# Version 1.26.1 [2022-05-28]

## Miscellaneous

 * TESTS: `R CMD check --as-cran` on R-devel and MS Windows would
   trigger a NOTE on "Check: for detritus in the temp directory" and
   "Found the following files/directories: 'Rscript1349cb8aeeba0'
   ...". There were two package tests that explicitly created PSOCK
   cluster without stopping them. A third test launched multisession
   future without resolving it, which prevented the PSOCK worker to
   terminate. This was not detected in R 4.2.0.  It is not a problem
   on macOS and Linux, because there background workers are
   automatically terminated when the main R session terminates.
   

# Version 1.26.0 [2022-05-27]

## Significant Changes

 * R options and environment variables are now reset on the workers
   after future is resolved as they were after any packages required
   by the future has been loaded and attached. Previously, they were
   reset to what they were before these were loaded and attached. In
   addition, only pre-existing R options and environment variables are
   reset. Any new ones added are not removed for now, because we do
   not know which added R options or environment variables might have
   been added from loading a package and that are essential for that
   package to work.

 * If it was changed while evaluating the future expression, the
   current working directory is now reset when the future has been
   resolved.

## New Features

 * `futureSessionInfo()` gained argument `anonymize`. If TRUE (default),
   host and user names are anonymized.

 * `futureSessionInfo()` now also report on the main R session details.

## Bug Fixes

 * The bug fix in **future** 1.22.0 that addressed the issue where object
   `a` in `future(fcn(), globals = list(a = 42, fcn = function() a))`
   would not be found has been redesigned in a more robust way.

 * Use of packages such as **data.table** and **ff** in cluster and
   multisession futures broke in **future** 1.25.0. For **data.table**, we
   saw "Error in setalloccol(ans) : verbose must be TRUE or FALSE".
   For **ff**, we saw "Error in splitted$path[nopath] <-
   getOption("fftempdir") : replacement has length zero".
   See 'Significant Changes' for why and how this was fixed.

 * The deprecation warning for using `local = FALSE` was silenced for
   sequential futures since **future** 1.25.0.

 * `futureCall()` ignored arguments `stdout`, `conditions`, `earlySignal`,
   `label`, and `gc`.

## Deprecated and Defunct

 * Strategy 'transparent' was deprecated in **future** 1.24.0 and is now
   defunct. Use `plan(sequential, split = TRUE)` instead.

 * Strategy 'multiprocess' was deprecated in **future** 1.20.0, and
   'remote' was deprecated in **future** 1.24.0.  Since then, attempts to
   use them in `plan()` would produce a deprecation warning, which was
   limited to one per R session.  Starting with this release, this
   warning is now produced whenever using `plan()` with these
   deprecated future strategies.


# Version 1.25.0 [2022-04-23]

## Significant Changes

 * R options and environment variables are now reset on the workers
   after future is resolved so that any changes to them by the future
   expression have no effect on following futures.

## New Features

 * Now `f <- future(..., stdout = structure(TRUE, drop = TRUE))` will
   cause the captured standard output to be dropped from the future
   object as soon as it has been relayed once, for instance, by
   `value(f)`. Similarly, `conditions = structure("conditions", drop =
   TRUE)` will drop captured non-error conditions as soon as they have
   been relayed.  This can help decrease the amount of memory used,
   especially if there are many active futures.

 * Now `resolve()` respects option `future.wait.interval`. Previously,
   it was hardcoded to poll for results every 0.1 seconds.

## Beta Features

  * Now, `value()` will only attempt to recover UTF-8 symbols in the
    captured standard output if the future was evaluated on an MS
    Windows that does not support capturing of UTF-8 symbols. Support
    for UTF-8 capturing on also MS Windows was added in R 4.2.0, but
    it typically requires an up-to-date MS Windows 10 or MS Windows
    Server 2022.

## Performance

 * The default value for option `future.wait.interval` was decreased
   from 0.2 seconds to 0.01 seconds. This controls the polling
   frequency for finding an available worker when all workers are
   currently busy. Starting with this release, this option also
   controls the polling frequency of `resolve()`.

## Bug Fixes

 * A bug was introduced in **future** 1.24.0 [2022-02-19] that caused
   future plan tweaking to break, e.g. `plan(multicore, workers = 2)`
   and `plan(sequential, split = TRUE)` introduced breaking side
   effects to the futures evaluated.


# Version 1.24.0 [2022-02-19]

## Significant Changes

 * Now `future(..., seed = TRUE)` forwards the RNG state in the calling R
   session. Previously, it would leave it intact.

## New Features

 * Now `plan()` and `tweak()` preserve calls in arguments, e.g. `plan(multisession, workers = 2, rscript_startup = quote(options(socketOptions="no-delay")))`,
   and `tweak(..., abc = quote(x == y))`.

## Bug Fixes

 * `nbrOfFreeWorkers()` would produce "Error: 'is.character(name)' is not TRUE"
   for `plan(multisession, workers = 1)`.

 * Internal calls to `FutureRegistry(action = "collect-first")` and
   `FutureRegistry(action = "collect-last")` could signal errors early
   when polling `resolved()`.

## Deprecated and Defunct

 * Strategy 'remote' is deprecated in favor of 'cluster'.  The `plan()` function
   will give an informative deprecation warning when 'remote' is used.
   For now, this warning is given only once per R session.

 * Strategy 'transparent' is deprecated in favor of 'sequential' with argument
   `split = TRUE` set.  The `plan()` function will give an informative
   deprecation warning when 'transparent' is used.  For now, this warning is
   given only once per R session.


# Version 1.23.0 [2021-10-30]

## Significant Changes

 * `plan()` now produces a one-time warning if a 'transparent' strategy is set.
   The warning reminds the user that 'transparent' should only be used for
   troubleshooting purposes and never be used in production. These days
   `plan(sequential, split = TRUE)` together with `debug()` is probably a better
   approach for troubleshooting. The long-term plan is to deprecate the
   'transparent' strategy.

 * Support for `persistent = TRUE` with multisession futures is defunct.

## Beta Features

 * UTF-8 symbols outputted on MS Windows would be relayed as escaped symbols,
   e.g. a UTF-8 check mark symbol (`\u2713`) would be relayed as `<U+2713>`
   (8 characters).  The reason for this is a limitation in R itself on MS
   Windows.  Now, `value()` attempts to recover such MS Windows output to UTF-8
   before relaying it.  There is an option for disabling this new feature.

## Miscellaneous

 * TESTS: Using more robust emulation of crashed forked parallel workers
   after understanding that `quit()` must not be used in forked R processes.

## Bug Fixes

 * Now `future(..., seed)` will set the random seed as late as possible just
   before the future expression is evaluated.  Previously it was done before
   package dependencies where attached, which could lead to non-reproduce
   random numbers in case a package dependency would update the RNG seed
   when attached.

## Deprecated and Defunct

 * `values()`, which has been deprecated since **future** 1.20.0, is now defunct.
   Use `value()` instead.

 * Support for `persistent = TRUE` with multisession futures is defunct.  If
   still needed, a temporary workaround is to use cluster futures. However,
   it is likely that support for `persistent` will eventually be deprecated
   for all future backends.

 * Argument `value` of `resolve()`, deprecated since **future** 1.15.0, is defunct
   in favor of argument `result`.
   

# Version 1.22.1 [2021-08-11]

## Miscellaneous

 * Disable package test that emulates crashing of forked parallel workers when
   using `parallel::makeCluster(..., type = "FORK")`.  This test is disabled on
   macOS, where it appears that the main R session becomes unstable after the
   FORK node is terminated.
 

# Version 1.22.0 [2021-08-11]

## Significant Changes

 * A lazy future remains a generic future until it is launched, which means
   it is not assigned a future backend class until launched.

 * Argument `seed` for `futureAssign()` and `futureCall()` now defaults to FALSE
   just like for `future()`.

 * `R_FUTURE_*` environment variables are now only read when the **future**
   package is loaded, where they set the corresponding `future.*` option.
   Previously, some of these environment variables were queried by different
   functions as a fallback to when an option was not set.  By only parsing
   them when the package is loaded, it decrease the overhead in functions,
   and it clarifies that options can be changed at runtime whereas environment
   variables should only be set at startup.

## Performance

 * The overhead of initiating futures have been significantly reduced.  For
   example, the roundtrip time for `value(future(NULL))` is about twice as fast
   for 'sequential', 'cluster', and 'multisession' futures.  For 'multicore'
   futures the roundtrip speedup is about 20%.
   The speedup comes from pre-compiling the R expression that will be used
   to resolve the future expression into R expression templates which then
   can quickly compiled for each future. This speeds up the creation of
   these expression by ~10 times, compared when re-compiling them each time.

 * The default timeout for `resolved()` was decreased from 0.20 to 0.01 seconds
   for cluster/multisession and multicore futures, which means they will
   spend less time waiting for results when they are not available.

## New Features

 * Analogously to how globals may be scanned for "non-exportable" objects when
   option `future.globals.onReference` is set to `"error"` or `"warning"`, `value()`
   will now check for similar problems in the resolved value object.  An
   example of this is `f <- future(xml2::read_xml("<body></body>"))`, which
   will result in an invalid `xml_document` object if run in parallel, because
   such objects cannot be transferred between R processes.

 * In addition to specify which condition classes to be captured and relayed,
   it is now possible to also specify condition classes to be ignored.  For
   example, `conditions = structure("condition", exclude = "message")` captures
   all conditions but message conditions.

 * Now cluster futures use `homogeneous = NULL` as the default instead of
   `homogeneous = TRUE`.  The new default will result in the **parallelly**
   package trying to infer whether TRUE or FALSE should be used based on
   the `workers` argument.

 * Now the the post-mortem analysis report of multicore and cluster futures
   in case their results could not be retrieved include information on
   globals and their sizes, and if some of them are non-exportable.
   A similar, detailed report is also produced when a cluster future fails
   to set up and launch itself on a parallel worker.

 * if option `future.fork.multithreading.enable` is FALSE, **RcppParallel**,
   in addition to **OpenMP**, is forced to run with a single threaded whenever
   running in a forked process (='multicore' futures).  This is done by setting
   environment variable `RCPP_PARALLEL_NUM_THREADS` to 1.

