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330 Commits

Author SHA1 Message Date
gcarq
b115963a70 Merge branch 'release/0.14.2' 2017-11-16 00:40:44 +01:00
gcarq
2e953a937d version bump 2017-11-16 00:40:36 +01:00
gcarq
4e05691cab check if balance list is empty (fixes #105) 2017-11-16 00:01:47 +01:00
gcarq
b5f58724a0 get_ticker_history: check if result is set (fixes #103) 2017-11-15 23:16:54 +01:00
gcarq
b83309b55d reduce calls_per_second to 1 2017-11-15 23:16:39 +01:00
gcarq
e8101a6da5 default BaseVolume to 0.0 if null 2017-11-14 17:48:19 +01:00
gcarq
dd9cb008fb refresh whitelist based on wallet health (fixes #60)
Refreshs the whitelist in each iteration based on the wallet health,
disabled wallets will be removed from the whitelist automatically.
2017-11-13 21:34:47 +01:00
gcarq
81f7172c4a sanitize get_ticker_history (fixes #100) 2017-11-13 19:54:09 +01:00
Michael Egger
bab59fbacd Merge pull request #99 from gcarq/more_triggers2
Expanding hyperopt
2017-11-13 12:11:15 +01:00
Janne Sinivirta
0f0b10b6cc adjust search spaces 2017-11-13 07:28:56 +02:00
Janne Sinivirta
8e68c5358e clean up prints during hyperopt 2017-11-12 09:44:31 +02:00
Janne Sinivirta
660f01b514 add hilbert transform leadsine trigger 2017-11-12 09:13:54 +02:00
Janne Sinivirta
13537e3ce4 add short ema guard to hyperopt 2017-11-12 08:45:32 +02:00
Janne Sinivirta
2963a90008 add stochastics trigger 2017-11-12 08:38:52 +02:00
Janne Sinivirta
15b20b83fa optimize hyperopt objective function 2017-11-12 08:30:58 +02:00
gcarq
1c3c316e45 reduce calls_per_second 2017-11-11 21:29:35 +01:00
gcarq
517879382b Add argument for dynamic-whitelist handling
If --dynamic-whitelist is passed the whitelist in the config file
is ignored. It gets automatically refreshed every 30 minutes and
currently selects the 20 topmost BaseVolume markets
2017-11-11 19:20:53 +01:00
gcarq
bcd3340a80 implement get_market_summaries 2017-11-11 19:20:16 +01:00
gcarq
12ae1e111e use get_candles from python-bittrex 2017-11-11 17:14:55 +01:00
gcarq
d3b3370f23 Add configurable throttle mechanism 2017-11-11 16:47:19 +01:00
gcarq
8f817a3634 use TTLCache for get_ticker_history 2017-11-11 15:29:31 +01:00
Janne Sinivirta
cf79b15651 use discrete values for filters 2017-11-11 11:50:10 +02:00
Janne Sinivirta
a4284351e3 fix green_candle 2017-11-11 11:22:12 +02:00
Janne Sinivirta
906caf329b remove two unused or poorly performing indicators 2017-11-11 11:22:12 +02:00
Janne Sinivirta
3db13fae13 add green_candle guard 2017-11-11 11:22:12 +02:00
Janne Sinivirta
274972f7af make faststoch trigger use crossed_above helper 2017-11-11 11:22:11 +02:00
Janne Sinivirta
83fd27e031 add sar reversal as trigger 2017-11-11 11:22:11 +02:00
gcarq
3126dcfcea drop sleep_time and use python-bittrex request delay 2017-11-10 23:39:49 +01:00
Michael Egger
72aec6c320 Merge pull request #96 from gcarq/feature/add-argparse
add argparse and implement basic arguments
2017-11-10 18:04:03 +01:00
gcarq
b709ccbf53 enhance logging messages 2017-11-10 17:56:03 +01:00
gcarq
7e99b13742 add missing commands to README 2017-11-10 17:27:19 +01:00
gcarq
8b464033ff add missing commands to README 2017-11-10 17:26:52 +01:00
gcarq
93c525a8fa Merge branch 'master' into develop 2017-11-10 17:18:21 +01:00
gcarq
54b15c1556 update README 2017-11-10 17:17:51 +01:00
gcarq
029f32af63 Merge tag '0.14.1' into develop
0.14.1
2017-11-09 23:53:14 +01:00
gcarq
de13df6ede Merge branch 'release/0.14.1' 2017-11-09 23:53:10 +01:00
gcarq
0de211674d version bump 2017-11-09 23:52:34 +01:00
gcarq
f7a27c156c add /version command handler 2017-11-09 23:51:32 +01:00
gcarq
98f11fc7bb fix sqlite threading issue 2017-11-09 23:45:22 +01:00
gcarq
013e13e546 use tabulate for /count 2017-11-09 23:45:03 +01:00
gcarq
6ff26c561a move plot_dataframe to scripts/ folder 2017-11-09 22:29:23 +01:00
gcarq
c81358c291 remove MagicBot 2017-11-09 22:11:02 +01:00
gcarq
ed34d9f22f add tests for /forcesell all 2017-11-09 22:08:28 +01:00
gcarq
ee05561ef3 refactor forcesellall to /forcesell all 2017-11-09 22:07:51 +01:00
Eoin
69ae99406a add telegram handler for forcesellall 2017-11-09 21:52:08 +01:00
gcarq
0cfbb56b6c enhance and test pair validation 2017-11-09 21:47:47 +01:00
gcarq
8960373f1c Merge tag '0.14.0' into develop
0.14.0
2017-11-09 20:56:12 +01:00
gcarq
349a91bd92 Merge branch 'release/0.14.0' 2017-11-09 20:56:07 +01:00
gcarq
991b43b7e5 version bump 2017-11-09 20:55:45 +01:00
gcarq
a0fa6abcdc use in-memory db for dry_run 2017-11-09 20:26:52 +01:00
gcarq
86501b43c0 adjust message formatting 2017-11-09 20:25:17 +01:00
gcarq
80592970e9 add more tests 2017-11-09 20:02:41 +01:00
gcarq
567ed4ecda remove version pinning from setup.py 2017-11-09 00:33:22 +01:00
gcarq
fafbb0abfe update python-bittrex to 0.2.0 2017-11-09 00:31:53 +01:00
gcarq
0f1a36b8e9 force to python3 2017-11-08 23:39:29 +01:00
gcarq
31c03cdce1 fix linter issue 2017-11-08 22:44:32 +01:00
gcarq
e01c85bb3a add argparse and implement basic arguments 2017-11-08 22:43:47 +01:00
gcarq
a1b91ad1ea remove unneeded wrapper function 2017-11-08 21:17:51 +01:00
gcarq
6ce6018bb7 add more tests 2017-11-07 22:27:44 +01:00
gcarq
18eec0f4d4 catch BaseException in command_handler 2017-11-07 22:27:16 +01:00
gcarq
32327c45c2 set close_date on sell_order update 2017-11-07 22:26:44 +01:00
gcarq
ba485fe2b2 return state changes 2017-11-07 22:26:08 +01:00
gcarq
f8084b117e apply pylint recommendations 2017-11-07 20:13:36 +01:00
gcarq
abdddd5193 define common fixtures 2017-11-07 20:12:56 +01:00
gcarq
8eeb02e592 make ticker interval configurable 2017-11-07 18:59:47 +01:00
gcarq
8555271102 remove unneeded header from get_ticker_history 2017-11-07 18:49:16 +01:00
gcarq
d921bae75e set executable bit 2017-11-07 18:42:40 +01:00
gcarq
a1388ef296 add tick_interval to get_ticker_history as an optional parameter 2017-11-07 18:41:48 +01:00
gcarq
ddc7c94a1d Merge branch 'develop' of https://github.com/gcarq/freqtrade into develop 2017-11-07 18:40:56 +01:00
Michael Egger
e36444df27 Merge pull request #95 from gcarq/improve_backtests
Share pytest fixtures. Cache testfile loading.
2017-11-07 18:40:00 +01:00
Janne Sinivirta
0395c92260 move testdata file loading to pytest fixture 2017-11-07 19:24:51 +02:00
gcarq
f03395b90d force python3 via shebang 2017-11-07 17:54:44 +01:00
gcarq
20d5628786 catch broader RequestException instead ConnectionError 2017-11-07 17:45:13 +01:00
gcarq
57e089efd3 fix NoneType issue in status command handle 2017-11-07 17:39:57 +01:00
Janne Sinivirta
fbbde9de25 put shared fixtures to conftest.py 2017-11-07 17:29:00 +02:00
Samuel Husso
3d42b9fd75 Merge pull request #94 from gcarq/autopep
autoformat with autopep8
2017-11-06 19:41:57 +02:00
Janne Sinivirta
adfae9e75c autoformat with autopep8 2017-11-06 19:17:23 +02:00
gcarq
117dfbb563 fix wording 2017-11-06 18:15:33 +01:00
Michael Egger
e66dc8b027 Merge pull request #93 from gcarq/feature/interpreter-version-check
add interpreter version check
2017-11-06 17:23:53 +01:00
Michael Egger
ae0b49f532 Merge pull request #92 from gcarq/feature/rework-dry_run-mode
rework dry_run
2017-11-06 16:54:55 +01:00
gcarq
a37ea13fd1 catch RuntimeError earlier
This makes it possible to to restart the bot, if there are temporary
server issues.
2017-11-06 01:03:37 +01:00
gcarq
cc29126d61 make download_backtest_data.py platform independent 2017-11-06 00:16:24 +01:00
gcarq
810f2f9243 drop minimum_date from get_ticker_history 2017-11-06 00:06:59 +01:00
gcarq
60e651cb4c only return data['result'] from get_ticker_history 2017-11-05 23:47:59 +01:00
gcarq
472ce8566d enhance bittrex exception messages 2017-11-05 22:47:55 +01:00
gcarq
27ac15f298 add tabulate to setup.py 2017-11-05 20:54:41 +01:00
gcarq
d12dba16db simplify status command 2017-11-05 18:35:32 +01:00
Michael Egger
0f1d114c03 Merge pull request #86 from flightcom/feature/advanced-status-command
telegram command: advanced status
2017-11-05 18:13:25 +01:00
gcarq
3e7700e9ac add interpreter version check 2017-11-05 17:44:58 +01:00
Sébastien Moreau
60615c232c Merge branch 'develop' into feature/advanced-status-command 2017-11-05 10:34:17 -05:00
Sébastien Moreau
3884cfb809 Merge branch 'develop' into feature/advanced-status-command 2017-11-05 10:32:53 -05:00
Sebastien Moreau
caa6e22e53 Adds unit tests 2017-11-05 10:26:03 -05:00
gcarq
19f6ff330c adapt float precision asserts 2017-11-05 16:21:13 +01:00
gcarq
8fdd127f72 fix float precision rendering 2017-11-05 16:13:55 +01:00
gcarq
0a5eba64e2 do not remove order from dry_run order list 2017-11-05 16:13:20 +01:00
gcarq
b82c4444b2 apply correct typehint 2017-11-05 16:12:58 +01:00
gcarq
95a17b8f98 dry_run: remove mock value notice 2017-11-05 15:35:15 +01:00
gcarq
325f72fd91 dry_run: keep list of open orders 2017-11-05 15:21:16 +01:00
Janne Sinivirta
a237225683 Merge pull request #91 from gcarq/multiple_builds_travis
Parallel build in Travis
2017-11-05 15:21:20 +02:00
Janne Sinivirta
29b173f4e7 only run four evals of hyperopt, just to check it works 2017-11-05 09:28:42 +02:00
Janne Sinivirta
50a979161c run parallel test envs 2017-11-05 09:27:49 +02:00
gcarq
264d71e29e fix some pylint warnings 2017-11-04 18:55:41 +01:00
gcarq
a873688a44 backtesting: init Trade with Bittrex fee 2017-11-04 18:43:23 +01:00
Michael Egger
7cc8533b8e Merge pull request #89 from gcarq/feature/take-fees-into-account
take fees into account & sell amount equal to amount purchased
2017-11-03 21:47:46 +01:00
gcarq
04342acff1 fix typo 2017-11-03 21:37:20 +01:00
gcarq
c37df0e70d inform about mocked values with dry_run 2017-11-03 21:36:55 +01:00
gcarq
460dfa1031 fix percentage formating in execute_sell 2017-11-02 19:00:25 +01:00
gcarq
08a1d3ca1d pylint changes 2017-11-02 19:00:25 +01:00
gcarq
1daeed4a52 fix assert 2017-11-02 19:00:25 +01:00
gcarq
99724e2458 use Decimal for profit calculation 2017-11-02 19:00:25 +01:00
gcarq
cd18629433 add fee to sqlalchemy model and respecting it in calc_profit 2017-11-02 19:00:25 +01:00
gcarq
41510fdb32 add dry_run for get_balance 2017-11-02 19:00:25 +01:00
gcarq
9cb249610a adapt dry_run return values 2017-11-02 19:00:25 +01:00
gcarq
543857ddb2 set initial open_rate and amount in create_trade
This is mostly needed by dry_run
2017-11-02 19:00:25 +01:00
gcarq
1e5b0e8726 adapt tests 2017-11-02 19:00:25 +01:00
gcarq
0d0d822904 bump dburl to tradesv3 2017-11-02 19:00:25 +01:00
gcarq
9ff4a7b205 refactor _process to update trade state 2017-11-02 19:00:25 +01:00
gcarq
0e96197a94 don't spend the whole coin balance when selling 2017-11-02 19:00:25 +01:00
gcarq
9b9d0250f7 replace get_open_oders() with get_order() and add property for fee 2017-11-02 18:58:55 +01:00
gcarq
4a35676794 rename and exchange instance and mark it as private 2017-11-02 18:58:55 +01:00
gcarq
465c91b9a9 telegram.cleanup: fix NoneType issue when telegram is deactivated 2017-11-02 18:56:57 +01:00
Sebastien Moreau
60249af04c Removes long format + pylint fixes 2017-11-02 13:25:19 -04:00
gcarq
c3653dc417 Merge branch 'master' of https://github.com/gcarq/freqtrade into develop 2017-11-01 18:37:27 +01:00
gcarq
3d61095ba4 modify header font size 2017-11-01 18:36:22 +01:00
gcarq
7a0be94cde adapt README 2017-11-01 18:32:27 +01:00
gcarq
fad6427078 coverage: omit vendor folder 2017-11-01 01:43:15 +01:00
gcarq
4dfde7f9a2 Merge tag '0.13.0' into develop
0.13.0
2017-11-01 01:15:35 +01:00
gcarq
e2eceaa904 Merge branch 'release/0.13.0' 2017-11-01 01:15:31 +01:00
gcarq
f34af0ad67 version bump 2017-11-01 01:15:06 +01:00
gcarq
e07904d436 PEP8 linting 2017-10-31 00:36:35 +01:00
gcarq
26468bef83 balance: filter currencies with 0.0 balances 2017-10-31 00:29:22 +01:00
Michael Egger
ea1b1e11ea Merge pull request #88 from gcarq/reduce_memory_use
Reduce memory use in backtesting
2017-10-31 00:28:38 +01:00
Janne Sinivirta
e68e6c0a1a reuse mock in hyperopt also 2017-10-30 22:31:28 +02:00
Janne Sinivirta
7190226c84 reuse same mock for get_ticker_history, just change return_value 2017-10-30 22:06:09 +02:00
gcarq
6f2915e25e move qtpylib to vendor folder
This is necessary to distribute qtpylib with
freqtrade when you install it globally.
2017-10-30 20:41:36 +01:00
gcarq
6f7ac0720b add qtpylib to manifest 2017-10-30 20:24:58 +01:00
gcarq
b76554a487 add __init__ file for qtpylib 2017-10-30 20:23:19 +01:00
Janne Sinivirta
8da55c3742 move patching of arrow.utcnow to remove 500 unnecessary mock objects 2017-10-30 19:56:53 +02:00
Michael Egger
05111edd04 Merge pull request #87 from gcarq/more_triggers
More triggers and guards to hyperopt
2017-10-30 14:43:18 +01:00
Sebastien Moreau
361bdd20d3 Updates README 2017-10-29 20:55:14 -04:00
Sebastien Moreau
8bdace68f6 Adds options for /status command 2017-10-29 20:51:38 -04:00
Sebastien Moreau
0e1eb20781 Adds /count command
Adds /count command

Adds /count command
2017-10-29 18:47:42 -04:00
Michael Egger
4c2dea83c5 Merge pull request #84 from gcarq/telegram/show-balance
Telegram command: /show balance
2017-10-29 22:05:10 +01:00
Janne Sinivirta
d066817d0b removed below_sma and over_sma to wait for better implementation 2017-10-29 21:33:57 +02:00
Janne Sinivirta
a632121368 add macd cross signal trigger to hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
473d09b5cd add ema50 and ema100. add long uptrend ema guard to hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
893738d6f0 add MACD to analyze 2017-10-29 21:33:57 +02:00
Janne Sinivirta
22cfef7d36 add ema5 cross ema10 trigger to hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
e1bbe1d9a9 adjust indicator ranges in hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
ec981b415a add RSI to hyperopt 2017-10-29 21:33:57 +02:00
Janne Sinivirta
57a17697a0 add RSI, MOM, EMA5 and EMA10 to analyze 2017-10-29 21:33:57 +02:00
Samuel Husso
f4fe09ffbf added get_balances as a abstract method to the interface baseclass 2017-10-29 17:57:57 +02:00
Michael Egger
871b5e17ee Merge pull request #85 from gcarq/datetime_fixes
Performance improvements for backtesting
2017-10-29 15:56:20 +01:00
Janne Sinivirta
9b00fc3474 use .ix instead of .loc for small perf boost 2017-10-29 16:28:55 +02:00
Janne Sinivirta
3b1dc36d8a switch to using itertuples instead of iterrows as it's a lot faster 2017-10-29 16:28:55 +02:00
Janne Sinivirta
4edf8f2079 copy only needed columns before iterating over them 2017-10-29 16:28:55 +02:00
Janne Sinivirta
54987fd9ca do date parsing while loading json, not later 2017-10-29 16:28:55 +02:00
Janne Sinivirta
da9c3e7d7d remove leftover dates from removing date filtering 2017-10-29 16:28:55 +02:00
Michael Egger
a948142ef5 Merge pull request #83 from gcarq/better-hyperopt-objective
Better hyperopt objective
2017-10-29 14:13:44 +01:00
Samuel Husso
4f6c3f94e0 added tests to /balance, minor cleanup 2017-10-29 10:10:00 +02:00
Janne Sinivirta
25d6d6bbe5 remove unused imports from test_hyperopt 2017-10-28 15:32:29 +03:00
Janne Sinivirta
649781d823 store result strings, display best result in summary. switch to a lot better objective algo 2017-10-28 15:26:22 +03:00
Janne Sinivirta
08ca7a8166 change print to format so result can be used in hyperopt Trials 2017-10-28 15:26:22 +03:00
Samuel Husso
dd78c62c3d added new command to return balance across all currencies 2017-10-28 08:59:43 +03:00
Samuel Husso
29de1645fe Merge pull request #82 from gcarq/feature/handle-process-signals
handle SIGINT, SIGTERM and SIGABRT process signals
2017-10-28 08:49:42 +03:00
gcarq
4139b0b0c7 add signal handler for SIGINT, SIGTERM and SIGABRT 2017-10-27 15:52:14 +02:00
Samuel Husso
0c33e917d5 Merge pull request #79 from gcarq/qtpylib
Include new indicators from qtpylib
2017-10-27 12:11:04 +03:00
Janne Sinivirta
e401a016f5 change analyze tests to use full json dump from bittrex 2017-10-26 16:50:31 +03:00
Janne Sinivirta
e0fde8665c Merge pull request #80 from gcarq/fix-testdate-dl-path
download testdata to correct folder when running from project root
2017-10-26 10:37:38 +03:00
Samuel Husso
752520c823 When running from project root download the files to the testdata folder instead of cwd 2017-10-26 10:24:22 +03:00
Janne Sinivirta
6ba2492360 add Awesome Oscillator and try it in hyperopt 2017-10-25 18:37:20 +03:00
Janne Sinivirta
d5d798f6fa pull in new indicators from QTPYLib 2017-10-25 18:37:20 +03:00
Janne Sinivirta
9c9cf76a0d Merge pull request #78 from gcarq/refactor-backtest
Refactor backtest functionality
2017-10-25 18:19:44 +03:00
Samuel Husso
041e201713 remove duplicated backtesting from hyperopt 2017-10-25 08:17:17 +03:00
gcarq
e09505b22d Merge tag '0.12.0' into develop
0.12.0
2017-10-24 18:14:41 +02:00
gcarq
6b15cb9b10 Merge branch 'release/0.12.0' 2017-10-24 18:14:37 +02:00
gcarq
ff4fcdc760 version bump 2017-10-24 18:14:31 +02:00
Samuel Husso
f43ba44b15 refactor backtesting to its own method as we use it also in hyperopt 2017-10-24 07:58:42 +03:00
Michael Egger
79c3e0583d Merge pull request #76 from gcarq/hyperopt
Use hyperopt to find optimal parameters for buy strategy
2017-10-23 09:40:13 +02:00
Janne Sinivirta
f6ef8383bb remove filtering from analyze that is super slow and not really needed 2017-10-22 21:50:07 +03:00
Janne Sinivirta
6f5307fda7 use more aggressive stop loss for hyperopt 2017-10-22 17:15:57 +03:00
Janne Sinivirta
37004e331a remove unused import and commented out code 2017-10-22 17:14:55 +03:00
Janne Sinivirta
57acf85b42 try a different objective function 2017-10-22 17:11:01 +03:00
Michael Egger
96790d50e5 Merge pull request #77 from gcarq/help-command
Help command to Telegram bot
2017-10-21 13:51:08 +02:00
Janne Sinivirta
d32ff3410c add help command to telegram bot 2017-10-21 11:08:08 +03:00
Janne Sinivirta
35838f5e64 upgrade to latest telegram lib 2017-10-21 11:07:29 +03:00
Janne Sinivirta
913488910c bump minimum evaluations to 40 rounds 2017-10-21 10:29:05 +03:00
Janne Sinivirta
17b984a7cd adjust objective function to emphasize trade lenghts more 2017-10-21 10:28:43 +03:00
Janne Sinivirta
f79b44eefe adjust ROI map for shorter trades 2017-10-21 10:28:02 +03:00
Janne Sinivirta
146c254c0f start adding other triggers than just the lower BBands 2017-10-21 10:26:38 +03:00
Janne Sinivirta
ce2966dd7f add uptrend_sma to hyperopt 2017-10-20 18:29:38 +03:00
Janne Sinivirta
0fbca8b8ef add CCI to hyperopt 2017-10-20 13:14:28 +03:00
Janne Sinivirta
3f7a583de6 add SAR to hyperopt. add over/under sma options to hyperopt 2017-10-20 12:56:44 +03:00
Janne Sinivirta
1196983d5f change objective to emphasize shorter trades and include average profit 2017-10-20 10:39:36 +03:00
Janne Sinivirta
bbb2c7cf62 more parametrizing. adjust ranges for previous parameters 2017-10-20 10:39:04 +03:00
Janne Sinivirta
ff100bdac4 the optimizer expects values in the order of smaller is better 2017-10-19 18:29:57 +03:00
Janne Sinivirta
4feb038d0a add hyperopt dependencies 2017-10-19 17:46:41 +03:00
Janne Sinivirta
1792e0fb9b use hyperopt to find optimal parameter values for indicators 2017-10-19 17:12:49 +03:00
Janne Sinivirta
d4f8b3ebbc remove setup.cfg as it's not used but it messes with running a single test 2017-10-19 17:12:08 +03:00
Michael Egger
aeef9bac33 Merge pull request #70 from dertione/patch-2
Download automatically altcoin datas
2017-10-17 13:36:33 +02:00
Michael Egger
eff361a104 Merge pull request #73 from gcarq/small_tweaks_to_strategy
Small tweaks to strategy
2017-10-15 18:08:18 +02:00
dertione
389f9b45bb update pylint 10/10 2017-10-15 17:24:49 +02:00
Janne Sinivirta
c9741cb291 adjust roi settings for faster trades 2017-10-15 17:32:07 +03:00
Janne Sinivirta
bf6f563df2 small tweaks to buy strategy and it's visualization 2017-10-15 17:32:07 +03:00
Michael Egger
58f34d4f4b Merge pull request #71 from steerio/develop
More efficient and flexible Docker builds
2017-10-15 15:46:39 +02:00
Janne Sinivirta
2c4d0144ba Add note about binding sqlite with dry_run enabled 2017-10-15 14:40:02 +03:00
dertione
afd1a0bf9b update for pylint 2017-10-14 14:40:26 +02:00
