semvec/pypi-packages huggingface dataset:
aio-omdb 0.0.3
Asyncronous and synchronous Python client for OMDb (the Open Movie Database)
Requires Python: >=3.9
Keywords: omdb

# aio-omdb
Asyncronous and synchronous Python clients for OMDb ([the Open Movie Database](https://www.omdbapi.com)).

## Usage

```python
from aio_omdb.client import AsyncOMDBClient, SyncOMDBClient

OMDB_API_KEY = '...'  # Get your key from OMDB

a_client = AsyncOMDBClient(api_key=OMDB_API_KEY)
s_client = SyncOMDBClient(api_key=OMDB_API_KEY)

# Client provides the following methods:

# Get by IMDB ID
await a_client.get_by_id('tt1000252')
s_client.get_by_id('tt1000252')

# Get by exact title
await a_client.get_by_id('Rome, open city')
s_client.get_by_id('Rome, open city')

# Search title by a word or phrase
await a_client.search('Spock')
s_client.search('Spock')
```

The following exceptions may be raised:
- `aio_omdb.exc.InvalidAPIKey`: if an invalid API key is used;
- `aio_omdb.exc.MovieNotFound`: if no movie can be found in `get_by_id` or `get_by_title`.


## Testing

1. Install the `testing` extras

```bash
pip install -Ue .[testing]
```

2. Create file `.env` in the project root and put your OMDb API key there:

```
OMDB_API_KEY=<your API key>
```

3. Run tests

```bash
make test
```

Enjoy!
namdtoolsnamdtools 0.2.dev41
A Python interface to NAMD

.. image:: namdtools.svg
   :alt: namdtools
   :height: 200

a Python interface to NAMD
http://www.ks.uiuc.edu/Research/namd/

..
   master

.. image:: https://img.shields.io/pypi/v/namdtools
   :target: https://pypi.org/project/namdtools/

.. image:: https://img.shields.io/codecov/c/github/clockhart/namdtools/master
   :target: https://codecov.io/gh/clockhart/namdtools

..
   *dev:*
   <nobr><img src="https://img.shields.io/travis/com/lockhartlab/molecular/dev"  alt="build-status-dev"/></nobr>
   <nobr><img src="https://img.shields.io/codecov/c/github/lockhartlab/molecular/dev" alt="coverage-dev"/></nobr>

note that this package is **still in development**
at this stage, I'm only building thing as they come to mind  
version 1.0 will be the first major release  
until then, consider this code heavily volatile

yet, install simply by calling `pip install namdtools` or `pip install --pre namdtools` for the latest development
release.

we endeavor to follow https://scikit-learn.org/stable/developers/performance.html

similar packages:
https://github.com/sunhwan/NAMD-replica
https://github.com/bio-phys/MDBenchmark
https://github.com/radakb/pynamd/