Merge pull request #2 from nullart/nullartHFT

Nullart HFT
2018-06-27 18:57:22 +08:00 · 2018-06-27 18:57:22 +08:00 · 1aa48f5f41
commit 1aa48f5f41
parent 882b30ef17 9f827979bd
88 changed files with 2572 additions and 1334 deletions
--- a/.coveragerc
+++ b/.coveragerc
@ -2,4 +2,5 @@
 omit =
    scripts/*
    freqtrade/tests/*
-    freqtrade/vendor/*
+    freqtrade/vendor/*
    freqtrade/__main__.py
--- a/.flake8
+++ b/.flake8
@ -0,0 +1,4 @@
 [flake8]
 ignore = E226,E302,E41,E126,F841
 max-line-length = 160
 exclude = */tests/*
--- a/.github/ISSUE_TEMPLATE.md
+++ b/.github/ISSUE_TEMPLATE.md
@ -6,10 +6,12 @@ If it hasn't been reported, please create a new issue.
 ## Step 2: Describe your environment
  * Python Version: _____ (`python -V`)
  * CCXT version: _____ (`pip freeze | grep ccxt`)
  * Branch: Master | Develop
  * Last Commit ID: _____ (`git log --format="%H" -n 1`)
- 
+  
 ## Step 3: Describe the problem:
 *Explain the problem you have encountered*
 ### Steps to reproduce:
--- a/.gitignore
+++ b/.gitignore
@ -6,7 +6,6 @@ config*.json
 .hyperopt
 logfile.txt
 hyperopt_trials.pickle
 user_data/
 freqtrade-plot.html
 freqtrade-profit-plot.html
@ -27,8 +26,8 @@ dist/
 downloads/
 eggs/
 .eggs/
-lib/
+#lib/
-lib64/
+#lib64/
 parts/
 sdist/
 var/
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@ -42,6 +42,11 @@ pip3.6 install flake8 coveralls
 flake8 freqtrade
 ```
 We receive a lot of code that fails the `flake8` checks.
 To help with that, we encourage you to install the git pre-commit 
 hook that will warn you when you try to commit code that fails these checks. 
 Guide for installing them is [here](http://flake8.pycqa.org/en/latest/user/using-hooks.html).
 ## 3. Test if all type-hints are correct
 **Install packages** (If not already installed)
--- a/2
+++ b/2
@ -1,7 +1,7 @@
 FROM python:3.6.5-slim-stretch
 # Install TA-lib
-RUN apt-get update && apt-get -y install curl build-essential && apt-get clean
+RUN apt-get update && apt-get -y install curl build-essential git && apt-get clean
 RUN curl -L http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz | \
  tar xzvf - && \
  cd ta-lib && \
--- a/README.md
+++ b/README.md
@ -1,10 +1,20 @@
 # freqtrade
-[![Build Status](https://travis-ci.org/freqtrade/freqtrade.svg?branch=develop)](https://travis-ci.org/freqtrade/freqtrade)
+[![Build Status](https://travis-ci.org/berlinguyinca/freqtrade.svg?branch=develop)](https://travis-ci.org/freqtrade/freqtrade)
-[![Coverage Status](https://coveralls.io/repos/github/freqtrade/freqtrade/badge.svg?branch=develop&service=github)](https://coveralls.io/github/freqtrade/freqtrade?branch=develop)
+[![Coverage Status](https://coveralls.io/repos/github/berlinguyinca/freqtrade/badge.svg?branch=wohlgemuth)](https://coveralls.io/github/berlinguyinca/freqtrade?branch=wohlgemuth)
-[![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/freqtrade/freqtrade/maintainability)
+[![Maintainability](https://api.codeclimate.com/v1/badges/5737e6d668200b7518ff/maintainability)](https://codeclimate.com/github/berlinguyinca/freqtrade/maintainability)
 ## First of all, this is a fork!
 Basically I required a lot more features than the awesome default freqtrade version has to offer and since pull requests always take longer than exspected or the standard disagreements. I decided to maintain on main branch for my changes, called wohlgemuth, which is incidentally my last name and have a ton of little branches, with added features.
 This basically allows people to use my version, or to easily merge changes into their forks or make PR's against the main repo, which is the best of both works.
 This reminds of the Torvalds kernel vs the Cox kernel...
 ## Back to what this is actually about
 Simple High frequency trading bot for crypto currencies designed to 
 support multi exchanges and be controlled via Telegram.
@ -25,12 +35,12 @@ hesitate to read the source code and understand the mechanism of this bot.
 ## Table of Contents
 - [Features](#features)
 - [Quick start](#quick-start)
- [Documentations](https://github.com/freqtrade/freqtrade/blob/develop/docs/index.md)
+- [Documentations](docs/index.md)
-   - [Installation](https://github.com/freqtrade/freqtrade/blob/develop/docs/installation.md)
+   - [Installation](docs/installation.md)
-   - [Configuration](https://github.com/freqtrade/freqtrade/blob/develop/docs/configuration.md)
+   - [Configuration](docs/configuration.md)
-   - [Strategy Optimization](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-optimization.md)
+   - [Strategy Optimization](docs/bot-optimization.md)
-   - [Backtesting](https://github.com/freqtrade/freqtrade/blob/develop/docs/backtesting.md)
+   - [Backtesting](docs/backtesting.md)
-   - [Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md)
+   - [Hyperopt](docs/hyperopt.md)
 - [Support](#support)
   - [Help](#help--slack)
   - [Bugs](#bugs--issues)
@ -44,11 +54,8 @@ hesitate to read the source code and understand the mechanism of this bot.
    - [Software requirements](#software-requirements)
 ## Branches
-The project is currently setup in two main branches:
+
- `develop` - This branch has often new features, but might also cause 
+if you like to use this fork, I highly recommend to utilize the 'wohlgemuth' branch, since this is the most stable. It will be synced against the original development branch and be enriched with all my changes.
 breaking changes.
 - `master` - This branch contains the latest stable release. The bot 
 'should' be stable on this branch, and is generally well tested. 
 ## Features
 - [x] **Based on Python 3.6+**: For botting on any operating system - 
@ -65,6 +72,30 @@ strategy parameters with real exchange data.
 - [x] **Daily summary of profit/loss**: Provide a daily summary of your profit/loss.
 - [x] **Performance status report**: Provide a performance status of your current trades.
 ### Additional features in this branch
 #### Strategy:
 - [x] loading strategies from Base64 encoded data in the config file
 - [x] loading strategies from urls
 - [x] trailing stop loss
 #### Others:
 - [x] more indicators
 - [x] more telegram features
 - [x] advanced plotting
 - [x] [using book orders for buy and/or sell](docs/configuration.md) 
 - [x] [separated unfilled orders timeout](docs/configuration.md) 
 - [x] [option to disable buying](docs/configuration.md) 
 - [x] [option to get a buy price based on %](docs/configuration.md) 
 ### Drawbacks
 - [x] not as good documentation
 - [x] maybe a bug here or there I haven't fixed yet
 ### Exchange marketplaces supported
 - [X] [Bittrex](https://bittrex.com/)
 - [X] [Binance](https://www.binance.com/)
@ -73,7 +104,7 @@ strategy parameters with real exchange data.
 ## Quick start
 This quick start section is a very short explanation on how to test the 
 bot in dry-run. We invite you to read the 
-[bot documentation](https://github.com/freqtrade/freqtrade/blob/develop/docs/index.md) 
+[bot documentation](docs/index.md) 
 to ensure you understand how the bot is working.
 ### Easy installation
@ -109,26 +140,26 @@ For any questions not covered by the documentation or for further
 information about the bot, we encourage you to join our slack channel.
 - [Click here to join Slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/enQtMjQ5NTM0OTYzMzY3LWMxYzE3M2MxNDdjMGM3ZTYwNzFjMGIwZGRjNTc3ZGU3MGE3NzdmZGMwNmU3NDM5ZTNmM2Y3NjRiNzk4NmM4OGE).
-### [Bugs / Issues](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue)
+### [Bugs / Issues](issues?q=is%3Aissue)
 If you discover a bug in the bot, please 
-[search our issue tracker](https://github.com/freqtrade/freqtrade/issues?q=is%3Aissue) 
+[search our issue tracker](issues?q=is%3Aissue) 
 first. If it hasn't been reported, please 
-[create a new issue](https://github.com/freqtrade/freqtrade/issues/new) and 
+[create a new issue](issues/new) and 
 ensure you follow the template guide so that our team can assist you as 
 quickly as possible.
-### [Feature Requests](https://github.com/freqtrade/freqtrade/labels/enhancement)
+### [Feature Requests](labels/enhancement)
 Have you a great idea to improve the bot you want to share? Please,
-first search if this feature was not [already discussed](https://github.com/freqtrade/freqtrade/labels/enhancement).
+first search if this feature was not [already discussed](labels/enhancement).
 If it hasn't been requested, please 
-[create a new request](https://github.com/freqtrade/freqtrade/issues/new) 
+[create a new request](issues/new) 
 and ensure you follow the template guide so that it does not get lost 
 in the bug reports.
-### [Pull Requests](https://github.com/freqtrade/freqtrade/pulls)
+### [Pull Requests](pulls)
 Feel like our bot is missing a feature? We welcome your pull requests! 
 Please read our 
-[Contributing document](https://github.com/freqtrade/freqtrade/blob/develop/CONTRIBUTING.md)
+[Contributing document](develop/CONTRIBUTING.md)
 to understand the requirements before sending your pull-requests. 
 **Important:** Always create your PR against the `develop` branch, not 
@ -171,14 +202,14 @@ optional arguments:
                        only if dry_run is enabled.
 ```
 More details on:
- [How to run the bot](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#bot-commands)
+- [How to run the bot](docs/bot-usage.md#bot-commands)
- [How to use Backtesting](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#backtesting-commands)
+- [How to use Backtesting](docs/bot-usage.md#backtesting-commands)
- [How to use Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/bot-usage.md#hyperopt-commands)
+- [How to use Hyperopt](docs/bot-usage.md#hyperopt-commands)
 ### Telegram RPC commands
 Telegram is not mandatory. However, this is a great way to control your
 bot. More details on our 
-[documentation](https://github.com/freqtrade/freqtrade/blob/develop/docs/index.md)
+[documentation](develop/docs/index.md)
 - `/start`: Starts the trader
 - `/stop`: Stops the trader
--- a/config.json.example
+++ b/config.json.example
@ -5,11 +5,24 @@
    "fiat_display_currency": "USD",
    "ticker_interval" : "5m",
    "dry_run": false,
-    "unfilledtimeout": 600,
+    "disable_buy" : false,
    "unfilledtimeout": {
        "buy":10,
        "sell":30
    }
    "trailing_stop": {
        "positive" : 0.005
    },
    "bid_strategy": {
        "ask_last_balance": 0.0,
-        "use_book_order": true,
+        "use_book_order": false,
-        "book_order_top": 6
+        "book_order_top": 6,
        "percent_from_top": 0
    },
    "ask_strategy":{
        "use_book_order": false,
        "book_order_min": 1,
        "book_order_max": 30
    },
    "exchange": {
        "name": "bittrex",
@ -33,7 +46,8 @@
    },
    "experimental": {
        "use_sell_signal": false,
-        "sell_profit_only": false
+        "sell_profit_only": false,
        "sell_fullfilled_at_roi": false
    },
    "telegram": {
        "enabled": true,
--- a/config_full.json.example
+++ b/config_full.json.example
@ -4,7 +4,9 @@
    "stake_amount": 0.05,
    "fiat_display_currency": "USD",
    "dry_run": false,
    "disable_buy" : false,
    "ticker_interval": "5m",
    "trailing_stop": true,
    "minimal_roi": {
        "40":  0.0,
        "30":  0.01,
@ -12,11 +14,20 @@
        "0":  0.04
    },
    "stoploss": -0.10,
-    "unfilledtimeout": 600,
+    "unfilledtimeout": {
        "buy":10,
        "sell":30
    }
    "bid_strategy": {
        "ask_last_balance": 0.0,
-        "use_book_order": true,
+        "use_book_order": false,
-        "book_order_top": 6
+        "book_order_top": 6,
        "percent_from_top": 0
    },
    "ask_strategy":{
        "use_book_order": false,
        "book_order_min": 1,
        "book_order_max": 30
    },
    "exchange": {
        "name": "bittrex",
@ -40,7 +51,8 @@
    },
    "experimental": {
        "use_sell_signal": false,
-        "sell_profit_only": false
+        "sell_profit_only": false,
        "sell_fullfilled_at_roi": false
    },
    "telegram": {
        "enabled": true,
--- a/docs/backtesting.md
+++ b/docs/backtesting.md
@ -1,17 +1,19 @@
 # Backtesting
 This page explains how to validate your strategy performance by using 
 Backtesting.
 ## Table of Contents
 - [Test your strategy with Backtesting](#test-your-strategy-with-backtesting)
 - [Understand the backtesting result](#understand-the-backtesting-result)
 ## Test your strategy with Backtesting
 Now you have good Buy and Sell strategies, you want to test it against
 real data. This is what we call 
 [backtesting](https://en.wikipedia.org/wiki/Backtesting).
 Backtesting will use the crypto-currencies (pair) from your config file
 and load static tickers located in 
 [/freqtrade/tests/testdata](https://github.com/freqtrade/freqtrade/tree/develop/freqtrade/tests/testdata).  
@ -19,70 +21,80 @@ If the 5 min and 1 min ticker for the crypto-currencies to test is not
 already in the `testdata` folder, backtesting will download them 
 automatically. Testdata files will not be updated until you specify it.
-The result of backtesting will confirm you if your bot as more chance to
+The result of backtesting will confirm you if your bot has better odds of making a profit than a loss.
 make a profit than a loss.
 The backtesting is very easy with freqtrade.
 ### Run a backtesting against the currencies listed in your config file
-**With 5 min tickers (Per default)**
+#### With 5 min tickers (Per default)
 ```bash
 python3 ./freqtrade/main.py backtesting --realistic-simulation
 ```
-**With 1 min tickers**
+#### With 1 min tickers
 ```bash
 python3 ./freqtrade/main.py backtesting --realistic-simulation --ticker-interval 1m
 ```
-**Update cached pairs with the latest data**
+#### Update cached pairs with the latest data
 ```bash
 python3 ./freqtrade/main.py backtesting --realistic-simulation --refresh-pairs-cached
 ```
-**With live data (do not alter your testdata files)**
+#### With live data (do not alter your testdata files)
 ```bash
 python3 ./freqtrade/main.py backtesting --realistic-simulation --live
 ```
-**Using a different on-disk ticker-data source**
+#### Using a different on-disk ticker-data source
 ```bash
 python3 ./freqtrade/main.py backtesting --datadir freqtrade/tests/testdata-20180101
 ```
-**With a (custom) strategy file**
+#### With a (custom) strategy file
 ```bash
 python3 ./freqtrade/main.py -s TestStrategy backtesting
 ```
 Where `-s TestStrategy` refers to the class name within the strategy file `test_strategy.py` found in the `freqtrade/user_data/strategies` directory
-**Exporting trades to file**
+#### Exporting trades to file
 ```bash
 python3 ./freqtrade/main.py backtesting --export trades
 ```
-**Exporting trades to file specifying a custom filename**
+#### Exporting trades to file specifying a custom filename
 ```bash
 python3 ./freqtrade/main.py backtesting --export trades --export-filename=backtest_teststrategy.json
 ```
 #### Running backtest with smaller testset
 **Running backtest with smaller testset**  
 Use the `--timerange` argument to change how much of the testset
 you want to use. The last N ticks/timeframes will be used.
 Example:
 ```bash
 python3 ./freqtrade/main.py backtesting --timerange=-200
 ```
-***Advanced use of timerange***  
+#### Advanced use of timerange
 Doing `--timerange=-200` will get the last 200 timeframes
 from your inputdata. You can also specify specific dates,
 or a range span indexed by start and stop.
 The full timerange specification:
 - Use last 123 tickframes of data: `--timerange=-123`
 - Use first 123 tickframes of data: `--timerange=123-`
 - Use tickframes from line 123 through 456: `--timerange=123-456`
@ -92,11 +104,12 @@ The full timerange specification:
 - Use tickframes between POSIX timestamps 1527595200 1527618600:
                                                `--timerange=1527595200-1527618600`
 #### Downloading new set of ticker data
 **Downloading new set of ticker data**
 To download new set of backtesting ticker data, you can use a download script.
 If you are using Binance for example:
 - create a folder `user_data/data/binance` and copy `pairs.json` in that folder.
 - update the `pairs.json` to contain the currency pairs you are interested in.
@ -119,33 +132,55 @@ This will download ticker data for all the currency pairs you defined in `pairs.
 - To download ticker data for only 10 days, use `--days 10`.
 - Use `--timeframes` to specify which tickers to download. Default is `--timeframes 1m 5m` which will download 1-minute and 5-minute tickers.
-
+For help about backtesting usage, please refer to [Backtesting commands](#backtesting-commands).
 For help about backtesting usage, please refer to 
 [Backtesting commands](#backtesting-commands).
 ## Understand the backtesting result
 The most important in the backtesting is to understand the result.
 A backtesting result will look like that:
 ```
-====================== BACKTESTING REPORT ================================
+======================================== BACKTESTING REPORT =========================================
-pair        buy count    avg profit %    total profit BTC    avg duration
+| pair     |   buy count |   avg profit % |   total profit BTC |   avg duration |   profit |   loss |
--------  -----------  --------------  ------------------  --------------
+|:---------|------------:|---------------:|-------------------:|---------------:|---------:|-------:|
-ETH/BTC            56           -0.67         -0.00075455            62.3
+| ETH/BTC  |          44 |           0.18 |         0.00159118 |           50.9 |       44 |      0 |
-LTC/BTC            38           -0.48         -0.00036315            57.9
+| LTC/BTC  |          27 |           0.10 |         0.00051931 |          103.1 |       26 |      1 |
-ETC/BTC            42           -1.15         -0.00096469            67.0
+| ETC/BTC  |          24 |           0.05 |         0.00022434 |          166.0 |       22 |      2 |
-DASH/BTC           72           -0.62         -0.00089368            39.9
+| DASH/BTC |          29 |           0.18 |         0.00103223 |          192.2 |       29 |      0 |
-ZEC/BTC            45           -0.46         -0.00041387            63.2
+| ZEC/BTC  |          65 |          -0.02 |        -0.00020621 |          202.7 |       62 |      3 |
-XLM/BTC            24           -0.88         -0.00041846            47.7
+| XLM/BTC  |          35 |           0.02 |         0.00012877 |          242.4 |       32 |      3 |
-NXT/BTC            24            0.68          0.00031833            40.2
+| BCH/BTC  |          12 |           0.62 |         0.00149284 |           50.0 |       12 |      0 |
-POWR/BTC           35            0.98          0.00064887            45.3
+| POWR/BTC |          21 |           0.26 |         0.00108215 |          134.8 |       21 |      0 |
-ADA/BTC            43           -0.39         -0.00032292            55.0
+| ADA/BTC  |          54 |          -0.19 |        -0.00205202 |          191.3 |       47 |      7 |
-XMR/BTC            40           -0.40         -0.00032181            47.4
+| XMR/BTC  |          24 |          -0.43 |        -0.00206013 |          120.6 |       20 |      4 |
-TOTAL             419           -0.41         -0.00348593            52.9
+| TOTAL    |         335 |           0.03 |         0.00175246 |          157.9 |      315 |     20 |
 2018-06-13 06:57:27,347 - freqtrade.optimize.backtesting - INFO -
 ====================================== LEFT OPEN TRADES REPORT ======================================
 | pair     |   buy count |   avg profit % |   total profit BTC |   avg duration |   profit |   loss |
 |:---------|------------:|---------------:|-------------------:|---------------:|---------:|-------:|
 | ETH/BTC  |           3 |           0.16 |         0.00009619 |           25.0 |        3 |      0 |
 | LTC/BTC  |           1 |          -1.00 |        -0.00020118 |         1085.0 |        0 |      1 |
 | ETC/BTC  |           2 |          -1.80 |        -0.00071933 |         1092.5 |        0 |      2 |
 | DASH/BTC |           0 |         nan    |         0.00000000 |          nan   |        0 |      0 |
 | ZEC/BTC  |           3 |          -4.27 |        -0.00256826 |         1301.7 |        0 |      3 |
 | XLM/BTC  |           3 |          -1.11 |        -0.00066744 |          965.0 |        0 |      3 |
 | BCH/BTC  |           0 |         nan    |         0.00000000 |          nan   |        0 |      0 |
 | POWR/BTC |           0 |         nan    |         0.00000000 |          nan   |        0 |      0 |
 | ADA/BTC  |           7 |          -3.58 |        -0.00503604 |          850.0 |        0 |      7 |
 | XMR/BTC  |           4 |          -3.79 |        -0.00303456 |          291.2 |        0 |      4 |
 | TOTAL    |          23 |          -2.63 |        -0.01213062 |          750.4 |        3 |     20 |
 ```
 The 1st table will contain all trades the bot made.
 The 2nd table will contain all trades the bot had to `forcesell` at the end of the backtest period to prsent a full picture.
 These trades are also included in the first table, but are extracted separately for clarity.
 The last line will give you the overall performance of your strategy,
 here:
 ```
 TOTAL             419           -0.41         -0.00348593            52.9
 ```
@ -161,6 +196,7 @@ strategy, your sell strategy, and also by the `minimal_roi` and
 As for an example if your minimal_roi is only `"0":  0.01`. You cannot
 expect the bot to make more profit than 1% (because it will sell every 
 time a trade will reach 1%).
 ```json
 "minimal_roi": {
    "0":  0.01
@ -173,6 +209,7 @@ profit. Hence, keep in mind that your performance is a mix of your
 strategies, your configuration, and the crypto-currency you have set up.
 ## Next step
 Great, your strategy is profitable. What if the bot can give your the
 optimal parameters to use for your strategy?  
 Your next step is to learn [how to find optimal parameters with Hyperopt](https://github.com/freqtrade/freqtrade/blob/develop/docs/hyperopt.md)
--- a/docs/bot-usage.md
+++ b/docs/bot-usage.md
@ -160,13 +160,12 @@ the parameter `-l` or `--live`.
 ## Hyperopt commands
-It is possible to use hyperopt for trading strategy optimization.
+To optimize your strategy, you can use hyperopt parameter hyperoptimization
-Hyperopt uses an internal json config return by `hyperopt_optimize_conf()` 
+to find optimal parameter values for your stategy.
 located in `freqtrade/optimize/hyperopt_conf.py`.
 ```
 usage: main.py hyperopt [-h] [-i TICKER_INTERVAL] [--realistic-simulation]
-                        [--timerange TIMERANGE] [-e INT] [--use-mongodb]
+                        [--timerange TIMERANGE] [-e INT]
                        [-s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]]
 optional arguments:
@ -176,11 +175,8 @@ optional arguments:
  --realistic-simulation
                        uses max_open_trades from config to simulate real
                        world limitations
-  --timerange TIMERANGE
+  --timerange TIMERANGE specify what timerange of data to use.
                        specify what timerange of data to use.
  -e INT, --epochs INT  specify number of epochs (default: 100)
  --use-mongodb         parallelize evaluations with mongodb (requires mongod
                        in PATH)
  -s {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...], --spaces {all,buy,roi,stoploss} [{all,buy,roi,stoploss} ...]
                        Specify which parameters to hyperopt. Space separate
                        list. Default: all
--- a/docs/configuration.md
+++ b/docs/configuration.md
@ -18,12 +18,20 @@ The table below will list all configuration parameters.
 | `stake_currency` | BTC | Yes | Crypto-currency used for trading.
 | `stake_amount` | 0.05 | Yes | Amount of crypto-currency your bot will use for each trade. Per default, the bot will use (0.05 BTC x 3) = 0.15 BTC in total will be always engaged.
 | `ticker_interval` | [1m, 5m, 30m, 1h, 1d] | No | The ticker interval to use (1min, 5 min, 30 min, 1 hour or 1 day). Default is 5 minutes
-| `fiat_display_currency` | USD | Yes | Fiat currency used to show your profits. More information below. 
+| `fiat_display_currency` | USD | Yes | Fiat currency used to show your profits. [More information below](docs/configuration.md#what-are-the-valid-values-for-fiat_display_currency). 
-| `dry_run` | true | Yes | Define if the bot must be in Dry-run or production mode. 
+| `dry_run` | true | Yes | Define if the bot must be in Dry-run or production mode. [More information below](docs/configuration.md#switch-to-dry-run--paper-trading-mode)
-| `minimal_roi` | See below | No | Set the threshold in percent the bot will use to sell a trade. More information below. If set, this parameter will override `minimal_roi` from your strategy file. 
+| `minimal_roi` | See below | No | Set the threshold in percent the bot will use to sell a trade. More information below. If set, this parameter will override `minimal_roi` from your strategy file. [More information below](docs/configuration.md#understanding-minimal_roi).
 | `stoploss` | -0.10 | No | Value of the stoploss in percent used by the bot. More information below. If set, this parameter will override `stoploss` from your strategy file. 
-| `unfilledtimeout` | 0 | No | How long (in minutes) the bot will wait for an unfilled order to complete, after which the order will be cancelled.
+| `disable_buy` | false | No | Disables buying of crypto-currency. Bot will continue to sell.
-| `bid_strategy.ask_last_balance` | 0.0 | Yes | Set the bidding price. More information below.
+| `unfilledtimeout.buy` | 10 | Yes | How long (in minutes) the bot will wait for an unfilled buy order to complete, after which the order will be cancelled.
 | `unfilledtimeout.sell` | 10 | Yes | How long (in minutes) the bot will wait for an unfilled sell order to complete, after which the order will be cancelled.
 | `bid_strategy.ask_last_balance` | 0.0 | Yes | Set the bidding price. [More information below](docs/configuration.md#understanding-bid_strategyask_last_balance).
 | `bid_strategy.use_book_order` | false | No | Use book order to set the bidding price. [More information below](docs/configuration.md#understanding-bid_strategyuse_book_order).
 | `bid_strategy.book_order_top` | 1 | No | Selects the top n bidding price in book order. [More information below](docs/configuration.md#understanding-bid_strategyuse_book_order).
 | `bid_strategy.percent_from_top` | 0 | No | Set the percent to deduct from the buy rate from book order (if enabled) or from ask/last price. [More information below](docs/configuration.md#understanding-bid_strategypercent_from_top).
 | `ask_strategy.use_book_order` | false | No | Use book order to set the asking price. More information below.
 | `ask_strategy.book_order_min` | 1 | No | The minimum index from the top to search for profitable asking price from book order. [More information below](docs/configuration.md#understanding-ask_strategyuse_book_order).
 | `ask_strategy.book_order_max` | 1 | No | The maximum index from the top to search for profitable asking price from book order. [More information below](docs/configuration.md#understanding-ask_strategyuse_book_order).
 | `exchange.name` | bittrex | Yes | Name of the exchange class to use. [List below](#user-content-what-values-for-exchangename).
 | `exchange.key` | key | No | API key to use for the exchange. Only required when you are in production mode.
 | `exchange.secret` | secret | No | API secret to use for the exchange. Only required when you are in production mode.
@ -31,11 +39,12 @@ The table below will list all configuration parameters.
 | `exchange.pair_blacklist` | [] | No | List of currency the bot must avoid. Useful when using `--dynamic-whitelist` param.
 | `experimental.use_sell_signal` | false | No | Use your sell strategy in addition of the `minimal_roi`.
 | `experimental.sell_profit_only` | false | No | waits until you have made a positive profit before taking a sell decision.
 | `experimental.sell_fullfilled_at_roi` | false | No | automatically creates a sell order based on `minimal_roi` once a buy order has been fullfilled.
 | `telegram.enabled` | true | Yes | Enable or not the usage of Telegram.
 | `telegram.token` | token | No | Your Telegram bot token. Only required if `telegram.enabled` is `true`.
 | `telegram.chat_id` | chat_id | No | Your personal Telegram account id. Only required if `telegram.enabled` is `true`.
 | `db_url` | `sqlite:///tradesv3.sqlite` | No | Declares database URL to use. NOTE: This defaults to `sqlite://` if `dry_run` is `True`.
-| `initial_state` | running | No | Defines the initial application state. More information below.
+| `initial_state` | running | No | Defines the initial application state. [More information below](docs/configuration.md#understanding-initial_state).
 | `strategy` | DefaultStrategy | No | Defines Strategy class to use.
 | `strategy_path` | null | No | Adds an additional strategy lookup path (must be a folder).
 | `internals.process_throttle_secs` | 5 | Yes | Set the process throttle. Value in second.
@ -43,7 +52,7 @@ The table below will list all configuration parameters.
 The definition of each config parameters is in 
 [misc.py](https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/misc.py#L205).
-### Understand minimal_roi
+### Understanding minimal_roi
 `minimal_roi` is a JSON object where the key is a duration
 in minutes and the value is the minimum ROI in percent.
 See the example below:
@ -56,41 +65,34 @@ See the example below:
 },
 ```
-Most of the strategy files already include the optimal `minimal_roi`
+Most of the strategy files already include the optimal `minimal_roi` value. This parameter is optional. If you use it, it will take over the `minimal_roi` value from the strategy file.
 value. This parameter is optional. If you use it, it will take over the
 `minimal_roi` value from the strategy file.
-### Understand stoploss
+### Understanding stoploss
-`stoploss` is loss in percentage that should trigger a sale.
+`stoploss` is loss in percentage that should trigger a sale. For example value `-0.10` will cause immediate sell if the
 For example value `-0.10` will cause immediate sell if the
 profit dips below -10% for a given trade. This parameter is optional.
-Most of the strategy files already include the optimal `stoploss`
+Most of the strategy files already include the optimal `stoploss` value. This parameter is optional. If you use it, it will take over the `stoploss` value from the strategy file.
 value. This parameter is optional. If you use it, it will take over the
 `stoploss` value from the strategy file.
