Data extraction from Salesforce with Python

We need a python script that extracts all tables and metadata from our Salesforce CRM organisation, and writes this data to zipped CSV files on Amazon S3. Requirements: 1. Download all data from all Salesforce objects into a CSV file. The selection of files should be filtered using a Regex (positive / negative - to download only a subset of objects) 2. Download all binary data (salesforce attachements) 3. Download all metadata from Salesforce into a CSV file, with the following columns (“meta data column”, “data type”, “possible values”, “description”) 4. Upload the CSV files for data and meta data and the attachments to a directory on S3 bucket Additional Requirements: - AWS SDK for Python is mandatory. - All files on S3 should be zipped using GZip. - Consistency of downloads is important / preferred over parallelization - CSV files should include quotation / escaping of data - Configuration should be done using configfilter (Salesforce OAuth, Bucket name, S3 folder, Regex for object filter) in separate ini file. - Regex for filtering objects will be used to download only files from a specific namespace OR everything except files from a specified namespace (we need to separate HR relevant data which is stored in 2 different SFDC apps - Releco and TargetRecruit)