Anti-Dalit comments made on Arnab Goswami’s show prove costly as demand grows for Ramdev’s arrest
by JKR StaffPatanjali founder Ramdev on Sunday found himself in the line of fire as Dalit supporters took to social media to demand his arrest for allegedly making insulting remarks against Periyar and followers of noted Dalit icon Dr BR Ambedkar on Arnab Goswami’s show. In a public speech, Ramdev criticised Periyar for his moolniwasi ideology and called him and the supporters of Ambedkar ‘intellectual terrorists.’
Dalit supporters, who trended hashtags such as #Ramdev_Insults_Periyar and #ArrestRamdev have shared videos of Ramdev’s criticism for Periyar and supporters of Ambedkar calling them ‘intellectual terrorists’. In one interview to Republic TV’s Arnab Goswami, Ramdev is heard saying, “In the name of Ambedkar, some people are propagating the moolniwasi (claiming Dalits are the native Indians and rest having come from outside) concept. Some people from BAMCEF (Dalit group founded by Kanshi Ram) are trying to create a rift. I have coined a term for them and that is ‘intellectual terrorism.”
In a separate video, Ramdev is seen addressing his followers while criticising Periyar by disparagingly calling him an atheist and criticising his moolniwasi ideology.
No sooner did the videos of Ramdev allegedly insulting noted Dalit icons emerged, social media users took to Twitter to express their outrage with many demanding the arrest of the Patanjali founder.
Here’s how they reacted on social media:
Periyar, often dubbed as South Indian Socrates, was an atheist and helmed social reforms by working against the caste discrimination. The noted Dravidian patriarch had famously said that those who invented the notion of god were fools.
As for Ambedkar, he’s arguably one of the biggest Dalit icons and was the architect of the Indian constitution.


Microservices in .NET Core, Second Edition Microservices in .NET Core, Second Edition</i> is a comprehensive guide to building microservice applications using the .NET stack. After a crystal-clear introduction to the microservices architectural style, it teaches you practical microservices develop...
Replicate your favorite VSCode theme in Windows Terminal Windows Terminal has been out for around 6 months now and it’s safe to say it’s a huge success.It’s a great way to handle working with multiple terminal applications in one space,…
The Svelte Compiler Handbook The Svelte compilation process can be broken down into 4-steps, 1) parsing source code into AST, 2) tracking references and dependencies, 3) creating code blocks and fragments, and 4) generate code.
Sunday Morning Live Hey Coders, Subscribe here - https://www.youtube.com/channel/UCetyodKOWGk5H6FoKoFnkZw Talk to us on - https://www.twitch.tv/curiousdrive Like our page - https://www.facebook.com/curiousdrive/ Follow us on - https://twitter.com/curious_drive Follow us ...
Theia - Cloud and Desktop IDE Theia is an open-source cloud desktop IDE framework implemented in TypeScript.
Regex Performance Improvements in .NET 5 | .NET Blog The System.Text.RegularExpressions namespace has been in .NET for years, all the way back to .NET Framework 1.1. It’s used in hundreds of places within the .NET implementation itself, and directly by thousands upon thousands of applications. Across all of...
Ryan C. Gordon is creating games, tools, and awesome things. | Patreon Become a patron of Ryan C. Gordon today: Read 68 posts by Ryan C. Gordon and get access to exclusive content and experiences on the world’s largest membership platform for artists and creators.
Yet another novel I will no longer write So, some years ago I blogged a whole bunch of times about books I wasn't going to write for one reason or another.
Boring Old Business Home This is the home page for Boring Old Business. Learn how to make money online using the best old-school marketing principles and strategies.
Newsletter - PL^G We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.Ok
OMG! We Made One Gram of Remdesivir! Two of the experimental coronavirus drugs, chloroquine, and hydroxychloroquine are a breeze to synthesize. But remdesivir, possibly the most promising candidate, is anything but. It's a royal pain. Here's why.
Bose QC 35 Firmware 4.5.2 Noise Cancellation Investigation Report Hello everyone, To preface this post, the content you will find below is a rich summary of the testing and history regarding our QC35 Acoustic Noise Cancelling performance and firmware 4.5.2. Our community members spent many hours providing us with fee...
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Kurzgesagt – In a Nutshell is creating Science Animation Videos | Patreon Become a patron of Kurzgesagt – In a Nutshell today: Read 210 posts by Kurzgesagt – In a Nutshell and get access to exclusive content and experiences on the world’s largest membership platform for artists and creators.
Kubernetes Research Survey Take this survey powered by surveymonkey.com. Create your own surveys for free.
Pretlist Careers Pretlist powers secure mesh networks. We help businesses and governments communicate and navigate offline and without Carrier Networks.


German police ask men in the city of Grevenbroich to take DNA tests to try to solve girl’s murder in 1996
Police have asked 900 men to step forward to be DNA tested in this town in a bid to solve the gruesome cold case murder of a young girl.
The girl, Claudia Ruf, was kidnapped, raped and choked to death by an anonymous murderer in 1996.
Her body was found in Euskirchen, 70km south of Grevenbroich, which is situated between Düsseldorf and Cologne.
It has a population of 63,000.
German news agency dpa reported that 900 men, who were between 14 and 70 years old at the time of Ruf’s killing, have received invitations for a saliva swab test to have their DNA identified.
Investigators already unsuccessfully tested some 350 men’s DNA in 2010. They say they now found new hints that could help them find the murderer by checking the 900 men.
Claudia disappeared while walking her neighbour’s dog in Grevenbroich (between Düsseldorf and Cologne). Two days later, the eleven-year-old was found murdered.
MORE NEWS
Meghan ‘horrified’ by Andrew interview
A new smartphone price war is coming
Local reports say police know why the body was found so far away from home, but they are refusing to reveal any further information at this time.


Scotland forwards coach Wilson to take over Glasgow Warriors job after Rennie
It’s the big (rugby) coaching news of the day.
by Sean FarrellTHE SRU AND Glasgow Warriors have this morning confirmed that Danny Wilson will take over as head coach of the Pro14 side next season.
Current Warriors boss Dave Rennie was yesterday named as the next Wallabies head coach. He will remain with the Scottish side for the rest of the season, taking over in Australia come July.
Wilson, who replaced Dan McFarland as Scotland forwards coach last year, will be involved in the recruitment and planning process with the Scotstoun club in the coming months. He will continue working with, former Glasgow coach, Gregor Townsend’s national setup through the Six Nations before formally taking over at Scotstoun in the summer.
“Danny brings significant Guinness Pro14 experience, has a European trophy to his credit, and international experience with Scotland,” says Warriors managing director Nathan Bombrys of the former Cardiff Blues and Wales U20 coach.
“His background as a forwards coach will bring a different perspective to our head coaching position.”
After signing on with last year’s beaten Pro14 finalists, Wilson said:
“I’ve been extremely impressed with the Scottish system in recent years and I’m looking forward to working with an exciting and talented squad of players at the Warriors.
“I want to build on the high-tempo style of play that I know the fans love and pay to see week in, week out.”


Release
Contact:
Philip Gooding
Release date:21 March 2015
Next release:25 April 2015 pre-release access list
Inflation measures the rate of increase in prices for goods and services using price indices. The rate of inflation used in the UK government’s inflation target is measured using the Consumer Prices Index (CPI). One way to understand the CPI is to think of a very large shopping basket containing a large selection of the goods and services bought by households, the CPI estimateschanges to the total cost of this basket.
The Consumer Price Inflation is a monthly release that contains percentage changes and weights for the CPI, CPIH, RPI and RPIJ.
Measures of inflation over time, including CPI, RPI, CPIH and RPIJ.
This dataset gives access to a comprehensive database of time series from major national statistics and social economic releases.
The United Kingdom Statistics Authority has designated these statistics as National Statistics, in accordance with the Statistics and Registration Service Act 2007 and signifying compliance with the Code of Practice for Official Statistics. Designation can be broadly interpreted to mean that the statistics: meet identified user needs, are well explained and readily accessible, are produced according to sound methods, and are managed impartially and objectively in the public interest. Once statistics have been designated as National Statistics it is a statutory requirement that the Code of Practice shall continue to be observed.
The phrase 'Pre-release Access' refers to the practice whereby official statistics in their final form, and any accompanying written commentary, are made available to an eligible person in advance of their publication. The rules and principles which govern pre-release access are featured within the Pre-release Access to Official Statistics Order 2008. Besides ONS staff, the following persons are given pre-release access by the period indicated before release.


Returns true if a value has the characteristics of a valid JavaScript accessor descriptor.
Please consider following this project's author, Jon Schlinkert, and consider starring the project to show your :heart: and support.
Install with npm:
$ npm install --save is-accessor-descriptor
var isAccessor = require('is-accessor-descriptor');
isAccessor({get: function() {}});
//=> true
You may also pass an object and property name to check if the property is an accessor:
isAccessor(foo, 'bar');
false
when not an object
isAccessor('a')
isAccessor(null)
isAccessor([])
//=> false
true
when the object has valid properties
and the properties all have the correct JavaScript types:
isAccessor({get: noop, set: noop})
isAccessor({get: noop})
isAccessor({set: noop})
//=> true
false
when the object has invalid properties
isAccessor({get: noop, set: noop, bar: 'baz'})
isAccessor({get: noop, writable: true})
isAccessor({get: noop, value: true})
//=> false
false
when an accessor is not a function
isAccessor({get: noop, set: 'baz'})
isAccessor({get: 'foo', set: noop})
isAccessor({get: 'foo', bar: 'baz'})
isAccessor({get: 'foo', set: 'baz'})
//=> false
false
when a value is not the correct type
isAccessor({get: noop, set: noop, enumerable: 'foo'})
isAccessor({set: noop, configurable: 'foo'})
isAccessor({get: noop, configurable: 'foo'})
//=> false
 Contributing
Pull requests and stars are always welcome. For bugs and feature requests, please create an issue.

 Running Tests
Running and reviewing unit tests is a great way to get familiarized with a library and its API. You can install dependencies and run tests with the following command:
$ npm install && npm test

 Building docs
(This project's readme.md is generated by verb, please don't edit the readme directly. Any changes to the readme must be made in the .verb.md readme template.)
To generate the readme, run the following command:
$ npm install -g verbose/verb#dev verb-generate-readme && verb

You might also be interested in these projects:
Object
constructor. | homepage| Commits | Contributor |
|---|---|
| 22 | jonschlinkert |
| 2 | realityking |
Jon Schlinkert
Copyright © 2017, Jon Schlinkert. Released under the MIT License.
This file was generated by verb-generate-readme, v0.6.0, on November 01, 2017.


