python程序运行几天就死机-6ren

python程序运行几天就死机

转载作者：太空宇宙更新时间：2023-11-03 16:24:40

问题是这样的:

我正在编写一个 python 程序，其目的是不断从 RSS 源收集新闻。我希望程序收集 1 周的数据。问题是该计划永远无法坚持到周末。有时运行几天就死机，有时运行几个小时甚至几分钟就死机。它总是卡住，没有错误。当我说卡住时，我的意思是解释器似乎仍在运行，因为我无法给它任何额外的命令。我怎么解决这个问题？

我将发布下面的代码。谢谢大家!!

from goose import Goose
from requests import get
import urllib2
import feedparser
from urllib2 import urlopen
import pandas as pd
import numpy as np
from bs4 import BeautifulSoup
import re
import datetime as dt
import time
import os
Symbols=['AAPL','T','BA','XOM','GOOG','JPM','PG','WMT']
url='http://finance.yahoo.com/rss/headline?s='

for t in xrange(7):
    AAPL=pd.DataFrame()
    AAPL['Published']=""
    AAPL['Title']=""
    AAPL['link']=""
    AAPL['ID']=""
    AAPL['News']=""

    T=pd.DataFrame()
    T['Published']=""
    T['Title']=""
    T['link']=""
    T['ID']=""
    T['News']=""

    BA=pd.DataFrame()
    BA['Published']=""
    BA['Title']=""
    BA['link']=""
    BA['ID']=""
    BA['News']=""

    XOM=pd.DataFrame()
    XOM['Published']=""
    XOM['Title']=""
    XOM['link']=""
    XOM['ID']=""
    XOM['News']=""

    GOOG=pd.DataFrame()
    GOOG['Published']=""
    GOOG['Title']=""
    GOOG['link']=""
    GOOG['ID']=""
    GOOG['News']=""

    JPM=pd.DataFrame()
    JPM['Published']=""
    JPM['Title']=""
    JPM['link']=""
    JPM['ID']=""
    JPM['News']=""

    PG=pd.DataFrame()
    PG['Published']=""
    PG['Title']=""
    PG['link']=""
    PG['ID']=""
    PG['News']=""

    WMT=pd.DataFrame()
    WMT['Published']=""
    WMT['Title']=""
    WMT['link']=""
    WMT['ID']=""
    WMT['News']=""




    DaysIDsAAPL=[]
    DaysIDsT=[]
    DaysIDsBA=[]
    DaysIDsXOM=[]
    DaysIDsGOOG=[]
    DaysIDsJPM=[]
    DaysIDsPG=[]
    DaysIDsWMT=[]



    count=0

    AAPLCount=0
    TCount=0
    BACount=0
    XOMCount=0
    GOOGCount=0
    JPMCount=0
    PGCount=0
    WMTCount=0

    date=dt.date.today()

