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gargantext
Commit eaf036ce authored by delanoe's avatar delanoe
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Merge branch 'romain-goodies' into unstable

parents a180ff49 0fa9e74a
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Showing with 347 additions and 145 deletions
gargantext/constants.py
View file @ eaf036ce
......@@ -250,6 +250,9 @@ DEFAULT_INDEX_SUBGRAMS = False # False <=> traditional
# at indexing after extraction)
# ngram lists import/export parameters -----------------------------------------
DEFAULT_CSV_DELIM = '\t' # for import/export CSV defaults
DEFAULT_CSV_DELIM_GROUP = '|&|'
# ------------------------------------------------------------------------------
......
gargantext/util/ngramlists_tools.py
View file @ eaf036ce
......@@ -15,6 +15,8 @@ from gargantext.models import Ngram, NodeNgram, NodeNodeNgram, \
from gargantext.util.lists import UnweightedList, Translations
from gargantext.constants import DEFAULT_CSV_DELIM, DEFAULT_CSV_DELIM_GROUP
# import will implement the same text cleaning procedures as toolchain
from gargantext.util.toolchain.parsing import normalize_chars
from gargantext.util.toolchain.ngrams_extraction import normalize_terms
......@@ -23,7 +25,7 @@ from sqlalchemy.sql import exists
from os import path
from csv import writer, reader, QUOTE_MINIMAL
from collections import defaultdict
from re import match
from re import match, findall
from io import StringIO # pseudo file to write CSV to memory
def query_list(list_id,
......@@ -124,57 +126,71 @@ def query_list(list_id,
# helper func for exports
def ngrams_to_csv_rows(ngram_objs, id_groupings={}, list_type=""):
def ngrams_to_csv_rows(ngram_objs, ngram_dico={}, group_infos={},
list_type="", groupings_delim=DEFAULT_CSV_DELIM_GROUP):
"""
@param: ngram_objs
an array of ngrams (eg: from a db query.all())
@param: optional id_groupings
a dict of sets {mainform_id : {subform_idA, subform_idB, etc}}
@param: optional group_infos as links and subs
ginfos{links} = a dict of sets
{mainform_id : {subform_idA, subform_idB, etc}}
ginfos{subs} = a reverse map
{subform_idA:mainform_id, subform_idB:mainform_id, etc}}
@param: list_type (a str 'map','main' or 'stop' to fill in col 4)
Outputs a basic info table per ngram
(ng_id, term string, term size, list_type)
Outputs a condensed info table per ngram
(list_type, "term string")
with an optional 5th column of grouped subforms ex: "4|42"
with an optional 3rd column of grouped subforms
ex: "othertermstring|yetanothertermstring"
Returns format is a csv_rows matrix (as a list of lists)
[
[ligne1_colA, ligne1_colB..],
[ligne2_colA, ligne2_colB..],
[row1_colA, row1_colB..],
[row2_colA, row2_colB..],
..
]
(to be used for instance like: csv.writer.writerows(csv_rows)
list_type ici:
0 <=> stopList
1 <=> miamList
2 <=> mapList
0 <=> stop
1 <=> miam
2 <=> map
"""
# transcrire les objets ngrammes en tableau (liste de listes)
# transcribe ngram objects to a table (array of row-arrays)
csv_rows = list()
for ng_obj in ngram_objs:
ng_id = ng_obj.id
if ng_id in id_groupings.keys():
this_grouped = "|".join(str(gid) for gid in id_groupings[ng_id])
else:
this_grouped = ""
# only mainforms will get their own row
if ng_id not in group_infos['subs']:
# if has subforms
if ng_id in group_infos['links']:
this_grouped_terms = groupings_delim.join(
# we replace grouped_ids by their terms string
[ngram_dico[subf_id] for subf_id in group_infos['links'][ng_id]]
)
# if no subforms
else:
this_grouped_terms = ""
# transcription : 5 columns
# ID , terme , n , type_de_liste , grouped_id|grouped_id...
# transcription :
# 3 columns = |status, | mainform, | forms
# (type_of_list) ( term ) ( subterm1|&|subterm2 )
csv_rows.append(
[ng_id,ng_obj.terms,ng_obj.n,list_type,this_grouped]
)
csv_rows.append(
[list_type,ng_obj.terms,this_grouped_terms]
)
return csv_rows
def export_ngramlists(node,fname=None,delimiter="\t",titles=False):
def export_ngramlists(node,fname=None,delimiter=DEFAULT_CSV_DELIM,titles=True):
"""
export of the 3 lists under a corpus node (MAP, MAIN, STOP)
with local combination of groups
......@@ -189,10 +205,9 @@ def export_ngramlists(node,fname=None,delimiter="\t",titles=False):
@param titles: optional flag to print or not a first line with headers
# ID , term , nwords , list_type , grouped_id|grouped_id...
1622 textile 1 main 1623|3397
3397 textile production 2 main
3410 possibility 1 stop
status label forms
map textile textiles|&|textile production
stop possibility
TODO : REFACTOR split list logic from corpus logic
=> possibility to act on one list
......@@ -211,7 +226,6 @@ def export_ngramlists(node,fname=None,delimiter="\t",titles=False):
# et les groupes de synonymes
group_node = node.children("GROUPLIST").first()
# listes de ngram_ids correspondantes
# ------------------------------------
# contenu: liste des objets ngrammes [(2562,"monterme",1),...]
......@@ -219,40 +233,56 @@ def export_ngramlists(node,fname=None,delimiter="\t",titles=False):
main_ngrams = query_list(mainlist_node.id, details=True, groupings_id=group_node.id).all()
map_ngrams = query_list(maplist_node.id, details=True, groupings_id=group_node.id).all()
# pour debug ---------->8 --------------------
#~ stop_ngrams = stop_ngrams[0:10]
#~ main_ngrams = main_ngrams[0:10]
#~ map_ngrams = map_ngrams[0:10]
# --------------------->8 --------------------
# pour la group_list on a des couples de ngram_ids
# preloop to fill a local copy of dictionary ng_id => ng_term_str
dico = {}
for li in [stop_ngrams, main_ngrams, map_ngrams]:
for (ngid, ngterm, ignored) in li:
dico[ngid] = ngterm
# for the groups we got couples of ids in the DB
# -------------------
# ex: [(3544, 2353), (2787, 4032), ...]
group_ngram_id_couples = query_groups(group_node.id).all()
# k couples comme set
# --------------------
# [(x => y1), (x => y2)] >~~~~~~~> [x => {y1,y2}]
grouped = defaultdict(set)
# we expend this to double structure for groups lookup
# 1) g['links'] = k couples (x,y_i) as a set [x => {y1,y2}]
# 2) g['subs'] = reverse map like translations [(y1 => x), (y2 => x)]
g = {
"links":defaultdict(set),
"subs":defaultdict(int)
}
for ngram in group_ngram_id_couples:
grouped[ngram[0]].add(ngram[1])
x = int(ngram[0])
y = int(ngram[1])
g['links'][x].add(y)
g['subs'][y] = x
# on applique notre fonction ng_to_csv sur chaque liste
# ------------------------------------------------------
map_csv_rows = ngrams_to_csv_rows(map_ngrams,
id_groupings=grouped,
ngram_dico=dico,
group_infos=g,
list_type="map")
stop_csv_rows = ngrams_to_csv_rows(stop_ngrams,
id_groupings=grouped,
ngram_dico=dico,
group_infos=g,
list_type="stop")
# miam contient map donc il y a un préalable ici
map_ngram_ids = {ng.id for ng in map_ngrams}
main_without_map = [ng for ng in main_ngrams if ng.id not in map_ngram_ids]
miam_csv_rows = ngrams_to_csv_rows(main_without_map,
id_groupings=grouped,
ngram_dico=dico,
group_infos=g,
list_type="main")
# all lists together now
......@@ -273,7 +303,7 @@ def export_ngramlists(node,fname=None,delimiter="\t",titles=False):
quoting=QUOTE_MINIMAL)
if titles:
csv_wr.writerow(["oldid","term","nwords","listtype","subforms"])
csv_wr.writerow(["status","label","forms"])
# write to outfile
csv_wr.writerows(this_corpus_all_rows)
......@@ -294,7 +324,8 @@ def export_ngramlists(node,fname=None,delimiter="\t",titles=False):
def import_ngramlists(fname, delimiter='\t', group_delimiter='|'):
def import_ngramlists(fname, delimiter=DEFAULT_CSV_DELIM,
group_delimiter=DEFAULT_CSV_DELIM_GROUP):
'''
This function reads a CSV of an ngrams table for a Corpus,
then it converts old ngram_ids to those of the current DB
......@@ -302,23 +333,61 @@ def import_ngramlists(fname, delimiter='\t', group_delimiter='|'):
then recreates an equivalent set of MAINLIST, MAPLIST, STOPLIST + GROUPS
Input example:
oldid | term |nwords| ltype |group_oldids
-------+---------------+------+--------+---------------
3842 water table 2 map 3724
3724 water tables 2 map
4277 water supply 2 map 190362|13415
13415 water supplies 2 map
190362 water-supply 1 map
20489 wastewater 1 map
status | label |forms
--------+---------------+---------------------
map water table water tables
map water supply water-supply|&|water supplies
stop wastewater
The title line is mandatory.
