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Boilerplate done, working with s3 on Openstack. Preliminary README done

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README.md
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# LAB-S3 # LAB-S3
Here's the updated README to include instructions for using `boto3` to interact with AWS S3 and to connect to an OpenStack Object Storage:
---
## Getting started # Python CLI for S3 and OpenStack Object Storage
To make it easy for you to get started with GitLab, here's a list of recommended next steps. This tutorial guides you through the installation and usage of the `boto3` SDK for AWS S3 interactions and demonstrates how to connect to OpenStack Object Storage using the OpenStack Python SDK.
Already a pro? Just edit this README.md and make it your own. Want to make it easy? [Use the template at the bottom](#editing-this-readme)! ## Installation
## Add your files
- [ ] [Create](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#create-a-file) or [upload](https://docs.gitlab.com/ee/user/project/repository/web_editor.html#upload-a-file) files First, install the required SDKs using `pip`:
- [ ] [Add files using the command line](https://docs.gitlab.com/ee/gitlab-basics/add-file.html#add-a-file-using-the-command-line) or push an existing Git repository with the following command:
``` ```bash
cd existing_repo pip install boto3 openstacksdk
git remote add origin https://gitedu.hesge.ch/lsds/teaching/bachelor/cloud-and-deployment/lab-s3.git
git branch -M main
git push -uf origin main
``` ```
## Integrate with your tools This command installs both `boto3` for AWS services and `openstacksdk` for interacting with OpenStack.
- [ ] [Set up project integrations](https://gitedu.hesge.ch/lsds/teaching/bachelor/cloud-and-deployment/lab-s3/-/settings/integrations) ## Using `boto3` for S3 Operations
## Collaborate with your team ### Setting Up AWS Credentials
- [ ] [Invite team members and collaborators](https://docs.gitlab.com/ee/user/project/members/) Before using `boto3`, you need to configure your AWS credentials. This can be done by creating a configuration file or using environment variables.
- [ ] [Create a new merge request](https://docs.gitlab.com/ee/user/project/merge_requests/creating_merge_requests.html)
- [ ] [Automatically close issues from merge requests](https://docs.gitlab.com/ee/user/project/issues/managing_issues.html#closing-issues-automatically)
- [ ] [Enable merge request approvals](https://docs.gitlab.com/ee/user/project/merge_requests/approvals/)
- [ ] [Set auto-merge](https://docs.gitlab.com/ee/user/project/merge_requests/merge_when_pipeline_succeeds.html)
## Test and Deploy In your local CLI, run the following command:
Use the built-in continuous integration in GitLab. ```bash
openstack --os-cloud=engines creadential list
```
- [ ] [Get started with GitLab CI/CD](https://docs.gitlab.com/ee/ci/quick_start/index.html) You should see a table with 5 columns. Under the column `Data`, there should be a JSON with `access`, `secret`, and `trust_id`
- [ ] [Analyze your code for known vulnerabilities with Static Application Security Testing (SAST)](https://docs.gitlab.com/ee/user/application_security/sast/)
- [ ] [Deploy to Kubernetes, Amazon EC2, or Amazon ECS using Auto Deploy](https://docs.gitlab.com/ee/topics/autodevops/requirements.html)
- [ ] [Use pull-based deployments for improved Kubernetes management](https://docs.gitlab.com/ee/user/clusters/agent/)
- [ ] [Set up protected environments](https://docs.gitlab.com/ee/ci/environments/protected_environments.html)
*** Replace `<YOUR_ACCESS_KEY_ID>` with the key after `access` and `<YOUR_SECRET_ACCESS_KEY>` with the key after `secret`.
# Editing this README If you don't have any keys, you can create one by doing:
```bash
openstack --os-cloud=engines ec2 creadential create
```
When you're ready to make this README your own, just edit this file and use the handy template below (or feel free to structure it however you want - this is just a starting point!). Thanks to [makeareadme.com](https://www.makeareadme.com/) for this template. ### Connecting to S3 and Performing Operations
## Suggestions for a good README Once the credentials are configured, you can use `boto3` to interact with S3. Here's how you can create an S3 client and perform common operations:
Every project is different, so consider which of these sections apply to yours. The sections used in the template are suggestions for most open source projects. Also keep in mind that while a README can be too long and detailed, too long is better than too short. If you think your README is too long, consider utilizing another form of documentation rather than cutting out information. #### Creating an S3 Client
## Name ```python
Choose a self-explaining name for your project. import boto3
## Description # Create an S3 client
Let people know what your project can do specifically. Provide context and add a link to any reference visitors might be unfamiliar with. A list of Features or a Background subsection can also be added here. If there are alternatives to your project, this is a good place to list differentiating factors. s3_client = boto3.client('s3')
```
## Badges #### Creating an S3 Bucket
On some READMEs, you may see small images that convey metadata, such as whether or not all the tests are passing for the project. You can use Shields to add some to your README. Many services also have instructions for adding a badge.
