大一些，然后你需要支付5块。
第二轮: 你猜是7，我告诉你，我的数字更大一些，你支付7块。
第三轮: 你猜是9，我告诉你，我的数字更小一些，你支付9块。
游戏结束。8 就是我选的数字。
你最终要支付 5 + 7 + 9 = 21 块钱。
</pre>
<p>给定 <strong>n ≥ 1，</strong>计算你至少需要拥有多少现金才能确保你能赢得这个游戏。</p>
| 26.5 | 146 | 0.672507 | eng_Latn | 0.936153 |
48a09da06d14b35b819d978dd2b303b83f884d77 | 582 | md | Markdown | services/proxy/README.md | Im-Mr-Chris/deso-game-demo | e1efdc78df470c4d842c421ce21cdf5e9ac7169e | [
"MIT"
] | 31 | 2021-08-28T01:32:45.000Z | 2022-03-23T12:08:44.000Z | services/proxy/README.md | Im-Mr-Chris/deso-game-demo | e1efdc78df470c4d842c421ce21cdf5e9ac7169e | [
"MIT"
] | 10 | 2021-09-02T21:46:23.000Z | 2022-03-30T00:32:44.000Z | services/proxy/README.md | Im-Mr-Chris/deso-game-demo | e1efdc78df470c4d842c421ce21cdf5e9ac7169e | [
"MIT"
] | 10 | 2021-08-28T02:23:42.000Z | 2022-03-29T12:02:25.000Z | # wsproxy
websocket tcp/udp proxy (based on websockify-c)
```Usage: wsproxy [options] [source_addr:]source_port
--verbose|-v verbose messages and per frame traffic
--daemon|-d become a daemon (background process)
--whitelist-hosts|-W LIST new-line separated target host whitelist file
--whitelist-ports|-P LIST new-line separated target port whitelist file
--pid|-p desired path of pid file. Default: '/var/run/websockify.pid'
```
Patch for emscripten:
https://github.com/FWGS/emscripten/commit/efcb8ecd0807c5590637812a29b4d1c7cd582719 | 34.235294 | 83 | 0.725086 | eng_Latn | 0.545721 |
48a10e959570d7ec06ef34ca48fd3f08b8b9f9f4 | 9,504 | md | Markdown | daprdocs/content/en/developing-applications/ides/vscode/vscode-how-to-debug-multiple-dapr-apps.md | apuzyrevsky/docs | 84587a4e7f8e375e01ce84ce2a20bc054a67342f | [
"MIT"
] | null | null | null | daprdocs/content/en/developing-applications/ides/vscode/vscode-how-to-debug-multiple-dapr-apps.md | apuzyrevsky/docs | 84587a4e7f8e375e01ce84ce2a20bc054a67342f | [
"MIT"
] | null | null | null | daprdocs/content/en/developing-applications/ides/vscode/vscode-how-to-debug-multiple-dapr-apps.md | apuzyrevsky/docs | 84587a4e7f8e375e01ce84ce2a20bc054a67342f | [
"MIT"
] | null | null | null | ---
type: docs
title: "How-To: Debug Dapr applications with Visual Studio Code"
linkTitle: "How-To: Debug with VSCode"
weight: 20000
description: "Learn how to configure VSCode to debug Dapr applications"
aliases:
- /developing-applications/ides/vscode/vscode-manual-configuration/
---
## Manual debugging
When developing Dapr applications, you typically use the Dapr CLI to start your daprized service similar to this:
```bash
dapr run --app-id nodeapp --app-port 3000 --dapr-http-port 3500 app.js
```
One approach to attaching the debugger to your service is to first run daprd with the correct arguments from the command line and then launch your code and attach the debugger. While this is a perfectly acceptable solution, it does require a few extra steps and some instruction to developers who might want to clone your repo and hit the "play" button to begin debugging.
If your application is a collection of microservices, each with a Dapr sidecar, it will be useful to debug them together in Visual Studio Code. This page will use the [hello world quickstart](https://github.com/dapr/quickstarts/tree/master/hello-world) to showcase how to configure VSCode to debug multiple Dapr application using [VSCode debugging](https://code.visualstudio.com/Docs/editor/debugging).
## Prerequisites
- Install the [Dapr extension]({{< ref vscode-dapr-extension.md >}}). You will be using the [tasks](https://code.visualstudio.com/docs/editor/tasks) it offers later on.
- Optionally clone the [hello world quickstart](https://github.com/dapr/quickstarts/tree/master/hello-world)
## Step 1: Configure launch.json
The file `.vscode/launch.json` contains [launch configurations](https://code.visualstudio.com/Docs/editor/debugging#_launch-configurations) for a VS Code debug run. This file defines what will launch and how it is configured when the user begins debugging. Configurations are available for each programming language in the [Visual Studio Code marketplace](https://marketplace.visualstudio.com/VSCode).
{{% alert title="Scaffold debugging configuration" color="primary" %}}
The [Dapr VSCode extension]({{< ref vscode-dapr-extension.md >}}) offers built-in scaffolding to generate `launch.json` and `tasks.json` for you.
{{< button text="Learn more" page="vscode-dapr-extension#scaffold-dapr-components" >}}
{{% /alert %}}
In the case of the hello world quickstart, two applications are launched, each with its own Dapr sidecar. One is written in Node.JS, and the other in Python. You'll notice each configuration contains a `daprd run` preLaunchTask and a `daprd stop` postDebugTask.
```json
{
"version": "0.2.0",
"configurations": [
{
"type": "pwa-node",
"request": "launch",
"name": "Nodeapp with Dapr",
"skipFiles": [
"<node_internals>/**"
],
"program": "${workspaceFolder}/app.js",
"preLaunchTask": "daprd-debug-node",
"postDebugTask": "daprd-down-node"
},
{
"type": "python",
"request": "launch",
"name": "Pythonapp with Dapr",
"program": "${workspaceFolder}/app.py",
"console": "integratedTerminal",
"preLaunchTask": "daprd-debug-python",
"postDebugTask": "daprd-down-python"
}
]
}
```
Each configuration requires a `request`, `type` and `name`. These parameters help VSCode identify the task configurations in the `.vscode/task.json` files.
- `type` defines the language used. Depending on the language, it might require an extension found in the marketplace, such as the [Python Extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python).
- `name` is a unique name for the configuration. This is used for compound configurations when calling multiple configurations in your project.
- `${workspaceFolder}` is a VS Code variable reference. This is the path to the workspace opened in VS Code.
- The `preLaunchTask` and `postDebugTask` parameters refer to the program configurations run before and after launching the application. See step 2 on how to configure these.
For more information on VSCode debugging parameters see [VS Code launch attributes](https://code.visualstudio.com/Docs/editor/debugging#_launchjson-attributes).
## Step 2: Configure task.json
For each [task](https://code.visualstudio.com/docs/editor/tasks) defined in `.vscode/launch.json` , a corresponding task definition must exist in `.vscode/task.json`.
For the quickstart, each service needs a task to launch a Dapr sidecar with the `daprd` type, and a task to stop the sidecar with `daprd-down`. The parameters `appId`, `httpPort`, `metricsPort`, `label` and `type` are required. Additional optional parameters are available, see the [reference table here](#daprd-parameter-table").
```json
{
"version": "2.0.0",
"tasks": [
{
"label": "daprd-debug-node",
"type": "daprd",
"appId": "nodeapp",
"appPort": 3000,
"httpPort": 3500,
"metricsPort": 9090
},
{
"label": "daprd-down-node",
"type": "daprd-down",
"appId": "nodeapp"
},
{
"label": "daprd-debug-python",
"type": "daprd",
"appId": "pythonapp",
"httpPort": 53109,
"grpcPort": 53317,
"metricsPort": 9091
},
{
"label": "daprd-down-python",
"type": "daprd-down",
"appId": "pythonapp"
}
]
}
```
## Step 3: Configure a compound launch in launch.json
A compound launch configuration can defined in `.vscode/launch.json` and is a set of two or more launch configurations that are launched in parallel. Optionally, a `preLaunchTask` can be specified and run before the individual debug sessions are started.
For this example the compound configuration is:
```json
{
"version": "2.0.0",
"tasks": [...],
"compounds": [
{
"name": "Node/Python Dapr",
"configurations": ["Nodeapp with Dapr","Pythonapp with Dapr"]
}
]
}
```
## Step 4: Launch your debugging session
You can now run the applications in debug mode by finding the compound command name you have defined in the previous step in the VS Code debugger:
<img src="/images/vscode-launch-configuration.png" width=400 >
You are now debugging multiple applications with Dapr!
## Daprd parameter table
Below are the supported parameters for VS Code tasks. These parameters are equivalent to `daprd` arguments as detailed in [this reference]({{< ref arguments-annotations-overview.md >}}):
| Parameter | Description | Required | Example |
|--------------|---------------|-------------|---------|
| `allowedOrigins` | Allowed HTTP origins (default "\*") | No | `"allowedOrigins": "*"`
| `appId`| The unique ID of the application. Used for service discovery, state encapsulation and the pub/sub consumer ID | Yes | `"appId": "divideapp"`
| `appMaxConcurrency` | Limit the concurrency of your application. A valid value is any number larger than 0 | No | `"appMaxConcurrency": -1`
| `appPort` | This parameter tells Dapr which port your application is listening on | Yes | `"appPort": 4000`
| `appProtocol` | Tells Dapr which protocol your application is using. Valid options are http and grpc. Default is http | No | `"appProtocol": "http"`
| `appSsl` | Sets the URI scheme of the app to https and attempts an SSL connection | No | `"appSsl": true`
| `args` | Sets a list of arguments to pass on to the Dapr app | No | "args": []
| `componentsPath` | Path for components directory. If empty, components will not be loaded. | No | `"componentsPath": "./components"`
| `config` | Tells Dapr which Configuration CRD to use | No | `"config": "./config"`
| `controlPlaneAddress` | Address for a Dapr control plane | No | `"controlPlaneAddress": "http://localhost:1366/"`
| `enableProfiling` | Enable profiling | No | `"enableProfiling": false`
| `enableMtls` | Enables automatic mTLS for daprd to daprd communication channels | No | `"enableMtls": false`
| `grpcPort` | gRPC port for the Dapr API to listen on (default “50001”) | Yes, if multiple apps | `"grpcPort": 50004`
| `httpPort` | The HTTP port for the Dapr API | Yes | `"httpPort": 3502`
| `internalGrpcPort` | gRPC port for the Dapr Internal API to listen on | No | `"internalGrpcPort": 50001`
| `logAsJson` | Setting this parameter to true outputs logs in JSON format. Default is false | No | `"logAsJson": false`
| `logLevel` | Sets the log level for the Dapr sidecar. Allowed values are debug, info, warn, error. Default is info | No | `"logLevel": "debug"`
| `metricsPort` | Sets the port for the sidecar metrics server. Default is 9090 | Yes, if multiple apps | `"metricsPort": 9093`
| `mode` | Runtime mode for Dapr (default “standalone”) | No | `"mode": "standalone"`
| `placementHostAddress` | Addresses for Dapr Actor Placement servers | No | `"placementHostAddress": "http://localhost:1313/"`
| `profilePort` | The port for the profile server (default “7777”) | No | `"profilePort": 7777`
| `sentryAddress` | Address for the Sentry CA service | No | `"sentryAddress": "http://localhost:1345/"`
| `type` | Tells VS Code it will be a daprd task type | Yes | `"type": "daprd"`
## Related Links
- [Visual Studio Code Extension Overview]({{< ref vscode-dapr-extension.md >}})
- [Visual Studio Code Debugging](https://code.visualstudio.com/docs/editor/debugging)
| 53.094972 | 402 | 0.689394 | eng_Latn | 0.919687 |
48a154ee0abb2a2d82a822ff6557969fbfa53254 | 1,126 | md | Markdown | _posts/gapreport/2021-04-03-gapreport.md | wizz13150/gapcoin-project.github.io | e5ab71856b4ddb40f1deac7656be2d14ca04a53f | [
"MIT"
] | 1 | 2021-05-01T20:49:52.000Z | 2021-05-01T20:49:52.000Z | _posts/gapreport/2021-04-03-gapreport.md | wizz13150/gapcoin-project.github.io | e5ab71856b4ddb40f1deac7656be2d14ca04a53f | [
"MIT"
] | null | null | null | _posts/gapreport/2021-04-03-gapreport.md | wizz13150/gapcoin-project.github.io | e5ab71856b4ddb40f1deac7656be2d14ca04a53f | [
"MIT"
] | 2 | 2021-03-18T05:17:21.000Z | 2021-05-20T09:07:16.000Z | ---
layout: post
author: Seth Trosis, copied over by Graham Higgins
title: PGS news for 3rd. April 2021
description: Latest news from the Mersenne Forum’s Prime Gap Search Group
date: 2021-04-03
category: primegaplist
tags: feature news gapreport psg
---
*(coped from the Mersenne Forum’s Prime Gap Search group as pertinent to Gapcoin)*
##### 2021-04-03, 00:55 [SethTro post to Mersenne Forum PSG](https://www.mersenneforum.org/showpost.php?p=575039&postcount=236)
Craig has continued with small gaps improving several hundred records <12000.
Including this new top 20 merit gap as well as many other top 100 / top 200 merit gaps.
```10470 36.3971 Craig Loizides 29052706830863*277#/30-5748```
David Stevens cleared one more gap from [#227](https://www.mersenneforum.org/showpost.php?p=571747&postcount=227)
```95278 12.1047 DStevens 9301541 * 7993#/505915410 -44226```
I (Seth) filled in even more of the #2221 primorial line
Michiel Jansen found a few more of the missing gaps < 125,000 (only 13 missing now)
*technically "more records have this year as discovery than last year" so maybe 20% fewer but IDK.*
| 36.322581 | 127 | 0.759325 | eng_Latn | 0.959117 |
48a1974c6ab9f67620b885455973b62734ae2613 | 215 | md | Markdown | api/docs/Date.toUTCString().md | miclle/qefqei | af1d5850682dbbb012a57387b591c72efc91b50b | [
"MIT"
] | 6 | 2015-01-29T04:10:41.000Z | 2019-01-24T11:36:51.000Z | api/docs/Date.toUTCString().md | miclle/qefqei | af1d5850682dbbb012a57387b591c72efc91b50b | [
"MIT"
] | null | null | null | api/docs/Date.toUTCString().md | miclle/qefqei | af1d5850682dbbb012a57387b591c72efc91b50b | [
"MIT"
] | 6 | 2015-03-26T15:16:19.000Z | 2022-02-23T00:58:37.000Z | # Date.toUTCString() _ECMAScript v1_
将Date转换为字符串（世界时）
## 摘要
date.toUTCString()
## 返回值
date的字符串表示，人们可以读取，用世界时表示。
## 描述
toUTCString()返回一个特于实现的字符串，这个字符串用世界时表示日期。
## 参阅
Date.toLocaleString()
Date.toString()
| 9.772727 | 40 | 0.72093 | yue_Hant | 0.989757 |
48a1cd00aaae8942862dfc69e1d491bee480f48d | 2,214 | md | Markdown | README.md | renecfjunior/TimerMobile | 614974737d9813f922ac3be02a836cb8a992f52a | [
"MIT"
] | 2 | 2021-09-06T16:03:46.000Z | 2021-10-04T22:23:07.000Z | README.md | renecfjunior/TimerMobile | 614974737d9813f922ac3be02a836cb8a992f52a | [
"MIT"
] | 1 | 2021-09-03T01:42:22.000Z | 2021-09-03T01:42:51.000Z | README.md | renecfjunior/TimerMobile | 614974737d9813f922ac3be02a836cb8a992f52a | [
"MIT"
] | null | null | null | <h1 align="center">
<img alt="Cronometro" title="Cronometro" src="https://user-images.githubusercontent.com/84996527/131933262-e31caacf-96b0-4450-a0fe-bbddb61c1920.png" width="220px" />
</h1>
<p align="center">Cronômetro em Java Utilizando o Android Studio</p>
<p align="center">
<a href="#tecnologias">Tecnologias</a> •
<a href="#project">Projeto</a> •
<a href="#install">Instalação</a> •
<a href="#license">Licença</a>
</p>
<br>
<p align="center">
<img alt="Page" src="https://user-images.githubusercontent.com/84996527/131934079-bab776e9-5475-44e1-92ef-b691b64207ba.JPG">
</p>
<br>
<h2 id="tecnologias" align="center">
Tecnologias :computer:
</h2>
<p align="center">
<img src="https://img.shields.io/static/v1?label=&message=JAVA&color=ff8f00&style=for-the-badge&logo=java"/>
<img src="https://img.shields.io/static/v1?label=&message=ANDROID&color=0a5a0a&style=for-the-badge&logo=android"/>
</p>
<h2 id="project" align="center">
Projeto :technologist:
</h2>
<p align="center">
• Timer com botões para Iniciar,Pausar e Reiniciar.<br>
• Ao clicar em Reiniciar o App Apresenta uma mensagem pedindo a confirmação do usuario. <br>
• O timer tem a funcionalidade de continuar rodando Ontime após o usúario sair do app sem fechá-lo.<br>
• Projeto bem simples desenvolvido com o intuito de praticar a linguagem Java. <br>
<h2 id="install" align="center">
Instalação :rocket:
</h2>
<p align="center">
Para instalar é só ir em <a href="https://github.com/renecfjunior/TimerMobile/releases">Releases</a> e selecionar a versão mais recente.<br>
Se você tiver o android studio instalado é só baixar o arquivo source code.zip e executar o projeto.<br>
Caso não tenha o android studio, disponibilizei o arquivo.apk para executar o app em seu smartphone.<br>
Para instalar é só executar o arquivo "cronometro1.0.apk" em seu smartphone e instalar.
</p>
<h2 id="license" align="center">
Licença 📝
</h2>
<p align="center">
Esse projeto está sob a licença MIT. Veja o arquivo <a href="LICENSE"> LICENSE </a> para mais detalhes.<br><br>
<a href="LICENSE"><img src="https://img.shields.io/static/v1?label=license&message=mit&color=green&style=for-the-badge&logo="/></a>
</p>
| 41 | 167 | 0.717254 | por_Latn | 0.900942 |
48a1fed87f9925c935a1b9c0bad0dcb52e975efd | 173 | md | Markdown | _themes/Dracula.md | vladimir-bebeshko/colorsublime.github.io | b05d41f46ef2ba605a1be18d3a1d705209dd7532 | [
"MIT"
] | 19 | 2018-05-07T07:37:37.000Z | 2021-12-18T23:04:16.000Z | _themes/Dracula.md | vladimir-bebeshko/colorsublime.github.io | b05d41f46ef2ba605a1be18d3a1d705209dd7532 | [
"MIT"
] | 3 | 2021-03-08T23:57:57.000Z | 2021-09-27T20:50:25.000Z | _themes/Dracula.md | vladimir-bebeshko/colorsublime.github.io | b05d41f46ef2ba605a1be18d3a1d705209dd7532 | [
"MIT"
] | 11 | 2017-11-19T00:27:05.000Z | 2021-05-09T15:39:23.000Z | ---
Author: "zenorocha"
Description: "https://github.com/zenorocha/dracula-theme"
FileName: "Dracula.tmTheme"
ID: "Dracula"
Title: "Dracula"
layout: theme
---
| 19.222222 | 59 | 0.66474 | zul_Latn | 0.312301 |
48a217b879832676fcb5b4ef4c026007dfe69a4b | 4,737 | md | Markdown | doc/functions.md | arthurpaulino/lean4 | 8f83c7ab32c765897b8184fcbfe53f2a1d933bcc | [
"Apache-2.0"
] | null | null | null | doc/functions.md | arthurpaulino/lean4 | 8f83c7ab32c765897b8184fcbfe53f2a1d933bcc | [
"Apache-2.0"
] | null | null | null | doc/functions.md | arthurpaulino/lean4 | 8f83c7ab32c765897b8184fcbfe53f2a1d933bcc | [
"Apache-2.0"
] | null | null | null | # Functions
Functions are the fundamental unit of program execution in any programming language.
As in other languages, a Lean function has a name, can have parameters and take arguments, and has a body.
Lean also supports functional programming constructs such as treating functions as values,
using unnamed functions in expressions, composition of functions to form new functions,
curried functions, and the implicit definition of functions by way of
the partial application of function arguments.
You define functions by using the `def` keyword followed by its name, a parameter list, return type and its body.
The parameter list consists of successive parameters that are separated by spaces.
You can specify an explicit type for each parameter.
If you do not specify a specific argument type, the compiler tries to infer the type from the function body.
An error is returned when it cannot be inferred.
The expression that makes up the function body is typically a compound expression consisting of a number of expressions
that culminate in a final expression that is the return value.
The return type is a colon followed by a type and is optional.
If you do not specify the type of the return value explicitly,
the compiler tries to determine the return type from the final expression.
```lean
def f x := x + 1
```
In the previous example, the function name is `f`, the argument is `x`, which has type `Nat`,
the function body is `x + 1`, and the return value is of type `Nat`.
The following example defines the factorial recursive function using pattern matching.
```lean
def fact x :=
match x with
| 0 => 1
| n+1 => (n+1) * fact n
#eval fact 100
```
By default, Lean only accepts total functions. The `partial` keyword should be used when Lean cannot
establish that a function always terminates.
```lean
partial def g (x : Nat) (p : Nat -> Bool) : Nat :=
if p x then
x
else
g (x+1) p
#eval g 0 (fun x => x > 10)
```
In the previous example, `g x p` only terminates if there is a `y >= x` such that `p y` returns `true`.
Of course, `g 0 (fun x => false)` never terminates.
# Lambda expressions
A lambda expression is an unnamed function.
You define lambda expressions by using the `fun` keyword. A lambda expression resembles a function definition, except that instead of the `:=` token,
the `=>` token is used to separate the argument list from the function body. As in a regular function definition,
the argument types can be inferred or specified explicitly, and the return type of the lambda expression is inferred from the type of the
last expression in the body.
```lean
def twice (f : Nat -> Nat) (x : Nat) : Nat :=
f (f x)
#eval twice (fun x => x + 1) 3
#eval twice (fun (x : Nat) => x * 2) 3
#eval List.map (fun x => x + 1) [1, 2, 3]
-- [2, 3, 4]
#eval List.map (fun (x, y) => x + y) [(1, 2), (3, 4)]
-- [3, 7]
```
# Syntax sugar for simple lambda expressions
Simple functions can be defined using parentheses and `·` as a placeholder.
```lean
#check (· + 1)
-- fun a => a + 1
#check (2 - ·)
-- fun a => 2 - a
#eval [1, 2, 3, 4, 5].foldl (· * ·) 1
-- 120
def h (x y z : Nat) :=
x + y + z
#check (h · 1 ·)
-- fun a b => h a 1 b
#eval [(1, 2), (3, 4), (5, 6)].map (·.1)
-- [1, 3, 5]
```
In the previous example, the term `(·.1)` is syntax sugar for `fun x => x.1`.
# Pipelining
Pipelining enables function calls to be chained together as successive operations. Pipelining works as follows:
```lean
def add1 x := x + 1
def times2 x := x * 2
#eval times2 (add1 100)
#eval 100 |> add1 |> times2
#eval times2 <| add1 <| 100
```
The result of the previous `#eval` commands is 202.
The forward pipeline `|>` operator takes a function and an argument and return a value.
In contrast, the backward pipeline `<|` operator takes an argument and a function and returns a value.
These operators are useful for minimizing the number of parentheses.
```lean
def add1Times3FilterEven (xs : List Nat) :=
List.filter (· % 2 == 0) (List.map (· * 3) (List.map (· + 1) xs))
#eval add1Times3FilterEven [1, 2, 3, 4]
-- [6, 12]
-- Define the same function using pipes
def add1Times3FilterEven' (xs : List Nat) :=
xs |> List.map (· + 1) |> List.map (· * 3) |> List.filter (· % 2 == 0)
#eval add1Times3FilterEven' [1, 2, 3, 4]
-- [6, 12]
```
Lean also supports the operator `|>.` which combines forward pipeline `|>` operator with the `.` field notation.
```lean
-- Define the same function using pipes
def add1Times3FilterEven'' (xs : List Nat) :=
xs.map (· + 1) |>.map (· * 3) |>.filter (· % 2 == 0)
#eval add1Times3FilterEven'' [1, 2, 3, 4]
-- [6, 12]
```
For users familiar with the Haskell programming language,
Lean also supports the notation `f $ a` for the backward pipeline `f <| a`.
| 35.088889 | 149 | 0.691577 | eng_Latn | 0.997926 |
48a25a387827d835bee28de775efe0638c4cc6e0 | 137 | md | Markdown | setup/installWin10.md | austin-2018/PiTempBackgroundApplication1 | 1bebc2340bc9994b6abb5c2b57e97c4c0e2f58ca | [
"Apache-2.0"
] | null | null | null | setup/installWin10.md | austin-2018/PiTempBackgroundApplication1 | 1bebc2340bc9994b6abb5c2b57e97c4c0e2f58ca | [
"Apache-2.0"
] | null | null | null | setup/installWin10.md | austin-2018/PiTempBackgroundApplication1 | 1bebc2340bc9994b6abb5c2b57e97c4c0e2f58ca | [
"Apache-2.0"
] | null | null | null | #### How to install Windows 10 IoT Core on Raspberry Pi 3
#### https://www.windowscentral.com/how-install-windows-10-iot-raspberry-pi-3
| 45.666667 | 77 | 0.737226 | yue_Hant | 0.643493 |
48a3022cae720a47e2dbeadf7c9ef19dec15221f | 4,261 | md | Markdown | products/logs/src/content/get-started/enable-destinations/s3-compatible-endpoints/index.md | 343guiltyspark/cloudflare-docs | ace34e0b88b4a488b75d3250b1576f55886299d1 | [
"MIT"
] | null | null | null | products/logs/src/content/get-started/enable-destinations/s3-compatible-endpoints/index.md | 343guiltyspark/cloudflare-docs | ace34e0b88b4a488b75d3250b1576f55886299d1 | [
"MIT"
] | null | null | null | products/logs/src/content/get-started/enable-destinations/s3-compatible-endpoints/index.md | 343guiltyspark/cloudflare-docs | ace34e0b88b4a488b75d3250b1576f55886299d1 | [
"MIT"
] | 1 | 2021-09-19T21:48:24.000Z | 2021-09-19T21:48:24.000Z | ---
order: 56
pcx-content-type: how-to
---
# Enable S3-compatible endpoints
Cloudflare Logpush supports pushing logs to S3-compatible destinations via the Cloudflare dashboard or via API, including:
* [Digital Ocean Spaces](https://www.digitalocean.com/docs/spaces/)
* [Backblaze B2](https://www.backblaze.com/b2/docs/s3_compatible_api.html)
* [Alibaba Cloud OSS](https://www.alibabacloud.com/help/doc-detail/64919.htm#title-37m-7gl-xy2)
* [JD Cloud Object Storage Service](https://docs.jdcloud.com/en/object-storage-service/introduction-2)
* [Oracle Cloud Object Storage](https://docs.cloud.oracle.com/en-us/iaas/Content/Object/Tasks/s3compatibleapi.htm)
* [Linode Object Storage](https://www.linode.com/products/object-storage/)
* On-premise [Ceph Object Gateway](https://docs.ceph.com/en/latest/radosgw/s3/)
For more information about Logpush and the current production APIs, see the [Cloudflare Logpush](/get-started/) documentation.
## Manage via the Cloudflare dashboard
Enable Logpush to S3-compatible destinations via the [Cloudflare dashboard](/get-started/logpush-dashboard/).
## Manage via API
To set up S3-compatible endpoints:
1. Create a job with the appropriate endpoint URL and authentication parameters.
2. Enable the job to begin pushing logs.
See below for detailed instructions.
<Aside type="note" header="Note">
Unlike Logpush jobs to Amazon S3, there is no ownership challenge with S3-compatible APIs.
</Aside>
## 1. Create a job
To create a job, make a `POST` request to the Logpush jobs endpoint with the following fields:
* `name` (optional) - Use your domain name as the job name.
* `destination_conf` - A log destination consisting of an endpoint name, bucket name, bucket path, region, access-key-id, and secret-access-key in the following string format:
```bash
"s3://<BUCKET-NAME>/<BUCKET-PATH>?region=<REGION>&access-key-id=<ACCESS-KEY-ID>&secret-access-key=<SECRET-ACCESS-KEY>&endpoint=<ENDPOINT-URL>"
```
<Aside type="note" header="Note">
`<ENDPOINT-URL>` is the url without the bucket name or path. Example: `endpoint=sfo2.digitaloceanspaces.com`
</Aside>
* `dataset` - the category of logs you want to receive; either `http_requests` (default), `spectrum_events` or `firewall_events`
* `logpull_options` (optional) - To configure fields, sample rate, and timestamp format, see [Logpush API options](/get-started/logpush-configuration-api/understanding-logpush-api#options)
Example request using cURL:
```bash
curl -s -X POST \
https://api.cloudflare.com/client/v4/zones/<ZONE_ID>/logpush/jobs \
-d '{"name":"<DOMAIN_NAME>",
"destination_conf":"s3://<BUCKET-NAME>/<BUCKET-PATH>?region=<REGION>&access-key-id=<ACCESS-KEY-ID>&secret-access-key=<SECRET-ACCESS-KEY>&endpoint=<ENDPOINT-URL>", "logpull_options":"fields=RayID,EdgeStartTimestamp×tamps=rfc3339", "dataset":"http_requests"}' | jq .
```
Response:
```json
{
"errors": [],
"messages": [],
"result": {
"id": 100,
"dataset": "http_requests",
"enabled": false,
"name": "<DOMAIN_NAME>",
"logpull_options": "fields=RayID,EdgeStartTimestamp×tamps=rfc3339",
"destination_conf": "s3://<BUCKET-NAME>/<BUCKET-PATH>?region=<REGION>&access-key-id=<ACCESS-KEY-ID>&secret-access-key=<SECRET-ACCESS-KEY>&endpoint=<ENDPOINT-URL>",
"last_complete": null,
"last_error": null,
"error_message": null
},
"success": true
}
```
## 2. Enable (update) a job
To enable a job, make a `PUT` request to the Logpush jobs endpoint. You’ll use the job ID returned from the previous step in the URL, and send `{"enabled": true}` in the request body.
Example request using cURL:
```bash
curl -s -X PUT \
https://api.cloudflare.com/client/v4/zones/<ZONE_ID>/logpush/jobs/100 -d'{"enabled":true}' | jq .
```
Response:
```json
{
"errors": [],
"messages": [],
"result": {
"id": 100,
"dataset": "http_requests",
"enabled": true,
"name": "<DOMAIN_NAME>",
"logpull_options": "fields=RayID,EdgeStartTimestamp×tamps=rfc3339",
"destination_conf": "s3://<BUCKET-NAME>/<BUCKET-PATH>?region=<REGION>&access-key-id=<ACCESS-KEY-ID>&secret-access-key=<SECRET-ACCESS-KEY>&endpoint=<ENDPOINT-URL>",
"last_complete": null,
"last_error": null,
"error_message": null
},
"success": true
}
```
| 36.732759 | 269 | 0.721192 | eng_Latn | 0.282385 |
48a38ea3e26f648695c172d14a174f54b0435389 | 341 | md | Markdown | README.md | Aidiakapi/advent-of-code-2016 | f02d8041594ac99a317588ef64866c66141166ef | [
"Unlicense"
] | null | null | null | README.md | Aidiakapi/advent-of-code-2016 | f02d8041594ac99a317588ef64866c66141166ef | [
"Unlicense"
] | null | null | null | README.md | Aidiakapi/advent-of-code-2016 | f02d8041594ac99a317588ef64866c66141166ef | [
"Unlicense"
] | null | null | null | # Advent of Code 2016
My solutions for [Advent of Code 2016](https://adventofcode.com/2016) written in Rust.
Run specify day: `cargo run -- dayXX` or `cargo test -- dayXX`
Run all days (optimized): `cargo run --release`
Uses a procedural macro and unorthodox `pub use` to significantly reduce the amount of boilerplate code necessary.
| 37.888889 | 114 | 0.744868 | eng_Latn | 0.968625 |
48a4de37d339731d3ee1f13db9b2dca752d8ed80 | 2,556 | md | Markdown | docs/odbc/reference/develop-app/row-status-array.md | v-brlaz/sql-docs | 5d902e328b551bb619fd95106ce3d320a8fdfbe9 | [
"CC-BY-4.0",
"MIT"
] | 1 | 2019-02-06T20:12:14.000Z | 2019-02-06T20:12:14.000Z | docs/odbc/reference/develop-app/row-status-array.md | v-brlaz/sql-docs | 5d902e328b551bb619fd95106ce3d320a8fdfbe9 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | docs/odbc/reference/develop-app/row-status-array.md | v-brlaz/sql-docs | 5d902e328b551bb619fd95106ce3d320a8fdfbe9 | [
"CC-BY-4.0",
"MIT"
] | 1 | 2020-12-22T22:24:34.000Z | 2020-12-22T22:24:34.000Z | ---
title: "Row Status Array | Microsoft Docs"
ms.custom: ""
ms.date: "01/19/2017"
ms.prod: "sql"
ms.prod_service: "drivers"
ms.service: ""
ms.component: "odbc"
ms.reviewer: ""
ms.suite: "sql"
ms.technology:
- "drivers"
ms.tgt_pltfrm: ""
ms.topic: "article"
helpviewer_keywords:
- "row status array [ODBC]"
- "cursors [ODBC], block"
- "result sets [ODBC], row status array"
- "block cursors [ODBC]"
- "result sets [ODBC], block cursors"
- "rowset status [ODBC]"
ms.assetid: 4b69f189-2722-4314-8a02-f4ffecd6dabd
caps.latest.revision: 5
author: "MightyPen"
ms.author: "genemi"
manager: craigg
ms.workload: "Inactive"
---
# Row Status Array
In addition to data, **SQLFetch** and **SQLFetchScroll** can return an array that gives the status of each row in the rowset. This array is specified through the SQL_ATTR_ROW_STATUS_PTR statement attribute. This array is allocated by the application and must have as many elements as are specified by the SQL_ATTR_ROW_ARRAY_SIZE statement attribute. The values in the array are set by **SQLBulkOperations**, **SQLFetch**, **SQLFetchScroll**, and **SQLSetPos.** The values describe the status of the row and whether that status has changed since it was last fetched.
|Row status array value|Description|
|----------------------------|-----------------|
|SQL_ROW_SUCCESS|The row was successfully fetched and has not changed since it was last fetched.|
|SQL_ROW_SUCCESS_WITH_INFO|The row was successfully fetched and has not changed since it was last fetched. However, a warning was returned about the row.|
|SQL_ROW_ERROR|An error occurred while fetching the row.|
|SQL_ROW_UPDATED|The row was successfully fetched and has been updated since it was last fetched. If the row is fetched again or refreshed by **SQLSetPos**, its status is changed to the new status.<br /><br /> Some drivers cannot detect changes to data and therefore cannot return this value. To determine whether a driver can detect updates to refetched rows, an application calls **SQLGetInfo** with the SQL_ROW_UPDATES option.|
|SQL_ROW_DELETED|The row has been deleted since it was last fetched.|
|SQL_ROW_ADDED|The row was inserted by **SQLBulkOperations**. If the row is fetched again or is refreshed by **SQLSetPos**, its status is SQL_ROW_SUCCESS.<br /><br /> This value is not set by **SQLFetch** or **SQLFetchScroll**.|
|SQL_ROW_NOROW|The rowset overlapped the end of the result set, and no row was returned that corresponded to this element of the row status array.|
| 62.341463 | 568 | 0.729656 | eng_Latn | 0.995997 |
48a59483b5a6c9603e11ad72cde6d6f1e6142b5f | 2,320 | md | Markdown | dynamicsax2012-technet/pol-create-a-credit-correction-for-packing-slip-ledger-postings-during-sales-invoice-posting.md | s0pach/DynamicsAX2012-technet | 8412306681e6b914ebcfad0a9ee05038474ef1e6 | [
"CC-BY-4.0",
"MIT"
] | 1 | 2020-06-16T22:06:04.000Z | 2020-06-16T22:06:04.000Z | dynamicsax2012-technet/pol-create-a-credit-correction-for-packing-slip-ledger-postings-during-sales-invoice-posting.md | s0pach/DynamicsAX2012-technet | 8412306681e6b914ebcfad0a9ee05038474ef1e6 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | dynamicsax2012-technet/pol-create-a-credit-correction-for-packing-slip-ledger-postings-during-sales-invoice-posting.md | s0pach/DynamicsAX2012-technet | 8412306681e6b914ebcfad0a9ee05038474ef1e6 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | ---
title: (POL) Create a credit correction for packing slip ledger postings during sales invoice posting
TOCTitle: (POL) Create a credit correction for packing slip ledger postings during sales invoice posting
ms:assetid: 3f2ac0a7-75c5-4c78-860f-c542dea3001e
ms:mtpsurl: https://technet.microsoft.com/library/JJ678180(v=AX.60)
ms:contentKeyID: 49386904
author: Khairunj
ms.date: 04/18/2014
mtps_version: v=AX.60
audience: Application User
ms.search.region: Poland
---
# (POL) Create a credit correction for packing slip ledger postings during sales invoice posting
_**Applies To:** Microsoft Dynamics AX 2012 R3, Microsoft Dynamics AX 2012 R2_
For a sales order, you can post a packing slip for credit correction in the **Posting packing slip** form. The posted packing slip is reversed when the invoice is posted as a correction transaction.
> [!NOTE]
> <P>This topic has not been fully updated for Microsoft Dynamics AX 2012 R2.</P>
1. Click **Accounts receivable** \> **Common** \> **Sales orders** \> **All sales orders**. On the **Action Pane**, in the **New** group, click **Sales order**.
2. On the **Sales order** form, click the **Pick and pack** tab.
3. On the **Pick and pack** tab, on the **Action Pane** in the **Generate** group, click **Packing slip**.
4. On the **Packing slip posting** form, on the **Other** tab, select the **Credit correction** check box to do the following:
- Reverse a debit transaction by adding a minus debit transaction to the Packing slip ledger account on the **Posting** form for **Inventory and warehouse management**. (Click **Inventory management** \> **Setup** \> **Posting** \> **Posting**. On the **Sales order** tab, select the **Packing slip** option.) For more information see [Posting (form)](https://technet.microsoft.com/library/aa551718\(v=ax.60\)).
- Reverse a credit transaction by adding a minus credit transaction to the Packing slip offset ledger account on the **Posting** form for **Inventory and warehouse management**. (Click **Inventory management** \> **Setup** \> **Posting** \> **Posting**. On the **Sales order** tab, select the **Packing slip offset** option.) For more information see [Posting (form)](https://technet.microsoft.com/library/aa551718\(v=ax.60\)).
5. Click **OK** to post the invoice.
| 52.727273 | 433 | 0.718534 | eng_Latn | 0.851156 |
48a5b08067ded661a0a84bba50f75dca66f2a822 | 153 | md | Markdown | _project/francesca.md | rumnamanya/rumnamanya.github.io | 2deadeff04c8a48cf683b885b7fa6ab9acc1d9d9 | [
"MIT"
] | null | null | null | _project/francesca.md | rumnamanya/rumnamanya.github.io | 2deadeff04c8a48cf683b885b7fa6ab9acc1d9d9 | [
"MIT"
] | null | null | null | _project/francesca.md | rumnamanya/rumnamanya.github.io | 2deadeff04c8a48cf683b885b7fa6ab9acc1d9d9 | [
"MIT"
] | null | null | null | ---
layout: project_single
title: "Francesca"
slug: "francesca"
parent: "junk-garden-ideas"
---
yard art Francesca by pete@eastbaywilds.com, via Flickr | 21.857143 | 56 | 0.745098 | eng_Latn | 0.469007 |
48a605e0092d41eee6b41e6d78ff2dd6d45653d4 | 4,578 | md | Markdown | server-2013/lync-server-2013-location-trend-report.md | MicrosoftDocs/OfficeDocs-SkypeforBusiness-Test-pr.de-de | 41875522f81c5db6dcade5cfdece0ecb9bb5a10b | [
"CC-BY-4.0",
"MIT"
] | 1 | 2020-05-19T19:28:03.000Z | 2020-05-19T19:28:03.000Z | server-2013/lync-server-2013-location-trend-report.md | MicrosoftDocs/OfficeDocs-SkypeforBusiness-Test-pr.de-de | 41875522f81c5db6dcade5cfdece0ecb9bb5a10b | [
"CC-BY-4.0",
"MIT"
] | 36 | 2018-04-26T15:58:54.000Z | 2018-08-23T00:35:22.000Z | server-2013/lync-server-2013-location-trend-report.md | MicrosoftDocs/OfficeDocs-SkypeforBusiness-Test-pr.de-de | 41875522f81c5db6dcade5cfdece0ecb9bb5a10b | [
"CC-BY-4.0",
"MIT"
] | 13 | 2018-05-29T23:18:03.000Z | 2021-11-15T11:23:43.000Z | ---
title: Standort-Trendbericht
TOCTitle: Standort-Trendbericht
ms:assetid: 61e2db3c-9f10-4411-8e7e-c6950faf8533
ms:mtpsurl: https://technet.microsoft.com/de-de/library/JJ204941(v=OCS.15)
ms:contentKeyID: 49294182
ms.date: 05/19/2016
mtps_version: v=OCS.15
ms.translationtype: HT
---
# Standort-Trendbericht
_**Letztes Änderungsdatum des Themas:** 2015-03-09_
Der Standort-Trendbericht enthält Angaben über den Verlauf der Anrufqualität für Netzwerkstandorte.
## Filter
Mithilfe von Filtern können Sie eine bestimmte Untermenge von Daten zurückgeben oder zurückgegebene Daten anders anzeigen lassen. So können Sie zum Beispiel im Standort-Trendbericht die zurückgegebenen Daten nach Aspekten wie dem Zugriffstyp (d. h. interner oder externer Zugriff) oder dem Netzwerktyp (verkabelt oder Funk) filtern. Sie können auch festlegen, wie Daten gruppiert werden sollen. In diesem Fall werden die Anrufe nach Stunde, Tag oder Woche gruppiert.
In der folgenden Tabelle sind die Filter aufgeführt, die Sie beim Standort-Trendbericht verwenden können.
### Filter im Standort-Trendbericht
<table>
<colgroup>
<col style="width: 50%" />
<col style="width: 50%" />
</colgroup>
<thead>
<tr class="header">
<th>Name</th>
<th>Beschreibung</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><p><strong>Von</strong></p></td>
<td><p>Anfangsdatum und -uhrzeit für den Zeitraum. Wenn die Daten nach Stunden angezeigt werden sollen, geben Sie Anfangsdatum und -uhrzeit wie folgt ein:</p>
<p>07.07.2012 13:00 Uhr</p>
<p>Wenn Sie keinen Anfangszeitpunkt eingeben, beginnt der Bericht automatisch am angegebenen Tag um 12:00 Uhr. Zum Anzeigen der Daten nach Tag geben Sie nur das Datum ein:</p>
<p>07.07.2012</p>
<p>Sollen die Daten nach Woche oder Monat angezeigt werden, geben Sie irgendein Datum ein, das in die anzuzeigende Woche oder den anzuzeigenden Monat fällt (Sie müssen nicht den ersten Tag der Woche oder des Monats eingeben):</p>
<p>03.07.2012</p>
<p>Eine Woche läuft immer von Sonntag bis einschließlich Samstag.</p></td>
</tr>
<tr class="even">
<td><p><strong>Bis</strong></p></td>
<td><p>Enddatum und -uhrzeit für den Zeitraum. Wenn die Daten nach Stunden angezeigt werden sollen, geben Sie Enddatum und -uhrzeit wie folgt ein:</p>
<p>07.07.2012 13:00 Uhr</p>
<p>Wenn Sie keinen Endzeitpunkt eingeben, endet der Bericht automatisch am angegebenen Tag um 12:00 Uhr. Zum Anzeigen der Daten nach Tag geben Sie nur das Datum ein:</p>
<p>07.07.2012</p>
<p>Sollen die Daten nach Woche oder Monat angezeigt werden, geben Sie irgendein Datum ein, das in die anzuzeigende Woche oder den anzuzeigenden Monat fällt (Sie müssen nicht den ersten Tag der Woche oder des Monats eingeben):</p>
<p>03.07.2012</p>
<p>Eine Woche läuft immer von Sonntag bis einschließlich Samstag.</p></td>
</tr>
<tr class="odd">
<td><p><strong>Intervall</strong></p></td>
<td><p>Zeitintervall. Wählen Sie eine der folgenden Optionen aus:</p>
<ul>
<li><p>Stündlich (maximal 25 Stunden können angezeigt werden)</p></li>
<li><p>Täglich (maximal 31 Tage können angezeigt werden)</p></li>
<li><p>Wöchentlich (maximal 12 Wochen können angezeigt werden)</p></li>
</ul>
<p>Wenn mit dem angegebenen Start- und Endzeitpunkt die maximale Anzahl der zulässigen Werte für das ausgewählte Intervall überschritten wird, wird nur die maximale Anzahl an Werten (beginnend mit dem Startzeitpunkt) angezeigt. Beispiel: Wenn Sie das Intervall "Täglich" mit dem Startdatum 01.01.2011 und dem Enddatum 28.02.2011 ausgewählt haben, werden Daten für die Tage 01.08.2011 12:00 Uhr bis 01.09.2011 12:00 Uhr angezeigt (d. h. Daten für insgesamt 31 Tage).</p></td>
</tr>
<tr class="even">
<td><p><strong>Zugriffstyp</strong></p></td>
<td><p>Gibt an, ob der Client am internen oder am externen Netzwerk angemeldet wurde, als der Anruf getätigt wurde. Wählen Sie eine der folgenden Optionen aus:</p>
<ul>
<li><p>[Alle]</p></li>
<li><p>Intern</p></li>
<li><p>Extern</p></li>
</ul></td>
</tr>
<tr class="odd">
<td><p><strong>Netzwerktyp</strong></p></td>
<td><p>Gibt den Typ des Netzwerks an, mit dem der Client verbunden wurde, als der Anruf erfolgte. Wählen Sie eine der folgenden Optionen aus:</p>
<ul>
<li><p>[Alle]</p></li>
<li><p>Verkabelt</p></li>
<li><p>Funk</p></li>
</ul></td>
</tr>
<tr class="even">
<td><p><strong>VPN</strong></p></td>
<td><p>Gibt an, ob ein externer Client eine VPN-Verbindung (Virtual Private Network) verwendete, als der Anruf getätigt wurde. Wählen Sie eine der folgenden Optionen aus:</p>
<ul>
<li><p>[Alle]</p></li>
<li><p>VPN</p></li>
<li><p>Nicht-VPN</p></li>
</ul></td>
</tr>
</tbody>
</table>
| 45.78 | 484 | 0.738969 | deu_Latn | 0.994358 |
48a618f32bb79fc213634b7d7aec3aee2f0c7735 | 22,524 | md | Markdown | container/centos7/README.md | fmadio/public | ebcb9c85f1bac1ec2b1c58370e9f2696f2d28b0d | [
"MIT"
] | 3 | 2022-02-05T04:43:33.000Z | 2022-03-07T22:05:41.000Z | container/centos7/README.md | fmadio/public | ebcb9c85f1bac1ec2b1c58370e9f2696f2d28b0d | [
"MIT"
] | 81 | 2016-03-09T07:39:10.000Z | 2016-10-26T06:49:43.000Z | container/centos7/README.md | fmadio/issues | ebcb9c85f1bac1ec2b1c58370e9f2696f2d28b0d | [
"MIT"
] | 1 | 2022-03-07T22:05:21.000Z | 2022-03-07T22:05:21.000Z | # CentOS 7 FMADIO LXC Container
Reference CentOS 7 FMADIO LXC Continer for use on FMADIO Packet Capture Systems.
