Author: admin yep

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Ladies and gentlemen, Buddy Brown and his new hit single, "Everything’s Gay in June":

Not the Bee

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FLAMETHROWER LEVEL 100 🔥

Not the Bee

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If you split a wheel in half, you shouldn’t still be able to ride on it, right? Well, watch this video from The Q, in which he cut two bike wheels and tires down the middle, connected them with a long chain and positioned them so one half is always touching the ground. Miraculously, the bike rides just fine.

The Awesomer

Are they really tricks or simply basic techniques combined to create a solution. Before writing these mechanics for using native MySQL to create a compound JSON object, let me point out that the easiest way to get one is to use the MySQL Node.js library, as shown recently in my “Is SQL Programming” blog post.

Moving data from a relational model output to a JSON structure isn’t as simple as a delimited list of columns in a SQL query. Let’s look at it in stages based on the MySQL Server 12.18.2 Functions that create JSON values.

Here’s how you return single row as a JSON object, which is quite straightforward:

SELECT JSON_OBJECT('first_name',c.first_name,'last_name',c.last_name) AS json_result
FROM   contact c
WHERE  first_name = 'Harry'
AND    last_name = 'Potter';

It returns:

+------------------------------------------------+
| json_result                                         |
+------------------------------------------------+
| {"last_name": "Potter", "first_name": "Harry"} |
+------------------------------------------------+
1 row in set (0.00 sec)

With a GROUP_CONCAT function, let’s capture a JSON array of all three Potter family members:

SELECT CONCAT('['
             , GROUP_CONCAT(
                 JSON_OBJECT('first_name',first_name
                            ,'last_name',last_name ) SEPARATOR ',')
             ,']') AS json_result 
FROM   contact c
WHERE  c.last_name = 'Potter';

It returns an array of JSON objects:

+-----------------------------------------------------------------------------------------------------------------------------------------------+
| [{"last_name": "Potter", "first_name": "Harry"},{"last_name": "Potter", "first_name": "Ginny"},{"last_name": "Potter", "first_name": "Lily"}] |
+-----------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.01 sec)

Next, let’s put a 1:many relationship between the member and contact table into a JSON structure with a single account number and an array of contact. It requires a second call to the JSON_OBJECT function and the addition of a GROUP BY clause in the query.

SELECT   JSON_OBJECT(
            'account_number', account_number
           ,'contact', CONCAT('['
                         , GROUP_CONCAT(
                              JSON_OBJECT('first_name',first_name
                             ,'last_name',last_name ) SEPARATOR ',')
                             ,']')
         ) AS json_result 
FROM     member m INNER JOIN contact c
ON       m.member_id = c.member_id
WHERE    c.last_name = 'Potter'
GROUP BY m.account_number;

It returns the following string with an annoying set of backslashes. It also inverts the column order, which appears unavoidable but it shouldn’t matter because the order of name-value pairs in JSON is immaterial.

+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| {"contact": "[{\"last_name\": \"Potter\", \"first_name\": \"Harry\"},{\"last_name\": \"Potter\", \"first_name\": \"Ginny\"},{\"last_name\": \"Potter\", \"first_name\": \"Lily\"}]", "account_number": "US00011"} |
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
1 row in set (0.00 sec)

The following quick little Python code cleans up the JSON string by removing the backslashes and extraneous quotes around the array of contacts.

# Import the library.
import mysql.connector
from mysql.connector import errorcode
 
try:
  # Open connection.
  cnx = mysql.connector.connect(user='student', password='student',
                                host='127.0.0.1',
                                database='studentdb')
  # Create cursor.
  cursor = cnx.cursor()
 
  # Set the query statement.
  query = ("SELECT JSON_OBJECT( "
           "'account_number', m.account_number "
           ",'contact', CONCAT('[' "
           "              , GROUP_CONCAT( "
           "                   JSON_OBJECT('first_name', c.first_name "
           "                  ,'last_name', c.last_name ) SEPARATOR ',') "
           "                  ,']')) AS json_result "
           "FROM   contact c INNER JOIN member m "
           "ON     c.member_id = m.member_id "
           "WHERE  c.last_name = %s "
           "GROUP BY account_number")
  
  # Execute cursor.
  cursor.execute(query,["Potter"])
 
  # Display the column returned by the query stripped of backslashes and
  # extraneous quotes.
  for (row) in cursor:
    for column in range(len(row)):
      print(row[column].replace("\\","").replace("\"[","[").replace("]\"","]"))
 
