mock<\/code> is available in Python 3 in the stdlib, as unittest.mock<\/code>.<\/p>\n\n\n\nInformation about the Python 2.x environment is reproduced below:<\/p>\n\n\n\n
The Python environment is augmented with a few REPL features as well as some helpful libraries.<\/p>\n\n\n\n
The REPL uses IPython<\/a> to provide a REPL with history, highlighting, and autocomplete. Additionally, whenever you run scripts in CoderPad\u2019s editor, the REPL will deposit you at the exact line and state of any exceptions. If there were no errors, you will have a REPL with access to all of the variables and functions defined in your script.<\/p>\n\n\n\nThe libraries included and ready for importing are:<\/p>\n\n\n\n
\n- requests<\/a> for simpler HTTP requests.<\/li>\n\n\n\n
- beautifulsoup4<\/a> for HTML parsing.<\/li>\n\n\n\n
- numpy<\/a>, scipy<\/a>, pandas<\/a>, scikit-learn<\/a>, and statsmodels<\/a> for advanced numerical analysis. Unfortunately, plotting does not work in CoderPad\u2019s purely textual interface at this time.<\/li>\n<\/ul>\n\n\n\n
Testing<\/h3>\n\n\n\n
We\u2019ve got a few ways you can test your Python code in CoderPad:<\/p>\n\n\n\n
\n- The unittest<\/a> library that ships with Python by default. Here\u2019s a quick example:<\/li>\n<\/ol>\n\n\n
import<\/span> unittest\n\nclass<\/span> TestStringMethods<\/span>(unittest.TestCase)<\/span>:<\/span>\n def<\/span> test_upper<\/span>(self)<\/span>:<\/span>\n self.assertEqual('foo'<\/span>.upper(), 'FOO'<\/span>)\n\n def<\/span> test_isupper<\/span>(self)<\/span>:<\/span>\n self.assertTrue('FOO'<\/span>.isupper())\n self.assertFalse('Foo'<\/span>.isupper())\n\n def<\/span> test_split<\/span>(self)<\/span>:<\/span>\n s = 'hello world'<\/span>\n self.assertEqual(s.split(), ['hello'<\/span>, 'world'<\/span>])\n # s.split should throw when the separator is not a string<\/span>\n with<\/span> self.assertRaises(TypeError):\n s.split(2<\/span>)\n\nunittest.main(exit=False<\/span>)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n\n- pytest<\/a>. The above snippet of code would look like the following when written for pytest:<\/li>\n<\/ol>\n\n\n
import<\/span> pytest\n\ndef<\/span> test_upper<\/span>()<\/span>:<\/span>\n assert<\/span> 'foo'<\/span>.upper() == 'FOO'<\/span>\n\ndef<\/span> test_isupper<\/span>()<\/span>:<\/span>\n assert<\/span> 'FOO'<\/span>.isupper()\n assert<\/span> not<\/span> 'Foo'<\/span>.isupper()\n\ndef<\/span> test_split<\/span>()<\/span>:<\/span>\n s = 'hello world'<\/span>\n assert<\/span> s.split() == ['hello'<\/span>, 'world'<\/span>]\n # s.split should throw when the separator is not a string<\/span>\n with<\/span> pytest.raises(TypeError):\n s.split(2<\/span>)\n\npytest.main()<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n\n- mock<\/a> is also available if you need to stub out some behavior.
mock<\/code> can be combined with unittest<\/code> and pytest<\/code>. Here\u2019s a quick usage example:<\/li>\n<\/ol>\n\n\nfrom<\/span> mock import<\/span> Mock\n\nmock = Mock()\nmock.method(1<\/span>, 2<\/span>, 3<\/span>)\nmock.method.assert_called_with('this should break'<\/span>)<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\n\n- hypothesis<\/a> is available for property-based testing in Python. Calling
test_decode_inverts_encode()<\/code> fires up Hypothesis and tries to find an input that breaks your code. You can read more about it on their website, but here\u2019s a stubbed example of how you might test that an encoding and decoding function both work:<\/li>\n<\/ol>\n\n\nfrom<\/span> hypothesis import<\/span> given\nfrom<\/span> hypothesis.strategies import<\/span> text\n\ndef<\/span> encode<\/span>(string)<\/span>:<\/span>\n # return encoded string<\/span>\n\ndef<\/span> decode<\/span>(string)<\/span>:<\/span>\n # return decoded string<\/span>\n\n@given(text())<\/span>\ndef<\/span> test_decode_inverts_encode<\/span>(s)<\/span>:<\/span>\n assert<\/span> decode(encode(s)) == s\n\ntest_decode_inverts_encode()<\/code><\/span>Code language:<\/span> Python<\/span> (<\/span>python<\/span>)<\/span><\/small><\/pre>\n\n\nDisplaying charts and graphs<\/h3>\n\n\n\n
If you want to display a chart or graph using libraries like Matplotlib<\/a>, you can use a pad with Django<\/a> selected. <\/p>\n\n\n\n![\"Pad](\"https:\/\/d2h1bfu6zrdxog.cloudfront.net\/wp-content\/uploads\/2023\/01\/image-82-1024x519.png\")
<\/a><\/figure>\n<\/div>\n\n\nDjango is a Python-based web framework that will allow you to display your charts in a convenient interface. We’ve created a ready-made Matplotlib sandbox pad<\/a> for you to use, all you need to do is edit the view.py<\/code> file with your chart or graph code and it will display to the UI on the right via the matplotlib.htm<\/code>l file.<\/p>\n\n\n\n![\"\"](\"https:\/\/d2h1bfu6zrdxog.cloudfront.net\/wp-content\/uploads\/2023\/01\/image-83-1024x466.png\")
<\/figure>\n\n\n\nIf you’d like to use another charting library, simply install the library using pip3 install [package]<\/code> in the Shell<\/strong> tab on the bottom right corner, and edit the view.py<\/code> file as needed to display the appropriate graph.<\/p>\n\n\n\n
![\"A](\"https:\/\/d2h1bfu6zrdxog.cloudfront.net\/wp-content\/uploads\/2023\/01\/image-84.png\")
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