The label will correspond to our DB mainform type.
Variants:
----------
For user accessibility, we allow different formats using equivalence rules:
1) It is implicit that the label string is also one of the forms
therefore the input example table is equivalent to this "verbose" table:
status | label |forms
--------+---------------+---------------------
map water table water table|&|water tables
map water supply water supply|&|water-supply|&|water supplies
stop wastewater wastewater
2) The default status is map and the status column is optional
thus, if we ignore "wastewater", the input table is also equivalent to:
label |forms
---------------+---------------------
water table water tables
water supply water-supply|&|water supplies
3) From DB point of view, both "forms that are labels" and "other forms" are
finally saved just as ngrams. So the input table is also equivalent to:
status | label |forms
--------+---------------+---------------------
map water table water tables
map water tables
map water supply water-supply|&|water supplies
map water supplies
map water-supply
stop wastewater
Output: 3 x UnweightedList + 1 x Translations
Output:
-------
3 x UnweightedList + 1 x Translations
@param fname a local filename or a filehandle-like
@param delimiter a character used as separator in the CSV
@param group_delimiter a character used as grouped subforms separator
(in the last column)
The conversion of old_id to ngram_id works in 2 steps:
The retrieval of ngram_ids works in 2 steps:
=> look up each term str in the DB with bulk_insert_ifnotexists
(creates absent ngrams if necessary)
=> use the new ids to map the relations involving the old ones
......@@ -328,28 +397,21 @@ def import_ngramlists(fname, delimiter='\t', group_delimiter='|'):
NB: To merge the imported lists into a corpus node's lists,
chain this function with merge_ngramlists()
'''
# --------------
#
# --------------
# ---------------
# ngram storage
# ---------------
# main storage for the ngrams by list
import_nodes_ngrams = {'stop':[], 'main':[], 'map':[]}
imported_nodes_ngrams = {'stop':[], 'main':[], 'map':[]}
# separate storage for the term's couples [(term str, nwords int),...]
imported_ngrams_dbdata = []
# and all the old ids, by term (for id lookup after dbdata bulk_insert)
imported_ngrams_oldids = {}
# and all the terms (for unique and for dbdata bulk_insert)
imported_unique_ngramstrs = {}
# and for the imported_grouping list of couples [(x1,y1),(x1,y2),(x2,y3),..]
# and for the imported_grouping list of couples [(str1,str1),(str1,str2)..]
imported_groupings = []
# /!\ imported_grouping contains only external ids (aka oldids)
# (ie imported ids.. that will have to be translated
# to target db ids)
# skipped lines can (very rarely) be used in groups => mark as ignored
ignored_oldids = []
# /!\ imported_grouping contains the subforms' terms themselves
# (that will have to be translated to ngram_ids for the target db)
# =============== READ CSV ===============
......@@ -382,77 +444,105 @@ def import_ngramlists(fname, delimiter='\t', group_delimiter='|'):
n_added_ng = 0
n_group_relations = 0
# columntype => int
columns = {}
# load CSV + initial checks
for i, csv_row in enumerate(ngrams_csv_rows):
# fyi
n_read_lines +=1
# print("---------------READ LINE %i" % i)
# headers
if i == 0:
n_cols = len(csv_row)
for j, colname in enumerate(csv_row):
if colname in ['label', 'status', 'forms']:
columns[colname] = j
else:
raise ValueError('Wrong header "%s" on line %i (only possible headers are "label", "forms" and "status")' % (colname, n_read_lines))
if 'label' not in columns:
raise ValueError('CSV must contain at least one column with the header "label"')
if not len(csv_row):
continue
try:
this_ng_oldid = str(csv_row[0])
this_ng_term = str(csv_row[1])
