%global _empty_manifest_terminate_build 0 Name: python-numerapi Version: 2.14.0 Release: 1 Summary: Automatically download and upload data for the Numerai machine learning competition License: MIT License URL: https://github.com/uuazed/numerapi Source0: https://mirrors.nju.edu.cn/pypi/web/packages/16/f4/445ce1a9eb06c8528a13191c6728ac23b75ac2b8a4eb117a13e2682e9bec/numerapi-2.14.0.tar.gz BuildArch: noarch Requires: python3-requests Requires: python3-pytz Requires: python3-dateutil Requires: python3-tqdm Requires: python3-click Requires: python3-pandas %description [![Build Status](https://app.travis-ci.com/uuazed/numerapi.svg)](https://app.travis-ci.com/uuazed/numerapi) [![codecov](https://codecov.io/gh/uuazed/numerapi/branch/master/graph/badge.svg)](https://codecov.io/gh/uuazed/numerapi) [![PyPI](https://img.shields.io/pypi/v/numerapi.svg)](https://pypi.python.org/pypi/numerapi) [![Downloads](https://pepy.tech/badge/numerapi/month)](https://pepy.tech/project/numerapi) [![Docs](https://readthedocs.org/projects/numerapi/badge/?version=stable)](http://numerapi.readthedocs.io/en/stable/?badge=stable) [![Requirements Status](https://requires.io/github/uuazed/numerapi/requirements.svg?branch=master)](https://requires.io/github/uuazed/numerapi/requirements/?branch=master) # Numerai Python API Automatically download and upload data for the Numerai machine learning competition. This library is a Python client to the Numerai API. The interface is programmed in Python and allows downloading the training data, uploading predictions, and accessing user, submission and competitions information. It works for both, the main competition and the newer Numerai Signals competition. If you encounter a problem or have suggestions, feel free to open an issue. # Installation `pip install --upgrade numerapi` # Usage Numerapi can be used as a regular, importable Python module or from the command line. Some actions (like uploading predictions or staking) require a token to verify that it is really you interacting with Numerai's API. These tokens consists of a `public_id` and `secret_key`. Both can be obtained by login in to Numer.ai and going to Account -> Custom API Keys. Tokens can be passed to the Python module as parameters or you can be set via environment variables (`NUMERAI_PUBLIC_ID` and `NUMERAI_SECRET_KEY`). ## Python module ### Usage example - main competition import numerapi # some API calls do not require logging in napi = numerapi.NumerAPI(verbosity="info") # download current dataset => also check `https://numer.ai/data/v4` napi.download_dataset("v4/train.parquet", "train.parquet") # get current leaderboard leaderboard = napi.get_leaderboard() # check if a new round has started if napi.check_new_round(): print("new round has started within the last 12hours!") else: print("no new round within the last 12 hours") # provide api tokens example_public_id = "somepublicid" example_secret_key = "somesecretkey" napi = numerapi.NumerAPI(example_public_id, example_secret_key) # upload predictions model_id = napi.get_models()['uuazed'] napi.upload_predictions("preds.csv", model_id=model_id) # check submission status napi.submission_status(model_id) # increase your stake by 1.2 NMR napi.stake_increase(1.2) # convert results to a pandas dataframe import pandas as pd df = pd.DataFrame(napi.daily_user_performances("uuazed")) ### Usage example - Numerai Signals import numerapi napi = numerapi.SignalsAPI() # get current leaderboard leaderboard = napi.get_leaderboard() # setup API with api tokens example_public_id = "somepublicid" example_secret_key = "somesecretkey" napi = numerapi.SignalsAPI(example_public_id, example_secret_key) # upload predictions model_id = napi.get_models()['uuazed'] napi.upload_predictions("preds.csv", model_id=model_id) # get submission status and invalid tickers status = napi.submission_status(model_id) invalid_tickers = status['invalidTickers'] # get daily performance as pandas dataframe import pandas as pd df = pd.DataFrame(napi.daily_user_performances("uuazed")) # using the diagnostics tool napi.upload_diagnostics("preds.csv", model_id=model_id) # ... or using a pandas DataFrame directly napi.upload_diagnostics(df=df, model_id=model_id) # fetch results napi.diagnostic(model_id) ## Command line interface To get started with the cli interface, let's take a look at the help page: $ numerapi --help Usage: numerapi [OPTIONS] COMMAND [ARGS]... Wrapper around the Numerai API Options: --help Show this message and exit. Commands: account Get all information about your account! check-new-round Check if a new round