I found myself in a situation where I had constructed a ProcessState class for storing the results of a cron job that runs on AWS. Passing the instance of ProcessState works just fine when it all happens in a single package. But then I needed to store the state in our database temporarily while the lambda kicks over to another procedure within a step function.

I needed two things:

1. A succinct way to export the state.
2. A way to load the state from the db and re-instantiate my ProcessState class

Two built-in Python methods did the trick: the __dict__ Special Attribute and the @classmethod decorator.

Starting File

Here's ProcessState:

import logging
from logging import Logger
import datetime
from .types.unit_dict import UnitDict


class ProcessState:
    """
    Object for storing and formatting Process State
    """

    def __init__(
        self,
        result: list[UnitDict] = [],
        complete: bool = False,
        errors: list[str] = [],
    ):
        self.result = result
        self.complete = complete
        self.errors = errors
        self.logger = logging.getLogger("ProcessLogger")

    def __repr__(self):
        return f"ProcessState('{self.result}', {self.complete}, {self.errors}"
        
    # Methods for updating and formatting date here.

From the type hints, you'll see that we're dealing here with properties of basic types: lists and a boolean. I've also instantiated the class with a logger.

Exporting with the Dict Attribute

If I want to get all of those properties, I can simply call the __dict__ attribute directly:

ps = ProcessState()

# Update the state here.

# Get the dictionary
dict = ps.__dict__

If I'm only storing values I want to pass along, this works great!

The wrinkle comes with the logger. I'm not interested in passing that along outside of my application. But the result will include reference to the logger.

So I'll have to handle filtering it out with a few helper functions:

class ProcessState:
    """
    Object for storing and formatting Process State
    """
    
    ...

    def get_dict_from_state(self):
        result = {k: v for k, v in self.__dict__.items() if self._is_value_property(v)}
        result["created_at"] = datetime.datetime.now().isoformat()

        return result

    def _is_value_property(self, v):
        if isinstance(v, Logger):
            return False
        return True

I've also gone ahead and added a "created_at" property.

Now, calling ps.get_dict_from_state() would provide only the errors, complete state, and result. Excellent!

Loading a Dictionary Into Our Class

Say I pass the result off to my DB. I then query the db for those values again.

Looking at my __init__ method above, I could almost get away with passing in the dictionary as-is with a spread operator like so:

ps = ProcessState(**dict)

However, my dict now includes a created_at property which I haven't included in the __init__ function!

If it were important to persist that field, I could add it to my init function. Or I could make use of an extra **kwargs at then end of my init signiture to catch any arguements not already defined.

BUT say that I also need to do some data massaging, such as instantiating another class within ProcessStates own initialization?

@classmethod is the answer.

I'll show how I'm using it, then how to construct it:

ps = ProcessState.from_dict(dict)

very similar to calling the __init__ method, though we're not tied to one signature. In fact, we could have multiple @classmethods for different scenarios, lending more flexibility to our instance construction.

The simplest way to implement thiswould be to pass everything in:

class ProcessState:
    """
    Object for storing and formatting Process State
    """
    
    . . . 
    
    @classmethod
    def from_dict(cls, values: dict) -> "CollectionState":
        return cls(**values)

However, as I mentioned, we have an unwanted attribute. Here I'll filter it out with list comprehension:

    @classmethod
    def from_dict(cls, values: dict) -> "CollectionState":
        filtered values = [x for x in values if x in ["errors", "results", "complete"]] 
        return cls(**values)

With that, we're back up and running, ready to use ProcessState in our function!

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No tears, no fears. Remember, there's always tomorrow... ~

Had the pleasure of playing this beautiful piano just outside of the Frisco Discovery Center:

Love painting this pup. Lucy is becoming my muse! 🐕

Sourced from Austin Kleon in his newsletter this week, Brian Eno's 2011 Moscow lecture.

Eno talks on how music (especially classical music) was a performative, hierarchy driven medium. Recorded music, however, takes out that hierarchy and makes the act of creating music more like painting. Really beautiful ideas, the whole thing is worth a listen.

After spending some time in Java, TypeScript, and C#, I've started to miss typing when it's not there.

While Python won't keep from compiling if there's a type issue, the autocomplete and clarity that comes with Type Hinting is a boon to productivity and clarity.

The Basics

A quick, simple example:

def say_name(name: str) -> str:
    return "My name is " + name

name: str is declaring that name is the built-in string type. The -> str denotes that we are returning a string.

