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• filter: Defines an expression to evaluate for each type. When the expression evaluates as true, that type is fetched.
• limit: Fetch only 'limit' results. Can be useful to debug a fetch which might grab a lot of results.
• include: Define specific properties of the Type to include in the fetch result. If not defined, all properties will be grabbed.
• order: An expression which defines the order to return the results in.

Here is a list of C3 documentation mentioning fetching:

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Examples of Fetch operations

Consider the DTI housing example located here: https://

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github.

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com/

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c3aidti/HouseCoverageExample

In this example, the Type BlockInfo defines information aggregated about census blocks. We can for example, fetch BlockInfo
types for which the 'prp_bf_lr' property is defined. Then we can order them based on their 'id' properly.

BlockInfo.fetch({
	'limit': -1,
	'filter': 'exists(prp_bf_lr)',
	'order': 'descending(id)',
	'include': 'pct_i_l,pct_t_l,prp_res_lr,pop10_ha_lr,hu10_ha_lr,eroom_ha_lr,med10_age,prp_bf_lr',
})

Here's how you would perform the same fetch in python

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:

from c3python import get_c3 
raw_df = c3.BlockInfo.fetch(spec={
    'limit': -1,
    'filter': 'exists(prp_bf_lr)',
    'order': 'descending(id)',
    'include': 'pct_i_l,pct_t_l,prp_res_lr,pop10_ha_lr,hu10_ha_lr,eroom_ha_lr,med10_age,prp_bf_lr'
})

Here is a list of C3 documentation mentioning fetching:

1. FetchSpec Documentation: https://developer.c3.ai/docs/7.12.0/type/FetchSpec
2. Fetching in Python: https://developer.c3.ai/docs/7.12.0/topic/ds-jupyter-notebooks

Converting Fetch results to usable forms in Jupyter Notebook

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