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2026-04-25 15:15:43 Group 120363160012947646 Advance global admin contacts Text
2026-04-25 15:15:42 Group 120363235383036143 Advance global admin contacts Text
2026-04-25 15:15:32 Group 120363260691887673 Advance global admin contacts Text
2026-04-25 13:48:50 Group 120363260691887673 Lodwar till needed Text
2026-04-25 13:47:52 Group 120363293481145950 <media:image> image/jpeg
2026-04-25 13:10:42 Group 120363160012947646 Dont be stuck with tills I distribute Non Geos to strategic shops. I dont charge clients bt admin pay facilitation of 500kshs. Inbox if interested. Text
2026-04-25 12:58:17 Group 120363288063209492 Saji pro available in bulk Special numbers available 0722Available SIM cards & swaps Available Text
2026-04-25 12:58:08 Group 120363293481145950 Saji pro available in bulk Special numbers available 0722Available SIM cards & swaps Available Text
2026-04-25 12:57:05 Group 120363260691887673 Saji pro available in bulk Special numbers available 0722Available SIM cards & swaps Available Text
2026-04-25 12:57:00 Group 120363235383036143 Saji pro available in bulk Special numbers available 0722Available SIM cards & swaps Available Text
2026-04-25 12:42:57 Group 120363235383036143 Advance global admin contacts Text
2026-04-25 12:42:57 Group 120363160012947646 Advance global admin contacts Text
2026-04-25 12:42:47 Group 120363260691887673 Advance global admin contacts Text
2026-04-25 10:05:36 Group 120363293481145950 Sajipro Available Non Geolock Tills Available Hit my inbox 📥 Text
2026-04-25 09:05:57 Group 120363293481145950 Meanwhile, Safaricom is saying that it closed the new agency applications. image/jpeg
2026-04-25 08:33:52 Group 120363293481145950 Raila gave Airtel Penalty wakashindwa kufungua, it's not easy. Equity may do it..They are soon rolling out Mpesa like mobile money and their lines to market... Text
2026-04-25 08:26:41 Group 120363293481145950 *Greetings* Small Dealership needed budget 15 to 20m Clean agency needed 60 to 70 tills with good commission @affordable price Text
2026-04-25 08:07:46 Group 120363288063209492 Saji pro available in bulk Special numbers available 0722Available SIM cards & swaps Available Text
2026-04-25 08:07:41 Group 120363293481145950 Saji pro available in bulk Special numbers available 0722Available SIM cards & swaps Available Text
2026-04-25 08:07:35 Group 120363260691887673 Saji pro available in bulk Special numbers available 0722Available SIM cards & swaps Available Text
2026-04-25 08:07:28 Group 120363235383036143 Saji pro available in bulk Special numbers available 0722Available SIM cards & swaps Available Text
2026-04-25 07:44:42 Group 120363309550985071 *THE FOLLOWING AGGREGATED MPESA TILLS ARE AVAILABLE; LOCATIONS;📍* Nanyuki CBD - Laikipia Gatanga Upper - Murang'a Landless - Thika Narok South Funyula - Busia Kisumu North Kangemi - Nairobi Baba Dogo - Nairobi Karura - Nairobi Kitengela - Kajiado Eldoret Pipeline Eldoret CBD Mikinduri - Meru Text
2026-04-24 18:24:22 Group 120363160012947646 Available tills Bungoma Busia Kitui Kavisuni Kisumu ahero Malindi Soin Muranga south Awasi kisumu Narok Siaya ndori Eastleigh Kericho cbd 3 Kisumu Nairobi cbd Eastleigh juja road Busia town Trans nzoia Narok Bungoma Kwale Isiolo Makueni Khwisero Naivasha Nyeri Transnzoia Narok Kakamega north Malindi Busia butula Makadara Belgut Ugunja Embu manyatta Ndori Text
2026-04-24 18:24:10 Group 120363235383036143 Available tills Bungoma Busia Kitui Kavisuni Kisumu ahero Malindi Soin Muranga south Awasi kisumu Narok Siaya ndori Eastleigh Kericho cbd 3 Kisumu Nairobi cbd Eastleigh juja road Busia town Trans nzoia Narok Bungoma Kwale Isiolo Makueni Khwisero Naivasha Nyeri Transnzoia Narok Kakamega north Malindi Busia butula Makadara Belgut Ugunja Embu manyatta Ndori Text
