diff --git a/poetry.lock b/poetry.lock
index 2afab51..b6b7502 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -4,7 +4,7 @@
 name = "adagio"
 version = "0.2.4"
 description = "The Dag IO Framework for Fugue projects"
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
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@@ -14,143 +14,22 @@ files = [
 [package.dependencies]
 triad = ">=0.6.1"
 
-[[package]]
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-version = "3.9.5"
-description = "Async http client/server framework (asyncio)"
-optional = true
-python-versions = ">=3.8"
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-]
-
-[package.dependencies]
-aiosignal = ">=1.1.2"
-async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
-attrs = ">=17.3.0"
-frozenlist = ">=1.1.1"
-multidict = ">=4.5,<7.0"
-yarl = ">=1.0,<2.0"
-
-[package.extras]
-speedups = ["Brotli", "aiodns", "brotlicffi"]
-
-[[package]]
-name = "aiosignal"
-version = "1.3.1"
-description = "aiosignal: a list of registered asynchronous callbacks"
-optional = true
-python-versions = ">=3.7"
-files = [
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-]
-
-[package.dependencies]
-frozenlist = ">=1.1.0"
-
 [[package]]
 name = "annotated-types"
-version = "0.6.0"
+version = "0.7.0"
 description = "Reusable constraint types to use with typing.Annotated"
 optional = false
 python-versions = ">=3.8"
 files = [
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-
-[[package]]
-name = "antlr4-python3-runtime"
-version = "4.11.1"
-description = "ANTLR 4.11.1 runtime for Python 3"
-optional = true
-python-versions = "*"
-files = [
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 ]
 
 [[package]]
 name = "appdirs"
 version = "1.4.4"
 description = "A small Python module for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "appdirs-1.4.4-py2.py3-none-any.whl", hash = "sha256:a841dacd6b99318a741b166adb07e19ee71a274450e68237b4650ca1055ab128"},
@@ -219,17 +98,6 @@ six = ">=1.12.0"
 astroid = ["astroid (>=1,<2)", "astroid (>=2,<4)"]
 test = ["astroid (>=1,<2)", "astroid (>=2,<4)", "pytest"]
 
-[[package]]
-name = "async-timeout"
-version = "4.0.3"
-description = "Timeout context manager for asyncio programs"
-optional = true
-python-versions = ">=3.7"
-files = [
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-
 [[package]]
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 version = "23.2.0"
@@ -251,13 +119,13 @@ tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "p
 
 [[package]]
 name = "authlib"
-version = "1.3.0"
+version = "1.3.1"
 description = "The ultimate Python library in building OAuth and OpenID Connect servers and clients."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -318,13 +186,13 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
 
 [[package]]
 name = "certifi"
-version = "2024.2.2"
+version = "2024.6.2"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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 ]
 
 [[package]]
@@ -530,7 +398,7 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 name = "cloudpickle"
 version = "3.0.0"
 description = "Pickler class to extend the standard pickle.Pickler functionality"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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@@ -567,13 +435,13 @@ test = ["pytest"]
 
 [[package]]
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-version = "3.24.0"
+version = "3.27.0"
 description = "Python commitizen client tool"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -675,16 +543,16 @@ rich = "*"
 
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-version = "0.0.8"
+version = "0.0.9"
 description = "Fast implementations of common forecasting routines"
-optional = true
+optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
@@ -692,63 +560,63 @@ numpy = ">=1.20.0"
 
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+version = "7.5.3"
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 [package.dependencies]
@@ -779,43 +647,43 @@ pyproject = ["toml (>=0.10)"]
 
 [[package]]
 name = "cryptography"
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 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = ">=3.7"
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 [package.dependencies]
@@ -850,7 +718,7 @@ tests = ["pytest", "pytest-cov", "pytest-xdist"]
 name = "cython"
 version = "3.0.10"
 description = "The Cython compiler for writing C extensions in the Python language."
-optional = true
+optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
 files = [
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-
 [[package]]
 name = "debugpy"
 version = "1.8.1"
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 description = "Minimal, easy-to-use, declarative cli tool"
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 [[package]]
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 [[package]]
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-    {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:55fdc093b5a3cb41d420884cdaf37a1e74c3c37a31f46e66286d9145d2063bd0"},
-    {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:82e8211d69a4f4bc360ea22cd6555f8e61a1bd211d1d5d39d3d228b48c83a897"},
-    {file = "frozenlist-1.4.1-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:89aa2c2eeb20957be2d950b85974b30a01a762f3308cd02bb15e1ad632e22dc7"},
-    {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:9d3e0c25a2350080e9319724dede4f31f43a6c9779be48021a7f4ebde8b2d742"},
-    {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:7268252af60904bf52c26173cbadc3a071cece75f873705419c8681f24d3edea"},
-    {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:0c250a29735d4f15321007fb02865f0e6b6a41a6b88f1f523ca1596ab5f50bd5"},
-    {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:96ec70beabbd3b10e8bfe52616a13561e58fe84c0101dd031dc78f250d5128b9"},
-    {file = "frozenlist-1.4.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:23b2d7679b73fe0e5a4560b672a39f98dfc6f60df63823b0a9970525325b95f6"},
-    {file = "frozenlist-1.4.1-cp39-cp39-win32.whl", hash = "sha256:a7496bfe1da7fb1a4e1cc23bb67c58fab69311cc7d32b5a99c2007b4b2a0e932"},
-    {file = "frozenlist-1.4.1-cp39-cp39-win_amd64.whl", hash = "sha256:e6a20a581f9ce92d389a8c7d7c3dd47c81fd5d6e655c8dddf341e14aa48659d0"},
-    {file = "frozenlist-1.4.1-py3-none-any.whl", hash = "sha256:04ced3e6a46b4cfffe20f9ae482818e34eba9b5fb0ce4056e4cc9b6e212d09b7"},
-    {file = "frozenlist-1.4.1.tar.gz", hash = "sha256:c037a86e8513059a2613aaba4d817bb90b9d9b6b69aace3ce9c877e8c8ed402b"},
-]
-
 [[package]]
 name = "fs"
 version = "2.4.16"
 description = "Python's filesystem abstraction layer"
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "fs-2.4.16-py2.py3-none-any.whl", hash = "sha256:660064febbccda264ae0b6bace80a8d1be9e089e0a5eb2427b7d517f9a91545c"},
@@ -1288,24 +1035,22 @@ scandir = ["scandir (>=1.5,<2.0)"]
 
 [[package]]
 name = "fsspec"
-version = "2024.3.1"
+version = "2024.6.0"
 description = "File-system specification"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fsspec-2024.3.1-py3-none-any.whl", hash = "sha256:918d18d41bf73f0e2b261824baeb1b124bcf771767e3a26425cd7dec3332f512"},
-    {file = "fsspec-2024.3.1.tar.gz", hash = "sha256:f39780e282d7d117ffb42bb96992f8a90795e4d0fb0f661a70ca39fe9c43ded9"},
+    {file = "fsspec-2024.6.0-py3-none-any.whl", hash = "sha256:58d7122eb8a1a46f7f13453187bfea4972d66bf01618d37366521b1998034cee"},
+    {file = "fsspec-2024.6.0.tar.gz", hash = "sha256:f579960a56e6d8038a9efc8f9c77279ec12e6299aa86b0769a7e9c46b94527c2"},
 ]
 
-[package.dependencies]
-aiohttp = {version = "<4.0.0a0 || >4.0.0a0,<4.0.0a1 || >4.0.0a1", optional = true, markers = "extra == \"http\""}
-
 [package.extras]
 abfs = ["adlfs"]
 adl = ["adlfs"]
 arrow = ["pyarrow (>=1)"]
 dask = ["dask", "distributed"]
-devel = ["pytest", "pytest-cov"]
+dev = ["pre-commit", "ruff"]
+doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
 dropbox = ["dropbox", "dropboxdrivefs", "requests"]
 full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
 fuse = ["fusepy"]
@@ -1322,58 +1067,37 @@ s3 = ["s3fs"]
 sftp = ["paramiko"]
 smb = ["smbprotocol"]
 ssh = ["paramiko"]
+test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
+test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
+test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
 tqdm = ["tqdm"]
 
