Memory-mapped file objects behave like both bytearray and likefile objects. You can use mmap objects in most placeswhere bytearray are expected; for example, you can use the remodule to search through a memory-mapped file. You can also change a singlebyte by doing obj[index]=97, or change a subsequence by assigning to aslice: obj[i1:i2]=b'..'. You can also read and write data starting atthe current file position, and seek() through the file to different positions.

A memory-mapped file is created by the mmap constructor, which isdifferent on Unix and on Windows. In either case you must provide a filedescriptor for a file opened for update. If you wish to map an existing Pythonfile object, use its fileno() method to obtain the correct value for thefileno parameter. Otherwise, you can open the file using theos.open() function, which returns a file descriptor directly (the filestill needs to be closed when done).

Note

The Python pickle module is a better choice for all the remaining use cases. If you don’t need a human-readable format or a standard interoperable format, or if you need to serialize custom objects, then go with pickle. Inside the Python pickle Module. The Python pickle module basically consists of four methods. As of 2/1/2021 Python 3.4 and 3.5 is deprecated. Python 2.7 was deprecated by the Python Software Foundation on January 1, 2020. Going forward, customers using the AWS CLI version 1 should transition to using Python 3, with a minimum of Python 3.6. Under the “Python Releases for Mac OS X” heading, click the link for the Latest Python 3 Release - Python 3.x.x. As of this writing, the latest version was Python 3.8.4. Scroll to the bottom and click macOS 64-bit installer to start the download. When the installer is finished downloading, move on to the next step. Step 2: Run the Installer.

If you want to create a memory-mapping for a writable, buffered file, youshould flush() the file first. This is necessary to ensurethat local modifications to the buffers are actually available to themapping.

For both the Unix and Windows versions of the constructor, access may bespecified as an optional keyword parameter. access accepts one of fourvalues: ACCESS_READ, ACCESS_WRITE, or ACCESS_COPY tospecify read-only, write-through or copy-on-write memory respectively, orACCESS_DEFAULT to defer to prot. access can be used on both Unixand Windows. If access is not specified, Windows mmap returns awrite-through mapping. The initial memory values for all three access typesare taken from the specified file. Assignment to an ACCESS_READmemory map raises a TypeError exception. Assignment to anACCESS_WRITE memory map affects both memory and the underlying file.Assignment to an ACCESS_COPY memory map affects memory but does notupdate the underlying file.

Changed in version 3.7: Added ACCESS_DEFAULT constant.

To map anonymous memory, -1 should be passed as the fileno along with the length.

class mmap.mmap(fileno, length, tagname=None, access=ACCESS_DEFAULT[, offset])

(Windows version) Maps length bytes from the file specified by thefile handle fileno, and creates a mmap object. If length is largerthan the current size of the file, the file is extended to contain lengthbytes. If length is 0, the maximum length of the map is the currentsize of the file, except that if the file is empty Windows raises anexception (you cannot create an empty mapping on Windows).

tagname, if specified and not None, is a string giving a tag name forthe mapping. Windows allows you to have many different mappings againstthe same file. If you specify the name of an existing tag, that tag isopened, otherwise a new tag of this name is created. If this parameter isomitted or None, the mapping is created without a name. Avoiding theuse of the tag parameter will assist in keeping your code portable betweenUnix and Windows.

offset may be specified as a non-negative integer offset. mmap referenceswill be relative to the offset from the beginning of the file. offsetdefaults to 0. offset must be a multiple of the ALLOCATIONGRANULARITY.

Raises an auditing eventmmap.__new__ with arguments fileno, length, access, offset.

class mmap.mmap(fileno, length, flags=MAP_SHARED, prot=PROT_WRITE PROT_READ, access=ACCESS_DEFAULT[, offset])

(Unix version) Maps length bytes from the file specified by the filedescriptor fileno, and returns a mmap object. If length is 0, themaximum length of the map will be the current size of the file whenmmap is called.

flags specifies the nature of the mapping. MAP_PRIVATE creates aprivate copy-on-write mapping, so changes to the contents of the mmapobject will be private to this process, and MAP_SHARED creates amapping that’s shared with all other processes mapping the same areas ofthe file. The default value is MAP_SHARED.

prot, if specified, gives the desired memory protection; the two mostuseful values are PROT_READ and PROT_WRITE, to specifythat the pages may be read or written. prot defaults toPROT_READPROT_WRITE.

access may be specified in lieu of flags and prot as an optionalkeyword parameter. It is an error to specify both flags, prot andaccess. See the description of access above for information on how touse this parameter.

offset may be specified as a non-negative integer offset. mmap referenceswill be relative to the offset from the beginning of the file. offsetdefaults to 0. offset must be a multiple of ALLOCATIONGRANULARITYwhich is equal to PAGESIZE on Unix systems.