Not Fool-Proof

Say that there are some conditions to the function:

def say_name_if_starts_with_j(name: str) -> str:
    if name[0] is 'J':
        return "My name is " + name
    else:
        return False

I've said this method will return a string, but in some cases it returns a boolean. In statically typed languages, this would raise an error at compile time, and/or my editor may alert me to the issue. In Python, however, these are only hints. So this code flies.

Let's fix it before moving on:

from typing import Union

def say_name_if_starts_with_j(name: str) -> Union[str, bool]:
    if name[0] is 'J':
        return "My name is " + name
    else:
        return False

Why It's Called Type Hinting

The main benefit here comes later as I'm calling the function. Say I'm in the middle of writing this code:

name = say_name_if_starts_with_j("Jake The Dog")
name.capitalize()
# autocomplete suggests string methods, such as "capitalize"

Because we've gone through the trouble of typing our return value, my code editor knows to suggest string methods (as well as boolean methods!)

Hovering over the say_name_if_starts_with_j method now also includes a line recreating my defenition:

(method) def say_name_if_starts_with_j(
    name: str
) -> str

We're missing some of the compiling and linting benefits of statically typed languages out of the box with Type Hinting. However, it's a feature of the language that still has value in communication!

Typing here allows for me to be intentional with my methods and allows for an opportunity to communicate clearly the expected inputs and outputs of my function. One less trip to another tab in my code editor or browser can go a long way for keeping the flow going.

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Groovin' on a Sunday mornin'

Our favorite time to walk the trail 🌅

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Recording a new album! Bit of a rock ballad vibe

I recently attended Vintage Computer Festival Southwest. It's a great, no frills celebration of the history and preservation of personal computing. Everything from Atari machines to the single body iMac G3's were present!

We're pretty spoiled with technological advancement and availability over here in the US of A. It's easy to forget how phenomenal what we have is.

If you haven't fooled with a classic computer in a few decaeds — it's an interesting cocktail of experiences! One part nostalgic, a dash of disorientation (how does this work again?), sometimes impressive for the time, and other times quaint.

One thing that was consistent across the folks I chatted with: Everyone had a story where their eyes brightened, the conversation got spirited, and they could tap into an early memory of being enamored with what was possible with a machine. Be it putting a PC together, playing games, or programming.

If you're really open to taking a step into your own early memories with these machines, there's a unique opportunity. It's a chance to connect with the spirit of why technology matters beyond its pragmatic function: to inspire awe and wonder.

(If you're looking for a quick taste, I'd recommend LGR on YouTube. I could watch this man repair 90s PCs for days on end.)

My favorite thing about learning to paint is how sunsets are now even more beautiful to look at. 🌅 🐑

My favorite spot to catch up with writers and artists is from the comfort of my own email inbox. Social media algorithms are fickle and too bite-sized to be sustaining. But sitting down for a couple of minutes to read an email long form is a delight!

I was curious about implementing the infrastructure for this very site. I don't plan on going full-on email marketer! I am interested, though, in a once or twice a year short note on what's going on in my corner of the internet.

And, the fun part — It means getting to write some node code to set up an email subscription flow!

API

My implementation started as a fork of Pete Houston's Simple Newsletter repo on GitHub. If you want to get started quickly with a project like this, I'd highly recommend taking a look there!

I'll breeze through, doing a few steps "off-camera first":

1. Setting Up a MongoDB database to store subscriptions
2. Writing my Schema for the above.
3. Importing Pete's mailer.js file for formatting and sending email templates
4. Integrating the API endpoint in my Next.js app under /pages/api/subscribe.js

This setup is fairly similar to my DIY Analytics put in place for a separate React project.

Writing /pages/api/subscribe.js will expose my endpoint at chrisdpadilla.com/api/subscribe. A POST request there will submit data to save the user subscription and send a welcome email.

Client Flow

Writing the client flow is just good-ol' React. I'll be using state, submitting a form, and handling the results.

On my subscribe.js page, I'll start by setting up state for form fields:

export default function Subscribe() {
  const [firstName, setFirstName] = useState('');
  const [lastName, setLastName] = useState('');
  const [email, setEmail] = useState('');
  const [frequency, setFrequency] = useState('ALL'); 
  const [submitting, setSubmitting] = useState(false);
  const [error, setError] = useState(false);
  const router = useRouter();
  
  ...
  
}

I'm also bringing in the useRouter hook to later forward the user to a success page on completion.

