blocks|key|1914987|text|退出代码137表示您的进程已被(信号9)+SIGKILL终止。在手动停止它的情况下-这就是你的答案。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1914988|如果你没有手动停止脚本，仍然得到这个错误代码，那么这个脚本就会被你的操作系统杀死。在大多数情况下，它是由过多的内存使用引起的。|1914989|entityMap^0|L|7|0|0^^$0|@$1|2|3|4|5|6|7|J|8|@$9|K|A|L|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|M|8|@]|D|@]|E|$]]|$1|H|3|-4|5|6|7|N|8|@]|D|@]|E|$]]]|I|$]]

Exit code 137 means that your process was killed by (signal 9) <code>SIGKILL</code> . In the case you manually stopped it - there's your answer. 

If you didn't manually stop the script and still got this error code, then the script was killed by your OS. In most of the cases, it is caused by excessive memory usage.

blocks|key|4025775|text|{根据我的经验}|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4025776|这是因为的内存问题。当我尝试使用sklearn+fit训练具有完整数据集的ml模型时，它突然中断并给出，而对于小数据，它工作得很好。|offset|length|style|BOLD|4025777|进程结束，退出代码为137+(被信号9:+SIGKILL中断)有趣的是，这也没有在异常块中捕获|4025778|entityMap^0|0|5|1P|0|0|1B|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|M|8|@$D|N|E|O|F|G]]|9|@]|A|$]]|$1|H|3|I|5|6|7|P|8|@$D|Q|E|R|F|G]]|9|@]|A|$]]|$1|J|3|-4|5|6|7|S|8|@]|9|@]|A|$]]]|K|$]]

{In my experience}

this is because of Memory issue. 
When I try to train ml model using sklearn fit with full data set , it abruptly breaks and gives whereas with small data it works fine.

Process finished with exit code 137 (interrupted by signal 9: SIGKILL)
Interestingly this is not caught in Exception block either

blocks|key|5444055|text|如果您使用的是Ubuntu，请增加交换内存。看起来不错。使用htop查看交换空间的使用情况，当它已满时，它会给出错误137。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5444056|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

If you are in Ubuntu, increase the SWAP memory. It will work. Use htop to see SWAP usage, when it is full, it will give error 137.

blocks|key|1574983|text|我也犯了同样的错误。在我的例子中，它与过度的内存使用有关。在重置/清除缓存数据后解决，为每个不再使用的变量添加以下代码：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1574984|MyVariableName+=+None|code-block|syntax|javascript|1574985|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

I had the same error. In my case was related to excessive memory usage. Solved after reseting/cleaning my cache data adding the following code for every variable that will not be used anymore : 

<pre><code>MyVariableName = None
</code></pre>

blocks|key|1915026|text|这并不总是内存问题。在我的例子中，使用了subprocess.Popen，它抛出的错误为137，看起来像signalKILL，原因肯定不是内存利用率，因为在运行时它几乎没有使用1%25的内存使用。经过更多的调查，这似乎是一个许可问题。我只需将脚本从/home/ubuntu移到根目录。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1915027|entityMap^0|K|G|3E|C|0^^$0|@$1|2|3|4|5|6|7|H|8|@$9|I|A|J|B|C]|$9|K|A|L|B|C]]|D|@]|E|$]]|$1|F|3|-4|5|6|7|M|8|@]|D|@]|E|$]]]|G|$]]

It's not always a memory issue. In my case <code>subprocess.Popen</code> was utilized and it was throwing the error as 137 which looks like signalKILL and the cause is definitely not the memory utilization, because during the runtime it was hardly using 1% of memory use. This seems to be a permission issue after more investigation. I simply moved the scripts from <code>/home/ubuntu</code> to the root directory.

blocks|key|1915187|text|我最近在M1+Mac+Mini上安装PyCharm时遇到了这个错误。它伴随着一个错误，说我的SDK在编译项目时是无效的。原来这是因为我的Python解释器指向了一个奇怪的目录，我不是100%25知道这是怎么发生的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1915188|我进入了首选项>项目:你的项目>+Python解释器SDK，并从下拉列表中选择了一个有效的(在我的例子中是Python3.8)。您将知道该包是有效的，因为它将使用包填充下面的包列表。|offset|length|style|BOLD|1915189|同样，不确定它是如何在安装时发生的，但这解决了它。|1915190|entityMap^0|0|4|15|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|M|8|@$D|N|E|O|F|G]]|9|@]|A|$]]|$1|H|3|I|5|6|7|P|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|K|$]]

I've recently run into this error installing PyCharm on an M1 Mac Mini. It was accompanied by an error that said my SDK was invalid upon compilation of a project. It turns out this was due to my Python Interpreter being pointed at a strange directory, I'm not 100% how this happened.
I went to Preferences &gt; Project:yourProject &gt; Python Interpreter and selected a valid SDK from the drop-down (in my case Python 3.8). You'll know the package is valid because it will populate the package list below with packages.
Again, not sure how it happened on install, but this solved it.

