Welcome to mpcq’s documentation!

mpcq is a powerful Python client library for querying and analyzing Minor Planet Center (MPC) data, made available through the Small Bodies Node (SBN). The data is hosted on Google BigQuery and maintained by the Asteroid Institute.

You can find the source code on GitHub and the package on PyPI.

For example, the library provides a simple interface to query MPC observations:

>>client = BigQueryMPCClient(
   dataset_id="your_subscribed_main_dataset_id"
)
>>observations = client.query_observations(["2013 RR165"])
>>print(f"Number of observations: {len(observations)}")
Number of observations: 40
>>print(f"Date range: {observations.obstime.min().mjd()} to {observations.obstime.max().mjd()}")
Date range: [55591.46905] to [58009.34117]
>>print(f"Observatories: {pc.unique(observations.stn)}")
Observatories: [
   "F51",
   "W84",
   "G96"
]

Features

• BigQuery Integration: Quickly analyze MPC data without having to maintain your own replica.

• Efficient Queries: Optimized query patterns for common asteroid data access patterns

• Rich Data Access: Query observations, orbits, submission history, and more

• Cross-Matching: Tools for matching observations and finding duplicates

Data Structures

The mpcq package uses adam-core data structures, which are built on top of Quivr. Quivr provides strongly-typed tables backed by Apache Arrow for efficient memory usage and fast operations. All query results are returned as Quivr tables with predefined schemas:

• MPCObservations: Contains observation data with columns like obstime, ra, dec, etc.

• MPCOrbits: Contains orbital elements with columns like a, e, i, etc.

• MPCSubmissionHistory: Contains submission history with columns like submission_time, num_obs, etc.

• MPCPrimaryObjects: Contains object identification data linking different designations.

All of the data structures can easily be converted to pandas DataFrames.

Contents:

• Installation
  • Requirements
  • Installing mpcq
  • Google Cloud Setup
  • Using the Client
  • Cost Considerations
  • Development Installation
• Quickstart Guide
  • Basic Setup
  • Subscribe to the Dataset
  • Initialize the Client
  • Query Observations
  • Working with Orbits
  • A Note on Quivr
  • Next Steps
• BigQuery Dataset
  • Dataset Scale and Storage
  • Dataset Access
  • Dataset Overview
  • Key Tables
  • Performance Optimization
  • Example Queries
  • Pricing and Free Tier
• API Reference
  • Data Structures
  • Client Classes
  • Submission Classes
• Examples
  • Basic Object Queries
  • MPC Orbit Queries
  • Cross-Matching with Observations
  • Get the status of a Submission
  • Working with Submission History
• Community
  • Mailing List
  • Slack Community
  • GitHub
  • PyPI Package
  • Getting Help
  • Contributing
• Contributing
  • Development Setup
  • Available Commands
  • Development Workflow
  • Coding Standards
  • Testing
  • Documentation
  • Pull Request Process
  • Questions and Support
  • License
• Changelog
  • [Unreleased]
  • [0.1.0] - 2024-02-14

Getting Started

To get started with mpcq, check out the Quickstart Guide guide.

BigQuery Dataset

The Asteroid Institute maintains a BigQuery replica of the Minor Planet Center’s Small Bodies Node database. This dataset is publicly accessible through Google Cloud Platform. For more information about accessing and using the dataset, see BigQuery Dataset.

Community

Join our community! We have an active mailing list and Slack workspace where you can get help, share ideas, and contribute to the project. See our Community page for more details on how to get involved.

Indices and tables

• Index

• Module Index

• Search Page