attempting to replace open() with a pandas subset, but I am given an __exit__ error?












3















I am trying to work with pylabels to create nametags for an upcoming event. In one section of the code, there is this tid-bit:



with open(os.path.join(base_path, "names.txt")) as names:

    sheet.add_labels(name.strip() for name in names)


where sheet = labels.Sheet(specs, write_name, border=True). So essentially, this will load each line of "names.txt" and call the function 'write_name', using specifications in 'specs', and add each name to unique labels. I'm attempting to change this code to the following:



with text_file[["Name"]] as names:

    sheet.add_labels(name.strip() for name in names)


But I get this error:



Traceback (most recent call last):

  File "sticker.V.7.py", line 173, in <module>

    with text_file[["Name"]] as names:

AttributeError: __exit__


Can anyone help me understand what exit means in this context? I do not understand from other submissions.



I am hoping to add this subsetting aspect so that I can add further details to the nametags.



I am using Python3.5






python python-3.x pandas contextmanager







share|improve this question

























  • What is text_file and why [["Name"]], obviously it is not something exitable and thus cannot be used with with.

    – MatrixTai
    Nov 15 '18 at 4:05













  • text_file is a dataframe made through pd.read_csv. [['Name']] is a column of the text_file dataframe. as text_file isn't a function, it should be exitable

    – agenttiny
    Nov 15 '18 at 4:34
















3















I am trying to work with pylabels to create nametags for an upcoming event. In one section of the code, there is this tid-bit:



with open(os.path.join(base_path, "names.txt")) as names:

    sheet.add_labels(name.strip() for name in names)


where sheet = labels.Sheet(specs, write_name, border=True). So essentially, this will load each line of "names.txt" and call the function 'write_name', using specifications in 'specs', and add each name to unique labels. I'm attempting to change this code to the following:



with text_file[["Name"]] as names:

    sheet.add_labels(name.strip() for name in names)


But I get this error:



Traceback (most recent call last):

  File "sticker.V.7.py", line 173, in <module>

    with text_file[["Name"]] as names:

AttributeError: __exit__


Can anyone help me understand what exit means in this context? I do not understand from other submissions.



I am hoping to add this subsetting aspect so that I can add further details to the nametags.



I am using Python3.5






python python-3.x pandas contextmanager







share|improve this question

























  • What is text_file and why [["Name"]], obviously it is not something exitable and thus cannot be used with with.

    – MatrixTai
    Nov 15 '18 at 4:05













  • text_file is a dataframe made through pd.read_csv. [['Name']] is a column of the text_file dataframe. as text_file isn't a function, it should be exitable

    – agenttiny
    Nov 15 '18 at 4:34














3












3








3








I am trying to work with pylabels to create nametags for an upcoming event. In one section of the code, there is this tid-bit:



with open(os.path.join(base_path, "names.txt")) as names:

    sheet.add_labels(name.strip() for name in names)


where sheet = labels.Sheet(specs, write_name, border=True). So essentially, this will load each line of "names.txt" and call the function 'write_name', using specifications in 'specs', and add each name to unique labels. I'm attempting to change this code to the following:



with text_file[["Name"]] as names:

    sheet.add_labels(name.strip() for name in names)


But I get this error:



Traceback (most recent call last):

  File "sticker.V.7.py", line 173, in <module>

    with text_file[["Name"]] as names:

AttributeError: __exit__


Can anyone help me understand what exit means in this context? I do not understand from other submissions.



I am hoping to add this subsetting aspect so that I can add further details to the nametags.



I am using Python3.5






python python-3.x pandas contextmanager







share|improve this question
















I am trying to work with pylabels to create nametags for an upcoming event. In one section of the code, there is this tid-bit:



with open(os.path.join(base_path, "names.txt")) as names:

    sheet.add_labels(name.strip() for name in names)


where sheet = labels.Sheet(specs, write_name, border=True). So essentially, this will load each line of "names.txt" and call the function 'write_name', using specifications in 'specs', and add each name to unique labels. I'm attempting to change this code to the following:



with text_file[["Name"]] as names:

    sheet.add_labels(name.strip() for name in names)


But I get this error:



Traceback (most recent call last):

  File "sticker.V.7.py", line 173, in <module>

    with text_file[["Name"]] as names:

AttributeError: __exit__


Can anyone help me understand what exit means in this context? I do not understand from other submissions.



I am hoping to add this subsetting aspect so that I can add further details to the nametags.



I am using Python3.5






python python-3.x pandas contextmanager




python python-3.x pandas contextmanager






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Nov 16 '18 at 9:20









cricket_007

82.5k1143111




82.5k1143111










asked Nov 15 '18 at 4:01









agenttinyagenttiny

184




184













  • What is text_file and why [["Name"]], obviously it is not something exitable and thus cannot be used with with.

    – MatrixTai
    Nov 15 '18 at 4:05













  • text_file is a dataframe made through pd.read_csv. [['Name']] is a column of the text_file dataframe. as text_file isn't a function, it should be exitable

    – agenttiny
    Nov 15 '18 at 4:34



















  • What is text_file and why [["Name"]], obviously it is not something exitable and thus cannot be used with with.

    – MatrixTai
    Nov 15 '18 at 4:05













  • text_file is a dataframe made through pd.read_csv. [['Name']] is a column of the text_file dataframe. as text_file isn't a function, it should be exitable

    – agenttiny
    Nov 15 '18 at 4:34

















What is text_file and why [["Name"]], obviously it is not something exitable and thus cannot be used with with.

