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Python Driver for ArangoDB

Project description

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Welcome to the GitHub page for python-arango, a Python driver for ArangoDB.

Announcements

  • Python-arango version 4.0.0 is now out!

  • Please see the releases page for details on latest updates.

Features

  • Clean Pythonic interface.

  • Lightweight.

  • High ArangoDB REST API coverage.

Compatibility

  • Python versions 2.7, 3.4, 3.5 and 3.6 are supported.

  • Python-arango 4.x supports ArangoDB 3.3+ (recommended).

  • Python-arango 3.x supports ArangoDB 3.0 ~ 3.2 only.

  • Python-arango 2.x supports ArangoDB 1.x ~ 2.x only.

Installation

To install a stable version from PyPi:

~$ pip install python-arango

To install the latest version directly from GitHub:

~$ pip install -e git+git@github.com:joowani/python-arango.git@master#egg=python-arango

You may need to use sudo depending on your environment.

Getting Started

Here is a simple usage example:

from arango import ArangoClient

# Initialize the client for ArangoDB.
client = ArangoClient(protocol='http', host='localhost', port=8529)

# Connect to "_system" database as root user.
sys_db = client.db('_system', username='root', password='passwd')

# Create a new database named "test".
sys_db.create_database('test')

# Connect to "test" database as root user.
db = client.db('test', username='root', password='passwd')

# Create a new collection named "students".
students = db.create_collection('students')

# Add a hash index to the collection.
students.add_hash_index(fields=['name'], unique=True)

# Insert new documents into the collection.
students.insert({'name': 'jane', 'age': 39})
students.insert({'name': 'josh', 'age': 18})
students.insert({'name': 'judy', 'age': 21})

# Execute an AQL query and iterate through the result cursor.
cursor = db.aql.execute('FOR doc IN students RETURN doc')
student_names = [document['name'] for document in cursor]

Here is another example with graphs:

from arango import ArangoClient

# Initialize the client for ArangoDB.
client = ArangoClient(protocol='http', host='localhost', port=8529)

# Connect to "test" database as root user.
db = client.db('test', username='root', password='passwd')

# Create a new graph named "school".
graph = db.create_graph('school')

# Create vertex collections for the graph.
students = graph.create_vertex_collection('students')
lectures = graph.create_vertex_collection('lectures')

# Create an edge definition (relation) for the graph.
register = graph.create_edge_definition(
    edge_collection='register',
    from_vertex_collections=['students'],
    to_vertex_collections=['lectures']
)

# Insert vertex documents into "students" (from) vertex collection.
students.insert({'_key': '01', 'full_name': 'Anna Smith'})
students.insert({'_key': '02', 'full_name': 'Jake Clark'})
students.insert({'_key': '03', 'full_name': 'Lisa Jones'})

# Insert vertex documents into "lectures" (to) vertex collection.
lectures.insert({'_key': 'MAT101', 'title': 'Calculus'})
lectures.insert({'_key': 'STA101', 'title': 'Statistics'})
lectures.insert({'_key': 'CSC101', 'title': 'Algorithms'})

# Insert edge documents into "register" edge collection.
register.insert({'_from': 'students/01', '_to': 'lectures/MAT101'})
register.insert({'_from': 'students/01', '_to': 'lectures/STA101'})
register.insert({'_from': 'students/01', '_to': 'lectures/CSC101'})
register.insert({'_from': 'students/02', '_to': 'lectures/MAT101'})
register.insert({'_from': 'students/02', '_to': 'lectures/STA101'})
register.insert({'_from': 'students/03', '_to': 'lectures/CSC101'})

# Traverse the graph in outbound direction, breadth-first.
result = graph.traverse(
    start_vertex='students/01',
    direction='outbound',
    strategy='breadthfirst'
)

Check out the documentation for more details.

Contributing

Please take a look at this page before submitting a pull request. Thanks!

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