feat: interval& None value for prev&`next (#252)

* test: for builtin functions

* test: expect fail for `datetime()`

* feat: add `interval()` fn(WIP)

* feat: `interval()` fn in builtin(UNTEST)

* refactor: move `py_vec_obj_to_array` to util.rs

* style: fmt

* test: simple `interval()` cases

* test: `interval()` with `last()`&`first()`

* doc: `ts` param of `interval()`

* log: common_telemetry for logging in script crate

* doc: corrsponding test fn for each .ron file

* feat: change to`mpsc` for schedule_job

* test: schedule_job

* dep: rm rustpython dep in common-function

* refactor: mv `schedule_job` into `Script` trait

* test: change to use `interval` to sample datapoint

* feat: add gen_none_array for generate None Array

* feat: impl Missing value for `prev`&`next`

* test: `sum(prev(values))`

* doc: add comment for why not support Float16 in `prev()`

* feat: add `interval` in py side mock module

* style: cargo fmt

* refactor: according to comments

* refactor: extract `apply_interval_function`

* style: cargo fmt

* refactor: remove `schedule()`

* style: cargo fmt

component/script/python/greptime/greptime.py

@@ -89,6 +89,11 @@ class vector(np.ndarray):
     def filter(self, lst_bool):
         return self[lst_bool]
 
+def last(lst):
+    return lst[-1]
+
+def first(lst):
+    return lst[0]
 
 def prev(lst):
     ret = np.zeros(len(lst))
@@ -96,35 +101,22 @@ def prev(lst):
     ret[0] = nan
     return ret
 
+def next(lst):
+    ret = np.zeros(len(lst))
+    ret[:-1] = lst[1:]
+    ret[-1] = nan
+    return ret
 
-def query(sql: str):
-    pass
-
-
-def interval(arr: list, duration: int, fill, step: None | int = None, explicitOffset=False):
+def interval(ts: vector, arr: vector, duration: int, func):
     """
     Note that this is a mock function with same functionailty to the actual Python Coprocessor
     `arr` is a vector of integral or temporal type.
-
-    `duration` is the length of sliding window
-
-    `step` being the length when sliding window take a step
-
-    `fill` indicate how to fill missing value:
-    - "prev": use previous
-    - "post": next
-    - "linear": linear interpolation, if not possible to interpolate certain types, fallback to prev
-    - "null": use null
-    - "none": do not interpolate
     """
-    if step is None:
-        step = duration
-
-    tot_len = int(np.ceil(len(arr) // step))
-    slices = np.zeros((tot_len, int(duration)))
-    for idx, start in enumerate(range(0, len(arr), step)):
-        slices[idx] = arr[start:(start + duration)]
-    return slices
+    start = np.min(ts)
+    end = np.max(ts)
+    masks = [(ts >= i) & (ts <= (i+duration)) for i in range(start, end, duration)]
+    lst_res = [func(arr[mask]) for mask in masks]
+    return lst_res
 
 
 def factor(unit: str) -> int: