Python dependencies visualization using pydeps

To see what Python modules are available on my system I can run

pydoc3 modules

One of the modules is pandas. Here's a script that just loads pandas module:

cat load_pandas.py 
import warnings
warnings.filterwarnings("ignore", category=DeprecationWarning)
import pandas as pd 

When the script is run nothing happens

python3 load_pandas.py

I have pydeps installed:

pydeps --version
pydeps v1.12.17

Output of analysis by pydeps:

pydeps -o myfile.png --show-dot -T png --noshow load_pandas.py 

digraph G {
    concentrate = true;

    rankdir = TB;
    node [style=filled,fillcolor="#ffffff",fontcolor="#000000",fontname=Helvetica,fontsize=10];

    load_pandas_py [fillcolor="#a65959",fontcolor="#ffffff",label="load_pandas.py"];
    pandas [fillcolor="#039595",fontcolor="#ffffff"];
    pandas__config [fillcolor="#24d0d0",label="pandas._config"];
    pandas__version [fillcolor="#47c2c2",label="pandas\.\n_version"];
    pandas__version_meson [fillcolor="#47c2c2",label="pandas\.\n_version_meson"];
    pandas_api [fillcolor="#3db8b8",label="pandas.api"];
    pandas_arrays [fillcolor="#46a4a4",label="pandas.arrays"];
    pandas_compat [fillcolor="#17d3d3",label="pandas.compat"];
    pandas_compat__optional [fillcolor="#31c4c4",label="pandas\.\ncompat\.\n_optional"];
    pandas_compat_pyarrow [fillcolor="#3db8b8",label="pandas\.\ncompat\.\npyarrow"];
    pandas_core [fillcolor="#10f9f9",label="pandas.core"];
    pandas_core_api [fillcolor="#3a8888",fontcolor="#ffffff",label="pandas\.\ncore\.\napi"];
    pandas_core_computation [fillcolor="#3bcece",label="pandas\.\ncore\.\ncomputation"];
    pandas_core_computation_api [fillcolor="#46a4a4",label="pandas\.\ncore\.\ncomputation\.\napi"];
    pandas_core_config_init [fillcolor="#3a8888",fontcolor="#ffffff",label="pandas\.\ncore\.\nconfig_init"];
    pandas_core_dtypes [fillcolor="#2fdbdb",label="pandas\.\ncore\.\ndtypes"];
    pandas_core_dtypes_dtypes [fillcolor="#339999",fontcolor="#ffffff",label="pandas\.\ncore\.\ndtypes\.\ndtypes"];
    pandas_core_reshape [fillcolor="#47c2c2",label="pandas\.\ncore\.\nreshape"];
    pandas_core_reshape_api [fillcolor="#46a4a4",label="pandas\.\ncore\.\nreshape\.\napi"];
    pandas_errors [fillcolor="#3ab0b0",label="pandas.errors"];
    pandas_io [fillcolor="#0bdfdf",label="pandas.io"];
    pandas_io_api [fillcolor="#46a4a4",label="pandas.io.api"];
    pandas_io_json [fillcolor="#23c8c8",label="pandas.io.json"];
    pandas_io_json__normalize [fillcolor="#4cb3b3",label="pandas\.\nio\.\njson\.\n_normalize"];
    pandas_plotting [fillcolor="#31c4c4",label="pandas\.\nplotting"];
    pandas_testing [fillcolor="#4cb3b3",label="pandas.testing"];
    pandas_tseries [fillcolor="#23c8c8",label="pandas.tseries"];
    pandas_tseries_api [fillcolor="#46a4a4",label="pandas\.\ntseries\.\napi"];
    pandas_tseries_offsets [fillcolor="#26d9d9",label="pandas\.\ntseries\.\noffsets"];
    pandas_util [fillcolor="#05e5e5",label="pandas.util"];
    pandas_util__print_versions [fillcolor="#409696",fontcolor="#ffffff",label="pandas\.\nutil\.\n_print_versions"];
    pandas_util__tester [fillcolor="#46a4a4",label="pandas\.\nutil\.\n_tester"];
    pandas -> load_pandas_py [fillcolor="#039595",minlen="2"];
    pandas__config -> pandas [fillcolor="#24d0d0"];
    pandas__config -> pandas_core_config_init [fillcolor="#24d0d0",minlen="2"];
    pandas__config -> pandas_errors [fillcolor="#24d0d0"];
    pandas__version -> pandas [fillcolor="#47c2c2"];
    pandas__version -> pandas_util__print_versions [fillcolor="#47c2c2",minlen="2"];
    pandas__version_meson -> pandas [fillcolor="#47c2c2"];
    pandas__version_meson -> pandas_util__print_versions [fillcolor="#47c2c2",minlen="2"];
    pandas_api -> pandas [fillcolor="#3db8b8"];
    pandas_arrays -> pandas [fillcolor="#46a4a4"];
    pandas_compat -> pandas [fillcolor="#17d3d3"];
    pandas_compat -> pandas_core_dtypes_dtypes [fillcolor="#17d3d3",minlen="3"];
    pandas_compat -> pandas_util__print_versions [fillcolor="#17d3d3",minlen="2"];
