What’s new

All major updates to Sciris are documented here.

By import convention, components of the Sciris library are listed beginning with sc., e.g. sc.odict().

Version 2.0.4 (2022-10-25)

  1. sc.stackedbar() will automatically plot a 2D array as a stacked bar chart.

  2. sc.parallelize() now always tries multiprocess if an exception is encountered and die=False (unless parallelizer already was 'multiprocess').

  3. Added a die argument to sc.save().

  4. Added a prefix argument to sc.urlopen(), allowing e.g. http:// to be omitted from the URL.

Version 2.0.3 (2022-10-24)

  1. Added sc.linregress() as a simple way to perform linear regression (fit a line of best fit).

  2. Improved sc.printarr() formatting.

  3. Reverted incompatibility with older Matplotlib versions introduced in version 2.0.2.

Version 2.0.2 (2022-10-22)

Parallelization

  1. The default parallelizer has been changed from multiprocess to concurrent.futures. The latter is faster, but less robust (e.g., it can’t parallelize lambda functions). If an error is encountered, it will automatically fall back to the former.

  2. For debugging, instead of sc.parallelize(..., serial=True), you can also now use sc.parallelize(..., parallelizer='serial').

  3. Arguments to sc.parallelize() are now no longer usually deepcopied, since usually they are automatically during the pickling/unpickling process. However, deepcopying has been retained for serial and thread parallelizers; to not deepcopy, use e.g. parallelizer='thread-nocopy'.

Bugfixes

  1. sc.autolist() now correctly handles input arguments, and can be added on to other objects. (Previously, if an object was added to an sc.autolist, it would itself become an sc.autolist.)

  2. sc.cat() now has the same default behavior as np.concatenate() for 2D arrays (i.e., concatenating rows). Use sc.cat(.., axis=None) for the previous behavior.

  3. sc.dataframe.from_dict() and sc.dataframe.from_records() now return an sc.dataframe object (previously they returned a pd.DataFrame object).

Other changes

  1. sc.dataframe.cat() will concatenate multiple objects (dataframes, arrays, etc.) into a single dataframe.

  2. sc.dataframe().concat() now by default does not modify in-place.

  3. Colormaps are now also available with a sciris- prefix, e.g. sciris-alpine, as well as their original names (to avoid possible name collisions).

  4. Added packaging as a dependency and removed the (deprecated) minimal install option.

Version 2.0.1 (2022-10-21)

New features

  1. sc.asciify() converts a Unicode input string to the closest ASCII equivalent.

  2. sc.dataframe().disp() flexibly prints a dataframe (by default, all rows/columns).

Improvements

  1. sc.findinds() now allows a wider variety of numeric-but-non-array inputs.

  2. sc.sanitizefilename() now handles more characters, including Unicode, and has many new options.

  3. sc.odict() now allows you to delete by index instead of key.

  4. sc.download() now creates folders if they do not already exist.

  5. sc.checktype(obj, 'arraylike') now returns True for pandas Series objects.

  6. sc.promotetoarray() now converts pandas Series or DataFrame objects into arrays.

  7. sc.savetext() can now save arrays (like np.savetxt()).

Bugfixes

  1. Fixed a bug with addition (concatenation) for sc.autolist().

  2. Fixed a bug with the _copy argument for sc.mergedicts() being ignored.

  3. sc.checkmem() no longer uses compression, giving more accurate estimates.

  4. Fixed a bug with sc.options() setting the plot style automatically; a 'default' style was also added that restores Matplotlib defaults (which is now the Sciris default as well; use 'sciris' or 'simple' for the Sciris style).

  5. Fixed a bug with packaging.version not being found on some systems.

  6. Fixed an issue with colormaps attempting to be re-registered, which caused warnings.

Version 2.0.0 (2022-08-18)

This version contains a number of major improvements, including:

  1. New functions: new functions for downloading (sc.download()), paths (sc.rmpath()), and data handling (sc.loadyaml()) have been added.

  2. Better parallelization: sc.parallel() now allows more flexibility in choosing the pool, including concurrent.futures. There’s a new sc.resourcemonitor() for monitoring or limiting resources during big runs.