Please select a playlist to clean up
{{Example}}
Choose a Playlist:
{{#playlists}}
{{name}}
{{/playlists}}


#include <ck_mot.h>
Public Types | |
| enum | PlayMode { PLAY_NORMAL, PLAY_LOOP, PLAY_KEEP } |
| The motion play modes. More... | |
Public Member Functions | |
| ckMot () | |
| Constructs a motion. | |
| ~ckMot () | |
| Destructs this motion. | |
| void | init (ckMdl *mdl, ckID mot_data_id) |
| Initializes this motion. | |
| u16 | getMotionIndex () const |
| Returns the index of the current motion. | |
| PlayMode | getPlayMode () const |
| Returns the play mode. | |
| r32 | getPlaySpeed () const |
| Returns the play speed. | |
| u16 | getInterpFrame () const |
| Returns the number of the frames for interporation. | |
| bool | isPlaying () const |
| Returns whether playing motion. | |
| void | play (ckMdl *mdl, u16 mot_index, PlayMode play_mode, r32 play_speed, u16 interp_frame) |
| Plays the specified motion. | |
| void | stop () |
| Stops playing motion. | |
| r32 | getNextUpdateFrame () const |
| Returns the frame number of next updating time. | |
| void | update (ckMdl *mdl) |
| Updates this motion. | |
Friends | |
| class | ckJoin |
Classes | |
| struct | InterpInfo |
| enum ckMot::PlayMode |
Initializes this motion.
| [in] | mdl | A target model. |
| [in] | mot_data_id | The ID of motion data. |
| u16 ckMot::getMotionIndex | ( | ) | const |
Returns the index of the current motion.
| PlayMode ckMot::getPlayMode | ( | ) | const |
Returns the play mode.
| r32 ckMot::getPlaySpeed | ( | ) | const |
Returns the play speed.
| u16 ckMot::getInterpFrame | ( | ) | const |
Returns the number of the frames for interporation.
| bool ckMot::isPlaying | ( | ) | const |
Returns whether playing motion.
| void ckMot::play | ( | ckMdl * | mdl, | |
| u16 | mot_index, | |||
| PlayMode | play_mode, | |||
| r32 | play_speed, | |||
| u16 | interp_frame | |||
| ) |
Plays the specified motion.
| [in] | mdl | A target model. |
| [in] | mot_index | The index of a motion. |
| [in] | play_mode | A play mode. |
| [in] | play_speed | A play speed. |
| [in] | interp_frame | The number of the frames for interporation. |


Aimee Concepcion
About Me
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Psychic Game
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Osg genes OsNAC protein drought rice RNA-Seq target transgenic using OsNAC, domain direct Plant root family loci stress expression gene binding analysis transcription ChIP-Seq data tolerance (Fig. Table file genomic plants proteins plant roots {border-style RCc:MYC-OsNAC containing TFs px;} #ffffff;} enriched up-regulated used Additional involved factor including total Kim factors genes, targets DNA identified number performed plants. related (Osg) OsERF Fig. NAC RCc:OsNAC, TFs, Wang abiotic cell molecular promoter chromatin immunoprecipitation regions Arabidopsis LINK Sci analyses identify kb) reads regulatory sequence signaling water (XLSX S). associated directly functional mechanisms precursor px; regulated response results yield {font-family (Additional Cell OsNACs PCR RCc:MYC-OsNAC, RCc:OsNAC Transcription analysis. cellular conditions control distribution down-regulated expressed font-size grain individual membrane obtained previously protoplasts roots, samples tolerance, tolerance. value wall (Table ChIP Choi DNA-binding Gene Jung MYC Mol National Oryza OsbHLH article color double; metal million overexpression processes region regulation reporter respectively, respectively. responses solution thaliana transporter ’UTR, (ChIP)-Seq (GO) (Osg), AgriGO BMC DEGs Genomics Jeong Protein RCc:OsNACs a). activity biosynthesis bold border-color border-width coding detected development differentially distributed encoding enlarged enrichment expressing fused grown growth, information interactions intergenic lines luciferase multiple ontology overexpressing promoter, purified regions. responsive role sativa sequencing sets shown solid; specific superfamily terms transcripts transient transport/detoxification vesicle {font-style {font-weight (pH ./j.-...x ./s--- Auxin Chen Chromatin Chung Genome-wide Heavy Helix-loop-helix Hi-Seq However, Illumina Korea Molecular MtN Osg, RNA Red Research TIP; TTS Thus, Total Venn Xyloglucan Zhang based blot carbohydrate changes constructed courier; crop cv. database described downstream em; exon, final functions generated genes. genome-wide germin-like independent internal intrinsic intron, involving japonica levels light lines. member metabolic method min. networks patterns promoters provide pt;} regulate relative represent represents resistance respectively root-specific secondary selected sequences sequencing. sets. shared showed shows supplementary transcript transmembrane up- vesicle’ ‘cellular ‘cytoplasmic


com.google.code.yanf4j.util
Class LinkedTransferQueue<E>
java.lang.Object
java.util.AbstractCollection<E>
java.util.AbstractQueue<E>
com.google.code.yanf4j.util.LinkedTransferQueue<E>
- Type Parameters:
E
- the type of elements held in this collection
- All Implemented Interfaces:
- java.lang.Iterable<E>, java.util.Collection<E>, java.util.concurrent.BlockingQueue<E>, java.util.Queue<E>
public class LinkedTransferQueue<E>
- extends java.util.AbstractQueue<E>
- implements java.util.concurrent.BlockingQueue<E>
An unbounded TransferQueue based on linked nodes.
This queue orders elements FIFO (first-in-first-out) with respect
to any given producer. The head of the queue is that
element that has been on the queue the longest time for some
producer. The tail of the queue is that element that has
been on the queue the shortest time for some producer.
Beware that, unlike in most collections, the size
method is NOT a constant-time operation. Because of the
asynchronous nature of these queues, determining the current number
of elements requires a traversal of the elements.
This class and its iterator implement all of the
optional methods of the Collection
and Iterator
interfaces.
Memory consistency effects: As with other concurrent
collections, actions in a thread prior to placing an object into a
LinkedTransferQueue
happen-before
actions subsequent to the access or removal of that element from
the LinkedTransferQueue
in another thread.
- Author:
- Doug Lea, The Netty Project (netty-dev@lists.jboss.org), Trustin Lee<EMAIL_ADDRESS>|
Constructor Summary |
LinkedTransferQueue()
Creates an initially empty LinkedTransferQueue. |
LinkedTransferQueue(java.util.Collection<? extends E> c)
Creates a LinkedTransferQueue
initially containing the elements of the given collection,
added in traversal order of the collection's iterator. |
| Methods inherited from class java.util.AbstractQueue |
add, addAll, clear, element, remove |
| Methods inherited from class java.util.AbstractCollection |
contains, containsAll, remove, removeAll, retainAll, toArray, toArray, toString |
| Methods inherited from class java.lang.Object |
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait |
| Methods inherited from interface java.util.concurrent.BlockingQueue |
add, contains, remove |
| Methods inherited from interface java.util.Queue |
element, remove |
| Methods inherited from interface java.util.Collection |
addAll, clear, containsAll, equals, hashCode, removeAll, retainAll, toArray, toArray |
LinkedTransferQueue
public LinkedTransferQueue()
- Creates an initially empty LinkedTransferQueue.
LinkedTransferQueue
public LinkedTransferQueue(java.util.Collection<? extends E> c)
- Creates a LinkedTransferQueue
initially containing the elements of the given collection,
added in traversal order of the collection's iterator.
- Parameters:
c
- the collection of elements to initially contain
- Throws:
java.lang.NullPointerException
- if the specified collection or any
of its elements are null
put
public void put(E e)
throws java.lang.InterruptedException
- Specified by:
put
in interface java.util.concurrent.BlockingQueue<E>
- Throws:
java.lang.InterruptedException
offer
public boolean offer(E e,
long timeout,
java.util.concurrent.TimeUnit unit)
throws java.lang.InterruptedException
- Specified by:
offer
in interface java.util.concurrent.BlockingQueue<E>
- Throws:
java.lang.InterruptedException
offer
public boolean offer(E e)
- Specified by:
offer
in interface java.util.concurrent.BlockingQueue<E>
- Specified by:
offer
in interface java.util.Queue<E>
transfer
public void transfer(E e)
throws java.lang.InterruptedException
- Throws:
java.lang.InterruptedException
tryTransfer
public boolean tryTransfer(E e,
long timeout,
java.util.concurrent.TimeUnit unit)
throws java.lang.InterruptedException
- Throws:
java.lang.InterruptedException
tryTransfer
public boolean tryTransfer(E e)
take
public E take()
throws java.lang.InterruptedException
- Specified by:
take
in interface java.util.concurrent.BlockingQueue<E>
- Throws:
java.lang.InterruptedException
poll
public E poll(long timeout,
java.util.concurrent.TimeUnit unit)
throws java.lang.InterruptedException
- Specified by:
poll
in interface java.util.concurrent.BlockingQueue<E>
- Throws:
java.lang.InterruptedException
poll
public E poll()
- Specified by:
poll
in interface java.util.Queue<E>
drainTo
public int drainTo(java.util.Collection<? super E> c)
- Specified by:
drainTo
in interface java.util.concurrent.BlockingQueue<E>
drainTo
public int drainTo(java.util.Collection<? super E> c,
int maxElements)
- Specified by:
drainTo
in interface java.util.concurrent.BlockingQueue<E>
iterator
public java.util.Iterator<E> iterator()
- Specified by:
iterator
in interface java.lang.Iterable<E>
- Specified by:
iterator
in interface java.util.Collection<E>
- Specified by:
iterator
in class java.util.AbstractCollection<E>
peek
public E peek()
- Specified by:
peek
in interface java.util.Queue<E>
isEmpty
public boolean isEmpty()
- Specified by:
isEmpty
in interface java.util.Collection<E>
- Overrides:
isEmpty
in class java.util.AbstractCollection<E>
hasWaitingConsumer
public boolean hasWaitingConsumer()
size
public int size()
- Returns the number of elements in this queue. If this queue
contains more than Integer.MAX_VALUE elements, returns
Integer.MAX_VALUE.
Beware that, unlike in most collections, this method is
NOT a constant-time operation. Because of the
asynchronous nature of these queues, determining the current
number of elements requires an O(n) traversal.
- Specified by:
size
in interface java.util.Collection<E>
- Specified by:
size
in class java.util.AbstractCollection<E>
- Returns:
- the number of elements in this queue
getWaitingConsumerCount
public int getWaitingConsumerCount()
remainingCapacity
public int remainingCapacity()
- Specified by:
remainingCapacity
in interface java.util.concurrent.BlockingQueue<E>
Copyright © 2011. All Rights Reserved.


