Metadata-Version: 1.1
Name: datacoco-cloud
Version: 0.1.19
Summary: Data common code for AWS Cloud Services by Equinox
Home-page: https://github.com/equinoxfitness/datacoco-cloud
Author: Equinox Fitness
Author-email: UNKNOWN
License: MIT
Description: datacoco-cloud
        =================
        
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        Datacoco-cloud contains interaction classes S3, Athena, SES, SNS, SQS, ECS, EMR, Cloudwatch logs
        
        Installation
        ------------
        
        datacoco-cloud requires Python 3.6+
        
        ::
        
            python3 -m venv <virtual env name>
            source <virtual env name>/bin/activate
            pip install datacoco-cloud
        
        Usage
        ~~~~~
        
        S3toS3Interaction
        ^^^^^^^^^^^^^^^^^
        
        Please take note that all AWS Permissions in `IAM` and `Bucket Policies` need to be properly in place for this utility to work.
        `Click here for more details <https://aws.amazon.com/premiumsupport/knowledge-center/cross-account-access-s3/>`_.
        
        Sample Code
        """""""""""
        
        ::
        
            # Import the class first
            from datacococloud.s3_to_s3_interaction import S3toS3Interaction
            
            # Instantiate with your key pairs
            s3toS3 = S3toS3Interaction(<source_aws_key>,
                                       <source_aws_secret>,
                                       <target_aws_key>,
                                       <target_aws_secret>,
                                       <source_aws_region>(optional default='us-east-1'),
                                       <target_aws_region>(optional default='us-east-1')
                                       )
        
            # Copying the files
            s3toS3.duplicate_objects(<source_bucket>,
                                     <target_bucket>,
                                     <source_bucket_prefix>,
                                     <target_path>,
                                     <source_bucket_suffix>(optional default=''))
        
        
            # Moving the files
            # This deletes the file from the source after copying to the target
            s3toS3.move_objects(<source_bucket>,
                                     <target_bucket>,
                                     <source_bucket_prefix>,
                                     <target_path>,
                                     <source_bucket_suffix>(optional default=''))
        
        Terms
        """""
        * ``source_aws_key`` - AWS key ID from source account
        * ``source_aws_secret`` - AWS key secret from source account
        * ``target_aws_key`` - AWS key ID from target account
        * ``target_aws_secret`` - AWS key secret from target account
        * ``source_aws_region`` - AWS region of the source `S3` bucket 
        * ``target_aws_region`` - AWS region of the source `S3` bucket
        
        * ``source_bucket`` - S3 bucket of the source file
        * ``target_bucket`` - S3 bucket where the files are going to be transferred
        * ``source_bucket_prefix`` - The prefix of the files to transfer from the source
            `Note:` Add ``/`` at the end to specify a folder e.g (`files/`)
        * ``target_path`` - the Path at the target bucket where the files will be transferred
            `Note:` if the the folder does not exist, it will auto create it for you
        * ``source_bucket_prefix`` - The suffix of the files to transfer from the source
        
        
        
        
        
        
        Quickstart
        ----------
        
        ::
        
            python3 -m venv <virtual env name>
            source <virtual env name>/bin/activate
            pip install --upgrade pip
            pip install -r requirements_dev.txt
        
        
        Development
        -----------
        
        Getting Started
        ~~~~~~~~~~~~~~~
        
        It is recommended to use the steps below to set up a virtual environment for development:
        
        ::
        
            python3 -m venv <virtual env name>
            source <virtual env name>/bin/activate
            pip install -r requirements.txt
        
        Testing
        ~~~~~~~
        
        ::
        
            pip install -r requirements_dev.txt
        
        To run the testing suite, simply run the command: ``tox`` or ``python -m unittest discover tests``
        
        
        
        Contributing
        ------------
        
        Contributions to datacoco\_cloud are welcome!
        
        Please reference guidelines to help with setting up your development
        environment
        `here <https://github.com/equinoxfitness/datacoco-cloud/blob/master/CONTRIBUTING.rst>`__.
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Natural Language :: English
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.6