 * Add `futureSessionInfo()` to get a quick overview of the future framework,
   its current setup, and to run simple tests on it.

 * Now `plan(multicore)` warns immediately if multicore processing, that is,
   forked processing, is not supported, e.g. when running in the RStudio
   Console.

## Bug Fixes

 * `plan(multiprocess, workers = n)` did not warn about 'multiprocess' being
   deprecated when argument `workers` was specified.

 * `getGlobalsAndPackages()` could throw a false error on "Did you mean to 
   create the future within a function? Invalid future expression tries to 
   use global `...` variables that do not exist: <some expression>" when `...`
   is solely part of a formula or used in some S4 generic functions.

 * When enabled, option `future.globals.onReference` could falsely alert on
   'Detected a non-exportable reference (externalptr) in one of the globals
   (<unknown\>) used in the future expression' in globals, e.g. when using
   **future.apply** or **furrr** map-reduce functions when using a 'multisession'
   backend.

 * `future(fcn(), globals = list(a = 42, fcn = function() a))` would
   fail with "Error in fcn() : object 'a' not found" when using
   sequential or multicore futures.  This affected also map-reduce
   calls such as `future.apply::future_lapply(1, function(x) a,
   future.globals = list(a = 42))`.

 * Resolving a 'sequential' future without globals would result in internal
   several `...future.*` objects being written to the calling environment,
   which might be the global environment.

 * Environment variable `R_FUTURE_PLAN` would propagate down with nested
   futures, forcing itself onto also nested future plans.  Now it is unset
   in nested futures, resulting in a sequential future strategy unless
   another was explicitly set by `plan()`.

 * Transparent futures no longer warn about `local = FALSE` being deprecated.
   Although `local = FALSE` is being deprecated, it is still used internally
   by 'transparent' futures for a while longer.  Please do not use
   'transparent' futures in production code and never in a package.

 * `remote()` could produce an error on "object 'homogeneous' not found".

 * `nbrOfFreeWorkers()` for 'cluster' futures assumed that the current plan
   is set to cluster too.


# Version 1.21.0 [2020-12-09]

## New Features

 * In order to handle them conditionally higher up in the call chain, warnings
   and errors produced from using the random number generator (RNG) in a future
   without declaring the intention to use one are now of class `RngFutureWarning`
   and `RngFutureError`, respectively.  Both of these classes inherits from
   `RngFutureCondition`.

 * Now run-time errors from resolving a future take precedence over
   `RngFutureError`:s. That is, `future({ rnorm(1); log("a") }, seed = FALSE)`
   will signal an error 'log("a")' instead of an RNG error when option
   `future.rng.onMisuse` is set to `"error"`.

## Beta Features

 * Add `nbrOfFreeWorkers()` to query how many workers are free to take on futures
   immediately.  Until all third-party future backends have implemented this,
   some backends might produce an error saying it is not yet supported.
   
## Bug Fixes

 * `future(..., seed = TRUE)` with 'sequential' futures would set the RNG kind of
   the parent process.  Now it behaves the same regardless of future backend.

 * Signaling `immediateCondition`:s with 'multicore' could result in "Error in
   save_rds(obj, file) : save_rds() failed to rename temporary save file 
   '/tmp/RtmpxNyIyK/progression21f3f31eadc.rds.tmp' (NA bytes; last modified
   on NA) to '/tmp/RtmpxNyIyK/progression21f3f31eadc.rds' (NA bytes; last 
   modified on NA)".  There was an assertion at the end of the internal
   `save_rds()` function that incorrectly assumed that the target file should
   exist.  However, the file might have already been processed and removed
   by the future in the main R session.     

 * `value()` with both a run-time error and an RNG mistake would signal the RNG
   warning instead of the run-time error when the for-internal-use-only
   argument `signal` was set to FALSE.

 * Due to a mistake introduced in **future** 1.20.0, the package would end up
   assigning a `.packageVersion` object to the global environment when loaded.
 

# Version 1.20.1 [2020-10-30]

## Bug Fixes

 * `future::plan("multisession")` would produce 'Error in if (debug)
   mdebug("covr::package_coverage() workaround ...") : argument is not
   interpretable as logical' if and only if the **covr** package was loaded.


# Version 1.20.0 [2020-10-30]

## Significant Changes

 * Strategy 'multiprocess' is deprecated in favor of either 'multisession' or
   'multicore', depending on operating system and R setup.  The `plan()` function
   will give an informative deprecation warning when 'multiprocess' is used.
   This warning is given only once per R session.

 * Launching R or Rscript with command-line option `--parallel=n`, where n > 1,
   will now use 'multisession' as future strategy.  Previously, it would use
   'multiprocess', which is now deprecated.

 * Support for `local = FALSE` is deprecated.  For the time being, it remains
   supported for 'transparent' futures and 'cluster' futures that use
   `persistent = TRUE`.  However, note that `persistent = TRUE` will also
   deprecated at some point in the future.  These deprecations are required in
   order to further standardize the Future API across various types of parallel
   backends.

 * Now multisession workers inherit the package library path from the main R
   session _when they are created_, that is, when calling `plan(multisession)`.
   To avoid this, use `plan(multisession, rscript_libs = NULL)`, which is an
   argument passed down to `makeClusterPSOCK()`.  With this update, 'sequential',
   'multisession', and 'multicore' futures see the exact same library path.

 * Several functions for managing **parallel**-style processing have been moved
   to a new **parallelly** package.  Specifically, functions `availableCores()`,
   `availableWorkers()`, `supportsMulticore()`, `as.cluster()`, `autoStopCluster()`,
   `makeClusterMPI()`, `makeClusterPSOCK()`, and `makeNodePSOCK()` have been moved.
   None of them are specific to futures per se and are likely useful elsewhere
   too.  Also, having them in a separate, standalone package will speed up the
   process of releasing any updates to these functions.  The code base of the
   **future** package shrunk about 10-15% from this migration.  For backward
   compatibility, the migrated functions remain in this package as re-exports.

## New Features

 * Setting up a future strategy with argument `split = TRUE` will cause the
   standard output and non-error conditions to be split ("tee:d") on the
   worker's end, while still relaying back to the main R session as before.
   This can be useful when debugging with `browse()` or `debug()`, e.g.
   `plan(sequential, split = TRUE)`.  Without it, debug output is not displayed.

 * Now multicore futures relay `immediateCondition`:s in a near-live fashion.

 * It is now possible to pass any arguments that `makeClusterPSOCK()` accepts in
   the call to `plan(cluster, ...)` and `plan(multisession, ...)`.  For instance,
   to set the working directory of the cluster workers to a temporary folder,
   pass argument `rscript_startup = "setwd(tempdir())"`.  Another example is
   `rscript_libs = c(libs, "*")` to prepend the library path on the worker
   with the paths in `libs`.

 * `plan()` and `tweak()` check for even more arguments that must not be set by
   either of them.  Specifically, attempts to adjust the following arguments
   of `future()` will result in an error: `conditions`, `envir`, `globals`,
   `packages`, `stdout`, and `substitute` in addition to already validated
   `lazy` and `seed`.
 
 * `tweak()` now returns a wrapper function that calls the original future
   strategy function with the modified defaults.  Previously, it would make a
   copy of the original function with modified argument defaults.  This new
   approach will make it possible to introduce new future arguments that can
   be modified by `tweak()` and `plan()` without having to update every future
   backend package, e.g. the new `split = TRUE` argument.

## Documentation

 * Add a 'Best Practices for Package Developers' vignette.

 * Add a 'How the Future Framework is Validated' vignette.

## Miscellaneous

 * Harmonizing Future constructor functions to also use `substitute = TRUE`.

## Bug Fixes

 * Since last version, **future** 1.19.1, `future(..., conditions = character(0L))`
   would no longer avoid intercepting conditions as intended; instead, it
   muffles all conditions.  From now on, use `conditions = NULL`.

 * Relaying of `immediateCondition`:s was not near-live for multisession and
   cluster if the underlying PSOCK cluster used `useXDR=FALSE` for communication.

 * `print()` for Future would also print any attributes of its environment.

 * The error message produced by ``nbrOfWorkers()`` was incomplete.
 
 * Renamed environment variable `R_FUTURE_MAKENODEPSOCK_tries` used by
   `makeClusterPSOCK()` to `R_FUTURE_MAKENODEPSOCK_TRIES`.

 * The Mandelbrot demo would produce random numbers without declaring so.

## Deprecated and Defunct

 * Strategy 'multiprocess' is deprecated in favor of either 'multisession' or
   'multicore', depending on operating system and R setup.

 * `values()` is deprecated. Use `value()` instead.

 * All backward compatible code for the legacy, defunct, internal `Future`
   element `value` is now removed.  Using or relying on it is an error.
 

# Version 1.19.1 [2020-09-21]

## Bug Fixes

 * When passing `...` as a globals, rather than via arguments, in higher-level
   map-reduce APIs such as **future.apply** and **furrr**, arguments in `...` could
   produce an error on "unused argument".
   
 
# Version 1.19.0 [2020-09-19]

## Significant Changes

 * Futures detect when random number generation (RNG) was used to resolve them.
   If a future uses RNG without parallel RNG was requested, then an informative
   warning is produced. To request parallel RNG, specify argument `seed`, e.g.
   `f <- future(rnorm(3), seed = TRUE)` or `y %<-% { rnorm(3) } %seed% TRUE`.
   Higher-level map-reduce APIs provide similarly named "seed" arguments to
   achieve the same.  To, escalate these warning to errors, set option
   `future.rng.onMisuse` to `"error"`.  To silence them, set it to `"ignore"`.

 * Now, all non-captured conditions are muffled, if possible.  For instance,
   `future(warning("boom"), conditions = c("message"))` will truly muffle the
   warning regardless of backend used.  This was needed to fix below bug.

## New Features

 * `makeClusterPSOCK()` will now retry to create a cluster node up to `tries`
   (default: 3) times before giving up.  If argument `port` species more than
   one port (e.g. `port = "random"`) then it will also attempt find a valid
   random port up to `tries` times before giving up.  The pre-validation of
   the random port is only supported in R (>= 4.0.0) and skipped otherwise.

 * `makeClusterPSOCK()` skips shell quoting of the elements in `rscript` if it
   inherits from `AsIs`.

