update docs and ancillary env files[skip ci]

benchmark/bench-environment.yml

@@ -1,7 +1,6 @@
 name: lh-bench
 channels:
   - conda-forge
-  - defaults
 dependencies:
   - astroquery
   - jupyter

docs/conda_installation_guide.md

@@ -2,50 +2,34 @@
 
 ## step 1: install conda
 
-*If you already have Anaconda or Miniconda installed on your computer, you can
+*If you already have another version of `conda` installed on your computer, you can
 skip this step. If it's very old or not working well, you should uninstall it first.
 We **definitely** don't recommend installing multiple versions of `conda`
 unless you have a strong and specific reason to do so.*
 
-[You can get `conda` here as part of the Miniconda distribution of Python](https://docs.conda.io/projects/continuumio-conda/en/latest/user-guide/install/index.html).
+[You can get `conda` here as part of the Miniforge distribution of Python](https://github.com/conda-forge/miniforge).
 Download the appropriate version of the installer for your operating system and 
 processor architecture (in most cases 64-bit) and follow the instructions on that 
-website to set up your environment. Make sure you download Miniconda3, not 
-Miniconda2. `lhorizon` is not compatible with Python 2.
+website to set up your environment.
 
-## step 2: create conda environment
+## step 2: install `lhorizon` from conda-forge
 
-Now that you have `conda` installed, you can set up a Python environment
-to use `lhorizon`. Open a terminal window: Anaconda Prompt on Windows, Terminal on macOS,
-or your console emulator of choice on Linux. Navigate to the directory where
-you put the repository and run the command:
-
-`conda env create -f environment.yml`
-
-Say yes at the prompts and let the installation finish. Then run:
-
-`conda env list`
-
-You should see `lhorizon` in the list of environments. Now run:
+Create a new conda environment and install `lhorizon` into it:
+`conda create -n lhorizon lhorizon`.
 
-`conda activate lhorizon`
+If you are using a different version of `conda` rather than the Miniforge version
+linked above, you may need to specify the conda-forge channel, like:
+`conda create -c conda-forge -n lhorizon lhorizon`.
 
-and you will be in a Python environment that contains all the packages
-`lhorizon` needs. 
+## step 3: use the `lhorizon` environment
 
-**Important:** now that you've created this environment, you should 
-always have it active whenever you work with `lhorizon`.
-
-If you can't activate the environment, see 'common gotchas' below.
-
-## step 3: install `lhorizon` as a site package
-
-With the "lhorizon" environment active, run `python setup.py install`.
-Now `lhorizon` can be imported in any code you run using the "lhorizon"
-environment.
+Now you have a Python environment that contains `lhorizon` and all its dependencies.
+ Open a terminal window: Anaconda Prompt on Windows, Terminal on macOS,
+or your console emulator of choice on Linux. Navigate to the directory where
+you put the repository and run the command:
 
-Now go try the example Jupyter Notebooks by running `jupyter notebook` and
-navigating to the /lhorizon/examples directory!
+`conda activate lhorizon`. Now you can download the example Notebooks from
+GitHub and run them, or write whatever other code you like using `lhorizon`
 
 ## common gotchas
 
@@ -57,4 +41,4 @@ navigating to the /lhorizon/examples directory!
 * If you've already got an installed version of `conda` on your system, installing 
   an additional version without uninstalling the old one may make environment setup very 
   challenging. We do not recommend installing multiple versions of `conda` at once 
-  unless you really need to.
+  unless you really need to.

lhorizon/tests/.doc-environment.yml

@@ -1,7 +1,6 @@
 name: lh-docs
 channels:
   - conda-forge
-  - defaults
 dependencies:
   - python=3.11
   - pydoc-markdown