    newpathAAPL = r'D:\News Data\AAPL\\'+str(t)
    newpathT = r'D:\News Data\T\\'+str(t)
    newpathBA = r'D:\News Data\BA\\'+str(t)
    newpathXOM = r'D:\News Data\XOM\\'+str(t)
    newpathGOOG = r'D:\News Data\GOOG\\'+str(t)
    newpathJPM = r'D:\News Data\JPM\\'+str(t)
    newpathPG = r'D:\News Data\PG\\'+str(t)
    newpathWMT = r'D:\News Data\WMT\\'+str(t)
    os.makedirs(newpathAAPL)
    os.makedirs(newpathT)
    os.makedirs(newpathBA)
    os.makedirs(newpathXOM)
    os.makedirs(newpathGOOG)
    os.makedirs(newpathJPM)
    os.makedirs(newpathPG)
    os.makedirs(newpathWMT)
    while dt.date.today()==date:
        print "Loop"
        try:
        #AAPL inner most loop
            d1=feedparser.parse(url+Symbols[0])  
            for x in xrange(len(d1['entries'])):
                if int(d1.entries[x]['id'][14:]) not in DaysIDsAAPL:
                    DaysIDsAAPL.append(int(d1.entries[x]['id'][14:]))
                    y = len(AAPL.index.tolist())
                    m=re.search(r'\*(.*)',d1.entries[x]['link'])
                    z=re.search(r'\?ru=yahoo\?mod=yahoo_itp',m.group(1))
                    if type(z) is not None:
                        m=re.sub(r'\?ru=yahoo\?mod=yahoo_itp', '', m.group(1))
                    AAPL.loc[y,'Title'] =d1.entries[x]['title'].encode('utf8')
                    AAPL.loc[y,'link'] =m.encode('utf8')
                    AAPL.loc[y,'Published'] =d1.entries[x]['published'].encode('utf8')
                    AAPL.loc[y,'ID'] =int(d1.entries[x]['id'][14:])
                    hdr = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
                    page = get(m,headers=hdr)
                    extractor = Goose()
                    article = extractor.extract(raw_html=page.text)
                    text = article.cleaned_text.encode('utf8')
                    if text == '':
                        try:
                            url2 = m
                            req = urllib2.Request(url2, None, hdr)
                            html2 = urlopen(req).read().decode('utf8')
                            raw = BeautifulSoup(html2,"lxml").get_text().encode('utf8')
                            Text_file = open(newpathAAPL+r"\\"+str(AAPLCount)+".txt", "w")
                            Text_file.write(raw)
                            Text_file.close()
                            AAPL.loc[y,'News'] = AAPLCount
                            AAPLCount+=1
                            AAPL=AAPL.fillna("")
                            AAPL.to_csv(newpathAAPL+r'\Key.csv')
                        except:
                            print m
                            print "AAPL"
                    else:
                        Text_file = open(newpathAAPL+r"\\"+str(AAPLCount)+".txt", "w")
                        Text_file.write(text)
                        Text_file.close()
                        AAPL.loc[y,'News'] =AAPLCount
                        AAPLCount+=1
                        AAPL=AAPL.fillna("")
                        AAPL.to_csv(newpathAAPL+r'\Key.csv')
                    print "AAPL"

            #T inner most loop
            d2=feedparser.parse(url+Symbols[1])

            for x in xrange(len(d2['entries'])):
                if int(d2.entries[x]['id'][14:]) not in DaysIDsT:
                    DaysIDsT.append(int(d2.entries[x]['id'][14:]))
                    y = len(T.index.tolist())
                    m=re.search(r'\*(.*)',d2.entries[x]['link'])
                    z=re.search(r'\?ru=yahoo\?mod=yahoo_itp',m.group(1))
                    if type(z) is not None:
                        m=re.sub(r'\?ru=yahoo\?mod=yahoo_itp', '', m.group(1))
                    T.loc[y,'Title'] =d2.entries[x]['title'].encode('utf8')
                    T.loc[y,'link'] =m.encode('utf8')
                    T.loc[y,'Published'] =d2.entries[x]['published'].encode('utf8')
                    T.loc[y,'ID'] =int(d2.entries[x]['id'][14:])
                    hdr = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
                    page = get(m,headers=hdr)
                    extractor = Goose()
                    article = extractor.extract(raw_html=page.text)
                    text = article.cleaned_text.encode('utf8')
                    if text == '':
                        try:
                            url2 = m
                            req = urllib2.Request(url2, None, hdr)
                            html2 = urlopen(req).read().decode('utf8')
                            raw = BeautifulSoup(html2,"lxml").get_text().encode('utf8')
                            Text_file = open(newpathT+r"\\"+str(TCount)+".txt", "w")
                            Text_file.write(raw)
                            Text_file.close()
                            T.loc[y,'News'] = TCount
                            TCount+=1
                            T=T.fillna("")
                            T.to_csv(newpathT+r'\Key.csv')
                        except:
                            print m
                            print "T"
                    else:
                        Text_file = open(newpathT+r"\\"+str(TCount)+".txt", "w")
                        Text_file.write(text)
                        Text_file.close()
                        T.loc[y,'News'] =TCount
                        TCount+=1
                        T=T.fillna("")
                        T.to_csv(newpathT+r'\Key.csv')
                    print "T"

