semvec/pypi-packages huggingface dataset:
Pyvish 0.0.1
Python To Html Code
Requires Python: >=3.6

Hi Developers,
This is Jeyesh Vishnu

Python Html Writer

Syntax
import jepy
from jepy import createSite
createSite(title,body(in dictionary format),"view")

#Example
createSite("Jeyesh",{'h1':'Hello','div':'World'},'view')

Building State
varbox 3.0
varbox package can be used to dump and load multiple variables through local file and can also be used as encryption vault
Requires Python: >=3.8.8
Keywords: varbox dump,varbox load,varbox pickle load,varbox pickle dump,varbox,variable dump,encryption,encryptor

# Variable dumpper/encryptor 

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
[![Python 3.8.8](https://img.shields.io/badge/python-3.8.8-blue.svg)](https://www.python.org/downloads/release/python-388/) 

## Example 1

 ```
# test.py
import varbox
class Glass:
    def __init__(self):
        self.amount = "500ml"
    def set_amount(self,a):
        self.amount = a
    def get_amount(self):
        return self.amount

g = Glass()
varbox.dump(1, 2, 3, g, filepath="var_file_path", varnames=["a", "b", "c", "g"])
k = varbox.load("var_file_path")
print(k["g"].amount)
  ```

## Example 2

 ```
import cipher
from constants import encryptions
print("==============================================================")
key = "0000000000000000"
plain_text = "I am the secret message"
encrypted_string,iv = cipher.encrypt(encryptions.AES, plain_text, key)
decrypted_text = cipher.decrypt(encryptions.AES, encrypted_string, key, iv)

print("plain_text\t\t\t:\t"+plain_text)
print("key\t\t\t\t\t:\t"+key)
print("encrypted_string\t:\t"+encrypted_string)
print("iv\t\t\t\t\t:\t"+str(iv))
print("decrypted_text\t\t:\t"+decrypted_text)

print("==============================================================")
key = "0000000000000000"
plain_text = "I am the secret message"
encrypted_string,iv = cipher.encrypt(encryptions.BLOW_FISH, plain_text, key)
decrypted_text = cipher.decrypt(encryptions.BLOW_FISH, encrypted_string, key, iv)

print("plain_text\t\t\t:\t"+plain_text)
print("key\t\t\t\t\t:\t"+key)
print("encrypted_string\t:\t"+encrypted_string)
print("iv\t\t\t\t\t:\t"+str(iv))
print("decrypted_text\t\t:\t"+decrypted_text)
print("==============================================================")
key = "0000000000000000"
plain_text = "I am the secret message"
encrypted_string,iv = cipher.encrypt(encryptions.ARC4, plain_text, key)
decrypted_text = cipher.decrypt(encryptions.ARC4, encrypted_string, key, iv)

print("plain_text\t\t\t:\t"+plain_text)
print("key\t\t\t\t\t:\t"+key)
print("encrypted_string\t:\t"+encrypted_string)
print("iv\t\t\t\t\t:\t"+str(iv))
print("decrypted_text\t\t:\t"+decrypted_text)
  ```
perfectoai 1.0.37
PerfectoAI is an automated emailable analytics tool along with AI graphs & predictions
Keywords: Perfecto,appium,selenium,testing,api,automation

PerfectoAI is an automated emailable analytics tool along with AI graphs & predictions specially designed for Perfecto's Smart Reports. Kindly reach out to Perfecto's Professional Services if interested.</br>
[![Downloads](https://pepy.tech/badge/perfectoai)](https://pepy.tech/project/perfectoai)

CHANGES
=======
1.0.37:
-------
- Handled if no CI jobs ran before
- Removed unnecessary warnings related to timezone converions. 
- UI upgrades