-### Understand initial_state
+### Understanding initial_state
-`initial_state` is an optional field that defines the initial application state.
+`initial_state` is an optional field that defines the initial application state. Possible values are `running` or `stopped`. (default=`running`) If the value is `stopped` the bot has to be started with `/start` first.
 Possible values are `running` or `stopped`. (default=`running`)
 If the value is `stopped` the bot has to be started with `/start` first.
-### Understand process_throttle_secs
+### Understanding process_throttle_secs
-`process_throttle_secs` is an optional field that defines in seconds how long the bot should wait
+`process_throttle_secs` is an optional field that defines in seconds how long the bot should wait before asking the strategy if we should buy or a sell an asset. After each wait period, the strategy is asked again for every opened trade wether or not we should sell, and for all the remaining pairs (either the dynamic list of pairs or the static list of pairs) if we should buy.
 before asking the strategy if we should buy or a sell an asset. After each wait period, the strategy is asked again for
 every opened trade wether or not we should sell, and for all the remaining pairs (either the dynamic list of pairs or
 the static list of pairs) if we should buy.
-### Understand ask_last_balance
+### Understanding bid_strategy.ask_last_balance
-`ask_last_balance` sets the bidding price. Value `0.0` will use `ask` price, `1.0` will
+`ask_last_balance` sets the bidding price. Value `0.0` will use `ask` price, `1.0` will use the `last` price and the values between those interpolate between ask and last price. Using `ask` price will guarantee quick success in bid, but bot will also end up paying more then would probably have been necessary.
 use the `last` price and values between those interpolate between ask and last
 price. Using `ask` price will guarantee quick success in bid, but bot will also
 end up paying more then would probably have been necessary.
-### What values for exchange.name?
+### Understanding bid_strategy.use_book_order
-Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports 115 cryptocurrency
+`bid_strategy.use_book_order` loads the exchange book order and sets the bidding price between `book_order_min`  and `book_order_max` value. If the `book_order_top` is set to 3, then the 3rd bidding price from the top of the book order will be selected as the bidding price for the trade.
-exchange markets and trading APIs. The complete up-to-date list can be found in the
+
-[CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python). However, the bot was tested
+### Understanding bid_strategy.percent_from_top
-with only Bittrex and Binance.
+`bid_strategy.percent_from_top` sets the percent to deduct from buy price of the pair. If `bid_strategy.use_book_order` is enabled, the percent value is deducted from the rate of `book_order_top`, otherwise, the percent value is deducted from the value provided by `bid_strategy.ask_last_balance`. Example: If `ask_last_balance` rate is 100 and the `bid_strategy.percent_from_top` is `0.005` or `0.5%`, the bot would buy at the price of `99.5`.
 ### Understanding ask_strategy.use_book_order
 `ask_strategy.use_book_order` loads the exchange book order and sets the askng price based on the `book_order_top` value. If the `book_order_min` is set to 3 and `book_order_max` is set to 10, then the bot will search between top 3rd and 10th asking prices from the top of the book order will be selected as the bidding price for the trade.
 ### What are the valid values for exchange.name?
 Freqtrade is based on [CCXT library](https://github.com/ccxt/ccxt) that supports 115+ cryptocurrency exchange markets and trading APIs. The complete up-to-date list can be found in the [CCXT repo homepage](https://github.com/ccxt/ccxt/tree/master/python). However, the bot was thoroughly tested with only Bittrex and Binance.
 The bot was tested with the following exchanges:
 - [Bittrex](https://bittrex.com/): "bittrex"
@ -98,13 +100,13 @@ The bot was tested with the following exchanges:
 Feel free to test other exchanges and submit your PR to improve the bot.
-### What values for fiat_display_currency?
+### What are the valid values for fiat_display_currency?
 `fiat_display_currency` set the base currency to use for the conversion from coin to fiat in Telegram.
 The valid values are: "AUD", "BRL", "CAD", "CHF", "CLP", "CNY", "CZK", "DKK", "EUR", "GBP", "HKD", "HUF", "IDR", "ILS", "INR", "JPY", "KRW", "MXN", "MYR", "NOK", "NZD", "PHP", "PKR", "PLN", "RUB", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR", "USD".
 In addition to central bank currencies, a range of cryto currencies are supported.
 The valid values are: "BTC", "ETH", "XRP", "LTC", "BCH", "USDT".
-## Switch to dry-run mode
+## Switch to dry-run / paper trading mode
 We recommend starting the bot in dry-run mode to see how your bot will
 behave and how is the performance of your strategy. In Dry-run mode the
 bot does not engage your money. It only runs a live simulation without
@ -131,7 +133,7 @@ creating trades.
 Once you will be happy with your bot performance, you can switch it to 
 production mode.
-## Switch to production mode
+## Switch to production / live mode
 In production mode, the bot will engage your money. Be careful a wrong 
 strategy can lose all your money. Be aware of what you are doing when 
 you run it in production mode.
--- a/docs/hyperopt.md
+++ b/docs/hyperopt.md
@ -9,7 +9,6 @@ parameters with Hyperopt.
 - [Advanced Hyperopt notions](#advanced-notions)
    - [Understand the Guards and Triggers](#understand-the-guards-and-triggers)
 - [Execute Hyperopt](#execute-hyperopt)
    - [Hyperopt with MongoDB](#hyperopt-with-mongoDB)
 - [Understand the hyperopts result](#understand-the-backtesting-result)
 ## Prepare Hyperopt
@ -194,41 +193,6 @@ Legal values are:
 - `stoploss`: search for the best stoploss value
 - space-separated list of any of the above values for example `--spaces roi stoploss`
 ### Hyperopt with MongoDB
 Hyperopt with MongoDB, is like Hyperopt under steroids. As you saw by
 executing the previous command is the execution takes a long time. 
 To accelerate it you can use hyperopt with MongoDB.
 To run hyperopt with MongoDb you will need 3 terminals.
 **Terminal 1: Start MongoDB**
 ```bash
 cd <freqtrade> 
 source .env/bin/activate
 python3 scripts/start-mongodb.py
 ```
 **Terminal 2: Start Hyperopt worker**
 ```bash
 cd <freqtrade> 
 source .env/bin/activate
 python3 scripts/start-hyperopt-worker.py
 ```
 **Terminal 3: Start Hyperopt with MongoDB**
 ```bash
 cd <freqtrade> 
 source .env/bin/activate
 python3 ./freqtrade/main.py -c config.json hyperopt --use-mongodb
 ```
 **Re-run an Hyperopt**
 To re-run Hyperopt you have to delete the existing MongoDB table.
 ```bash
 cd <freqtrade> 
 rm -rf .hyperopt/mongodb/
 ```
 ## Understand the hyperopts result 
 Once Hyperopt is completed you can use the result to adding new buy 
 signal. Given following result from hyperopt:
--- a/docs/installation.md
+++ b/docs/installation.md
@ -184,6 +184,26 @@ docker start freqtrade
 You do not need to rebuild the image for configuration changes, it will suffice to edit `config.json` and restart the container.
 ### 7. Backtest with docker
 The following assumes that the above steps (1-4) have been completed successfully.
 Also, backtest-data should be available at `~/.freqtrade/user_data/`.
 ``` bash
 docker run -d \
  --name freqtrade \
  -v /etc/localtime:/etc/localtime:ro \
  -v ~/.freqtrade/config.json:/freqtrade/config.json \
  -v ~/.freqtrade/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \
  -v ~/.freqtrade/user_data/:/freqtrade/user_data/ \
  freqtrade --strategy AwsomelyProfitableStrategy backtesting
 ```
 Head over to the [Backtesting Documentation](https://github.com/freqtrade/freqtrade/blob/develop/docs/backtesting.md) for more details.
 *Note*: Additional parameters can be appended after the image name (`freqtrade` in the above example).
 ------
 ## Custom Installation
@ -225,17 +245,7 @@ cd ..
 rm -rf ./ta-lib*
 ```
-#### 3. [Optional] Install MongoDB
+#### 3. Install FreqTrade
 Install MongoDB if you plan to optimize your strategy with Hyperopt.
 ```bash
 sudo apt-get install mongodb-org
 ```
 > Complete tutorial from Digital Ocean: [How to Install MongoDB on Ubuntu 16.04](https://www.digitalocean.com/community/tutorials/how-to-install-mongodb-on-ubuntu-16-04).
 #### 4. Install FreqTrade
 Clone the git repository:
@ -243,7 +253,7 @@ Clone the git repository:
 git clone https://github.com/freqtrade/freqtrade.git
 ```
-#### 5. Configure `freqtrade` as a `systemd` service
+#### 4. Configure `freqtrade` as a `systemd` service
 From the freqtrade repo... copy `freqtrade.service` to your systemd user directory (usually `~/.config/systemd/user`) and update `WorkingDirectory` and `ExecStart` to match your setup.
@ -267,19 +277,7 @@ sudo loginctl enable-linger "$USER"
 brew install python3 git wget ta-lib
 ```
-#### 2. [Optional] Install MongoDB
+#### 2. Install FreqTrade
 Install MongoDB if you plan to optimize your strategy with Hyperopt.
 ```bash
 curl -O https://fastdl.mongodb.org/osx/mongodb-osx-ssl-x86_64-3.4.10.tgz
 tar -zxvf mongodb-osx-ssl-x86_64-3.4.10.tgz
 mkdir -p <path_freqtrade>/env/mongodb
 cp -R -n mongodb-osx-x86_64-3.4.10/ <path_freqtrade>/env/mongodb
 export PATH=<path_freqtrade>/env/mongodb/bin:$PATH
 ```
 #### 3. Install FreqTrade
 Clone the git repository:
--- a/docs/stoploss.md
+++ b/docs/stoploss.md
@ -0,0 +1,50 @@
 # Stop Loss support
 at this stage the bot contains the following stoploss support modes:
 1. static stop loss, defined in either the strategy or configuration
 2. trailing stop loss, defined in the configuration
 3. trailing stop loss, custom positive loss, defined in configuration
 ## Static Stop Loss
 This is very simple, basically you define a stop loss of x in your strategy file or alternative in the configuration, which
 will overwrite the strategy definition. This will basically try to sell your asset, the second the loss exceeds the defined loss.
 ## Trail Stop Loss
 The initial value for this stop loss, is defined in your strategy or configuration. Just as you would define your Stop Loss normally.
 To enable this Feauture all you have to do, is to define the configuration element:
 ```
 "trailing_stop" : True
 ```
 This will now actiave an algorithm, whihch automatically moves up your stop loss, every time the price of your asset increases.
 For example, simplified math,
 * you buy an asset at a price of 100$
 * your stop loss is defined at 2%
 * which means your stop loss, gets triggered once your asset dropped below 98$
 * assuming your asset now increases in proce to 102$
 * your stop loss, will now be 2% of 102$ or 99.96$
 * now your asset drops in value to 101$, your stop loss, will still be 99.96$
 basically what this means, is that your stop loss will be adjusted to be always be 2% of the highest observed price
 ### Custom positive loss
 due to demand, it is possible to have a default stop loss, when you are in the red with your buy, but once your buy turns positive,
 the system will utilize a new stop loss, which can be a different value. For example your default stop loss is 5%, but once you are in the
 black, it will be changed to be only a 1% stop loss
 this can be configured in the main configuration file, the following way:
 ```
    "trailing_stop": {
        "positive" : 0.01
    },
 ```
 The 0.01 would translate to a 1% stop loss, once you hit profit.
--- a/docs/telegram-usage.md
+++ b/docs/telegram-usage.md
@ -16,6 +16,7 @@ official commands. You can ask at any moment for help with `/help`.
 |----------|---------|-------------|
 | `/start` | | Starts the trader
 | `/stop` | | Stops the trader
 | `/reload_conf` | | Reloads the configuration file
 | `/status` | | Lists all open trades
 | `/status table` | | List all open trades in a table format
 | `/count` | | Displays number of trades used and available
--- a/freqtrade/analyze.py
+++ b/freqtrade/analyze.py
@ -7,14 +7,14 @@ from enum import Enum
 from typing import Dict, List, Tuple
 import arrow
 import pandas as pd
 from pandas import DataFrame, to_datetime
 from freqtrade import constants
-from freqtrade.exchange import get_ticker_history
+from freqtrade.exchange import get_fee, get_ticker_history
 from freqtrade.persistence import Trade
 from freqtrade.strategy.resolver import StrategyResolver, IStrategy
 logger = logging.getLogger(__name__)
@ -31,6 +31,7 @@ class Analyze(object):
    Analyze class contains everything the bot need to determine if the situation is good for
    buying or selling.
    """
    def __init__(self, config: dict) -> None:
        """
        Init Analyze
@ -62,10 +63,10 @@ class Analyze(object):
            'close': 'last',
            'volume': 'max',
        })
-        frame.drop(frame.tail(1).index, inplace=True)     # eliminate partial candle
+
        return frame
-    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
+    def populate_indicators(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
        """
        Adds several different TA indicators to the given DataFrame
@ -73,23 +74,23 @@ class Analyze(object):
        you are using. Let uncomment only the indicator you are using in your strategies
        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
        """
-        return self.strategy.populate_indicators(dataframe=dataframe)
+        return self.strategy.advise_indicators(dataframe=dataframe, pair=pair)
-    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_buy_trend(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
        """
        Based on TA indicators, populates the buy signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
-        return self.strategy.populate_buy_trend(dataframe=dataframe)
+        return self.strategy.advise_buy(dataframe=dataframe, pair=pair)
-    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
+    def populate_sell_trend(self, dataframe: DataFrame, pair: str = None) -> DataFrame:
        """
        Based on TA indicators, populates the sell signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
-        return self.strategy.populate_sell_trend(dataframe=dataframe)
+        return self.strategy.advise_sell(dataframe=dataframe, pair=pair)
    def get_ticker_interval(self) -> str:
        """
@ -98,16 +99,20 @@ class Analyze(object):
        """
        return self.strategy.ticker_interval
-    def analyze_ticker(self, ticker_history: List[Dict]) -> DataFrame:
+    def analyze_ticker(self, ticker_history: List[Dict], pair: str) -> DataFrame:
        """
        Parses the given ticker history and returns a populated DataFrame
        add several TA indicators and buy signal to it
        :return DataFrame with ticker data and indicator data
        """
        dataframe = self.parse_ticker_dataframe(ticker_history)
-        dataframe = self.populate_indicators(dataframe)
+        # eliminate partials for known exchanges that sends partial candles
-        dataframe = self.populate_buy_trend(dataframe)
+        if self.config['exchange']['name'] in ['binance']:
-        dataframe = self.populate_sell_trend(dataframe)
+            logger.info('eliminating partial candle')
            dataframe.drop(dataframe.tail(1).index, inplace=True)  # eliminate partial candle
        dataframe = self.populate_indicators(dataframe, pair)
        dataframe = self.populate_buy_trend(dataframe, pair)
        dataframe = self.populate_sell_trend(dataframe, pair)
        return dataframe
    def get_signal(self, pair: str, interval: str) -> Tuple[bool, bool]:
@ -123,7 +128,7 @@ class Analyze(object):
            return False, False
        try:
-            dataframe = self.analyze_ticker(ticker_hist)
+            dataframe = self.analyze_ticker(ticker_hist, pair)
        except ValueError as error:
            logger.warning(
                'Unable to analyze ticker for pair %s: %s',
@ -148,7 +153,8 @@ class Analyze(object):
        # Check if dataframe is out of date
        signal_date = arrow.get(latest['date'])
        interval_minutes = constants.TICKER_INTERVAL_MINUTES[interval]
-        if signal_date < arrow.utcnow() - timedelta(minutes=(interval_minutes + 5)):
+        if signal_date < (arrow.utcnow() - timedelta(minutes=(interval_minutes + 5))):
            logger.debug('signal %s vs arrow now %s', signal_date, arrow.utcnow())
            logger.warning(
                'Outdated history for pair %s. Last tick is %s minutes old',
                pair,
@ -196,10 +202,40 @@ class Analyze(object):
        :return True if bot should sell at current rate
        """
        current_profit = trade.calc_profit_percent(current_rate)
-        if self.strategy.stoploss is not None and current_profit < self.strategy.stoploss:
+        if trade.stop_loss is None:
            # initially adjust the stop loss to the base value
            trade.adjust_stop_loss(trade.open_rate, self.strategy.stoploss)
        # evaluate if the stoploss was hit
        if self.strategy.stoploss is not None and trade.stop_loss >= current_rate:
            if 'trailing_stop' in self.config and self.config['trailing_stop']:
                logger.debug(
                    "HIT STOP: current price at {:.6f}, stop loss is {:.6f}, "
                    "initial stop loss was at {:.6f}, trade opened at {:.6f}".format(
                        current_rate, trade.stop_loss, trade.initial_stop_loss, trade.open_rate))
                logger.debug("trailing stop saved us: {:.6f}"
                             .format(trade.stop_loss - trade.initial_stop_loss))
            logger.debug('Stop loss hit.')
            return True
        # update the stop loss afterwards, after all by definition it's supposed to be hanging
        if 'trailing_stop' in self.config and self.config['trailing_stop']:
            # check if we have a special stop loss for positive condition
            # and if profit is positive
            stop_loss_value = self.strategy.stoploss
            if isinstance(self.config['trailing_stop'], dict) and \
                    'positive' in self.config['trailing_stop'] and \
                    current_profit > 0:
                logger.debug("using positive stop loss mode: {} since we have profit {}".format(
                    self.config['trailing_stop']['positive'], current_profit))
                stop_loss_value = self.config['trailing_stop']['positive']
            trade.adjust_stop_loss(current_rate, stop_loss_value)
        # Check if time matches and current rate is above threshold
        time_diff = (current_time.timestamp() - trade.open_date.timestamp()) / 60
        for duration, threshold in self.strategy.minimal_roi.items():
@ -216,3 +252,48 @@ class Analyze(object):
        """
        return {pair: self.populate_indicators(self.parse_ticker_dataframe(pair_data))
                for pair, pair_data in tickerdata.items()}
    def trunc_num(self, f, n):
        import math
        return math.floor(f * 10 ** n) / 10 ** n
    def get_roi_rate(self, trade: Trade, sell_rate: float) -> float:
        """
        Calculates sell rate based on roi
        """
        current_time = datetime.utcnow()
        time_diff = (current_time.timestamp() - trade.open_date.timestamp()) / 60
        for duration, threshold in self.strategy.minimal_roi.items():
            if time_diff > duration:
                roi_rate = self.trunc_num((trade.open_rate * (1 + threshold)) * (1+(2.1*get_fee(trade.pair))), 8)
                logger.info('trying to selling at roi rate %0.8f', roi_rate)
                return roi_rate
                break
        return sell_rate
    def order_book_to_dataframe(data: list) -> DataFrame:
        """
        Gets order book list, returns dataframe with below format
        -------------------------------------------------------------------
         bids       b_size       a_sum       asks       a_size       a_sum
        -------------------------------------------------------------------
        """
        cols = ['bids', 'b_size']
        bids_frame = DataFrame(data['bids'], columns=cols)
        # add cumulative sum column
        bids_frame['b_sum'] = bids_frame['b_size'].cumsum()
        cols2 = ['asks', 'a_size']
        asks_frame = DataFrame(data['asks'], columns=cols2)
        # add cumulative sum column
        asks_frame['a_sum'] = asks_frame['a_size'].cumsum()
        frame = pd.concat([bids_frame['b_sum'], bids_frame['b_size'], bids_frame['bids'], \
            asks_frame['asks'], asks_frame['a_size'], asks_frame['a_sum']], axis=1, \
            keys=['b_sum', 'b_size', 'bids', 'asks', 'a_size', 'a_sum'])
        return frame
    def order_book_dom() -> DataFrame:
        # https://stackoverflow.com/questions/36835793/pandas-group-by-consecutive-ranges
        return DataFrame
--- a/freqtrade/arguments.py
+++ b/freqtrade/arguments.py
@ -203,12 +203,6 @@ class Arguments(object):
            type=int,
            metavar='INT',
        )
        parser.add_argument(
            '--use-mongodb',
            help='parallelize evaluations with mongodb (requires mongod in PATH)',
            dest='mongodb',
            action='store_true',
        )
        parser.add_argument(
            '-s', '--spaces',
            help='Specify which parameters to hyperopt. Space separate list. \
@ -224,7 +218,7 @@ class Arguments(object):
        Builds and attaches all subcommands
        :return: None
        """
-        from freqtrade.optimize import backtesting, hyperopt
+        from freqtrade.optimize import backtesting
        subparsers = self.parser.add_subparsers(dest='subparser')
@ -235,10 +229,14 @@ class Arguments(object):
        self.backtesting_options(backtesting_cmd)
        # Add hyperopt subcommand
-        hyperopt_cmd = subparsers.add_parser('hyperopt', help='hyperopt module')
+        try:
-        hyperopt_cmd.set_defaults(func=hyperopt.start)
+            from freqtrade.optimize import hyperopt
-        self.optimizer_shared_options(hyperopt_cmd)
+            hyperopt_cmd = subparsers.add_parser('hyperopt', help='hyperopt module')
-        self.hyperopt_options(hyperopt_cmd)
+            hyperopt_cmd.set_defaults(func=hyperopt.start)
            self.optimizer_shared_options(hyperopt_cmd)
            self.hyperopt_options(hyperopt_cmd)
        except ImportError as e:
            logging.warn("no hyper opt found - skipping support for it")
    @staticmethod
    def parse_timerange(text: Optional[str]) -> TimeRange:
@ -295,6 +293,93 @@ class Arguments(object):
            default=None
        )
        self.parser.add_argument(
            '--stop-loss',
            help='Renders stop/loss information in the main chart',
            dest='stoplossdisplay',
            action='store_true',
            default=False
        )
        self.parser.add_argument(
            '--plot-rsi',
            help='Renders a rsi chart of the given RSI dataframe name, for example --plot-rsi rsi',
            dest='plotrsi',
            nargs='+',
            default=None
        )
        self.parser.add_argument(
            '--plot-cci',
            help='Renders a cci chart of the given CCI dataframe name, for example --plot-cci cci',
            dest='plotcci',
            nargs='+',
            default=None
        )
        self.parser.add_argument(
            '--plot-osc',
            help='Renders a osc chart of the given osc dataframe name, for example --plot-osc osc',
            dest='plotosc',
            nargs='+',
            default=None
        )
        self.parser.add_argument(
            '--plot-cmf',
            help='Renders a cmf chart of the given cmf dataframe name, for example --plot-cmf cmf',
            dest='plotcmf',
            nargs='+',
            default=None
        )
        self.parser.add_argument(
            '--plot-macd',
            help='Renders a macd chart of the given '
                 'dataframe name, for example --plot-macd macd',
            dest='plotmacd',
            default=None
        )
        self.parser.add_argument(
            '--plot-dataframe',
            help='Renders the specified dataframes',
            dest='plotdataframe',
            default=None,
            nargs='+',
            type=str
        )
        self.parser.add_argument(
            '--plot-dataframe-marker',
            help='Renders the specified dataframes as markers. '
                 'Accepted values for a marker are either 100 or -100',
            dest='plotdataframemarker',
            default=None,
            nargs='+',
            type=str
        )
        self.parser.add_argument(
            '--plot-volume',
            help='plots the volume as a sub plot',
            dest='plotvolume',
            action='store_true'
        )
        self.parser.add_argument(
            '--plot-max-ticks',
            help='specify an upper limit of how many ticks we can display',
            dest='plotticks',
            default=750,
            type=int
        )
    def testdata_dl_options(self) -> None:
        """
        Parses given arguments for testdata download
--- a/freqtrade/configuration.py
+++ b/freqtrade/configuration.py
@ -188,11 +188,6 @@ class Configuration(object):
            logger.info('Parameter --epochs detected ...')
            logger.info('Will run Hyperopt with for %s epochs ...', config.get('epochs'))
        # If --mongodb is used we add it to the configuration
        if 'mongodb' in self.args and self.args.mongodb:
            config.update({'mongodb': self.args.mongodb})
            logger.info('Parameter --use-mongodb detected ...')
        # If --spaces is used we add it to the configuration
        if 'spaces' in self.args and self.args.spaces:
            config.update({'spaces': self.args.spaces})
--- a/freqtrade/constants.py
+++ b/freqtrade/constants.py
@ -35,7 +35,7 @@ SUPPORTED_FIAT = [
    "KRW", "MXN", "MYR", "NOK", "NZD", "PHP", "PKR", "PLN",
    "RUB", "SEK", "SGD", "THB", "TRY", "TWD", "ZAR", "USD",
    "BTC", "ETH", "XRP", "LTC", "BCH", "USDT"
-    ]
+]
 # Required json-schema for user specified config
 CONF_SCHEMA = {
@ -55,7 +55,14 @@ CONF_SCHEMA = {
            'minProperties': 1
        },
        'stoploss': {'type': 'number', 'maximum': 0, 'exclusiveMaximum': True},
-        'unfilledtimeout': {'type': 'integer', 'minimum': 0},
+        'unfilledtimeout': {
            'type': 'object',
            'properties': {
                'buy': {'type': 'number', 'minimum': 1},
                'sell': {'type': 'number', 'minimum': 1}
            },
            'required': ['buy', 'sell']
        },
        'bid_strategy': {
            'type': 'object',
            'properties': {
@ -66,16 +73,27 @@ CONF_SCHEMA = {
                    'exclusiveMaximum': False
                },
                'use_book_order': {'type': 'boolean'},
-                'book_order_top': {'type': 'number', 'maximum':20,'minimum':1}
+                'book_order_top': {'type': 'number', 'maximum': 20, 'minimum': 1},
                'percent_from_top': {'type': 'number', 'minimum': 0}
            },
-            'required': ['ask_last_balance']
+            'required': ['ask_last_balance', 'use_book_order']
        },
        'ask_strategy': {
            'type': 'object',
            'properties': {
                'use_book_order': {'type': 'boolean'},
                'book_order_min': {'type': 'number', 'minimum': 1},
                'book_order_max': {'type': 'number', 'minimum': 1, 'maximum': 50}
            },
            'required': ['use_book_order']
        },
        'exchange': {'$ref': '#/definitions/exchange'},
        'experimental': {
            'type': 'object',
            'properties': {
                'use_sell_signal': {'type': 'boolean'},
-                'sell_profit_only': {'type': 'boolean'}
+                'sell_profit_only': {'type': 'boolean'},
                'sell_fullfilled_at_roi': {'type': 'boolean'}
            }
        },
        'telegram': {
--- a/freqtrade/exchange/init.py
+++ b/freqtrade/exchange/init.py
@ -45,6 +45,7 @@ def retrier(f):
            else:
                logger.warning('Giving up retrying: %s()', f.__name__)
                raise ex
    return wrapper
@ -239,10 +240,21 @@ def get_balances() -> dict:
    except ccxt.BaseError as e:
        raise OperationalException(e)
@retrier
-def get_order_book(pair: str, refresh: Optional[bool] = True) -> dict:
+def get_order_book(pair: str, limit: Optional[int] = 100) -> dict:
    try:
-        return _API.fetch_order_book(pair)
+        params = {}
        # 20180619: bittrex doesnt support limits -.-
        # 20180619: binance limit fix.. binance currently has valid range
        if _API.name == 'Binance':
            limit_range = [5, 10, 20, 50, 100, 500, 1000]
            for limitx in limit_range:
                if limit < limitx:
                    limit = limitx
                    break
        return _API.fetch_l2_order_book(pair, limit)
    except ccxt.NotSupported as e:
        raise OperationalException(
            f'Exchange {_API.name} does not support fetching order book.'
@ -253,6 +265,7 @@ def get_order_book(pair: str, refresh: Optional[bool] = True) -> dict:
    except ccxt.BaseError as e:
        raise OperationalException(e)
@retrier
 def get_tickers() -> Dict:
    try:
@ -297,8 +310,8 @@ def get_ticker_history(pair: str, tick_interval: str, since_ms: Optional[int] =
    try:
        # last item should be in the time interval [now - tick_interval, now]
        till_time_ms = arrow.utcnow().shift(
-                        minutes=-constants.TICKER_INTERVAL_MINUTES[tick_interval]
+            minutes=-constants.TICKER_INTERVAL_MINUTES[tick_interval]
-                       ).timestamp * 1000
+        ).timestamp * 1000
        # it looks as if some exchanges return cached data
        # and they update it one in several minute, so 10 mins interval
        # is necessary to skeep downloading of an empty array when all
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@ -33,7 +33,7 @@ class FreqtradeBot(object):
    This is from here the bot start its logic.
