joystream/analyses/fee-analysis/README.md

Fee analysis

This directory has a CLI to output the analysis of weights into a CSV and a more interactive notebook

Requirements

• python >= 3.9
• (virtualenv)[https://pypi.org/project/virtualenv/]

Steps to run

• virtualenv .venv
• source .venv/bin/activate
• pip install -r requirements.txt
• jupyter notebook
• a browser tab should launch with the files in this directory

To run the CLI

This CLI will output a CSV with the weights of the extrinsics given a file or directory with files that are output by the FRAME benchmarks. Furthermore, given the parameters in a configuration file it will calculate the token fees for the given weights.

Moreover, it can optionally try to estimate the price in fiat currency of the extrinsics given the total issuance of tokens in the system and the market cap.

• python analysis_cli --help will output the help

You will need to provide a path to a directory containing the weight files or the path to a single weight file.

By default the output will be in output.csv where the cli is run, to change this use the -o option.

For the CSV to include an analysis pass the parameter -p (Meaning the calculated price in tokens and prices)

The parameter configurations is found in config.json in the analysis_cli directory, you can change the file using the -c option.

The config file has the following form:

{
    "weight_coefficient": Number,
    "issuance": Number,
    "length_coefficient": Number,
    "min_market_cap": Number,
    "max_market_cap": Number,
    "lengths": {
        "<extrinsic_name>": Number
    },
    "params": {
        "<extrinsic_name>": {
            "i": Number,
            "j": Number,
            "k": Number,
            ...
        }
    }
}

Where:

• weight_coefficient: is the coefficient for converting a weight to a token fee, this can be found in runtime/src/constants.rs as part of the WeightToFeePolynomial implementation by WeightToFee.
• issuance: The total number of tokens available in the system, this is found in runtime/src/constants.rs as JOYS.
• length_coefficient: This is how much a byte of an extrinsic cost in number of tokens, this is found in runtime/src/constants.rs as TransactionByteFee.
• min_market_cap: This is the estimated minimum market cap of the token. This is only used when the dollar price of a extrinsics is calculated.
• max_market_cap: This is the estimated maximum market cap of the token. This is only used when the dollar price of a extrinsics is calculated.
• lengths: This is a dictionary containing <extrinsic_name>. This entries maps to a length in bytes for a given extrinsic. When calculating the token fee of an extrinsic this will be added over its weight fee using length_coefficient for the convertion. (It's specially important to set a length for runtime_upgrade since this extrinsic can easily take up to 3MB in size which will make a considerable part of its cost.
• params: This is a dictionary of dictionaries, each entry on the first level represent a different extrinsic with <extrinsic_name>. Each of these entries are a dictionary with <parameter> that represent a value of a parameter that will be used when calculating the weight of the extrinsic with its corresponding function.

Note that the <extrinsic_name> need its fully qualified path, e.g. proposals_discussion::add_post.

Currently the weight_coefficient and the length_coefficient is set to the same as the runtime.

Note: The output csv file already sums the EXTRINSIC_BASE_WEIGHT to the weight column

To run the notebook

• open main_notebook.ipynb
• The notebook has the information on how to proceed