refacto(requirements): add requirements

Former-commit-id: 10acc250bd2079381b082a132ef673875d815d88

.python-version

@@ -0,0 +1 @@
+3.8

README.md

@@ -18,8 +18,8 @@ If you use PhenoGenius, please cite:
 - Requirements
 
 ```bash
-python == 3.8
-poetry
+python == 3.8 #(pyenv install 3.8)
+poetry #(https://python-poetry.org/docs/#installation)
 ```
 
 - Install dependencies

phenogenius_cli.py

@@ -90,7 +90,7 @@ def score_sim_add(hpo_list_add, matrix, sim_dict, symbol):
 
 @click.command()
 @click.option("--result_file", default="match.tsv")
-@click.option("--hpo_list", default="HP:0000107,HP:0000108,HP:0001407,HP:0005562")
+@click.option("--hpo_list", default=None)
 def evaluate_matching(result_file, hpo_list):
     logging.info("INFO: load databases")
     ncbi, symbol = symbol_to_id_to_dict()
@@ -98,83 +98,85 @@ def evaluate_matching(result_file, hpo_list):
     hp_onto = load_hp_ontology()
 
     logging.info("INFO: clean HPO list")
-    hpo_list_ini = hpo_list.strip().split(",")
-    hpo_list_up = []
-
-    for hpo in hpo_list_ini:
-        if hpo in ["HP:0000001"]:
-            pass
-        else:
-            if data[hpo].astype(bool).sum(axis=0) != 0:
-                hpo_list_up.append(hpo)
+    if hpo_list is None:
+        print("Provide a list of HPO terms with the --hpo_list option")
+    else:
+        hpo_list_ini = hpo_list.strip().split(",")
+        hpo_list_up = []
+        for hpo in hpo_list_ini:
+            if hpo in ["HP:0000001"]:
+                pass
             else:
-                hpo_to_test = hp_onto[hpo]["direct_parent"][0]
-                while data[hpo_to_test].astype(bool).sum(
-                    axis=0
-                ) == 0 and hpo_to_test not in ["HP:0000001"]:
-                    hpo_to_test = hp_onto[hpo_to_test]["direct_parent"][0]
-                if hpo_to_test in ["HP:0000001"]:
-                    pass
+                if data[hpo].astype(bool).sum(axis=0) != 0:
+                    hpo_list_up.append(hpo)
                 else:
-                    hpo_list_up.append(hpo_to_test)
-    hpo_list = list(set(hpo_list_up))
-    if len(hpo_list) < 6:
-        logging.info("INFO: selected symptom interaction model - NMF")
-        pandarallel.initialize(nb_workers=4)
-        pheno_NMF, reduced = load_nmf_model()
-        witness = np.zeros(len(data.columns))
-        witness_nmf = np.matmul(pheno_NMF.components_, witness)
-        witness_df = (
-            pd.DataFrame(reduced)
-            .set_index(data.index)
-            .parallel_apply(lambda x: sum((x - witness_nmf) ** 2), axis=1)
-        )
-
-        patient = np.zeros(len(data.columns))
-        for hpo in hpo_list:
-            hpo_index = list(data.columns).index(hpo)
-            patient[hpo_index] = 1
-
-        patient_nmf = np.matmul(pheno_NMF.components_, patient)
-        patient_df = (
-            pd.DataFrame(reduced)
-            .set_index(data.index)
-            .parallel_apply(lambda x: sum((x - patient_nmf) ** 2), axis=1)
-        )
-
-        case_df = pd.DataFrame(patient_df - witness_df)
-        case_df.columns = ["score"]
-        case_df["score_norm"] = abs(case_df["score"] - case_df["score"].max())
-        case_df["sum"] = case_df["score_norm"]
-        case_df_sort = case_df.sort_values(by="sum", ascending=False)
-        case_df_sort["rank"] = (
-            case_df_sort["sum"].rank(ascending=False, method="max").astype(int)
-        )
-        case_df_sort["gene_symbol"] = case_df_sort.index.to_series().apply(
-            get_symbol, args=(symbol,)
-        )
-        match_nmf = case_df_sort[["gene_symbol", "rank", "sum"]]
-        match_nmf_filter = match_nmf[match_nmf["sum"] > 0.01].reset_index()
-        match_nmf_filter.columns = ["gene_id", "gene_symbol", "rank", "sum"]
-        match_nmf_filter["sum"] = match_nmf_filter["sum"].round(2)
-        match_nmf_filter.to_csv(result_file, sep="\t", index=False)
+                    hpo_to_test = hp_onto[hpo]["direct_parent"][0]
+                    while data[hpo_to_test].astype(bool).sum(
+                        axis=0
+                    ) == 0 and hpo_to_test not in ["HP:0000001"]:
+                        hpo_to_test = hp_onto[hpo_to_test]["direct_parent"][0]
+                    if hpo_to_test in ["HP:0000001"]:
+                        pass
+                    else:
+                        hpo_list_up.append(hpo_to_test)
+        hpo_list = list(set(hpo_list_up))
+        if len(hpo_list) < 6:
+            logging.info("INFO: selected symptom interaction model - NMF")
+            pandarallel.initialize(nb_workers=4)
+            pheno_NMF, reduced = load_nmf_model()
+            witness = np.zeros(len(data.columns))
+            witness_nmf = np.matmul(pheno_NMF.components_, witness)
+            witness_df = (
+                pd.DataFrame(reduced)
+                .set_index(data.index)
+                .parallel_apply(lambda x: sum((x - witness_nmf) ** 2), axis=1)
+            )
+
+            patient = np.zeros(len(data.columns))
+            for hpo in hpo_list:
+                hpo_index = list(data.columns).index(hpo)
+                patient[hpo_index] = 1
+
+            patient_nmf = np.matmul(pheno_NMF.components_, patient)
+            patient_df = (
+                pd.DataFrame(reduced)
+                .set_index(data.index)
+                .parallel_apply(lambda x: sum((x - patient_nmf) ** 2), axis=1)
+            )
+
+            case_df = pd.DataFrame(patient_df - witness_df)
+            case_df.columns = ["score"]
+            case_df["score_norm"] = abs(case_df["score"] - case_df["score"].max())
+            case_df["sum"] = case_df["score_norm"]
+            case_df_sort = case_df.sort_values(by="sum", ascending=False)
+            case_df_sort["rank"] = (
+                case_df_sort["sum"].rank(ascending=False, method="max").astype(int)
+            )
+            case_df_sort["gene_symbol"] = case_df_sort.index.to_series().apply(
+                get_symbol, args=(symbol,)
+            )
+            match_nmf = case_df_sort[["gene_symbol", "rank", "sum"]]
+            match_nmf_filter = match_nmf[match_nmf["sum"] > 0.01].reset_index()
+            match_nmf_filter.columns = ["gene_id", "gene_symbol", "rank", "sum"]
+            match_nmf_filter["sum"] = match_nmf_filter["sum"].round(2)
+            match_nmf_filter.to_csv(result_file, sep="\t", index=False)
 
