tibber.py - The Python wrapper for the Tibber API

Note that this is NOT pyTibber which is the official python wrapper endorsed by Tibber themselves.

tibber.py is an unofficial python wrapper package for communication with the Tibber API. This package aims to cover all functionalities of the Tibber API in the most beginner-friendly modern Pythonic way. You can read all the capabilites of the API and explore it with Tibbers' API explorer. For documentation on how to use tibber.py head over to https://tibberpy.readthedocs.io/en/latest/.

Every field of the API types should be found in the corresponding tibber.type (e.g. the size: Int field of Home type, should be accessed in the tibber.py package as: Home.size and return an int). In addition to these "1 to 1" relations between the tibber.py package and the Tibber API, there might be extra properties or methods for simpler access of common properties (one example: it is possible to simply write home.address1 instead of home.address.address1, although the latter is also supported). The docstrings of the tibber.types correspond to the description of each type in the api explorer docs (located on the right side of the Tibber API explorer).

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Installation

Install via pip

python -m pip install tibber.py

Requirements

tibber.py depends on gql, gql[aiohttp], gql[websockets] and graphql-core. tibber.py supports Python versions 3.7 and up!

Examples

Getting basic account data

import tibber

account = tibber.Account(tibber.DEMO_TOKEN) # Log in with an access token. All information gets updated here and stored in cache.

# These properties are retrieved from cache and DO NOT reflect data at the given time
# (but rather the data as it was when it last was cached)
print(account.name)         # "Arya Stark"
print(account.user_id)      # "dcc2355e-6f55-45c2-beb9-274241fe450c"
print(account.account_type) # ["tibber", "customer"]
print(account.login)        # "arya@winterfell.com"

# To update the cache with new data straight from the tibber api, run this:
account.update()

# Now use the updated data as you would before:
print(account.name)

Getting basic home data

import tibber

account = tibber.Account(tibber.DEMO_TOKEN)
home = account.homes[0]

print(home.id)                     # "cc83e83e-8cbf-4595-9bf7-c3cf192f7d9c"
print(home.time_zone)              # "Europe/Stockholm"
print(home.app_nickname)           # "Vitahuset"
print(home.app_avatar)             # "FLOORHOUSE3"
print(home.size)                   # 195
print(home.type)                   # "HOUSE"
print(home.number_of_residents)    # 5
print(home.primary_heating_source) # "GROUND"
print(home.has_ventilation_system) # False
print(home.main_fuse_size)         # 25

Reading historical data

import tibber

account = tibber.Account(tibber.DEMO_TOKEN)
home = account.homes[0]

# Get the first 10 hours of consumption available
hour_data = home.fetch_consumption("HOURLY", first=10)

# Get the last 3 days of consumption
day_data = home.fetch_consumption("DAILY", last=3)

# Get last 2 months
month_data = home.fetch_consumption("MONTHLY", last=2)

for hour in hour_data:
    print(hour.from_time)
    print(hour.to_time)
    print(f"{hour.unit_price}{hour.currency}")
    print(hour.consumption)
    print(hour.cost)

Reading live measurements

Note how you can register multiple callbacks for the same event. These will be run in asynchronously (at the same time)!

import tibber

account = tibber.Account(tibber.DEMO_TOKEN)
home = account.homes[0]

@home.event("live_measurement")
async def show_current_power(data):
  print(data.power)

# Multiple callback functions for the same event!
@home.event("live_measurement")
async def show_accumulated_cost(data):
  print(f"{data.accumulated_cost} {data.currency}")
  
def when_to_stop(data):
  return data.power < 1500

# Start the live feed. This runs until data.power is less than 1500.
# If a user agent was not defined earlier, this will be required here
home.start_live_feed(user_agent = "UserAgent/0.0.1", exit_condition = when_to_stop)