## Visuals ```python
Depending on what you are making, it can be a good idea to include screenshots or even a video (you'll frequently see GIFs rather than actual videos). Tools like ttygif can help, but check out Asciinema for a more sophisticated method. bucket_name = 'your-bucket-name'
s3_client.create_bucket(Bucket=bucket_name)
print(f"Bucket '{bucket_name}' created successfully.")
```
## Installation #### Listing Buckets
Within a particular ecosystem, there may be a common way of installing things, such as using Yarn, NuGet, or Homebrew. However, consider the possibility that whoever is reading your README is a novice and would like more guidance. Listing specific steps helps remove ambiguity and gets people to using your project as quickly as possible. If it only runs in a specific context like a particular programming language version or operating system or has dependencies that have to be installed manually, also add a Requirements subsection.
```python
response = s3_client.list_buckets()
buckets = [bucket['Name'] for bucket in response['Buckets']]
print(f"Buckets: {buckets}")
```
## Usage #### Uploading a File to S3
Use examples liberally, and show the expected output if you can. It's helpful to have inline the smallest example of usage that you can demonstrate, while providing links to more sophisticated examples if they are too long to reasonably include in the README.
## Support ```python
Tell people where they can go to for help. It can be any combination of an issue tracker, a chat room, an email address, etc. file_name = 'path/to/your/file.txt'
object_name = 'file.txt'
bucket_name = 'your-bucket-name'
## Roadmap s3_client.upload_file(file_name, bucket_name, object_name)
If you have ideas for releases in the future, it is a good idea to list them in the README. print(f"File '{file_name}' uploaded to bucket '{bucket_name}' as '{object_name}'.")
```
#### Deleting an S3 Bucket
## Contributing ```python
State if you are open to contributions and what your requirements are for accepting them. bucket_name = 'your-bucket-name'
s3_client.delete_bucket(Bucket=bucket_name)
print(f"Bucket '{bucket_name}' deleted successfully.")
```
For people who want to make changes to your project, it's helpful to have some documentation on how to get started. Perhaps there is a script that they should run or some environment variables that they need to set. Make these steps explicit. These instructions could also be useful to your future self. For more information on `boto3` and the various S3 operations, refer to the [boto3 documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/index.html).
You can also document commands to lint the code or run tests. These steps help to ensure high code quality and reduce the likelihood that the changes inadvertently break something. Having instructions for running tests is especially helpful if it requires external setup, such as starting a Selenium server for testing in a browser.
## Authors and acknowledgment ## Summary
Show your appreciation to those who have contributed to the project.
## License With this guide, you can now use `boto3` to manage AWS S3 storage to connect to and manage resources in an OpenStack Object Storage environment. Both SDKs provide powerful ways to automate and streamline cloud storage tasks.
For open source projects, say how it is licensed.
## Project status
If you have run out of energy or time for your project, put a note at the top of the README saying that development has slowed down or stopped completely. Someone may choose to fork your project or volunteer to step in as a maintainer or owner, allowing your project to keep going. You can also make an explicit request for maintainers.
lab-s3.py 0 → 100644
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#!/usr/bin/env python3
import logging
import sys
import boto3
from botocore.exceptions import NoCredentialsError, ClientError
# Setup logging configuration
def setup_logging():
logger = logging.getLogger("lab-s3-cli")
# Log format
log_format = "[%(asctime)s] %(levelname)s: %(message)s"
# Setting log level to DEBUG, this can be changed to INFO, WARNING, ERROR, or CRITICAL as needed
logger.setLevel(logging.DEBUG)
# Create a stream handler to output logs to console
handler = logging.StreamHandler(sys.stdout)
handler.setLevel(logging.DEBUG)
handler.setFormatter(logging.Formatter(log_format))
# Add handler to logger
logger.addHandler(handler)
return logger
# Initialize the logger
logger = setup_logging()
# Initialize the S3 client
session = boto3.session.Session()
client = session.client(
service_name='s3',
aws_access_key_id='<YOUR ACCESS KEY>',
aws_secret_access_key='<YOUR SECRET KEY>',
endpoint_url='https://os.zhdk.cloud.switch.ch'
)
# Example function to create an S3 bucket
def create_bucket(bucket_name):
logger.info(f"Creating a new S3 bucket: {bucket_name}...")
try:
# FINISH THIS CODE
logger.debug(f"Bucket {bucket_name} created successfully.")
except ClientError as e:
logger.error(f"Failed to create bucket: {e}")
# Example function to list S3 buckets
def list_buckets():
logger.info("Listing all S3 buckets...")
