semvec/pypi-packages huggingface dataset:
hgpmatch 1.0.1
A CSV driven solver for resident/hospital style matching markets
Requires Python: >=3.7

[![Build Status](https://travis-ci.org/klittlepage/hgpmatch.svg?branch=master)](https://travis-ci.org/klittlepage/hgpmatch)
[![Documentation Status](https://readthedocs.org/projects/hgpmatch/badge/?version=latest)](https://hgpmatch.readthedocs.io/en/latest/?badge=latest)
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# Project Documentation

Documentation on `hgpmatch` lives [here](https://hgpmatch.readthedocs.io/).
netmetr-proxy 0.1.3
Helper proxy to sit between netmetr web client and backend. Adds a token/key and calls backend.
Requires Python: >=3.6
Keywords: netmetr

# ![NetMetr](https://www.netmetr.cz/theme/images/netmetr-logo.svg) `netmetr-proxy`

Helper proxy to sit between [netmetr](https://www.netmetr.cz/) web client and backend. Adds a token/key and calls backend for:

- Monthly stats approval
- Uncleaned data download

```
browser       netmetr-proxy          backend
   |                 |                   |
   |     GET         |     POST          |
   | --- month ----> | --- month-------> |
   |   + year        |   + year          |
   |                 |   + token         |
   |                 |                   |
   | <-- response -- | <-- response ---- |
   |   (zip or json) |                   |
   |                 |                   |
```

It also adds some input validation, since the backend will happily return empty CSVs for future dates or even a `.zip` file with plaintext `"illegal parameters"` content.

## Dependencies

- Python >= 3.6
- pyaml >= 17
- flask >= 0.12

## Installation

```
$ virtualenv -p `which python3.6` .venv
$ source .venv/bin/activate
$ pip install netmetr_proxy
$ cp config.example.yml config.yml
$ $EDITOR config.yml # set backend url & access token
```

### Running in production

uWSGI:

```
$ uwsgi --master --single-interpreter --threads 2 --http :5000 -H .venv -w netmetr_proxy.server
```

GUnicorn:

```
$ gunicorn -w 2 -k gevent --timeout 160 -n netmetr-proxy netmetr_proxy:server:app
```

## Usage

### Downloading uncleaned open data

```
GET /opendata
month <int>
year <int>
```

Returns opendata ZIP for download (`NetMetr-opendata-dirty-{year}-{month}.zip`).

### Monthly stats approval

```
GET /approve
month <int>
year <int>
```

Returns:

```
GET /approve?year=2018&month=3
-> 200
   {"success": true, "message": "Results for 2018-03 were successfully approved."}
```

if called again:

```
GET /approve?year=2018&month=3
-> 200
   {"success": true, "message": "Results for 2018-03 were already approved before."}
```

### Error responses

Returns errors from backend wrapped in JSON:

```
GET /opendata?year=2018&month=1
# invalid key in config results in "ERROR: invalid key!" message
# from backend (with HTTP 200 for some reason…)
-> 403
   {'error': 'invalid key!'}
```

Returns HTTP 400 and an error message for missing invalid params (bad format or future date):

```
GET /opendata?year=2018&month=0
-> 400
   {'error': 'Invalid date.'}
```

```
GET /opendata?year=0&month=march
-> 400
   {'error': 'Invalid date.'}
```

```
GET /approve?year=2018
-> 400
   {'error': 'Missing or invalid parameter (year, month).'}
```

Returns 404 for any non-existing endpoint:

```
GET /
-> 404
```

```
GET /foo
-> 404
```

## Development

Starting server with auto reload on file changes:

```
$ FLASK_APP=netmetr_proxy/server.py FLASK_DEBUG=1 flask run
```

Linting Python code:

```
$ flake8 --config=.flake8rc *py
```

## License

GPLv3
gsheet 0.0.1
Read en excel file throgh google drive to plot a graph

gsheets
=======

|PyPI version| |License| |Supported Python| |Format|


``gsheets`` is a small wrapper around the [`Google Sheets API`_ (v4)](https://docs.google.com/spreadsheets) to provide
more convenient access to [`Google Sheets`_](https://docs.google.com/spreadsheets) from Python scripts.

