https://github.com/faserf/ha-bahnvorhersage
bahnvorhersage.de Homeassistant fetching
https://github.com/faserf/ha-bahnvorhersage
bahn hacs-integration homeassistant
Last synced: over 1 year ago
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bahnvorhersage.de Homeassistant fetching
- Host: GitHub
- URL: https://github.com/faserf/ha-bahnvorhersage
- Owner: FaserF
- License: apache-2.0
- Created: 2025-01-25T22:46:07.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-02T10:50:30.000Z (over 1 year ago)
- Last Synced: 2025-02-02T11:26:58.625Z (over 1 year ago)
- Topics: bahn, hacs-integration, homeassistant
- Language: Python
- Homepage:
- Size: 140 KB
- Stars: 4
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: .github/CONTRIBUTING.md
- Funding: .github/FUNDING.yml
- License: LICENSE
- Codeowners: .github/CODEOWNERS
Awesome Lists containing this project
README
[](https://github.com/hacs/integration)
# Deprecation notice
The backend API owner does not allow API fetching in intervals, therefore this integration needs to be shut down and wont work anymore. More details are explained [here](https://github.com/FaserF/ha-bahnvorhersage/issues/1). Please use [ha-db_infoscreen](https://github.com/FaserF/ha-db_infoscreen) instead.
# Bahnvorhersage Homeassistant Sensor
The `bahnvorhersage` sensor will give you the prediction departure time of the next trains for the given start & destination combination, containing many more attribute informations.
This integration works great side-by-side with [ha-db_infoscreen](https://github.com/FaserF/ha-db_infoscreen).
This is a superior to [ha-deutschebahn](https://github.com/FaserF/ha-deutschebahn).
## Installation
### 1. Using HACS (recommended way)
This integration is NO official HACS Integration right now.
Open HACS then install the "bahnvorhersagen" integration or use the link below.
[](https://my.home-assistant.io/redirect/hacs_repository/?owner=FaserF&repository=ha-bahnvorhersage&category=integration)
If you use this method, your component will always update to the latest version.
### 2. Manual
- Download the latest zip release from [here](https://github.com/FaserF/ha-bahnvorhersage/releases/latest)
- Extract the zip file
- Copy the folder "bahnvorhersage" from within custom_components with all of its components to `/custom_components/`
where `` is your Home Assistant configuration directory.
>__NOTE__: Do not download the file by using the link above directly, the status in the "master" branch can be in development and therefore is maybe not working.
## Configuration
Go to Configuration -> Integrations and click on "add integration". Then search for "bahnvorhersage".
[](https://my.home-assistant.io/redirect/config_flow_start/?domain=bahnvorhersage)
### Configuration Variables
| Key | Type | Required | Default | Description |
|----------------------------|---------|----------|---------|-------------|
| `start_station` | string | Yes | - | The starting station* |
| `destination_station` | string | Yes | - | The destination station* |
| `next_departures` | int | No | 2 | Number of upcoming departures to show |
| `update_interval` | int | No | 3 | Update interval in seconds |
| `hide_low_delay` | boolean | No | False | Hide trains with low delays |
| `show_stopovers` | boolean | No | False | Shop stopover details (not recommended due to performance decreasement) |
| `drop_late_trains` | boolean | No | False | Exclude very late trains |
| `search_for_arrival` | boolean | No | False | Search for arrival times instead of departure times |
| `only_regional` | boolean | No | False | Only show regional trains |
| `bike` | boolean | No | False | Show bike-friendly trains |
| `offset` | string | No | 00:00 | Time offset for departure search |
| `ignored_traintypes` | list | No | [] | List of train types to ignore |
*: Please check your station on [https://bahnvorhersage.de](https://bahnvorhersage.de) on how to write it. It is important to choose the correct way of spaces and/or "-" symbols. If your station is not supported there, I can also not support it here, but you could then give [ha-db_infoscreen](https://github.com/FaserF/ha-db_infoscreen) a try instead.
## Automation Examples for Home Assistant
### 1. Predict Next Departure delay
This automation sends a push notification with the next predicted departure delay from **Start** to **Destination**.
```yaml
alias: "Next Train predicted Departure Delay Notification"
trigger:
- platform: time
at: "07:00:00"
condition: []
action:
- service: notify.mobile_app_your_smartphone
data:
title: "Train Forecast with prediction"
message: >
The next train from {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'start_station') }}
to {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'destination_station') }}
has an estimated predicted departure delay {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['departureDelayPrediction']['predictions'] }}.
Estimated arrival delay: {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['arrivalDelayPrediction']['predictions'] }}.
mode: single
```
### 2. Notify on Next Departure
This automation sends a push notification with the next scheduled departure from **Start** to **Destination**.
```yaml
alias: "Next Train Departure Notification"
trigger:
- platform: time
at: "07:00:00"
condition: []
action:
- service: notify.mobile_app_your_smartphone
data:
title: "Train Forecast"
message: >
The next train from {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'start_station') }}
to {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'destination_station') }}
departs at {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['departure'] }}.
Estimated arrival: {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['arrival'] }}.
mode: single
```
### 3. Delay Warning for the Next Train
This automation sends a warning notification if the predicted departure delay exceeds 2 minutes.
```yaml
alias: "Train Delay Warning"
trigger:
- platform: template
value_template: >
{% set delay_predictions = state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['departureDelayPrediction']['predictions'] %}
{{ (delay_predictions | sum / delay_predictions | length) > 2 }}
condition: []
action:
- service: notify.mobile_app_your_smartphone
data:
title: "Train Delay Alert"
message: >
The train from {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'start_station') }}
to {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'destination_station') }} is expected to be delayed.