dertione
37f6c213f6 fork test 2017-10-13 15:50:50 +02:00
Roland Venesz
76736902c6 Merge branch 'master' into develop 2017-10-13 15:48:25 +02:00
Roland Venesz
d266171ed8 Docker improvements (faster and more secure builds) 2017-10-13 15:47:13 +02:00
Michael Egger
e7df373544 Merge pull request #67 from gcarq/upgrade-deps
Upgrade dependencies
2017-10-12 09:49:45 +02:00
Michael Egger
aa4b64d0bb Merge pull request #65 from xsmile/patch-4
set exchange in analyze.__main__ to fix plotting
2017-10-12 09:42:20 +02:00
Michael Egger
4559ddd74f Merge pull request #64 from xsmile/patch-1
Bittrex provider
2017-10-12 09:37:15 +02:00
xsmile
eecc45f8ba set exchange in analyze.__main__ to fix plotting
requires #64
2017-10-11 20:04:31 +02:00
xsmile
d76476040a Bittrex provider
remove redundant 'name' property and pair validation call
2017-10-11 19:51:37 +02:00
Janne Sinivirta
0c8c149b86 Fix the command for running backtesting in README.md 2017-10-11 13:09:57 +03:00
Janne Sinivirta
60a7f8614c upgrade dependencies 2017-10-10 19:04:05 +03:00
gcarq
c31b67bf7a Merge tag '0.11.0' into develop
0.11.0
2017-10-10 17:55:10 +02:00
gcarq
604a888791 Merge branch 'release/0.11.0' 2017-10-10 17:55:05 +02:00
gcarq
bfac1936d9 version bump 2017-10-10 17:54:42 +02:00
Janne Sinivirta
b1de0de5a5 Merge pull request #61 from xsmile/patch-2
add exchange package to manifest
2017-10-09 10:30:41 +03:00
xsmile
75ea2c4e1a add exchange package to manifest 2017-10-08 23:01:36 +02:00
Michael Egger
5e0f143a38 Merge pull request #58 from xsmile/exchange-interface
Exchange refactoring
2017-10-08 15:56:50 +02:00
gcarq
2d983db2e0 Merge branch 'master' into develop 2017-10-08 15:15:44 +02:00
gcarq
d9b01eee15 adapt install section 2017-10-08 15:15:11 +02:00
xsmile
2e368ef7aa docstring fix 2017-10-07 18:10:45 +02:00
xsmile
34c774c067 move exchange module content to exchange package and the interface to a new module 2017-10-07 18:07:29 +02:00
xsmile
ac32850034 simplify exchange initialization 2017-10-07 17:38:33 +02:00
xsmile
95e5c2e6c1 remove 'enabled' property in exchange config 2017-10-07 17:36:48 +02:00
Janne Sinivirta
aef42336e6 fixes to README.md
- Fix the command for running unit tests
- Add command to run backtest unit tests
2017-10-06 14:12:23 +03:00
Janne Sinivirta
f78427d236 Merge pull request #57 from shusso/fix-backtest-path
fix incorrect backtest testdata path
2017-10-06 14:04:01 +03:00
xsmile
b9eb266236 Exchange refactoring 2017-10-06 12:22:04 +02:00
Samuel Husso
e0896fdd7b fix incorrect backtest testdata path 2017-10-06 10:54:04 +03:00
Michael Egger
11f97ccf87 Merge pull request #54 from gcarq/fix-coverage
Fix coverage
2017-10-02 19:29:33 +02:00
Janne Sinivirta
3506e3ceec try directly invoking pytest for fixing coveralls issue 2017-10-02 20:17:14 +03:00
Janne Sinivirta
27b2624a67 let pytest do coverage 2017-10-02 19:48:47 +03:00
Janne Sinivirta
8500032bff add coverage config file to omit test files from coverage report 2017-10-02 19:27:18 +03:00
Janne Sinivirta
b2522b8dbc add pytest-cov dependency 2017-10-02 19:17:54 +03:00
Janne Sinivirta
0f3ceebcd4 Merge pull request #53 from gcarq/feature/patch-missing-calls
patch missing calls
2017-10-02 10:38:01 +03:00
gcarq
f44ab2f44b patch missing http calls 2017-10-01 23:28:09 +02:00
Janne Sinivirta
3fe5302db3 Merge pull request #52 from gcarq/convert-to-pytest
Switch to using Pytest
2017-10-01 17:28:23 +03:00
Janne Sinivirta
ea62c49c3a fix passing parameters to pytest 2017-10-01 17:19:14 +03:00
Janne Sinivirta
02673b94dd use explicit package name for pytest running 2017-10-01 17:04:38 +03:00
Janne Sinivirta
17e8bbacc3 add pytest-mock to setup.py 2017-10-01 16:17:27 +03:00
Janne Sinivirta
463123adc5 Merge branch 'develop' into convert-to-pytest 2017-10-01 16:14:50 +03:00
Janne Sinivirta
5537f0bf5b simplify unnecessary == True and == False assertions 2017-10-01 15:45:31 +03:00
Janne Sinivirta
5551c9ec3b add pragmas to disable pylint warnings for missing docstrings in test files 2017-10-01 15:40:40 +03:00
Janne Sinivirta
ff145b6306 use mocker for mocking to get rid of deep nesting 2017-10-01 15:40:12 +03:00
Janne Sinivirta
add6c875d6 add pytest-mock to requirements.txt 2017-10-01 15:24:27 +03:00
gcarq
378b5a3b14 fix indentation 2017-10-01 14:07:09 +02:00
gcarq
e14cc2e4f6 add setup.cfg to force pytest 2017-10-01 14:06:18 +02:00
Janne Sinivirta
616d5b61cc remove numbers from test method names 2017-10-01 11:11:20 +03:00
Janne Sinivirta
9cca42e371 add pytest to requirements.txt 2017-10-01 11:06:40 +03:00
Janne Sinivirta
06ad311aa3 remove Test classes and use pytest fixtures 2017-10-01 11:02:47 +03:00
gcarq
e42edd9de7 add required folders to MANIFEST 2017-09-30 21:01:23 +02:00
gcarq
3456ead839 add numpy as required dep 2017-09-30 21:00:53 +02:00
gcarq
a4a1f7961a set executable bit 2017-09-30 21:00:42 +02:00
gcarq
8057333501 adapt Dockerfile for new project structure 2017-09-30 21:00:14 +02:00
gcarq
1eee0c91bf adapt README 2017-09-30 20:59:54 +02:00
Janne Sinivirta
53b4c3722e convert asserts to pytest style 2017-09-30 20:38:19 +03:00
gcarq
3f6f502e66 add code coverage badge 2017-09-30 19:05:37 +02:00
Janne Sinivirta
d73c656514 Merge pull request #50 from gcarq/feature/fix-whitelist-vanishing
fix whitelist vanishing
2017-09-30 20:00:38 +03:00
gcarq
f409bdbba8 add coveralls.io to measure code quality 2017-09-30 18:55:48 +02:00
gcarq
4b42e1af4b use deepcopy 2017-09-30 18:23:11 +02:00
gcarq
898ab5a370 implement test to reproduce it 2017-09-30 18:22:05 +02:00
Janne Sinivirta
6389778d49 Merge pull request #47 from gcarq/feature/project-structure
Refactor project structure (closes #34)
2017-09-30 19:19:00 +03:00
gcarq
b85b913657 revert coveralls 2017-09-30 17:13:08 +02:00
gcarq
bbef0edcd1 add coveralls.io to measure code quality 2017-09-30 17:06:15 +02:00
gcarq
8d3a6279b2 use pytest 2017-09-30 15:58:31 +02:00
gcarq
df4da75535 add pypi classifiers 2017-09-29 20:15:54 +02:00
gcarq
04bba626a8 define install_requires for package distribution 2017-09-29 20:07:50 +02:00
gcarq
9c6c21637d fix testsuite 2017-09-29 19:28:32 +02:00
gcarq
09b27d2094 add manifest file 2017-09-29 19:28:32 +02:00
gcarq
998a887736 add command line script 2017-09-29 19:28:32 +02:00
gcarq
00499fa0d7 add setup.py 2017-09-29 19:28:32 +02:00
gcarq
0c517ee3b6 move project into freqtrade/ 2017-09-29 19:28:32 +02:00
gcarq
b225b0cb90 remove python nightly interpreter 2017-09-29 19:07:25 +02:00
Janne Sinivirta
d045116297 upgraded to latest telegram library (8.0) 2017-09-29 18:59:05 +03:00
Janne Sinivirta
8b859ad358 Merge pull request #44 from gcarq/another-better-strategy
Better buy strategy and sell criteria
2017-09-29 13:32:00 +03:00
Janne Sinivirta
0085db825d Merge branch 'develop' into another-better-strategy 2017-09-29 13:13:44 +03:00
Janne Sinivirta
1f1e64560a adjust roi and stop loss in config.json.example 2017-09-29 09:58:00 +03:00
Janne Sinivirta
c9226a329c adjust roi and stop loss for backtesting 2017-09-29 09:56:52 +03:00
Janne Sinivirta
44cdf3e0c2 improved buy signal strategy 2017-09-29 09:55:11 +03:00
Janne Sinivirta
b97f0f0705 use btc-eth as default pair for analyze graph 2017-09-29 09:49:19 +03:00
Janne Sinivirta
b2f4778352 show last 24hours in analyze graph 2017-09-29 09:48:59 +03:00
Janne Sinivirta
272abed807 show two decimals in average profit in backtesting results 2017-09-29 09:46:45 +03:00
Michael Egger
0437546e4b Merge pull request #41 from xsmile/optional-telegram
Telegram: Fix being optional
2017-09-29 00:37:46 +02:00
xsmile
2df2041d53 Telegram: Fix being optional 2017-09-29 00:15:38 +02:00
Michael Egger
3b9d354a62 Merge pull request #30 from freshfunkee/feature/handle-empty-dataframe
dataframe empty check
2017-09-28 21:49:06 +02:00
Eoin
a45073997d review comments: change log to warning 2017-09-28 20:07:33 +01:00
gcarq
d102a8f8a1 Merge tag '0.10.0' into develop
0.10.0
2017-09-28 19:17:08 +02:00
gcarq
c20030783b Merge branch 'release/0.10.0' 2017-09-28 19:17:01 +02:00
gcarq
ff5a6633c6 version bump 2017-09-28 19:14:18 +02:00
gcarq
af6b07efb1 Merge branch 'master' of https://github.com/gcarq/freqtrade into develop 2017-09-28 19:03:53 +02:00
gcarq
d416aba95e add setup tutorial (closes #40) 2017-09-28 19:01:02 +02:00
gcarq
775414d494 add slack invite link 2017-09-28 19:00:42 +02:00
Michael Egger
f493df7a82 Merge pull request #33 from gcarq/disable-debuglog-backtest
Disable debug level logging when running backtesting
2017-09-28 16:52:55 +02:00
Janne Sinivirta
a2f7709cfd disable debug level logging when running backtesting 2017-09-28 17:00:14 +03:00
Janne Sinivirta
9a64522f45 Merge pull request #25 from alangvand/whitelist-on-sale
add whitelist to execute_sell and append sold pair to it
2017-09-28 11:02:23 +03:00
Janne Sinivirta
e7620b46ae Merge pull request #29 from gcarq/backtesting
Backtesting
2017-09-28 10:52:42 +03:00
Eoin
0e5edd08e5 add dataframe empty check 2017-09-27 23:43:32 +01:00
Janne Sinivirta
41849c4a1e add three more currency pairs to back testing. redownloaded all test data 2017-09-25 22:01:54 +03:00
Janne Sinivirta
c9dcc1e57c disable the backtesting by default 2017-09-25 21:39:43 +03:00
Janne Sinivirta
9f7a72a990 shorten report text 2017-09-25 21:39:28 +03:00
Janne Sinivirta
5f98649b7d backtesting over 7 different coins and a month of 5min ticker data 2017-09-25 21:06:15 +03:00
Janne Sinivirta
4198220b68 extract sell criteria to it's own method for testing 2017-09-25 21:05:37 +03:00
Janne Sinivirta
877dd6d3fa simplify sell conditions 2017-09-25 15:17:29 +03:00
Janne Sinivirta
f3ccca1c66 try running analyze_ticker with mock data 2017-09-24 17:23:29 +03:00
Janne Sinivirta
9b63f02e1c add set of test data 2017-09-24 17:20:25 +03:00
Janne Sinivirta
72432c1285 Fix link markup for issues 2017-09-21 09:08:13 -07:00
Michael Egger
be86a40207 Merge pull request #28 from gcarq/contribute-readme
Updated README.md
2017-09-21 15:30:43 +02:00
Janne Sinivirta
73ad3b4c85 Updated README.md 2017-09-20 08:06:10 -07:00
Janne Sinivirta
2bd51d8be3 Merge pull request #26 from gcarq/bid-balance
Set balance for bid price between ask and last
2017-09-20 07:58:20 -07:00
Janne Sinivirta
358a1eb73f add type hint for ticker 2017-09-20 07:34:47 -07:00
Janne Sinivirta
e5a742cf2e add a little more explanation for ask_last_balance to README 2017-09-18 05:09:45 -07:00
Janne Sinivirta
4d651e0082 add ask_last_balance to README.md 2017-09-18 05:08:05 -07:00
Janne Sinivirta
465dc47b23 balance bid price between ask and last 2017-09-17 23:21:46 +03:00
Janne Sinivirta
989682457e add a field to config for setting balance between trying to buy with ask price and last price 2017-09-17 22:37:46 +03:00
André Øien Langvand
e9e76da054 add whitelist to execute_sell and append sold pair to it 2017-09-17 18:42:42 +02:00
gcarq
f84c58c3eb add slack token 2017-09-12 19:20:49 +02:00
gcarq
d4fb7bd776 Merge branch 'develop' of https://github.com/gcarq/freqtrade into develop 2017-09-12 17:50:08 +02:00
Michael Egger
8ed8e1e103 Merge pull request #20 from vertti/newer-strategy
New buy strategy
2017-09-12 16:01:18 +02:00
Janne Sinivirta
1280670ea3 use five minute ticker for a much more stable indicators 2017-09-12 10:53:42 +02:00
Janne Sinivirta
cedc207097 remove unused import 2017-09-12 10:49:30 +02:00
Janne Sinivirta
a5b3428552 rename variable to get rid of bunch of pylint shadowing complaints 2017-09-12 10:49:10 +02:00
Janne Sinivirta
2221a0fbbc implement new buying strategy 2017-09-12 10:47:23 +02:00
gcarq
ffa32df40f remove poloniex from CONF_SCHEMA 2017-09-11 14:06:52 +02:00
gcarq
f91cd8ea96 drop support for poloniex 2017-09-11 13:59:38 +02:00
gcarq
48beb279c0 rename btc_amount to stake_amount 2017-09-11 13:59:11 +02:00
gcarq
dc1cfe7a7a Merge tag '0.9.0' into develop
0.9.0
2017-09-10 22:57:20 +02:00
56 changed files with 4008 additions and 1576 deletions

5
.coveragerc Normal file
View File

@@ -0,0 +1,5 @@
[run]
omit =
scripts/*
freqtrade/tests/*
freqtrade/vendor/*

6
.dockerignore Normal file
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@@ -0,0 +1,6 @@
.git
.gitignore
Dockerfile
.dockerignore
config.json*
*.sqlite

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@@ -1,2 +1,3 @@
[BASIC]
good-names=logger
ignore=vendor

View File

@@ -1,28 +1,29 @@
sudo: false
os:
- linux
- linux
language: python
python:
- 3.6
- nightly
matrix:
allow_failures:
- python: nightly
- 3.6
env:
- BACKTEST=
- BACKTEST=true
addons:
apt:
packages:
- libelf-dev
- libdw-dev
- binutils-dev
- libelf-dev
- libdw-dev
- binutils-dev
install:
- wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
- tar zxvf ta-lib-0.4.0-src.tar.gz
- cd ta-lib && ./configure && sudo make && sudo make install && cd ..
- export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
- pip install -r requirements.txt
- wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
- tar zxvf ta-lib-0.4.0-src.tar.gz
- cd ta-lib && ./configure && sudo make && sudo make install && cd ..
- export LD_LIBRARY_PATH=/usr/local/lib:$LD_LIBRARY_PATH
- pip install coveralls
- pip install -r requirements.txt
script:
- python -m unittest
- pytest --cov=freqtrade --cov-config=.coveragerc freqtrade/tests/
after_success:
- coveralls
notifications:
slack:
secure: 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

View File

@@ -1,17 +1,23 @@
FROM python:3.6.2
FROM python:3.6.2
RUN pip install numpy
RUN apt-get update
RUN apt-get -y install build-essential
RUN wget http://prdownloads.sourceforge.net/ta-lib/ta-lib-0.4.0-src.tar.gz
RUN tar zxvf ta-lib-0.4.0-src.tar.gz
RUN cd ta-lib && ./configure && make && make install
# Install TA-lib
RUN apt-get update && apt-get -y install build-essential && 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 && \
./configure && make && make install && \
cd .. && rm -rf ta-lib
ENV LD_LIBRARY_PATH /usr/local/lib
RUN mkdir -p /freqtrade
# Prepare environment
RUN mkdir /freqtrade
WORKDIR /freqtrade
ADD ./requirements.txt /freqtrade/requirements.txt
RUN pip install -r requirements.txt
ADD . /freqtrade
CMD python main.py
# Install dependencies
COPY requirements.txt /freqtrade/
RUN pip install -r requirements.txt
# Install and execute
COPY . /freqtrade/
RUN pip install -e .
CMD ["freqtrade"]

5
MANIFEST.in Normal file
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@@ -0,0 +1,5 @@
include LICENSE
include README.md
include config.json.example
recursive-include freqtrade *.py
include freqtrade/tests/testdata/*.json

118
README.md
View File

@@ -1,9 +1,11 @@
# freqtrade
[![Build Status](https://travis-ci.org/gcarq/freqtrade.svg?branch=develop)](https://travis-ci.org/gcarq/freqtrade)
[![Coverage Status](https://coveralls.io/repos/github/gcarq/freqtrade/badge.svg?branch=develop)](https://coveralls.io/github/gcarq/freqtrade?branch=develop)
Simple High frequency trading bot for crypto currencies.
Currently supported exchanges: bittrex, poloniex (partly implemented)
Currently supports trading on Bittrex exchange.
This software is for educational purposes only.
Don't risk money which you are afraid to lose.
@@ -14,29 +16,32 @@ and enter the telegram `token` and your `chat_id` in `config.json`
Persistence is achieved through sqlite.
#### Telegram RPC commands:
### Telegram RPC commands:
* /start: Starts the trader
* /stop: Stops the trader
* /status: Lists all open trades
* /status [table]: Lists all open trades
* /count: Displays number of open trades
* /profit: Lists cumulative profit from all finished trades
* /forcesell <trade_id>: Instantly sells the given trade (Ignoring `minimum_roi`).
* /forcesell <trade_id>|all: Instantly sells the given trade (Ignoring `minimum_roi`).
* /performance: Show performance of each finished trade grouped by pair
* /balance: Show account balance per currency
* /help: Show help message
* /version: Show version
#### Config
### Config
`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:
```
"minimal_roi": {
"2880": 0.005, # Sell after 48 hours if there is at least 0.5% profit
"1440": 0.01, # Sell after 24 hours if there is at least 1% profit
"720": 0.02, # Sell after 12 hours if there is at least 2% profit
"360": 0.02, # Sell after 6 hours if there is at least 2% profit
"0": 0.025 # Sell immediately if there is at least 2.5% profit
"50": 0.0, # Sell after 30 minutes if the profit is not negative
"40": 0.01, # Sell after 25 minutes if there is at least 1% profit
"30": 0.02, # Sell after 15 minutes if there is at least 2% profit
"0": 0.045 # Sell immediately if there is at least 4.5% profit
},
```
`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
profit dips below -10% for a given trade. This parameter is optional.
@@ -44,15 +49,31 @@ profit dips below -10% for a given trade. This parameter is optional.
Possible values are `running` or `stopped`. (default=`running`)
If the value is `stopped` the bot has to be started with `/start` first.
`ask_last_balance` sets the bidding price. Value `0.0` will use `ask` price, `1.0` will
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.
The other values should be self-explanatory,
if not feel free to raise a github issue.
#### Prerequisites
### Prerequisites
* python3.6
* sqlite
* [TA-lib](https://github.com/mrjbq7/ta-lib#dependencies) binaries
#### Install
### Install
#### Arch Linux
Use your favorite AUR helper and install `python-freqtrade-git`.
#### Manually
`master` branch contains the latest stable release.
`develop` branch has often new features, but might also cause breaking changes. To use it, you are encouraged to join our [slack channel](https://join.slack.com/t/highfrequencybot/shared_invite/enQtMjQ5NTM0OTYzMzY3LWMxYzE3M2MxNDdjMGM3ZTYwNzFjMGIwZGRjNTc3ZGU3MGE3NzdmZGMwNmU3NDM5ZTNmM2Y3NjRiNzk4NmM4OGE).
```
$ cd freqtrade/
# copy example config. Dont forget to insert your api keys
@@ -60,18 +81,77 @@ $ cp config.json.example config.json
$ python -m venv .env
$ source .env/bin/activate
$ pip install -r requirements.txt
$ ./main.py
$ pip install -e .
$ ./freqtrade/main.py
```
#### Execute tests
There is also an [article](https://www.sales4k.com/blockchain/high-frequency-trading-bot-tutorial/) about how to setup the bot (thanks [@gurghet](https://github.com/gurghet)).*
```
$ python -m unittest
```
\* *Note:* that article was written for an earlier version, so it may be outdated
#### Docker
Building the image:
```
$ cd freqtrade
$ docker build -t freqtrade .
$ docker run --rm -it freqtrade
```
For security reasons, your configuration file will not be included in the
image, you will need to bind mount it. It is also advised to bind mount
a SQLite database file (see second example) to keep it between updates.
You can run a one-off container that is immediately deleted upon exiting with
the following command (config.json must be in the current working directory):
```
$ docker run --rm -v `pwd`/config.json:/freqtrade/config.json -it freqtrade
```
To run a restartable instance in the background (feel free to place your
configuration and database files wherever it feels comfortable on your
filesystem):
```
$ cd ~/.freq
$ touch tradesv3.sqlite
$ docker run -d \
--name freqtrade \
-v ~/.freq/config.json:/freqtrade/config.json \
-v ~/.freq/tradesv3.sqlite:/freqtrade/tradesv3.sqlite \
freqtrade
```
If you are using `dry_run=True` it's not necessary to mount `tradesv3.sqlite`.
You can then use the following commands to monitor and manage your container:
```
$ docker logs freqtrade
$ docker logs -f freqtrade
$ docker restart freqtrade
$ docker stop freqtrade
$ 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.
### Execute tests
```
$ pytest
```
This will by default skip the slow running backtest set. To run backtest set:
```
$ BACKTEST=true pytest -s freqtrade/tests/test_backtesting.py
```
### Contributing
Feel like our bot is missing a feature? We welcome your pull requests! Few pointers for contributions:
- Create your PR against the `develop` branch, not `master`.
