inputs = zip(urls, fns) Function to download a URL This way we can pass a single argument (the tuple) that contains two pieces of information. Each tuple in the list will contain two elements a URL and the download filename for the URL. So we’ll zip the urls and fns lists together to get a list of tuples. To download a file we’ll need to pass two arguments, a URL and a filename. Multiprocessing requires parallel functions to have only one argument (there are some workarounds, but we won’t get into that here). Given your application, you may want to write code that will parse the input URL and download it to a specific directory. I’ve hardcoded the filenames in a list for simplicity and transparency. Here, I’m downloading the files to the Windows ‘Downloads’ directory. urls = ['',Įach URL must be associated with its download location. In other applications, you may programmatically generate a list of files to download. Here, I specify the URLs to four files in a list. I’ll demonstrate parallel file downloads in Python using gridMET NetCDF files that contain daily precipitation data for the United States. import requestsįrom multiprocessing.pool import ThreadPool Define URLs and filenames The time module is also part of the Python standard library. We’ll also import the time module to keep track of how long it takes to download individual files and compare performance between the serial and parallel download routines. The requests and multiprocessing modules are both available from the Python standard library, so you won’t need to perform any installations. Import modulesįor this example, we only need the requests and multiprocessing Python modules to download files in parallel. The code in this tutorial uses only modules available from the Python standard library, so no installations are required. The tutorial demonstrates how to develop a generic file download function in Python and apply it to download multiple files with serial and parallel approaches. With a parallel file download routine, you can download multiple files simultaneously and save a considerable amount of time. This serial approach can work well with a few small files, but if you are downloading many files or large files, you’ll want to use a parallel approach to maximize your computational resources. The easiest way to download files is using a simple Python loop to iterate through a list of URLs to download.
There are several ways for automating file downloads in Python. Automating file downloads can save a lot of time.
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