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batch-analytics
Commit 25142ce7 authored by aakash.bedi's avatar aakash.bedi
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batch_master_qty logic added

parent a4ad1f05
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Showing with 170 additions and 138 deletions
app.py
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...@@ -33,7 +33,46 @@ class BatchMaster: ...@@ -33,7 +33,46 @@ class BatchMaster:
logger.exception(f"Exception - {e}") logger.exception(f"Exception - {e}")
@staticmethod @staticmethod
def preprocess_master_df_proto(df, process_stage_name): def batch_master(df, process_stage_name, batch_product, ideal_batch_cycle_time_hr, batch_setup_time_hr,
process_stage_id, work_order_no="P2E-STD-01", work_order_item_no="P2E-STD-01-01",
final_product="P2E"):
try:
df = df[['Batch Number', 'Start Time.1', 'End Time.1', 'Downtime', 'Equipment']]
df.rename(columns={'Batch Number': 'batch_no', 'Start Time.1': 'batch_start_time',
'End Time.1': 'batch_end_time', 'Downtime': 'downtime',
'Equipment': 'used_equipment'}, inplace=True)
df['live_batch_end_time'] = None
df['process_stage_name'] = process_stage_name
df['process_stage_id'] = process_stage_id
df['work_order_no'] = work_order_no
df['work_order_item_no'] = work_order_item_no
df['final_product'] = final_product
df['batch_product'] = batch_product
df['ideal_batch_cycle_time_hr'] = ideal_batch_cycle_time_hr
df['batch_cycle_time'] = df['batch_end_time'] - df['batch_start_time']
df['batch_cycle_time_minutes'] = df['batch_cycle_time'].dt.total_seconds() // 60
df['batch_setup_time_hr'] = batch_setup_time_hr
df['selected_equipments'] = df['used_equipment']
df['created_on'] = df['batch_start_time'].dt.date
df['created_by'] = 'Aakash'
df['last_updated_on'] = df['batch_end_time'].dt.date
df['last_updated_by'] = 'Aakash'
df['golden_batch'] = None
df = df.astype({'batch_cycle_time': str})
df = df[['batch_no', 'final_product', 'batch_product', 'process_stage_name', 'process_stage_id',
'work_order_no', 'work_order_item_no', 'ideal_batch_cycle_time_hr', 'batch_start_time',
'batch_end_time', 'live_batch_end_time', 'batch_cycle_time', 'batch_cycle_time_minutes',
'batch_setup_time_hr', 'downtime', 'selected_equipments', 'created_on', 'created_by',
'last_updated_on', 'last_updated_by', 'golden_batch']]
df.reset_index(drop=True, inplace=True)
return df
except Exception as e:
logger.exception(f"Exception - {e}")
@staticmethod
def batch_material_master(df, process_stage_name):
try: try:
df.rename(columns={'Batch Number': 'batch_no', 'Start Time.1': 'batch_start_time', df.rename(columns={'Batch Number': 'batch_no', 'Start Time.1': 'batch_start_time',
'End Time.1': 'batch_end_time', 'Downtime': 'downtime', 'End Time.1': 'batch_end_time', 'Downtime': 'downtime',
...@@ -43,9 +82,6 @@ class BatchMaster: ...@@ -43,9 +82,6 @@ class BatchMaster:
df_stage['batch_no'] = df['batch_no'] df_stage['batch_no'] = df['batch_no']
df_stage['input_qty'] = df['Input Qty. (kg) F00056-BULK-001'] df_stage['input_qty'] = df['Input Qty. (kg) F00056-BULK-001']
df_stage['input_qty_uom'] = 'kg' df_stage['input_qty_uom'] = 'kg'
df_stage['formaldehyde_content'] = df['F00041-BULK-001 content nil']
df_stage['unreactive_alpha_picoline'] = df['un reacted F00056-BULK-001 ( for infor.)']