 [[package]]
 name = "fugue"
-version = "0.8.7"
+version = "0.9.0"
 description = "An abstraction layer for distributed computation"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "fugue-0.8.7-py3-none-any.whl", hash = "sha256:d4dc16bac9850024109b999cd163a6ca4976bd0bf190a85730d91ff74737c3f2"},
-    {file = "fugue-0.8.7.tar.gz", hash = "sha256:4c56946de46083778cdd6ec5b91ac5d37a847164c80790771edc6832bb9a260d"},
+    {file = "fugue-0.9.0-py3-none-any.whl", hash = "sha256:939442c60c6ab5d97bddc672bff4f71b3e45b7b956cad1f0e5a51f71a9fc6783"},
+    {file = "fugue-0.9.0.tar.gz", hash = "sha256:fcc50110e0854a6c0f1da81bb4924029bab344cf7c4ad5d461557dc975cc465b"},
 ]
 
 [package.dependencies]
 adagio = ">=0.2.4"
-fugue-sql-antlr = ">=0.1.6"
-jinja2 = "*"
-qpd = ">=0.4.4"
-sqlglot = "*"
-triad = ">=0.9.3"
+triad = ">=0.9.6"
 
 [package.extras]
-all = ["dask-sql", "dask[dataframe,distributed] (>=2023.5.0)", "duckdb (>=0.5.0)", "fugue-sql-antlr[cpp] (>=0.1.6)", "ibis-framework (>=3.2.0,<6)", "ipython (>=7.10.0)", "jinja2", "jupyterlab", "notebook", "pandas (>=2.0.2)", "polars", "pyarrow (>=6.0.1)", "pyspark (>=3.1.1)", "ray[data] (>=2.4.0)", "sqlglot"]
-cpp-sql-parser = ["fugue-sql-antlr[cpp] (>=0.1.6)"]
-dask = ["dask[dataframe,distributed] (>=2023.5.0)", "pandas (>=2.0.2)", "pyarrow (>=7.0.0)"]
-duckdb = ["duckdb (>=0.5.0)", "numpy"]
-ibis = ["ibis-framework (>=3.2.0,<6)"]
+all = ["dask-sql", "dask[dataframe,distributed] (>=2023.5.0)", "duckdb (>=0.5.0)", "fugue-sql-antlr (>=0.2.0)", "ibis-framework", "ipython (>=7.10.0)", "jinja2", "jupyterlab", "notebook", "pandas (>=2.0.2,<2.2)", "polars", "pyarrow (>=6.0.1)", "pyspark (>=3.1.1)", "qpd (>=0.4.4)", "ray[data] (>=2.5.0)", "sqlglot"]
+cpp-sql-parser = ["fugue-sql-antlr[cpp] (>=0.2.0)"]
+dask = ["dask[dataframe,distributed] (>=2023.5.0)", "dask[dataframe,distributed] (>=2024.4.0)", "pandas (>=2.0.2)", "pyarrow (>=7.0.0)"]
+duckdb = ["duckdb (>=0.5.0)", "fugue-sql-antlr (>=0.2.0)", "jinja2", "numpy", "qpd (>=0.4.4)", "sqlglot"]
+ibis = ["fugue-sql-antlr (>=0.2.0)", "ibis-framework", "jinja2", "pandas (<2.2)", "qpd (>=0.4.4)", "sqlglot"]
 notebook = ["ipython (>=7.10.0)", "jupyterlab", "notebook"]
 polars = ["polars"]
-ray = ["duckdb (>=0.5.0)", "pyarrow (>=6.0.1)", "ray[data] (>=2.4.0)"]
+ray = ["duckdb (>=0.5.0)", "pandas (<2.2)", "pyarrow (>=7.0.0)", "ray[data] (>=2.5.0)"]
 spark = ["pyspark (>=3.1.1)"]
-sql = ["fugue-sql-antlr (>=0.1.6)", "jinja2", "qpd (>=0.4.4)", "sqlglot"]
-
-[[package]]
-name = "fugue-sql-antlr"
-version = "0.2.0"
-description = "Fugue SQL Antlr Parser"
-optional = true
-python-versions = ">=3.8"
-files = [
-    {file = "fugue-sql-antlr-0.2.0.tar.gz", hash = "sha256:e15433aaf09502c5b0423019d9fa93e161172ceb08e7bd27af0175dadf3cf552"},
-]
-
-[package.dependencies]
-antlr4-python3-runtime = "<4.12"
-jinja2 = "*"
-packaging = "*"
-triad = ">=0.6.8"
-
-[package.extras]
-cpp = ["fugue-sql-antlr-cpp (==0.2.0)"]
-test = ["speedy_antlr_tool"]
+sql = ["fugue-sql-antlr (>=0.2.0)", "jinja2", "qpd (>=0.4.4)", "sqlglot"]
 
 [[package]]
 name = "gitdb"
@@ -1409,13 +1133,13 @@ test = ["coverage[toml]", "ddt (>=1.1.1,!=1.4.3)", "mock", "mypy", "pre-commit",
 
 [[package]]
 name = "holidays"
-version = "0.47"
+version = "0.50"
 description = "Generate and work with holidays in Python"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "holidays-0.47-py3-none-any.whl", hash = "sha256:b1a3487a6b0e711c7085e75720e293e5bd05004077d85f1d68f4521b3ae009a7"},
-    {file = "holidays-0.47.tar.gz", hash = "sha256:8ca475d2f18b78abc453ccda5949346da10a3a15b82ef429821edc702e752bbc"},
+    {file = "holidays-0.50-py3-none-any.whl", hash = "sha256:7f17ce3a29bc77194ab90eaa320a8cc71823f6beb8a034c0d892cc20114278c3"},
+    {file = "holidays-0.50.tar.gz", hash = "sha256:f9b7de6c98bafefc5d19087dbb721926b31670133704f414032c22b309648e8a"},
 ]
 
 [package.dependencies]
@@ -1547,21 +1271,21 @@ test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pa
 
 [[package]]
 name = "ipywidgets"
-version = "8.1.2"
+version = "8.1.3"
 description = "Jupyter interactive widgets"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "ipywidgets-8.1.2-py3-none-any.whl", hash = "sha256:bbe43850d79fb5e906b14801d6c01402857996864d1e5b6fa62dd2ee35559f60"},
-    {file = "ipywidgets-8.1.2.tar.gz", hash = "sha256:d0b9b41e49bae926a866e613a39b0f0097745d2b9f1f3dd406641b4a57ec42c9"},
+    {file = "ipywidgets-8.1.3-py3-none-any.whl", hash = "sha256:efafd18f7a142248f7cb0ba890a68b96abd4d6e88ddbda483c9130d12667eaf2"},
+    {file = "ipywidgets-8.1.3.tar.gz", hash = "sha256:f5f9eeaae082b1823ce9eac2575272952f40d748893972956dc09700a6392d9c"},
 ]
 
 [package.dependencies]
 comm = ">=0.1.3"
 ipython = ">=6.1.0"
-jupyterlab-widgets = ">=3.0.10,<3.1.0"
+jupyterlab-widgets = ">=3.0.11,<3.1.0"
 traitlets = ">=4.3.1"
-widgetsnbextension = ">=4.0.10,<4.1.0"
+widgetsnbextension = ">=4.0.11,<4.1.0"
 
 [package.extras]
 test = ["ipykernel", "jsonschema", "pytest (>=3.6.0)", "pytest-cov", "pytz"]
@@ -1587,13 +1311,13 @@ testing = ["Django", "attrs", "colorama", "docopt", "pytest (<7.0.0)"]
 
 [[package]]
 name = "jinja2"
-version = "3.1.3"
+version = "3.1.4"
 description = "A very fast and expressive template engine."
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "Jinja2-3.1.3-py3-none-any.whl", hash = "sha256:7d6d50dd97d52cbc355597bd845fabfbac3f551e1f99619e39a35ce8c370b5fa"},
-    {file = "Jinja2-3.1.3.tar.gz", hash = "sha256:ac8bd6544d4bb2c9792bf3a159e80bba8fda7f07e81bc3aed565432d5925ba90"},
+    {file = "jinja2-3.1.4-py3-none-any.whl", hash = "sha256:bc5dd2abb727a5319567b7a813e6a2e7318c39f4f487cfe6c89c6f9c7d25197d"},
+    {file = "jinja2-3.1.4.tar.gz", hash = "sha256:4a3aee7acbbe7303aede8e9648d13b8bf88a429282aa6122a993f0ac800cb369"},
 ]
 
 [package.dependencies]
@@ -1604,24 +1328,24 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "joblib"
-version = "1.4.0"
+version = "1.4.2"
 description = "Lightweight pipelining with Python functions"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "joblib-1.4.0-py3-none-any.whl", hash = "sha256:42942470d4062537be4d54c83511186da1fc14ba354961a2114da91efa9a4ed7"},
-    {file = "joblib-1.4.0.tar.gz", hash = "sha256:1eb0dc091919cd384490de890cb5dfd538410a6d4b3b54eef09fb8c50b409b1c"},
+    {file = "joblib-1.4.2-py3-none-any.whl", hash = "sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6"},
+    {file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"},
 ]
 
 [[package]]
 name = "jsonschema"
-version = "4.21.1"
+version = "4.22.0"
 description = "An implementation of JSON Schema validation for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jsonschema-4.21.1-py3-none-any.whl", hash = "sha256:7996507afae316306f9e2290407761157c6f78002dcf7419acb99822143d1c6f"},
-    {file = "jsonschema-4.21.1.tar.gz", hash = "sha256:85727c00279f5fa6bedbe6238d2aa6403bedd8b4864ab11207d07df3cc1b2ee5"},
+    {file = "jsonschema-4.22.0-py3-none-any.whl", hash = "sha256:ff4cfd6b1367a40e7bc6411caec72effadd3db0bbe5017de188f2d6108335802"},
+    {file = "jsonschema-4.22.0.tar.gz", hash = "sha256:5b22d434a45935119af990552c862e5d6d564e8f6601206b305a61fdf661a2b7"},
 ]
 
 [package.dependencies]
@@ -1650,13 +1374,13 @@ referencing = ">=0.31.0"
 
 [[package]]
 name = "jupyter-client"
-version = "8.6.1"
+version = "8.6.2"
 description = "Jupyter protocol implementation and client libraries"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_client-8.6.1-py3-none-any.whl", hash = "sha256:3b7bd22f058434e3b9a7ea4b1500ed47de2713872288c0d511d19926f99b459f"},
-    {file = "jupyter_client-8.6.1.tar.gz", hash = "sha256:e842515e2bab8e19186d89fdfea7abd15e39dd581f94e399f00e2af5a1652d3f"},
+    {file = "jupyter_client-8.6.2-py3-none-any.whl", hash = "sha256:50cbc5c66fd1b8f65ecb66bc490ab73217993632809b6e505687de18e9dea39f"},
+    {file = "jupyter_client-8.6.2.tar.gz", hash = "sha256:2bda14d55ee5ba58552a8c53ae43d215ad9868853489213f37da060ced54d8df"},
 ]
 
 [package.dependencies]
@@ -1668,7 +1392,7 @@ traitlets = ">=5.3"
 
 [package.extras]
 docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
-test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
+test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest (<8.2.0)", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
 
 [[package]]
 name = "jupyter-core"
@@ -1703,13 +1427,13 @@ files = [
 
 [[package]]
 name = "jupyterlab-widgets"
-version = "3.0.10"
+version = "3.0.11"
 description = "Jupyter interactive widgets for JupyterLab"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "jupyterlab_widgets-3.0.10-py3-none-any.whl", hash = "sha256:dd61f3ae7a5a7f80299e14585ce6cf3d6925a96c9103c978eda293197730cb64"},
-    {file = "jupyterlab_widgets-3.0.10.tar.gz", hash = "sha256:04f2ac04976727e4f9d0fa91cdc2f1ab860f965e504c29dbd6a65c882c9d04c0"},
+    {file = "jupyterlab_widgets-3.0.11-py3-none-any.whl", hash = "sha256:78287fd86d20744ace330a61625024cf5521e1c012a352ddc0a3cdc2348becd0"},
+    {file = "jupyterlab_widgets-3.0.11.tar.gz", hash = "sha256:dd5ac679593c969af29c9bed054c24f26842baa51352114736756bc035deee27"},
 ]
 
 [[package]]
@@ -1849,32 +1573,11 @@ dask = ["dask[array,dataframe,distributed] (>=2.0.0)", "pandas (>=0.24.0)"]
 pandas = ["pandas (>=0.24.0)"]
 scikit-learn = ["scikit-learn (!=0.22.0)"]
 
-[[package]]
-name = "lightning-utilities"
-version = "0.11.2"
-description = "Lightning toolbox for across the our ecosystem."
-optional = true
-python-versions = ">=3.8"
-files = [
-    {file = "lightning-utilities-0.11.2.tar.gz", hash = "sha256:adf4cf9c5d912fe505db4729e51d1369c6927f3a8ac55a9dff895ce5c0da08d9"},
-    {file = "lightning_utilities-0.11.2-py3-none-any.whl", hash = "sha256:541f471ed94e18a28d72879338c8c52e873bb46f4c47644d89228faeb6751159"},
-]
-
-[package.dependencies]
-packaging = ">=17.1"
-setuptools = "*"
-typing-extensions = "*"
-
-[package.extras]
-cli = ["fire"]
-docs = ["requests (>=2.0.0)"]
-typing = ["mypy (>=1.0.0)", "types-setuptools"]
-
 [[package]]
 name = "llvmlite"
 version = "0.42.0"
 description = "lightweight wrapper around basic LLVM functionality"
-optional = true
+optional = false
 python-versions = ">=3.9"
 files = [
     {file = "llvmlite-0.42.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3366938e1bf63d26c34fbfb4c8e8d2ded57d11e0567d5bb243d89aab1eb56098"},
@@ -1995,13 +1698,13 @@ files = [
 
 [[package]]
 name = "marshmallow"
-version = "3.21.1"
+version = "3.21.3"
 description = "A lightweight library for converting complex datatypes to and from native Python datatypes."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "marshmallow-3.21.1-py3-none-any.whl", hash = "sha256:f085493f79efb0644f270a9bf2892843142d80d7174bbbd2f3713f2a589dc633"},
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 [package.dependencies]
@@ -2009,44 +1712,45 @@ packaging = ">=17.0"
 
 [package.extras]
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 tests = ["pytest", "pytz", "simplejson"]
 
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 name = "matplotlib"
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 ]
 
 [package.dependencies]
@@ -2054,12 +1758,15 @@ contourpy = ">=1.0.1"
 cycler = ">=0.10"
 fonttools = ">=4.22.0"
 kiwisolver = ">=1.3.1"
-numpy = ">=1.21"
+numpy = ">=1.23"
 packaging = ">=20.0"
 pillow = ">=8"
 pyparsing = ">=2.3.1"
 python-dateutil = ">=2.7"
 
+[package.extras]
+dev = ["meson-python (>=0.13.1)", "numpy (>=1.25)", "pybind11 (>=2.6)", "setuptools (>=64)", "setuptools_scm (>=7)"]
+
 [[package]]
 name = "matplotlib-inline"
 version = "0.1.7"
@@ -2096,156 +1803,40 @@ files = [
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 ]
 
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-python-versions = "*"
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-docs = ["sphinx"]
-gmpy = ["gmpy2 (>=2.1.0a4)"]
-tests = ["pytest (>=4.6)"]
-
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 ]
 
 [package.dependencies]
@@ -2294,13 +1885,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
-version = "7.16.3"
+version = "7.16.4"
 description = "Converting Jupyter Notebooks (.ipynb files) to other formats.  Output formats include asciidoc, html, latex, markdown, pdf, py, rst, script.  nbconvert can be used both as a Python library (`import nbconvert`) or as a command line tool (invoked as `jupyter nbconvert ...`)."
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 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -2321,9 +1912,9 @@ tinycss2 = "*"
 traitlets = ">=5.1"
 
