floe-python

Python bindings for floe — a high-performance data ingestion and quality engine written in Rust.

Run floe pipelines at full Rust speed directly from Python notebooks, scripts, or orchestrators.

Installation

pip install floe-python

Quick start

import floe

# Validate a pipeline config
floe.validate("pipeline.yml")

# Run the full pipeline
outcome = floe.run("pipeline.yml")
print(outcome.summary["results"])

# Dry run — see which files would be processed
outcome = floe.run("pipeline.yml", dry_run=True)
for preview in outcome.dry_run_previews:
    print(preview["name"], preview["scanned_files"])

# Run a subset of entities
outcome = floe.run("pipeline.yml", entities=["customers", "orders"])

# Live progress in Jupyter
floe.set_observer(lambda e: print(f"[{e['event']}]", e.get("name", "")))
outcome = floe.run("pipeline.yml")
floe.clear_observer()

# Profile overrides (variables + catalog config)
floe.run("pipeline.yml", profile_path="profile.yml")
floe.run("pipeline.yml", profile_vars={"output_bucket": "s3://my-bucket"})

# Inspect / reset incremental state
state = floe.inspect_entity_state("pipeline.yml", "customers")
floe.reset_entity_state("pipeline.yml", "customers")

Error handling

try:
    floe.validate("config.yml")
except floe.FloeConfigError as e:
    print(f"Config problem: {e}")
except floe.FloeRunError as e:
    print(f"Run failed: {e}")
except floe.FloeError as e:
    print(f"Floe error: {e}")

API reference

Function Description
validate(config_path, *, entities, profile_vars, profile_path) Validate a config file
run(config_path, *, entities, dry_run, run_id, profile_vars, profile_path) Execute the pipeline
load_config(config_path) Parse config into a RootConfig object
extract_config_env_vars(config_path) List placeholder variables in the config
inspect_entity_state(config_path, entity_name) Inspect incremental state for an entity
reset_entity_state(config_path, entity_name) Delete incremental state for an entity
set_observer(callback) Register a live-event callback
clear_observer() Remove the current callback

Jupyter

RunOutcome renders as a color-coded HTML table automatically in Jupyter — no extra code needed. Just end a cell with the variable:

outcome = floe.run("orders.yml")
outcome  # renders inline HTML table with per-entity status, accepted/rejected counts

Use outcome.to_dict() to turn results into a plain dict for pandas:

import pandas as pd
df = pd.DataFrame(outcome.entity_reports)

Observing progress

Register a callback to receive live events as the run proceeds:

floe.set_observer(lambda e: print(f"[{e['event']}]", e.get("name", e.get("entity", ""))))
outcome = floe.run("orders.yml")
floe.clear_observer()

Event types: run_started, entity_started, file_started, file_finished, schema_evolution_applied, entity_finished, run_finished, log. See the full guide for all event fields.

Profile overrides

Override config variables or cloud credentials without editing the YAML:

floe.run("orders.yml", profile_vars={"incoming_root": "s3://my-bucket/incoming"})
floe.run("orders.yml", profile_path="prod.yml")

Building from source

pip install maturin
git clone https://github.com/malon64/floe
cd floe/crates/floe-python
maturin develop

License

Apache 2.0

→ Full API reference and examples: docs/python-bindings.md

Project links

Data verified by PyPI on Jul 22, 2026
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Key dates

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Latest release

1 maintainer

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Avatar for malon64 from gravatar.com malon64

Credits

Author: Floe contributors

GitHub Statistics

Data verified by PyPI on Jul 22, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

Apache-2.0

Requires

Python >=3.10

Provides Extra

dev

Tags

ingestion data-quality yaml polars

Classifiers

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