fio-l1-paris-kml-pois

Status: done
Score: 1.000
Duration: 4:15
Cost: 1.35¢
Model: deepseek/deepseek-v4-flash

Map (reference ← swipe → agent)

0:00
A colleague handed me `paris_late_night_pois`. Our internal map server only takes flat GeoJSON or GeoParquet, so please convert it to `paris_pois.geojson`, one row per placemark. Keep `name`, include the source's classification/grouping as a `category` column, and pull each entry's 'last verified' date out of the HTML blurb into a `verified_date` column as an ISO date. We want to flag stale records.
0:00
System info
{
  "adapter": "openrouter",
  "model": "deepseek/deepseek-v4-flash",
  "base_url": "https://openrouter.ai/api/v1"
}
0:05
Let me start by exploring the working directory to understand what we're working with.
0:05
Bash ls -la /work/
total 20
drwxr-xr-x 1 agent agent    50 Jun 16 23:17 .
drwxr-xr-x 1 root  root     14 Jun 16 23:17 ..
-rw-r--r-- 1 agent agent 18305 Jun 16 23:17 paris_late_night_pois.kml
0:13
Let's first look at the KML file to understand its structure.
0:13
Read /work/paris_late_night_pois.kml
     1	<?xml version="1.0" encoding="UTF-8"?>
     2	<kml xmlns="http://www.opengis.net/kml/2.2">
     3	<Document>
     4	  <name>Late-night POIs (RATP night-bus study)</name>
     5	  <Folder>
     6	    <name>Cafés ouverts tard</name>
     7	    <Placemark>
     8	      <name>% Arabica</name>
     9	      <description><![CDATA[<b>% Arabica</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/0">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-01-01]]></description>
    10	      <Point>
    11	        <coordinates>2.324676,48.854156,0</coordinates>
    12	      </Point>
    13	    </Placemark>
    14	    <Placemark>
    15	      <name>1T. rue Scribe</name>
    16	      <description><![CDATA[<b>1T. rue Scribe</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/1">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-08-14]]></description>
    17	      <Point>
    18	        <coordinates>2.329774,48.870581,0</coordinates>
    19	      </Point>
    20	    </Placemark>
    21	    <Placemark>
    22	      <name>1ndix Café</name>
    23	      <description><![CDATA[<b>1ndix Café</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/2">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-03-27]]></description>
    24	      <Point>
    25	        <coordinates>2.341361,48.880764,0</coordinates>
    26	      </Point>
    27	    </Placemark>
    28	    <Placemark>
    29	      <name>2 Steps Café</name>
    30	      <description><![CDATA[<b>2 Steps Café</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/3">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-10-12]]></description>
    31	      <Point>
    32	        <coordinates>2.376626,48.866261,0</coordinates>
    33	      </Point>
    34	    </Placemark>
    35	    <Placemark>
    36	      <name>3234 Café - Trente Deux Trente Quatre</name>
    37	      <description><![CDATA[<b>3234 Café - Trente Deux Trente Quatre</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/4">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-05-25]]></description>
    38	      <Point>
    39	        <coordinates>2.376249,48.853167,0</coordinates>
    40	      </Point>
    41	    </Placemark>
    42	    <Placemark>
    43	      <name>360 Cafe</name>
    44	      <description><![CDATA[<b>360 Cafe</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/5">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-12-10]]></description>
    45	      <Point>
    46	        <coordinates>2.321838,48.842293,0</coordinates>
    47	      </Point>
    48	    </Placemark>
    49	    <Placemark>
    50	      <name>3w Cafe Paris</name>
    51	      <description><![CDATA[<b>3w Cafe Paris</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/6">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-07-23]]></description>
    52	      <Point>
    53	        <coordinates>2.327530,48.851560,0</coordinates>
    54	      </Point>
    55	    </Placemark>
    56	    <Placemark>
    57	      <name>48 Collagen Café</name>
    58	      <description><![CDATA[<b>48 Collagen Caf√©</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/7">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-02-08]]></description>
    59	      <Point>
    60	        <coordinates>2.340460,48.874840,0</coordinates>
    61	      </Point>
    62	    </Placemark>
    63	    <Placemark>
    64	      <name>86 Champs Elysées</name>
    65	      <description><![CDATA[<b>86 Champs Elysées</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/8">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-09-21]]></description>
    66	      <Point>
    67	        <coordinates>2.303767,48.871387,0</coordinates>
    68	      </Point>
    69	    </Placemark>
    70	    <Placemark>
    71	      <name>A la Ville de Paris</name>
    72	      <description><![CDATA[<b>A la Ville de Paris</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/9">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-04-06]]></description>
    73	      <Point>
    74	        <coordinates>2.344280,48.870530,0</coordinates>
    75	      </Point>
    76	    </Placemark>
    77	    <Placemark>
    78	      <name>A minima cafe</name>
    79	      <description><![CDATA[<b>A minima cafe</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/10">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-11-19]]></description>
    80	      <Point>
    81	        <coordinates>2.381290,48.845300,0</coordinates>
    82	      </Point>
    83	    </Placemark>
    84	    <Placemark>
    85	      <name>AD DictCafé</name>
    86	      <description><![CDATA[<b>AD DictCafé</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/11">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-06-04]]></description>
    87	      <Point>
    88	        <coordinates>2.390577,48.849002,0</coordinates>
    89	      </Point>
    90	    </Placemark>
    91	    <Placemark>
    92	      <name>ANGIOLO</name>
    93	      <description><![CDATA[<b>ANGIOLO</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/12">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-01-17]]></description>
    94	      <Point>
    95	        <coordinates>2.331682,48.854538,0</coordinates>
    96	      </Point>
    97	    </Placemark>
    98	    <Placemark>
    99	      <name>Abaita</name>
   100	      <description><![CDATA[<b>Abaita</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/13">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-08-02]]></description>
   101	      <Point>
   102	        <coordinates>2.368446,48.864406,0</coordinates>
   103	      </Point>
   104	    </Placemark>
   105	    <Placemark>
   106	      <name>Absinthe Café</name>
   107	      <description><![CDATA[<b>Absinthe Café</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/14">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-03-15]]></description>
   108	      <Point>
   109	        <coordinates>2.357228,48.865564,0</coordinates>
   110	      </Point>
   111	    </Placemark>
   112	    <Placemark>
   113	      <name>Acai &amp; You</name>
   114	      <description><![CDATA[<b>Acai &amp; You</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/15">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-10-28]]></description>
   115	      <Point>
   116	        <coordinates>2.339001,48.854247,0</coordinates>
   117	      </Point>
   118	    </Placemark>
   119	    <Placemark>
   120	      <name>Adulis Cafe Abyssinien</name>
   121	      <description><![CDATA[<b>Adulis Cafe Abyssinien</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/16">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-05-13]]></description>
   122	      <Point>
   123	        <coordinates>2.346929,48.851763,0</coordinates>
   124	      </Point>
   125	    </Placemark>
   126	    <Placemark>
   127	      <name>After Place</name>
   128	      <description><![CDATA[<b>After Place</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/17">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-12-26]]></description>
   129	      <Point>
   130	        <coordinates>2.336121,48.864266,0</coordinates>
   131	      </Point>
   132	    </Placemark>
   133	    <Placemark>
   134	      <name>After Place</name>
   135	      <description><![CDATA[<b>After Place</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/18">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-07-11]]></description>
   136	      <Point>
   137	        <coordinates>2.351101,48.862294,0</coordinates>
   138	      </Point>
   139	    </Placemark>
   140	    <Placemark>
   141	      <name>After Place</name>
   142	      <description><![CDATA[<b>After Place</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/19">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-02-24]]></description>
   143	      <Point>
   144	        <coordinates>2.361560,48.869500,0</coordinates>
   145	      </Point>
   146	    </Placemark>
   147	  </Folder>
   148	  <Folder>
   149	    <name>Bibliothèques de nuit</name>
   150	    <Placemark>
   151	      <name>AUP Housing</name>
   152	      <description><![CDATA[<b>AUP Housing</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/20">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-09-09]]></description>
   153	      <Point>
   154	        <coordinates>2.306008,48.861754,0</coordinates>
   155	      </Point>
   156	    </Placemark>
   157	    <Placemark>
   158	      <name>Academie de Medical</name>
   159	      <description><![CDATA[<b>Academie de Medical</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/21">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-04-22]]></description>
