GSoC 2017 @ dateparser

So finally Google Summer of Code 2017 is coming to an end. It was an amazing experience to be a part of this prestigious program and I learned a lot in these three months about open source development. Work Summary I worked on dateparser , a project under sub-org Scrapinghub of Python Software Foundation (PSF) , that deals with parsing dates in various languages and formats. The objective of the project was to integrate translation data of all locales in Unicode Common Locale Data Repository(CLDR) which is a standard repository of locale specific data with the existing translation data in dateparser. Here is a brief outline of the work done on my project on dateparser during GSoC 2017: Work Completed 1.   Retrieved Translation data from Unicode CLDR Scripts were written to retrieve translation data from unicode CLDR  github repository. The translation data for dates and numerals were separately stored. 2. Ordered languages by population The languages were...

Finally I have successfully implemented translation of date strings with new integrated data. I have been working on it for a long while now, much more than I expected. I expected to be completely finished with translation of date strings without numeral words much earlier and I was planning to get started with numeral parser as early as possible. But it took me a while longer as I did not think clearly and therefore started on with a complicated solution and then moved on to simpler solutions. As I mentioned in my last blog post, the problem was to translate relative date strings, which are of two types, one that have no digits like 'yesterday' and the other that have digits and are stored as regex patterns like '(\\d+) day ago'. Currently dateparser uses translations for 'ago' and 'in' along with other words and relative dates are translated in a similar way as other date strings. First dates are splitted by numbers within dates and then by known wo...

As I mentioned in the last blog post, I have been working to modify the codebase so that dateparser could use new data to parse date strings. Most of the new data for date translation is similar to previous data used for translation, the only major difference is in dealing with relative type date strings. The previous data used translations for ago and in to translate relative type date strings like "10 years ago",  "15 hours 10 minutes ago", "in 10 minutes and 8 seconds". But the data retrieved from unicode CLDR contains translation for complete date strings so that they translate directly to formats like "** year ago" or "in ** month" which can be used further for parsing. Initially I thought direct translations like these would work but then I realised that many relative dates are not covered in these translations. These include dates that contains more than one date fields, like "1 year 3 months ago" and dates that includ...

So far translation data is ready to be used for translation of date strings. This includes combined data from unicode CLDR and supplementary data contributed by many individuals. Initially the data from unicode CLDR was stored as json files and supplementary data was stored as yaml files and data from both these sources were to be combined after loading each separately which was then supposed to be used for translating dates. But after discussion with my mentor we agreed upon a better approach suggested by him that we could store data directly in python modules. Storing data in python modules directly has the advantage that importing data from python modules is faster than loading from json and yaml files. And considering the fact that we don't have to combine data from cldr and supplementary data files at run time, storing data in Python modules proves to be much more efficient. As the data is ready, now is the time to make necessary modifications in the codebase to support l...

So I have been finally selected for Google Summer of Code 2017  at Python Software Foundation . Python Software Foundation(PSF) serves as an umbrella organisation comprising various sub-orgs that have projects that contribute to the development of the Python language. The sub-org I am going to work with is Scrapinghub . About Scrapinghub Scrapinghub, as its name clearly suggests, deals primarily with scraping the web. Scrapinghub is a company concerned with Information Retrieval and its later manipulation, i.e., it deals with both data extraction and data processing after retrieval. It has various projects that deal with these topics and the one I am going to work on deals with data processing after retrieval. I am going to work with dateparser , which is a Python library that primarily deals with parsing dates in various languages and formats. About dateparser dateparser is a Python library that is used to parse various forms of dates in different languages to a common for...