go to [google console](console.cloud.google.com) <br />
1.Create a Project in google cloud <br />
2.through Navigation menu Go ti API'S & Services and go to library <br />
3.search for google sheets api and enable it <br />
4.search for google drive api enable it and on the right side corner click on create credentials
select google drive api in which api you are using column and web server (eg node js tomcat) in  Where will you be calling the API from dropdown and tick on application data. and then no and press button<br />
5.fill any name in account and role select project and then editor and type json and submit. it will download the json file .<br />
6.open json file search client email go to google sheet you want to use and select share and give access to client email and send.<br />


Links
-----
- GitHub: https://github.com/manasgupta07/Gsheet

Libraries
_________
.. code:: bash

    $ pip install -r requirements.txt

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

This package runs under Python 2.7, and 3.6+, use pip_ to install:

.. code:: bash

    $ pip install read-excel

This will also install google-api-python-client_ and its dependencies, notably
httplib2_ and oauth2client_, as required dependencies.


Quickstart
----------

Log into the `Google Developers Console`_ with the Google account whose
spreadsheets you want to access. Create (or select) a project and enable the
**Drive API** and **Sheets API** (under **Google Apps APIs**).

Go to the **Credentials** for your project and create **New credentials** >
**OAuth client ID** > of type **Other**. In the list of your **OAuth 2.0 client
IDs** click **Download JSON** for the Client ID you just created. Save the
file as ``client_secrets.json`` in your home directory (user directory).

import the library and load the data by passing the filename and json file downloaded from console it will return a dataframe and print top 5 rows of your data:

.. code:: python

    >>> import read-excel as rf

    >>> dataframe = rf.load_data(filename_of_your_sheet,json_path)

For plotting the data you have to pass the dataframe you just loaded and pass the name X axis  columns name and Y axis column name it will plot the data for you:

.. code:: python

    for plotting
    >>> plot_data(dataframe,"x-axis-column","y-axis-column")
...
fenix-checker 0.1.4
A small server which checks if user's IP is in a trusted Fenix network.
Requires Python: >=3.6
Keywords: fenix

# [![Fenix](https://fe.nix.cz/images/logo_fenix.png)](https://fe.nix.cz/) `fenix-checker`

A small server which checks if user's IP is in a trusted [Fenix](https://fe.nix.cz/) network. Used by [`ipv6widget`](https://gitlab.nic.cz/labs/ipv6widget) and [standard-konektivity.cz](https://www.standardkonektivity.cz/).

## Dependencies

- Python >= 3.6
- pyaml >= 17
- psycopg2 >= 2.7.4

## Installation

```
$ virtualenv -p `which python3.6` .venv
$ source .venv/bin/activate
$ pip install fenix_checker
$ cp config.example.yml config.yml
$ $EDITOR config.yml # set DB credentials
```

### Running in production

uWSGI:

```
$ uwsgi --master --single-interpreter --threads 2 --http :5000 -H .venv -w fenix_checker.server
```

GUnicorn:

```
$ gunicorn -w 2 -k gevent --timeout 160 -n netmetr-proxy fenix_checker:server:app
```

## Usage

```
GET /
-> 200
   {"result": 1}
```

Result is:

- `0` for non-Fenix networks
- `>= 1` for Fenix networks

IP is validated with Python's [`ipaddress`](https://docs.python.org/3/library/ipaddress.html) module before passing it to DB:

```
GET /  # with client IP somehow spoofed to eg. "127.0.0.1'); DROP TABLE networks;"
-> 400
  {"error": "Invalid IP"}
```

## Development

Starting server with auto reload on file changes:

```
$ FLASK_APP=fenix_checker/server.py FLASK_DEBUG=1 flask run
```

Linting Python code:

```
$ flake8 --config=.flake8rc *py
```

## License

GPLv3