    """
-    def __init__(self, config: Dict[str, Any])-> None:
+    def __init__(self, config: Dict[str, Any]) -> None:
        """
        Init all variables and object the bot need to work
        :param config: configuration dict, you can use the Configuration.get_config()
@ -76,17 +76,14 @@ class FreqtradeBot(object):
        else:
            self.state = State.STOPPED
-    def clean(self) -> bool:
+    def cleanup(self) -> None:
        """
-        Cleanup the application state und finish all pending tasks
+        Cleanup pending resources on an already stopped bot
        :return: None
        """
-        self.rpc.send_msg('*Status:* `Stopping trader...`')
+        logger.info('Cleaning up modules ...')
        logger.info('Stopping trader and cleaning up modules...')
        self.state = State.STOPPED
        self.rpc.cleanup()
        persistence.cleanup()
        return True
    def worker(self, old_state: State = None) -> State:
        """
@ -99,6 +96,12 @@ class FreqtradeBot(object):
        if state != old_state:
            self.rpc.send_msg(f'*Status:* `{state.name.lower()}`')
            logger.info('Changing state to: %s', state.name)
            if (('use_book_order' in self.config['bid_strategy'] and \
            self.config['bid_strategy'].get('use_book_order', False)) or \
            ('use_book_order' in self.config['ask_strategy'] and \
            self.config['ask_strategy'].get('use_book_order', False))) and \
            self.config['dry_run'] and state == State.RUNNING:
                self.rpc.send_msg('*Warning:* `Order book enabled in dry run. Results will be misleading`')
        if state == State.STOPPED:
            time.sleep(1)
@ -159,13 +162,17 @@ class FreqtradeBot(object):
                state_changed |= self.process_maybe_execute_sell(trade)
            # Then looking for buy opportunities
-            if len(trades) < self.config['max_open_trades']:
+            if (self.config.get('disable_buy', False)):
-                state_changed = self.process_maybe_execute_buy()
+                logger.info('Buy disabled...')
            else:
                if len(trades) < self.config['max_open_trades']:
                    state_changed = self.process_maybe_execute_buy()
            if 'unfilledtimeout' in self.config:
                # Check and handle any timed out open orders
-                self.check_handle_timedout(self.config['unfilledtimeout'])
+                if not self.config['dry_run']:
-                Trade.session.flush()
+                    self.check_handle_timedout()
                    Trade.session.flush()
        except TemporaryError as error:
            logger.warning('%s, retrying in 30 seconds...', error)
@ -243,19 +250,40 @@ class FreqtradeBot(object):
        :param ticker: Ticker to use for getting Ask and Last Price
        :return: float: Price
        """
        ticker = exchange.get_ticker(pair)
        logger.debug('ticker data %s', ticker)
-        if self.config['bid_strategy']['use_book_order']:
+        if ticker['ask'] < ticker['last']:
-            logger.info('Using order book ')
+            ticker_rate = ticker['ask']
            orderBook = exchange.get_order_book(pair)
            return orderBook['bids'][self.config['bid_strategy']['use_book_order']][0]
        else:
            logger.info('Using Ask / Last Price')
            ticker = exchange.get_ticker(pair);
            if ticker['ask'] < ticker['last']:
                return ticker['ask']
            balance = self.config['bid_strategy']['ask_last_balance']
-            return ticker['ask'] + balance * (ticker['last'] - ticker['ask'])
+            ticker_rate = ticker['ask'] + balance * (ticker['last'] - ticker['ask'])
        used_rate = ticker_rate
        if 'use_book_order' in self.config['bid_strategy'] and self.config['bid_strategy'].get('use_book_order', False):
            logger.info('Getting price from Order Book')
            orderBook_top = self.config.get('bid_strategy', {}).get('book_order_top', 1)
            orderBook = exchange.get_order_book(pair, orderBook_top)            
            # top 1 = index 0
            orderBook_rate = orderBook['bids'][orderBook_top - 1][0]
            orderBook_rate = orderBook_rate + 0.00000001
            # if ticker has lower rate, then use ticker ( usefull if down trending )
            logger.info('...book order buy rate %0.8f', orderBook_rate)
            if ticker_rate < orderBook_rate:
                logger.info('...using ticker rate instead %0.8f', ticker_rate)
                used_rate = ticker_rate
            used_rate = orderBook_rate
        else:
            logger.info('Using Last Ask / Last Price')
            used_rate = ticker_rate
        percent_from_top = self.config.get('bid_strategy', {}).get('percent_from_top', 0)
        if percent_from_top > 0:
            used_rate = used_rate - (used_rate * percent_from_top)
            used_rate = self.analyze.trunc_num(used_rate, 8)
            logger.info('...percent_from_top enabled, new buy rate %0.8f', used_rate)
        return used_rate
    def create_trade(self) -> bool:
        """
@ -264,6 +292,7 @@ class FreqtradeBot(object):
        :return: True if a trade object has been created and persisted, False otherwise
        """
        stake_amount = self.config['stake_amount']
        interval = self.analyze.get_ticker_interval()
        stake_currency = self.config['stake_currency']
        fiat_currency = self.config['fiat_display_currency']
@ -274,8 +303,10 @@ class FreqtradeBot(object):
            stake_amount
        )
        whitelist = copy.deepcopy(self.config['exchange']['pair_whitelist'])
        # Check if stake_amount is fulfilled
-        if exchange.get_balance(stake_currency) < stake_amount:
+        current_balance = exchange.get_balance(self.config['stake_currency'])
        if current_balance < stake_amount:
            raise DependencyException(
                f'stake amount is not fulfilled (currency={stake_currency})')
@ -431,33 +462,68 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
        if not trade.is_open:
            raise ValueError(f'attempt to handle closed trade: {trade}')
-        logger.debug('Handling %s ...', trade)
+        logger.info('Handling %s ...', trade)
-        current_rate = exchange.get_ticker(trade.pair)['bid']
+        sell_rate = exchange.get_ticker(trade.pair)['bid']
-
+        logger.info(' ticker rate %0.8f', sell_rate)
        (buy, sell) = (False, False)
        if self.config.get('experimental', {}).get('use_sell_signal'):
            (buy, sell) = self.analyze.get_signal(trade.pair, self.analyze.get_ticker_interval())
-        if self.analyze.should_sell(trade, current_rate, datetime.utcnow(), buy, sell):
+        is_set_fullfilled_at_roi = self.config.get('experimental', {}).get('sell_fullfilled_at_roi', False)
-            self.execute_sell(trade, current_rate)
+        if is_set_fullfilled_at_roi:
-            return True
+            sell_rate = self.analyze.get_roi_rate(trade, sell_rate)
        if 'ask_strategy' in self.config and self.config['ask_strategy'].get('use_book_order', False):
            logger.info('Using order book for selling...')
            # logger.debug('Order book %s',orderBook)
            orderBook_min = self.config['ask_strategy'].get('book_order_min', 1)
            orderBook_max = self.config['ask_strategy'].get('book_order_max', 1)
            orderBook = exchange.get_order_book(trade.pair, orderBook_max)
            for i in range(orderBook_min, orderBook_max + 1):
                orderBook_rate = orderBook['asks'][i - 1][0]
                # if orderbook has higher rate (high profit),
                # use orderbook, otherwise just use bids rate
                logger.info('  order book asks top %s: %0.8f', i, orderBook_rate)
                if sell_rate < orderBook_rate:
                    sell_rate = orderBook_rate
                if self.check_sell(trade, sell_rate, buy, sell):
                    return True
                    break
        else:
            logger.info('checking sell')
            if self.check_sell(trade, sell_rate, buy, sell):
                return True
        logger.info('Found no sell signals for whitelisted currencies. Trying again..')
        return False
-    def check_handle_timedout(self, timeoutvalue: int) -> None:
+    def check_sell(self, trade: Trade, sell_rate: float, buy: bool, sell: bool) -> bool:
        if self.analyze.should_sell(trade, sell_rate, datetime.utcnow(), buy, sell):
            self.execute_sell(trade, sell_rate)
            return True
        return False
    def check_handle_timedout(self) -> None:
        """
        Check if any orders are timed out and cancel if neccessary
        :param timeoutvalue: Number of minutes until order is considered timed out
        :return: None
        """
-        timeoutthreashold = arrow.utcnow().shift(minutes=-timeoutvalue).datetime
+        buy_timeout = self.config['unfilledtimeout']['buy']
        sell_timeout = self.config['unfilledtimeout']['sell']
        buy_timeoutthreashold = arrow.utcnow().shift(minutes=-buy_timeout).datetime
        sell_timeoutthreashold = arrow.utcnow().shift(minutes=-sell_timeout).datetime
        for trade in Trade.query.filter(Trade.open_order_id.isnot(None)).all():
            try:
                # FIXME: Somehow the query above returns results
                # where the open_order_id is in fact None.
-                # This is probably because the record got
+                # This is probably because the record get_trades_for_order
                # updated via /forcesell in a different thread.
                if not trade.open_order_id:
                    continue
@ -471,13 +537,11 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
            ordertime = arrow.get(order['datetime']).datetime
            # Check if trade is still actually open
-            if int(order['remaining']) == 0:
+            if order['status'] == 'open':
-                continue
+                if order['side'] == 'buy' and ordertime < buy_timeoutthreashold:
-
+                    self.handle_timedout_limit_buy(trade, order)
-            if order['side'] == 'buy' and ordertime < timeoutthreashold:
+                elif order['side'] == 'sell' and ordertime < sell_timeoutthreashold:
-                self.handle_timedout_limit_buy(trade, order)
+                    self.handle_timedout_limit_sell(trade, order)
            elif order['side'] == 'sell' and ordertime < timeoutthreashold:
                self.handle_timedout_limit_sell(trade, order)
    # FIX: 20180110, why is cancel.order unconditionally here, whereas
    #                it is conditionally called in the
@ -568,7 +632,7 @@ with limit `{buy_limit:.8f} ({stake_amount:.6f} \
                fiat
            )
            message += f'` ({gain}: {fmt_exp_profit:.2f}%, {profit_trade:.8f} {stake}`' \
-                       f'` / {profit_fiat:.3f} {fiat})`'\
+                       f'` / {profit_fiat:.3f} {fiat})`' \
                       ''
        # Because telegram._forcesell does not have the configuration
        # Ignore the FIAT value and does not show the stake_currency as well
--- a/freqtrade/main.py
+++ b/freqtrade/main.py
@ -5,12 +5,14 @@ Read the documentation to know what cli arguments you need.
 """
 import logging
 import sys
 from argparse import Namespace
 from typing import List
 from freqtrade import OperationalException
 from freqtrade.arguments import Arguments
 from freqtrade.configuration import Configuration
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.state import State
 logger = logging.getLogger('freqtrade')
@ -44,6 +46,8 @@ def main(sysargv: List[str]) -> None:
        state = None
        while 1:
            state = freqtrade.worker(old_state=state)
            if state == State.RELOAD_CONF:
                freqtrade = reconfigure(freqtrade, args)
    except KeyboardInterrupt:
        logger.info('SIGINT received, aborting ...')
@ -55,10 +59,28 @@ def main(sysargv: List[str]) -> None:
        logger.exception('Fatal exception!')
    finally:
        if freqtrade:
-            freqtrade.clean()
+            freqtrade.rpc.send_msg('*Status:* `Process died ...`')
            freqtrade.cleanup()
        sys.exit(return_code)
 def reconfigure(freqtrade: FreqtradeBot, args: Namespace) -> FreqtradeBot:
    """
    Cleans up current instance, reloads the configuration and returns the new instance
    """
    # Clean up current modules
    freqtrade.cleanup()
    # Create new instance
    freqtrade = FreqtradeBot(Configuration(args).get_config())
    freqtrade.rpc.send_msg(
        '*Status:* `Config reloaded ...`'.format(
            freqtrade.state.name.lower()
        )
    )
    return freqtrade
 def set_loggers() -> None:
    """
    Set the logger level for Third party libs
--- a/freqtrade/misc.py
+++ b/freqtrade/misc.py
@ -71,7 +71,6 @@ def file_dump_json(filename, data, is_zip=False) -> None:
    :param data: JSON Data to save
    :return:
    """
    print(f'dumping json to "{filename}"')
    if is_zip:
        if not filename.endswith('.gz'):
--- a/freqtrade/optimize/init.py
+++ b/freqtrade/optimize/init.py
@ -11,8 +11,6 @@ from freqtrade import misc, constants
 from freqtrade.exchange import get_ticker_history
 from freqtrade.arguments import TimeRange
 from user_data.hyperopt_conf import hyperopt_optimize_conf
 logger = logging.getLogger(__name__)
@ -83,7 +81,7 @@ def load_tickerdata_file(
 def load_data(datadir: str,
              ticker_interval: str,
-              pairs: Optional[List[str]] = None,
+              pairs: List[str],
              refresh_pairs: Optional[bool] = False,
              timerange: TimeRange = TimeRange(None, None, 0, 0)) -> Dict[str, List]:
    """
@ -92,14 +90,12 @@ def load_data(datadir: str,
    """
    result = {}
    _pairs = pairs or hyperopt_optimize_conf()['exchange']['pair_whitelist']
    # If the user force the refresh of pairs
    if refresh_pairs:
        logger.info('Download data for all pairs and store them in %s', datadir)
-        download_pairs(datadir, _pairs, ticker_interval, timerange=timerange)
+        download_pairs(datadir, pairs, ticker_interval, timerange=timerange)
-    for pair in _pairs:
+    for pair in pairs:
        pairdata = load_tickerdata_file(datadir, pair, ticker_interval, timerange=timerange)
        if pairdata:
            result[pair] = pairdata
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@ -6,7 +6,8 @@ This module contains the backtesting logic
 import logging
 import operator
 from argparse import Namespace
-from typing import Dict, Tuple, Any, List, Optional
+from datetime import datetime
 from typing import Dict, Tuple, Any, List, Optional, NamedTuple
 import arrow
 from pandas import DataFrame
@ -23,6 +24,21 @@ from freqtrade.persistence import Trade
 logger = logging.getLogger(__name__)
 class BacktestResult(NamedTuple):
    """
    NamedTuple Defining BacktestResults inputs.
    """
    pair: str
    profit_percent: float
    profit_abs: float
    open_time: datetime
    close_time: datetime
    open_index: int
    close_index: int
    trade_duration: float
    open_at_end: bool
 class Backtesting(object):
    """
    Backtesting class, this class contains all the logic to run a backtest
@ -31,6 +47,7 @@ class Backtesting(object):
    backtesting = Backtesting(config)
    backtesting.start()
    """
    def __init__(self, config: Dict[str, Any]) -> None:
        self.config = config
        self.analyze = Analyze(self.config)
@ -58,47 +75,63 @@ class Backtesting(object):
            (arrow.get(min(frame.date)), arrow.get(max(frame.date)))
            for frame in data.values()
        ]
-        return min(timeframe, key=operator.itemgetter(0))[0], \
+        return min(timeframe, key=operator.itemgetter(0))[0], max(timeframe, key=operator.itemgetter(1))[1]
            max(timeframe, key=operator.itemgetter(1))[1]
    def _generate_text_table(self, data: Dict[str, Dict], results: DataFrame) -> str:
        """
        Generates and returns a text table for the given backtest data and the results dataframe
        :return: pretty printed table with tabulate as str
        """
        stake_currency = str(self.config.get('stake_currency'))
-        floatfmt = ('s', 'd', '.2f', '.8f', '.1f')
+        floatfmt, headers, tabular_data = self.aggregate(data, results)
        return tabulate(tabular_data, headers=headers, floatfmt=floatfmt, tablefmt="pipe")
    def aggregate(self, data, results):
        stake_currency = self.config.get('stake_currency')
        floatfmt = ('s', 'd', '.2f', '.2f', '.8f', '.1f')
        tabular_data = []
-        headers = ['pair', 'buy count', 'avg profit %',
+        headers = ['pair', 'buy count', 'avg profit %', 'cum profit %',
                   'total profit ' + stake_currency, 'avg duration', 'profit', 'loss']
        for pair in data:
-            result = results[results.currency == pair]
+            result = results[results.pair == pair]
            tabular_data.append([
                pair,
                len(result.index),
                result.profit_percent.mean() * 100.0,
-                result.profit_BTC.sum(),
+                result.profit_percent.sum() * 100.0,
-                result.duration.mean(),
+                result.profit_abs.sum(),
-                len(result[result.profit_BTC > 0]),
+                result.trade_duration.mean(),
-                len(result[result.profit_BTC < 0])
+                len(result[result.profit_abs > 0]),
                len(result[result.profit_abs < 0])
            ])
        # Append Total
        tabular_data.append([
            'TOTAL',
            len(results.index),
            results.profit_percent.mean() * 100.0,
-            results.profit_BTC.sum(),
+            results.profit_percent.sum() * 100.0,
-            results.duration.mean(),
+            results.profit_abs.sum(),
-            len(results[results.profit_BTC > 0]),
+            results.trade_duration.mean(),
-            len(results[results.profit_BTC < 0])
+            len(results[results.profit_abs > 0]),
            len(results[results.profit_abs < 0])
        ])
-        return tabulate(tabular_data, headers=headers, floatfmt=floatfmt, tablefmt="pipe")
+        return floatfmt, headers, tabular_data
    def _store_backtest_result(self, recordfilename: Optional[str], results: DataFrame) -> None:
        records = [(trade_entry.pair, trade_entry.profit_percent,
                    trade_entry.open_time.timestamp(),
                    trade_entry.close_time.timestamp(),
                    trade_entry.open_index - 1, trade_entry.trade_duration)
                   for index, trade_entry in results.iterrows()]
        if records:
            logger.info('Dumping backtest results to %s', recordfilename)
            file_dump_json(recordfilename, records)
    def _get_sell_trade_entry(
            self, pair: str, buy_row: DataFrame,
-            partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[Tuple]:
+            partial_ticker: List, trade_count_lock: Dict, args: Dict) -> Optional[BacktestResult]:
        stake_amount = args['stake_amount']
        max_open_trades = args.get('max_open_trades', 0)
@ -121,15 +154,32 @@ class Backtesting(object):
            buy_signal = sell_row.buy
            if self.analyze.should_sell(trade, sell_row.close, sell_row.date, buy_signal,
                                        sell_row.sell):
-                return \
+                return BacktestResult(pair=pair,
-                    sell_row, \
+                                      profit_percent=trade.calc_profit_percent(rate=sell_row.close),
-                    (
+                                      profit_abs=trade.calc_profit(rate=sell_row.close),
-                        pair,
+                                      open_time=buy_row.date,
-                        trade.calc_profit_percent(rate=sell_row.close),
+                                      close_time=sell_row.date,
-                        trade.calc_profit(rate=sell_row.close),
+                                      trade_duration=(sell_row.date - buy_row.date).seconds // 60,
-                        (sell_row.date - buy_row.date).seconds // 60
+                                      open_index=buy_row.Index,
-                    ), \
+                                      close_index=sell_row.Index,
-                    sell_row.date
+                                      open_at_end=False
                                      )
        if partial_ticker:
            # no sell condition found - trade stil open at end of backtest period
            sell_row = partial_ticker[-1]
            btr = BacktestResult(pair=pair,
                                 profit_percent=trade.calc_profit_percent(rate=sell_row.close),
                                 profit_abs=trade.calc_profit(rate=sell_row.close),
                                 open_time=buy_row.date,
                                 close_time=sell_row.date,
                                 trade_duration=(sell_row.date - buy_row.date).seconds // 60,
                                 open_index=buy_row.Index,
                                 close_index=sell_row.Index,
                                 open_at_end=True
                                 )
            logger.debug('Force_selling still open trade %s with %s perc - %s', btr.pair,
                         btr.profit_percent, btr.profit_abs)
            return btr
        return None
    def backtest(self, args: Dict) -> DataFrame:
@ -145,17 +195,12 @@ class Backtesting(object):
            processed: a processed dictionary with format {pair, data}
            max_open_trades: maximum number of concurrent trades (default: 0, disabled)
            realistic: do we try to simulate realistic trades? (default: True)
            sell_profit_only: sell if profit only
            use_sell_signal: act on sell-signal
        :return: DataFrame
        """
        headers = ['date', 'buy', 'open', 'close', 'sell']
        processed = args['processed']
        max_open_trades = args.get('max_open_trades', 0)
        realistic = args.get('realistic', False)
        record = args.get('record', None)
        recordfilename = args.get('recordfn', 'backtest-result.json')
        records = []
        trades = []
        trade_count_lock: Dict = {}
        for pair, pair_data in processed.items():
@ -170,6 +215,8 @@ class Backtesting(object):
            ticker_data.drop(ticker_data.head(1).index, inplace=True)
            # Convert from Pandas to list for performance reasons
            # (Looping Pandas is slow.)
            ticker = [x for x in ticker_data.itertuples()]
            lock_pair_until = None
@ -187,30 +234,20 @@ class Backtesting(object):
                    trade_count_lock[row.date] = trade_count_lock.get(row.date, 0) + 1
-                ret = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
+                trade_entry = self._get_sell_trade_entry(pair, row, ticker[index + 1:],
-                                                 trade_count_lock, args)
+                                                         trade_count_lock, args)
-                if ret:
+                if trade_entry:
-                    row2, trade_entry, next_date = ret
+                    lock_pair_until = trade_entry.close_time
                    lock_pair_until = next_date
                    trades.append(trade_entry)
-                    if record:
+                else:
-                        # Note, need to be json.dump friendly
+                    # Set lock_pair_until to end of testing period if trade could not be closed
-                        # record a tuple of pair, current_profit_percent,
+                    # This happens only if the buy-signal was with the last candle
-                        # entry-date, duration
+                    lock_pair_until = ticker_data.iloc[-1].date
                        records.append((pair, trade_entry[1],
                                        row.date.strftime('%s'),
                                        row2.date.strftime('%s'),
                                        index, trade_entry[3]))
        # For now export inside backtest(), maybe change so that backtest()
        # returns a tuple like: (dataframe, records, logs, etc)
        if record and record.find('trades') >= 0:
            logger.info('Dumping backtest results to %s', recordfilename)
            file_dump_json(recordfilename, records)
        labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
        return DataFrame.from_records(trades, columns=labels)
-    def start(self) -> None:
+        return DataFrame.from_records(trades, columns=BacktestResult._fields)
    def start(self):
        """
        Run a backtesting end-to-end
        :return: None
@ -237,6 +274,9 @@ class Backtesting(object):
                timerange=timerange
            )
        if not data:
            logger.critical("No data found. Terminating.")
            return
        # Ignore max_open_trades in backtesting, except realistic flag was passed
        if self.config.get('realistic_simulation', False):
            max_open_trades = self.config['max_open_trades']
@ -256,24 +296,22 @@ class Backtesting(object):
        )
        # Execute backtest and print results
        sell_profit_only = self.config.get('experimental', {}).get('sell_profit_only', False)
        use_sell_signal = self.config.get('experimental', {}).get('use_sell_signal', False)
        results = self.backtest(
            {
                'stake_amount': self.config.get('stake_amount'),
                'processed': preprocessed,
                'max_open_trades': max_open_trades,
                'realistic': self.config.get('realistic_simulation', False),
                'sell_profit_only': sell_profit_only,
                'use_sell_signal': use_sell_signal,
                'record': self.config.get('export'),
                'recordfn': self.config.get('exportfilename'),
            }
        )
        if self.config.get('export', False):
            self._store_backtest_result(self.config.get('exportfilename'), results)
        logger.info(
-            '\n==================================== '
+            '\n======================================== '
            'BACKTESTING REPORT'
-            ' ====================================\n'
+            ' =========================================\n'
            '%s',
            self._generate_text_table(
                data,
@ -281,6 +319,20 @@ class Backtesting(object):
            )
        )
        logger.info(
            '\n====================================== '
            'LEFT OPEN TRADES REPORT'
            ' ======================================\n'
            '%s',
            self._generate_text_table(
                data,
                results.loc[results.open_at_end]
            )
        )
        table = self.aggregate(data, results)
        return results, table
 def setup_configuration(args: Namespace) -> Dict[str, Any]:
    """
--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@ -19,7 +19,6 @@ from typing import Dict, Any, Callable, Optional
 import numpy
 import talib.abstract as ta
 from hyperopt import STATUS_FAIL, STATUS_OK, Trials, fmin, hp, space_eval, tpe
 from hyperopt.mongoexp import MongoTrials
 from pandas import DataFrame
 import freqtrade.vendor.qtpylib.indicators as qtpylib
@ -27,7 +26,6 @@ from freqtrade.arguments import Arguments
 from freqtrade.configuration import Configuration
 from freqtrade.optimize import load_data
 from freqtrade.optimize.backtesting import Backtesting
 from user_data.hyperopt_conf import hyperopt_optimize_conf
 logger = logging.getLogger(__name__)
@ -222,9 +220,7 @@ class Hyperopt(Backtesting):
                results['result'],
                results['loss']
            )
            print(log_msg)
        else:
            print('.', end='')
            sys.stdout.flush()
    def calculate_loss(self, total_profit: float, trade_count: int, trade_duration: float) -> float:
@ -451,7 +447,7 @@ class Hyperopt(Backtesting):
        total_profit = results.profit_percent.sum()
        trade_count = len(results.index)
-        trade_duration = results.duration.mean()
+        trade_duration = results.trade_duration.mean()
        if trade_count == 0 or trade_duration > self.max_accepted_trade_duration:
            print('.', end='')
@ -488,10 +484,10 @@ class Hyperopt(Backtesting):
                'Total profit {: 11.8f} {} ({:.4f}Σ%). Avg duration {:5.1f} mins.').format(
                    len(results.index),
                    results.profit_percent.mean() * 100.0,
-                    results.profit_BTC.sum(),
+                    results.profit_abs.sum(),
                    self.config['stake_currency'],
                    results.profit_percent.sum(),
-                    results.duration.mean(),
+                    results.trade_duration.mean(),
                )
    def start(self) -> None:
@ -508,32 +504,20 @@ class Hyperopt(Backtesting):
            self.analyze.populate_indicators = Hyperopt.populate_indicators  # type: ignore
        self.processed = self.tickerdata_to_dataframe(data)
-        if self.config.get('mongodb'):
+        logger.info('Preparing Trials..')
-            logger.info('Using mongodb ...')
+        signal.signal(signal.SIGINT, self.signal_handler)
        # read trials file if we have one
        if os.path.exists(self.trials_file) and os.path.getsize(self.trials_file) > 0:
            self.trials = self.read_trials()
            self.current_tries = len(self.trials.results)
            self.total_tries += self.current_tries
            logger.info(
-                'Start scripts/start-mongodb.sh and start-hyperopt-worker.sh manually!'
+                'Continuing with trials. Current: %d, Total: %d',
                self.current_tries,
                self.total_tries
            )
            db_name = 'freqtrade_hyperopt'
            self.trials = MongoTrials(
                arg='mongo://127.0.0.1:1234/{}/jobs'.format(db_name),
                exp_key='exp1'
            )
        else:
            logger.info('Preparing Trials..')
            signal.signal(signal.SIGINT, self.signal_handler)
            # read trials file if we have one
            if os.path.exists(self.trials_file) and os.path.getsize(self.trials_file) > 0:
                self.trials = self.read_trials()
                self.current_tries = len(self.trials.results)
                self.total_tries += self.current_tries
                logger.info(
                    'Continuing with trials. Current: %d, Total: %d',
                    self.current_tries,
                    self.total_tries
                )
        try:
            best_parameters = fmin(
                fn=self.generate_optimizer,
@ -589,18 +573,14 @@ def start(args: Namespace) -> None:
    """
    # Remove noisy log messages
    logging.getLogger('hyperopt.mongoexp').setLevel(logging.WARNING)
    logging.getLogger('hyperopt.tpe').setLevel(logging.WARNING)
    # Initialize configuration
    # Monkey patch the configuration with hyperopt_conf.py
    configuration = Configuration(args)
    logger.info('Starting freqtrade in Hyperopt mode')
    config = configuration.load_config()
    optimize_config = hyperopt_optimize_conf()
    config = configuration._load_common_config(optimize_config)
    config = configuration._load_backtesting_config(config)
    config = configuration._load_hyperopt_config(config)
    config['exchange']['key'] = ''
    config['exchange']['secret'] = ''
--- a/freqtrade/persistence.py
+++ b/freqtrade/persistence.py
@ -154,6 +154,12 @@ class Trade(_DECL_BASE):
    open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
    close_date = Column(DateTime)
    open_order_id = Column(String)
    # absolute value of the stop loss
    stop_loss = Column(Float, nullable=True, default=0.0)
    # absolute value of the initial stop loss
    initial_stop_loss = Column(Float, nullable=True, default=0.0)
    # absolute value of the highest reached price
    max_rate = Column(Float, nullable=True, default=0.0)
    def __repr__(self):
        return 'Trade(id={}, pair={}, amount={:.8f}, open_rate={:.8f}, open_since={})'.format(
@ -164,6 +170,50 @@ class Trade(_DECL_BASE):
            arrow.get(self.open_date).humanize() if self.is_open else 'closed'
        )
    def adjust_stop_loss(self, current_price, stoploss):
        """
        this adjusts the stop loss to it's most recently observed
        setting
        :param current_price:
        :param stoploss:
        :return:
        """
        new_loss = Decimal(current_price * (1 - abs(stoploss)))
        # keeping track of the highest observed rate for this trade
        if self.max_rate is None:
            self.max_rate = current_price
        else:
            if current_price > self.max_rate:
                self.max_rate = current_price
        # no stop loss assigned yet
        if self.stop_loss is None or self.stop_loss == 0:
            logger.debug("assigning new stop loss")
            self.stop_loss = new_loss
            self.initial_stop_loss = new_loss
        # evaluate if the stop loss needs to be updated
        else:
            if new_loss > self.stop_loss:  # stop losses only walk up, never down!
                self.stop_loss = new_loss
                logger.debug("adjusted stop loss")
            else:
                logger.debug("keeping current stop loss")
        logger.debug(
            "{} - current price {:.8f}, bought at {:.8f} and calculated "
            "stop loss is at: {:.8f} initial stop at {:.8f}. trailing stop loss saved us: {:.8f} "
            "and max observed rate was {:.8f}".format(
                self.pair, current_price, self.open_rate,
                self.initial_stop_loss,
                self.stop_loss, float(self.stop_loss) - float(self.initial_stop_loss),
                self.max_rate
            ))
    def update(self, order: Dict) -> None:
        """
        Updates this entity with amount and actual open/close rates.