The image has a minimial setup of
- GCC / build essentials
- basic networking tools
- fmadio platform checkout (https://github.com/fmadio/platform)
# Install
Download/Checkout the LXC Image file onto the FMADIO Packet Capture host system.
Extract the contents of the tarball "fmadio_lxc_centos7.9.tar.gz"
Into /opt/fmadio/lxc/ running as sudo or root, example below
```
root@fmadioMAG-290:/# cd /opt/fmadio/lxc/
root@fmadioMAG-290:/mnt/store0/lxc/lib/lxc#
root@fmadioMAG-290:/mnt/store0/lxc/lib/lxc# tar xfzv /mnt/store0/git/public/container/centos7/fmadio_lxc_centos7.9.tar.gz
centos7/
centos7/config
centos7/rootfs/
centos7/rootfs/sbin
centos7/rootfs/tmp/
centos7/rootfs/tmp/.font-unix/
centos7/rootfs/tmp/.X11-unix/
centos7/rootfs/tmp/.ICE-unix/
centos7/rootfs/tmp/.Test-unix/
centos7/rootfs/tmp/.XIM-unix/
centos7/rootfs/srv/
centos7/rootfs/var/
centos7/rootfs/var/.updated
centos7/rootfs/var/tmp/
centos7/rootfs/var/gopher/
centos7/rootfs/var/mail
centos7/rootfs/var/db/
centos7/rootfs/var/db/Makefile
centos7/rootfs/var/db/sudo/
centos7/rootfs/var/db/sudo/lectured/
centos7/rootfs/var/db/sudo/lectured/fmadio
centos7/rootfs/var/empty/
centos7/rootfs/var/empty/sshd/
centos7/rootfs/var/cache/
centos7/rootfs/var/cache/ldconfig/
centos7/rootfs/var/cache/ldconfig/aux-cache
centos7/rootfs/var/cache/yum/
centos7/rootfs/var/cache/yum/x86_64/
centos7/rootfs/var/cache/yum/x86_64/7/
centos7/rootfs/var/cache/yum/x86_64/7/timedhosts.txt
centos7/rootfs/var/cache/yum/x86_64/7/timedhosts
centos7/rootfs/var/cache/yum/x86_64/7/.gpgkeyschecked.yum
centos7/rootfs/var/cache/yum/x86_64/7/extras/
centos7/rootfs/var/cache/yum/x86_64/7/extras/mirrorlist.txt
centos7/rootfs/var/cache/yum/x86_64/7/extras/gen/
centos7/rootfs/var/cache/yum/x86_64/7/extras/gen/primary_db.sqlite
centos7/rootfs/var/cache/yum/x86_64/7/extras/cachecookie
centos7/rootfs/var/cache/yum/x86_64/7/extras/db1c88508275ffebdc6cd8686da08745d2552e5b219b2e6f4cbde7b8afd3b1a3-primary.sqlite.bz2
centos7/rootfs/var/cache/yum/x86_64/7/extras/repomd.xml
centos7/rootfs/var/cache/yum/x86_64/7/extras/packages/
centos7/rootfs/var/cache/yum/x86_64/7/updates/
centos7/rootfs/var/cache/yum/x86_64/7/updates/mirrorlist.txt
centos7/rootfs/var/cache/yum/x86_64/7/updates/gen/
centos7/rootfs/var/cache/yum/x86_64/7/updates/gen/primary_db.sqlite
centos7/rootfs/var/cache/yum/x86_64/7/updates/cachecook
.
.
.
.
.
.
centos7/rootfs/usr/bin/glib-compile-schemas
centos7/rootfs/selinux/
centos7/rootfs/selinux/enforce
centos7/rootfs/run/
centos7/rootfs/run/blkid/
centos7/rootfs/.autorelabel
centos7/rootfs/proc/
centos7/rootfs/bin
centos7/rootfs/mnt/
root@fmadioMAG-290:/mnt/store0/lxc/lib/lxc#
root@fmadioMAG-290:/mnt/store0/lxc/lib/lxc#
root@fmadioMAG-290:/mnt/store0/lxc/lib/lxc#
root@fmadioMAG-290:/mnt/store0/lxc/lib/lxc# ls -al centos7/
total 16
drwxrwx--- 3 root root 4096 Jan 30 11:47 .
drwxr-xr-x 6 root root 4096 Jan 30 13:21 ..
-rw-r--r-- 1 root root 856 Jan 30 11:47 config
drwxr-xr-x 18 root root 4096 Jan 16 16:00 rootfs
root@fmadioMAG-290:/mnt/store0/lxc/lib/lxc#
```
# Networking
By default FMADIO uses virtual ethernet bridged networking, this allows the container to be utilized as a full standalone linux system running off a different IP, even tho its running in paralel and simultaniously on the FMADIO Packet Capture hardware. Network topology is shown below
### Host System
In the above diagram the FMADIO Packet Capture system running on as Host (baremetal) uses the virtual ethernet bridge "man0" with a static IP of 192.168.1.10/24 This interface is the general management used for FMADIO GUI, SSH etc to operate the core FMADIO Packet Capture System.
### Container 0
In additionm the above diagram has "CentOS LXC Container 0" which is a virtualized (Using LXC) CentOS image running on the FMAD Packet Capture Hardware. It also uses the virtual ethernet bridge "man0" for connectivity and has its ethernet interface configured for 192.168.1.11/24
### Container 1
Siliarly a 2nd "CentOS LXC Container 1" image is also running on the FMADIO Packet Capture Hardware, also using the virtual ethernet bridge "man0" with a static IP of 192.168.1.12/24
### Topology
All these interfaces utilize the "man0" virtual ethernet bridge, meaning while they share the same physical network interface "phy0" they all have unique and seperate IP addresse on the 192.168.1.0/24 network. From an external server it appears they are 3 seperate systems.
While this example usses "man0" with physical network interface "phy0" a 1G RJ45 socket. This can be applied to the 10G/40G physical network interfaces "phy10" and "phy11" for higher management interface bandwidth.
## Config
The FMADIO Host interface is configured using
```
/opt/fmadio/etc/network.lua
```
For details see our user documentation [docs.fmad.io](https://docs.fmad.io/fmadio-documentation/configuration/network-configuration-cli)
The containers network configuration by default is the static IP address is 192.168.1.10/24 Gateway 192.168.1.1
LXC Config is located in
```
/opt/fmadio/lxc/centos7/config
```
Default config is as follows
```
# Distribution configuration
lxc.include = /usr/share/lxc/config/centos.common.conf
lxc.arch = x86_64
# Container specific configuration
lxc.rootfs.path = dir:/opt/fmadio/lxc/centos7/rootfs
lxc.uts.name = centos7
# Network configuration
lxc.net.0.type = veth
lxc.net.0.link = man0
lxc.net.0.flags = up
lxc.net.0.ipv4.address = 192.168.1.11
lxc.net.0.ipv4.gateway = 192.168.1.1
# map passthru queue
lxc.mount.entry = /opt/fmadio/queue/lxc_ring0 opt/fmadio/queue/lxc_ring0 none bind,create=file 0 0
```
In addition the CentOS 7 network configuration file is located in
```
/opt/fmadio/lxc/centos7/rootfs/etc/sysconfig/network-scripts/ifcfg-eth0
```
Default configuration is as follows
```
DEVICE=eth0
BOOTPROTO=none
ONBOOT=yes
HOSTNAME=centos
NM_CONTROLLED=no
TYPE=Ethernet
MTU=
IPADDR=192.168.1.11
PREFIX=24
GATEWAY=192.168.1.1
DNS1=192.168.1.1
```
To change the static IP address please update both files appropriately
# Running
Booting the container use the following command
```
sudo lxc-start -n centos7
```
then attach to the console as follows
```
sudo lxc-attach -n centos7
```
This will drop to a shell allowing further configuration and customization.
Example shown below
```
root@fmadioMAG-290:# lxc-start -n centos7
root@fmadioMAG-290:# lxc-attach -n centos7
root@centos7:/# ifconfig
eth0: flags=4163<UP,BROADCAST,RUNNING,MULTICAST> mtu 1500
inet 192.168.2.206 netmask 255.255.255.0 broadcast 192.168.2.255
inet6 fe80::f05a:98ff:fe56:9928 prefixlen 64 scopeid 0x20<link>
ether f2:5a:98:56:99:28 txqueuelen 1000 (Ethernet)
RX packets 48 bytes 15088 (14.7 KiB)
RX errors 0 dropped 0 overruns 0 frame 0
TX packets 13 bytes 916 (916.0 B)
TX errors 0 dropped 0 overruns 0 carrier 0 collisions 0
lo: flags=73<UP,LOOPBACK,RUNNING> mtu 65536
inet 127.0.0.1 netmask 255.0.0.0
inet6 ::1 prefixlen 128 scopeid 0x10<host>
loop txqueuelen 1000 (Local Loopback)
RX packets 0 bytes 0 (0.0 B)
RX errors 0 dropped 0 overruns 0 frame 0
TX packets 0 bytes 0 (0.0 B)
TX errors 0 dropped 0 overruns 0 carrier 0 collisions 0
root@centos7:/#
```
# Container Packet Capture
The CentOS image has a version of the FMADIO Platform installed, its recommened to get the latest version using GIT.
```
root@centos7:~# cd /opt/fmadio/platform/
root@centos7:/opt/fmadio/platform# git pull
Already up-to-date.
root@centos7:/opt/fmadio/platform#
```
Packets can then be captured using the tool "fmadio2pcap" which is fully opensource, this utility is used as a minimial code example on how to receive and process packets within a container.
Full code is here [https://github.com/fmadio/platform/blob/main/fmadio2pcap/main.c](https://github.com/fmadio/platform/blob/main/fmadio2pcap/main.c)
## Process Historical Capture
**Execute FMADIO Host**
First step is to start the FMADIO Packet Capture Tx Path. This has full flow control ensuring there are Zero Packet drops. On the host system find the capture file to send to the container and run
```
sudo stream_cat -v <full capture name to replay> --ring /opt/fmadio/queue/lxc_ring1
```
Example output as follows
```
fmadio@fmadio20v3-287:$ sudo stream_cat -v <full capture name to replay> --ring /opt/fmadio/queue/lxc_ring0
outputting to FMAD Ring [/opt/fmadio/queue/lxc_ring0j
Ring size : 10489868 16777216
Ring Version: 100 100
RING: Put:5638
RING: Get:5638
0M Offset: 0GB ChunkID:65417929 TS:00:00:14.506.442.653 | Pending 10665 MB 1.007Gbps 0.414Mpps CPUIdle:0.000 CPUFetch:0.137 CPUSend:0.000
1M Offset: 1GB ChunkID:65423026 TS:01:02:05.528.618.296 | Pending 9391 MB 10.550Gbps 1.068Mpps CPUIdle:0.000 CPUFetch:0.174 CPUSend:0.000
2M Offset: 2GB ChunkID:65428016 TS:01:53:07.401.746.274 | Pending 8144 MB 10.332Gbps 1.038Mpps CPUIdle:0.000 CPUFetch:0.150 CPUSend:0.000
3M Offset: 3GB ChunkID:65433020 TS:02:23:40.771.210.710 | Pending 6892 MB 10.365Gbps 0.990Mpps CPUIdle:0.000 CPUFetch:0.155 CPUSend:0.000
4M Offset: 4GB ChunkID:65437915 TS:03:00:17.830.519.599 | Pending 5669 MB 10.110Gbps 1.086Mpps CPUIdle:0.000 CPUFetch:0.288 CPUSend:0.000
.
.
.
.
```
**Execute Container**
On the container, run the command in the /opt/fmadio/platform/fmadio2pcap directory to start the Rx Path
```
sudo ./fmadio2pcap -i /opt/fmadio/queue/lxc_ring0 | tcpdump -r - -nn | head -n 100
```
Example output as below
```
[fmadio@centos7 fmadio2pcap]$ cd /opt/fmadio/platform/fmadio2pcap
[fmadio@centos7 fmadio2pcap]$ sudo ./fmadio2pcap -i /opt/fmadio/queue/lxc_ring0 | tcpdump -r - -nn | head -n 100
fmadio2pcap
FMAD Ring [/opt/fmadio/queue/lxc_ring0]
Ring size : 10489868 10489868 16777216
Ring Version: 100 100
RING: Put:4d93
RING: Get:4d93
reading from file -, link-type EN10MB (Ethernet)
00:11:08.562510 IP 192.168.2.65.46666 > 192.168.2.205.30464: Flags [.], seq 2377520938:2377522386, ack 3714236327, win 229, options [nop,nop,TS val 3075767777 ecr 3394241810], length 1448
00:11:08.562523 IP 192.168.2.65.46666 > 192.168.2.205.30464: Flags [.], seq 1448:2896, ack 1, win 229, options [nop,nop,TS val 3075767777 ecr 3394241810], length 1448
00:11:08.562529 IP 192.168.2.205.30464 > 192.168.2.65.46666: Flags [.], ack 4294944128, win 10578, options [nop,nop,TS val 3394241810 ecr 3075767777], length 0
00:11:08.562535 IP 192.168.2.65.46666 > 192.168.2.205.30464: Flags [.], seq 2896:4344, ack 1, win 229, options [nop,nop,TS val 3075767777 ecr 3394241810], length 1448
00:11:08.562547 IP 192.168.2.65.46666 > 192.168.2.205.30464: Flags [.], seq 4344:5792, ack 1, win 229, options [nop,nop,TS val 3075767777 ecr 3394241810], length 1448
.
.
.
.
```
We use tcpdump for example purposes, the utlity fmadio2pcap outputs a standard PCAP with Nanosecond timestamps. Any application that uses this format will work
## Process Live Capture
Recommend using a 1sec flush period to ensure data gets delivered at a regular interval. Otherwise the frequency of when data is seen depends on the link activity.
(Setting 1sec flush interval)[https://docs.fmad.io/fmadio-documentation/configuration/capture-pipeline-flush#flushperiod]
Example setting (/opt/fmadio/etc/time.lua)
```
["Capture"] =
{
["FlushPktCnt"] = 2000,
["FlushPeriod"] = 1e9,
["FlushIdle"] = 0,
},
```
Start the packet capture system
**Execute FMADIO Host**
```
fmadio@fmadio20v3-287:$ sudo stream_cat -v --follow --ring /opt/fmadio/queue/lxc_ring0
stream_cat: follow mode
outputting to FMAD Ring [/opt/fmadio/queue/lxc_ring0j
Ring size : 10489868 16777216
Ring Version: 100 100
RING: Put:942d96
RING: Get:942d96
0M Offset: 0GB ChunkID:65468565 TS:00:00:00.000.000.000 | Pending 21 MB 0.000Gbps 0.000Mpps CPUIdle:0.000 CPUFetch:0.787 CPUSend:0.000
0M Offset: 0GB ChunkID:65468631 TS:00:00:00.000.000.000 | Pending 8 MB 0.022Gbps 0.003Mpps CPUIdle:0.981 CPUFetch:0.006 CPUSend:0.000
0M Offset: 0GB ChunkID:65468637 TS:09:58:01.151.885.306 | Pending 8 MB 0.008Gbps 0.001Mpps CPUIdle:0.998 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65468645 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.999 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65468660 TS:09:58:04.680.546.967 | Pending 8 MB 0.007Gbps 0.001Mpps CPUIdle:0.998 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65468683 TS:09:58:09.057.469.788 | Pending 10 MB 0.015Gbps 0.002Mpps CPUIdle:0.997 CPUFetch:0.001 CPUSend:0.000
0M Offset: 0GB ChunkID:65468710 TS:09:58:10.382.692.610 | Pending 8 MB 0.040Gbps 0.004Mpps CPUIdle:0.995 CPUFetch:0.002 CPUSend:0.000
0M Offset: 0GB ChunkID:65468716 TS:09:58:10.393.894.920 | Pending 8 MB 0.012Gbps 0.001Mpps CPUIdle:0.998 CPUFetch:0.000 CPUSend:0.000
.
.
.
.
```
**Execute Container**
```
[fmadio@centos7 fmadio2pcap]$ cd /opt/fmadio/platform/fmadio2pcap
[fmadio@centos7 fmadio2pcap]$ sudo ./fmadio2pcap -i /opt/fmadio/queue/lxc_ring0 | tcpdump -r - -nn | head
fmadio2pcap
FMAD Ring [/opt/fmadio/queue/lxc_ring0]
Ring size : 10489868 10489868 16777216
Ring Version: 100 100
RING: Put:953f66
RING: Get:953f66
reading from file -, link-type EN10MB (Ethernet)
09:59:36.377127 IP 192.168.2.130 > 192.168.2.125: ICMP echo request, id 3256, seq 5820, length 64
09:59:36.377157 IP 192.168.2.125 > 192.168.2.130: ICMP echo reply, id 3256, seq 5820, length 64
09:59:36.378684 IP 210.193.124.58.991 > 124.120.36.246.22599: Flags [.], seq 1452:2904, ack 1, win 1783, length 1452
09:59:36.378697 IP 210.193.124.58.991 > 124.120.36.246.22599: Flags [.], seq 2904:4356, ack 1, win 1783, length 1452
09:59:36.378709 IP 210.193.124.58.991 > 124.120.36.246.22599: Flags [.], seq 4356:5808, ack 1, win 1783, length 1452
09:59:36.378721 IP 210.193.124.58.991 > 124.120.36.246.22599: Flags [.], seq 5808:7260, ack 1, win 1783, length 1452
.
.
.
.
```
The data will ebb and flow based on the traffic volume. The processing is always fully lossless with thoughput based on how fast the Container software can recevied/process the data. Tcpdump is pretty slow so the thoughput wont be too high.
## Process Filtered Live Capture
In addition to Live data capture, filtering of the data before it gets sent to the Container is possible using standard BPF filters. The following example output uses the BPF filter "arp" to filter and only send ARP requests to the container.
**Execute FMADIO Host**
```
fmadio@fmadio20v3-287:$ sudo stream_cat -v --follow --ring /opt/fmadio/queue/lxc_ring0 --bpf "arp"
stream_cat: follow mode
outputting to FMAD Ring [/opt/fmadio/queue/lxc_ring0j
BPF Filter [arp]
Using Filename [asdf_20220130_0957]
Ring size : 10489868 16777216
Ring Version: 100 100
RING: Put:954430
RING: Get:954430
0M Offset: 0GB ChunkID:65470683 TS:00:00:00.000.000.000 | Pending 21 MB 0.000Gbps 0.000Mpps CPUIdle:0.000 CPUFetch:0.764 CPUSend:0.000
0M Offset: 0GB ChunkID:65470741 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.996 CPUFetch:0.002 CPUSend:0.000
0M Offset: 0GB ChunkID:65470748 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.998 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65470752 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.999 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65470757 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.999 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65470761 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.999 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65470766 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.999 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65470772 TS:10:04:37.644.451.695 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.998 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65470777 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.999 CPUFetch:0.000 CPUSend:0.000
0M Offset: 0GB ChunkID:65470781 TS:00:00:00.000.000.000 | Pending 8 MB 0.000Gbps 0.000Mpps CPUIdle:0.999 CPUFetch:0.000 CPUSend:0.000
.
.
.
.
.
```
**Execute Container**
```
[fmadio@centos7 fmadio2pcap]$ cd /opt/fmadio/platform/fmadio2pcap
[fmadio@centos7 fmadio2pcap]$ sudo ./fmadio2pcap -i /opt/fmadio/queue/lxc_ring0 | tcpdump -r - -nn
fmadio2pcap
FMAD Ring [/opt/fmadio/queue/lxc_ring0]
Ring size : 10489868 10489868 16777216
Ring Version: 100 100
RING: Put:9543f0
RING: Get:9543f0
reading from file -, link-type EN10MB (Ethernet)
10:03:05.468490 ARP, Request who-has 192.168.2.130 tell 192.168.2.73, length 50
10:03:05.468558 ARP, Reply 192.168.2.130 is-at 00:16:3e:bc:a1:6f, length 50
10:03:08.380996 ARP, Request who-has 192.168.2.130 tell 192.168.2.125, length 50
10:03:08.381030 ARP, Reply 192.168.2.130 is-at 00:16:3e:bc:a1:6f, length 50
10:03:11.860161 ARP, Request who-has 192.168.2.65 tell 192.168.2.130, length 50
10:03:11.860189 ARP, Reply 192.168.2.65 is-at 30:9c:23:df:f0:5f, length 50
10:03:12.548218 ARP, Request who-has 192.168.2.223 tell 192.168.2.130, length 50
10:03:12.548381 ARP, Reply 192.168.2.223 is-at 18:c0:4d:b4:0e:72, length 50
.
.
.
.
.
.
```
# Container Performance
## Container Forwarding 64B packets
The following is 10Gbps 64B line rate packet capture file, post capture forwarded into the container
The forwarding speed is ~ 3.1Gbps @ 6.1Mpps
NOTE: The processing bottleneck is all per packet overhead, not data throughput limited
```
fmadio@fmadio20v3-287:/mnt/store0/git/platform_20220120_rc1/include$ sudo stream_cat -v test64_20220120_1906 --ring /opt/fmadio/queue/lxc_ring0 --cpu 29
outputting to FMAD Ring [/opt/fmadio/queue/lxc_ring0j
stream_cat CPU Affinity: 29
Ring Version: 100 100
RING: Put:2243c0a
RING: Get:2243c0a
0M Offset: 0GB ChunkID:64466562 TS:10:07:05.413.425.671 | Pending 76314 MB 0.771Gbps 1.505Mpps CPUIdle:0.000 CPUFetch:0.085 CPUSend:0.000
6M Offset: 0GB ChunkID:64468447 TS:10:07:05.838.281.925 | Pending 75843 MB 3.162Gbps 6.174Mpps CPUIdle:0.000 CPUFetch:0.068 CPUSend:0.000
12M Offset: 0GB ChunkID:64470333 TS:10:07:06.263.363.566 | Pending 75371 MB 3.163Gbps 6.176Mpps CPUIdle:0.000 CPUFetch:0.064 CPUSend:0.000
18M Offset: 1GB ChunkID:64472219 TS:10:07:06.688.445.233 | Pending 74900 MB 3.164Gbps 6.178Mpps CPUIdle:0.000 CPUFetch:0.062 CPUSend:0.000
24M Offset: 1GB ChunkID:64474105 TS:10:07:07.113.526.867 | Pending 74428 MB 3.164Gbps 6.178Mpps CPUIdle:0.000 CPUFetch:0.061 CPUSend:0.000
30M Offset: 1GB ChunkID:64475993 TS:10:07:07.539.059.284 | Pending 73956 MB 3.166Gbps 6.182Mpps CPUIdle:0.000 CPUFetch:0.060 CPUSend:0.000
37M Offset: 2GB ChunkID:64477881 TS:10:07:07.964.591.727 | Pending 73484 MB 3.167Gbps 6.184Mpps CPUIdle:0.000 CPUFetch:0.058 CPUSend:0.000
43M Offset: 2GB ChunkID:64479769 TS:10:07:08.390.124.144 | Pending 73012 MB 3.166Gbps 6.182Mpps CPUIdle:0.000 CPUFetch:0.057 CPUSend:0.000
49M Offset: 2GB ChunkID:64481657 TS:10:07:08.815.656.574 | Pending 72540 MB 3.166Gbps 6.182Mpps CPUIdle:0.000 CPUFetch:0.058 CPUSend:0.000
55M Offset: 3GB ChunkID:64483545 TS:10:07:09.241.188.984 | Pending 72068 MB 3.167Gbps 6.183Mpps CPUIdle:0.000 CPUFetch:0.057 CPUSend:0.000
61M Offset: 3GB ChunkID:64485433 TS:10:07:09.666.721.414 | Pending 71596 MB 3.166Gbps 6.183Mpps CPUIdle:0.000 CPUFetch:0.056 CPUSend:0.000
68M Offset: 4GB ChunkID:64487321 TS:10:07:10.092.253.838 | Pending 71124 MB 3.167Gbps 6.183Mpps CPUIdle:0.000 CPUFetch:0.057 CPUSend:0.000
74M Offset: 4GB ChunkID:64489209 TS:10:07:10.517.786.255 | Pending 70652 MB 3.166Gbps 6.182Mpps CPUIdle:0.000 CPUFetch:0.056 CPUSend:0.000
80M Offset: 4GB ChunkID:64491093 TS:10:07:10.942.417.133 | Pending 70181 MB 3.160Gbps 6.171Mpps CPUIdle:0.000 CPUFetch:0.055 CPUSend:0.000
86M Offset: 5GB ChunkID:64492971 TS:10:07:11.365.695.677 | Pending 69712 MB 3.150Gbps 6.150Mpps CPUIdle:0.000 CPUFetch:0.056 CPUSend:0.000
.
.
.
```
And running on the Container, piping the data to /dev/null as a benchmark
```
[fmadio@centos7 fmadio2pcap]$ sudo ./fmadio2pcap -i /opt/fmadio/queue/lxc_ring0 --cpu 30 > /dev/null
fmadio2pcap
FMAD Ring [/opt/fmadio/queue/lxc_ring0]
setting cpu affinity
Ring size : 10489868 10489868 16777216
Ring Version: 100 100
RING: Put:2243c0a
RING: Get:2243c0a
.
.
```
## Container Forwarding Mixed packets
Following is performance thoughput test using real world traffic, with mixed packet size going to 1500MTU
Thoughput is ~ 17Gbps or so @ 1.8Mpps
On the Host
```
fmadio@fmadio20v3-287:/mnt/store0/git/platform_20220120_rc1/include$ sudo stream_cat -v fmadio20v3-287_20220130_0000 --ring /opt/fmadio/queue/lxc_ring0 --cpu 29
outputting to FMAD Ring [/opt/fmadio/queue/lxc_ring0j
stream_cat CPU Affinity: 29
Ring size : 10489868 16777216
Ring Version: 100 100
RING: Put:3dbf060a
RING: Get:3dbf060a
0M Offset: 0GB ChunkID:65417929 TS:00:00:14.506.442.653 | Pending 10665 MB 1.179Gbps 0.485Mpps CPUIdle:0.000 CPUFetch:0.110 CPUSend:0.000
1M Offset: 1GB ChunkID:65426046 TS:01:28:59.437.696.294 | Pending 8636 MB 16.803Gbps 1.692Mpps CPUIdle:0.000 CPUFetch:0.251 CPUSend:0.000
3M Offset: 4GB ChunkID:65434754 TS:02:48:14.220.858.936 | Pending 6459 MB 18.020Gbps 1.818Mpps CPUIdle:0.000 CPUFetch:0.216 CPUSend:0.000
5M Offset: 6GB ChunkID:65443512 TS:03:04:20.921.455.321 | Pending 4270 MB 18.111Gbps 1.931Mpps CPUIdle:0.000 CPUFetch:0.200 CPUSend:0.000
7M Offset: 8GB ChunkID:65451887 TS:05:03:51.200.697.429 | Pending 2176 MB 17.270Gbps 2.286Mpps CPUIdle:0.000 CPUFetch:0.184 CPUSend:0.000
9M Offset: 10GB ChunkID:65460574 TS:05:26:24.511.380.279 | Pending 4 MB 17.960Gbps 1.941Mpps CPUIdle:0.000 CPUFetch:0.197 CPUSend:0.000
.
.
```
And the same /dev/null forwarding in the Container for benchmarking purposes.
```
[fmadio@centos7 fmadio2pcap]$ sudo ./fmadio2pcap -i /opt/fmadio/queue/lxc_ring0 --cpu 30 > /dev/null
fmadio2pcap
FMAD Ring [/opt/fmadio/queue/lxc_ring0]
setting cpu affinity
Ring size : 10489868 10489868 16777216
Ring Version: 100 100
RING: Put:2243c0a
RING: Get:2243c0a
.
.
```
| 40.078292 | 284 | 0.745116 | eng_Latn | 0.371942 |
48a6fee5a5c50231aacf79986dfc7a80043dc49a | 1,447 | md | Markdown | TheAssignment.md | dautermann/500pxDemoBrowser | ab12cef2e3b92f1ee542e6a0329cce7d9141326e | [
"MIT"
] | null | null | null | TheAssignment.md | dautermann/500pxDemoBrowser | ab12cef2e3b92f1ee542e6a0329cce7d9141326e | [
"MIT"
] | null | null | null | TheAssignment.md | dautermann/500pxDemoBrowser | ab12cef2e3b92f1ee542e6a0329cce7d9141326e | [
"MIT"
] | null | null | null | ## A Photo app using the 500px API
Process:
- *This should take about 2 hours for the basics, and up to a day for the Nice to Haves*
- *You will be working in a new Swift 2.0 Xcode project.*
- *Skip 3rd-party libraries, so you would not need Carthage or Cocoapods.*
- *make meaningful commits*
- *write unit tests if they make sense*
- *include a README.md detailing any thoughts, issues, comments etc. you would like to communicate*
- *reply with a zipped copy of the repo, or a link to a remote repo*
Develop an app that parses the JSON from [this](https://api.500px.com/v1/photos?feature=popular&consumer_key=vW8Ns53y0F57vkbHeDfe3EsYFCatTJ3BrFlhgV3W) endpoint, and presents the encoded photos in a `UITableView` with cells set up like this:
i.e., show the photo, the photo's title, the user's thumbnail, and the user's name.
(API documentation is [here](https://github.com/500px/api-documentation/blob/master/endpoints/photo/GET_photos.md))
- tapping on a cell shows a detail view with the photo
- add paging to the detail view
- add search filtering for `title`
## Nice to haves
- support paging for the endpoint (see `current_page`, `total_pages`). As the user scrolls to the end, load more photos.
- instead of table view, use `UICollectionView`
- custom animations. E.g., animate in photo cells one by one
| 46.677419 | 240 | 0.75812 | eng_Latn | 0.992552 |
48a75308265c70b44764d1dab0abd087bcf0a8bc | 399 | md | Markdown | source/_posts/were-not-dead-just-working-on-tcp.md | Tox-Archive/Tox-blog | 9303a830bd36f675efc1a7e7d77b879dce6fb499 | [
"Apache-2.0"
] | 1 | 2015-11-20T16:01:28.000Z | 2015-11-20T16:01:28.000Z | source/_posts/were-not-dead-just-working-on-tcp.md | Tox-Archive/Tox-blog | 9303a830bd36f675efc1a7e7d77b879dce6fb499 | [
"Apache-2.0"
] | null | null | null | source/_posts/were-not-dead-just-working-on-tcp.md | Tox-Archive/Tox-blog | 9303a830bd36f675efc1a7e7d77b879dce6fb499 | [
"Apache-2.0"
] | null | null | null | title: "We're Not Dead; Just Working on TCP"
id: 261
categories:
- Tox Core
date: 2014-05-04 18:09:18
tags:
---
Just for those who may be worried that there haven't been any commits to the master branch in a few days, irungentoo and others are all making commits to the TCP branch of the GitHub repository. You can view our progress [here.](https://github.com/irungentoo/ProjectTox-Core/tree/TCP) | 44.333333 | 284 | 0.756892 | eng_Latn | 0.993667 |
48a78c7899bf44734f33bc69af510d6950e39daf | 11,851 | md | Markdown | CHANGELOG.md | phlipper/chef-datadog | 5f8e2615cdc76dadf7672ee5f91d2c1debfb15d5 | [
"Apache-2.0"
] | null | null | null | CHANGELOG.md | phlipper/chef-datadog | 5f8e2615cdc76dadf7672ee5f91d2c1debfb15d5 | [
"Apache-2.0"
] | null | null | null | CHANGELOG.md | phlipper/chef-datadog | 5f8e2615cdc76dadf7672ee5f91d2c1debfb15d5 | [
"Apache-2.0"
] | null | null | null | Changes
=======
# 2.0.0 / 2014-08-22
* **BREAKING CHANGE**: Datadog Agent 5.0.0 Release Edition
With the release of Datadog Agent 5.x, all Python dependencies are now bundled, and extensions for monitoring are no
longer needed. Integration-specific recipes no longer install any packages, so if you are using a version older than
5.x, you may have to install these yourself. This greatly simplifies deployment of all components for monitoring.
See commit b77582122f3db774a838f90907b421e544dd099c for the exact package resources that have been removed.
Affected recipes:
- hdfs
- memcache
- mongodb
- mysql
- postgres
- redisdb
* **BREAKING CHANGE**: Removed chef_gem support for Chef versions pre 0.10.9.
We haven't supported this version of Chef in some time, so it's unlikely that you will be affected at all.
Just in case, please review what versions of Chef you have installed, and use an older version of this cookbook until
you can upgrade them.
* [OPTIMIZE] Update repository recipe to choose correct arch, [@remh][]
* [OPTIMIZE] Remove conditional python dep for Ubuntu 11.04, [@miketheman][]
* [OPTIMIZE] Remove extra `apt-get` call during Agent recipe run, [@miketheman][]
* [FEATURE] Add `kafka` monitoring recipe & tests, [#113][] [@qqfr2507][]
* [FEATURE] Allow database name to be passed into postgres template, [@miketheman][]
* [MISC] Many updates to testing suite. Faster style, better specs. [@miketheman][]
# 1.2.0 / 2014-03-24
* [FEATURE] Add `relations` parameter to Postgres check config, [#97][] [@miketheman][]
* [FEATURE] Add `sock` parameter to MySQL check configuration, [#105][] [@thisismana][]
* [FEATURE] Add more parameters to the haproxy templte to collect status metrics, [#103][] [@evan2645][] & [@miketheman][]
* [FEATURE] `datadog::mongo` recipe now installs `pymongo` and prerequisites, [#81][] [@dwradcliffe][]
* [FEATURE] Allow attribute control over whether to allow the local Agent to handle non-local traffic, [#100][] [@coosh][]
* [FEATURE] Allow attribute control over whether the Chef Handler is activated, [#95][] [@jedi4ever][], [@miketheman][]
* [FEATURE] Allow attribute control over whether Agent should be running, [#94][] [@jedi4ever][], [@miketheman][]
* [FEATURE] Reintroduce attribute config for dogstatsd daemon, [#90][] [@jedi4ever][], [@miketheman][]
* [FEATURE] Allow jmx template to accept arbitrary `key, value` statements, [#93][] [@clofresh][]
* [FEATURE] Allow cassandra/zookeeper templates to accept arbitrary `key, value` statements, [@miketheman][]
* [FEATURE] Add name param to varnish recipe, [#86][] [@clofresh][]
* [FEATURE] Allow attribute-driven settings for web proxy, [#82][] [@antonio-osorio][]
* [FEATURE] Allow override of Agent config for hostname via attribute, [#76][] [@ryandjurovich][]
* [FEATURE] Allow for non-conf.d integrations to be set via attributes, [#66][] [@babbottscott][]
* [FEATURE] added hdfs recipe and template, [#77][] [@phlipper][]
* [FEATURE] added zookeeper recipe and template, [#74][] [@phlipper][]
* [BUGFIX] Warn user when more than one `network` instance is defined, [#98][] [@miketheman][]
* [BUGFIX] Properly indent jmx template, [#88][] [@flah00][]
* [BUGFIX] Handle unrecognized Python version strings in a better fashion, [#79][] [#80][] [#84][], [@jtimberman][], [@schisamo][], [@miketheman][]
* [BUGFIX] Set gpgcheck to false for `yum` repo if it exists, [#89][] [@alexism][], [#101][] [@nkts][]
* [MISC] Inline doc for postgres recipe, [#83][] [@timusg][]
# 1.1.1 / 2013-10-17
* [FEATURE] added rabbitmq recipe and template, [@miketheman][]
* [BUGFIX] memcache dependencies and template, [#67][] [@elijahandrews][]
* [BUGFIX] redis python client check was not properly checking the default version, [@remh][]
* [MISC] tailor 1.3.1 caught some cosmetic issue, [@alq][]
# 1.1.0 / 2013-08-20
* [FEATURE] Parameterize chef-handler-datadog Gem version, [#60][] [@mfischer-zd][]
* [FEATURE] Allow control of `network.yaml` via attributes, [#63][] [@JoeDeVries][]
* [FEATURE] Use Python version from Ohai to determine packages to install, [#65][] [@elijahandrews][]
* [BUGFIX] redisdb default port in template should be 6379, [#59][] [@miketheman][]
* [BUGFIX] templates creating empty `tags` in config when unspecified for multiple integrations [#61][] [@alq][]
* [MISC] updated tests [@elijahandrews][], [@miketheman][]
* [MISC] correct the riak integration example, [@miketheman][]
* [MISC] updated CHANGELOG.md style, [@miketheman][]
#### Dependency Note
One of the dependencies of this cookbook is the `apt` cookbook.
A change introduced in the `apt` cookbook 2.0.0 release was a Chef 11-specific feature that would break on any Chef 10 system, so we considered adding a restriction in our `metadata.rb` to anything below 2.0.0.
A fix has gone in to `apt` 2.1.0 that relaxes this condition, and plays well with both Chef 10 and 11. We recommend using this version, or higher.
# 1.0.1 / 2013-05-14
* Fixed iis and rabbitmq template syntax - [#58][] [@gregf][]
* Updated style/spacing in ActiveMQ template
* Updated test suite to validate cookbook & templates
* Updated chefignore to clean the built cookbook from containing cruft
# 1.0.0 / 2013-05-06
* **BREAKING CHANGE**: Moved all attributes into `datadog` namespace - [#46][] ([#23][], [#26][])
Reasoning behind this was that originally we attempted to auto-detect many common attributes and deploy automatic monitoring for them.
We found that since inclusion of the `datadog` cookbook early in the run list caused the compile phase to be populated with our defaults (mostly `nil`), instead of the desired target, and namespacing of the attributes became necessary.
* **NEW PROVIDER**: Added a new `datadog_monitor` provider for integration use
The new provider is used in many pre-provided integration recipes, such as `datadog::apache`.
This enables a run list to include this recipe, as well as populate a node attribute with the needed instance details to monitor the given service
* Updated dependencies in Gemfile, simplifies travis build - [#34][], [#55][]
* Much improved test system (chefspec, test-kitchen) - [#35][] & others
* Tests against multiple versions of Chef - [#18][]
* Added language-specific recipes for installing `dogstatsd` - ([#28][])
* Added ability to control `dogstatsd` from agent config via attribute - [#27][]
* Placed the `dogstatsd` log file in `/var/log/` instead of `/tmp`
* Added attribute to configure dogstreams in `datadog.conf` - [#37][]
* Updated for `platform_family` semantics
* Added `node['datadog']['agent_version']` attribute
* (Handler Recipe) Better handling of EC2 instance ID for Handler - [#44][]
* Updated for agent 3.6.x logging syntax
* Generated config file removes some whitespace - [#56][]
* Removed dependency on `yum::epel`, only uses `yum` for the `repository` recipe
# 0.1.4 / 2013-04-25
* Quick fix for backporting test code to support upload in ruby 1.8.7
# 0.1.3 / 2013-01-27
* Work-around for COOK-2171
# 0.1.2 / 2012-10-15
* Fixed typo in jmx section
# 0.1.1 / 2012-09-18
* Added support for postgres, redis & memcached
* `dd-agent` - updated to include more platforms
* `dd-handler` - updated to leverage `chef_gem` resource if available
* Updated copyright for 2012
* Updated syntax for node attribute accessors
* Some syntax styling fixes
* Added agent logging configuration
* Removed extraneous dependencies
* Added automated testing suite
# 0.0.12
* Updated for CentOS dependencies
# 0.0.11
* Link to github repository.
# 0.0.10
* `dd-handler` - Corrects attribute name.
# 0.0.9
* `dd-agent` - Adds an explicit varnish attribute.
# 0.0.8
* `dd-agent` - Add varnish support.
# 0.0.7
* `dd-agent` - default to using instance IDs as hostnames when running dd-agent on EC2
# 0.0.5
* `dd-agent` - Full datadog.conf template using attributes (thanks [@drewrothstein][])
# 0.0.4
* `dd-agent` - Added support for Nagios PerfData and Graphite.
# 0.0.3
* `dd-agent` - Added support for RPM installs - Red Hat, CentOS, Scientific, Fedora
# 0.0.2
* Initial refactoring, including the `dd-agent` cookbook here
* Adding chef-handler-datadog to report to the newsfeed
* Added ruby-dev dependency
<!--- The following link definition list is generated by PimpMyChangelog --->
[#18]: https://github.com/DataDog/chef-datadog/issues/18
[#22]: https://github.com/DataDog/chef-datadog/issues/22
[#23]: https://github.com/DataDog/chef-datadog/issues/23
[#26]: https://github.com/DataDog/chef-datadog/issues/26
[#27]: https://github.com/DataDog/chef-datadog/issues/27
[#28]: https://github.com/DataDog/chef-datadog/issues/28
[#34]: https://github.com/DataDog/chef-datadog/issues/34
[#35]: https://github.com/DataDog/chef-datadog/issues/35
[#37]: https://github.com/DataDog/chef-datadog/issues/37
[#44]: https://github.com/DataDog/chef-datadog/issues/44
[#46]: https://github.com/DataDog/chef-datadog/issues/46
[#55]: https://github.com/DataDog/chef-datadog/issues/55
[#56]: https://github.com/DataDog/chef-datadog/issues/56
[#58]: https://github.com/DataDog/chef-datadog/issues/58
[#59]: https://github.com/DataDog/chef-datadog/issues/59
[#60]: https://github.com/DataDog/chef-datadog/issues/60
[#61]: https://github.com/DataDog/chef-datadog/issues/61
[#63]: https://github.com/DataDog/chef-datadog/issues/63
[#65]: https://github.com/DataDog/chef-datadog/issues/65
[#66]: https://github.com/DataDog/chef-datadog/issues/66
[#67]: https://github.com/DataDog/chef-datadog/issues/67
[#74]: https://github.com/DataDog/chef-datadog/issues/74
[#76]: https://github.com/DataDog/chef-datadog/issues/76
[#77]: https://github.com/DataDog/chef-datadog/issues/77
[#79]: https://github.com/DataDog/chef-datadog/issues/79
[#80]: https://github.com/DataDog/chef-datadog/issues/80
[#81]: https://github.com/DataDog/chef-datadog/issues/81
[#82]: https://github.com/DataDog/chef-datadog/issues/82
[#83]: https://github.com/DataDog/chef-datadog/issues/83
[#84]: https://github.com/DataDog/chef-datadog/issues/84
[#86]: https://github.com/DataDog/chef-datadog/issues/86
[#88]: https://github.com/DataDog/chef-datadog/issues/88
[#89]: https://github.com/DataDog/chef-datadog/issues/89
[#90]: https://github.com/DataDog/chef-datadog/issues/90
[#93]: https://github.com/DataDog/chef-datadog/issues/93
[#94]: https://github.com/DataDog/chef-datadog/issues/94
[#95]: https://github.com/DataDog/chef-datadog/issues/95
[#97]: https://github.com/DataDog/chef-datadog/issues/97
[#98]: https://github.com/DataDog/chef-datadog/issues/98
[#100]: https://github.com/DataDog/chef-datadog/issues/100
[#101]: https://github.com/DataDog/chef-datadog/issues/101
[#103]: https://github.com/DataDog/chef-datadog/issues/103
[#105]: https://github.com/DataDog/chef-datadog/issues/105
[#113]: https://github.com/DataDog/chef-datadog/issues/113
[@JoeDeVries]: https://github.com/JoeDeVries
[@alexism]: https://github.com/alexism
[@alq]: https://github.com/alq
[@antonio-osorio]: https://github.com/antonio-osorio
[@babbottscott]: https://github.com/babbottscott
[@clofresh]: https://github.com/clofresh
[@coosh]: https://github.com/coosh
[@drewrothstein]: https://github.com/drewrothstein
[@dwradcliffe]: https://github.com/dwradcliffe
[@elijahandrews]: https://github.com/elijahandrews
[@evan2645]: https://github.com/evan2645
[@flah00]: https://github.com/flah00
[@gregf]: https://github.com/gregf
[@jedi4ever]: https://github.com/jedi4ever
[@jtimberman]: https://github.com/jtimberman
[@mfischer-zd]: https://github.com/mfischer-zd
[@miketheman]: https://github.com/miketheman
[@nkts]: https://github.com/nkts
[@phlipper]: https://github.com/phlipper
[@qqfr2507]: https://github.com/qqfr2507
[@remh]: https://github.com/remh
[@ryandjurovich]: https://github.com/ryandjurovich
[@schisamo]: https://github.com/schisamo
[@thisismana]: https://github.com/thisismana
[@timusg]: https://github.com/timusg
| 49.585774 | 237 | 0.72458 | eng_Latn | 0.499421 |
48a87fcd3ac644792495f4b4e9b00b6117899afe | 1,072 | md | Markdown | README.md | PaDuckk/node-user-agent-parse | e4223bc0e4ccafe055908576186306ee90c215bc | [
"MIT"
] | 12 | 2015-05-08T10:24:58.000Z | 2021-03-12T10:30:44.000Z | README.md | PaDuckk/node-user-agent-parse | e4223bc0e4ccafe055908576186306ee90c215bc | [
"MIT"
] | 1 | 2020-02-11T05:58:38.000Z | 2021-03-12T14:35:17.000Z | README.md | PaDuckk/node-user-agent-parse | e4223bc0e4ccafe055908576186306ee90c215bc | [
"MIT"
] | 5 | 2020-02-11T06:06:46.000Z | 2021-01-15T13:27:53.000Z | # Node User Agent Parse
Very simple, no deps user agent string parser.
[](https://nodei.co/npm/user-agent-parse/)
[](https://travis-ci.org/jujhars13/node-user-agent-parse)
## Overview
Parse user agents a bit like PHP's [get_browser()](http://php.net/manual/en/function.get-browser.php).
Rudimentary but it works.
