From ad85c3b444052302f47176be56677a48ef11d8c8 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 09:36:15 +0200 Subject: [PATCH 01/16] feat: make place for the getting links lesson --- .../scraping_basics_python/09_getting_links.md | 14 ++++++++++++++ .../{09_crawling.md => 10_crawling.md} | 2 +- 2 files changed, 15 insertions(+), 1 deletion(-) create mode 100644 sources/academy/webscraping/scraping_basics_python/09_getting_links.md rename sources/academy/webscraping/scraping_basics_python/{09_crawling.md => 10_crawling.md} (95%) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md new file mode 100644 index 000000000..ce7b46d44 --- /dev/null +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -0,0 +1,14 @@ +--- +title: Getting links form HTML with Python +sidebar_label: Getting links from HTML +description: Lesson about building a Python application for watching prices. Using the Beautiful Soup library to locate links to individual product pages. +sidebar_position: 9 +slug: /scraping-basics-python/getting-links +--- + + +:::danger Work in progress + +This course is incomplete. As we work on adding new lessons, we would love to hear your feedback. You can comment right here under each page or [file a GitHub Issue](https://github.com/apify/apify-docs/issues) to discuss a problem. + +::: diff --git a/sources/academy/webscraping/scraping_basics_python/09_crawling.md b/sources/academy/webscraping/scraping_basics_python/10_crawling.md similarity index 95% rename from sources/academy/webscraping/scraping_basics_python/09_crawling.md rename to sources/academy/webscraping/scraping_basics_python/10_crawling.md index 23f1f7336..39b5083e8 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_crawling.md +++ b/sources/academy/webscraping/scraping_basics_python/10_crawling.md @@ -2,7 +2,7 @@ title: Crawling websites with Python sidebar_label: Crawling websites description: TODO -sidebar_position: 9 +sidebar_position: 10 slug: /scraping-basics-python/crawling --- From e2aacd3cd8ef6c5953d25c7a8be04f8732e1222e Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 10:18:35 +0200 Subject: [PATCH 02/16] feat: lesson intro --- .../09_getting_links.md | 19 +++++++++++++++++++ 1 file changed, 19 insertions(+) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index ce7b46d44..696bb188e 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -6,6 +6,25 @@ sidebar_position: 9 slug: /scraping-basics-python/getting-links --- +import Exercises from './_exercises.mdx'; + +**In this lesson, we'll locate and extract links to individual product pages. We'll use BeautifulSoup to find the relevant bits of HTML.** + +--- + +The previous lesson concludes our effort to create a scraper. Our program now downloads HTML, locates and extracts data from the markup, and saves the data in a structured and reusable way. For some use cases, this is already enough! In other cases, though, scraping just one page is hardly useful. The data is spread across the website, over several pages. + +## Following links + +We'll use a technique called crawling, i.e. following links and scraping multiple pages. The algorithm goes like this: + +1. Visit the start URL. +1. Extract new URLs (and data), and save them. +1. Visit one of the newly found URLs and save data and/or more URLs from it. +1. Repeat 2 and 3 until you have everything you need. + +This will help us figure out the actual prices of products, as right now, for some, we're only getting the minimum price. + :::danger Work in progress From c706974fdab5614c5fd1774c2da3ff0be2eae684 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 11:14:03 +0200 Subject: [PATCH 03/16] feat: refactor the scraper --- .../09_getting_links.md | 160 +++++++++++++++++- 1 file changed, 156 insertions(+), 4 deletions(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 696bb188e..7002102ca 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -1,5 +1,5 @@ --- -title: Getting links form HTML with Python +title: Getting links from HTML with Python sidebar_label: Getting links from HTML description: Lesson about building a Python application for watching prices. Using the Beautiful Soup library to locate links to individual product pages. sidebar_position: 9 @@ -23,11 +23,163 @@ We'll use a technique called crawling, i.e. following links and scraping multipl 1. Visit one of the newly found URLs and save data and/or more URLs from it. 1. Repeat 2 and 3 until you have everything you need. -This will help us figure out the actual prices of products, as right now, for some, we're only getting the minimum price. +This will help us figure out the actual prices of products, as right now, for some, we're only getting the min price. +## Introducing functions -:::danger Work in progress +Implementing the algorithm requires quite a few changes to our code. However, over the course of the previous lessons, the code of our program grew to almost 50 lines containing downloading, parsing, and exporting: -This course is incomplete. As we work on adding new lessons, we would love to hear your feedback. You can comment right here under each page or [file a GitHub Issue](https://github.com/apify/apify-docs/issues) to discuss a problem. +```py +from decimal import Decimal +import httpx +from bs4 import BeautifulSoup +import csv +import json + +url = "https://warehouse-theme-metal.myshopify.com/collections/sales" +response = httpx.get(url) +response.raise_for_status() + +html_code = response.text +soup = BeautifulSoup(html_code, "html.parser") + +data = [] +for product in soup.select(".product-item"): + title = product.select_one(".product-item__title").text.strip() + + price_text = ( + product + .select_one(".price") + .contents[-1] + .strip() + .replace("$", "") + .replace(",", "") + ) + if price_text.startswith("From "): + min_price = Decimal(price_text.removeprefix("From ")) + price = None + else: + min_price = Decimal(price_text) + price = min_price + + data.append({"title": title, "min_price": min_price, "price": price}) + +with open("products.csv", "w") as file: + writer = csv.DictWriter(file, fieldnames=["title", "min_price", "price"]) + writer.writeheader() + for row in data: + writer.writerow(row) + +def serialize(obj): + if isinstance(obj, Decimal): + return str(obj) + raise TypeError("Object not JSON serializable") + +with open("products.json", "w") as file: + json.dump(data, file, default=serialize) +``` + +Let's introduce several functions which will make the whole thing easier to digest. First, we can turn the beginning of our program into this `download()` function, which takes a URL and returns a `BeautifulSoup` instance: + +```py +def download(url): + response = httpx.get(url) + response.raise_for_status() + + html_code = response.text + return BeautifulSoup(html_code, "html.parser") +``` + +Next, we can put parsing to a `parse_product()` function, which takes the product item element, and returns the dictionary with data: + +```py +def parse_product(product): + title = product.select_one(".product-item__title").text.strip() + + price_text = ( + product + .select_one(".price") + .contents[-1] + .strip() + .replace("$", "") + .replace(",", "") + ) + if price_text.startswith("From "): + min_price = Decimal(price_text.removeprefix("From ")) + price = None + else: + min_price = Decimal(price_text) + price = min_price + + return {"title": title, "min_price": min_price, "price": price} +``` + +Now the CSV export. We'll make a small change here. Having to specify the field names here is not ideal. What if we add more field names in the parsing function? We'd have to always remember we need to go and edit the export function as well. If we could figure out the field names in place, we'd remove this dependency. One way would be to infer the field names from dictionary keys of the first row: + +```py +def export_csv(file, data): + # highlight-next-line + fieldnames = list(data[0].keys()) + writer = csv.DictWriter(file, fieldnames=fieldnames) + writer.writeheader() + for row in data: + writer.writerow(row) +``` + +:::note Fragile code + +The code above assumes that the data variable contains at least one item, and that all the items have the same keys. This isn't robust and could break, but in our program this isn't a problem and omitting these corner cases allows us to keep the code examples more succint. + +::: + +Last function we'll add will take care of the JSON export: + +```py +def export_json(file, data): + def serialize(obj): + if isinstance(obj, Decimal): + return str(obj) + raise TypeError("Object not JSON serializable") + + json.dump(data, file, default=serialize) +``` + +Now let's put it all together: + +```py +from decimal import Decimal +import httpx +from bs4 import BeautifulSoup +import csv +import json + +def download(url): + ... + +def parse_product(product): + ... + +def export_csv(file, data): + ... + +def export_json(file, data): + ... + +url = "https://warehouse-theme-metal.myshopify.com/collections/sales" +soup = download(url) +data = [parse_product(product) in soup.select(".product-item")] + +with open("products.csv", "w") as file: + export_csv(file, data) + +with open("products.json", "w") as file: + export_json(file, data) +``` + +The program is much easier to read now. With the `parse_product()` function handy we could also replace the convoluted loop with a [list comprehension](https://docs.python.org/3/tutorial/datastructures.html#list-comprehensions). + +:::tip Refactoring + +We restructured existing code without changing its behavior to improve its structure. This process has a name: [refactoring](https://en.wikipedia.org/wiki/Code_refactoring). ::: From ca7fa13d2c3b21a9d44efb81f865946569a17a11 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 11:27:19 +0200 Subject: [PATCH 04/16] feat: improve the tip about refactoring --- .../09_getting_links.md | 4 +++- .../images/refactoring.gif | Bin 0 -> 3867831 bytes 2 files changed, 3 insertions(+), 1 deletion(-) create mode 100644 sources/academy/webscraping/scraping_basics_python/images/refactoring.gif diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 7002102ca..3415d92a8 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -180,6 +180,8 @@ The program is much easier to read now. With the `parse_product()` function hand :::tip Refactoring -We restructured existing code without changing its behavior to improve its structure. This process has a name: [refactoring](https://en.wikipedia.org/wiki/Code_refactoring). +We turned the whole program upside down, and at the same time, we didn’t make any actual changes! 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+ Solution + + ```py + import httpx + from bs4 import BeautifulSoup + from urllib.parse import urljoin + + listing_url = "https://en.wikipedia.org/wiki/List_of_sovereign_states_and_dependent_territories_in_Africa" + response = httpx.get(listing_url) + response.raise_for_status() + + html_code = response.text + soup = BeautifulSoup(html_code, "html.parser") + + for name_cell in soup.select(".wikitable tr td:nth-child(3)"): + link = name_cell.select_one("a") + url = urljoin(listing_url, link["href"]) + print(url) + ``` + +
