Python Read Different Type of Files

In this blog we will read different type of files like text, csv, tsv, json, xml and excel sheet. For that we will use csv, json, xml.etree.ElementTree and xlrd module.

Photo by Hitesh Choudhary on Unsplash

Installation

Installation for reading csv, tsv, json and xml file

csv is part of python’s standard library so you don’t need to install it with pip.

Python comes with a built-in package called json for encoding and decoding JSON data.So no need to install it with pip.

Python’s standard library contains xml package. The xml.etree.ElementTree module implements a simple and efficient API for parsing and creating XML data. so installation is required.

Installation for reading excel sheet

xlrd is a library for reading data and formatting information from Excel files in the historical .xls format.

pip install xlrd

Sample files

We have created sample files for this blog. If you want to download, click on following links.

sample.txt
sample.csv
sample.json
sample1.json
sample.xml
sample.xlsx
sample.tsv

Read text file

Declare the text file path and open file. After that print.

txtFile = "input/sample.txt"
with open(txtFile) as f:
    lines = f.read()
    print(lines)
    pass

Output:

Read each line from text file

with open(txtFile) as f:
    for line in f:
        print (line)
        pass
    pass

Output:

Read file from readlines()

readlines() — Return all lines in the file, as a list.

with open(txtFile) as f:
    lines = f.readlines()
    print(lines)
    
    pass

Output:

Print each lines

with open(txtFile) as f:
    lines = f.readlines()
    #print(lines)
    
    for line in lines:
        print(line)
        pass
    
    pass

Output:

Read csv file

import csv module

import csv

Help on built-in function reader in module _csv:

reader(…)
csv_reader = reader(iterable [, dialect=’excel’]
[optional keyword args])
for row in csv_reader:
process(row)

The “iterable” argument can be any object that returns a line
of input for each iteration, such as a file object or a list. The
optional “dialect” parameter is discussed below. The function
also accepts optional keyword arguments which override settings
provided by the dialect.

The returned object is an iterator. Each iteration returns a row
of the CSV file (which can span multiple input lines).

Declare csv file path, open and then read

csvFile = "input/sample.csv"
with open(csvFile, newline='') as cf:
    csv_reader = csv.reader(cf)
    print(csv_reader)
    pass

Output: <_csv.reader object at 0x7f0838395cd0>

Print each line

with open(csvFile, newline='') as cf:
    csv_reader = csv.reader(cf)
    #print(csv_reader)
    #read each line and print
    for each_row in csv_reader:
        print(each_row)
        pass
    pass

Output:

Read csv with DictReader

csv.DictReader(f, fieldnames=None, restkey=None, restval=None, dialect=’excel’, args, *kwds)

Create an object that operates like a regular reader but maps the information in each row to a dict whose keys are given by the optional fieldnames parameter.

with open(csvFile, 'r') as cf:
    reader = csv.DictReader(cf)
    print(reader)
    pass

Output: <csv.DictReader object at 0x7f0838351290>

with open(csvFile, 'r') as cf:
    reader = csv.DictReader(cf)
    #print(reader)
    #print each row
    for row in reader:
        print(row)
        pass
    pass

Output:

with open(csvFile, 'r') as cf:
    reader = csv.DictReader(cf)
    #print(reader)
    #print each row
    for row in reader:
        print(f'First name: {row["Firstname"]} and Last name is {row["Lastname"]}')
        pass
    pass

Output:

Read JSON file

Import json module

import json

Open json file and read

jsonFile = 'input/sample.json'
with open(jsonFile) as jf:
    jsonData = json.load(jf)
    print(jsonData)
    pass

Output:

with open(jsonFile) as jf:
    jsonData = json.load(jf)
    #print(jsonData)
    
    print('id: ' + str(jsonData['id']))
    print('name: ' + str(jsonData['name']))
    print('subject: ' + str(jsonData['subject']))
    
    pass

Output:

Read another json with multiple records

jsonFile = 'input/sample1.json'
with open(jsonFile) as jf1:
    jsonData = json.load(jf1)
    print(jsonData)
    
    pass

Output:

with open(jsonFile) as jf1:
    jsonData = json.load(jf1)
    #print(jsonData)
    for s in jsonData:
        print(f'\nid: {s["id"]}')
        print(f'name: {s["name"]}')
        print(f'subject: {s["subject"]}')
        pass
    pass

