error-markov


Nameerror-markov JSON
Version 0.1.0 PyPI version JSON
download
home_pageNone
SummaryThis is a markov-chain module/package/library/idk and it is dumb
upload_time2025-07-22 08:22:13
maintainerNone
docs_urlNone
authorsomeone624
requires_pythonNone
licenseNone
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # error_markov
This is just your normal markov-chain module/package/library/what do you call this. If your life is on the line, don't use this, it's unreliable. This **will** not work I can guarantee you. Its here if you want something dumb that you can easily frame as AI.
## Installation
```bash
pip install error_markov
```
## Usage
```python
from error_markov import DumbMarkov

bot = DumbMarkov(order=1) # If order is not specified, it will default to 2
```
### Training
```python
text = "your text here"
bot.train(text)
```
You can also use multiple sentences:
- 1 train command
```python
text = "An apple is existing. Yes an apple is not existing."
bot.train(text)
```
- many train commands
```python
bot.train("An apple is existing.")
bot.train("Yes an apple is not existing.")
```
### Generating
```python
bot.generate()
```
The code above will generate 1 sentence with a max of 50 words. It will start with a random word.
- If you want to start with something specific
```python
inputt = "Yes an"
output = bot.generate(start=inputt)
# To start with something, do:
# start=
```
- If you want to change the max words
```python
max_w = 75
inputt = "Yes an"
output = bot.generate(max_words=max_w, start=inputt)
```
- And then print the output:
```python
print(output)
```
## License
This thing is licensed under the WTFPL.
---
            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "error-markov",
    "maintainer": null,
    "docs_url": null,
    "requires_python": null,
    "maintainer_email": null,
    "keywords": null,
    "author": "someone624",
    "author_email": null,
    "download_url": "https://files.pythonhosted.org/packages/b5/62/77eb3e7c221e83c19cd6a9d765aac8ff7fabc06fdd74a548de5a313810f4/error_markov-0.1.0.tar.gz",
    "platform": null,
    "description": "# error_markov\nThis is just your normal markov-chain module/package/library/what do you call this. If your life is on the line, don't use this, it's unreliable. This **will** not work I can guarantee you. Its here if you want something dumb that you can easily frame as AI.\n## Installation\n```bash\npip install error_markov\n```\n## Usage\n```python\nfrom error_markov import DumbMarkov\n\nbot = DumbMarkov(order=1) # If order is not specified, it will default to 2\n```\n### Training\n```python\ntext = \"your text here\"\nbot.train(text)\n```\nYou can also use multiple sentences:\n- 1 train command\n```python\ntext = \"An apple is existing. Yes an apple is not existing.\"\nbot.train(text)\n```\n- many train commands\n```python\nbot.train(\"An apple is existing.\")\nbot.train(\"Yes an apple is not existing.\")\n```\n### Generating\n```python\nbot.generate()\n```\nThe code above will generate 1 sentence with a max of 50 words. It will start with a random word.\n- If you want to start with something specific\n```python\ninputt = \"Yes an\"\noutput = bot.generate(start=inputt)\n# To start with something, do:\n# start=\n```\n- If you want to change the max words\n```python\nmax_w = 75\ninputt = \"Yes an\"\noutput = bot.generate(max_words=max_w, start=inputt)\n```\n- And then print the output:\n```python\nprint(output)\n```\n## License\nThis thing is licensed under the WTFPL.\n---",
    "bugtrack_url": null,
    "license": null,
    "summary": "This is a markov-chain module/package/library/idk and it is dumb",
    "version": "0.1.0",
    "project_urls": null,
    "split_keywords": [],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "d04c6c683e5dee0c84c8f691349786d7970da7bb6c61d850639188aa1bf47119",
                "md5": "9365bb131b582a4f3842a19a67430581",
                "sha256": "f6748befe16c3aa43d6ede305b9759949d8aa3755e495b6545b54ca3e1a26b42"
            },
            "downloads": -1,
            "filename": "error_markov-0.1.0-py2.py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "9365bb131b582a4f3842a19a67430581",
            "packagetype": "bdist_wheel",
            "python_version": "py2.py3",
            "requires_python": null,
            "size": 2963,
            "upload_time": "2025-07-22T08:22:12",
            "upload_time_iso_8601": "2025-07-22T08:22:12.281003Z",
            "url": "https://files.pythonhosted.org/packages/d0/4c/6c683e5dee0c84c8f691349786d7970da7bb6c61d850639188aa1bf47119/error_markov-0.1.0-py2.py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "b56277eb3e7c221e83c19cd6a9d765aac8ff7fabc06fdd74a548de5a313810f4",
                "md5": "9a738d704e8ad7cb2d233893a8d45e48",
                "sha256": "39b8b872001b93dc52c9b0dbaab4594711a60323b5caf911f810efe66cb3f044"
            },
            "downloads": -1,
            "filename": "error_markov-0.1.0.tar.gz",
            "has_sig": false,
            "md5_digest": "9a738d704e8ad7cb2d233893a8d45e48",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 2176,
            "upload_time": "2025-07-22T08:22:13",
            "upload_time_iso_8601": "2025-07-22T08:22:13.613117Z",
            "url": "https://files.pythonhosted.org/packages/b5/62/77eb3e7c221e83c19cd6a9d765aac8ff7fabc06fdd74a548de5a313810f4/error_markov-0.1.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-07-22 08:22:13",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "lcname": "error-markov"
}
        
Elapsed time: 1.00984s