Staying Consistent in Unpredictable Weather

Brian’s fitness journal after a brain stroke

The weather in Nashville has been behaving like a rollercoaster lately. Yesterday the temperature jumped up by about 20°F, and today it dropped by nearly the same amount. So winter, after briefly pretending to leave, has returned with enthusiasm.

Since my brain stroke, my body does not regulate temperature very well. My practical solution has been simple: adjust the outfit instead of fighting the weather. Even so, the cold this morning made me check the forecast twice just to confirm we were not facing another surprise snow day. Fortunately, there was no snow—at least not today.

Unless we have lightning, ice storms, or heavy snow, I try to keep my running routine. Consistency matters to me, so I run whenever conditions allow it.

When winter temperatures drop too much, I usually wait until the warmest part of the day before heading out. Nashville winters can feel colder than they appear, especially for someone whose internal thermostat does not cooperate. If I can avoid the worst cold, I will.

Cold weather affects my runs more than I would like. My body spends so much effort trying to stay warm that it leaves less energy for actual running. On Saturdays, I usually run 10 km, and ideally, I prefer conditions that are neither too cold nor too hot.

Today, however, timing worked against me.

I delayed the run longer than usual while waiting for the temperature to improve, which started to disrupt the rest of our Saturday schedule. Eventually, I decided that waiting any longer would only make things worse.

So I went out and ran anyway.

Even in the afternoon, the air remained stubbornly cold. My pace was slower than usual, which felt a bit disappointing. Still, I finished the full 10K despite the strong temptation to cut it short.

In winter running, sometimes the real achievement is not speed—it is simply showing up and finishing.

Adding Quiz Mode to Your Streamlit History App

Day 93 of 100 Days Coding Challenge: Python

Ninety-three days into this Python marathon, it suddenly hit me: I’ve only got a week left. The thought made me a little sad—like reaching the last few pages of a great book and realizing the ending is near. But rather than mope, I decided to channel that energy into something fun.

Today’s feature: quizzes. That’s right, the Civilization Timeline Builder is now handing out pop quizzes like a history teacher who drank too much coffee. The quiz pulls from the same filters (year range, regions, tags) you’ve already selected and generates random questions. “Which came first?” “Match the civ to the years?” It’s like turning my carefully curated data into a trivia night—minus the nachos, unfortunately. When you finish, the program even returns your score. History with instant feedback—cool, right?

Today’s Motivation / Challenge

Why does this matter? Because learning sticks better when you test yourself. You can scroll through timelines all day, but nothing sharpens your memory like a question asking, “Did the Gupta Empire adopt iron later than Rome?” Quizzes make history interactive, playful, and just a little competitive—especially if you’re the type who hates losing, even to yourself.

Purpose of the Code (Object)

The code auto-generates quiz questions based on your current filters. It randomizes both the content and the order, then provides a scoring system when you submit. There’s even a “show answers” toggle, so you can learn from your mistakes without a stern lecture.

AI Prompt

Please add the following function:
Quiz mode

  • Auto-generate 10 questions (“Which came first?”, “Match civ→years”).
  • Accept: scoring & “show answers” toggle.

Functions & Features

  • Generate random quiz questions from filtered civilizations and events.
  • Support multiple-choice or “which came first” style questions.
  • Return a score when the quiz is submitted.
  • Provide reset and show-answer options for replay and review.

Requirements / Setup

You’ll need:

  • Python 3.11

Installs:

pip install streamlit

Minimal Code Sample

import random

questions = random.sample(filtered_events, 10)

for q in questions:

    st.write(f”Which came first: {q[0].name} or {q[1].name}?”)

Picks 10 random event pairs and asks the user to guess which happened earlier.

The Civilization Timeline Builder

Notes / Lessons Learned

As long as I followed the instructions, it was surprisingly straightforward. Since it shares the same sidebar filters, I had to insert the quiz logic right after the filter selections.