            #BA inner most loop
            d3=feedparser.parse(url+Symbols[2])

            for x in xrange(len(d3['entries'])):
                if int(d3.entries[x]['id'][14:]) not in DaysIDsBA:
                    DaysIDsBA.append(int(d3.entries[x]['id'][14:]))
                    y = len(BA.index.tolist())
                    m=re.search(r'\*(.*)',d3.entries[x]['link'])
                    z=re.search(r'\?ru=yahoo\?mod=yahoo_itp',m.group(1))
                    if type(z) is not None:
                        m=re.sub(r'\?ru=yahoo\?mod=yahoo_itp', '', m.group(1))
                    BA.loc[y,'Title'] =d3.entries[x]['title'].encode('utf8')
                    BA.loc[y,'link'] =m.encode('utf8')
                    BA.loc[y,'Published'] =d3.entries[x]['published'].encode('utf8')
                    BA.loc[y,'ID'] =int(d3.entries[x]['id'][14:])
                    hdr = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
                    page = get(m,headers=hdr)
                    extractor = Goose()
                    article = extractor.extract(raw_html=page.text)
                    text = article.cleaned_text.encode('utf8')
                    if text == '':
                        try:
                            url2 = m
                            req = urllib2.Request(url2, None, hdr)
                            html2 = urlopen(req).read().decode('utf8')
                            raw = BeautifulSoup(html2,"lxml").get_text().encode('utf8')
                            Text_file = open(newpathBA+r"\\"+str(BACount)+".txt", "w")
                            Text_file.write(raw)
                            Text_file.close()
                            BA.loc[y,'News'] = BACount
                            BACount+=1
                            BA=BA.fillna("")
                            BA.to_csv(newpathBA+r'\Key.csv')
                        except:
                            print m
                            print "BA"
                    else:
                        Text_file = open(newpathBA+r"\\"+str(BACount)+".txt", "w")
                        Text_file.write(text)
                        Text_file.close()
                        BA.loc[y,'News'] =BACount
                        BACount+=1
                        BA=BA.fillna("")
                        BA.to_csv(newpathBA+r'\Key.csv')
                    print "BA"

            #XOM inner most loop
            d4=feedparser.parse(url+Symbols[3])

            for x in xrange(len(d4['entries'])):
                if int(d4.entries[x]['id'][14:]) not in DaysIDsXOM:
                    DaysIDsXOM.append(int(d4.entries[x]['id'][14:]))
                    y = len(XOM.index.tolist())
                    m=re.search(r'\*(.*)',d4.entries[x]['link'])
                    z=re.search(r'\?ru=yahoo\?mod=yahoo_itp',m.group(1))
                    if type(z) is not None:
                        m=re.sub(r'\?ru=yahoo\?mod=yahoo_itp', '', m.group(1))
                    XOM.loc[y,'Title'] =d4.entries[x]['title'].encode('utf8')
                    XOM.loc[y,'link'] =m.encode('utf8')
                    XOM.loc[y,'Published'] =d4.entries[x]['published'].encode('utf8')
                    XOM.loc[y,'ID'] =int(d4.entries[x]['id'][14:])
                    hdr = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
                    page = get(m,headers=hdr)
                    extractor = Goose()
                    article = extractor.extract(raw_html=page.text)
                    text = article.cleaned_text.encode('utf8')
                    if text == '':
                        try:
                            url2 = m
                            req = urllib2.Request(url2, None, hdr)
                            html2 = urlopen(req).read().decode('utf8')
                            raw = BeautifulSoup(html2,"lxml").get_text().encode('utf8')
                            Text_file = open(newpathXOM+r"\\"+str(XOMCount)+".txt", "w")
                            Text_file.write(raw)
                            Text_file.close()
                            XOM.loc[y,'News'] = XOMCount
                            XOMCount+=1
                            XOM=XOM.fillna("")
                            XOM.to_csv(newpathXOM+r'\Key.csv')
                        except:
                            print m
                            print "XOM"
                    else:
                        Text_file = open(newpathXOM+r"\\"+str(XOMCount)+".txt", "w")
                        Text_file.write(text)
                        Text_file.close()
                        XOM.loc[y,'News'] =XOMCount
                        XOMCount+=1
                        XOM=XOM.fillna("")
                        XOM.to_csv(newpathXOM+r'\Key.csv')

            #GOOG inner most loop
            d5=feedparser.parse(url+Symbols[4])

            for x in xrange(len(d5['entries'])):
                if int(d5.entries[x]['id'][14:]) not in DaysIDsGOOG:
                    DaysIDsGOOG.append(int(d5.entries[x]['id'][14:]))
                    y = len(GOOG.index.tolist())
                    m=re.search(r'\*(.*)',d5.entries[x]['link'])
                    z=re.search(r'\?ru=yahoo\?mod=yahoo_itp',m.group(1))
                    if type(z) is not None:
                        m=re.sub(r'\?ru=yahoo\?mod=yahoo_itp', '', m.group(1))
                    GOOG.loc[y,'Title'] =d5.entries[x]['title'].encode('utf8')
                    GOOG.loc[y,'link'] =m.encode('utf8')
                    GOOG.loc[y,'Published'] =d5.entries[x]['published'].encode('utf8')
                    GOOG.loc[y,'ID'] =int(d5.entries[x]['id'][14:])
                    hdr = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
                    page = get(m,headers=hdr)
                    extractor = Goose()
                    article = extractor.extract(raw_html=page.text)
                    text = article.cleaned_text.encode('utf8')
                    if text == '':
                        try:
                            url2 = m
                            req = urllib2.Request(url2, None, hdr)
                            html2 = urlopen(req).read().decode('utf8')
                            raw = BeautifulSoup(html2,"lxml").get_text().encode('utf8')
                            Text_file = open(newpathGOOG+r"\\"+str(GOOGCount)+".txt", "w")
                            Text_file.write(raw)
                            Text_file.close()
                            GOOG.loc[y,'News'] = GOOGCount
                            GOOGCount+=1
                            GOOG=GOOG.fillna("")
                            GOOG.to_csv(newpathGOOG+r'\Key.csv')
                        except:
                            print m
                            print "GOOG"
                    else:
                        Text_file = open(newpathGOOG+r"\\"+str(GOOGCount)+".txt", "w")
                        Text_file.write(text)
                        Text_file.close()
                        GOOG.loc[y,'News'] =GOOGCount
                        GOOGCount+=1
                        GOOG=GOOG.fillna("")
                        GOOG.to_csv(newpathGOOG+r'\Key.csv')
                    print "GOOG"

            #JPM inner most loop
            d6=feedparser.parse(url+Symbols[5])

            for x in xrange(len(d6['entries'])):
                if int(d6.entries[x]['id'][14:]) not in DaysIDsJPM:
                    DaysIDsJPM.append(int(d6.entries[x]['id'][14:]))
                    y = len(JPM.index.tolist())
                    m=re.search(r'\*(.*)',d6.entries[x]['link'])
                    z=re.search(r'\?ru=yahoo\?mod=yahoo_itp',m.group(1))
                    if type(z) is not None:
                        m=re.sub(r'\?ru=yahoo\?mod=yahoo_itp', '', m.group(1))
                    JPM.loc[y,'Title'] =d6.entries[x]['title'].encode('utf8')
                    JPM.loc[y,'link'] =m.encode('utf8')
                    JPM.loc[y,'Published'] =d6.entries[x]['published'].encode('utf8')
                    JPM.loc[y,'ID'] =int(d6.entries[x]['id'][14:])
                    hdr = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
                    page = get(m,headers=hdr)
                    extractor = Goose()
                    article = extractor.extract(raw_html=page.text)
                    text = article.cleaned_text.encode('utf8')
                    if text == '':
                        try:
                            url2 = m
                            req = urllib2.Request(url2, None, hdr)
                            html2 = urlopen(req).read().decode('utf8')
                            raw = BeautifulSoup(html2,"lxml").get_text().encode('utf8')
                            Text_file = open(newpathJPM+r"\\"+str(JPMCount)+".txt", "w")
                            Text_file.write(raw)
                            Text_file.close()
                            JPM.loc[y,'News'] = JPMCount
                            JPMCount+=1
                            JPM=JPM.fillna("")
                            JPM.to_csv(newpathJPM+r'\Key.csv')
                        except:
                            print m
                            print "JPM"
                    else:
                        Text_file = open(newpathJPM+r"\\"+str(JPMCount)+".txt", "w")
                        Text_file.write(text)
                        Text_file.close()
                        JPM.loc[y,'News'] =JPMCount
                        JPMCount+=1
                        JPM=JPM.fillna("")
                        JPM.to_csv(newpathJPM+r'\Key.csv')
                    print "JPM"


