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Rnumerai

R Interface to the Numerai Machine Learning Tournament API

This interface allows download of tournament data, submit predictions, get user information, stake NMR's and much more. Using the functions from this package end user can write R code to automate the whole procedure related to numerai tournament.

If you encounter a problem or have suggestions, feel free to open an issue.

Installation

  • For the latest development release:
devtools::install_github("Omni-Analytics-Group/Rnumerai")
  • For the latest stable release:
install.packages("Rnumerai")

Documentation Jump

Basic functions to perform tasks other than automating submissions

1. Load the package.

library(Rnumerai)

2. Set Public Key and Secret API key variables.

Get your public key and api key by going to numer.ai and then going to Custom API Keys section under your Account Tab. Select appropriate scopes to generate the key or select all scopes to use the full functionality of this package.

set_public_id("public_id_here")
set_api_key("api_key_here")

3. Get all information about your account

get_account()

3. Get all of your models in Main and Signal Tournament

  • For Main Tournament
get_models(tournament=8)
  • For Signals Tournament
get_models(tournament=11)

4. Get number of the current active round.

get_current_round()

5. Get info on rounds in Main and Signal Tournament

  • For Main Tournament
get_competitions(tournament=8)
  • For Signals Tournament
get_competitions(tournament=11)

6. Set Bio and Link Field for a Model Id

set_bio(model_id = get_models()[["bayo"]], bio = "This Model Rocks")
set_link(model_id = get_models()[["bayo"]], link = "https://www.google.com",link_text = "Google")

7. Get all transactions in your wallet.

wallet_transactions()

8. Set a model's submission webhook used in Numerai Compute.

set_submission_webhook(model_id = get_models()[["bayo"]], webhook = "..")

9. Fetch round's model performance of any user

  • For Main Tournament
round_model_performances(username = "bayo",tournament=8)
  • For Signals Tournament
round_model_performances(username = "bayo",tournament=11)

10. Fetch Daily model performance of any user

  • For Main Tournament
daily_model_performances(username = "bayo",tournament=8)
  • For Signals Tournament
daily_model_performances(username = "bayo",tournament=11)

11. Fetch Daily submission performance of any user

  • For Main Tournament
daily_submission_performances(username = "bayo",tournament=8)
  • For Signals Tournament
daily_submission_performances(username = "bayo",tournament=11)

12. Get Leaderboard

  • For Main Tournament
get_leaderboard(tournament=8)
  • For Signals Tournament
get_leaderboard(tournament=11)

13. Submission status of the last submission associated with the account

  • For Main Tournament
model_id = get_models(tournament=8)[["bayo"]]
submission_status(model_id = model_id, tournament=8)
  • For Signals Tournament
model_id = get_models(tournament=11)[["test5678"]]
submission_status(model_id = model_id, tournament=11)

14. Run a custom query

run_query(query = 'query{account{username}}', auth=TRUE)
run_query(query = 'query{rounds{number,closeTime}}', auth=FALSE)

Automatic submission using this package (Main Competition)

1. Load the package.

library(Rnumerai)

2. Set Public Key and Secret API key variables.

Get your public key and api key by going to numer.ai and then going to Custom API Keys section under your Account Tab. Select appropriate scopes to generate the key or select all scopes to use the full functionality of this package.

set_public_id("public_id_here")
set_api_key("api_key_here")

3. List the datasets for current round

list_datasets()

4A. For V2 Data (Released in late 2019), Download Train, Validation and Live data and submit predictions

  • Download
download_dataset("v2/numerai_datasets.zip", "numerai_datasets.zip")
download_dataset("v2/numerai_live_data.parquet", "numerai_live_data.parquet")
  • Load in R
unzip("numerai_datasets.zip",overwrite = TRUE, list = FALSE)
data_train <- read.csv("numerai_training_data.csv")
data_tournament <- read.csv("numerai_tournament_data.csv")
data_live <- data.table::setDT(arrow::read_parquet("numerai_live_data.parquet"))
  • Make Dummy Prediction and submit
predictions <- data.frame(id=data_live$id,prediction=sample(400:600,nrow(data_live),replace=TRUE)/1000)
upload_predictions(model_id = get_models()[["bayo"]],df=predictions)

4B. For V3 Data (Released in September of 2021), Download Train, Validation and Live data and submit predictions

  • Download
download_dataset("v3/numerai_training_data.parquet", "numerai_training_data.parquet")
download_dataset("v3/numerai_validation_data.parquet", "numerai_validation_data.parquet")
download_dataset("v3/numerai_live_data.parquet", "numerai_live_data.parquet")
download_dataset("v3/numerai_datasets.zip", "numerai_datasets.zip")
  • Load in R
data_train <- data.table::setDT(arrow::read_parquet("numerai_training_data.parquet"))
data_validation <- data.table::setDT(arrow::read_parquet("numerai_validation_data.parquet"))
data_live <- data.table::setDT(arrow::read_parquet("numerai_live_data.parquet"))
  • Make Dummy Prediction and submit
predictions <- data.frame(id=data_live$id,prediction=sample(400:600,nrow(data_live),replace=TRUE)/1000)
upload_predictions(model_id = get_models()[["bayo"]],df=predictions)
  • Make Dummy Diagnostics and submit
diagnostics <- data.frame(id=data_validation$id,prediction=sample(400:600,nrow(data_validation),replace=TRUE)/1000)
diagnostics_id <- upload_diagnostics(model_id = get_models()[["bayo"]],df=diagnostics)
diagnostics(model_id = get_models()[["bayo"]],diagnostics_id=diagnostics_id)

