Metadata-Version: 2.1
Name: pynasapower
Version: 0.0.1a0
Summary: Download meteorological data from NASA POWER API (https://power.larc.nasa.gov/)
Home-page: https://github.com/alekfal/pynasapower
Author: Falagas Alekos
Author-email: Alekos Falagas <alek.falagas@gmail.com>
Maintainer-email: Alekos Falagas <alek.falagas@gmail.com>
License: GPL3
Classifier: Intended Audience :: Science/Research
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: GIS
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: requests
Requires-Dist: geopandas
Requires-Dist: shapely
Requires-Dist: xarray
Requires-Dist: scipy
Provides-Extra: docs
Requires-Dist: sphinx; extra == "docs"
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Requires-Dist: sphinx_rtd_theme; extra == "docs"
Requires-Dist: myst_parser; extra == "docs"
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Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
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Requires-Dist: pytest-dependency; extra == "dev"
Requires-Dist: pytest-lazy-fixture; extra == "dev"
Requires-Dist: pytest-mock; extra == "dev"

# pynasapower
![nasa](https://user-images.githubusercontent.com/18232521/75673566-eb882880-5c8b-11ea-9a65-995f94b876bf.png)

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[![Supported Python versions](https://img.shields.io/pypi/pyversions/pynasapower.svg?style=flat-square)](https://pypi.org/project/pynasapower/)
[![Overall downloads](https://pepy.tech/badge/pynasapower)](https://pepy.tech/project/pynasapower)
[![Last month downloads](https://pepy.tech/badge/pynasapower/month)](https://pepy.tech/project/pynasapower)

Download meteorological data from NASA POWER restful API (https://power.larc.nasa.gov/) using pynasapower API client.

The NASA POWER database is a global database of daily meteorological data designed for agrometeorological applications and more. 
Data are retrieced from in-situ observations in combination with satellite data. The meteorological data is updated with a delay of about 3 months. For more information on the NASA POWER database see the documentation at: https://power.larc.nasa.gov/

### Installation from source

```bash
git clone https://github.com/alekfal/pynasapower.git
cd pynasapower/
pip install .
```

### Instalation from PyPI

```bash
pip install pynasapower
```

### Examples

Download meteorological data for a point in Athens, Greece and save result in `*.csv` format.

```python
from pynasapower.get_data import query_power
from pynasapower.geometry import point, bbox
import datetime

# Run for point in Athens and save the result in csv format
gpoint = point(23.727539, 37.983810, "EPSG:4326")
start = datetime.date(2022, 1, 1)
end = datetime.date(2022, 2, 1)
data = query_power(gpoint, start, end, "./data", True, "ag", [], "daily", "point", "csv")
```

Download meteorological data for a polygon in Athens, Greece and save result in `*.csv` format.

```python
# Run for small bbox in Athens and save the result in csv format
gbbox = bbox(23.727539, 26.73, 37.983810, 40.99, "EPSG:4326")
start = datetime.date(2022, 1, 1)
end = datetime.date(2022, 2, 1)
data = query_power(gpoint, start, end, "./data", True, "ag", [], "daily", "regional", "csv")
```

Read more about the software in readthedocs.
