semvec/pypi-packages huggingface dataset:
antenna-intensity-modeler 0.1.1
Create near-field plots of parabolic dish antennas.
Requires Python: >=3.5,<4.0

=========================
antenna-intensity-modeler
=========================


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Create near-field plots of parabolic dish antennas.


* Free software: GNU General Public License v3

* Documentation: https://wboxx1.github.io/antenna-intensity-modeler



Installation:
-------------

.. code-block:: console

    $ pip install antenna-intensity-modeler

Features
--------

* TODO

Credits
-------

This package was created with Cookiecutter_ and the `wboxx1/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`wboxx1/cookiecutter-pypackage`: https://github.com/wboxx1/cookiecutter-pypackage-poetry
txbillsearch 0.1.9
Scrape Texas Legislature Online Bill Search results.

[![PyPI version](https://badge.fury.io/py/txbillsearch.svg)](https://pypi.org/project/txbillsearch/)
![Python 3](https://img.shields.io/pypi/pyversions/txbillsearch.svg)

A thin, incomplete Python 3 library wrapper around the [Texas Legislature Online
Bill Search](https://capitol.texas.gov/Search/BillSearch.aspx).

## Install and Test

```bash
$ pip install txbillsearch
...
$ python -m txbillsearch
3 bills found...
result 1 of 3: HB 20 by Capriglione H Filed 2019-01-24
result 2 of 3: HB 1096 by Capriglione H Filed 2019-01-25
result 3 of 3: HJR 10 by Capriglione H Filed 2019-01-24
The next page of results is None
$
```

## Usage

```python
import txbillsearch

capriglione_finance = 'https://capitol.texas.gov/Search/BillSearch.aspx?NSP=3&SPL=True&SPC=False&SPA=True&SPS=True&Leg=86&Sess=R&ChamberH=True&ChamberS=True&BillType=B;JR;CR;R;;;&AuthorCode=A2345&SponsorCode=&ASAndOr=O&IsPA=True&IsJA=False&IsCA=False&IsPS=True&IsJS=False&IsCS=False&CmteCode=&CmteStatus=&OnDate=&FromDate=&ToDate=&FromTime=&ToTime=&LastAction=False&Actions=H001;S001;&AAO=O&Subjects=I0747;I0748;&SAO=O&TT=&ID=abcDEFghi'

search = txbillsearch.Search(capriglione_finance)

for index, bill in enumerate(search.results):
    print(f'result {index+1} of {search.result_count}: {bill}')
```

## Technical Details

For some reason,
[BillSearchResults.aspx](https://capitol.texas.gov/Search/BillSearchResults.aspx)
requires that you supply an ID, generated on
[BillSearch.aspx](https://capitol.texas.gov/Search/BillSearch.aspx). This ID
must be "fresh"; that is it must have been generated less than 24-ish hours ago
(I don't know the exact time interval). Without a "fresh" ID,
BillSearchResults.aspx displays "No bills were found matching the entered
search criteria." or redirects the client back to BillSearch.aspx.  The ID is associated with the search criteria you supply on BillSearch.aspx, so it cannot be reused with other searches on BillSearchResults.aspx alone.


This ID is generated during the ASP.NET
POSTback that occurs to BillSearch.aspx after you have selected your search
criteria, but before you are redirected to BillSearchResults.aspx:

![bill search sequence diagram](Doc/sequencediagram.png)

## Disclaimer

I made my best effort to read through the Texas Legislature Online Terms and
Conditions, and found nothing that prohibited or discouraged
automated/programmatic use or access of this information for personal and/or
non-commercial use. The [FTP site](https://capitol.texas.gov/billlookup/filedownloads.aspx) is no substitute
for a modern web service. If there's a better way to do this (e.g., a *real*
web service) I'd love to know about it, and would much prefer to use it to the
wasteful and inconvenient method developed herein.
fec-reader 2.1.1
retrieves data from FEC.gov website

FEC Data Reader
==========================

A quick way to retrieve FEC bulk data from https://www.fec.gov:

``` {.sourceCode .python}
>>> import fec_reader as fec
>>> reader = fec.DataReader(data_dir='/raw') # pick a target directory
>>> reader.get_pac_summary(2010, 2018)
```

Each reader function allows you to specify year ranges for the data downloads. For example, the code below
retrieves 3 data files:

`reader.get_pac_summary(2014, 2018)`

This is because the data in each file spans two calendar years.

This package is a demonstration of ETL skills for Alexus Wong. However, it is also important
that we as a society can efficiently consume the inordinate amount of information available
today. If we can process it, we can take steps in the right direction.

There is a 5 second delay between files to respect FEC.gov's bandwith.

Features
---------------

FEC Reader currently retrieves these data files:

-   PAC Summary - https://www.fec.gov/campaign-finance-data/pac-and-party-summary-file-description/ - `reader.get_pac_summary(start, end)`
-   Candidate Master - https://www.fec.gov/campaign-finance-data/candidate-master-file-description/ - `reader.get_candidate_master(start, end)`
-   Contributions from committees to candidates and independent expenditures - https://www.fec.gov/campaign-finance-data/contributions-committees-candidates-file-description/ - `reader.get_contributions_to_candidates(start, end)`

Installation
------------

To install FEC Reader, simply use pip:

``` {.sourceCode .bash}
$ pip install fec-reader
```
bfscraper 0.1.1
Scrapes Betfair price data for Australian horse racing

# bfscraper

---

The package scrapes Betfair price data (BSP, WAP etc) for Australian horse racing markets.

---

You can use the package in the following way:

```python
from bfscraper import bfscraper

df = bfscraper.scrape("2018-01-01", "2018-12-31")

print(df)
```

---

The above code would scrape the relevant data from January 1, 2018 till December 31, 2018.

The data would be returned in a Pandas dataframe format which can then be exported to a CSV or other file formats.

There may be scope in the future to expand this package to other jurisdictions and racing codes.
movies-module-micah 1.3.1
Micah-specific exercise modules

# movies_module_micah Package

This is an exercise module that provides
a function called print_lol() that prints
lists that may or may not contain nested lists.

This function takes a positional argument
called 'the_list', which can be any Python
list (or a list containing nested lists).
Each item in the specified list is
(recursively) printed to the screen,
 one row each.