research-data-science-training/python-workshops/webscraping-introduction/01-gazpacho-basics.qmd at main · PovertyAction/research-data-science-training · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
---
title: "Getting Started with Gazpacho"
abstract: |
  Learn the fundamentals of gazpacho, a simple Python library for web scraping. Install the library, understand basic concepts, and write your first web scraping script.
date: last-modified

format:
  html: default

# Authors
authors:
  - "[Niall Keleher](https://poverty-action.org/people/niall-keleher)"

# # Contributors
# contributors:
#   - "[Contributor Name](https://poverty-action.org/people/contributor_name)"

keywords: ["Python", "Web Scraping", "Gazpacho", "Installation", "HTML", "HTTP Requests", "Tutorial"]
license: "CC BY 4.0"
---

::: {.callout-note}

## Learning Objectives

- Install and configure gazpacho for web scraping
- Understand basic HTML structure and web scraping concepts
- Make your first HTTP request using gazpacho.get()
- Handle common installation and certificate issues
- Write a simple web scraping script
- Understand the difference between HTML and text content
:::

::: {.callout-tip}

## Key Questions

- How do I install and set up gazpacho?
- What is HTML and how does web scraping work?
- How do I make basic HTTP requests to fetch web pages?
- What common issues might I encounter and how do I fix them?
:::

::: {.callout-note}

## Attribution

This tutorial is based on concepts from the [gazpacho library](https://github.com/maxhumber/gazpacho) by Max Humber (MIT License) and the [calmcode.io gazpacho course](https://calmcode.io/course/gazpacho/introduction) (CC BY 4.0 License).
:::

## What is Gazpacho?

Gazpacho is a lightweight Python library designed to make web scraping simple and accessible. Unlike more complex alternatives like requests + BeautifulSoup, gazpacho provides a streamlined API for common web scraping tasks.

**Key benefits of gazpacho**:

- **Simple syntax**: Minimal code to get started
- **Built-in HTTP handling**: No need for separate requests library
- **Intuitive parsing**: Easy-to-understand methods for data extraction
- **Lightweight**: Fast and efficient for basic scraping needs

### Web Scraping Fundamentals

Before diving into gazpacho, let's understand what happens when we scrape a website:

1. **HTTP Request**: Your script requests a webpage from a server
2. **HTML Response**: The server returns HTML content
3. **HTML Parsing**: Your script extracts data from the HTML structure
4. **Data Processing**: Convert extracted data into usable formats

## Installation and Setup

### Installing Gazpacho

Install gazpacho using pip:

```bash
pip install gazpacho
```

**Verify installation**:

```python
import gazpacho
print(gazpacho.__version__)
```

### Common Installation Issues

#### Certificate Verification Errors (macOS)

If you encounter SSL certificate errors, try one of these solutions:

#### Solution 1: Install certifi

```bash
pip install certifi
```

#### Solution 2: Update certificates (macOS)

```bash
/Applications/Python\ 3.x/Install\ Certificates.command
```

Replace `3.x` with your Python version (e.g., `3.9`, `3.10`).

::: {.callout-note}

## Try This: Test Your Installation

Create a simple test file to verify gazpacho works:

```python
# test_gazpacho.py
from gazpacho import get

# Test with a simple webpage
url = "https://httpbin.org/html"
html = get(url)
print("Installation successful!")
print(f"Fetched {len(html)} characters of HTML")
```

Run this script to confirm everything is working properly.
:::

## Understanding HTML Structure

Web scraping requires basic understanding of HTML (HyperText Markup Language).

### HTML Basics

HTML uses **tags** to structure content:

```html
<!DOCTYPE html>
<html>
<head>
    <title>Page Title</title>
</head>
<body>
    <h1>Main Heading</h1>
    <p>This is a paragraph.</p>
    <ul>
        <li>List item 1</li>
        <li>List item 2</li>
    </ul>
</body>
</html>
```

### Common HTML Elements

**Text elements**:

- `<h1>`, `<h2>`, etc.: Headings
- `<p>`: Paragraphs
- `<span>`: Inline text

**Structure elements**:

- `<div>`: Block containers
- `<ul>`, `<ol>`: Lists
- `<li>`: List items

**Data elements**:

- `<table>`: Tables
- `<tr>`: Table rows
- `<td>`: Table cells

### HTML Attributes

Elements can have attributes that provide additional information:

```html
<div class="content" id="main">
<a href="https://example.com">Link</a>
<img src="image.jpg" alt="Description">
```

Common attributes:

- `class`: CSS styling class
- `id`: Unique identifier
- `href`: Link destination
- `src`: Source for images/media

## Your First Web Scraping Script

### Making HTTP Requests with gazpacho.get()

The `get()` function is gazpacho's primary method for fetching web pages:

```python
from gazpacho import get

# Fetch a webpage
url = "https://example.com"
html = get(url)
```

### Practical Example: Scraping a Simple Page

Let's scrape a page with structured data:

```python
from gazpacho import get

# Target a page with structured content
url = "https://httpbin.org/html"
html = get(url)

# Display the raw HTML
print("Raw HTML content:")
print(html[:500])  # First 500 characters
print("...")
```

### Understanding the Response

The `get()` function returns the raw HTML as a string:

```python
from gazpacho import get

html = get("https://httpbin.org/html")

# Check what we received
print(f"Type: {type(html)}")
print(f"Length: {len(html)} characters")
print(f"First 100 chars: {html[:100]}")
```

::: {.callout-note}

## Try This: Explore Different Websites

Try fetching HTML from different websites to see various HTML structures:

```python
from gazpacho import get

# Try different sites
sites = [
    "https://httpbin.org/html",
    "https://example.com",
    "https://httpbin.org/json"  # This returns JSON, not HTML
]

for site in sites:
    try:
        html = get(site)
        print(f"\n{site}:")
        print(f"Length: {len(html)} characters")
        print(f"First 100 chars: {html[:100]}")
    except Exception as e:
        print(f"Error fetching {site}: {e}")
```

:::

## Error Handling and Debugging

### Common HTTP Errors

**404 Not Found**:

```python
from gazpacho import get

try:
    html = get("https://example.com/nonexistent-page")
except Exception as e:
    print(f"Error: {e}")
```

**Connection Errors**:

```python
from gazpacho import get
import time

def safe_get(url, max_retries=3):
    for attempt in range(max_retries):
        try:
            return get(url)
        except Exception as e:
            print(f"Attempt {attempt + 1} failed: {e}")
            if attempt < max_retries - 1:
                time.sleep(2)  # Wait before retry
            else:
                raise e

# Use safe_get for unreliable connections
html = safe_get("https://example.com")
```

### Debugging Tips

**Inspect HTML structure**:

```python
from gazpacho import get

html = get("https://example.com")

# Save HTML to file for inspection
with open("scraped_page.html", "w", encoding="utf-8") as f:
    f.write(html)

print("HTML saved to scraped_page.html for inspection")
```

**Check response content**:

```python
from gazpacho import get

html = get("https://httpbin.org/html")

# Look for specific content
if "<title>" in html:
    print("Found title tag")
if "<!DOCTYPE html>" in html:
    print("Valid HTML document")
```

## Practical Example: Scraping Real Data

Let's put it all together with a practical example:

```python
from gazpacho import get
import re

def scrape_page_title(url):
    """Extract the title from a webpage."""
    try:
        # Fetch the HTML
        html = get(url)

        # Find the title using regex
        title_match = re.search(r'<title>(.*?)</title>', html, re.IGNORECASE)

        if title_match:
            title = title_match.group(1).strip()
            return title
        else:
            return "No title found"

    except Exception as e:
        return f"Error: {e}"

# Test with different websites
urls = [
    "https://example.com",
    "https://httpbin.org/html",
    "https://python.org"
]

for url in urls:
    title = scrape_page_title(url)
    print(f"{url}: {title}")
```

