# plan a week

    

index d717578..a72ec30 100644
@@ -78,9 +78,9 @@ More:
1. ./new-year.md                (31 December 2020, 18:00)
1. ./scopes.md                  (25 February 2021, 18:00)
1. ./nonlocal.md                (2 March 2021, 18:00)
-1. ./str-concat.md
-1. ./bytearray.md
-1. ./join-lists.md
+1. ./str-concat.md              (4 March 2021, 18:00)
+1. ./bytearray.md               (9 March 2021, 18:00)
+1. ./join-lists.md              (11 March 2021, 18:00)
1. ./is-warning.md
1. ./float.md
1. ./inf.md
diff --git a/pythonetc/join-lists.md b/pythonetc/join-lists.md
index 4d21dd1..f2cb728 100644
--- a/pythonetc/join-lists.md
+++ b/pythonetc/join-lists.md
@@ -1,10 +1,10 @@
-Suppose, we have 10 lists:
+Suppose, you have 10 lists:

python
lists = [list(range(10_000)) for _ in range(10)]


-What's the fastest way to do it? To have a baseline, let's just + everything together:
+What's the fastest way to join them into one? To have a baseline, let's just + everything together:

python
s = lists
@@ -21,7 +21,7 @@ from operator import add
# 1.65 ms ± 27.2 µs per loop


-Good, about the same speed. However, reduce is not "pythonic" anymore, this is why it was moved from built-ins into functools. The more beautiful way to do it is uning sum:
+Good, about the same speed. However, reduce is not "pythonic" anymore, this is why it was moved from built-ins into functools. The more beautiful way to do it is using sum:

python
%timeit sum(lists, start=[])
@@ -46,4 +46,4 @@ for lst in lists:
# 250 µs ± 5.96 µs per loop


-Turned out, the most straightforward and simple to understand solution is the fastest one.
+Turned out, the most straightforward and simple solution is the fastest one.