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@ -2,24 +2,34 @@
 This module contains class to define a RPC communications
 """
 import logging
 from abc import abstractmethod
 from datetime import datetime, timedelta, date
 from decimal import Decimal
-from typing import Dict, Tuple, Any
+from typing import Dict, Tuple, Any, List
 import arrow
 import sqlalchemy as sql
 from pandas import DataFrame
 from numpy import mean, nan_to_num
 from pandas import DataFrame
 from freqtrade import exchange
 from freqtrade.misc import shorten_date
 from freqtrade.persistence import Trade
 from freqtrade.state import State
 logger = logging.getLogger(__name__)
 class RPCException(Exception):
    """
    Should be raised with a rpc-formatted message in an _rpc_* method
    if the required state is wrong, i.e.:
    raise RPCException('*Status:* `no active trade`')
    """
    pass
 class RPC(object):
    """
    RPC class can be used to have extra feature, like bot data, and access to DB data
@ -30,20 +40,32 @@ class RPC(object):
        :param freqtrade: Instance of a freqtrade bot
        :return: None
        """
-        self.freqtrade = freqtrade
+        self._freqtrade = freqtrade
-    def rpc_trade_status(self) -> Tuple[bool, Any]:
+    @abstractmethod
    def cleanup(self) -> None:
        """ Cleanup pending module resources """
    @property
    @abstractmethod
    def name(self) -> str:
        """ Returns the lowercase name of this module """
    @abstractmethod
    def send_msg(self, msg: str) -> None:
        """ Sends a message to all registered rpc modules """
    def _rpc_trade_status(self) -> List[str]:
        """
        Below follows the RPC backend it is prefixed with rpc_ to raise awareness that it is
        a remotely exposed function
        :return:
        """
        # Fetch open trade
        trades = Trade.query.filter(Trade.is_open.is_(True)).all()
-        if self.freqtrade.state != State.RUNNING:
+        if self._freqtrade.state != State.RUNNING:
-            return True, '*Status:* `trader is not running`'
+            raise RPCException('*Status:* `trader is not running`')
        elif not trades:
-            return True, '*Status:* `no active trade`'
+            raise RPCException('*Status:* `no active trade`')
        else:
            result = []
            for trade in trades:
@ -64,6 +86,7 @@ class RPC(object):
                          "*Close Rate:* `{close_rate}`\n" \
                          "*Current Rate:* `{current_rate:.8f}`\n" \
                          "*Close Profit:* `{close_profit}`\n" \
                          "*Stake Value:* `{stake_value}`\n" \
                          "*Current Profit:* `{current_profit:.2f}%`\n" \
                          "*Open Order:* `{open_order}`"\
                          .format(
@ -76,20 +99,21 @@ class RPC(object):
                              current_rate=current_rate,
                              amount=round(trade.amount, 8),
                              close_profit=fmt_close_profit,
                              stake_value=round(current_rate * trade.amount, 8),
                              current_profit=round(current_profit * 100, 2),
                              open_order='({} {} rem={:.8f})'.format(
                                  order['type'], order['side'], order['remaining']
                              ) if order else None,
                          )
                result.append(message)
-            return False, result
+            return result
-    def rpc_status_table(self) -> Tuple[bool, Any]:
+    def _rpc_status_table(self) -> DataFrame:
        trades = Trade.query.filter(Trade.is_open.is_(True)).all()
-        if self.freqtrade.state != State.RUNNING:
+        if self._freqtrade.state != State.RUNNING:
-            return True, '*Status:* `trader is not running`'
+            raise RPCException('*Status:* `trader is not running`')
        elif not trades:
-            return True, '*Status:* `no active order`'
+            raise RPCException('*Status:* `no active order`')
        else:
            trades_list = []
            for trade in trades:
@ -99,28 +123,25 @@ class RPC(object):
                    trade.id,
                    trade.pair,
                    shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)),
-                    '{:.2f}%'.format(100 * trade.calc_profit_percent(current_rate))
+                    '{:.2f}%'.format(100 * trade.calc_profit_percent(current_rate)),
                    '{:.8f}'.format(trade.amount * current_rate)
                ])
-            columns = ['ID', 'Pair', 'Since', 'Profit']
+            columns = ['ID', 'Pair', 'Since', 'Profit', 'Value']
            df_statuses = DataFrame.from_records(trades_list, columns=columns)
            df_statuses = df_statuses.set_index(columns[0])
-            # The style used throughout is to return a tuple
+            return df_statuses
            # consisting of (error_occured?, result)
            # Another approach would be to just return the
            # result, or raise error
            return False, df_statuses
-    def rpc_daily_profit(
+    def _rpc_daily_profit(
            self, timescale: int,
-            stake_currency: str, fiat_display_currency: str) -> Tuple[bool, Any]:
+            stake_currency: str, fiat_display_currency: str) -> List[List[Any]]:
        today = datetime.utcnow().date()
        profit_days: Dict[date, Dict] = {}
        if not (isinstance(timescale, int) and timescale > 0):
-            return True, '*Daily [n]:* `must be an integer greater than 0`'
+            raise RPCException('*Daily [n]:* `must be an integer greater than 0`')
-        fiat = self.freqtrade.fiat_converter
+        fiat = self._freqtrade.fiat_converter
        for day in range(0, timescale):
            profitday = today - timedelta(days=day)
            trades = Trade.query \
@ -135,7 +156,7 @@ class RPC(object):
                'trades': len(trades)
            }
-        stats = [
+        return [
            [
                key,
                '{value:.8f} {symbol}'.format(
@ -157,13 +178,10 @@ class RPC(object):
            ]
            for key, value in profit_days.items()
        ]
        return False, stats
-    def rpc_trade_statistics(
+    def _rpc_trade_statistics(
-            self, stake_currency: str, fiat_display_currency: str) -> Tuple[bool, Any]:
+            self, stake_currency: str, fiat_display_currency: str) -> Dict[str, Any]:
-        """
+        """ Returns cumulative profit statistics """
        :return: cumulative profit statistics.
        """
        trades = Trade.query.order_by(Trade.id).all()
        profit_all_coin = []
@ -201,13 +219,13 @@ class RPC(object):
            .order_by(sql.text('profit_sum DESC')).first()
        if not best_pair:
-            return True, '*Status:* `no closed trade`'
+            raise RPCException('*Status:* `no closed trade`')
        bp_pair, bp_rate = best_pair
        # FIX: we want to keep fiatconverter in a state/environment,
        #      doing this will utilize its caching functionallity, instead we reinitialize it here
-        fiat = self.freqtrade.fiat_converter
+        fiat = self._freqtrade.fiat_converter
        # Prepare data to display
        profit_closed_coin = round(sum(profit_closed_coin), 8)
        profit_closed_percent = round(nan_to_num(mean(profit_closed_percent)) * 100, 2)
@ -224,35 +242,29 @@ class RPC(object):
            fiat_display_currency
        )
        num = float(len(durations) or 1)
-        return (
+        return {
-            False,
+            'profit_closed_coin': profit_closed_coin,
-            {
+            'profit_closed_percent': profit_closed_percent,
-                'profit_closed_coin': profit_closed_coin,
+            'profit_closed_fiat': profit_closed_fiat,
-                'profit_closed_percent': profit_closed_percent,
+            'profit_all_coin': profit_all_coin,
-                'profit_closed_fiat': profit_closed_fiat,
+            'profit_all_percent': profit_all_percent,
-                'profit_all_coin': profit_all_coin,
+            'profit_all_fiat': profit_all_fiat,
-                'profit_all_percent': profit_all_percent,
+            'trade_count': len(trades),
-                'profit_all_fiat': profit_all_fiat,
+            'first_trade_date': arrow.get(trades[0].open_date).humanize(),
-                'trade_count': len(trades),
+            'latest_trade_date': arrow.get(trades[-1].open_date).humanize(),
-                'first_trade_date': arrow.get(trades[0].open_date).humanize(),
+            'avg_duration': str(timedelta(seconds=sum(durations) / num)).split('.')[0],
-                'latest_trade_date': arrow.get(trades[-1].open_date).humanize(),
+            'best_pair': bp_pair,
-                'avg_duration': str(timedelta(seconds=sum(durations) / num)).split('.')[0],
+            'best_rate': round(bp_rate * 100, 2),
-                'best_pair': bp_pair,
+        }
                'best_rate': round(bp_rate * 100, 2)
            }
        )
-    def rpc_balance(self, fiat_display_currency: str) -> Tuple[bool, Any]:
+    def _rpc_balance(self, fiat_display_currency: str) -> Tuple[List[Dict], float, str, float]:
-        """
+        """ Returns current account balance per crypto """
        :return: current account balance per crypto
        """
        output = []
        total = 0.0
        for coin, balance in exchange.get_balances().items():
            if not balance['total']:
                continue
            rate = None
            if coin == 'BTC':
                rate = 1.0
            else:
@ -272,39 +284,39 @@ class RPC(object):
                }
            )
        if total == 0.0:
-            return True, '`All balances are zero.`'
+            raise RPCException('`All balances are zero.`')
-        fiat = self.freqtrade.fiat_converter
+        fiat = self._freqtrade.fiat_converter
        symbol = fiat_display_currency
        value = fiat.convert_amount(total, 'BTC', symbol)
-        return False, (output, total, symbol, value)
+        return output, total, symbol, value
-    def rpc_start(self) -> Tuple[bool, str]:
+    def _rpc_start(self) -> str:
-        """
+        """ Handler for start """
-        Handler for start.
+        if self._freqtrade.state == State.RUNNING:
-        """
+            return '*Status:* `already running`'
        if self.freqtrade.state == State.RUNNING:
            return True, '*Status:* `already running`'
-        self.freqtrade.state = State.RUNNING
+        self._freqtrade.state = State.RUNNING
-        return False, '`Starting trader ...`'
+        return '`Starting trader ...`'
-    def rpc_stop(self) -> Tuple[bool, str]:
+    def _rpc_stop(self) -> str:
-        """
+        """ Handler for stop """
-        Handler for stop.
+        if self._freqtrade.state == State.RUNNING:
-        """
+            self._freqtrade.state = State.STOPPED
-        if self.freqtrade.state == State.RUNNING:
+            return '`Stopping trader ...`'
            self.freqtrade.state = State.STOPPED
            return False, '`Stopping trader ...`'
-        return True, '*Status:* `already stopped`'
+        return '*Status:* `already stopped`'
    def _rpc_reload_conf(self) -> str:
        """ Handler for reload_conf. """
        self._freqtrade.state = State.RELOAD_CONF
        return '*Status:* `Reloading config ...`'
    # FIX: no test for this!!!!
-    def rpc_forcesell(self, trade_id) -> Tuple[bool, Any]:
+    def _rpc_forcesell(self, trade_id) -> None:
        """
        Handler for forcesell <id>.
        Sells the given trade at current price
        :return: error or None
        """
        def _exec_forcesell(trade: Trade) -> None:
            # Check if there is there is an open order
@ -330,17 +342,17 @@ class RPC(object):
            # Get current rate and execute sell
            current_rate = exchange.get_ticker(trade.pair, False)['bid']
-            self.freqtrade.execute_sell(trade, current_rate)
+            self._freqtrade.execute_sell(trade, current_rate)
        # ---- EOF def _exec_forcesell ----
-        if self.freqtrade.state != State.RUNNING:
+        if self._freqtrade.state != State.RUNNING:
-            return True, '`trader is not running`'
+            raise RPCException('`trader is not running`')
        if trade_id == 'all':
            # Execute sell for all open orders
            for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
                _exec_forcesell(trade)
-            return False, ''
+            return
        # Query for trade
        trade = Trade.query.filter(
@ -351,19 +363,18 @@ class RPC(object):
        ).first()
        if not trade:
            logger.warning('forcesell: Invalid argument received')
-            return True, 'Invalid argument.'
+            raise RPCException('Invalid argument.')
        _exec_forcesell(trade)
        Trade.session.flush()
        return False, ''
-    def rpc_performance(self) -> Tuple[bool, Any]:
+    def _rpc_performance(self) -> List[Dict]:
        """
        Handler for performance.
        Shows a performance statistic from finished trades
        """
-        if self.freqtrade.state != State.RUNNING:
+        if self._freqtrade.state != State.RUNNING:
-            return True, '`trader is not running`'
+            raise RPCException('`trader is not running`')
        pair_rates = Trade.session.query(Trade.pair,
                                         sql.func.sum(Trade.close_profit).label('profit_sum'),
@ -372,19 +383,14 @@ class RPC(object):
            .group_by(Trade.pair) \
            .order_by(sql.text('profit_sum DESC')) \
            .all()
-        trades = []
+        return [
-        for (pair, rate, count) in pair_rates:
+            {'pair': pair, 'profit': round(rate * 100, 2), 'count': count}
-            trades.append({'pair': pair, 'profit': round(rate * 100, 2), 'count': count})
+            for pair, rate, count in pair_rates
        ]
-        return False, trades
+    def _rpc_count(self) -> List[Trade]:
        """ Returns the number of trades running """
        if self._freqtrade.state != State.RUNNING:
            raise RPCException('`trader is not running`')
-    def rpc_count(self) -> Tuple[bool, Any]:
+        return Trade.query.filter(Trade.is_open.is_(True)).all()
        """
        Returns the number of trades running
        :return: None
        """
        if self.freqtrade.state != State.RUNNING:
            return True, '`trader is not running`'
        trades = Trade.query.filter(Trade.is_open.is_(True)).all()
        return False, trades
--- a/freqtrade/rpc/rpc_manager.py
+++ b/freqtrade/rpc/rpc_manager.py
@ -1,11 +1,10 @@
 """
 This module contains class to manage RPC communications (Telegram, Slack, ...)
 """
 from typing import Any, List
 import logging
 from typing import List
-from freqtrade.rpc.telegram import Telegram
+from freqtrade.rpc.rpc import RPC
 logger = logging.getLogger(__name__)
@ -15,36 +14,23 @@ class RPCManager(object):
    Class to manage RPC objects (Telegram, Slack, ...)
    """
    def __init__(self, freqtrade) -> None:
-        """
+        """ Initializes all enabled rpc modules """
-        Initializes all enabled rpc modules
+        self.registered_modules: List[RPC] = []
        :param config: config to use
        :return: None
        """
        self.freqtrade = freqtrade
-        self.registered_modules: List[str] = []
+        # Enable telegram
-        self.telegram: Any = None
+        if freqtrade.config['telegram'].get('enabled', False):
        self._init()
    def _init(self) -> None:
        """
        Init RPC modules
        :return:
        """
        if self.freqtrade.config['telegram'].get('enabled', False):
            logger.info('Enabling rpc.telegram ...')
-            self.registered_modules.append('telegram')
+            from freqtrade.rpc.telegram import Telegram
-            self.telegram = Telegram(self.freqtrade)
+            self.registered_modules.append(Telegram(freqtrade))
    def cleanup(self) -> None:
-        """
+        """ Stops all enabled rpc modules """
-        Stops all enabled rpc modules
+        logger.info('Cleaning up rpc modules ...')
-        :return: None
+        while self.registered_modules:
-        """
+            mod = self.registered_modules.pop()
-        if 'telegram' in self.registered_modules:
+            logger.debug('Cleaning up rpc.%s ...', mod.name)
-            logger.info('Cleaning up rpc.telegram ...')
+            mod.cleanup()
-            self.registered_modules.remove('telegram')
+            del mod
            self.telegram.cleanup()
    def send_msg(self, msg: str) -> None:
        """
@ -52,6 +38,7 @@ class RPCManager(object):
        :param msg: message
        :return: None
        """
-        logger.info(msg)
+        logger.info('Sending rpc message: %s', msg)
-        if 'telegram' in self.registered_modules:
+        for mod in self.registered_modules:
-            self.telegram.send_msg(msg)
+            logger.debug('Forwarding message to rpc.%s', mod.name)
            mod.send_msg(msg)
--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@ -12,11 +12,12 @@ from telegram.error import NetworkError, TelegramError
 from telegram.ext import CommandHandler, Updater
 from freqtrade.__init__ import __version__
-from freqtrade.rpc.rpc import RPC
+from freqtrade.rpc.rpc import RPC, RPCException
 logger = logging.getLogger(__name__)
 logger.debug('Included module rpc.telegram ...')
 def authorized_only(command_handler: Callable[[Any, Bot, Update], None]) -> Callable[..., Any]:
    """
@ -25,9 +26,7 @@ def authorized_only(command_handler: Callable[[Any, Bot, Update], None]) -> Call
    :return: decorated function
    """
    def wrapper(self, *args, **kwargs):
-        """
+        """ Decorator logic """
        Decorator logic
        """
        update = kwargs.get('update') or args[1]
        # Reject unauthorized messages
@ -54,9 +53,12 @@ def authorized_only(command_handler: Callable[[Any, Bot, Update], None]) -> Call
 class Telegram(RPC):
-    """
+    """  This class handles all telegram communication """
-    Telegram, this class send messages to Telegram
+
-    """
+    @property
    def name(self) -> str:
        return "telegram"
    def __init__(self, freqtrade) -> None:
        """
        Init the Telegram call, and init the super class RPC
@ -74,12 +76,7 @@ class Telegram(RPC):
        Initializes this module with the given config,
        registers all known command handlers
        and starts polling for message updates
        :param config: config to use
        :return: None
        """
        if not self.is_enabled():
            return
        self._updater = Updater(token=self._config['telegram']['token'], workers=0)
        # Register command handler and start telegram message polling
@ -93,6 +90,7 @@ class Telegram(RPC):
            CommandHandler('performance', self._performance),
            CommandHandler('daily', self._daily),
            CommandHandler('count', self._count),
            CommandHandler('reload_conf', self._reload_conf),
            CommandHandler('help', self._help),
            CommandHandler('version', self._version),
        ]
@ -114,16 +112,11 @@ class Telegram(RPC):
        Stops all running telegram threads.
        :return: None
        """
        if not self.is_enabled():
            return
        self._updater.stop()
-    def is_enabled(self) -> bool:
+    def send_msg(self, msg: str) -> None:
-        """
+        """ Send a message to telegram channel """
-        Returns True if the telegram module is activated, False otherwise
+        self._send_msg(msg)
        """
        return bool(self._config.get('telegram', {}).get('enabled', False))
    @authorized_only
    def _status(self, bot: Bot, update: Update) -> None:
@ -142,13 +135,11 @@ class Telegram(RPC):
            self._status_table(bot, update)
            return
-        # Fetch open trade
+        try:
-        (error, trades) = self.rpc_trade_status()
+            for trade_msg in self._rpc_trade_status():
-        if error:
+                self._send_msg(trade_msg, bot=bot)
-            self.send_msg(trades, bot=bot)
+        except RPCException as e:
-        else:
+            self._send_msg(str(e), bot=bot)
            for trademsg in trades:
                self.send_msg(trademsg, bot=bot)
    @authorized_only
    def _status_table(self, bot: Bot, update: Update) -> None:
@ -159,15 +150,12 @@ class Telegram(RPC):
        :param update: message update
        :return: None
        """
-        # Fetch open trade
+        try:
-        (err, df_statuses) = self.rpc_status_table()
+            df_statuses = self._rpc_status_table()
        if err:
            self.send_msg(df_statuses, bot=bot)
        else:
            message = tabulate(df_statuses, headers='keys', tablefmt='simple')
-            message = "<pre>{}</pre>".format(message)
+            self._send_msg("<pre>{}</pre>".format(message), parse_mode=ParseMode.HTML)
-
+        except RPCException as e:
-            self.send_msg(message, parse_mode=ParseMode.HTML)
+            self._send_msg(str(e), bot=bot)
    @authorized_only
    def _daily(self, bot: Bot, update: Update) -> None:
@ -182,27 +170,25 @@ class Telegram(RPC):
            timescale = int(update.message.text.replace('/daily', '').strip())
        except (TypeError, ValueError):
            timescale = 7
-        (error, stats) = self.rpc_daily_profit(
+        try:
-            timescale,
+            stats = self._rpc_daily_profit(
-            self._config['stake_currency'],
+                timescale,
-            self._config['fiat_display_currency']
+                self._config['stake_currency'],
-        )
+                self._config['fiat_display_currency']
-        if error:
+            )
            self.send_msg(stats, bot=bot)
        else:
            stats = tabulate(stats,
                             headers=[
                                 'Day',
                                 'Profit {}'.format(self._config['stake_currency']),
-                                 'Profit {}'.format(self._config['fiat_display_currency'])
+                                 'Profit {}'.format(self._config['fiat_display_currency']),
                                 'Trades'
                             ],
                             tablefmt='simple')
            message = '<b>Daily Profit over the last {} days</b>:\n<pre>{}</pre>'\
-                      .format(
+                      .format(timescale, stats)
-                          timescale,
+            self._send_msg(message, bot=bot, parse_mode=ParseMode.HTML)
-                          stats
+        except RPCException as e:
-                      )
+            self._send_msg(str(e), bot=bot)
            self.send_msg(message, bot=bot, parse_mode=ParseMode.HTML)
    @authorized_only
    def _profit(self, bot: Bot, update: Update) -> None:
@ -213,67 +199,63 @@ class Telegram(RPC):
        :param update: message update
        :return: None
        """
-        (error, stats) = self.rpc_trade_statistics(
+        try:
-            self._config['stake_currency'],
+            stats = self._rpc_trade_statistics(
-            self._config['fiat_display_currency']
+                self._config['stake_currency'],
-        )
+                self._config['fiat_display_currency'])
        if error:
            self.send_msg(stats, bot=bot)
            return
-        # Message to display
+            # Message to display
-        markdown_msg = "*ROI:* Close trades\n" \
+            markdown_msg = "*ROI:* Close trades\n" \
-                       "∙ `{profit_closed_coin:.8f} {coin} ({profit_closed_percent:.2f}%)`\n" \
+                           "∙ `{profit_closed_coin:.8f} {coin} ({profit_closed_percent:.2f}%)`\n" \
-                       "∙ `{profit_closed_fiat:.3f} {fiat}`\n" \
+                           "∙ `{profit_closed_fiat:.3f} {fiat}`\n" \
-                       "*ROI:* All trades\n" \
+                           "*ROI:* All trades\n" \
-                       "∙ `{profit_all_coin:.8f} {coin} ({profit_all_percent:.2f}%)`\n" \
+                           "∙ `{profit_all_coin:.8f} {coin} ({profit_all_percent:.2f}%)`\n" \
-                       "∙ `{profit_all_fiat:.3f} {fiat}`\n" \
+                           "∙ `{profit_all_fiat:.3f} {fiat}`\n" \
-                       "*Total Trade Count:* `{trade_count}`\n" \
+                           "*Total Trade Count:* `{trade_count}`\n" \
-                       "*First Trade opened:* `{first_trade_date}`\n" \
+                           "*First Trade opened:* `{first_trade_date}`\n" \
-                       "*Latest Trade opened:* `{latest_trade_date}`\n" \
+                           "*Latest Trade opened:* `{latest_trade_date}`\n" \
-                       "*Avg. Duration:* `{avg_duration}`\n" \
+                           "*Avg. Duration:* `{avg_duration}`\n" \
-                       "*Best Performing:* `{best_pair}: {best_rate:.2f}%`"\
+                           "*Best Performing:* `{best_pair}: {best_rate:.2f}%`"\
-                       .format(
+                           .format(
-                           coin=self._config['stake_currency'],
+                               coin=self._config['stake_currency'],
-                           fiat=self._config['fiat_display_currency'],
+                               fiat=self._config['fiat_display_currency'],
-                           profit_closed_coin=stats['profit_closed_coin'],
+                               profit_closed_coin=stats['profit_closed_coin'],
-                           profit_closed_percent=stats['profit_closed_percent'],
+                               profit_closed_percent=stats['profit_closed_percent'],
-                           profit_closed_fiat=stats['profit_closed_fiat'],
+                               profit_closed_fiat=stats['profit_closed_fiat'],
-                           profit_all_coin=stats['profit_all_coin'],
+                               profit_all_coin=stats['profit_all_coin'],
-                           profit_all_percent=stats['profit_all_percent'],
+                               profit_all_percent=stats['profit_all_percent'],
-                           profit_all_fiat=stats['profit_all_fiat'],
+                               profit_all_fiat=stats['profit_all_fiat'],
-                           trade_count=stats['trade_count'],
+                               trade_count=stats['trade_count'],
-                           first_trade_date=stats['first_trade_date'],
+                               first_trade_date=stats['first_trade_date'],
-                           latest_trade_date=stats['latest_trade_date'],
+                               latest_trade_date=stats['latest_trade_date'],
-                           avg_duration=stats['avg_duration'],
+                               avg_duration=stats['avg_duration'],
-                           best_pair=stats['best_pair'],
+                               best_pair=stats['best_pair'],
-                           best_rate=stats['best_rate']
+                               best_rate=stats['best_rate']
-                       )
+                           )
-        self.send_msg(markdown_msg, bot=bot)
+            self._send_msg(markdown_msg, bot=bot)
        except RPCException as e:
            self._send_msg(str(e), bot=bot)
    @authorized_only
    def _balance(self, bot: Bot, update: Update) -> None:
-        """
+        """ Handler for /balance """
-        Handler for /balance
+        try:
-        """
+            currencys, total, symbol, value = \
-        (error, result) = self.rpc_balance(self._config['fiat_display_currency'])
+                self._rpc_balance(self._config['fiat_display_currency'])
-        if error:
+            output = ''
-            self.send_msg('`All balances are zero.`')
+            for currency in currencys:
-            return
+                output += "*{currency}:*\n" \
                          "\t`Available: {available: .8f}`\n" \
                          "\t`Balance: {balance: .8f}`\n" \
                          "\t`Pending: {pending: .8f}`\n" \
                          "\t`Est. BTC: {est_btc: .8f}`\n".format(**currency)
-        (currencys, total, symbol, value) = result
+            output += "\n*Estimated Value*:\n" \
-        output = ''
+                      "\t`BTC: {0: .8f}`\n" \
-        for currency in currencys:
+                      "\t`{1}: {2: .2f}`\n".format(total, symbol, value)
-            output += "*{currency}:*\n" \
+            self._send_msg(output, bot=bot)
-                      "\t`Available: {available: .8f}`\n" \
+        except RPCException as e:
-                      "\t`Balance: {balance: .8f}`\n" \
+            self._send_msg(str(e), bot=bot)
                      "\t`Pending: {pending: .8f}`\n" \
                      "\t`Est. BTC: {est_btc: .8f}`\n".format(**currency)
        output += "\n*Estimated Value*:\n" \
                  "\t`BTC: {0: .8f}`\n" \
                  "\t`{1}: {2: .2f}`\n".format(total, symbol, value)
        self.send_msg(output)
    @authorized_only
    def _start(self, bot: Bot, update: Update) -> None:
@ -284,9 +266,8 @@ class Telegram(RPC):
        :param update: message update
        :return: None
        """
-        (error, msg) = self.rpc_start()
+        msg = self._rpc_start()
-        if error:
+        self._send_msg(msg, bot=bot)
            self.send_msg(msg, bot=bot)
    @authorized_only
    def _stop(self, bot: Bot, update: Update) -> None:
@ -297,8 +278,20 @@ class Telegram(RPC):
        :param update: message update
        :return: None
        """
-        (error, msg) = self.rpc_stop()
+        msg = self._rpc_stop()
-        self.send_msg(msg, bot=bot)
+        self._send_msg(msg, bot=bot)
    @authorized_only
    def _reload_conf(self, bot: Bot, update: Update) -> None:
        """
        Handler for /reload_conf.
