### Start Backend Server with Local Python

Source: https://github.com/earthobservations/wetterdienst/blob/main/frontend/tests/e2e/README.md

Commands to install the Wetterdienst locally and start the backend API server. This is an alternative to using Docker.

```bash
# From the project root
pip install -e .
wetterdienst restapi --listen 0.0.0.0:3000
```

--------------------------------

### Clone Repository and Install Prerequisites

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/contribution/development.md

Clone the Wetterdienst repository and install necessary prerequisites like git, python, and uv. Installation commands vary for macOS, Linux, and Windows.

```bash
git clone https://github.com/earthobservations/wetterdienst
cd wetterdienst

# Prerequisites
## Mac
brew install git python uv
## Linux
sudo apt install git python3 python3-venv uv
## Windows
# install via chocolatey or manually

# Regarding `uv` the following page lists all releases:
# - https://github.com/astral-sh/uv/releases
```

--------------------------------

### Install wetterdienst via PyPI

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Install the standard version of the wetterdienst library using pip.

```bash
pip install wetterdienst
```

--------------------------------

### Start Backend Server with Docker Compose

Source: https://github.com/earthobservations/wetterdienst/blob/main/frontend/tests/e2e/README.md

Command to start the Wetterdienst backend server using Docker Compose. This is the recommended method.

```bash
# From the project root
docker compose --profile backend up -d
```

--------------------------------

### Check wetterdienst installation

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Verify the installation of the wetterdienst library by running the command-line interface help command.

```bash
wetterdienst --help
```

--------------------------------

### Install wetterdienst from GitHub

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Install the most recent version of the wetterdienst library directly from its GitHub repository.

```bash
pip install git+https://github.com/earthobservations/wetterdienst
```

--------------------------------

### Install system dependencies for Raspberry Pi

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Install necessary system packages like gfortran and lxml on Raspberry Pi/Linux ARM before installing wetterdienst.

```bash
# not all installations may be required to get lxml running
sudo apt-get install gfortran
sudo apt-get install libopenblas-base
sudo apt-get install libopenblas-dev
sudo apt-get install libatlas-base-dev
sudo apt-get install python3-lxml
```

--------------------------------

### Install Frontend Dependencies

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Installs all necessary dependencies for the Nuxt 3 / Vue 3 frontend using pnpm. Run this after cloning the repository or updating dependencies.

```bash
cd frontend
pnpm install
```

--------------------------------

### Install wetterdienst with SQL support

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Install wetterdienst with the 'sql' extra, which includes support for querying data using DuckDB.

```bash
pip install wetterdienst[sql]
```

--------------------------------

### Acquire and Process DWD RADOLAN CDC Data with wradlib

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-examples.md

Example of acquiring RADOLAN_CDC data with daily resolution from DWD using wetterdienst and processing it with wradlib. Data is rounded to HH:50min for RADOLAN_CDC. Requires wetterdienst and wradlib to be installed.

```python
from wetterdienst.provider.dwd.radar import DwdRadarValues, DwdRadarParameter, DwdRadarResolution
import wradlib as wrl

radar = DwdRadarValues(
    parameter=DwdRadarParameter.RADOLAN_CDC,
    resolution=DwdRadarResolution.DAILY,
    start_date="2020-09-04T12:00:00",
    end_date="2020-09-04T12:00:00"
)

for item in radar.query():
    # Decode data using wradlib.
    data, attributes = wrl.io.read_radolan_composite(item.data)

    # Do something with the data (numpy.ndarray) here.
    break
    
attributes
```

--------------------------------

### Synchronize Dependencies with uv

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/contribution/development.md

Install all required dependencies, including extras and all groups, using the `uv sync` command.

```bash
uv sync --all-extras --all-groups
```

--------------------------------

### Install Playwright Browsers

Source: https://github.com/earthobservations/wetterdienst/blob/main/frontend/tests/e2e/README.md

Commands to install Playwright browsers. You can install the default browser, all browsers, or specific ones.

```bash
# Install Firefox (current default)
npx playwright install firefox

# Or install all browsers
npx playwright install

# Or install specific browsers
npx playwright install chromium webkit
```