  3. Improved dataframe: sc.dataframe() is now implemented as an extension of a pandas DataFrame.

New features

  1. sc.resourcemonitor() provides memory or CPU limits, as well as monitors running processes.

  2. sc.download() downloads multiple files in parallel.

  3. sc.rmpath() removes both files and folders, with an optional interactive mode.

  4. sc.ispath() is an alias for isinstance(obj, pathlib.Path).

  5. sc.loadyaml() and sc.saveyaml() load and save YAML files, respectively.

  6. sc.loadzip() extracts (or reads data from) zip files.

  7. sc.count() counts the number of matching elements in an array (similar to np.count_nonzero(), but more flexible with e.g. float vs. int mismatches).

  8. sc.rmnans() and sc.fillnans() have been added as aliases of sc.sanitize() with default options.

  9. sc.strsplit() will automatically split common types of delimited strings (e.g. sc.strsplit('a b c')).

  10. sc.parse_env() parses environment variables into common types (e.g., will interpret 'False' as False).

  11. sc.LazyModule() handles lazily loaded modules (see sc.importbyname() for usage).

  12. sc.randsleep() sleeps for a nondeterministic period of time.

Bugfixes

  1. sc.mergedicts() now handles keyword arguments (previously they were silently ignored). Non-dict inputs also now raise an error by default rather than being silently ignored (except for None).

  2. sc.savespreadsheet() now allows NaNs to be saved.

  3. sc.loadspreadsheet() has been updated to match current pd.read_excel() syntax.

  4. Spreadsheet objects no longer pickle the binary spreadsheet (in some cases reducing size by 50%).

  5. File-saving functions now have a sanitizepath argument (previously, some used file path sanitization and others didn’t). They also now return the full path of the saved file.

Improvements

Major

  1. If a copy/deepcopy is not possible, sc.cp()/sc.dcp() now raise an exception by default (previously, they silenced it).

  2. sc.dataframe() has been completely revamped, and is now a backwards-compatible extension of pd.DataFrame().

  3. sc.parallelize() now supports additional parallelization options, e.g. concurrent.futures, and new maxcpu/maxmem arguments.

Time/date

  1. sc.timer() now has plot() and total() methods, as well as indivtimings and cumtimings properties. It also has new methods tocout() and ttout(), which return output by default (rather than print a string).

  2. sc.daterange() now accepts datedelta arguments, e.g. sc.daterange('2022-02-22', weeks=2).

  3. sc.date() can now read np.datetime64 objects.

Plotting

  1. sc.animation() now defaults to ffmpeg for saving.

  2. sc.commaticks() can now set both x and y axes in a single call.

  3. sc.savefig() by default now creates folders if they don’t exist.

  4. sc.loadmetadata() can now read metadata from JPG files.

Math

  1. sc.findinds() can now handle multiple inputs, e.g. sc.findinds(data>0.1, data<0.5).

  2. sc.checktype() now includes boolean arrays as being arraylike, and has a new 'bool' option.

  3. sc.sanitize() can now handle multidimensional arrays.

Files

  1. sc.urlopen() can now save to files.

  2. sc.savezip() can now save data to zip files (instead of just compressing files).

  3. sc.path() is more flexible, including handling None inputs.

  4. sc.Spreadsheet() now has a new() method that creates a blank workbook.

Other

  1. Added dict_keys(), dict_values(), and dict_items() methods for sc.odict().

  2. sc.checkmem() now returns a dictionary of sizes rather than prints to screen.

  3. sc.importbyname() can now load multiple modules, and load them lazily.

  4. sc.prettyobj() and sc.dictobj() now both take either positional or keyword arguments, e.g. sc.prettyobj(a=3) or sc.dictobj({'a':3}).

Housekeeping

  1. pyyaml has been added as a dependency.

  2. Profiling and load balancing functions have beem moved from sc.sc_utils and sc.sc_parallel to a new submodule, sc.sc_profiling.

