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https://github.com/vmware-archive/py-gemfire-rest

Python client for Gemfire's REST service.
https://github.com/vmware-archive/py-gemfire-rest

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Python client for Gemfire's REST service.

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README 

        
# py-gemfire-rest

=================



This library enables your python applications to use GemFire as a datastore. (GemFire is a distributed key-value store. A short tutorial can be found at http://goo.gl/rF93fn). This library exposes Spring's CrudRepository like methods in an effort to simplify GemFire's APIs while still giving access to advanced GemFire features (details below). 



## Installation

---------------



Using pip installation is simple

```

    $ sudo pip install gemfire-rest

```

or from source:

```

    $ sudo python setup.py install

```

## Quick Start

--------------



1. Start the GemFire REST service by [following the instructions](http://gemfire.docs.pivotal.io/docs-gemfire/latest/rest_apps/setup_config.html)

2. Create a Region on the server (Region is a distributed ConcurrentMap in which GemFire stores the data). 

```

    gfsh>create region --name=orders --type=PARTITION

```

3. 

```python

    >>> from gemfire import *

    >>> client = GemfireClient.GemfireClient(hostname="localhost", port=8080)

    >>> myRepo = client.create_repository("orders")

    >>> myRepo.save(order)

```



where the order object has an "id" instance variable. The library handles converting the object to/from json. 



## API Reference

----------------



This library exercises [GemFire's REST APIs](http://gemfire.docs.pivotal.io/docs-gemfire/latest/rest_apps/book_intro.html) for enabling your python application to use GemFire as its datastore. To get started, we create a client by providing a hostname and port for an already running endpoint. 

```python

    client = GemfireClient(hostname="localhost", port=8080, user="gfadmin", password="password")

```



For each type of Object that we want to store in GemFire, we create a repository (Please not that you will have to create a Region on the server with the same name as the repository).

```python

    orders = client.create_repository("orders")

```

The client provides a method to look up all the Regions that have been created on the server already:

```python

    client.list_all_regions()

```



GemfireClient also has methods for querying and function execution which we will see later.



### Repository

--------------



Just like Spring's CrudRepository interface, the following methods are available on the Repository

```python

    save(entities)   #saves one or more entities in GemFire

    find(ids)        #finds entities with the given ids

    find_all()       #returns all data in region

    exists(id)       #checks to see if an entity with the given id exists

    delete(entities) #deletes the given entities from GemFire

    delete_all()     #deletes all data in the GemFire region

```



As the naming suggests, intention of these methods is pretty clear. One thing that needs to be highlighted here is that all entities need an identity; this library uses "id" instance variable as identity. So all entities that are stored in GemFire need to have an instance variable named "id".



### Region

----------



For advanced operations, we also provide access to Region, which defines the following methods:

```python

    create(key, value)  #will insert only if key does not exists

    update(key, value)  #will update only if the key exists

    keys()              # returns all keys in the region

    compare_and_set(key, oldvalue, newvalue) #sets the key to newvalue only if current value is equal ot oldvalue

```



### Querying

------------

GemfireClient provides API for running ad-hoc [OQL queries](http://gemfire.docs.pivotal.io/docs-gemfire/latest/developing/querying_basics/chapter_overview.html) on the server.

```python

    adhoc_query(query_string)  #OQL query string

```



For faster performance, you will want to run prepared OQL queries. GemfireClient provides the following APIs for this:

```python

    new_query(query_id, query_string) #registers and prepares the OQL query on the server

    run_query(query_id, query_args)   #runs the query with specified parameters 

```