--------------------------------

### Start Wetterdienst REST API

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/restapi.md

Invoke the Wetterdienst REST API from the command line.

```bash
wetterdienst restapi
```

--------------------------------

### Start REST API Server

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Launches the Wetterdienst REST API server, listening on all interfaces (0.0.0.0) on port 3000. This makes the API accessible locally.

```bash
wetterdienst restapi --listen 0.0.0.0:3000
```

--------------------------------

### Run Full Stack Docker Compose

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Starts both the backend and frontend services using Docker Compose. This provides a complete local development environment.

```bash
docker compose --profile app up
```

--------------------------------

### Use wetterdienst command line in Docker

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Demonstrates how to create an alias for the wetterdienst Docker command for convenient shell usage and shows example commands.

```bash
# Make an alias to use it conveniently from your shell.
alias wetterdienst='docker run -ti ghcr.io/earthobservations/wetterdienst wetterdienst'

wetterdienst --help
wetterdienst --version
wetterdienst info
```

--------------------------------

### Get Station History Snapshots (Python)

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/station_history.md

Retrieve historical station metadata snapshots for a given station ID and date range using the Python API. This example shows how to access different aspects of the station's history, such as name changes, device updates, geographical information, parameter changes, and missing data periods.

```python
from src.wetterdienst import Settings
from src.wetterdienst.provider.dwd.observation import DwdObservationRequest

settings = Settings()

# Get history snapshots for station 1048 between 2010-01-01 and 2020-01-01
request = DwdObservationRequest(
    parameters=[("daily", "kl")],
    settings=settings
).filter_by_station_id(1048)
history = next(request.history.query())
# access history for climate summary daily station 1048 (Dresden Klotzsche)
# naming
for station_name_change in history.history.name.station:
    print(station_name_change)
for operator_name_change in history.history.name.operator:
    print(operator_name_change)
# device changes
for device_change in history.history.device:
    print(device_change)
# geography changes
print(history.history.geography)
# parameter (measurement) changes
print(history.history.parameter)
# missing data periods
print(history.history.missing_data)
```

--------------------------------

### Run Full Test Suite

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/contribution/development.md

Execute the entire test suite using `uv run poe test`. Ensure Firefox and geckodriver are installed.

```bash
uv run poe test
```

--------------------------------

### Sync Dependencies (Python Backend)

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Synchronizes project dependencies, ensuring all required packages are installed and up-to-date.

```bash
uv run poe sync
```

--------------------------------

### Run Frontend Only with Docker Compose

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Starts only the frontend service using Docker Compose, accessible on port 4000. Useful for focusing on frontend development.

```bash
docker compose --profile frontend up
```

--------------------------------

### Start Frontend Dev Server

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Launches the Nuxt 3 / Vue 3 development server, typically on port 4000. Enables live reloading and hot module replacement during development.

```bash
pnpm dev
```

--------------------------------

### Python API Usage

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/station_history.md

Example of how to retrieve station history using the Python API.

```APIDOC
## Python API Usage

Example usage via the Python API:

```python
from src.wetterdienst import Settings
from src.wetterdienst.provider.dwd.observation import DwdObservationRequest

settings = Settings()

# Get history snapshots for station 1048 between 2010-01-01 and 2020-01-01
request = DwdObservationRequest(
    parameters=[("daily", "kl")],
    settings=settings
).filter_by_station_id(1048)
history = next(request.history.query())
# access history for climate summary daily station 1048 (Dresden Klotzsche)
# naming
for station_name_change in history.history.name.station:
    print(station_name_change)
for operator_name_change in history.history.name.operator:
    print(operator_name_change)
# device changes
for device_change in history.history.device:
    print(device_change)
# geography changes
print(history.history.geography)
# parameter (measurement) changes
print(history.history.parameter)
# missing data periods
print(history.history.missing_data)
```
```

--------------------------------

### Run Backend Only with Docker Compose

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Starts only the backend service using Docker Compose, accessible on port 3000. Useful for focusing on backend development.

```bash
docker compose --profile backend up
```

--------------------------------

### Query API Coverage

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/restapi.md

Get information about the API's coverage using httpie.

```bash
http localhost:7890/api/coverage
```

--------------------------------

### Wetterdienst CLI: Get All Stations

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Use this command to retrieve a list of all available stations for daily climate summary data in JSON format. Specify the provider and network for accurate results.

```bash
wetterdienst stations --provider=dwd --network=observation --parameters=daily/kl --all
```

--------------------------------

### List All Wetterdienst Parameters

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/data/parameters.md

Get a list of all available parameter names from the core Parameter enumeration. This can be used to understand the scope of data available across different weather services.

```python
from wetterdienst.metadata.parameter import Parameter

parameters = [parameter.value.lower() for parameter in Parameter]
print(f"Number of parameters: {len(parameters)}")
print("Parameters:")
print("\n".join(parameters))
```

--------------------------------

### Get historical climate summary

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Example of fetching historical climate summary data for specific German stations between 1990 and 2020 using DwdObservationRequest. Settings are configured for tidy data, humanized parameters, and unit conversion.

```python
from wetterdienst import Settings
from wetterdienst.provider.dwd.observation import DwdObservationRequest

settings = Settings(
    ts_shape="long",  # tidy data
    ts_humanize=True,  # humanized parameters
    ts_convert_units=True  # convert values to SI units
)

request = DwdObservationRequest(
    parameters=[
        ("daily", "climate_summary", "precipitation_height"),
    ],
    start_date="2002-08-11",  # if not given timezone defaulted to UTC
    end_date="2002-08-13",  # if not given timezone defaulted to UTC
    settings=settings
).filter_by_station_id(station_id=(5779,))

stations = request.df
stations.head()
# ┌────────────┬─────────────────┬────────────┬─────────────────────────┬───┬───────────┬────────┬──────────────────────┬─────────┐
# │ resolution ┆ dataset         ┆ station_id ┆ start_date              ┆ … ┆ longitude ┆ height ┆ name                 ┆ state   │
# │ ---        ┆ ---             ┆ ---        ┆ ---                     ┆   ┆ ---       ┆ ---    ┆ ---                  ┆ ---     │
# │ str        ┆ str             ┆ str        ┆ datetime[μs, UTC]       ┆   ┆ f64       ┆ f64    ┆ str                  ┆ str     │

```

--------------------------------

### Get All Stations

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Retrieve information about all available stations for a given dataset/parameter and period.

```APIDOC
## Get All Stations

Retrieve information about all available stations for a given dataset/parameter and period.

### Code Example

```python
import datetime as dt
from wetterdienst.provider.dwd.observation import DwdObservationRequest

request = DwdObservationRequest(
    parameters=("daily", "precipitation_more"),
    start_date=dt.datetime(2020, 1, 1),
    end_date=dt.datetime(2020, 1, 20)
)
stations = request.all()
df = stations.df
print(df)
```

### Response

The function returns a Polars DataFrame with information about the available stations.
```

--------------------------------

### Import and Show Default Settings

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/settings.md

Import the Settings class and display the default configuration. This is useful for understanding the initial state of the settings.

```python
from wetterdienst import Settings

settings = Settings()
settings
```

--------------------------------

### Build Wheel Package

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/contribution/development.md

Create a recent wheel package from the current working tree using the `uv build` command.

```bash
uv build
```

--------------------------------

### Get All Available Units

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/units.md

Instantiate UnitConverter to view all available units for each unit type.

```python
from wetterdienst.model.unit import UnitConverter

unit_converter = UnitConverter()
unit_converter.units
```

--------------------------------

### Get Default Units

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/units.md

Instantiate UnitConverter to view the default units for each unit type.

```python
from wetterdienst.model.unit import UnitConverter

unit_converter = UnitConverter()
unit_converter.targets
```

--------------------------------

### Get historical period enum

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Demonstrates how to access the Period enumeration for historical data.

```python
from wetterdienst.metadata.period import Period

Period.HISTORICAL
```

