https://github.com/tomdyson/octodata
Tools for getting your Octopus Energy electricity data into a SQLite database
https://github.com/tomdyson/octodata
datasette energy energy-consumption
Last synced: 9 days ago
JSON representation
Tools for getting your Octopus Energy electricity data into a SQLite database
- Host: GitHub
- URL: https://github.com/tomdyson/octodata
- Owner: tomdyson
- License: mit
- Created: 2022-11-17T12:17:21.000Z (almost 3 years ago)
- Default Branch: main
- Last Pushed: 2022-11-29T10:05:48.000Z (almost 3 years ago)
- Last Synced: 2025-05-09T09:48:49.752Z (5 months ago)
- Topics: datasette, energy, energy-consumption
- Language: Python
- Homepage:
- Size: 8.79 KB
- Stars: 6
- Watchers: 2
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Octodata
Tools for getting your Octopus Energy electricity data into a SQLite database,
for exploration in [Datasette](https://datasette.io).
## Usage
1. Install the dependencies: `pip install -r requirements.txt`
2. Find your API key, serial number and MPAN from
https://octopus.energy/dashboard/developer/
3. Rename `.env-example` to `.env` and fill in the details
4. Fetch all your historic data with `python all.py`. This may take a few
minutes
5. Get daily updates with `python daily.py`
6. Use Datasette to explore your data: `datasette readings.db`
## Useful queries
### Total usage by month
```sql
select
strftime("%m-%Y", start_time) as 'month-year',
sum(usage) as monthly_usage
from readings
group by strftime("%m-%Y", start_time);
```
### Average usage per month
```sql
select
strftime("%m-%Y", start_time) as 'month-year',
avg(usage) as avg_usage
from readings
group by strftime("%m-%Y", start_time);
```
### Average use on Mondays
```sql
select
strftime("%m-%Y", start_time) as 'month-year',
avg(usage) as avg_usage
from readings
where strftime("%w", start_time) = "1"
group by strftime("%m-%Y", start_time);
```
### Average use per hour:
```sql
select
strftime("%H", start_time) as time,
avg(usage) as avg_usage
from readings
group by strftime("%H", start_time);
```
### Last seven days:
```sql
select
strftime("%Y-%m-%d", start_time) as Date,
case
cast (strftime('%w', start_time) as integer)
when 0 then 'Sunday'
when 1 then 'Monday'
when 2 then 'Tuesday'
when 3 then 'Wednesday'
when 4 then 'Thursday'
when 5 then 'Friday'
else 'Saturday'
end as Day,
cast(sum(usage) as integer) as Usage
from
readings
where
date(start_time) >
date('now', '-8 day')
group by
strftime("%Y-%m-%d", start_time);
```