Output:

Read XML

import xml.etree.ElementTree as ET

Parse xml file

xmlFile = 'input/sample.xml'
tree = ET.parse(xmlFile)
#get the root of xml file
root = tree.getroot()
print(root)

Output: <Element ‘data’ at 0x7f08382efa70>

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Print child tag and it’s attributes

tree = ET.parse(xmlFile)
#get the root of xml file
root = tree.getroot()
#print(root)
#print child tag and it's attributes
for child in root:
    print(child.tag)
    print(child.attrib)
    print("\n")
    pass

Output:

Print the children ‘neighbor’ of root node

tree = ET.parse(xmlFile)
#get the root of xml file
root = tree.getroot()
#print(root)
#print child tag and it's attributes
for child in root:
    print(child.tag)
    print(child.attrib)
    print("\n")
    pass
#print the children 'neighbor' of root node
for neighbor in root.iter('neighbor'):
    print(neighbor.attrib)
    print("\n")
    pass

Output:

Print the children ‘year’ of root node

tree = ET.parse(xmlFile)
#get the root of xml file
root = tree.getroot()
#print(root)
#print child tag and it's attributes
for child in root:
    print(child.tag)
    print(child.attrib)
    print("\n")
    pass
#print the children 'neighbor' of root node
for neighbor in root.iter('neighbor'):
    print(neighbor.attrib)
    print("\n")
    pass
#print the children 'year' of root node
for year in root.iter('year'):
    print(int(year.text))
    print("\n")
    pass

Output:

Find all the countries

tree = ET.parse(xmlFile)
#get the root of xml file
root = tree.getroot()
#print(root)
#print child tag and it's attributes
for child in root:
    print(child.tag)
    print(child.attrib)
    print("\n")
    pass
#print the children 'neighbor' of root node
for neighbor in root.iter('neighbor'):
    print(neighbor.attrib)
    print("\n")
    pass
    
#print the children 'year' of root node
for year in root.iter('year'):
    print(int(year.text))
    print("\n")
    pass
#find all the countries
for country in root.findall('country'):
    rank = int(country.find('rank').text)
    print("Country ranks are: ")
    print(rank)
    print(country.attrib)
    pass

Output:

Read excel file

import xlrd

Open workbook and take first sheet.

excelFile = "input/sample.xlsx"
wb = xlrd.open_workbook(excelFile)
sheet = wb.sheet_by_index(0)
print(sheet)

Output: <xlrd.sheet.Sheet object at 0x7f0809e62b10>

Print the numbers of columns in the excel sheet

print(sheet.ncols)

Output: 4

Print the column names

for i in range(sheet.ncols):
    print(sheet.cell_value(0, i))
    pass

Output:

Print the number of rows in the excel sheet

print(sheet.nrows)

Output: 6

Print the rows values

for i in range(sheet.nrows):
    print(sheet.row_values(i))
    pass

Output:

Print the specific row values

print(sheet.row_values(1))

Output:

Read tsv file

import csv

Open tsv file and read

tsvFile = "input/sample.tsv"
with open(tsvFile) as tf:
    tsv_reader = csv.reader(tf, delimiter="\t")
    #print each row
    for row in tsv_reader:
        print(row)
        pass
    pass

Output:

Read tsv file with DictReader()

with open(tsvFile) as tf:
    #read tsv file with DictReader()
    tsv_reader = csv.DictReader(tf, dialect='excel-tab')
    #iterate tsv_reader
    for row in tsv_reader:
        #print each row
        print(row)
        pass
    
    pass

Output:

with open(tsvFile) as tf:
    #read tsv file with DictReader()
    tsv_reader = csv.DictReader(tf, dialect='excel-tab')
    #iterate tsv_reader
    for row in tsv_reader:
        #print each row
        #print(row)
        #print row with key
        print(row['SrNo'], row['Username'])
        pass
    pass

Output:

That’s it. Thanks for reading.