 * `makeClusterPSOCK()`, or actually `makeNodePSOCK()`, gained argument `quiet`,
   which can be used to silence output produced by `manual = TRUE`.

 * If multithreading is disabled but multicore futures fail to acknowledge
   the setting on the current system, then an informative `FutureWarning` is
   produced by such futures.

 * Now `availableCores()` better supports Slurm.  Specifically, if environment
   variable `SLURM_CPUS_PER_TASK` is not set, which requires that option
   `--slurm-cpus-per-task=n` is specified and `SLURM_JOB_NUM_NODES=1`, then it
   falls back to using `SLURM_CPUS_ON_NODE`, e.g. when using `--ntasks=n`.

 * Now `availableCores()` and `availableWorkers()` supports LSF/OpenLava.
   Specifically, they acknowledge environment variable `LSB_DJOB_NUMPROC`
   and `LSB_HOSTS`, respectively.

## Performance

 * Now `plan(multisession)`, `plan(cluster, workers = <number>)`, and
   `makeClusterPSOCK()` which they both use internally, sets up localhost
   workers twice as fast compared to versions since **future** 1.12.0, which
   brings it back to par with a bare-bone `parallel::makeCluster(...,
   setup_strategy = "sequential")` setup.  The slowdown was introduced in
   **future** 1.12.0 (2019-03-07) when protection against leaving stray R
   processes behind from failed worker startup was implemented.  This
   protection now makes use of memoization for speedup.

## Bug Fixes

 * Sequential and multicore backends, but not multisession, would produce
   errors on "'...' used in an incorrect context" in cases where `...` was
   part of argument `globals` and not the evaluation environment.

 * Contrary to other future backends, any conditions produced while resolving
   a sequential future using `future(..., conditions = character())` would be
   signaled, although the most reasonable expectation would be that they are
   silenced. Now, all non-captured conditions are muffled, if possible.

 * Option `future.rng.onMisuse` was not passed down to nested futures.
 
 * Disabling multithreading in forked processes by setting R option
   `future.fork.multithreading.enable` or environment variable
   `R_FUTURE_FORK_MULTITHREADING_ENABLE` to `FALSE` would cause multicore
   futures to always return value `1L`.  This bug was introduced in
   **future** 1.17.0 (2020-04-17).

 * `getGlobalsAndPackages()` did not always return a `globals` element that was
   of class `FutureGlobals`.
   
 * `getGlobalsAndPackages(..., globals)` would recalculate `total_size` even
   when it was already calculated or known to be zero.
   
 * `getGlobalsAndPackages(Formula::Formula(~ x))` would produce "the condition
   has length > 1" warnings (which will become errors in future R versions).


# Version 1.18.0 [2020-07-08]

## Significant Changes

 * Support for `persistent = TRUE` with multisession futures is deprecated.

## New Features

 * `print()` on `RichSOCKcluster` gives information not only on the name of the
   host but also on the version of R and the platform of each node ("worker"),
   e.g. "Socket cluster with 3 nodes where 2 nodes are on host 'localhost' (R
   version 4.0.0 (2020-04-24), platform x86_64-w64-mingw32), 1 node is on host
   'n3' (R version 3.6.3 (2020-02-29), platform x86_64-pc-linux-gnu)".

 * Error messages from cluster future failures are now more informative than
   "Unexpected result (of class 'NULL' != 'FutureResult')".  For example, if
   the **future** package is not installed on the worker, then the error message
   clearly says so.  Even, if there is an unexpected result error from a PSOCK
   cluster future, then the error produced give extra information on node where
   it failed, e.g. "Unexpected result (of class 'NULL' != 'FutureResult') 
   retrieved for ClusterFuture future (label = '<none>', expression = '...'): 
   This suggests that the communication with `ClusterFuture` worker 
   ('RichSOCKnode' #1 on host 'n3' (R version 3.6.3 (2020-02-29), platform
   x86_64-pc-linux-gnu)) is out of sync."

 * It is now possible to set environment variables on workers before they are
   launched by `makeClusterPSOCK()` by specify them as as `"<name>=<value>"`
   as part of the `rscript` vector argument, e.g. `rscript = c("ABC=123",
   "DEF='hello world'", "Rscript")`. This works because elements in `rscript`
   that match regular expression `[[:alpha:]_][[:alnum:]_]*=.*` are no longer
   shell quoted.

 * `makeClusterPSOCK()` now returns a cluster that in addition to inheriting
   from `SOCKcluster` it will also inherit from `RichSOCKcluster`.

## Bug Fixes

 * Made `makeClusterPSOCK()` and `makeNodePSOCK()` agile to the name change from
   `parallel:::.slaveRSOCK()` to `parallel:::.workRSOCK()` in R (>= 4.1.0).

 * `makeClusterPSOCK(..., rscript)` will not try to locate `rscript[1]` if
   argument `homogeneous` is FALSE (or inferred to be FALSE).

 * `makeClusterPSOCK(..., rscript_envs)` would result in a syntax error when
   starting the workers due to non-ASCII quotation marks if option
   `useFancyQuotes` was not set to FALSE.

 * `plan(list(...))` would produce 'Error in UseMethod("tweak") : no applicable
   method for 'tweak' applied to an object of class "list"' if a non-function
   object named 'list' was on the search path.

 * `plan(x$abc)` with x <- list(abc = sequential) would produce 'Error in
   UseMethod("tweak") : no applicable method for 'tweak' applied to an object
   of class "c('FutureStrategyList', 'list')"'.

 * TESTS: `R_FUTURE_FORK_ENABLE=false R CMD check ...` would produce 'Error: 
   connections left open: ...' when checking the 'multiprocess' example.

## Deprecated and Defunct

 * Support for `persistent = TRUE` with multisession futures is deprecated.
   If still needed, a temporary workaround is to use cluster futures. However,
   it is likely that support for `persistent` will eventually be deprecated
   for all future backends.
 
 * Options `future.globals.method`, `future.globals.onMissing`, and
   `future.globals.resolve` are deprecated and produce warnings if set. They
   may only be used for troubleshooting purposes because they may affect how
   futures are evaluated, which means that reproducibility cannot be guaranteed
   elsewhere.
 

# Version 1.17.0 [2020-04-17]

## Significant Changes

 * Renamed `values()` to `value()` to clean up and simplify the API.

## New Features

 * `makeClusterPSOCK()` gained argument `rscript_envs` for setting environment
   variables in workers on startup, e.g. `rscript_envs = c(FOO = "3.14", "BAR")`.

 * Now the result of a future holds session details in case an error occurred
   while evaluating the future.

## Miscellaneous

 * Not all CRAN servers have `_R_CHECK_LIMIT_CORES_` set.  To better emulate
   CRAN submission checks, the **future** package will, when loaded, set this
   environment variable to 'TRUE' if unset and if `R CMD check` is running.
   Note that `future::availableCores()` respects `_R_CHECK_LIMIT_CORES_` and
   returns at most `2L` (two cores) if detected.

## Bug Fixes

 * Any globals named `version` and `has_future` would be overwritten with
   "garbage" values internally.

 * Disabling of multi-threading when using 'multicore' futures did not work
   on all platforms.

## Deprecated and Defunct

 * All `values()` S3 methods have been renamed to `value()` since they are closely
   related to the original purpose `value()`.  The `values()` methods will continue
   to work but will soon be formally deprecated and later be made defunct and
   finally be removed.  Please replace all `values()` with `value()` calls.
 

# Version 1.16.0 [2020-01-15]

## Significant Changes

 * Now `oplan <- plan(new_strategy)` returns the list of all nested strategies
   previously set, instead of just the strategy on top of this stack. This
   makes it easier to temporarily use another plan. For the old behavior,
   use `oplan <- plan(new_strategy)[[1]]`.

## New Features

 * Now `value()` detects if a `future(..., seed = FALSE)` call generated random
   numbers, which then might give unreliable results because non-parallel
   safe, non-statistically sound random number generation (RNG) was used.
   If option `future.rng.onMisuse` is `"warning"`, a warning is produced. If
   `"error"`, an error is produced.  If `"ignore"` (default), the mistake is
   silently ignored. Using `seed = NULL` is like `seed = FALSE` but without
   performing the RNG validation.

 * For convenience, argument `seed` of `future()` may now also be an ordinary
   single integer random seed.  If so, a L'Ecuyer-CMRG RNG seed is created
   from this seed.  If `seed = TRUE`, then a L'Ecuyer-CMRG RNG seed based on the
   current RNG state is used.  Use `seed = FALSE` when it is known that the
   future does not use RNG.

 * `ClusterFuture`:s now relay `immediateCondition`:s back to the main process
   momentarily after they are signaled and before the future is resolved.

## Beta Features

 * Add support for automatically disable multi-threading when using 'multicore'
   futures. For now, the default is to allow multi-threaded processing but
   this might change in the future. To disable multi-threaded, set option
   `future.fork.multithreading.enable` or environment variable
   `R_FUTURE_FORK_MULTITHREADING_ENABLE` to `FALSE`. This requires that
   **RhpcBLASctl** package is installed. Parallelization via multi-threaded
   processing (done in native code by some packages and externally library)
   while at the same time using forked (aka "multicore") parallel processing
   is unstable in some cases.  Note that this is not only true when using
   `plan(multicore)` but also when using, for instance, `parallel::mclapply()`.
   This is in beta so the above names and options might change later.

## Bug Fixes

 * Evaluation of futures could fail if the global environment contained
   *functions* with the same names as a small set of base R functions, e.g.
   `raw()`, `list()`, and `options()`.

 * `future(alist(a =))` would produce "Error in objectSize_list(x, depth =
   depth - 1L) : argument "x_kk" is missing, with no default"

## Deprecated and Defunct

 * `Future` and `FutureResult` objects with an internal version 1.7 or older have
   been deprecated since 1.14.0 (July 2019) and are now defunct.
   
 * Defunct hidden argument `progress` of `resolve()`, and hidden arguments/fields
   `condition` and `calls` of `FutureResult` are now gone.


# Version 1.15.1 [2019-11-23]

## New Features

 * The default range of ports that `makeClusterPSOCK()` draws a random port from
   (when argument `port` is not specified) can now be controlled by environment
   variable `R_FUTURE_RANDOM_PORTS`.  The default range is still `11000:11999`
   as with the **parallel** package.
 
