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Python Code Scrapy

Scrapy response.meta

capture your start urls in your output with Scrapy response.meta

scrapy real estate scraping

Every web scraping project has aspects that are different or interesting and worth remembering for future use.

This is a look at a recent real world project and looks saving more than one start url in the output.

This assumes basic knowledge of web scraping, and identifying selectors. See my other videos if you would like to learn more about selectors (xpath & css)

scraping a real estate site for houses and appartments

We want to fill all of the columns in our client’s master excel sheet.

We could* then provide them with a CSV which they can import and do with what they wish.

We want 1500+ properties so we will be using Scrapy and Python

scrapy spider logic

Considerations

One of the required fields requires us to pass the particular start url all the way through to the CSV (use response.meta)

Some of the required values are inside text and will require parsing with re (use regular expressions) ¡We don’t care about being fast – edit “settings.py” with conservative values for concurrent connections, download delay

This is a German website so I will use Google Chrome browser and translate to English.

Scrapy response.meta

We will use Scrapy’s Request.meta attribute to achieve the following:

Capture whichever of the multiple start_urls is used – pass it all the way through to the output CSV.

scrapy response documentation

Create a “meta” dictionary in the initial Request in start_requests 

“surl” represents each of our start urls

(we have 2, one for ‘rent’ and one for the ‘buy’ url, we could have many more if required)

start_requests
response.meta
start_url output
we still have the start_url (converted to human a readable label)
start_url in final csv output
End result : we have the start url converted to a human readable name, that represents the particular URL that scrapy used for the particular listing

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Categories
MySQL Pandas Python Code Raspberry Pi web scraping

Add data to a database from a CSV using Python, Pandas, and SQL

Do you have a CSV file and a database to transfer the data into?

The data needs to go into your database and you want to automate this?

For instance : you have been web scraping and extracted publicly available data and now need to store it in a database table?

This guide will show you a basic example of how to get the data from a CSV, convert it to a pandas dataframe, and insert it into your chosen database table.

# |r|e|d|a|n|d|g|r|e|e|n|.|c|o|.|u|k|

# CSV to PANDAS to SQL example

Import a CSV and convert it into a pandas dataframe

import pandas as pd

df = pd.read_csv(r’claims.csv‘)

df

pat_numclaimstatus
0111222123accepted
1111333234accepted
2222444432rejected
3444555431rejected
4666777655accpted
The example csv as a pandas dataframe

Connect to existing SQL database and check we can query some data

# Module Imports
import mariadb
import sys

# Connect to MariaDB Platform
try:
    conn = mariadb.connect(
        user="user2",
        password="password2",
        host="192.168.1.9",
        port=3306,
        database="newz"

    )
except mariadb.Error as e:
    print(f"Error connecting to MariaDB Platform: {e}")
    sys.exit(1)

# Get Cursor
cur = conn.cursor()
# Select the first 8 results as a check

cur.execute(
    "SELECT title,story FROM tnewz WHERE publication=? LIMIT 8", ("independent.co.uk",)
)
# Print results selection

for (title, publication) in cur:
    print(f"Title: {title}, Story: {publication}")
Title: We need to get back to normality, and fast – I appear to have fallen in love with my robot vacuum cleaner, Story: It is absurdly easy to anthropomorphise this creature, which spins around picking up fluff – especially in the absence of a puppy or a baby in the house, writes 
Title: ‘This ends now’: Biden demands Trump make national address to end Capitol siege, Story: President-elect condemns Capitol violence: 'This is not dissent. It's disorder. It's chaos. It borders on sedition’
Title: ‘We love you, you’re all very special’: Trump tells mob to ‘go home’ but repeats false claims about election, Story: 'I know your pain. I know you're hurt’
Title: Senate evacuates after sudden recess while certifying Biden’s win amid reports of shots fired on Capitol Hill, Story: Congress calls surprise recess as protesters storm Capitol building
Title: Capitol Hill riots: Dramatic videos show Trump supporters storming Capitol building, Story: Videos posted to social media from reporters and lawmakers depicted a chaotic, terrifying scene of pro-Trump rioters breaking into the Capitol building
Title: Capitol riots: The Simpsons eerily predicted incident in 1996, Story: Scene in question shows characters running up Capitol steps, firing guns
Title: Prince William tells children of NHS staff sacrifices ‘every day’ during pandemic, Story: 'We're making sure the children understand all of the sacrifices that all of you are making,' says Duke of Cambridge
Title: Sriwijaya Air flight SJ182: Boeing 737 loses contact in Indonesia, Story: The aircraft is a ‘classic’ 737 — two generations older than the Boeing 737 Max

Connect to new database and prepare to insert dataframe

# Connect to MariaDB Platform
try:
    conn = mariadb.connect(
        user="user3",
        password="redandgreen",
        host="192.168.1.9",
        port=3306,
        database="exampledb"

    )
except mariadb.Error as e:
    print(f"Error connecting to MariaDB Platform: {e}")
    sys.exit(1)

# Get Cursor
cursor = conn.cursor()

Create new table (do this just once)

# Create Table
cursor.execute('CREATE TABLE IF NOT EXISTS patients3 (id INT AUTO_INCREMENT PRIMARY KEY, pat_num varchar(50), claim varchar(50), status varchar(50))')
for row in df.itertuples():
    cursor.execute("""
                INSERT INTO patients3
                (pat_num, claim, status)
                VALUES 
                (%s,%s,%s)
                """,
                (row.pat_num, 
                row.claim,
                row.status,
                )
)
conn.commit()

Check your database table for new data

SQL-output

If you have access to your database server then you can create a database and user with these commands:

## Useful mariadb commands :

# sudo mysql -u root -p
# CREATE DATABASE exampledb;
# CREATE USER 'user3'@'localhost' IDENTIFIED BY 'redandgreen';

# DROP USER IF EXISTS 'user3'@'%';
# CREATE USER 'user3'@'%' IDENTIFIED BY 'redandgreen';
# GRANT ALL PRIVILEGES ON exampledb.* TO 'user3'@'%';
# FLUSH PRIVILEGES;

# The % allows remote connections 

Query the SQL database and print the Patient Numbers

cur = conn.cursor()
cur.execute(
    "SELECT pat_num FROM patients3"
)
# Print results selection from SQL query

for (pat_num) in cur:
    print(f"PatientNumber: {pat_num}")
PatientNumber: ('111222',)
PatientNumber: ('111333',)
PatientNumber: ('222444',)
PatientNumber: ('3444555',)
PatientNumber: ('4666777',)
PatientNumber: ('111222',)
PatientNumber: ('111333',)

Print results selection from SQL using Pandas with an SQL query

# Create SQL query for Pandas to run
sql = """

SELECT *
FROM patients3

"""
df = pd.read_sql(sql, conn)
df.head()
idpat_numclaimstatus
01111222123accepted
12111333234accepted
23222444432rejected
343444555431rejected
45466677765accpted
Data retrieved from the SQL table using Pandas “pd.read”

Summary

We have shown how to :

  • Import a CSV into a pandas dataframe using Python
  • Connect to a MariaDB (SQL) database
  • INSERT the contents of the dataframe into a table
  • SELECT values from the database using SQL and also using Pandas

Note : (If you don’t have access to the SQL database and the table you will need the database administrator to give you the permissions to it).