    pandas_compat -> pandas_util__tester [fillcolor="#17d3d3",minlen="2"];
    pandas_compat__optional -> pandas [fillcolor="#31c4c4",minlen="2"];
    pandas_compat__optional -> pandas_util__print_versions [fillcolor="#31c4c4",minlen="2"];
    pandas_compat__optional -> pandas_util__tester [fillcolor="#31c4c4",minlen="2"];
    pandas_compat_pyarrow -> pandas [fillcolor="#3db8b8",minlen="2"];
    pandas_compat_pyarrow -> pandas_compat [fillcolor="#3db8b8",weight="2"];
    pandas_core -> pandas [fillcolor="#10f9f9"];
    pandas_core -> pandas_arrays [fillcolor="#10f9f9"];
    pandas_core -> pandas_util [fillcolor="#10f9f9"];
    pandas_core_api -> pandas [fillcolor="#3a8888",minlen="2"];
    pandas_core_computation -> pandas [fillcolor="#3bcece",minlen="2"];
    pandas_core_computation -> pandas_core_config_init [fillcolor="#3bcece",weight="2"];
    pandas_core_computation_api -> pandas [fillcolor="#46a4a4",minlen="3"];
    pandas_core_config_init -> pandas [fillcolor="#3a8888",minlen="2"];
    pandas_core_dtypes -> pandas [fillcolor="#2fdbdb",minlen="2"];
    pandas_core_dtypes -> pandas_core_api [fillcolor="#2fdbdb",weight="2"];
    pandas_core_dtypes -> pandas_core_config_init [fillcolor="#2fdbdb",weight="2"];
    pandas_core_dtypes_dtypes -> pandas [fillcolor="#339999",minlen="3"];
    pandas_core_dtypes_dtypes -> pandas_core_api [fillcolor="#339999",minlen="2",weight="2"];
    pandas_core_reshape -> pandas [fillcolor="#47c2c2",minlen="2"];
    pandas_core_reshape_api -> pandas [fillcolor="#46a4a4",minlen="3"];
    pandas_errors -> pandas [fillcolor="#3ab0b0"];
    pandas_errors -> pandas_core_dtypes_dtypes [fillcolor="#3ab0b0",minlen="3"];
    pandas_io -> pandas [fillcolor="#0bdfdf"];
    pandas_io -> pandas_core_api [fillcolor="#0bdfdf",minlen="2"];
    pandas_io -> pandas_core_config_init [fillcolor="#0bdfdf",minlen="2"];
    pandas_io_api -> pandas [fillcolor="#46a4a4",minlen="2"];
    pandas_io_json -> pandas [fillcolor="#23c8c8",minlen="2"];
    pandas_io_json -> pandas_io [fillcolor="#23c8c8",weight="2"];
    pandas_io_json -> pandas_io_api [fillcolor="#23c8c8",weight="2"];
    pandas_io_json__normalize -> pandas [fillcolor="#4cb3b3",minlen="3"];
    pandas_plotting -> pandas [fillcolor="#31c4c4"];
    pandas_plotting -> pandas_core_config_init [fillcolor="#31c4c4",minlen="2"];
    pandas_testing -> pandas [fillcolor="#4cb3b3"];
    pandas_tseries -> pandas [fillcolor="#23c8c8"];
    pandas_tseries -> pandas_core_api [fillcolor="#23c8c8",minlen="2"];
    pandas_tseries_api -> pandas [fillcolor="#46a4a4",minlen="2"];
    pandas_tseries_offsets -> pandas [fillcolor="#26d9d9",minlen="2"];
    pandas_tseries_offsets -> pandas_core_api [fillcolor="#26d9d9",minlen="2"];
    pandas_tseries_offsets -> pandas_tseries [fillcolor="#26d9d9",weight="2"];
    pandas_tseries_offsets -> pandas_tseries_api [fillcolor="#26d9d9",weight="2"];
    pandas_util -> pandas [fillcolor="#05e5e5"];
    pandas_util -> pandas_arrays [fillcolor="#05e5e5"];
    pandas_util -> pandas_compat__optional [fillcolor="#05e5e5",minlen="2"];
    pandas_util -> pandas_compat_pyarrow [fillcolor="#05e5e5",minlen="2"];
    pandas_util -> pandas_core_dtypes_dtypes [fillcolor="#05e5e5",minlen="3"];
    pandas_util -> pandas_errors [fillcolor="#05e5e5"];
    pandas_util__print_versions -> pandas [fillcolor="#409696",minlen="2"];
    pandas_util__tester -> pandas [fillcolor="#46a4a4",minlen="2"];
}

tracing Python in JSON-based workflow is untenable

I added

def mytrace(frame, event, arg):
    if event == "call":
        print("call", frame.f_code.co_name, frame.f_locals)
    elif event == "return":
        print("return", frame.f_code.co_name, arg)
    return mytrace

sys.settrace(mytrace)

to https://github.com/allofphysicsgraph/proofofconcept/blob/gh-pages/v7_pickle_web_interface/flask/controller.py but the output wasn't that useful since I'm passing the entire database as JSON. The full JSON shows up in almost every argument and return value, making the output of the trace unreadable.

When I switch to the Neo4j/Cypher-based approach, the trace might be more usable.