# wordasso
small python package, several word association function based on datamuse API
## Installation
```
pip install wordasso
```
if it can not install spacy and the model needed automatically, you could fix this by installing it manually
```
pip install spacy
python -m spacy download en_core_web_sm
```
and then
```
pip install wordasso
```
## Usage
these functions are based on datamuse means like API which could be used to query 100 related words of a given word
### syn_words
return related words which has 'synonym' in tags list
```
>>> from wordasso.wordasso import syn_words
>>> print(syn_words("author"))
# output
['writer', 'source', 'generator']
```
### pho_words
return related words which sound like the key word most, default list size is 10.
```
>>> from wordasso.wordasso import pho_words
>>> print(pho_words("author"))
# output
['writer', 'actor', 'authorship', 'writers', 'drafter', 'reporter', 'owner', 'songwriter', 'signer', 'source']
>>> print(pho_words("author", L=5)
# output
['writer', 'actor', 'authorship', 'writers', 'drafter']
```
### ent_words
return Named Entities associated to the related words of the given word.
```
>>> from wordasso.wordasso import ent_words
>>> print(ent_words("author"))
# output
{French, Judeo, Christian, Islam, trustee, Medina, trustee, Judeo, Mecca, Muhammad}
```
small python package, several word association function based on datamuse API
## Installation
```
pip install wordasso
```
if it can not install spacy and the model needed automatically, you could fix this by installing it manually
```
pip install spacy
python -m spacy download en_core_web_sm
```
and then
```
pip install wordasso
```
## Usage
these functions are based on datamuse means like API which could be used to query 100 related words of a given word
### syn_words
return related words which has 'synonym' in tags list
```
>>> from wordasso.wordasso import syn_words
>>> print(syn_words("author"))
# output
['writer', 'source', 'generator']
```
### pho_words
return related words which sound like the key word most, default list size is 10.
```
>>> from wordasso.wordasso import pho_words
>>> print(pho_words("author"))
# output
['writer', 'actor', 'authorship', 'writers', 'drafter', 'reporter', 'owner', 'songwriter', 'signer', 'source']
>>> print(pho_words("author", L=5)
# output
['writer', 'actor', 'authorship', 'writers', 'drafter']
```
### ent_words
return Named Entities associated to the related words of the given word.
```
>>> from wordasso.wordasso import ent_words
>>> print(ent_words("author"))
# output
{French, Judeo, Christian, Islam, trustee, Medina, trustee, Judeo, Mecca, Muhammad}
```
Metadata
Release files for wordasso 0.2.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| wordasso-0.2.1.tar.gz | 4.4 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| wordasso-0.2.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 8.6 kB
Release files / wordasso-0.2.1.tar.gz
| Download URL | wordasso-0.2.1.tar.gz |
|---|---|
| Size | 4.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
89b5c1ce09106a9d1c55af5eba771c754a9aadae3439844a730ba1afe1a2f49e
|
|
BLAKE2b-256 checksum How to use checksums |
4b67584846547c23d52e0910a81886822e0c3e0c220d3b1cd826cb46c60e9e4f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
Release files / wordasso-0.2.1-py3-none-any.whl
| Download URL | wordasso-0.2.1-py3-none-any.whl |
|---|---|
| Size | 4.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
0305507a494cdf37bcc8c40568b5b8591515bb2d3df498461c01af70b7fc8733
|
|
BLAKE2b-256 checksum How to use checksums |
21638407c31045ac82d044a48b7af7870b1e27ff19214a8f37f8ed59626b1c3b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |