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How to use just_draw_columns method in hypothesis

Best Python code snippet using hypothesis

impl.py

Source:impl.py

...407        )408        rewritten_columns.append(c)409    if rows is None:410        @st.composite411        def just_draw_columns(draw):412            index = draw(index_strategy)413            local_index_strategy = st.just(index)414            data = OrderedDict((c.name, None) for c in rewritten_columns)415            # Depending on how the columns are going to be generated we group416            # them differently to get better shrinking. For columns with fill417            # enabled, the elements can be shrunk independently of the size,418            # so we can just shrink by shrinking the index then shrinking the419            # length and are generally much more free to move data around.420            # For columns with no filling the problem is harder, and drawing421            # them like that would result in rows being very far apart from422            # each other in the underlying data stream, which gets in the way423            # of shrinking. So what we do is reorder and draw those columns424            # row wise, so that the values of each row are next to each other.425            # This makes life easier for the shrinker when deleting blocks of426            # data.427            columns_without_fill = [428                c for c in rewritten_columns if c.fill.is_empty]429            if columns_without_fill:430                for c in columns_without_fill:431                    data[c.name] = pandas.Series(432                        np.zeros(shape=len(index), dtype=c.dtype),433                        index=index,434                    )435                seen = {436                    c.name: set() for c in columns_without_fill if c.unique}437                for i in hrange(len(index)):438                    for c in columns_without_fill:439                        if c.unique:440                            for _ in range(5):441                                value = draw(c.elements)442                                if value not in seen[c.name]:443                                    seen[c.name].add(value)444                                    break445                            else:446                                reject()447                        else:448                            value = draw(c.elements)449                        data[c.name][i] = value450            for c in rewritten_columns:451                if not c.fill.is_empty:452                    data[c.name] = draw(series(453                        index=local_index_strategy, dtype=c.dtype,454                        elements=c.elements, fill=c.fill, unique=c.unique))455            return pandas.DataFrame(data, index=index)456        return just_draw_columns()457    else:458        @st.composite459        def assign_rows(draw):460            index = draw(index_strategy)461            result = pandas.DataFrame(OrderedDict(462                (c.name, pandas.Series(463                    np.zeros(dtype=c.dtype, shape=len(index)), dtype=c.dtype))464                for c in rewritten_columns465            ), index=index)466            fills = {}467            any_unique = any(c.unique for c in rewritten_columns)468            if any_unique:469                all_seen = [470                    set() if c.unique else None for c in rewritten_columns]...

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