blocks|key|5444028|text|在我的例子中，我的RAM用完了，不管它是真实的还是虚拟的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|5444029|将数据拆分成小块或扩展虚拟内存。|5444030|我选择后者。|5444031|在我的ubuntu20.04tls上跟随scipts的工作。|5444032|#+disable+the+use+of+swap
sudo+swapoff+-a

#+create+the+SWAP+file.+Make+sure+you+have+enough+space+on+the+hard+disk.
#+here+is+my+size,+the+total+size+is+bs*count+B
sudo+dd+if=/dev/zero+of=/swapfile+bs=1024+count=136314880+status=progress
#+output:
#+139458259968+bytes+(139+GB,+130+GiB)+copied,+472+s,+295+MB/s
#+136314880%2B0+records+in
#+136314880%2B0+records+out
#+139586437120+bytes+(140+GB,+130+GiB)+copied,+472.372+s,+296+MB/s

#+Mark+the+file+as+SWAP+space:
sudo+mkswap+/swapfile
#+output:
#+Setting+up+swapspace+version+1,+size+=+130+GiB+(139586433024+bytes)
#+no+label,+UUID=25a565d9-d19c-4913-87a5-f02750ab625d

#+enable+the+SWAP.
sudo+swapon+/swapfile

#+check+if+SWAP+is+created
sudo+swapon+--show
#+output:
#+NAME++++++TYPE+SIZE+USED+PRIO
#+/swapfile+file+130G+++0B+++-2

#+Once+everything+is+set,+you+must+set+the+SWAP+file+as+permanent,+else+you+will+lose+the+SWAP+after+reboot.+Run+this+command:
echo+'/swapfile+none+swap+sw+0+0'+%7C+sudo+tee+-a+/etc/fstab|code-block|syntax|javascript|5444033|在你运行你的进程之后，内存会增长。|5444034|下面是我的：|5444035|​|5444036|📷|atomic|offset|length|5444037|5444038|祝好运!|5444039|reference+1，reference+2|5444040|entityMap|0|IMAGE|mutability|IMMUTABLE|imageUrl|https://ask.qcloudimg.com/http-save/yehe-900000/6f1cfbd74f5e6b9603d5027c9d3d0c47.png|imageAlt|1|LINK|MUTABLE|url|https://askubuntu.com/questions/920595/fallocate-fallocate-failed-text-file-busy-in-ubuntu-17-04|2|https://www.cnblogs.com/exciting/p/13668841.html^0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|B|1|C|B|2|0^^$0|@$1|2|3|4|5|6|7|1I|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|1J|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|1K|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|1L|8|@]|9|@]|A|$]]|$1|H|3|I|5|J|7|1M|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|1N|8|@]|9|@]|A|$]]|$1|O|3|P|5|6|7|1O|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|1P|8|@]|9|@]|A|$]]|$1|S|3|T|5|U|7|1Q|8|@]|9|@$V|1R|W|1S|1|1T]]|A|$]]|$1|X|3|R|5|6|7|1U|8|@]|9|@]|A|$]]|$1|Y|3|Z|5|6|7|1V|8|@]|9|@]|A|$]]|$1|10|3|11|5|6|7|1W|8|@]|9|@$V|1X|W|1Y|1|1Z]|$V|20|W|21|1|22]]|A|$]]|$1|12|3|-4|5|6|7|23|8|@]|9|@]|A|$]]]|13|$14|$5|15|16|17|A|$18|19|1A|-4]]|1B|$5|1C|16|1D|A|$1E|1F]]|1G|$5|1C|16|1D|A|$1E|1H]]]]

In my case, my RAM ran out, whether it is real or virtual.
Split your data into small pieces or expand your virtual memory.
I choose the latter.
Following scipts works on my ubuntu 20.04 TLS.
<pre class="lang-sh prettyprint-override"><code># disable the use of swap
sudo swapoff -a

# create the SWAP file. Make sure you have enough space on the hard disk.
# here is my size, the total size is bs*count B
sudo dd if=/dev/zero of=/swapfile bs=1024 count=136314880 status=progress
# output:
# 139458259968 bytes (139 GB, 130 GiB) copied, 472 s, 295 MB/s
# 136314880+0 records in
# 136314880+0 records out
# 139586437120 bytes (140 GB, 130 GiB) copied, 472.372 s, 296 MB/s

# Mark the file as SWAP space:
sudo mkswap /swapfile
# output:
# Setting up swapspace version 1, size = 130 GiB (139586433024 bytes)
# no label, UUID=25a565d9-d19c-4913-87a5-f02750ab625d

