Pythonhome作业

Python作业通常是指在学习Python编程语言时，老师或者教育机构布置的练习或任务。Python作业的内容可以涵盖各个方面，包括基础语法、数据类型、条件语句、循环语句、函数、模块、文件操作等等。

在完成Python作业时，你可能需要使用Python的编程环境（如Anaconda、PyCharm等）来编写代码，并且需要理解作业要求，根据要求编写相应的代码逻辑。通常，作业会提供一些具体的问题或者任务，你需要根据问题的要求编写相应的代码来解决问题。

为了更好地帮助你，可以提供一些具体的Python作业问题或者任务要求，我将尽力给出相应的解答和指导。

相关问题

hadoop maper reducer python

Hadoop MapReduce是一个分布式计算框架，可以用于处理大规模数据集。Mapper和Reducer是MapReduce的两个主要组件。Python是一种流行的编程语言，也可以用于编写Hadoop MapReduce作业。

在Python中编写MapReduce作业，您可以使用Hadoop Streaming API。该API允许您使用任何可执行文件作为Mapper和Reducer。以下是一个使用Python编写Mapper和Reducer的示例：

Mapper:

#!/usr/bin/env python

import sys

# input comes from STDIN (standard input)
for line in sys.stdin:
    # remove leading and trailing whitespace
    line = line.strip()
    # split the line into words
    words = line.split()
    # increase counters
    for word in words:
        # write the results to STDOUT (standard output);
        # what we output here will be the input for the
        # Reduce step, i.e. the input for reducer.py
        #
        # tab-delimited; the trivial word count is 1
        print '%s\t%s' % (word, 1)

Reducer:

#!/usr/bin/env python

from operator import itemgetter
import sys

current_word = None
current_count = 0
word = None

# input comes from STDIN
for line in sys.stdin:
    # remove leading and trailing whitespace
    line = line.strip()

    # parse the input we got from mapper.py
    word, count = line.split('\t', 1)

    # convert count (currently a string) to int
    try:
        count = int(count)
    except ValueError:
        # count was not a number, so silently
        # ignore/discard this line
        continue

    # this IF-switch only works because Hadoop sorts map output
    # by key (here: word) before it is passed to the reducer
    if current_word == word:
        current_count += count
    else:
        if current_word:
            # write result to STDOUT
            print '%s\t%s' % (current_word, current_count)
        current_count = count
        current_word = word

# do not forget to output the last word if needed!
if current_word == word:
    print '%s\t%s' % (current_word, current_count)

这些脚本可以使用Hadoop Streaming API提交为MapReduce作业，如下所示：

$HADOOP_HOME/bin/hadoop jar $HADOOP_HOME/share/hadoop/tools/lib/hadoop-streaming-2.7.3.jar \
-input input_file \
-output output_directory \
-mapper mapper.py \
-reducer reducer.py \
-file mapper.py \
-file reducer.py

其中，input_file是输入文件的路径，output_directory是输出目录的路径，mapper.py和reducer.py是上述Python脚本的文件名。

python./../

在Python中，"./"表示当前文件所在的目录，"../"表示当前文件的上一层目录。这些路径通常用于指定文件的位置。举例来说，假设当前文件的路径是`/home/user/folder/1.py`，那么使用"./1.txt"或者"../folder/1.txt"就可以打开同级目录下的1.txt文件。而使用"/1.txt"则表示打开根目录下的1.txt文件。同时，使用`os.getcwd()`函数可以获取当前文件的工作路径。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
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