1.0.34:
-------
- Support for Epoch time in ms for startDate and endDate parameters. This allows the ability to query results as accurate to two different timestamp with milliseconds
- Manual Interactive session results will no longer be included under top failed tests and top recommendations
- JobName and Job Number will now be empty if not applicable in failures html
- Important fix to handle multiple repetitive special characters in Smart Reporting's failure message
- Summary Report hyperlinks will now reach to applicable Smart Reporting urls when jobs=All Jobs
- Failure html files are renamed like unique_failures.html as they contain details of unique failures only
- All table layouts will follow responsive design even when test names or failures are very huge

1.0.32:
-------

- Clicking on header logo will navigate to perfecto cloud website
- Removed unnecessary logs, packages & non relevant code to improve speed by 20%
- Graphs have meaningful headings
- Deprecating tags of -e parameter and replaced it with addInfo to make it more meaningful
- Appending " -d true" parameter to your existing query will now enable downloading of .txt files and extra console statements
- Appending "|ci=false" to -e parameter will automatically open report post execution. It will not be opened automatically by default in order to provide a seamless devops experience.
pywin-mutex 1.0.0
A module for creating and using a shared mutex on Windows.
Requires Python: >=3.9

# **Projectinformation**

This module allows the use of a shared mutex on Windows.
By installing this package the pywin32 module is also installed.

The code has been tested with Python >=3.9.4

# **Installing the Python Package**

Install via PIP: 
```
python -m pip install pywin-mutex
```

# **Examples**

After the installation is completed you can open **example.py**
in the *examples* folder 2 or more times and execute them to 
test if the Mutex works.
sick-json 0.0.4
A simple tool to parse the non-normal JSON that LLM responds to.
Requires Python: >=3.5

# A simple tool to parse the non-normal JSON

The only function implemented in this module is `parse`.

`parse` is similar to json.loads. However, it corrects some mistakes that LLM can make.

It can be installed with `pip install sick-json` and used with `import sick_json;sick_json.parse(something)`.

By default, it uses a JSON5 parser, which solves the following problems.

- Identifiers without quotes
```json5
{
    name: "Kim"
}
```
- Trailing comma
```json5
{
    "name": "Kim",
}
```
- JS-style comment
```json5
{
    "name": "Kim" // something
}
```

Additionally, it heuristically solves a few problems.

- Allow "True" and "False"
```json5
{
    "name": "Kim",
    "is_good_guy": True
}
```
- Verbose before and after JSON
```json5
blah blah blah
{
    "name": "Kim"
}
blah blah blah
```
- If you have multiple JSONs, it will return the longest by default, or you can specify a pydantic format.
```python
import sick_json
from pydantic import BaseModel
maybe_json = 'blah{"name": "Kim"}blah{"names": ["Kim", "Lee"]}blah'
sick_json.parse(maybe_json)
# it return {"names": ["Kim", "Lee"]}
class MyModel(BaseModel):
    name: str
sick_json.parse(maybe_json, pydantic_model=MyModel)
# it return {"name": "Kim"}
```
- Type-correcting by pydantic model
```python
import sick_json
from pydantic import BaseModel
maybe_json = '{"name": "Kim", "age": "13"}'
class MyModel(BaseModel):
    name: str
    age: int
sick_json.parse(maybe_json, pydantic_model=MyModel)
# it return {"name": "Kim", "age": 13}
```
secrets-cli 0.1.3
Run any applications with secrets stored in the Pangea Vault
Requires Python: >=3.7.2,<4.0

# Secrets CLI

A tool to dynamically load your secrets from the secure vault into your runtime environment.

## Getting Start

Install the CLI using pip
```bash
$ pip install secrets-cli
```

Setup the CLI with Pangea's vault. Visit [Pangea](https://console.pangea.cloud/service/vault/data) and create a new token.
```bash
$ pangea setup
```
Enter your pangea token when prompted.

Now, select folder to load your secrets from
```bash
$ pangea select --folder-name <FOLDER_NAME>
```

You're all set 🏎️ \
Run any application in any environment and pull your secrets securely from Pangea using the `pangea run`

```bash
$ pangea run npm run dev
```

OR

```bash
$ pangea run python3 app.py
```