readme.md

@@ -8,57 +8,71 @@
 
 ### purpose
 
-`lhorizon` helps you find things in the Solar System. It is built around a thick Python wrapper for the 
-Jet Propulsion Laboratory (JPL) [Horizons](https://ssd.jpl.nasa.gov/?horizons) service. _Horizons_, provided by JPL's
-Solar System Dynamics Group (SSD), is one of the only sources in the world that offers no-assembly-required 
-high-precision data on the relative positions and velocities of almost every known body in the Solar System. 
-`lhorizon` offers tools to query _Horizons_ for data, parse its responses into useful Python objects, and smoothly 
-incorporate them into bulk calculation and transformation workflows.
+`lhorizon` helps you find things in the Solar System. It is built around a thick 
+Python wrapper for the Jet Propulsion Laboratory (JPL) [Horizons](https://ssd.jpl.nasa.gov/?horizons) service,
+supplemented by some uses of the SPICE toolkit. _Horizons_, provided by JPL's 
+Solar System Dynamics Group (SSD), is one of the only sources in the world that 
+offers no-assembly-required high-precision data on the relative positions and 
+velocities of almost every known body in the Solar System. `lhorizon` offers 
+tools to query _Horizons_ for data, parse its responses into useful Python 
+objects, and smoothly incorporate them into bulk calculation and transformation 
+workflows.
 
 If you would a quick overview of major package functionality, 
 [you can try these example Notebooks on Binder.](https://mybinder.org/v2/gh/MillionConcepts/lhorizon/main?filepath=examples)
 
 ### origin
 
 `lhorizon` began as a fork of [astroquery.jplhorizons](https://github.com/astropy/astroquery/tree/master/astroquery/jplhorizons) 
-(originally written by Michael Mommert around 2016). We wrote it in order to circumvent a bug introduced to `jplhorizons` by 
-serverside changes at JPL that prevented it from correctly parsing queries involving target or observer locations given 
-in planetodetic coordinates, and more specifically to provide suppport for queries related to arbitrary locations on 
-the lunar surface. In the process, we extended it to implement a more efficient parser, add support for fast queries in 
-bulk, and remove the use of `astroquery` and `astropy` features (for both performance and API compatibility reasons). 
-At some point, we realized that a fast, standalone interface to Horizons might be useful to the community at large and 
-decided to polish it into a general-use package.
+(originally written by Michael Mommert around 2016). We wrote it in order to 
+circumvent a bug (since fixed) introduced to `jplhorizons` by serverside changes at JPL that 
+prevented it from correctly parsing queries involving target or observer locations given 
+in planetodetic coordinates, and more specifically to provide suppport for queries 
+related to arbitrary locations on the lunar surface. In the process, we extended 
+it to implement a more efficient parser, add support for fast queries in bulk, and 
+remove the use of `astroquery` and `astropy` features (for both performance and 
+API compatibility reasons). At some point, we realized that a fast, standalone 
+interface to Horizons might be useful to the community at large and decided to 
+polish it into a general-use package.
 
 ### pronunciation
 
-along the lines of "l'horizon" or "low-ree-zahn;" like "the horizon" in French, or the famous Palm Springs Desert 
-Modern hotel (an easy drive from Pasadena).
+along the lines of "l'horizon" or "low-ree-zahn;" like "the horizon" in French, 
+or the famous Palm Springs Desert Modern hotel (an easy drive from Pasadena).
 
 ## installation
 
 ### automated
 
-`lhorizon` is available on `conda-forge`, and we recommend installing it using the `conda` package manager: 
-`conda install -c conda-forge lhorizon`.
+`lhorizon` is available on `conda-forge`, and we recommend installing it using 
+the `conda` package manager: `conda install -c conda-forge lhorizon`.
 
-We do not test or officially support the use of non-`conda` environments for `lhorizon`, but it can also be installed from PyPi: 
-`pip install lhorizon`, or, if you'd like all the bells and whistles, `pip install lhorizon[target, examples, tests]`.
+We do not test or officially support the use of non-`conda` environments for 
+`lhorizon`, but it can also be installed from PyPi: `pip install lhorizon`, 
+or, if you'd like all the bells and whistles, `pip install lhorizon[target, examples, tests]`.
 
 ### manual
 
-If you'd like to install `lhorizon` by hand, we again recommend that you use `conda` to assemble a Python environment.
+If you'd like to install `lhorizon` by hand, we again recommend that you use 
+`conda` to assemble a Python environment.
 
-If you're already equipped with `conda`, you can create an environment (named "lhorizon") for this package by cloning this repository
-and running: `conda env create -f environment.yml` from the repository root directory. 
-(You could instead add its dependencies to an existing environment by running `conda env update -n existing_env -f environment.yml`). 
-Then, if you'd like`lhorizon` installed as a site package in this environment, activate the environment and run `pip install -e .`. 
+If you're already equipped with `conda`, you can create an environment (named 
+"lhorizon") for this package by cloning this repository and running: `conda 
+env create -f environment.yml` from the repository root directory. (You could 
+instead add its dependencies to an existing environment by running `conda env 
+update -n existing_env -f environment.yml`). Then, if you'd like`lhorizon` 
+installed as a site package in this environment, activate the environment and run 
+`pip install -e .`. 
 
