And it isn't difficult to extract just a subset of a large directory structure (in Windows you mealy copy-paste a selection of files)ħ-Zip is able to do this as well but you have to press the "Copy" button and then specify the destination. Indeed most operating systems, including Windows, natively support opening a ZIP folder to review file names and metadata without extracting the entire archive. The advantage of ZIP is that the contents can be individually extracted exactly as you are hoping to do without extracting the entire archive. tar.gz format which is frequently used on Linux platforms. The ZIP file format is really just a container (basically a folder) which contains compressed files. Running this script in the directory will create separate ZIP files for each CSV file and will delete the original CSV file upon successful compression. # Remove the original CSV file after successful compression Skipping compression."Įcho "File $file compressed successfully into $zip_file." ![]() # Check if the target ZIP file already exists, if yes, skip compressionĮcho "File $zip_file already exists. Target_directory="/path/to/your/directory" I've tested this process, and Python, particularly with Pandas, can easily read these archives without manual extraction. You can execute this script within a directory containing the files to generate ZIP archives. Below is an example of a Bash script that individually compresses files into distinct ZIP archives, making them separately extractible. I have a script that can assist with this task. I am aware of the -s switch in zip and the -v switch in 7z, but they both require the users to have all the parts of the archive to be able to decompress any part of it, which is much less desirable. I think I would be able to write a bash or python script that fits the first few requirements, but I doubt it would be fast enough. ![]() The method should be able to show a progress bar.All resulting archives can be decompressed independently to reconstruct part of the folder (sometimes I may want to use only part of the dataset for tests, in which case I don't want to have to decompress the entire dataset).The method can work on any folder structure, no matter how deep.I am therefore looking for a way to do this. These time and space savings increase as we increase the number of separate zip files. Meanwhile, I only need to have at maximum zip2, folder1 and folder2 on disk at the same time, so 50+100+100 = 250GB of disk space. I can do: 2.5 minutes downloading zip1, 5 minutes decompressing zip1 and 2.5 minutes downloading zip2 simultaneously, delete zip1, then decompress zip2 in 5 minutes, for a total of 2.5+5+5 = 12.5 minutes. zip, let's say downloading each takes 2.5 minutes and decompressing each takes 5 minutes. zip had a 50% compression ratio, I need to use 100+200 = 300GB disk space. ![]() zip, let's say downloading takes 5 minutes and decompressing takes 10 minutes. This can be pretty convenient as it enables me to pipeline the download -> decompress -> delete archive process, which is more efficient in terms of both time and storage space, as explained below with arbitrary time/sizes: ![]() zip files, which can be unzipped independently into the same folder as one consistent dataset. I have seen that some datasets can be downloaded as a set of. I work with some big image datasets containing millions of images, and I often need to compress the results of each step of processing to be uploaded as backup.
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