Django Database Functions Performance Test

• In this post we will measure performance for django database function(Concat) and python f string concatenation for some data.
• IPython, Python 3.8.5, Django 3.2.2 were used.

x
In [1]: from django.db.models import Value
In [2]: from django.db.models.functions import Concat
​
In [5]: def load_fullnames_v1(limit):
   ...:     names = list(
   ...:     Person.objects.annotate(
   ...:             full_name=Concat('fname',Value(" "),'lname')
   ...:         ).values_list('full_name')[:limit]
   ...:     )
   ...:     return names
   ...: 
​
In [6]: def load_fullnames_v2(limit):
   ...:     names = [f"{p.fname} {p.lname}" for p in Person.objects.all()[:limit]]
   ...:     return names
   ...: 
​
In [7]: %timeit for i in range(100): load_fullnames_v1(100)
83.5 ms ± 856 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)
​
In [8]: %timeit for i in range(100): load_fullnames_v2(100)
89.6 ms ± 860 µs per loop (mean ± std. dev. of 7 runs, 10 loops each)
​
In [9]: %timeit for i in range(100): load_fullnames_v1(10000)
1.06 s ± 9.11 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
​
In [10]: %timeit for i in range(100): load_fullnames_v2(10000)
6.68 s ± 41.3 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
​
In [11]: %timeit for i in range(100): load_fullnames_v1(100000)
10.8 s ± 91.9 ms per loop (mean ± std. dev. of 7 runs, 1 loop each)
​
In [12]: %timeit for i in range(100): load_fullnames_v2(100000)
1min 7s ± 2.47 s per loop (mean ± std. dev. of 7 runs, 1 loop each)

 

Limit	Django DB function	Python f string
100	83.5 ms	89.6 ms
10000	1.06 s	6.68 s
100000	10.8 s	1 min 7 s

Conclusion

• Django database functions are higher performance than f string or any other concatenation.