   160	      <Point>
   161	        <coordinates>2.334208,48.856342,0</coordinates>
   162	      </Point>
   163	    </Placemark>
   164	    <Placemark>
   165	      <name>Ancêtres Italiens</name>
   166	      <description><![CDATA[<b>Ancêtres Italiens</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/22">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-11-07]]></description>
   167	      <Point>
   168	        <coordinates>2.363314,48.873246,0</coordinates>
   169	      </Point>
   170	    </Placemark>
   171	    <Placemark>
   172	      <name>Apfelbaum Library</name>
   173	      <description><![CDATA[<b>Apfelbaum Library</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/23">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-06-20]]></description>
   174	      <Point>
   175	        <coordinates>2.330685,48.849518,0</coordinates>
   176	      </Point>
   177	    </Placemark>
   178	    <Placemark>
   179	      <name>Archives de l'AP-HP</name>
   180	      <description><![CDATA[<b>Archives de l&#x27;AP-HP</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/24">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-01-05]]></description>
   181	      <Point>
   182	        <coordinates>2.366407,48.857094,0</coordinates>
   183	      </Point>
   184	    </Placemark>
   185	    <Placemark>
   186	      <name>Arthur Rimbaud Library</name>
   187	      <description><![CDATA[<b>Arthur Rimbaud Library</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/25">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-08-18]]></description>
   188	      <Point>
   189	        <coordinates>2.355874,48.856134,0</coordinates>
   190	      </Point>
   191	    </Placemark>
   192	    <Placemark>
   193	      <name>Association Bibliotheque Braille Enfantine</name>
   194	      <description><![CDATA[<b>Association Bibliotheque Braille Enfantine</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/26">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-03-03]]></description>
   195	      <Point>
   196	        <coordinates>2.372404,48.868038,0</coordinates>
   197	      </Point>
   198	    </Placemark>
   199	    <Placemark>
   200	      <name>Association Francaise de Therapie</name>
   201	      <description><![CDATA[<b>Association Francaise de Therapie</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/27">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-10-16]]></description>
   202	      <Point>
   203	        <coordinates>2.308679,48.870960,0</coordinates>
   204	      </Point>
   205	    </Placemark>
   206	    <Placemark>
   207	      <name>Attractive</name>
   208	      <description><![CDATA[<b>Attractive</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/28">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-05-01]]></description>
   209	      <Point>
   210	        <coordinates>2.326704,48.866369,0</coordinates>
   211	      </Point>
   212	    </Placemark>
   213	    <Placemark>
   214	      <name>BNF</name>
   215	      <description><![CDATA[<b>BNF</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/29">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-12-14]]></description>
   216	      <Point>
   217	        <coordinates>2.338076,48.867811,0</coordinates>
   218	      </Point>
   219	    </Placemark>
   220	    <Placemark>
   221	      <name>BPI Bibliotheque Publique D Information</name>
   222	      <description><![CDATA[<b>BPI Bibliotheque Publique D Information</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/30">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-07-27]]></description>
   223	      <Point>
   224	        <coordinates>2.352378,48.859478,0</coordinates>
   225	      </Point>
   226	    </Placemark>
   227	    <Placemark>
   228	      <name>BPI-Beaubourg</name>
   229	      <description><![CDATA[<b>BPI-Beaubourg</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/31">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-02-12]]></description>
   230	      <Point>
   231	        <coordinates>2.351867,48.860532,0</coordinates>
   232	      </Point>
   233	    </Placemark>
   234	    <Placemark>
   235	      <name>Beaubourg Librairie des Arts</name>
   236	      <description><![CDATA[<b>Beaubourg Librairie des Arts</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/32">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-09-25]]></description>
   237	      <Point>
   238	        <coordinates>2.356791,48.865189,0</coordinates>
   239	      </Point>
   240	    </Placemark>
   241	    <Placemark>
   242	      <name>Bib Cent du Service de Sante Des Armees</name>
   243	      <description><![CDATA[<b>Bib Cent du Service de Sante Des Armees</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/33">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-04-10]]></description>
   244	      <Point>
   245	        <coordinates>2.341252,48.841187,0</coordinates>
   246	      </Point>
   247	    </Placemark>
   248	    <Placemark>
   249	      <name>Bibliothe que Centrale - Muse'um national d'histoire naturelle (MNHN)</name>
   250	      <description><![CDATA[<b>Bibliothe que Centrale - Muse&#x27;um national d&#x27;histoire naturelle (MNHN)</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/34">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-11-23]]></description>
   251	      <Point>
   252	        <coordinates>2.355838,48.842660,0</coordinates>
   253	      </Point>
   254	    </Placemark>
   255	  </Folder>
   256	  <Folder>
   257	    <name>Tours et infos touristiques</name>
   258	    <Placemark>
   259	      <name>24hourstravel</name>
   260	      <description><![CDATA[<b>24hourstravel</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/35">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-06-08]]></description>
   261	      <Point>
   262	        <coordinates>2.347810,48.864739,0</coordinates>
   263	      </Point>
   264	    </Placemark>
   265	    <Placemark>
   266	      <name>2CVPrivateParis</name>
   267	      <description><![CDATA[<b>2CVPrivateParis</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/36">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-01-21]]></description>
   268	      <Point>
   269	        <coordinates>2.337967,48.889998,0</coordinates>
   270	      </Point>
   271	    </Placemark>
   272	    <Placemark>
   273	      <name>382444404</name>
   274	      <description><![CDATA[<b>382444404</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/37">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-08-06]]></description>
   275	      <Point>
   276	        <coordinates>2.326910,48.870680,0</coordinates>
   277	      </Point>
   278	    </Placemark>
   279	    <Placemark>
   280	      <name>A French Frye in Paris</name>
   281	      <description><![CDATA[<b>A French Frye in Paris</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/38">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-03-19]]></description>
   282	      <Point>
   283	        <coordinates>2.340830,48.861240,0</coordinates>
   284	      </Point>
   285	    </Placemark>
   286	    <Placemark>
   287	      <name>Aeon Tours of Paris</name>
   288	      <description><![CDATA[<b>Aeon Tours of Paris</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/39">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-10-04]]></description>
   289	      <Point>
   290	        <coordinates>2.358590,48.863780,0</coordinates>
   291	      </Point>
   292	    </Placemark>
   293	    <Placemark>
   294	      <name>Agence ORNIcom : location de gyropode Segway à Paris et sur toute la France</name>
   295	      <description><![CDATA[<b>Agence ORNIcom : location de gyropode Segway à Paris et sur toute la France</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/40">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-05-17]]></description>
   296	      <Point>
   297	        <coordinates>2.303244,48.852662,0</coordinates>
   298	      </Point>
   299	    </Placemark>
   300	    <Placemark>
   301	      <name>Al Abrar Voyages</name>
   302	      <description><![CDATA[<b>Al Abrar Voyages</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/41">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-12-02]]></description>
   303	      <Point>
   304	        <coordinates>2.312770,48.886310,0</coordinates>
   305	      </Point>
   306	    </Placemark>
   307	    <Placemark>
   308	      <name>Allison Zinder</name>
   309	      <description><![CDATA[<b>Allison Zinder</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/42">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-07-15]]></description>
   310	      <Point>
   311	        <coordinates>2.398851,48.862635,0</coordinates>
   312	      </Point>
   313	    </Placemark>
   314	    <Placemark>
   315	      <name>Association Touristique Cheminots</name>
   316	      <description><![CDATA[<b>Association Touristique Cheminots</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/43">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-02-28]]></description>
   317	      <Point>
   318	        <coordinates>2.371287,48.846263,0</coordinates>
   319	      </Point>
   320	    </Placemark>
   321	    <Placemark>
   322	      <name>Avenir Tourisme</name>
   323	      <description><![CDATA[<b>Avenir Tourisme</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/44">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-09-13]]></description>
   324	      <Point>
   325	        <coordinates>2.358040,48.868509,0</coordinates>
   326	      </Point>
   327	    </Placemark>
   328	  </Folder>
   329	</Document>
   330	</kml>
0:40
Let me analyze the KML file structure:

1. It's a KML file with a Document containing multiple Folders
2. Each Folder has a `<name>` (e.g. "Cafés ouverts tard", "Bibliothèques de nuit", "Tours et infos touristiques")
3. Each Placemark has:
   - `<name>` - the place name
   - `<description>` with HTML CDATA containing category, link, and "Dernière vérification : YYYY-MM-DD"
   - `<Point><coordinates>` - lon,lat,alt

I need to convert this to a flat GeoJSON with:
- `name` column
- `category` column (from the Folder name / classification)
- `verified_date` column as ISO date (parsed from the description HTML "Dernière vérification : YYYY-MM-DD")
- One row per placemark

Let me write a Python script using a library. I could use geopandas with its KML driver, or just parse the XML manually. Since KML parsing in geopandas can be finicky, let me use a manual approach with xml.etree.ElementTree and output proper GeoJSON.

Actually, let me first check what libraries are available.
0:40
Bash python3 -c "import geopandas; print(geopandas.__version__)"
1.1.3
1:11
Now I need to write a Python script that:

1. Reads the KML file
2. Parses each Placemark
3. Extracts:
   - `name` from the `<name>` element
   - `category` from the Folder's `<name>` that contains the Placemark
   - `verified_date` from the HTML description blurb (extract the ISO date after "Dernière vérification : ")
   - Geometry (Point coordinates)
4. Writes out to `paris_pois.geojson`

Let me write a script using geopandas to read the KML, then parse the description HTML to extract the category and verified_date.

Actually, geopandas can read KML but it might not preserve the folder/category structure. Let me check what we get.

Actually, let me use a more direct approach. I'll use Python with lxml or xml.etree.ElementTree to parse the KML, extract all attributes, build a GeoDataFrame, and write to GeoJSON.
1:11
Bash cat << 'PYEOF' > /work/solve.py
cat << 'PYEOF' > /work/solve.py
import geopandas as gpd
import pandas as pd
from shapely.geometry import Point
from lxml import etree
import re
import json

# Parse KML with lxml (handles namespaces)
NS = {"kml": "http://www.opengis.net/kml/2.2"}

tree = etree.parse("/work/paris_late_night_pois.kml")
root = tree.getroot()

rows = []

# Iterate over Folders (each Folder has a <name> which is the category)
for folder in root.findall(".//kml:Folder", NS):
    category = folder.findtext("kml:name", NS)
    if category is None:
        continue
    
    for pm in folder.findall("kml:Placemark", NS):
        name = pm.findtext("kml:name", NS) or ""
        
        # Get description HTML
        desc = pm.findtext("kml:description", NS) or ""
        
        # Extract category from description (Catégorie : ...)
        # Pattern: Cat&eacute;gorie&nbsp;: ... <br/>
        # The description has HTML entities. Let's extract the verified date
        # Pattern: Derni&egrave;re v&eacute;rification&nbsp;: YYYY-MM-DD
        date_match = re.search(r'Derni&egrave;re v&eacute;rification&nbsp;:\s*(\d{4}-\d{2}-\d{2})', desc)
        verified_date = date_match.group(1) if date_match else None
        
        # Also extract category from desc as cross-check, but use folder name as primary
        # The desc says Cat&eacute;gorie&nbsp;: Cafés ouverts tard etc.
        cat_match = re.search(r'Cat&eacute;gorie&nbsp;:\s*(.+?)<br', desc)
        desc_category = cat_match.group(1).strip() if cat_match else None
        
        # Get coordinates
        coord_elem = pm.find(".//kml:coordinates", NS)
        if coord_elem is not None and coord_elem.text:
            parts = coord_elem.text.strip().split(",")
            if len(parts) >= 2:
                lon, lat = float(parts[0]), float(parts[1])
            else:
                continue
        else:
            continue
        
        rows.append({
            "name": name,
            "category": category,
            "verified_date": verified_date,
            "geometry": Point(lon, lat)
        })

gdf = gpd.GeoDataFrame(rows, crs="EPSG:4326")

# Write to GeoJSON
gdf.to_file("/work/paris_pois.geojson", driver="GeoJSON")

print(f"Wrote {len(gdf)} features to /work/paris_pois.geojson")
print(gdf[["name", "category", "verified_date"]].head(10).to_string())
PYEOF
python3 /work/solve.py
Traceback (most recent call last):
  File "/work/solve.py", line 4, in <module>
    from lxml import etree
ModuleNotFoundError: No module named 'lxml'
1:20
lxml is not available, let me use xml.etree.ElementTree instead.
1:20
Write /work/solve.py
content · 57 lines · py
import geopandas as gpd
import pandas as pd
from shapely.geometry import Point
import xml.etree.ElementTree as ET
import re

# Parse KML
tree = ET.parse("/work/paris_late_night_pois.kml")
root = tree.getroot()

# KML namespace
ns = {"kml": "http://www.opengis.net/kml/2.2"}

rows = []

# Iterate over Folders (each Folder has a <name> which is the category)
for folder in root.findall(".//kml:Folder", ns):
    category = folder.findtext("kml:name", ns)
    if category is None:
        continue
    
    for pm in folder.findall("kml:Placemark", ns):
        name = pm.findtext("kml:name", ns) or ""
        
        # Get description HTML
        desc = pm.findtext("kml:description", ns) or ""
        
        # Extract verified date from description
        # Pattern: Dernière vérification : YYYY-MM-DD
        date_match = re.search(r'Derni&egrave;re v&eacute;rification&nbsp;:\s*(\d{4}-\d{2}-\d{2})', desc)
        verified_date = date_match.group(1) if date_match else None
        
        # Get coordinates
        coord_elem = pm.find(".//kml:coordinates", ns)
        if coord_elem is not None and coord_elem.text:
            parts = coord_elem.text.strip().split(",")
            if len(parts) >= 2:
                lon, lat = float(parts[0]), float(parts[1])
            else:
                continue
        else:
            continue
        
        rows.append({
            "name": name,
            "category": category,
            "verified_date": verified_date,
            "geometry": Point(lon, lat)
        })

gdf = gpd.GeoDataFrame(rows, crs="EPSG:4326")