--------------------------------

### Discover available APIs

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Use Wetterdienst.discover() to find out which APIs are available.

```python
from wetterdienst import Wetterdienst

coverage = Wetterdienst.discover()
coverage
```

--------------------------------

### Build Frontend for Production

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Creates a production-ready build of the Nuxt 3 / Vue 3 frontend. This optimizes assets and code for deployment.

```bash
pnpm build
```

--------------------------------

### Get DWD MOSMIX-LARGE Data

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-examples.md

Retrieve MOSMIX-LARGE data from DWD. Requires importing DwdMosmixRequest.

```python
from wetterdienst.provider.dwd.mosmix import DwdMosmixRequest

stations = DwdMosmixRequest(
    parameters=("hourly", "large"),
)

stations = request.all()
df = stations.df
df
```

--------------------------------

### Initialize Wetterdienst API

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Instantiate the Wetterdienst API by specifying the provider and network of data.

```python
from wetterdienst import Wetterdienst

Wetterdienst(provider="dwd", network="observation")
```

--------------------------------

### Display Wetterdienst CLI Help

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/cli.md

Prints the help message for the wetterdienst CLI. Use this to understand available commands and options.

```python
from wetterdienst.ui.cli import wetterdienst_help

print(wetterdienst_help)
```

--------------------------------

### Get DWD MOSMIX-SMALL Stations

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-examples.md

Retrieve stations for MOSMIX-SMALL data from DWD. Requires importing DwdMosmixRequest.

```python
from wetterdienst.provider.dwd.mosmix import DwdMosmixRequest

request = DwdMosmixRequest(
    parameters=("hourly", "small"),
)

stations = request.all()
df = stations.df
df
```

--------------------------------

### Get Cache Path

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/known_issues.md

Run this code to find the path to your caching folder. This can be useful when troubleshooting cache-related issues.

```python
import wetterdienst
wetterdienst.info()
```

--------------------------------

### Discover DWD Observation Metadata

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-examples.md

Get available parameters for daily historical data from DWD. Requires importing DwdObservationRequest.

```python
from wetterdienst.provider.dwd.observation import DwdObservationRequest

metadata = DwdObservationRequest.discover(
    resolutions="daily",
)

metadata
```

--------------------------------

### Initialize Wetterdienst API

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Initialize the Wetterdienst API by specifying the provider and network of data.

```APIDOC
## Initialize Wetterdienst API

Initialize the Wetterdienst API by specifying the provider and network of data.

### Code Example

```python
from wetterdienst import Wetterdienst

Wetterdienst(provider="dwd", network="observation")
```
```

--------------------------------

### Get DWD Field Metadata (Precipitation, Hourly, Historical)

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/data/provider/dwd/observation/index.md

Retrieves metadata for historical hourly precipitation observations in English.

```bash
# Historical hourly station observations of precipitation for Germany.
# English language.
wetterdienst dwd about fields --parameter=precipitation --resolution=hourly --period=historical
```

--------------------------------

### Fetch Weather Data with Skip Empty Settings

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Configure settings to skip empty stations based on a minimum skip criterion and threshold. This is useful when filtering by rank to avoid stations with insufficient data.

```python
from wetterdienst import Settings
from wetterdienst.provider.dwd.observation import DwdObservationRequest

settings = Settings(ts_skip_empty=True, ts_skip_criteria="min", ts_skip_threshold=0.2)
karlsruhe = (49.19780976647141, 8.135207205143768)
request = DwdObservationRequest(
  parameters=[("daily", "kl")],
  start_date="2021-01-01",
  end_date="2021-12-31",
  settings=settings,
)
stations = request.filter_by_rank(latlon=karlsruhe, rank=2)
values = stations.values.all()
print(values.df.head())
# df_stations has only stations that appear in the values
values.df_stations
```

--------------------------------

### Get DWD Daily Precipitation Stations

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-examples.md

Retrieve all stations for daily historical precipitation data from DWD. Requires importing DwdObservationRequest.

```python
from wetterdienst.provider.dwd.observation import DwdObservationRequest

request = DwdObservationRequest(
    parameters=("daily", "precipitation_more"),
    periods="historical",
)

stations = request.all()
df = stations.df
df
```

