Fix merge

.pre-commit-config.yaml

@@ -11,6 +11,16 @@ repos:
       - id: mixed-line-ending
       - id: trailing-whitespace
 
+  - repo: https://github.com/python-poetry/poetry
+    rev: 1.8.2
+    hooks:
+      - id: poetry-check
+      - id: poetry-lock
+      - id: poetry-export
+        args: ["--without", "dev", "-f", "requirements.txt", "-o", "requirements.txt"]
+      - id: poetry-export
+        args: ["--only", "dev", "-f", "requirements.txt", "-o", "requirements-dev.txt"]
+
   - repo: https://github.com/astral-sh/ruff-pre-commit
     rev: v0.4.4
     hooks:

README.md

@@ -5,7 +5,7 @@ Sentiment Analysis
 1. Clone the repository
 2. `cd` into the repository
 3. Run `just install` to install the dependencies
-4. Run `just run --help` to see the available commands
+4. Run `just app --help` to see the available commands
 
 ### Datasets
 - [Sentiment140](https://www.kaggle.com/datasets/kazanova/sentiment140)
@@ -17,15 +17,6 @@ Sentiment Analysis
 - `poetry`
 
 ### TODO
-- [ ] CLI using `click` (commands: predict, train, evaluate) with settings set via flags or environment variables
-- [ ] GUI using `gradio` (tabs: predict, train, evaluate, compare, settings)
-- [ ] For the sklearn model, add more classifiers
 - [ ] Use random search for hyperparameter tuning and grid search for fine-tuning
-- [ ] Finish the text pre-processing transformer
-- [ ] For vectorization, use custom stopwords
-- [ ] Write own tokenizer/vectorizer
-- [ ] Add more datasets
-- [ ] Add more models (e.g. BERT)
-- [ ] Write tests
+- [ ] Use a stopword list
 - [ ] Use xgboost?
-- [ ] Deploy to huggingface?

app/cli.py

@@ -7,11 +7,7 @@ import click
 
 __all__ = ["cli_wrapper"]
 
-ERROR_STR = click.style("ERROR", fg="red")
 DONE_STR = click.style("DONE", fg="green")
-POSITIVE_STR = click.style("POSITIVE", fg="green")
-NEUTRAL_STR = click.style("NEUTRAL", fg="yellow")
-NEGATIVE_STR = click.style("NEGATIVE", fg="red")
 
 
 @click.group()
@@ -62,8 +58,8 @@ def predict(model_path: Path, text: list[str]) -> None:
         text = piped_text or text
 
     if not text:
-        click.echo(f"{ERROR_STR}: No text provided")
-        return
+        msg = "No text provided"
+        raise click.UsageError(msg)
 
     click.echo("Loading model... ", nl=False)
     model = joblib.load(model_path)
@@ -72,11 +68,11 @@ def predict(model_path: Path, text: list[str]) -> None:
     click.echo("Performing sentiment analysis... ", nl=False)
     prediction = model.predict([text])[0]
     if prediction == 0:
-        sentiment = NEGATIVE_STR
+        sentiment = click.style("NEGATIVE", fg="red")
     elif prediction == 1:
-        sentiment = POSITIVE_STR
+        sentiment = click.style("POSITIVE", fg="green")
     else:
-        sentiment = NEUTRAL_STR
+        sentiment = click.style("NEUTRAL", fg="yellow")
     click.echo(sentiment)
 
 

