diff --git a/README.md b/README.md index 77afe6f..a05fcb4 100644 --- a/README.md +++ b/README.md @@ -62,6 +62,26 @@ app = ClassifyTask.from_df( cross_verify_num=2,) ``` +#### Preset the tagging +You can set a column in dataframe, eg. called ```guessed_tags```, to preset the tagging result. + +Each cell can contain the format of tagging result, eg. +```json +{"tags":[ + {"text": "Genomicare Bio Tech", "offset":32, "label":"company"}, + {"text": "East China University of Politic Science & Law", "offset":96, "label":"company"}, + ]} +``` + +Then you can run the app with preset tag column +```python +app = NERTask.from_df( + df, text_col="description", + options=["institution", "company", "name"], + preset_tag_col="guessed_tags") +app.run("0.0.0.0", port=5000) +``` + #### Order strategy The order of which text got tagged first is according to order_strategy. diff --git a/docs/loader/README.md b/docs/loader/README.md index 7f03256..ce4a357 100644 --- a/docs/loader/README.md +++ b/docs/loader/README.md @@ -54,7 +54,9 @@ len(train_ds), len(val_ds) ```python -x, y = data_ds.one_batch(5) +batch = data_ds.one_batch(5) +x = batch['input_ids'] +y = batch['targets'] ``` diff --git a/langhuan/options.py b/langhuan/options.py index 1ec2be1..f28a521 100644 --- a/langhuan/options.py +++ b/langhuan/options.py @@ -33,7 +33,7 @@ def __init__( dict(options=self.option_vals, idx=self.df_idx)) self.option_col = self.df["options"] - self.df.set_index("idx") + self.df = self.df.set_index("idx") def __len__(self): return len(self.df) diff --git a/langhuan/tasks.py b/langhuan/tasks.py index 4193f22..652feeb 100644 --- a/langhuan/tasks.py +++ b/langhuan/tasks.py @@ -27,6 +27,7 @@ def from_df( task_name: str = None, options: List[str] = None, load_history: bool = False, + preset_tag_col: str = None, save_frequency: int = 42, order_strategy: Union[str, Callable] = "forward_march", order_by_column: str = None, @@ -42,6 +43,8 @@ def from_df( you don't even have to decide this now, you can input None and configure it on /admin page later - load_history: bool = False, load the saved history if True + - preset_tag_col: str = None, a column name + that contains preset tags - task_name: str, name of your task, if not provided - order_strategy: Union[str, Callable] = "forward_march", a function defining how progress move one by one. As a @@ -90,7 +93,7 @@ def from_df( app.config['TEMPLATES_AUTO_RELOAD'] = True HyperFlask(app) - app.register(df, text_col, Options(df, options)) + app.register(df, text_col, preset_tag_col, Options(df, options)) app.create_progress( order_strategy, order_by_column, @@ -219,9 +222,16 @@ def raw_data(): rt = dict(idx=idx, index=index, text=text, options=list(options)) + # Scenario 1, when we have tagged data in progress if user_id in self.progress.depth[index].keys(): rt.update({"record": self.progress.depth[index][user_id]}) + # Scenario 2, when we have preset tag defined in dataframe + elif self.preset_tag_col is not None: + preset_tag = self.df.loc[idx, self.preset_tag_col] + if preset_tag is not None: + rt.update({"record": preset_tag}) + return jsonify(rt) @self.route("/tagging", methods=["POST"]) @@ -357,10 +367,16 @@ def register( self, df: pd.DataFrame, text_col: Union[List[str], str], + preset_tag_col: str, options: List[str], ) -> None: + """ + Register properties to the class + """ self.df = df self.text_col = text_col + self.preset_tag_col = preset_tag_col + self.options = options self.register_functions() diff --git a/langhuan/templates/ner.html b/langhuan/templates/ner.html index cf1d4fd..ec87786 100644 --- a/langhuan/templates/ner.html +++ b/langhuan/templates/ner.html @@ -4,7 +4,8 @@ {{super()}}

- NER task

+ NER task + {%endblock%} {%block controls%} @@ -54,7 +55,7 @@
