https://github.com/tomwhite/dboard
A dashboard for Type 1 Diabetes.
https://github.com/tomwhite/dboard
diabetes nightscout t1d
Last synced: 7 months ago
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A dashboard for Type 1 Diabetes.
- Host: GitHub
- URL: https://github.com/tomwhite/dboard
- Owner: tomwhite
- License: apache-2.0
- Created: 2018-11-17T17:47:05.000Z (almost 7 years ago)
- Default Branch: master
- Last Pushed: 2018-12-31T17:02:21.000Z (almost 7 years ago)
- Last Synced: 2025-01-17T21:43:52.857Z (9 months ago)
- Topics: diabetes, nightscout, t1d
- Language: Python
- Size: 487 KB
- Stars: 4
- Watchers: 4
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.txt
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README
# dboard
A dashboard for Type 1 Diabetes.
Visualize your historical blood glucose levels in a calendar-like view, with weekly summaries
of a few key metrics.
Generated from data stored in [Nightscout](http://www.nightscout.info/).
## Usage
Install Python dependencies:
```bash
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt
```
Export data from Nightscout
```bash
mongoexport -h -d -u -p \
-c entries \
--fields type,sgv,mbg,date,dateString \
--type csv \
-o /tmp/entries.csv
```
Publish locally
```bash
./dboard.py --bg_lower 3.9 --bg_upper 8 /tmp/entries.csv out
python3 -m http.server 8000
```
Then open [http://localhost:8000/out](http://localhost:8000/out) in a browser.
Alternatively, publish to Google Cloud to keep a permanent record
```bash
export GOOGLE_APPLICATION_CREDENTIALS=... # see https://cloud.google.com/docs/authentication/production#obtaining_and_providing_service_account_credentials_manually
./dboard.py --bg_lower 3.9 --bg_upper 8 /tmp/entries.csv gs://
```
Then open `https://storage.googleapis.com//index.html` in a browser.
## How it works
There is a single web page, _index.html_, that has a small amount of JavaScript (no libraries)
to load data from a metadata file, _index.json_ and display the images for each day.
Here's a snippet of _index.json_:
```json
[
{
"week_start": "03/09/2018",
"plots": [
"2018/09/03/plot.png",
"2018/09/04/plot.png",
"2018/09/05/plot.png",
"2018/09/06/plot.png",
"2018/09/07/plot.png",
"2018/09/08/plot.png",
"2018/09/09/plot.png"
],
"range_low": 3.9,
"range_high": 8.0,
"tir": "81.0%",
"average_bg": "6.7",
"est_hba1c": "40.1"
},
{
"week_start": "10/09/2018",
"plots": [
"2018/09/10/plot.png",
"2018/09/11/plot.png",
"2018/09/12/plot.png",
"2018/09/13/plot.png",
"2018/09/14/plot.png",
"2018/09/15/plot.png",
"2018/09/16/plot.png"
],
"range_low": 3.9,
"range_high": 8.0,
"tir": "80.3%",
"average_bg": "6.2",
"est_hba1c": "37.0"
}
]
```
The `plots` element contains paths to the images for each day in the week.
The JSON and PNG files are generated by the `dboard` Python package.
The [traces](https://traces.readthedocs.io/en/latest/) library is used to interpolate
BG values to every minute; this ensures that accurate statistics can be produced from the data
(Time In Range, Average, Estimated HbA1c). For plotting, Matplotlib is used to render
each daily plot.
## Reports
There are a few other reports (daily carbs, insulin) that are produced separately.
```bash
mkdir -p reports
./dboard.py /tmp/treatments.csv reports
```
Then look in the `reports` directory.
## Testing
```bash
pytest
```
Coverage
```bash
pip install pytest-cov
pytest --cov-report html --cov=dboard
open htmlcov/index.html
```