Hey, let's play a small game all you have to do is fill all these text fileds. To help you,
you can read the rule that is implemented below.
Good luck!
const email = new Rule({
type: 'email',
domain: d => ['hotmail', 'outlook', 'gmail'].indexOf(d) !== -1,
});
const PhoneNumber = new Rule({
type: 'string-int',
minLength: 10,
maxLength: 10,
match: /0(7|6).*/,
})
const PassWord = new Rule({
type: 'password',
minLength: 8,
maxLength: 10,
matchesOneOf: ['@', '_', '-', '.', '?', '$'],
numbers: 1,
uppercase: 1,
});
const url = new Rule({
type: 'url',
domain: domain => domain === 'github.com',
protocol: protocol => protocol === 'https',
});
const country = new Rule({
type: 'string',
oneOf: ['FR', 'US', 'EN'],
});
const zipcode = new Rule({
type: 'string-int',
minLength: 5,
maxLength: 5,
});
const street = new Rule({
type: 'string',
notEmpty: true,
});
const streetNumber = new Rule({
type: 'string-int',
});
Last game.
Edit the code so that you have at least two valid tests!


To get things done
Fill in what you need to get done, and hit 'add'
Add
The things I need to get done:
Your free! You have nothing to do!
Clear all tasks


{% extends "base.html" %} {% block css %} {% load static %} {% endblock %} {% block content %}
Insert the email address where you would like us to send the password reset details.
{{ form.email }}


Massive.js 3.0: A Postgres-centric Data Access Tool
Massive.js is a data mapper for Node.js that goes all in on PostgreSQL and fully embraces the power and flexibility of the SQL language and relational metaphors. Providing minimal abstractions for the interfaces and tools you already use, its goal is to do just enough to make working with your data as easy and intuitive as possible, then get out of your way.
Massive is not an object-relational mapper (ORM)! It doesn't use models, it doesn't track state, and it doesn't limit you to a single entity-based metaphor for accessing and persisting data. You've already got a data model: your schema. Massive introspects your database at runtime and returns a connected instance with your tables, views, functions, and scripts attached and ready to query, write, or execute.
Here are some of the high points:
- Dynamic query generation: Massive features a versatile query builder with support for a wide variety of operators, all generated from a simple criteria object.
- Do as much, or as little, as you need: if you're coming from an ORM background, you might be expecting to have to create or load an entity instance before you can write it to the database. You don't. As long as you don't run afoul of
NOT NULL
constraints, you can emit inserts and updates which affect only the columns you actually need to write and make up the data on the spot. - Document storage: PostgreSQL's JSONB storage type makes it possible to blend relational and document strategies. Massive offers a robust API to simplify working with documents: objects in, objects out, with document metadata managed for you.
- Postgres everything: committing to a single RDBMS allows us to leverage it to the fullest extent possible. Massive supports array fields, JSON storage, pattern matching with regular expressions, and many, many more features found in PostgreSQL but not in other databases.
Full Documentation
Full documentation including API docs is available on GitHub Pages.
Table of Contents
Installation
npm i massive --save
Starting with version 3, Massive uses Promises exclusively. If you need a callback-based API, download version 2.x from the Releases page.
Examples are presented using the standard then()
construction for compatibility, but use of ES2017 async
and await
or a flow control library such as co to manage promises is highly recommended.
Quickstart
Once installed, require
the library and connect to your database with a parameter object or connection string:
const massive = require('massive');
massive({
host: '<IP_ADDRESS>',
port: 5432,
database: 'appdb',
user: 'appuser',
password: 'apppwd'
}).then(db => {...});
When you instantiate Massive, it introspects your database for tables, views, and functions. Along with files in your scripts directory (/db
by default), these become an API that allows you to query database objects and execute scripts and functions. This initialization process is fast, but not instantaneous, and you don't want to be doing it every time you run a new query. Massive is designed to be initialized once, with the instance retained and used throughout the rest of your application. In Express, you can store it with app.set
in your entry point and retrieve it with req.app.get
in your routes; with koa, using app.context
. If no such mechanism is available, you can take advantage of Node's module caching to require the object as necessary.
Raw SQL
Need to get weird? Massive offers a lot of features for interacting with your database objects in abstract terms which makes bridging the JavaScript-Postgres divide much easier and more convenient, but sometimes there's no way around handcrafting a query. If you need a prepared statement, consider using the scripts directory (see below) but if it's a one-off, there's always db.run
.
db.run('select * from tests where id > $1', [1]).then(tests => {
// all tests matching the criteria
});
run
takes named parameters as well:
db.run('select * from tests where id > ${something}', {something: 1}).then(tests => {
// all tests matching the criteria
});
Tables and Views
Massive loads all views (including materialized views), all tables having primary key constraints, and foreign tables (which cannot have primary keys). Unlike object/relational mappers, Massive does not traverse relationships or build model trees. Limited support for mapping complex result objects is a potential future consideration, but if you need to correlate data from multiple tables using a view is recommended.
Schemas
Massive understands database schemas and treats any schema other than the default public
as a namespace. Objects bound to the public
schema are attached directly to the database object, while other schemas will be represented by a namespace attached to the database object, with their respective tables and views bound to the namespace.
// query a table on the public schema
db.tests.find(...).then(...);
// query a table on the auth schema
db.auth.users.find(...).then(...);
Criteria Objects
Many functions use criteria objects to build a query WHERE clause. A criteria object is a JavaScript map matching database fields to values. Unless otherwise specified in the field name, the predicate operation is assumed to be equality. Massive's query builder is extremely flexible and accommodates both standard and Postgres-specific predicates, including JSON object traversal and array and regexp operations.
{
'field': 'value', // equality
'field <>': 'value', // inequality
'field': [1, 2, 3], // IN (x, y, z) tests
'field >': 1, // greater than
'field <=': 1, // less than or equal
'field BETWEEN': [1, 100], // BETWEEN
'field LIKE': 'val%', // LIKE
'field NOT ILIKE': 'Val%', // NOT LIKE (case-insensitive)
'field ~': 'val[ue]+', // regexp match
'field !~*': 'Val[ue]+', // no regexp match (case-insensitive)
'field @>': ['value', 'Value'], // array contains
'field ->> attr': 'value' // JSON traversal
}
There are many more; see the full documentation for the complete list.
Query Options
The finder functions -- find
, findOne
, findDoc
, search
, and searchDoc
-- allow usage of an options object as the second argument. Like the criteria object, this is an ordinary JavaScript map; however, the field names are fixed. Any field may be omitted if not needed.
{
build: true, // return query text and parameters without executing anything
document: true, // query is against a document table (see below)
order: 'id desc', // creates an ORDER BY clause to enforce sorting
orderBody: true, // force order to apply to fields in a document body instead of the table fields
offset: 20, // adds an OFFSET to skip the first n rows
limit: 10, // adds a LIMIT to restrict the number of rows returned
single: true, // force returning the first result object instead of a results array
stream: true, // return results as a readable stream (see below)
only: true // restrict the query to the target table, ignoring descendant tables
}
Querying
findOne finds a single object with a primary key or a criteria object.
db.tests.findOne(1).then(test1 => {
// the test with ID 1
});
db.tests.findOne({
is_active: true,
'version >': 1,
'name ilike': 'home%'
}).then(tests => {
// the first active test with a higher version and a name matching ILIKE criteria
});
find
is a general-purpose query function which returns a result list.
db.tests.find({
is_active: true,
'version >': 1,
'name ilike': 'home%'
}, {
columns: ['name', 'version'],
order: 'created_at desc',
offset: 20,
limit: 10
}).then(tests => {
// all active tests with higher versions and a name matching ILIKE criteria
// options are not required; these set the select list and results ordering, offset, and limit
});
count
returns the resultset length.
db.tests.count({
is_active: true,
'version >': 1,
'name ilike': 'home%'
}).then(count => {
//
});
search
performs full-text searches.
db.tests.search({
fields: ["name"],
term: "home"}
).then(tests => {
// all tests with 'home' in the name
});
where
allows you to write your own WHERE clause instead of using a criteria object.
db.tests.where('is_active = $1 AND version > $2', [true, 1]).then(tests => {
// all active tests with higher versions
});
Persisting
save
performs an upsert, inserting if the object has no primary key value and updating if it does. save
can only be used with local tables, since foreign tables do not have primary keys to test.
db.tests.save({
version: 1,
name: 'homepage'
}).then(tests => {
// an array containing the newly-inserted test
});
db.tests.save({
id: 1,
version: 2,
priority: 'high'
}).then(tests => {
// an array containing the updated test; note that the name will not have changed!
});
insert
creates a new row or rows (if passed an array).
db.tests.insert({
name: 'homepage',
version: 1
}).then(tests => {
// an array containing the newly-inserted test
});
db.tests.insert([{
name: 'homepage',
version: 1
}, {
name: 'about us',
version: 1
}]).then(tests => {
// an array containing both newly-inserted tests
});
update
has two variants. Passed an object with a value for the table's primary key field, it updates all included fields of the object based on the primary key; or, passed a criteria object and a changes map, it applies all changes to all rows matching the criteria. Only the latter variant can be used with foreign tables.
db.tests.update({
id: 1,
version: 2,
priority: 'high'
}).then(tests => {
// an array containing the updated test
});
db.tests.update({
priority: 'high'
}, {
priority: 'moderate'
}).then(tests => {
// an array containing all tests which formerly had priority 'high'
// since this issues a prepared statement note that the version field cannot be incremented here!
});
Documents
Postgres' JSONB functionality allows for a more free-form approach to data than relational databases otherwise support. Working with JSONB fields is certainly possible with the suite of standard table functions, but Massive also allows the dynamic creation and usage of dedicated document tables with a separate set of functions.
Document tables consist of some metadata, including the primary key, and a body
JSONB field. A GIN index is also created for the document body and a full-text search vector to speed up queries. When querying a document table, the primary key is added to the body
; when persisting, it is pulled off and used to locate the record.
saveDoc
writes a document to the database. It may be invoked from the database object itself in order to create the table on the fly.
db.saveDoc('reports', {
title: 'Week 12 Throughput',
lines: [{
name: '1 East',
numbers: [5, 4, 6, 6, 4]
}, {
name: '2 East',
numbers: [4, 4, 4, 3, 7]
}]
}).then(report => {
// the reports table has been created and the initial document is assigned a primary key value and returned
});
If the document table already exists, saveDoc
can be invoked on it just as the standard table functions are. This function performs an insert if no id
is provided, or an update otherwise. The entire document will be added or modified; for partial changes, use modify
.
db.reports.saveDoc({
id: 1, // omit in order to insert
title: 'Week 12 Throughput',
lines: [{
name: '1 East',
numbers: [5, 4, 6, 6, 4]
}, {
name: '2 East',
numbers: [4, 4, 4, 3, 7]
}]
}).then(report => {
// the newly created report
});
modify
adds and updates fields in an existing document (or any JSON/JSONB column) without replacing the entire body. Fields not defined in the changes
object are not modified.
db.reports.modify(1, {
title: 'Week 11 Throughput'
}).then(report => {
// the updated report, with a changed 'title' attribute
});
db.products.modify(1, {
colors: ['gray', 'purple', 'red']
}, 'info').then(widget => {
// the product with an 'info' field containing the colors array
});
Much of the standard queryable API has corresponding functionality with document tables. Document query functions only use criteria objects and (in the case of findDoc
) primary key values. Simple criteria objects, testing equality only, can leverage the GIN index on the document table for improved performance.
db.reports.countDoc({
'title ilike': '%throughput%'
}).then(count => {
// number of matching documents
});
db.reports.findDoc(1).then(report => {
// the report document body with the primary key included
});
db.reports.findDoc({
'title ilike': '%throughput%'
}).then(reports => {
// all report documents matching the criteria
});
db.reports.searchDoc({
fields : ["title", "description"],
term : "Kauai"
}.then(docs => {
// reports returned with an on-the-fly full text search for 'Kauai'
});
Deleting
There's only one function to delete data: destroy
, which takes a criteria object. To destroy a document, use the primary key or specify JSON traversal operations in the criteria object.
db.tests.destroy({
priority: 'high'
}).then(tests => {
// an array containing all removed tests
});
Functions and Scripts
Object-relational mappers tend to ignore functions. For many, the database exists solely as a repository, with data manipulation reserved for application logic and external jobs.
To be fair, this setup is perfectly sufficient for many use cases. But when it isn't, it hurts. With functions, you can perform complex operations on your data at a scope and speed unrivaled by anything else. Why go to the trouble of querying bulk data into another system and manipulating it -- only to put it back where it was with a second trip across the wire? Especially when there's a powerful, flexible language purpose-built for set operations right there? You wouldn't work that way, and Massive won't make you: functions are first-class citizens as far as it's concerned.
Massive actually loads functions from two locations: the database itself, and a /db directory in your project root which contains prepared statements in .sql script files (the location may be changed by passing a scripts
parameter on initialization). Subdirectories in /db are, like schemas, treated as namespaces; although, unlike schemas, they may be nested.
Functions and scripts are loaded onto the database object and can be invoked directly:
db.uuid_generate_v1mc().then(arr => {
// an array containing the generated UUID (requires the uuid-ossp extension)
});
db.myTestQueries.restartTests([5, true]).then(results => {
// this runs the prepared statement in db/myTestQueries/restartTests.sql with the above parameters and returns any output from a RETURNING clause
});
Like run
, prepared statements in script files can use named parameters instead of $1
-style indexed parameters. Named parameters are formatted ${name}
. Other delimiters besides braces are supported; consult the pg-promise documentation for a full accounting.
db.myTestQueries.restartTests({category: 5, force: true}).then(results => {
// as above; the prepared statement should use ${category} and ${force} instead of $1 and $2.
});
Streams
To improve performance with large result sets, you might want to consider using a stream instead of getting your results in an array all at once. This has the upside of returning something to read right away (which can be a big deal for slow queries too!), but the price is that the connection remains open until you're done. To turn on streaming, add {stream: true}
to your options object.
db.tests.find({priority: 'low'}, {stream: true}).then(stream => {
const tests = [];
stream.on('readable', () => {
tests.push(stream.read());
});
stream.on('end', () => {
// do something with tests here
});
});
Accessing the Driver
Massive is focused on convenience and simplicity, not completeness. There will always be features we don't cover; that's why there's db.run
for arbitrary queries. In the same vein, Massive exposes the pg-promise driver (as db.pgp
) and connected instance (as db.instance
) so client code can easily use its lower-level functions when necessary.
REPL
Massive.js ships with a REPL (read-evaluate-print loop), an interactive console that lets you connect to a database and execute JavaScript code. The easiest way to run it is to install globally:
npm i -g massive
You can then fire up a connection and start writing JavaScript:
massive -d appdb
db > db.tables.map(table => table.name);
[ 'tests',
'users' ]
db > db.tests.find({priority: 'low'}).then(...);
In addition to the tables
collection, the views
and functions
collections are also exposed on the database object.
When invoking functions, you may omit the then
if you just want to see output -- Massive provides a resolver which logs the results to make it easy to query with the REPL.
Exit the REPL by pressing Ctrl-C twice.
Older Versions
Release versions are tagged and available here.
Documentation for Massive.js 2.x is at readthedocs.
 If you've found a bug, please include a minimal code sample I can use to hunt the problem down.
To run the tests, first create an empty massive
database. The postgres
superuser should have trust
authentication enabled for local socket connections.
createdb massive
Run the tests with npm:
npm test


