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Scraping toolkit to generate PhD dataset

Project description

Python 3.6 PyPI version Build Status


phd_scraper is a tool to download daily and hourly LatinAmerica Hydrometeorological datasets using Python. Currently phd_scraper support the following websites:

Users need to regard that the entire dataset does not present control quality. The use of this data will be the sole responsibility of the user (see below).

DISCLAIMER (Adapted from:

The scripts outlined in this document is published under the GNU General Public License, version 3 (GPL-3.0). The GPL is an open source, copyleft license that allows for the modification and redistribution of original works.Programs licensed under the GPL come with NO WARRANTY. In our case, a simple Python script isn’t likely to blow up your computer or kill your cat. Nonetheless, it is always a good idea to pay attention to what you are doing, to ensure that you have downloaded the correct data, and that everything looks ship-shape.


If you run into an issue while you are using this script, you can email us and we can help you troubleshoot the issue. However, if the issue is related to the script and not your own fault, you should contribute back to the open source community by reporting the issue. You can report any issues to us here on GitHub.

If that seems like a lot of work, just think about how much work it would have been to do all the work this package does for you, or how much time went in to writing these functions … it is more than I’d like to admit!


SENAMHI’s terms of use are in, but as of writing that link was redirecting to the SENAMHI home page. An archived version is available in The terms allow for the free and public access to information on the SENAMHI website, in both for-profit and non-profit applications. However, SENAMHI stipulates that any use of the data must be accompanied by a disclaimer that SENAMHI is the proprietor of the information. The following text is recommended (official text in Spanish):

Official Spanish: Información recopilada y trabajada por el Servicio Nacional de Meteorología e Hidrología del Perú. El uso que se le da a esta información es de mi (nuestra) entera responsabilidad. English translation: This information was compiled and maintained by Peru’s National Meteorology and Hydrology Service (SENAMHI). The use of this data is of my (our) sole responsibility.



pip install phd_scraper


unzip master && cd phd_scraper-master
python install


SENAMHI - hydrometeorological: Hydrometeorological data throughout Peru.
Parameters Description
station_code station new code
init_date Init date to start to download
last_date Last date to start to download
completedata Whether it is True the missing dates will be completed with np.NaN
to_csv Output filename
metadata_db Represent the metadata of the entire network (see phd_scraper.create_metadata)

Basic Usage

from phd_scraper import se_hydrometeo, init_date=2019-01-01, last_date=2019-02-02)

Console mode

$ cd ~/phd_scraper/phd_scraper/
$ python3 --station_code 100090 --init_date 2019-01-01 --last_date 2019-02-02 --to_csv test.csv
SENAMHI - historic
Parameters Description
station_code station new code
to_csv String; Output filename.

Basic Usage

from phd_scraper import se_historic'152204')

Console mode

$ cd ~/phd_scraper/phd_scraper/
$ python3 --station_code 152204 --outfile test.csv

version 0.1.3 (2019-12-19)

  • se_historic and se_hydrometeo return a pandas.DataFrame

version 0.1.2 (2019-12-17)

  • First release on PyPI.

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