try:
# FINISH THIS CODE
logger.debug(f"Buckets: {buckets}")
return buckets
except ClientError as e:
logger.error(f"Failed to list buckets: {e}")
# Example function to list contents of s3 bucket
def list_bucket_contents(bucket_name):
logger.info(f"Listing contents of bucket: {bucket_name}")
try:
# Retrieve the list of objects in the specified bucket
# FINISH THIS CODE
# Check if the bucket contains any objects
if 'Contents' in response:
print(f"Contents of bucket '{bucket_name}':")
for obj in response['Contents']:
print(f" - {obj['Key']}")
else:
print(f"Bucket '{bucket_name}' is empty.")
except ClientError as e:
print(f"Error: {e}")
# Example function to upload a file to an S3 bucket
def upload_file(bucket_name, file_name, object_name=None):
if object_name is None:
object_name = file_name
logger.info(f"Uploading {file_name} to bucket {bucket_name}...")
try:
# FINISH THIS CODE
logger.debug(f"File {file_name} uploaded as {object_name} in bucket {bucket_name}.")
except FileNotFoundError:
logger.error(f"The file {file_name} was not found.")
except NoCredentialsError:
logger.error("Credentials not available.")
except ClientError as e:
logger.error(f"Failed to upload file: {e}")
# Example function to download a file to an S3 bucket
def download(bucket_name, object_name, file_name=None):
# object_name - name of the file to download
# file_name - name of the file in your local machine
# If no file name is provided, use the object name as the file name
if file_name is None:
file_name = object_name
logger.info(f"Uploading {file_name} to bucket {bucket_name}...")
try:
# FINISH THIS CODE
logger.debug(f"Object {object_name} in bucket {bucket_name} downloaded as {file_name} .")
except FileNotFoundError:
logger.error(f"The file {file_name} was not found.")
except NoCredentialsError:
logger.error("Credentials not available.")
except ClientError as e:
logger.error(f"Failed to upload file: {e}")
# Example function to delete an S3 bucket
def delete_bucket(bucket_name):
logger.info(f"Deleting S3 bucket: {bucket_name}...")
try:
# FINISH THIS CODE
logger.debug(f"Bucket {bucket_name} deleted successfully.")
except ClientError as e:
logger.error(f"Failed to delete bucket: {e}")
# Example function to delete an object in an S3 bucket
def delete_object(bucket_name, object_name):
logger.info(f"Deleting object {object_name} from bucket {bucket_name}...")
try:
# FINISH THIS CODE
logger.debug(f"Object {object_name} deleted successfully from bucket {bucket_name}.")
except ClientError as e:
logger.error(f"Failed to delete object: {e}")
# Main function to simulate command-line arguments
if __name__ == "__main__":
if len(sys.argv) < 2:
logger.error("No command provided. Use 'create-bucket', 'list-buckets', 'upload', 'delete-bucket', or 'delete-object'.")
sys.exit(1)
command = sys.argv[1]
if command == "create-bucket":
if len(sys.argv) < 3:
logger.error("Please provide a bucket name to create.")
sys.exit(1)
bucket_name = sys.argv[2]
create_bucket(bucket_name)
elif command == "list-buckets":
buckets = list_buckets()
logger.info(f"Buckets: {buckets}")
elif command == "upload":
if len(sys.argv) < 4:
logger.error("Please provide a bucket name and file name to upload.")
sys.exit(1)
bucket_name = sys.argv[2]
file_name = sys.argv[3]
object_name = sys.argv[4]
upload_file(bucket_name, file_name, object_name)
elif command == "download":
if len(sys.argv) < 4:
logger.error("Please provide a bucket name and file name to upload.")
sys.exit(1)
bucket_name = sys.argv[2]
object_name = sys.argv[3]
file_name = sys.argv[4]
download(bucket_name, object_name, file_name)
elif command == "list-bucket-content":
if len(sys.argv) < 3:
logger.error("Please provide a bucket name to list.")
sys.exit(1)
bucket_name = sys.argv[2]
list_bucket_contents(bucket_name)
elif command == "delete-bucket":
if len(sys.argv) < 3:
logger.error("Please provide a bucket name to delete.")
sys.exit(1)
bucket_name = sys.argv[2]
delete_bucket(bucket_name)
elif command == "delete-object":
if len(sys.argv) < 4:
logger.error("Please provide a bucket name and object name to delete.")
sys.exit(1)
bucket_name = sys.argv[2]
object_name = sys.argv[3]
delete_object(bucket_name, object_name)
else:
logger.error(f"Unknown command: {command}. Use 'create-bucket', 'list-buckets', 'upload', 'delete-bucket', or 'delete-object'.")
sys.exit(1)
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