def __init__(self, pipeline_screen, bundle_name, start_date, end_date, \ exchange_calendar="NYSE", data_frequency="daily"): self.pipeline_screen = pipeline_screen # aka universe self.bundle_name = bundle_name self.exchange_calendar = exchange_calendar self.data_frequency = data_frequency # Set start_date and end_date self.start_date = self.get_date(start_date) self.end_date = self.get_date(end_date) # Set environment variable 'ZIPLINE_ROOT' to the path where the most recent data is located # ZIPLINE_ROOT = ./udacity/ os.environ['ZIPLINE_ROOT'] = os.path.join(os.getcwd(), '..') print("ZIPLINE_ROOT set") # create ingest function self.ingest_func = csvdir_equities([data_frequency], bundle_name)
watchlists = ['All EQ Current & Past'], start_session = '1970-01-01', ) register_norgatedata_equities_bundle( bundlename = 'norgatedata-all-eq-dr', symbol_list = ['$SPXTR','$SPXTR1970','$SPXTR1936','$SPXATR','$SPXDTR','$SPXSTR','$SPXETR','$SPXFTR','$SPXITR','$SPXMTR','$SPXLTR','$SPXUTR','$SPXTTR','$SPXRTR'], watchlists = ['All EQ DR Current & Past'], start_session = '1970-01-01', ) import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities start_session = pd.Timestamp('1990-1-2', tz='utc') end_session = pd.Timestamp('2019-11-22', tz='utc') inputDirectory='F:/marketData/global_monitoring/premium/zipline/SP500/raw/' register( 'custom-sp500-bundle', csvdir_equities( ['daily'], inputDirectory, ), calendar_name='NYSE', # US equities start_session=start_session, )
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities start_session = pd.Timestamp('2016-01-04', tz='utc') end_session = pd.Timestamp('2099-01-01', tz='utc') register( 'hose', csvdir_equities( ['daily'], '/home/user/documents/project/csvdir', ), calendar_name='HOSE', # HOSE Vietnam start_session=start_session, end_session=end_session)
from zipline.data import bundles from zipline.pipeline import Pipeline from zipline.data.data_portal import DataPortal from zipline.utils.calendars import get_calendar from zipline.pipeline.data import USEquityPricing from zipline.data.bundles.csvdir import csvdir_equities from zipline.pipeline.factors import AverageDollarVolume from zipline.pipeline.engine import SimplePipelineEngine from zipline.pipeline.loaders import USEquityPricingLoader # Specify the bundle name bundle_name = 'm4-quiz-eod-quotemedia' # Create an ingest function ingest_func = csvdir_equities(['daily'], bundle_name) # Register the data bundle and its ingest function bundles.register(bundle_name, ingest_func) # Set environment variable 'ZIPLINE_ROOT' to the path where the most recent data is located os.environ['ZIPLINE_ROOT'] = os.path.join(os.getcwd(), '..', '..', 'data', 'module_4_quizzes_eod') # Load the data bundle bundle_data = bundles.load(bundle_name) # Create a screen for our Pipeline universe = AverageDollarVolume(window_length=120).top(500) # Create an empty Pipeline with the given screen
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities register( 'custom-stocks-csvdir-bundle', csvdir_equities( ['daily'], '/home/sustechcs/test/Backtest_MachineLearning/csv/stocks', ), calendar_name='NYSE', # US equities )
) # register 'tse' calendar register_calendar('TSE', TehranExchangeCalendar( start=start_session, end=end_session)) # register the bundle """ command: zipline ingest --bundle tse_stocks """ register( 'tse_stocks', # name we select for the bundle csvdir_equities( # name of the directory as specified above (named after data frequency) ['daily'], # path to directory containing the path ), calendar_name='TSE', start_session=start_session, end_session=end_session ) """ command: zipline ingest --bundle 'zipline_bundle_tehran_stocks' """ register('zipline_bundle_tehran_stocks', zipline_bundle_tehran_stocks.ingest, calendar_name='TSE') """ https://github.com/quantopian/zipline/issues/2018
