This repository has a handful of tools for interacting with the [gRPC](https://grpc.io/) service implemented on the Starlink user terminal (AKA "the dish").
For more information on what Starlink is, see [starlink.com](https://www.starlink.com/) and/or the [r/Starlink subreddit](https://www.reddit.com/r/Starlink/).
Most of the scripts here are [Python](https://www.python.org/) 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, version 3.7 or later.
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](https://play.google.com/store/apps/details?id=com.starlink.mobile), [iOS app](https://apps.apple.com/us/app/starlink/id1537177988), 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. See [here](https://github.com/starlink-community/knowledge-base/wiki#using-your-own-router) for more detail on this.
Running the scripts within a [Docker](https://www.docker.com/) container requires Docker to be installed. Information about how to install that can be found at https://docs.docker.com/engine/install/. See below for how to pull the starlink-grpc-tools container image.
The easiest way to get the Python modules used by the scripts is to do the following, which will install latest versions of a superset of the required modules:
If you really care about the details here or wish to minimize your package requirements, you can find more detail about which specific modules are required for what usage in [this Wiki article](https://github.com/sparky8512/starlink-grpc-tools/wiki/Python-Module-Dependencies).
This step is no longer required, nor is it particularly recommended, so the details have been moved to [this Wiki article](https://github.com/sparky8512/starlink-grpc-tools/wiki/gRPC-Protocol-Modules).
This step is only required if you want to use the `location` data group with the grpc scripts. Note that it will allow any device on your local (home) network to access the physical location (GPS) data for your dish. If you are not comfortable with that, then do not enable it.
Access to location data must be enabled per dish and currently (2022-Sep), this can only be done using the Starlink mobile app, version 2022.09.0 or later. It cannot be done using the browser app. To enable access, you must be logged in to your Starlink account. You can log in by pressing the user icon in the upper left corner of the main screen of the app. Once logged in, from the main screen, select SETTINGS, then select ADVANCED, then select DEBUG DATA. Scroll down and you should see a toggle switch for "allow access on local network" in a section labelled STARLINK LOCATION, which should be off by default. Turn that switch on to enable access or off to disable it. This may move in the future, and there is no guarantee the ability to enable this feature will remain in the app.
Note that the Starlink mobile app can be pretty finicky and painfully slow. It's best to wait for the screens to load completely before going on to the next one.
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.
This set of scripts includes `dish_grpc_text.py`, `dish_grpc_influx.py`, `dish_grpc_influx2.py`, `dish_grpc_sqlite.py`, `dish_grpc_mqtt.py`, and `dish_grpc_prometheus.py`. They mostly support the same functionality, but write their output in different ways. `dish_grpc_text.py` writes data to standard output, `dish_grpc_influx.py` and `dish_grpc_influx2.py` send it to an InfluxDB 1.x and 2.x server, respectively, `dish_grpc_sqlite.py` writes it to a sqlite database, and `dish_grpc_mqtt.py` sends it to a MQTT broker. `dish_grpc_prometheus.py` does not write anywhere but will listen for HTTP requests and
All these scripts support processing status data and/or history data in various modes. The status data is mostly what appears related to the dish in the Debug Data section of the Starlink app, whereas most of the data displayed in the Statistics page of the Starlink app comes from the history data. Specific status or history data groups can be selected by including their mode names on the command line. Run the scripts with `-h` command line option to get a list of available modes. See the documentation at the top of `starlink_grpc.py` for detail on what each of the fields means within each mode group.
By default, most 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:
The exception to this is `dish_grpc_prometheus.py`, for which the timing interval is determined by whatever is polling the HTTP page it exports.
Some of the scripts (currently only the InfluxDB and MQTT ones) also support specifying options through environment variables. See details in the scripts for the environment variables that map to options.
`dish_grpc_influx.py`, `dish_grpc_influx2.py`, `dish_grpc_sqlite.py`, and `dish_grpc_text.py` also support a bulk history mode that collects and writes the full second-by-second data instead of summary stats. To select bulk mode, use `bulk_history` for the mode argument. You'll probably also want to use the `-t` option to have it run in a loop.
A recent (as of 2021-Aug) change in the dish firmware appears to have reduced the amount of history data returned from the most recent 12 hours to the most recent 15 minutes, so if you are using the `-t` option to poll either bulk history or history-based statistics, you should choose an interval less than 900 seconds; otherwise, you will not capture all the data.
Computing history statistics (one or more of groups `ping_drop`, `ping_run_length`, `ping_latency`, `ping_loaded_latency`, and `usage`) across periods longer than the 15 minute history buffer may be done by combining the `-t` and `-o` options. The history data will be polled at the interval specified by the `-t` option, but it will be aggregated the number of times specified by the `-o` option and statistics will be computed against the aggregated data which will be a period of the `-t` option value times the `-o` option value. For example, the following:
```shell script
python3 dish_grpc_text.py -t 60 -o 60 ping_drop
```
will poll history data once per minute, but compute statistics only once per hour. This also reduces data loss due to a dish reboot, since the `-o` option will aggregate across reboots, too.
