PTC-W0019 · Consider using literal syntax to create the data structure

sassoftware / python-sasctl

Active

Consider using literal syntax to create the data structure PTC-W0019

Performance

Minor

2 months ago — 4 years old

unnecessary dict call - write as literal

1302                    json_dict[1]["data"][j].update(roc_dict[j])
1303                    fitstat_data = None
1304                    if roc_dict[j]["dataMap"]["_KS_"] == 1:
1305                        fitstat_data = dict()1306                        missing_stats = (
1307                            "_KS_",
1308                            "_KS2_",

unnecessary list call - write as literal

src/sasctl/pzmm/write_json_files.py

2682        var_importances = var_importances.sort_values(
2683            by=["RelVarImportance"], ascending=False
2684        ).reset_index(drop=True)
2685        relative_importances = list()2686        for index, row in var_importances.iterrows():
2687            if row["Variable"] in interval_vars:
2688                level = "INTERVAL"

unnecessary list call - write as literal

src/sasctl/pzmm/write_json_files.py

2757                roc_table = json.load(roc_file)
2758        correct_text = ["CORRECT", "INCORRECT", "CORRECT", "INCORRECT"]
2759        outcome_values = ["1", "0", "0", "1"]
2760        misc_data = list()2761        # Iterates through ROC table to get TRAIN, TEST, and VALIDATE data with a cutoff of .5
2762        for i in range(50, 300, 100):
2763            roc_data = roc_table["data"][i]["dataMap"]

unnecessary list call - write as literal

src/sasctl/pzmm/write_json_files.py

2613
2614        # Load actionset necessary to generate variable importance
2615        conn.loadactionset("dataPreprocess")
2616        request_packages = list()2617        if target_type == "classification":
2618            method = "DTREE"
2619            treeCrit = "Entropy"

unnecessary list call - write as literal

src/sasctl/pzmm/write_json_files.py

2624            raise RuntimeError(
2625                "The selected model type is unsupported. Currently, only models that have prediction or classification target types are supported."
2626            )
2627        request_packages = list()2628        if interval_vars:
2629            request_packages.append(
2630                {

Description

Using the literal syntax can give minor performance bumps compared to using function calls to create dict, list and tuple.

In [1]: timeit.timeit(stmt="dict()", number=100000000)
Out[1]: 9.560388602000103

In [2]: timeit.timeit(stmt="{}", number=100000000)
Out[2]: 1.685333584000091

In [3]: timeit.timeit(stmt="tuple()", number=100000000)
Out[3]: 4.509182139000131

In [4]: timeit.timeit(stmt="()", number=100000000)
Out[4]: 0.5455615430000762

In [5]: timeit.timeit(stmt="list()", number=100000000)
Out[5]: 7.356000728000254

In [6]: timeit.timeit(stmt="[]", number=100000000)
Out[6]: 1.573771306999788

This is because here, the name dict must be looked up in the global scope in case it has been rebound. Same goes for the other two types list() and tuple().