semvec/pypi-packages huggingface dataset:
uscg-leetcode-validator-2 1.0.0
Used to validate restricted python code inputs against test cases.
Requires Python: >=3.6

# USCG Leetcode Validator

A secure Python code validator for coding challenge platforms like LeetCode-style or CTF environments.

This package runs and validates submitted Python functions under strict constraints using Python's AST (Abstract Syntax Tree). It ensures that only allowed operations (like basic loops, arithmetic, and safe built-ins) are used. This is ideal for running untrusted user code in coding competitions, while preventing unsafe or unwanted behavior.

---

## 🚀 Features

- ✅ Accepts only a single top-level function in the submitted code
- ✅ Rejects all imports, lambdas, classes, and custom function definitions
- ✅ Optionally allows safe built-ins like `len()` and `range()`
- ✅ Enforces AST-level constraints before execution
- ✅ Runs submitted function against a list of test cases
- ✅ Outputs time taken and pass/fail result for each test case

---

## 📦 Installation

To install from PyPI:

```bash
pip install uscg-leetcode-validator
```
scrapy-curl-cffi 0.2.0
Scrapy integration with curl_cffi (curl-impersonate).
Requires Python: >=3.10

# scrapy-curl-cffi

[Scrapy][1] integration with [curl_cffi][2] ([curl-impersonate][3]).

## Installation

```sh
pip install scrapy-curl-cffi
```

Another option, to enable Scrapy's support for modern HTTP compression
protocols:

```sh
pip install scrapy-curl-cffi[compression]
```

## Configuration

Update your Scrapy project settings as follows:

```python
DOWNLOAD_HANDLERS = {
    "http": "scrapy_curl_cffi.handler.CurlCffiDownloadHandler",
    "https": "scrapy_curl_cffi.handler.CurlCffiDownloadHandler",
}

DOWNLOADER_MIDDLEWARES = {
    "scrapy_curl_cffi.middlewares.CurlCffiMiddleware": 200,
    "scrapy_curl_cffi.middlewares.DefaultHeadersMiddleware": 400,
    "scrapy_curl_cffi.middlewares.UserAgentMiddleware": 500,
    "scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware": None,
    "scrapy.downloadermiddlewares.useragent.UserAgentMiddleware": None,
}

TWISTED_REACTOR = "twisted.internet.asyncioreactor.AsyncioSelectorReactor"
```

## Usage

To download a [`scrapy.Request`][4] with `curl_cffi`, add the
`curl_cffi_options` special key to the [`Request.meta`][5] attribute. The value
should be a dict with any of the following options:

- `impersonate` (`str`) - which browser version to impersonate
- `default_headers` (`bool`) - whether to set default browser headers when
  impersonating (default: `True`)
- `ja3` (`str`) - ja3 string to impersonate
- `akamai` (`str`) - akamai string to impersonate
- `extra_fp` (`str`) - extra fingerprints options, in complement to ja3 and
  akamai strings
- `verify` (`bool`) - whether to verify https certs (default: `False`)

See the [curl_cffi documentation][6] for more info on these options.

Alternatively, you can use the `curl_cffi_options` spider attribute or the
`CURL_CFFI_OPTIONS` setting to automatically assign the `curl_cffi_options` meta
for all requests.

### Example spider

```python
class FingerprintsSpider(scrapy.Spider):
    name = "fingerprints"
    start_urls = ["https://tls.browserleaks.com/json"]
    curl_cffi_options = {"impersonate": "chrome"}

    def parse(self, response):
        yield response.json()
```

## curl_cffi interop

`scrapy-curl-cffi` strives to adhere to established Scrapy conventions, ensuring
that most Scrapy settings, spider attributes, request/response attributes and
meta keys configure the crawler's behavior in an expected manner.

## Similar projects

- [scrapy-impersonate](https://github.com/jxlil/scrapy-impersonate)
- [scrapy-fingerprint](https://github.com/tieyongjie/scrapy-fingerprint)

[1]: https://github.com/scrapy/scrapy
[2]: https://github.com/lexiforest/curl_cffi
[3]: https://github.com/lexiforest/curl-impersonate
[4]: https://docs.scrapy.org/en/latest/topics/request-response.html#request-objects
[5]: https://docs.scrapy.org/en/latest/topics/request-response.html#scrapy.Request.meta
[6]: https://curl-cffi.readthedocs.io
eventweave 0.5.0
Weave multiple streams of intervals into combinations
Requires Python: >=3.10

# eventweave

**Eventweave** is a lightweight Python utility that groups overlapping events
into chronological combinations. It is useful for temporal reasoning and event
sourcing, allowing you to analyze and visualize the relationships between
events that occur simultaneously.

