This research was carried out by the researchers at Quantstamp funded by Quantstamp and the Ethereum Foundation Grant ID FY23-0922 (Evaluating Rollup Compression)
0.1.0. September 1, 2023.
- Roshan Palakkal, Blockchain Researcher @ Quantstamp, [email protected]
- Jan Gorzny, Ph.D., Head of L2 Scaling @ Quantstamp, [email protected]
- Martin Derka, Ph.D., Head of New Initiatives @ Quantstamp, [email protected]
The main code to run the analysis is in experiments.
Results, including generated charts are in results.
In optimism-decoder, there is a script that decodes Ethereum L1 appendSequencerBatch() transactions, which was used to collect the data for this project.
Sample data -- namely, a subset of the data used for the final results -- is available at the Evaluating Rollup Compression - Sample Data repository. Note that the full data is too large to be shared via GitHub.
To use it, you will need to initialize and update the data folder by running the following commands in the root of this repository:
git submodule init
git submodule update
Use the correct version of python: pyenv install 3.8.13.
Then, create a vitural environment:
pip3 install virtualenv
virtualenv .env
source .env/bin/activate
Then install the dependencies below, or all of them all at once: python3 -m pip install -r requirements.txt.
pip3 install brotli
pip3 install zstd
pip3 install eth_utils
pip3 install 'rlp==0.6.0'
pip3 install pandas
pip3 install matplotlib
The main entrypoint is experiments/experiment.py, which can be called by running python3 experiment.py run a1 or python3 experiment.py run a2, for approaches a1 and a2 described in the paper (as A1 and A2).
You can use python3 experiments/experiment.py results/a1_stats to generate the a1_stats plots (use a2_stats for the A2 plots) after the data has been generated.
You can use python3 experiments/plot_both_experiments.py to generate scatter plots with both A1 and A2 data.