path: root/python-odd-models.spec

%global _empty_manifest_terminate_build 0
Name:		python-odd-models
Version:	2.0.29
Release:	1
Summary:	Open Data Discovery Models
License:	Apache-2.0
URL:		https://github.com/opendatadiscovery/odd-models-package
Source0:	https://mirrors.aliyun.com/pypi/web/packages/39/05/a1006b2bb97ec15dc074e73f0d130cf7a2835bf9a999eee855e870e51210/odd_models-2.0.29.tar.gz
BuildArch:	noarch

Requires:	python3-pydantic
Requires:	python3-sqlparse
Requires:	python3-requests
Requires:	python3-sql-metadata
Requires:	python3-loguru
Requires:	python3-oddrn-generator
Requires:	python3-funcy

%description
[![PyPI version](https://badge.fury.io/py/odd-models.svg)](https://badge.fury.io/py/odd-models)

# OpenDataDiscovery Models package
Has some useful tools for working with OpenDataDiscovery. Such as:
1. Generated Python models from OpenDataDiscovery specification.
2. API Client for working with OpenDataDiscovery.
3. API for manual discovering data entities.

### Installation
```bash
pip install odd-models
```

### Models using example
**odd-models.models** package provides automatically generated Python model by OpenDataDiscovery specification.
It can be used for creating data entities for uploading them into the Platform.

Code example ([full code](./examples/postgres_models.py)):
```python
from oddrn_generator import PostgresqlGenerator
from odd_models.models import DataEntity, DataSet, DataSetField, DataSetFieldType, DataEntityType, Type, MetadataExtension
generator = PostgresqlGenerator(host_settings="localhost", databases="my_database", schemas="public")
DataEntity(
    oddrn=generator.get_oddrn_by_path("tables", "my_table"),
    name="my_table",
    type=DataEntityType.TABLE,
    metadata=[MetadataExtension(schema_url="https://example.com/schema.json", metadata={"env": "DEV"})],
    dataset=DataSet(
        field_list=[
            DataSetField(
                oddrn=generator.get_oddrn_by_path("tables_columns", "name"),
                name="name",
                type=DataSetFieldType(
                    type=Type.TYPE_STRING,
                    logical_type='str',
                    is_nullable=False
                ),
            )
        ]
    )
)
```


### HTTP Client for OpenDataDiscovery
___
**odd-models.client** package provides API client for OpenDataDiscovery API.
Client provides an API for working with OpenDataDiscovery Platform.
It has various methods for working with data sources, data entities, management etc.

Code example([full code](./examples/client.py)):

```python
from odd_models.api_client.v2.odd_api_client import Client
from examples.postgres_models import data_entity_list

client = Client(host="http://localhost:8080")
client.auth(name="dev_aws_token", description="Token for dev AWS account data sources")
client.ingest_data_entity_list(data_entity_list)
```

### Manual Discovery API
___
When there is no programmatic way to discover data sources and data entities, **odd-models.discovery** package provides API for manual discovery of data sources and data entities.

Code example([full code](./examples/lambda_discovery.py)):

```python
from odd_models.discovery import DataSource
from odd_models.discovery.data_assets import AWSLambda, S3Artifact
from odd_models.discovery.data_assets.data_asset_list import DataAssetsList

with DataSource("//cloud/aws/dev") as data_source:
    validation_lambda = AWSLambda.from_params(
        region="eu-central-1", account="0123456789", function_name="validation"
    )
    input_artifact = S3Artifact.from_url("s3://bucket/folder/test_data.csv")

    results = S3Artifact.from_url("s3://bucket/folder/test_result.csv")
    metrics = S3Artifact.from_url("s3://bucket/folder/test_metrics.json")

    input_artifact >> validation_lambda >> DataAssetsList([results, metrics])

    data_source.add_data_asset(validation_lambda)
```

# Development

### Installation
```bash
# Install dependencies
poetry install

# Activate virtual environment
poetry shell
```

### Generating models
```bash
# Generate models. Will generate models pydantic into odd_models/models
make generate_models

# Generate api client. Will generate api client into odd_models/api_client
make generate_client
```