 [package.extras]
-all = ["nbconvert[docs,qtpdf,serve,test,webpdf]"]
+all = ["flaky", "ipykernel", "ipython", "ipywidgets (>=7.5)", "myst-parser", "nbsphinx (>=0.2.12)", "playwright", "pydata-sphinx-theme", "pyqtwebengine (>=5.15)", "pytest (>=7)", "sphinx (==5.0.2)", "sphinxcontrib-spelling", "tornado (>=6.1)"]
 docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sphinx-theme", "sphinx (==5.0.2)", "sphinxcontrib-spelling"]
-qtpdf = ["nbconvert[qtpng]"]
+qtpdf = ["pyqtwebengine (>=5.15)"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
 test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest (>=7)"]
@@ -2361,29 +1952,11 @@ files = [
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 ]
 
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-
 [[package]]
 name = "nfoursid"
 version = "1.0.1"
 description = "Implementation of N4SID, Kalman filtering and state-space models"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
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@@ -2397,23 +1970,20 @@ pandas = ">=1.1"
 
 [[package]]
 name = "nodeenv"
-version = "1.8.0"
+version = "1.9.1"
 description = "Node.js virtual environment builder"
 optional = false
-python-versions = ">=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*"
+python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7"
 files = [
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 ]
 
-[package.dependencies]
-setuptools = "*"
-
 [[package]]
 name = "numba"
 version = "0.59.1"
 description = "compiling Python code using LLVM"
-optional = true
+optional = false
 python-versions = ">=3.9"
 files = [
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@@ -2488,156 +2058,15 @@ files = [
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 ]
 
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-[[package]]
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-[[package]]
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-[package.dependencies]
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-
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-
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 [[package]]
 name = "packaging"
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+version = "24.1"
 description = "Core utilities for Python packages"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -2648,6 +2077,7 @@ optional = false
 python-versions = ">=3.9"
 files = [
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     {file = "pandas-2.2.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8635c16bf3d99040fdf3ca3db669a7250ddf49c55dc4aa8fe0ae0fa8d6dcc1f0"},
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@@ -2668,6 +2098,7 @@ files = [
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@@ -2752,7 +2183,7 @@ files = [
 name = "patsy"
 version = "0.5.6"
 description = "A Python package for describing statistical models and for building design matrices."
-optional = true
+optional = false
 python-versions = "*"
 files = [
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@@ -2768,13 +2199,13 @@ test = ["pytest", "pytest-cov", "scipy"]
 
 [[package]]
 name = "pdoc"
-version = "14.4.0"
+version = "14.5.0"
 description = "API Documentation for Python Projects"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "pdoc-14.5.0-py3-none-any.whl", hash = "sha256:9a8a84e19662610c0620fbe9f2e4174e3b090f8b601ed46348786ebb7517c508"},
+    {file = "pdoc-14.5.0.tar.gz", hash = "sha256:79f534dc8a6494638dd6056b78e17a654df7ed34cc92646553ce3a7ba5a4fa4a"},
 ]
 
 [package.dependencies]
@@ -2887,18 +2318,19 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "platformdirs"
-version = "4.2.0"
-description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
+version = "4.2.2"
+description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.8"
 files = [
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 [package.extras]
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 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
+type = ["mypy (>=1.8)"]
 
 [[package]]
 name = "pluggy"
@@ -2919,7 +2351,7 @@ testing = ["pytest", "pytest-benchmark"]
 name = "pmdarima"
 version = "2.0.4"
 description = "Python's forecast::auto.arima equivalent"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
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@@ -2968,13 +2400,13 @@ urllib3 = "*"
 
 [[package]]
 name = "poethepoet"
-version = "0.25.1"
+version = "0.26.1"
 description = "A task runner that works well with poetry."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2986,13 +2418,13 @@ poetry-plugin = ["poetry (>=1.0,<2.0)"]
 
 [[package]]
 name = "pre-commit"
-version = "3.7.0"
+version = "3.7.1"
 description = "A framework for managing and maintaining multi-language pre-commit hooks."
 optional = false
 python-versions = ">=3.9"
 files = [
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+    {file = "pre_commit-3.7.1.tar.gz", hash = "sha256:8ca3ad567bc78a4972a3f1a477e94a79d4597e8140a6e0b651c5e33899c3654a"},
 ]
 
 [package.dependencies]
@@ -3016,26 +2448,6 @@ files = [
 [package.dependencies]
 wcwidth = "*"
 
-[[package]]
-name = "protobuf"
-version = "5.26.1"
-description = ""
-optional = true
-python-versions = ">=3.8"
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-]
-
 [[package]]
 name = "psutil"
 version = "5.9.8"
@@ -3091,47 +2503,47 @@ tests = ["pytest"]
 
 [[package]]
 name = "pyarrow"
-version = "16.0.0"
+version = "16.1.0"
 description = "Python library for Apache Arrow"
-optional = true
+optional = false
 python-versions = ">=3.8"
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@@ -3260,27 +2672,26 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pygments"
-version = "2.17.2"
+version = "2.18.0"
 description = "Pygments is a syntax highlighting package written in Python."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 [package.extras]
-plugins = ["importlib-metadata"]
 windows-terminal = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "pyod"
-version = "1.1.3"
+version = "2.0.0"
 description = "A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)"
-optional = true
+optional = false
 python-versions = "*"
 files = [
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 [package.dependencies]
@@ -3288,9 +2699,8 @@ joblib = "*"
 matplotlib = "*"
 numba = ">=0.51"
 numpy = ">=1.19"
-scikit_learn = ">=0.22.0"
+scikit-learn = ">=0.22.0"
 scipy = ">=1.5.1"
-six = "*"
 
 [[package]]
 name = "pyparsing"
@@ -3308,13 +2718,13 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
 name = "pytest"
-version = "8.1.1"
+version = "8.2.2"
 description = "pytest: simple powerful testing with Python"
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 python-versions = ">=3.8"
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 [package.dependencies]
@@ -3322,11 +2732,11 @@ colorama = {version = "*", markers = "sys_platform == \"win32\""}
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 iniconfig = "*"
 packaging = "*"
-pluggy = ">=1.4,<2.0"
+pluggy = ">=1.5,<2.0"
 tomli = {version = ">=1", markers = "python_version < \"3.11\""}
 
 [package.extras]
-testing = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
+dev = ["argcomplete", "attrs (>=19.2)", "hypothesis (>=3.56)", "mock", "pygments (>=2.7.2)", "requests", "setuptools", "xmlschema"]
 
 [[package]]
 name = "pytest-mock"
@@ -3347,18 +2757,18 @@ dev = ["pre-commit", "pytest-asyncio", "tox"]
 
 [[package]]
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+version = "3.6.1"
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 [package.dependencies]
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+execnet = ">=2.1"
+pytest = ">=7.0.0"
 
 [package.extras]
 psutil = ["psutil (>=3.0)"]
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 [package.extras]
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 [[package]]
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 version = "2024.1"
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 [package.dependencies]
 joblib = ">=1.2.0"
 numpy = ">=1.19.5"
 scipy = ">=1.6.0"
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+    {file = "shap-0.45.1.tar.gz", hash = "sha256:24e7d7e2c0d6b798701b83eacee063d64926426a150a0d261b4a135f60639f10"},
 ]
 
 [package.dependencies]
@@ -4114,14 +3474,14 @@ packaging = ">20.9"
 pandas = "*"
 scikit-learn = "*"
 scipy = "*"
-slicer = "0.0.7"
+slicer = "0.0.8"
 tqdm = ">=4.27.0"
 