- New features need to contain unit tests.
- If you are unsure, discuss the feature on [slack](https://join.slack.com/t/highfrequencybot/shared_invite/enQtMjQ5NTM0OTYzMzY3LWMxYzE3M2MxNDdjMGM3ZTYwNzFjMGIwZGRjNTc3ZGU3MGE3NzdmZGMwNmU3NDM5ZTNmM2Y3NjRiNzk4NmM4OGE) or in a [issue](https://github.com/gcarq/freqtrade/issues) before a PR.

View File

@@ -1,165 +0,0 @@
import time
from datetime import timedelta
import logging
import arrow
import requests
from pandas.io.json import json_normalize
from pandas import DataFrame
import talib.abstract as ta
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
def get_ticker(pair: str, minimum_date: arrow.Arrow) -> dict:
"""
Request ticker data from Bittrex for a given currency pair
"""
url = 'https://bittrex.com/Api/v2.0/pub/market/GetTicks'
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36',
}
params = {
'marketName': pair.replace('_', '-'),
'tickInterval': 'OneMin',
'_': minimum_date.timestamp * 1000
}
data = requests.get(url, params=params, headers=headers).json()
if not data['success']:
raise RuntimeError('BITTREX: {}'.format(data['message']))
return data
def parse_ticker_dataframe(ticker: list, minimum_date: arrow.Arrow) -> DataFrame:
"""
Analyses the trend for the given pair
:param pair: pair as str in format BTC_ETH or BTC-ETH
:return: DataFrame
"""
df = DataFrame(ticker) \
.drop('BV', 1) \
.rename(columns={'C':'close', 'V':'volume', 'O':'open', 'H':'high', 'L':'low', 'T':'date'}) \
.sort_values('date')
return df[df['date'].map(arrow.get) > minimum_date]
def populate_indicators(dataframe: DataFrame) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
"""
dataframe['close_30_ema'] = ta.EMA(dataframe, timeperiod=30)
dataframe['close_90_ema'] = ta.EMA(dataframe, timeperiod=90)
dataframe['sar'] = ta.SAR(dataframe, 0.02, 0.2)
# calculate StochRSI
stochrsi = ta.STOCHRSI(dataframe)
dataframe['stochrsi'] = stochrsi['fastd'] # values between 0-100, not 0-1
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macds'] = macd['macdsignal']
dataframe['macdh'] = macd['macdhist']
return dataframe
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
"""
Based on TA indicators, populates the buy trend for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.loc[
(dataframe['stochrsi'] < 20)
& (dataframe['macd'] > dataframe['macds'])
& (dataframe['close'] > dataframe['sar']),
'buy'
] = 1
dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
return dataframe
def analyze_ticker(pair: str) -> DataFrame:
"""
Get ticker data for given currency pair, push it to a DataFrame and
add several TA indicators and buy signal to it
:return DataFrame with ticker data and indicator data
"""
minimum_date = arrow.utcnow().shift(hours=-6)
data = get_ticker(pair, minimum_date)
dataframe = parse_ticker_dataframe(data['result'], minimum_date)
dataframe = populate_indicators(dataframe)
dataframe = populate_buy_trend(dataframe)
return dataframe
def get_buy_signal(pair: str) -> bool:
"""
Calculates a buy signal based several technical analysis indicators
:param pair: pair in format BTC_ANT or BTC-ANT
:return: True if pair is good for buying, False otherwise
"""
dataframe = analyze_ticker(pair)
latest = dataframe.iloc[-1]
# Check if dataframe is out of date
signal_date = arrow.get(latest['date'])
if signal_date < arrow.now() - timedelta(minutes=10):
return False
signal = latest['buy'] == 1
logger.debug('buy_trigger: %s (pair=%s, signal=%s)', latest['date'], pair, signal)
return signal
def plot_dataframe(dataframe: DataFrame, pair: str) -> None:
"""
Plots the given dataframe
:param dataframe: DataFrame
:param pair: pair as str
:return: None
"""
import matplotlib
matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt
# Three subplots sharing x axe
fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
fig.suptitle(pair, fontsize=14, fontweight='bold')
ax1.plot(dataframe.index.values, dataframe['close'], label='close')
ax1.plot(dataframe.index.values, dataframe['close_30_ema'], label='EMA(30)')
ax1.plot(dataframe.index.values, dataframe['close_90_ema'], label='EMA(90)')
# ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy')
ax1.legend()
ax2.plot(dataframe.index.values, dataframe['macd'], label='MACD')
ax2.plot(dataframe.index.values, dataframe['macds'], label='MACDS')
ax2.plot(dataframe.index.values, dataframe['macdh'], label='MACD Histogram')
ax2.plot(dataframe.index.values, [0] * len(dataframe.index.values))
ax2.legend()
ax3.plot(dataframe.index.values, dataframe['stochrsi'], label='StochRSI')
ax3.plot(dataframe.index.values, [80] * len(dataframe.index.values))
ax3.plot(dataframe.index.values, [20] * len(dataframe.index.values))
ax3.legend()
# Fine-tune figure; make subplots close to each other and hide x ticks for
# all but bottom plot.
fig.subplots_adjust(hspace=0)
plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
plt.show()
if __name__ == '__main__':
# Install PYQT5==5.9 manually if you want to test this helper function
while True:
pair = 'BTC_ANT'
#for pair in ['BTC_ANT', 'BTC_ETH', 'BTC_GNT', 'BTC_ETC']:
# get_buy_signal(pair)
plot_dataframe(analyze_ticker(pair), pair)
time.sleep(60)

4
bin/freqtrade Executable file
View File

@@ -0,0 +1,4 @@
#!/usr/bin/env python3
from freqtrade.main import main
main()

View File

@@ -4,19 +4,17 @@
"stake_amount": 0.05,
"dry_run": false,
"minimal_roi": {
"2880": 0.005,
"720": 0.01,
"0": 0.02
"50": 0.0,
"40": 0.01,
"30": 0.02,
"0": 0.045
},
"stoploss": -0.10,
"poloniex": {
"enabled": false,
"key": "key",
"secret": "secret",
"pair_whitelist": []
"stoploss": -0.40,
"bid_strategy": {
"ask_last_balance": 0.0
},
"bittrex": {
"enabled": true,
"exchange": {
"name": "bittrex",
"key": "key",
"secret": "secret",
"pair_whitelist": [
@@ -36,5 +34,8 @@
"token": "token",
"chat_id": "chat_id"
},
"initial_state": "running"
"initial_state": "running",
"internals": {
"process_throttle_secs": 5
}
}

View File

@@ -1,201 +0,0 @@
import enum
import logging
from typing import List
from bittrex.bittrex import Bittrex
from poloniex import Poloniex
logger = logging.getLogger(__name__)
# Current selected exchange
EXCHANGE = None
_API = None
_CONF = {}
class Exchange(enum.Enum):
POLONIEX = 0
BITTREX = 1
def init(config: dict) -> None:
"""
Initializes this module with the given config,
it does basic validation whether the specified
exchange and pairs are valid.
:param config: config to use
:return: None
"""
global _API, EXCHANGE
_CONF.update(config)
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
use_poloniex = config.get('poloniex', {}).get('enabled', False)
use_bittrex = config.get('bittrex', {}).get('enabled', False)
if use_poloniex:
EXCHANGE = Exchange.POLONIEX
_API = Poloniex(key=config['poloniex']['key'], secret=config['poloniex']['secret'])
elif use_bittrex:
EXCHANGE = Exchange.BITTREX
_API = Bittrex(api_key=config['bittrex']['key'], api_secret=config['bittrex']['secret'])
else:
raise RuntimeError('No exchange specified. Aborting!')
# Check if all pairs are available
markets = get_markets()
for pair in config[EXCHANGE.name.lower()]['pair_whitelist']:
if pair not in markets:
raise RuntimeError('Pair {} is not available at Poloniex'.format(pair))
def buy(pair: str, rate: float, amount: float) -> str:
"""
Places a limit buy order.
:param pair: Pair as str, format: BTC_ETH
:param rate: Rate limit for order
:param amount: The amount to purchase
:return: order_id of the placed buy order
"""
if _CONF['dry_run']:
return 'dry_run'
elif EXCHANGE == Exchange.POLONIEX:
_API.buy(pair, rate, amount)
# TODO: return order id
elif EXCHANGE == Exchange.BITTREX:
data = _API.buy_limit(pair.replace('_', '-'), amount, rate)
if not data['success']:
raise RuntimeError('BITTREX: {}'.format(data['message']))
return data['result']['uuid']
def sell(pair: str, rate: float, amount: float) -> str:
"""
Places a limit sell order.
:param pair: Pair as str, format: BTC_ETH
:param rate: Rate limit for order
:param amount: The amount to sell
:return: None
"""
if _CONF['dry_run']:
return 'dry_run'
elif EXCHANGE == Exchange.POLONIEX:
_API.sell(pair, rate, amount)
# TODO: return order id
elif EXCHANGE == Exchange.BITTREX:
data = _API.sell_limit(pair.replace('_', '-'), amount, rate)
if not data['success']:
raise RuntimeError('BITTREX: {}'.format(data['message']))
return data['result']['uuid']
def get_balance(currency: str) -> float:
"""
Get account balance.
:param currency: currency as str, format: BTC
:return: float
"""
if _CONF['dry_run']:
return 999.9
elif EXCHANGE == Exchange.POLONIEX:
data = _API.returnBalances()
return float(data[currency])
elif EXCHANGE == Exchange.BITTREX:
data = _API.get_balance(currency)
if not data['success']:
raise RuntimeError('BITTREX: {}'.format(data['message']))
return float(data['result']['Balance'] or 0.0)
def get_ticker(pair: str) -> dict:
"""
Get Ticker for given pair.
:param pair: Pair as str, format: BTC_ETC
:return: dict
"""
if EXCHANGE == Exchange.POLONIEX:
data = _API.returnTicker()
return {
'bid': float(data[pair]['highestBid']),
'ask': float(data[pair]['lowestAsk']),
'last': float(data[pair]['last'])
}
elif EXCHANGE == Exchange.BITTREX:
data = _API.get_ticker(pair.replace('_', '-'))
if not data['success']:
raise RuntimeError('BITTREX: {}'.format(data['message']))
return {
'bid': float(data['result']['Bid']),
'ask': float(data['result']['Ask']),
'last': float(data['result']['Last']),
}
def cancel_order(order_id: str) -> None:
"""
Cancel order for given order_id
:param order_id: id as str
:return: None
"""
if _CONF['dry_run']:
pass
elif EXCHANGE == Exchange.POLONIEX:
raise NotImplemented('Not implemented')
elif EXCHANGE == Exchange.BITTREX:
data = _API.cancel(order_id)
if not data['success']:
raise RuntimeError('BITTREX: {}'.format(data['message']))
def get_open_orders(pair: str) -> List[dict]:
"""
Get all open orders for given pair.
:param pair: Pair as str, format: BTC_ETC
:return: list of dicts
"""
if _CONF['dry_run']:
return []
elif EXCHANGE == Exchange.POLONIEX:
raise NotImplemented('Not implemented')
elif EXCHANGE == Exchange.BITTREX:
data = _API.get_open_orders(pair.replace('_', '-'))
if not data['success']:
raise RuntimeError('BITTREX: {}'.format(data['message']))
return [{
'id': entry['OrderUuid'],
'type': entry['OrderType'],
'opened': entry['Opened'],
'rate': entry['PricePerUnit'],
'amount': entry['Quantity'],
'remaining': entry['QuantityRemaining'],
} for entry in data['result']]
def get_pair_detail_url(pair: str) -> str:
"""
Returns the market detail url for the given pair
:param pair: pair as str, format: BTC_ANT
:return: url as str
"""
if EXCHANGE == Exchange.POLONIEX:
raise NotImplemented('Not implemented')
elif EXCHANGE == Exchange.BITTREX:
return 'https://bittrex.com/Market/Index?MarketName={}'.format(pair.replace('_', '-'))
def get_markets() -> List[str]:
"""
Returns all available markets
:return: list of all available pairs
"""
if EXCHANGE == Exchange.POLONIEX:
# TODO: implement
raise NotImplemented('Not implemented')
elif EXCHANGE == Exchange. BITTREX:
data = _API.get_markets()
if not data['success']:
raise RuntimeError('BITTREX: {}'.format(data['message']))
return [m['MarketName'].replace('-', '_') for m in data['result']]

3
freqtrade/__init__.py Normal file
View File

@@ -0,0 +1,3 @@
__version__ = '0.14.2'
from . import main

112
freqtrade/analyze.py Normal file
View File

@@ -0,0 +1,112 @@
import logging
from datetime import timedelta
import arrow
import talib.abstract as ta
from pandas import DataFrame, to_datetime
from freqtrade.exchange import get_ticker_history
from freqtrade.vendor.qtpylib.indicators import awesome_oscillator
logger = logging.getLogger(__name__)
def parse_ticker_dataframe(ticker: list) -> DataFrame:
"""
Analyses the trend for the given ticker history
:param ticker: See exchange.get_ticker_history
:return: DataFrame
"""
columns = {'C': 'close', 'V': 'volume', 'O': 'open', 'H': 'high', 'L': 'low', 'T': 'date'}
frame = DataFrame(ticker) \
.drop('BV', 1) \
.rename(columns=columns)
frame['date'] = to_datetime(frame['date'], utc=True, infer_datetime_format=True)
frame.sort_values('date', inplace=True)
return frame
def populate_indicators(dataframe: DataFrame) -> DataFrame:
"""
Adds several different TA indicators to the given DataFrame
"""
dataframe['sar'] = ta.SAR(dataframe)
dataframe['adx'] = ta.ADX(dataframe)
stoch = ta.STOCHF(dataframe)
dataframe['fastd'] = stoch['fastd']
dataframe['fastk'] = stoch['fastk']
dataframe['blower'] = ta.BBANDS(dataframe, nbdevup=2, nbdevdn=2)['lowerband']
dataframe['sma'] = ta.SMA(dataframe, timeperiod=40)
dataframe['tema'] = ta.TEMA(dataframe, timeperiod=9)
dataframe['mfi'] = ta.MFI(dataframe)
dataframe['rsi'] = ta.RSI(dataframe)
dataframe['ema5'] = ta.EMA(dataframe, timeperiod=5)
dataframe['ema10'] = ta.EMA(dataframe, timeperiod=10)
dataframe['ema50'] = ta.EMA(dataframe, timeperiod=50)
dataframe['ema100'] = ta.EMA(dataframe, timeperiod=100)
dataframe['ao'] = awesome_oscillator(dataframe)
macd = ta.MACD(dataframe)
dataframe['macd'] = macd['macd']
dataframe['macdsignal'] = macd['macdsignal']
dataframe['macdhist'] = macd['macdhist']
hilbert = ta.HT_SINE(dataframe)
dataframe['htsine'] = hilbert['sine']
dataframe['htleadsine'] = hilbert['leadsine']
return dataframe
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
"""
Based on TA indicators, populates the buy trend for the given dataframe
:param dataframe: DataFrame
:return: DataFrame with buy column
"""
dataframe.ix[
(dataframe['close'] < dataframe['sma']) &
(dataframe['tema'] <= dataframe['blower']) &
(dataframe['mfi'] < 25) &
(dataframe['fastd'] < 25) &
(dataframe['adx'] > 30),
'buy'] = 1
dataframe.ix[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
return dataframe
def analyze_ticker(pair: str) -> DataFrame:
"""
Get ticker data for given currency pair, push it to a DataFrame and
add several TA indicators and buy signal to it
:return DataFrame with ticker data and indicator data
"""
ticker_hist = get_ticker_history(pair)
if not ticker_hist:
logger.warning('Empty ticker history for pair %s', pair)
return DataFrame()
dataframe = parse_ticker_dataframe(ticker_hist)
dataframe = populate_indicators(dataframe)
dataframe = populate_buy_trend(dataframe)
return dataframe
def get_buy_signal(pair: str) -> bool:
"""
Calculates a buy signal based several technical analysis indicators
:param pair: pair in format BTC_ANT or BTC-ANT
:return: True if pair is good for buying, False otherwise
"""
dataframe = analyze_ticker(pair)
if dataframe.empty:
return False
latest = dataframe.iloc[-1]
# Check if dataframe is out of date
signal_date = arrow.get(latest['date'])
if signal_date < arrow.now() - timedelta(minutes=10):
return False
signal = latest['buy'] == 1
logger.debug('buy_trigger: %s (pair=%s, signal=%s)', latest['date'], pair, signal)
return signal

View File

@@ -0,0 +1,175 @@
import enum
import logging
from random import randint
from typing import List, Dict, Any, Optional
import arrow
from cachetools import cached, TTLCache
from freqtrade.exchange.bittrex import Bittrex
from freqtrade.exchange.interface import Exchange
logger = logging.getLogger(__name__)
# Current selected exchange
_API: Exchange = None
_CONF: dict = {}
# Holds all open sell orders for dry_run
_DRY_RUN_OPEN_ORDERS: Dict[str, Any] = {}
class Exchanges(enum.Enum):
"""
Maps supported exchange names to correspondent classes.
"""
BITTREX = Bittrex
def init(config: dict) -> None:
"""
Initializes this module with the given config,
it does basic validation whether the specified
exchange and pairs are valid.
:param config: config to use
:return: None
"""
global _CONF, _API
_CONF.update(config)
if config['dry_run']:
logger.info('Instance is running with dry_run enabled')
exchange_config = config['exchange']
# Find matching class for the given exchange name
name = exchange_config['name']
try:
exchange_class = Exchanges[name.upper()].value
except KeyError:
raise RuntimeError('Exchange {} is not supported'.format(name))
_API = exchange_class(exchange_config)
# Check if all pairs are available
validate_pairs(config['exchange']['pair_whitelist'])
def validate_pairs(pairs: List[str]) -> None:
"""
Checks if all given pairs are tradable on the current exchange.
Raises RuntimeError if one pair is not available.
:param pairs: list of pairs
:return: None
"""
markets = _API.get_markets()
stake_cur = _CONF['stake_currency']
for pair in pairs:
if not pair.startswith(stake_cur):
raise RuntimeError(
'Pair {} not compatible with stake_currency: {}'.format(pair, stake_cur)
)
if pair not in markets:
raise RuntimeError('Pair {} is not available at {}'.format(pair, _API.name.lower()))
def buy(pair: str, rate: float, amount: float) -> str:
if _CONF['dry_run']:
global _DRY_RUN_OPEN_ORDERS
order_id = 'dry_run_buy_{}'.format(randint(0, 1e6))
_DRY_RUN_OPEN_ORDERS[order_id] = {
'pair': pair,
'rate': rate,
'amount': amount,
'type': 'LIMIT_BUY',
'remaining': 0.0,
'opened': arrow.utcnow().datetime,
'closed': arrow.utcnow().datetime,
}
return order_id
return _API.buy(pair, rate, amount)
def sell(pair: str, rate: float, amount: float) -> str:
if _CONF['dry_run']:
global _DRY_RUN_OPEN_ORDERS
order_id = 'dry_run_sell_{}'.format(randint(0, 1e6))
_DRY_RUN_OPEN_ORDERS[order_id] = {
'pair': pair,
'rate': rate,
'amount': amount,
'type': 'LIMIT_SELL',
'remaining': 0.0,
'opened': arrow.utcnow().datetime,
'closed': arrow.utcnow().datetime,
}
return order_id
return _API.sell(pair, rate, amount)
def get_balance(currency: str) -> float:
if _CONF['dry_run']:
return 999.9
return _API.get_balance(currency)
def get_balances():
if _CONF['dry_run']:
return []
return _API.get_balances()
def get_ticker(pair: str) -> dict:
return _API.get_ticker(pair)
@cached(TTLCache(maxsize=100, ttl=30))
def get_ticker_history(pair: str, tick_interval: Optional[int] = 5) -> List[Dict]:
return _API.get_ticker_history(pair, tick_interval)
def cancel_order(order_id: str) -> None:
if _CONF['dry_run']:
return
return _API.cancel_order(order_id)
def get_order(order_id: str) -> Dict:
if _CONF['dry_run']:
order = _DRY_RUN_OPEN_ORDERS[order_id]
order.update({
'id': order_id
})
return order
return _API.get_order(order_id)
def get_pair_detail_url(pair: str) -> str:
return _API.get_pair_detail_url(pair)
def get_markets() -> List[str]:
return _API.get_markets()
def get_market_summaries() -> List[Dict]:
return _API.get_market_summaries()
def get_name() -> str:
return _API.name
def get_fee() -> float:
return _API.fee
def get_wallet_health() -> List[Dict]:
return _API.get_wallet_health()

View File

@@ -0,0 +1,171 @@
import logging
from typing import List, Dict
from bittrex.bittrex import Bittrex as _Bittrex, API_V2_0, API_V1_1
from freqtrade.exchange.interface import Exchange
logger = logging.getLogger(__name__)
_API: _Bittrex = None
_API_V2: _Bittrex = None
_EXCHANGE_CONF: dict = {}
class Bittrex(Exchange):
"""
Bittrex API wrapper.
"""
# Base URL and API endpoints
BASE_URL: str = 'https://www.bittrex.com'
PAIR_DETAIL_METHOD: str = BASE_URL + '/Market/Index'
def __init__(self, config: dict) -> None:
global _API, _API_V2, _EXCHANGE_CONF
_EXCHANGE_CONF.update(config)
_API = _Bittrex(
api_key=_EXCHANGE_CONF['key'],
api_secret=_EXCHANGE_CONF['secret'],
calls_per_second=1,
api_version=API_V1_1,
)
_API_V2 = _Bittrex(
api_key=_EXCHANGE_CONF['key'],
api_secret=_EXCHANGE_CONF['secret'],
calls_per_second=1,
api_version=API_V2_0,
)
@property
def fee(self) -> float:
# See https://bittrex.com/fees
return 0.0025
def buy(self, pair: str, rate: float, amount: float) -> str:
data = _API.buy_limit(pair.replace('_', '-'), amount, rate)
if not data['success']:
raise RuntimeError('{message} params=({pair}, {rate}, {amount})'.format(
message=data['message'],
pair=pair,
rate=rate,
amount=amount))
return data['result']['uuid']
def sell(self, pair: str, rate: float, amount: float) -> str:
data = _API.sell_limit(pair.replace('_', '-'), amount, rate)
if not data['success']:
raise RuntimeError('{message} params=({pair}, {rate}, {amount})'.format(
message=data['message'],
pair=pair,
rate=rate,
amount=amount))
return data['result']['uuid']
def get_balance(self, currency: str) -> float:
data = _API.get_balance(currency)
if not data['success']:
raise RuntimeError('{message} params=({currency})'.format(
message=data['message'],
currency=currency))
return float(data['result']['Balance'] or 0.0)
def get_balances(self):
data = _API.get_balances()
if not data['success']:
raise RuntimeError('{message}'.format(message=data['message']))
return data['result']
def get_ticker(self, pair: str) -> dict:
data = _API.get_ticker(pair.replace('_', '-'))
if not data['success']:
raise RuntimeError('{message} params=({pair})'.format(
message=data['message'],
pair=pair))
if not data['result']['Bid'] or not data['result']['Ask'] or not data['result']['Last']:
raise RuntimeError('{message} params=({pair})'.format(
message=data['message'],
pair=pair))
return {
'bid': float(data['result']['Bid']),
'ask': float(data['result']['Ask']),
'last': float(data['result']['Last']),
}
def get_ticker_history(self, pair: str, tick_interval: int) -> List[Dict]:
if tick_interval == 1:
interval = 'oneMin'
elif tick_interval == 5:
interval = 'fiveMin'
else:
raise ValueError('Cannot parse tick_interval: {}'.format(tick_interval))
data = _API_V2.get_candles(pair.replace('_', '-'), interval)
# These sanity check are necessary because bittrex cannot keep their API stable.
if not data.get('result'):
return []
for prop in ['C', 'V', 'O', 'H', 'L', 'T']:
for tick in data['result']:
if prop not in tick.keys():
logger.warning('Required property %s not present in response', prop)
return []
if not data['success']:
raise RuntimeError('{message} params=({pair})'.format(
message=data['message'],
pair=pair))
return data['result']
def get_order(self, order_id: str) -> Dict:
data = _API.get_order(order_id)
if not data['success']:
raise RuntimeError('{message} params=({order_id})'.format(
message=data['message'],
order_id=order_id))
data = data['result']
return {
'id': data['OrderUuid'],
'type': data['Type'],
'pair': data['Exchange'].replace('-', '_'),
'opened': data['Opened'],
'rate': data['PricePerUnit'],
'amount': data['Quantity'],
'remaining': data['QuantityRemaining'],
'closed': data['Closed'],
}
def cancel_order(self, order_id: str) -> None:
data = _API.cancel(order_id)
if not data['success']:
raise RuntimeError('{message} params=({order_id})'.format(
message=data['message'],
order_id=order_id))
def get_pair_detail_url(self, pair: str) -> str:
return self.PAIR_DETAIL_METHOD + '?MarketName={}'.format(pair.replace('_', '-'))
def get_markets(self) -> List[str]:
data = _API.get_markets()
if not data['success']:
raise RuntimeError('{message}'.format(message=data['message']))
return [m['MarketName'].replace('-', '_') for m in data['result']]
def get_market_summaries(self) -> List[Dict]:
data = _API.get_market_summaries()
if not data['success']:
raise RuntimeError('{message}'.format(message=data['message']))
return data['result']
def get_wallet_health(self) -> List[Dict]:
data = _API_V2.get_wallet_health()
if not data['success']:
raise RuntimeError('{message}'.format(message=data['message']))
return [{
'Currency': entry['Health']['Currency'],
'IsActive': entry['Health']['IsActive'],
'LastChecked': entry['Health']['LastChecked'],
'Notice': entry['Currency'].get('Notice'),
} for entry in data['result']]

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from abc import ABC, abstractmethod
from typing import List, Dict
class Exchange(ABC):
@property
def name(self) -> str:
"""
Name of the exchange.
:return: str representation of the class name
"""
return self.__class__.__name__
@property
def fee(self) -> float:
"""
Fee for placing an order
:return: percentage in float
"""
@abstractmethod
def buy(self, pair: str, rate: float, amount: float) -> str:
"""
Places a limit buy order.
:param pair: Pair as str, format: BTC_ETH
:param rate: Rate limit for order
:param amount: The amount to purchase
:return: order_id of the placed buy order
"""
@abstractmethod
def sell(self, pair: str, rate: float, amount: float) -> str:
"""
Places a limit sell order.
:param pair: Pair as str, format: BTC_ETH
:param rate: Rate limit for order
:param amount: The amount to sell
:return: order_id of the placed sell order
"""
@abstractmethod
def get_balance(self, currency: str) -> float:
"""
Gets account balance.
:param currency: Currency as str, format: BTC
:return: float
"""
@abstractmethod
def get_balances(self) -> List[dict]:
"""
Gets account balances across currencies
:return: List of dicts, format: [
{
'Currency': str,
'Balance': float,
'Available': float,
'Pending': float,
}
...
]
"""
@abstractmethod
def get_ticker(self, pair: str) -> dict:
"""
Gets ticker for given pair.
:param pair: Pair as str, format: BTC_ETC
:return: dict, format: {
'bid': float,
'ask': float,
'last': float
}
"""
@abstractmethod
def get_ticker_history(self, pair: str, tick_interval: int) -> List[Dict]:
"""
Gets ticker history for given pair.
:param pair: Pair as str, format: BTC_ETC
:param tick_interval: ticker interval in minutes
:return: list, format: [
{
'O': float, (Open)
'H': float, (High)
'L': float, (Low)
'C': float, (Close)
'V': float, (Volume)
'T': datetime, (Time)
'BV': float, (Base Volume)
},
...
]
"""
def get_order(self, order_id: str) -> Dict:
"""
Get order details for the given order_id.
:param order_id: ID as str
:return: dict, format: {
'id': str,
'type': str,
'pair': str,
'opened': str ISO 8601 datetime,
'closed': str ISO 8601 datetime,
'rate': float,
'amount': float,
'remaining': int
}
"""
@abstractmethod
def cancel_order(self, order_id: str) -> None:
"""
Cancels order for given order_id.
:param order_id: ID as str
:return: None
"""
@abstractmethod
def get_pair_detail_url(self, pair: str) -> str:
"""
Returns the market detail url for the given pair.
:param pair: Pair as str, format: BTC_ETC
:return: URL as str
"""
@abstractmethod
def get_markets(self) -> List[str]:
"""
Returns all available markets.
:return: List of all available pairs
"""
@abstractmethod
def get_market_summaries(self) -> List[Dict]:
"""
Returns a 24h market summary for all available markets
:return: list, format: [
{
'MarketName': str,
'High': float,
'Low': float,
'Volume': float,
'Last': float,
'TimeStamp': datetime,
'BaseVolume': float,
'Bid': float,
'Ask': float,
'OpenBuyOrders': int,
'OpenSellOrders': int,
'PrevDay': float,
'Created': datetime
},
...
]
"""
@abstractmethod
def get_wallet_health(self) -> List[Dict]:
"""
Returns a list of all wallet health information
:return: list, format: [
{
'Currency': str,
'IsActive': bool,
'LastChecked': str,
'Notice': str
},
...
"""

361
freqtrade/main.py Executable file
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#!/usr/bin/env python3
import copy
import json
import logging
import time
import traceback
from datetime import datetime
from signal import signal, SIGINT, SIGABRT, SIGTERM
from typing import Dict, Optional, List
import requests
from cachetools import cached, TTLCache
from jsonschema import validate
from freqtrade import __version__, exchange, persistence
from freqtrade.analyze import get_buy_signal
from freqtrade.misc import CONF_SCHEMA, State, get_state, update_state, build_arg_parser, throttle
from freqtrade.persistence import Trade
from freqtrade.rpc import telegram
logger = logging.getLogger('freqtrade')
_CONF = {}
def refresh_whitelist(whitelist: Optional[List[str]] = None) -> None:
"""
Check wallet health and remove pair from whitelist if necessary
:param whitelist: a new whitelist (optional)
:return: None
"""
whitelist = whitelist or _CONF['exchange']['pair_whitelist']
sanitized_whitelist = []
health = exchange.get_wallet_health()
for status in health:
pair = '{}_{}'.format(_CONF['stake_currency'], status['Currency'])
if pair not in whitelist:
continue
if status['IsActive']:
sanitized_whitelist.append(pair)
else:
logger.info(
'Ignoring %s from whitelist (reason: %s).',
pair, status.get('Notice') or 'wallet is not active'
)
if _CONF['exchange']['pair_whitelist'] != sanitized_whitelist:
logger.debug('Using refreshed pair whitelist: %s ...', sanitized_whitelist)
_CONF['exchange']['pair_whitelist'] = sanitized_whitelist
def _process(dynamic_whitelist: Optional[bool] = False) -> bool:
"""
Queries the persistence layer for open trades and handles them,
otherwise a new trade is created.
:param: dynamic_whitelist: True is a dynamic whitelist should be generated (optional)
:return: True if a trade has been created or closed, False otherwise
"""
state_changed = False
try:
# Refresh whitelist based on wallet maintenance
refresh_whitelist(
gen_pair_whitelist(_CONF['stake_currency']) if dynamic_whitelist else None
)
# Query trades from persistence layer
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if len(trades) < _CONF['max_open_trades']:
try:
# Create entity and execute trade
trade = create_trade(float(_CONF['stake_amount']))
if trade:
Trade.session.add(trade)
state_changed = True
else:
logger.info(
'Checked all whitelisted currencies. '
'Found no suitable entry positions for buying. Will keep looking ...'
)
except ValueError:
logger.exception('Unable to create trade')
for trade in trades:
# Get order details for actual price per unit
if trade.open_order_id:
# Update trade with order values
logger.info('Got open order for %s', trade)
trade.update(exchange.get_order(trade.open_order_id))
if not close_trade_if_fulfilled(trade):
# Check if we can sell our current pair
state_changed = handle_trade(trade) or state_changed
Trade.session.flush()
except (requests.exceptions.RequestException, json.JSONDecodeError) as error:
msg = 'Got {} in _process(), retrying in 30 seconds...'.format(error.__class__.__name__)
logger.exception(msg)
time.sleep(30)
except RuntimeError:
telegram.send_msg('*Status:* Got RuntimeError:\n```\n{traceback}```{hint}'.format(
traceback=traceback.format_exc(),
hint='Issue `/start` if you think it is safe to restart.'
))
logger.exception('Got RuntimeError. Stopping trader ...')
update_state(State.STOPPED)
return state_changed
def close_trade_if_fulfilled(trade: Trade) -> bool:
"""
Checks if the trade is closable, and if so it is being closed.
:param trade: Trade
:return: True if trade has been closed else False
"""
# If we don't have an open order and the close rate is already set,
# we can close this trade.
if trade.close_profit is not None \
and trade.close_date is not None \
and trade.close_rate is not None \
and trade.open_order_id is None:
trade.is_open = False
logger.info(
'Marking %s as closed as the trade is fulfilled and found no open orders for it.',
trade
)
return True
return False
def execute_sell(trade: Trade, limit: float) -> None:
"""
Executes a limit sell for the given trade and limit
:param trade: Trade instance
:param limit: limit rate for the sell order
:return: None
"""
# Execute sell and update trade record
order_id = exchange.sell(str(trade.pair), limit, trade.amount)
trade.open_order_id = order_id
fmt_exp_profit = round(trade.calc_profit(limit) * 100, 2)
message = '*{}:* Selling [{}]({}) with limit `{:.8f} (profit: ~{:.2f}%)`'.format(
trade.exchange,
trade.pair.replace('_', '/'),
exchange.get_pair_detail_url(trade.pair),
limit,
fmt_exp_profit
)
logger.info(message)
telegram.send_msg(message)
def should_sell(trade: Trade, current_rate: float, current_time: datetime) -> bool:
"""
Based an earlier trade and current price and configuration, decides whether bot should sell
:return True if bot should sell at current rate
"""
current_profit = trade.calc_profit(current_rate)
if 'stoploss' in _CONF and current_profit < float(_CONF['stoploss']):
logger.debug('Stop loss hit.')
return True
for duration, threshold in sorted(_CONF['minimal_roi'].items()):
# Check if time matches and current rate is above threshold
time_diff = (current_time - trade.open_date).total_seconds() / 60
if time_diff > float(duration) and current_profit > threshold:
return True
logger.debug('Threshold not reached. (cur_profit: %1.2f%%)', current_profit * 100.0)
return False
def handle_trade(trade: Trade) -> bool:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: True if trade has been sold, False otherwise
"""
if not trade.is_open:
raise ValueError('attempt to handle closed trade: {}'.format(trade))
logger.debug('Handling %s ...', trade)
current_rate = exchange.get_ticker(trade.pair)['bid']
if should_sell(trade, current_rate, datetime.utcnow()):
execute_sell(trade, current_rate)
return True
return False
def get_target_bid(ticker: Dict[str, float]) -> float:
""" Calculates bid target between current ask price and last price """
if ticker['ask'] < ticker['last']:
return ticker['ask']
balance = _CONF['bid_strategy']['ask_last_balance']
return ticker['ask'] + balance * (ticker['last'] - ticker['ask'])
def create_trade(stake_amount: float) -> Optional[Trade]:
"""
Checks the implemented trading indicator(s) for a randomly picked pair,
if one pair triggers the buy_signal a new trade record gets created
:param stake_amount: amount of btc to spend
"""
logger.info(
'Checking buy signals to create a new trade with stake_amount: %f ...',
stake_amount
)
whitelist = copy.deepcopy(_CONF['exchange']['pair_whitelist'])
# Check if stake_amount is fulfilled
if exchange.get_balance(_CONF['stake_currency']) < stake_amount:
raise ValueError(
'stake amount is not fulfilled (currency={})'.format(_CONF['stake_currency'])
)
# Remove currently opened and latest pairs from whitelist
for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
if trade.pair in whitelist:
whitelist.remove(trade.pair)
logger.debug('Ignoring %s in pair whitelist', trade.pair)
if not whitelist:
raise ValueError('No pair in whitelist')
# Pick pair based on StochRSI buy signals
for _pair in whitelist:
if get_buy_signal(_pair):
pair = _pair
break
else:
return None
# Calculate amount and subtract fee
fee = exchange.get_fee()
buy_limit = get_target_bid(exchange.get_ticker(pair))
amount = (1 - fee) * stake_amount / buy_limit
order_id = exchange.buy(pair, buy_limit, amount)
# Create trade entity and return
message = '*{}:* Buying [{}]({}) with limit `{:.8f}`'.format(
exchange.get_name().upper(),
pair.replace('_', '/'),
exchange.get_pair_detail_url(pair),
buy_limit
)
logger.info(message)
telegram.send_msg(message)
# Fee is applied twice because we make a LIMIT_BUY and LIMIT_SELL
return Trade(pair=pair,
stake_amount=stake_amount,
amount=amount,
fee=fee * 2,
open_rate=buy_limit,
open_date=datetime.utcnow(),
exchange=exchange.get_name().upper(),
open_order_id=order_id)
def init(config: dict, db_url: Optional[str] = None) -> None:
"""
Initializes all modules and updates the config
:param config: config as dict
:param db_url: database connector string for sqlalchemy (Optional)
:return: None
"""
# Initialize all modules
telegram.init(config)
persistence.init(config, db_url)
exchange.init(config)
# Set initial application state
initial_state = config.get('initial_state')
if initial_state:
update_state(State[initial_state.upper()])
else:
update_state(State.STOPPED)
# Register signal handlers
for sig in (SIGINT, SIGTERM, SIGABRT):
signal(sig, cleanup)
@cached(TTLCache(maxsize=1, ttl=1800))
def gen_pair_whitelist(base_currency: str, topn: int = 20, key: str = 'BaseVolume') -> List[str]:
"""
Updates the whitelist with with a dynamically generated list
:param base_currency: base currency as str
:param topn: maximum number of returned results
:param key: sort key (defaults to 'BaseVolume')
:return: List of pairs
"""
summaries = sorted(
(s for s in exchange.get_market_summaries() if s['MarketName'].startswith(base_currency)),
key=lambda s: s.get(key) or 0.0,
reverse=True
)
return [s['MarketName'].replace('-', '_') for s in summaries[:topn]]
def cleanup(*args, **kwargs) -> None:
"""
Cleanup the application state und finish all pending tasks
:return: None
"""
telegram.send_msg('*Status:* `Stopping trader...`')
logger.info('Stopping trader and cleaning up modules...')
update_state(State.STOPPED)
persistence.cleanup()
telegram.cleanup()
exit(0)
def main():
"""
Loads and validates the config and handles the main loop
:return: None
"""
global _CONF
args = build_arg_parser().parse_args()
# Initialize logger
logging.basicConfig(
level=args.loglevel,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
)
logger.info(
'Starting freqtrade %s (loglevel=%s)',
__version__,
logging.getLevelName(args.loglevel)
)
# Load and validate configuration
with open(args.config) as file:
_CONF = json.load(file)
if 'internals' not in _CONF:
_CONF['internals'] = {}
logger.info('Validating configuration ...')
validate(_CONF, CONF_SCHEMA)
# Initialize all modules and start main loop
if args.dynamic_whitelist:
logger.info('Using dynamically generated whitelist. (--dynamic-whitelist detected)')
init(_CONF)
old_state = None
while True:
new_state = get_state()
# Log state transition
if new_state != old_state:
telegram.send_msg('*Status:* `{}`'.format(new_state.name.lower()))
logger.info('Changing state to: %s', new_state.name)
if new_state == State.STOPPED:
time.sleep(1)
elif new_state == State.RUNNING:
throttle(
_process,
min_secs=_CONF['internals'].get('process_throttle_secs', 10),
dynamic_whitelist=args.dynamic_whitelist,
)
old_state = new_state
if __name__ == '__main__':
main()

168
freqtrade/misc.py Normal file
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import argparse
import enum
import logging
from typing import Any, Callable
import time
from wrapt import synchronized
from freqtrade import __version__
logger = logging.getLogger(__name__)
class State(enum.Enum):
RUNNING = 0
STOPPED = 1
# Current application state
_STATE = State.STOPPED
@synchronized
def update_state(state: State) -> None:
"""
Updates the application state
:param state: new state
:return: None
"""
global _STATE
_STATE = state
@synchronized
def get_state() -> State:
"""
Gets the current application state
:return:
"""
return _STATE
def throttle(func: Callable[..., Any], min_secs: float, *args, **kwargs) -> Any:
"""
Throttles the given callable that it
takes at least `min_secs` to finish execution.
:param func: Any callable
:param min_secs: minimum execution time in seconds
:return: Any
"""
start = time.time()
result = func(*args, **kwargs)
end = time.time()
duration = max(min_secs - (end - start), 0.0)
logger.debug('Throttling %s for %.2f seconds', func.__name__, duration)
time.sleep(duration)
return result
def build_arg_parser() -> argparse.ArgumentParser:
""" Builds and returns an ArgumentParser instance """
parser = argparse.ArgumentParser(
description='Simple High Frequency Trading Bot for crypto currencies'
)
parser.add_argument(
'-c', '--config',
help='specify configuration file (default: config.json)',
dest='config',
default='config.json',
type=str,
metavar='PATH',
)
parser.add_argument(
'-v', '--verbose',
help='be verbose',
action='store_const',
dest='loglevel',
const=logging.DEBUG,
default=logging.INFO,
)
parser.add_argument(
'--version',
action='version',
version='%(prog)s {}'.format(__version__),
)
parser.add_argument(
'--dynamic-whitelist',
help='dynamically generate and update whitelist based on 24h BaseVolume',
action='store_true',
)
return parser
# Required json-schema for user specified config
CONF_SCHEMA = {
'type': 'object',
'properties': {
'max_open_trades': {'type': 'integer', 'minimum': 1},
'stake_currency': {'type': 'string', 'enum': ['BTC', 'ETH', 'USDT']},
'stake_amount': {'type': 'number', 'minimum': 0.0005},
'dry_run': {'type': 'boolean'},
'minimal_roi': {
'type': 'object',
'patternProperties': {
'^[0-9.]+$': {'type': 'number'}
},
'minProperties': 1
},
'stoploss': {'type': 'number', 'maximum': 0, 'exclusiveMaximum': True},
'bid_strategy': {
'type': 'object',
'properties': {
'ask_last_balance': {
'type': 'number',
'minimum': 0,
'maximum': 1,
'exclusiveMaximum': False
},
},
'required': ['ask_last_balance']
},
'exchange': {'$ref': '#/definitions/exchange'},
'telegram': {
'type': 'object',
'properties': {
'enabled': {'type': 'boolean'},
'token': {'type': 'string'},
'chat_id': {'type': 'string'},
},
'required': ['enabled', 'token', 'chat_id']
},
'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
'internals': {
'type': 'object',
'properties': {
'process_throttle_secs': {'type': 'number'}
}
}
},
'definitions': {
'exchange': {
'type': 'object',
'properties': {
'name': {'type': 'string'},
'key': {'type': 'string'},
'secret': {'type': 'string'},
'pair_whitelist': {
'type': 'array',
'items': {'type': 'string'},
'uniqueItems': True
}
},
'required': ['name', 'key', 'secret', 'pair_whitelist']
}
},
'anyOf': [
{'required': ['exchange']}
],
'required': [
'max_open_trades',
'stake_currency',
'stake_amount',
'dry_run',
'minimal_roi',
'bid_strategy',
'telegram'
]
}

112
freqtrade/persistence.py Normal file
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import logging
from datetime import datetime
from decimal import Decimal, getcontext
from typing import Optional, Dict
import arrow
from sqlalchemy import Boolean, Column, DateTime, Float, Integer, String, create_engine
from sqlalchemy.engine import Engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm.scoping import scoped_session
from sqlalchemy.orm.session import sessionmaker
from sqlalchemy.pool import StaticPool
logger = logging.getLogger(__name__)
_CONF = {}
_DECL_BASE = declarative_base()
def init(config: dict, engine: Optional[Engine] = None) -> None:
"""
Initializes this module with the given config,
registers all known command handlers
and starts polling for message updates
:param config: config to use
:param engine: database engine for sqlalchemy (Optional)
:return: None
"""
_CONF.update(config)
if not engine:
if _CONF.get('dry_run', False):
engine = create_engine('sqlite://',
connect_args={'check_same_thread': False},
poolclass=StaticPool,
echo=False)
else:
engine = create_engine('sqlite:///tradesv3.sqlite')
session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True))
Trade.session = session()
Trade.query = session.query_property()
_DECL_BASE.metadata.create_all(engine)
def cleanup() -> None:
"""
Flushes all pending operations to disk.
:return: None
"""
Trade.session.flush()
class Trade(_DECL_BASE):
__tablename__ = 'trades'
id = Column(Integer, primary_key=True)
exchange = Column(String, nullable=False)
pair = Column(String, nullable=False)
is_open = Column(Boolean, nullable=False, default=True)
fee = Column(Float, nullable=False, default=0.0)
open_rate = Column(Float)
close_rate = Column(Float)
close_profit = Column(Float)
stake_amount = Column(Float, nullable=False)
amount = Column(Float)
open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
close_date = Column(DateTime)
open_order_id = Column(String)
def __repr__(self):
return 'Trade(id={}, pair={}, amount={}, open_rate={}, open_since={})'.format(
self.id,
self.pair,
self.amount,
self.open_rate,
arrow.get(self.open_date).humanize() if self.is_open else 'closed'
)
def update(self, order: Dict) -> None:
"""
Updates this entity with amount and actual open/close rates.
:param order: order retrieved by exchange.get_order()
:return: None
"""
if not order['closed']:
return
logger.debug('Updating trade (id=%d) ...', self.id)
if order['type'] == 'LIMIT_BUY':
# Update open rate and actual amount
self.open_rate = order['rate']
self.amount = order['amount']
elif order['type'] == 'LIMIT_SELL':
# Set close rate and set actual profit
self.close_rate = order['rate']
self.close_profit = self.calc_profit()
self.close_date = datetime.utcnow()
else:
raise ValueError('Unknown order type: {}'.format(order['type']))
self.open_order_id = None
def calc_profit(self, rate: Optional[float] = None) -> float:
"""
Calculates the profit in percentage (including fee).
:param rate: rate to compare with (optional).
If rate is not set self.close_rate will be used
:return: profit in percentage as float
"""
getcontext().prec = 8
return float((Decimal(rate or self.close_rate) - Decimal(self.open_rate))
/ Decimal(self.open_rate) - Decimal(self.fee))

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freqtrade/rpc/telegram.py Normal file
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import logging
import re
from datetime import timedelta
from typing import Callable, Any
from pandas import DataFrame
from tabulate import tabulate
import arrow
from sqlalchemy import and_, func, text
from telegram import ParseMode, Bot, Update
from telegram.error import NetworkError
from telegram.ext import CommandHandler, Updater
from freqtrade import exchange, __version__
from freqtrade.misc import get_state, State, update_state
from freqtrade.persistence import Trade
# Remove noisy log messages
logging.getLogger('requests.packages.urllib3').setLevel(logging.INFO)
logging.getLogger('telegram').setLevel(logging.INFO)
logger = logging.getLogger(__name__)
_UPDATER: Updater = None
_CONF = {}
def init(config: dict) -> None:
"""
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
"""
global _UPDATER
_CONF.update(config)
if not is_enabled():
return
_UPDATER = Updater(token=config['telegram']['token'], workers=0)
# Register command handler and start telegram message polling
handles = [
CommandHandler('status', _status),
CommandHandler('profit', _profit),
CommandHandler('balance', _balance),
CommandHandler('start', _start),
CommandHandler('stop', _stop),
CommandHandler('forcesell', _forcesell),
CommandHandler('performance', _performance),
CommandHandler('count', _count),
CommandHandler('help', _help),
CommandHandler('version', _version),
]
for handle in handles:
_UPDATER.dispatcher.add_handler(handle)
_UPDATER.start_polling(
clean=True,
bootstrap_retries=3,
timeout=30,
read_latency=60,
)
logger.info(
'rpc.telegram is listening for following commands: %s',
[h.command for h in handles]
)
def cleanup() -> None:
"""
Stops all running telegram threads.
