library(projmgr)

cfr_plan_txt <- "
- title: 2009 is a problem
  description: >
    The 2009 files continue to display weird results
  issue:
    - title: Investigate issue
      body: Not sure about path
      assignees: [willwheels]
      labels: [long-term]


- title: Redo network
  description: >
    Recreate network with tidygraph; do all data steps in initial dataframe
  issue:
    - title: Remove igraph steps
      body: nuke igraph
    - title: Move data steps
      body: Move all weight and size calculations to data frame creation
    - title: Visualizations
      body: recreate network visualizations"

cfr_plan <- read_plan(cfr_plan_txt)

cfr_repo_ref <- create_repo_ref("willwheels", "CFR")
#> Requests will authenticate with GITHUB_PAT

check_credentials(cfr_repo_ref)
#> -- With provided credentials -- 
#> + Login: willwheels
#> + Type: User
#> -- In the CFR repo -- 
#> + Admin: FALSE
#> + Push: FALSE
#> + Pull: FALSE

cfr_plan
#> Plan: 
#> 1. 2009 is a problem (1 issues) 
#> 2. Redo network (3 issues)

cfr_repo_ref
#> + Repository Owner: willwheels
#> + Repository: CFR
#> + From URL: https://api.github.com/
#> + Authenticating with: GITHUB_PAT

post_plan(cfr_repo_ref, cfr_plan)
#> Error in gh::gh(endpoint = paste0(ref$base_url, ref$repo_path, api_endpoint), : GitHub API error (404): 404 Not Found
#>   Not Found

library(projmgr)

cfr_plan_txt <- "
- title: 2009 is a problem
  description: >
    The 2009 files continue to display weird results
  issue:
    - title: Investigate issue
      body: Not sure about path
      assignees: [willwheels]
      labels: [long-term]


- title: Redo network
  description: >
    Recreate network with tidygraph; do all data steps in initial dataframe
  issue:
    - title: Remove igraph steps
      body: nuke igraph
    - title: Move data steps
      body: Move all weight and size calculations to data frame creation
    - title: Visualizations
      body: recreate network visualizations"

cfr_plan <- read_plan(cfr_plan_txt)

cfr_repo_ref <- create_repo_ref("willwheels", "CFR")
#> Requests will authenticate with GITHUB_PAT

check_credentials(cfr_repo_ref)
#> -- With provided credentials -- 
#> + Login: willwheels
#> + Type: User
#> -- In the CFR repo -- 
#> + Admin: TRUE
#> + Push: TRUE
#> + Pull: TRUE

cfr_plan
#> Plan: 
#> 1. 2009 is a problem (1 issues) 
#> 2. Redo network (3 issues)

cfr_repo_ref
#> + Repository Owner: willwheels
#> + Repository: CFR
#> + From URL: https://api.github.com/
#> + Authenticating with: GITHUB_PAT

post_plan(cfr_repo_ref, cfr_plan)
#>   milestone_number   milestone_title issue_number         issue_title
#> 1                1 2009 is a problem            5   Investigate issue
#> 2                2      Redo network            6 Remove igraph steps
#> 3                2      Redo network            7     Move data steps
#> 4                2      Redo network            8      Visualizations

library(projmgr)
library(magrittr)
repo <- create_repo_ref("JiaxiangBU", "tutoring")
#> Requests will authenticate with GITHUB_PAT
issue_list <- get_issues(repo) %>% parse_issues()
nrow(issue_list)
#> [1] 28

update_issue <- function(ref, issue_number, ...) {
    ...
}

library(projmgr)
my_repo <- create_repo_ref('andrie', 'spanner')
#> Requests will authenticate with GITHUB_PAT
get_issues(my_repo, state = 'open') %>% parse_issues()
#> Error in `$<-.data.frame`(`*tmp*`, "labels_name", value = structure(c("bug", : replacement has 2 rows, data has 1

library(projmgr)
# connect to repo (emily i added you just in case)
my_ref <- create_repo_ref("sctyner", "magic-tidying-data")
#> Requests will authenticate with GITHUB_PAT

# run to make sure you can read/write
check_credentials(my_ref)
#> -- With provided credentials -- 
#> + Login: sctyner
#> + Type: User
#> -- In the magic-tidying-data repo -- 
#> + Admin: TRUE
#> + Push: TRUE
#> + Pull: TRUE

# yaml examples 

broken <-"- title: Enter a short, informative title of your goal
  description: >
    Enter a longer description of the objectives
  due_on: 2018-12-31T12:59:59Z
  issue:
    - title: Title of task 1 to complete
      body: Describe this step
      assignees: [sctyner]
      labels: [a, b, c]
    - title: Title of task 2 to comple
      body: Describe this step
      labels: [low]

- title: Enter another short, informative title of your goal
  description: >
    Enter a longer description of the objectives
  issue:
    - title: Title of task 1 to complete
      body: Describe this step
    - title: Title of task 2 to complete
      body: Describe this step
"

okay <- "- title: Data cleaning and validation
  description: >
    We will conduct data quality checks,
    resolve issues with data quality, and
    document this process
  due_on: 2018-12-31T12:59:59Z
  issue:
    - title: Define data quality standards
      body: List out decision rules to check data quality
      assignees: [sctyner]
      labels: [a, b, c]
    - title: Assess data quality
      body: Use assertthat to test decision rules on dataset
      labels: [low]
    - title: Resolve data quality issues
      body: Conduct needed research to resolve any issues

