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A Python wrapper for (most) New York Times APIs

Project description

pynytimes

Build Status PyPI - Python Version PyPI

Use all (actually most) New York Times APIs, get all the data you need from the Times!

Installation

There are multiple options to install and ugprade pynytimes, but the easiest is by just installing it using pip (or pip3).

Linux and Mac

pip install --upgrade pynytimes

Windows

python -m pip install --upgrade pynytimes

Development

You can also install pynytimes manually from GitHub itself. This can be done by cloning this repository first, and then installing it using Python. This might install an unreleased version, installation using this method is only advised if you want to modify the code or help maintain this library.

git clone https://github.com/michadenheijer/pynytimes.git
cd pynytimes
python setup.py install

Usage

You can easily import this library using:

from pynytimes import NYTAPI

Then you can simply add your API key (get your API key from The New York Times Dev Portal):

nyt = NYTAPI("Your API key")

Optionally you can also set to use http instead of https.

nyt = NYTAPI("Your API key", https=False)
Variables Description Data type Required
key The API key from The New York Times str True
https Whether you'd want requests over https bool False
session A requests session that you'd like the wrapper to use requests.sessions.Session False

Supported APIs

When you have imported this library you can use the following features from the New York Times API.

Top stories

You can request the top stories from the New York Times. You can also get the top stories from a specific section.

top_stories = nyt.top_stories()

# Get all the top stories from a specific category
top_science_stories = nyt.top_stories(section = "science")
Variables Description Data type Required
section Get Top Stories from a specific section str False

The possible sections are: arts, automobiles, books, business, fashion, food, health, home, insider, magazine, movies, national, nyregion, obituaries, opinion, politics, realestate, science, sports, sundayreview, technology, theater, tmagazine, travel, upshot, and world.

Most viewed articles

The New York Times API can provide the most popular articles from the last day, week or month.

most_viewed = nyt.most_viewed()

# Get most viewed articles of last 7 or 30 days
most_viewed = nyt.most_viewed(days = 7)
most_viewed = nyt.most_viewed(days = 30)
Variables Description Data type Required
days Get most viewed articles over the last 1, 7 or 30 days int False

Most shared articles

Not only can you request the most viewed articles from the New York Times API, you can also request the most shared articles. You can even request the articles that are most shared by email and Facebook. You can get the most shared articles per day, week or month.

most_shared = nyt.most_shared()

# Get most emaild articles of the last day
most_shared = myt.most_shared(
    days = 1,
    method = "email"
)

# Get most shared articles to Facebook of the last 7 days
most_shared = nyt.most_shared(
    days = 7,
    method = "facebook"    
)

# Get most shared articles to Facebook of the last 30 days
most_shared = nyt.most_shared(
    days = 30,
    method = "facebook"
)
Variables Description Data type Required
days Get most viewed articles over the last 1, 7 or 30 days int False
method Method of sharing (email or facebook) str False

Article search (beta)

You can also search all New York Times articles. Optionally you can define your search query (using the query option), the amount of results (using results) and the amount of results you'd like. You can even add more options so you can filter the results.

import datetime

articles = nyt.article_search(
    query = "Obama",
    results = 30,
    dates = {
        "begin": datetime.datetime(2019, 1, 31),
        "end": datetime.datetime(2019, 2, 28)
    },
    options = {
        "sort": "oldest",
        "sources": [
            "New York Times",
            "AP",
            "Reuters",
            "International Herald Tribune"
        ],
        "news_desk": [
            "Politics"
        ],
        "type_of_material": [
            "News Analysis"
        ]
    }
)
Variables Description Data type Required
query What you want to search for str False
results The amount of results that you want to receive (returns a multiple of 10) int False
dates A dictionary of the dates you'd like the results to be between dict False
options A dictionary of additional options dict False

dates

Variables Description Data type Required
begin Results should be published at or after this date datetime.datetime False
end Results should be published at or before this date datetime.datetime False

options

Variables Description Data type Required
sort How you want the results to be sorted (oldest, newest or relevance) str False
sources Results should be from one of these sources list False
news_desk Results should be from one of these news desks (valid options) list False
type_of_material Results should be from this type of material (valid options) list False
section_name Results should be from this section (valid options) list False

Book reviews

You can easily find book reviews for every book you've read. You can find those reviews by searching for the author, ISBN or title of the book.