:return: None
"""
if not is_enabled():
return
_UPDATER.stop()
def is_enabled() -> bool:
"""
Returns True if the telegram module is activated, False otherwise
"""
return bool(_CONF['telegram'].get('enabled', False))
def authorized_only(command_handler: Callable[[Bot, Update], None]) -> Callable[..., Any]:
"""
Decorator to check if the message comes from the correct chat_id
:param command_handler: Telegram CommandHandler
:return: decorated function
"""
def wrapper(*args, **kwargs):
bot, update = kwargs.get('bot') or args[0], kwargs.get('update') or args[1]
# Reject unauthorized messages
chat_id = int(_CONF['telegram']['chat_id'])
if int(update.message.chat_id) != chat_id:
logger.info('Rejected unauthorized message from: %s', update.message.chat_id)
return wrapper
logger.info('Executing handler: %s for chat_id: %s', command_handler.__name__, chat_id)
try:
return command_handler(*args, **kwargs)
except BaseException:
logger.exception('Exception occurred within Telegram module')
return wrapper
@authorized_only
def _status(bot: Bot, update: Update) -> None:
"""
Handler for /status.
Returns the current TradeThread status
:param bot: telegram bot
:param update: message update
:return: None
"""
# Check if additional parameters are passed
params = update.message.text.replace('/status', '').split(' ') \
if update.message.text else []
if 'table' in params:
_status_table(bot, update)
return
# Fetch open trade
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if get_state() != State.RUNNING:
send_msg('*Status:* `trader is not running`', bot=bot)
elif not trades:
send_msg('*Status:* `no active trade`', bot=bot)
else:
for trade in trades:
order = None
if trade.open_order_id:
order = exchange.get_order(trade.open_order_id)
# calculate profit and send message to user
current_rate = exchange.get_ticker(trade.pair)['bid']
current_profit = trade.calc_profit(current_rate)
fmt_close_profit = '{:.2f}%'.format(
round(trade.close_profit * 100, 2)
) if trade.close_profit else None
message = """
*Trade ID:* `{trade_id}`
*Current Pair:* [{pair}]({market_url})
*Open Since:* `{date}`
*Amount:* `{amount}`
*Open Rate:* `{open_rate:.8f}`
*Close Rate:* `{close_rate}`
*Current Rate:* `{current_rate:.8f}`
*Close Profit:* `{close_profit}`
*Current Profit:* `{current_profit:.2f}%`
*Open Order:* `{open_order}`
""".format(
trade_id=trade.id,
pair=trade.pair,
market_url=exchange.get_pair_detail_url(trade.pair),
date=arrow.get(trade.open_date).humanize(),
open_rate=trade.open_rate,
close_rate=trade.close_rate,
current_rate=current_rate,
amount=round(trade.amount, 8),
close_profit=fmt_close_profit,
current_profit=round(current_profit * 100, 2),
open_order='{} ({})'.format(
order['remaining'], order['type']
) if order else None,
)
send_msg(message, bot=bot)
@authorized_only
def _status_table(bot: Bot, update: Update) -> None:
"""
Handler for /status table.
Returns the current TradeThread status in table format
:param bot: telegram bot
:param update: message update
:return: None
"""
# Fetch open trade
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if get_state() != State.RUNNING:
send_msg('*Status:* `trader is not running`', bot=bot)
elif not trades:
send_msg('*Status:* `no active order`', bot=bot)
else:
trades_list = []
for trade in trades:
# calculate profit and send message to user
current_rate = exchange.get_ticker(trade.pair)['bid']
trades_list.append([
trade.id,
trade.pair,
shorten_date(arrow.get(trade.open_date).humanize(only_distance=True)),
'{:.2f}'.format(100 * trade.calc_profit(current_rate))
])
columns = ['ID', 'Pair', 'Since', 'Profit']
df_statuses = DataFrame.from_records(trades_list, columns=columns)
df_statuses = df_statuses.set_index(columns[0])
message = tabulate(df_statuses, headers='keys', tablefmt='simple')
message = "<pre>{}</pre>".format(message)
send_msg(message, parse_mode=ParseMode.HTML)
@authorized_only
def _profit(bot: Bot, update: Update) -> None:
"""
Handler for /profit.
Returns a cumulative profit statistics.
:param bot: telegram bot
:param update: message update
:return: None
"""
trades = Trade.query.order_by(Trade.id).all()
profit_amounts = []
profits = []
durations = []
for trade in trades:
if not trade.open_rate:
continue
if trade.close_date:
durations.append((trade.close_date - trade.open_date).total_seconds())
if trade.close_profit:
profit = trade.close_profit
else:
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
profit = trade.calc_profit(current_rate)
profit_amounts.append(profit * trade.stake_amount)
profits.append(profit)
best_pair = Trade.session.query(Trade.pair, func.sum(Trade.close_profit).label('profit_sum')) \
.filter(Trade.is_open.is_(False)) \
.group_by(Trade.pair) \
.order_by(text('profit_sum DESC')) \
.first()
if not best_pair:
send_msg('*Status:* `no closed trade`', bot=bot)
return
bp_pair, bp_rate = best_pair
markdown_msg = """
*ROI:* `{profit_btc:.8f} ({profit:.2f}%)`
*Trade Count:* `{trade_count}`
*First Trade opened:* `{first_trade_date}`
*Latest Trade opened:* `{latest_trade_date}`
*Avg. Duration:* `{avg_duration}`
*Best Performing:* `{best_pair}: {best_rate:.2f}%`
""".format(
profit_btc=round(sum(profit_amounts), 8),
profit=round(sum(profits) * 100, 2),
trade_count=len(trades),
first_trade_date=arrow.get(trades[0].open_date).humanize(),
latest_trade_date=arrow.get(trades[-1].open_date).humanize(),
avg_duration=str(timedelta(seconds=sum(durations) / float(len(durations)))).split('.')[0],
best_pair=bp_pair,
best_rate=round(bp_rate * 100, 2),
)
send_msg(markdown_msg, bot=bot)
@authorized_only
def _balance(bot: Bot, update: Update) -> None:
"""
Handler for /balance
Returns current account balance per crypto
"""
output = ''
balances = [
c for c in exchange.get_balances()
if c['Balance'] or c['Available'] or c['Pending']
]
if not balances:
output = '`All balances are zero.`'
for currency in balances:
output += """*Currency*: {Currency}
*Available*: {Available}
*Balance*: {Balance}
*Pending*: {Pending}
""".format(**currency)
send_msg(output)
@authorized_only
def _start(bot: Bot, update: Update) -> None:
"""
Handler for /start.
Starts TradeThread
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() == State.RUNNING:
send_msg('*Status:* `already running`', bot=bot)
else:
update_state(State.RUNNING)
@authorized_only
def _stop(bot: Bot, update: Update) -> None:
"""
Handler for /stop.
Stops TradeThread
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() == State.RUNNING:
send_msg('`Stopping trader ...`', bot=bot)
update_state(State.STOPPED)
else:
send_msg('*Status:* `already stopped`', bot=bot)
@authorized_only
def _forcesell(bot: Bot, update: Update) -> None:
"""
Handler for /forcesell <id>.
Sells the given trade at current price
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() != State.RUNNING:
send_msg('`trader is not running`', bot=bot)
return
trade_id = update.message.text.replace('/forcesell', '').strip()
if trade_id == 'all':
# Execute sell for all open orders
for trade in Trade.query.filter(Trade.is_open.is_(True)).all():
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
from freqtrade.main import execute_sell
execute_sell(trade, current_rate)
return
# Query for trade
trade = Trade.query.filter(and_(
Trade.id == trade_id,
Trade.is_open.is_(True)
)).first()
if not trade:
send_msg('Invalid argument. See `/help` to view usage')
logger.warning('/forcesell: Invalid argument received')
return
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
from freqtrade.main import execute_sell
execute_sell(trade, current_rate)
@authorized_only
def _performance(bot: Bot, update: Update) -> None:
"""
Handler for /performance.
Shows a performance statistic from finished trades
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() != State.RUNNING:
send_msg('`trader is not running`', bot=bot)
return
pair_rates = Trade.session.query(Trade.pair, func.sum(Trade.close_profit).label('profit_sum')) \
.filter(Trade.is_open.is_(False)) \
.group_by(Trade.pair) \
.order_by(text('profit_sum DESC')) \
.all()
stats = '\n'.join('{index}.\t<code>{pair}\t{profit:.2f}%</code>'.format(
index=i + 1,
pair=pair,
profit=round(rate * 100, 2)
) for i, (pair, rate) in enumerate(pair_rates))
message = '<b>Performance:</b>\n{}'.format(stats)
logger.debug(message)
send_msg(message, parse_mode=ParseMode.HTML)
@authorized_only
def _count(bot: Bot, update: Update) -> None:
"""
Handler for /count.
Returns the number of trades running
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() != State.RUNNING:
send_msg('`trader is not running`', bot=bot)
return
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
message = tabulate({
'current': [len(trades)],
'max': [_CONF['max_open_trades']]
}, headers=['current', 'max'], tablefmt='simple')
message = "<pre>{}</pre>".format(message)
logger.debug(message)
send_msg(message, parse_mode=ParseMode.HTML)
@authorized_only
def _help(bot: Bot, update: Update) -> None:
"""
Handler for /help.
Show commands of the bot
:param bot: telegram bot
:param update: message update
:return: None
"""
message = """
*/start:* `Starts the trader`
*/stop:* `Stops the trader`
*/status [table]:* `Lists all open trades`
*table :* `will display trades in a table`
*/profit:* `Lists cumulative profit from all finished trades`
*/forcesell <trade_id>|all:* `Instantly sells the given trade or all trades, regardless of profit`
*/performance:* `Show performance of each finished trade grouped by pair`
*/count:* `Show number of trades running compared to allowed number of trades`
*/balance:* `Show account balance per currency`
*/help:* `This help message`
*/version:* `Show version`
"""
send_msg(message, bot=bot)
@authorized_only
def _version(bot: Bot, update: Update) -> None:
"""
Handler for /version.
Show version information
:param bot: telegram bot
:param update: message update
:return: None
"""
send_msg('*Version:* `{}`'.format(__version__), bot=bot)
def shorten_date(date):
"""
Trim the date so it fits on small screens
"""
new_date = re.sub('seconds?', 'sec', date)
new_date = re.sub('minutes?', 'min', new_date)
new_date = re.sub('hours?', 'h', new_date)
new_date = re.sub('days?', 'd', new_date)
new_date = re.sub('^an?', '1', new_date)
return new_date
def send_msg(msg: str, bot: Bot = None, parse_mode: ParseMode = ParseMode.MARKDOWN) -> None:
"""
Send given markdown message
:param msg: message
:param bot: alternative bot
:param parse_mode: telegram parse mode
:return: None
"""
if not is_enabled():
return
bot = bot or _UPDATER.bot
try:
bot.send_message(_CONF['telegram']['chat_id'], msg, parse_mode=parse_mode)
except NetworkError as error:
# Sometimes the telegram server resets the current connection,
# if this is the case we send the message again.
logger.warning(
'Got Telegram NetworkError: %s! Trying one more time.',
error.message
)
bot.send_message(_CONF['telegram']['chat_id'], msg, parse_mode=parse_mode)

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# pragma pylint: disable=missing-docstring
import json
from datetime import datetime
from unittest.mock import MagicMock
import pytest
from jsonschema import validate
from telegram import Message, Chat, Update
from freqtrade.misc import CONF_SCHEMA
@pytest.fixture(scope="module")
def default_conf():
""" Returns validated configuration suitable for most tests """
configuration = {
"max_open_trades": 1,
"stake_currency": "BTC",
"stake_amount": 0.05,
"dry_run": True,
"minimal_roi": {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
},
"stoploss": -0.05,
"bid_strategy": {
"ask_last_balance": 0.0
},
"exchange": {
"name": "bittrex",
"enabled": True,
"key": "key",
"secret": "secret",
"pair_whitelist": [
"BTC_ETH",
"BTC_TKN",
"BTC_TRST",
"BTC_SWT",
"BTC_BCC"
]
},
"telegram": {
"enabled": True,
"token": "token",
"chat_id": "0"
},
"initial_state": "running"
}
validate(configuration, CONF_SCHEMA)
return configuration
@pytest.fixture(scope="module")
def backtest_conf():
return {
"minimal_roi": {
"40": 0.0,
"30": 0.01,
"20": 0.02,
"0": 0.04
},
"stoploss": -0.05
}
@pytest.fixture(scope="module")
def backdata():
result = {}
for pair in ['btc-neo', 'btc-eth', 'btc-omg', 'btc-edg', 'btc-pay',
'btc-pivx', 'btc-qtum', 'btc-mtl', 'btc-etc', 'btc-ltc']:
with open('freqtrade/tests/testdata/' + pair + '.json') as data_file:
result[pair] = json.load(data_file)
return result
@pytest.fixture
def update():
_update = Update(0)
_update.message = Message(0, 0, datetime.utcnow(), Chat(0, 0))
return _update
@pytest.fixture
def ticker():
return MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061,
})
@pytest.fixture
def health():
return MagicMock(return_value=[{
'Currency': 'BTC',
'IsActive': True,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}, {
'Currency': 'ETH',
'IsActive': True,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}, {
'Currency': 'TRST',
'IsActive': True,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}, {
'Currency': 'SWT',
'IsActive': True,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}, {
'Currency': 'BCC',
'IsActive': False,
'LastChecked': '2017-11-13T20:15:00.00',
'Notice': None
}])
@pytest.fixture
def limit_buy_order():
return {
'id': 'mocked_limit_buy',
'type': 'LIMIT_BUY',
'pair': 'mocked',
'opened': datetime.utcnow(),
'rate': 0.07256061,
'amount': 206.43811673387373,
'remaining': 0.0,
'closed': datetime.utcnow(),
}
@pytest.fixture
def limit_sell_order():
return {
'id': 'mocked_limit_sell',
'type': 'LIMIT_SELL',
'pair': 'mocked',
'opened': datetime.utcnow(),
'rate': 0.0802134,
'amount': 206.43811673387373,
'remaining': 0.0,
'closed': datetime.utcnow(),
}

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# pragma pylint: disable=missing-docstring
from datetime import datetime
import json
import pytest
from pandas import DataFrame
from freqtrade.analyze import parse_ticker_dataframe, populate_buy_trend, populate_indicators, \
get_buy_signal
@pytest.fixture
def result():
with open('freqtrade/tests/testdata/btc-eth.json') as data_file:
return parse_ticker_dataframe(json.load(data_file))
def test_dataframe_correct_columns(result):
assert result.columns.tolist() == \
['close', 'high', 'low', 'open', 'date', 'volume']
def test_dataframe_correct_length(result):
assert len(result.index) == 5751
def test_populates_buy_trend(result):
dataframe = populate_buy_trend(populate_indicators(result))
assert 'buy' in dataframe.columns
assert 'buy_price' in dataframe.columns
def test_returns_latest_buy_signal(mocker):
buydf = DataFrame([{'buy': 1, 'date': datetime.today()}])
mocker.patch('freqtrade.analyze.analyze_ticker', return_value=buydf)
assert get_buy_signal('BTC-ETH')
buydf = DataFrame([{'buy': 0, 'date': datetime.today()}])
mocker.patch('freqtrade.analyze.analyze_ticker', return_value=buydf)
assert not get_buy_signal('BTC-ETH')

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# pragma pylint: disable=missing-docstring
import logging
import os
import pytest
import arrow
from pandas import DataFrame
from freqtrade import exchange
from freqtrade.analyze import analyze_ticker
from freqtrade.exchange import Bittrex
from freqtrade.main import should_sell
from freqtrade.persistence import Trade
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
def format_results(results):
return 'Made {} buys. Average profit {:.2f}%. Total profit was {:.3f}. Average duration {:.1f} mins.'.format(
len(results.index), results.profit.mean() * 100.0, results.profit.sum(), results.duration.mean() * 5)
def print_pair_results(pair, results):
print('For currency {}:'.format(pair))
print(format_results(results[results.currency == pair]))
def backtest(backtest_conf, backdata, mocker):
trades = []
exchange._API = Bittrex({'key': '', 'secret': ''})
mocked_history = mocker.patch('freqtrade.analyze.get_ticker_history')
mocker.patch.dict('freqtrade.main._CONF', backtest_conf)
mocker.patch('arrow.utcnow', return_value=arrow.get('2017-08-20T14:50:00'))
for pair, pair_data in backdata.items():
mocked_history.return_value = pair_data
ticker = analyze_ticker(pair)[['close', 'date', 'buy']].copy()
# for each buy point
for row in ticker[ticker.buy == 1].itertuples(index=True):
trade = Trade(
open_rate=row.close,
open_date=row.date,
amount=1,
fee=exchange.get_fee() * 2
)
# calculate win/lose forwards from buy point
for row2 in ticker[row.Index:].itertuples(index=True):
if should_sell(trade, row2.close, row2.date):
current_profit = trade.calc_profit(row2.close)
trades.append((pair, current_profit, row2.Index - row.Index))
break
labels = ['currency', 'profit', 'duration']
results = DataFrame.from_records(trades, columns=labels)
return results
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
def test_backtest(backtest_conf, backdata, mocker, report=True):
results = backtest(backtest_conf, backdata, mocker)
print('====================== BACKTESTING REPORT ================================')
for pair in backdata:
print_pair_results(pair, results)
print('TOTAL OVER ALL TRADES:')
print(format_results(results))

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# pragma pylint: disable=missing-docstring
from unittest.mock import MagicMock
import pytest
from freqtrade.exchange import validate_pairs
def test_validate_pairs(default_conf, mocker):
api_mock = MagicMock()
api_mock.get_markets = MagicMock(return_value=[
'BTC_ETH', 'BTC_TKN', 'BTC_TRST', 'BTC_SWT', 'BTC_BCC',
])
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
validate_pairs(default_conf['exchange']['pair_whitelist'])
def test_validate_pairs_not_available(default_conf, mocker):
api_mock = MagicMock()
api_mock.get_markets = MagicMock(return_value=[])
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
with pytest.raises(RuntimeError, match=r'not available'):
validate_pairs(default_conf['exchange']['pair_whitelist'])
def test_validate_pairs_not_compatible(default_conf, mocker):
api_mock = MagicMock()
api_mock.get_markets = MagicMock(return_value=['BTC_ETH', 'BTC_TKN', 'BTC_TRST', 'BTC_SWT'])
default_conf['stake_currency'] = 'ETH'
mocker.patch('freqtrade.exchange._API', api_mock)
mocker.patch.dict('freqtrade.exchange._CONF', default_conf)
with pytest.raises(RuntimeError, match=r'not compatible'):
validate_pairs(default_conf['exchange']['pair_whitelist'])

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# pragma pylint: disable=missing-docstring
import logging
import os
from functools import reduce
from math import exp
from operator import itemgetter
import pytest
from hyperopt import fmin, tpe, hp, Trials, STATUS_OK
from pandas import DataFrame
from freqtrade.tests.test_backtesting import backtest, format_results
from freqtrade.vendor.qtpylib.indicators import crossed_above
logging.disable(logging.DEBUG) # disable debug logs that slow backtesting a lot
# set TARGET_TRADES to suit your number concurrent trades so its realistic to 20days of data
TARGET_TRADES = 1300
TOTAL_TRIES = 4
current_tries = 0
def buy_strategy_generator(params):
def populate_buy_trend(dataframe: DataFrame) -> DataFrame:
conditions = []
# GUARDS AND TRENDS
if params['uptrend_long_ema']['enabled']:
conditions.append(dataframe['ema50'] > dataframe['ema100'])
if params['uptrend_short_ema']['enabled']:
conditions.append(dataframe['ema5'] > dataframe['ema10'])
if params['mfi']['enabled']:
conditions.append(dataframe['mfi'] < params['mfi']['value'])
if params['fastd']['enabled']:
conditions.append(dataframe['fastd'] < params['fastd']['value'])
if params['adx']['enabled']:
conditions.append(dataframe['adx'] > params['adx']['value'])
if params['rsi']['enabled']:
conditions.append(dataframe['rsi'] < params['rsi']['value'])
if params['over_sar']['enabled']:
conditions.append(dataframe['close'] > dataframe['sar'])
if params['green_candle']['enabled']:
conditions.append(dataframe['close'] > dataframe['open'])
if params['uptrend_sma']['enabled']:
prevsma = dataframe['sma'].shift(1)
conditions.append(dataframe['sma'] > prevsma)
# TRIGGERS
triggers = {
'lower_bb': dataframe['tema'] <= dataframe['blower'],
'faststoch10': (crossed_above(dataframe['fastd'], 10.0)),
'ao_cross_zero': (crossed_above(dataframe['ao'], 0.0)),
'ema5_cross_ema10': (crossed_above(dataframe['ema5'], dataframe['ema10'])),
'macd_cross_signal': (crossed_above(dataframe['macd'], dataframe['macdsignal'])),
'sar_reversal': (crossed_above(dataframe['close'], dataframe['sar'])),
'stochf_cross': (crossed_above(dataframe['fastk'], dataframe['fastd'])),
'ht_sine': (crossed_above(dataframe['htleadsine'], dataframe['htsine'])),
}
conditions.append(triggers.get(params['trigger']['type']))
dataframe.loc[
reduce(lambda x, y: x & y, conditions),
'buy'] = 1
dataframe.loc[dataframe['buy'] == 1, 'buy_price'] = dataframe['close']
return dataframe
return populate_buy_trend
@pytest.mark.skipif(not os.environ.get('BACKTEST', False), reason="BACKTEST not set")
def test_hyperopt(backtest_conf, backdata, mocker):
mocked_buy_trend = mocker.patch('freqtrade.analyze.populate_buy_trend')
def optimizer(params):
mocked_buy_trend.side_effect = buy_strategy_generator(params)
results = backtest(backtest_conf, backdata, mocker)
result = format_results(results)
total_profit = results.profit.sum() * 1000
trade_count = len(results.index)
trade_loss = 1 - 0.4 * exp(-(trade_count - TARGET_TRADES) ** 2 / 10 ** 5.2)
profit_loss = max(0, 1 - total_profit / 15000) # max profit 15000
global current_tries
current_tries += 1
print('{}/{}: {}'.format(current_tries, TOTAL_TRIES, result))
return {
'loss': trade_loss + profit_loss,
'status': STATUS_OK,
'result': result
}
space = {
'mfi': hp.choice('mfi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('mfi-value', 5, 25, 1)}
]),
'fastd': hp.choice('fastd', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('fastd-value', 10, 50, 1)}
]),
'adx': hp.choice('adx', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('adx-value', 15, 50, 1)}
]),
'rsi': hp.choice('rsi', [
{'enabled': False},
{'enabled': True, 'value': hp.quniform('rsi-value', 20, 40, 1)}
]),
'uptrend_long_ema': hp.choice('uptrend_long_ema', [
{'enabled': False},
{'enabled': True}
]),
'uptrend_short_ema': hp.choice('uptrend_short_ema', [
{'enabled': False},
{'enabled': True}
]),
'over_sar': hp.choice('over_sar', [
{'enabled': False},
{'enabled': True}
]),
'green_candle': hp.choice('green_candle', [
{'enabled': False},
{'enabled': True}
]),
'uptrend_sma': hp.choice('uptrend_sma', [
{'enabled': False},
{'enabled': True}
]),
'trigger': hp.choice('trigger', [
{'type': 'lower_bb'},
{'type': 'faststoch10'},
{'type': 'ao_cross_zero'},
{'type': 'ema5_cross_ema10'},
{'type': 'macd_cross_signal'},
{'type': 'sar_reversal'},
{'type': 'stochf_cross'},
{'type': 'ht_sine'},
]),
}
trials = Trials()
best = fmin(fn=optimizer, space=space, algo=tpe.suggest, max_evals=TOTAL_TRIES, trials=trials)
print('\n\n\n\n==================== HYPEROPT BACKTESTING REPORT ==============================')
print('Best parameters {}'.format(best))
newlist = sorted(trials.results, key=itemgetter('loss'))
print('Result: {}'.format(newlist[0]['result']))

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# pragma pylint: disable=missing-docstring
import copy
from unittest.mock import MagicMock
import pytest
import requests
from sqlalchemy import create_engine
from freqtrade.exchange import Exchanges
from freqtrade.main import create_trade, handle_trade, close_trade_if_fulfilled, init, \
get_target_bid, _process
from freqtrade.misc import get_state, State
from freqtrade.persistence import Trade
def test_process_trade_creation(default_conf, ticker, health, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_wallet_health=health,
buy=MagicMock(return_value='mocked_limit_buy'))
init(default_conf, create_engine('sqlite://'))
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
assert len(trades) == 0
result = _process()
assert result is True
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
assert len(trades) == 1
trade = trades[0]
assert trade is not None
assert trade.stake_amount == default_conf['stake_amount']
assert trade.is_open
assert trade.open_date is not None
assert trade.exchange == Exchanges.BITTREX.name
assert trade.open_rate == 0.072661
assert trade.amount == 0.6864067381401302
def test_process_exchange_failures(default_conf, ticker, health, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
sleep_mock = mocker.patch('time.sleep', side_effect=lambda _: None)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_wallet_health=health,
buy=MagicMock(side_effect=requests.exceptions.RequestException))
init(default_conf, create_engine('sqlite://'))
result = _process()
assert result is False
assert sleep_mock.has_calls()
def test_process_runtime_error(default_conf, ticker, health, mocker):
msg_mock = MagicMock()
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=msg_mock)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_wallet_health=health,
buy=MagicMock(side_effect=RuntimeError))
init(default_conf, create_engine('sqlite://'))
assert get_state() == State.RUNNING
result = _process()
assert result is False
assert get_state() == State.STOPPED
assert 'RuntimeError' in msg_mock.call_args_list[-1][0][0]
def test_process_trade_handling(default_conf, ticker, limit_buy_order, health, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
get_wallet_health=health,
buy=MagicMock(return_value='mocked_limit_buy'),
get_order=MagicMock(return_value=limit_buy_order))
init(default_conf, create_engine('sqlite://'))
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
assert len(trades) == 0
result = _process()
assert result is True
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
assert len(trades) == 1
result = _process()
assert result is False
def test_create_trade(default_conf, ticker, limit_buy_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_limit_buy'))
# Save state of current whitelist
whitelist = copy.deepcopy(default_conf['exchange']['pair_whitelist'])
init(default_conf, create_engine('sqlite://'))
trade = create_trade(15.0)
Trade.session.add(trade)
Trade.session.flush()
assert trade is not None
assert trade.stake_amount == 15.0
assert trade.is_open
assert trade.open_date is not None
assert trade.exchange == Exchanges.BITTREX.name
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
assert trade.open_rate == 0.07256061
assert trade.amount == 206.43811673387373
assert whitelist == default_conf['exchange']['pair_whitelist']
def test_create_trade_no_stake_amount(default_conf, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_limit_buy'),
get_balance=MagicMock(return_value=default_conf['stake_amount'] * 0.5))
with pytest.raises(ValueError, match=r'.*stake amount.*'):
create_trade(default_conf['stake_amount'])
def test_create_trade_no_pairs(default_conf, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_limit_buy'))
with pytest.raises(ValueError, match=r'.*No pair in whitelist.*'):
conf = copy.deepcopy(default_conf)
conf['exchange']['pair_whitelist'] = []
mocker.patch.dict('freqtrade.main._CONF', conf)
create_trade(default_conf['stake_amount'])
def test_handle_trade(default_conf, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=MagicMock(return_value={
'bid': 0.17256061,
'ask': 0.172661,
'last': 0.17256061
}),
buy=MagicMock(return_value='mocked_limit_buy'),
sell=MagicMock(return_value='mocked_limit_sell'))
init(default_conf, create_engine('sqlite://'))
trade = create_trade(15.0)
trade.update(limit_buy_order)
Trade.session.add(trade)
Trade.session.flush()
trade = Trade.query.filter(Trade.is_open.is_(True)).first()
assert trade
handle_trade(trade)
assert trade.open_order_id == 'mocked_limit_sell'
assert close_trade_if_fulfilled(trade) is False
# Simulate fulfilled LIMIT_SELL order for trade
trade.update(limit_sell_order)
assert trade.close_rate == 0.0802134
assert trade.close_profit == 0.10046755
assert trade.close_date is not None
def test_close_trade(default_conf, ticker, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
mocker.patch.multiple('freqtrade.main.telegram', init=MagicMock(), send_msg=MagicMock())
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_limit_buy'))
# Create trade and sell it
init(default_conf, create_engine('sqlite://'))
trade = create_trade(15.0)
trade.update(limit_buy_order)
trade.update(limit_sell_order)
Trade.session.add(trade)
Trade.session.flush()
trade = Trade.query.filter(Trade.is_open.is_(True)).first()
assert trade
# Simulate that there is no open order
trade.open_order_id = None
closed = close_trade_if_fulfilled(trade)
assert closed
assert not trade.is_open
with pytest.raises(ValueError, match=r'.*closed trade.*'):
handle_trade(trade)
def test_balance_fully_ask_side(mocker):
mocker.patch.dict('freqtrade.main._CONF', {'bid_strategy': {'ask_last_balance': 0.0}})
assert get_target_bid({'ask': 20, 'last': 10}) == 20
def test_balance_fully_last_side(mocker):
mocker.patch.dict('freqtrade.main._CONF', {'bid_strategy': {'ask_last_balance': 1.0}})
assert get_target_bid({'ask': 20, 'last': 10}) == 10
def test_balance_bigger_last_ask(mocker):
mocker.patch.dict('freqtrade.main._CONF', {'bid_strategy': {'ask_last_balance': 1.0}})
assert get_target_bid({'ask': 5, 'last': 10}) == 5

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# pragma pylint: disable=missing-docstring
import time
from freqtrade.misc import throttle
def test_throttle():
def func():
return 42
start = time.time()
result = throttle(func, 0.1)
end = time.time()
assert result == 42
assert end - start > 0.1
result = throttle(func, -1)
assert result == 42

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# pragma pylint: disable=missing-docstring
import pytest
from freqtrade.exchange import Exchanges
from freqtrade.persistence import Trade
def test_update(limit_buy_order, limit_sell_order):
trade = Trade(
pair='BTC_ETH',
stake_amount=1.00,
fee=0.1,
exchange=Exchanges.BITTREX,
)
assert trade.open_order_id is None
assert trade.open_rate is None
assert trade.close_profit is None
assert trade.close_date is None
trade.open_order_id = 'something'
trade.update(limit_buy_order)
assert trade.open_order_id is None
assert trade.open_rate == 0.07256061
assert trade.close_profit is None
assert trade.close_date is None
trade.open_order_id = 'something'
trade.update(limit_sell_order)
assert trade.open_order_id is None
assert trade.open_rate == 0.07256061
assert trade.close_profit == 0.00546755
assert trade.close_date is not None
def test_update_open_order(limit_buy_order):
trade = Trade(
pair='BTC_ETH',
stake_amount=1.00,
fee=0.1,
exchange=Exchanges.BITTREX,
)
assert trade.open_order_id is None
assert trade.open_rate is None
assert trade.close_profit is None
assert trade.close_date is None
limit_buy_order['closed'] = False
trade.update(limit_buy_order)
assert trade.open_order_id is None
assert trade.open_rate is None
assert trade.close_profit is None
assert trade.close_date is None
def test_update_invalid_order(limit_buy_order):
trade = Trade(
pair='BTC_ETH',
stake_amount=1.00,
fee=0.1,
exchange=Exchanges.BITTREX,
)
limit_buy_order['type'] = 'invalid'
with pytest.raises(ValueError, match=r'Unknown order type'):
trade.update(limit_buy_order)

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# pragma pylint: disable=missing-docstring, too-many-arguments, too-many-ancestors
import re
from datetime import datetime
from random import randint
from unittest.mock import MagicMock
import pytest
from sqlalchemy import create_engine
from telegram import Update, Message, Chat
from telegram.error import NetworkError
from freqtrade import __version__
from freqtrade.main import init, create_trade
from freqtrade.misc import update_state, State, get_state
from freqtrade.persistence import Trade
from freqtrade.rpc import telegram
from freqtrade.rpc.telegram import (
_status, _status_table, _profit, _forcesell, _performance, _count, _start, _stop, _balance,
authorized_only, _help, is_enabled, send_msg,
_version)
def test_is_enabled(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
default_conf['telegram']['enabled'] = False
assert is_enabled() is False
def test_init_disabled(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
default_conf['telegram']['enabled'] = False
telegram.init(default_conf)
def test_authorized_only(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
chat = Chat(0, 0)
update = Update(randint(1, 100))
update.message = Message(randint(1, 100), 0, datetime.utcnow(), chat)
state = {'called': False}
@authorized_only
def dummy_handler(*args, **kwargs) -> None:
state['called'] = True
dummy_handler(MagicMock(), update)
assert state['called'] is True
def test_authorized_only_unauthorized(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
chat = Chat(0xdeadbeef, 0)
update = Update(randint(1, 100))
update.message = Message(randint(1, 100), 0, datetime.utcnow(), chat)
state = {'called': False}
@authorized_only
def dummy_handler(*args, **kwargs) -> None:
state['called'] = True
dummy_handler(MagicMock(), update)
assert state['called'] is False
def test_authorized_only_exception(default_conf, mocker):
mocker.patch.dict('freqtrade.rpc.telegram._CONF', default_conf)
update = Update(randint(1, 100))
update.message = Message(randint(1, 100), 0, datetime.utcnow(), Chat(0, 0))
@authorized_only
def dummy_handler(*args, **kwargs) -> None:
raise Exception('test')
dummy_handler(MagicMock(), update)
def test_status_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
_status(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'trader is not running' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
update_state(State.RUNNING)
_status(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'no active trade' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
# Create some test data
trade = create_trade(15.0)
assert trade
Trade.session.add(trade)
Trade.session.flush()
# Trigger status while we have a fulfilled order for the open trade
_status(bot=MagicMock(), update=update)
assert msg_mock.call_count == 2
assert '[BTC_ETH]' in msg_mock.call_args_list[-1][0][0]
def test_status_table_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_order_id'))
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
_status_table(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'trader is not running' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
update_state(State.RUNNING)
_status_table(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'no active order' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
# Create some test data
trade = create_trade(15.0)
assert trade
Trade.session.add(trade)
Trade.session.flush()
_status_table(bot=MagicMock(), update=update)
text = re.sub('</?pre>', '', msg_mock.call_args_list[-1][0][0])
line = text.split("\n")
fields = re.sub('[ ]+', ' ', line[2].strip()).split(' ')
assert int(fields[0]) == 1
assert fields[1] == 'BTC_ETH'
assert msg_mock.call_count == 2
def test_profit_handle(default_conf, update, ticker, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
_profit(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'no closed trade' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
# Create some test data
trade = create_trade(15.0)
assert trade
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
_profit(bot=MagicMock(), update=update)
assert msg_mock.call_count == 2
assert 'no closed trade' in msg_mock.call_args_list[-1][0][0]
msg_mock.reset_mock()
# Simulate fulfilled LIMIT_SELL order for trade
trade.update(limit_sell_order)
trade.close_date = datetime.utcnow()
trade.is_open = False
Trade.session.add(trade)
Trade.session.flush()
_profit(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '*ROI:* `1.50701325 (10.05%)`' in msg_mock.call_args_list[-1][0][0]
assert 'Best Performing:* `BTC_ETH: 10.05%`' in msg_mock.call_args_list[-1][0][0]
def test_forcesell_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
# Create some test data
trade = create_trade(15.0)
assert trade
Trade.session.add(trade)
Trade.session.flush()
update.message.text = '/forcesell 1'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 2
assert 'Selling [BTC/ETH]' in msg_mock.call_args_list[-1][0][0]
assert '0.07256061 (profit: ~-0.64%)' in msg_mock.call_args_list[-1][0][0]
def test_forcesell_all_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
# Create some test data
for _ in range(4):
Trade.session.add(create_trade(15.0))
Trade.session.flush()
msg_mock.reset_mock()
update.message.text = '/forcesell all'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 4
for args in msg_mock.call_args_list:
assert '0.07256061 (profit: ~-0.64%)' in args[0][0]
def test_forcesell_handle_invalid(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock())
init(default_conf, create_engine('sqlite://'))
# Trader is not running
update_state(State.STOPPED)
update.message.text = '/forcesell 1'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'not running' in msg_mock.call_args_list[0][0][0]
# No argument
msg_mock.reset_mock()
update_state(State.RUNNING)
update.message.text = '/forcesell'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'Invalid argument' in msg_mock.call_args_list[0][0][0]
# Invalid argument
msg_mock.reset_mock()
update_state(State.RUNNING)
update.message.text = '/forcesell 123456'
_forcesell(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'Invalid argument.' in msg_mock.call_args_list[0][0][0]
def test_performance_handle(
default_conf, update, ticker, limit_buy_order, limit_sell_order, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker)
init(default_conf, create_engine('sqlite://'))
# Create some test data
trade = create_trade(15.0)
assert trade
# Simulate fulfilled LIMIT_BUY order for trade
trade.update(limit_buy_order)
# Simulate fulfilled LIMIT_SELL order for trade
trade.update(limit_sell_order)
trade.close_date = datetime.utcnow()
trade.is_open = False
Trade.session.add(trade)
Trade.session.flush()
_performance(bot=MagicMock(), update=update)
assert msg_mock.call_count == 2
assert 'Performance' in msg_mock.call_args_list[-1][0][0]
assert '<code>BTC_ETH\t10.05%</code>' in msg_mock.call_args_list[-1][0][0]
def test_count_handle(default_conf, update, ticker, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple(
'freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock(),
get_ticker=ticker,
buy=MagicMock(return_value='mocked_order_id'))
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
_count(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'not running' in msg_mock.call_args_list[0][0][0]
msg_mock.reset_mock()
update_state(State.RUNNING)
# Create some test data
Trade.session.add(create_trade(15.0))
Trade.session.flush()
msg_mock.reset_mock()
_count(bot=MagicMock(), update=update)
msg = '<pre> current max\n--------- -----\n 1 {}</pre>'.format(
default_conf['max_open_trades']
)
assert msg in msg_mock.call_args_list[0][0][0]
def test_performance_handle_invalid(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch('freqtrade.main.get_buy_signal', side_effect=lambda _: True)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
validate_pairs=MagicMock())
init(default_conf, create_engine('sqlite://'))
# Trader is not running
update_state(State.STOPPED)
_performance(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert 'not running' in msg_mock.call_args_list[0][0][0]
def test_start_handle(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
_CONF=default_conf,
init=MagicMock())
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
assert get_state() == State.STOPPED
_start(bot=MagicMock(), update=update)
assert get_state() == State.RUNNING
assert msg_mock.call_count == 0
def test_start_handle_already_running(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
_CONF=default_conf,
init=MagicMock())
init(default_conf, create_engine('sqlite://'))
update_state(State.RUNNING)
assert get_state() == State.RUNNING
_start(bot=MagicMock(), update=update)
assert get_state() == State.RUNNING
assert msg_mock.call_count == 1
assert 'already running' in msg_mock.call_args_list[0][0][0]
def test_stop_handle(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
_CONF=default_conf,
init=MagicMock())
init(default_conf, create_engine('sqlite://'))
update_state(State.RUNNING)
assert get_state() == State.RUNNING
_stop(bot=MagicMock(), update=update)
assert get_state() == State.STOPPED
assert msg_mock.call_count == 1
assert 'Stopping trader' in msg_mock.call_args_list[0][0][0]
def test_stop_handle_already_stopped(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
_CONF=default_conf,
init=MagicMock())
init(default_conf, create_engine('sqlite://'))
update_state(State.STOPPED)
assert get_state() == State.STOPPED
_stop(bot=MagicMock(), update=update)
assert get_state() == State.STOPPED
assert msg_mock.call_count == 1
assert 'already stopped' in msg_mock.call_args_list[0][0][0]
def test_balance_handle(default_conf, update, mocker):
mock_balance = [{
'Currency': 'BTC',
'Balance': 10.0,
'Available': 12.0,
'Pending': 0.0,
'CryptoAddress': 'XXXX',
}, {
'Currency': 'ETH',
'Balance': 0.0,
'Available': 0.0,
'Pending': 0.0,
'CryptoAddress': 'XXXX',
}]
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
mocker.patch.multiple('freqtrade.main.exchange',
get_balances=MagicMock(return_value=mock_balance))
_balance(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '*Currency*: BTC' in msg_mock.call_args_list[0][0][0]
assert 'Balance' in msg_mock.call_args_list[0][0][0]
def test_help_handle(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
_help(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '*/help:* `This help message`' in msg_mock.call_args_list[0][0][0]
def test_version_handle(default_conf, update, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
msg_mock = MagicMock()
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock(),
send_msg=msg_mock)
_version(bot=MagicMock(), update=update)
assert msg_mock.call_count == 1
assert '*Version:* `{}`'.format(__version__) in msg_mock.call_args_list[0][0][0]
def test_send_msg(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock())
bot = MagicMock()
send_msg('test', bot)
assert len(bot.method_calls) == 0
bot.reset_mock()
default_conf['telegram']['enabled'] = True
send_msg('test', bot)
assert len(bot.method_calls) == 1
def test_send_msg_network_error(default_conf, mocker):
mocker.patch.dict('freqtrade.main._CONF', default_conf)
mocker.patch.multiple('freqtrade.main.telegram',
_CONF=default_conf,
init=MagicMock())
default_conf['telegram']['enabled'] = True
bot = MagicMock()
bot.send_message = MagicMock(side_effect=NetworkError('Oh snap'))
with pytest.raises(NetworkError, match=r'Oh snap'):
send_msg('test', bot)
# Bot should've tried to send it twice
assert len(bot.method_calls) == 2

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#!/usr/bin/env python3
"""This script generate json data from bittrex"""
import json
from os import path
from freqtrade import exchange
from freqtrade.exchange import Bittrex
PAIRS = ['BTC-OK', 'BTC-NEO', 'BTC-DASH', 'BTC-ETC', 'BTC-ETH', 'BTC-SNT']
TICKER_INTERVAL = 1 # ticker interval in minutes (currently implemented: 1 and 5)
OUTPUT_DIR = path.dirname(path.realpath(__file__))
# Init Bittrex exchange
exchange._API = Bittrex({'key': '', 'secret': ''})
for pair in PAIRS:
data = exchange.get_ticker_history(pair, TICKER_INTERVAL)
filename = path.join(OUTPUT_DIR, '{}-{}m.json'.format(
pair.lower(),
TICKER_INTERVAL,
))
with open(filename, 'w') as fp:
json.dump(data, fp)

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#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# QTPyLib: Quantitative Trading Python Library
# https://github.com/ranaroussi/qtpylib
#
# Copyright 2016 Ran Aroussi
#
# Licensed under the GNU Lesser General Public License, v3.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.gnu.org/licenses/lgpl-3.0.en.html
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
import numpy as np
import pandas as pd
import warnings
import sys
from datetime import datetime, timedelta
from pandas.core.base import PandasObject
# =============================================
# check min, python version
if sys.version_info < (3, 4):
raise SystemError("QTPyLib requires Python version >= 3.4")
# =============================================
warnings.simplefilter(action="ignore", category=RuntimeWarning)
# =============================================
def numpy_rolling_window(data, window):
shape = data.shape[:-1] + (data.shape[-1] - window + 1, window)
strides = data.strides + (data.strides[-1],)
return np.lib.stride_tricks.as_strided(data, shape=shape, strides=strides)
def numpy_rolling_series(func):
def func_wrapper(data, window, as_source=False):
series = data.values if isinstance(data, pd.Series) else data
new_series = np.empty(len(series)) * np.nan
calculated = func(series, window)
new_series[-len(calculated):] = calculated
if as_source and isinstance(data, pd.Series):
return pd.Series(index=data.index, data=new_series)
return new_series
return func_wrapper
@numpy_rolling_series
def numpy_rolling_mean(data, window, as_source=False):
return np.mean(numpy_rolling_window(data, window), -1)
@numpy_rolling_series
def numpy_rolling_std(data, window, as_source=False):
return np.std(numpy_rolling_window(data, window), -1)
# ---------------------------------------------
def session(df, start='17:00', end='16:00'):
""" remove previous globex day from df """
if len(df) == 0:
return df
# get start/end/now as decimals
int_start = list(map(int, start.split(':')))
int_start = (int_start[0] + int_start[1] - 1 / 100) - 0.0001
int_end = list(map(int, end.split(':')))
int_end = int_end[0] + int_end[1] / 100
int_now = (df[-1:].index.hour[0] + (df[:1].index.minute[0]) / 100)
# same-dat session?
is_same_day = int_end > int_start
# set pointers
curr = prev = df[-1:].index[0].strftime('%Y-%m-%d')
# globex/forex session
if not is_same_day:
prev = (datetime.strptime(curr, '%Y-%m-%d') -
timedelta(1)).strftime('%Y-%m-%d')
# slice
if int_now >= int_start:
df = df[df.index >= curr + ' ' + start]
else:
df = df[df.index >= prev + ' ' + start]
return df.copy()
# ---------------------------------------------
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'] = (
(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)
return pd.DataFrame(
index=bars.index,
data={
'open': bars['ha_open'],
'high': bars['ha_high'],
'low': bars['ha_low'],
'close': bars['ha_close']})
# ---------------------------------------------
def tdi(series, rsi_len=13, bollinger_len=34, rsi_smoothing=2,
rsi_signal_len=7, bollinger_std=1.6185):
rsi_series = rsi(series, rsi_len)
bb_series = bollinger_bands(rsi_series, bollinger_len, bollinger_std)
signal = sma(rsi_series, rsi_signal_len)
rsi_series = sma(rsi_series, rsi_smoothing)
return pd.DataFrame(index=series.index, data={
"rsi": rsi_series,
"signal": signal,
"bbupper": bb_series['upper'],
"bblower": bb_series['lower'],
"bbmid": bb_series['mid']
})
# ---------------------------------------------
def awesome_oscillator(df, weighted=False, fast=5, slow=34):
midprice = (df['high'] + df['low']) / 2
if weighted:
ao = (midprice.ewm(fast).mean() - midprice.ewm(slow).mean()).values
else:
ao = numpy_rolling_mean(midprice, fast) - \
numpy_rolling_mean(midprice, slow)
return pd.Series(index=df.index, data=ao)
# ---------------------------------------------
def nans(len=1):
mtx = np.empty(len)
mtx[:] = np.nan
return mtx
# ---------------------------------------------
def typical_price(bars):
res = (bars['high'] + bars['low'] + bars['close']) / 3.
return pd.Series(index=bars.index, data=res)
# ---------------------------------------------
def mid_price(bars):
res = (bars['high'] + bars['low']) / 2.