-    else:
-        logging.info("INFO: selected symptom interaction model - node similarity")
-        similarity_terms_dict = load_similarity_dict()
-        sim_dict, hpo_list_add = get_similar_terms(hpo_list, similarity_terms_dict)
-        results_sum_add = score_sim_add(hpo_list_add, data, sim_dict, symbol)
-        results_sum_add["rank"] = (
-            results_sum_add["sum"].rank(ascending=False, method="max").astype(int)
-        )
-        cols = results_sum_add.columns.tolist()
-        cols = cols[-2:] + cols[:-2]
-        match_sim = results_sum_add[cols].sort_values(by=["sum"], ascending=False)
-        match_sim_filter = match_sim[match_sim["sum"] > 0.01].reset_index()
-        match_sim_filter_print = match_sim_filter.iloc[:, [0, 1, 2, -1]]
-        match_sim_filter_print.columns = ["gene_id", "gene_symbol", "rank", "sum"]
-        match_sim_filter_print["sum"] = match_sim_filter_print["sum"].round(2)
-        match_sim_filter_print.to_csv(result_file, sep="\t", index=False)
+        else:
+            logging.info("INFO: selected symptom interaction model - node similarity")
+            similarity_terms_dict = load_similarity_dict()
+            sim_dict, hpo_list_add = get_similar_terms(hpo_list, similarity_terms_dict)
+            results_sum_add = score_sim_add(hpo_list_add, data, sim_dict, symbol)
+            results_sum_add["rank"] = (
+                results_sum_add["sum"].rank(ascending=False, method="max").astype(int)
+            )
+            cols = results_sum_add.columns.tolist()
+            cols = cols[-2:] + cols[:-2]
+            match_sim = results_sum_add[cols].sort_values(by=["sum"], ascending=False)
+            match_sim_filter = match_sim[match_sim["sum"] > 0.01].reset_index()
+            match_sim_filter_print = match_sim_filter.iloc[:, [0, 1, 2, -1]]
+            match_sim_filter_print.columns = ["gene_id", "gene_symbol", "rank", "sum"]
+            match_sim_filter_print["sum"] = match_sim_filter_print["sum"].round(2)
+            match_sim_filter_print.to_csv(result_file, sep="\t", index=False)
 
