Merge branch 'develop' into config-allow-comments

docs/bot-usage.md

@@ -59,8 +59,8 @@ working directory.
 
 The bot allows you to use multiple configuration files by specifying multiple
 `-c/--config` options in the command line. Configuration parameters
-defined in the last configuration file override parameters with the same name
-defined in the previous configuration file specified in the command line.
+defined in the latter configuration files override parameters with the same name
+defined in the previous configuration files specified in the command line earlier.
 
 For example, you can make a separate configuration file with your key and secrete
 for the Exchange you use for trading, specify default configuration file with
@@ -259,12 +259,13 @@ optional arguments:
   --continue            Continue hyperopt from previous runs. By default,
                         temporary files will be removed and hyperopt will
                         start from scratch.
-  --hyperopt-loss       NAME
-                        Specify the class name of the hyperopt loss function
+  --hyperopt-loss NAME  Specify the class name of the hyperopt loss function
                         class (IHyperOptLoss). Different functions can
                         generate completely different results, since the
-                        target for optimization is different. (default:
-                        `DefaultHyperOptLoss`).
+                        target for optimization is different. Built-in
+                        Hyperopt-loss-functions are: DefaultHyperOptLoss,
+                        OnlyProfitHyperOptLoss, SharpeHyperOptLoss.
+                        (default: `DefaultHyperOptLoss`).
 ```
 
 ## Edge commands

docs/data-analysis.md

@@ -31,6 +31,16 @@ df = load_trades_from_db("sqlite:///tradesv3.sqlite")
 df.groupby("pair")["sell_reason"].value_counts()
 ```
 
+### Load multiple configuration files
+
+This option can be usefull to inspect the results of passing in multiple configs in case of problems
+
+``` python
+from freqtrade.configuration import Configuration
+config = Configuration.from_files(["config1.json", "config2.json"])
+print(config)
+```
+
 ## Strategy debugging example
 
 Debugging a strategy can be time-consuming. FreqTrade offers helper functions to visualize raw data.

docs/developer.md

@@ -17,6 +17,29 @@ Alternatively (if your system is not supported by the setup.sh script), follow t
 
 This will install all required tools for development, including `pytest`, `flake8`, `mypy`, and `coveralls`.
 
+### Tests
+
+New code should be covered by basic unittests. Depending on the complexity of the feature, Reviewers may request more in-depth unittests.
+If necessary, the Freqtrade team can assist and give guidance with writing good tests (however please don't expect anyone to write the tests for you).
+
+#### Checking log content in tests
+
+Freqtrade uses 2 main methods to check log content in tests, `log_has()` and `log_has_re()` (to check using regex, in case of dynamic log-messages).
+These are available from `conftest.py` and can be imported in any test module.
+
+A sample check looks as follows:
+
+``` python
+from freqtrade.tests.conftest import log_has, log_has_re
+
+def test_method_to_test(caplog):
+    method_to_test()
+
+    assert log_has("This event happened", caplog)
+    # Check regex with trailing number ...
+    assert log_has_re(r"This dynamic event happened and produced \d+", caplog)
+```
+
 ## Modules
 
 ### Dynamic Pairlist

docs/hyperopt.md

@@ -164,7 +164,11 @@ By default, FreqTrade uses a loss function, which has been with freqtrade since
 A different loss function can be specified by using the `--hyperopt-loss <Class-name>` argument.
 This class should be in its own file within the `user_data/hyperopts/` directory.
 
-Currently, the following loss functions are builtin: `DefaultHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function), `SharpeHyperOptLoss` (optimizes Sharpe Ratio calculated on the trade returns) and `OnlyProfitHyperOptLoss` (which takes only amount of profit into consideration).
+Currently, the following loss functions are builtin:
+
+* `DefaultHyperOptLoss` (default legacy Freqtrade hyperoptimization loss function)
+* `OnlyProfitHyperOptLoss` (which takes only amount of profit into consideration)
+* `SharpeHyperOptLoss` (optimizes Sharpe Ratio calculated on the trade returns)
 
 ### Creating and using a custom loss function