Which cellpy loaders exist, and which can actually run on this machine.

Load one cell file and return a handle plus what the data can support.

mass_mg is the active-material mass. Without it every *_gravimetric column is computed against a default of 1.0 mg — the numbers still appear, they are simply wrong, so supply it when you know it.

The cells loaded in this session.

Summary plot families cellpy offers, and whether the loaded cells support them.

Availability is judged on what a family asks the summary for (summary_options().columns), not on the columns it draws — the drawn list includes columns the collector manufactures, and checking those reports "missing columns" for families that work perfectly well.

Build a collection. kind is one of: summary, cycles, ica, dva.

Returns a handle and the frame's shape — never the frame. Use preview_collection for rows, export_collection for the numbers.

For summary, give either columns or family (a name from describe_plot_families; the family supplies its own collect options). For cycles / ica / dva, give cycles.

A few rows, capped. This is the only tool that returns data, on purpose.

Draw a collection and write the figure to path (.json or .html).

kind="film" gives a 2-D density rendering. Note it is a kind, not a layout: on cellpy 2.1.2 layout="film" silently drew lines instead (fixed in 2.1.3). The returned trace_types is how you check what you actually got.

Write the collected frame to path (.csv, .parquet or .json).

Find cellpy calls by name, or by what their first docstring line says.

Use this when you know the task but not the call — "average cycles", "loading", "mass". describe_api then gives the arguments.

What a cellpy call takes and what it does, from the installed package.

name is a dotted path (cellpy.get, cellpy.collect.collect_summary) or a bare name (get_cap) looked up in the index.

Read undocumented_parameters before answering a question about one of them. cellpy documents roughly half its arguments, so an argument missing from doc means the package never said what it does — not that it does not matter. Ask again with include_source=True rather than guessing.

When delegates_to is set, the docstring pointed at another call with a Sphinx reference and delegate_doc is where the arguments are actually described — read it, it is usually the real documentation.

Batch templates available for new_project, registered and local.

cellpy new --list prints this and returns nothing, so this reads the registry directly (jepegit/cellpy#991 asks for a library form).

Create a batch project from a template — the cellpy new workflow.

project is the folder, experiment the lookup value; the template dates the experiment folder itself, so experiment="exp001" becomes something like 2026_09_05_exp001. Writes inside the data directories only.

Downloads the cookiecutter from GitHub on first use.