Run pysr in secondary instance

gui/app.py

@@ -1,11 +1,7 @@
-import io
 import gradio as gr
-import sys
 import os
 import tempfile
-import numpy as np
 import pandas as pd
-import traceback as tb
 
 empty_df = pd.DataFrame(
     {
@@ -14,7 +10,6 @@ empty_df = pd.DataFrame(
         "complexity": [],
     }
 )
-Main = None
 
 def greet(
     file_obj: tempfile._TemporaryFileWrapper,
@@ -23,12 +18,6 @@ def greet(
     binary_operators: list,
     unary_operators: list,
 ):
-    global Main
-    if Main is not None:
-        return (
-            empty_df,
-            "Refresh the page to run with a different configuration."
-        )
     if col_to_fit == "":
         return (
             empty_df,
@@ -44,71 +33,12 @@ def greet(
             empty_df,
             "Please upload a CSV file!",
         )
-    niterations = int(niterations)
-
-    # Install Julia:
-    os.system(
-        """if [ ! -d "/home/user/julia" ]; then
-        wget https://julialang-s3.julialang.org/bin/linux/x64/1.7/julia-1.7.3-linux-x86_64.tar.gz
-        tar zxvf julia-1.7.3-linux-x86_64.tar.gz
-        mkdir /home/user/julia
-        mv julia-1.7.3/* /home/user/julia/
-    fi""")
-    os.environ["PATH"] += ":/home/user/julia/bin/"
-    # Need to install PySR in separate python instance:
-    os.system(
-        """if [ ! -d "/home/user/.julia/environments/pysr-0.9.3" ]; then
-        export PATH="$PATH:/home/user/julia/bin/"
-        python -c 'import pysr; pysr.install()'
-    fi"""
-    )
-
-    import pysr
-    try:
-        from julia.api import JuliaInfo
-        info = JuliaInfo.load(julia="/home/user/julia/bin/julia")
-        from julia import Main as _Main
-        pysr.sr.Main = _Main
-    except Exception as e:
-        error_message = tb.format_exc()
-        return (
-            empty_df,
-            error_message,
-        )
-    from pysr import PySRRegressor
-
-    df = pd.read_csv(file_obj.name)
-    y = np.array(df[col_to_fit])
-    X = df.drop([col_to_fit], axis=1)
-
-    model = PySRRegressor(
-        update=False,
-        temp_equation_file=True,
-        niterations=niterations,
-        binary_operators=binary_operators,
-        unary_operators=unary_operators,
-    )
-    try:
-        model.fit(X, y)
-    # Catch all error:
-    except Exception as e:
-        error_traceback = tb.format_exc()
-        if "CalledProcessError" in error_traceback:
-            return (
-                empty_df,
-                "Could not initialize Julia. Error message:\n"
-                + error_traceback,
-            )
-        else:
-            return (
-                empty_df,
-                "Failed due to error:\n" + error_traceback,
-            )
 
-    df = model.equations_[["equation", "loss", "complexity"]]
-    # Convert all columns to string type:
-    df = df.astype(str)
-    return df, "Successful."
+    os.system("bash install_pysr.sh")
+    os.system(f"python run_pysr_and_save.py --niterations {niterations} --binary_operators '{binary_operators}' --unary_operators '{unary_operators}' --col_to_fit {col_to_fit} --filename {file_obj.name}")
+    df = pd.read_csv("pysr_output.csv")
+    error_log = open("error.log", "r").read()
+    return df, error_log
 
 
 def main():

gui/install_pysr.sh

@@ -0,0 +1,12 @@
+import os
+
+# Install Julia:
+if [ ! -f "/home/user/.local/bin/julia" ]; then
+    bash -ci "$(curl -fsSL https://raw.githubusercontent.com/abelsiqueira/jill/main/jill.sh)"
+fi
+
+# Need to install PySR in separate python instance:
+if [ ! -d "/home/user/.julia/environments/pysr-0.9.3" ]; then
+    export PATH="$PATH:/home/user/julia/bin/"
+    python -c 'import pysr; pysr.install()'
+fi

gui/run_pysr_and_save.py

@@ -0,0 +1,68 @@
+import os
+import pandas as pd
+import traceback as tb
+import numpy as np
+from argparse import ArgumentParser
+
+# Args:
+# niterations
+# binary_operators
+# unary_operators
+# col_to_fit
+
+empty_df = pd.DataFrame(
+    {
+        "equation": [],
+        "loss": [],
+        "complexity": [],
+    }
+)
+
+if __name__ == "__main__":
+    parser = ArgumentParser()
+    parser.add_argument("niterations", type=int)
+    parser.add_argument("binary_operators", type=str)
+    parser.add_argument("unary_operators", type=str)
+    parser.add_argument("col_to_fit", type=str)
+    parser.add_argument("filename", type=str)
+    args = parser.parse_args()
+    niterations = args.niterations
+    binary_operators = eval(args.binary_operators)
+    unary_operators = eval(args.unary_operators)
+    col_to_fit = args.col_to_fit
+    filename = args.filename
+
+    os.environ["PATH"] += ":/home/user/.local/bin/"
+
+    try:
+        import pysr
+        from julia.api import JuliaInfo
+        info = JuliaInfo.load(julia="/home/user/.local/bin/julia")
+        from julia import Main as _Main
+        pysr.sr.Main = _Main
+
+        from pysr import PySRRegressor
+
+        df = pd.read_csv(filename)
+        y = np.array(df[col_to_fit])
+        X = df.drop([col_to_fit], axis=1)
+
+        model = PySRRegressor(
+            update=False,
+            niterations=niterations,
+            binary_operators=binary_operators,
+            unary_operators=unary_operators,
+        )
+        model.fit(X, y)
+
+        df = model.equations_[["equation", "loss", "complexity"]]
+        # Convert all columns to string type:
+        df = df.astype(str)
+        df.to_csv("pysr_output.csv", index=False)
+    except Exception as e:
+        error_message = tb.format_exc()
+        # Dump to file:
+        empty_df.to_csv("pysr_output.csv", index=False)
+        with open("error.log", "w") as f:
+            f.write(error_message)
+