history of honda motors company - Extensions
History of the Honda Motor Company - Video Dailymotion Sep 25, 2011 . WatchMojo takes a look at the history of the Honda Motor Company, from its popular motorcycles to the Civic and the Accord. http://www.dailymotion.com/video/xlary6_history-of-the-honda-motor-company_tech
You can develop your own extensions
using the vantora flat hdmi cable.
Syntax-Highlighting Addons
Honda Motor Co.,Ltd.: Honda Worldwide Honda Motor Co.,Ltd. Honda Worldwide - Visit the official Honda global web site and find information on all Honda Motor and its subsidiaries and affiliates. . History, - Honda R&D, - Design, -- Behind the Scenes of Honda Design, -- 42nd . http://world.honda.com/
Honda History Honda Motor Company is by far the world's biggest motorcycle maker. Honda's first motorcycle was born out of necessity in immediate post World War II Japan, . http://smokeriders.com/History/Honda_History/body_honda_history.html in one installer (526 kb).
Honda In 1948, Honda Motor Company was established with the financial backing from investors. . In 1972, Honda launched the most important car in its history, Civic. http://www.autozine.org/Manufacturer/Japan/Honda.html
Honda Motor Company is incorporated History.com This Day in ... On this day, motorcycle builder Soichiro Honda incorporated the Honda Motor Company in Hamamatsu, Japan. http://www.history.com/this-day-in-history/honda-motor-company-is-incorporated
Honda - Historic Timeline HISTORY BY DECADE. 1947. Honda produces its first product, the A-type bicycle engine. 100% Loaded. 1959. On June 11, American Honda Motor Co., Inc. is . http://corporate.honda.com/america/timeline.aspx
A simple JavaScript Formatter (47kb)History of Honda Motor Company Limited FundingUniverse Company History: Honda Motor Company Limited is perhaps best known as an automaker--it is the third largest automaker in Japan--but the company has its . http://www.fundinguniverse.com/company-histories/honda-motor-company-limited-history/
Honda Motor Company, Ltd. (HMC) Dividend History - Nasdaq.com Honda Motor Company, Ltd. (HMC) Dividend History - find dividend history and stay alerted to dividend announcements for HMC and all the companies you . http://www.nasdaq.com/symbol/hmc/dividend-history CertMaker for iOS and Android
Honda Motor Company, Ltd. (Japanese corporation) -- Britannica ... Login | Subscribe. Contributors; History; Citations . Honda Motor Company, Ltd.: 10,000,000th Honda vehicle made in North America rolling. leading Japanese . http://www.britannica.com/EBchecked/topic/270748/Honda-Motor-Company-Ltd
Windows 8 AppContainer Loopback Utility
HMC Historical Prices | Honda Motor Company, Ltd. Commo Stock ... Discover historical prices for HMC stock on Yahoo! Finance. View daily, weekly or monthly format back to when Honda Motor Company, Ltd. Commo stock was . http://finance.yahoo.com/q/hp?s=HMC Download
Now (60kb) or
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Traffic Differ
Honda Motor Company Founded (1948) - This Day in History - English ... Honda Motor Company Founded (1948) In 1946, Japanese mechanic, race car driver, and self-taught engineer Soichiro Honda founded a . http://forum.thefreedictionary.com/postst19257_Honda-Motor-Company-Founded--1948-.aspx Download now (47kb).
SAZ Clipboard
Honda History - Auto and Motorcycle History, Soichiro Honda Honda History - a Time Line of American Honda Motor Co., Inc. - Soichiro Honda establishes the Honda Technical Research Institute. Honda produces its first . http://corporate.honda.com/america/history.aspx
Gallery
The Gallery extension (50kb) Honda Worldwide | History Highlights from Honda's History: See the photos, and read the episodes straight from . Copyright, Honda Motor Co., Ltd. and its subsidiaries and affiliates. http://world.honda.com/history/
Honda - Wikipedia, the free encyclopedia From a young age, Honda's founder, Soichiro Honda (?? ???, . Honda Motor Company grew in a short time to become the world's . http://en.wikipedia.org/wiki/Honda
AnyWHERE (sample)
The AnyWHERE extension (40kb) Honda Corporate - Vision, Offices, Headquarters, Corporate History . to Honda Corporate, the official online headquarters of the American Honda Motor Company, Inc. The Honda . Honda corporate vision, offices, headquarters and corporate history. http://corporate.honda.com/
RulesTab (sample)
All About The Honda Motor Company Learn about the history of the Honda Motor Company and information about the company today. The Honda Motor Company is best known for producing . http://www.essortment.com/honda-motor-company-57429.html
Privacy Scanner
The Privacy Scanner
(41kb) Honda Worldwide | History This was the opening passage of a Honda Motor Company history published for the seventh anniversary of the founding. The president, of course, was Soichiro . http://world.honda.com/history/limitlessdreams/encounter/text01/
Content-Blocking (sample)
The Content Blocker
sample (11kb) Honda Motor Co., Ltd. (ADR) Stock Quote HMC | DailyFinance American Honda Motor Co. v. V.M. Paolozzi Imports, 7:10-CV-955. 3/28/2013 by New York Law Journal. New York Auto Show Winners and Losers. 3/28/2013 . http://www.dailyfinance.com/quote/nyse/honda-motor-co-ltd-adr/hmc
Image-Flipper (sample)
The Image
Flipper sample (6kb) Honda Accord History for HONDA MOTOR CO LTD (HMC) Honda Motor Company (HMC) . 25 years that Car and Driver editors have been conducting the competition, more than any other vehicle in the award's history. http://www.wikinvest.com/stock/Honda_Motor_Company_(HMC)/Honda_Accord_History
3rd-Party Extensions
Honda Motor Company, Ltd. Commo Stock Chart | HMC Interactive ... 6 days ago . Interact with the HMC stock chart on Yahoo! Finance. Change the date range, view event overlays and compare Honda Motor Company, Ltd. http://finance.yahoo.com/echarts?s=HMC+Interactive
HMC Profile | Honda Motor Company, Ltd. Commo Stock - Yahoo ... See the company profile for Honda Motor Company, Ltd. Commo (HMC) . Historical chart data and daily updates provided by Commodity Systems, Inc. ( CSI). http://finance.yahoo.com/q/pr?s=hmc
neXpert Performance Report Generator
Honda's History » About Honda » Honda New Zealand History. The Honda Motor Co Ltd is recognised internationally as being one of the leading manufacturers of automobiles, motorcycles and power equipment in . http://www.honda.co.nz/abouthonda/history/
StresStimulus
HMC: Summary for Honda Motor Company, Ltd. Commo- Yahoo ... Change the date range, chart type and compare Honda Motor Company, Ltd. . Historical chart data and daily updates provided by Commodity Systems, Inc. http://finance.yahoo.com/q?s=HMC
Watcher - Passive Security Auditor
History of the Honda Motor Company video from Answers.com Videos Though this company is famous for its cars, it actually started as a motorcycle manufacturer. WatchMojo takes a look at the history of the Honda Motor Company, . http://video.answers.com/history-of-the-honda-motor-company-517166340
Japan: Tokyo:7267 Stock Price Today - Honda Motor Co. Ltd. Stock ... Honda Motor Co. . QUICK LINKS 7267 : Interactive Charting; Insider Trading; Options; Historical Prices; Time & Sales Data . Honda Sees March Sales Gain . http://quotes.wsj.com/JP/7267
Ammonite - Security Scanner
Honda Company Slideshow Feb 5, 2009 . Marissa Doria Block 3; History of Honda. 1946Soichiro . 1959American Honda Motor Company Incorporated opens in Los Angelas . http://www.slideshare.net/Doriam/honda-company-slideshow
Honda Motor Co Ltd, 7267:TYO company performance - FT.com Get latest Honda Motor Co Ltd (7267:TYO) share price including interactive charts, historical prices, comparative analysis, forecasts, business profile and more. http://markets.ft.com/research/Markets/Tearsheets/Summary?s=7267:TYO
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x5s - Automated XSS Security Testing AssistantHonda Motor Co Ltd: TYO:7267 quotes & news - Google Finance Get detailed financial information on Honda Motor Co Ltd (TYO:7267) including real-time stock quotes, historical charts & financial news, all for free! http://www.google.com/finance?cid=674891
- Detecting where safe encodings were not applied to emitted
user-inputs
- Detecting where Unicode character transformations might bypass
security filters
- Detecting where non-shortest UTF-8 encodings might bypass security
filters
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intruder21
The History of Honda: Motorcycles to the Civic and Accord - YouTube Sep 23, 2011 . WatchMojo.com takes a look at the history of the Honda Motor Company, from its popular motorcycles to the Civic and the Accord. http://www.youtube.com/watch?v=HZ26tYbN8GU
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HTML Inspector
Honda Worldwide | Overview Company Name Honda Motor Co., Ltd. Head Office 1-1, 2-chome, Minami- Aoyama, Minato-ku, Tokyo 107-8556, Japan Tel: +81-(0)3-3423-1111. Established . http://world.honda.com/profile/overview/
Honda Motor Co., Ltd. - New York Stock Exchange Feb 11, 1977 . Honda Motor Co., Ltd. (Honda) develops, produces and . The Company has four business segments. . Corporate History/Profile · Financial . http://www.nyse.com/listed/hmc.html
WCF Binary-Encoded Message Inspector
Honda Reviews - Honda Cars | Edmunds Honda cars: research Honda cars, read Honda reviews, find Honda car listings and get Honda pricing & dealer quotes. . Read more Honda history. honda . http://www.edmunds.com/honda/
Chad Sowald's Request-To-Code
Honda Worldwide | Profile Honda Worldwide - Visit the official Honda global web site and find information on all Honda Motor and its subsidiaries and affiliates. . Corporate Profile. Company Overview: Details of Honda's Head Office. Honda Philosophy: Honda's Basic . http://world.honda.com/profile/
Eyal's Extensions
- smith's landing watervliet michigan has written two extensions:
Thomas Deml's Export WCAT Script extension
HONDA MOTOR CO LTD-SPONS ADR (HMC:New York): Stock ... HONDA MOTOR CO LTD-SPONS ADR (HMC) stock price & investing information . Find HONDA MOTOR CO LTD-SPONS ADR historical stock quotes, key . http://investing.businessweek.com/research/stocks/snapshot/snapshot.asp?ticker=HMC
Per-Response Latency Extension
Honda | Cambodia | About Us - Honda Motor Co.,Ltd. Company Name Honda Motor Co., Ltd. Head Office 1-1, 2-chome, Minami- Aoyama, Minato-ku, Tokyo 107-8556, Japan Tel: +81-(0)3-3423-1111. Established . http://www.honda.com.kh/abouthonda/
WPAD Server
Honda Motor Co Ltd : Honda Automoveis do Brasil Reaches 1 ... Dec 19, 2012 . Honda Motor Co Ltd : Honda Automoveis do Brasil Reaches 1 Million . December 14, 2012 - 2012 has been a historical year for Honda . http://www.4-traders.com/HONDA-MOTOR-CO-LTD-6492457/news/Honda-Motor-Co-Ltd-Honda-Automoveis-do-Brasil-Reaches-1-Million-Vehicles-Sold-in-Brazil-15659810/
XML Request InspectorHonda Motor Co. Ltd. ADS, HMC Stock Quote - (NYSE) HMC ... Ways to track Honda Motor Co. Ltd. ADS. Facebook . Historical and current end -of-day data provided by SIX Financial Information. Intraday data delayed per . http://www.marketwatch.com/investing/stock/hmc XML DataSet InspectorThe History of the Honda Motor Co. Ltd. | eHow.com The History of the Honda Motor Co. Ltd.. Honda Motor Co. has a reputation in Japan and the United States for making quality cars at affordable prices. Honda . http://www.ehow.com/about_5045790_history-honda-motor-co-ltd.html
©2013 Telerik
|


Former Democratic Party chairman Albert Ho attacked in Tin Hau
Former Democratic Party lawmaker Albert Ho Chun-yan was attacked by unidentified men in Tin Hau on Tuesday.
Ho, who currently chairs the Hong Kong Alliance in Support of Patriotic Democratic Movements in China, organizer of the June 4 candlelight vigils, told media that he was about to leave Tin Hau MTR Station at around 7 p.m., when he was told by residents that several black-clad men were right outside, but he did not mind their warning.
As he was walking on an alley near the Central Library, he noticed that he was being tailed by several people, who then started assaulting him with long, hard objects that appeared to be canes, Ho said.
After the assailants fled, Ho said he was able to hail a taxi and went to Ruttonjee Hospital, where he received medical treatment for six or seven welts on his back and injuries to both arms.
Ho said his right arm had to be in a cast due to a slight bone fracture, adding that he has reported the incident to the police, the Hong Kong Economic Journal reported.
Back in 2006, Ho was attacked by club-wielding men at a McDonald’s outlet in Central.
Tuesday night’s attack came only a few days before the District Council elections scheduled for Sunday, but Ho said he did not want to speculate any link between the incident and the coming polls.
He said many politicians have become targets of violence over the past months, but he had not received any specific threat recently, nor would he try to guess the motives of the attackers, RTHK reported.
In a statement issued on Tuesday night, pan-democratic lawmakers strongly condemned the attack on Ho, and urged the police to bring the culprits to justice promptly.
– Contact us at<EMAIL_ADDRESS>TL/JC/CG


Home > Grids
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WIAA D5: Lake Country Lutheran storms back, tops Stratford 22-13
by FOX Sports WisconsinThings weren’t looking great for Lake Country Lutheran early on.
Stratford scored on its opening two possessions — a two-yard run by Beau Gross and a 17-yard strike to Justin Radke from quarterback Max Schwabe — to open a 13-0 lead.
The tides turned, however, late in the second quarter.
After being stopped on its first four drives of the game, Lake Country Lutheran used a bit of trickery to get into the end zone, as Andrew Schumacher caught a five-yard pass from receiver Jacob Studer to make it 13-6.
The Lightning never looked back.
Lake Country Lutheran went on to score 22 unanswered points to erase the 13-point deficit and secure the D5 championship with a 22-13 victory — the school’s first football title since it opened in 1999.
Quarterback Luke Haertle put the Lightning ahead for good with a 20-yard touchdown rush with four minutes to play.
Chase Caliendo was a monster on the defensive line, logging 3.5 sacks and the game-sealing safety in the fourth quarter.
Haertle and Schumacher put on a show, as the two connected for five receptions for 97 yards and two scores. Zech Hans tallied four catches for 105 yards and also intercepted a pass from backup quarterback Chandler Schmidt on a trick play in the fourth.
Stratford has now suffered two consecutive losses in the D5 state championship. The Tigers fell 20-17 to St. Mary’s Springs last year. Stratford hasn’t won a state title since taking home six straight championships from 2003-08.


This is a tool for analyzing the way your time is divided. A timer is always running, because time is always passing.
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This is a tool for analyzing the way your time is divided. A timer is always running, because time is always passing.
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NumPy NdarrayNdarray is the n-dimensional array object defined in the numpy which stores the collection of the similar type of elements. In other words, we can define a ndarray as the collection of the data type (dtype) objects. The ndarray object can be accessed by using the 0 based indexing. Each element of the Array object contains the same size in the memory. Creating a ndarray objectThe ndarray object can be created by using the array routine of the numpy module. For this purpose, we need to import the numpy. Consider the below image. We can also pass a collection object into the array routine to create the equivalent n-dimensional array. The syntax is given below. The parameters are described in the following table.
To create an array using the list, use the following syntax. To create a multi-dimensional array object, use the following syntax. To change the data type of the array elements, mention the name of the data type along with the collection. Finding the dimensions of the ArrayThe ndim function can be used to find the dimensions of the array. Finding the size of each array elementThe itemsize function is used to get the size of each array item. It returns the number of bytes taken by each array element. Consider the following example. ExampleOutput: Each item contains 8 bytes. Finding the data type of each array itemTo check the data type of each array item, the dtype function is used. Consider the following example to check the data type of the array items. ExampleOutput: Each item is of the type int64 Finding the shape and size of the arrayTo get the shape and size of the array, the size and shape function associated with the numpy array is used. Consider the following example. ExampleOutput: Array Size: 7 Shape: (1, 7) Reshaping the array objectsBy the shape of the array, we mean the number of rows and columns of a multi-dimensional array. However, the numpy module provides us the way to reshape the array by changing the number of rows and columns of the multi-dimensional array. The reshape() function associated with the ndarray object is used to reshape the array. It accepts the two parameters indicating the row and columns of the new shape of the array. Let's reshape the array given in the following image. ExampleOutput: printing the original array.. [[1 2] [3 4] [5 6]] printing the reshaped array.. [[1 2 3] [4 5 6]] Slicing in the ArraySlicing in the NumPy array is the way to extract a range of elements from an array. Slicing in the array is performed in the same way as it is performed in the python list. Consider the following example to print a particular element of the array. ExampleOutput: 2 5 The above program prints the 2nd element from the 0th index and 0th element from the 2nd index of the array. LinspaceThe linspace() function returns the evenly spaced values over the given interval. The following example returns the 10 evenly separated values over the given interval 5-15 ExampleOutput: [ 5. 6.11111111 7.22222222 8.33333333 9.44444444 10.55555556 11.66666667 12.77777778 13.88888889 15. ] Finding the maximum, minimum, and sum of the array elementsThe NumPy provides the max(), min(), and sum() functions which are used to find the maximum, minimum, and sum of the array elements respectively. Consider the following example. ExampleOutput: The array: [ 1 2 3 10 15 4] The maximum element: 15 The minimum element: 1 The sum of the elements: 35 NumPy Array AxisA NumPy multi-dimensional array is represented by the axis where axis-0 represents the columns and axis-1 represents the rows. We can mention the axis to perform row-level or column-level calculations like the addition of row or column elements. To calculate the maximum element among each column, the minimum element among each row, and the addition of all the row elements, consider the following example. ExampleOutput: The array: [[1 2 30] [10 15 4]] The maximum elements of columns: [10 15 30] The minimum element of rows [1 4] The sum of all rows [33 29] Finding square root and standard deviationThe sqrt() and std() functions associated with the numpy array are used to find the square root and standard deviation of the array elements respectively. Standard deviation means how much each element of the array varies from the mean value of the numpy array. Consider the following example. ExampleOutput: [[1. 1.41421356 5.47722558] [3.16227766 3.87298335 2. ]] 10.044346115546242 Arithmetic operations on the arrayThe numpy module allows us to perform the arithmetic operations on multi-dimensional arrays directly. In the following example, the arithmetic operations are performed on the two multi-dimensional arrays a and b. ExampleArray ConcatenationThe numpy provides us with the vertical stacking and horizontal stacking which allows us to concatenate two multi-dimensional arrays vertically or horizontally. Consider the following example. ExampleOutput: Arrays vertically concatenated [[ 1 2 30] [10 15 4] [ 1 2 3] [12 19 29]] Arrays horizontally concatenated [[ 1 2 30 1 2 3] [10 15 4 12 19 29]]
Next TopicNumPy DataTypes
|
NumPy NdarrayNdarray is the n-dimensional array object defined in the numpy which stores the collection of the similar type of elements. In other words, we can define a ndarray as the collection of the data type (dtype) objects. The ndarray object can be accessed by using the 0 based indexing. Each element of the Array object contains the same size in the memory. Creating a ndarray objectThe ndarray object can be created by using the array routine of the numpy module. For this purpose, we need to import the numpy. Consider the below image. We can also pass a collection object into the array routine to create the equivalent n-dimensional array. The syntax is given below. The parameters are described in the following table.
To create an array using the list, use the following syntax. To create a multi-dimensional array object, use the following syntax. To change the data type of the array elements, mention the name of the data type along with the collection. Finding the dimensions of the ArrayThe ndim function can be used to find the dimensions of the array. Finding the size of each array elementThe itemsize function is used to get the size of each array item. It returns the number of bytes taken by each array element. Consider the following example. ExampleOutput: Each item contains 8 bytes. Finding the data type of each array itemTo check the data type of each array item, the dtype function is used. Consider the following example to check the data type of the array items. ExampleOutput: Each item is of the type int64 Finding the shape and size of the arrayTo get the shape and size of the array, the size and shape function associated with the numpy array is used. Consider the following example. ExampleOutput: Array Size: 7 Shape: (1, 7) Reshaping the array objectsBy the shape of the array, we mean the number of rows and columns of a multi-dimensional array. However, the numpy module provides us the way to reshape the array by changing the number of rows and columns of the multi-dimensional array. The reshape() function associated with the ndarray object is used to reshape the array. It accepts the two parameters indicating the row and columns of the new shape of the array. Let's reshape the array given in the following image. ExampleOutput: printing the original array.. [[1 2] [3 4] [5 6]] printing the reshaped array.. [[1 2 3] [4 5 6]] Slicing in the ArraySlicing in the NumPy array is the way to extract a range of elements from an array. Slicing in the array is performed in the same way as it is performed in the python list. Consider the following example to print a particular element of the array. ExampleOutput: 2 5 The above program prints the 2nd element from the 0th index and 0th element from the 2nd index of the array. LinspaceThe linspace() function returns the evenly spaced values over the given interval. The following example returns the 10 evenly separated values over the given interval 5-15 ExampleOutput: [ 5. 6.11111111 7.22222222 8.33333333 9.44444444 10.55555556 11.66666667 12.77777778 13.88888889 15. ] Finding the maximum, minimum, and sum of the array elementsThe NumPy provides the max(), min(), and sum() functions which are used to find the maximum, minimum, and sum of the array elements respectively. Consider the following example. ExampleOutput: The array: [ 1 2 3 10 15 4] The maximum element: 15 The minimum element: 1 The sum of the elements: 35 NumPy Array AxisA NumPy multi-dimensional array is represented by the axis where axis-0 represents the columns and axis-1 represents the rows. We can mention the axis to perform row-level or column-level calculations like the addition of row or column elements. To calculate the maximum element among each column, the minimum element among each row, and the addition of all the row elements, consider the following example. ExampleOutput: The array: [[1 2 30] [10 15 4]] The maximum elements of columns: [10 15 30] The minimum element of rows [1 4] The sum of all rows [33 29] Finding square root and standard deviationThe sqrt() and std() functions associated with the numpy array are used to find the square root and standard deviation of the array elements respectively. Standard deviation means how much each element of the array varies from the mean value of the numpy array. Consider the following example. ExampleOutput: [[1. 1.41421356 5.47722558] [3.16227766 3.87298335 2. ]] 10.044346115546242 Arithmetic operations on the arrayThe numpy module allows us to perform the arithmetic operations on multi-dimensional arrays directly. In the following example, the arithmetic operations are performed on the two multi-dimensional arrays a and b. ExampleArray ConcatenationThe numpy provides us with the vertical stacking and horizontal stacking which allows us to concatenate two multi-dimensional arrays vertically or horizontally. Consider the following example. ExampleOutput: Arrays vertically concatenated [[ 1 2 30] [10 15 4] [ 1 2 3] [12 19 29]] Arrays horizontally concatenated [[ 1 2 30 1 2 3] [10 15 4 12 19 29]]
Next TopicNumPy DataTypes
|
NumPy NdarrayNdarray is the n-dimensional array object defined in the numpy which stores the collection of the similar type of elements. In other words, we can define a ndarray as the collection of the data type (dtype) objects. The ndarray object can be accessed by using the 0 based indexing. Each element of the Array object contains the same size in the memory. Creating a ndarray objectThe ndarray object can be created by using the array routine of the numpy module. For this purpose, we need to import the numpy. Consider the below image. We can also pass a collection object into the array routine to create the equivalent n-dimensional array. The syntax is given below. The parameters are described in the following table.
To create an array using the list, use the following syntax. To create a multi-dimensional array object, use the following syntax. To change the data type of the array elements, mention the name of the data type along with the collection. Finding the dimensions of the ArrayThe ndim function can be used to find the dimensions of the array. Finding the size of each array elementThe itemsize function is used to get the size of each array item. It returns the number of bytes taken by each array element. Consider the following example. ExampleOutput: Each item contains 8 bytes. Finding the data type of each array itemTo check the data type of each array item, the dtype function is used. Consider the following example to check the data type of the array items. ExampleOutput: Each item is of the type int64 Finding the shape and size of the arrayTo get the shape and size of the array, the size and shape function associated with the numpy array is used. Consider the following example. ExampleOutput: Array Size: 7 Shape: (1, 7) Reshaping the array objectsBy the shape of the array, we mean the number of rows and columns of a multi-dimensional array. However, the numpy module provides us the way to reshape the array by changing the number of rows and columns of the multi-dimensional array. The reshape() function associated with the ndarray object is used to reshape the array. It accepts the two parameters indicating the row and columns of the new shape of the array. Let's reshape the array given in the following image. ExampleOutput: printing the original array.. [[1 2] [3 4] [5 6]] printing the reshaped array.. [[1 2 3] [4 5 6]] Slicing in the ArraySlicing in the NumPy array is the way to extract a range of elements from an array. Slicing in the array is performed in the same way as it is performed in the python list. Consider the following example to print a particular element of the array. ExampleOutput: 2 5 The above program prints the 2nd element from the 0th index and 0th element from the 2nd index of the array. LinspaceThe linspace() function returns the evenly spaced values over the given interval. The following example returns the 10 evenly separated values over the given interval 5-15 ExampleOutput: [ 5. 6.11111111 7.22222222 8.33333333 9.44444444 10.55555556 11.66666667 12.77777778 13.88888889 15. ] Finding the maximum, minimum, and sum of the array elementsThe NumPy provides the max(), min(), and sum() functions which are used to find the maximum, minimum, and sum of the array elements respectively. Consider the following example. ExampleOutput: The array: [ 1 2 3 10 15 4] The maximum element: 15 The minimum element: 1 The sum of the elements: 35 NumPy Array AxisA NumPy multi-dimensional array is represented by the axis where axis-0 represents the columns and axis-1 represents the rows. We can mention the axis to perform row-level or column-level calculations like the addition of row or column elements. To calculate the maximum element among each column, the minimum element among each row, and the addition of all the row elements, consider the following example. ExampleOutput: The array: [[1 2 30] [10 15 4]] The maximum elements of columns: [10 15 30] The minimum element of rows [1 4] The sum of all rows [33 29] Finding square root and standard deviationThe sqrt() and std() functions associated with the numpy array are used to find the square root and standard deviation of the array elements respectively. Standard deviation means how much each element of the array varies from the mean value of the numpy array. Consider the following example. ExampleOutput: [[1. 1.41421356 5.47722558] [3.16227766 3.87298335 2. ]] 10.044346115546242 Arithmetic operations on the arrayThe numpy module allows us to perform the arithmetic operations on multi-dimensional arrays directly. In the following example, the arithmetic operations are performed on the two multi-dimensional arrays a and b. ExampleArray ConcatenationThe numpy provides us with the vertical stacking and horizontal stacking which allows us to concatenate two multi-dimensional arrays vertically or horizontally. Consider the following example. ExampleOutput: Arrays vertically concatenated [[ 1 2 30] [10 15 4] [ 1 2 3] [12 19 29]] Arrays horizontally concatenated [[ 1 2 30 1 2 3] [10 15 4 12 19 29]]
Next TopicNumPy DataTypes
|
NumPy NdarrayNdarray is the n-dimensional array object defined in the numpy which stores the collection of the similar type of elements. In other words, we can define a ndarray as the collection of the data type (dtype) objects. The ndarray object can be accessed by using the 0 based indexing. Each element of the Array object contains the same size in the memory. Creating a ndarray objectThe ndarray object can be created by using the array routine of the numpy module. For this purpose, we need to import the numpy. Consider the below image. We can also pass a collection object into the array routine to create the equivalent n-dimensional array. The syntax is given below. The parameters are described in the following table.
To create an array using the list, use the following syntax. To create a multi-dimensional array object, use the following syntax. To change the data type of the array elements, mention the name of the data type along with the collection. Finding the dimensions of the ArrayThe ndim function can be used to find the dimensions of the array. Finding the size of each array elementThe itemsize function is used to get the size of each array item. It returns the number of bytes taken by each array element. Consider the following example. ExampleOutput: Each item contains 8 bytes. Finding the data type of each array itemTo check the data type of each array item, the dtype function is used. Consider the following example to check the data type of the array items. ExampleOutput: Each item is of the type int64 Finding the shape and size of the arrayTo get the shape and size of the array, the size and shape function associated with the numpy array is used. Consider the following example. ExampleOutput: Array Size: 7 Shape: (1, 7) Reshaping the array objectsBy the shape of the array, we mean the number of rows and columns of a multi-dimensional array. However, the numpy module provides us the way to reshape the array by changing the number of rows and columns of the multi-dimensional array. The reshape() function associated with the ndarray object is used to reshape the array. It accepts the two parameters indicating the row and columns of the new shape of the array. Let's reshape the array given in the following image. ExampleOutput: printing the original array.. [[1 2] [3 4] [5 6]] printing the reshaped array.. [[1 2 3] [4 5 6]] Slicing in the ArraySlicing in the NumPy array is the way to extract a range of elements from an array. Slicing in the array is performed in the same way as it is performed in the python list. Consider the following example to print a particular element of the array. ExampleOutput: 2 5 The above program prints the 2nd element from the 0th index and 0th element from the 2nd index of the array. LinspaceThe linspace() function returns the evenly spaced values over the given interval. The following example returns the 10 evenly separated values over the given interval 5-15 ExampleOutput: [ 5. 6.11111111 7.22222222 8.33333333 9.44444444 10.55555556 11.66666667 12.77777778 13.88888889 15. ] Finding the maximum, minimum, and sum of the array elementsThe NumPy provides the max(), min(), and sum() functions which are used to find the maximum, minimum, and sum of the array elements respectively. Consider the following example. ExampleOutput: The array: [ 1 2 3 10 15 4] The maximum element: 15 The minimum element: 1 The sum of the elements: 35 NumPy Array AxisA NumPy multi-dimensional array is represented by the axis where axis-0 represents the columns and axis-1 represents the rows. We can mention the axis to perform row-level or column-level calculations like the addition of row or column elements. To calculate the maximum element among each column, the minimum element among each row, and the addition of all the row elements, consider the following example. ExampleOutput: The array: [[1 2 30] [10 15 4]] The maximum elements of columns: [10 15 30] The minimum element of rows [1 4] The sum of all rows [33 29] Finding square root and standard deviationThe sqrt() and std() functions associated with the numpy array are used to find the square root and standard deviation of the array elements respectively. Standard deviation means how much each element of the array varies from the mean value of the numpy array. Consider the following example. ExampleOutput: [[1. 1.41421356 5.47722558] [3.16227766 3.87298335 2. ]] 10.044346115546242 Arithmetic operations on the arrayThe numpy module allows us to perform the arithmetic operations on multi-dimensional arrays directly. In the following example, the arithmetic operations are performed on the two multi-dimensional arrays a and b. ExampleArray ConcatenationThe numpy provides us with the vertical stacking and horizontal stacking which allows us to concatenate two multi-dimensional arrays vertically or horizontally. Consider the following example. ExampleOutput: Arrays vertically concatenated [[ 1 2 30] [10 15 4] [ 1 2 3] [12 19 29]] Arrays horizontally concatenated [[ 1 2 30 1 2 3] [10 15 4 12 19 29]]
Next TopicNumPy DataTypes
|


