major overhaul of workflow arrangement, first fully working WF-100, WF-200

This commit is contained in:
Florian Förster 2026-01-28 16:05:08 +01:00
parent 3b2e0e5773
commit 4b31142d13
3 changed files with 382 additions and 163 deletions

View File

@ -12,6 +12,7 @@ from pprint import pprint
import dopt_basics.datetime as dt
import oracledb
import polars as pl
import polars.selectors as cs
import sqlalchemy as sql
from dopt_basics import configs, io
from sqlalchemy import event
@ -406,6 +407,7 @@ ORDER_QTY_CRIT: typing.Final[str] = "BEDP_MENGE_BEDARF_VM"
RESULT_COLUMN_ORDER: typing.Final[tuple[str, ...]] = tuple(
db.EXT_DOPT_ERGEBNIS.columns.keys()
)
ORDER_QTY_EXPR_KWARGS: typing.Final[types.OrderQtyExprKwArgs] = types.OrderQtyExprKwArgs()
def get_starting_date(
@ -491,7 +493,7 @@ def save_result_data_native(results: pl.DataFrame) -> None:
with engine.begin() as conn:
raw_conn = conn.connection.connection
with raw_conn.cursor() as cursor:
cursor.executemany(stmt, tmp.to_pandas(use_pyarrow_extension_array=True))
cursor.executemany(stmt, results.to_pandas(use_pyarrow_extension_array=True))
def _apply_several_filters(
@ -582,28 +584,15 @@ class PipelineResult:
self,
data: pl.DataFrame,
vorlage: bool,
wf_id: int,
wf_id: types.Workflows,
freigabe_auto: types.Freigabe,
is_out: bool,
order_qty_expr: pl.Expr,
) -> None:
results = data.rename(db.map_data_to_result)
# TODO rework because it is not WF-agnostic
order_qty_expr: pl.Expr
if is_out:
order_qty_expr = (
pl.lit(0)
.alias("ORDER_QTY_CRIT")
.alias("BEST_MENGE")
.cast(db.results_schema_map["BEST_MENGE"])
)
else:
order_qty_expr = pl.col(ORDER_QTY_CRIT).alias("best_menge")
results = results.with_columns(
[
# pl.lit(0).alias("ID").cast(db.results_schema_map["ID"]),
pl.lit(vorlage).alias("VORLAGE").cast(db.results_schema_map["VORLAGE"]),
pl.lit(wf_id).alias("WF_ID").cast(db.results_schema_map["WF_ID"]),
pl.lit(wf_id.value).alias("WF_ID").cast(db.results_schema_map["WF_ID"]),
order_qty_expr,
pl.lit(freigabe_auto.value)
.alias("FREIGABE_AUTO")
@ -621,14 +610,83 @@ class PipelineResult:
"MANDFUEHR",
]
)
# TODO remove
# results = results.select(RESULT_COLUMN_ORDER)
print(results)
print("####################")
# print(results)
# print("####################")
# print(self._results)
self._subtract_data(data)
self._add_results(results)
class ExprOrderQty(typing.Protocol): ...
class ExprOrderQty_Base(ExprOrderQty, typing.Protocol):
def __call__(self) -> pl.Expr: ...
ExprOrderQty_Base_Types: typing.TypeAlias = (
typing.Literal[types.Workflows.ID_200]
| typing.Literal[types.Workflows.ID_900]
| typing.Literal[types.Workflows.ID_910]
)
class ExprOrderQty_WF100(ExprOrderQty, typing.Protocol):
def __call__(self, empty: bool) -> pl.Expr: ...
@typing.overload
def get_expr_order_qty(
wf_id: typing.Literal[types.Workflows.ID_100],
) -> ExprOrderQty_WF100: ...
@typing.overload
def get_expr_order_qty(
wf_id: ExprOrderQty_Base_Types,
) -> ExprOrderQty_Base: ...
def get_expr_order_qty(
wf_id: types.Workflows,
) -> ExprOrderQty:
empty_expr = (
pl.lit(0)
.alias(ORDER_QTY_CRIT)
.alias("BEST_MENGE")
.cast(db.results_schema_map["BEST_MENGE"])
)
def _empty() -> pl.Expr:
return empty_expr
func: ExprOrderQty
match wf_id:
case types.Workflows.ID_100:
def _func(empty: bool) -> pl.Expr:
order_qty_expr: pl.Expr
if empty:
order_qty_expr = empty_expr
else:
order_qty_expr = pl.col(ORDER_QTY_CRIT).alias("BEST_MENGE")
return order_qty_expr
func = _func
case types.Workflows.ID_200 | types.Workflows.ID_900 | types.Workflows.ID_910:
func = _empty
case _:
raise NotImplementedError(
f"Order expression for WF-ID {wf_id.value} is not implemented"
)
return func
# post-processing the results
# TODO: order quantity not always necessary
# TODO: change relevant criterion for order quantity
@ -682,11 +740,11 @@ class PipelineResult:
# return pipe_result
def workflow_900(
def wf900(
pipe_result: PipelineResult,
) -> PipelineResult:
"""filter 'Meldenummer' and fill non-feasible entries"""
ORDER_QTY_FUNC = get_expr_order_qty(types.Workflows.ID_900)
filter_meldenummer_null = pl.col("MELDENUMMER").is_not_null()
filter_mandant = pl.col(MANDANT_CRITERION).is_in((1, 90))
res = _apply_several_filters(
@ -696,25 +754,29 @@ def workflow_900(
filter_mandant,
),
)
pipe_result.write_results(
data=res.out_,
vorlage=False,
wf_id=900,
wf_id=types.Workflows.ID_900,
freigabe_auto=types.Freigabe.WF_900,
is_out=True,
order_qty_expr=ORDER_QTY_FUNC(),
)
pipe_result.update_open(res.in_.with_columns(pl.col("MENGE_VORMERKER").fill_null(0)))
pipe_result.update_open(res.in_.with_columns(pl.col("BEDP_MENGE_BEDARF_VM").fill_null(0)))
pipe_result.update_open(
res.in_.with_columns(
pl.col("MENGE_VORMERKER").fill_null(0),
pl.col("BEDP_MENGE_BEDARF_VM").fill_null(0),
)
)
return pipe_result
def workflow_910(
def wf910(
pipe_result: PipelineResult,
) -> PipelineResult:
# TODO check if necessary because of WF-900
ORDER_QTY_FUNC = get_expr_order_qty(types.Workflows.ID_910)
filter_mandant = pl.col(MANDANT_CRITERION).is_in((1, 90))
filter_ignore_MNR26 = pl.col("MELDENUMMER") != 26
@ -726,13 +788,12 @@ def workflow_910(
filter_ignore_MNR26,
),
)
# write results for entries which were filtered out
pipe_result.write_results(
data=res.out_,
vorlage=False,
wf_id=910,
wf_id=types.Workflows.ID_910,
freigabe_auto=types.Freigabe.WF_910,
is_out=True,
order_qty_expr=ORDER_QTY_FUNC(),
)
return pipe_result
@ -740,10 +801,12 @@ def workflow_910(
# this a main routine:
# receives and gives back result objects
def workflow_100_umbreit(
def wf100_umbreit(
pipe_result: PipelineResult,
vm_criterion: str,
) -> PipelineResult:
ORDER_QTY_FUNC = get_expr_order_qty(types.Workflows.ID_100)
filter_meldenummer = pl.col("MELDENUMMER") == 18
filter_mandant = pl.col(MANDANT_CRITERION) == 1
filter_number_vm = pl.col(vm_criterion) > 0
@ -758,19 +821,20 @@ def workflow_100_umbreit(
)
pipe_result.write_results(
