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skills/n8n-code-python/STANDARD_LIBRARY.md

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+# Standard Library Reference - Python Code Node
+
+Complete guide to available Python standard library modules in n8n Code nodes.
+
+---
+
+## ⚠️ Critical Limitation
+
+**NO EXTERNAL LIBRARIES AVAILABLE**
+
+Python Code nodes in n8n have **ONLY** the Python standard library. No pip packages.
+
+```python
+# ❌ NOT AVAILABLE - Will cause ModuleNotFoundError
+import requests      # No HTTP library!
+import pandas        # No data analysis!
+import numpy         # No numerical computing!
+import bs4          # No web scraping!
+import selenium     # No browser automation!
+import psycopg2     # No database drivers!
+import pymongo      # No MongoDB!
+import sqlalchemy   # No ORMs!
+
+# ✅ AVAILABLE - Standard library only
+import json
+import datetime
+import re
+import base64
+import hashlib
+import urllib.parse
+import urllib.request
+import math
+import random
+import statistics
+```
+
+**Recommendation**: Use **JavaScript** for 95% of use cases. JavaScript has more capabilities in n8n.
+
+---
+
+## Available Modules
+
+### Priority 1: Most Useful (Use These)
+
+1. **json** - JSON parsing and generation
+2. **datetime** - Date and time operations
+3. **re** - Regular expressions
+4. **base64** - Base64 encoding/decoding
+5. **hashlib** - Hashing (MD5, SHA256, etc.)
+6. **urllib.parse** - URL parsing and encoding
+
+### Priority 2: Moderately Useful
+
+7. **math** - Mathematical functions
+8. **random** - Random number generation
+9. **statistics** - Statistical functions
+10. **collections** - Specialized data structures
+
+### Priority 3: Occasionally Useful
+
+11. **itertools** - Iterator tools
+12. **functools** - Higher-order functions
+13. **operator** - Standard operators as functions
+14. **string** - String constants and templates
+15. **textwrap** - Text wrapping utilities
+
+---
+
+## Module 1: json - JSON Operations
+
+**Most common module** - Parse and generate JSON data.
+
+### Parse JSON String
+
+```python
+import json
+
+# Parse JSON string to Python dict
+json_string = '{"name": "Alice", "age": 30}'
+data = json.loads(json_string)
+
+return [{
+    "json": {
+        "name": data["name"],
+        "age": data["age"],
+        "parsed": True
+    }
+}]
+```
+
+### Generate JSON String
+
+```python
+import json
+
+# Convert Python dict to JSON string
+data = {
+    "users": [
+        {"id": 1, "name": "Alice"},
+        {"id": 2, "name": "Bob"}
+    ],
+    "total": 2
+}
+
+json_string = json.dumps(data, indent=2)
+
+return [{
+    "json": {
+        "json_output": json_string,
+        "length": len(json_string)
+    }
+}]
+```
+
+### Handle JSON Errors
+
+```python
+import json
+
+webhook_data = _input.first()["json"]["body"]
+json_string = webhook_data.get("data", "")
+
+try:
+    parsed = json.loads(json_string)
+    status = "valid"
+    error = None
+except json.JSONDecodeError as e:
+    parsed = None
+    status = "invalid"
+    error = str(e)
+
+return [{
+    "json": {
+        "status": status,
+        "data": parsed,
+        "error": error
+    }
+}]
+```
+
+### Pretty Print JSON
+
+```python
+import json
+
+# Format JSON with indentation
+data = _input.first()["json"]
+
+pretty_json = json.dumps(data, indent=2, sort_keys=True)
+
+return [{
+    "json": {
+        "formatted": pretty_json
+    }
+}]
+```
+
+---
+
+## Module 2: datetime - Date and Time
+
+**Very common** - Date parsing, formatting, calculations.
+
+### Current Date and Time
+
+```python
+from datetime import datetime
+
+now = datetime.now()
+
+return [{
+    "json": {
+        "timestamp": now.isoformat(),
+        "date": now.strftime("%Y-%m-%d"),
+        "time": now.strftime("%H:%M:%S"),
+        "formatted": now.strftime("%B %d, %Y at %I:%M %p")
+    }
+}]
+```
+
+### Parse Date String
+
+```python
+from datetime import datetime
+
+date_string = "2025-01-15T14:30:00"
+dt = datetime.fromisoformat(date_string)
+
+return [{
+    "json": {
+        "year": dt.year,
+        "month": dt.month,
+        "day": dt.day,
+        "hour": dt.hour,
+        "weekday": dt.strftime("%A")
+    }
+}]
+```
+
+### Date Calculations
+
+```python
+from datetime import datetime, timedelta
+
+now = datetime.now()
+
+# Calculate future/past dates
+tomorrow = now + timedelta(days=1)
+yesterday = now - timedelta(days=1)
+next_week = now + timedelta(weeks=1)
+one_hour_ago = now - timedelta(hours=1)
+
+return [{
+    "json": {
+        "now": now.isoformat(),
+        "tomorrow": tomorrow.isoformat(),
+        "yesterday": yesterday.isoformat(),
+        "next_week": next_week.isoformat(),
+        "one_hour_ago": one_hour_ago.isoformat()
+    }
+}]
+```
+
+### Compare Dates
+
+```python
+from datetime import datetime
+
+date1 = datetime(2025, 1, 15)
+date2 = datetime(2025, 1, 20)
+
+# Calculate difference
+diff = date2 - date1
+
+return [{
+    "json": {
+        "days_difference": diff.days,
+        "seconds_difference": diff.total_seconds(),
+        "date1_is_earlier": date1 < date2,
+        "date2_is_later": date2 > date1
+    }
+}]
+```
+
+### Format Dates
+
+```python
+from datetime import datetime
+
+dt = datetime.now()
+
+return [{
+    "json": {
+        "iso": dt.isoformat(),
+        "us_format": dt.strftime("%m/%d/%Y"),
+        "eu_format": dt.strftime("%d/%m/%Y"),
+        "long_format": dt.strftime("%A, %B %d, %Y"),
+        "time_12h": dt.strftime("%I:%M %p"),
+        "time_24h": dt.strftime("%H:%M:%S")
+    }
+}]
+```
+
+---
+
+## Module 3: re - Regular Expressions
+
+**Common** - Pattern matching, text extraction, validation.
+
+### Pattern Matching
+
+```python
+import re
+
+text = "Email: alice@example.com, Phone: 555-1234"
+
+# Find email
+email_match = re.search(r'\b[\w.-]+@[\w.-]+\.\w+\b', text)
+email = email_match.group(0) if email_match else None
+
+# Find phone
+phone_match = re.search(r'\d{3}-\d{4}', text)
+phone = phone_match.group(0) if phone_match else None
+
+return [{
+    "json": {
+        "email": email,
+        "phone": phone
+    }
+}]
+```
+
+### Extract All Matches
+
+```python
+import re
+
+text = "Tags: #python #automation #workflow #n8n"
+
+# Find all hashtags
+hashtags = re.findall(r'#(\w+)', text)
+
+return [{
+    "json": {
+        "tags": hashtags,
+        "count": len(hashtags)
+    }
+}]
+```
+
+### Replace Patterns
+
+```python
+import re
+
+text = "Price: $99.99, Discount: $10.00"
+
+# Remove dollar signs
+cleaned = re.sub(r'\$', '', text)
+
+# Replace multiple spaces with single space
+normalized = re.sub(r'\s+', ' ', cleaned)
+
+return [{
+    "json": {
+        "original": text,
+        "cleaned": cleaned,
+        "normalized": normalized
+    }
+}]
+```
+
+### Validate Format
+
+```python
+import re
+
+email = _input.first()["json"]["body"].get("email", "")
+
+# Email validation pattern
+email_pattern = r'^[\w.-]+@[\w.-]+\.\w+$'
+is_valid = bool(re.match(email_pattern, email))
+
+return [{
+    "json": {
+        "email": email,
+        "valid": is_valid
+    }
+}]
+```
+
+### Split on Pattern
+
+```python
+import re
+
+text = "apple,banana;orange|grape"
+
+# Split on multiple delimiters
+items = re.split(r'[,;|]', text)
+
+# Clean up whitespace
+items = [item.strip() for item in items]
+
+return [{
+    "json": {
+        "items": items,
+        "count": len(items)
+    }
+}]
+```
+
+---
+
+## Module 4: base64 - Encoding/Decoding
+
+**Common** - Encode binary data, API authentication.
+
+### Encode String to Base64
+
+```python
+import base64
+
+text = "Hello, World!"