+ +### Scrape links to F1 news + +Download Guardian's page with the latest F1 news, use Beautiful Soup to parse it, and print links to all the listed articles. Start with this URL: + +```text +https://www.theguardian.com/sport/formulaone +``` + +Your program should print something like the following: + +```text +https://www.theguardian.com/world/2024/sep/13/africa-f1-formula-one-fans-lewis-hamilton-grand-prix +https://www.theguardian.com/sport/2024/sep/12/mclaren-lando-norris-oscar-piastri-team-orders-f1-title-race-max-verstappen +https://www.theguardian.com/sport/article/2024/sep/10/f1-designer-adrian-newey-signs-aston-martin-deal-after-quitting-red-bull +https://www.theguardian.com/sport/article/2024/sep/02/max-verstappen-damns-his-undriveable-monster-how-bad-really-is-it-and-why +... +``` + +
+ Solution + + ```py + import httpx + from bs4 import BeautifulSoup + from urllib.parse import urljoin + + url = "https://www.theguardian.com/sport/formulaone" + response = httpx.get(url) + response.raise_for_status() + + html_code = response.text + soup = BeautifulSoup(html_code, "html.parser") + + for item in soup.select("#maincontent ul li"): + link = item.select_one("a") + url = urljoin(url, link["href"]) + print(url) + ``` -TODO + Note that some cards contain two links. One leads to the article, and one to the comments. If we selected all the links in the list by `#maincontent ul li a`, we would get incorrect output like this: -### TODO + ```text + https://www.theguardian.com/sport/article/2024/sep/02/example + https://www.theguardian.com/sport/article/2024/sep/02/example#comments + ``` -TODO +
From edb950dec55e4dda0ce1da650f3681e353f3f102 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Mon, 7 Oct 2024 13:53:08 +0200 Subject: [PATCH 15/16] include complete code example --- .../09_getting_links.md | 38 +++++++++++++++++-- 1 file changed, 34 insertions(+), 4 deletions(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 6c2dfd6c6..7f1e28bb9 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -157,16 +157,46 @@ import csv import json def download(url): - ... + response = httpx.get(url) + response.raise_for_status() + + html_code = response.text + return BeautifulSoup(html_code, "html.parser") def parse_product(product): - ... + title = product.select_one(".product-item__title").text.strip() + + price_text = ( + product + .select_one(".price") + .contents[-1] + .strip() + .replace("$", "") + .replace(",", "") + ) + if price_text.startswith("From "): + min_price = Decimal(price_text.removeprefix("From ")) + price = None + else: + min_price = Decimal(price_text) + price = min_price + + return {"title": title, "min_price": min_price, "price": price} def export_csv(file, data): - ... + fieldnames = list(data[0].keys()) + writer = csv.DictWriter(file, fieldnames=fieldnames) + writer.writeheader() + for row in data: + writer.writerow(row) def export_json(file, data): - ... + def serialize(obj): + if isinstance(obj, Decimal): + return str(obj) + raise TypeError("Object not JSON serializable") + + json.dump(data, file, default=serialize, indent=2) listing_url = "https://warehouse-theme-metal.myshopify.com/collections/sales" soup = download(listing_url) From 6ca5b1dc1080a74251e457f63a8219f010618d68 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Thu, 10 Oct 2024 16:04:45 +0200 Subject: [PATCH 16/16] fix: don't use directional language MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Co-authored-by: Michał Olender <92638966+TC-MO@users.noreply.github.com> --- .../webscraping/scraping_basics_python/09_getting_links.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 7f1e28bb9..69c9bcc48 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -244,7 +244,7 @@ def parse_product(product): return {"title": title, "min_price": min_price, "price": price, "url": url} ``` -In the code above, we've also added the URL to the dictionary returned by the function. If we run the scraper now, it should produce exports where each product contains a link to its product page: +In the previous code example, we've also added the URL to the dictionary returned by the function. If we run the scraper now, it should produce exports where each product contains a link to its product page: ```json title=products.json

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zOvw3+EOwI~+f_+cUb*9zW5NGRSiJszQx`3?fHO=a({N+CIN&V#iM^fEViu02pF+zi zs_3GaPTxTWN*gzH{0C22af{NkFPau9Y>s}+Eo#h(XGds(^7bj6qH0&urK@#_QfZk? z$Lzz$ebW5i*Ox3kOqe=vDxsl*=bdVi3BTOPm_W3d89sr+4lYPj zWXiWQj?IiGh#HlkoCl~Xm#Hc;X<7t#hL}Y`rB8XWu?cRL_e46qtz+T=)NH(S5~NhG zWZ(Ouq`-Hnr3ueb-Emm@PIVma$c;VbF%NeHVznm34}S5p&;7cV5QPvcBn$CXg9s$R zVg0W_^0?$B>tR6bAV)gVxz5|pSh(OM>LxSG$rt}1Hx0e$C(ByS8Ij_}@VGHks?