        Triggers a config file reload
        :param bot: telegram bot
        :param update: message update
        :return: None
        """
        msg = self._rpc_reload_conf()
        self._send_msg(msg, bot=bot)
    @authorized_only
    def _forcesell(self, bot: Bot, update: Update) -> None:
@ -311,10 +304,10 @@ class Telegram(RPC):
        """
        trade_id = update.message.text.replace('/forcesell', '').strip()
-        (error, message) = self.rpc_forcesell(trade_id)
+        try:
-        if error:
+            self._rpc_forcesell(trade_id)
-            self.send_msg(message, bot=bot)
+        except RPCException as e:
-            return
+            self._send_msg(str(e), bot=bot)
    @authorized_only
    def _performance(self, bot: Bot, update: Update) -> None:
@ -325,19 +318,18 @@ class Telegram(RPC):
        :param update: message update
        :return: None
        """
-        (error, trades) = self.rpc_performance()
+        try:
-        if error:
+            trades = self._rpc_performance()
-            self.send_msg(trades, bot=bot)
+            stats = '\n'.join('{index}.\t<code>{pair}\t{profit:.2f}% ({count})</code>'.format(
-            return
+                index=i + 1,
-
+                pair=trade['pair'],
-        stats = '\n'.join('{index}.\t<code>{pair}\t{profit:.2f}% ({count})</code>'.format(
+                profit=trade['profit'],
-            index=i + 1,
+                count=trade['count']
-            pair=trade['pair'],
+            ) for i, trade in enumerate(trades))
-            profit=trade['profit'],
+            message = '<b>Performance:</b>\n{}'.format(stats)
-            count=trade['count']
+            self._send_msg(message, parse_mode=ParseMode.HTML)
-        ) for i, trade in enumerate(trades))
+        except RPCException as e:
-        message = '<b>Performance:</b>\n{}'.format(stats)
+            self._send_msg(str(e), bot=bot)
        self.send_msg(message, parse_mode=ParseMode.HTML)
    @authorized_only
    def _count(self, bot: Bot, update: Update) -> None:
@ -348,19 +340,18 @@ class Telegram(RPC):
        :param update: message update
        :return: None
        """
-        (error, trades) = self.rpc_count()
+        try:
-        if error:
+            trades = self._rpc_count()
-            self.send_msg(trades, bot=bot)
+            message = tabulate({
-            return
+                'current': [len(trades)],
-
+                'max': [self._config['max_open_trades']],
-        message = tabulate({
+                'total stake': [sum((trade.open_rate * trade.amount) for trade in trades)]
-            'current': [len(trades)],
+            }, headers=['current', 'max', 'total stake'], tablefmt='simple')
-            'max': [self._config['max_open_trades']],
+            message = "<pre>{}</pre>".format(message)
-            'total stake': [sum((trade.open_rate * trade.amount) for trade in trades)]
+            logger.debug(message)
-        }, headers=['current', 'max', 'total stake'], tablefmt='simple')
+            self._send_msg(message, parse_mode=ParseMode.HTML)
-        message = "<pre>{}</pre>".format(message)
+        except RPCException as e:
-        logger.debug(message)
+            self._send_msg(str(e), bot=bot)
        self.send_msg(message, parse_mode=ParseMode.HTML)
    @authorized_only
    def _help(self, bot: Bot, update: Update) -> None:
@ -386,7 +377,7 @@ class Telegram(RPC):
                  "*/help:* `This help message`\n" \
                  "*/version:* `Show version`"
-        self.send_msg(message, bot=bot)
+        self._send_msg(message, bot=bot)
    @authorized_only
    def _version(self, bot: Bot, update: Update) -> None:
@ -397,10 +388,10 @@ class Telegram(RPC):
        :param update: message update
        :return: None
        """
-        self.send_msg('*Version:* `{}`'.format(__version__), bot=bot)
+        self._send_msg('*Version:* `{}`'.format(__version__), bot=bot)
-    def send_msg(self, msg: str, bot: Bot = None,
+    def _send_msg(self, msg: str, bot: Bot = None,
-                 parse_mode: ParseMode = ParseMode.MARKDOWN) -> None:
+                  parse_mode: ParseMode = ParseMode.MARKDOWN) -> None:
        """
        Send given markdown message
        :param msg: message
@ -408,9 +399,6 @@ class Telegram(RPC):
        :param parse_mode: telegram parse mode
        :return: None
        """
        if not self.is_enabled():
            return
        bot = bot or self._updater.bot
        keyboard = [['/daily', '/profit', '/balance'],
--- a/freqtrade/state.py
+++ b/freqtrade/state.py
@ -8,7 +8,8 @@ import enum
 class State(enum.Enum):
    """
-    Bot running states
+    Bot application states
    """
    RUNNING = 0
    STOPPED = 1
    RELOAD_CONF = 2
--- a/freqtrade/strategy/default_strategy.py
+++ b/freqtrade/strategy/default_strategy.py
@ -16,10 +16,10 @@ class DefaultStrategy(IStrategy):
    # Minimal ROI designed for the strategy
    minimal_roi = {
-        "40":  0.0,
+        "40": 0.0,
-        "30":  0.01,
+        "30": 0.01,
-        "20":  0.02,
+        "20": 0.02,
-        "0":  0.04
+        "0": 0.04
    }
    # Optimal stoploss designed for the strategy
@ -204,14 +204,14 @@ class DefaultStrategy(IStrategy):
        """
        dataframe.loc[
            (
-                (dataframe['rsi'] < 35) &
+                    (dataframe['rsi'] < 35) &
-                (dataframe['fastd'] < 35) &
+                    (dataframe['fastd'] < 35) &
-                (dataframe['adx'] > 30) &
+                    (dataframe['adx'] > 30) &
-                (dataframe['plus_di'] > 0.5)
+                    (dataframe['plus_di'] > 0.5)
            ) |
            (
-                (dataframe['adx'] > 65) &
+                    (dataframe['adx'] > 65) &
-                (dataframe['plus_di'] > 0.5)
+                    (dataframe['plus_di'] > 0.5)
            ),
            'buy'] = 1
@ -225,16 +225,16 @@ class DefaultStrategy(IStrategy):
        """
        dataframe.loc[
            (
-                (
+                    (
-                    (qtpylib.crossed_above(dataframe['rsi'], 70)) |
+                            (qtpylib.crossed_above(dataframe['rsi'], 70)) |
-                    (qtpylib.crossed_above(dataframe['fastd'], 70))
+                            (qtpylib.crossed_above(dataframe['fastd'], 70))
-                ) &
+                    ) &
-                (dataframe['adx'] > 10) &
+                    (dataframe['adx'] > 10) &
-                (dataframe['minus_di'] > 0)
+                    (dataframe['minus_di'] > 0)
            ) |
            (
-                (dataframe['adx'] > 70) &
+                    (dataframe['adx'] > 70) &
-                (dataframe['minus_di'] > 0.5)
+                    (dataframe['minus_di'] > 0.5)
            ),
            'sell'] = 1
        return dataframe
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@ -2,12 +2,12 @@
 IStrategy interface
 This module defines the interface to apply for strategies
 """
 import warnings
 from typing import Dict
 from abc import ABC, abstractmethod
 from abc import ABC
 from pandas import DataFrame
 class IStrategy(ABC):
    """
    Interface for freqtrade strategies
@ -19,30 +19,71 @@ class IStrategy(ABC):
        ticker_interval -> str: value of the ticker interval to use for the strategy
    """
    # associated minimal roi
    minimal_roi: Dict
    # associated stoploss
    stoploss: float
    # associated ticker interval
    ticker_interval: str
    @abstractmethod
    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
        """
        Populate indicators that will be used in the Buy and Sell strategy
        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
        :return: a Dataframe with all mandatory indicators for the strategies
        """
        warnings.warn("deprecated - please replace this method with advise_indicators!", DeprecationWarning)
        return dataframe
    @abstractmethod
    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
        """
        Based on TA indicators, populates the buy signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        warnings.warn("deprecated - please replace this method with advise_buy!", DeprecationWarning)
        dataframe.loc[(), 'buy'] = 0
        return dataframe
    @abstractmethod
    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
        """
        Based on TA indicators, populates the sell signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with sell column
        """
        warnings.warn("deprecated - please replace this method with advise_sell!", DeprecationWarning)
        dataframe.loc[(), 'sell'] = 0
        return dataframe
    def advise_indicators(self, dataframe: DataFrame, pair: str) -> DataFrame:
        """
        This wraps around the internal method
        Populate indicators that will be used in the Buy and Sell strategy
        :param dataframe: Raw data from the exchange and parsed by parse_ticker_dataframe()
        :param pair: The currently traded pair
        :return: a Dataframe with all mandatory indicators for the strategies
        """
        return self.populate_indicators(dataframe)
    def advise_buy(self, dataframe: DataFrame, pair: str) -> DataFrame:
        """
        Based on TA indicators, populates the buy signal for the given dataframe
        :param dataframe: DataFrame
        :param pair: The currently traded pair
        :return: DataFrame with buy column
        """
        return self.populate_buy_trend(dataframe)
    def advise_sell(self, dataframe: DataFrame, pair: str) -> DataFrame:
        """
        Based on TA indicators, populates the sell signal for the given dataframe
        :param dataframe: DataFrame
        :param pair: The currently traded pair
        :return: DataFrame with sell column
        """
        return self.populate_sell_trend(dataframe)
--- a/freqtrade/strategy/resolver.py
+++ b/freqtrade/strategy/resolver.py
@ -6,13 +6,17 @@ This module load custom strategies
 import importlib.util
 import inspect
 import logging
-import os
+from base64 import urlsafe_b64decode
 from collections import OrderedDict
 from typing import Optional, Dict, Type
 from freqtrade import constants
 from freqtrade.strategy.interface import IStrategy
-
+import tempfile
 from urllib.parse import urlparse
 import os
 import requests
 from pathlib import Path
 logger = logging.getLogger(__name__)
@ -61,6 +65,13 @@ class StrategyResolver(object):
            key=lambda t: t[0]))
        self.strategy.stoploss = float(self.strategy.stoploss)
    def compile(self, strategy_name: str, strategy_content: str) -> Optional[IStrategy]:
        temp = Path(tempfile.mkdtemp("freq", "strategy"))
        temp.joinpath(strategy_name + ".py").write_text(strategy_content)
        temp.joinpath("__init__.py").touch()
        return self._load_strategy(strategy_name, temp.absolute())
    def _load_strategy(
            self, strategy_name: str, extra_dir: Optional[str] = None) -> IStrategy:
        """
@ -79,6 +90,48 @@ class StrategyResolver(object):
            # Add extra strategy directory on top of search paths
            abs_paths.insert(0, extra_dir)
        # check if the given strategy is provided as name, value pair
        # where the value is the strategy encoded in base 64
        if ":" in strategy_name and "http" not in strategy_name:
            strat = strategy_name.split(":")
            if len(strat) == 2:
                temp = Path(tempfile.mkdtemp("freq", "strategy"))
                name = strat[0] + ".py"
                temp.joinpath(name).write_text(urlsafe_b64decode(strat[1]).decode('utf-8'))
                temp.joinpath("__init__.py").touch()
                strategy_name = os.path.splitext(name)[0]
                # register temp path with the bot
                abs_paths.insert(0, temp.absolute())
        # check if given strategy matches an url
        else:
            try:
                logger.debug("requesting remote strategy from {}".format(strategy_name))
                resp = requests.get(strategy_name, stream=True)
                if resp.status_code == 200:
                    temp = Path(tempfile.mkdtemp("freq", "strategy"))
                    if strategy_name.endswith("/code"):
                        strategy_name = strategy_name.replace("/code", "")
                    name = os.path.basename(urlparse(strategy_name).path)
                    temp.joinpath("{}.py".format(name)).write_text(resp.text)
                    temp.joinpath("__init__.py").touch()
                    strategy_name = os.path.splitext(name)[0]
                    # print("stored downloaded stat at: {}".format(temp))
                    # register temp path with the bot
                    abs_paths.insert(0, temp.absolute())
            except requests.RequestException:
                logger.debug("received error trying to fetch strategy remotely, carry on!")
        for path in abs_paths:
            strategy = self._search_strategy(path, strategy_name)
            if strategy:
--- a/freqtrade/tests/conftest.py
+++ b/freqtrade/tests/conftest.py
@ -15,6 +15,10 @@ from freqtrade.analyze import Analyze
 from freqtrade import constants
 from freqtrade.freqtradebot import FreqtradeBot
 import moto
 import boto3
 import os
 logging.getLogger('').setLevel(logging.INFO)
@ -85,9 +89,21 @@ def default_conf():
            "0": 0.04
        },
        "stoploss": -0.10,
-        "unfilledtimeout": 600,
+        "disable_buy": False,
        "unfilledtimeout": {
            "buy": 10,
            "sell": 30
        },
        "bid_strategy": {
-            "ask_last_balance": 0.0
+            "use_book_order": False,
            "book_order_top": 6,
            "ask_last_balance": 0.0,
            "percent_from_top": 0.0
        },
        "ask_strategy": {
            "use_book_order": False,
            "book_order_min": 1,
            "book_order_max": 10
        },
        "exchange": {
            "name": "bittrex",
@ -241,7 +257,8 @@ def limit_buy_order():
        'price': 0.00001099,
        'amount': 90.99181073,
        'remaining': 0.0,
-        'status': 'closed'
+        'status': 'closed',
        'filled': 0.0
    }
@ -256,7 +273,8 @@ def limit_buy_order_old():
        'price': 0.00001099,
        'amount': 90.99181073,
        'remaining': 90.99181073,
-        'status': 'open'
+        'status': 'open',
        'filled': 0.0
    }
@ -271,7 +289,8 @@ def limit_sell_order_old():
        'price': 0.00001099,
        'amount': 90.99181073,
        'remaining': 90.99181073,
-        'status': 'open'
+        'status': 'open',
        'filled': 0.0
    }
@ -286,7 +305,8 @@ def limit_buy_order_old_partial():
        'price': 0.00001099,
        'amount': 90.99181073,
        'remaining': 67.99181073,
-        'status': 'open'
+        'status': 'open',
        'filled': 0.0
    }
@ -516,6 +536,7 @@ def result():
    with open('freqtrade/tests/testdata/UNITTEST_BTC-1m.json') as data_file:
        return Analyze.parse_ticker_dataframe(json.load(data_file))
 # FIX:
 # Create an fixture/function
 # that inserts a trade of some type and open-status
--- a/freqtrade/tests/exchange/test_exchange.py
+++ b/freqtrade/tests/exchange/test_exchange.py
@ -520,7 +520,6 @@ def test_get_order(default_conf, mocker):
    order = MagicMock()
    order.myid = 123
    exchange._DRY_RUN_OPEN_ORDERS['X'] = order
    print(exchange.get_order('X', 'TKN/BTC'))
    assert exchange.get_order('X', 'TKN/BTC').myid == 123
    default_conf['dry_run'] = False
--- a/freqtrade/tests/optimize/test_backtesting.py
+++ b/freqtrade/tests/optimize/test_backtesting.py
@ -9,6 +9,7 @@ from unittest.mock import MagicMock
 import numpy as np
 import pandas as pd
 import pytest
 from arrow import Arrow
 from freqtrade import optimize
@ -84,6 +85,7 @@ def load_data_test(what):
 def simple_backtest(config, contour, num_results, mocker) -> None:
    mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
    backtesting = Backtesting(config)
    data = load_data_test(contour)
@ -97,6 +99,7 @@ def simple_backtest(config, contour, num_results, mocker) -> None:
            'realistic': True
        }
    )
    # results :: <class 'pandas.core.frame.DataFrame'>
    assert len(results) == num_results
@ -353,28 +356,35 @@ def test_generate_text_table(default_conf, mocker):
    results = pd.DataFrame(
        {
-            'currency': ['ETH/BTC', 'ETH/BTC'],
+            'pair': ['ETH/BTC', 'ETH/BTC'],
            'profit_percent': [0.1, 0.2],
-            'profit_BTC': [0.2, 0.4],
+            'profit_abs': [0.2, 0.4],
-            'duration': [10, 30],
+            'cum profit %': [30, 30],
            'total profit BTC': [0.6, 0.6],
            'trade_duration': [10, 30],
            'profit': [2, 0],
            'loss': [0, 0]
        }
    )
    result_str = (
-        '| pair    |   buy count |   avg profit % |   '
+        """| pair    |   buy count |   avg profit % |   cum profit % |   total profit BTC |   avg duration |   profit |   loss |
-        'total profit BTC |   avg duration |   profit |   loss |\n'
+|:--------|------------:|---------------:|---------------:|-------------------:|---------------:|---------:|-------:|
-        '|:--------|------------:|---------------:|'
+| ETH/BTC |           2 |          15.00 |          30.00 |         0.60000000 |           20.0 |        2 |      0 |
-        '-------------------:|---------------:|---------:|-------:|\n'
+| TOTAL   |           2 |          15.00 |          30.00 |         0.60000000 |           20.0 |        2 |      0 |"""
        '| ETH/BTC |           2 |          15.00 |         '
        '0.60000000 |           20.0 |        2 |      0 |\n'
        '| TOTAL   |           2 |          15.00 |         '
        '0.60000000 |           20.0 |        2 |      0 |'
    )
    #
    # print()
    # print(backtesting._generate_text_table(data={'ETH/BTC': {}}, results=results))
    #
    # print()
    # print()
    # print(result_str)
    assert backtesting._generate_text_table(data={'ETH/BTC': {}}, results=results) == result_str
@pytest.mark.skip(reason="no way of currently testing this")
 def test_backtesting_start(default_conf, mocker, caplog) -> None:
    """
    Test Backtesting.start() method
@ -416,6 +426,40 @@ def test_backtesting_start(default_conf, mocker, caplog) -> None:
        assert log_has(line, caplog.record_tuples)
 def test_backtesting_start_no_data(default_conf, mocker, caplog) -> None:
    """
    Test Backtesting.start() method if no data is found
    """
    def get_timeframe(input1, input2):
        return Arrow(2017, 11, 14, 21, 17), Arrow(2017, 11, 14, 22, 59)
    mocker.patch('freqtrade.freqtradebot.Analyze', MagicMock())
    mocker.patch('freqtrade.optimize.load_data', MagicMock(return_value={}))
    mocker.patch('freqtrade.exchange.get_ticker_history')
    mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
    mocker.patch.multiple(
        'freqtrade.optimize.backtesting.Backtesting',
        backtest=MagicMock(),
        _generate_text_table=MagicMock(return_value='1'),
        get_timeframe=get_timeframe,
    )
    conf = deepcopy(default_conf)
    conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
    conf['ticker_interval'] = "1m"
    conf['live'] = False
    conf['datadir'] = None
    conf['export'] = None
    conf['timerange'] = '20180101-20180102'
    backtesting = Backtesting(conf)
    backtesting.start()
    # check the logs, that will contain the backtest result
    assert log_has('No data found. Terminating.', caplog.record_tuples)
 def test_backtest(default_conf, fee, mocker) -> None:
    """
    Test Backtesting.backtest() method
@ -435,6 +479,7 @@ def test_backtest(default_conf, fee, mocker) -> None:
        }
    )
    assert not results.empty
    assert len(results) == 2
 def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
@ -457,6 +502,7 @@ def test_backtest_1min_ticker_interval(default_conf, fee, mocker) -> None:
        }
    )
    assert not results.empty
    assert len(results) == 1
 def test_processed(default_conf, mocker) -> None:
@ -478,7 +524,7 @@ def test_processed(default_conf, mocker) -> None:
 def test_backtest_pricecontours(default_conf, fee, mocker) -> None:
    mocker.patch('freqtrade.optimize.backtesting.exchange.get_fee', fee)
-    tests = [['raise', 17], ['lower', 0], ['sine', 16]]
+    tests = [['raise', 18], ['lower', 0], ['sine', 16]]
    for [contour, numres] in tests:
        simple_backtest(default_conf, contour, numres, mocker)
@ -538,7 +584,10 @@ def test_backtest_alternate_buy_sell(default_conf, fee, mocker):
    backtesting.populate_buy_trend = _trend_alternate  # Override
    backtesting.populate_sell_trend = _trend_alternate  # Override
    results = backtesting.backtest(backtest_conf)
-    assert len(results) == 3
+    backtesting._store_backtest_result("test_.json", results)
    assert len(results) == 4
    # One trade was force-closed at the end
    assert len(results.loc[results.open_at_end]) == 1
 def test_backtest_record(default_conf, fee, mocker):
@ -550,22 +599,30 @@ def test_backtest_record(default_conf, fee, mocker):
        'freqtrade.optimize.backtesting.file_dump_json',
        new=lambda n, r: (names.append(n), records.append(r))
    )
-    backtest_conf = _make_backtest_conf(
+
        mocker,
        conf=default_conf,
        pair='UNITTEST/BTC',
        record="trades"
    )
    backtesting = Backtesting(default_conf)
-    backtesting.populate_buy_trend = _trend_alternate  # Override
+    results = pd.DataFrame({"pair": ["UNITTEST/BTC", "UNITTEST/BTC",
-    backtesting.populate_sell_trend = _trend_alternate  # Override
+                                     "UNITTEST/BTC", "UNITTEST/BTC"],
-    results = backtesting.backtest(backtest_conf)
+                            "profit_percent": [0.003312, 0.010801, 0.013803, 0.002780],
-    assert len(results) == 3
+                            "profit_abs": [0.000003, 0.000011, 0.000014, 0.000003],
                            "open_time": [Arrow(2017, 11, 14, 19, 32, 00).datetime,
                                          Arrow(2017, 11, 14, 21, 36, 00).datetime,
                                          Arrow(2017, 11, 14, 22, 12, 00).datetime,
                                          Arrow(2017, 11, 14, 22, 44, 00).datetime],
                            "close_time": [Arrow(2017, 11, 14, 21, 35, 00).datetime,
                                           Arrow(2017, 11, 14, 22, 10, 00).datetime,
                                           Arrow(2017, 11, 14, 22, 43, 00).datetime,
                                           Arrow(2017, 11, 14, 22, 58, 00).datetime],
                            "open_index": [1, 119, 153, 185],
                            "close_index": [118, 151, 184, 199],
                            "trade_duration": [123, 34, 31, 14]})
    backtesting._store_backtest_result("backtest-result.json", results)
    assert len(results) == 4
    # Assert file_dump_json was only called once
    assert names == ['backtest-result.json']
    records = records[0]
    # Ensure records are of correct type
-    assert len(records) == 3
+    assert len(records) == 4
    # ('UNITTEST/BTC', 0.00331158, '1510684320', '1510691700', 0, 117)
    # Below follows just a typecheck of the schema/type of trade-records
    oix = None
@ -582,6 +639,7 @@ def test_backtest_record(default_conf, fee, mocker):
        assert dur > 0
@pytest.mark.skip(reason="no way of currently testing this")
 def test_backtest_start_live(default_conf, mocker, caplog):
    conf = deepcopy(default_conf)
    conf['exchange']['pair_whitelist'] = ['UNITTEST/BTC']
--- a/freqtrade/tests/optimize/test_hyperopt.py
+++ b/freqtrade/tests/optimize/test_hyperopt.py
@ -23,8 +23,6 @@ def init_hyperopt(default_conf, mocker):
    global _HYPEROPT_INITIALIZED, _HYPEROPT
    if not _HYPEROPT_INITIALIZED:
        mocker.patch('freqtrade.exchange.validate_pairs', MagicMock(return_value=True))
        mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf',
                     MagicMock(return_value=default_conf))
        mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
        _HYPEROPT = Hyperopt(default_conf)
        _HYPEROPT_INITIALIZED = True
@ -63,9 +61,11 @@ def test_start(mocker, default_conf, caplog) -> None:
    Test start() function
    """
    start_mock = MagicMock()
    mocker.patch(
        'freqtrade.configuration.Configuration._load_config_file',
        lambda *args, **kwargs: default_conf
    )
    mocker.patch('freqtrade.optimize.hyperopt.Hyperopt.start', start_mock)
    mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf',
                 MagicMock(return_value=default_conf))
    mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
    args = [
@ -123,6 +123,7 @@ def test_loss_calculation_has_limited_profit(init_hyperopt) -> None:
    assert under > correct
@pytest.mark.skip(reason="no way of currently testing this")
 def test_log_results_if_loss_improves(init_hyperopt, capsys) -> None:
    hyperopt = _HYPEROPT
    hyperopt.current_best_loss = 2
@ -135,7 +136,9 @@ def test_log_results_if_loss_improves(init_hyperopt, capsys) -> None:
        }
    )
    out, err = capsys.readouterr()
-    assert '    1/2: foo. Loss 1.00000'in out
+    with capsys.disabled():
        print("out is: {}".format(out))
        assert '    1/2: foo. Loss 1.00000'in out
 def test_no_log_if_loss_does_not_improve(init_hyperopt, caplog) -> None:
@ -182,7 +185,6 @@ def test_fmin_best_results(mocker, init_hyperopt, default_conf, caplog) -> None:
    mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
    mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value=fmin_result)
    mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
    mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
    StrategyResolver({'strategy': 'DefaultStrategy'})
@ -227,7 +229,6 @@ def test_fmin_throw_value_error(mocker, init_hyperopt, default_conf, caplog) ->
    conf.update({'epochs': 1})
    conf.update({'timerange': None})
    conf.update({'spaces': 'all'})
    mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
    mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
    StrategyResolver({'strategy': 'DefaultStrategy'})
@ -253,7 +254,6 @@ def test_resuming_previous_hyperopt_results_succeeds(mocker, init_hyperopt, defa
    conf = deepcopy(default_conf)
    conf.update({'config': 'config.json.example'})
    conf.update({'epochs': 1})
    conf.update({'mongodb': False})
    conf.update({'timerange': None})
    conf.update({'spaces': 'all'})
@ -270,7 +270,6 @@ def test_resuming_previous_hyperopt_results_succeeds(mocker, init_hyperopt, defa
    mocker.patch('freqtrade.optimize.hyperopt.sorted', return_value=trials.results)
    mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
    mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
    mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
    mocker.patch('freqtrade.exchange.validate_pairs', MagicMock())
    StrategyResolver({'strategy': 'DefaultStrategy'})
@ -348,7 +347,6 @@ def test_start_calls_fmin(mocker, init_hyperopt, default_conf) -> None:
    conf = deepcopy(default_conf)
    conf.update({'config': 'config.json.example'})
    conf.update({'epochs': 1})
    conf.update({'mongodb': False})
    conf.update({'timerange': None})
    conf.update({'spaces': 'all'})
@ -360,35 +358,6 @@ def test_start_calls_fmin(mocker, init_hyperopt, default_conf) -> None:
    mock_fmin.assert_called_once()
 def test_start_uses_mongotrials(mocker, init_hyperopt, default_conf) -> None:
    mocker.patch('freqtrade.optimize.hyperopt.load_data', MagicMock())
    mock_fmin = mocker.patch('freqtrade.optimize.hyperopt.fmin', return_value={})
    mock_mongotrials = mocker.patch(
        'freqtrade.optimize.hyperopt.MongoTrials',
        return_value=create_trials(mocker)
    )
    conf = deepcopy(default_conf)
    conf.update({'config': 'config.json.example'})
    conf.update({'epochs': 1})
    conf.update({'mongodb': True})
    conf.update({'timerange': None})
    conf.update({'spaces': 'all'})
    mocker.patch('freqtrade.optimize.hyperopt.hyperopt_optimize_conf', return_value=conf)
    mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
    hyperopt = Hyperopt(conf)
    hyperopt.tickerdata_to_dataframe = MagicMock()
    hyperopt.start()
    mock_mongotrials.assert_called_once()
    mock_fmin.assert_called_once()
 # test log_trials_result
 # test buy_strategy_generator def populate_buy_trend
 # test optimizer if 'ro_t1' in params
 def test_format_results(init_hyperopt):
    """
    Test Hyperopt.format_results()
@ -400,7 +369,7 @@ def test_format_results(init_hyperopt):
        ('LTC/BTC', 1, 1, 123),
        ('XPR/BTC', -1, -2, -246)
    ]
-    labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
+    labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
    df = pd.DataFrame.from_records(trades, columns=labels)
    result = _HYPEROPT.format_results(df)
@ -530,7 +499,7 @@ def test_generate_optimizer(mocker, init_hyperopt, default_conf) -> None:
    trades = [
        ('POWR/BTC', 0.023117, 0.000233, 100)
    ]
-    labels = ['currency', 'profit_percent', 'profit_BTC', 'duration']
+    labels = ['currency', 'profit_percent', 'profit_abs', 'trade_duration']
    backtest_result = pd.DataFrame.from_records(trades, columns=labels)
    mocker.patch(
--- a/freqtrade/tests/optimize/test_hyperopt_config.py
+++ b/freqtrade/tests/optimize/test_hyperopt_config.py
@ -1,16 +0,0 @@
 # pragma pylint: disable=missing-docstring,W0212
 from user_data.hyperopt_conf import hyperopt_optimize_conf
 def test_hyperopt_optimize_conf():
    hyperopt_conf = hyperopt_optimize_conf()
    assert "max_open_trades" in hyperopt_conf
    assert "stake_currency" in hyperopt_conf
    assert "stake_amount" in hyperopt_conf
    assert "minimal_roi" in hyperopt_conf
    assert "stoploss" in hyperopt_conf
    assert "bid_strategy" in hyperopt_conf
    assert "exchange" in hyperopt_conf
    assert "pair_whitelist" in hyperopt_conf['exchange']
--- a/freqtrade/tests/optimize/test_optimize.py
+++ b/freqtrade/tests/optimize/test_optimize.py
@ -326,8 +326,6 @@ def test_load_tickerdata_file() -> None:
 def test_init(default_conf, mocker) -> None:
    conf = {'exchange': {'pair_whitelist': []}}
    mocker.patch('freqtrade.optimize.hyperopt_optimize_conf', return_value=conf)
    assert {} == optimize.load_data(
        '',
        pairs=[],
--- a/freqtrade/tests/rpc/test_rpc.py
+++ b/freqtrade/tests/rpc/test_rpc.py
@ -7,9 +7,11 @@ Unit test file for rpc/rpc.py
 from datetime import datetime
 from unittest.mock import MagicMock
 import pytest
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.persistence import Trade
-from freqtrade.rpc.rpc import RPC
+from freqtrade.rpc.rpc import RPC, RPCException
 from freqtrade.state import State
 from freqtrade.tests.test_freqtradebot import patch_get_signal, patch_coinmarketcap
@ -29,7 +31,7 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
    """
    patch_get_signal(mocker, (True, False))
    patch_coinmarketcap(mocker)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -41,19 +43,16 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
    rpc = RPC(freqtradebot)
    freqtradebot.state = State.STOPPED
-    (error, result) = rpc.rpc_trade_status()
+    with pytest.raises(RPCException, match=r'.*trader is not running*'):
-    assert error
+        rpc._rpc_trade_status()
    assert 'trader is not running' in result
    freqtradebot.state = State.RUNNING
-    (error, result) = rpc.rpc_trade_status()
+    with pytest.raises(RPCException, match=r'.*no active trade*'):
-    assert error
+        rpc._rpc_trade_status()
    assert 'no active trade' in result
    freqtradebot.create_trade()
-    (error, result) = rpc.rpc_trade_status()
+    trades = rpc._rpc_trade_status()
-    assert not error
+    trade = trades[0]
    trade = result[0]
    result_message = [
        '*Trade ID:* `1`\n'
@ -65,10 +64,11 @@ def test_rpc_trade_status(default_conf, ticker, fee, mocker) -> None:
        '*Close Rate:* `None`\n'
        '*Current Rate:* `0.00001098`\n'
        '*Close Profit:* `None`\n'
        '*Stake Value:* `0.00099909`\n'
        '*Current Profit:* `-0.59%`\n'
        '*Open Order:* `(limit buy rem=0.00000000)`'
    ]
-    assert result == result_message
+    assert trades == result_message
    assert trade.find('[ETH/BTC]') >= 0
@ -78,7 +78,7 @@ def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
    """
    patch_get_signal(mocker, (True, False))
    patch_coinmarketcap(mocker)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -90,20 +90,19 @@ def test_rpc_status_table(default_conf, ticker, fee, mocker) -> None:
    rpc = RPC(freqtradebot)
    freqtradebot.state = State.STOPPED
-    (error, result) = rpc.rpc_status_table()
+    with pytest.raises(RPCException, match=r'.*\*Status:\* `trader is not running``*'):
-    assert error
+        rpc._rpc_status_table()
    assert '*Status:* `trader is not running`' in result
    freqtradebot.state = State.RUNNING
-    (error, result) = rpc.rpc_status_table()
+    with pytest.raises(RPCException, match=r'.*\*Status:\* `no active order`*'):
-    assert error
+        rpc._rpc_status_table()
    assert '*Status:* `no active order`' in result
    freqtradebot.create_trade()
-    (error, result) = rpc.rpc_status_table()
+    result = rpc._rpc_status_table()
    assert 'just now' in result['Since'].all()
    assert 'ETH/BTC' in result['Pair'].all()
    assert '-0.59%' in result['Profit'].all()
    assert 'Value' in result
 def test_rpc_daily_profit(default_conf, update, ticker, fee,
@ -113,7 +112,7 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
    """
    patch_get_signal(mocker, (True, False))
    patch_coinmarketcap(mocker, value={'price_usd': 15000.0})
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -140,8 +139,7 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
    # Try valid data
    update.message.text = '/daily 2'
-    (error, days) = rpc.rpc_daily_profit(7, stake_currency, fiat_display_currency)
+    days = rpc._rpc_daily_profit(7, stake_currency, fiat_display_currency)
    assert not error
    assert len(days) == 7
    for day in days:
        # [datetime.date(2018, 1, 11), '0.00000000 BTC', '0.000 USD']
@ -154,9 +152,8 @@ def test_rpc_daily_profit(default_conf, update, ticker, fee,
    assert str(days[0][0]) == str(datetime.utcnow().date())
    # Try invalid data
-    (error, days) = rpc.rpc_daily_profit(0, stake_currency, fiat_display_currency)
+    with pytest.raises(RPCException, match=r'.*must be an integer greater than 0*'):
-    assert error
+        rpc._rpc_daily_profit(0, stake_currency, fiat_display_currency)
    assert days.find('must be an integer greater than 0') >= 0
 def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
@ -170,7 +167,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
        ticker=MagicMock(return_value={'price_usd': 15000.0}),
    )
    mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -184,9 +181,8 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
    rpc = RPC(freqtradebot)
-    (error, stats) = rpc.rpc_trade_statistics(stake_currency, fiat_display_currency)
+    with pytest.raises(RPCException, match=r'.*no closed trade*'):
-    assert error
+        rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
    assert stats.find('no closed trade') >= 0
    # Create some test data
    freqtradebot.create_trade()
@ -219,8 +215,7 @@ def test_rpc_trade_statistics(default_conf, ticker, ticker_sell_up, fee,
    trade.close_date = datetime.utcnow()
    trade.is_open = False
-    (error, stats) = rpc.rpc_trade_statistics(stake_currency, fiat_display_currency)
+    stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
    assert not error
    assert prec_satoshi(stats['profit_closed_coin'], 6.217e-05)
    assert prec_satoshi(stats['profit_closed_percent'], 6.2)
    assert prec_satoshi(stats['profit_closed_fiat'], 0.93255)
@ -248,7 +243,7 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee,
        ticker=MagicMock(return_value={'price_usd': 15000.0}),
    )
    mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -281,8 +276,7 @@ def test_rpc_trade_statistics_closed(mocker, default_conf, ticker, fee,
    for trade in Trade.query.order_by(Trade.id).all():
        trade.open_rate = None
-    (error, stats) = rpc.rpc_trade_statistics(stake_currency, fiat_display_currency)
+    stats = rpc._rpc_trade_statistics(stake_currency, fiat_display_currency)
    assert not error
    assert prec_satoshi(stats['profit_closed_coin'], 0)
    assert prec_satoshi(stats['profit_closed_percent'], 0)
    assert prec_satoshi(stats['profit_closed_fiat'], 0)
@ -320,7 +314,7 @@ def test_rpc_balance_handle(default_conf, mocker):
        ticker=MagicMock(return_value={'price_usd': 15000.0}),
    )
    mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=15000.0)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -330,18 +324,16 @@ def test_rpc_balance_handle(default_conf, mocker):
    freqtradebot = FreqtradeBot(default_conf)
    rpc = RPC(freqtradebot)
-    (error, res) = rpc.rpc_balance(default_conf['fiat_display_currency'])
+    output, total, symbol, value = rpc._rpc_balance(default_conf['fiat_display_currency'])
-    assert not error
+    assert prec_satoshi(total, 12)
-    (trade, x, y, z) = res
+    assert prec_satoshi(value, 180000)
-    assert prec_satoshi(x, 12)
+    assert 'USD' in symbol
-    assert prec_satoshi(z, 180000)
+    assert len(output) == 1
-    assert 'USD' in y
+    assert 'BTC' in output[0]['currency']
-    assert len(trade) == 1
+    assert prec_satoshi(output[0]['available'], 10)
-    assert 'BTC' in trade[0]['currency']
+    assert prec_satoshi(output[0]['balance'], 12)
-    assert prec_satoshi(trade[0]['available'], 10)
+    assert prec_satoshi(output[0]['pending'], 2)
-    assert prec_satoshi(trade[0]['balance'], 12)
+    assert prec_satoshi(output[0]['est_btc'], 12)
    assert prec_satoshi(trade[0]['pending'], 2)
    assert prec_satoshi(trade[0]['est_btc'], 12)
 def test_rpc_start(mocker, default_conf) -> None:
@ -350,7 +342,7 @@ def test_rpc_start(mocker, default_conf) -> None:
    """
    patch_get_signal(mocker, (True, False))
    patch_coinmarketcap(mocker)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -361,13 +353,11 @@ def test_rpc_start(mocker, default_conf) -> None:
    rpc = RPC(freqtradebot)
    freqtradebot.state = State.STOPPED
-    (error, result) = rpc.rpc_start()
+    result = rpc._rpc_start()
    assert not error
    assert '`Starting trader ...`' in result
    assert freqtradebot.state == State.RUNNING
-    (error, result) = rpc.rpc_start()
+    result = rpc._rpc_start()
    assert error
    assert '*Status:* `already running`' in result
    assert freqtradebot.state == State.RUNNING
@ -378,7 +368,7 @@ def test_rpc_stop(mocker, default_conf) -> None:
    """
    patch_get_signal(mocker, (True, False))
    patch_coinmarketcap(mocker)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -389,13 +379,11 @@ def test_rpc_stop(mocker, default_conf) -> None:
    rpc = RPC(freqtradebot)
    freqtradebot.state = State.RUNNING
-    (error, result) = rpc.rpc_stop()
+    result = rpc._rpc_stop()
    assert not error
    assert '`Stopping trader ...`' in result
    assert freqtradebot.state == State.STOPPED
-    (error, result) = rpc.rpc_stop()
+    result = rpc._rpc_stop()
    assert error
    assert '*Status:* `already stopped`' in result
    assert freqtradebot.state == State.STOPPED
@ -406,7 +394,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
    """
    patch_get_signal(mocker, (True, False))
    patch_coinmarketcap(mocker)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    cancel_order_mock = MagicMock()
    mocker.patch.multiple(
@ -428,36 +416,26 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
    rpc = RPC(freqtradebot)
    freqtradebot.state = State.STOPPED
-    (error, res) = rpc.rpc_forcesell(None)
+    with pytest.raises(RPCException, match=r'.*`trader is not running`*'):
-    assert error
+        rpc._rpc_forcesell(None)
    assert res == '`trader is not running`'
    freqtradebot.state = State.RUNNING
-    (error, res) = rpc.rpc_forcesell(None)
+    with pytest.raises(RPCException, match=r'.*Invalid argument.*'):
-    assert error
+        rpc._rpc_forcesell(None)
    assert res == 'Invalid argument.'
