starlink-grpc-tools

This repository has a handful of tools for interacting with the gRPC service implemented on the Starlink user terminal (AKA "the dish").

For more information on what Starlink is, see starlink.com and/or the r/Starlink subreddit.

Prerequisites

Most of the scripts here are Python scripts. To use them, you will either need Python installed on your system or you can use the Docker image. If you use the Docker image, you can skip the rest of the prerequisites other than making sure the dish IP is reachable and Docker itself. For Linux systems, the python package from your distribution should be fine, as long as it is Python 3. The JSON script should actually work with Python 2.7, but the grpc scripts all require Python 3 (and Python 2.7 is past end-of-life, so is not recommended anyway).

parseJsonHistory.py operates on a JSON format data representation of the protocol buffer messages, such as that output by gRPCurl. The command lines below assume grpcurl is installed in the runtime PATH. If that's not the case, just substitute in the full path to the command.

All the tools that pull data from the dish expect to be able to reach it at the dish's fixed IP address of 192.168.100.1, as do the Starlink Android app, iOS app, and the browser app you can run directly from http://192.168.100.1. When using a router other than the one included with the Starlink installation kit, this usually requires some additional router configuration to make it work. That configuration is beyond the scope of this document, but if the Starlink app doesn't work on your home network, then neither will these scripts. That being said, you do not need the Starlink app installed to make use of these scripts.

The scripts that don't use grpcurl to pull data require the grpcio Python package at runtime and generating the necessary gRPC protocol code requires the grpcio-tools package. Information about how to install both can be found at https://grpc.io/docs/languages/python/quickstart/

The scripts that use MQTT for output require the paho-mqtt Python package. Information about how to install that can be found at https://www.eclipse.org/paho/index.php?page=clients/python/index.php

The scripts that use InfluxDB for output require the influxdb Python package. Information about how to install that can be found at https://github.com/influxdata/influxdb-python. Note that this is the (slightly) older version of the InfluxDB client Python module, not the InfluxDB 2.0 client. It can still be made to work with an InfluxDB 2.0 server, but doing so requires using influx v1 CLI commands on the server to map the 1.x username, password, and database names to their 2.0 equivalents.

Running the scripts within a Docker container requires Docker to be installed. Information about how to install that can be found at https://docs.docker.com/engine/install/

Usage

Of the 3 groups below, the grpc scripts are really the only ones being actively developed. The others are mostly by way of example of what could be done with the underlying data.

The JSON parser script

parseJsonHistory.py takes input from a file and writes its output to standard output. The easiest way to use it is to pipe the grpcurl command directly into it. For example:

grpcurl -plaintext -d {\"get_history\":{}} 192.168.100.1:9200 SpaceX.API.Device.Device/Handle | python parseJsonHistory.py

For more usage options, run:

python parseJsonHistory.py -h

When used as-is, parseJsonHistory.py will summarize packet loss information from the data the dish records. There's other bits of data in there, though, so that script (or more likely the parsing logic it uses, which now resides in starlink_json.py) could be used as a starting point or example of how to iterate through it. Most of the data displayed in the Statistics page of the Starlink app appears to come from this same get_history gRPC response. See the file get_history_notes.txt for some ramblings on how to interpret it.

The one bit of functionality this script has over the grpc scripts is that it supports capturing the grpcurl output to a file and reading from that, which may be useful if you're collecting data in one place but analyzing it in another. Otherwise, it's probably better to use dishHistoryStats.py, described below.

The grpc scripts

This set of scripts can do the gRPC communication directly, but they require some generated code to support the specific gRPC protocol messages used. These would normally be generated from .proto files that specify those messages, but to date (2020-Dec), SpaceX has not publicly released such files. The gRPC service running on the dish appears to have server reflection enabled, though. grpcurl can use that to extract a protoset file, and the protoc compiler can use that to make the necessary generated code:

grpcurl -plaintext -protoset-out dish.protoset 192.168.100.1:9200 describe SpaceX.API.Device.Device
mkdir src
cd src
python3 -m grpc_tools.protoc --descriptor_set_in=../dish.protoset --python_out=. --grpc_python_out=. spacex/api/device/device.proto
python3 -m grpc_tools.protoc --descriptor_set_in=../dish.protoset --python_out=. --grpc_python_out=. spacex/api/common/status/status.proto
python3 -m grpc_tools.protoc --descriptor_set_in=../dish.protoset --python_out=. --grpc_python_out=. spacex/api/device/command.proto
python3 -m grpc_tools.protoc --descriptor_set_in=../dish.protoset --python_out=. --grpc_python_out=. spacex/api/device/common.proto
python3 -m grpc_tools.protoc --descriptor_set_in=../dish.protoset --python_out=. --grpc_python_out=. spacex/api/device/dish.proto
python3 -m grpc_tools.protoc --descriptor_set_in=../dish.protoset --python_out=. --grpc_python_out=. spacex/api/device/wifi.proto
python3 -m grpc_tools.protoc --descriptor_set_in=../dish.protoset --python_out=. --grpc_python_out=. spacex/api/device/wifi_config.proto

Then move the resulting files to where the Python scripts can find them in the import path, such as in the same directory as the scripts themselves.

