semvec/pypi-packages huggingface dataset:
marshmallow-mongoengine-query-schema 1.3
Marshmallow schema for generating mongoengine filters in url query.
License: MIT
Keywords: mongoengine,marshmallow,schema

# Marshmallow Mongoengine Query Schema
## _Mongoengine filters in your API with no effort!_

A marshmallow schema for use in url query which checks for possible mongoengine [query filters](https://docs.mongoengine.org/guide/querying.html) (as well as `only` and `order_by` args)
and converts their types based on requirements for filters (eg. ints for number comparition operators)
and fields themselves (eg. list inner type when using for example `list__0`)

Supports all mongoengine filters except [geo queries](https://docs.mongoengine.org/guide/querying.html#geo-queries)

> *Note: This has nothing to do with [marshmallow-mongoengine](https://pypi.org/project/marshmallow-mongoengine/), I just couldn't think of better name*

### Usage:
```py
from marshmallow_mongoengine_query_schema import QuerySchema


class SomeQuerySchema(QuerySchema):
    __query_fields__ = SomeSchema().declared_fields
    class Meta:  # optional settings
        query_enable_filters = False
        query_enable_only = True
        query_enable_order_by = False
        query_allowed_infixes = ['__']
```

### Usage in url:
```
example.com/someendpoint?no_comments=5&name__startswith=b&list__size=2&list__0=somestring
```
Every type is converted automatically but there's couple of things to point out:
> When list type is needed, comma delimited list is used in url: `?list=a,b,c,d`

> `match` operator and `__raw__` are expecting a dictionary(json): `?__raw__={"name": "hello"}`

### Installation
Very complicated black magic stuff:
```sh
pip3 install marshmallow_mongoengine_query_schema
```

### License

MIT
Tanker 0.8.9
Tanker is a Python database library targeting analytic operations
License: MIT

Tanker is a Python database library targeting analytic operations but
it also fits most transactional processing.

As its core it's mainly a query builder that simplify greatly the join
operations. It also comes with an way to automatically create the
database tables based on your schema definition.

Currently Postgresql and Sqlite are supported and the API is made to
seamlessly integrate with pandas DataFrames.
mildom-dl 0.0.3
"Command-line program to download videos from Mildom.com"
License: MIT

# Mildom_dl

this project is currently under development.

([日本語](https://github.com/NDSLib/mildom_dl/blob/master/README-JA.md)/English)

## How to install mildom_dl
```bash
$ pip3 install git+https://github.com/NDSLib/mildom_dl
```


## TODO
- [x] archive download
- [x] live download
- [x] command support
- [ ] Resolution Change support

## Usage


```bash
$ mildom-dl -u https://www.mildom.com/playback/10738086?v_id=10738086-1598025891 -o out.mp4
```

or 

```py
from mildom_dl.mildomDL import MildomDL

mdl = MildomDL(url="https://www.mildom.com/playback/10738086?v_id=10738086-1598025891")
mdl.download("test.mp4")
```

### 切り抜いて保存(not working)

args :
    -s : start（seconds)
    -e : end (seconds)


```bash
$ mildom-dl -u https://www.mildom.com/playback/10738086?v_id=10738086-1598025891 -s 30 -e 530 -o out.mp4
```
or 
```py
...
mdl.download("test.mp4",start=30,end=530)
```

# args
```
-u URL
-o output filename

-s start time (seconds)
-e end time (seconds)
```