To keep things flexible, I used st.number_input to let users decide how many questions they want. With the random library already installed, the program pulls events at random and builds the quiz. I even added two buttons: one to submit answers and another to reset the quiz entirely, giving users the choice to try again.

What struck me is how reusable this structure is. Today it’s history trivia, but tomorrow it could just as easily be a vocabulary quiz, a math drill, or even a fun little self-test on Python syntax. Who knew that adding a quiz mode could make history—and coding—feel a lot like game night?

Optional Ideas for Expansion

  • Add a timer for extra pressure (and bragging rights).
  • Track high scores across sessions.

Let users choose the quiz type: matching, multiple-choice, or true/false.

Exporting Timelines as CSV and PNG in Streamlit

Day 92 of 100 Days Coding Challenge: Python

Today I taught my app how to pack its bags and leave. In other words, I added import and export features. Sure, I could already copy-paste data or grab a screenshot with Greenshot, but sometimes you want your history neat and official—like a CSV for number crunching, a JSON for data nerds, or even a PNG snapshot to show off.

As an accountant, I’m a little obsessed with documentation. If it isn’t written down (preferably in triplicate), it might as well not exist. So this feature speaks to my soul: a one-click way to preserve the work I’ve done without juggling external tools. The first step? Adding Plotly’s Kaleido, which lets charts gracefully turn into PNGs instead of stubbornly staring back at you.

Today’s Motivation / Challenge

Why does this matter? Because sometimes you want to share your findings with others—or just keep a record for yourself—without re-running all the filters. Import/export turns the app into a portable historian. Think of it like saving leftovers: you can pack up today’s insights, reheat them later, and maybe even share with a friend.

Purpose of the Code (Object)

The code adds the ability to import data into the app and export filtered timelines as CSV, JSON, or PNG. That means you can save what you’re looking at, reload it later, or use it in another tool. It makes the app more than just an interactive toy—it becomes a proper record-keeper.

AI Prompt

I would like to add the following function:
Day 17 — Import/Export

  • CSV/JSON importers
  • Export filtered timeline as CSV + PNG snapshot
  • Accept: round-trip a tiny dataset; PNG file downloads

Functions & Features

  • Import datasets in CSV or JSON format.
  • Export filtered results as CSV for spreadsheets.
  • Save a PNG snapshot of the current timeline view.
  • Round-trip: test importing and exporting to confirm nothing gets lost.

Requirements / Setup

You’ll need:

  • Python 3.11

Installs:

pip install plotly kaleido streamlit

Minimal Code Sample

# Export timeline to PNG

fig.write_image(“timeline.png”)

# Export filtered data to CSV

df.to_csv(“filtered_timeline.csv”, index=False)

One saves your visualization as an image, the other exports your filtered data as a spreadsheet.

The Civilization Timeline Builder

Notes / Lessons Learned

Adding the helper functions was straightforward, but the placement of the sidebar UI block was trickier than expected. I initially dropped it in the wrong spot in streamlit_app.py, which triggered a spectacular cascade of errors. Once I moved it to sit neatly after the existing filters (year_range, selected_regions, selected_tags), everything clicked into place.

The PNG export was almost an afterthought—I nearly skipped it, exhausted after five hours of coding. But I pushed through, added it, and suddenly there it was: a crisp timeline image sitting on my desktop. Oddly enough, that little success gave me more motivation than any lecture on perseverance. Sometimes the best reward is seeing history look good in a file you can actually keep.

Optional Ideas for Expansion

  • Add Excel export for people who live in spreadsheets.
  • Bundle multiple outputs (CSV + PNG) into a single downloadable zip file.
  • Create an auto-backup option so every filter session saves itself without asking.

Warm Winter Essentials: Switching to Insulated Pants After a Cold Season

Brian’s fitness journal after a brain stroke

Over the years, after my brain stroke, I came to realize it’s important to know the warm winter essentials. Today, I officially retired my old sweatpants and upgraded to a new pair my wife ordered for me. The decision was long overdue. She had noticed a hole in the knee—courtesy of our cat—and gently declared that the pants had reached the end of their honorable service life.

