Remove scrapingh & fix broken links

docs/how-to-guides/scraping.ipynb

@@ -1,104 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import httpx\n",
-    "\n",
-    "transport = httpx.AsyncHTTPTransport(retries=2)\n",
-    "limits = httpx.Limits(max_connections=None)\n",
-    "timeout = httpx.Timeout(connect=60.0, read=300, write=60, pool=None)\n",
-    "async with httpx.AsyncClient(\n",
-    "    transport=transport, limits=limits, timeout=timeout\n",
-    ") as client:\n",
-    "    pass"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\u001b[38;5;226m2022-07-11 19:00:27 |  WARNING | Environment variable ENVIRONMENT is not set, defaulting to development mode ‼️\u001b[0m\n",
-      "\u001b[38;5;226m2022-07-11 19:00:27 |  WARNING | Cannot find credentials files, defaulting to using ParallelTinyDbDriver\u001b[0m\n",
-      "\u001b[38;5;226m2022-07-11 19:00:27 |  WARNING | The selected tracing database (ParallelTinyDbDriver) is not recommended for production\u001b[0m\n",
-      "\u001b[38;5;226m2022-07-11 19:00:27 |  WARNING | Cannot find credentials files, defaulting to using LargeFileLocal\u001b[0m\n",
-      "\u001b[38;5;39m2022-07-11 19:00:27 |     INFO | GreatAI (v0.1.3): configured ✅\u001b[0m\n",
-      "\u001b[38;5;39m2022-07-11 19:00:27 |     INFO |   🔩 tracing_database: ParallelTinyDbDriver\u001b[0m\n",
-      "\u001b[38;5;39m2022-07-11 19:00:27 |     INFO |   🔩 large_file_implementation: LargeFileLocal\u001b[0m\n",
-      "\u001b[38;5;39m2022-07-11 19:00:27 |     INFO |   🔩 is_production: False\u001b[0m\n",
-      "\u001b[38;5;39m2022-07-11 19:00:27 |     INFO |   🔩 should_log_exception_stack: True\u001b[0m\n",
-      "\u001b[38;5;39m2022-07-11 19:00:27 |     INFO |   🔩 prediction_cache_size: 512\u001b[0m\n",
-      "\u001b[38;5;39m2022-07-11 19:00:27 |     INFO |   🔩 dashboard_table_size: 50\u001b[0m\n",
-      "\u001b[38;5;226m2022-07-11 19:00:27 |  WARNING | You still need to check whether you follow all best practices before trusting your deployment.\u001b[0m\n",
-      "\u001b[38;5;226m2022-07-11 19:00:27 |  WARNING | > Find out more at https://se-ml.github.io/practices\u001b[0m\n"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "Trace[str]({'created': '2022-07-11T17:00:27.064568',\n",
-       "  'exception': None,\n",
-       "  'feedback': None,\n",
-       "  'logged_values': {'arg:your_name:length': 3, 'arg:your_name:value': 'Bob'},\n",
-       "  'models': [],\n",
-       "  'original_execution_time_ms': 0.0896,\n",
-       "  'output': 'Hi Bob',\n",
-       "  'tags': ['greeter', 'online', 'development'],\n",
-       "  'trace_id': '8ff5b268-2613-4e85-96ae-f248666a051f'})"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from great_ai import configure, RouteConfig\n",
-    "from great_ai import GreatAI\n",
-    "\n",
-    "\n",
-    "@GreatAI.create\n",
-    "def greeter(your_name: str) -> str:\n",
-    "    return f\"Hi {your_name}\"\n",
-    "\n",
-    "\n",
-    "greeter(\"Bob\")"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3.10.4 ('.env': venv)",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.4"
-  },
-  "orig_nbformat": 4,
-  "vscode": {
-   "interpreter": {
-    "hash": "02dd6d3afbfa9fbbe1037d64ad9014965528a1ccad21929d6e72f466389a68ad"
-   }
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}

docs/reference/utilities.md

@@ -10,10 +10,10 @@ Well-tested tools that can be used in production with confidence. The toolbox of
 
