semvec/pypi-packages huggingface dataset:
movie-file-fixer 0.3.0
Given a directory of poorly formatted movie files, `movie-file-fixer` will create a beautifully formatted library of films folders, complete with posters, subtitles, and IMDb metadata.
License: MIT
Keywords: movies television backups multimedia omdb api imdb metadata

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# movie-file-fixer

Given a directory of poorly formatted movie files, `movie-file-fixer` will create a beautifully formatted directory of films folders, complete with posters, subtitles, and IMDb metadata.

## Algorithm
Given a directory string,
1. `folderize()` - Prepare the directory space.

    - Place all single files (except `contents.json` and `errors.json`) into folders using the file name. - [`Folderizer`]

    - Pull all subtitle files out of `subs` folders if they exist.
2. `cleanup()` - Folder cleanup.

    - Remove non-movie files, based on a list of "bad" extensions (i.e., .nfo, .txt, etc.) - [`FileRemover`]
3. `format()` - Format folders, movie files, and relevant metafiles based on IMDb movie titles.

    - Rename the movie file and folder (i.e., `<movie_title> [<year_of_release>]`) - [`Formatter`]

    - Create a `contents.json` file to store the metadata, including poster URLs.

    - Create an `errors.json` file to contain any files or folders that had issues being formatted.
4. `get_posters()` - Download the movie poster and name the file `poster.<extension>` (where `<extension>` is the original extension of the poster file) - [`PosterFinder`]
5. `get_subtitles()` - Download the subtitles using SubDb (http://thesubdb.com/) and an md5 hash of the movie file and name the file `<movie_title> [<year_of_release>].srt` - [`SubtitleFinder`]
primer-kit 0.1.1a0
Primer is a lightweight toolbox for debugging and benchmarking Python code.
License: MIT
Requires Python: >=3.5
Keywords: debug,benchmark

Primer
======

Primer is a lightweight toolkit for debugging and benchmarking Python code.

With only one line inserted, primer improves your coding experience.

```python
from primer import debug, profile, performance
```

Install
-------

Requirements
- Python >= 3.5

```bash
pip install primer-kit
```

Debug
-----

Exception hook helps you debug your code whenever exception is raise.

```python
debug.setup_hook()
```

Call decorator monitors every call to the function and its arguments.

```python
@debug.call
def my_function(args):
```

Profile
-------

Time and memory profilers measure the duration and memory allocation for some code.

```python
with profile.time(), profile.memory():
```

They can also be used as decorators over functions. A log frequency of 10 outputs results once per 10 calls.

```python
@profile.time(log_frequency=10)
def my_function(args):
```

Performance
-----------

Slot decorator converts all member variables to static slots, which saves memory and runs faster.

```python
@performance.slot
class MyClass(object):
```

Shared ndarray can be passed across processes without copy, which saves memory by several times and runs faster.

```python
import numpy as np
import multiprocessing as mp

arrays = [performance.SharedNDArray(np.random.rand(100000)) for _ in range(4)]
results = mp.Pool(4).map(np.sum, arrays)
```