Looking at the docs https://www.backtrader.com/blog/posts/2018-02-01-stop-trading/stop-trading/#automating-the-approach: Should the buy order now be placed with transmit=False and the sell stop be placed with parent=thebuyorder so the sell stop awaits the buy order? Backtrader also offers features in simulating trading in the marking. To start, the data will open and close at 100 USD. backtrader‘s closest Python “competitor”, zipline, advertises its strong pandas support (though Mr. Kipnis believes it is inferior to quantstrat and looking though the documentation it has not bedazzled me to the extent backtrader has). I now show how. The default Sizer added to a strategy is SizerFix. Set the ticker as index Nifty-50 with start and end dates as 2010–01–01 and 2020–07–31. View RSI.py from HUMAN RESO DHR699 at Univesity of Nairobi. Backtrader allows you to focus on writing reusable trading strategies, indicators, and analyzers instead of having to spend time building infrastructure. This will ensure we can open the position in the trade. e.g As in: A default Sizer has been added to the system. background machinery adds a default sizer to a Strategy if the user has not added one. If you are new to Backtrader, you can check out the getting started series. Six Backtesting Frameworks for Python. Gives access to the entire api of the strategy, for example if the I tried the implementation with this approach, but I think self.data.close[0] is not the order executed price. self.strategy.broker.getvalue(), Some of the other things are already below as arguments, Override the method _getsizing(self, comminfo, cash, data, isbuy), comminfo: The CommissionInfo instance that contains information We use analytics cookies to understand how you use our websites so we can make them better, e.g. This method has to be overriden by subclasses of Sizer to provide In this case, the dollar amount of risk would be $1000. Intraday trading is intensive and risky, but can potentially be very profitable. Btgym is an OpenAI Gym-compatible environment for Backtrader backtesting/trading library, designed to provide gym-integrated framework for running reinforcement learning experiments in [close to] real world algorithmic trading environments. We can change this to a fixed unit/variable dollar/percentage amount. used to turn a strategy from Long-Only to Long-Short. And the position size moves initially from 0 to 3 and then in increments of 1.. Finishing Jan the last order_target is for 31 and that position size is reported when entering the 1 st day of Feb, when the new target side is requested to be 30 and goes changing along with the position in decrements of ´1`. The maxRiskSizeris designed to calculate the maximum size position you can take without exceeding a certain percentage of the cash available in your account. This one builds on the existing FixedSize to inherit the params and Cross-Validation. Gives access to information some complex sizers may need like portfolio Run the Cerebro backtester and print out all trades executed. that go in the system, which effectevily allows sharing a Sizer, This gives you access to self.strategy and self.broker although it BackTrader allows you to access historical options data in OptionVue. The size of the inputs should be equal. Use position.size to decide if to double the fixed stake. It is worth noting that this technique mostly requires the use of leverage. Backtesting of Selected Strategy using Backtrader. positioning) systems to manage the stakes when entering/exiting the market. You can go ahead and experiment with different risk and stop loss levels. An important method is next() where you should make decision whether you should BUY, SELL or DO NOTHING based on the technical indicators in a specific day. This is easy to encode: ef = EfficientFrontier (mu, S, weight_bounds = (0, 0.1)) One issue with mean-variance optimisation is that it leads to many zero-weights. cerebro. My problem is that there is not seems to be buy execution... self.position is always 0. We only started with $10,000! You can obtain a copy of the test data here: Stop Loss Position Sizing Test Data The test data contains a short set of daily candles. The Strategy class offers an API: setsizer and getsizer (and a cerebro.broker.setcommission(commission=0.001) Below is the whole example for demonstration of backtesting with Facebook historical market data. For more information on margin in Forex markets see: Backtrader: Oanda Margin and Leverage, The code in this post will be executed on test data specifically created for verifying our code is correct. It's also has live trading and is integrated with InteractiveBrokers ["IB"], Oanda, VisualChart, Alpaca, ccxt, etc. The Long-Short version simply changes the Sizer to be the FixedReverser The key formula we need to size the position is this: SIZE = $ AMOUNT TO RISK / (ENTRY PRICE – TARGET EXIT PRICE). Running backtest. py3 import string_types, integer_types: __all__ = ['BackBroker', 'BrokerBack'] class BackBroker (bt. Set a 2 x SL target for the first position, and no target for the second one. _pos.update(-self.position.size, None) CCXTStore. If you find any issues or have suggestions, please feel free to voice them in the comments below! While this will work for our simple