# Specify the bundle name bundle_name = "eod-quotemedia" # Second, we need to register the data bundle and its ingest function with Zipline, using the `bundles.register()` function. The ingest function is responsible for loading the data into memory and passing it to a set of writer objects provided by Zipline to convert the data to Zipline’s internal format. Since the original Quotemedia data was contained in `.csv` files, we will use the `csvdir_equities()` function to generate the ingest function for our Quotemedia data bundle. In addition, since Quotemedia's `.csv` files contained daily stock data, we will set the time frame for our ingest function, to `daily`. # In[ ]: from zipline.data import bundles from zipline.data.bundles.csvdir import csvdir_equities # Create an ingest function ingest_func = csvdir_equities(["daily"], bundle_name) # Register the data bundle and its ingest function bundles.register(bundle_name, ingest_func) # Once our data bundle and ingest function are registered, we can load our data using the `bundles.load()` function. Since this function loads our previously ingested data, we need to set `ZIPLINE_ROOT` to the path of the most recent ingested data. The most recent data is located in the `cwd/../../data/project_4_eod/` directory, where `cwd` is the current working directory. We will specify this location using the `os.environ[]` command. # In[ ]: import os # Set environment variable 'ZIPLINE_ROOT' to the path where the most recent data is located os.environ["ZIPLINE_ROOT"] = os.path.join( os.getcwd(), "..", "..", "data", "project_4_eod"
# This script INGESTS the csv's in the directory "minute" # ... found at /csv_data , bound to the docker-image import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities CSVDIR = '/csv_data/' # Will ingest with this range # TODO: make a main() which accepts args to digest as desired # TODO: will have to move the csv's, or parameterize convert_csv.py, to match start_session = pd.Timestamp('2008-01-02', tz='utc') end_session = pd.Timestamp('2016-01-12', tz='utc') register('csv-bundle', csvdir_equities(['minute'], CSVDIR), start_session=start_session, end_session=end_session)
# Code added by Erol on 9/15/2020 to run my custom bundle using Polygon data # from zipline.data.bundles import register, stock_data # register('stock_data', stock_data.stock_data, calendar_name='NYSE') import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities # Set the start and end dates of the bars, should also align with the Trading Calendar start_session = pd.Timestamp('2005-1-3', tz='utc') end_session = pd.Timestamp('2020-10-26', tz='utc') register( 'custom-bundle', # What to call the new bundle csvdir_equities( ['daily'], # Are these daily or minute bars '/Users/erolaspromatis/Trading/Code/ZiplineBundle/data/csvs', # Directory where the formatted bar data is ), calendar_name='NYSE', # US equities default start_session=start_session, end_session=end_session) """ Some commandline reference code on ingesting and cleaning up data bundles zipline bundles zipline clean -b custom-csvdir-bundle --keep-last 1 zipline clean -b custom-csvdir-bundle --after 2020-10-1 zipline ingest -b test-csvdir """
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities start_session = pd.Timestamp('2009-5-20', tz='utc') end_session = pd.Timestamp('2020-5-15', tz='utc') register('eod-nifty500', csvdir_equities( ['daily'], 'AI-Alpha/data', ), calendar_name='XBOM', start_session=start_session, end_session=end_session)
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities #start_session = pd.Timestamp('1991-01-02', tz='utc') #end_session = pd.Timestamp('2017-12-29', tz='utc') start_session = pd.Timestamp('2014-01-28', tz='utc') end_session = pd.Timestamp('2014-02-07', tz='utc') register( 'csvdir', csvdir_equities( ["daily"], # '/Users/jonathan/devwork/misc_research/futures' '/Users/jonathan/devwork/misc_research/bug1_repro/data' ), start_session=start_session, end_session=end_session )
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities start_session = pd.Timestamp('2007-1-2', tz='utc') end_session = pd.Timestamp('2017-10-27', tz='utc') register( 'custom_history', csvdir_equities( ['minute'], '/home/kaiyan/Workspace/zipline/custom_history', ), calendar_name='CFX', start_session=start_session, end_session=end_session, minutes_per_day=24 * 60, )
calendar_name='CME', ) #register( # 'futures', # csvdir_futures( # 'daily', # '/Users/jonathan/devwork/pricing_data/CME_2018' # ), # calendar_name='CME', #) start_session = pd.Timestamp('1991-01-02', tz='utc') end_session = pd.Timestamp('2017-12-29', tz='utc') #start_session = pd.Timestamp('2014-01-28', tz='utc') #end_session = pd.Timestamp('2014-02-07', tz='utc') register( # 'csvdir', 'treasury-futures', csvdir_equities( ["daily"], '/Users/jonathan/devwork/misc_research/futures' ), start_session=start_session, end_session=end_session )