Once those are available, the dishHistoryStats.py script can be used in place of the grpcurl | parseJsonHistory.py pipeline, with most of the same command line options. For example:

python3 parseHistoryStats.py

By default, parseHistoryStats.py (and parseJsonHistory.py) will output the stats in CSV format. You can use the -v option to instead output in a (slightly) more human-readable format.

To collect and record summary stats at the top of every hour, you could put something like the following in your user crontab (assuming you have moved the scripts to ~/bin and made them executable):

00 * * * * [ -e ~/dishStats.csv ] || ~/bin/dishHistoryStats.py -H >~/dishStats.csv; ~/bin/dishHistoryStats.py >>~/dishStats.csv

dishHistoryInflux.py and dishHistoryMqtt.py are similar, but they send their output to an InfluxDB server and a MQTT broker, respectively. Run them with -h command line option for details on how to specify server and/or database options.

dishStatusCsv.py, dishStatusInflux.py, and dishStatusMqtt.py output the status data instead of history data, to various data backends. The information they pull is mostly what appears related to the dish in the Debug Data section of the Starlink app. As with the corresponding history scripts, run them with -h command line option for usage details.

By default, all of these scripts will pull data once, send it off to the specified data backend, and then exit. They can instead be made to run in a periodic loop by passing a -t option to specify loop interval, in seconds. For example, to capture status information to a InfluxDB server every 30 seconds, you could do something like this:

python3 dishStatusInflux.py -t 30 [... probably other args to specify server options ...] 

Some of the scripts (currently only the InfluxDB ones) also support specifying options through environment variables. See details in the scripts for the environment variables that map to options.

Other scripts

dishDumpStatus.py is a simple example of how to use the grpc modules (the ones generated by protoc, not starlink_grpc.py) directly. Just run it as:

python3 dishDumpStatus.py

and revel in copious amounts of dish status information. OK, maybe it's not as impressive as all that. This one is really just meant to be a starting point for real functionality to be added to it.

Possibly more simple examples to come, as the other scripts have started getting a bit complicated.

To Be Done (Maybe)

There are reboot and dish_stow requests in the Device protocol, too, so it should be trivial to write a command that initiates dish reboot and stow operations. These are easy enough to do with grpcurl, though, as there is no need to parse through the response data. For that matter, they're easy enough to do with the Starlink app.

Proper Python packaging, since some of the scripts are no longer self-contained.

Other Tidbits

The Starlink Android app actually uses port 9201 instead of 9200. Both appear to expose the same gRPC service, but the one on port 9201 uses an HTTP/1.1 wrapper, whereas the one on port 9200 uses HTTP/2.0, which is what most gRPC tools expect.

The Starlink router also exposes a gRPC service, on ports 9000 (HTTP/2.0) and 9001 (HTTP/1.1).

Docker for InfluxDB ( & MQTT under development )

Initialization of the container can be performed with the following command:

docker run -d -t --name='starlink-grpc-tools' -e INFLUXDB_HOST={InfluxDB Hostname} \
    -e INFLUXDB_PORT={Port, 8086 usually} \
    -e INFLUXDB_USER={Optional, InfluxDB Username} \
    -e INFLUXDB_PWD={Optional, InfluxDB Password} \
    -e INFLUXDB_DB={Pre-created DB name, starlinkstats works well} \
    neurocis/starlink-grpc-tools dishStatusInflux.py -v

The -t option to docker run will prevent Python from buffering the script's standard output and can be omitted if you don't care about seeing the verbose output in the container logs as soon as it is printed.

The dishStatusInflux.py -v is optional and omitting it will run same but not verbose, or you can replace it with one of the other scripts if you wish to run that instead, or use other command line options. There is also a GrafanaDashboard - Starlink Statistics.json which can be imported to get some charts like:

You'll probably want to run with the -t option to dishStatusInflux.py to collect status information periodically for this to be meaningful.