Python实现简单HTML表格解析的方法
本文实例讲述了Python实现简单HTML表格解析的方法。分享给大家供大家参考。具体分析如下:
这里依赖libxml2dom,确保首先安装!导入到你的脚步并调用parse_tables() 函数。
1. source = a string containing the source code you can pass in just the table or the entire page code
2. headers = a list of ints OR a list of strings
If the headers are ints this is for tables with no header, just list the 0 based index of the rows in which you want to extract data.
If the headers are strings this is for tables with header columns (with the tags) it will pull the information from the specified columns
3. The 0 based index of the table in the source code. If there are multiple tables and the table you want to parse is the third table in the code then pass in the number 2 here
It will return a list of lists. each inner list will contain the parsed information.
具体代码如下:
#The goal of table parser is to get specific information from specific #columns in a table. #Input: source code from a typical website #Arguments: a list of headers the user wants to return #Output: A list of lists of the data in each row import libxml2dom def parse_tables(source, headers, table_index): """parse_tables(string source, list headers, table_index) headers may be a list of strings if the table has headers defined or headers may be a list of ints if no headers defined this will get data from the rows index. This method returns a list of lists """ #Determine if the headers list is strings or ints and make sure they #are all the same type j = 0 print 'Printing headers: ',headers #route to the correct function #if the header type is int if type(headers[0]) == type(1): #run no_header function return no_header(source, headers, table_index) #if the header type is string elif type(headers[0]) == type('a'): #run the header_given function return header_given(source, headers, table_index) else: #return none if the headers aren't correct return None #This function takes in the source code of the whole page a string list of #headers and the index number of the table on the page. It returns a list of #lists with the scraped information def header_given(source, headers, table_index): #initiate a list to hole the return list return_list = [] #initiate a list to hold the index numbers of the data in the rows header_index = [] #get a document object out of the source code doc = libxml2dom.parseString(source,html=1) #get the tables from the document tables = doc.getElementsByTagName('table') try: #try to get focue on the desired table main_table = tables[table_index] except: #if the table doesn't exits then return an error return ['The table index was not found'] #get a list of headers in the table table_headers = main_table.getElementsByTagName('th') #need a sentry value for the header loop loop_sentry = 0 #loop through each header looking for matches for header in table_headers: #if the header is in the desired headers list if header.textContent in headers: #add it to the header_index header_index.append(loop_sentry) #add one to the loop_sentry loop_sentry+=1 #get the rows from the table rows = main_table.getElementsByTagName('tr') #sentry value detecting if the first row is being viewed row_sentry = 0 #loop through the rows in the table, skipping the first row for row in rows: #if row_sentry is 0 this is our first row if row_sentry == 0: #make the row_sentry not 0 row_sentry = 1337 continue #get all cells from the current row cells = row.getElementsByTagName('td') #initiate a list to append into the return_list cell_list = [] #iterate through all of the header index's for i in header_index: #append the cells text content to the cell_list cell_list.append(cells[i].textContent) #append the cell_list to the return_list return_list.append(cell_list) #return the return_list return return_list #This function takes in the source code of the whole page an int list of #headers indicating the index number of the needed item and the index number #of the table on the page. It returns a list of lists with the scraped info def no_header(source, headers, table_index): #initiate a list to hold the return list return_list = [] #get a document object out of the source code doc = libxml2dom.parseString(source, html=1) #get the tables from document tables = doc.getElementsByTagName('table') try: #Try to get focus on the desired table main_table = tables[table_index] except: #if the table doesn't exits then return an error return ['The table index was not found'] #get all of the rows out of the main_table rows = main_table.getElementsByTagName('tr') #loop through each row for row in rows: #get all cells from the current row cells = row.getElementsByTagName('td') #initiate a list to append into the return_list cell_list = [] #loop through the list of desired headers for i in headers: try: #try to add text from the cell into the cell_list cell_list.append(cells[i].textContent) except: #if there is an error usually an index error just continue continue #append the data scraped into the return_list return_list.append(cell_list) #return the return list return return_list
希望本文所述对大家的Python程序设计有所帮助。

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

The speed of mobile XML to PDF depends on the following factors: the complexity of XML structure. Mobile hardware configuration conversion method (library, algorithm) code quality optimization methods (select efficient libraries, optimize algorithms, cache data, and utilize multi-threading). Overall, there is no absolute answer and it needs to be optimized according to the specific situation.

It is impossible to complete XML to PDF conversion directly on your phone with a single application. It is necessary to use cloud services, which can be achieved through two steps: 1. Convert XML to PDF in the cloud, 2. Access or download the converted PDF file on the mobile phone.

There is no built-in sum function in C language, so it needs to be written by yourself. Sum can be achieved by traversing the array and accumulating elements: Loop version: Sum is calculated using for loop and array length. Pointer version: Use pointers to point to array elements, and efficient summing is achieved through self-increment pointers. Dynamically allocate array version: Dynamically allocate arrays and manage memory yourself, ensuring that allocated memory is freed to prevent memory leaks.

An application that converts XML directly to PDF cannot be found because they are two fundamentally different formats. XML is used to store data, while PDF is used to display documents. To complete the transformation, you can use programming languages and libraries such as Python and ReportLab to parse XML data and generate PDF documents.

XML can be converted to images by using an XSLT converter or image library. XSLT Converter: Use an XSLT processor and stylesheet to convert XML to images. Image Library: Use libraries such as PIL or ImageMagick to create images from XML data, such as drawing shapes and text.

XML formatting tools can type code according to rules to improve readability and understanding. When selecting a tool, pay attention to customization capabilities, handling of special circumstances, performance and ease of use. Commonly used tool types include online tools, IDE plug-ins, and command-line tools.

To convert XML images, you need to determine the XML data structure first, then select a suitable graphical library (such as Python's matplotlib) and method, select a visualization strategy based on the data structure, consider the data volume and image format, perform batch processing or use efficient libraries, and finally save it as PNG, JPEG, or SVG according to the needs.

There is no APP that can convert all XML files into PDFs because the XML structure is flexible and diverse. The core of XML to PDF is to convert the data structure into a page layout, which requires parsing XML and generating PDF. Common methods include parsing XML using Python libraries such as ElementTree and generating PDFs using ReportLab library. For complex XML, it may be necessary to use XSLT transformation structures. When optimizing performance, consider using multithreaded or multiprocesses and select the appropriate library.
