![]() ![]() I have no idea why when I download it from the website, it downloads correctly as a. I got the message return from urlretrieve and it gives this: x-amz-id-2: vUOH963SZ6x NBjj02vFIFmpgzBPfxhIvZLSE qcKcfeJzlfFwZQdq8OvWgazQeXrupowH9OxtI=ĮTag: "74e84c081cb7fbe5fc0ad4850fc38d51-7" It is not attached to the actual downloaded file unless it is also in zipped file name (.csv.zip). csv from the zipped file too (when replacing. Save_dir = 'C:/Users/Acer/Downloads/Testing/'Įdit: I have experimented with an answer to How can I replace (or strip) an extension from a filename in Python? but this actually removes the. Year_save_dir = save_dir year '.csv.zip' # Changing the below line is what is causing issues csv extension to the file, is this possible or is there a better solution/method available? I am using Python 3.7 if that makes a difference.ĭEFAULT_YEARS = ĭef csv_download(save_dir: str, years: list = DEFAULT_YEARS) -> None: zip in this case) but also add the needed. How can I download the files with compressed extensions (. zip it compresses fine but then returns just a file with no extensions: csv.zip looking like (true size of ~1.75GB, reading this with pandas returns the above error): If I download the files with no added extension in year_save_dir = it looks like this: I understand why there is an error, but I am unsure how to fix it. Zipfile.BadZipFile: File is not a zip file Raise BadZipFile("File is not a zip file") csv.zip file extension it returns this error: File "C:\Python37\lib\zipfile.py", line 1325, in _RealGetContents When I try to read the file using pandas with the. csv.zip added at the end as otherwise, there is no extension on the downloaded file (and it is significantly smaller so I am assuming it is meant to be a. However my issue is that at the moment I am putting the save directory ( year_save_dir) with. gzip for Linux, which I have already created a method for changing the extension) files due to the size of them (20 GB total across all 23 files). However, I would like a def function that can automate this downloading process and I would prefer to have. ![]() csv file extension is added automatically and there have been no issues using it with pandas. ![]() I noticed that when I download manually from the website in question the. csv files from a URL where the only variable is the year that needs adding to the end of the constant URL string. It does not offer extra features or functionality, and that's great because, in the end, you get exactly what is advertised, nothing more and nothing less.I am trying to download multiple. The only thing that will be left to do is to check the quality of your resulting files.Ĭsv File Split is nothing more than its name implies. Hit the start button for the final part of this process. Tell the app if your added file includes column titles, adjust the number of files you'd like to have at the end of conversion, and also the number of records each should contain. Point the program in the right direction, and make sure you also adjust the output path. One particularly important aspect in the conversion process is represented by the files you'd like to transform. In terms of getting things started, firstly, the program won't require installation, making it ideal for transport on external drives. It's true that it won't be used that often, but in a way integrating itself with the rest of the utilities in an OS, makes the whole toolbox look tidier. Modern interface, despite app simplicityĪlthough we were indeed expecting the program to avoid as much detail in looks as possible, the fact that its simple outline is after all also modern, integrating quite well with all recent Windows OS iterations, is satisfying. The program doesn't seem all that different from similar splitters. Even so, the program is great at what it was designed to do, and as a result, it manages to be a noticeable option for those who need to divide big CSV files into tinier, easier-to-use files. It's a tool, so you shouldn't really expect much from it, other than what its name implies. Csv File Split is your typical splitting application. ![]()
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