 [package.extras]
 docs = ["ipython", "matplotlib", "myst-parser (==2.0.0)", "nbsphinx (==0.9.3)", "numpydoc", "requests", "sphinx (==7.2.6)", "sphinx-github-changelog (==1.2.1)", "sphinx-rtd-theme (==2.0.0)"]
 others = ["lime"]
 plots = ["ipython", "matplotlib"]
-test = ["catboost", "gpboost", "lightgbm", "ngboost", "opencv-python", "protobuf (==3.20.3)", "pyod", "pyspark", "pytest", "pytest-cov", "pytest-mpl", "sentencepiece", "tensorflow", "torch", "torch (==2.2.0)", "torchvision", "transformers", "xgboost"]
+test = ["catboost", "gpboost", "lightgbm", "ngboost", "opencv-python", "protobuf (==3.20.3)", "pyod", "pyspark", "pytest", "pytest-cov", "pytest-mpl", "sentencepiece", "tensorflow (<2.16)", "torch", "torch (==2.2.0)", "torchvision", "transformers", "xgboost"]
 test-core = ["pytest", "pytest-cov", "pytest-mpl"]
 test-notebooks = ["datasets", "jupyter", "keras", "nbconvert", "nbformat", "nlp", "transformers"]
 
@@ -4163,13 +3523,13 @@ files = [
 
 [[package]]
 name = "slicer"
-version = "0.0.7"
+version = "0.0.8"
 description = "A small package for big slicing."
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "slicer-0.0.7-py3-none-any.whl", hash = "sha256:0b94faa5251c0f23782c03f7b7eedda91d80144059645f452c4bc80fab875976"},
-    {file = "slicer-0.0.7.tar.gz", hash = "sha256:f5d5f7b45f98d155b9c0ba6554fa9770c6b26d5793a3e77a1030fb56910ebeec"},
+    {file = "slicer-0.0.8-py3-none-any.whl", hash = "sha256:6c206258543aecd010d497dc2eca9d2805860a0b3758673903456b7df7934dc3"},
+    {file = "slicer-0.0.8.tar.gz", hash = "sha256:2e7553af73f0c0c2d355f4afcc3ecf97c6f2156fcf4593955c3f56cf6c4d6eb7"},
 ]
 
 [[package]]
@@ -4194,21 +3554,6 @@ files = [
     {file = "soupsieve-2.5.tar.gz", hash = "sha256:5663d5a7b3bfaeee0bc4372e7fc48f9cff4940b3eec54a6451cc5299f1097690"},
 ]
 
-[[package]]
-name = "sqlglot"
-version = "23.11.2"
-description = "An easily customizable SQL parser and transpiler"
-optional = true
-python-versions = ">=3.7"
-files = [
-    {file = "sqlglot-23.11.2-py3-none-any.whl", hash = "sha256:816d045304c3bd2a3ac907953e3540a4aa8f3fb19c124bd56be0c3010ae3851f"},
-    {file = "sqlglot-23.11.2.tar.gz", hash = "sha256:abb31d2924f615f95e5ff2e597e3fd2cc909e8d259b75a1d9bce6c1750649a37"},
-]
-
-[package.extras]
-dev = ["duckdb (>=0.6)", "maturin (>=1.4,<2.0)", "mypy", "pandas", "pandas-stubs", "pdoc", "pre-commit", "pyspark", "python-dateutil", "ruff (==0.3.2)", "types-python-dateutil", "typing-extensions"]
-rs = ["sqlglotrs (==0.2.0)"]
-
 [[package]]
 name = "stack-data"
 version = "0.6.3"
@@ -4230,18 +3575,18 @@ tests = ["cython", "littleutils", "pygments", "pytest", "typeguard"]
 
 [[package]]
 name = "statsforecast"
-version = "1.7.4"
+version = "1.7.5"
 description = "Time series forecasting suite using statistical models"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "statsforecast-1.7.4-py3-none-any.whl", hash = "sha256:0863d371e87fdfaf0e157bfee5d242e9899365a50c558a30331ec0d965c0cc64"},
-    {file = "statsforecast-1.7.4.tar.gz", hash = "sha256:eaea757f0a8835bea5a710df02c3248c0bc0eff940ae8d83a46fc339abb52280"},
+    {file = "statsforecast-1.7.5-py3-none-any.whl", hash = "sha256:35512bb6ac3c9413f010d959d5baf08f431dfc065e9e19995b1d55a22649ba68"},
+    {file = "statsforecast-1.7.5.tar.gz", hash = "sha256:18ad1e68ea8096e9ae59ca39079b8c3c5f8977025a1c67bea67a695a37a077ca"},
 ]
 
 [package.dependencies]
 cloudpickle = "*"
-coreforecast = ">=0.0.7"
+coreforecast = ">=0.0.9"
 fugue = ">=0.8.1"
 numba = ">=0.55.0"
 numpy = ">=1.21.6"
@@ -4250,11 +3595,11 @@ scipy = ">=1.7.3"
 statsmodels = ">=0.13.2"
 threadpoolctl = "*"
 tqdm = "*"
-utilsforecast = ">=0.0.24"
+utilsforecast = ">=0.1.4"
 
 [package.extras]
 dask = ["fugue[dask] (>=0.8.1)"]
-dev = ["black", "datasetsforecast", "flake8", "fugue[dask] (>=0.8.1)", "fugue[ray] (>=0.8.1)", "fugue[spark] (>=0.8.1)", "mypy", "nbdev", "nbdev-plotly", "pandas[plot]", "plotly", "plotly-resampler", "pmdarima", "polars", "prophet", "protobuf (>=3.15.3,<4.0.0)", "pyarrow", "ray (<2.8)", "scikit-learn", "supersmoother"]
+dev = ["black", "datasetsforecast", "fugue[dask] (>=0.8.1)", "fugue[ray] (>=0.8.1)", "fugue[spark] (>=0.8.1)", "mypy", "nbdev", "nbdev-plotly", "pandas[plot]", "plotly", "plotly-resampler", "pmdarima", "polars", "pre-commit", "prophet", "protobuf (>=3.15.3,<4.0.0)", "pyarrow", "ray (<2.8)", "ruff", "scikit-learn", "setuptools (<70)", "supersmoother"]
 plotly = ["plotly", "plotly-resampler"]
 polars = ["polars"]
 ray = ["fugue[ray] (>=0.8.1)", "protobuf (>=3.15.3,<4.0.0)", "ray (<2.8)"]
@@ -4264,7 +3609,7 @@ spark = ["fugue[spark] (>=0.8.1)"]
 name = "statsmodels"
 version = "0.14.2"
 description = "Statistical computations and models for Python"
-optional = true
+optional = false
 python-versions = ">=3.9"
 files = [
     {file = "statsmodels-0.14.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:df5d6f95c46f0341da6c79ee7617e025bf2b371e190a8e60af1ae9cabbdb7a97"},
@@ -4305,20 +3650,6 @@ build = ["cython (>=0.29.33)"]
 develop = ["colorama", "cython (>=0.29.33)", "cython (>=3.0.10,<4)", "flake8", "isort", "joblib", "matplotlib (>=3)", "pytest (>=7.3.0,<8)", "pytest-cov", "pytest-randomly", "pytest-xdist", "pywinpty", "setuptools-scm[toml] (>=8.0,<9.0)"]
 docs = ["ipykernel", "jupyter-client", "matplotlib", "nbconvert", "nbformat", "numpydoc", "pandas-datareader", "sphinx"]
 
-[[package]]
-name = "sympy"
-version = "1.12"
-description = "Computer algebra system (CAS) in Python"
-optional = true
-python-versions = ">=3.8"
-files = [
-    {file = "sympy-1.12-py3-none-any.whl", hash = "sha256:c3588cd4295d0c0f603d0f2ae780587e64e2efeedb3521e46b9bb1d08d184fa5"},
-    {file = "sympy-1.12.tar.gz", hash = "sha256:ebf595c8dac3e0fdc4152c51878b498396ec7f30e7a914d6071e674d49420fb8"},
-]
-
-[package.dependencies]
-mpmath = ">=0.19"
-
 [[package]]
 name = "tabulate"
 version = "0.9.0"
@@ -4337,7 +3668,7 @@ widechars = ["wcwidth"]
 name = "tbats"
 version = "1.1.3"
 description = "BATS and TBATS for time series forecasting"
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "tbats-1.1.3-py3-none-any.whl", hash = "sha256:aff37f39115583028dacbd87227bc2ac65e696ea25543ddcd78e334e1fbe8e3a"},
@@ -4353,22 +3684,6 @@ scipy = "*"
 [package.extras]
 dev = ["pip-tools", "pytest", "rpy2"]
 
