def test_string_io(self):
df = DataFrame(np.random.randn(10, 2))
s = df.to_msgpack(None)
result = read_msgpack(s)
tm.assert_frame_equal(result, df)
s = df.to_msgpack()
result = read_msgpack(s)
tm.assert_frame_equal(result, df)
s = df.to_msgpack()
result = read_msgpack(compat.BytesIO(s))
tm.assert_frame_equal(result, df)
s = to_msgpack(None, df)
result = read_msgpack(s)
tm.assert_frame_equal(result, df)
with ensure_clean(self.path) as p:
s = df.to_msgpack()
fh = open(p, 'wb')
fh.write(s)
fh.close()
result = read_msgpack(p)
tm.assert_frame_equal(result, df)
def read_msgpack(path_or_buf, encoding='utf-8', iterator=False, **kwargs):
"""
Load msgpack pandas object from the specified
file path
THIS IS AN EXPERIMENTAL LIBRARY and the storage format
may not be stable until a future release.
Parameters
----------
path_or_buf : string File path, BytesIO like or string
encoding: Encoding for decoding msgpack str type
iterator : boolean, if True, return an iterator to the unpacker
(default is False)
Returns
-------
obj : type of object stored in file
"""
path_or_buf, _, _ = get_filepath_or_buffer(path_or_buf)
if iterator:
return Iterator(path_or_buf)
def read(fh):
l = list(unpack(fh, encoding=encoding, **kwargs))
if len(l) == 1:
return l[0]
return l
# see if we have an actual file
if isinstance(path_or_buf, compat.string_types):
try:
exists = os.path.exists(path_or_buf)
except (TypeError, ValueError):
exists = False
if exists:
with open(path_or_buf, 'rb') as fh:
return read(fh)
if isinstance(path_or_buf, compat.binary_type):
# treat as a binary-like
fh = None
try:
# We can't distinguish between a path and a buffer of bytes in
# Python 2 so instead assume the first byte of a valid path is
# less than 0x80.
if compat.PY3 or ord(path_or_buf[0]) >= 0x80:
fh = compat.BytesIO(path_or_buf)
return read(fh)
finally:
if fh is not None:
fh.close()
elif hasattr(path_or_buf, 'read') and compat.callable(path_or_buf.read):
# treat as a buffer like
return read(path_or_buf)
raise ValueError('path_or_buf needs to be a string file path or file-like')
def read_msgpack(path_or_buf, iterator=False, **kwargs):
"""
Load msgpack pandas object from the specified
file path
THIS IS AN EXPERIMENTAL LIBRARY and the storage format
may not be stable until a future release.
Parameters
----------
path_or_buf : string File path, BytesIO like or string
iterator : boolean, if True, return an iterator to the unpacker
(default is False)
Returns
-------
obj : type of object stored in file
"""
path_or_buf, _, _ = get_filepath_or_buffer(path_or_buf)
if iterator:
return Iterator(path_or_buf)
def read(fh):
l = list(unpack(fh, **kwargs))
if len(l) == 1:
return l[0]
return l
# see if we have an actual file
if isinstance(path_or_buf, compat.string_types):
try:
exists = os.path.exists(path_or_buf)
except (TypeError, ValueError):
exists = False
if exists:
with open(path_or_buf, 'rb') as fh:
return read(fh)
# treat as a binary-like
if isinstance(path_or_buf, compat.binary_type):
fh = None
try:
fh = compat.BytesIO(path_or_buf)
return read(fh)
finally:
if fh is not None:
fh.close()
# a buffer like
if hasattr(path_or_buf, 'read') and compat.callable(path_or_buf.read):
return read(path_or_buf)
raise ValueError('path_or_buf needs to be a string file path or file-like')
def _read_zipped_sdmx(path_or_buf):
""" Unzipp data contains SDMX-XML """
data = _read_content(path_or_buf)
zp = compat.BytesIO()
zp.write(compat.str_to_bytes(data))
f = zipfile.ZipFile(zp)
files = f.namelist()
assert len(files) == 1
return f.open(files[0])
def testPackUnicode(self):
test_data = [u(""), u("abcd"), [u("defgh")], u("Русский текст"), ]
for td in test_data:
re = unpackb(
packb(td, encoding='utf-8'), use_list=1, encoding='utf-8')
assert re == td
packer = Packer(encoding='utf-8')
data = packer.pack(td)
re = Unpacker(
compat.BytesIO(data), encoding='utf-8', use_list=1).unpack()
assert re == td
def testArraySize(self, sizes=[0, 5, 50, 1000]):
bio = compat.BytesIO()
packer = Packer()
for size in sizes:
bio.write(packer.pack_array_header(size))
for i in range(size):
bio.write(packer.pack(i))
bio.seek(0)
unpacker = Unpacker(bio, use_list=1)
for size in sizes:
assert unpacker.unpack() == list(range(size))
def testMapSize(self, sizes=[0, 5, 50, 1000]):
bio = compat.BytesIO()
packer = Packer()
for size in sizes:
bio.write(packer.pack_map_header(size))
for i in range(size):
bio.write(packer.pack(i)) # key
bio.write(packer.pack(i * 2)) # value
bio.seek(0)
unpacker = Unpacker(bio)
for size in sizes:
assert unpacker.unpack() == dict((i, i * 2) for i in range(size))
def test_manualreset(self, sizes=[0, 5, 50, 1000]):
packer = Packer(autoreset=False)
for size in sizes:
packer.pack_array_header(size)
for i in range(size):
packer.pack(i)
bio = compat.BytesIO(packer.bytes())
unpacker = Unpacker(bio, use_list=1)
for size in sizes:
assert unpacker.unpack() == list(range(size))
packer.reset()
assert packer.bytes() == b''
def test_readbytes(self):
unpacker = Unpacker(read_size=3)
unpacker.feed(b'foobar')
assert unpacker.unpack() == ord(b'f')
assert unpacker.read_bytes(3) == b'oob'
assert unpacker.unpack() == ord(b'a')
assert unpacker.unpack() == ord(b'r')
# Test buffer refill
unpacker = Unpacker(compat.BytesIO(b'foobar'), read_size=3)
assert unpacker.unpack() == ord(b'f')
assert unpacker.read_bytes(3) == b'oob'
assert unpacker.unpack() == ord(b'a')
assert unpacker.unpack() == ord(b'r')
def to_msgpack(path_or_buf, *args, **kwargs):
"""
msgpack (serialize) object to input file path
THIS IS AN EXPERIMENTAL LIBRARY and the storage format
may not be stable until a future release.