  3. Most instances of DeprecationWarning have been changed to FutureWarning.

  4. Python 2 compatibility functions (e.g. sc.loadobj2or3()) have been moved to a separate module, sc.sc_legacy, which is no longer imported by default.

  5. Added style and contributing guides.

  6. Added official support for Python 3.7-3.10.

  7. sc.wget() was renamed sc.urlopen().

  8. Sciris now has a “lazy loading” option, which does not import submodules, meaning loading is effectively instant. To use, set the environment variable SCIRIS_LAZY=1, then load submodules via e.g. from sciris import sc_odict as sco.

Regression information

  1. The default for sc.cp() and sc.dcp() changed from die=False to die=True, which may cause previously caught exceptions to be uncaught. For previous behavior, use sc.dcp(..., die=False).

  2. The argument maxload (in sc.loadbalancer(), sc.parallelize(), etc.) has been renamed maxcpu (for consistency with the new maxmem argument).

  3. Previously sc.loadbalancer(maxload=None) was interpreted as a default load limit (0.8); None is now interpreted as no limit.

  4. Legacy load functions have been moved to a separate module and must be used from there, e.g. sc.sc_legacy.loadobj2or3().

Version 1.3.3 (2022-01-16)

Plotting

  1. Added sc.savefig(), which is like pl.savefig() but stores additional metadata in the figure – the file that created the figure, git hash, even the entire contents of pip freeze if desired. Useful for making figures more reproducible.

  2. Likewise, sc.loadmetadata() will load the metadata from a PNG/SVG file saved with sc.savefig().

  3. Added sc.animation() as a more flexible alternative to sc.savemovie(). While sc.savemovie() works directly with Matplotlib artists, sc.animation() works with entire figure objects so if you can plot it, you can animate it.

  4. Split sc.dateformatter() into two: sc.dateformatter() reformats axes that already use dates (e.g. pl.plot(sc.daterange('2022-01-01', '2022-01-31'), pl.rand(31))), while sc.datenumformatter() reformats axes that use numbers (e.g. pl.plot(np.arange(31), pl.rand(31))).

  5. Added flexibility for sc.boxoff() to turn off any sides of the box.

Other changes

  1. Added sc.capture(), which will redirect stdout to a string, e.g. with sc.capture() as txt: print('This will be stored in "txt"'). This is very useful for writing tests against text that is supposed to be printed out.

  2. Added quick aliases for sc.colorize(), e.g. sc.printgreen('This is like print(), but green'). Colors available are red, green, blue, cyan, yellow, magenta.

  3. Keyword arguments are now allowed for sc.mergedicts(), e.g. sc.mergedicts({'a':1}, b=2). Existing keywords have been renamed to start with an underscore, e.g. _strict.

  4. Added an every argument to sc.progressbar(), to not update on every step.

  5. Fixed labeling bugs in several corner cases for sc.timer().

  6. Added an explicit start argument to sc.timedsleep().

  7. Added additional flexibility to sc.getcaller(), including storing the code of the calling line.

Version 1.3.2 (2022-01-13)

  1. Additional flexibility in sc.timer(): it now stores a list of times (timer.timings), allows auto-generated labels (sc.timer(auto=True), and has a new method timer.tt() (short for toctic) that will restart the timer (i.e. time diff rather than cumulative time).

  2. Fixed a bug preventing the label from being passed in timer.toc().

  3. Fixed a bug blocking style=None in sc.dateformatter(), and added an argument to allow using the y axis.

Version 1.3.1 (2022-01-11)

Changes to odict and objdict

  1. Major improvements to sc.odict() performance: key lookup (e.g. my_odict['key']) is ~30% faster, nearly identical to native dict(); integer lookup (my_odict[3]) is now 10-100x faster. This was achieved by caching the keys rather than looking them up each time.

  2. Allow dicts with integer keys to be converted to odicts via the makefrom() method, e.g. sc.odict.makefrom({0:'foo', 1:'bar'}). If an odict has integer keys, then these take precedence.

  3. Added force option to objdict.setattribute() to allow attributes to be set even if they already exist. Added objdict.delattribute() to delete attributes.

