cshelve 1.0.0

Propulsing the shelve module to the cloud

Cloud Shelve

Cloud Shelve (cshelve) is a Python package that provides a seamless way to store and manage data in the cloud using the familiar Python Shelve interface. It is designed for efficient and scalable storage solutions, allowing you to leverage cloud providers for persistent storage while keeping the simplicity of the shelve API.

Installation

Install cshelve via pip:

pip install cshelve # For testing purposes
pip install cshelve[azure-blob]  # For Azure Blob Storage

Usage

The cshelve module provides a simple key-value interface for storing data in the cloud.

Quick Start Example

Here is a quick example demonstrating how to store and retrieve data using cshelve:

import cshelve

# Open a local database file
d = cshelve.open('local.db')

# Store data
d['my_key'] = 'my_data'

# Retrieve data
print(d['my_key'])  # Output: my_data

# Close the database
d.close()

Cloud Storage Example (e.g., Azure)

To configure remote cloud storage, you need to provide an INI file containing your cloud provider's configuration. The file should have a .ini extension. Remote storage also requires the installation of optional dependencies for the cloud provider you want to use.

Example Azure Blob Configuration

First, install the Azure Blob Storage provider:

pip install cshelve[azure-blob]

Then, create an INI file with the following configuration:

$ cat azure-blob.ini
[default]
provider        = azure-blob
account_url     = https://myaccount.blob.core.windows.net
auth_type       = passwordless
container_name  = mycontainer

Once the INI file is ready, you can interact with remote storage the same way as with local storage. Here's an example using Azure:

import cshelve

# Open using the remote storage configuration
d = cshelve.open('azure-blob.ini')

# Store data
d['my_key'] = 'my_data'

# Retrieve data
print(d['my_key'])  # Output: my_data

# Close the connection to the remote storage
d.close()

Advanced Scenario: Storing DataFrames in the Cloud

In this advanced example, we will demonstrate how to store and retrieve a Pandas DataFrame using cshelve with Azure Blob Storage.

First, install the required dependencies:

pip install cshelve[azure-blob] pandas

Create an INI file with the Azure Blob Storage configuration:

$ cat azure-blob.ini
[default]
provider        = azure-blob
account_url     = https://myaccount.blob.core.windows.net
auth_type       = passwordless
container_name  = mycontainer

Here's the code to store and retrieve a DataFrame:

import cshelve
import pandas as pd

# Create a sample DataFrame
df = pd.DataFrame({
    'name': ['Alice', 'Bob', 'Charlie'],
    'age': [25, 30, 35],
    'city': ['New York', 'Los Angeles', 'Chicago']
})

# Open the remote storage using the Azure Blob configuration
with cshelve.open('azure-blob.ini') as db:
    # Store the DataFrame
    db['my_dataframe'] = df

# Retrieve the DataFrame
with cshelve.open('azure-blob.ini') as db:
    retrieved_df = db['my_dataframe']

print(retrieved_df)

More configuration examples for other cloud providers can be found here.

Providers configuration

In Memory

Provider: in-memory Installation: No additional installation required.

The In-Memory provider uses an in-memory data structure to simulate storage. This is useful for testing and development purposes.

Option	Description	Required	Default Value
persist-key	If set, its value will be conserved and reused during the program execution.	:x:	None
exists	If True, the database exists; otherwise, it will be created.	:x:	False

Azure Blob

Provider: azure-blob Installation: pip install cshelve[azure-blob]

The Azure provider uses Azure Blob Storage as remote storage. The module considers the provided container as dedicated to the application. The impact might be significant. For example, if the flag n is provided to the open function, the entire container will be purged, aligning with the official interface.

Option	Description	Required	Default Value
account_url	The URL of your Azure storage account.	:x:
auth_type	The authentication method to use: access_key, passwordless, connection_string or anonymous.	:white_check_mark:
container_name	The name of the container in your Azure storage account.	:white_check_mark:

Depending on the open flag, the permissions required by cshelve for blob storage vary.

Flag	Description	Permissions Needed
r	Open an existing blob storage container for reading only.	Storage Blob Data Reader
w	Open an existing blob storage container for reading and writing.	Storage Blob Data Contributor
c	Open a blob storage container for reading and writing, creating it if it doesn't exist.	Storage Blob Data Contributor
n	Purge the blob storage container before using it.	Storage Blob Data Contributor

Authentication type supported:

Auth Type	Description	Advantage	Disadvantage	Example Configuration
Access Key	Uses an Access Key or a Shared Access Signature for authentication.	Fast startup as no additional credential retrieval is needed.	Credentials need to be securely managed and provided.	Example
Anonymous	No authentication for anonymous access on public blob storage.	No configuration or credentials needed.	Read-only access.	Example
Connection String	Uses a connection string for authentication. Credentials are provided directly in the string.	Fast startup as no additional credential retrieval is needed.	Credentials need to be securely managed and provided.	Example
Passwordless	Uses passwordless authentication methods such as Managed Identity.	Recommended for better security and easier credential management.	May impact startup time due to the need to retrieve authentication credentials.	Example

Contributing

We welcome contributions from the community! Have a look at our issues.

License

This project is licensed under the MIT License. See the LICENSE file for more details.

Contact

If you have any questions, issues, or feedback, feel free to open an issue.