python

Name: python
Author: sordi-ai

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How to install python?

sordi-ai/skill-everything/python

$npx -y skills add sordi-ai/skill-everything --skill python

Installs into the current project.

Summary

Apply when writing Python code. Type hints, error handling, mutable defaults, async patterns, and packaging conventions.

Files · 1

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SKILL.md

1	# Sub-Skill: Python Best Practices
2	<!-- target: ~2200 tokens (real tiktoken count) \| 20 rules with severity classification -->
3
4	Purpose: Prevents the Python-specific mistakes LLMs make on autopilot — mutable defaults, bare excepts, missing guards, and subtle performance traps that pass review but break in production.
5
6	## Rule classification
7
8	- MUST — load-bearing. Violating causes bugs, security issues, or invisible failures. Never break.
9	- SHOULD — default behavior. Deviation needs a documented reason in the code or PR.
10	- AVOID — usually wrong; documented exception inline where needed.
11
12	Where these rules don't strictly apply: test fixtures, generated code, throwaway scripts, REPL exploration, and tutorial snippets may legitimately differ. The rules below apply to production code paths and reusable libraries.
13
14	---
15
16	## Rules
17
18	### Type Hints
19
20	1. SHOULD: Annotate function signatures with types. `def process(data)` tells callers nothing. Use `def process(data: list[str]) -> dict[str, int]:`. Return type `None` should be explicit too. Exception: lambdas and short generator helpers in private scope.
21
22	2. SHOULD: Use built-in lowercase generics for Python 3.9+. `list[str]`, `dict[str, int]`, `tuple[int, ...]` rather than `List`, `Dict`, `Tuple` from `typing`.
23
24	3. MUST: Use `Optional[X]` or `X \| None` for nullable parameters, never a bare default of `None` without a type annotation. `def find(id: int) -> User \| None:` not `def find(id):`.
25
26	4. AVOID: `Any` as a shortcut. If the type is genuinely unknown, document why with a comment. `Any` silences the type checker and hides bugs. Exception: third-party libraries without stubs and explicit dynamic-data boundaries (e.g. JSON decode at the API edge).
27
28	---
29
30	### Error Handling
31
32	5. MUST: Never use bare `except:`. It catches `SystemExit`, `KeyboardInterrupt`, and `GeneratorExit`. Always catch `except Exception:` at minimum, or a specific exception class.
33
34	```python
35	# Wrong
36	try:
37	risky()
38	except:
39	pass
40
41	# Correct
42	try:
43	risky()
44	except ValueError as e:
45	logger.warning("Invalid value: %s", e)
46	```
47
48	6. MUST: Never silently swallow exceptions with `pass`. At minimum log the error. Silent failures produce ghost bugs that are impossible to trace.
49
50	7. SHOULD: Raise with context when re-raising. Use `raise NewError("msg") from original_error` to preserve the traceback chain, not `raise NewError("msg")` alone.
51
52	---
53
54	### Common Pitfalls
55
56	8. MUST: Never use mutable default arguments. Python evaluates defaults once at function definition, not per call. The list or dict is shared across all calls.
57
58	```python
59	# Wrong — items accumulates across calls
60	def append_item(val, items=[]):
61	items.append(val)
62	return items
63
64	# Correct
65	def append_item(val, items=None):
66	if items is None:
67	items = []
68	items.append(val)
69	return items
70	```
71
72	9. MUST: Guard script entry points with `if __name__ == "__main__":`. Without it, importing the module executes top-level code, breaking tests and imports.
73
74	10. MUST: Use `with` for file handles, sockets, and locks. Never open a file without a context manager. `f = open(...)` without `with` leaks handles on exceptions.
75
76	```python
77	# Wrong
78	f = open("data.txt")
79	data = f.read()
80	f.close()
81
82	# Correct
83	with open("data.txt") as f:
84	data = f.read()
85	```
86
87	11. AVOID: String concatenation in loops. Each `+=` on a string creates a new object. Collect into a list and call `"".join(parts)` at the end.
88
89	```python
90	# Wrong — O(n^2) memory
91	result = ""
92	for word in words:
93	result += word + " "
94
95	# Correct
96	result = " ".join(words)
97	```
98
99	12. SHOULD: Use f-strings for string interpolation in Python 3.6+. Avoid `%` formatting or `"Hello " + name`. F-strings are faster, safer, and readable.
100
101	```python
102	# Avoid
103	msg = "User %s has %d items" % (name, count)
104
105	# Prefer
106	msg = f"User {name} has {count} items"
107	```
108
109	13. AVOID: `dict()` constructor when a literal suffices. `{}` is faster and more idiomatic. `dict(key=value)` is only justified when keys are dynamic or come from variables.
110
111	---
112
113	### Performance
114
115	14. SHOULD: Use list comprehensions or generator expressions instead of `map`/`filter` with `lambda`. Comprehensions are more readable and equally fast. Use generators when the full list is not needed at once.
116
117	```python
118	# Avoid
119	result = list(map(lambda x: x * 2, items))
120
121	# Prefer
122	result = [x * 2 for x in items]
123
124	# For large data, use a generator
125	total = sum(x * 2 for x in items)
126	```
127
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python

17stars3forks

View on GitHub

How to install python?

sordi-ai/skill-everything/python

$npx -y skills add sordi-ai/skill-everything --skill python

Installs into the current project.

