semvec/pypi-packages huggingface dataset:
randomchar 0.0.1
Generating a random string
Requires Python: >=3.9

# RandomChar

## Install
```shell
pip install randomchar
```

## How to use

### Basic
```python
import RandomChar
from RandomChar.Generator import CharType

char = RandomChar.create(CharType.LOWER)
print(char)
```

```commandline
ex: xyfntp
```

### Length
```python
import RandomChar
from RandomChar.Generator import CharType

char = RandomChar.create(CharType.LOWER, length=10)
print(char)
```

```commandline
ex: xyfntpqncy
```
Length default: 6

### CharType
```python
import RandomChar
from RandomChar.Generator import CharType

char = RandomChar.create(CharType.LOWER, CharType.UPPER, CharType.DIGITS, CharType.PUNCTUATION)
print(char)
```

```commandline
ex: dp8N!n
```

---

### Secure
```python
import RandomChar

char = RandomChar.secure_create(length=16)
print(char)
```

```commandline
ex: nAq1s_QhWe4t-3zP
```
Length default: 10

URL-safe, base64
alga 2.2.0
CLI for remote controlling LG webOS TVs
Requires Python: >=3.10
Keywords: lg, lgtv, remote, remote-control, webos, webos-tv

Alga
====

A command line utility for controlling a LG webOS TV over the network.


Installing
----------

Alga is [available on PyPI](https://pypi.org/project/alga/).
I would recommend installing it via [pipx](https://pipx.pypa.io/stable/):

```shell
$ pipx install alga
```

Or, via [Nix flakes](https://nixos.org/):

```shell
nix run github:Tenzer/alga
```


Setup
-----

The first time you use the utility, you will need to setup a connection to the TV.
With the TV on, run `alga tv add <identifier> [hostname/IP]`.
This will bring up a prompt on the TV asking if you want to accept the pairing.
When accepted, Alga will be ready to use.

If no hostname or IP address is provided to `alga tv add`, it will be default try to connect to "lgwebostv" which should work.

The hostname, a key and MAC address will be written to `~/.config/alga/config.json` for future use.


Usage
-----

See [usage](usage.md) for a list of available commands.


Development
-----------

The code base is fully type annotated and test coverage is being enforced.
Types can be checked via `uv run mypy .` and tests via `uv run pytest`.

Tests are run for each of the supported Python versions in CI.

[pre-commit](https://pre-commit.com/) used to run Ruff for linting and formatting.

`usage.md` is updated via `uv run ./generate-usage.sh`.
perftrack 0.1.1
Lightweight CLI tool to detect performance regressions by comparing local benchmark snapshots.
Requires Python: >=3.9
Keywords: benchmark, cli, performance, regression

# PerfTrack

PerfTrack is a command-line tool that helps detect performance regressions in open-source projects and CI pipelines. It requires no external services and tracks performance locally.

Designed for Python projects (Django, Pandas, FastAPI, ML libraries), internal tooling, and personal benchmarking workflows

## Why PerfTrack?
Performance regressions often go unnoticed because:

- CI timing is noisy and unreliable for benchmarking
- Tools like ASV or pytest-benchmark require setup and maintenance
- There is no simple utility to store a baseline and fail CI when performance drops

PerfTrack stores local performance snapshots and compares them against future runs, both locally and in CI.

## What It Measures
- Wall-clock time
- CPU time
- Peak RSS memory usage

Baseline cached locally → regression check in CI.

## Installation

```bash
pip install perftrack

```

## Quick start

```bash
# run a command and record performance
perftrack run "python script.py"

# set the latest run as baseline
perftrack baseline set-latest

# later compare new results with baseline
perftrack compare --fail-on-regression

# Generate Simple HTML report
perftrack report

```
Replace "python script.py" with whatever you want to benchmark (scripts, test suites, build steps, ML training, etc.)

## Directory
Perftrack store results under:

```bash
.perftrack/
  baseline.json
  latest.json

```

## CI Regression Example
PerfTrack guarantees that performance regressions are caught before merge.
Here is a ([pull request](https://github.com/p-r-a-v-i-n/perftrack-examples/pull/7)) where we intentionally slowed down code to demonstrate PerfTrack in CI.

<img width="741" height="209" alt="perftrack" src="https://github.com/user-attachments/assets/25eca2c6-0226-4608-9614-a2eb0102e67e" />