trifacta 2.5

Trifacta client

trifacta

Trifacta client that makes it easy to integrate Trifacta into your production and data science workflows

Usage Scenarios

• Jupyter: Invoke Trifacta jobs from a Jupyter notebook and pass data back and forth between Jupyter and Trifacta
• Other Notebooks: Integrate Trifacta with Azure Databricks, Zepellin or any other notebook-style interface that supports Python
• Scripts: Automate Trifacta jobs and input/output using python scripts that can be easily executed from the command line or called from an external scheduler

Functionality

This library makes it simple to do the following:

1. Connect to a Trifacta instance
2. Run a job
3. Download results to a csv file and view in pandas dataframe

Note that file uploads and downloads are performed using Amazon S3, using the boto3 API

#!pip install trifacta
import trifacta

If you need an access token, you can generate it as follows:

#Step 1: Connect to Trifacta by providing the URL and API Access Token
t = trifacta.Client('http://partnerdemo.amer.trifacta.net:3005', 'YOUR_ACCESS_TOKEN')

Get the wrangled dataset id from the URL in the Trifacta UI

Make sure that you have run the job manually at least once

Note the output path (be sure to set it to "replace")

#Step 2: Run the job
t.run_job(23)

About to run job
{'sessionId': '9d339e65-8898-4165-871b-b9db848dc099', 'reason': 'JobStarted', 'jobGraph': {'vertices': [76, 77], 'edges': [{'source': 76, 'target': 77}]}, 'id': 42, 'jobs': {'data': [{'id': 76}, {'id': 77}]}}
2020-02-25 11:19:58.508231 InProgress
2020-02-25 11:20:03.700189 InProgress
2020-02-25 11:20:08.887794 Complete





True

%env AWS_PROFILE=trifacta_master_trial

env: AWS_PROFILE=trifacta_master_trial

#Step 3: Download results to a csv file and view in pandas dataframe
import boto3
s3 = boto3.client('s3', region_name='us-west-2')

s3.download_file(Bucket='trifacta-partnerdemo-trifactabucket-kkcpnw234feu',
                Key='trifacta/queryResults/[e-mail]/MarketingAnalytics.csv',
                Filename='MarketingAnalytics.csv')

import pandas as pd
df = pd.read_csv('MarketingAnalytics.csv')

df.head()

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</style>

	user_id	customerkey	event_type	event_subtype	Date	advertiser_id	creative_id	url	product_id	domain_url	...	customeraccount_number	customerphone	customeraddress	cusotmerstate	customerzipcode	customercountry	socialmedia	totalsale	Outlier_Identifier	currencykey
0	1126310400000-424	1126310400000-424	click	click	10-19-2005	164332	543027	http://zdnet.com/praesent/lectus/vestibulum/qu...	1124064000000-475	zdnet	...	310170445527596	[phone]	156 Cozy Berry Arc	CA	78710	USA	deneleaf	7004.54	False	1
1	1229126400000-20	1229126400000-20	click	click	08-17-2009	164332	252030	http://hostgator.com/a/feugiat.js?pid=12331008...	1233100800000-528	hostgator	...	310150240507900	[phone]	3641 Euismod Avenue	CA	10769	USA	kinphanng	4853.35	False	1
2	1126828800000-518	1126828800000-518	view	view	04-05-2006	164332	562765	http://fc2.com/convallis/duis/consequat/dui/ne...	1121904000000-509	fc2	...	310170133079761	[phone]	Ap #543-7410 Accumsan Rd.	CA	92845	USA	waldeelbailarin	6885.15	False	1
3	1130112000000-336	1130112000000-336	click	click	04-05-2006	164332	466942	http://biblegateway.com/est/phasellus/sit/amet...	1130284800000-343	biblegateway	...	310120073380564	[phone]	900-8123 Aliquam Av.	CA	85517	USA	charlrey	2593.31	False	1
4	1121990400000-216	1121990400000-216	view	view	09-27-2005	164332	400316	https://zdnet.com/elementum/nullam/varius/null...	1108339200000-416	zdnet	...	310160496868669	301 742 1112	164 Cozy Anchor Rd	CA	60101	USA	scottylago	3958.25	False	1

5 rows × 31 columns