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Tools for processing AWS detailed billing reports

Project Description

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details

Utilities to process AWS detailed billing reports.

Installation

The easiest way to install details is by using pip:

$ pip install details

Backgroud

The details package parses the detailed billing reports produced by AWS. You can find out more about these reports and how to enable them for your AWS accounts [here](http://docs.aws.amazon.com/awsaccountbilling/latest/aboutv2/detailed-billing-reports.html). All testing thus far has been done using the Detailed billing report with resources and tags but the code should work with any detailed billing report.

Once you have enabled detailed billing on your accounts, AWS will begin to save these CSV reports in the S3 bucket you have configured. The details library assumes you have copied the reports from S3 to your local file system and uncompressed them if necessary. The [AWS CLI](https://aws.amazon.com/cli) is a good way to copy the files from S3.

The detailed billing files contain a row (a line item) for every charge on an account with hourly granularity. These files can get huge. These tools currently load an entire months worth of data into memory so if you have a really large bill this could become impractical. However, it has been demonstrated to work reasonably well on detailed billing reports containing millions of line item records.

Usage

Once you have a detailed billing CSV file available locally, you can load the file into details like this:

>>> import details
>>> total = details.load('../../bills/123456789012-aws-billing-detailed...')

The variable costs now points to a Cost object which contains all of the line item data for the entire billing file. Note that depending on the size of your detailed billing report, this operation can take some time.

Now that you have the Cost object, you can start by asking it for the total cost of the detailed billing report:

>>> total.cost
Decimal('1035.7549984289')
>>>

This number should match (or very nearly match, there are some rounding errors at times) the total on your bill. The other thing to note is that the value returned is a Python Decimal number. The Decimal type is used to avoid any further rounding errors within the details package. You can use these Decimal numbers as you would normal ints or floats. Checkout [this](https://docs.python.org/2/library/decimal.html) for more details on the Decimal type.

In addition to telling you the total cost, the Cost object has a few other useful methods.

To find all of the columns in CSV data:

>>> total.columns
['InvoiceID',
 'PayerAccountId',
 'LinkedAccountId',
 'RecordType',
 'RecordId',
 'ProductName',
 'RateId',
 'SubscriptionId',
 'PricingPlanId',
 'UsageType',
 'Operation',
 'AvailabilityZone',
 'ReservedInstance',
 'ItemDescription',
 'UsageStartDate',
 'UsageEndDate',
 'UsageQuantity',
 'BlendedRate',
 'BlendedCost',
 'UnBlendedRate',
 'UnBlendedCost',
 'ResourceId',
 'user:Name',
 'user:Role']

To find all possible values found within a particular column:

>>> total.values('ProductName')
['Amazon Simple Storage Service',
 'Amazon DynamoDB',
 'Amazon Route 53',
 'Route 53 Domain Registration Service',
 'AWS Data Pipeline',
 'Amazon Elastic MapReduce',
 'Amazon RDS Service',
 'Amazon Zocalo',
 'Amazon Simple Queue Service',
 'AWS Support (Business)',
 'Amazon Simple Notification Service',
 'Amazon CloudFront',
 'AWS Support (Developer)',
 'Amazon WorkSpaces',
 'Amazon Redshift',
 'Amazon Elastic Compute Cloud',
 'Amazon ElastiCache',
 'Amazon Kinesis',
 'Amazon CloudSearch',
 'Amazon SimpleDB',
 'Amazon Simple Email Service']

This list will include only the services that actually were used within this account.

If this report was for a consolidated account, you could find all of the accounts contained within this report like this:

>>> total.values('LinkedAccountId')
['012345678901',
 '123456789012']
>>>

The above total represents all of the costs for all services within this account. What if you wanted to find the costs just for the EC2 service? To do this, use the filter method. It takes a list of filters where each filter consists of a column name and a regular expression. Each value in that column name is compared to the regular expression and if it matches it is collected and returned with all of the other matches in another Costs object.

>>> ec2 = total.filter([('ProductName', '.*Compute Cloud.*')])
>>> ec2.cost
Decimal('315.88505363')
>>>

So the total cost for EC2 in this account was $315.89. However, if you compare that to your bill you will probably find that it doesn’t match. The reason (probably) is that this number includes all Data Transfer charges incurred as part of the EC2 usage but your monthly bill breaks data transfer out as a separate line item. To break out the data transfer costs:

>>> data_transfer = ec2.filter([('UsageType', '.*DataTransfer.*')])
>>> data_transfer.cost
Decimal('35.45916220')
>>>

So, if you subtract the data transfer costs from the EC2 costs you should see the number on your bill.

Release History

Release History

This version
History Node

0.2.0

History Node

0.1.0

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
details-0.2.0.tar.gz (11.8 kB) Copy SHA256 Checksum SHA256 Source Oct 14, 2014

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