datajunction 0.0.1a47

DataJunction client library for connecting to a DataJunction server

DataJunction Python Client

This is a short introduction into the Python version of the DataJunction (DJ) client. For a full comprehensive intro into the DJ functionality please check out datajunction.io.

Installation

To install:

pip install datajunction

Intro

We have three top level client classes that help you choose the right path for your DataJunction actions.

1. DJClient for basic read only access to metrics, dimensions, SQL and data.
2. DJBuilder for those who would like to modify their DJ data model, build new nodes and/or modify the existing ones.
3. DJAdmin for the administrators of the system to define the connections to your data catalog and engines.

DJ Client : Basic Access

Here you can see how to access and use the most common DataJunction features.

Examples

To initialize the client:

from datajunction import DJClient

dj = DJClient("http://localhost:8000")

NOTE If you are running in our demo docker environment please change the above URL to "http://dj:8000".

You are now connected to your DJ service and you can start looking around. Let's see what namespaces we have in the system:

dj.list_namespaces()

['default']

Next let's see what metrics and dimensions exist in the default namespace:

dj.list_metrics(namespace="default")

['default.num_repair_orders',
 'default.avg_repair_price',
 'default.total_repair_cost',
 'default.avg_length_of_employment',
 'default.total_repair_order_discounts',
 'default.avg_repair_order_discounts',
 'default.avg_time_to_dispatch']

dj.list_dimensions(namespace="default")

['default.date_dim',
 'default.repair_order',
 'default.contractor',
 'default.hard_hat',
 'default.local_hard_hats',
 'default.us_state',
 'default.dispatcher',
 'default.municipality_dim']

Now let's pick two metrics and see what dimensions they have in common:

dj.common_dimensions(
  metrics=["default.num_repair_orders", "default.total_repair_order_discounts"],
  name_only=True
)

['default.dispatcher.company_name',
 'default.dispatcher.dispatcher_id',
 'default.dispatcher.phone',
 'default.hard_hat.address',
 'default.hard_hat.birth_date',
 'default.hard_hat.city',
 ...

And finally let's ask DJ to show us some data for these metrics and some dimensions:

dj.data(
    metrics=["default.num_repair_orders", "default.total_repair_order_discounts"],
    dimensions=["default.hard_hat.city"]
)

| default_DOT_num_repair_orders	| default_DOT_total_repair_order_discounts | city        |
| ----------------------------- | ---------------------------------------- | ----------- |
| 4                             |                              5475.110138 | Jersey City |
| 3                             |                             11483.300049 | Billerica   |
| 5	                            |                              6725.170074 | Southgate   |
...

Reference

List of all available DJ client methods:

• DJClient:

  list

  • list_namespaces( prefix: Optional[str])

  • list_dimensions( namespace: Optional[str])

  • list_metrics( namespace: Optional[str])

  • list_cubes( namespace: Optional[str])

  • list_sources( namespace: Optional[str])

  • list_transforms( namespace: Optional[str])

  • list_nodes( namespace: Optional[str], type_: Optional[NodeType])

  • list_nodes_with_tags( tag_names: List[str], node_type: Optional[NodeType])

  • list_catalogs()

  • list_engines()

  find

  • common_dimensions( metrics: List[str], name_only: bool = False)
  • common_metrics( dimensions: List[str], name_only: bool = False)

  execute

  • sql( metrics: List[str], dimensions: Optional[List[str]], filters: Optional[List[str]], engine_name: Optional[str], engine_version: Optional[str])
  • data( metrics: List[str], dimensions: Optional[List[str]], filters: Optional[List[str]], engine_name: Optional[str], engine_version: Optional[str], async_: bool = True)

DJ Builder : Data Modelling

In this section we'll show you few examples to modify the DJ data model and its nodes.

Start Here

To initialize the DJ builder:

from datajunction import DJBuilder

djbuilder = DJBuilder("http://localhost:8000")

NOTE If you are running in our demo docker container please change the above URL to "http://dj:8000".

Namespaces

To access a namespace or check if it exists you can use the same simple call:

djbuilder.namespace("default")

Namespace(dj_client=..., namespace='default')

djbuilder.namespace("foo")

[DJClientException]: Namespace `foo` does not exist.

To create a namespace:

djbuilder.create_namespace("foo")

Namespace(dj_client=..., namespace='foo')

To delete (or restore) a namespace:

djbuilder.delete_namespace("foo")

djbuilder.restore_namespace("foo")

NOTE: The cascade parameter in both of above methods allows for cascading effect applied to all underlying nodes and namespaces. Use it with caution!

Tags

You can read existing tags as well as create new ones.

djbuilder.tag(name="deprecated", description="This node has been deprecated.", tag_type="standard", tag_metadata={"contact": "Foo Bar"})

Tag(dj_client=..., name='deprecated', description='This node has been deprecated.', tag_type='standard', tag_metadata={"contact": "Foo Bar"})

djbuilder.tag("official")

[DJClientException]: Tag `official` does not exist.