const create_option_list = (options) => { var option_list = []; var option_to_data = {} - var color_ct=0; + var color_ct = 0; for (var i in options) { if (color_ct >= flavors.length) { color_ct = 0 @@ -80,18 +81,24 @@
this.node.title = d.label; var node = this.node + /* + Click the selected to remove tag + */ this.node.addEventListener("click", () => { node.after(node.innerText) node.remove() }) } - get_node(){ + get_node() { return this.node } } const calc_label = () => { + /* + From the DOM, get the tagged data + */ var nodes = document.querySelector("#raw").childNodes var tags = []; @@ -119,7 +126,6 @@
tagging(data) } - document.querySelector("#next").addEventListener("click", next_btn) document.querySelector("#skip").addEventListener("click", skipping) @@ -155,24 +161,27 @@
const get_history = async () => { var user_id = get_user_id() fetch(`/personal_history?user_id=${user_id}`) - .then(res=>res.json()) - .then(data=>{ - d3.select("#histories") - .selectAll(".history_entry") - .data(data) - .enter() - .append("div") - .attr("class", - "history_entry m-3 pt-1 pb-1 pl-3 pr-3 border border-primary rounded-pill border-3 border-top-0 border-bottom-0") - .text(d=>{return `${d.time.substring(9,17)} (${d.tags}x🏷)`}) - .on("click", (e, data) => { - window.location = `/?index=${data.index}` + .then(res => res.json()) + .then(data => { + d3.select("#histories") + .selectAll(".history_entry") + .data(data) + .enter() + .append("div") + .attr("class", + "history_entry m-3 pt-1 pb-1 pl-3 pr-3 border border-primary rounded-pill border-3 border-top-0 border-bottom-0") + .text(d => { return `${d.time.substring(9, 17)} (${d.tags}x🏷)` }) + .on("click", (e, data) => { + window.location = `/?index=${data.index}` + }) }) - }) - .catch(console.error) + .catch(console.error) } const visualize_options = (options) => { + /* + Visualize the options as buttons + */ d3.select("#label_pool").selectAll("button") .data(options) .enter().append("button") @@ -214,7 +223,7 @@
subs.push({ text: text.substring(ct, text.length) }) // console.log(subs) - raw.innerHTML="" + raw.innerHTML = "" for (var i in subs) { var sub = subs[i]; diff --git a/langhuan/utility.py b/langhuan/utility.py index 8a928fd..e8bf4a1 100644 --- a/langhuan/utility.py +++ b/langhuan/utility.py @@ -3,6 +3,7 @@ from typing import Union import json from pathlib import Path +import regex def now_str(): return datetime.now().strftime("%y%m%d_%H%M%S") @@ -38,3 +39,12 @@ def arg_by_key(key: str) -> Union[str, int, float]: def get_root() -> Path: return Path(__file__).parent.absolute() + + +def findall_word_position(text: str, word: str) -> list: + """ + find all the position of word in text + """ + text = text.lower() + word = word.lower() + return [m.start() for m in regex.finditer(word, text)] diff --git a/settings.ini b/settings.ini index d05de87..06a77cb 100644 --- a/settings.ini +++ b/settings.ini @@ -6,7 +6,7 @@ keywords = python pandas label data science author = xiaochen(ray) zhang author_email = b2ray2c@gmail.com branch = main -version = 0.0.18 +version = 0.1.0 min_python = 3.6 audience = Developers language = English diff --git a/tests/loader.ipynb b/tests/loader.ipynb index 9dc5958..259f0f8 100644 --- a/tests/loader.ipynb +++ b/tests/loader.ipynb @@ -106,6 +106,98 @@ "len(train_ds), len(val_ds)" ] }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[{'index': 0,\n", + " 'now': '21-02-01_15:39:20',\n", + " 'pandas': 0,\n", + " 'remote_addr': '127.0.0.1',\n", + " 'tags': [{'label': 'school',\n", + " 'offset': 122,\n", + " 'text': 'University of Maryland'},\n", + " {'label': 'company', 'offset': 346, 'text': 'Bricklin'}],\n", + " 'user_id': '4de71c07fa'},\n", + " {'index': 1,\n", + " 'now': '21-02-01_15:38:29',\n", + " 'pandas': 1,\n", + " 'remote_addr': '127.0.0.1',\n", + " 'tags': [{'label': 'school',\n", + " 'offset': 213,\n", + " 'text': 'University of Washington'},\n", + " {'label': 'company', 'offset': 340, 'text': 'SI'}],\n", + " 