Detailed explanation of the method of obtaining data in Flask request

1. Working principle

In Flask, all client requested data are accessed through the global request object. This object is part of the request context and exists only during request processing. Flask automatically creates a request object when receiving a request, parses the data according to the request type (such as GET, POST) and content type (such as form, JSON), and encapsulates data from different sources into corresponding attributes (such as args, form, json).

2. Common methods

Query parameters (URL parameters)

use(type:ImmutableMultiDict) Get the query parameters in the URL.

name = ('name')  # Get a single parameterall_args = .to_dict()  # Convert to dictionary

Form data

Forapplication/x-www-form-urlencodedormultipart/form-dataType of POST request, use。

username = ('username')

JSON data

When requestedContent-Typeforapplication/jsonWhen usingDirectly get the parsed dictionary.

data =

File upload

passGet the uploaded file (type:FileStorage）。

file = ('file')
if file:
    ('uploaded_file.txt')

Raw data
useGet unprocessed raw byte data (such as non-form, non-JSON request body).
Request header and cookies

user_agent = ('User-Agent')
user_token = ('token')

3. Advanced usage

Handle multi-value parameters
When the parameter has multiple values (such as multi-check boxes), usegetlist：

selected_ids = ('ids')

Forced parsing JSON
even thoughContent-Typenoapplication/json, can also be forced to parse:

data = request.get_json(force=True)

Streaming large files
useRead data block by block to avoid memory overflow:

@('/upload', methods=['POST'])
def upload():
    def generate():
        chunk_size = 4096
        while True:
            chunk = (chunk_size)
            if not chunk:
                break
            # Handle chunk...    return 'Upload complete'

Mixed data (form + JSON)useMerge query parameters and form data (combination is not recommended, logic needs to be handled with caution).

4. Complete example

from flask import Flask, request, jsonify

app = Flask(__name__)

@('/api', methods=['GET', 'POST'])
def handle_request():
    # Get query parameters    query_param = ('q')
    
    # Process data according to different request types    if  == 'POST':
        # Process form data        username = ('username')
        
        # Process JSON data        json_data = request.get_json(silent=True)  # Resolution failed to return None        
        # Process file upload        uploaded_file = ('file')
        if uploaded_file:
            uploaded_file.save('uploads/' + uploaded_file.filename)
        
        return jsonify({
            "query_param": query_param,
            "username": username,
            "json_data": json_data,
            "file_uploaded": bool(uploaded_file)
        })
    else:
        return jsonify({"query_param": query_param})

if __name__ == '__main__':
    (debug=True)

5. Things to note

Request method affects data acquisition
- GET request onlyargs,noneformorfiles。
- POST needs to be based onContent-TypeSelect the correct attribute (such asformorjson）。
Process missing data
use.get('key')Rather than['key']avoidKeyError, you can specify the default value:

value = ('key', 'default')

JSON parsing security
- userequest.get_json(silent=True)Avoid throwing exceptions if parsing failed.
- useforce=TrueWhen paying attention, the client may send illegal data.
File upload security
- Limit file type and size (byMAX_CONTENT_LENGTHConfiguration).
- Verify file names to avoid path traversal vulnerabilities.

6. Expand knowledge

Request hook preprocessing
use@app.before_requestUnified verification or preprocessing of data before request processing:

@app.before_request
def check_auth():
    if not  == 'login' and not validate_token(('Token')):
        return jsonify({"error": "Unauthorized"}), 401

Third-party library extensions
- Flask-RESTful: Build a REST API to automatically parse requested data.
- Flask-WTF: Integrated WTForms, handle form validation and CSRF protection.
Performance optimization
- For large file uploads, use streaming or block transfer.
- EnablegzipCompression reduces the amount of data transmission.
Test request
Use Flask to test client mock requests:

with app.test_client() as client:
    response = ('/api', data={'username': 'test'}, headers={'Content-Type': 'multipart/form-data'})
    assert response.status_code == 200

7. Error handling and debugging skills

1. Elegantly handle data parsing errors

When parsing client data, you may encounter format errors or illegal content, and you need to reasonably catch the exception:

@('/parse-json', methods=['POST'])
def parse_json():
    try:
        data = request.get_json()
        if data is None:
            raise ValueError("Invalid JSON")
        # Processing data...    except ValueError as e:
        return jsonify({"error": str(e)}), 400

Key points：

usesilent=TrueWhen , no exception will be thrown even if the parsing fails, but manual check is requireddataIs itNone。
For file upload errors, you can checkWhether it exists and the file object is valid.

