Persistence Reading and writing Format operator File names and paths Catching “expectations Databases Pipes Writing module

1. Files
Vikram Neerugatti
Sri Venkateswara
College of Engineering

2. Content
• Persistence
• Reading and writing
• Format operator
• File names and paths
• Catching expectations
• Databases
• Pipes
• Writing modules

3. Persistence
• Means storing the data for long time in disk.
• Pickle-Python object serialization
• Shelve-Python object persistence
• Marshal-internal python object serialization
• Sqlite3-Sqlite databases
• Json-safe
• Th pickle and marshal modules can turn many
python data types into a stream of bytes and
then recreate the objects from the bytes.

4. Persistence
• The pickle module implements binary protocols for
serializing and de-serializing a Python object
structure.
• “Pickling” is the process whereby a Python object
hierarchy is converted into a byte stream,
• and “unpickling” is the inverse operation, whereby a
byte stream (from a binary file or bytes-like object)
is converted back into an object hierarchy.
• Pickling (and unpickling) is alternatively known as
“serialization”, “marshalling,” 1 or “flattening”;
• however, to avoid confusion, the terms used here
“pickling” and “unpickling”.

5. Reading and
Writing
• How to create a Text File
• F=open(“nani.txt”,”w+”)
• F.close()
• How to append data to a file
• F=open(“nani.txt”,”a+”)
• How to read a file
• F=open(“nani.txt”,”r”)
• F.readlines()
• Pandas module

6. Reading and Writing
• File modes in Python

7. Format
operator
• Python uses C-style string formatting to create
new, formatted strings.
• The "%" operator is used to format a set of
variables enclosed in a "tuple" (a fixed size list),
together with a format string, which contains
normal text together with "argument
specifiers", special symbols like "%s" and "%d".
• Example:
• >># This prints out "John is 23 years old.“
• >>name = "John“
• >>age = 23
• >>print("%s is %d years old." % (name, age))

8. File names and paths

9. Catching
expectations
• Exception in and error
• Catching Exceptions will handle it
• Syntax:
• Try:
• Some text here
• Except:
• Exception handling
• Example:
• try:
• print 1/0
• except ZeroDivisionError:
• print "You can't divide by zero, you're silly."

10. Databases
SQL NoSQL Mysql

11. To create a
database in
mysql
•
mydb = mysql.connector.connect(
host="localhost",
user="yourusername",
passwd="yourpassword"
)
mycursor = mydb.cursor()
mycursor.execute("CREATE DATABASE
mydatabase")

12. To check if
database
exists
• import mysql.connector
mydb = mysql.connector.connect(
host="localhost",
user="yourusername",
passwd="yourpassword"
)
mycursor = mydb.cursor()
mycursor.execute("SHOW DATABASES")
for x in mycursor:
print(x)

13. To connect to
the database
• import mysql.connector
mydb = mysql.connector.connect(
host="localhost",
user="yourusername",
passwd="yourpassword",
database="mydatabase"
)

14. Pipes
• pipe() method in Python is used to create
a pipe.
• A pipe is a method to pass information from
one process to another process.
• It offers only one-way communication and the
passed information is held by the system until it
is read by the receiving process.
• Used in operating system
•

15. Writing
modules
• Module is a code library
• To create a module, write a code and save In file
mymodule.py
• def greeting(name):
print("Hello, " + name)
• To use it
• import mymodule
mymodule.greeting("Jonathan“)
• Output: hello,Jonathan

16. Summary
• Persistence
• Reading and writing
• Format operator
• File names and paths
• Catching “expectations
• Databases
• Pipes
• Writing modules