2026-04-24 18:22:51 Group 120363260691887673 Available tills Bungoma Busia Kitui Kavisuni Kisumu ahero Malindi Soin Muranga south Awasi kisumu Narok Siaya ndori Eastleigh Kericho cbd 3 Kisumu Nairobi cbd Eastleigh juja road Busia town Trans nzoia Narok Bungoma Kwale Isiolo Makueni Khwisero Naivasha Nyeri Transnzoia Narok Kakamega north Malindi Busia butula Makadara Belgut Ugunja Embu manyatta Ndori Text
2026-04-24 17:27:38 Group 120363260691887673 Ziko Text
2026-04-24 16:14:16 Group 120363293481145950 Asenomac Admin contact please Text
2026-04-24 16:11:33 Group 120363293481145950 Agent No.13979 Store No.441417 Kabo ltd Admin number help me members Text
2026-04-24 15:58:25 Group 120363260691887673 NEEDED TILLS Olenguruone Kesses Nairobi cbd Text
2026-04-24 15:56:08 Group 120363309550985071 *SAJIPRO AVAILABLE IN BULK @ 1K EACH* Text
2026-04-24 15:56:00 Group 120363260691887673 *SAJIPRO AVAILABLE IN BULK @ 1K EACH* Text
2026-04-24 15:55:43 Group 120363235383036143 *SAJIPRO AVAILABLE IN BULK @ 1K EACH* Text
2026-04-24 15:39:40 Group 120363235383036143 Western kakamega mbale Till needed Text
2026-04-24 15:39:34 Group 120363260691887673 Western kakamega mbale Till needed Text
2026-04-24 15:39:28 Group 120363309550985071 Western kakamega mbale Till needed Text
2026-04-24 15:39:21 Group 120363288063209492 Western kakamega mbale Till needed Text
2026-04-24 15:22:04 DM +254721499435 P051436757P Text
2026-04-24 15:20:41 DM +254721499435 https://etims-sbx.kra.go.ke/basic/login/indexLogin Text
2026-04-24 15:12:23 DM +254721499435 import json import requests import sqlite3 import csv import sys from datetime import datetime import pandas as pd now = datetime.now() print(now) # Example output: 2025-01-30 14:30:25.123456 url="http://192.168.100.48:8088/" url="http://localhost:8088" url="http://192.168.100.11:8088/" url="http://localhost:8088" url="http://192.168.100.16:8088/" url="http://192.168.100.40:8088/" url="http://localhost:8088" url="http://109.123.240.141:8088" ## "109.123.240.141" file_nam = "_testresults_"+ now.strftime("%Y-%m-%d_%H-%M-%S") file_csv = file_nam +".csv" with open(file_csv, 'a') as file: file.write(",".join(["path", "resultCd", "resultMsg", "resultDt", "dataReturned"]) + "\n") # Create an empty DataFrame with just headers file_name = file_nam + '.xlsx' # Define column headers columns = ["path", "resultCd", "resultMsg", "resultDt", "dataReturned"] # Create an empty DataFrame with just headers df = pd.DataFrame(columns=columns) # Print the DataFrame as a table (empty but with headers) print(df.to_markdown(index=False)) # Save empty DataFrame to CSV and Excel (only headers) df.to_excel(file_name, index=False, engine="openpyxl") def selectInitInfo(data): try: response = KraSend("/initializer/selectInitInfo",data) data = json.loads(response.text) ''' *Response data should look like the below { "resultCd": "902", "resultMsg": "This device is installed", "resultDt": "20250128092053", "data": null } ''' print(data) #region x = data["resultCd"] print(x) x = data["resultMsg"] print(x) x = data["resultDt"] print(x) x = data["data"] print(x) #endregion if response.status_code == 200: try: # Create a DataFrame from the iterable_data = {key: [value] for key, value in data.items()} # Create a DataFrame df = pd.DataFrame(iterable_data) # Print the DataFrame as a table print(df.to_markdown(index=False)) df.to_excel('selectInitInfo' + now.strftime("%Y-%m-%d_%H-%M-%S") + '.xlsx', index=False) # Export to CSV df.to_csv('selectInitInfo' + now.strftime("%Y-%m-%d_%H-%M-%S") + '.csv', index=False) except Exception