'user_id': '4de71c07fa'},\n", + " {'index': 2,\n", + " 'now': '21-02-01_15:39:03',\n", + " 'pandas': 2,\n", + " 'remote_addr': '127.0.0.1',\n", + " 'tags': [{'label': 'school', 'offset': 89, 'text': 'Purdue University'},\n", + " {'label': 'company', 'offset': 107, 'text': 'Engineering Computer Network'},\n", + " {'label': 'company',\n", + " 'offset': 1795,\n", + " 'text': 'Purdue Electrical Engineering'}],\n", + " 'user_id': '4de71c07fa'},\n", + " {'index': 3,\n", + " 'now': '21-02-01_15:39:11',\n", + " 'pandas': 3,\n", + " 'remote_addr': '127.0.0.1',\n", + " 'tags': [{'label': 'company',\n", + " 'offset': 73,\n", + " 'text': 'Harris Computer Systems Division'},\n", + " {'label': 'company', 'offset': 645, 'text': 'Harris Corporation'}],\n", + " 'user_id': '4de71c07fa'},\n", + " {'index': 4,\n", + " 'now': '21-02-01_15:40:03',\n", + " 'pandas': 4,\n", + " 'remote_addr': '127.0.0.1',\n", + " 'tags': [{'label': 'school',\n", + " 'offset': 102,\n", + " 'text': 'Smithsonian Astrophysical Observatory'}],\n", + " 'user_id': '4de71c07fa'},\n", + " {'index': 5,\n", + " 'now': '21-02-01_15:40:38',\n", + " 'pandas': 5,\n", + " 'remote_addr': '127.0.0.1',\n", + " 'tags': [],\n", + " 'user_id': '4de71c07fa'},\n", + " {'index': 6,\n", + " 'now': '21-02-01_15:40:55',\n", + " 'pandas': 6,\n", + " 'remote_addr': '127.0.0.1',\n", + " 'tags': [{'label': 'school',\n", + " 'offset': 151,\n", + " 'text': 'University of Chicago'}],\n", + " 'user_id': '4de71c07fa'},\n", + " {'index': 7,\n", + " 'now': '21-02-01_15:43:01',\n", + " 'pandas': 7,\n", + " 'remote_addr': '127.0.0.1',\n", + " 'tags': [{'label': 'school',\n", + " 'offset': 75,\n", + " 'text': 'New Mexico State University'},\n", + " {'label': 'company', 'offset': 1936, 'text': 'IBM'},\n", + " {'label': 'company', 'offset': 2151, 'text': 'IBM'},\n", + " {'label': 'company', 'offset': 2238, 'text': 'Quadra'},\n", + " {'label': 'company', 'offset': 2266, 'text': 'Apple'},\n", + " {'label': 'company', 'offset': 2753, 'text': 'Quadra'},\n", + " {'label': 'company', 'offset': 2790, 'text': 'Digital Review'}],\n", + " 'user_id': '4de71c07fa'}]" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "data_ds.labels" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/tests/ner_test.ipynb b/tests/ner_test.ipynb index ba9b68d..0184a97 100644 --- a/tests/ner_test.ipynb +++ b/tests/ner_test.ipynb @@ -7,8 +7,11 @@ "outputs": [], "source": [ "from langhuan import NERTask\n", + "from langhuan.utility import findall_word_position\n", "from forgebox.imports import *\n", - "from sklearn.datasets import fetch_20newsgroups" + "from sklearn.datasets import fetch_20newsgroups\n", + "from uuid import uuid4\n", + "import regex" ] }, { @@ -91,19 +94,238 @@ "metadata": {}, "outputs": [], "source": [ - "app = NERTask.from_df(df, text_col=\"text\", options=[\"institution\", \"company\", \"name\"])" + "def word_finder(kw, label):\n", + " def get_tags(text):\n", + " tags = []\n", + " for offset in findall_word_position(text, kw):\n", + " tags.append(dict(\n", + " text=text[offset:offset+len(kw)],\n", + " label=label,\n", + " offset=offset\n", + " ))\n", + " return dict(tags=tags, preset=\"preset\")\n", + " return get_tags" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set extra unique id" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, + "outputs": [], + "source": [ + "df[\"special_id\"] = list(str(uuid4()) for uid in range(len(df)))\n", + "df = df.set_index(\"special_id\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Preset some tags" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "df[\"guess\"] = df.text.apply(word_finder(\"university\",\"institution\"))" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
textguess
special_id
f7ec2c6f-046a-469f-a18a-d4a0540af07bFrom: lerxst@wam.umd.edu (where's my thing)\\nS...{'tags': [{'text': 'University', 'label': 'ins...
4c2eecd7-39f4-4d7c-b586-a7c7803a74c0From: guykuo@carson.u.washington.edu (Guy Kuo)...{'tags': [{'text': 'University', 'label': 'ins...
a96d71fa-47d4-474a-b835-6078761865d7From: twillis@ec.ecn.purdue.edu (Thomas E Will...{'tags': [{'text': 'University', 'label': 'ins...
acd720f6-d70b-457b-ac1c-fb175f91bd9eFrom: jgreen@amber (Joe Green)\\nSubject: Re: W...{'tags': [], 'preset': 'preset'}
c34a56dc-a053-4cfe-8606-498087d49e79From: jcm@head-cfa.harvard.edu (Jonathan McDow...{'tags': [], 'preset': 'preset'}
.........
47d62545-3a21-402c-83a6-7a590981d06cFrom: jim.zisfein@factory.com (Jim Zisfein) \\n...{'tags': [], 'preset': 'preset'}
829cde95-4d2d-4b85-ad15-0d062832b4dcFrom: ebodin@pearl.tufts.edu\\nSubject: Screen ...{'tags': [{'text': 'University', 'label': 'ins...
3b96eff1-8ba6-4d98-9c11-49e661230a20From: westes@netcom.com (Will Estes)\\nSubject:...{'tags': [], 'preset': 'preset'}
952f8e26-e817-4bb2-ab84-243e43bcf094From: steve@hcrlgw (Steven Collins)\\nSubject: ...{'tags': [], 'preset': 'preset'}
39ce49c8-ac3e-4310-9c8f-9f29f2a18f86From: gunning@cco.caltech.edu (Kevin J. Gunnin...{'tags': [], 'preset': 'preset'}
\n", + "

11314 rows × 2 columns

\n", + "
" + ], + "text/plain": [ + " text \\\n", + "special_id \n", + "f7ec2c6f-046a-469f-a18a-d4a0540af07b From: lerxst@wam.umd.edu (where's my thing)\\nS... \n", + "4c2eecd7-39f4-4d7c-b586-a7c7803a74c0 From: guykuo@carson.u.washington.edu (Guy Kuo)... \n", + "a96d71fa-47d4-474a-b835-6078761865d7 From: twillis@ec.ecn.purdue.edu (Thomas E Will... \n", + "acd720f6-d70b-457b-ac1c-fb175f91bd9e From: jgreen@amber (Joe Green)\\nSubject: Re: W... \n", + "c34a56dc-a053-4cfe-8606-498087d49e79 From: jcm@head-cfa.harvard.edu (Jonathan McDow... \n", + "... ... \n", + "47d62545-3a21-402c-83a6-7a590981d06c From: jim.zisfein@factory.com (Jim Zisfein) \\n... \n", + "829cde95-4d2d-4b85-ad15-0d062832b4dc From: ebodin@pearl.tufts.edu\\nSubject: Screen ... \n", + "3b96eff1-8ba6-4d98-9c11-49e661230a20 From: westes@netcom.com (Will Estes)\\nSubject:... \n", + "952f8e26-e817-4bb2-ab84-243e43bcf094 From: steve@hcrlgw (Steven Collins)\\nSubject: ... \n", + "39ce49c8-ac3e-4310-9c8f-9f29f2a18f86 From: gunning@cco.caltech.edu (Kevin J. Gunnin... \n", + "\n", + " guess \n", + "special_id \n", + "f7ec2c6f-046a-469f-a18a-d4a0540af07b {'tags': [{'text': 'University', 'label': 'ins... \n", + "4c2eecd7-39f4-4d7c-b586-a7c7803a74c0 {'tags': [{'text': 'University', 'label': 'ins... \n", + "a96d71fa-47d4-474a-b835-6078761865d7 {'tags': [{'text': 'University', 'label': 'ins... \n", + "acd720f6-d70b-457b-ac1c-fb175f91bd9e {'tags': [], 'preset': 'preset'} \n", + "c34a56dc-a053-4cfe-8606-498087d49e79 {'tags': [], 'preset': 'preset'} \n", + "... ... \n", + "47d62545-3a21-402c-83a6-7a590981d06c {'tags': [], 'preset': 'preset'} \n", + "829cde95-4d2d-4b85-ad15-0d062832b4dc {'tags': [{'text': 'University', 'label': 'ins... \n", + "3b96eff1-8ba6-4d98-9c11-49e661230a20 {'tags': [], 'preset': 'preset'} \n", + "952f8e26-e817-4bb2-ab84-243e43bcf094 {'tags': [], 'preset': 'preset'} \n", + "39ce49c8-ac3e-4310-9c8f-9f29f2a18f86 {'tags': [], 'preset': 'preset'} \n", + "\n", + "[11314 rows x 2 columns]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Run service" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Service with preset tags" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [], + "source": [ + "app = NERTask.from_df(df, text_col=\"text\", options=[\"institution\", \"company\", \"name\"], preset_tag_col=\"guess\")" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Service without preset tags" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [], + "source": [ + "app = NERTask.from_df(df, text_col=\"text\", options=[\"institution\", \"company\", \"name\"])" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - " * Serving Flask app \"task_NER_210120_155940\" (lazy loading)\n", + " * Serving Flask app \"task_NER_210901_105527\" (lazy loading)\n", " * Environment: production\n", " WARNING: This is a development server. Do not use it in a production deployment.\n", " Use a production WSGI server instead.\n", @@ -115,15 +337,17 @@ "output_type": "stream", "text": [ " * Running on http://0.0.0.0:5001/ (Press CTRL+C to quit)\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[37mGET / HTTP/1.1\u001b[0m\" 200 -\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[37mGET /static/js/jquery.min.js HTTP/1.1\u001b[0m\" 200 -\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[37mGET /static/js/bootstrap.min.js HTTP/1.1\u001b[0m\" 200 -\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[37mGET /static/js/popper.min.js HTTP/1.1\u001b[0m\" 200 -\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[37mGET /static/js/d3.js HTTP/1.1\u001b[0m\" 200 -\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[37mGET /static/css/bootstrap.css HTTP/1.1\u001b[0m\" 200 -\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[37mPOST /data HTTP/1.1\u001b[0m\" 200 -\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[37mGET /personal_history?user_id=2fe81aa184 HTTP/1.1\u001b[0m\" 200 -\n", - "127.0.0.1 - - [20/Jan/2021 15:59:55] \"\u001b[33mGET /favicon.ico HTTP/1.1\u001b[0m\" 404 -\n" + "127.0.0.1 - - [01/Sep/2021 10:55:38] \"\u001b[37mGET /admin HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:38] \"\u001b[37mPOST /get_options HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:38] \"\u001b[37mPOST /stats HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:42] \"\u001b[37mGET /?index=3 HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:43] \"\u001b[37mPOST /data HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:43] \"\u001b[37mGET /personal_history?user_id=2fe81aa184 HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:56] \"\u001b[37mPOST /tagging HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:56] \"\u001b[37mGET / HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:56] \"\u001b[37mPOST /data HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:55:56] \"\u001b[37mGET /personal_history?user_id=2fe81aa184 HTTP/1.1\u001b[0m\" 200 -\n", + "127.0.0.1 - - [01/Sep/2021 10:56:01] \"\u001b[37mPOST /data HTTP/1.1\u001b[0m\" 200 -\n" ] } ],