meteoblue-dataset-sdk 0.0.15

Easy access to the meteoblue dataset API

meteoblue Python Dataset SDK

This library simplifies access to the meteoblue dataset API.

WARNING: This library is under development and has no declared stable version 1.0 yet! Use with caution!

In order to use this library you need a meteoblue API key.

Features:

• Fetch any dataset from the meteoblue environmental data archive
• Transparently integrates job queues to query large datasets
• Efficiently transfers data using compressed protobuf messages
• Asynchronous interface to query data in parallel
• Data can be used as simple floating-point arrays. No further formatting required.

Installation

• Ensure that you are using at least Python 3.7 with python --version (Sometimes python3)
• Install the module with pip install 'meteoblue_dataset_sdk >=0.0,<0.1' (Sometimes pip3)

This module will also install the following dependencies automatically:

• aiohttp >=3.6,<4
• protobuf >=3.0,<4

Usage

See main.py for a working example. To generate the query JSON it is highly recommended to use the dataset API web interfaces

Note: This demo code implies that you are using async functions. If you do not want to use async/await, use result = client.querySync(query).

import meteoblue_dataset_sdk

query = {
    "units": {
        "temperature": "C",
        "velocity": "km/h",
        "length": "metric",
        "energy": "watts",
    },
    "geometry": {
        "type": "MultiPoint",
        "coordinates": [[7.57327, 47.558399, 279]],
        "locationNames": ["Basel"],
    },
    "format": "json",
    "timeIntervals": ["2019-01-01T+00:00/2019-01-01T+00:00"],
    "timeIntervalsAlignment": "none",
    "queries": [
        {
            "domain": "NEMSGLOBAL",
            "gapFillDomain": None,
            "timeResolution": "hourly",
            "codes": [{"code": 11, "level": "2 m above gnd"}],
        }
    ],
}
client = meteoblue_dataset_sdk.Client(apikey="xxxxxx")  # ask for key
result = await client.query(query)
# result is a structured object containing timestamps and data

timestamps = result.geometries[0].timeIntervals[0].timestamps
data = result.geometries[0].codes[0].timeIntervals[0].data

print(timestamps)
# [1546300800, 1546304400, 1546308000, 1546311600, 1546315200, ...
print(data)
# [2.89, 2.69, 2.549999, 2.3800001,

More detailed output of the result object. The output is defined as this protobuf structure.

geometries {
  domain: "NEMSGLOBAL"
  lats: 47.66651916503906
  lons: 7.5
  asls: 499.7736511230469
  locationNames: "Basel"
  nx: 1
  ny: 1
  timeResolution: "hourly"
  timeIntervals {
    timestamps: 1546300800
    timestamps: 1546304400
    timestamps: 1546308000
    timestamps: 1546311600
    timestamps: 1546315200
    timestamps: 1546318800
    timestamps: 1546322400
    timestamps: 1546326000
    timestamps: 1546329600
    timestamps: 1546333200
    timestamps: 1546336800
    timestamps: 1546340400
    timestamps: 1546344000
    timestamps: 1546347600
    timestamps: 1546351200
    timestamps: 1546354800
    timestamps: 1546358400
    timestamps: 1546362000
    timestamps: 1546365600
    timestamps: 1546369200
    timestamps: 1546372800
    timestamps: 1546376400
    timestamps: 1546380000
    timestamps: 1546383600
  }
  codes {
    code: 11
    level: "2 m above gnd"
    unit: "\302\260C"
    aggregation: "none"
    timeIntervals {
      data: 2.890000104904175
      data: 2.690000057220459
      data: 2.549999952316284
      data: 2.380000114440918
      data: 2.2699999809265137
      data: 2.119999885559082
      data: 1.9900000095367432
      data: 1.8300000429153442
      data: 1.8200000524520874
      data: 2.0999999046325684
      data: 2.430000066757202
      data: 2.9200000762939453
      data: 3.7200000286102295
      data: 3.930000066757202
      data: 3.9100000858306885
      data: 3.5299999713897705
      data: 3.130000114440918
      data: 2.880000114440918
      data: 2.6500000953674316
      data: 2.4600000381469727
      data: 2.2799999713897705
      data: 2.0299999713897705
      data: 1.690000057220459
      data: 1.3799999952316284
    }
  }
}

Developer setup

python3 -m venv env
source env/bin/activate
pip3 install -r requirements.txt