Posts tagged: python

All posts with the tag "python"

268 posts latest post 2026-03-31
Publishing rhythm
Jan 2026 | 3 posts
Glances can watch docker processes

Glances is a system monitor with a ton of features, including docker processes.

I have started using portainer to look at running docker processes, its a great heavy-weight docker process monitor. glances works as a great lightweight monitor to just give you the essentials, ( Name, Status, CPU%, MEM, /MAX, IOR/s, IOW/s, Rx/s, Tx/s, Command)

You will need to install glances to use the glances webui. We can still use pipx to manage our virtual environment for us so that we do not need to do so manually or run the risk of globally installed package dependency hell.

pipx install glances pipx inject glances "glances[docker]"

You will be presented with this success message.

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Glances webui with pipx

Glances has a pretty incredible webui to view system processes and information like htop, or task manager for windows.

The nice thing about the webui is that it can be accessed from a remote system. This would be super nice on something like a raspberry pi, or a vm running in the cloud. Its also less intimidating and easier to search if you are not a terminal junky.

You will need to install glances to use the glances webui. We can still use pipx to manage our virtual environment for us so that we do not need to do so manually or run the risk of globally installed package dependency hell.

pipx install glances pipx inject glances "glances[web]"

You will be presented with this success message.

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Run glances without install with pipx

Glances is a fully featured system monitoring tool written in python. Out of the box it’s quite similar to htop, but has quite a few more features, and can be ran without installing anything other than pipx, which you should already have installed if you do anything with python.

pipx run glances

Once you run this you will be in a tui application similar to htop. You can kill processes with k, use left and right arrows to change the sorting column, and up and down to select different processes.

Nested requirements.txt in python

python requirements text files can in fact depend on each other due to the fact that you can pass pip install arguments right into your requirements.txt file. The trick is to just prefix the file with a -r flag, just like you would if you were installing it with pip install

Lets create two requirements files in a new directory to play with.

mkdir requirements-nest cd requirements-nest touch requirements.txt requirements_dev.txt

Then add the following to each requirements file.

# requirements.txt kedro[pandas.ParquetDataSet] 

# requirements_dev.txt -r requirements.txt ipython

Installing #

Installing requirements_dev.txt will install both ipython and pandas since it includes the base requirements file.

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View AWS event bridge rules with visidata

Reading eventbridge rules from the command line can be a total drag, pipe it into visidata to make it a breeze.

I just love when I start thinking through how to parse a bunch of json at the command line, maybe building out my own custom cli, then the solution is as simple as piping it into visidata. Which is a fantastic tui application that had a ton of vim-like keybindings and data features.

Read stderr from python subprocess.Popen

I often run shell commands from python with Popen, but not often enough do I set up error handline for these subprocesses. It’s not too hard, but it can be a bit awkward if you don’t do it enough.

import subprocess from subprocess import Popen # this will run the shell command `cat me` and capture stdout and stderr proc = Popen(["cat", "me"], stdout=subprocess.PIPE, stderr=subprocess.PIPE) # this will wait for the process to finish. proc.wait()

reading from stderr #

To get the stderr we must get it from the proc, read it, and decode the bystring. Note that we can only get the stderr object once, so if you want to do more than just read it you will need to store a copy of it.

proc.stderr.read().decode()

Better Exception #

Now that we can read the stderr we can make better error tracking for the user so they can see what to do to resolve the issue rather than blindly failing.

Using a Python Markdown ast to Find All Paragraphs

In looking for a way to automatically generate descriptions for pages I stumbled into a markdown ast in python. It allows me to go over the markdown page and get only paragraph text. This will ignore headings, blockquotes, and code fences.

import commonmark import frontmatter post = frontmatter.load("post.md") parser = commonmark.Parser() ast = parser.parse(post.content) paragraphs = '' for node in ast.walker(): if node[0].t == "paragraph": paragraphs += " " paragraphs += node[0].first_child.literal

It’s also super fast, previously I was rendering to html and using beautifulsoup to get only the paragraphs. Using the commonmark ast was about 5x faster on my site.