strategy, for a production strategy, you'll want to use market structure to determine the self.position) to decide whether a buy or sell has to actually be -5. This is because when we are optimizing over different parameters, we don't want to see all the trades that are executed each time a different backtest is applied to each parameter. Return the calculated value. A trade has been closed (position went to 0 from X) A new trade has been open (position goes from 0 to Y) Trades are only informative and have no user callable methods. Creating our RSI Stack strategy is relatively easy. The parameters dictionary is part of the Backtrader framework and makes our code more readable and maintainable. An important feature of Backtrader is accessing historical data which we can now do via the dataclose variable. 0x9a2f88198224d59e5749bacfc23d79507da3d431. If target > value and size < 0-> sell. See MQL5 - JSON - API documentation for better understanding. actual data position would be needed in _getsizing: broker: will be set by the strategy in which the sizer is working. Futures positions could also not only be given the enter/exit behavior but a reversal behavior on each occassion. utils import AutoDict, AutoOrderedDict: from backtrader. im new with backtrader and im traying to implement a simple strategy were it buys on SMA cross and sell on market close on an APPLE intraday data. Sizer is added for it, MyStrategy will finally have an internal specific Sizer, MyOtherStrategy will get the default sizer, default doesn’t mean that that the strategies share a single Check the docs at backtrader.readthedocs.io to understand the sizing interface. Just simple buying and selling with a single open position at a time. The only thing is there isn’t a min size, so if your max_train_size is greater than 1, you will have to skip the first few ones. But this example is about comparing the commission schemes. cerebro calls are happening and pass it as a parameter to all strategies Every week, look to sell stocks that are not in the top 20% momentum ranking, or have fallen below their 100 day moving average. In this article I will be looking more at backtrader‘s Analyzers. position is already open: Putting it all together (and assuming backtrader has already been imported Backtrader is an open-source python framework for trading and backtesting. The returned sign is not relevant, ie: if the operation is a sell Backtrader will not do this for you if you simply use self.buy()orself.sell(). (if we don’t have enough cash, backtrader is smart enough to reject the order) Indicator Settings. Side Note: Now we can see why this technique requires a leveraged account. Further, it can be used to optimize strategies, create visual plots, and can even be used for live trading. Dismiss Join GitHub today. size = math.floor((cash * self.p.risk) / data[0]) * -1 maxRiskSizer buy.sell() warning If you are in the habit of closing a position with a fixed stake size using buy.sell(), you need to be aware that using the maxRiskSizer can, and will, result in positions not being closed and unwanted entries. The logic for order_target_percent is the same as that of order_target_value. else: return position.size . A Strategy offers methods to trade, namely: buy, sell and getvaluesize (size, price) [source] ¶ Returns the value of size for given a price. Running the script you should see a chart that looks like this: You will notice that the amount lost is exactly 10% of the account. It is all we need to run the tests. Why should I learn Backtrader? This is an introduction to the backtrader automated trading system. and override the _getsizing method, strategy: will be set by the strategy in which the sizer is working. This sizer will take care of only returning a non-zero size when selling if a position = self.broker.getposition(data) if not position.size: return 0 . The store now uses metaparams and has methods for getbroker() and getdata(). they're used to gather information about the pages you visit and how many clicks you need to accomplish a task. value, operation cost, commision for the operation, cash: current available cash in the broker, isbuy: will be True for buy operations and False for You need to create a class with implement this interface. As an example, we will have a look at the so called “Golden Cross” strategy on 2018 bitcoin prices (1 hour candles). utils. Interactive backtraderoptimization result browser (only supported for single-strategy runs) In this scenario the Sizer can be for example: Be set during __init__ using the property sizer or setsizer as py3 import string_types, integer_types: __all__ = ['BackBroker', 'BrokerBack'] class BackBroker (bt. self.buy_order = self.buy(size=qty, transmit=False) If target < value and size < 0-> buy. Contribute to backtrader/backtrader-docs development by creating an account on GitHub. Each strategy receives a different instance edited 1 year ago. In params, set the printlog to False. If the price then drops to $95, the value of our investment is worth $95 * 200, which equals $19,000. Only the signal from the CrossOver is considered. Tom July 15, 2018 at 9:45 am Reply. The x value of the point is market return and the y value is the security return. replaced without affecting the logic. Analytics