## Example Usage
```javascript
const userAgent = require('user-agent-parse');
userAgent.parse('Mozilla/5.0 (Windows; U; Windows NT 5.1; en) AppleWebKit/526.9 (KHTML, like Gecko) Version/4.0dp1 Safari/526.8');
// => { name: 'safari', version: '4.0dp1', os: 'Windows XP', full: '... same string as above ...', device_type:'desktop' }
```
## Tests
See `/test/test.js` for a simple suite
## Credits
Heavily based on (blatantly ripped from *ahem*) https://github.com/soldair/node-ua-device-type and https://github.com/jujhars13/node-user-agent-parse
## License
License is [MIT](LICENCE.md), go nuts.
| 33.5 | 149 | 0.714552 | kor_Hang | 0.172025 |
48a8e097ec8c1161140d5f83c082b94b69b8af34 | 674 | md | Markdown | src/main/markdown/attack-tables/short/navrpg/navrpg-club.md | PeterRudin-Burgess/Bare-Metal-Edition | 840afc579e7e7733bbd22b08d0b39e8c5d150a0a | [
"CC-BY-4.0"
] | 3 | 2020-05-16T14:46:16.000Z | 2020-06-07T04:11:22.000Z | src/main/markdown/attack-tables/short/navrpg/navrpg-club.md | PeterRudin-Burgess/Bare-Metal-Edition | 840afc579e7e7733bbd22b08d0b39e8c5d150a0a | [
"CC-BY-4.0"
] | 4 | 2020-05-23T09:02:20.000Z | 2020-05-27T23:24:42.000Z | src/main/markdown/attack-tables/short/navrpg/navrpg-club.md | PeterRudin-Burgess/Bare-Metal-Edition | 840afc579e7e7733bbd22b08d0b39e8c5d150a0a | [
"CC-BY-4.0"
] | 1 | 2021-06-02T01:00:01.000Z | 2021-06-02T01:00:01.000Z | ##### Club
| | Armor ||||
| Result | No | Lt | Md | Hvy |
|:--------:|:-----:|:-----:|:-----:|:-----:|
| 149 - 150 | 36EK | 26EK | 21EK | 10EK |
| 146 - 148 | 35EK | 25EK | 20EK | 10EK |
| 143 - 145 | 33EK | 24EK | 19DK | 10DK |
| 139 - 142 | 32EK | 23EK | 19DK | 10DK |
| 133 - 138 | 30EK | 22EK | 18DK | 9DK |
| 126 - 132 | 27EK | 20DK | 16CK | 9DK |
| 118 - 125 | 24EK | 18CK | 15CK | 8CK |
| 109 - 117 | 21DK | 16CK | 13BK | 7AK |
| 99 - 108 | 16CK | 13BK | 11AK | 6AK |
| 88 - 98 | 12BK | 10AK | 9 | 5 |
| 75 - 87 | 7 | 7 | 6 | 4 |
| 62 - 74 | -- | 3 | 4 | 3 |
| 47 - 61 | -- | -- | -- | 2 |
| 1 - F | F | F | F | F |
{.attack-table}
| 30.636364 | 51 | 0.396142 | yue_Hant | 0.881803 |
48a8ebf07d61c11dcfb633a12d8af8724558f2bb | 609,889 | md | Markdown | _posts/2021-07-20-15518.md | akrvkn/rospriroda | 43731b2aee2f8177ccd2f84f4b5e918224f5d6e3 | [
"MIT"
] | null | null | null | _posts/2021-07-20-15518.md | akrvkn/rospriroda | 43731b2aee2f8177ccd2f84f4b5e918224f5d6e3 | [
"MIT"
] | null | null | null | _posts/2021-07-20-15518.md | akrvkn/rospriroda | 43731b2aee2f8177ccd2f84f4b5e918224f5d6e3 | [
"MIT"
] | null | null | null | ---
layout: post
title: В 2020 году сотрудники Росприроднадзора по просьбе Прокуратуры Баймакского района Республики Башкортостан приняли участие в проверке золотодобывающей компании «Таналык»
category: news
---
В 2020 году сотрудники Росприроднадзора по просьбе Прокуратуры Баймакского района Республики Башкортостан приняли участие в проверке золотодобывающей компании «Таналык». Специалисты Службы проверили соблюдение действующего природоохранного законодательства.
Проверка показала, что «Таналык» вел добычу за пределами земельного участка Таналыкская Россыпь. Работы велись открытым способом при помощи бульдозеров и экскаваторов. Это привело к уничтожению плодородного слоя почвы.
Расчет ущерба был направлен компании для добровольного возмещения. Однако ООО «Таналык» проигнорировало требование. Служба обратилась в суд, где добилась взыскания с золотодобытчика 604,8 млн рублей. Средства будут направлены в муниципальный бюджет. Также принято решение обязать «Таналык» и Администрацию Баймакского района разработать и утвердить проект рекультивации нарушенных земельных участков общей площадью 48 389,14 кв.м и провести рекультивацию нарушенных земельных участков.<!--more-->
<img alt="Росприроды информирует" src="data:image/jpg;base64,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"> | 50,824.083333 | 608,696 | 0.954718 | yue_Hant | 0.435823 |
48a926f108cba9b497d086ec8c41e7f2b526e6af | 600 | md | Markdown | algorithms/016-3Sum Closest/Bingjian-Zhu.md | laijinhang/leetcode | 2a858cfaf87135e66a4b12f6dfe7f83e7fee9fd0 | [
"MIT"
] | 81 | 2019-04-25T06:49:04.000Z | 2021-04-25T02:02:58.000Z | algorithms/016-3Sum Closest/Bingjian-Zhu.md | laijinhang/leetcode | 2a858cfaf87135e66a4b12f6dfe7f83e7fee9fd0 | [
"MIT"
] | 4 | 2019-06-17T10:18:19.000Z | 2019-06-26T11:07:58.000Z | algorithms/016-3Sum Closest/Bingjian-Zhu.md | laijinhang/leetcode | 2a858cfaf87135e66a4b12f6dfe7f83e7fee9fd0 | [
"MIT"
] | 42 | 2019-04-25T06:41:46.000Z | 2021-03-17T02:25:40.000Z | 排序+双指针
```golang
func threeSumClosest(nums []int, target int) int {
lenNum := len(nums)
sort.Ints(nums)
min := abs(nums[0] + nums[1] + nums[2] - target)
minSum := nums[0] + nums[1] + nums[2]
for i := 0; i < lenNum; i++ {
left := i + 1
right := lenNum - 1
for left < right {
sum := nums[i] + nums[left] + nums[right]
tmp := abs(sum - target)
if tmp < min {
minSum, min = sum, tmp
}
if tmp == 0 {
return minSum
} else if sum < target {
left++
} else {
right--
}
}
}
return minSum
}
func abs(x int) int {
if x < 0 {
return -x
}
return x
}
``` | 17.142857 | 50 | 0.53 | eng_Latn | 0.320908 |
48a9b0c840dd6cc917b3517f84e7bb468c6bfae9 | 2,556 | md | Markdown | README.md | lrothack/cookiecutter-pydevops | 70d94f6a889619b40cfe470445264e22c6cb2af7 | [
"MIT"
] | 1 | 2022-01-21T07:31:55.000Z | 2022-01-21T07:31:55.000Z | README.md | lrothack/cookiecutter-pydevops | 70d94f6a889619b40cfe470445264e22c6cb2af7 | [
"MIT"
] | null | null | null | README.md | lrothack/cookiecutter-pydevops | 70d94f6a889619b40cfe470445264e22c6cb2af7 | [
"MIT"
] | null | null | null | # Cookiecutter PyDevops
Cookiecutter template for a dockerized dev-ops pipeline with SonarQube code-quality monitoring.
[Cookiecutter](https://github.com/audreyr/cookiecutter) provides a command-line interface for creating projects from templates.
- [Sample project](https://github.com/lrothack/dev-ops) for this cookiecutter (including detailed documentation).
- This cookiecutter has been generated with the command-line client [devopstemplate](https://github.com/lrothack/dev-ops-admin).
- Also check out [audreyr/cookiecutter-pypackage](https://github.com/audreyr/cookiecutter-pypackage) for additional Python package templates.
## Features
The template provides a minimal dev-ops pipeline that supports:
- testing and deployment in a multi-stage [Docker](https://www.docker.com) environment,
- packaging with [setuptools](https://setuptools.readthedocs.io/en/latest/),
- code analysis with [pylint](https://www.pylint.org/), [bandit](https://bandit.readthedocs.io/en/latest/), [pytest](https://docs.pytest.org/en/stable/) and [coverage](https://coverage.readthedocs.io/en/latest/),
- code quality monitoring with [SonarQube](https://www.sonarqube.org).
The dev-ops pipeline is mostly implemented in a `Makefile` and a `Dockerfile` which are
independent of your Python code.
## Quickstart
Install the latest cookiecutter:
```bash
pip install -U cookiecutter
```
Generate an instance of the template:
```bash
cookiecutter https://github.com/lrothack/cookiecutter-pydevops.git
```
Then switch to the project directory and:
- Set up a virtual environment for your project and activate it (requires Python >= 3.6).
- Run `make help` in order to get an overview of the targets provided by `Makefile`.
- Run `make install-dev` in order to install the package (and all dependencies) in development mode.
- Run `make lint` in order to run code analysis with pylint and bandit.
- Run `make test` in order to run unit tests with pytest and coverage.
- Run `make dist` in order to build a Python package (binary and source).
- Run `docker-compose -p sonarqube -f sonarqube/docker-compose.yml up -d` in order to start a SonarQube server.
- Run `make sonar` in order to run `sonar-scanner` and report results to your local SonarQube server.
- Run `make docker-build` in order to analyze, test, package and deploy in a multi-stage Docker build. Test your docker image with `docker run`.
Advanced configurations can be made in the *configuration* sections of `Makefile`. See [lrothack/dev-ops](https://github.com/lrothack/dev-ops) for more information.
| 52.163265 | 212 | 0.771518 | eng_Latn | 0.902455 |
48a9d7bde2c75a5be934a097ee9e3de01403c2b7 | 601 | md | Markdown | README.md | HoneySanghani/portfolio-generator | 25e8e6ab61caf988c301b658f52f149a98d0973d | [
"MIT"
] | null | null | null | README.md | HoneySanghani/portfolio-generator | 25e8e6ab61caf988c301b658f52f149a98d0973d | [
"MIT"
] | null | null | null | README.md | HoneySanghani/portfolio-generator | 25e8e6ab61caf988c301b658f52f149a98d0973d | [
"MIT"
] | null | null | null | # Portfolio Generator
## Purpose
To create a webpage using commandline.
## Function
User is presented with couple of questions regarding their webpage and answered a webpage is generated.
## Build-with
nodejs ES6 css
## Video Demo URL
https://drive.google.com/file/d/1z93CyvnQxVf1x-Ikxr6x4VT64-iZ9TR1/view
## Repository
https://github.com/HoneySanghani/portfolio-generator.git
## Output
| 40.066667 | 211 | 0.806988 | kor_Hang | 0.318347 |
48ac1abd88545d1ef0e66fd0160c1ab712dd3c02 | 631 | md | Markdown | README.md | maior/mkclient | f2cc1f1ed9fca1b4c928f654fe8dd178e7bab23c | [
"MIT"
] | null | null | null | README.md | maior/mkclient | f2cc1f1ed9fca1b4c928f654fe8dd178e7bab23c | [
"MIT"
] | null | null | null | README.md | maior/mkclient | f2cc1f1ed9fca1b4c928f654fe8dd178e7bab23c | [
"MIT"
] | null | null | null | # mkclient
client of mkblock
- It's for "MKBLOCK". Before you run mkclient, mkblock should be running. please install mkblock first.
- Download "mkblock" : git clone https//github.com/maior/mkblock.git
- refer "mkweb", you can make smart?contract but i'm not sure it's smart ^_______^;
Built With
- Intellij IDEA
- Gradle
How to Run
- Run "Main"
Usage
- following command
- ">> getinfo"
- ">> getnewaccount"
- ">> trypos"
- ">> compile" (Before you compile(deploy), you should check configuration files(*.json) out.)
Author
- Kenneth Kwon - maiordba@gmail.com
License mkclient is released under the terms of the MIT license.
| 25.24 | 103 | 0.725832 | eng_Latn | 0.935276 |
48ac9bb347acd4ae22094f9d7c0af4ff3148f612 | 573 | md | Markdown | lesson02/README.md | malloblenne/teaching_programming_python | 1c166c7b54204608d4bfeb9f37320041736dbe77 | [
"MIT"
] | null | null | null | lesson02/README.md | malloblenne/teaching_programming_python | 1c166c7b54204608d4bfeb9f37320041736dbe77 | [
"MIT"
] | null | null | null | lesson02/README.md | malloblenne/teaching_programming_python | 1c166c7b54204608d4bfeb9f37320041736dbe77 | [
"MIT"
] | null | null | null | # Lesson 2
Lesson 2 will add important features given by most of programming languages, and also some specific ones for python.
Some syntactic sugar is introduced.
## Content
- list
- for loop
- play with string and list and for loop
- stack and queue https://stackabuse.com/stacks-and-queues-in-python/
- break
- range(), enumerate()
- tuple
- dict
- exercise with dict
- explanation example 7dwarf
- mutable/immutable types
- function
- exercise
- extra file and json/yaml format?
- homework: konamicode, morse, mastermind, '7 e mezzo'
| 20.464286 | 117 | 0.710297 | eng_Latn | 0.987882 |
48ad3bc1ea1d61075a8a77e5425bc7fc5b1dee11 | 1,675 | md | Markdown | README.md | xloem/kivy-launcher | 4f932b9138cfa109bbd05b77676bc63f7a786c61 | [
"MIT"
] | 53 | 2018-03-01T16:09:27.000Z | 2022-03-27T16:09:25.000Z | README.md | xloem/kivy-launcher | 4f932b9138cfa109bbd05b77676bc63f7a786c61 | [
"MIT"
] | 22 | 2018-03-11T18:32:59.000Z | 2022-02-16T10:27:45.000Z | README.md | xloem/kivy-launcher | 4f932b9138cfa109bbd05b77676bc63f7a786c61 | [
"MIT"
] | 37 | 2018-03-16T17:30:39.000Z | 2022-02-24T13:51:51.000Z | # Kivy Launcher
(work in progress, not yet published on Google Play)
This is a reboot of the previously pygame/kivy launcher, implemented in Java in Python for android. It was barely maintainable, and with the rewrite of the new Python for android, it was lost.
This version aimed to provide a replacement for the launcher, but works also on desktop, on Python 2 or 3.
Anybody can clone the repo, add the dependencies we would not provide by default, and recompile it.
## How it works
Follow the guide the same as before:
https://kivy.org/docs/guide/packaging-android.html#packaging-your-application-for-the-kivy-launcher
Then just start the launcher, you should see your application listed, then press play.
## `android.txt` specification
- `title`: Title of the application
- `author`: Author of the application
- `orientation`: Default orientation, one of "landscape", "portrait", "sensor"
## Works
- Provide a simple UI to discover and start another app
- Start another main.py as a `__name__ == '__main__'`
- Reduce to the minimum the overhead of the launcher to launch another app
- Support landscape / portrait / sensor
## Ideas
- Act as a server to just launch any Kivy-based app from desktop to mobile
- Ability to configure multiple paths to look for applications
- Different ordering: by name, last updated, size
- Add tiny icon to show what application orientation is
- Allow to change multiple configuration token / environemnt (like different density/dpi to simulate other screens)
- Support for application without "android.txt"
| 39.880952 | 192 | 0.775522 | eng_Latn | 0.994533 |
48adb6407aa101b2a5b83295288cdfe9114e073c | 3,291 | md | Markdown | add/metadata/System.Web.UI.WebControls/ImageButton.meta.md | MarktW86/dotnet.docs | 178451aeae4e2c324aadd427ed6bf6850e483900 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | add/metadata/System.Web.UI.WebControls/ImageButton.meta.md | MarktW86/dotnet.docs | 178451aeae4e2c324aadd427ed6bf6850e483900 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | add/metadata/System.Web.UI.WebControls/ImageButton.meta.md | MarktW86/dotnet.docs | 178451aeae4e2c324aadd427ed6bf6850e483900 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | ---
uid: System.Web.UI.WebControls.ImageButton
ms.author: "riande"
manager: "wpickett"
---
---
uid: System.Web.UI.WebControls.ImageButton.OnCommand(System.Web.UI.WebControls.CommandEventArgs)
ms.author: "riande"
manager: "wpickett"
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uid: System.Web.UI.WebControls.ImageButton.PostBackUrl
ms.author: "riande"
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---
uid: System.Web.UI.WebControls.ImageButton.Command
ms.author: "riande"
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uid: System.Web.UI.WebControls.ImageButton.OnPreRender(System.EventArgs)
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uid: System.Web.UI.WebControls.ImageButton.GetPostBackOptions
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uid: System.Web.UI.WebControls.ImageButton.RaisePostBackEvent(System.String)
ms.author: "riande"
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uid: System.Web.UI.WebControls.ImageButton.LoadPostData(System.String,System.Collections.Specialized.NameValueCollection)
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manager: "wpickett"
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uid: System.Web.UI.WebControls.ImageButton.Text
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uid: System.Web.UI.WebControls.ImageButton.CausesValidation
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uid: System.Web.UI.WebControls.ImageButton.ValidationGroup
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uid: System.Web.UI.WebControls.ImageButton.GenerateEmptyAlternateText
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---
uid: System.Web.UI.WebControls.ImageButton.System#Web#UI#WebControls#IButtonControl#Text
ms.author: "riande"
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uid: System.Web.UI.WebControls.ImageButton.CommandName
ms.author: "riande"
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uid: System.Web.UI.WebControls.ImageButton.#ctor
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uid: System.Web.UI.WebControls.ImageButton.System#Web#UI#IPostBackEventHandler#RaisePostBackEvent(System.String)
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uid: System.Web.UI.WebControls.ImageButton.AddAttributesToRender(System.Web.UI.HtmlTextWriter)
ms.author: "riande"
manager: "wpickett"
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uid: System.Web.UI.WebControls.ImageButton.RaisePostDataChangedEvent
ms.author: "riande"
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uid: System.Web.UI.WebControls.ImageButton.System#Web#UI#IPostBackDataHandler#RaisePostDataChangedEvent
ms.author: "riande"
manager: "wpickett"
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---
uid: System.Web.UI.WebControls.ImageButton.Enabled
ms.author: "riande"
manager: "wpickett"
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uid: System.Web.UI.WebControls.ImageButton.SupportsDisabledAttribute
ms.author: "riande"
manager: "wpickett"
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uid: System.Web.UI.WebControls.ImageButton.OnClick(System.Web.UI.ImageClickEventArgs)
ms.author: "riande"
manager: "wpickett"
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---
uid: System.Web.UI.WebControls.ImageButton.Click
ms.author: "riande"
manager: "wpickett"
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uid: System.Web.UI.WebControls.ImageButton.CommandArgument
ms.author: "riande"
manager: "wpickett"
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---
uid: System.Web.UI.WebControls.ImageButton.System#Web#UI#IPostBackDataHandler#LoadPostData(System.String,System.Collections.Specialized.NameValueCollection)
ms.author: "riande"
manager: "wpickett"
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---
uid: System.Web.UI.WebControls.ImageButton.OnClientClick
ms.author: "riande"
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---
uid: System.Web.UI.WebControls.ImageButton.TagKey
ms.author: "riande"
manager: "wpickett"
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| 20.314815 | 156 | 0.75357 | yue_Hant | 0.292055 |
48adc5a8fb6e3799d68d2fd81b5c97d683b30271 | 115 | md | Markdown | mkdocs/docs/release-notes/services/remote-execution.md | RemoteCloud/public-documentation | 2d7521ebfb34535f222cadaac3831ac3b340f375 | [
"MIT"
] | null | null | null | mkdocs/docs/release-notes/services/remote-execution.md | RemoteCloud/public-documentation | 2d7521ebfb34535f222cadaac3831ac3b340f375 | [
"MIT"
] | null | null | null | mkdocs/docs/release-notes/services/remote-execution.md | RemoteCloud/public-documentation | 2d7521ebfb34535f222cadaac3831ac3b340f375 | [
"MIT"
] | null | null | null | title: Remote Execution
## v2.1.4
- [low] Automatic bug reporting endpoint changed
## v2.1.3
## v2.1.2.1
- ... | 10.454545 | 48 | 0.626087 | eng_Latn | 0.813903 |
48adf213985c9a0e00714ae94dcc4e68951bc2fc | 904 | md | Markdown | docs/access/desktop-database-reference/program-flow.md | MicrosoftDocs/office-developer-client-docs.es-ES | d4568d789fd46de778fdecb250a28fb84b4bf02e | [
"CC-BY-4.0",
"MIT"
] | 2 | 2020-05-19T18:52:21.000Z | 2021-04-21T00:13:46.000Z | docs/access/desktop-database-reference/program-flow.md | MicrosoftDocs/office-developer-client-docs.es-ES | d4568d789fd46de778fdecb250a28fb84b4bf02e | [
"CC-BY-4.0",
"MIT"
] | 3 | 2021-12-08T02:36:34.000Z | 2021-12-08T03:08:40.000Z | docs/access/desktop-database-reference/program-flow.md | MicrosoftDocs/office-developer-client-docs.es-ES | d4568d789fd46de778fdecb250a28fb84b4bf02e | [
"CC-BY-4.0",
"MIT"
] | 2 | 2018-10-24T20:53:01.000Z | 2019-10-13T18:19:17.000Z | ---
title: Flujo de programa (referencia de base de datos de escritorio de Access)
TOCTitle: Program flow
ms:assetid: 1ca43854-f15b-45f8-a227-eaa8e1aec75f
ms:mtpsurl: https://msdn.microsoft.com/library/Dn123920(v=office.15)
ms:contentKeyID: 52071559
ms.date: 09/18/2015
mtps_version: v=office.15
ms.localizationpriority: medium
ms.openlocfilehash: 91f38143d18bff19c3f83e8e7717baad4089811b
ms.sourcegitcommit: a1d9041c20256616c9c183f7d1049142a7ac6991
ms.translationtype: MT
ms.contentlocale: es-ES
ms.lasthandoff: 09/24/2021
ms.locfileid: "59606446"
---
# <a name="program-flow"></a>Flujo de programas
**Se aplica a:** Access 2013, Office 2013
- [If...Then...Else (bloque de macro)](if-then-else-macro-block.md)
- [Comentario (instrucción de macro)](comment-macro-statement.md)
- [Grupo (instrucción de macro)](group-macro-statement.md)
- [Submacro (instrucción de macro)](submacro-macro-statement.md)
| 34.769231 | 78 | 0.780973 | spa_Latn | 0.124031 |
48ae442a8815fb622953a1919721e28a6bf1aa4c | 10,749 | md | Markdown | articles/api-management/import-function-app-as-api.md | Myhostings/azure-docs.tr-tr | 536eaf3b454f181f4948041d5c127e5d3c6c92cc | [
"CC-BY-4.0",
"MIT"
] | 16 | 2017-08-28T08:29:36.000Z | 2022-01-02T16:46:30.000Z | articles/api-management/import-function-app-as-api.md | Ahmetmaman/azure-docs.tr-tr | 536eaf3b454f181f4948041d5c127e5d3c6c92cc | [
"CC-BY-4.0",
"MIT"
] | 470 | 2017-11-11T20:59:16.000Z | 2021-04-10T17:06:28.000Z | articles/api-management/import-function-app-as-api.md | Ahmetmaman/azure-docs.tr-tr | 536eaf3b454f181f4948041d5c127e5d3c6c92cc | [
"CC-BY-4.0",
"MIT"
] | 25 | 2017-11-11T19:39:08.000Z | 2022-03-30T13:47:56.000Z | ---
title: Azure İşlev Uygulaması API Management API olarak içeri aktarma
titleSuffix: Azure API Management
description: Bu makalede bir Azure İşlev Uygulaması Azure API Management bir API 'ye nasıl içeri aktarılacağı gösterilmektedir.
services: api-management
documentationcenter: ''
author: mikebudzynski
manager: cfowler
editor: ''
ms.service: api-management
ms.workload: mobile
ms.tgt_pltfrm: na
ms.topic: article
ms.date: 04/16/2021
ms.author: apimpm
ms.openlocfilehash: 8e8047fc6865bab8f4aac2315b269bf7526b1e42
ms.sourcegitcommit: 950e98d5b3e9984b884673e59e0d2c9aaeabb5bb
ms.translationtype: MT
ms.contentlocale: tr-TR
ms.lasthandoff: 04/18/2021
ms.locfileid: "107599388"
---
# <a name="import-an-azure-function-app-as-an-api-in-azure-api-management"></a>Azure İşlev Uygulamasını Azure API Management'da API olarak içeri aktarma
Azure API Management, Azure İşlev Uygulamalarının yeni API olarak içeri aktarılmasını veya var olan API'lere eklenmesini destekler. Bu işlemin ardından Azure İşlev Uygulamasında otomatik olarak bir konak anahtarı oluşturulur. Bu anahtar daha sonra Azure API Management'taki bir adlandırılmış değere atanır.
Bu makalede bir Azure İşlev Uygulaması Azure API Management API 'SI olarak içeri ve test etme adımları anlatılmaktadır.
Şunları öğrenirsiniz:
> [!div class="checklist"]
> * Azure İşlev Uygulamalarını API olarak içeri aktarma
> * Azure İşlev Uygulamalarını API'lere ekleme
> * Yeni Azure İşlev Uygulaması ana bilgisayar anahtarını ve Azure API Management adlandırılmış değerini görüntüleme
> * Azure portalında API’yi test etme
## <a name="prerequisites"></a>Önkoşullar
* [Azure API Management örneği oluşturma](get-started-create-service-instance.md) hızlı başlangıcı ' nı doldurun.
* Aboneliğinizde bir Azure İşlevleri uygulaması bulunduğundan emin olun. Daha fazla bilgi için bkz. [Azure İşlev Uygulaması oluşturma](../azure-functions/functions-get-started.md). İşlevlerin HTTP tetikleyicisi ve Yetkilendirme düzeyi *anonim* veya *işlev* olarak ayarlanmış olmalıdır.
> [!NOTE]
> API 'lerinizi içeri aktarmak ve yönetmek için Visual Studio Code API Management uzantısını kullanabilirsiniz. Yüklemek ve başlamak için [API Management uzantısı öğreticisini](visual-studio-code-tutorial.md) izleyin.
[!INCLUDE [api-management-navigate-to-instance.md](../../includes/api-management-navigate-to-instance.md)]
## <a name="import-an-azure-function-app-as-a-new-api"></a><a name="add-new-api-from-azure-function-app"></a> Azure İşlev Uygulamalarını yeni API olarak içeri aktarma
Bir Azure İşlev Uygulamasından yeni API oluşturmak için aşağıdaki adımları uygulayın.
1. Azure portal API Management hizmetinize gidin ve menüden **API 'leri** seçin.
2. **Yeni API ekleyin** listesinde **İşlev Uygulaması**'nı seçin.
:::image type="content" source="./media/import-function-app-as-api/add-01.png" alt-text="İşlev Uygulaması kutucuğunu gösteren ekran görüntüsü.":::
3. İçeri aktarılacak İşlevleri seçmek için **Gözat**'a tıklayın.
:::image type="content" source="./media/import-function-app-as-api/add-02.png" alt-text="Tarama düğmesini vurgulayan ekran görüntüsü.":::
4. Kullanılabilir İşlev Uygulamaları listesinden seçim yapmak için **İşlev Uygulaması** bölümüne tıklayın.
:::image type="content" source="./media/import-function-app-as-api/add-03.png" alt-text="İşlev Uygulaması bölümünü vurgulayan ekran görüntüsü.":::
5. İşlevlerini içeri aktarmak istediğiniz İşlev Uygulamasını bulun, uygulamaya tıklayın ve **Seç**'e basın.
:::image type="content" source="./media/import-function-app-as-api/add-04.png" alt-text="Işlevleri içeri aktarmak istediğiniz İşlev Uygulaması ve seçim düğmesini vurgulayan ekran görüntüsü.":::
6. İçeri aktarmak istediğiniz İşlevleri seçin ve **Seç**'e tıklayın.
* Yalnızca *anonim* veya *işlev* yetkilendirme düzeylerine sahip http tetikleyicisini temel alarak işlevleri içeri aktarabilirsiniz.
:::image type="content" source="./media/import-function-app-as-api/add-05.png" alt-text="İçeri aktarılacak Işlevleri ve seçim düğmesini vurgulayan ekran görüntüsü.":::
7. **Tam** görünümüne geçiş yapın ve yeni API’nize **Ürün** atayın.
8. Gerekirse, oluşturma sırasında diğer alanları belirtin veya daha sonra **Ayarlar** sekmesini kullanarak yapılandırın.
* Ayarlar, [Ilk API 'Nizi Içeri aktarma ve yayımlama](import-and-publish.md#import-and-publish-a-backend-api) öğreticisinde açıklanmıştır.
>[!NOTE]
> Ürünler, geliştirici portalı aracılığıyla geliştiricilere sunulan bir veya daha fazla API 'nin ilişkilerinden biridir. İlk olarak, geliştiricilerin API 'ye erişim sağlamak için bir ürüne abone olmaları gerekir. Abone olduktan sonra, söz konusu üründeki tüm API 'leri için bir abonelik anahtarı alırlar. API Management örneğinin Oluşturucusu olarak, bir yöneticiyseniz ve varsayılan olarak her ürüne abone olursunuz.
>
> Her bir API Management örneği iki varsayılan örnek ürünle birlikte gelir:
> - **Başlangıç**
> - **Sınırsız**
9. **Oluştur**’a tıklayın.
## <a name="append-azure-function-app-to-an-existing-api"></a><a name="append-azure-function-app-to-api"></a> Azure İşlev Uygulamalarını var olan API'lere ekleme
Azure İşlev Uygulamasını var olan bir API'ye eklemek için aşağıdaki adımları uygulayın.
1. **Azure API Management** hizmet örneğinizde soldaki menüden **API'ler** seçeneğini belirleyin.
2. Azure İşlev Uygulamasından içeri aktarmak istediğiniz bir API'yi seçin. **...** simgesine tıklayın ve bağlam menüsünden **İçeri Aktar**'ı seçin.
:::image type="content" source="./media/import-function-app-as-api/append-function-api-1.png" alt-text="Içeri aktar menü seçeneğini vurgulayan ekran görüntüsü.":::
3. **İşlev Uygulaması** kutucuğuna tıklayın.
:::image type="content" source="./media/import-function-app-as-api/append-function-api-2.png" alt-text="İşlev Uygulaması kutucuğunu vurgulayan ekran görüntüsü.":::
4. Açılır pencerede **Gözat**'a tıklayın.
:::image type="content" source="./media/import-function-app-as-api/append-function-api-3.png" alt-text="Tarama düğmesini gösteren ekran görüntüsü.":::
5. Kullanılabilir İşlev Uygulamaları listesinden seçim yapmak için **İşlev Uygulaması** bölümüne tıklayın.
:::image type="content" source="./media/import-function-app-as-api/add-03.png" alt-text="Işlev uygulamalarının listesini vurgulayan ekran görüntüsü.":::
6. İşlevlerini içeri aktarmak istediğiniz İşlev Uygulamasını bulun, uygulamaya tıklayın ve **Seç**'e basın.
:::image type="content" source="./media/import-function-app-as-api/add-04.png" alt-text="İşlevleri içe aktarmak istediğiniz İşlev Uygulaması vurgulayan ekran görüntüsü.":::
7. İçeri aktarmak istediğiniz İşlevleri seçin ve **Seç**'e tıklayın.
:::image type="content" source="./media/import-function-app-as-api/add-05.png" alt-text="İçe aktarmak istediğiniz işlevleri vurgulayan ekran görüntüsü.":::
8. **İçeri Aktar**’a tıklayın.
:::image type="content" source="./media/import-function-app-as-api/append-function-api-4.png" alt-text="İşlev Uygulamasından ekleme":::
## <a name="authorization"></a><a name="authorization"></a> Yetkisi
Bir Azure İşlev Uygulaması içeri aktarıldığında aşağıdakiler otomatik olarak oluşturulur:
* İşlev Uygulaması içindeki ana bilgisayar anahtarı apim-{*Azure API Management hizmet örneğiniz* adı},
* Oluşturulan ana bilgisayar anahtarını içeren, Azure API Management örneği içindeki adlandırılmış değer {*azure işlev uygulaması örneğiniz* adı}-anahtar.
4 Nisan 2019 ' den sonra oluşturulan API 'Ler için, ana bilgisayar anahtarı API Management olan HTTP isteklerinde bir başlıktaki İşlev Uygulaması geçirilir. Eski API 'Ler, ana bilgisayar anahtarını [bir sorgu parametresi](../azure-functions/functions-bindings-http-webhook-trigger.md#api-key-authorization)olarak iletir. Bu davranışı, `PATCH Backend` işlev uygulaması Ilişkili *arka uç* varlığındaki [REST API çağrısı](/rest/api/apimanagement/2019-12-01/backend/update#backendcredentialscontract) aracılığıyla değiştirebilirsiniz.
> [!WARNING]
> Azure İşlev Uygulaması ana bilgisayar anahtarı değerini ya da Azure API Management adlandırılmış değeri kaldırmak veya değiştirmek, hizmetler arasındaki iletişimi bozacaktır. Değerler otomatik olarak eşitlenmez.
>
> Ana bilgisayar anahtarını döndürmeniz gerekirse Azure API Management'taki adlandırılmış değerin de değiştirildiğinden emin olun.
### <a name="access-azure-function-app-host-key"></a>Azure İşlev Uygulaması ana bilgisayar anahtarına erişim
1. Azure İşlev Uygulaması örneğinize gidin.
:::image type="content" source="./media/import-function-app-as-api/keys-01.png" alt-text="Işlev uygulaması örneğinizi seçmeyi vurgulayan ekran görüntüsü.":::
2. Yan gezinti menüsünün **işlevler** bölümünde **uygulama anahtarları**' nı seçin.
:::image type="content" source="./media/import-function-app-as-api/keys-02b.png" alt-text="Işlev uygulamaları ayarları seçeneğini vurgulayan ekran görüntüsü.":::
3. **Ana bilgisayar anahtarları** bölümünün altındaki anahtarları bulun.
:::image type="content" source="./media/import-function-app-as-api/keys-03.png" alt-text="Ana bilgisayar anahtarları bölümünü vurgulayan ekran görüntüsü.":::
### <a name="access-the-named-value-in-azure-api-management"></a>Azure API Management'taki adlandırılmış değere erişim
Azure API Management örneğinize gidin ve soldaki menüden **Adlandırılmış değerler**'i seçin. Azure İşlev Uygulaması anahtarı burada depolanır.
:::image type="content" source="./media/import-function-app-as-api/api-named-value.png" alt-text="İşlev Uygulamasından ekleme":::
## <a name="test-the-new-api-in-the-azure-portal"></a><a name="test-in-azure-portal"></a> Azure portal yeni API 'YI test etme
İşlemleri doğrudan Azure portaldan çağırabilirsiniz. Azure portalı kullanarak bir API'nin işlemlerini kolayca görüntüleyebilir ve test edebilirsiniz.
:::image type="content" source="./media/import-function-app-as-api/test-api.png" alt-text="Test yordamını vurgulayan ekran görüntüsü.":::
1. Bir önceki bölümde oluşturduğunuz API'yi seçin.
2. **Test** sekmesini seçin.
3. Test etmek istediğiniz işlemi seçin.
* Sayfada sorgu parametreleri ve üst bilgiler için alanlar görüntülenir.
* Bu API ile ilişkili ürün abonelik anahtarı için üst bilgilerden biri "OCP-apim-Subscription-Key" dır.
* API Management örneğinin Oluşturucusu olarak, zaten bir Yöneticinizde, anahtar otomatik olarak doldurulur.
4. **Gönder**’i seçin.
* Sınama başarılı olduğunda, arka uç **200 Tamam** ve bazı veriler ile yanıt verir.
[!INCLUDE [api-management-define-api-topics.md](../../includes/api-management-define-api-topics.md)]
## <a name="next-steps"></a>Sonraki adımlar
> [!div class="nextstepaction"]
> [Yayımlanan API’yi dönüştürme ve koruma](transform-api.md)
| 59.38674 | 530 | 0.776723 | tur_Latn | 0.998936 |
48ae7b61cec37785797a769c2f27c5e858e2b84f | 2,544 | md | Markdown | README.md | isabella232/try.haxe.org | 831405a85f0c395b0e7c53e1ceef6c22305d8807 | [
"MIT"
] | 7 | 2021-02-27T18:00:14.000Z | 2021-06-05T08:29:09.000Z | README.md | isabella232/try.haxe.org | 831405a85f0c395b0e7c53e1ceef6c22305d8807 | [
"MIT"
] | 6 | 2021-02-27T20:05:48.000Z | 2021-06-22T23:01:22.000Z | README.md | isabella232/try.haxe.org | 831405a85f0c395b0e7c53e1ceef6c22305d8807 | [
"MIT"
] | 5 | 2021-02-27T18:52:37.000Z | 2022-03-16T11:25:56.000Z | # try.haxe.org
The try-haxe project is a browser-based IDE for testing Haxe code. It provides a
quick and easy environment for playing with the Haxe language and compiles to
JavaScript, Eval, HashLink or Neko, instantly viewable in the browser. It also allows saving
and sharing of programs with the auto-generated hyperlink hash-codes.
The official project is hosted at [try.haxe.org](https://try.haxe.org).
This repository is a direct successor of [try-haxe](https://github.com/clemos/try-haxe) project founded by [clemos](https://github.com/clemos) and it's fork the dockerized mrcdk version by [mrcdk](https://github.com/mrcdk).
## Technical notes
The try-haxe project is written in Haxe, with part of the application compiling to
JavaScript for use on the client, and part of the application compiling to PHP as
a backend service. The backend PHP service provides server-side compilation of
programs as well as language auto-complete results. The backend uses Docker to enable the use of multiple Haxe versions and macro support.
## Run your own instance (Docker)
### Install Docker and docker-compose
<https://www.docker.com/get-started>
### compile application
```bash
npm i lix
lix download
haxe build.hxml
```
### build all containers (in project root)
```bash
docker-compose -f docker-compose-all.yml up -d
```
you should get http server on `127.0.0.1:623`
Note: you might have to adjust web container's gid for docker group, to match your outside docker's gid. also make sure outside www-data user is part of docker group.
### install Haxe versions
(outside container - copy selected versions from your local lix installation). new versions show up after reloading your browser.
```bash
cp -a ~/haxe/neko lixSetup/haxe/neko
cp -a ~/haxe/versions/4.1.5 lixSetup/haxe/versions
```
### Recompile haxe code after you change source code outside
`haxe build.hxml`
### To shutdown container
`docker-compose -f docker-compose-all.yml down`
### Linux
Docker group can have a different group id / number than the web container's docker group. To fix it find docker group id:
`cat /etc/group | grep docker`
then use `docker exec -it try-haxe_web_1 /bin/bash` to enter web container and edit `/etc/group` inside:
```bash
apt install vim-tiny
vi /etc/group
# find entry with docker (should be last) and change number to host group id
:wq
service apache2 restart
```
### macOS
After building containers run:
`docker exec -it try-haxe_web_1 sh -c "chgrp docker /var/run/docker.sock; chmod g+w /var/run/docker.sock"`
| 31.407407 | 223 | 0.756682 | eng_Latn | 0.987978 |
48af7e8fea373d74be23efa896376fb35620ac52 | 3,236 | md | Markdown | _posts/2018-10-18-SEO-for-my-Jeykll-Blog.md | ctolan/ctolan.github.io | ebd80c52ba932cade887a116437afebfea0d0cbe | [
"MIT"
] | null | null | null | _posts/2018-10-18-SEO-for-my-Jeykll-Blog.md | ctolan/ctolan.github.io | ebd80c52ba932cade887a116437afebfea0d0cbe | [
"MIT"
] | null | null | null | _posts/2018-10-18-SEO-for-my-Jeykll-Blog.md | ctolan/ctolan.github.io | ebd80c52ba932cade887a116437afebfea0d0cbe | [
"MIT"
] | null | null | null | ---
layout: post
title: "Starting To Learn SEO"
date: 2018-10-18 09:56:31 +0100
author:
twitter: ConorT
tags: SEO Learning
---
I had some idea, but really no idea just how complex Search Engine Optimisation (SEO) had gotten. I have added Google Analytics to this site for insight and experience. I’m only starting out so as expected I’ve next to not readers, but with my PowerShell Lambda posts coming within a month of their publication I thought maybe I’d be higher in the organic ranking for the specific keywords AWS Lambda PowerShell. Boy was I wrong.
Not even close to the front page, I’m on with that, it is not why I’m doing this, but it got me wondering why.
I dug a little bit and started to wonder if my site was SEO optimised or not. I did have the [basic SEO enabled](https://blog.github.com/2016-05-10-better-discoverability-for-github-pages-sites/), but reading a couple of [optimise your Jekyll](https://blog.webjeda.com/optimize-jekyll-seo/) blog posts I found [posts about speed](https://blog.webjeda.com/jekyll-speed/) which linked out to [GTmetrix](https://gtmetrix.com/).
This site was a real eye opener to the sheer complexity of detail that goes into SEO. I had under estimated the impact of not resizing my images and the tests were quick to point out that my 3mb photo could be resized to 1400x800 and optimized to save 82% file size. It is detailed and specific, and highlighted the need for alt text on my images, which mostly I had. It though was able to see that my avatar did not have alt text. I ventured into my layouts and found the image src and added one, I added site.name as that’ll be me and it is better than hard coding it.
```html
<header class="masthead clearfix">
<a href="{{ site.baseurl }}/" class="site-avatar"><img src="{{ site.avatar }}" alt="{{ site.name }}"/></a>
```
Here is a scan of an optimised page, not a lot left I can optimise. I guess I can scale down my avatar photo….
On the waterfall tab you see the timeline of the items downloads for your page. My favicon was getting a 404, I’ve since fixed that. It was not an out of the box setting in Jeykll so it may never have happened if it was not for seeing this test.
One thing that struck me quite quickly is that this is not a quick process, it is not a case of flipping a switch and your entire blog is SEO’d. This will take time, time of resize and optimise my images, time to hunt down CSS for above and below the fold and time to tweak my URL choices, all for better organic search scores.
Check out my home page, after more than one pass at optimising it.
Still not pretty.
What was really insightful though was how bad the Disqus comments add on was for my page. I had tracking pixels and added to the page load time, all in all I decided to just remove it. It’ll be a project for another time to find a less intrusive comments section.
Maybe this is over thinking it and I should return to not caring for now, not until I’ve a lot more free time than I do right now. | 87.459459 | 570 | 0.757726 | eng_Latn | 0.999338 |
48af992555175d0f60f6e631795571e091eaa10a | 2,803 | md | Markdown | docs/index.md | mlfreeman2/NLog.Targets.Splunk | fb1459870c29aa8305ad6721bced010e3f0586ac | [
"Apache-2.0"
] | 8 | 2017-05-23T20:09:44.000Z | 2021-03-04T07:39:19.000Z | docs/index.md | mlfreeman2/NLog.Targets.Splunk | fb1459870c29aa8305ad6721bced010e3f0586ac | [
"Apache-2.0"
] | 43 | 2018-02-01T12:16:35.000Z | 2022-03-20T21:41:19.000Z | docs/index.md | mlfreeman2/NLog.Targets.Splunk | fb1459870c29aa8305ad6721bced010e3f0586ac | [
"Apache-2.0"
] | 26 | 2017-05-24T14:22:38.000Z | 2022-02-10T11:18:50.000Z | NLog.Targets.Splunk is a [Splunk HTTP Event Collector](http://dev.splunk.com/view/event-collector/SP-CAAAE7F) target for [NLog](http://nlog-project.org/)
[](https://badge.fury.io/nu/NLog.Targets.Splunk)
## Getting started
First you will need to have a running install of Splunk Enterprise and [setup a HTTP Event Collector](http://docs.splunk.com/Documentation/Splunk/latest/Data/UsetheHTTPEventCollector)
Then configure the SplunkHttpEventCollector with `ServerUrl` and `Token`:
```xml
<?xml version="1.0" encoding="utf-8" ?>
<nlog xmlns="http://www.nlog-project.org/schemas/NLog.xsd" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" >
<extensions>
<add assembly="NLog.Targets.Splunk" />
</extensions>
<targets async="true">
<target name="Splunk"
xsi:type="SplunkHttpEventCollector"
serverUrl="https://splunk-server:8088"
token="token-guid"
channel="channel-guid"
retriesOnError="0"
batchSizeBytes="0"
batchSizeCount="0"
includeEventProperties="true"
includeMdlc="false"
includePositionalParameters="false"
MaxConnectionsPerServer="10"
IgnoreSslErrors="false">
<contextproperty name="host" layout="${machinename}" />
<contextproperty name="threadid" layout="${threadid}" />
<contextproperty name="logger" layout="${logger}" />
</target>
</targets>
<rules>
<logger name="*" minlevel="Debug" writeTo="Splunk" />
</rules>
</nlog>
```
## Feedback / Issues
Feel free to tweet [@alanbarber](http://twitter.com/alanbarber) for questions or comments on the code.
You can also submit a GitHub issue [here](https://github.com/alanbarber/NLog.Targets.Splunk/issues).
## License
https://github.com/alanbarber/NLog.Targets.Splunk/blob/master/LICENSE
## Release Notes
### Verison 2.2.1
- Introduced MaxConnectionsPerServer property to limit number of connections to splunk server by Rolf Kristensen (https://github.com/snakefoot)
### Version 2.2.0
- Updated NLog version from 4.5.6 to 4.5.9
- Added support for Splunk HEC Data channel by David Matz (https://github.com/davidmatz)
### Version 2.1.0
- Updated NLog version from 4.5.3 to 4.5.6
- Adding 'IgnoreSslErrors' property to config to allow for using Splunk with self signed certs
- updated to work with NLog's paremeter tooling
- adding abilty to toggle logging of parameters on or off
- several performance updates
- Speical thanks to Rolf Kristensen (https://github.com/snakefoot) for help with this release!