When I originally wrote this post, I did not realize at the time that commonmark duplicates nodes. I still do not understand why, but I have had success duplicating them based on the source position of the node with the snippet below.

python dict get

For an embarassingly long time, til today, I have been wrapping my dict gets with key errors in python. I’m sure I’ve read it in code a bunch of times, but just brushed over why you would use get. That is until I read a bunch of PR’s from my buddy Nic and notice that he never gets things with brackets and always with .get. This turns out so much cleaner to create a default case than try except.

Lets consider this example for prices of supplies. Here we set a variable of prices as a dictionary of items and thier price.

prices = {'pen': 1.2, 'pencil', 0.3, 'eraser', 2.3}

Except KeyError #

What I would always do is try to get the key, and if it failed on KeyError, I would set the value (paper_price in this case) to a default value.

try: paper_price = prices['paper'] except KeyError: paper_price = None

.get #

What I noticed Nic does is to use get. This feels just so much cleaner that it’s a one liner and feels much easier to read and...

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Find all Headings with BeautifulSoup

BeautifulSoup is a DOM like library for python. It’s quite useful to manipulate html. Here is an example to find_all html headings. I stole the regex from stack overflow, but who doesn’t.

sample.html

Lets make a sample.html file with the following contents. It mainly has some headings, <h1> and <h2> tags that I want to be able to find.

<!DOCTYPE html> <html lang="en"> <body> <h1>hello</h1> <p>this is a paragraph</p> <h2>second heading</h2> <p>this is also a paragraph</p> <h2>third heading</h2> <p>this is the last paragraph</p> </body> </html>

Get the headings with BeautifulSoup #

Lets import our packages, read in our sample.html using pathlib and find all headings...

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Lambda Function as a Kedro Node

I keep my nodes short and sweet. They do one thing and do it well. I turn almost every DataFrame transformation into its own node. It makes it must easier to pull catalog entries, than firing up the pipeline, running it, and starting a debugger. For this reason many of my nodes can be built from inline lambdas.

Here are two examples, the first one lambda x: x is sometimes referred to as an identity function. This is super common to use in the early phases of a project. It lets you follow standard layering conventions, without skipping a layer, overthinking if you should have the layer or not, and leaves a good placholder to fill in later when you need it.

Many times I just want to get the data in as fast as possible, learn about it, then go back and tidy it up.

from kedro.pipeline import node my_first_node = node( func=lambda x: x, inputs='raw_cars', output='int_cars', tags=['int',] ) my_first_node = node( func=lambda cars: cars[['mpg', 'cyl', 'disp',]].query('disp>200'), inputs='raw_cars', output='int_cars', tags=['pri',] )

Note: try not to take the idea...

Add New Dependencies to Your Kedro Project

As you work on your kedro projects you are bound to need to add more dependencies to the project eventually. Kedro uses a fantastic command pip-compile under the hood to ensure that everyone is on the same version of packages at all times, and able to easily upgrade them. It might be a bit different workflow than what you have seen, let’s take a look at it.

Before you start mucking around with any changes to dependencies make sure that your git status is clean. I’d even reccomend starting a new branch for this, and if you are working on a team potentially submit this as its own PR for clarity.

git status git checkout main git checkout -b add-rich-dependency

requirements.in #

New requirements get added to a requirements.in file. If you need to specify an exact version, or a minimum version you can do that, but if all versions generally work you can leave it open.

# requirements.in rich

Here I added the popular rich package to my requirements.in file. Since I am ok with the latest version I am not going to pin anything,...

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Practice making pipelines with kedro

I am a huge believer in practicing your craft. Professional athletes spend most of their time honing their skills and making themsleves better. In Engineering many spend nearly 0 time practicing. I am not saying that you need to spend all your free time practicing, but a few minutes trying new things can go a long way in how you understand what you are doing and make a hue impact on your long term productivity.

What is Kedro

practice building pipelines with #kedro today

Go to your playground directory, and if you don’t have one, make one.

