Installation

The betflux package bundles the Python client library and the betflux CLI. Python 3.10+.

Install the CLI

For command-line use, install BetFlux as an isolated uv tool:

uv tool install betflux
betflux --version
betflux auto-update status

Starting with BetFlux 0.3.0, automatic stable-release updates are enabled by default for verified uv tool install betflux installations on Linux and macOS. If you installed the CLI with uv before 0.3.0, run this once to get the updater:

uv tool upgrade betflux

Then verify that betflux --version reports 0.3.0 or later and betflux auto-update status reports updates are on. uv preserves the version constraint from your original installation. If it excludes 0.3.0, revise the pin deliberately before upgrading.

Updates run before data commands and may occasionally delay startup. They use uv’s saved package source and version constraints. Automatic updates do not run for Windows, pip or editable installs, or temporary uvx commands. Importing the Python SDK never checks for or installs updates.

Disable updates in CI or for reproducible scripts by setting BETFLUX_NO_AUTO_UPDATE=1 for the process. For persistent settings and manual updates, see CLI updates.

Install the Python SDK

Install the Python package into your project environment with pip:

pip install betflux            # core client + CLI
pip install "betflux[pandas]"  # adds pandas for .df() DataFrames
pip install "betflux[polars]"  # adds polars — build frames from .rows()

The pip install also provides the CLI, but pip, editable, and project installs do not update automatically. For an isolated CLI, use uv as shown above.

Run a one-off command without installing a tool:

uvx betflux keys check

pip install betflux-cli also works — it is an alias that depends on betflux, so either name gives you the same library and the same CLI. For automatic updates, use a supported uv tool installation that exposes the betflux command.

The core install includes pyarrow — dataset payloads are per-game Parquet files, and the SDK parses and filters them locally, so it’s a required dependency rather than an extra.

.df() is pandas-only. The [polars] extra just installs polars alongside the client — build the frame yourself from .rows():

import polars as pl
df = pl.DataFrame(bf.closing_lines.rows(league="NBA", date_from="2026-05-01", date_to="2026-05-07"))

Configuration

Sign in through your browser to save a key for CLI commands and Python clients:

betflux login

Enter the terminal code on the website and select Approve access. See Browser login for the full walkthrough, headless setup, and logout.

You can also configure the client and CLI with environment variables:

export BETFLUX_API_KEY=bfx_live_...   # optional — overrides saved login
export BETFLUX_BASE_URL=...           # optional — override the API host

Both can also be passed explicitly — Client(api_key=...) in Python, betflux --api-key ... on the CLI.

Verify the setup:

betflux keys check

This calls GET /v1/me with your key and reports your connection, plan, limits and the period’s games usage.