- title: Exploratory data analysis
  description: >
    Create basic statistics and views to better
    understand dataset and relationships
  issue:
    - title: Summary statistics
      body: Calculate summary statistics
    - title: Visualizations
      body: Create univariate and bivariate plots
"

my_plan <- read_plan(broken)
er_plan <- read_plan(okay)

# comparing my_plan and er_plan
is.list(my_plan)
#> [1] TRUE
my_plan
#> Plan: 
#> 1. Enter a short, informative title of your goal (2 issues) 
#> 2. Enter another short, informative title of your goal (2 issues)
er_plan
#> Plan: 
#> 1. Data cleaning and validation (3 issues) 
#> 2. Exploratory data analysis (2 issues)

milestones <- lapply(my_plan,
                     FUN = function(x) x[intersect( names(x), c("title", help_post_milestone()) )])
milestones
#> [[1]]
#> [[1]]$title
#> [1] "Enter a short, informative title of your goal"
#> 
#> [[1]]$description
#> [1] "Enter a longer description of the objectives\n"
#> 
#> [[1]]$due_on
#> [1] "2018-12-31T12:59:59Z"
#> 
#> 
#> [[2]]
#> [[2]]$title
#> [1] "Enter another short, informative title of your goal"
#> 
#> [[2]]$description
#> [1] "Enter a longer description of the objectives\n"

milestoneser <- lapply(er_plan,
                       FUN = function(x) x[intersect( names(x), c("title", help_post_milestone()) )])
milestoneser
#> [[1]]
#> [[1]]$title
#> [1] "Data cleaning and validation"
#> 
#> [[1]]$description
#> [1] "We will conduct data quality checks, resolve issues with data quality, and document this process\n"
#> 
#> [[1]]$due_on
#> [1] "2018-12-31T12:59:59Z"
#> 
#> 
#> [[2]]
#> [[2]]$title
#> [1] "Exploratory data analysis"
#> 
#> [[2]]$description
#> [1] "Create basic statistics and views to better understand dataset and relationships\n"

issues_per_milestone <- vapply(my_plan, FUN = function(x) length(x[["issue"]]), FUN.VALUE = integer(1), USE.NAMES = FALSE )
issues_per_milestone
#> [1] 2 2

issues_per_milestoneer <- vapply(er_plan, FUN = function(x) length(x[["issue"]]), FUN.VALUE = integer(1), USE.NAMES = FALSE )
issues_per_milestoneer
#> [1] 3 2

milestone_title <- vapply(milestones, FUN = function(x) x[["title"]], FUN.VALUE = character(1))
milestone_title
#> [1] "Enter a short, informative title of your goal"      
#> [2] "Enter another short, informative title of your goal"


milestone_titleer <- vapply(milestoneser, FUN = function(x) x[["title"]], FUN.VALUE = character(1))
milestone_titleer
#> [1] "Data cleaning and validation" "Exploratory data analysis"

# here is where it explodes 
issues <- unlist( sapply(my_plan, FUN = function(x) x[["issue"]]), recursive = FALSE )
issueser <- unlist( sapply(er_plan, FUN = function(x) x[["issue"]]), recursive = FALSE )
issues
#> $title
#> [1] "Title of task 1 to complete"
#> 
#> $body
#> [1] "Describe this step"
#> 
#> $assignees
#> [1] "sctyner"
#> 
#> $labels
#> [1] "a" "b" "c"
#> 
#> $title
#> [1] "Title of task 2 to comple"
#> 
#> $body
#> [1] "Describe this step"
#> 
#> $labels
#> [1] "low"
#> 
#> $title
#> [1] "Title of task 1 to complete"
#> 
#> $body
#> [1] "Describe this step"
#> 
#> $title
#> [1] "Title of task 2 to complete"
#> 
#> $body
#> [1] "Describe this step"
issueser
#> [[1]]
#> [[1]]$title
#> [1] "Define data quality standards"
#> 
#> [[1]]$body
#> [1] "List out decision rules to check data quality"
#> 
#> [[1]]$assignees
#> [1] "sctyner"
#> 
#> [[1]]$labels
#> [1] "a" "b" "c"
#> 
#> 
#> [[2]]
#> [[2]]$title
#> [1] "Assess data quality"
#> 
#> [[2]]$body
#> [1] "Use assertthat to test decision rules on dataset"
#> 
#> [[2]]$labels
#> [1] "low"
#> 
#> 
#> [[3]]
#> [[3]]$title
#> [1] "Resolve data quality issues"
#> 
#> [[3]]$body
#> [1] "Conduct needed research to resolve any issues"
#> 
#> 
#> [[4]]
#> [[4]]$title
#> [1] "Summary statistics"
#> 
#> [[4]]$body
#> [1] "Calculate summary statistics"
#> 
#> 
#> [[5]]
#> [[5]]$title
#> [1] "Visualizations"
#> 
#> [[5]]$body
#> [1] "Create univariate and bivariate plots"

post_plan(my_ref, my_plan)
#> Warning in mapply(FUN = function(x, y) {: longer argument not a multiple of
#> length of shorter
#> Error in do.call(post_local, x): second argument must be a list
post_plan(my_ref, er_plan)
#>   milestone_number              milestone_title issue_number
#> 1                3 Data cleaning and validation            1
#> 2                3 Data cleaning and validation            2
#> 3                3 Data cleaning and validation            3
#> 4                4    Exploratory data analysis            4
#> 5                4    Exploratory data analysis            5
#>                     issue_title
#> 1 Define data quality standards
#> 2           Assess data quality
#> 3   Resolve data quality issues
#> 4            Summary statistics
#> 5                Visualizations