To be fair, I tend to use clothing for a very long time. If something still functions, I keep it. However, the hole had grown well beyond its original “claw-sized” stage, and the fabric itself had become noticeably thin. At that point, even I had to admit the insulation had quietly retired years ago.

My wife specifically searched for something very warm because I am almost always cold. She explained that some pants have better insulation, and my old pair once did too—before age gradually wore it away. Fabric, much like people, loses resilience over time.

Since today was laundry day, it felt like the perfect moment to make the swap. The difference was immediate. The new pants are significantly warmer, have no mysterious knee ventilation, and include a soft insulating inner layer. The warmth was almost surprising.

We also keep the house relatively cool in winter because my wife prefers a moderate indoor temperature. She usually sets it around 65°F (18°C), believing that overly hot houses in winter—and overly cold ones in summer—are not ideal for health. As a result, I normally rely on hoodies and extra layers to stay comfortable.

Since my brain stroke, my temperature regulation has not been the same. Without layered clothing, I often feel cold even on warmer days. At times, I can feel hot and cold simultaneously, which is as confusing as it sounds. It is as if my internal thermostat occasionally sends mixed signals.

One amusing detail: the inside of the new pants is so well insulated that the outside fabric can feel cool to the touch while the inside stays very warm. Apparently, my body heat now creates a cozy zone—because our kitten has started choosing my chest or belly as her preferred resting spot. Clearly, she has conducted her own thermal research and approved the results.

My wife even suggested buying an extra pair as a spare, but I declined. I still have another pair for laundry rotation, and buying too many would feel unnecessary. Warmth is important, but so is practicality.

That said, I must admit: I genuinely like these new pants. Sometimes, a small upgrade in daily comfort makes a noticeable difference—especially during a cold season where warmth quietly becomes a daily priority.

Building a Sources & Citations System in SQLModel

Day 91 of 100 Days Coding Challenge: Python

Today was a reminder that computers are ruthless sticklers for details. I decided to add sources linked to the detailed card—because just like in academic papers, you can’t just “borrow” information floating around the internet without tipping your hat to whoever wrote it first. Seems fair, right?

But of course, the minute I touched the database, I triggered the classic relationship drama. My code started yelling at me: “source not defined.” Over and over. It was like being haunted by an ex who just wouldn’t leave the room. I spent five solid hours untangling imports, relationships, and annotations, trying everything from brute force to delicate tweaks. Eventually, the stars aligned, and the errors gave up. Victory never felt so earned.

Today’s Motivation / Challenge

Why spend a day on sources? Because information without sources is gossip, and gossip doesn’t belong in a timeline app. Adding citations isn’t just academic—it’s about trust. If you’re building a history tool, you want to know where the facts came from. Think of it like putting a bibliography on your app so it won’t get expelled for plagiarism.

Purpose of the Code (Object)


This code connects events and civilizations in the database to their sources, so each detail card can show where the information came from. Instead of a bare timeline with floating facts, now you get credibility built in. It’s like footnotes, but without the foot pain.

AI Prompt (for reference)

Day 16 — Sources & citations

  • sources table; link events/civs to sources; show bibliography per page.

Accept: civ detail lists sources with links.

Functions & Features

  • Add and store sources in a dedicated table.
  • Link sources to both events and civilizations.
  • Display a neat bibliography with clickable references on detail pages.

Requirements / Setup

  • Python 3.11+
  • Install SQLModel and SQLAlchemy 2.0+

pip install sqlmodel sqlalchemy

Minimal Code Sample

from typing import TYPE_CHECKING

from sqlmodel import SQLModel, Field, Relationship

class Source(SQLModel, table=True):

    id: int = Field(primary_key=True)

    title: str

    # Source linked to events

    events: list[“Event”] = Relationship(back_populates=”sources”)

# Ensures circular imports don’t trip us up

if TYPE_CHECKING:

    from .models import Event

This shows how a Source model can safely connect to events without circular import chaos.