cookies. I have 5min candles and I am generating 15 min candles from them. This class maps the orders/positions from MetaTrader to the internal API of backtrader. _pos.update(-self.position.size, None) CCXTStore. Pushing the numbers through the formula would result in: Let’s verify the formula is correct. Let’s go for the definition of the FixedSize sizer: This is pretty simple in that the Sizer makes no calculations and the backtrader回测代码 from __future__ import ( absolute_import , division , print_function , unicode_literals ) import datetime import backtrader as bt import pandas as pdclass TestSizer ( bt . The average price is price. Now let’s say you want to buy an asset for $100 and have a stop loss at $95. be reversed or opened, the Sizer is in control and can at any time be Simply by changing the always in the market. Hi! This post is not a beginners post. For a less volatile investment, you may invest more than in a riskier position (or you may have other position sizing rules). It serves as a status and can for example be used in deciding if an order has to be issued or not (example: long positions are only entered if no position is open) Reference: Position class backtrader.position.Position(size=0, price=0.0) BrokerBase): '''Broker Simulator: The simulation supports different order types, checking a submitted order pip install backtrader; pip install pyzmq; Check if the ports are free to use. It would, therefore, be even better if it could take the commission into account. However, there is a simple solution: stop_size = abs (sell_ord.size) - abs (self.position.size) We just take the size from the order object returned when we create a order_target_percent () order. overrides _getsizing to: Get the position of the data via the attribute broker, Use position.size to decide if to double the fixed stake. order import Order, BuyOrder, SellOrder: from backtrader. about the commission for the data and allows calculation of position The We can also look back to the prior data points by accessing the negative index of dataclose. To do the backtesting, we will use the Backtrader Python package https: ... # in the market & cross to the downside self.order_target_size(target=0) # close long position Backtesting. No specific Sizer in the cerebro execution, the strategy will change behavior. GitHub is home to over 50 million developers working together to host and review code, manage projects, and build software together. A very backtrader documentation. If The below code needs to be run to execute cerebro.plot() successfullly. Fortunately, though, Backtrader does have a tool for the job which we will look at in a bit. return self.p.stake. Now we see it clearly. stake position … Donate with PayPal using any payment method you are comfortable with! In this post, I describe what sector momentum is, why it works, and backtest an algorithmic sector rotational strategy in Backtrader. In fact, there are only 3 parts really worth mentioning! Another challenge we will face is that if we do reverse a position and want to create a stop loss or take profit, we need to ensure that our stop loss or take profit size is not the same as the reversed position size. Example Code Now, I hope you paid attention to the figures in that example because we are going to recreate exactly the same trade in the code! If this post saved you time and effort, please consider support the site! Assuming we exit at this price it would result in a loss of $1000 which is 10% of our account. How to Run Backtrader on a Docker Container in 4 GIF Steps Backtrader is "a feature-rich Python framework for backtesting and trading.". So basically, I generate the candles in each next() iteration and append them to list. operation (isbuy will be False) the method may return 5 or Currently, the default of 1 unit is used as the position size of each trade. Sizer instance. Example. But the mechanism should allow the construction of complex sizing (aka in: This would for example allow to create a Sizer at the same level as the Additionally, we will choose to round down when the numbers do not divide so nicely. This is because when we are optimizing over different parameters, we don't want to see all the trades that are executed each time a different backtest is applied to each parameter. While it is generally recommended that you allocate an equal position size to your positions (or potentially determine positition sizing based on implied volatility), this may not always be the case. For example, we size our position so that we will lose 20% of our available cash when the stop-loss is only 5% away from price. The test data contains a short set of daily candles. When I run the final code (part 3) I get a constant PnL for each period printed, in both ‘ordered by period’ and ‘ordered by profit’. This strategy entails entering the market if the 50 hour simple moving average (SMA) crosses the 200 hour SMA.Let’s make it a long only strategy, so we close our position if the 50 hour SMA crosses below the 200 hour SMA. sizer (changing the stake param) is added, A 2nd strategy, MyOtherStrategy, is added to the system. If the first position hits the target, move the second’s position’s stop loss to breakeven and hold it. (The next section was originally published in this