Week 7: Working with External Data
with open() context managerwith?: Automatically closes the file even if errors occur"r" (read), "w" (write/overwrite), "a" (append)with - prevents file corruption and resource leaks# Saving a contact list to a text file - messy!
with open("contacts.txt", "w") as f:
f.write("Alice|alice@example.com|555-1234\n")
f.write("Bob|bob@example.com|555-5678\n")
# Reading it back - lots of manual parsing
with open("contacts.txt", "r") as f:
for line in f:
parts = line.strip().split("|")
name, email, phone = parts
print(f"{name}: {email}")|), fragile parsing, no nested data, no type info|? What about optional fields? Nested addresses?| JSON Type | Python Type | Example |
|---|---|---|
Object {} |
Dictionary | {"name": "Alice", "age": 30} |
Array [] |
List | [1, 2, 3, 4, 5] |
| String | String | "hello" |
| Number | int/float | 42, 3.14 |
| Boolean | Boolean | true → True, false → False |
| Null | None | null → None |
json librarydump() and load()import json
# Python dictionary (complex, nested structure)
contacts = {
"people": [
{"name": "Alice", "email": "alice@example.com", "age": 30},
{"name": "Bob", "email": "bob@example.com", "age": 25}
],
"count": 2
}
# Write Python object to JSON file
with open("contacts.json", "w") as f:
json.dump(contacts, f, indent=4) # indent=4 makes it readable
# Read JSON file back into Python object
with open("contacts.json", "r") as f:
data = json.load(f)
print(data["people"][0]["name"]) # Output: Alicejson.dump(obj, file): Python object → JSON filejson.load(file): JSON file → Python objectindent=4: Makes JSON human-readable (use in development, skip in production)https://api.github.com/users/octocat/repos
└─┬─┘ └────────┬─────────┘ └─────┬────────┘
│ base URL endpoint path
protocolhttps://api.github.com - the server you’re talking to/users/octocat/repos - the specific resource you wantGET (retrieve data), POST (send data), PUT (update), DELETE (remove)GET requests to retrieve datarequests libraryjson, we need to install requestsurlliburllib3, but requests is still preferred for simplicityimport requests
# Make a GET request to the PokeAPI
url = "https://pokeapi.co/api/v2/pokemon/pikachu"
response = requests.get(url)
# Check if the request was successful
if response.status_code == 200:
# Parse the JSON response into a Python dictionary
data = response.json()
print(f"Name: {data['name'].title()}")
print(f"Height: {data['height']} decimetres")
print(f"Weight: {data['weight']} hectograms")
else:
print(f"Error: Received status code {response.status_code}")requests.get(url): Makes HTTP GET request, returns response objectresponse.status_code: HTTP status code (200 = success)response.json(): Parses JSON response → Python dict (same as json.load()!)| Code | Meaning | Example |
|---|---|---|
| 200 | OK - Success | Data retrieved successfully |
| 201 | Created | New resource created |
| 400 | Bad Request | Invalid data sent |
| 401 | Unauthorized | Need authentication |
| 404 | Not Found | Resource doesn’t exist |
| 500 | Server Error | Something broke on server |
response.status_code before processing dataReading JSON from a file:
import requests
url = "https://api.example.com/data"
try:
response = requests.get(url, timeout=5) # 5 second timeout
response.raise_for_status() # Raises exception for 4xx/5xx codes
data = response.json()
print(f"Success: {data}")
except requests.exceptions.Timeout:
print("Error: Request timed out")
except requests.exceptions.ConnectionError:
print("Error: Could not connect to server")
except requests.exceptions.HTTPError as e:
print(f"Error: HTTP {e.response.status_code}")
except requests.exceptions.JSONDecodeError:
print("Error: Response was not valid JSON")timeout= parameter (seconds)raise_for_status(): Converts error codes into exceptions.env files, never commit to git)import json
import requests
# 1. Fetch live data from API
response = requests.get("https://pokeapi.co/api/v2/pokemon/ditto")
pokemon_data = response.json()
# 2. Process the data (extract what we need)
simplified = {
"name": pokemon_data["name"],
"height": pokemon_data["height"],
"weight": pokemon_data["weight"],
"types": [t["type"]["name"] for t in pokemon_data["types"]]
}
# 3. Save to local JSON file for offline use
with open("pokemon_cache.json", "w") as f:
json.dump(simplified, f, indent=4)
print("Data fetched from API and saved locally!")requestsjson.load() (files) and response.json() (APIs) both give you Python dictsNext steps: - Review Lab 07 instructions in labs/lab07/README.md - Choose an API that interests you - Start with simple examples, then build complexity
Office hours: Available for API selection guidance and debugging!
IS4010: App Development with AI