Functions, namespace, memory management - Revision history

WikiSysop: /* Subjects covered */

2026-03-16T11:10:11Z

Subjects covered

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	* Short about functions		* Short about functions
	* Namespace in Python		* Namespace in Python
	* ~~Memory management~~		* Function decorators

	== Exercises to be handed in ==		== Exercises to be handed in ==

WikiSysop: /* Required course material for the lesson */

2026-03-16T11:09:53Z

Required course material for the lesson

← Older revision		Revision as of 13:09, 16 March 2026
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	Powerpoint: [https://teaching.healthtech.dtu.dk/material/22118/22118_05-Functions.ppt Functions] - this will be short as it is a reminder.<br>		Powerpoint: [https://teaching.healthtech.dtu.dk/material/22118/22118_05-Functions.ppt Functions] - this will be short as it is a reminder.<br>
	Powerpoint: [https://teaching.healthtech.dtu.dk/material/22118/22118_05-Namespace.ppt Namespace].<br>		Powerpoint: [https://teaching.healthtech.dtu.dk/material/22118/22118_05-Namespace.ppt Namespace].<br>
	Powerpoint: [https://teaching.healthtech.dtu.dk/material/22118/~~22118_05~~-~~MemoryManagement~~.ppt ~~Memory management~~].<br>		Powerpoint: [https://teaching.healthtech.dtu.dk/material/22118/22118_07-Decorators.ppt Decorators]<br>
	Video: [https://panopto.dtu.dk/Panopto/Pages/Viewer.aspx?id=f509116f-48e5-445b-bf6e-af27012ba23f Functions in Python]<br>		Video: [https://panopto.dtu.dk/Panopto/Pages/Viewer.aspx?id=f509116f-48e5-445b-bf6e-af27012ba23f Functions in Python]<br>
	Video: [https://panopto.dtu.dk/Panopto/Pages/Viewer.aspx?id=21e9d4d0-2ba5-465c-9939-af27012b7a7e Examples and identifying data types]<br>		Video: [https://panopto.dtu.dk/Panopto/Pages/Viewer.aspx?id=21e9d4d0-2ba5-465c-9939-af27012b7a7e Examples and identifying data types]<br>

WikiSysop: /* Exercises to be handed in */

2026-03-03T17:34:13Z

Exercises to be handed in

← Older revision		Revision as of 19:34, 3 March 2026
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	# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>		# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>
	# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>		# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>
	# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is ~~404~~ in ''employee-data.csv''<br><br>		# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 403 in ''employee-data.csv''<br><br>

	Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is no headline strip. Also, I have uploaded an new version of the employee-data.csv file, as there were some charset coding errors in it.		Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is no headline strip. Also, I have uploaded an new version of the employee-data.csv file, as there were some charset coding errors in it.

	== Exercises for extra practice ==		== Exercises for extra practice ==

WikiSysop: /* Exercises to be handed in */

2026-03-03T17:32:02Z

Exercises to be handed in

← Older revision		Revision as of 19:32, 3 March 2026
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	# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>		# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>

	Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is no headline strip.		Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is no headline strip. Also, I have uploaded an new version of the employee-data.csv file, as there were some charset coding errors in it.

	== Exercises for extra practice ==		== Exercises for extra practice ==

WikiSysop: /* Exercises to be handed in */

2026-03-03T17:03:02Z

Exercises to be handed in

← Older revision		Revision as of 19:03, 3 March 2026
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	# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>		# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>
	# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>		# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>
	# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns ~~not removing any headline~~. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>		# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>

	Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is no headline strip.		Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is no headline strip.

	== Exercises for extra practice ==		== Exercises for extra practice ==

WikiSysop: /* Exercises to be handed in */

2026-03-03T17:02:20Z

Exercises to be handed in

← Older revision		Revision as of 19:02, 3 March 2026
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	# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>		# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>

	Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is ~~not~~ headline strip.		Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is no headline strip.

	== Exercises for extra practice ==		== Exercises for extra practice ==

WikiSysop: /* Exercises to be handed in */

2026-03-03T17:02:02Z

Exercises to be handed in

← Older revision		Revision as of 19:02, 3 March 2026
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	# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>		# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>
	# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>		# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>

			Note that I added a description of the output in exercise 8, and changed the wording of 9, so there is not headline strip.

