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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