Packagist Yii2 REST API Doc Python API Docs | dltHub

chemezov/yii2-rest-api-doc is a Yii2 extension for generating REST API documentation from defined endpoints and annotations. It simplifies documentation for Yii2 REST applications. The package is available on Packagist. The REST API base URL is https://your-api.example.com and Authentication method varies; commonly a Bearer token is used..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Packagist Yii2 REST API Doc data in under 10 minutes.

---

What data can I load from Packagist Yii2 REST API Doc?

Here are some of the endpoints you can load from Packagist Yii2 REST API Doc:

---

How do I authenticate with the Packagist Yii2 REST API Doc API?

Requests typically include an 'Authorization: Bearer ' header; alternatives such as HTTP Basic or session cookies may also be used depending on the application.

1. Get your credentials

1. Deploy your Yii2 application built with the chosen package.
2. Implement or enable an authentication controller (e.g., /login) that issues JWT or bearer tokens.
3. Use the endpoint to obtain a token by providing valid user credentials.
4. Store the received token for use in dlt configuration.

2. Add them to .dlt/secrets.toml

Copy
[sources.packagist_yii2_rest_api_doc_source]
api_key = "your_bearer_token_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

Copy
uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

Copy
dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

Copy
dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Packagist Yii2 REST API Doc API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

Copy
python packagist_yii2_rest_api_doc_pipeline.py

If everything is configured correctly, you'll see output like this:

Copy
Pipeline packagist_yii2_rest_api_doc_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset packagist_yii2_rest_api_doc_data
The duckdb destination used duckdb:/packagist_yii2_rest_api_doc.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

Copy
dlt pipeline packagist_yii2_rest_api_doc_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

---

Python pipeline example

This example loads users and posts from the Packagist Yii2 REST API Doc API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

Copy
import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def packagist_yii2_rest_api_doc_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://your-api.example.com",
            "auth": {
                "type": "bearer",
                "token": api_key,
            },
        },
        "resources": [
            {"name": "users", "endpoint": {"path": "users", "data_selector": "data"}},
            {"name": "posts", "endpoint": {"path": "posts", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="packagist_yii2_rest_api_doc_pipeline",
        destination="duckdb",
        dataset_name="packagist_yii2_rest_api_doc_data",
    )
    load_info = pipeline.run(packagist_yii2_rest_api_doc_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

---

How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

Copy
import dlt

data = dlt.pipeline("packagist_yii2_rest_api_doc_pipeline").dataset()
sessions_df = data.users.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM packagist_yii2_rest_api_doc_data.users LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("packagist_yii2_rest_api_doc_pipeline").dataset()
data.users.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

---

What destinations can I load Packagist Yii2 REST API Doc data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

---

Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

Copy
dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack