| Name | genwatch JSON |
| Version |
0.1.1
JSON |
| download |
| home_page | None |
| Summary | Decorator for tracing Python generator internals |
| upload_time | 2025-08-08 20:53:31 |
| maintainer | None |
| docs_url | None |
| author | Azema Shaik |
| requires_python | >=3.10 |
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| keywords |
generator
tracing
decorator
|
| VCS |
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| requirements |
No requirements were recorded.
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# genwatch
Tiny, surgical **observability for classic Python generators**.
`genwatch` wraps a generator function and emits **structured JSON logs** for the core lifecycle only. By design:
- In `_ProxyReporter.__iter__` **every event logs at `INFO`**.
- **Only** when an unexpected exception escapes the generator do we log at `ERROR` (and re-raise).
- No `DEBUG`, no `WARNING`, no `CRITICAL` inside `__iter__`.
This keeps the noise floor flat and makes logs deterministic and cheap.
---
## Install
```bash
pip install genwatch
```
Python 3.10+.
---
## Why this exists
- You want the **return value** from a generator (`StopIteration.value`) visible in logs.
- You need to **trace delegation** (`yield from`) without global tracing hooks.
- You prefer **stable, assertion-friendly logs** over verbose, level-juggling traces.
- You want a one-line decorator that works on **functions and methods**.
---
## Quick start
```python
import logging
from genwatch import GeneratorReporter
from genwatch._logger import JSONFormatter # optional
# Minimal JSON logger
logger = logging.getLogger("genwatch.demo")
logger.setLevel(logging.INFO)
h = logging.StreamHandler()
h.setFormatter(JSONFormatter())
logger.addHandler(h)
@GeneratorReporter(logger=logger)
def demo(n):
for i in range(n):
received = (yield i) # you can .send(...) into this if you want
return "done"
g = demo(2)
next(g) # -> 0
g.send(None) # -> 1
try:
next(g) # StopIteration with value "done"
except StopIteration as e:
assert e.value == "done"
```
Sample output (with `JSONFormatter`):
```json
{"timestamp":"2025-08-09T19:00:00.123456","level":"INFO","filename":"example.py","lineno":12,"msg":"[genwatch] start demo"}
{"timestamp":"2025-08-09T19:00:00.124000","level":"INFO","filename":"example.py","lineno":12,"msg":"[genwatch] done demo → return 'done'"}
{"timestamp":"2025-08-09T19:00:00.124100","level":"INFO","filename":"example.py","lineno":12,"msg":"[genwatch] closed demo"}
```
If an unexpected exception escapes, you’ll additionally see one `ERROR` log before it’s re-raised.
---
## Practical examples
### 1) Function — streaming CSV parser
Parses a CSV stream row-by-row (nice for big files). Returns the total rows parsed.
```python
import io
import csv
import logging
from genwatch import GeneratorReporter
from genwatch._logger import JSONFormatter # optional
logger = logging.getLogger("genwatch.demo.func")
logger.setLevel(logging.INFO)
h = logging.StreamHandler()
h.setFormatter(JSONFormatter())
logger.addHandler(h)
@GeneratorReporter(logger=logger)
def parse_csv(stream):
reader = csv.DictReader(stream)
count = 0
for row in reader:
_ = (yield row) # consume or react to .send(...) if needed
count += 1
return count
# usage
sample = io.StringIO("id,name\n1,Ana\n2,Bao\n3,Chirag\n")
g = parse_csv(sample)
for row in g:
pass
try:
next(g)
except StopIteration as e:
assert e.value == 3
```
Expected logs:
```json
{"timestamp": "2025-08-09T01:57:52.100597", "level": "INFO", "filename": "example.py", "msg": "parse_csv"}
{"timestamp": "2025-08-09T01:57:52.101668", "level": "INFO", "filename": "example.py", "msg": {"gi_code": "<code object parse_csv at 0x000001735A6828B0, file \"example.py\", line 4>", "gi_frame": "<frame at 0x000001735A743AC0, file 'example.py', line 9, code parse_csv>", "gi_running": "False", "gi_suspended": "True", "gi_yieldfrom": null}, "lineno": 9}
{"timestamp": "2025-08-09T01:57:52.102694", "level": "INFO", "filename": "example.py", "msg": {"yielded_value": {"id": "1", "name": "Ana"}}, "lineno": 9}
{"timestamp": "2025-08-09T01:57:52.103717", "level": "INFO", "filename": "example.py", "msg": {"value_sent_gen": "No value sent to, the generator"}, "lineno": 9}
{"timestamp": "2025-08-09T01:57:52.103717", "level": "INFO", "filename": "example.py", "msg": {"gi_code": "<code object parse_csv at 0x000001735A6828B0, file \"example.py\", line 4>", "gi_frame": "<frame at 0x000001735A743AC0, file 'example.py', line 9, code parse_csv>", "gi_running": "False", "gi_suspended": "True", "gi_yieldfrom": null}, "lineno": 9}
{"timestamp": "2025-08-09T01:57:52.104733", "level": "INFO", "filename": "example.py", "msg": {"yielded_value": {"id": "2", "name": "Bao"}}, "lineno": 9}
```
---
### 2) Method — batching records in a service
Yields fixed-size batches; accepts live size changes via `.send(...)`. Returns a small summary dict.
