Here's my jupyter notebook's cell 1 (notebook is called tested.ipynb)
def func(a,b):
return a+b
Here's the testbook testing python code (tester.py):
import testbook
#testbook.testbook('tested.ipynb',execute=True)
def test_func(tb):
func=tb.ref("func")
assert func(1,2)==0
I then run the following command from terminal:
python tester.py
It should fail the unit test. But I'm not getting any output at all. No failures, no messages. How do I make the failure appear?
That's because you still need to use pytest, or another unit testing library, to run your tests. Note under 'Features' it says:
"Works with any unit testing library - unittest, pytest or nose" -SOURCE
Testbook just makes writing the unit tests easier. See here under 'Unit testing with testbook' for an example of the process of using testbook in your toolchain with pytest, although bear in mind a lot of the syntax doesn't match the the current documentation. And so instead of running python tester.py from the terminal, run the following command from terminal if you've installed pytest:
pytest tester.py
One thing I note, is that your import and decorator lines don't match the current documentation. Nevertheless, your code works when using pytest tester.py. However, it may be best to adopt the current best practices illustrated in the documentation to keep your code more robust as development continues.
Related
I have developed a very basic microservice using Flask framework.
A method in the application looks like this
#app.route('/add, methods=['POST'])
def add_info():
final = []
try:
info_obj.append(json.loads(request.data))
...
return jsonify(final)
Now I am attempting to write Unittest for this method and other method in this microservice. I am using import unittest to write my test.
Now here I am confused is how can I write tests to test the functionality of these http functions, which don't take regular argument of return regular results but rather fetch arguments from request data and return json based on that.
Is my approach correct? and if yes how can I test Microservices-like functionality using unittest module?
If you absolutely want unittesting, follow Patrick's guide here. But I suggest using PyTest. It's a breeze to get started. First you need a conftest.py. Then add your testfiles named test_... .py . The where your conftest is do $ pytest
Patrick has yet another PyTest + Flask guide here. You can view a demo of a conftest in a project here on how to set up db etc and a test file here
Why log10() is failing to be recognized when called within a function definition in another script? I'm running Python3 in Anaconda (Jupyter and Spyder).
I've had success with log10() in Jupyter (oddly without even calling "import math"). I've had success with defining functions in a .py file and calling those functions within a separate script. I should be able to perform a simple log10.
I created a new function (in Spyder) and saved it in a file "test_log10.py":
def test_log10(input):
import math
return math.log10(input)
In a separate script (Jupyter notebook) I run :
import test_log10
test_log10.test_log10(10)
I get the following error:
"NameError: name 'log10' is not defined"
What am I missing?
Since I'm not using the environment of Jupyther and alike, I don't know how to correct it in these system, perhaps there is some configuration file over there,check the documentation.
But exactly on the issue, when this happens its because python has not "linked" well something at the import, so I suggest a workaround with the libs in the next way:
import numpy as np
import math
and when you are using functions from math, simply add the np. before, i.e.:
return math.log10(input)
to
return np.math.log10(input)
Exactly I don't know why the mismatch, but this worked for me.
I'm new to NiFi. I'm trying to execute a Python script using ExecuteScript processor. When I tried a simple script which has no import commands it ran fine and showed output in nifi.StdOut. When I tried to run a script which includes import commands like import pandas. It showing the below error:
Import Error: No module named Pandas
I tried providing the path of the pkgs in the Module directory in properties. But it doesn't workout. Any help would be appreciated!
I believe the issue is that pandas is a natively-compiled module (it is written in C) rather than being pure Python. The reason this is a problem is that due to the JSR-223 engine, the Apache NiFi ExecuteScript processor uses Jython rather than actual Python. So Python code is fine to run, but it can't depend on modules that aren't pure Python.
The workaround is to use the ExecuteStreamCommand processor to invoke the Python script which depends on pandas via the command-line (i.e. python my_script_that_uses_pandas.py). The flowfile content will be streamed to STDIN and captured from STDOUT. Here's a related answer describing this in detail.
The goal is to use the pytest unit test framework for a Python3 project that uses Cython. This is not a plug-and-play thing, because pytest by default is not able to import the Cython modules. Namely, I get the following error when importing from a Cython .pyx module, in my case named 'calculateScore':
package/mainmodule.py:5: in <module>
from calculateScore import some_functions
E ImportError: No module named 'calculateScore'
This problem occurs both when using the pytest-runner as well as the pytest-cython approach. Strangely enough, the code runs just fine as a python application when you're not trying to test it using pytest.
Changing the import style to import calculateScore or import package.calculateScore does not help.
I have no idea why this is happening, but for me the easiest solution was to use the pytest-cython approach and change one or multiple things listed below in the package's setup.py file:
when defining your Extension for the ext_modules to include the Cython .pyx files, do not use distutils.extension.Extension but rather use setuptools.Extension
The reason why I manually create an Extension instead of using the Cython.Build.cythonize function, is not important here. But please note that for the pytest-runner approach:
do not use the cythonize function, but create the Extension manually
After writing this post I cannot even seem to reproduce the problem using pytest-cython anymore, which suggests that maybe something else is the cause of the problem. An additional thing you could try is to make sure that:
when manually creating an Extension for your .pyx module, make sure the name of the Extension is identical to the name of the module (so name it 'calculateScore' and not for instance 'package.calculateScore').
delete the compiled .so file corresponding to your .pyx file and then re-run.
I wrote some python code that works great, now I'm tasked with writing tests for that code.
My team uses mock and pytest, but I haven't really been able to copy-paste and modify something useful.
I just need a kick start, for example here is a part of my code:
ssh = paramiko.SSHClient()
ssh.load_system_host_keys()
ssh.connect(hostname='1.2.3.4', username='ubuntu')
Can someone help me write a simple unittest for this?
I understand that going forward I'd have to think about my code and write the tests as I go, but I've never done this before so I'm really just looking to get a practical start to get going.
Unit testing ensures the code works per requirements. Get the requirements and write tests to check that the code works and show that the code throws appropriate errors. You can use RobotFramework or another test automation SW to automate the tests. Some questions you might ask yourself are listed below:
ssh = paramiko.SSHClient()
Does paramiko.SSHClient exist?
is it working?
what if it fails?
do you get an error or does the SW hang?
ssh.load_system_host_keys()
Can you load the system keys?
How can you verify this?
ssh.connect(hostname='1.2.3.4', username='ubuntu')
How can you prove the connection exists?
What happens if you try to connect to another host?
Do you get an error message?
Can you logon with username 'ubuntu'?
What if you try another username?
Does the connection fail?
Do you get a generic error so you don't give crackers clues about your security?
Proof of unit testing is usually a screen capture, log entry, or some documentation showing you got the result you expected when you ran the test. Hope this helps.
you can use unit test module like below
import unittest
import paramiko
class SimpleWidgetTestCase(unittest.TestCase): #This class inherits unittest.TestCase
#setup will run first
def setUp(self):
self.ssh = paramiko.SSHClient()
self.ssh.load_system_host_keys()
self.ssh.connect(hostname='1.2.3.4', username='ubuntu')
#Your test cases goes here with 'test' prefix
def test_split(self):
#your code here
pass
#this will run after the test cases
def tearDown(self):
#your code to clean or close the connection
pass
if __name__ == '__main__':
unittest.main()
detailed information about how to use unittest can be found here https://docs.python.org/2/library/unittest.html
one suggestion: robotframework is better option to design test cases in comparison to unit test, so until unless its not compulsory , you can invest your time in Robotframework