Capture Points and RAAS lanes are automatically extracted from Squad maps.
If you spot any specific errors, please open an issue! That helps us get an overview.
See Captain's video to find out how to work with our official deployment at squadlanes.com.
In order to run your own instance of Squadlanes, you need to
- Extract the map images and layer data with our Python extraction scripts
- Package the static files with ParcelJS
- Deploy the static files to a web server, e.g., nginx
These tasks are futher explained in the following sections. We only provide a deployment guide for Linux systems. If you're using another operating system, then you're on your own.
Note that if you're trying to port this to a different operating system,
the umodel-squadlanes executable included in this repository is not from the
original UEViewer project but instead
from our own fork.
Our version behaves very differently and the original umodel executable will
not work for our use case.
You have to use our fork to build an executable for your operating system.
Even though we only need map layer data and map images, we're unpacking most of the game files, which will take up about 70 GiB of additional space. Make sure you have that available. You can change the config parameters in step 4 if you need to write to another drive.
- Install the following dependencies:
- Python 3.8 or compatible
- Poetry 1.1.5 or compatible
- Docker 20.10.5 or compatible
- Wine 6.9 or compatible
- Move into the extraction sub-project:
cd extraction - Install the virtual environment and dependencies with Poetry
# (Optional) Configure Poetry to create the virtual environment inside the project directory. # This will make sure the project stays self-contained. poetry config virtualenvs.in-project true poetry install
- Edit
extraction/squadlanes_extraction/config.py. You will probably have to change at least the required settings. - Unpack / decrypt the steam-distributed game files.
This can take a couple of minutes.
poetry run unpack
- Extract the full-size map images and layer data from the unpacked game files.
This should only take about a minute.
poetry run extract
- Split the full-size map images into smaller tiles for lazy loading.
poetry run tiles
- The map tiles are now in
dist/map-tilesif you're using the default config. The layer data was saved toextraction/raas-data-auto.yml. If you want to, you can make manual changes to the layer data. Once you're done, overwrite the existing file insrc/assets/raas-data.yaml. Note that instead of using the layer data you just generated, you can also just use the layer data included in this repository. The important part of this process is the extraction of the map tiles, which are too big (~1 GiB) to be included here.
If any of these steps don't seem to work, e.g., poetry run tiles finishes instantly but doesn't
actually produce any tiles, then open the config file, set LOG_LEVEL = "debug" and try again.
That should provide you with more verbose output.
If you want to deploy this locally to change the front-end files and test around, follow the "Development" instructions.
If you want to deploy this to a production server, follow the "Production" instructions.
- Run
yarn run start. - ParcelJS will now package the static files. This should only take a couple of seconds.
- The development server can now be reached at
http://localhost:1234/. Changing any files while the server is running will cause an automatic update. However, you might still need to hit F5 for some parts, e.g., changes to the map logic.
- Run
yarn run build. - ParcelJS will now package the static files. This can take a couple of minutes on your first run.
- The packaged static files are now in
dist/. - Upload the contents of
dist/into your server's webroot and make your web server return theindex.htmlthat you just uploaded.
If you want a nice and easy way to delta-upload your dist directory to your web server
with rsync, take a look at the deploy command in package.json and adjust that to
your needs.
Big parts of this project are in a somewhat unpolished and largely undocumented state. The front-end, especially the map logic, has good commenting and if you're familiar with graph algorithms you might be able to make sense of it.
The python data mining scripts, however, are very spaghetti at the moment.
We apologize for this but don't have specific plans to fix this in the immediate future.
If you want to contribute at this point in time, feel free to open issues and pull requests and we'll be happy to work with you.
Just be warned, it's probably a lot of work to get into it.
- Squad map backgrounds and capture point information were extracted from game files
shipped through Steam.
We hope our usage here is fine.
If it is not, please contact w4rum via email or
Discord DM (
Tim | w4rum#4344, reach me via https://discord.gg/aM5CYjnFxN) - Leaflet. Released under BSD 2-Clause "Simplified" License.
- Bootstrap. Copyright 2013-2020 Start Bootstrap LLC. Code released under the MIT license.
- This project relies on Konstantin Nosov's UEViewer. We use our own fork that we have modified slightly to better fit our use case. Code released under the MIT license.
- The original contributions found in this repository are released under AGPLv3 (see LICENSE).
- The favicons in
src/assets/faviconsare based on the Geo alt icon from Bootstrap Icons v1.9.1 licensed under the MIT License.