semvec/pypi-packages huggingface dataset:
genuine-bs-shengxio 1.2.3
A complete random content generator created based on en_core_web_md vocabulary.
Requires Python: >=3.6

# Welcome to Genuine BS!

Inspired by project Genuine-fake, I decided to create a package to help people that have needs to create or test random large text functionality to save time and create random text.
You may find the details of the inspiring project link here: [https://pypi.org/project/Genuine-fake/]

## What does it do?

Just as the name suggest, it will produce completely random text (BS) in a common text format. Please note that at this phase of the project, grammar and semantics are in the scope, nor do I intend to add them in. The text from this package is completely random.

## Why

During my development time for the database, I realized that there are no existing easy methods to create random text strings to simulate real world content input. With that thought in mind, I decided to create this package for countering the situation.

## How to use it

### To install:

```markdown
$ pip install genuine-bs-shengxio
```

### Usage

```markdown
from genuine_bs import bs

bs.rand_username()
bs.rand_version())
bs.rand_url()
bs.rand_ip()
bs.rand_list()
bs.rand_words()
bs.rand_sentence()
bs.rand_paragraph()
bs.rand_article()

```

## Support or Contact

Please leave comments or issue in the github repo page. Let me know if you questions or concerns. Thanks!
sqlwhatTranslated 1.0.1
rus sqlwhat
Requires Python: >=3.6

# sqlwhat

[![Build Status](https://travis-ci.org/datacamp/sqlwhat.svg?branch=master)](https://travis-ci.org/datacamp/sqlwhat)
[![codecov](https://codecov.io/gh/datacamp/sqlwhat/branch/master/graph/badge.svg)](https://codecov.io/gh/datacamp/sqlwhat)
[![PyPI version](https://badge.fury.io/py/sqlwhat.svg)](https://badge.fury.io/py/sqlwhat)

`sqlwhat` enables you to write Submission Correctness Tests (SCTs) for interactive SQL exercises on DataCamp.

- If you are new to teaching on DataCamp, check out https://authoring.datacamp.com.
- If you want to learn what SCTs are and how they work, visit [this article](https://authoring.datacamp.com/courses/exercises/technical-details/sct.html) specifically.
- For more information about writing SCTs for SQL exercises, consult https://sqlwhat.readthedocs.io.

## Installing

```
pip install sqlwhat     # install from pypi
make install            # install from source
```

## Reference

* API Docs: https://sqlwhat.readthedocs.io
* AST viewer: https://ast-viewer.datacamp.com
* Extensions: https://github.com/datacamp/sqlwhat-ext

## Raising issues with how SQL is parsed

Please raise an issue on the respsective parser repo:

* [antlr-tsql](https://github.com/datacamp/antlr-tsql)
* [antlr-psql](https://github.com/datacamp/antlr-plsql)

## Basic Use

```python
from sqlwhat.State import State    # State holds info needed for tests
from sqlwhat.Reporter import Reporter
from sqlwhat.checks import *       # imports all SCTs
from sqlalchemy import create_engine

code = "SELECT * FROM artists WHERE id < 100"

state = State(
    student_code = code,
    solution_code = code,
    pre_exercise_code = "",
    student_conn = create_engine('sqlite:///'),
    solution_conn = create_engine('sqlite:///'),
    student_result = {'id': [1,2,3], 'name': ['greg', 'jon', 'martha']},
    solution_result = {'id': [1,2,3], 'name': ['toby', 'keith', 'deb']},
    reporter = Reporter()
    )

# test below passes, since code is equal for student and solution
has_equal_ast(state)

# test below raises a TestFail error, since 'name' col of results
# doesn't match between student and solution results
check_result(state)
# shows error data
state.reporter.build_payload()

# can also be done using a chain
from sqlwhat.sct_syntax import Ex
Ex(state).check_result()
```

## Running unit tests

```bash
pytest -m "not backend"
```

If you also want to run the backend tests, you need to set a `GITHUB_TOKEN` environment variable with access to the (private) `sqlbackend` repository.
After this, you can:

```bash
make install
pytest
```

### Rules of testing

1. Running queries is the backend's job
2. If a test doesn't run queries, it doesn't need the backend
3. Very few tests should run queries

## Building Docs

Install sqlwhat and run ..

```
cd docs
make html
```
DiST-Net 0.1.5
keras implementation of DiSTNet & utilities for mother machine data analysis with keras
Requires Python: >=3
Keywords: Segmentation,Tracking,SelfAttention,Tensorflow,Keras

# DistNet: Deep Tracking by displacement regression: application to bacteria growing in the __Mother Machine__

[Link to preprint](https://arxiv.org/abs/2003.07790)

This repo contains sources for:
- Distnet model keras/tensorflow implementation (link to pre-print). Tu use: `disnet.keras_models.get_distnet_model()`
- Flexible keras unet implementation / unet++ implementatoin. See: `disnet.keras_models.unet.py`
- A class of dataset_iterator for training: `distnet.data_generator.dy_iterator.py`
- A class of image data generator with specific transformations for mother machine data. See `distnet.data_generator.image_data_generator_mm.py`
- Utilities for models in keras/tensorflow and image processing. See `distnet.utils.pre_processing.py`
python-driver 0.0.2
parker motion ipa python driver
Requires Python: >=3.6

# About

A Python driver for the "Intelligent Parker Amplifier" or IPA servo drive/controller by Park Motion

Model: IPA04-HC
Product Page: http://www.parkermotion.com/products/Servo_Drive_Controllers__7313__30_32_80_567_29.html

## Setting up a development environment

```bash
# Create virtual enviroment
python -m venv .venv

# Activate virtual environment Unix/MacOs
source .venv/Scripts/activate
# or activate on Windows
.venv\Scripts\activate.bat

# Upgrade pip (depending on the Python version installed, a newly created virtual environment will how have a version of pip that is vastly out of date)
python -m pip install --upgrade pip

# Install required packages
pip install -r requirements.txt
```

## Helpful Resources

### Parker Motion Manager (PPM)

- Location: `/product_materials/Software/Parker Motion Manager Ver 2.2.1050/pmm_installer_2_2_1050.exe`
- Allows you to interact with the rail
- Has useful help documents
  - See "Parameter Reference"
  - C:\Program Files (x86)\Parker Hannifin\Parker Motion Manager\Help Files\Reference Guides.chm
- Parker Motion Manager Guide:
  - \User Guides\ACR_Programmers_Guide.pdf

### Reference IPA Add-on Instructions

- Location: `/product_materials/Software/Add On Instructions v5/IPA_AOI_Rev5.zip/IPA_AOI_v5/EthernetIP_IPA_B.pdf`
- Location: `/product_materials/Software/Add On Instructions v5/IPA_AOI_Rev5.zip/IPA_AOI_v5/Information/IPA Ethernet IP Parameter Mapping.xlsx`
- .L5X files are presumably used with certain PLC software, but there is some useful reference material in the pdfs.

### ComACRServer6 Communications Server

- Location: `/product_materials/Software/ComACRServer6x`
- An automation server that provides communications between ACR controllers and PC software applications
- Includes samples applications in VB.NET, C#, C++ and VB6

### pycomm3 documentation

- https://docs.pycomm3.dev/en/latest/index.html
- Useful pages:
  - https://docs.pycomm3.dev/en/latest/usage/cipdriver.html
  - https://docs.pycomm3.dev/en/latest/examples/generic_messaging_examples.html#generic-messaging
  - https://docs.pycomm3.dev/en/latest/api_reference/data_types.html