To create a tag:

djbuilder.create_tag(name="deprecated", description="This node has been deprecated.", tag_type="standard", tag_metadata={"contact": "Foo Bar"})

Tag(dj_client=..., name="deprecated", description="This node has been deprecated.", tag_type="standard", tag_metadata={"contact": "Foo Bar"})

To add a tag to a node:

repair_orders = djbuilder.source("default.repair_orders")
repair_orders.tags.append(djbuilder.tag("deprecated"))
repair_orders.save()

And to list the node names with a specific tag (or set of tags):

djbuilder.list_nodes_with_tags(tag_names=["deprecated"])  # works with DJClient() as well

["default.repair_orders"]

Nodes

To learn what Node means in the context of DJ, please check out this datajuntion.io page.

To list all (or some) nodes in the system you can use the list_<node-type>() methods described in the DJ Client : Basic Access section or you can use the namespace based method:

All nodes for a given namespace can be found with:

djbuilder.namespace("default").nodes()

Specific node types can be retrieved with:

djbuilder.namespace("default").sources()
djbuilder.namespace("default").dimensions()
djbuilder.namespace("default").metrics()
djbuilder.namespace("default").transforms()
djbuilder.namespace("default").cubes()

To create a source node:

repair_orders = djbuilder.create_source(
    name="repair_orders",
    display_name="Repair Orders",
    description="Repair orders",
    catalog="dj",
    schema_="roads",
    table="repair_orders",
)

Nodes can also be created in draft mode:

repair_orders = djbuilder.create_source(
    ...,
    mode=NodeMode.DRAFT
)

To create a dimension node:

repair_order = djbuilder.create_dimension(
    name="default.repair_order_dim",
    query="""
    SELECT
      repair_order_id,
      municipality_id,
      hard_hat_id,
      dispatcher_id
    FROM default.repair_orders
    """,
    description="Repair order dimension",
    primary_key=["repair_order_id"],
)

To create a transform node:

large_revenue_payments_only = djbuilder.create_transform(
    name="default.large_revenue_payments_only",
    query="""
    SELECT
      payment_id,
      payment_amount,
      customer_id,
      account_type
    FROM default.revenue
    WHERE payment_amount > 1000000
    """,
    description="Only large revenue payments",
)

To create a metric:

num_repair_orders = djbuilder.create_metric(
    name="default.num_repair_orders",
    query="""
    SELECT
      count(repair_order_id)
    FROM repair_orders
    """,
    description="Number of repair orders",
)

Reference

List of all available DJ builder methods:

• DJBuilder:

  namespaces

  • namespace( namespace: str)
  • create_namespace( namespace: str)
  • delete_namespace(self, namespace: str, cascade: bool = False)
  • restore_namespace(self, namespace: str, cascade: bool = False)

  nodes

  • delete_node(self, node_name: str)
  • restore_node(self, node_name: str)

  nodes: source

  • source(self, node_name: str)
  • create_source( ..., mode: Optional[NodeMode] = NodeMode.PUBLISHED)
  • register_table( catalog: str, schema: str, table: str)

  nodes: transform

  • transform(self, node_name: str)
  • create_transform( ..., mode: Optional[NodeMode] = NodeMode.PUBLISHED)

  nodes: dimension

  • dimension(self, node_name: str)
  • create_dimension( ..., mode: Optional[NodeMode] = NodeMode.PUBLISHED)

  nodes: metric

  • metric(self, node_name: str)
  • create_metric( ..., mode: Optional[NodeMode] = NodeMode.PUBLISHED)

  nodes: cube

  • cube(self, node_name: str)
  • create_cube( ..., mode: Optional[NodeMode] = NodeMode.PUBLISHED)

DJ System Administration

In this section we'll describe how to manage your catalog and engines.

Start Here

To initialize the DJ admin:

from datajunction import DJAdmin

djadmin = DJAdmin("http://localhost:8000")

NOTE If you are running in our demo docker container please change the above URL to "http://dj:8000".

Examples

To list available catalogs:

djadmin.list_catalogs()

['warehouse']

To list available engines:

djadmin.list_engines()

[{'name': 'duckdb', 'version': '0.7.1'}]

To create a catalog:

djadmin.add_catalog(name="my-new-catalog")

To create a new engine:

djadmin.add_engine(
  name="Spark",
  version="3.2.1",
  uri="http:/foo",
  dialect="spark"
)

To linke an engine to a catalog:

djadmin.link_engine_to_catalog(
  engine="Spark", version="3.2.1", catalog="my-new-catalog"
)

Reference

List of all available DJ builder methods:

• DJAdmin:

  Catalogs

  • list_catalogs() # in DJClient
  • get_catalog( name: str)
  • add_catalog( name: str)

  Engines

  • list_engines() # in DJClient
  • get_engine( name: str)
  • add_engine( name: str,version: str, uri: Optional[str], dialect: Optional[str])

  Together

  • link_engine_to_catalog( engine_name: str, engine_version: str, catalog: str)