# Get reviews by author (first and last name)
reviews = nyt.book_reviews(author = "George Orwell")

# Get reviews by ISBN
reviews = nyt.book_reviews(isbn = 9780062963673)

# Get book reviews by title
reviews = nyt.book_reviews(title = "Becoming")
Variables Description Data type Required
author Reviews of books from this author str One of these three
isbn Reviews of books with this ISBN str One of these three
title Reviews of books with this title str One of these three

Movie reviews

You can not only get the book reviews, but the movie reviews too.

import datetime

reviews = nyt.movie_reviews(
    keyword = "Green Book",
    options = {
        "order": "by-opening-date",
        "reviewer": "A.O. Scott",
        "critics_pick": False
    },
    dates = {
        "opening_date_start": datetime.datetime(2017, 1, 1),
        "opening_date_end": datetime.datetime(2019, 1, 1),
        "publication_date_start": datetime.datetime(2017, 1, 1),
        "publication_date_end": datetime.datetime(2019, 1, 1)
})
Variables Description Data type Required
keyword Reviews of movies with this keyword str False
options Dictionary of search options dict False
dates Dictionary of dates about the review dict False

options

Variables Description Data type Required
order How to sort the results (by-title, by-publication-dateor by-opening-date) str False
reviewer Name of the reviewer str False
critics_pick Only return critics' pick if True bool False

dates

Variables Description Data type Required
opening_date_start Reviews about movies released at or after this date datetime.datetime False
opening_date_end Reviews about movies released at or before this date datetime.datetime False
publication_date_start Reviews released at or after this date datetime.datetime False
publication_date_end Reviews released at or before this date datetime.datetime False

Best sellers lists

The New York Times has multiple best sellers lists. You can easily request those lists using this library.

# Get all the available New York Times best sellers lists
lists = nyt.best_sellers_lists()

# Get fiction best sellers list
books = nyt.best_sellers_list()

# Get non-fiction best sellers list
books = nyt.best_sellers_list(
    name = "combined-print-and-e-book-nonfiction"
)

# Get best sellers lists from other date
import datetime

books = nyt.best_sellers_list(
    name = "combined-print-and-e-book-nonfiction",
    date = datetime.datetime(2019, 1, 1)
)
Variables Description Data type Required
name Name of best sellers list str False
date Date of best sellers list datetime.datetime False

Article metadata

With an URL from a New York Times article you can easily get all the metadata you need from it.

metadata = nyt.article_metadata(
    url = "https://www.nytimes.com/2019/10/20/world/middleeast/erdogan-turkey-nuclear-weapons-trump.html"
)
Variables Description Data type Required
url URL of the article str True

Load latest articles

You can easily load the latest articles published by the New York Times.

latest = nyt.latest_articles(
    source = "nyt",
    section = "books"
)
Variables Description Data type Required
source Source of article (all, nyt and inyt) str False
section Section of articles str False

You can find all possible sections using:

sections = nyt.section_list()

Tag query

The New York Times has their own tags library. You can query this library with this API.

tags = nyt.tag_query(
    "pentagon",
    max_results = 20
)
Variables Description Data type Required
query Tags you're looking for str True
max_results Maximum results you'd like int False
filter_options Filter options list False

Archive metadata

If you want to load all the metadata from a specific month, then this API makes that possible. Be aware you'll download a big JSON file (about 20 Mb), so it can take a while.

import datetime

data = nyt.archive_metadata(
    date = datetime.datetime(2019, 1, 1)
)
Variables Description Data type Required
date Date of month of all the metadata datetime.datetime True

License

License: MIT

Disclaimer: This project is not made by anyone from the New York Times, nor is it affiliated with The New York Times Company.

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