  4. Removed the to_OD() method (since dicts preserve order, dict(my_odict) is now much more common).

  5. Made sc.dictobj() a subclass of dict, so isinstance(my_dictobj, dict) is now True.

  6. Added sc.ddict() as an alias to collections.defaultdict().

Plotting

  1. Updated sc.commaticks() to use a more thoughtful number of significant figures.

Printing

  1. Fixed a bug in sc.heading() that printed an extraneous None. Also allows more flexibility in spaces before/after the heading.

  2. Fixed a bug in sc.fonts() that prevented using a Path object. Also added a rebuild argument that rebuilds the Matplotlib font cache (useful when added fonts don’t show up).

  3. Updated sc.colorize() to wrap the ansicolors module, allowing more flexible inputs such as sc.colorize('cat', fg='orange').

  4. Added output argument to sc.pp() which acts as an alias to pprint.pformat().

Other changes

  1. Removed the pkg_resources import, which roughly halves Sciris import time (from 0.3 s to 0.15 s, assuming matplotlib.pyplot is already imported).

  2. Added option to search the source code in sc.help().

  3. Improved the implementations of sc.smooth(), sc.gauss1d(), and sc.gauss2d() to handle different object types and edge cases.

  4. Fixed requirements for minimal install option.

  5. Removed the openpyexcel dependency (falling back to the nearly identical openpyxl).

Version 1.3.0 (2021-12-30)

This version contains a number of major improvements, including:

  1. Better date plotting: sc.dateformatter() has been revamped to provide compact and intuitive date plotting.

  2. Better smoothing: The new functions sc.convolve()/sc.gauss1d()/sc.gauss2d(), and the updated sc.smooth(), provide new options for smoothing data.

  3. Simpler fonts: sc.fonts() can both list fonts and add new ones.

  4. Simpler options: Need a bigger font? Just do sc.options(fontsize=18).

New functions and methods

  1. Added a settings module to quickly set both Sciris and Matplotlib options; e.g. sc.options(dpi=150) is a shortcut for pl.rc('figure', dpi=150), while e.g. sc.options(aspath=True) will globally set Sciris functions to return Path objects instead of strings.

  2. Added sc.timer() as a simpler and more flexible way of accessing sc.tic()/sc.toc() and sc.Timer().

  3. Added sc.convolve(), a simple fix to np.convolve() that avoids edge effects (see update to sc.smooth() below).

  4. Added sc.gauss1d() and sc.gauss2d() as additional (high-performance) smoothing functions.

  5. Added sc.fonts(), to easily list or add fonts for use in plotting.

  6. Added sc.dictobj(), the inverse of sc.objdict() – an object that acts like a dictionary (instead of a dictionary that acts like an object). Compared to sc.objdict(), sc.dictobj() is lighter-weight and slightly faster but less powerful.

  7. Added sc.swapdict(), a shortcut for swapping the keys and values of a dictionary.

  8. Added sc.loadobj2or3(), for legacy support for loading Python 2 pickles. (Support had been removed in version 1.1.1.)

  9. Added sc.help(), to quickly allow searching of Sciris’ docstrings.

Bugfixes

  1. Fixed edge effects when using sc.smooth() by using sc.convolve() instead of np.convolve().

  2. Fixed a bug with checking types when saving files via sc.save(). (Thanks to Rowan Martin-Hughes.)

  3. Fixed a bug with output=True not being passed correctly for sc.heading().

Improvements

  1. sc.dateformatter() is now an interface to a new formatter for plotting dates (ScirisDateFormatter). This formatter is optimized for aesthetics, combining the best aspects of Matplotlib’s and Plotly’s date formatters. (Thanks to Daniel Klein.)

  2. sc.daterange() now accepts an interval argument.

  3. sc.datedelta() can now return the actual delta rather than just the date.

  4. sc.toc() has more flexible printing options.

  5. sc.Spreadsheet() now keeps a copy of the opened workbook, so there is no need to reopen it for every operation.

  6. sc.commaticks() can now use non-comma separators.

  7. Many other functions had small usability improvements, e.g. input arguments are more consistent and more flexible.

Housekeeping

  1. xlrd has been removed as a dependency; openpyexcel is used instead, with simple spreadsheet loading now done by pandas.

