Support progress bar for skill.

.gitignore

@@ -1,3 +1,4 @@
 dist
 tests/__pycache__
 skillmap/__pycache__
+__pycache__

CHANGELOG.md

@@ -1,3 +1,5 @@
+# 0.3.0 - 2022-03-01
+* support progress bar for skill
 # 0.2.3 - 2022-02-27
 * add a default skill map name and mark python 3.8 to be the min version
 # 0.2.2 - 2022-02-27

docs/skillmap_descriptor.md

@@ -26,10 +26,7 @@
   * `name`: [optional] the name of the skillmap/group/skill. It will be used as a label in the diagram. .
   * `icon`: [optional] a fontawsome icon name. It will be used as an icon in the diagram. You can find the fontawsome icon list [here](https://fontawesome.com/v4.7.0/icons/).
   * `requires`: [optional] a list of strings. It indicates a list of skill groups or skills to be learned before this learning this skill group/skill. where each string is a toml table name of a group/skill. It will be rendered as an edge(s) from one node to another. 
-  * `status`: [optional] only applies to a `skill` toml table. It indicates the status of the skill. Nodes will be rendered with different colors according to different statuses. It can be one of the following:
-    * `new`: the skill is newly unveiled and not master/learned yet (default value if not specified)
-    * `beingLearned`: the skill is being leanred currently.
-    * `learned`: the skill is learned.
+  * `progress`: [optional] only applies to a `skill` toml table. It is a fraction number string like `1/3` that indicates the learning progression of the skill. A progress bar like `■□□` will be shown in the skill node to visualize the progress. Skill nodes will be rendered with different colors according to different progresses (zero progress, ongoing, finished).
   * locked skill: if a skill table doesn't have name or icon, it will be rendered as a locked skill (a grey box + lock icon + `???` as name).
 
 ## Example

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "skillmap"
-version = "0.2.3"
+version = "0.3.0"
 description = "Skillmap generates a skill tree from a toml file"
 authors = ["Yue Ni <[email protected]>"]
 readme = "README.md"

skillmap/main.py

@@ -7,7 +7,7 @@
 from distutils.util import strtobool
 
 from skillmap.skillmap_parser import SkillMapParser
-from skillmap.skillmap_visitor import SkillMapVisitor
+from skillmap.nodes.skillmap_node import create_skillmap_graph
 
 import importlib.metadata
 
@@ -32,13 +32,6 @@ def _skillmap_parser():
         help="show version number",
     )
 
-    # parser.add_argument(
-    #     "-f",
-    #     "--format",
-    #     type=str,
-    #     default="mermaid",
-    #     help="export format, [mermaid] are supported",
-    # )
     return parser
 
 
@@ -50,7 +43,7 @@ def parse_sys_args(sys_args):
 
 def generate(skillmap_file, format = None):
     skillmap_dict = SkillMapParser().parse(skillmap_file)
-    skillmap_graph = SkillMapVisitor().visit(skillmap_dict)
+    skillmap_graph = create_skillmap_graph(skillmap_dict)
     return skillmap_graph
 
 

skillmap/nodes/common.py

@@ -0,0 +1,21 @@
+SECTION_SEPARATOR = "%" * 30
+
+def get_required_node_edges(qualified_node_id, required_node_ids):
+    node_requires = [
+        f"{required_node_id}-->{qualified_node_id}"
+        for required_node_id in required_node_ids
+    ]
+    return "\n".join(node_requires)
+
+
+def get_icon(dict_value):
+    icon = ""
+    if "icon" in dict_value:
+        icon = f"fa:fa-{dict_value['icon']}"
+    return icon
+
+
+def get_node_content(items, multi_lines_layout=True):
+    separator = "<br/>" if multi_lines_layout else " "
+    # join non empty items
+    return separator.join([i for i in items if i])

