prompter: How do I create a website data scraper in Python? I want you to write an example Python 3 file that, when run, extracts the textual content from any website.

assistant: Below is an example of a Python 3 file that can be used as a website data scraper. This example uses the requests and BeautifulSoup libraries to extract the textual content from any website.

# Import the libraries
import requests
from bs4 import BeautifulSoup

# Specify the URL of the website
url = 'http://example.com'

# Create a GET request to the URL
response = requests.get(url)

# Parse the response into HTML
soup = BeautifulSoup(response.text, 'html.parser')

# Extract the textual content from the response
text = soup.get_text()

# Print the text
print(text)

prompter: Modify the example to be in the form of a web application which takes user input to specify the URL to scrape and then prints the scraped text to the user after they click the Submit button.

prompter: Please modify the script to save the extracted text as a file in the results subdirectory, that lives in the same directory as the script.
Also add error handling please.

assistant: To extract textual content from a website using Python, you can use the BeautifulSoup library along with the requests library. Here is an example that demonstrates how to extract all the text from a website:

```python
import requests
from bs4 import BeautifulSoup

# Make a request to the website
url = 'https://www.example.com'
response = requests.get(url)

# Check if the request was successful
if response.status_code == 200:
    # Parse the HTML content of the page
    soup = BeautifulSoup(response.content, 'html.parser')

    # Find all the text in the page
    text = soup.get_text()
    
    # Print the extracted text
    print(text)
else:
    print(f'Request failed with status code {response.status_code}')

```

This code uses the `requests.get` function to make a GET request to the website, and then it uses the `BeautifulSoup` library to parse the HTML content of the page and extract all the text. Finally, it prints the extracted text.

assistant: One way to scrape data from a website in python is to use selenium. Selenium is a package that allows you to control and extract data from a web browser.

1. Install the selenium package

You can use the pip command to install selenium:
```sh
pip install selenium
```

2. Download the web driver for your browser and put it in your project directory
Mozilla Firefox - https://github.com/mozilla/geckodriver/releases/latest
Google Chrome - https://chromedriver.chromium.org/downloads
Microsoft Edge - https://developer.microsoft.com/microsoft-edge/tools/webdriver

3. import selenium

```python
from selenium.webdriver.chrome.service import Service
from selenium.webdriver.common.by import By
from selenium import webdriver
from time import sleep

service = Service(executable_path="/path/to/chromedriver")
driver = webdriver.Chrome(service=service)
```
Please note that the "Service" import may differ depending on what driver you are using.

4. opening a webpage

```python
driver.get("https://www.example.com")
sleep(3)
```
You should see your browser open, display example.com and close 3 seconds later.

5. reading webpage content

 you can use the driver.find_element function to find elements and read their contents, here is an example on how to do so:
```python
h1_elements = driver.find_elements(By.TAG_NAME, "h1")
print("all h1 elements:")
for element in h1_elements:
   print(element.text)
```

Beware that many websites do not want their content to be scraped, you should always be careful when scraping data, and always respect the choices of the website owners.

prompter: what is pip command?

assistant: pip is the package installer for Python. You can simply install or upgrade the Python package using it. In this case you have to open your command prompt and type in "pip install -U selenium" to install selenium.

assistant: a pip command is a command in python that manages the installed packages available to python on your computer (or virtual machine).
pip stands for preferred installer program and allows the programmer to add, modify or installed packages in python

assistant: First, you need to make an http/s request to the website. For this you could use the standard http.client. Here is the relevant documentation https://docs.python.org/3/library/http.client.html
Tweaking the Example code slightly we can obtain:
```py
import http.client
conn = http.client.HTTPSConnection("www.python.org") # Replace this URL with your target site's base name.
conn.request("GET", "/") # Here qui can request a specific page / resource.
r1 = conn.getresponse()
data1 = r1.read()  # Read the entire response.
```

After that you would need an HTML parser, such can be found in the standard http.parser. Here is the relevant documentation https://docs.python.org/3.8/library/html.parser.html
Once again, tweaking the example code slightly we can obtain:
```py
from html.parser import HTMLParser

class MyHTMLParser(HTMLParser):
    def handle_starttag(self, tag, attrs):
        pass # We are not interested in the opening tags

    def handle_endtag(self, tag):
        pass # We are not interested in the closing tags

    def handle_data(self, data):
        print(data) # We are interested in the content of the tags

## Example usage
parser = MyHTMLParser()
parser.feed('<html><head><title>Test</title></head>'
            '<body><h1>Parse me!</h1></body></html>')
```

To finalize the extraction you could integrate both programs by making the parser parse the data from the first program.
Some further considerations are required though.
Not all data in HTML elements is shown as text always. For example text inside a noscript tag would only be shown if the browser does not support javascript.
Also, you would need to take into account the CSS as this can make certain elements invisible.

A possible approach is to filter by tag and only print the data if the tag is one of a list.

To do this you could use a stack to keep track of the current tag.
In the starttag you would push elements on and on the endtag you could pop elements off.
In this way the data method would know which tag it is currently in.

Then you could have a list of valid tagnames that are used to determine if the data is relevant.

I.E.

```py
import http.client
from html.parser import HTMLParser
conn = http.client.HTTPSConnection("www.python.org") # Replace this URL with your target site's base name.
conn.request("GET", "/") # Here qui can request a specific page / resource.
response = conn.getresponse()
responseData = response.read()  # Read the entire response.

class MyHTMLParser(HTMLParser):
    elementStack = ["base"]
    validElements = ["p", "h1", "h2"] # TODO: Add more valid elements
    def handle_starttag(self, tag, attrs):
        elementStack.append(tag)

    def handle_endtag(self, tag):
        elementStack.pop()

    def handle_data(self, data):
        if (elementStack[-1] in validElements):
            print(data) # We are interested in the content of the tag

parser = MyHTMLParser()
parser.feed(responseData)
```

assistant: Write the following code in a file called `scrap.py`:

```python
import sys
import requests
from bs4 import BeautifulSoup

def scrap(url: str) -> str:
    # Download the page with an HTTP GET.
    response = requests.get(url)
    if response.status_code == 200:
        # Extract text from the page’s HTML.
        return BeautifulSoup(response.content, 'html.parser').get_text()
    else:
        raise Exception(f"scrap: fetching URL {url} failed with error {response.status_code}")

if __name__ == '__main__':
    print(scrap(sys.argv[1]))
```

You can run it in your terminal with the command `python3 scrap.py https://example.com`.

prompter: Could you also rewrite the code to handle status codes other than 200 as well?