semvec/pypi-packages huggingface dataset:
blobhub 0.1.5
BlobHub Python SDK
License: MIT
Keywords: blobhub,data,onnx,git,graph

# BlobHub Python SDK 

## Overview 

BlobHub is a service offering versioned storage of structured data.     

**BlobHub SDK** provides developers with convenient access to the functionality of **BlobHub** platform.

## BlobHub Portal 

### Registration 

Free [BlobHub](https://blobhub.io/) account needs to be created in order to make use of the SDK.

Follow these steps to get started with **BlobHub**:
 
  1. Create free BlobHub account at:  
     [https://blobhub.io/](https://blobhub.io/)
  2. Create new organization to store your blobs:   
     [https://blobhub.io/p/me/org/create](https://blobhub.io/p/me/org/create)
  3. Create blob of desired type (see the section on **Presets** library below for examples).      
  4. Under blob's Settings create API key with **write** access to the blob. 
  
### Access Control   

Some of the principles in the foundation of **BlobHub** access model: 

  - Blob (and organization holding it) can remain **private** until it is ready to be exposed for public consumption. 
  - Private Blobs can be shared with **BlobHub** members directly.   
  - API keys provide ability to enable mutable access to blob data (via API and SDK).   

### Blob Types

Blob type defines the structure of the data stored within the blob.
It also determines the set of available operations.  

The following blob types are supported at the moment:

  - **ONNX Model**   
    Provides storage of deep neural network computational graphs in [ONNX](https://onnx.ai/) format. 

## Installation 

To install, use:

```bash
pip install blobhub
``` 

## Usage

### Authentication

Use the following snippet to get access to the blob:

```python
from blobhub.blob import Blob, Revision

blob = Blob(
    org_id="<< organization alias or id >>", 
    blob_id="<< blob alias or id >>", 
    api_key="<< API key from blob settings >>")
revision = blob.revisions.latest()
assert blob[Blob.FIELD_STATUS] == Blob.STATUS_READY
assert revision[Revision.FIELD_STATUS] == Revision.STATUS_READY
assert revision[Revision.FIELD_PHASE] == Revision.PHASE_DRAFT
```

## Presets Library 

Presets library is created to simplify operating with blobs of various types (ONNX, OrientDB Graph, etc.). 

### ONNX Module 

**ONNX Model** blobs are designed to store deep neural network models exported in [ONNX](https://onnx.ai/) format. 

Follow these steps to make use of the module: 

  - Initialize preset:

```python
from blobhub.presets.onnx import Onnx, Model

onnx = Onnx(revision=revision)
``` 

  - Upload local model:  

```python
local_model = Model.from_local_file(onnx=onnx, path="/path/to/local/model.onnx")
success = onnx.upload(model=local_model)
assert True == success
```

  - Download model:  

```python
downloaded_model = onnx.download()
assert None != downloaded_model
```

  - (Optional) Confirm that downloaded model is identical to the original one: 

```python
assert downloaded_model.is_identical(model=local_model)
```