Next, we'll render the form:

return (
    <Layout>
      <Head>
        <title>Newsletter | Chris Padilla</title>
      </Head>
      <Header />
      <Container>
        <h1>Email Newsletter</h1>
        <p>A quiet set of updates — just a couple a year — on what I'm up to. Unsubscribe anytime.</p>
        <p>Looing to update your subscription? <Link href={`/update-sub`}>Click here</Link>.</p>
                <form onSubmit={onSubmit}>
          <label htmlFor="firstName">First name:</label><br />
          <input type="text" id="firstName" name="firstName" required value={firstName} onChange={e => setFirstName(e.currentTarget.value)} /><br />
          <label htmlFor="lastName">Last name:</label><br />
          <input type="text" id="lastName" name="lastName" required value={lastName} onChange={e => setLastName(e.currentTarget.value)} /><br />
          <label htmlFor="email">Email:</label><br />
          <input type="email" id="email" name="email" required value={email} onChange={e => setEmail(e.currentTarget.value)} /><br />
  
          <button type="submit" disabled={submitting}>{submitting ? 'Submitting...' : 'Sign Me Up!'}</button>
          {error && (
            <p>Oops! Something went wrong... try refreshing. If all else fails,  <Link href={`/contact`}>
            <a>reach out to me directly.</a>
          </Link>.</p>
          )}
                </form>
      </Container>
    </Layout>
  );

Next I'll handle radio elements for emailing frequency. Most input fields are simple enough with one element. Radio elements, however, require special logic to work. Here, I'm setting the value to true only if our state matches the current element. The onChange is then responsible for updating the state to its value.

<fieldset value={frequency}>
  <legend>How often would you like to receive emails?</legend>
    <input type="radio" id="contactChoice1" name="frequency" value="ALL" checked={frequency === 'ALL'} onChange={e => setFrequency("ALL")}/>
    <label htmlFor="contactChoice1">Sometimes (a few times a year)</label>

    <input type="radio" id="contactChoice2" name="frequency" value="SOME" checked={frequency === 'SOME'} onChange={e => setFrequency("SOME")}/>
    <label htmlFor="contactChoice2">Rarely (once a year)</label>

    <input type="radio" id="contactChoice3" name="frequency" value="UNSUBSCRIBE" checked={frequency === 'UNSUBSCRIBE'} onChange={e => setFrequency("UNSUBSCRIBE")}/>
    <label htmlFor="contactChoice3">None</label>
  </fieldset><br />

Now for submitting the form! My submit handler will set the submitting state so the input button won't accidentally be double-clicked.

Then, I'll gather the values from state. From there, the fetch API is used to send the request. And upon successful submission, the user is then redirected to /subscribed?n={firstName}. The query param is added to customize the message when they land.

That's all there is to it! There's more work involved with handling updating subscription status and using the templates. If your curious, I'd recommend digging into Pete Houston's Simple Newsletter repo and playing with it yourself!

Oh, by the way! You can see the working page here!

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From Neon Genesis Evangelion! So mysterious. Who is Rei? What is her DEAL even???

Beautiful trail views close to home! 🌳

I came across Maggie Appleton's tremendous post "A Brief History & Ethos of the Digital Garden"!

I've heard of the publishing philosophy in passing and found the term itself to resonate. A counter to high-production, corporate leaning purposes for owning a domain name, a digital garden assumes work in progress, a broad spectrum of topics and interests, and an ever evolving space online where ideas and things of beauty can blossom. Lovely!

There are a few patterns that show up with folks that have taken on the spirit of digital gardening. One that caught my eye was "Topography over Timelines."

Gardens are organized around contextual relationships and associative links; the concepts and themes within each note determine how it's connected to others.

This runs counter to the time-based structure of traditional blogs: posts presented in reverse chronological order based on publication date.

Gardens don't consider publication dates the most important detail of a piece of writing. Dates might be included on posts, but they aren't the structural basis of how you navigate around the garden. Posts are connected to other by posts through related themes, topics, and shared context.

One of the best ways to do this is through Bi-Directional Links – links that make both the destination page and the source page visible to the reader. This makes it easy to move between related content.

Because garden notes are densely linked, a garden explorer can enter at any location and follow any trail they link through the content, rather than being dumped into a "most recent” feed.

Love it! My favorite discoveries are with sites that link well. It's a blast hopping around, continuing the conversation from page to page. Wikis are the prime example of this. Tough, some bloggers like Austin Kleon also do this particularly well.

