Skip to main content

Library to download information using Minka API.

Project description

cos4cloud

Library to extract information collected in the Minka API. This library is part of MECODA (ModulE for Citizen Observatory Data Analysis), aimed to facilitate analysis and viewing of citizen science data.

embimos

This repository is part of the work made by the EMBIMOS Reseach Group, at Marine Sciences Institute (CSIC) of Barcelona.

Installation

pip install mecoda-minka

Use

Get observations

With get_obs you can extract data from the observations collected in the API. The function supports combinations of these arguments, which act as filters, getting the observations in descending order of id, with a maximum of 20,000 (API limitation):

Argument Descrition Example
query Word or phrase found in the data of an observation query="quercus quercus"
project_name Name of a project project_name="urbamar"
id_project Identification number of a project id_project=806
id_obs Identification number of a specific observation id_obs=425
user Name of user who has uploaded the observations user="zolople"
taxon One of the main taxonomies taxon="fungi"
place_id Identification number of a place place_id=1011
place_name Name of a place place_name="Barcelona"
year Year of observations year=2019

For the taxon argument the possible values are: chromista, protozoa, animalia, mollusca, arachnida, insecta, aves, mammalia, amphibia, reptilia, actinopterygii, fungi, plantae, cnidaria, annelida, platyhelminthes, echinodermata, bryozoa, porifera, elasmobranchii, crustacea y ctenophora.

Example of use:

from mecoda_minka import get_obs

observations = get_obs(year=2018, taxon='fungi')

observations is an object list Observation.

Get projects

With get_project you can get the information of the projects collected in the API. The function supports a single argument, which can be the project identification number or the name of the project. In case the name does not correspond exclusively to a project, it returns the information from the list of projects that include that word.

Example of use:

from mecoda_minka import get_project

projects = get_project("urbamar")

projects es siempre una lista de objetos Project.

Get count of observations by taxonomic family

With get_count_by_taxon we can know the number of observations that correspond to each of the taxonomic families. The function does not take any argument.

Example of use:

from mecoda_minka import get_count_by_taxon

count = get_count_by_taxon()

count is a dictionary with the structure {taxonomy: number of observations}

Models

The models are defined using objects from [Pydantic] (https://pydantic-docs.helpmanual.io/). Type validation of all attributes is done and data can be extracted with the dict or json method.

Observation

The object Observation contains the information of each of the observations registered in [Minka] (https://minka-sdg.org/observations) and has the following attributes:

Attribute Type Description Default value
id int Observation number
captive Optional[bool] State of captivity None
created_at Optional[datetime] Creation date None
updated_at Optional[datetime] Update date None
observed_on Optional[date] Observation date None
description Optional[str] Observation description None
iconic_taxon Optional[IconicTaxon] Taxonomic family None
taxon_id Optional[int] Identification number of the specific taxonomy None
taxon_name Optional[str] Name of the species observed None
taxon_ancestry Optional[str] String of the taxonomic sequence to which the observation corresponds, with identifiers separated by / None
latitude Optional[float] Latitude None
longitude Optional[float] Longitude None
place_name Optional[str] Observation site name None
quality_grade Optional[QualityGrade] Quality grade: research, casual o needs_id None
user_id Optional[int] User identification number None
user_login Optional[str] User registration name None
photos List[Photo] Object lists Photo, that include information about each photograph of the observation []
num_identification_agreements Optional[int] Number of votes in favor of identification None
num_identification_disagreements Optional[int] Number of unfavorable votes to identification None

Project

The Project object contains the information of each of the projects registered in [Minka] (https://minka-sdg.org/observations) and has the following attributes:

Attribute Type Description Default value
id int Project identification number
title str Title of the project
description Optional[str] Project description None
created_at Optional[datetime] Project creation date None
updated_at Optional[datetime] Project update date None
latitude Optional[float] Latitude None
longitude Optional[float] Longitude None
place_id Optional[int] Place identification number None
parent_id Optional[int] Identification number of the project in which it is included None
children_id List[int] Identification numbers of the projects it has inside []
user_id Optional[int] Identification number of the user who creates it None
icon_url Optional[str] Link to project icon None
observed_taxa_count Optional[int] Number of observations included in the project None

Photo

The Photo object contains the information of each photography linked to an observation and has the following attributes.

Attribute Type Description Default value
id int Photo identification number
large_url str Link to large format photo
medium_url str Link to the photograph in medium format
small_url str Link to the photo in small format

Contributions

To contribute to this library, follow the steps below.

  • You need to have Python 3.7 or higher, virtualenv and git installed.

  • Create a github fork of this project.

  • Clone your fork and enter the directory

    git clone git@github.com:<your_username>/mecoda_minka.git
    cd mecoda_minka
    
  • Configure your virtualenv to run the tests:

    virtualenv -p `which python3.7` env
    source env/bin/activate
    
  • Install mecoda_minka and its dependencies.

    pip3 install -e .
    pip3 install -r requirements-dev.txt
    
  • Create a new branch and make your changes:

    git checkout -b mi-nueva-rama
    
  • Run the tests with:

    python -m pytest --cov-report term-missing --cov src tests
    

    If you need to pass a specific test, you can use pytest -k <test-name>.

  • Update the documentation.

  • Make commit, push and create your pull request.

Upload a new version

  • Switch to master and update:

    git checkout master
    git pull
    
  • Create a new branch:

    git checkout -b <branch-name>
    git pull
    
  • Make changes to the code

  • Run the tests:

    python -m pytest --cov-report term-missing --cov src tests
    
  • Edit the setup.py file to upload the version, which means changing the version argument in the setup function. The convention is 0.1.0 == major.minor.patch. major is to introduce changes that break the existing code. minor refers to changes that add functionality but do not break existing code. patch refers to changes that fix bugs but do not add functionality.

  • Make commit and push:

    git add .
    git commit -m "<comment>"
    git push --set-upstream origin <branch-name>
    
  • Follow the link to github returned by the push and merge.

  • Update master:

    git checkout master
    git pull
    
  • Create tag with the new version:

    git tag <new-version>
    git push --tags
    
  • Build the package:

    rm dist/ build/ -r
    python setup.py -q bdist_wheel
    python setup.py -q sdist
    
  • Upload package to pypi:

    twine upload -r pypi dist/*
    

Thanks for contributing to this project!

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

mecoda-minka-1.5.0.tar.gz (3.0 MB view hashes)

Uploaded Source

Built Distribution

mecoda_minka-1.5.0-py3-none-any.whl (3.0 MB 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