Laundry Pi

Laundry machine availability for Cinnamon College.

This is the code that lives on the Raspberry Pi:

The main script, main.py, checks whether the indicator light on each machine is on, and updates Firestore. Device specific configuration is in config.py - an example file (config.py.example) is uploaded.

In addition, there is a system (flagger.py, runner.py) to help restart the code on the RPi each time a new commit on master branch in Github is made (checks every minute). Do not rebase/modify commits in master, it will break this system (probably can be fixed by changing the git pull command run on the RPi to git pull --force?)

Reading the log files

main.py will write log files to the directory specified in config.py. Our current convention for the log directory is ~/laundro_logs/<pi ID>/.

A log file can be read with live updates using:

tail -f <name of log file>

all.log contains all log messages, info.log contains only INFO level and above log messages. Practically speaking, log messages for individual sensor readings will be in all.log and not info.log.

Setup

1. Install dependencies

pip install :

• firebase-admin
• Adafruit-Blinka
• Adafruit-ADS1x15

2. Setup device specific configuration in config.py

1. Generate another firestore cert, and save it somewhere on the RPi
2. Copy config.py.example as config.py and fill in it in appropriately. FIRESTORE_CERT refers to the path to the firestore cert file we generated above.

3. Add tasks to crontab

crontab -e then add:

• @reboot cd path/to/laundro && python3 runner.py main.py main (start the main script when the RPi boots up)
• * * * * * cd path/to/laundro && git pull && git log --pretty=oneline -1 | python3 flagger.py (check Github for updates every minute)

FYI: How things work

System to update from Github: flagger.py and runner.py

This is a small ecosystem to reload the code on the pi each time a new commit is made.

I can't quite figure out how to robustly do dynamic imports . ^ .

This means runner.py currently only works when it is in the same parent directory as the main routine.

flagger.py

This script receives a version identifier through stdin and compares it to .lastcommit. If there are differences (i.e. a change has been made), .lastcommit is updated and a .flag is set.

.lastcommit and .flag are always in the same directory as flagger.py

The intended usage is: git pull && git log --pretty=oneline -1 | python3 flagger.py

runner.py [module path] [function]

This script loads a module with the python import path module path and runs function in a process. Upon the process terminating, module path is reloaded and the new function is run in a new process.

The intended usage is: python3 runner.py main.py main

For testing: python3 runner.py runner test (.py isn't necessary in module path)

Requirements for main routine (currently main.py)

The main routine should regularly check for .flag and terminate once it is set (it should also remove the flag). When this happens runner.py will restart the main routine so it is running the updated code. flagger.py contains a simple flag class that can be used.

Firestore database

About Firestore: Firestore is an unstructured database. It can have collections, which can contain other collections and documents. A document is basically a database record. Each document has a unique string ID, which is what you see in the sidebar on the Firestore webpage. Documents in the same collection need not have the same fields (same "structure"), as you would in a relational database, but we try to do so in this project to make life easier.

The laundro database has 3 collections: laundry_status, pi_status and laundry_status_history.

pi_status

This keeps track of the information about each RPi (potentially other devices in the future), namely:

1. piNo (number): a unique number to identify this RPi.
2. level (number): the floor the RPi is on.
3. lastSeen (timestamp): when the RPi was last seen. This is updated whenever any of the machines change status, or after 5 minutes, whichever it sooner.

laundry_status

This keeps track of the current status for each washer/dryer. The document ID is unique to each washer/dryer in Cinnamon. Each document has the following fields:

1. *pinNo (number): unique number to identify each laundry machine in Cinnamon. I might change this to a more descriptive string in the future (eg. lvl17-1)
2. *piNo (number): the RPi this laundry machine's sensor is connected to.
3. *on (boolean): is the laundry machine on?
4. *timeChanged (timestamp): when the laundry machine changed from on->off or vice versa.
5. *timeChangedCertain (boolean): is the start time for the washing/drying cycle accurate?
6. *washer (boolean): is this a washing machine?
7. name (string): name that Cinnabot displays.
8. ezlink (boolean): does this machine use ezlink card payment?
9. cinnabot (boolean): should Cinnabot display this machine?

*: These fields are needed for the code here, the rest are not and used for the frontend (Cinnabot) instead. (not the best database design but it's easier to view and saves Firestore reads)

laundry_status_history

This is a backup of all the changes to the laundry machine status, whenever a machine changes from on to off / vice versa.