Parameters
----------
path_or_buf : string File path, buffer-like, or None
if None, return generated string
args : an object or objects to serialize
encoding: encoding for unicode objects
append : boolean whether to append to an existing msgpack
(default is False)
compress : type of compressor (zlib or blosc), default to None (no
compression)
"""
global compressor
compressor = kwargs.pop('compress', None)
if compressor:
compressor = u(compressor)
append = kwargs.pop('append', None)
if append:
mode = 'a+b'
else:
mode = 'wb'
def writer(fh):
for a in args:
fh.write(pack(a, **kwargs))
path_or_buf = _stringify_path(path_or_buf)
if isinstance(path_or_buf, compat.string_types):
with open(path_or_buf, mode) as fh:
writer(fh)
elif path_or_buf is None:
buf = compat.BytesIO()
writer(buf)
return buf.getvalue()
else:
writer(path_or_buf)
def __init__(self, filepath_or_buffer, index=None, encoding='ISO-8859-1',
chunksize=None):
self._encoding = encoding
self._lines_read = 0
self._index = index
self._chunksize = chunksize
if isinstance(filepath_or_buffer, str):
filepath_or_buffer, encoding, compression = get_filepath_or_buffer(
filepath_or_buffer, encoding=encoding)
if isinstance(filepath_or_buffer, (str, compat.text_type, bytes)):
self.filepath_or_buffer = open(filepath_or_buffer, 'rb')
else:
# Copy to BytesIO, and ensure no encoding
contents = filepath_or_buffer.read()
try:
contents = contents.encode(self._encoding)
except:
pass
self.filepath_or_buffer = compat.BytesIO(contents)
self._read_header()
def get_data(geo, resolution, session):
geo = conv_geo(geo)
resolution = conv_resol(resolution)
response = download_data(geo, resolution, session)
logger.info("Request done")
logger.info("Create stream file")
zip_data = compat.BytesIO(response.content)
logger.info("Creating a DataFrame per symbol")
d = {}
cols = None
with ZipFile(zip_data, 'r') as zf:
filelist = zf.filelist
df_info = pd.DataFrame(filelist)
df_info['filename'] = df_info[0].map(lambda x: x.filename)
df_info['file_size'] = df_info[0].map(lambda x: x.file_size)
df_info['date_time'] = df_info[0].map(
lambda x: datetime.datetime(*x.date_time))
del df_info[0]
for zinfo in filelist:
filename = zinfo.filename
filename_short, filename_ext = os.path.splitext(filename)
with zf.open(filename) as zfile:
if filename_ext.lower() == '.txt':
file_exchange = filename.split('/')[3]
file_symbol = os.path.split(filename_short)[-1].upper()
logger.info(
"Building DataFrame for '%s' at '%s' from '%s' (%.1f)"
% (file_symbol, file_exchange, filename,
float(zinfo.file_size) / 1024))
if zinfo.file_size > 0:
try:
if resolution == 'd':
df = pd.read_csv(zfile, parse_dates=0)
else:
df = pd.read_csv(zfile, parse_dates=[[0, 1]])
df = df.rename(columns={'Date_Time': 'Date'})
df = df.set_index('Date')
df['Exchange'] = file_exchange
d[file_symbol] = df
if cols is None:
cols = df.columns
except KeyboardInterrupt:
logger.error("CTRL+C was pressed - exit")
break
except Exception as e:
logger.error(
"Can't build DataFrame for '%s' at '%s' from '%s'"
% (file_symbol, file_exchange,
filename.replace(' ', '\ ')))
logger.error(traceback.format_exc())
d[file_symbol] = None
df['Exchange'] = file_exchange
else:
logger.error(
"Can't build DataFrame for '%s' at '%s' from '%s' (empty file)"
% (file_symbol, file_exchange,
filename.replace(' ', '\ ')))
d[file_symbol] = None
df['Exchange'] = file_exchange
logger.info("Create Panel from DataFrame")
panel = pd.Panel(d)
panel = panel.transpose(2, 1, 0)
panel.major_axis = panel.major_axis.map(lambda n: pd.to_datetime(str(n)))
return (panel, df_info)