df_stage['moisture_content'] = df['Moisture content \n(for infor)']
df_stage['output_qty'] = df['Output Qty. (kg)'] df_stage['output_qty'] = df['Output Qty. (kg)']
df_stage['output_qty_uom'] = 'kg' df_stage['output_qty_uom'] = 'kg'
...@@ -53,9 +89,6 @@ class BatchMaster: ...@@ -53,9 +89,6 @@ class BatchMaster:
df_stage['batch_no'] = df['batch_no'] df_stage['batch_no'] = df['batch_no']
df_stage['input_qty'] = df['Input Qty.\n(kg) Stage-I'] df_stage['input_qty'] = df['Input Qty.\n(kg) Stage-I']
df_stage['input_qty_uom'] = 'kg' df_stage['input_qty_uom'] = 'kg'
df_stage['formaldehyde_content'] = None
df_stage['unreactive_alpha_picoline'] = df['F00056-BULK-001 \n(NLT 50 %)']
df_stage['moisture_content'] = df['Moisture content \n(for Information).1']
df_stage['output_qty'] = df['Output \nQty. (kg)'] df_stage['output_qty'] = df['Output \nQty. (kg)']
df_stage['output_qty_uom'] = 'kg' df_stage['output_qty_uom'] = 'kg'
...@@ -63,200 +96,199 @@ class BatchMaster: ...@@ -63,200 +96,199 @@ class BatchMaster:
df_stage['batch_no'] = df['batch_no'] df_stage['batch_no'] = df['batch_no']
df_stage['input_qty'] = df['Input Qty. (kg) Stage-I'] df_stage['input_qty'] = df['Input Qty. (kg) Stage-I']
df_stage['input_qty_uom'] = 'kg' df_stage['input_qty_uom'] = 'kg'
df_stage['formaldehyde_content'] = None
df_stage['unreactive_alpha_picoline'] = None
df_stage['moisture_content'] = df['M/C for infor']
df_stage['output_qty'] = df['Output Qty. (kg)'] df_stage['output_qty'] = df['Output Qty. (kg)']
df_stage['output_qty_uom'] = 'kg' df_stage['output_qty_uom'] = 'kg'
elif process_stage_name == "Stage-04": elif process_stage_name == "Stage-04":
df_stage['batch_no'] = df['batch_no'] df_stage['batch_no'] = df['batch_no']
df_stage['input_qty'] = None df_stage['input_qty'] = df['Input Qty. (kg)\n/Stage-I']
df_stage['input_qty_uom'] = 'kg' df_stage['input_qty_uom'] = 'kg'
df_stage['formaldehyde_content'] = None df_stage['output_qty'] = df['Output \nQty. (kg)']
df_stage['unreactive_alpha_picoline'] = None
df_stage['moisture_content'] = df['NMT 0.5%']
df_stage['output_qty'] = None
df_stage['output_qty_uom'] = 'kg' df_stage['output_qty_uom'] = 'kg'
elif process_stage_name == "Stage-05": elif process_stage_name == "Stage-05":
df_stage['batch_no'] = df['batch_no'] df_stage['batch_no'] = df['batch_no']
df_stage['input_qty'] = None df_stage['input_qty'] = df['Input \nQty. Kg\nStage-I']
df_stage['input_qty_uom'] = 'kg' df_stage['input_qty_uom'] = 'kg'
df_stage['formaldehyde_content'] = None df_stage['output_qty'] = df['Output \nQty. (kg)']
df_stage['unreactive_alpha_picoline'] = None
df_stage['moisture_content'] = df[' NMT 1.0%']
df_stage['output_qty'] = None
df_stage['output_qty_uom'] = 'kg' df_stage['output_qty_uom'] = 'kg'
df_stage.reset_index(drop=True, inplace=True) df_stage.reset_index(drop=True, inplace=True)
df_stage = df_stage[['batch_no', 'input_qty', 'input_qty_uom', 'formaldehyde_content', df_stage = df_stage[['batch_no', 'input_qty', 'input_qty_uom', 'output_qty', 'output_qty_uom']]
'unreactive_alpha_picoline', 'moisture_content', 'output_qty',
'output_qty_uom']]
return df_stage return df_stage
except Exception as e: except Exception as e:
logger.exception(f"Exception - {e}") logger.exception(f"Exception - {e}")
@staticmethod @staticmethod
def preprocess_master_df(df, process_stage_name, batch_product, ideal_batch_cycle_time_hr, batch_setup_time_hr, def batch_kpi_master(df, process_stage_name, process_stage_id):
process_stage_id, work_order_no="P2E-STD-01", work_order_item_no="P2E-STD-01-01",
final_product="P2E-Stage-05"):
try: try:
df = df[['Batch Number', 'Start Time.1', 'End Time.1', 'Downtime', 'Equipment']]
