semvec/pypi-packages huggingface dataset:
mlfinlab 0.0.1
This is a PyPI placeholder for the MlFinLab package.
Requires Python: <3.9,>=3.6
Keywords: machinelearning,finance,investment,education

<div align="center">
   <a href="https://hudsonthames.org/">
   <img src="https://raw.githubusercontent.com/PanPip/mlfinlab/master/docs/source/logo/Hudson%20%26%20Thames_verticalblack.png" height="300"><br>
   <a/>
</div>


-----------------
# Machine Learning Financial Laboratory (MlFinLab)
MlFinlab is a python package which helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools. 

## Note

* This PyPI placeholder for the MlFinLab package. To get access to the MlFinLab package visit https://portal.hudsonthames.org
gmailify 1.0.0
This tool validates if gmail addresses and corporate emails with google mail servers are valid without being authenticated. The default thread is 10 to avoid being rate limited.
Requires Python: >=3.6

# gmailify
This tool validates if gmail addresses and corporate emails with google mail servers are valid without being authenticated. The default thread is 10 to avoid being rate limited.

# Installation
```
python -m pip install gmailify
```

## Check a single gmail address
```
python -m gmailify -e example@gmail.com
```
## Input from file
```
python -m gmailify -f emails.txt
```
## Pass through proxy
```
python -m gmailify -p http://127.0.0.1:8080 -f emails.txt
```
## Output to a file
```
python -m gmailify -f emails.txt -o output.txt
```
pydockercompose-pkg-dadianas 0.0.1
Package to generate docker compose files.
Requires Python: >=3.6

# pydockercompose 
## Description

This package is a python package for generating Docker Compose file.
It contains two classes :
*   DockerCompose : which represent represent docker-compose file.
    In this version, it supports adding the following parameters:
       -  version
       -  services
       -  volumes
       -  networks
*   Service: This class represent docker compose service. 
    In this version, Service class supports adding the following parameters:
    *   image
    *   build
    *   container_name
    *   environment
    *   restart
    *   ports
    *   volumes
    *   networks
    *   ulimits
    *   links

To find out more about these parameters, you can check [docker-compose](https://docs.docker.com/compose/compose-file/compose-file-v3/) documentation.

## Usecase

In this example we used `pydockercompose` package to generate `docker-compose.yml` for :
- ElasticSearch service
- ElasticSearch Client service that will be built using Dockerfile.

        import pydockercompose
        import os,sys

        def generate_elastic_docker_compose_file():
            docker_compose = DockerCompose(version="3.3")
        
            # Create ElasticSearch service.
            elastic_svc = Service(container_name="es",
                                  image="elasticsearch:7.13.3",
                                  restart="on-failure",
                                  ports=["9200:9200"],
                                  networks=["es-network"],
                                  volumes=["es-data:/usr/share/elasticsearch/data"],
                                  environments=["discovery.type=single-node"])
            elastic_svc.set_ulimits("memlock", {"soft": -1, "hard": -1})
        
            # Create ElasticSearch Customer service.
            cmd = "while [ 1 -e 1 ]; do curl 'http://es:9200/' && sleep 3 ; done"
            with open("Dockerfile", "w") as dockerfile:
                dockerfile.write("FROM alpine:3\nRUN apk add curl\nCMD "+cmd)
            customer_svc = Service(container_name="es-customer",
                                   build=".",
                                   restart="on-failure",
                                   depends_on=["es"],
                                   networks=["es-network"])
        
            # Add services to DockerCompose object.
            docker_compose.add_service("es", elastic_svc)
            docker_compose.add_service("es-customer", customer_svc)
        
            # Add the network es-network
            docker_compose.add_network("es-network", {"driver": "bridge"})
        
            # Add the volume es-data
            docker_compose.add_volumes("es-data", {"driver": "local"})
            return docker_compose
        
        
        if __name__ == '__main__':
            generate_elastic_docker_compose_file().to_yaml()
            os.system("docker-compose up")
flask-errors-as-nested-dicts 0.0.1
Changes standard flask and jwt errors format
Requires Python: >=3.6