```python
import logging
from itertools import islice
from genwatch import GeneratorReporter
from genwatch._logger import JSONFormatter # optional
logger = logging.getLogger("genwatch.demo.method")
logger.setLevel(logging.INFO)
h = logging.StreamHandler()
h.setFormatter(JSONFormatter())
logger.addHandler(h)
class BatchService:
def __init__(self, name: str, *, logger: logging.Logger | None = None):
self.name = name
self.logger = logger or logging.getLogger("genwatch.demo.method")
@GeneratorReporter(logger=logger) # descriptor binding makes this work on methods
def batches(self, items, size: int):
total = 0
emitted = 0
it = iter(items)
while True:
chunk = list(islice(it, size))
if not chunk:
break
total += len(chunk)
emitted += 1
control = (yield chunk) # .send(int) to change the batch size
if isinstance(control, int) and control > 0:
size = control
return {"batches": emitted, "items": total, "service": self.name}
# usage
svc = BatchService("orders", logger=logger)
g = svc.batches(range(7), size=3)
first = next(g) # -> [0,1,2]
second = g.send(2) # -> [3,4]
third = next(g) # -> [5,6]
try:
next(g)
except StopIteration as e:
assert e.value == {"batches": 3, "items": 7, "service": "orders"}
```
Expected logs:
```json
{"timestamp": "2025-08-09T01:46:30.250727", "level": "INFO", "filename": "example.py", "msg": "batches"}
{"timestamp": "2025-08-09T01:46:30.253206", "level": "INFO", "filename": "example.py", "msg": {"gi_code": "<code object batches at 0x0000026597279550, file \"example.py\", line 18>", "gi_frame": "<frame at 0x0000026597272D40, file 'example.py', line 29, code batches>", "gi_running": "False", "gi_suspended": "True", "gi_yieldfrom": null}, "lineno": 29}
{"timestamp": "2025-08-09T01:46:30.254881", "level": "INFO", "filename": "example.py", "msg": {"yielded_value": [0, 1, 2]}, "lineno": 29}
{"timestamp": "2025-08-09T01:46:30.255919", "level": "INFO", "filename": "example.py", "msg": {"value_sent_gen": "Value sent to generator: 2"}, "lineno": 29}
{"timestamp": "2025-08-09T01:46:30.256940", "level": "INFO", "filename": "example.py", "msg": {"gi_code": "<code object batches at 0x0000026597279550, file \"example.py\", line 18>", "gi_frame": "<frame at 0x0000026597272D40, file 'example.py', line 29, code batches>", "gi_running": "False", "gi_suspended": "True", "gi_yieldfrom": null}, "lineno": 29}
```
---
## Logging policy (tailored)
Inside `_ProxyReporter.__iter__` we log only:
- **INFO**
- Start of iteration (source filename, and line if available).
- Normal completion with the **returned value** (`StopIteration.value`).
- **ERROR**
- Only when a non-`StopIteration` exception bubbles out of the generator.
- The exception is re-raised; behavior is unchanged.
This yields **stable, low-variance logs** that are easy to diff, assert on, and parse in CI.
---
## API
```python
GeneratorReporter(func: Optional[GeneratorFunction] = None, *, logger: Optional[logging.Logger] = None)
```
- Use as a **decorator** on generator functions.
- Accepts an optional `logging.Logger` instance. If omitted, a default logger with a JSON stream handler is used.
