Creating Zip file from stream and downloading it
I have a DataTable that i want to convert it to xml and then zip it, using DotNetZip. finally user can download it via Asp.Net webpage.
My code in below
I have a DataTable that i want to convert it to xml and then zip it, using DotNetZip. finally user can download it via Asp.Net webpage.
My code in below
I need to construct and send a zip to a user.
Need to dynamically package some files into a .zip to create a SCORM package, anyone know how this can be done using code? Is it possible to build the folder structure dynamically inside of the .zip as well?
I have a folder on my web server that has hundreds of mp3 files in it. I would like to provide the option for a user to download a zipped archive of every mp3 in the directory from a web page.
I’m wondering how I can send a zip file to a WebApi controller and vice versa.
The problem is that my WebApi uses json to transmit data. A zip file is not serializable, either is a stream. A string would be serializable. But there has to be an other solution than to convert the zip into a string and than send the string. That just sounds wrong.
I have a download page where there are 3 download options: Word, Zip, and PDF. There is a folder containing .doc files. When a user clicks the Zip option on the page, I want ASP.NET to zip the folder with the .doc files into a temporary .zip file. Then the client will download it from the server. When the user’s download is finished, the temporary Zip file should delete itself.
Is there a built-in function that works like zip() but that will pad the results so that the length of the resultant list is the length of the longest input rather than the shortest input?
How can I create a zip archive of a directory structure in Python?
I read through the zipfile documentation, but couldn’t understand how to unzip a file, only how to zip a file. How do I unzip all the contents of a zip file into the same directory?
Often enough, I’ve found the need to process a list by pairs. I was wondering which would be the pythonic and efficient way to do it, and found this on Google: