Learning Outcomes
On completion of this page you will know:
- the meaning of serialisation
- how to add objects to a list
- how to serialise the list (including its objects)
- how to deserialise a list
Serialisation
Introduction
In an earlier lesson we looked at saving data to a text file. In that lesson we were able to save only unstructured text and numeric data. Again we had to write each individual data item to the file. The unstructured data saved to those files could be easily viewed in any simple text editor.
Since then we have encountered structured data such as lists and even the more structured classes and objects. Serialisation allows us to save those structures directly to a file along with their data, and to subsequently retrieve them in their original structure.
For our example we shall use our payroll application again. Each class will contain private variables for the employee's name, hours worked, hourly rate, gross, tax and net. They will also contain the code for processing the payroll and displaying the results.
Go to topClass and pickle
Here we shall look at the details of our serialisation example. the program is divided into it's main components in Listing 1, Listing 2 and Listing 3. The full code is shown in Listing 4.
import pickle
class Employee:
__strName=""
__floatHours=0.0
__floatRate=0.0
__floatGross=0.0
__floatTax=0.0
__floatNet=0.0
def __init__(self, nme, hrs, rt):
self.__strName = nme
self.__floatHours = hrs
self.__floatRate = rt
self.__calculate()
def __calculate(self):
self.__floatGross = self.__floatHours * self.__floatRate
self.__floatTax = self.__floatGross * 0.25
self.__floatNet = self.__floatGross - self.__floatTax
def results(self):
return(f'Employee name: {self.__strName},\nHours worked: {self.__floatHours},\nHourly Rate: {self.__floatRate},\nGross: {self.__floatGross},\nTax: {self.__floatTax},\nNet: {self.__floatNet}')
The contents of Listing 1 should be familiar to you by now apart from Line 1 and Line 20
Line 1 imports the oddly named library pickle This library contains functions for processing structured data. In our case the structures will be a list that will contain objects of the class Employee and the individual payroll data that will be stored within each each object. The pickle functions that we shall use in this example will be load() and dump(). We shall discuss them in more detail below.
In line 20 a new technique for printing labelled values is used.
Notice that the return string contains four types of text:
- the first is a solitary f at the very beginning. This simply indicates that the subsequent text between the enclosing single quotes has special formatting
- the next is normal text constants such as Employee name:, Hours worked: etc. These are simply labels for the variables that follow them.
- variable names enclosed in curly brackets. When returned for printing the value of the variables will replace the variable names
- \n. These cause line breaks within the string so that each label and the value of the corresponding variable appear on their own line.
Below we see a screen dump of a sample run of the program which illustrates how the formatted string works.
Main Variables
Salaries = []
WorkerName=""
Here we initialise two variables that we shall use to control the program.
The first, Salaries is a list that will contain objects of the class Employee. When we are serialising our data, it is this list that we serialise. All of the objects contained within it will be saved along with it. Also when we are deserialising data from our file, this same list along with its objects will be deserialised.
WorkerName is a string variable. It's value will be used to control a while loop, which terminates when the value of WorkerName is null.
Go to topMain Processing
with open("Workers","rb") as infile:
Salaries = pickle.load(infile)
WorkerName=input("Enter employee name")
while WorkerName !="":
WorkerHours = float(input("Enter hours worked"))
WorkerRate = float(input("Enter hourly rate"))
Worker = Employee(WorkerName, WorkerHours, WorkerRate)
Salaries.append(Worker)
WorkerName=input("Enter employee name")
print("Saving data to file")
with open("Workers","wb") as outfile:
pickle.dump(Salaries,outfile)
print("Data saved to file")
for salaried in Salaries:
print(salaried.results())
This section of the program can be divided into four subsections, each of which is discussed below.
Lines 25 - 26: Here the file "Workers" is opened at line 25 and the load() function from the library pickle is used to read the contents of the file and store them in the list Salaries
Lines 28 - 34: These lines form the body of a while loop. Line 28 forms the priming read. If the value of WorkerName is not a blank, then the values of hours and rate are received at lines 30 and 31 and stored in the variables WorkerHours and WorkerRate respectively.At line 32 an object of the class Employee called Worker is created and the values for the name, hours and rate are passed to its constructor. At line 33 the newly created object is appended to the list Salaries. At line 34 the user is asked for another value for the employee name and control passes back to line 29 for another iteration of the loop.
Program control moves to line 36 once the user enters a blank for the employee name at either line 29 or line 34. Lines 36 and 39 simply inform the user of the activities currently taking place. The main processing occurs at lines 37 and 38. The file "Workers" is open for writing and the dump() function from the pickle library is used to store the list Salaries and it's contents to the file.