- Works on free functions, instance methods, and class methods (via descriptor binding).
### Validation & misuse
- Decorating a non-generator function → `TypeError`.
- Attempting to decorate an existing reporter instance → `TypeError`.
---
## JSON logs
`_logger.JSONFormatter` formats dict-style messages into JSON lines:
```python
# record.msg structure
{
"filename": "/path/to/file.py",
"lineno": 42, # may be omitted if unknown
"msg": "[genwatch] start <name>"
}
```
Use your own formatter if you prefer; `JSONFormatter` is provided for convenience.
---
## Design notes
- **Decorator** wraps generator functions without modifying bodies.
- **Descriptor** support ensures bound/unbound methods work.
- **Proxy** forwards `__iter__/send/throw/close`, injecting lifecycle logs.
- Light **introspection** (`gi_frame`, `gi_code`) to annotate source info without global traces.
---
## Performance
- INFO-only lifecycle logs are cheap.
- No heavy introspection unless available (`gi_frame`/`gi_code`), and even then minimal fields.
- Works well in hot loops and test harnesses.
Raw data
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"description": "# genwatch\r\n\r\nTiny, surgical **observability for classic Python generators**.\r\n\r\n`genwatch` wraps a generator function and emits **structured JSON logs** for the core lifecycle only. By design:\r\n\r\n- In `_ProxyReporter.__iter__` **every event logs at `INFO`**.\r\n- **Only** when an unexpected exception escapes the generator do we log at `ERROR` (and re-raise).\r\n- No `DEBUG`, no `WARNING`, no `CRITICAL` inside `__iter__`.\r\n\r\nThis keeps the noise floor flat and makes logs deterministic and cheap.\r\n\r\n---\r\n\r\n## Install\r\n\r\n```bash\r\npip install genwatch\r\n```\r\n\r\nPython 3.10+.\r\n\r\n---\r\n\r\n## Why this exists\r\n\r\n- You want the **return value** from a generator (`StopIteration.value`) visible in logs.\r\n- You need to **trace delegation** (`yield from`) without global tracing hooks.\r\n- You prefer **stable, assertion-friendly logs** over verbose, level-juggling traces.\r\n- You want a one-line decorator that works on **functions and methods**.\r\n\r\n---\r\n\r\n## Quick start\r\n\r\n```python\r\nimport logging\r\nfrom genwatch import GeneratorReporter\r\nfrom genwatch._logger import JSONFormatter # optional\r\n\r\n# Minimal JSON logger\r\nlogger = logging.getLogger(\"genwatch.demo\")\r\nlogger.setLevel(logging.INFO)\r\nh = logging.StreamHandler()\r\nh.setFormatter(JSONFormatter())\r\nlogger.addHandler(h)\r\n\r\n@GeneratorReporter(logger=logger)\r\ndef demo(n):\r\n for i in range(n):\r\n received = (yield i) # you can .send(...) into this if you want\r\n return \"done\"\r\n\r\ng = demo(2)\r\nnext(g) # -> 0\r\ng.send(None) # -> 1\r\ntry:\r\n next(g) # StopIteration with value \"done\"\r\nexcept StopIteration as e:\r\n assert e.value == \"done\"\r\n```\r\n\r\nSample output (with `JSONFormatter`):\r\n\r\n```json\r\n{\"timestamp\":\"2025-08-09T19:00:00.123456\",\"level\":\"INFO\",\"filename\":\"example.py\",\"lineno\":12,\"msg\":\"[genwatch] start demo\"}\r\n{\"timestamp\":\"2025-08-09T19:00:00.124000\",\"level\":\"INFO\",\"filename\":\"example.py\",\"lineno\":12,\"msg\":\"[genwatch] done demo \u2192 return 'done'\"}\r\n{\"timestamp\":\"2025-08-09T19:00:00.124100\",\"level\":\"INFO\",\"filename\":\"example.py\",\"lineno\":12,\"msg\":\"[genwatch] closed demo\"}\r\n```\r\n\r\nIf an unexpected exception escapes, you\u2019ll additionally see one `ERROR` log before it\u2019s re-raised.\r\n\r\n---\r\n\r\n## Practical examples\r\n\r\n### 1) Function \u2014 streaming CSV parser\r\n\r\nParses a CSV stream row-by-row (nice for big files). Returns the total rows parsed.