added ctcmp historic data load scripts

info.py

+# Please add all configurations and then run main.py
+import copy
+import os
+import time
+from datetime import datetime
+import logging
+
+import httpx
+import pandas as pd
+import requests
+
+from main import DynamciAssetModel
+dynamic_asset_model = DynamciAssetModel()
+
+login_token = "14f662070a5c406e830c3ceb4e19885a"
+project_id = "project_105"
+user_id = "user_234"
+cookies = {'login-token': login_token, 'project_id': project_id, "user_id": user_id}
+headers = {'login-token': login_token, 'projectId': project_id, "user_id": user_id}
+filename_summary = 'CTCMP_OPE_Sheet_FY23 28-09-22.xlsm'
+
+json_path = os.path.join(os.getcwd(), filename_summary)
+xls = pd.ExcelFile(json_path)
+oee_df_daily_production = pd.read_excel(xls, 'Production')
+oee_df_daily_production.fillna(0, inplace=True)
+oee_df_daily_production = oee_df_daily_production.to_records()
+from_date = datetime.strptime(input("Enter from date"), "%Y-%m-%d")
+from_date_str = datetime.strftime(from_date, "%Y-%m-%d")
+to_date = datetime.strptime(input("Enter to date"), "%Y-%m-%d")
+to_date_str = datetime.strftime(to_date, "%Y-%m-%d")
+
+
+url = "https://jubilant-dev.ilens.io/ilens_api/tags_v2/search_asset"
+payload = {"searchBy": "asset_model", "tag_type": None, "valueQualifier": None, "parameter": None, "currentState": None,
+           "value": "asset_model_160", "asset_version": "1.0", "project_type": "customer",
+           "tz": "Asia/Kolkata", "project_id": "project_105", "language": "en"}
+
+with httpx.Client() as client:
+    payload['value'] = "asset_model_167"
+    try:
+        Reactor_data = client.post(url=url, cookies=cookies, json=payload, headers=headers)
+        if Reactor_data.status_code in [204, 200, 201]:
+            Reactor_data = Reactor_data.json()['data']['tree_view']
+    except Exception as e:
+        logging.error(str(e))
+        raise
+
+
+with httpx.Client() as client:
+    payload['value'] = "asset_model_160"
+    try:
+        Vessel_data = client.post(url=url, cookies=cookies, json=payload, headers=headers)
+        if Vessel_data.status_code in [204, 200, 201]:
+            Vessel_data = Vessel_data.json()['data']['tree_view']
+    except Exception as e:
+        logging.error(str(e))
+        raise
+
+
+with httpx.Client() as client:
+    payload['value'] = "asset_model_171"
+    try:
+        Other_data = client.post(url=url, cookies=cookies, json=payload, headers=headers)
+        if Other_data.status_code in [204, 200, 201]:
+            Other_data = Other_data.json()['data']['tree_view']
+    except Exception as e:
+        logging.error(str(e))
+        raise
+
+asset_model_data = {
+    "asset_model_167": Reactor_data,
+    "asset_model_160": Vessel_data,
+    "asset_model_171": Other_data
+}
+
+def hit_external_service(api_url, request_json, date):
+    try:
+        # print(api_url)
+        # print(request_json)
+        # print(date)
+        with httpx.Client() as client:
+            for _ in range(3):
+                resp = client.post(url=api_url, cookies=cookies, json=request_json, headers=headers)
+                if resp.status_code in [204, 200, 201]:
+                    response = resp.json()
+                    print(f"Response:{response} for the date {date}")
+                    return True
+            print(f"Response:{resp.status_code} for the date {date}")
+    except requests.exceptions.ConnectionError as e:
+        print(e.args)
+
+
+asset = "site_116$dept_134$line_361$equipment_4315$tag_6950"
+
+task_id = "task_2420"
+stages = ["stage_20132", "stage_20135", "stage_20136", None, None]
+
+asset_model_dict = {
+    "Reactor": "asset_model_167",
+    "Vessel": "asset_model_160",
+    "Other": "asset_model_171"
+}
+master_stage_id = "stage_20136"
+production_stage_id = "stage_20132"
+losses_stage_id = "stage_20134"
+custom_api = 'https://jubilant.ilens.io/form-mt/render/form?save=True'
+master_data_payload = {"data": {
+    "textField": 9405000,
+    "bct": 1440,
+    "batch_size": 3000.00,
+    "c_div_t": 2.0833,
+    "c_div_t1": 92.88
+}}
+
+cookies = {'login-token': login_token, 'project_id': project_id, "user_id": user_id}
+headers = {'login-token': login_token, 'projectId': project_id, "user_id": user_id}
+
+general_payload = {"type": "save", "tz": "Asia/Calcutta", "project_id": project_id,
+                   "current_status": "IN PROGRESS", "task_id": task_id,
+                   "stages": stages,
+                   "project_type": "customer", "language": "en"}
+for each in range(len(oee_df_daily_production)):
+    if pd.to_datetime(str(oee_df_daily_production[each][1])).strftime('%Y-%m-%d') >= from_date_str and pd.to_datetime(
+            str(oee_df_daily_production[each][1])).strftime('%Y-%m-%d') <= to_date_str:
+        form_payload_master = copy.deepcopy(general_payload)
+        form_payload_master.update(dict(triggers=dict(date=str(oee_df_daily_production[each][1]))),
+                                   submitted_data=master_data_payload,