To ensure validity of the created memory mapping the file specifiedby the descriptor fileno is internally automatically synchronizedwith physical backing store on Mac OS X and OpenVMS.

Update python to 3.7 mac

This example shows a simple way of using mmap:

mmap can also be used as a context manager in a withstatement:

New in version 3.2: Context manager support.

The next example demonstrates how to create an anonymous map and exchangedata between the parent and child processes:

Raises an auditing eventmmap.__new__ with arguments fileno, length, access, offset.

Memory-mapped file objects support the following methods:

close()

Closes the mmap. Subsequent calls to other methods of the object willresult in a ValueError exception being raised. This will not closethe open file.

closed

True if the file is closed.

New in version 3.2.

find(sub[, start[, end]])

Returns the lowest index in the object where the subsequence sub isfound, such that sub is contained in the range [start, end].Optional arguments start and end are interpreted as in slice notation.Returns -1 on failure.

Changed in version 3.5: Writable bytes-like object is now accepted.

flush([offset[, size]])

Flushes changes made to the in-memory copy of a file back to disk. Withoutuse of this call there is no guarantee that changes are written back beforethe object is destroyed. If offset and size are specified, onlychanges to the given range of bytes will be flushed to disk; otherwise, thewhole extent of the mapping is flushed. offset must be a multiple of thePAGESIZE or ALLOCATIONGRANULARITY.

None is returned to indicate success. An exception is raised when thecall failed.

Changed in version 3.8: Previously, a nonzero value was returned on success; zero was returnedon error under Windows. A zero value was returned on success; anexception was raised on error under Unix.

madvise(option[, start[, length]])

Send advice option to the kernel about the memory region beginning atstart and extending length bytes. option must be one of theMADV_* constants available on the system. Ifstart and length are omitted, the entire mapping is spanned. Onsome systems (including Linux), start must be a multiple of thePAGESIZE.

Availability: Systems with the madvise() system call.

move(dest, src, count)

Copy the count bytes starting at offset src to the destination indexdest. If the mmap was created with ACCESS_READ, then calls tomove will raise a TypeError exception.

read([n])

Return a bytes containing up to n bytes starting from thecurrent file position. If the argument is omitted, None or negative,return all bytes from the current file position to the end of themapping. The file position is updated to point after the bytes that werereturned.

Women with money pdf free download free. After her death, while family members extolled her virtues, claimants to her estate painted a different picture: of a prostitute, the mother of George Washington's illegitimate son, and a wife who ruthlessly defrauded her husband and perhaps even plotted his death.

Changed in version 3.3: Argument can be omitted or None.

read_byte()

Returns a byte at the current file position as an integer, and advancesthe file position by 1.

readline()

Returns a single line, starting at the current file position and up to thenext newline. The file position is updated to point after the bytes that werereturned.

resize(newsize)

Resizes the map and the underlying file, if any. If the mmap was createdwith ACCESS_READ or ACCESS_COPY, resizing the map willraise a TypeError exception.

rfind(sub[, start[, end]])

Returns the highest index in the object where the subsequence sub isfound, such that sub is contained in the range [start, end].Optional arguments start and end are interpreted as in slice notation.Returns -1 on failure.

Changed in version 3.5: Writable bytes-like object is now accepted.

seek(pos[, whence])

Set the file’s current position. whence argument is optional anddefaults to os.SEEK_SET or 0 (absolute file positioning); othervalues are os.SEEK_CUR or 1 (seek relative to the currentposition) and os.SEEK_END or 2 (seek relative to the file’s end).

size()

Return the length of the file, which can be larger than the size of thememory-mapped area.

tell()

Returns the current position of the file pointer.

write(bytes)

Write the bytes in bytes into memory at the current position of thefile pointer and return the number of bytes written (never less thanlen(bytes), since if the write fails, a ValueError will beraised). The file position is updated to point after the bytes thatwere written. If the mmap was created with ACCESS_READ, thenwriting to it will raise a TypeError exception.

Changed in version 3.5: Writable bytes-like object is now accepted.

