semvec/pypi-packages huggingface dataset:
csv2parquet 0.0.9
A tool to convert CSVs to Parquet files

# csv2parquet

[![Build Status](https://travis-ci.org/cldellow/csv2parquet.svg?branch=master)](https://travis-ci.org/cldellow/csv2parquet)
[![codecov](https://codecov.io/gh/cldellow/csv2parquet/branch/master/graph/badge.svg)](https://codecov.io/gh/cldellow/csv2parquet)

Convert a CSV to a parquet file. You may also find [sqlite-parquet-vtable](https://github.com/cldellow/sqlite-parquet-vtable) or
[parquet-metadata](https://github.com/cldellow/parquet-metadata) useful.

## Installing

If you just want to use the tool:

```
sudo pip install pyarrow csv2parquet
```

If you want to clone the repo and work on the tool, install its dependencies via pipenv:

```
pipenv install
```

## Usage

Next, create some Parquet files. The tool supports CSV and TSV files.

```
usage: csv2parquet [-h] [-n ROWS] [-r ROW_GROUP_SIZE] [-o OUTPUT] [-c CODEC]
                   [-i INCLUDE [INCLUDE ...] | -x EXCLUDE [EXCLUDE ...]]
                   [-R RENAME [RENAME ...]] [-t TYPE [TYPE ...]]
                   csv_file

positional arguments:
  csv_file              input file, can be CSV or TSV

optional arguments:
  -h, --help            show this help message and exit
  -n ROWS, --rows ROWS  The number of rows to include, useful for testing.
  -r ROW_GROUP_SIZE, --row-group-size ROW_GROUP_SIZE
                        The number of rows per row group.
  -o OUTPUT, --output OUTPUT
                        The parquet file
  -c CODEC, --codec CODEC
                        The compression codec to use (brotli, gzip, snappy,
                        zstd, none)
  -i INCLUDE [INCLUDE ...], --include INCLUDE [INCLUDE ...]
                        Include the given columns (by index or name)
  -x EXCLUDE [EXCLUDE ...], --exclude EXCLUDE [EXCLUDE ...]
                        Exclude the given columns (by index or name)
  -R RENAME [RENAME ...], --rename RENAME [RENAME ...]
                        Rename a column. Specify the column to be renamed and
                        its new name, eg: 0=age or person_age=age
  -t TYPE [TYPE ...], --type TYPE [TYPE ...]
                        Parse a column as a given type. Specify the column and
                        its type, eg: 0=bool? or person_age=int8. Parse errors
                        are fatal unless the type is followed by a question
                        mark. Valid types are string (default), base64, bool,
                        float32, float64, int8, int16, int32, int64, timestamp
```

## Testing

```
pylint csv2parquet
pytest
```
brainfuck-swimmy4days 0.0.3
A BrainFuck Interpreter
Requires Python: >=3.6

# BrainFuck interpreter
![](https://img.shields.io/pypi/v/brainfuck-swimmy4days) ![](https://img.shields.io/pypi/l/brainfuck-swimmy4days) 
- A simple to use, open source brainfuck interpreter
- Easy to run
- Optional debugger
- Changeable  cell size
- Print as an integer insted of ASCII 
- And mush more features

# What is BrainFuck?
brainfuck is an esoteric programming language with only 8 oparetions

|operation  | Explanation|
|- | -|
|`>` |  increment the data pointer.|
|`<` | decrement the data pointer.|
|`+` | increment the byte at the data pointer.|
|`-`  | decrement the byte at the data pointer.|
|`.` | output the byte at the data pointer.|
|`,` | accept one byte of input, storing its value in the byte at the data pointer.|
|`[` |if the byte at the data pointer is zero, then instead of moving the instruction pointer forward to the next command, jump it forward to the command after the matching `]` command.|
|`]` |if the byte at the data pointer is nonzero, then instead of moving the instruction pointer forward to the next command, jump it back to the command after the matching `[` command.|
[More Information](https://en.wikipedia.org/wiki/Brainfuck)

[Even More Information](https://esolangs.org/wiki/Brainfuck)

# To download from PYPI 

`$ python -m pip install brainfuck-swimmy4days`

#### To download the required packages in order to run the source type in the shell 
`$ python -m pip install -r requirements.txt`

