Remove closing strategies section from the docs

Author: gwaramadze

docs/windowing.md

@@ -729,73 +729,6 @@ Also, specifying a grace period using `grace_ms` will increase the latency, beca
 
 You can use `final()` mode when some latency is allowed, but the emitted results must be complete and unique.
 
-## Closing strategies
-
-By default, windows use the **key** closing strategy.  
-In this strategy, messages advance time and close only windows with the **same** message key.
-
-If some message keys appear irregularly in the stream, the latest windows can remain unprocessed until the message with the same key is received.
-
-```python
-from datetime import timedelta
-from quixstreams import Application
-from quixstreams.dataframe.windows import Sum
-
-app = Application(...)
-sdf = app.dataframe(...)
-
-# Calculate a sum of values over a window of 10 seconds 
-# and use .final() to emit results only when the window is complete
-sdf = sdf.tumbling_window(timedelta(seconds=10)).agg(value=Sum()).final(closing_strategy="key")
-
-# Details:
-# -> Timestamp=100, Key="A", value=1   -> emit nothing (the window is not closed yet) 
-# -> Timestamp=101, Key="B", value=2   -> emit nothing (the window is not closed yet) 
-# -> Timestamp=105, Key="C", value=3   -> emit nothing (the window is not closed yet) 
-# -> Timestamp=10100, Key="B", value=2 -> emit one message with key "B" and value {"start": 0, "end": 10000, "value": 2}, the time has progressed beyond the window end for the "B" key only.
-# -> Timestamp=8000, Key="A", value=1 -> emit nothing (the window is not closed yet)
-# -> Timestamp=10001, Key="A", value=1 -> emit one message with key "A" and value {"start": 0, "end": 10000, "value": 2}, the time has progressed beyond the window end for the "A" key.
-
-# Results:
-# (key="B", value={"start": 0, "end": 10000, "value": 2})
-# (key="A", value={"start": 0, "end": 10000, "value": 2})
-# No message for key "C" as the window is never closed since no messages with key "C" and a timestamp later than 10000 was received 
-```
-
-An alternative is to use the **partition** closing strategy.  
-In this strategy, messages advance time and close windows for the whole partition to which this key belongs.
-
-If messages aren't ordered accross keys some message can be skipped if the windows are already closed.
-
-```python
-from datetime import timedelta
-from quixstreams import Application
-from quixstreams.dataframe.windows import Sum
-
-app = Application(...)
-sdf = app.dataframe(...)
-
-# Calculate a sum of values over a window of 10 seconds 
-# and use .final() to emit results only when the window is complete
-sdf = sdf.tumbling_window(timedelta(seconds=10)).agg(value=Sum()).final(closing_strategy="partition")
-
-# Details:
-# -> Timestamp=100, Key="A", value=1   -> emit nothing (the window is not closed yet) 
-# -> Timestamp=101, Key="B", value=2   -> emit nothing (the window is not closed yet)
-# -> Timestamp=105, Key="C", value=3   -> emit nothing (the window is not closed yet) 
-# -> Timestamp=10100, Key="B", value=1 -> emit three messages, the time has progressed beyond the window end for all the keys in the partition
-#                                           1. first one with key "A" and value {"start": 0, "end": 10000, "value": 1}
-#                                           2. second one with key "B" and value {"start": 0, "end": 10000, "value": 2}
-#                                           3. third one with key "C" and value {"start": 0, "end": 10000, "value": 3}
-# -> Timestamp=8000, Key="A", value=1 -> emit nothing and value isn't part of the sum (the window is already closed)
-# -> Timestamp=10001, Key="A", value=1 -> emit nothing (the window is not closed yet)
-
-# Results:
-# (key="A", value={"start": 0, "end": 10000, "value": 1})
-# (key="B", value={"start": 0, "end": 10000, "value": 2})
-# (key="C", value={"start": 0, "end": 10000, "value": 3})
-```
-
 ## Transforming the result of a windowed aggregation
 Windowed aggregations return aggregated results in the following format/schema: