减少Python脚本中的RAM使用量

Question

我写了一个快速的小程序来从教科文组织网站上删除书籍数据,其中包含有关书籍翻译的信息.代码正在按照我的意愿行事,但是当它处理大约20个国家时,它正在使用~6GB的RAM.由于我需要处理大约200个,这对我来说不起作用.

我不确定所有RAM的使用来自哪里,所以我不确定如何减少它.我假设它是包含所有书籍信息的字典,但我并不积极.我不确定我是否应该简单地让程序为每个国家运行一次,而不是处理它们中的很多？或者,如果有更好的方法吗？

这是我第一次写这样的东西,而且我是一个非常新手,自学成才的程序员,所以请指出代码中的任何重大缺陷,或者你提出的改进技巧可能与问题没有直接关系在眼前.

这是我的代码,提前感谢任何帮助.

from __future__ import print_function
import urllib2, os
from bs4 import BeautifulSoup, SoupStrainer

''' Set list of countries and their code for niceness in explaining what
is actually going on as the program runs. '''
countries = {"AFG":"Afghanistan","ALA":"Aland Islands","DZA":"Algeria"}

'''List of country codes since dictionaries aren't sorted in any
way, this makes processing easier to deal with if it fails at
some point, mid run.'''
country_code_list = ["AFG","ALA","DZA"]

base_url = "http://www.unesco.org/xtrans/bsresult.aspx?lg=0&c="
destination_directory = "/Users/robbie/Test/"
only_restable = SoupStrainer(class_="restable")

class Book(object):
    def set_author(self,book): 
        '''Parse the webpage to find author names. Finds last name, then
        first name of original author(s) and sets the Book object's 
        Author attribute to the resulting string.'''

        authors = ""
        author_last_names = book.find_all('span',class_="sn_auth_name")
        author_first_names = book.find_all('span', attrs={\
            'class':"sn_auth_first_name"})
        if author_last_names == []: self.Author = [" "]

        for author in author_last_names:
            try: 
                first_name = author_first_names.pop()
                authors = authors + author.getText() + ', ' + \
                    first_name.getText()

            except IndexError:
                authors = authors + (author.getText())
        self.author = authors

    def set_quality(self,book):
        ''' Check to see if book page is using Quality, then set it if 
        so.'''

        quality = book.find_all('span', class_="sn_auth_quality")

        if len(quality) == 0: self.quality = " "

        else: self.quality = quality[0].contents[0]

    def set_target_title(self,book): 
        target_title = book.find_all('span', class_="sn_target_title")
        if len(target_title) == 0: self.target_title = " "
        else: self.target_title = target_title[0].contents[0]

    def set_target_language(self,book): 
        target_language = book.find_all('span', class_="sn_target_lang")
        if len(target_language) == 0: self.target_language = " "
        else: self.target_language = target_language[0].contents[0]

    def set_translator_name(self,book) : 
        translators = ""
        translator_last_names = book.find_all('span', class_="sn_transl_name")
        translator_first_names = book.find_all('span', \
                                               class_="sn_transl_first_name")
        if translator_first_names == [] and translator_last_names == [] :
            self.translators = " "
            return None

        for translator in translator_last_names:
            try: 
                first_name = translator_first_names.pop()
                translators = translators + \
                    (translator.getText() + ',' \
                     + first_name.getText())
            except IndexError:
                translators = translators + \
                    (translator.getText())

        self.translators = translators  

    def set_published_city(self,book) : 
        published_city = book.find_all('span', class_="place")
        if len(published_city) == 0: 
            self.published_city = " "
        else: self.published_city = published_city[0].contents[0]

    def set_publisher(self,book) : 
        publisher = book.find_all('span', class_="place")
        if len(publisher) == 0: 
            self.publisher = " "
        else: self.publisher = publisher[0].contents[0] 

    def set_published_country(self,book) : 
        published_country = book.find_all('span', \
                                        class_="sn_country")
        if len(published_country) == 0: 
            self.published_country = " "
        else: self.published_country = published_country[0].contents[0]

    def set_year(self,book) : 
        year = book.find_all('span', class_="sn_year")
        if len(year) == 0: 
            self.year = " "
        else: self.year = year[0].contents[0]   

    def set_pages(self,book) : 
        pages = book.find_all('span', class_="sn_pagination")
        if len(pages) == 0: 
            self.pages = " "
        else: self.pages = pages[0].contents[0] 

    def set_edition(self, book) :
        edition = book.find_all('span', class_="sn_editionstat")
        if len(edition) == 0: 
            self.edition = " "
        else: self.edition = edition[0].contents[0]

    def set_original_title(self,book) : 
        original_title = book.find_all('span', class_="sn_orig_title")
        if len(original_title) == 0: 
            self.original_title = " "
        else: self.original_title = original_title[0].contents[0]   

    def set_original_language(self,book) :
        languages = ''
        original_languages = book.find_all('span', \
                                         class_="sn_orig_lang")

        for language in original_languages:
            languages = languages + language.getText() + ', '

        self.original_languages = languages

    def export(self, country): 
        ''' Function to allow us to easilly pull the text from the 
        contents of the Book object's attributes and write them to the 
        country in which the book was published's CSV file.'''

        file_name = os.path.join(destination_directory + country + ".csv")

        with open(file_name, "a") as by_country_csv:        
            print(self.author.encode('UTF-8') + " & " + \
                  self.quality.encode('UTF-8') + " & " + \
                  self.target_title.encode('UTF-8') + " & " + \
                  self.target_language.encode('UTF-8') + " & " + \
                  self.translators.encode('UTF-8') + " & " + \
                  self.published_city.encode('UTF-8') + " & " + \
                  self.publisher.encode('UTF-8') + " & " + \

                  self.published_country.encode('UTF-8') + " & " + \
                  self.year.encode('UTF-8') + " & " + \
                  self.pages.encode('UTF-8') + " & " + \
                  self.edition.encode('UTF-8') + " & " + \
                  self.original_title.encode('UTF-8') + " & " + \
                  self.original_languages.encode('UTF-8'), file=by_country_csv)

        by_country_csv.close()

    def __init__(self, book, country):
        ''' Initialize the Book object by feeding it the HTML for its 
        row'''
        self.set_author(book)
        self.set_quality(book)
        self.set_target_title(book)
        self.set_target_language(book)

        self.set_translator_name(book)
        self.set_published_city(book)
        self.set_publisher(book)
        self.set_published_country(book)

        self.set_year(book)
        self.set_pages(book)
        self.set_edition(book)
        self.set_original_title(book)

        self.set_original_language(book)


def get_all_pages(country,base_url):
    ''' Create a list of URLs to be crawled by adding the ISO_3166-1_alpha-3
    country code to the URL and then iterating through the results every 10
    pages. Returns a string.'''

    base_page = urllib2.urlopen(base_url+country)
    page = BeautifulSoup(base_page, parse_only=only_restable)

    result_number = page.find_all('td',class_="res1",limit=1)
    if not result_number:
        return 0

    str_result_number = str(result_number[0].getText())
    results_total = int(str_result_number.split('/')[1])

    page.decompose()

    return results_total


def build_list(country_code_list, countries):
    '''  Build the list of all the books, and return a list of Book objects
    in case you want to do something with them in something else, ever.'''
    for country in country_code_list:

        print("Processing %s now..." % countries[country])
        results_total = get_all_pages(country, base_url)

        for url in range(results_total):
            if url % 10 == 0 :
                all_books = []  
                target_page = urllib2.urlopen(base_url + country \
                                             +"&fr="+str(url))
                page = BeautifulSoup(target_page, parse_only=only_restable)
                books = page.find_all('td',class_="res2")
                for book in books:
                    all_books.append(Book (book,country))
                page.decompose()

                for title in all_books:
                    title.export(country)    
    return

if __name__ == "__main__":
    build_list(country_code_list,countries)
    print("Completed.")

Answer 1

我想我只会列出一些问题或可能没有特定顺序的改进:

1. 关注PEP 8.

   现在,你已经有很多变量和函数使用像camel-case命名setAuthor.这不是Python的传统风格; Python通常会命名set_author(published_country而不是PublishedCountry等).您甚至可以更改您正在调用的某些内容的名称:例如,BeautifulSoup支持findAll兼容性,但find_all建议您使用.

   除了命名之外,PEP 8还指定了其他一些东西; 例如,你想要重写这个:

   if len(resultNumber) == 0 : return 0
   

   如下:

   if len(result_number) == 0:
       return 0
   

   甚至考虑到空名单是假的这一事实:

   if not result_number:
       return 0
   

2. 传递SoupStrainer到BeautifulSoup.

   您正在寻找的信息可能只是文档的一部分; 你不需要将整个事物解析成树.将a SoupStrainer作为parse_only参数传递给BeautifulSoup.这应该通过尽早丢弃不必要的部分来减少内存使用量.

3. decompose 你完成它的汤.

   Python 主要使用引用计数,因此删除所有循环引用(如同decompose)应该让它的主要机制进行垃圾收集,引用计数,释放大量内存.Python还有一个半传统的垃圾收集器来处理循环引用,但引用计数要快得多.

4. 不要Book.__init__写东西到磁盘.

   在大多数情况下,我不希望只创建一个类的实例来写入磁盘.删除电话export; export如果用户希望将其放在磁盘上,请让用户调用.

5. 停止在内存中保留这么多数据.

   您将所有这些数据累积到字典中,然后将其导出.减少内存显而易见的事情是尽快将其转储到磁盘上.您的评论表明您将其放入字典中以保持灵活性; 但这并不意味着你必须在列表中收集它们:使用生成器,在刮​​掉它们时产生物品.然后用户可以像列表一样迭代它:

   for book in scrape_books():
       book.export()
   

   ......但是有一个优点,就是一次只能将一本书保存在记忆中.

6. 使用函数os.path而不是自己修改路径.

   在路径名称中,您的代码现在相当脆弱.如果我不小心删除了尾随斜线destinationDirectory,会发生意外情况.使用os.path.join可防止这种情况发生并处理跨平台差异:

   >>> os.path.join("/Users/robbie/Test/", "USA")
   '/Users/robbie/Test/USA'
   >>> os.path.join("/Users/robbie/Test", "USA")  # still works!
   '/Users/robbie/Test/USA'
   >>> # or say we were on Windows:
   >>> os.path.join(r"C:\Documents and Settings\robbie\Test", "USA")
   'C:\\Documents and Settings\\robbie\\Test\\USA'
   

7. 缩写attrs={"class":...}为class_=....

   BeautifulSoup 4.1.2引入了搜索功能class_,从而消除了对详细信息的需求attrs={"class":...}.

我想有更多的事情你可以改变,但这开始有很多.