---
title: "Hummingbird feeder tracker"
url: ""
featureImage: "/projects/hummingbirds.jpg"
short: "hummingbirds"
category: "science"
ai: "Built by Claude"
order: "06"
year: "2026"
tags: ["python", "tkinter", "matplotlib"]
---
I wanted to know how many hummingbirds were visiting my feeders. Counting
them is hopeless, so instead I log what I can measure (each feeder's weight
or nectar level, the time, what the birds were doing) and a small desktop
app works out the rest:
- **Consumption** from the change in weight over the nectar's density,
cross-checked against the drop in level wherever there are both.
- **Bird counts** from 3 to 7 ml of nectar per bird per day, carried
through as a range instead of averaged into one confident-looking
number, because that rule of thumb is the biggest uncertainty in it.
- **Feeding time** measured to civil twilight, not by the clock, since
hummingbirds sleep through the night.
- **Spoilage** accumulated hour by hour from the local temperature, pulled
from Open-Meteo.
- **Seasonality** for the region from GBIF's bird records, divided by all
bird records for the same week, so that it measures birds rather than
how many people were out looking.
It was the first thing I built with Claude Code's ultracode, its
multi-agent mode.
Above: the Charts tab, comparing my feeders' season (orange) with ten years
of the region's ruby-throated hummingbird records (blue).
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<a class="visit" href="${frontmatter.url}">${frontmatter.url}</a>
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skyblue <a href="https://github.com/mas-4/skyblue">${sky.version}</a> (compiled by cprime <a href="https://github.com/mas-4/cprime">${sky.compiler}</a>)
<span class="prompt">$</span> skyblue -i src -o build
skyblue: ${sky.pages} pages and ${sky.files} files -> build
<span class="note"># ${sky.date}, ${sky.time}, ${sky.ms} ms. Two small scripts: the candle and the light switch.</span></pre>
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<pre class="listing"><code>${source.code}</code></pre>
scienceBuilt by Claude2026
Hummingbird feeder tracker
I wanted to know how many hummingbirds were visiting my feeders. Counting
them is hopeless, so instead I log what I can measure (each feeder's weight
or nectar level, the time, what the birds were doing) and a small desktop
app works out the rest:
- Consumption from the change in weight over the nectar's density,
cross-checked against the drop in level wherever there are both.
- Bird counts from 3 to 7 ml of nectar per bird per day, carried
through as a range instead of averaged into one confident-looking
number, because that rule of thumb is the biggest uncertainty in it.
- Feeding time measured to civil twilight, not by the clock, since
hummingbirds sleep through the night.
- Spoilage accumulated hour by hour from the local temperature, pulled
from Open-Meteo.
- Seasonality for the region from GBIF's bird records, divided by all
bird records for the same week, so that it measures birds rather than
how many people were out looking.
It was the first thing I built with Claude Code's ultracode, its
multi-agent mode.
Above: the Charts tab, comparing my feeders' season (orange) with ten years
of the region's ruby-throated hummingbird records (blue).