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README.md

PhotosynQ | Python

Build Status

Truly Collaborative Plant Research

PhotosynQ helps you to make your plant research more efficient. For advanced analysis, this package allows you to pull data right into Python.

New python users should consider installing Anaconda which includes both the python interpreter and the Jupyter python editor.

For advanced users, we recommend using Spyder to edit and run python code.


Installation

Install using pip in the terminal.

pip install git+https://github.com/Photosynq/PhotosynQ-Python.git --upgrade --no-cache-dir

Getting started

Standard usage

Retrieve project data and meta-data in a convenient DataFrame

import photosynq_py as ps

# use your photosynq account to login (you will be prompted for your password)
email = "john.doe@domain.com"
ps.login(email)

# retrieve a dataframe with data from the given project ID
projectId = 1556
df = ps.get_project_dataframe(projectId)

# logout
ps.logout();

Other Functions

Advanced users can retrieve project data and meta-data/info separately, as json strings.

getProjectInfo, getProjectData and buildProjectDataFrame (below) are components of getProjectDataFrame (above)

ps.login( "john.doe@domain.com" )
projectId = 1556
info = ps.get_project_info(projectId)
data = ps.get_project_data(projectId, processed_data=False) # Use raw data
df = ps.build_project_dataframe(info, data)
ps.logout()

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Python package with convenience functions for accessing the PhotosynQ website API

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