@@ -120,14 +120,15 @@ documentation.
 TODO
 ====
 
-- writing: packaging
+- picking a license
 - badge for google slides
 - change documentation links to main branch
-- joblib example in profile
+- joblib for parallelizing, example in profile
 - github page
 - point out features in scripts: object-oriented, asserts, tqdm, type hints
 - matplotlib, pytest, black in dev install
 - manifest file to not include file in package
 - GitHub actions for releasing to PyPi when changes to version
-- cupy / pytorch compatible
+- cupy for GPU
+- pytorch compatible
 - Cython / C++
@@ -0,0 +1,45 @@
+"""
+Example of using `joblib` to parallelize a loop.
+
+pip install joblib
+
+"""
+
+from joblib import Parallel, delayed
+import numpy as np
+import time
+
+
+def f(seed, n, proc_time):
+    np.random.seed(seed)
+    x = np.random.randn(n)
+    time.sleep(proc_time)  # simulate some long running process
+    return np.fft.fft(x)
+
+
+if __name__ == "__main__":
+
+    # Create a list of inputs
+    n = 2048
+    n_exp = 100
+    proc_time = 0.2
+    n_cpu = 6
+
+    # Compare processing time for serial and parallel processing
+
+    # Serial processing
+    start = time.time()
+    outputs_ser = []
+    for seed in range(n_exp):
+        outputs_ser.append(f(seed, n, proc_time))
+    serial_time = time.time() - start
+    print(f"Serial processing took {serial_time} seconds")
+
+    # Parallel processing
+    start = time.time()
+    outputs_par = Parallel(n_jobs=n_cpu)(delayed(f)(seed, n, proc_time) for seed in range(n_exp))
+    parallel_time = time.time() - start
+    print(f"Parallel processing took {parallel_time} seconds")
+
+    # Speed-up
+    print(f"Speed-up: {serial_time / parallel_time}")