Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
Testing Research Software
Search
Nikoleta
March 14, 2017
Programming
0
310
Testing Research Software
Slides for the talk Writing tests for research software for PyCon Namibia 2017
Nikoleta
March 14, 2017
Tweet
Share
More Decks by Nikoleta
See All by Nikoleta
A trip to earth science with python as a companion
nikoletav3
0
49
Arcas: Using Python to access open research literature
nikoletav3
1
180
Optimisation of short memory strategies in the Iterated Prisoners Dilemma
nikoletav3
0
55
Arcas
nikoletav3
0
460
SSI Selection Day
nikoletav3
0
400
SWORDS-03-10-2016
nikoletav3
0
51
PyCon UK 2016
nikoletav3
0
160
Other Decks in Programming
See All in Programming
AI駆動開発ライフサイクル(AI-DLC)のホワイトペーパーを解説
swxhariu5
0
1.1k
AIと協働し、イベントソーシングとアクターモデルで作る後悔しないアーキテクチャ Regret-Free Architecture with AI, Event Sourcing, and Actors
tomohisa
2
3.8k
Honoを技術選定したAI要件定義プラットフォームAcsimでの意思決定
codenote
0
250
JJUG CCC 2025 Fall: Virtual Thread Deep Dive
ternbusty
3
460
全員アーキテクトで挑む、 巨大で高密度なドメインの紐解き方
agatan
2
2.6k
[堅牢.py #1] テストを書かない研究者に送る、最初にテストを書く実験コード入門 / Let's start your ML project by writing tests
shunk031
9
4.3k
Bakuraku E2E Scenario Test System Architecture #bakuraku_qa_study
teyamagu
PRO
0
770
Feature Flags Suck! - KubeCon Atlanta 2025
phodgson
0
150
2026年向け会社紹介資料
misu
0
240
JEP 496 と JEP 497 から学ぶ耐量子計算機暗号入門 / Learning Post-Quantum Crypto Basics from JEP 496 & 497
mackey0225
2
400
Java_プロセスのメモリ監視の落とし穴_NMT_で見抜けない_glibc_キャッシュ問題_.pdf
ntt_dsol_java
0
210
Herb to ReActionView: A New Foundation for the View Layer @ San Francisco Ruby Conference 2025
marcoroth
0
140
Featured
See All Featured
ReactJS: Keep Simple. Everything can be a component!
pedronauck
666
130k
The Pragmatic Product Professional
lauravandoore
36
7k
Bash Introduction
62gerente
615
210k
YesSQL, Process and Tooling at Scale
rocio
174
15k
Rails Girls Zürich Keynote
gr2m
95
14k
Performance Is Good for Brains [We Love Speed 2024]
tammyeverts
12
1.3k
Music & Morning Musume
bryan
46
7k
The Hidden Cost of Media on the Web [PixelPalooza 2025]
tammyeverts
1
35
Visualizing Your Data: Incorporating Mongo into Loggly Infrastructure
mongodb
48
9.8k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
37
2.6k
Automating Front-end Workflow
addyosmani
1371
200k
Facilitating Awesome Meetings
lara
57
6.6k
Transcript
Writing tests for research software @NikoletaGlyn
None
TESTING
0, 1, 1, 2, 3, 5, 8, 13, 21, 34
...
F0 = 0 F1 = 1 Fn = Fn−1 +
Fn−2
main.py def fib(n): if n == 0: return 0 if
n == 1: return 1 return 2 * fib(n - 1)
n 2 3 4 . . . 16 17 18
Fn 1 2 3 . . . 987 1597 2584 Fn−1 1 1 2 . . . 610 987 1597 Fn Fn−1 1.000 2.000 1.500 . . . 1.618 1.618 1.618
n 2 3 4 . . . 16 17 18
Fn 1 2 3 . . . 987 1597 2584 Fn−1 1 1 2 . . . 610 987 1597 Fn Fn−1 1.000 2.000 1.500 . . . 1.618 1.618 1.618 φ 1.61803...