  2. Source files were refactored and split into smaller pieces (e.g. sc_utils.py was split into sc_utils.py, sc_printing.py, sc_datetime.py, sc_nested.py).

Regression information

  1. To restore previous spreadsheet loading behavior, use sc.loadspreadsheet(..., method='xlrd').

  2. To use previous smoothing (with edge effects), use sc.smooth(..., legacy=True)

Version 1.2.3 (2021-08-27)

  1. Fixed a bug with sc.asd() failing for verbose > 1. (Thanks to Nick Scott and Romesh Abeysuriya.)

  2. Added sc.rolling() as a shortcut to pandas’ rolling average function.

  3. Added a die argument to sc.findfirst() and sc.findlast(), to allow returning no indices without error.

Version 1.2.2 (2021-08-21)

New functions and methods

  1. A new class, sc.autolist(), is available to simplify appending to lists, e.g. ls = sc.autolist(); ls += 'not a list'.

  2. Added sc.freeze() as a programmatic equivalent of pip freeze.

  3. Added sc.require() as a flexible way of checking (or asserting) environment requirements, e.g. sc.require('numpy').

  4. Added sc.path() as an alias to pathlib.Path().

Improvements

  1. Added an even more robust unpickler, that should be able to recover data even if exceptions are raised when unpickling.

  2. Updated sc.loadobj() to allow loading standard (not gzipped) pickles and from dill.

  3. Updated sc.saveobj() to automatically swap arguments if the object is supplied first, then the filename.

  4. Updated sc.asd() to allow more flexible argument passing to the optimized function; also updated verbose to allow skipping iterations.

  5. Added a path argument to sc.thisdir() to more easily allow subfolders/files.

  6. Instead of being separate function definitions, sc.load(), sc.save(), and sc.jsonify() are now identical to their aliases (e.g. sc.loadobj()).

  7. sc.dateformatter() now allows a rotation argument, since date labels often collide.

  8. sc.readdate() and sc.date() can now read additional numeric dates, e.g. sc.readdate(16166, dateformat='ordinal').

Backwards-incompatible changes

  1. sc.promotetolist() now converts (rather than wraps) ranges and dict_keys objects to lists. To restore the previous behavior, use the argument coerce='none'.

  2. The start_day argument has been renamed start_date for sc.day() and sc.dateformatter().

  3. The dateformat argument for sc.date() has been renamed outformat, to differentiate from readformat.

Version 1.2.1 (2021-07-07)

  1. Added openpyxl as a Sciris dependency, since it was removed from pandas.

  2. Added sc.datedelta(), a function that wraps datetime.timedelta to easily do date operations on strings, e.g. sc.datedelta('2021-07-07', days=-3) returns '2021-07-04'.

  3. Added additional supported date formats to sc.readdate(), along with new 'dmy' and 'mdy' options to dateformat, to read common day-month-year and month-day-year formats.

  4. Added the ability for sc.compareversions() to handle '<', '>=', etc.

  5. Errors loading pickles from sc.load() are now more informative.

Version 1.2.0 (2021-07-05)

New functions and methods

  1. Added sc.figlayout() as an alias to both fig.set_tight_layout(True) and fig.subplots_adjust().

  2. Added sc.midpointnorm() as an alias to Matplotlib’s TwoSlopeNorm; it can also be used in e.g. sc.vectocolor().

  3. Added sc.dateformatter(), which will (semi-)automatically format the x-axis using dates.

  4. Added sc.getplatform(), sc.iswindows(), sc.islinux(), and sc.ismac(). These are all shortcuts for checking sys.platform output directly.

  5. Added sc.cpu_count() as a simple alias for multiprocessing.cpu_count().

Bugfixes

  1. Fixed sc.checkmem() from failing when an attribute was None.

  2. Fixed a file handle that was being left open by sc.gitinfo().

odict updates

  1. Defined + for sc.odict and derived classes; adding two dictionaries is the same as calling sc.mergedicts() on them.

  2. Updated nested dictionary functions, and added them as methods to sc.odict() and derived classes (like sc.objdict()); for example, you can now do nestedobj = sc.objdict(); nestedobj.setnested(['a','b','c'], 4).