-[[package]]
-name = "tensorboardx"
-version = "2.6.2.2"
-description = "TensorBoardX lets you watch Tensors Flow without Tensorflow"
-optional = true
-python-versions = "*"
-files = [
-    {file = "tensorboardX-2.6.2.2-py2.py3-none-any.whl", hash = "sha256:160025acbf759ede23fd3526ae9d9bfbfd8b68eb16c38a010ebe326dc6395db8"},
-    {file = "tensorboardX-2.6.2.2.tar.gz", hash = "sha256:c6476d7cd0d529b0b72f4acadb1269f9ed8b22f441e87a84f2a3b940bb87b666"},
-]
-
-[package.dependencies]
-numpy = "*"
-packaging = "*"
-protobuf = ">=3.20"
-
 [[package]]
 name = "termcolor"
 version = "2.4.0"
@@ -4396,24 +3711,24 @@ files = [
 
 [[package]]
 name = "threadpoolctl"
-version = "3.4.0"
+version = "3.5.0"
 description = "threadpoolctl"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "threadpoolctl-3.4.0-py3-none-any.whl", hash = "sha256:8f4c689a65b23e5ed825c8436a92b818aac005e0f3715f6a1664d7c7ee29d262"},
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+    {file = "threadpoolctl-3.5.0.tar.gz", hash = "sha256:082433502dd922bf738de0d8bcc4fdcbf0979ff44c42bd40f5af8a282f6fa107"},
 ]
 
 [[package]]
 name = "tinycss2"
-version = "1.2.1"
+version = "1.3.0"
 description = "A tiny CSS parser"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4421,7 +3736,7 @@ webencodings = ">=0.4"
 
 [package.extras]
 doc = ["sphinx", "sphinx_rtd_theme"]
-test = ["flake8", "isort", "pytest"]
+test = ["pytest", "ruff"]
 
 [[package]]
 name = "tomli"
@@ -4436,130 +3751,44 @@ files = [
 
 [[package]]
 name = "tomlkit"
-version = "0.12.4"
+version = "0.12.5"
 description = "Style preserving TOML library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "tomlkit-0.12.4-py3-none-any.whl", hash = "sha256:5cd82d48a3dd89dee1f9d64420aa20ae65cfbd00668d6f094d7578a78efbb77b"},
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-]
-
-[[package]]
-name = "torch"
-version = "2.2.2"
-description = "Tensors and Dynamic neural networks in Python with strong GPU acceleration"
-optional = true
-python-versions = ">=3.8.0"
-files = [
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-
 [[package]]
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 description = "Tornado is a Python web framework and asynchronous networking library, originally developed at FriendFeed."
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+python-versions = ">=3.8"
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 ]
 
 [[package]]
 name = "tqdm"
-version = "4.66.2"
+version = "4.66.4"
 description = "Fast, Extensible Progress Meter"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -4590,7 +3819,7 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 name = "triad"
 version = "0.9.6"
 description = "A collection of python utils for Fugue projects"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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@@ -4608,45 +3837,22 @@ six = "*"
 [package.extras]
 ciso8601 = ["ciso8601"]
 
-[[package]]
-name = "triton"
-version = "2.2.0"
-description = "A language and compiler for custom Deep Learning operations"
-optional = true
-python-versions = "*"
-files = [
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-
-[package.dependencies]
-filelock = "*"
-
-[package.extras]
-build = ["cmake (>=3.20)", "lit"]
-tests = ["autopep8", "flake8", "isort", "numpy", "pytest", "scipy (>=1.7.1)", "torch"]
-tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
-
 [[package]]
 name = "typeguard"
-version = "4.2.1"
+version = "4.3.0"
 description = "Run-time type checker for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "typeguard-4.2.1.tar.gz", hash = "sha256:c556a1b95948230510070ca53fa0341fb0964611bd05d598d87fb52115d65fee"},
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 ]
 
 [package.dependencies]
-typing-extensions = {version = ">=4.10.0", markers = "python_version < \"3.13\""}
+typing-extensions = ">=4.10.0"
 
 [package.extras]
-doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)"]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme (>=1.3.0)"]
 test = ["coverage[toml] (>=7)", "mypy (>=1.2.0)", "pytest (>=7)"]
 
 [[package]]
@@ -4679,13 +3885,13 @@ files = [
 
 [[package]]
 name = "typing-extensions"
-version = "4.11.0"
+version = "4.12.2"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
+    {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
 ]
 
 [[package]]
@@ -4699,6 +3905,43 @@ files = [
     {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
 ]
 
+[[package]]
+name = "u8darts"
+version = "0.29.0"
+description = "A python library for easy manipulation and forecasting of time series."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "u8darts-0.29.0-py3-none-any.whl", hash = "sha256:652523d260ae50f201a3dcb2cf012d453530981dcb9cacdf51245ca081ec8fc4"},
+    {file = "u8darts-0.29.0.tar.gz", hash = "sha256:b4e2ed16bf4980123b2b753c7be8f08602f71fdeca5ee1d7cd7f7e77de86dd87"},
+]
+
+[package.dependencies]
+holidays = ">=0.11.1"
+joblib = ">=0.16.0"
+matplotlib = ">=3.3.0"
+nfoursid = ">=1.0.0"
+numpy = ">=1.19.0"
+pandas = {version = ">=1.0.5", markers = "python_version >= \"3.9\""}
+pmdarima = ">=1.8.0"
+pyod = ">=0.9.5"
+requests = ">=2.22.0"
+scikit-learn = ">=1.0.1"
+scipy = ">=1.3.2"
+shap = ">=0.40.0"
+statsforecast = ">=1.4"
+statsmodels = ">=0.14.0"
+tbats = ">=1.1.0"
+tqdm = ">=4.60.0"
+typing-extensions = "*"
+xarray = ">=0.17.0"
+xgboost = ">=1.6.0"
+
+[package.extras]
+all = ["catboost (>=1.0.6)", "holidays (>=0.11.1)", "joblib (>=0.16.0)", "lightgbm (>=3.2.0)", "matplotlib (>=3.3.0)", "nfoursid (>=1.0.0)", "numpy (>=1.19.0)", "pandas (>=1.0.5)", "pandas (>=1.0.5,<2.0.0)", "pmdarima (>=1.8.0)", "prophet (>=1.1.1)", "pyod (>=0.9.5)", "pytorch-lightning (>=1.5.0)", "requests (>=2.22.0)", "scikit-learn (>=1.0.1)", "scipy (>=1.3.2)", "shap (>=0.40.0)", "statsforecast (>=1.4)", "statsmodels (>=0.14.0)", "tbats (>=1.1.0)", "tensorboardX (>=2.1)", "torch (>=1.8.0)", "tqdm (>=4.60.0)", "typing-extensions", "xarray (>=0.17.0)", "xgboost (>=1.6.0)"]
+notorch = ["catboost (>=1.0.6)", "lightgbm (>=3.2.0)", "prophet (>=1.1.1)"]
+torch = ["pytorch-lightning (>=1.5.0)", "tensorboardX (>=2.1)", "torch (>=1.8.0)"]
+
 [[package]]
 name = "urllib3"
 version = "2.2.1"
@@ -4718,13 +3961,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "utilsforecast"
-version = "0.1.5"
+version = "0.1.10"
 description = "Forecasting utilities"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
@@ -4740,13 +3983,13 @@ scalers = ["numba", "scipy"]
 
 [[package]]
 name = "virtualenv"
-version = "20.25.3"
+version = "20.26.2"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
@@ -4782,35 +4025,35 @@ files = [
 
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 name = "widgetsnbextension"
-version = "4.0.10"
+version = "4.0.11"
 description = "Jupyter interactive widgets for Jupyter Notebook"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
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 name = "xarray"
-version = "2024.3.0"
+version = "2024.5.0"
 description = "N-D labeled arrays and datasets in Python"
-optional = true
+optional = false
 python-versions = ">=3.9"
 files = [
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 [package.dependencies]
 numpy = ">=1.23"
-packaging = ">=22"
-pandas = ">=1.5"
+packaging = ">=23.1"
+pandas = ">=2.0"
 
