معرفی شرکت ها
daachorse-0.1.7
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشتر
تبلیغات ما
مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.
مشاهده بیشترتوضیحات
A fast implementation of the Aho-Corasick algorithm using the compact double-array data structure
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | daachorse-0.1.7 |
| نام | daachorse |
| نسخه کتابخانه | 0.1.7 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Koichi Akabe <vbkaisetsu@gmail.com> |
| ایمیل نویسنده | Koichi Akabe <vbkaisetsu@gmail.com> |
| آدرس صفحه اصلی | https://github.com/daac-tools/python-daachorse |
| آدرس اینترنتی | https://pypi.org/project/daachorse/ |
| مجوز | MIT OR Apache-2.0 |
# python-daachorse
[daachorse](https://github.com/daac-tools/daachorse) is a fast implementation of the Aho-Corasick algorithm using the compact double-array data structure.
This is a Python wrapper.
[](https://pypi.org/project/daachorse/)
[](https://github.com/vbkaisetsu/python-daachorse/actions)
[](https://python-daachorse.readthedocs.io/en/latest/?badge=latest)
## Installation
### Install pre-built package from PyPI
Run the following command:
```
$ pip install daachorse
```
### Build from source
You need to install the Rust compiler following [the documentation](https://www.rust-lang.org/tools/install) beforehand.
daachorse uses `pyproject.toml`, so you also need to upgrade pip to version 19 or later.
```
$ pip install --upgrade pip
```
After setting up the environment, you can install daachorse as follows:
```
$ pip install git+https://github.com/daac-tools/python-daachorse
```
## Example usage
Daachorse contains some search options,
ranging from basic matching with the Aho-Corasick algorithm to trickier matching.
All of them will run very fast based on the double-array data structure and
can be easily plugged into your application as shown below.
### Finding overlapped occurrences
To search for all occurrences of registered patterns
that allow for positional overlap in the input text,
use `find_overlapping()`. When you instantiate a new automaton,
unique identifiers are assigned to each pattern in the input order.
The match result has the character positions of the occurrence and its identifier.
```python
>> import daachorse
>> patterns = ['bcd', 'ab', 'a']
>> pma = daachorse.Automaton(patterns)
>> pma.find_overlapping('abcd')
[(0, 1, 2), (0, 2, 1), (1, 4, 0)]
```
### Finding non-overlapped occurrences with standard matching
If you do not want to allow positional overlap, use `find()` instead.
It performs the search on the Aho-Corasick automaton
and reports patterns first found in each iteration.
```python
>> import daachorse
>> patterns = ['bcd', 'ab', 'a']
>> pma = daachorse.Automaton(patterns)
>> pma.find('abcd')
[(0, 1, 2), (1, 4, 0)]
```
### Finding non-overlapped occurrences with longest matching
If you want to search for the longest pattern without positional overlap in each iteration,
use `MATCH_KIND_LEFTMOST_LONGEST` in the construction.
```python
>> import daachorse
>> patterns = ['ab', 'a', 'abcd']
>> pma = daachorse.Automaton(patterns, daachorse.MATCH_KIND_LEFTMOST_LONGEST)
>> pma.find('abcd')
[(0, 4, 2)]
```
### Finding non-overlapped occurrences with leftmost-first matching
If you want to find the the earliest registered pattern
among ones starting from the search position,
use `MATCH_KIND_LEFTMOST_FIRST`.
This is so-called *the leftmost first match*, a bit tricky search option.
For example, in the following code,
`ab` is reported because it is the earliest registered one.
```python
>> import daachorse
>> patterns = ['ab', 'a', 'abcd']
>> pma = daachorse.Automaton(patterns, daachorse.MATCH_KIND_LEFTMOST_FIRST)
>> pma.find('abcd')
[(0, 2, 0)]
```
## License
Licensed under either of
* Apache License, Version 2.0
([LICENSE-APACHE](LICENSE-APACHE) or http://www.apache.org/licenses/LICENSE-2.0)
* MIT license
([LICENSE-MIT](LICENSE-MIT) or http://opensource.org/licenses/MIT)
at your option.
نحوه نصب
نصب پکیج whl daachorse-0.1.7:
pip install daachorse-0.1.7.whl
نصب پکیج tar.gz daachorse-0.1.7:
pip install daachorse-0.1.7.tar.gz