numba now is a mandatory requirement

.github/workflows/python-package.yml

@@ -8,8 +8,8 @@ on:
     branches: [ master ]
   pull_request:
     branches: [ master ]
-    
-concurrency: 
+
+concurrency:
   group: ${{ github.workflow }}-${{ github.ref }}
   cancel-in-progress: true
 
@@ -21,15 +21,15 @@ jobs:
       matrix:
        # os: [ubuntu-latest, macos-latest, windows-latest]
         os: [ubuntu-latest]
-        include: 
+        include:
         - os: ubuntu-latest
           path: ~/.cache/pip
-        #- os: macos-latest
+        #- os: macos-latest-xlarge
         #  path: ~/Library/Caches/pip
         #- os: windows-latest
         #  path: ~\AppData\Local\pip\Cache
-        python-version: [3.8, 3.9, '3.10']
-        
+        python-version: [3.8, 3.9, '3.10', 3.11]
+
 
     steps:
       - name: Checkout

jesse/indicators/alma.py

@@ -4,6 +4,7 @@
 
 from jesse.helpers import get_candle_source, slice_candles
 
+
 def alma(candles: np.ndarray, period: int = 9, sigma: float = 6.0, distribution_offset: float = 0.85,
          source_type: str = "close", sequential: bool = False) -> Union[
     float, np.ndarray]:

jesse/indicators/apo.py

@@ -1,9 +1,9 @@
 from typing import Union
 
 import numpy as np
-from jesse.indicators.ma import ma
 
 from jesse.helpers import get_candle_source, slice_candles
+from jesse.indicators.ma import ma
 
 
 def apo(candles: np.ndarray, fast_period: int = 12, slow_period: int = 26, matype: int = 0, source_type: str = "close",

jesse/indicators/bandpass.py

@@ -1,15 +1,12 @@
 from collections import namedtuple
 
 import numpy as np
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a : a
-
-from .high_pass import high_pass_fast
+from numba import njit
 
 from jesse.helpers import get_candle_source, slice_candles
 
+from .high_pass import high_pass_fast
+
 BandPass = namedtuple('BandPass', ['bp', 'bp_normalized', 'signal', 'trigger'])
 
 
@@ -49,7 +46,7 @@ def bandpass(candles: np.ndarray, period: int = 20, bandwidth: float = 0.3,  sou
         return BandPass(bp[-1], bp_normalized[-1], signal[-1], trigger[-1])
 
 
-@njit
+@njit(cache=True)
 def bp_fast(source, hp, alpha, beta):  # Function is compiled to machine code when called the first time
 
     bp = np.copy(hp)

jesse/indicators/bollinger_bands.py

@@ -2,12 +2,12 @@
 
 import numpy as np
 import talib
+
+from jesse.helpers import get_candle_source, slice_candles
 from jesse.indicators.ma import ma
 from jesse.indicators.mean_ad import mean_ad
 from jesse.indicators.median_ad import median_ad
 
-from jesse.helpers import get_candle_source, slice_candles
-
 BollingerBands = namedtuple('BollingerBands', ['upperband', 'middleband', 'lowerband'])
 
 

jesse/indicators/bollinger_bands_width.py

@@ -2,12 +2,12 @@
 
 import numpy as np
 import talib
+
+from jesse.helpers import get_candle_source, slice_candles
 from jesse.indicators.ma import ma
 from jesse.indicators.mean_ad import mean_ad
 from jesse.indicators.median_ad import median_ad
 
-from jesse.helpers import get_candle_source, slice_candles
-
 
 def bollinger_bands_width(candles: np.ndarray, period: int = 20, devup: float = 2, devdn: float = 2, matype: int = 0,
                     devtype: int = 0,

jesse/indicators/cfo.py

@@ -3,8 +3,7 @@
 import numpy as np
 import talib
 
-from jesse.helpers import get_candle_source
-from jesse.helpers import slice_candles
+from jesse.helpers import get_candle_source, slice_candles
 
 
 def cfo(candles: np.ndarray, period: int = 14, scalar: float = 100, source_type: str = "close",

jesse/indicators/cg.py

@@ -1,10 +1,7 @@
 from typing import Union
 
 import numpy as np
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a : a
+from numba import njit
 
 from jesse.helpers import get_candle_source, same_length, slice_candles
 
@@ -29,7 +26,7 @@ def cg(candles: np.ndarray, period: int = 10, source_type: str = "close", sequen
     return same_length(candles, res) if sequential else res[-1]
 