-If you're new to `conda` or Python environment management in general, please take a look at our easy 
-[conda installation guide](docs/conda_installation_guide.md). 
+If you're new to `conda` or Python environment management in general, please 
+take a look at our easy [conda installation guide](docs/conda_installation_guide.md). 
 
 ### dependencies and requirements
 
-`lhorizon` requires Python >= 3.9 (there are no plans to implement support for older Python versions).
+`lhorizon` requires Python >= 3.11 (there are no plans to implement support 
+for older Python versions). A handful of feactures that rely on Horizons 
+capabilities only available through Telnet will not function on Python 3.13;
+finding a replacement for deprecated PSL Telnet functionality is planned.
 
 the following packages are required for usage / installation:
 * `more-itertools`
@@ -67,20 +81,23 @@ the following packages are required for usage / installation:
 * `requests`
 * `pyerfa`
 
-the following dependencies are optional and could potentially be omitted in restrictive install environments: 
+the following dependencies are optional and could potentially be omitted in 
+restrictive install environments: 
 * `jupyter` is only required to run examples
 * `pytest`, `pytest-cov`, and `pytest-mock` are only required to run tests
 * `spiceypy` and `sympy` are only required for `lhorizon.target` and related tests and examples
 
-Some features of `lhorizon` can be used without internet connectivity, but much of the library requires you to be able
-to dial out to the jpl.nasa.gov domain.
+Some features of `lhorizon` can be used without internet connectivity, but much of 
+the library requires you to be able to dial out to the jpl.nasa.gov domain.
 
-`lhorizon` should function in any OS supported by `conda`. The baseline system requirements are fairly light. 
-Counting dependencies and a base miniconda environment,`lhorizon` takes up about 2.6 GB of space. The respository itself
-is ~75 MB, almost all of which could be pruned in a restrictive install environment that did not require full `git` 
-history and the included SPICE kernels. Many uses of `lhorizon` are not resource-intensive and will run comfortably on 
-a small machine like an AWS EC2 t3a.micro instance. Conversely, resource requirements can scale as high as you like if 
-you are planning to process extremely large sets of geometry data.
+`lhorizon` should function in any OS supported by `conda`. The baseline system 
+requirements are fairly light. Counting dependencies and a base miniconda 
+environment,`lhorizon` takes up about 2.6 GB of space. The respository itself is 
+~75 MB, almost all of which could be pruned in a restrictive install environment 
+that did not require full `git` history and the included SPICE kernels. Many uses 
+of `lhorizon` are not resource-intensive and will run comfortably on a small machine 
+like an AWS EC2 t3a.micro instance. Conversely, resource requirements can scale as 
+high as you like if you are planning to process extremely large sets of geometry data.
 
 ## usage
 
@@ -99,6 +116,38 @@ running them can be found in [benchmarks/readme.md](benchmarks/readme.md)
 
 ## changelog
 
+* 2024-09-26
+  * updates for ephemerides changes
+  * updates to CI
+  * fixed environment issue with SPICE kernel loading
+* 2024-04-24:
+  * visibility flags now available in LHorizon.table() 
+  * dependency updates
+* 2024-02-26:
+  * assorted QoL improvements
+  * improved display of API errors
+  * handling for ass't OOB times including BCE dates
+  * updates for new ephemerides
+* 2023-12-16:
+  * improved table design
+  * updates to test for new ephemerides versions
+  * fixed a number of edge cases
+* 2023-07-12:
+  * time conversion improvements and optimizations
+  * updates to tests for new ephemerides
+  * various fixes for upstream changes
+  * optimizations for frame-of-reference transformations
+* 2022-12-10:
+  * package now uses new Horizons API endpoint
+  * type hint compatibility fixes
+* 2021-09-13:
+  * added assorted CI workflows
+  * improved interface for concatenated tables
+  * added nbviewer / binder hooks
+  * improved test coverage
+  * improved user-facing and in-code documentation
+  * fixed some edge cases in targeter
+  * added functionality to retrieve observer quantity codes
 * 2021-06-21: Full 1.0.0 release. Extensive changes from older versions:
   * completes and rationalizes interface 
   * concatenates and standardizes target submodule