semvec/pypi-packages huggingface dataset:
usefullog 0.8.7
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Requires Python: >=3.12

# UsefulLog
*Yet another logging library - made by BravestCheetah, Used by BravestCheetah*

## The main class
Everything in this library builds upon the Logger class: 
`from usefullog.logger import Logger`

### The Logger Class
To use the tool you first gotta initialize an instance of the Logger class, you can do it just like this, including the name of the project:

`logger = Logger("My Awesome Project")`

When logging simple data like this: `logger.log("cool logs")` youll get some output like this:

`2025-08-16 12:51:00 ( Test ) | [LOG] cool logs`

There are other log formats too! Here they are:

`.info("This is some info")` - `2025-08-16 12:51:00 ( Test ) | [INFO] This is some info`

`.warn("You have been warned!")` - `2025-08-16 12:51:00 ( Test ) | [WARN] You have been warned!`

`.error("Something went wrong :(")` - `2025-08-16 12:51:00 ( Test ) | [ERROR] Something went wrong :(`

`.critical("CRITICAL ERROR")` - `2025-08-16 12:51:00 ( Test ) | [CRITICAL] CRITICAL ERROR`

`.raw("only contents :O")` - `only contents :O`

`.space()` - Newline (`\n`)

**All logs are colored using the termcolor library which should be compatible with your terminal - Not visible in the documentation, but its there :D**

### Customization

But the logger does have multiple optional arguments to customize your logs. Lets list them:

#### 1. Subname - `Logger("My Awesome Project", sub_name="cool subsystem")`
Result:
`2025-08-16 12:55:19 ( Test/cool subsystem ) | [LOG] This is a test log`

Useful for separating different systems or parts of your codebase for easier debugging.

#### 2. Disable Timestamps - `logger = Logger("Test", do_timestamps=False)`
Result: 
` ( Test ) | [LOG] This is a test log`

Useful to declutter logs if timestamps arent necessary, makes the logs look more clean

#### 3. Save Logs - `logger = Logger("Test", do_log_saving=True)`
Saves Logs Into .log files by default in the /logs folder. Each new instance of the Logger class creates a new  log file.

Useful for saving and sharing logs

#### 4. Disable Log Printing - `logger = Logger("Test", print_logs=False)`
Disables printing for logs, when paired with log saving you can safely store logs without filling the terminal.

#### 5. Color Saved Logs - `logger = Logger("Test", do_saved_log_decolouring=False)`
When False the argument will keep the coloruing characters in the save folder, though most text editors may display these as normal characters and not colour them colours can be viewed when using a tool like `cat` to print the contents to the terminal directly.

#### 6. Change Log Folder - `logger = Logger("Test", log_save_folder="other folder")`
When used logs will be saved in that path instead of the default /logs
sparkdataframecomparer 2.0.16
Deep Comparer for Spark Data Frames
Requires Python: >=3

[![Build and Test](https://github.com/imranq2/SparkDataFrameComparer/actions/workflows/build_and_test.yml/badge.svg)](https://github.com/imranq2/SparkDataFrameComparer/actions/workflows/build_and_test.yml)

[![Upload Python Package](https://github.com/imranq2/SparkDataFrameComparer/actions/workflows/main.yml/badge.svg)](https://github.com/imranq2/SparkDataFrameComparer/actions/workflows/main.yml)

[![Known Vulnerabilities](https://snyk.io/test/github/imranq2/SparkDataFrameComparer/badge.svg?targetFile=requirements.txt)](https://snyk.io/test/github/imranq2/SparkDataFrameComparer?targetFile=requirements.txt)

# SparkDataFrameComparer
Deep compare of two data frames (recurses down into array and struct columns)
sparkfhirschemas 2.0.4
FHIR Schemas for Spark
Requires Python: >=3

# SparkFhirSchemas


This project is a collection of [FHIR](https://www.hl7.org/fhir/) schemas for [Apache Spark](https://spark.apache.org/).

## Usage
1. First update the `fhir.schema.json` file with the FHIR schema you want to use.
   2. You can find the FHIR schema in the [FHIR specification](https://hl7.org/fhir/R4B/fhir.schema.json).
3. Run `make schema-RXX` to generate the Spark schema for RXX. Replace "XX" with the verison you desire. For instance if you want to update R4B you would run `make schema-R4B`.
4. Run `make schema-stu3` to generate the Spark schema for STU3.
5. Run `make schema-dstu2` to generate the Spark schema for DSTU2.

This will generate the Spark schema in the spark_fhir_schemas directory.