--------------------------------

### Build OCI Images for Docker

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/contribution/development.md

Build OCI images suitable for Docker, Podman, and Kubernetes. Set necessary environment variables and use `docker build` with the specified tag and Dockerfile.

```bash
export DOCKER_BUILDKIT=1
export COMPOSE_DOCKER_CLI_BUILD=1
export BUILDKIT_PROGRESS=plain

docker build \
  --tag=local/wetterdienst \
  --file=.github/release/Dockerfile \
  .
```

--------------------------------

### Get Cache Directory Location

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Retrieve the current cache directory location used by wetterdienst settings. This is useful for managing cache files.

```python
from wetterdienst import Settings

settings = Settings()
settings.cache_dir
```

--------------------------------

### Get all stations for a given parameter and period

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Retrieve all available stations for a specific dataset/parameter and time period. The result is returned as a Polars DataFrame.

```python
import datetime as dt
from wetterdienst.provider.dwd.observation import DwdObservationRequest

request = DwdObservationRequest(
    parameters=("daily", "precipitation_more"),
    start_date=dt.datetime(2020, 1, 1),
    end_date=dt.datetime(2020, 1, 20)
)
stations = request.all()
df = stations.df
df
```

--------------------------------

### Run CLI

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/docker.md

Invoke the wetterdienst command line interface within a Docker container to check its version.

```bash
docker run -it --rm ghcr.io/earthobservations/wetterdienst wetterdienst --version
```

--------------------------------

### Run Specific Tests by Tags

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/contribution/development.md

Execute tests filtered by tags using the `-m` flag, for example, to exclude remote or slow tests.

```bash
# Run tests by tags.
uv run poe test -m "not (remote or slow)"
```

--------------------------------

### Configure swap file on Raspberry Pi

Source: https://github.com/earthobservations/wetterdienst/blob/main/README.md

Instructions to increase the swap file size to 2048 MB on Raspberry Pi, which may be required for running wetterdienst.

```bash
sudo nano /etc/dphys-swapfile
```

--------------------------------

### Run Single Test File (Python Backend)

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Executes tests from a specific file. Useful for focusing on a particular module or feature.

```bash
uv run pytest tests/provider/dwd/observation/test_api.py -vvv
```

--------------------------------

### Define parameters using a list of metadata objects

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Create a DwdObservationRequest by providing a list of metadata objects, allowing for multiple dataset selections.

```python
from wetterdienst.provider.dwd.observation import DwdObservationRequest, DwdObservationMetadata

DwdObservationRequest(
    parameters=[DwdObservationMetadata.daily.kl, DwdObservationMetadata.daily.more_precip]
)
```

--------------------------------

### Acquire ICON Data

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/restapi.md

Acquire ICON weather data for a specific station and date.

```bash
http localhost:7890/api/values provider==dwd network==dmo parameters==hourly/icon/temperature_air_mean_2m station==01001 date==2024-05-27
```

--------------------------------

### Query First Daily Precipitation Values from DWD

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-examples.md

Get the first set of daily historical precipitation values from DWD. Requires importing DwdObservationRequest.

```python
from wetterdienst.provider.dwd.observation import DwdObservationRequest

request = DwdObservationRequest(
    parameters=("daily", "precipitation_more"),
    periods="historical",
)

first_values = next(request.all().values.query())
df = first_values.df
df
```

--------------------------------

### CI/CD Workflow for E2E Tests

Source: https://github.com/earthobservations/wetterdienst/blob/main/frontend/tests/e2e/README.md

Commands for integrating E2E tests into a CI/CD pipeline. Ensures backend is running before tests and cleans up afterwards.

```bash
# Start backend
docker compose --profile backend up -d

# Run E2E tests
npm run test:e2e

# Cleanup
docker compose --profile backend down
```

