iSSKJr SSKJrJr SSKJrJr SSKJ r /SQr \"SS55r \ "SS S S 9r \ "S S SSSS.SSS.SSS.SSS.SSSSS./S9r g )) cpu_count) dataclassfield)IntList)get_time)StudyAllStudy CommonStudyc\rSrSr%Sr\\S'\"\S9r \ \S'\ "5r \ \S'Sr\\S'\"S S 9r\\S 'S rS rSrSrSrg)r aStudy DataClass Class to name and group indicators for processing. Parameters: name (str): Name. ta (list of dicts): i.e [{"kind": "ema", "length", 50}] cores (int): The number cores to use for multiprocessing. Default: ```cpu_count()``` description (str): Description of what the Study. Default: ```""``` created (str): DateTime String at creation. Default: Automatically generated. Returns: (DataClass): The Study to be processed by ```df.ta.study()``` Example: All or Common Study Run ```py # Run "All" df.ta.study(ta.AllStudy, **kwargs) # Run "Common" df.ta.study(ta.CommonStudy, **kwargs) ``` Example: Custom Study Create ```py DemoStudy = ta.Study( name="Demo Study", description="Example Study Group", cores=0, # Usually faster than multiprocessing ta = [ {"kind": "sma", "length": 200}, {"kind": "sma", "close": "volume", "length": 50}, {"kind": "bbands", "length": 20}, {"kind": "rsi"}, {"kind": "macd", "fast": 8, "slow": 21}, {"kind": "sma", "close": "volume", "length": 20, "prefix": "VOLUME"} ] ``` Run ```py df.ta.study(DemoStudy, **kwargs) ``` Note: * See [also](../getting-started/usage.md) the Pandas TA "Study" Examples * Case-insensitive "All" is reserved. Warning: Multiprocessing **Not recommended** for: * Small sets of indicators * Indicator chains name)default_factorytacores descriptionT) to_stringcreatedc[UR[5(aBURS:a2UR[5::a[UR5UlS/nUR 5(aUR S5 UR cSUlO-UR5(dSnUS- nUR U5 [U5S:aUVs/sHn[U5PM nggs snf)Nrz-[X] Study requires the following argument(s):zE - name. Must be a string. Example: "My TA". Note: "all" is reserved.zJ - ta. Format is a list of dicts. Example: [{'kind': 'sma', 'length': 10}]zP Check the indicator for the correct arguments if you receive this error.) isinstancerintr_is_nameappendr_is_talenprint)selfreq_argss_s Q/var/www/html/trading/venv/lib/python3.13/site-packages/pandas_ta/utils/_study.py __post_init__Study.__post_init__Ts djj# & &4::?tzzY[?XTZZDJCD ==?? OOW Y 77?DG\A d dA OOA  x=1 ' (x!U1Xx (  (s C9cjURSL=(d [UR[5(+$)N)rrstrrs r#rStudy._is_namejs$yyD B 499c(B$BBc "[UR[5(akUR5S:aW[ URVs/sH6n[U[ 5=(a [ UR55S:PM8 sn5$gs snf)NrF)rrlisttotal_taalldictrkeys)rr"s r#r Study._is_tansg dggt $ $1)<477S7a 1d+AAFFH 0AA7ST TTs=B cJURb[UR5$S$)Nr)rrr(s r#r-Study.total_taxs#ww2s477|99r*)rrN)__name__ __module__ __qualname____firstlineno____doc__r'__annotations__rr,rrrrrrrrr$rrr-__static_attributes__r*r#r r sX9t IT*B*+E3Kd+GS+,C:r*r AllzBAll the indicators with their default settings. Pandas TA default.N)rrrzCommon Price and Volume SMAsz6Common Price SMAs: 10, 20, 50, 200 and Volume SMA: 20.sma )kindlength2volumeVOL)r?closer@prefix)rrrr)multiprocessingr dataclassesrrpandas_ta._typingrrpandas_ta.utils._timer__all__r r r r;r*r#rMs%('*  g:g: g:X  T   'H "%"%"%#&R5I   r*