Reading CSV Files with Python's urllib

Comma separated value (CSV) files are a common file format used to store tabular data like spreadsheets or databases. Often you need to read data from a CSV file into a Python program for analysis and reporting. Python's built-in urllib module provides a simple way to download and parse CSV data.

In this article, we'll cover the key things you need to know to read CSV data from a URL using Python.

Downloading the CSV File

The first step is to download the raw CSV file contents from a URL. Here's an example using urllib.request:

import urllib.request

url = "https://people.sc.fsu.edu/~jburkardt/data/csv/addresses.csv"  

response = urllib.request.urlopen(url)
csv_data = response.read()

This opens the URL, gets the response, and reads the raw bytes into the csv_data variable.

Parsing as CSV

Next we need to parse the CSV data. The built-in csv module handles parsing:

import csv

rows = csv.reader(csv_data.splitlines())

for row in rows:
    print(row)

Here we:

By default it expects commas as delimiters. You can customize the dialect and delimiters used.

Putting It Together

Here is the full code to download a CSV file from a URL and parse it with csv.reader:

import urllib.request
import csv

url = "https://people.sc.fsu.edu/~jburkardt/data/csv/addresses.csv"  

response = urllib.request.urlopen(url)
csv_data = response.read()

rows = csv.reader(csv_data.splitlines())

for row in rows:
    print(row)

This provides the complete workflow to go from a URL to parsed CSV rows.

Dealing with Headers

Often CSV files have header rows describing each column. We can skip the headers easily:

next(rows) # skip header row 
for row in rows:
   print(row)

Use next(rows) to advance the reader past the first row.

Practical Considerations

Here are some things to keep in mind when using urllib to read CSV data:

Use Cases

Some examples of cases where using urllib to download and parse CSV data is helpful:

The direct URL access allows easily integrating remote CSV data into Python programs.

Next Steps

To take your CSV skills further:

I hope this overview gives you a solid starting point for using Python and urllib to access CSV file data!