_78 gDik9No(qL+`b1eU!66W}PAWk{+_}_pu7CglJLFZI>;M1& literal 0 HcmV?d00001 From a61a33ccb05ef18c0a3537bc193fa262bf044523 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 11:39:59 +0200 Subject: [PATCH 05/16] feat: plan subsequent lesson structure --- .../09_getting_links.md | 26 ++++++++++++++++++- 1 file changed, 25 insertions(+), 1 deletion(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 3415d92a8..0c513b349 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -128,7 +128,7 @@ def export_csv(file, data): :::note Fragile code -The code above assumes that the data variable contains at least one item, and that all the items have the same keys. This isn't robust and could break, but in our program this isn't a problem and omitting these corner cases allows us to keep the code examples more succint. +The code above assumes that the `data` variable contains at least one item, and that all the items have the same keys. This isn't robust and could break, but in our program this isn't a problem and omitting these corner cases allows us to keep the code examples more succint. ::: @@ -185,3 +185,27 @@ We turned the whole program upside down, and at the same time, we didn’t make ![Refactoring](images/refactoring.gif) ::: + +## Locating links + +TODO + +## Extracting links + +TODO + +--- + + + +### TODO + +TODO + +### TODO + +TODO + +### TODO + +TODO From 641cdc897e823a07da7f5d55eb9b0d2d8c0e528c Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 11:40:23 +0200 Subject: [PATCH 06/16] fix: typo --- .../webscraping/scraping_basics_python/09_getting_links.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 0c513b349..e92b00a42 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -128,7 +128,7 @@ def export_csv(file, data): :::note Fragile code -The code above assumes that the `data` variable contains at least one item, and that all the items have the same keys. This isn't robust and could break, but in our program this isn't a problem and omitting these corner cases allows us to keep the code examples more succint. +The code above assumes that the `data` variable contains at least one item, and that all the items have the same keys. This isn't robust and could break, but in our program this isn't a problem and omitting these corner cases allows us to keep the code examples more succinct. ::: From 5caa258155552ce4ff25d0b8a035a82c0b187572 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 12:23:32 +0200 Subject: [PATCH 07/16] feat: extract links --- .../09_getting_links.md | 95 ++++++++++++++++--- 1 file changed, 80 insertions(+), 15 deletions(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index e92b00a42..361df537c 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -12,22 +12,24 @@ import Exercises from './_exercises.mdx'; --- -The previous lesson concludes our effort to create a scraper. Our program now downloads HTML, locates and extracts data from the markup, and saves the data in a structured and reusable way. For some use cases, this is already enough! In other cases, though, scraping just one page is hardly useful. The data is spread across the website, over several pages. +The previous lesson concludes our effort to create a scraper. Our program now downloads HTML, locates and extracts data from the markup, and saves the data in a structured and reusable way. -## Following links +For some use cases, this is already enough! In other cases, though, scraping just one page is hardly useful. The data is spread across the website, over several pages. -We'll use a technique called crawling, i.e. following links and scraping multiple pages. The algorithm goes like this: +## Crawling websites + +We'll use a technique called crawling, i.e. following links to scrape multiple pages. The algorithm goes like this: 1. Visit the start URL. 1. Extract new URLs (and data), and save them. 1. Visit one of the newly found URLs and save data and/or more URLs from it. 1. Repeat 2 and 3 until you have everything you need. -This will help us figure out the actual prices of products, as right now, for some, we're only getting the min price. +This will help us figure out the actual prices of products, as right now, for some, we're only getting the min price. Implementing the algorithm would require quite a few changes to our code though. -## Introducing functions +## Restructuring code -Implementing the algorithm requires quite a few changes to our code. However, over the course of the previous lessons, the code of our program grew to almost 50 lines containing downloading, parsing, and exporting: +Over the course of the previous lessons, the code of our program grew to almost 50 lines containing downloading, parsing, and exporting: ```py from decimal import Decimal @@ -132,7 +134,7 @@ The code above assumes that the `data` variable contains at least one item, and ::: -Last function we'll add will take care of the JSON export: +Last function we'll add will take care of the JSON export. For better readability of the JSON export, let's make a small change here too, and set the indentation level to two spaces: ```py def export_json(file, data): @@ -141,7 +143,8 @@ def export_json(file, data): return str(obj) raise TypeError("Object not JSON serializable") - json.dump(data, file, default=serialize) + # highlight-next-line + json.dump(data, file, default=serialize, indent=2) ``` Now let's put it all together: @@ -165,9 +168,9 @@ def export_csv(file, data): def export_json(file, data): ... -url = "https://warehouse-theme-metal.myshopify.com/collections/sales" -soup = download(url) -data = [parse_product(product) in soup.select(".product-item")] +listing_url = "https://warehouse-theme-metal.myshopify.com/collections/sales" +soup = download(listing_url) +data = [parse_product(product) for product in soup.select(".product-item")] with open("products.csv", "w") as file: export_csv(file, data) @@ -186,13 +189,75 @@ We turned the whole program upside down, and at the same time, we didn’t make ::: -## Locating links +## Extracting links -TODO +With everything in place, we can now start working towards a scraper which scrapes also