 ::: great_ai.utilities.clean
 ::: great_ai.utilities.get_sentences
-::: great_ai.utilities.predict_language
+::: great_ai.utilities.language.predict_language
-::: great_ai.utilities.is_english
+::: great_ai.utilities.language.english_name_of_language
-::: great_ai.utilities.english_name_of_language
+::: great_ai.utilities.language.is_english
-::: great_ai.utilities.evaluate_ranking
+::: great_ai.utilities.evaluate_ranking.evaluate_ranking
 
 ## Parallel processing
 
@@ -29,7 +29,7 @@ Multiprocessing and multithreading-based parallelism with support for `async` fu
 
 ## Composable parallel processing
 
-Because both [threaded_parallel_map][great_ai.utilities.parallel_map.threaded_parallel_map.threaded_parallel_map] and [parallel_map][great_ai.utilities.parallel_map.parallel_map] have a streaming interface, it is easy to compose them and end up with, for example, a process for each CPU core with its own thread-pool or event-loop. Longer pipelines are also easy to imagine. The chunking methods help in these compositions.
+Because both [threaded_parallel_map][great_ai.utilities.parallel_map.threaded_parallel_map.threaded_parallel_map] and [parallel_map][great_ai.utilities.parallel_map.parallel_map.parallel_map] have a streaming interface, it is easy to compose them and end up with, for example, a process for each CPU core with its own thread-pool or event-loop. Longer pipelines are also easy to imagine. The chunking methods help in these compositions.
 
 For more info, check-out [the scraping guide](/how-to-guides/scraping).
 

great_ai/deploy/great_ai.py

@@ -190,7 +190,7 @@ class GreatAI(Generic[T, V]):
     ) -> List[Trace[V]]:
         """Map the wrapped function over a list of input_values (`batch`).
 
-        A wrapper over [parallel_map][great_ai.utilities.parallel_map]
+        A wrapper over [parallel_map][great_ai.utilities.parallel_map.parallel_map.parallel_map]
         providing type-safety and a progressbar through tqdm.
 
         Args:

great_ai/tracing/add_ground_truth.py

@@ -66,7 +66,7 @@ def add_ground_truth(
         train_split_ratio: The probability-weight of giving each trace the `train` tag.
         test_split_ratio: The probability-weight of giving each trace the `test` tag.
         validation_split_ratio: The probability-weight of giving each trace the
-        `validation` tag.
+            `validation` tag.
     """
 
     inputs = list(inputs)

great_ai/utilities/get_sentences.py

@@ -34,7 +34,7 @@ def get_sentences(
     Args:
         text: Text to be segmented into sentences.
         ignore_partial: Filter out sentences that are not capitalised/don't end with a
-        punctuation.
+            punctuation.
         true_case: Crude method: lowercase the first word of each sentence.
         remove_punctuation: Remove all kinds of punctuation.
 

great_ai/utilities/language/english_name_of_language.py

@@ -18,7 +18,7 @@ def english_name_of_language(language_code: Optional[str]) -> str:
 
     Args:
         language_code: Language code, for example, returned by
-            [great_ai.utilities.predict_language][].
+            [great_ai.utilities.language.predict_language.predict_language][].
 
     Returns:
         English name of language.

great_ai/utilities/language/is_english.py

@@ -21,7 +21,7 @@ def is_english(language_code: Optional[str]) -> bool:
 
     Args:
         language_code: Language code, for example, returned by
-            `[great_ai.utilities.predict_language][].
+            `[great_ai.utilities.language.predict_language.predict_language][].
 
     Returns:
         Boolean indicating whether it's English.

mkdocs.yaml

@@ -101,7 +101,6 @@ nav:
     - how-to-guides/handle-training-data.md
     - how-to-guides/large_file.md
     - how-to-guides/call-remote.md
-    - how-to-guides/scraping.ipynb
   - Reference:
     - reference/index.md
     - reference/utilities.md