# enable the SWAP.
sudo swapon /swapfile

# check if SWAP is created
sudo swapon --show
# output:
# NAME TYPE SIZE USED PRIO
# /swapfile file 130G 0B -2

# Once everything is set, you must set the SWAP file as permanent, else you will lose the SWAP after reboot. Run this command:
echo '/swapfile none swap sw 0 0' | sudo tee -a /etc/fstab
</code></pre>
After you run your process, memory will grow.
Here is mine:
<a href="https://i.stack.imgur.com/73KTd.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/73KTd.png" alt="enter image description here" /></a>
Good Luck!
<a href="https://askubuntu.com/questions/920595/fallocate-fallocate-failed-text-file-busy-in-ubuntu-17-04">reference 1</a>，<a href="https://www.cnblogs.com/exciting/p/13668841.html" rel="nofollow noreferrer">reference 2</a>

blocks|key|1579082|text|我的python进程被137错误代码终止，因为我的Docker+for+Windows内存限制设置得太低。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1579083|entityMap^0|0^^$0|@$1|2|3|4|5|6|7|D|8|@]|9|@]|A|$]]|$1|B|3|-4|5|6|7|E|8|@]|9|@]|A|$]]]|C|$]]

My python process get killed with the 137 error code because my Docker for Windows memory limit was set too low.

blocks|key|1575104|text|type|unstyled|depth|inlineStyleRanges|entityRanges|data|1575105|如果其他任何人在mac上安装pycharm时，在执行简单的打印(‘PyCharm’)命令时出现错误代码137，这肯定是因为在创建的新项目中存在解释器的路径。|ordered-list-item|1575106|我认为错误是因为python是通过brew安装的，并且它没有出现在"Python+X.YZ+/Library/Frameworks/Python.framework/Versions/X.YZ/bin/pythonX“path|1575107|Work+and+python+version+using+brew，然后手动安装它。|1575108|Now+it将出现在"Preferences->+->+Gear+symbol+->+add+base+interpreter“下的解释器路径下，指向/+->+/Frameworks/...下的path|1575109|1575110|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|-4|4|5|6|M|7|@]|8|@]|9|$]]|$1|A|3|B|4|C|6|N|7|@]|8|@]|9|$]]|$1|D|3|E|4|C|6|O|7|@]|8|@]|9|$]]|$1|F|3|G|4|C|6|P|7|@]|8|@]|9|$]]|$1|H|3|I|4|C|6|Q|7|@]|8|@]|9|$]]|$1|J|3|-4|4|5|6|R|7|@]|8|@]|9|$]]|$1|K|3|-4|4|5|6|S|7|@]|8|@]|9|$]]]|L|$]]

<ol>
<li>If anyone else were installing pycharm on mac and got the code 137 in PyCharm error while doing a simple print('test') command it most certainly is because of the path to interpreter being present in the new project created.</li>
<li>The error I believe is because of python being installed through brew and it not showing up in the &quot;Python X.YZ /Library/Frameworks/Python.framework/Versions/X.YZ/bin/pythonX&quot; path</li>
<li>Work around uninstall installed python version using brew and then manually install it.</li>
<li>Now it would appear under the interpreter path which is under &quot;Preferences-&gt; Project -&gt; Python Interpreter -&gt; Gear symbol -&gt; add base interpreter&quot; point this to under /Library/Frameworks/.... path</li>
</ol>

blocks|key|4026076|text|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4026077|单击齿轮图标。|ordered-list-item|4026078|然后将诗歌环境设置为Python+3.x。|4026079|单击确定并应用。|4026080|4026081|现在代码可以运行了，不会显示任何错误！|4026082|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|-4|4|5|6|M|7|@]|8|@]|9|$]]|$1|A|3|B|4|C|6|N|7|@]|8|@]|9|$]]|$1|D|3|E|4|C|6|O|7|@]|8|@]|9|$]]|$1|F|3|G|4|C|6|P|7|@]|8|@]|9|$]]|$1|H|3|-4|4|5|6|Q|7|@]|8|@]|9|$]]|$1|I|3|J|4|5|6|R|7|@]|8|@]|9|$]]|$1|K|3|-4|4|5|6|S|7|@]|8|@]|9|$]]]|L|$]]

<ol>
<li>Click on the gear icon.</li>
<li>Then set the Poetry environment to Python 3.x.</li>
<li>Click Ok and Apply.</li>
</ol>
Now the code can run without showing any error!

When I stop the script manually in PyCharm, process finished with exit code 137. But I didn't stop the script. Still got the exit code 137. What's the problem?

Python version is 3.6, process finished when running xgboost.train() method.

Process finished with exit code 137 in PyCharm

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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当我在PyCharm中手动停止脚本时，进程结束，退出代码为137。但我没有停止剧本。仍然有退出代码137。有什么问题吗？Python版本为3.6，运行xgboost.train()方法时进程结束。

问进程已完成，PyCharm中的退出代码为137
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问进程已完成，PyCharm中的退出代码为137EN

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问进程已完成，PyCharm中的退出代码为137
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