the product pages. For that we'll need links of those pages. Let's open browser DevTools and remind ourselves about the structure of a single product item: -## Extracting links +![Product card's child elements](./images/child-elements.png) -TODO +Several ways how to transition from one page to another exist, but the most common one is a link tag, which looks like this: + +```html +Text of the link +``` + +In DevTools we can see that each product title is in fact also a link tag. We already locate the titles, so that makes our task easier. We only need to modify the code in a way that it extracts not only the text of the element, but also the `href` attribute. Beautiful Soup elements support accessing attributes as if they were dictionary keys: + +```py +def parse_product(product): + # highlight-next-line + title_element = product.select_one(".product-item__title") + # highlight-next-line + title = title_element.text.strip() + # highlight-next-line + url = title_element["href"] + + price_text = ( + product + .select_one(".price") + .contents[-1] + .strip() + .replace("$", "") + .replace(",", "") + ) + if price_text.startswith("From "): + min_price = Decimal(price_text.removeprefix("From ")) + price = None + else: + min_price = Decimal(price_text) + price = min_price + + # highlight-next-line + return {"title": title, "min_price": min_price, "price": price, "url": url} +``` + +In the code above we've also already added the URL to the dictionary returned by the function. If we run the scraper now, it should produce exports where each product contains also a link to its product page: + +```json +[ + { + "title": "JBL Flip 4 Waterproof Portable Bluetooth Speaker", + "min_price": "74.95", + "price": "74.95", + "url": "/products/jbl-flip-4-waterproof-portable-bluetooth-speaker" + }, + { + "title": "Sony XBR-950G BRAVIA 4K HDR Ultra HD TV", + "min_price": "1398.00", + "price": null, + "url": "/products/sony-xbr-65x950g-65-class-64-5-diag-bravia-4k-hdr-ultra-hd-tv" + }, + ... +] +``` + +Hmm, but that isn't what we wanted! Where is the beginning of each URL? It turns out the HTML contains so called relative links. + +## Processing relative links + +Browsers reading the HTML know the base address and automatically resolve such links, but we'll have to do this manually. + +... --- From 583a4bd9d069b8ccfed816fde2aee2ee2c084dac Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 12:37:34 +0200 Subject: [PATCH 08/16] feat: deal with relative links --- .../07_extracting_data.md | 4 +- .../09_getting_links.md | 80 ++++++++++++++----- 2 files changed, 60 insertions(+), 24 deletions(-) diff --git a/sources/academy/webscraping/scraping_basics_python/07_extracting_data.md b/sources/academy/webscraping/scraping_basics_python/07_extracting_data.md index 48e4b0d2e..676b82b01 100644 --- a/sources/academy/webscraping/scraping_basics_python/07_extracting_data.md +++ b/sources/academy/webscraping/scraping_basics_python/07_extracting_data.md @@ -163,9 +163,9 @@ Great! Only if we didn't overlook an important pitfall called [floating-point er These errors are small and usually don't matter, but sometimes they can add up and cause unpleasant discrepancies. That's why it's typically best to avoid `float()` when working with money. Let's instead use Python's built-in [`Decimal()`](https://docs.python.org/3/library/decimal.html) type: ```py -from decimal import Decimal import httpx from bs4 import BeautifulSoup +from decimal import Decimal url = "https://warehouse-theme-metal.myshopify.com/collections/sales" response = httpx.get(url) @@ -323,8 +323,8 @@ Hints: ```py import httpx - from datetime import datetime from bs4 import BeautifulSoup + from datetime import datetime url = "https://www.theguardian.com/sport/formulaone" response = httpx.get(url) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 361df537c..3835a6302 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -32,9 +32,9 @@ This will help us figure out the actual prices of products, as right now, for so Over the course of the previous lessons, the code of our program grew to almost 50 lines containing downloading, parsing, and exporting: ```py -from decimal import Decimal import httpx from bs4 import BeautifulSoup +from decimal import Decimal import csv import json @@ -150,9 +150,9 @@ def export_json(file, data): Now let's put it all together: ```py -from decimal import Decimal import httpx from bs4 import BeautifulSoup +from decimal import Decimal import csv import json @@ -205,29 +205,12 @@ In DevTools we can see that each product title is in fact also a link tag. We al ```py def parse_product(product): - # highlight-next-line title_element = product.select_one(".product-item__title") - # highlight-next-line title = title_element.text.strip() - # highlight-next-line url = title_element["href"] - price_text = ( - product - .select_one(".price") - .contents[-1] - .strip() - .replace("$", "") - .replace(",", "") - ) - if price_text.startswith("From "): - min_price = Decimal(price_text.removeprefix("From ")) - price = None - else: - min_price = Decimal(price_text) - price = min_price + ... - # highlight-next-line return {"title": title, "min_price": min_price, "price": price, "url": url} ``` @@ -255,9 +238,62 @@ Hmm, but that isn't what we wanted! Where is the beginning of each URL? It turns ## Processing relative links -Browsers reading the HTML know the base address and automatically resolve such links, but we'll have to do this manually. +Browsers reading the