 
-@njit
+@njit(cache=True)
 def go_fast(source, period):  # Function is compiled to machine code when called the first time
     res = np.full_like(source, fill_value=np.nan)
     for i in range(source.size):

jesse/indicators/cksp.py

@@ -5,7 +5,6 @@
 
 from jesse.helpers import slice_candles
 
-
 CKSP = namedtuple('CKSP', ['long', 'short'])
 
 def cksp(candles: np.ndarray, p: int = 10, x: float = 1.0,  q: int = 9, sequential: bool = False) -> CKSP:

jesse/indicators/cmo.py

@@ -3,8 +3,7 @@
 import numpy as np
 import talib
 
-from jesse.helpers import get_candle_source
-from jesse.helpers import slice_candles
+from jesse.helpers import get_candle_source, slice_candles
 
 
 def cmo(candles: np.ndarray, period: int = 14, source_type: str = "close", sequential: bool = False) -> Union[

jesse/indicators/correlation_cycle.py

@@ -1,10 +1,7 @@
 from collections import namedtuple
 
 import numpy as np
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a : a
+from numba import njit
 
 from jesse.helpers import get_candle_source, np_shift, slice_candles
 
@@ -42,7 +39,7 @@ def correlation_cycle(candles: np.ndarray, period: int = 20, threshold: int = 9,
         return CC(realPart[-1], imagPart[-1], angle[-1], state[-1])
 
 
-@njit
+@njit(cache=True)
 def go_fast(source, period):  # Function is compiled to machine code when called the first time
     # Correlation Cycle Function
     PIx2 = 4.0 * np.arcsin(1.0)

jesse/indicators/cvi.py

@@ -3,7 +3,7 @@
 import numpy as np
 import tulipy as ti
 
-from jesse.helpers import slice_candles, same_length
+from jesse.helpers import same_length, slice_candles
 
 
 def cvi(candles: np.ndarray, period: int = 5, sequential: bool = False) -> Union[float, np.ndarray]:

jesse/indicators/cwma.py

@@ -1,11 +1,7 @@
 from typing import Union
-import numpy as np
-
 
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a : a
+import numpy as np
+from numba import njit
 
 from jesse.helpers import get_candle_source, slice_candles
 
@@ -35,7 +31,7 @@ def cwma(candles: np.ndarray, period: int = 14, source_type: str = "close", sequ
     return res if sequential else res[-1]
 
 
-@njit
+@njit(cache=True)
 def vpwma_fast(source, period):
     newseries = np.copy(source)
     for j in range(period + 1, source.shape[0]):

jesse/indicators/damiani_volatmeter.py

@@ -2,13 +2,9 @@
 
 import numpy as np
 import talib
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a : a
+from numba import njit
 
-from jesse.helpers import get_candle_source
-from jesse.helpers import slice_candles
+from jesse.helpers import get_candle_source, slice_candles
 
 DamianiVolatmeter = namedtuple('DamianiVolatmeter', ['vol', 'anti'])
 
@@ -46,7 +42,7 @@ def damiani_volatmeter(candles: np.ndarray, vis_atr: int = 13, vis_std: int = 20
         return DamianiVolatmeter(vol[-1], t[-1])
 
 
-@njit
+@njit(cache=True)
 def damiani_volatmeter_fast(source, sed_std, atrvis, atrsed, vis_std,
                             threshold):  # Function is compiled to machine code when called the first time
     lag_s = 0.5

jesse/indicators/dec_osc.py

@@ -3,6 +3,7 @@
 import numpy as np
 
 from jesse.helpers import get_candle_source, slice_candles
+
 from .high_pass_2_pole import high_pass_2_pole_fast
 
 

jesse/indicators/decycler.py

@@ -3,6 +3,7 @@
 import numpy as np
 
 from jesse.helpers import get_candle_source, slice_candles
+
 from .high_pass_2_pole import high_pass_2_pole_fast
 
