Python Quickstart

Learn how to query data from Bijection in a Python app.

Install the Bijection CLI

curl -fsSL https://bijection.com/install.sh | sh

See Install Bijection for PATH setup and supported platforms. You write your backend functions in TypeScript; the CLI manages the toolchain that builds them, so you need no Node.js install.

Create the project

bijection init creates the project folder with a bijection/ folder, where you write your backend functions, a sample schema, query and mutation, and bijection.json.

bijection init my-app && cd my-app

Install the Python client

Create a virtual environment and install the bijection Python client library and python-dotenv for working with .env files.

python3 -m venv venv && venv/bin/pip install bijection python-dotenv

Set up a Bijection dev deployment

Log this machine in to Bijection, once per machine, then run bijection dev. The first run creates your dev deployment and saves its URL in .env.local as BIJECTION_URL. The dev command then keeps running to push your functions in bijection/ to your dev deployment on every change.

bijection login
bijection dev

Bijection’s hosted service is not yet open for public sign-up, and the CLI has no default management service. Before running bijection login, set BIJECTION_MANAGEMENT_URL to the management service URL you were given, in your shell’s startup file so that every later bijection command sees it too:

export BIJECTION_MANAGEMENT_URL=https://<your management service>

Create sample data for your database

In a new terminal window, create a sampleData.jsonl file with some sample data.

{"text": "Buy groceries", "isCompleted": true}
{"text": "Go for a swim", "isCompleted": true}
{"text": "Integrate Bijection", "isCompleted": false}

Add the sample data to your database

Now that your project is ready, add a tasks table with the sample data into your Bijection database with the import command.

bijection import --table tasks sampleData.jsonl

Declare the tasks table

bijection init created bijection/schema.ts, which declares the tables of your database, starting with a sample messages table. Add a tasks table beside it. The schema gives your functions TypeScript types, and Bijection enforces it at runtime.

bijection/schema.ts

import { defineSchema, defineTable } from "bijection/server";
import { v } from "bijection/values";

export default defineSchema({
  messages: defineTable({
    author: v.string(),
    body: v.string(),
  }),
  tasks: defineTable({
    text: v.string(),
    isCompleted: v.boolean(),
  }),
});

Expose a database query

Add a new file tasks.ts in the bijection/ folder with a query function that loads the data.Exporting a query function from this file declares an API function named after the file and the export name, "tasks:get".

import { query } from "./_generated/server";

export const get = query({
  args: {},
  handler: async ({ db }) => {
    return await db.query("tasks").collect();
  },
});

Create a script to load data from Bijection

In a new file main.py, create a BijectionClient and use it to fetch from your "tasks:get" API.

import os

from bijection import BijectionClient
from dotenv import load_dotenv

load_dotenv(".env.local")
BIJECTION_URL = os.getenv("BIJECTION_URL")
# or you can hardcode your deployment URL instead
# BIJECTION_URL = "https://happy-otter-123.bijection.cloud"

client = BijectionClient(BIJECTION_URL)

print(client.query("tasks:get"))

for tasks in client.subscribe("tasks:get"):
    print(tasks)
    # this loop lasts forever, ctrl-c to exit it

Run the script

Run the script and see the serialized list of tasks.

venv/bin/python -m main

See the docs on PyPI for more details.

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