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
