Metadata-Version: 2.1
Name: pynytimes
Version: 0.2.1
Summary: A Python wrapper for (most) New York Times APIs
Home-page: https://github.com/michadenheijer/pynytimes
Author: Micha den Heijer
Author-email: micha@michadenheijer.com
License: MIT
Description: # pynytimes
        
        [<img src="https://raw.githubusercontent.com/michadenheijer/pynytimes/master/.github/poweredby_nytimes.png" height="20px">](https://developer.nytimes.com/) [![Build Status](https://travis-ci.com/michadenheijer/pynytimes.svg?token=8nhCHVYqgufX65p8PRDx&branch=master)](https://travis-ci.com/michadenheijer/pynytimes) [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)
        
        Use all (actually most) New York Times APIs, get all the data you need from the Times!
        
        This project is not made by anyone from the New York Times, nor is it affiliated with the New York Times.
        
        ## Installation
        
        There are multiple options to install pynytimes, but the easiest is by just installing it using pip (or pip3).
        
        ```bash
        pip install pynytimes
        ```
        
        ### Advanced (not better, just different)
        
        You can also install pynytimes manually from GitHub itself. This can be done by cloning this repository first, and then installing it using Python.
        
        ```bash
        git clone https://github.com/michadenheijer/pynytimes.git
        cd pynytimes
        python setup.py install
        ```
        
        ## Usage
        
        You can easily import this library using:
        
        ```python
        from pynytimes import NYTAPI
        ```
        
        Then you can simply add your API key (get your API key from [The New York Times Dev Portal](https://developer.nytimes.com/)):
        
        ```python
        nyt = NYTAPI("Your API key")
        ```
        
        When you have imported this library you can use the following features from the New York Times API.
        - [Top stories](#top-stories)
        - [Most viewed articles](#most-viewed-articles)
        - [Most shared articles](#most-shared-articles)
        - [Article search](#article-search-beta)
        - [Book reviews](#book-reviews)
        - [Movie reviews](#movie-reviews)
        - [Best sellers lists](#best-sellers-lists)
        - [Article metadata (Times Wire)](#article-metadata)
        - [Tag query (TimesTags)](#tag-query)
        - [Archive metadata](#archive-metadata)
        
        ### Top stories
        
        You can request the top stories from the New York Times. You can also get the top stories from a specific section.
        
        ```python
        top_stories = nyt.top_stories()
        
        # Get all the top stories from a specific category
        top_science_stories = nyt.top_stories(section = "science")
        ```
        
        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.
        
        ```python
        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)
        ```
        
        ### 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, Facebook and Twitter. You can get the most shared articles per day, week or month.
        
        ```python
        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"
        )
        ```
        
        ### Article search (beta)
        
        You can also search all New York Times articles. You can also define which sources you want to include. (Not all functions are implemented)
        
        ```python
        import datetime
        
        articles = nyt.article_search(
            query = "Obama",
            results = 30,
            dates = {
                "begin": datetime.datetime(2019, 1, 31),
                "end": datetime.datetime(2019, 2, 28)
            }
            options = {
                sources = [
                    "New York Times",
                    "AP",
                    "Reuters",
                    "International Herald Tribune"
                ]
            }
        )
        ```
        
        ### 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.
        
        ```python
        # 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")
        ```
        
        ### Movie reviews
        
        You can not only get the book reviews, but the movie reviews too.
        
        ```python
        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)
        })
        ```
        
        ### Best sellers lists
        
        The New York Times has multiple best sellers lists. You can easily request those lists using this library.
        
        ```python
        # 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)
        )
        ```
        
        ### Article metadata
        
        With an URL from a New York Times article you can easily get all the metadata you need from it.
        
        ```python
        metadata = nyt.article_metadata(
            url = "https://www.nytimes.com/2019/10/20/world/middleeast/erdogan-turkey-nuclear-weapons-trump.html"
        )
        ```
        
        ### Tag query
        
        The New York Times has their own tags library. You can query this library with this API.
        
        ```python
        tags = nyt.tag_query(
            "pentagon",
            max_results = 20
        )
        ```
        
        ### 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.
        
        ```python
        import datetime
        
        data = nyt.archive_metadata(
            date = datetime.datetime(2019, 1, 1)
        )
        ```
        
        ## License
        
        [MIT](LICENSE)
        
Platform: UNKNOWN
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: ~=3.5
Description-Content-Type: text/markdown
