Add note about create-datadir to install instruction
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@ -200,8 +200,8 @@ If the day shows the same day, then the last candle can be assumed as incomplete
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To keep the jupyter notebooks aligned with the documentation, the following should be ran after updating a example notebook.
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``` bash
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jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace user_data/notebooks/strategy_analysis_example.ipynb
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jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to markdown user_data/notebooks/strategy_analysis_example.ipynb --stdout > docs/strategy_analysis_example.md
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jupyter nbconvert --ClearOutputPreprocessor.enabled=True --inplace freqtrade/templates/strategy_analysis_example.ipynb
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jupyter nbconvert --ClearOutputPreprocessor.enabled=True --to markdown freqtrade/templates/strategy_analysis_example.ipynb --stdout > docs/strategy_analysis_example.md
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```
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## Continuous integration
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@ -15,7 +15,7 @@ To learn how to get data for the pairs and exchange you're interrested in, head
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## Prepare Hyperopting
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Before we start digging into Hyperopt, we recommend you to take a look at
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the sample hyperopt file located in [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt.py).
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the sample hyperopt file located in [user_data/hyperopts/](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt.py).
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Configuring hyperopt is similar to writing your own strategy, and many tasks will be similar and a lot of code can be copied across from the strategy.
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@ -423,7 +423,7 @@ These ranges should be sufficient in most cases. The minutes in the steps (ROI d
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If you have the `generate_roi_table()` and `roi_space()` methods in your custom hyperopt file, remove them in order to utilize these adaptive ROI tables and the ROI hyperoptimization space generated by Freqtrade by default.
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Override the `roi_space()` method if you need components of the ROI tables to vary in other ranges. Override the `generate_roi_table()` and `roi_space()` methods and implement your own custom approach for generation of the ROI tables during hyperoptimization if you need a different structure of the ROI tables or other amount of rows (steps). A sample for these methods can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py).
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Override the `roi_space()` method if you need components of the ROI tables to vary in other ranges. Override the `generate_roi_table()` and `roi_space()` methods and implement your own custom approach for generation of the ROI tables during hyperoptimization if you need a different structure of the ROI tables or other amount of rows (steps). A sample for these methods can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
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### Understand Hyperopt Stoploss results
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@ -458,7 +458,7 @@ If you are optimizing stoploss values, Freqtrade creates the 'stoploss' optimiza
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If you have the `stoploss_space()` method in your custom hyperopt file, remove it in order to utilize Stoploss hyperoptimization space generated by Freqtrade by default.
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Override the `stoploss_space()` method and define the desired range in it if you need stoploss values to vary in other range during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/hyperopts/sample_hyperopt_advanced.py).
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Override the `stoploss_space()` method and define the desired range in it if you need stoploss values to vary in other range during hyperoptimization. A sample for this method can be found in [user_data/hyperopts/sample_hyperopt_advanced.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_hyperopt_advanced.py).
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### Validate backtesting results
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@ -162,7 +162,7 @@ Clone the git repository:
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```bash
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git clone https://github.com/freqtrade/freqtrade.git
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cd freqtrade
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```
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Optionally checkout the master branch to get the latest stable release:
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@ -171,22 +171,24 @@ Optionally checkout the master branch to get the latest stable release:
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git checkout master
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```
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#### 4. Initialize the configuration
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```bash
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cd freqtrade
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cp config.json.example config.json
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```
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> *To edit the config please refer to [Bot Configuration](configuration.md).*
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#### 5. Install python dependencies
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#### 4. Install python dependencies
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``` bash
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python3 -m pip install --upgrade pip
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python3 -m pip install -e .
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```
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#### 5. Initialize the configuration
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```bash
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# Initialize the user_directory
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freqtrade create-userdir --userdir user_data/
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cp config.json.example config.json
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```
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> *To edit the config please refer to [Bot Configuration](configuration.md).*
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#### 6. Run the Bot
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If this is the first time you run the bot, ensure you are running it in Dry-run `"dry_run": true,` otherwise it will start to buy and sell coins.
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@ -227,7 +229,7 @@ If that is not available on your system, feel free to try the instructions below
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Make sure to use 64bit Windows and 64bit Python to avoid problems with backtesting or hyperopt due to the memory constraints 32bit applications have under Windows.
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!!! Hint
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Using the [Anaconda Distribution](https://www.anaconda.com/distribution/) under Windows can greatly help with installation problems. Check out the [Conda section](#using-conda) in this document.
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Using the [Anaconda Distribution](https://www.anaconda.com/distribution/) under Windows can greatly help with installation problems. Check out the [Conda section](#using-conda) in this document for more information.
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#### Clone the git repository
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@ -48,7 +48,7 @@ Future versions will require this to be set.
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freqtrade trade --strategy AwesomeStrategy
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```
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**For the following section we will use the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py)
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**For the following section we will use the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py)
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file as reference.**
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!!! Note "Strategies and Backtesting"
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@ -114,7 +114,7 @@ def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame
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```
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!!! Note "Want more indicator examples?"
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Look into the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py).
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Look into the [user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py).
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Then uncomment indicators you need.
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### Strategy startup period
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@ -478,7 +478,7 @@ Printing more than a few rows is also possible (simply use `print(dataframe)` i
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### Where can i find a strategy template?
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The strategy template is located in the file
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[user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/user_data/strategies/sample_strategy.py).
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[user_data/strategies/sample_strategy.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py).
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### Specify custom strategy location
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