Hacky export of snark pool

connect-pool-state.py

# Get snark-jobs.json from mina advanced snark-job-list > snark-jobs.json
# Get snark-pool.json from mina advanced snark-pool-list > snark-pool.json

import json
import numpy as np
import pandas as pd

output = []

# Trees are indexed from 0
treeNumber = 0

with open('./snark-jobs.json') as json_file:
    data = json.load(json_file)

    for tree in data:
    
        for d in tree:

            # Is this a merge or base transaction SNARK work
            for key in d[1]:
                workType = key

            # Do we have any work for this slot?
            if d[1][workType] and workType == "B":
                # Base transactions just have a single work id
                workId = d[1][workType][0]["Work_id"]
                order = d[1][workType][1]
                status = d[1][workType][2]["Status"]
            elif d[1][workType] and workType == "M":
                # Merge transactions have two work ids
                workId = [d[1][workType][0]["Work_id"],d[1][workType][1]["Work_id"]]
                order = d[1][workType][2]
                status = d[1][workType][3]["Status"]
            else:
                workId = ""
                order = ""
                status = "Not used"

            # Format the output
            work = {
                "tree": treeNumber,
                "slot": d[0],
                "type": workType,
                "workId": workId,
                "order": order,
                "status": status,
                "fees": 0,
                "prover": "pending"
            }

            output.append(work)

        treeNumber += 1

    # Now append the fees
    with open('./snark-pool.json') as json_file:
        data = json.load(json_file)

        for work in output:
            
            if work["workId"]:

                # Merge proofs have multiple work ids so check first
                if work["type"] == "M":
                    workId = work["workId"][0]
                    #print(workId)
                else:
                    workId = work["workId"]

                # Is there matching work in the pool?
                for d in data:
                    if workId in d["work_ids"]:
                        work["fees"] = float(d["fee"])
                        work["prover"] = d["prover"]

with open('./data.json', 'w') as outfile:
    json.dump(output, outfile, indent=2)

df = pd.DataFrame(output)
#pd.set_option('display.max_rows', 150)
#pd.set_option('display.float_format', lambda x: '%.9f' % x)
todo = df[df.status=='Todo'].groupby(["fees", "prover"])["tree"].count()

print(todo)