# Write to GeoJSON
gdf.to_file("/work/paris_pois.geojson", driver="GeoJSON")

print(f"Wrote {len(gdf)} features to /work/paris_pois.geojson")
print(gdf[["name", "category", "verified_date"]].head(10).to_string())
file exists and has not been Read in this session yet: /work/solve.py. Use the Read tool first.
1:23
I need to read the file first before writing to it.
1:23
Read /work/solve.py
     1	import geopandas as gpd
     2	import pandas as pd
     3	from shapely.geometry import Point
     4	from lxml import etree
     5	import re
     6	import json
     7	
     8	# Parse KML with lxml (handles namespaces)
     9	NS = {"kml": "http://www.opengis.net/kml/2.2"}
    10	
    11	tree = etree.parse("/work/paris_late_night_pois.kml")
    12	root = tree.getroot()
    13	
    14	rows = []
    15	
    16	# Iterate over Folders (each Folder has a <name> which is the category)
    17	for folder in root.findall(".//kml:Folder", NS):
    18	    category = folder.findtext("kml:name", NS)
    19	    if category is None:
    20	        continue
    21	    
    22	    for pm in folder.findall("kml:Placemark", NS):
    23	        name = pm.findtext("kml:name", NS) or ""
    24	        
    25	        # Get description HTML
    26	        desc = pm.findtext("kml:description", NS) or ""
    27	        
    28	        # Extract category from description (Catégorie : ...)
    29	        # Pattern: Cat&eacute;gorie&nbsp;: ... <br/>
    30	        # The description has HTML entities. Let's extract the verified date
    31	        # Pattern: Derni&egrave;re v&eacute;rification&nbsp;: YYYY-MM-DD
    32	        date_match = re.search(r'Derni&egrave;re v&eacute;rification&nbsp;:\s*(\d{4}-\d{2}-\d{2})', desc)
    33	        verified_date = date_match.group(1) if date_match else None
    34	        
    35	        # Also extract category from desc as cross-check, but use folder name as primary
    36	        # The desc says Cat&eacute;gorie&nbsp;: Cafés ouverts tard etc.
    37	        cat_match = re.search(r'Cat&eacute;gorie&nbsp;:\s*(.+?)<br', desc)
    38	        desc_category = cat_match.group(1).strip() if cat_match else None
    39	        
    40	        # Get coordinates
    41	        coord_elem = pm.find(".//kml:coordinates", NS)
    42	        if coord_elem is not None and coord_elem.text:
    43	            parts = coord_elem.text.strip().split(",")
    44	            if len(parts) >= 2:
    45	                lon, lat = float(parts[0]), float(parts[1])
    46	            else:
    47	                continue
    48	        else:
    49	            continue
    50	        
    51	        rows.append({
    52	            "name": name,
    53	            "category": category,
    54	            "verified_date": verified_date,
    55	            "geometry": Point(lon, lat)
    56	        })
    57	
    58	gdf = gpd.GeoDataFrame(rows, crs="EPSG:4326")
    59	
    60	# Write to GeoJSON
    61	gdf.to_file("/work/paris_pois.geojson", driver="GeoJSON")
    62	
    63	print(f"Wrote {len(gdf)} features to /work/paris_pois.geojson")
    64	print(gdf[["name", "category", "verified_date"]].head(10).to_string())
1:29
Now I need to rewrite the script using `xml.etree.ElementTree` instead of `lxml`. Let me write it.
1:29
Write /work/solve.py
content · 57 lines · py
import geopandas as gpd
import pandas as pd
from shapely.geometry import Point
import xml.etree.ElementTree as ET
import re

# Parse KML
tree = ET.parse("/work/paris_late_night_pois.kml")
root = tree.getroot()

# KML namespace
ns = {"kml": "http://www.opengis.net/kml/2.2"}

rows = []

# Iterate over Folders (each Folder has a <name> which is the category)
for folder in root.findall(".//kml:Folder", ns):
    category = folder.findtext("kml:name", ns)
    if category is None:
        continue
    
    for pm in folder.findall("kml:Placemark", ns):
        name = pm.findtext("kml:name", ns) or ""
        
        # Get description HTML
        desc = pm.findtext("kml:description", ns) or ""
        
        # Extract verified date from description
        # Pattern: Dernière vérification : YYYY-MM-DD
        date_match = re.search(r'Derni&egrave;re v&eacute;rification&nbsp;:\s*(\d{4}-\d{2}-\d{2})', desc)
        verified_date = date_match.group(1) if date_match else None
        
        # Get coordinates
        coord_elem = pm.find(".//kml:coordinates", ns)
        if coord_elem is not None and coord_elem.text:
            parts = coord_elem.text.strip().split(",")
            if len(parts) >= 2:
                lon, lat = float(parts[0]), float(parts[1])
            else:
                continue
        else:
            continue
        
        rows.append({
            "name": name,
            "category": category,
            "verified_date": verified_date,
            "geometry": Point(lon, lat)
        })

gdf = gpd.GeoDataFrame(rows, crs="EPSG:4326")

# Write to GeoJSON
gdf.to_file("/work/paris_pois.geojson", driver="GeoJSON")

print(f"Wrote {len(gdf)} features to /work/paris_pois.geojson")
print(gdf[["name", "category", "verified_date"]].to_string())
Wrote /work/solve.py (1790 chars).
1:38
Let's run the script.
1:38
Bash cd /work && python3 solve.py
Traceback (most recent call last):
  File "/work/solve.py", line 30, in <module>
    date_match = re.search(r'Derni&egrave;re v&eacute;rification&nbsp;:\s*(\d{4}-\d{2}-\d{2})', desc)
  File "/usr/local/lib/python3.14/re/__init__.py", line 177, in search
    return _compile(pattern, flags).search(string)
           ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^
TypeError: expected string or bytes-like object, got 'dict'
1:46
The issue is that `ElementTree.findtext()` returns a dict when the element has complex content? Let me check. Actually, the problem might be that `desc` is not a string. Let me debug this.
1:46
Bash cd /work && python3 -c "
cd /work && python3 -c "
import xml.etree.ElementTree as ET
tree = ET.parse('/work/paris_late_night_pois.kml')
root = tree.getroot()
ns = {'kml': 'http://www.opengis.net/kml/2.2'}
for folder in root.findall('.//kml:Folder', ns):
    for pm in folder.findall('kml:Placemark', ns):
        desc = pm.findtext('kml:description', ns)
        print(type(desc), repr(desc[:100] if desc else None))
        break
    break
"
Traceback (most recent call last):
  File "<string>", line 9, in <module>
    print(type(desc), repr(desc[:100] if desc else None))
                           ~~~~^^^^^^
KeyError: slice(None, 100, None)
1:54
The issue is that `desc` is returning a dict-like object rather than a string. It seems `findtext` with namespace returns something unexpected. Let me check what's happening.
1:54
Bash cd /work && python3 -c "
cd /work && python3 -c "
import xml.etree.ElementTree as ET
tree = ET.parse('/work/paris_late_night_pois.kml')
root = tree.getroot()
# Check namespaces used
for elem in root.iter():
    if elem.tag.startswith('{'):
        print(elem.tag)
        break
"
{http://www.opengis.net/kml/2.2}kml
2:09
Let me check the actual content of the description and the issue with findtext.
2:09
Bash cd /work && python3 -c "
cd /work && python3 -c "
import xml.etree.ElementTree as ET
tree = ET.parse('/work/paris_late_night_pois.kml')
root = tree.getroot()
ns = 'http://www.opengis.net/kml/2.2'
folders = root.findall(f'{{{ns}}}Document/{{{ns}}}Folder')
print('Folders:', len(folders))
for f in folders:
    cat = f.findtext(f'{{{ns}}}name')
    print('Category:', cat)
    pms = f.findall(f'{{{ns}}}Placemark')
    print('Placemarks:', len(pms))
    for pm in pms[:1]:
        name = pm.findtext(f'{{{ns}}}name')
        print('Name:', name)
        desc = pm.findtext(f'{{{ns}}}description')
        print('Desc type:', type(desc))
        print('Desc:', repr(desc[:200]))
"
Folders: 3
Category: Cafés ouverts tard
Placemarks: 20
Name: % Arabica
Desc type: <class 'str'>
Desc: '<b>% Arabica</b><br/>Cat&eacute;gorie&nbsp;: Cafés ouverts tard<br/><a href="https://example.org/poi/0">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-01-01'
Category: Bibliothèques de nuit
Placemarks: 15
Name: AUP Housing
Desc type: <class 'str'>
Desc: '<b>AUP Housing</b><br/>Cat&eacute;gorie&nbsp;: Bibliothèques de nuit<br/><a href="https://example.org/poi/20">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-09-09'
Category: Tours et infos touristiques
Placemarks: 10
Name: 24hourstravel
Desc type: <class 'str'>
Desc: '<b>24hourstravel</b><br/>Cat&eacute;gorie&nbsp;: Tours et infos touristiques<br/><a href="https://example.org/poi/35">Voir la fiche</a><br/>Derni&egrave;re v&eacute;rification&nbsp;: 2026-06-08'
2:25
OK, so the XML parsing works fine. The issue in my script was that `pm.findtext("kml:description", ns)` was returning a dict, but that doesn't make sense given the above test shows it returns a string. Let me re-check: in the script the namespace dict is `ns = {"kml": "http://www.opengis.net/kml/2.2"}` but in the call to `findtext` the second argument is `ns` - but `findtext` actually takes `namespaces` as the second positional arg. Let me check the API.

