Skip to main content

Routines for parsing SPICE text kernels

Project description

GitHub release; latest by date GitHub Release Date Test Status Documentation Status Code coverage
PyPI - Version PyPI - Format PyPI - Downloads PyPI - Python Version
GitHub commits since latest release GitHub commit activity GitHub last commit
Number of GitHub open issues Number of GitHub closed issues Number of GitHub open pull requests Number of GitHub closed pull requests
GitHub License Number of GitHub stars GitHub forks

Introduction

textkernel is a set of routines for parsing SPICE text kernels. This module implements the complete syntax specification as discussed in the SPICE Kernel Required Reading document, "kernel.req": https://naif.jpl.nasa.gov/pub/naif/toolkit_docs/C/req/kernel.html

textkernel is a product of the PDS Ring-Moon Systems Node.

Installation

The textkernel module is available via the rms-textkernel package on PyPI and can be installed with:

pip install rms-textkernel

Getting Started

The textkernel module provides two functions for reading text kernels:

  • from_text: Given a string representing the contents of a text kernel, return a dictionary of the values found.
  • from_file: Given the path to a text kernel, read the contents and return a dictionary of the values found.

and two functions for manipulating text kernels:

  • continued_value: Interpret a list of strings as one or more continued strings.
  • update_dict: Merge the contents of two text kernel dictionaries, preserving nested values.

Details of each function are available in the module documentation.

The simplest use case is as follows:

import textkernel
tkdict = textkernel.from_file('path/to/kernel/file')

The returned dictionary tkdict is keyed by all the parameter names (on the left side of an equal sign) in the text kernel, and each associated dictionary value is that found on the right side. Values are Python ints, floats, strings, datetime objects, or lists of one or more of these.

Hierarchical Keys

For convenience, the returned dictionary adds additional "hierarchical" keys that provide alternative access to the same values. Hierarchical keys are substrings from the original parameter name, which return a sub-dictionary keyed by part or all of the remainder of that parameter name.

Parameter names with a slash are split apart as if they represented components of a file directory tree, so these are equivalent:

tkdict["DELTET/EB"] == tkdict["DELTET"]["EB"]

When a body or frame ID is embedded inside a parameter name, it is extracted, converted to integer, and used as a piece of the hierarchy, making these equivalent:

tkdict["BODY399_POLE_RA"] == tkdict["BODY"][399]["POLE_RA"]
tkdict["SCLK01_MODULI_32"] == tkdict["SCLK"][-32]["01_MODULI"]

Leading and trailing underscores before and after the embedded numeric ID are stripped from the hierarchical keys, as you can see in the examples above. Note also that the components of the parameter name are re-ordered in the second example, so that the second key is always the numeric ID.

When the name associated with a body or frame ID is known, that name can be used in the place of the integer ID:

tkdict["BODY"][399] == tkdict["BODY"]["EARTH"]
tkdict["FRAME"][10013] == tkdict["FRAME"]["IAU_EARTH"]
tkdict["SCLK"][-32] == tkdict["SCLK"]["VOYAGER 2"]

If a frame is uniquely or primarily associated with a particular central body, that body's ID can also be used in place of the frame's ID:

tkdict["FRAME"][399] == tkdict["FRAME"]["IAU_EARTH"]

Note that the "BODY" and "FRAME" dictionaries also have an additional entry keyed by "ID", which returns the associated integer ID:

tkdict["FRAME"][623]["ID"] = 623
tkdict["FRAME"]["IAU_SUTTUNGR"]["ID"] = 623

This ensures that you can look up a body or frame by name and readily obtain its ID.

Contributing

Information on contributing to this package can be found in the Contributing Guide.

Links

Licensing

This code is licensed under the Apache License v2.0.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

rms_textkernel-1.0.4.tar.gz (267.5 kB view details)

Uploaded Source

Built Distribution

rms_textkernel-1.0.4-py3-none-any.whl (43.0 kB view details)

Uploaded Python 3

File details

Details for the file rms_textkernel-1.0.4.tar.gz.

File metadata

  • Download URL: rms_textkernel-1.0.4.tar.gz
  • Upload date:
  • Size: 267.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.12.4

File hashes

Hashes for rms_textkernel-1.0.4.tar.gz
Algorithm Hash digest
SHA256 1d8cb57ed9447f402ef31d18df5da9409f12ba1fc7a09b8d5cf68e3515e013ef
MD5 e31b94cd459f13b17ef4793c7eb51f3c
BLAKE2b-256 4862890bff00808fe8fa0aa815974d762d06ccb5a5302c4b64f6f3736cbb46aa

See more details on using hashes here.

File details

Details for the file rms_textkernel-1.0.4-py3-none-any.whl.

File metadata

File hashes

Hashes for rms_textkernel-1.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 570f6727a8b9f3b72604561f06218be4ea382aca30f2e2247bb74c8f0576f227
MD5 00702e31466e44554746e1c19b271f30
BLAKE2b-256 e1b104c67ef4a0c05326e8451f6b894167df4f2f193c94db512293b9802d62ee

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page