this_ng_nwords = int(csv_row[2])
this_list_type = str(csv_row[3])
this_ng_group = str(csv_row[4])
# string normalizations
this_ng_term = normalize_terms(normalize_chars(this_ng_term))
# try:
# mandatory column
this_row_label = str(csv_row[columns['label']])
except:
if i == 0:
print("IMPORT WARN: (skip line) probable header line at CSV %s:l.0" % fname)
continue
else:
raise ValueError("Error on CSV read line %i" %n_read_lines)
# other columns or their default values
if 'status' in columns:
this_list_type = str(csv_row[columns['status']])
else:
this_list_type = 'map'
# --- check format before any old ID retrieve
if not match(r"\d+$", this_ng_oldid):
print("IMPORT WARN: (skip line) bad ID at CSV %s:l.%i" % (fname, i))
continue
if 'forms' in columns:
this_row_forms = str(csv_row[columns['forms']])
else:
this_ng_oldid = int(this_ng_oldid)
this_row_forms = ''
# string normalizations
this_row_label = normalize_terms(normalize_chars(this_row_label))
# except:
# if i == 0:
# print("IMPORT WARN: (skip line) probable header line at CSV %s:l.0" % fname)
# continue
# else:
# raise ValueError("Error on CSV read line %i" % i)
# --- term checking
if not len(this_ng_term) > 0:
if not len(this_row_label) > 0:
print("IMPORT WARN: (skip line) empty term at CSV %s:l.%i" % (fname, i))
ignored_oldids.append(this_ng_oldid)
continue
# --- check if not a duplicate string
if this_ng_term in imported_ngrams_oldids:
ignored_oldids.append(this_ng_oldid)
print("IMPORT WARN: (skip line) term appears more than once (previous id: %i) at CSV %s:l.%i"
% (imported_ngrams_oldids[this_ng_term], fname, i))
continue
# --- check correct list type
if not this_list_type in ['stop','main','map']:
ignored_oldids.append(this_ng_oldid)
print("IMPORT WARN: (skip line) wrong list type at CSV %s:l.%i" % (fname, i))
continue
# subforms can be duplicated (in forms and another label)
# but we must take care of unwanted other duplicates too
if this_row_label in imported_unique_ngramstrs:
print("TODO IMPORT DUPL: (skip line) term appears more than once at CSV %s:l.%i"
% (fname, i))
# ================= Store the data ====================
# the ngram data
imported_ngrams_dbdata.append([this_ng_term, this_ng_nwords])
imported_ngrams_oldids[this_ng_term] = this_ng_oldid
# the ngram census
imported_unique_ngramstrs[this_row_label] = True
# and the "list to ngram" relation
import_nodes_ngrams[this_list_type].append(this_ng_oldid)
imported_nodes_ngrams[this_list_type].append(this_row_label)
# ====== Store synonyms from the import (if any) ======
if len(this_ng_group) != 0:
group_as_external_ids = this_ng_group.split('|')
for external_subform_id in group_as_external_ids:
external_subform_id = int(external_subform_id)
imported_groupings.append(
(this_ng_oldid,external_subform_id)
)
if len(this_row_forms) != 0:
other_terms = []
for raw_term_str in this_row_forms.split(group_delimiter):
# each subform is also like an ngram declaration
term_str = normalize_terms(normalize_chars(raw_term_str))
imported_unique_ngramstrs[term_str] = True
imported_nodes_ngrams[this_list_type].append(term_str)
# the optional repeated mainform doesn't interest us
# because we already have it via the label
if term_str != this_row_label:
# save links
imported_groupings.append(
(this_row_label, term_str)
)
# ======== ngram save + id lookup =========
n_total_ng = len(imported_ngrams_dbdata)
n_total_ng = len(imported_unique_ngramstrs)
# prepare data format
imported_ngrams_dbdata = []
for ngram_str in imported_unique_ngramstrs:
# DB needs the number of separate words
n_words = 1 + len(findall(r' ', ngram_str))
imported_ngrams_dbdata.append((ngram_str, n_words))
# returns a dict {term => id} and a count of inserted ones
(new_ngrams_ids, n_added_ng) = bulk_insert_ifnotexists(
