關於使用PyCharm遠程調試運行時StanfordCoreNLP報無法找到java的問題解決
最近學習NLP，在PyCharm配置好了遠程調試運行，在使用stanfordcorenlp的時候報錯FileNotFoundError: [Errno 2] No such file or directory: 'java': 'java'，原本以爲可以和上一篇文章《關於pyhanlp報FileNotFoundError: [Errno 2] No such file or directory: '/usr/lib/jvm'錯誤的解決》一樣，添加環境變量即可，但無濟於事。網上也沒有查到類似的錯誤，看來是我jdk的安裝比較奇葩？
報錯詳情：
ssh://yl@IP:PORT/home/USER/anaconda3/envs/tensorflow/bin/python -u /home/yl/python/nlp/learing/test01.py
Traceback (most recent call last):
File "/home/yl/python/nlp/learing/test01.py", line 7, in <module>
snlp = StanfordCoreNLP(os.sep + 'opt' + os.sep + "nlp" + os.sep + 'stanford-corenlp', lang='zh')
File "/home/yl/anaconda3/envs/tensorflow/lib/python3.7/site-packages/stanfordcorenlp/corenlp.py", line 46, in __init__
if not subprocess.call(['java', '-version'], stdout=subprocess.PIPE, stderr=subprocess.STDOUT) == 0:
File "/home/yl/anaconda3/envs/tensorflow/lib/python3.7/subprocess.py", line 323, in call
with Popen(*popenargs, **kwargs) as p:
File "/home/yl/anaconda3/envs/tensorflow/lib/python3.7/subprocess.py", line 774, in __init__
restore_signals, start_new_session)
File "/home/yl/anaconda3/envs/tensorflow/lib/python3.7/subprocess.py", line 1522, in _execute_child
raise child_exception_type(errno_num, err_msg, err_filename)
FileNotFoundError: [Errno 2] No such file or directory: 'java': 'java'
原因分析：
老辦法，網上找不到答案，慢慢看源代碼找原因吧。打開文件/home/yl/anaconda3/envs/tensorflow/lib/python3.7/subprocess.py找到_execute_child()這個函數，並在1522行附近有如下代碼
if issubclass(child_exception_type, OSError) and hex_errno:
errno_num = int(hex_errno, 16)
child_exec_never_called = (err_msg == "noexec")
if child_exec_never_called:
err_msg = ""
# The error must be from chdir(cwd).
err_filename = cwd
else:
err_filename = orig_executable
if errno_num != 0:
err_msg = os.strerror(errno_num)
if errno_num == errno.ENOENT:
err_msg += ': ' + repr(err_filename)
raise child_exception_type(errno_num, err_msg, err_filename)
可以看到當errno_no不爲0的時候報錯，依次向上查看，可以看到錯誤來源 errno_no -> hex_errno -> errpipe_data -> errpipe_read -> self.pid = _posixsubprocess.fork_exec()執行時產生（1452行左右），從該函數輸入參數名來看，應該是executable_list和env_list影響了是否能找到java位置。於是在executable_list生成附近print了查看其變化情況，如下（1436行至1442行）
executable = os.fsencode(executable)
print('executable: ', executable) # 打印 從上面傳入的初始值
if os.path.dirname(executable):
executable_list = (executable,)
else:
# This matches the behavior of os._execvpe().
print('env: ', env) # 打印 env
print('get_exec_path of env: ', os.get_exec_path(env)) # 打印 從env獲取系統可執行路徑 應該是 PATH 變量
executable_list = tuple(
os.path.join(os.fsencode(dir), executable)
for dir in os.get_exec_path(env))
print('executable_list: ', executable_list) # 打印 最終的路徑結果
PyCharm中導入stanfordcorenlp執行StanfordCoreNLP時輸出如下：
executable: b'java'
env: None
get_exec_path of env: ['/usr/local/sbin', '/usr/local/bin', '/usr/sbin', '/usr/bin', '/sbin', '/bin', '/usr/games', '/usr/local/games']
executable_list: (b'/usr/local/sbin/java', b'/usr/local/bin/java', b'/usr/sbin/java', b'/usr/bin/java', b'/sbin/java', b'/bin/java', b'/usr/games/java', b'/usr/local/games/java')
Traceback (most recent call last):
在linux終端中運行輸出如下：
yl@ylhome [20:24:07] ~$ /home/yl/anaconda3/envs/tensorflow/bin/python
Python 3.7.3 (default, Mar 27 2019, 22:11:17)
[GCC 7.3.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import os
>>> from stanfordcorenlp import StanfordCoreNLP
>>> stanford_nlp = StanfordCoreNLP(os.sep + '/opt' + os.sep + "/nlp" + os.sep + '/stanford-corenlp', lang='zh')
executable: b'java'
env: None
get_exec_path of env: ['/home/yl/.local/bin', '/home/yl/bin', '/usr/local/cuda/bin', '/home/yl/anaconda3/bin', '/usr/local/java/latest/bin', '/usr/local/cuda/bin', '/usr/local/sbin', '/usr/local/bin', '/usr/sbin', '/usr/bin', '/sbin', '/bin', '/usr/games', '/usr/local/games', '/snap/bin']
executable_list: (b'/home/yl/.local/bin/java', b'/home/yl/bin/java', b'/usr/local/cuda/bin/java', b'/home/yl/anaconda3/bin/java', b'/usr/local/java/latest/bin/java', b'/usr/local/cuda/bin/java', b'/usr/local/sbin/java', b'/usr/local/bin/java', b'/usr/sbin/java', b'/usr/bin/java', b'/sbin/java', b'/bin/java', b'/usr/games/java', b'/usr/local/games/java', b'/snap/bin/java')
executable: b'/bin/sh'
>>>
命令行中讀取到的PATH的值是正確的，PyCharm遠程調用時無法獲取用戶自行添加的PATH。那麼，一個便捷的方式是將java鏈接到PyCharm調用時能讀取到的位置，如/usr/local/bin中。
具體內在的原因，由於時間匆忙就不予深究了，暫時解決問題以後再來回顧。
解決辦法：
將java命令鏈接到系統默認的可執行目錄，如/usr/bin或/usr/local/bin等地方。我的配置：
sudo ln -sf /usr/local/java/latest/bin/java /usr/local/bin/java
運行效果：
然後在PyCharm中運行stanfordcorenlp包，可以正常運行
from stanfordcorenlp import StanfordCoreNLP
import os
snlp = StanfordCoreNLP(os.sep + 'opt' + os.sep + "nlp" + os.sep + 'stanford-corenlp', lang='zh')
str = '今天晚上吃火鍋啊！'
print(snlp.ner(str))
結果：
