Category: Python

VS Code “Test result not found for:” When Running Tests for a Python Project [SOLVED]

Posted on by rchapin

I finally was able to get Visual Studio Code set-up correctly to run and debug unit and integration tests for a Python 3.8 project that I am working on (I’ll add a link to that post here once it is up).

After making some changes to the code and adding a test I got the following error when trying to debug the test:

Test result not found for: ./mylibs/integration_tests/myclient_integration_test.py::MyClientIntegrationTest::test_happy_path

? An odd error message, to be sure.

After a little while I figured out that when this happens it is ultimately the result of some syntax, interpretation error that occurs at runtime that the IDE may not flag as a problem for you.

Check the Output panel and click on the drop-down and select Python Test Log to see the stack trace of the error to see where you have a typo.

Compiling Python Under Linux

Posted on by rchapin

The following should work with just about any version of Python. I am using it to compile, currently 3.10.x, on distros where those packages are not readily available for installation. The following is a quick how to on getting it compiled under both RedHat/CentOS/Almalinux and Debian based systems.

Download the Tarball for the Version You Want To Install

Download the tar.gz archive for the version that you want to install from here. Verify the download and then save the path to this file for later.

Install Dependencies

This assumes that you already have the “build-essentials” and kernel headers installed on the box, which is an exercise for the reader.

RedHat/CentOS/Almalinux

yum install -y bzip2-devel expat-devel gdbm-devel ncurses-devel openssl-devel readline-devel wget sqlite-devel tk-devel xz-devel zlib-devel libffi-devel gmp-devel libmpc-devel mpfr-devel openssl-devel liblzma-devel

Debian

apt install -y build-essential zlib1g-dev libncurses5-dev libgdbm-dev libnss3-dev libssl-dev libsqlite3-dev libreadline-dev libffi-dev curl libbz2-dev liblzma-dev

Compile Python

The following enables a non-root user to unpack, compile, and install it into their home directory. Copy this file to /var/tmp/compile-python.sh and then run as follows

/var/tmp/compile-python.sh <path-to-tarball>
#!/bin/bash

set -u
set -e

# The path to the downloaded tarball
py_tarball=$1

export PY_DIR=$(echo $py_tarball | awk -F/ '{ print $NF }' | sed 's/.tgz//')
export PY_PREFIX=$(echo ~/usr/local/$PY_DIR | tr [:upper:] [:lower:])

mkdir -p ~/usr/local/src ~/usr/local/bin ~/usr/local/include $PY_PREFIX
rm -rf $PY_PREFIX
tar -xzf $py_tarball -C ~/usr/local/src/
cd ~/usr/local/src/$PY_DIR
./configure --prefix=$PY_PREFIX --exec-prefix=$PY_PREFIX
make && make install

Add the following to your PATH in ~/.bash_profile

PYTHON_HOME=~/usr/local/python-<version>

export PATH=$PATH:$PYTHON_HOME/bin

Creating a Launch Config in VSCode to Debug a Python Invoke Script

Posted on by rchapin

I regularly use Python Invoke and Fabric for the automation of various tasks; from deploying code to developing my own set of tools for various projects. Following is an example on how to write a launch.json launch configuration for vscode so that you can step through the tasks.py code and debug it.

Assuming that you have created a virtual environment and pip installed invoke into it. And, assuming that you have defined a task in your tasks.py file as follows:

from invoke import task

@task()
def do_something(ctx, some_path, some_other_path):
    # Do something with data in these dirs . . .

The following is a template you can use for a launch configuration that you can use to debug your task. 

{
  "version": "0.2.0",
  "configurations": [
    {
      "name": "invoke",
      "type": "python",
      "request": "launch",
      // The complete path to the invoke python script in your virtual environment
      "program": "/my/virtualenv/path/bin/invoke",
      "justMyCode": false,
      // The args that you would otherwise enter on the command line
      // when invoking your task
      "args": [
        "do-something",
        "--some-path",
        "/var/tmp/a/",
        "--some-other-path",
        "/var/tmp/b/"
      ],
      "cwd": "/the/path/to/the/dir/that/contains/your/tasks/script",
    }
  ]
}

Creating a Counter or Progress Bar for a Python Program

Posted on by rchapin

I’ve written a number of Python apps where I would like it to print some sort of counter or progress bar to STDOUT to let me know that it is still running instead of locked up or died somehow without me being able to see it.

I had tried using a couple of different existing progress bar related modules but none of them really worked except in a very specific use case.

So, after a bit of futzing around I came up with a very simple way to print out a updating counter to STDOUT. The synchronization code was gleaned from this post here, thank you Daniel.

Following is a working example for Python 3.7. You could write your own implementation of the progress function to render whatever you want to STDOUT.

import threading
import sys
import time

def synchronized(func):
    func.__lock__ = threading.Lock()
    def synced_func(*args, **kws):
        with func.__lock__:
            return func(*args, **kws)
    return synced_func

total = 0

@synchronized
def progress(count):
    global total
    total += count
    sys.stdout.write(f'\rtotal: [{total}]')
    sys.stdout.flush()

for i in range(500):
    progress(1)
    time.sleep(0.01)

print(f'\nFinished...')

Running this will generate the following output with the total value dynamically updating as the application runs:

(progressbar) rchapin@leviathan:progressbar$ python progressbar.py 
total: [500]
Finished...

Dynamically Instantiating Classes in Python

Posted on by rchapin

A common design pattern is to define a class or list of classeses in configuration such that at runtime the classes can be dynamically instantiated.

I’ve done this before in many other languages and had need to do so today in Python (2.7.11)

It seems as though the clean way to do so is by using the Pyton importlib module.  By using it, it enables you to cleanly dynamically import sub modules

Following is an example:

import importlib

klass_1_module = 'some.module.name'
klass_1_classname = 'KlassNameOne'

klass_2_module = 'klass2module'
klass_2_classname = 'KlassNameOne'

Klass1 = getattr(importlib.import_module(klass_1_module), klass_1_classname)
klass1_instance = Klass1()

Klass2 = getattr(importlib.import_module(klass_2_module), klass_2_classname)
klass2_instance = Klass1('some_arg')
© 2005 Ryan Chapin