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https://github.com/ddeutils/ddeutil-vendors
DDE Vendors Utility Objects
https://github.com/ddeutils/ddeutil-vendors
Last synced: 1 day ago
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DDE Vendors Utility Objects
- Host: GitHub
- URL: https://github.com/ddeutils/ddeutil-vendors
- Owner: ddeutils
- License: mit
- Created: 2024-08-06T15:13:00.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2024-09-13T14:02:25.000Z (about 2 months ago)
- Last Synced: 2024-09-14T04:43:24.634Z (about 2 months ago)
- Language: Python
- Size: 36.1 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Vendors Data Computing
[](https://github.com/ddeutils/ddeutil-vendors)
[](https://github.com/ddeutils/ddeutil-vendors/blob/main/LICENSE)
[](https://github.com/psf/black)
This **Utility Vendors** data computing objects that implement connection and
dataset objects that will use the vendor API like `polars`, `deltalake`, etc,
package to be interface object.
> [!NOTE]
> This project will define the main propose and future objective soon. I think I
> want to create the simplest package that allow me to use it for data transformation
> & data quality with declarative template.
## Installation
This package does not publish with this name yet.
```shell
pip install ddeutil-vendor
```
## Features
### Connection
The connection for worker able to do any thing.
```yaml
conn_postgres_data:
type: conn.Postgres
url: 'postgres//username:${ENV_PASS}@hostname:port/database?echo=True&time_out=10'
```
```python
from ddeutil.vendors.conn import Conn
conn = Conn.from_loader(name='conn_postgres_data', externals={})
assert conn.ping()
```
### Dataset
The dataset is define any objects on the connection. This feature was implemented
on `/vendors` because it has a lot of tools that can interact with any data systems
in the data tool stacks.
```yaml
ds_postgres_customer_tbl:
type: dataset.PostgresTbl
conn: 'conn_postgres_data'
features:
id: serial primary key
name: varchar( 100 ) not null
```
```python
from ddeutil.vendors.vendors.pg import PostgresTbl
dataset = PostgresTbl.from_loader(name='ds_postgres_customer_tbl', externals={})
assert dataset.exists()
```
## Usage
```yaml
dq-some-data-domain:
type: dq.Postgres
assets:
- source: .
query: |
...
```
### Models
The Model objects was implemented from the [Pydantic V2](https://docs.pydantic.dev/latest/)
which is the powerful parsing and serializing data model to the Python object.
> [!NOTE]
> So, I use this project to learn and implement a limit and trick of the Pydantic
> package.
The model able to handle common logic validations and able to adjust by custom code
for your specific requirements (Yeah, it just inherits Sub-Class from `BaseModel`).
#### Data Types
```python
from ddeutil.vendors.models.dtype import StringType
dtype = StringType()
assert dtype.type == "string"
assert dtype.max_length == -1
```
#### Constraints
```python
from ddeutil.vendors.models.const import Pk
const = Pk(of="foo", cols=["bar", "baz"])
assert const.name == "foo_bar_baz_pk"
assert const.cols == ["bar", "baz"]
```
#### Datasets
```python
from ddeutil.vendors.models.datasets import Col, Tbl
tbl = Tbl(
name="table_foo",
features=[
Col(name="id", dtype="integer primary key"),
Col(name="foo", dtype="varchar( 10 )"),
],
)
assert tbl.name == "table_foo"
assert tbl.features[0].name == "id"
assert tbl.features[0].dtype.type == "integer"
```
## :beers: Usage
### Models
If I have some catalog config, it easy to pass this config to model object.
```python
import yaml
from ddeutil.vendors.models.datasets import Scm
config = yaml.safe_load("""
name: "warehouse"
tables:
- name: "customer_master"
features:
- name: "id"
dtype: "integer"
pk: true
- name: "name"
dtype: "varchar( 256 )"
nullable: false
""")
schema = Scm.model_validate(config)
assert len(schema.tables) == 1
assert schema.tables[0].name == 'customer_master'
```