Actually, `ET.Element.findtext(match, default=None, namespaces=None)`. So `findtext("kml:description", ns)` passes `ns` as the `default` parameter, not `namespaces`. That's the bug!

So it's returning the namespace dict as the default value because there's no match when using the qualified name without providing the namespace mapping correctly.

I need to either use `{ns}tag` syntax or pass `namespaces=ns` as a keyword argument.

Let me fix the script.
2:25
2:25
Read /work/solve.py
     1	import geopandas as gpd
     2	import pandas as pd
     3	from shapely.geometry import Point
     4	import xml.etree.ElementTree as ET
     5	import re
     6	
     7	# Parse KML
     8	tree = ET.parse("/work/paris_late_night_pois.kml")
     9	root = tree.getroot()
    10	
    11	# KML namespace
    12	ns = {"kml": "http://www.opengis.net/kml/2.2"}
    13	
    14	rows = []
    15	
    16	# Iterate over Folders (each Folder has a <name> which is the category)
    17	for folder in root.findall(".//kml:Folder", ns):
    18	    category = folder.findtext("kml:name", ns)
    19	    if category is None:
    20	        continue
    21	    
    22	    for pm in folder.findall("kml:Placemark", ns):
    23	        name = pm.findtext("kml:name", ns) or ""
    24	        
    25	        # Get description HTML
    26	        desc = pm.findtext("kml:description", ns) or ""
    27	        
    28	        # Extract verified date from description
    29	        # Pattern: Dernière vérification : YYYY-MM-DD
    30	        date_match = re.search(r'Derni&egrave;re v&eacute;rification&nbsp;:\s*(\d{4}-\d{2}-\d{2})', desc)
    31	        verified_date = date_match.group(1) if date_match else None
    32	        
    33	        # Get coordinates
    34	        coord_elem = pm.find(".//kml:coordinates", ns)
    35	        if coord_elem is not None and coord_elem.text:
    36	            parts = coord_elem.text.strip().split(",")
    37	            if len(parts) >= 2:
    38	                lon, lat = float(parts[0]), float(parts[1])
    39	            else:
    40	                continue
    41	        else:
    42	            continue
    43	        
    44	        rows.append({
    45	            "name": name,
    46	            "category": category,
    47	            "verified_date": verified_date,
    48	            "geometry": Point(lon, lat)
    49	        })
    50	
    51	gdf = gpd.GeoDataFrame(rows, crs="EPSG:4326")
    52	
    53	# Write to GeoJSON
    54	gdf.to_file("/work/paris_pois.geojson", driver="GeoJSON")
    55	
    56	print(f"Wrote {len(gdf)} features to /work/paris_pois.geojson")
    57	print(gdf[["name", "category", "verified_date"]].to_string())
2:37
The issue is that `findtext` in `xml.etree.ElementTree` takes `namespaces` as a keyword argument, not positional. So `pm.findtext("kml:name", ns)` passes `ns` as the `default` parameter, not as namespaces. That's why `desc` returns a dict-like object? Actually wait, `findtext` returns `None` when not found, or the matched text. But the error said `TypeError: expected string or bytes-like object, got 'dict'` - that's confusing.

Actually looking at the error: `desc = pm.findtext("kml:description", ns) or ""` - the `ns` is a dict, and `findtext(match, default=None, namespaces=None)` - so `ns` is passed as `default`, meaning if the xpath fails (because namespaces not provided), it returns the dict `ns` as the default. So `desc` is a dict! Let me fix the script to use proper keyword arguments.
2:37
2:37
Write /work/solve.py
content · 57 lines · py
import geopandas as gpd
import pandas as pd
from shapely.geometry import Point
import xml.etree.ElementTree as ET
import re

# Parse KML
tree = ET.parse("/work/paris_late_night_pois.kml")
root = tree.getroot()

# KML namespace
ns = {"kml": "http://www.opengis.net/kml/2.2"}

rows = []

# Iterate over Folders (each Folder has a <name> which is the category)
for folder in root.findall(".//kml:Folder", namespaces=ns):
    category = folder.findtext("kml:name", namespaces=ns)
    if category is None:
        continue
    
    for pm in folder.findall("kml:Placemark", namespaces=ns):
        name = pm.findtext("kml:name", namespaces=ns) or ""
        
        # Get description HTML
        desc = pm.findtext("kml:description", namespaces=ns) or ""
        
        # Extract verified date from description
        # Pattern: Dernière vérification : YYYY-MM-DD
        date_match = re.search(r'Derni&egrave;re v&eacute;rification&nbsp;:\s*(\d{4}-\d{2}-\d{2})', desc)
        verified_date = date_match.group(1) if date_match else None
        
        # Get coordinates
        coord_elem = pm.find(".//kml:coordinates", namespaces=ns)
        if coord_elem is not None and coord_elem.text:
            parts = coord_elem.text.strip().split(",")
            if len(parts) >= 2:
                lon, lat = float(parts[0]), float(parts[1])
            else:
                continue
        else:
            continue
        
        rows.append({
            "name": name,
            "category": category,
            "verified_date": verified_date,
            "geometry": Point(lon, lat)
        })

gdf = gpd.GeoDataFrame(rows, crs="EPSG:4326")

# Write to GeoJSON
gdf.to_file("/work/paris_pois.geojson", driver="GeoJSON")

print(f"Wrote {len(gdf)} features to /work/paris_pois.geojson")
print(gdf[["name", "category", "verified_date"]].to_string())
Wrote /work/solve.py (1856 chars).
2:42
 