Finally a for loop iterates through the list Salaries and for each object there calls the method results to print out the values stored in the current object.
Go to topComplete Program
import pickle
class Employee:
__strName=""
__floatHours=0.0
__floatRate=0.0
__floatGross=0.0
__floatTax=0.0
__floatNet=0.0
def __init__(self, nme, hrs, rt):
self.__strName = nme
self.__floatHours = hrs
self.__floatRate = rt
self.__calculate()
def __calculate(self):
self.__floatGross = self.__floatHours * self.__floatRate
self.__floatTax = self.__floatGross * 0.25
self.__floatNet = self.__floatGross - self.__floatTax
def results(self):
return(f'Employee name: {self.__strName},\nHours worked: {self.__floatHours},\nHourly Rate: {self.__floatRate},\nGross: {self.__floatGross},\nTax: {self.__floatTax},\nNet: {self.__floatNet}')
Salaries = []
WorkerName=""
with open("Workers","rb") as infile:
Salaries = pickle.load(infile)
WorkerName=input("Enter employee name")
while WorkerName !="":
WorkerHours = float(input("Enter hours worked"))
WorkerRate = float(input("Enter hourly rate"))
Worker = Employee(WorkerName, WorkerHours, WorkerRate)
Salaries.append(Worker)
WorkerName=input("Enter employee name")
print("Saving data to file")
with open("Workers","wb") as outfile:
pickle.dump(Salaries,outfile)
print("Data saved to file")
for salaried in Salaries:
print(salaried.results())
Summary
Serialisation is the practice of transferring structured data from the computer's memory to a disk storage. The structured data must be stored as a single unit.
In our example the structure was a list, which contained a series of objects of the class Employee. Notice at line 38 above that we 'dump' only the list Salaries; The objects stored in this list are automatically stored with it.
Go to topExercise
Part 1
Using Listing 3 above as an example create an application that processes a customer's bill.
For the bill the required data are:
- Customer Name
- Unit price of item
- Amount purchased
From the above the total for this particular item is calculated.
The customer may purchase as many items as they wish.
On completion of their order, all the subtotals are added up to give a total for the order itself.
The data is serialised with the customer's name used as the file name.
Part 2
Extend the above application so that the customers' names are also added to a separate list. This list is then saved separately.
Now extend the application further so that a list of each customer is printed, and for each customer that their purchases are shown.
Go to topRevision
Multi choice
- What is the main purpose of serialization in Python?
- To save data as plain text
- To convert structured data into a storable format
- To execute programs faster
- To encrypt sensitive information
- Which Python library is used for serialization in the example provided?
- JSON
- Pickle
- CSV
- XML
- What is the structure of data serialized in the given payroll example?
- A dictionary of employee details
- A single string containing all details
- A list of objects of the Employee class
- A CSV file
- What does the pickle.dump() function do?
- Reads serialized data from a file
- Writes serialized data to a file
- Converts an object into JSON format
- Displays serialized data on the console
- In the Employee class, what is the purpose of the __calculate method?
- To save employee data to a file
- To initialize employee variables
- To compute gross, tax, and net values
- To append employee objects to a list
- Why is the letter f used at the beginning of the return string in the results method of the Employee class?
- It defines a function string
- It enables formatting within the string
- It marks the function as final
- It indicates an error-free function
- In the payroll example, which variable is used to control the loop for adding new employee details?
- Salaries
- WorkerHours
- WorkerName
- EmployeeList
- What happens when the pickle.load() function is used?
- It deletes serialized data from a file
- It loads serialized data from a file into memory
- It converts data into a JSON format
- It appends new data to an existing list
- In serialization, what is automatically stored along with the list?
- The filename
- The memory address of the list
- All objects contained within the list
- The length of the list
- Which of the following is a potential disadvantage of using the pickle library?
- It is incompatible with structured data
- It cannot serialize numeric data
- It may not be secure for untrusted data
- It only works with JSON formats
Fill the blanks
- Serialization is the process of transferring ________ data from memory to disk storage.
- In the provided example, the structured data being serialized is a ________ containing objects of the Employee class.
- The Python library used for serialization in the example is called ________.
- The pickle.dump() function is used to ________ serialized data to a file.
- The pickle.load() function is used to ________ serialized data from a file.
- In the payroll example, the loop for adding new employee details is controlled by the variable ________.
- The method in the Employee class that calculates gross pay, tax, and net pay is called ________.
- When serializing a list, the objects stored within the list are automatically ________ along with it.
- The f at the beginning of a string in the results method of the Employee class enables ________ within the string.
- In the example, the while loop continues to accept employee details until the variable ________ is empty.