pyaair

Name	pyaair JSON
Version	0.0.0 JSON
	download
home_page	None
Summary	American Airlines scraper in Python
upload_time	2024-04-27 00:38:15
maintainer	None
docs_url	None
author	None
requires_python	None
license	MIT
keywords	american airlines aa scraper crawler
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # American Airlines scraper in Python

## Overview
This project is an open-source tool developed in Python for extracting product information from American Airlines. It's designed to be easy to use, making it an ideal solution for developers looking for American Airlines product data.

## Features
- Full search support
- Extracts detailed product information from American Airlines
- Implemented in Python just because it's popular
- Easy to integrate with existing Python projects

### Install

```bash
$ pip install pyaair
```
## Examples

```Python
fromDir="miami"
toDir="texas"
airports1=pyaair.airports(fromDir,"")
airports2=pyaair.airports(toDir,"")
f = open("./airports1.json", "w")
f.write(json.dumps(airports1))
f.close()
f2 = open("./airports2.json", "w")
f2.write(json.dumps(airports2))
f2.close()
```

```Python
originAirport = "GYE"
destinationAirport = "MIA"
departDate = "2024-05-01"
returnDate = "2024-05-04"
passengers = 1
#locale: where you are located, probably for increasing the price or is just for statistics, I DON'T KNOW, do not say that I said this field is for incresing the price, it's jut a theory
locale = "es_EC" 
flights=pyaair.flights(locale, originAirport, destinationAirport, departDate, returnDate, passengers,"")
f2 = open("./flights.json", "w")
f2.write(json.dumps(flights))
f2.close()
```

```Python
fromDir = "new york"
toDir = "galapagos"
departDate = "2024-05-01"
returnDate = "2024-05-04"
passengers = 1
#locale: where you are located, probably for increasing the price or is just for statistics, I DON'T KNOW, do not say that I said this field is for incresing the price, it's jut a theory
locale = "es_EC" 
airports1=pyaair.airports(fromDir,"")
airports2=pyaair.airports(toDir,"")
flights=pyaair.flights(locale, airports1[0]["code"], airports2[0]["code"], departDate, returnDate, passengers,"")
f2 = open("./flights.json", "w")
f2.write(json.dumps(flights))
f2.close()
```

            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "pyaair",
    "maintainer": null,
    "docs_url": null,
    "requires_python": null,
    "maintainer_email": null,
    "keywords": "American airlines, aa, scraper, crawler",
    "author": null,
    "author_email": "John Balvin <johnchristian@hotmail.es>",
    "download_url": "https://files.pythonhosted.org/packages/06/1c/7bffc017be9febc047200577dca4cec8ac8549befa40b8aa015dbc88f91e/pyaair-0.0.0.tar.gz",
    "platform": null,
    "description": "# American Airlines scraper in Python\r\n\r\n## Overview\r\nThis project is an open-source tool developed in Python for extracting product information from American Airlines. It's designed to be easy to use, making it an ideal solution for developers looking for American Airlines product data.\r\n\r\n## Features\r\n- Full search support\r\n- Extracts detailed product information from American Airlines\r\n- Implemented in Python just because it's popular\r\n- Easy to integrate with existing Python projects\r\n\r\n### Install\r\n\r\n```bash\r\n$ pip install pyaair\r\n```\r\n## Examples\r\n\r\n```Python\r\nfromDir=\"miami\"\r\ntoDir=\"texas\"\r\nairports1=pyaair.airports(fromDir,\"\")\r\nairports2=pyaair.airports(toDir,\"\")\r\nf = open(\"./airports1.json\", \"w\")\r\nf.write(json.dumps(airports1))\r\nf.close()\r\nf2 = open(\"./airports2.json\", \"w\")\r\nf2.write(json.dumps(airports2))\r\nf2.close()\r\n```\r\n\r\n```Python\r\noriginAirport = \"GYE\"\r\ndestinationAirport = \"MIA\"\r\ndepartDate = \"2024-05-01\"\r\nreturnDate = \"2024-05-04\"\r\npassengers = 1\r\n#locale: where you are located, probably for increasing the price or is just for statistics, I DON'T KNOW, do not say that I said this field is for incresing the price, it's jut a theory\r\nlocale = \"es_EC\" \r\nflights=pyaair.flights(locale, originAirport, destinationAirport, departDate, returnDate, passengers,\"\")\r\nf2 = open(\"./flights.json\", \"w\")\r\nf2.write(json.dumps(flights))\r\nf2.close()\r\n```\r\n\r\n```Python\r\nfromDir = \"new york\"\r\ntoDir = \"galapagos\"\r\ndepartDate = \"2024-05-01\"\r\nreturnDate = \"2024-05-04\"\r\npassengers = 1\r\n#locale: where you are located, probably for increasing the price or is just for statistics, I DON'T KNOW, do not say that I said this field is for incresing the price, it's jut a theory\r\nlocale = \"es_EC\" \r\nairports1=pyaair.airports(fromDir,\"\")\r\nairports2=pyaair.airports(toDir,\"\")\r\nflights=pyaair.flights(locale, airports1[0][\"code\"], airports2[0][\"code\"], departDate, returnDate, passengers,\"\")\r\nf2 = open(\"./flights.json\", \"w\")\r\nf2.write(json.dumps(flights))\r\nf2.close()\r\n```\r\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "American Airlines scraper in Python",
    "version": "0.0.0",
    "project_urls": {
        "Homepage": "https://github.com/johnbalvin/pyaair"
    },
    "split_keywords": [
        "american airlines",
        " aa",
        " scraper",
        " crawler"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "b7f078aeb70e170860e5971878e2e32698df7d1dd4be468d8c115680ce36ce51",
                "md5": "cef569483b634705a349be4aa514eb0b",
                "sha256": "0371b57af522ae4efd2e2e3239a2267884bf8ced95fd93ab8f3451ea41b01d5b"
            },
            "downloads": -1,
            "filename": "pyaair-0.0.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "cef569483b634705a349be4aa514eb0b",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 5212,
            "upload_time": "2024-04-27T00:38:14",
            "upload_time_iso_8601": "2024-04-27T00:38:14.045085Z",
            "url": "https://files.pythonhosted.org/packages/b7/f0/78aeb70e170860e5971878e2e32698df7d1dd4be468d8c115680ce36ce51/pyaair-0.0.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "061c7bffc017be9febc047200577dca4cec8ac8549befa40b8aa015dbc88f91e",
                "md5": "2436baba74e14f8f8bba2e5e62921212",
                "sha256": "6bb529e7da6e514f52c264ee3e813ea279abdcf36d1b152d39ad804a97780121"
            },
            "downloads": -1,
            "filename": "pyaair-0.0.0.tar.gz",
            "has_sig": false,
            "md5_digest": "2436baba74e14f8f8bba2e5e62921212",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 4310,
            "upload_time": "2024-04-27T00:38:15",
            "upload_time_iso_8601": "2024-04-27T00:38:15.310197Z",
            "url": "https://files.pythonhosted.org/packages/06/1c/7bffc017be9febc047200577dca4cec8ac8549befa40b8aa015dbc88f91e/pyaair-0.0.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-04-27 00:38:15",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "johnbalvin",
    "github_project": "pyaair",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "pyaair"
}