+
+# Encode to base64
+encoded_bytes = base64.b64encode(text.encode('utf-8'))
+encoded_string = encoded_bytes.decode('utf-8')
+
+return [{
+    "json": {
+        "original": text,
+        "encoded": encoded_string
+    }
+}]
+```
+
+### Decode Base64 to String
+
+```python
+import base64
+
+encoded = "SGVsbG8sIFdvcmxkIQ=="
+
+# Decode from base64
+decoded_bytes = base64.b64decode(encoded)
+decoded_string = decoded_bytes.decode('utf-8')
+
+return [{
+    "json": {
+        "encoded": encoded,
+        "decoded": decoded_string
+    }
+}]
+```
+
+### Basic Auth Header
+
+```python
+import base64
+
+username = "admin"
+password = "secret123"
+
+# Create Basic Auth header
+credentials = f"{username}:{password}"
+encoded = base64.b64encode(credentials.encode('utf-8')).decode('utf-8')
+auth_header = f"Basic {encoded}"
+
+return [{
+    "json": {
+        "authorization": auth_header
+    }
+}]
+```
+
+---
+
+## Module 5: hashlib - Hashing
+
+**Common** - Generate checksums, hash passwords, create IDs.
+
+### MD5 Hash
+
+```python
+import hashlib
+
+text = "Hello, World!"
+
+# Generate MD5 hash
+md5_hash = hashlib.md5(text.encode('utf-8')).hexdigest()
+
+return [{
+    "json": {
+        "original": text,
+        "md5": md5_hash
+    }
+}]
+```
+
+### SHA256 Hash
+
+```python
+import hashlib
+
+data = _input.first()["json"]["body"]
+text = data.get("password", "")
+
+# Generate SHA256 hash (more secure than MD5)
+sha256_hash = hashlib.sha256(text.encode('utf-8')).hexdigest()
+
+return [{
+    "json": {
+        "hashed": sha256_hash
+    }
+}]
+```
+
+### Generate Unique ID
+
+```python
+import hashlib
+from datetime import datetime
+
+# Create unique ID from multiple values
+unique_string = f"{datetime.now().isoformat()}-{_json.get('user_id', 'unknown')}"
+unique_id = hashlib.sha256(unique_string.encode('utf-8')).hexdigest()[:16]
+
+return [{
+    "json": {
+        "id": unique_id,
+        "generated_at": datetime.now().isoformat()
+    }
+}]
+```
+
+---
+
+## Module 6: urllib.parse - URL Operations
+
+**Common** - Parse URLs, encode parameters.
+
+### Parse URL
+
+```python
+from urllib.parse import urlparse
+
+url = "https://example.com/path?key=value&foo=bar#section"
+
+parsed = urlparse(url)
+
+return [{
+    "json": {
+        "scheme": parsed.scheme,      # "https"
+        "netloc": parsed.netloc,      # "example.com"
+        "path": parsed.path,          # "/path"
+        "query": parsed.query,        # "key=value&foo=bar"
+        "fragment": parsed.fragment    # "section"
+    }
+}]
+```
+
+### URL Encode Parameters
+
+```python
+from urllib.parse import urlencode
+
+params = {
+    "name": "Alice Smith",
+    "email": "alice@example.com",
+    "message": "Hello, World!"
+}
+
+# Encode parameters for URL
+encoded = urlencode(params)
+
+return [{
+    "json": {
+        "query_string": encoded,
+        "full_url": f"https://api.example.com/submit?{encoded}"
+    }
+}]
+```
+
+### Parse Query String
+
+```python
+from urllib.parse import parse_qs
+
+query_string = "name=Alice&age=30&tags=python&tags=n8n"
+
+# Parse query string
+params = parse_qs(query_string)
+
+return [{
+    "json": {
+        "name": params.get("name", [""])[0],
+        "age": int(params.get("age", ["0"])[0]),
+        "tags": params.get("tags", [])
+    }
+}]
+```
+
+### URL Encode/Decode Strings
+
+```python
+from urllib.parse import quote, unquote
+
+text = "Hello, World! 你好"
+
+# URL encode
+encoded = quote(text)
+
+# URL decode
+decoded = unquote(encoded)
+
+return [{
+    "json": {
+        "original": text,
+        "encoded": encoded,
+        "decoded": decoded
+    }
+}]
+```
+
+---
+
+## Module 7: math - Mathematical Operations
+
+**Moderately useful** - Advanced math functions.