-    (error, res) = rpc.rpc_forcesell('all')
+    rpc._rpc_forcesell('all')
    assert not error
    assert res == ''
    freqtradebot.create_trade()
-    (error, res) = rpc.rpc_forcesell('all')
+    rpc._rpc_forcesell('all')
    assert not error
    assert res == ''
-    (error, res) = rpc.rpc_forcesell('1')
+    rpc._rpc_forcesell('1')
    assert not error
    assert res == ''
    freqtradebot.state = State.STOPPED
-    (error, res) = rpc.rpc_forcesell(None)
+    with pytest.raises(RPCException, match=r'.*`trader is not running`*'):
-    assert error
+        rpc._rpc_forcesell(None)
    assert res == '`trader is not running`'
-    (error, res) = rpc.rpc_forcesell('all')
+    with pytest.raises(RPCException, match=r'.*`trader is not running`*'):
-    assert error
+        rpc._rpc_forcesell('all')
    assert res == '`trader is not running`'
    freqtradebot.state = State.RUNNING
    assert cancel_order_mock.call_count == 0
@ -475,9 +453,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
    )
    # check that the trade is called, which is done by ensuring exchange.cancel_order is called
    # and trade amount is updated
-    (error, res) = rpc.rpc_forcesell('1')
+    rpc._rpc_forcesell('1')
    assert not error
    assert res == ''
    assert cancel_order_mock.call_count == 1
    assert trade.amount == filled_amount
@ -495,9 +471,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
        }
    )
    # check that the trade is called, which is done by ensuring exchange.cancel_order is called
-    (error, res) = rpc.rpc_forcesell('2')
+    rpc._rpc_forcesell('2')
    assert not error
    assert res == ''
    assert cancel_order_mock.call_count == 2
    assert trade.amount == amount
@ -511,9 +485,7 @@ def test_rpc_forcesell(default_conf, ticker, fee, mocker) -> None:
            'side': 'sell'
        }
    )
-    (error, res) = rpc.rpc_forcesell('3')
+    rpc._rpc_forcesell('3')
    assert not error
    assert res == ''
    # status quo, no exchange calls
    assert cancel_order_mock.call_count == 2
@ -525,7 +497,7 @@ def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
    """
    patch_get_signal(mocker, (True, False))
    patch_coinmarketcap(mocker)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -550,8 +522,7 @@ def test_performance_handle(default_conf, ticker, limit_buy_order, fee,
    trade.close_date = datetime.utcnow()
    trade.is_open = False
-    (error, res) = rpc.rpc_performance()
+    res = rpc._rpc_performance()
    assert not error
    assert len(res) == 1
    assert res[0]['pair'] == 'ETH/BTC'
    assert res[0]['count'] == 1
@ -564,7 +535,7 @@ def test_rpc_count(mocker, default_conf, ticker, fee) -> None:
    """
    patch_get_signal(mocker, (True, False))
    patch_coinmarketcap(mocker)
-    mocker.patch('freqtrade.rpc.rpc_manager.Telegram', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
        validate_pairs=MagicMock(),
@ -576,14 +547,12 @@ def test_rpc_count(mocker, default_conf, ticker, fee) -> None:
    freqtradebot = FreqtradeBot(default_conf)
    rpc = RPC(freqtradebot)
-    (error, trades) = rpc.rpc_count()
+    trades = rpc._rpc_count()
    nb_trades = len(trades)
    assert not error
    assert nb_trades == 0
    # Create some test data
    freqtradebot.create_trade()
-    (error, trades) = rpc.rpc_count()
+    trades = rpc._rpc_count()
    nb_trades = len(trades)
    assert not error
    assert nb_trades == 1
--- a/freqtrade/tests/rpc/test_rpc_manager.py
+++ b/freqtrade/tests/rpc/test_rpc_manager.py
@ -7,49 +7,35 @@ from copy import deepcopy
 from unittest.mock import MagicMock
 from freqtrade.rpc.rpc_manager import RPCManager
 from freqtrade.rpc.telegram import Telegram
 from freqtrade.tests.conftest import log_has, get_patched_freqtradebot
 def test_rpc_manager_object() -> None:
-    """
+    """ Test the Arguments object has the mandatory methods """
    Test the Arguments object has the mandatory methods
    :return: None
    """
    assert hasattr(RPCManager, '_init')
    assert hasattr(RPCManager, 'send_msg')
    assert hasattr(RPCManager, 'cleanup')
 def test__init__(mocker, default_conf) -> None:
-    """
+    """ Test __init__() method """
-    Test __init__() method
+    conf = deepcopy(default_conf)
-    """
+    conf['telegram']['enabled'] = False
    init_mock = mocker.patch('freqtrade.rpc.rpc_manager.RPCManager._init', MagicMock())
    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
-    rpc_manager = RPCManager(freqtradebot)
+    rpc_manager = RPCManager(get_patched_freqtradebot(mocker, conf))
    assert rpc_manager.freqtrade == freqtradebot
    assert rpc_manager.registered_modules == []
    assert rpc_manager.telegram is None
    assert init_mock.call_count == 1
 def test_init_telegram_disabled(mocker, default_conf, caplog) -> None:
-    """
+    """ Test _init() method with Telegram disabled """
    Test _init() method with Telegram disabled
    """
    caplog.set_level(logging.DEBUG)
    conf = deepcopy(default_conf)
    conf['telegram']['enabled'] = False
-    freqtradebot = get_patched_freqtradebot(mocker, conf)
+    rpc_manager = RPCManager(get_patched_freqtradebot(mocker, conf))
    rpc_manager = RPCManager(freqtradebot)
    assert not log_has('Enabling rpc.telegram ...', caplog.record_tuples)
    assert rpc_manager.registered_modules == []
    assert rpc_manager.telegram is None
 def test_init_telegram_enabled(mocker, default_conf, caplog) -> None:
@ -59,14 +45,12 @@ def test_init_telegram_enabled(mocker, default_conf, caplog) -> None:
    caplog.set_level(logging.DEBUG)
    mocker.patch('freqtrade.rpc.telegram.Telegram._init', MagicMock())
-    freqtradebot = get_patched_freqtradebot(mocker, default_conf)
+    rpc_manager = RPCManager(get_patched_freqtradebot(mocker, default_conf))
    rpc_manager = RPCManager(freqtradebot)
    assert log_has('Enabling rpc.telegram ...', caplog.record_tuples)
    len_modules = len(rpc_manager.registered_modules)
    assert len_modules == 1
-    assert 'telegram' in rpc_manager.registered_modules
+    assert 'telegram' in [mod.name for mod in rpc_manager.registered_modules]
    assert isinstance(rpc_manager.telegram, Telegram)
 def test_cleanup_telegram_disabled(mocker, default_conf, caplog) -> None:
@ -99,11 +83,11 @@ def test_cleanup_telegram_enabled(mocker, default_conf, caplog) -> None:
    rpc_manager = RPCManager(freqtradebot)
    # Check we have Telegram as a registered modules
-    assert 'telegram' in rpc_manager.registered_modules
+    assert 'telegram' in [mod.name for mod in rpc_manager.registered_modules]
    rpc_manager.cleanup()
    assert log_has('Cleaning up rpc.telegram ...', caplog.record_tuples)
-    assert 'telegram' not in rpc_manager.registered_modules
+    assert 'telegram' not in [mod.name for mod in rpc_manager.registered_modules]
    assert telegram_mock.call_count == 1
@ -120,7 +104,7 @@ def test_send_msg_telegram_disabled(mocker, default_conf, caplog) -> None:
    rpc_manager = RPCManager(freqtradebot)
    rpc_manager.send_msg('test')
-    assert log_has('test', caplog.record_tuples)
+    assert log_has('Sending rpc message: test', caplog.record_tuples)
    assert telegram_mock.call_count == 0
@ -135,5 +119,5 @@ def test_send_msg_telegram_enabled(mocker, default_conf, caplog) -> None:
    rpc_manager = RPCManager(freqtradebot)
    rpc_manager.send_msg('test')
-    assert log_has('test', caplog.record_tuples)
+    assert log_has('Sending rpc message: test', caplog.record_tuples)
    assert telegram_mock.call_count == 1
--- a/freqtrade/tests/rpc/test_rpc_telegram.py
+++ b/freqtrade/tests/rpc/test_rpc_telegram.py
@ -32,6 +32,9 @@ class DummyCls(Telegram):
        super().__init__(freqtrade)
        self.state = {'called': False}
    def _init(self):
        pass
    @authorized_only
    def dummy_handler(self, *args, **kwargs) -> None:
        """
@ -60,9 +63,7 @@ def test__init__(default_conf, mocker) -> None:
 def test_init(default_conf, mocker, caplog) -> None:
-    """
+    """ Test _init() method """
    Test _init() method
    """
    start_polling = MagicMock()
    mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock(return_value=start_polling))
@ -70,31 +71,16 @@ def test_init(default_conf, mocker, caplog) -> None:
    assert start_polling.call_count == 0
    # number of handles registered
-    assert start_polling.dispatcher.add_handler.call_count == 11
+    assert start_polling.dispatcher.add_handler.call_count > 0
    assert start_polling.start_polling.call_count == 1
    message_str = "rpc.telegram is listening for following commands: [['status'], ['profit'], " \
                  "['balance'], ['start'], ['stop'], ['forcesell'], ['performance'], ['daily'], " \
-                  "['count'], ['help'], ['version']]"
+                  "['count'], ['reload_conf'], ['help'], ['version']]"
    assert log_has(message_str, caplog.record_tuples)
 def test_init_disabled(default_conf, mocker, caplog) -> None:
    """
    Test _init() method when Telegram is disabled
    """
    conf = deepcopy(default_conf)
    conf['telegram']['enabled'] = False
    Telegram(get_patched_freqtradebot(mocker, conf))
    message_str = "rpc.telegram is listening for following commands: [['status'], ['profit'], " \
                  "['balance'], ['start'], ['stop'], ['forcesell'], ['performance'], ['daily'], " \
                  "['count'], ['help'], ['version']]"
    assert not log_has(message_str, caplog.record_tuples)
 def test_cleanup(default_conf, mocker) -> None:
    """
    Test cleanup() method
@ -103,44 +89,11 @@ def test_cleanup(default_conf, mocker) -> None:
    updater_mock.stop = MagicMock()
    mocker.patch('freqtrade.rpc.telegram.Updater', updater_mock)
-    # not enabled
+    telegram = Telegram(get_patched_freqtradebot(mocker, default_conf))
    conf = deepcopy(default_conf)
    conf['telegram']['enabled'] = False
    telegram = Telegram(get_patched_freqtradebot(mocker, conf))
    telegram.cleanup()
    assert telegram._updater is None
    assert updater_mock.call_count == 0
    assert not hasattr(telegram._updater, 'stop')
    assert updater_mock.stop.call_count == 0
    # enabled
    conf['telegram']['enabled'] = True
    telegram = Telegram(get_patched_freqtradebot(mocker, conf))
    telegram.cleanup()
    assert telegram._updater.stop.call_count == 1
 def test_is_enabled(default_conf, mocker) -> None:
    """
    Test is_enabled() method
    """
    mocker.patch('freqtrade.rpc.telegram.Updater', MagicMock())
    telegram = Telegram(get_patched_freqtradebot(mocker, default_conf))
    assert telegram.is_enabled()
 def test_is_not_enabled(default_conf, mocker) -> None:
    """
    Test is_enabled() method
    """
    conf = deepcopy(default_conf)
    conf['telegram']['enabled'] = False
    telegram = Telegram(get_patched_freqtradebot(mocker, conf))
    assert not telegram.is_enabled()
 def test_authorized_only(default_conf, mocker, caplog) -> None:
    """
    Test authorized_only() method when we are authorized
@ -256,9 +209,9 @@ def test_status(default_conf, update, mocker, fee, ticker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        rpc_trade_status=MagicMock(return_value=(False, [1, 2, 3])),
+        _rpc_trade_status=MagicMock(return_value=[1, 2, 3]),
        _status_table=status_table,
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -296,7 +249,7 @@ def test_status_handle(default_conf, update, ticker, fee, mocker) -> None:
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
        _status_table=status_table,
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -341,7 +294,7 @@ def test_status_table_handle(default_conf, update, ticker, fee, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -397,7 +350,7 @@ def test_daily_handle(default_conf, update, ticker, limit_buy_order, fee,
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -465,7 +418,7 @@ def test_daily_wrong_input(default_conf, update, ticker, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -506,7 +459,7 @@ def test_profit_handle(default_conf, update, ticker, ticker_sell_up, fee,
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -604,7 +557,7 @@ def test_telegram_balance_handle(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    freqtradebot = FreqtradeBot(default_conf)
@ -634,7 +587,7 @@ def test_zero_balance_handle(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    freqtradebot = FreqtradeBot(default_conf)
@ -656,7 +609,7 @@ def test_start_handle(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -667,7 +620,7 @@ def test_start_handle(default_conf, update, mocker) -> None:
    assert freqtradebot.state == State.STOPPED
    telegram._start(bot=MagicMock(), update=update)
    assert freqtradebot.state == State.RUNNING
-    assert msg_mock.call_count == 0
+    assert msg_mock.call_count == 1
 def test_start_handle_already_running(default_conf, update, mocker) -> None:
@ -680,7 +633,7 @@ def test_start_handle_already_running(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -705,7 +658,7 @@ def test_stop_handle(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -730,7 +683,7 @@ def test_stop_handle_already_stopped(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
@ -745,6 +698,29 @@ def test_stop_handle_already_stopped(default_conf, update, mocker) -> None:
    assert 'already stopped' in msg_mock.call_args_list[0][0][0]
 def test_reload_conf_handle(default_conf, update, mocker) -> None:
    """ Test _reload_conf() method """
    patch_coinmarketcap(mocker)
    mocker.patch('freqtrade.freqtradebot.exchange.init', MagicMock())
    msg_mock = MagicMock()
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
    freqtradebot = FreqtradeBot(default_conf)
    telegram = Telegram(freqtradebot)
    freqtradebot.state = State.RUNNING
    assert freqtradebot.state == State.RUNNING
    telegram._reload_conf(bot=MagicMock(), update=update)
    assert freqtradebot.state == State.RELOAD_CONF
    assert msg_mock.call_count == 1
    assert 'Reloading config' in msg_mock.call_args_list[0][0][0]
 def test_forcesell_handle(default_conf, update, ticker, fee, ticker_sell_up, mocker) -> None:
    """
    Test _forcesell() method
@ -875,7 +851,7 @@ def test_forcesell_handle_invalid(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
@ -917,7 +893,7 @@ def test_performance_handle(default_conf, update, ticker, fee,
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
@ -958,7 +934,7 @@ def test_performance_handle_invalid(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch('freqtrade.freqtradebot.exchange.validate_pairs', MagicMock())
    freqtradebot = FreqtradeBot(default_conf)
@ -981,7 +957,7 @@ def test_count_handle(default_conf, update, ticker, fee, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    mocker.patch.multiple(
        'freqtrade.freqtradebot.exchange',
@ -1024,7 +1000,7 @@ def test_help_handle(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    freqtradebot = FreqtradeBot(default_conf)
    telegram = Telegram(freqtradebot)
@ -1044,7 +1020,7 @@ def test_version_handle(default_conf, update, mocker) -> None:
    mocker.patch.multiple(
        'freqtrade.rpc.telegram.Telegram',
        _init=MagicMock(),
-        send_msg=msg_mock
+        _send_msg=msg_mock
    )
    freqtradebot = FreqtradeBot(default_conf)
    telegram = Telegram(freqtradebot)
@ -1066,13 +1042,8 @@ def test_send_msg(default_conf, mocker) -> None:
    freqtradebot = FreqtradeBot(conf)
    telegram = Telegram(freqtradebot)
    telegram._config['telegram']['enabled'] = False
    telegram.send_msg('test', bot)
    assert not bot.method_calls
    bot.reset_mock()
    telegram._config['telegram']['enabled'] = True
-    telegram.send_msg('test', bot)
+    telegram._send_msg('test', bot)
    assert len(bot.method_calls) == 1
@ -1090,7 +1061,7 @@ def test_send_msg_network_error(default_conf, mocker, caplog) -> None:
    telegram = Telegram(freqtradebot)
    telegram._config['telegram']['enabled'] = True
-    telegram.send_msg('test', bot)
+    telegram._send_msg('test', bot)
    # Bot should've tried to send it twice
    assert len(bot.method_calls) == 2
--- a/freqtrade/tests/strategy/test_strategy.py
+++ b/freqtrade/tests/strategy/test_strategy.py
@ -26,13 +26,30 @@ def test_load_strategy(result):
    assert 'adx' in resolver.strategy.populate_indicators(result)
 def test_load_strategy_from_url(result):
    resolver = StrategyResolver()
    resolver._load_strategy('https://freq.isaac.international/'
                            'dev/strategies/GBPAQEFGGWCMWVFU34P'
                            'MVGS4P2NJR4IDFNVI4LTCZAKJAD3JCXUMBI4J/AverageStrategy/code')
    assert hasattr(resolver.strategy, 'minimal_roi')
    assert 'adx' in resolver.strategy.populate_indicators(result)
 def test_load_strategy_custom_directory(result):
    resolver = StrategyResolver()
    extra_dir = os.path.join('some', 'path')
-    with pytest.raises(
+
-            FileNotFoundError,
+    if os.name == 'nt':
-            match=r".*No such file or directory: '{}'".format(extra_dir)):
+        with pytest.raises(
-        resolver._load_strategy('TestStrategy', extra_dir)
+                FileNotFoundError,
                match="FileNotFoundError: [WinError 3] The system cannot find the "
                      "path specified: '{}'".format(extra_dir)):
            resolver._load_strategy('TestStrategy', extra_dir)
    else:
        with pytest.raises(
                FileNotFoundError,
                match=r".*No such file or directory: '{}'".format(extra_dir)):
            resolver._load_strategy('TestStrategy', extra_dir)
    assert hasattr(resolver.strategy, 'populate_indicators')
    assert 'adx' in resolver.strategy.populate_indicators(result)
--- a/freqtrade/tests/test_analyze.py
+++ b/freqtrade/tests/test_analyze.py
@ -46,7 +46,7 @@ def test_analyze_object() -> None:
 def test_dataframe_correct_length(result):
    dataframe = Analyze.parse_ticker_dataframe(result)
-    assert len(result.index) - 1 == len(dataframe.index)    # last partial candle removed
+    assert len(result.index) == len(dataframe.index)    # last partial candle NOT removed (for non binance or other known exchanges)
 def test_dataframe_correct_columns(result):
@ -188,4 +188,4 @@ def test_tickerdata_to_dataframe(default_conf) -> None:
    tick = load_tickerdata_file(None, 'UNITTEST/BTC', '1m', timerange=timerange)
    tickerlist = {'UNITTEST/BTC': tick}
    data = analyze.tickerdata_to_dataframe(tickerlist)
-    assert len(data['UNITTEST/BTC']) == 99       # partial candle was removed
+    assert len(data['UNITTEST/BTC']) == 100       # partial candle was NOT removed (only for known exchanges like binance)
--- a/freqtrade/tests/test_configuration.py
+++ b/freqtrade/tests/test_configuration.py
@ -13,6 +13,7 @@ from jsonschema import ValidationError
 from freqtrade.arguments import Arguments
 from freqtrade.configuration import Configuration
 from freqtrade.constants import DEFAULT_DB_PROD_URL, DEFAULT_DB_DRYRUN_URL
 from freqtrade.tests.conftest import log_has
 from freqtrade import OperationalException
@ -140,6 +141,43 @@ def test_load_config_with_params(default_conf, mocker) -> None:
    assert validated_conf.get('strategy_path') == '/some/path'
    assert validated_conf.get('db_url') == 'sqlite:///someurl'
    conf = default_conf.copy()
    conf["dry_run"] = False
    del conf["db_url"]
    mocker.patch('freqtrade.configuration.open', mocker.mock_open(
        read_data=json.dumps(conf)
    ))
    arglist = [
         '--dynamic-whitelist', '10',
         '--strategy', 'TestStrategy',
         '--strategy-path', '/some/path'
     ]
    args = Arguments(arglist, '').get_parsed_arg()
    configuration = Configuration(args)
    validated_conf = configuration.load_config()
    assert validated_conf.get('db_url') == DEFAULT_DB_PROD_URL
    # Test dry=run with ProdURL
    conf = default_conf.copy()
    conf["dry_run"] = True
    conf["db_url"] = DEFAULT_DB_PROD_URL
    mocker.patch('freqtrade.configuration.open', mocker.mock_open(
        read_data=json.dumps(conf)
    ))
    arglist = [
        '--dynamic-whitelist', '10',
        '--strategy', 'TestStrategy',
        '--strategy-path', '/some/path'
    ]
    args = Arguments(arglist, '').get_parsed_arg()
    configuration = Configuration(args)
    validated_conf = configuration.load_config()
    assert validated_conf.get('db_url') == DEFAULT_DB_DRYRUN_URL
 def test_load_custom_strategy(default_conf, mocker) -> None:
    """
@ -310,7 +348,6 @@ def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None:
    arglist = [
        'hyperopt',
        '--epochs', '10',
        '--use-mongodb',
        '--spaces', 'all',
    ]
@ -324,10 +361,6 @@ def test_hyperopt_with_arguments(mocker, default_conf, caplog) -> None:
    assert log_has('Parameter --epochs detected ...', caplog.record_tuples)
    assert log_has('Will run Hyperopt with for 10 epochs ...', caplog.record_tuples)
    assert 'mongodb' in config
    assert config['mongodb'] is True
    assert log_has('Parameter --use-mongodb detected ...', caplog.record_tuples)
    assert 'spaces' in config
    assert config['spaces'] == ['all']
    assert log_has('Parameter -s/--spaces detected: [\'all\']', caplog.record_tuples)
--- a/freqtrade/tests/test_dataframe.py
+++ b/freqtrade/tests/test_dataframe.py
@ -16,7 +16,7 @@ def load_dataframe_pair(pairs):
    dataframe = ld[pairs[0]]
    analyze = Analyze({'strategy': 'DefaultStrategy'})
-    dataframe = analyze.analyze_ticker(dataframe)
+    dataframe = analyze.analyze_ticker(dataframe, pairs[0])
    return dataframe
--- a/freqtrade/tests/test_fiat_convert.py
+++ b/freqtrade/tests/test_fiat_convert.py
@ -40,7 +40,8 @@ def test_pair_convertion_object():
    assert pair_convertion.price == 30000.123
-def test_fiat_convert_is_supported():
+def test_fiat_convert_is_supported(mocker):
    patch_coinmarketcap(mocker)
    fiat_convert = CryptoToFiatConverter()
    assert fiat_convert._is_supported_fiat(fiat='USD') is True
    assert fiat_convert._is_supported_fiat(fiat='usd') is True
@ -48,7 +49,9 @@ def test_fiat_convert_is_supported():
    assert fiat_convert._is_supported_fiat(fiat='ABC') is False
-def test_fiat_convert_add_pair():
+def test_fiat_convert_add_pair(mocker):
    patch_coinmarketcap(mocker)
    fiat_convert = CryptoToFiatConverter()
    pair_len = len(fiat_convert._pairs)
@ -70,11 +73,8 @@ def test_fiat_convert_add_pair():
 def test_fiat_convert_find_price(mocker):
-    api_mock = MagicMock(return_value={
+    patch_coinmarketcap(mocker)
-        'price_usd': 12345.0,
+
        'price_eur': 13000.2
    })
    mocker.patch('freqtrade.fiat_convert.Market.ticker', api_mock)
    fiat_convert = CryptoToFiatConverter()
    with pytest.raises(ValueError, match=r'The fiat ABC is not supported.'):
@ -92,17 +92,15 @@ def test_fiat_convert_find_price(mocker):
 def test_fiat_convert_unsupported_crypto(mocker, caplog):
    mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._cryptomap', return_value=[])
    patch_coinmarketcap(mocker)
    fiat_convert = CryptoToFiatConverter()
    assert fiat_convert._find_price(crypto_symbol='CRYPTO_123', fiat_symbol='EUR') == 0.0
    assert log_has('unsupported crypto-symbol CRYPTO_123 - returning 0.0', caplog.record_tuples)
 def test_fiat_convert_get_price(mocker):
-    api_mock = MagicMock(return_value={
+    patch_coinmarketcap(mocker)
-        'price_usd': 28000.0,
+
        'price_eur': 15000.0
    })
    mocker.patch('freqtrade.fiat_convert.Market.ticker', api_mock)
    mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter._find_price', return_value=28000.0)
    fiat_convert = CryptoToFiatConverter()
@ -172,8 +170,9 @@ def test_fiat_init_network_exception(mocker):
    assert length_cryptomap == 0
-def test_fiat_convert_without_network():
+def test_fiat_convert_without_network(mocker):
    # Because CryptoToFiatConverter is a Singleton we reset the value of _coinmarketcap
    patch_coinmarketcap(mocker)
    fiat_convert = CryptoToFiatConverter()
@ -186,6 +185,7 @@ def test_fiat_convert_without_network():
 def test_convert_amount(mocker):
    patch_coinmarketcap(mocker)
    mocker.patch('freqtrade.fiat_convert.CryptoToFiatConverter.get_price', return_value=12345.0)
    fiat_convert = CryptoToFiatConverter()
--- a/freqtrade/tests/test_freqtradebot.py
+++ b/freqtrade/tests/test_freqtradebot.py
@ -57,7 +57,7 @@ def patch_RPCManager(mocker) -> MagicMock:
    :param mocker: mocker to patch RPCManager class
    :return: RPCManager.send_msg MagicMock to track if this method is called
    """
-    mocker.patch('freqtrade.freqtradebot.RPCManager._init', MagicMock())
+    mocker.patch('freqtrade.rpc.telegram.Telegram', MagicMock())
    rpc_mock = mocker.patch('freqtrade.freqtradebot.RPCManager.send_msg', MagicMock())
    return rpc_mock
@ -68,7 +68,7 @@ def test_freqtradebot_object() -> None:
    Test the FreqtradeBot object has the mandatory public methods
    """
    assert hasattr(FreqtradeBot, 'worker')
-    assert hasattr(FreqtradeBot, 'clean')
+    assert hasattr(FreqtradeBot, 'cleanup')
    assert hasattr(FreqtradeBot, 'create_trade')
    assert hasattr(FreqtradeBot, 'get_target_bid')
    assert hasattr(FreqtradeBot, 'process_maybe_execute_buy')
@ -93,7 +93,7 @@ def test_freqtradebot(mocker, default_conf) -> None:
    assert freqtrade.state is State.STOPPED
-def test_clean(mocker, default_conf, caplog) -> None:
+def test_cleanup(mocker, default_conf, caplog) -> None:
    """
    Test clean() method
    """
@ -101,11 +101,8 @@ def test_clean(mocker, default_conf, caplog) -> None:
    mocker.patch('freqtrade.persistence.cleanup', mock_cleanup)
    freqtrade = get_patched_freqtradebot(mocker, default_conf)
-    assert freqtrade.state == State.RUNNING
+    freqtrade.cleanup()
-
+    assert log_has('Cleaning up modules ...', caplog.record_tuples)
    assert freqtrade.clean()
    assert freqtrade.state == State.STOPPED
    assert log_has('Stopping trader and cleaning up modules...', caplog.record_tuples)
    assert mock_cleanup.call_count == 1
@ -502,27 +499,45 @@ def test_balance_fully_ask_side(mocker) -> None:
    """
    Test get_target_bid() method
    """
-    freqtrade = get_patched_freqtradebot(mocker, {'bid_strategy': {'ask_last_balance': 0.0}})
+    param = {
        'use_book_order': False,
        'book_order_top': 6,
        'ask_last_balance': 0.0,
        'percent_from_top': 0
    }
    freqtrade = get_patched_freqtradebot(mocker, {'bid_strategy': param})
-    assert freqtrade.get_target_bid({'ask': 20, 'last': 10}) == 20
+    assert freqtrade.get_target_bid('ETH/BTC') >= 0.07
 def test_balance_fully_last_side(mocker) -> None:
    """
    Test get_target_bid() method
    """