	== Exercises for extra practice ==		== Exercises for extra practice ==

WikiSysop: /* Exercises to be handed in */

2026-03-03T17:00:24Z

Exercises to be handed in

← Older revision		Revision as of 19:00, 3 March 2026
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	# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>		# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>
	# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>		# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>
	# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order~~, but stripped of the headline~~. If you use the -n option it will display the named columns in the list in the given order ~~- no headline strip~~. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>		# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order. If you use the -n option it will display the named columns in the list in the given order. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>

	== Exercises for extra practice ==		== Exercises for extra practice ==

WikiSysop: /* Exercises to be handed in */

2026-03-03T16:04:19Z

Exercises to be handed in

← Older revision		Revision as of 18:04, 3 March 2026
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	# This is the first part of a larger program - you might want to also read the next 3 exercises to get the full picture. You know that column based files can use different delimiters. The typical example of this is a tab-separated file, where the tab separates the columns. Other classic delimiters can be comma, colon, semicolon or the pipe sign. Now make a function, '''determineDelimiter''', that as argument takes a line, investigates the line and determines if the delimiter is tab, comma, colon, semicolon or pipe sign in the preferred order, and return a single char which is the delimiter. It is required that the delimiter is present at least once in the line. If no delimiter can be found, return None.<br><br>		# This is the first part of a larger program - you might want to also read the next 3 exercises to get the full picture. You know that column based files can use different delimiters. The typical example of this is a tab-separated file, where the tab separates the columns. Other classic delimiters can be comma, colon, semicolon or the pipe sign. Now make a function, '''determineDelimiter''', that as argument takes a line, investigates the line and determines if the delimiter is tab, comma, colon, semicolon or pipe sign in the preferred order, and return a single char which is the delimiter. It is required that the delimiter is present at least once in the line. If no delimiter can be found, return None.<br><br>
	# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>		# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>
	# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c-: positiveIntegerList, '-n': nameList}<br><br>		# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c': positiveIntegerList, '-n': nameList}<br><br>
	# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order, but stripped of the headline. If you use the -n option it will display the named columns in the list in the given order - no headline strip. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>		# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order, but stripped of the headline. If you use the -n option it will display the named columns in the list in the given order - no headline strip. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>

	== Exercises for extra practice ==		== Exercises for extra practice ==

WikiSysop: /* Exercises to be handed in */

2026-03-03T16:03:49Z

Exercises to be handed in

← Older revision		Revision as of 18:03, 3 March 2026
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	# This is the first part of a larger program - you might want to also read the next 3 exercises to get the full picture. You know that column based files can use different delimiters. The typical example of this is a tab-separated file, where the tab separates the columns. Other classic delimiters can be comma, colon, semicolon or the pipe sign. Now make a function, '''determineDelimiter''', that as argument takes a line, investigates the line and determines if the delimiter is tab, comma, colon, semicolon or pipe sign in the preferred order, and return a single char which is the delimiter. It is required that the delimiter is present at least once in the line. If no delimiter can be found, return None.<br><br>		# This is the first part of a larger program - you might want to also read the next 3 exercises to get the full picture. You know that column based files can use different delimiters. The typical example of this is a tab-separated file, where the tab separates the columns. Other classic delimiters can be comma, colon, semicolon or the pipe sign. Now make a function, '''determineDelimiter''', that as argument takes a line, investigates the line and determines if the delimiter is tab, comma, colon, semicolon or pipe sign in the preferred order, and return a single char which is the delimiter. It is required that the delimiter is present at least once in the line. If no delimiter can be found, return None.<br><br>
	# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>		# This is the second part. Sometimes column based files uses the first line as an identifying headline where each column gets a name that describes the data in the column. See the ''employee-data.csv'' file as an example. Make a function '''identifyColumn''', that takes three arguments, a delimiter, a headline and a column name and return which column number the column name belongs to. Return None if a column can not be identified.<br><br>
	# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both.<br><br>		# This the the third part. You learned about input from command line and options last week. Now make a function '''parseCommand''' that analyzes the command line for input. Specifically the function should parse a command line that look like this:<br>'''someprog.py [-c <positiveIntegerList>] [-n <nameList>] <filename>'''<br> The two lists are comma-separated with no spaces. It must return a (possibly empty) list of numbers and a (possibly empty) list of names and a file name. The two options are mutually exclusive, which means it is an error to use both. The function should return a dict with this content {'file':filename, '-c-: positiveIntegerList, '-n': nameList}<br><br>
	# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order, but stripped of the headline. If you use the -n option it will display the named columns in the list in the given order - no headline strip. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>		# This is the fourth and final part. Use your 3 functions to make a program '''namedcut.py''', that works a bit like the Unix cut command in the sense that it selects the columns to display. The program will use as input the ''employee-data.csv'' file. If you use the -c option, it will display the columns in the list in the given order, but stripped of the headline. If you use the -n option it will display the named columns in the list in the given order - no headline strip. No matter the original delimiter the output should always be tab-separated. If a column based file is missing a headline then using the -n option is an error. Note that you would benefit from making a '''usage''' function for easy error handling. If neither option -c nor option -n are used, then the program displays all columns not removing any headline. This effectively means you can use the program to change the delimiter from comma/colon/semicolon to tab. If you have trouble using the functions in your program, think about the tasks/steps that are required to successfully make the program. Also, test your program on the ''ex1.dat'' file as the program is (should be) designed to work on that too. The number of Asians in the Ethnicity column is 404 in ''employee-data.csv''<br><br>

	== Exercises for extra practice ==		== Exercises for extra practice ==