### Version 2.0.0
- Updated to support .Net Standard 2.0 and .Net 4.5 w/ NLog 4.5.3
### Version 1.0.0
- Code cleanup and performance improvements
### Verison 0.0.1
- First publish to NuGet
| 34.182927 | 183 | 0.706386 | eng_Latn | 0.387508 |
48afaeb5f13b1b32adaee4c7b68e209239159b4e | 53 | md | Markdown | README.md | gargoyle-ai/alchemy | 939452d2f408347bf21eae9b6dd2fe7ca77126d0 | [
"MIT"
] | null | null | null | README.md | gargoyle-ai/alchemy | 939452d2f408347bf21eae9b6dd2fe7ca77126d0 | [
"MIT"
] | null | null | null | README.md | gargoyle-ai/alchemy | 939452d2f408347bf21eae9b6dd2fe7ca77126d0 | [
"MIT"
] | null | null | null | # alchemy
open source formulas for fighting COVID-19
| 17.666667 | 42 | 0.811321 | eng_Latn | 0.842573 |
48b0ba2cc77243a8a42c72ffaacb61a7f6adedc0 | 559 | md | Markdown | docs/selecting_fields.md | JessengBijleng/larapi | dae0a3b58c4bfd57e0abe00f61a629978a26793a | [
"MIT"
] | 88 | 2020-09-08T18:12:33.000Z | 2021-12-14T08:39:58.000Z | docs/selecting_fields.md | JessengBijleng/larapi | dae0a3b58c4bfd57e0abe00f61a629978a26793a | [
"MIT"
] | 8 | 2020-09-28T09:55:12.000Z | 2022-02-17T14:11:00.000Z | docs/selecting_fields.md | JessengBijleng/larapi | dae0a3b58c4bfd57e0abe00f61a629978a26793a | [
"MIT"
] | 12 | 2020-08-13T15:33:28.000Z | 2022-03-07T13:03:13.000Z | # Selecting fields
Sometimes you'll want to fetch only a couple fields to reduce the overall size of your SQL query. This can be done by specifying some fields in request by query parameter.
# Basic usage
The following example fetches only the users' id and name:
```console
{base_url}/users?select=id,name
```
The SQL query will look like this:
```sql
`SELECT "id", "name" FROM "users"`
```
# Selecting fields for included relations
The following example fetches only the authors' id and name:
```console
{base_url}/books?include=author:id,name.
``` | 22.36 | 171 | 0.744186 | eng_Latn | 0.999466 |
48b1295f294cf32ed75090825ece393595bfb539 | 199 | md | Markdown | README.md | reworkman/hummingbird | 768d724d8a31f0e974132ac0ed7e8147983bdc12 | [
"MIT"
] | 1 | 2017-09-26T01:55:03.000Z | 2017-09-26T01:55:03.000Z | README.md | reworkman/hummingbird | 768d724d8a31f0e974132ac0ed7e8147983bdc12 | [
"MIT"
] | 1 | 2018-09-30T00:34:25.000Z | 2018-09-30T00:34:25.000Z | README.md | reworkman/hummingbird | 768d724d8a31f0e974132ac0ed7e8147983bdc12 | [
"MIT"
] | 1 | 2018-08-14T12:10:45.000Z | 2018-08-14T12:10:45.000Z | # Hummingbird Analysis
This repo for code associated with analysis of Hummingbird transcriptomic data.
Contains parameters for BUSCO, GMAP, BLAST, ANGEL, and basic scripts for data manipulation.
| 39.8 | 92 | 0.809045 | eng_Latn | 0.971878 |
48b25ce50f705ef9f1bc7eb3935d24774e09d841 | 2,289 | md | Markdown | README.md | gradikay/Gradi-Kayamba-Project- | a74769e29b30164c63d445d9a1c380b067936386 | [
"BSD-2-Clause"
] | 1 | 2019-10-29T23:51:00.000Z | 2019-10-29T23:51:00.000Z | README.md | gradikay/Gradi-Kayamba-Project- | a74769e29b30164c63d445d9a1c380b067936386 | [
"BSD-2-Clause"
] | null | null | null | README.md | gradikay/Gradi-Kayamba-Project- | a74769e29b30164c63d445d9a1c380b067936386 | [
"BSD-2-Clause"
] | null | null | null | 
***
Welcome to my world! On here you can see some of my old and new work, please search on...!
`
Go here to see the webpage` https://gradikay.github.io/Gradi-Kayamba-Project/
***
## Where to start? Here is a starting point
`1. Gradi Kayamba Project` - Here you will know about the entire Git updates and how to navigate around!
`2. KinCentral News` - Here I have build a website with `XML, HTML5, CSS3, JAVASCRIPT`. https://gradikay.github.io/Kincentral-times/.
`3. Zonimoold` - Here you can see my old Animal Database project [See Animal Database for Updates]
`4. Animal Database` - Here you can see my 2015 project about an animal database. comming soon...
`5. Resposive CSS3` - Here you can see a project built with `CSS3 FLEXBOX` https://gradikay.github.io/Learning-Resposive-css/
```sh
# UPDATE AS OF 11/15/2019
ANIMAL DATABASE EXTENSIBLE (ADE)
```
`6. Learn HTML 101` - This is my cheatsheet on HTML. You can also see how I learned HTML.
***
# Overview
I am documenting my work, as I go to this journey of programming.
To me, programming could be summerized into one simple definition `"Freedom of the mind."`
```sh
# Gradi Kayamba
I am a Front-End | Back End Web Developer
```
***
### Checkout my old project code named `Zonimo` this aims to create an animal database
***
`7. CSS3 Animation` - See some animation powered with css. https://gradikay.github.io/css-animation-/
***
### Checkout my Table and Navigation designs
See table and navbars here!!! https://gradikay.github.io/kayamba-design/
| 36.919355 | 133 | 0.748362 | eng_Latn | 0.469401 |
48b2b66c4b183891a06e075ffc72c3f4d8a15e95 | 3,068 | md | Markdown | gatsby_files/typewriting_posts/src/pages/converted_posts/2003/six_or_less.md | sreynen/typewriting.org | 4f244bd6f766dc7aad3bc334253737d55d4ed180 | [
"MIT"
] | null | null | null | gatsby_files/typewriting_posts/src/pages/converted_posts/2003/six_or_less.md | sreynen/typewriting.org | 4f244bd6f766dc7aad3bc334253737d55d4ed180 | [
"MIT"
] | 2 | 2018-09-19T11:55:30.000Z | 2018-12-16T20:03:07.000Z | gatsby_files/typewriting_posts/src/pages/converted_posts/2003/six_or_less.md | sreynen/typewriting.org | 4f244bd6f766dc7aad3bc334253737d55d4ed180 | [
"MIT"
] | null | null | null | ---
path: "/2003/11/07/six_or_less"
date: "2003/11/07 22:43:18"
title: "six or less"
---
<p><a href="http://weblog.delacour.net/archives/2003/11/vivacious.php">jonathon delacour</a> writes <q>I also enjoy talking about interesting things with not just "one or two" but up to *three* people!</q> last night i attended a meeting with three other people. the meeting went well. the night before, i attended a meeting with six or seven other people. that meeting also went well, but looking back, it occurs to me that it may not have gone so well (from my perspective) had we sat at a round table. as it was conversation generally polarized toward the ends of the long table, in groups of three or four. last week i attended a meeting with about twenty other people, but we split into groups of two or three for a large part of the meeting.</p><br><p>this last meeting was for the <a href="http://bncpj.pabn.org/">bloomington-normal citizens for peace and justice</a>, a local community organization i've been involved in to varying degrees, depending on my geographic distance, since it was founded shortly after september 11, 2001. now that i'm back in bloomington-normal, i'm much more actively involved than i was from taiwan or michigan. and i've resumed pushing for more small group time. this pushing played some part in the small group time we had at the last meeting.</p><br><p>prior to today, i would have said that my reason for pushing for small groups is something i read a long time ago in a book about the practice of organization. the book said something like "meet in groups of six or less", and i've since been encouraging organizations i'm involved in to do just that. but it occurs to me now that my interest in that advice and my remembering it for years after are likely strongly tied to being an introvert. were i an extrovert, i might well have read that same passage and discarded the advice in an instant, finding large groups much more conducive to getting work done.</p><br><p>i still think the advice sound, however, even after realizing my own bias toward accepting it. my reasoning now is that any organization is likely to have introverts as members, and i suspect (though i'm not at all sure) whatever discomfort an extrovert may feel in participating in a small group is significantly less than that an introvert feels in participating in a large group. for the groups i'm involved in, participation is vital. <a href="http://mamamusings.net/archives/2003/03/03/an_extrovert_speaks_quelle_surprise.php">elizabeth lawley</a> has done some intial explaining of extrovert perspective, but i still have a question for any extroverts out there: do extroverts feel uncomfortable participating in small groups? maybe "uncomfortable" is the wrong word even. when i'm in a large group setting, i don't usually feel "uncomfortable" participating. i more often feel unable to participate, because the pace of conversation is faster than my ability to solidify my thoughts. do extroverts have a similar (or opposite) sensation in small groups?</p> | 511.333333 | 2,976 | 0.78455 | eng_Latn | 0.999868 |
48b2d4f2227ef9699a4a8f427cd9dbc850f38419 | 6,396 | md | Markdown | servlets/2.Web Technologies Basics.md | sakav1111/sakav1111.github.io | 9b492477312b7e05d6430f7f543b003b74545d53 | [
"MIT"
] | null | null | null | servlets/2.Web Technologies Basics.md | sakav1111/sakav1111.github.io | 9b492477312b7e05d6430f7f543b003b74545d53 | [
"MIT"
] | 1 | 2020-10-19T12:55:08.000Z | 2021-12-20T11:43:09.000Z | servlets/2.Web Technologies Basics.md | sakav1111/sakav1111.github.io | 9b492477312b7e05d6430f7f543b003b74545d53 | [
"MIT"
] | null | null | null | ---
title: Servlets- Web Technologies Basics
permalink: "/servlets/web-technologies-basics"
key: servlets-web-technologies-basics
categories:
- Servlets
tags:
- Servlets
---
Basics of Web Technologies
============================
| **Static Website** | **Dynamic Website** |
|-------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------|
| Prebuilt content is same every time the page is loaded. | Content is generated quickly and changes regularly. |
| It uses the **HTML **code for developing a website. | It uses the server side languages such as **PHP, SERVLET, JSP, and ASP.NET **etc. for developing a website. |
| It sends exactly the same response for every request. | It may generate different HTML for each of the request. |
| The content is only changes when someone publishes and updates the file (sends it to the web server). | The page contains **"server-side"** code it allows the server to generate the unique content when the page is loaded. |
<br>
**1. HTTP (Hyper Text Transfer Protocol)**
HTTP is TCP/IP based communication protocol, which is used to deliver the data
like image files, query results, HTML files etc on the World Wide Web (WWW) with
the default port is TCP 80. It provides the standardized way for computers to
communicate with each other.
There are three fundamental features that make the HTTP a simple and powerful
protocol used for communication:
- **HTTP is media independent:** It refers to any type of media content can be
sent by HTTP as long as both the server and the client can handle the data
content.
- **HTTP is connectionless:** It is a connectionless approach in which HTTP
client i.e., a browser initiates the HTTP request and after the request is
sends the client disconnects from server and waits for the response.
- **HTTP is stateless:** The client and server are aware of each other during
a current request only. Afterwards, both of them forget each other. Due to
the stateless nature of protocol, neither the client nor the server can
retain the information about different request across the web pages.
<br>
**2. HTTP Requests**
The request sends by the computer to a web server that contains all sorts of
potentially interesting information is known as HTTP requests.
It will send following information to Server
- The analysis of source IP address, proxy and port
- The analysis of destination IP address, protocol, port and host
- The Requested URI (Uniform Resource Identifier)
- The Request method and Content
- The User-Agent header
- The Connection control header
We have following HTTP request methods:
<br>
**3. GET vs POST**
| **GET** | **POST** |
|------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------|
| 1) In case of Get request, only limited amount of data can be sent because data is sent in header. | In case of post request, large amount of data can be sent because data is sent in body. |
| 2) Get request is not secured because data is exposed in URL bar. | Post request is secured because data is not exposed in URL bar. |
| 3) Get request **can be bookmarked.** | Post request **cannot be bookmarked.** |
| 4) Get request is **idempotent.** It means second request will be ignored until response of first request is delivered | Post request is **non-idempotent.** |
| 5) Get request is **more efficient** and used more than Post. | Post request is **less efficient** and used less than get. |
<br>
**4. Servlet Container:**
is the place where Servlet programs are executed
The servlet container is used in java for dynamically generate the web pages on
the server side. Therefore the servlet container is the part of a web server
that interacts with the servlet for handling the dynamic web pages from the
client.
*The Servlet Container performs many operations that are given below:*
**Life Cycle Management**
1. **Multithreaded support**
2. **Object Pooling**
3. **Security etc.**
<br>
**5. Web Server VS Application Server**
<br>
**6. Content Type**
Content Type is also known as MIME (Multipurpose internet Mail Extension) Type.
It is a HTTP header that provides the description about what are you sending to
the browser.
- **It supports the non-ASCII characters**
- **It supports the multiple attachments in a single message**
- **It supports the attachment contains audio, images and video files etc.**
- **It supports the unlimited message length.**
Commonly used content types are given below:
- **text/html**
- **text/plain**
- **application/msword**
- **application/vnd.ms-excel**
- **application/jar**
- **application/pdf**
- **application/octet-stream**
- **application/x-zip**
- **images/jpeg**
- **images/png**
- **images/gif**
- **audio/mp3**
- **video/mp4**
- **Video/quicktime etc.** | 41 | 225 | 0.560663 | eng_Latn | 0.994289 |
48b3052f841a10a4361a8f18fb4b0d47afd5eadf | 4,767 | md | Markdown | _posts/2016-08-24-Where-Not-To-Put-Your-Tablespaces.md | hunleyd/lanyon | 0f1153fc4af3d718d29143f581cc57e52b28a776 | [
"MIT"
] | null | null | null | _posts/2016-08-24-Where-Not-To-Put-Your-Tablespaces.md | hunleyd/lanyon | 0f1153fc4af3d718d29143f581cc57e52b28a776 | [
"MIT"
] | null | null | null | _posts/2016-08-24-Where-Not-To-Put-Your-Tablespaces.md | hunleyd/lanyon | 0f1153fc4af3d718d29143f581cc57e52b28a776 | [
"MIT"
] | null | null | null | ---
date: 2016-08-24 11:55:12
layout: post
title: Where Not To Put Your Tablespaces
tags:
- postgresql
---
From the PostgreSQL [docs](https://www.postgresql.org/docs/current/static/manage-ag-tablespaces.html):
> Tablespaces in PostgreSQL allow database administrators to define locations in the file system where the files representing database objects can be stored. Once created, a tablespace can be referred to by name when creating database objects.
> By using tablespaces, an administrator can control the disk layout of a PostgreSQL installation. This is useful in at least two ways. First, if the partition or volume on which the cluster was initialized runs out of space and cannot be extended, a tablespace can be created on a different partition and used until the system can be reconfigured.
> Second, tablespaces allow an administrator to use knowledge of the usage pattern of database objects to optimize performance. For example, an index which is very heavily used can be placed on a very fast, highly available disk, such as an expensive solid state device. At the same time a table storing archived data which is rarely used or not performance critical could be stored on a less expensive, slower disk system.
As you can see, while not as powerful as tablespaces in, say, Oracle, they do still have their uses in PostgreSQL. You can use them to make use of different filesystems, or different mount options, or different disk types and, in doing so, intelligently apply performance characteristics to subsets of your data. For example, you could put your highest volume tables in a tablespace that is mounted from SSDs while the rest of your db is mounted from spinning rust.
Sounds decent, right? Now you before you go off and be "clever" and create an SSD-backed mountpoint for your new tablespace, understand that there are places you *should not* create the tablespace. You shouldn't create tablespaces on any kind of ephemeral storage, for example on a `tmpfs` or a `ramfs` or similar. *You also should not create your new tablespaces under $PGDATA*. Yes, I'm aware there is `$PGDATA/pg_tblspc` but that directory is *not for you*. The system will auto-populate that directory with pointers to the real location of your tablespaces!
So what happens when you create a tablespace inside $PGDATA? Let's find out. First, we'll create the directory for the tablespace:
```bash
$ mkdir $PGDATA/tablespaces
$ cd $PGDATA/tablespaces
$ pwd
/Users/doug.hunley/pgdata/tablespaces
```
And we see that nothing bad has happened yet. So, let's pop over into `psql` and actually create the tablespace:
```sql
> CREATE TABLESPACE ts1 LOCATION '/Users/doug.hunley/pgdata/tablespaces';
WARNING: 42P17: tablespace location should not be inside the data directory
LOCATION: CreateTableSpace, tablespace.c:295
CREATE TABLESPACE
Time: 7.797 ms
```
We get a warning (not an error, for some reason) but it works and all appears fine. Now you can spend minutes/days/months/years using your new tablespace and never notice that you've got a problem. So where does the problem come in?
Let's try to make a backup of our cluster:
```bash
$ pg_basebackup -D pgdata2 -Fp -R -Xs -c fast -l 'clone for slave' -P -v
transaction log start point: 2/17000028 on timeline 1
pg_basebackup: directory "/Users/doug.hunley/pgdata/tablespaces" exists but is not empty
```
There it is.
When creating the backup, it tries to ensure the tablespace location is the same, but then it won't write to a non-empty directory. My example is two different $PGDATA locations on the same box, but the issue is the same when using different machines because `pg_basebackup` backs up *everything* in $PGDATA which means your tablespace directory gets cloned before it gets to the actual cloning of the data in the tablespace so you end up with "stuff" in the dir, making it non-empty. Which gives you the same error and output.
OK, so it breaks backups. I can work around that by using another backup method. What else?
How about using `pg_upgrade` to do an upgrade? No matter if you run in `link` mode or not, `pg_upgrade` *will not move* your tablespace location. So you may have `~/pgdata95` and `~/pgdata96` after the upgrade, but your tablespaces *are still in* `~/pgdata95/tablespaces`. So, as per the [docs](https://www.postgresql.org/docs/current/static/pgupgrade.html):
> Once you are satisfied with the upgrade, you can delete the old cluster's data directories by running the script mentioned when pg_upgrade completes.
And *boom* you've just deleted your tablespaces off disk. Congratulations!
So there you have it. Two very good reasons to not create tablespaces inside $PGDATA. Please, don't do this. Everyone who admins that cluster going forward will thank you.
| 75.666667 | 561 | 0.782043 | eng_Latn | 0.998478 |
48b325eec46e050e911772b0f22c7f796164d5ca | 649 | md | Markdown | _posts/2006-07-12-server-response-sms.md | devinreams/devinreams.github.io | 711fdc2ab52144f4b42e15d44ec3b1f005caef9f | [
"CC-BY-3.0",
"MIT"
] | null | null | null | _posts/2006-07-12-server-response-sms.md | devinreams/devinreams.github.io | 711fdc2ab52144f4b42e15d44ec3b1f005caef9f | [
"CC-BY-3.0",
"MIT"
] | 3 | 2015-07-02T11:39:12.000Z | 2017-10-11T17:09:54.000Z | _posts/2006-07-12-server-response-sms.md | devinreams/devinreams.github.io | 711fdc2ab52144f4b42e15d44ec3b1f005caef9f | [
"CC-BY-3.0",
"MIT"
] | 1 | 2015-07-02T00:31:38.000Z | 2015-07-02T00:31:38.000Z | ---
title: Server Response SMS
author: Devin Reams
layout: post
permalink: /2006/server-response-sms/
btc_comment_counts:
- 'a:0:{}'
categories:
- Internet
tags:
- Antiquated
---
If I can find just one person who understands [these codes][1] that’d make my <strike>day</strike> year. I don’t know why but I’d get a certain amount of pleasure using server response codes to converse. Someday, I can imagine this moving into everyday conversation, just like ‘lol’ and ‘omg’ I can tell that girl that her dress is 406.
[1]: http://lizrevision.com/lol/sms-shorthand-for-geeks-using-server-response-codes | 43.266667 | 378 | 0.742681 | eng_Latn | 0.970876 |
48b41ca7c332d231ab6acde57357becd91f56017 | 73 | md | Markdown | README.md | aikrasnov/otus-examples | 607fe0c11d812bdff57d92fc0949d5bdf3356c22 | [
"MIT"
] | 8 | 2019-11-03T18:59:08.000Z | 2020-10-10T18:50:09.000Z | README.md | aikrasnov/otus-examples | 607fe0c11d812bdff57d92fc0949d5bdf3356c22 | [
"MIT"
] | null | null | null | README.md | aikrasnov/otus-examples | 607fe0c11d812bdff57d92fc0949d5bdf3356c22 | [
"MIT"
] | null | null | null | # otus-examples
Примеры для курса по питону
https://github.com/aikrasnov | 18.25 | 28 | 0.794521 | rus_Cyrl | 0.224636 |
48b55bfbb3d84cc2a2625cc5ee6a4ef20f32d5bb | 38 | md | Markdown | README.md | ylamgarchal/dci-pipeline | a8ff167745eecdd9fd998237c452b6ee2024a184 | [
"Apache-2.0"
] | 1 | 2020-06-17T12:46:23.000Z | 2020-06-17T12:46:23.000Z | README.md | ylamgarchal/dci-pipeline | a8ff167745eecdd9fd998237c452b6ee2024a184 | [
"Apache-2.0"
] | 1 | 2020-07-13T10:27:07.000Z | 2020-07-13T10:27:07.000Z | README.md | ylamgarchal/dci-pipeline | a8ff167745eecdd9fd998237c452b6ee2024a184 | [
"Apache-2.0"
] | 2 | 2020-06-19T08:55:49.000Z | 2020-07-10T19:38:49.000Z | # CI pipeline management for DCI jobs
| 19 | 37 | 0.789474 | eng_Latn | 0.952022 |
48b68c86e0077d28004b555461b4c608c3d310d1 | 716 | md | Markdown | sources/h/hair-dryer.md | ordbok/ordbok-translations | 58a0e964731f3cbd06e89b1ed487b34abfdb916b | [
"MIT"
] | null | null | null | sources/h/hair-dryer.md | ordbok/ordbok-translations | 58a0e964731f3cbd06e89b1ed487b34abfdb916b | [
"MIT"
] | 3 | 2019-07-13T16:21:52.000Z | 2022-01-19T22:57:06.000Z | sources/h/hair-dryer.md | ordbok/translations | 0b696aa111e2e293c921351f18248cc6e5a03a30 | [
"MIT"
] | null | null | null | Meta
====
Structure: Singular, Indefinite ; Singular, Definite ; Plural, Indefinite ; Plural, Definite
Grammar: Noun
English
=======
Translation: (a) hair dryer ; the hair dryer ; hair dryers ; the hair dryers
Grammar: Neuter
German
======
Translation: (ein) Haartrockner ; der Haartrockner ; Haartrockner ; die Haartrockner
Grammar: Masculine
New Norwegian
=============
Translation: (ein) hårtørkar ; hårtørkaren ; hårtørkarar ; hårtørkarane
Grammar: Masculine
Norwegian
=========
Translation: (en) hårtørker ; hårtørkeren ; hårtørkere ; hårtørkerne
Grammar: Masculine
Swedish
=======
Translation: (en) hårtork ; hårtorken ; hårtorkar ; hårtorkarna
Grammar: Common
| 13.769231 | 92 | 0.680168 | dan_Latn | 0.227203 |
48b6ed80845e3087e15c3fd3cb3aac2d6c0f7cdf | 15,137 | md | Markdown | articles/search/search-api-migration.md | maiemy/azure-docs.it-it | b3649d817c2ec64a3738b5f05f18f85557d0d9b6 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | articles/search/search-api-migration.md | maiemy/azure-docs.it-it | b3649d817c2ec64a3738b5f05f18f85557d0d9b6 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | articles/search/search-api-migration.md | maiemy/azure-docs.it-it | b3649d817c2ec64a3738b5f05f18f85557d0d9b6 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | ---
title: Aggiornare le versioni dell'API REST
titleSuffix: Azure Cognitive Search
description: Esaminare le differenze nelle versioni dell'API e scoprire quali azioni sono necessarie per eseguire la migrazione del codice esistente alla versione più recente dell'API REST del servizio ricerca cognitiva di Azure.
manager: nitinme
author: brjohnstmsft
ms.author: brjohnst
ms.service: cognitive-search
ms.topic: conceptual
ms.date: 10/09/2020
ms.openlocfilehash: d7734fde529c24e8113ea3b019d343b7223f0122
ms.sourcegitcommit: 50802bffd56155f3b01bfb4ed009b70045131750
ms.translationtype: MT
ms.contentlocale: it-IT
ms.lasthandoff: 10/09/2020
ms.locfileid: "91929643"
---
# <a name="upgrade-to-the-latest-rest-api-in-azure-cognitive-search"></a>Eseguire l'aggiornamento alla versione più recente dell'API REST in Azure ricerca cognitiva
Se si usa una versione precedente dell' [**API REST di ricerca**](/rest/api/searchservice/), questo articolo consentirà di aggiornare l'applicazione alla versione più recente dell'API disponibile a livello generale, **2020-06-30**.
La versione 2020-06-30 include una nuova funzionalità importante ([Archivio informazioni](knowledge-store-concept-intro.md)) e introduce diverse modifiche di comportamento minori. Questa versione è per lo più compatibile con le versioni precedenti, pertanto le modifiche al codice devono essere minime se si esegue l'aggiornamento dalla versione precedente (2019-05-06).
> [!NOTE]
> Un servizio di ricerca supporta un intervallo di versioni dell'API REST, incluse quelle precedenti. È possibile continuare a usare queste versioni dell'API, ma è consigliabile eseguire la migrazione del codice alla versione più recente, in modo da poter accedere a nuove funzionalità. Nel corso del tempo, le versioni più obsolete dell'API REST saranno deprecate e [non sono più supportate](search-api-versions.md#unsupported-versions).
<a name="UpgradeSteps"></a>
## <a name="how-to-upgrade"></a>Come eseguire l'aggiornamento
Quando si esegue l'aggiornamento a una nuova versione, probabilmente non sarà necessario apportare molte modifiche al codice, tranne che per modificare il numero di versione. Le uniche situazioni in cui può essere necessario modificare il codice si verificano quando:
* Il codice ha esito negativo quando vengono restituite proprietà sconosciute in una risposta API. Per impostazione predefinita, l'applicazione deve ignorare le proprietà che non riconosce.
* Il codice rende persistenti le richieste API e tenta di inviarle nuovamente alla nuova versione dell'API. Ad esempio, questa situazione può verificarsi se l'applicazione mantiene i token di continuazione restituiti dall'API di ricerca. Per altre informazioni, cercare `@search.nextPageParameters` nel [riferimento all'API di ricerca](/rest/api/searchservice/Search-Documents).
* Il codice fa riferimento a una versione API che precede 2019-05-06 ed è soggetta a una o più delle modifiche di rilievo apportate a tale versione. La sezione [aggiornamento a 2019-05-06](#upgrade-to-2019-05-06) fornisce maggiori dettagli.
Se si verifica una di queste situazioni, potrebbe essere necessario modificare il codice di conseguenza. In caso contrario, non dovrebbe essere necessario apportare modifiche, anche se è possibile iniziare a usare le funzionalità aggiunte nella nuova versione.
## <a name="upgrade-to-2020-06-30"></a>Aggiornamento a 2020-06-30
La versione 2020-06-30 è la nuova versione disponibile a livello generale dell'API REST. Esiste una modifica sostanziale e diverse differenze di comportamento.
Le funzionalità sono ora disponibili a livello generale in questa versione dell'API, tra cui:
* [Archivio informazioni](knowledge-store-concept-intro.md), archiviazione permanente di contenuti arricchiti creati tramite skillsets, creati per l'analisi downstream e l'elaborazione tramite altre applicazioni. Con questa funzionalità, una pipeline di arricchimento di intelligenza artificiale basata sull'indicizzatore può popolare un archivio informazioni oltre a un indice di ricerca. Se è stata usata la versione di anteprima di questa funzionalità, è equivalente alla versione disponibile a livello generale. L'unica modifica del codice richiesta è la modifica della versione API.
### <a name="breaking-change"></a>Modifica
Il codice esistente scritto con le versioni precedenti dell'API si interrompe in API-Version = 2020-06-30 e versioni successive se il codice contiene le funzionalità seguenti:
* Tutti i valori letterali EDM. date (una data costituita dall'anno-mese-giorno, ad esempio `2020-12-12` ) nelle espressioni di filtro devono seguire il formato EDM. DateTimeOffset: `2020-12-12T00:00:00Z` . Questa modifica era necessaria per gestire i risultati di query errati o imprevisti a causa di differenze del fuso orario.
### <a name="behavior-changes"></a>Modifiche del comportamento
* L' [algoritmo di classificazione BM25](index-ranking-similarity.md) sostituisce l'algoritmo di classificazione precedente con la tecnologia più recente. I nuovi servizi utilizzeranno questo algoritmo automaticamente. Per i servizi esistenti, è necessario impostare i parametri per l'utilizzo del nuovo algoritmo.
* I risultati ordinati per i valori null sono stati modificati in questa versione, con i valori Null visualizzati per primi se l'ordinamento è `asc` e l'ultimo se l'ordinamento è `desc` . Se è stato scritto codice per gestire il modo in cui vengono ordinati i valori null, tenere presente questa modifica.
## <a name="upgrade-to-2019-05-06"></a>Aggiornamento a 2019-05-06
La versione 2019-05-06 è la versione disponibile a livello generale precedente dell'API REST. Le funzionalità che sono diventate disponibili a livello generale in questa versione dell'API includono:
* Il [completamento automatico](index-add-suggesters.md) è una funzionalità di typeahead che completa un input di termine parzialmente specificato.
* I [tipi complessi](search-howto-complex-data-types.md) forniscono il supporto nativo per i dati di oggetti strutturati nell'indice di ricerca.
* [Modalità di analisi di JsonLines](search-howto-index-json-blobs.md), parte dell'indicizzazione BLOB di Azure, crea un documento di ricerca per entità JSON separato da una nuova riga.
* L' [arricchimento di intelligenza artificiale](cognitive-search-concept-intro.md) fornisce l'indicizzazione che sfrutta i motori di arricchimento di intelligenza artificiale dei servizi cognitivi.
### <a name="breaking-changes"></a>Modifiche di rilievo
Il codice esistente scritto con le versioni precedenti dell'API si interrompe in API-Version = 2019-05-06 e versioni successive se il codice contiene le funzionalità seguenti:
#### <a name="indexer-for-azure-cosmos-db---datasource-is-now-type-cosmosdb"></a>Indexer per Azure Cosmos DB-DataSource è ora "Type": "cosmosdb"
Se si utilizza un [indicizzatore di Cosmos DB](search-howto-index-cosmosdb.md ), è necessario modificare `"type": "documentdb"` in `"type": "cosmosdb"` .
#### <a name="indexer-execution-result-errors-no-longer-have-status"></a>Gli errori di risultato dell'esecuzione dell'indicizzatore non hanno più lo stato
La struttura di errore per l'esecuzione dell'indicizzatore aveva in precedenza un `status` elemento. Questo elemento è stato rimosso perché non forniva informazioni utili.
#### <a name="indexer-data-source-api-no-longer-returns-connection-strings"></a>L'API dell'origine dati dell'indicizzatore non restituisce più le stringhe di connessione
Dalle versioni API 2019-05-06 e 2019-05-06-Preview in poi, l'API dell'origine dati non restituisce più le stringhe di connessione nella risposta di qualsiasi operazione REST. Nelle versioni precedenti dell'API, per le origini dati create con POST, Azure ricerca cognitiva ha restituito **201** seguito dalla risposta OData, che conteneva la stringa di connessione in testo normale.
#### <a name="named-entity-recognition-cognitive-skill-is-now-discontinued"></a>Il riconoscimento delle entità denominate skill cognitive è ora interrotto
Se è stata chiamata la competenza [Riconoscimento entità nome](cognitive-search-skill-named-entity-recognition.md) nel codice, la chiamata avrà esito negativo. La funzionalità di sostituzione è il [riconoscimento delle entità](cognitive-search-skill-entity-recognition.md). Dovrebbe essere possibile sostituire il riferimento a skill senza altre modifiche. La firma API è identica per entrambe le versioni.
### <a name="upgrading-complex-types"></a>Aggiornamento di tipi complessi
La versione API 2019-05-06 ha aggiunto il supporto formale per i tipi complessi. Se il codice ha implementato raccomandazioni precedenti per l'equivalenza dei tipi complessi in 2017-11-11-Preview o 2016-09-01-Preview, sono stati introdotti alcuni limiti nuovi e modificati a partire dalla versione 2019-05-06 di cui è necessario essere consapevoli:
+ I limiti relativi alla profondità dei sottocampi e al numero di raccolte complesse per indice sono stati ridotti. Se sono stati creati indici che superano questi limiti usando le versioni API di anteprima, qualsiasi tentativo di aggiornarli o ricrearli usando l'API versione 2019-05-06 avrà esito negativo. Se si applica questo problema, sarà necessario riprogettare lo schema in base ai nuovi limiti e quindi ricompilare l'indice.
+ È presente un nuovo limite a partire da API-Version 2019-05-06 sul numero di elementi di raccolte complesse per documento. Se sono stati creati indici con documenti che superano questi limiti usando le versioni API di anteprima, qualsiasi tentativo di reindicizzare i dati con API-Version 2019-05-06 avrà esito negativo. Se si applica questo problema, sarà necessario ridurre il numero di elementi di raccolta complessi per documento prima di reindicizzare i dati.
Per altre informazioni, vedere [limiti dei servizi per Azure ricerca cognitiva](search-limits-quotas-capacity.md).
#### <a name="how-to-upgrade-an-old-complex-type-structure"></a>Come aggiornare una struttura di tipi complessi obsoleti
Se il codice usa tipi complessi con una delle versioni precedenti dell'API di anteprima, è possibile che si stia usando un formato di definizione di indice simile al seguente:
```json
{
"name": "hotels",
"fields": [
{ "name": "HotelId", "type": "Edm.String", "key": true, "filterable": true },
{ "name": "HotelName", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": true, "facetable": false },
{ "name": "Description", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "en.microsoft" },
{ "name": "Description_fr", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "fr.microsoft" },
{ "name": "Category", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "Tags", "type": "Collection(Edm.String)", "searchable": true, "filterable": true, "sortable": false, "facetable": true, "analyzer": "tagsAnalyzer" },
{ "name": "ParkingIncluded", "type": "Edm.Boolean", "filterable": true, "sortable": true, "facetable": true },
{ "name": "LastRenovationDate", "type": "Edm.DateTimeOffset", "filterable": true, "sortable": true, "facetable": true },
{ "name": "Rating", "type": "Edm.Double", "filterable": true, "sortable": true, "facetable": true },
{ "name": "Address", "type": "Edm.ComplexType" },
{ "name": "Address/StreetAddress", "type": "Edm.String", "filterable": false, "sortable": false, "facetable": false, "searchable": true },
{ "name": "Address/City", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "Address/StateProvince", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "Address/PostalCode", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "Address/Country", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true },
{ "name": "Location", "type": "Edm.GeographyPoint", "filterable": true, "sortable": true },
{ "name": "Rooms", "type": "Collection(Edm.ComplexType)" },
{ "name": "Rooms/Description", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "en.lucene" },
{ "name": "Rooms/Description_fr", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "fr.lucene" },
{ "name": "Rooms/Type", "type": "Edm.String", "searchable": true },
{ "name": "Rooms/BaseRate", "type": "Edm.Double", "filterable": true, "facetable": true },
{ "name": "Rooms/BedOptions", "type": "Edm.String", "searchable": true },
{ "name": "Rooms/SleepsCount", "type": "Edm.Int32", "filterable": true, "facetable": true },
{ "name": "Rooms/SmokingAllowed", "type": "Edm.Boolean", "filterable": true, "facetable": true },
{ "name": "Rooms/Tags", "type": "Collection(Edm.String)", "searchable": true, "filterable": true, "facetable": true, "analyzer": "tagsAnalyzer" }
]
}
```
Un nuovo formato di tipo albero per la definizione dei campi di indice è stato introdotto nella versione API 2017-11-11-Preview. Nel nuovo formato ogni campo complesso dispone di una raccolta di campi in cui sono definiti i relativi campi secondari. Nella versione API 2019-05-06, questo nuovo formato viene usato esclusivamente e il tentativo di creare o aggiornare un indice con il vecchio formato avrà esito negativo. Se sono stati creati indici con il formato precedente, sarà necessario usare la versione API 2017-11-11-Preview per aggiornarli nel nuovo formato prima di poterli gestire con la versione 2019-05-06 dell'API.
È possibile aggiornare gli indici "flat" al nuovo formato con i passaggi seguenti usando l'API versione 2017-11-11-Preview:
1. Eseguire una richiesta GET per recuperare l'indice. Se è già nel nuovo formato, l'operazione è terminata.
2. Tradurre l'indice dal formato "flat" al nuovo formato. È necessario scrivere codice perché non è disponibile codice di esempio al momento della stesura di questo articolo.
3. Eseguire una richiesta PUT per aggiornare l'indice al nuovo formato. Assicurarsi di non modificare altri dettagli dell'indice, ad esempio la ricercabilità/filtrabilità dei campi, perché questo non è consentito dall'API Update index.
> [!NOTE]
> Non è possibile gestire gli indici creati con il vecchio formato "flat" dal portale di Azure. Aggiornare gli indici dalla rappresentazione "flat" alla rappresentazione "Tree" con la prima convenienza.
## <a name="next-steps"></a>Passaggi successivi
Vedere la documentazione di riferimento dell'API REST di ricerca. Se si verificano problemi, chiedere assistenza per [stack overflow](https://stackoverflow.com/) o [contattare il supporto tecnico](https://azure.microsoft.com/support/community/?product=search).
> [!div class="nextstepaction"]
> [Informazioni di riferimento sull'API REST del servizio di ricerca](/rest/api/searchservice/)
| 97.032051 | 628 | 0.768052 | ita_Latn | 0.996937 |
48b70b3a015cfcde2e1b5bef028607c67a36fb67 | 624 | md | Markdown | readme.md | HackRU/ludicrous-hackru-components | 1909c5c82a9ad701bae62a8256d5df4bea8d5e5d | [
"MIT"
] | null | null | null | readme.md | HackRU/ludicrous-hackru-components | 1909c5c82a9ad701bae62a8256d5df4bea8d5e5d | [
"MIT"
] | null | null | null | readme.md | HackRU/ludicrous-hackru-components | 1909c5c82a9ad701bae62a8256d5df4bea8d5e5d | [
"MIT"
] | null | null | null | # HackRU: Ludicrous Component Library (LCL)
_"Everything is ludicrous!"_
[](https://www.npmjs.com/package/lcs) [](https://standardjs.com)
## Quick Start
Run the following commands:
```bash
git clone https://github.com/HackRU/ludicrous-hackru-components
cd lcl
npm install
cd examples
npm install
cd ..
npm run dev
```
This will spawn three instances processes:
## License
MIT © [HackRU](https://github.com/hackru) 2019
`HackRU Frontend Team` | 27.130435 | 199 | 0.746795 | yue_Hant | 0.234876 |
48b76614a4a1c31d63c13c278e8e7c86b73fe3c8 | 2,734 | md | Markdown | CHANGELOG.md | mjankowski/basecrm-ruby | f73c439c347c6d183044616ac6e6a34401540b0f | [
"MIT"
] | 1 | 2020-01-16T18:05:29.000Z | 2020-01-16T18:05:29.000Z | CHANGELOG.md | mjankowski/basecrm-ruby | f73c439c347c6d183044616ac6e6a34401540b0f | [
"MIT"
] | null | null | null | CHANGELOG.md | mjankowski/basecrm-ruby | f73c439c347c6d183044616ac6e6a34401540b0f | [
"MIT"
] | 1 | 2021-01-07T10:20:37.000Z | 2021-01-07T10:20:37.000Z | ## CHANGELOG
v1.3.6 (2019-02-18)
**Features and Improvements**
* Update Contact model documentation
* Replace deprecated `BigDecimal.new()` with `BigDecimal()`
* Replace deprecated `FactoryGirl` gem with `FactoryBot` gem
v1.3.5 (2018-10-09)
**Features and Improvements**
* Added new models support: TextMessage, Visit and VisitOutcome
v1.3.4 (2018-07-04)
**Features and Improvements**
* Added new models support: Call, CallOutcome
v1.3.3 (2018-06-05)
**Features and Improvements**
* Added new models support: LeadUnqualifiedReason, DealUnqualifiedReason
v1.3.2 (2018-01-11)
**Features and Improvements**
* Fixed undefined method exception on error handling [issue #54](https://github.com/basecrm/basecrm-ruby/issues/54)
v1.3.1 (2017-12-08)
**Features and Improvements**
* Fixed issue where could not update deal without passing value
v1.3.0 (2017-10-19)
**Features and Improvements**
* Added new models support: LeadSource, DealSource, Product, Order, LineItem
* Deal model update, added estimated_close_date and customized_win_likelihood
v1.2.3 (2017-10-02)
**Features and Improvements**
* Missing source_id in Leads model
* Relax upper version boundary for JSON gem dependency
v1.2.2 (2017-04-03)
**Features and Improvements**
* Missing last_stage_change_at in Deals model [#45](https://github.com/basecrm/basecrm-ruby/pull/45)
v1.2.1 (2016-11-18)
**Features and Improvements**
* Fix deal creation with hash as argument [#39](https://github.com/basecrm/basecrm-ruby/pull/39)
## v1.2.0 (2016-07-24)
**Features and Improvements**
* Decimal deal values support [#34](https://github.com/basecrm/basecrm-ruby/pull/34)
* Deal value is now a BigDecimal [#34](https://github.com/basecrm/basecrm-ruby/pull/34)
### v1.1.3 (2015-06-17)
**Features and Improvements**
* Compatibility with Ruby 2.0.0+
### v1.1.2 (2015-06-17)
**Features and Improments**
* `BaseCRM::HttpClient` prints response payload in debug mode.
* `BaseCRM::SyncService#fetch` method return `nil` value if there is nothing more to synchronize. Previously it returned an empty array. This change fixes an issue where the sync service can return an empty array as a valid response.
### v1.1.1 (2015-06-10)
**Features and Improvements**
* Sync API support
* better handling of unexpected entity types
* `BaseCRM::SyncService#fetch` method returns `BaseCRM::Meta`instead of `BaseCRM::SyncMeta`.
This gives you additional information such as type.
* High-level `BaseCRM::Sync` wrapper expects either `meta.sync.ack` or `meta.sync.nack` to be called.
### v1.1.0 (2015-05-29)
**Features and Improvements**
* Sync API support
* New `BaseCRM::SyncService`
* High-level `BaseCRM::Sync` wrapper
### v1.0.0 (2015-04-17)
* Birth!
| 27.616162 | 233 | 0.735187 | eng_Latn | 0.838937 |
48b77d6e46144fa90ca303a6cb131e807ed3e0a6 | 1,233 | md | Markdown | docs/ref/rand.md | dcrossey/docs | 737486f8fdaf9f734bfb1a0d9ccf5f9c493a2aa2 | [
"CC-BY-4.0"
] | null | null | null | docs/ref/rand.md | dcrossey/docs | 737486f8fdaf9f734bfb1a0d9ccf5f9c493a2aa2 | [
"CC-BY-4.0"
] | 1 | 2020-09-14T16:04:31.000Z | 2020-09-14T16:04:31.000Z | docs/ref/rand.md | dcrossey/docs | 737486f8fdaf9f734bfb1a0d9ccf5f9c493a2aa2 | [
"CC-BY-4.0"
] | 1 | 2020-09-10T15:35:06.000Z | 2020-09-10T15:35:06.000Z | ---
title: rand | Reference | kdb+ and q documentation
description: rand is a q keyword that randomly picks a number, or an item from a list.
author: Stephen Taylor
keywords: deal, kdb+, q, rand, random, roll
---
# `rand`
_Pick randomly_
```syntax
rand x rand[x]
```
## Pick an item from a list
Where `x` is a **list** returns one item chosen randomly from `x`
```q
q)rand 1 30 45 32
32
q)rand("abc";"def";"ghi") / list of lists
"ghi"
```
## Pick a value at random
Where `x` is an **atom** returns an atom of the same type.
```q
q)rand 100
10
q)rand each 20#6 /roll twenty 6-sided dice
2 5 4 5 1 0 5 2 4 5 1 2 0 1 1 2 1 0 0 5
q)rand 3.14159
1.277572
q)rand 2012.09.12
2008.02.04
q)rand `3
`afe
```
Right domain and range are as for [Roll and Deal](deal.md#generate).
!!! tip "Returns a single item"
`rand` is exactly equivalent to `{first 1?x}`.
If you need a list result, use [Roll](deal.md).
The following expressions all roll a million six-sided dice.
q)\ts rand each 1000000#6
264 41166192
q)\ts {first 1?x}each 1000000#6
210 41166496
q)\ts 1000000?6 / Roll
6 8388800
---
:fontawesome-solid-book:
[Random seed](deal.md#seed) | 18.969231 | 86 | 0.631792 | eng_Latn | 0.929551 |
48b8d2a0bd29c84221b1211e626f9ae6eb3e31d9 | 1,200 | md | Markdown | aspnet/web-forms/overview/data-access/paging-and-sorting-with-the-datalist-and-repeater/index.md | Yukaii/Docs.zh-tw | e5adb8cfafb5e3b26d0578bf2aa7f44767ac5ad5 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | aspnet/web-forms/overview/data-access/paging-and-sorting-with-the-datalist-and-repeater/index.md | Yukaii/Docs.zh-tw | e5adb8cfafb5e3b26d0578bf2aa7f44767ac5ad5 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | aspnet/web-forms/overview/data-access/paging-and-sorting-with-the-datalist-and-repeater/index.md | Yukaii/Docs.zh-tw | e5adb8cfafb5e3b26d0578bf2aa7f44767ac5ad5 | [
"CC-BY-4.0",
"MIT"
] | 1 | 2021-07-13T15:20:45.000Z | 2021-07-13T15:20:45.000Z | ---
uid: web-forms/overview/data-access/paging-and-sorting-with-the-datalist-and-repeater/index
title: 分頁和排序使用 DataList 與重複項 |Microsoft Docs
author: rick-anderson
description: 這些教學課程會示範如何將分頁支援新增至 DataList 或 Repeater 控制項，以建立分頁和排序的極具彈性的 UI。
ms.author: riande
ms.date: 10/05/2011
ms.assetid: 8996b59e-042c-4395-b28a-f1ab95ac16af
msc.legacyurl: /web-forms/overview/data-access/paging-and-sorting-with-the-datalist-and-repeater
msc.type: chapter
ms.openlocfilehash: d92c21dc854f849cea22ae3e4feb5559cb50270e
ms.sourcegitcommit: 45ac74e400f9f2b7dbded66297730f6f14a4eb25
ms.translationtype: MT
ms.contentlocale: zh-TW
ms.lasthandoff: 08/16/2018
ms.locfileid: "48254264"
---
<a name="paging-and-sorting-with-the-datalist-and-repeater"></a>分頁和排序使用 DataList 與重複項
====================
> 這些教學課程會示範如何將分頁支援新增至 DataList 或 Repeater 控制項，以建立分頁和排序的極具彈性的 UI。
- [DataList 或重複項控制項中的分頁報表資料 (C#)](paging-report-data-in-a-datalist-or-repeater-control-cs.md)
- [DataList 或重複項控制項中的排序資料 (C#)](sorting-data-in-a-datalist-or-repeater-control-cs.md)
- [DataList 或重複項控制項中的分頁報表資料 (VB)](paging-report-data-in-a-datalist-or-repeater-control-vb.md)
- [DataList 或重複項控制項中的排序資料 (VB)](sorting-data-in-a-datalist-or-repeater-control-vb.md)
| 44.444444 | 96 | 0.791667 | yue_Hant | 0.425945 |
48b8eaaf792016f9f3c332cde57abb962adb560b | 11,038 | md | Markdown | specs/Device/Device/doc/spec.md | neeeel/dataModels | feb9af60476eaa62db7ed49a87cdc5ca1f4480a8 | [
"MIT"
] | null | null | null | specs/Device/Device/doc/spec.md | neeeel/dataModels | feb9af60476eaa62db7ed49a87cdc5ca1f4480a8 | [
"MIT"
] | null | null | null | specs/Device/Device/doc/spec.md | neeeel/dataModels | feb9af60476eaa62db7ed49a87cdc5ca1f4480a8 | [
"MIT"
] | null | null | null | # Device
## Description
An apparatus (hardware + software + firmware) intended to accomplish a
particular task (sensing the environment, actuating, etc.). A Device is a
tangible object which contains some logic and is producer and/or consumer of
data. A Device is always assumed to be capable of communicating electronically
via a network.