......@@ -464,15 +554,11 @@ def import_ngramlists(fname, delimiter='\t', group_delimiter='|'):
)
del imported_ngrams_dbdata
# loop on old ngrams and create direct mapping old_id => new_id
old_to_new_id_map = {}
for term, oldid in imported_ngrams_oldids.items():
old_to_new_id_map[oldid] = new_ngrams_ids[term]
del new_ngrams_ids
del imported_ngrams_oldids
# new_ngrams_ids contains a direct mapping ng_str => new_id
del imported_unique_ngramstrs
# print(old_to_new_id_map)
# print(import_nodes_ngrams)
# print(new_ngrams_ids)
# print(imported_nodes_ngrams)
# ======== Import into lists =========
# 3 x abstract lists + 1 translations
......@@ -483,27 +569,26 @@ def import_ngramlists(fname, delimiter='\t', group_delimiter='|'):
'groupings' : Translations()
}
for list_type in import_nodes_ngrams:
for old_id in import_nodes_ngrams[list_type]:
new_id = old_to_new_id_map[old_id]
for list_type in imported_nodes_ngrams:
for ng_str in imported_nodes_ngrams[list_type]:
new_id = new_ngrams_ids[ng_str]
# add to the abstract list
result[list_type].items.add(new_id)
# for main also add map elements
if list_type == 'main':
for old_id in import_nodes_ngrams['map']:
new_id = old_to_new_id_map[old_id]
for ng_str in imported_nodes_ngrams['map']:
new_id = new_ngrams_ids[ng_str]
result['main'].items.add(new_id)
# ======== Synonyms =========
for (x,y) in imported_groupings:
if (x not in ignored_oldids) and (y not in ignored_oldids):
new_mainform_id = old_to_new_id_map[x]
new_subform_id = old_to_new_id_map[y]
for (x_str,y_str) in imported_groupings:
new_mainform_id = new_ngrams_ids[x_str]
new_subform_id = new_ngrams_ids[y_str]
# /!\ Translations use (subform => mainform) order
result['groupings'].items[new_subform_id] = new_mainform_id
n_group_relations += 1
# /!\ Translations use (subform => mainform) order
result['groupings'].items[new_subform_id] = new_mainform_id
n_group_relations += 1
# ------------------------------------------------------------------
print("IMPORT: read %i lines from the CSV" % n_read_lines)
......@@ -511,6 +596,7 @@ def import_ngramlists(fname, delimiter='\t', group_delimiter='|'):
% (n_total_ng, n_added_ng, n_total_ng-n_added_ng) )
print("IMPORT: read %i grouping relations" % n_group_relations)
# print("IMPORT RESULT", result)
return result
......
gargantext/views/api/ngramlists.py
View file @ eaf036ce
......@@ -66,29 +66,42 @@ class CSVLists(APIView):
/!\ We assume we checked the file size client-side before upload
£TODO check authentication and user.id
"""
if not request.user.is_authenticated():
res = HttpResponse("Unauthorized")
res.status_code = 401
return res
# this time the corpus param is the one with the target lists to be patched
params = get_parameters(request)
corpus_id = int(params.pop("onto_corpus"))
corpus_node = cache.Node[corpus_id]
if request.user.id != corpus_node.user_id:
res = HttpResponse("Unauthorized")
res.status_code = 401
return res
# request also contains the file
# csv_file has type django.core.files.uploadedfile.InMemoryUploadedFile
# ----------------------
csv_file = request.data['csvfile']
# import the csv
new_lists = import_ngramlists(csv_file)
del csv_file
# merge the new_lists onto those of the target corpus
log_msg = merge_ngramlists(new_lists, onto_corpus=corpus_node)
return JsonHttpResponse({
'log': log_msg,
}, 200)
try:
new_lists = import_ngramlists(csv_file)
del csv_file
# merge the new_lists onto those of the target corpus
log_msg = merge_ngramlists(new_lists, onto_corpus=corpus_node)
return JsonHttpResponse({
'log': log_msg,
}, 200)
except Exception as e:
return JsonHttpResponse({
'err': str(e),
}, 400)
......
static/lib/gargantext/tables.css
View file @ eaf036ce
......@@ -87,7 +87,7 @@ p.note > label {
opacity: 0.3;
}
tr:hover {
#my-ajax-table tr:hover {
cursor: pointer;
font-weight: bold;
}
......