Summary

Apply when writing Python code. Type hints, error handling, mutable defaults, async patterns, and packaging conventions.

Files · 1

View on GitHub

SKILL.md

1	# Sub-Skill: Python Best Practices
2	<!-- target: ~2200 tokens (real tiktoken count) \| 20 rules with severity classification -->
3
4	Purpose: Prevents the Python-specific mistakes LLMs make on autopilot — mutable defaults, bare excepts, missing guards, and subtle performance traps that pass review but break in production.
5
6	## Rule classification
7
8	- MUST — load-bearing. Violating causes bugs, security issues, or invisible failures. Never break.
9	- SHOULD — default behavior. Deviation needs a documented reason in the code or PR.
10	- AVOID — usually wrong; documented exception inline where needed.
11
12	Where these rules don't strictly apply: test fixtures, generated code, throwaway scripts, REPL exploration, and tutorial snippets may legitimately differ. The rules below apply to production code paths and reusable libraries.
13
14	---
15
16	## Rules
17
18	### Type Hints
19
20	1. SHOULD: Annotate function signatures with types. `def process(data)` tells callers nothing. Use `def process(data: list[str]) -> dict[str, int]:`. Return type `None` should be explicit too. Exception: lambdas and short generator helpers in private scope.
21
22	2. SHOULD: Use built-in lowercase generics for Python 3.9+. `list[str]`, `dict[str, int]`, `tuple[int, ...]` rather than `List`, `Dict`, `Tuple` from `typing`.
23
24	3. MUST: Use `Optional[X]` or `X \| None` for nullable parameters, never a bare default of `None` without a type annotation. `def find(id: int) -> User \| None:` not `def find(id):`.
25
26	4. AVOID: `Any` as a shortcut. If the type is genuinely unknown, document why with a comment. `Any` silences the type checker and hides bugs. Exception: third-party libraries without stubs and explicit dynamic-data boundaries (e.g. JSON decode at the API edge).
27
28	---
29
30	### Error Handling
31
32	5. MUST: Never use bare `except:`. It catches `SystemExit`, `KeyboardInterrupt`, and `GeneratorExit`. Always catch `except Exception:` at minimum, or a specific exception class.
33
34	```python
35	# Wrong
36	try:
37	risky()
38	except:
39	pass
40
41	# Correct
42	try:
43	risky()
44	except ValueError as e:
45	logger.warning("Invalid value: %s", e)
46	```
47
48	6. MUST: Never silently swallow exceptions with `pass`. At minimum log the error. Silent failures produce ghost bugs that are impossible to trace.
49
50	7. SHOULD: Raise with context when re-raising. Use `raise NewError("msg") from original_error` to preserve the traceback chain, not `raise NewError("msg")` alone.
51
52	---
53
54	### Common Pitfalls
55
56	8. MUST: Never use mutable default arguments. Python evaluates defaults once at function definition, not per call. The list or dict is shared across all calls.
57
58	```python
59	# Wrong — items accumulates across calls
60	def append_item(val, items=[]):
61	items.append(val)
62	return items
63
64	# Correct
65	def append_item(val, items=None):
66	if items is None:
67	items = []
68	items.append(val)
69	return items
70	```
71
72	9. MUST: Guard script entry points with `if __name__ == "__main__":`. Without it, importing the module executes top-level code, breaking tests and imports.
73
74	10. MUST: Use `with` for file handles, sockets, and locks. Never open a file without a context manager. `f = open(...)` without `with` leaks handles on exceptions.
75
76	```python
77	# Wrong
78	f = open("data.txt")
79	data = f.read()
80	f.close()
81
82	# Correct
83	with open("data.txt") as f:
84	data = f.read()
85	```
86
87	11. AVOID: String concatenation in loops. Each `+=` on a string creates a new object. Collect into a list and call `"".join(parts)` at the end.
88
89	```python
90	# Wrong — O(n^2) memory
91	result = ""
92	for word in words:
93	result += word + " "
94
95	# Correct
96	result = " ".join(words)
97	```
98
99	12. SHOULD: Use f-strings for string interpolation in Python 3.6+. Avoid `%` formatting or `"Hello " + name`. F-strings are faster, safer, and readable.
100
101	```python
102	# Avoid
103	msg = "User %s has %d items" % (name, count)
104
105	# Prefer
106	msg = f"User {name} has {count} items"
107	```
108
109	13. AVOID: `dict()` constructor when a literal suffices. `{}` is faster and more idiomatic. `dict(key=value)` is only justified when keys are dynamic or come from variables.
110
111	---
112
113	### Performance
114
115	14. SHOULD: Use list comprehensions or generator expressions instead of `map`/`filter` with `lambda`. Comprehensions are more readable and equally fast. Use generators when the full list is not needed at once.
116
117	```python
118	# Avoid
119	result = list(map(lambda x: x * 2, items))
120
121	# Prefer
122	result = [x * 2 for x in items]
123
124	# For large data, use a generator
125	total = sum(x * 2 for x in items)
126	```
127
128	1

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6 picks

Type