Changed in version 3.6: The number of bytes written is now returned.

write_byte(byte)

Write the integer byte into memory at the currentposition of the file pointer; the file position is advanced by 1. Ifthe mmap was created with ACCESS_READ, then writing to it willraise a TypeError exception.

MADV_* Constants¶

mmap.MADV_NORMAL
mmap.MADV_RANDOM
mmap.MADV_SEQUENTIAL
mmap.MADV_WILLNEED
mmap.MADV_DONTNEED
mmap.MADV_REMOVE
mmap.MADV_DONTFORK
mmap.MADV_DOFORK
mmap.MADV_HWPOISON
mmap.MADV_MERGEABLE
mmap.MADV_UNMERGEABLE
mmap.MADV_SOFT_OFFLINE
mmap.MADV_HUGEPAGE
mmap.MADV_NOHUGEPAGE
mmap.MADV_DONTDUMP
mmap.MADV_DODUMP
mmap.MADV_FREE
mmap.MADV_NOSYNC
mmap.MADV_AUTOSYNC
mmap.MADV_NOCORE
mmap.MADV_CORE
mmap.MADV_PROTECT

These options can be passed to mmap.madvise(). Not every option willbe present on every system.

Availability: Systems with the madvise() system call.

The easiest way to install statsmodels is to install it as part of the Anacondadistribution, a cross-platform distribution for data analysis and scientificcomputing. This is the recommended installation method for most users.

Instructions for installing from PyPI, source or a development version are also provided.

Python Support¶

statsmodels supports Python 3.6, 3.7 and 3.8.

Anaconda¶

statsmodels is available through conda provided byAnaconda. The latest release canbe installed using:

PyPI (pip)¶

To obtain the latest released version of statsmodels using pip:

Follow this link to our PyPI page to directlydownload wheels or source.

For Windows users, unofficial recent binaries (wheels) are occasionallyavailable here.

Update Python To 3.7 Macos

Obtaining the Source¶

We do not release very often but the master branch of our source code isusually fine for everyday use. You can get the latest source from ourgithub repository. Or if youhave git installed:

If you want to keep up to date with the source on github just periodically do:

in the statsmodels directory.

Installation from Source¶

You will need a C compiler installed to build statsmodels. If you are buildingfrom the github source and not a source release, then you will also needCython. You can follow the instructions below to get a C compiler setup forWindows.

If your system is already set up with pip, a compiler, and git, you can try:

If you do not have pip installed or want to do the installation more manually,you can also type:

Or even more manually

statsmodels can also be installed in develop mode which installs statsmodelsinto the current python environment in-place. The advantage of this is thatedited modules will immediately be re-interpreted when the python interpreterrestarts without having to re-install statsmodels.

Compilers¶

Linux¶

Update Python 3.7 To 3.8 Mac

If you are using Linux, we assume that you are savvy enough to install gcc onyour own. More than likely, it is already installed.

Upgrade Python To 3.7 Mac Terminal

Windows¶

It is strongly recommended to use 64-bit Python if possible.

Getting the right compiler is especially confusing for Windows users. Over time,Python has been built using a variety of different Windows C compilers.This guide should helpclarify which version of Python uses which compiler by default.

Upgrade Python 2.7 To 3.7 Macos

Mac¶

Installing statsmodels on MacOS requires installing gcc which providesa suitable C compiler. We recommend installing Xcode and the Command LineTools.

Dependencies¶

The current minimum dependencies are:

  • Python >= 3.6

  • NumPy >= 1.15

  • SciPy >= 1.2

  • Pandas >= 0.23

  • Patsy >= 0.5.1

Cython is required to build from a git checkout but not to run or install from PyPI:

  • Cython >= 0.29 is required to build the code fromgithub but not from a source distribution.

Given the long release cycle, statsmodels follows a loose time-based policy fordependencies: minimal dependencies are lagged about one and a half to twoyears. Our next planned update of minimum versions is expected in the firsthalf of 2020.

Optional Dependencies¶

  • cvxopt is required for regularized fitting ofsome models.

  • Matplotlib >= 2.2 is needed for plottingfunctions and running many of the examples.

  • If installed, X-12-ARIMA orX-13ARIMA-SEATS can be usedfor time-series analysis.

  • pytest is required to runthe test suite.

  • IPython >= 5.0 is required to build thedocs locally or to use the notebooks.

  • joblib >= 0.9 can be used to accelerate distributedestimation for certain models.

  • jupyter is needed to run the notebooks.