 [package.extras]
 accel = ["bottleneck", "flox", "numbagg", "opt-einsum", "scipy"]
 complete = ["xarray[accel,dev,io,parallel,viz]"]
-dev = ["hypothesis", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-timeout", "pytest-xdist", "ruff", "xarray[complete]"]
+dev = ["hypothesis", "mypy", "pre-commit", "pytest", "pytest-cov", "pytest-env", "pytest-timeout", "pytest-xdist", "ruff", "xarray[complete]"]
 io = ["cftime", "fsspec", "h5netcdf", "netCDF4", "pooch", "pydap", "scipy", "zarr"]
 parallel = ["dask[complete]"]
 viz = ["matplotlib", "nc-time-axis", "seaborn"]
@@ -4842,128 +4085,22 @@ plotting = ["graphviz", "matplotlib"]
 pyspark = ["cloudpickle", "pyspark", "scikit-learn"]
 scikit-learn = ["scikit-learn"]
 
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-    {file = "yarl-1.9.4-py3-none-any.whl", hash = "sha256:928cecb0ef9d5a7946eb6ff58417ad2fe9375762382f1bf5c55e61645f2c43ad"},
-    {file = "yarl-1.9.4.tar.gz", hash = "sha256:566db86717cf8080b99b58b083b773a908ae40f06681e87e589a976faf8246bf"},
-]
-
-[package.dependencies]
-idna = ">=2.0"
-multidict = ">=4.0"
-
 [[package]]
 name = "zipp"
-version = "3.18.1"
+version = "3.19.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.18.1-py3-none-any.whl", hash = "sha256:206f5a15f2af3dbaee80769fb7dc6f249695e940acca08dfb2a4769fe61e538b"},
-    {file = "zipp-3.18.1.tar.gz", hash = "sha256:2884ed22e7d8961de1c9a05142eb69a247f120291bc0206a00a7642f09b5b715"},
+    {file = "zipp-3.19.2-py3-none-any.whl", hash = "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c"},
+    {file = "zipp-3.19.2.tar.gz", hash = "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
-
-[extras]
-darts = ["darts"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10,<4.0"
-content-hash = "bee2ba953e26b67021ad25854506c53f9371fe8aa05fbb2cd157894160da4199"
+content-hash = "6ce6fa286783f5870203d73f11523bacdf9cc1cfa98b6f0872db9dac20c0575e"
diff --git a/pyproject.toml b/pyproject.toml
index 0c3492c..9eb30d9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -19,20 +19,17 @@ version_provider = "poetry"
 [tool.poetry.dependencies]  # https://python-poetry.org/docs/dependency-specification/
 python = ">=3.10,<4.0"
 numpy = ">=1.22.0"
+pandas = ">=1.0.5"
 scikit-learn = ">=1.0.0"
 scipy = ">=1.5.0"
+u8darts = ">=0.25.0"
 xgboost = ">=2.0.0"
-darts = { version = ">=0.25.0", optional = true }
-
-[tool.poetry.extras]  # https://python-poetry.org/docs/pyproject/#extras
-darts = ["darts"]
 
 [tool.poetry.group.test.dependencies]  # https://python-poetry.org/docs/master/managing-dependencies/
 commitizen = ">=3.21.3"
 coverage = { extras = ["toml"], version = ">=7.4.4" }
 lightgbm = ">=4.3.0"
 mypy = ">=1.9.0"
-pandas = ">=2.2.1"
 poethepoet = ">=0.25.0"
 pre-commit = ">=3.7.0"
 pytest = ">=8.1.1"
diff --git a/src/conformal_tights/_conformal_coherent_quantile_regressor.py b/src/conformal_tights/_conformal_coherent_quantile_regressor.py
index 8c61e15..a006b7d 100644
--- a/src/conformal_tights/_conformal_coherent_quantile_regressor.py
+++ b/src/conformal_tights/_conformal_coherent_quantile_regressor.py
@@ -1,9 +1,10 @@
 """Conformal Coherent Quantile Regressor meta-estimator."""
 
-from typing import TYPE_CHECKING, Any, Literal, TypeVar, overload
+from typing import Any, Literal, TypeVar, overload
 
 import numpy as np
 import numpy.typing as npt
+import pandas as pd
 from sklearn.base import BaseEstimator, MetaEstimatorMixin, RegressorMixin, clone
 from sklearn.exceptions import NotFittedError
 from sklearn.model_selection import train_test_split
@@ -18,9 +19,6 @@
 from conformal_tights._coherent_linear_quantile_regressor import CoherentLinearQuantileRegressor
 from conformal_tights._typing import FloatMatrix, FloatVector
 
-if TYPE_CHECKING:
-    import pandas as pd
-
 F = TypeVar("F", np.float32, np.float64)
 
 
@@ -88,8 +86,8 @@ def __init__(  # noqa: PLR0913
 
     def fit(
         self,
-        X: "FloatMatrix[F] | pd.DataFrame",
-        y: "FloatVector[F] | pd.Series",
+        X: FloatMatrix[F] | pd.DataFrame,
+        y: FloatVector[F] | pd.Series,
         *,
         sample_weight: "FloatVector[F] | pd.Series | None" = None,
     ) -> "ConformalCoherentQuantileRegressor":
@@ -242,19 +240,19 @@ def predict_quantiles(
     @overload
     def predict_quantiles(
         self,
-        X: "pd.DataFrame",
+        X: pd.DataFrame,
         *,
         quantiles: npt.ArrayLike,
         priority: Literal["accuracy", "coverage"] = "accuracy",
-    ) -> "pd.DataFrame": ...
+    ) -> pd.DataFrame: ...
 
     def predict_quantiles(
         self,
-        X: "FloatMatrix[F] | pd.DataFrame",
+        X: FloatMatrix[F] | pd.DataFrame,
         *,
         quantiles: npt.ArrayLike,
         priority: Literal["accuracy", "coverage"] = "accuracy",
-    ) -> "FloatMatrix[F] | pd.DataFrame":
+    ) -> FloatMatrix[F] | pd.DataFrame:
         """Predict conformally calibrated quantiles on a given dataset."""
         # Predict the absolute and relative quantiles.
         quantiles = np.asarray(quantiles)
@@ -285,25 +283,20 @@ def predict_quantiles(
             ŷ_quantiles = ŷ_quantiles.astype(self.y_dtype_)
         # Convert ŷ_quantiles to a pandas DataFrame if X is a pandas DataFrame.
         if hasattr(X, "dtypes") and hasattr(X, "index"):
-            try:
-                import pandas as pd
-            except ImportError:
-                pass
-            else:
-                ŷ_quantiles_df = pd.DataFrame(ŷ_quantiles, index=X.index, columns=quantiles)
-                ŷ_quantiles_df.columns.name = "quantile"
-                return ŷ_quantiles_df
+            ŷ_quantiles_df = pd.DataFrame(ŷ_quantiles, index=X.index, columns=quantiles)
+            ŷ_quantiles_df.columns.name = "quantile"
+            return ŷ_quantiles_df
         return ŷ_quantiles
 
     @overload
     def predict_interval(self, X: FloatMatrix[F], *, coverage: float = 0.95) -> FloatMatrix[F]: ...
 
     @overload
-    def predict_interval(self, X: "pd.DataFrame", *, coverage: float = 0.95) -> "pd.DataFrame": ...
+    def predict_interval(self, X: pd.DataFrame, *, coverage: float = 0.95) -> pd.DataFrame: ...
 
     def predict_interval(
-        self, X: "FloatMatrix[F] | pd.DataFrame", *, coverage: float = 0.95
-    ) -> "FloatMatrix[F] | pd.DataFrame":
+        self, X: FloatMatrix[F] | pd.DataFrame, *, coverage: float = 0.95
+    ) -> FloatMatrix[F] | pd.DataFrame:
         """Predict conformally calibrated intervals on a given dataset."""
         # Convert the coverage probability to lower and upper quantiles.
         lb = (1 - coverage) / 2
@@ -329,26 +322,26 @@ def predict(
 
     @overload
     def predict(
-        self, X: "pd.DataFrame", *, coverage: None = None, quantiles: None = None
-    ) -> "pd.Series": ...
+        self, X: pd.DataFrame, *, coverage: None = None, quantiles: None = None
+    ) -> pd.Series: ...
 
