Download in Bulk

To unlock local access to the US Equities dataset, open the Pricing page of your organization and subscribe to at least one of the following data packages:

• US Equity Daily History by AlgoSeek
• US Equity Hourly History by AlgoSeek
• US Equity Minute History by AlgoSeek
• US Equity Second History by AlgoSeek
• US Equity Tick History by AlgoSeek

If you don't already subscribe to the US Equity Security Master by QuantConnect data package, subscribe to it too. You need billing permissions to change the organization's subscriptions.

After you subscribe to local access, to download the US Equities data, follow these steps:

1. Log in to the Algorithm Lab.
2. On the CLI tab of the dataset listing, use the CLI Command Generator to generate your download command and then copy it.
3. Open a terminal in your organization workspace and then run the command from the CLI Command Generator.

To download the US Equity Security Master, run:

$ lean data download --dataset "US Equity Security Master"

After you bulk download the US Equities dataset, new daily updates are available at 7 AM Eastern Time (ET) after each trading day. To unlock local access to the data updates, open the Pricing page of your organization and subscribe to at least one of the following data packages:

• US Equity Daily Updates by AlgoSeek
• US Equity Hourly Updates by AlgoSeek
• US Equity Minute Updates by AlgoSeek
• US Equity Second Updates by AlgoSeek
• US Equity Tick Updates by AlgoSeek

You need billing permissions to change the organization's subscriptions.

After you subscribe to dataset updates, to update your local copy of the US Equities dataset, use the CLI Command Generator to generate your download command and then run it in a terminal in your organization workspace. Alternatively, instead of directly calling the lean data download command, you can place a Python script in the data directory of your organization workspace and run it to update your data files. The following example script updates all data resolutions:

import os
import pandas as pd
from datetime import datetime, time, timedelta
from pytz import timezone
from os.path import abspath, dirname
os.chdir(dirname(abspath(__file__)))

OVERWRITE = False

# Define a method to download the data
def __download_data(resolution, start=None, end=None):
    print(f"Updating {resolution} data...")
    command = f'lean data download --dataset "US Equities" --data-type "Bulk"  --resolution "{resolution}"'
    if start:
        end = end if end else start
        command += f" --start {start} --end {end}"
    if OVERWRITE:
        command += " --overwrite"
    print(command)
    os.system(command)

def __get_end_date() -> str:
    now = datetime.now(timezone("US/Eastern"))
    if now.time() > time(7,30):
        return (now - timedelta(1)).strftime("%Y%m%d")
    print('New data is available at 07:30 AM EST')
    return (now - timedelta(2)).strftime("%Y%m%d")

def __download_high_frequency_data(latest_on_cloud):
    for resolution in ["minute", "second", "tick"]:
        dir_name = f"equity/usa/{resolution}/spy".lower()
        if not os.path.exists(dir_name):
            __download_data(resolution, '19980101')
            continue
        latest_on_disk = sorted(os.listdir(dir_name))[-1].split('_')[0]
        if latest_on_disk >= latest_on_cloud:
            print(f"{resolution} data is already up to date.")
            continue
        __download_data(resolution, latest_on_disk, latest_on_cloud)

def __download_low_frequency_data(latest_on_cloud):
    for resolution in ["daily", "hour"]:
        file_name = f"equity/usa/{resolution}/spy.zip".lower()
        if not os.path.exists(file_name):
            __download_data(resolution)
            continue
        latest_on_disk = str(pd.read_csv(file_name, header=None)[0].iloc[-1])[:8]
        if latest_on_disk >= latest_on_cloud:
            print(f"{resolution} data is already up to date.")
            continue
        __download_data(resolution)

if __name__ == "__main__":
    latest_on_cloud = __get_end_date()
    __download_low_frequency_data(latest_on_cloud)
    __download_high_frequency_data(latest_on_cloud)

The preceding script checks the date of the most recent SPY data you have for all resolutions. If there is new data available for any of these resolutions, it downloads the new data files and overwrites your hourly and daily files. If you don't intend to download all resolutions, adjust this script to your needs.

To update your local copy of the US Equity Security Master, run:

$ lean data download --dataset "US Equity Security Master"

The following table shows the size and format of the US Equities dataset for each resolution:

For more information about the file format, see the Data / equity directory in the LEAN repository.

To view the prices of the datasets, see the Pricing tab of the US Equities and US Equity Security Master dataset listings.