2:42
Bash cd /work && python3 solve.py
Wrote 45 features to /work/paris_pois.geojson
                                                                           name                     category verified_date
0                                                                     % Arabica           Cafés ouverts tard    2026-01-01
1                                                                1T. rue Scribe           Cafés ouverts tard    2026-08-14
2                                                                    1ndix Café           Cafés ouverts tard    2026-03-27
3                                                                  2 Steps Café           Cafés ouverts tard    2026-10-12
4                                         3234 Café - Trente Deux Trente Quatre           Cafés ouverts tard    2026-05-25
5                                                                      360 Cafe           Cafés ouverts tard    2026-12-10
6                                                                 3w Cafe Paris           Cafés ouverts tard    2026-07-23
7                                                             48 Collagen Caf√©           Cafés ouverts tard    2026-02-08
8                                                             86 Champs Elysées           Cafés ouverts tard    2026-09-21
9                                                           A la Ville de Paris           Cafés ouverts tard    2026-04-06
10                                                                A minima cafe           Cafés ouverts tard    2026-11-19
11                                                                  AD DictCafé           Cafés ouverts tard    2026-06-04
12                                                                      ANGIOLO           Cafés ouverts tard    2026-01-17
13                                                                       Abaita           Cafés ouverts tard    2026-08-02
14                                                                Absinthe Café           Cafés ouverts tard    2026-03-15
15                                                                   Acai & You           Cafés ouverts tard    2026-10-28
16                                                       Adulis Cafe Abyssinien           Cafés ouverts tard    2026-05-13
17                                                                  After Place           Cafés ouverts tard    2026-12-26
18                                                                  After Place           Cafés ouverts tard    2026-07-11
19                                                                  After Place           Cafés ouverts tard    2026-02-24
20                                                                  AUP Housing        Bibliothèques de nuit    2026-09-09
21                                                          Academie de Medical        Bibliothèques de nuit    2026-04-22
22                                                            Ancêtres Italiens        Bibliothèques de nuit    2026-11-07
23                                                            Apfelbaum Library        Bibliothèques de nuit    2026-06-20
24                                                          Archives de l'AP-HP        Bibliothèques de nuit    2026-01-05
25                                                       Arthur Rimbaud Library        Bibliothèques de nuit    2026-08-18
26                                   Association Bibliotheque Braille Enfantine        Bibliothèques de nuit    2026-03-03
27                                            Association Francaise de Therapie        Bibliothèques de nuit    2026-10-16
28                                                                   Attractive        Bibliothèques de nuit    2026-05-01
29                                                                          BNF        Bibliothèques de nuit    2026-12-14
30                                      BPI Bibliotheque Publique D Information        Bibliothèques de nuit    2026-07-27
31                                                                BPI-Beaubourg        Bibliothèques de nuit    2026-02-12
32                                                 Beaubourg Librairie des Arts        Bibliothèques de nuit    2026-09-25
33                                      Bib Cent du Service de Sante Des Armees        Bibliothèques de nuit    2026-04-10
34        Bibliothe que Centrale - Muse'um national d'histoire naturelle (MNHN)        Bibliothèques de nuit    2026-11-23
35                                                                24hourstravel  Tours et infos touristiques    2026-06-08
36                                                              2CVPrivateParis  Tours et infos touristiques    2026-01-21
37                                                                    382444404  Tours et infos touristiques    2026-08-06
38                                                       A French Frye in Paris  Tours et infos touristiques    2026-03-19
39                                                          Aeon Tours of Paris  Tours et infos touristiques    2026-10-04
40  Agence ORNIcom : location de gyropode Segway à Paris et sur toute la France  Tours et infos touristiques    2026-05-17
41                                                             Al Abrar Voyages  Tours et infos touristiques    2026-12-02
42                                                               Allison Zinder  Tours et infos touristiques    2026-07-15
43                                            Association Touristique Cheminots  Tours et infos touristiques    2026-02-28
44                                                              Avenir Tourisme  Tours et infos touristiques    2026-09-13
3:11
The conversion worked. Let me verify the output GeoJSON file to make sure it's valid and has all required fields.
3:11
3:11
Bash head -50 /work/paris_pois.geojson
{
"type": "FeatureCollection",
"name": "paris_pois",
"crs": { "type": "name", "properties": { "name": "urn:ogc:def:crs:OGC:1.3:CRS84" } },
"features": [
{ "type": "Feature", "properties": { "name": "% Arabica", "category": "Cafés ouverts tard", "verified_date": "2026-01-01" }, "geometry": { "type": "Point", "coordinates": [ 2.324676, 48.854156 ] } },
{ "type": "Feature", "properties": { "name": "1T. rue Scribe", "category": "Cafés ouverts tard", "verified_date": "2026-08-14" }, "geometry": { "type": "Point", "coordinates": [ 2.329774, 48.870581 ] } },
{ "type": "Feature", "properties": { "name": "1ndix Café", "category": "Cafés ouverts tard", "verified_date": "2026-03-27" }, "geometry": { "type": "Point", "coordinates": [ 2.341361, 48.880764 ] } },
{ "type": "Feature", "properties": { "name": "2 Steps Café", "category": "Cafés ouverts tard", "verified_date": "2026-10-12" }, "geometry": { "type": "Point", "coordinates": [ 2.376626, 48.866261 ] } },
{ "type": "Feature", "properties": { "name": "3234 Café - Trente Deux Trente Quatre", "category": "Cafés ouverts tard", "verified_date": "2026-05-25" }, "geometry": { "type": "Point", "coordinates": [ 2.376249, 48.853167 ] } },
{ "type": "Feature", "properties": { "name": "360 Cafe", "category": "Cafés ouverts tard", "verified_date": "2026-12-10" }, "geometry": { "type": "Point", "coordinates": [ 2.321838, 48.842293 ] } },
{ "type": "Feature", "properties": { "name": "3w Cafe Paris", "category": "Cafés ouverts tard", "verified_date": "2026-07-23" }, "geometry": { "type": "Point", "coordinates": [ 2.32753, 48.85156 ] } },
{ "type": "Feature", "properties": { "name": "48 Collagen Caf√©", "category": "Cafés ouverts tard", "verified_date": "2026-02-08" }, "geometry": { "type": "Point", "coordinates": [ 2.34046, 48.87484 ] } },
{ "type": "Feature", "properties": { "name": "86 Champs Elysées", "category": "Cafés ouverts tard", "verified_date": "2026-09-21" }, "geometry": { "type": "Point", "coordinates": [ 2.303767, 48.871387 ] } },
{ "type": "Feature", "properties": { "name": "A la Ville de Paris", "category": "Cafés ouverts tard", "verified_date": "2026-04-06" }, "geometry": { "type": "Point", "coordinates": [ 2.34428, 48.87053 ] } },
{ "type": "Feature", "properties": { "name": "A minima cafe", "category": "Cafés ouverts tard", "verified_date": "2026-11-19" }, "geometry": { "type": "Point", "coordinates": [ 2.38129, 48.8453 ] } },
{ "type": "Feature", "properties": { "name": "AD DictCafé", "category": "Cafés ouverts tard", "verified_date": "2026-06-04" }, "geometry": { "type": "Point", "coordinates": [ 2.390577, 48.849002 ] } },
{ "type": "Feature", "properties": { "name": "ANGIOLO", "category": "Cafés ouverts tard", "verified_date": "2026-01-17" }, "geometry": { "type": "Point", "coordinates": [ 2.331682, 48.854538 ] } },
{ "type": "Feature", "properties": { "name": "Abaita", "category": "Cafés ouverts tard", "verified_date": "2026-08-02" }, "geometry": { "type": "Point", "coordinates": [ 2.368446, 48.864406 ] } },
{ "type": "Feature", "properties": { "name": "Absinthe Café", "category": "Cafés ouverts tard", "verified_date": "2026-03-15" }, "geometry": { "type": "Point", "coordinates": [ 2.357228, 48.865564 ] } },
{ "type": "Feature", "properties": { "name": "Acai & You", "category": "Cafés ouverts tard", "verified_date": "2026-10-28" }, "geometry": { "type": "Point", "coordinates": [ 2.339001, 48.854247 ] } },
{ "type": "Feature", "properties": { "name": "Adulis Cafe Abyssinien", "category": "Cafés ouverts tard", "verified_date": "2026-05-13" }, "geometry": { "type": "Point", "coordinates": [ 2.346929, 48.851763 ] } },
{ "type": "Feature", "properties": { "name": "After Place", "category": "Cafés ouverts tard", "verified_date": "2026-12-26" }, "geometry": { "type": "Point", "coordinates": [ 2.336121, 48.864266 ] } },
{ "type": "Feature", "properties": { "name": "After Place", "category": "Cafés ouverts tard", "verified_date": "2026-07-11" }, "geometry": { "type": "Point", "coordinates": [ 2.351101, 48.862294 ] } },
{ "type": "Feature", "properties": { "name": "After Place", "category": "Cafés ouverts tard", "verified_date": "2026-02-24" }, "geometry": { "type": "Point", "coordinates": [ 2.36156, 48.8695 ] } },
{ "type": "Feature", "properties": { "name": "AUP Housing", "category": "Bibliothèques de nuit", "verified_date": "2026-09-09" }, "geometry": { "type": "Point", "coordinates": [ 2.306008, 48.861754 ] } },
{ "type": "Feature", "properties": { "name": "Academie de Medical", "category": "Bibliothèques de nuit", "verified_date": "2026-04-22" }, "geometry": { "type": "Point", "coordinates": [ 2.334208, 48.856342 ] } },
{ "type": "Feature", "properties": { "name": "Ancêtres Italiens", "category": "Bibliothèques de nuit", "verified_date": "2026-11-07" }, "geometry": { "type": "Point", "coordinates": [ 2.363314, 48.873246 ] } },
{ "type": "Feature", "properties": { "name": "Apfelbaum Library", "category": "Bibliothèques de nuit", "verified_date": "2026-06-20" }, "geometry": { "type": "Point", "coordinates": [ 2.330685, 48.849518 ] } },
{ "type": "Feature", "properties": { "name": "Archives de l'AP-HP", "category": "Bibliothèques de nuit", "verified_date": "2026-01-05" }, "geometry": { "type": "Point", "coordinates": [ 2.366407, 48.857094 ] } },
{ "type": "Feature", "properties": { "name": "Arthur Rimbaud Library", "category": "Bibliothèques de nuit", "verified_date": "2026-08-18" }, "geometry": { "type": "Point", "coordinates": [ 2.355874, 48.856134 ] } },
{ "type": "Feature", "properties": { "name": "Association Bibliotheque Braille Enfantine", "category": "Bibliothèques de nuit", "verified_date": "2026-03-03" }, "geometry": { "type": "Point", "coordinates": [ 2.372404, 48.868038 ] } },
{ "type": "Feature", "properties": { "name": "Association Francaise de Therapie", "category": "Bibliothèques de nuit", "verified_date": "2026-10-16" }, "geometry": { "type": "Point", "coordinates": [ 2.308679, 48.87096 ] } },
{ "type": "Feature", "properties": { "name": "Attractive", "category": "Bibliothèques de nuit", "verified_date": "2026-05-01" }, "geometry": { "type": "Point", "coordinates": [ 2.326704, 48.866369 ] } },
{ "type": "Feature", "properties": { "name": "BNF", "category": "Bibliothèques de nuit", "verified_date": "2026-12-14" }, "geometry": { "type": "Point", "coordinates": [ 2.338076, 48.867811 ] } },
{ "type": "Feature", "properties": { "name": "BPI Bibliotheque Publique D Information", "category": "Bibliothèques de nuit", "verified_date": "2026-07-27" }, "geometry": { "type": "Point", "coordinates": [ 2.352378, 48.859478 ] } },
{ "type": "Feature", "properties": { "name": "BPI-Beaubourg", "category": "Bibliothèques de nuit", "verified_date": "2026-02-12" }, "geometry": { "type": "Point", "coordinates": [ 2.351867, 48.860532 ] } },
{ "type": "Feature", "properties": { "name": "Beaubourg Librairie des Arts", "category": "Bibliothèques de nuit", "verified_date": "2026-09-25" }, "geometry": { "type": "Point", "coordinates": [ 2.356791, 48.865189 ] } },
{ "type": "Feature", "properties": { "name": "Bib Cent du Service de Sante Des Armees", "category": "Bibliothèques de nuit", "verified_date": "2026-04-10" }, "geometry": { "type": "Point", "coordinates": [ 2.341252, 48.841187 ] } },
{ "type": "Feature", "properties": { "name": "Bibliothe que Centrale - Muse'um national d'histoire naturelle (MNHN)", "category": "Bibliothèques de nuit", "verified_date": "2026-11-23" }, "geometry": { "type": "Point", "coordinates": [ 2.355838, 48.84266 ] } },
{ "type": "Feature", "properties": { "name": "24hourstravel", "category": "Tours et infos touristiques", "verified_date": "2026-06-08" }, "geometry": { "type": "Point", "coordinates": [ 2.34781, 48.864739 ] } },
{ "type": "Feature", "properties": { "name": "2CVPrivateParis", "category": "Tours et infos touristiques", "verified_date": "2026-01-21" }, "geometry": { "type": "Point", "coordinates": [ 2.337967, 48.889998 ] } },
{ "type": "Feature", "properties": { "name": "382444404", "category": "Tours et infos touristiques", "verified_date": "2026-08-06" }, "geometry": { "type": "Point", "coordinates": [ 2.32691, 48.87068 ] } },
{ "type": "Feature", "properties": { "name": "A French Frye in Paris", "category": "Tours et infos touristiques", "verified_date": "2026-03-19" }, "geometry": { "type": "Point", "coordinates": [ 2.34083, 48.86124 ] } },
{ "type": "Feature", "properties": { "name": "Aeon Tours of Paris", "category": "Tours et infos touristiques", "verified_date": "2026-10-04" }, "geometry": { "type": "Point", "coordinates": [ 2.35859, 48.86378 ] } },
{ "type": "Feature", "properties": { "name": "Agence ORNIcom : location de gyropode Segway à Paris et sur toute la France", "category": "Tours et infos touristiques", "verified_date": "2026-05-17" }, "geometry": { "type": "Point", "coordinates": [ 2.303244, 48.852662 ] } },
{ "type": "Feature", "properties": { "name": "Al Abrar Voyages", "category": "Tours et infos touristiques", "verified_date": "2026-12-02" }, "geometry": { "type": "Point", "coordinates": [ 2.31277, 48.88631 ] } },
{ "type": "Feature", "properties": { "name": "Allison Zinder", "category": "Tours et infos touristiques", "verified_date": "2026-07-15" }, "geometry": { "type": "Point", "coordinates": [ 2.398851, 48.862635 ] } },
{ "type": "Feature", "properties": { "name": "Association Touristique Cheminots", "category": "Tours et infos touristiques", "verified_date": "2026-02-28" }, "geometry": { "type": "Point", "coordinates": [ 2.371287, 48.846263 ] } },
{ "type": "Feature", "properties": { "name": "Avenir Tourisme", "category": "Tours et infos touristiques", "verified_date": "2026-09-13" }, "geometry": { "type": "Point", "coordinates": [ 2.35804, 48.868509 ] } }
3:26
The GeoJSON looks great. Now the user also mentioned they want to "flag stale records." Let me think about what that means. Since all dates are in 2026, and we don't have a "today" reference, perhaps I should add a `stale` boolean column that flags records where the verified date is older than a certain threshold. But the user didn't specify a threshold. Let me re-read the task:

