fork/cellxgene
1
0
Fork 0
mirror of https://github.com/chanzuckerberg/cellxgene.git synced 2026-09-27 09:38:11 +08:00
Code Issues Packages Projects Releases Wiki Activity

Makefile modularity, test targets, and auto-formatting (#1070)

Browse Source 
* Fix Makefile whitespace and .PHONY use

* Fix Makefile filename

* Modularize Makefile into client and server Makefiles

Part of the reason that the Makefile in the root directory is a bit
complicated is that it tries to handle tasks that can be handled
separately in the client and server modules.

This commit pushes some of the make logic specific to each module into
their own makefiles and calls out to those makefiles from that in the
project root.

* Add auto-formatting to client and server modules

One thing that can make linting faster is auto-formatting. This commit
adds the yapf auto-formatting tool to the server module and uses
eslint's "fix" functionality to speed up the linting/formatting process.

* Add yapf for automatic code formatting

* Add a root test target that calls sub-tests

* Apply yapf to python files

* Do not duplicate npm commands, simply pass through

* Update documentation

* Do not shadow reserved word len

* Add general test target

* Fix make call in dev-env

* Use black instead of yapf

* Run flake8 from the root directory

* Revert "Apply yapf to python files"

This reverts commit cdca128a01.

* Apply black to python code

* Resolve lint errors resulting from black format

* Add explanation of server unit tests in dev guidelines
This commit is contained in:
Matt Weiden
2019-12-27 14:43:37 -08:00
committed by GitHub
parent ec79995be8
commit f3015cb9df
37 changed files with 738 additions and 806 deletions
Download Patch File Download Diff File Expand all files Collapse all files
server/app/util/matrix_proxy.py
+30 -32
View File
@@ -18,6 +18,7 @@ class _ArrayProxyBase(abc.ABC):
Private base class for array or matrix proxy. This summarizes
the interface used by the rest of cellxgene.
"""
@property
@abc.abstractmethod
def dtype(self):
@@ -68,10 +69,10 @@ class MatrixProxy(_ArrayProxyBase):
Sub-classes automatically register.
"""
base_proxy_registry = {
'pandas.core.frame.DataFrame': True,
'numpy.ndarray': True,
'scipy.sparse.csc.csc_matrix': True,
'scipy.sparse.csr.csr_matrix': True,
"pandas.core.frame.DataFrame": True,
"numpy.ndarray": True,
"scipy.sparse.csc.csc_matrix": True,
"scipy.sparse.csr.csr_matrix": True,
}
proxy_registry = None
last_cache_token = None
@@ -103,7 +104,7 @@ class MatrixProxy(_ArrayProxyBase):
"""
cls.build_proxy_registry()
t = type(matrix)
fqtn = t.__module__ + '.' + t.__name__
fqtn = t.__module__ + "." + t.__name__
proxy_cls = cls.proxy_registry.get(fqtn, None)
if proxy_cls is None:
raise Exception(f"Matrix format `{fqtn}` is unsupported by proxy.")
@@ -128,21 +129,17 @@ class MatrixProxyView(MatrixProxy):
"""
2D matrix view to a 2D matrix
"""
def __init__(self, arg1, shape=None, index=(),
transposed=False, copy=False):
def __init__(self, arg1, shape=None, index=(), transposed=False, copy=False):
if not copy:
m = arg1
super().__init__(m)
if shape is None:
shape = m.shape
assert(len(shape) == 2)
assert len(shape) == 2
index = tuple(
map(lambda s_i:
slice(0, s_i[0], 1) if s_i[1] is None else s_i[1],
zip_longest(shape, index))
)
index = tuple(map(lambda s_i: slice(0, s_i[0], 1) if s_i[1] is None else s_i[1], zip_longest(shape, index)))
self._shape = shape
self._index = index
@@ -234,20 +231,20 @@ class MatrixProxyView(MatrixProxy):
NOTE: these follow the numpy rules for dimensionality reduction
when an integer index is specified.
"""
def _getitem_intXint(self, row, col):
return self.m[row, col]
def _getitem_intXslice(self, row, col):
shape = (_slice_length(col, self.m.shape[1]), )