### Tests
```bash
pytest .
```

### Docker build
```bash
docker build -t odd-models .
```

%package -n python3-odd-models
Summary:	Open Data Discovery Models
Provides:	python-odd-models
BuildRequires:	python3-devel
BuildRequires:	python3-setuptools
BuildRequires:	python3-pip
%description -n python3-odd-models
[![PyPI version](https://badge.fury.io/py/odd-models.svg)](https://badge.fury.io/py/odd-models)

# OpenDataDiscovery Models package
Has some useful tools for working with OpenDataDiscovery. Such as:
1. Generated Python models from OpenDataDiscovery specification.
2. API Client for working with OpenDataDiscovery.
3. API for manual discovering data entities.

### Installation
```bash
pip install odd-models
```

### Models using example
**odd-models.models** package provides automatically generated Python model by OpenDataDiscovery specification.
It can be used for creating data entities for uploading them into the Platform.

Code example ([full code](./examples/postgres_models.py)):
```python
from oddrn_generator import PostgresqlGenerator
from odd_models.models import DataEntity, DataSet, DataSetField, DataSetFieldType, DataEntityType, Type, MetadataExtension
generator = PostgresqlGenerator(host_settings="localhost", databases="my_database", schemas="public")
DataEntity(
    oddrn=generator.get_oddrn_by_path("tables", "my_table"),
    name="my_table",
    type=DataEntityType.TABLE,
    metadata=[MetadataExtension(schema_url="https://example.com/schema.json", metadata={"env": "DEV"})],
    dataset=DataSet(
        field_list=[
            DataSetField(
                oddrn=generator.get_oddrn_by_path("tables_columns", "name"),
                name="name",
                type=DataSetFieldType(
                    type=Type.TYPE_STRING,
                    logical_type='str',
                    is_nullable=False
                ),
            )
        ]
    )
)
```


### HTTP Client for OpenDataDiscovery
___
**odd-models.client** package provides API client for OpenDataDiscovery API.
Client provides an API for working with OpenDataDiscovery Platform.
It has various methods for working with data sources, data entities, management etc.

Code example([full code](./examples/client.py)):

```python
from odd_models.api_client.v2.odd_api_client import Client
from examples.postgres_models import data_entity_list

client = Client(host="http://localhost:8080")
client.auth(name="dev_aws_token", description="Token for dev AWS account data sources")
client.ingest_data_entity_list(data_entity_list)
```

### Manual Discovery API
___
When there is no programmatic way to discover data sources and data entities, **odd-models.discovery** package provides API for manual discovery of data sources and data entities.

Code example([full code](./examples/lambda_discovery.py)):

```python
from odd_models.discovery import DataSource
from odd_models.discovery.data_assets import AWSLambda, S3Artifact
from odd_models.discovery.data_assets.data_asset_list import DataAssetsList

with DataSource("//cloud/aws/dev") as data_source:
    validation_lambda = AWSLambda.from_params(
        region="eu-central-1", account="0123456789", function_name="validation"
    )
    input_artifact = S3Artifact.from_url("s3://bucket/folder/test_data.csv")

    results = S3Artifact.from_url("s3://bucket/folder/test_result.csv")
    metrics = S3Artifact.from_url("s3://bucket/folder/test_metrics.json")

    input_artifact >> validation_lambda >> DataAssetsList([results, metrics])

    data_source.add_data_asset(validation_lambda)
```

# Development

### Installation
```bash
# Install dependencies
poetry install

# Activate virtual environment
poetry shell
```

### Generating models
```bash
# Generate models. Will generate models pydantic into odd_models/models
make generate_models

# Generate api client. Will generate api client into odd_models/api_client
make generate_client
```

### Tests
```bash
pytest .
```

### Docker build
```bash
docker build -t odd-models .
```

%package help
Summary:	Development documents and examples for odd-models
Provides:	python3-odd-models-doc
%description help
[![PyPI version](https://badge.fury.io/py/odd-models.svg)](https://badge.fury.io/py/odd-models)

# OpenDataDiscovery Models package
Has some useful tools for working with OpenDataDiscovery. Such as:
1. Generated Python models from OpenDataDiscovery specification.
2. API Client for working with OpenDataDiscovery.
3. API for manual discovering data entities.

### Installation
```bash
pip install odd-models
```

### Models using example
**odd-models.models** package provides automatically generated Python model by OpenDataDiscovery specification.
It can be used for creating data entities for uploading them into the Platform.

Code example ([full code](./examples/postgres_models.py)):
```python
from oddrn_generator import PostgresqlGenerator
from odd_models.models import DataEntity, DataSet, DataSetField, DataSetFieldType, DataEntityType, Type, MetadataExtension
generator = PostgresqlGenerator(host_settings="localhost", databases="my_database", schemas="public")
DataEntity(
    oddrn=generator.get_oddrn_by_path("tables", "my_table"),
    name="my_table",
    type=DataEntityType.TABLE,
    metadata=[MetadataExtension(schema_url="https://example.com/schema.json", metadata={"env": "DEV"})],
    dataset=DataSet(
        field_list=[
            DataSetField(
                oddrn=generator.get_oddrn_by_path("tables_columns", "name"),
                name="name",
                type=DataSetFieldType(
                    type=Type.TYPE_STRING,
                    logical_type='str',
                    is_nullable=False
                ),
            )
        ]
    )
)
```


### HTTP Client for OpenDataDiscovery
___
**odd-models.client** package provides API client for OpenDataDiscovery API.
Client provides an API for working with OpenDataDiscovery Platform.
It has various methods for working with data sources, data entities, management etc.

Code example([full code](./examples/client.py)):

```python
from odd_models.api_client.v2.odd_api_client import Client
from examples.postgres_models import data_entity_list

client = Client(host="http://localhost:8080")
client.auth(name="dev_aws_token", description="Token for dev AWS account data sources")
client.ingest_data_entity_list(data_entity_list)
```

### Manual Discovery API
___
When there is no programmatic way to discover data sources and data entities, **odd-models.discovery** package provides API for manual discovery of data sources and data entities.

Code example([full code](./examples/lambda_discovery.py)):

```python
from odd_models.discovery import DataSource
from odd_models.discovery.data_assets import AWSLambda, S3Artifact
from odd_models.discovery.data_assets.data_asset_list import DataAssetsList

with DataSource("//cloud/aws/dev") as data_source:
    validation_lambda = AWSLambda.from_params(
        region="eu-central-1", account="0123456789", function_name="validation"
    )
    input_artifact = S3Artifact.from_url("s3://bucket/folder/test_data.csv")

    results = S3Artifact.from_url("s3://bucket/folder/test_result.csv")
    metrics = S3Artifact.from_url("s3://bucket/folder/test_metrics.json")

    input_artifact >> validation_lambda >> DataAssetsList([results, metrics])

    data_source.add_data_asset(validation_lambda)
```

# Development

### Installation
```bash
# Install dependencies
poetry install

# Activate virtual environment
poetry shell
```

### Generating models
```bash
# Generate models. Will generate models pydantic into odd_models/models
make generate_models

# Generate api client. Will generate api client into odd_models/api_client
make generate_client
```

### Tests
```bash
pytest .
```

### Docker build
```bash
docker build -t odd-models .
```

%prep
%autosetup -n odd_models-2.0.29

%build
%py3_build

%install
%py3_install
install -d -m755 %{buildroot}/%{_pkgdocdir}
if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
pushd %{buildroot}
if [ -d usr/lib ]; then
	find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/lib64 ]; then
	find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/bin ]; then
	find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
if [ -d usr/sbin ]; then
	find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst
fi
touch doclist.lst
if [ -d usr/share/man ]; then
	find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst
fi
popd
mv %{buildroot}/filelist.lst .
mv %{buildroot}/doclist.lst .

%files -n python3-odd-models -f filelist.lst
%dir %{python3_sitelib}/*

%files help -f doclist.lst
%{_docdir}/*

%changelog
* Thu Jun 08 2023 Python_Bot <Python_Bot@openeuler.org> - 2.0.29-1
- Package Spec generated