HTML know the base address and automatically resolve such links, but we'll have to do this manually. Function [`urljoin`](https://docs.python.org/3/library/urllib.parse.html#urllib.parse.urljoin) from the Python's standard library will help us. Let's add it to our imports first: + +```py +import httpx +from bs4 import BeautifulSoup +from decimal import Decimal +import csv +import json +# highlight-next-line +from urllib.parse import urljoin +``` + +Next, we'll change the `parse_product()` function so that it also takes the base URL as an argument, and then joins it with the relative URL to the product page: + +```py +# highlight-next-line +def parse_product(product, base_url): + title_element = product.select_one(".product-item__title") + title = title_element.text.strip() + # highlight-next-line + url = urljoin(base_url, title_element["href"]) + + ... + + return {"title": title, "min_price": min_price, "price": price, "url": url} +``` + +Now we'll pass the base URL to the function in the main body of our program: + +```py +listing_url = "https://warehouse-theme-metal.myshopify.com/collections/sales" +soup = download(listing_url) +data = [parse_product(product, listing_url) for product in soup.select(".product-item")] +``` + +When we run the scraper now, we should see full URLs in our exports: + +```json +[ + { + "title": "JBL Flip 4 Waterproof Portable Bluetooth Speaker", + "min_price": "74.95", + "price": "74.95", + "url": "https://warehouse-theme-metal.myshopify.com/products/jbl-flip-4-waterproof-portable-bluetooth-speaker" + }, + { + "title": "Sony XBR-950G BRAVIA 4K HDR Ultra HD TV", + "min_price": "1398.00", + "price": null, + "url": "https://warehouse-theme-metal.myshopify.com/products/sony-xbr-65x950g-65-class-64-5-diag-bravia-4k-hdr-ultra-hd-tv" + }, + ... +] +``` -... +Tada! We managed to get links to the product pages. In the next lesson we'll crawl these URLs so that we can have more details about the products in our dataset. --- From eafbd7da1ca7a00d0908894a74bea70d67ecfb94 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 12:38:32 +0200 Subject: [PATCH 09/16] chore: skip linting incomplete JSON --- .../webscraping/scraping_basics_python/09_getting_links.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 3835a6302..f80a85c3a 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -216,6 +216,7 @@ def parse_product(product): In the code above we've also already added the URL to the dictionary returned by the function. If we run the scraper now, it should produce exports where each product contains also a link to its product page: + ```json [ { @@ -275,6 +276,7 @@ data = [parse_product(product, listing_url) for product in soup.select(".product When we run the scraper now, we should see full URLs in our exports: + ```json [ { From 13939042d929290fbe2921195f243a6d4586d348 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 12:50:06 +0200 Subject: [PATCH 10/16] feat: add file titles --- .../webscraping/scraping_basics_python/09_getting_links.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index f80a85c3a..f90b5b9e5 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -217,7 +217,7 @@ def parse_product(product): In the code above we've also already added the URL to the dictionary returned by the function. If we run the scraper now, it should produce exports where each product contains also a link to its product page: -```json +```json title=products.json [ { "title": "JBL Flip 4 Waterproof Portable Bluetooth Speaker", @@ -277,7 +277,7 @@ data = [parse_product(product, listing_url) for product in soup.select(".product When we run the scraper now, we should see full URLs in our exports: -```json +```json title=products.json [ { "title": "JBL Flip 4 Waterproof Portable Bluetooth Speaker", From 7cb2aa64791ab0463f6bca470f1b0ad61b1d0e9e Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 12:50:54 +0200 Subject: [PATCH 11/16] style: better heading --- .../webscraping/scraping_basics_python/09_getting_links.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index f90b5b9e5..6ff840a57 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -237,7 +237,7 @@ In the code above we've also already added the URL to the dictionary returned by Hmm, but that isn't what we wanted! Where is the beginning of each URL? It turns out the HTML contains so called relative links. -## Processing relative links +## Turning relative links into absolute Browsers reading the HTML know the base address and automatically resolve such links, but we'll have to do this manually. Function [`urljoin`](https://docs.python.org/3/library/urllib.parse.html#urllib.parse.urljoin) from the Python's standard library will help us. Let's add it to our imports first: From 419186588e2fad8797c3e28590722d8cda7f5211 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 12:58:06 +0200 Subject: [PATCH 12/16] feat: small bits --- .../webscraping/scraping_basics_python/09_getting_links.md | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index 6ff840a57..dc810f097 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -271,6 +271,7 @@ Now we'll pass the base URL to the function in the main body of our program: ```py listing_url = "https://warehouse-theme-metal.myshopify.com/collections/sales" soup = download(listing_url) +# highlight-next-line data = [parse_product(product, listing_url) for product in soup.select(".product-item")] ``` @@ -295,7 +296,7 @@ When we run the scraper now, we should see full URLs in our exports: ] ``` -Tada! We managed to get links to the product pages. In the next lesson we'll crawl these URLs so that we can have more details about the products in our dataset. +Ta-da! We managed to get links leading to the product pages. In the next lesson we'll crawl these URLs so that we can have more details about the products in our dataset. --- From 6ad4813f287a7a862c7e11c729b158f969d765ff Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 14:31:58 +0200 Subject: [PATCH 13/16] fix: improve English --- .../09_getting_links.md | 34 +++++++++---------- 1 file changed, 17 insertions(+), 17 deletions(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index dc810f097..ed0e5db8a 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -23,9 +23,9 @@ We'll use a technique called crawling, i.e. following links to scrape multiple p 1. Visit the start URL. 1. Extract new URLs (and data), and save them. 1. Visit one of the newly found URLs and save data and/or more URLs from it. -1. Repeat 2 and 3 until you have everything you need. +1. Repeat steps 2 and 3 until you have everything you need. -This will help us figure out the actual prices of products, as right now, for some, we're only getting the min price. Implementing the algorithm would require quite a few changes to our code though. +This will help us figure out the actual prices of products, as right now, for some, we're only getting the min price. Implementing the algorithm will require quite a few changes to our code, though. ## Restructuring code @@ -81,7 +81,7 @@ with open("products.json", "w") as file: json.dump(data, file, default=serialize) ``` -Let's introduce several functions which will make the whole thing easier to digest. First, we can turn the beginning of our program into this `download()` function, which takes a URL and returns a `BeautifulSoup` instance: +Let's introduce several functions to make the whole thing easier to digest. First, we can turn the beginning of our program into this `download()` function, which takes a URL and returns a `BeautifulSoup` instance: ```py def download(url): @@ -92,7 +92,7 @@ def download(url): return BeautifulSoup(html_code, "html.parser") ``` -Next, we can put parsing to a `parse_product()` function, which takes the product item element, and returns the dictionary with data: +Next, we can put parsing into a `parse_product()` function, which takes the product item element and returns the dictionary with data: ```py def parse_product(product): @@ -116,7 +116,7 @@ def parse_product(product): return {"title": title, "min_price": min_price, "price": price} ``` -Now the CSV export. We'll make a small change here. Having to specify the field names here is not ideal. What if we add more field names in the parsing function? We'd have to always remember we need to go and edit the export function as well. If we could figure out the field names in place, we'd remove this dependency. One way would be to infer the field names from dictionary keys of the first row: +Now the CSV export. We'll make a small change here. Having to specify the field names is not ideal. What if we add more field names in the parsing function? We'd always have to remember to go and edit the export function as well. If we could figure out the field names in place, we'd remove this dependency. One way would be to infer the field names from the dictionary keys of the first row: ```py def export_csv(file, data): @@ -130,11 +130,11 @@ def export_csv(file, data): :::note Fragile code -The code above assumes that the `data` variable contains at least one item, and that all the items have the same keys. This isn't robust and could break, but in our program this isn't a problem and omitting these corner cases allows us to keep the code examples more succinct. +The code above assumes the `data` variable contains at least one item, and that all the items have the same keys. This isn't robust and could break, but in our program, this isn't a problem, and omitting these corner cases allows us to keep the code examples more succinct. ::: -Last function we'll add will take care of the JSON export. For better readability of the JSON export, let's make a small change here too, and set the indentation level to two spaces: +The last function we'll add will take care of the JSON export. For better readability of the JSON export, let's make a small change here too and set the indentation level to two spaces: ```py def export_json(file, data): @@ -179,11 +179,11 @@ with open("products.json", "w") as file: export_json(file, data) ``` -The program is much easier to read now. With the `parse_product()` function handy we could also replace the convoluted loop with a [list comprehension](https://docs.python.org/3/tutorial/datastructures.html#list-comprehensions). +The program is much easier to read now. With the `parse_product()` function handy, we could also replace the convoluted loop with a [list comprehension](https://docs.python.org/3/tutorial/datastructures.html#list-comprehensions). :::tip Refactoring -We turned the whole program upside down, and at the same time, we didn’t make any actual changes! This is [refactoring](https://en.wikipedia.org/wiki/Code_refactoring): improving the structure of existing code without changing its behavior. +We turned the whole program upside down, and at the same time, we didn't make any actual changes! This is [refactoring](https://en.wikipedia.org/wiki/Code_refactoring): improving the structure of existing code without