## Bug Fixes

 * The change introduced to `resolved()` in **future** 1.15.0 would cause lazy
   futures to block if all workers were occupied.


# Version 1.15.0 [2019-11-07]

## Significant Changes

 * `resolved()` will now launch lazy futures.

## New Features

 * Now the "visibility" of future values is recorded and reflected by `value()`.

 * Now option `future.globals.onReference` defaults to environment variable
   `R_FUTURE_GLOBALS_ONREFERENCE`.

## Documentation

 * Added 'Troubleshooting' section to `?makeClusterPSOCK` with instructions on
   how to troubleshoot when the setup of local and remote clusters fail.

## Bug Fixes

 * `values()` would resignal `immediateCondition`:s despite those should only be
   signaled at most once per future.

 * `makeClusterPSOCK()` could produce warnings like "cannot open file
   '/tmp/alice/Rtmpi69yYF/future.parent=2622.a3e32bc6af7.pid': No such file",
   e.g. when launching R workers running in Docker containers.
   
 * Package would set or update the RNG state of R (`.Random.seed`) when loaded,
   which could affect RNG reproducibility.
   
 * Package could set `.Random.seed` to NULL, instead of removing it, which in
   turn would produce a warning on "'.Random.seed' is not an integer vector but
   of type 'NULL', so ignored" when the next random number generated.

 * Now a future assignment to list environments produce more informative error
   messages if attempting to assign to more than one element.
   
 * `makeClusterMPI()` did not work for MPI clusters with `comm` other than `1`.

## Deprecated and Defunct

 * Argument `value` of `resolve()` is deprecated. Use `result` instead.

 * Use of internal argument `evaluator` to `future()` is now defunct.


# Version 1.14.0 [2019-07-01]

## Significant Changes

 * All types of conditions are now captured and relayed.  Previously, only
   conditions of class `message` and `warning` were relayed.

 * If one of the futures in a collection produces an error, then `values()`
   will signal that error as soon as it is detected.  This means that while
   calling `values()` guarantees to resolve all futures, it does not guarantee
   that the result from all futures are gathered back to the master R session
   before the error is relayed.

## New Features

 * `values()` now relays `stdout` and signal as soon as possible as long as
   the standard output and the conditions are relayed in their original order.

 * If a captured condition can be "muffled", then it will be muffled.  This
   helps to prevent conditions from being handled twice by condition handlers
   when futures are evaluated in the main R session, e.g. `plan(sequential)`.
   Messages and warnings were already muffled in the past.

 * Forked processing is considered unstable when running R from certain
   environments, such as the RStudio environment.  Because of this, 'multicore'
   futures have been disabled in those cases since **future** 1.13.0.  This change
   caught several RStudio users by surprise.  Starting with **future** 1.14.0, an
   informative one-time-per-session warning will be produced when attempts to
   use 'multicore' is made in non-supported environments such as RStudio.
   This warning will also be produced when using 'multiprocess', which will
   fall back to using 'multisession' futures.  The warning can be disabled by
   setting R option `future.supportsMulticore.unstable`, or environment
   variable `FUTURE_SUPPORTSMULTICORE_UNSTABLE` to `"quiet"`.

 * Now option `future.startup.script` falls back to environment variable
   `R_FUTURE_STARTUP_SCRIPT`.
   
 * Conditions inheriting `immediateCondition` are signaled as soon as possible.
   Contrary to other types of conditions, these will be signaled only once per
   future, despite being collected.

## Bug Fixes

 * Early signaling did not take place for `resolved()` for `ClusterFuture` and
   `MulticoreFuture`.

 * When early signaling was enabled, functions such as `resolved()` and
   `resolve()` would relay captured conditions multiple times.  This would,
   for instance, result in the same messages and warnings being outputted
   more than once.  Now it is only `value()` that will resignal conditions.

 * The validation of connections failed to detect when the connection had
   been serialized (= a `NIL` external pointer) on some macOS systems.

## Deprecated and Defunct

 * Argument `progress` of `resolve()` is now defunct (was deprecated since
   **future** 1.12.0).  Option `future.progress` is ignored.  This will make
   room for other progress-update mechanisms that are in the works.

 * Usage of internal argument `evaluator` to `future()` is now deprecated.
 
 * Removed defunct argument `output` from `FutureError()`.

 * `FutureResult` fields/arguments `condition` and `calls` are now defunct.
   Use `conditions` instead.

 * `Future` and `FutureResult` objects with an internal version 1.7 or older are
   deprecated and will eventually become defunct.  Future backends that
   implement their own `Future` classes should update to implement a `result()`
   method instead of a `value()` method for their `Future` classes.  All future
   backends available on CRAN and Bioconductor have already been updated
   accordingly.
 

# Version 1.13.0 [2019-05-08]

## Significant Changes

 * Forked processing is now disabled by default when running R via RStudio
   When disabled, 'multicore' futures fall back to a 'sequential' futures.
   This update follows from an RStudio recommendation against using _forked_
   parallel processing from within RStudio because it is likely to break the
   RStudio R session.  See `help("supportsMulticore")` for more details, e.g.
   how to re-enable process forking.  Note that parallelization via
   'multisession' is unaffected and will still work as before.  Also, when
   forked processing is disabled, or otherwise not supported, using
   `plan("multiprocess")` will fall back to using 'multisession' futures.
   
## New Features

 * Forked processing can be disabled by setting R option `future.fork.enable`
   to FALSE (or environment variable `R_FUTURE_FORK_ENABLE=false`).  When
   disabled, 'multicore' futures fall back to a 'sequential' futures even if
   the operating system supports process forking.  If set of TRUE, 'multicore'
   will not fall back to 'sequential'.  If NA, or not set (the default), a
   set of best-practices rules will decide whether forking is enabled or not.
   See `help("supportsMulticore")` for more details.

 * Now `availableCores()` also recognizes PBS environment variable `NCPUS`,
   because the PBSPro scheduler does not set `PBS_NUM_PPN`.

 * If, option `future.availableCores.custom` is set to a function, then
   `availableCores()` will call that function and interpret its value as
   number of cores.  Analogously, option `future.availableWorkers.custom`
   can be used to specify a hostnames of a set of workers that
   `availableWorkers()` sees.  These new options provide a mechanism for anyone
   to customize `availableCores()` and `availableWorkers()` in case they do not
   (yet) recognize, say, environment variables that are specific the user's
   compute environment or HPC scheduler.

 * `makeClusterPSOCK()` gained support for argument `rscript_startup` for
   evaluating one or more R expressions in the background R worker prior
   to the worker event loop launching.  This provides a more convenient
   approach than having to use, say, `rscript_args = c("-e", sQuote(code))`.

 * `makeClusterPSOCK()` gained support for argument `rscript_libs` to control the
   R package library search path on the workers.  For example, to _prepend_ the
   folder `~/R-libs` on the workers, use `rscript_libs = c("~/R-libs", "*")`,
   where `"*"` will be resolved to the current `.libPaths()` on the workers.

 * Debug messages are now prepended with a timestamp.

## Documentation

 * Add vignette on 'Non-Exportable Objects' (extracted from another vignette).

## Bug Fixes

 * `makeClusterPSOCK()` did not shell quote the Rscript executable when running
   its pre-tests checking whether localhost Rscript processes can be killed by
   their PIDs or not.

## Deprecated and Defunct

 * Argument `value` of `resolve()` has been renamed to `result` to better reflect
   that not only values are collected when this argument is used.  Argument
   `value` still works for backward compatibility, but will eventually be
   formally deprecated and then defunct.


# Version 1.12.0 [2019-03-07]

## New Features

 * If `makeClusterPSOCK()` fails to create one of many nodes, then it will
   attempt to stop any nodes that were successfully created.  This lowers
   the risk for leaving R worker processes behind.

 * Future results now hold the timestamps when the evaluation of the future
   started and finished.
 
## Bug Fixes

 * Functions no longer produce "partial match of 'condition' to 'conditions'"
   warnings with `options(warnPartialMatchDollar = TRUE)`.

 * When future infix operators (`%conditions%`, `%globals%`, `%label%`, `%lazy%`,
   `%packages%`, `%seed%`, and `%stdout%`) that are intended for future assignments
   were used in the wrong context, they would incorrectly be applied to the
   next future created. Now they're discarded.

 * `makeClusterPSOCK()` in **future** (>= 1.11.1) produced warnings when argument
   `rscript` had `length(rscript) > 1`.

 * Validation of L'Ecuyer-CMRG RNG seeds failed in recent R devel.

 * With `options(OutDec = ",")`, the default value of several argument would
   resolve to `NA_real_` rather than a numeric value resulting in errors such
   as "is.finite(alpha) is not TRUE".

## Deprecated and Defunct

 * Argument `progress` of `resolve()` is now deprecated.
 
 * Argument `output` of `FutureError()` is now defunct.

 * `FutureError` no longer inherits `simpleError`.


# Version 1.11.1.1 [2019-01-25]

## Bug Fixes

 * When `makeClusterPSOCK()` fails to connect to a worker, it produces an error
   with detailed information on what could have happened.  In rare cases,
   another error could be produced when generating the information on what
   the workers PID is.
 

# Version 1.11.1 [2019-01-25]

## New Features

 * The defaults of several arguments of `makeClusterPSOCK()` and `makeNodePSOCK()`
   can now be controlled via environment variables in addition to R options
   that was supported in the past. An advantage of using environment variables
   is that they will be inherited by child processes, also nested ones.

 * The printing of future plans is now less verbose when the `workers` argument
   is a complex object such as a PSOCK cluster object.  Previously, the output
   would include verbose output of attributes, etc.

## Software Quality

 * TESTS: When the **future** package is loaded, it checks whether `R CMD check`
   is running or not.  If it is, then a few future-specific environment
   variables are adjusted such that the tests play nice with the testing
   environment.  For instance, it sets the socket connection timeout for
   PSOCK cluster workers to 120 seconds (instead of the default 30 days!).
   This will lower the risk for more and more zombie worker processes
   cluttering up the test machine (e.g. CRAN servers) in case a worker process
   is left behind despite the main R processes is terminated.  Note that these
   adjustments are applied automatically to the checks of any package that
   depends on, or imports, the **future** package.

