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Pythonic interface to the Skydipper API.

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# Skydipper ## The Vizzuality Ecosystem Python Interface

[![Build Status](https://travis-ci.org/Skydipper/Skydipper.svg?branch=master)](https://travis-ci.org/Skydipper/Skydipper) [![codecov](https://codecov.io/gh/Vizzuality/Skydipper/branch/master/graph/badge.svg)](https://codecov.io/gh/Vizzuality/Skydipper) [![PyPI](https://img.shields.io/pypi/v/Skydipper.svg?style=flat)](https://pypi.org/project/Skydipper/) ![](https://img.shields.io/pypi/pyversions/Skydipper.svg?style=flat) ![](https://img.shields.io/pypi/wheel/Skydipper.svg?style=flat) [![Documentation Status](https://readthedocs.org/projects/skydipper/badge/?version=latest)](https://skydipper.readthedocs.io/en/latest/?badge=latest) [![License](https://img.shields.io/badge/License-MIT-brightgreen.svg)](https://github.com/Vizzuality/Skydipper/blob/master/LICENSE)

Skydipper is a Python library with hooks to Jupyter, backed by the [Skydipper API](https://github.com/Skydipper). It provides many functions related to adding, analysing and working with open geospatial datasets.

## Read the Docs

[Read the docs pages](https://skydipper.readthedocs.io/en/latest/).

## Installation

pip install Skydipper

## Use

` $ python >>> import Skydipper `

Create a Dataset object based on an existing ID on default server. ` >>> ds = Dataset('044f4af8-be72-4999-b7dd-13434fc4a394') >>> print(ds) Dataset 044f4af8-be72-4999-b7dd-13434fc4a394 `

Create a Layer object based on an existing ID on default server. ` >>> ly = Layer(id_hash='dc6f6dd2-0718-4e41-81d2-109866bb9edd') >>> print(ly) Layer dc6f6dd2-0718-4e41-81d2-109866bb9edd `

Create a Table object based on an existing ID. ` >>> table = Table('fbf159d7-a462-4af3-8228-43ee3e3391e7') # return the head of the table as a geopandas dataframe >>> df = table.head(5) # return a query of the table as a geopandas dataframe >>> result = table.query(sql='SELECT count(*) as my_count FROM data WHERE year > 1991 and year < 1995' ) `

Obtain a collection of objects using a search term. ` >>> col = Collection(search='tree',object_type=['dataset'], app=['gfw'],limit=5) >>> print(col) [Dataset 70e2549c-d722-44a6-a8d7-4a385d78565e, Dataset 897ecc76-2308-4c51-aeb3-495de0bdca79, Dataset 89755b9f-df05-4e22-a9bc-05217c8eafc8, Dataset 83f8365b-f40b-4b91-87d6-829425093da1, Dataset 044f4af8-be72-4999-b7dd-13434fc4a394] ` Check the docs for more info!

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