templates/pages/corpora/terms.html
View file @ eaf036ce
......@@ -7,6 +7,53 @@
<link rel="stylesheet" type="text/css" href="{% static "lib/gargantext/tables.css"%}"/>
<link rel="stylesheet" type="text/css" href="{% static "lib/gargantext/charts.css"%}"/>
<style>
#formatinfos-announce {
font-size: 12px ;
padding-top: .5em;
}
#formatinfos {
background-color: #CCC ;
font-size: 12px ;
padding: 1em;
border-radius: 1em;
margin: 1.5em;
}
#formatinfos table {
margin-left: 2.5em;
margin-bottom: 1em;
margin-top: 1em;
}
#formatinfos tr:hover {
font-weight: normal
}
#formatinfos td {
color: inherit ;
hover: none ;
}
#formatinfos h4 {
font-size: 14px;
color: #777;
font-weight: bold;
}
#formatinfos p {
font-size: 14px;
}
#formatinfos em {
font-weight:bold ;
}
</style>
<script type="text/javascript" src="{% static "lib/d3/d3.js"%}"></script>
<script type="text/javascript" src="{% static "lib/d3/crossfilter.js"%}"></script>
<script type="text/javascript" src="{% static "lib/d3/dc.js"%}"></script>
......@@ -126,7 +173,7 @@
<div class="modal-content">
<div class="modal-header">
<button type="button" class="close" data-dismiss="modal" aria-hidden="true">×</button>
<h3 id="myModalLabel">Import a CSV term list</h3>
<h3 id="myModalLabel">Import a Termlist</h3>
</div>
<div class="modal-body" id="uploadform">
<form id="csvimportform"
......@@ -134,8 +181,36 @@
enctype="multipart/form-data"
method="post">
{% csrf_token %}
<label>From your disk:</label>
<label>From a CSV on your disk:</label>
<input type="file" id="csvfile" accept="text/csv">
<p id="formatinfos-announce">
<span
id="formatinfos-icon"
class="glyphicon glyphicon-triangle-right"
onclick="toggleFormatInfos()"></span>
More infos about CSV expected format
</p>
<div id="formatinfos" style="display:none;">
<h4>Example table</h4>
<table class="table-condensed note">
<tr><th>status</th> <th>label</th> <th>forms</th></tr>
<tr><td>map</td> <td>barograph</td> <td></td></tr>
<tr><td>map</td> <td>seafaring</td> <td>seafarer|&amp;|ocean travel</td></tr>
<tr><td>main</td> <td>electromagnetic</td> <td>electro-magnetic</td></tr>
</table>
<h4>Remarks</h4>
<ul>
<li>Tabulation is the expected delimiter between columns.</li>
<li>The only mandatory column is <em>label</em>.</li>
<li>If <em>status</em> is absent, default target status is "map"</li>
<li>When a column is there, always add its header on the 1st line: <em>status</em>, <em>label</em>, <em>forms</em></li>
<li>The label will be always added as a form, even if it's not in 'forms' column</li>
<li>The string <em>|&amp;|</em> (3 characters) is the expected delimiter between forms.</li>
</ul>
</div>
<br/>
<label>From another corpus:</label>
<p>TODO</p>
......@@ -153,6 +228,28 @@
<script type="text/javascript" src="{% static "lib/gargantext/NGrams_dyna_chart_and_table.js" %}"></script>
<script type="text/javascript">
var formatInfosOpen = false;
function toggleFormatInfos() {
// when already open => we close
if (formatInfosOpen) {
// hide div
$('#formatinfos').hide()
// change icon
$('#formatinfos-icon')[0].classList.remove('glyphicon-triangle-bottom')
$('#formatinfos-icon')[0].classList.add('glyphicon-triangle-right')
// toggle flag
formatInfosOpen = false;
}
else {
// opposite case
$('#formatinfos').show()
$('#formatinfos-icon')[0].classList.remove('glyphicon-triangle-right')
$('#formatinfos-icon')[0].classList.add('glyphicon-triangle-bottom')
formatInfosOpen = true;
}
}
/* merci c24b !
* Uses csvimportroute variable from the django template
......@@ -202,7 +299,7 @@ function postCSV(e){
xhr.setRequestHeader("X-CSRFToken", getCookie("csrftoken"));
},
success: function(response) {
my_html = "<h2 color='green'>IMPORT OK ! </h2>"
my_html = '<h3 style="color:green">IMPORT OK</h3>'
my_html += "<p class='note'>" + response['log'].replace(/\n/g, '<br/>') + "</p>"
my_html += "<p'>(this page will reload in 3s)</p>"
$('#formanswer').html(my_html);
......@@ -211,7 +308,10 @@ function postCSV(e){
setTimeout("location.reload(true)", 3000);
},
error: function(result) {
$('#formanswer').html('Erreur');
my_html = '<h3 style="color:red">Error</h3>'
my_html += "<p class='note'>please correct your CSV file and retry</p>"
my_html += "<p>"+ result.responseJSON['err']+"</p>"
$('#formanswer').html(my_html);
console.error(result);
},
});
......
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