2. Practical method for debugging requested data

During development, a quick view of the original request data helps locate issues:

@('/debug', methods=['POST'])
def debug_endpoint():
    print("Headers:", )
    print("Raw Data:", ('utf-8'))
    print("Form Data:", )
    return "Debug information logged"

Tool recommendations：

Postman: Simulate complex requests (such as multipart/form-data or custom headers).
curl command: Quick test API interface:

curl -X POST http://localhost:5000/api -H "Content-Type: application/json" -d '{"key": "value"}'

8. Security reinforcement strategy

1. Prevent common attacks

CSRF Protection:useFlask-WTFExtended automatic generation and verification CSRF Token:

from flask_wtf.csrf import CSRFProtect
csrf = CSRFProtect(app)

Add hidden fields to the form:

<input type="hidden" name="csrf_token" value="{{ csrf_token() }}">

SQL Injection Protection: Always use ORMs (such as SQLAlchemy) or parameterized queries to avoid splicing SQL strings.
XSS Protection: Escape the content entered by the user (Flask templates are automatically escaped by default).

2. File upload security practice

Limit file extensions：

allowed_extensions = {'png', 'jpg', 'jpeg'}
filename = uploaded_file.filename
if '.' not in filename or ('.')[-1].lower() not in allowed_extensions:
    return "Invalid file type", 400

Prevent path traversal:usesecure_filenameProcess file name:

from  import secure_filename
safe_filename = secure_filename(uploaded_file.filename)
uploaded_file.save(f'uploads/{safe_filename}')

9. Asynchronous and Performance Optimization

1. Asynchronously handle large requests

useasync/awaitProcessing time-consuming operations (requires Flask 2.0+ to support asynchronous views):

@('/async-upload', methods=['POST'])
async def async_upload():
    data = await request.get_data()
    # Asynchronous processing of data (such as writing to the database)    return "Processing completed"

Applicable scenarios：

Background processing after large files are uploaded (such as video transcoding).
Non-blocking IO operation under high concurrency.

2. Performance tuning suggestions

Configure request body size limit：

['MAX_CONTENT_LENGTH'] = 100 * 1024 * 1024  # Limit to 100MB

Enable compression: Compress response data via Nginx or GzipMiddleware:

from flask_compress import Compress
Compress(app)

10. Integrate with other technology stacks

1. Process data in combination with the front-end framework

React/Vue Form Submission: Ensure the front endContent-TypeMatching with the backend:

// Use FormData to process file uploadconst formData = new FormData();
('file', [0]);
fetch('/api/upload', { method: 'POST', body: formData });

AJAX Request Processing: Flask automatic parsingapplication/json, the front-end needs to clearly set headers:

fetch('/api/data', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: ({ key: 'value' })
});

2. Extended data format support (such as XML)

If you need to parse XML requests, you can customize the parsing logic:

from  import ElementTree

@('/xml', methods=['POST'])
def parse_xml():
    xml_data = 
    root = (xml_data)
    value = ('key').text
    return jsonify({"value": value})

11. Practical case: Building a RESTful API

1. User registration interface

Processing mixed data (JSON + file avatar upload):

@('/register', methods=['POST'])
def register():
    # parse JSON data    user_data = request.get_json()
    username = user_data.get('username')
    
    # Process avatar files    avatar = ('avatar')
    if avatar:
        (f'avatars/{secure_filename()}')
    
    # Save the user to the database (pseudocode)    save_user(username)
    
    return jsonify({"status": "success"})

2. Pagination query interface

Combining query parameters and data filtering:

@('/articles', methods=['GET'])
def get_articles():
    page = ('page', 1, type=int)
    per_page = ('per_page', 10, type=int)
    articles = (page=page, per_page=per_page)
    return jsonify({
        "data": [article.to_dict() for article in ],
        "total_pages": 
    })

12. Summary

Flask's request data acquisition mechanism takes into account flexibility and simplicity. Developers need to choose appropriate methods based on the actual scenario:

Basic scene: Use directly、、。
Complex scenes: Combined with streaming processing, asynchronous operation or third-party library extension functions.
Safety first: Always verify input, limit resources, and prevent common attacks.

By rationally designing data flow and error handling mechanisms, efficient and robust web applications can be built.

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