changing its behavior. ![Refactoring](images/refactoring.gif) @@ -191,17 +191,17 @@ We turned the whole program upside down, and at the same time, we didn’t make ## Extracting links -With everything in place, we can now start working towards a scraper which scrapes also the product pages. For that we'll need links of those pages. Let's open browser DevTools and remind ourselves about the structure of a single product item: +With everything in place, we can now start working on a scraper that also scrapes the product pages. For that, we'll need the links to those pages. Let's open the browser DevTools and remind ourselves of the structure of a single product item: ![Product card's child elements](./images/child-elements.png) -Several ways how to transition from one page to another exist, but the most common one is a link tag, which looks like this: +Several methods exist for transitioning from one page to another, but the most common is a link tag, which looks like this: ```html Text of the link ``` -In DevTools we can see that each product title is in fact also a link tag. We already locate the titles, so that makes our task easier. We only need to modify the code in a way that it extracts not only the text of the element, but also the `href` attribute. Beautiful Soup elements support accessing attributes as if they were dictionary keys: +In DevTools, we can see that each product title is, in fact, also a link tag. We already locate the titles, so that makes our task easier. We just need to edit the code so that it extracts not only the text of the element but also the `href` attribute. Beautiful Soup elements support accessing attributes as if they were dictionary keys: ```py def parse_product(product): @@ -214,7 +214,7 @@ def parse_product(product): return {"title": title, "min_price": min_price, "price": price, "url": url} ``` -In the code above we've also already added the URL to the dictionary returned by the function. If we run the scraper now, it should produce exports where each product contains also a link to its product page: +In the code above, we've also added the URL to the dictionary returned by the function. If we run the scraper now, it should produce exports where each product contains a link to its product page: ```json title=products.json @@ -235,11 +235,11 @@ In the code above we've also already added the URL to the dictionary returned by ] ``` -Hmm, but that isn't what we wanted! Where is the beginning of each URL? It turns out the HTML contains so called relative links. +Hmm, but that isn't what we wanted! Where is the beginning of each URL? It turns out the HTML contains so-called relative links. ## Turning relative links into absolute -Browsers reading the HTML know the base address and automatically resolve such links, but we'll have to do this manually. Function [`urljoin`](https://docs.python.org/3/library/urllib.parse.html#urllib.parse.urljoin) from the Python's standard library will help us. Let's add it to our imports first: +Browsers reading the HTML know the base address and automatically resolve such links, but we'll have to do this manually. The function [`urljoin`](https://docs.python.org/3/library/urllib.parse.html#urllib.parse.urljoin) from Python's standard library will help us. Let's add it to our imports first: ```py import httpx @@ -251,7 +251,7 @@ import json from urllib.parse import urljoin ``` -Next, we'll change the `parse_product()` function so that it also takes the base URL as an argument, and then joins it with the relative URL to the product page: +Next, we'll change the `parse_product()` function so that it also takes the base URL as an argument and then joins it with the relative URL to the product page: ```py # highlight-next-line @@ -296,7 +296,7 @@ When we run the scraper now, we should see full URLs in our exports: ] ``` -Ta-da! We managed to get links leading to the product pages. In the next lesson we'll crawl these URLs so that we can have more details about the products in our dataset. +Ta-da! We've managed to get links leading to the product pages. In the next lesson, we'll crawl these URLs so that we can gather more details about the products in our dataset. --- From 5aa5d4307eb2c90fac60bddf531b784f7f387a48 Mon Sep 17 00:00:00 2001 From: Honza Javorek Date: Fri, 13 Sep 2024 14:55:09 +0200 Subject: [PATCH 14/16] feat: add exercises --- .../09_getting_links.md | 89 +++++++++++++++++-- 1 file changed, 83 insertions(+), 6 deletions(-) diff --git a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md index ed0e5db8a..6c2dfd6c6 100644 --- a/sources/academy/webscraping/scraping_basics_python/09_getting_links.md +++ b/sources/academy/webscraping/scraping_basics_python/09_getting_links.md @@ -302,14 +302,91 @@ Ta-da! We've managed to get links leading to the product pages. In the next less -### TODO +### Scrape links to countries in Africa -TODO +Download Wikipedia's page with the list of African countries, use Beautiful Soup to parse it, and print links to Wikipedia pages of all the states and territories mentioned in all tables. Start with this URL: -### TODO +```text +https://en.wikipedia.org/wiki/List_of_sovereign_states_and_dependent_territories_in_Africa +``` + +Your program should print the following: + +```text +https://en.wikipedia.org/wiki/Algeria +https://en.wikipedia.org/wiki/Angola +https://en.wikipedia.org/wiki/Benin +https://en.wikipedia.org/wiki/Botswana +... +``` + +

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