Skip to main content

The api-24sea package contains modules that are aimed at helping a user interact with the 24SEA API.

Project description

API 24Sea

api_24sea is a project designed to provide aid for the interaction with data from the 24SEA API.

Installation

pip install api_24sea

DataSignals Usage

The following example shows the classical usage of the datasignals module.

  • The first step is to import the package and the necessary libraries.
  • Then, the environment variables are loaded from a .env file.
  • After that, the package is initialized and the user is authenticated with the API.
  • Finally, the user can get data from the API.

Importing the package

# %%
# **Package Imports**
# - From the Python Standard Library
import logging
import os

# - From third party libraries
import dotenv
import pandas as pd

# - Local imports
from api_24sea.version import __version__, parse_version
import api_24sea

Setting up the environment variables

This step assumes that you have a file structure similar to the following one:

.
├── env/
│   └── .env
├── notebooks/
│   └── example.ipynb
└── requirements.txt

The .env file should look like this:

API_USERNAME=your_username
API_PASSWORD=your_password

With this in mind, the following code snippet shows how to load the environment variables from the .env file:

# %%
_ = dotenv.load_dotenv("../env/.env")
if _:
    print("Environment Variables Loaded Successfully")
    print(os.getenv("API_USERNAME"))
else:
    raise Exception("Environment Variables Not Loaded")

Initializing an empty dataframe

Initializing an empty dataframe is necessary to use the API, as here is where the data will be stored.

# %%
df = pd.DataFrame()

# %%
try:
    df.datasignals.get_metrics()
except Exception as e:
    print("API not available")
    print(e)

Authenticating with the API

The authentication step allows the user to access the API and check the available metrics.

# %%
df.datasignals.authenticate(
    os.getenv("API_USERNAME"), os.getenv("API_PASSWORD")
)
# After authentication, the user can access the API

Checking the available metrics after authentication

# %%
df.datasignals.metrics_overview
# It will show all the available metrics with the corresponding units
# and the time window for which the user is allowed to get data

Getting sample data from the API

After loading the environment variables and authenticating with the API, the user can get data from 24SEA API endpoints.

# %%
sites = ["windfarm"]
locations = ["a01", "a02"]
metrics = ["mean WinDSpEed", "Std-windspeed", "mean_pitch", "mean power"]

start_timestamp = "2020-03-01T00:00:00Z"
end_timestamp = "2020-06-01T00:00:00Z"

df.datasignals.get_data(sites, locations, metrics,
                        start_timestamp, end_timestamp,
                        outer_join_on_timestamp=True)

Checking the metrics selected

# %%
df.datasignals.selected_metrics

Checking the data

# %%
df

Project Structure

.
├── .azure/
├── api_24sea/
│   ├── __init__.py
│   ├── datasignals/
│      ├── __init__.py
│      └── schemas.py
│   ├── utils.py
│   └── version.py
├── tests/
├── docs/
├── notebooks/
├── pyproject.toml
├── LICENSE
├── VERSION
└── README.md

License

The package is licensed under the GNU General Public License v3.0.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

api_24sea-0.6.0.tar.gz (26.7 kB view hashes)

Uploaded Source

Built Distribution

api_24sea-0.6.0-py3-none-any.whl (26.0 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page