It uses http-equiv and content attribute. The http-equiv attribute has value refresh. The content attribute has value seconds


Rats, a dead mouse and pigeon faeces: Record 23 enforcement orders in November
by By Steve NevilleThe Food Safety Authority of Ireland (FSAI) has revealed that there were 23 enforcement orders served to food business in November.
Twenty-one closure orders and two prohibition orders were served for breaches of food safety legislation.
It is the highest number of enforcement orders in one month since the legislation was introduced in 1998.
Some of the reason for the enforcement orders included:
- Evidence of rats in a premises;
- A dead mouse was found in a trap in a kitchen;
- The presence of mouse droppings in bar area;
- 'Substantial' pigeon faeces present on the wash basin in a food packing area;
- A live rodent was observed running in the direction of the food storage and equipment washing area;
- Dead cockroaches were found behind a service fridge, staff toilet, beside the grease trap and in a container holding bottles of sauces;
- Raw chicken and raw chicken juices directly contaminating ready-to-eat foods;
- The presence of cobwebs, spiders and insects such as woodlouse were present throughout a kitchen;
- Failure to comply with improvement notices;
- High levels of E. coli and coliforms were found in drinking water and ice samples taken from a premises.
FSAI boss Dr Pamela Byrne condemned the record number of food businesses issued with enforcement orders in one month as unacceptable.
"November had the highest amount of enforcement orders in one month which the FSAI has seen since the legislation was introduced in 1998," said Dr Byrne.
"Twenty-three enforcement orders over a one-month period is totally unacceptable.
"The presence of rodents and other pests presents a grave and immediate danger to consumers’ health and food businesses must put in place more robust pest control systems.
"Some of the reasons for enforcement orders in November demonstrate totally inadequate hygiene standards and these operators are damaging the reputation of the food industry as we enter one of the busiest months of the year.
"With the Christmas period already underway, food businesses must ensure they maintain high food safety standards and I hope in December we see a significant reduction in enforcement orders and improving food safety standards."
Eleven closure orders were served under the FSAI Act, 1998 on:
- New Century Chinese Takeaway, Riverstown, Dundalk, Louth
- Hui Kee (Take Away) (Closed area: Area to the rear of the premises housing coldroom), 52 Bulfin Road Inchicore, Dublin 8
- Vernon Catering (Packer) (Closed area: Packing area of open food in warehouse), Unit C104, Castleforbes Business Park, Sheriff Street Upper, East Wall, Dublin 1
- Sajna Exclusive Dining (Restaurant/ Café), 28/29 Bishop Street, Cobh, Cork
- Apache Pizza (Restaurant/ Café), 58 Dame Street, Temple Bar, Dublin 2
- Blackchurch Inn (Restaurant/ Café), Naas Road, Rathcoole, Co. Dublin
- Hilan Chinese and Korean BBQ Restaurant (Restaurant/ Café),45 Capel Street, Dublin 1
- The Kitchen (Restaurant/ Café), Emmet Street, Trim, Meath
- Roma Restaurant (Closed Area:- the external area to the rear and side of the premises used for food production and storage), Dundalk Street, Carlingford, Louth
- East Ocean (Take Away), 61 Port Road, Letterkenny, Donegal
- Elita Meats (Small Meat Manufacturing Plant), Unit D4, Dunshaughlin Business Park, Dunshaughlin, Meath
10 closure orders were served under the EC (Official Control of Foodstuffs) Regulations, 2010 on:
- Tony's Bistro (Restaurant/ Café), 69 North Main Street, Cork
- Capital Turkish Kebab House (Restaurant/ Café), 3 Eglington Street, Galway
- Ballyneety Pizza (Take Away), Ballyneety, Limerick
- Westmanstown Sports Centre (Restaurant/ Café), Westmanstown, Dublin 15
- The Blue Anchor (Restaurant/ Café), Bellurgan Point, Dundalk, Louth
- Tikka Asian Street Food (Restaurant/ Café), Schooner House, South Quay, Wicklow
- Salvetas Take Away and Café (Restaurant/ Café), 4A Church Street, Finglas, Dublin 11
- Khan Spices (Retailer), 84 North Main Street, Cork
- Maliks Tandoori Restaurant (Restaurant/ Café), 1 Lower Pearse Road, Sligo
- The Paragon (Public House) (Closed activity: all activities with the exception of service of hot and cold drinks and prepackaged ready to eat snacks), Main Street, Skibbereen, Cork
Two prohibition orders were served under the FSAI Act, 1998 on:
- Vernon Catering (Packer), Unit C104, Castleforbes Business Park, Sheriff Street Upper, East Wall, Dublin 1
- Elita Meats (Small Meat Manufacturing Plant), Unit D4, Dunshaughlin Business Park, Dunshaughlin, Meath
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More rain on way as Storm Atiyah leaves thousands without power