--------------------------------

### Run All E2E Tests (Headless)

Source: https://github.com/earthobservations/wetterdienst/blob/main/frontend/tests/e2e/README.md

Execute all end-to-end tests in headless mode. This is typically used for automated runs.

```bash
npm run test:e2e
```

--------------------------------

### Get DWD Field Metadata (Air Temperature, 10 Minutes, Historical)

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/data/provider/dwd/observation/index.md

Retrieves metadata for historical 10-minute air temperature observations in German.

```bash
# Historical 10-minute station observations of pressure, air temperature (at 5cm and 2m height), humidity and dew point for Germany.
# German language.
wetterdienst dwd about fields --parameter=air_temperature --resolution=10_minutes --period=historical --language=de
```

--------------------------------

### Query Weather Data using SQL

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Filters weather data using SQL queries on a virtual 'data' table. Requires DwdObservationRequest, settings, and filtering by station ID.

```python
from wetterdienst import Settings
from wetterdienst.provider.dwd.observation import DwdObservationRequest

settings = Settings(ts_shape="long", ts_humanize=True, ts_convert_units=True)  # defaults
request = DwdObservationRequest(
  parameters=("hourly", "temperature_air", "temperature_air_mean_2m"),
  start_date="2019-01-01",
  end_date="2020-01-01",
  settings=settings
)
stations = request.filter_by_station_id(station_id=[1048])
values = stations.values.all()
df = values.filter_by_sql("parameter='temperature_air_mean_2m' AND value < -7.0;")
df
```

--------------------------------

### Query Data for Specific Stations

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-api.md

Query observed data for selected stations. This example shows how to iterate through results and process individual station dataframes.

```python
from wetterdienst.provider.dwd.observation import DwdObservationRequest
from wetterdienst import Settings

# if no settings are provided, default settings are used which are
# Settings(ts_shape="long", ts_humanize=True, ts_si_units=True)
request = DwdObservationRequest(
    parameters=[("daily", "kl"), ("daily", "solar")],
    start_date="1990-01-01",
    end_date="2020-01-01",
)
stations = request.filter_by_station_id(station_id=("00003", "01048"))

# From here you can query data by station
for result in stations.values.query():
    # analyse the station here
    break

df = result.df.drop_nulls()
df
```

--------------------------------

### Run Explorer UI Service

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/docker.md

Run the wetterdienst Explorer UI service in a Docker container, exposing it on port 7891.

```bash
docker run -it --rm --publish=7891:7891 ghcr.io/earthobservations/wetterdienst wetterdienst explorer --listen 0.0.0.0:7891
```

--------------------------------

### Run All Tests (Python Backend)

Source: https://github.com/earthobservations/wetterdienst/blob/main/AGENTS.md

Executes all tests, including parallel and cflake tests, for the Python backend. Use this for a comprehensive test suite run.

```bash
uv run poe test
```

--------------------------------

### Query DWD Historical Precipitation Height Data

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-examples.md

Get historical precipitation height data from DWD using a list of parameters. Requires importing DwdObservationRequest.

```python
from wetterdienst.provider.dwd.observation import DwdObservationRequest

request = DwdObservationRequest(
    parameters=[("daily", "precipitation_more", "precipitation_height")],
    periods="historical",
)

first_values = next(request.all().values.query())
df = first_values.df
df
```

--------------------------------

### Query Stations with SQL

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/restapi.md

Query a list of stations using SQL for filtering.

```bash
http localhost:7890/api/stations provider==dwd network==observation parameters==daily/kl periods==recent sql=="lower(name) LIKE lower('%dresden%');"
```

--------------------------------

### Query DWD Climate Summary Precipitation Height

Source: https://github.com/earthobservations/wetterdienst/blob/main/docs/usage/python-examples.md

Get daily historical climate summary precipitation height data from DWD. Requires importing DwdObservationRequest.

```python
from wetterdienst.provider.dwd.observation import DwdObservationRequest

request = DwdObservationRequest(
    parameters=("daily", "climate_summary", "precipitation_height"),
    periods="historical",
)

first_values = next(request.all().values.query())
df = first_values.df
df
```