# Flask Errors as Nested Dicts
This extension was developed for personal use and changes standard flask and jwt response errors to nested dicts, i. e.


```javascript
{
  "code": 404,
  "status": "Not Found"
}
```

to:

```javascript
{
  "errors": {
    "json": {
      "url": [
        "Does not exist."
      ]
    }
  }
}
```

Installing
----------

Install and update using pip:

```bash
$ pip install flask-errors-as-nested-dicts
```

Usage
----------------

```python
from flask import Flask
from flask_jwt_extended import JWTManager

app = Flask(__name__)
jwt = JWTManager(app)
ErrorsAsNestedDicts(app, jwt)

```
sas2sqlite3 0.0.2
Import sas7bdat files to sqlite3 dbase
Requires Python: >=3.6

# sas2sqlite3

Import sas7bdat files to sqlite3 dbase. Uses the [sas7bdat][sas7bdat] SAS 
dataset file parser.

Command-line and python library interface with minimal requirements.


## CLI usage

Create and import data into `some_dataset` table in `some_sqlite.db`

```sh
sas2sqlite some_dataset.sas7bdat some_sqlite.db
```

Import data into existing `some_table` table in `some_sqlite.db`

```sh
sas2sqlite some_dataset.sas7bdat some_sqlite.db --table some_table --no-create-table
```

Import data storing dates and datetimes as Julian days, and times as `HH:MM`:

```sh
sas2sqlite some_dataset.sas7bdat some_sqlite.db \
    --time "%H:%M" --date julian --datetime julian
```


## Install

_Requires python 3.6+ and pip._

```sh
pip install sas2sqlite3
```

_Note: the package has a '3' at the end. The executable does not._


## Other tools

- [sas2db][sas2db]: Import SAS dataset and XPT files to any database supported
  by [SQL Alchemy][SQLAlchemy]. Uses [pandas][pandas] SAS parser under the hood.


[sas7bdat]: https://pypi.org/project/sas7bdat
[sas2db]: https://pypi.org/project/sas2db
[SQLAlchemy]: https://www.sqlalchemy.org
[pandas]: https://pandas.pydata.org
brange 1.1.0.post1
A range which automatically deals with either direction.
Requires Python: >=3.9,<4.0

# Better Range

A range which automatically deals with either direction.


### Installation
```
pip install brange
```

### Usage

Start is always inclusive and end is always exclusive. Step must be a positive integer, as it always steps toward the end. A negative value will result in an empty range.

#### Regular

```py
from brange import brange

# This will create a list between 10 (inclusive) and -40 (exclusive)
# [10, 11, 12, ... -37, -38, -39]
[i for i in brange(10, -40)]
```

#### N-dimensional

```py
from brange import nbrange

dimensions = [
    (1, 10, 2), # X
    (3, -2, 1), # Y
    (-2, 5, 1), # Z
]

[xyz for xyz in nbrange(*dimensions)]

# This will result in a list as below:
# [
#     (1, 3, -2),
#     (1, 3, -1),
#     ...
#     (9, -1, 2),
#     (9, -1, 3),
#     (9, -1, 4),
# ]
```
tr-id-validator 0.0.3
Turkish ID Validator control Turkish ID validity status
Requires Python: >=3.9
Keywords: data science,python,


# Turkish Identification Number Validator

Turkish Identification Number is a unique personal identification number that is assigned to every citizen of Turkey.
You are developing project for your Turkish client and if you don't know to validate Turkish ID number you are in the correct place.
**tr_id_validator** provides information about validity of given ID number.




## Installation

Install project with git command line

```bash
  pip install tr-id-validator==0.0.3
```
    
## Usage/Examples

```python
from tr_id_validator.src.tr_id_validator.tr_id_validator import check_turkish_id

tr_id_list = ["12345678901",
              "12345678901",
              "12345678901",
              "12345678901"]

for tr_id in tr_id_list:
    if (check_turkish_id(tr_id)):
        print("TR ID Number Valid", tr_id)
    else:
        print("TR ID Number Invalid", tr_id)

```
## Features

- Validity status of Turkish ID number
 
  
## Author

- Github : [Hasan Ozdemir](https://www.github.com/hasanozdem1r)