– MatrixTai
Nov 15 '18 at 4:05







What is text_file and why [["Name"]], obviously it is not something exitable and thus cannot be used with with.

– MatrixTai
Nov 15 '18 at 4:05















text_file is a dataframe made through pd.read_csv. [['Name']] is a column of the text_file dataframe. as text_file isn't a function, it should be exitable

– agenttiny
Nov 15 '18 at 4:34





text_file is a dataframe made through pd.read_csv. [['Name']] is a column of the text_file dataframe. as text_file isn't a function, it should be exitable

– agenttiny
Nov 15 '18 at 4:34












1 Answer
1






active

oldest

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2















Can anyone help me understand what __exit__ means in this context? I do not understand from other submissions. ... As text_file isn't a function, it should be exitable.




When you use with statement context managers, that object must define these two methods:




  • __enter__

  • __exit__


Whatever text_file[["Name"]] is (a Pandas DataFrame, it seems), it doesn't implement either of these methods. As indicated by the traceback, it doesn't define __enter__ at all, so execution stops right there and raises an exception.



I don't see a need to use a DataFrame as a context manager. A typical use-case is when you want to ensure that something happens at the end of the with block, namely, closing a file stream. (Like a try/finally block--you want to make sure __exit__ gets called unconditionally.) With a Pandas DataFrame, I'm not sure if there is any analogy that would necessitate have those two dunder methods.






share|improve this answer
























  • Thanks for the advice! ill try another method that includes an exit call.

    – agenttiny
    Nov 15 '18 at 8:05











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2















Can anyone help me understand what __exit__ means in this context? I do not understand from other submissions. ... As text_file isn't a function, it should be exitable.




When you use with statement context managers, that object must define these two methods:




  • __enter__

  • __exit__


Whatever text_file[["Name"]] is (a Pandas DataFrame, it seems), it doesn't implement either of these methods. As indicated by the traceback, it doesn't define __enter__ at all, so execution stops right there and raises an exception.



I don't see a need to use a DataFrame as a context manager. A typical use-case is when you want to ensure that something happens at the end of the with block, namely, closing a file stream. (Like a try/finally block--you want to make sure __exit__ gets called unconditionally.) With a Pandas DataFrame, I'm not sure if there is any analogy that would necessitate have those two dunder methods.






share|improve this answer
























  • Thanks for the advice! ill try another method that includes an exit call.

    – agenttiny
    Nov 15 '18 at 8:05
















2















Can anyone help me understand what __exit__ means in this context? I do not understand from other submissions. ... As text_file isn't a function, it should be exitable.




When you use with statement context managers, that object must define these two methods:




  • __enter__

  • __exit__


Whatever text_file[["Name"]] is (a Pandas DataFrame, it seems), it doesn't implement either of these methods. As indicated by the traceback, it doesn't define __enter__ at all, so execution stops right there and raises an exception.



I don't see a need to use a DataFrame as a context manager. A typical use-case is when you want to ensure that something happens at the end of the with block, namely, closing a file stream. (Like a try/finally block--you want to make sure __exit__ gets called unconditionally.) With a Pandas DataFrame, I'm not sure if there is any analogy that would necessitate have those two dunder methods.






share|improve this answer
























  • Thanks for the advice! ill try another method that includes an exit call.

    – agenttiny
    Nov 15 '18 at 8:05














2












2








2








Can anyone help me understand what __exit__ means in this context? I do not understand from other submissions. ... As text_file isn't a function, it should be exitable.




When you use with statement context managers, that object must define these two methods:




  • __enter__

  • __exit__


Whatever text_file[["Name"]] is (a Pandas DataFrame, it seems), it doesn't implement either of these methods. As indicated by the traceback, it doesn't define __enter__ at all, so execution stops right there and raises an exception.



I don't see a need to use a DataFrame as a context manager. A typical use-case is when you want to ensure that something happens at the end of the with block, namely, closing a file stream. (Like a try/finally block--you want to make sure __exit__ gets called unconditionally.) With a Pandas DataFrame, I'm not sure if there is any analogy that would necessitate have those two dunder methods.






share|improve this answer














Can anyone help me understand what __exit__ means in this context? I do not understand from other submissions. ... As text_file isn't a function, it should be exitable.




When you use with statement context managers, that object must define these two methods:




  • __enter__

  • __exit__


Whatever text_file[["Name"]] is (a Pandas DataFrame, it seems), it doesn't implement either of these methods. As indicated by the traceback, it doesn't define __enter__ at all, so execution stops right there and raises an exception.



I don't see a need to use a DataFrame as a context manager. A typical use-case is when you want to ensure that something happens at the end of the with block, namely, closing a file stream. (Like a try/finally block--you want to make sure __exit__ gets called unconditionally.) With a Pandas DataFrame, I'm not sure if there is any analogy that would necessitate have those two dunder methods.







share|improve this answer












share|improve this answer



share|improve this answer










answered Nov 15 '18 at 4:32









Brad SolomonBrad Solomon

13.7k83486




13.7k83486













  • Thanks for the advice! ill try another method that includes an exit call.

    – agenttiny
    Nov 15 '18 at 8:05



















  • Thanks for the advice! ill try another method that includes an exit call.

    – agenttiny
    Nov 15 '18 at 8:05

















Thanks for the advice! ill try another method that includes an exit call.

– agenttiny
Nov 15 '18 at 8:05





Thanks for the advice! ill try another method that includes an exit call.

– agenttiny
Nov 15 '18 at 8:05




















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