Category: Python Answers

Sometimes, we want to have Django serve downloadable files with Python.

In this article, we’ll look at how to have Django serve downloadable files with Python.

How to have Django serve downloadable files with Python?

To have Django serve downloadable files with Python, we can return a file download response in our view.

For instance, we write

from django.utils.encoding import smart_str

response = HttpResponse(content_type='application/force-download') 
response['Content-Disposition'] = 'attachment; filename=%s' % smart_str(file_name)
response['X-Sendfile'] = smart_str(path_to_file)
return response

to create a HttpResponse object that has the content_type argument set to 'application/force-download'.

Then we set the Content-Disposition response header to 'attachment; filename=%s' % smart_str(file_name).

Next, we set the X-Sendfile response header to smart_str(path_to_file).

Now the response should download the file at path_to_file.

And then we return the response.

Conclusion

To have Django serve downloadable files with Python, we can return a file download response in our view.

Sometimes, we want to do string formatting in Python

In this article, we’ll look at how to do string formatting in Python.

How to do string formatting in Python?

To do string formatting in Python, we can use the string format method.

For instance, we write

s = "[{0}, {1}, {2}]".format(1, 2, 3)

to call format with 3 values to interpolate them into the placeholders, which are the numbers surrounded with braces.

Conclusion

To do string formatting in Python, we can use the string format method.

Sometimes, we want to copy a nested lists in Python.

In this article, we’ll look at how to copy a nested lists in Python.

How to copy a nested lists in Python?

To copy a nested lists in Python, we can use the copy.deepcopy method.

For instance, we write

import copy

b = copy.deepcopy(a)

to copy the nested list a with copy.deepcopy and assign the copied list to b.

Conclusion

To copy a nested lists in Python, we can use the copy.deepcopy method.

Sometimes, we want to convert an XML file to a Python Pandas dataframe.

In this article, we’ll look at how to convert an XML file to a Python Pandas dataframe.

How to convert an XML file to a Python Pandas dataframe?

To convert an XML file to a Python Pandas dataframe, we can use the iter method.

For instance, we write

import pandas as pd
import xml.etree.ElementTree as ET
import io

def iter_docs(author):
    author_attr = author.attrib
    for doc in author.iter('document'):
        doc_dict = author_attr.copy()
        doc_dict.update(doc.attrib)
        doc_dict['data'] = doc.text
        yield doc_dict

xml_data = io.StringIO(u'''...''')

etree = ET.parse(xml_data)
doc_df = pd.DataFrame(list(iter_docs(etree.getroot())))

to create the iter_docs function that iterates through the document elements in the author XML DOM object.

And then we insert the values into the doc_dict dictionary.

Then we use yield to yield the value.

Next, we read the XML string with

xml_data = io.StringIO(u'''...''')

Then we parse the XML string with

etree = ET.parse(xml_data)

And then we use iter_docs to return the items with

iter_docs(etree.getroot())

Then we convert the iterator items to a list with list and use the list as the argument for DataFrame to create the data frame.

Conclusion

To convert an XML file to a Python Pandas dataframe, we can use the iter method.

Sometimes, we want to remove list elements in a for loop in Python.

In this article, we’ll look at how to remove list elements in a for loop in Python.

How to remove list elements in a for loop in Python?

To remove list elements in a for loop in Python, we can use the filter function.

For instance, we write

a = filter(lambda item: has_condition(item), a)

to call filter with a lambda function that returns the condition of the items we want to include in the returned iterator and list a.

And then we assign the returned value back to a.

Conclusion

To remove list elements in a for loop in Python, we can use the filter function.