skillmap/nodes/group_node.py

@@ -0,0 +1,76 @@
+from skillmap.nodes.common import get_icon, get_node_content, get_required_node_edges, SECTION_SEPARATOR
+from skillmap.nodes.skill_node import create_skill_node
+
+
+def _qualify(group_id):
+    return f"groups.{group_id}"
+
+
+def _qualified_skill_id(qualified_group_id, skill_id):
+    return f"{qualified_group_id}.skills.{skill_id}"
+
+
+def create_groups_edges(map_id, groups):
+    group_ids = [
+        _qualify(group_id)
+        for group_id, group_value in groups.items()
+        if "requires" not in group_value  # all groups without requires
+    ]
+    groups_edges = "\n".join([f"{map_id}-->{gid}" for gid in group_ids])
+    return groups_edges
+
+
+def get_group_skills_list(qualified_group_id, group_skills):
+    group_skills = [
+        create_skill_node(
+            _qualified_skill_id(qualified_group_id, skill_id), skill_value
+        )
+        for skill_id, skill_value in group_skills.items()
+    ]
+    return "\n".join(group_skills)
+
+
+def get_group_status(group_skills):
+    for _, skill_value in group_skills.items():
+        skill_status = skill_value.get("status", "")
+        if skill_status not in ("new", ""):
+            return "normal"
+    return "new"
+
+
+def create_group_subgraph(group_id, group_value):
+    qualified_group_id = _qualify(group_id)
+    group_name = group_value.get("name", "")
+    group_icon = get_icon(group_value)
+    group_icon_label = get_node_content([group_icon, group_name], False)
+    group_skills_list = get_group_skills_list(
+        qualified_group_id, group_value.get("skills", {})
+    )
+    group_status = get_group_status(group_value.get("skills", {}))
+
+    group_requires_list = get_required_node_edges(
+        qualified_group_id, group_value.get("requires", [])
+    )
+
+    group_id_and_name = f"subgraph {qualified_group_id}[{group_icon_label}]"
+    group_style = f"class {qualified_group_id} {group_status}SkillGroup;"
+    group_subgraph_end = "end"
+    sections = [
+        SECTION_SEPARATOR,
+        group_id_and_name,
+        group_skills_list,
+        group_subgraph_end,
+        group_style,
+        group_requires_list,
+    ]
+
+    group_graph = "\n".join(sections)
+    return group_graph
+
+
+def create_group_subgraphs(groups):
+    group_graphs = [
+        create_group_subgraph(group_id, group_value)
+        for group_id, group_value in groups.items()
+    ]
+    return "\n\n".join(group_graphs)

skillmap/nodes/skill_node.py

@@ -0,0 +1,50 @@
+from skillmap.nodes.common import get_icon, get_node_content, get_required_node_edges
+from fractions import Fraction
+from enum import Enum
+
+class Status(Enum):
+    NEW = "new"
+    BEING_LEANRED = "beingLearned"
+    LEARNED = "learned"
+    UNKNOWN = "unknown"
+
+def _is_locked_skill_value(skill_value):
+    icon = skill_value.get("icon", None)
+    status = skill_value.get("status", None)
+    return icon == "lock" and status == "unknown"
+
+def get_progress(skill_value):
+    if _is_locked_skill_value(skill_value):
+        return ("", Status.UNKNOWN)
+
+    progress_string = skill_value.get("progress", None)
+    if progress_string:
+        Fraction(progress_string)
+        current, total = map(int, progress_string.split("/"))
+        status = Status.NEW
+        if current > 0:
+            status = Status.BEING_LEANRED if current < total else Status.LEARNED
+
+        return (f"{'■' * current}{'□' * (total - current)}", status)
+    else:
+        return ("", Status.NEW)
+
+
+def create_skill_node(skill_id, skill_value):
+    if not skill_value:
+        locked_skill_value = {"name": "???", "icon": "lock", "status": "unknown"}
+        skill_value = locked_skill_value
+    skill_name = skill_value.get("name", "")
+    skill_icon = get_icon(skill_value)
+    skill_progress, skill_status = get_progress(skill_value)
+    skill_icon_label = get_node_content([skill_icon, skill_name, skill_progress])
+    skill_id_and_name = f"{skill_id}(\"{skill_icon_label}\")"
+    skill_style = f"class {skill_id} {skill_status.value}Skill;"
+    skill_requires = get_required_node_edges(skill_id, skill_value.get("requires", []))
+    sections = [
+        skill_id_and_name,
+        skill_style,
+        skill_requires,
+    ]
+    skill_graph = "\n".join(sections)
+    return skill_graph

skillmap/nodes/skillmap_node.py

@@ -0,0 +1,43 @@
+from skillmap.theme_loader import load_theme
+from skillmap.nodes.common import get_icon, get_node_content, SECTION_SEPARATOR
+from skillmap.nodes.group_node import create_group_subgraphs, create_groups_edges
+import re
+
+
+def alphanumerize(s):
+    return re.sub(r"\W+", "_", s)
+
+
+def get_orientation(skill_map_dict):
+    orientation = skill_map_dict.get("orientation", "TD")
+    if orientation not in ["TD", "TB", "BT", "RL", "LR"]:
+        orientation = "TD"
+    return orientation
+
+
+# generate a mermaid graph from a skill map toml dict
+def create_skillmap_graph(skill_map):
+    skill_map_dict = skill_map.get("skillmap", {})
+    map_name = skill_map_dict.get("name", "unamed_skill_map")
+    map_id = alphanumerize(map_name)
+    theme = skill_map_dict.get("theme", "ocean")
+    orientation = get_orientation(skill_map_dict)
+    map_icon = get_icon(skill_map_dict)
+    map_icon_label = get_node_content([map_icon, map_name])
+
+    map_to_group_edges = create_groups_edges(map_id, skill_map.get("groups", {}))
+    map_group_subgraphs = create_group_subgraphs(skill_map.get("groups", {}))
+
+    skill_map_node = f"{map_id}({map_icon_label})"
+    skill_map_node_style = f"class {map_id} normalSkillGroup;"
+    skill_map_header = f"flowchart {orientation}"
+    sections = [
+        skill_map_header,
+        skill_map_node,
+        map_group_subgraphs,
+        SECTION_SEPARATOR,
+        map_to_group_edges,
+        load_theme(theme),
+        skill_map_node_style,
+    ]
+    return "\n".join(sections)