Add new character type

[josephburkhart]

Description

These changes make the Python API more approachable by adding support for reading and writing strings to GSD data chunks. My changes add a new character data type on the C side, and modify the python api to automatically decode strings for the user. The new changes are accompanied by a new test, which fully covers the expected use cases.

Motivation and Context

Currently, strings are implicitly encoded as uint8 data, but it is up to the user to figure out how to decode that data upon reading. The Python API is intended to be approachable, allowing users to, for example, create a pandas dataframe from a GSD log in one line. However, this oneliner will break if the log contains varying textual information, because pandas requires uniform dimensions in each column. These changes make it so users don't have to convert decimal unicode to text on their own, allowing the one-line example to work.

This PR resolves #375.

How Has This Been Tested?

I have modified test_fl.py, adding a new test specifically for the string dtype (test_string_dtype). The new test covers both fl and pygsd.

• Please build the sphinx documentation and check that any changes to documentation display properly

Checklist:

• I have reviewed the Contributor Guidelines.
• I agree with the terms of the GSD Contributor Agreement.
• My name is on the list of contributors (doc/credits.rst) in the pull request source branch.
• I have added a change log entry to CHANGELOG.rst.

[josephburkhart]

pre-commit.ci autofix

[joaander]

We need to remove stray print() calls, commented code, and unused imports.

[josephburkhart]

Great catches - apologies for the omissions!

[joaander]

Thanks!

[github-actions]

This pull request has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs.

[joaander]

I tested the original motivation for this feature.

In the test_hoomd.py::read_log test, pandas is indeed able to create a DataFrame with the strings:

    import pandas
    df = pandas.DataFrame(logged_data_dict)
    print()
    print(df)

   configuration/step  log/value/potential_energy  log/value/pressure log/category
0                   0                          10                  -3            A
1                   1                          10                   5          BBB