diff --git a/cdlib/algorithms/bipartite_clustering.py b/cdlib/algorithms/bipartite_clustering.py
index 151744fc..f608f8ed 100644
--- a/cdlib/algorithms/bipartite_clustering.py
+++ b/cdlib/algorithms/bipartite_clustering.py
@@ -1,15 +1,21 @@
 from cdlib import BiNodeClustering
-
 import networkx as nx
+from cdlib.utils import convert_graph_formats
+from collections import defaultdict
+from cdlib.algorithms.internal.pycondor import condor_object, initial_community, brim
+
+missing_packages = set()
 
 try:
     import infomap as imp
 except ModuleNotFoundError:
+    missing_packages.add("infomap")
     imp = None
 
 try:
     from wurlitzer import pipes
 except ModuleNotFoundError:
+    missing_packages.add("wurlitzer")
     pipes = None
 
 try:
@@ -20,11 +26,14 @@
 try:
     import leidenalg
 except ModuleNotFoundError:
+    missing_packages.add("leidenalg")
     leidenalg = None
 
-from cdlib.utils import convert_graph_formats
-from collections import defaultdict
-from cdlib.algorithms.internal.pycondor import condor_object, initial_community, brim
+if len(missing_packages) > 0:
+    print(
+        "Note: to be able to use all bipartite methods, you need to install some additional packages: ",
+        missing_packages,
+    )
 
 __all__ = ["bimlpa", "CPM_Bipartite", "infomap_bipartite", "condor"]
 
@@ -123,11 +132,15 @@ def CPM_Bipartite(
 
     .. note:: Reference implementation: https://leidenalg.readthedocs.io/en/stable/multiplex.html?highlight=bipartite#bipartite
     """
+    global leidenalg
     if ig is None or leidenalg is None:
-        raise ModuleNotFoundError(
-            "Optional dependency not satisfied: install igraph and leidenalg to use the "
-            "selected feature."
-        )
+        try:
+            import leidenalg
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install igraph and leidenalg to use the "
+                "selected feature."
+            )
 
     g = convert_graph_formats(g_original, ig.Graph)
 
@@ -201,14 +214,21 @@ def infomap_bipartite(g_original: object, flags: str = "") -> BiNodeClustering:
     .. note:: Infomap Python API documentation: https://mapequation.github.io/infomap/python/
     """
 
+    global imp, pipes
     if imp is None:
-        raise ModuleNotFoundError(
-            "Optional dependency not satisfied: install infomap to use the selected feature."
-        )
+        try:
+            import infomap as imp
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install infomap to use the selected feature."
+            )
     if pipes is None:
-        raise ModuleNotFoundError(
-            "Optional dependency not satisfied: install package wurlitzer to use infomap."
-        )
+        try:
+            from wurlitzer import pipes
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install package wurlitzer to use infomap."
+            )
 
     g = convert_graph_formats(g_original, nx.Graph)
 
diff --git a/cdlib/algorithms/crisp_partition.py b/cdlib/algorithms/crisp_partition.py
index 075a2b11..0be2dcba 100644
--- a/cdlib/algorithms/crisp_partition.py
+++ b/cdlib/algorithms/crisp_partition.py
@@ -1,35 +1,11 @@
-try:
-    import infomap as imp
-except ModuleNotFoundError:
-    imp = None
-
-try:
-    from wurlitzer import pipes
-except ModuleNotFoundError:
-    pipes = None
-
-try:
-    import igraph as ig
-except ModuleNotFoundError:
-    ig = None
-
-try:
-    import leidenalg
-except ModuleNotFoundError:
-    leidenalg = None
-
-try:
-    import graph_tool.all as gt
-except ModuleNotFoundError:
-    gt = None
-
-import warnings
+import sys
 import numpy as np
 from typing import Callable
 from copy import deepcopy
 from cdlib.algorithms.internal import DER
-import community as louvain_modularity
-import warnings
+
+# import community as louvain_modularity
+from community import community_louvain
 from collections import defaultdict
 from cdlib import NodeClustering, FuzzyNodeClustering
 from cdlib.algorithms.internal.belief_prop import detect_belief_communities
@@ -57,23 +33,12 @@
 from cdlib.algorithms.internal.principled import principled
 from cdlib.algorithms.internal.MCODE import m_code
 from cdlib.algorithms.internal.RSC import rsc_evaluate_graph
+import warnings
 