return pd.Series(index=bars.index, data=res)
# ---------------------------------------------
def ibs(bars):
""" Internal bar strength """
res = np.round((bars['close'] - bars['low']) /
(bars['high'] - bars['low']), 2)
return pd.Series(index=bars.index, data=res)
# ---------------------------------------------
def true_range(bars):
return pd.DataFrame({
"hl": bars['high'] - bars['low'],
"hc": abs(bars['high'] - bars['close'].shift(1)),
"lc": abs(bars['low'] - bars['close'].shift(1))
}).max(axis=1)
# ---------------------------------------------
def atr(bars, window=14, exp=False):
tr = true_range(bars)
if exp:
res = rolling_weighted_mean(tr, window)
else:
res = rolling_mean(tr, window)
res = pd.Series(res)
return (res.shift(1) * (window - 1) + res) / window
# ---------------------------------------------
def crossed(series1, series2, direction=None):
if isinstance(series1, np.ndarray):
series1 = pd.Series(series1)
if isinstance(series2, int) or isinstance(series2, float) or isinstance(series2, np.ndarray):
series2 = pd.Series(index=series1.index, data=series2)
if direction is None or direction == "above":
above = pd.Series((series1 > series2) & (
series1.shift(1) <= series2.shift(1)))
if direction is None or direction == "below":
below = pd.Series((series1 < series2) & (
series1.shift(1) >= series2.shift(1)))
if direction is None:
return above or below
return above if direction is "above" else below
def crossed_above(series1, series2):
return crossed(series1, series2, "above")
def crossed_below(series1, series2):
return crossed(series1, series2, "below")
# ---------------------------------------------
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:
return numpy_rolling_std(series, window, True)
else:
try:
return series.rolling(window=window, min_periods=min_periods).std()
except BaseException:
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:
return numpy_rolling_mean(series, window, True)
else:
try:
return series.rolling(window=window, min_periods=min_periods).mean()
except BaseException:
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()
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)
# ---------------------------------------------
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()
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)
# ---------------------------------------------
def rolling_weighted_mean(series, window=200, min_periods=None):
min_periods = window if min_periods is None else min_periods
try:
return series.ewm(span=window, min_periods=min_periods).mean()
except BaseException:
return pd.ewma(series, span=window, min_periods=min_periods)
# ---------------------------------------------
def hull_moving_average(series, window=200):
wma = (2 * rolling_weighted_mean(series, window=window / 2)) - \
rolling_weighted_mean(series, window=window)
return rolling_weighted_mean(wma, window=np.sqrt(window))
# ---------------------------------------------
def sma(series, window=200, min_periods=None):
return rolling_mean(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def wma(series, window=200, min_periods=None):
return rolling_weighted_mean(series, window=window, min_periods=min_periods)
# ---------------------------------------------
def hma(series, window=200):
return hull_moving_average(series, window=window)
# ---------------------------------------------
def vwap(bars):
"""
calculate vwap of entire time series
(input can be pandas series or numpy array)
bars are usually mid [ (h+l)/2 ] or typical [ (h+l+c)/3 ]
"""
typical = ((bars['high'] + bars['low'] + bars['close']) / 3).values
volume = bars['volume'].values
return pd.Series(index=bars.index,
data=np.cumsum(volume * typical) / np.cumsum(volume))
# ---------------------------------------------
def rolling_vwap(bars, window=200, min_periods=None):
"""
calculate vwap using moving window
(input can be pandas series or numpy array)
bars are usually mid [ (h+l)/2 ] or typical [ (h+l+c)/3 ]
"""
min_periods = window if min_periods is None else min_periods
typical = ((bars['high'] + bars['low'] + bars['close']) / 3)
volume = bars['volume']
left = (volume * typical).rolling(window=window,
min_periods=min_periods).sum()
right = volume.rolling(window=window, min_periods=min_periods).sum()
return pd.Series(index=bars.index, data=(left / right))
# ---------------------------------------------
def rsi(series, window=14):
"""
compute the n period relative strength indicator
"""
# 100-(100/relative_strength)
deltas = np.diff(series)
seed = deltas[:window + 1]
# default values
ups = seed[seed > 0].sum() / window
downs = -seed[seed < 0].sum() / window
rsival = np.zeros_like(series)
rsival[:window] = 100. - 100. / (1. + ups / downs)
# period values
for i in range(window, len(series)):
delta = deltas[i - 1]
if delta > 0:
upval = delta
downval = 0
else:
upval = 0
downval = -delta
ups = (ups * (window - 1) + upval) / window
downs = (downs * (window - 1.) + downval) / window
rsival[i] = 100. - 100. / (1. + ups / downs)
# return rsival
return pd.Series(index=series.index, data=rsival)
# ---------------------------------------------
def macd(series, fast=3, slow=10, smooth=16):
"""
compute the MACD (Moving Average Convergence/Divergence)
using a fast and slow exponential moving avg'
return value is emaslow, emafast, macd which are len(x) arrays
"""
macd = rolling_weighted_mean(series, window=fast) - \
rolling_weighted_mean(series, window=slow)
signal = rolling_weighted_mean(macd, window=smooth)
histogram = macd - signal
# return macd, signal, histogram
return pd.DataFrame(index=series.index, data={
'macd': macd.values,
'signal': signal.values,
'histogram': histogram.values
})
# ---------------------------------------------
def bollinger_bands(series, window=20, stds=2):
sma = rolling_mean(series, window=window)
std = rolling_std(series, window=window)
upper = sma + std * stds
lower = sma - std * stds
return pd.DataFrame(index=series.index, data={
'upper': upper,
'mid': sma,
'lower': lower
})
# ---------------------------------------------
def weighted_bollinger_bands(series, window=20, stds=2):
ema = rolling_weighted_mean(series, window=window)
std = rolling_std(series, window=window)
upper = ema + std * stds
lower = ema - std * stds
return pd.DataFrame(index=series.index, data={
'upper': upper.values,
'mid': ema.values,
'lower': lower.values
})
# ---------------------------------------------
def returns(series):
try:
res = (series / series.shift(1) -
1).replace([np.inf, -np.inf], float('NaN'))
except BaseException:
res = nans(len(series))
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def log_returns(series):
try:
res = np.log(series / series.shift(1)
).replace([np.inf, -np.inf], float('NaN'))
except BaseException:
res = nans(len(series))
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def implied_volatility(series, window=252):
try:
logret = np.log(series / series.shift(1)
).replace([np.inf, -np.inf], float('NaN'))
res = numpy_rolling_std(logret, window) * np.sqrt(window)
except BaseException:
res = nans(len(series))
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def keltner_channel(bars, window=14, atrs=2):
typical_mean = rolling_mean(typical_price(bars), window)
atrval = atr(bars, window) * atrs
upper = typical_mean + atrval
lower = typical_mean - atrval
return pd.DataFrame(index=bars.index, data={
'upper': upper.values,
'mid': typical_mean.values,
'lower': lower.values
})
# ---------------------------------------------
def roc(series, window=14):
"""
compute rate of change
"""
res = (series - series.shift(window)) / series.shift(window)
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def cci(series, window=14):
"""
compute commodity channel index
"""
price = typical_price(series)
typical_mean = rolling_mean(price, window)
res = (price - typical_mean) / (.015 * np.std(typical_mean))
return pd.Series(index=series.index, data=res)
# ---------------------------------------------
def stoch(df, window=14, d=3, k=3, fast=False):
"""
compute the n period relative strength indicator
http://excelta.blogspot.co.il/2013/09/stochastic-oscillator-technical.html
"""
highs_ma = pd.concat([df['high'].shift(i)
for i in np.arange(window)], 1).apply(list, 1)
highs_ma = highs_ma.T.max().T
lows_ma = pd.concat([df['low'].shift(i)
for i in np.arange(window)], 1).apply(list, 1)
lows_ma = lows_ma.T.min().T
fast_k = ((df['close'] - lows_ma) / (highs_ma - lows_ma)) * 100
fast_d = numpy_rolling_mean(fast_k, d)
if fast:
data = {
'k': fast_k,
'd': fast_d
}
else:
slow_k = numpy_rolling_mean(fast_k, k)
slow_d = numpy_rolling_mean(slow_k, d)
data = {
'k': slow_k,
'd': slow_d
}
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)
mean = numpy_rolling_mean(bars[col], window)
return (bars[col] - mean) / (std * stds)
# ---------------------------------------------
def pvt(bars):
""" Price Volume Trend """
pvt = ((bars['close'] - bars['close'].shift(1)) /
bars['close'].shift(1)) * bars['volume']
return pvt.cumsum()
# =============================================
PandasObject.session = session
PandasObject.atr = atr
PandasObject.bollinger_bands = bollinger_bands
PandasObject.cci = cci
PandasObject.crossed = crossed
PandasObject.crossed_above = crossed_above
PandasObject.crossed_below = crossed_below
PandasObject.heikinashi = heikinashi
PandasObject.hull_moving_average = hull_moving_average
PandasObject.ibs = ibs
PandasObject.implied_volatility = implied_volatility
PandasObject.keltner_channel = keltner_channel
PandasObject.log_returns = log_returns
PandasObject.macd = macd
PandasObject.returns = returns
PandasObject.roc = roc
PandasObject.rolling_max = rolling_max
PandasObject.rolling_min = rolling_min
PandasObject.rolling_mean = rolling_mean
PandasObject.rolling_std = rolling_std
PandasObject.rsi = rsi
PandasObject.stoch = stoch
PandasObject.zscore = zscore
PandasObject.pvt = pvt
PandasObject.tdi = tdi
PandasObject.true_range = true_range
PandasObject.mid_price = mid_price
PandasObject.typical_price = typical_price
PandasObject.vwap = vwap
PandasObject.rolling_vwap = rolling_vwap
PandasObject.weighted_bollinger_bands = weighted_bollinger_bands
PandasObject.rolling_weighted_mean = rolling_weighted_mean
PandasObject.sma = sma
PandasObject.wma = wma
PandasObject.hma = hma

257
main.py
View File

@@ -1,257 +0,0 @@
#!/usr/bin/env python
import json
import logging
import time
import traceback
from datetime import datetime
from typing import Optional
from jsonschema import validate
import exchange
import persistence
from persistence import Trade
from analyze import get_buy_signal
from misc import CONF_SCHEMA, get_state, State, update_state
from rpc import telegram
logging.basicConfig(level=logging.DEBUG,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger(__name__)
__author__ = "gcarq"
__copyright__ = "gcarq 2017"
__license__ = "GPLv3"
__version__ = "0.9.0"
_CONF = {}
def _process() -> None:
"""
Queries the persistence layer for open trades and handles them,
otherwise a new trade is created.
:return: None
"""
try:
# Query trades from persistence layer
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if len(trades) < _CONF['max_open_trades']:
try:
# Create entity and execute trade
trade = create_trade(float(_CONF['stake_amount']), exchange.EXCHANGE)
if trade:
Trade.session.add(trade)
else:
logging.info('Got no buy signal...')
except ValueError:
logger.exception('Unable to create trade')
for trade in trades:
# Check if there is already an open order for this trade
orders = exchange.get_open_orders(trade.pair)
orders = [o for o in orders if o['id'] == trade.open_order_id]
if orders:
logger.info('There is an open order for: %s', orders[0])
else:
# Update state
trade.open_order_id = None
# Check if this trade can be closed
if not close_trade_if_fulfilled(trade):
# Check if we can sell our current pair
handle_trade(trade)
Trade.session.flush()
except (ConnectionError, json.JSONDecodeError) as error:
msg = 'Got {} in _process()'.format(error.__class__.__name__)
logger.exception(msg)
def close_trade_if_fulfilled(trade: Trade) -> bool:
"""
Checks if the trade is closable, and if so it is being closed.
:param trade: Trade
:return: True if trade has been closed else False
"""
# If we don't have an open order and the close rate is already set,
# we can close this trade.
if trade.close_profit is not None \
and trade.close_date is not None \
and trade.close_rate is not None \
and trade.open_order_id is None:
trade.is_open = False
logger.info('No open orders found and trade is fulfilled. Marking %s as closed ...', trade)
return True
return False
def execute_sell(trade: Trade, current_rate: float) -> None:
"""
Executes a sell for the given trade and current rate
:param trade: Trade instance
:param current_rate: current rate
:return: None
"""
# Get available balance
currency = trade.pair.split('_')[1]
balance = exchange.get_balance(currency)
profit = trade.exec_sell_order(current_rate, balance)
message = '*{}:* Selling [{}]({}) at rate `{:f} (profit: {}%)`'.format(
trade.exchange.name,
trade.pair.replace('_', '/'),
exchange.get_pair_detail_url(trade.pair),
trade.close_rate,
round(profit, 2)
)
logger.info(message)
telegram.send_msg(message)
def handle_trade(trade: Trade) -> None:
"""
Sells the current pair if the threshold is reached and updates the trade record.
:return: None
"""
try:
if not trade.is_open:
raise ValueError('attempt to handle closed trade: {}'.format(trade))
logger.debug('Handling open trade %s ...', trade)
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
current_profit = 100.0 * ((current_rate - trade.open_rate) / trade.open_rate)
if 'stoploss' in _CONF and current_profit < float(_CONF['stoploss']) * 100.0:
logger.debug('Stop loss hit.')
execute_sell(trade, current_rate)
return
for duration, threshold in sorted(_CONF['minimal_roi'].items()):
duration, threshold = float(duration), float(threshold)
# Check if time matches and current rate is above threshold
time_diff = (datetime.utcnow() - trade.open_date).total_seconds() / 60
if time_diff > duration and current_rate > (1 + threshold) * trade.open_rate:
execute_sell(trade, current_rate)
return
logger.debug('Threshold not reached. (cur_profit: %1.2f%%)', current_profit)
except ValueError:
logger.exception('Unable to handle open order')
def create_trade(stake_amount: float, _exchange: exchange.Exchange) -> Optional[Trade]:
"""
Checks the implemented trading indicator(s) for a randomly picked pair,
if one pair triggers the buy_signal a new trade record gets created
:param stake_amount: amount of btc to spend
:param _exchange: exchange to use
"""
logger.info('Creating new trade with stake_amount: %f ...', stake_amount)
whitelist = _CONF[_exchange.name.lower()]['pair_whitelist']
# Check if btc_amount is fulfilled
if exchange.get_balance(_CONF['stake_currency']) < stake_amount:
raise ValueError(
'stake amount is not fulfilled (currency={}'.format(_CONF['stake_currency'])
)
# Remove currently opened and latest pairs from whitelist
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
latest_trade = Trade.query.filter(Trade.is_open.is_(False)).order_by(Trade.id.desc()).first()
if latest_trade:
trades.append(latest_trade)
for trade in trades:
if trade.pair in whitelist:
whitelist.remove(trade.pair)
logger.debug('Ignoring %s in pair whitelist', trade.pair)
if not whitelist:
raise ValueError('No pair in whitelist')
# Pick pair based on StochRSI buy signals
for _pair in whitelist:
if get_buy_signal(_pair):
pair = _pair
break
else:
return None
open_rate = exchange.get_ticker(pair)['ask']
amount = stake_amount / open_rate
order_id = exchange.buy(pair, open_rate, amount)
# Create trade entity and return
message = '*{}:* Buying [{}]({}) at rate `{:f}`'.format(
_exchange.name,
pair.replace('_', '/'),
exchange.get_pair_detail_url(pair),
open_rate
)
logger.info(message)
telegram.send_msg(message)
return Trade(pair=pair,
btc_amount=stake_amount,
open_rate=open_rate,
open_date=datetime.utcnow(),
amount=amount,
exchange=_exchange,
open_order_id=order_id,
is_open=True)
def init(config: dict, db_url: Optional[str] = None) -> None:
"""
Initializes all modules and updates the config
:param config: config as dict
:param db_url: database connector string for sqlalchemy (Optional)
:return: None
"""
# Initialize all modules
telegram.init(config)
persistence.init(config, db_url)
exchange.init(config)
# Set initial application state
initial_state = config.get('initial_state')
if initial_state:
update_state(State[initial_state.upper()])
else:
update_state(State.STOPPED)
def app(config: dict) -> None:
"""
Main function which handles the application state
:param config: config as dict
:return: None
"""
logger.info('Starting freqtrade %s', __version__)
init(config)
try:
old_state = get_state()
logger.info('Initial State: %s', old_state)
telegram.send_msg('*Status:* `{}`'.format(old_state.name.lower()))
while True:
new_state = get_state()
# Log state transition
if new_state != old_state:
telegram.send_msg('*Status:* `{}`'.format(new_state.name.lower()))
logging.info('Changing state to: %s', new_state.name)
if new_state == State.STOPPED:
time.sleep(1)
elif new_state == State.RUNNING:
_process()
# We need to sleep here because otherwise we would run into bittrex rate limit
time.sleep(25)
old_state = new_state
except RuntimeError:
telegram.send_msg('*Status:* Got RuntimeError: ```\n{}\n```'.format(traceback.format_exc()))
logger.exception('RuntimeError. Trader stopped!')
finally:
telegram.send_msg('*Status:* `Trader has stopped`')
if __name__ == '__main__':
with open('config.json') as file:
_CONF = json.load(file)
validate(_CONF, CONF_SCHEMA)
app(_CONF)

92
misc.py
View File

@@ -1,92 +0,0 @@
import enum
from wrapt import synchronized
class State(enum.Enum):
RUNNING = 0
STOPPED = 1
# Current application state
_STATE = State.STOPPED
@synchronized
def update_state(state: State) -> None:
"""
Updates the application state
:param state: new state
:return: None
"""
global _STATE
_STATE = state
@synchronized
def get_state() -> State:
"""
Gets the current application state
:return:
"""
return _STATE
# Required json-schema for user specified config
CONF_SCHEMA = {
'type': 'object',
'properties': {
'max_open_trades': {'type': 'integer', 'minimum': 1},
'stake_currency': {'type': 'string', 'enum': ['BTC', 'ETH', 'USDT']},
'stake_amount': {'type': 'number', 'minimum': 0.0005},
'dry_run': {'type': 'boolean'},
'minimal_roi': {
'type': 'object',
'patternProperties': {
'^[0-9.]+$': {'type': 'number'}
},
'minProperties': 1
},
'stoploss': {'type': 'number', 'maximum': 0, 'exclusiveMaximum': True},
'poloniex': {'$ref': '#/definitions/exchange'},
'bittrex': {'$ref': '#/definitions/exchange'},
'telegram': {
'type': 'object',
'properties': {
'enabled': {'type': 'boolean'},
'token': {'type': 'string'},
'chat_id': {'type': 'string'},
},
'required': ['enabled', 'token', 'chat_id']
},
'initial_state': {'type': 'string', 'enum': ['running', 'stopped']},
},
'definitions': {
'exchange': {
'type': 'object',
'properties': {
'enabled': {'type': 'boolean'},
'key': {'type': 'string'},
'secret': {'type': 'string'},
'pair_whitelist': {
'type': 'array',
'items': {'type': 'string'},
'uniqueItems': True
}
},
'required': ['enabled', 'key', 'secret', 'pair_whitelist']
}
},
'anyOf': [
{'required': ['poloniex']},
{'required': ['bittrex']}
],
'required': [
'max_open_trades',
'stake_currency',
'stake_amount',
'dry_run',
'minimal_roi',
'telegram'
]
}

View File

@@ -1,89 +0,0 @@
from datetime import datetime
from typing import Optional
from sqlalchemy import Boolean, Column, DateTime, Float, Integer, String, create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm.scoping import scoped_session
from sqlalchemy.orm.session import sessionmaker
from sqlalchemy.types import Enum
import exchange
_CONF = {}
Base = declarative_base()
def init(config: dict, db_url: Optional[str] = None) -> None:
"""
Initializes this module with the given config,
registers all known command handlers
and starts polling for message updates
:param config: config to use
:param db_url: database connector string for sqlalchemy (Optional)
:return: None
"""
_CONF.update(config)
if not db_url:
if _CONF.get('dry_run', False):
db_url = 'sqlite:///tradesv2.dry_run.sqlite'
else:
db_url = 'sqlite:///tradesv2.sqlite'
engine = create_engine(db_url, echo=False)
session = scoped_session(sessionmaker(bind=engine, autoflush=True, autocommit=True))
Trade.session = session()
Trade.query = session.query_property()
Base.metadata.create_all(engine)
class Trade(Base):
__tablename__ = 'trades'
id = Column(Integer, primary_key=True)
exchange = Column(Enum(exchange.Exchange), nullable=False)
pair = Column(String, nullable=False)
is_open = Column(Boolean, nullable=False, default=True)
open_rate = Column(Float, nullable=False)
close_rate = Column(Float)
close_profit = Column(Float)
btc_amount = Column(Float, nullable=False)
amount = Column(Float, nullable=False)
open_date = Column(DateTime, nullable=False, default=datetime.utcnow)
close_date = Column(DateTime)
open_order_id = Column(String)
def __repr__(self):
if self.is_open:
open_since = 'closed'
else:
open_since = round((datetime.utcnow() - self.open_date).total_seconds() / 60, 2)
return 'Trade(id={}, pair={}, amount={}, open_rate={}, open_since={})'.format(
self.id,
self.pair,
self.amount,
self.open_rate,
open_since
)
def exec_sell_order(self, rate: float, amount: float) -> float:
"""
Executes a sell for the given trade and updated the entity.
:param rate: rate to sell for
:param amount: amount to sell
:return: current profit as percentage
"""
profit = 100 * ((rate - self.open_rate) / self.open_rate)
# Execute sell and update trade record
order_id = exchange.sell(str(self.pair), rate, amount)
self.close_rate = rate
self.close_profit = profit
self.close_date = datetime.utcnow()
self.open_order_id = order_id
# Flush changes
Trade.session.flush()
return profit

View File

@@ -1,15 +1,25 @@
-e git+https://github.com/s4w3d0ff/python-poloniex.git#egg=Poloniex
-e git+https://github.com/ericsomdahl/python-bittrex.git#egg=python-bittrex
SQLAlchemy==1.1.13
python-telegram-bot==7.0.1
-e git+https://github.com/ericsomdahl/python-bittrex.git@0.2.0#egg=python-bittrex
SQLAlchemy==1.1.14
python-telegram-bot==8.1.1
arrow==0.10.0
cachetools==2.0.1
requests==2.18.4
urllib3==1.22
wrapt==1.10.11
pandas==0.20.3
matplotlib==2.0.2
scikit-learn==0.19.0
scipy==0.19.1
jsonschema==2.6.0
numpy==1.13.3
TA-Lib==0.4.10
#PYQT5==5.9
pytest==3.2.3
pytest-mock==1.6.3
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
tabulate==0.8.1
# Required for plotting data
#matplotlib==2.1.0
#PYQT5==5.9

View File

@@ -1,324 +0,0 @@
import logging
from datetime import timedelta
from typing import Callable, Any
import arrow
from sqlalchemy import and_, func, text
from telegram.error import NetworkError
from telegram.ext import CommandHandler, Updater
from telegram import ParseMode, Bot, Update
from misc import get_state, State, update_state
from persistence import Trade
import exchange
# Remove noisy log messages
logging.getLogger('requests.packages.urllib3').setLevel(logging.INFO)
logging.getLogger('telegram').setLevel(logging.INFO)
logger = logging.getLogger(__name__)
_updater = None
_CONF = {}
def init(config: dict) -> None:
"""
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
"""
global _updater
_updater = Updater(token=config['telegram']['token'], workers=0)
_CONF.update(config)
# Register command handler and start telegram message polling
handles = [
CommandHandler('status', _status),
CommandHandler('profit', _profit),
CommandHandler('start', _start),
CommandHandler('stop', _stop),
CommandHandler('forcesell', _forcesell),
CommandHandler('performance', _performance),
]
for handle in handles:
_updater.dispatcher.add_handler(handle)
_updater.start_polling(
clean=True,
bootstrap_retries=3,
timeout=30,
read_latency=60,
)
logger.info(
'rpc.telegram is listening for following commands: %s',
[h.command for h in handles]
)
def authorized_only(command_handler: Callable[[Bot, Update], None]) -> Callable[..., Any]:
"""
Decorator to check if the message comes from the correct chat_id
:param command_handler: Telegram CommandHandler
:return: decorated function
"""
def wrapper(*args, **kwargs):
bot, update = kwargs.get('bot') or args[0], kwargs.get('update') or args[1]
if not isinstance(bot, Bot) or not isinstance(update, Update):
raise ValueError('Received invalid Arguments: {}'.format(*args))
chat_id = int(_CONF['telegram']['chat_id'])
if int(update.message.chat_id) == chat_id:
logger.info('Executing handler: %s for chat_id: %s', command_handler.__name__, chat_id)
return command_handler(*args, **kwargs)
else:
logger.info('Rejected unauthorized message from: %s', update.message.chat_id)
return wrapper
@authorized_only
def _status(bot: Bot, update: Update) -> None:
"""
Handler for /status.