So! Why only be bound by linking in one chronological direction? I took to the idea and whipped up a script to employ this myself!

Developing Bi-Directional Linking

This site uses markdown for posts. So doing this job is largely about text parsing. Much of the logic, in fact, is similar to how I parse my posts to display an art grid.

I'll start by writing the function to actually get the url value from my links. The regex is looking for the value with parenthesis in the typical markdown shorthand for links: ![alt text](link)

// api.js

export const getInternalLinksFromMarkdown = (md) => {
  const regex =
    /(?:__|[*#])|\[(.*?)\]\(\/(.*?)\)/g;
  return Array.from(md.matchAll(regex)).map((res) => {
    if (res && res.length > 1) {
      return res[2];
    }
  });
};

The value of index 2 of the array will give me the capture group I've targeted because that's how it's done in Node!

From here, I'll then pass in my posts and systematically generate an object that grabs both the targeted url as well as the current post url.

// api.js

export function getAllPostRefs(
  fields = ['content', 'slug', 'title'],
  options = {}
) {
  const slugs = getPostSlugs();
  let posts = slugs
    .map((slug) => getPostBySlug(slug, fields))
    // Filter false values (.DS_STORE)
    .filter((post) => post)
    // sort posts by date in descending order
    .sort((post1, post2) => (post1.date > post2.date ? -1 : 1));

  const links = {}
  posts.forEach((post) => {
    const postLinks = getInternalLinksFromMarkdown(post.content);
    postLinks.forEach((src) => {
      if (src && !src.includes('/')) {
        if (!links[src]) {
          links[src] = [];
        }
        if (!links[src].find(entry => entry.slug === post.slug))
        links[src].push({
          slug: post.slug,
          title: post.title,
        })
      }
    });
  })

  return links;
}

A Set data structure would be ideal for keeping duplicates out of the list, but we'll be converting this to JSON, and I'd rather avoid the hassle of bringing in a library for the conversion.

Finally, I'll call this function and save the results to a JSON file for refference.

biDirectionalLink.js

import { getAllPostRefs } from "./api"
const FileSystem = require("fs");

export const getRefs = () => {
    const links = getAllPostRefs();
    FileSystem.writeFile('_cache/backlinks.json', JSON.stringify(links), (error) => {
    if (error) throw error;
  });
}

Here's an snippet of what it generates:

{
    "30": [
        {
            "slug": "2022",
            "title": "2022"
        },
        {
            "slug": "iwataonpeople",
            "title": "Iwata on Creative People"
        },
        {
            "slug": "transcience",
            "title": "Transience"
        },
        {
            "slug": "web2000",
            "title": "A Love Letter to 2000s Websites"
        }
    ],
    "2022": [
        {
            "slug": "testingandwriting",
            "title": "Testing Software for the Same Reason You Write Notes"
        }
    ],
    
    ...
}

Voilà! Now I have the data of pages that are referenced. I can now call this method anytime the site regenerates and use this as the source of truth for back-linking.

To consume this in Next.js, I'm going to read the file in getStaticProps (or in an RSC if I were using the App Router)

// [slug].js

export async function getStaticProps({ params }) {
  if (post) {
    const file = await fs.readFile(process.cwd() + '/_cache/backlinks.json', 'utf8');
    const backlinks = JSON.parse(file);
    let pagesLinkingBackTo = null;

    if (backlinks[params.slug]) {
      pagesLinkingBackTo = backlinks[params.slug];
    }

And, following some prop drilling, I can now programmatically display these on matching pages:

// backLinkSection.js

import React from 'react';
import NextLink from './NextLink';

const BacklinksSection = ({pagesLinkingBackTo}) => {
    if (!pagesLinkingBackTo) return <></>
    return (
        <aside>
            <h4>
                Pages referencing this post:
                <ul>

                {pagesLinkingBackTo.map(link => (
                    <li><NextLink href={link.slug}>{link.title}</NextLink> </li>
                ))}
                </ul>
            </h4>
        </aside>
    );
};

export default BacklinksSection;

Assuming I haven't link to this page yet, you can see this in action at the bottom of my Parsing Mardkown in Node post. Now with handy links to click and explore related topics.

I'm excited to keep tending the garden! I've already seen themes emerge through the regular tags I use. Here's to a great harvest someday!

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Short and sweet this week! A little phrase from a very young Beethoven.