data=res.in_,
vorlage=True,
wf_id=100,
vorlage=False,
wf_id=types.Workflows.ID_100,
freigabe_auto=types.Freigabe.WF_100,
is_out=False,
order_qty_expr=ORDER_QTY_FUNC(empty=False),
)
return pipe_result
def workflow_100_petersen(
def wf100_petersen(
pipe_result: PipelineResult,
vm_criterion: str,
) -> PipelineResult:
ORDER_QTY_FUNC = get_expr_order_qty(types.Workflows.ID_100)
# difference WDB and others
# // WDB branch
@ -788,19 +852,17 @@ def workflow_100_petersen(
filter_number_vm,
),
)
pipe_result.write_results(
data=res.in_,
vorlage=False,
wf_id=100,
wf_id=types.Workflows.ID_100,
freigabe_auto=types.Freigabe.WF_100,
is_out=False,
order_qty_expr=ORDER_QTY_FUNC(empty=True),
)
# TODO add check for orders or quantity to transform
# TODO show them
filter_meldenummer = pl.col("MELDENUMMER") == 18
filter_mandant = pl.col(MANDANT_CRITERION) == 90
filter_WDB = pl.col("VERLAGSNR").is_in((76008, 76070))
filter_number_vm = pl.col(vm_criterion) > 0
res_candidates = _apply_several_filters(
pipe_result.open,
@ -812,14 +874,12 @@ def workflow_100_petersen(
),
)
wdb_sub_pipe = PipelineResult(res_candidates.in_)
wdb_sub_pipe = wf100_petersen_wdb_sub1(wdb_sub_pipe)
assert len(wdb_sub_pipe.open) == 0
wdb_sub_pipe = _wf100_petersen_sub1_wdb(wdb_sub_pipe)
assert wdb_sub_pipe.open.height == 0
pipe_result.merge_pipeline(wdb_sub_pipe)
# // other branch
# show always entries with #VM > 1
filter_meldenummer = pl.col("MELDENUMMER") == 18
filter_mandant = pl.col(MANDANT_CRITERION) == 90
filter_number_vm = pl.col(vm_criterion) > 1
res = _apply_several_filters(
pipe_result.open,
@ -832,13 +892,11 @@ def workflow_100_petersen(
pipe_result.write_results(
data=res.in_,
vorlage=True,
wf_id=100,
wf_id=types.Workflows.ID_100,
freigabe_auto=types.Freigabe.WF_100,
is_out=False,
order_qty_expr=ORDER_QTY_FUNC(empty=False),
)
filter_meldenummer = pl.col("MELDENUMMER") == 18
filter_mandant = pl.col(MANDANT_CRITERION) == 90
filter_number_vm = pl.col(vm_criterion) > 0
res = _apply_several_filters(
pipe_result.open,
@ -850,18 +908,19 @@ def workflow_100_petersen(
)
pipe_result.write_results(
data=res.in_,
vorlage=True,
wf_id=100,
vorlage=False,
wf_id=types.Workflows.ID_100,
freigabe_auto=types.Freigabe.WF_100,
is_out=False,
order_qty_expr=ORDER_QTY_FUNC(empty=False),
)
return pipe_result
def wf100_petersen_wdb_sub1(
def _wf100_petersen_sub1_wdb(
pipe_result: PipelineResult,
) -> PipelineResult:
ORDER_QTY_FUNC = get_expr_order_qty(types.Workflows.ID_100)
# input: pre-filtered entries (WDB titles and #VM > 0)
# more then 1 VM
# !! show these entries
@ -873,9 +932,9 @@ def wf100_petersen_wdb_sub1(
pipe_result.write_results(
data=res.in_,
vorlage=True,
wf_id=100,
wf_id=types.Workflows.ID_100,
freigabe_auto=types.Freigabe.WF_100,
is_out=False,
order_qty_expr=ORDER_QTY_FUNC(empty=False),
)
# filtered out entries (WDB with #VM == 1) must be analysed for orders in the
@ -892,21 +951,143 @@ def wf100_petersen_wdb_sub1(
.agg(pl.col("BESP_TITELNR").count().alias("count"))
.filter(pl.col("count") > 1)
)