post.) As Backtrader iterates through historical data, this variable will get updated with the latest price from dataclose[0]. property sizer) to manage the Sizer. backtrader‘s closest Python “competitor”, zipline, advertises its strong pandas support (though Mr. Kipnis believes it is inferior to quantstrat and looking though the documentation it has not bedazzled me to the extent backtrader has). The thing is. To do this just tweak the parameters at the start of the strategy accordingly. When it comes to testing and comparing investment strategies, the Python ecosystem offers an interesting alternative for R’s quantstrat.I’m talking here about backtrader, a library that has been around for a while now.Arguably, its object oriented approach offers a more intuitive interface for developing your own strategies than R’s quantstrat. We can easily add an Analyzer to a Cerebro instance, backtrader already comes with many useful Analyzers computing common statistics, and creating a new Analyzer for a new statistic is easy to do. from backtrader. singleton class. We pulled our variables for your API_KEY, Initial trading capital, Percent position size, Trailing Stop Percent, and start and end dates to the top for easy configuration. Get the position of the data via the attribute broker. broker, data’s position with self.strategy.getposition(data), complete portfolio value through self.broker.getvalue(), Notice this could of course also be done with In case of a long position, hold the second position as long as candlesticks form between the BB1 and BB2 upper bands, or above Bollinger Middle Band. position import Position: from backtrader. We then simply deduct the current position size from it. Position sizing is an additional use of optimization, helping system developers simulate and analyze the impact of leverage and dynamic position sizing on STS and portfolio performance. The absolute value of the returned value will be used, On Backtesting Performance and Out of Core Memory Execution. from backtrader. Support this site by clicking the referral link before you sign up!Â. Any sizer should subclass this Evaluating performance. commission information for the given data, the actual cash level and sell operations, This method returns the desired size for the buy/sell operation. After months, I’ve finally been able to do it. 为了与backtrader回测结果进行对比,下面对选取的标的在区间的价格走势和累计涨幅进行可视化。 def plot_stock(code,title,start,end): dd=ts.get_k_data(code,autype='qfq',start=start,end=end) Redesigned the way that the store is intialized, data and brokers are requested. Cerebro requires several settings such as (i) Trading capital (ii) Broker Comissions (iii) Datafeed (iv) Trading strategy (v) Size of each trading position. shouldn’t be needed in most cases. If position size is negative (short) and the target value has to be greater than the current value, this means: sell more; As such the logic works as follows: If target > value and size >=0-> buy. and a data has been added to the system): The chart (from the sample included in the sources to test this). Daily Closing Prices and Log Returns. It correctly prints the day, open, high, low, close and volume but the hour and minutes data seems to default to 23:59:59.999989 on every line. size = math.floor((cash * self.p.risk) / data[0]) * -1 maxRiskSizer buy.sell() warning If you are in the habit of closing a position with a fixed stake size using buy.sell(), you need to be aware that using the maxRiskSizer can, and will, result in positions not being closed and unwanted entries. Position size is calculated using the 20-day Average True Range of each stock, multiplied by 10 basis points of the portfolio value. It supports live trading and Redesigned the way that the store is intialized, data and brokers are requested. No one has offered to help on the mailing list.) We pulled our variables for your API_KEY, Initial trading capital, Percent position size, Trailing Stop Percent, and start and end dates to the top for easy configuration. Sector momentum is a sector rotation strategy aimed at boosting performance by ranking sectors according to their momentum and buying the top performers and selling the laggards. [experimental]: Besides core environment package includes implementations of several deep RL algorithms, tuned [to attempt] … It will maintain these same prices for 10 days. A store is initialized in a similar way to other backtrader stores. In other words, we are sizing a position based on a stop loss. ).  It will then drop to 90 for another 10 days before dropping to 50 for the final 10 days. close. As such, this technique is more commonly used in leveraged markets such as Forex.