Scrapy practice: crawling and analyzing data from a game forum

In recent years, the use of Python for data mining and analysis has become more and more popular. Scrapy is a popular tool when it comes to scraping website data. In this article, we will introduce how to use Scrapy to crawl data from a game forum for subsequent data analysis.

1. Select the target

First, we need to select a target website. Here, we choose a game forum.

As shown in the picture below, this forum contains various resources, such as game guides, game downloads, player communication, etc.

Our goal is to obtain the post title, author, publishing time, number of replies and other information for subsequent data analysis.

2. Create a Scrapy project

Before we start crawling data, we need to create a Scrapy project. At the command line, enter the following command:

scrapy startproject forum_spider

This will create a new project named "forum_spider".

3. Configure Scrapy settings

In the settings.py file, we need to configure some settings to ensure that Scrapy can successfully crawl the required data from the forum website. The following are some commonly used settings:

BOT_NAME = 'forum_spider'

SPIDER_MODULES = ['forum_spider.spiders']
NEWSPIDER_MODULE = 'forum_spider.spiders'

ROBOTSTXT_OBEY = False # 忽略robots.txt文件
DOWNLOAD_DELAY = 1 # 下载延迟
COOKIES_ENABLED = False # 关闭cookies

4. Writing Spider

In Scrapy, Spider is the class used to perform the actual work (ie, crawl the website). We need to define a spider to get the required data from the forum.

We can use Scrapy's Shell to test and debug our Spider. At the command line, enter the following command:

scrapy shell "https://forum.example.com"

This will open an interactive Python shell with the target forum.

In the shell, we can use the following command to test the required Selector:

response.xpath("xpath_expression").extract()

Here, "xpath_expression" should be the XPath expression used to select the required data.

For example, the following code is used to obtain all threads in the forum:

response.xpath("//td[contains(@id, 'td_threadtitle_')]").extract()

After we have determined the XPath expression, we can create a Spider.

In the spiders folder, we create a new file called "forum_spider.py". The following is the code of Spider:

import scrapy

class ForumSpider(scrapy.Spider):
    name = "forum"
    start_urls = [
        "https://forum.example.com"
    ]

    def parse(self, response):
        for thread in response.xpath("//td[contains(@id, 'td_threadtitle_')]"):
            yield {
                'title': thread.xpath("a[@class='s xst']/text()").extract_first(),
                'author': thread.xpath("a[@class='xw1']/text()").extract_first(),
                'date': thread.xpath("em/span/@title").extract_first(),
                'replies': thread.xpath("a[@class='xi2']/text()").extract_first()
            }

In the above code, we first define the name of Spider as "forum" and set a starting URL. Then, we defined the parse() method to handle the response of the forum page.

In the parse() method, we use XPath expressions to select the data we need. Next, we use the yield statement to generate the data into a Python dictionary and return it. This means that our Spider will crawl all the threads in the forum homepage one by one and extract the required data.

5. Run Spider

Before executing Spider, we need to ensure that Scrapy has been configured correctly. We can test whether the spider is working properly using the following command:

scrapy crawl forum

This will start our spider and output the captured data in the console.

6. Data Analysis

After we successfully crawl the data, we can use some Python libraries (such as Pandas and Matplotlib) to analyze and visualize the data.

We can first store the crawled data as a CSV file to facilitate data analysis and processing.

import pandas as pd

df = pd.read_csv("forum_data.csv")
print(df.head())

This will display the first five rows of data in the CSV file.

We can use libraries such as Pandas and Matplotlib to perform statistical analysis and visualization of data.

Here is a simple example where we sort the data by posting time and plot the total number of posts.

import matplotlib.pyplot as plt
import pandas as pd

df = pd.read_csv("forum_data.csv")

df['date'] = pd.to_datetime(df['date']) #将时间字符串转化为时间对象
df['month'] = df['date'].dt.month

grouped = df.groupby('month')
counts = grouped.size()

counts.plot(kind='bar')
plt.title('Number of Threads by Month')
plt.xlabel('Month')
plt.ylabel('Count')
plt.show()

In the above code, we convert the release time into a Python Datetime object and group the data according to month. We then used Matplotlib to create a histogram to show the number of posts published each month.

7. Summary

This article introduces how to use Scrapy to crawl data from a game forum, and shows how to use Python's Pandas and Matplotlib libraries for data analysis and visualization. These tools are Python libraries that are very popular in the field of data analysis and can be used to explore and visualize website data.

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