has started within... competitions Retrieves information about all... current-round Get number of the current active round. daily-model-performances Fetch daily performance of a model. daily-submissions-performances Fetch daily performance of a user's... dataset-url Fetch url of the current dataset. download-dataset Download specified file for the given... download-dataset-old Download dataset for the current active... leaderboard Get the leaderboard. list-datasets List of available data files models Get map of account models! profile Fetch the public profile of a user. stake-decrease Decrease your stake by `value` NMR. stake-drain Completely remove your stake. stake-get Get stake value of a user. stake-increase Increase your stake by `value` NMR. submission-filenames Get filenames of your submissions submission-status checks the submission status submit Upload predictions from file. transactions List all your deposits and withdrawals. user Get all information about you!... version Installed numerapi version. Each command has it's own help page, for example: $ numerapi submit --help Usage: numerapi submit [OPTIONS] PATH Upload predictions from file. Options: --tournament INTEGER The ID of the tournament, defaults to 1 --model_id TEXT An account model UUID (required for accounts with multiple models --help Show this message and exit. # API Reference Checkout the [detailed API docs](http://numerapi.readthedocs.io/en/latest/api/numerapi.html#module-numerapi.numerapi) to learn about all available methods, parameters and returned values. %package -n python3-numerapi Summary: Automatically download and upload data for the Numerai machine learning competition Provides: python-numerapi BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip %description -n python3-numerapi [![Build Status](https://app.travis-ci.com/uuazed/numerapi.svg)](https://app.travis-ci.com/uuazed/numerapi) [![codecov](https://codecov.io/gh/uuazed/numerapi/branch/master/graph/badge.svg)](https://codecov.io/gh/uuazed/numerapi) [![PyPI](https://img.shields.io/pypi/v/numerapi.svg)](https://pypi.python.org/pypi/numerapi) [![Downloads](https://pepy.tech/badge/numerapi/month)](https://pepy.tech/project/numerapi) [![Docs](https://readthedocs.org/projects/numerapi/badge/?version=stable)](http://numerapi.readthedocs.io/en/stable/?badge=stable) [![Requirements Status](https://requires.io/github/uuazed/numerapi/requirements.svg?branch=master)](https://requires.io/github/uuazed/numerapi/requirements/?branch=master) # Numerai Python API Automatically download and upload data for the Numerai machine learning competition. This library is a Python client to the Numerai API. The interface is programmed in Python and allows downloading the training data, uploading predictions, and accessing user, submission and competitions information. It works for both, the main competition and the newer Numerai Signals competition. If you encounter a problem or have suggestions, feel free to open an issue. # Installation `pip install --upgrade numerapi` # Usage Numerapi can be used as a regular, importable Python module or from the command line. Some actions (like uploading predictions or staking) require a token to verify that it is really you interacting with Numerai's API. These tokens consists of a `public_id` and `secret_key`. Both can be obtained by login in to Numer.ai and going to Account -> Custom API Keys. Tokens can be passed to the Python module as parameters or you can be set via environment variables (`NUMERAI_PUBLIC_ID` and `NUMERAI_SECRET_KEY`). ## Python module ### Usage example - main competition import numerapi # some API calls do not require logging in napi = numerapi.NumerAPI(verbosity="info") # download current dataset => also check `https://numer.ai/data/v4` napi.download_dataset("v4/train.parquet", "train.parquet") # get current leaderboard leaderboard = napi.get_leaderboard() # check if a new round has started if napi.check_new_round(): print("new round has started within the last 12hours!") else: print("no new round within the last 12 hours") # provide api tokens example_public_id = "somepublicid" example_secret_key = "somesecretkey" napi = numerapi.NumerAPI(example_public_id, example_secret_key) # upload predictions model_id = napi.get_models()['uuazed'] napi.upload_predictions("preds.csv", model_id=model_id) # check submission status napi.submission_status(model_id) # increase your stake by 1.2 NMR napi.stake_increase(1.2) # convert results to a pandas dataframe import pandas as pd df = pd.DataFrame(napi.daily_user_performances("uuazed")) ### Usage example - Numerai Signals import numerapi napi = numerapi.SignalsAPI() # get current leaderboard leaderboard = napi.get_leaderboard() # setup API with api tokens example_public_id = "somepublicid" example_secret_key = "somesecretkey" napi = numerapi.SignalsAPI(example_public_id, example_secret_key) # upload predictions model_id = napi.get_models()['uuazed'] napi.upload_predictions("preds.csv", model_id=model_id) # get submission status and invalid tickers status = napi.submission_status(model_id) invalid_tickers = status['invalidTickers'] # get daily performance as pandas dataframe import pandas as pd df = pd.DataFrame(napi.daily_user_performances("uuazed")) # using the diagnostics tool napi.upload_diagnostics("preds.csv", model_id=model_id) # ... or using a pandas DataFrame directly napi.upload_diagnostics(df=df, model_id=model_id) # fetch results napi.diagnostic(model_id) ## Command line interface To get started with the cli interface, let's take a look at the help page: $ numerapi --help Usage: numerapi [OPTIONS] COMMAND [ARGS]... Wrapper around the Numerai API Options: --help Show this message and exit. Commands: account Get all information about your account! check-new-round Check if a new round has started within... competitions Retrieves information about all... current-round Get number of the current active round. daily-model-performances Fetch daily performance of a model. daily-submissions-performances Fetch daily performance of a user's... dataset-url Fetch url of the current dataset. download-dataset Download specified file for the given... download-dataset-old Download dataset for the current active... leaderboard Get the leaderboard. list-datasets List of available data files models Get map of account models! profile Fetch the public profile of a user. stake-decrease Decrease your stake by `value` NMR. stake-drain Completely remove your stake. stake-get Get stake value of a user. stake-increase Increase your stake by `value` NMR. submission-filenames Get filenames of your submissions submission-status checks the submission status submit Upload predictions from file. transactions List all your deposits and withdrawals. user Get all information about you!... version Installed numerapi version. Each command has it's own help page, for example: $ numerapi submit --help Usage: numerapi submit [OPTIONS] PATH Upload predictions from file. Options: --tournament INTEGER The ID of the tournament, defaults to 1 --model_id TEXT An account model UUID (required for accounts with multiple models --help Show this message and exit. # API Reference Checkout the [detailed API docs](http://numerapi.readthedocs.io/en/latest/api/numerapi.html#module-numerapi.numerapi) to learn about all available methods, parameters and returned values. %package help Summary: Development documents and examples for numerapi Provides: python3-numerapi-doc %description help [![Build Status](https://app.travis-ci.com/uuazed/numerapi.svg)](https://app.travis-ci.com/uuazed/numerapi) [![codecov](https://codecov.io/gh/uuazed/numerapi/branch/master/graph/badge.svg)](https://codecov.io/gh/uuazed/numerapi) [![PyPI](https://img.shields.io/pypi/v/numerapi.svg)](https://pypi.python.org/pypi/numerapi) [![Downloads](https://pepy.tech/badge/numerapi/month)](https://pepy.tech/project/numerapi) [![Docs](https://readthedocs.org/projects/numerapi/badge/?version=stable)](http://numerapi.readthedocs.io/en/stable/?badge=stable) [![Requirements Status](https://requires.io/github/uuazed/numerapi/requirements.svg?branch=master)](https://requires.io/github/uuazed/numerapi/requirements/?branch=master) # Numerai Python API Automatically download and upload data for the Numerai machine learning competition. This library is a Python client to the Numerai API. The interface is programmed in Python and allows downloading the training data, uploading predictions, and accessing user, submission and competitions information. It works for both, the main competition and the newer Numerai Signals competition. If you encounter a problem or have suggestions, feel free to open an issue. # Installation `pip install --upgrade numerapi` # Usage Numerapi can be used as a regular, importable Python module or from the command line. Some actions (like uploading predictions or staking) require a token to verify that it is really you interacting with Numerai's API. These tokens consists of a `public_id` and `secret_key`. Both can be obtained by login in to Numer.ai and going to Account -> Custom API Keys. Tokens can be passed to the Python module as parameters or you can