A line on the earth’s surface which passes through the north and south poles and crosses the equator at right angles.
A great circle passing through the poles.
A line of constant longitude.
The prime or principal meridian is the one passing through Greenwich, at zero longitude.


| Units | Section | Mini | Days | Begin | End | Teaching Location | Bldg/Room | Instructor | |
|---|---|---|---|---|---|---|---|---|---|
| 12.0 | A | MW | 04:30PM | 05:50PM | Pittsburgh, Pennsylvania | GHC 4307 |
|
Computing in the cloud has emerged as a leading paradigm for cost-effective, scalable, well-managed computing. Users pay for services provided in a broadly shared, power efficient datacenter, enabling dynamic computing needs to be met without paying for more than is needed. Actual machines may be virtualized into machine-like services, or more abstract programming platforms, or application-specific services, with the cloud computing infrastructure managing sharing, scheduling, reliability, availability, elasticity, privacy, provisioning and geographic replication. Please refer to https://www.cs.cmu.edu/csd-grad/courseschedules16.html for the most recent schedule updates.


Ezekiel 33:3
If when he seeth the sword come upon the land, he blow the trumpet, and warn the people;


2 Kings 4:19
And he said unto his father, My head, my head. And he said to a lad, Carry him to his mother.


2017 RoboBoat control panel
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Team selected: {{course.teamInWater}}
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{{course.runSetup}}
{{course.showText}} debug info
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--- layout: base --- {{ content }} {% include inputs/lzss.html %} {% include inputs/lzss_decode.html %}
Output:


Kentucky safety officials advise ‘Buckle Up Phone Down’
by The Associated PressFRANKFORT, Ky. — Kentucky’s highways will be busy with travellers during Thanksgiving week, and safety officials are advising them to buckle up their seat belts and put down their phones.
Kentucky Office of Highway Safety acting Executive Director Jason Siwula says this is one of the busiest travel times, and deaths and injuries can be prevented by fastening safety belts and putting cellphones down.
Last year, there were nearly 2,000 crashes during the Thanksgiving holiday in Kentucky, with 420 injuries and seven deaths. Three of the people killed weren’t wearing a seat belt, and one death involved a distraction.
As of Thursday, there have been 659 Kentucky roadway deaths in 2019, 10 more than the same time last year. Of those deaths, 265 weren’t wearing a seat belt, and over 140 involved distraction.
The Associated Press


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SourceLength
Set of rules that analyse the length of sections of code.
Rules
MaxLinesInFunction - FS0025
Cause
A function is made up of more than a configurable number of lines.
Rationale
The larger a function becomes the more complex it becomes, it also indicates that it may have too many different responsibilities.
How To Fix
Refactor to extract out code into smaller composable functions.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a function. (Default 70)
MaxLinesInLambdaFunction - FS0022
Cause
A lambda function is made up of more than a configurable number of lines.
Rationale
Lambda functions are usually used for single lines of code that aren't worth naming to make code more concise. A large lambda function indicates it should probably be a named function.
How To Fix
Consider using a named function rather than a lambda function.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a lambda function. (Default 7)
MaxLinesInMatchLambdaFunction - FS0023
Cause
A match function is made up of more than a configurable number of lines.
Rationale
The larger a function becomes the more complex it becomes, it also indicates that it may have too many different responsibilities.
How To Fix
Use active patterns to help reduce the number of matches/extract code out into composable functions.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a match function. (Default 70)
MaxLinesInValue - FS0024
Cause
A statement binded to a value is made up of more than a configurable number of lines. For example the following would break the rule when the maximum number of lines is set to 4:
1: 2: 3: 4: 5: 6: |
|
Rationale
The larger a value becomes the more complex it becomes.
How To Fix
Refactor to extract out code into smaller composable functions.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a value binding. (Default 70)
MaxLinesInConstructor - FS0027
Cause
A class constructor is made up of more than a configurable number of lines.
Rationale
The larger a constructor becomes the more complex it becomes, it also indicates that it may have too many different responsibilities.
How To Fix
Extract code out into private methods or functions.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a class constructor. (Default 70)
MaxLinesInMember - FS0026
Cause
A member is made up of more than a configurable number of lines.
Rationale
The larger a member becomes the more complex it becomes, it also indicates that it may have too many different responsibilities.
How To Fix
Extract code out into private methods or functions.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a member. (Default 70)
MaxLinesInProperty - FS0028
Cause
A property is made up of more than a configurable number of lines.
Rationale
The larger a property becomes the more complex it becomes, it also indicates that it may have too many different responsibilities.
How To Fix
Extract code out into private methods or functions.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a property. (Default 70)
MaxLinesInClass - FS0033
Cause
A class is made up of more than a configurable number of lines.
Rationale
The larger a class becomes the more complex it becomes, it also indicates that it may have too many different responsibilities.
How To Fix
Extract code out into smaller composable classes.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a class. (Default 500)
MaxLinesInEnum - FS0031
Cause
An enum is made up of more than a configurable number of lines.
Rationale
The larger a enum becomes the more complex it becomes, it also indicates that all the items may not be related.
How To Fix
Extract code out into smaller enums.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a enum. (Default 500)
MaxLinesInUnion - FS0032
Cause
A discriminated union is made up of more than a configurable number of lines.
Rationale
The larger a discriminated union becomes the more complex it becomes, it also indicates that all the items may not be related.
How To Fix
Extract code out into smaller composed discriminated unions.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a discriminated union. (Default 500)
MaxLinesInRecord - FS0030
Cause
A record is made up of more than a configurable number of lines.
Rationale
The larger a record becomes the more complex it becomes, it also indicates that all the items may not be related.
How To Fix
Extract code out into smaller composed records.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a record. (Default 500)
MaxLinesInModule - FS0029
Cause
A module is made up of more than a configurable number of lines.
Rationale
The larger a module becomes the more complex it becomes, it also indicates that it may have too many different responsibilities.
How To Fix
Extract code out into smaller modules.
Rule Settings
enabled
- A boolean property that can enable and disable this rule. (Default true)
maxLines
- Maximum number of lines in a module. (Default 1000)
Full name: SourceLength.value


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Memories
Thought of the Day
It’s like my very first memory, which I guess is the first time I was alive.
- Stephen Chbosky
Thinking about my first memory is actually much harder than it sounds, as if finding a needle in the haystack. Beside that I agree that a lot of our long term memories are moments that affect us to our core & events which shape something fundamental to our being. When I think about it, most of things I remember about my past life are such instances which either gave me great joy and some which made me realize the reality. Given the vast expanse of the universe, and my brief, transient existence I don’t know if it matters in the first place. To paraphrase from Murakami, the room where we store our memories is like our private library. And you’ll live forever in your own private library.
Maybe that is a worthy way to live - focusing on enriching your personal library with moments that do not make you feel infinitesimally small. ✨
What brought me joy today?
- Observing a beautiful sunset sitting by the lake in the Citadelpark.
- Light showers providing some respite from the summer heat.


|
MAX32665 SDK Documentation
0.2
Software Development Kit Overview and API Documentation
|
Register for controlling SPI clock rate. More...
Macros | |
| #define | MXC_F_SPIXR_BRG_CTRL_LOW_POS 0 |
| BRG_CTRL_LOW Position. | |
| #define | MXC_F_SPIXR_BRG_CTRL_LOW ((uint32_t)(0xFFUL << MXC_F_SPIXR_BRG_CTRL_LOW_POS)) |
| BRG_CTRL_LOW Mask. | |
| #define | MXC_V_SPIXR_BRG_CTRL_LOW_DIS ((uint32_t)0x0UL) |
| BRG_CTRL_LOW_DIS Value. | |
| #define | MXC_S_SPIXR_BRG_CTRL_LOW_DIS (MXC_V_SPIXR_BRG_CTRL_LOW_DIS << MXC_F_SPIXR_BRG_CTRL_LOW_POS) |
| BRG_CTRL_LOW_DIS Setting. | |
| #define | MXC_F_SPIXR_BRG_CTRL_HI_POS 8 |
| BRG_CTRL_HI Position. | |
| #define | MXC_F_SPIXR_BRG_CTRL_HI ((uint32_t)(0xFFUL << MXC_F_SPIXR_BRG_CTRL_HI_POS)) |
| BRG_CTRL_HI Mask. | |
| #define | MXC_V_SPIXR_BRG_CTRL_HI_DIS ((uint32_t)0x0UL) |
| BRG_CTRL_HI_DIS Value. | |
| #define | MXC_S_SPIXR_BRG_CTRL_HI_DIS (MXC_V_SPIXR_BRG_CTRL_HI_DIS << MXC_F_SPIXR_BRG_CTRL_HI_POS) |
| BRG_CTRL_HI_DIS Setting. | |
| #define | MXC_F_SPIXR_BRG_CTRL_SCALE_POS 16 |
| BRG_CTRL_SCALE Position. | |
| #define | MXC_F_SPIXR_BRG_CTRL_SCALE ((uint32_t)(0xFUL << MXC_F_SPIXR_BRG_CTRL_SCALE_POS)) |
| BRG_CTRL_SCALE Mask. | |


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