cleaning branches

Mapping_using_the_API.py

@@ -12,7 +12,7 @@ from scipy.stats import hypergeom
 from utils import excel_file_writer, pre_cut, recup_all_inf_excel, cor_index
 FOLDER = "C:\\Users\\mumec\\Desktop\\Mini_codes\\mapping_using_the_api\\"
 import certifi
-
+import urlopen
 
 
 def send_request_to_mapping_api(url, data_json, head, met='POST'):
@@ -27,50 +27,17 @@ def send_request_to_mapping_api(url, data_json, head, met='POST'):
 
     Returns:
         Type of return: 1 excel file whith 5 columns
-
-    req = request.Request(url, data=data_json, headers=head, method=met)
-    with request.urlopen(req) as response:
-        result = response.read()
-    out_data = result.decode('utf-8')
-    return out_data
     """
-    print()
-    context = ssl.create_default_context(cafile=certifi.where())
-    r = requests.post(url, data_json, headers=head, verify=certifi.where())
-    print(type(r))
-    return r
-
-
-"""
-def send_request_to_mapping_api(url, data_json, head, met='POST'):
-
-
-    This function gives the result of mapping of a metabolites list from RAMP.
-    Here's an example of 4 metabolites giving 505 lines.
-    ["KEGG:C01157","hmdb:HMDB0000064","hmdb:HMDB0000148","chebi:16015"]
-
-    Arg:
-        url = the url to use
-        data_json = the data to post
-        head = headers to use
-        met = 'POST'
-
-    Returns:
-        Type of return: 1 excel file with 5 columns
-
-    try:
-        req = request.Request(url, data=data_json, headers=head, method=met, verify=certifi.where())
+    try :
+        req = request.Request(url, data=data_json, headers=head, method=met)
         with request.urlopen(req) as response:
             result = response.read()
         out_data = result.decode('utf-8')
-        return out_data
-    except error.HTTPError as e:
-        print(f"Error: The server couldn't fulfill the request. {e}")
-        return []
-    except Exception as e:
-        print(f"An unexpected error occurred: {e}")
-        return []
-"""
+    except error.URLError as e:
+        r = requests.post(url, data=data_json, headers=head, verify=False)
+        return r.text
+    return out_data
+
 
 def mapping_ramp_api(metabolites_list, outfile, inf="flow"):
     """
@@ -767,8 +734,7 @@ def opti_multimapping(file, outfolder, mapping="flow"):
         cpdbf = outfolder+recap[i_map_opt][0]+"_mapping_opti.xlsx"
         datas_cpdb = m_ora_cpdb(cpdb_o_opti, acctype, infos="flow",
                                 ofile=cpdbf, cor_inf=[name_opti, cpdb_o_opti])
-
-    #Probléme RAMP voir aprés
+    print("CEST AU TOUR DE RAMP")
     for line in inf[1:]:
         to_test.append(line[1])
     l_opt_ramp = []
@@ -814,8 +780,6 @@ def opti_multimapping(file, outfolder, mapping="flow"):
     print("lines Ramp", n_map)
     l_opt_ramp_tri[0] = "RAMP"
     recap.append(l_opt_ramp_tri)
-
-    datas_ramp = ["NA" for i in range(len(file)+1) ] # provisoire aussi !!!!
     recap.append(modulation)
     df_recap = pd.DataFrame(data=recap).transpose()
     n_out_f = outfolder+"recap_multimapping.xlsx"

main.py

@@ -9,8 +9,7 @@ import pandas as pd
 import py4cytoscape as p4c
 sys.path.append('C:\\Users\\mumec\\Desktop\\Dossier_gitlab_local\\traitement_des_données')
 sys.path.append('C:\\Users\\mumec\\Desktop\\Dossier_gitlab_local\\chebi-ids.git')
-sys.path.append("C:\\Users\\mumec\\Desktop\\Mini_codes\\pdf_PyPDF2")
-from test_pdf import out_pdf_mapping
+from pdf_generation_toolbox import out_pdf_mapping
 from Recovery_of_associated_Chebi_IDs import chebi_horizontal
 from utils import excel_file_writer, pre_cut, recup_all_inf_excel
 from complete_processing_of_mapping_results import c_p_o_m_r
@@ -125,13 +124,12 @@ def workflow(infile, out_folder):
     result_cpdb, result_ramp, recap = opti_multimapping(datas_f_map, out_folder,
                                                         mapping="flow")
     # ajouter la mention ID exact !
-    #l_visu = c_p_o_m_r(result_ramp, out_folder, "RAMP", f_view_sav=out_folder,
-    #                   modul="flow", f_modul=recap)
+    l_visu = c_p_o_m_r(result_ramp, out_folder, "RAMP", f_view_sav=out_folder,
+                       modul="flow", f_modul=recap)
     l_visu_c = c_p_o_m_r(result_cpdb, out_folder, "CPDB", f_view_sav=out_folder,
                          modul="flow", f_modul=recap)
-    #l_visu += l_visu_c[1:]
-    #l_visu.append(l_visu_c[0])
-    l_visu  = l_visu_c # provisooire aussi !
+    l_visu += l_visu_c[1:]
+    l_visu.append(l_visu_c[0])
     result_ramp_pdf = []
     result_cpdb_pdf = []
     recap_pdf = []
@@ -144,9 +142,9 @@ def workflow(infile, out_folder):
                 new_line.append(str(i_line[i_col]))
             liste_reverse[i_liste].append(new_line)
     file_path = "Modele_de_pdf_feneratio_en_anglais_rev_19-02-2024.docx"
-    #out_pdf_mapping(file_path, data_input, chebi_hori, recap_pdf,
-    #                result_ramp_pdf[:8], result_cpdb_pdf[:4],
-    #                out_folder, l_visu)
+    out_pdf_mapping(file_path, data_input, chebi_hori, recap_pdf,
+                    result_ramp_pdf[:8], result_cpdb_pdf[:4],
+                    out_folder, l_visu)
     l_bdd = ["Wikipathways", "KEGG", "EHMN",
              "HumanCyc", "INOH", "Reactome"] # "SMPDB" plantage
     t2 = time()
@@ -155,23 +153,18 @@ def workflow(infile, out_folder):
     for bddnow in l_bdd:
         t_i_name = [recap[0] + recap[0], recap[1] + recap[2]]  #not opti
         print(t_i_name)
-        #out_links = out_folder + "CPDB_links_network" + bddnow + "datas_base.xlsx"
         out_links = out_folder + "Network CPDB with only "+ bddnow + " pathways.xlsx"
         edge_data, nodes_data = paths_link_cpdb(result_cpdb, out_links, recap,
                                                 bdd=bddnow, flow=True,
                                                 tab_id_name=t_i_name)
-    """
         if bddnow == "Reactome":
             print(network_visu(edge_data[0:3], nodes_data,
                   bdd=bddnow, sav_fol=out_folder))
         else:
             print(network_visu(edge_data[0:3], nodes_data, bdd=bddnow))
-    """
     t3 = time()
-    """
     print("le temps nécessaires pour effectuer les visualisation a était de ",
           t3-t1, "secondes.")
-    """
     print("le temps total pour faire tourner le programme est a était ",
           t3-t1, "secondes.")