Merge pull request AnthonyBloomer#92 from AnthonyBloomer/remove-v1-te…

…sts-examples Remove v1 tests & examples
marisakamoto · Mar 31, 2021 · 90cc48d · 90cc48d
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diff --git a/README.md b/README.md
@@ -1,5 +1,6 @@
 # Daftlistings
 
+
 [![Build Status](https://travis-ci.org/AnthonyBloomer/daftlistings.svg?branch=dev)](https://travis-ci.org/AnthonyBloomer/daftlistings)
 [![codecov](https://codecov.io/gh/AnthonyBloomer/daftlistings/branch/master/graph/badge.svg)](https://codecov.io/gh/AnthonyBloomer/daftlistings)
 
@@ -60,215 +61,6 @@ for listing in listings:
     print(listing.price)
 ```
 
-By default, the Daft `search` function iterates over each page of results and appends each Listing object to the array that is returned. If you wish to disable this feature, you can set `fetch_all` to `False`:
-
- ``` python
-daft.search(fetch_all=False)
-```
-
-
-### Examples
-
-Get apartments to let in Dublin City that are between €1000 and €1500 and contact the advertiser of each listing.
-
-``` python
-from daftlistings import Daft, RentType
-
-daft = Daft()
-
-daft.set_county("Dublin City")
-daft.set_listing_type(RentType.APARTMENTS)
-daft.set_min_price(1000)
-daft.set_max_price(1500)
-
-listings = daft.search()
-
-for listing in listings:
-
-    contact = listing.contact_advertiser(
-        name="Jane Doe",
-        contact_number="019202222",
-        email="[email protected]",
-        message="Hi, I seen your listing on daft.ie and I would like to schedule a viewing."
-    )
-
-    if contact:
-        print("Advertiser contacted")
-```
-
-You can sort the listings by price, distance, upcoming viewing or date using the SortType object. The SortOrder object allows you to sort the listings descending or ascending.
-
-``` python
-
-from daftlistings import Daft, SortOrder, SortType, RentType
-
-daft = Daft()
-
-daft.set_county("Dublin City")
-daft.set_listing_type(RentType.ANY)
-daft.set_sort_order(SortOrder.ASCENDING)
-daft.set_sort_by(SortType.PRICE)
-daft.set_max_price(2500)
-
-listings = daft.search()
-
-for listing in listings:
-    print(listing.formalised_address)
-    print(listing.daft_link)
-    print(listing.price)
-    features = listing.features
-    if features is not None:
-        print('Features: ')
-        for feature in features:
-            print(feature)
-    print("")
-
-```
-
-Parse listing data from a given search result url.
-
-``` python
-
-from daftlistings import Daft
-
-daft = Daft()
-daft.set_result_url("https://www.daft.ie/dublin/apartments-for-rent?")
-listings = daft.search()
-
-for listing in listings:
-    print(listing.formalised_address)
-    print(listing.price)
-    print(' ')
-
-
-```
-
-Find student accommodation near UCD that is between 850 and 1000 per month
-
-``` python
-from daftlistings import Daft, SortOrder, SortType, RentType, University, StudentAccommodationType
-
-daft = Daft()
-daft.set_listing_type(RentType.STUDENT_ACCOMMODATION)
-daft.set_university(University.UCD)
-daft.set_student_accommodation_type(StudentAccommodationType.ROOMS_TO_SHARE)
-daft.set_min_price(850)
-daft.set_max_price(1000)
-daft.set_sort_by(SortType.PRICE)
-daft.set_sort_order(SortOrder.ASCENDING)
-daft.set_offset(offset)
-listings = daft.search()
-
-for listing in listings:
-    print(listing.price)
-    print(listing.formalised_address)
-    print(listing.daft_link)
-
-```
-
-
-
-Map the 2-bed rentling properties in Dublin and color code them wrt to prices.
-Save the map in a html file.
-
-``` python
-from daftlistings import Daft, SortOrder, SortType, RentType, MapVisualization
-import pandas as pd
-
-daft = Daft()
-daft.set_county("Dublin City")
-daft.set_listing_type(RentType.ANY)
-daft.set_sort_order(SortOrder.ASCENDING)
-daft.set_sort_by(SortType.PRICE)
-# must sort by price in asending order, MapVisualization class will take care of the weekly/monthly value mess
-daft.set_max_price(2400)
-daft.set_min_beds(2)
-daft.set_max_beds(2)
-
-listings = daft.search()
-properties = []
-print("Translating {} listing object into json, it will take a few minutes".format(str(len(listings))))
-print("Ignore the error message")
-for listing in listings:
-    try:
-        if listing.search_type != 'rental':
-            continue
-        properties.append(listing.as_dict_for_mapping())
-    except:
-        continue
-
-
-df = pd.DataFrame(properties)
-print(df)
-
-dublin_map = MapVisualization(df)
-dublin_map.add_markers()
-dublin_map.add_colorbar()
-dublin_map.save("dublin_apartment_to_rent_2_bed_price_map.html")
-print("Done, please checkout the html file")
-
-```
-
-
-
-
-For more examples, check the [Examples folder](https://github.com/AnthonyBloomer/daftlistings/tree/dev/examples)
-
-### Parallel as_dict()
-
-lisitng.as_dict() is relatively slow for large volume of listings. Below is an exmple script using threading and joblib library technique to speedup this process
-
-``` python
-from daftlistings import Daft, RentType
-from joblib import Parallel, delayed
-import time
-
-def translate_listing_to_json(listing):
-    try:
-        if listing.search_type != 'rental':
-            return None
-        return listing.as_dict_for_mapping()
-    except:
-        return None
-
-daft = Daft()
-daft.set_county("Dublin City")
-daft.set_listing_type(RentType.ANY)
-daft.set_max_price(2000)
-daft.set_min_beds(2)
-daft.set_max_beds(2)
-
-listings = daft.search()
-properties = []
-print("Translating {} listing object into json, it will take a few minutes".format(str(len(listings))))
-print("Ignore the error message")
-
-# time the translation
-start = time.time()
-properties = Parallel(n_jobs=6, prefer="threads")(delayed(translate_listing_to_json)(listing) for listing in listings)
-properties = [p for p in properties if p is not None] # remove the None
-end = time.time()
-print("Time for json translations {}s".format(end-start))
-
-```
-
-Table of perfomance speedup for 501 listings
-Threads | Time (s) | Speedup
------------- | ------------- | -------------
-1 | 178 | 1.0
-2 | 101 | 1.8
-3 | 72  | 2.5
-4 | 61  | 2.9
-6 | 54  | 3.3
-
-## Tests
-
-The Python unittest module contains its own test discovery function, which you can run from the command line:
-
-```
- python -m unittest discover tests/
-```
-
 ## Contributing
 
   - Fork the project and clone locally.

diff --git a/daftlistings/__init__.py b/daftlistings/__init__.py
@@ -1,4 +1,3 @@
 from .daft import *
 from .enums import *
-from .exceptions import DaftException
 from .map_visualization import *
diff --git a/daftlistings/property_for_rent.py b/daftlistings/property_for_rent.py
diff --git a/daftlistings/property_for_sale.py b/daftlistings/property_for_sale.py
diff --git a/daftlistings/request.py b/daftlistings/request.py
diff --git a/examples/as_dict.py b/examples/as_dict.py