            #PG inner most loop
            d7=feedparser.parse(url+Symbols[6])

            for x in xrange(len(d7['entries'])):
                if int(d7.entries[x]['id'][14:]) not in DaysIDsPG:
                    DaysIDsPG.append(int(d7.entries[x]['id'][14:]))
                    y = len(PG.index.tolist())
                    m=re.search(r'\*(.*)',d7.entries[x]['link'])
                    z=re.search(r'\?ru=yahoo\?mod=yahoo_itp',m.group(1))
                    if type(z) is not None:
                        m=re.sub(r'\?ru=yahoo\?mod=yahoo_itp', '', m.group(1))
                    PG.loc[y,'Title'] =d7.entries[x]['title'].encode('utf8')
                    PG.loc[y,'link'] =m.encode('utf8')
                    PG.loc[y,'Published'] =d7.entries[x]['published'].encode('utf8')
                    PG.loc[y,'ID'] =int(d7.entries[x]['id'][14:])
                    hdr = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
                    page = get(m,headers=hdr)
                    extractor = Goose()
                    article = extractor.extract(raw_html=page.text)
                    text = article.cleaned_text.encode('utf8')
                    if text == "":
                        try:
                            url2 = m
                            req = urllib2.Request(url2, None, hdr)
                            html2 = urlopen(req).read().decode('utf8')
                            raw = BeautifulSoup(html2,"lxml").get_text().encode('utf8')
                            Text_file = open(newpathPG+r"\\"+str(PGCount)+".txt", "w")
                            Text_file.write(raw)
                            Text_file.close()
                            PG.loc[y,'News'] = PGCount
                            PGCount+=1
                            PG=PG.fillna("")
                            PG.to_csv(newpathPG+r'\Key.csv')
                        except:
                            print m
                            print "PG"
                    else:
                        Text_file = open(newpathPG+r"\\"+str(PGCount)+".txt", "w")
                        Text_file.write(text)
                        Text_file.close()
                        PG.loc[y,'News'] =PGCount
                        PGCount+=1
                        PG=PG.fillna("")
                        PG.to_csv(newpathPG+r'\Key.csv')
                    print "PG"


            #WMT inner most loop
            d8=feedparser.parse(url+Symbols[7])

            for x in xrange(len(d8['entries'])):
                if int(d8.entries[x]['id'][14:]) not in DaysIDsWMT:
                    DaysIDsWMT.append(int(d8.entries[x]['id'][14:]))
                    y = len(WMT.index.tolist())
                    m=re.search(r'\*(.*)',d8.entries[x]['link'])
                    z=re.search(r'\?ru=yahoo\?mod=yahoo_itp',m.group(1))
                    if type(z) is not None:
                        m=re.sub(r'\?ru=yahoo\?mod=yahoo_itp', '', m.group(1))
                    WMT.loc[y,'Title'] =d8.entries[x]['title'].encode('utf8')
                    WMT.loc[y,'link'] =m.encode('utf8')
                    WMT.loc[y,'Published'] =d8.entries[x]['published'].encode('utf8')
                    WMT.loc[y,'ID'] =int(d8.entries[x]['id'][14:])
                    hdr = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/39.0.2171.95 Safari/537.36'}
                    page = get(m,headers=hdr)
                    extractor = Goose()
                    article = extractor.extract(raw_html=page.text)
                    text = article.cleaned_text.encode('utf8')
                    if text == "":
                        try:
                            url2 = m
                            req = urllib2.Request(url2, None, hdr)
                            html2 = urlopen(req).read().decode('utf8')
                            raw = BeautifulSoup(html2,"lxml").get_text().encode('utf8')
                            Text_file = open(newpathWMT+r"\\"+str(WMTCount)+".txt", "w")
                            Text_file.write(raw)
                            Text_file.close()
                            WMT.loc[y,'News'] = WMTCount
                            WMTCount+=1
                            WMT=WMT.fillna("")
                            WMT.to_csv(newpathWMT+r'\Key.csv')
                        except:
                            print m
                            print "WMT"
                    else:
                        Text_file = open(newpathWMT+r"\\"+str(WMTCount)+".txt", "w")
                        Text_file.write(text)
                        Text_file.close()
                        WMT.loc[y,'News'] =WMTCount
                        WMTCount+=1
                        WMT=WMT.fillna("")
                        WMT.to_csv(newpathWMT+r'\Key.csv')
                    print "WMT"       
            count+=1
            print count
            time.sleep(1)
        except:
            print "Error"
    AAPL=AAPL.fillna("")
    AAPL.to_csv(newpathAAPL+r'\Key.csv')
    T=T.fillna("")
    T.to_csv(newpathT+r'\Key.csv')
    BA=BA.fillna("")
    BA.to_csv(newpathBA+r'\Key.csv')
    XOM=XOM.fillna("")
    XOM.to_csv(newpathXOM+r'\Key.csv')
    GOOG=GOOG.fillna("")
    GOOG.to_csv(newpathGOOG+r'\Key.csv')
    JPM=JPM.fillna("")
    JPM.to_csv(newpathJPM+r'\Key.csv')
    PG=PG.fillna("")
    PG.to_csv(newpathPG+r'\Key.csv')
    WMT=WMT.fillna("")
    WMT.to_csv(newpathWMT+r'\Key.csv')

最佳答案

当程序收集过多的提要或系统上有其他事件进程时，会消耗过多的 RAM(这就是卡住时间不同的原因)，请参阅 Why does a simple python script crash my system

程序运行的进程将用于计算的数组和变量存储在进程内存中，即内存

您可以通过强制程序使用硬盘内存来解决此问题。

有关解决方法(搁置、定期将收集的提要保存到文本文件(将信息从 ram 移动到 rom 并释放 ram)，...)请参阅以下链接

memory usage, how to free memory

Python large variable RAM usage

I need to free up RAM by storing a Python dictionary on the hard drive, not in RAM. Is it possible?

关于python程序运行几天就死机，我们在Stack Overflow上找到一个类似的问题： https://stackoverflow.com/questions/38109506/

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我搜索了又搜索，但对我帮助不大，因此发布了新问题。平台Ubuntu 11.10 服务器 64 位虚拟机 1.7.0_03 Tomcat 7 配置中没有什么特别之处——前端服务器是使用 ajp 连接器的
c - 在 C 中写入大量文件后 Ubuntu 死机
我的整个系统(Ubuntu 18.04)总是在我的 c 程序不断将一些日志写入文件大约一小时后卡住。创建的每个文件大约为 100 到 200MB，系统停机前这些文件的总量约为 40-60GB。通常，此
java - 从 Java 内部调用时 VLC 死机
我现在遇到一个问题，我什至不知道如何正确调查。欢迎并感谢任何有关我如何获得更多信息的建议。我的公司销售以 WinXP PC 为核心的产品。该产品的任务之一是能够按需启动视频播放器——在本例中为 VL
python - 当 python 开始运行时，Raspberry Pi 死机
我在 Mac 上用 python 编写了一个程序，打算在 Raspberry Pi 上运行。它包括一个会变化的背景图片，以及一个开始/停止音乐播放的按钮。该程序使用pygame。在 Mac 上，
node.js - 更新后 NPM 死机 - 找不到模块 (OSX)
刚刚将 npm 小更新到最新版本(我不记得它是什么，因为 npm 不再有效 - 因此问题)但我认为我的更新前安装的版本是5.6.0。但这可能是错误的。无论如何在运行之后...... sudo npm
c - 如果使用 Ctrl+c 关闭客户端，服务器会在 `send` 死机
我不明白为什么这个应用程序在 send 时死掉。这是服务器的代码: #include #include #include #include #include #include #defin
amazon-web-services - Jupyter 笔记本内核在一段时间后断开连接/死机，无法重新连接到亚马逊 EC2 实例并完成(当前正在运行)操作。
当我通过 Mobaxterm 连接到 EC2 实例时，一段时间后我的 jupyter notebook 内核失去连接。并且一些非常耗时的操作/(当前正在运行的任务)需要一次又一次地重新执行并且永无止

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python程序运行几天就死机