The Civilization Timeline Builder

Notes / Lessons Learned

Those “source not defined” errors? Almost always circular-import headaches. The fix: postpone annotation evaluation, only import for type checking, and pass actual class objects instead of string guesses. SQLAlchemy 2.0 makes you play by the rules, and if you don’t, it punishes you with cryptic error messages.

After five hours of trial and error, I realized programming is like fixing plumbing: leaks pop up where you least expect them, and you just have to stay calm, systematic, and maybe a little stubborn. My biggest takeaway? Debugging isn’t a sprint—it’s therapy with a keyboard.

Optional Ideas for Expansion

  • Add clickable links so users can jump straight to the source online.
  • Allow filtering events by source—for example, “show me all events documented by Herodotus.”
  • Add a “source credibility” rating, so you can separate legends from solid history.

Historical Narrative Generator with One Click

Day 90 of 100 Days Coding Challenge: Python

Today I set out to give my app a voice of its own. The mission: generate a short 200–300-word historical narrative generator for whatever filters I’ve chosen. Basically, I wanted my app to play historian, skimming the top events and spitting out a digestible report. To do this, I turned to the trusty textwrap library.

Now, textwrap doesn’t sound glamorous—it’s no flashing map or animated arrow—but it does something crucial: it formats and wraps text so it looks neat and tidy. Think of it as the digital equivalent of that English teacher who insisted your essays had to fit on one page, double-spaced, 12-point font. Without it, you end up with messy, runaway text blocks. With it, you get something polished enough to pass off as a summary, a report, or maybe even a history newsletter.

It felt oddly satisfying—like giving the app its own narrator.

Today’s Motivation / Challenge

Why does this matter? Because clicking through endless events is like reading footnotes without the main text. A historical narrative generator summarizes a historical event and gives you the big picture: what happened, where it mattered, and why you should care. It’s like the “Previously on…” segment at the start of a TV show—except the show is about Mesopotamia instead of crime dramas.

Purpose of the Code (Object)

The code pulls the most important events from the current filter and stitches them into a compact narrative. It uses textwrap to make the summary readable and presentable. The end result is a neat little block of text you can generate with a button click, then edit as you see fit.

AI Prompt

We would like to add:
Narrative summary (extractive)

  • Generate 200–300-word summary for current filter (extract top events).
  • Accept: button produces summary; editable text area.

Functions & Features

  • Extract top events from the current filter.
  • Auto-generate a narrative summary (200–300 words).
  • Display the summary in an editable text box for user tweaks.
  • Format the text neatly with textwrap.

Requirements / Setup

You’ll need:

  • Python 3.11

Installs:

pip install textwrap3 streamlit

Minimal Code Sample

import textwrap

summary = ” “.join([e.description for e in top_events])

wrapped = textwrap.fill(summary, width=80)

st.text_area(“Generated Summary”, value=wrapped, height=200)

Collects event descriptions, wraps the text neatly, and displays it for editing.

The Civilization Timeline Builder

Notes / Lessons Learned

After wiring up the function, I thought everything was ready—until I realized my civilization details had disappeared. Worse, the shiny new “Generate Summary” button was missing too. The culprit? Code order. My narrative block had slipped into the wrong conditional, pairing itself with the diffusion toggle instead of the list/detail switch.

So when diffusion was off, the else: block tried to show a nonexistent detail view, and the summary button went into hiding. Once I moved everything back under the right branch, the details returned, and my summary button reappeared like a magician pulling a rabbit from a hat.

Lesson learned: order matters. Functions can’t just float wherever they want—think of them like stubborn cats. If you put them in the wrong room, they’ll refuse to come out until you move them properly.

Optional Ideas for Expansion

  • Add a “copy to clipboard” button for easy sharing.
  • Export summaries as a text or PDF file.
  • Let users choose between a short, medium, or long summary length.