## Features

- Accepts any iterable of events with user-defined start and end times
- Yields sets of events that are simultaneously active at some point in time
- Handles edge cases for back-to-back, non-overlapping intervals
- Supports atomic events that start and end at the same time
- Runs in `O(n log n)` time and `O(n)` space

## Installation

This project is self-contained with no dependencies beyond the Python standard library.

You can install it using pip:

```bash
python -m pip install eventweave
```

Supported for Python 3.13 and above.

## Example Usage

Define your events and a key function:

    >>> from eventweave import interweave
    >>>
    >>> events = [
    ...     ("A", (1, 4)),
    ...     ("B", (2, 5)),
    ...     ("C", (5, 6)),
    ... ]
    >>>
    >>> def key(event):
    ...     return event[1]

Use interweave to iterate over overlapping combinations:

    >>> result = list(interweave(events, key))
    >>> expected = [
    ...     {('A', (1, 4))},
    ...     {('A', (1, 4)), ('B', (2, 5))},
    ...     {('B', (2, 5))},
    ...     {('C', (5, 6))},
    ... ]
    >>> assert result == expected

## Clarification of Overlapping Events

If one event ends at time `T` and another begins at time `T`, they are **not
considered overlapping**. The model assumes the starting event ends just after
`T` to preserve strict separation of events that merely touch.

**Instantaneous events** - where the start and end times are the same - are
considered to be active exactly at this point in time. If an event `E` starts
and ends at time `T`, it will overlap with any other event that ends at `T`.
However, it will not overlap with any event that starts at `T`, due to the
rule above.
uscg-leetcode-validator 1.0.8
Used to validate restricted python code inputs against test cases.
Requires Python: >=3.6

# USCG Leetcode Validator

A secure Python code validator for coding challenge platforms like LeetCode-style or CTF environments.

This package runs and validates submitted Python functions under strict constraints using Python's AST (Abstract Syntax Tree). It ensures that only allowed operations (like basic loops, arithmetic, and safe built-ins) are used. This is ideal for running untrusted user code in coding competitions, while preventing unsafe or unwanted behavior.

---

## 🚀 Features

- ✅ Accepts only a single top-level function in the submitted code
- ✅ Rejects all imports, lambdas, classes, and custom function definitions
- ✅ Optionally allows safe built-ins like `len()` and `range()`
- ✅ Enforces AST-level constraints before execution
- ✅ Runs submitted function against a list of test cases
- ✅ Outputs time taken and pass/fail result for each test case

---

## 📦 Installation

To install from PyPI:

```bash
pip install uscg-leetcode-validator
```
pigweed 0.0.24
Pigweed Python modules
Requires Python: >=3.7

# Pigweed

Pigweed is an open source collection of embedded-targeted libraries–or as we
like to call them, modules. These modules are building blocks and infrastructure
that enable faster and more reliable development on small-footprint MMU-less
32-bit microcontrollers like the STMicroelectronics STM32L452 or the Nordic
nRF52832.

For more information please see our website: https://pigweed.dev/.

## Links

- [Documentation](https://pigweed.dev/)
- [Source Code](https://cs.pigweed.dev/pigweed)
- [Code Reviews](https://pwrev.dev/)
- [Mailing List](https://groups.google.com/forum/#!forum/pigweed)
- [Chat Room](https://discord.gg/M9NSeTA)
- [Issue Tracker](https://pwbug.dev/)
alumathprimes 0.1.1
A simple library to multiply matrices of different dimensions
Requires Python: >=3.6

This is a brief step by step guide on how to install and use this library that multiplies two matrices of different dimensions.

1. Installation
    - run *pip install alumathprimes* from your terminal

2. Usage
    - Import the library using *from alumathprimes import multiplier*
    Where *multiplier* is the name of a function called to do the multiplication.

3. Error handling
    - The ValueError is set to display the message *Number of columns of A must equal number of rows of B.* whenever the entered mutrices can not be multiplied.

4. Uninstallation
    - To uninstall the library, run *pip uninstall alumathprimes*