This data model has been partially developed in cooperation with mobile
operators and the [GSMA](http://www.gsma.com/connectedliving/iot-big-data/).
This data model reuses concepts coming from the
[SAREF Ontology](http://www.etsi.org/deliver/etsi_ts/103200_103299/103264/01.01.01_60/ts_103264v010101p.pdf)
part of [ETSI](http://www.etsi.org) standards.
## Data Model
The data model is defined as shown below:
- `id` : Unique identifier.
- `type` : Entity type. It must be equal to `Device`.
- `source` : A sequence of characters giving the source of the entity data.
- Attribute type: Text or URL
- Optional
- `dataProvider` : Specifies the URL to information about the provider of this
information
- Attribute type: URL
- Optional
- `category` : See attribute `category` from
[DeviceModel](../../DeviceModel/doc/spec.md). Optional but recommended to
optimize queries.
- `controlledProperty` : See attribute `controlledProperty` from
[DeviceModel](../../DeviceModel/doc/spec.md). Optional but recommended to
optimize queries.
- `controlledAsset` : The asset(s) (building, object, etc.) controlled by the
device.
- Attribute type: List of [Text](https://schema.org) or Reference(s) to
another entity.
- Optional
- `mnc` : This property identifies the Mobile Network Code (MNC) of the
network the device is attached to. The MNC is used in combination with a
Mobile Country Code (MCC) (also known as a "MCC / MNC tuple") to uniquely
identify a mobile phone operator/carrier using the GSM, CDMA, iDEN, TETRA
and 3G / 4G public land mobile networks and some satellite mobile networks.
- Attribute type: [Text](https://schema.org/Text)
- Optional
- `mcc` : Mobile Country Code - This property identifies univoquely the
country of the mobile network the device is attached to.
- Attribute type: [Text](https://schema.org/Text)
- Optional
- `macAddress` : The MAC address of the device.
- Attribute type: List of [Text](https://schema.org/Text)
- Optional
- `ipAddress` : The IP address of the device. It can be a comma separated list
of values if the device has more than one IP address.
- Attribute type: List of [Text](https://schema.org/Text)
- Optional
- `supportedProtocol` : See attribute `supportedProtocol` from
[DeviceModel](../../DeviceModel/doc/spec.md). Needed if due to a software
update new protocols are supported. Otherwise it is better to convey it at
`DeviceModel` level.
- `configuration` : Device's technical configuration. This attribute is
intended to be a dictionary of properties which capture parameters which
have to do with the configuration of a device (timeouts, reporting periods,
etc.) and which are not currently covered by the standard attributes defined
by this model.
- Attribute type: [StructuredValue](https://schema.org/StructuredValue)
- Attribute metadata:
- `dateModified` : Last update timestamp of this attribute.
- Metadata type: [DateTime](https://schema.org/DateTime)
- Read-Only. Automatically generated.
- Optional
- `location` : Location of this device represented by a GeoJSON geometry of
type point.
- Attribute type: `geo:json`.
- Normative References:
[https://tools.ietf.org/html/rfc7946](https://tools.ietf.org/html/rfc7946)
- Optional.
- `name` : A mnemonic name given to the device.
- Normative References: [name](https://schema.org/name)
- Optional
- `description` : Device's description.
- Normative References: [description](https://schema.org/description)
- Optional
- `dateInstalled` : A timestamp which denotes when the device was installed
(if it requires installation).
- Attribute type: [DateTime](https://schema.org/DateTime)
- Optional
- `dateFirstUsed` : A timestamp which denotes when the device was first used.
- Attribute type: [DateTime](https://schema.org/DateTime)
- Optional
- `dateManufactured` : A timestamp which denotes when the device was
manufactured.
- Attribute type: [DateTime](https://schema.org/DateTime)
- Optional
- `hardwareVersion` : The hardware version of this device.
- Attribute type: [Text](https://schema.org/Text)
- Optional
- `softwareVersion` : The software version of this device.
- Attribute type: [Text](https://schema.org/Text)
- Optional
- `firmwareVersion` : The firmware version of this device.
- Attribute type: [Text](https://schema.org/Text)
- Optional
- `osVersion` : The version of the host operating system device.
- Attribute type: [Text](https://schema.org/Text)
- Optional
- `dateLastCalibration` : A timestamp which denotes when the last calibration
of the device happened.
- Attribute type: [DateTime](https://schema.org/DateTime)
- Optional
- `serialNumber` : The serial number assigned by the manufacturer.
- Normative References:
[https://schema.org/serialNumber](https://schema.org/serialNumber)
- Optional
- `provider` : The provider of the device.
- Normative References:
[https://schema.org/provider](https://schema.org/provider)
- Optional
- `refDeviceModel` : The device's model.
- Attribute type: Reference to an entity of type
[DeviceModel](../../DeviceModel/doc/spec.md).
- Optional
- `batteryLevel` : Device's battery level. It must be equal to `1.0` when
battery is full. `0.0` when battery ìs empty. `null` when cannot be
determined.
- Type: [Number](https://schema.org/Number)
- Allowed values: Interval \[0,1\]
- Attribute metadata:
- `timestamp`: Timestamp when the last update of the attribute
happened. This value can also appear as a FIWARE
[TimeInstant](https://github.com/telefonicaid/iotagent-node-lib#TimeInstant)
- Type: [DateTime](http://schema.org/DateTime)
- Optional
- `deviceState` : State of this device from an operational point of view. Its
value can be vendor dependent.
- Type: [Text](https://schema.org/Text)
- Attribute metadata:
- `timestamp`: Timestamp when the last update of the attribute
happened. This value can also appear as a FIWARE
[TimeInstant](https://github.com/telefonicaid/iotagent-node-lib#TimeInstant)
- Type: [DateTime](http://schema.org/DateTime)
- Optional
- `dateLastValueReported` : A timestamp which denotes the last time when the
device successfully reported data to the cloud.
- Attribute type: [DateTime](https://schema.org/DateTime)
- Optional
- `value` : A observed or reported value. For actuator devices, it is an
attribute that allows a controlling application to change the actuation
setting. For instance, a switch device which is currently _on_ can report a
value `"on"`of type `Text`. Obviously, in order to toggle the referred
switch, this attribute value will have to be changed to `"off"`.
- Attribute type: Any type, depending on the device. Usually
[Text](https://schema.org/Text) or
[QuantitativeValue](https://schema.org/QuantitativeValue).
- Attribute metadata:
- `timestamp`: Timestamp when the last update of the attribute
happened. This value can also appear as a FIWARE
[TimeInstant](https://github.com/telefonicaid/iotagent-node-lib#TimeInstant)
- Type: [DateTime](http://schema.org/DateTime)
- Optional
- `dateModified` : Last update timestamp of this entity.
- Attribute type: [DateTime](https://schema.org/DateTime)
- Read-Only. Automatically generated.
- `dateCreated` : Entity's creation timestamp.
- Attribute type: [DateTime](https://schema.org/DateTime)
- Read-Only. Automatically generated.
- `owner` : The owners of a Device.
- Attribute type: List of references to [Person](http://schema.org/Person)
or [Organization](https://schema.org/Organization).
- Optional
**Note**: JSON Schemas only capture the NGSI simplified representation, this
means that to test the JSON schema examples with a
[FIWARE NGSI version 2](http://fiware.github.io/specifications/ngsiv2/stable)
API implementation, you need to use the `keyValues` mode (`options=keyValues`).
## Examples
### Normalized Example
Normalized NGSI response
```json
{
"id": "device-9845A",
"type": "Device",
"category": {
"value": ["sensor"]
},
"batteryLevel": {
"value": 0.75
},
"dateFirstUsed": {
"type": "DateTime",
"value": "2014-09-11T11:00:00Z"
},
"controlledAsset": {
"value": ["wastecontainer-Osuna-100"]
},
"serialNumber": {
"value": "9845A"
},
"mcc": {
"value": "214"
},
"value": {
"value": "l%3D0.22%3Bt%3D21.2"
},
"refDeviceModel": {
"type": "Relationship",
"value": "myDevice-wastecontainer-sensor-345"
},
"controlledProperty": {
"value": ["fillingLevel", "temperature"]
},
"owner": {
"value": ["http://person.org/leon"]
},
"mnc": {
"value": "07"
},
"ipAddress": {
"value": ["192.14.56.78"]
},
"deviceState": {
"value": "ok"
}
}
```
### key-value pairs Example
Sample uses simplified representation for data consumers `?options=keyValues`
```json
{
"id": "device-9845A",
"type": "Device",
"category": ["sensor"],
"controlledProperty": ["fillingLevel""temperature"],
"controlledAsset":["wastecontainer-Osuna-100"],
"ipAddress": ["192.14.56.78"],
"mcc": "214",
"mnc": "07",
"batteryLevel": 0.75,
"serialNumber": "9845A",
"refDeviceModel":"myDevice-wastecontainer-sensor-345",
"value": "l=0.22;t=21.2",
"deviceState": "ok",
"dateFirstUsed": "2014-09-11T11:00:00Z",
"owner": ["http://person.org/leon"]
}
```
**N.B.:** This example to work in Orion Context Broker implementation of NGSI
v2, requires that value attribute is URL Encoded. As documented
[here](https://fiware-orion.readthedocs.io/en/master/user/forbidden_characters/index.html)
`=` is a forbidden character.
## Test it with a real service
T.B.D.
## Issues
- Is `function` really needed?
- Do we need a `state` attribute as it happens in SAREF?
- Check consistency with oneM2M and SAREF ontologies.
| 33.147147 | 108 | 0.658181 | eng_Latn | 0.860426 |
48b9971b40544d66605b38164c41338c8cdad57f | 2,394 | md | Markdown | _pages/Brief Life Trajectory.md | nwrim/nwrim.github.io | ae3f1cdfb24ec5e3362fd0de9ec694d5848acc7e | [
"MIT"
] | null | null | null | _pages/Brief Life Trajectory.md | nwrim/nwrim.github.io | ae3f1cdfb24ec5e3362fd0de9ec694d5848acc7e | [
"MIT"
] | null | null | null | _pages/Brief Life Trajectory.md | nwrim/nwrim.github.io | ae3f1cdfb24ec5e3362fd0de9ec694d5848acc7e | [
"MIT"
] | null | null | null | ---
layout: archive
title: "Brief Life Trajectory"
permalink: /brief-life-trajectory/
author_profile: true
---
I was very interested in biology during elementary school and middle school. I was a member of the science education academy for the gifted at a national university and won a prize in the Korean Biology Olympiad Middle School Division.
This interest in biology led me to a high school for the gifted named [Korean Minjok Leadership Academy](http://english.minjok.hs.kr/). I took the entrance exam as a Biology major and kept on taking Biology courses throughout my time at the school, eventually getting a full mark at the AP exam in Biology. However, the school offered a variety of courses in diverse disciplines ranging from ancient Chinese text reading to JAVA programming. I took a course in AP Psychology during my sophomore year. The course was centered around a lot of classical results in Psychology, and one of the experiments it talked about was the iconic memory and the Sperling partial report paradigm. Upon hearing about the experiment, I was awestruck by the fact that the experiment was so succinct but informative at the same time. I thought it was almost beautiful. One thing led to others after that, and I ended up in as a Psychology major at Korea University.
Of the vast subfields of Psychology, I gradually realized that I was interested in the more cognitive and biological division of Psychology. I started studying statistics on my own during my mandatory military service. (I was stationed in an office because I was an interpreter, which let me have more regular working hours) After being discharged from the military, I chose Brain Cognitive Science as my second major to take courses from the Department of Computer Science & Engineering and the Department of Biological Science. I also worked as an undergraduate RA in Professor Cho’s lab.
Upon graduation, I realized that my interests were closely related to computational modeling of human cognition, and I also wanted to learn how we can incorporate "Big data" (which I learned that this topic is increasingly attracted a lot of interests from various discipline) into psychological researches. This led me to join the Masters in Computational Social Science program at the University of Chicago, where I thought I could get deeper training in computational techniques and statistical modeling. | 184.153846 | 945 | 0.812448 | eng_Latn | 0.999837 |
48ba6b0917252554cdcd55864b19cc087181f858 | 3,363 | md | Markdown | README.md | blacktm/r2d | 3ebaea5a0adbe47cd139b997cd4a6b16a731ec13 | [
"MIT"
] | 4 | 2015-08-20T16:32:26.000Z | 2018-12-05T17:49:18.000Z | README.md | blacktm/r2d | 3ebaea5a0adbe47cd139b997cd4a6b16a731ec13 | [
"MIT"
] | null | null | null | README.md | blacktm/r2d | 3ebaea5a0adbe47cd139b997cd4a6b16a731ec13 | [
"MIT"
] | null | null | null | # R2D: 2D Graphics for Ruby
**This project has been deprecated!** Check out its successor, [Ruby 2D](https://github.com/ruby2d/ruby2d).
R2D is a gem for drawing 2D graphics, animations, playing audio, capturing input, and more. It aims to be a simple and lightweight programmable graphics engine suitable for casual 2D games, visualizations, education, and more.
**WARNING: This gem is still in development!** This means the API and implementation are very much in flux. Review the latest API [documentation](http://www.ruby2d.com/docs) and the [change log](http://www.ruby2d.com/docs/history.html) for more info.
[View the R2D website](http://www.ruby2d.com) for news and updates (*this site is also still in development*). To share ideas, ask questions, or discuss anything in general, check out the [Google group](https://groups.google.com/d/forum/r2d-gem). Tweet me (the author) at [@blacktm](https://twitter.com/blacktm).
## Installing
Until a v0.1.0 public release, this gem will only be available locally. To build and install, use:
```
$ rake build
```
This Rake task will build and install the gem locally and verbosely.
### Installing on OS X
This gem requires [Homebrew](http://brew.sh) on OS X to install [SDL2](http://www.libsdl.org). If you prefer not to install Homebrew and already have SDL2 available on your `$PATH`, use the `--use-system-libs` option:
```
$ gem install r2d -- --use-system-libs
```
This option will search for SDL2 libs using `-lSDL2` style arguments. The [`extconf.rb`](/ext/r2d/extconf.rb) will check to make sure libs are available during the `gem install` process.
### Installing on Windows and Linux
This gem doesn't currently support Windows or Linux, but we're working on it (including the [Raspberry Pi](http://www.raspberrypi.org)).
If you know of a way to conveniently install SDL2 on Windows, [let me know](https://twitter.com/blacktm)!
## Running the Examples
The [`examples/`](/examples) directory contains a variety of R2D sample applications. These examples are being used to test the gem while implementing the API and underlying engine.
## Running the Tests
Run tests using:
```
$ rake test
```
This gem uses `minitest`, but we have no tests at the moment. A big challenge in testing a gem for graphics and audio is some tests can't be fully automated, e.g. did that square draw correctly, or did that sound play correctly? For this reason, we're still working on a comprehensive testing strategy.
## Requirements and OS Support
R2D requires Ruby 2.0 or greater. Native extensions are used in this gem, so a compiler is needed. The intent is for R2D to be a fully cross-platform graphics environment and should run on OS X, Windows, and Linux.
So far, the gem has been tested on:
| OS | Ruby | Env | SDL2 |
| ----------- | ---------- | ----------- | ---------------- |
| OS X 10.9 | 2.0.0-p353 | rbenv 0.4.0 | 2.0.1 / Homebrew |
| OS X 10.9.1 | 2.1.0 | rbenv 0.4.0 | 2.0.1 / Homebrew |
<!-- - Windows 7 32-bit using the [RubyInstaller](http://rubyinstaller.org/) for Windows and the [MinGW DevKit](http://rubyinstaller.org/add-ons/devkit/) (required for building native extensions). -->
<!-- If you've tested R2D on other platforms or configurations, please [let me know](https://twitter.com/blacktm)! This thing should work everywhere. -->
| 51.738462 | 312 | 0.715135 | eng_Latn | 0.98107 |
48bac8277d00e91b011f70abb9d21132849062ee | 1,487 | md | Markdown | company-profiles/udacity.md | rajatvijay/remote-jobs | 47759adaf088e35104f21494a2a92fb7f549365a | [
"CC0-1.0"
] | null | null | null | company-profiles/udacity.md | rajatvijay/remote-jobs | 47759adaf088e35104f21494a2a92fb7f549365a | [
"CC0-1.0"
] | null | null | null | company-profiles/udacity.md | rajatvijay/remote-jobs | 47759adaf088e35104f21494a2a92fb7f549365a | [
"CC0-1.0"
] | null | null | null | # Udacity
## Company blurb
Udacity is an online education platform that leads to meaningful skills and gainful employment.
At Udacity, our mission is to empower our students to not just advance their education, but to land their dream job in technology through a relevant 21st century education.
## Company size
200+ (50+ on Engineering/Product/Design)
## Remote status
We believe in working however suits you best; not in measuring productivity by how often you come into the office. Whether you prefer our main office in Mountain View, our co-working space in San Francisco, a home office on the East Coast or a beach cafe in some tropical paradise, we'll make sure you're able to productively collaborate and communicate with the rest of your team via Slack, Hangouts and GitHub.
## Region
Worldwide
## Company technologies
Much like *where* we work, we believe *how* we work should be dictated by productivity and fit for the task at hand. Our team uses a number of technologies (React/GraphQL, Ruby on Rails, Go, Scala, Python, Angular, Java and Objective-C to name a few), but you're welcome to use whatever language/framework/dev environment will let you do your best work.
## Office locations
Our Main Office is in Mountain View, CA. We have additional offices in San Francisco and Shanghai, with more on the way.
## How to apply
[Open positions](https://jobs.lever.co/udacity?lever-via=XleBPrSxxN)
[Video about Udacity Engineering](https://vimeo.com/135723573)
| 42.485714 | 412 | 0.779422 | eng_Latn | 0.998909 |
48baea8be0e3fcb30947863e99f6208e146a44fa | 750 | md | Markdown | _posts/2011-06-08-trendy-replica-sunglasses.md | BlogToolshed50/velikazvjerka.com | 6c7d6805a776d3bac8c154c619e76975ff3dbdb2 | [
"CC-BY-4.0"
] | null | null | null | _posts/2011-06-08-trendy-replica-sunglasses.md | BlogToolshed50/velikazvjerka.com | 6c7d6805a776d3bac8c154c619e76975ff3dbdb2 | [
"CC-BY-4.0"
] | null | null | null | _posts/2011-06-08-trendy-replica-sunglasses.md | BlogToolshed50/velikazvjerka.com | 6c7d6805a776d3bac8c154c619e76975ff3dbdb2 | [
"CC-BY-4.0"
] | null | null | null | ---
id: 720
title: Trendy Replica Sunglasses
date: 2011-06-08T07:53:18+00:00
author: admin
layout: post
guid: http://www.velikazvjerka.com/2011/06/08/trendy-replica-sunglasses/
permalink: /2011/06/08/trendy-replica-sunglasses/
categories:
- General
---
Anyone is looking for the latest style of sunglasses at a very reasonable price, then Nine A Pair is the perfect spot for you. They offer a wide selection of most popular [replica sunglasses](http://www.nineapair.com/) at a very competitive price, people can view the styles to select the right one that meets all your expectations and budget. They are listed the trendy replica sunglasses in their website, people can select their choice of one for their needs and buy them safe and secure way. | 62.5 | 495 | 0.785333 | eng_Latn | 0.99548 |
48bb22df5a0e9f744042c6102aabd119d23a4f63 | 1,313 | md | Markdown | 2020/09/07/2020-09-07 05:00.md | zhzhzhy/WeiBoHot_history | 32ce4800e63f26384abb17d43e308452c537c902 | [
"MIT"
] | 3 | 2020-07-14T14:54:15.000Z | 2020-08-21T06:48:24.000Z | 2020/09/07/2020-09-07 05:00.md | zhzhzhy/WeiBoHot_history | 32ce4800e63f26384abb17d43e308452c537c902 | [
"MIT"
] | null | null | null | 2020/09/07/2020-09-07 05:00.md | zhzhzhy/WeiBoHot_history | 32ce4800e63f26384abb17d43e308452c537c902 | [
"MIT"
] | null | null | null | 2020年09月07日05时数据
Status: 200
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| 6.436275 | 21 | 0.767708 | yue_Hant | 0.442708 |
48bbe336f9ac5094002951e151b83f0c0d29e2bf | 4,643 | md | Markdown | articles/service-fabric-mesh/service-fabric-mesh-howto-auto-scale-services.md | hcyang1012/azure-docs.ko-kr | e0844b72effe5055ad69dc006a9eb3c4656efc80 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | articles/service-fabric-mesh/service-fabric-mesh-howto-auto-scale-services.md | hcyang1012/azure-docs.ko-kr | e0844b72effe5055ad69dc006a9eb3c4656efc80 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | articles/service-fabric-mesh/service-fabric-mesh-howto-auto-scale-services.md | hcyang1012/azure-docs.ko-kr | e0844b72effe5055ad69dc006a9eb3c4656efc80 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | ---
title: Azure 서비스 패브릭 메시에서 실행 중인 앱 자동 크기 조정
description: Service Fabric Mesh 애플리케이션의 서비스에 대 한 자동 크기 조정 정책을 구성하는 방법에 알아봅니다.
author: dkkapur
ms.topic: conceptual
ms.date: 12/07/2018
ms.author: dekapur
ms.custom: mvc, devcenter
ms.openlocfilehash: fb72806dd7ba838ba7170bda409715bc074e1d99
ms.sourcegitcommit: 2ec4b3d0bad7dc0071400c2a2264399e4fe34897
ms.translationtype: MT
ms.contentlocale: ko-KR
ms.lasthandoff: 03/27/2020
ms.locfileid: "75461981"
---
# <a name="create-autoscale-policies-for-a-service-fabric-mesh-application"></a>Service Fabric Mesh 애플리케이션에 대한 자동 크기 조정 정책 만들기
서비스 패브릭 메시에 응용 프로그램을 배포할 때의 주요 장점 중 하나는 서비스를 쉽게 확장하거나 확장할 수 있다는 것입니다. 이는 서비스에 대한 다양한 양의 부하를 처리하거나 가용성을 개선하는 데 사용해야 합니다. 수동으로 서비스를 확대 또는 축소하거나 자동 크기 조정 정책을 설정할 수 있습니다.
[자동 크기 조정](service-fabric-mesh-scalability.md#autoscaling-service-instances)를 사용하여 서비스 인스턴스의 수를 동적으로 조정할 수 있습니다(수평 크기 조정). 자동 크기 조정은 탄력성이 뛰어나 CPU 또는 메모리 사용률에 따라 서비스 인스턴스를 프로비전하거나 제거할 수 있습니다.
## <a name="options-for-creating-an-auto-scaling-policy-trigger-and-mechanism"></a>자동 크기 조정 정책, 트리거 및 메커니즘을 만들기 위한 옵션
자동 크기 조정 정책은 크기를 조정하려는 각 서비스에 대해 정의됩니다. 정책은 YAML 서비스 리소스 파일 또는 JSON 배포 템플릿으로 정의됩니다. 각 크기 조정 정책은 트리거 및 크기 조정 메커니즘 두 부분으로 구성됩니다.
트리거는 자동 크기 조정 정책이 호출될 시간을 정의합니다. 트리거(평균 부하) 및 메트릭의 종류를 모니터(CPU 또는 메모리)에 지정합니다. 상한 및 하한 임계값을 백분율로 지정합니다. 눈금 간격은 현재 배포된 모든 서비스 인스턴스에서 지정된 사용률(예: 평균 CPU 로드)을 얼마나 자주 확인하는지(초 단위)를 정의합니다. 모니터링된 메트릭이 하한 임계값 아래로 떨어지거나 상한 임계값 위로 증가할 때 메커니즘이 트리거됩니다.
크기 조정 메커니즘은 정책이 트리거될 때 크기 조정 작업을 수행하는 방법을 정의합니다. 메커니즘의 종류(복제본 추가/제거)를 지정하면 최소 및 최대 복제본을 계산합니다(정수). 서비스 복제본의 수는 최소 수 이하 또는 최대 수 이상으로 크기 조정되지 않습니다. 또한 조정 작업에서 추가 또는 제거할 수 있는 복제본의 수인 크기 조정 증분을 정수로 지정합니다.
## <a name="define-an-auto-scaling-policy-in-a-json-template"></a>JSON 템플릿에서 자동 크기 조정 정책 정의
다음 예제는 JSON 배포 템플릿에서 자동 크기 조정 정책을 보여 줍니다. 자동 크기 조정 정책은 크기를 조정할 서비스의 속성에서 선언됩니다. 이 예제에서는 CPU 평균 로드 트리거가 정의됩니다. 모든 배포 인스턴스의 평균 CPU 로드가 0.2(20%) 미만으로 떨어지거나 (80%)0.8 이상으로 올라가는 경우 메커니즘은 트리거됩니다. CPU 로드는 60초마다 확인됩니다. 정책이 트리거될 경우 크기 조정 메커니즘은 인스턴스를 추가 또는 제거하도록 정의됩니다. 서비스 인스턴스는 1 단위로 추가되거나 제거됩니다. 또한 최소 인스턴스 수는 1로 최대 인스턴스 수는 40으로 정의됩니다.
```json
{
"apiVersion": "2018-09-01-preview",
"name": "WorkerApp",
"type": "Microsoft.ServiceFabricMesh/applications",
"location": "[parameters('location')]",
"dependsOn": [
"Microsoft.ServiceFabricMesh/networks/worker-app-network"
],
"properties": {
"services": [
{ ... },
{
"name": "WorkerService",
"properties": {
"description": "Worker Service",
"osType": "linux",
"codePackages": [
{ ... }
],
"replicaCount": 1,
"autoScalingPolicies": [
{
"name": "AutoScaleWorkerRule",
"trigger": {
"kind": "AverageLoad",
"metric": {
"kind": "Resource",
"name": "cpu"
},
"lowerLoadThreshold": "0.2",
"upperLoadThreshold": "0.8",
"scaleIntervalInSeconds": "60"
},
"mechanism": {
"kind": "AddRemoveReplica",
"minCount": "1",
"maxCount": "40",
"scaleIncrement": "1"
}
}
],
...
}
}
]
}
}
```
## <a name="define-an-autoscale-policy-in-a-serviceyaml-resource-file"></a>Service.yaml 리소스 파일에서 자동 크기 조정 정책 정의
다음 예제는 서비스 리소스(YAML) 파일에서 자동 크기 조정 정책을 보여줍니다. 자동 크기 조정 정책은 크기를 조정할 서비스의 속성에서 선언됩니다. 이 예제에서는 CPU 평균 로드 트리거가 정의됩니다. 모든 배포 인스턴스의 평균 CPU 로드가 0.2(20%) 미만으로 떨어지거나 (80%)0.8 이상으로 올라가는 경우 메커니즘은 트리거됩니다. CPU 로드는 60초마다 확인됩니다. 정책이 트리거될 경우 크기 조정 메커니즘은 인스턴스를 추가 또는 제거하도록 정의됩니다. 서비스 인스턴스는 1 단위로 추가되거나 제거됩니다. 또한 최소 인스턴스 수는 1로 최대 인스턴스 수는 40으로 정의됩니다.
```yaml
## Service definition ##
application:
schemaVersion: 1.0.0-preview2
name: WorkerApp
properties:
services:
- name: WorkerService
properties:
description: WorkerService description.
osType: Linux
codePackages:
...
replicaCount: 1
autoScalingPolicies:
- name: AutoScaleWorkerRule
trigger:
kind: AverageLoad
metric:
kind: Resource
name: cpu
lowerLoadThreshold: 0.2
upperLoadThreshold: 0.8
scaleIntervalInSeconds: 60
mechanism:
kind: AddRemoveReplica
minCount: 1
maxCount: 40
scaleIncrement: 1
...
```
## <a name="next-steps"></a>다음 단계
[수동으로 서비스를 크기 조정](service-fabric-mesh-tutorial-template-scale-services.md)하는 방법 알아보기
| 39.016807 | 338 | 0.60995 | kor_Hang | 1.00001 |
48bc2ebd13c66e9d1f09d631195c9f3133860220 | 1,165 | md | Markdown | DeployOffice/privacy/toc.md | MicrosoftDocs/OfficeDocs-DeployOffice-pr.vi-vn | 3503f91b72b1909d221bfde434d08c81b6a12604 | [
"CC-BY-4.0",
"MIT"
] | 3 | 2020-05-19T19:11:40.000Z | 2021-04-21T00:13:50.000Z | DeployOffice/privacy/toc.md | MicrosoftDocs/OfficeDocs-DeployOffice-pr.vi-vn | 3503f91b72b1909d221bfde434d08c81b6a12604 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | DeployOffice/privacy/toc.md | MicrosoftDocs/OfficeDocs-DeployOffice-pr.vi-vn | 3503f91b72b1909d221bfde434d08c81b6a12604 | [
"CC-BY-4.0",
"MIT"
] | 1 | 2019-10-11T19:53:16.000Z | 2019-10-11T19:53:16.000Z | # Quyền riêng tư cho ứng dụng Microsoft 365 dành cho doanh nghiệp lớn
## [Tổng quan về kiểm soát quyền riêng tư](overview-privacy-controls.md)
## [Kiểm soát quyền riêng tư có sẵn cho các sản phẩm Office](products-versions-privacy-controls.md)
## Quản lý điều khiển quyền riêng tư
### [Cài đặt chính sách Windows](manage-privacy-controls.md)
### [Tùy chọn Mac](mac-privacy-preferences.md)
### [Tùy chọn iOS](ios-privacy-preferences.md)
### [Cài đặt chính sách Android](android-privacy-controls.md)
### [Cài đặt chính sách Office cho web](office-web-privacy-controls.md)
## Dữ liệu chẩn đoán
### [Dữ liệu chẩn đoán bắt buộc](required-diagnostic-data.md)
### [Dữ liệu chẩn đoán tùy chọn](optional-diagnostic-data.md)
### [Sử dụng Trình xem chẩn đoán dữ liệu](https://support.microsoft.com/office/cf761ce9-d805-4c60-a339-4e07f3182855)
## Trải nghiệm được kết nối
### [Trải nghiệm được kết nối](connected-experiences.md)
### [Trải nghiệm được kết nối tuỳ chọn](optional-connected-experiences.md)
### [Dữ liệu dịch vụ bắt buộc](required-service-data.md)
## [Các dịch vụ cần thiết](essential-services.md)
## [Các đề xuất trong sản phẩm](in-product-recommendations.md) | 48.541667 | 116 | 0.738197 | vie_Latn | 0.999755 |
48bccc967297c65574e6aefbd72cf005c35bbfd4 | 5,270 | md | Markdown | tutorials/concepts/azimuth.md | pimato/docs | 55da472cb9042d6a8f38c3767f8c31a5acdfb8e9 | [
"MIT"
] | null | null | null | tutorials/concepts/azimuth.md | pimato/docs | 55da472cb9042d6a8f38c3767f8c31a5acdfb8e9 | [
"MIT"
] | null | null | null | tutorials/concepts/azimuth.md | pimato/docs | 55da472cb9042d6a8f38c3767f8c31a5acdfb8e9 | [
"MIT"
] | null | null | null | +++
title = "Azimuth"
weight = 4
template = "doc.html"
aliases = ["/docs/learn/azimuth"]
+++
Azimuth is a general-purpose public-key infrastructure (PKI) on the Ethereum blockchain, used as a platform for _Urbit identities_. You need such an identity to use the Arvo network.
The primary way to interact with Azimuth is through our [Bridge](https://github.com/urbit/bridge) application and the node libraries that it depends on, [azimuth-js](https://github.com/urbit/azimuth-js) and [urbit-key-generation](https://github.com/urbit/urbit-key-generation). Take a look at the source and play around, or see [Getting Started](/using/install).
## Arvo vs. Azimuth
Urbit is a project, not a single computer system. It has multiple components: Arvo, the operating system; and Azimuth, the identity system. Let's compare them.
**Arvo** is an operating system that provides the software for a personal server. These personal servers together constitute the peer-to-peer Arvo network. To make this network work on the social level, Arvo is built to work with a system of scarce and immutable identities.
**Azimuth** is the public-key infrastructure built to be such a system. A suite of smart-contracts on the Ethereum blockchain, Azimuth determines which Ethereum addresses own which Azimuth identities, called _Urbit identities_, or just _identities_. All identity-related operations, such as transfers, are governed at this layer. But Azimuth isn't built strictly for Arvo -- it could be used as a generalized identity system for other projects.
These otherwise-parallel systems meet when you want to connect to the Arvo network. Your Arvo personal server, called your _ship_, needs to be able to prove cryptographically that it is who it says it is. This proof comes in the form of a keyfile, derived from your identity, that you use to start your ship.
A metaphor might help illustrate the relationship between these two systems: the Arvo network is the neighborhood that you live in; Azimuth is the bank vault that stores the deed to your house.
## The Urbit HD Wallet
Owners of Urbit identities need safeguards that allow for the use of Urbit without jeopardizing cryptographic ownership of their assets. Toward this end, we created the **Urbit Hierarchical Deterministic (HD) Wallet** for the storage of identities. The Urbit HD Wallet is not one key-pair, but a system of related key-pairs that each have distinct powers, from setting networking keys for communicating in the Arvo network to transferring ownership of identities.
The Urbit HD Wallet's derivation paths have a hierarchical structure, so that keys with different powers can be physically separated. A \"master ticket" can re-derive the entire wallet in case of loss. The encryption and authentication keys that identities ships use to sign messages within the network are also derived from the wallet.
Urbit HD wallets are composed of the following items, which are each assigned to their own individual Ethereum key-pairs.
### Master Ticket
Think of your master ticket like a very high-value password. The master ticket is the secret code from which all of your other keys are derived. Technically, your master ticket is seed entropy. You should never share it with anyone, and store it very securely. This ticket can derive all of your other keys: your ownership key and all of the related proxies.
### Ownership Address
An ownership address has all rights over the assets deeded to it. These rights are on-chain actions described and implemented in the Ecliptic, Azimuth's suite of governing smart-contracts.
### Proxies
Proxy addresses allow you to execute non-ownership related actions like spawning child identities, voting, and setting networking keys without jeopardizing the keys you've designated with ownership rights. Setting proxy rights is optional, but it is recommended for on-chain actions you will execute more frequently.
- **Management Proxy**
Can configure or set Arvo networking keys and conduct sponsorship related
operations.
- **Voting Proxy**
Galaxies only. Galaxies are the part of the galactic senate, and this means
they can cast votes on new proposals including changes to the Ecliptic.
- **Spawn Proxy**
For stars and galaxies only. Can create new child identities.
Most Ethereum tokens use the ERC-20 standard for smart contracts. Urbit identities
are, however, essentially different from most Ethereum tokens, due to identities not
being fungible. Since any two stars will handle social-networking realities in a
different way, they will carry a different reputation. identities are to houses as
tokens are to gold.
The ERC-721 standard, having been made specifically to provide a smart-contract
interface for non-fungible assets, serves our needs well. This is the standard
that we use for deeding Urbit identities.
identities, and all of their blockchain operations, are governed by the Ecliptic.
The Ecliptic is an Ethereum smart-contract that governs identity state and the
ownership, spawn, management, and voting rights affiliated with your identities.
For the technical implementation details, take a look at Azimuth's
[Github repository](https://github.com/urbit/azimuth).
| 69.342105 | 463 | 0.795066 | eng_Latn | 0.999507 |
48bd02942cec23f24c873425a927d4ed9cec6ec3 | 8,563 | md | Markdown | src/1993/titulo-i/capitulo-i.md | jeqo/peru-constitucion | bb5498be350789b69740306c7b80f43a3bf78e85 | [
"CC0-1.0"
] | null | null | null | src/1993/titulo-i/capitulo-i.md | jeqo/peru-constitucion | bb5498be350789b69740306c7b80f43a3bf78e85 | [
"CC0-1.0"
] | null | null | null | src/1993/titulo-i/capitulo-i.md | jeqo/peru-constitucion | bb5498be350789b69740306c7b80f43a3bf78e85 | [
"CC0-1.0"
] | null | null | null | # CAPITULO I DERECHOS FUNDAMENTALES DE LA PERSONA
## ARTICULO 1
La defensa de la persona humana y el respeto de su dignidad son el fin supremo de la sociedad y del Estado.
## ARTICULO 2
Toda persona tiene derecho:
1. A la vida, a su identidad, a su integridad moral, psíquica y física y a su libre desarrollo y bienestar.
El concebido es sujeto de derecho en todo cuanto le favorece.
2. A la igualdad ante la ley.
Nadie debe ser discriminado por motivo de origen, raza, sexo, idioma, religión, opinión, condición económica o de cualquiera otra índole.
3. A la libertad de conciencia y de religión, en forma individual o asociada.
No hay persecución por razón de ideas o creencias.
No hay delito de opinión. El ejercicio público de todas las confesiones es libre, siempre que no ofenda la moral ni altere el orden público.
4. A las libertades de información, opinión, expresión y difusión del pensamiento mediante la palabra oral o escrita o la imagen, por cualquier medio de comunicación social, sin previa autorización ni censura ni impedimento algunos, bajo las responsabilidades de ley.
Los delitos cometidos por medio del libro, la prensa y demás medios de comunicación social se tipifican en el Código Penal y se juzgan en el fuero común.
Es delito toda acción que suspende o clausura algún órgano de expresión o le impide circular libremente.
Los derechos de informar y opinar comprenden los de fundar medios de comunicación.
5. A solicitar sin expresión de causa la información que requiera y a recibirla de cualquier entidad pública, en el plazo legal, con el costo que suponga el pedido.
Se exceptúan las informaciones que afectan la intimidad personal y las que expresamente se excluyan por ley o por razones de seguridad nacional.
El secreto bancario y la reserva tributaria pueden levantarse a pedido del Juez, del Fiscal de la Nación, o de una comisión investigadora del Congreso con arreglo a ley y siempre que se refieran al caso investigado.
6. A que los servicios informáticos, computarizados o no, públicos o privados, no suministren informaciones que afecten la intimidad personal y familiar.
7. Al honor y a la buena reputación, a la intimidad personal y familiar así como a la voz y a la imagen propias.
Toda persona afectada por afirmaciones inexactas o agraviada en cualquier medio de comunicación social tiene derecho a que éste se rectifique en forma gratuita, inmediata y proporcional, sin perjuicio de las responsabilidades de ley.
8. A la libertad de creación intelectual, artística, técnica y científica, así como a la propiedad sobre dichas creaciones y a su producto.
El Estado propicia el acceso a la cultura y fomenta su desarrollo y difusión.
9. A la inviolabilidad del domicilio.
Nadie puede ingresar en él ni efectuar investigaciones o registros sin autorización de la persona que lo habita o sin mandato judicial, salvo flagrante delito o muy grave peligro de su perpetración.
Las excepciones por motivos de sanidad o de grave riesgo son reguladas por la ley.
10. Al secreto y a la inviolabilidad de sus comunicaciones y documentos privados.
Las comunicaciones, telecomunicaciones o sus instrumentos sólo pueden ser abiertos, incautados, interceptados o intervenidos por mandamiento motivado del juez, con las garantías previstas en la ley.
Se guarda secreto de los asuntos ajenos al hecho que motiva su examen.
Los documentos privados obtenidos con violación de este precepto no tienen efecto legal.
Los libros, comprobantes y documentos contables y administrativos están sujetos a inspección o fiscalización de la autoridad competente, de conformidad con la ley.
Las acciones que al respecto se tomen no pueden incluir su sustracción o incautación, salvo por orden judicial.
11. A elegir su lugar de residencia, a transitar por el territorio nacional y a salir de él y entrar en él, salvo limitaciones por razones de sanidad o por mandato judicial o por aplicación de la ley de extranjería.
12. A reunirse pacíficamente sin armas. Las reuniones en locales privados o abiertos al público no requieren aviso previo. Las que se convocan en plazas y vías públicas exigen anuncio anticipado a la autoridad, la que puede prohibirlas solamente por motivos probados de seguridad o de sanidad públicas.
13. A asociarse y a constituir fundaciones y diversas formas de organización jurídica sin fines de lucro, sin autorización previa y con arreglo a ley.
No pueden ser disueltas por resolución administrativa.
14. A contratar con fines lícitos, siempre que no se contravengan leyes de orden público.
15. A trabajar libremente, con sujeción a ley.
16. A la propiedad y a la herencia.
17. A participar, en forma individual o asociada, en la vida política, económica, social y cultural de la Nación.
Los ciudadanos tienen, conforme a ley, los derechos de elección, de remoción o revocación de autoridades, de iniciativa legislativa y de referéndum.
18. A mantener reserva sobre sus convicciones políticas, filosóficas, religiosas o de cualquiera otra índole, así como a guardar el secreto profesional.
19. A su identidad étnica y cultural.
El Estado reconoce y protege la pluralidad étnica y cultural de la Nación. Todo peruano tiene derecho a usar su propio idioma ante cualquier autoridad mediante un intérprete.
Los extranjeros tienen este mismo derecho cuando son citados por cualquier autoridad.
20. A formular peticiones, individual o colectivamente, por escrito ante la autoridad competente, la que está obligada a dar al interesado una respuesta también por escrito dentro del plazo legal, bajo responsabilidad.
Los miembros de las Fuerzas Armadas y de la Policía Nacional sólo pueden ejercer individualmente el derecho de petición.
21. A su nacionalidad. Nadie puede ser despojado de ella.
Tampoco puede ser privado del derecho de obtener o de renovar su pasaporte dentro o fuera del territorio de la República.
22. A la paz, a la tranquilidad, al disfrute del tiempo libre y al descanso, así como a gozar de un ambiente equilibrado y adecuado al desarrollo de su vida.
23. A la legítima defensa.
24. A la libertad y a la seguridad personales.
En consecuencia:
a. Nadie está obligado a hacer lo que la ley no manda, ni impedido de hacer lo que ella no prohíbe.
b. No se permite forma alguna de restricción de la libertad personal, salvo en los casos previstos por la ley.
Están prohibidas la esclavitud, la servidumbre y la trata de seres humanos en cualquiera de sus formas.
c. No hay prisión por deudas.
Este principio no limita el mandato judicial por incumplimiento de deberes alimentarios.
d. Nadie será procesado ni condenado por acto u omisión que al tiempo de cometerse no esté previamente calificado en la ley, de manera expresa e inequívoca, como infracción punible; ni sancionado con pena no prevista en la ley.
e. Toda persona es considerada inocente mientras no se haya declarado judicialmente su responsabilidad.
f. Nadie puede ser detenido sino por mandamiento escrito y motivado del juez o por las autoridades policiales en caso de flagrante delito.
El detenido debe ser puesto a disposición del juzgado correspondiente, dentro de las veinticuatro horas o en el término de la distancia.
Estos plazos no se aplican a los casos de terrorismo, espionaje y tráfico ilícito de drogas.
En tales casos, las autoridades policiales pueden efectuar la detención preventiva de los presuntos implicados por un término no mayor de quince días naturales.
Deben dar cuenta al Ministerio Público y al juez, quien puede asumir jurisdicción antes de vencido dicho término.
g. Nadie puede ser incomunicado sino en caso indispensable para el esclarecimiento de un delito, y en la forma y por el tiempo previstos por la ley.
La autoridad está obligada bajo responsabilidad a señalar, sin dilación y por escrito, el lugar donde se halla la persona detenida.
h. Nadie debe ser víctima de violencia moral, psíquica o física, ni sometido a tortura o a tratos inhumanos o humillantes. Cualquiera puede pedir de inmediato el examen médico de la persona agraviada o de aquélla imposibilitada de recurrir por sí misma a la autoridad.
Carecen de valor las declaraciones obtenidas por la violencia. Quien la emplea incurre en responsabilidad.