Tech Diffusion — Tracing How Innovations Spread Across Civilizations

Day 89 of 100 Days Coding Challenge: Python

Today I gave my app a new toy: Tech Diffusion (beta). This feature traces how a chosen technology or theme spread from one civilization to another. It builds a mini-timeline of “first appearances” and plots arrows on a map showing the likely diffusion paths. It’s basically gossip for inventions—who did it first, and who copied whom.

I tested it with ironworking, fully expecting to see a neat west-to-east progression from the Middle East to Asia. Instead, I was surprised. Rome and Han China both show ironworking popping up around the same time, while the Gupta Empire only catches on centuries later. The Silk Road could explain part of this, but it still made me pause. Either the tech sprinted faster than my app shows—or my data has some catching up to do. Either way, it’s a reminder: history doesn’t always follow the tidy arrows we imagine.

Today’s Motivation / Challenge

Why does this matter? Because inventions don’t just happen—they move. From ironworking to paper to gunpowder, tracking how ideas spread reveals the hidden highways of human history. It’s the connective tissue between civilizations, proof that even ancient cultures were networked (without Wi-Fi, no less).

Purpose of the Code (Object)

The code identifies the earliest events tagged with a given theme, orders them on a timeline, and draws map arrows from early adopters to later ones. With it, you can watch technology hopscotch across regions, showing not only who led the way but also who eventually caught on. It’s a way to visualize cultural diffusion, not just in theory but in clickable, colorful practice.

AI Prompt

Please add the following function:
Tech diffusion

  • For tag “ironworking” (example), show first appearances → later adoptions timeline & map arrows.

Functions & Features

  • Search events by theme (e.g., “ironworking,” “Christianity”).
  • Identify earliest appearances for each civilization.
  • Plot a timeline ordered by first adopters.
  • Draw arrows on a map to suggest diffusion paths.

Requirements / Setup

You’ll need:

  • Python 3.11

Installs:

pip install streamlit plotly

Minimal Code Sample

events = [e for e in all_events if “ironworking” in e.tags]

events.sort(key=lambda e: e.year)

for i in range(1, len(events)):

    fig.add_annotation(

        x=events[i].lon, y=events[i].lat,

        ax=events[i-1].lon, ay=events[i-1].lat,

        arrowhead=2, showarrow=True

    )

Orders events by year, then draws arrows between earlier and later adopters.

The Civilization Timeline Builder

Notes / Lessons Learned

The build went smoothly—until testing. When I searched for Christianity, everything worked: Rome’s Edict of Milan showed up, and Aksum’s adoption of Christianity appeared right where it belonged. But when I tested ironworking, nothing showed. After a few puzzled minutes, I discovered the culprit: my seed data. Rome and Han had tags with “ironworking,” but Gupta’s event was missing the tag altogether. No data, no arrows.

It reminded me of earlier struggles mapping civilizations—if the data isn’t there, no amount of clever code will conjure it. After correcting my CSV and reseeding, the function worked perfectly. Lesson learned: the best code still depends on the quality of the story you feed it.

Optional Ideas for Expansion

  • Add multiple themes at once (e.g., track ironworking and horse domestication).
  • Let users toggle arrow thickness by time delay (longer gaps = thinner arrows).
  • Animate the diffusion so technologies appear and spread in real time.

Managing Potassium, Kidney Health, and Anemia Step by Step

Brian’s fitness journal after a brain stroke

After my recent visit to the nephrologist, I learned a few important things about my current health. One of the biggest concerns was how to maintain my kidney health and anemia.

First, the good news: my latest blood panel showed that my potassium levels have returned to normal. That was a relief. The dietary changes I’ve been following seem to be working, so I plan to continue them carefully. With kidney conditions, consistency matters more than enthusiasm. One good result does not mean I can suddenly negotiate with potassium again.

However, the appointment also revealed that I have become anemic.

