Example

of building a notebook-friendly object into the output of the data API

Author: Dan Gunter

Initialization

Imports

Set up matplotlib, the qgrid (nice table), and import biokbase



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%matplotlib inline
import matplotlib.pyplot as plt



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import qgrid
qgrid.nbinstall()



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from biokbase import data_api
from biokbase.data_api import display
display.nbviewer_mode(True)









    Out[3]:





True

Authorization

In the vanilla notebook, you need to manually set an auth. token. You'll need your own value for this, of course. Get this from the running narrative, e.g. write a narrative code cell that has: import os; print(os.environ('KB_AUTH_TOKEN'))



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import os
os.environ['KB_AUTH_TOKEN'] = open('/tmp/kb_auth_token.txt').read().strip()

Find and load an object

Open the workspace (1019) and get a Rhodobacter assembly from it



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b = data_api.browse(1019)



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x = b[0].object # Assembly object

Get the contigs for the assembly

This takes a while because the current implementation loads the whole assembly, not just the 300 or so strings with the contig values.



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cid_strings = x.get_contig_ids() # 1 min









    



---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-7-e8b4c752251a> in <module>()
----> 1 cid_strings = x.get_contig_ids() # 1 min

AttributeError: 'GenomeAnnotationAPI' object has no attribute 'get_contig_ids'



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cids = display.Contigs(cid_strings)

View the contigs

The Contigs object wraps the list of contigs as a Pandas DataFrame (with the qgrid output enabled), so as you can see the plot() function is immediately available. The list of strings in the raw contig IDs is parsed to a set of columns and values for the DataFrame.

The default display is the nice sortable, scrollable, etc. table from the qgrid package.



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from biokbase import data_api
from biokbase.data_api import display



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list(b)



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rg = b[0]



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rgo = rg.object



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type(rgo)



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