as e: print(f"An error occurred: {e}") else: # we need to check the type return when there is an error print("we need to check the type return when there is an error") except Exception as e: print(f"An error occurred: {e}") print("-"*100) def selectCodes(data): try: response = KraSend("/code/selectCodes",data) data = json.loads(response.text) ''' *Response data should look like the below { "resultCd": "902", "resultMsg": "This device is installed", "resultDt": "20250128092053", "data": null } ''' print(data) #region x = data["resultCd"] print(x) x = data["resultMsg"] print(x) x = data["resultDt"] print(x) x = data["data"] print(x) #endregion if response.status_code == 200: try: # Create a DataFrame from the iterable_data = {key: [value] for key, value in data.items()} # Create a DataFrame df = pd.DataFrame(iterable_data) # Print the DataFrame as a table print(df.to_markdown(index=False)) df.to_excel('selectCodes' + now.strftime("%Y-%m-%d_%H-%M-%S") + '.xlsx', index=False) # Export to CSV df.to_csv('selectCodes' + now.strftime("%Y-%m-%d_%H-%M-%S") + '.csv', index=False) x = data['data']['clsList'] # Export the data df = pd.DataFrame(x) # Print the DataFrame as a table print(df.to_markdown(index=False)) df.to_excel('selectCodesData' + now.strftime("%Y-%m-%d_%H-%M-%S") + '.xlsx', index=False) # Export to CSV df.to_csv('selectCodesData' + now.strftime("%Y-%m-%d_%H-%M-%S") + '.csv', index=False) except Exception as e: print(f"An error occurred: {e}") else: # we need to check the type return when there is an error print("we need to check the type return when there is an error") except Exception as e: print(f"An error occurred: {e}") print("-"*100) def selectItemsClass(data): try: response = K... Text
2026-04-24 15:09:36 Group 120363293481145950 It's going down since it started with the app Text
2026-04-24 15:08:04 Group 120363293481145950 Safaricom imeanza kuanguka... Ianguke tu. Airtel will one day take over the Kenyan market Text
2026-04-24 15:07:03 Group 120363293481145950 <media:video> video/mp4
2026-04-24 15:06:15 DM +254721499435 p Text
2026-04-24 14:59:38 DM +254721499435 import json import requests import mylib5 import pandas as pd from datetime import datetime # Get the current date and time now = datetime.now() # Format the datetime object into the required string format "YYYYMMDDhhmmss" datel = now.strftime("%Y%m%d%H%M%S") dates = now.strftime("%Y%m%d") invcNo = 1 dt = "20180131175302" tin = "P051189216Y" tin = "P051436757P" tin = "P051109164C" tin = "P600002996A" dvcSrlNo = 'D04FTQ1' bhfId = '00' tin = "P052471029S" tin = "P600002997A" dvcSrlNo = 'IPOS 2026' print("."*100) data0 = { "tin": tin, "bhfId": bhfId, "dvcSrlNo":dvcSrlNo } data2 = { "tin": tin, "bhfId": bhfId, "lastReqDt":dt } response = mylib5.selectInitInfo(data0) response = mylib5.selectCodes(data2) response = mylib5.selectItemsClass(data2) data3 = { "tin": tin, "bhfId": bhfId, "custmTin": "A987654321Z" } response = mylib5.selectCustomer(data3) data3 = { "tin": tin, "bhfId": bhfId, "custmTin": "A123456789Z" } response = mylib5.selectCustomer(data3) data3 = { "tin": tin, "bhfId": bhfId, "custmTin": "A006330184N" } response = mylib5.selectCustomer(data3) data3 = { "tin": tin, "bhfId": bhfId, "custmTin": "P052180506J" } response = mylib5.selectCustomer(data3) response = mylib5.selectBranches(data2) print("-"*100) data4 = {"tin": tin,"bhfId": bhfId,"custNo": "BEE987","custTin": "P052180506J","custNm": "BEE EAST LTD","adrs": "","telNo": "","email": "","faxNo": "","useYn": "Y","remark": "","regrNm": "sa","regrId": "sa","modrNm": "sa","modrId": "sa"} response = mylib5.saveBrancheCustomers(data4) data4 = {"tin": tin,"bhfId": bhfId,"custNo": "F000657X","custTin": "A006330184N","custNm": "BENARD