     @overload
     def predict(
-        self, X: "pd.DataFrame", *, coverage: float, quantiles: None = None
-    ) -> "pd.DataFrame": ...
+        self, X: pd.DataFrame, *, coverage: float, quantiles: None = None
+    ) -> pd.DataFrame: ...
 
     @overload
     def predict(
-        self, X: "pd.DataFrame", *, coverage: None = None, quantiles: npt.ArrayLike
-    ) -> "pd.DataFrame": ...
+        self, X: pd.DataFrame, *, coverage: None = None, quantiles: npt.ArrayLike
+    ) -> pd.DataFrame: ...
 
     def predict(
         self,
-        X: "FloatMatrix[F] | pd.DataFrame",
+        X: FloatMatrix[F] | pd.DataFrame,
         *,
         coverage: float | None = None,
         quantiles: npt.ArrayLike | None = None,
-    ) -> "FloatVector[F] | pd.Series | FloatMatrix[F] | pd.DataFrame":
+    ) -> FloatVector[F] | pd.Series | FloatMatrix[F] | pd.DataFrame:
         """Predict on a given dataset."""
         assert coverage is None or quantiles is None
         check_is_fitted(self)
@@ -363,13 +356,8 @@ def predict(
         if not np.issubdtype(self.y_dtype_, np.integer):
             ŷ = ŷ.astype(self.y_dtype_)
         if hasattr(X, "dtypes") and hasattr(X, "index"):
-            try:
-                import pandas as pd
-            except ImportError:
-                pass
-            else:
-                ŷ_series = pd.Series(ŷ, index=X.index)
-                return ŷ_series
+            ŷ_series = pd.Series(ŷ, index=X.index)
+            return ŷ_series
         return ŷ
 
     def _more_tags(self) -> dict[str, Any]:
diff --git a/src/conformal_tights/_darts_forecaster.py b/src/conformal_tights/_darts_forecaster.py
index afe2ac0..c41baae 100644
--- a/src/conformal_tights/_darts_forecaster.py
+++ b/src/conformal_tights/_darts_forecaster.py
@@ -1,52 +1,21 @@
 """Darts Forecaster."""
 
 from collections.abc import Sequence
-from typing import TYPE_CHECKING, Any, TypeVar
+from typing import Any, TypeVar
 
 import numpy as np
 import numpy.typing as npt
+import pandas as pd
+from darts import TimeSeries
+from darts.models.forecasting.regression_model import (
+    FUTURE_LAGS_TYPE,
+    LAGS_TYPE,
+    RegressionModel,
+    RegressionModelWithCategoricalCovariates,
+    _LikelihoodMixin,
+)
 from sklearn.utils import check_random_state
 
-if TYPE_CHECKING:
-    import pandas as pd
-else:
-    try:
-        import pandas as pd
-    except ImportError:
-        pd = None
-
-if TYPE_CHECKING:
-    from darts import TimeSeries
-    from darts.models.forecasting.regression_model import (
-        FUTURE_LAGS_TYPE,
-        LAGS_TYPE,
-        RegressionModel,
-        RegressionModelWithCategoricalCovariates,
-        _LikelihoodMixin,
-    )
-else:
-    try:
-        from darts import TimeSeries
-        from darts.models.forecasting.regression_model import (
-            FUTURE_LAGS_TYPE,
-            LAGS_TYPE,
-            RegressionModel,
-            RegressionModelWithCategoricalCovariates,
-            _LikelihoodMixin,
-        )
-    except ImportError:
-        FUTURE_LAGS_TYPE = tuple[int, int] | list[int] | dict[str, tuple[int, int] | list[int]]
-        LAGS_TYPE = int | list[int] | dict[str, int | list[int]]
-
-        class TimeSeries: ...
-
-        class RegressionModel: ...
-
-        class RegressionModelWithCategoricalCovariates: ...
-
-        class _LikelihoodMixin: ...
-
-
 from conformal_tights._conformal_coherent_quantile_regressor import (
     ConformalCoherentQuantileRegressor,
 )
@@ -63,7 +32,7 @@ def __init__(
         self.quantile = quantile
         self.quantiles = np.asarray(quantiles)
 
-    def predict(self, x: "pd.DataFrame", **kwargs: Any) -> FloatMatrix[F]:
+    def predict(self, x: pd.DataFrame, **kwargs: Any) -> FloatMatrix[F]:
         # Call ConformalCoherentQuantileRegressor's predict_quantiles.
         q = np.asarray(self.model.predict_quantiles(x, quantiles=self.quantiles))
         # Filter out the requested quantile.
@@ -92,13 +61,6 @@ def __init__(  # noqa: PLR0913
         categorical_static_covariates: str | list[str] | None = None,
     ) -> None:
         """Initialize a Darts Conformal Coherent Quantile Regressor."""
-        # Verify that the required dependencies are installed.
-        try:
-            import darts  # noqa: F401
-            import pandas as pd  # noqa: F401
-        except ImportError:
-            required_dependencies = "Please install darts and pandas to use DartsForecaster."
-            raise ImportError(required_dependencies) from None
         # Initialise _LikelihoodMixin.
         self.likelihood = "quantile"
         self._model_container = self._get_model_container()
@@ -138,7 +100,7 @@ def _create_lagged_data(
         past_covariates: Sequence[TimeSeries],
         future_covariates: Sequence[TimeSeries],
         max_samples_per_ts: int,
-    ) -> tuple["pd.DataFrame", FloatVector[F]]:
+    ) -> tuple[pd.DataFrame, FloatVector[F]]:
         """Override training data to add support for categorical covariates."""
         # Validate categoricals with RegressionModelWithCategoricalCovariates. We cannot inherit
         # from RegressionModelWithCategoricalCovariates because it was developed with LightGBM in
@@ -162,7 +124,7 @@ def _create_lagged_data(
         )
         # Convert categorical columns to pd.Categorical so that the wrapped regressor can handle
         # them appropriately.
-        self.cat_col_categories_: dict[float, "pd.Index"] = {}
+        self.cat_col_categories_: dict[float, pd.Index] = {}
         training_samples_df = pd.DataFrame(training_samples)
         cols = training_samples_df.columns
         for cat_col_index in cat_col_indices:
diff --git a/tests/test_optional_dependencies.py b/tests/test_optional_dependencies.py
deleted file mode 100644
index 616a419..0000000
--- a/tests/test_optional_dependencies.py
+++ /dev/null
@@ -1,30 +0,0 @@
-"""Test this package's optional dependencies."""
-
-import sys
-from unittest.mock import patch
-
-import pytest
-
-
-@pytest.mark.parametrize("optional_dependency", ["darts", "pandas"])
-def test_optional_dependencies(optional_dependency: str) -> None:
-    """Test that we get an expected error when an optional dependency are not available."""
-    # Prevent the optional dependency from being loaded.
-    with patch.dict("sys.modules", {optional_dependency: None}):
-        # Unload Conformal Tights.
-        mods_to_unload = [mod for mod in sys.modules if mod.startswith("conformal_tights")]
-        for mod in mods_to_unload:
-            del sys.modules[mod]
-
-        # Reload Conformal Tights now that the selected optional dependency is not available.
-        from conformal_tights import ConformalCoherentQuantileRegressor, DartsForecaster
-
-        # Test that we raise the appropriate error.
-        conformal_predictor = ConformalCoherentQuantileRegressor()
-        with pytest.raises(ImportError, match=f".*install.*{optional_dependency}.*"):
-            _ = DartsForecaster(model=conformal_predictor)
-
-        # Unload Conformal Tights again.
-        mods_to_unload = [mod for mod in sys.modules if mod.startswith("conformal_tights")]
-        for mod in mods_to_unload:
-            del sys.modules[mod]