Script for downloading tournament data

Tournament
2

Unfortunately roundDetails query doesn’t return the model correlation with Meta Model information. In case you need that too, you have to make use of v3UserProfile query, much less efficient, but this is the only way at the moment.

from numerapi import NumerAPI
import pandas as pd
import json

napi = NumerAPI(
    #    public_id='',
    #    secret_key='',
    verbosity="info")

START_ROUND = 300
END_ROUND = 333
TOURNAMENT = 8

query1 = """
  query($roundNumber: Int!, $tournament: Int!) {
    roundDetails (roundNumber: $roundNumber, tournament: $tournament) {
      roundNumber
      tournament
      roundTarget
      status
      totalStakes
      totalAtStake
      totalPayout
      payoutFactor
      models {
        modelName
      }
   }
}
"""

query2 = """
  query($modelName: String!) {
   v3UserProfile(modelName: $modelName) {
    roundModelPerformances {
      roundNumber
      roundPayoutFactor
      selectedStakeValue
      corr
      corrPercentile
      corrMultiplier
      corrWMetamodel
      fnc
      fncPercentile
      fncV3
      fncV3Percentile
      tc
      tcPercentile
      tcMultiplier
    }
   }
}
"""

rounds = []
modelNames = None

for round_num in range(START_ROUND, END_ROUND+1):

    arguments = {'roundNumber': round_num, 'tournament': TOURNAMENT}
    roundDetails = napi.raw_query(query1, arguments)['data']['roundDetails']

    r = {k: v for k, v in roundDetails.items() if k != 'models'}
    rounds.append(r)

    roundModelNames = set(m['modelName'] for m in roundDetails['models'])
    if modelNames is None:
        modelNames = roundModelNames
    else:
        #modelNames.update(roundModelNames)
        modelNames &= roundModelNames

    print(f"Round {round_num}: total names {len(modelNames)}")

pd.DataFrame(rounds).to_csv(f'round-details.csv', index=False)

data = []

for i,modelName in enumerate(modelNames):

    print(f"Model {modelName} {i}/{len(modelNames)}")

    arguments = {'modelName': modelName}
    perf = napi.raw_query(query2, arguments)['data']['v3UserProfile']

    perf = pd.DataFrame(perf['roundModelPerformances'])
    perf = perf[ (perf.roundNumber >= START_ROUND) & (perf.roundNumber <= END_ROUND) ]
    perf['modelName'] = modelName

    data.append(perf)

df = pd.concat(data).dropna(how='any')
pd.DataFrame(df).to_csv(f'round-{START_ROUND}-{END_ROUND}.csv', index=False)
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