Made by [@swimmy4days](https://github.com/swimmy4days)
morecvutils 1.0.2
Computer Vision utilities, OpenCV plot helpers for Optical Flow and Blob Analysis, AVI codec helpers
Requires Python: >=3.6
Keywords: computer vision,opencv

[![image](https://zenodo.org/badge/19711552.svg)](https://zenodo.org/badge/latestdoi/19711552)
[![Actions Status](https://github.com/scivision/morecvutils/workflows/ci_python/badge.svg)](https://github.com/scivision/morecvutils/actions)



[![Python versions (PyPI)](https://img.shields.io/pypi/pyversions/morecvutils.svg)](https://pypi.python.org/pypi/morecvutils)
[![Downloads](https://pepy.tech/badge/morecvutils)](https://pepy.tech/project/morecvutils)

# CVutils

Uses Python with
[OpenCV](https://scivision.dev/category/opencv/)
in miscellaneous demos of algorithms useful for computer vision.

Note: Line clipping was [moved to its own repo](https://github.com/scivision/lineclipping-python-fortran).

## Install

```sh
python -m pip install -e .
```

## Functions

* draw_flow()  given a 2-D complex Numpy array of optical flow `flow`, draw flow vectors with arrows
* draw_hsv() make a colored HSV image corresponding to flow direction and intensity at each point
* connectedComponents.py  given a binary image `morphed` and the `blobdet` from `setupblob()`, along with `img`, do connected components analysis
* OpticalFlow_Matlab_vs_Python.py   using Horn-Schunck optical flow estimation with OpenCV in Python. Not so obvious from the docs, and with notes on how to make this
  [match Matlab's vision.opticalFlowHS method](https://scivision.dev/opencv-cv-calcopticalflowhs-horn-schunck-smoothness-lambda-parameter/).
  [Install Matlab Engine for Python](https://scivision.dev/matlab-engine-callable-from-python-how-to-install-and-setup/)
pylineclip 1.0.0
Line clipping: Cohen-Sutherland
Requires Python: >=3.5
Keywords: line clipping,cohen-sutherland

[![Actions Status](https://github.com/scivision/lineclipping-python-fortran/workflows/ci_python/badge.svg)](https://github.com/scivision/lineclipping-python-fortran/actions)


[![PyPi versions](https://img.shields.io/pypi/pyversions/pylineclip.svg)](https://pypi.python.org/pypi/pylineclip)
[![PyPi Download stats](http://pepy.tech/badge/pylineclip)](http://pepy.tech/project/pylineclip)

# Line clipping

-   `lineclipping.f90` Cohen-Sutherland line clipping algorithm for
    massively parallel coarray modern Fortran. Input scalars or arrays,
    output intersections or `NaN` if no intersection.
-   `lineClipping.py` Cohen-Sutherland line clipping algorithm for Python.
    Input scalars, output intersection length, or `None` if no intersection.


Julia line clipping is at https://github.com/scivision/lineclipping-julia

## Install

To install the latest release:

```sh
pip install pylineclip
```



### Fortran

If you want to use the Fortran Cohen-Sutherland line clipping modules
directly (optional):

```sh
meson build

meson test -C build
```

## Usage

The main difference with textbook implementations is that I return a
sentinel value (NaN, None, nothing) if there's no intersection of line
with box.

### Python

```python
import pylineclip.lineclipping as lc

x3,y3,x4,y4 = lc.cohensutherland((xmin, ymax, xmax, ymin, x1, y1, x2, y2)
```

If no intersection, `(None, None, None, None)` is returned.

### Fortran

lineclipping.f90 has two subroutines.
Pick Ccohensutherland if you're calling from C/C++/Python, which cannot tolerate assummed-shape arrays.
It's a slim wrapper to cohensutherland which is elemental (can handle scalar or any rank array).

Fortran programs will simply use

```fortran
use lineclipping
call cohensutherland(xmin,ymax,xmax,ymin,x1,y1,x2,y2)
```

The arguments are:

    INPUTS
    ------
    xmin,ymax,xmax,ymin:  upper left and lower right corners of box (pixel coordinates)

    INOUT
    -----
    x1,y1,x2,y2:
    in - endpoints of line
    out - intersection points with box. If no intersection, all NaN