. |-- main.py |-- golden.py
golden.py import main for n in range(10, 100000): golden_ratio =
fib(n) / fib(n - 1) print(golden_ratio)
golden.py import main for n in range(10, 100000): golden_ratio =
fib(n) / fib(n - 1) print(golden_ratio) 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 ...
golden.py import main for n in range(10, 100000): golden_ratio =
fib(n) / fib(n - 1) print(golden_ratio) 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 ... Glynatsi 2017, “SOLVES THE FIBONACCI MYSTERY”
WRITE REVIEW PUBLISH
20% OF GENETIC RESEARCH IS WRONG Gene name errors are
widespread in the scientific literature by Mark Ziemann, Yotam Eren and Assam El-Osta
INDUSTRY
INDUSTRY AMAZON
. |-- main.py |-- golden.py |-- test_main.py
test main.py import unittest import main class TestExample(unittest.TestCase): def test_initial(self):
self.assertEqual(fib(0), 0) self.assertEqual(fib(1), 1) def test_fib(self): self.assertEqual(fib(2), 1) self.assertEqual(fib(3), 2)
test main.py import unittest import main class TestExample(unittest.TestCase): def test_initial(self):
self.assertEqual(fib(0), 0) self.assertEqual(fib(1), 1) def test_fib(self): self.assertEqual(fib(2), 1) self.assertEqual(fib(3), 2) python -m unittest test_main.py
test main.py import unittest import main class TestExample(unittest.TestCase): def test_initial(self):
self.assertEqual(fib(0), 0) self.assertEqual(fib(1), 1) def test_fib(self): self.assertEqual(fib(2), 1) self.assertEqual(fib(3), 2) python -m unittest test_main.py self.assertEqual(fib(2), 1) AssertionError: 2 != 1 ----------------------------- Ran 2 tests in 0.000s FAILED (failures=1)
main.py def fib(n): if n == 0: return 0 if
n == 1: return 1 return 2 * fib(n - 1)
main.py def fib(n): if n == 0: return 0 if
n == 1: return 1 return fib(n - 1) + fib(n - 2)
main.py def fib(n): if n == 0: return 0 if
n == 1: return 1 return fib(n - 1) + fib(n - 2) python -m unittest test_main.py ------------------------------- Ran 2 tests in 0.000s OK
main.py def fib(n): if n == 0: return 0 if
n == 1: return 1 return fib(n - 1) + fib(n - 2) python -m unittest test_main.py ------------------------------- Ran 2 tests in 0.000s OK Glynatsi 2017, “TRYING TO RECLAIM REPUTATION”
Doc Testing
main.py import unittest def fib(n): """Returns the n th fibonacci
number. For example: >>> fib(5) 5 >>> fib(6) 8 >>> fib(5) + fib(6) 13 >>> fib(7) 10 """ if n == 0: return 0 elif n == 1: return 1 else: return fib(n - 1) + fib(n - 2)
python -m doctest main.py Failed example: fib(7) Expected: 10 Got:
13 **************************** 1 items had failures: 1 of 4 in main.fib ***Test Failed*** 1 failures.
main.py import unittest def fib(n): """Returns the n th fibonacci
number. For example: >>> fib(5) 5 >>> fib(6) 8 >>> fib(5) + fib(6) 13 >>> fib(7) 13 """ if n == 0: return 0 elif n == 1: return 1 else: return fib(n - 1) + fib(n - 2)
Property Based Testing
from hypothesis import given from hypothesis.strategies import integers class TestFib(unittest.TestCase):
@given(k=integers(min_value=2)) def test_fib(self, k): self.assertTrue(fib(k), fib(k - 1) + fib(k - 2)) https://github.com/HypothesisWorks @DRMacIver
It’s impossible to conduct research without software, say 7 out
of 10 UK researchers Simon Hettrick uk/blog/2016-09-12-its-impossible-conduct-research-without-out-10-uk- researchers
USE 92%
IMPOSSIBLE 69%
DEVELOP 56%
TRAINING 79%
USE 92% IMPOSSIBLE 69% DEVELOP 56% TRAINING 79%
Axelrod : https://github.com/Axelrod-Python/Axelrod Arcas: https://github.com/Nikoleta-v3/Arcas Ciw: https://github.com/CiwPython/Ciw Pandas: https://github.com/pandas-dev/pandas Skleanr:
http://scikit-learn.org/stable/ Numpy: https://github.com/numpy/numpy cryptography: https://github.com/pyca/cryptography fastnumbers: https://github.com/SethMMorton/fastnumbers yacluster: https://github.com/KrzysiekJ/yacluster binaryornot: https://github.com/audreyr/binaryornot . . .
None
@NikoletaGlyn https://github.com/Nikoleta-v3 @SoftwateSaved @PhoenixCUni