NextStep is an organization which has a pool of resource persons to conduct training workshops on various topics related to ICT. The data of all its Resource Persons is stored in a binary file RESOURCES.DAT using the following record structure (each record is a tuple) :

(R_ID, R_Name, R_Expertise, Charges)

where:

R_ID - Resource Person's ID (An integer) R_Name - Resource Person's Name (A string) R_Expertise - Area of expertise of the Resource Person Charges - Charges (in rupees) per hour to conduct a workshop For example, a record in the file is :

(12, 'P. Velusami','Machine Learning',5000)

In this context, write the following user defined functions in Python :

(i)

Append() - To input the data of a Resource Person and write it in the file RESOURCES . DAT.

(ii)

Update() - To increase the Charges of each resource person by 500.

 import pickle
    def Append(): #Assuming independent tuples in file
                F=open("RESOURCES.DAT","ab")
                R_ID = int(input("Resource Person ID:"))
                R_Name = input("Resource Person Name:")
                R_Expertise = input("Area of Expertise:")
                Charges = int(input("Hourly Charges:"))
                Rec=(R_ID, R_Name, R_Expertise, Charges)
                #[R_ID, R_Name, R_Expertise, Charges] also valid
                pickle.dump (Rec, F)
                F.close()
    def Append(): #Assuming list of tuples in file
        with open("RESOURCES.DAT","rb+") as F:
                Rec=pickle.load(F)
                R_ID = int(input("Resource Person ID:"))
                R_Name = input("Resource Person Name:")
                R_Expertise = input("Area of Expertise:")
                Charges = int(input("Hourly Charges:"))
                Rec.append((R_ID, R_Name, R_Expertise, Charges))
                F.seek(0)
                pickle.dump(Rec,F)
    # Also consider a code, which reads from file using rb, and writes the
    # appended content of records by reopening the same file in wb mode or
    # dumping the content in a new file
    (i)

(ii) import pickle
    def Update(): #Assuming independent tuples in file
    F=open("RESOURCES.DAT","rb+")
    try:
    while True:
        Pos=F.tell()
        Rec=pickle.load(F)
        Newrec=list(Rec)
        Newrec[3]+=500
        F.seek(Pos)
        pickle.dump(tuple(Newrec),F)
    except:
    F.close()
    import pickle #Assuming list of tuples in file
    def Update():
    with open("RESOURCES.DAT","rb+") as F:
    Rec = pickle.load(F)
    for I in range(len(Rec)):
    Rec[I]=list(Rec[I])
    Rec[I][3]+=500
    F.seek(0)
    pickle.dump(Rec,F)
# Also consider a code, which reads from file using rb, and writes the
# updated record by reopening the same file in wb mode or dumping the
# content in a new file
(ii)