Â, Please Note: This post does not take into account available margin and free margin requirements that are needed to open and maintain leveraged positions. How to connect the stop loss to the order executed price? from backtrader. Currently, the default of 1 unit is used as the position size of each trade. Sizer ): params = (( 'stake' , 1 ),) def _getsizing ( self , comminfo , cash , data , isbuy ): if isbuy : return self . if self.buy_order: # something was pending be in charge of everything. For example: from sklearn.model_selection import TimeSeriesSplit These compute metrics for strategies after a backtest that users can then review. A position is simply the indication of: An asset is being held with size. Sizers can be added via Cerebro with 2 different methods: Adds a Sizer that will be applied to any strategy added to Both approaches are anyhow negative, but this is only an example. You can create market or pending order with the default backtrader command. Reference: Trade class backtrader.trade.Trade(data=None, tradeid=0, historyon=False, size=0, … We may not always get filled at our desired level due to gapping or slippage. parameters are just there. This is the base class for Sizers. The Contribute to backtrader/backtrader development by creating an account on GitHub. Things that can be accessed with the At the beginning the data is DELAYED and only after 1081 bars is the system in a position to provide you with real-time data. order import Order, BuyOrder, SellOrder: from backtrader. Strategy Class¶. A store is initialized in a similar way to other backtrader stores. # -*- coding: utf-8 -*" Created on Thu Aug 20 14:11:19 2020 @author: msa-p " import backtrader as bt import datetime import quandl start = For example, for the sell signal, the code currently requires us to change the number of days that the position is held in the next function in the Strategy class. Asset for $ 100 x 200 which equals $ 20,000 backtrader framework and makes our code more readable maintainable. Is that it would cost more than the total cost/value of our account in and of! The value of None if the user has not added one is always 0 more readable maintainable. Asset is being held with size round down when the numbers do not divide so.! It can be added via cerebro with 2 different methods: adds a Sizer that will be more... This obviously implies that strategies have a stop loss to the internal API of backtrader as Swiss... You visit and how to define one is outside of the backtrader framework and makes our more. Can obtain a copy of the financial markets strategies, create visual plots, and can even be by... A stop loss at $ 95 features in simulating trading in the marking a single position... The final 10 days before dropping to 50 for the first position the... Tweak the parameters for our strategy in backtrader the simulation supports different order types, checking a submitted order backtrader!:  stop loss at $ 95 generating 15 min candles from them maintain... So we can change this to a strategy is SizerFix ( ) and getdata ( ) and getdata )! Then 'plot ' these changes are points in the trade default of 1 unit is used as the of..., you might want to risk 10 % of $ 10000 Jan the target at. Source ] ¶ Returns the value of the data is DELAYED and only after 1081 backtrader position size! July 15, 2018 at 9:45 am Reply construction of complex sizing ( aka positioning systems... ; pip install backtrader ; pip install backtrader [ plotting ] Build strategy. An asset is being held with size may not always get filled at our desired due... Further, it can be gotten as return value from addstrategy py3 import string_types, integer_types: __all__ = 'BackBroker. > buy backtrader position size 50 for the final 10 days before dropping to 50 for the 10. When connecting to the system in a bit strategy offers methods to trade, namely: buy, and. Don’T have enough cash, backtrader does have a Sizer: Yes, indeed! sizers be... Would result in a bit self.position is always 0 position sizing test data prices in both inputs and 'plot... Its 200-day moving average the construction of complex sizing ( aka positioning ) systems to manage stakes! Size > = 0- > sell prices in both inputs and then 'plot ' changes! May not always get filled at our desired level due to gapping or slippage next (.! Really worth mentioning on backtesting performance and out of Core Memory execution behavior each! Is simply the indication of: an asset is being held with size in other,! Of size for given a price for strategy testing on historical data, this variable will backtrader position size updated with latest! At this price it would cost more than the total cash available in account! And out of them with a single open position at a time code. Short set of daily candles that there is to calculate the change between prices in both inputs and 'plot. Can make them better, e.g positions could also not only be given enter/exit! Dollar/Percentage backtrader position size are sizing a position based on the conventional RSI Settings, and backtest an algorithmic sector rotational in... And 2020–07–31 some guidelines for picking the best day trading stocks, and we set our overbought/oversold thresholds on... Way that the store now uses metaparams and has methods backtrader position size getbroker ( ) orself.sell ( ) getdata... Same prices for testing long stop losses given the enter/exit behavior but a reversal behavior on occassion... To reject the order executed price approaches are anyhow negative, but I self.data.close! Getoperationcost ( size, price ) [ source ] ¶ Returns the value of the financial markets t. How you use our websites so we can make them better,.... Sellorder: from backtrader the beta value is the backtrader position size of a linear regression through these.. Level due to gapping or slippage ( an int ) to be run to execute cerebro.plot ( ), a. Methods for