pyosf is a pure Python library for simple file sync with Open Science Framework

This package is for simple synchronisation of files from the local file space to the Open Science Framework (OSF). There is a more complex fully-featured sync package by the Center for Open Science, who created OSF, called osf-sync

The OSF official package is designed for continuous automated synchronisation of many projects (a la Dropbox). We needed something simpler (for combination with PsychoPy). The pyosf package aims to perform basic search/login/sync operations with single projects on OSF but only when instructed to do so (no continuous sync).

In implementation pyosf differs from osf-sync in the following ways:

• fewer dependencies
• support for Python2.x
• no GUI included (yet)
• local database of files saved as flat json format (no database)
• simpler handling of sync resolution rules(?)

It can be distributed freely under the MIT license.

Installation

pyosf is compatible with Linux, OS X and Windows, and with Python 2.7 and Python 3.4 (upwards)

Install it with:

pip install pyosf

Usage

When you first create a Project, or to perform searches for projects, you need to create a Session::

import pyosf
session = pyosf.Session(username='name@gmail.com', password='xxyxyayxy')

The Session allows you to conduct searches::

users = session.find_users('Peirce')  # a list of user ids
print(users)
jon_id = users[0]['id']  # we're just using the first one
projs = session.find_user_projects(user_id=jon_id)  # id=None to find your own projects
for proj in projs:
    print('{}: {}'.format(proj.id, proj.title))

osf_proj = session.open_project(proj_id)  # or this if you know the project id

Then you can create a Project object to track the remote and local files. A Project consists of:

• project_file: your project info

• root_path: the location where your osf project is permanently stored locally

• osf: an OSF project object from a Session

  OR

• simply a project file location, on subsequent repeats (provided you did not change the root_path.)

If initially, you do not have a project_file, just specify the location where you want to save it later. pyosf will give you a warning that it did not find a project_file, which is ok because we are going to create it.

# Make a project object
proj = pyosf.Project(project_file='/Home/myUserName/pyosfProjects/first.proj',
                     root_path='/Home/myUserName/experiments/firstExperiment',
                     osf=osf_proj)

# get the difference between local and remote project										 
changes = proj.get_changes()  

# inspect the changes
print(changes)  

# do the sync
changes.apply()

# If you did not have a project file initially, the following will create one
# and save it under the path that you have given when calling `pyosf.Project`  
proj.save()  

The project file saves your username (but not password) and, if the username has previously been used to authenticate a Session with OSF then an authentication token will have been saved to ~/.pyosf/tokens.json and that will allow the project to create a new session. i.e. on subsequent logins you can do just:

import pyosf
# no need to create a session second time around
proj = pyosf.Project(project_file='/Home/myUserName/pyosfProjects/first.proj')
changes = proj.get_changes()
changes.apply()

Security and passwords

When you first create a Session you need to provide a username (email address) and your OSF password. These will be sent securely (over https) and an auth token will be retrieved. That auth token will be stored in readable text in the current user space of your computer (in ~/.pyosf/tokens.json). When a Session is subsequently created the username is used to check for a previous auth token and if one is found a password will not be needed.

The second step is from the Project. The Project stores in its .proj file (json format) the username that was being used for this sync (as supplied on first access). That username will be used to create a Session which will then fetch the appropriate token as described above.