Metadata-Version: 2.4
Name: async-strict-timer
Version: 0.1.0
Summary: A precise, cancellation-safe asyncio timer for Python that avoids drift
Author-email: sumitdhyani <sumitdhyani1@gmail.com>
Keywords: asyncio timer,deterministic,drift,overrun
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Framework :: AsyncIO
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Utilities
Requires-Python: >=3.8
Description-Content-Type: text/markdown

# asynctimer

Deterministic, **asyncio-native** timer for predictable, repeated execution

## Overview

asynctimer is a precise, cancellation-safe asyncio timer for Python that avoids drift and enforces fixed scheduling semantics.
It is intentionally conservative and explicit, making it suitable for protecting external systems (APIs, databases, hardware) where **bursts and ambiguity are unacceptable**.

## Why this library exists

Many timer utilities:
- implicitly drift over time
- allow bursts by default
- rely on best-effort timing
- do not clearly specify stop or overrun behavior

**asynctimer** takes a different approach:

> Behavior is explicit, testable, and deterministic — even if that costs some throughput, though in case of timers that's virtually never a concern.

---

## Why not just use `asyncio.sleep()`?

A common way to implement a repeating task is:

```python
while True:
    await asyncio.sleep(interval)
    do_work()
```

This approach introduces timer drift because:
- execution time is added to the interval
- event loop scheduling latency compounds over time
- For long-running tasks, this drift becomes observable and problematic.
- No cancellation mechanism

## Installation

```bash
pip install asynctimer
```

---

### What it does

Implements a repeating, async-friendly timer that calls a user-provided callback at a fixed interval until stopped. Callbacks may be synchronous functions or async coroutines.


### Timer Guarantees

- Callbacks never execute concurrently
- Calling stop() guarantees that no further callbacks will be scheduled or started after it returns.
- Drift behavior is explicitly configurable
- Overrun behavior is well-defined and tested


### API

- `Timer(timeout: int | float, callback: Callback, schedule_policy: str = "FIXED_SCHEDULE")` — create a timer with a repeat interval, callback, and drift policy.
    - **timeout_ns**: Tick interval in nanoseconds
    - **callback**: `Callable[[], None | Awaitable[None]]`
        - May be a synchronous function or an async coroutine
        - Takes no arguments
        - Returns nothing
    - **schedule_policy**: Drift policy
        - `"FIXED_SCHEDULE"` (default)
        - `"FIXED_DELAY"`
    - `start()` — start the timer loop (non-blocking; schedules repeated executions).
    - `stop()` — stop the timer loop.

### Drift / Schedule Policy

Timers can be scheduled in two fundamentally different ways.

#### Fixed Schedule (drift-free)

```
next_tick = initial_start + N × interval
```

- Anchored to the original schedule
- Prevents long-term drift
- Suitable for:
  - heartbeats
  - simulations
  - clock-aligned tasks

```python
from asynctimer import Timer
# callback can be async too
def callback():
    print('tick')

timer = Timer(
    2000_000_000,
    callback,
    schedule_policy="FIXED_SCHEDULE"
)
timer.start()  # starts the repeating timer
# ... later: timer.stop()
```

#### Fixed Delay (completion-relative)

```
next_tick = callback_completion + interval
```

- Guarantees spacing between executions
- Suitable for:
  - retries
  - polling
  - cooldowns
  - background maintenance

```python
from asynctimer import Timer

timer = Timer(
    2000_000_000,
    callback,
    schedule_policy="FIXED_DELAY"
)
timer.start()
```

### Overrun Behavior

If a callback takes longer than the interval:
- Missed ticks are not executed retroactively
- The timer resumes according to its original schedule policy

This avoids burst execution and keeps behavior predictable.

### Stop Semantics

Calling `stop()` guarantees:
- No further callbacks will be scheduled or started after it returns.

### Example

```python
import asyncio
from asynctimer import Timer

# callback can be async too
def callback():
    print('tick')

async def main():
    timer = Timer(2000_000_000, callback)
    timer.start()  # starts the repeating timer
    await asyncio.sleep(10)
    timer.stop()

asyncio.run(main())
```


## Working Examples

For concrete examples showing actual working code using these classes, see the example code in the `examples/` directory:

- [examples/BasicTimerExample.py](examples/BasicTimerExample.py) — basic `Timer` usage
- [examples/MultipleTimersExample.py](examples/MultipleTimersExample.py) — using multiple `Timer` instances
- [examples/SchedulePolicyTimerExample.py](examples/SchedulePolicyTimerExample.py) — using `SchedulePolicy` with `Timer`

---

## Build Package from Source

The project uses `pyproject.toml`. To build distribution archives install `build` and run:

```bash
pip install --upgrade build
python -m build
```

The above produces a `dist/` folder with `.whl` and `.tar.gz` files. You can also install locally with:

```bash
pip install .        # install from source
pip install -e .     # editable install for development
```

Alternatively, this repository includes `build_package.py`; you can run it if you prefer (it wraps standard build steps):

```bash
python build_package.py
```

---

## Run Tests

The tests are in the `tests/` directory and use `unittest`'s async test support. You can run them with `unittest` or with `pytest`.

Run with unittest (cross-platform):
```bash
python -m unittest discover -v
```

Run with pytest (if installed):
```bash
pip install pytest
pytest -q
```

Platform-specific helper scripts are provided:
- Windows: `run_tests.bat`
- Unix/macOS: `run_tests.sh`

---

## Notes & Troubleshooting

- The utilities depend only on Python's standard library (`asyncio`, `datetime`, etc.). Tests use `unittest.IsolatedAsyncioTestCase` which requires Python 3.8+.
---

## License

MIT
