251 lines
4.2 KiB
Markdown
251 lines
4.2 KiB
Markdown
# Using Relational Databases
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**SELECT FROM WHERE**
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```SQL
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SELECT *
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FROM Planets
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WHERE diameter > 5;
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```
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**Aproximate matching**
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```SQL
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SELECT *
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FROM Planets
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WHERE name LIKE '%er';
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```
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where '%er' is a wildcard, it's case insensite, it could be '%ER'
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**UPDATE**
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```SQL
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UPDATE *
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SET name = 'Mars'
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WHERE anem = 'Mers';
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```
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**INSERT**
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```SQL
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INSERT INTO Planets (name, diameter)
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VALUES
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('Gethen', 9483),
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('Athshe', 8210)
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```
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```SQL
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INSERT INTO Planets (name)
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SELECT DISTINCT name
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FROM Moons;
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```
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Here we have a subquery and we insert the result of this query into the Planets table.
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**DELETE**
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```SQL
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DELETE FROM Planets
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WHERE diameter < 2500;
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```
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**DROP**
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```SQL
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DROP TABLE Planets;
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```
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**TRUNCATE**
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```SQL
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TRUNCATE TABLE Planets;
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```
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Removes all entries but leaves the structure.
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**CREATE**
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```SQL
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CREATE DATABASE Planets;
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CREATE TABLE Planets (
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PlanetName CHAR(8),
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dayLength INT,
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YearLength INT,
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PRIMARY KEY (PlanetName)
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);
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```
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**ALTER**
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```SQL
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ALTER TABLE Planets
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ADD COLUMN
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Diameter INT;
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```
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## Data exchange
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```SQL
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SELECT *
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FROM Planets
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INTO OUTPUTFILE 'Planets.txt';
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```
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```SQL
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LOAD DATA INFILE 'Planets.txt'
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INTO TABLE Planets;
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```
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## Agregate functions
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We identify who they are for and we group them together
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We then summarize the information by adding up the price.
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This translates to SQL as:
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```SQL
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SELECT *
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FROM Shopping
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WHERE
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BoughtFor = 'Mum';
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```
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```SQL
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<SOMETHING>
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FROM Shopping
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GROUP BY BoughtFor;
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```
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```SQL
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SELECT BoughtFor,
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SUM(Price)
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FROM Shopping
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GROUP BY BoughtFor;
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```
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This gives us the sum of groups
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We also have
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* SUM
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* AVG
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* STD (deviation)
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* VARIANCE
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* MAX (Also works on other data types such as dates, most recent)
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* MIN (least recent or oldest)
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* COUNT
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* COUNT(DISTINCT)
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* GROUP_CONCAT (for strings)
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```SQL
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SELECT Gender, COUNT(*) FROM Locations JOIN Actors ON Actor1 = ENName
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GROUP BY Gender;
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```
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```SQL
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SELECT Gender, COUNT(*) FROM Locations JOIN Actors ON Actor2 = ENName
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GROUP BY Gender;
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```
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```SQL
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SELECT Gender, COUNT(*) FROM Locations JOIN Actors ON Actor3 = ENName
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GROUP BY Gender;
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```
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```SQL
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SELECT Actor1, COUNT(*) AS Appearances FROM Locations GROUP BY Actor1 ORDER BY Appearances DESC LIMIT 20;
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```
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(ASC/DESC)
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In the Lab
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```SQL
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LOAD DATA
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INFILE '/home/coder/project/SF_film_locations.csv'
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REPLACE
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INTO TABLE Locations
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FIELDS
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TERMINATED BY ','
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OPTIONALLY ENCLOSED BY '"'
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ESCAPED BY '"'
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IGNORE 1 ROWS;
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```
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```SQL
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LOAD DATA
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INFILE '/home/coder/project/wikidata-film-actors.csv'
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REPLACE
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INTO TABLE Locations
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FIELDS
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TERMINATED BY ','
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OPTIONALLY ENCLOSED BY '"'
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ESCAPED BY '"'
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IGNORE 1 ROWS;
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```
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```SQL
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LOAD DATA
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INFILE '/home/coder/project/wikidata-film-composers.csv'
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REPLACE
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INTO TABLE Locations
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FIELDS
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TERMINATED BY ','
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OPTIONALLY ENCLOSED BY '"'
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ESCAPED BY '"'
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IGNORE 1 ROWS;
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```
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Age of Actor1
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```SQL
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SELECT DISTINCT Actor1, Year, DOB, FLOOR(DATEDIFF(MakeDate(Year, 1), DOB)/365) AS Age, Title AS Movie FROM Locations JOIN Actors ON Actor1 = ENName LIMIT 20;
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```
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Update the age of Charles Chaplin
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``` SQL
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UPDATE Actors SET DOB = '1889-04-16' WHERE ENName = 'Charles Chaplin';
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```
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## Database libraries
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* Create a (persistent) connection
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* Send commands
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* Receive (and structure) response
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## Create a (persistent) connection
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`conn <- newCnnection(host, username, password, database)`
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`conn.connect()`
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Or both steps in one
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`conn <- connect(host, username, password, database)`
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## Sending commands
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`resource <- conn.execute(query)`
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`resource.fetchData()`
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Or
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`result <- conn.query(query)`
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## Receive response
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The result will usually be iterable.
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Each row may be an object or an array.
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## Using PHP SQL libraries
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```PHP
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$db = new mysqli(host, user, pwd, db);
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```
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```PHP
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$result = $db->query("SELECT * FROM Planets");
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```
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Returns a mysqli_result object
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We can iterate through this response
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```PHP
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foreach ($result as $moon) {
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echo $moon['radius'];
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}
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```
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or treat it as a 2D array
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```PHP
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$moons = $result->fetch_all();
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echo $moons[5][2];
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```
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or provide an option to use keys
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```PHP
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$moons = $result->fetch_all(MYSQL_ASSOC);
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echo $moons[5]['radius'];
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```
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