`dish_obstruction_map.py` is a little different in that it doesn't write to a database, but rather writes PNG images to the local filesystem. To get a single image of the current obstruction map using the default colors, you can do the following:
```shell script
python3 dish_obstruction_map.py obstructions.png
```
or to run in a loop writing a sequence of images once per hour, you can do the following:
`dish_control.sh` is a simple stand alone script that can issue reboot, stow, or unstow commands to the dish:
```shell script
python3 dish_control.py reboot
python3 dish_control.py stow
python3 dish_control.py unstow
```
These operations can also be done using `grpcurl`, thus avoiding the need to use Python or install the required Python module dependencies. See [here](https://github.com/sparky8512/starlink-grpc-tools/wiki/Useful-grpcurl-commands) for specific `grpcurl` commands for these operations.
`dish_json_text.py` operates on a JSON format data representation of the protocol buffer messages, such as that output by [gRPCurl](https://github.com/fullstorydev/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.
`dish_json_text.py` is similar to `dish_grpc_text.py`, but it takes JSON format input from a file instead of pulling it directly from the dish via grpc call. It also does not support the status info modes, because those are easy enough to interpret directly from the JSON data. The easiest way to use it is to pipe the `grpcurl` command directly into it. For example:
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 `dish_grpc_text.py`, described above.
`dump_dish_status.py` is a simple example of how to use the grpc modules (the ones generated by protoc, not `starlink_grpc`) directly. This script does require the [generated gRPC protocol modules](https://github.com/sparky8512/starlink-grpc-tools/wiki/gRPC-Protocol-Modules), contrary to the above recommendation against generating them. Once those are in place, just run as:
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. For a (relatively) simple example of using reflection to avoid the requirement to generate protocol modules, see `dish_control.py`.
`poll_history.py` is another silly example, but this one illustrates how to periodically poll the status and/or bulk history data using the `starlink_grpc` module's API. It's not really useful by itself, but if you really want to, you can run it as:
`extract_protoset.py` can be used in place of `grpcurl` for recording the dish protocol information. See [the related Wiki article](https://github.com/sparky8512/starlink-grpc-tools/wiki/gRPC-Protocol-Modules) for more details.
The supported docker image for this project is now the one hosted in the [GitHub Packages repository](https://github.com/sparky8512/starlink-grpc-tools/pkgs/container/starlink-grpc-tools/versions).
This will pull the image tagged as "latest". There should also be images for all recent tagged releases of this project, but those tend to be few and far between, so the most recent one will often be missing some important changes. See the package repository for a full list of tagged images.
You can run it with the following:
```shell script
docker run --name='starlink-grpc-tools' ghcr.io/sparky8512/starlink-grpc-tools <script_name>.py<scriptargs...>
```
For example, the following will print current status info and then exit:
```shell script
docker run --name='starlink-grpc-tools' ghcr.io/sparky8512/starlink-grpc-tools dish_grpc_text.py -v status alert_detail
```
Of course, you can change the name to whatever you want instead, and use other docker run options, as appropriate.
The default command is `dish_grpc_influx.py status alert_detail`, which is really only useful if you pass in environment variables with user and database info, such as:
```shell script
docker run --name='starlink-grpc-tools' -e INFLUXDB_HOST={InfluxDB Hostname} \
When running in the background, you will probably want to specify a `-t` script option, to run in a loop, otherwise it will exit right away and leave an inactive container. For example:
```shell script
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} \
ghcr.io/sparky8512/starlink-grpc-tools -v -t 60 status alert_detail
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.
If there is some problem with accessing the image from the GitHub Packages repository, there is also an image available on Docker Hub, which can be accessed as `neurocis/starlink-grpc-tools`, but note that that image may not be as up to date with changes as the supported one.
Several users have built dashboards for displaying data collected by the scripts in this project. Information on those can be found in [this Wiki article](https://github.com/sparky8512/starlink-grpc-tools/wiki/Dashboards). If you have one you would like to add, please feel free to edit the Wiki page to do so.
Note that feeding a dashboard will likely need the `-t` script option to `dish_grpc_influx.py` in order to collect status and/or history information periodically.
The [Wiki for this GitHub project](https://github.com/sparky8512/starlink-grpc-tools/wiki) has a little more information, and was originally planned to have more detail on some aspects of the history data, but that's mostly been obsoleted by changes to the gRPC service. It still may be updated some day with more use case examples or other information. In the mean time, it is configured as editable by anyone with a GitHub login, so if you have relevant content you believe to be useful, feel free to add it.
No further data collection functionality is planned at this time. If there's something you'd like to see added, please feel free to open a feature request issue. Bear in mind, though, that functionality will be limited to that which the Starlink gRPC services support. In general, those services are limited to what is required by the Starlink app, so unless the app has some related feature, it is unlikely the gRPC services will be sufficient to implement it in these tools.
[ChuckTSI's Better Than Nothing Web Interface](https://github.com/ChuckTSI/BetterThanNothingWebInterface) uses grpcurl and PHP to provide a spiffy web UI for some of the same data this project works on.
[starlink-cli](https://github.com/starlink-community/starlink-cli) is another command line tool for interacting with the Starlink gRPC services, including the one on the Starlink router, in case Go is more your thing.