## ARTICULO 3
La enumeración de los derechos establecidos en este capítulo no excluye los demás que la Constitución garantiza, ni otros de naturaleza análoga o que se fundan en la dignidad del hombre, o en los principios de soberanía del pueblo, del Estado democrático de derecho y de la forma republicana de gobierno.
| 98.425287 | 305 | 0.805208 | spa_Latn | 0.999125 |
48bec0715705e9e43a9671efba2fc070ffa3766a | 2,352 | md | Markdown | content/zh/projects/bda3/Estimate_the_speed_of_light.md | xiaomuliu/academic-kickstart | b8e9ffdf49be905aa22b966a9e8a69231f7e14b7 | [
"MIT"
] | null | null | null | content/zh/projects/bda3/Estimate_the_speed_of_light.md | xiaomuliu/academic-kickstart | b8e9ffdf49be905aa22b966a9e8a69231f7e14b7 | [
"MIT"
] | null | null | null | content/zh/projects/bda3/Estimate_the_speed_of_light.md | xiaomuliu/academic-kickstart | b8e9ffdf49be905aa22b966a9e8a69231f7e14b7 | [
"MIT"
] | null | null | null | ---
title: Normal model for Simon Newcomb's experiment (BDA3 Ch3 p.66)
date: 2020-07-01T16:58:03-07:00
draft: false
linktitle: Normal model for Simon Newcomb's experiment
toc: true
type: docs
menu:
bda3:
parent: Chapter 3
weight: 2
# Prev/next pager order (if `docs_section_pager` enabled in `params.toml`)
weight: 4
---
Normal model for Simon Newcomb's experiment (BDA3 p.66)
```python
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt
%matplotlib inline
```
```python
# with open('../data/light.txt', 'r') as f:
# data = f.readlines()
# y = np.asarray(y, dtype=int)
y = np.loadtxt('../data/light.txt')
plt.hist(y, bins=30)
plt.title('Histogram of Newcomb\'s measurements');
```
```python
# sufficient statistics
n = len(y)
y_mean = np.mean(y)
y_var = np.var(y, ddof=1) # ddof=1 -> sample estimate
# grid for computing density of mu
mu_grid = np.linspace(np.min(y[y>0]), np.max(y), 100)
# compute the exact marginal posterior density for mu
# multiplication by 1./sqrt(y_var/n) is due to the transformation of variable
pm_mu = stats.t.pdf((mu_grid - y_mean) / np.sqrt(y_var/n), n-1) / np.sqrt(y_var/n)
mu025, mu975 = y_mean + stats.t.ppf(0.025, n-1), y_mean + stats.t.ppf(0.975, n-1)
# plot the posterior of mu
plt.plot(mu_grid, pm_mu)
plt.axvline(mu025, color='red')
plt.axvline(mu975, color='red')
axes = plt.gca()
plt.text(
mu025,
axes.get_ylim()[1]+0.03,
'2.5%',
horizontalalignment='right'
)
plt.text(
mu975,
axes.get_ylim()[1]+0.03,
'97.5%',
horizontalalignment='left'
)
plt.xlabel(r'$\mu$')
plt.title(r'Maginal posterior distribution for $\mu$');
```
```python
# calculate posterior interval by simulation
n_sample = 1000
# draw sigma squares
sigma2_sample = (n-1)* y_var / stats.chi2.rvs(df=n-1, size=n_sample)
mu_sample = stats.norm.rvs(y_mean, sigma2_sample/n, size=(1, n_sample))
# posterior median and 95% posterior interval
mu_sample_median = np.median(mu_sample)
mu_sample_025, mu_sample_975 = np.percentile(mu_sample, [2.5, 97.5])
print('mu sample median: {0:.2f}\n95% posterior interval:[{1:.2f}, {2:.2f}]'.format(mu_sample_median, mu_sample_025, mu_sample_975))
```
mu sample median: 26.23
95% posterior interval:[22.32, 29.78]
| 22.615385 | 132 | 0.690051 | eng_Latn | 0.437257 |
48bf1c0349015c77df8599f79e224c1c5489d5dc | 1,106 | md | Markdown | README.md | AlienKevin/straight-parse | 7565789c1e4f51eb1a5e8af9a5606625a8b35bce | [
"MIT"
] | 4 | 2020-04-04T21:41:45.000Z | 2021-12-30T02:39:01.000Z | README.md | AlienKevin/lip | 7565789c1e4f51eb1a5e8af9a5606625a8b35bce | [
"MIT"
] | null | null | null | README.md | AlienKevin/lip | 7565789c1e4f51eb1a5e8af9a5606625a8b35bce | [
"MIT"
] | null | null | null | 
# Lip
Lip provides powerful parser combinators for creating reusable and flexible parsers.
# Why Lip?
* Easy to understand - uses intuitive combinators like keep and skip
* Compact - takes less than an hour to learn this library fully
* Flexible and composable parser combinators
* Efficient - minimal backtracking
* Built-in support for precise, located error messages
* Keep track of extra states like line number and instruction index
* Extensible - create your own combinators if needed
```rust
// Parse an (x, y) position pair
use lip::*;
let position = succeed!(|x, y| (x, y))
.keep(int())
.skip(token(","))
.keep(int())
.run("2,3", ()); // run this parser on string "2,3" without extra states
// when parsing finished, position == (2, 3)
```
# Tutorial
Reading the [parser combinator](https://bodil.lol/parser-combinators/) by Bodil is an excellent way to know how parser combinators work.
# License
MIT
# Credits
Based on Bodil's [Parser Combinator Tutorial](https://bodil.lol/parser-combinators/) and Evan's [elm/paser](https://github.com/elm/parser). | 33.515152 | 139 | 0.729656 | eng_Latn | 0.956989 |
48c024951106a4ddcf2a6cc8ae6d4f7d5d6bd2e3 | 288 | md | Markdown | source/_assessments/27704.md | salihzeki12000/Website | 733c8f7ea86f6ee4967cbbbb83cfc10d12cf7c12 | [
"MIT"
] | null | null | null | source/_assessments/27704.md | salihzeki12000/Website | 733c8f7ea86f6ee4967cbbbb83cfc10d12cf7c12 | [
"MIT"
] | 10 | 2019-08-13T10:55:15.000Z | 2022-02-26T10:21:10.000Z | source/_assessments/27704.md | wing5wong/artisan-whs-static | cb36480c54adcb5cbe1fd25c1a741bb525112a72 | [
"MIT"
] | 1 | 2020-10-30T12:55:04.000Z | 2020-10-30T12:55:04.000Z | ---
title: "27704"
description: "Design and construct item(s) to meet production needs for a performance context"
level: "2"
assessment: "Internal"
credits: "4"
pdf: "http://c1940652.r52.cf0.rackcdn.com/55d3e975ff2a7c4dd0000277/27704.pdf"
categories:
- "PAT2"
---
| 19.2 | 94 | 0.680556 | eng_Latn | 0.440822 |
48c16a7d9e7033e8db194cdfcaa15dda8a2637ec | 21 | md | Markdown | README.md | rodkulman/scaling-octo-dollop | ea1f92ad8c582e13e38d79a4dbbf276b96bb28ac | [
"MIT"
] | null | null | null | README.md | rodkulman/scaling-octo-dollop | ea1f92ad8c582e13e38d79a4dbbf276b96bb28ac | [
"MIT"
] | null | null | null | README.md | rodkulman/scaling-octo-dollop | ea1f92ad8c582e13e38d79a4dbbf276b96bb28ac | [
"MIT"
] | null | null | null | # scaling-octo-dollop | 21 | 21 | 0.809524 | vie_Latn | 0.362774 |
48c1c2a2d44643e34c5d0f024ded10b486a61754 | 14,209 | md | Markdown | participating-projects.md | bettinaheim/unitaryhack | 81be69af30876cf8cadcd8a0ca9ca39b216fc6d5 | [
"MIT"
] | 1 | 2022-01-25T02:48:47.000Z | 2022-01-25T02:48:47.000Z | participating-projects.md | bettinaheim/unitaryhack | 81be69af30876cf8cadcd8a0ca9ca39b216fc6d5 | [
"MIT"
] | null | null | null | participating-projects.md | bettinaheim/unitaryhack | 81be69af30876cf8cadcd8a0ca9ca39b216fc6d5 | [
"MIT"
] | null | null | null | ---
layout: page
title: Projects
---
> #### You can see all of the tagged issues on GitHub [here](https://github.com/topics/unitaryhack)!
<style type="text/css">
.tg {border-collapse:collapse;border-spacing:0;}
.tg td{border-color:grey;border-style:none;border-width:1px;
overflow:hidden;padding:5px 5px;word-break:normal;}
.tg .tg-sj11{!important;;font-size:medium; text-align:left;vertical-align:middle}
</style>
<table class="tg">
<tbody>
<tr>
<td class="tg-sj11"><a href="#mitiq">Mitiq</a></td>
<td class="tg-sj11"><a href="#pennylane">PennyLane</a></td>
<td class="tg-sj11"><a href="#strawberry-fields">Strawberry Fields</a></td>
<td class="tg-sj11"><a href="#the-walrus">The Walrus</a></td>
</tr>
<tr>
<td class="tg-sj11"><a href="#toqito">toqito</a></td>
<td class="tg-sj11"><a href="#scirate">SciRate</a></td>
<td class="tg-sj11"><a href="#qunetsim">QuNetSim</a></td>
<td class="tg-sj11"><a href="#interlin-q">Interlin-q</a></td>
</tr>
<tr>
<td class="tg-sj11"><a href="#qrand">QRAND</a></td>
<td class="tg-sj11"><a href="#qrack">Qrack</a></td>
<td class="tg-sj11"><a href="#qutip">QuTiP</a></td>
<td class="tg-sj11"><a href="#pulser">Pulser</a></td>
</tr>
<tr>
<td class="tg-sj11"><a href="#qcor">QCOR</a></td>
<td class="tg-sj11"><a href="#xacc">XACC</a></td>
<td class="tg-sj11"><a href="#qosf-monthly-challenges">QOSF Monthly Challenges</a></td>
<td class="tg-sj11"><a href="#yao">Yao</a></td>
</tr>
<tr>
<td class="tg-sj11"><a href="#quantify">Quantify</a></td>
<td class="tg-sj11"><a href="#qqcs">QQCS</a></td>
<td class="tg-sj11"></td>
<td class="tg-sj11"></td>
</tr>
</tbody>
</table>
---
## [Mitiq](https://github.com/unitaryfund/mitiq)
Mitiq is a Python toolkit for implementing error mitigation techniques on quantum computers.
Current quantum computers are noisy due to interactions with the environment, imperfect gate applications, state preparation and measurement errors, etc. Error mitigation seeks to reduce these effects at the software level by compiling quantum programs in clever ways.
> General issues we are looking for help with during [unitaryHACK](https://github.com/unitaryfund/mitiq/labels/unitaryhack)
### Bounties
#### $100 each
- [Add tutorial example where mitiq makes a variational problem trainable](https://github.com/unitaryfund/mitiq/issues/529)
#### $50 each
- [Add documentation about parameter scaling](https://github.com/unitaryfund/mitiq/issues/501)
#### $25 each
- [Add type check to CI](https://github.com/unitaryfund/mitiq/issues/489)
- [Add an XACC executor example and item to software list](https://github.com/unitaryfund/mitiq/issues/357)
- [Testing or updating or replacing the TensorFlow Quantum executor example](https://github.com/unitaryfund/mitiq/issues/559)
- [Warn users when their programs are too short](https://github.com/unitaryfund/mitiq/issues/275)
---
## [PennyLane](https://github.com/PennyLaneAI/pennylane)
PennyLane is a cross-platform Python library for differentiable programming of quantum computers.
Train a quantum computer the same way as a neural network.
### Bounties
#### $100 each
- [Create a quantum simulator in PyTorch](https://github.com/PennyLaneAI/pennylane/issues/1225)
---
## [Strawberry Fields](https://github.com/XanaduAI/strawberryfields)
Strawberry Fields is a full-stack Python library for designing, simulating, and optimizing continuous-variable quantum optical circuits.
### Bounties
#### $100 each
- [Add a hybrid Gaussian/non-Gaussian compiler that merges Gaussian gates](https://github.com/XanaduAI/strawberryfields/issues/574)
---
## [The Walrus](https://github.com/XanaduAI/thewalrus)
A library for the fast calculation of hafnians, Hermite polynomials, and Gaussian boson sampling.
### Bounties
#### $50 each
- [Improve the calculation of multidimensional hermite polynomials](https://github.com/XanaduAI/thewalrus/issues/214)
---
## [toqito](https://github.com/vprusso/toqito)
The toqito package is an open source Python library for studying various
objects in quantum information, namely, states, channels, and measurements.
Specifically, toqito focuses on providing numerical tools to study problems
pertaining to entanglement theory, nonlocal games, matrix analysis, and other
aspects of quantum information that are often associated with computer science.
> A complete list of issues can be found
[here](https://github.com/vprusso/toqito/issues)
### Bounties
#### $85 each
- [Implement feature for calculating the NPA hierarchy](https://github.com/vprusso/toqito/issues/5)
- [Implement feature for converting a binary constraint game to a nonlocal game](https://github.com/vprusso/toqito/issues/44)
- [Implement feature for determining whether an operator is block-positive](https://github.com/vprusso/toqito/issues/45)
---
## [SciRate](https://github.com/scirate/scirate)
[SciRate](http://scirate.com/) is an open source rating and commenting system
for arXiv preprints. Papers are upvoted and discussed by the community, and
we sometimes play host to more in depth peer review.
> Check out some issues we are looking for help with ["help
wanted"](https://github.com/scirate/scirate/issues?q=is%3Aissue+is%3Aopen+label%3A%22help+wanted%22).
### Bounties
TBD
---
## [QuNetSim](https://github.com/tqsd/QuNetSim)
QuNetSim is a quantum network simulation framework. With it, one can develop protocols for quantum networks
such as QKD, quantum teleportation, anonymous transmission, and many more over custom network topologies.
> The complete list of issues for QuNetSim are [here](https://github.com/tqsd/QuNetSim/issues).
### Bounties
#### $60 each
- [Develop a user interface for QuNetSim](https://github.com/tqsd/QuNetSim/issues/82)
- [Develop QKD protocols](https://github.com/tqsd/QuNetSim/issues/90)
- [Develop a more complex templating script](https://github.com/tqsd/QuNetSim/issues/52)
- [Develop an example of a second generation quantum repeater](https://github.com/tqsd/QuNetSim/issues/91)
---
## [Interlin-q](https://github.com/Interlin-q/Interlin-q)
Interlin-q is a simulation platform for simulating distributed quantum algorithms. The purpose
of Interlin-q is to be able to enter a monolithic quantum circuit and based on the distributed
architecture, automatically map the circuit and then simulate the control process to run the algorithm.
### Bounties
#### $250
- [Integrate pyQuirk with Interlin-q](https://github.com/Interlin-q/Interlin-q/issues/35)
---
## [QRAND](https://github.com/pedrorrivero/qrand)
QRAND is a smart quantum random number generator for arbitrary probability
distributions, which operates by providing a multiplatform NumPy adapter
interface (e.g. qiskit, cirq, qsharp). To boost the randomness production
speed it implements an efficient randomness retrieval strategy based on caching
and multithreading.
On top of that, it also allows the design and use of different platform-agnostic
quantum randomness generation protocols; as well as performing validation on the
results, according to a variety of NIST standards.
- [Unitary Hack sponsored issues](https://github.com/pedrorrivero/qrand/labels/unitaryhack)
- [Complete list of issues](https://github.com/pedrorrivero/qrand/issues)
### Bounties
#### $100 each
- [Cirq support](https://github.com/pedrorrivero/qrand/issues/1)
- [Q# support](https://github.com/pedrorrivero/qrand/issues/2)
#### $50 each
- [Entropy validation suite](https://github.com/pedrorrivero/qrand/issues/3)
---
## [Qrack](https://github.com/vm6502q/qrack)
Qrack is a GPU-accelerated HPC quantum computer simulator framework. The core library is
dependency-free C++11, with optional OpenCL and Boost headers. Hardware supports spans from desktop,
to mobile, to distributed clusters, and OS support includes Linux, Windows, Mac, Android, and iOS.
Qrack aims to optimize the performance of noiseless pure state simulations. To this end, it contains
many "layers" of functionality and novel optimization techniques.
- A complete list of issues can be found
[here](https://github.com/vm6502q/qrack/issues)
### Bounties
#### $125
- [Feature: Cirq plugin](https://github.com/vm6502q/qrack/issues/678)
#### $125
- [Feature: Optional CUDA Support](https://github.com/vm6502q/qrack/issues/397)
---
## [QuTiP](https://github.com/qutip/qutip)
QuTiP is an open-source Python library for simulating the dynamics of closed
and open quantum systems, including quantum information processing and
quantum control.
### Bounties
#### $25
- [Fix error raised by ffmpeg command from User Guide](https://github.com/qutip/qutip/issues/799)
- [Bloch sphere requires matplotlib >= 3.3](https://github.com/qutip/qutip/issues/1502)
- [Address deprecation warnings in Matplotlib 3.4](https://github.com/qutip/qutip/issues/1503)
#### $75
- [Address "malloc: Incorrect checksum" error in qutip.testing qt.run()](https://github.com/qutip/qutip/issues/1160)
TBD
---
## [Pulser](https://github.com/pasqal-io/Pulser)
Pulser is a Python library for programming neutral-atom quantum devices at the pulse level. The low-level nature of Pulser makes it a versatile framework for quantum control both in the digital and analog settings. The library also contains simulation routines for studying and exploring the outcome of pulse sequences for small systems.
> We recommend tackling [these issues](https://github.com/pasqal-io/Pulser/issues?q=is%3Aissue+is%3Aopen+label%3Aunitaryhack). If you want to start with a simple contribution, look also for a ["good first issue"](https://github.com/pasqal-io/Pulser/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22).
### Bounties
#### $100 each
- [Add Support for Simulation in XY Mode](https://github.com/pasqal-io/Pulser/issues/147)
- [Add type hints, and mypy CI tests](https://github.com/pasqal-io/Pulser/issues/16)
#### $50
- [Option to display pulses' areas and phases on a plot](https://github.com/pasqal-io/Pulser/issues/149)
---
## [QCOR](https://github.com/ornl-qci/qcor)
QCOR is a quantum-retargetable compiler platform providing language extensions for both C++
and Python that allows programmers to express quantum code as stand-alone kernel functions.
### Bounties
#### $25
- [API for command-line argument parsing](https://github.com/ornl-qci/qcor/issues/123)
- [Improved CMake Target Exporting and Downstream Quantum-Classical add_executable()](https://github.com/ornl-qci/qcor/issues/101)
#### $50
- [Quantum JIT Cache Manager](https://github.com/ornl-qci/qcor/issues/126)
#### $150
- [Python Wheels or Conda Binary](https://github.com/ornl-qci/qcor/issues/129)
---
## [XACC](https://github.com/eclipse/xacc)
XACC is a service-oriented, system-level software infrastructure in C++ promoting an
extensible API for the typical quantum-classical programming, compilation, and execution
workflow.
### Bounties
#### $50
- [xacc::getAccelerator("ibm") automatic backend selection based on jobs in the queue](https://github.com/eclipse/xacc/issues/441)
#### $100
- [Flexible Instruction Simulation](https://github.com/eclipse/xacc/issues/442)
- [Implement 3-qubit decomposition](https://github.com/eclipse/xacc/issues/437)
---
## [Yao](https://github.com/QuantumBFS/Yao.jl)
Yao is an open source framework that aims to empower quantum information research with software tools in the [Julia programming language](http://julialang.org/).
### Bounties
#### $50
- [integration with PastaQ](https://github.com/QuantumBFS/Yao.jl/issues/280)
#### $100
- [integrate YaoBlocks with IBMQClient and OpenQASM](https://github.com/QuantumBFS/Yao.jl/issues/279)
- [webpage (tutorial/documentation/etc.) pipeline improvements](https://github.com/QuantumBFS/Yao.jl/issues/278)
---
## [QOSF Monthly Challenges](https://github.com/qosf/monthly-challenges/)
The Quantum Open Source Foundation (QOSF) Monthly Challenges aim to help participants hone their general quantum computing skills. These are open to everyone and welcome solo or team contributions. Solutions are peer-reviewed.
### Bounties
#### $25
- [Design a challenge!](https://github.com/qosf/monthly-challenges/issues/33)
- [Design a challenge!](https://github.com/qosf/monthly-challenges/issues/34)
---
## [QQCS](https://github.com/dde/qqcs)
QQCS is a simple linear notation for the simulation of quantum circuits.
> A list of issues can be found [here](https://github.com/dde/qqcs/issues)
### Bounties
#### $125 Each
- [Design new syntax to declare circuit lines to be divided into separate registers.](https://github.com/dde/qqcs/issues/15)
- [Add an adjoint operator (') the gate suffix syntax and to the interpreter.](https://github.com/dde/qqcs/issues/16)
#### $25
- [Add a command line switch to display sparse matrices with periods (.) replacing zero elements (0).](https://github.com/dde/qqcs/issues/18)
---
## [Quantify](https://gitlab.com/quantify-os)
Quantify is a python based data acquisition platform focused on Quantum Computing and solid-state physics experiments. It is built on top of [QCoDeS](https://qcodes.github.io/Qcodes/) and is a spiritual successor of [PycQED](https://github.com/DiCarloLab-Delft/PycQED_py3). Quantify currently consists of [quantify-core](https://gitlab.com/quantify-os/quantify-core) and [quantify-scheduler](https://gitlab.com/quantify-os/quantify-scheduler).
A list of other issues can be found here:
- [Quantify-core issues](https://gitlab.com/quantify-os/quantify-core/-/issues?label_name%5B%5D=unitaryhack)
- [Quantify-scheduler issues](https://gitlab.com/quantify-os/quantify-scheduler/-/issues?label_name%5B%5D=unitaryhack)
### Bounties
#### $25
- [Create an interactive data browser](https://gitlab.com/quantify-os/quantify-core/-/issues/204)
- [Save JSON schedule to harddisk](https://gitlab.com/quantify-os/quantify-scheduler/-/issues/2)
#### $50
- [Replace PyQT5 for realtime visualization](https://gitlab.com/quantify-os/quantify-core/-/issues/203)
#### $75
- [Support loops and classical logic in quantify-scheduler](https://gitlab.com/quantify-os/quantify-scheduler/-/issues/33)
- [Parser and generator for Qiskit, Cirq](https://gitlab.com/quantify-os/quantify-scheduler/-/issues/111)
| 39.912921 | 443 | 0.743472 | eng_Latn | 0.709326 |
2c8b475c742f60554944a25c57061e82c7843392 | 352 | md | Markdown | Public/extend/ckeditor/tests/plugins/font/manual/changingfontsize.md | superredman/em | b30f4fc3241f6d17c09ecbf251c009442c815468 | [
"BSD-2-Clause"
] | 1 | 2019-10-11T11:28:04.000Z | 2019-10-11T11:28:04.000Z | Public/extend/ckeditor/tests/plugins/font/manual/changingfontsize.md | superredman/em | b30f4fc3241f6d17c09ecbf251c009442c815468 | [
"BSD-2-Clause"
] | null | null | null | Public/extend/ckeditor/tests/plugins/font/manual/changingfontsize.md | superredman/em | b30f4fc3241f6d17c09ecbf251c009442c815468 | [
"BSD-2-Clause"
] | null | null | null | @bender-tags: 4.4.6, tc
@bender-ui: collapsed
@bender-ckeditor-plugins: wysiwygarea, toolbar, font, enterkey, elementspath
1. Change font size to 72.
1. Type a word.
1. Change font size to 20.
* There should be only one "span" in the elements path.
1. Type a word.
1. Press enter.
1. Type a word.
* The caret and the word should be around 20px high. | 29.333333 | 76 | 0.724432 | eng_Latn | 0.94254 |
2c8c10857ac3ac575584a17594882b9b0858f1f9 | 2,065 | md | Markdown | README.md | dulibrarytech/digitaldu-frontend-v1 | 841b65314296cced5d62b87e4bf8d4f9f82304ea | [
"Apache-2.0"
] | null | null | null | README.md | dulibrarytech/digitaldu-frontend-v1 | 841b65314296cced5d62b87e4bf8d4f9f82304ea | [
"Apache-2.0"
] | 1 | 2020-02-18T17:56:24.000Z | 2020-02-18T17:56:24.000Z | README.md | dulibrarytech/digitaldu-frontend-v1 | 841b65314296cced5d62b87e4bf8d4f9f82304ea | [
"Apache-2.0"
] | null | null | null | # Digital Collections Frontend - digitaldu
## Background
The frontend of the University of Denver's Digital Collections repository, https://specialcollections.du.edu.
## Contributing
Check out our [contributing guidelines](/CONTRIBUTING.md) for ways to offer feedback and contribute.
## Licenses
[Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0).
All other content is released under [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/).
## Maintainers
@jrynhart
## Acknowledgments
@freyesdulib
@kimpham54
@jackflaps
@josephlabrecque
## Local Development Setup
- Steps to configure Digital Collections app locally...
1. Clone the application files from Git repository(https://github.com/dulibrarytech/digitaldu-frontend.git")
2. Run "sudo npm install" from the root folder to install dependencies
3. Create a file ".env" in the project root folder. It should contain the following properties:
```
NODE_ENV=development
NODE_TLS_REJECT_UNAUTHORIZED=1
APP_HOST=http://localhost
APP_PORT=9006
CLIENT_HOST=http://localhost:9006
CLIENT_PATH=
ELASTICSEARCH_HOST={HOST}
ELASTICSEARCH_PORT={PORT}
ELASTICSEARCH_INDEX={INDEX}
REPOSITORY={REPOSITORY}
CANTALOUPE_URL={CANTALOPE_URL}
IIIF_URL={IIIF_URL}
```
4. APP_HOST is the url to the server. Do not add the port to this url, add that to APP_PORT. Set APP_PORT to whatever port the nodejs app should run on.
5. CLIENT_HOST is the url to the client. Add the port to the end if necessary
6. IIIF_URL can be localhost, as the service is included with DigitalCollections. Make sure the port listed here is the port that DigitalCollections is running on.
7. Setup a local instance of Cantaloupe image server and update the CANTALOUPE_URL field in .env
8. Run the app by using "node discovery.js" or "nodejs discovery.js" from the app root folder.
| 29.927536 | 169 | 0.693462 | eng_Latn | 0.822846 |
2c8c7d86825f51f1adbe8944b306d15699fb6239 | 3,966 | md | Markdown | content/tech/2020-08-27-vercel-serverless-functions-web-api-をデプロイする.md | jiri3/kotsu2to | 8f9fbb09d440a696333fad75e3174ce9afe1f135 | [
"MIT"
] | null | null | null | content/tech/2020-08-27-vercel-serverless-functions-web-api-をデプロイする.md | jiri3/kotsu2to | 8f9fbb09d440a696333fad75e3174ce9afe1f135 | [
"MIT"
] | 4 | 2022-02-14T21:38:20.000Z | 2022-03-01T23:18:02.000Z | content/tech/2020-08-27-vercel-serverless-functions-web-api-をデプロイする.md | jiri3/kotsu2to | 8f9fbb09d440a696333fad75e3174ce9afe1f135 | [
"MIT"
] | null | null | null | ---
category: tech
date: 2020-08-28T10:00:00.000Z
updatedate: 2020-09-02T07:05:31.838Z
title: "[Vercel] Serverless Functions(Web API)をデプロイする"
description: Vercel の Serverless Functions(Web API)をデプロイする手順を説明します。
tags:
- Vercel
---
[Vercel](https://vercel.com/) とは静的サイトや Serverless Functions をホスティングするサービスです。
無料で利用できる枠もあるので、試しに使うのにはもってこいです。
Serverless Functions とは、HTTPリクエストを受け取りレスポンスを返すコードのことのようです[^1]。
> With Vercel, you can deploy Serverless Functions, which are pieces of code written with backend languages that take an HTTP request and provide a response.
今回は、Hello World をレスポンスとして返す Serverless Functions（Web API）をVercelを利用してデプロイしてみます。
それでは、Serverless Functions の作成手順の説明に進みます。
1. Vercel でアカウントを作成する
2. Serverless Functions を実装する
3. デプロイする
以下、手順に沿って説明していきます。
#### Vercel でアカウントを作成する
[こちら](https://vercel.com/signup)からアカウントを作成してください。
作成するためには、GitHub、GitLab または Bitbucket のいずれかのアカウントが必要になるので、
事前にそちらのアカウントも作成しておいてください。
私は GitHub ユーザーなので、以下の説明は GitHubでアカウントを作成した想定で進めます。
#### Serverless Functions を実装する
Vercel は、GitHub と連動させることが可能で、push するとデプロイまで自動で実行してくれます。
この機能を利用するため、まずはGitHub の方でレポジトリを作成します。
レポジトリ作成後は、開発環境用にレポジトリをクローンしてきます。
```bash
$ git clone `https://github.com/{username}/{repository-name}.git`
```
次にクローンしてきたレポジトリのルートディレクトリ配下に api ディレクトリを作成します[^2]。
この api ディレクトリ配下にソースコードを格納する必要があります。
```bash
$ mkdir ./api
```
次に実装に入ります。今回は Node.js で開発します。
ちなみに[こちらのプログラミング言語](https://vercel.com/docs/serverless-functions/supported-languages#supported-languages:)がサポートされています。
また、TypeScript を使いたいので、次のパッケージをインストールします[^3]。
```bash
$ npm init -y
$ npm install @vercel/node --save-dev
```
それでは、Hello world をレスポンスとして返すソースを実装します。
```javascript
// api/hello.ts
import { NowRequest, NowResponse } from "@vercel/node";
export default function (req: NowRequest, res: NowResponse) {
const { name = "World" } = req.query;
res.send(`Hello ${name}!`);
}
```
以上で実装は完了したので、commit してリモートレポジトリに push します。
```bash
$ git add .
$ git commit -m "commit message"
$ git push
```
#### デプロイする
まずは、Vercel と push したレポジトリを関連付けます。
Vercel ログイン後に表示されるダッシュボードに「Import Project」ボタンがあるので押下してください。
Import Git Repository の「Continue」ボタンを押下します。
次の画面で先ほどの Git レポジトリの URL を入力して、「Continue」ボタンを押下します。
次の画面は、ソースコードが入っているディレクトリを選択するのですが、
root ディレクトリのままにして「Continue」ボタンを押下してください。
ここで、api を選択してしまうと Serverless Functions が動作しなくなるのでご注意ください。
次の画面は、特に修正は不要です。「Deploy」ボタンを押下してください。
以上で、デプロイが完了しました。
#### 動作確認する
作成した Serverless Functions の動作確認をしてみます。
Serverless FunctionsへアクセスするためのURLですが、
`https://デプロイ先のドメイン/api/ソースコードのファイル名（拡張子を覗く）`となります。
（これはデフォルトの場合です。設定で変更可能です。）
デプロイ先のドメインは、下図の通りデプロイしたプロジェクトのダッシュボードに記載されています。
（デプロイ完了後の画面の「Open Dashbord」ボタンを押下するとプロジェクトのダッシュボードが開けます。）
今回の場合は、次の URLがServerless Functionsへのアクセス先となります。
https://vercel-sample-nine.vercel.app/api/hello
ブラウザからアクセスするか、次のように curl コマンドを利用すると動作確認ができます。
URL パラメータを指定しなければ、「Hello World!」と表示されると思います。
```bash
$ curl https://vercel-sample-nine.vercel.app/api/hello
```
---
今回は、Vercel の Serverless Functions の作成方法について紹介しました。
Vercel には、1 日にデプロイできる回数などの制限があるので、
利用前に[こちら](https://vercel.com/docs/platform/limits)を一読すると良いかと思います。
#### 参考
- [JAMstack ってなに？実践に学ぶ高速表示を実現するアーキテクチャの構成](https://employment.en-japan.com/engineerhub/entry/2019/12/10/103000)
[^1]: [Serverless Functions](https://vercel.com/docs/serverless-functions/introduction)
[^2]: [Creating Serverless Functions](https://vercel.com/docs/serverless-functions/introduction#creating-serverless-functions)
[^3]: [Using TypeScript with the Node.js Runtime](https://vercel.com/docs/runtimes#official-runtimes/node-js/using-typescript-with-the-node-js-runtime)
| 26.44 | 157 | 0.779627 | yue_Hant | 0.334999 |
2c8d5c0ed34014d47dabdf74cb01c98717429a72 | 406 | md | Markdown | Research/index.md | xiaohanzai/xiaohanzai.github.io | 99c99d9104b25ed6a69a2177d911178609032dc0 | [
"MIT"
] | null | null | null | Research/index.md | xiaohanzai/xiaohanzai.github.io | 99c99d9104b25ed6a69a2177d911178609032dc0 | [
"MIT"
] | null | null | null | Research/index.md | xiaohanzai/xiaohanzai.github.io | 99c99d9104b25ed6a69a2177d911178609032dc0 | [
"MIT"
] | null | null | null | ---
layout: page
title: ""
---
## Projects
* [Non-parametric halo biasing model](NonParam_Lag_bias/)
* [Pop-III reionization and the CMB](PopIII_CMB/)
* [Accuracy of moment-based radiative transfer methods](RT_Eddington_tensor/)
* [Temperature fluctuations in the Lyman-α forest](T_fluc_forest/)
* [Photoheating feedback during reionization](ArepoRT_reion/)
* [Simba EoR galaxies](Simba_EoR/)
| 21.368421 | 77 | 0.746305 | eng_Latn | 0.709668 |
2c8d7a09223d3b2d1e020ba2aec7944df290c937 | 560 | md | Markdown | README.md | GEEK1050/Book_Rental_Application | 30aa7cba27c2ba1c3c9584af024784eba7e1a249 | [
"MIT"
] | 5 | 2022-01-28T15:18:29.000Z | 2022-02-02T13:30:04.000Z | README.md | Moussaddak/Book-Rental-Management-System | 30aa7cba27c2ba1c3c9584af024784eba7e1a249 | [
"MIT"
] | null | null | null | README.md | Moussaddak/Book-Rental-Management-System | 30aa7cba27c2ba1c3c9584af024784eba7e1a249 | [
"MIT"
] | 1 | 2022-02-01T12:37:56.000Z | 2022-02-01T12:37:56.000Z | # Book_Rental_Application
A web application that manage library system.
## Built With
* [React.js](https://reactjs.org/)
* [Bootstrap](https://getbootstrap.com)
* [Node.Js](https://nodejs.org)
* [Socket.io](https://socket.io)
* [MongoDB](https://www.mongodb.com)
## Installation
Clone the repo:
```bash
git clone https://github.com/GEEK1050/Book_Rental_Application.git
```
### Usage
```bash
cd client
npm install
npm start
```
In other terminal
```bash
cd server
npm install
npm start
```
## License
[MIT](https://choosealicense.com/licenses/mit/)
| 14 | 65 | 0.703571 | kor_Hang | 0.310362 |
2c8e3ca1c89532394dff8d03478cbc48bed0b0c3 | 2,239 | md | Markdown | vendor/coduo/php-matcher/CHANGELOG.md | mohamedshaaban/symfony | d7a63b1159b47ee501626f35cd27476783fd7370 | [
"MIT"
] | 2 | 2016-12-28T14:10:59.000Z | 2017-06-07T20:54:37.000Z | vendor/coduo/php-matcher/CHANGELOG.md | mohamedshaaban/symfony | d7a63b1159b47ee501626f35cd27476783fd7370 | [
"MIT"
] | 2 | 2020-07-17T10:05:11.000Z | 2021-05-09T08:06:09.000Z | vendor/coduo/php-matcher/CHANGELOG.md | mohamedshaaban/symfony | d7a63b1159b47ee501626f35cd27476783fd7370 | [
"MIT"
] | 2 | 2019-07-10T04:09:15.000Z | 2020-11-04T03:54:27.000Z | # 2.0.0-r2
* Added or operator ``@string@||@null@`` - @partikus
# 2.0.0-r1
# 2.0.0-beta
* Openssl/lib-array2xml dependency is now more flexible - @blazarecki
# 2.0.0-alpha2
* PHPUnit integration - @jakzal
# 2.0.0-alpha1
* Added support for PHP7
* Updated dependencies to support Symfony3 components
* Added ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\MatchRegexTest`` expander - @blazarecki
* Added ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\IsEmpty`` expander - @blazarecki
* Added PHPMatcher facade in order to improve developers experience
# 1.1.0
* Added pattern expanders mechanism with following expanders:
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\Contains``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\EndsWith``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\GreaterThan``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\InArray``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\IsDateTime``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\IsEmail``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\IsUrl``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\LowerThan``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\MatchRegex``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\OneOf``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\StartsWith``
# 1.0.0
* PHPMatcher initial release with following matchers:
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\ArrayMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\CallbackMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\CaptureMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\ChainMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\ExpressionMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\JsonMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\NullMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\ScalarMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\TypeMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\WildcardMatcher``
* ``Coduo\PHPMatcher\Tests\Matcher\Pattern\Expander\XmlMatcher``
| 42.245283 | 97 | 0.749888 | yue_Hant | 0.795973 |
2c901890aa110c566b8447d2f5d12f044c7d9ebe | 1,552 | md | Markdown | content/resources/courses.md | yamanoku/awesome-vue | 6e3009c91b053363e75e59fa139d3f01ccf470bd | [
"Unlicense"
] | 223 | 2018-10-03T06:09:18.000Z | 2022-03-31T07:37:32.000Z | content/resources/courses.md | yamanoku/awesome-vue | 6e3009c91b053363e75e59fa139d3f01ccf470bd | [
"Unlicense"
] | 36 | 2019-03-11T05:49:23.000Z | 2022-03-26T00:49:16.000Z | content/resources/courses.md | yamanoku/awesome-vue | 6e3009c91b053363e75e59fa139d3f01ccf470bd | [
"Unlicense"
] | 76 | 2019-01-19T19:03:11.000Z | 2022-02-10T05:58:27.000Z | ---
meta:
- name: description
content: Vue.js courses
- name: og:title
content: Courses
- name: og:type
content: website
- name: og:url
content: https://awesome-vue.js.org/resources/courses.html
- name: og:image
content: https://awesome-vue.js.org/hero.png
- name: og:description
content: Vue.js courses
- name: twitter:card
content: summary
- name: twitter:title
content: Courses
- name: twitter:description
content: Vue.js courses
- name: twitter:image:src
content: https://awesome-vue.js.org/hero.png
---
# Courses
- [Learn Vue by Building and Deploying a CRUD App](https://testdriven.io/courses/learn-vue/) - This course is focused on teaching the fundamentals of Vue by building and testing a web application using Test-Driven Development (TDD)
- [Introduction to Vue.js](https://frontendmasters.com/courses/vue/) - An introductory course that explores the basics of features like directives and modifiers, concepts like components, reactive programming, Nuxt.js, and Vuex
- [Advanced Vue.js Features from the Ground Up](https://frontendmasters.com/courses/advanced-vue/) - Learn how to build more accessible routing, state management, form validation and internationalization libraries from the ground up
- [Become a Ninja with Vue 3](https://vue-exercises.ninja-squad.com) - This course teaches how to build a complete application with Vue 3, step by step, using Vue CLI, TypeScript and the Composition API. Each exercise comes with instructions and tests to check 100% of your code
| 50.064516 | 278 | 0.744845 | eng_Latn | 0.905911 |
2c9060eada0f459c8488adfd2fe186a22ae973f6 | 1,561 | md | Markdown | README.md | code-native/open-refine-clustering-key-methods | 6c77d1e005ebe364ae5a05bc615570dcc835183b | [
"MIT"
] | null | null | null | README.md | code-native/open-refine-clustering-key-methods | 6c77d1e005ebe364ae5a05bc615570dcc835183b | [
"MIT"
] | null | null | null | README.md | code-native/open-refine-clustering-key-methods | 6c77d1e005ebe364ae5a05bc615570dcc835183b | [
"MIT"
] | 1 | 2019-11-22T00:48:50.000Z | 2019-11-22T00:48:50.000Z | # OpenRefine Clustering Key Methods
## Motivation
[OpenRefine](http://openrefine.org/) has effetive text clustering feature. It is based on several text signature methodologies.
1. Fingerprint
2. N-Gram Fingerprint
3. Phonetic Fingerprint
4. Nearest Neighbor Methods
5. Levenshtein Distance
6. PPM
I want to create a easy to use API based on these methods. Implementation is in Python. Live API is serverless.
## Prior Art
### OpenRefine
If you want to have a quick overview on how OpenRefine clustern works watch this [Video: 4 minutes](https://www.youtube.com/watch?v=-aa02-9lf8o). OpenRefine has detailed explaination of the clustering feature and description of all methods on [Clustering In Depth](https://github.com/OpenRefine/OpenRefine/wiki/Clustering-In-Depth).
### Python Packages
In order to reduce the amount of code to write and maintain, existing libraries should be studied. Many fine implementation of the algorithems already exist. Each package is evaluated to determind its suitablility.
1. Fingerprint
2. N-Gram Fingerprint
- [ngram](https://pypi.org/project/ngram/3.2/)
3. Phonetic Fingerprint
- [abydos](https://pypi.org/project/abydos/)
4. Nearest Neighbor Methods (kNN)
- [Scikit-Learn](https://scikit-learn.org/)
5. Levenshtein Distance
- [abydos](https://pypi.org/project/abydos/)
- [python-Levenshtein](https://pypi.org/project/python-Levenshtein/)
6. Prediction by Partial Matching
- [xunzheng](https://github.com/xunzheng/ppm)
- [pluskid](https://github.com/pluskid/pyppm)
- [VaLID](https://pypi.org/project/VaLID/)
| 34.688889 | 332 | 0.767457 | eng_Latn | 0.750019 |
2c90892c079ddab5c4ae789b3bb2a33c43ec2e03 | 530 | md | Markdown | _posts/2020-05-15-hadoop-windows.md | HadiFadl/hadifadl.github.io | b29273a3fa0b945e2c773b8adb5396b68574e5e4 | [
"MIT"
] | 1 | 2020-11-16T17:10:02.000Z | 2020-11-16T17:10:02.000Z | _posts/2020-05-15-hadoop-windows.md | HadiFadl/hadifadl.github.io | b29273a3fa0b945e2c773b8adb5396b68574e5e4 | [
"MIT"
] | null | null | null | _posts/2020-05-15-hadoop-windows.md | HadiFadl/hadifadl.github.io | b29273a3fa0b945e2c773b8adb5396b68574e5e4 | [
"MIT"
] | null | null | null | ---
layout: post
title: Reasons to not install Hadoop on Windows
published: true
date: '2020-05-15'
image: /assets/img/posts/hadooplogo.png
external_url: 'https://medium.com/@hadi.fadlullah/reasons-to-not-install-hadoop-on-windows-5bf22f3f0005'
tags:
- big data
- hadoop
- windows
subtitle: Munchy Bytes
---
After working on several projects, I ended up with a consequence that it is not recommended to install Hadoop on windows operating system. In this article, I briefly described the main reasons for this consequence.
| 35.333333 | 215 | 0.773585 | eng_Latn | 0.992326 |
2c90b2646b3a0dee8c5e6fa98284b1c5c6f927d4 | 1,376 | md | Markdown | docs/Index.md | xdnice/build | 5d9e5bc7ca67ccd3541e3898e87d6c3e1f08cbcd | [
"MIT"
] | null | null | null | docs/Index.md | xdnice/build | 5d9e5bc7ca67ccd3541e3898e87d6c3e1f08cbcd | [
"MIT"
] | null | null | null | docs/Index.md | xdnice/build | 5d9e5bc7ca67ccd3541e3898e87d6c3e1f08cbcd | [
"MIT"
] | 1 | 2019-05-07T17:10:43.000Z | 2019-05-07T17:10:43.000Z | # 帮助文档
* [简介](main/Summary.md)
* [安装](main/Install.md)
* [升级](main/Upgrade.md)
* [常用命令](main/Commands.md)
* [登录](main/Login.md)
* [常见问题](main/FAQ.md)
* 通用设置
* [管理界面](settings/Service.md)
* [个人资料](settings/Profile.md)
* [登录设置](settings/Login.md)
* [MongoDB](settings/MongoDB.md)
* 代理
* [原理](proxy/Architect.md)
* [添加代理](proxy/CreateProxy.md)
* [域名](proxy/Domain.md)
* [绑定网络地址](proxy/Listen.md)
* [HTTPS](proxy/HTTPS.md)
* [后端服务器](proxy/Backend.md)
* [路径规则](proxy/Location.md)
* [自定义Header](proxy/Header.md)
* [Fastcgi](proxy/Fastcgi.md)
* [重写规则](proxy/Rewrite.md)
* [Websocket](proxy/Websocket.md)
* 访问日志
* 统计
* 缓存
* [内置变量](proxy/Variables.md)
* 前端代理
* [Nginx](proxy/Nginx.md)
<!-- * Apache -->
<!-- * Varnish -->
<!-- * Squid -->
<!-- * HAProxy -->
* Agent
* [Agent概念](agents/Index.md)
* [安装Agent](agents/Install.md)
* [应用（App）](agents/App.md)
<!--* 任务-->
* [监控项](agents/Item.md)
* [阈值](agents/Threshold.md)
* [监控实例-监控进程](agents/examples/Mongo.md)
* [监控实例-监控Nginx](agents/examples/Nginx.md)
* 高级
* [外部监控API](advanced/APIMonitor.md)
* [主机监控项API](advanced/APIMonitorAgentItem.md)
* 集群
* [性能指南](advanced/Performance.md)
* 开发者
* [从源码启动或编译](main/Build.md)
* 插件
* [写一个插件](plugins/Write.md)
* [安装插件](plugins/Install.md)
* [TeaWeb+](plus/Index.md)
* [捐助作者](donate/Index.md) | 25.018182 | 47 | 0.59811 | yue_Hant | 0.751561 |
2c9154dba91819ac13badaf8ff8b7ad6b8ca2e96 | 1,301 | md | Markdown | content/pipeline/kubernetes/syntax/parallelism.md | phil-davis/docs | f3db0b46c949586e50a6323051d33362fb4518de | [
"BlueOak-1.0.0"
] | 151 | 2015-01-30T23:32:00.000Z | 2022-02-20T20:23:46.000Z | content/pipeline/kubernetes/syntax/parallelism.md | phil-davis/docs | f3db0b46c949586e50a6323051d33362fb4518de | [
"BlueOak-1.0.0"
] | 339 | 2015-01-04T05:21:48.000Z | 2022-03-26T07:08:04.000Z | content/pipeline/kubernetes/syntax/parallelism.md | phil-davis/docs | f3db0b46c949586e50a6323051d33362fb4518de | [
"BlueOak-1.0.0"
] | 386 | 2015-01-04T05:08:19.000Z | 2022-03-29T19:05:10.000Z | ---
date: 2000-01-01T00:00:00+00:00
title: Parallelism
author: bradrydzewski
weight: 6
toc: false
description: |
Configure pipeline steps to execute in parallel.
---
Pipeline steps are executed sequentially by default. You can optionally describe your build steps as a [directed acyclic graph](https://en.wikipedia.org/wiki/Directed_acyclic_graph). In the below example we fan-out to execute the first two steps in parallel, and then once complete, we fan-in to execute the final step:
{{< highlight text "linenos=table,hl_lines=23-25" >}}
kind: pipeline
type: kubernetes
name: default
steps:
- name: backend
image: golang
commands:
- go build
- go test
- name: frontend
image: node
commands:
- npm install
- npm test
- name: notify
image: plugins/slack
settings:
webhook:
from_secret: webhook
depends_on:
- frontend
- backend
{{< / highlight >}}
The above example is quite simple, however, you can use this syntax to create very complex execution flows.
<div class="alert">
Note that when you define the dependency graph you must configure dependencies for all pipeline steps.
</div>
<div class="alert">
Note that you can use conditional steps in your dependency graph. The scheduler automatically corrects the dependency graph for skipped steps.