4C. For V4 Data (Released in April of 2022), Download Train, Validation and Live data and submit predictions

  • Download
download_dataset("v4/train.parquet", "train.parquet")
download_dataset("v4/validation.parquet", "validation.parquet")
download_dataset("v4/live.parquet", "live.parquet")
download_dataset("v4/live_example_preds.parquet", "live_example_preds.parquet")
download_dataset("v4/validation_example_preds.parquet", "validation_example_preds.parquet")
download_dataset("v4/features.json", "features.json")
  • Load in R
data_train <- data.table::setDT(arrow::read_parquet("train.parquet"))
data_validation <- data.table::setDT(arrow::read_parquet("validation.parquet"))
data_live <- data.table::setDT(arrow::read_parquet("live.parquet"))
  • Make Dummy Prediction and submit
predictions <- data.frame(id=data_live$id,prediction=sample(400:600,nrow(data_live),replace=TRUE)/1000)
upload_predictions(model_id = get_models()[["bayo"]],df=predictions)
  • Make Dummy Diagnostics and submit
diagnostic_preds <- data.frame(id=data_validation$id,prediction=sample(400:600,nrow(data_validation),replace=TRUE)/1000)
diagnostics_id <- upload_diagnostics(model_id = get_models()[["bayo"]],df=diagnostic_preds)
diagnostics(model_id = get_models()[["bayo"]],diagnostics_id=diagnostics_id)

5. Change your stake

  • Increase
stake_change(nmr=.01,action="increase",model_id = get_models()[["bayo"]])
  • Decrease
stake_change(nmr=.01,action="decrease",model_id = get_models()[["bayo"]])
  • Change Stake Type
set_stake_type(model_id = get_models()[["bayo"]],corr_multiplier=1,tc_multiplier=2,tournament=8)

Automatic submission using this package (Signals Competition)

1. Load the package.

library(Rnumerai)

2. Set Public Key and Secret API key variables.

Get your public key and api key by going to numer.ai and then going to Custom API Keys section under your Account Tab. Select appropriate scopes to generate the key or select all scopes to use the full functionality of this package.

set_public_id("public_id_here")
set_api_key("api_key_here")

3. Download the ticker universe.

tickers <- ticker_universe()

4. Make Dummy Predictions and submit

predictions <- cbind(tickers,signal = sample(400:600,nrow(tickers),replace=TRUE)/1000)
upload_predictions(model_id = get_models(tournament=11)[["test5678"]],df=predictions,tournament=11)

5. Make Dummy Diagnostics and submit

download_validation_data(file_path = "signals_historical_targets.csv")
data_validation <- read.csv("signals_historical_targets.csv")
data_validation <- data_validation[sample(1:nrow(data_validation),1000),1:3]
data_validation$data_type <- "validation"
diagnostic_preds <- cbind(data_validation,signal = sample(400:600,nrow(data_validation),replace=TRUE)/1000)
diagnostics_id <- upload_diagnostics(model_id = get_models(tournament=11)[["test5678"]],df=diagnostic_preds,tournament=11)
diagnostics(model_id = get_models(tournament=11)[["test5678"]],tournament=11,diagnostics_id=diagnostics_id)

6. Change your stake

  • Increase
stake_change(nmr=.01,action="increase",tournament=11,model_id = get_models(tournament=11)[["test5678"]])
  • Decrease
stake_change(nmr=.01,action="decrease",tournament=11,model_id = get_models(tournament=11)[["test5678"]])
  • Change Stake Type
set_stake_type(model_id = get_models(tournament=11)[["test5678"]],corr_multiplier=1,tc_multiplier=2,tournament=11)

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Version

Install

install.packages('Rnumerai')

Monthly Downloads

258

Version

3.0.1

License

GPL-3

Issues

1

Pull Requests

0

Stars

35

Forks

9

Maintainer

Eric Hare

Last Published

September 14th, 2022

Functions in Rnumerai (3.0.1)

set_public_id

Sets the Numerai Public ID
upload_diagnostics

Upload predictions to diagnostics from file.
submission_status

Submission status of the last submission associated with the account
wallet_transactions

Get all transactions in your wallet.
set_submission_webhook

Set a model's submission webhook used in Numerai Compute
stake_change

Change stake by `value` NMR
set_link

Set link field for a model id
ticker_universe

Fetch universe of accepted tickers
upload_predictions

Upload predictions from file.
daily_model_performances

Fetch Daily performance of any user
get_api_key

Gets the Numerai API key
get_competitions

Retrieves information about all rounds
download_dataset

Download specified file for the given round.
get_account

Get all information about your account
download_validation_data

Download CSV file with historical targets and ticker universe
daily_submission_performances

Fetch Daily Submission Performance of any user
get_current_round

Get number of the current active round.
get_leaderboard

Get the current leaderboard
diagnostics

Fetch results of diagnostics run
get_public_id

Gets the Numerai Public ID
set_bio

Set bio field for a model id
set_api_key

Sets the Numerai API key
set_stake_type

Change stake type by model
run_query

Run a custom query
get_models

Get mapping of account model names to model ids for convenience
list_datasets

List of available data files
round_model_performances

Fetch round model performance of any user