Average predicted delay: {{ (state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['departureDelayPrediction']['predictions'] | sum / state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['departureDelayPrediction']['predictions'] | length) | round(1) }} minutes.
mode: single
```
### 4. Announce Train Departure on Smart Speaker
This automation announces the next departure time using a smart speaker like Google Home or Amazon Echo.
```yaml
alias: "Announce Next Train Departure"
trigger:
- platform: time_pattern
minutes: "/5" # Check every 5 minutes
condition: []
action:
- service: tts.google_translate_say
entity_id: media_player.living_room_speaker
data:
message: >
The next train from {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'start_station') }}
to {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'destination_station') }}
departs at {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['departure'] }}
from platform {{ state_attr('sensor.start_to_destination_bahnvorhersage', 'next_departures')[0]['departurePlatform'] }}.
mode: single
```
## API Data
### Accessing their data
The bahnvorhersage.de data is being accessed with the [API](https://bahnvorhersage.de/api/journeys) and a POST request
```json
{
"start": "Start Station",
"destination": "Destination",
"date": "25.01.2025 12:00",
"search_for_arrival": false,
"only_regional": false,
"bike": false
}
```
### JSON Format
The API returns data in the following json format usually:
```json
[{
"legs": [{
"origin": {
"id": "1234567",
"name": "Start",
"location": {
"id": "1234567",
"latitude": 12.345678,
"longitude": 12.345678
},
"products": null,
"type": "station"
},
"destination": {
"id": "1234567",
"name": "Destination",
"location": {
"id": "1234567",
"latitude": 12.345678,
"longitude": 12.345678
},
"products": null,
"type": "station"
},
"departure": "2025-01-25T12:02:00+01:00",
"departurePlatform": "5",
"arrival": "2025-01-25T13:04:00+01:00",
"arrivalPlatform": "3",
"cancelled": false,
"direction": "München-Pasing",
"stopovers": [{
"stop": {
"id": "1234567",
"name": "Zorneding",
"location": {
"id": "1234567",
"latitude": 12.345678,
"longitude": 12.345678
},
"products": null,
"type": "station"
},
"arrival": null,
"plannedArrival": null,
"arrivalPlatform": "5",
"departure": "2025-01-25T12:02:00+01:00",
"plannedDeparture": "2025-01-25T12:02:00+01:00",
"departurePlatform": "5",
"cancelled": false,
"type": "stopover"
},
[...]
{
"stop": {
"id": "1234567",
"name": "Starnberg",
"location": {
"id": "1234567",
"latitude": 12.345678,
"longitude": 12.345678
},
"products": null,
"type": "station"
},
"arrival": "2025-01-25T14:04:00+01:00",
"plannedArrival": "2025-01-25T14:04:00+01:00",
"arrivalPlatform": "3",
"departure": null,
"plannedDeparture": null,
"departurePlatform": "3",
"cancelled": false,
"type": "stopover"
}],
"plannedDeparture": "2025-01-25T13:02:00+01:00",
"plannedDeparturePlatform": "5",
"departureDelayPrediction": {
"predictions": [0.00047, 0.00084, 0.00777, 0.32811, 0.29321, 0.12286, 0.05807, 0.04459, 0.03696, 0.02058, 0.01624, 0.01396, 0.01007, 0.00752, 0.00457, 0.00473, 0.00366, 0.00221, 0.00247, 0.00234, 0.00293, 0.00199, 0.00233, 0.00223, 0.00122, 0.00194, 0.00125, 0.00071, 0.00074, 0.00069, 0.00047, 0.0005, 0.00127, 0.0005],
"offset": 3,
"type": "delayPrediction"
},
"plannedArrival": "2025-01-25T14:04:00+01:00",
"plannedArrivalPlatform": "3",
"arrivalDelayPrediction": {
"predictions": [0.00043, 0.00112, 0.01883, 0.20492, 0.12529, 0.10636, 0.08477, 0.06242, 0.05973, 0.02657, 0.02752, 0.02364, 0.01864, 0.01251, 0.00584, 0.01028, 0.01035, 0.00974, 0.00533, 0.00509, 0.00918, 0.0388, 0.02247, 0.0193, 0.04173, 0.02942, 0.00706, 0.00305, 0.00247, 0.00305, 0.00129, 0.00099, 0.00127, 0.00053],
"offset": 3,
"type": "delayPrediction"
},
"line": {
"id": "s-6662",
"name": "S 1",
"operator": {
"type": "operator",
"id": "db-regio-ag-s-bahn-munchen",
"name": "DB Regio AG S-Bahn München"
},
"isRegio": true,
"productName": "S",
"mode": "train",
"fahrtNr": "6662",
"adminCode": "800725",
"type": "line"
},
"tripId": "2|#VN#1#ST#1737574886#PI#",
"type": "leg"
}],
"price": null,
"refreshToken": "1234###",
"type": "journey"
}]
```
## Bug reporting
Open an issue over at [github issues](https://github.com/FaserF/ha-bahnvorhersage/issues). Please prefer sending over a log with debugging enabled.
To enable debugging enter the following in your configuration.yaml
```yaml
logger:
logs:
custom_components.bahnvorhersage: debug
```
You can then find the log in the HA settings -> System -> Logs -> Enter "bahnvorhersage" in the search bar -> "Load full logs"
## Thanks to
The data is coming from the [bahnvorhersage.de](https://bahnvorhersage.de/) website.