</div>
| 26.02 | 319 | 0.74558 | eng_Latn | 0.992594 |
2c915d6d7312031f9ab1d9e697f4c7134566a967 | 3,400 | md | Markdown | day-2/intermediate_lilypond.md | DaviRaubach/intensive | f2abce0f888f1231d0f8da6f24d41c921ea6aca1 | [
"MIT"
] | null | null | null | day-2/intermediate_lilypond.md | DaviRaubach/intensive | f2abce0f888f1231d0f8da6f24d41c921ea6aca1 | [
"MIT"
] | null | null | null | day-2/intermediate_lilypond.md | DaviRaubach/intensive | f2abce0f888f1231d0f8da6f24d41c921ea6aca1 | [
"MIT"
] | null | null | null | ## Software Preliminaries: Downloads
### Download LilyPond
http://lilypond.org/download.html
### Follow Command Line Installation Instructions (required for Abjad)
Windows http://lilypond.org/windows.html
Mac http://lilypond.org/macos-x.html
Linux http://lilypond.org/unix.html
### Download Frescobaldi
http://frescobaldi.org/download.html
## Conceptual Preliminaries: The Leaf, Container, Spanner, Indicator Model of a Musical Score
Throughout, we will consider a musical score as a hierarchy of containers http://abjad.mbrsi.org/core_concepts/lcsi.html
## Review: Basic Leaves
Pitch Entry http://lilypond.org/doc/v2.19/Documentation/notation-big-page.html#pitches
Rhythm Entry http://lilypond.org/doc/v2.19/Documentation/notation-big-page.html#rhythms
Chord Entry http://lilypond.org/doc/v2.19/Documentation/learning/combining-notes-into-chords
Spacer Rests http://lilypond.org/doc/v2.18/Documentation/notation/writing-rests
## Indicators and Spanners in LilyPond
Markup http://lilypond.org/doc/v2.18/Documentation/learning/adding-text
Dynamics http://lilypond.org/doc/v2.19/Documentation/learning/articulation-and-dynamics#dynamics
Expression http://lilypond.org/doc/v2.18/Documentation/learning/adding-text
Articulations(Staccato/Tenuto/Accent) http://lilypond.org/doc/v2.19/Documentation/learning/articulation-and-dynamics#articulations
Ties http://lilypond.org/doc/v2.16/Documentation/learning/ties-and-slurs.en.html
Slurs http://lilypond.org/doc/v2.16/Documentation/learning/ties-and-slurs.en.html
Beams (be sure you have at least eighth notes in your hello.ly file) http://lilypond.org/doc/v2.18/Documentation/notation/beams
Dynamic Hairpins http://lilypond.org/doc/v2.19/Documentation/learning/articulation-and-dynamics
Tempo change spanners http://lilypond.org/doc/v2.18/Documentation/notation/writing-text (see rit. Example)
Octavization http://lilypond.org/doc/v2.19/Documentation/notation/displaying-pitches#ottava-brackets
Piano pedal markings http://lilypond.org/doc/v2.19/Documentation/notation/piano#piano-pedals
Time Signatures http://lilypond.org/doc/v2.18/Documentation/notation/displaying-rhythms.en.html#time-signature
Lyrics http://lilypond.org/doc/v2.19/Documentation/notation/techniques-specific-to-lyrics
## Containers as Contexts in LilyPond
Contexts Listed and Explained http://lilypond.org/doc/v2.18/Documentation/notation/contexts-explained
Voices and Stem Direction http://lilypond.org/doc/v2.19/Documentation/learning/explicitly-instantiating-voices
Bach chorales for engraving practice https://github.com/Abjad/presentations/blob/master/porto/bachChoralesTwoStaves.pdf
An .ly file to get started https://github.com/Abjad/presentations/blob/master/porto/containers.ly
## Contexts, Engravers, and Tweaks in LilyPond
Engravers Explained http://lilypond.org/doc/v2.18/Documentation/learning/engravers-explained
Adding and Removing Engravers http://lilypond.org/doc/v2.19/Documentation/learning/adding-and-removing-engravers
LilyPond Engravers Reference http://lilypond.org/doc/v2.18/Documentation/internals/engravers-and-performers
Introduction to Tweaks http://lilypond.org/doc/v2.19/Documentation/learning/tweaking-methods
The Override Command http://lilypond.org/doc/v2.18/Documentation/notation/the-override-command
So What?: Parametric Cello Example https://github.com/Abjad/intensive/blob/master/day-4/cello-refactored/cello.ly
| 43.589744 | 130 | 0.813235 | yue_Hant | 0.670543 |
2c916fb1e9e5320e186d85e735978e294c1d6893 | 2,508 | md | Markdown | avoiding_common_attacks.md | zirgudaga/eco-capt | d6e10004e1a8c43c493ec214b992c256f47dc1e2 | [
"MIT"
] | 4 | 2021-04-21T08:49:51.000Z | 2022-01-01T11:29:16.000Z | avoiding_common_attacks.md | zirgudaga/eco-capt | d6e10004e1a8c43c493ec214b992c256f47dc1e2 | [
"MIT"
] | null | null | null | avoiding_common_attacks.md | zirgudaga/eco-capt | d6e10004e1a8c43c493ec214b992c256f47dc1e2 | [
"MIT"
] | 6 | 2021-04-09T07:37:46.000Z | 2021-05-06T09:23:07.000Z | # avoiding_common_attacks.md
- [x] Re-Entrancy
- [x] Arithmetic Overflow and Underflow
- [x] Accessing Private Data
📌 Security checks currently in place :
## Re-Entrancy
- No possible re-entrancy because we do not use any outside smart contract. **LedgerContract** address is displayed when deployed and will not be modified.
- **isOwner** is used everystep of the way as regard to keep contract functions.
- Sets of **modifier** are in place to limit the access to certain functionalities.
**Toggle Status** and **Id Checks** are in place:
```modifier isContractActive() {
require(_myConfig.isActive, "Contract off line");
_;
}
modifier isServiceActive(uint _serviceId) {
require(_serviceId < _serviceIdCounter.current(), "Service not exist");
require(_services[_serviceId].isActive, "Service off line");
_;
}
modifier isRulesActive(uint _ruleId) {
require(_ruleId < _ruleIdCounter.current(), "Rules not exist");
require(_serviceRules[_ruleId].isActive, "Rules off line");
_;
}
modifier onlyCustomer() {
require (_myConfig.customerAddress == msg.sender || owner() == msg.sender, "Access denied");
_;
}
modifier onlyBridge(uint _serviceId) {
require (_services[_serviceId].bridgeAddress == msg.sender || owner() == msg.sender, "Access denied");
_;
}
modifier onlyTechMaster(uint _serviceId) {
require (_services[_serviceId].techMasterAddress == msg.sender || owner() == msg.sender, "Access denied");
_;
}
modifier onlyLegislator(uint _serviceId) {
require (_services[_serviceId].legislatorAddress == msg.sender || owner() == msg.sender, "Access denied");
_;
}```
## Arithmetic Overflow and Underflow
The 2 cases where we use arithmetic operations are for index implemntation by mapping via the Counter.sol class from the **OpenZepellin** which protects himself from underflow. We no longer use SaFeMath from @openzeppelin since we have upgraded Solidity to 0.8 which handles this natively.
## Accessing Private Data
Our solution is based on Open Data, there are no sensible data, everything is public.
# Unnecessary security measures
- [ ] Self Destruct
- [ ] Delegatecall
- [ ] Source of Randomness
- [ ] Denial of Service
- [ ] Phishing with tx.origin
- [ ] Hiding Malicious Code with External Contract
- [ ] Honeypot
- [ ] Front Running
- [ ] Block Timestamp Manipulation
- [ ] Signature Replay
| 33.44 | 289 | 0.688596 | eng_Latn | 0.923662 |
2c9331d9f8e7d63d8f84b8639ffb5b4807539b83 | 1,628 | md | Markdown | windows-driver-docs-pr/print/configuring-a-port.md | i35010u/windows-driver-docs.zh-cn | e97bfd9ab066a578d9178313f802653570e21e7d | [
"CC-BY-4.0",
"MIT"
] | 1 | 2021-02-04T01:49:58.000Z | 2021-02-04T01:49:58.000Z | windows-driver-docs-pr/print/configuring-a-port.md | i35010u/windows-driver-docs.zh-cn | e97bfd9ab066a578d9178313f802653570e21e7d | [
"CC-BY-4.0",
"MIT"
] | null | null | null | windows-driver-docs-pr/print/configuring-a-port.md | i35010u/windows-driver-docs.zh-cn | e97bfd9ab066a578d9178313f802653570e21e7d | [
"CC-BY-4.0",
"MIT"
] | null | null | null | ---
title: 配置端口
description: 配置端口
keywords:
- 端口管理 WDK 打印，配置端口
- ConfigurePort
ms.date: 04/20/2017
ms.localizationpriority: medium
ms.openlocfilehash: 9fbf7c1a8ebc16d9dc8df4300b60efdd389129d9
ms.sourcegitcommit: 418e6617e2a695c9cb4b37b5b60e264760858acd
ms.translationtype: MT
ms.contentlocale: zh-CN
ms.lasthandoff: 12/07/2020
ms.locfileid: "96797579"
---
# <a name="configuring-a-port"></a>配置端口
配置端口包括为先前添加的端口修改端口监视器服务器 DLL 的存储配置信息。
当应用程序调用打印后台处理程序的 [**ConfigurePort**](/previous-versions/ff546286(v=vs.85)) 函数时 (Microsoft Windows SDK 文档) 中所述， **ConfigurePort** 函数会调用相应端口监视器的端口监视器 UI DLL 中包含的 [**ConfigurePortUI**](/windows-hardware/drivers/ddi/winsplp/nf-winsplp-configureportui) 函数。
端口监视器 UI DLL 的 [**ConfigurePortUI**](/windows-hardware/drivers/ddi/winsplp/nf-winsplp-configureportui) 函数应执行以下操作：
1. 调用打印后台处理程序的 OpenPrinter 函数 (Windows SDK 文档) 中所述，这将导致调用端口监视器服务器 DLL 中的 [**XcvOpenPort**](/windows-hardware/drivers/ddi/winsplp/nf-winsplp-xcvopenport) 函数。
2. 一次或多次调用打印后台处理程序的 [**XcvData**](/previous-versions/ff564255(v=vs.85)) 函数，以便在 UI dll 和服务器 dll 之间传输配置信息。 **XcvData** 函数调用服务器 DLL 的 [**XcvDataPort**](/windows-hardware/drivers/ddi/winsplp/nf-winsplp-xcvdataport)函数。 [**ConfigurePortUI**](/windows-hardware/drivers/ddi/winsplp/nf-winsplp-configureportui)函数通常通过显示对话框从用户那里获取配置信息。
3. 调用打印后台处理程序的 ClosePrinter 函数 (Windows SDK 文档) 中所述，这将导致调用端口监视器服务器 DLL 中的 [**XcvClosePort**](/windows-hardware/drivers/ddi/winsplp/nf-winsplp-xcvcloseport) 函数。
有关这些操作的详细信息，请参阅 [**ConfigurePortUI**](/windows-hardware/drivers/ddi/winsplp/nf-winsplp-configureportui)的说明。 另请参阅 [存储端口配置信息](storing-port-configuration-information.md)。
| 42.842105 | 325 | 0.788084 | yue_Hant | 0.60845 |
2c9351409275afc1d721ac5507364bbafde3b7f6 | 2,202 | md | Markdown | hugo/themes/minimal-bootstrap-hugo-theme/exampleSite/content/post/use-snap-to-install-the-hugo-edge-version-on-fedora-and-ubuntu.md | wwlib/react-static-example | cc440f40d6087430129c853b7668da3679aa3a1f | [
"MIT"
] | null | null | null | hugo/themes/minimal-bootstrap-hugo-theme/exampleSite/content/post/use-snap-to-install-the-hugo-edge-version-on-fedora-and-ubuntu.md | wwlib/react-static-example | cc440f40d6087430129c853b7668da3679aa3a1f | [
"MIT"
] | 3 | 2021-03-09T13:06:28.000Z | 2021-09-01T19:46:55.000Z | hugo/themes/minimal-bootstrap-hugo-theme/exampleSite/content/post/use-snap-to-install-the-hugo-edge-version-on-fedora-and-ubuntu.md | wwlib/react-static-example | cc440f40d6087430129c853b7668da3679aa3a1f | [
"MIT"
] | null | null | null | ---
title: "Use Snap to install the Hugo edge version on Fedora and Ubuntu"
date: 2018-10-26T12:59:51-05:00
publishdate: 2018-10-26
lastmod: 2018-10-26
draft: false
aliases:
- /use-snap-to-install-the-hugo-edge-version-on-fedora/
---
If you are using the Fedora or Ubuntu Linux distributions -- I'm currently on Fedora 28 -- and would like to [help test the latest development version of Hugo](https://discourse.gohugo.io/t/help-test-upcoming-hugo-0-50/14880), or if you just want to be on the bleeding-edge of things, this post is for you.
## Fedora-only steps
To get started, [install Snap on Fedora](https://docs.snapcraft.io/installing-snap-on-fedora/6755):
```
sudo dnf install snapd
```
Add the [Snap directory](https://docs.snapcraft.io/commands-and-aliases/3950) to your `PATH` by adding this line to your `~/.bashrc` file. Then restart your terminal to pick up the change:
```
export PATH="$PATH:/var/lib/snapd/snap/bin"
```
## Ubuntu-only steps
Ubuntu 16.04 and above come with [Snap already installed](https://docs.snapcraft.io/installing-snap-on-ubuntu/6740). If you're using an older Ubuntu version, install Snap by running:
```
sudo apt update && sudo apt install snapd
```
Check if the Snap directory is on your `PATH` by listing each entry:
```
echo $PATH | tr ':' '\n'
```
If you don't see `/snap/bin` listed, then add this line to your `~/.bashrc` file. Then restart your terminal to pick up the change:
```
export PATH="$PATH:/snap/bin"
```
## Install Hugo
See which Snap channels are available for Hugo:
```
snap info hugo
```
Install Hugo from the edge channel:
```
sudo snap install hugo --channel=edge
```
Or, if you prefer Hugo Extended -- which has the [Hugo Pipes](https://gohugo.io/hugo-pipes/) feature -- install it from the extended edge channel:
```
sudo snap install hugo --channel=extended/edge
```
Lastly, confirm the location and version of Hugo that was intalled:
```
which hugo && hugo version
```
Happy testing :)
## Update or remove Hugo
Snaps are [updated automatically](https://docs.snapcraft.io/keeping-snaps-up-to-date/7022). To manually update Hugo:
```
sudo snap refresh hugo
```
To remove Hugo:
```
sudo snap remove hugo
``` | 25.310345 | 307 | 0.717075 | eng_Latn | 0.939829 |
2c94e7e55abd1901e6546665a03d21748e504b04 | 18,020 | md | Markdown | articles/security-center/security-center-just-in-time.md | gschrijvers/azure-docs.nl-nl | e46af0b9c1e4bb7cb8088835a8104c5d972bfb78 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | articles/security-center/security-center-just-in-time.md | gschrijvers/azure-docs.nl-nl | e46af0b9c1e4bb7cb8088835a8104c5d972bfb78 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | articles/security-center/security-center-just-in-time.md | gschrijvers/azure-docs.nl-nl | e46af0b9c1e4bb7cb8088835a8104c5d972bfb78 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | ---
title: Just-in-time-toegang tot virtuele machines in Azure Security Center | Microsoft Docs
description: In dit document wordt gedemonstreerd hoe just-in-time-VM-toegang in Azure Security Center u de toegang tot uw virtuele Azure-machines kunt beheren.
services: security-center
author: memildin
manager: rkarlin
ms.service: security-center
ms.topic: conceptual
ms.date: 02/25/2020
ms.author: memildin
ms.openlocfilehash: cc4e267c6912b8938db1ba5497a27f9c0026bd79
ms.sourcegitcommit: 849bb1729b89d075eed579aa36395bf4d29f3bd9
ms.translationtype: MT
ms.contentlocale: nl-NL
ms.lasthandoff: 04/28/2020
ms.locfileid: "80887330"
---
# <a name="secure-your-management-ports-with-just-in-time-access"></a>Beveilig uw beheer poorten met Just-in-time-toegang
Als u zich in de Standard-prijs categorie van Security Center bevindt (Zie [prijzen](/azure/security-center/security-center-pricing)), kunt u inkomend verkeer naar uw Azure-vm's vergren delen met Just-in-time-toegang (VM) voor virtuele machines. Dit vermindert de bloot stelling aan aanvallen en biedt zo eenvoudig toegang om verbinding te maken met Vm's wanneer dat nodig is.
> [!NOTE]
> Security Center just-in-time-VM-toegang ondersteunt momenteel alleen Vm's die via Azure Resource Manager zijn geïmplementeerd. Zie [Azure Resource Manager vs. klassieke implementatie](../azure-resource-manager/management/deployment-models.md)voor meer informatie over het klassieke en Resource Manager-implementatie model.
[!INCLUDE [security-center-jit-description](../../includes/security-center-jit-description.md)]
## <a name="configure-jit-on-a-vm"></a>JIT configureren op een virtuele machine
Er zijn drie manieren om een JIT-beleid te configureren op een virtuele machine:
- [JIT-toegang configureren in Azure Security Center](#jit-asc)
- [JIT-toegang configureren op een Azure VM-pagina](#jit-vm)
- [Een JIT-beleid op een virtuele machine via een programma configureren](#jit-program)
## <a name="configure-jit-in-azure-security-center"></a>JIT configureren in Azure Security Center
Vanuit Security Center kunt u een JIT-beleid configureren en toegang aanvragen tot een virtuele machine met behulp van een JIT-beleid
### <a name="configure-jit-access-on-a-vm-in-security-center"></a>JIT-toegang configureren op een virtuele machine in Security Center<a name="jit-asc"></a>
1. Open het dashboard van **Security Center**.
1. Selecteer in het linkerdeel venster **just-in-time-VM-toegang**.
Het venster **just-in-time-VM-toegang** wordt geopend en toont informatie over de status van uw vm's:
- **Geconfigureerd** : vm's die zijn geconfigureerd voor ondersteuning van just-in-time-VM-toegang. De gegevens die worden weer gegeven, zijn de afgelopen week en bevatten voor elke VM het aantal goedgekeurde aanvragen, de datum en tijd van laatste toegang en de laatste gebruiker.
- **Aanbevolen** : vm's die just-in-time-VM-toegang kunnen ondersteunen, maar die niet zijn geconfigureerd voor. U wordt aangeraden just-in-time-VM-toegangs beheer in te scha kelen voor deze Vm's.
- **Geen aanbeveling**: redenen waarom een VM mogelijk niet wordt aanbevolen zijn:
- Ontbrekende NSG: voor de just-in-time-oplossing moet een NSG aanwezig zijn.
- Klassieke VM-Security Center just-in-time-VM-toegang ondersteunt momenteel alleen Vm's die via Azure Resource Manager zijn geïmplementeerd. Een klassieke implementatie wordt niet ondersteund door de just-in-time-oplossing.
- Andere-een VM bevindt zich in deze categorie als de just-in-time-oplossing is uitgeschakeld in het beveiligings beleid van het abonnement of de resource groep, of als op de virtuele machine een openbaar IP-adres ontbreekt en er geen NSG aanwezig is.
1. Selecteer het tabblad **Aanbevolen** .
1. Onder **virtuele machine**klikt u op de virtuele machines die u wilt inschakelen. Hiermee wordt een vinkje bij een virtuele machine geplaatst.
1. Klik op **JIT inschakelen op vm's**. Er wordt een deel venster geopend met de standaard poorten die worden aanbevolen door Azure Security Center:
- 22-SSH
- 3389-RDP
- 5985-WinRM
- 5986-WinRM
1. U kunt desgewenst aangepaste poorten toevoegen aan de lijst:
1. Klik op **Add**. Het venster **poort configuratie toevoegen** wordt geopend.
1. Voor elke poort die u wilt configureren, zowel standaard als aangepast, kunt u de volgende instellingen aanpassen:
- **Protocol type**: het protocol dat is toegestaan op deze poort wanneer een aanvraag wordt goedgekeurd.
- **Toegestane IP-adressen van bron**-de IP-bereiken die op deze poort zijn toegestaan wanneer een aanvraag wordt goedgekeurd.
- **Maximale aanvraag tijd**: de maximale tijd venster gedurende welke een specifieke poort kan worden geopend.
1. Klik op **OK**.
1. Klik op **Opslaan**.
> [!NOTE]
>Wanneer JIT-VM-toegang is ingeschakeld voor een virtuele machine, maakt Azure Security Center de regels ' alle binnenkomend verkeer weigeren ' voor de geselecteerde poorten in de netwerk beveiligings groepen die zijn gekoppeld en Azure Firewall. Als er andere regels zijn gemaakt voor de geselecteerde poorten, hebben de bestaande regels voor rang op de nieuwe regels ' alle inkomende verkeer weigeren '. Als er geen bestaande regels zijn op de geselecteerde poorten, hebben de nieuwe regels voor het weigeren van binnenkomend verkeer de hoogste prioriteit in de netwerk beveiligings groepen en de Azure Firewall.
## <a name="request-jit-access-via-security-center"></a>JIT-toegang aanvragen via Security Center
Om toegang te vragen tot een virtuele machine via Security Center:
1. Onder **just-in-time-VM-toegang**selecteert u het tabblad **geconfigureerd** .
1. Onder **virtuele machine**klikt u op de virtuele machines waarvoor u toegang wilt aanvragen. Hiermee wordt een vinkje naast de virtuele machine geplaatst.
- Het pictogram in de kolom **verbindings Details** geeft aan of JIT is ingeschakeld op de NSG of FW. Als de functie is ingeschakeld op beide, wordt alleen het pictogram Firewall weer gegeven.
- In de kolom **verbindings Details** vindt u de informatie die nodig is om verbinding te maken met de virtuele machine en de bijbehorende open poorten.
1. Klik op **toegang aanvragen**. Het venster **toegang tot aanvragen** wordt geopend.
1. Configureer onder **toegang aanvragen**voor elke virtuele machine de poorten die u wilt openen en de bron-IP-adressen waarop de poort is geopend en het tijd venster waarvoor de poort wordt geopend. Het is alleen mogelijk om toegang aan te vragen voor de poorten die zijn geconfigureerd in het just-in-time-beleid. Elke poort heeft een Maxi maal toegestane tijd die is afgeleid van het just-in-time-beleid.
1. Klik op **poorten openen**.
> [!NOTE]
> Als een gebruiker die toegang aanvraagt zich achter een proxy bevindt, werkt de optie **Mijn IP** mogelijk niet. Mogelijk moet u het volledige IP-adres bereik van de organisatie definiëren.
## <a name="edit-a-jit-access-policy-via-security-center"></a>Een JIT-toegangs beleid bewerken via Security Center
U kunt het bestaande just-in-time-beleid van een virtuele machine wijzigen door een nieuwe poort toe te voegen en te configureren voor de beveiliging van die virtuele machine of door een andere instelling te wijzigen die betrekking heeft op een reeds beveiligde poort.
Een bestaande just-in-time-beleid van een virtuele machine bewerken:
1. Op het tabblad **geconfigureerd** , onder **vm's**, selecteert u een virtuele machine waaraan u een poort wilt toevoegen door te klikken op de drie puntjes in de rij voor die virtuele machine.
1. Selecteer **bewerken**.
1. Onder **JIT VM-toegangs configuratie**kunt u de bestaande instellingen van een reeds beveiligde poort bewerken of een nieuwe aangepaste poort toevoegen.
## <a name="audit-jit-access-activity-in-security-center"></a>JIT-toegangs activiteit controleren in Security Center
U kunt inzicht krijgen in VM-activiteiten met zoeken in Logboeken. Logboeken weer geven:
1. Onder **just-in-time-VM-toegang**selecteert u het tabblad **geconfigureerd** .
2. Onder **vm's**selecteert u een virtuele machine om informatie weer te geven over door te klikken op de drie puntjes in de rij voor die VM en selecteert u **activiteiten logboek** in het menu. Het **activiteiten logboek** wordt geopend.
Het **activiteiten logboek** bevat een gefilterde weer gave van eerdere bewerkingen voor die virtuele machine, samen met tijd, datum en abonnement.
U kunt de logboek gegevens downloaden door **hier te klikken om alle items te downloaden als CSV**-bestand.
Wijzig de filters en klik op **Toep assen** om een zoek opdracht en logboek te maken.
## <a name="configure-jit-access-from-an-azure-vms-page"></a>JIT-toegang vanaf een Azure VM-pagina configureren<a name="jit-vm"></a>
Voor uw gemak kunt u vanuit de pagina van de virtuele machine in Security Center verbinding maken met een virtuele machine met behulp van JIT.
### <a name="configure-jit-access-on-a-vm-via-the-azure-vm-page"></a>JIT-toegang op een virtuele machine configureren via de Azure VM-pagina
Als u de just-in-time-toegang op uw Vm's eenvoudig wilt implementeren, kunt u een virtuele machine zo instellen dat alleen just-in-time-toegang rechtstreeks vanuit de virtuele machine wordt toegestaan.
1. Zoek in het [Azure Portal](https://ms.portal.azure.com)naar **virtuele machines**en selecteer deze.
2. Selecteer de virtuele machine die u wilt beperken tot just-in-time-toegang.
3. Selecteer in het menu **configuratie**.
4. Onder **just-in-time-toegang**selecteert u **just-in-time inschakelen**.
Dit maakt just-in-time-toegang voor de virtuele machine mogelijk met de volgende instellingen:
- Windows-servers:
- RDP-poort 3389
- Drie uur voor Maxi maal toegestane toegang
- Toegestane IP-adressen van bron worden ingesteld op een
- Linux-servers:
- SSH-poort 22
- Drie uur voor Maxi maal toegestane toegang
- Toegestane IP-adressen van bron worden ingesteld op een
Als een virtuele machine al just-in-time is ingeschakeld, kunt u, wanneer u naar de pagina configuratie gaat, zien dat just-in-time is ingeschakeld en kunt u de koppeling gebruiken om het beleid in Azure Security Center te openen om de instellingen weer te geven en te wijzigen.
### <a name="request-jit-access-to-a-vm-via-an-azure-vms-page"></a>JIT-toegang aanvragen tot een virtuele machine via de pagina van een Azure-VM
Wanneer u in de Azure Portal probeert verbinding te maken met een virtuele machine, controleert Azure of u een just-in-time-toegangs beleid op die VM hebt geconfigureerd.
- Als u een JIT-beleid op de virtuele machine hebt geconfigureerd, kunt u op **toegang aanvragen** klikken om toegang te verlenen volgens het JIT-beleid dat is ingesteld voor de virtuele machine.
>
Toegang is aangevraagd met de volgende standaard parameters:
- **bron-IP**: ' any ' (*) (kan niet worden gewijzigd)
- **tijds bereik**: drie uur (kan niet worden gewijzigd) <!--Isn't this set in the policy-->
- **poort nummer** RDP-poort 3389 voor Windows/poort 22 voor Linux (kan worden gewijzigd)
> [!NOTE]
> Nadat een aanvraag is goedgekeurd voor een virtuele machine die wordt beveiligd door Azure Firewall, geeft Security Center de gebruiker de juiste verbindings gegevens (de poort toewijzing van de tabel DNAT) die moet worden gebruikt om verbinding te maken met de virtuele machine.
- Als u geen JIT hebt geconfigureerd op een virtuele machine, wordt u gevraagd om een JIT-beleid te configureren.
## <a name="configure-a-jit-policy-on-a-vm-programmatically"></a>Een JIT-beleid op een virtuele machine via een programma configureren<a name="jit-program"></a>
U kunt just-in-time instellen en gebruiken via REST Api's en via Power shell.
### <a name="jit-vm-access-via-rest-apis"></a>JIT-VM-toegang via REST-Api's
De just-in-time VM-toegangs functie kan worden gebruikt via de Azure Security Center-API. U kunt informatie krijgen over geconfigureerde Vm's, nieuwe toevoegen, toegang aanvragen tot een virtuele machine en meer via deze API. Zie [JIT-netwerk toegangs beleid](https://docs.microsoft.com/rest/api/securitycenter/jitnetworkaccesspolicies)voor meer informatie over de just-in-time-rest API.
### <a name="jit-vm-access-via-powershell"></a>JIT-VM-toegang via Power shell
Als u de just-in-time-toegang tot een VM wilt gebruiken via Power shell, gebruikt u de officiële Azure Security Center `Set-AzJitNetworkAccessPolicy`Power shell-cmdlets en specifiek.
In het volgende voor beeld wordt een just-in-time-VM-toegangs beleid ingesteld op een specifieke virtuele machine en worden de volgende opties ingesteld:
1. Sluit poort 22 en 3389.
2. Stel een maximum tijd venster van drie uur in voor elke periode zodat deze kan worden geopend per goedgekeurde aanvraag.
3. Hiermee staat u toe dat de gebruiker die toegang aanvraagt om de bron-IP-adressen te beheren en de gebruiker in staat stelt een geslaagde sessie te maken op een goedgekeurde just-in-time-toegangs aanvraag.
Voer de volgende handelingen uit in Power shell om dit te bewerkstelligen:
1. Wijs een variabele toe die het just-in-time-VM-toegangs beleid voor een virtuele machine bevat:
$JitPolicy = (@ {id = "/subscriptions/SUBSCRIPTIONID/resourceGroups/RESOURCEGROUP/providers/Microsoft.Compute/virtualMachines/VMNAME" poorten = (@ {Number = 22; Protocol = "\*"; allowedSourceAddressPrefix = @ ("\*"); maxRequestAccessDuration = "PT3H"}, @ {Number = 3389; Protocol = "\*"; allowedSourceAddressPrefix = @ ("\*"); maxRequestAccessDuration = "PT3H"})})
2. Voeg het just-in-time-VM-toegangs beleid in op een matrix:
$JitPolicyArr = @ ($JitPolicy)
3. Configureer het just-in-time-toegangs beleid voor de virtuele machine op de geselecteerde VM:
Set-AzJitNetworkAccessPolicy-type "Basic"-Location "locatie"-name ""-ResourceGroupName "RESOURCEGROUP"-VirtualMachine $JitPolicyArr
### <a name="request-access-to-a-vm-via-powershell"></a>Toegang aanvragen tot een virtuele machine via Power shell
In het volgende voor beeld ziet u een just-in-time-toegangs aanvraag voor een virtuele machine naar een specifieke virtuele machine waarvoor poort 22 is aangevraagd voor het openen van een specifiek IP-adres en voor een specifieke hoeveelheid tijd:
Voer het volgende uit in Power shell:
1. De toegangs eigenschappen van de VM-aanvraag configureren
$JitPolicyVm 1 = (@ {id = "/SUBSCRIPTIONID/resourceGroups/RESOURCEGROUP/providers/Microsoft.Compute/virtualMachines/VMNAME" poorten = (@ {Number = 22; endTimeUtc = "2018-09-17T17:00:00.3658798 Z"; allowedSourceAddressPrefix = @ ("IPV4ADDRESS")})})
2. De para meters voor de VM-toegangs aanvraag invoegen in een matrix:
$JitPolicyArr = @ ($JitPolicyVm 1)
3. De aanvraag toegang verzenden (gebruik de resource-ID die u in stap 1 hebt ontvangen)
Start-AzJitNetworkAccessPolicy-ResourceId "/subscriptions/SUBSCRIPTIONID/resourceGroups/RESOURCEGROUP/providers/Microsoft.Security/locations/LOCATION/jitNetworkAccessPolicies/default"-VirtualMachine $JitPolicyArr
Zie de [Power shell-cmdlet-documentatie](https://docs.microsoft.com/powershell/scripting/developer/cmdlet/cmdlet-overview)voor meer informatie.
## <a name="automatic-cleanup-of-redundant-jit-rules"></a>Automatisch opschonen van redundante JIT-regels
Telkens wanneer u een JIT-beleid bijwerkt, wordt automatisch een Cleanup-hulp programma uitgevoerd om de geldigheid van de volledige ruleset te controleren. Het hulp programma zoekt naar verschillen tussen regels in uw beleid en regels in het NSG. Als het hulp programma voor opschonen een niet-overeenkomend item detecteert, wordt de oorzaak bepaald en, wanneer het veilig is om dit te doen, verwijdert u ingebouwde regels die niet meer nodig zijn. De verruiming verwijdert nooit regels die u hebt gemaakt.
Voor beelden van scenario's waarin de Removal een ingebouwde regel kan verwijderen:
- Wanneer er twee regels met identieke definities bestaan en een hogere prioriteit heeft dan de andere, (wat betekent dat de regel met een lagere prioriteit nooit wordt gebruikt)
- Wanneer een regel beschrijving de naam bevat van een virtuele machine die niet overeenkomt met de doel-IP in de regel
## <a name="next-steps"></a>Volgende stappen
In dit artikel hebt u geleerd hoe u met Just-in-time-VM-toegang in Security Center de toegang tot uw virtuele Azure-machines kunt beheren.
Zie de volgende onderwerpen voor meer informatie over Security Center:
- Met de module Microsoft Learn [worden uw servers en virtuele machines beschermd tegen brute-force-aanvallen en schadelijke software met Azure Security Center](https://docs.microsoft.com/learn/modules/secure-vms-with-azure-security-center/)
- [Beveiligings beleid instellen](tutorial-security-policy.md) : informatie over het configureren van beveiligings beleid voor uw Azure-abonnementen en-resource groepen.
- [Aanbevelingen voor beveiliging beheren](security-center-recommendations.md) : Ontdek hoe u met aanbevelingen uw Azure-resources kunt beveiligen.
- [Bewaking van beveiligings status](security-center-monitoring.md) : Leer hoe u de status van uw Azure-resources kunt bewaken.
| 68.778626 | 614 | 0.772364 | nld_Latn | 0.998603 |
2c94f9904f23a56632258f9e7d0cc4603f5913fd | 2,134 | md | Markdown | README.md | zpc888/whole-test-gradle-plugin | 536cb245531910114bbdd581b03b8f516b3557cc | [
"Apache-2.0"
] | 2 | 2020-02-25T15:33:34.000Z | 2022-03-16T00:42:25.000Z | README.md | zpc888/whole-test-gradle-plugin | 536cb245531910114bbdd581b03b8f516b3557cc | [
"Apache-2.0"
] | null | null | null | README.md | zpc888/whole-test-gradle-plugin | 536cb245531910114bbdd581b03b8f516b3557cc | [
"Apache-2.0"
] | null | null | null | # whole-test-gradle-plugin
Unit test helps only at component level, at high level, there are needs to do test multiple
components, or per functional set, or end to end by using on-demand test docker containers.
To test them, we need create different types of tests, such as integrationTest, functionalTests,
performanceTest, dockerTest, etc.
These kinds of tests may fail often due to data out of date or function spec changing, their failure
should not block deployable artifact output, in some cases they may run after deploying build artifacts.
This plugin is to provide the ability to have integrationTest, functionalTest, performanceTest
under different folders, run after unit-test phase.
To use this plugin, please see: https://plugins.gradle.org/plugin/com.prot.wholetest
In short, for single project with gradle version greater than 2.1 and less than 4.0, using:
```gradle
plugins {
id "com.prot.wholetest" version "0.2" // for gradle 4.0 -
// id "com.prot.wholetest" version "4.0" // for gradle version 4.0 or 4.0+
}
```
For multi-project application, at root project, using:
```gradle
plugins {
id "com.prot.wholetest" version "0.2" apply false // for gradle 4.0 -
// id "com.prot.wholetest" version "4.0" apply false // for gradle version 4.0 or 4.0+
}
```
and then:
```gradle
allprojects {
apply plugin 'com.prot.wholetest'
}
```
or (if only want to run for all sub-projects)
```gradle
subprojects {
apply plugin 'com.prot.wholetest'
}
```
or (if only want to run for projects whose name starts with 'xyz')
```gradle
configure( allprojects.findAll { it.name.startsWith("xyz") } ) {
apply plugin 'com.prot.wholetest'
}
```
or (another way)
```gradle
allprojects { prj ->
if (prj.name.startsWith("xyz")) {
apply plugin 'com.prot.wholetest'
}
}
```
Note: it only provides integrationTest with src/integTest/java and src/integTest/resources
sourceSets for now. It can be easily expanded to different languages such as groovy, scala,
kotlin with different kinds of high level tests, such as performanceTest with
src/perfTest/java and src/perfTest/resources.
| 31.850746 | 104 | 0.731022 | eng_Latn | 0.988423 |
2c95c9b0400f7511f6ff2e7a991161235475b1e0 | 15 | md | Markdown | README.md | wuliaozhiren5/WWCSpec | ce5c5eb8cca5799a64f4a27ea9f0b646398b8258 | [
"MIT"
] | null | null | null | README.md | wuliaozhiren5/WWCSpec | ce5c5eb8cca5799a64f4a27ea9f0b646398b8258 | [
"MIT"
] | null | null | null | README.md | wuliaozhiren5/WWCSpec | ce5c5eb8cca5799a64f4a27ea9f0b646398b8258 | [
"MIT"
] | null | null | null | # WWCSpec
Spec
| 5 | 9 | 0.733333 | epo_Latn | 0.178092 |
2c95e73fb5ffc999c33cfd3fa515b43c57fcab56 | 1,767 | md | Markdown | Notes.md | jordaninthewind/succulence-fis-project-with-js-frontend | 47bba59ae6a346594c65c047ddc9d36a9e816919 | [
"MIT"
] | null | null | null | Notes.md | jordaninthewind/succulence-fis-project-with-js-frontend | 47bba59ae6a346594c65c047ddc9d36a9e816919 | [
"MIT"
] | null | null | null | Notes.md | jordaninthewind/succulence-fis-project-with-js-frontend | 47bba59ae6a346594c65c047ddc9d36a9e816919 | [
"MIT"
] | null | null | null | Notes during assessment:
- Refer URL in Partial
----------------------------------------------------------------------------------------------------------------------------
- Start with ability to select collection plant and draw association from there.
- Later add ability to make new plant that has association in controller (or restrict to only admin flow)
- # work in belongs to that allows plants through garden_plants (User model)
- Add authorization manually
A user is able to make gardens.
- Should be able to edit gardens and garden_plants in gardens
A garden can have plants associated with it.
- A garden should be able to make a new plant and associate the plant with itself
- A garden is able to delete plants
A plant can only belong to one garden.
First Phase
When a user logs in, they are presented with an index page that shows their gardens and an option to make a new garden. By clicking on the garden link, they will be shown details about the garden, including any garden_plants that are present. There is also the ability to add a plant to a garden.
---
Second Phase
Plants have a time period that they are to be watered during, X, when the timestamp and the current time are greater than X number of days, an overdue reminder is updated on the page. By clicking on the button 'watered', the timestamp is updated to current time and the timer is restarted.
---
Big Details
X - Implement garden_plants join table to enable plants as single entries
X - Add User Logic
- Add Omniauth with new instructions from Lab
X - Add more information to views for UI flow
- Begin to work in control flow and authentication/authorization
Little Details
- Add time formatting for views
V2 Ideas
- Add regions for dynamic watering schedules | 38.413043 | 296 | 0.724392 | eng_Latn | 0.999679 |
2c963e72f35ff7c3c3d2664e6cc90dbb3be8697a | 5,954 | md | Markdown | README.md | julianschick/splitflap | 72ed6caeba0f04e281b3dea683889891612d04a6 | [
"MIT"
] | 2 | 2019-08-23T18:32:20.000Z | 2019-10-24T06:19:24.000Z | README.md | julianschick/fallblatt-schematics-ep3 | 72ed6caeba0f04e281b3dea683889891612d04a6 | [
"MIT"
] | null | null | null | README.md | julianschick/fallblatt-schematics-ep3 | 72ed6caeba0f04e281b3dea683889891612d04a6 | [
"MIT"
] | null | null | null | # Fallblattanzeiger der Deutschen Bahn
Die Deutsche Bahn verwendete lange Zeit standardisierte Fallblattanzeigemodule mit Platinen, die mit *MANTronic* beschriftet sind, also vermutlich von der Firma MAN hergestellt wurden.
Möchte man diese alten Module wieder zum klappern bringen, so hat man grundsätzlich erstmal zwei Möglichkeiten. Die Module wurden offenbar über eine RS485-Schnittstelle angesteuert. Das Protokoll ist vermutlich ein Protokoll ähnlich dem CAN-Bus. Meine gründliche Recherche ergab allerdings keine Quellen im Internet, denen bekannt ist, wie dieses Protokoll genau aussieht. Diese Möglichkeit ist daher eher schwierig.
Eine andere Möglichkeit besteht darin, den zentralen ZiLOG-Microcontroller auf der Platine durch einen eigenen Microcontroller zu ersetzen. Ich habe zu diesem Zweck den ZiLOG-Chip von der Platine geschnitten. Praktischerweise sind auf der Platine nicht nur die SMD-Lötpads für den ZiLOG-Chip, sondern auch etwas größere Pads im DIP-Raster, an die man sehr gut Kabel anlöten kann. Vermutlich ein überbleibsel von älteren Platinenversionen, bei denen ein größerer Microcontroller verwendet wurde.
Mit einer Kombination aus eigener Intuition und Bestätigung durch die Schaltpläne dieses [Hackaday-Projekts](https://hackaday.io/project/9070-fallblattfahrzielanzeige-of-s-bahn-berlin) war es nicht schwer, die Pinbelegung des ZiLOG-Controllers zu ermitteln und so herauszufinden, welche Pins angesteuert bzw. ausgelesen werden müssen. Weiter unten habe ich das mit einer Skizze und einem Foto dokumentiert.
Gemäß der Einteilung im [Wikipedia-Artikel](https://de.wikipedia.org/wiki/Fallblattanzeige) in die vom Aufbau her zu unterscheidenden Epochen 1 bis 4 fällt diese Anzeige in die Epoche 3.
## Funktionsweise
Die Funktionsweise des Fallblattmoduls ist gar nicht so kompliziert. Die Blätter sitzen auf einer Welle die über ein Getriebe von einem Synchronmotor (Berger Lahr RSM 42/12 NG) angetrieben wird, der tatsächlich auch heute noch erhältlich ist ([Datenblatt](https://www.abi.nl/assets/uploads/Downloads/Aandrijvingen/Kleine%20vertragingsmotoren/Synchroonmotoren/Catalogus_RSM_D.pdf)).
Damit der Motor weiß, wann er anhalten soll, sind zwei Infrarot-Transmitter mit Photodioden als Sensoren verbaut. Ein Sensor erzeugt pro fallendem Blatt einen erhöhten Spannungspegel, der andere dient zur Erkennung der Nullposition und weist nur einmal pro Umdrehung der ganzen Welle einen erhöhten Spannungspegel auf. Das ganze wird durch weiße Blenden bewerkstelligt, die beim Vorbeistreichen am Sensor durch die Reflektion der Infrarotstrahlen des Transmitters für mehr Einfall von Infrarotstrahlung in die Photodiode und dadurch einen höheren Spannungspegel sorgen.
Die Verdrahtung der Sensoren auf der Platine ist etwas eigenwillig. Beide Sensoren gehen auf den gleichen Eingang (Sensor IN), an dem mit Hilfe eines ADC die anliegende Spannung messen kann. Um die Sensoren einzeln abfragen zu können, kann man die Sensoren getrennt mit Spannung versorgen (Sensor 1 / Sensor 2) und dann jeweils nur den Sensor auslesen, der mit Spannung versorgt wird. Der Motor ist einfach anzusteuern: Zieht man den Motor-Pin auf LOW, läuft der Motor los, zieht man ihn auf HIGH (3,3V oder 5V), bleibt der Motor stehen.
## Pinbelegung ZiLOG
## Stromversorgung
Die Platine hat zwei Stromkreise, ein Niederspannungsstromkreis für die Steuerungselektronik, der ursprünglich wohl mit 5 V DC betrieben wurde. Ich habe auch mit nur 3.3 V DC keine Probleme festgestellt. Der andere Stromkreis sollte mit etwa 42 V AC bei 50 Hz gespeist werden. Mit diesem Strom wird der Synchronmotor zum Antrieb der Welle betrieben. Die folgende Skizze zeigt die Pinbelegung des Wannensteckers am Rand der Platine bezüglich der Spannungsversorgung.
## Code
Code für die Platine kann in den Repositories [fallblatt-code-legacy](https://github.com/julianschick/fallblatt-code-legacy) und [fallblatt-code](https://github.com/julianschick/fallblatt-code) gefunden werden, wobei letzterer aktueller und mit mehr Funktionen ausgestattet ist.
## Teileliste
Mit passenden Artikelbezeichnungen für den Berliner Elektroteilehändler [Segor](https://www.segor.de).
Anzahl | Beschreibung | Segor-Artikelbezeichnung | Alt. Link
--|--|--|--
1 | Schraubklemme 2-polig RM 7,5mm | *ARK 2-Lift/RM7,5*
1 | Varistor >300V RM 7,5mm | *VDR 300-K 7* | [Reichelt](https://www.reichelt.de/varistor-rm-7-5-mm-300-v-10-epc-b72210-s030-p239932.html)
1 | Brückengleichrichter Rund, Wechselstrompins gegenüber, RM 5mm | *B 80C1500 R* | [Reichelt](https://www.reichelt.de/brueckengleichrichter-100-v-1-5-a-b70c1500rund-p181713.html)
1 | Transformator 9V _Block VB 2,0/1/9_ | | [Reichelt](https://www.reichelt.de/printtrafo-2-va-9-v-222-ma-rm-20-mm-ei-30-15-5-109-p27328.html)
1 | Transformator 2x24V *Block VC 10/2/24* | | [Reichelt](https://www.reichelt.de/printtrafo-10-va-2x-24-v-2x-208-ma-rm-27-5-mm-ei-48-16-8-224-p27492.html)
1 | ESP32-Development-Board (es gibt 2 Varianten bei eBay, für diese Platine wird die unüblichere mit 19 Pins je Reihe und GND/VCC auf gegenüberliegenden, nicht nebeneinanderliegenden Pins benötigt; diese wird oft unter dem Namen _ESP32S_ verkauft.) |
1 | Spannungsregler 3,3V Formfaktor TO-220 _STM LD1117 V33C_ | *LD 1117 V33* | [Reichelt](https://www.reichelt.de/ldo-regler-fest-3-3-v-to-220-ld1117-v33c-p200891.html)
1 | Elektrolytkondensator 470u, >12V, RM 5mm | *ELRA 470u-25/105°lowESR* |
1 | Elektrolytkondensator 10u, >12V, RM 2mm | *ELRA 470u-35/105°* |
1 | Kondensator 100n, >12V, RM 2,5mm | *u10-R2.5-X7R* |
1 | D-Sub Buchse 9-polig, Printmontage 90°, Abstand Pinreihe zu Steckerfläche 10mm | DS09F-90°-10mm |
1 | D-Sub Buchse 25-polig, Printmontage 90°, Abstand Pinreihe zu Steckerfläche 10mm | DS25F-90°-10mm |
4 | Pinheader 20-polig, Female, Vertikal, RM 2,54mm |
2 | Pinheader 2-polig, Male, Vertikal, RM 2,54mm
| 110.259259 | 569 | 0.797615 | deu_Latn | 0.995408 |
2c965f432fd0d0cfe59f7ba75bec67853f3599e4 | 12 | md | Markdown | README.md | jabber1wockey/weirdo | db22ef8d30b44a6751ead5b45876e2aa12875f8e | [
"Apache-2.0"
] | null | null | null | README.md | jabber1wockey/weirdo | db22ef8d30b44a6751ead5b45876e2aa12875f8e | [
"Apache-2.0"
] | null | null | null | README.md | jabber1wockey/weirdo | db22ef8d30b44a6751ead5b45876e2aa12875f8e | [
"Apache-2.0"
] | null | null | null | # weirdo
Hi
| 4 | 8 | 0.666667 | war_Latn | 0.789071 |
2c9686a44c48a7d6bd183026eadef582858df2e4 | 458 | md | Markdown | model_repository/dbmdz.bert-large-cased-finetuned-conll03-english/README.md | aychang95/fastnn | 93f02b860845959a8c625f6c99267f103756318b | [
"MIT"
] | 7 | 2020-12-03T07:04:47.000Z | 2022-03-25T11:51:15.000Z | model_repository/dbmdz.bert-large-cased-finetuned-conll03-english/README.md | aychang95/fastnn | 93f02b860845959a8c625f6c99267f103756318b | [
"MIT"
] | null | null | null | model_repository/dbmdz.bert-large-cased-finetuned-conll03-english/README.md | aychang95/fastnn | 93f02b860845959a8c625f6c99267f103756318b | [
"MIT"
] | null | null | null | ---
language:
- en
thumbnail:
tags:
- token-classification
- torchscript
- FastNN
license: mit
datasets:
- conll2003
metrics:
---
# TorchScript model of dbmdz/bert-large-cased-finetuned-conll03-english
## Model description
A serialized torchscript model of [dbmdz/bert-large-cased-finetuned-conll03-english](https://huggingface.co/dbmdz/bert-large-cased-finetuned-conll03-english) with a config.pbtxt for deployment using NVIDIA Triton Inference Server. | 24.105263 | 230 | 0.78821 | eng_Latn | 0.39814 |
2c96fba8d8451fe4d38cd027feb11c22d6b87898 | 7,410 | md | Markdown | fusion-plugin-universal-events/README.md | gkanishk/fusionjs | 8002ca487ce487f10e1f7ac04ac6bedc485f9908 | [
"MIT"
] | 1 | 2021-03-27T21:23:37.000Z | 2021-03-27T21:23:37.000Z | fusion-plugin-universal-events/README.md | gkanishk/fusionjs | 8002ca487ce487f10e1f7ac04ac6bedc485f9908 | [
"MIT"
] | null | null | null | fusion-plugin-universal-events/README.md | gkanishk/fusionjs | 8002ca487ce487f10e1f7ac04ac6bedc485f9908 | [
"MIT"
] | null | null | null | # fusion-plugin-universal-events
[](https://buildkite.com/uberopensource/fusion-plugin-universal-events)
The `fusion-plugin-universal-events` is commonly required by other Fusion.js plugins and is used as an event emitter for data such as statistics and analytics. This plugin captures events emitted from the client, sends them in batches to the server periodically, and allows the server to handle them. Note that due to the batched and fire-and-forget nature of the client-to-server event emission, this library is not suitable for timing-sensitive requests such as error logging or RPC calls.