-try:
-    from GraphRicciCurvature.OllivierRicci import OllivierRicci
-except ModuleNotFoundError:
-    OllivierRicci = None
-
-try:
-    import pycombo as pycombo_part
-except ModuleNotFoundError:
-    pycombo_part = None
-
-from karateclub import EdMot, GEMSEC, SCD
 import markov_clustering as mc
 from chinese_whispers import chinese_whispers as cw
 from chinese_whispers import aggregate_clusters
 from thresholdclustering.thresholdclustering import best_partition as th_best_partition
-
 import networkx as nx
 
 from cdlib.utils import (
@@ -83,6 +48,59 @@
     nx_node_integer_mapping,
 )
 
+missing_packages = set()
+
+try:
+    import infomap as imp
+except ModuleNotFoundError:
+    missing_packages.add("infomap")
+    imp = None
+
+try:
+    from wurlitzer import pipes
+except ModuleNotFoundError:
+    missing_packages.add("wurlitzer")
+    pipes = None
+
+try:
+    import igraph as ig
+except ModuleNotFoundError:
+    ig = None
+
+try:
+    import leidenalg
+except ModuleNotFoundError:
+    missing_packages.add("leidenalg")
+    leidenalg = None
+
+try:
+    import graph_tool.all as gt
+except ModuleNotFoundError:
+    missing_packages.add("graph_tool")
+    gt = None
+
+try:
+    import karateclub
+except ModuleNotFoundError:
+    missing_packages.add("karateclub")
+
+
+if len(missing_packages) > 0:
+    print(
+        "Note: to be able to use all crisp methods, you need to install some additional packages: ",
+        missing_packages,
+    )
+
+try:
+    from GraphRicciCurvature.OllivierRicci import OllivierRicci
+except ModuleNotFoundError:
+    OllivierRicci = None
+
+try:
+    import pycombo as pycombo_part
+except ModuleNotFoundError:
+    pycombo_part = None
+
 __all__ = [
     "louvain",
     "leiden",
@@ -509,7 +527,7 @@ def louvain(
 
     g = convert_graph_formats(g_original, nx.Graph)
 
-    coms = louvain_modularity.best_partition(
+    coms = community_louvain.best_partition(
         g, weight=weight, resolution=resolution, randomize=randomize
     )
 
@@ -568,12 +586,15 @@ def leiden(
 
     .. note:: Reference implementation: https://github.com/vtraag/leidenalg
     """
-
+    global leidenalg
     if ig is None or leidenalg is None:
-        raise ModuleNotFoundError(
-            "Optional dependency not satisfied: install igraph and leidenalg to use the "
-            "selected feature."
-        )
+        try:
+            import leidenalg
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install igraph and leidenalg to use the "
+                "selected feature."
+            )
 
     g = convert_graph_formats(g_original, ig.Graph)
 
@@ -1049,15 +1070,21 @@ def infomap(g_original: object, flags: str = "") -> NodeClustering:
 
     .. note:: Infomap Python API documentation: https://mapequation.github.io/infomap/python/
     """
-
+    global imp, pipes
     if imp is None:
-        raise ModuleNotFoundError(
-            "Optional dependency not satisfied: install infomap to use the selected feature."
-        )
+        try:
+            import infomap as imp
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install infomap to use the selected feature."
+            )
     if pipes is None:
-        raise ModuleNotFoundError(
-            "Optional dependency not satisfied: install package wurlitzer to use infomap."
-        )
+        try:
+            from wurlitzer import pipes
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install package wurlitzer to use infomap."
+            )
 
     g = convert_graph_formats(g_original, nx.Graph, directed=g_original.is_directed())
 