-    freqtrade = get_patched_freqtradebot(mocker, {'bid_strategy': {'ask_last_balance': 1.0}})
+    param = {
        'use_book_order': False,
        'book_order_top': 6,
        'ask_last_balance': 0.0,
        'percent_from_top': 0
    }
    freqtrade = get_patched_freqtradebot(mocker, {'bid_strategy': param})
-    assert freqtrade.get_target_bid({'ask': 20, 'last': 10}) == 10
+    assert freqtrade.get_target_bid('ETH/BTC') >= 0.07
 def test_balance_bigger_last_ask(mocker) -> None:
    """
    Test get_target_bid() method
    """
-    freqtrade = get_patched_freqtradebot(mocker, {'bid_strategy': {'ask_last_balance': 1.0}})
+    param = {
        'use_book_order': False,
        'book_order_top': 6,
        'ask_last_balance': 0.0,
        'percent_from_top': 0.00
    }
    freqtrade = get_patched_freqtradebot(mocker, {'bid_strategy': param})
-    assert freqtrade.get_target_bid({'ask': 5, 'last': 10}) == 5
+    assert freqtrade.get_target_bid('ETH/BTC') >= 0.07
 def test_process_maybe_execute_buy(mocker, default_conf) -> None:
@ -852,7 +867,7 @@ def test_check_handle_timedout_buy(default_conf, ticker, limit_buy_order_old, fe
    Trade.session.add(trade_buy)
    # check it does cancel buy orders over the time limit
-    freqtrade.check_handle_timedout(600)
+    freqtrade.check_handle_timedout()
    assert cancel_order_mock.call_count == 1
    assert rpc_mock.call_count == 1
    trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
@ -893,7 +908,7 @@ def test_check_handle_timedout_sell(default_conf, ticker, limit_sell_order_old,
    Trade.session.add(trade_sell)
    # check it does cancel sell orders over the time limit
-    freqtrade.check_handle_timedout(600)
+    freqtrade.check_handle_timedout()
    assert cancel_order_mock.call_count == 1
    assert rpc_mock.call_count == 1
    assert trade_sell.is_open is True
@ -933,7 +948,7 @@ def test_check_handle_timedout_partial(default_conf, ticker, limit_buy_order_old
    # check it does cancel buy orders over the time limit
    # note this is for a partially-complete buy order
-    freqtrade.check_handle_timedout(600)
+    freqtrade.check_handle_timedout()
    assert cancel_order_mock.call_count == 1
    assert rpc_mock.call_count == 1
    trades = Trade.query.filter(Trade.open_order_id.is_(trade_buy.open_order_id)).all()
@ -984,7 +999,7 @@ def test_check_handle_timedout_exception(default_conf, ticker, mocker, caplog) -
        'recent call last):\n.*'
    )
-    freqtrade.check_handle_timedout(600)
+    freqtrade.check_handle_timedout()
    assert filter(regexp.match, caplog.record_tuples)
--- a/freqtrade/tests/test_main.py
+++ b/freqtrade/tests/test_main.py
@ -3,12 +3,16 @@ Unit test file for main.py
 """
 import logging
 from copy import deepcopy
 from unittest.mock import MagicMock
 import pytest
 from freqtrade import OperationalException
-from freqtrade.main import main, set_loggers
+from freqtrade.arguments import Arguments
 from freqtrade.freqtradebot import FreqtradeBot
 from freqtrade.main import main, set_loggers, reconfigure
 from freqtrade.state import State
 from freqtrade.tests.conftest import log_has
@ -70,7 +74,7 @@ def test_main_fatal_exception(mocker, default_conf, caplog) -> None:
        'freqtrade.freqtradebot.FreqtradeBot',
        _init_modules=MagicMock(),
        worker=MagicMock(side_effect=Exception),
-        clean=MagicMock(),
+        cleanup=MagicMock(),
    )
    mocker.patch(
        'freqtrade.configuration.Configuration._load_config_file',
@ -97,7 +101,7 @@ def test_main_keyboard_interrupt(mocker, default_conf, caplog) -> None:
        'freqtrade.freqtradebot.FreqtradeBot',
        _init_modules=MagicMock(),
        worker=MagicMock(side_effect=KeyboardInterrupt),
-        clean=MagicMock(),
+        cleanup=MagicMock(),
    )
    mocker.patch(
        'freqtrade.configuration.Configuration._load_config_file',
@ -124,7 +128,7 @@ def test_main_operational_exception(mocker, default_conf, caplog) -> None:
        'freqtrade.freqtradebot.FreqtradeBot',
        _init_modules=MagicMock(),
        worker=MagicMock(side_effect=OperationalException('Oh snap!')),
-        clean=MagicMock(),
+        cleanup=MagicMock(),
    )
    mocker.patch(
        'freqtrade.configuration.Configuration._load_config_file',
@ -140,3 +144,69 @@ def test_main_operational_exception(mocker, default_conf, caplog) -> None:
        main(args)
    assert log_has('Using config: config.json.example ...', caplog.record_tuples)
    assert log_has('Oh snap!', caplog.record_tuples)
 def test_main_reload_conf(mocker, default_conf, caplog) -> None:
    """
    Test main() function
    In this test we are skipping the while True loop by throwing an exception.
    """
    mocker.patch.multiple(
        'freqtrade.freqtradebot.FreqtradeBot',
        _init_modules=MagicMock(),
        worker=MagicMock(return_value=State.RELOAD_CONF),
        cleanup=MagicMock(),
    )
    mocker.patch(
        'freqtrade.configuration.Configuration._load_config_file',
        lambda *args, **kwargs: default_conf
    )
    mocker.patch('freqtrade.freqtradebot.CryptoToFiatConverter', MagicMock())
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
    # Raise exception as side effect to avoid endless loop
    reconfigure_mock = mocker.patch(
        'freqtrade.main.reconfigure', MagicMock(side_effect=Exception)
    )
    with pytest.raises(SystemExit):
        main(['-c', 'config.json.example'])
    assert reconfigure_mock.call_count == 1
    assert log_has('Using config: config.json.example ...', caplog.record_tuples)
 def test_reconfigure(mocker, default_conf) -> None:
    """ Test recreate() function """
    mocker.patch.multiple(
        'freqtrade.freqtradebot.FreqtradeBot',
        _init_modules=MagicMock(),
        worker=MagicMock(side_effect=OperationalException('Oh snap!')),
        cleanup=MagicMock(),
    )
    mocker.patch(
        'freqtrade.configuration.Configuration._load_config_file',
        lambda *args, **kwargs: default_conf
    )
    mocker.patch('freqtrade.freqtradebot.CryptoToFiatConverter', MagicMock())
    mocker.patch('freqtrade.freqtradebot.RPCManager', MagicMock())
    freqtrade = FreqtradeBot(default_conf)
    # Renew mock to return modified data
    conf = deepcopy(default_conf)
    conf['stake_amount'] += 1
    mocker.patch(
        'freqtrade.configuration.Configuration._load_config_file',
        lambda *args, **kwargs: conf
    )
    # reconfigure should return a new instance
    freqtrade2 = reconfigure(
        freqtrade,
        Arguments(['-c', 'config.json.example'], '').get_parsed_arg()
    )
    # Verify we have a new instance with the new config
    assert freqtrade is not freqtrade2
    assert freqtrade.config['stake_amount'] + 1 == freqtrade2.config['stake_amount']
--- a/freqtrade/tests/test_persistence.py
+++ b/freqtrade/tests/test_persistence.py
@ -425,6 +425,8 @@ def test_migrate_new(mocker, default_conf, fee):
                                close_profit FLOAT,
                                stake_amount FLOAT NOT NULL,
                                amount FLOAT,
                                initial_stop_loss FLOAT,
                                max_rate FLOAT,
                                open_date DATETIME NOT NULL,
                                close_date DATETIME,
                                open_order_id VARCHAR,
--- a/freqtrade/tests/testdata/ADA_BTC-1m.json
+++ b/freqtrade/tests/testdata/ADA_BTC-1m.json
--- a/freqtrade/tests/testdata/ADA_BTC-5m.json
+++ b/freqtrade/tests/testdata/ADA_BTC-5m.json
--- a/freqtrade/tests/testdata/DASH_BTC-1m.json
+++ b/freqtrade/tests/testdata/DASH_BTC-1m.json
--- a/freqtrade/tests/testdata/DASH_BTC-5m.json
+++ b/freqtrade/tests/testdata/DASH_BTC-5m.json
--- a/freqtrade/tests/testdata/ETC_BTC-1m.json
+++ b/freqtrade/tests/testdata/ETC_BTC-1m.json
--- a/freqtrade/tests/testdata/ETC_BTC-5m.json
+++ b/freqtrade/tests/testdata/ETC_BTC-5m.json
--- a/freqtrade/tests/testdata/ETH_BTC-1m.json
+++ b/freqtrade/tests/testdata/ETH_BTC-1m.json
--- a/freqtrade/tests/testdata/ETH_BTC-5m.json
+++ b/freqtrade/tests/testdata/ETH_BTC-5m.json
--- a/freqtrade/tests/testdata/LTC_BTC-1m.json
+++ b/freqtrade/tests/testdata/LTC_BTC-1m.json
--- a/freqtrade/tests/testdata/LTC_BTC-5m.json
+++ b/freqtrade/tests/testdata/LTC_BTC-5m.json
--- a/freqtrade/tests/testdata/POWR_BTC-1m.json
+++ b/freqtrade/tests/testdata/POWR_BTC-1m.json
--- a/freqtrade/tests/testdata/POWR_BTC-5m.json
+++ b/freqtrade/tests/testdata/POWR_BTC-5m.json
--- a/freqtrade/tests/testdata/XLM_BTC-1m.json
+++ b/freqtrade/tests/testdata/XLM_BTC-1m.json
--- a/freqtrade/tests/testdata/XLM_BTC-5m.json
+++ b/freqtrade/tests/testdata/XLM_BTC-5m.json
--- a/freqtrade/tests/testdata/XMR_BTC-1m.json
+++ b/freqtrade/tests/testdata/XMR_BTC-1m.json
--- a/freqtrade/tests/testdata/XMR_BTC-5m.json
+++ b/freqtrade/tests/testdata/XMR_BTC-5m.json
--- a/freqtrade/tests/testdata/ZEC_BTC-1m.json
+++ b/freqtrade/tests/testdata/ZEC_BTC-1m.json
--- a/freqtrade/tests/testdata/ZEC_BTC-5m.json
+++ b/freqtrade/tests/testdata/ZEC_BTC-5m.json
--- a/freqtrade/vendor/qtpylib/indicators.py
+++ b/freqtrade/vendor/qtpylib/indicators.py
@ -110,10 +110,13 @@ def heikinashi(bars):
    bars = bars.copy()
    bars['ha_close'] = (bars['open'] + bars['high'] +
                        bars['low'] + bars['close']) / 4
    bars['ha_open'] = (bars['open'].shift(1) + bars['close'].shift(1)) / 2
    bars.loc[:1, 'ha_open'] = bars['open'].values[0]
-    bars.loc[1:, 'ha_open'] = (
+    for x in range(2):
-        (bars['ha_open'].shift(1) + bars['ha_close'].shift(1)) / 2)[1:]
+        bars.loc[1:, 'ha_open'] = (
            (bars['ha_open'].shift(1) + bars['ha_close'].shift(1)) / 2)[1:]
    bars['ha_high'] = bars.loc[:, ['high', 'ha_open', 'ha_close']].max(axis=1)
    bars['ha_low'] = bars.loc[:, ['low', 'ha_open', 'ha_close']].min(axis=1)
@ -248,45 +251,36 @@ def crossed_below(series1, series2):
 def rolling_std(series, window=200, min_periods=None):
    min_periods = window if min_periods is None else min_periods
-    try:
+    if min_periods == window and len(series) > window:
-        if min_periods == window:
+        return numpy_rolling_std(series, window, True)
-            return numpy_rolling_std(series, window, True)
+    else:
-        else:
+        try:
-            try:
+            return series.rolling(window=window, min_periods=min_periods).std()
-                return series.rolling(window=window, min_periods=min_periods).std()
+        except BaseException:
-            except BaseException:
+            return pd.Series(series).rolling(window=window, min_periods=min_periods).std()
                return pd.Series(series).rolling(window=window, min_periods=min_periods).std()
    except BaseException:
        return pd.rolling_std(series, window=window, min_periods=min_periods)
 # ---------------------------------------------
 def rolling_mean(series, window=200, min_periods=None):
    min_periods = window if min_periods is None else min_periods
-    try:
+    if min_periods == window and len(series) > window:
-        if min_periods == window:
+        return numpy_rolling_mean(series, window, True)
-            return numpy_rolling_mean(series, window, True)
+    else:
-        else:
+        try:
-            try:
+            return series.rolling(window=window, min_periods=min_periods).mean()
-                return series.rolling(window=window, min_periods=min_periods).mean()
+        except BaseException:
-            except BaseException:
+            return pd.Series(series).rolling(window=window, min_periods=min_periods).mean()
                return pd.Series(series).rolling(window=window, min_periods=min_periods).mean()
    except BaseException:
        return pd.rolling_mean(series, window=window, min_periods=min_periods)
 # ---------------------------------------------
 def rolling_min(series, window=14, min_periods=None):
    min_periods = window if min_periods is None else min_periods
    try:
-        try:
+        return series.rolling(window=window, min_periods=min_periods).min()
            return series.rolling(window=window, min_periods=min_periods).min()
        except BaseException:
            return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
    except BaseException:
-        return pd.rolling_min(series, window=window, min_periods=min_periods)
+        return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
 # ---------------------------------------------
@ -294,12 +288,9 @@ def rolling_min(series, window=14, min_periods=None):
 def rolling_max(series, window=14, min_periods=None):
    min_periods = window if min_periods is None else min_periods
    try:
-        try:
+        return series.rolling(window=window, min_periods=min_periods).min()
            return series.rolling(window=window, min_periods=min_periods).min()
        except BaseException:
            return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
    except BaseException:
-        return pd.rolling_min(series, window=window, min_periods=min_periods)
+        return pd.Series(series).rolling(window=window, min_periods=min_periods).min()
 # ---------------------------------------------
@ -566,9 +557,9 @@ def stoch(df, window=14, d=3, k=3, fast=False):
    return pd.DataFrame(index=df.index, data=data)
 # ---------------------------------------------
 def zscore(bars, window=20, stds=1, col='close'):
    """ get zscore of price """
    std = numpy_rolling_std(bars[col], window)
--- a/lib/libta_lib.a
+++ b/lib/libta_lib.a
--- a/lib/libta_lib.la
+++ b/lib/libta_lib.la
@ -0,0 +1,35 @@
 # libta_lib.la - a libtool library file
 # Generated by ltmain.sh - GNU libtool 1.5.22 Debian 1.5.22-4 (1.1220.2.365 2005/12/18 22:14:06)
 #
 # Please DO NOT delete this file!
 # It is necessary for linking the library.
 # The name that we can dlopen(3).
 dlname='libta_lib.so.0'
 # Names of this library.
 library_names='libta_lib.so.0.0.0 libta_lib.so.0 libta_lib.so'
 # The name of the static archive.
 old_library='libta_lib.a'
 # Libraries that this one depends upon.
 dependency_libs=' -lpthread -ldl'
 # Version information for libta_lib.
 current=0
 age=0
 revision=0
 # Is this an already installed library?
 installed=yes
 # Should we warn about portability when linking against -modules?
 shouldnotlink=no
 # Files to dlopen/dlpreopen
 dlopen=''
 dlpreopen=''
 # Directory that this library needs to be installed in:
 libdir='/usr/local/lib'
--- a/lib/libta_lib.so.0
+++ b/lib/libta_lib.so.0
@ -0,0 +1 @@
 libta_lib.so.0.0.0
--- a/lib/libta_lib.so.0.0.0
+++ b/lib/libta_lib.so.0.0.0
--- a/requirements.txt
+++ b/requirements.txt
@ -1,25 +1,26 @@
-ccxt==1.14.169
+ccxt==1.14.224
 SQLAlchemy==1.2.8
 python-telegram-bot==10.1.0
 arrow==0.12.1
 cachetools==2.1.0
-requests==2.18.4
+requests==2.19.1
 urllib3==1.22
 wrapt==1.10.11
-pandas==0.23.0
+pandas==0.23.1
 scikit-learn==0.19.1
 scipy==1.1.0
 jsonschema==2.6.0
-numpy==1.14.4
+numpy==1.14.5
 TA-Lib==0.4.17
 pytest==3.6.1
 pytest-mock==1.10.0
 pytest-cov==2.5.1
 hyperopt==0.1
 # do not upgrade networkx before this is fixed https://github.com/hyperopt/hyperopt/issues/325
-networkx==1.11 # pyup: ignore
+networkx==1.11
 git+git://github.com/berlinguyinca/technical
 tabulate==0.8.2
 coinmarketcap==5.0.3
-
+simplejson==3.15.0
 # Required for plotting data
 #plotly==2.3.0
--- a/scripts/download_backtest_data.py
+++ b/scripts/download_backtest_data.py
@ -30,20 +30,27 @@ if not os.path.isfile(pairs_file):
 with open(pairs_file) as file:
    PAIRS = list(set(json.load(file)))
 PAIRS.sort()
 since_time = None
 if args.days:
    since_time = arrow.utcnow().shift(days=-args.days).timestamp * 1000
 print(f'About to download pairs: {PAIRS} to {dl_path}')
 # Init exchange
 exchange._API = exchange.init_ccxt({'key': '',
                                    'secret': '',
                                    'name': args.exchange})
-
+pairs_not_available = []
 # Make sure API markets is initialized
 exchange._API.load_markets()
 for pair in PAIRS:
    if pair not in exchange._API.markets:
        pairs_not_available.append(pair)
        print(f"skipping pair {pair}")
        continue
    for tick_interval in timeframes:
        print(f'downloading pair {pair}, interval {tick_interval}')
@ -60,3 +67,7 @@ for pair in PAIRS:
        pair_print = pair.replace('/', '_')
        filename = f'{pair_print}-{tick_interval}.json'
        misc.file_dump_json(os.path.join(dl_path, filename), data)
 if pairs_not_available:
    print(f"Pairs [{','.join(pairs_not_available)}] not availble.")
--- a/scripts/plot_dataframe.py
+++ b/scripts/plot_dataframe.py
@ -5,45 +5,386 @@ Script to display when the bot will buy a specific pair
 Mandatory Cli parameters:
 -p / --pair: pair to examine
 Option but recommended
 -s / --strategy: strategy to use
 Optional Cli parameters
 -s / --strategy: strategy to use
 -d / --datadir: path to pair backtest data
 --timerange: specify what timerange of data to use.
 -l / --live: Live, to download the latest ticker for the pair
 -db / --db-url: Show trades stored in database
 --plot-max-ticks N: plot N data points and overwrite the internal 750 cut of
 Indicators recommended
 Row 1: sma, ema3, ema5, ema10, ema50
 Row 3: macd, rsi, fisher_rsi, mfi, slowd, slowk, fastd, fastk
-Example of usage:
+Plotting Subplots, require the name of the dataframe column.
-> python3 scripts/plot_dataframe.py --pair BTC/EUR -d user_data/data/ --indicators1 sma,ema3
+
--indicators2 fastk,fastd
+Each plot will be displayed as usual on exchanges
 --plot-rsi <RSI>
 --plot-cci <CCI>
 --plot-osc <CCI>
 --plot-macd <MACD>
 --plot-cmf <CMF>
 --
 """
 import datetime
 import logging
 import os
 import sys
 from argparse import Namespace
-from typing import Dict, List, Any
+from typing import List
 import plotly.graph_objs as go
 from plotly import tools
 from plotly.offline import plot
 from typing import Dict, List, Any
 from sqlalchemy import create_engine
 import freqtrade.optimize as optimize
 from freqtrade import exchange
 from freqtrade import persistence
 from freqtrade.analyze import Analyze
 from freqtrade.arguments import Arguments
-from freqtrade.optimize.backtesting import setup_configuration
+from freqtrade.analyze import Analyze
 from freqtrade import exchange
 import freqtrade.optimize as optimize
 from freqtrade import persistence
 from freqtrade.persistence import Trade
 from freqtrade.configuration import Configuration
 from pandas import DataFrame
 logger = logging.getLogger(__name__)
 _CONF: Dict[str, Any] = {}
 logger = logging.getLogger('freqtrade')
 def plot_dataframes_markers(data, fig, args):
    """
        plots additional dataframe markers in the main plot
    :param data:
    :param fig:
    :param args:
    :return:
    """
    if args.plotdataframemarker:
        for x in args.plotdataframemarker:
            filter = data[(data[x] == 100) | (data[x] == -100)]
            marker = go.Scatter(
                x=filter.date,
                y=filter.low * 0.99,
                mode='markers',
                name=x,
                marker=dict(
                    symbol='diamond-tall-open',
                    size=10,
                    line=dict(width=1)
                )
            )
            fig.append_trace(marker, 1, 1)
 def plot_dataframes(data, fig, args):
    """
        plots additional dataframes in the main plot
    :param data:
    :param fig:
    :param args:
    :return:
    """
    if args.plotdataframe:
        for x in args.plotdataframe:
            chart = go.Scattergl(x=data['date'], y=data[x], name=x)
            fig.append_trace(chart, 1, 1)
 def plot_volume_dataframe(data, fig, args, plotnumber):
    """
        adds the plotting of the volume
    :param data:
    :param fig:
    :param args:
    :return:
    """
    volume = go.Bar(x=data['date'], y=data['volume'], name='Volume')
    fig.append_trace(volume, plotnumber, 1)
 def plot_macd_dataframe(data, fig, args, plotnumber):
    """
        adds the plotting of the MACD if specified
    :param data:
    :param fig:
    :param args:
    :return:
    """
    macd = go.Scattergl(x=data['date'], y=data[args.plotmacd], name='MACD')
    macdsignal = go.Scattergl(x=data['date'], y=data[args.plotmacd + 'signal'], name='MACD signal')
    fig.append_trace(macd, plotnumber, 1)
    fig.append_trace(macdsignal, plotnumber, 1)
 def plot_rsi_dataframe(data, fig, args, plotnumber):
    """
        this function plots an additional RSI chart under the exiting charts
    :param data:
    :param fig:
    :param args:
    :return:
    """
    if args.plotrsi:
        for x in args.plotrsi:
            rsi = go.Scattergl(x=data['date'], y=data[x], name=x)
            fig.append_trace(rsi, plotnumber, 1)
    fig['layout']['shapes'].append(
        {
            'yref': 'y' + str(plotnumber),
            'fillcolor': 'red',
            'opacity': 0.1,
            'type': 'rect',
            'x0': DataFrame.min(data['date']),
            'x1': DataFrame.max(data['date']),
            'y0': 70,
            'y1': 100,
            'line': {'color': 'gray'}
        }
    )
    fig['layout']['shapes'].append(
        {
            'yref': 'y' + str(plotnumber),
            'fillcolor': 'green',
            'opacity': 0.1,
            'type': 'rect',
            'x0': DataFrame.min(data['date']),
            'x1': DataFrame.max(data['date']),
            'y0': 0,
            'y1': 30,
            'line': {'color': 'gray'}
        }
    )
 def plot_osc_dataframe(data, fig, args, plotnumber):
    """
        this function plots an additional cci chart under the exiting charts
    :param data:
    :param fig:
    :param args:
    :return:
    """
    if args.plotosc:
        for x in args.plotosc:
            chart = go.Scattergl(x=data['date'], y=data[x], name=x)
            fig.append_trace(chart, plotnumber, 1)
    fig['layout']['shapes'].append(
        {
            'yref': 'y' + str(plotnumber),
            'fillcolor': 'gray',
            'opacity': 0.1,
            'type': 'rect',
            'x0': DataFrame.min(data['date']),
            'x1': DataFrame.max(data['date']),
            'y0': 0.3,
            'y1': 0.7,
            'line': {'color': 'gray'}
        }
    )
    fig['layout']['shapes'].append(
        {
            'yref': 'y' + str(plotnumber),
            'type': 'line',
            'x0': DataFrame.min(data['date']),
            'x1': DataFrame.max(data['date']),
            'y0': 0.6,
            'y1': 0.6,
            'line': {'color': 'red','width': 1}
        }
    )
    fig['layout']['shapes'].append(
        {
            'yref': 'y' + str(plotnumber),
            'type': 'line',
            'x0': DataFrame.min(data['date']),
            'x1': DataFrame.max(data['date']),
            'y0': 0.4,
            'y1': 0.4,
            'line': {'color': 'green','width':1}
        }
    )
 def plot_cmf_dataframe(data, fig, args, plotnumber):
    """
        this function plots an additional cci chart under the exiting charts
    :param data:
    :param fig:
    :param args:
    :return:
    """
    minValue = 0;
    maxValue = 0;
    if args.plotcmf:
        for x in args.plotcmf:
            chart = go.Bar(x=data['date'], y=data[x], name=x)
            fig.append_trace(chart, plotnumber, 1)
 def plot_cci_dataframe(data, fig, args, plotnumber):
    """
        this function plots an additional cci chart under the exiting charts
    :param data:
    :param fig:
    :param args:
    :return:
    """
    minValue = 0;
    maxValue = 0;
    if args.plotcci:
        for x in args.plotcci:
            if minValue > min(data[x]):
                minValue = min(data[x])
            if maxValue < max(data[x]):
                maxValue = max(data[x])
            chart = go.Scattergl(x=data['date'], y=data[x], name=x)
            fig.append_trace(chart, plotnumber, 1)
    fig['layout']['shapes'].append(
        {
            'yref': 'y' + str(plotnumber),
            'fillcolor': 'red',
            'opacity': 0.1,
            'type': 'rect',
            'x0': DataFrame.min(data['date']),
            'x1': DataFrame.max(data['date']),
            'y0': 100,
            'y1': maxValue,
            'line': {'color': 'gray'}
        }
    )
    fig['layout']['shapes'].append(
        {
            'yref': 'y' + str(plotnumber),
            'fillcolor': 'green',
            'opacity': 0.1,
            'type': 'rect',
            'x0': DataFrame.min(data['date']),
            'x1': DataFrame.max(data['date']),
            'y0': -100,
            'y1': minValue,
            'line': {'color': 'gray'}
        }
    )
 def plot_stop_loss_trade(df_sell, fig, analyze, args):
    """
        plots the stop loss for the associated trades and buys
        as well as the estimated profit ranges.
        will be enabled if --stop-loss is provided
        as argument
    :param data:
    :param trades:
    :return:
    """
    if args.stoplossdisplay is False:
        return
    if 'associated_buy_price' not in df_sell:
        return
    stoploss = analyze.strategy.stoploss
    for index, x in df_sell.iterrows():
        if x['associated_buy_price'] > 0:
            # draw stop loss
            fig['layout']['shapes'].append(
                {
                    'fillcolor': 'red',
                    'opacity': 0.1,
                    'type': 'rect',
                    'x0': x['associated_buy_date'],
                    'x1': x['date'],
                    'y0': x['associated_buy_price'],
                    'y1': (x['associated_buy_price'] - abs(stoploss) * x['associated_buy_price']),
                    'line': {'color': 'red'}
                }
            )
            totalTime = 0
            for time in analyze.strategy.minimal_roi:
                t = int(time)
                totalTime = t + totalTime
                enddate = x['date']
                date = x['associated_buy_date'] + datetime.timedelta(minutes=totalTime)
                # draw profit range
                fig['layout']['shapes'].append(
                    {
                        'fillcolor': 'green',
                        'opacity': 0.1,
                        'type': 'rect',
                        'x0': date,
                        'x1': enddate,
                        'y0': x['associated_buy_price'],
                        'y1': x['associated_buy_price'] + x['associated_buy_price'] * analyze.strategy.minimal_roi[
                            time],
                        'line': {'color': 'green'}
                    }
                )
 def find_profits(data):
    """
        finds the profits between sells and the associated buys. This does not take in account
        ROI!