  3. Added sc.odict.enumvalues() as an alias to sc.odict.enumvals().

Plotting updates

  1. Updated sc.commaticks() to use better formatting.

  2. Removed the fig argument from sc.commaticks() and sc.SIticks(); now, the first argument can be an Axes object, a Figure object, or a list of axes.

  3. Updated sc.get_rows_cols() to optionally create subplots, rather than just return the number of rows/columns.

  4. Removed sc.SItickformatter; use sc.SIticks() instead.

Other updates

  1. Updated sc.heading() to handle arguments the same way as print(), e.g. sc.heading([1,2,3], 'is a list').

  2. Allowed more flexibility with the ncpus argument of sc.parallelize(): it can now be a fraction, representing a fraction of available CPUs. Also, it will now never exceed the number of tasks to be run.

  3. Updated sc.suggest() to modify the threshold to be based on the length of the input word.

Version 1.1.1 (2021-03-17)

  1. The implementations of sc.odict() and sc.objdict() have been updated, to allow for more flexible use of the defaultdict argument, including better nesting and subclassing.

  2. A new serial argument has been added to sc.parallelize() to allow for quick debugging.

  3. Legacy support for Python 2 has been removed from sc.loadobj() and sc.saveobj().

  4. A fallback method for sc.gitinfo() (based on gitpython) has been added, in case reading from the filesystem fails.

Version 1.1.0 (2021-03-12)

New functions

  1. sc.mergelists() is similar to sc.mergedicts(): it will take a sequence of inputs and attempt to merge them into a list.

  2. sc.transposelist() will perform a transposition on a list of lists: for example, a list of 10 lists (or tuples) each of length 3 will be transformed into a list of 3 lists each of length 10.

  3. sc.strjoin() and sc.newlinejoin() are shortcuts to ', '.join(items) and '\n'.join(items), respectively. The latter is especially useful inside f-strings since you cannot use the \n character.

Bugfixes

  1. sc.day() now returns a numeric array when an array of datetime objects is passed to it; a bug which was introduced in version 1.0.2 which meant it returned an object array instead.

  2. Slices with numeric start and stop indices have been fixed for sc.odict().

  3. sc.objatt() now correctly handles objects with slots instead of a dict.

Improvements

  1. sc.loadobj() now accepts a remapping argument, which lets the user load old pickle files even if the modules no longer exist.

  2. Most file functions (e.g. sc.makefilepath, sc.getfilelist() now accept an aspath argument, which, if True, will return a pathlib.Path object instead of a string.

  3. Most array-returning functions, such as sc.promotetoarray() and sc.cat(), now accept a copy argument and other keywords; these keywords are passed to np.array(), allowing e.g. the dtype to be set.

  4. A fallback option for sc.findinds() has been implemented, allowing it to work even if the input array isn’t numeric.

  5. sc.odict() now has a defaultdict argument, which lets you use it like a defaultdict as well as an ordered dict.

  6. sc.odict() has a transpose argument for methods like items() and enumvalues(), which will return a tuple of lists instead of a list of tuples.

  7. sc.objdict() now prints out differently, to distinguish it from an sc.odict.

  8. sc.promotetolist() has a new coerce argument, which will convert that data type into a list (instead of wrapping it).

Renamed/removed functions

  1. The functions sc.tolist() and sc.toarray() have been added as aliases of sc.promotetolist() and sc.promotetoarray(), respectively. You may use whichever you prefer.

  2. The skipnone keyword has been removed from sc.promotetoarray() and replaced with keepnone (which does something slightly different).

Other updates

  1. Exceptions have been made more specific (e.g. TypeError instead of Exception).

  2. Test code coverage has been increased significantly (from 63% to 84%).

Version 1.0.2 (2021-03-10)

  1. Fixed bug (introduced in version 1.0.1) with sc.readdate() returning only the first element of a list of a dates.

  2. Fixed bug (introduced in version 1.0.1) with sc.date() treating an integer as a timestamp rather than an integer number of days when a start day is supplied.