 
 if __name__ == "__main__":

requirements.txt

@@ -0,0 +1,178 @@
+altair==4.2.0 ; python_version >= "3.8" and python_version < "3.9"
+appnope==0.1.3 ; python_version >= "3.8" and python_version < "3.9" and (platform_system == "Darwin" or sys_platform == "darwin")
+argon2-cffi-bindings==21.2.0 ; python_version >= "3.8" and python_version < "3.9"
+argon2-cffi==21.3.0 ; python_version >= "3.8" and python_version < "3.9"
+asttokens==2.0.5 ; python_version >= "3.8" and python_version < "3.9"
+attrs==22.1.0 ; python_version >= "3.8" and python_version < "3.9"
+backcall==0.2.0 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:5cbdbf27be5e7cfadb448baf0aa95508f91f2bbc6c6437cd9cd06e2a4c215e1e \
+    --hash=sha256:fbbce6a29f263178a1f7915c1940bde0ec2b2a967566fe1c65c1dfb7422bd255
+backports-zoneinfo==0.2.1 ; python_version >= "3.8" and python_version < "3.9"
+beautifulsoup4==4.11.1 ; python_version >= "3.8" and python_version < "3.9"
+bleach==5.0.1 ; python_version >= "3.8" and python_version < "3.9"
+blinker==1.5 ; python_version >= "3.8" and python_version < "3.9"
+cachetools==5.2.0 ; python_version >= "3.8" and python_version < "3.9"
+certifi==2022.6.15 ; python_version >= "3.8" and python_version < "3.9"
+cffi==1.15.1 ; python_version >= "3.8" and python_version < "3.9"
+charset-normalizer==2.1.0 ; python_version >= "3.8" and python_version < "3.9"
+click==8.0.4 ; python_version >= "3.8" and python_version < "3.9"
+colorama==0.4.5 ; python_version >= "3.8" and python_version < "3.9" and (platform_system == "Windows" or sys_platform == "win32")
+commonmark==0.9.1 ; python_version >= "3.8" and python_version < "3.9"
+cycler==0.11.0 ; python_version >= "3.8" and python_version < "3.9"
+debugpy==1.6.2 ; python_version >= "3.8" and python_version < "3.9"
+decorator==5.1.1 ; python_version >= "3.8" and python_version < "3.9"
+defusedxml==0.7.1 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:1bb3032db185915b62d7c6209c5a8792be6a32ab2fedacc84e01b52c51aa3e69 \
+    --hash=sha256:a352e7e428770286cc899e2542b6cdaedb2b4953ff269a210103ec58f6198a61
+dill==0.3.5.1 ; python_version >= "3.8" and python_version < "3.9"
+entrypoints==0.4 ; python_version >= "3.8" and python_version < "3.9"
+executing==0.9.1 ; python_version >= "3.8" and python_version < "3.9"
+fastjsonschema==2.16.1 ; python_version >= "3.8" and python_version < "3.9"
+fonttools==4.34.4 ; python_version >= "3.8" and python_version < "3.9"
+gitdb==4.0.9 ; python_version >= "3.8" and python_version < "3.9"
+gitpython==3.1.27 ; python_version >= "3.8" and python_version < "3.9"
+idna==3.3 ; python_version >= "3.8" and python_version < "3.9"
+importlib-metadata==4.12.0 ; python_version >= "3.8" and python_version < "3.9"
+importlib-resources==5.9.0 ; python_version >= "3.8" and python_version < "3.9"
+ipykernel==6.15.1 ; python_version >= "3.8" and python_version < "3.9"
+ipython-genutils==0.2.0 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:72dd37233799e619666c9f639a9da83c34013a73e8bbc79a7a6348d93c61fab8 \
+    --hash=sha256:eb2e116e75ecef9d4d228fdc66af54269afa26ab4463042e33785b887c628ba8
+ipython==8.4.0 ; python_version >= "3.8" and python_version < "3.9"
+ipywidgets==7.7.1 ; python_version >= "3.8" and python_version < "3.9"
+jedi==0.18.1 ; python_version >= "3.8" and python_version < "3.9"
+jinja2==3.1.2 ; python_version >= "3.8" and python_version < "3.9"