Returns the current TradeThread status
:param bot: telegram bot
:param update: message update
:return: None
"""
# Fetch open trade
trades = Trade.query.filter(Trade.is_open.is_(True)).all()
if get_state() != State.RUNNING:
send_msg('*Status:* `trader is not running`', bot=bot)
elif not trades:
send_msg('*Status:* `no active order`', bot=bot)
else:
for trade in trades:
# calculate profit and send message to user
current_rate = exchange.get_ticker(trade.pair)['bid']
current_profit = 100 * ((current_rate - trade.open_rate) / trade.open_rate)
orders = exchange.get_open_orders(trade.pair)
orders = [o for o in orders if o['id'] == trade.open_order_id]
order = orders[0] if orders else None
fmt_close_profit = '{:.2f}%'.format(
round(trade.close_profit, 2)
) if trade.close_profit else None
message = """
*Trade ID:* `{trade_id}`
*Current Pair:* [{pair}]({market_url})
*Open Since:* `{date}`
*Amount:* `{amount}`
*Open Rate:* `{open_rate}`
*Close Rate:* `{close_rate}`
*Current Rate:* `{current_rate}`
*Close Profit:* `{close_profit}`
*Current Profit:* `{current_profit:.2f}%`
*Open Order:* `{open_order}`
""".format(
trade_id=trade.id,
pair=trade.pair,
market_url=exchange.get_pair_detail_url(trade.pair),
date=arrow.get(trade.open_date).humanize(),
open_rate=trade.open_rate,
close_rate=trade.close_rate,
current_rate=current_rate,
amount=round(trade.amount, 8),
close_profit=fmt_close_profit,
current_profit=round(current_profit, 2),
open_order='{} ({})'.format(order['remaining'], order['type']) if order else None,
)
send_msg(message, bot=bot)
@authorized_only
def _profit(bot: Bot, update: Update) -> None:
"""
Handler for /profit.
Returns a cumulative profit statistics.
:param bot: telegram bot
:param update: message update
:return: None
"""
trades = Trade.query.order_by(Trade.id).all()
profit_amounts = []
profits = []
durations = []
for trade in trades:
if trade.close_date:
durations.append((trade.close_date - trade.open_date).total_seconds())
if trade.close_profit:
profit = trade.close_profit
else:
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
profit = 100 * ((current_rate - trade.open_rate) / trade.open_rate)
profit_amounts.append((profit / 100) * trade.btc_amount)
profits.append(profit)
best_pair = Trade.session.query(Trade.pair, func.sum(Trade.close_profit).label('profit_sum')) \
.filter(Trade.is_open.is_(False)) \
.group_by(Trade.pair) \
.order_by(text('profit_sum DESC')) \
.first()
if not best_pair:
send_msg('*Status:* `no closed trade`', bot=bot)
return
bp_pair, bp_rate = best_pair
markdown_msg = """
*ROI:* `{profit_btc:.2f} ({profit:.2f}%)`
*Trade Count:* `{trade_count}`
*First Trade opened:* `{first_trade_date}`
*Latest Trade opened:* `{latest_trade_date}`
*Avg. Duration:* `{avg_duration}`
*Best Performing:* `{best_pair}: {best_rate:.2f}%`
""".format(
profit_btc=round(sum(profit_amounts), 8),
profit=round(sum(profits), 2),
trade_count=len(trades),
first_trade_date=arrow.get(trades[0].open_date).humanize(),
latest_trade_date=arrow.get(trades[-1].open_date).humanize(),
avg_duration=str(timedelta(seconds=sum(durations) / float(len(durations)))).split('.')[0],
best_pair=bp_pair,
best_rate=round(bp_rate, 2),
)
send_msg(markdown_msg, bot=bot)
@authorized_only
def _start(bot: Bot, update: Update) -> None:
"""
Handler for /start.
Starts TradeThread
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() == State.RUNNING:
send_msg('*Status:* `already running`', bot=bot)
else:
update_state(State.RUNNING)
@authorized_only
def _stop(bot: Bot, update: Update) -> None:
"""
Handler for /stop.
Stops TradeThread
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() == State.RUNNING:
send_msg('`Stopping trader ...`', bot=bot)
update_state(State.STOPPED)
else:
send_msg('*Status:* `already stopped`', bot=bot)
@authorized_only
def _forcesell(bot: Bot, update: Update) -> None:
"""
Handler for /forcesell <id>.
Sells the given trade at current price
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() != State.RUNNING:
send_msg('`trader is not running`', bot=bot)
return
try:
trade_id = int(update.message.text
.replace('/forcesell', '')
.strip())
# Query for trade
trade = Trade.query.filter(and_(
Trade.id == trade_id,
Trade.is_open.is_(True)
)).first()
if not trade:
send_msg('There is no open trade with ID: `{}`'.format(trade_id))
return
# Get current rate
current_rate = exchange.get_ticker(trade.pair)['bid']
# Get available balance
currency = trade.pair.split('_')[1]
balance = exchange.get_balance(currency)
# Execute sell
profit = trade.exec_sell_order(current_rate, balance)
message = '*{}:* Selling [{}]({}) at rate `{:f} (profit: {}%)`'.format(
trade.exchange.name,
trade.pair.replace('_', '/'),
exchange.get_pair_detail_url(trade.pair),
trade.close_rate,
round(profit, 2)
)
logger.info(message)
send_msg(message)
except ValueError:
send_msg('Invalid argument. Usage: `/forcesell <trade_id>`')
logger.warning('/forcesell: Invalid argument received')
@authorized_only
def _performance(bot: Bot, update: Update) -> None:
"""
Handler for /performance.
Shows a performance statistic from finished trades
:param bot: telegram bot
:param update: message update
:return: None
"""
if get_state() != State.RUNNING:
send_msg('`trader is not running`', bot=bot)
return
pair_rates = Trade.session.query(Trade.pair, func.sum(Trade.close_profit).label('profit_sum')) \
.filter(Trade.is_open.is_(False)) \
.group_by(Trade.pair) \
.order_by(text('profit_sum DESC')) \
.all()
stats = '\n'.join('{index}. <code>{pair}\t{profit:.2f}%</code>'.format(
index=i + 1,
pair=pair,
profit=round(rate, 2)
) for i, (pair, rate) in enumerate(pair_rates))
message = '<b>Performance:</b>\n{}\n'.format(stats)
logger.debug(message)
send_msg(message, parse_mode=ParseMode.HTML)
def send_msg(msg: str, bot: Bot = None, parse_mode: ParseMode = ParseMode.MARKDOWN) -> None:
"""
Send given markdown message
:param msg: message
:param bot: alternative bot
:param parse_mode: telegram parse mode
:return: None
"""
if _CONF['telegram'].get('enabled', False):
try:
bot = bot or _updater.bot
try:
bot.send_message(_CONF['telegram']['chat_id'], msg, parse_mode=parse_mode)
except NetworkError as error:
# Sometimes the telegram server resets the current connection,
# if this is the case we send the message again.
logger.warning(
'Got Telegram NetworkError: %s! Trying one more time.',
error.message
)
bot.send_message(_CONF['telegram']['chat_id'], msg, parse_mode=parse_mode)
except Exception:
logger.exception('Exception occurred within Telegram API')

51
scripts/plot_dataframe.py Executable file
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@@ -0,0 +1,51 @@
#!/usr/bin/env python3
import matplotlib # Install PYQT5 manually if you want to test this helper function
matplotlib.use("Qt5Agg")
import matplotlib.pyplot as plt
from freqtrade import exchange, analyze
def plot_analyzed_dataframe(pair: str) -> None:
"""
Calls analyze() and plots the returned dataframe
:param pair: pair as str
:return: None
"""
# Init Bittrex to use public API
exchange._API = exchange.Bittrex({'key': '', 'secret': ''})
dataframe = analyze.analyze_ticker(pair)
# Two subplots sharing x axis
fig, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)
fig.suptitle(pair, fontsize=14, fontweight='bold')
ax1.plot(dataframe.index.values, dataframe['close'], label='close')
# ax1.plot(dataframe.index.values, dataframe['sell'], 'ro', label='sell')
ax1.plot(dataframe.index.values, dataframe['sma'], '--', label='SMA')
ax1.plot(dataframe.index.values, dataframe['tema'], ':', label='TEMA')
ax1.plot(dataframe.index.values, dataframe['blower'], '-.', label='BB low')
ax1.plot(dataframe.index.values, dataframe['buy_price'], 'bo', label='buy')
ax1.legend()
ax2.plot(dataframe.index.values, dataframe['adx'], label='ADX')
ax2.plot(dataframe.index.values, dataframe['mfi'], label='MFI')
# ax2.plot(dataframe.index.values, [25] * len(dataframe.index.values))
ax2.legend()
ax3.plot(dataframe.index.values, dataframe['fastk'], label='k')
ax3.plot(dataframe.index.values, dataframe['fastd'], label='d')
ax3.plot(dataframe.index.values, [20] * len(dataframe.index.values))
ax3.legend()
# Fine-tune figure; make subplots close to each other and hide x ticks for
# all but bottom plot.
fig.subplots_adjust(hspace=0)
plt.setp([a.get_xticklabels() for a in fig.axes[:-1]], visible=False)
plt.show()
if __name__ == '__main__':
plot_analyzed_dataframe('BTC_ETH')

49
setup.py Normal file
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@@ -0,0 +1,49 @@
from sys import version_info
from setuptools import setup
if version_info.major == 3 and version_info.minor < 6 or \
version_info.major < 3:
print('Your Python interpreter must be 3.6 or greater!')
exit(1)
from freqtrade import __version__
setup(name='freqtrade',
version=__version__,
description='Simple High Frequency Trading Bot for crypto currencies',
url='https://github.com/gcarq/freqtrade',
author='gcarq and contributors',
author_email='michael.egger@tsn.at',
license='GPLv3',
packages=['freqtrade'],
scripts=['bin/freqtrade'],
setup_requires=['pytest-runner'],
tests_require=['pytest', 'pytest-mock', 'pytest-cov'],
install_requires=[
'python-bittrex',
'SQLAlchemy',
'python-telegram-bot',
'arrow',
'requests',
'urllib3',
'wrapt',
'pandas',
'scikit-learn',
'scipy',
'jsonschema',
'TA-Lib',
'tabulate',
'cachetools',
],
dependency_links=[
"git+https://github.com/ericsomdahl/python-bittrex.git@0.2.0#egg=python-bittrex"
],
include_package_data=True,
zip_safe=False,
classifiers=[
'Programming Language :: Python :: 3.6',
'License :: OSI Approved :: GNU General Public License v3 (GPLv3)',
'Topic :: Office/Business :: Financial :: Investment',
'Intended Audience :: Science/Research',
])

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@@ -1,49 +0,0 @@
# pragma pylint: disable=missing-docstring
import unittest
from unittest.mock import patch
from pandas import DataFrame
import arrow
from analyze import parse_ticker_dataframe, populate_buy_trend, populate_indicators, analyze_ticker, get_buy_signal
RESULT_BITTREX = {
'success': True,
'message': '',
'result': [
{'O': 0.00065311, 'H': 0.00065311, 'L': 0.00065311, 'C': 0.00065311, 'V': 22.17210568, 'T': '2017-08-30T10:40:00', 'BV': 0.01448082},
{'O': 0.00066194, 'H': 0.00066195, 'L': 0.00066194, 'C': 0.00066195, 'V': 33.4727437, 'T': '2017-08-30T10:34:00', 'BV': 0.02215696},
{'O': 0.00065311, 'H': 0.00065311, 'L': 0.00065311, 'C': 0.00065311, 'V': 53.85127609, 'T': '2017-08-30T10:37:00', 'BV': 0.0351708},
{'O': 0.00066194, 'H': 0.00066194, 'L': 0.00065311, 'C': 0.00065311, 'V': 46.29210665, 'T': '2017-08-30T10:42:00', 'BV': 0.03063118},
]
}
class TestAnalyze(unittest.TestCase):
def setUp(self):
self.result = parse_ticker_dataframe(RESULT_BITTREX['result'], arrow.get('2017-08-30T10:00:00'))
def test_1_dataframe_has_correct_columns(self):
self.assertEqual(self.result.columns.tolist(),
['close', 'high', 'low', 'open', 'date', 'volume'])
def test_2_orders_by_date(self):
self.assertEqual(self.result['date'].tolist(),
['2017-08-30T10:34:00',
'2017-08-30T10:37:00',
'2017-08-30T10:40:00',
'2017-08-30T10:42:00'])
def test_3_populates_buy_trend(self):
dataframe = populate_buy_trend(populate_indicators(self.result))
self.assertTrue('buy' in dataframe.columns)
self.assertTrue('buy_price' in dataframe.columns)
def test_4_returns_latest_buy_signal(self):
buydf = DataFrame([{'buy': 1, 'date': arrow.utcnow()}])
with patch('analyze.analyze_ticker', return_value=buydf):
self.assertEqual(get_buy_signal('BTC-ETH'), True)
buydf = DataFrame([{'buy': 0, 'date': arrow.utcnow()}])
with patch('analyze.analyze_ticker', return_value=buydf):
self.assertEqual(get_buy_signal('BTC-ETH'), False)
if __name__ == '__main__':
unittest.main()

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@@ -1,105 +0,0 @@
import unittest
from unittest.mock import patch, MagicMock
from jsonschema import validate
import exchange
from main import create_trade, handle_trade, close_trade_if_fulfilled, init
from misc import CONF_SCHEMA
from persistence import Trade
class TestMain(unittest.TestCase):
conf = {
"max_open_trades": 3,
"stake_currency": "BTC",
"stake_amount": 0.05,
"dry_run": True,
"minimal_roi": {
"2880": 0.005,
"720": 0.01,
"0": 0.02
},
"poloniex": {
"enabled": False,
"key": "key",
"secret": "secret",
"pair_whitelist": []
},
"bittrex": {
"enabled": True,
"key": "key",
"secret": "secret",
"pair_whitelist": [
"BTC_ETH"
]
},
"telegram": {
"enabled": True,
"token": "token",
"chat_id": "chat_id"
}
}
def test_1_create_trade(self):
with patch.dict('main._CONF', self.conf):
with patch('main.get_buy_signal', side_effect=lambda _: True) as buy_signal:
with patch.multiple('main.telegram', init=MagicMock(), send_msg=MagicMock()):
with patch.multiple('main.exchange',
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id')):
init(self.conf, 'sqlite://')
trade = create_trade(15.0, exchange.Exchange.BITTREX)
Trade.session.add(trade)
Trade.session.flush()
self.assertIsNotNone(trade)
self.assertEqual(trade.open_rate, 0.072661)
self.assertEqual(trade.pair, 'BTC_ETH')
self.assertEqual(trade.exchange, exchange.Exchange.BITTREX)
self.assertEqual(trade.amount, 206.43811673387373)
self.assertEqual(trade.btc_amount, 15.0)
self.assertEqual(trade.is_open, True)
self.assertIsNotNone(trade.open_date)
buy_signal.assert_called_once_with('BTC_ETH')
def test_2_handle_trade(self):
with patch.dict('main._CONF', self.conf):
with patch.multiple('main.telegram', init=MagicMock(), send_msg=MagicMock()):
with patch.multiple('main.exchange',
get_ticker=MagicMock(return_value={
'bid': 0.17256061,
'ask': 0.172661,
'last': 0.17256061
}),
buy=MagicMock(return_value='mocked_order_id')):
trade = Trade.query.filter(Trade.is_open.is_(True)).first()
self.assertTrue(trade)
handle_trade(trade)
self.assertEqual(trade.close_rate, 0.17256061)
self.assertEqual(trade.close_profit, 137.4872490056564)
self.assertIsNotNone(trade.close_date)
self.assertEqual(trade.open_order_id, 'dry_run')
def test_3_close_trade(self):
with patch.dict('main._CONF', self.conf):
trade = Trade.query.filter(Trade.is_open.is_(True)).first()
self.assertTrue(trade)
# Simulate that there is no open order
trade.open_order_id = None
closed = close_trade_if_fulfilled(trade)
self.assertTrue(closed)
self.assertEqual(trade.is_open, False)
@classmethod
def setUpClass(cls):
validate(cls.conf, CONF_SCHEMA)
if __name__ == '__main__':
unittest.main()

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@@ -1,28 +0,0 @@
import unittest
from unittest.mock import patch
from exchange import Exchange
from persistence import Trade
class TestTrade(unittest.TestCase):
def test_1_exec_sell_order(self):
with patch('main.exchange.sell', side_effect='mocked_order_id') as api_mock:
trade = Trade(
pair='BTC_ETH',
btc_amount=1.00,
open_rate=0.50,
amount=10.00,
exchange=Exchange.BITTREX,
open_order_id='mocked'
)
profit = trade.exec_sell_order(1.00, 10.00)
api_mock.assert_called_once_with('BTC_ETH', 1.0, 10.0)
self.assertEqual(profit, 100.0)
self.assertEqual(trade.close_rate, 1.0)
self.assertEqual(trade.close_profit, profit)
self.assertIsNotNone(trade.close_date)
if __name__ == '__main__':
unittest.main()

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@@ -1,198 +0,0 @@
import unittest
from unittest.mock import patch, MagicMock
from datetime import datetime
from jsonschema import validate
from telegram import Bot, Update, Message, Chat
import exchange
from main import init, create_trade
from misc import CONF_SCHEMA, update_state, State, get_state
from persistence import Trade
from rpc.telegram import _status, _profit, _forcesell, _performance, _start, _stop
class MagicBot(MagicMock, Bot):
pass
class TestTelegram(unittest.TestCase):
conf = {
"max_open_trades": 3,
"stake_currency": "BTC",
"stake_amount": 0.05,
"dry_run": True,
"minimal_roi": {
"2880": 0.005,
"720": 0.01,
"0": 0.02
},
"poloniex": {
"enabled": False,
"key": "key",
"secret": "secret",
"pair_whitelist": []
},
"bittrex": {
"enabled": True,
"key": "key",
"secret": "secret",
"pair_whitelist": [
"BTC_ETH"
]
},
"telegram": {
"enabled": True,
"token": "token",
"chat_id": "0"
},
"initial_state": "running"
}
def test_1_status_handle(self):
with patch.dict('main._CONF', self.conf):
with patch('main.get_buy_signal', side_effect=lambda _: True):
msg_mock = MagicMock()
with patch.multiple('main.telegram', _CONF=self.conf, init=MagicMock(), send_msg=msg_mock):
with patch.multiple('main.exchange',
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id')):
init(self.conf, 'sqlite://')
# Create some test data
trade = create_trade(15.0, exchange.Exchange.BITTREX)
self.assertTrue(trade)
Trade.session.add(trade)
Trade.session.flush()
_status(bot=MagicBot(), update=self.update)
self.assertEqual(msg_mock.call_count, 2)
self.assertIn('[BTC_ETH]', msg_mock.call_args_list[-1][0][0])
def test_2_profit_handle(self):
with patch.dict('main._CONF', self.conf):
with patch('main.get_buy_signal', side_effect=lambda _: True):
msg_mock = MagicMock()
with patch.multiple('main.telegram', _CONF=self.conf, init=MagicMock(), send_msg=msg_mock):
with patch.multiple('main.exchange',
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id')):
init(self.conf, 'sqlite://')
# Create some test data
trade = create_trade(15.0, exchange.Exchange.BITTREX)
self.assertTrue(trade)
trade.close_rate = 0.07256061
trade.close_profit = 100.00
trade.close_date = datetime.utcnow()
trade.open_order_id = None
trade.is_open = False
Trade.session.add(trade)
Trade.session.flush()
_profit(bot=MagicBot(), update=self.update)
self.assertEqual(msg_mock.call_count, 2)
self.assertIn('(100.00%)', msg_mock.call_args_list[-1][0][0])
def test_3_forcesell_handle(self):
with patch.dict('main._CONF', self.conf):
with patch('main.get_buy_signal', side_effect=lambda _: True):
msg_mock = MagicMock()
with patch.multiple('main.telegram', _CONF=self.conf, init=MagicMock(), send_msg=msg_mock):
with patch.multiple('main.exchange',
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id')):
init(self.conf, 'sqlite://')
# Create some test data
trade = create_trade(15.0, exchange.Exchange.BITTREX)
self.assertTrue(trade)
Trade.session.add(trade)
Trade.session.flush()
self.update.message.text = '/forcesell 1'
_forcesell(bot=MagicBot(), update=self.update)
self.assertEqual(msg_mock.call_count, 2)
self.assertIn('Selling [BTC/ETH]', msg_mock.call_args_list[-1][0][0])
self.assertIn('0.072561', msg_mock.call_args_list[-1][0][0])
def test_4_performance_handle(self):
with patch.dict('main._CONF', self.conf):
with patch('main.get_buy_signal', side_effect=lambda _: True):
msg_mock = MagicMock()
with patch.multiple('main.telegram', _CONF=self.conf, init=MagicMock(), send_msg=msg_mock):
with patch.multiple('main.exchange',
get_ticker=MagicMock(return_value={
'bid': 0.07256061,
'ask': 0.072661,
'last': 0.07256061
}),
buy=MagicMock(return_value='mocked_order_id')):
init(self.conf, 'sqlite://')
# Create some test data
trade = create_trade(15.0, exchange.Exchange.BITTREX)
self.assertTrue(trade)
trade.close_rate = 0.07256061
trade.close_profit = 100.00
trade.close_date = datetime.utcnow()
trade.open_order_id = None
trade.is_open = False
Trade.session.add(trade)
Trade.session.flush()
_performance(bot=MagicBot(), update=self.update)
self.assertEqual(msg_mock.call_count, 2)
self.assertIn('Performance', msg_mock.call_args_list[-1][0][0])
self.assertIn('BTC_ETH 100.00%', msg_mock.call_args_list[-1][0][0])
def test_5_start_handle(self):
with patch.dict('main._CONF', self.conf):
msg_mock = MagicMock()
with patch.multiple('main.telegram', _CONF=self.conf, init=MagicMock(), send_msg=msg_mock):
init(self.conf, 'sqlite://')
update_state(State.STOPPED)
self.assertEqual(get_state(), State.STOPPED)
_start(bot=MagicBot(), update=self.update)
self.assertEqual(get_state(), State.RUNNING)
self.assertEqual(msg_mock.call_count, 0)
def test_6_stop_handle(self):
with patch.dict('main._CONF', self.conf):
msg_mock = MagicMock()
with patch.multiple('main.telegram', _CONF=self.conf, init=MagicMock(), send_msg=msg_mock):
init(self.conf, 'sqlite://')
update_state(State.RUNNING)
self.assertEqual(get_state(), State.RUNNING)
_stop(bot=MagicBot(), update=self.update)
self.assertEqual(get_state(), State.STOPPED)
self.assertEqual(msg_mock.call_count, 1)
self.assertIn('Stopping trader', msg_mock.call_args_list[0][0][0])
def setUp(self):
self.update = Update(0)
self.update.message = Message(0, 0, datetime.utcnow(), Chat(0, 0))
@classmethod
def setUpClass(cls):
validate(cls.conf, CONF_SCHEMA)
if __name__ == '__main__':
unittest.main()