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities start_session = pd.Timestamp('2017-01-01 00:00:00', tz='utc') end_session = pd.Timestamp('2017-12-31 23:59:00', tz='utc') register( 'crypto-bundle', csvdir_equities( ['minute'], '/path/to/your/csvs', ), calendar_name='NYSE', # US equities start_session=start_session, end_session=end_session)
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities start_session = pd.Timestamp('2013-01-02', tz='UTC') end_session = pd.Timestamp('2018-07-03', tz='UTC') register( 'sharadar-pricing', csvdir_equities( ['daily'], '/Users/calmitchell/s/Springbok-filled/processed_data/pricing', ), calendar_name='NYSE', # US equities start_session=start_session, end_session=end_session )
from zipline.data.bundles import register from zipline.data.bundles.binance_api import api_to_bundle from zipline.data.bundles.binance_csv import csv_to_bundle from zipline.data.bundles.csvdir import csvdir_equities register( 'binance_api', api_to_bundle(interval='1d'), calendar_name='Binance', ) register( 'binance_csv', csv_to_bundle(reload_csv=False, interval='1d'), calendar_name='Binance', ) register('binance_test', csvdir_equities( ['minute'], '/home/bo/.zipline/custom_data', ), calendar_name='24/7')
# This file should be under zipline's folder to ingest customized data import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities start_session = pd.Timestamp('2018-1-1', tz='utc') end_session = pd.Timestamp('2021-1-10', tz='utc') register( 'victor-csvdir-bundle', csvdir_equities( ['daily'], 'C:/Users/16477/Desktop/zipline/dat', ), calendar_name='NYSE', start_session=start_session, end_session=end_session )
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities register( 'custom-currency-csvdir-bundle', csvdir_equities( ['minute'], '/home/sustechcs/test/Backtest_MachineLearning/csv/currency', ), calendar_name='24/7', #AlwaysOpenCalendar )
#!/usr/bin/env python # encoding: utf-8 #Created by Peter Bakker on 2017-10-04. #Copyright (c) 2017 . All rights reserved. import sys import os from zipline.data.bundles import register sys.path.append(os.path.dirname(__file__)) from zipline.data.bundles.csvdir import csvdir_equities os.environ['CSVDIR'] = "/root/data" register('csvdir',csvdir_equities(["daily"], "/root/data")) register('csvdirmin',csvdir_equities(["minute"], "/root/data"))
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities # zipline bundles # cp extension.py ~/.zipline/ # zipline ingest -b custom-csv-bundle start_session = pd.Timestamp('2012-1-3', tz='utc') end_session = pd.Timestamp('2014-12-31', tz='utc') register( 'custom-csv-bundle', csvdir_equities( ['daily'], '/Users/xiaoqingsong/py_study/zipline_demo/csvdir' ), calendar_name='XNYS', # US equities start_session=start_session, end_session=end_session )
import pandas as pd from trading_calendars import get_calendar from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities register('shanghai-equities-daily', csvdir_equities( ['daily'], '/home/china/data', ), calendar_name='XSHG')
import pandas as pd from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities # zipline bundles # cp extension.py ~/.zipline/ # zipline ingest -b custom-csv-bundle start_session = pd.Timestamp('2012-1-3', tz='utc') end_session = pd.Timestamp('2014-12-31', tz='utc') register( 'custom-csv-bundle', csvdir_equities( ['daily'], '/Users/U201811950/py_study/zipline_demo/csvdir' ), calendar_name='XNYS', # US equities start_session=start_session, end_session=end_session )
import six import pandas as pd from toolz import curry from zipline.data.bundles import register from zipline.data.bundles.csvdir import csvdir_equities from algotrade.backend.db.csv_cacher import bundler start_session = pd.Timestamp('1998-01-02', tz='utc') start_session1 = pd.Timestamp('2020-02-20', tz='utc') end_session = pd.Timestamp('2020-02-20', tz='utc') register( 'alphavantage-daily', csvdir_equities( ['daily'], '/mnt/c/Users/byron.LAPTOP-6A9A5QNU/Desktop/GitHub/algotrade/data', ), calendar_name='NYSE', start_session=start_session, end_session=end_session) register( 'alphavantage-intraday', bundler(), calendar_name='NYSE', ) def create_args(args, root): """ Encapsulates a set of custom command line arguments in key=value