Author: John Au-Yeung

Sometimes, we want to pretty print nested dictionaries with Python.

In this article, we’ll look at how to pretty print nested dictionaries with Python.

How to pretty print nested dictionaries with Python?

To pretty print nested dictionaries with Python, we call json.dumps with the indent argument.

For instance, we write

import json

print(
    json.dumps(
        {"a": 2, "b": {"x": 3, "y": {"t1": 4, "t2": 5}}}, sort_keys=True, indent=4
    )
)

to print the JSON string returned by json.dumps.

We call it with indent set to 4 to indent by 4 spaces in each level.

Conclusion

To pretty print nested dictionaries with Python, we call json.dumps with the indent argument.

Sometimes, we want to iterate over model instance field names and values in template with Python Django.

In this article, we’ll look at how to iterate over model instance field names and values in template with Python Django.

How to iterate over model instance field names and values in template with Python Django?

To iterate over model instance field names and values in template with Python Django, we can use a for loop.

For instance, we write

from django.forms.models import model_to_dict


def show(request, object_id):
    object = FooForm(data=model_to_dict(Foo.objects.get(pk=object_id)))
    return render_to_response("foo/foo_detail.html", {"object": object})

in the show view that passes the object object to the foo_detail.html template.

Then in the template, we write

{% for field in object %}
    <li><b>{{ field.label }}:</b> {{ field.data }}</li>
{% endfor %}

to loop through the object attributes and get the attribute name from label and the attribute value from data.

Conclusion

To iterate over model instance field names and values in template with Python Django, we can use a for loop.

Sometimes, we want to get list from Python Pandas dataframe column or row.

In this article, we’ll look at how to get list from Python Pandas dataframe column or row.

How to get list from Python Pandas dataframe column or row?

To get list from Python Pandas dataframe column or row, we use the tolist method.

For instance, we write

import pandas as pd

data_dict = {
    "one": pd.Series([1, 2, 3], index=["a", "b", "c"]),
    "two": pd.Series([1, 2, 3, 4], index=["a", "b", "c", "d"]),
}

df = pd.DataFrame(data_dict)
col_one_list = df["one"].tolist()

to create the df data frame from the data_dict dict.

Then we get column one’s values with df['one'] and call tolist to return the values in the series as a list.

Conclusion

To get list from Python Pandas dataframe column or row, we use the tolist method.

Sometimes, we want to execute a file within the Python interpreter.

In this article, we’ll look at how to execute a file within the Python interpreter.

How to execute a file within the Python interpreter?

To execute a file within the Python interpreter, we can run python with the file name of the file.

In the interactive prompt, we can use exec.

For instance, we run

python filename.py

to run filename.py from the shell.

When we’re in the REPL, we run

exec(open("filename.py").read())

to run filename.py by opening it with open and then call read to read the code.

Then we call exec with the returned code to run it.

Conclusion

To execute a file within the Python interpreter, we can run python with the file name of the file.

In the interactive prompt, we can use exec.