Waylon Walker WaylonWalker

## dynamic_pydantic_models.py
from datetime import datetime
from typing import List, Optional

from pydantic import BaseModel, create_model, validator
import toml


class User(BaseModel):
    id: int
    name = "John Doe"

## first_nodes.py
"""
first_nodes.py

used in video https://youtu.be/-gEwU-MrPuA
Full Post 👉 https://waylonwalker.com/kedro-your-first-nodes/
"""

from kedro.pipeline import node


## ipython_prompt.py
from IPython.terminal.prompts import Prompts, Token
from pathlib import Path
import os
from platform import python_version
import subprocess

def get_branch():
    try:
        return (
            subprocess.check_output(

## standard_config.py
"""Standard Config.
A module to load tooling config from a users project space.

One day this may become a package, for now its a gist.

Inspired from frustrations that some tools have a tool.ini, .tool.ini,
setup.cfg, or pyproject.toml.  Some allow for global configs, some don't.  Some
properly follow the users home directory, others end up in a weird temp
directory.  Windows home directory is only more confusing.  Some will even
respect the users `$XDG_HOME` directory.

## copy_easyclip_to_windows.py
import re
import pyperclip


def copy():
    with open('C:/Debian/rootfs/home/<user>/.easyclip') as f:
        easyclip = f.readlines(1)

    first = re.sub(r"^.*text': '", "", easyclip[0])
    last = re.sub(r"'}\n$", "", first)

## KedroBasics_startup.sh
#!/bin/bash
# curl -s -L https://gist.githubusercontent.com/WaylonWalker/0532e9e9f41432d9a375490235286cd6/raw/4bc499518889aa9ad8ee0e410bc44f96a860f1e0/KedroBasics_startup.sh | bash
apt-get update
DEBIAN_FRONTEND=noninteractive apt-get upgrade -yq

apt install zsh -y
sh -c "$(curl -fsSL https://raw.githubusercontent.com/ohmyzsh/ohmyzsh/master/tools/install.sh)" "" --unattended
mkdir -p ~/starship
wget https://starship.rs/install.sh -O ~/starship/install.sh
bash ~/starship/install.sh -y

## kedro-debug-hook.py
""" Kedro Debug Hook module """
from kedro.framework.hooks import hook_impl

class debug_hook:
    """ Kedro Debug Hook

    Opens a debugger at any hook-able point of your kedro projects lifecycle.
    debug_hook is applied by adding it to the pipeline and setting the desired
    debug points to true.

## kedro-class-hook-template.py
from kedro.framework.hooks import hook_impl

class <hook_name>:

    def __init__(self):
        pass

    @hook_impl
    def before_pipeline_run(self, run_params, pipeline, catalog):
        pass

## kedro-preflight.py
# full article https://waylonwalker.com/blog/creating-the-kedro-preflight-hook/

from kedro.hooks import hook_impl
from kedro.io.core import DataSetNotFoundError
from colorama import Fore
import textwrap


@hook_impl
def before_pipeline_run(run_params, pipeline, catalog):

## jupyter-onedark.css
/*-----------------------------------------------------------------------------
| Copyright (c) Jupyter Development Team.
| Distributed under the terms of the Modified BSD License.
|----------------------------------------------------------------------------*/
/*
The following CSS variables define the main, public API for styling JupyterLab.
These variables should be used by all plugins wherever possible. In other
words, plugins should not define custom colors, sizes, etc unless absolutely
necessary. This enables users to change the visual theme of JupyterLab
by changing these variables.
	from datetime import datetime
	from typing import List, Optional

	from pydantic import BaseModel, create_model, validator
	import toml


	class User(BaseModel):
	id: int
	name = "John Doe"
	"""
	first_nodes.py

	used in video https://youtu.be/-gEwU-MrPuA
	Full Post 👉 https://waylonwalker.com/kedro-your-first-nodes/
	"""

	from kedro.pipeline import node
	from IPython.terminal.prompts import Prompts, Token
	from pathlib import Path
	import os
	from platform import python_version
	import subprocess

	def get_branch():
	try:
	return (
	subprocess.check_output(
	"""Standard Config.
	A module to load tooling config from a users project space.

	One day this may become a package, for now its a gist.

	Inspired from frustrations that some tools have a tool.ini, .tool.ini,
	setup.cfg, or pyproject.toml. Some allow for global configs, some don't. Some
	properly follow the users home directory, others end up in a weird temp
	directory. Windows home directory is only more confusing. Some will even
	respect the users `$XDG_HOME` directory.
	import re
	import pyperclip


	def copy():
	with open('C:/Debian/rootfs/home/<user>/.easyclip') as f:
	easyclip = f.readlines(1)

	first = re.sub(r"^.*text': '", "", easyclip[0])
	last = re.sub(r"'}\n$", "", first)
	#!/bin/bash
	# curl -s -L https://gist.githubusercontent.com/WaylonWalker/0532e9e9f41432d9a375490235286cd6/raw/4bc499518889aa9ad8ee0e410bc44f96a860f1e0/KedroBasics_startup.sh \| bash
	apt-get update
	DEBIAN_FRONTEND=noninteractive apt-get upgrade -yq

	apt install zsh -y
	sh -c "$(curl -fsSL https://raw.githubusercontent.com/ohmyzsh/ohmyzsh/master/tools/install.sh)" "" --unattended
	mkdir -p ~/starship
	wget https://starship.rs/install.sh -O ~/starship/install.sh
	bash ~/starship/install.sh -y
	""" Kedro Debug Hook module """
	from kedro.framework.hooks import hook_impl

	class debug_hook:
	""" Kedro Debug Hook

	Opens a debugger at any hook-able point of your kedro projects lifecycle.
	debug_hook is applied by adding it to the pipeline and setting the desired
	debug points to true.
	from kedro.framework.hooks import hook_impl

	class <hook_name>:

	def __init__(self):
	pass

	@hook_impl
	def before_pipeline_run(self, run_params, pipeline, catalog):
	pass
	# full article https://waylonwalker.com/blog/creating-the-kedro-preflight-hook/

	from kedro.hooks import hook_impl
	from kedro.io.core import DataSetNotFoundError
	from colorama import Fore
	import textwrap


	@hook_impl
	def before_pipeline_run(run_params, pipeline, catalog):
	/*-----------------------------------------------------------------------------
	\| Copyright (c) Jupyter Development Team.
	\| Distributed under the terms of the Modified BSD License.
	\|----------------------------------------------------------------------------*/
	/*
	The following CSS variables define the main, public API for styling JupyterLab.
	These variables should be used by all plugins wherever possible. In other
	words, plugins should not define custom colors, sizes, etc unless absolutely
	necessary. This enables users to change the visual theme of JupyterLab
	by changing these variables.