df.rename(columns={'Batch Number': 'batch_no', 'Start Time.1': 'batch_start_time', df.rename(columns={'Batch Number': 'batch_no', 'Start Time.1': 'batch_start_time',
'End Time.1': 'batch_end_time', 'Downtime': 'downtime', 'End Time.1': 'batch_end_time', 'Quality': 'quality'}, inplace=True)
'Equipment': 'used_equipment'}, inplace=True)
df['process_stage_name'] = process_stage_name df['process_stage_name'] = process_stage_name
df['process_stage_id'] = process_stage_id df['process_stage_id'] = process_stage_id
df['work_order_no'] = work_order_no
df['work_order_item_no'] = work_order_item_no
df['final_product'] = final_product
df['batch_product'] = batch_product
df['ideal_batch_cycle_time_hr'] = ideal_batch_cycle_time_hr
df['batch_cycle_time'] = df['batch_end_time'] - df['batch_start_time']
df['batch_cycle_time_minutes'] = df['batch_cycle_time'].dt.total_seconds() // 60
df['batch_setup_time_hr'] = batch_setup_time_hr
df['selected_equipments'] = df['used_equipment']
df['created_on'] = df['batch_start_time'].dt.date
df['created_by'] = 'Aakash'
df['last_updated_on'] = df['batch_end_time'].dt.date
df['last_updated_by'] = 'Aakash'
df = df.astype({'batch_cycle_time': str})
df = df[['batch_no', 'final_product', 'batch_product', 'process_stage_name', 'process_stage_id', if process_stage_name == "Stage-01":
'work_order_no', 'work_order_item_no', 'ideal_batch_cycle_time_hr', 'batch_start_time', df['formaldehyde_content'] = df['F00041-BULK-001 content nil']
'batch_end_time', 'batch_cycle_time', 'batch_cycle_time_minutes', 'batch_setup_time_hr', df['unreactive_alpha_picoline'] = df['un reacted F00056-BULK-001 ( for infor.)']
'downtime', 'selected_equipments', 'created_on', 'created_by', 'last_updated_on', df['moisture_content'] = df['Moisture content \n(for infor)']
'last_updated_by']]
df.reset_index(drop=True, inplace=True)
return df
except Exception as e:
logger.exception(f"Exception - {e}")
@staticmethod elif process_stage_name == "Stage-02":
def preprocess_kpi_df(df, kpi, process_stage_name, process_stage_id): df['formaldehyde_content'] = None
try: df['unreactive_alpha_picoline'] = df['F00056-BULK-001 \n(NLT 50 %)']
if kpi == "Quality": df['moisture_content'] = df['Moisture content \n(for Information).1']
df = df[['Batch Number', 'Start Time.1', 'End Time.1', 'Quality']]
df.rename(columns={'Batch Number': 'batch_no', 'Start Time.1': 'batch_start_time', elif process_stage_name == "Stage-03":
'End Time.1': 'batch_end_time', 'Quality': 'kpi_value'}, inplace=True) df['formaldehyde_content'] = None
df['process_stage_name'] = process_stage_name df['unreactive_alpha_picoline'] = None
df['process_stage_id'] = process_stage_id df['moisture_content'] = df['M/C for infor']
df['kpi_name'] = kpi
df['kpi_description'] = f'{kpi} of this batch' elif process_stage_name == "Stage-04":
df['formaldehyde_content'] = None
df['unreactive_alpha_picoline'] = None
df['moisture_content'] = df['NMT 0.5%']
elif process_stage_name == "Stage-05":
df['formaldehyde_content'] = None
df['unreactive_alpha_picoline'] = None
df['moisture_content'] = df[' NMT 1.0%']
df = df[['batch_no', 'quality', 'formaldehyde_content', 'unreactive_alpha_picoline',
'moisture_content']]
return df return df
except Exception as e: except Exception as e:
logger.exception(f"Exception - {e}") logger.exception(f"Exception - {e}")
def orchestrator_kpi(self): def orchestrator_master(self):
try: try:
df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5 = self.read_df() df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5 = self.read_df()
df_stage_1 = self.preprocess_kpi_df(df_stage_1, kpi="Quality", process_stage_name="Stage-01", df_stage_1 = self.batch_master(df_stage_1, process_stage_name="Stage-01",
process_stage_id="P2E-STAGE-001") process_stage_id="P2E-STAGE-001",
df_stage_2 = self.preprocess_kpi_df(df_stage_2, kpi="Quality", process_stage_name="Stage-02", batch_product="P2E-Stage-01", ideal_batch_cycle_time_hr=720,
process_stage_id="P2E-STAGE-002") batch_setup_time_hr=1)
df_stage_3 = self.preprocess_kpi_df(df_stage_3, kpi="Quality", process_stage_name="Stage-03", df_stage_2 = self.batch_master(df_stage_2, process_stage_name="Stage-02",
process_stage_id="P2E-STAGE-003") process_stage_id="P2E-STAGE-002",
df_stage_4 = self.preprocess_kpi_df(df_stage_4, kpi="Quality", process_stage_name="Stage-04", batch_product="P2E-Stage-02", ideal_batch_cycle_time_hr=1440,
process_stage_id="P2E-STAGE-004") batch_setup_time_hr=1)
df_stage_5 = self.preprocess_kpi_df(df_stage_5, kpi="Quality", process_stage_name="Stage-05", df_stage_3 = self.batch_master(df_stage_3, process_stage_name="Stage-03",
process_stage_id="P2E-STAGE-005") process_stage_id="P2E-STAGE-003",
batch_product="P2E-Stage-03", ideal_batch_cycle_time_hr=2880,
batch_setup_time_hr=1)
df_stage_4 = self.batch_master(df_stage_4, process_stage_name="Stage-04",
process_stage_id="P2E-STAGE-004",
batch_product="P2E-Stage-04", ideal_batch_cycle_time_hr=7440,
batch_setup_time_hr=1)
df_stage_5 = self.batch_master(df_stage_5, process_stage_name="Stage-05",
process_stage_id="P2E-STAGE-005",
batch_product="P2E-Stage-05", ideal_batch_cycle_time_hr=6570,
batch_setup_time_hr=1)
df = pd.concat([df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5], axis=0) df = pd.concat([df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5], axis=0)
# print(df.columns)
df = df[['batch_no', 'process_stage_name', 'process_stage_id',
'batch_start_time', 'batch_end_time', 'kpi_name',
'kpi_description', 'kpi_value']]
df.reset_index(drop=True, inplace=True) df.reset_index(drop=True, inplace=True)
df.to_excel(f"{base_path}/batch_kpi_master.xlsx", index=False)
logger.info(f'Pushing batch_kpi_master to postgres') df = df.astype({'ideal_batch_cycle_time_hr': float})
df.set_index('batch_no').to_sql("batch_kpi_master", df = df.round(2)
"postgresql://ilens:iLens$456@192.168.0.207:5328/ilens_ai", df.to_excel(f"{base_path}/t_batch_master.xlsx", index=False)
logger.info(f'Pushing batch_master to postgres')
df.set_index('batch_no').to_sql("t_batch_master",
"postgresql://ilens:iLens$456@192.168.0.207:5455/ilens_ai",
if_exists="replace") if_exists="replace")
logger.debug(f'Pushed batch_kpi_master to postgres')
logger.debug(f'Pushed batch_master to postgres')
return df return df
except Exception as e: except Exception as e:
logger.exception(f"Exception - {e}") logger.exception(f"Exception - {e}")
def orchestrator_master(self): def orchestrator_batch_material_master(self):
try: try:
df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5 = self.read_df() df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5 = self.read_df()
df_stage_1 = self.preprocess_master_df(df_stage_1, process_stage_name="Stage-01", df_stage_1 = self.batch_material_master(df_stage_1, process_stage_name="Stage-01")
process_stage_id="P2E-STAGE-001", df_stage_2 = self.batch_material_master(df_stage_2, process_stage_name="Stage-02")
batch_product="P2E-Stage-01", ideal_batch_cycle_time_hr=12, df_stage_3 = self.batch_material_master(df_stage_3, process_stage_name="Stage-03")
batch_setup_time_hr=1) df_stage_4 = self.batch_material_master(df_stage_4, process_stage_name="Stage-04")
df_stage_2 = self.preprocess_master_df(df_stage_2, process_stage_name="Stage-02", df_stage_5 = self.batch_material_master(df_stage_5, process_stage_name="Stage-05")
process_stage_id="P2E-STAGE-002",
batch_product="P2E-Stage-02", ideal_batch_cycle_time_hr=24,
batch_setup_time_hr=1)
df_stage_3 = self.preprocess_master_df(df_stage_3, process_stage_name="Stage-03",