@@ -1445,12 +1472,15 @@ def sbm_dl(
 
     .. note:: Implementation from graph-tool library, please report to https://graph-tool.skewed.de for details
     """
+
     if gt is None:
         raise Exception(
             "===================================================== \n"
             "The graph-tool library seems not to be installed (or incorrectly installed). \n"
-            "Please check installation procedure there https://git.skewed.de/count0/graph-tool/wikis/installation-instructions#native-installation \n"
-            "on linux/mac, you can use package managers to do so(apt-get install python3-graph-tool, brew install graph-tool, etc.)"
+            "Please check installation procedure there "
+            "https://git.skewed.de/count0/graph-tool/wikis/installation-instructions#native-installation \n"
+            "on linux/mac, you can use package managers to do so "
+            "(apt-get install python3-graph-tool, brew install graph-tool, etc.)"
         )
     gt_g = convert_graph_formats(g_original, nx.Graph)
     gt_g, label_map = __from_nx_to_graph_tool(gt_g)
@@ -1498,13 +1528,21 @@ def sbm_dl_nested(
 
     .. note:: Implementation from graph-tool library, please report to https://graph-tool.skewed.de for details
     """
+    global gt
+
     if gt is None:
-        raise Exception(
-            "===================================================== \n"
-            "The graph-tool library seems not to be installed (or incorrectly installed). \n"
-            "Please check installation procedure there https://git.skewed.de/count0/graph-tool/wikis/installation-instructions#native-installation \n"
-            "on linux/mac, you can use package managers to do so(apt-get install python3-graph-tool, brew install graph-tool, etc.)"
-        )
+        try:
+            import graph_tool.all as gt
+        except ModuleNotFoundError:
+            raise Exception(
+                "===================================================== \n"
+                "The graph-tool library seems not to be installed (or incorrectly installed). \n"
+                "Please check installation procedure "
+                "there https://git.skewed.de/count0/graph-tool/wikis/installation-instructions#native-installation \n"
+                "on linux/mac, you can use package managers to do so(apt-get install python3-graph-tool, "
+                "brew install graph-tool, etc.)"
+            )
+
     gt_g = convert_graph_formats(g_original, nx.Graph)
     gt_g, label_map = __from_nx_to_graph_tool(gt_g)
     state = gt.minimize_nested_blockmodel_dl(gt_g)
@@ -1716,9 +1754,18 @@ def edmot(
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
+    global karateclub
+
+    if "karateclub" not in sys.modules:
+        try:
+            import karateclub
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install karateclub to use the selected feature."
+            )
 
     g = convert_graph_formats(g_original, nx.Graph)
-    model = EdMot(component_count=2, cutoff=10)
+    model = karateclub.EdMot(component_count=2, cutoff=10)
 
     model.fit(g)
     members = model.get_memberships()
@@ -2360,8 +2407,17 @@ def gemsec(
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
+    global karateclub
+    if "karateclub" not in sys.modules:
+        try:
+            import karateclub
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install karateclub to use the selected feature."
+            )
+
     g = convert_graph_formats(g_original, nx.Graph)
-    model = GEMSEC(
+    model = karateclub.GEMSEC(
         walk_number=walk_number,
         walk_length=walk_length,
         dimensions=dimensions,
@@ -2438,8 +2494,18 @@ def scd(
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
+    global karateclub
+
+    if "karateclub" not in sys.modules:
+        try:
+            import karateclub
+        except ModuleNotFoundError:
+            raise ModuleNotFoundError(
+                "Optional dependency not satisfied: install karateclub to use the selected feature."
+            )
+
     g = convert_graph_formats(g_original, nx.Graph)
-    model = SCD(iterations=iterations, eps=eps, seed=seed)
+    model = karateclub.SCD(iterations=iterations, eps=eps, seed=seed)
     model.fit(g)
     members = model.get_memberships()
 
diff --git a/cdlib/algorithms/overlapping_partition.py b/cdlib/algorithms/overlapping_partition.py
index e8734377..16db1cea 100644
--- a/cdlib/algorithms/overlapping_partition.py
+++ b/cdlib/algorithms/overlapping_partition.py
@@ -1,17 +1,4 @@
-try:
-    import igraph as ig
-except ModuleNotFoundError:
-    ig = None
-try:
-    from angel import Angel
-except ModuleNotFoundError:
-    Angel = None
-
-try:
-    from ASLPAw_package import ASLPAw
-except ModuleNotFoundError:
-    ASLPAw = None
-
+import sys
 from random import sample
 from demon import Demon
 from cdlib.algorithms.internal.NodePerception import NodePerception
@@ -31,7 +18,6 @@
 from cdlib.algorithms.internal.PercoMCV import percoMVC
 from cdlib.algorithms.internal.LPAM import LPAM
 from cdlib.algorithms.internal.core_exp import findCommunities as core_exp_find
-from karateclub import DANMF, EgoNetSplitter, NNSED, MNMF, BigClam, SymmNMF
 from cdlib.algorithms.internal.weightedCommunity import weightedCommunity
 from cdlib.algorithms.internal.LPANNI import LPANNI, GraphGenerator
 from cdlib.algorithms.internal.DCS import main_dcs
@@ -46,6 +32,50 @@
     endntm_find_overlap_cluster,
     endntm_evalFuction,
 )
+import warnings
+
+missing_packages = set()
+
+
+def __try_load_karate(init=False):
+    global karateclub
+    if init == True or "karateclub" not in sys.modules:
+        try:
+            import karateclub
+
+        except ModuleNotFoundError:
+            if not init:
+                raise ModuleNotFoundError(
+                    "Optional dependency not satisfied: install karateclub to use the selected feature."
+                )
+
+
+__try_load_karate(init=True)
+if "karateclub" not in sys.modules:
+    karateclub = None
+    missing_packages.add("karateclub")
+
+
+try:
+    import igraph as ig
+except ModuleNotFoundError:
+    ig = None
+try:
+    from angel import Angel
+except ModuleNotFoundError:
+    Angel = None
+
+try:
+    from ASLPAw_package import ASLPAw
+except ModuleNotFoundError:
+    ASLPAw = None
+    missing_packages.add("ASLPAw")
+
+if len(missing_packages) > 0:
+    print(
+        "Note: to be able to use all overlapping methods, you need to install some additional packages: ",
+        missing_packages,
+    )
 
 __all__ = [
     "ego_networks",
@@ -878,10 +908,10 @@ def big_clam(
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
-
+    __try_load_karate()
     g = convert_graph_formats(g_original, nx.Graph)
 
-    model = BigClam(
+    model = karateclub.BigClam(
         dimensions=dimensions, iterations=iterations, learning_rate=learning_rate
     )
     model.fit(g)
@@ -949,8 +979,11 @@ def danmf(
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
+
+    __try_load_karate()
+
     g = convert_graph_formats(g_original, nx.Graph)
-    model = DANMF(layers, pre_iterations, iterations, seed, lamb)
+    model = karateclub.DANMF(layers, pre_iterations, iterations, seed, lamb)
 
     mapping = {node: i for i, node in enumerate(g.nodes())}
     rev = {i: node for node, i in mapping.items()}
@@ -1012,8 +1045,10 @@ def egonet_splitter(g_original: object, resolution: float = 1.0) -> NodeClusteri
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
+    __try_load_karate()
+
     g = convert_graph_formats(g_original, nx.Graph)
-    model = EgoNetSplitter(resolution=resolution)
+    model = karateclub.EgoNetSplitter(resolution=resolution)
 
     mapping = {node: i for i, node in enumerate(g.nodes())}
     rev = {i: node for node, i in mapping.items()}
@@ -1074,8 +1109,11 @@ def nnsed(
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
+
+    __try_load_karate()
+
     g = convert_graph_formats(g_original, nx.Graph)
-    model = NNSED(dimensions=dimensions, iterations=iterations, seed=seed)
+    model = karateclub.NNSED(dimensions=dimensions, iterations=iterations, seed=seed)
     model.fit(g)
     members = model.get_memberships()
 
@@ -1148,8 +1186,9 @@ def mnmf(
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
+    __try_load_karate()
     g = convert_graph_formats(g_original, nx.Graph)
-    model = MNMF(
+    model = karateclub.MNMF(
         dimensions=dimensions,
         clusters=clusters,
         lambd=lambd,
@@ -1601,8 +1640,11 @@ def symmnmf(
 
     .. note:: Reference implementation: https://karateclub.readthedocs.io/
     """
+    __try_load_karate()
     g = convert_graph_formats(g_original, nx.Graph)
-    model = SymmNMF(dimensions=dimensions, iterations=iterations, rho=rho, seed=seed)
+    model = karateclub.SymmNMF(
+        dimensions=dimensions, iterations=iterations, rho=rho, seed=seed
+    )
     model.fit(g)
     members = model.get_memberships()
 
diff --git a/cdlib/test/test_community_discovery_models.py b/cdlib/test/test_community_discovery_models.py
index 2e52c8e6..232b87e4 100644
--- a/cdlib/test/test_community_discovery_models.py
+++ b/cdlib/test/test_community_discovery_models.py
@@ -5,6 +5,11 @@
 import random
 import os
 