+                                   stage_id=master_stage_id)
+        hit_external_service(custom_api, form_payload_master, str(oee_df_daily_production[each][1]))
+        time.sleep(10)
+        output = oee_df_daily_production[each][4]
+        form_payload_production = copy.deepcopy(general_payload)
+        submitted_data = {"data": {
+            "output": f"{output}",
+            "rework": "0",
+            "defect": "0",
+            "shift_incharge": "",
+            "label18": ""}}
+        form_payload_production.update(dict(triggers=dict(date=str(oee_df_daily_production[each][1]))),
+                                       submitted_data=submitted_data,
+                                       stage_id=production_stage_id)
+        hit_external_service(custom_api, form_payload_production, str(oee_df_daily_production[each][1]))
+
+oee_losses_df = pd.read_excel(xls, 'Downtime')
+oee_losses_df.fillna(0, inplace=True)
+oee_losses_df = oee_losses_df.to_records()
+
+
+def get_losses_payload(each_loss):
+    if pd.isna(oee_losses_df[each_loss][6]) or pd.isna(
+            oee_losses_df[each_loss][7] or pd.isna(oee_losses_df[each_loss][2]) or pd.isna(
+                oee_losses_df[each_loss][3])):
+        return
+    if oee_losses_df[each_loss][2] not in [pd.NaT, 'NaT'] and oee_losses_df[each_loss][3] not in [pd.NaT, 'NaT']:
+        # print(str(oee_losses_df[each_loss][7]))
+        asset_model = asset_model_dict.get(str(oee_losses_df[each_loss][6]), None)
+        # print(asset_model)
+        # oee_losses_df[each_loss][7] = "Reactor R-7209"
+        asset_hierarchy = {}
+        dynamic_asset_model.dynamic_asset_model(str(oee_losses_df[each_loss][7]), asset_model_data[asset_model], asset_hierarchy)
+        data_grid_dict = {"from_time": str(oee_losses_df[each_loss][2]), "to_time": str(oee_losses_df[each_loss][3]),
+                          "loss_category": oee_losses_df[each_loss][8], "loss_reason": oee_losses_df[each_loss][9],
+                          "loss_reason_comment": oee_losses_df[each_loss][10],
+                          "assets": {"asset_model": asset_model,
+                                     "asset": asset_hierarchy[asset_model]},
+                          "loss_in_minutes": int(abs(oee_losses_df[each_loss][5] * 60))}
+
+        planned_time, available_time = 0, 0
+        if oee_losses_df[each_loss][8] == "Management_Loss" and oee_losses_df[each_loss][9] in ["No Plan", "Holiday",
+                                                                                                "No Order"]:
+            planned_time = int(abs(oee_losses_df[each_loss][5] * 60))
+        else:
+            available_time = int(abs(oee_losses_df[each_loss][5] * 60))
+        return dict(data=dict(booked_loss_in_time=int(abs(oee_losses_df[each_loss][5] * 60)),
+                              planned_loss_in_minutes=planned_time, available_loss_in_minutes=available_time,
+                              unadjusted_loss_in_time=0, unadjusted_loss_in_time_hours=0,
+                              booked_loss_in_time_hours=int(abs(oee_losses_df[each_loss][5])),
+                              planned_loss_in_hours=float(planned_time / 60),
+                              available_loss_in_hours=float(available_time / 60), data_grid=[data_grid_dict]))
+
+
+count = 0
+for each in range(len(oee_losses_df)):
+    count = count + 1
+    # print("count", count)
+    if oee_losses_df[each][2] == 0:
+        break
+    if pd.to_datetime(str(oee_losses_df[each][2])).strftime('%Y-%m-%d') >= from_date_str and pd.to_datetime(
+            str(oee_losses_df[each][2])).strftime('%Y-%m-%d') <= to_date_str:
+        form_payload_losses = get_losses_payload(each)
+        form_payload_losses_updated = copy.deepcopy(general_payload)
+        form_payload_losses_updated.update(dict(triggers=dict(date=str(oee_losses_df[each][2]))),
+                                           submitted_data=form_payload_losses,
+                                           stage_id=losses_stage_id)
+        hit_external_service(custom_api, form_payload_losses_updated, str(oee_losses_df[each][2]))
+        time.sleep(10)
+print("Executed Successfully")

main.py

+class DynamciAssetModel:
+    def dynamic_asset_model(self, asset_name, asset_model_data, asset_hierarchy):
+        for asset_model in asset_model_data:
+            if "children" in asset_model:
+                self.dynamic_asset_model(asset_name, asset_model['children'], asset_hierarchy)
+            elif asset_model["name"] == asset_name:
+                asset_hierarchy[asset_model['name']] = asset_model['hierarchy']
+
+    # def check_asset(self, asset_name, asset_model_data, asset):
+    #     for asset_model in asset_model_data:
+    #         if "children" in asset_model:
+    #             self.check_asset(asset_name, asset_model['children'], asset)
+    #         elif asset_model["name"] == asset_name:
+    #             asset['asset'] = asset_model['hierarchy']
+
+