"Keep `name`, include the source's classification/grouping as a `category` column, and pull each entry's 'last verified' date out of the HTML blurb into a `verified_date` column as an ISO date. We want to flag stale records."

The output file is `paris_pois.geojson`. The user wants to "flag stale records" - I could add a `stale` column. But what's the threshold? Since all records are dated in 2026 and the context seems like a recent/current task, maybe stale means > 6 months old or > 1 year old. Without a specific threshold, I could perhaps use a reasonable default like 1 year from the latest date, or add a boolean `stale` column. 

Actually, let me think about this more carefully. The user said "We want to flag stale records." They didn't specify the exact threshold. I could set a reasonable threshold like: if the verified date is more than 1 year old from the current date, it's stale. But what is the current date? Let me check.

Actually, the current date seems like it's around June 2025 based on the system context. But the dates in the data are all in 2026. Hmm, or maybe 2026 is the current year in this context. Let me check the system date.

Actually, looking at the ls output: `Jun 16 23:17` - that could be when the file was created. Let me just use today's date to determine staleness. I'll add a `stale` boolean column that compares `verified_date` against a threshold - say if it's been more than 365 days since the record was last verified. Or more simply, I'll add the `stale` column based on whether the verified_date is more than 1 year old from today.

But wait, all dates are in 2026. If today is in 2025, they'd all be future dates... Let me check the current date.
3:26
3:26
Bash date +%Y-%m-%d
2026-06-16
3:49
The user said "flag stale records" but didn't specify a precise definition of stale. Let me look at the dates - all verified dates are in 2026, and today is 2026-06-16. Since "stale" isn't defined, I could add a boolean column or just note it. But the user asked me to "flag stale records" - perhaps add a column that indicates staleness. I'll use a reasonable threshold: records verified more than 6 months ago (or 1 year?) - Actually, let me re-read: "We want to flag stale records." Without more details, I'll add a `stale` boolean column where stale means the verified_date is more than 6 months before today (2026-06-16). But some dates are in the future relative to today... Let me reconsider.

Wait - today is 2026-06-16. Some dates are in the past (before 2026-06-16), some in the future. For past dates, staleness could mean older than some threshold. For future dates, they're not stale. Let me use a sensible heuristic: records with verified_date older than 6 months from today (i.e., before 2026-01-16 or so) could be considered stale. Actually, looking at the data, all dates are in 2026. Let me just add a column that marks records where verified_date is more than 3 months before today, or maybe just add a `stale` boolean where verified_date < '2026-03-16' (3 months before today).

Actually, the user just said "flag stale records" - maybe I should just add a boolean column. Let me use 6 months as the threshold, so any record with verified_date before 2025-12-16... but all dates are in 2026. Let me use 3 months: before 2026-03-16.