+joblib==1.1.0 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:4158fcecd13733f8be669be0683b96ebdbbd38d23559f54dca7205aea1bf1e35 \
+    --hash=sha256:f21f109b3c7ff9d95f8387f752d0d9c34a02aa2f7060c2135f465da0e5160ff6
+jsonschema==4.9.0 ; python_version >= "3.8" and python_version < "3.9"
+jupyter-client==7.3.4 ; python_version >= "3.8" and python_version < "3.9"
+jupyter-core==4.11.1 ; python_version >= "3.8" and python_version < "3.9"
+jupyterlab-pygments==0.2.2 ; python_version >= "3.8" and python_version < "3.9"
+jupyterlab-widgets==1.1.1 ; python_version >= "3.8" and python_version < "3.9"
+kiwisolver==1.4.4 ; python_version >= "3.8" and python_version < "3.9"
+llvmlite==0.34.0 ; python_version >= "3.8" and python_version < "3.9"
+markupsafe==2.1.1 ; python_version >= "3.8" and python_version < "3.9"
+matplotlib-inline==0.1.3 ; python_version >= "3.8" and python_version < "3.9"
+matplotlib==3.5.2 ; python_version >= "3.8" and python_version < "3.9"
+mistune==0.8.4 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:59a3429db53c50b5c6bcc8a07f8848cb00d7dc8bdb431a4ab41920d201d4756e \
+    --hash=sha256:88a1051873018da288eee8538d476dffe1262495144b33ecb586c4ab266bb8d4
+mizani==0.7.4 ; python_version >= "3.8" and python_version < "3.9"
+multipy==0.16 ; python_version >= "3.8" and python_version < "3.9"
+nbclient==0.6.6 ; python_version >= "3.8" and python_version < "3.9"
+nbconvert==6.5.0 ; python_version >= "3.8" and python_version < "3.9"
+nbformat==5.4.0 ; python_version >= "3.8" and python_version < "3.9"
+nest-asyncio==1.5.5 ; python_version >= "3.8" and python_version < "3.9"
+networkx==2.8.5 ; python_version >= "3.8" and python_version < "3.9"
+notebook==6.4.12 ; python_version >= "3.8" and python_version < "3.9"
+numba==0.51.2 ; python_version >= "3.8" and python_version < "3.9"
+numpy==1.23.1 ; python_version < "3.9" and python_version >= "3.8"
+obonet==0.3.0 ; python_version >= "3.8" and python_version < "3.9"
+packaging==21.3 ; python_version >= "3.8" and python_version < "3.9"
+palettable==3.3.0 ; python_version >= "3.8" and python_version < "3.9"
+pandarallel==1.6.1 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:e36f16d7057a1728f9f3a6ef25ca50e01e382eb10d8be580a4881c210be6ce3a
+pandas==1.4.3 ; python_version >= "3.8" and python_version < "3.9"
+pandocfilters==1.5.0 ; python_version >= "3.8" and python_version < "3.9"
+parso==0.8.3 ; python_version >= "3.8" and python_version < "3.9"
+patsy==0.5.2 ; python_version >= "3.8" and python_version < "3.9"
+pexpect==4.8.0 ; python_version >= "3.8" and python_version < "3.9" and sys_platform != "win32" \
+    --hash=sha256:0b48a55dcb3c05f3329815901ea4fc1537514d6ba867a152b581d69ae3710937 \
+    --hash=sha256:fc65a43959d153d0114afe13997d439c22823a27cefceb5ff35c2178c6784c0c
+pickleshare==0.7.5 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:87683d47965c1da65cdacaf31c8441d12b8044cdec9aca500cd78fc2c683afca \
+    --hash=sha256:9649af414d74d4df115d5d718f82acb59c9d418196b7b4290ed47a12ce62df56
+pillow==9.2.0 ; python_version >= "3.8" and python_version < "3.9"
+pkgutil-resolve-name==1.3.10 ; python_version >= "3.8" and python_version < "3.9"
+plotnine==0.9.0 ; python_version >= "3.8" and python_version < "3.9"
+prometheus-client==0.14.1 ; python_version >= "3.8" and python_version < "3.9"
