62 lines
2.3 KiB
Plaintext
62 lines
2.3 KiB
Plaintext
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Metadata-Version: 2.1
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Name: funda-scraper
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Version: 0.0.2
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Summary: FundaScaper provides you the easiest way to perform web scraping from Funda, the Dutch housing website.
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Home-page: https://github.com/whchien/funda-scraper
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Author: Will Chien
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Author-email: locriginal@gmail.com
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License: gpl-3.0
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Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3.6
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Classifier: Programming Language :: Python :: 3.7
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: Implementation :: CPython
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Classifier: Programming Language :: Python :: Implementation :: PyPy
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Requires-Python: >=3.7.0
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Description-Content-Type: text/markdown
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Requires-Dist: beautifulsoup4 (>=4.8)
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Requires-Dist: requests (>=2)
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Requires-Dist: diot (>=0.1.5)
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Requires-Dist: PyYAML (>=5.0)
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Requires-Dist: tqdm (>=4.42.0)
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Requires-Dist: pandas (>=1.2)
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Requires-Dist: lxml (>=4)
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# FundaScraper
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`FundaScaper` provides you the easiest way to perform web scraping from Funda, the Dutch housing website.
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You can find listings from either house-buyer or rental market, and you can find historical data from the past few year.
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## Install
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```
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pip install funda-scraper
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```
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## Quickstart
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```
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from funda_scraper import FundaScraper
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scraper = FundaScraper(area="amsterdam", want_to="rent", find_past=False)
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df = scraper.run()
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df.head()
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```
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You can pass several arguments to `FundaScraper()` for customized scraping:
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- `area`: Specify the city or specific area you want to look for, eg. Amsterdam, Utrecht, Rotterdam, etc
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- `want_to`: You can choose either `buy` or `rent`, which finds houses either for sale or for rent.
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- `find_past`: Specify whether you want to check the historical data. The default is `False`.
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- `n_pages`: Indicate how many pages you want to look up. The default is `1`.
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## Advanced usage
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You can check the [example notebook](https://colab.research.google.com/drive/1hNzJJRWxD59lrbeDpfY1OUpBz0NktmfW?usp=sharing) for further details.
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Please give me a [star](https://github.com/whchien/funda-scraper) if you find this project helpful.
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