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polish readme
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shikokuchuo committed Oct 2, 2024
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6 changes: 3 additions & 3 deletions README.Rmd
Original file line number Diff line number Diff line change
Expand Up @@ -64,7 +64,7 @@ To wait for and collect the return value, use the mirai's `[]` method:
```{r call}
m[]
```
As a mirai represents an async operation, it is never necessary to wait for it. Other code can continue to be run. Once it completes, the return value automatically becomes available at `$data`.
As a mirai represents an async operation, it is never necessary to wait for it. Other code can continue to run. Once it completes, the return value automatically becomes available at `$data`.
```{r resolv}
while (unresolved(m)) {
# do work here that does not depend on 'm'
Expand Down Expand Up @@ -142,9 +142,9 @@ The following core integrations are documented, with usage examples in the linke

### Powering Crew and Targets High Performance Computing

[<img alt="targets" src="https://github.com/ropensci/targets/raw/main/man/figures/logo.png" width="40" height="46" />](https://docs.ropensci.org/targets/) &nbsp; `targets`, a Make-like pipeline tool for statistics and data science, has integrated and adopted `crew` as its default high-performance computing backend.
[<img alt="targets" src="https://github.com/ropensci/targets/raw/main/man/figures/logo.png" width="40" height="46" />](https://docs.ropensci.org/targets/) &nbsp; Targets, a Make-like pipeline tool for statistics and data science, has integrated and adopted `crew` as its default high-performance computing backend.

[<img alt="crew" src="https://github.com/wlandau/crew/raw/main/man/figures/logo.png" width="40" height="46" />](https://wlandau.github.io/crew/) &nbsp; `crew` is a distributed worker-launcher extending `mirai` to different distributed computing platforms, from traditional clusters to cloud services.
[<img alt="crew" src="https://github.com/wlandau/crew/raw/main/man/figures/logo.png" width="40" height="46" />](https://wlandau.github.io/crew/) &nbsp; Crew is a distributed worker-launcher extending `mirai` to different distributed computing platforms, from traditional clusters to cloud services.

[<img alt="crew.cluster" src="https://github.com/wlandau/crew.cluster/raw/main/man/figures/logo.png" width="40" height="46" />](https://wlandau.github.io/crew.cluster/) &nbsp; `crew.cluster` enables mirai-based workflows on traditional high-performance computing clusters using LFS, PBS/TORQUE, SGE and Slurm.

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10 changes: 5 additions & 5 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -75,11 +75,11 @@ To wait for and collect the return value, use the mirai’s `[]` method:

``` r
m[]
#> [1] 6.331538 7.989301 6.017000 7.694094 6.836757
#> [1] 7.781188 5.028784 8.031969 7.663697 7.517325
```

As a mirai represents an async operation, it is never necessary to wait
for it. Other code can continue to be run. Once it completes, the return
for it. Other code can continue to run. Once it completes, the return
value automatically becomes available at `$data`.

``` r
Expand All @@ -89,7 +89,7 @@ while (unresolved(m)) {
m
#> < mirai [$data] >
m$data
#> [1] 6.331538 7.989301 6.017000 7.694094 6.836757
#> [1] 7.781188 5.028784 8.031969 7.663697 7.517325
```

#### Daemons
Expand Down Expand Up @@ -208,12 +208,12 @@ to be used seamlessly across parallel processes.
### Powering Crew and Targets High Performance Computing

[<img alt="targets" src="https://github.com/ropensci/targets/raw/main/man/figures/logo.png" width="40" height="46" />](https://docs.ropensci.org/targets/)
  `targets`, a Make-like pipeline tool for statistics and data science,
  Targets, a Make-like pipeline tool for statistics and data science,
has integrated and adopted `crew` as its default high-performance
computing backend.

[<img alt="crew" src="https://github.com/wlandau/crew/raw/main/man/figures/logo.png" width="40" height="46" />](https://wlandau.github.io/crew/)
  `crew` is a distributed worker-launcher extending `mirai` to different
  Crew is a distributed worker-launcher extending `mirai` to different
distributed computing platforms, from traditional clusters to cloud
services.

Expand Down

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