  # Close cursor.
  cursor.close()
 
# ------------------------------------------------------------
# Handle exception and close connection.
except mysql.connector.Error as e:
  if e.errno == errorcode.ER_ACCESS_DENIED_ERROR:
    print("Something is wrong with your user name or password")
  elif e.errno == errorcode.ER_BAD_DB_ERROR:
    print("Database does not exist")
  else:
    print("Error code:", e.errno)        # error number
    print("SQLSTATE value:", e.sqlstate) # SQLSTATE value
    print("Error message:", e.msg)       # error message
 
# Close the connection when the try block completes.
else:
  cnx.close()

It returns:

{"contact": [{"last_name": "Potter", "first_name": "Harry"},{"last_name": "Potter", "first_name": "Ginny"},{"last_name": "Potter", "first_name": "Lily"}], "account_number": "US00011"}

I hope this helps exhibit less well known MySQL syntax.

Planet MySQL

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However else your Thursday is going, you can be happy knowing that the Supreme Court just hand-delivered the country a magnificent win for the Second Amendment on a silver platter:

Not the Bee

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Kyle Rittenhouse, our favorite rapscallion, surveyed the land and thought about how next to trigger the left and the media (but I repeat myself). They are still upset he was found not guilty of first-degree murder by acting in self-defense against a pedophile. If he comments on gas prices, they can’t calm down. But this new venture? Young Kyle is getting into the video game industry. It’s a shooting game. A turkey shooting game. And someone wrote the words "fake news" on the side of the turkeys.

You hunt fake news turkeys. Kyle Rittenhouse developed a video game that allows you to hunt fake news turkeys as Kyle Rittenhouse.

Kyle Rittenhouse’s Turkey Shoot OFFICIAL GAME

youtu.be

"The media is nothing but a bunch of turkeys with nothing better to do than push their lying agenda and destroy innocent people’s lives. […] Help me fund the lawsuits to stop these fake news turkeys."

You can preorder at RittenhouseGame.com. It’s to raise money for his Media Accountability Project so the defamation lawsuit can finally begin.

Kyle is working with Mint Studios. CEO Mint Chip — I’m trusting the Washington Examiner that’s his real name — felt the need step in after he saw what the media did to Rittenhouse. "Before the trial, you couldn’t even mention his name in a positive manner on social media without getting banned. The truth literally got you suspended. We fight for the truth."

Unfortunately, it does not look like the turkeys are named after our favorite fake news personalities. No Gobbles Stelter or Whoopi Goldfowl. Also, due to Kyle’s young age, he wouldn’t know to recreate the WKRP Turkey Drop. Only, where you need to stop the White House from bombarding a MAGA rally with Iive turkeys.

Kyle Rittenhouse is hunting fake news in a video game. The kids got some stones. I’ll give him that.

The Louder with Crowder Dot Com Website is on Instagram now! Follow us at @lwcnewswire and tell a friend!

Kyle Rittenhouse’s Rifle Gets Shredded: A Tribute | Louder With Crowder

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Louder With Crowder

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In a way, the staff on The Office are kind of like the Minions from Despicable Me. They each have a quirky personality, and they all work for an annoying boss played by Steve Carrell. To celebrate the release of the new movie Minions: Rise of Gru, Illumination Entertainment released this special remake of The Office’s opening credits.

The Awesomer

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There’s a thrilling scene in one of the Captain America movies where a heavily-armored SUV driven by Nick Fury comes under attack. The vehicle withstands an incredible amount of damage.

There’s a terrifying scene from last year, where a failed heist in South Africa yielded real-life footage of an armored 70 Series Toyota Land Cruiser coming under fire. It, too, withstood an incredible amount of damage, though not the Marvel-movie level.

Just how much punishment could a real-world armored SUV take? Canadian firm Inkas Armored Vehicle Manufacturing should know, as they specialize in the design and production of armored vehicles for embassies, paramilitary groups, law enforcement agencies, executive protection companies, security companies and civilians.

This month Inkas released footage of the insane testing done to certify one of their modified Land Cruiser 300s. To design effective ballistic and blast protection, this is what their test mules are subjected to—a grenade on the roof, a grenade beneath the car, land mines, 15kg of dynamite, nearly 800 rounds fired by assault rifles:

"In order to obtain the certification, the armored Land Cruiser 300 endured extensive ballistic testing, which specifically targeted the potential points of failure where the vehicle would be most susceptible to penetration during an attack. The INKAS Armored Land Cruiser successfully proved its reliability in the field – withstanding over 780 rounds of ammunition from various calibre firearms, 6 roof-level hand grenades (DM51), 4 underbody hand grenades (DM51), 2 land mines (DM31) as well as a 15kg TNT (equivalent) explosion from a 2 meter distance."

Core77

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Gizmodo

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Lifehacker