+try:
+    import karateclub
+except ModuleNotFoundError:
+    karateclub = None
+
 try:
     import pycombo as pycombo_part
 except ModuleNotFoundError:
@@ -348,6 +353,8 @@ def test_markov_clustering(self):
                 self.assertEqual(type(communities.communities[0][0]), int)
 
     def test_bigClam(self):
+        if karateclub is None:
+            return
         g = nx.karate_club_graph()
         coms = algorithms.big_clam(g)
         self.assertEqual(type(coms.communities), list)
@@ -478,6 +485,8 @@ def test_sbm_nested_dl(self):
                 self.assertEqual(type(coms.communities[0][0]), str)
 
     def test_danmf(self):
+        if karateclub is None:
+            return
         g = get_string_graph()
         coms = algorithms.danmf(g)
         self.assertEqual(type(coms.communities), list)
@@ -486,6 +495,8 @@ def test_danmf(self):
             self.assertEqual(type(coms.communities[0][0]), str)
 
     def test_egonet_splitter(self):
+        if karateclub is None:
+            return
         g = get_string_graph()
         coms = algorithms.egonet_splitter(g)
         self.assertEqual(type(coms.communities), list)
@@ -494,6 +505,8 @@ def test_egonet_splitter(self):
             self.assertEqual(type(coms.communities[0][0]), str)
 
     def test_nnsed(self):
+        if karateclub is None:
+            return
         g = nx.karate_club_graph()
         coms = algorithms.nnsed(g)
         self.assertEqual(type(coms.communities), list)
@@ -502,6 +515,8 @@ def test_nnsed(self):
             self.assertEqual(type(coms.communities[0][0]), int)
 
     def test_mnmf(self):
+        if karateclub is None:
+            return
         g = nx.karate_club_graph()
         coms = algorithms.mnmf(g)
         self.assertEqual(type(coms.communities), list)
@@ -510,6 +525,8 @@ def test_mnmf(self):
             self.assertEqual(type(coms.communities[0][0]), int)
 
     def test_edmot(self):
+        if karateclub is None:
+            return
         g = nx.karate_club_graph()
         coms = algorithms.edmot(g)
         self.assertEqual(type(coms.communities), list)
@@ -625,7 +642,8 @@ def test_CPM_Bipartite(self):
         g = ig.Graph.Erdos_Renyi(n=80, m=600)
         g.vs["type"] = 0
         g.vs[15:]["type"] = 1
-
+        if leidenalg is None:
+            return
         coms = algorithms.CPM_Bipartite(g, 0.3)
         self.assertEqual(type(coms.communities), list)
         if len(coms.communities) > 0:
@@ -640,6 +658,8 @@ def test_CPM_Bipartite(self):
             self.assertEqual(type(coms.communities[0][0]), int)
 
     def test_infomap_Bipartite(self):
+        if infomap is None:
+            return
         g = nx.algorithms.bipartite.random_graph(300, 100, 0.2)
         coms = algorithms.infomap_bipartite(g)
         self.assertEqual(type(coms.communities), list)
@@ -788,6 +808,8 @@ def test_kcut(self):
             print("Kcut error to be checked (conda packaging)")
 
     def test_symmnmf(self):
+        if karateclub is None:
+            return
         G = nx.karate_club_graph()
 
         coms = algorithms.symmnmf(G)
@@ -806,6 +828,8 @@ def test_scd(self):
             self.assertEqual(type(coms.communities[0][0]), int)
 
     def test_gemsec(self):
+        if karateclub is None:
+            return
         G = nx.karate_club_graph()
 
         coms = algorithms.gemsec(G)
diff --git a/cdlib/viz/networks.py b/cdlib/viz/networks.py
index 0f9cffc9..ec8eb8bb 100644
--- a/cdlib/viz/networks.py
+++ b/cdlib/viz/networks.py
@@ -5,7 +5,7 @@
 import networkx as nx
 from cdlib import NodeClustering
 from cdlib.utils import convert_graph_formats
-from community import induced_graph
+from community import community_louvain
 