It's useful for when you want to collect data about user actions or other metrics, and send them in bulk to the server to minimize the number of HTTP requests.
For convenience, this plugin automatically flushes its queue before page unload on `document.visibilityState === 'hidden'`.
If you need to use the universal event emitter from React, use [`fusion-plugin-universal-events-react`](https://github.com/fusionjs/fusionjs/tree/master/fusion-plugin-universal-events-react)
### Differences between UniversalEvents and other event emitter libraries
The `UniversalEvents` abstraction was designed to allow you to emit and react to events without worrying about whether you are on the server or the browser. It also provides the ability for observers to map event payloads to new ones. For example, you might want to add the some piece of context such as a session id to every event of a certain type.
---
### Table of contents
* [Installation](#installation)
* [Usage](#usage)
* [Setup](#setup)
* [API](#api)
* [Registration API](#registration-api)
* [`UniversalEvents`](#universalevents)
* [Dependencies](#dependencies)
* [`FetchToken`](#fetchtoken)
* [Service API](#service-api)
* [Other examples](#other-examples)
---
### Installation
```sh
yarn add fusion-plugin-universal-events
```
---
### Usage
```js
export default createPlugin({
deps: {events: UniversalEventsToken},
middleware: ({events}) => {
events.on('some-event', (payload) => {
console.log(payload)
});
events.on('some-scoped-event', (payload, ctx) => {
console.log(payload)
});
events.emit('some-event', {some: 'payload'});
return (ctx, next) => {
const scoped = events.from(ctx);
scoped.on('some-scoped-event', (payload, ctx) => {
console.log(payload)
});
scoped.emit('some-scoped-event', {some: 'scoped-payload'});
};
},
});
```
---
### Setup
```js
// main.js
import React from 'react';
import App from 'fusion-react';
import UniversalEvents, {UniversalEventsToken} from 'fusion-plugin-universal-events';
import {FetchToken} from 'fusion-tokens';
export default function() {
const app = new App();
app.register(UniversalEventsToken, UniversalEvents);
__BROWSER__ && app.register(FetchToken, window.fetch.bind(window));
return app;
}
```
---
### API
#### Registration API
##### `UniversalEvents`
```js
import UniversalEvents from 'fusion-plugin-universal-events';
```
The plugin. Provides the [service API](#service-api). Typically should be registered to `UniversalEventsToken`.
#### Dependencies
##### `FetchToken`
```js
import {FetchToken} from 'fusion-tokens';
// ...
__BROWSER__ && app.register(FetchToken, window.fetch.bind(window));
```
**Required. Browser-only.** See [https://github.com/fusionjs/fusionjs/tree/master/fusion-tokens#fetchtoken](https://github.com/fusionjs/fusionjs/tree/master/fusion-tokens#fetchtoken)
##### `UniversalEventsBatchStorageToken`
```js
import {UniversalEventsBatchStorageToken, localBatchStorage} from 'fusion-plugin-universal-events';
// ...
__BROWSER__ && app.register(UniversalEventsBatchStorageToken, inMemoryBatchStorage);
```
**Optional. Browser-only.**
By default events will be stored in browser local storage before they are sent to the server.
If you wish to override this behavior you can supply your own batch storage providing it complies with the `BatchStorage` interface type.
---
#### Service API
##### `events.on`
Registers a callback to be called when an event of a type is emitted. Note that the callback will not be called if the event is emitted before the callback is registered.
```js
events.on(type: string, callback: (payload: Object, ctx: ?Context, type: string) => void)
```
- `type: string` - Required. The type of event to listen on. The type `*` denotes all events.
- `callback: (mappedPayload: Object, ctx: ?Context) => void` - Required. Runs when an event of matching type occurs. Receives the `payload` after it has been transformed by [mapper functions](#eventsmap), as well an optional ctx object.
##### `events.emit`
```js
events.emit(type:string, payload: Object)
```
- `type: string` - Required. The type of event to emit. The type `*` denotes all events.
- `payload: Object` - Optional. Data to be passed to event handlers
##### `events.map`
Mutates the payload. Useful if you need to modify the payload to include metrics or other meta data.
```js
events.map(type: string, callback: (payload: Object, ctx: ?Context, type: string) => Object)
```
- `type: string` - Required. The type of event to listen on. The type `*` denotes all events.
- `callback: (payload: Object, ctx: ?Context) => Object` - Required. Runs when an event of matching type occurs. Should return a modified `payload`
##### `events.flush`
Flushes the data queue to the server immediately. Does not affect flush frequency
```js
events.flush()
```
##### `events.setFrequency`
```js
events.setFrequency(frequency: number)
```
Sets the frequency at which data is flushed to the server. Resets the interval timer.
- `frequency: number` - Required.
##### `events.teardown`
```js
events.teardown()
```
Stops the interval timer, clears the data queue and prevents any further data from being flushed to the server. Useful for testing
##### `events.from`
```js
const scoped = events.from(ctx: Context);
```
Returns a scoped version of the events api.
- `ctx: Context` - A [Fusion.js context](https://github.com/fusionjs/fusionjs/tree/master/fusion-core#context)
---
### Other examples
#### Event transformation
It's possible to transform event data with a mapping function, for example to attach a timestamp to all actions of a type.
```js
events.map('user-action', payload => {
return {...payload, time: new Date().getTime()};
});
events.on('user-action', payload => {
console.log(payload); // logs {type: 'click', time: someTimestamp}
});
events.emit('user-action', {type: 'click'});
```
#### Accessing `ctx`
Event mappers and handlers take an optional second parameter `ctx`. For example:
```js
events.on('type', (payload, ctx) => {
//...
})
```
This parameter will be present when events are emitted from the `ctx` scoped EventsEmitter instance. For example:
```js
app.middleware({events: UniversalEventsToken}, ({events}) => {
events.on('some-scoped-event', (payload, ctx) => {});
return (ctx, next) => {
const scoped = events.from(ctx);
scoped.emit('some-scoped-event', {some: 'payload'});
};
});
```
#### * event type
`*` is a special event type which denotes all events. This allows you to add a mapper or handler to all events. For example:
```js
events.map('*', payload => {
//
});
```
| 30.121951 | 491 | 0.712281 | eng_Latn | 0.921353 |
2c96fdf829cb788fe3d07fbaffa65235df75dfaa | 1,961 | md | Markdown | docs/behaviors/userstoppedtypingbehavior.md | brminnick/xamarin-communitytoolkit | 16e30cc7047a049dfc45373889327fb611e98a79 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | docs/behaviors/userstoppedtypingbehavior.md | brminnick/xamarin-communitytoolkit | 16e30cc7047a049dfc45373889327fb611e98a79 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | docs/behaviors/userstoppedtypingbehavior.md | brminnick/xamarin-communitytoolkit | 16e30cc7047a049dfc45373889327fb611e98a79 | [
"CC-BY-4.0",
"MIT"
] | null | null | null | ---
title: "Xamarin Community Toolkit UserStoppedTypingBehavior"
author: sthewissen
ms.author: joverslu
description: "The UserStoppedTypingBehavior allows the user to trigger an action when a user has stopped data input into an Entry."
ms.date: 12/08/2020
---
# Xamarin Community Toolkit UserStoppedTypingBehavior
The UserStoppedTypingBehavior is a behavior that allows the user to trigger an action when a user has stopped data input an `Entry`. Examples of its usage include triggering a search when a user has stopped entering their search query.
## Syntax
```xml
<Entry>
<Entry.Behaviors>
<xct:UserStoppedTypingBehavior
Command="{Binding SearchCommand}"
StoppedTypingTimeThreshold="1000"
MinimumLengthThreshold="3"
ShouldDismissKeyboardAutomatically="True" />
</Entry.Behaviors>
</Entry>
```
## Properties
|Property |Type |Description |
|---------|---------|---------|
| Command | [ICommand](xref:System.Windows.Input.ICommand) | The command to execute when the user has stopped providing input. |
| MinimumLengthThreshold | int | The minimum length of the input value required before the command will be executed. |
| ShouldDismissKeyboardAutomatically | int | Indicates whether or not the keyboard should be dismissed automatically. |
| StoppedTypingTimeThreshold | bool | The time of inactivity in milliseconds after which the command will be executed. |
## Sample
- [UserStoppedTypingBehavior sample page Source](https://github.com/xamarin/XamarinCommunityToolkit/blob/main/samples/XCT.Sample/Pages/Behaviors/UserStoppedTypingBehaviorPage.xaml)
You can see this in action in the [Xamarin Community Toolkit Sample App](https://github.com/xamarin/XamarinCommunityToolkit).
## API
* [UserStoppedTypingBehavior source code](https://github.com/xamarin/XamarinCommunityToolkit/blob/main/src/CommunityToolkit/Xamarin.CommunityToolkit/Behaviors/UserStoppedTypingBehavior.shared.cs)
| 43.577778 | 235 | 0.765426 | eng_Latn | 0.789504 |
2c974516e81b54675a1691ccec230f484da76dcc | 5,905 | md | Markdown | README.md | hallefy/ktor | b5dcbe5b740c2d25c7704104e01e0a01bf53d675 | [
"Apache-2.0"
] | 1 | 2017-06-20T02:03:26.000Z | 2017-06-20T02:03:26.000Z | README.md | hallefy/ktor | b5dcbe5b740c2d25c7704104e01e0a01bf53d675 | [
"Apache-2.0"
] | null | null | null | README.md | hallefy/ktor | b5dcbe5b740c2d25c7704104e01e0a01bf53d675 | [
"Apache-2.0"
] | null | null | null | <img src="https://github.com/Kotlin/ktor/wiki/resources/ktor.png" alt="Ktor" width="600" style="max-width:100%;">
[  ](https://bintray.com/kotlin/ktor/ktor/_latestVersion)
[](https://teamcity.jetbrains.com/viewType.html?buildTypeId=KotlinTools_Ktor_Build&branch_KotlinTools_Ktor=%3Cdefault%3E&tab=buildTypeStatusDiv)
[](http://www.apache.org/licenses/LICENSE-2.0)
Ktor is a framework for quickly creating web applications in Kotlin with minimal effort.
```kotlin
import org.jetbrains.ktor.netty.*
import org.jetbrains.ktor.routing.*
import org.jetbrains.ktor.application.*
import org.jetbrains.ktor.host.*
import org.jetbrains.ktor.http.*
import org.jetbrains.ktor.response.*
fun main(args: Array<String>) {
embeddedServer(Netty, 8080) {
routing {
get("/") {
call.respondText("Hello, world!", ContentType.Text.Html)
}
}
}.start(wait = true)
}
```
* Runs embedded web server on `localhost:8080`
* Installs routing and responds with `Hello, world!` when receiving GET http request for root path
## Documentation
Please visit our [Documentation Wiki](https://github.com/Kotlin/ktor/wiki) for quick start, detailed explanations of
features, usage and machinery.
If you want to contribute to Documentation please clone [Documentation Repository](https://github.com/Kotlin/ktor-wiki),
edit it and send us a Pull Request. We will sync wiki in this project and that repository periodically as needed.
## Principles
### Unopinionated
Ktor Framework doesn't impose a lot of constraints on what technology a project is going to use – logging, templating, messaging, persistent, serializing, dependency injection, etc. Rarely it may be required to implement pretty simple interface, but usually it is a matter of writing a transforming or intercepting function. Features are installed into application using unified *interception* mechanism which allows building arbitrary pipelines.
Ktor Application can be hosted in any servlet container with Servlet 3.0+ API support such as Tomcat, or standalone using Netty or Jetty. Support for other hosts can be added, though admittedly it's not an easy task.
Ktor APIs are mostly functions calls with lambdas. Thanks to Kotlin DSL capabilities, code looks declarative. Application composition is entirely developer's choice – with functions or classes, using dependency injection framework or doing it all manually in main function.
### Asynchronous
Ktor pipeline machinery and API is utilising a number of Kotlin features to provide easy-to-use asynchronous programming model without making it too cumbersome.
### Testable
Ktor application can be hosted in a [TestHost](https://github.com/Kotlin/ktor/wiki/Testing), which emulates to some
extent web server without actually doing any networking. It provides easy way to test an application without mocking
too much stuff, and still achieve good performance while validating application calls. Integration tests with real
embedded web server are of course possible, too.
## Features
In addition to core HTTP request processing and response building, Ktor provides a number of features out of the box, all implemented through its extensibility:
* Routing: attaches code to specific path/query/method/header and extract parameters from placeholders
* Sessions: stores and retrieves additional information attached to client session
* Content transformations: transforms response content on the fly and utilise unified mechanism to build a response
* Authentication: authenticates client using Basic, Digest, Form, OAuth (1a & 2)
* Custom status pages: sends custom content for specific status responses such as 404 Not Found
* Content type mapping: maps file extension to mime type for static file serving
* Template engines: uses content transformation to enable transparent template engine usage
* Static content: serves streams of data from local file system with full asynchronous support
* HTTP core features
* Compression: enables gzip/deflate compression when client accepts it
* Conditional Headers: sends 304 Not Modified response when if-modified-since/etag indicate content is the same
* Partial Content: sends partial content for streaming ranges, like in video streams
* Automatic HEAD response: responds to HEAD requests by running through pipeline and dropping response body
* CORS: verifies and sends headers according to cross-origin resource sharing control
* HSTS and https redirect: supports strict transport security
## Maven
Add a repository
```
<repository>
<snapshots>
<enabled>false</enabled>
</snapshots>
<id>bintray-kotlin-ktor</id>
<name>bintray</name>
<url>https://dl.bintray.com/kotlin/ktor</url>
</repository>
```
Add a dependency:
```
<dependency>
<groupId>org.jetbrains.ktor</groupId>
<artifactId>ktor-core</artifactId>
<version>${ktor.version}</version>
</dependency>
<!-- you also may need to include host implementation as well, for example
<dependency>
<groupId>org.jetbrains.ktor</groupId>
<artifactId>ktor-jetty</artifactId>
<version>${ktor.version}</version>
</dependency>
-->
```
## Gradle
```
repositories {
jcenter()
maven { url "https://dl.bintray.com/kotlin/kotlinx" }
maven { url "https://dl.bintray.com/kotlin/ktor" }
}
```
dependency:
```
dependencies {
compile "org.jetbrains.ktor:ktor-core:$ktorVersion"
// you may also need to include host implementation as well, for example
// compile "org.jetbrains.ktor:ktor-jetty:$ktorVersion"
}
```
## Inspirations
Wasabi, Kara
| 42.482014 | 447 | 0.762913 | eng_Latn | 0.95843 |
2c989822f6d32e4817275cde6b60ae73b6ed0071 | 1,145 | md | Markdown | README.md | SilexFriends/silex-soundcloud | 8e199f2f2375d5fb0db707380e42f65d55a7d634 | [
"MIT"
] | 1 | 2016-07-14T02:39:41.000Z | 2016-07-14T02:39:41.000Z | README.md | SilexFriends/silex-soundcloud | 8e199f2f2375d5fb0db707380e42f65d55a7d634 | [
"MIT"
] | null | null | null | README.md | SilexFriends/silex-soundcloud | 8e199f2f2375d5fb0db707380e42f65d55a7d634 | [
"MIT"
] | 1 | 2017-05-09T12:39:10.000Z | 2017-05-09T12:39:10.000Z | # SoundCloud Silex Provider
[](https://travis-ci.org/SilexFriends/SoundCloud)
[](https://codeclimate.com/github/SilexFriends/SoundCloud)
[](https://codeclimate.com/github/SilexFriends/SoundCloud/coverage)
[](https://codeclimate.com/github/SilexFriends/SoundCloud)
## Install
```
composer require mrprompt/silex-soundcloud
```
## Usage
```
use SilexFriends\SoundCloud\SoundCloud;
use Silex\Application;
$client_id = getenv('SOUNDCLOUD_CLIENT_ID');
$client_secret = getenv('SOUNDCLOUD_CLIENT_SECRET');
$app = new Application;
$app->register(new SoundCloud($client_id, $client_secret));
/* @var $url string */
$url = $app['request']->get('url');
/* @var $sound array */
$sound = $app['soundcloud']($url);
var_dump($sound);
```
## Tests
```
./vendor/bin/phpunit
```
## License
MIT | 27.926829 | 159 | 0.743231 | yue_Hant | 0.620985 |
2c98b104c6a9c30727a0c4e7d0f24ed2390e2b34 | 4,759 | md | Markdown | README.md | easy-monitor/metrics-server-exporter | 5a0d2169272e76be2cb8f5d109077376ec55a7a9 | [
"MIT"
] | null | null | null | README.md | easy-monitor/metrics-server-exporter | 5a0d2169272e76be2cb8f5d109077376ec55a7a9 | [
"MIT"
] | null | null | null | README.md | easy-monitor/metrics-server-exporter | 5a0d2169272e76be2cb8f5d109077376ec55a7a9 | [
"MIT"
] | null | null | null | # metrics-server-exporter [](https://circleci.com/gh/grupozap/metrics-server-exporter) [](https://lgtm.com/projects/g/grupozap/metrics-server-exporter/alerts/) [](https://lgtm.com/projects/g/grupozap/metrics-server-exporter/context:python)
metrics-server-exporter provides cpu and memory metrics for nodes and pods, directly querying the metrics-server API `/apis/metrics.k8s.io/v1beta1/{pods, nodes}`
### Node metrics
* kube_metrics_server_nodes_mem
* Provides nodes memory information in kibibytes.
* kube_metrics_server_nodes_cpu
* Provides nodes CPU information in nanocores.
##### labels
* instance
### Pod metrics
* kube_metrics_server_pods_mem
* Provides pods/container memory information.
* kube_metrics_server_pods_cpu
* Provides pods/container memory information.
##### labels
* pod_name
* pod_namespace
* pod_container_name
### API metrics
* kube_metrics_server_response_time
* Provides API response time in seconds.
### Variables
* K8S_ENDPOINT
* Url of API of kubernetes (default kubernetes.default.svc)
* K8S_TOKEN
* The authorization token (default ServiceAccount token)
* K8S_FILEPATH_TOKEN
* Path of ServiceAccount token file (default /var/run/secrets/kubernetes.io/serviceaccount/token)
* K8S_CA_CERT_PATH
* Path of Kubernetes CA certificate (default /var/run/secrets/kubernetes.io/serviceaccount/ca.crt)
* NAMES_BLACKLIST
* A list of names from pods, containers or namespaces to exclude from metrics.
* NAMESPACE_WHITELIST
* A list of namespace to scrape from this way you can create namespaced rolebinding instead of cluster binding. ( quite useful for larger clusters ) ( default : '' (all namespaces))
* LABEL_SELECTOR
* A list of Label Selectors.
### Options
* --insecure-tls
* Disables TLS verification of the Kubernetes API Server. (Not recommended in production)
### How to build
$ docker build . -t vivareal/metrics-server-exporter
### How to run
You will need `K8S_TOKEN` and `K8S_ENDPOINT` to access the api-server. Use "--insecure-tls" or mount the CA certificate into the container. Kubernetes will provide the CA certificate in a Kubernetes installation.
$ docker run -p 8000:8000 -e "K8S_ENDPOINT=${K8S_ENDPOINT}" -e "K8S_TOKEN=${K8S_TOKEN}" vivareal/metrics-server-exporter --insecure-tls
### How to deploy
Set you target k8s context and apply the deployment files
$ kubectl apply -f apply/
#### Blacklist
If you want, you could blacklist some names of namespaces, pods or containers, you just need to apply this ConfigMap, replacing the example names
```yaml
apiVersion: v1
kind: ConfigMap
metadata:
name: metrics-server-exporter
labels:
k8s-app: metrics-server-exporter
data:
NAMES_BLACKLIST: kube-proxy,calico-node,kube2iam # example names
```
### Minikube
How to test in Minikube
$ minikube delete; minikube start --vm-driver=kvm2 --cpus=2 --memory=4096
* Deleting "minikube" from kvm2 ...
* The "minikube" cluster has been deleted.
* minikube v1.2.0 on linux (amd64)
* Creating kvm2 VM (CPUs=2, Memory=4096MB, Disk=20000MB) ...
* Configuring environment for Kubernetes v1.15.0 on Docker 18.09.6
* Downloading kubelet v1.15.0
* Downloading kubeadm v1.15.0
* Pulling images ...
* Launching Kubernetes ...
* Verifying: apiserver proxy etcd scheduler controller dns
* Done! kubectl is now configured to use "minikube"
Enable metrics-server addon
$ minikube addons enable metrics-server
* metrics-server was successfully enabled
Deploy the files in minikube
$ kubectl apply -R -f deploy/ -n kube-system
Then, test the connectivity
$ kubectl port-forward -n kube-system svc/metrics-server-exporter 9104:9104 &
$ curl http://localhost:9104/metrics
### Helm
To install metrics-server-exporter, use
$ helm install --name=metrics-server-exporter --namespace kube-system helm/
You could set the variables using the `--set` parameters
$ helm install --name=metrics-server-exporter --set custom.k8s_endpoint=https://kubernetes.default.svc helm/
You could assign a specific nodePort.
$ helm install --name=metrics-server-exporter --set service.type=NodePort --set service.nodePort=31001 helm/
### Grafana Dashboard
You can use the following dashboard to plot metrics from metrics-server-exporter to Grafana.
https://grafana.com/grafana/dashboards/12363
| 33.992857 | 564 | 0.758563 | eng_Latn | 0.573569 |
2c98c67de155297dbe1a9e2725744f802f92d7f1 | 629 | md | Markdown | list/product-reviews.md | jjmpsp/jjmpsp.github.io | dcacfa63bce737b1056e0cf83964f72146aa4bac | [
"MIT"
] | null | null | null | list/product-reviews.md | jjmpsp/jjmpsp.github.io | dcacfa63bce737b1056e0cf83964f72146aa4bac | [
"MIT"
] | null | null | null | list/product-reviews.md | jjmpsp/jjmpsp.github.io | dcacfa63bce737b1056e0cf83964f72146aa4bac | [
"MIT"
] | null | null | null | ---
title: Product Reviews
narrow: false
permalink: /product-reviews/
show_profile: true
description: Product reviews by Joel Murphy.
ogDescription: Product reviews by Joel Murphy.
---
{% assign collectionCount = site.product_reviews | size %}
{% if site.product_reviews and collectionCount > 0 %}
{% for product_review in site.product_reviews %}
- [{{ product_review.title }}]({{ site.baseurl }}{{ product_review.url }})
{% endfor %}
{% else %}
Unfortunately, I haven't found the time to post any Product Reviews just yet. Please check back soon!
{% endif %}
{% include toc-scroll-to-top.html excludeHierarchy=true %}
| 31.45 | 101 | 0.72337 | eng_Latn | 0.661338 |
2c99250bb621601e0e507af28c61a04d3e523b5c | 51 | md | Markdown | algorithm/leetcode/135-candy.md | zhuwhr/interview | b769a18bf3128d5f5e3c176fb42cb69ce879d4ad | [
"MIT"
] | null | null | null | algorithm/leetcode/135-candy.md | zhuwhr/interview | b769a18bf3128d5f5e3c176fb42cb69ce879d4ad | [
"MIT"
] | null | null | null | algorithm/leetcode/135-candy.md | zhuwhr/interview | b769a18bf3128d5f5e3c176fb42cb69ce879d4ad | [
"MIT"
] | null | null | null | [135. Candy](https://leetcode.com/problems/candy/)
| 25.5 | 50 | 0.72549 | pol_Latn | 0.23409 |
2c995e8d8abe7b73f9313a0e03b3aef4cd5c7df6 | 10,387 | md | Markdown | _posts/releases/qemu-arm/2020-12-20-qemu-arm-v2-8-0-11-released.md | xpack/web-jekyll | ca7c4166c581b7d016f717baee33960b40d2669f | [
"MIT",
"BSD-3-Clause"
] | null | null | null | _posts/releases/qemu-arm/2020-12-20-qemu-arm-v2-8-0-11-released.md | xpack/web-jekyll | ca7c4166c581b7d016f717baee33960b40d2669f | [
"MIT",
"BSD-3-Clause"
] | 5 | 2020-09-10T15:15:47.000Z | 2021-04-30T21:24:18.000Z | _posts/releases/qemu-arm/2020-12-20-qemu-arm-v2-8-0-11-released.md | xpack/web-jekyll | ca7c4166c581b7d016f717baee33960b40d2669f | [
"MIT",
"BSD-3-Clause"
] | 1 | 2021-03-23T15:03:02.000Z | 2021-03-23T15:03:02.000Z | ---
title: xPack QEMU Arm v2.8.0-11 released
summary: "Version 2.8.0-11 is a maintenance release; it add support for STM32F407VGTx and STM32F429ZITx."
version: 2.8.0-11
npm_subversion: 1
download_url: https://github.com/xpack-dev-tools/qemu-arm-xpack/releases/tag/v2.8.0-11/
date: 2020-12-20 17:48:00 +0200
categories:
- releases
- qemu
tags:
- releases
- qemu
- emulator
- arm
- cortex-m
---
[The xPack QEMU Arm](https://xpack.github.io/qemu-arm/)
is the **xPack** distribution of the
[QEMU](http://www.qemu.org), with several extensions for Arm Cortex-M
devices.
There are separate binaries for **Windows** (Intel 32/64-bit),
**macOS** (Intel 64-bit) and **GNU/Linux** (Intel 32/64-bit, Arm 32/64-bit).
{% include note.html content="The main targets for the Arm binaries
are the **Raspberry Pi** class devices." %}
## Download
The binary files are available from GitHub [releases]({{ page.download_url }}).
## Install
The full details of installing the **xPack QEMU Arm** on various platforms
are presented in the separate
[Install]({{ site.baseurl }}/qemu-arm/install/) page.
### Easy install
The easiest way to install QEMU Arm is with
[`xpm`]({{ site.baseurl }}/xpm/)
by using the **binary xPack**, available as
[`@xpack-dev-tools/qemu-arm`](https://www.npmjs.com/package/@xpack-dev-tools/qemu-arm)
from the [`npmjs.com`](https://www.npmjs.com) registry.
To install the latest version available, use:
```console
$ xpm install --global @xpack-dev-tools/qemu-arm@latest
```
To install this specific version, use:
```console
$ xpm install --global @xpack-dev-tools/qemu-arm@{{ page.version }}.{{ page.npm_subversion }}
```
## Compliance
xPack QEMU Arm currently is based on the official [QEMU](http://www.qemu.org),
with major changes.
The current version is based on:
- QEMU version 2.8.0, commit [0737f32](https://github.com/xpack-dev-tools/qemu/commit/0737f32daf35f3730ed2461ddfaaf034c2ec7ff0) from Dec 20th, 2016.
## Changes
Compared to the master `qemu-system-arm`, the changes are major, all
application class Arm
devices were removed and replaced by several Cortex-M devices.
The supported boards are:
```console
xPack 64-bit QEMU v2.8.0 (qemu-system-gnuarmeclipse).
Supported boards:
Maple LeafLab Arduino-style STM32 microcontroller board (r5)
NUCLEO-F103RB ST Nucleo Development Board for STM32 F1 series
NUCLEO-F411RE ST Nucleo Development Board for STM32 F4 series
NetduinoGo Netduino GoBus Development Board with STM32F4
NetduinoPlus2 Netduino Development Board with STM32F4
OLIMEXINO-STM32 Olimex Maple (Arduino-like) Development Board
STM32-E407 Olimex Development Board for STM32F407ZGT6
STM32-H103 Olimex Header Board for STM32F103RBT6
STM32-P103 Olimex Prototype Board for STM32F103RBT6
STM32-P107 Olimex Prototype Board for STM32F107VCT6
STM32F0-Discovery ST Discovery kit for STM32F051 lines
STM32F4-Discovery ST Discovery kit for STM32F407/417 lines
STM32F429I-Discovery ST Discovery kit for STM32F429/439 lines
generic Generic Cortex-M board; use -mcu to define the device
Supported MCUs:
STM32F051R8
STM32F103RB
STM32F107VC
STM32F405RG
STM32F407VG
STM32F407VGTx <- new
STM32F407ZG
STM32F411RE
STM32F429ZI
STM32F429ZITx <- new>
```
Warning: support for hardware floating point on Cortex-M4 devices is not
available yet.
## Bug fixes
- none.
## Enhancements
- [[#5](https://github.com/xpack-dev-tools/qemu/pull/5)] - add support
for STM32F407VGTx and STM32F429ZITx.
## Known problems
- Ctrl-C does not interrupt the execution if the `--nographic` option is used.
## Shared libraries
On all platforms the packages are standalone, and expect only the standard
runtime (including X11) to be present on the host.
All dependencies that are build as shared libraries are copied locally in the
same folder as the executable.
### `DT_RPATH` and `LD_LIBRARY_PATH`
On GNU/Linux the binaries are adjusted to use a relative path:
```console
$ readelf -d library.so | grep rpath
0x000000000000001d (RPATH) Library runpath: [$ORIGIN]
```
In the GNU ld.so search strategy, the `DT_RPATH` has
the highest priority, higher than `LD_LIBRARY_PATH`, so if this later one
is set in the environment, it should not interfere with the xPack binaries.
Please note that previous versions, up to mid-2020, used `DT_RUNPATH`, which
has a priority lower than `LD_LIBRARY_PATH`, and does not tolerate setting
it in the environment.
### `@executable_path`
Similarly, on macOS, the binaries are adjusted with `otool` to use a
relative path.
## Documentation
The original documentation is available in the `share/doc` folder.
## Supported platforms
Binaries for **Windows**, **macOS** and **GNU/Linux** are provided.
The binaries were built using the
[xPack Build Box (XBB)](https://github.com/xpack/xpack-build-box), a set
of build environments based on slightly older distributions, that should be
compatible with most recent systems.
- Intel GNU/Linux: all binaries were built with GCC 9.3, running in an
Ubuntu 12 Docker container
- Arm GNU/Linux: all binaries were built with GCC 9.3, running in an
Ubuntu 16 Docker container (added in mid-2020)
- Windows: all binaries were built with mingw-w64 GCC 9.3, running in an
Ubuntu 12 Docker container
- macOS: all binaries were built with GCC 9.3, running in a separate
folder on macOS 10.10.5.
## Build
The scripts used to build this distribution are in:
- `distro-info/scripts`
For the prerequisites and more details on the build procedure, please see the
[How to build](https://github.com/xpack-dev-tools/qemu-arm-xpack/blob/xpack/README-BUILD.md) page.
## Travis tests
The first set of tests were performed on Travis, by running
a simple script to check if the binaries start on a wide range of
platforms and distributions:
- [test xPack QEMU Arm on stable platforms](https://travis-ci.org/github/xpack-dev-tools/qemu-arm-xpack/builds/750670793)
- [test xPack QEMU Arm on latest platforms](https://travis-ci.org/github/xpack-dev-tools/qemu-arm-xpack/builds/750670833)
## Tests
The binaries were testes on Windows 10 Pro 32/64-bit, Ubuntu 18 LTS 64-bit,
Xubuntu 18 LTS 32-bit and macOS 10.14.
The tests consist in running a simple blinky application
on the graphically emulated STM32F4DISCOVERY board. The binaries were
those generated by
[simple Eclipse projects](https://github.com/xpack-dev-tools/arm-none-eabi-gcc-xpack/tree/xpack/tests/eclipse)
available in the **xPack GNU Arm Embedded GCC** project. Use the
`arm-f4b-fs-debug-qemu` debug luncher available in the `arm-f4b-fs` project.
On Arm platforms, where Eclipse is not yet available, the binaries were
tested on Raspberry Pi OS 10 (buster) 32-bit by manually starting the
blinky test on the emulated STM32F4DISCOVERY board.
```
~/opt/xPacks/@xpack-dev-tools/qemu-arm/2.8.0-11.1/.content/bin/qemu-system-gnuarmeclipse --version
mkdir -p ~/Downloads
(cd ~/Downloads; curl -L --fail -o f407-disc-blink-tutorial.elf \
https://github.com/xpack-dev-tools/qemu-eclipse-test-projects/raw/master/f407-disc-blink-tutorial/Debug/f407-disc-blink-tutorial.elf)
~/opt/xPacks/@xpack-dev-tools/qemu-arm/2.8.0-11.1/.content/bin/qemu-system-gnuarmeclipse \
--board STM32F4-Discovery \
-d unimp,guest_errors \
--nographic \
--image ~/Downloads/f407-disc-blink-tutorial.elf \
--semihosting-config enable=on,target=native \
--semihosting-cmdline test 6
DISPLAY=:1.0 ~/opt/xPacks/@xpack-dev-tools/qemu-arm/2.8.0-11.1/.content/bin/qemu-system-gnuarmeclipse \
--board STM32F4-Discovery \
-d unimp,guest_errors \
--image ~/Downloads/f407-disc-blink-tutorial.elf \
--semihosting-config enable=on,target=native \
--semihosting-cmdline test 6
```
On Raspberry Pi OS 10 (buster) 64-bit the program was able to run in non
graphic mode, but did not start in graphic mode due to a
missing driver. To be further investigated.
## Checksums
The SHA-256 hashes for the files are:
```
2332844b95c51aa08bdae3ef5ce948eff28872afdf1d65c2ac4447906ddac79a
xpack-qemu-arm-2.8.0-11-darwin-x64.tar.gz
b67e5e34b919a238352d32fd5ade3a9333d797251efa8e45805e9055a10d5bed
xpack-qemu-arm-2.8.0-11-linux-arm64.tar.gz
50b62d96da97db01d6d89d6382fbc5b1ef536e6b452d4c813c229e92619474e6
xpack-qemu-arm-2.8.0-11-linux-arm.tar.gz
1929dd497281c55158d7db973050bb536e7a781248bb5b841ced282e8caea6eb
xpack-qemu-arm-2.8.0-11-linux-ia32.tar.gz
30d761dab5f945ecf15a6c51d12d813c2847e186eec5b6cd4ff81bf17ddae532
xpack-qemu-arm-2.8.0-11-linux-x64.tar.gz
923d4267d8dc0995d526d4b20a9cfa5953971a5895bed1f29f577ce94afc0e9c
xpack-qemu-arm-2.8.0-11-win32-ia32.zip
3184bbb2427b0bdd17a53c716812103965abe1e003338d323d4a69ba2670bde9
xpack-qemu-arm-2.8.0-11-win32-x64.zip
```
## Download analytics
- GitHub [xpack-dev-tools/qemu-arm-xpack](https://github.com/xpack-dev-tools/qemu-arm-xpack/)
- this release [](https://github.com/xpack-dev-tools/qemu-arm-xpack/releases/v{{ page.version }}/)
- all xPack releases [](https://github.com/xpack-dev-tools/qemu-arm-xpack/releases/)
- all GNU MCU Eclipse releases [](https://github.com/gnu-mcu-eclipse/qemu/releases/)
- [individual file counters](https://somsubhra.github.io/github-release-stats/?username=xpack-dev-tools&repository=qemu-arm-xpack) (grouped per release)
- npmjs.com [@xpack-dev-tools/qemu-arm](https://www.npmjs.com/package/@xpack-dev-tools/qemu-arm)
- latest releases [](https://www.npmjs.com/package/@xpack-dev-tools/qemu-arm/)
- all @xpack-dev-tools releases [](https://www.npmjs.com/package/@xpack-dev-tools/qemu-arm/)
- all @gnu-mcu-eclipse releases [](https://www.npmjs.com/package/@gnu-mcu-eclipse/qemu/)
Credit to [Shields IO](https://shields.io) for the badges and to
[Somsubhra/github-release-stats](https://github.com/Somsubhra/github-release-stats)
for the individual file counters.
| 36.191638 | 224 | 0.754116 | eng_Latn | 0.756779 |
2c9a7c5f25441b9a3142c7da38b39d85d1260b50 | 4,721 | md | Markdown | _posts/2021-11-6-Death-By-Daylight.md | dmsheril/dmsheril.github.io | abc1447b8f3d9f7d2380b3dc995d323d51a89cb2 | [
"MIT"
] | null | null | null | _posts/2021-11-6-Death-By-Daylight.md | dmsheril/dmsheril.github.io | abc1447b8f3d9f7d2380b3dc995d323d51a89cb2 | [
"MIT"
] | null | null | null | _posts/2021-11-6-Death-By-Daylight.md | dmsheril/dmsheril.github.io | abc1447b8f3d9f7d2380b3dc995d323d51a89cb2 | [
"MIT"
] | null | null | null | ---
layout: post
title: Death By Daylight
---
## Background
This project is inspired by [a recent NY Times podcast](https://www.nytimes.com/2021/11/05/learning/do-you-think-it-is-time-to-get-rid-of-daylight-saving-time.html) featuring a debate over the merits of daylight saving time vs. standard time. Both sides advocated for doing away with the current US system of changing twice a year and settling upon a single time system for the entire year. But they had arrived at opposite conclusions about which time system was best.
What piqued my curiosity was a research finding cited by the neurologist arguing in favor of adopting standard time year round. He cited a study comparing cancer rates on the western edge of US time zones vs. the eastern edge. Cancer rates were found to be higher on the western edge, where the sun sets later. He proposed the underlying mechanism to be the "social jetlag" induced by people going to sleep later in areas where the sun sets later, but still having to wake up to meet the obligatory schedules of society whose timing is fixed (e.g., school and work start times), such that they are more chronically sleep deprived than their counterparts in areas where the sun sets earlier. Sleep deprivation has long been associated with negative health outcomes, ergo higher cancer rates for the sleepier cohort.
The implication of this comparison across time zone boundaries is that year-round daylight saving time would be even worse for human health because it causes people nationwide to go to bed later.
I googled to learn more, and found a [2019 Washington Post article](https://www.washingtonpost.com/business/2019/04/19/how-living-wrong-side-time-zone-can-be-hazardous-your-health/) on the subject. This article reprints a beautiful visualization of average annual sunset time from the [original 2019 journal article](https://www.sciencedirect.com/science/article/abs/pii/S0167629618309718) by researchers from Pittsburgh and Switzerland.
## Project Plan
My goal is to reproduce this effect in data from other sources. No guarantee I'll actually see an effect but it will be a useful learning experience. This project will help me build toolsets for visualizing geospatial data in 2D maps. It will also give me practice with performing regression analysis. Also I'll get familiar with identifying and collating real-world sources of health outcome data.
To do list:
- Find a suitable dataset (publicly available, nationwide, related to health outcomes, with many geospatial subdivisions per time zone)
- Vet the dataset (structural complexity? how much missing/quirky data? how much variability?)
- Gather demographics of the geospatial subdivisions (population, economic, education, etc.)
- Compute annual average sunset times for each geospatial subdivision
- Recreate the nifty map of average sunset times, and create versions of that map colorcoded by health outcome value.
- Run the regression of health outcomes as a function of average sunset times
### Candidate Datasets
CDC's [Behavioral Risk Factor Surveillance System](https://chronicdata.cdc.gov/Behavioral-Risk-Factors/Behavioral-Risk-Factors-Selected-Metropolitan-Area/j32a-sa6u)
- 153k rows, 27 columns
- downloaded CSV on 11/6/21 from CDC website
- subdivisions are selected metropolitan statistical areas (MMSAs)
- years covered: 2011-2019
- tons of health outcome measures, unclear how complete the coverage is though (only questions/years/MMSAs where there were more than 500 responses per MMSA are included)
- includes a lat-lon column for the location! I wouldn't have to compute it...
IHME's [United States Mortality Rates by County](https://www.kaggle.com/IHME/us-countylevel-mortality)
- 67k rows, 30 columns
- downloaded CSV on 11/5/21 from Kaggle
- subdivisions are US counties (appears to be all, and state level stats are given as well)
- years covered: every 5 years 1980-2010 plus 2014
- simpler to interpret outcome measures: age-standardized mortality rate (death per 100k population) by category
- This website has kernel for using R to create maps!
### Code for Sunset Times
I found [some R code on Github](https://gist.github.com/jonspring/78b2124cf9daa351de98b5e031473585) by a guy who made some cool animations in R showing how sunrise & sunset times shift for different cities throughout the year, and also showing a US map rotating to show correlation between later sunsets and voting patterns. He [tweeted](https://twitter.com/JustTheSpring/status/1194355907745865728) about it too!
Also found a [Python library](https://pypi.org/project/suncalc/) to do sun calculations for given locations.
_To be continued..._
| 92.568627 | 815 | 0.798136 | eng_Latn | 0.995657 |
2c9b0720bebb0450f9743aa686784c0e0ecb7b57 | 445 | md | Markdown | README.md | bcgov/nr-flnr-ecas-processing | 29c1f3d778c421625c76f3db26f1a3a29e1fd02c | [
"CC0-1.0"
] | null | null | null | README.md | bcgov/nr-flnr-ecas-processing | 29c1f3d778c421625c76f3db26f1a3a29e1fd02c | [
"CC0-1.0"
] | 5 | 2021-04-09T18:25:20.000Z | 2022-02-05T21:57:14.000Z | README.md | bcgov/nr-flnr-ecas-processing | 29c1f3d778c421625c76f3db26f1a3a29e1fd02c | [
"CC0-1.0"
] | null | null | null | # nr-flnr-ecas-processing
The Coast Area Pricing team risk assessment scripts
The FLNR's Coast Area Pricing team works with a risk assessment spreadsheet that connects to the production oracle database server, and retrieves ECAS data on a regular basis.
This is a demo example see actual here - https://github.com/bcgov/nr-flnr-coast-riskrating
[](<Redirect-URL>)
| 49.444444 | 176 | 0.793258 | eng_Latn | 0.921209 |
2c9bb7874907316c2181c66e5c60dd12c49a1f85 | 862 | md | Markdown | README.md | commoncurriculum/autocomplete-tailwind | bd35a05a583450cf2322c67bbdfa7d0731bf8e81 | [
"MIT"
] | null | null | null | README.md | commoncurriculum/autocomplete-tailwind | bd35a05a583450cf2322c67bbdfa7d0731bf8e81 | [
"MIT"
] | null | null | null | README.md | commoncurriculum/autocomplete-tailwind | bd35a05a583450cf2322c67bbdfa7d0731bf8e81 | [
"MIT"
] | null | null | null | # autocomplete-tailwind [](https://travis-ci.com/vinkla/autocomplete-tailwind)
> An autocompletion provider for the utility-first CSS framework Tailwind.
Autocompletion provider for Atom with the default Tailwind CSS configuration and modules.
## Installation
To install the package in Atom, run the command below in the terminal.
```sh
$ apm install autocomplete-tailwind
```
## Credits
This project uses the [`tailwind-class-names`](https://unpkg.com/tailwind-class-names@0.6.0/dist/index.js) package by [Brad Cornes](https://github.com/bradlc) which is doing the heavy lifting.
## License
[MIT](LICENSE) © [Vincent Klaiber](https://doubledip.se)
| 35.916667 | 192 | 0.776102 | eng_Latn | 0.531894 |
2c9c839cfecf33c98babcf8eef5498f9198b0138 | 1,304 | md | Markdown | pages/articles/2016-03-10-post-3/index.md | jcfa01/gatsby-blog-jcfa01 | e601617ca86f1cc9c2af1d949bd5c0e083a64752 | [
"MIT"
] | null | null | null | pages/articles/2016-03-10-post-3/index.md | jcfa01/gatsby-blog-jcfa01 | e601617ca86f1cc9c2af1d949bd5c0e083a64752 | [
"MIT"
] | null | null | null | pages/articles/2016-03-10-post-3/index.md | jcfa01/gatsby-blog-jcfa01 | e601617ca86f1cc9c2af1d949bd5c0e083a64752 | [
"MIT"
] | null | null | null | ---
title: $(document).ready(function() {
date: "2016-03-10T00:00:00.169Z"
layout: post
path: "/post-3/"
category: "jQuery"
description: ""
---
```
$(‘jQuery’).progress(function(){ $(this).basic(‘100%’); $(this).advanced(‘20%’); $(this).expert(‘0%’); });
});
```
So, I have done the basics of jQuery. the syntax, event handlers, common effects and animations, and some UI. in order for me to adjust my advanced percentage, I must apply it in my working test project or tutorial stage project. and for the expert I must apply it on my dream project. for now that is what I called it because I haven’t done anything to it. and in order for me to start on that, I have to learn all of the basics of full-stack web development. so far I’m making slow progress because of my other ventures. I hope I do less and less of it. I still haven’t done my nodejs and mongoDB connection. and that’s my agenda for tommorrow. I hope there will be progress by then. for now. I’m done with jQuery “Basics!”.it.
| 81.5 | 729 | 0.547546 | eng_Latn | 0.996842 |