Metadata-Version: 2.1
Name: aws-databridge
Version: 2.0.1
Summary: An AWS EC2 CLI application that supports XML, TXT, JSON, and CSV imports to various AWS databases.
Home-page: https://github.com/Jaysalgado/aws-databridge
Author: Jay, Aban, Matt
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: boto3 >=1.20.0
Requires-Dist: pandas
Requires-Dist: pymysql
Requires-Dist: lxml

# AWS-DataBridge

AWS-DataBridge is a CLI application designed for AWS EC2 instances that allows users to import data from various file formats (XML, TXT, JSON, CSV) into multiple AWS databases including RDS, DynamoDB, Neptune, and DocumentDB. This tool automates the process of data conversion and storage, ensuring flexibility and ease of use for different database needs.

## Features

- Converts and imports XML, TXT, JSON, and CSV files into AWS databases.
- Supports AWS RDS, DynamoDB, Neptune, and DocumentDB.
- Provides flexibility for users to import data into multiple databases from a single file.
- Automatically creates tables and databases if they do not already exist.

## Installation

### To install AWS DataBridge using pip:

In your Ec2 instance run the following command

```bash
pip3 install -i https://test.pypi.org/simple/ aws-databridge --extra-index-url https://pypi.org/simple
```

## Usage

After the install you can run the following command to run the program

```bash
aws-databridge
```

## Neccessary Environment Setup

There are some neccessary set up requirements in order to use the application without errors for each database

### IAM Role

Make sure your EC2 has the required IAM Role permissions attached to your EC2 instance for each of the databases you are attempting to import to

### RDS env variables

To interact with your RDS instance you need to have the following credentials stored on your EC2

```bash
export RDS_HOST="your-rds-endpoint.rds.amazonaws.com"
export RDS_USER="your-username"
export RDS_PASSWORD="your-password"
export RDS_DB="your-database-name"
export RDS_PORT="3306"
```
### DocumentDB env variables 

To import into DocmunetDB you need to have the following credentials stored on your EC2 
```bash
MONGO_URL = os.getenv('MONGO_URL', 'mongodb://localhost:27017')
MONGO_USERNAME = os.getenv('MONGO_USERNAME', 'default-user')
MONGO_PASSWORD = os.getenv('MONGO_PASSWORD', 'default_password')
MONGO_TLS = os.getenv('MONGO_TLS', 'global-bundle.pem')
```
### Neptune env variables 

To import into Neptune you need to have the following credentials stored on your EC2 
```bash
NEP_ENDPOINT = os.getenv('NEP_ENDPOINT', 'db-neptune-1.cluster-cfsssmgsia9l.us-east-1.neptune.amazonaws.com')
IAM_ROLE_ARN = os.getenv('IAM_ROLE_ARN', 'arn:aws:iam::123456789012:role/NeptuneAccessDev')
IMPORT_BUCKET = os.getenv('IMPORT_BUCKET', 'default-bucket-name')

```

### Data Location

Currently data can be imported from an S3 bucket or from the local EC2 instance. To transfer a file from your machine to the EC2 use the following command:

```bash
rsync -avz --exclude '.venv' -e "ssh -i ~/.ssh/<your pem name>.pem" <path to your code> ec2-user@<ec2 ip>:/home/ec2-user/
```

## Compatibility

This code has been tested and verified to work on the AWS Linux 2023 AMI EC2. Compatibility with other environments or operating systems is not guaranteed.

## Contributing

If you would like to Contribute:

1. Fork the repository
2. Create a new branch (git checkout -b feature-branch).
3. Make your changes and commit (git commit -m 'Add new feature').
4. Push your changes (git push origin feature-branch).
5. Open a pull request.

Also feel free to open an issue if you spot any problems with the program!

## License

This project is licensed under the MIT License.