 __all__ = ["plot_network_clusters", "plot_community_graph"]
 
@@ -202,7 +202,7 @@ def plot_community_graph(
     s = nx.subgraph(graph, node_to_com.keys())
 
     # algorithms graph construction
-    c_graph = induced_graph(node_to_com, s)
+    c_graph = community_louvain.induced_graph(node_to_com, s)
     node_cms = [[node] for node in c_graph.nodes()]
 
     return plot_network_clusters(
diff --git a/conda/meta.yaml b/conda/meta.yaml
index 33400fe4..7d3780ab 100644
--- a/conda/meta.yaml
+++ b/conda/meta.yaml
@@ -1,5 +1,5 @@
 {% set name = "cdlib" %}
-{% set version = "0.2.5" %}
+{% set version = "0.2.6" %}
 
 package:
   name: "{{ name|lower }}"
@@ -45,8 +45,6 @@ requirements:
     - demon
     - dynetx
     - eva_lcd
-    - karateclub
-    - leidenalg
     - markov_clustering
     - matplotlib
     - networkx>=2.4
@@ -65,7 +63,6 @@ requirements:
     - seaborn
     - thresholdclustering
     - tqdm
-    - wurlitzer
 
 test:
   imports:
diff --git a/docs/conf.py b/docs/conf.py
index da37cc17..0c48f392 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -134,9 +134,9 @@ def __getattr__(cls, name):
 # built documents.
 #
 # The short X.Y version.
-version = u"0.2.5"
+version = u"0.2.6"
 # The full version, including alpha/beta/rc tags.
-release = u"0.2.5"
+release = u"0.2.6"
 
 # The language for content autogenerated by Sphinx. Refer to documentation
 # for a list of supported languages.
diff --git a/environment.yml b/environment.yml
index 3b737b64..10eae4d6 100644
--- a/environment.yml
+++ b/environment.yml
@@ -14,17 +14,13 @@ dependencies:
 - seaborn
 - pandas
 - eva_lcd
-- karateclub
 - bimlpa
 - markov_clustering
 - chinese_whispers
 - python-igraph
-- leidenalg
 - angel_cd
 - pooch
 - dynetx
-- python-infomap
-- wurlitzer
 - thresholdclustering
 - pyclustering
 - python-Levenshtein
diff --git a/requirements.txt b/requirements.txt
index ee42ae70..229b478c 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -5,24 +5,20 @@ scikit-learn
 tqdm
 networkx>=2.4
 demon
-python-louvain
+python-louvain>=0.16
 nf1
 scipy
 pulp
 seaborn
 pandas
 eva_lcd
-karateclub
 bimlpa
 markov_clustering
 chinese_whispers
 python-igraph
-leidenalg
 angel-cd
 pooch
 dynetx
-infomap
-wurlitzer
 thresholdclustering
 pyclustering
 cython
diff --git a/requirements_optional.txt b/requirements_optional.txt
index d90da8d1..c328df25 100644
--- a/requirements_optional.txt
+++ b/requirements_optional.txt
@@ -1,5 +1,7 @@
-infomap>=1.3.0
-wurlitzer>=1.0.2
 GraphRicciCurvature==0.5.2.1
 networkit
 pycombo
+karateclub
+leidenalg
+infomap>=1.3.0
+wurlitzer>=1.0.2
\ No newline at end of file
diff --git a/setup.py b/setup.py
index 786f365c..7ac88ec6 100644
--- a/setup.py
+++ b/setup.py
@@ -18,7 +18,7 @@
 
 
 setup(name='cdlib',
-      version='0.2.5',
+      version='0.2.6',
       license='BSD-Clause-2',
       description='Community Discovery Library',
       url='https://github.com/GiulioRossetti/cdlib',
@@ -51,7 +51,7 @@
       long_description=long_description,
       long_description_content_type='text/markdown',
       extras_require={
-        'C':  ["infomap>=1.3.0", "wurlitzer>=1.0.2", "GraphRicciCurvature", "networkit", "pycombo"],
+        'C':  ["infomap>=1.3.0", "wurlitzer>=1.0.2", "GraphRicciCurvature", "networkit", "pycombo","leidenalg","karateclub"],
       },
       packages=find_packages(exclude=["*.test", "*.test.*", "test.*", "test", "cdlib.test", "cdlib.test.*"]),
       )