This program will go to The Astrophysical Journal website and retrieve the 'Received' and 'Accepted' dates for a sample of articles accepted in ApJ or ApJL in the previous year, saving them into a spreadsheet.
Inputs: journal name ('ApJ' or 'ApJL'), number of articles to sample per issue
Outputs: .csv file (open in Excel)
Assumptions:
- There are at least 30 articles per issue
- There are 2 issues per volume
- There are 18 volumes per year (1.5 per month, averaged)
The program will attempt to load the URLs of the first 30 articles in issue 1 of the starting volume. It will retrieve the dates for as many of these as possible, before doing the same for issue 1 of the previous volume, and then issue 1 of the volume before that, etc. It will loop through the previous 18 volumes in this manner, corresponding to the previous year, to return the dates for a sample of at least 500 articles (URLs on the ApJ website are not entirely consistent, so the date retrieval may fail for some articles).
An article accepted on 1st January will take roughly a month to make it into a published issue, so articles accepted in a given year start appearing around February. Similarly, the January issue of the given year will contain mostly articles accepted in December of the year before that. The program therefore automatically detects the first completely-February volume of the current year (e.g. Volume 836: Number 1, 10 February 2017), and loops back through to the previous February, doing some final filtering to remove articles not accepted in the desired year.
The parameters (number of articles to use per issue, and whether to sample ApJ or ApJL) are defined in the file 'parameters.py', and can be changed by the user. For at least 2012 - 2016 inclusive, there have been 18 volumes of ApJ per year, each with 2 issues, so it is assumed that this pattern will continue and the number of volumes per year (18) is hard-coded in.
Please be aware that using this program for anything other than its intended purpose may contravene copyright regulations. The program targets the ApJ and ApJL journals hosted on the IoP website, and text and data mining for non-commercial research are, as of 2014, exceptions to UK copyright law (https://www.gov.uk/guidance/exceptions-to-copyright). Text and data mining may not be permissible in other countries and on other websites, and will probably contravene the terms of use of such sites in any case.