semvec/pypi-packages huggingface dataset:
dataMovies 0.0.15
Movies datasets package based on Imdb API.
Requires Python: >=3.8


# Table of Contents

1.  [Description 😊](#org660b55e)
    1.  [Maintainers 👨👩👧👦](#orged9041f)
2.  [Prerequisites 🏁](#org40169ba)
3.  [Installation ✅](#orgbdd3be0)
4.  [Usage 😁](#org0d50776)
5.  [Run tests ⚙](#org5f6690e)
    1.  [Clone the repository](#org40cf692)
    2.  [run unit tests](#org397d5e4)



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# Description 😊

DataMovies is a data-science focused library that allows you to request movies/series dataset via ImDb&rsquo;s API.

Available for now:

-   search all users reviews for a specific movie
-   search all ratings distributions for a specific movie
    -   statistic by ratings
    -   ratings per age range for man
    -   ratings per age range for woman
    -   ratings per age range for all


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## Maintainers 👨👩👧👦

-   [@rizerkrof](https://github.com/rizerkrof)
-   [@Zuwhity](https://github.com/Zuwhity)
-   [@HaozGU](https://github.com/HaozGU)


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# Prerequisites 🏁

-   Python >= 3.8
-   pip


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# Installation ✅

From [official repository](https://pypi.org/project/dataMovies/):

    pip install dataMovies


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# Usage 😁

Look at the [example](https://github.com/rizerkrof/libray-dataMovies/tree/main/example) to know more about the use. Do not forget to check the [documentation](https://rizerkrof.github.io/libray-dataMovies/dataMovies/dataMovies.html) to see all features information!


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# Run tests ⚙


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## Clone the repository

    git clone https://github.com/rizerkrof/libray-dataMovies.git
    cd libray-dataMovies


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## run unit tests

    python3 -m unittest discover --top-level-directory=. --start-directory=./tests/tests_dataMovies/
aiotorndb 0.2
asynchronous tornado database connection
Requires Python: >=3.7

[torndb](https://github.com/bdarnell/torndb) rewrite to asynchronous

## Example

First get a connection object

```python
from aiotorndb import Connection

conn = Connection(
    host="127.0.0.1",
    db="test",
    user="root",
    password="123456",
    port=3306,
    time_zone="+8:00",
    charset="utf8",
)
```

Next, you can use methods such as select, update, insert, delete, etc.

```python
import asyncio

async def test():
    get_result = await conn.get("select * from user where id = 1")
    print(get_result)
    # {'id': 1, 'name': 'tom'}

    select_result = await conn.select("select * from user")
    print(select_result)
    # [{'id': 1, 'name': 'tom'}, {'id': 2, 'name': 'ellis'}]

    update_result = await conn.update("update user set name = %(name)s where id = 1", name="eddie")
    print(update_result)
    # 1

    insert_result = await conn.insert("insert into user (name) values (%(name)s)", name="dav")
    print(insert_result)
    # 3

    # sql = select * from user where id in (1, 3)
    select_result2 = await conn.select("select * from user where id in %(user_ids)s", user_ids=[1, 3])
    print(select_result2)
    # [{'id': 1, 'name': 'eddie'}, {'id': 3, 'name': 'dav'}]

    # sql = select * from project_tag where name like '%e%'
    select_result3 = await conn.select("select * from project_tag where name like %(name)s", name="%e%")
    print(select_result3)
    # [{'id': 1, 'name': 'eddie'}, {'id': 2, 'name': 'ellis'}]

asyncio.run(test())
```