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Inserting data via the PostgREST API using Python


Building upon our previous dive into PostgREST's read capabilities, this post unveils the secrets of securely writing data via the PostgREST API.

PostgREST enables you to define secure API endpoints through SQL. Whether you have your own PostgREST API running, or would like to update your Supabase data from an external Python script, this post is for you!

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The data tables: a refresher

As outlined in the preceding blog post, my live portfolio incorporates SQL views exposed as REST endpoints. The functionality of these endpoints relies on the existence of two source tables: trades and portfolio_history.

Let's delve into their respective schemas:

CREATE TYPE market_enum as enum('kraken');
CREATE TYPE interval_enum as enum('week', 'day');
CREATE TABLE portfolio_history (
    timestamp BIGINT NOT NULL,
    updated_at BIGINT,
    market market_enum,
    interval interval_enum,
    usd_total_value NUMERIC(48, 18),
    usd_held NUMERIC(48, 18),
    interval_pct_return NUMERIC(48, 18),
    benchmark_btc_value NUMERIC(48, 18),
    benchmark_btc_interval_pct_return NUMERIC(48, 18),
    benchmark_eth_value NUMERIC(48, 18),
    benchmark_eth_interval_pct_return NUMERIC(48, 18),
    PRIMARY KEY (id)
    timestamp BIGINT NOT NULL,
    market market_enum NOT NULL,
    symbol TEXT NOT NULL,
    base_asset TEXT NOT NULL,
    quote_asset TEXT NOT NULL,
    is_buy BOOL NOT NULL,
    amount NUMERIC(48, 18) NOT NULL,
    price NUMERIC(48, 18) NOT NULL,
    usd_value NUMERIC(48, 18) NOT NULL,
    PRIMARY KEY (id)

For data to be returned by REST endpoints like /api/latest_trades, it must first exist in the database. Let's explore how my local scripts leverage PostgREST UPDATE endpoints to insert new data and update existing records.

Scaffolding PostgREST permissions

The write endpoints feature JWT token authentication for protection. In our previous post, we operated the PostgREST server with a SECRET_KEY environment variable. This represents the simpler of the two security schemes offered by PostgREST, where the JWT token is symmetrically encrypted and decrypted using the same key (learn more).


For scenarios where authentication is tied to individual users, it is advisable to opt for the asymmetric key scheme with an external OAuth provider, like Google.

We establish a distinct role, api_data_producer, endowed with more permissions than the default api_anon role. The name of this role is not special; you simply need to use the same when generating your JWT token.

CREATE ROLE api_data_producer nologin;
GRANT api_data_producer TO authenticator;

Just like for the api_anon role, the authenticator role requires permission to impersonate it. We shall remember that the authenticator role is the special initialization role that PostgREST uses to then use other roles based on the auth token provided.

Update endpoints

Trades endpoint

To create a writeable endpoint, the only thing needed is to grant appropriate permissions to the desired role. As for public views, PostgREST recommends writing to views and not to tables. And yes, you can insert data into a view as long as it satisfies certain conditions.

-- Restricted access to api_data_producer
CREATE VIEW api.all_trades AS (
GRANT USAGE on SCHEMA api to api_data_producer;
GRANT SELECT, INSERT, UPDATE ON api.all_trades to api_data_producer;

Portfolio history

Nothing much different for the portfolio history view, except that we decided to support deletion. The update script deletes the last incomplete entry (the ongoing week, for example) and creates a new one every time.

CREATE VIEW api.portfolio_history AS (
        timestamp / 1000 as timestamp_s,
GRANT USAGE, SELECT ON SEQUENCE portfolio_history_id_seq TO api_data_producer;
GRANT SELECT, INSERT, UPDATE, DELETE, TRUNCATE ON api.portfolio_history to api_data_producer;

I'm not exactly sure anymore if the GRANT on the portfolio_history_id_seq is necessary. Let me know if you try it out!

Adding data from an external Python script

Now that we have writable REST endpoints, securely invoking them is the next step. The Python implementation provided here is language-agnostic in its approach.

Generating the JWT token

PostgREST utilizes the standard Authorization: 'Bearer ...' header for authorization. Here's how to generate the token in Python using symmetrical encryption:

import jwt
def generate_jwt(target_url: str, role: str, jwt_secret: Optional[str] = None):
    if jwt_secret is None:
        jwt_secret = os.environ["PGRST_JWT_SECRET"]
    return jwt.encode({"role": role, "aud": target_url}, jwt_secret, algorithm="HS256")

As an example, using this website and the api_data_producer role:

auth_header = f'Bearer {generate_jwt(target_url, role)}'

Adding trades

Once we have a JWT token, we can now POST data to our REST API. Utilizing the postgrest-py library, Python makes this task seamless:

import datetime
import jwt
import postgrest
def generate_jwt(target_url: str, role: str, jwt_secret: Optional[str] = None):
    if jwt_secret is None:
        jwt_secret = os.environ["PGRST_JWT_SECRET"]
    return jwt.encode({"role": role, "aud": target_url}, jwt_secret, algorithm="HS256")
def datetime_to_ms(dt: Optional[datetime.datetime] = None):
    if not dt:
        dt = datetime.datetime.utcnow()
    return int((dt - datetime.datetime(1970, 1, 1)).total_seconds() * 1e3)
target_url = ''
role = 'api_data_producer'
jwt_secret = '...'
headers = {
    "Authorization": f"Bearer {generate_jwt(target_url, role, jwt_secret=jwt_secret)}"
client = postgrest.SyncPostgrestClient(
    target_url, schema="api", headers=headers, timeout=60
my_trade = {
    "id": "unique-order-id",
    "timestamp": datetime_to_ms(),
    "market": "kraken",
    "symbol": "ETH/USD",
    "base_asset": "ETH",
    "quote_asset": "USD",
    "is_buy": True,
    "amount": 1.0,
    "price": 2013.20,
    "usd_value": 2013.20,
    [my_trade], upsert=True

This Python script effectively inserts the specified trade into the remote database. Note that the id column can be any string, and with the upsert=True option, existing orders are replaced.

I utilize the Hummingbot order ID. If the order already exists, it will be seamlessly replaced. This feature enables my script to eagerly re-insert existing trades, eliminating concerns about duplicates.


In conclusion, this tutorial has equipped you with the technical prowess to establish a robust writable API for your PostgreSQL database, seamlessly integrating Python and PostgREST. From configuring your schema for write-able views to crafting JWT tokens with appropriate permissions, and finally, executing data insertions to the all_trades endpoint.

While we intentionally omitted the Python code to write to the portfolio_history endpoint for brevity, the same insertion principles we showed related to all_trades can be extended to that view as well.

Such a REST API opens the gateway to constructing publicly accessible, yet highly secure, writable endpoints. This tutorial marks the commencement of an exploration into the extensive possibilities that lie ahead in your SQL and Python journey. Happy coding!

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