process_stage_id="P2E-STAGE-003",
batch_product="P2E-Stage-03", ideal_batch_cycle_time_hr=48,
batch_setup_time_hr=1)
df_stage_4 = self.preprocess_master_df(df_stage_4, process_stage_name="Stage-04",
process_stage_id="P2E-STAGE-004",
batch_product="P2E-Stage-04", ideal_batch_cycle_time_hr=124,
batch_setup_time_hr=1)
df_stage_5 = self.preprocess_master_df(df_stage_5, process_stage_name="Stage-05",
process_stage_id="P2E-STAGE-005",
batch_product="P2E-Stage-05", ideal_batch_cycle_time_hr=None,
batch_setup_time_hr=1)
df = pd.concat([df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5], axis=0) df = pd.concat([df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5], axis=0)
df.reset_index(drop=True, inplace=True) df.reset_index(drop=True, inplace=True)
df.to_excel(f"{base_path}/batch_master.xlsx", index=False) df = df[['batch_no', 'input_qty', 'input_qty_uom', 'output_qty', 'output_qty_uom']]
df = df.round(2)
df.to_excel(f"{base_path}/t_batch_material_master.xlsx", index=False)
logger.info(f'Pushing batch_master to postgres') logger.info(f'Pushing batch_master to postgres')
df.set_index('batch_no').to_sql("batch_master", df.set_index('batch_no').to_sql("t_batch_material_master",
"postgresql://ilens:iLens$456@192.168.0.207:5328/ilens_ai", "postgresql://ilens:iLens$456@192.168.0.207:5455/ilens_ai",
if_exists="replace") if_exists="replace")
logger.debug(f'Pushed batch_master to postgres') logger.debug(f'Pushed batch_master to postgres')
return df return df
except Exception as e: except Exception as e:
logger.exception(f"Exception - {e}") logger.exception(f"Exception - {e}")
@staticmethod def orchestrator_batch_kpi_master(self):
def join_df_proto(df_master, df_other):
try: try:
df = pd.merge(left=df_master, right=df_other, how='left', on='batch_no') df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5 = self.read_df()
df['bct_input_qty_ratio'] = df['batch_cycle_time_minutes']/df['input_qty'] df_stage_1 = self.batch_kpi_master(df_stage_1, process_stage_name="Stage-01",
process_stage_id="P2E-STAGE-001")
df_stage_2 = self.batch_kpi_master(df_stage_2, process_stage_name="Stage-02",
process_stage_id="P2E-STAGE-002")
df_stage_3 = self.batch_kpi_master(df_stage_3, process_stage_name="Stage-03",
process_stage_id="P2E-STAGE-003")
df_stage_4 = self.batch_kpi_master(df_stage_4, process_stage_name="Stage-04",
process_stage_id="P2E-STAGE-004")
df_stage_5 = self.batch_kpi_master(df_stage_5, process_stage_name="Stage-05",
process_stage_id="P2E-STAGE-005")
df = pd.concat([df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5], axis=0)
df = df[['batch_no', 'quality', 'formaldehyde_content', 'unreactive_alpha_picoline', 'moisture_content']]
df.reset_index(drop=True, inplace=True) df.reset_index(drop=True, inplace=True)
df.to_excel(f"{base_path}/master_batch_material.xlsx", index=False) df = df.round(2)
logger.info(f'Pushing master_join to postgres') df.to_excel(f"{base_path}/t_batch_kpi_master.xlsx", index=False)
df.set_index('batch_no').to_sql("master_batch_material", "postgresql://ilens:iLens$456@192.168.0.207:5328/ilens_ai", if_exists='replace') logger.info(f'Pushing batch_kpi_master to postgres')
logger.debug(f'Pushed master_join to postgres') df.set_index('batch_no').to_sql("t_batch_kpi_master",
"postgresql://ilens:iLens$456@192.168.0.207:5455/ilens_ai",
if_exists="replace")
logger.debug(f'Pushed batch_kpi_master to postgres')
return df
except Exception as e: except Exception as e:
logger.exception(f"Exception - {e}") logger.exception(f"Exception - {e}")
def orchestrator_master_proto(self): @staticmethod
def join_master(df_batch_master, df_batch_kpi_master, df_batch_material_master):
try: try:
df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5 = self.read_df() df_kpi_join = pd.merge(left=df_batch_master, right=df_batch_kpi_master, how='left', on='batch_no')
df_stage_1 = self.preprocess_master_df_proto(df_stage_1, process_stage_name="Stage-01") df = pd.merge(left=df_kpi_join, right=df_batch_material_master, how='left', on='batch_no')
df_stage_2 = self.preprocess_master_df_proto(df_stage_2, process_stage_name="Stage-02") df['bct_input_qty_ratio'] = df['batch_cycle_time_minutes']/df['input_qty']
df_stage_3 = self.preprocess_master_df_proto(df_stage_3, process_stage_name="Stage-03")
df_stage_4 = self.preprocess_master_df_proto(df_stage_4, process_stage_name="Stage-04")
df_stage_5 = self.preprocess_master_df_proto(df_stage_5, process_stage_name="Stage-05")
df = pd.concat([df_stage_1, df_stage_2, df_stage_3, df_stage_4, df_stage_5], axis=0) min_bct_1 = df.loc[df['process_stage_id'] == 'P2E-STAGE-001', 'batch_cycle_time_minutes'].min()
min_bct_2 = df.loc[df['process_stage_id'] == 'P2E-STAGE-002', 'batch_cycle_time_minutes'].min()
min_bct_3 = df.loc[df['process_stage_id'] == 'P2E-STAGE-003', 'batch_cycle_time_minutes'].min()
min_bct_4 = df.loc[df['process_stage_id'] == 'P2E-STAGE-004', 'batch_cycle_time_minutes'].min()
min_bct_5 = df.loc[df['process_stage_id'] == 'P2E-STAGE-005', 'batch_cycle_time_minutes'].min()
df.loc[(df['process_stage_id'] == 'P2E-STAGE-001') & (df['batch_cycle_time_minutes'] == min_bct_1),
'golden_batch'] = 'Golden Batch'
df.loc[(df['process_stage_id'] == 'P2E-STAGE-002') & (df['batch_cycle_time_minutes'] == min_bct_2),
'golden_batch'] = 'Golden Batch'
df.loc[(df['process_stage_id'] == 'P2E-STAGE-003') & (df['batch_cycle_time_minutes'] == min_bct_3),
'golden_batch'] = 'Golden Batch'
df.loc[(df['process_stage_id'] == 'P2E-STAGE-004') & (df['batch_cycle_time_minutes'] == min_bct_4),
'golden_batch'] = 'Golden Batch'
df.loc[(df['process_stage_id'] == 'P2E-STAGE-005') & (df['batch_cycle_time_minutes'] == min_bct_5),
'golden_batch'] = 'Golden Batch'
df.reset_index(drop=True, inplace=True) df.reset_index(drop=True, inplace=True)
df.to_excel(f"{base_path}/batch_material.xlsx", index=False) df = df.round(2)
logger.info(f'Pushing batch_master to postgres') df.to_excel(f"{base_path}/t_batch_information_master.xlsx", index=False)
df.set_index('batch_no').to_sql("batch_material", logger.info(f'Pushing master_join to postgres')
"postgresql://ilens:iLens$456@192.168.0.207:5328/ilens_ai", df.set_index('batch_no').to_sql("t_batch_information_master",
if_exists="replace") "postgresql://ilens:iLens$456@192.168.0.207:5455/ilens_ai", if_exists='replace')
logger.debug(f'Pushed batch_master to postgres') logger.debug(f'Pushed master_join to postgres')
return df
except Exception as e: except Exception as e:
logger.exception(f"Exception - {e}") logger.exception(f"Exception - {e}")
if __name__=="__main__": if __name__=="__main__":
batch_master = BatchMaster() batch_master = BatchMaster()
df_master = batch_master.orchestrator_master() df_batch_master = batch_master.orchestrator_master()
# df_kpi = batch_master.orchestrator_kpi() df_batch_kpi_master = batch_master.orchestrator_batch_kpi_master()
df_master_quantity = batch_master.orchestrator_master_proto() df_batch_material_master = batch_master.orchestrator_batch_material_master()
# batch_master.join_df(df_master=df_master, df_kpi=df_kpi) batch_master.join_master(df_batch_master=df_batch_master,
batch_master.join_df_proto(df_master=df_master, df_other=df_master_quantity) df_batch_kpi_master=df_batch_kpi_master,
logger.info(f'{df_master.shape}') df_batch_material_master=df_batch_material_master)
logger.info('Module Completed')
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