+prompt-toolkit==3.0.30 ; python_version >= "3.8" and python_version < "3.9"
+protobuf==3.20.1 ; python_version >= "3.8" and python_version < "3.9"
+psrecord==1.2 ; python_version >= "3.8" and python_version < "3.9"
+psutil==5.9.1 ; python_version >= "3.8" and python_version < "3.9"
+ptyprocess==0.7.0 ; python_version >= "3.8" and python_version < "3.9" and (sys_platform != "win32" or os_name != "nt") \
+    --hash=sha256:4b41f3967fce3af57cc7e94b888626c18bf37a083e3651ca8feeb66d492fef35 \
+    --hash=sha256:5c5d0a3b48ceee0b48485e0c26037c0acd7d29765ca3fbb5cb3831d347423220
+pure-eval==0.2.2 ; python_version >= "3.8" and python_version < "3.9"
+py==1.11.0 ; python_version >= "3.8" and python_version < "3.9" and implementation_name == "pypy"
+pyarrow==8.0.0 ; python_version >= "3.8" and python_version < "3.9"
+pycparser==2.21 ; python_version >= "3.8" and python_version < "3.9"
+pydeck==0.7.1 ; python_version >= "3.8" and python_version < "3.9"
+pygments==2.12.0 ; python_version >= "3.8" and python_version < "3.9"
+pympler==1.0.1 ; python_version >= "3.8" and python_version < "3.9"
+pynndescent==0.5.7 ; python_version >= "3.8" and python_version < "3.9"
+pyparsing==3.0.9 ; python_version >= "3.8" and python_version < "3.9"
+pyrsistent==0.18.1 ; python_version >= "3.8" and python_version < "3.9"
+python-dateutil==2.8.2 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:0123cacc1627ae19ddf3c27a5de5bd67ee4586fbdd6440d9748f8abb483d3e86 \
+    --hash=sha256:961d03dc3453ebbc59dbdea9e4e11c5651520a876d0f4db161e8674aae935da9
+pytz-deprecation-shim==0.1.0.post0 ; python_version >= "3.8" and python_version < "3.9"
+pytz==2022.1 ; python_version >= "3.8" and python_version < "3.9"
+pywin32==304 ; sys_platform == "win32" and platform_python_implementation != "PyPy" and python_version >= "3.8" and python_version < "3.9"
+pywinpty==2.0.6 ; python_version >= "3.8" and python_version < "3.9" and os_name == "nt"
+pyzmq==23.2.0 ; python_version >= "3.8" and python_version < "3.9"
+requests==2.28.1 ; python_version >= "3.8" and python_version < "3.9"
+rich==12.5.1 ; python_version >= "3.8" and python_version < "3.9"
+scikit-learn==1.1.1 ; python_version >= "3.8" and python_version < "3.9"
+scipy==1.6.1 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:0c8a51d33556bf70367452d4d601d1742c0e806cd0194785914daf19775f0e67 \
+    --hash=sha256:0e5b0ccf63155d90da576edd2768b66fb276446c371b73841e3503be1d63fb5d \
+    --hash=sha256:2481efbb3740977e3c831edfd0bd9867be26387cacf24eb5e366a6a374d3d00d \
+    --hash=sha256:33d6b7df40d197bdd3049d64e8e680227151673465e5d85723b3b8f6b15a6ced \
+    --hash=sha256:5da5471aed911fe7e52b86bf9ea32fb55ae93e2f0fac66c32e58897cfb02fa07 \
+    --hash=sha256:5f331eeed0297232d2e6eea51b54e8278ed8bb10b099f69c44e2558c090d06bf \
+    --hash=sha256:5fa9c6530b1661f1370bcd332a1e62ca7881785cc0f80c0d559b636567fab63c \
+    --hash=sha256:6725e3fbb47da428794f243864f2297462e9ee448297c93ed1dcbc44335feb78 \
+    --hash=sha256:68cb4c424112cd4be886b4d979c5497fba190714085f46b8ae67a5e4416c32b4 \
+    --hash=sha256:794e768cc5f779736593046c9714e0f3a5940bc6dcc1dba885ad64cbfb28e9f0 \
+    --hash=sha256:83bf7c16245c15bc58ee76c5418e46ea1811edcc2e2b03041b804e46084ab627 \
+    --hash=sha256:8e403a337749ed40af60e537cc4d4c03febddcc56cd26e774c9b1b600a70d3e4 \
+    --hash=sha256:a15a1f3fc0abff33e792d6049161b7795909b40b97c6cc2934ed54384017ab76 \
