SAS Code Extender

import functools

@functools.lru_cache(maxsize=128)
def fibonacci(n):
    if n < 2:
        return n
    return fibonacci(n-1) + fibonacci(n-2)

import asyncio

async def main():
    await asyncio.sleep(1)
    print('Hello, world!')

asyncio.run(main())

public class Singleton {
    private static Singleton instance;
    private Singleton() {}
    public static Singleton getInstance() {
        if (instance == null) {
            instance = new Singleton();
        }
        return instance;
    }
}

SELECT * FROM orders
WHERE order_date BETWEEN '2000-01-01' AND '2020-12-31'
GROUP BY customer_id
HAVING COUNT(order_id) > 5
ORDER BY COUNT(order_id) DESC;

from sklearn.ensemble import RandomForestClassifier
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
from sklearn.metrics import classification_report

iris = load_iris()
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.3, random_state=42)

clf = RandomForestClassifier(n_estimators=100)
clf.fit(X_train, y_train)

predictions = clf.predict(X_test)
print(classification_report(y_test, predictions))

library(ggplot2)

p <- ggplot(mtcars, aes(wt, mpg))

p + geom_point(aes(color = cyl > 4))

=LET(x, 4, y, 3, x ^ y)

eval <- function(func, df1, df2) {
  func(df1, df2)
}

add <- function(df1, df2) {
  df1 + df2
}

eval(add, 1, 2)

EVALUATE
CALCULATETABLE(
    'Sales',
    FILTER(
        ALL('Sales'[Order Date]),
        'Sales'[Order Date] IN VALUES('DateTable'[Date])
    )
)

def quicksort(arr):
    if len(arr) <= 1:
        return arr
    pivot = arr[len(arr) // 2]
    left = [x for x in arr if x < pivot]
    middle = [x for x in arr if x == pivot]
    right = [x for x in arr if x > pivot]
    return quicksort(left) + middle + quicksort(right)