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Tmux hotkey for copier templates

I have added a hotkey to my copier template setup to quickly access all my templates at any time from tmux. At any point I can hit <c-b><c-b>, thats holding control and hitting bb, and I will get a popup list of all of my templates directory names. Its an fzf list, which means that I can fuzzy search through it for the template I want, or arrow key to the one I want if I am feeling insane. I even setup it up so that the preview is a list of the files that come with the template in tree view.

bind-key c-b popup -E -w 80% -d '#{pane_current_path}' "\ pipx run copier copy ~/.copier-templates/`ls ~/.copier-templates |\ fzf --header $(pwd) --preview='tree ~/.copier-templates/{} |\ lolcat'` . \ "

I’ve had this on my systems for a few weeks now and I am constantly using it for my tils,

python linux tmux copier
Markata Filters as Telescope Pickers in Neovim

I often pop into my blog from neovim with the intent to look at just a single series of posts, til, gratitude, or just see todays posts. Markata has a great way of mapping over posts and returning their path that is designe exactly for this use case.

Markata listing out posts from the command line

To tie these into a Telescope picker you add the command as the find_command, and comma separate the words of the command, with no spaces. I did also --sort,date,--reverse in there so that the newest posts are closest to the cursor.

nnoremap geit <cmd>Telescope find_files find_command=markata,list,--map,path,--filter,date==today<cr> nnoremap geil...

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Copier Tasks | Python templating post run task

Copier allows you to run post render tasks, just like cookiecutter. These are defined as a list of tasks in your copier.yml. They are simply shell commands to run.

The example I have below runs an update-gratitude bash script after the copier template has been rendered.

# copier.yml num: 128 _answers_file: .gratitude-copier-answers.yml _tasks: - "update-gratitude"

I have put the script in ~/.local/bin so that I know it’s always on my $PATH. It will reach back into the copier.yml and update the default number.

Gradual Typing in Python

I’ve referenced a video from Anthony Sotile in passing conversation several times. Walking through his gradual typing process has really helped me understand typing better, and has helped me make some projects better over time rather than getting slammed with typing errors.

https://youtu.be/Rk-Y71P_9KE

Run Mypy as is, don’t get fancy yet. This will not reach into any functions unless they are alreay explicitly typed. It will not enforce you to type them either.

pip install mypy mypy . # or your specific project to avoid .venvs mypy src # or a single file mypy my-script.py

Step 2 #

Next we will add check-untyped-defs, this will start checking inside functions that are not typed. To add this to your config create a setup.cfg with the following.

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Python Reverse Sluggify

In order to make an auto title plugin for markata I needed to come up with a way to reverse the slug of a post to create a title for one that does not explicitly have a title.

Here I have a path available that gives me the articles path, ex. python-reverse-sluggify.md. An easy way to get rid of the file extension, is to pass it into pathlib.Path and ask for the stem, which returns python-reverse-sluggify. Then from There I chose to replace - and _ with a space.

article["title"] = ( Path(article["path"]).stem.replace("-", " ").replace("_", " ").title() )

To turn this into a markata plugin I put it into a pre_render hook.

Get Python docstring with ast

Getting docstrings from python’s ast is far simpler and more reliable than any method of regex or brute force searching. It’s also much less intimidating than I originally thought.

First you need to load in some python code as a string, and parse it with ast.parse. This gives you a tree like object, like an html dom.

py_file = Path("plugins/auto_publish.py") raw_tree = py_file.read_text() tree = ast.parse(raw_tree)

Getting the Docstring #

You can then use ast.get_docstring to get the docstring of the node you are currently looking at. In the case of freshly loading in a file, this will be the module level doctring that is at the very top of a file.

module_docstring = ast.get_docstring(tree)

Walking for all functions

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Python Respect the .gitignore

Many tools such as ripgrep respect the .gitignore file in the directory it’s searching in. This helps make it incredibly faster and generally more intuitive for the user as it just searches files that are part of thier project and not things like their virtual environments, node modules, or compiled builds.

Editors like vscode often do not include files that are .gitignored in their search either.

pathspec is a pattern matching library that implements git’s wildmatch pattern so that you can ignore files included in your .gitignore patterns. You might want this to help make your libraries more performant, or more intuitive for you users.

import pathspec from pathlib import Path markdown_files = Path().glob('**/*.md') if (Path(".gitignore").exists(): lines = Path(".gitignore").read_text().splitlines() spec = pathspec.PathSpec.from_lines("gitwildmatch", lines) markdown_files = [ file for file in...