  3. Updated sc.readdate(), sc.date(), and sc.day() to always return consistent output types (e.g. if an array is supplied as an input, an array is supplied as an output).

Version 1.0.1 (2021-03-01)

  1. Fixed bug with Matplotlib 3.4.0 also defining colormap 'turbo', which caused Sciris to fail to load.

  2. Added a new function, sc.orderlegend(), that lets you specify the order you want the legend items to appear.

  3. Fixed bug with paths returned by sc.getfilelist(nopath=True).

  4. Fixed bug with sc.loadjson() only reading from a string if fromfile=False.

  5. Fixed recursion issue with printing sc.Failed objects.

  6. Changed sc.approx() to be an alias to np.isclose(); this function may be removed in future versions.

  7. Changed sc.findinds() to call np.isclose(), allowing for greater flexibility.

  8. Changed the repr for sc.objdict() to differ from sc.odict().

  9. Improved sc.maximize() to work on more platforms (but still not inline or on Macs).

  10. Improved the flexiblity of sc.htmlify() to handle tabs and other kinds of newlines.

  11. Added additional checks to sc.prepr() to avoid failing on recursive objects.

  12. Updated sc.mergedicts() to return the same type as the first dict supplied.

  13. Updated sc.readdate() and sc.date() to support timestamps as well as strings.

  14. Updated sc.gitinfo() to try each piece independently, so if it fails on one (e.g., extracting the date) it will still return the other pieces (e.g., the hash).

  15. Pinned xlrd to 1.2.0 since later versions fail to read xlsx files.

Version 1.0.0 (2020-11-30)

This major update (and official release!) includes many new utilities adopted from the Covasim and Atomica libraries, as well as important improvements and bugfixes for parallel processing, object representation, and file I/O.

New functions

Math functions

  1. sc.findfirst() and sc.findlast() return the first and last indices, respectively, of what sc.findinds() would return. These keywords (first and last) can also be passed directly to sc.findinds().

  2. sc.randround() probabilistically rounds numbers to the nearest integer; e.g. 1.2 will round down 80% of the time.

  3. sc.cat() is a generalization of np.append()/np.concatenate() that handles arbitrary types and numbers of inputs.

  4. sc.isarray() checks if the object is a Numpy array.

Plotting functions

  1. A new diverging colormap, 'orangeblue', has been added (courtesy Prashanth Selvaraj). It is rather pretty; you should try it out.

  2. sc.get_rows_cols() solves the small but annoying issue of trying to figure out how many rows and columns you need to plot N axes. It is similar to np.unravel_index(), but allows the desired aspect ratio to be varied.

  3. sc.maximize() maximizes the current figure window.

Date functions

  1. sc.date() will convert practically anything to a date.

  2. sc.day() will convert practically anything to an integer number of days from a starting point; for example, sc.day(sc.now()) returns the number of days since Jan. 1st.

  3. sc.daydiff() computes the number of days between two or more start and end dates.

  4. sc.daterange() returns a list of date strings or date objects between the start and end dates.

  5. sc.datetoyear() converts a date to a decimal year (from Romesh Abeysuriya via Atomica).

Other functions

  1. The “flagship” functions sc.loadobj()/sc.saveobj() now have shorter aliases: sc.load()/sc.save(). These functions can be used interchangeably.

  2. A convenience function, sc.toctic(), has been added that does sc.toc(); sc.tic(), i.e. for sequentially timing multiple blocks of code.

  3. sc.checkram() reports the current process’ RAM usage at the current moment in time; useful for debugging memory leaks.

  4. sc.getcaller() returns the name and line number of the calling function; useful for logging and version control purposes.

  5. sc.nestedloop() iterates over lists in the specified order (from Romesh Abeysuriya via Atomica).

  6. sc.parallel_progress() runs a function in parallel whilst displaying a single progress bar across all processes (from Romesh Abeysuriya via Atomica).

  7. An experimental function, sc.asobj(), has been added that lets any dictionary-like object be used with attributes instead (i.e. foo.bar instead of foo['bar']).

