semvec/pypi-packages huggingface dataset:
robocorp-logging 0.0.9
Automatic trace logging for Python
Requires Python: >=3.9,<4.0

# Logging for python based Robocorp projects

Logging focused on RPA projects for Robocorp robots.

> Note: The current version is still pre-alpha and the [format specified](/docs/format.md) may still change.

## Why

Although the python logging is flexible it may be hard to analyze the logging afterwards and
provide a nice representation. Also, the format may end up using a big amount of disk space.

`robocorp-logging` improves those aspects by using a structured format which enables using less disk space
while also providing a viewer for the generated content.

Also, it provides utilities to setup logging so that logging is done automatically without having
to explicitly add calls to add content to the logging (although it's still possible to do so
when needed).


### Installation

Install with:

`pip install robocorp-logging`


## Dealing with sensitive data in the logs

* See: [Handling Sensitive Data](/docs/handling_sensitive_data.md)


## Internal structure

* [Format specification](/docs/format.md)
flixy2app 0.2.4
A UI-Builder that helps programmers build the front-end without codding it.

# flixy2app
flixy2app is a python library for converting pythonista flixy UI library into mac or windows executble file.

# usage
- first install pythonista on iPadOS or iOS.
- install the library from: https://github.com/SKbarbon/flixy .
- install this tool using pip.

after you install it, write this command:

```cmd
python3 -m flixy2app.generate 
```

then folow the Instructions of the window.
ddc-indices 0.5.2
Package for calculating meteorological indices
Requires Python: >=3.8

# DDC Meteorological Indices

This is the Danube Data Cube Meteorological Indices library, 
a python implementation for calculating common meteorological indices,
utilizing data cubes.

The following indices are available:
- SPI, Standardized Precipitation Index, utilizing both gamma and Pearson Type III distributions
- SPEI, Standardized Precipitation Evapotranspiration Index, utilizing both gamma and Pearson Type III distributions
- PDSI, Palmer Drought Severity Index
- PNI, Percentage of Normal Precipitation Index

### Installation
```
$ pip install ddc-indices
```

### Example
```
$ python

# Calculating the Standardized Precipitation Index (SPI)
>>> import xarray as xr
>>> from ddc_indices import DdcIndices
>>> from ddc_indices import SpiConfig

# import my dataset containing precipitation data
>>> dataset = xr.open_zarr('path_to_zarr')
>>> config = SpiConfig(variables={'prec': 'prec'}, periodicity='daily')
>>> spi = DdcIndices().initialize(dataset, config)
>>> spi.compute()
>>> spi.index

```
cmdlogtime 0.0.4
This package does command line processing, allows for logging, and keeps track of start, end, and elapsed time, along with a bunch of other stuff.

# How to use CMD Log time:

## Write a Command file that teaches cmdlogtime how to parse your input args:

```
# first line is the description of what the program does.
# subsequent lines list positional arguments (PA), then key-value (KV)arguments (KVA).
# Positional line:
# PA_name|PA_Description|Is_out_dir|Is_Dir|Check_Directory|Is_file|Check_File|||
# Key/Value Line:
# KVA_name|KVA_Description|Is_out_dir|Is_Dir|Check_Directory|Is_file|Check_File|alternate_KVA_name|default value|type
# -print_x_thresh|print every X threshold|0|0|0|0|0|--print_every_x_threshold|1|int
# For KVAs for booleans, set default value to BOOLEANFALSE or BOOLEANTRUE.
# If default is BOOLEANFALSE, then if you set the flag it will be True. (or vice-versa)
# -get_top_words|get top most probable words|0|0|0|0|0|--get_top_probable_words|BOOLEANFALSE|
#  out_dir must be given.
# 
# Example below. First line describes the program
Compute AUCROC and other stats from infile. Print AUCROC and PR curves.
out_dir|Top level directory that holds all the results|1|1|1|0|0|||
infile|file path of file with a file with header in format call(1 or 0)\tX\tValue|0|0|0|1|1|||
-print_x_thresh|print every X threshold|0|0|0|0|0|--print_every_x_threshold|1|int
```
## Call cmdlinetime from your code as follows:

```python
#!/usr/bin/env python
#  need to import cmdlogtime
import cmdlogtime

#need to specify a command line definition file.  See example command line definition file in this directory.
COMMAND_LINE_DEF_FILE = "./processLincsCommandLine.txt"

#There is also an example python file that uses all this stuff in this directory.
def main():
    # Call cmdlogtime.begin() at the beginning of main()
    (start_time_secs, pretty_start_time, my_args, logfile) = cmdlogtime.begin(COMMAND_LINE_DEF_FILE, sys.argv[0])
    
    # the command line arguments will be in the my_args dictionary returned, so you can access them like this:
    get_treats_vectors = my_args["get_treats_vectors"]
    
    #  Then you put all of your code here.....
    
    # if you want to add stuff to the logfile:
    logfile.write("Run Skim here for each of the B terms files in B_TERMS_DIR")
       
    #The only functions you probably will ever need in cmdlogtime are begin(), end(), and maybe make_dir. Here's an example:
    cmdlogtime.make_dir(intermediate_out_dir)

    # Call cmdlogtime.end() at the end of main()
    cmdlogtime.end(logfile, start_time_secs)

if __name__ == "__main__":
    main()

```


Reference Blog: https://towardsdatascience.com/an-end-to-end-guide-to-publish-your-python-package-bdb56639662c
django-cheroot 1.0.2
Django Cheroot provides a bridge to use Cheroot which is the high-performance, pure-Python HTTP server used by CherryPy
Requires Python: >=3.5

# Django Cheroot

Django Cheroot provides a bridge to use [Cheroot](https://github.com/cherrypy/cheroot) which is the high-performance, pure-Python HTTP server used by CherryPy.

_Alternative for other WSGI servers like Gunicorn, etc._

## Install

`pip install django-cheroot`

In `settings.py` add application to `INSTALLED_APPS`

```python
INSTALLED_APPS = [
  ...
  'django_cheroot',
]
```

## Usage

Simplest usage with default settings is:

```shell
python manage.py cheroot
```

Default arguments

```shell
python manage.py cheroot -h 127.0.0.1 -p 8000 -w 40 -t 30 -c 20
```
```shell
python manage.py cheroot --host 127.0.0.1 --port 8000 --maxthreads 40 --minthreads 30 --connections 20
```

## Arguments

| Name                       | Short | Long          | Type | Default   |
| -------------------------- | ----- | ------------- | ---- | --------- |
| IP Address                 | -ip   | --hostip      | str  | 127.0.0.1 |
| Port                       | -p    | --port        | int  | 8000      |
| Max Worker Threads         | -w    | --maxthreads  | int  | 40        |
| Min Threads in Thread Pool | -t    | --minthreads  | int  | 30        |
| Max Queued Connections     | -c    | --connections | int  | 20        |