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Given the following text description, write Python code to implement the functionality described below step by step
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Description:
 Language Detection
Polyglot depends on pycld2 library which in turn depends on cld2 library for detecting language(s) used in plain text.
Step2:  Example
Step4:  Mixed Text
Step5:  If the text contains snippets from different languages, the detector is able to find the most probable langauges used in the text.
For each language, we can query the model confidence level
Step6:  To take a closer look, we can inspect the text line by line, notice that the confidence in the detection went down for the first line
Step7:  Best Effort Strategy
Sometimes, there is no enough text to make a decision, like detecting a language from one word.
This forces the detector to switch to a best effort strategy, a warning will be thrown and the attribute reliable will be set to False.
Step8:  In case, that the detection is not reliable even when we are using the best effort strategy, an exception UnknownLanguage will be thrown.
Step9:  Such an exception may not be desirable especially for trivial cases like characters that could belong to so many languages.
In this case, we can silence the exceptions by passing setting quiet to True
Step10:  Command Line
Step11:  The subcommand detect tries to identify the language code for each line in a text file.
This could be convieniet if each line represents a document or a sentence that could have been generated by a tokenizer
Step12:  Supported Languages
cld2 can detect up to 165 languages.
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Python Code:
from polyglot.detect import Detector
Explanation: Language Detection
Polyglot depends on pycld2 library which in turn depends on cld2 library for detecting language(s) used in plain text.
End of explanation
arabic_text = u
أفاد مصدر امني في قيادة عمليات صلاح الدين في العراق بأن " القوات الامنية تتوقف لليوم
الثالث على التوالي عن التقدم الى داخل مدينة تكريت بسبب
انتشار قناصي التنظيم الذي يطلق على نفسه اسم "الدولة الاسلامية" والعبوات الناسفة
والمنازل المفخخة والانتحاريين، فضلا عن ان القوات الامنية تنتظر وصول تعزيزات اضافية ".
detector = Detector(arabic_text)
print(detector.language)
Explanation: Example
End of explanation
mixed_text = u
China (simplified Chinese: 中国; traditional Chinese: 中國),
officially the People's Republic of China (PRC), is a sovereign state located in East Asia.
Explanation: Mixed Text
End of explanation
for language in Detector(mixed_text).languages:
  print(language)
Explanation: If the text contains snippets from different languages, the detector is able to find the most probable langauges used in the text.
For each language, we can query the model confidence level:
End of explanation
for line in mixed_text.strip().splitlines():
  print(line + u"\n")
  for language in Detector(line).languages:
    print(language)
  print("\n")
Explanation: To take a closer look, we can inspect the text line by line, notice that the confidence in the detection went down for the first line
End of explanation
detector = Detector("pizza")
print(detector)
Explanation: Best Effort Strategy
Sometimes, there is no enough text to make a decision, like detecting a language from one word.
This forces the detector to switch to a best effort strategy, a warning will be thrown and the attribute reliable will be set to False.
End of explanation
print(Detector("4"))
Explanation: In case, that the detection is not reliable even when we are using the best effort strategy, an exception UnknownLanguage will be thrown.
End of explanation
print(Detector("4", quiet=True))
Explanation: Such an exception may not be desirable especially for trivial cases like characters that could belong to so many languages.
In this case, we can silence the exceptions by passing setting quiet to True
End of explanation
!polyglot detect --help
Explanation: Command Line
End of explanation
!polyglot detect --input testdata/cricket.txt
Explanation: The subcommand detect tries to identify the language code for each line in a text file.
This could be convieniet if each line represents a document or a sentence that could have been generated by a tokenizer
End of explanation
from polyglot.utils import pretty_list
print(pretty_list(Detector.supported_languages()))
Explanation: Supported Languages
cld2 can detect up to 165 languages.
End of explanation
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