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[](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.
generate a JSON file containing metadata describing your data
generate a CSV file with your data
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.
Metadata
Release files for pyAnalyticsCloud 0.8.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pyAnalyticsCloud-0.8.0.tar.gz | 6.5 kB | Details |
Release files / pyAnalyticsCloud-0.8.0.tar.gz
| Download URL | pyAnalyticsCloud-0.8.0.tar.gz |
|---|---|
| Size | 6.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
1eb8cc104f501ff5137306c66143f087d8c6073c6c6a2bff1b149ec76df82381
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