This part was not entirely surprising. I have a genetic blood condition called thalassemia, which often makes me appear anemic on lab results. My nephrologist already knows this, but the lab report suggests that this time the anemia relates more directly to my kidney condition rather than genetics alone. Because of that, I received a referral to a hematologist.

Hearing the word “anemia” brought back memories of the year I had my brain stroke. At that time, I lost a significant amount of blood, and my kidneys were in stage 5 condition. The combination made the anemia much worse, and I had to receive injections to stabilize my blood levels.

Compared to that period, my situation now is far more stable.

It is possible that my current blood count needs support again, likely through a hormone injection such as Epogen. I took this treatment shortly after my stroke, and it was manageable, even if not particularly enjoyable. Today, the hematologist’s office contacted me to schedule an appointment for next week, which means the next step is already in motion. I may not be excited about it, but it is necessary, and I prefer to address issues early rather than wait for them to worsen.

On days like this, I remind myself to move forward one step at a time.

Objectively, my condition has improved compared to the past. After the stroke, my kidneys were near stage 5. Now they are closer to stage 3, which is meaningful progress. Yes, I am slightly anemic, but many of my other health markers have improved over the past few months.

When I compare the present to where I once was, the difference is clear.
This is not a decline. This is management.

And for chronic health conditions, steady improvement—however gradual—is a victory worth acknowledging.

Sequence Hints in Streamlit: Find Neighbor Events Within ±50 Years

Day 88 of 100 Days Coding Challenge: Python

Today, I rolled out an experimental function for my civilization app—something I’ve never attempted before. The idea? Track what’s happening in neighboring civilizations within ±50 years of a major event. The goal isn’t to claim causation, but to look for ripples because history loves ripples.

Take Rome, for example. If you see a burst of military aggression from nearby empires around the same time Rome is wobbling, you can start to piece together the larger story. And it doesn’t stop at politics or warfare. Cultural and technological shifts—like paper-making or gunpowder—also spread from neighbor to neighbor, changing the trajectory of civilizations in ways subtle and spectacular.

Honestly, I was pretty excited to build this. It feels like uncovering the “behind-the-scenes” footage of history, where you see not just what happened but what was happening in the background.

Today’s Motivation / Challenge

Why does this matter? Because no civilization exists in isolation. Every rise or fall has echoes in neighboring regions. Whether it’s Rome watching the Huns thunder in, or India passing along the concept of zero, the world is full of crossovers. By tracking those overlaps, we get a richer picture of history’s interconnected web—basically, the original shared universe.

Purpose of the Code (Object)

The code adds a “sequence hints” feature that scans for major neighbor changes within ±50 years of a civilization’s events. The results are shown as a neat badge with tooltips, so you can quickly see counts and peek at details. It’s not claiming “X caused Y,” but it highlights when civilizations were moving in sync—or clashing in spectacular ways.

AI Prompt

Please add this function:
Day 13 — Sequence hints

  • For each civ, list major neighbor changes within ±50 years (label “sequence, not causation”).
  • Accept: UI badge shows counts; tooltip text is clear.

Functions & Features

  • Scan for significant neighbor events within ±50 years.
  • Display overlaps as badges with event counts.
  • Provide tooltips with details like event type, year, and time delta.
  • Sync with the same filters (region, tags, years).

Requirements / Setup

You’ll need:

  • Python 3.11

Installs:

pip install streamlit plotly

Minimal Code Sample

def sequence_hints(civ, all_civs):

    hints = []

    for neighbor in all_civs:

        if neighbor.id == civ.id: 

            continue

        for event in neighbor.events:

            if abs(event.year – civ.year) <= 50:

                hints.append((neighbor.name, event))

    return hints

Checks if a neighbor’s event happened within ±50 years and records it.

