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Beamer Merkle-Drop

The Beamer Merkle-Drop is based on Trustlines Merkle-Drop, but with removed decaying balances.

Installation from git checkout

Please make sure you have the following requirements installed:

  • solidity compiler == v0.8.0
  • python == 3.8

Activate a fresh virtualenv and run make install. This will install the merkle-drop program. Please run merkle-drop --help to get an overview of available command line options. This document covers only a subset of the available options.

Compute the merkle root

The root subcommand computes the merkle root from a CSV file containing addresses and balances.

$ merkle-drop root airdrop.csv
0x5a7973598b5c9040bb842e4ff16c4685b4fd4bd1ac62645b9b844a9df35592d6

Example for airdrop.csv:

0xc2c543161A3B26DFb0a29a01c11351781Bff11F3,10000000000000000000
0xa1F7A26e4729de760D6074063F25054b4fA7bAb2,20000000000000000000
0x2147a30412206c6A39c7bf8aF10903020419024d,15000000000000000001
0xc8EC4CCa92AaA39B5dD24493670c63Dfb74D36e0,1500000000000000000
0x45eEC844d18f1dbeFD6Ac784552BC86f303BA07B,1800000000000000000

Please be aware that you need to specify balances with the full decimal count (i.e. in wei)

Running the backend server

The best way to start the backend server is to use gunicorn as a WSGI-container:

gunicorn -c config.py merkle_drop.server:app

The following config should be suitable.

Make sure that the correct airdrop.csv is present

import merkle_drop.server

bind = "0.0.0.0:8080"
airdrop_filename = "airdrop.csv"

workers = 4
max_requests = 500


def on_starting(server):
    merkle_drop.server.init_gunicorn_logging()
    merkle_drop.server.init_cors(origins="*")
    merkle_drop.server.init(
        airdrop_filename
    )

Generating a proof via GET request

With the server running, you can generate a proof by calling curl or http:

$ http http://localhost:8080/entitlement/0x00000000007F6202Ba718DF41ec639b32Dd7fBCF
HTTP/1.1 200 OK
Access-Control-Allow-Origin: *
Connection: close
Content-Length: 1471
Content-Type: application/json
Date: Thu, 30 Jan 2020 10:43:55 GMT
Server: gunicorn/19.9.0

{
    "address": "0x00000000007F6202Ba718DF41ec639b32Dd7fBCF",
    "tokens": "204385112839531052032",
    "proof": [
        "0x975abbe47f8637e8f048bf838f59d081162e5b549518a8f465385be9bf16102d",
        "0x28fac2c585927d7d7c1f43bdbc37aa8c561f1ad7e8b52466acb2f2ac7b11e4a5",
        "0x64c80aeb687d4d1a28600cfec22d0dbd4f3c3455cf0e4d6c2aaf8c1916769bc4",
        "0x4b848b4f810b2129913be0ae2e374abeecab72243cb98f361cb1c68d96f6cbe8",
        "0x100b182a927b2b4ddfb0ce959008d20dc71296b2610a125c82ca85acc286dad7",
        "0x28716fd1643fb3e7388d2494f36cf802292588d2cbd6d3170f99d80eeeb25b5e",
        "0xd762cf132b42da6a15c11ab7dd47cae5e3cb5dc4c260737535e88920b6f02209",
        "0x16070ef5fad1b3a0a1d8a05c5b023007aa7c2fa644ef858f2551f07c3816b8b1",
        "0xd0ac1aee8a660c0f4bd003f9afddb956819f75eb72064d1246f5ad4d9488b663",
        "0xa7022577eb35dbce83c3cf7d74a86394300211096fd3f55561f89a22108a1924",
        "0x317e02325e8f0bd9dec6afc4449fc4e0cb8bfbedfaa3dae02cc50640196252b3",
        "0x5c308d95607cce2091a2eca114d0b3964c7381e574ddbc24589ad812a9974735",
        "0x0f58b54296b8ab1b1c582308bb30fa0d2167b5aab94c30d95f785e4ab4d38b3b",
        "0xa171f84c30a2060c7430c5207d8cf8c24f6e5430e4f4c80db441c9d662aae426",
        "0x296cd18ee97193654eb82078de8d1d37d98ccb6cad261da7ae2593161bfa7455",
        "0x95bf1328bcae3de81d2ebe03069f447937d681d1caa25f788aec576b8b6203af",
        "0x2ea199528b5586a57124356972d412fe6e1f99356c716f2432204d6ad0d17f6a",
        "0x3567daef60454362d49a375347426f5e0b0cc5d914f57338a25a709cbcbb010d",
        "0x0fd54647afad0616b0d051eb8408349f525a1f8981809f963bd52ac0eb73d849"
    ]
}

Generating a proof via the command line

The proof subcommand can be used to generate a proof from the command line:

$ merkle-drop proof  0x00000000007F6202Ba718DF41ec639b32Dd7fBCF /path/to/merkle-drop-data/airdrop.csv
0x975abbe47f8637e8f048bf838f59d081162e5b549518a8f465385be9bf16102d 0x28fac2c585927d7d7c1f43bdbc37aa8c561f1ad7e8b52466acb2f2ac7b11e4a5 0x64c80aeb687d4d1a28600cfec22d0dbd4f3c3455cf0e4d6c2aaf8c1916769bc4 0x4b848b4f810b2129913be0ae2e374abeecab72243cb98f361cb1c68d96f6cbe8 0x100b182a927b2b4ddfb0ce959008d20dc71296b2610a125c82ca85acc286dad7 0x28716fd1643fb3e7388d2494f36cf802292588d2cbd6d3170f99d80eeeb25b5e 0xd762cf132b42da6a15c11ab7dd47cae5e3cb5dc4c260737535e88920b6f02209 0x16070ef5fad1b3a0a1d8a05c5b023007aa7c2fa644ef858f2551f07c3816b8b1 0xd0ac1aee8a660c0f4bd003f9afddb956819f75eb72064d1246f5ad4d9488b663 0xa7022577eb35dbce83c3cf7d74a86394300211096fd3f55561f89a22108a1924 0x317e02325e8f0bd9dec6afc4449fc4e0cb8bfbedfaa3dae02cc50640196252b3 0x5c308d95607cce2091a2eca114d0b3964c7381e574ddbc24589ad812a9974735 0x0f58b54296b8ab1b1c582308bb30fa0d2167b5aab94c30d95f785e4ab4d38b3b 0xa171f84c30a2060c7430c5207d8cf8c24f6e5430e4f4c80db441c9d662aae426 0x296cd18ee97193654eb82078de8d1d37d98ccb6cad261da7ae2593161bfa7455 0x95bf1328bcae3de81d2ebe03069f447937d681d1caa25f788aec576b8b6203af 0x2ea199528b5586a57124356972d412fe6e1f99356c716f2432204d6ad0d17f6a 0x3567daef60454362d49a375347426f5e0b0cc5d914f57338a25a709cbcbb010d 0x0fd54647afad0616b0d051eb8408349f525a1f8981809f963bd52ac0eb73d849

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