Recently, I looked through our Forums and Digest, and there is no relevant information about Python crawler. Based on the FMZ spirit of comprehensive development, I went to simply learn about the concepts and knowledge of crawler. After learning about it, I found that there is still more to learn about "crawler technique". This article is only a preliminary exploration of "crawler technique", and a simplest practice of crawler technique on FMZ Quant trading platform.


For traders who like IPO trading, they always want to get the platform listing information as soon as possible. It is obviously unrealistic to manually stare at a platform website all the time. Then you need to use the crawler script to monitor the announcement page of the platform, and detect new announcements in order to be notified and reminded at the first time.

Initial Exploration

Use a very simple program as a start (really powerful crawler scripts are far more complex, so take your time). The program logic is very simple, that is, let the program continuously visit the announcement page of a platform, parse the acquired HTML content, and detect whether the content of a specifed label is updated.

Code Implementation

You can use some useful crawler structures. Considering that the demand is very simple, you can also write directly.

The python libraries to be used:
requests, which can be simply regarded as the library used to access web pages.
bs4, which can be simply regarded as the library used to parse the HTML code of web pages.


from bs4 import BeautifulSoup
import requests

urlBinanceAnnouncement = ""  # Binance announcement web page address 

def openUrl(url):
    headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.108 Safari/537.36'}
    r = requests.get(url, headers=headers)     # use "requests" library to access url, namely the Binance announcement web page address 

    if r.status_code == 200:
        r.encoding = 'utf-8'
        # Log("success! {}".format(url))
        return r.text                          # if the access succeeds, return the text of the page content  
        Log("failed {}".format(url))

def main():
    preNews_href = ""
    lastNews = ""
    Log("watching...", urlBinanceAnnouncement, "#FF0000")
    while True:
        ret = openUrl(urlBinanceAnnouncement)
        if ret:
            soup = BeautifulSoup(ret, 'html.parser')                       # parse the page text into objects 
            lastNews_href = soup.find('a', class_='css-1ej4hfo')["href"]   # find specified lables, to obtain href
            lastNews = soup.find('a', class_='css-1ej4hfo').get_text()     # obtain the content in the label 
            if preNews_href == "":
                preNews_href = lastNews_href
            if preNews_href != lastNews_href:                              # the label change detected, namely the new announcement generated
                Log("New Cryptocurrency Listing update!")                  # print the prompt message 
                preNews_href = lastNews_href
        LogStatus(_D(), "\n", "preNews_href:", preNews_href, "\n", "news:", lastNews)
        Sleep(1000 * 10)




You can even extend it, such as the detection of new announcement, analysis of newly listed currency symbols, and automatic ordering of IPO trade.

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