The Civilization Timeline Builder

Notes / Lessons Learned

The feature turned out to be fascinating in practice. I tested it with the Roman Republic, focusing on 0–400 CE, and the results popped:

  • Gupta Empire
    400: Decimal & Zero · tech · Δ5 yrs
    415: Iron Pillar of Delhi · tech · Δ20 yrs
    500: Decline Under Huns · war · Δ24 yrs
  • Kingdom of Aksum
    330: Adopts Christianity · religion · Δ17 yrs

Not exactly the sweeping revelations I imagined, but enough to prove the concept. The catch? I only uploaded 12 civilizations so far. To make this function shine, I’ll need a much larger dataset.

Lesson of the day: even pilot versions can teach you a lot, but history—like data science—works best with more data points.

Optional Ideas for Expansion

  • Add filters to focus on specific event types (e.g., only tech overlaps).
  • Visualize the overlaps on the map with arrows or connectors.
  • Show a timeline side-by-side view to compare ripple effects across civilizations.

 Save Filter Presets — Add Theme Lenses to Your History App

Day 87 of 100 Days Coding Challenge: Python

Because I have another commitment tomorrow, I decided to sneak today’s function into the schedule a little early. The feature of the day? Saving filters. Think of it as adding a “save game” button to history. If you’ve ever played a Nintendo game that didn’t let you save, you know the pain—hours of progress gone because your little brother unplugged the console. I didn’t want my carefully chosen filters to vanish the same way.

Of course, no feature comes without a little drama. I hit two big issues. Back when I started coding, any red error message would send me into full panic mode. Now, I’ve learned that most problems are just puzzles with bad timing. Today reminded me of that: slow down, breathe, and fix one thing at a time.

Today’s Motivation / Challenge

Why does this matter? Because sometimes you don’t want to rebuild the same filter every time you open the app. Imagine crafting the perfect view of “iron adoption in Eurasia, 800 BCE–200 CE,” then losing it forever because you clicked away. Saving presets means you can revisit your favorite “lenses” with one click, whether it’s maritime trade routes or technological revolutions.

Purpose of the Code (Object)

The code lets you save your current filter selections as JSON presets—called “theme lenses.” You can load, switch, and reuse them later. This way, your app remembers what you care about, and you can jump straight into exploring without re-selecting everything.

AI Prompt

Please add the following functions:
Theme lenses

  • Save filter presets (JSON): “maritime trade”, “iron adoption”, etc.

Accept: load/switch lenses in 1 click

Functions & Features

  • Save current filter selections as named JSON files.
  • Load a saved filter (“lens”) instantly with one click.
  • Keep taxonomy tags (like “tech” or “war”) consistent, even if not in the current tag list.

Requirements / Setup

You’ll need:

  • Python 3.11

Installs:

pip install streamlit

Minimal Code Sample

def save_lens(name, filters):

    with open(f”lenses/{name}.json”, “w”) as f:

        json.dump(filters, f)

def load_lens(name):

    with open(f”lenses/{name}.json”) as f:

        return json.load(f)

One function saves filters as JSON; the other loads them back into the app.

The Civilization Timeline Builder

Notes / Lessons Learned

The first bug was almost comical: I forgot to delete the existing sidebar widget, so suddenly I had two period selectors glaring at me. That one was an easy fix. The trickier problem was when lenses like “maritime trade” or “iron adoption” triggered Streamlit errors. The issue? I had assigned values that didn’t exist in the current all_tags list. Streamlit doesn’t like when you ask for something it doesn’t offer.

The solution was to create a script that merges the database-derived options with whatever free-form values the lens needed. That way, even if the lens specifies tags like “sea” or “tech,” it still works, whether or not those appear in all_tags. After some careful debugging, everything finally clicked into place.

The real lesson: don’t try to fix every error at once. Solve one, breathe, then tackle the next. The process is a lot less stressful that way.

Optional Ideas for Expansion

  • Add a dropdown of saved lenses in the sidebar for quick access.
  • Allow exporting and sharing lenses with friends (history study group, anyone?).
  • Include a “random lens” button for surprise explorations.