bx 0.3.0

Simple in-memory storage for Python

# Bx

In-memory storage for Python


---

```
__
___~~~` `~~__
___~~~ `~~_
|~_ `~_
| ~_ ___ ~~ |
| ~_ __~~~ |
| ~_ __~~~ |
| | |
| | |
| | bx |
~_ | __|
~_ | __~~~
~_ | __~~~
~|__~~~
```

bx lets you store things in memory. It has a few special features:

* Thread safe
* Setting a timeout before object is destroyed
* JSON Schema validation
* Clean & simple API
* Badass ASCII art
* Supports Python 2.7 and 3.4

## Installation

Just make sure you have Python 2.7.x or 3.4.x and pip installed:

```bash
$ pip install bx
```

## Usage

The code is pretty simple and well-commented, but here's some example usage. If
you want more detail, run `pydoc bx.Db` once you've installed it or look through
the code to get info.

```python
import bx

student = {
'title': 'student',
'type': 'object',
'required': ['name', 'major', 'gpa'],
'properties': {
'name': {
'type': 'string'
},
'major': {
'type': 'string'
},
'gpa': {
'type': 'number'
}
}
}

# The schema argument defaults to None, and there is also an optional
# debug mode (for console logging) that defaults to False
db = bx.Db(schema=student)

try:
db.put('bad', 'data')
except bx.db.ValidationError: # same as jsonschema.exceptions.ValidationError
print('This does not fit the schema!')

john = {
'name': 'John Doe',
'major': 'Computer Science',
'gpa': 3.6
}

susan = {
'name': 'Susan Jones',
'major': 'Physics',
'gpa': 3.96
}

db.put('john', john)
db.put('susan', susan)

# get average gpa
print(sum([v['gpa'] for v in db.vals()]) / len(db.vals()))

db.delete('susan')

try:
db.delete('bob')
except KeyError:
print('bob is not in the data store!')
```