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Tools to help load data into Salesforce.com Analytics Cloud

Project description

[![GitHub license](https://img.shields.io/github/license/heroku/pyAnalyticsCloud.svg)](https://github.com/heroku/pyAnalyticsCloud)

Salesforce.com Wave Data Loader

Tools to help load data into Salesforce.com Wave

Usage

First, you will need to set your SFDC credencials via environment variables:

export SFDC_USERNAME=youruser@example.com
export SFDC_PASSWORD=yourpassword
export SFDC_TOKEN=yourtoken

More information about getting your [Security Token](https://help.salesforce.com/apex/HTViewHelpDoc?id=user_security_token.htm)

The quickest way to get started is to load an entire table into Salesforce Wave

pyac-table postgres://username:password@db.example.com/database table_name

This command will execute the following three step process.

  1. generate a JSON file containing metadata describing your data

  2. generate a CSV file with your data

  3. upload the metadata and data to Analytics Cloud

pyAnalyticsCloud also provides commands help with each step, this allows you to customize your data before upload:

pyac-metadata postgres://username:password@db.example.com/database table_name -o metadata.json
pyac-dump postgres://username:password@db.example.com/database table_name -o data.csv
pyac-upload metadata.json data.csv

Rather than manually editing the datafiles, you may want to simply create a new DB table that is populated with your data and use pyac-table.

Library

If you want to develop more advanced workflows you can use pyAnalyticsCloud as a library for a Python application.

Project details


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pyAnalyticsCloud-0.8.0.tar.gz (6.5 kB view hashes)

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