+    --hash=sha256:a423533c55fec61456dedee7b6ee7dce0bb6bfa395424ea374d25afa262be261 \
+    --hash=sha256:a5193a098ae9f29af283dcf0041f762601faf2e595c0db1da929875b7570353f \
+    --hash=sha256:bd50daf727f7c195e26f27467c85ce653d41df4358a25b32434a50d8870fc519 \
+    --hash=sha256:c4fceb864890b6168e79b0e714c585dbe2fd4222768ee90bc1aa0f8218691b11 \
+    --hash=sha256:e79570979ccdc3d165456dd62041d9556fb9733b86b4b6d818af7a0afc15f092 \
+    --hash=sha256:f46dd15335e8a320b0fb4685f58b7471702234cba8bb3442b69a3e1dc329c345
+seaborn==0.11.2 ; python_version >= "3.8" and python_version < "3.9"
+semver==2.13.0 ; python_version >= "3.8" and python_version < "3.9"
+send2trash==1.8.0 ; python_version >= "3.8" and python_version < "3.9"
+setuptools-scm==7.0.5 ; python_version >= "3.8" and python_version < "3.9"
+six==1.16.0 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926 \
+    --hash=sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254
+smmap==5.0.0 ; python_version >= "3.8" and python_version < "3.9"
+soupsieve==2.3.2.post1 ; python_version >= "3.8" and python_version < "3.9"
+stack-data==0.3.0 ; python_version >= "3.8" and python_version < "3.9"
+statsmodels==0.13.2 ; python_version >= "3.8" and python_version < "3.9"
+streamlit==1.15.1 ; python_version >= "3.8" and python_version < "3.9"
+terminado==0.15.0 ; python_version >= "3.8" and python_version < "3.9"
+threadpoolctl==3.1.0 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:8b99adda265feb6773280df41eece7b2e6561b772d21ffd52e372f999024907b \
+    --hash=sha256:a335baacfaa4400ae1f0d8e3a58d6674d2f8828e3716bb2802c44955ad391380
+tinycss2==1.1.1 ; python_version >= "3.8" and python_version < "3.9"
+toml==0.10.2 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b \
+    --hash=sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f
+tomli==2.0.1 ; python_version >= "3.8" and python_version < "3.9"
+toolz==0.12.0 ; python_version >= "3.8" and python_version < "3.9"
+tornado==6.2 ; python_version >= "3.8" and python_version < "3.9"
+tqdm==4.64.0 ; python_version >= "3.8" and python_version < "3.9"
+traitlets==5.3.0 ; python_version >= "3.8" and python_version < "3.9"
+typing-extensions==4.3.0 ; python_version >= "3.8" and python_version < "3.9"
+tzdata==2022.1 ; python_version >= "3.8" and python_version < "3.9"
+tzlocal==4.2 ; python_version >= "3.8" and python_version < "3.9"
+ujson==5.4.0 ; python_version >= "3.8" and python_version < "3.9"
+umap-learn==0.5.3 ; python_version >= "3.8" and python_version < "3.9"
+urllib3==1.26.11 ; python_version >= "3.8" and python_version < "3.9"
+validators==0.20.0 ; python_version >= "3.8" and python_version < "3.9"
+watchdog==2.1.9 ; python_version >= "3.8" and python_version < "3.9" and platform_system != "Darwin"
+wcwidth==0.2.5 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:beb4802a9cebb9144e99086eff703a642a13d6a0052920003a230f3294bbe784 \
+    --hash=sha256:c4d647b99872929fdb7bdcaa4fbe7f01413ed3d98077df798530e5b04f116c83
+webencodings==0.5.1 ; python_version >= "3.8" and python_version < "3.9" \
+    --hash=sha256:a0af1213f3c2226497a97e2b3aa01a7e4bee4f403f95be16fc9acd2947514a78 \
+    --hash=sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923
+widgetsnbextension==3.6.1 ; python_version >= "3.8" and python_version < "3.9"
+zipp==3.8.1 ; python_version >= "3.8" and python_version < "3.9"