熱血巴!衝浪怪獸!Kirin!

如何抓到峰值(支撐位) InfluxDB / Grafana 先畫出基本線圖 from ( bucket : "quote" ) | > range ( start : v . timeRangeStart , stop : v . timeRangeStop ) | > filter ( fn : ( r ) => r . _measurement == "daily" and r . valmean == "high" and r . symbol == "${symbolSel}" ) 找出低點支撐位 這時候就可以透過 min來找出一段區間的 最低位 from ( bucket : "quote" ) | > range ( start : v . timeRangeStart , stop : v . timeRangeStop ) | > filter ( fn : ( r ) => r . _measurement == "daily" and r . valmean == "high" and r . symbol == "${symbolSel}" ) | > window ( every : 15 d ) | > min ( ) 可以去調整  every: 15d  來去決定低點的區間 把這些低點變成曲線 目前序列都變成單獨的點 可以透過以下語法再把點變成序列 | > window ( every : inf ) 整合 完整flux from ( bucket : "quote" ) | > range ( start : v . timeRangeStart , stop : v . timeRangeStop ) | > filter ( fn : ( r )

InfluxDB Flux & Grafana 整合筆記  留言 基本查詢 from ( bucket : "quote" ) | > range ( start : v . timeRangeStart , stop : v . timeRangeStop ) | > filter ( fn : ( r ) => r . _measurement == "realtime" and r . symbol == "${symbolSel}" and r . _field == "volume_24h" ) 兩個序列 join join ( tables : { t1 : t1 , t2 : t2 } , on : [ "_time" ] ) | > map ( fn : ( r ) => ( { r with _value : ( r . _value_t1 - r . _value_t2 ) / r . _value_t2 } ) ) | > map ( fn : ( r ) => ( { r with alias : "120d 投資比" } ) ) pivot 同序列不同欄位 join | > pivot ( rowKey : [ "_time" ] , columnKey : [ "valmean" ] , valueColumn : "_value" ) | > map ( fn : ( r ) => ( { r with _value : r . volume / r . open } ) ) 時間粗化 | > map ( fn : ( r ) => ( { r with _time : date . truncate ( t : r . _time , unit

  Python **kwargs 的實測   都必填 都有帶入值 def test_func ( a1, a2 ): print(a1) print(a2) if __name__ == '__main__' : d = dict () d[ 'a1' ] = 1 d[ 'a2' ] = 2 test_func(**d) out put 1 2 有值未帶入 def test_func ( a1, a2 ): print(a1) print(a2) if __name__ == '__main__' : d = dict () d[ 'a1' ] = 1 test_func(**d) out put Traceback (most recent call last): File "xxx/main.py" , line 44, in <module> test_func(**d) TypeError: test_func() missing 1 required positional argument: 'a2' 有預設值參數 def test_func ( a1, a2= None ): print(a1) print(a2) if __name__ == '__main__' : d = dict () d[ 'a1' ] = 1 test_func(**d) output 1 None 帶入沒有該參數的key & value (unexpected-keyword-arguments) def test_func ( a1, a2= None ): print(a1) print(a2) if __name__ == '__main__' : d = dict ()