 

jesse/indicators/devstop.py

@@ -2,10 +2,10 @@
 
 import numpy as np
 import talib
-from jesse.indicators.mean_ad import mean_ad
-from jesse.indicators.median_ad import median_ad
 
 from jesse.helpers import slice_candles
+from jesse.indicators.mean_ad import mean_ad
+from jesse.indicators.median_ad import median_ad
 
 
 def devstop(candles: np.ndarray, period: int = 20, mult: float = 0, devtype: int = 0, direction: str = "long",

jesse/indicators/edcf.py

@@ -1,11 +1,7 @@
 from typing import Union
 
 import numpy as np
-
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a: a
+from numba import njit
 
 from jesse.helpers import get_candle_source, slice_candles
 
@@ -35,7 +31,7 @@ def edcf(candles: np.ndarray, period: int = 15, source_type: str = "hl2", sequen
     return res if sequential else res[-1]
 
 
-@njit
+@njit(cache=True)
 def edcf_fast(source, period):
     newseries = np.full_like(source, np.nan)
 

jesse/indicators/efi.py

@@ -2,10 +2,7 @@
 
 import numpy as np
 import talib
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a : a
+from numba import njit
 
 from jesse.helpers import get_candle_source, same_length, slice_candles
 
@@ -34,7 +31,7 @@ def efi(candles: np.ndarray, period: int = 13, source_type: str = "close", seque
     return res_with_nan if sequential else res_with_nan[-1]
 
 
-@njit
+@njit(cache=True)
 def efi_fast(source, volume):
     dif = np.zeros(source.size - 1)
     for i in range(1, source.size):

jesse/indicators/emd.py

@@ -2,10 +2,7 @@
 
 import numpy as np
 import talib
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a : a
+from numba import njit
 
 from jesse.helpers import slice_candles
 
@@ -42,7 +39,7 @@ def emd(candles: np.ndarray, period: int = 20, delta=0.5, fraction=0.1, sequenti
         return EMD(avg_peak[-1], mean[-1], avg_valley[-1])
 
 
-@njit
+@njit(cache=True)
 def bp_fast(price, period, delta):
     # bandpass filter
     beta = np.cos(2 * np.pi / period)
@@ -58,7 +55,7 @@ def bp_fast(price, period, delta):
     return bp
 
 
-@njit
+@njit(cache=True)
 def peak_valley_fast(bp, price):
     peak = np.copy(bp)
     valley = np.copy(bp)

jesse/indicators/emv.py

@@ -3,7 +3,7 @@
 import numpy as np
 import tulipy as ti
 
-from jesse.helpers import slice_candles, same_length
+from jesse.helpers import same_length, slice_candles
 
 
 def emv(candles: np.ndarray, sequential: bool = False) -> Union[float, np.ndarray]:

jesse/indicators/epma.py

@@ -1,11 +1,7 @@
 from typing import Union
-import numpy as np
-
 
-try:
-    from numba import njit
-except ImportError:
-    njit = lambda a : a
+import numpy as np
+from numba import njit
 
 from jesse.helpers import get_candle_source, slice_candles
 
@@ -36,7 +32,7 @@ def epma(candles: np.ndarray, period: int = 11, offset: int = 4, source_type: st
     return res if sequential else res[-1]
 
 
-@njit
+@njit(cache=True)
 def epma_fast(source, period, offset):
     newseries = np.copy(source)
     for j in range(period + offset + 1 , source.shape[0]):

jesse/indicators/er.py

@@ -3,7 +3,7 @@
 import numpy as np
 from numpy.lib.stride_tricks import sliding_window_view
 
-from jesse.helpers import get_candle_source, slice_candles, same_length
+from jesse.helpers import get_candle_source, same_length, slice_candles
 
 
 def er(candles: np.ndarray, period: int = 5, source_type: str = "close", sequential: bool = False) -> Union[

jesse/indicators/eri.py

@@ -1,9 +1,9 @@
 from collections import namedtuple
 
 import numpy as np
-from jesse.indicators.ma import ma
 
 from jesse.helpers import get_candle_source, slice_candles
+from jesse.indicators.ma import ma
 
 ERI = namedtuple('ERI', ['bull', 'bear'])
 

jesse/indicators/fisher.py

@@ -3,7 +3,7 @@
 import numpy as np
 import tulipy as ti
 
-from jesse.helpers import slice_candles, same_length
+from jesse.helpers import same_length, slice_candles
 
 FisherTransform = namedtuple('FisherTransform', ['fisher', 'signal'])