+
+### Basic Math Functions
+
+```python
+import math
+
+number = 16.7
+
+return [{
+    "json": {
+        "ceiling": math.ceil(number),      # 17
+        "floor": math.floor(number),       # 16
+        "rounded": round(number),          # 17
+        "square_root": math.sqrt(16),      # 4.0
+        "power": math.pow(2, 3),          # 8.0
+        "absolute": math.fabs(-5.5)       # 5.5
+    }
+}]
+```
+
+### Trigonometry
+
+```python
+import math
+
+angle_degrees = 45
+angle_radians = math.radians(angle_degrees)
+
+return [{
+    "json": {
+        "sine": math.sin(angle_radians),
+        "cosine": math.cos(angle_radians),
+        "tangent": math.tan(angle_radians),
+        "pi": math.pi,
+        "e": math.e
+    }
+}]
+```
+
+### Logarithms
+
+```python
+import math
+
+number = 100
+
+return [{
+    "json": {
+        "log10": math.log10(number),     # 2.0
+        "natural_log": math.log(number), # 4.605...
+        "log2": math.log2(number)        # 6.644...
+    }
+}]
+```
+
+---
+
+## Module 8: random - Random Numbers
+
+**Moderately useful** - Generate random data, sampling.
+
+### Random Numbers
+
+```python
+import random
+
+return [{
+    "json": {
+        "random_float": random.random(),           # 0.0 to 1.0
+        "random_int": random.randint(1, 100),      # 1 to 100
+        "random_range": random.randrange(0, 100, 5) # 0, 5, 10, ..., 95
+    }
+}]
+```
+
+### Random Choice
+
+```python
+import random
+
+colors = ["red", "green", "blue", "yellow"]
+users = [{"id": 1, "name": "Alice"}, {"id": 2, "name": "Bob"}]
+
+return [{
+    "json": {
+        "random_color": random.choice(colors),
+        "random_user": random.choice(users)
+    }
+}]
+```
+
+### Shuffle List
+
+```python
+import random
+
+items = [1, 2, 3, 4, 5]
+shuffled = items.copy()
+random.shuffle(shuffled)
+
+return [{
+    "json": {
+        "original": items,
+        "shuffled": shuffled
+    }
+}]
+```
+
+### Random Sample
+
+```python
+import random
+
+items = list(range(1, 101))
+
+# Get 10 random items without replacement
+sample = random.sample(items, 10)
+
+return [{
+    "json": {
+        "sample": sample,
+        "count": len(sample)
+    }
+}]
+```
+
+---
+
+## Module 9: statistics - Statistical Functions
+
+**Moderately useful** - Calculate stats from data.
+
+### Basic Statistics
+
+```python
+import statistics
+
+numbers = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
+
+return [{
+    "json": {
+        "mean": statistics.mean(numbers),           # 55.0
+        "median": statistics.median(numbers),       # 55.0
+        "mode": statistics.mode([1, 2, 2, 3]),     # 2
+        "stdev": statistics.stdev(numbers),        # 30.28...
+        "variance": statistics.variance(numbers)   # 916.67...
+    }
+}]
+```
+
+### Aggregate from Items
+
+```python
+import statistics
+
+all_items = _input.all()
+
+# Extract amounts
+amounts = [item["json"].get("amount", 0) for item in all_items]
+
+if amounts:
+    return [{
+        "json": {
+            "count": len(amounts),
+            "total": sum(amounts),
+            "average": statistics.mean(amounts),
+            "median": statistics.median(amounts),
+            "min": min(amounts),
+            "max": max(amounts),
+            "range": max(amounts) - min(amounts)
+        }
+    }]
+else:
+    return [{"json": {"error": "No data"}}]
+```
+
+---
+
+## Workarounds for Missing Libraries
+
+### HTTP Requests (No requests library)
+
+```python
+# ❌ Can't use requests library
+# import requests  # ModuleNotFoundError!
+
+# ✅ Use HTTP Request node instead
+# Add HTTP Request node BEFORE Code node
+# Access the response in Code node
+
+response_data = _input.first()["json"]
+
+return [{
+    "json": {
+        "status": response_data.get("status"),
+        "data": response_data.get("body"),
+        "processed": True
+    }
+}]
+```
+
+### Data Processing (No pandas)
+
+```python
+# ❌ Can't use pandas
+# import pandas as pd  # ModuleNotFoundError!