\r\n\r\n```python\r\nimport io\r\nimport csv\r\nimport logging\r\n\r\nfrom genwatch import GeneratorReporter\r\nfrom genwatch._logger import JSONFormatter # optional\r\n\r\nlogger = logging.getLogger(\"genwatch.demo.func\")\r\nlogger.setLevel(logging.INFO)\r\nh = logging.StreamHandler()\r\nh.setFormatter(JSONFormatter())\r\nlogger.addHandler(h)\r\n\r\n@GeneratorReporter(logger=logger)\r\ndef parse_csv(stream):\r\n reader = csv.DictReader(stream)\r\n count = 0\r\n for row in reader:\r\n _ = (yield row) # consume or react to .send(...) if needed\r\n count += 1\r\n return count\r\n\r\n# usage\r\nsample = io.StringIO(\"id,name\\n1,Ana\\n2,Bao\\n3,Chirag\\n\")\r\ng = parse_csv(sample)\r\n\r\nfor row in g:\r\n pass\r\n\r\ntry:\r\n next(g)\r\nexcept StopIteration as e:\r\n assert e.value == 3\r\n```\r\n\r\nExpected logs:\r\n\r\n```json\r\n{\"timestamp\": \"2025-08-09T01:57:52.100597\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": \"parse_csv\"}\r\n{\"timestamp\": \"2025-08-09T01:57:52.101668\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"gi_code\": \"<code object parse_csv at 0x000001735A6828B0, file \\\"example.py\\\", line 4>\", \"gi_frame\": \"<frame at 0x000001735A743AC0, file 'example.py', line 9, code parse_csv>\", \"gi_running\": \"False\", \"gi_suspended\": \"True\", \"gi_yieldfrom\": null}, \"lineno\": 9}\r\n{\"timestamp\": \"2025-08-09T01:57:52.102694\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"yielded_value\": {\"id\": \"1\", \"name\": \"Ana\"}}, \"lineno\": 9}\r\n{\"timestamp\": \"2025-08-09T01:57:52.103717\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"value_sent_gen\": \"No value sent to, the generator\"}, \"lineno\": 9}\r\n{\"timestamp\": \"2025-08-09T01:57:52.103717\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"gi_code\": \"<code object parse_csv at 0x000001735A6828B0, file \\\"example.py\\\", line 4>\", \"gi_frame\": \"<frame at 0x000001735A743AC0, file 'example.py', line 9, code parse_csv>\", \"gi_running\": \"False\", \"gi_suspended\": \"True\", \"gi_yieldfrom\": null}, \"lineno\": 9}\r\n{\"timestamp\": \"2025-08-09T01:57:52.104733\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"yielded_value\": {\"id\": \"2\", \"name\": \"Bao\"}}, \"lineno\": 9}\r\n```\r\n\r\n---\r\n\r\n### 2) Method \u2014 batching records in a service\r\n\r\nYields fixed-size batches; accepts live size changes via `.send(...)`. Returns a small summary dict.\r\n\r\n```python\r\nimport logging\r\nfrom itertools import islice\r\nfrom genwatch import GeneratorReporter\r\nfrom genwatch._logger import JSONFormatter # optional\r\n\r\nlogger = logging.getLogger(\"genwatch.demo.method\")\r\nlogger.setLevel(logging.INFO)\r\nh = logging.StreamHandler()\r\nh.setFormatter(JSONFormatter())\r\nlogger.addHandler(h)\r\n\r\nclass BatchService:\r\n def __init__(self, name: str, *, logger: logging.Logger | None = None):\r\n self.name = name\r\n self.logger = logger or logging.getLogger(\"genwatch.demo.method\")\r\n\r\n @GeneratorReporter(logger=logger) # descriptor binding makes this work on methods\r\n def batches(self, items, size: int):\r\n total = 0\r\n emitted = 0\r\n it = iter(items)\r\n while True:\r\n chunk = list(islice(it, size))\r\n if not chunk:\r\n break\r\n total += len(chunk)\r\n emitted += 1\r\n control = (yield chunk) # .send(int) to change the batch size\r\n if isinstance(control, int) and control > 0:\r\n size = control\r\n return {\"batches\": emitted, \"items\": total, \"service\": self.name}\r\n\r\n# usage\r\nsvc = BatchService(\"orders\", logger=logger)\r\ng = svc.batches(range(7), size=3)\r\n\r\nfirst = next(g) # -> [0,1,2]\r\nsecond = g.send(2) # -> [3,4]\r\nthird = next(g) # -> [5,6]\r\n\r\ntry:\r\n next(g)\r\nexcept StopIteration as e:\r\n assert e.value == {\"batches\": 3, \"items\": 7, \"service\": \"orders\"}\r\n```\r\n\r\nExpected logs:\r\n\r\n```json\r\n{\"timestamp\": \"2025-08-09T01:46:30.250727\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": \"batches\"}\r\n{\"timestamp\": \"2025-08-09T01:46:30.253206\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"gi_code\": \"<code object batches at 0x0000026597279550, file \\\"example.py\\\", line 18>\", \"gi_frame\": \"<frame at 0x0000026597272D40, file 'example.py', line 29, code batches>\", \"gi_running\": \"False\", \"gi_suspended\": \"True\", \"gi_yieldfrom\": null}, \"lineno\": 29}\r\n{\"timestamp\": \"2025-08-09T01:46:30.254881\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"yielded_value\": [0, 1, 2]}, \"lineno\": 29}\r\n{\"timestamp\": \"2025-08-09T01:46:30.255919\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"value_sent_gen\": \"Value sent to generator: 2\"}, \"lineno\": 29}\r\n{\"timestamp\": \"2025-08-09T01:46:30.256940\", \"level\": \"INFO\", \"filename\": \"example.py\", \"msg\": {\"gi_code\": \"<code object batches at 0x0000026597279550, file \\\"example.py\\\", line 18>\", \"gi_frame\": \"<frame at 0x0000026597272D40, file 'example.py', line 29, code batches>\", \"gi_running\": \"False\", \"gi_suspended\": \"True\", \"gi_yieldfrom\": null}, \"lineno\": 29}\r\n```\r\n\r\n---\r\n\r\n## Logging policy (tailored)\r\n\r\nInside `_ProxyReporter.__iter__` we log only:\r\n\r\n- **INFO**\r\n - Start of iteration (source filename, and line if available).\r\n - Normal completion with the **returned value** (`StopIteration.value`).\r\n\r\n- **ERROR**\r\n - Only when a non-`StopIteration` exception bubbles out of the generator.\r\n - The exception is re-raised; behavior is unchanged.\r\n\r\n\r\nThis yields **stable, low-variance logs** that are easy to diff, assert on, and parse in CI.\r\n\r\n---\r\n\r\n## API\r\n\r\n```python\r\nGeneratorReporter(func: Optional[GeneratorFunction] = None, *, logger: Optional[logging.Logger] = None)\r\n```\r\n\r\n- Use as a **decorator** on generator functions.\r\n- Accepts an optional `logging.Logger` instance. If omitted, a default logger with a JSON stream handler is used.\r\n- Works on free functions, instance methods, and class methods (via descriptor binding).\r\n\r\n### Validation & misuse\r\n\r\n- Decorating a non-generator function \u2192 `TypeError`.\r\n- Attempting to decorate an existing reporter instance \u2192 `TypeError`.\r\n\r\n---\r\n\r\n## JSON logs\r\n\r\n`_logger.JSONFormatter` formats dict-style messages into JSON lines:\r\n\r\n```python\r\n# record.msg structure\r\n{\r\n \"filename\": \"/path/to/file.py\",\r\n \"lineno\": 42, # may be omitted if unknown\r\n \"msg\": \"[genwatch] start <name>\"\r\n}\r\n```\r\n\r\nUse your own formatter if you prefer; `JSONFormatter` is provided for convenience.\r\n\r\n---\r\n\r\n## Design notes\r\n\r\n- **Decorator** wraps generator functions without modifying bodies.\r\n- **Descriptor** support ensures bound/unbound methods work.\r\n- **Proxy** forwards `__iter__/send/throw/close`, injecting lifecycle logs.\r\n- Light **introspection** (`gi_frame`, `gi_code`) to annotate source info without global traces.\r\n\r\n---\r\n\r\n## Performance\r\n\r\n- INFO-only lifecycle logs are cheap.\r\n- No heavy introspection unless available (`gi_frame`/`gi_code`), and even then minimal fields.\r\n- Works well in hot loops and test harnesses.\r\n",
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