shape = (_slice_length(col, self.m.shape[1]),)
return self.__class__.create_array(self.m, shape=shape, index=(row, col))
def _getitem_sliceXint(self, row, col):
shape = (_slice_length(row, self.m.shape[0]), )
shape = (_slice_length(row, self.m.shape[0]),)
return self.__class__.create_array(self.m, shape=shape, index=(row, col))
def _getitem_sliceXslice(self, row, col):
shape = (_slice_length(row, self.m.shape[0]),
_slice_length(col, self.m.shape[1]))
shape = (_slice_length(row, self.m.shape[0]), _slice_length(col, self.m.shape[1]))
return self.__class__(self.m, shape=shape, index=(row, col), transposed=self.transposed)
def toarray(self):
@@ -261,22 +258,23 @@ class ArrayProxyView(_ArrayProxyBase):
"""
1D array view to a 2D matrix
"""
def __init__(self, arg1, shape=None, index=None, copy=False):
super().__init__()
if not copy:
m = arg1
# one index MUST be an integer and the other MUST be a slice
assert(len(index) == 2)
assert(all(isinstance(idx, INT_TYPES + (slice, )) for idx in index))
assert(isinstance(index[0], INT_TYPES) != isinstance(index[1], INT_TYPES))
assert len(index) == 2
assert all(isinstance(idx, INT_TYPES + (slice,)) for idx in index)
assert isinstance(index[0], INT_TYPES) != isinstance(index[1], INT_TYPES)
if shape is None:
if isinstance(index[0], INT_TYPES):
shape = (m.shape[0], )
shape = (m.shape[0],)
else:
shape = (m.shape[1], )
assert(len(shape) == 1)
shape = (m.shape[1],)
assert len(shape) == 1
self._shape = shape
self.m = m
@@ -336,7 +334,7 @@ class ArrayProxyView(_ArrayProxyBase):
elif isinstance(col, slice):
return self._getitem_intXslice(row, col)
elif isinstance(row, slice):
assert(isinstance(col, INT_TYPES))
assert isinstance(col, INT_TYPES)
return self._getitem_sliceXint(row, col)
raise IndexError("unsupported column index types")
@@ -345,11 +343,11 @@ class ArrayProxyView(_ArrayProxyBase):
return self.m[row, col]
def _getitem_intXslice(self, row, col):
shape = (_slice_length(col, self.m.shape[1]), )
shape = (_slice_length(col, self.m.shape[1]),)
return self.__class__(self.m, shape=shape, index=(row, col))
def _getitem_sliceXint(self, row, col):
shape = (_slice_length(row, self.m.shape[0]), )
shape = (_slice_length(row, self.m.shape[0]),)
return self.__class__(self.m, shape=shape, index=(row, col))
def toarray(self):
@@ -358,7 +356,7 @@ class ArrayProxyView(_ArrayProxyBase):
def _unpack_index(index, shape):
if not isinstance(index, tuple):
index = (index, )
index = (index,)
if len(shape) < len(index):
raise IndexError("invalid index dimensionality - must be 2")
@@ -366,7 +364,7 @@ def _unpack_index(index, shape):
for shp, idx in zip_longest(shape, index):
idx = slice(None) if idx is None else idx
idx = _slice_defaults(idx, shp) if isinstance(idx, slice) else idx
unpacked += (idx, )
unpacked += (idx,)
return unpacked
@@ -376,7 +374,7 @@ def _slice_slice(outer, outer_len, inner, inner_len):
slice a slice - we take advantage of Python 3 range's support
for indexing.
"""
assert(outer_len >= inner_len)
assert outer_len >= inner_len
outer_rng = range(*outer.indices(outer_len))
rng = outer_rng[inner]
start, stop, step = rng.start, rng.stop, rng.step
@@ -387,8 +385,8 @@ def _slice_slice(outer, outer_len, inner, inner_len):
def _range_length(start, stop, step):
""" return length of range """
assert(step != 0)
assert(start is not None and stop is not None and step is not None)
assert step != 0
assert start is not None and stop is not None and step is not None
if step > 0 and start < stop:
return 1 + (stop - 1 - start) // step
elif step < 0 and start > stop:
@@ -404,7 +402,7 @@ def _slice_length(s, length):
def _slice_defaults(s, length):
""" apply slice defaulting conventions """
assert(length >= 0)
assert length >= 0
step = 1 if s.step is None else s.step