USMS

An unofficial Python library to interface with your USMS account and smart meters.

Getting Started

Installation

python -m pip install usms

Quickstart

python -m usms --help

usage: __main__.py [-h] [-l LOG] -u USERNAME -p PASSWORD [-m METER] [--unit] [--consumption] [--credit]

options:
  -h, --help            show this help message and exit
  -l LOG, --log LOG
  -u USERNAME, --username USERNAME
  -p PASSWORD, --password PASSWORD
  -m METER, --meter METER
  --unit
  --consumption
  --credit

As an example, you can use the following command to get the current remaining unit:

python -m usms -u <ic_number> -p <password> -m <meter> --unit

You can also use environment variables for the login information:

export USMS_USERNAME="<ic_number>"
export USMS_PASSWORD="<password>"
python -m usms -m <meter> --unit

Or:

USMS_USERNAME="<ic_number>" USMS_PASSWORD="<password>" python -m usms -m <meter> --unit

Usage

import httpx

from usms import initialize_usms_account

username = "01001234" # your ic number
password = "hunter1"

# initialize the account
account = initialize_usms_account(
    username=username,
    password=password,
    client=httpx.Client(),  # or httpx.AsyncClient(), optional
)

# if you let the library create the client, use a context manager so it gets
# closed. A client you pass in stays yours and is never closed for you.
with initialize_usms_account(username=username, password=password) as account:
    ...  # async: `async with await initialize_usms_account(..., async_mode=True)`

# print out the account information
print(account.name)

# print out info on all meters under the account
for meter in account.meters:
    print(meter.no)
    print(meter.type)
    print(meter.address)
    print(meter.remaining_unit)
    print(meter.remaining_credit)
    print(meter.unit)

# get the number of the second meter
meter_no = account.meters[1].no

# to get info from a specific meter
meter = account.get_meter(meter_no)

# get today's consumptions
print(meter.get_last_n_days_hourly_consumptions(n=0))

# getting daily breakdown of last month's comsumptions
daily_consumptions = meter.get_previous_n_month_consumptions(n=1)
print(daily_consumptions)
# get last month's total cost based on total consumption
print(meter.calculate_total_cost(daily_consumptions))

# water meters have no hourly report, only a daily one
if not meter.supports_hourly_consumptions:
    print(meter.get_all_daily_consumptions())

# debt and customer details, from the meter's Top Up page
meter.fetch_payment_info()
print(meter.customer_type, meter.total_debt_owing, meter.has_debt)

# topping up cannot be automated - USMS redirects to the bank - so open this
print(meter.topup_url)

Login captcha

What changed

In October 2026 USMS added an image captcha (a DevExpress ASPxCaptcha) to the residential login. Every login since then has failed with USMSLoginError: Invalid login., even with the correct password. The captcha is a second step, not a field of the first form:

1. The username and password are posted with the captcha left empty. If they are correct, USMS answers with a redirect back to the login page, now carrying an sc query parameter. Wrong credentials still get the usual error message here.
2. That ResLogin?sc=... page serves the captcha that will actually be checked: five characters, lowercase letters and digits, warped and overlapping.
3. The credentials and the answer are posted to ResLogin?sc=.... A correct answer redirects through LoginSession with the Sig token, as before.

USMS also added a field to the meter card at the same time, which shifted the position of every field after it, so meter details are now read by their label rather than by position.

How the library gets past it

The library performs the step itself. It reads the captcha with a small text-recognition network bundled with the package, fetches a fresh captcha instead of submitting when a guess is not five characters long, and retries with a new one when an answer is rejected. Measured against live USMS captchas, about nine in ten submitted answers are accepted, and three attempts are allowed per login.

The network is ddddocr's general-purpose OCR model (common_old.onnx). ddddocr itself needs onnxruntime, which publishes no wheels for musl Linux and so cannot be installed on Home Assistant OS. The model is therefore exported once (see tools/export_captcha_model.py) into a node list and weight arrays, and usms.captcha evaluates it with numpy alone. Its 8210 output classes are cut down to the CTC blank plus a-z and 0-9, which shrinks the model to 3.7 MB and means it can never answer with a character USMS does not draw. The only new dependencies are numpy and Pillow.