be set via environment variables (`NUMERAI_PUBLIC_ID` and `NUMERAI_SECRET_KEY`). ## Python module ### Usage example - main competition import numerapi # some API calls do not require logging in napi = numerapi.NumerAPI(verbosity="info") # download current dataset => also check `https://numer.ai/data/v4` napi.download_dataset("v4/train.parquet", "train.parquet") # get current leaderboard leaderboard = napi.get_leaderboard() # check if a new round has started if napi.check_new_round(): print("new round has started within the last 12hours!") else: print("no new round within the last 12 hours") # provide api tokens example_public_id = "somepublicid" example_secret_key = "somesecretkey" napi = numerapi.NumerAPI(example_public_id, example_secret_key) # upload predictions model_id = napi.get_models()['uuazed'] napi.upload_predictions("preds.csv", model_id=model_id) # check submission status napi.submission_status(model_id) # increase your stake by 1.2 NMR napi.stake_increase(1.2) # convert results to a pandas dataframe import pandas as pd df = pd.DataFrame(napi.daily_user_performances("uuazed")) ### Usage example - Numerai Signals import numerapi napi = numerapi.SignalsAPI() # get current leaderboard leaderboard = napi.get_leaderboard() # setup API with api tokens example_public_id = "somepublicid" example_secret_key = "somesecretkey" napi = numerapi.SignalsAPI(example_public_id, example_secret_key) # upload predictions model_id = napi.get_models()['uuazed'] napi.upload_predictions("preds.csv", model_id=model_id) # get submission status and invalid tickers status = napi.submission_status(model_id) invalid_tickers = status['invalidTickers'] # get daily performance as pandas dataframe import pandas as pd df = pd.DataFrame(napi.daily_user_performances("uuazed")) # using the diagnostics tool napi.upload_diagnostics("preds.csv", model_id=model_id) # ... or using a pandas DataFrame directly napi.upload_diagnostics(df=df, model_id=model_id) # fetch results napi.diagnostic(model_id) ## Command line interface To get started with the cli interface, let's take a look at the help page: $ numerapi --help Usage: numerapi [OPTIONS] COMMAND [ARGS]... Wrapper around the Numerai API Options: --help Show this message and exit. Commands: account Get all information about your account! check-new-round Check if a new round has started within... competitions Retrieves information about all... current-round Get number of the current active round. daily-model-performances Fetch daily performance of a model. daily-submissions-performances Fetch daily performance of a user's... dataset-url Fetch url of the current dataset. download-dataset Download specified file for the given... download-dataset-old Download dataset for the current active... leaderboard Get the leaderboard. list-datasets List of available data files models Get map of account models! profile Fetch the public profile of a user. stake-decrease Decrease your stake by `value` NMR. stake-drain Completely remove your stake. stake-get Get stake value of a user. stake-increase Increase your stake by `value` NMR. submission-filenames Get filenames of your submissions submission-status checks the submission status submit Upload predictions from file. transactions List all your deposits and withdrawals. user Get all information about you!... version Installed numerapi version. Each command has it's own help page, for example: $ numerapi submit --help Usage: numerapi submit [OPTIONS] PATH Upload predictions from file. Options: --tournament INTEGER The ID of the tournament, defaults to 1 --model_id TEXT An account model UUID (required for accounts with multiple models --help Show this message and exit. # API Reference Checkout the [detailed API docs](http://numerapi.readthedocs.io/en/latest/api/numerapi.html#module-numerapi.numerapi) to learn about all available methods, parameters and returned values. %prep %autosetup -n numerapi-2.14.0 %build %py3_build %install %py3_install install -d -m755 %{buildroot}/%{_pkgdocdir} if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi pushd %{buildroot} if [ -d usr/lib ]; then find usr/lib -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "/%h/%f\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "/%h/%f\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "/%h/%f.gz\n" >> doclist.lst fi popd mv %{buildroot}/filelist.lst . mv %{buildroot}/doclist.lst . %files -n python3-numerapi -f filelist.lst %dir %{python3_sitelib}/* %files help -f doclist.lst %{_docdir}/* %changelog * Tue Apr 11 2023 Python_Bot - 2.14.0-1 - Package Spec generated