# TODO IS IN check good because of performance?
filter_titleno = pl.col("BEDP_TITELNR").is_in(entries_show["BESP_TITELNR"].to_list())
res = _apply_several_filters(pipe_result.open, (filter_titleno,))
pipe_result.write_results(
data=res.in_,
vorlage=True,
wf_id=100,
wf_id=types.Workflows.ID_100,
freigabe_auto=types.Freigabe.WF_100,
is_out=False,
order_qty_expr=ORDER_QTY_FUNC(empty=False),
)
pipe_result.write_results(
data=pipe_result.open,
vorlage=False,
wf_id=100,
wf_id=types.Workflows.ID_100,
freigabe_auto=types.Freigabe.WF_100,
is_out=False,
order_qty_expr=ORDER_QTY_FUNC(empty=False),
)
return pipe_result
def wf200_umbreit(
pipe_result: PipelineResult,
) -> PipelineResult:
relevant_mnr: tuple[int, ...] = (17, 18)
filter_meldenummer = pl.col("MELDENUMMER").is_in(relevant_mnr)
filter_mandant = pl.col("BEDP_MAN") == 1
res = _apply_several_filters(
pipe_result.open,
(filter_meldenummer, filter_mandant),
)
sub_pipe = PipelineResult(res.in_)
sub_pipe = _wf200_sub1(sub_pipe)
assert sub_pipe.open.height == 0
pipe_result.merge_pipeline(sub_pipe)
return pipe_result
def wf200_petersen(
pipe_result: PipelineResult,
) -> PipelineResult:
ORDER_QTY_FUNC = get_expr_order_qty(types.Workflows.ID_200)
RELEVANT_MNR: tuple[int, ...] = (17, 18)
# // WDB branch
filter_meldenummer = pl.col("MELDENUMMER").is_in(RELEVANT_MNR)
filter_mandant = pl.col(MANDANT_CRITERION) == 90
filter_WDB = pl.col("VERLAGSNR").is_in((76008, 76070))
res = _apply_several_filters(
pipe_result.open,
(
filter_meldenummer,
filter_mandant,
filter_WDB,
),
)
# ignore these
pipe_result.write_results(
data=res.in_,
vorlage=False,
wf_id=types.Workflows.ID_200,
freigabe_auto=types.Freigabe.WF_200,
order_qty_expr=ORDER_QTY_FUNC(),
)
# // other branch
res = _apply_several_filters(
pipe_result.open,
(
filter_meldenummer,
filter_mandant,
),
)
sub_pipe = PipelineResult(res.in_)
sub_pipe = _wf200_sub1(sub_pipe)
assert sub_pipe.open.height == 0
pipe_result.merge_pipeline(sub_pipe)
return pipe_result
def _wf200_sub1(
pipe_result: PipelineResult,
) -> PipelineResult:
save_tmp_data(pipe_result.open)
ORDER_QTY_FUNC = get_expr_order_qty(types.Workflows.ID_200)
RELEVANT_DATE = get_starting_date(90)
join_condition = db.tmp_data.c.BEDP_TITELNR == db.EXT_AUFPAUF.c.TITELNR
filter_ = sql.and_(
db.EXT_AUFPAUF.c.AUFTRAGS_DATUM >= RELEVANT_DATE,
db.EXT_AUFPAUF.c.KUNDE_RECHNUNG.not_in((608991, 260202)),
db.EXT_AUFPAUF.c.AUFTRAGS_ART.in_((1, 99)),
)
stmt = (
sql.select(
db.tmp_data,
db.EXT_AUFPAUF.c.KUNDE_RECHNUNG,
db.EXT_AUFPAUF.c.AUFTRAGS_ART,
)
.select_from(db.tmp_data.join(db.EXT_AUFPAUF, join_condition))
.where(filter_)
)
sub1 = stmt.subquery()
unique_count_col = sql.func.count(sub1.c.KUNDE_RECHNUNG.distinct())
stmt = (
sql.select(
sub1.c.BEDP_TITELNR,
sql.func.count().label("count"),
unique_count_col.label("customer_count"),
)
.select_from(sub1)
.group_by(sub1.c.BEDP_TITELNR)
.having(unique_count_col >= 3)
)
relevant_titles = pl.read_database(
stmt,
engine,
)
entries_to_show = pipe_result.open.filter(
pl.col.BEDP_TITELNR.is_in(relevant_titles["BEDP_TITELNR"].unique().implode())
)
pipe_result.write_results(
data=entries_to_show,
vorlage=True,
wf_id=types.Workflows.ID_200,
freigabe_auto=types.Freigabe.WF_200,
order_qty_expr=ORDER_QTY_FUNC(),
)
pipe_result.write_results(
data=pipe_result.open,
vorlage=False,
wf_id=types.Workflows.ID_200,
freigabe_auto=types.Freigabe.WF_200,
order_qty_expr=ORDER_QTY_FUNC(),
)
return pipe_result
@ -963,7 +1144,7 @@ raw_data = df.clone()
# pipe_res = get_empty_pipeline_result(raw_data)
pipe_res = PipelineResult(raw_data)
pipe_res.results
pipe_res = workflow_900(pipe_res)
pipe_res = wf900(pipe_res)
print(f"Length of base data: {len(raw_data):>18}")
print(f"Number of entries pipe data: {len(pipe_res):>10}")
print(f"Number of entries result data: {len(pipe_res.results):>8}")
@ -977,60 +1158,11 @@ pipe_res.results
res = pipe_res.results.clone()
res.height
# %%
# %%
# %%
save_result_data(res)
get_result_data()
# %%
clear_result_data()
# %%
get_result_data()
# %%
stmt = sql.text("TRUNCATE TABLE EXT_DOPT_ERGEBNIS")
with engine.begin() as conn:
conn.exec_driver_sql("TRUNCATE TABLE UMB.EXT_DOPT_ERGEBNIS")
# %%
stmt = sql.insert(db.EXT_DOPT_ERGEBNIS)
print(stmt.compile(engine))
# %%
engine.dispose()
# %%
# %%
t1 = time.perf_counter()
save_result_data(res)
t2 = time.perf_counter()
print(f"Elapsed: {t2 - t1}")
# %%
get_result_data()
# %%
clear_result_data()
get_result_data()
# %%
t1 = time.perf_counter()
raw_input(res)
t2 = time.perf_counter()
print(f"Elapsed: {t2 - t1}")
# %%
# %%
# raw_data.filter(pl.col("BEDARFNR") == 166982).filter(pl.col("BEDP_SEQUENZ") == 1)
# %%
# pipe_res.open.filter(pl.col("BEDP_MENGE_BEDARF_VM") > pl.col("MENGE_VORMERKER"))
# %%
pipe_res = workflow_910(pipe_res)
pipe_res = wf910(pipe_res)
print(f"Length of base data: {len(raw_data):>18}")
print(f"Number of entries pipe data: {len(pipe_res):>10}")
print(f"Number of entries result data: {len(pipe_res.results):>8}")
@ -1038,30 +1170,33 @@ print(f"Number of entries open data: {len(pipe_res.open):>10}")
# %%
# pipe_res.results.select(pl.col("vorlage").value_counts())
# %%
pipe_res = workflow_100_umbreit(pipe_res, VM_CRITERION)
pipe_res = wf100_umbreit(pipe_res, VM_CRITERION)
print(f"Length of base data: {len(raw_data):>18}")
print(f"Number of entries pipe data: {len(pipe_res):>10}")
print(f"Number of entries result data: {len(pipe_res.results):>8}")
print(f"Number of entries open data: {len(pipe_res.open):>10}")
# %%
pipe_res = workflow_100_petersen(pipe_res, VM_CRITERION)
pipe_res = wf100_petersen(pipe_res, VM_CRITERION)
print(f"Length of base data: {len(raw_data):>18}")
print(f"Number of entries pipe data: {len(pipe_res):>10}")
print(f"Number of entries result data: {len(pipe_res.results):>8}")
print(f"Number of entries open data: {len(pipe_res.open):>10}")
# %%
pipe_res.open.filter(pl.col.MELDENUMMER == 18).filter(pl.col.BEDP_MENGE_BEDARF_VM > 0)
pipe_res = wf200_umbreit(pipe_res)
print(f"Length of base data: {len(raw_data):>18}")
print(f"Number of entries pipe data: {len(pipe_res):>10}")
print(f"Number of entries result data: {len(pipe_res.results):>8}")
print(f"Number of entries open data: {len(pipe_res.open):>10}")
# %%
pipe_res.results.select(pl.col("vorlage").value_counts())
pipe_res = wf200_petersen(pipe_res)
print(f"Length of base data: {len(raw_data):>18}")
print(f"Number of entries pipe data: {len(pipe_res):>10}")
print(f"Number of entries result data: {len(pipe_res.results):>8}")
print(f"Number of entries open data: {len(pipe_res.open):>10}")
# %%
pipe_res.results.filter(pl.col("vorlage") == True)
pipe_res.open.filter(pl.col.MELDENUMMER.is_in((17, 18)))
# %%
raw_data.filter(pl.col("BEDARFNR") == 922160).filter(pl.col("BEDP_SEQUENZ") == 3)
# %%
raw_data.head()
pipe_res.results.select(pl.col("VORLAGE").value_counts())
# %%
# ---------------------------------------------------------------------------- #
# Workflow 200 (Umbreit only)
@ -1072,26 +1207,14 @@ wf_200_start_data
# %%
def workflow_200_umbreit(
pipe_result: PipelineResult,
) -> PipelineResult:
relevant_mnr: tuple[int, ...] = (17, 18)
filter_meldenummer = pl.col("MELDENUMMER").is_in(relevant_mnr)
filter_mandant = pl.col("BEDP_MAN") == 1
# not relevant, because already done in WF-100
# filter_number_vm = pl.col(vm_criterion) == 0
res = _apply_several_filters(
pipe_result.open,
(filter_meldenummer, filter_mandant),
)
# %%
relevant_mnr: tuple[int, ...] = (17, 18)
filter_meldenummer = pl.col("MELDENUMMER").is_in(relevant_mnr)
filter_mandant = pl.col("BEDP_MAN") == 1
res = _apply_several_filters(
pipe_res.open,
wf_200_start_data,
(filter_meldenummer, filter_mandant),
)
# %%
@ -1104,52 +1227,136 @@ res = _apply_several_filters(
# -- JOIN ON temp.BEDP_TITELNR = EXT_AUFPAUF.TITELNR
# -- WHERE EXT_AUFPAUF.AUFTRAGS_DATUM > (CURRENT_DATE - 3 months) AND
# -- EXT_AUFPAUF.KUNDE_RECHNUNG NOT IN (608991, 260202) AND
# --
res.in_
#
# this is a separate sub-pipeline like in Petersen WF-100
# these entries are either to be shown or not
sub_pipe_umbreit = PipelineResult(res.in_)
# %%
sub_pipe_umbreit.open
# %%
# %%
save_tmp_data(sub_pipe_umbreit.open)
# %%
# // demo query with IN statement
data = res.in_.clone()
title_sub_choice = data["BEDP_TITELNR"][:300].to_list()
rel_date = get_starting_date(90)
rel_date
# %%
# old way using in statements
# filter_ = sql.and_(
# db.EXT_AUFPAUF.c.TITELNR.in_(title_sub_choice),
# db.EXT_AUFPAUF.c.AUFTRAGS_DATUM >= rel_date,
# db.EXT_AUFPAUF.c.KUNDE_RECHNUNG.not_in((608991, 260202)),
# )
# join_condition = db.tmp_data.c.BEDP_TITELNR == db.EXT_AUFPAUF.c.TITELNR
# filter_ = sql.and_(
# db.EXT_AUFPAUF.c.AUFTRAGS_DATUM >= rel_date,
# db.EXT_AUFPAUF.c.KUNDE_RECHNUNG.not_in((608991, 260202)),
# db.EXT_AUFPAUF.c.AUFTRAGS_ART.in_((1, 99)),
# )
# stmt = (
# sql.select(
# db.tmp_data,
# db.EXT_AUFPAUF.c.KUNDE_RECHNUNG,
# db.EXT_AUFPAUF.c.AUFTRAGS_ART,
# )
# .select_from(db.tmp_data.join(db.EXT_AUFPAUF, join_condition))
# .where(filter_)
# )
# print(stmt.compile(engine))
# new_schema = db.EXT_AUFPAUF_schema_map.copy()
# new_schema.update(db.tmp_data_schema_map)
# new_schema
# %%
# demo = pl.read_database(
# stmt,
# engine,
# schema_overrides=db.EXT_AUFPAUF_schema_map,
# )
# # %%
# demo
# # %%
# demo.select(pl.col.AUFTRAGS_ART).unique()
# %%
get_tmp_data()
# %%
# demo_2 = demo.clone()
# # demo_2.head()
# print(f"Number of titles before filtering: {len(demo_2)}")
# demo_2 = demo_2.filter(pl.col.AUFTRAGS_ART.is_in((1, 99)))
# demo_2 = (
# demo_2.group_by("BEDP_TITELNR", maintain_order=True)
# .agg(
# pl.len().alias("count"),
# pl.col.KUNDE_RECHNUNG.n_unique().alias("customer_count"),
# )
# .filter(pl.col.customer_count >= 3)
# )
# # these remaining titles are relevant and should be shown
# # the others should be disposed
# print(f"Number of titles which are relevant: {len(demo_2)}")
# print(f"Number of titles which are to be disposed: {len(demo) - len(demo_2)}")
# demo_2
# %%
# make a subquery for the pre-filtered entries
# // query to obtain relevant title numbers
join_condition = db.tmp_data.c.BEDP_TITELNR == db.EXT_AUFPAUF.c.TITELNR
filter_ = sql.and_(
db.EXT_AUFPAUF.c.TITELNR.in_(title_sub_choice),
db.EXT_AUFPAUF.c.AUFTRAGS_DATUM >= rel_date,
db.EXT_AUFPAUF.c.KUNDE_RECHNUNG.not_in((608991, 260202)),
db.EXT_AUFPAUF.c.AUFTRAGS_ART.in_((1, 99)),
)
stmt = (
sql.select(
db.tmp_data,
db.EXT_AUFPAUF.c.KUNDE_RECHNUNG,
db.EXT_AUFPAUF.c.AUFTRAGS_ART,
)
.select_from(db.tmp_data.join(db.EXT_AUFPAUF, join_condition))
.where(filter_)
)
sub1 = stmt.subquery()
unique_count_col = sql.func.count(sub1.c.KUNDE_RECHNUNG.distinct())
stmt = (
sql.select(
sub1.c.BEDP_TITELNR,
sql.func.count().label("count"),
unique_count_col.label("customer_count"),
)
.select_from(sub1)
.group_by(sub1.c.BEDP_TITELNR)
.having(unique_count_col >= 3)
)
stmt = sql.select(db.EXT_AUFPAUF).where(filter_)
print(stmt.compile(engine))
# %%
demo = pl.read_database(
demo_agg = pl.read_database(
stmt,
engine,
schema_overrides=db.EXT_AUFPAUF_schema_map,
)
# %%
demo.head()
demo_agg
# %%
demo_2 = demo.clone()
demo_2.head()
print(f"Number of titles before filtering: {len(demo_2)}")
demo_2 = demo_2.filter(pl.col.AUFTRAGS_ART.is_in((1, 99)))
demo_2 = (
demo_2.group_by("TITELNR", maintain_order=True)
.agg(
pl.len().alias("count"),
pl.col.KUNDE_RECHNUNG.n_unique().alias("customer_count"),
)
.filter(pl.col.customer_count >= 3)
)
sub_pipe_umbreit.open
# sub_pipe_umbreit.open.select("BEDP_TITELNR").n_unique()
# these remaining titles are relevant and should be shown
# the others should be disposed
print(f"Number of titles which are relevant: {len(demo_2)}")
print(f"Number of titles which are to be disposed: {len(demo) - len(demo_2)}")
demo_2
# %%
# now obtain these entries from the open data
demo_agg["BEDP_TITELNR"].unique().implode()
entries_to_show = sub_pipe_umbreit.open.filter(
pl.col.BEDP_TITELNR.is_in(demo_agg["BEDP_TITELNR"].unique().implode())
)
entries_to_show
# %%
sub_pipe_umbreit.open
# %%
df, filt_out = _init_workflow_200_umbreit(results, wf_200_start_data, VM_CRITERION)
df

View File

@ -141,7 +141,7 @@ EXT_BESPBES_INFO_null_values: PolarsNullValues = {}
EXT_AUFPAUF = Table(
"EXT_AUFPAUF",
metadata,
Column("TITELNR", sql.Integer, nullable=False),
Column("TITELNR", sql.Integer, primary_key=True, autoincrement=False, nullable=False),
Column("AUFTRAGSNUMMER", sql.Integer, nullable=False),
Column("AUFTRAGS_DATUM", sql.DateTime, nullable=False),
Column("AUFTRAGS_ART", sql.Integer, nullable=False),

View File

@ -25,6 +25,18 @@ class FilterResult:
# return len(self.results) + len(self.open)
class Workflows(enum.Enum):
ID_100 = 100
ID_200 = 200
ID_900 = 900
ID_910 = 910
@dataclass(slots=True, repr=False, eq=False)
class OrderQtyExprKwArgs:
empty: bool = False
class Freigabe(enum.Enum):
WF_100 = False
WF_200 = False