Sandbox E-Invoice Portal Python API Docs | dltHub
Build a Sandbox E-Invoice Portal-to-database pipeline in Python using dlt with AI Workbench support for Claude Code, Cursor, and Codex.
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E‑Invoice Portal is a sandbox REST API for Indian GST taxpayers to generate, retrieve, and manage e‑invoice and e‑waybill data. The REST API base URL is https://einv-apisandbox.nic.in and All requests require an AuthToken obtained via the authentication endpoint, passed in the Authorization header; payloads are encrypted with SEK..
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 Sandbox E-Invoice Portal data in under 10 minutes.
What data can I load from Sandbox E-Invoice Portal?
Here are some of the endpoints you can load from Sandbox E-Invoice Portal:
| Resource | Endpoint | Method | Data selector | Description |
|---|---|---|---|---|
| get_irn_details | /v1.04/irn/details/{irn} | GET | Data.IrnDetails | Retrieve details of a specific IRN |
| get_invoice_by_irn | /v1.04/invoice/irn/{irn} | GET | Data.Invoice | Retrieve the full e‑invoice JSON for a given IRN |
| get_invoice_by_ackno | /v1.04/invoice/ackno/{ackNo} | GET | Data.Invoice | Retrieve invoice using acknowledgment number |
| get_invoice_by_invoiceno | /v1.04/invoice/invoiceNo/{invoiceNo} | GET | Data.Invoice | Retrieve invoice using the original invoice number |
| get_ewaybill_by_irn | /v1.04/ewaybill/irn/{irn} | GET | Data.EWayBill | Retrieve e‑Waybill details for a given IRN |
| generate_irn | /v1.04/irn/generate | POST | Data.IRN | Generate a new IRN (included for completeness) |
How do I authenticate with the Sandbox E-Invoice Portal API?
Authentication is performed via a POST to /v1.04/auth with taxpayer credentials (username, password, GSTIN) and AppKey; the returned AuthToken must be sent in the Authorization header for all subsequent calls, and the SEK key is used for payload encryption.
1. Get your credentials
- Log in to the NIC sandbox developer portal (https://developer.sandbox.co.in).\n2. Navigate to "Enable API Access on E‑Invoice Portal".\n3. Request access for the "E‑Invoice" service.\n4. Once approved, download the credentials package which contains the AppKey, public key, and sample username/password for the sandbox taxpayer.\n5. Store the AppKey and the generated username/password; they will be used in the authentication request.
2. Add them to .dlt/secrets.toml
[sources.sandbox_e_invoice_portal_source] auth_token = "your_auth_token_here" sek = "your_sek_here" app_key = "your_app_key_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:
uv venv && source .venv/bin/activate uv pip install "dlt[workspace]"
1. Install the dlt AI Workbench:
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:
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 Sandbox E-Invoice Portal 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:
python sandbox_e_invoice_portal_pipeline.py
If everything is configured correctly, you'll see output like this:
Pipeline sandbox_e_invoice_portal_pipeline load step completed in 0.26 seconds 1 load package(s) were loaded to destination duckdb and into dataset sandbox_e_invoice_portal_data The duckdb destination used duckdb:/sandbox_e_invoice_portal.duckdb location to store data Load package 1749667187.541553 is LOADED and contains no failed jobs
Inspect your pipeline and data:
dlt pipeline sandbox_e_invoice_portal_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 get_irn_details and get_invoice_by_irn from the Sandbox E-Invoice Portal API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:
import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def sandbox_e_invoice_portal_source(auth_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://einv-apisandbox.nic.in", "auth": { "type": "bearer", "token": auth_token, }, }, "resources": [ {"name": "get_irn_details", "endpoint": {"path": "v1.04/irn/details/{irn}", "data_selector": "Data.IrnDetails"}}, {"name": "get_invoice_by_irn", "endpoint": {"path": "v1.04/invoice/irn/{irn}", "data_selector": "Data.Invoice"}} ], } yield from rest_api_resources(config) def get_data() -> None: pipeline = dlt.pipeline( pipeline_name="sandbox_e_invoice_portal_pipeline", destination="duckdb", dataset_name="sandbox_e_invoice_portal_data", ) load_info = pipeline.run(sandbox_e_invoice_portal_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):
import dlt data = dlt.pipeline("sandbox_e_invoice_portal_pipeline").dataset() sessions_df = data.get_irn_details.df() print(sessions_df.head())
SQL (DuckDB example):
SELECT * FROM sandbox_e_invoice_portal_data.get_irn_details LIMIT 10;
In a marimo or Jupyter notebook:
import dlt data = dlt.pipeline("sandbox_e_invoice_portal_pipeline").dataset() data.get_irn_details.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 Sandbox E-Invoice Portal data to?
dlt supports loading into any of these destinations — only the destination parameter changes:
| Destination | Example value |
|---|---|
| DuckDB (local, default) | "duckdb" |
| PostgreSQL | "postgres" |
| BigQuery | "bigquery" |
| Snowflake | "snowflake" |
| Redshift | "redshift" |
| Databricks | "databricks" |
| Filesystem (S3, GCS, Azure) | "filesystem" |
Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.
Troubleshooting
Authentication Errors
- 1015 Invalid GSTIN for user – occurs when the GSTIN supplied does not match any sandbox taxpayer. Verify the GSTIN value.
- 1017 Incorrect user id – the username is wrong; check the sandbox credentials.
- 1019 Incorrect password – password mismatch; ensure the password is correct and encrypted as required.
Token Expiry
- Tokens are valid for 60 minutes in sandbox. After expiry, receive a 401 error. Re‑authenticate using the
/v1.04/authendpoint.
Server Errors
- GEN5008 GSTN Server Error – internal service failure; retry after a short delay.
- Rate limiting is not explicitly documented; if a 429 response is received, back‑off exponentially.
Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.
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.
dlt ai toolkit data-exploration install dlt ai toolkit dlthub-runtime install
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