app/model/base.py

@@ -1,49 +0,0 @@
-from __future__ import annotations
-
-from abc import ABC, abstractmethod
-from typing import TYPE_CHECKING
-
-import joblib
-
-if TYPE_CHECKING:
-    from pathlib import Path
-
-    from sklearn.pipeline import Pipeline
-
-
-class Model(ABC):
-    """Base class for all models"""
-
-    @property
-    @abstractmethod
-    def pipeline(self) -> Pipeline:
-        """Pipeline used for the model"""
-        ...
-
-    @property
-    @abstractmethod
-    def description(self) -> str:
-        """Description of the architecture"""
-        ...
-
-    @abstractmethod
-    def _predict(self, text: str) -> int:
-        """Predict the sentiment of the given text"""
-        ...
-
-    @staticmethod
-    def from_file(path: Path) -> Model:
-        """Load the model from the given file"""
-        return joblib.load(path)
-
-    def to_file(self, path: Path) -> None:
-        """Save the model to the given file"""
-        joblib.dump(self, path)
-
-    def predict(self, text: str) -> int:
-        """Perform sentiment analysis on the given text"""
-        return self._predict(text)
-
-    def train(self, x: list[str], y: list[int]) -> None:
-        """Train the model on the given data"""
-        self.pipeline.fit(x, y)

app/model/tfid_lr.py

@@ -1,35 +0,0 @@
-from __future__ import annotations
-
-from sklearn.feature_extraction.text import CountVectorizer, TfidfTransformer
-from sklearn.linear_model import LogisticRegression
-from sklearn.pipeline import Pipeline
-
-from .base import Model
-
-
-class TfidfLR(Model):
-    """Sentiment analysis model using TF-IDF and Logistic Regression"""
-
-    def __init__(self):
-        self._pipeline = Pipeline(
-            [
-                (
-                    "vectorize",
-                    CountVectorizer(stop_words="english", ngram_range=(1, 2), max_features=10000),
-                ),
-                ("tfidf", TfidfTransformer()),
-                ("clf", LogisticRegression(max_iter=1000, random_state=self.rng)),
-            ],
-            memory=self.cache,
-        )
-
-    @property
-    def pipeline(self) -> Pipeline:
-        return self._pipeline
-
-    @property
-    def description(self) -> str:
-        return "TF-IDF with Logistic Regression"
-
-    def _predict(self, text: str) -> int:
-        return self.pipeline.predict([text])[0]

pyproject.toml

@@ -9,8 +9,6 @@ scikit-learn = "^1.4.2"
 gradio = "^4.31.0"
 colorama = "^0.4.6"
 nltk = "^3.8.1"
-
-[tool.poetry.group.train.dependencies]
 pandas = "^2.2.2"
 numpy = "^1.26.4"
 seaborn = "^0.13.2"
@@ -33,32 +31,6 @@ indent-width = 4
 
 [tool.ruff.lint]
 fixable = ["ALL"]
-# select = [
-#   "E",   # pycodestyle
-#   "F",   # Pyflakes
-#   "UP",  # pyupgrade
-#   "B",   # flake8-bugbear
-#   "SIM", # flake8-simplify
-#   "I",   # isort
-# ]
-# ignore = [
-#   # Conflicting rules with the formatter
-#   "W191",   # tab-indentation
-#   "E111",   # indentation-with-invalid-multiple
-#   "E114",   # indentation-with-invalid-multiple-comment
-#   "E117",   # over-indented
-#   "D206",   # indent-with-spaces
-#   "D300",   # triple-single-quotes
-#   "Q000",   # bad-quotes-inline-string
-#   "Q001",   # bad-quotes-multiline-string
-#   "Q002",   # bad-quotes-docstring
-#   "Q003",   # avoidable-escaped-quote
-#   "COM812", # missing-trailing-comma
-#   "COM819", # prohibited-trailing-comma
-#   "ISC001", # single-line-implicit-string-concatenation
-#   "ISC002", # multi-line-implicit-string-concatenation
-#   "E501",   # line-too-long
-# ]
 ignore = [
   "E501",    # pycodestyle line too long, handled by black
   "D100",    # pydocstyle - missing docstring in public module

requirements-dev.txt

@@ -0,0 +1,735 @@
+appnope==0.1.4 ; python_version >= "3.12" and python_version < "4.0" and platform_system == "Darwin" \
+    --hash=sha256:1de3860566df9caf38f01f86f65e0e13e379af54f9e4bee1e66b48f2efffd1ee \
+    --hash=sha256:502575ee11cd7a28c0205f379b525beefebab9d161b7c964670864014ed7213c
+asttokens==2.4.1 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:051ed49c3dcae8913ea7cd08e46a606dba30b79993209636c4875bc1d637bc24 \
+    --hash=sha256:b03869718ba9a6eb027e134bfdf69f38a236d681c83c160d510768af11254ba0
+cffi==1.16.0 ; python_version >= "3.12" and python_version < "4.0" and implementation_name == "pypy" \
+    --hash=sha256:0c9ef6ff37e974b73c25eecc13952c55bceed9112be2d9d938ded8e856138bcc \
+    --hash=sha256:131fd094d1065b19540c3d72594260f118b231090295d8c34e19a7bbcf2e860a \
+    --hash=sha256:1b8ebc27c014c59692bb2664c7d13ce7a6e9a629be20e54e7271fa696ff2b417 \
+    --hash=sha256:2c56b361916f390cd758a57f2e16233eb4f64bcbeee88a4881ea90fca14dc6ab \
+    --hash=sha256:2d92b25dbf6cae33f65005baf472d2c245c050b1ce709cc4588cdcdd5495b520 \
+    --hash=sha256:31d13b0f99e0836b7ff893d37af07366ebc90b678b6664c955b54561fc36ef36 \
+    --hash=sha256:32c68ef735dbe5857c810328cb2481e24722a59a2003018885514d4c09af9743 \
+    --hash=sha256:3686dffb02459559c74dd3d81748269ffb0eb027c39a6fc99502de37d501faa8 \
+    --hash=sha256:582215a0e9adbe0e379761260553ba11c58943e4bbe9c36430c4ca6ac74b15ed \
+    --hash=sha256:5b50bf3f55561dac5438f8e70bfcdfd74543fd60df5fa5f62d94e5867deca684 \
+    --hash=sha256:5bf44d66cdf9e893637896c7faa22298baebcd18d1ddb6d2626a6e39793a1d56 \
+    --hash=sha256:6602bc8dc6f3a9e02b6c22c4fc1e47aa50f8f8e6d3f78a5e16ac33ef5fefa324 \
+    --hash=sha256:673739cb539f8cdaa07d92d02efa93c9ccf87e345b9a0b556e3ecc666718468d \
+    --hash=sha256:68678abf380b42ce21a5f2abde8efee05c114c2fdb2e9eef2efdb0257fba1235 \
+    --hash=sha256:68e7c44931cc171c54ccb702482e9fc723192e88d25a0e133edd7aff8fcd1f6e \
+    --hash=sha256:6b3d6606d369fc1da4fd8c357d026317fbb9c9b75d36dc16e90e84c26854b088 \
+    --hash=sha256:748dcd1e3d3d7cd5443ef03ce8685043294ad6bd7c02a38d1bd367cfd968e000 \
+    --hash=sha256:7651c50c8c5ef7bdb41108b7b8c5a83013bfaa8a935590c5d74627c047a583c7 \
+    --hash=sha256:7b78010e7b97fef4bee1e896df8a4bbb6712b7f05b7ef630f9d1da00f6444d2e \
+    --hash=sha256:7e61e3e4fa664a8588aa25c883eab612a188c725755afff6289454d6362b9673 \
+    --hash=sha256:80876338e19c951fdfed6198e70bc88f1c9758b94578d5a7c4c91a87af3cf31c \
+    --hash=sha256:8895613bcc094d4a1b2dbe179d88d7fb4a15cee43c052e8885783fac397d91fe \
+    --hash=sha256:88e2b3c14bdb32e440be531ade29d3c50a1a59cd4e51b1dd8b0865c54ea5d2e2 \
+    --hash=sha256:8f8e709127c6c77446a8c0a8c8bf3c8ee706a06cd44b1e827c3e6a2ee6b8c098 \
+    --hash=sha256:9cb4a35b3642fc5c005a6755a5d17c6c8b6bcb6981baf81cea8bfbc8903e8ba8 \
+    --hash=sha256:9f90389693731ff1f659e55c7d1640e2ec43ff725cc61b04b2f9c6d8d017df6a \
+    --hash=sha256:a09582f178759ee8128d9270cd1344154fd473bb77d94ce0aeb2a93ebf0feaf0 \
+    --hash=sha256:a6a14b17d7e17fa0d207ac08642c8820f84f25ce17a442fd15e27ea18d67c59b \
+    --hash=sha256:a72e8961a86d19bdb45851d8f1f08b041ea37d2bd8d4fd19903bc3083d80c896 \
+    --hash=sha256:abd808f9c129ba2beda4cfc53bde801e5bcf9d6e0f22f095e45327c038bfe68e \
+    --hash=sha256:ac0f5edd2360eea2f1daa9e26a41db02dd4b0451b48f7c318e217ee092a213e9 \
+    --hash=sha256:b29ebffcf550f9da55bec9e02ad430c992a87e5f512cd63388abb76f1036d8d2 \
+    --hash=sha256:b2ca4e77f9f47c55c194982e10f058db063937845bb2b7a86c84a6cfe0aefa8b \
+    --hash=sha256:b7be2d771cdba2942e13215c4e340bfd76398e9227ad10402a8767ab1865d2e6 \
+    --hash=sha256:b84834d0cf97e7d27dd5b7f3aca7b6e9263c56308ab9dc8aae9784abb774d404 \
+    --hash=sha256:b86851a328eedc692acf81fb05444bdf1891747c25af7529e39ddafaf68a4f3f \
+    --hash=sha256:bcb3ef43e58665bbda2fb198698fcae6776483e0c4a631aa5647806c25e02cc0 \
+    --hash=sha256:c0f31130ebc2d37cdd8e44605fb5fa7ad59049298b3f745c74fa74c62fbfcfc4 \
+    --hash=sha256:c6a164aa47843fb1b01e941d385aab7215563bb8816d80ff3a363a9f8448a8dc \
+    --hash=sha256:d8a9d3ebe49f084ad71f9269834ceccbf398253c9fac910c4fd7053ff1386936 \
+    --hash=sha256:db8e577c19c0fda0beb7e0d4e09e0ba74b1e4c092e0e40bfa12fe05b6f6d75ba \
+    --hash=sha256:dc9b18bf40cc75f66f40a7379f6a9513244fe33c0e8aa72e2d56b0196a7ef872 \
+    --hash=sha256:e09f3ff613345df5e8c3667da1d918f9149bd623cd9070c983c013792a9a62eb \
+    --hash=sha256:e4108df7fe9b707191e55f33efbcb2d81928e10cea45527879a4749cbe472614 \
+    --hash=sha256:e6024675e67af929088fda399b2094574609396b1decb609c55fa58b028a32a1 \
+    --hash=sha256:e70f54f1796669ef691ca07d046cd81a29cb4deb1e5f942003f401c0c4a2695d \
+    --hash=sha256:e715596e683d2ce000574bae5d07bd522c781a822866c20495e52520564f0969 \
+    --hash=sha256:e760191dd42581e023a68b758769e2da259b5d52e3103c6060ddc02c9edb8d7b \
+    --hash=sha256:ed86a35631f7bfbb28e108dd96773b9d5a6ce4811cf6ea468bb6a359b256b1e4 \
+    --hash=sha256:ee07e47c12890ef248766a6e55bd38ebfb2bb8edd4142d56db91b21ea68b7627 \
+    --hash=sha256:fa3a0128b152627161ce47201262d3140edb5a5c3da88d73a1b790a959126956 \
+    --hash=sha256:fcc8eb6d5902bb1cf6dc4f187ee3ea80a1eba0a89aba40a5cb20a5087d961357
+cfgv==3.4.0 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9 \
+    --hash=sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560
+colorama==0.4.6 ; python_version >= "3.12" and python_version < "4.0" and sys_platform == "win32" \
+    --hash=sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44 \
+    --hash=sha256:4f1d9991f5acc0ca119f9d443620b77f9d6b33703e51011c16baf57afb285fc6
+comm==0.2.2 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:3fd7a84065306e07bea1773df6eb8282de51ba82f77c72f9c85716ab11fe980e \
+    --hash=sha256:e6fb86cb70ff661ee8c9c14e7d36d6de3b4066f1441be4063df9c5009f0a64d3
+contourpy==1.2.1 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:00e5388f71c1a0610e6fe56b5c44ab7ba14165cdd6d695429c5cd94021e390b2 \
+    --hash=sha256:10a37ae557aabf2509c79715cd20b62e4c7c28b8cd62dd7d99e5ed3ce28c3fd9 \
+    --hash=sha256:11959f0ce4a6f7b76ec578576a0b61a28bdc0696194b6347ba3f1c53827178b9 \
+    --hash=sha256:187fa1d4c6acc06adb0fae5544c59898ad781409e61a926ac7e84b8f276dcef4 \
+    --hash=sha256:1a07fc092a4088ee952ddae19a2b2a85757b923217b7eed584fdf25f53a6e7ce \
+    --hash=sha256:1cac0a8f71a041aa587410424ad46dfa6a11f6149ceb219ce7dd48f6b02b87a7 \
+    --hash=sha256:1d59e739ab0e3520e62a26c60707cc3ab0365d2f8fecea74bfe4de72dc56388f \
+    --hash=sha256:2855c8b0b55958265e8b5888d6a615ba02883b225f2227461aa9127c578a4922 \
+    --hash=sha256:2e785e0f2ef0d567099b9ff92cbfb958d71c2d5b9259981cd9bee81bd194c9a4 \
+    --hash=sha256:309be79c0a354afff9ff7da4aaed7c3257e77edf6c1b448a779329431ee79d7e \
+    --hash=sha256:39f3ecaf76cd98e802f094e0d4fbc6dc9c45a8d0c4d185f0f6c2234e14e5f75b \
+    --hash=sha256:457499c79fa84593f22454bbd27670227874cd2ff5d6c84e60575c8b50a69619 \
+    --hash=sha256:49e70d111fee47284d9dd867c9bb9a7058a3c617274900780c43e38d90fe1205 \
+    --hash=sha256:4c75507d0a55378240f781599c30e7776674dbaf883a46d1c90f37e563453480 \
+    --hash=sha256:4c863140fafc615c14a4bf4efd0f4425c02230eb8ef02784c9a156461e62c965 \
+    --hash=sha256:4d8908b3bee1c889e547867ca4cdc54e5ab6be6d3e078556814a22457f49423c \
+    --hash=sha256:5b9eb0ca724a241683c9685a484da9d35c872fd42756574a7cfbf58af26677fd \
+    --hash=sha256:6022cecf8f44e36af10bd9118ca71f371078b4c168b6e0fab43d4a889985dbb5 \
+    --hash=sha256:6150ffa5c767bc6332df27157d95442c379b7dce3a38dff89c0f39b63275696f \
+    --hash=sha256:62828cada4a2b850dbef89c81f5a33741898b305db244904de418cc957ff05dc \
+    --hash=sha256:7b4182299f251060996af5249c286bae9361fa8c6a9cda5efc29fe8bfd6062ec \
+    --hash=sha256:94b34f32646ca0414237168d68a9157cb3889f06b096612afdd296003fdd32fd \
+    --hash=sha256:9ce6889abac9a42afd07a562c2d6d4b2b7134f83f18571d859b25624a331c90b \
+    --hash=sha256:9cffe0f850e89d7c0012a1fb8730f75edd4320a0a731ed0c183904fe6ecfc3a9 \
+    --hash=sha256:a12a813949e5066148712a0626895c26b2578874e4cc63160bb007e6df3436fe \
+    --hash=sha256:a1eea9aecf761c661d096d39ed9026574de8adb2ae1c5bd7b33558af884fb2ce \
+    --hash=sha256:a31f94983fecbac95e58388210427d68cd30fe8a36927980fab9c20062645609 \
+    --hash=sha256:ac58bdee53cbeba2ecad824fa8159493f0bf3b8ea4e93feb06c9a465d6c87da8 \
+    --hash=sha256:af3f4485884750dddd9c25cb7e3915d83c2db92488b38ccb77dd594eac84c4a0 \
+    --hash=sha256:b33d2bc4f69caedcd0a275329eb2198f560b325605810895627be5d4b876bf7f \
+    --hash=sha256:b59c0ffceff8d4d3996a45f2bb6f4c207f94684a96bf3d9728dbb77428dd8cb8 \
+    --hash=sha256:bb6834cbd983b19f06908b45bfc2dad6ac9479ae04abe923a275b5f48f1a186b \
+    --hash=sha256:bd3db01f59fdcbce5b22afad19e390260d6d0222f35a1023d9adc5690a889364 \
+    --hash=sha256:bd7c23df857d488f418439686d3b10ae2fbf9bc256cd045b37a8c16575ea1040 \
+    --hash=sha256:c2528d60e398c7c4c799d56f907664673a807635b857df18f7ae64d3e6ce2d9f \
+    --hash=sha256:d31a63bc6e6d87f77d71e1abbd7387ab817a66733734883d1fc0021ed9bfa083 \
+    --hash=sha256:d4492d82b3bc7fbb7e3610747b159869468079fe149ec5c4d771fa1f614a14df \
+    --hash=sha256:ddcb8581510311e13421b1f544403c16e901c4e8f09083c881fab2be80ee31ba \
+    --hash=sha256:e1d59258c3c67c865435d8fbeb35f8c59b8bef3d6f46c1f29f6123556af28445 \
+    --hash=sha256:eb3315a8a236ee19b6df481fc5f997436e8ade24a9f03dfdc6bd490fea20c6da \
+    --hash=sha256:ef2b055471c0eb466033760a521efb9d8a32b99ab907fc8358481a1dd29e3bd3 \
+    --hash=sha256:ef5adb9a3b1d0c645ff694f9bca7702ec2c70f4d734f9922ea34de02294fdf72 \
+    --hash=sha256:f32c38afb74bd98ce26de7cc74a67b40afb7b05aae7b42924ea990d51e4dac02 \
+    --hash=sha256:fe0ccca550bb8e5abc22f530ec0466136379c01321fd94f30a22231e8a48d985
+cycler==0.12.1 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:85cef7cff222d8644161529808465972e51340599459b8ac3ccbac5a854e0d30 \
+    --hash=sha256:88bb128f02ba341da8ef447245a9e138fae777f6a23943da4540077d3601eb1c
+debugpy==1.8.1 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:016a9fcfc2c6b57f939673c874310d8581d51a0fe0858e7fac4e240c5eb743cb \
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+    --hash=sha256:7236d1e080e4936be2dc3e326cec0af72acf9212a7e1d060210e70a47e253523 \
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+    --hash=sha256:f6c21c00478a7bea93caaaef9e7629145d4153b15a8653e8bb4609d4bc70dbfc
+ruff==0.4.4 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:1aecced1269481ef2894cc495647392a34b0bf3e28ff53ed95a385b13aa45768 \
+    --hash=sha256:29d44ef5bb6a08e235c8249294fa8d431adc1426bfda99ed493119e6f9ea1bf6 \
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+    --hash=sha256:60ed88b636a463214905c002fa3eaab19795679ed55529f91e488db3fe8976ab \
+    --hash=sha256:8e7e6ebc10ef16dcdc77fd5557ee60647512b400e4a60bdc4849468f076f6eef \
+    --hash=sha256:958b4ea5589706a81065e2a776237de2ecc3e763342e5cc8e02a4a4d8a5e6f95 \
+    --hash=sha256:9da73eb616b3241a307b837f32756dc20a0b07e2bcb694fec73699c93d04a69e \
+    --hash=sha256:b1867ee9bf3acc21778dcb293db504692eda5f7a11a6e6cc40890182a9f9e595 \
+    --hash=sha256:b5eb0a4bfd6400b7d07c09a7725e1a98c3b838be557fee229ac0f84d9aa49c36 \
+    --hash=sha256:b90fc5e170fc71c712cc4d9ab0e24ea505c6a9e4ebf346787a67e691dfb72e85 \
+    --hash=sha256:b9ddb2c494fb79fc208cd15ffe08f32b7682519e067413dbaf5f4b01a6087bcd \
+    --hash=sha256:c4efe62b5bbb24178c950732ddd40712b878a9b96b1d02b0ff0b08a090cbd891 \
+    --hash=sha256:c51c928a14f9f0a871082603e25a1588059b7e08a920f2f9fa7157b5bf08cfe9 \
+    --hash=sha256:cb53473849f011bca6e754f2cdf47cafc9c4f4ff4570003a0dad0b9b6890e876 \
+    --hash=sha256:f87ea42d5cdebdc6a69761a9d0bc83ae9b3b30d0ad78952005ba6568d6c022af
+setuptools==69.5.1 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:6c1fccdac05a97e598fb0ae3bbed5904ccb317337a51139dcd51453611bbb987 \
+    --hash=sha256:c636ac361bc47580504644275c9ad802c50415c7522212252c033bd15f301f32
+six==1.16.0 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926 \
+    --hash=sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254
+stack-data==0.6.3 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:836a778de4fec4dcd1dcd89ed8abff8a221f58308462e1c4aa2a3cf30148f0b9 \
+    --hash=sha256:d5558e0c25a4cb0853cddad3d77da9891a08cb85dd9f9f91b9f8cd66e511e695
+tornado==6.4 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:02ccefc7d8211e5a7f9e8bc3f9e5b0ad6262ba2fbb683a6443ecc804e5224ce0 \
+    --hash=sha256:10aeaa8006333433da48dec9fe417877f8bcc21f48dda8d661ae79da357b2a63 \
+    --hash=sha256:27787de946a9cffd63ce5814c33f734c627a87072ec7eed71f7fc4417bb16263 \
+    --hash=sha256:6f8a6c77900f5ae93d8b4ae1196472d0ccc2775cc1dfdc9e7727889145c45052 \
+    --hash=sha256:71ddfc23a0e03ef2df1c1397d859868d158c8276a0603b96cf86892bff58149f \
+    --hash=sha256:72291fa6e6bc84e626589f1c29d90a5a6d593ef5ae68052ee2ef000dfd273dee \
+    --hash=sha256:88b84956273fbd73420e6d4b8d5ccbe913c65d31351b4c004ae362eba06e1f78 \
+    --hash=sha256:e43bc2e5370a6a8e413e1e1cd0c91bedc5bd62a74a532371042a18ef19e10579 \
+    --hash=sha256:f0251554cdd50b4b44362f73ad5ba7126fc5b2c2895cc62b14a1c2d7ea32f212 \
+    --hash=sha256:f7894c581ecdcf91666a0912f18ce5e757213999e183ebfc2c3fdbf4d5bd764e \
+    --hash=sha256:fd03192e287fbd0899dd8f81c6fb9cbbc69194d2074b38f384cb6fa72b80e9c2
+traitlets==5.14.3 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:9ed0579d3502c94b4b3732ac120375cda96f923114522847de4b3bb98b96b6b7 \
+    --hash=sha256:b74e89e397b1ed28cc831db7aea759ba6640cb3de13090ca145426688ff1ac4f
+virtualenv==20.26.2 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:82bf0f4eebbb78d36ddaee0283d43fe5736b53880b8a8cdcd37390a07ac3741c \
+    --hash=sha256:a624db5e94f01ad993d476b9ee5346fdf7b9de43ccaee0e0197012dc838a0e9b
+wcwidth==0.2.13 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859 \
+    --hash=sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5
+widgetsnbextension==4.0.10 ; python_version >= "3.12" and python_version < "4.0" \
+    --hash=sha256:64196c5ff3b9a9183a8e699a4227fb0b7002f252c814098e66c4d1cd0644688f \
+    --hash=sha256:d37c3724ec32d8c48400a435ecfa7d3e259995201fbefa37163124a9fcb393cc