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generate.py
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generate.py
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# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean CLI v1.0. Copyright 2021 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from datetime import datetime
from typing import Optional
from click import command, option, Choice, IntRange
from lean.click import DateParameter, LeanCommand, ensure_options
from lean.constants import DEFAULT_ENGINE_IMAGE
from lean.container import container
@command(cls=LeanCommand, requires_lean_config=True, requires_docker=True)
@option("--start",
type=DateParameter(),
required=True,
help="Start date for the data to generate in yyyyMMdd format")
@option("--end",
type=DateParameter(),
default=datetime.today().strftime("%Y%m%d"),
help="End date for the data to generate in yyyyMMdd format (defaults to today)")
@option("--symbol-count",
type=IntRange(min=0),
help="The number of symbols to generate data for")
@option("--tickers",
type=str,
required=False,
default="",
help="Comma separated list of tickers to use for generated data")
@option("--security-type",
type=Choice(["Equity", "Forex", "Cfd", "Future", "Crypto", "Option"], case_sensitive=False),
default="Equity",
help="The security type to generate data for (defaults to Equity)")
@option("--resolution",
type=Choice(["Tick", "Second", "Minute", "Hour", "Daily"], case_sensitive=False),
default="Minute",
help="The resolution of the generated data (defaults to Minute)")
@option("--data-density",
type=Choice(["Dense", "Sparse", "VerySparse"], case_sensitive=False),
default="Dense",
help="The density of the generated data (defaults to Dense)")
@option("--include-coarse",
type=bool,
default=True,
help="Whether coarse universe data should be generated for Equity data (defaults to True)")
@option("--market",
type=str,
default="",
help="The market to generate data for (defaults to standard market for the security type)")
@option("--quote-trade-ratio",
type=float,
default=1.0,
help="The ratio of generated quotes to generated trades. Values larger than 1 mean more quotes than "
"trades. Only used for Option, Future and Crypto (defaults to 1)")
@option("--random-seed",
type=IntRange(min=0),
default=None,
help="The random number generator seed. Defaults to None, which means no seed will be used")
@option("--ipo-percentage",
type=float,
default=5.0,
help="The probability each equity generated will have an IPO event. Note that this is not the total "
"probability for all symbols generated. Only used for Equity (defaults to 5.0)")
@option("--rename-percentage",
type=float,
default=30.0,
help="The probability each equity generated will have a rename event. Note that this is not the total "
"probability for all symbols generated. Only used for Equity (defaults to 30.0)")
@option("--splits-percentage",
type=float,
default=15.0,
help="The probability each equity generated will have a stock split event. Note that this is not the "
"total probability for all symbols generated. Only used for Equity (defaults to 15.0)")
@option("--dividends-percentage",
type=float,
default=60.0,
help="The probability each equity generated will have dividends. Note that this is not the probability "
"for all symbols genearted. Only used for Equity (defaults to 60.0)")
@option("--dividend-every-quarter-percentage",
type=float,
default=30.0,
help="The probability each equity generated will have a dividend event every quarter. Note that this is "
"not the total probability for all symbols generated. Only used for Equity (defaults to 30.0)")
@option("--option-price-engine",
type=str,
default="BaroneAdesiWhaleyApproximationEngine",
help="The stochastic process, and returns new pricing engine to run calculations for that option "
"(defaults to BaroneAdesiWhaleyApproximationEngine)")
@option("--volatility-model-resolution",
type=Choice(["Tick", "Second", "Minute", "Hour", "Daily"], case_sensitive=False),
default="Daily",
help="The volatility model period span (defaults to Daily)")
@option("--chain-symbol-count",
type=IntRange(min=0),
default=10,
help="The size of the option chain (defaults to 10)")
@option("--image",
type=str,
help=f"The LEAN engine image to use (defaults to {DEFAULT_ENGINE_IMAGE})")
@option("--update",
is_flag=True,
default=False,
help="Pull the LEAN engine image before running the generator")
def generate(start: datetime,
end: datetime,
symbol_count: Optional[int],
tickers: str,
security_type: str,
resolution: str,
data_density: str,
include_coarse: bool,
market: str,
quote_trade_ratio: float,
random_seed: Optional[int],
ipo_percentage: float,
rename_percentage: float,
splits_percentage: float,
dividends_percentage: float,
dividend_every_quarter_percentage: float,
option_price_engine: str,
volatility_model_resolution: str,
chain_symbol_count: int,
image: Optional[str],
update: bool) -> None:
"""Generate random market data.
\b
This uses the random data generator in LEAN to generate realistic market data using a Brownian motion model.
This generator supports the following security types, tick types and resolutions:
| Security type | Generated tick types | Supported resolutions |
| ------------- | -------------------- | ------------------------------------ |
| Equity | Trade | Tick, Second, Minute, Hour and Daily |
| Forex | Quote | Tick, Second, Minute, Hour and Daily |
| CFD | Quote | Tick, Second, Minute, Hour and Daily |
| Future | Trade and Quote | Tick, Second, Minute, Hour and Daily |
| Crypto | Trade and Quote | Tick, Second, Minute, Hour and Daily |
| Option | Trade and Quote | Minute |
\b
The following data densities are available:
- Dense: at least one data point per resolution step.
- Sparse: at least one data point per 5 resolution steps.
- VerySparse: at least one data point per 50 resolution steps.
\b
Example which generates minute data for 100 equity symbols since 2015-01-01:
$ lean data generate --start=20150101 --symbol-count=100
\b
Example which generates daily data for 100 crypto symbols since 2015-01-01:
$ lean data generate --start=20150101 --symbol-count=100 --security-type=Crypto --resolution=Daily
By default the official LEAN engine image is used.
You can override this using the --image option.
Alternatively you can set the default engine image for all commands using `lean config set engine-image <image>`.
"""
lean_config_manager = container.lean_config_manager
data_dir = lean_config_manager.get_data_directory()
entrypoint = ["dotnet", "QuantConnect.ToolBox.dll",
"--destination-dir", "/Lean/Data",
"--app", "randomdatagenerator",
"--start", start.strftime("%Y%m%d"),
"--end", end.strftime("%Y%m%d"),
"--security-type", security_type,
"--resolution", resolution,
"--data-density", data_density,
"--include-coarse", str(include_coarse).lower(),
"--market", market.lower(),
"--quote-trade-ratio", str(quote_trade_ratio),
"--ipo-percentage", str(ipo_percentage),
"--rename-percentage", str(rename_percentage),
"--splits-percentage", str(splits_percentage),
"--dividends-percentage", str(dividends_percentage),
"--dividend-every-quarter-percentage", str(dividend_every_quarter_percentage),
"--option-price-engine", option_price_engine,
"--volatility-model-resolution", volatility_model_resolution,
"--chain-symbol-count", str(chain_symbol_count)]
if tickers:
entrypoint.extend(["--tickers", tickers])
entrypoint.extend(["--symbol-count", str(len(tickers.split(",")))])
else:
ensure_options(["symbol_count"])
entrypoint.extend(["--symbol-count", str(symbol_count)])
if random_seed:
entrypoint.extend(["--random-seed", str(random_seed)])
run_options = {
"entrypoint": entrypoint,
"volumes": {
str(data_dir): {
"bind": "/Lean/Data",
"mode": "rw"
}
}
}
engine_image = container.cli_config_manager.get_engine_image(image)
container.update_manager.pull_docker_image_if_necessary(engine_image, update)
success = container.docker_manager.run_image(engine_image, **run_options)
if not success:
raise RuntimeError(
"Something went wrong while running the random data generator, see the logs above for more information")