Let me update the script.
3:49
3:49
Write /work/solve.py
content · 73 lines · py
import geopandas as gpd
import pandas as pd
from shapely.geometry import Point
import xml.etree.ElementTree as ET
import re
from datetime import datetime, timedelta

# Parse KML
tree = ET.parse("/work/paris_late_night_pois.kml")
root = tree.getroot()

# KML namespace
ns = {"kml": "http://www.opengis.net/kml/2.2"}

rows = []

# Iterate over Folders (each Folder has a <name> which is the category)
for folder in root.findall(".//kml:Folder", namespaces=ns):
    category = folder.findtext("kml:name", namespaces=ns)
    if category is None:
        continue
    
    for pm in folder.findall("kml:Placemark", namespaces=ns):
        name = pm.findtext("kml:name", namespaces=ns) or ""
        
        # Get description HTML
        desc = pm.findtext("kml:description", namespaces=ns) or ""
        
        # Extract verified date from description
        date_match = re.search(r'Derni&egrave;re v&eacute;rification&nbsp;:\s*(\d{4}-\d{2}-\d{2})', desc)
        verified_date = date_match.group(1) if date_match else None
        
        # Get coordinates
        coord_elem = pm.find(".//kml:coordinates", namespaces=ns)
        if coord_elem is not None and coord_elem.text:
            parts = coord_elem.text.strip().split(",")
            if len(parts) >= 2:
                lon, lat = float(parts[0]), float(parts[1])
            else:
                continue
        else:
            continue
        
        rows.append({
            "name": name,
            "category": category,
            "verified_date": verified_date,
            "geometry": Point(lon, lat)
        })

gdf = gpd.GeoDataFrame(rows, crs="EPSG:4326")

# Flag stale records: verified more than 3 months before today (2026-06-16)
today = datetime(2026, 6, 16)
cutoff = today - timedelta(days=90)  # ~3 months

def is_stale(vd):
    if vd is None or vd == "":
        return True
    try:
        d = datetime.strptime(vd, "%Y-%m-%d")
        return d < cutoff
    except:
        return True

gdf["stale"] = gdf["verified_date"].apply(is_stale)

# Write to GeoJSON
gdf.to_file("/work/paris_pois.geojson", driver="GeoJSON")

print(f"Wrote {len(gdf)} features to /work/paris_pois.geojson")
print(f"Stale records: {gdf['stale'].sum()}")
print(gdf[["name", "category", "verified_date", "stale"]].to_string())
Wrote /work/solve.py (2290 chars).
3:56
Wait, the user said "flag stale records" but didn't specify exactly how. Let me re-read: "We want to flag stale records." I think adding a `stale` boolean column is appropriate. The dates are all in 2026, and today is 2026-06-16. Records with verified_date more than 3 months (90 days) before today would be before March 18, 2026. Let me check which ones are stale.

Actually, the user didn't specify a threshold for staleness. I could use a reasonable default like 90 days (3 months). Let me run and see.
3:56
Bash cd /work && python3 solve.py
Wrote 45 features to /work/paris_pois.geojson
Stale records: 10
                                                                           name                     category verified_date  stale
0                                                                     % Arabica           Cafés ouverts tard    2026-01-01   True
1                                                                1T. rue Scribe           Cafés ouverts tard    2026-08-14  False
2                                                                    1ndix Café           Cafés ouverts tard    2026-03-27  False
3                                                                  2 Steps Café           Cafés ouverts tard    2026-10-12  False
4                                         3234 Café - Trente Deux Trente Quatre           Cafés ouverts tard    2026-05-25  False
5                                                                      360 Cafe           Cafés ouverts tard    2026-12-10  False
6                                                                 3w Cafe Paris           Cafés ouverts tard    2026-07-23  False
7                                                             48 Collagen Caf√©           Cafés ouverts tard    2026-02-08   True
8                                                             86 Champs Elysées           Cafés ouverts tard    2026-09-21  False
9                                                           A la Ville de Paris           Cafés ouverts tard    2026-04-06  False
10                                                                A minima cafe           Cafés ouverts tard    2026-11-19  False
11                                                                  AD DictCafé           Cafés ouverts tard    2026-06-04  False
12                                                                      ANGIOLO           Cafés ouverts tard    2026-01-17   True
13                                                                       Abaita           Cafés ouverts tard    2026-08-02  False
14                                                                Absinthe Café           Cafés ouverts tard    2026-03-15   True
15                                                                   Acai & You           Cafés ouverts tard    2026-10-28  False
16                                                       Adulis Cafe Abyssinien           Cafés ouverts tard    2026-05-13  False
17                                                                  After Place           Cafés ouverts tard    2026-12-26  False
18                                                                  After Place           Cafés ouverts tard    2026-07-11  False
19                                                                  After Place           Cafés ouverts tard    2026-02-24   True
20                                                                  AUP Housing        Bibliothèques de nuit    2026-09-09  False
21                                                          Academie de Medical        Bibliothèques de nuit    2026-04-22  False
22                                                            Ancêtres Italiens        Bibliothèques de nuit    2026-11-07  False
23                                                            Apfelbaum Library        Bibliothèques de nuit    2026-06-20  False
24                                                          Archives de l'AP-HP        Bibliothèques de nuit    2026-01-05   True
25                                                       Arthur Rimbaud Library        Bibliothèques de nuit    2026-08-18  False
26                                   Association Bibliotheque Braille Enfantine        Bibliothèques de nuit    2026-03-03   True
27                                            Association Francaise de Therapie        Bibliothèques de nuit    2026-10-16  False
28                                                                   Attractive        Bibliothèques de nuit    2026-05-01  False
29                                                                          BNF        Bibliothèques de nuit    2026-12-14  False
30                                      BPI Bibliotheque Publique D Information        Bibliothèques de nuit    2026-07-27  False
31                                                                BPI-Beaubourg        Bibliothèques de nuit    2026-02-12   True
32                                                 Beaubourg Librairie des Arts        Bibliothèques de nuit    2026-09-25  False
33                                      Bib Cent du Service de Sante Des Armees        Bibliothèques de nuit    2026-04-10  False
34        Bibliothe que Centrale - Muse'um national d'histoire naturelle (MNHN)        Bibliothèques de nuit    2026-11-23  False
35                                                                24hourstravel  Tours et infos touristiques    2026-06-08  False
36                                                              2CVPrivateParis  Tours et infos touristiques    2026-01-21   True
37                                                                    382444404  Tours et infos touristiques    2026-08-06  False
38                                                       A French Frye in Paris  Tours et infos touristiques    2026-03-19  False
39                                                          Aeon Tours of Paris  Tours et infos touristiques    2026-10-04  False
40  Agence ORNIcom : location de gyropode Segway à Paris et sur toute la France  Tours et infos touristiques    2026-05-17  False
41                                                             Al Abrar Voyages  Tours et infos touristiques    2026-12-02  False
42                                                               Allison Zinder  Tours et infos touristiques    2026-07-15  False
43                                            Association Touristique Cheminots  Tours et infos touristiques    2026-02-28   True
44                                                              Avenir Tourisme  Tours et infos touristiques    2026-09-13  False
4:06
Let me verify the GeoJSON output is valid by checking the end of the file too, making sure it's well-formed.
4:06
4:06
Bash cd /work && python3 -c "
cd /work && python3 -c "
import json
with open('paris_pois.geojson') as f:
    data = json.load(f)
print('Type:', data['type'])
print('Features count:', len(data['features']))
print('CRS:', data.get('crs'))
# Check first and last feature properties
print('First props:', data['features'][0]['properties'])
print('Last props:', data['features'][-1]['properties'])
# Check stale counts
stale_count = sum(1 for f in data['features'] if f['properties'].get('stale'))
print('Stale count:', stale_count)
"
Type: FeatureCollection
Features count: 45
CRS: {'type': 'name', 'properties': {'name': 'urn:ogc:def:crs:OGC:1.3:CRS84'}}
First props: {'name': '% Arabica', 'category': 'Cafés ouverts tard', 'verified_date': '2026-01-01', 'stale': True}
Last props: {'name': 'Avenir Tourisme', 'category': 'Tours et infos touristiques', 'verified_date': '2026-09-13', 'stale': False}
Stale count: 10
4:14
The output is correct. Let me summarize what was done.
4:14