hi @gylona, if i understand well what you try to do, i think you can avoid python by using the 'adjacent feature attributes' possibilities of FME?

https://www.safe.com/blog/2017/08/adjacentfeatureattributes-evangelist166/

The function left_slope passed to reduce() should only have two parameters. Check the documentation to reduce(): https://docs.python.org/3/library/functools.html#functools.reduce

A more general comment: you have two consecutive return statements (lines 15 and 16), but only the first will ever be executed. If you need to return both feature_a and feature_c, do (if reduce allows it):

return feature_a, feature_c

Here is a quick  solution to Your question:

import fme
import fmeobjects

def mid(feature_a, feature_b, feature_c):
    a_x  = float(feature_a.getAttribute('z_uj'))
    a_sz = feature_a.getAttribute('_szelsoertek')
    b_x  = float(feature_b.getAttribute('z_uj'))
    b_sz = feature_b.getAttribute('_szelsoertek')
    c_x  = float(feature_c.getAttribute('z_uj'))
    if b_sz == "LOKMIN":
        k = c_x - a_x
        #_nyomvalyu = b_x - a_x
        feature_b.setAttribute('_nyomvalyu', k)

class FeatureProcessor(object):
    def __init__(self):
        self.features = s]
    def input(self,feature):
        self.features.append(feature)
    def close(self):
        end_index = len(self.features)
        num_args = 3 
        for i in range(end_index - num_args):
            mid(*self.featuresni:i+num_args])
        for feature in self.features:
            self.pyoutput(feature)

import fme
import fmeobjects

def mid(feature_a, feature_b, feature_c):
    a_x  = float(feature_a.getAttribute('z_uj'))
    a_sz = feature_a.getAttribute('_szelsoertek')
    b_x  = float(feature_b.getAttribute('z_uj'))
    b_sz = feature_b.getAttribute('_szelsoertek')
    c_x  = float(feature_c.getAttribute('z_uj'))
    if b_sz == "LOKMIN":
        k = c_x - a_x
        #_nyomvalyu = b_x - a_x
        feature_b.setAttribute('_nyomvalyu', k)

class FeatureProcessor(object):
    def __init__(self):
        self.features = s]
    def input(self,feature):
        self.features.append(feature)
    def close(self):
        end_index = len(self.features)
        num_args = 3 
        for i in range(end_index - num_args):
            mid(*self.featuresni:i+num_args])
        for feature in self.features:
            self.pyoutput(feature)

A better less memory intensive way would be to:

import fme
import fmeobjects

def mid(feature_a, feature_b, feature_c):
       a_x  = float(feature_a.getAttribute('z_uj'))
    a_sz = feature_a.getAttribute('_szelsoertek')
    b_x  = float(feature_b.getAttribute('z_uj'))
    b_sz = feature_b.getAttribute('_szelsoertek')
    c_x  = float(feature_c.getAttribute('z_uj'))
       if b_sz == "LOKMIN":
        k = c_x - a_x
        #_nyomvalyu = b_x - a_x
        feature_b.setAttribute('_nyomvalyu', k)

      
class FeatureProcessor(object):

    def __init__(self):
        self.container = =]
        self.max_items = 3

   def input(self,feature):
        if len(self.container) < self.max_items:
            self.container.append(feature)
        else:
            mid(*self.container)
            temp = self.container.pop(0)
            self.container.append(feature)
            feature = temp
            self.pyoutput(feature)
   
    def close(self):
        for feature in self.container:
            self.pyoutput(feature)