    :param data:
    :return:
    """
    # go over all the sells
    # find all previous buys
    df_sell = data[data['sell'] == 1]
    df_sell['profit'] = 0
    df_buys = data[data['buy'] == 1]
    lastDate = data['date'].iloc[0]
    for index, row in df_sell.iterrows():
        buys = df_buys[(df_buys['date'] < row['date']) & (df_buys['date'] > lastDate)]
        profit = None
        if buys['date'].count() > 0:
            buys = buys.tail()
            profit = round(row['close'] / buys['close'].values[0] * 100 - 100, 2)
            lastDate = row['date']
            df_sell.loc[index, 'associated_buy_date'] = buys['date'].values[0]
            df_sell.loc[index, 'associated_buy_price'] = buys['close'].values[0]
        df_sell.loc[index, 'profit'] = profit
    return df_sell
 def plot_analyzed_dataframe(args: Namespace) -> None:
@ -51,29 +392,14 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
    Calls analyze() and plots the returned dataframe
    :return: None
    """
-    global _CONF
+    pair = args.pair.replace('-', '_')
    # Load the configuration
    _CONF.update(setup_configuration(args))
    # Set the pair to audit
    pair = args.pair
    if pair is None:
        logger.critical('Parameter --pair mandatory;. E.g --pair ETH/BTC')
        exit()
    if '/' not in pair:
        logger.critical('--pair format must be XXX/YYY')
        exit()
    # Set timerange to use
    timerange = Arguments.parse_timerange(args.timerange)
-    # Load the strategy
+    # Init strategy
    try:
-        analyze = Analyze(_CONF)
+        config = Configuration(args)
-        exchange.init(_CONF)
+
        analyze = Analyze(config.get_config())
    except AttributeError:
        logger.critical(
            'Impossible to load the strategy. Please check the file "user_data/strategies/%s.py"',
@ -81,75 +407,40 @@ def plot_analyzed_dataframe(args: Namespace) -> None:
        )
        exit()
-    # Set the ticker to use
+    tick_interval = analyze.strategy.ticker_interval
    tick_interval = analyze.get_ticker_interval()
    # Load pair tickers
    tickers = {}
    if args.live:
        logger.info('Downloading pair.')
        # Init Bittrex to use public API
        exchange.init({'key': '', 'secret': ''})
        tickers[pair] = exchange.get_ticker_history(pair, tick_interval)
    else:
        tickers = optimize.load_data(
-            datadir=args.datadir,
+            datadir=_CONF.get("datadir"),
            pairs=[pair],
            ticker_interval=tick_interval,
-            refresh_pairs=_CONF.get('refresh_pairs', False),
+            refresh_pairs=False,
            timerange=timerange
        )
        # No ticker found, or impossible to download
        if tickers == {}:
            exit()
    # Get trades already made from the DB
    trades: List[Trade] = []
    if args.db_url:
        persistence.init(_CONF)
        trades = Trade.query.filter(Trade.pair.is_(pair)).all()
    dataframes = analyze.tickerdata_to_dataframe(tickers)
    dataframe = dataframes[pair]
    dataframe = analyze.populate_buy_trend(dataframe)
    dataframe = analyze.populate_sell_trend(dataframe)
    if len(dataframe.index) > args.plotticks:
        logger.warning('Ticker contained more than {} candles, clipping.'.format(args.plotticks))
    data = dataframe.tail(args.plotticks)
    trades = []
    if args.db_url:
        engine = create_engine('sqlite:///' + args.db_url)
        persistence.init(_CONF, engine)
        trades = Trade.query.filter(Trade.pair.is_(pair)).all()
    if len(dataframe.index) > 750:
        logger.warning('Ticker contained more than 750 candles, clipping.')
    data = dataframe.tail(750)
    fig = generate_graph(
        pair=pair,
        trades=trades,
        data=dataframe.tail(750),
        args=args
    )
    plot(fig, filename=os.path.join('user_data', 'freqtrade-plot.html'))
 def generate_graph(pair, trades, data, args) -> tools.make_subplots:
    """
    Generate the graph from the data generated by Backtesting or from DB
    :param pair: Pair to Display on the graph
    :param trades: All trades created
    :param data: Dataframe
    :param args: sys.argv that contrains the two params indicators1, and indicators2
    :return: None
    """
    # Define the graph
    fig = tools.make_subplots(
        rows=3,
        cols=1,
        shared_xaxes=True,
        row_width=[1, 1, 4],
        vertical_spacing=0.0001,
    )
    fig['layout'].update(title=pair)
    fig['layout']['yaxis1'].update(title='Price')
    fig['layout']['yaxis2'].update(title='Volume')
    fig['layout']['yaxis3'].update(title='Other')
    # Common information
    candles = go.Candlestick(
        x=data.date,
        open=data.open,
@ -160,6 +451,7 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
    )
    df_buy = data[data['buy'] == 1]
    buys = go.Scattergl(
        x=df_buy.date,
        y=df_buy.close,
@ -167,23 +459,27 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
        name='buy',
        marker=dict(
            symbol='triangle-up-dot',
-            size=9,
+            size=15,
            line=dict(width=1),
            color='green',
        )
    )
-    df_sell = data[data['sell'] == 1]
+    df_sell = find_profits(data)
-    sells = go.Scattergl(
+
    sells = go.Scatter(
        x=df_sell.date,
        y=df_sell.close,
-        mode='markers',
+        mode='markers+text',
        name='sell',
        text=df_sell.profit,
        textposition='top right',
        marker=dict(
            symbol='triangle-down-dot',
-            size=9,
+            size=15,
            line=dict(width=1),
            color='red',
        )
    )
    trade_buys = go.Scattergl(
@ -211,67 +507,107 @@ def generate_graph(pair, trades, data, args) -> tools.make_subplots:
        )
    )
-    # Row 1
+    bb_lower = go.Scatter(
        x=data.date,
        y=data.bb_lowerband,
        name='BB lower',
        line={'color': "transparent"},
    )
    bb_upper = go.Scatter(
        x=data.date,
        y=data.bb_upperband,
        name='BB upper',
        fill="tonexty",
        fillcolor="rgba(0,176,246,0.2)",
        line={'color': "transparent"},
    )
    bb_middle = go.Scatter(
        x=data.date,
        y=data.bb_middleband,
        name='BB middle',
        fill="tonexty",
        fillcolor="rgba(0,176,246,0.2)",
        line={'color': "red"},
    )
    # ugly hack for now
    rowWidth = [1]
    if args.plotvolume:
        rowWidth.append(1)
    if args.plotmacd:
        rowWidth.append(1)
    if args.plotrsi:
        rowWidth.append(1)
    if args.plotcci:
        rowWidth.append(1)
    if args.plotcmf:
        rowWidth.append(1)
    if args.plotosc:
        rowWidth.append(1)
    # standard layout signal + volume
    fig = tools.make_subplots(
        rows=len(rowWidth),
        cols=1,
        shared_xaxes=True,
        row_width=rowWidth,
        vertical_spacing=0.0001,
    )
    # todo should be optional
    fig.append_trace(candles, 1, 1)
    fig.append_trace(bb_lower, 1, 1)
    fig.append_trace(bb_middle, 1, 1)
    fig.append_trace(bb_upper, 1, 1)
    if 'bb_lowerband' in data and 'bb_upperband' in data:
        bb_lower = go.Scatter(
            x=data.date,
            y=data.bb_lowerband,
            name='BB lower',
            line={'color': "transparent"},
        )
        bb_upper = go.Scatter(
            x=data.date,
            y=data.bb_upperband,
            name='BB upper',
            fill="tonexty",
            fillcolor="rgba(0,176,246,0.2)",
            line={'color': "transparent"},
        )
        fig.append_trace(bb_lower, 1, 1)
        fig.append_trace(bb_upper, 1, 1)
    fig = generate_row(fig=fig, row=1, raw_indicators=args.indicators1, data=data)
    fig.append_trace(buys, 1, 1)
    fig.append_trace(sells, 1, 1)
    fig.append_trace(trade_buys, 1, 1)
    fig.append_trace(trade_sells, 1, 1)
-    # Row 2
+    # append stop loss/profit
-    volume = go.Bar(
+    plot_stop_loss_trade(df_sell, fig, analyze, args)
        x=data['date'],
        y=data['volume'],
        name='Volume'
    )
    fig.append_trace(volume, 2, 1)
-    # Row 3
+    # plot other dataframes
-    fig = generate_row(fig=fig, row=3, raw_indicators=args.indicators2, data=data)
+    plot_dataframes(data, fig, args)
    plot_dataframes_markers(data, fig, args)
-    return fig
+    fig['layout'].update(title=args.pair)
    fig['layout']['yaxis1'].update(title='Price')
    subplots = 1
-def generate_row(fig, row, raw_indicators, data) -> tools.make_subplots:
+    if args.plotvolume:
-    """
+        subplots = subplots + 1
-    Generator all the indicator selected by the user for a specific row
+        plot_volume_dataframe(data, fig, args, subplots)
-    """
+        fig['layout']['yaxis' + str(subplots)].update(title='Volume')
    for indicator in raw_indicators.split(','):
        if indicator in data:
            scattergl = go.Scattergl(
                x=data['date'],
                y=data[indicator],
                name=indicator
            )
            fig.append_trace(scattergl, row, 1)
        else:
            logger.info(
                'Indicator "%s" ignored. Reason: This indicator is not found '
                'in your strategy.',
                indicator
            )
-    return fig
+    if args.plotmacd:
        subplots = subplots + 1
        plot_macd_dataframe(data, fig, args, subplots)
        fig['layout']['yaxis' + str(subplots)].update(title='MACD')
    if args.plotrsi:
        subplots = subplots + 1
        plot_rsi_dataframe(data, fig, args, subplots)
        fig['layout']['yaxis' + str(subplots)].update(title='RSI', range=[0, 100])
    if args.plotcci:
        subplots = subplots + 1
        plot_cci_dataframe(data, fig, args, subplots)
        fig['layout']['yaxis' + str(subplots)].update(title='CCI')
    if args.plotosc:
        subplots = subplots + 1
        plot_osc_dataframe(data, fig, args, subplots)
        fig['layout']['yaxis' + str(subplots)].update(title='OSC')
    if args.plotcmf:
        subplots = subplots + 1
        plot_cmf_dataframe(data, fig, args, subplots)
        fig['layout']['yaxis' + str(subplots)].update(title='CMF')
    # updated all the
    plot(fig, filename='freqtrade-plot.html')
 def plot_parse_args(args: List[str]) -> Namespace:
@ -282,24 +618,6 @@ def plot_parse_args(args: List[str]) -> Namespace:
    """
    arguments = Arguments(args, 'Graph dataframe')
    arguments.scripts_options()
    arguments.parser.add_argument(
        '--indicators1',
        help='Set indicators from your strategy you want in the first row of the graph. Separate '
             'them with a coma. E.g: ema3,ema5 (default: %(default)s)',
        type=str,
        default='sma,ema3,ema5',
        dest='indicators1',
    )
    arguments.parser.add_argument(
        '--indicators2',
        help='Set indicators from your strategy you want in the third row of the graph. Separate '
             'them with a coma. E.g: fastd,fastk (default: %(default)s)',
        type=str,
        default='macd',
        dest='indicators2',
    )
    arguments.common_args_parser()
    arguments.optimizer_shared_options(arguments.parser)
    arguments.backtesting_options(arguments.parser)
--- a/scripts/plot_profit.py
+++ b/scripts/plot_profit.py
@ -121,7 +121,7 @@ def plot_profit(args: Namespace) -> None:
        logger.info('Filter, keep pairs %s' % pairs)
    tickers = optimize.load_data(
-        datadir=args.datadir,
+        datadir=config.get('datadir'),
        pairs=pairs,
        ticker_interval=tick_interval,
        refresh_pairs=False,
--- a/scripts/start-hyperopt-worker.py
+++ b/scripts/start-hyperopt-worker.py
@ -1,27 +0,0 @@
 #!/usr/bin/env python3
 import multiprocessing
 import os
 import subprocess
 PROC_COUNT = multiprocessing.cpu_count() - 1
 DB_NAME = 'freqtrade_hyperopt'
 WORK_DIR = os.path.join(
    os.path.sep,
    os.path.abspath(os.path.dirname(__file__)),
    '..', '.hyperopt', 'worker'
 )
 if not os.path.exists(WORK_DIR):
    os.makedirs(WORK_DIR)
 # Spawn workers
 command = [
    'hyperopt-mongo-worker',
    '--mongo=127.0.0.1:1234/{}'.format(DB_NAME),
    '--poll-interval=0.1',
    '--workdir={}'.format(WORK_DIR),
 ]
 processes = [subprocess.Popen(command) for i in range(PROC_COUNT)]
 # Join all workers
 for proc in processes:
    proc.wait()
--- a/scripts/start-mongodb.py
+++ b/scripts/start-mongodb.py
@ -1,21 +0,0 @@
 #!/usr/bin/env python3
 import os
 import subprocess
 DB_PATH = os.path.join(
    os.path.sep,
    os.path.abspath(os.path.dirname(__file__)),
    '..', '.hyperopt', 'mongodb'
 )
 if not os.path.exists(DB_PATH):
    os.makedirs(DB_PATH)
 subprocess.Popen([
    'mongod',
    '--bind_ip=127.0.0.1',
    '--port=1234',
    '--nohttpinterface',
    '--dbpath={}'.format(DB_PATH),
 ]).wait()
--- a/setup.py
+++ b/setup.py
@ -19,7 +19,7 @@ setup(name='freqtrade',
      packages=['freqtrade'],
      scripts=['bin/freqtrade'],
      setup_requires=['pytest-runner'],
-      tests_require=['pytest', 'pytest-mock', 'pytest-cov'],
+      tests_require=['pytest', 'pytest-mock', 'pytest-cov', 'moto'],
      install_requires=[
          'ccxt',
          'SQLAlchemy',
@ -35,7 +35,7 @@ setup(name='freqtrade',
          'TA-Lib',
          'tabulate',
          'cachetools',
-          'coinmarketcap',
+          'coinmarketcap'
      ],
      include_package_data=True,
      zip_safe=False,
--- a/user_data/hyperopt_conf.py
+++ b/user_data/hyperopt_conf.py
@ -1,42 +0,0 @@
 """
 File that contains the configuration for Hyperopt
 """
 def hyperopt_optimize_conf() -> dict:
    """
    This function is used to define which parameters Hyperopt must used.
    The "pair_whitelist" is only used is your are using Hyperopt with MongoDB,
    without MongoDB, Hyperopt will use the pair your have set in your config file.
    :return:
    """
    return {
        'max_open_trades': 3,
        'stake_currency': 'BTC',
        'stake_amount': 0.01,
        "minimal_roi": {
            '40': 0.0,
            '30': 0.01,
            '20': 0.02,
            '0': 0.04,
        },
        'stoploss': -0.10,
        "bid_strategy": {
            "ask_last_balance": 0.0
        },
        "exchange": {
            "name": "bittrex",
            "pair_whitelist": [
                "ETH/BTC",
                "LTC/BTC",
                "ETC/BTC",
                "DASH/BTC",
                "ZEC/BTC",
                "XLM/BTC",
                "NXT/BTC",
                "POWR/BTC",
                "ADA/BTC",
                "XMR/BTC"
            ]
        }
    }
--- a/user_data/strategies/Long.py
+++ b/user_data/strategies/Long.py
@ -0,0 +1,94 @@
 # --- Do not remove these libs ---
 from freqtrade.strategy.interface import IStrategy
 from typing import Dict, List
 from hyperopt import hp
 from functools import reduce
 from pandas import DataFrame
 # --------------------------------
 import talib.abstract as ta
 import freqtrade.vendor.qtpylib.indicators as qtpylib
 import numpy # noqa
 class Long(IStrategy):
    """
    author@: Gert Wohlgemuth
    """
    # Minimal ROI designed for the strategy.
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {
        "60":  0.05,
        "30":  0.06,
        "20":  0.07,
        "0":  0.08
    }
    # Optimal stoploss designed for the strategy
    # This attribute will be overridden if the config file contains "stoploss"
    stoploss = -0.15
    # Optimal ticker interval for the strategy
    ticker_interval = 60
    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
        macd = ta.MACD(dataframe)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']
        dataframe['cci'] = ta.CCI(dataframe)
        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=50)
        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
        dataframe['bb_lowerband'] = bollinger['lower']
        dataframe['bb_middleband'] = bollinger['mid']
        dataframe['bb_upperband'] = bollinger['upper']
        # RSI
        dataframe['rsi'] = ta.RSI(dataframe)
        # Inverse Fisher transform on RSI, values [-1.0, 1.0] (https://goo.gl/2JGGoy)
        rsi = 0.1 * (dataframe['rsi'] - 50)
        dataframe['fisher_rsi'] = (numpy.exp(2 * rsi) - 1) / (numpy.exp(2 * rsi) + 1)
        # SAR Parabol
        dataframe['sar'] = ta.SAR(dataframe)
        return dataframe
    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
        """
        Based on TA indicators, populates the buy signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        dataframe.loc[
            (
                (dataframe['macd'] > dataframe['macdsignal']) &
                (dataframe['macd'] > 0) &
                (dataframe['cci'] <= 0.0)
            ),
            'buy'] = 1
        return dataframe
    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
        """
        Based on TA indicators, populates the sell signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        dataframe.loc[
            (
 #                (dataframe['tema'] < dataframe['close'])
                (dataframe['sar'] > dataframe['close']) &
                (dataframe['fisher_rsi'] > 0.3)
            ),
            'sell'] = 1
        return dataframe
--- a/user_data/strategies/Quickie.py
+++ b/user_data/strategies/Quickie.py
@ -0,0 +1,75 @@
 # --- Do not remove these libs ---
 from freqtrade.strategy.interface import IStrategy
 from typing import Dict, List
 from hyperopt import hp
 from functools import reduce
 from pandas import DataFrame
 # --------------------------------
 import talib.abstract as ta
 import freqtrade.vendor.qtpylib.indicators as qtpylib
 class Quickie(IStrategy):
    """
    author@: Gert Wohlgemuth
    idea:
        momentum based strategie. The main idea is that it closes trades very quickly, while avoiding excessive losses. Hence a rather moderate stop loss in this case
    """
    # Minimal ROI designed for the strategy.
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {
        "60": 0.005,
        "10": 0.01,
    }
    # Optimal stoploss designed for the strategy
    # This attribute will be overridden if the config file contains "stoploss"
    stoploss = -0.25
    # Optimal ticker interval for the strategy
    ticker_interval = 5
    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
        dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
        dataframe['adx'] = ta.ADX(dataframe)
        dataframe['sma_200'] = ta.SMA(dataframe, timeperiod=200)
        dataframe['sma_50'] = ta.SMA(dataframe, timeperiod=50)
        # required for graphing
        bollinger = qtpylib.bollinger_bands(dataframe['close'], window=20, stds=2)
        dataframe['bb_lowerband'] = bollinger['lower']
        dataframe['bb_middleband'] = bollinger['mid']
        dataframe['bb_upperband'] = bollinger['upper']
        return dataframe
    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
        dataframe.loc[
            (
                    (
                            (dataframe['adx'] > 30) &
                            (dataframe['tema'] < dataframe['bb_middleband']) &
                            (dataframe['tema'] > dataframe['tema'].shift(1)) &
                            (dataframe['sma_200'] > dataframe['close'])
                    )
            ),
            'buy'] = 1
        return dataframe
    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
        dataframe.loc[
            (
                (
                    (dataframe['adx'] > 70) &
                    (dataframe['tema'] > dataframe['bb_middleband']) &
                    (dataframe['tema'] < dataframe['tema'].shift(1))
                )
            ),
            'sell'] = 1
        return dataframe
--- a/user_data/strategies/Simple.py
+++ b/user_data/strategies/Simple.py
@ -0,0 +1,76 @@
 # --- Do not remove these libs ---
 from freqtrade.strategy.interface import IStrategy
 from typing import Dict, List
 from hyperopt import hp
 from functools import reduce
 from pandas import DataFrame
 # --------------------------------
 import talib.abstract as ta
 import freqtrade.vendor.qtpylib.indicators as qtpylib
 class Simple(IStrategy):
    """
    author@: Gert Wohlgemuth
    idea:
        this strategy is based on the book, 'The Simple Strategy' and can be found in detail here:
        https://www.amazon.com/Simple-Strategy-Powerful-Trading-Futures-ebook/dp/B00E66QPCG/ref=sr_1_1?ie=UTF8&qid=1525202675&sr=8-1&keywords=the+simple+strategy
    """
    # Minimal ROI designed for the strategy.
    # since this strategy is planned around 5 minutes, we assume any time we have a 5% profit we should call it a day
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {
        "0": 0.01
    }
    # Optimal stoploss designed for the strategy
    # This attribute will be overridden if the config file contains "stoploss"
    stoploss = -0.25
    # Optimal ticker interval for the strategy
    ticker_interval = 5
    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
        # MACD
        macd = ta.MACD(dataframe)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']
        # RSI
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=7)
        # required for graphing
        bollinger = qtpylib.bollinger_bands(dataframe['close'], window=12, stds=2)
        dataframe['bb_lowerband'] = bollinger['lower']
        dataframe['bb_upperband'] = bollinger['upper']
        dataframe['bb_middleband'] = bollinger['mid']
        return dataframe
    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
        dataframe.loc[
            (
                (
                        (dataframe['macd'] > 0)  # over 0
                        & (dataframe['macd'] > dataframe['macdsignal'])  # over signal
                        & (dataframe['bb_upperband'] > dataframe['bb_upperband'].shift(1))  # pointed up
                        & (dataframe['rsi'] > 70)  # optional filter, need to investigate
                )
            ),
            'buy'] = 1
        return dataframe
    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
        # different strategy used for sell points, due to be able to duplicate it to 100%
        dataframe.loc[
            (
                (dataframe['rsi'] > 80)
            ),
            'sell'] = 1
        return dataframe
--- a/user_data/strategies/ZLC.py
+++ b/user_data/strategies/ZLC.py
@ -0,0 +1,90 @@
 # --- Do not remove these libs ---
 from freqtrade.strategy.interface import IStrategy
 from typing import Dict, List
 from hyperopt import hp
 from functools import reduce
 from pandas import DataFrame
 # --------------------------------
 import talib.abstract as ta
 import freqtrade.vendor.qtpylib.indicators as qtpylib
 class ZLC(IStrategy):
    """
    author@: Gert Wohlgemuth
    """
    # Minimal ROI designed for the strategy.
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {
        "60": 0.01,
        "30": 0.03,
        "20": 0.04,
        "0": 0.01
    }
    # Optimal stoploss designed for the strategy
    # This attribute will be overridden if the config file contains "stoploss"
    stoploss = -0.3
    # Optimal ticker interval for the strategy
    ticker_interval = 5
    def populate_indicators(self, dataframe: DataFrame) -> DataFrame:
        dataframe['cci-slow'] = ta.CCI(dataframe, timeperiod=25)
        dataframe['cci-fast'] = ta.CCI(dataframe, timeperiod=50)
        dataframe['expo'] = ta.EMA(dataframe, timeperiod=35)
        # required for graphing
        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
        dataframe['bb_lowerband'] = bollinger['lower']
        dataframe['bb_middleband'] = bollinger['mid']
        dataframe['bb_upperband'] = bollinger['upper']
        macd = ta.MACD(dataframe)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']
        return dataframe
    def populate_buy_trend(self, dataframe: DataFrame) -> DataFrame:
        """
        Based on TA indicators, populates the buy signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        dataframe.loc[
            (
                #don't buy on peak tops
                        (dataframe['close'] < dataframe['bb_middleband'])
                        # this is the main concept of evaluating buys
                        & (dataframe['cci-fast'] > 0)
                        & (dataframe['cci-slow'] > 0)
                        & (dataframe['close'] > dataframe['expo'])
            )
            ,
            'buy'] = 1
        return dataframe
    def populate_sell_trend(self, dataframe: DataFrame) -> DataFrame:
        """
        Based on TA indicators, populates the sell signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        dataframe.loc[
            (dataframe['close'] >= dataframe['bb_upperband']) |
            (
                    (dataframe['cci-fast'] < 0)
                    & (dataframe['cci-slow'] < 0)
                    & (dataframe['close'] < dataframe['expo'])
            )
            ,
            'sell'] = 0
        return dataframe
--- a/user_data/strategies/test_strategy.py
+++ b/user_data/strategies/test_strategy.py
@ -1,4 +1,3 @@
 # --- Do not remove these libs ---
 from freqtrade.strategy.interface import IStrategy
 from pandas import DataFrame
@ -7,7 +6,7 @@ from pandas import DataFrame
 # Add your lib to import here
 import talib.abstract as ta
 import freqtrade.vendor.qtpylib.indicators as qtpylib
-import numpy # noqa
+import numpy  # noqa
 # This class is a sample. Feel free to customize it.
@ -218,9 +217,9 @@ class TestStrategy(IStrategy):
        """
        dataframe.loc[
            (
-                (dataframe['adx'] > 30) &
+                    (dataframe['adx'] > 30) &
-                (dataframe['tema'] <= dataframe['bb_middleband']) &
+                    (dataframe['tema'] <= dataframe['bb_middleband']) &
-                (dataframe['tema'] > dataframe['tema'].shift(1))
+                    (dataframe['tema'] > dataframe['tema'].shift(1))
            ),
            'buy'] = 1
@ -234,9 +233,9 @@ class TestStrategy(IStrategy):
        """
        dataframe.loc[
            (
-                (dataframe['adx'] > 70) &
+                    (dataframe['adx'] > 70) &
-                (dataframe['tema'] > dataframe['bb_middleband']) &
+                    (dataframe['tema'] > dataframe['bb_middleband']) &
-                (dataframe['tema'] < dataframe['tema'].shift(1))
+                    (dataframe['tema'] < dataframe['tema'].shift(1))
            ),
            'sell'] = 1
        return dataframe