| Name | tzfpy JSON |
| Version |
0.15.5
JSON |
| download |
| home_page | None |
| Summary | Probably the fastest Python package to convert longitude/latitude to timezone name |
| upload_time | 2024-04-12 05:53:20 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
|
| VCS |
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| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
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| coveralls test coverage |
No coveralls.
|
# tzfpy [](https://pypi.org/project/tzfpy/) [](https://anaconda.org/conda-forge/tzfpy)
> [!NOTE]
>
> 0. It's probably the fastest Python package to convert longitude/latitude to
> timezone name.
> 1. This package use a simplified polygon data and not so accurate around
> borders.
> 2. Rust use lazy init, so first calling will be a little slow.
> 3. Use about 40MB memory.
> 4. It's tested under Python 3.9+ but support 3.8+(noqa).
## Usage
Please note that new timezone names may be added to tzfpy, which could be
incompatible with old version package like pytz. As an option, tzfpy supports
install compatible version of those packages with extra params.
```bash
# Install just tzfpy
pip install tzfpy
# Install tzfpy with pytz
pip install "tzfpy[pytz]"
# Install via conda, see more in https://github.com/conda-forge/tzfpy-feedstock
conda install -c conda-forge tzfpy
```
```python
>>> from tzfpy import get_tz, get_tzs
>>> get_tz(116.3883, 39.9289) # in (longitude, latitude) order.
'Asia/Shanghai'
>>> get_tzs(87.4160, 44.0400) # in (longitude, latitude) order.
['Asia/Shanghai', 'Asia/Urumqi']
```
## Performance
Benchmark runs under
[`v0.15.3`](https://github.com/ringsaturn/tzfpy/releases/tag/v0.15.3) on my
MacBook Pro with Apple M3 Max.
```bash
pytest tests/test_bench.py
```
```
------------------------------------------------------------ benchmark: 1 tests ------------------------------------------------------------
Name (time in ns) Min Max Mean StdDev Median IQR Outliers OPS (Kops/s) Rounds Iterations
--------------------------------------------------------------------------------------------------------------------------------------------
test_tzfpy_random_cities 837.4918 11,183.2982 1,973.3456 833.9543 1,820.9103 1,066.7020 6422;511 506.7536 20000 10
--------------------------------------------------------------------------------------------------------------------------------------------
Legend:
Outliers: 1 Standard Deviation from Mean; 1.5 IQR (InterQuartile Range) from 1st Quartile and 3rd Quartile.
OPS: Operations Per Second, computed as 1 / Mean
Results (1.95s):
4 passed
```
Or you can view more benchmark results on
[GitHub Action summary page](https://github.com/ringsaturn/tzfpy/actions/workflows/Test.yml).
## Background
`tzfpy` was originally written in Go named [`tzf`][tzf] and use CGO compiled to
`.so` to be used by Python. Since `v0.11.0` it's rewritten in Rust built on PyO3
and [`tzf-rs`][tzf-rs], a tzf's Rust port.
I have written an article about the history of tzf, its Rust port, and its Rust
port's Python binding; you can view it
[here](https://blog.ringsaturn.me/en/posts/2023-01-31-history-of-tzf/).
[tzf]: https://github.com/ringsaturn/tzf
[tzf-rs]: https://github.com/ringsaturn/tzf-rs
## Project status
`tzfpy` is still under development and it has been deployed into
[my current company](https://github.com/caiyunapp)'s production environment and
it works well under high concurrency for weather API and location related data
processed. So I think it's ready to be used in production with caution.
I haven't release the v1.0.0 yet and I will try my best to keep current API as
stable as possible(only 3 functions). I'm still working on performance
improvements on Rust side, which is a release blocker for both tzf-rs and tzfpy.
## Compare with other packages
Please note that directly compare with other packages is not fair, because they
have different use cases and design goals, for example, the precise.
### [TimezoneFinder](https://github.com/jannikmi/timezonefinder)
I got lots of inspiration from it. Timezonefinder is a very good package and
it's mostly written in Python, so it's easy to use. And it's much
[more widely used](https://github.com/jannikmi/timezonefinder/network/dependents)
compared with tzfpy if you care about that.
However, it's slower than tzfpy, especially around the borders, and I have lots
of API requests from there. That's the reason I created tzf originally. And then
tzf-rs and tzfpy.
### [pytzwhere](https://github.com/pegler/pytzwhere)
I recommend to read timezonefinder's
[Comparison to pytzwhere](https://timezonefinder.readthedocs.io/en/latest/3_about.html#comparison-to-pytzwhere)
since it's very detailed.
## LICENSE
This project is licensed under the [MIT license](./LICENSE). The data is
licensed under the
[ODbL license](https://github.com/ringsaturn/tzf-rel/blob/main/LICENSE), same as
[`evansiroky/timezone-boundary-builder`](https://github.com/evansiroky/timezone-boundary-builder)
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