If every attempt fails, the login raises USMSCaptchaError. It is deliberately not a USMSLoginError: the credentials were accepted, and retrying later with fresh captchas usually works, whereas prompting for the password again would not.

To use your own solver, pass any callable that takes the captcha image as PNG bytes and returns its text:

account = initialize_usms_account(username="...", password="...", captcha_solver=my_solver)

Migrating from 0.x

Consumptions are now plain dictionaries. Every method that returned a pandas.Series now returns a dict[datetime, float] keyed by the start of each period, and pandas is no longer a dependency at all. The keys are always timezone-aware and in Brunei time.

# 0.x
consumptions.empty            consumptions.sum()          consumptions.index.min()
# 1.0
not consumptions              sum(consumptions.values())  min(consumptions)

Gaps are simply absent rather than materialised as NaN rows, so summing and iterating skip them without special handling.

Hourly readings were shifted by an hour. 0.x mapped the first row of a day's report to 23:00 of the previous day. Besides misdating every reading, that stray timestamp made the cache believe it already held data for the previous day, so fetching that day returned a single row instead of 24. If you have stored consumptions or imported statistics from 0.x, re-fetch them to correct both.

Other changes. calculate_unit() takes an optional consumed_units so credit can be priced from the tier a meter has actually reached, rather than from zero. An exhausted re-authentication now raises USMSLoginError instead of quietly returning the login page as if it were data.

To-Do

• Add more test coverage
• Support for water meter
• Support for commercial/corporate accounts

Contributing

Prerequisites

1. Generate an SSH key and add the SSH key to your GitHub account.

2. Configure SSH to automatically load your SSH keys:

   cat << EOF >> ~/.ssh/config
   
   Host *
     AddKeysToAgent yes
     IgnoreUnknown UseKeychain
     UseKeychain yes
     ForwardAgent yes
   EOF
   

3. Install Docker Desktop.

4. Install VS Code and VS Code's Dev Containers extension. Alternatively, install PyCharm.

5. Optional: install a Nerd Font such as FiraCode Nerd Font and configure VS Code or PyCharm to use it.

Development Environments

The following development environments are supported:

1. ⭐️ GitHub Codespaces: click on Open in GitHub Codespaces to start developing in your browser.

2. ⭐️ VS Code Dev Container (with container volume): click on Open in Dev Containers to clone this repository in a container volume and create a Dev Container with VS Code.

3. ⭐️ uv: clone this repository and run the following from root of the repository:

   # Create and install a virtual environment
   uv sync --python 3.10 --all-extras
   
   # Activate the virtual environment
   source .venv/bin/activate
   
   # Install the pre-commit hooks
   pre-commit install --install-hooks
   

4. VS Code Dev Container: clone this repository, open it with VS Code, and run Ctrl/⌘ + ⇧ + P → Dev Containers: Reopen in Container.

5. PyCharm Dev Container: clone this repository, open it with PyCharm, create a Dev Container with Mount Sources, and configure an existing Python interpreter at /opt/venv/bin/python.

6. nix develop: clone this repository and run nix develop.

Developing

• This project follows the Conventional Commits standard to automate Semantic Versioning and Keep A Changelog with Commitizen.
• Run poe from within the development environment to print a list of Poe the Poet tasks available to run on this project.
• Run uv add {package} from within the development environment to install a run time dependency and add it to pyproject.toml and uv.lock. Add --dev to install a development dependency.
• Run uv sync --upgrade from within the development environment to upgrade all dependencies to the latest versions allowed by pyproject.toml. Add --only-dev to upgrade the development dependencies only.
• Run cz bump to bump the package's version, update the CHANGELOG.md, and create a git tag. Then push the changes and the git tag with git push origin main --tags.

License

Distributed under the MIT License. See LICENSE for more information.

Acknowledgments

• USMS
• ddddocr by sml2h3, MIT licensed. The captcha solver's model (src/usms/captcha/graph.json and weights.npz) is derived from ddddocr's common_old.onnx, reduced to the characters USMS uses. ddddocr's licence is reproduced in src/usms/captcha/LICENSE-ddddocr.
• ONNX and ONNX Runtime, whose operator specifications (including the com.microsoft contrib operators such as DynamicQuantizeLSTM) the numpy interpreter in usms.captcha.model follows.

Project Template

This project was built using the superlinear-ai/substrate template.