tabpfn-common-utils 0.2.23

Utilities shared between TabPFN codebases

TabPFN Common Utilities

Shared Python utilities used across the TabPFN ecosystem (the tabular foundation model).

Features

Data Processing Utilities

• Regression Results: Handling of prediction outputs with mean, median, mode, and quantiles
• Data Serialization: Convert between pandas DataFrames, NumPy arrays, and CSV formats
• Dataset Management: Load and preprocess standard ML datasets with proper train/test splits
• Preprocessing Configuration: Options for data transformation strategies

Cost Estimation

• Resource Planning: Estimation of computational costs and duration for TabPFN predictions
• Cloud Pricing: Useful for resource planning in cloud-based TabPFN services
• Task-Specific Calculations: Different cost models for classification vs regression tasks

Telemetry (optional, opt-out)

• Anonymous & Aggregated: No personal information or sensitive data is collected or transmitted
• Configurable: Can be disabled via environment variable
• Usage Patterns: Aggregate signals used to improve TabPFN

Installation

pip install tabpfn-common-utils

Or with uv:

uv add tabpfn-common-utils

Quick Start

Regression Results

from tabpfn_common_utils.regression_pred_result import RegressionPredictResult

# Handle regression prediction results
result = RegressionPredictResult({
    "mean": [1.2, 2.3, 3.4],
    "median": [1.1, 2.2, 3.3],
    "mode": [1.0, 2.0, 3.0],
    "quantile_0.25": [0.9, 1.9, 2.9],
    "quantile_0.75": [1.5, 2.5, 3.5]
})

# Convert to basic representation for serialization
basic_repr = RegressionPredictResult.to_basic_representation(result)

Data Utilities

from tabpfn_common_utils.utils import get_example_dataset, serialize_to_csv_formatted_bytes
import pandas as pd

# Load example dataset
X_train, X_test, y_train, y_test = get_example_dataset("iris")

# Serialize data to CSV bytes
csv_bytes = serialize_to_csv_formatted_bytes(X_train)

Telemetry

from tabpfn_common_utils.telemetry import ProductTelemetry

# Initialize telemetry service (anonymous; opt-out)
telemetry = ProductTelemetry()

# Track usage events
telemetry.capture(...)

# Disable via environment variable
export TABPFN_DISABLE_TELEMETRY=1

Telemetry notes

• Anonymous and aggregated only — no user identification or tracking
• Disabled by setting TABPFN_DISABLE_TELEMETRY=1
• Open source — see src/tabpfn_common_utils/telemetry/ for what is sent

Development

Setup

# Install dependencies
uv sync

# Activate virtual environment
source .venv/bin/activate

# Run tests
uv run pytest

# Type checking
uv run pyright

# Code formatting
uv run ruff check --fix

Adding Dependencies

# Add runtime dependency
uv add <package_name>

# Add development dependency
uv add --group dev <package_name>

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

Contributing

Contributions are welcome! Please ensure all code passes type checking and formatting requirements.

Links

• TabPFN Main Repository
• Documentation
• Issues