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eldar-0.0.8
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Boolean text search in Python
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | eldar-0.0.8 |
| نام | eldar |
| نسخه کتابخانه | 0.0.8 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Maixent Chenebaux |
| ایمیل نویسنده | max.chbx@gmail.com |
| آدرس صفحه اصلی | https://github.com/kerighan/eldar |
| آدرس اینترنتی | https://pypi.org/project/eldar/ |
| مجوز | - |
# Boolean text search using Eldar
## Getting Started
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
### Installing
You can install the method by typing:
```
pip install eldar
```
### Basic usage
```python
from eldar import Query
# build list
documents = [
"Gandalf is a fictional character in Tolkien's The Lord of the Rings",
"Frodo is the main character in The Lord of the Rings",
"Ian McKellen interpreted Gandalf in Peter Jackson's movies",
"Elijah Wood was cast as Frodo Baggins in Jackson's adaptation",
"The Lord of the Rings is an epic fantasy novel by J. R. R. Tolkien"]
eldar = Query('("gandalf" OR "frodo") AND NOT ("movie" OR "adaptation")')
# use `filter` to get a list of matches:
print(eldar.filter(documents))
# >>> ["Gandalf is a fictional character in Tolkien's The Lord of the Rings",
# 'Frodo is the main character in The Lord of the Rings']
# call to see if the text matches the query:
print(eldar(documents[0]))
# >>> True
# by default, words must match. Thus, "movie" != "movies":
print(eldar(documents[2]))
# >>> True
```
You can also use it to mask Pandas DataFrames:
```python
from eldar import Query
import pandas as pd
# build dataframe
df = pd.DataFrame([
"Gandalf is a fictional character in Tolkien's The Lord of the Rings",
"Frodo is the main character in The Lord of the Rings",
"Ian McKellen interpreted Gandalf in Peter Jackson's movies",
"Elijah Wood was cast as Frodo Baggins in Jackson's adaptation",
"The Lord of the Rings is an epic fantasy novel by J. R. R. Tolkien"],
columns=['content'])
# build query object
eldar = Query('("gandalf" OR "frodo") AND NOT ("movie" OR "adaptation")')
# eldar's call returns True if the text matches the query.
# You can filter a dataframe using pandas mask syntax:
df = df[df.content.apply(eldar)]
print(df)
```
### Parameters
There are three parameters that you can adjust in the query builder.
By default:
```python
Query(..., ignore_case=True, ignore_accent=True, match_word=True)
```
Let the query be ```query = '"movie"'```:
* If `ignore_case` is True, the documents "Movie" and "movie" will be matched. If False, only "movie" will be matched.
* If `ignore_accent` is True, the documents "mövie" will be matched.
* If `match_word` is True, the document will be tokenized and the query terms will have to match exactly. If set to False, the documents "movies" and "movie" will be matched. Setting this option to True may slow down the query.
### Wildcards
Queries also support `*` as wildcard character. Wildcard matches any number (including none) of alphanumeric characters.
```python
from eldar import Query
# sample document and query with multiple wildcards:
document = "Gandalf is a fictional character in Tolkien's The Lord of the Rings"
eldar = Query('"g*dal*"')
# call to see if the text matches the query:
print(eldar(document))
# >>> True
```
### Building an index for faster queries
Searching in a large corpus using the Query object is slow, as each document has to be checked.
For (much) faster queries, create an `Index` object, and build it using a list of documents.
```python
from eldar import Index
from eldar.trie import Trie
documents = [
"Gandalf is a fictional character in Tolkien's The Lord of the Rings",
"Frodo is the main character in The Lord of the Rings",
"Ian McKellen interpreted Gandalf in Peter Jackson's movies",
"Elijah Wood was cast as Frodo Baggins in Jackson's adaptation",
"The Lord of the Rings is an epic fantasy novel by J. R. R. Tolkien",
"Frodo Baggins is a hobbit"
]
index = Index(ignore_case=True, ignore_accent=True)
index.build(documents) # must only be done once
# persist and retrieve index from disk
index.save("index.p") # but documents are copied to disk
index = Index.load("index.p")
print(index.search('"frodo b*" AND NOT hobbit')) # support wildcards
print(index.count('"frodo b*" AND NOT hobbit')) # shows only the count
# to only return document ids, set `return_ids` to True:
print(index.search('"frodo b*" AND NOT hobbit', return_ids=True))
```
It works like a usual search engine does: by keeping a dictionary that maps each word to its document ids. The boolean query is turned into an operation tree, where document ids are joined or intersected in order to return the desired matches.
## License
This package is MIT licensed.
نحوه نصب
نصب پکیج whl eldar-0.0.8:
pip install eldar-0.0.8.whl
نصب پکیج tar.gz eldar-0.0.8:
pip install eldar-0.0.8.tar.gz