KABUE NJUGUNA","adrs": "","telNo": "","email": "","faxNo": "","useYn": "Y","remark": "","regrNm": "sa","regrId": "sa","modrNm": "sa","modrId": "sa"} response = mylib5.saveBrancheCustomers(data4) data3 = { "tin": tin, "bhfId": bhfId, "custmTin": "A006330184N" } response = mylib5.selectCustomer(data3) response = mylib5.selectNotices(data2) data = { "tin": tin, "bhfId": bhfId, "userId": "userId2", "userNm": "User Name2 ", "pwd": "12341234", "adrs": None, "cntc": None, "authCd": None, "remark": None, "useYn": "Y", "regrNm": "Admin", "regrId": "Admin", "modrNm": "Admin", "modrId": "Admin" } response = mylib5.saveBrancheUsers(data) data = { "tin": tin, "bhfId": bhfId, "isrccCd": "ISRCC01", "isrccNm": "RSSB Insurance", "isrcRt": 20, "useYn": "Y", "regrNm": "Admin", "regrId": "Admin", "modrNm": "Admin", "modrId": "Admin" } response = mylib5.saveBrancheInsurances(data) print("-"*100) data = { "tin": tin, "bhfId": bhfId, "lastReqDt":dt } data = {"tin": tin,"bhfId": bhfId,"itemClsCd": "56100000","itemCd": "KE2GRMBA0000001","itemTyCd": "2","itemNm": "Item 1","itemStdNm": "","orgnNatCd": "KE","pkgUnitCd": "BA","qtyUnitCd": "GRM","taxTyCd": "B","btchNo": "","bcd": "1","dftPrc": 232,"grpPrcL1": 232,"grpPrcL2": 0,"grpPrcL3": 0,"grpPrcL4": 0,"grpPrcL5": 0,"addInfo": "","sftyQty": 0,"isrcAplcbYn": "N","useYn": "N","regrNm": "sa","regrId": "sa","modrNm": "sa","modrId": "sa"} data = {"tin": tin,"bhfId": bhfId,"itemClsCd": "56100000","itemCd": "KE2BLLAM0010005","itemTyCd": "2","itemNm": "Item 10","itemStdNm": "","orgnNatCd": "KE","pkgUnitCd": "AM","qtyUnitCd": "BLL","taxTyCd": "B","btchNo": "","bcd": "10","dftPrc": 232,"grpPrcL1": 232,"grpPrcL2": 0,"grpPrcL3": 0,"grpPrcL4": 0,"grpPrcL5": 0,"addInfo": "","sftyQty": 0,"isrcAplcbYn": "N","useYn": "N","regrNm": "sa","regrId": "sa","modrNm": "sa","modrId": "sa"} response = mylib5.saveItems(data) data = {"tin": tin,"bhfId": bhfId,"itemClsCd": "84110000","itemCd": "KE2KGAM0000002","itemTyCd": "2","itemNm": "Item 2","itemStdNm": "","orgnNatCd": "KE","pkgUnitCd": "AM","qtyUnitCd": "KG","taxTyCd": "B","btchNo": "","bcd": "2","dftPrc": 232,"grpPrcL1": 232,"grpPrcL2": 0,"grpPrcL3": 0,"grpPrcL4": 0,"grpPrcL5": 0,"addInfo": "","sftyQty": 0,"isrcAplcbYn": "N","useYn": "N","regrNm": "sa","regrId": "sa","modrNm": "sa","modrId": "sa"} response = mylib5.saveItems(data) data = {"tin": tin,"bhfId": bhfId,"itemClsCd": "12160000","itemCd": "KE2GRMBG0010002","itemTyCd": "2","itemNm": "Item 3","itemStdNm": "","orgnNatCd": "KE","pkgUnitCd": "BG","qtyUnitCd": "GRM","taxTyCd": "B","btchNo": "","bcd": "3","dftPrc": 232,"grpPrcL1": 232,"grpPrcL2": 0,"grpPrcL3": 0,"grpPrcL4": 0,"grpPrcL5": 0,"addInfo": "","sftyQty": 0,"isrcAplcbYn": "N","useYn": "N","regrNm": "sa","regrId": "sa","modrNm": "sa","modrId": "sa"} response = mylib5.saveItems(data) data = {"tin": tin,"bhfId": bhfId,"itemClsCd": "31200000","itemCd": "KE2GRMBL0010003","itemTyCd": "2","itemNm": "Item 4","itemStdNm": "","orgnNatCd": "KE","pkgUnitCd": "BL","qtyUnitCd": "GRM","taxTyCd": "B","btchNo": "","bcd": "4","dftPrc": 232,"grpPrcL1": 232,"grpPrcL2": 0,"grpPrcL3": 0,"grpPrcL4": 0,"grpPrcL5": 0,"addInfo": "","sft... Text
2026-04-24 14:47:22 DM +254721499435 0789374099 Text
2026-04-24 14:47:05 Group 120363293481145950 3 tills with allocation needed Text
2026-04-24 14:46:48 Group 120363288063209492 3 tills with allocation needed Text
2026-04-24 14:10:30 Group 120363309550985071 AVAILABLE Sajipros Sim swaps Simcards Money detectors Text
2026-04-24 14:10:26 Group 120363260691887673 AVAILABLE Sajipros Sim swaps Simcards Money detectors Text
2026-04-24 14:10:25 Group 120363293481145950 AVAILABLE Sajipros Sim swaps Simcards Money detectors Text