## Bug Fixes

 * Whenever `makeClusterPSOCK()` would fail to connect to a worker, for instance
   due to a port clash, then it would leave the R worker process running - also
   after the main R process terminated.  When the worker is running on the same
   machine, `makeClusterPSOCK()` will now attempt to kill such stray R processes.
   Note that `parallel::makePSOCKcluster()` still has this problem.


# Version 1.11.0 [2019-01-21]

## Significant Changes

 * Message and warning conditions are now captured and relayed by default.

## New Features

 * The future call stack ("traceback") is now recorded when the evaluation of a
   future produces an error.  Use `backtrace()` on the future to retrieve it.

 * Now `futureCall()` defaults to `args = list()` making is easier to call
   functions that do not take arguments, e.g. `futureCall(function() 42)`.

 * `plan()` gained argument `.skip = FALSE`.  When TRUE, setting the same future
   strategy as already set will be skipped, e.g. calling `plan(multisession)`
   consecutively will have the same effect as calling it just once.

 * `makeClusterPSOCK()` produces more informative error messages whenever the
   setup of R workers fails.  Also, its verbose messages are now prefixed
   with `[local output] ` to help distinguish the output produced by the
   current R session from that produced by background workers.
   
 * It is now possible to specify what type of SSH clients `makeClusterPSOCK()`
   automatically searches for and in what order, e.g.
   `rshcmd = c("<rstudio-ssh>", "<putty-plink>")`.

 * Now `makeClusterPSOCK()` preserves the global RNG state (`.Random.seed`) also
   when it draws a random port number.
   
 * `makeClusterPSOCK()` gained argument `rshlogfile`.

 * Cluster futures provide more informative error messages when the
   communication with the worker node is out of sync.

## Bug Fixes

 * Argument `stdout` was forced to TRUE when using single-core multicore or
   single-core multisession futures.

 * When evaluated in a local environment, `futureCall(..., globals = "a")` would
   set the value of global `a` to NULL, regardless if it exists or not and
   what its true value is.

 * `makeClusterPSOCK(..., rscript = "my_r")` would in some cases fail to find
   the intended `my_r` executable.

 * ROBUSTNESS: A cluster future, including a multisession one, could retrieve
   results from the wrong workers if a new set of cluster workers had been
   set up after the future was created/launched but before the results were
   retrieved.  This could happen because connections in R are indexed solely
   by integers which are recycled when old connections are closed and new ones
   are created.  Now cluster futures assert that the connections to the workers
   are valid, and if not, an informative error message is produced.

 * Calling `result()` on a non-resolved `UniprocessFuture` would signal evaluation
   errors.

## Deprecated and Defunct

 * Removed defunct `future::future_lapply()`.  Please use the one in the
   **future.apply** package instead.


# Version 1.10.0 [2018-10-16]

## New Features

 * Add support for manually specifying globals in addition to those that are
   automatically identified via argument `globals` or `%globals%`. Two examples
   are `globals = structure(TRUE, add = list(a = 42L, b = 3.14))` and
   `globals = structure(TRUE, add = c("a", "b"))`.  Analogously, attribute
   `ignore` can be used to exclude automatically identified globals.

 * The error reported when failing to retrieve the results of a future
   evaluated on a localhost cluster/multisession worker or a forked/multicore
   worker is now more informative. Specifically, it mentions whether the worker
   process is still alive or not.

 * Add `makeClusterMPI(n)` for creating MPI-based clusters of a similar kind as
   `parallel::makeCluster(n, type = "MPI")` but that also attempts to workaround
   issues where `parallel::stopCluster()` causes R to stall.
   
 * `makeClusterPSOCK()` and `makeClusterMPI()` gained argument `autoStop` for
   controlling whether the cluster should be automatically stopped when
   garbage collected or not.

 * BETA: Now `resolved()` for `ClusterFuture` is non-blocking also for clusters
   of type `MPIcluster` as created by `parallel::makeCluster(..., type = "MPI")`.

## Bug Fixes

 * On Windows, `plan(multiprocess)` would not initiate the workers. Instead
   workers would be set up only when the first future was created.


# Version 1.9.0 [2018-07-22]

## Significant Changes

 * Standard output is now captured and re-outputted when `value()` is called.
   This new behavior can be controlled by the argument `stdout` to `future()`
   or by specifying the `%stdout%` operator if a future assignment is used.

## New Features

 * R option `width` is passed down so that standard output is captured
   consistently across workers and consistently with the master process.
   
 * Now more `future.*` options are passed down so that they are also
   acknowledged when using nested futures.

## Documentation

 * Add vignette on 'Outputting Text'.

 * CLEANUP: Only the core parts of the API are now listed in the help index.
   This was done to clarify the Future API.  Help for non-core parts are still
   via cross references in the indexed API as well via `help()`.

## Bug Fixes

 * When using forced, nested 'multicore' parallel processing, such as,
   `plan(list(tweak(multicore, workers = 2), tweak(multicore, workers = 2)))`,
   then the child process would attempt to resolve futures owned by the parent
   process resulting in an error (on 'bad error message').
   
 * When using `plan(multicore)`, if a forked worker would terminate unexpectedly,
   it could corrupt the master R session such that any further attempts of
   using forked workers would fail.  A forked worker could be terminated this
   way if the user pressed <kbd>Ctrl-C</kbd> (the worker receives a `SIGINT` signal).

 * `makeClusterPSOCK()` produced a warning when environment variable
   `R_PARALLEL_PORT` was set to `random` (e.g. as on CRAN).

 * Printing a `plan()` could produce an error when the deparsed call used to set
   up the `plan()` was longer than 60 characters.
 
## Deprecated and Defunct

 * `future::future_lapply()` is defunct (gives an error if called).  Please use
   the one in the **future.apply** package instead.

 * Argument `output` of `FutureError()` is formally deprecated.

 * Removed all `FutureEvaluationCondition` classes and related methods.
 

# Version 1.8.1 [2018-05-02]

## New Features

 * `getGlobalsAndPackages()` gained argument `maxSize`.

 * `makeClusterPSOCK()` now produces a more informative warning if environment
   variable `R_PARALLEL_PORT` specifies a non-numeric port.

 * Now `plan()` gives a more informative error message in case it fails, e.g.
   when the internal future validation fails and why.

 * Added `UnexpectedFutureResultError` to be used by backends for signaling
   in a standard way that an unexpected result was retrieved from a worker.

## Bug Fixes

 * When the communication between an asynchronous future and a background R
   process failed, further querying of the future state/results could end up
   in an infinite waiting loop.  Now the failed communication error is
   recorded and re-signaled if any further querying attempts.
 
 * Internal, seldom used `myExternalIP()` failed to recognize IPv4 answers
   from some of the lookup servers. This could in turn produce another error.

 * In R (>= 3.5.0), multicore futures would produce multiple warnings
   originating from querying whether background processes have completed
   or not. These warnings are now suppressed.
   

# Version 1.8.0 [2018-04-08]

## Significant Changes

 * Errors produces when evaluating futures are now (re-)signaled on the master
   R process as-is with the original content and class attributes.
 
## New Features

 * More errors related to orchestration of futures are of class `FutureError` to
   make it easier to distinguish them from future evaluation errors.
   
 * Add support for a richer set of results returned by resolved futures.
   Previously only the value of the future expression, which could be a
   captured error to be resignaled, was expected. Now a `FutureResult` object
   may be returned instead.  Although not supported in this release, this
   update opens up for reporting on additional information from the evaluation
   of futures, e.g. captured output, timing and memory benchmarks, etc. Before
   that can take place, existing future backend packages will have to be
   updated accordingly.

 * `backtrace()` returns only the last call that produced the error.  It is
   unfortunately not possible to capture the call stack that led up to the
   error when evaluating a future expression.
   
## Bug Fixes

 * `value()` for `MulticoreFuture` would not produce an error when a (forked)
   background R workers would terminate before the future expression is
   resolved.  This was a limitation inherited from the **parallel** package.
   Now an informative `FutureError` message is produced.

 * `value()` for `MulticoreFuture` would not signal errors unless they inherited
   from `simpleError` - now it's enough for them to inherits from `error`.

 * `value()` for `ClusterFuture` no longer produces a `FutureEvaluationError`, but
   `FutureError`, if the connection to the R worker has changed (which happens
   if something as drastic as `closeAllConnections()` have been called.)

 * `futureCall(..., globals = FALSE)` would produce "Error: second argument must
   be a list", because the explicit arguments where not exported.  This could
   also happen when specifying globals by name or as a named list.

 * Nested futures were too conservative in requiring global variables to exist,
   even when they were false positives.

## Deprecated and Defunct

 * `future::future_lapply()` is formally deprecated. Please use the one in the
   **future.apply** package instead.
  
 * Recently introduced `FutureEvaluationCondition` classes are deprecated,
   because they no longer serve a purpose since future evaluation conditions
   are now signaled as-is.
   

# Version 1.7.0 [2018-02-10]

## Significant Changes

 * `future_lapply()` has moved to the **future.apply** package available on CRAN.

## New Features

 * Argument `workers` of future strategies may now also be a function, which
   is called without argument when the future strategy is set up and used as
   is.  For instance, `plan(multiprocess, workers = halfCores)` where
   `halfCores <- function() { max(1, round(`availableCores()` / 2)) }` will use
   half of the number of available cores.  This is useful when using nested
   future strategies with remote machines.
 
 * On Windows, `makeClusterPSOCK()`, and therefore `plan(multisession)` and
   `plan(multiprocess)`, will use the SSH client distributed with RStudio as
   a fallback if neither `ssh` nor `plink` is available on the system `PATH`.

 * Now `plan()` makes sure that `nbrOfWorkers()` will work for the new strategy.
   This will help catch mistakes such as `plan(cluster, workers = cl)` where
   `cl` is a basic R list rather than a `cluster` list early on.

 * Added `%packages%` to explicitly control packages to be attached when a
   future is resolved, e.g. `y %<-% { YT[2] } %packages% "data.table"`.
   Note, this is only needed in cases where the automatic identification of
   global and package dependencies is not sufficient.

 * Added condition classes `FutureCondition`, `FutureMessage`, `FutureWarning`, and
   `FutureError` representing conditions that occur while a future is setup,
   launched, queried, or retrieved.  They do *not* represent conditions that
   occur while evaluating the future expression.  For those conditions, new
   classes `FutureEvaluationCondition`, `FutureEvaulationMessage`,
   `FutureEvaluationWarning`, and `FutureEvaluationError` exists.

## Documentation

 * Vignette 'Common Issues with Solutions' now documents the case where the
   future framework fails to identify a variable as being global because it
   is only so conditionally, e.g. `if (runif(1) < 1/2) x <- 0; y <- 2 * x`.

## Beta Features

 * Added mechanism for detecting globals that _may_ not be exportable to an
   external R process (a "worker").  Typically, globals that carry connections
   and external pointers (`externalptr`) can not be exported, but there are
   exceptions.  By setting options `future.globals.onReference` to `"warning"`,
   a warning is produced informing the user about potential problems.  If
   `"error"`, an error is produced.  Because there might be false positive, the
   default is `"ignore"`, which will cause above scans to be skipped.  If there
   are non-exportable globals and these tests are skipped, a run-time error
   may be produced only when the future expression is evaluated.

## Bug Fixes

 * The total size of global variables was overestimated, and dramatically so
   if defined in the global environment and there were are large objects there
   too.  This would sometimes result in a false error saying that the total
   size is larger than the allowed limit.

 * An assignment such as `x <- x + 1` where the left-hand side (LHS) `x` is a
   global failed to identify `x` as a global because the right-hand side (RHS)
   `x` would override it as a local variable.  Updates to the **globals** package
   fixed this problem.

 * `makeClusterPSOCK(..., renice = 19)` would launch each PSOCK worker via
   `nice +19` resulting in the error "nice: '+19': No such file or directory".
   This bug was inherited from `parallel::makePSOCKcluster()`.  Now using
   `nice --adjustment=19` instead.

 * Protection against passing future objects to other futures did not work
   for future strategy 'multicore'.
 
## Deprecated and Defunct

 * `future_lapply()` has moved to the new **future.apply** package available on CRAN.
   The `future::future_lapply()` function will soon be deprecated, then defunct,
   and eventually be removed from the **future** package. Please update your code
   to make use of `future.apply::future_lapply()` instead.
   
 * Dropped defunct 'eager' and 'lazy' futures; use 'sequential' instead.

 * Dropped defunct arguments `cluster` and `maxCores`; use `workers` instead.

 * In previous version of the **future** package the `FutureError` class was used
   to represent both orchestration errors (now `FutureError`) and evaluation
   errors (now `FutureEvaluationError`).  Any usage of class `FutureError` for
   the latter type of errors is deprecated and should be updated to
   `FutureEvaluationError`.


# Version 1.6.2 [2017-10-16]

## New Features

 * Now `plan()` accepts also strings such as `"future::cluster"`.

 * Now `backtrace(x[[ER]])` works also for non-environment `x`:s, e.g. lists.

## Bug Fixes

 * When measuring the size of globals by scanning their content, for certain
   types of classes the inferred lengths of these objects were incorrect
   causing internal subset out-of-range issues.

 * `print()` for `Future` would output one global per line instead of
   concatenating the information with commas.


# Version 1.6.1 [2017-09-08]

## New Features

 * Now exporting `getGlobalsAndPackages()`.

## Bug Fixes

 * `future_lapply()` would give "Error in objectSize.env(x, depth = depth - 1L):
   object 'nnn' not found" when for instance 'nnn' is part of an unresolved
   expression that is an argument value.

## Software Quality

 * FIX: Some of the package assertion tests made too precise assumptions about
   the object sizes, which fails with the introduction of ALTREP in R-devel
   which causes the R's SEXP header size to change.
 

# Version 1.6.0 [2017-08-11]

## New Features

 * Now `tweak()`, and hence `plan()`, generates a more informative error message if
   a non-future function is specified by mistake, e.g. calling `plan(cluster)`
   with the **survival** package attached after **future** is equivalent to calling
   `plan(survival::cluster)` when `plan(future::cluster)` was intended.

## Bug Fixes

 * `nbrOfWorkers()` gave an error with `plan(remote)`. Fixed by making the 'remote'
   future inherit `cluster` (as it should).

## Software Quality

 * TESTS: No longer testing forced termination of forked cluster workers when
   running on Solaris. The termination was done by launching a future that
   called `quit()`, but that appeared to have corrupted the main R session when
   running on Solaris.

## Deprecated and Defunct

 * Formally defunct 'eager' and 'lazy' futures; use 'sequential' instead.

 * Dropped previously defunct `%<=%` and `%=>%` operators.
 

# Version 1.5.0 [2017-05-24]

## Significant Changes

 * Multicore and multisession futures no longer reserve one core for the
   main R process, which was done to lower the risk for producing a higher
   CPU load than the number of cores available for the R session.
 
## New Features

 * `makeClusterPSOCK()` now defaults to use the Windows PuTTY software's SSH
   client `plink -ssh`, if `ssh` is not found.

 * Argument `homogeneous` of `makeNodePSOCK()`, a helper function of
   `makeClusterPSOCK()`, will default to FALSE also if the hostname is a
   fully qualified domain name (FQDN), that is, it "contains periods".
   For instance, `c('node1', 'node2.server.org')` will use `homogeneous = TRUE`
   for the first worker and `homogeneous = FALSE` for the second.

 * `makeClusterPSOCK()` now asserts that each cluster node is functioning by
   retrieving and recording the node's session information including the
   process ID of the corresponding R process.

 * Nested futures sets option `mc.cores` to prevent spawning of recursive
   parallel processes by mistake.  Because 'mc.cores' controls _additional_
   processes, it was previously set to zero.  However, since some functions
   such as `mclapply()` does not support that, it is now set to one instead.   

## Documentation

 * Help on `makeClusterPSOCK()` gained more detailed descriptions on arguments
   and what their defaults are.
 
## Deprecated and Defunct

 * Formally deprecated eager futures; use sequential instead.

## Bug Fixes

 * `future_lapply()` with multicore / multisession futures, would use a
   suboptimal workload balancing where it split up the data in one chunk too
   many.  This is no longer a problem because of how argument `workers` is
   now defined for those type of futures (see note on top).
 
 * `future_lapply()`, as well as lazy multicore and lazy sequential futures, did
   not respect option `future.globals.resolve`, but was hardcoded to always
   resolve globals (`future.globals.resolve = TRUE`).

 * When globals larger than the allowed size (option `future.globals.maxSize`)
   are detected an informative error message is generated.  Previous version
   introduced a bug causing the error to produce another error.

 * Lazy sequential futures would produce an error when resolved if required
   packages had been detached.

 * `print()` would not display globals gathered for lazy sequential futures.

## Software Quality

 * Added package tests for globals part of formulas part of other globals,
   e.g. `purrr::map(x, ~ rnorm(.))`, which requires **globals** (>= 0.10.0).

 * Now package tests with `parallel::makeCluster()` not only test for
   `type = "PSOCK"` clusters but also `"FORK"` (when supported).

 * TESTS: Cleaned up test scripts such that the overall processing time for
   the tests was roughly halved, while preserving the same test coverage.
 

# Version 1.4.0 [2017-03-12]

## Significant Changes

 * The default for `future_lapply()` is now to _not_ generate RNG seeds
   (`future.seed = FALSE`).  If proper random number generation is needed,
   use `future.seed = TRUE`.  For more details, see help page.
   
## New Features

 * `future()` and `future_lapply()` gained argument `packages` for explicitly
   specifying packages to be attached when the futures are evaluated.
   Note that the default throughout the **future** package is that all globals
   and all required packages are automatically identified and gathered, so
   in most cases those do not have to be specified manually.

 * The default values for arguments `connectTimeout` and `timeout` of
   `makeNodePSOCK()` can now be controlled via global options.

## Random Number Generation

 * Now `future_lapply()` guarantees that the RNG state of the calling R process
   after returning is updated compared to what it was before and in the exact
   same way regardless of `future.seed` (except FALSE), `future.scheduling`
   and future strategy used.  This is done in order to guarantee that an R
   script calling `future_lapply()` multiple times should be numerically
   reproducible given the same initial seed.

 * It is now possible to specify a pre-generated sequence of `.Random.seed`
   seeds to be used for each `FUN(x[[i]], ...)` call in `future_lapply(x, FUN, ...)`.

## Performance

 * `future_lapply()` scans global variables for non-resolved futures (to resolve
   them) and calculate their total size once.  Previously, each chunk
   (a future) would redo this.

## Bug Fixes

 * Now `future_lapply(X, FUN, ...)` identifies global objects among `X`, `FUN`
   and `...` recursively until no new globals are found.  Previously, only
   the first level of globals were scanned.  This is mostly thanks to a bug
   fix in **globals** 0.9.0.

 * A future that used a global object `x` of a class that overrides `length()`
   would produce an error if `length(x)` reports more elements than what can
   be subsetted.

 * `nbrOfWorkers()` gave an error with `plan(cluster, workers = cl)` where
   `cl` is a `cluster` object created by `parallel::makeCluster()`, etc.
   This prevented for instance `future_lapply()` to work with such setups.

 * `plan(cluster, workers = cl)` where `cl <- makeCluster(..., type = MPI")`
   would give an instant error due to an invalid internal assertion.

## Deprecated and Defunct

 * Previously deprecated arguments `maxCores` and `cluster` are now defunct.

 * Previously deprecated assignment operators `%<=%` and `%=>%` are now defunct.

 * `availableCores(method = "mc.cores")` is now defunct in favor of `"mc.cores+1"`.


# Version 1.3.0 [2017-01-18]

## Significant Changes

 * Where applicable, workers are now initiated when calling `plan()`, e.g.
   `plan(cluster)` will set up workers on all cluster nodes.  Previously,
   this only happened when the first future was created.

## New Features

 * Renamed 'eager' futures to 'sequential', e.g. `plan(sequential)`.
   The 'eager' futures will be deprecated in an upcoming release.
   
 * Added support for controlling whether a future is resolved eagerly
   or lazily when creating the future, e.g. `future(..., lazy = TRUE)`,
   `futureAssign(..., lazy = TRUE)`, and `x %<-% { ... } %lazy% TRUE`.

 * `future()`, `futureAssign()` and `futureCall()` gained argument `seed`,
   which specifies a L'Ecuyer-CMRG random seed to be used by the future.
   The seed for future assignment can be specified via `%seed%`.
   
 * `futureAssign()` now passes all additional arguments to `future()`.

 * Added `future_lapply()` which supports load balancing ("chunking")
   and perfect reproducibility (regardless of type of load balancing
   and how futures are resolved) via initial random seed.
 
 * Added `availableWorkers()`.  By default it returns localhost workers
   according to `availableCores()`.  In addition, it detects common
   HPC allocations given in environment variables set by the HPC
   scheduler.
   
 * The default for `plan(cluster)` is now `workers = availableWorkers()`.
 
 * Now `plan()` stops any clusters that were implicitly created. For
   instance, a multisession cluster created by `plan(multisession)` will
   be stopped when `plan(eager)` is called.

 * `makeClusterPSOCK()` treats workers that refer to a local machine by
   its local or canonical hostname as "localhost".  This avoids having
   to launch such workers over SSH, which may not be supported on all
   systems / compute cluster.

 * Option `future.debug = TRUE` also reports on total size of
   globals identified and for cluster futures also the size of the
   individual global variables exported.

 * Option `future.wait.timeout` (replaces `future.wait.times`) specifies
   the maximum waiting time for a free workers (e.g. a core or a
   compute node) before generating a timeout error.  

 * Option `future.availableCores.fallback`, which defaults to environment
   variable `R_FUTURE_AVAILABLECORES_FALLBACK` can now be used to specify
   the default number of cores / workers returned by `availableCores()`
   and `availableWorkers()` when no other settings are available.  For
   instance, if `R_FUTURE_AVAILABLECORES_FALLBACK=1` is set system wide
   in an HPC environment, then all R processes that uses `availableCores()`
   to detect how many cores can be used will run as single-core processes.
   Without this fallback setting, and without other core-specifying settings,
   the default will be to use all cores on the machine, which does not play
   well on multi-user systems.

## Globals

 * Globals part of locally defined functions are now also identified
   thanks to **globals** (>= 0.8.0) updates.
   
## Deprecated and Defunct

 * Lazy futures and `plan(lazy)` are now deprecated. Instead, use `plan(eager)`
   and then `f <- future(..., lazy = TRUE)` or `x %<-% { ... } %lazy% TRUE`.
   The reason behind this is that in some cases code that uses futures
   only works under eager evaluation (`lazy = FALSE`; the default), or vice
   verse. By removing the "lazy" future strategy, the user can no longer
   override the `lazy = TRUE / FALSE` that the developer is using.  
 
## Bug Fixes

 * Creation of cluster futures (including multisession ones) would
   time out already after 40 seconds if all workers were busy.
   New default timeout is 30 days (option `future.wait.timeout`).

 * `nbrOfWorkers()` gave an error for `plan(cluster, workers)` where `workers`
   was a character vector or a `cluster` object of the **parallel** package.
   Because of this, `future_lapply()` gave an error with such setups.

 * `availableCores(methods = "_R_CHECK_LIMIT_CORES_")` would give an error
   if not running `R CMD check`.
   
    
# Version 1.2.0 [2016-11-12]

## New Features

 * Added `makeClusterPSOCK()` - a version of `parallel::makePSOCKcluster()`
   that allows for more flexible control of how PSOCK cluster workers
   are set up and how they are launched and communicated with if running
   on external machines.

 * Added generic `as.cluster()` for coercing objects to cluster objects
   to be used as in `plan(cluster, workers = as.cluster(x))`.  Also added
   a `c()` implementation for cluster objects such that multiple cluster
   objects can be combined into a single one.

 * Added `sessionDetails()` for gathering details of the current R session.

 * `plan()` and `plan("list")` now prints more user-friendly output.

 * On Unix, internal `myInternalIP()` tries more alternatives for finding
   the local IP number.

## Deprecated and Defunct

 * `%<=%` is deprecated. Use `%<-%` instead. Same for `%=>%`.
    
## Bug Fixes

 * `values()` for lists and list environments of futures where one or more
   of the futures resolved to NULL would give an error.

 * `value()` for `ClusterFuture` would give cryptic error message
   "Error in stop(ex) : bad error message" if the cluster worker had
   crashed / terminated.  Now it will instead give an error message like
   "Failed to retrieve the value of `ClusterFuture` from cluster node #1 on
   'localhost'. The reason reported was "error reading from connection".

 * Argument `user` to `remote()` was ignored (since 1.1.0).
    
    
# Version 1.1.1 [2016-10-10]

## Bug Fixes

 * For the special case where 'remote' futures use `workers = "localhost"`
   they (again) use the exact same R executable as the main / calling R
   session (in all other cases it uses whatever `Rscript` is found in the
   `PATH`).  This was already indeed implemented in 1.0.1, but with the
   added support for reverse SSH tunnels in 1.1.0 this default behavior
   was lost.
    
    
# Version 1.1.0 [2016-10-09]

## New Features

 * REMOTE CLUSTERS: It is now very simple to use `cluster()` and `remote()`
   to connect to remote clusters / machines.  As long as you can connect
   via SSH to those machines, it works also with these future.  The new
   code completely avoids incoming firewall and incoming port forwarding
   issues previously needed.  This is done by using reverse SSH tunneling.
   There is also no need to worry about internal or external IP numbers.

 * Added optional argument `label` to all futures, e.g.
   `f <- future(42, label = "answer")` and `v %<-% { 42 } %label% "answer"`.

 * Added argument `user` to `cluster()` and `remote()`.

 * Now all `Future` classes supports `run()` for launching the future and
   `value()` calls `run()` if the future has not been launched.

 * MEMORY: Now `plan(cluster, gc = TRUE)` causes the background
   R session to be garbage collected immediately after the value
   is collected.  Since multisession and remote futures are special
   cases of cluster futures, the same is true for these as well.

 * ROBUSTNESS: Now the default future strategy is explicitly set when
   no strategies are set, e.g. when used nested futures.  Previously,
   only mc.cores was set so that only a single core was used, but now
   also `plan("default")` set.

 * WORKAROUND: `resolved()` on cluster futures would block on Linux until
   future was resolved.  This is due to a bug in R.  The workaround is
   to use round the timeout (in seconds) to an integer, which seems to
   always work / be respected.

## Globals

 * Global variables part of subassignments in future expressions
   are recognized and exported (iff found), e.g. `x$a <- value`,
   `x[["a"]] <- value`, and `x[1,2,3] <- value`.

 * Global variables part of formulae in future expressions are
   recognized and exported (iff found), e.g. `y ~ x | z`.

 * As an alternative to the default automatic identification of
   globals, it is now also possible to explicitly specify them either
   by their names (as a character vector) or by their names and values
   (as a named list), e.g. `f <- future({ 2*a }, globals = c("a"))` or
   `f <- future({ 2*a }, globals = list(a = 42))`.  For future assignments one
   can use the `%globals%` operator, e.g. `y %<-% { 2*a } %globals% c("a")`.

## Documentation

 * Added vignette on command-line options and other methods for
   controlling the default type of futures to use.
    
    
# Version 1.0.1 [2016-07-04]

## New Features

 * ROBUSTNESS: For the special case where 'remote' futures use
   `workers = "localhost"` they now use the exact same R executable
   as the main / calling R session (in all other cases it uses
   whatever `Rscript` is found in the `PATH`).

 * `FutureError` now extends `simpleError` and no longer the error
   class of captured errors.

## Documentation

 * Adding section to vignette on globals in formulas describing how
   they are currently not automatically detected and how to explicitly
   export them.

## Bug Fixes
  
 * Since **future** 0.13.0, a global `pkg` would be overwritten by the
   name of the last package attached in future.

 * Futures that generated `R.oo::Exception` errors, they triggered
   another internal error.
   
    
# Version 1.0.0 [2016-06-24]

## New Features

 * Add support for `remote(..., myip = "<external>")`, which now
   queries a set of external lookup services in case one of them
   fails.

 * Add `mandelbrot()` function used in demo to the API for convenience.

 * ROBUSTNESS: If `.future.R` script, which is sourced when the **future**
   package is attached, gives an error, then the error is ignored
   with a warning.

 * TROUBLESHOOTING: If the future requires attachment of packages,
   then each namespace is loaded separately and before attaching
   the package.  This is done in order to see the actual error
   message in case there is a problem while loading the namespace.
   With `require()`/`library()` this error message is otherwise suppressed
   and replaced with a generic one.

## Globals

 * Falsely identified global variables no longer generate
   an error when the future is created.  Instead, we leave it to R
   and the evaluation of the individual futures to throw an error
   if the a global variable is truly missing.  This was done in order
   to automatically handle future expressions that use non-standard
   evaluation (NSE), e.g. `subset(df, x < 3)` where `x` is falsely
   identified as a global variable.

 * Dropped support for system environment variable `R_FUTURE_GLOBALS_MAXSIZE`.

## Documentation

 * DEMO: Now the Mandelbrot demo tiles a single Mandelbrot region
   with one future per tile. This better illustrates parallelism.

 * Documented R options used by the **future** package.
    
## Bug Fixes

 * Custom futures based on a constructor function that
   is defined outside a package gave an error.

 * `plan("default")` assumed that the `future.plan` option
   was a string; gave an error if it was a function.

 * Various future options were not passed on to futures.

 * A startup `.future.R` script is no longer sourced if the
   **future** package is attached by a future expression.
    
    
# Version 0.15.0 [2016-06-13]

## New Features

 * Added remote futures, which are cluster futures with convenient
   default arguments for simple remote access to R, e.g.
   `plan(remote, workers = "login.my-server.org")`.

 * Now `.future.R` (if found in the current directory or otherwise in
   the user's home directory) is sourced when the **future** package is
   attach (but not loaded).  This helps separating scripts from
   configuration of futures.

 * Added support for `plan(cluster, workers = c("n1", "n2", "n2", "n4"))`,
   where `workers` (also for `ClusterFuture()`) is a set of host names
   passed to `parallel::makeCluster(workers)`.  It can also be the number
   of localhost workers.

 * Added command line option `--parallel=<p>`, which is long for `-p <p>`.

 * Now command line option `-p <p>` also set the default future strategy
   to multiprocessing (if p >= 2 and eager otherwise), unless another
   strategy is already specified via option `future.plan` or system
   environment variable `R_FUTURE_PLAN`.

 * Now `availableCores()` also acknowledges environment variable `NSLOTS`
   set by Sun/Oracle Grid Engine (SGE).

 * MEMORY: Added argument `gc = FALSE` to all futures.  When TRUE, the
   garbage collector will run at the very end in the process that
   evaluated the future (just before returning the value).  This may
   help lowering the overall memory footprint when running multiple
   parallel R processes.  The user can enable this by specifying
   `plan(multiprocess, gc = TRUE)`.  The developer can control this using
   `future(expr, gc = TRUE)` or `v %<-% { expr } %tweak% list(gc = TRUE)`.

## Performance

 * Significantly decreased the overhead of creating a future, particularly
   multicore futures.
    
## Bug Fixes

 * Future would give an error with `plan(list("eager"))`,
   whereas it did work with `plan("eager")` and `plan(list(eager))`.
    
    
# Version 0.14.0 [2016-05-16]

## New Features

 * Added `nbrOfWorkers()`.

 * Added informative `print()` method for the `Future` class.

 * `values()` passes arguments `...` to `value()` of each future.

 * Added `FutureError` class.

## Deprecated and Defunct

 * Renamed arguments `maxCores` and `cluster` to `workers`.  If using
   the old argument names a deprecation warning will be generated, but
   it will still work until made defunct in a future release.
    
## Bug Fixes

 * `resolve()` for lists and environments did not work
   properly when the set of futures was not resolved in order,
   which could happen with asynchronous futures.
    
    
# Version 0.13.0 [2016-04-13]

## New Features

 * Add support to `plan()` for specifying different future strategies for
   the different levels of nested futures.

 * Add `backtrace()` for listing the trace the expressions evaluated (the
   calls made) before a condition was caught.

 * Add transparent futures, which are eager futures with early signaling
   of conditioned enabled and whose expression is evaluated in the calling
   environment.  This makes the evaluation of such futures as similar
   as possible to how R evaluates expressions, which in turn simplifies
   troubleshooting errors, etc.

 * Add support for early signaling of conditions.  The default is
   (as before) to signal conditions when the value is queried.
   In addition, they may be signals as soon as possible, e.g. when
   checking whether a future is resolved or not.

 * Signaling of conditions when calling `value()` is now controlled by
   argument `signal` (previously `onError`).

 * Now `UniprocessFuture`:s captures the call stack for errors occurring
   while resolving futures.

 * `ClusterFuture()` gained argument `persistent = FALSE`. With `persistent = TRUE`,
   any objects in the cluster R session that was created during the
   evaluation of a previous future is available for succeeding futures
   that are evaluated in the same session.  Moreover, globals are
   still identified and exported but "missing" globals will not give
   an error - instead it is assumed such globals are available in the
   environment where the future is evaluated.

 * OVERHEAD: Utility functions exported by `ClusterFuture` are now much
   smaller; previously they would export all of the package environment.
    
## Bug Fixes
  
 * `f <- multicore(NA, maxCores = 2)` would end up in an endless
   waiting loop for a free core if `availableCores()` returned one.

 * `ClusterFuture()` would ignore `local = TRUE`.
    
    
# Version 0.12.0 [2016-02-23]

## New Features

 * Added multiprocess futures, which are multicore futures if supported,
   otherwise multisession futures.  This makes it possible to use
   `plan(multiprocess)` everywhere regardless of operating system.

 * Future strategy functions gained class attributes such that it is
   possible to test what type of future is currently used, e.g.
   `inherits(plan(), "multicore")`.

 * ROBUSTNESS: It is only the R process that created a future that can
   resolve it. If a non-resolved future is queried by another R process,
   then an informative error is generated explaining that this is not
   possible.

 * ROBUSTNESS: Now `value()` for multicore futures detects if the underlying
   forked R process was terminated before completing and if so generates
   an informative error messages.

## Performance

 * Adjusted the parameters for the schema used to wait for next available
   cluster node such that nodes are polled more frequently.

## Globals

 * `resolve()` gained argument `recursive`.

 * Added option `future.globals.resolve` for controlling whether
   global variables should be resolved for futures or not.  If TRUE, then
   globals are searched recursively for any futures and if found such
   "global" futures are resolved.  If FALSE, global futures are not
   located, but if they are later trying to be resolved by the parent
   future, then an informative error message is generated clarifying
   that only the R process that created the future can resolve it.
   The default is currently FALSE.

## Bug Fixes

 * FIX: Exports of objects available in packages already attached
   by the future were still exported.

 * FIX: Now `availableCores()` returns `3L` (=`2L+1L`) instead of `2L`
   if `_R_CHECK_LIMIT_CORES_` is set.
    
    
# Version 0.11.0 [2016-01-15]

## New Features

 * Add multisession futures, which analogously to multicore ones,
   use multiple cores on the local machine with the difference
   that they are evaluated in separate R session running in the
   background rather than separate forked R processes.
   A multisession future is a special type of cluster futures that
   do not require explicit setup of cluster nodes.

 * Add support for cluster futures, which can make use of a cluster
   of nodes created by `parallel::makeCluster()`.

 * Add `futureCall()`, which is for futures what `do.call()` is otherwise.

 * Standardized how options are named, i.e. `future.<option>`.
   If you used any future options previously, make sure to check
   they follow the above format.

## Globals

 * All futures now validates globals by default (`globals = TRUE`).
   
    
# Version 0.10.0 [2015-12-30]

## New Features

 * Now `%<=%` can also assign to multi-dimensional list environments.

 * Add `futures()`, `values()` and `resolved()`.

 * Add `resolve()` to resolve futures in lists and environments.

 * Now `availableCores()` also acknowledges the number of CPUs
   allotted by Slurm.

 * CLEANUP: Now the internal future variable created by `%<=%` is
   removed when the future variable is resolved.
    
## Bug Fixes

 * `futureOf(envir = x)` did not work properly when `x` was
   a list environment.
    
    
# Version 0.9.0 [2015-12-11]

## New Features

 * ROBUSTNESS: Now values of environment variables are trimmed
   before being parsed.

 * ROBUSTNESS: Add reproducibility test for random number
   generation using Pierre L'Ecuyer's RNG stream regardless
   of how futures are evaluated, e.g. eager, lazy and multicore.

## Globals

 * Now globals ("unknown" variables) are identified using the
   new `findGlobals(..., method = "ordered")` in **globals** (> 0.5.0)
   such that a global variable preceding a local variable with
   the same name is properly identified and exported/frozen.

## Documentation

 * Updated vignette on common issues with the case where a global
   variable is not identified because it is hidden by an element
   assignment in the future expression.
    
## Bug Fixes
 
 * Errors occurring in multicore futures could prevent
   further multicore futures from being created.
    
    
# Version 0.8.2 [2015-10-14]
    
## Bug Fixes
  
 * Globals that were copies of package objects were not exported to the
   future environments.

 * The **future** package had to be attached or `future::future()` had to be
   imported, if `%<=%` was used internally in another package.
   Similarly, it also had to be attached if multicore futures where used.
    
    
# Version 0.8.1 [2015-10-05]

## Documentation

 * Added vignette 'Futures in R: Common issues with solutions'.

## Globals

 * `eager()` and `multicore()` gained argument `globals`, where
   `globals = TRUE` will validate that all global variables
   identified can be located already before the future is
   created.  This provides the means for providing the same
   tests on global variables with eager and multicore futures
   as with lazy futures.

## Bug Fixes

 * `lazy(sum(x, ...), globals = TRUE)` now properly passes `...`
   from the function from which the future is setup.  If not
   called within a function or called within a function without
   `...` arguments, an informative error message is thrown.
    
    
# Version 0.8.0 [2015-09-06]

## New Features

 * `plan("default")` resets to the default strategy, which is
   synchronous eager evaluation unless option `future_plan`
   or environment variable `R_FUTURE_PLAN` has been set.

 * `availableCores("mc.cores")` returns `getOption("mc.cores") + 1L`,
   because option `mc.cores` specifies "allowed number of _additional_
   R processes" to be used in addition to the main R process.
    
## Bug Fixes

 * `plan(future::lazy)` and similar gave errors.
    
    
# Version 0.7.0 [2015-07-13]

## New Features

 * `multicore()` gained argument `maxCores`, which makes it
   possible to use for instance `plan(multicore, maxCores = 4L)`.

 * Add `availableMulticore()` [from (in-house) **async** package].

## Documentation

 * More colorful `demo("mandelbrot", package = "future")`.
    
## Bug Fixes
  
 * ROBUSTNESS: `multicore()` blocks until one of the CPU cores
   is available, iff all are currently occupied by other
   multicore futures.

 * `old <- plan(new)` now returns the old plan/strategy
   (was the newly set one).
    
    
# Version 0.6.0 [2015-06-18]

## New Features

 * Add multicore futures, which are futures that are resolved
   asynchronously in a separate process.  These are only
   supported on Unix-like systems, but not on Windows.
    
    
# Version 0.5.1 [2015-06-18]

## New Features

 * Eager and lazy futures now records the result internally
   such that the expression is only evaluated once, even if
   their error values are requested multiple times.

 * Eager futures are always created regardless of error or not.

 * All `Future` objects are environments themselves that record
   the expression, the call environment and optional variables.
    
    
# Version 0.5.0 [2015-06-16]

## Globals

 * `lazy()` "freezes" global variables at the time when
   the future is created.  This way the result of a lazy
   future is more likely to be the same as an 'eager' future.
   This is also how globals are likely to be handled by
   asynchronous futures.
    
    
# Version 0.4.2 [2015-06-15]

## New Features

 * `plan()` records the call.

## Documentation

 * Added `demo("mandelbrot", package = "future")`, which can be
   re-used by other future packages.
    
    
# Version 0.4.1 [2015-06-14]

## New Features

 * Added `plan()`.

 * Added eager future - useful for troubleshooting.
    
    
# Version 0.4.0 [2015-06-07]

 * Distilled Future API from (in-house) **async** package.