+
+# ✅ Use Python's built-in list comprehensions
+all_items = _input.all()
+
+# Filter
+active_items = [
+    item for item in all_items
+    if item["json"].get("status") == "active"
+]
+
+# Group by
+from collections import defaultdict
+grouped = defaultdict(list)
+
+for item in all_items:
+    category = item["json"].get("category", "other")
+    grouped[category].append(item["json"])
+
+# Aggregate
+import statistics
+amounts = [item["json"].get("amount", 0) for item in all_items]
+total = sum(amounts)
+average = statistics.mean(amounts) if amounts else 0
+
+return [{
+    "json": {
+        "active_count": len(active_items),
+        "grouped": dict(grouped),
+        "total": total,
+        "average": average
+    }
+}]
+```
+
+### Database Operations (No drivers)
+
+```python
+# ❌ Can't use database drivers
+# import psycopg2  # ModuleNotFoundError!
+# import pymongo   # ModuleNotFoundError!
+
+# ✅ Use n8n database nodes instead
+# Add Postgres/MySQL/MongoDB node BEFORE Code node
+# Process results in Code node
+
+db_results = _input.first()["json"]
+
+return [{
+    "json": {
+        "record_count": len(db_results) if isinstance(db_results, list) else 1,
+        "processed": True
+    }
+}]
+```
+
+---
+
+## Complete Standard Library List
+
+**Available** (commonly useful):
+- json
+- datetime, time
+- re
+- base64
+- hashlib
+- urllib.parse, urllib.request, urllib.error
+- math
+- random
+- statistics
+- collections (defaultdict, Counter, namedtuple)
+- itertools
+- functools
+- operator
+- string
+- textwrap
+
+**Available** (less common):
+- os.path (path operations only)
+- copy
+- typing
+- enum
+- decimal
+- fractions
+
+**NOT Available** (external libraries):
+- requests (HTTP)
+- pandas (data analysis)
+- numpy (numerical computing)
+- bs4/beautifulsoup4 (HTML parsing)
+- selenium (browser automation)
+- psycopg2, pymongo, sqlalchemy (databases)
+- flask, fastapi (web frameworks)
+- pillow (image processing)
+- openpyxl, xlsxwriter (Excel)
+
+---
+
+## Best Practices
+
+### 1. Use Standard Library When Possible
+
+```python
+# ✅ GOOD: Use standard library
+import json
+import datetime
+import re
+
+data = _input.first()["json"]
+processed = json.loads(data.get("json_string", "{}"))
+
+return [{"json": processed}]
+```
+
+### 2. Fall Back to n8n Nodes
+
+```python
+# For operations requiring external libraries,
+# use n8n nodes instead:
+# - HTTP Request for API calls
+# - Postgres/MySQL for databases
+# - Extract from File for parsing
+
+# Then process results in Code node
+result = _input.first()["json"]
+return [{"json": {"processed": result}}]
+```
+
+### 3. Combine Multiple Modules
+
+```python
+import json
+import base64
+import hashlib
+from datetime import datetime
+
+# Combine modules for complex operations
+data = _input.first()["json"]["body"]
+
+# Hash sensitive data
+user_id = hashlib.sha256(data.get("email", "").encode()).hexdigest()[:16]
+
+# Encode for storage
+encoded_data = base64.b64encode(json.dumps(data).encode()).decode()
+
+return [{
+    "json": {
+        "user_id": user_id,
+        "encoded_data": encoded_data,
+        "timestamp": datetime.now().isoformat()
+    }
+}]
+```
+
+---
+
+## Summary
+
+**Most Useful Modules**:
+1. json - Parse/generate JSON
+2. datetime - Date operations
+3. re - Regular expressions
+4. base64 - Encoding
+5. hashlib - Hashing
+6. urllib.parse - URL operations
+
+**Critical Limitation**:
+- NO external libraries (requests, pandas, numpy, etc.)
+
+**Recommended Approach**:
+- Use **JavaScript** for 95% of use cases
+- Use Python only when specifically needed
+- Use n8n nodes for operations requiring external libraries
+
+**See Also**:
+- [SKILL.md](SKILL.md) - Python Code overview
+- [DATA_ACCESS.md](DATA_ACCESS.md) - Data access patterns
+- [COMMON_PATTERNS.md](COMMON_PATTERNS.md) - Production patterns
+- [ERROR_PATTERNS.md](ERROR_PATTERNS.md) - Avoid common mistakes