#!/usr/bin/env python
# coding: utf-8

# This notebooks is hosted on [codeberg](https://codeberg.org/cknoll/kram/src/branch/main/python-stuff/mastodon-discourse-visualization). It demonstrates how to generate the following toot-relation-graph.
# 

# In[1]:


from IPython.display import SVG, display, HTML; svg_fname = "toot-analysis-107742285383682464.svg"; svgfile = open(svg_fname, "r"); svg_data = svgfile.read(); svgfile.close(); display(SVG(svg_data))


# This notebook depends on some packages and files which are not part of this repo:
# 
# - https://mastodonpy.readthedocs.io/en/stable/index.html#
# - https://networkx.org/documentation/stable/reference/drawing.html
# - https://github.com/twosigma/nxv
# - https://codeberg.org/cknoll/cachewrapper (optional)
# 
# 
# Install these dependencies by 
# ```
# pip install mastodonpy networkx nxv
# 
# ```

# In[2]:


import time
print(time.ctime())
# https://github.com/cknoll/ipydex (optional)
get_ipython().run_line_magic('load_ext', 'ipydex.displaytools')


# In[3]:


from mastodon import Mastodon  # https://mastodonpy.readthedocs.io/en/stable/index.html#
import networkx as nx  # https://networkx.org/documentation/stable/reference/drawing.html
import nxv  # https://github.com/twosigma/nxv
from matplotlib import pyplot as plt
try:
    import cachewrapper as cw # https://codeberg.org/cknoll/cachewrapper (optional)
except ImportError:
    cw = None
from IPython.display import SVG, display, HTML


masto_url = "https://social.tchncs.de"
cache_path = "cache.pcl"


# mc means "mastodon-client"
mc = Mastodon(
    access_token = 'pymastoclient_usercred.secret',
    api_base_url = masto_url,
)

# this is optional (to save api-calls)
if 0 and cw:
    mc = cw.CacheWrapper(mc)
    mc.load_cache(cache_path)

# id taken from local url (click on `···`→ expand this post (in the toot)  )
# 107742285383682464
root_id = "107742285383682464"
res = mc.status_context(root_id) ##:i
#mc.save_cache(cache_path)

ancestors = res["ancestors"] ##:i
descendants = res["descendants"] ##:i


# In[4]:


res.keys()


# In[5]:


# ancestors


# In[6]:


# instantiate the default color_cycler from matlotlib
color_cycler = plt.rcParamsDefault['axes.prop_cycle']()
# next(color_cycler) -> {'color': '#2ca02c'} etc


# In[7]:


author_color_map = {}


# In[8]:


def get_author_color(data):
    aid = data["account"]["id"]
    color = author_color_map.get(aid)
    if color:
        return color
    else:
        # get new color from cycler, save it, return it
        color = next(color_cycler)["color"]
        author_color_map[aid] = color
        return color
    


# In[9]:


class Node(object):
    def __init__(self, data: dict):
        self.id = str(data["id"])
        self.label = self.id
        self.data = data
        self.title= "foo"
        
        
        author = data["account"]["display_name"]
        N = 10
        if len(author) > N:
            author = f"{author[:N-2]}…"
        # label-trick: generate strings like r'{K12345}'
        # these can be substituted later -> two keys for linebreak
        self.repr_str = f"{author}:\n{{K{self.id}}}\n{{X{self.id}}}"
        
        self.style_dict = {
            "color": get_author_color(data),
            "fillcolor": get_author_color(data)+"20", # add low alpha-value for transparency
            "style": "filled",
            "shape": "circle",
            "fixedsize": True,
            "width": 0.7,
            "fontsize": 8,
            "penwidth": 2,

        }

    def __repr__(self):
        
        return self.repr_str


# In[10]:


G = nx.DiGraph()

root_node = Node(data=mc.status(root_id))
id_map = {root_id: root_node}

G.add_node(root_node)
parent = root_node

for obj_data in descendants:
    node = Node(obj_data)
    id_map[node.id] = node
    
    parent = id_map[str(node.data["in_reply_to_id"])]
    G.add_node(node, color="red", shape="pentagon")
    G.add_edge(parent, node)
    
    


# In[11]:


nn = list(G.nodes)[0]


# In[12]:


import bleach


# In[13]:


bleach.clean(nn.data["content"], tags=[], strip=True)


# In[14]:


# <title>node0009</title>
old_title_str_template = "<title>node{:04d}</title>" 
new_title_str_template = "<title>{}</title>"


# generate replacement tuples
rpl_tuples = []
for i, node in enumerate(G.nodes):
    s1 = old_title_str_template.format(i)
    stripped_content = bleach.clean(node.data["content"], tags=[], strip=True)
    s2 = new_title_str_template.format(stripped_content)
    rpl_tuples.append((s1, s2))


# In[15]:


# see https://nxv.readthedocs.io/en/latest/reference.html#styling
style = nxv.Style(
    graph={"rankdir": "TB"},
    node=lambda u, d: u.style_dict,
        # u is a node and d is its attribute dict (which is ignored here)
    edge=lambda u, v, d: {"style": "solid", "arrowType": "normal", "label": ""},
)



svg_data = nxv.render(G, style, format="svg")

entity_links = []

for node in G.nodes.keys():
    date = node.data["created_at"]
    str1 = f'<a href="{node.data["url"]}">{date.strftime("%Y-%m-%d")}</a>'
    str2 = f'<a href="{node.data["url"]}">{date.strftime("%H:%M:%S")}</a>'
    entity_links.append((f"K{node.id}", str1))
    entity_links.append((f"X{node.id}", str2))

# insert links to wiki data urls
svg_data = svg_data.decode("utf8").format(**dict(entity_links))

for s1, s2 in rpl_tuples:
    svg_data = svg_data.replace(s1, s2)

svg_data = svg_data.encode("utf8")

svg_fname = f"toot-analysis-{root_id}.svg"

with open(svg_fname, "wb") as svgfile:
    svgfile.write(svg_data)

#display(SVG(svg_data))

display(HTML(f"<a href='{svg_fname}'>{svg_fname}</a>"))


# In[16]:


# display(HTML(f"<img src='{svg_fname}'>")) # this is prone to unexpected behavior due to caching
display(SVG(svg_data))
# click in the gray area below `In [..]` to disable/enable scrolling