::: {.callout-note}

## Try This: Extract Multiple Elements

Practice extracting different HTML elements:

```python
from gazpacho import get
import re

def analyze_webpage(url):
    """Analyze basic elements of a webpage."""
    html = get(url)

    # Count different elements
    title_count = len(re.findall(r'<title>', html, re.IGNORECASE))
    h1_count = len(re.findall(r'<h1>', html, re.IGNORECASE))
    p_count = len(re.findall(r'<p>', html, re.IGNORECASE))
    link_count = len(re.findall(r'<a\s+[^>]*href', html, re.IGNORECASE))

    print(f"Analysis of {url}:")
    print(f"  Titles: {title_count}")
    print(f"  H1 tags: {h1_count}")
    print(f"  Paragraphs: {p_count}")
    print(f"  Links: {link_count}")

# Analyze different pages
analyze_webpage("https://example.com")
```

:::

## Best Practices for HTTP Requests

### Respectful Scraping

**Add delays between requests**:

```python
from gazpacho import get
import time

def polite_scraper(urls, delay=1):
    """Scrape multiple URLs with delays."""
    results = []

    for url in urls:
        print(f"Scraping {url}...")
        html = get(url)
        results.append(html)

        # Be polite - wait between requests
        time.sleep(delay)

    return results

urls = ["https://example.com", "https://httpbin.org/html"]
pages = polite_scraper(urls, delay=2)
```

### User Agent Headers

While gazpacho handles basic headers automatically, understanding user agents is important:

```python
# Gazpacho automatically sets appropriate headers
# but you can still inspect what was sent
from gazpacho import get

html = get("https://httpbin.org/user-agent")
print("User agent information:")
print(html)
```

## Troubleshooting Common Issues

### Issue: "Module not found" Error

**Solution**: Ensure gazpacho is installed in the correct Python environment

```bash
python -m pip install gazpacho
# or
pip3 install gazpacho
```

### Issue: Certificate Verification Failed

**Solution**: Install certifi or update certificates

```bash
pip install certifi
```

### Issue: Connection Timeout

**Solution**: Implement retry logic with delays

```python
from gazpacho import get
import time

def robust_get(url, retries=3, delay=2):
    for i in range(retries):
        try:
            return get(url)
        except Exception as e:
            if i < retries - 1:
                time.sleep(delay)
                continue
            else:
                raise e
```

::: {.callout-note}

## Exercise: Build Your First Scraper

Create a script that:

1. Fetches a webpage of your choice
2. Checks if the request was successful
3. Extracts and displays the page title
4. Counts the number of links on the page
5. Saves the HTML to a file for inspection

```python
from gazpacho import get
import re

def my_first_scraper(url):
    """A complete first scraper example."""
    try:
        # Step 1: Fetch the webpage
        print(f"Fetching {url}...")
        html = get(url)

        # Step 2: Check if successful
        if not html:
            print("Failed to fetch content")
            return

        print(f"Successfully fetched {len(html)} characters")

        # Step 3: Extract title
        title_match = re.search(r'<title>(.*?)</title>', html, re.IGNORECASE)
        title = title_match.group(1).strip() if title_match else "No title"
        print(f"Page title: {title}")

        # Step 4: Count links
        links = re.findall(r'<a\s+[^>]*href', html, re.IGNORECASE)
        print(f"Number of links: {len(links)}")

        # Step 5: Save HTML
        filename = f"scraped_{url.split('//')[1].replace('/', '_')}.html"
        with open(filename, 'w', encoding='utf-8') as f:
            f.write(html)
        print(f"HTML saved to {filename}")

    except Exception as e:
        print(f"Error: {e}")

# Test your scraper
my_first_scraper("https://example.com")
```

:::

## Next Steps

Now that you understand gazpacho basics and can make HTTP requests, you're ready to learn more advanced parsing techniques. In the next tutorial, we'll explore how to extract specific data from HTML using gazpacho's parsing capabilities.

::: {.callout-important}

## Key Points

- Gazpacho simplifies web scraping with an intuitive API
- The `get()` function fetches HTML content from URLs
- Always handle errors and implement retry logic
- Understanding basic HTML structure is essential
- Be respectful with request timing and frequency
- Save scraped content for debugging and analysis
- Practice with simple examples before tackling complex sites
:::

[← Previous: Introduction](index.qmd) | [Next: Getting Data →](02-getting-data.qmd)