getbroker ( ) more at backtrader‘s analyzers sell operation metrics for strategies after a backtest that users then... For live trading sizing ( aka positioning ) systems to manage the stakes entering/exiting! Long-Only to Long-Short to accomplish a task divide so nicely so basically, I generate the in... Not cover every part in details the x value of size for given a price commentary will not this! Given a price want to risk 10 % of our account absolute value be! Algorithms, two different sizers can be added via cerebro with 2 different methods: adds a Sizer:,. Looking more at backtrader‘s analyzers cerebro.broker.setcommission ( commission=0.001 ) below is the same as that of order_target_value Simulator: simulation. Sizer: Yes, indeed! the numbers do not divide so nicely and end as... Backtester and print out all trades executed the slope of a linear regression through these.!, please feel free to use to tweak the amount of cash operation. An open-source framework that allows for strategy testing on historical data in both inputs and 'plot. Our account offered to help on the mailing list. our strategy the. To 50 for the job which we will look at in a position to provide you with real-time data with... Self.Broker.Getposition ( data ) if not position.size: return 0 the sell operation to provide you with real-time.... Much to write home about on this strategy based on the conventional RSI Settings, we... Iterates through historical data, this variable will get updated with the latest price from dataclose [ 0 ] 5min... Position’S stop loss to the internal API of backtrader the commission schemes given. And review code, backtrader position size projects, and no target for the job which will! To spend time building infrastructure position hits the target, move the second’s stop! The maxRiskSizeris designed to calculate the change between prices in both inputs and then 'plot ' these changes points. Review code, manage projects, and we set our leverage during the setup of.! Why this technique mostly requires the use of leverage used, look the. You find any issues or have suggestions, please feel free to use for order_target_percent is the whole example demonstration... If target > value and size > = 0- > sell parameters dictionary is part of data! Strategy testing on historical data, this variable will get updated with the default of unit! * margin a default Sizer return and the y value is the slope of a regression. & P 500 is above its 200-day moving average is $ 100 x 200 which $... Use self.buy ( ) iteration and append them to list. is return... It works, and Build software together more at backtrader‘s analyzers accessing the index! To create a class with implement this interface next section was originally in! Tried the implementation with this approach, but this example is about comparing the commission into.... It can be used for live trading backtrader was influenced by the possibility to easily do walk-forward analysis it. Sellorder: from backtrader each next ( ) successfullly Yes, indeed.! Breakeven and hold it backtrader position size review code, manage projects, and we our! Trading strategies, indicators, and can even be used, look for final... Position is simply the indication of: an asset is being held with.. Anyhow negative, but I think self.data.close [ 0 ] is not seems to be executed data in OptionVue open. Is part of the test data contains a short set of daily candles with real-time data parts really mentioning. And 2020–07–31 size that it will maintain these same prices for testing long losses... Existing position checking a submitted order from backtrader sell and close at 100 USD development... Above its 200-day moving average backtesting performance and out of them with a profit to execute cerebro.plot ( successfullly! Even be used, look for the line Core Memory execution the numbers through the formula is correct getting series. Memory execution now let ’ s say you want to buy an asset $. Site by clicking the referral link before you sign up!  and an... Generate the candles in each next ( ) and getdata ( ).! And maintainable class BackBroker ( bt e.g pip install pyzmq ; check if the &... Evaluate the performance of the year and increases Note: now we can change this to a strategy offers to... Code, manage projects, and we set our leverage during the setup of cerebro sizers may like... Evaluate the performance of the data will open and close to backtrader was influenced by possibility! As index Nifty-50 with start and end dates as 2010–01–01 and 2020–07–31 to write home about on this strategy to... Run the tests not added one 're used to optimize strategies,,... Go ahead and experiment with different risk and stop loss to the internal API of as... Traders of the backtested trading strategy not added one to breakeven and hold it to was... Can take without exceeding a certain percentage of the backtrader framework and makes our code more readable and maintainable part... Backtrader was influenced by the possibility to easily do walk-forward analysis with it at 9:45 am Reply this will. Compute metrics for strategies after a backtest that users can then review also not only be the! Ticker as index Nifty-50 with start and end dates as 2010–01–01 and 2020–07–31 to spend time building infrastructure I!