Bugfixes and other improvements

  1. sc.parallelize() now uses the multiprocess library instead of multiprocessing. This update fixes bugs with trying to run parallel processing in certain environments (e.g., in Jupyter notebooks). This function also returns a more helpful error message when running in the wrong context on Windows.

  2. sc.prepr() has been updated to use a simpler method of parsing objects for display; this should be faster and more robust. A default 3 second time limit has also been added.

  3. sc.savejson() now uses an indent of 2 by default, leading to much more human-readable JSON files.

  4. sc.gitinfo() has been updated to use the code from Atomica’s fast_gitinfo() instead (courtesy Romesh Abeysuriya).

  5. sc.thisdir() now no longer requires the __file__ argument to be supplied to get the current folder.

  6. sc.readdate() can now handle a list of dates.

  7. sc.getfilelist() now has more options, such as to return the absolute path or no path, as well as handling file matching patterns more flexibly.

  8. sc.Failed and sc.Empty, which may be encountered when loading a corrupted pickle file, are now exposed to the user (before they could only be accessed via sc.sc_fileio.Failed).

  9. sc.perturb() can now use either uniform or normal perturbations via the normal argument.

Renamed/removed functions

  1. The function sc.quantile() has been removed. Please use np.quantile() instead (though admittedly, it is extremely unlikely you were using it to begin with).

  2. The function sc.scaleratio() has been renamed sc.normsum(), since it normalizes an array by the sum.

Other updates

  1. Module imports were moved to inside functions, improving Sciris loading time by roughly 30%.

  2. All tests were refactored to be in consistent format, increasing test coverage by roughly 50%.

  3. Continuous integration testing was updated to use GitHub Actions instead of Travis/Tox.

Version 0.17.4 (2020-08-11)

  1. sc.profile() and sc.mprofile() now return the line profiler instance for later use (e.g., to extract additional statistics).

  2. sc.prepr() (also used in sc.prettyobj()) can now support objects with slots instead of dicts.

Version 0.17.3 (2020-07-21)

  1. sc.parallelize() now explicitly deep-copies objects, since on some platforms this copying does not take place as part of the parallelization process.

Version 0.17.2 (2020-07-13)

  1. sc.search() is a new function to find nested attributes/keys within objects or dictionaries.

Version 0.17.1 (2020-07-07)

  1. sc.Blobject has been modified to allow more flexibility with saving (e.g., Path objects).

Version 0.17.0 (2020-04-27)

  1. sc.mprofile() has been added, which does memory profiling just like sc.profile().

  2. sc.progressbar() has been added, which prints a progress bar.

  3. sc.jsonpickle() and sc.jsonunpickle() have been added, wrapping the module of the same name, to convert arbitrary objects to JSON.

  4. sc.jsonify() checks objects for a to_json() method, handling e.g Pandas dataframes, and falls back to sc.jsonpickle() instead of raising an exception for unknown object types.

  5. sc.suggest() now uses jellyfish instead of python-levenshtein for fuzzy string matching.

  6. sc.saveobj() now uses protocol 4 instead of the latest by default, to avoid backwards incompatibility issues caused by using protocol 5 (only compatible with Python 3.8).

  7. sc.odict() and related classes now raise sc.KeyNotFoundError exceptions. These are derived from KeyError, but fix a bug in the string representation to allow multi-line error messages.

  8. Rewrote all tests to be pytest-compatible.

Version 0.16.8 (2020-04-11)

  1. sc.makefilepath() now has a checkexists flag, which will optionally raise an exception if the file does (or doesn’t) exist.

  2. sc.sanitizejson() now handles datetime.date and datetime.time.

  3. sc.uuid() and sc.fast_uuid() now work with non-integer inputs, e.g., sc.uuid(n=10e3).

  4. sc.thisdir() now accepts additional arguments, so can be used to form a full path, e.g. sc.thisdir(__file__, 'myfile.txt').

  5. sc.checkmem() has better parsing of objects.

  6. sc.prepr() now lists properties of objects, and has some aesthetic improvements.