Carl Cervone

Towards a Pluralism Passport Built from DeSoc Legos

July 28, 2022

Since reading the DeSoc paper back in May, I’ve been fascinated with the concept of on-chain identity.

It started with exploring DAO voting records to identify wallets that were active in multiple DAOs and that were willing to make non-consensus votes more frequently than other token-holders.

I then went deep into POAP data, trying to isolate POAP farmers and events that tended to attract large numbers of farmers.

In July, I started contributing afterhours to Gitcoin’s Fraud Detection & Defense workstream. I expanded my research to a broader set of on-chain identity protocols. And I applied the research to a large dataset of Gitcoin Grants Round 14 contributors to see if on-chain, “DeSoc legos” could aide the DAO with Sybil detection and Gitcoin Passport trust scores.

Here is a write-up of the findings so far. It’s a lot of slides, though it’s full of colorful dataviz, so you can flick through them pretty fast.

I’ve also pushed a public version of the analysis to Gitcoin’s FDD repo, availabe here.

If you’re interested in conducting your own analysis, here are the APIs and some starter queries.

Sites

Some sample queries to get you started

In each of the cases below, substitute the $WALLETS field with a list of wallet addresses (0x…)

Lens Protocol

query Profiles {
  profiles(
    request: { 
        ownedBy: [$WALLETS], 
        limit: 50 
    }
  ) {
    items {
      id
      name
      ownedBy
      stats {
        totalFollowers
        totalFollowing
      }
    }
  }
}

POAP

query POAPs {
  accounts(
    where: {
      id_in: [$WALLETS]
    }
  ) {
    id
    tokensOwned
    tokens (first: 1000) {
      event {
        id
      }
    }
  }
}

Snapshot

query Votes {
  votes (
    first: 10000
    skip: 0
    where: {
      voter_in: [$WALLETS]
    }
  ) {
    id
    voter
    created
    proposal {
      id
    }
    choice
    space {
      id
    }
  }
}

Automating queries

Once you’ve configured your queries, here are some simple Python scripts for automating requests. Note: these scripts are fine for ad hoc analysis, not for building applications.

You’ll need to provide values for my_api_url, my_graphql_docstring and my_list_of_wallets.

Method 1: Using requests

str_list = ", ".join(f'"{w}"' for w in my_list_of_wallets)
query = my_graphql_docstring.replace("$WALLETS", str_list)
r = requests.post(my_api_url, json={"query": query})
json_data = json.loads(r.text)

Method 2: Using gql

This approach is better for more complex tasking and uses a Python GraphQL client (gql3).

Get the gql package here.

from gql import gql, Client
from gql.transport.requests import RequestsHTTPTransport
sample_transport=RequestsHTTPTransport(
    url=my_api_url,
    verify=True,
    retries=3,
)
client = Client(
    transport=sample_transport
)
str_list = ", ".join(f'"{w}"' for w in my_list_of_wallets)
query = my_graphql_docstring.replace("$WALLETS", str_list)
q = gql(my_graphql_docstring)
r = client.execute(q)
json_data = json.loads(r.text)