Get images of great find / 47 sites using Python (Part 2/2: I published the target list on github)

Postscript after publication of the article

As a skeleton, I uploaded an empty folder under jpg to the github repository by region (region)-by prefecture (2020/11/3, 11:30). I think this saved me a little time.

In response to the previous article

In response to previous article, the target list has been released on github. We decided that it would be better for us to obtain and publish the script as a reference rather than to publish the script and increase the access to find / 47 unnecessarily. The image is not an open post but a screening method, and 1080 images seems to have settled down once, so this should be enough for the time being.

• https://github.com/cj3029412/find47-image-url-index

File description

I think 02.csv is easy to write a simple script and get an image.

--First column: Download destination (acquisition source) URL --Second column: Specifying example when saving the download zip file by region and prefecture in the jpg directory directly under (a faithful reproduction of the find / 47 hierarchy. I prepared a skeleton in the github repository, so if you don't mind Please use)

01.csv is the prototype of 02.csv. This is the output of the previous article.

--First column: Regional classification code used by find / 47. 0 is Hokkaido, 7 is Kyushu Okinawa --Second column: State code used by find / 47. 0 is Hokkaido, 46 is Okinawa --Third column: Distinguished name uniquely given to the image by find / 47 --Column 4: Maximum size offered (downloadable) of xl, l, m, s. If you don't need up to xl and want to save storage space, change this to s. After a quick look, size s and size m seem to be provided in all images. Some images of size l are not provided (although some).

For wallpaper purposes, it is recommended to get it step by step for each region or prefecture, or to get only the index line of the specified integer multiple by FizzBuzz.

So far, it was a simple explanation that only those who can see the contents of the CSV file and this explanation and the implementation of image acquisition can use it. Thank you for your understanding.

Precautions

If you use 02.csv to acquire images as they are, 1080 images will be obtained at the maximum resolution (mostly XL) that can be acquired for each image. The required storage capacity in this case is around 10GB or more. The downloaded zip file contains the image jpeg file and the description txt file, and even if you delete the original zip and txt and leave only the jpeg, you will need about 10GB. Also, if I put enough access weights to get all 1080 images, it took one night (about 8-10 hours) to complete in my operation. The image is for reference of the file name and size as it is taken out from the zip.

Supplement

We will check the latest status from time to time to see if it has increased from 1080, and will update the list on github. Also, with the next 2+ articles as the final episode, I will briefly touch on the setting to automatically change the wallpaper using variety.